Jo Dewulf, Simone Manfredi, Serenella Sala, Valentina Castellani, Małgorzata Góralczyk Bruno Notarnicola, Giuseppe Tassielli, Pietro A. Renzulli Paulo Ferrão, André Pina, Patrícia Baptista Monica Lavagna
Deliverable 5
Indicators and targets for the reduction of the
environmental impact of EU consumption: Basket-of-
products indicators and prototype targets for the
reduction of environmental impact of EU consumption
2014
European Commission
Joint Research Centre
Institute for Environment and Sustainability
Contact information
Małgorzata Góralczyk
Address: Joint Research Centre, Via Enrico Fermi 2749, TP 290, 21027 Ispra (VA), Italy
E-mail: [email protected]
Tel.: +39 0332 78 9949
Acknowledgements:
The report was created with the support of the experts, who developed the baskets of products for food, housing and
mobility. Their contribution is the following:
o Bruno Notarnicola, Giuseppe Tassielli, Pietro A. Renzulli (Università degli Studi di Bari, Italy): food basket of
products (section 2)
o Paulo Ferrão, André Pina, Patrícia Baptista (Instituto Superior Técnico, Lisboa, Portugal): mobility basket of
products (section 3)
o Monica Lavagna (Politecnico di Milano, ABC Department, Italy) with support of Andrea Campioli, Serena
Giorgi, Anna Dalla Valle: housing basket of products (section 4)
3
Executive summary
Objectives
The objective of this report is to provide the environmental impacts of 3 key consumption categories (food,
housing and mobility), as well as the impacts of representative products within each consumption category in
relation to their relevance for the EU sustainable product policy.
The environmental impact (basket-of-products) indicators are developed in order to help policy makers to
monitor and evaluate the progress towards the reduction of the lifecycle environmental impacts of European
consumption, including helping focus eco-innovation and other different policy activities.
This report also aims at applying the life cycle based methodology proposed in Sala et al 2014 in support to a
comprehensive and systematic target setting. This methodology for target setting has so far been applied on
the food sector as preliminary example.
Description of work
The Basket-of-Products indicators developed provide insights into overall life cycle impacts related to
consumption in key product groups and consumption categories. These are based on product life cycle data
(environmental profiles of products) combined with consumption statistics. This also allows for the
development of more informed targets based on detailed product-group insights than would be feasible using
heavily aggregated macro scale indicators alone.
For each consumption category and associated products the indicators are built for the most relevant
environmental impact categories, as defined in the recent EC Product Environmental Footprint (PEF) method
and the International Reference Life Cycle Data System (ILCD).
Conclusions
Sections 2, 3 and 4 of this report present the results of the BoPs indicators for food, mobility and housing,
expressed per EU citizen, for the 14 considered impact categories. The estimated potential impacts are
subdivided according to the products in the respective baskets and equally according to the life cycle stages
that have been accounted for.
Results show that the production and use phases dominate the impacts with an average contribution of 51.8
and 45.6%, respectively. The End-of-Life (EoL) phase is, on the other hand, far less contributing; for some
impacts, the recovery can even result in some avoided impact – standing for environmental benefits, explaining
the numerically negative contributions. With respect to the production phase, relative contributions to the
overall life cycle impacts are the highest for human toxicity (cancer effects) (89.2%) and terrestrial
eutrophication (82.8%), moderate for impacts like climate change (31.9%) and low for ozone depletion (15.1%).
Analysis of the relative contribution of the use phase to the total life cycle impacts shows that ozone depletion
(85.7%), photochemical ozone formation (71.9%) and climate change (69.8%) are significantly impacted;
human toxicity (non-cancer effects) is instead poorly impacted (13.4%).
When zooming into the production phase, the role of the three BoPs can be analysed. On average, food
production contributes 54.5% to the total impact by production, mobility 34.3%, and shelter 11.2%. Food
production accounts for over 90% of the contribution to acidification, terrestrial eutrophication and land use.
The largest share of mobility is in resource depletion, i.e. 80.0% of the overall impact.
Analysing the impacts of the different BoPs at the use stage, on average it turns out that it is dominated by
housing (51.8%) and mobility (45.9%), while food only accounts for 2.2%. Highest impact for the use phase
for mobility is in land use (70.4%) and for housing in ionizing radiation Ecosystem (73.8%).
With respect to EoL, impacts are dominated by mobility: 90.6% on average. Contributions of food is 9.5%,
whereas housing is negligible with -0.1% on average.
4
Perspectives
A crucial phase in the development of the BoP indicators was the initial definition of the three selected basket
categories (food, mobility and shelter) and, even more important, the population of the three baskets, i.e. the
identification of the representative products to be included in each basket. Given the profound importance of
this phase for the subsequent quantification of the potential environmental impacts associated with each
basket, it is recommended to carefully assess the robustness of the selection of the representative products.
Such a robustness check should in particular be aimed at (1) identify (and avoid) any possible overlaps among
product groups, (2) identify (and avoid) any gaps, i.e. relevant product-groups that have not been included in
the calculations. Also, towards further development of the LC Indicators, it seems relevant to define and
consider not just one basket for each category (e.g. one basket of products for the category food), but – ideally
- a range of different baskets from the “best performing” (from an environmental view point) one to the “worst
performing” one.
The development of country-specific baskets should also be explored via e.g. an ad-hoc feasibility study on the
availability of the necessary country-specific data. While developing 100% country-specific baskets may not
yet be viable, it would be certainly possible to progressively adapt the baskets including more and more
country-specific datasets.
An increased availability of high quality LCI-data would of course help increasing comprehensiveness and
robustness of the assessment. A better integration of existing data with Input/Output (IO) data seems a viable
option, as these data are luckily to already include country-specific and lifecycle-stage specific information,
which is seen as important for developing further the indicators. In order to limit the data collection efforts
(and costs), the present calculations should be carefully checked (via e.g. sensitivity analysis) to identify some
key hotspot / product groups / part of the system that are most relevant in that they influence most the
environmental performance. Data collection efforts could then initially be limited to these identified
components.
It is also noted that a meaningful way to further facilitate the calculation of the BoP LC Indicators through
tailoring the set of impact categories in function of the basket under study. In fact, while some impact
categories could be calculated as default for all baskets (e.g. climate change), others could become basket-
specific. This calls for the definition of relevant criteria for the attribution of impact categories to the three
specific baskets.
The current study considers three key BoPs: food, shelter, and mobility. However, other consumption activities
contribute to the impacts as well. To further complete the impact profile of consumption by the EU citizen, an
extension with other consumption categories can be explored. First, when it comes to the basic needs the
current set of food, housing and mobility might be expanded with health care products and services. Further
on, other but less basic needs could be considered: communication and information products and services and
leisure activities like tourism.
The LCA-based methodology for target setting has been applied on the food sector only. The application of the
methodology has highlighted the need of a complementary approach, where literature review on hotspots is
coupled with LCA. In literature, the majority of the studies focus on energy and climate related impacts of food
supply chains, whereas the LCA applied to the food BoP supports a more holistic hotspot analysis. Indeed, LCA
offers a broader and multi-criteria based assessment of food supply. However, in the future variability and
ranges in the underlying datasets may give further relevant input in target setting. For example, consumer
choice and behaviour and hence associated datasets may vary considerably, leading to different impacts
attributable to the use phase and the overall BoP. In general, an uncertainty analysis of the result should be
conducted in order to highlight what is the relevance of the hotspots under different assumptions. Any
improvement and target should be anyway subject to further evaluation at system level and multi-criteria level
to ensure that a benefit in one impact category or life cycle stage is not leading to higher impacts elsewhere.
5
Table of Contents
Executive summary 3
1 Introduction 7
2 Basket of Products: food 8
2.1 Introduction 8
2.2 Definition of the basket of products for foods 8
2.2.1 Data sources 8
2.2.2 Assumptions 8
2.2.3 Final selection of the Basket of Products for Food (products per capita for one year) 11
2.3 Life cycle Inventory of the selected basket products 14
2.3.1 Data sources 18
2.3.2 Assumptions 19
2.3.3 Final selection: overview per product and life cycle stage 25
2.4 Results of the environmental impact of the selected products for one EU citizen 28
2.4.1 Result per product 28
2.4.2 Results per life cycle stage 36
2.4.3 Overall results of the environmental impact assessment of basket products per EU citizen 38
2.5 Interpretation of the results 40
2.6 References 42
3 Basket of Products: mobility 45
3.1 Introduction 45
3.2 Definition of the basket of products for mobility 45
3.2.1 Data Sources 48
3.2.2 Assumptions 49
3.2.3 Final selection 51
3.3 Life cycle Inventory of the selected products 51
3.3.1 Data sources 52
3.3.2 Assumptions 52
3.3.3 Final selection: overview per product and life cycle stage 59
3.4 Results of the environmental impact of the selected products for one EU citizen 61
3.4.1 Results per product 61
3.4.2 Results per life cycle stage 64
3.4.3 Results overall of environmental impact of mobility for one EU citizen 69
3.5 Interpretation of the results 73
3.6 References 74
Abbreviations 75
4 Basket of Products: housing 76
4.1 Introduction 76
4.2 Definition of the basket of products for housing 76
6
4.2.1 Data Sources 77
4.2.2 Assumptions 78
4.2.3 Final selection 81
4.3 Life Cycle Inventory of the selected products 89
4.3.1 Data sources 89
4.3.2 Assumptions 89
4.4 Results of the environmental impacts of the selected products for one EU citizen 94
4.4.1 Results per impact category 95
4.4.2 Interpretation of results 113
4.5 References 116
5 Application of the methodology for life cycle based targets setting to food Basket of Products 119
5.1 Identification of key economic sectors 120
5.2 Literature review on hotspots and megatrends about food consumption 122
5.3 LCA of the products in the Basket of products (BoP) food 124
5.4 LCA-based hotspot analysis of BoP food 125
5.5 Feasibility analysis of improvements 130
5.5.1 Identification of possible solutions 130
5.5.2 Quantitative target proposal 133
5.6 Identification of policy options, policy development and stakeholders hearings 138
5.7 Conclusions and outlook 139
5.8 References 140
6 Conclusions and perspectives 143
6.1 Conclusions 143
6.1.1 Conclusions on the BoPs results 143
6.1.2 Interpretation by comparison with other studies 143
6.1.3 Conclusions on the application of a LCA methodology for target setting 143
6.2 Perspectives on methodological issues 145
6.2.1 Definition of the current basket: consistency/overlap + bringing in a range 145
6.2.2 Representativeness/quality (data): country specific vs. European average 146
6.2.3 Impact categories: comprehensiveness/relevance of impact categories – inserting accounting (pressure
indicators) before coming to impacts 146
6.2.4 Basket of Products extension 146
6.2.5 Target methodology 146
7
1 Introduction
This report covers the work performed in the task 5 of the Administrative Arrangement, namely the development of
the basket of products indicators, as well as prototype targets. The basket of products indicators are intended to assess
the environmental impact of the European consumption (with distinction of the consumption categories). The baskets
of products developed under Task 5 cover three key consumption categories: food (section 2), mobility (section 3) and
housing (section 4). For each consumption category and related products the indicators were built for the impact
categories, as defined in the Product Environmental Footprint1 and the International Reference Life Cycle Data System
(ILCD)2. The calculations were made for the European Union as a whole (EU27) for the reference year 2010.
The basket-of-products approach matches statistics on private consumption per capita with life cycle inventory (LCI:
emissions and resource use) for each product consumed. As the products included in the basket are only a subset of
total consumption, the basket-of-products indicators provide an index for monitoring and analysis, and not an absolute
measure of environmental impact per person (EC, 2012c).
In order to develop the each of the basket of products the following steps were performed:
• Quantitative and qualitative analysis of the structure of the European consumption in each of the consumption
category – during the years 2000-2010 – including international trade.
• Selection of a basket of products representative for the structure of consumption for the reference year 2010 and
the development of a detailed list of the available datasets for the identified products with the feasibility
assessment of their application for the purpose of the project.
• Calculation of the environmental impact results for each of the basket as well as per citizen, which included:
o Development of process-based life cycle inventory models for the selected representative products.
o Development of the corresponding process based life cycle inventories (conforming to the ILCD format)
for selected representative products.
• Quantitative and qualitative analysis of the environmental impacts of each of the basket.
The objective of the calculation of the basket of products is to provide the profile of environmental impacts as well as
the impacts of representative products within each consumption category in relation to their relevance for the EU
sustainable product policy. The environmental impact (basket-of-products) indicators are developed in order to help
policy makers to monitor and evaluate the progress towards the reduction of the lifecycle environmental impacts of
European consumption, including helping focus eco-innovation and other different policy activities.
This report also aims at applying the life cycle based methodology in support to a comprehensive and systematic
target setting. This methodology for target setting has so far been applied on the food sector as preliminary example
(section 5).
The report covers also the conclusions and recommendations for the future work (section 6).
1 http://ec.europa.eu/environment/eussd/smgp/pdf/annex2_recommendation.pdf
2 http://lct.jrc.ec.europa.eu/assessment/publications
8
2 Basket of Products: food
2.1 Introduction
The development of baskets of products responds to the needs of analysing and monitoring European consumption
patterns and their global influence in order to shift to more resource efficient consumption. Specifically, basket of
products indicators quantify the environmental impacts for the EU-27 using the life cycle data, as well as data on
expenditure and consumption statistics.
The basket of products regarding human nutrition is particularly significant since food and beverage consumption is
responsible for over one third of the overall environmental burden caused by private consumption (Tukker et al. 2006)..
2.2 Definition of the basket of products for foods
2.2.1 Data sources
In order to identify the most representative food and beverage products to include in the basket, data related to food
consumption was analysed, mainly originating from:
• the Eurostat and FAO databases
• specific nutrition and food consumption literature concerning current emerging consumption trends
Whenever incomplete or incongruent Eurostat data was encountered it was verified, integrated or substituted with the
generic data from the FAO databases concerning food and drinks. Other useful information for the identification of
the basket was gathered from reports on the subject of food consumption and relative environmental aspects within
the EU (EEA 2012, DEFRA 2012, FAO 2011, Eurostat 2011, EC 2012c-d-e, Foster et al. 2006, Tukker et al. 2006).
The basket of products was calculated for the year 2010 based on an analysis of the data regarding food consumption
in EU27 within the 2000-2010 time span.
2.2.2 Assumptions
The summary of the main assumptions and of the approach used for the definition of the basket of products for food
and beverages are presented below.
Identification of the representative food data from the databases
Data concerning the average consumption per capita for EU citizens was collected by Eurostat until 2006. After this
period this specific database was discontinued. Since this data source is no longer available the starting point for the
identification of the apparent consumption of food products is the data from the Eurostat Prodcom Annual Sold (NACE
Rev. 2.) database.
Such data contains information on the production, import and export of all main categories of food and drink products
which allows a calculation of the apparent consumption (availability for human consumption) in terms of mass and
economic value (Consumption = Production - Exports + Imports).
The following Prodcom data about apparent food and drink consumption were not taken into account during the
selection process of the basket products:
• products unfit for human consumption (e.g. wastes such as oilcake and pet food)
• products not directly used by consumers for cooking or that are not directly edible (i.e those requiring further
processing before consumption - e.g. crude palm oil, starches)
• products with incoherent data: the export quantities were superior to the sum of the import plus production
quantities.
The quantities, in terms of mass, of the 2010 apparent consumption of the all Prodcom food products are shown in
Figure 1 (see also Annex 1). These quantities are divided among various food categories, namely processed meat and
seafood, production of meat products, cereal based products, dairy products, sugar based products, oils and fats, fresh
vegetables and fruit, processed and preserved fruit and vegetables, alcoholic and non-alcoholic beverages.
9
Table 1 illustrates the total quantity of EU 27 food and beverage apparent consumption (Prodcom), considered for the
selection of the basket products (excluding fruit for fresh consumption and vegetables), and the per-capita
consumption for the year 2010.
The Prodcom database does not contain information on non-processed or fresh vegetables and fruit. Hence the
Eurostat Agricultural production (apro) database and the FAO database were used to identify such data. The
information on the imports and exports of such food products was obtained from the Eurostat EU trade database-
HS6.
Figure 1 EU 27 main quantities of the apparent consumption of all the PRODCOM food categories for the
year 2010 (in tonnes)
Table 1 EU 27 food and beverage apparent consumption (PRODCOM data 2010): total and per capita
Total apparent consumption of all (Prodcom) products considered for the selection of the basket products,
excluding fruit for fresh consumption and vegetables - year 2010 (t) 468,936,745
EU population 1/1/2011 502,489,100
Per capita apparent consumption (kg/inhabitant.year) 933.2
The trade database was also used for the identification of the countries of origin of the imports of the selected basket
products. Annex 2 lists all the main countries from which at least 90% of the imports originate. Such information was
used in the environmental assessment illustrated in section 2.3 of this report. In some cases the Eurostat trade data
was substituted with more specific data from the FAO database or with data from the EC Agriculture and Rural
Development product reports (e.g. EC 2012c).
Information on the specific EU member countries responsible for the production of the basket products is illustrated
in Annex 3. In some cases, there are some discrepancies between the aggregated values of production supplied by
Eurostat and those calculated by summing the production of each EU27 country. Nonetheless from such data it is
possible to extract a picture of the main producing countries for each basket product.
Prodcom data for the year 2010 was substituted in the following cases:
• Milk and cheese production data per EU country was inconsistent with the aggregated values provided by the
Prodcom database. In such cases the Eurostat Agricultural production (apro) database was used as a data source
for the production information regarding each individual EU member state.
• Butter and sugar production data per EU country was inconsistent with the aggregated values provided by the
Prodcom database. In such cases the FAO Production / Livestock Processed database was used as a data source
for the production information concerning each individual EU member state.
Meat and fish66,765,541t
14%
Fruit and vegetable processing
37,849,295t 8%
Oils and fats22,170,737t
5%
Dairy product65,847,657t
14%
Cereal products43,372,722t
9%
Sugar and confectionaries
32,178,523t7%
Pre prepareed meals
5,300,568t1%
Non alcoholic drinks
127,056,080t 27%
Alcoholic drinks50,847,414t
11%
Other17,548,206t
4%
TOTAL APPARENT CONSUMPTION OF FOOD CATEGORIES FROM PRODCOM DATA (2010):468,936,745t
10
• Sunflower oil production data per EU country was inconsistent with the aggregated values provided by the
Prodcom database for the year 2010. In such case the data related to the production for each country was
extracted from the same database but for the year 2013.
• In some cases, a single missing value for the production/import or export of a product in a specific country was
substituted (whenever possible) either with the value from the preceding/successive year or with the average of
values calculated from the previous years.
Analysis of the structure of the consumption category of food during the period 2000-2010 and
consumption trends
Social, economic and political changes are constantly altering the way in which consumer goods, including food and
beverages, are consumed in the EU27. Specifically the economic crisis, immigration, demographic changes (in terms
of overall population, number of families and people per family, number of people per household), technological
advancements employed both at work and during recreation and leisure time are all affecting nutritional habits (EEA
2012).
The analysis of apparent food consumption for the 2000-2010 period (Annex 5) and the consultation of several
scientific reports and publications regarding food consumption and sustainability (CBI 2009, DEFRA 2012, EEA 2012,
EC 2012b, Eurostat 2011, Eurostat 2013) highlighted the following trends in this consumption category:
• Increase in the purchase of pre-prepared and frozen meals and convenience foods
• Increasing expenditure and frequency of eating take away food and in restaurants
• Increase in imported frozen vegetables and fruit especially from China
• Increase in the consumption of bottled water. Consumption in the EU was on average 105 litres per person in
2009 and was 117 litres per person in 2012 (EU 27).
These trends represent EU average consumption patterns that can actually differ significantly from country to country
since the effects financial and economic crisis have varied considerably in Europe. For example, whilst northern Europe
seems to be slowly exiting the current crisis, the Baltic countries and Greece are still suffering this crisis with a
generalised contraction of consumer goods (Eurostat 2013).
In view of the above considerations ‘prepared meals and dishes’ and ‘mineral water’ were included in the basket of
products as illustrated in Annex 4 and the section 2.2.3.
Data selection criteria and identification of the basket products
This section summarises the criteria with which the food and beverage apparent consumption data from the Prodcom,
other Eurostat databases and FAO databases was analysed in order to define a nutrition basket of products for the
year 2010 for the EU 27.
Among all the identified Prodcom data regarding apparent food and beverage consumption (Figure 1), some entire
specific food categories (according to the Prodcom NACE 2.0 classification) were excluded as potential basket products,
namely:
• ‘Manufacture of other food products n.e.c.’ (Nace 2.0 code 1089): even though these represent 1.6% of the overall
mass and 4.24% of the overall value of all Prodcom apparent consumption, the nature of the individual products
in this category is varied and none of the individual products are consumed in significant quantities.
• ‘Manufacture of homogenised food preparations and dietetic food’ and ‘Manufacture of condiments and
seasonings’ (Nace 2.0 code 1086 and 1084): these represent only modest quantities of the overall mass and of
the overall value of all Prodcom apparent consumption.
The remaining apparent consumption data, including those concerning the principal fresh vegetables and fruits, was
divided among the product groups from which to select the basket products (see Annex 4 and Figure 1). Specific data
concerning apparent consumption of the types of food and beverage products belonging to each of the above
mentioned product groups were then analysed and the final choice of products for the basket was based on criteria
regarding:
• Apparent food and drink consumption and the respective economic value of such amounts of product. Food types
consumed in the largest quantities were considered as potential basket products.
11
• Prior knowledge of the magnitude of environmental impacts of a type of food product. It is well known that the
certain food types, such as meat and dairy products (Foster et al. 2006), are the most impacting not only within
the food category but also amongst all of the privately consumed goods (Tukker et al. 2006) especially in terms
of greenhouse-gas-emissions (GHG) (Gerber et al. 2013). Such food types were included in the basket
independently of the amounts of their apparent consumption.
• Consumption trends of food and drink during the last ten years. Types of food and beverage whose consumption
trend has been increasing during this time period, independently of the magnitude of their environmental impact
and the extent of their apparent consumption, were included in the basket (see previous paragraphs on
consumption trends).
2.2.3 Final selection of the Basket of Products for Food (products per capita for one
year)
Based on the above mentioned criteria, the food and beverage product types illustrated in Table 2 and Table 3 were
identified as those most representative of the nutrition basket for the year 2010 for the EU 27. These are similar in
nature to the main food types of the ‘Farm to Fork’ study (Eurostat 2011) and to those of the previous basket of
products study dating back to 2006 (EC 2012a).
Table 2 Basket of products and respective product groups (year 2010)
Product groups Selected Basket Product
Meat and seafood Beef, Pork, Poultry
Dairy products Milk, Cheese, Butter
Crop based products Olive Oil, Sunflower Oil, Sugar
Cereal based products Bread
Vegetable Potatoes
Fruits Oranges and Apples
Beverages Coffee, Mineral Water, Beer
Pre-prepared meals Meat based meals
With respect to the products included in the basket of the previous 2012 report (EC 2012a), the new basket includes
all the previous product types and adds 4 new ones. Bread is included in order to represent the cereal food category.
Meat based pre-prepared meals have also been included in order to represent a current consumption trend. The other
added products are mineral water and olive oil.
Brief description of each of the basket products (year 2010)
MEAT: Among the meat and fish products category beef, pork and poultry resulted as the most consumed products.
Fish products were the least consumed products of this category and were thus excluded from the basket (Annex 4).
Some meat subcategories representing a mixture of various types of meat (e.g. ‘Edible offal of bovine animals, swine,
sheep, goats, horses and other equines, fresh or chilled’) were not included in the calculations of the overall
consumption of each of the meat types.
Data representing meat consumption (processed meat, e.g. carcasses, fresh cuts, whole chickens and turkeys) does
not include prepared meat products such as sausages etc. Since these prepared products are derived from the
processed meat, the apparent consumption of processed meat implicitly includes the apparent consumption of
prepared meat products. Furthermore the amount of prepared meat (pork, beef and poultry) products imported and
exported are less than 3% of the total of the processed pig and beef meat; this implies that the calculated
environmental impacts for the processed meat are effectively occurring in the EU. Prepared meat products (beef, pork
and poultry) for the year 2010 represent one third of the overall consumption of processed meat.
Some of the processed meat will inevitably end up in other products such as for example meat based pre-prepared
meals and stuffed pasta. In order to avoid double counting issues for the category of meat based ‘prepared meals and
dishes’ (see section 2.3), the environmental impact of the meat production was accounted for only in the assessement
of such dish and was not accounted for in the LCA of the beef basket category. Similarly the sunflower oil and potatoes
used for the preparation of the dish were also only accounted for in the impact assessment of the prepared meal.
12
Pig meat: the total yearly apparent consumption in terms of sold quantities of processed pork amounts to
20.6 million tonnes and is made up of principally fresh or chilled meat and hams, carcasses, fat and lard. The
economic value of this consumption amounts to 33.7 billion EUR. The main producers, responsible for over
78% of the production are Germany, Spain, France, Italy, Denmark and Poland. Imports of such product are
negligible (0.11% of the total production – see Annex 4).
Beef: the 2010 processed beef apparent consumption consists of 6.9 million tonnes of carcasses and fresh
or chilled cuts and has an economic value of 26.4 billion EUR. The main producers are France, Germany, Italy,
United Kingdom, Spain and Ireland which are responsible for nearly 80% of the overall 2010 production. The
imports amount to 2.9% of the yearly beef production and originate principally from Argentina, Uruguay,
Brazil, Botswana, United States, Namibia, Australia and New Zealand.
Poultry: the processed poultry meat yearly consumption (11.5 million tonnes, for a value of 23.2 million EUR)
is ascribable to cuts of chicken (39%), fresh or chilled whole chickens (32%) and cuts of turkey (11%). A major
part of the total production (12.5 million tonnes) is evenly distributed among Germany, Spain, Poland, United
Kingdom, Italy, France and Netherlands. Imports amount to 1.34% of the yearly poultry production and are
chiefly from Brazil, Chile and Argentina.
Table 3 Basket of products and apparent consumption (year 2010, EU 27)
Basket of product Total consumption of
basket product (kg/year)
Per-capita apparent
consumption
(kg/inhabitant.year)
% of total per-capita
apparent basket
consumption
Economic value of the
consumption fo each
basket product (€/year)
Pig meat 20,577,780,453 41.0 7.6% 33,662,075,184
Beef 6,908,857,637 13.7 2.5% 26,364,299,736
Poultry 11,493,631,410 22.9 4.2% 23,205,612,920
Bread 19,753,915,765 39.3 7.3% 26,903,954,621
Milk and Cream 40,246,421,375 80.1 14.8% 22,898,901,633
Cheese 7,519,349,214 15.0 2.8% 28,952,575,241
Butter 1,825,989,144 3.6 0.7% 5,929,095,967
Sugar 14,965,056,818 29.8 5.5% 8,036,450,518
Refined Sunflower oil 2,725,842,346 5.4 1.0% 2,372,460,990
Olive oil 2,680,017,479 5.3 1.0% 4,703,361,683
Potatoes 35,241,000,000 70.1 13.0% 10,166,193,000
Oranges 8,723,122,900 17.4 3.2% 5,096,920,710*
Apples 8,065,996,300 16.1 3.0% 4,730,706,830*
Mineral water 52,741,838,200 (litres) 105.0 (litres) 19.4% 8,920,405,677
Roasted Coffee 1,748,478,908 3.5 0.6% 9,277,724,061
Beer 35,056,541,024 (litres) 69.8 (litres) 12.9% 28,682,876,500
Prepared dishes and
meals- meat based 1,438,891,580 2.9 0.5% 13,737,753,774
TOTAL 271,712,730,553 540.7 100.0% 263,641,369,045
* Estimated economic value of production
BREAD: among the cereal based products bread represents over 45% of the total mass and 35% of the total economic
value of all the consumed products of the category. The amount of bread consumed in EU 27 for the year 2010
amounts to 19.7 million tonnes. Over 75% of the production occurs in Germany, United Kingdom, Italy, Poland, Spain,
France and Romania. More than 136 million tonnes of wheat were produced in the EU in 2010.
For the same year the wheat imports to amount 3.1% of the total yearly wheat production and such imports are
mostly durum wheat imports mainly from Canada, US, Mexico, Turkey and Australia.
MILK AND CREAM: the 2010 yearly production of cow milk in the EU amounts to 148 million tonnes. The overall
consumption of milk and cream for fresh consumption amounts to 40.2 million tonnes with an economic value of 22.9
billion EUR. Approximately 77% of this production occurs in the United Kingdom, Germany, France, Spain, Italy, Poland
13
and Sweden. The small amounts of imported milk in 2010 (8.5 thousand tonnes) were mostly from Norway,
Switzerland and Croatia.
CHEESE: cheese consumption for the year 2010 amounts to 7.5 million tonnes with an overall value of 29 billion EUR.
Over 55% of the mass quantity is attributable to cheese whilst the rest is ascribable to cheese spreads and other fresh
cheese. The main producers are Germany, France, Italy, Netherlands Poland, UK and Spain. The main imports are
minimal (0.97% of the overall yearly cheese production) and originate mainly from Switzerland and New Zealand.
BUTTER: butter consumption totals 1.83 million tonnes in 2010 and has a value of 5.9 billion EUR. Over 80% of this
product is produced in France, Germany, Poland, Ireland, Netherlands, United Kingdom and Italy. The imports amount
to 1.96% of the overall butter production (1.9 million tonnes) and originate nearly totally from New Zealand and the
US.
REFINED SUGAR: this yearly consumption totals 14.97 million tonnes and has an economic value of 8 billion EUR. FAO
data on centrifugal sugar indicates that the main producers of such commodity are France, Germany, Poland, Ukraine,
UK and Netherlands. The imports of such refined products amount to 4.53% of the yearly production (16.2 million
tonnes of refined sugar) and originate primarily from Mauritius, Serbia, Croatia, Brazil and Swaziland.
OILS AND FATS: within this category olive oil and sunflower oil consumption amount to over 28% of the mass total
surpassing animal and vegetable fats. Refined colza, palm and rape oil consumption was higher than any other oil,
however they were not selected as basket products since they are not typically used for domestic food preparation
and a large share of these oils is consumed for the production of bio-fuels (EC 2008).
Refined sunflower oil: the 2010 apparent consumption totals 2.7 million tonnes with an economic value of
2.4 billion EUR. The 2013 country specific data regarding such product (2010-11-12 data was incomplete)
indicates that the main production (over 88% of total) occurs in Spain, Italy, Hungary, Germany, France, and
Romania. Imports amount to 4% of the yearly sunflower oil production and are primarily from Ukraine,
Argentina, Russia, Bosnia and Herzegovina and Moldova.
Olive oil: the 2010 apparent consumption amounts to 2.7 million tonnes and is worth 4.7 billion EUR.
Production occurs in the Mediterranean countries with Spain and Italy being responsible for over 95% of the
production. The imports (2.77% of the total EU production) of such product are mainly from the neighbouring
Mediterranean non EU countries such as Tunisia and Morocco.
POTATOES: 2010 potato apparent consumption of all types of potatoes (including seed and early potatoes) according
to the Eurostat data amounts to 55.3 million tonnes. The FAO database indicates an effective per capita potato
consumption of 70.1 kg/year which corresponds to a total apparent consumption for the year 2010 of 35.2 million
tonnes.
The value of the 2010 production amounts to 10.2 billion EUR. Such production is concentrated mostly in the northern
EU countries such as Germany, Poland, Netherlands, France, United Kingdom, Belgium and Romania. In 2012 0.42
million tonnes were imported mainly from Israel and Egypt.
FRUIT: the most consumed fruits in the EU 27 are oranges and apples.
Oranges: this is the most consumed fruit in the EU. In 2010 8.7 million tonnes were consumed. The production
occurs mainly in the Mediterranean countries of the EU, namely Italy, Spain and Greece (these first three
countries responsible for over 97% of the production), Portugal, France and Malta. The production has a value
of 5.1 billion EUR.
Imports for 2010 amount to 0.95 million tonnes and originate principally from South Africa, Egypt, Morocco,
Argentina, Uruguay, Brazil, Zimbabwe and Tunisia. In 2010 the EU production of un-concentrated orange juice
(frozen and non) amounted to 3.1 million tonnes.
Apples: this is the second most consumed fruit in the EU. The overall production of apples for 2010 totals 8.7
million tonnes with Italy, France, Poland and Germany responsible for over 64% of the production. Such
production has a value of 4.7 billion EUR.
In terms of apparent consumption, 8.06 million tonnes of apples for fresh consumption were consumed in
2010. The imports represent 7.1% of the production of apples for fresh consumption and originate mainly
from Chile, New Zealand, South Africa, Brazil, Argentina and The Former Yugoslav Republic Of Macedonia.
14
MINERAL WATER: among the non-alcoholic drinks mineral water resulted by far the most consumed beverage (1.5
times the volume of consumed soft drinks; 5 times the amount of consumed fruit juices). In 2010 52.7 billion litres of
mineral water were consumed with an economic value of 8.9 billion EUR. The Prodcom data concerning the production
of mineral water indicates Italy as the largest producer (26% of the total) followed by France, Spain, Poland, Romania,
United Kingdom, Portugal, Hungary and Greece. The imports are very modest (96 thousand tonnes for 2010) and are
mainly from Turkey, Norway, Croatia, Belarus, Georgia and Switzerland.
ROASTED COFFEE: the apparent consumption of roasted coffee for 2010 totals 1.75 million tonnes (caffeinated and
decaffeinated) with an economic value of 9.2 billion EUR. The production of this roasted coffee occurs mainly (over
80% of the total production) in Germany, Italy, Spain, France, Netherlands, Sweden, Belgium and Finland. Annual
imports (31.4 million kg) represent 1.8% of the annual production and originate predominantly from Switzerland and
Brazil. Green coffee which is used to produce roasted coffee is not cultivated in the EU but it is entirely imported.
Specifically, EU 27 imports of green coffee for 2010 amount to 2.2 million tonnes and originate mainly from Brazil,
Indonesia, Honduras, Peru, India, Uganda, Ethiopia, Colombia, Guatemala, El Salvador, Nicaragua, Kenya, Cameroon
and Mexico.
BEER: this is the most consumed alcoholic drink in the EU 27 (3 times the volume of consumed wine products) and
was thus chosen as a representative basket product. In 2010, 35.1 million litres were consumed for a total value of
28.6 billion EUR. The largest productions occur in Germany (23%), UK (14%), Poland (10%), Spain (9%), Netherlands
(7%), Belgium (5% ), Romania (5% ) and Czech Republic (5%). The imports are modest when compared to the
production (0.71% of the 2010 production of 37.2 million tonnes) and originate mostly from Mexico, Russia, Belarus,
China, Ukraine, US, Thailand, Switzerland, Turkey, Trinidad and Tobago and Croatia.
PREPARED DISHES AND MEALS - MEAT BASED: the overall apparent consumption of prepared dishes and meals in
2010 was 5.3 million tonnes with an economic value of 13.7 billion EUR. Among this main class of products in 2010
‘prepared meals and dishes based on meat, meat offal or blood’ is the most dominant with an apparent consumption
of 1.4 million tonnes/year.
2.3 Life cycle Inventory of the selected basket products
After identification of the nutrition basket-of-products was identified, the individual LCA of each product in the basket
products was implemented. First it was necessary to build a common framework relative to assumptions and models
to be used for the single product assessments in order to achieve consistent LCAs and to obtain comparable results.
The next step was the development of the process-based life cycle inventory models for the selected representative
products and of the corresponding process-based life cycle inventories. The inventories constructed for each product
regard not only the production phase of single food products but all stages of the food chain including losses and end
of life of products and waste. The main methodological considerations for the nutrition category products are given in
the following paragraphs.
Reference System
The reference system refers to the consumption per capita in EU-27 for the above listed products.
Functional Unit
The functional unit is defined as the average food consumption per person in EU in terms of food categories (including
the food losses at each stage).
System Boundaries
System boundaries consider a cradle-to-grave approach. For each stage of the life cycle, the process-based life cycle
inventories were developed for the selected representative products. System boundaries cover the agricultural and
production stage of each product, the logistics including international trade, the internal distribution to the retailer and
the consumer’s home, the packaging production and end of life, the use phase which considers home preparation of
food and food scraps, the end of life which covers the waste management of human excretion by wastewater
treatment plants and the end of life of food scraps into the municipal solid waste system. Food losses throughout the
life cycle have also been accounted for.
15
The general system boundaries of the analysed products are shown in Figure 2, divided into six parts:
agriculture/breeding, industrial processing, logistics, packaging, use and end of life. The stages considered in the
different life cycle phases are the following:
Agriculture/breeding
• Cultivation of crops
• Animal rearing
• Food waste management
Industrial processing
• Processing of ingredients
• Slaughtering, processing and storage of meat
• Chilled or frozen storage
• Food waste management
Logistics
• International transport of imports
• Transport to manufacturer
• Transport to regional distribution centre
• Distribution
• Transport to retailer
• Food waste management
Packaging
• Manufacture of packaging
• Final disposal of packaging
Use
• Transport of the products from retailer to consumer’s home
• Refrigerated storage at home
• Cooking of the meal
End of life
• Final disposal of food waste
• Wastewater treatment and auxiliary processes due to human excretion
In Annex 8 the specific system boundaries and the flow diagrams of the 17 basket products are reported.
16
Figure 2 System Boundaries
Allocation Rules
All food systems include at various stages of their life cycle the production of scraps or other materials that may be
considered in many cases co-products. Therefore, the problem of the allocation of environmental loads is present in
almost all food chains. This problem is further complicated by the fact that the mass of the co-products very often
exceeds by far the mass of useful food products obtained.
By performing the allocation on a mass basis would result in the displacement of a large part of the impact associated
with the food chains to the co-products rather than burdening the product for which the entire supply chain was built.
Based on these considerations, allocation of environmental impacts during food production is solved on the basis of
economic allocation.
Cut-off Rules
The life cycle data for a minimum of 99% of total inflows in terms of mass have been included for each basket
product. Inflows not included in the LCA are specified in the section referred to the specific assumptions per product.
Agriculture
product
Industrial processing
product
Trasport of imports
waste/loss
Packaging
product
Distribution
Retail
Home transport
Use
End of life packaging
eaten product
Wastewater treatment
Internal trasport
product
waste/loss
waste/loss
End of life organic waste
waste/loss
17
LCIA Methodology
The impact assessment method for the assessment of inventories is ILCD which refers to midpoint impact categories
(EC 2010). The selected impact categories are those included in the method with the respective characterization
factors. Long-term emissions are excluded from the assessment according to Aronsson et al. (2013).
Data quality requirements
Different data quality requirements have been implemented in order to choose the inventory data which was most
adaptable to the present study and approach, including the country of origin of available data.
Data quality has been assessed on the basis of the following parameters in a pedigree matrix:
• Time-related coverage: age of data
• Geographical coverage: geographical area from which data for unit processes have been collected
• Technology coverage: specific technology or technology mix
• Completeness: type of provided flow
• Consistency: coherence of data with the methodology and assumptions of the study.
The specifications of the indicators with the relative score are given in the Table 4 which shows the Pedigree matrix
used to assess the quality of data sources. The approach followed was partly taken from Weidema et al. (2013) and
modified in order to align it to the objectives of the study.
The overall quality of the data set can be derived from the quality rating of the various quality indicators. This has
been calculated by summing the achieved quality rating for each of the quality components; the sum is then divided
by the number of applicable quality components. Therefore the score of each data is the arithmetic average of the
scores obtained in the various requirements. No further classification of the final overall quality scores was made.
For example, the application of the matrix to the evaluation of the data quality of the paper by Schmidt Rivera et al.
(2014), relative to the pre-prepared meals, was carried out in the following way. Time-related coverage is less than 3
years (score 1). Geographical coverage is respected via the use of data deriving from the area under study (score 1).
As regards technology coverage, the processes and materials under study refer to a specific technology and not to a
representative technology for the whole production; therefore the score is 2. Completeness scores 1 as a complete
tree of processes is provided with a very detailed description; this means that data are given for each of the sub-
processes in which the system can be divided and not as a single aggregate inventory of the whole system. The
consistency gets a score of 2 because the hypotheses and assumptions about allocation and cut-offs are different
from those at the base of this study. In any case, since the inventory of the processes is provided in a disaggregated
way, it is possible to apply much of the methodology and assumptions of the present study, especially with regard to
the agricultural phase of the various products which constitute the inputs of pre-prepared food. The final score obtained
from this data set is equal to 1.4 which is the arithmetic average of the scores obtained for each of the different
requirements. This score was used to identify the representative data set of the product in question.
With regard to the requirement of coherence, many studies report the data in terms of an environmental inventory of
the life cycle of the products in terms of elementary flows. From these data it is not possible to apply the assumptions
made for example for the agricultural phase, since the inventory define the amount of natural resources used by the
system, but these cannot be traced to the amount of fertilizer needed for the estimation of emissions of ammonia,
N2O, etc. In these cases the methodology is therefore not applicable and the score assigned to this requirement is 5.
18
Table 4 Pedigree matrix used to assess the quality of data sources (modified from Weidema et al. 2013).
Indicator score 1 2 3 4 5
Time-related coverage Less than 3 years
of difference to
the time period of
the dataset
Less than 6 years
of difference to
the time period of
the dataset
Less than 10
years of
difference to the
time period of
the dataset
Less than 15 years
of difference to
the time period of
the dataset
Age of data
unknown or more
than 15 years of
difference to the
time period of the
dataset
Geographical coverage Data from area
under study
Average data
from larger area
in which the area
under study is
included
Data from area
with similar
production
conditions
Data from area
with slightly
similar production
conditions
Data from
unknown or
distinctly
different area
Technology coverage Data from
processes and
materials under
study and from
different
technologies
Data from
processes and
materials under
study but from a
specific
technology
Data on related
processes or
materials
Data on outdated
technology
Data on related
processes on
laboratory scale
or from different
technology
Completeness provided a
complete tree of
processes and a
very detailed
description
provided a
complete process
not as a tree
integrated
system of black
boxes
provided an
incomplete
process not as a
tree
incomplete black
box
Consistency applicable the
methodology and
assumptions of
the study
applicable much
of the
methodology and
assumptions of
the study
applicable part
of the
methodology
and assumptions
of the study
applicable to a
small extent the
methodology and
assumptions of
the study
non applicable
the methodology
and assumptions
of the study
2.3.1 Data sources
In order to identify useful datasets representing inventory data for each stage of the lifecycle of the basket products,
described in Section 2.2.3, a literature review of work regarding the environmental assessment of each basket product
(with particular emphasis on the LCA approach) was carried out.
The scientific publications containing relevant inventory information useful for the formation of datasets are listed in
Annex 6 (referred to each basket product). Annex 7 contains a table with the indication, for each of the papers listed
in Annex 6, of the lifecycle phases for which useful inventory data may be extracted from these publications.
By applying the methods described in the Data Quality Requirements section to the collected literature, the most
representative datasets for each product in the basket were identified. In particular, for each process or stage of the
life cycle, choosing the most representative data set was performed by comparing the data quality scores obtained
from the various data sources; the data set chosen was the one which obtained the lowest score (which corresponds
to a higher quality), regardless of the specific level. With the same final score, the data set having a better score in
the geographical coverage requirement was preferred.
LCI datasets of the agriculture/production stage for the basket products are briefly summarized in Table 5. These
datasets have been identified on the basis of data quality requirements, in the above mentioned way. For
completeness, the table also shows the producing country that is the country to which the data in question relates;
this does not necessarily mean that the country could be considered a key producer, representative of the European
production.
Foreground data were obtained from literature and direct industry sources. Background data are mainly taken from
the Agrifootprint and Ecoinvent v.3 databases.
19
Country specific import data for the basket products are taken from Eurostat international trade database for the year
2010 (unless otherwise specified). Import countries distances and modes of transport were also accounted for as
reported in Annex 2.
Table 5 Overview of LCI datasets relative to the agriculture/production phase
Product category Representative
products
Sources of representative datasets
Alcoholic, non-
alcoholic
beverages
Coffee Production of 1 kg roasted coffee. Agricultural production in Brazil in the 2006 reference
year and wet processing for the production of green beans in the 2014 reference year.
Roasting process in the 2009 reference year. Data from Coltro et al. (2006).
Beer Production of 1 L of beer in the 2012 reference year, assuming EU-27 electricity. Data
from Schaltegger et al. (2012).
Mineral water Production of 1 L of mineral water in the 2014 reference year from Vanderheyden and
Aerts (2014).
Cereal based
products
Bread Production of 1 kg of bread in UK in the 2011 reference year. Data for bread production
from Espinoza-Orias et al. (2011). Main data for wheat production are relative to
Germany in the 2014 reference year, assuming EU-27 electricity and pesticides (from
Agri-footprint database).
Meat and
seafood
Beef Production of 1 kg of fresh cut in Ireland in the 2014 reference year. Data on both
rearing and slaughtering are referred to the same country. Main data from Agri-
footprint database.
Pork Production of 1 kg of fresh cut in The Netherlands in the 2014 reference year. Data on
both rearing and slaughtering are referred to the same country. Main data from Agri-
footprint database.
Poultry Production of 1 kg of fresh cut in The Netherlands in the 2014 reference year. Data on
both rearing and slaughtering are referred to the same country. Main data from Agri-
footprint database.
Dairy products Milk Production of 1 kg of milk in the 2014 reference year, assuming EU-27 electricity. Data
on raw milk are referred to The Netherlands (from Agri-footprint database) while data
on processing to Italy (from Fantin et al. 2012).
Butter Production of 1 kg of butter in Serbia in the 2014 reference year, assuming EU-27
electricity. Data from Djekic et al. (2014)
Cheese Production of 1 kg of milk in Serbia in the 2014 reference year, assuming EU-27
electricity. Data from Djekic et al. (2014)
Crop-based
products
Sugar Production of 1 kg of sugar from sugar beet in Germany in the 2014 reference year,
assuming EU-27 electricity and pesticides. Main data from Agri-footprint database.
Sunflower oil Production of 1 kg of sunflower oil in Ukraine in the 2014 reference year, assuming EU-
27 electricity and pesticides. Main data from Agri-footprint database.
Olive oil Production of 1 kg of extra virgin olive oil in Italy in the 2013 reference year. Data on
agricultural production and olive oil processing are directly taken respectively from
producers and industry. Data from Notarnicola et al. (2013).
Vegetables Potatoes Production of 1 kg of potatoes in Germany in the 2014 reference year, assuming EU-
27 electricity and pesticides. Main data from Agri-footprint database.
Fruits Apples Production of 1 kg of apples in Switzerland in the 2006 reference year, assuming EU-
27 electricity and pesticides. Data from Milà i Canals et al. 2007.
Oranges Production of 1 kg of oranges in Italy in the 2013 reference year, assuming EU-27
electricity and pesticides. Data from Pergola et al. (2013).
Pre-prepared
meals
Pre-prepared
meals based on
meat
Production of 1 kg of pre-prepared meal based on meat. Data from Schmidt Rivera et
al. (2014) in the reference year 2014, including poultry meat, potatoes, tomato sauce
and dressings.
2.3.2 Assumptions
The LCI methodology follows in many aspects the methodology used to process Ecoinvent background data
(Frischknecht et al. 2007). The following main assumptions are considered:
20
• Lifetime of food products are considered to be less than 1 year.
• Infrastructure is included with a life time of 50 years and a construction time of 2 years
• Waste management is included.
• EU-27 dataset for electricity is used. In the inventory, electricity consumed in the food chain always refers to low
voltage electricity (LV). In the distribution system of electricity the medium-voltage is used in the intermediate
portions of the electricity grid between the high-voltage receiving stations from the power lines and the cabins of
final transformation for delivery at low-voltage. Low voltage electricity is used in most of the private electrical
systems, both civil and industrial, as well as in secondary distribution networks. Only some large users buy
electricity directly at medium voltage, but in any case they reduce it by providing LV with private cabins. This study
considers low voltage the range of electric voltage between 50 and 1,000 volts in terms of AC current. So the
choice of this voltage seems adequate to represent the actual situation of food plants and consequently, for the
inventory of electricity, the process taken from the ELCD database named “Electricity mix, AC, consumption mix,
at consumer, < 1kV EU-27 S” was used. However this assumption is referred to the foreground of the product
systems and not to all the other background processes which could make use of medium voltage electricity.
• Double counting occurs when considering pre-prepared meals made with other basket products. In this case the
amount of products contained in the pre-prepared meal is subtracted from the relative amount of basket product
calculated and described in section 2.2.3 and allocated to the pre-prepared meal.
• The imports of basket products have been treated as if they were produced domestically (in the EU).
A comprehensive list of assumptions organized by life cycle stages is given in the following paragraphs.
Agricultural/Breeding stage
Fertilizers
The data used for consumption of fertilizers in the various phases of agricultural production depends on the quality of
the bibliographic source used. When consumption data related to the specific fertilizers was available, the specific
environmental inventories extracted from databases were directly associated to such consumption data.
In many cases the data relative to the agricultural phases of the examined processes report the consumption of
fertilizers in terms of N, P2O5 e K2O content and not in terms of fertilizer. Sometimes consumption is reported in more
aggregated terms as the sum of the three main nutrients.
In these cases, the approach used to generate inventory data for fertilizers and their respective emissions was similar
to that followed by the Agri-footprint and Ecoinvent databases (described below), so that the processes obtained were
consistent with those extrapolated from these databases.
Standard distances were used for the transport of materials from their production site to the processing plant or the
farm. This is 500 km by lorry. Ecoinvent transport unit processes are used.
The following section illustrates the hypotheses and assumptions made to estimate the consumption of fertilizers and
subsequently those related to emissions associated with the use of fertilizers.
Synthetic fertilizer application rates
As previously mentioned, in the case in which the data relative to the agricultural phases of the examined processes
report the consumption of fertilizers in terms of N, P2O5 e K2O content and not in terms of fertilizer, an approach for
the estimation of synthetic fertilizer application rates was followed.
The first step is the identification of the type of fertilizer employed (eg. urea or potassium chloride, etc.) starting from
the total consumption of ingredients, in order to associate it to the relevant environmental inventory.
In practice statistical data on the use of fertilizers in a given country were employed in order to disaggregate
consumption given in terms of N, P2O5 e K2O. The relative rates of fertilizer consumption were obtained from the
database of the International Fertilizer Industry Association (IFA 2012) that provides regionalized data on production,
import, export and consumption of fertilizers. The data series used cover the period 2008-2011 and for each data
item the average consumption observed in the four years mentioned was considered. The data were broken down by
country as well as for type of fertilizer.
By using such a database it was possible to reconstruct for each country the percentage of consumption of each type
of fertilizer.
21
For example, the average consumption of nitrogen contained in fertilizers in EU-27 for the period 2008-11 amounted
to 9.6 Mt; in the following table, the percentage of nitrogen that is sold in the form of indicated fertilizers is reported.
The indicated percentages refer only to the nitrogen content and not the entire weight of the fertilizer.
Ammonium
sulphate Urea
Ammonium
nitrate
Calcim ammonium
nitrate
Nitrogen
solutions
Ammonium
phosphate
N P K
compound
3% 21% 22% 25% 12% 2% 15%
If the consumption of nitrogen fertilizer in the production of apples, for example, amounts to 140 kg N/ha, this
consumption was broken down using the percentages indicated above. As these data are expressed in terms of N
content, they were then converted into the amount of fertilizer using their titles.
In the example specified, then 140 kg of N is shared among the different fertilizer multiplying by the appropriate
percentage. For the ammonium nitrate, 140 kg N/ha per 22% results in 30.8 kg N/ha; this means that on a hectare
30.8 kg N are delivered in the form of ammonium nitrate. Since the title of N in the ammonium nitrate is 35%, this
equals to 30.8 kg N divided 0.35, amounting to 88 kg of ammonium nitrate delivered to the field. The same calculation
is performed for all other fertilizers.
Of course, by adopting this approach in the analysis, it is assumed that the relative consumption rates of fertilizers
are the same for all crops within a certain country; thus, continuing the previous example, if the consumption of
nitrogen fertilizer amounts to 140 kg N/ha also for the production of oranges, the result is that even for oranges
production the use of ammonium nitrate will be equal to 88 kg/ha.
Some fertilizers supply multiple nutrient types (for example ammonium phosphate application supplies both N and P
to agricultural soil). In IFA statistics, the share of ammonium phosphate is given as part of total N and also as part of
total P supplied in a region. To avoid double counting, this dual function was taken into account. The same issue arises
for the NPK compounds.
Emissions from application of fertilizers
The application of fertilizers results in a number of important emissions that affect global warming, eutrophication
and other impact categories.
The emissions of N2O from managed soils and CO2 emissions from lime and urea application have been estimated
according to the IPCC methodologies (IPCC 2006a). By applying the calculation suggested by the IPCC guide, the
ammonia emissions to air and the nitrate leaching in the soil were also estimated. The NH3 and NO3-calculations were
carried out following the approach of Brentrup et al. (2000). It is assumed that all nitrogen that volatises converts to
ammonia, and that all nitrogen that leaches is emitted as nitrate. The phosphorus emissions to water from fertilizers
are calculated based on the phosphorus content of the applied fertilizer. The fraction of phosphorus emission that
reaches freshwater is estimated as 5% of phosphorus applied as fertilizer.
This approach is the same as that followed for the inventories of the Agri-footprint database (Blonk, 2014). This
guarantees the coherence between the various inventories of the different basket products.
Pesticides
Pesticides are among the most important inputs in the agricultural phase, having an impact on human and
environmental toxicity. The estimate of emissions from pesticides is essential to assess the environmental burden of
agricultural production. In order to make this estimate, it is necessary to have adequate data concerning both the
amount of pesticides used and the emitted quantities of the various active ingredients into the different environmental
compartments.
Pesticides application rates
For the purposes of the present work the approach indicated by Fantke et al 2014 was followed. This approach consists
of a framework developed to assist the quantification of pesticide fractions starting from different levels of publicly
available data. The data used for the estimation of the pesticides quantities used in various cultures were obtained
from Eurostat Statistical Book ‘The use of plant protection products in the European Union’, which contains data on
the consumption of pesticides in various European countries from 1992 to 2003 (EC 2007). The data used are those
of 2003 (the last available year) and relate to the total consumption of pesticides per European country and to the
22
consumption per hectare of various categories of pesticides, divided into herbicides, fungicides, insecticides and other
plant protection products.
The report also shows consumption per hectare for various crops and the top five active ingredients used per country
and per chemical class.
Dosages of plant protection products used by crop have been used; these show the consumption of active ingredient
per hectare divided among the major categories. In order to identify the active ingredients associated with each
category the following procedure was used:
• The main chemical classes were identified by crop and then, for each of these classes, the main active ingredients
were identified; these active ingredients were chosen among those listed in the top 10 active ingredients of each
category. A handbook of agriculture was consulted for information on the use of such ingredients in specific crops.
A value equal to the total consumption of the specific category was assigned to the ingredients identified. For
example, for the cultivation of citrus fruits, a total consumption of herbicides in Europe is indicated as 4.0 kg/ha
in terms of active ingredients. A table reports the main chemical classes of herbicides applied to citrus crops. This
table shows that 2,031 tonnes of organophosphorus herbicides are consumed on a total of 2,289 tonnes is used
for the cultivation of citrus fruits; this amounts to about 90% of total herbicides consumption. All other herbicides
have a consumption of less than 3%. Glyphosate is the main herbicide of the organophosphorus herbicides class.
Therefore for the cultivation of citrus fruits a consumption of glyphosate was assumed to be equal to the total of
the class which is 4.0 kg/ha in terms of active ingredient. The total amount of herbicide produced was obtained
starting from the percentage of active ingredient contained in commercial products; this figure is useful for the
purpose of calculating inventories of pesticide production and transport. For glyphosate a content of 40% of active
ingredient weight/weight is considered for the commercial product.
For crops covered by the report, the following approach was used. Eg. apple crop was associated with the cultivation
of fruit trees, oranges to the cultivation of citrus plants, while wheat to the cultivation of cereals. For the rest of the
products for which this type of association was not possible, such as eg. olive oil, data from the specific literature or
from a handbook of agriculture were used (Ribaudo 2011).
Standard distances were used for the transport of materials from their production site to the processing plant or the
farm. This is 500 km by lorry. Ecoinvent transport unit processes were used.
Emissions from application of pesticides
Since there is still no consensus on which model to apply, in order to estimate emissions from the use of pesticides,
and in particular the fate modelling from technosphere to biosphere, the following procedure was used:
• The name of pesticide and the amount active ingredient applied are used to model the environmental fate of
pesticides in the inventory. The environmental fate is assumed to be 100 % to soil. This statement follows the
code of life cycle inventory practice (de Beaufort-Langeveld et al. 2003) which is also applied in the Ecoinvent
background data and in the Agri-footprint database methodology.
Of course the results of this approach represent the worst case scenario.
Animal breeding systems
The analysis of farming systems requires data on animal growth, enteric emissions, feed production. The animal
breeding models taken into account in this study for the various types of products (dairy products, meat from beef,
pork and poultry) are those reported in Blonk Consultants (2014).
In particular, for livestock products the animal enteric fermentation and the type of manure management were
accounted for. The feed production is also taken into account.
The inventories regarding the impacts of livestock are calculated according to the approach indicated by IPCC in chapter
10 Vol.4 (IPCC 2006b).
The main emissions deriving from livestock included in the inventories are the following:
• manure management: the relative emissions are constituted mainly by methane and nitrous oxide deriving from
the aerobic and anaerobic decomposition of the manure and from ammonia;
• enteric fermentation: this includes the emissions of methane produced mainly by ruminant digestive systems and
in minor amount by those of non-ruminant animals.
23
The emissions factors taken from IPCC are specified by category of livestock and regional grouping.
Food losses throughout the supply chain
The loss of matter that takes place in the various life cycles of products has been accounted for. Food losses or waste
are the masses of food lost or wasted in the part of food chains leading to edible products going to human
consumption. Co-products, waste and losses are defined and related to each other in different manners. Co-products
are those useful products obtained together with the main product which have an economic value; waste is the rest
of matter. Co-products leave the system through allocation while waste is sent to the EU27 food waste treatment
scenario. Another distinction is that regarding waste from processes and food loss; food loss is intended as the useful
food that for various reasons is lost within the supply chain and not the physiological waste produced in a process
(according to the definition given in the FAO report used as a main data source). Losses also consist of the food waste
deriving from the inefficiencies of the food chains.
When specific literature data were available, these were used for the calculation of loss in a specific supply chain, as
in the case of apples and oranges. For other cases, the loss data were obtained from the FAO report ‘Global food losses
and food waste – Extent, causes and prevention’ (FAO 2011) which highlights the losses occurring along the entire
food chain, and makes assessments of their magnitude. Data are reported for agricultural production, post-harvest
handling and storage, processing, distribution and consumption.
Data are referred to commodity groups and not to single products. Accordingly, the various basket products were
associated with a reference food commodity group and the loss of the group was then assigned to the single product.
Not all the products can be associated to the groups; in these cases losses are reported only for the life cycle phases
for which data are available.
The end of life of the waste generated from losses was also considered. The end of life scenario of food waste was
evaluated starting from data on the disposal of waste in EU-27. Eurostat contains statistics on the “Treatment of
waste [env_wastrt]” database; the most recent available data is that of 2010. This database details the amount of
waste divided into various types; for the purposes of this study the “Animal and vegetable wastes (subtotal, W091 +
W092 + W093)” waste category was considered, which represents 4% of the total waste. The statistics indicate the
following disposal treatments: 8% of food waste is sent to landfill, 5% is incinerated, and 87% is sent to other recovery
treatments. It is assumed that such a recovery treatment is 80% composting and 20% anaerobic digestion for biogas
production; therefore 69.6% of total waste is set to composting while 17.4% to anaerobic digestion. Food waste coming
from the various supply chains has been assumed to undergo this end of life scenario, with the above mentioned
treatments and percentages.
The assumption made for food losses is that the burden deriving from the treatment of lost matter is attributed the
life cycle phase that generated that loss. E.g. the waste treatment of food matter lost in the distribution stage is
attributed to the distribution phase. Consequently the EU27 waste treatment scenario is applied, including landfill,
incineration, composting and anaerobic digestion.
Industrial processing
Data on individual production units were considered for all products that require industrial processing. As regards
refrigeration, which occurs during processing and storage, the electric energy consumption is assumed 1.8 Wh/L per
day for meat and 1.2 Wh/L per day for fruit and vegetables (EPD 2012). For the various products the number of days
of refrigeration and the specific weight is considered as reported in Annex 9.
Packaging
For all basket products the primary packaging was considered; whenever possible even the secondary packaging was
added to inventories.
The packaging phase also includes the end of life of the packaging itself. Specifically, for the packaging used in the
life cycles an end of life scenario was built. This considers that a part of the packaging is recycled and the rest is
destined to incineration and landfill. The percentage of waste sent to the various treatments are different from
material to material and were taken from the Ecoinvent database.
24
Logistics
Logistics can be divided into international trade, distribution and retail.
International trade. For all products in the basket the international trade was considered with the exception of pre-
prepared meals for which data on imports per country were not available; in particular for imports, the relevant amount
in relation to domestic production and the countries of origin were considered. Those countries that represent the
source of at least 90% of the total EU imports of a specific basket product were considered (Annex 2) for the impact
assessment. Logistics linked to international trade has been assumed with regard to the transport of commodities
from the capital of the exporting country to the city of Frankfurt, which is considered a central destination for the
arrival of imports in Europe. For those countries not connected to Europe by land routes, different means of transport
were considered: a transport by lorry between the capital of the exporting country and the country's main port; a
transport by ship from the port of the exporting country to the main European ports and finally, a transport by lorry
between the port of destination and the city of Frankfurt. Rotterdam and Marseilles were considered as the European
ports of arrival of the goods. The distances between ports in kilometres have been taken from http://www.sea-
distances.org/. For those exporting countries directly connected to Europe by land, such as Switzerland or Belarus, only
a transport by lorry was considered from the capital of the exporting country to the city of Frankfurt. Annex 2 contains
all the above mentioned information relative to EU imports of basket products.
Distribution. It consists of a transport by lorry from the manufacturer/farm to a regional distribution centre and a
further transport by lorry from the regional distribution centre to the retailer. The total distance travelled was assumed
to be 500 km for all products. In the case in which the product required a refrigerated transport, a 20% increase in
fuel consumption was assumed (Lalonde et al. 2013).
Retail. The energy consumption associated to the permanence of the product in retail was considered using data taken
from the LCA Food DK database. For those products that require refrigeration, the consumption of electrical energy
associated with this operation was considered equal to 1.2 Wh/L per day (EPD 2012). For the various products the
number of days of refrigeration and the specific weight is considered as reported in Annex 9.
Use phase
The use phase consists of consumer home transport and domestic consumption.
Home transport consists of a transport by passenger car from the consumer’s home to the retailer and back. The
distance travelled was assumed to be 4 km. As consumer spending covers both food products and non, the allocation
of transport between the various products occurs in this phase; in order to solve allocation it was assumed that the
consumer buys a total of 30 products in each purchase. Therefore 3.33% of transport burden has been allocated to
the purchased product as each product represents one of thirty items purchased (Vanderheyden and Aerts 2014). For
each product of the basket the amount of basket product purchased in a journey has been fixed as reported in Annex
9.
Domestic consumption is associated both to the consumption of electricity for the refrigeration of food and to the
impacts due to the preparation and cooking of food.
As regards refrigeration the electric energy consumption of domestic refrigerator is assumed 2.3 Wh/L per day while
the freezer one is 4.2 Wh/L per day (Nielsen et al. 2003). For the various products the number of days of refrigeration
and the specific weight is considered as reported in Annex 9.
As regards to home preparation the following operations are considered together with the specific energy consumption
(Foster et al. 2006):
• Boiling: 2 MJ of natural gas/kg product
• Frying: 7.5 MJ of natural gas/kg product
• Baking: 0.75 kWh electricity/ kg product
• Roasting: 8.5 MJ of natural gas/kg product
End of life
The end of life includes the following elements:
25
• Food scraps and not consumed foods. This is the part of food which is not edible, such as the peel of the apple or
potato, and the proportion of edible food not consumed and thrown away as waste. For both of these food wastes
the end of life scenario described in the section on food losses throughout the supply chain has been applied for
all the solid products. For liquid products, such as beer and coffee, it was assumed that the non-consumed part
of such drink goes from the user’s home to the unpolluted wastewater treatment.
• Human faeces. For the environmental assessment of human metabolism products, the model by Muñoz et al.
(2007) was used. This model includes processes such as human excretion due to food intake, auxiliary processes
related to toilet use, and treatment of human excretion products present in wastewater through a sewage
treatment plant.
2.3.3 Final selection: overview per product and life cycle stage
This paragraph describes the final selection of basket products, based on the application of the hypotheses,
assumptions and data described in the previous paragraphs.
Table 6 summarises the mapping of the coverage in terms of life cycle stages and inventories (LCI) for a given
representative product. The letter “Y” indicates that a life cycle stage is included in the system. The table highlights
that for all the phases of the life cycle of the representative products the life cycle inventories were included. Some
coverage differences are present as far as processes regarding packaging and the inventory of losses are concerned.
In fact a further specification is given in the case of packaging: with “P” specifies the inclusion of data on primary
packaging, while “S” indicates the inclusion of data on secondary packaging. As regards to packaging, the primary
packaging was included for all the products, while the secondary packaging was included only where data was
available. The same applies to the inventory of losses; by applying the information drawn from the indicated data
sources, for a certain number of products, it is possible to calculate losses regarding the whole life cycle. For other
products losses are limited only to the use or retail phases.
Table 6 Mapping of the coverage in terms of life cycle stages, inventories (LCI) for a given representative
product
Representative product Agricultural
production/
livestock
Industrial
processing
Logistics Packaging Use End of
life
other inventory
data - losses
Coffee Y Y Y Y: P-S Y Y Only for use phase
Beer Y Y Y Y: P Y Y Only for use phase
Mineral water Y Y Y Y: P Y Y Only for use phase
Bread Y Y Y Y: P Y Y Y
Beef Y Y Y Y: P Y Y Y
Pork Y Y Y Y: P Y Y Y
Poultry Y Y Y Y: P Y Y Y
Milk Y Y Y Y: P Y Y Y
Butter Y Y Y Y: P Y Y Y
Cheese Y Y Y Y: P-S Y Y Y
Sugar Y Y Y Y: P Y Y Only for use phase
Sunflower oil Y Y Y Y: P Y Y Y
Olive oil Y Y Y Y: P-S Y Y Only for use phase
Potatoes Y Y Y Y: P Y Y Y for retail and use
Apples Y Y Y Y: P Y Y Y
Oranges Y Y Y Y: P Y Y Y
Pre-prepared meals
based on meat
Y Y Y Y: P-S Y Y Y
Y=included P=primary S=secondary
Particular attention was paid to the application of the previously mentioned fertiliser and pesticide models.
Table 7 shows the chosen data sources and models for the agricultural stage of each product of the basket. Most of
data are taken from the Agri-Footprint database; this choice is due to the fact that the methodology used for the
26
inventory building of this database is perfectly comparable with the model adopted in the present study. Therefore
data from the Agri-Footprint database constitutes the main option.
In any case for the datasets, taken from the various databases, data regarding pesticide consumption are replaced,
whenever possible, by those taken from the EU report on pesticide application in Europe, already cited in the paragraph
on pesticide application rates. In order to guarantee the coherence between the various models and data sources, the
pesticide modelling is made by assuming a 100% to soil emission of active ingredients.
Table 7 Application of assumptions to agriculture
Basket products Data sources Fertiliser modelling Pesticide data source Pesticide modelling
apples Milà i Canals et al. 2006
according to the
assumptions EU report 100% soil
barley (beer) Agri-Footprint Agri-Footprint EU report 100% soil
wheat (bread) Agri-Footprint Agri-Footprint EU report 100% soil
coffee Coltro et al. 2006
according to the
assumptions from cited literature 100% soil
olive Notarnicola et al. 2013
according to the
assumptions from cited literature 100% soil
oranges Beccali et al. 2013
according to the
assumptions EU report 100% soil
potatoes Agri-Footprint Agri-Footprint EU report 100% soil
sugar beet Agri-Footprint Agri-Footprint EU report 100% soil
sunflower seed Agri-Footprint Agri-Footprint EU report 100% soil
tomato (pre-prepared) Ecoinvent
according to the
assumptions Ecoinvent 100% soil
onion (pre-prepared) Ecoinvent
according to the
assumptions Ecoinvent 100% soil
sunflower seed (pre-prepared) Agri-Footprint Agri-Footprint EU report 100% soil
carrot (pre-prepared) Ecoinvent
according to the
assumptions Ecoinvent 100% soil
pea (pre-prepared) Agri-Footprint Agri-Footprint Agri-Footprint 100% soil
raw milk (milk, cheese, butter) Agri-Footprint - - -
meat - bovine Agri-Footprint - - -
meat - pork Agri-Footprint - - -
meat - poultry Agri-Footprint - - -
mineral water Vanderheyden et al. 2014 - - -
Another calculation was needed for the estimate of the impact of international transport of imported goods on the
environmental profile of the basket. Starting from the country specific import data for the basket products, taken from
Eurostat international trade database for the year 2010, and the import countries distances and modes of transport
reported in Annex 2, the total loads and distances travelled by different means have been calculated. The reference
data are reported in Table 8. It can be noted that in some cases the value of ship transport per kg of product is
particularly relevant, as in the case of butter and apples. No data were found for pre-prepared foods. The share of
production and imports with respect to the total available quantity of commodities are illustrated in
Table 9. The percentage of imports is very low for all products with the exception of green coffee, which is entirely
produced abroad, and oranges which have 10% share of imports.
A comprehensive list of assumptions organized by life cycle stages is given in Annex 9.
27
Table 8 Means of transport and loads relative to imported goods
ship (tkm) truck (tkm) imports (kg) ship (tkm/kg
import)
truck (tkm/kg
import)
mineral water 18,031,681 124,693,351 96,597,737 0.19 1.29
beer 1,938,981,261 269,688,942 265,354,674 7.31 1.02
green coffee 17,158,134,456 3,459,870,070 2,205,468,800 7.78 1.57
roasted coffee 12,609,886 15,473,615 31,609,600 0.40 0.49
apples 7,646,368,614 544,470,475 616,581,500 12.40 0.88
oranges 8,307,724,111 869,669,869 948,171,200 8.76 0.92
potatoes 1,071,555,040 438,422,583 420,384,900 2.55 1.04
wheat 14,126,149,508 1,845,344,063 6,456,483,100 2.19 0.29
olive oil 80,126,094 74,853,682 86,043,700 0.93 0.87
sunflwer oil 181,493,602 88,412,207 109,589,200 1.66 0.81
sugar 314,113,151 71,043,903 737,408,600 0.43 0.10
milk 2,997,535 4,985,637 8,476,300 0.35 0.59
cheese 477,731,456 14,989,849 78,528,600 6.08 0.19
butter 692,633,736 23,241,482 37,944,900 18.25 0.61
beef 2,008,377,310 193,609,452 203,426,500 9.87 0.95
pork 185,249,920 11,517,852 25,461,200 7.28 0.45
poultry 1,224,537,275 345,091,413 166,822,800 7.34 2.07
pre-prepared - - - - -
Table 9 Share of production and imports in the total available quantity of goods
Total (EU 27
aggregated value)
production (kg)
Total (EU 27
aggregated value)
imports (kg)
total production +
imports (kg)
% EU27
production
% imports
mineral water 54,000,000,000 96,597,737 54,096,597,737 99.8 0.2
beer 37,200,000,000 265,354,674 37,465,354,674 99.3 0.7
green coffee - 2,205,468,800 2,205,468,800 0.0 100.0
roasted coffee 1,793,803,908 31,609,600 1,825,413,508 98.3 1.7
apples 8,676,325,000 616,581,500 9,292,906,500 93.4 6.6
oranges 8,016,200,000 948,171,200 8,964,371,200 89.4 10.6
potato 56,129,700,000 420,384,900 56,550,084,900 99.3 0.7
wheat 145,674,000,000 6,456,483,100 152,130,000,000 95.8 4.2
olive oil 3,107,520,779 86,043,700 3,193,564,479 97.3 2.7
sunflwer oil 2,709,820,346 109,589,200 2,819,409,546 96.1 3.9
sugar 16,271,354,553 737,408,600 17,008,763,153 95.7 4.3
milk 40,246,421,375 8,476,300 40,254,897,675 100.0 0.0
cheese 8,124,999,714 78,528,600 8,203,528,314 99.0 1.0
butter 1,936,152,644 37,944,900 1,974,097,544 98.1 1.9
beef 6,922,017,037 203,426,500 7,125,443,537 97.1 2.9
pork 22,202,347,353 25,461,200 22,227,808,553 99.9 0.1
poultry 12,455,944,110 166,822,800 12,622,766,910 98.7 1.3
pre-prepared - - - - -
28
2.4 Results of the environmental impact of the selected products for one
EU citizen
The results of the LCA of the basket-of-products concerning food and beverage, described in the following pages, are
organised in the following manner:
1. Results per product
2. Results per life cycle stage
3. Overall results of the environmental impact assessment of basket products per EU citizen.
2.4.1 Result per product
The full impact assessment results of the 17 different basket products, for an EU citizen during the 2010 reference
year, is reported in Table 10. In Table 11, the same figure in percentage units is shown; moreover in this table a colour-
based approach has been used to rank the significance of the impact:
• white, not relevant: contribution ≤ 5% of the impact category;
• yellow, slightly relevant: contribution between 6% and 10% of the impact category;
• green, relevant: contribution between 11% and 15% of the impact category;
• brown, significantly relevant: contribution between 16% and 20% of the impact category;
• red, dominant: contribution ≥ 21% of the impact category.
The tables indicate that some of the highest contributions (hot spots) are related to beef and pork meat. Specifically
these two products contribute the most to eleven of the sixteen impact categories. In particular beef has:
• four dominant impacts, on Terrestrial eutrophication (26%) and on Acidification (25%), Climate change and
Particulate matter (both 21%)
• four significantly relevant impacts, Marine Eutrophication (20%), Land Use (20%), Human toxicity cancer effect
(18%), Human toxicity non cancer effect (17%)
Pork has:
• five dominant impacts, on Terrestrial eutrophication (24%) and on Acidification (23%), Marine Eutrophication
(22%), Land use (22%), Human toxicity non cancer effect (21%)
• five significantly relevant impacts, Feshwater ecotoxicity (20%), Feshwater eutrophication (20%), Particulate
matter (19%), Human toxicity cancer effect (18%), Climate change (18%).
The impact categories of Terrestrial eutrophication, Acidification and Marine eutrophication in the beef life cycle are
respectively due to:
• the emissions of ammonia (96%) and nitrogen oxides (3%) which occur during the livestock breeding and
agricultural phases for the production of fodder;
• the emissions of ammonia (95%), nitrogen oxides (2%) and sulphur dioxide (2%) which occur during the livestock
breeding and agricultural phases for the production of fodder;
• the emissions of nitrates in water (78%), ammonia in air (9%), nitrogen in water (9%), nitrogen oxides in air (4%),
which occur during the agricultural operations for pasture and waste water treatment.
Climate change of the beef life cycle is due to methane (52%), di-nitrogen monoxide (20%) and carbon dioxide (26%)
emissions occurring during livestock breeding, manure management, and forage production processes together with
the energy from diesel use and farming operations.
With regards to pork meat consumption, the contributions to the Freshwater eutrophication impact category, is due to
the emissions of phosphates which occur during the domestic wastewater treatment and during the feed production.
Moreover the relevant contributions to the impact categories of Human toxicity non cancer effects (21%) are due to
emissions of zinc to soil (95%) (and other heavy metal such as lead and cadmium) which occur during animal feed
production. The relevant contributions to the impact categories of Feshwater ecotoxicity are due to emissions of
pesticides (50%), zinc to soil (25%) and copper to soil (16%) occurring during feed production.
29
It must be stressed that in this basket the consumption of beef meat is about one third of that of pork. Consequently,
if the comparison were carried out on an equal weight basis, the respective contributions of the two meats would be
completely different.
Beer is characterised by one dominant impact: Mineral fossil & resource depletion (22% contribution) and one
significantly relevant Ozone depletion (18% contribution), due to emissions of Halon and CFC which occur during the
electricity production. Other relevant impacts in the life cycle of beer regard the Ionizing radiation due to the emissions
of Carbon-14 (76%), Cesium-137 (13%), Radon-222 (4%) occurring in the electricity production.
Coffee and bread contribute to over 25% (12 and 13% respectively) of the overall Ionizing radiation impact of the
entire basket due to the emissions occurring during the electricity production.
Cheese has three significantly relevant contributions to three impact categories: Water resource depletion (20%),
Freshwater eutrophication (17%) and Human toxicity non cancer (17%). Cheese has also a relevant contribution to ten
impact categories. In particular Freshwater eutrophication, related to cheese, is due to the emissions of phosphates to
water (99%) and phosphate (1%) and phosphorous to soil which occur in the domestic wastewater depuration, whilst
Human toxicity non cancer indicator is due mainly to heavy metals, in particular zinc to soil, mercury to soil and lead
to soil due agricultural operations regarding crop and grazing grass cultivation.
Milk and poultry are characterised by slightly relevant impacts in almost all impact categories, while potato by a
relevant impact in the Mineral fossil & renewable resource depletion, due to the processes of aluminium production
for packaging (39%), production of pesticides (29%) and production of fertilizers (10%).
The other foods of the basket – mineral water, apple, orange, olive and sunflower oil, sugar, butter, pre-prepared meal
are characterised by slight and not relevant impacts. In particular, pre-prepared meals perform very well in all the
impact categories due essentially to the very small quantities present in the basket of the European citizen, 2.9
kg/citizen per year (0.5% of the per-capita apparent basket consumption).
30
Table 10 Life cycle impact assessment for an average citizen of EU-27 in the nutrition basket-of-products shared for the seventeen representative food
products of the basket
Impact Category
Uni
t
min
eral w
ate
r
beer
66
cL
coff
ee
app
le
orang
e
pota
to
bre
ad
oliv
e oi
l
sunf
low
er o
il
sugar
milk
chee
se
butt
er
mea
t -
beef
mea
t -
pork
mea
t -
poult
ry
pre-
prep
are
d m
eal
Tota
l
Climate change kg CO2 eq. 28.6 80.1 39.6 8.3 11.8 45.8 44.1 13.3 39.0 30.6 112.8 192.6 86.6 313.4 274.1 144.9 18.0 1483.6
Ozone depletion kg CFC-11 eq. 3.85E-06 1.08E-05 5.37E-06 1.08E-06 1.23E-06 6.15E-06 6.21E-06 1.54E-06 1.33E-06 1.40E-06 4.61E-06 6.87E-06 9.88E-07 8.12E-07 3.86E-06 2.14E-06 1.63E-06 5.99E-05
Human toxicity, cancer effects CTUh 3.17E-07 1.09E-06 1.42E-07 6.15E-08 1.04E-07 7.57E-07 5.16E-07 1.15E-07 2.01E-06 6.53E-07 1.56E-06 2.42E-06 1.30E-06 3.48E-06 3.48E-06 1.65E-06 1.68E-07 1.98E-05
Human toxicity, non-cancer effects CTUh 2.27E-06 6.67E-05 1.86E-06 4.22E-07 7.45E-07 5.59E-05 7.21E-05 1.98E-06 7.72E-05 7.40E-05 2.00E-04 3.51E-04 2.01E-04 3.39E-04 4.35E-04 1.60E-04 1.26E-05 2.05E-03
Particulate matter kg PM2.5 eq. 1.57E-02 6.97E-02 2.31E-02 3.79E-03 6.10E-03 2.09E-02 2.52E-02 1.16E-02 2.02E-02 2.67E-02 6.04E-02 9.53E-02 4.73E-02 1.83E-01 1.62E-01 7.35E-02 9.57E-03 8.54E-01
Ionizing radiation HH kBq U235 eq. 2.90 6.09 5.97 1.00 1.03 4.93 6.38 1.17 0.38 0.54 3.82 5.75 0.92 0.60 3.66 2.00 1.71 48.9
Ionizing radiation E (interim) CTUe 2.76E-05 5.72E-05 5.86E-05 9.67E-06 9.77E-06 4.78E-05 6.25E-05 1.11E-05 3.49E-06 4.90E-06 3.67E-05 5.25E-05 8.84E-06 5.72E-06 3.55E-05 1.94E-05 1.64E-05 4.68E-04
Photochemical ozone formation kg NMVOC eq. 0.138 0.316 0.111 0.032 0.043 0.134 0.134 0.062 0.101 0.082 0.221 0.278 0.102 0.407 0.415 0.196 0.040 2.81
Acidification molc H+ eq. 0.18 0.88 0.52 0.07 0.13 0.48 0.67 0.15 0.70 1.00 2.16 3.66 2.00 7.45 6.68 2.68 0.21 29.63
Terrestrial eutrophication molc N eq 0.4647 2.6224 1.4415 0.1899 0.4650 1.5736 2.3598 0.4576 2.8428 4.4037 9.2335 15.7245 8.8413 32.8887 29.5298 11.8197 0.7047 125.56
Freshwater eutrophication kg P eq. 1.22E-03 2.81E-02 2.92E-03 2.43E-04 3.67E-03 2.67E-02 2.35E-02 1.73E-03 1.99E-02 6.83E-03 7.13E-02 7.24E-02 1.20E-02 5.58E-02 8.89E-02 1.76E-02 1.87E-03 4.35E-01
Marine eutrophication kg N eq. 0.048 0.326 0.240 0.030 0.081 0.356 0.566 0.066 0.386 0.491 0.948 1.553 0.627 2.375 2.625 1.098 0.080 11.90
Freshwater ecotoxicity CTUe 16.6 436.6 398.7 48.9 94.7 82.0 72.5 25.8 239.9 73.9 290.7 488.4 273.6 552.6 860.4 376.9 49.9 4382.2
Land use kg C deficit 70.0 398.4 281.1 64.5 98.8 223.5 337.1 476.6 1390.9 301.5 818.8 1373.5 766.8 2864.0 3233.5 1718.9 123.0 14540.9
Water resource depletion m3 water eq. 3.33 1.33 1.35 1.77 4.07 3.13 1.06 1.44 1.70 2.47 3.29 8.73 0.65 5.53 1.71 1.05 1.03 43.63
Mineral, fossil & ren resource
depletion kg Sb eq. 8.56E-04 3.50E-03 1.01E-03 1.58E-04 3.83E-04 1.98E-03 3.84E-04 6.98E-04 8.20E-04 3.92E-04 1.23E-03 9.74E-04 8.51E-04 8.11E-04 1.11E-03 6.09E-04 1.84E-04 1.59E-02
31
Table 11 Life cycle impact assessment for an average citizen of EU-27 in the nutrition basket-of-products shared for the seventeen representative food
products of the basket (in percentage unit)
Impact Category
Unit
min
eral w
ate
r
bee
r 6
6 c
L
coff
ee
app
le
ora
nge
pota
to
bre
ad
oliv
e oi
l
sunfl
ow
er o
il
sugar
milk
chee
se
butt
er
mea
t -
bee
f
mea
t -
pork
mea
t -
poult
ry
pre-
prep
are
d m
eal
Climate change % 2 5 3 1 1 3 3 1 3 2 8 13 6 21 18 10 1
Ozone depletion % 6 18 9 2 2 10 10 3 2 2 8 11 2 1 6 4 3
Human toxicity, cancer effects % 2 5 1 0 1 4 3 1 10 3 8 12 7 18 18 8 1
Human toxicity, non-cancer effects % 0 3 0 0 0 3 4 0 4 4 10 17 10 17 21 8 1
Particulate matter % 2 8 3 0 1 2 3 1 2 3 7 11 6 21 19 9 1
Ionizing radiation HH % 6 12 12 2 2 10 13 2 1 1 8 12 2 1 7 4 3
Ionizing radiation E (interim) % 6 12 13 2 2 10 13 2 1 1 8 11 2 1 8 4 4
Photochemical ozone formation % 5 11 4 1 2 5 5 2 4 3 8 10 4 14 15 7 1
Acidification % 1 3 2 0 0 2 2 1 2 3 7 12 7 25 23 9 1
Terrestrial eutrophication % 0 2 1 0 0 1 2 0 2 4 7 13 7 26 24 9 1
Freshwater eutrophication % 0 6 1 0 1 6 5 0 5 2 16 17 3 13 20 4 0
Marine eutrophication % 0 3 2 0 1 3 5 1 3 4 8 13 5 20 22 9 1
Freshwater ecotoxicity % 0 10 9 1 2 2 2 1 5 2 7 11 6 13 20 9 1
Land use % 0 3 2 0 1 2 2 3 10 2 6 9 5 20 22 12 1
Water resource depletion % 8 3 3 4 9 7 2 3 4 6 8 20 1 13 4 2 2
Mineral, fossil & ren resource depletion % 5 22 6 1 2 12 2 4 5 2 8 6 5 5 7 4 1
dominant - very relevant impact: x ≥ 21% of the impact of the impact category
significantly relevant: 16% ≤ x ≤ 20% of the impact of the impact category
relevant: 11% ≤ x ≤ 15% of the impact of the impact category
slightly relevant: 6% ≤ x ≤ 10% of the impact of the impact category
not relevant: x ≤ 5 of the impact of the impact category
32
In the following figures (Figures 3 to 12) the contributions of the seventeen foods to some selected
impact categories, representative of the environmental profile of the basket, will be illustrated. The
categories have been selected on the basis of the classifications that will be described in paragraph
2.4.2. For the sake of brevity, the impact categories which perform very similar to others have been
excluded and reported in Annex 10. The categories which will be described in the next section are the
following: Climate change, Acidification, Freshwater ecotoxicity, Photochemical ozone formation, Water
resource depletion, Ozone depletion, Mineral fossil and renewable resource depletion, Freshwater
eutrophication.
Climate change
Climate change, which is usually dominated by the use of fossil fuels, in the case of foods is due mainly
to the methane emissions from the enteric fermentation and to the emissions of dinitrogen monoxide
as a consequence of the use of nitrogen fertilizers for forage production (agricultural and livestock
stages). Consequently, it is not surprising that Figure 3 identifies beef (21%), pork (18%) and cheese
(13%) as the basket products contributing the most to climate change. Agriculture results as the most
contributing stage to this category (71%). The most contributing substances to climate change are
carbon dioxide (56%), biogenic methane (27%), dinitrogen monoxide (16%) occurring mainly in the beef
and dairy cattle rearing (21%), animal feed production (14%), electricity production (11%) and diesel use
for machinery (4%).
As regards to the subdivision of this impact among the single lifecycle phases of each basket product:
the agriculture/zoo-technical stage is particularly significant for butter, beef, pork, poultry (respectively
96%, 95%, 84%, 84% of their climate change indicator); industrial processing is particularly significant
for bread (51% of its indicator).
Figure 3 Climate change for one EU-27 citizen due to the consumption of food products
Acidification
The Acidification impact category is also dominated by the agriculture stage (91%). The basket foods
which contribute the most to this indicator are beef (25%), pork (23%) and cheese (12%) (Figure 4).
Ammonia (88%), sulphur dioxide (7%) and nitrogen oxide (4%) emissions, which occur during animal
rearing and agricultural phases, namely grazing grass, manure management and feed production and
during electricity production, are the most significant emissions of the basket of foods to this impact
category.
0
50
100
150
200
250
300
350
min
eral
wat
er
bee
r 6
6 c
L
coff
ee
app
le
ora
nge
po
tato
bre
ad
oliv
e o
il
sun
flo
we
r o
il
suga
r
milk
ch
eese
bu
tte
r
mea
t -
bee
f
mea
t -
po
rk
mea
t -
po
ult
ry
pre
-pre
par
ed m
eal
kg C
O2
eq
.
EoL
Use
Packaging
Logistics
Industrial processing
Agriculture
33
Figure 4 Acidification for one EU-27 citizen due to the consumption of food products
Freshwater ecotoxicity
As illustrated in Figure 5, the most burdening basket foods to this impact category are pork (20%), beef
(13%), cheese (11%), coffee (10%) and beer (9%). The agricultural stage has an 87% share of the total
basket impact. The most significant emissions of the whole basket to this indicator are those to soil, in
particular copper (29%) and zinc (22%) and chlorpyriphos (19%) and those to water in terms of zinc
(4%) and chromium (2%) occurring during the agricultural activities.
As regards to the subdivision of this impact among the single lifecycle phases of each basket product:
the end-of-life stage is particularly significant for beer (80% of its respective freshwater ecotoxicity
indicator); the agriculture stage is relevant for butter, beef and pork (respectively 99%, 98% and 97%
of their respective indicator).
Figure 5 Freshwater ecotoxicity for one EU-27 citizen due to the consumption of food
products
Photochemical ozone formation
The agricultural stage contributes for 49% to this impact category, followed by 17% of the logistics and
13% of the industrial processing phases. The foods contributing the most to this impact category are
pork, beef and beer, respectively with 15%, 14% and 11% (Figure 6). The most significant emissions of
the basket foods to this indicator are those in atmosphere, namely nitrogen oxides (60%), nitrogen
dioxide (15%), NMVOC (9%), methane (6%), sulphur dioxide (4%), which occur during the production of
012345678
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eral
wat
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EoL
Use
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Industrial processing
Agriculture
0100200300400500600700800900
1000
min
eral
wat
er
bee
r 6
6 c
L
coff
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app
le
ora
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po
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pre
-pre
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eal
CTU
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Use
Packaging
Logistics
Industrialprocessing
34
heat, steam and electricity and during transport by lorry and truck, transport by sea ship and packaging
of glass.
As regards to the subdivision of this impact among the single lifecycle phases of each basket product:
the agriculture phase is particularly significant for beef and pork (90% and 72% of their respective
POCP indicator); the packaging stage is significant for beer (51% of its respective indicator) whilst the
logistics phase is relevant for mineral water and apples (respectively 54% and 46% of their indicator).
Also the use phase is significant for coffee and potato (37% and 22% of their indicator) due to boiling
of coffee and boiling, baking and frying of potatoes.
Figure 6 Photochemical ozone formation for one EU-27 citizen due to the consumption of food
products
Water resource depletion
The agricultural stage contributes the most to this impact category with a share of 41%, followed by the
industrial processing with a share of 31%. The most significant contributions to the entire indicator are
those of cheese (20%), beef (13%) and orange (9%) (Figure 7). The water consumption occurs especially
during the energy production; this energy is used in the process of bio-waste composting, during the
transport and in the packaging production phases.
As regards to the subdivision of this impact among the single lifecycle phases of each basket product:
the agriculture/zoo-technical phase is particularly significant for beef (93% of its respective water
depletion indicator); the industrial stage is relevant for cheese (76 % of its respective indicator).
Figure 7 Water resource depletion for one EU-27 citizen due to the consumption of food
products
00.05
0.10.15
0.20.25
0.30.35
0.40.45
min
eral
wat
er
bee
r 6
6 c
L
coff
ee
app
le
ora
nge
po
tato
bre
ad
oliv
e o
il
sun
flo
we
r o
il
suga
r
milk
ch
eese
bu
tte
r
mea
t -
bee
f
mea
t -
po
rk
mea
t -
po
ult
ry
pre
-pre
par
ed m
eal
kg N
MV
OC
eq
EoL
Use
Packaging
Logistics
Industrial processing
Agriculture
-2
0
2
4
6
8
10
min
eral
wat
er
bee
r 6
6 c
L
coff
ee
app
le
ora
nge
po
tato
bre
ad
oliv
e o
il
sun
flo
we
r o
il
suga
r
milk
ch
eese
bu
tte
r
mea
t -
bee
f
mea
t -
po
rk
mea
t -
po
ult
ry
pre
-pre
par
ed m
eal
m3
wat
er
eq
.
EoL
Use
Packaging
Logistics
Industrial processing
Agriculture
35
Ozone depletion
The impact category of ozone depletion (together with those of Ionizing radiation human health and
Ionizing radiation ecosystems) is dominated by the impacts of electricity production. Consequently, it is
not a surprising result if meat (beef, pork and poultry) score much better than other products in these
impact categories; in fact, the electricity consumption during the life cycle of beef is less of that, for
instance of beer, due to smaller quantities of final food in the basket (consumption of beef, in terms of
mass, is approximately one sixth of that of beer) or lack of glass packaging for the beef. Figure 8
indicates that the foods contributing the most to the ozone depletion of the basket are beer (18%),
cheese (11%), potato and bread (both 10%). The most contributing substances to ozone depletion in the
entire basket are Halon 1301, CFC-114 and CFC-11 emitted to air during electricity production.
As regards to the subdivision of this impact among the single lifecycle phases of each basket product:
the industrial processing phase is particularly significant for bread and cheese (respectively 79% and
77% of the respective ODP indicator) due to the electricity consumption; the use stage for coffee and
potato (respectively 79% and 36%) due respectively to boiling and baking and the industrial processing,
and the packaging stages for beer (35% and 38%).
Figure 8 Ozone depletion for one EU-27 citizen due to the consumption of food products
Mineral, fossil &renewable resource depletion
The packaging stage contributes the most to this impact category with a share of 45%, followed by the
agriculture stage with a share of 32%. Figure 9 highlights that the most contributing basket foods for
this impact category are beer (22%), potato (12%) and milk (8%). Their impact is due to the depletion of
indium (52%), phosphorous (24%), cadmium (6%), and lead (3%); indium is used in the life cycle of
secondary aluminium whilst phosphorous is used for the manufacture of phosphatic fertilisers.
0
0.000002
0.000004
0.000006
0.000008
0.00001
0.000012
min
eral
wat
er
bee
r 6
6 c
L
coff
ee
app
le
ora
nge
po
tato
bre
ad
oliv
e o
il
sun
flo
we
r o
il
suga
r
milk
ch
eese
bu
tte
r
mea
t -
bee
f
mea
t -
po
rk
mea
t -
po
ult
ry
pre
-pre
par
ed m
eal
kg C
FC 1
1 e
q.
EoL
Use
Packaging
Logistics
Industrial processing
Agriculture
36
Figure 9 Mineral, fossil &renewable resource depletion for one EU-27 citizen due to the
consumption of food products
Freshwater eutrophication
The contribution to this impact category is mainly due by the end-of-life stage of the basket products
(54%), followed by the agricultural stage (43%). The most significant contributions to the entire indicator
are due to the consumption of pork (20%), cheese (17%) and milk (16%). The most contributing
substances to this impact category are the emissions of phosphorous and phosphates to water and soil
occurring during the domestic wastewater depuration. Such wastewater treatment is attributable to milk
(13%), cheese (12%), pork (12%) and potato (5%) (Figure 10).
Figure 10 Freshwater eutrophication for one EU-27 citizen due to the consumption of food
products
2.4.2 Results per life cycle stage
Figure 11 shows the contribution analysis of the six life cycle stages of the entire basket to every impact
category. The sixteen indicators have been grouped in the following way:
0
0.0005
0.001
0.0015
0.002
0.0025
0.003
0.0035
0.004
min
eral
wat
er
bee
r 6
6 c
L
coff
ee
app
le
ora
nge
po
tato
bre
ad
oliv
e o
il
sun
flo
we
r o
il
suga
r
milk
ch
eese
bu
tte
r
mea
t -
bee
f
mea
t -
po
rk
mea
t -
po
ult
ry
kg S
b e
q EoL
Use
Packaging
Logistics
Industrial processing
Agriculture
00.010.020.030.040.050.060.070.080.09
0.1
min
eral
wat
er
bee
r 6
6 c
L
coff
ee
app
le
ora
nge
po
tato
bre
ad
oliv
e o
il
sun
flo
we
r o
il
suga
r
milk
ch
eese
bu
tte
r
mea
t -
bee
f
mea
t -
po
rk
mea
t -
po
ult
ry
pre
-pre
par
ed m
eal
kg P
eq
.
EoL
Use
Packaging
Logistics
Industrial processing
Agriculture
37
Indicators greatly dominated by the agricultural stage - nine impact categories: Climate change with a
share of 71% (contribution of the agricultural stage to the respective indicator), Human toxicity, cancer
effect 84%, Human toxicity non-cancer effect 99%, Particulate matter 77%, Acidification 91%,
Terrestrial eutrophication 95%, Marine eutrophication 72%, Freshwater ecotoxicity 87%, Land use 95%;
Indicators characterised by the major contribution of the agricultural stage - two impact categories:
Photochemical ozone formation with a share of 49%, (contribution of the agricultural stage to the
respective indicator), Water resource depletion 41%, followed by the contributions of the other stages;
Indicators characterised by the major contribution of the industrial processing stage - three impact
categories: Ionizing radiation human health with a share of 37%, (contribution of the industrial
processing stage to the respective indicator), Ionizing radiation ecosystems 37%, Ozone depletion 34%,
followed by the contributions of the other stages;
Indicators characterised by a major contribution of the packaging stage followed by relevant contribution
of the agricultural stage: Mineral, fossil and renewable resource depletion with a share of 45%
(contribution of the packaging stage to the respective indicator);
Indicator characterised by a major contribution of the end-of-life stage, followed by a relevant
contribution of the agricultural stage: Freshwater eutrophication with a share of 54% (contribution of
the end-of-life stage to the respective indicator).
Group I
38
Group II
Group III
Group IV Group V
Figure 11 Mineral, fossil & renewable resource depletion for one EU-27 citizen due to the
consumption of basket food products
2.4.3 Overall results of the environmental impact assessment of basket
products per EU citizen
The aggregated impact assessment for a EU citizen, in the 2010 reference year, of the nutrition basket-
of-product per life cycle macro stages, is reported in Table 12. Table 13 depicts the same data in terms
of percentages. As in the previous paragraph in this table a colour-based approach has been used to
rank the significance of the impact:
white, not relevant: contribution ≤ 10% of the impact category;
yellow, slightly relevant: contribution between11% and 30% of the impact category;
green, relevant: contribution between 31% and 50% of the impact category;
brown, significantly relevant: contribution between 51% and 70% of the impact category;
red, dominant: contribution ≥ 71% of the impact category.
39
Table 12 Life cycle impact assessment for an average citizen of EU-27 in the food basket-
of-products
Impact Category
Unit
Agri
cult
ure
Indust
rial pr
oc.
Logis
tics
Pack
agin
g
Use
EoL
Tota
l
Climate change kg CO2 eq. 1059.6 154.8 64.5 74.0 81.4 49.3 1483.6
Ozone depletion kg CFC-11 eq. 9.05E-06 2.01E-05 1.02E-05 7.51E-06 9.02E-06 3.99E-06 5.99E-05
Human toxicity, cancer effects CTUh 1.66E-05 5.34E-07 7.99E-07 1.03E-06 3.84E-07 4.74E-07 1.98E-05
Human toxicity, non-cancer effects CTUh 2.02E-03 8.51E-06 4.73E-06 7.38E-06 1.92E-06 5.06E-06 2.05E-03
Particulate matter kg PM2.5 eq. 6.59E-01 4.88E-02 2.52E-02 7.29E-02 2.06E-02 2.74E-02 8.54E-01
Ionizing radiation HH kBq U235 eq. 8.4 18.2 3.3 4.9 9.8 4.2 48.9
Ionizing radiation E (interim) CTUe 8.25E-05 1.74E-04 3.02E-05 4.53E-05 9.53E-05 4.00E-05 4.68E-04
Photochemical ozone formation kg NMVOC eq. 1.37 0.37 0.49 0.29 0.15 0.15 2.81
Acidification molc H+ eq. 27.09 0.82 0.45 0.55 0.34 0.38 29.63
Terrestrial eutrophication molc N eq 119.77 1.33 1.81 0.96 0.44 1.26 125.56
Freshwater eutrophication kg P eq. 1.85E-01 1.09E-02 9.60E-04 2.86E-03 4.43E-04 2.35E-01 4.35E-01
Marine eutrophication kg N eq. 8.61 0.15 0.17 0.11 0.04 2.81 11.90
Freshwater ecotoxicity CTUe 3834.4 41.1 35.5 46.8 7.8 416.5 4382.2
Land use kg C deficit 13861.4 93.5 158.4 203.1 37.1 187.4 14540.9
Water resource depletion m3 water eq. 17.80 13.42 1.20 5.63 0.06 5.51 43.63
Mineral, fossil & ren resource depletion kg Sb eq. 5.13E-03 9.32E-04 1.72E-03 7.17E-03 4.81E-04 5.07E-04 1.59E-02
Table 13 Life cycle impact assessment for an average citizen of EU-27 in the nutrition basket-
of-products (in percentage unit)
Impact Category Unit Agriculture Industrial
processing Logistics Packaging Use EoL
Climate change % 71 10 4 5 5 3
Ozone depletion % 15 34 17 13 15 7
Human toxicity, cancer effects % 84 3 4 5 2 2
Human toxicity, non-cancer effects % 99 0 0 0 0 0
Particulate matter % 77 6 3 9 2 3
Ionizing radiation HH % 17 37 7 10 20 9
Ionizing radiation E (interim) % 18 37 6 10 20 9
Photochemical ozone formation % 49 13 17 10 5 5
Acidification % 91 3 2 2 1 1
Terrestrial eutrophication % 95 1 1 1 0 1
Freshwater eutrophication % 43 3 0 1 0 54
Marine eutrophication % 72 1 1 1 0 24
Freshwater ecotoxicity % 87 1 1 1 0 10
Land use % 95 1 1 1 0 1
Water resource depletion % 41 31 3 13 0 13
Mineral, fossil & ren resource
depletion % 32 6 11 45 3 3
40
Legend
dominant - very relevant impact: x ≥ 71% of the impact of the impact category
relevant impact: 51% ≤ x ≤ 70% of the impact of the impact category
medium relevant: 31% ≤ x ≤ 50% of the impact of the impact category
slightly relevant: 11% ≤ x ≤ 30% of the impact of the impact category
not relevant: x ≤ 10% of the impact of the impact category
The results presented so far have excluded the effects of long term emissions. If the long term emissions
in the LCIA were to be considered, the contributions to seven impact categories would be increased from
0.03% to 109%, as reported in Table 14.
Table 14 Life cycle impact assessment of the nutrition basket-of-products per EU-27 citizen:
the effect of taking into consideration of the long term emissions
Impact categories without long term
emissions
with long term
emissions
%
increase
Climate change kg CO2 eq 1,483.6 1,483.6
Ozone depletion kg CFC-11 eq 5.99E-05 5.99E-05
Human toxicity, cancer effects CTUh 1.98E-05 2.93E-05 48%
Human toxicity, non-cancer effects CTUh 2.05E-03 2.12E-03 3%
Particulate matter kg PM2.5 eq 0.854264 0.854507 0.03%
Ionizing radiation HH kBq U235 eq 48.87 62.15 27%
Ionizing radiation E (interim) CTUe 4.68E-04 4.68E-04
Photochemical ozone formation kg NMVOC eq 2.81 2.81
Acidification molc H+ eq 29.6 29.6
Terrestrial eutrophication molc N eq 125.6 125.6
Freshwater eutrophication kg P eq 4.35E-01 4.71E-01 8%
Marine eutrophication kg N eq 11.90 11.92 0.17%
Freshwater ecotoxicity CTUe 4382.2 9168.1 109%
Land use kg C deficit 14540.9 14540.9
Water resource depletion m3 water eq 43.63 43.63
Mineral, fossil & ren resource depletion kg Sb eq 0.016 0.016
2.5 Interpretation of the results
The LCA of the food basket-of-products indicates that in the majority of the impact categories the most
burdening foods are:
• Meat products: beef, pork and poultry.
• Dairy products: cheese, milk and butter.
This result is the effect of two factors: the magnitude of the unit impact of the food and the quantity of
its relative consumption at European level. Beef meat, for instance, results as the most burdening food
of the meat products since, although its annual consumption is the lowest among the meat products
(13.7 kg/citizen per year) it has the highest unit environmental impact.
On the other hand pork meat, whose impact in the basket is as high as beef, presents a lower
environmental burden compared to beef, which is counterbalanced by a higher per-capita consumption
(41 kg/citizen per year). The same can be stated for dairy products, for instance milk, where the relatively
low unit environmental burden is counterbalanced by its per-capita consumption of 80.1 kg/citizen per
41
year. Fruit contributes the least to the overall result since its relatively low impact is coupled with light
packaging, fresh consumption and the lack of domestic processing or cooking.
All other foods fall between these two profiles, since for each of these there is a either a particular
process or material leading to a relevant particular impact, as for instance the packaging, or the domestic
operations (cooking, refrigeration, baking, frying etc.).
As far as the analysis of the impact categories and the life cycle phases is concerned, the sixteen
indicators have been divided in five groups, on the basis of the relevance of the agricultural stage (Group
I, Group II of Figure 11), of the major contribution of the industrial processing stage, of the major
contribution of the packaging stage (Group IV) and of the major contribution of the end-of-life stage.
The first group is characterised by the impacts of all the agricultural and zoo-technical activities, which
involve high energy consumption with respective emissions of greenhouse gases, particulate, ammonia,
sulphur dioxide, nitrogen oxide, heavy metals, such as zinc to soil and water, mercury and lead to soil
due to agricultural operations for crop and grazing grass cultivation.
The second is characterised by the impacts due to energy production and water consumption. The most
significant emissions of the basket of food products to atmosphere, namely nitrogen oxides, nitrogen
dioxide, NMVOC, methane, sulphur dioxide, occur during the production of heat, steam and electricity,
during transport by lorry and truck, transport by sea ship and packaging of glass.
The third group is dominated by the impacts of electricity production, with consequent emissions of CFC-
114, CFC-11, Halon 1301 Carbon-14 in air, Radon-222 in air and Cesium-137 in water which occur
during the electricity production.
The fourth group, includes only Mineral fossil & renewable resource depletion. Major mineral fossil &
renewable resource depletion are due to the use of indium, phosphorous, cadmium, organic carbon in
soil or biomass stock and tantalum, which are used in the life cycle of secondary aluminium or for the
manufacture of phosphatic fertilisers.
The fifth group, includes only freshwater eutrophication, and is dominated by the end-of-life stage and
caused by the depuration of the wastewater, waste treatment (in particular compost production) and by
the packaging life cycle, with consequently emissions of phosphorous and phosphate to water to soil.
In the first group the foods contributing most to the environmental impact of the basket are beef, pork
and cheese; in the second group beef, pork and cheese; in the third beer, bread, cheese, coffee and
potato; in the fourth beer, milk; in the fifth pork, cheese and milk.
The agricultural stage results the most burdening one for most of the impact categories (eleven out of
sixteen impact categories, with relevant contributions also in the remaining five).
By examining the results, in general, it can be ascertained that the end-of-life stage has to be taken into
consideration, especially human excretion and wastewater treatments, since their burden is often higher
than that of the transports and operations occurring in the food industrial manufacturing plants.
The losses which occur during the whole life cycle, during agricultural/industrial phases and at home, in
terms of food scraps and wastage food, have to also be taken in consideration, since they can contribute
up to 60% of the initial weight of the food.
The results almost always tend to go in the same direction as the results of the international scientific
LCA literature published both on scientific journals and in Food LCA Conferences (Notarnicola et al. 2010
2012a,b, 2014; Corson et al. 2012; Nemecek et al. 2008; Haldberg et al. 2007; SIK 2001 2007).
On the methodological side, this study has reached the following results:
• Development of a methodological framework fully replicable and fully coherent with the structure
of the main LCA databases;
• Development of process tree inventories highly disaggregated and based on a modular approach;
• Identification of the data sets for the basket of nutrition based on a comprehensive bibliographic
research;
42
• Implementation of basket foods with a coverage which represents at least 50% of the European
food consumption.
Future further developments of this study could entail:
• Expansion of the basket-of-products to a greater range of foods covering almost 100% of the
European Food Consumption
• Implementing new data sets
• Implementing a coherent and representative model of commodity transports within the EU.
2.6 References
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assessment methodology and sustainability indicators for products and supply chains. SENSE - Harmonised
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Blonk Consultants (2014). Agri-footprint Description of data. V 1.0. Retrieved from: www.agri-
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market for frozen fruit and vegetables. Available from http://www.cbi.eu/system/files/marketintel/2009_-
_Frozen_fruit_and_vegetables1.pdf.
Coltro L., Mourad A.L., Oliveira P.A.P.L.V., Baddini J.P.O.A., Kletecke R.M. (2006). Environmental Profile of Brazilian
Green Coffee. Int J LCA 11 (1) 2006, 16 – 21.
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Assessment in the Agri-Food Sector (LCA Food 2012), 1-4 October 2012, Saint Malo, France. INRA, Rennes, France,
p. 407-412.
de Beaufort-Langeveld A. S. H., Bretz R., van Hoof G., Hischier R., Jean P., Tanner T. and Huijbregts M. A. J. (2003).
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DEFRA (2012). Family Food (2012). Report published by the Department for Environment, Food and Rural Affairs.
Available on the Defra website: https://www.gov.uk/government/collections/family-food-statistics.
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products. Journal of Cleaner Production 68 (2014) 64-72
EC (2007). Eurostat Statistical Books: The use of plant protection products in the European Union – Data 1992-2003,
2007 Edition. European Commission, Brussels.
EC (2008). Biofuels in the European Context: Facts and Uncertainties. European Commission, Joint Research Centre,
Institute for Energy.
EC (2010). Joint Research Centre - Institute for Environment and Sustainability: International Reference Life Cycle
Data System (ILCD) Handbook - General guide for Life Cycle Assessment - Detailed guidance. First edition March
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EC (2012a). Life cycle indicators basket-of-products: development of life cycle based macro-level monitoring
indicators for resources, products and waste for the EU-27. European Commission, Joint Research Centre, Institute
for Environment and Sustainability.
EC (2012b). DG Agriculture & Rural Development. Monitoring Agri-trade Policy - The EU and major world players in
Fruit and Vegetable Trade. Available from: http://ec.europa.eu/agriculture/trade-analysis/map/2012-2_en.pdf.
EC (2012c). European Commission, Agriculture and Rural Development, Fruit and vegetables, Product reports: Apple
and Pears. Available from http://ec.europa.eu/agriculture/fruit-and-vegetables/product-reports/apples-and-
pears/index_en.htm
EC (2012d). European Commission, Agriculture and Rural Development, Fruit and vegetables, Product reports: Apple
and Pears. Available from http://ec.europa.eu/agriculture/fruit-and-vegetables/product-reports/citrus-
fruit/index_en.htm
EC (2012e). European Commission, Agriculture and Rural Development, Fruit and vegetables, Product reports:
Potatoes. Available from http://ec.europa.eu/agriculture/fruit-and-vegetables/product-reports/potatoes/index_en.htm
43
EEA (2012). Consumption and the environment — 2012 update. The European environment state and outlook 2010.
European Environment Agency, Copenhagen.
Espinoza-Orias N., Stichnothe H. & Azapagic A. (2011). The carbon footprint of bread. The International Journal of
Life Cycle Assessment, Volume 16, Issue 4, pp 351-365
EPD (2012). PCR 2012:08; CPC 2131 – PCR for frozen vegetables, pulses and potatoes. Ver. 1.0, 2012-08-28. The
International EPD System.
Eurostat (2011). Food: from farm to fork statistics. Eurostat Pocketbooks, EU Publications. Available on the Eurostat
website: epp.eurostat.ec.europa.eu/cache/ITY.../KS.../KS-32-11-743-EN.PDF
Eurostat (2013). Statistics in focus 2/2013. Analysis of EU-27 household final consumption expenditure — Baltic
countries and Greece still suffering most from the economic and financial crisis Available on the Eurostat website:
http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Household_consumption_expenditure_-
_national_accounts#EU-27_final_and_actual_household_consumption.
Fantin V., Buttol P., Pergreffi R., & Masoni P. (2012). Life cycle assessment of Italian high quality milk production. A
comparison with an EPD study. Journal of Cleaner Production 28, 150-159.
Fantke P., Laurent A., Reichenberger S., Sala S., Garthwaite D., Hart A. (2014). Guidelines to estimate initial pesticide
distribution for emission and exposure quantification in risk and life cycle assessment. (in preparation)
FAO (2011). Global food losses and food waste – Extent, causes and prevention. Rome
Foster, C., Green, K., Bleda, M., Dewick, P., Evans, B. Flynn, A., Mylan J. (2006). Environmental Impacts of Food
Production and Consumption: A report to the Department for Environment, Food and Rural Affairs. Manchester
Business School. Defra, London.
Frischknecht R., Jungbluth N., Althaus H.-J., Doka G., Dones R., Heck T., Hellweg S., Hischier R., Nemecek T., Rebitzer G.
and Spielmann M. (2007). Overview and Methodology. ecoinvent report No. 1, v2.0. Swiss Centre for Life Cycle
Inventories, Dübendorf, CH, retrieved from: www.ecoinvent.org.
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change through livestock – A global assessment of emissions and mitigation opportunities. Food and Agriculture
Organization of the United Nations (FAO), Rome.
IFA (2012). Database of the International Fertilizer Industry Association available at
http://ifadata.fertilizer.org/ucSearch.aspx
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11), 4, 1–54.
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use. International Environmental Science and Pollution Research, 14, 338-344.
Muñoz I., Milà i Canals L., Clift R., Doka G., (2007). A simple model to include human excretion and wastewater
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University of Surrey.
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diet including human excretion. The International Journal of Life Cycle Assessment, 15, 794-805.
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Notarnicola B., Salomone R., Petti L., Renzulli P.A., Roma R., Cerutti A.K. (2015). Life cycle assessment in the agri-food
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VII Conference of the Italian LCA Network. Milan, 27-28th June 2013, pp. 29-35.
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44
Pergola M., D’Amico M., Celano G., Palese A.M., Scuderi A., Di Vita G., Pappalardo G., Inglese P. (2013). Sustainability
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Ecoinvent Centre.
45
3 Basket of Products: mobility
3.1 Introduction
The pursue of a more sustainable development has been one of the main goals of the European Union
with the development of specific strategies such as the Europe 2020 strategy [1] and the Resource-
efficient Europe flagship initiative [2].
The development of life-cycle indicators to monitor the progress towards sustainability constitutes a key
strategy to accomplish sustainability goals. This life cycle perspective enables an integrated approach
considering consumption, production, resource depletion, resource use, resource recycling and waste
generation. The environmental impacts along the life cycle phases of a product or a service are quantified
making use of Life-Cycle Assessment (LCA), based on the quantification of the physical exchanges with
the environment, either as inputs (resources, such as materials, land use, water and energy) or as outputs
(emissions to air, water and soil). The classification of these inputs and outputs according to
environmental impact categories results in the potential environmental impact of the product or service.
These environmental impact indicators may even be compared with the economic performance of a
region or country (for instance, in comparison with GDP) to obtain an eco-efficiency indicator.
These indicators are useful tools for helping decision makers in policy making, by incorporating significant
environmental impacts and resources consumed in a product’s life cycle. The basket-of-products
indicator reflects the resource consumption associated with the final consumption of an average citizen
in the EU27 in different demand categories, such as nutrition, shelter, consumer goods or mobility.
This section focuses on the mobility basket-of-products for the reference year of 2010, in order to define
the most relevant mobility products and quantify the resulting resource consumption and subsequent
environmental impacts. The characterization of the basket-of-products for mobility and the associated
energy consumption are presented in subsection 3.2. The environmental impacts occurred due to the
mobility basket-of-products are quantified in subsection 3.3. Finally, a summary of the conclusions
drawn from this work and lines for future work are presented in subsection 3.4.
3.2 Definition of the basket of products for mobility
The transport sector accounted in 2010 for 31% of the final energy consumption in the EU27 (Figure 12
a). The main transport consumer is the road transport sector with approximately 82%, followed by
aviation with 14% and rail (including subway and trams) with 2% (Figure 12 b). Since road transport is
responsible for the largest energy consumption share, this subsector will be analysed in more detail.
The maritime sub-sector is responsible for a small part of the total energy consumption (≈1%) and,
consequently, it is responsible for little environmental impacts. Additionally, it has a residual passenger
transport contribution (≈0.4%, Figure 13 a), since it is mainly used for goods transport, contributing with
18% stake in the freight transported (Figure 13 b). As a result of these facts, for this analysis of
passenger’s mobility basket-of-products, the maritime sub-sector was not considered.
Additionally, due to their low environmental impacts, activities such as walking and cycling were also
excluded from this analysis.
Based on this analysis, the main sub-sectors related to passenger mobility are road, rail and air transport.
The basket-of-products for mobility considers two major groups of products:
1. Private road transport - transportation service not available to the general public, which is divided
in:
o Passenger cars; and
o Two wheelers (2W, including mopeds and motorcycles).
2. Mass transit - shared passenger transport service available to the general public, which is divided in
the following categories:
46
o Buses (including Urban buses, mainly used for urban transport, and coaches for long distance
transport);
o Rail; and
o Air.
The new suggested basket-of-products considers 76 mobility sub-products (Figure 14 b), including 36
vehicle categories for passenger cars (accounting for 6 vehicle categories sub-divided with 5 Euro
standards), 15 categories for buses, 20 categories for 2W, 2 categories for rail transport (electric and
other energy sources) and 3 categories for air transport (national, intra-EU and extra-EU flights).
The mobility service provided by the Basket-of-products is quantified through an estimation of the level
of service for each sub-product. In the case of mobility this is translated in kilometres travelled and,
more importantly, in number of passengers transported (based on average occupancy factors, presented
in Table A.1 in the Annex), which is reflected in a passenger-kilometres analysis.
The analysis presented in this document performs a study by country, considering different types of
usage conditions of the different mobility products, as is presented in Figure 15.
a)
b)
Figure 12 EU27 energy use by the transport sector in comparison with the total final energy
consumption (a), and disaggregated by mode of transport (b) [3]
0
10,000
20,000
30,000
40,000
50,000
60,000
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
20
12
Ene
rgy
con
sum
pti
on
(P
J)
Final energyconsumption
Transport sector
0
2.000
4.000
6.000
8.000
10.000
12.000
14.000
16.000
18.000
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
20
12
Ene
rgy
con
sum
pti
on
(P
J)
Total
Road
Rail
Aviation
Maritime
Unspecified
47
a) b)
Figure 13 a) EU27 passenger split per transport mode in 2010, and b) EU27 distribution of
goods transport (based in ton of freight transported) per transport mode in 2010 [3]
Figure 14 Fleet composition disaggregation for the suggested Basket-of-products
83.2%
8.6%7.0%
0.8%0.4%
Passenger cars
Buses
Rail
Aviation
Maritime 73.9%
18.1%
7.9%
0.1%
Road
Maritime
Rail
Aviation
Fleet composition
Road transport
Rail transport
Air transport
Light duty vehicles
Buses
Two wheelers
Diesel <2l
LPG
Diesel Urban buses
CNG Urban buses
Mopeds 2-stroke
68 Types of aircrafts
Railcars
Locomotives
Electric
Diesel
Electric
Diesel
Steam
Conventional, Euros 1, 2, 3, 4 and 5
Conventional, Euros 1, 2, 3, 4 and 5
Conventional, Euros 1, 2, 3, 4 and 5
Conventional, Euros 1, 2, 3, 4 and 5
Conventional, Euros 1, 2, 3, 4 and 5
Conventional, Euros 1, 2, 3, 4 and 5
Conventional, Euros 1, 2, 3, 4 and 5
Diesel CoachesConventional, Euros
1, 2, 3, 4 and 5
Conventional, Euros 1, 2, 3, 4 and 5
Conventional, Euros 1, 2 and 3
Conventional, Euros 1, 2, and 3
Conventional, Euros 1, 2, and 3
Gasoline <1.4l
Gasoline 1.4l - 2l
Gasoline >2l
Diesel >2l
Motorcycles <250cm3
Motorcycles >250cm3
Private transport
Mass transit
Analysis per country
Aircraft type 1
Aircraft type 68
...National flights
Intra-EU flights
Extra-EU flights
Electric
Other
48
Figure 15 Level of service disaggregation
3.2.1 Data Sources
The data sources used for defining and characterizing the Mobility basket-of-products are described
next.
The road transport sector was characterized using the existing Eurostat data sets [4] for EU27 countries,
which included the following variables:
1. Number of vehicles per vehicle technology for several years (for passenger cars, buses, coaches and
two-wheelers, considering the fuel use of gasoline, diesel and LPG – liquefied petroleum gas). These
datasets include passenger cars, independently of whether they are used for private or business
purposes;
2. Engine displacement distribution time series (for passenger cars and two-wheeler); and
3. Vehicle age distribution time series (for passenger cars and buses). The vehicle age distribution
allows characterizing different Euro Standards [5], which have imposed in the last two decades
reductions in local pollutant emissions.
The rail transport sector was characterized using the existing Eurostat data sets [4] for EU27 countries,
which included the following variables:
1. Total number of vehicles per vehicle technology time series (for locomotives and railcars, considering
the fuel use of diesel, electricity and steam);
2. Number of passenger-vehicles per vehicle type time series (for coaches and railcars);
3. Total passenger-kilometres time series;
4. Vehicle-kilometres travelled per vehicle technology time series (for locomotives and railcars,
considering the fuel use of diesel, electricity and steam, and for goods, passengers or other vehicles);
and
Level of service
Road transport
Rail transport
Air transport
Driving conditions, vkm and average
speed
Average occupancy factors
Highway
Rural
Urban
National flights
Train kilometers
Passenger kilometers
Intra-EU flights
Analysis per country
Extra-EU flights
68 Types of aircraft models
Distance travelled and occupancy
factors
49
5. Energy consumption for rail transportation time series (considering the fuel use of gas/diesel oil,
electricity, solid fuels and biodiesels).
The air transport sector was characterized using the existing Eurostat data sets [4] for EU27 countries,
which included the following variables:
1. Number of passenger aircrafts by aircraft size (for 4 sizes based on the number of seats);
2. Number of commercial passenger air flights by aircraft model and flight type (for 68 aircraft model
types and national, intra-EU and extra-EU flights); and
3. Number of passengers transported per flight type time series (for national, intra-EU and extra-EU
flights).
3.2.2 Assumptions
3.2.2.1 Road transport
The existing data sets for road transportation do not cover all the EU27 countries and, as a consequence,
the following assumptions were performed:
1. Variables without an attributed value in 2010 were given the existing value in the closest year;
2. Countries without any data were characterized by the same normalized characteristics of
comparable countries. For instance, when the disaggregation between gasoline and diesel fuel use
was not available, it was assumed that Bulgaria has similar shares of gasoline vehicles than
Romania, that Denmark is similar to Sweden, Greece to Portugal, Lithuania to Latvia, and Slovakia
to Czech Republic;
3. No engine displacement disaggregation was considered for LPG vehicles;
4. All mopeds consider an engine displacement of 50 cm3, using a two-stroke petrol blend;
5. The bus and coach category was represented by standard 12 meter buses; and
6. The distribution of buses between urban buses and coaches was based on the vehicle-kilometres
travelled in urban and rural contexts (assumed for urban buses) versus highway conditions (assumed
for coaches), provided by Eurostat [4]. This results in an average distribution of 90% urban bus to
10% coach.
Additionally, the age distribution was characterized for each vehicle type, based on the Eurostat age
distribution categories (less than 2 years, 2 to 5 years, 5 to 10 years, more than 10 years) and adapted
to include the Euro standard implementation years. For the two-wheelers, since no EU27 data was
available, the Portuguese 2W age distribution was used [6]. Since it corresponds to a small percentage
of the mobility basket-of-products and the assumption simply distributes the total number of 2W per
Euro standard, it is considered not to affect the outputs significantly.
For passenger cars, and for 16 of the EU27 countries (accounting for 72% of the total EU27 fleet), the
combination of the passenger-kilometres travelled dataset with the existing fleet dataset and
considering an occupancy factor allows estimating the number of kilometres travelled per passenger car
per year per country, as is presented in Equation 1. The remaining countries were assumed to have a
behaviour similar to comparable countries. The vkm obtained this way represents the average vkm of all
passenger cars in each country, independent of the vehicle technology. This value is necessary to
estimate the total vehicle-kilometres travelled in the EU27 countries and, subsequently, the total energy
consumption.
𝒗𝒌𝒎𝒑𝒂𝒔𝒔𝒆𝒏𝒈𝒆𝒓 𝒄𝒂𝒓𝒔 =𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝒑𝒂𝒔𝒔𝒆𝒏𝒈𝒆𝒓. 𝒌𝒊𝒍𝒐𝒎𝒆𝒕𝒆𝒓𝒔
𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝒗𝒆𝒉𝒊𝒄𝒍𝒆𝒔×
𝟏
𝑶𝒄𝒄𝒖𝒑𝒂𝒏𝒄𝒚 𝒇𝒂𝒄𝒕𝒐𝒓𝒑𝒂𝒔𝒔𝒆𝒏𝒈𝒆𝒓 𝒄𝒂𝒓𝒔
Equation 1
50
A smaller Eurostat dataset for five EU27 countries contained the vehicle-kilometres travelled both for
gasoline and diesel passenger cars. Based on these statistics, a 33% increase in vkm for diesel vehicles
compared to the country’s average vkm and an 11% decrease in vkm for gasoline vehicles compared to
the country’s average vkm was observed. These ratios were used for the remaining EU27 countries.
The average occupancy factor for passenger cars was estimated by comparing the pkm dataset with the
smaller vkm per vehicle dataset, as presented in Equation 2. An average 1.57 value was obtained for
passenger cars.
𝑶𝒄𝒄𝒖𝒑𝒂𝒏𝒄𝒚 𝒇𝒂𝒄𝒕𝒐𝒓𝒑𝒂𝒔𝒔𝒆𝒏𝒈𝒆𝒓 𝒄𝒂𝒓𝒔 =
𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝒑𝒂𝒔𝒔𝒆𝒏𝒈𝒆𝒓. 𝒌𝒊𝒍𝒐𝒎𝒆𝒕𝒆𝒓𝒔𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝒗𝒆𝒉𝒊𝒄𝒍𝒆𝒔
𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝒌𝒊𝒍𝒐𝒎𝒆𝒕𝒆𝒓𝒔 𝒑𝒆𝒓 𝒗𝒆𝒉𝒊𝒄𝒍𝒆
Equation 2
For buses and 2W, the combination of the vehicle-kilometres travelled dataset with the number of
vehicles allowed estimating an average EU27 value of ≈34000 km per bus per year (Equation 3).
Countries without any data entry in vehicle-kilometres travelled were attributed the EU average. For 2W,
the few available data allowed estimating an average value of 3700 km per 2W per year (Equation 3),
which was considered for all EU27 countries.
𝒗𝒌𝒎𝑩𝒖𝒔𝒆𝒔 𝒐𝒓 𝟐𝑾 =𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝒗𝒆𝒉𝒊𝒄𝒍𝒆. 𝒌𝒊𝒍𝒐𝒎𝒆𝒕𝒆𝒓𝒔
𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝒗𝒆𝒉𝒊𝒄𝒍𝒆𝒔
Equation 3
The considered occupancy factor for buses were based on Swiss data from the Ecoinvent database [7],
which refers values of 14 passengers for urban buses and 21 passengers for coaches, due to a lack of
representative data for EU27. A 1.1 occupancy factor was considered for 2W [7].
3.2.2.2 Rail transport
The existing data sets for rail transport did not cover all the EU27 countries and some assumptions were
performed:
1. Variables without an attributed value in 2010 were given the existing value in the closest year;
2. Countries without any data on the partition between passenger-train-kilometres and freight-train-
kilometres by fuel type were assumed to have the same normalized characteristics as countries with
similar energy consumption per train and passenger-kilometre. For instance, when the
disaggregation between electricity and diesel fuel use was not available, it was assumed that
Portugal would have a similar share of electricity and diesel for rail passenger transportation than
Spain, and that Luxembourg would be similar to Belgium.
The level of service provided per vehicle type (electric and others) for the rail transport was estimated
first as the number of vehicle-kilometres travelled for passenger transport (vkmp) and second as the
number of passenger-kilometres travelled (pkm). Given that only 12 countries had data available on the
vkmp for the year 2010, an estimation was performed for the rest of the countries based on data from
other years and energy consumption data (calculating average vehicle efficiencies for years with all data
available and using the 2010 data for energy consumption in rail transport). Average occupancy factors
were estimated for each country based on the total passenger-kilometres and total train-kilometres
travelled. This assumes that the occupancy factor of the electric trains and other trains are the same for
each country. The pkm for each vehicle type were calculated based on the average occupancy factors
and the vkmp.
3.2.2.3 Air transport
The existing data sets for air transport did not have data on the number of flights by aircraft model for
the year 2010, and as such the values for 2011 were used. The level of service provided per flight type
(national, intra-EU and extra-EU) for the air transport was estimated first as the number of vehicle-
kilometres travelled for passenger transport (vkmp) and second as the number of passenger-kilometres
travelled (pkm). The vkmp were estimated based on the number of flights performed in each country, by
51
flight type, and assuming average distances travelled based on the size of each country, the size of
Europe and considering the average flight distance declared by oneworld, Star Alliance and SkyTeam [8].
The average distance for intra-EU flights and extra-EU flights was assumed to be the same for all
countries.
The average occupancy factors of each flight type were estimated for each country based on the data
of passengers transported and number of flights. For the extra-EU flights, it was assumed that 50% of
the passengers transported were Europeans, and the average occupancy factor was calculated taking
this into consideration. The pkm for each country and flight type were calculated from the vkmp and the
average occupancy factors.
3.2.3 Final selection
The quantification of the mobility service provided by the basket-of-products, in passenger-kilometres
(pkm) per sub-product, is presented in Figure 16, with the average passenger-kilometres travelled by
each citizen of each EU27 country being shown in Table 15. The total vehicle-kilometres and passenger-
kilometres travelled in each EU27 country by vehicle category are presented in Table A.2 and A.3 in the
Annex.
The main passenger-kilometre providers are passenger cars with 62% of pkm, followed by the aviation
sector with 24%. Buses represent 6% and rail 5%, while 2W represent the smaller share with just 3%.
3.3 Life cycle Inventory of the selected products
The life-cycle assessment calculations conducted in this work were performed using Simapro 8.0.3.14
[9]. The available Simapro processes were adjusted in order to reflect the mobility basket-of-products
reality. The impact assessment method used was the ILCD 2011 Midpoint method [10].
The transportation sector life-cycle stages considered for the mobility life-cycle inventory are presented
in Figure 17, and incorporate the Use, Production and End-of-life stages.
Figure 18 presents the schematics of the analysis performed, highlighting that an average EU27 usage
efficiency for each mobility sub-product was the basis for analysis.
Figure 16 Total EU27 pkm for the basket-of-products, in 2010
0
400000
800000
1200000
1600000
2000000
Die
sel >
2,0
l
Die
sel 1
,4 -
2,0
l
Gas
olin
e >2
,0 l
Gas
olin
e 0,
8 -
1,4
l
Gas
olin
e 1,
4 -
2,0
l
LPG
Co
ach
es
Urb
an B
use
s
Urb
an C
NG
Bu
ses
2-s
tro
ke <
50
cm
³
Mo
torc
ycle
s
2-s
tro
ke >
50
cm
³
4-s
tro
ke <
25
0 c
m³
4-s
tro
ke >
75
0 c
m³
4-s
tro
ke 2
50
- 7
50
cm³
Ele
ctri
c
Die
sel
Nat
ion
al f
ligh
ts
Intr
a-EU
flig
hts
Extr
a-EU
flig
hts
Passengers cars Buses 2W Train Aviation
Mill
ion
pkm
52
Table 15 Average passenger-kilometres per citizen for the vehicle categories considered for
each EU27 country, in 2010
Country
Passenger cars
2W
Urban
buses
and
Coaches
Rail Air
Gasoline Diesel LPG Electric Others National
flights
Intra-
EU
flights
Extra-
EU
flights
Austria 3415 6316 0 343 580 938 222 25 2206 2737
Belgium 3557 8354 65 207 753 860 84 1 1692 2182
Bulgaria 2931 1956 0 69 2014 224 57 7 744 581
Cyprus 6260 1041 0 205 2091 0 0 3 8212 5901
Czech Republic 3938 2173 0 552 663 293 334 8 959 1094
Denmark 8306 2035 0 152 1314 329 782 77 3322 3728
Estonia 6048 2999 0 99 1616 23 163 3 971 637
Finland 10057 3645 0 375 1593 598 142 214 1973 1800
France 4285 6940 42 160 772 1094 276 284 955 2295
Germany 6988 3882 96 280 471 702 311 153 1211 2330
Greece 2572 3126 38 953 1235 14 110 176 2261 1393
Hungary 2977 1125 0 84 891 468 296 0 743 599
Ireland 6686 2203 0 65 892 0 369 22 5218 1923
Italy 5819 5951 499 616 850 581 152 238 1172 1170
Latvia 2990 2213 0 71 1564 74 275 0 1902 1889
Lithuania 6559 4008 0 74 1276 8 70 0 748 352
Luxembourg 4683 11558 9 352 1627 616 75 0 2986 2150
Malta 5028 2948 0 203 145 0 0 0 8695 1999
Netherlands 6996 2211 239 289 342 767 191 0 2009 3956
Poland 3461 1915 815 209 837 352 106 12 415 339
Portugal 3325 4040 49 194 733 375 14 245 1986 1453
Romania 1780 1188 0 17 1224 105 153 15 408 185
Slovakia 2838 1566 0 67 630 223 206 1 332 198
Slovenia 6851 5460 0 183 1041 205 151 0 449 936
Spain 3143 5074 0 443 675 389 85 1482 2404 1464
Sweden 8270 2026 0 163 722 1075 119 380 1992 1666
United Kingdom 6337 3891 8 81 1217 305 588 142 2044 3254
3.3.1 Data sources
The process-based life-cycle inventory models were developed and the emissions inventory and impacts
assessment were calculated for the EU27 using the Ecoinvent 3 database [11] in Simapro. Due to
constraints on data availability, the 76 basket-of-products categories were aggregated into 27 Simapro
processes for the Use stage and 11 for the Production and End-of-life stages, as is presented in Table
16.
3.3.2 Assumptions
The energy consumption of each sub-product of the Basket-of-products in the Vehicle use stage was
estimated by combining the fleet composition and the level of service information with international
reference methodologies or data sources. This analysis was performed, firstly, in an energy per vehicle
kilometres approach (MJ/vkm) in order to validate the vehicle technology’s energy efficiency with
53
reference values and, in a second stage, in energy per pkm (MJ/pkm) in order to compare the overall
efficiency in the service of transporting passenger.
The methodologies estimating energy consumption in the Vehicle use stage for each transport sub-
products are briefly described next:
1. Road transport – Tier 3 energy consumption calculation based on COPERT [12] and EMEP-inventory-
guidebook methodology [13], including weather conditions, type of road (urban, rural, highway) and
average speed;
2. Rail transport – Estimated from energy consumption data on the rail sector from Eurostat statistics
[4]; and
3. Air transport – Based on EMEP-inventory-guidebook methodology [13] for 75 aircraft models and
flight types and distances (national, intra-EU, extra-EU).
Figure 17 Life-cycle stages considered
Figure 18 LCI methodology overview
Fleet composition
Fleet level of service
Basket-of-products
Use
Production
End-of-life
Combustion emissions
Brake wear emissions
Tire wear emissions
Road wear emissions
Fuel production pathway
Infrastructure
Vehicle Maintenance
Vehicle Production
Vehicle dismantling
Vehicle Usage
Reuse
Recycling
Recovery
Landfill
End-of-life
Fleet composition
Fleet level of service
Energy consumption
Basket-of-products Analysis per country
Total EU27Impacts Assessment
EU27
EU27 Energy consumption and emissions inventory:
• Fuel production• Vehicle usageEU27 fleet characterization
and emissions inventory:• Production of
infrastructure• Production of vehicles• Vehicle maintenance• Vehicle end-of-life
54
Table 16 Number of processes for each sub-product category
Basket-of-products Number of processes
Use Production End-of-life
Passenger Cars 16 2
Mopeds 3 2
Buses 3 2
Rail Transport 2 1
Air Transport 3 4
Total 27 11
In order to more accurately characterize the energy efficiency of each of the road mobility sub-products,
the analysis focused on the volume of kilometres occurring in different driving conditions (highway, urban
and rural roads). By analysing the datasets referring to vehicle-kilometres travelled that were driven in
Motorways (highway), Roads within built-up areas (urban) and Roads outside built-up area (rural) for
passenger cars, buses and motorcycles a distribution of kilometres travelled was estimated. Mopeds
were considered to drive in urban conditions. Due to the lack of more accurate information, coaches were
attributed with the kilometres performed in highways condition while urban buses were considered to
drive in urban and rural conditions.
Summarizing, the EU27 average energy consumption in the Vehicle use stage by grouped sub-products
was calculated as is presented in Figure 19. The values obtained for the individual sub-products are
presented in Table A.4 in the Annex. This energy per kilometre analysis serves as validation of the
methodology applied, since the obtained values are in accordance with typical literature values [14].
Higher values are presented for the more energy intensive technologies such as buses and planes when
compared to passenger cars, 2W and trains.
Figure 19 Average vehicle efficiency (MJ/vkm) for the basket-of-products in the Vehicle use
stage, in 2010
In order to compare the overall efficiency in the service of transporting passengers, the energy per
passenger-kilometres analysis was performed (see Figure 20). When incorporating the average
occupancy factors (Table A.1 in the Annex), rail transport becomes the more efficient followed by buses.
2.8 3.3 2.3 1.5
12.1
69.897.8
174.3 164.6202.1
0
50
100
150
200
250
0
2
4
6
8
10
12
14
Die
sel
Gas
olin
e
LPG
2W
Bu
ses
Ele
ctri
c
Die
sel
Nat
ion
al
Intr
a-EU
Extr
a-EU
Passenger cars 2W Buses Rail Aviation
Oth
ers
en
erg
y co
nsu
mp
tio
n (
MJ/
vkm
)
Ro
ad t
ran
spo
rt e
ne
rgy
co
nsu
mp
tio
n
(MJ/
vkm
)
Road transport
Others
55
Figure 20 Average transport mode efficiency (MJ/pkm) for the basket-of-products in the
Vehicle use stage, in 2010
Based on the analysis performed at a country level, the values in the Ecoinvent 3 database concerning
the sub-product energy consumption were adjusted for the calculated EU average.
The life-cycle assumptions performed for each of the sub-products are described next. A summary
description can be found in Table A.5 in the Annex.
3.3.2.1 Production
The Infrastructure Production components considered are described below:
- Road: The considered dataset represents the expenditures and interventions associated with the
provision of road, tunnel and bridge infrastructures, the renewal of different road layers and
eventual road disposal. All environmental impacts refer to one meter and year (m*a). Road provision
is modelled as a constant renewal rather than as a one-time expenditure and end-of-life, and is
assumed directly related to gross vehicle weight (vehicle plus load). The dataset is based on a
modelling of Swiss motorways and Class 1, 2 & 3 roads. The operation and maintenance of roads
then refers to aspects of lighting, weed control, line marking, etc. rather than the replacement and
repair of road sections and is therefore directly related to km use. Operation and maintenance are
not considered in this road construction dataset.
- Rail: The inventory includes construction of the rail track (track bedding, substructures, and catenary
system) as well as the construction of tunnels and bridges, based on average conditions in
Switzerland and specific conditions in Germany3. Further components of rail track infrastructure,
such as signalling infrastructure, train overtaking stations, sound insulation walls and buildings
(stations, service garages) are not included. Land use is not considered, but accounted for in the
maintenance and operation, railway track. For the maintenance and land use, the inventory includes
the energy consumption required for the operation of the rail track as well as the operation of
tunnels. The use and emissions to soil of herbicides (weed control) and lubricates (point
maintenance) are taken into account. Also land transformation and occupation are accounted for.
Disposal is included.
- Air: The dataset includes construction, maintenance and land use and disposal of airport
infrastructure based on the conditions at Zurich airport in Switzerland. It includes material
consumption for the construction (concrete, gravel and reinforcing steel), energy consumption (diesel
3 While the conditions in Switzerland and Germany might not be representative of all EU27 countries, the dataset
available was used due to data constraints.
1.782.11
1.49 1.330.82
0.490.82
2.42
1.69 1.51
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Die
sel
Gas
olin
e
LPG
2W
Bu
ses
Ele
ctri
c
Die
sel
Nat
ion
al
Intr
a-EU
Extr
a-EU
Passenger cars 2W Buses Rail Aviation
Ener
gy c
on
sum
pti
on
(M
J/p
km)
Road Transport
Others
56
and electricity) for construction, excavation, construction of the building, land transformation and
occupation, energy consumption (electricity, natural gas, light fuel oil, diesel and petrol) for
maintenance and operation, consumption of propylene glycol and ethylene glycol for de-icing of
aircrafts and sealed area, the water consumption (tap water), emissions to air (carbon dioxide,
carbon monoxide, NMVOC and nitrogen oxides), emissions to water (BOD5, DOC, TOC and COD) and
treatment of sewage.
In terms of Vehicle Production the following considerations were taken into account:
- Road (Passenger cars): These datasets represent the production of a petrol and of a diesel
passenger car of compact size. The entries are based on a per kg basis. The model is based on
averages over passenger cars technologies spanning from 2000 to 2010 and is estimated for a
vehicle of about 1234 kg for gasoline and 1314 kg for diesel. It is subdivided in two modules, the
glider and the drivetrain. Each module contains the specific material needs, production efforts and
emissions. The vehicle production includes the impacts of the vehicle production factory. The specific
end-of-life treatment of each module is covered in the respective dataset. The treatment of the
used passenger car only includes the manual dismantling of the car in the various modules. For
passenger cars production and end-of-life, weight correction factors were applied for engine
displacement differences in sub-products (proxy for vehicle size). The assumed material composition
for passenger cars consists mainly of steel and aluminium, as presented in Table 17, and the
production requires a consumption of 2.95 kg of water per kg of vehicle.
- Road (2W): The 50 cm3 scooter data set includes all processes and materials for scooter
manufacturing, containing an ICE motor. Transport to regional storage included. It includes as well
the disposal of a scooter. Data for manufacturing in Asia and retail in Europe. The assumed material
composition for 2W consists mainly of steel, PE and aluminium, as presented in Table 17, and the
production requires a consumption of 2.20 kg of water per kg of vehicle.
- Road (Buses): The Bus dataset represents the production of one bus (material composition, energy
consumption and emissions of the manufacturing). Vehicle manufacturing data are taken from one
production site in Germany. The disposal of bus is also included. It includes the material used for the
production, the energy consumption of the building machines, the water consumption, the airborne
emissions and the emissions to water. The assumed material composition for buses consists mainly
of steel, aluminium and ferro metals, as presented in Table 17, and the production requires a
consumption of 1.53 kg of water per kg of vehicle.
- Rail: The train manufacturing is derived from an assessment of the "IC 2000", a long-distance train
which is currently used for long distance transportation in Switzerland. The life span of the train is
assumed to be 40 years resulting in a life time performance of 20,000,000 vkm. For manufacturing,
electricity and light oil burned in industrial furnace are included. For the transportation of materials,
standard distances are applied. The assumed material composition for trains consists mainly of
aluminium, PE and steel, as presented in Table 17.
- Air: The datasets consider the production of a medium haul aircraft, based on an "Airbus A 320"
with a max. zero fuel weight of 61 t and a typical seating of 150 seats, and the production of a long
haul aircraft, based on an "Airbus A340-600" with 240 t max. zero fuel weight and a typical seating
of 380 seats. It includes material consumption (aluminium and polyethylene), energy consumption
(natural gas, electricity and light fuel oil), water consumption, treatment of sewage and NMVOC
emissions. The vehicle manufacturing data are taken from 16 production site in Germany, France,
Spain and the UK. The assumed material composition for aircrafts consists mainly of aluminium, as
presented in Table 17, and the production requires a consumption of 73.77 kg of water per kg of
medium haul aircraft and of 47.50 kg of water per kg of long haul aircraft.
57
Table 17 Material composition of each vehicle type modelled in Simapro (percentage)
Material type Passenger cars 2W Bus Train Aircraft
Aluminium 12 15 16 50 90
Coppers 1 1 1 3 0
Ferro metals 0 0 14 0 0
Glass 2 0 5 3 0
LO 1 0 1 0 0
Non-ferro 1 1 1 0 0
Others 2 1 5 0 0
Paint 0 0 0 2 0
PE 2 16 5 24 10
PET 0 0 0 0 0
Plastics 2 0 0 0 0
PP 4 7 0 0 0
PUR 2 0 0 0 0
PVC 1 2 0 0 0
Rubber 4 3 4 0 0
Steel 66 52 49 17 0
Textile 1 0 0 0 0
Zincs 0 0 0 0 0
3.3.2.2 Use
In the Use stage, the Fuel Production Pathway considered the following assumptions:
- For all fossil fuel products, the inventory for the distribution of petroleum products to the final
consumer including all necessary transports was considered. Transportation of the product from the
refinery to the end user is considered, as well as the operation of storage tanks and petrol stations.
Emissions from evaporation and treatment of effluents are included.
- For diesel, a 6% (weight) incorporation of biodiesel was considered, as result of the EU directive [15,
16], except for rail transport which considers only diesel. Biodiesel using rape oil as feedstock was
considered. The process includes the esterification process of oil to methyl ester and glycerin,
intermediate storage of the oil and products, treatment of specific wastewater effluents. System
boundary is at the esterification plant. The typical rape oil esterification plant is designed for rape
methyl ester (RME) production (for use in the vehicle fuels market).
- For electricity, the average EU27 mix was calculated based on the share of electricity produced in
each country, estimated from Eurostat. Due to a lack of data for some EU countries (Cyprus, Estonia,
Latvia, Lithuania and Malta), the mix was calculated using only the other countries which account
for 99% of the electricity produced in the EU27. The electricity production in each country includes
the transmission network, direct emissions to air (ozone and N2O), electricity losses during
transmission and losses during transformation.
As for the Vehicle Usage, the assumptions made are presented next.
- Road: The vehicle usage stage includes the emission factors for tailpipe emissions as well as the
road, tire and brake wear emissions. Since the Ecoinvent 3 database available in Simapro only
presented the environmental impacts for the Euro Standards 3, 4 and 5 of each vehicle sub-group,
the Conventional, Euro 1, 2 and 3 products were aggregated and simulated under the Euro 3 process.
- Rail: The vehicle usage includes particulate emissions due to abrasion of rail tracks, wheels, brakes
and overhead contact line, as well as emission of sulphur hexafluoride (SF6) occurring during
conversion at traction substations.
58
- Air: The vehicle usage includes the consumption of fuel, airborne gaseous emissions, particulate
emissions and heavy metal emissions.
- All: For each of the vehicle sub-products presented in Table 19, an average EU27 energy
consumption factor was considered and incorporated in the Simapro existing processes. As a result
of this, the environmental impacts were considered to be linear with energy consumption.
In terms of Vehicle Maintenance, the following considerations were made:
- Road: The considered dataset represents the service of passenger car maintenance, representing
the maintenance demands over the complete lifetime of a vehicle. The exchanges represent the
replacement of regular components and substances such as tires, motor oil, coolant and battery.
Disposal of these materials is also accounted for. Data are based on an LCI analysis of standard car
(Golf A4, 1240 kg), an average bus with data based on Swiss conditions and a 50 cm3 scooter with
90 kg. The dataset was scaled to match the mass of the vehicle fulfilling the transport service.
- Rail: The maintenance of trains includes expenditures for one major revision as well as a regular
substitution of brake shoes (40 kg brake shoes/car). Also, the disposal of wood, glass and plastics is
addressed. Land use and material expenditures due to buildings of service garages are not included.
The data represents train maintenance in Switzerland.
- Air: The maintenance of aircrafts was not considered due to lack of data.
- All: The total impacts are spread along the vehicles lifetime.
3.3.2.3 End-of-life
For the vehicles end-of-life, it is considered that all vehicles go through a dismantling process that
disaggregates it in its different components (aggregated in the material types presented in Table 17).
The impacts of the dismantling facility are considered only for passenger cars and 2W. The materials
obtained from the dismantling can be reused, go through a recycling or recovery process or be placed in
a landfill. Using this approach, the modelling methodology allows for the accounting of avoided impacts
through the reuse, recycling and recovery of materials.
Table 18 Waste scenario modelled in Simapro (percentage)
Material type Reuse Recycling Recovery Landfill
Aluminium 10.0 87.8 0.0 2.2
Coppers 10.0 87.8 0.0 2.2
Ferro metals 4.8 94.0 0.0 1.2
Glass 3.3 46.7 0.0 50.0
Lubricating oils 0.0 0.0 100.0 0.0
Non-ferro 10.0 87.8 0.0 2.2
Others 0.0 0.0 0.0 100.0
Paint 0.0 0.0 0.0 100.0
PE 1.7 18.3 10.0 70.0
PET 1.7 18.3 10.0 70.0
Plastics 1.7 18.3 10.0 70.0
PP 1.7 18.3 10.0 70.0
PUR 1.7 18.3 10.0 70.0
PVC 1.7 18.3 10.0 70.0
Rubber 20.0 30.0 50.0 0.0
Steel 4.8 94.0 0.0 1.2
Textile 0.0 10.0 0.0 90.0
Zincs 10.0 87.8 0.0 2.2
59
For each material type, the shares of materials that go through each of these waste processes were
considered as presented in Table 18. This waste scenario is based on the Advanced Standards of End of
Life Vehicles treatment scenario of a reference report [17]. While based on available data for the end-
of-life of road vehicles, the same waste scenario was applied to all sub-products of the basket-of-
products due to data availability constraints. Nonetheless, this could be improved if new data becomes
available.
The total reuse, recycling, recovery and landfill rates obtained for passenger cars are in accordance with
the Eurostat statistics for 2010 of 87.2% for Recovery and Reuse of cars, which is disaggregated into
83.3% Reuse (including recycling) and 3.9% Recovery [18]. These estimates validate the waste scenario
considered. Furthermore, these values allow the fulfilment of the EU guideline of achieving 85% of
Recovery and Reuse, in place since 2006 [19].
For recovery, the lower heating values used for lubricating oils, plastics and rubber were 39.3, 33.5 and
25.6 MJ/kg, respectively [17]. An efficiency of 7.7% for electricity and 31.3% for heat was considered for
the municipal solid waste incineration facility [17].
3.3.3 Final selection: overview per product and life cycle stage
Table 19 presents the number of sub-products considered (27) and the detailed aggregation performed
in each mobility sub-product modelled in Simapro for the different stages previously defined: Production;
Use; and End-of-life. For each sub-product, the different stages were further characterized as described
in Figure 17, Section 3.3.2 and Table A.5 in the Annex.
Table 19 Mobility sub-products modelled in Simapro
Products Designati
on
Sub-products in Use
stage
Sub-products in Production
stage
Sub-products in End-of-
life stage
Road
transpo
rt
Passeng
er Cars
Mobility
sub-
product
(SP) 1
Gasoline
<1,4 l
Convention
al, Euro 1,
2, 3
Passenger car petrol/natural gas
SP 2 Gasoline
<1,4 l Euro 4
SP 3 Gasoline
<1,4 l Euro 5
SP 4 Gasoline
1,4 - 2,0 l
Convention
al, Euro 1,
2, 3
SP 5 Gasoline
1,4 - 2,0 l Euro 4
SP 6 Gasoline
1,4 - 2,0 l Euro 5
SP 7 Gasoline
>2,0 l
Convention
al, Euro 1,
2, 3
SP 8 Gasoline
>2,0 l Euro 4
SP 9 Gasoline
>2,0 l Euro 5
SP 10 Diesel 1,4
- 2,0 l
Convention
al, Euro 1,
2, 3 Passenger car diesel
SP 11 Diesel 1,4
- 2,0 l Euro 4
60
SP 12 Diesel 1,4
- 2,0 l Euro 5
SP 13 Diesel
>2,0 l
Convention
al, Euro 1,
2, 3
SP 14 Diesel
>2,0 l Euro 4
SP 15 Diesel
>2,0 l Euro 5
SP 16 LPG
Convention
al, Euro 1,
2, 3, 4, 5
Passenger car petrol/natural gas
2W
SP 17 Mopeds
<50 cm³
Convention
al, Euro 1,
2, 3
Motor scooter 50 cm3 (RER) + Motor scooter 50 cm3
(ROW) SP 18
Motorcycl
es <250
cm³
Convention
al
SP 19
Motorcycl
es >250
cm³
Convention
al, Euro 1,
2, 3
Buses
SP 20
Urban
Buses
Standard
15 - 18 t
Convention
al, Euro 1,
2, 3, 4, 5
Bus (RER) + Bus (ROW) SP 21
Coaches
Standard
<=18 t
Convention
al, Euro 1,
2, 3, 4, 5
SP 22
Urban
CNG
Buses
Euro 1, 2, 3
Rail transport SP 23 Electric Train passenger long distance
SP 24 Diesel
Air transport
SP 25 National flights Medium haul aircraft (RER) + Medium haul aircraft
(ROW) SP 26 Intra-EU flights
SP 27 Extra-EU flights Long haul aircraft (RER) + Long haul aircraft (ROW)
The main Simapro input for the quantification of the annual impacts of the mobility products are the
vehicle-kilometres travelled for the road transport sector for each of the vehicle categories considered
or passenger-kilometres travelled for rail and air transport, as is presented in Table 20.
.
61
Table 20 Mobility needs Simapro inputs for each of the vehicle categories considered in the
basket-of-products
Mobility sub-product Vehicle-kilometres (million) Passenger-kilometres (million)
Road
transport
Passenger
cars
Gasoline
SP1 588267 -
SP 2 112794 -
SP 3 74617 -
SP 4 530852 -
SP 5 101344 -
SP 6 67043 -
SP 7 97936 -
SP 8 18762 -
SP 9 12412 -
Diesel
SP 10 816541 -
SP 11 155884 -
SP 12 103123 -
SP 13 207188 -
SP 14 39554 -
SP 15 26166 -
LPG SP 16 48971 -
2W
SP 17 48168 -
SP 18 22440 -
SP 19 44377 -
Buses
SP 20 24971 -
SP 21 2288 -
SP 22 2288 -
Rail transport SP23 - 286014
SP24 - 114581
Air transport
SP25 - 121434
SP26 - 726695
SP27 - 931449
Total 3145985 2180173
3.4 Results of the environmental impact of the selected products
for one EU citizen
The EU27 LC impacts for the mobility sub-products were quantified and are presented according to the
life-cycle stages presented earlier.
3.4.1 Results per product
The disaggregation of impacts according to the mobility sub-products is presented Table 21.
62
Table 21 Environmental impacts in 2010 for the whole EU27, from each mobility sub-products
Sub-
product
Climate
change
Ozone
depletion
Human
toxicity,
cancer
effects
Human
toxicity,
non-cancer
effects
Particulate
matter
Ionizing
radiation HH
Ionizing
radiation E
(interim)
Photochemical
ozone
formation
Acidifi-
cation
Terrestrial
eutrophi-
cation
Freshwater
eutrophi-
cation
Marine
eutrophi-
cation
Freshwater
ecotoxicity Land use
Water
resource
depletion
Mineral, fossil
& ren
resource
depletion
kg CO2 eq kg CFC-11
eq CTUh CTUh kg PM2.5 eq
kBq U235
eq CTUe kg NMVOC eq molc H+ eq molc N eq kg P eq kg N eq CTUe kg C deficit
m3 water
eq kg Sb eq
SP 1 2.24E+11 1.55E+04 5.91E+03 3.79E+04 6.92E+07 1.63E+10 8.25E+04 5.35E+08 4.87E+08 1.02E+09 1.64E+07 1.01E+08 1.35E+12 2.19E+11 4.40E+10 2.16E+07
SP 2 3.99E+10 2.83E+03 1.06E+03 7.03E+03 1.24E+07 2.91E+09 1.50E+04 9.04E+07 8.09E+07 1.56E+08 2.88E+06 1.57E+07 2.54E+11 3.90E+10 7.45E+09 4.03E+06
SP 3 2.64E+10 1.87E+03 7.04E+02 4.65E+03 8.19E+06 1.92E+09 9.94E+03 5.95E+07 5.29E+07 9.92E+07 1.91E+06 1.00E+07 1.68E+11 2.58E+10 4.93E+09 2.67E+06
SP 4 2.42E+11 1.72E+04 6.65E+03 4.39E+04 7.51E+07 1.77E+10 9.11E+04 5.51E+08 5.08E+08 1.03E+09 1.80E+07 1.03E+08 1.59E+12 2.38E+11 4.62E+10 2.53E+07
SP 5 4.16E+10 3.00E+03 1.26E+03 8.28E+03 1.37E+07 3.13E+09 1.58E+04 9.34E+07 8.67E+07 1.65E+08 3.37E+06 1.69E+07 3.02E+11 4.31E+10 8.59E+09 4.82E+06
SP 6 2.75E+10 1.98E+03 8.33E+02 5.48E+03 9.04E+06 2.07E+09 1.04E+04 6.14E+07 5.67E+07 1.06E+08 2.23E+06 1.09E+07 2.00E+11 2.85E+10 5.68E+09 3.19E+06
SP 7 5.75E+10 4.07E+03 1.54E+03 1.01E+04 1.74E+07 4.18E+09 2.16E+04 1.26E+08 1.19E+08 2.36E+08 4.16E+06 2.37E+07 3.66E+11 5.55E+10 1.07E+10 5.84E+06
SP 8 1.13E+10 8.01E+02 2.95E+02 1.95E+03 3.38E+06 8.19E+08 4.25E+03 2.38E+07 2.25E+07 4.18E+07 8.01E+05 4.23E+06 7.02E+10 1.08E+10 2.07E+09 1.12E+06
SP 9 7.49E+09 5.30E+02 1.95E+02 1.29E+03 2.24E+06 5.42E+08 2.81E+03 1.56E+07 1.47E+07 2.68E+07 5.30E+05 2.72E+06 4.65E+10 7.15E+09 1.37E+09 7.40E+05
SP 10 2.34E+11 1.70E+04 7.42E+03 6.88E+04 1.88E+08 1.81E+10 8.96E+04 6.77E+08 6.81E+08 2.19E+09 1.95E+07 2.74E+08 1.75E+12 1.99E+12 4.96E+10 2.68E+07
SP 11 4.08E+10 3.00E+03 1.40E+03 1.27E+04 2.59E+07 3.24E+09 1.58E+04 1.03E+08 1.08E+08 3.10E+08 3.66E+06 4.11E+07 3.32E+11 3.47E+11 9.28E+09 5.10E+06
SP 12 2.70E+10 1.98E+03 9.27E+02 8.37E+03 1.14E+07 2.14E+09 1.04E+04 6.82E+07 7.15E+07 2.07E+08 2.42E+06 2.74E+07 2.20E+11 2.29E+11 6.14E+09 3.37E+06
SP 13 7.28E+10 5.30E+03 2.35E+03 2.16E+04 5.24E+07 5.65E+09 2.79E+04 1.99E+08 2.03E+08 6.30E+08 6.16E+06 8.04E+07 5.53E+11 6.20E+11 1.56E+10 8.48E+06
SP 14 1.41E+10 1.02E+03 4.49E+02 4.16E+03 8.00E+06 1.09E+09 5.41E+03 3.36E+07 3.57E+07 1.01E+08 1.18E+06 1.37E+07 1.06E+11 1.20E+11 2.99E+09 1.62E+06
SP 15 9.34E+09 6.78E+02 2.97E+02 2.75E+03 3.63E+06 7.22E+08 3.58E+03 2.11E+07 2.28E+07 6.22E+07 7.80E+05 8.60E+06 6.99E+10 7.96E+10 1.98E+09 1.07E+06
SP 16 1.39E+10 1.12E+03 7.31E+02 4.76E+03 6.34E+06 1.27E+09 5.60E+03 3.71E+07 3.47E+07 7.27E+07 1.89E+06 7.80E+06 1.79E+11 2.01E+10 4.63E+09 2.89E+06
SP 17 4.43E+10 3.36E+03 2.87E+02 7.28E+03 2.05E+07 2.74E+09 1.57E+04 4.61E+08 3.67E+08 1.83E+09 1.39E+06 1.81E+08 9.89E+10 3.77E+11 5.19E+09 7.63E+05
SP 18 4.16E+09 3.47E+02 2.85E+01 7.38E+02 1.95E+06 2.85E+08 1.65E+03 4.29E+07 3.46E+07 1.70E+08 1.37E+05 1.70E+07 9.27E+09 4.01E+10 5.06E+08 7.15E+04
SP 19 4.28E+09 6.43E+02 3.80E+01 2.48E+02 5.80E+05 1.93E+08 7.79E+02 4.16E+06 6.59E+06 1.08E+07 2.30E+05 8.51E+05 8.27E+09 2.20E+09 5.52E+08 6.42E+04
SP 20 4.55E+09 2.85E+02 8.87E+01 7.29E+02 1.51E+06 2.79E+08 1.57E+03 1.22E+08 1.44E+07 5.06E+07 1.89E+05 4.90E+06 3.16E+10 3.41E+09 5.59E+08 3.78E+05
SP 21 3.51E+09 2.19E+02 4.71E+01 3.99E+02 1.13E+06 2.07E+08 1.21E+03 9.73E+07 1.09E+07 3.94E+07 1.10E+05 3.70E+06 1.54E+10 2.33E+09 3.47E+08 1.80E+05
SP 22 1.14E+10 7.05E+02 1.11E+02 9.76E+02 3.59E+06 6.54E+08 3.90E+03 3.21E+08 3.50E+07 1.28E+08 2.85E+05 1.18E+07 3.27E+10 6.96E+09 9.59E+08 3.69E+05
SP 23 2.65E+10 2.09E+03 2.09E+03 7.86E+03 8.93E+06 1.21E+10 2.04E+04 5.66E+07 1.21E+08 1.94E+08 2.21E+07 2.21E+07 2.03E+11 2.49E+10 9.91E+10 6.04E+05
SP 24 9.07E+09 5.68E+02 2.40E+02 6.86E+02 5.32E+06 6.16E+08 3.27E+03 1.37E+08 1.03E+08 5.10E+08 5.97E+05 4.66E+07 1.50E+10 1.06E+10 2.00E+09 2.15E+05
SP 25 2.55E+10 1.69E+03 7.94E+01 4.89E+02 3.88E+06 1.46E+09 9.39E+03 1.31E+08 1.09E+08 4.53E+08 3.13E+05 4.14E+07 6.24E+09 1.44E+10 1.32E+09 6.13E+04
SP 26 1.06E+11 7.05E+03 3.39E+02 2.10E+03 1.63E+07 6.14E+09 3.92E+04 5.48E+08 4.56E+08 1.89E+09 1.39E+06 1.73E+08 2.72E+10 6.07E+10 5.86E+09 2.98E+05
SP 27 1.25E+11 8.25E+03 5.05E+02 3.12E+03 2.10E+07 7.50E+09 4.61E+04 6.40E+08 5.40E+08 2.20E+09 2.59E+06 2.01E+08 4.76E+10 7.85E+10 1.09E+10 3.54E+05
Total 1.45E+12 1.03E+05 3.59E+04 2.68E+05 5.91E+08 1.14E+11 5.55E+05 5.26E+09 4.38E+09 1.39E+10 1.15E+08 1.44E+09 8.05E+12 4.69E+12 3.48E+11 1.22E+08
63
Figure 21 Disaggregation of environmental impacts for the whole EU27 in 2010, by mobility
product
Table 22 Disaggregation of environmental impacts for the whole EU27 in 2010, by mobility
product
Impact category Mobility products
Passenger cars 2W Buses Rail Air
Climate change kg CO2 eq 1.09E+12 1.94E+10 5.28E+10 3.56E+10 2.56E+11
Ozone depletion kg CFC-11 eq 7.78E+04 1.21E+03 4.35E+03 2.66E+03 1.70E+04
Human toxicity, cancer effects CTUh 3.20E+04 2.47E+02 3.54E+02 2.33E+03 9.23E+02
Human toxicity, non-cancer
effects CTUh 2.44E+05 2.10E+03 8.27E+03 8.55E+03 5.71E+03
Particulate matter kg PM2.5 eq 5.07E+08 6.23E+06 2.31E+07 1.42E+07 4.12E+07
Ionizing radiation HH kBq U235 eq 8.18E+10 1.14E+09 3.22E+09 1.27E+10 1.51E+10
Ionizing radiation E (interim) CTUe 4.12E+05 6.68E+03 1.81E+04 2.37E+04 9.47E+04
Photochemical ozone
formation kg NMVOC eq 2.69E+09 5.40E+08 5.08E+08 1.93E+08 1.32E+09
Acidification molc H+ eq 2.58E+09 6.03E+07 4.08E+08 2.23E+08 1.11E+09
Terrestrial eutrophication molc N eq 6.46E+09 2.18E+08 2.01E+09 7.04E+08 4.54E+09
Freshwater eutrophication kg P eq 8.59E+07 5.83E+05 1.75E+06 2.27E+07 4.29E+06
Marine eutrophication kg N eq 7.41E+08 2.04E+07 1.99E+08 6.86E+07 4.15E+08
Freshwater ecotoxicity CTUe 7.55E+12 7.97E+10 1.16E+11 2.18E+11 8.11E+10
Land use kg C deficit 4.08E+12 1.27E+10 4.20E+11 3.55E+10 1.54E+11
Water resource depletion m3 water eq 2.21E+11 1.86E+09 6.25E+09 1.01E+11 1.80E+10
Mineral, fossil & ren resource
depletion kg Sb eq 1.19E+08 9.27E+05 8.99E+05 8.19E+05 7.13E+05
Figure 21 and Table 22 present the results by transport mode, showing a clear predominance of
passenger cars. Nonetheless, air transport has very significant shares in some impact categories, being
responsible for up to 33% of total impacts. The rail transport is only relevant in 3 impact categories,
while buses and 2W have lower responsibilities of the total impacts. This follows closely the distribution
0%
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Per
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Air
Rail
Buses
2W
Passenger cars
64
of pkm by transport mode presented previously (Figure 16). The results obtained by mobility product and
life cycle stage are presented in Tables A.6 to A.10 in the Annex.
3.4.2 Results per life cycle stage
3.4.2.1 Road transport
The assessment of the environmental impacts of the road transport sub-products included passenger
cars (Figure 22), two-wheelers (Figure 24) and buses (Figure 23). The absolute values for the
environmental impacts are presented in Tables A.6 to A.8 in the Annex.
Passenger cars are accountable for 91% of the environmental impacts of road transport. Within this
category, the most significant contributions are from SP1 (Gasoline <1,4 l Conventional, Euro 1, 2, 3),
SP4 (Gasoline 1.4 - 2.0 l Conventional, Euro 1, 2, 3) and SP10 (Diesel 1.4 - 2.0 l Conventional, Euro 1, 2,
3), which is a result of having the higher number of vehicle-kilometres travelled (Table 20).
A predominance of the Use stage is observed, mainly for buses and two-wheelers. Nonetheless, for some
environmental impacts, the Production and End-of-life stages are also very significant.
Figure 22 Passenger cars environmental impacts for the whole EU27 in 2010. Negative
impacts account for avoided environmental impacts associated to End-of-life processes.
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End-of-life [EOL]
Vehicle maintenance [Use]
Vehicle usage [Use]
Fuel production pathway [Use]
Vehicle production [Production]
Infrastructure [Production]
65
Figure 23 Two-wheelers environmental impacts for the whole EU27 in 2010. Negative impacts
account for avoided environmental impacts associated to End-of-life processes.
Figure 24 Buses environmental impacts for the whole EU27 in 2010. Negative impacts
account for avoided environmental impacts associated to End-of-life processes.
-60%
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pac
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End-of-life [EOL]
Vehicle maintenance [Use]
Vehicle usage [Use]
Fuel production pathway [Use]
Vehicle production [Production]
Infrastructure [Production]
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End-of-life [EOL]
Vehicle maintenance [Use]
Vehicle usage [Use]
Fuel production pathway [Use]
Vehicle production [Production]
Infrastructure [Production]
66
3.4.2.2 Rail transport
The environmental impacts of the rail transport are mainly dominated by the Use stage, as can be seen
in Figure 25. The Production stage is the dominant stage in only one category (Land use), being
nonetheless responsible for more than 30% of the impacts in 3 other categories (Human toxicity, cancer
effects; Particulate matter; and Mineral, fossil & renewable resources depletion). The absolute values for
the environmental impacts are presented in Table A.9 in the Annex.
Figure 25 Rail transport environmental impacts for the whole EU27 in 2010. Negative impacts
account for avoided environmental impacts associated to End-of-life processes.
The electric trains are responsible for 72% of the environmental impacts of the rail transportation sector.
This is mainly due to the high share of passenger-kilometres attributed to the electric rail transport.
3.4.2.3 Air transport
The environmental impacts of the air transport are mainly dominated by the Use stage, as can be seen
in Figure 26. While the Use stage is the most relevant for all categories, the Production stage is still
responsible for more than 30% of the impacts in 3 categories (Freshwater eutrophication; Freshwater
ecotoxicity; and Water resource depletion). The absolute values for the environmental impacts are
presented in Table A.10 in the Annex.
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End-of-life [EOL]
Vehicle maintenance [Use]
Vehicle usage [Use]
Fuel production pathway [Use]
Vehicle production [Production]
Infrastructure [Production]
67
Figure 26 Air transport environmental impacts for the whole EU27 in 2010. Negative impacts
account for avoided environmental impacts associated to End-of-life processes.
The most relevant sub-product in the air transport sector is the extra-EU flights, which are responsible
for around 52% of the environmental impacts. The intra-EU flights are responsible for 39% while the
national flights only account for 9%. These results are explained mainly due to the high share of
passenger-kilometres attributed to the extra-EU and intra-EU flights.
3.4.2.4 Total mobility impacts
The environmental impacts of the total EU27 mobility products were quantified and are presented in
Figure 27 and Table 23.
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End-of-life [EOL]
Vehicle maintenance [Use]
Vehicle usage [Use]
Fuel production pathway [Use]
Vehicle production [Production]
Infrastructure [Production]
68
Figure 27 Environmental impacts from the mobility basket-of-products of the whole EU27 in
2010, by life stage
Table 23 Environmental impacts from the mobility basket-of-products of the whole EU27 in
2010, by life stage
Impact category LC stage
LCI Total
Production Use EOL
Climate change kg CO2 eq 2.00E+11 1.35E+12 -1.00E+11 1.45E+12
Ozone depletion kg CFC-11 eq 2.10E+04 8.66E+04 -4.58E+03 1.03E+05
Human toxicity, cancer effects CTUh 4.89E+04 7.40E+03 -2.05E+04 3.59E+04
Human toxicity, non-cancer effects CTUh 1.66E+05 9.97E+04 2.75E+03 2.68E+05
Particulate matter kg PM2.5 eq 1.91E+08 5.02E+08 -1.02E+08 5.91E+08
Ionizing radiation HH kBq U235 eq 2.96E+10 8.83E+10 -3.96E+09 1.14E+11
Ionizing radiation E (interim) CTUe 7.87E+04 4.89E+05 -1.25E+04 5.55E+05
Photochemical ozone formation kg NMVOC eq 1.17E+09 4.49E+09 -4.07E+08 5.26E+09
Acidification molc H+ eq 1.63E+09 3.66E+09 -9.17E+08 4.38E+09
Terrestrial eutrophication molc N eq 2.84E+09 1.22E+10 -1.15E+09 1.39E+10
Freshwater eutrophication kg P eq 1.25E+08 4.72E+07 -5.74E+07 1.15E+08
Marine eutrophication kg N eq 2.70E+08 1.24E+09 -6.49E+07 1.44E+09
Freshwater ecotoxicity CTUe 4.92E+12 1.77E+12 1.36E+12 8.05E+12
Land use kg C deficit 7.53E+11 4.01E+12 -6.40E+10 4.70E+12
Water resource depletion m3 water eq 2.57E+11 1.97E+11 -1.06E+11 3.49E+11
Mineral, fossil & ren resource depletion kg Sb eq 6.82E+07 1.21E+07 4.18E+07 1.22E+08
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
Clim
ate
chan
ge
Ozo
ne
dep
leti
on
Hu
man
to
xici
ty, c
ance
r ef
fect
s
Hu
man
to
xici
ty, n
on
-can
cer
effe
cts
Par
ticu
late
mat
ter
Ion
izin
g ra
dia
tio
n H
H
Ion
izin
g ra
dia
tio
n E
(in
teri
m)
Ph
oto
chem
ical
ozo
ne
form
atio
n
Aci
dif
icat
ion
Terr
est
rial
eu
tro
ph
icat
ion
Fre
shw
ater
eu
tro
ph
icat
ion
Mar
ine
eutr
op
hic
atio
n
Fre
shw
ater
eco
toxi
city
Lan
d u
se
Wat
er r
eso
urc
e d
eple
tio
n
Min
eral
, fo
ssil
& r
en r
eso
urc
e…Per
cen
tage
of
imp
acts
End-of-life [EOL]
Vehicle maintenance [Use]
Vehicle usage [Use]
Fuel production pathway [Use]
Vehicle production [Production]
Infrastructure [Production]
69
3.4.3 Results overall of environmental impact of mobility for one EU citizen
The average mobility impacts per EU citizen were also quantified and are presented in Table 24.
Table 24 Environmental impacts per average EU27 citizen in 2010, from the mobility basket-
of-products
Impact category Mobility
Climate change kg CO2 eq 2.91E+03
Ozone depletion kg CFC-11 eq 2.06E-04
Human toxicity, cancer effects CTUh 7.19E-05
Human toxicity, non-cancer effects CTUh 5.38E-04
Particulate matter kg PM2.5 eq 1.18E+00
Ionizing radiation HH kBq U235 eq 2.28E+02
Ionizing radiation E (interim) CTUe 1.11E-03
Photochemical ozone formation kg NMVOC eq 1.05E+01
Acidification molc H+ eq 8.78E+00
Terrestrial eutrophication molc N eq 2.79E+01
Freshwater eutrophication kg P eq 2.31E-01
Marine eutrophication kg N eq 2.89E+00
Freshwater ecotoxicity CTUe 1.61E+04
Land use kg C deficit 9.42E+03
Water resource depletion m3 water eq 6.98E+02
Mineral, fossil & ren resource depletion kg Sb eq 2.44E-01
A more complete description of the environmental impacts per EU27 citizen and by mobility sub-product,
aggregated by mobility product and life cycle stage is shown in Table 25, Table 26 and Table 27,
respectively.
70
Table 25 Environmental impacts in 2010 per average EU27 citizen, from each mobility sub-products
Sub-
product
Climate
change
Ozone
depletion
Human
toxicity,
cancer
effects
Human
toxicity,
non-cancer
effects
Particulate
matter
Ionizing
radiation HH
Ionizing
radiation E
(interim)
Photochemical
ozone
formation
Acidifi-
cation
Terrestrial
eutrophi-
cation
Freshwater
eutrophi-
cation
Marine
eutrophi-
cation
Freshwater
ecotoxicity Land use
Water
resource
depletion
Mineral, fossil
& ren
resource
depletion
kg CO2 eq kg CFC-11
eq CTUh CTUh kg PM2.5 eq
kBq U235
eq CTUe kg NMVOC eq molc H+ eq molc N eq kg P eq kg N eq CTUe kg C deficit
m3 water
eq kg Sb eq
SP 1 4.49E+02 3.11E-05 1.18E-05 7.59E-05 1.39E-01 3.27E+01 1.65E-04 1.07E+00 9.76E-01 2.04E+00 3.29E-02 2.02E-01 2.70E+03 4.39E+02 8.82E+01 4.33E-02
SP 2 7.99E+01 5.67E-06 2.12E-06 1.41E-05 2.48E-02 5.83E+00 3.01E-05 1.81E-01 1.62E-01 3.13E-01 5.77E-03 3.15E-02 5.09E+02 7.81E+01 1.49E+01 8.07E-03
SP 3 5.29E+01 3.75E-06 1.41E-06 9.32E-06 1.64E-02 3.86E+00 1.99E-05 1.19E-01 1.06E-01 1.99E-01 3.82E-03 2.01E-02 3.37E+02 5.17E+01 9.88E+00 5.35E-03
SP 4 4.85E+02 3.45E-05 1.33E-05 8.80E-05 1.50E-01 3.55E+01 1.83E-04 1.10E+00 1.02E+00 2.06E+00 3.61E-02 2.06E-01 3.19E+03 4.77E+02 9.26E+01 5.07E-02
SP 5 8.34E+01 6.01E-06 2.52E-06 1.66E-05 2.74E-02 6.27E+00 3.17E-05 1.87E-01 1.74E-01 3.31E-01 6.75E-03 3.39E-02 6.05E+02 8.64E+01 1.72E+01 9.66E-03
SP 6 5.51E+01 3.97E-06 1.67E-06 1.10E-05 1.81E-02 4.15E+00 2.09E-05 1.23E-01 1.14E-01 2.12E-01 4.47E-03 2.17E-02 4.00E+02 5.71E+01 1.14E+01 6.39E-03
SP 7 1.15E+02 8.15E-06 3.09E-06 2.02E-05 3.49E-02 8.38E+00 4.33E-05 2.52E-01 2.38E-01 4.73E-01 8.34E-03 4.75E-02 7.33E+02 1.11E+02 2.14E+01 1.17E-02
SP 8 2.26E+01 1.60E-06 5.91E-07 3.91E-06 6.77E-03 1.64E+00 8.52E-06 4.77E-02 4.51E-02 8.38E-02 1.60E-03 8.48E-03 1.41E+02 2.16E+01 4.15E+00 2.24E-03
SP 9 1.50E+01 1.06E-06 3.91E-07 2.58E-06 4.49E-03 1.09E+00 5.63E-06 3.13E-02 2.95E-02 5.37E-02 1.06E-03 5.45E-03 9.32E+01 1.43E+01 2.74E+00 1.48E-03
SP 10 4.69E+02 3.41E-05 1.49E-05 1.38E-04 3.77E-01 3.63E+01 1.80E-04 1.36E+00 1.36E+00 4.39E+00 3.91E-02 5.49E-01 3.51E+03 3.99E+03 9.94E+01 5.37E-02
SP 11 8.17E+01 6.01E-06 2.81E-06 2.54E-05 5.19E-02 6.49E+00 3.17E-05 2.06E-01 2.16E-01 6.21E-01 7.33E-03 8.23E-02 6.65E+02 6.95E+02 1.86E+01 1.02E-02
SP 12 5.41E+01 3.97E-06 1.86E-06 1.68E-05 2.28E-02 4.29E+00 2.08E-05 1.37E-01 1.43E-01 4.15E-01 4.85E-03 5.49E-02 4.41E+02 4.59E+02 1.23E+01 6.75E-03
SP 13 1.46E+02 1.06E-05 4.71E-06 4.33E-05 1.05E-01 1.13E+01 5.59E-05 3.99E-01 4.07E-01 1.26E+00 1.23E-02 1.61E-01 1.11E+03 1.24E+03 3.13E+01 1.70E-02
SP 14 2.83E+01 2.04E-06 9.00E-07 8.34E-06 1.60E-02 2.18E+00 1.08E-05 6.73E-02 7.15E-02 2.02E-01 2.36E-03 2.74E-02 2.12E+02 2.40E+02 5.99E+00 3.25E-03
SP 15 1.87E+01 1.36E-06 5.95E-07 5.51E-06 7.27E-03 1.45E+00 7.17E-06 4.23E-02 4.57E-02 1.25E-01 1.56E-03 1.72E-02 1.40E+02 1.59E+02 3.97E+00 2.14E-03
SP 16 2.79E+01 2.24E-06 1.46E-06 9.54E-06 1.27E-02 2.54E+00 1.12E-05 7.43E-02 6.95E-02 1.46E-01 3.79E-03 1.56E-02 3.59E+02 4.03E+01 9.28E+00 5.79E-03
SP 17 8.88E+01 6.73E-06 5.75E-07 1.46E-05 4.11E-02 5.49E+00 3.15E-05 9.24E-01 7.35E-01 3.67E+00 2.79E-03 3.63E-01 1.98E+02 7.55E+02 1.04E+01 1.53E-03
SP 18 8.34E+00 6.95E-07 5.71E-08 1.48E-06 3.91E-03 5.71E-01 3.31E-06 8.60E-02 6.93E-02 3.41E-01 2.74E-04 3.41E-02 1.86E+01 8.03E+01 1.01E+00 1.43E-04
SP 19 8.58E+00 1.29E-06 7.61E-08 4.97E-07 1.16E-03 3.87E-01 1.56E-06 8.34E-03 1.32E-02 2.16E-02 4.61E-04 1.71E-03 1.66E+01 4.41E+00 1.11E+00 1.29E-04
SP 20 9.12E+00 5.71E-07 1.78E-07 1.46E-06 3.03E-03 5.59E-01 3.15E-06 2.44E-01 2.89E-02 1.01E-01 3.79E-04 9.82E-03 6.33E+01 6.83E+00 1.12E+00 7.57E-04
SP 21 7.03E+00 4.39E-07 9.44E-08 7.99E-07 2.26E-03 4.15E-01 2.42E-06 1.95E-01 2.18E-02 7.89E-02 2.20E-04 7.41E-03 3.09E+01 4.67E+00 6.95E-01 3.61E-04
SP 22 2.28E+01 1.41E-06 2.22E-07 1.96E-06 7.19E-03 1.31E+00 7.81E-06 6.43E-01 7.01E-02 2.56E-01 5.71E-04 2.36E-02 6.55E+01 1.39E+01 1.92E+00 7.39E-04
SP 23 5.31E+01 4.19E-06 4.19E-06 1.57E-05 1.79E-02 2.42E+01 4.09E-05 1.13E-01 2.42E-01 3.89E-01 4.43E-02 4.43E-02 4.07E+02 4.99E+01 1.99E+02 1.21E-03
SP 24 1.82E+01 1.14E-06 4.81E-07 1.37E-06 1.07E-02 1.23E+00 6.55E-06 2.74E-01 2.06E-01 1.02E+00 1.20E-03 9.34E-02 3.01E+01 2.12E+01 4.01E+00 4.31E-04
SP 25 5.11E+01 3.39E-06 1.59E-07 9.80E-07 7.77E-03 2.93E+00 1.88E-05 2.62E-01 2.18E-01 9.08E-01 6.27E-04 8.29E-02 1.25E+01 2.89E+01 2.64E+00 1.23E-04
SP 26 2.12E+02 1.41E-05 6.79E-07 4.21E-06 3.27E-02 1.23E+01 7.85E-05 1.10E+00 9.14E-01 3.79E+00 2.79E-03 3.47E-01 5.45E+01 1.22E+02 1.17E+01 5.97E-04
SP 27 2.49E+02 1.65E-05 1.01E-06 6.25E-06 4.21E-02 1.50E+01 9.24E-05 1.28E+00 1.08E+00 4.40E+00 5.18E-03 4.03E-01 9.54E+01 1.57E+02 2.17E+01 7.08E-04
Total 2.91E+03 2.07E-04 7.19E-05 5.38E-04 1.18E+00 2.28E+02 1.11E-03 1.05E+01 8.78E+00 2.79E+01 2.31E-01 2.89E+00 1.61E+04 9.40E+03 6.98E+02 2.44E-01
71
Table 26 Disaggregation of environmental impacts per average EU27 citizen in 2010, by mobility
product
Impact category Mobility products
Passenger cars 2W Buses Rail Air
Climate change kg CO2 eq 2.18E+03 3.89E+01 1.06E+02 7.13E+01 5.14E+02
Ozone depletion kg CFC-11 eq 1.56E-04 2.42E-06 8.72E-06 5.32E-06 3.40E-05
Human toxicity, cancer effects CTUh 6.42E-05 4.95E-07 7.08E-07 4.66E-06 1.85E-06
Human toxicity, non-cancer
effects CTUh 4.88E-04 4.21E-06 1.66E-05 1.71E-05 1.14E-05
Particulate matter kg PM2.5 eq 1.01E+00 1.25E-02 4.62E-02 2.86E-02 8.26E-02
Ionizing radiation HH kBq U235 eq 1.64E+02 2.28E+00 6.44E+00 2.54E+01 3.03E+01
Ionizing radiation E (interim) CTUe 8.25E-04 1.34E-05 3.63E-05 4.75E-05 1.90E-04
Photochemical ozone
formation kg NMVOC eq 5.40E+00 1.08E+00 1.02E+00 3.88E-01 2.64E+00
Acidification molc H+ eq 5.18E+00 1.21E-01 8.17E-01 4.47E-01 2.21E+00
Terrestrial eutrophication molc N eq 1.29E+01 4.37E-01 4.04E+00 1.41E+00 9.09E+00
Freshwater eutrophication kg P eq 1.72E-01 1.17E-03 3.51E-03 4.55E-02 8.59E-03
Marine eutrophication kg N eq 1.48E+00 4.09E-02 3.99E-01 1.37E-01 8.32E-01
Freshwater ecotoxicity CTUe 1.51E+04 1.60E+02 2.33E+02 4.37E+02 1.62E+02
Land use kg C deficit 8.17E+03 2.54E+01 8.41E+02 7.10E+01 3.08E+02
Water resource depletion m3 water eq 4.43E+02 3.74E+00 1.25E+01 2.03E+02 3.61E+01
Mineral, fossil & ren resource
depletion kg Sb eq 2.38E-01 1.86E-03 1.80E-03 1.64E-03 1.43E-03
Table 27 Environmental impacts from the mobility basket-of-products per average EU27 citizen in
2010, by life stage
Impact category LC stage
LCI Total
Production Use EOL
Climate change kg CO2 eq 4.00E+02 2.71E+03 -2.01E+02 2.91E+03
Ozone depletion kg CFC-11 eq 4.21E-05 1.74E-04 -9.18E-06 2.06E-04
Human toxicity, cancer effects CTUh 9.81E-05 1.48E-05 -4.10E-05 7.19E-05
Human toxicity, non-cancer effects CTUh 3.32E-04 2.00E-04 5.50E-06 5.38E-04
Particulate matter kg PM2.5 eq 3.83E-01 1.01E+00 -2.04E-01 1.18E+00
Ionizing radiation HH kBq U235 eq 5.93E+01 1.77E+02 -7.94E+00 2.28E+02
Ionizing radiation E (interim) CTUe 1.58E-04 9.79E-04 -2.50E-05 1.11E-03
Photochemical ozone formation kg NMVOC eq 2.35E+00 8.99E+00 -8.16E-01 1.05E+01
Acidification molc H+ eq 3.28E+00 7.34E+00 -1.84E+00 8.78E+00
Terrestrial eutrophication molc N eq 5.70E+00 2.45E+01 -2.30E+00 2.79E+01
Freshwater eutrophication kg P eq 2.51E-01 9.45E-02 -1.15E-01 2.31E-01
Marine eutrophication kg N eq 5.41E-01 2.48E+00 -1.30E-01 2.89E+00
Freshwater ecotoxicity CTUe 9.85E+03 3.54E+03 2.73E+03 1.61E+04
Land use kg C deficit 1.51E+03 8.04E+03 -1.28E+02 9.42E+03
Water resource depletion m3 water eq 5.14E+02 3.96E+02 -2.12E+02 6.98E+02
Mineral, fossil & ren resource depletion kg Sb eq 1.37E-01 2.42E-02 8.37E-02 2.44E-01
72
To more accurately compare the environmental impacts, a normalization was performed using the reference
Product Environmental Footprint [20], as is presented in Table 28.
Table 28 Normalization factors
Impact category Normalization factors
(Domestic)
Climate change kg CO2 eq 4.55E+12
Ozone depletion kg CFC-11 eq 1.08E+07
Human toxicity, cancer effects CTUh 1.84E+04
Human toxicity, non-cancer effects CTUh 2.66E+05
Particulate matter kg PM2.5 eq 2.41E+09
Ionizing radiation HH kBq U235 eq 5.64E+11
Ionizing radiation E (interim) CTUe N/A
Photochemical ozone formation kg NMVOC eq 1.59E+10
Acidification molc H+ eq 2.36E+10
Terrestrial eutrophication molc N eq 8.73E+10
Freshwater eutrophication kg P eq 7.41E+08
Marine eutrophication kg N eq 8.42E+09
Freshwater ecotoxicity CTUe 4.36E+12
Land use kg C deficit 3.15E+14
Water resource depletion m3 water eq 3.95E+10
Mineral, fossil & ren resource depletion kg Sb eq 5.03E+07
The normalized results are presented in Table 29, with the red colour representing very relevant impacts, the
yellow colour representing relevant impacts and the green colour representing slightly relevant impacts, with
the remaining being not relevant. As can be seen, while the Use stage was found to be the most relevant in
many of the environmental impact categories, the Production stage is the most relevant in the categories which
are above the normalization factors for the EU27.
Table 29 Normalized environmental impacts, disaggregated between life-cycle stages
Impact category Production Use End-of-life Total
Climate change 0.044 0.298 -0.022 0.319
Ozone depletion 0.002 0.008 0.000 0.010
Human toxicity, cancer effects 2.660 0.402 -1.112 1.950
Human toxicity, non-cancer effects 0.624 0.375 0.010 1.009
Particulate matter 0.079 0.208 -0.042 0.245
Ionizing radiation HH 0.052 0.157 -0.007 0.202
Ionizing radiation E (interim) N/A N/A N/A 0.000
Photochemical ozone formation 0.074 0.282 -0.026 0.331
Acidification 0.069 0.155 -0.039 0.186
Terrestrial eutrophication 0.033 0.140 -0.013 0.160
Freshwater eutrophication 0.169 0.064 -0.077 0.155
Marine eutrophication 0.032 0.147 -0.008 0.172
Freshwater ecotoxicity 1.128 0.406 0.313 1.846
Land use 0.002 0.013 0.000 0.015
Water resource depletion 6.497 4.999 -2.673 8.824
Mineral, fossil & ren resource depletion 1.356 0.240 0.830 2.426
73
Colour scales - red: impacts above 1; yellow: impacts below 1 and above 0.25; red: impacts below 0.25 and
above 0.05; no colour: impacts below 0.5.
3.5 Interpretation of the results
The basket-of-products for mobility was defined as consisting of five products: passenger cars, two wheelers,
buses, rail and air. Each product was divided in sub-products, resulting in a total of 76 sub-products. For
modelling purposes of the environmental impacts, the number of processes considered was reduced to 27 for
the Use stage and 11 for the Production and End-of-life stages.
The analysis showed that the Use stage is a large contributor for the environmental impacts of the total EU27
mobility needs, being responsible for between 10% and 87% of different environmental impact categories. On
the other hand, the End-of-life stage was found to enable the avoidance of up to 36% of the environmental
impacts in some categories. However, it was found that the Production stage was the main responsible in the
impact categories which are well above the normalization factors for the EU27, which are classified as very
relevant impacts.
Concerning the individual products assessment, passenger cars were found to have the largest share of the
total environmental impacts (46 to 97%), followed by air transport (1 to 33%) and rail transport (1 to 29%).
This follows closely the distribution of passenger-kilometers by transportation mode calculated for the EU27.
To improve the environmental impacts of the mobility basket-of-products, different actions can be further
studied and promoted in the different life-cycle stages considered, as presented in Figure 28.
Figure 28 Policy options for the life-cycle stages considered
The Production stage is shown to have an important share in the total environmental impacts of the mobility
basket-of-products. To promote light-weighting or changing the materials composition in the vehicle
components to more sustainable options will have a definite impact in the vehicle’s environmental results [21].
However, these changes are highly influenced by the materials price competitiveness, which may hamper its
widespread adoption. Furthermore, more sustainable vehicle production facilities may be a further step on the
reduction of the environmental impacts. Good examples in this topic start to arise, namely the BMW electric
vehicle production facilities in Leipzig [22] aiming for maximum efficiency of resources throughout the whole
value added chain.
When considering the Usage stage, vehicles’ energy efficiency is currently addressed by the CO2 target
reduction to 130 g/vkm by 2015 and 95 g/vkm by 2021 [23] in new vehicle sales. The current EU27 vehicle
stock is still far from these values, with an average 276 g/vkm for the passenger cars analysed. Another
possibility in the usage stage is to promote the reduction of vkm, either by increasing occupancy factor, with
measures such as promoting high occupancy vehicle (HOV) lanes, or by promoting a modal shift to more
sustainable transport modes (e.g. train, soft modes such as walking and biking). Reducing the environmental
impacts of fuel production, by increasing the use of CHP, retrofitting/replacing equipment or improving the
processes that are used, can also provide significant benefits.
In the End-of-life stage, the promotion of more ambitious waste treatment scenarios will also lead to a
reduction in the environmental impacts of the mobility basket-of-products, mainly by increasing the amount
of avoided impacts. With the average EU27 at an 87.2% of Recovery and Reuse of cars in 2010, the
implementation of a higher target would lead to improvements in this area. Currently, the EU directive specifies
an overall 95% of Recovery and Reuse [19] in 2015.
Production
• Light-weighting and more sustainable materials
• More efficient vehicle production facilities
Use
• Improve fuel efficiency
• Reduce vkm
• Promote alternative energy sources
• Reduce impacts of fuel production
End-of-life
• Stricter end-of-life waste treatment guidelines
74
Overall, the shift from conventional internal combustion engine vehicles to hybrid or electric vehicles could
support the reduction of the environmental impacts in the road transportation sector [24]. Nonetheless, the
possible benefits to be obtained from this shift are highly dependent on the energy sources used for electricity
production, as in the cases in which the electricity for the electric vehicles is produced from fossil fuels the
total impacts might increase [25]. Furthermore, the use of electric vehicles results in an increase of the
environmental impacts of the production stage [25], which is already the most relevant stage in the impact
categories in which the estimated environmental impacts are already above the normalization values for the
EU27. A comprehensive strategy for the transportation, electricity, electronic and metal industry sectors is
therefore required to maximize the potential benefits from shifting to these alternative vehicles [26].
All the presented options related to the vehicle itself are highly influenced by the vehicles’ turnover rates (of
over a decade), which may mean that policy options influencing the amount of vehicle usage, mainly of
passenger cars, may have more immediate results.
Finally, future work should be developed on a country by country analysis with more detailed and accurate
assumptions. Future scenarios should be tested, by considering different compositions of the basket-of-
product, and quantifying the previously mentioned policy options, to estimate the potential environmental
impacts of possible scenarios for the evolution of the mobility sector. A detailed sensitivity analysis should be
performed, possibly considering also best and worst values for each product.
3.6 References
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final, 2010.
2. European Commission, Making sustainable consumption and production a reality. A guide for business and policy
makers to Life Cycle Thinking and Assessment. European Commission, 2010, Joint Research Centre, Institute for
Environment and Sustainability,.
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2007.
8. European Commission, Annual Analyses of the EU Air Transport Market 2010 - Final Report, 2011.
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2013 and revised February 2014., 2014.
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emissions from road transport, 2014, ETC/AEM.
13. EEA, EMEP/EEA emission inventory guidebook 2013, 2013, European Environment Agency.
14. IEA, World Energy Outlook 2012 by International Energy Agency, 2012.
15. EU, Directive 2003/30/EC on the promotion of the use of biofuels or other renewable fuels for transport. , 2003.
16. EU, RED Directive - DIRECTIVE 2009/28/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 23 April
2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives
2001/77/EC and 2003/30/EC, 2009.
17. GHK, B.I.S., A study to examine the benefits of the End of Life Vehicles Directive and the costs and benefits of a
revision of the 2015 targets for recycling, re-use and recovery under the ELV Directive, 2006.
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19. EU, DIRECTIVE 2000/53/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 18 September 2000 on end-
of life vehicles, 2000.
75
20. EU, Product Environmental Footprint Pilot Guidance, Guidance for the implementation of the EU Product
Environmental Footprint (PEF) during the Environmental Footprint (EF) pilot phase - Version 4.0, 2014.
21. Mayyas, A., A. Qattawi, and M. Oma, Life cycle assessment-based selection for a sustainable lightweight body-in-
white design, Energy, 2012, 39(1), p. 412-425.
22. BMW, Manufacturing facilities, Leipzig plant, 2014 Available from: http://www.bmw-werk-
leipzig.de/leipzig/deutsch/lowband/com/en/index.html.
23. EU, Proposal 2007/0297 for a Regulation of the European Parliament and the Council Setting emission
performance standards for new passenger cars as part of the Community's integrated approach to reduce CO2 emissions
from light-duty vehicles, 2007.
24. Faria, R., et al., Impact of the electricity mix and use profile in the life-cycle assessment of electric vehicles,
Renewable and Sustainable Energy Reviews, 2013, 24, p. 271–287.
25. Ma, H., et al., A new comparison between the life cycle greenhouse gas emissions of battery electric vehicles and
internal combustion vehicles, Energy Policy, 44, p. 160–173.
26. Hawkins, T., B. Singh, G. Majeau-Bettez, and A. Stomman, Comparative Environmental Life Cycle Assessment of
Conventional and Electric Vehicles, Journal of Industrial Ecology, 2012, 17(1), p. 53-64.
Abbreviations
2W Two wheelers
EOL End-of-life
EU European Union
EU27 European Union 27 countries
GDP Gross Domestic Product
ILCD International Reference Life Cycle Data System
LC Life-cycle
LCA Life-cycle assessment
LCI Life-cycle inventory
LO Lubricant oils
LPG Liquid petroleum gas
PE Polyethylene
PET Polyethylene terephthalate
pkm Passenger-kilometer
PP Polypropylene
PUR Polyurethane
PVC Polyvinyl chloride
RER Europe
RME Rape-seed methyl ester
ROW Rest of world
SP Sub-product
vkm Vehicle-kilometers travelled
vkmp Vehicle-kilometers for passengers transport
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4 Basket of Products: housing
4.1 Introduction
The basket-of-products approach matches statistics on private consumption of housing per capita with life
cycle inventory (LCI) for each product (dwelling). The objective is to identify, through representative products,
the average environmental impact of a citizen in EU-27 in 2010, identifying the impact of the different
representative products and therefore having the possibility to define targets for improvement.
Each representative product (dwelling) is a LCI dataset, containing different datasets related to sub-products
(building materials) and processes (e.g. energy production, waste treatment). The system boundary
encompasses a cradle-to-grave approach. The representative product’s datasets contain all environmentally
relevant flows of resources from and emissions to the natural environmental across the entire life cycle of the
product, from raw material extraction through production, construction, use, maintenance and disposal (end-
of-life).
Once the macro statistics and life cycle inventories have been matched, the potential impacts on the
environment were calculated using impact assessment methods, following the recommendation of ILCD
handbook.
Double counting can occur within the basket-of-products for certain products for e.g. housing and food. The
approach taken to avoid double counting is the following: for flows which are listed under the consumption
category food, the energy and material consumption and waste generation during their use stage are
subtracted from the use stage of a house (e.g. energy for cooking).
To define the impacts per year, the impacts of the production-construction-use-maintenance-EOL stages were
annualized over the lifetime of the product (dwelling). The annualized impacts were then multiplied for the
total number of dwelling of that type and divided by EU-27 population in order to derive total annualized
impacts per capita (for one EU citizen in 2010) by representative product (dwelling).
4.2 Definition of the basket of products for housing
The present report focuses on the stock of permanently occupied dwellings, because the ultimate goal is the
assessment of consumption for housing related to the person, and the housing of the person is his main
residence, the permanently occupied dwelling.
It is important to note that also the statistics are related only to permanently occupied dwellings (few data are
available on vacant dwellings and second homes) and that the "consumptions of the use phase" (especially
those that are related to energy, which are the most important) are only related to the actual use in permanent
dwellings. Therefore, the assessment does not consider:
• vacant dwellings and second homes,
• shelter for homeless and vulnerable people without a home.
A dwelling is defined as a unit of accommodation, such as a building (for example a single family house) or a
part of a building (for example an apartment in a multifamily house). The path to define the average value of
impacts related to housing for each citizen of EU-27 in a year (2010) starts from the definition of
representative products in the category of housing. In order to identify the most representative products for
housing to be included in the basket-of-products, data regarding housing stock was analysed: it was carried
out a quantitative and qualitative analysis of the structure of the housing in the years 2000-2010. It is very
hard to define the aggregate categories of buildings for "classifying” them in product groups and to define then
a representative product for each category. The reasons are several:
• even if materials, components and processes in the building sector can be standardized, building is not a
standardized (repeatable) product (each building is unique);
• a building is a complex product, made by quite a number of (sub)products combined in a different way in
each building, so each building has different characteristics;
77
• buildings are site-specific; their use phase changes in relation to the climate (i.e. the same object in
different places changes its energy consumption);
• the building is a long-lasting good with a long life; the use phase of the building is the one with the highest
impacts, but it is also the phase with the highest variability from building to building.
In the building sector there isn’t a common way to sort the buildings by different types and the possibility of
aggregation for families is very large (also in statistical data there are different interpretations of the
categories). Different physical characteristics could be used to “classify” buildings, and each of them can have
great variability. For example:
• the building typology (e.g. detached house, terraced house, multifamily house, high rise buildings)
• the building size
• the number of flats in the building
• the number of floors
• the surface-area-to-volume ratio S/V
• the dwelling size in square meters
• the constructive technology
• the Wall to Window Ratio WWR
• the thermal insulation level, U-value
• the heating systems
• the dimensions of underground spaces.
These physical characteristics are related to other aspects, such as:
• number of inhabitants
• the period of construction of the dwelling
• the residual life
• the climate and Heating Degree Days.
All these characteristics affect the environmental impacts of a dwelling, and in particular the heating energy
consumption in the use phase. Each of these characteristics combine many variables, and each variable
radically change the environmental impacts of a building. Being impossible to model all the variables, it was
decided to restrict them to the ones for which it is possible to find statistical data of the related quantity of
housing stock.
4.2.1 Data Sources
A first screening for statistical data collection has been conducted using the Eurostat database. Another useful
source was the report “Housing Statistics in the European Union 2010” (Delft University of Technology, 2010).
The most detailed information for housing are available from the results of several European researches
Intelligent Energy Europe (IEE Projects): ENTRANZE, ODYSSEE, TABULA and EPISCOPE (co-founded by the
Intelligent Energy Europe Programme of the European Union). The aim of these studies is to quantify the
building stock and classify it by period of construction and physical characteristics, relating the characteristics
to energy consumption in the use phase. All data collected in these studies were from national statistics.
For the scope of this report, the most useful data were found in the Data Hub elaborated by the Buildings
Performance Institute Europe (BPIE), a not-for-profit think tank that supports several IEE and FP7 European
Projects, collecting data related to the quantity and quality of the building stock and related to energy
performance of buildings, from national statistics and studies.
It has to be noted that data change among the different data sources, including the official ones. Very few
reports cover all information needed, so different sources have been combined. The analysis of the available
statistical data showed different way of aggregating data from country to country. This is partly explained by
different building classification rules.
It was not always possible to find data related to the object of investigation of this study, namely the reference
year 2010 and the reference countries of EU-27. It should however be noted that the average value of
statistical data (e.g. square meters of a dwelling) fluctuates very little from year to year and considering two
78
countries more or two countries less (for example, EU-27 or EU-29). So, data related to EU-29 and to 2008
were used where there were no data available for EU-27 in 2010.
4.2.2 Assumptions
The variables of housing characteristics were restricted to those for which it was possible to find statistical
data of the distribution of housing stock. From the statistical data analysis emerged that a possible
classification of the housing stock could be done by dwelling type, period of construction and climate area.
As concerns the selection of dwelling type and building typology, dwelling type can be classified as:
• Single Family House (SHF);
• Apartment in a Multi-Family House (MFH).
Statistical data on the quantity of Single Family and Multi-Family House in EU-27 in 2010 are available, so this
classification can support the definition of the product groups.
To define the representative products in each product group it is possible to identify different types of building
for each category of dwelling.
For Single Family House the building typology can be:
• Detached House, that are individual houses inhabited by one family;
• Semi-Detached Houses, that consists of pairs of houses built side by side sharing a party wall;
• Terraced Houses, where a row of identical houses share side walls.
In Multi-Family Houses, multiple separate housing units for residential inhabitants (flats) are contained within
one building.
For Multi-Family House the building typology can be:
• Multi-Family House with less than 10 dwellings
• Multi-Family House with 10 or more dwellings (low-rise)
• Multi-Family House with 10 or more dwellings (high-rise).
In statistical data there is a quantification of dwellings in Single Family Houses and flats in Multi-Family Houses,
but there are no statistical data on the distribution (quantity) of the total Single Family Houses and Multi-
Family Houses by building typology.
Multi-Family Houses can vary greatly in relation to the number of flats and the number of floors. There are no
statistical data to identify the number of buildings in relation to the size.
So, for each product group, one dwelling in a representative building of the group is chosen as the
representative “product” for the group, based on its greater diffusion (even if not supported by the knowledge
of the actual number):
• a Detached House for the product group Single Family House, knowing that 34.4% of the EU-27 population
live in detached houses (Eurostat);
• an apartment in a Multi-Family House low-rise with more than 10 dwellings for the product group
apartment in a Multi-Family House (the diffusion of this building typology is evident even if the exact
quantification is not supported by statistical data).
These two building types are representative of different size and different Surface-area-to-volume ratio. The
environmental impacts per capita in relation to housing change very much in relation to the size of the dwelling
(dwelling type) and therefore to the square meters/person, and in relation to the overall shape of the building
in which the dwelling is located, based on optimizations of the relationship surface-area-to-volume ratio (S/V).
Regarding the selection of the context by climatic area, to be able to define representative products, a
simplification was therefore made, dividing Europe into three climatic zones (Figure 29) in relation to the
average Heating Degree Day (HDD) of each country:
• climatic zone 1, warm climate, 500-2300 HDD
• climatic zone 2, moderate climate, 2301-4000 HDD
79
• climatic zone 3, cold climate, 4001-6000 HDD.
The subdivision in three climatic zone has already been adopted by other studies (Ecofys, 2007; JRC/IPTS,
“IMPRO-Building”, 2008) and reflects the changes of Heating Degree Days related to latitude (35°-45°; 45°-
55° and 55°-70°).
This subdivision does not fully catch the differences of climate in each climatic zone (for example, it must be
taken into account that in Italy, in the Alps, there is the same climate of northern Europe). Both macroclimate
(region) and microclimate (local) influence the energy consumption of the building. In particular it should be
noted that altitude, landscape, presence of water streams, presence of obstructions to solar radiation affect
the microclimate in terms of temperature, relative humidity, solar radiation, sunshine, wind direction. So the
variables of the building (physical characteristics), added to the variables related to the characteristics of the
context, open to virtually infinite possible combinations. The context strongly influences the use phase of the
building, especially from the point of view of energy consumption for heating. The national average Heating
Degree Days, however, return the variation in existing climate at different latitudes that affects the average
heating energy consumption of buildings of the different countries. In any case, it should be emphasized that
in this study the energy consumption in the use phase was not calculated on the basis of national average
degree-days but on the basis of actual energy consumption (for each state).
With reference to the selection of building period of construction, depending on the availability of statistical
data on the distribution of the housing stock by period of construction, four period groups (
Table 30) were chosen and aggregated according to the technological shifts/innovations (single-double glazing,
thickness of insulating materials, radiators-radiant floors, etc.) and to the increasing attention to energy
consumption: before 1945, 1945-1969, 1970-1989, 1990-2008.
Figure 29 Climatic zones in EU-27 and heating degree days. Source: authors.
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The building age influences the environmental impacts for the following aspects:
• construction (or renovation) impacts (related to construction technologies)
• energy consumption for heating (i.e. thermal performance of the envelope).
Concerning the selection of building technology, typical construction technologies were selected considering
the period of construction of the building and the different climatic zone. The distribution of the building stock
by climatic zone and period of construction is related to different technologies (especially for the building
envelope), different levels of insulation (U-value) and different systems (efficiency of heating systems) that
affect different energy consumption levels in the use phase.
The reference study to define the typical technology of each period and climatic zone was the research TABULA,
founded by Intelligent Energy Europe Program. No representative technologies for the period group before
1945 was selected because this stock is too heterogeneous in the constructive and physical characteristics (it
includes also historical buildings). So the same characteristics of the period 1945-1969 have been assumed
because there wasn’t a relevant change in the use of building materials (that could be considered a valid
assumption for the stock of the period 1900-1945; for the period before 1900 is very difficult to define a
representative technology because it include historical buildings).
All the envelope technical solutions of the representative buildings were sized and defined in the materials in
relation to the thermal average U-value defined in the statistical sources: BPIE data were assumed for the
average transmittance of walls, roof and floor (bottom) and TABULA data were assumed for the average
transmittance of the windows.
Table 30 Distribution of dwellings by period of construction and climatic zone. Source: reworking
of authors (aggregated data) from ENTRANZE. For Latvia only total number of dwellings were
available, so the total number has been divided by period in equal parts.
For the representative products, the heavy construction (concrete structure and bricks envelope) has been
assumed as “typical” solution in EU-27 context in the warm and moderate climate and in the cold climate for
Multi-Family House, instead the light construction (wood structure and wood frame with insulation and
prefabricated panels as covering for the envelope) has been assumed as typical in the cold climate for Single
Malta dwellings 27,353 23,791 34,953 20,367 dwellings 3,612 8,672 10,881 12,211
Cyprus dwellings 9,962 28,902 70,541 105,742 dwellings 146 3,471 28,920 51,592
Portugal dwellings 377,999 446,439 806,382 607,475 dwellings 136,257 249,221 639,602 530,345
Greece dwellings 132,365 481,723 677,673 264,760 dwellings 187,893 683,812 961,968 457,079
Spain dwellings 1,087,668 1,039,326 1,371,712 1,462,011 dwellings 1,098,207 2,846,361 3,869,173 3,966,923
Italy dwellings 2,354,731 1,920,087 2,068,582 555,600 dwellings 4,137,269 7,186,276 6,815,655 1,905,800
total by period dwellings 3,990,078 3,940,268 5,029,842 3,015,954 dwellings 5,563,385 10,977,814 12,326,198 6,923,950
total by climate zone dwellings dwellings
France dwellings 3,471,362 2,745,414 5,773,799 3,261,725 dwellings 3,485,856 2,121,534 3,563,895 2,615,016
Slovenia dwellings 87,114 56,858 79,084 53,238 dwellings 157,575 109,265 134,990 86,033
Hungary dwellings 322,595 641,359 1,051,934 463,112 dwellings 595,265 389,988 264,088 299,660
Romania dwellings 682,803 1,463,096 1,592,752 439,235 dwellings 81,740 752,197 2,181,501 157,823
Bulgaria dwellings 366,620 567,279 490,745 272,391 dwellings 69,248 335,035 525,394 455,288
Ireland dwellings 254,077 236,685 377,392 595,298 dwellings 23,790 15,452 21,119 125,596
Netherlands dwellings 1,145,056 1,200,193 1,518,797 1,011,956 dwellings 443,659 587,910 654,462 424,790
Belgium dwellings 1,367,357 759,643 771,429 431,571 dwellings 422,357 234,643 304,762 231,238
Luxembourg dwellings 41,612 30,654 30,086 17,648 dwellings 11,615 18,301 16,898 21,186
U. Kingdom dwellings 3,810,199 5,895,443 5,787,863 2,910,302 dwellings 701,762 616,248 1,564,014 1,253,385
Slovakia dwellings 281,089 215,703 190,784 161,424 dwellings 135,890 320,052 282,889 141,168
Germany dwellings 4,574,237 5,189,433 4,612,898 3,704,732 dwellings 3,906,371 7,683,325 6,646,956 2,892,118
Austria dwellings 381,000 517,000 536,000 358,000 dwellings 478,000 520,000 420,000 353,000
Czech Rep. dwellings 579,000 444,314 392,986 283,423 dwellings 354,195 873,225 768,060 302,447
Poland dwellings 1,178,000 1,342,308 1,270,286 1,637,406 dwellings 1,569,000 1,705,769 2,292,418 2,426,813
Denmark dwellings 511,253 436,092 397,715 233,940 dwellings 447,538 260,128 208,501 175,522
total by period dwellings 19,053,376 21,741,474 24,874,549 15,835,402 dwellings 12,883,862 16,543,072 19,849,947 11,961,082
total by climate zone dwellings dwellings
Lithuania dwellings 166,280 158,273 159,920 55,077 dwellings 229,214 264,380 396,512 107,262
Latvia dwellings 76,400 76,400 76,400 76,400 dwellings 170,652 170,652 170,652 170,652
Estonia dwellings 72,575 41,519 27,421 22,355 dwellings 49,618 139,120 244,848 55,744
Sweden dwellings 586,454 490,422 539,942 159,182 dwellings 760,574 731,226 582,800 320,400
Finland dwellings 235,296 356,598 454,454 316,652 dwellings 116,891 275,603 437,015 256,490
total by period dwellings 1,137,005 1,123,212 1,258,137 629,666 dwellings 1,326,949 1,580,981 1,831,828 910,548
total by climate zone dwellings dwellings
TOTAL EU dwellings dwellings
NUMBER OF DWELLINGS
4,148,020 5,820,958
101,628,962.06 102,850,268.28
81,504,800
unit <1945 1945-1969 1970-1989 1990-2008 unit <1945
Single Family House Multy-Family House
61,237,963
1945-1969 1970-1989 1990-2008
15,976,142 35,791,347
81
Family House (considering TABULA report, the output from interviews with local architects and the
characteristics of local material culture).
In heavy constructions the structural slabs are made of reinforced concrete and the envelope is made by bricks;
in warm climate the typical slabs are made of reinforced concrete with light precast bricks. In light construction
the structure is made by timber frames and the envelope is in wood frame.
In the Single Family Houses, pitched roof has always been assumed as the typical one (only after 1990, it was
assumed the transition to the flat roof). The attic space (between the roof and the last level floor) has always
been assumed not as living space (unheated) and, when insulation is present, it has been hypothesized to be a
layer of the last level floor. For warm climate, it was assumed that the structure of the sloped roof was made
by concrete and precast bricks, while in moderate and cold climate the pitched roof was assumed with wooden
beams and boards.
The internal walls were considered in bricks in warm climate and in wood frame with plasterboard (light
construction) in moderate and cold climate.
The insulation material chosen for all the representative products is rock wool, which (together with glass wool)
account for 60% of the market; organic foamy materials, expanded and extruded polystyrene and polyurethane
account only for 27% of the market (Papadopoulos, 2005).
For heating, the use of radiators up to 1990 in warm and moderate climates has been assumed. Since 1990,
the transition from radiators to radiant floor have been assumed. Between 1945 and 1970 the steel pipes of
the heating system increase for the change by radiators closest to the hallway (to save the pipes) to the
radiators sub-window (for improving the heat distribution and comfort).
In cold climate, the typical heating systems is related to electricity, so convector heaters have been
hypothesized.
As concerns the selection of dwelling size for each representative product, statistical data about the average
floor per dwelling by dwelling type (Single Family House and Multi-Family House), by climate (warm, moderate
and cold) and by period of construction were used to define the size (square meters) per dwelling of each
product (Table 32).
Starting from the national data, the average values by dwelling type and by period of construction related to
the three climatic zone were calculated. The calculation was done using a weighted average, taking into account
the number of dwellings in each country. The average floor area of each climate zone was also calculated as
the weighted average of the average floor of the different periods of construction.
These data, the size of dwellings in different climatic zones and in different periods of construction related to
the amount of dwellings (Table 32), were used for the development of the dwelling models (representative
products) and calculation of the total EU environmental impacts by representative product.
The average inhabitants by dwelling type, useful to calculate water and energy consumption in the use phase,
has been calculated from statistical data (Table 33). In 2010, 41.8% of the EU-27 population lived in the
apartment, just over a third (34.4%) in detached houses and 23.0% in semi-detached houses (Eurostat).
Starting from the total number of dwellings and known the distribution by climate zone and by period of
construction, with 24 building models (representative products) it is possible to cover the 100% of the dwelling
stock (Table 34).
Moderate climate is the most populated. Single Family Houses (SFH) and apartments in Multi-Family Houses
(MFH) are the same quantity (in number of dwellings). The distribution by period of construction is quite
homogeneous, with the largest number of dwellings in the period 1970-1989.
4.2.3 Final selection
According to data collected, the following criteria were defined:
• two dwelling types (Single Family House, Apartment in Multifamily House),
• four periods of construction (<1945, 1945-1969, 1970-1989, 1990-2010),
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• three climate areas (warm, moderate, cold).
From the combination of these variables 24 models were derived, 12 for Single Family House and 12 for Multi-
Family House (Table 35).
The detailed description of the characteristics of the representative products is shown in Table 36 and Table
37. For the products <1945, the same characteristics as the products of 1945-1969 were assumed, changing
only the energy consumption of the use phase.
The building models of the representative products were modelled with Archicad 15, a BIM software for
architecture that allows to model the building in 3D (Figure 30), define the characteristics of the building’s
element and quantify the volume of materials in the building (useful information to define the flows and
compile the LCI of the production and maintenance phases). It must be emphasized that, since the
characteristics of the buildings have been defined as average, the building models tend to be very similar
among them. For example, the size of housing in m2, having been derived from average data, fluctuates slightly
from one model to the other (e.g. 90-130 m2 for Multi-Family House), while in reality the size of the
accommodation can vary greatly (e.g. 60-150 m2 for Multi-Family House).
83
Table 31 Average floor area per dwelling by dwelling type, by climate zone and by period of
construction in EU-27. Source: reworking of authors (aggregated data) from ENTRANZE.
Table 32 Average floor area per dwelling by dwelling type, by climate zone and by period of
construction in EU-27 and relative number of dwellings. Source: reworking of authors (aggregated
data) from ENTRANZE
Malta m2/dwelling 99.00 99.00 99.00 99.00 m2/dwelling 85.00 85.00 85.00 85.00
Cyprus m2/dwelling n.a. n.a. n.a. n.a. m2/dwelling n.a. n.a. n.a. n.a.
Portugal m2/dwelling 86.58 89.57 119.18 149.71 m2/dwelling 77.50 86.72 95.77 107.32
Greece m2/dwelling 61.22 64.21 76.27 86.50 m2/dwelling 88.37 83.78 93.46 100.23
Spain m2/dwelling 94.72 95.16 108.16 136.93 m2/dwelling 87.41 73.16 86.84 95.10
Italy m2/dwelling 123.54 109.40 94.98 106.85 m2/dwelling 90.80 90.80 90.80 90.80
total by period m2/dwelling 109.92 97.73 100.03 129.00 m2/dwelling 89.72 85.69 90.01 95.18
total by climate zone m2 m2
France m2/dwelling 58.79 111.62 104.36 86.41 m2/dwelling 54.04 65.92 63.83 n.a
Slovenia m2/dwelling 89.02 90.21 100.38 104.41 m2/dwelling 56.06 46.85 61.26 64.42
Hungary m2/dwelling 93.15 93.15 93.15 93.15 m2/dwelling 46.73 46.73 46.73 46.73
Romania m2/dwelling 72.58 72.58 71.46 72.58 m2/dwelling 55.36 45.68 46.53 74.46
Bulgaria m2/dwelling 64.78 63.16 64.91 60.63 m2/dwelling 64.48 64.48 64.48 64.48
Ireland m2/dwelling 99.03 97.52 114.23 135.89 m2/dwelling 50.00 50.00 69.24 71.26
Netherlands m2/dwelling 129.34 111.14 107.29 113.13 m2/dwelling 41.72 32.86 30.92 32.40
Belgium m2/dwelling 73.00 73.00 73.00 73.00 m2/dwelling 113.91 113.91 114.00 114.00
Luxembourg m2/dwelling 80.45 83.01 97.09 95.89 m2/dwelling 83.18 86.08 86.94 86.08
U. Kingdom m2/dwelling 101.09 77.24 73.31 82.04 m2/dwelling 55.20 51.67 48.45 45.47
Slovakia m2/dwelling 86.40 91.22 102.32 112.45 m2/dwelling 64.07 58.66 48.85 53.96
Germany m2/dwelling 100.24 100.15 111.15 119.12 m2/dwelling n.a. 66.04 58.80 64.05
Austria m2/dwelling 111.27 111.37 126.03 131.88 m2/dwelling 70.96 65.72 77.58 73.83
Czech Rep. m2/dwelling 86.56 94.65 104.10 129.12 m2/dwelling 64.07 58.66 61.25 62.61
Poland m2/dwelling 76.32 79.16 113.10 111.61 m2/dwelling 52.24 43.78 51.85 59.34
Denmark m2/dwelling 136.35 124.07 137.84 151.36 m2/dwelling 82.04 89.10 59.80 57.20
total by period m2/dwelling 89.84 91.19 95.80 101.53 m2/dwelling 58.54 60.98 57.07 59.97
total by climate zone m2 m2
Lithuania m2/dwelling 72.43 84.58 104.06 178.09 m2/dwelling 18.60 49.17 62.68 85.06
Latvia m2/dwelling 96.00 96.00 96.00 96.00 m2/dwelling 52.00 52.00 52.00 52.00
Estonia m2/dwelling 86.11 86.11 86.11 80.10 m2/dwelling 47.80 47.80 47.80 47.80
Sweden m2/dwelling 125.00 125.00 125.00 125.00 m2/dwelling 67.00 67.00 67.00 67.00
Finland m2/dwelling 70.68 73.88 113.70 118.62 m2/dwelling 56.00 56.00 56.00 56.00
total by period m2/dwelling 102.05 99.93 116.92 124.82 m2/dwelling 55.47 59.61 60.25 64.36
total by climate zone m2 m2
TOTAL EU m2 m2
average floor
AVERAGE FLOOR AREA OF DWELLING
Single family house Multy family house
unit <1945 1945-1969 1970-1989 1990-2008 average floor unit <1945 1945-1969 1970-1989 1990-2008
107.40 89.641,715,847,520.19 3,208,367,279.95
94.29 59.007,684,970,507.84 3,613,041,661.08
108.34 58.65449,404,127.87 331,407,734.50
9,850,222,155.90 7,152,816,675.53
<1945 109.92 3,990,078 438,589,374
1945-1969 97.73 3,940,270 385,082,587
1970-1989 100.03 5,029,840 503,134,895
1990-2008 129.00 3,015,950 389,057,550
<1945 89.84 19,053,376 1,711,755,300
1945-1969 91.19 21,741,470 1,982,604,649
1970-1989 95.80 24,874,550 2,382,981,890
1990-2008 101.53 15,835,400 1,607,768,162
<1945 102.05 1,137,005 116,031,360
1945-1969 99.93 1,123,212 112,242,575
1970-1989 116.92 1,258,137 147,101,378
1990-2008 124.82 629,666 78,594,910
<1945 89.72 5,563,385 499,146,902
1945-1969 85.69 10,977,810 940,688,539
1970-1989 90.01 12,326,200 1,109,481,262
1990-2008 95.18 6,923,950 659,021,561
<1945 58.54 12,883,862 754,221,281
1945-1969 60.98 16,543,070 1,008,796,409
1970-1989 57.07 19,849,950 1,132,836,647
1990-2008 59.97 11,961,080 717,305,968
<1945 55.47 1,326,949 73,605,861
1945-1969 59.61 1,580,981 94,242,277
1970-1989 60.25 1,831,828 110,367,637
1990-2008 64.36 910,548 58,602,869
SFH
MFH
WARM
MODERATE
COLD
WARM
MODERATE
COLD
average floor
area/dwelling (m2)
total number of
dwellingstotal floor area (m2)
84
Table 33 Average persons per dwelling by dwelling type and by climatic zone in EU-27 in 2010.
Source: reworking of authors from Eurostat (number of person) and ENTRANZE (number of
dwellings)
Table 34 Distribution of dwellings by type (SFH= Single Family House and MFH = Multi Family
House), climate and period. Source: reworking of authors (aggregated data) from ENTRANZE.
Malta 414,027 210,739.74 106,463.60 201,217.12 35,376.40
Cyprus 819,140 625,822.96 215,147.16 183,487.36 84,129.08
Portugal 10,573,479 6,608,424.38 2,238,294.17 3,922,760.71 1,555,425.57
Greece 11,183,516 4,674,709.69 1,556,521.00 6,508,806.31 2,290,753.00
Spain 46,486,619 16,223,830.03 4,960,716.00 30,216,302.35 11,780,663.00
Italy 59,190,143 26,457,993.92 6,899,000.00 31,607,536.36 20,045,000.00
total by climate zone 54,801,520.72 15,976,141.93 72,640,110.22 35,791,347.06
person/dwelling
France 64,658,856 42,610,186.10 15,252,300.00 21,919,352.18 11,786,300.00
Slovenia 2,046,976 1,455,399.94 276,294.53 583,388.16 487,862.14
Hungary 10,014,324 6,969,969.50 2,479,000.00 2,974,254.23 1,549,000.00
Romania 20,294,683 12,724,766.24 4,177,885.60 7,569,916.76 3,173,261.88
Bulgaria 7,421,766 4,215,563.09 1,697,034.45 3,169,094.08 1,384,965.55
Ireland 4,549,428 4,349,253.17 1,463,452.00 191,075.98 185,956.00
Netherlands 16,574,989 12,779,316.52 4,876,002.57 2,966,923.03 2,110,820.16
Belgium 10,839,905 8,585,204.76 3,330,000.00 2,200,500.72 1,193,000.00
Luxembourg 502,066 332,869.76 120,000.00 166,183.85 68,000.00
U. Kingdom 62,510,197 53,696,259.22 18,403,807.44 8,751,427.58 4,135,409.54
Slovakia 5,390,410 2,711,376.23 849,000.00 2,679,033.77 880,000.00
Germany 81,802,257 36,811,015.65 18,081,300.42 43,600,602.98 21,128,771.28
Austria 8,375,290 4,748,789.43 1,792,000.00 3,542,747.67 1,771,000.00
Czech Rep. 10,462,088 4,885,795.10 1,699,723.27 5,523,982.46 2,297,926.63
Poland 38,167,329 20,228,684.37 5,428,000.00 17,862,309.97 7,994,000.00
Denmark 5,534,738 3,946,268.19 1,579,000.00 1,588,469.81 1,091,690.12
total by climate zone 221,050,717.27 81,504,800.27 125,289,263.22 61,237,963.30
person/dwelling
Lithuania 3,141,976 1,347,907.70 539,549.87 1,781,500.39 997,367.93
Latvia 2,120,504 727,332.87 305,600.00 1,386,809.62 682,610.00
Estonia 1,333,290 466,651.50 163,870.00 859,972.05 489,330.00
Sweden 9,340,682 5,632,431.25 1,776,000.00 3,680,228.71 2,395,000.00
Finland 5,351,427 3,558,698.96 1,363,000.00 1,755,268.06 1,086,000.00
total by climate zone 11,733,022.28 4,148,019.87 9,463,778.82 5,650,307.92
person/dwelling
number of
person lived
Multi-Family
House
number of
dwellings in
Multi-Family
House
number of
person 2010
number of
person lived
Single Family
House
number of
dwellings in
Single Family
House
3.43 2.03
2.71 2.05
2.83 1.67
<1945 24.98%
1945-1969 24.66%
1970-1989 31.48%
1990-2008 18.88%
<1945 23.38%
1945-1969 26.67%
1970-1989 30.52%
1990-2008 19.43%
<1945 27.41%
1945-1969 27.08%
1970-1989 30.33%
1990-2008 15.18%
<1945 15.54%
1945-1969 30.67%
1970-1989 34.44%
1990-2008 19.35%
<1945 21.05%
1945-1969 27.01%
1970-1989 32.41%
1990-2008 19.53%
<1945 23.49%
1945-1969 27.98%
1970-1989 32.42%
1990-2008 16.11%
MULTI
FAMILY HOUSE
50.26%
COLD 5.50%
MODERATE
59.64%
WARM 34.86%
SINGLE FAMILY
HOUSE
49.74%
COLD 4.08%
MODERATE
80.20%
WARM
15.72%
85
Table 35 Product groups, representative products and LCI datasets
Product group(s) Representative product(s) LCI dataset(s)
Single Family House
Single Family House _ warm _ <1945 SFH_warm_<1945
Single Family House _ warm _ 1945-1969 SFH_warm_1945-1969
Single Family House _ warm_ 1970-1989 SFH_warm_1970-1989
Single Family House _ warm _ 1990-2010 SFH_warm_1990-2010
Single Family House _ moderate _ <1945 SFH_ moderate _<1945
Single Family House _ moderate _ 1945-1969 SFH_ moderate _1945-1969
Single Family House _ moderate_ 1970-1989 SFH_ moderate _1970-1989
Single Family House _ moderate _ 1990-2010 SFH_ moderate _1990-2010
Single Family House _ cold _ <1945 SFH_cold_<1945
Single Family House _ cold _ 1945-1969 SFH_cold_1945-1969
Single Family House _ cold _ 1970-1989 SFH_cold_1970-1989
Single Family House _ cold _ 1990-2010 SFH_cold_1990-2010
Multi-Family House
Multi-Family House _ warm _ <1945 MFH_warm_<1945
Multi-Family House _ warm _ 1945-1969 MFH_warm_1945-1969
Multi-Family House _ warm_ 1970-1989 MFH_warm_1970-1989
Multi-Family House _ warm _ 1990-2010 MFH_warm_1990-2010
Multi-Family House _ moderate _ <1945 MFH_ moderate _<1945
Multi-Family House _ moderate _ 1945-1969 MFH_ moderate _1945-1969
Multi-Family House _ moderate_ 1970-1989 MFH_ moderate _1970-1989
Multi-Family House _ moderate _ 1990-2010 MFH_ moderate _1990-2010
Multi-Family House _ cold _ <1945 MFH_cold_<1945
Multi-Family House _ cold _ 1945-1969 MFH_cold_1945-1969
Multi-Family House _ cold _ 1970-1989 MFH_cold_1970-1989
Multi-Family House _ cold _ 1990-2010 MFH_cold_1990-2010
86
Table 36 Description of representative products of Single Family House
Dwelling type
LCI dataset SFH_warm_<1945 SFH_warm_1945-69 SFH_warm_1970-89 SFH_warm_1990-2010SFH_mod_<1945 SFH_mod_1945-69 SFH_mod_1970-89 SFH_mod_1990-2010SFH_cold_<1945 SFH_cold_1945-69 SFH_cold_1970-89 SFH_cold_1990-2010
Building typology Detached House Detached House Detached House Detached House Detached House Detached House Detached House Detached House Detached House Detached House Detached House Detached House
Building size XS XS XS XS XS XS XS XS XS XS XS XS
Dwelling size (m2) 98 98 100 129 91 91 96 102 100 100 117 125
Model dwelling size (m2) 100 100 100 130 90 90 100 100 100 100 120 120
Number of inhabitants 3.43 3.43 3.43 3.43 2.71 2.71 2.71 2.71 2.83 2.83 2.83 2.83
Year of construction 1945-1969 1945-1969 1970-1989 1990-2010 1945-1969 1945-1969 1970-1989 1990-2010 1945-1969 1945-1969 1970-1989 1990-2010
Lifetime of the building 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years
Number of dwelling 1 1 1 1 1 1 1 1 1 1 1 1
Number of floors 2 2 2 2 2 2 2 2 2 2 2 2
Internal height (m) 2.7 2.7 2.7 2.7 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5
Net area (m2) 98 98 98 126 86 86 97 97 99 99 118 118
Gross area (m2) 119 119 119 156 114 114 122 126 108 108 128 128
Underground (m2) 28 28 28 35 26 26 28 30 28 28 32 32
Gross volume (m3) 357 357 357 469 321 321 342 354 317 317 375 377
Heated volume (m3) 293 293 293 379 241 241 271 271 290 290 346 346
Surface/Volume 0.92 0.92 0.92 0.85 0.98 0.98 0.95 0.95 0.92 0.92 0.87 0.87
WallWindowRatio 0.29 0.29 0.29 0.31 0.30 0.30 0.32 0.32 0.30 0.30 0.28 0.28
Constructive technology heavy heavy heavy heavy heavy heavy heavy heavy light, dry assembly light, dry assembly light, dry assembly light, dry assembly
Foundations reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb
Underground retaining walls reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete
Load bearing elements masonry in brick masonry in brick masonry in brick masonry in brick masonry in brick masonry in brick masonry in brick masonry in brick timber frame timber frame timber frame timber frame
Floors (structure) reinfor concr/bricks reinfor concr/bricks reinfor concr/bricks reinfor concr/bricks reinforced concrete reinforced concrete reinforced concrete reinforced concrete timber frame + board timber frame + board timber frame + board timber frame + board
Stairs reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete timber frame timber frame timber frame timber frame
masonry brick (25 cm) masonry brick (25 cm) masonry brick (25 cm) masonry brick (25 cm) masonry brick (32 cm) masonry brick (38 cm) masonry brick (30 cm) masonry brick (32 cm) timber frame timber frame timber frame timber frame
no insulation no insulation no insulation insulation (2 cm) no insulation no insulation no insulation insulation (5 cm) insulation (4 cm) insulation (4 cm) insulation (5 cm) insulation (6 cm)
External walls finishes plaster plaster plaster plaster plaster plaster plaster plaster wood wood wood wood
Windows wood frame wood frame wood frame wood frame wood frame wood frame wood frame PVC frame wood frame wood frame wood frame wood frame
single glass single glass single glass single glass single glass single glass single glass double glass single glass single glass double glass triple glass
pitched pitched pitched flat pitched pitched pitched pitched pitched pitched pitched pitched
no insulation no insulation no insulation insulation (2 cm) insulation (2 cm) insulation (2 cm) insulation (5 cm) insulation (10 cm) insulation (4 cm) insulation (4 cm) insulation (4 cm) insulation (7 cm)
Bottom floor no insulation no insulation insulation (1 cm) insulation (1 cm) insulation (1 cm) insulation (1 cm) insulation (2 cm) insulation (8 cm) insulation (7 cm) insulation (7 cm) insulation (8 cm) insulation (11 cm)
Roof finishes brick tiles brick tiles brick tiles brick tiles brick tiles brick tiles brick tiles brick tiles cement tiles cement tiles cement tiles cement tiles
Internal walls hollow brciks hollow brciks hollow bricks hollow bricks wood frame wood frame wood frame wood frame wood frame wood frame wood frame wood frame
Internal walls finishes plaster plaster plaster plaster plasterboard plasterboard plasterboard plasterboard plasterboard plasterboard plasterboard plasterboard
Flooring ceramic tiles ceramic tiles ceramic tiles ceramic tiles ceramic tiles ceramic tiles ceramic tiles ceramic tiles wood wood wood wood
Climate warm warm warm warm moderate moderate moderate moderate cold cold cold cold
HeatingDegreeDays 500-2300 500-2300 500-2300 500-2300 2301-4000 2301-4000 2301-4000 2301-4000 4001-6000 4001-6000 4001-6000 4001-6000
Uvalue walls 1.71 1.71 1.47 0.82 1.54 1.54 0.98 0.5 0.64 0.64 0.52 0.39
Uvalue roof 2.32 2.32 2.19 1.18 1.38 1.38 0.72 0.35 0.75 0.75 0.71 0.47
Uvalue windows 4.00 4.00 3.45 3.00 3.65 3.65 2.65 1.84 2.30 2.30 2.01 1.87
Uvalue bottom floor 1.76 1.76 1.71 1.48 1.63 1.63 1.16 0.49 0.49 0.49 0.43 0.33
Heating energy consumption102 102 76 62 184 184 151 100 175 175 150 115
Heating systems boiler boiler boiler boiler boiler boiler boiler boiler electricity electricity electricity electricity
Heating terminal unit radiators radiators radiators radiant floor radiators radiators radiators radiant floor convector heaters convector heaters convector heaters convector heaters
tot nr. of dwellings in EU-27 3,990,078 3,940,268 5,029,842 3,015,954 19,053,376 21,741,474 24,874,549 15,835,402 1,137,005 1,123,212 1,258,137 629,666
External walls
Insulation
Roof
Insulation
Single Family House
87
Table 37 Description of representative products of Multi-Family Houses
Dwelling type
LCI dataset MFH_warm_1945-69 MFH_warm_<1945 MFH_warm_1970-89 MFH_warm_1990-2010MFH_mod_<1945 MFH_moderate_1945-69MFH_mod_1970-89 MFH_mod_1990-2010MFH_cold_<1945 MFH_cold_1945-69 MFH_cold_1970-89 MFH_cold 1990-2010
Building typology Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart Low-rise > 10 apart
Building size M M M M M M M M M M M M
Dwelling size (m2) 86 86 90 95 61 61 57 60 60 60 60 64
Model dwelling size (m2) 90 90 90 90 60 60 60 60 60 60 60 60
Number of inhabitants 2.03 2.03 2.03 2.03 2.05 2.05 2.05 2.05 1.67 1.67 1.67 1.67
Year of construction 1945-1969 1945-1969 1970-1989 1990-2010 1945-1969 1945-1969 1970-1989 1990-2010 1945-1969 1945-1969 1970-1989 1990-2010
Lifetime of the building 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years 100 years
Number of dwelling 16 16 16 16 16 16 16 16 16 16 16 16
Number of floors 4 4 4 4 4 4 4 4 4 4 4 4
Internal height (m) 2.7 2.7 2.7 2.7 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5
Net area (m2) 1383 1383 1383 1383 939 939 939 939 939 939 939 939
Gross area (m2) 1591 1591 1591 1579 1125 1125 1098 1104 1104 1104 1095 1095
Underground (m2) 933 933 933 933 752 752 752 752 752 752 752 752
Gross volume (m3) 5511 5511 5511 5471 3698 3698 3611 3633 3633 3633 3603 3603
Heated volume (m3) 4149 4149 4149 4149 2628 2628 2628 2628 2628 2628 2628 2628
Surface/Volume 0.55 0.55 0.55 0.55 0.65 0.65 0.65 0.65 0.65 0.65 0.65 0.65
WallWindowRatio 0.22 0.22 0.22 0.22 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.26
Constructive technology heavy heavy heavy heavy heavy heavy heavy heavy light, dry assembly light, dry assembly light, dry assembly light, dry assembly
Foundations reinf concr curb reinf concr curb reinf concr curb reinforced concrete curbreinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb reinf concr curb
Underground retaining walls reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete reinfor concrete
Load bearing elements reinforced concrete framereinf concr frame reinf concr frame reinf concr frame reinf concr frame reinf concr frame reinf concr frame reinf concr frame reinf concr frame reinf concr frame reinf concr frame reinf concr frame
Floors (structure) reinfor concr/bricks reinfor concr/bricks reinfor concr/bricks reinfor concr/bricks reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete
Stairs reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete reinforced concrete
hollow bricks (30 cm) hollow bricks (30 cm) hollow bricks (30 cm) hollow bricks (30 cm) hollow bricks (30 cm) hollow bricks (30 cm) hollow bricks (20 cm) hollow bricks (20 cm) hollow bricks 8 cm hollow bricks 8 cm hollow bricks 8 cm hollow bricks 8 cm
no insulation no insulation no insulation insulation (2 cm) no insulation no insulation insulation (2 cm) insulation (4 cm) insulation (3 cm) insulation (3 cm) insulation (3 cm) insulation (3 cm)
External walls finishes plaster plaster plaster plaster plaster plaster plaster plaster facing bricks (12 cm) facing bricks (12 cm) facing bricks (12 cm) facing bricks (12 cm)
Windows wood frame wood frame alumin frame alumin frame wood frame wood frame PVC frame PVC frame wood frame wood frame wood frame alum frame
single glass single glass double glass double glass double glass double glass double glass double glass single glass single glass double glass double glass
flat flat flat flat flat flat flat flat pitched pitched pitched pitched
no insulation no insulation no insulation insulation (2 cm) insulation (2 cm) insulation (2 cm) insulation (4 cm) insulation (10 cm) insulation (4 cm) insulation (4 cm) insulation (5 cm) insulation (8 cm)
Bottom floor no insulation no insulation insulation (1 cm) insulation (1 cm) insulation (1 cm) insulation (1 cm) insulation (2 cm) insulation (7 cm) insulation (5 cm) insulation (5 cm) insulation (6 cm) insulation (9 cm)
Roof finishes bitumen bitumen bitumen bitumen bitumen bitumen bitumen bitumen cement tiles cement tiles cement tiles cement tiles
Internal walls bricks bricks bricks bricks wood frame wood frame wood frame wood frame wood frame wood frame wood frame wood frame
Internal walls finishes plaster plaster plaster plaster plasterboard plasterboard plasterboard plasterboard plasterboard plasterboard plasterboard plasterboard
Flooring ceramic tiles ceramic tiles ceramic tiles ceramic tiles ceramic tile ceramic tile ceramic tile ceramic tile wood wood wood wood
Climate warm warm warm warm moderate moderate moderate moderate cold cold cold cold
HeatingDegreeDays 500-2300 500-2300 500-2300 500-2300 2301-4000 2301-4000 2301-4000 2301-4000 4001-6000 4001-6000 4001-6000 4001-6000
Uvalue walls 1.76 1.76 1.47 0.81 1.55 1.55 0.98 0.54 0.71 0.71 0.54 0.58
Uvalue roof 2.25 2.25 2.11 1.16 1.42 1.42 0.75 0.39 0.79 0.79 0.73 0.48
Uvalue windows 4.80 4.80 4.90 3.75 3.81 3.81 2.90 1.93 2.20 2.20 2.04 1.97
Uvalue bottom floor 1.81 1.81 1.73 1.52 1.67 1.67 1.16 0.51 0.57 0.57 0.51 0.38
Heating energy consumption98 98 63 52 182 182 133 98 168 168 148 129
Heating systems boiler boiler boiler boiler boiler boiler boiler boiler electricity electricity electricity electricity
Heating terminal unit radiators radiators radiators radiant floor radiators radiators radiators radiant floor convector heaters convector heaters convector heaters convector heaters
tot nr. of dwellings in EU-27 5,563,385 10,977,814 12,326,198 6,923,950 12,883,862 16,543,072 19,849,947 11,961,082 1,326,949 1,580,981 1,831,829 910,548
Multi-Family House
External walls
Insulation
Roof
Insulation
89
4.3 Life Cycle Inventory of the selected products
For the development of LCA of each representative product (dwelling), it was first necessary to build a common
framework related to assumptions to be used in order to achieve consistent LCAs and to obtain comparable
results. Several studies have been analysed to identify assumptions for each life cycle stage.
The functional unit is defined as the average consumption related to housing per person in EU-27 in 2010.
The system boundaries were defined according to the European Standard EN 15978: 2011 “Sustainability of
construction works - Assessment of environmental performance of buildings - Calculation method”, from the
production stage to the end of life stage (Figure 31). The inventories were organized with the modular structure
of the EN 15978: production stage, construction stage, use stage, end of life stage (Table 38).
The focus is on the building; the curtilage (that means the land immediately surrounding) is omitted. No cut-
off was considered.
Figure 31 Different stages of the building assessment. Source: EN 15978: 2011.
4.3.1 Data sources
Unlike other products, it is not possible to find in LCI databases the datasets of buildings because each building
is unique. A lot of LCA studies can be found in literature, but it is difficult to define an average environmental
profile of a building based on them.
On the other hand datasets related to materials and building products are readily available in databases
commonly used for LCA.
So, it was conducted an analysis of LCA studies related to buildings, selecting only studies related to residential
buildings in Europe, with the goal of obtaining references in relation to the different life cycle stages and
assumptions to be adopted as reference values ("typical") to be considered in the definition of the process-
based life cycle inventory models of the representative products (dwelling) analysed in this report.
It was then made a screening to select datasets to be used in this study. The reference databases are Ecoinvent
(v2.2 and v3) and ELCD. The attributional allocation model was selected. The datasets were selected by
choosing those representative of the European scale (RER), where possible, or those relating to Switzerland-
Germany-Austria area.
4.3.2 Assumptions
The assumptions are mainly based on the literature review and the statistical data (for energy and water
consumptions). A brief description follows:
• Production: the system boundaries of materials production included: raw materials extraction or recovery
of recycled materials (as available in Ecoinvent datasets; EU average when possible), transport to the plant
and production of building materials; the buildings’ elements considered are: supporting structure
90
(foundations, underground retaining walls, load-bearing elements, floors, stairs), envelope (external walls,
windows, roof, lower floor), internal walls, finishes, systems (heating, wiring, plumbing, sanitary appliances).
• Construction: the impact of transport from plant to building site were calculated considering an average
distance of 50 km for heavy materials and 100 km for the other materials; the impact of the assembly
phase was evaluated in terms of electrical consumption (2% of the embodied energy of building materials),
as reported in the literature (Scheuer et alii, 2003; Beccali et alii, 2013; Asdrubali et alii, 2013), and of
construction waste (4% of the weight of building products); it was also considered the impact due to the
production of the materials become "construction waste" (4% of the total production impacts).
• Use phase (energy and water): rather than calculate energy consumption of each representative dwelling
from its characteristics, which could lead to assume consumptions peculiar to a single building as if they
were representative of the average, the actual average energy consumption were derived from EU-27
energy statistics; the average heating consumption for each representative product (Table 40) has been
calculated, merging statistical data in BPIE on trend in heating consumption (divided by dwelling type, by
period of construction and by climatic zone) with actual heating consumption data in ODYSSE ( Table 39).
Table 38 Total national heating consumption of dwellings at normal climate (average Heating
Degree Days of the last 30 years) in EU-27. Source: reworking of authors from ODYSSEE
Table 39 Average heating consumption of dwellings in EU-27 (kWh/m2/y). Source: reworking of
authors from BPIE and ODYSSEE data
For the other energy consumptions (water heating, space cooling, lighting, appliances), a European average
value for each energy consumption type have been considered, based on Eurostat statistical data and on
ODYSSEE data related to the person; considering that cooling is a consumption typical of warm climate, the
total cooling consumption in Europe has been attributed to warm climate only; to avoid over-estimation of
Malta toe/dwelling 0.1 dwelling 131,909.00 toe 13,190.90
Cyprus toe/dwelling 0.26 dwelling 331,324.00 toe 86,144.24
Portugal toe/dwelling 0.15 dwelling 3,932,010.00 toe 589,801.50
Greece toe/dwelling 0.73 dwelling 4,572,262.00 toe 3,337,751.26
Spain toe/dwelling 0.46 dwelling 17,626,453.00 toe 8,108,168.38
Italy toe/dwelling 0.87 dwelling 25,175,793.00 toe 21,902,939.91
France toe/dwelling 1.07 dwelling 27,244,700.00 toe 29,151,829.00
Slovenia toe/dwelling 0.99 dwelling 766,177.00 toe 758,515.23
Hungary toe/dwelling 0.98 dwelling 3,878,000.00 toe 3,800,440.00
Romania toe/dwelling 0.55 dwelling 7,450,000.00 toe 4,097,500.00
Bulgaria toe/dwelling 0.52 dwelling 3,071,000.00 toe 1,596,920.00
Ireland toe/dwelling 1.15 dwelling 1,611,986.00 toe 1,853,783.90
Netherlands toe/dwelling 1.01 dwelling 7,044,333.00 toe 7,114,776.33
Belgium toe/dwelling 1.19 dwelling 4,635,382.00 toe 5,516,104.58
Luxembourg toe/dwelling n.d. dwelling 203,427.00 toe n.d.
U. Kingdom toe/dwelling 1.17 dwelling 26,634,800.00 toe 31,162,716.00
Slovakia toe/dwelling 0.88 dwelling 1,744,780.00 toe 1,535,406.40
Germany toe/dwelling 1.1 dwelling 37,925,160.00 toe 41,717,676.00
Austria toe/dwelling 1.32 dwelling 3,624,300.00 toe 4,784,076.00
Czech Rep. toe/dwelling 1.06 dwelling 4,082,148.00 toe 4,327,076.88
Poland toe/dwelling 1.03 dwelling 13,470,000.00 toe 13,874,100.00
Denmark toe/dwelling 1.36 dwelling 2,718,000.00 toe 3,696,480.00
Lithuania toe/dwelling 0.84 dwelling 1,269,970.00 toe 1,066,774.80
Latvia toe/dwelling 1.13 dwelling 817,000.00 toe 923,210.00
Estonia toe/dwelling 0.97 dwelling 627,030.00 toe 608,219.10
Sweden toe/dwelling 0.95 dwelling 4,431,000.00 toe 4,209,450.00
Finland toe/dwelling 1.5 dwelling 2,537,197.00 toe 3,805,795.50
Unit 2010 Unitnumber of
dwellingUnit
total
consumption
Malta kWh 153,410,167
Cyprus kWh 1,001,857,511
Portugal kWh 6,859,391,445
Greece kWh 38,818,047,154
Spain kWh 94,297,998,259
Italy kWh 254,731,191,153
total by climate zone kWh 395,861,895,690
France kWh 339,035,771,270
Slovenia kWh 8,821,532,125
Hungary kWh 44,199,117,200
Romania kWh 47,653,925,000
Bulgaria kWh 18,572,179,600
Ireland kWh 21,559,506,757
Netherlands kWh 82,744,848,718
Belgium kWh 64,152,296,265
Luxembourg kWh n.a.
U. Kingdom kWh 362,422,387,080
Slovakia kWh 17,856,776,432
Germany kWh 485,176,571,880
Austria kWh 55,638,803,880
Czech Rep. kWh 50,323,904,114
Poland kWh 161,355,783,000
Denmark kWh 42,990,062,400
total by climate zone kWh 1,802,503,465,722
Lithuania kWh 12,406,590,924
Latvia kWh
Estonia kWh 7,073,588,133
Sweden kWh 48,955,903,500
Finland kWh 44,261,401,665
total by climate zone kWh 112,697,484,222
FINAL CONSUMPTION OF RESIDENTIAL FOR SPACE
HEATING (with climatic corrections)
Unit 2010
<1945 1945-1969 1970-1989 1990-2008 <1945 1945-1969 1970-1989 1990-2008
total zone warm 108 102 76 62 101 98 63 52
total zone moderate 220 184 151 100 182 182 133 98
total zone cold 190 175 150 115 158 168 148 129
Multy-Family House
HEATING ENERGY CONSUMPTION kWh/m2 a
Single Family House
91
energy consumption in warm climate, the average consumption related to water heating and lighting were
reduced by 30% and the average consumptions were increased in the other climatic zone (increased by 20%
in the moderate climate and 30% in cold climate); these changes have been made verifying that the total
consumption of each climatic zone correspond to the actual total consumption statistical data; the calculated
average consumption for person was then multiplied for the number of average inhabitants of each
representative dwelling; for defining the environmental impacts related to energy consumption it was also
necessary to know the type of energy, so data about the household energy consumption by energy source
(ODYSSEE) were used; the European electricity mix has been assumed; also for water consumption, a European
average value of 150 l/p/d (Eurostat; Lauranson, Mudgal, 2009) has been considered and for wastewater it
was assumed the same quantity of the water consumption; solid waste were not considered because not
building related and also to avoid double counting with food basket of products.
Table 40 Average energy consumption per person in EU-27 in 2010. Source: calculated data starting
from ODYSSEE -Enerdata
total consumption
household EU-27
(Mtoe/year)
nr. persons in EU-27
in 2010
consumption per
person
(toe/year)
consumption per person
(kWh/year)
Water heating 38 499,100,105 0.076 884
Cooling 3 499,100,105 0.006 70
El. appliances 32 499,100,105 0.064 744
Lighting 7 499,100,105 0.014 163
Table 41 Total consumption of residential sector by energy source in EU-27 in 2008. Source:
reworking of authors from ODYSSEE
Malta Mtoe 0.00 0.02 0.00 0.00 0.00 0.06
Cyprus Mtoe 0.00 0.13 n.a. 0.00 0.05 0.14
Portugal Mtoe 0.00 0.55 0.30 n.a. 1.18 1.16
Greece Mtoe 0.01 2.56 0.21 0.04 0.84 1.56
Spain Mtoe 0.19 3.54 3.64 0.00 2.05 5.97
Italy Mtoe 0.00 4.21 13.54 0.04 1.44 5.88
total by fuel Mtoe 0.20 11.01 17.69 0.09 5.57 14.77
total by climate zone Mtoe
percentage of fuel % 0.41 22.32 35.86 0.18 11.29 29.95
France Mtoe 0.19 7.85 13.82 1.51 6.00 12.91
Slovenia Mtoe 0.00 0.32 0.10 0.10 0.32 0.27
Hungary Mtoe 0.17 0.10 3.29 0.55 0.48 0.99
Romania Mtoe 0.05 0.30 2.21 1.21 3.42 0.90
Bulgaria Mtoe 0.21 0.02 0.04 0.35 0.64 0.86
Ireland Mtoe 0.51 1.20 0.67 0.00 0.04 0.73
Netherlands Mtoe 0.00 0.09 7.42 0.26 0.22 2.13
Belgium Mtoe 0.16 3.36 3.30 0.01 0.22 1.68
Luxembourg Mtoe 0.00 0.23 0.20 0.00 0.02 0.07
U. Kingdom Mtoe 0.69 2.87 27.82 0.05 0.33 10.30
Slovakia Mtoe 0.06 0.02 1.18 0.44 0.04 0.39
Germany Mtoe 1.07 16.18 22.46 3.92 5.48 11.99
Austria Mtoe 0.08 1.34 1.18 0.74 1.52 1.44
Czech Rep. Mtoe 0.46 0.02 2.05 1.15 1.06 1.26
Poland Mtoe 5.68 0.86 3.14 4.18 2.46 2.33
Denmark Mtoe 0.00 0.50 0.63 1.52 1.00 0.88
total by fuel Mtoe 9.33 35.25 89.53 15.99 23.25 49.15
total by climate zone Mtoe
percentage of fuel % 4.19 15.84 40.24 7.19 10.45 22.09
Lithuania Mtoe 0.04 0.04 0.15 0.51 0.57 0.23
Latvia Mtoe 0.02 0.03 0.11 0.39 0.72 0.17
Estonia Mtoe 0.01 0.01 0.05 0.33 0.39 0.16
Sweden Mtoe 0.00 0.24 0.03 2.38 1.04 3.58
Finland Mtoe 0.00 0.53 0.04 1.51 1.21 1.75
total by fuel Mtoe 0.07 0.86 0.38 5.12 3.94 5.90
total by climate zone Mtoe
percentage of fuel % 0.43 5.26 2.35 31.49 24.21 36.25
49.33
222.50
16.26
CONSUMPTION OF RESIDENTIAL SECTOR BY ENERGY SOURCE 2008
Unit COAL OIL GAS HEAT WOOD ELECTRICITY
92
Table 42 Example of calculation for a representative dwelling (SFH_moderate_<1945): the average
heating consumption (kWh/m2/y) were multiplied for the average size of the dwelling (m2); the
average water heating and lighting consumption (increased by 20% than EU average) and the
appliances consumption were multiplied for the average number of inhabitants of the dwelling; the
total energy consumption was then distributed by energy source (average percentage of Table 12
by climatic zone). Source: authors.
• Use phase (maintenance): the boundary for replacement included the production of the replaced
components, the transportation of the replaced components, the end of life stage of the removed
components; typical replacement intervals were assumed derived by literature (30 years for mineral
insulation, 30 years for windows, 50 years for external walls in wood frame (light construction), 30 years
for internal walls in wood frame (light construction), 20 years for waterproofing, 50 years for finishes
(replacement of 50% of the finishes every 25 years), 50 years for the systems (replacement of 50% of
the systems every 25 years); the typical replacement intervals were applied both in case of new buildings
(as future scenario along the service life) and in case of the old stock (assuming that since it was built
maintenance work has already undergone).
• The total lifetime of the buildings is assumed to be 100 years (considering that an important part of the
building stock has been constructed before 1945).
• End-Of-Life: the system boundaries include the dismantling process, transport to sorting plants, final
disposal of waste materials; benefits from materials recycling and energy recovery (incineration) are not
included in the system boundaries, in accordance with the allocation procedure proposed by Kloepffer
(1996).
kWh/person/y kWh/m2/y m2 kWh/y per/dw kWh/y TOT cons % kWh/y
heating 220 90 19800 19,800 25,223 40.24 10150 gas
water heating 1061 2.71 2,875 kWh/dw/y 15.84 3995 oil
lighting 196 2.71 531 10.45 2636 wood
appliance (electricity) 744 2.71 2,016 7.19 1814 district heat
4.19 1057 coal
22.09 5572 electricity
93
Table 43 Example of the inventory of a representative products (and of the organization of
datasets).
DATASET SFH_cold_1990-2010
120 m2
normalisation: dwelling/year (reference year 2010)
building lifetime: 100 years
number of inhabitants: 2.83
datasets of SimaPro 8.0.3.14 /year /year
PRODUCTION PHASE SFH_cold_1990-2010_A_production
raw materials- transports-manufacturing of building's materials
m3/y kg/y
undergroud structure foundations gravel Gravel, round {CH}, gravel and sand quarry operation, Alloc Def, U 0.032 70.299
foundations reinforced concrete curb (50 cm) Concrete, normal {CH}, production, Alloc Def, U 0.479 1,150.363
undergroud retaining walls reinforced concrete (20 cm) Reinforcing steel, at plant/RER U 0.010 76.300
structure pillars timber frame (20 cm x 20 cm) Sawnwood, hardwood, air/kiln dried, planed {RER}, planing, hardwood, air/kiln dried, Alloc Def, U0.197 98.700
floors timber frame (16 cm x 30 cm)
wood board (2 cm + 2 cm)
stairs timber frame
envelope external walls wood frame Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.009 4.350
insulation (4 cm) Rockwool {CH}, production, Alloc Def, U 0.153 7.665
windows wood frame Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.007 3.350
triple glass Flat glass, uncoated {RER}, production, Alloc Def, U 0.005 13.500
roof roof battens Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.008 4.200
insulation (7 cm)
bottom floor insulation (11 cm)
internal walls internal walls wood frame Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.006 2.900
finishes external walls wood cladding Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.019 9.250
internal walls Gypsum plasterboard {CH}, production, Alloc Def, U 0.076 68.400
flooring wood Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.012 6.100
light concrete screed Concrete, normal {CH}, production, Alloc Def, U 0.114 205.380
roof cement tiles Cement tile {CH}, production, Alloc Def, U 0.022 49.060
systems convector heaters steel Steel, unalloyed {RER}, steel production, converter, unalloyed, Alloc Def, U0.000 1.200
wiring copper Copper {RER}, production, primary, Alloc Def, U 0.000 0.275
plumbing system steel Steel, unalloyed {RER}, steel production, converter, unalloyed, Alloc Def, U0.000 0.486
PVC Polyvinylchloride, suspension polymerised {RER}, polyvinylchloride production, suspension polymerisation, Alloc Def, U0.000 0.180
sanitary appliances ceramic Sanitary ceramics {CH}, production, Alloc Def, U 0.000 4.360
CONSTRUCTION PHASE SFH_cold_1990-2010_B_construction tkm/y
transport to site 50 km Lorry 16-32 t Transport, freight, lorry 16-32 metric ton, EURO3 {RER}, Alloc Def, U 75.117
100 km Lorry 3.5-7.5 t Transport, freight, lorry 3.5-7.5 metric ton, EURO3 {RER}, Alloc Def, U 27.398
MJ
energy electricity 2% embodied energy of production Electricity mix, AC, consumption mix, at consumer, < 1kV EU-27 S 56.77
kg/y
construction waste 4% production SFH_cold_1990-2010_A_production 0.04
construction waste 4% production Waste concrete, not reinforced {CH}, treatment of, sorting plant, Alloc Def, U 59.004
Waste gypsum plasterboard (waste treatment) {CH}, treatment of, sorting plant, Conseq, U 2.736
Waste wood, untreated (waste treatment) {CH}, treatment of waste wood, untreated, municipal inceneration Alloc Def, U5.154
Waste mineral wool (waste treatment) {CH}, treatment of, sorting plant, Alloc Def, U 0.307
USE PHASE energy and water SFH_cold_1990-2010_C_use phase (energy and water)
kWh/y l/y
energy heating natural gas Heat, central or small-scale, natural gas {Europe without Switzerland}, at boiler atmospheric non-modulating <100kW, Alloc Def, U395
water heating oil Heat, central or small-scale, other than natural gas {Europe without Switzerland}, light fuel oil, at boiler 100kW non-modulating, Alloc Def, U883
cooling wood Heat, central or small-scale, other than natural gas {CH}, softwood chips from forest, at furnace 50kW, Alloc Def, U4066
lighting district heat Heat, district or industrail, other than natural gas {CH}, treatment of municipal waste, incineration, Alloc, Def, U6222
appliance (electricity) coal Heat, central or small-scale, other than natural gas {Europe without Switzerland}, hard coal coke, stove 5-15kW, Alloc Def, U72
electricity Electricity mix, AC, consumption mix, at consumer, < 1kV EU-27 S 7162
water consumption Tap water, at user {Europe without Switzerland}, tap water production and supply, Alloc Def, U154,943
wastewater treatment Treatment, sewage, unpolluted, from residence, to wastewater treatment, class 2/CH U 154,943
USE PHASE maintenance SFH_cold_1990-2010_D_use phase (maintenance) m3/y kg/y
substitution of insulation 30 years Rockwool {CH}, production, Alloc Def, U 15.33
wood frame external walls 50 years Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.009 4.35
wood frame internal walls 30 years Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.012 5.80
windows 30 years Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.013 6.700
Flat glass, uncoated {RER}, production, Alloc Def, U 27.000
finishes 30 years Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.037 18.500
Gypsum plasterboard {CH}, production, Alloc Def, U 136.800
Sawnwood, softwood, kiln dried, planed {RER}, planing, softwood, kiln dried, Alloc Def, U0.024 12.200
50 years Cement tile {CH}, production, Alloc Def, U 98.120
systems 50 years Steel, unalloyed {RER}, steel production, converter, unalloyed, Alloc Def, U 1.200
Copper {RER}, production, primary, Alloc Def, U 0.275
Steel, unalloyed {RER}, steel production, converter, unalloyed, Alloc Def, U 0.486
Polyvinylchloride, suspension polymerised {RER}, polyvinylchloride production, suspension polymerisation, Alloc Def, U0.180
Sanitary ceramics {CH}, production, Alloc Def, U 4.360
tkm/y
transport 50 km Lorry 16-32 t Transport, freight, lorry 16-32 metric ton, EURO3 {RER}, Alloc Def, U 0.000
100 km Lorry 3.5-7.5 t Transport, freight, lorry 3.5-7.5 metric ton, EURO3 {RER}, Alloc Def, U 34.484
replacement waste window frame, wall frame, finishes Waste wood, untreated (waste treatment) {CH}, treatment of waste wood, untreated, municipal inceneration Alloc Def, U47.550
glass Waste glass sheet (waste treatment) {CH}, treatment of waste glass sheet, sorting plant, Alloc Def, U27.000
plasterboard Waste gypsum plasterboard (waste treatment) {CH}, treatment of, sorting plant, Conseq, U136.800
insulation Waste mineral wool (waste treatment) {CH}, treatment of, sorting plant, Alloc Def, U 15.330
END OF LIFE SFH_cold_1990-2010_E_EOL
deconstruction
transport
sorting plant reinforced concrete Waste reinforced concrete (waste treatment) {CH}, treatment of, sorting plant, Alloc Def, U1,150.36
steel Waste reinforcement steel (waste treatment) {CH}, treatment of, recycling, Alloc Def, U 76.30
glass Waste glass sheet (waste treatment) {CH}, treatment of waste glass sheet, sorting plant, Alloc Def, U13.50
gravel, mortar, screed Waste concrete, not reinforced {CH}, treatment of, sorting plant, Alloc Def, U 324.74
plasterboard Waste gypsum plasterboard (waste treatment) {CH}, treatment of, sorting plant, Conseq, U68.400
insulation Waste mineral wool (waste treatment) {CH}, treatment of, sorting plant, Alloc Def, U 7.67
wood Waste wood, untreated (waste treatment) {CH}, treatment of waste wood, untreated, municipal inceneration Alloc Def, U128.85
PVC Waste polyvinylchloride product (waste treatment) {CH},treatment of waste polyvinylchloride product, collection for final disposal Alloc Def, U0.18
94
4.4 Results of the environmental impacts of the selected products
for one EU citizen
As a first step, the calculations of environmental impacts (datasets) were related to one dwelling/year. The
impacts of the production, construction, maintenance, use and end of life stages were annualized over the
lifetime of the dwelling (100 years). The life-cycle assessment tool used in this study is Simapro 8.
Then, for each representative product (dwelling), the total LCA impacts was multiplied for the number of
dwellings of that type and divided by EU-27 population in 2010 in order to derive annualised impacts per capita
by representative product.
The final results are representative of the average consumption of a European citizen in relation to housing,
since they were built from statistical averages and photographing products with "average" data (m2, energy
consumption, etc.).
The final results are affected by the number of dwellings for each representative product (dwelling
type/period/climate), so it is necessary to consider that major impacts do not means major impacts of the
representative product itself, but probably major number of dwellings for that representative products. It is
necessary also to underline that, in particular, the subdivision in climatic zone (warm, moderate, cold) hide
different quantity of population, dwellings, territory. The results should be read as aggregated values, which
return the picture of the overall average impacts of housing in EU-27, and can be used to understand which
stages of the life cycle are more impacting than the others or which indicators are more significant for housing.
The evaluation method used was the ILCD 2011 Midpoint method. This LCIA method includes 16 midpoint
impact categories.
The indicators are:
• Climate change midpoint
• Ozone depletion midpoint
• Human toxicity midpoint, cancer effects
• Human toxicity midpoint, non-cancer effects
• Particulate matter/Respiratory inorganics
midpoint
• Ionizing radiation midpoint, human health
• Ionizing radiation midpoint, ecosystems
• Photochemical ozone formation midpoint,
human health
• Acidification
• Terrestrial eutrophication midpoint
• Freshwater eutrophication midpoint
• Marine eutrophication midpoint
• Freshwater ecotoxicity midpoint
• Land use
• Water resource depletion
• Mineral, fossil and resource depletion.
95
4.4.1 Results per impact category
Climate change midpoint
Figure 32 Climate change per person per year in EU-27 in 2010 by product
Figure 33 Climate change per person per year in EU-27 in 2010 by product and by life cycle stages
96
Ozone depletion midpoint
Figure 34 Ozone depletion per person per year in EU-27 in 2010 by product
Figure 35 Ozone depletion per person per year in EU-27 in 2010 by product and by life cycle stages
97
Human toxicity midpoint, cancer effects
Figure 36 Human toxicity, cancer effects, per person per year in EU-27 in 2010 by product
Figure 37 Human toxicity, cancer effects, per person per year in EU-27 in 2010 by product and by
life cycle stages
98
Human toxicity, non-cancer effects
Figure 38 Human toxicity, non-cancer effects, per person per year in EU-27 in 2010 by product
Figure 39 Human toxicity, non-cancer effects, per person per year in EU-27 in 2010 by product and
by life cycle stages
99
Particulate matter midpoint
Figure 40 Particulate matter per person per year in EU-27 in 2010 by product
Figure 41 Particulate matter per person per year in EU-27 in 2010 by product and by life cycle
stages.
100
Ionizing radiation midpoint, Human Health
Figure 42 Ionizing radiation, Human Health, per person per year in EU-27 in 2010 by product
Figure 43 Ionizing radiation, Human Health, per person per year in EU-27 in 2010 by product and
by life cycle stages
101
Ionizing radiation midpoint, Ecosystems (interim)
Figure 44 Ionizing radiation, Ecosystems, per person per year in EU-27 in 2010 by product
Figure 45 Ionizing radiation, Ecosystems, per person per year in EU-27 in 2010 by product and by
life cycle stages
102
Photochemical ozone formation midpoint
Figure 46 Photochemical ozone formation per person per year in EU-27 in 2010 by product
Figure 47 Photochemical ozone formation per person per year in EU-27 in 2010 by product and by
life cycle stages
103
Acidification midpoint
Figure 48 Acidification per person per year in EU-27 in 2010 by product
Figure 49 Acidification per person per year in EU-27 in 2010 by product and by life cycle stages
104
Terrestrial eutrophication midpoint
Figure 50 Terrestrial eutrophication per person per year in EU-27 in 2010 by product
Figure 51 Terrestrial eutrophication per person per year in EU-27 in 2010 by product and by life
cycle stages
105
Freshwater eutrophication midpoint
Figure 52 Freshwater eutrophication per person per year in EU-27 in 2010 by product
Figure 53 Freshwater eutrophication per person per year in EU-27 in 2010 by product and by life
cycle stages
106
Marine eutrophication midpoint
Figure 54 Marine eutrophication per person per year in EU-27 in 2010 by product
Figure 55 Marine eutrophication per person per year in EU-27 in 2010 by product and by life cycle
stages
107
Freshwater ecotoxicity midpoint
Figure 56 Freshwater ecotoxicity per person per year in EU-27 in 2010 by product
Figure 57 Freshwater ecotoxicity per person per year in EU-27 in 2010 by product and by life cycle
stages
108
Land use midpoint
Figure 58 Land use per person per year in EU-27 in 2010 by product
Figure 59 Land use per person per year in EU-27 in 2010 by product and by life cycle stages
109
Water resource depletion midpoint
Figure 60 Water resource depletion per person per year in EU-27 in 2010 by product
Figure 61 Water resource depletion per person per year in EU-27 in 2010 by product and by life
cycle stages
110
Resource depletion, mineral, fossils and renewables
Figure 62 Resource depletion, mineral, fossil and renewables per person per year in EU-27 in 2010
by product
Figure 63 Resource depletion, mineral, fossil and ren per person per year in EU-27 in 2010 by
product and by life cycle stages
111
Table 44 Total results per person per year in EU-27 in 2010 by product
Impact category Unit SFH
_w
arm
_<
19
45
SFH
_w
arm
_1
94
5-6
9
SFH
_w
arm
_1
97
0-8
9
SFH
_w
arm
_1
99
0-2
01
0
SFH
_m
od
era
te_
<1
94
5
SFH
_m
od
era
te_
19
45
-69
SFH
_m
od
era
te_
19
70
-89
SFH
_m
od
era
te_
19
90
-20
10
SFH
_co
ld_
<1
94
5
SFH
_co
ld_
19
45
-69
SFH
_co
ld_
19
70
-89
SFH
_co
ld_
19
90
-20
10
MFH
_w
arm
_<
19
45
MFH
_w
arm
_1
94
5-6
9
MFH
_w
arm
_1
97
0-8
9
MFH
_w
arm
_1
99
0-2
01
0
MFH
_m
od
era
te_
<1
94
5
MFH
_m
od
era
te_
19
45
-69
MFH
_m
od
era
te_
19
70
-89
MFH
_m
od
era
te_
19
90
-20
10
MFH
_co
ld_
<1
94
5
MFH
_co
ld_
19
45
-69
MFH
_co
ld_
19
70
-89
MFH
_co
ld_
19
90
-20
10
TOTA
L
Climate change kg CO2 eq 50.48 48.34 52.9 33.83 323.7 327.4 350.3 176.4 18.65 17.41 20.11 8.491 52.3 101.3 91.77 47.71 130.2 167.2 165.3 85.02 11.82 14.66 15.66 6.118 2317
Ozone depletion kg CFC-11 eq 7E-06 7E-06 7E-06 4E-06 5E-05 5E-05 5E-05 3E-05 6E-06 6E-06 6E-06 3E-06 7E-06 1E-05 1E-05 6E-06 2E-05 2E-05 2E-05 1E-05 4E-06 5E-06 5E-06 2E-06 4E-04
Human toxicity, cancer effects CTUh 2E-06 2E-06 2E-06 1E-06 1E-05 1E-05 2E-05 9E-06 1E-06 1E-06 1E-06 6E-07 2E-06 5E-06 5E-06 3E-06 6E-06 8E-06 9E-06 5E-06 9E-07 1E-06 1E-06 5E-07 1E-04
Human toxicity, non-cancer effects CTUh 8E-06 8E-06 9E-06 6E-06 5E-05 6E-05 6E-05 3E-05 5E-06 5E-06 6E-06 2E-06 8E-06 2E-05 2E-05 8E-06 2E-05 3E-05 3E-05 2E-05 3E-06 4E-06 5E-06 2E-06 4E-04
Particulate matter kg PM2.5 eq 0.032 0.031 0.035 0.023 0.212 0.217 0.238 0.124 0.019 0.018 0.021 0.009 0.034 0.066 0.062 0.033 0.088 0.113 0.114 0.06 0.012 0.015 0.016 0.006 1.6
Ionizing radiation HH kBq U235 eq 9.196 8.798 9.599 6.053 56.67 57.16 61.42 30.59 6.036 5.619 6.473 2.704 9.587 18.56 16.81 8.643 22.71 29.16 28.69 14.63 3.705 4.607 4.894 1.889 424.2
Ionizing radiation E (interim) CTUe 8E-05 7E-05 8E-05 5E-05 4E-04 4E-04 4E-04 2E-04 4E-05 4E-05 4E-05 2E-05 8E-05 2E-04 1E-04 7E-05 2E-04 2E-04 2E-04 1E-04 2E-05 3E-05 3E-05 1E-05 0.003
Photochemical ozone formation kg NMVOC eq 0.115 0.11 0.122 0.08 0.765 0.78 0.841 0.434 0.062 0.058 0.067 0.029 0.118 0.23 0.212 0.112 0.309 0.397 0.399 0.208 0.039 0.048 0.052 0.02 5.604
Acidification molc H+ eq 0.276 0.264 0.288 0.183 1.757 1.778 1.928 0.975 0.156 0.146 0.173 0.073 0.287 0.555 0.497 0.257 0.733 0.941 0.94 0.487 0.098 0.122 0.131 0.051 13.1
Terrestrial eutrophication molc N eq 0.37 0.356 0.396 0.258 2.296 2.351 2.543 1.321 0.203 0.19 0.22 0.094 0.382 0.742 0.69 0.362 0.927 1.19 1.199 0.629 0.129 0.159 0.17 0.066 17.25
Freshwater eutrophication kg P eq 0.003 0.003 0.004 0.003 0.029 0.031 0.035 0.019 0.002 0.002 0.002 0.001 0.003 0.007 0.008 0.004 0.012 0.016 0.016 0.009 0.001 0.002 0.002 8E-04 0.216
Marine eutrophication kg N eq 0.035 0.033 0.037 0.024 0.215 0.22 0.24 0.125 0.019 0.018 0.021 0.009 0.036 0.069 0.065 0.034 0.087 0.112 0.113 0.059 0.012 0.015 0.016 0.006 1.619
Freshwater ecotoxicity CTUe 122.3 120 139.1 96.28 868.9 930.2 1058 612 87.07 82.11 97.61 42.85 121.3 238.4 254.7 144.2 356.5 457.8 491.2 276.6 58 71.31 78.45 30.94 6836
Land use kg C deficit 72.27 69.27 76.4 48.57 502.1 509.5 553.7 275.7 65.55 61.31 70.31 29.83 74.64 144.7 129.1 66.57 199.6 256.3 252.1 129.3 38.15 47.4 50 18.99 3742
Water resource depletion m3 water eq 8.797 8.566 9.999 6.551 58 61.29 67.03 37.54 4.127 3.903 4.627 2.06 8.659 16.93 27.79 15.44 21.3 27.36 28.48 15.49 2.494 3.07 3.338 1.956 444.8
Mineral, fossil & ren resource depletion kg Sb eq 9E-04 9E-04 0.001 8E-04 0.005 0.006 0.007 0.004 4E-04 4E-04 4E-04 2E-04 1E-03 0.002 0.002 0.001 0.002 0.003 0.003 0.002 2E-04 3E-04 3E-04 1E-04 0.044
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Table 45 Total results per person per year in EU-27 in 2010 by life cycle stage
Impact category Unit PRODUCTION CONSTRUCTION USE (ener & wat) USE (mainten) EOL TOTAL
Climate change kg CO2 eq 2.10E+02 2.34E+01 2.03E+03 4.05E+01 1.43E+01 2.32E+03
Ozone depletion kg CFC-11 eq 9.34E-06 2.19E-06 3.39E-04 3.21E-06 1.20E-06 3.55E-04
Human toxicity, cancer effects CTUh 6.37E-05 2.97E-06 3.85E-05 4.79E-06 1.58E-06 1.12E-04
Human toxicity, non-cancer effects CTUh 7.72E-05 7.44E-06 2.26E-04 3.02E-05 6.64E-05 4.07E-04
Particulate matter kg PM2.5 eq 1.64E-01 1.55E-02 1.23E+00 1.24E-01 6.51E-02 1.60E+00
Ionizing radiation HH kBq U235 eq 2.55E+01 3.24E+00 3.85E+02 7.15E+00 2.86E+00 4.24E+02
Ionizing radiation E (interim) CTUe 6.93E-05 2.00E-05 3.02E-03 1.78E-05 9.00E-06 3.14E-03
Photochemical ozone formation kg NMVOC eq 6.30E-01 1.23E-01 4.52E+00 1.78E-01 1.49E-01 5.60E+00
Acidification molc H+ eq 8.80E-01 1.50E-01 1.13E+01 5.70E-01 1.86E-01 1.31E+01
Terrestrial eutrophication molc N eq 2.22E+00 4.35E-01 1.35E+01 5.37E-01 5.13E-01 1.72E+01
Freshwater eutrophication kg P eq 6.25E-02 3.36E-03 1.29E-01 1.90E-02 1.88E-03 2.16E-01
Marine eutrophication kg N eq 2.14E-01 4.03E-02 1.26E+00 6.03E-02 4.69E-02 1.62E+00
Freshwater ecotoxicity CTUe 1.48E+03 1.63E+02 3.05E+03 7.01E+02 1.45E+03 6.84E+03
Land use kg C deficit 2.88E+02 3.35E+01 3.24E+03 1.15E+02 6.46E+01 3.74E+03
Water resource depletion m3 water eq 1.10E+02 6.94E+00 2.76E+02 4.09E+01 1.04E+01 4.45E+02
Mineral, fossil & ren resource depletion kg Sb eq 1.51E-02 1.01E-03 1.48E-02 1.31E-02 2.15E-04 4.42E-02
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4.4.2 Interpretation of results
The contribution of each representative product (pie charts) is fairly uniform in percentage on all indicators. The
main contribution of the dwellings in the moderate climate and the lower contribution of dwellings in cold climate
is due to the number of dwellings.
Instead, despite the number of dwellings is similar to Multi-Family Houses, the Single Family Houses cause 60%
of the impact on all indicators. The reason is due to the fact that the Single Family Houses have a larger surface
area (60% of the residential area in EU is in Single Family Houses), and consequently higher consumption (energy
and materials used). In warm climate we can observe an increase in the contribution of Multi-Family Houses
compared to Single Family Houses, but it is due to the greater number of dwellings in Multi-Family Houses in this
climatic zone.
The use phase dominates all the impacts (more than 50% on all the indicators), because of energy consumption in
the use phase. The production phase dominates only in one indicator, Human toxicity, cancer effect, due to the
contribution of reinforcing steel. The end of life stands only in two indicators, Human toxicity, non-cancer effects,
and Ecotoxicity freshwater. The contribution of construction phase never exceeds 3% in all indicators.
It can be seen that dwellings of the period 1990-2010 are those with lower impacts (for all the indicators) than
others dwelling groups of the same type and climate zone; the data is influenced by the fact that this age group is
also the one with the fewest number of dwellings.
Climate Change. This impact is dominated (87% as average) by the burning of fossil fuels for the energy
consumption in the use phase of buildings. The contribution of electricity production, considering the European mix,
related to the use phase is always more than 45% in all the representative dwellings. The contribution of the
production phase is always less than 13% and the contribution of the other phases (construction, maintenance,
EOL) is less than 5% each.
It is important to highlight that the reduction of energy consumption and the increased use of energy from
renewable sources in building sector is a strong European objective (Directive 2002/91/EC and Directive 2010/31/EU
on the energy performance of buildings), but the effort related to the European energy directive is not already
readable, because the guidelines of the energy directives have not yet had widespread effect during the period
under observation (2010). It should also be pointed out that new buildings (that are adapted to the new regulatory)
suffered a setback due to the economic crisis of 2009 and existing buildings continue to be upgraded at a very low
rate; it is estimated that the existing European building stock is currently being retrofitted at a rate of approximately
1-3% of total needed per year only (Ascione, de Rossi et al. 2011).
Some authors (Asadi, da Silva et al. 2012; Flourentzou and Roulet 2002; Xing, Hewitt et al. 2011; Biekšaa,
Šiupšinskas et al. 2011; Užšilaitytea and Martinaitis 2010; Ascione, de Rossi et al. 2011; Verbeeck and Hens 2005;
Cohen, Goldman et al. 1991), deal with energy efficiency improvement of buildings through different functional
retrofit technologies; these mainly consist in adopting strategies to reduce building heating and cooling demand,
promoting the use of energy efficient equipment and low energy technologies. It should be emphasized that not
all routes, including legislative ones, to energy efficiency also lead to an overall reduction of environmental impacts.
In fact, while in the old buildings the ratio of impacts related to the production of materials and the impact on
energy consumption in the use phase is 1:10, in the zero energy building that ratio is often 1:1 (Blengini, Di Carlo,
2010; Paleari, Lavagna, Campioli, 2013).
Ozone depletion. This impact is dominated (95% as average) by the use phase of buildings, in particular related to
the electricity consumption (more than 50% of the use phase impact for all the representative dwellings). Also
district heating (by incineration of municipal solid waste) has a great contribution to this impact (due to refrigerant
HCFC-22 and trichloromethane production for wastewater treatment).
Human toxicity, cancer effects. This impact is dominated (57% as average) by the production phase, due to the
contribution of reinforcing steel (disposal to landfill of slag of unalloyed steel produced in electric furnaces, basic
114
oxygen furnace waste and sludge from steel rolling). The use phase (35% as average) contributes, due to
wastewater treatment (due to Chromium VI); natural gas, oil, coal and wood (heat) have a similar contribution;
instead the district heating (by incineration of municipal solid waste) has the greatest contribution to this impact
within the use phase (due to residue from Na-dichromate production and sludge). Small contribution comes from
maintenance (4% as average), due to the production of copper for wiring (Chromium VI and arsenic), aluminium
for windows (Chromium VI) and ceramic tiles (Chromium VI and chromium).
Human toxicity, non-cancer effects. This impact is dominated by use phase (56% as average), mainly due to wood
heat (zinc in wood ashes), district heating (by incineration of municipal solid waste) and electricity, and secondarily
to others energy sources. The production phase contribute (19% as average) due to the contribution of reinforcing
steel and concrete. In the maintenance phase (7% as average) the main contribution comes from the production
of copper (wiring). The end of life stands out in this indicator (16% as average) for the waste treatment of reinforced
concrete.
Particulate matter. This impact is dominated by use phase (77% as average), mainly due to wood heat (due to
combustion of softwood chips from forest), electricity, and secondarily to district heating (by incineration of
municipal solid waste) and coal. The production phase contribute (19% as average) due to the production of
reinforcing steel and concrete. In the maintenance phase (7% as average) the main contribution comes from the
production of copper (wiring). The end of life stand out in this indicator (16% as average) for the waste treatment
of reinforced concrete.
Ionizing radiation, human health. This impact is dominated by use phase (91% as average), mainly due to electricity
(always more than 60% of the impact of the use phase) and secondarily to district heating (15% in moderate
climate and 30% in cold climate).
Ionizing radiation, ecosystems. This impact is dominated by use phase (96% as average), mainly due to electricity
(always more than 90% of the impact of the use phase).
Photochemical ozone formation. This impact is dominated by use phase (81% as average), mainly due to electricity
(always more than 45% of the impact of the use phase), wood heat (always more than 10% of the impact of the
use phase), oil (more than 10% of the impact of the use phase in warm and moderate climate) and secondarily to
coal (more than 10% of the impact of the use phase in moderate climate) and district heating (more than 20% of
the impact of the use phase in cold climate).
Acidification. This impact is dominated by use phase (86% as average), mainly due to electricity (always more than
70% of the impact of the use phase) and secondarily to district heating (20% of the impact of the use phase in
cold climate and 10% in moderate climate) and coal (10% of the impact of the use phase in moderate climate).
Terrestrial eutrophication. This impact is dominated by use phase (79% as average), mainly due to electricity
(always more than 50% of the impact of the use phase) and secondarily to wood heat (20% of the impact of the
use phase in moderate climate and warm climate) and district heating (20% of the impact of the use phase in cold
climate and 10% of the impact of the use phase in moderate climate).
Freshwater eutrophication. This impact is dominated by use phase (60% as average), mainly due to natural gas
(30% of the impact of the use phase in warm climate and 15% of the impact of the use phase in moderate climate),
wood heat (20% of the impact of the use phase in warm climate, 15% of the impact of the use phase in cold
climate and 10% of the impact of the use phase in moderate climate), coal (more than 35% of the impact of the
use phase in moderate climate), and district heating (more than 70% of the impact of the use phase in cold climate
and 20% of the impact of the use phase in moderate climate). Also emerge a role of tap water supply and
wastewater treatment. A significant contribution derive also from production phase (29% as average) due to the
production of reinforcing steel, copper, concrete and bricks.
Marine eutrophication. This impact is dominated by use phase (78% as average), due to electricity (always more
than 50% of the impact of the use phase), wood heat (20% of the impact of the use phase in cold climate and
115
15% of the impact of the use phase in moderate and warm climate) and district heating (25% of the impact of the
use phase in cold climate and 10% of the impact of the use phase in moderate climate).
Freshwater ecotoxicity. This impact is dominated by use phase (45% as average), mainly due to district heating
(50% of the impact of the use phase in moderate climate and 85% of the impact of the use phase in cold climate)
and secondarily to natural gas and coal. Also emerge a significant role of tap water supply and wastewater
treatment. A significant contribution derive also from production phase (22% as average) mainly due to the
production of reinforcing steel and copper, and also of concrete, bricks and ceramic tiles. A significant contribution
derive also from EOL phase (21% as average) mainly due to the waste treatment of reinforcing steel at sorting
plant, and also of bricks, concrete and mineral plaster.
Land use. This impact is dominated by use phase (87% as average), mainly due to wood heat (more than 85% of
the impact of the use phase in warm and cold climate, and 75% of the impact of the use phase in moderate
climate).
Water resource depletion. This impact is dominated by use phase (62% as average), mainly due to tap water
consumption at users (always more than 15% of the impact of the use phase), natural gas (35% of the impact of
the use phase in moderate climate and 30% of the impact of the use phase in warm climate) and district heating
(15% of the impact of the use phase in moderate climate and more than 40% of the impact of the use phase in
cold climate).
Resource depletion, mineral, fossil and renewables. The production phase, the use phase and the maintenance
phase contribute in the same way (30-35%) to this impact. In the use phase, a significant contribution derive from
district heating (90% of the impact of the use phase in cold climate and more than 50% of the impact of the use
phase in moderate climate), tap water supply (25% of the impact of the use phase in warm climate, 10% of the
impact of the use phase in moderate climate and 5% of the impact of the use phase in cold climate) and natural
gas (25% of the impact of the use phase in moderate climate and 40% of the impact of the use phase in warm
climate). In the production phase, the greatest contribution derive from ceramic tile, than concrete, bricks and
copper. In the maintenance phase, the greatest contribution derive from ceramic tiles (3 replacement in 100 years
in the assumption) and copper.
116
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5 Application of the methodology for life cycle based targets
setting to food Basket of Products
A life cycle based methodology for supporting a more comprehensive and systematic approach to target setting
has been developed and proposed in Sala et al 2014. The methodology makes use of LCA in different steps: both
in the hotspots identification, in terms of the most relevant life cycle stages and environmental impacts, and in the
evaluation of the benefits associated to possible improvements to reduce the impacts.
The LCA-based methodological steps for defining targets as presented in the flowchart (figure 64), are as follows:
1. Identification of the key economic sectors4 responsible of the majority of the environmental impacts.
2. LCA of the products selected in the basket of products (BoP)
3. Literature review on hotspots for the specific sector/area of consumption and analysis of the economic,
environmental, technological megatrends
4. LCA-based hotspots analysis of “basket of products” (BoP), assessing the relevant impacts in the different
impact categories ( e.g. climate change, acidification, eutrophication etc) and life cycle stages (raw material
extraction, manufacturing, distribution use, end of life)
5. Feasibility analysis of potential improvements options, entailing the identification of possible solution and the
verification of the associated benefits
6. Quantitative targets proposal
7. Identification of policy options, policy development and stakeholders hearings
In the proposed methodology, hotspots are mentioned several times. It has to be clarified that hotspots are
evaluated at three levels. Hotspots in terms of 1. the most important economic sectors that imply impact in the
environment (e.g. food, mobility, housing); 2. the most relevant products within each category, selected according
to mass/economic coverage of the market; 3 the life cycle stages that contribute most to each impact category,
derived from the results of product life cycle analyses.
The following paragraphs illustrate the application of the methodology, starting from the identification of the key
economic sectors (section 5.1) and then focusing on the case of BoP food (sections 5.2 to 5.6). The feasibility of
the improvements and the numerical formulation of the target should be based on stakeholders and sector’s
experts. Therefore, in the current document, this aspects are partially covered (e.g. feasibility is based on
improvements proposed in sectors specific context, e.g. BAT; numerical targets are reported as they are available
in literature).
4 This could be valid also for areas of consumption and products group
120
Figure 64 Flowchart of the LCA based methodology for setting target. The core of the methodological
development presented in this report is within the dashed lines. Step 7 is the further policy
development for the adoption of the target set (LCIND Administrative Arrangement Deliverable 4, Sala
et al, 2014).
5.1 Identification of key economic sectors
Food, mobility and housing have been recognised as relevant categories of consumption by a number of European
and international documents. For example, those categories are among those leading to the majority of
environmental impacts in a life cycle perspective, as stated in study based on environmental input/ output analysis
(e.g. the EIPRO study, EC- JRC, 2006). An overview of the current situation in Europe is also presented in a recent
EEA report (EEA, 2012) where summary figures on consumption related impacts are presented.
Figure 65 illustrates the relative importance of the three sectors in terms of impacts generated by a single citizen
in comparison to the overall impacts generated in EU-27 (normalisation phase). Figures about the impacts from
the three sectors are taken form the results of the exercise done for the Basket of Products (BoP) indicators,
presented in section 5.4 of the present document, whereas figures about the overall impacts for EU-27 are the
normalisation reference factors for Product Environmental Footprint (PEF) (Benini et al, 2014). In addition, the
normalisation factors for an average EU-27 citizen are reported as reference for the interpretation of normalisation
results.
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Figure 65 Normalisation of housing, mobility and food impacts generated by an average EU citizen
applying the EU-27 normalisation factors for 2010. Please note that the figures for water resource
depletion for shelter and mobility has been cut for illustrative purposes. Labels at the top of the
columns report the actual value.
The normalisation step can help to identify the impact categories that might be more relevant for each BoP, i.e. the
ones that should be investigated more in detail. These are: HT-cancer (shelter and mobility), HT-non cancer (food),
FE (food and mobility), WD (food, shelter and mobility) and MFRRD (mobility).
There are some impact categories, namely Human toxicity-cancer effects, Human toxicity-non cancer effects,
Terrestrial eutrophication, Marine eutrophication, Freshwater ecotoxicity, Water resource depletion and Mineral,
fossil and renewable resource depletion for which the sum of the impacts from the three baskets exceed the
normalisation factor (i.e. the total impact per citizen for that category). This could be due to several reasons:
• The different approach used for the calculation of normalisation factors (top-down calculation based on
domestic emission and resource extraction in 2010 in EU-27) and the one used for the BoP (bottom-up
calculation based on process LCA and inventories for representative products).
• The temporal scale of the two systems
• Trade component included in the BoP (some products are produced outside EU and then imported for domestic
consumption or some stages of the life cycle – e.g. agricultural phase – are performed outside EU-27, i.e. not
accounted in the normalisation factors).
1.10E-06 1.79E-06
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FOOD SHELTER MOBILITY Normalisation factor citizen
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Figure 66 Relative contribution of the three BoP. 100% is the sum of the impacts per citizen for the
three BoPs for each impact category.
If we consider only the sum of the impacts per citizen generated by the three selected BoPs, illustrated in Figure
66, we can observe that BoP food mostly contributes to HT-non cancer, AP, TE, FEut, ME and LU. BoP shelter is
more relevant for ODP, HT-cancer, PM and IR. BoP mobility mostly contributes to CC (even if the contribution he
three BoPs present a similar share), POF, FEcotox, WD and MFRRD.
5.2 Literature review on hotspots and megatrends about food
consumption
The analysis of the impacts associated to BoP food could be complemented with the analysis of specific hotspots
and megatrends (e.g. see EEA, 2011) at product category/sector level. This is a fundamental step as LCA should be
complemented in terms of pressures and impacts covered (e.g. GMO’s are not taken into account in the LCA
framework) and as this analysis of the context may help better modelling the products.
Most of the studies available in the literature highlight the high contribution of all the life cycle stages of the food
production chain to GHGs emission (see, for instance, Defra, 2011; Garrone et al, 2014; Paparguyropoulou et al,
2014, Garnett 2011). EC-JRC (2006) attributes about 22% of EU GHG emission to the food sector. This is mainly
due to the emissions from landfill (food waste put in landfill emits large amount of methane – which has a high
global warming potential - and carbon dioxide), and the use of energy in all the production stages (from agriculture
- including land use change - to processing, manufacturing, transportation, storage, refrigeration, distribution, retail
and use phases). (Padfield et al., 2012; Tuncer and Schroeder, 2011; Lundqvist et al., 2008).
Other environmental impacts associated to food production are natural resource depletion (mainly in the
agricultural stage), the alteration of biogeochemical cycles of N and P - used as fertilizers in agriculture – (Smill,
2002), water consumption (Lundqvist et al., 2008), both in agriculture and in the food manufacturing stages, land
use (Meier et al, 2014) and biodiversity loss from use of pesticide, land use change and reduction of natural
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Climate change
Ozone depletion
Human toxicity, cancer effects
Human toxicity, non-cancer effects
Particulate matter
Ionizing radiation HH
Photochemical ozone formation
Acidification
Terrestrial eutrophication
Freshwater eutrophication
Marine eutrophication
Freshwater ecotoxicity
Land use
Water resource depletion
Mineral, fossil & ren resource depletion
FOOD SHELTER MOBILITY
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ecosystems for food and feed cultivation (EEA, 2012). Moreover, food waste along the whole food production chain
is a relevant source of impacts (WRAP, 2009, WRAP 2013).
Some food sectors generate higher environmental impacts than others do. Beef, butter and cheese generally have
higher environmental burdens, especially related to their carbon footprint and material intensity, while vegetables,
cereal products, potatoes and fruit such as apples, when consumed in proper season, generally have much lower
impacts (EEA, 2012).
Within the livestock sector, feed-related emissions (including land-use change) account for about 3.3 Gt CO2-eq,
that is, about half of total emissions from livestock supply chains (Gerber et al., 2013, LEAP, 2014).
Future research for reducing the environmental burden of agricultural systems should address the following issues:
precision agriculture, low leaching cropping systems, management of soil biological processes and maximum
recirculation, reduction of nutrient imbalances (Kirchmann, and Thorvaldsson, 2000).
Regarding the food manufacturing, there are studies pointing out that, due to the highly diversified nature of the
food industry, various food processing, handling and packaging operations create wastes of different quality and
quantity, which, if not treated, could lead to increasing disposal problems and severe pollution problems (Kroyer,
1995).
Extending the analysis from the agriculture and production up to the consumption phase, according to EEA (2012)
food and drink consumption is found to be responsible for around 20–30 % of environmental impacts caused by
consumption in the EU in most impact categories. Since meat and dairy products production chains have a higher
environmental impact, some studies (e.g. Rejinders and Soret, 2003, Scarborough et al, 2012, Saxe et al, 2013,
Westhoek et al, 2014) model the possible environmental impact reduction through dietary shift (e.g. comparing the
environmental impact of different dietary protein choice)
A number of very specific and detailed sector studies are available in literature and they usually cover a specific
typology of impact and life cycle stage at the time. For example, there are specific studies on food waste (e.g.
Garrone et al, 2014; Mirabella et al 2014b, Paparguyropoulou et al, 2014; Parfitt et al, 2010), on non-conventional
agricultural systems such as organic farming (e.g. Schader et al, 2014), on convenience food, i.e. comparing the
impacts of ready and home-made meals (Schmidt Rivera et al, 2014).
Other studies focus on specific food sectors which are considered more environmentally relevant, such as meat
and dairy products (e.g. Westhoeck et al, 2014) or on specific environmental impacts, such as importance of input
of nitrogen for the impact related eutrophication (e.g. Audsley and Wilkinson, 2014; Leip et al 2013).
The literatures also suggest that LCA coupled with other approaches in the food sector provides much more reliable
and comprehensive information on sustainable products and production processes (Roy et al 2009).
Grounding on the existing knowledge from literature, some technical reports and scientific papers (e.g. Garrone et
al, 2014; Tukker et al, 2009; Weidema et al, 2008; WRAP, 2013.) identify three main strategies for reducing the
impacts generated by food supply chains:
i) an environmentally sustainable increase in agricultural productivity coupled with measures aimed at
reducing emissions to air, to water and to soil,
ii) dietary changes on the consumption side (e.g. reducing the consumption of meat and dairy products)
iii) better efficiency in reducing food losses and managing food waste (e.g. through improved rate of food
waste recovery).
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5.3 LCA of the products in the Basket of products (BoP) food
Process-based LCA of the products in the BoPs are necessary to assess the impact associated to representative
product categories. The assumptions in BoP are key elements for the robustness and representativeness of the
basket. Details on this stage for BoP food are reported in section 2.2.
Figure 67 Example of LCIA results from the basket of products. For each product, it is possible to assign
the relative contribution to the total impact due to the different life cycle stages
Figure 67 illustrates the contribution analysis for the 6 life cycle stages identified for products in the BoP food:
Agriculture, Industrial processing, Logistics, Packaging, use and EoL.
Agriculture is the stage contributing the most in almost all the impact categories. the majority of the contribution
to impact is due to four processes related to animal feeding: “grass, at dairy farm”, “grass, at beef farm”, “grass
silage” and “grass, grazed in pasture” (source: Agrifootprint database - Blonk Consultants, 2014). These processes
are the major contributors to HT-cancer and HT-non cancer, AP, TEutr, MEutr and FEcotox.
As for the elementary flows, human toxicity impacts (both cancer and non-cancer) are dominated by the emission
of metals to water and to soil, especially chromium VI, chromium, zinc, copper and lead. These flows derive again
from the agricultural process related to animal feeding, but also from the treatment of biodegradable waste and
the processes for packaging production.
Long term emissions have been excluded from the LCIA, because in the dataset were accounted emission up to
60000 years. Despite delayed emission may represent an issue as highlighted by several studies (e.g. Pettersen
and Hertwich 2008, Hauschild et al 2008), in this context we accounted only for short and mid-term emission
(maximum 100 yrs).
If we include long-term emissions in LCIA, the impact to HT-cancer is about 45% higher (from 2.34e-05
CTUh/person*year-1 to 3.37e-05 CTUh/person*year-1). This does not apply to HT-non cancer.
Elementary flows of metals (especially copper and zinc, both to water and to soil) coming from the same animal
feed related activities contribute also to freshwater ecotoxicity impacts, jointly with the use of pesticides (e.g.
chlorpyrifos). Also in this case, if long term emissions of metals are included the impact is more than twice as
before (from 5.06e03 CTUe/person*year-1 to 1.08e04 CTUe/person*year-1).
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Other relevant contributions from agricultural processes derive from ammonia released by animal husbandry
activities (e.g. for acidification potential) and manure management related to grass grazing for animal feeding
(contributing to terrestrial eutrophication).
Industrial processing present overall a less share of the overall impact. Nonetheless, improvement in terms of
resource efficiency (accounting for 17% of energy consumption, Pelletier et al, 2011), waste reduction and emission
reduction (especially those related to eutrophication) are considered important as stated in sectorial studies (e.g.
Tusseau-Vuillemin, 2001, Hall and Howe, 2012, Wattanapinyo and Mol, 2013)). In the basket, hotspot are related
to potential impacts on ODP and IR, mainly due to emission of CFC-114, CFC-11, Halon 1301 Carbon-14 in air,
Radon-222 in air and Cesium-137 in water which occur during the electricity production.
Packaging of products in the BoP contribute mainly to resources depletion (water and other resources). Relevant
processes refer to the raw materials used, e.g. aluminium, glass, PET and paper and also to some packaging
production processes (e.g. glass production, blow moulding of plastic, etc.), especially due to energy consumption.
Water resource depletion is mainly related to cooling water in electricity generation plants. An additional burden on
water is the pollution of water due to the treatment of biodegradable waste.
Logistics and use phase do not appear as hotspots for the food sector in the current study, if compared to other
phases, whereas in sectorial studies logistic is also considered relevant (e.g. accounting for 12% of GHG emission
in Garnett, 2011) . This is of particular relevance when refrigeration is involved (Dabbene et al 2008, Oleglethorpe,
2010). Additionally, consumers’ choice pre and post purchase are considered upmost for several impacts. In the
BoP the consumer behavior has been modeled as defined in Vanderheyden and Aerts (2014) for the transport of
food, Nielsen et al. (2003) for refrigeration and Foster et al. (2006) for home preparation of the food. Multiple
choices/ behaviour are possible ultimately leading to higher impacts (Vázquez-Rowe et al 2013).
Finally, the only impact category to which EoL shows significant contribution is freshwater eutrophication, due to
the human metabolism of food (see section 2.4 for details).
5.4 LCA-based hotspot analysis of BoP food
The results of the process based LCA for BoP are the basis for the LCA-based hotspot analysis. The LCA of each of
the products is carried out up to the so-called ‘normalization’ step i.e. the LCA step in which the indicators associated
to the product are normalized through a set of factors so to make them comparable each other on a given relative
scale5. Generally, normalization factors represent the overall impact generated within a territorial entity (e.g. the
globe, Europe). Thus, by dividing the impacts associated to a product by the total impact observed in the globe it is
possible to understand whether the contribution of that product to the totals is high or not and then to compare
different indicators on a common basis (i.e. the share over the totals).
The normalisation step and the identification of hotspots, in BoP food is made comparing LCA results to STATUS
QUO6 and to DESIRABLE STATUS QUO7 in terms of magnitude of the environmental impacts. The status quo is
assessed through the resource efficiency life cycle indicators (based on inventory of emission and impacts for all
impact categories) used to calculate the set of normalisation factors 8 for 2010. The desirable status quo is
5 Traditionally, normalisation cannot be used as a basis to cross-compare as the absolute indicators for a given region are not directly equivalent
in terms of importance. For example, the impacts of the EU’s climate change contributions cannot be easily compared to the absolute indicator
for resource scarcity. This is only achievable within some area of protection using natural science, but primarily using socio-economic approaches
to weighting.
6 Status quo refers to the baseline situation. In our case, it represents the overall environmental impact of EU27 in 2010 for 14 impact
categories, according to the results of the Life Cycle Indicators for resources (see deliverable 3.)
7 Desirable status quo is the environmental impact of EU 27 that we may expect in the future (e.g.2020) in case our policy targets have been
reached
8 Normalisation factors reflect the overall magnitude of the impact for each impact category (e.g. the global warming potential associated to
the whole emission of CO2 and other greenhouse gases in EU in 2010 correspond to 3.9E12 kg of CO2, 1.87E10 kg of CH4 etc. the potential
126
assessed applying macro-scale targets to the status quo of 2010 (assuming which could be the status quo in 2020
if the targets are all achieved)9.
In the normalisation referred to status quo, impacts values for each of the products in the basket and for the total
BoP food are compared to the total impacts in EU-27 in 2010 (using 2010 normalisation factors for PEF, NF2010).
In order to identify for which products, in which life cycle stage and in which impact category the majority of
impacts occur, two summary tables (Table 46 and Table 47) highlighting hotspots have been prepared. Figure 68,
reporting only to the total normalized values for BoP food is added to provide an additional and simplified
information. These data can help to identify the product categories, the life cycle stages and the impact categories
on which it is necessary to concentrate effort in identifying existing or possible future eco-innovations.
Table 46 Normalisation of BoP food impacts. Normalized values for each phase are colored with a
scale from red (higher value in the table) to green (lower value in the table), to better highlight the
phases that contribute most and the most relevant impact categories
Human toxicity is the most relevant impact generated by the BoP food, followed by water resource depletion,
freshwater and marine eutrophication terrestrial eutrophication and acidification. As mentioned before, agriculture
is the most impacting phase for the majority of impact categories. When normalising impacts, EoL become a higher
contributing stage for eutrophication, ecotoxicity and water depletion, with respect to absolute values presented in
Figure 67.
impact could be expressed considering the global warming potential associated to those emission (4.60 E12 Kg CO2eq ). This figure is the
normalisation factor for EU 2010, namely the magnitude of the impact due to greenhouse gases emission in the specific year) . This set of
normalisation factors entails an hybrid production/ consumption approach (it accounts for emission from industries – production, and from
household – consumption)
9 Applying “future” normalisation factors and compare the results with 2010 figures may highlight areas of possible product improvements in
order to reach macro-scale policy objectives.
Impact Category Unit AgricultureIndustrial
processingLogistics Packaging Use EoL Total
Climate change kg CO2 eq 2.3E-10 3.4E-11 1.4E-11 1.6E-11 1.8E-11 1.1E-11 3.22E-10
Ozone depletion kg CFC-11 eq 8.3E-13 1.9E-12 9.4E-13 6.9E-13 8.3E-13 3.7E-13 5.52E-12
Human toxicity, cancer effects CTUh 9.0E-10 2.9E-11 4.3E-11 5.6E-11 2.1E-11 2.6E-11 1.08E-09
Human toxicity, non-cancer
effects CTUh 7.6E-09 3.2E-11 1.8E-11 2.8E-11 7.2E-12 1.9E-11 7.72E-09
Particulate matter kg PM2.5 eq 3.5E-10 2.6E-11 1.3E-11 3.8E-11 1.1E-11 1.4E-11 4.50E-10
Ionizing radiation HH kBq U235 eq 1.5E-11 3.2E-11 5.9E-12 8.7E-12 1.7E-11 7.5E-12 8.66E-11
Photochemical ozone
formation kg NMVOC eq 8.7E-11 2.3E-11 3.1E-11 1.8E-11 9.4E-12 9.3E-12 1.78E-10
Acidification molc H+ eq 1.1E-09 3.5E-11 1.9E-11 2.3E-11 1.4E-11 1.6E-11 1.26E-09
Terrestrial eutrophication molc N eq 1.4E-09 1.5E-11 2.1E-11 1.1E-11 5.1E-12 1.4E-11 1.43E-09
Freshwater eutrophication kg P eq 2.5E-10 1.5E-11 1.3E-12 3.9E-12 6.0E-13 3.2E-10 5.86E-10
Marine eutrophication kg N eq 1.0E-09 1.8E-11 2.0E-11 1.3E-11 4.7E-12 3.3E-10 1.41E-09
Freshwater ecotoxicity CTUe 8.8E-10 9.4E-12 8.1E-12 1.1E-11 1.8E-12 9.5E-11 1.00E-09
Land use kg C deficit 3.7E-10 2.5E-12 4.2E-12 5.4E-12 9.9E-13 5.0E-12 3.89E-10
Water resource depletion m3 water eq 4.4E-10 3.3E-10 3.0E-11 1.4E-10 1.6E-12 1.4E-10 1.07E-09
Mineral, fossil & ren resource
depletion kg Sb eq 1.0E-10 1.9E-11 3.4E-11 1.4E-10 9.6E-12 1.0E-11 3.17E-10
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Figure 68 Normalisation of total BoP food impacts
If we analyse more in detail the normalised results for the representative products in the BoP food (Table 47 - part
1 and part 2), we can note that human toxicity-non cancer is a hotspot for most of the products, as it is for the
entire BoP. The same applies to human toxicity-cancer, even if fewer products are classified as hotspot in this
impact category. As already mentioned in the discussion of BoP food absolute results, the products that generate
the highest impacts are those associated with animal husbandry and related feeding: beef, pork and poultry meat
and dairy products. Other hotspots, even if only for some impact categories, are beer, sunflower oil and sugar from
beet and - to a lesser extent – coffee, potato and bread. The products that contribute less to the environmental
impact of an EU-27 citizen, among those selected for the BoP food, are fruits (apple and orange), olive oil, mineral
water and pre-prepared meals. However, it has to be taken into account that, according the megatrends forecast
for food consumption (EEA, 2012), the purchase of pre-prepared meals is likely to significantly increase in the
future consumption habits of people.
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Table 47 (part 1) Normalisation of the impacts of products in BoP food. Normalized values for each
product are coloured with a scale from red (higher value in the table – part 1 and part 2) to green
(lower value in the whole table – part 1 and part 2), to better highlight the phases that contribute
most and the most relevant impact categories
Table 47 (part 2) Normalisation of the impacts of products in BoP food. Normalized values for each
product are coloured with a scale from red (higher value in the table – part 1 and part 2) to green
(lower value in the whole table – part 1 and part 2), to better highlight the phases that contribute
most and the most relevant impact categories
As explained before, the normalisation of BoP food referred to desirable status quo is made comparing BoP food
LCA results to two set of normalisation factors, developed in deliverable 4 of the LCIND project (Sala et al, 2014).
The first one, named NF 2020A is derived assuming the complete implementation of binding targets for 2020 to
Impact Category Unitmineral
waterbeer 66 cL coffee apple orange potato bread olive oil
sunflower
oil
sugar from
beet milk cheese butter
beef
meat
pork
meat
poultry
meat
pre-
prepared
meal
Total
Climate change kg CO2 eq 6.2E-12 1.7E-11 8.6E-12 1.8E-12 2.6E-12 1.0E-11 9.6E-12 2.9E-12 8.5E-12 6.6E-12 2.5E-11 4.2E-11 1.9E-11 6.8E-11 6.0E-11 3.1E-11 3.9E-12 3.2E-10
Ozone depletion kg CFC-11 eq 3.6E-13 9.9E-13 5.0E-13 1.0E-13 1.1E-13 5.7E-13 5.7E-13 1.4E-13 1.2E-13 1.3E-13 4.3E-13 6.3E-13 9.1E-14 7.5E-14 3.6E-13 2.0E-13 1.5E-13 5.5E-12
Human toxicity, cancer
effects CTUh 1.7E-11 5.9E-11 7.7E-12 3.3E-12 5.6E-12 4.1E-11 2.8E-11 6.3E-12 1.1E-10 3.6E-11 8.5E-11 1.3E-10 7.1E-11 1.9E-10 1.9E-10 9.0E-11 9.1E-12 1.1E-09
Human toxicity, non-cancer
effects CTUh 8.6E-12 2.5E-10 7.0E-12 1.6E-12 2.8E-12 2.1E-10 2.7E-10 7.4E-12 2.9E-10 2.8E-10 7.5E-10 1.3E-09 7.5E-10 1.3E-09 1.6E-09 6.0E-10 4.7E-11 7.7E-09
Particulate matter kg PM2.5 eq 8.3E-12 3.7E-11 1.2E-11 2.0E-12 3.2E-12 1.1E-11 1.3E-11 6.1E-12 1.1E-11 1.4E-11 3.2E-11 5.0E-11 2.5E-11 9.7E-11 8.5E-11 3.9E-11 5.0E-12 4.5E-10
Ionizing radiation HH kBq U235 eq 5.1E-12 1.1E-11 1.1E-11 1.8E-12 1.8E-12 8.7E-12 1.1E-11 2.1E-12 6.8E-13 9.5E-13 6.8E-12 1.0E-11 1.6E-12 1.1E-12 6.5E-12 3.5E-12 3.0E-12 8.7E-11
Photochemical ozone
formation kg NMVOC eq 8.7E-12 2.0E-11 7.0E-12 2.0E-12 2.7E-12 8.5E-12 8.5E-12 3.9E-12 6.4E-12 5.2E-12 1.4E-11 1.8E-11 6.5E-12 2.6E-11 2.6E-11 1.2E-11 2.5E-12 1.8E-10
Acidification molc H+ eq 7.8E-12 3.7E-11 2.2E-11 2.9E-12 5.7E-12 2.0E-11 2.9E-11 6.5E-12 3.0E-11 4.2E-11 9.2E-11 1.6E-10 8.5E-11 3.2E-10 2.8E-10 1.1E-10 9.0E-12 1.3E-09
Terrestrial eutrophication molc N eq 5.3E-12 3.0E-11 1.6E-11 2.2E-12 5.3E-12 1.8E-11 2.7E-11 5.2E-12 3.2E-11 5.0E-11 1.1E-10 1.8E-10 1.0E-10 3.8E-10 3.4E-10 1.3E-10 8.0E-12 1.4E-09
Freshwater eutrophication kg P eq 1.6E-12 3.8E-11 3.9E-12 3.3E-13 5.0E-12 3.6E-11 3.2E-11 2.3E-12 2.7E-11 9.2E-12 9.6E-11 9.8E-11 1.6E-11 7.5E-11 1.2E-10 2.4E-11 2.5E-12 5.9E-10
Marine eutrophication kg N eq 5.6E-12 3.9E-11 2.8E-11 3.6E-12 9.7E-12 4.2E-11 6.7E-11 7.8E-12 4.6E-11 5.8E-11 1.1E-10 1.8E-10 7.4E-11 2.8E-10 3.1E-10 1.3E-10 9.5E-12 1.4E-09
Freshwater ecotoxicity CTUe 3.8E-12 1.0E-10 9.1E-11 1.1E-11 2.2E-11 1.9E-11 1.7E-11 5.9E-12 5.5E-11 1.7E-11 6.7E-11 1.1E-10 6.3E-11 1.3E-10 2.0E-10 8.6E-11 1.1E-11 1.0E-09
Land use kg C deficit 1.9E-12 1.1E-11 7.5E-12 1.7E-12 2.6E-12 6.0E-12 9.0E-12 1.3E-11 3.7E-11 8.1E-12 2.2E-11 3.7E-11 2.1E-11 7.7E-11 8.7E-11 4.6E-11 3.3E-12 3.9E-10
Water resource depletion m3 water eq 8.2E-11 3.3E-11 3.3E-11 4.3E-11 1.0E-10 7.7E-11 2.6E-11 3.5E-11 4.2E-11 6.1E-11 8.1E-11 2.2E-10 1.6E-11 1.4E-10 4.2E-11 2.6E-11 2.5E-11 1.1E-09
Mineral, fossil & ren
resource depletion kg Sb eq 1.7E-11 7.0E-11 2.0E-11 3.1E-12 7.6E-12 3.9E-11 7.6E-12 1.4E-11 1.6E-11 7.8E-12 2.4E-11 1.9E-11 1.7E-11 1.6E-11 2.2E-11 1.2E-11 3.7E-12 3.2E-10
Impact Category Unitmineral
waterbeer 66 cL coffee apple orange potato bread olive oil
sunflower
oil
sugar from
beet milk cheese butter
beef
meat
pork
meat
poultry
meat
pre-
prepared
meal
Total
Climate change kg CO2 eq 6.2E-12 1.7E-11 8.6E-12 1.8E-12 2.6E-12 1.0E-11 9.6E-12 2.9E-12 8.5E-12 6.6E-12 2.5E-11 4.2E-11 1.9E-11 6.8E-11 6.0E-11 3.1E-11 3.9E-12 3.2E-10
Ozone depletion kg CFC-11 eq 3.6E-13 9.9E-13 5.0E-13 1.0E-13 1.1E-13 5.7E-13 5.7E-13 1.4E-13 1.2E-13 1.3E-13 4.3E-13 6.3E-13 9.1E-14 7.5E-14 3.6E-13 2.0E-13 1.5E-13 5.5E-12
Human toxicity, cancer
effects CTUh 1.7E-11 5.9E-11 7.7E-12 3.3E-12 5.6E-12 4.1E-11 2.8E-11 6.3E-12 1.1E-10 3.6E-11 8.5E-11 1.3E-10 7.1E-11 1.9E-10 1.9E-10 9.0E-11 9.1E-12 1.1E-09
Human toxicity, non-cancer
effects CTUh 8.6E-12 2.5E-10 7.0E-12 1.6E-12 2.8E-12 2.1E-10 2.7E-10 7.4E-12 2.9E-10 2.8E-10 7.5E-10 1.3E-09 7.5E-10 1.3E-09 1.6E-09 6.0E-10 4.7E-11 7.7E-09
Particulate matter kg PM2.5 eq 8.3E-12 3.7E-11 1.2E-11 2.0E-12 3.2E-12 1.1E-11 1.3E-11 6.1E-12 1.1E-11 1.4E-11 3.2E-11 5.0E-11 2.5E-11 9.7E-11 8.5E-11 3.9E-11 5.0E-12 4.5E-10
Ionizing radiation HH kBq U235 eq 5.1E-12 1.1E-11 1.1E-11 1.8E-12 1.8E-12 8.7E-12 1.1E-11 2.1E-12 6.8E-13 9.5E-13 6.8E-12 1.0E-11 1.6E-12 1.1E-12 6.5E-12 3.5E-12 3.0E-12 8.7E-11
Photochemical ozone
formation kg NMVOC eq 8.7E-12 2.0E-11 7.0E-12 2.0E-12 2.7E-12 8.5E-12 8.5E-12 3.9E-12 6.4E-12 5.2E-12 1.4E-11 1.8E-11 6.5E-12 2.6E-11 2.6E-11 1.2E-11 2.5E-12 1.8E-10
Acidification molc H+ eq 7.8E-12 3.7E-11 2.2E-11 2.9E-12 5.7E-12 2.0E-11 2.9E-11 6.5E-12 3.0E-11 4.2E-11 9.2E-11 1.6E-10 8.5E-11 3.2E-10 2.8E-10 1.1E-10 9.0E-12 1.3E-09
Terrestrial eutrophication molc N eq 5.3E-12 3.0E-11 1.6E-11 2.2E-12 5.3E-12 1.8E-11 2.7E-11 5.2E-12 3.2E-11 5.0E-11 1.1E-10 1.8E-10 1.0E-10 3.8E-10 3.4E-10 1.3E-10 8.0E-12 1.4E-09
Freshwater eutrophication kg P eq 1.6E-12 3.8E-11 3.9E-12 3.3E-13 5.0E-12 3.6E-11 3.2E-11 2.3E-12 2.7E-11 9.2E-12 9.6E-11 9.8E-11 1.6E-11 7.5E-11 1.2E-10 2.4E-11 2.5E-12 5.9E-10
Marine eutrophication kg N eq 5.6E-12 3.9E-11 2.8E-11 3.6E-12 9.7E-12 4.2E-11 6.7E-11 7.8E-12 4.6E-11 5.8E-11 1.1E-10 1.8E-10 7.4E-11 2.8E-10 3.1E-10 1.3E-10 9.5E-12 1.4E-09
Freshwater ecotoxicity CTUe 3.8E-12 1.0E-10 9.1E-11 1.1E-11 2.2E-11 1.9E-11 1.7E-11 5.9E-12 5.5E-11 1.7E-11 6.7E-11 1.1E-10 6.3E-11 1.3E-10 2.0E-10 8.6E-11 1.1E-11 1.0E-09
Land use kg C deficit 1.9E-12 1.1E-11 7.5E-12 1.7E-12 2.6E-12 6.0E-12 9.0E-12 1.3E-11 3.7E-11 8.1E-12 2.2E-11 3.7E-11 2.1E-11 7.7E-11 8.7E-11 4.6E-11 3.3E-12 3.9E-10
Water resource depletion m3 water eq 8.2E-11 3.3E-11 3.3E-11 4.3E-11 1.0E-10 7.7E-11 2.6E-11 3.5E-11 4.2E-11 6.1E-11 8.1E-11 2.2E-10 1.6E-11 1.4E-10 4.2E-11 2.6E-11 2.5E-11 1.1E-09
Mineral, fossil & ren
resource depletion kg Sb eq 1.7E-11 7.0E-11 2.0E-11 3.1E-12 7.6E-12 3.9E-11 7.6E-12 1.4E-11 1.6E-11 7.8E-12 2.4E-11 1.9E-11 1.7E-11 1.6E-11 2.2E-11 1.2E-11 3.7E-12 3.2E-10
Impact Category Unitmineral
waterbeer 66 cL coffee apple orange potato bread olive oil
sunflower
oil
sugar from
beet milk cheese butter
beef
meat
pork
meat
poultry
meat
pre-
prepared
meal
Total
Climate change kg CO2 eq 6.2E-12 1.7E-11 8.6E-12 1.8E-12 2.6E-12 1.0E-11 9.6E-12 2.9E-12 8.5E-12 6.6E-12 2.5E-11 4.2E-11 1.9E-11 6.8E-11 6.0E-11 3.1E-11 3.9E-12 3.2E-10
Ozone depletion kg CFC-11 eq 3.6E-13 9.9E-13 5.0E-13 1.0E-13 1.1E-13 5.7E-13 5.7E-13 1.4E-13 1.2E-13 1.3E-13 4.3E-13 6.3E-13 9.1E-14 7.5E-14 3.6E-13 2.0E-13 1.5E-13 5.5E-12
Human toxicity, cancer
effects CTUh 1.7E-11 5.9E-11 7.7E-12 3.3E-12 5.6E-12 4.1E-11 2.8E-11 6.3E-12 1.1E-10 3.6E-11 8.5E-11 1.3E-10 7.1E-11 1.9E-10 1.9E-10 9.0E-11 9.1E-12 1.1E-09
Human toxicity, non-cancer
effects CTUh 8.6E-12 2.5E-10 7.0E-12 1.6E-12 2.8E-12 2.1E-10 2.7E-10 7.4E-12 2.9E-10 2.8E-10 7.5E-10 1.3E-09 7.5E-10 1.3E-09 1.6E-09 6.0E-10 4.7E-11 7.7E-09
Particulate matter kg PM2.5 eq 8.3E-12 3.7E-11 1.2E-11 2.0E-12 3.2E-12 1.1E-11 1.3E-11 6.1E-12 1.1E-11 1.4E-11 3.2E-11 5.0E-11 2.5E-11 9.7E-11 8.5E-11 3.9E-11 5.0E-12 4.5E-10
Ionizing radiation HH kBq U235 eq 5.1E-12 1.1E-11 1.1E-11 1.8E-12 1.8E-12 8.7E-12 1.1E-11 2.1E-12 6.8E-13 9.5E-13 6.8E-12 1.0E-11 1.6E-12 1.1E-12 6.5E-12 3.5E-12 3.0E-12 8.7E-11
Photochemical ozone
formation kg NMVOC eq 8.7E-12 2.0E-11 7.0E-12 2.0E-12 2.7E-12 8.5E-12 8.5E-12 3.9E-12 6.4E-12 5.2E-12 1.4E-11 1.8E-11 6.5E-12 2.6E-11 2.6E-11 1.2E-11 2.5E-12 1.8E-10
Acidification molc H+ eq 7.8E-12 3.7E-11 2.2E-11 2.9E-12 5.7E-12 2.0E-11 2.9E-11 6.5E-12 3.0E-11 4.2E-11 9.2E-11 1.6E-10 8.5E-11 3.2E-10 2.8E-10 1.1E-10 9.0E-12 1.3E-09
Terrestrial eutrophication molc N eq 5.3E-12 3.0E-11 1.6E-11 2.2E-12 5.3E-12 1.8E-11 2.7E-11 5.2E-12 3.2E-11 5.0E-11 1.1E-10 1.8E-10 1.0E-10 3.8E-10 3.4E-10 1.3E-10 8.0E-12 1.4E-09
Freshwater eutrophication kg P eq 1.6E-12 3.8E-11 3.9E-12 3.3E-13 5.0E-12 3.6E-11 3.2E-11 2.3E-12 2.7E-11 9.2E-12 9.6E-11 9.8E-11 1.6E-11 7.5E-11 1.2E-10 2.4E-11 2.5E-12 5.9E-10
Marine eutrophication kg N eq 5.6E-12 3.9E-11 2.8E-11 3.6E-12 9.7E-12 4.2E-11 6.7E-11 7.8E-12 4.6E-11 5.8E-11 1.1E-10 1.8E-10 7.4E-11 2.8E-10 3.1E-10 1.3E-10 9.5E-12 1.4E-09
Freshwater ecotoxicity CTUe 3.8E-12 1.0E-10 9.1E-11 1.1E-11 2.2E-11 1.9E-11 1.7E-11 5.9E-12 5.5E-11 1.7E-11 6.7E-11 1.1E-10 6.3E-11 1.3E-10 2.0E-10 8.6E-11 1.1E-11 1.0E-09
Land use kg C deficit 1.9E-12 1.1E-11 7.5E-12 1.7E-12 2.6E-12 6.0E-12 9.0E-12 1.3E-11 3.7E-11 8.1E-12 2.2E-11 3.7E-11 2.1E-11 7.7E-11 8.7E-11 4.6E-11 3.3E-12 3.9E-10
Water resource depletion m3 water eq 8.2E-11 3.3E-11 3.3E-11 4.3E-11 1.0E-10 7.7E-11 2.6E-11 3.5E-11 4.2E-11 6.1E-11 8.1E-11 2.2E-10 1.6E-11 1.4E-10 4.2E-11 2.6E-11 2.5E-11 1.1E-09
Mineral, fossil & ren
resource depletion kg Sb eq 1.7E-11 7.0E-11 2.0E-11 3.1E-12 7.6E-12 3.9E-11 7.6E-12 1.4E-11 1.6E-11 7.8E-12 2.4E-11 1.9E-11 1.7E-11 1.6E-11 2.2E-11 1.2E-11 3.7E-12 3.2E-10
129
the NF 2010 set. The second one, named NF 2020B, is derived assuming the implementation of both binding and
non-binding targets for 2020 to the NF 2010 set. Results of the normalisation step with the two sets applied to
BoP food are presented in figure 69. The results normalised with the three NF sets (NF 2010, NF 2020A and NF
2020B) show no big differences in general, except for the impact category water resource depletion, where BoP
food has a higher importance when applying NF 2020B. Small differences between NF 2010 and NF 2020 A or
2020 B arise in HT-cancer, PM, AP and eutrophication.
Figure 69 Normalisation of total BoP food impacts applying NF 2010, NF 2020A and NF 2020B
In addition to this, a second set of NF for 2010 (NF 2010C), limited to some of the impact categories included in
ILCD, has been developed by Bjørn and Hauschild (2014), following the carrying capacity approach applied to
planetary boundaries studies. Figure 70 compares the result of BoP food normalisation made with NF 2010 and
NF 2010C (only for the impact categories for which NF 2010C are available). BoP food results normalised with NF
2010C are generally lower than the ones normalised with NF 2010, with the exception of climate change. This is
likely do to the fact that NF 2010C refer to the desirable worldwide impact, whereas NF 2010 refer specifically to
EU-27 impacts, without taking into account the impacts generated by supply chains outside from the EU boundaries.
0.00E+00
1.00E-09
2.00E-09
3.00E-09
4.00E-09
5.00E-09
6.00E-09
7.00E-09
8.00E-09
Clim
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Normalized BoP food NF2010 Normalized BoP food NF2020A Normalized BoP food NF2020B
130
Figure 70 Normalisation of total BoP food impacts applying NF 2010 and NF 2010C
5.5 Feasibility analysis of improvements
Direct application of macro-scale targets to sectors and product groups is considered very difficult, as there are
significant differences among sectors and related reduction potentials. A guideline for setting target for the specific
sector/ product group is required and should follow two steps: identification of possible solutions; verification of
the benefits associated to the proposed solutions.
5.5.1 Identification of possible solutions
Possible solutions for reducing impacts of the sector/ product group should strategically address the hotspots (in
terms of product categories, life cycle stages or type of impacts) identified before. Strategies for improvements
are selected according to the sustainability principles listed in the checklist for eco-innovation presented in
deliverable 4 and a literature review on BATs and eco-innovations performed specifically for this work (see section
5.5.3).
As resulting from the figures presented in the previous sections (5.1 to 5.6), the hotspots for BoP food are:
• in terms of impact categories: Human toxicity, followed by water resource depletion, freshwater and marine
ecotoxicity, terrestrial eutrophication and acidification.
• In terms of life cycle stages: agriculture, which contributes to over 85% of impacts in 11 impact categories out
of the 15 considered in ILCD, followed by EoL, which generate eutrophication impacts due to the human
metabolism of food, and industrial processing, especially for what concerns water depletion.
• In terms of product categories: food products related to animal husbandry and related feeding, such as beef,
pork and poultry meat and dairy products. Other hotspots, even if only for some impact categories, are beer,
sunflower oil and sugar from beet and - to a lesser extent – coffee, potato and bread.
Another hotspot, which is cross-cutting among products and life cycle stages, is food loss happening throughout
the whole FSC, from agriculture to food consumption of households.
0.00E+00
2.00E-10
4.00E-10
6.00E-10
8.00E-10
1.00E-09
1.20E-09
1.40E-09
Clim
ate
ch
ange
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chem
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NormalizedBoP foodNF2010
NormalizedBoP foodNF2010C
131
As mentioned already in section 5.2, the main strategies for reducing for reducing impacts related to those hotspots
can be grouped in three main areas:
i) an environmentally sustainable increase in agricultural productivity coupled with measures aimed at reducing
emissions to air, to water and to soil,
ii) dietary changes on the consumption side (e.g. reducing the consumption of meat and dairy products),
iii) higher efficiency in reducing food losses and managing food waste (e.g. through improved rate of food waste
recovery).
More detailed improvements and eco-innovations for all the stages of the FSC are presented below.
5.5.1.1 Reduction of emissions:
Agriculture
• Avoiding oversupply of nutrients in the diet of cattle, pig and poultry, to reduce nutrients and metals emissions
in manure (which can be also used in cultivation)
• Avoiding oversupply of nutrients to crops
• Reducing the use of pesticides in crops cultivation
• Land use management option to increase CO2 fixation
• Reducing the use of antibiotics for animal husbandry
• Reducing ammonia emissions from manure storage and management
• Improve energy efficiency in animal husbandry facilities (e.g. lighting in poultry rearing, heating in pigs rearing,
etc.)
• Avoiding overproduction (i.e. production inputs and emissions with no associated outputs)
Industrial processing
• Improving energy efficiency in food processing plants
• Implementing water saving measures in food processing plants (e.g. reducing the amount of water used to
clean slaughterhouses facilities)
• Implementing efficient methods to separate solid waste from wastewater, to reduce the need of wastewater
treatments and reduce freshwater eutrophication
Logistics
• Reducing transport distance of raw materials and finished products (paying attention to possible burden
shifting – e.g. higher emissions for electricity generation in a country where the energy mix has a lower share
of renewable energy sources than in more distant countries)
Use
• Implementing dietary choices with preference to less impacting food products (e.g. reducing the amount of
meat and dairy products)
EoL
• Improving the efficiency of wastewater treatment systems to reduce eutrophication from human metabolism
and from the treatment of wastewater from industrial processing plants.
5.5.1.2 Eco-efficiency:
Agriculture
• Reducing/optimising input of resources (water, fertilisers, pesticides, etc.)
132
• Increasing crop yields to reduce the area needed for cultivation
• Optimizing nutrients input in animal diet according to actual requirements (avoiding oversupply). The
optimization of feed inputs helps also to reduce the amount of excretion from animals. In some cases, e.g. for
pigs, a more balanced input of feed can help to reduce also the water needed.
Industrial processing
• Reducing energy use
• Reducing water use. Water saving measures can also imply a reduction of the energy use (in case water needs
to be heated or cooled) and of wastewater treatment needs.
Use
• Reducing input (energy and material) for retail activities (e.g. cooling/storage)
• Optimizing the consumption of food in households (e.g. through meal planning), also to avoid waste (see related
section for details)
Packaging
• Reducing the amount of packaging per unit of product (e.g. avoiding or reducing packaging for products that
don’t need packaging for food preservation)
• Reducing the amount of resources needed to perform the same packaging function (e.g. using lighter materials,
avoiding secondary packaging when not needed, etc)
Logistics
• Optimization of logistic to reduce fuel inputs for transport
5.5.1.3 Waste as resource and industrial symbiosis potential
Agriculture
• Reducing losses due to mechanical damage and/or spillage during harvest operation (e.g. threshing or fruit
picking), crops sorted out post-harvest, etc.
• Optimisation of the use of residues in the field
• Reducing product losses during postharvest handling and storage and transportation between farm and
distribution.
Industrial processing
• Reducing losses due to spillage and degradation during industrial or domestic processing, e.g. juice production,
canning and bread baking. Losses may occur when crops are sorted out if not suitable to process or during
washing, peeling, slicing and boiling or during process interruptions and accidental spillage.
• Assessment of potential use of by-products of the food manufacturing industries as input for other
process/products. For instance, many wastes in the food sector contain active ingredients that could be used
for cosmetic and nutraceutic products (Mirabella et al 2014), or bio-chemicals (Sheldon, 2014). This kind of
interventions are aimed at fulfilling the objective of zero landfilling for food waste. Examples can be find in
Turon et al (2014), Luque and Clark (2013), Lin et al (2013) and Pleissner et al (2013).
Use
• Reducing losses and waste in the market system, at e.g. wholesale markets, supermarkets, retailers and wet
markets. Food losses at the distribution and retailing stages can be partially avoided through programmes for
the re-distribution of products not suitable for selling but still edible (e.g. through charity initiatives)
133
• Reducing food waste from household consumption, e.g. through accurate meal planning and shopping planning
(e.g. avoiding to buy products not needed because the consumer didn’t check food already available at home
before going to the shop)
• Implementing proper waste separate collection, i.e. allowing for composting of food waste
EoL
• Evaluation of the best options for food waste treatment for recovering resources (e.g. composting, biogas and
bioenergy, etc.)
5.5.2 Quantitative target proposal
Specific targets for the BoP food related to the improvements and eco-innovation needed in the FSC to make these
strategies operational are identified through a review of documents about eco-innovation in the food sector, such
as10: scientific literature, technical reports (e.g. by DGENV/JRC/etc.), IMPRO studies, Best Available Technologies
Reference Document (BREF).
10 Detailed bibliography of the documents used to identify possible improvements in support to targets definition is listed in
Table 3
134
Table 48 List of suggested improvements and related targets for the hotspots of the BoP food. Superscript letters after each improvement
and target indicate the related bibliographic reference: aAudsley and Wilkinson, 2014; bWeidema et al, 2008; cEC-JRC, 2013; dEC, 2005; eEC,
2006; fWesthoek et al, 2014; gSchmidt Rivera et al, 2014; hWRAP, 2013; iEC, 2011; lFrench Ministry for Agriculture, Food and Forests (2010); mDourmad and Jondreville, 2007; nGarrone et al, 2014; oTuron et al (2014); pLuque and Clark (2013); qLin et al (2013); rPleissner et al (2013); sGarnett, 2011; tCordell et al, 2011; uScholz et al, 2013; vScholz et al, 2014; zPetzet and Cornel, 2013
Agriculture Industrial processing
Logistics Packaging Use EoL
Crops Animal husbandry
Pigs and poultry rearing
Slaughterhouses
Manufacturing of food and drinks
Climate change
Suggested improvement
Agronomic measures to increase cereal crops yields and to reduce N inputa
To reduce methane emissions from dairy cows and animal manure (partly by using 50% of all manure for biogas production)b
Efficient use of energy - Applying better lighting schemes and substituting light bulbs with more efficient onesc
Use of defrost-on-demand system for cooled roomsd
Improve energy efficiency and reduce electricity usee
Switch off the engine and refrigerator unit of a vehicle during loading/unloading and when parkede
Diet change - Reduction of the amount of meat and dairyf
Better land use to improve carbon balance (e.g. by sequestration)s
Efficient use of energy - Better insulation of the poultry and pigs housingsc
Eating home-made meals instead of ready-made onesg
Reported range of
input/emission shift or
reported target
Around 5-15% GHG reductiona
18 kg/t milk producedb
up to 75% energy savingsc
up to 30% energy savings for cooled roomsd
up to 15% energy savingse not quantifiede
25–40% reduction in GHGs emissionsf
Controversial, not yet quantified as target
30-50% savings of gas use for poultryc 20% savings of thermal energy use for pigsc
up to 35% reduction GHGs emissiong
Human toxicity
Suggested improvement
To reduce pesticide usel
To reduce Cu emissions to soilb
To reduce Cu emissions to soilb
To avoid oversupply of Cu and Zn in pig dietm
Reported range of
input/emission shift or
reported target
50% reduction in pesticide usel
5 kgCu/t milk producedb 2.3 g/pigb
Max conc of Cu in pigs diet: 3g/pigm Max conc of Zn in pigs diet: 9g/pigm
135
Agriculture Industrial processing
Logistics Packaging Use EoL
Crops Animal husbandry
Pigs and poultry rearing
Slaughterhouses
Manufacturing of food and drinks
Eutrophication
Suggested improvement
To reduce nitrate leaching from cereal productionb
To reduce nitrate leaching from animal manureb
Reducing emissions to soil from manure storage (e.g. storage on a solid impermeable floor and coverage of manure stored)c
Removing (or avoiding) solids from wastewaterd
Removing (or avoiding) solids from wastewater in fish processinge
Eating home-made meals instead of ready-made onesg
Synergic implementation of improved nutritional strategies to reduce ammonia emissionsc
Diet change - Reduction of the amount of meat and dairyf
0.1% reduction of P in feed for pigs and poultryc
Closing the loop of P nutrientt,u,v,z
Reported range of
input/emission shift or
reported target
6.5 kg N/t cerealsb
6.3 kg N/t milk producedb
10-65% reduction of ammonia emissions from manure storagec
Reduction up tod: 75% COD 70% BOD 55% total N 70% total P 85% fat
Reduction up toe: 40% COD 30% BOD
up to 75% reduction of eutrophication potentialg
up to 70% ammonia emission reductionc
40% reduction in nitrogen emissionsg
20-40% reduction of P excretion for pigsc 20% reduction of P excretion for poultryc
No P emissions from agricultural systemst,u,v,z
136
Agriculture Industrial processing
Logistics Packaging Use EoL
Crops Animal husbandry
Pigs and poultry rearing
Slaughterhouses
Manufacturing of food and drinks
Acidification
Suggested improvement
Efficient use of energy - Applying better lighting schemes and substituting light bulbs with more efficient onesc
Use of defrost-on-demand system for cooled roomsd
Switch off the engine and refrigerator unit of a vehicle during loading/unloading and when parkede
Eating home-made meals instead of ready-made onesg
Efficient use of energy - Better insulation of the poultry and pigs housingsc
Reported range of
input/emission shift or
reported target
up to 75% energy savingsc
up to 30% energy savings for cooled roomsd not quantifiede
Up to 75% reduction of acidification potentialg
30-50% savings of gas use for poultryc 20% savings of thermal energy use for pigsc
Ecotoxicity
Suggested improvement
To reduce pesticide use in agriculturel
To avoid oversupply of Cu and Zn in pig diet
Reported range of
input/emission shift or
reported target 50% reduction in pesticide usel
Max conc of Cu in pigs diet: 3g/pigMax conc of Zn in pigs diet: 9g/pig
Resource efficiency
Suggested improvement
To increase cereal crops yields to reduce the area requirementb
3% reduction of proteins in feeding for poultry rearingc
Implementation of water saving measures (e.g. when washing the floor or the equipment)d
Implementation of water saving measurese
To reduce the amount of packaging per unit of product
Reducing the quantity of edible food that is wasted at retailer shops or canteens
Reduction of resource input
137
Agriculture Industrial processing
Logistics Packaging Use EoL
Crops Animal husbandry
Pigs and poultry rearing
Slaughterhouses
Manufacturing of food and drinks
Reported range of
input/emission shift or
reported target 4500kgcereals/hab
8% reduction in water needsc
Up to 75% water savingsd
Up to 40% water savingse not quantified
50% of potential food losses avoided in the retailing and consumption stagesn
20% reduction of resource input in the whole FSC as foreseen by Roadmap to a Resource Efficient Europei
Waste
Suggested improvement
Synergic implementation of improved nutritional strategies (phase feeding) to reduce nutrients emissionsc
Removing (or avoiding) solids from wastewaterd
Removing (or avoiding) solids from wastewater in fish processinge
Prevention of food waste at householdsh
Prevention of food losses throughout the whole stagesi
Avoiding landfilling of food waste through circular economy practicies (e.g. industrial symbiosis for agriculture and food manufacturing waste)
Reported range of
input/emission shift or
reported target 10-30% reduction of N excretedc
Reduction up tod: 75% COD 70% BOD 55% total N 70% total P 85% fat
Reduction up toe: 40% COD 30% BOD
11.4% reduction of food waste compared to 2012 levels (e.g. in the UK)h
50% food waste reduction target for 2020 set by Roadmap to a Resource Efficient Europei
Zero landfill of food wasteo,p,q,r
138
5.6 Identification of policy options, policy development and
stakeholders hearings
Based on target proposal, several policy options (not only limited to environmental policies, but affecting a
broad range of policy sectors) may be possible and they are besides the scope of this deliverable. However, it
is worthy to discuss how to ensure positive benefits associated to target implementation and support to target
definition in policies.
Many improvements are proposed in literature, focusing on a specific issue at the time. In table 3, in which we
present a selection of the most relevant improvements identified form the review, we cover the impact
categories and the life cycle stages were a hotspot has been identified.
To support the further selection of targets and assessing the real benefits related to their implementation, a
further step is needed. Indeed, in our methodology proposed in Sala et al 2014, all the proposed improvements
and targets should be subjected to an integrated analysis in order to avoid burden shifting. E.g., if the
achievement of the zero food waste target as to be reached, including extensive development of biorefinery
(e.g. see Clark et al 2006), it has to be ensured that the new process introduced are not offsetting the benefit
associated to the used of the waste as resources. This is very much needed to ensure that an improvement in
one impact category/ life cycle stage is not leading to increased impact in another one.
The application of sustainability principles and strategies may indeed lead to situation in which there are
conflicting results and where an LCA may help identifying the best option or supporting a strategy for impact
reduction. We report below a selection of examples where a strategy following sustainability principles may be
challenged by other impacts occurring when implemented.
Buy local vs dietary shift
Despite significant recent public concern and media attention to the environmental impacts of food, few studies
in the United States have systematically compared the life-cycle greenhouse gas (GHG) emissions associated
with food production against long-distance distribution, aka “food-miles.” Weber and Matthews (2008) found
that that although food is transported long distances in general (1640 km delivery and 6760 km life-cycle
supply chain on average) the GHG emissions associated with food are dominated by the production phase,
contributing 83% of the average U.S. household’s 8.1 t CO2e/yr footprint for food consumption. Transportation
as a whole represents only 11% of life-cycle GHG emissions, and final delivery from producer to retail
contributes only 4%. Different food groups exhibit a large range in GHG-intensity; on average, red meat is
around 150% more GHG-intensive than chicken or fish. Thus, they suggest that dietary shift can be a more
effective means of lowering an average household’s food-related climate footprint than “buying local.” Shifting
less than one day per week’s worth of calories from red meat and dairy products to chicken, fish, eggs, or a
vegetable-based diet achieves more GHG reduction than buying all locally sourced food. This could be true for
GHG-related emission but should be verified against all the different impact categories involved.
Buy organic vs systematized logistic for food delivery
Coley et al 2009, provides a critical commentary on the conception of food distance followed by an empirical
application of food distance to two contrasting food distribution systems based on carbon emissions accounting
within these systems. The comparison is between the carbon emissions resultant from operating a large-scale
vegetable box system and those from a supply system where the customer travels to a local farm shop. The
study is based on fuel and energy use data collected from one of the UK’s largest suppliers of organic produce.
The findings suggest that if a customer drives a round-trip distance of more than 6.7 km in order to purchase
their organic vegetables, their carbon emissions are likely to be greater than the emissions from the system of
cold storage, packing, transport to a regional hub and final transport to customer’s doorstep used by large-
scale vegetable box suppliers. Consequently some of the ideas behind localism in the food sector may need to
be revisited. However, other impacts other than GHG may be related to the different choice and should be taken
into account.
139
Organic vs land use intensity and reduced productivity
The choice of organic food is perceived from different point of view as a more sustainable one. Organic
agriculture refers to a farming system that enhance soil fertility through maximizing the efficient use of local
resources, while foregoing the use of agrochemicals, the use of Genetic Modified Organisms (GMO), as well as
that of many synthetic compounds used as food additives. Organic agriculture relies on a number of farming
practices based on ecological cycles, and aims at minimizing the environmental impact of the food industry,
preserving the long term sustainability of soil and reducing to a minimum the use of non-renewable resources.
Several studies carried out a comparative review of the environmental performances of organic agriculture
versus conventional farming, and also discusses the difficulties inherent in this comparison process (Gomiero
et al 2011). Some studies support the fact that, overall, organic agriculture appears to perform better than
conventional farming, and provides also other important environmental advantages, such as halting the use of
harmful chemicals and their spread in the environment and along the trophic chain, and reducing water use.
However, in the case of organic agriculture, the implications of a reduced productivity for increasing land
needed and impact on the socioeconomic system should be considered and suitable agricultural policies worked
out.
Moreover, there are situation in which efficiency should be assessed at a system level and not at a field/
product level. E.g. the objective of increasing productivity when a high amount of yields is left in the field for
economic reasons (e.g. keeping high the price of the product) or in presence of so called “harmful subsides”.
Kummu et al 2012 found that around one quarter of the produced food supply (614 kcal/cap/day) is lost within
the food supply chain (FSC). The production of these lost and wasted food crops accounts for 24% of total
freshwater resources used in food crop production (27 m3/cap/yr), 23% of total global cropland area
(31 × 10− 3 ha/cap/yr), and 23% of total global fertiliser use (4.3 kg/cap/yr). The per capita use of resources
for food losses is largest in North Africa & West-Central Asia (freshwater and cropland) and North America &
Oceania (fertilisers). The smallest per capita use of resources for food losses is found in Sub-Saharan Africa
(freshwater and fertilisers) and in Industrialised Asia (cropland). Relative to total food production, the smallest
food supply and resource losses occur in South & Southeast Asia. If the lowest loss and waste percentages
achieved in any region in each step of the FSC could be reached globally, food supply losses could be halved.
By doing this, there would be enough food for approximately one billion extra people.
Additionally, it has to be noted that targets related to behaviour could be more difficult to be introduced in
policy. However, promoting targets on the eco-friendly behaviour may be couple with health-related claims:
• Healthy and environmentally friendly diet: shift in diet and better health condition (reducing cardiovascular
diseases, cancers, diabetes etc. - e.g. Saxe, 2013, Scarborough, 2012)
• Healthy and environmentally friendly houses: reducing the use of harmful substances in construction
materials may enhance health of house’s occupants (allergies, asthma etc.); reducing average temperature
in the houses may help avoiding seasonal disease;
• Healthy and environmentally friendly mobility options: reducing the use of private car, towards public
transport/ bicycle etc. not only reduces environmental impact but increases the chance of making physical
activity.
Finally, in order to facilitate the understanding of the results for BoP food and to support the discussion in
stakeholder hearings, a summary sheet of the result may be of help. The same summary can also be provided
for specific food categories (e.g. meat, dairy, fruits, etc.) when the discussion need to be more focused on a
single food production sector.
5.7 Conclusions and outlook
The LCA-based methodology for target setting has been applied on the food sector as preliminary example.
The application of the methodology has highlighted the need of a complementary approach, in which literature
review on hotspot is coupled with LCA. In literature, the majority of study focus on energy and climate related
impacts of FSC (e.g. Garnett 2011) whereas the LCA applied to the BoP simultaneously accounting for different
impact categories support a more comprehensive hotspot analysis. Indeed, LCA may give broader and multi-
criteria assessment of FSC while missing some impact due to the variability in specific life cycle stage. For
140
example, consumer choice and behaviour may vary considerably, leading to different impacts attributable to
the use phase and the overall BoP. This should be modelled in order to identify which is the variability
associated to that phase. In general, an uncertainty analysis of the result should be conducted in order to
highlight what is the relevance of the hotspots under different assumptions.
The current selection of improvements has been based on a rather static analysis of impact as from BoP
results, including the adoption of sustainability principles. Indeed, agriculture and the FS are among the sectors
where circular economy could be better developed. This is due to the fact that they are based on biological
materials/biomass and were traditionally based on closed loop, ultimately opened due to industrialization and
globalization. However, agriculture and food are intrinsically able to close the loops. This could be seen as
economic and socially complicated in some circumstances but still is physically possible.
Any improvement and target should be anyway subject to further evaluation at system level and multi-criteria
level to ensure that a benefit in one impact category or life cycle stage is not leading to higher impacts
elsewhere.
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6 Conclusions and perspectives
6.1 Conclusions
6.1.1 Conclusions on the BoPs results
The sections 2, 3 and 4 present the results of the BoPs indicators for food, mobility and housing, expressed per
EU citizen, for 14 impact categories. The estimated potential impacts are subdivided according to the products
in the respective baskets and equally according to the life cycle stages that have been accounted for. In the
table 49 in below, a comprehensive overview reporting the role of the life cycle stages of the considered BoPs
is provided.
Interpretation of the results in the table reveals that the production and use phases dominate the impacts with
an average contribution of 51.8 and 45.6%, respectively. The End-of-Life (EoL) phase is, on the other hand, far
less contributing; for some impacts, the recovery can even result in some avoided impact – standing for
environmental benefits, explaining the numerically negative contributions. With respect to the production phase,
relative contributions to the overall life cycle impacts are the highest for human toxicity (cancer effects)
(89.2%) and terrestrial eutrophication (82.8%), moderate for impacts like climate change (31.9%) and low for
ozone depletion (15.1%). Analysis of the relative contribution of the use phase to the total life cycle impacts
shows that ozone depletion (85.7%), photochemical ozone formation (71.9%) and climate change (69.8%) are
significantly impacted; human toxicity (non-cancer effects) is instead poorly impacted (13.4%).
The role of the three BoPs can be analysed in the production phase. On average, food production contributes
54.5% to the total impact by production, mobility 34.3%, and shelter 11.2%. Food production accounts for over
90% of the contribution to acidification, terrestrial eutrophication and land use. The largest share of mobility
is in resource depletion, i.e. 80.0% of the overall impact.
Analysing the impacts of the different BoPs at the use phase, on average it turns out that it is dominated by
housing (51.8%) and mobility (45.9%), while food only accounts for 2.2%. Highest impact for the use phase
for mobility is in land use (70.4%) and for housing in ionizing radiation Ecosystem (73.8%).
With respect to EoL, impacts are dominated by mobility: 90.6% on average. Contributions of food is 9.5%,
whereas housing is negligible with -0.1% on average.
6.1.2 Interpretation by comparison with other studies
The robustness of the current report results can come from a cross check with other reports. E.g. the ETC SCP
reports about 9 tonnes CO2 eq. per capita for the EEA-32, which is quite well matching with the current study
showing that about 7 tonnes result from food, mobility and shelter. In the recent review by Heller et al. (2013),
results for impact by food consumption are summarized, including those for climate change. The impacts
reported in six European countries range from 1500 to 2700 kg CO2 eq. are summarized, quite well matching
with the 1750 kg CO2 eq. in the current study.
6.1.3 Conclusions on the application of a LCA methodology for target setting
The LCA-based methodology proposed in deliverable 4 for targets setting has been tested on BoP food (section
5). LCA results of BoP food were normalised using three different sets of NF factors, referred to status quo (NF
2010) and desirable status quo (NF 2020A and NF 2020B). Normalised results obtained with the three sets
are quite similar, with the exception of water depletion, which become highly more relevant when using NF
2020B (NF factors derived from the implementation of binding and non-binding targets for 2020).
Normalisation is used to support the identification of the hotspots for BoP food. The most relevant impact
category is by far human toxicity- non cancer effects, mainly due to the emissions from agriculture activities.
Among these, the activities related to animal husbandry and related feeding are the biggest contributors. It has
to be noted that human toxicity is dominated by zinc emissions to soil for 90%. This contribution should be
further explored with a deeper analysis of the underlying dataset used for the LCI.
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Table 49 Overview of the impacts of the different life cycle stages of the three considered BoPs with their relative contribution (%) to the overall impact
(*includes agriculture, industrial processing, logistics and packaging; **includes production and construction; *** includes energy and water use, and
maintenance)
OVERALL
Food* Mobility Shelter** TotalTotal
(%)Food Mobility Shelter*** Total
Total
(%)Food Mobility Shelter Total
Total
(%)Total
Climate change kg CO2 eq. 1.59E+03 4.01E+02 2.33E+02 2.23E+03 31.9 9.15E+01 2.71E+03 2.07E+03 4.87E+03 69.8 7.07E+01 -2.01E+02 1.43E+01 -1.16E+02 -1.66 6.98E+03
Ozone depletion kg CFC-11 eq. 3.86E-05 4.21E-05 1.15E-05 9.23E-05 15.1 8.92E-06 1.74E-04 3.42E-04 5.25E-04 85.7 3.56E-06 -9.19E-06 1.20E-06 -4.43E-06 -0.72 6.13E-04
Human toxicity, cancer effects CTUh 2.89E-05 9.81E-05 6.67E-05 1.94E-04 89.2 1.44E-06 1.49E-05 4.33E-05 5.96E-05 27.4 3.40E-06 -4.11E-05 1.58E-06 -3.62E-05 -16.65 2.17E-04
Human toxicity, non-cancer effects CTUh 2.50E-03 3.33E-04 8.46E-05 2.91E-03 84.1 7.08E-06 2.00E-04 2.56E-04 4.63E-04 13.4 1.62E-05 5.52E-06 6.64E-05 8.81E-05 2.54 3.47E-03
Particulate matter kg PM2.5 eq. 1.10E+00 3.83E-01 1.80E-01 1.67E+00 42.1 2.97E-02 1.01E+00 1.35E+00 2.39E+00 60.5 3.62E-02 -2.05E-01 6.51E-02 -1.03E-01 -2.61 3.95E+00
Ionizing radiation HH kBq U235 eq. 4.46E+01 5.94E+01 2.88E+01 1.33E+02 18.6 1.06E+01 1.77E+02 3.93E+02 5.80E+02 81.2 6.60E+00 -7.95E+00 2.86E+00 1.51E+00 0.21 7.15E+02
Ionizing radiation E (interim) CTUe 3.19E-04 1.58E-04 8.93E-05 5.66E-04 12.1 9.53E-05 9.81E-04 3.04E-03 4.11E-03 87.6 2.98E-05 -2.51E-05 9.00E-06 1.37E-05 0.29 4.69E-03
Photochemical ozone formation kg NMVOC eq. 2.76E+00 2.35E+00 7.53E-01 5.86E+00 30.4 1.50E-01 9.01E+00 4.70E+00 1.39E+01 71.9 2.30E-01 -8.17E-01 1.49E-01 -4.38E-01 -2.27 1.93E+01
Acidif ication molc H+ eq. 4.12E+01 3.27E+00 1.03E+00 4.55E+01 71.2 3.60E-01 7.35E+00 1.19E+01 1.96E+01 30.6 4.70E-01 -1.84E+00 1.86E-01 -1.18E+00 -1.85 6.39E+01
Terrestrial eutrophication molc N eq 1.79E+02 5.70E+00 2.65E+00 1.87E+02 82.8 4.30E-01 2.45E+01 1.41E+01 3.90E+01 17.3 1.56E+00 -2.31E+00 5.12E-01 -2.36E-01 -0.10 2.26E+02
Freshw ater eutrophication kg P eq. 6.08E-02 2.51E-01 6.59E-02 3.78E-01 49.7 4.06E-03 9.47E-02 1.48E-01 2.47E-01 32.6 2.48E-01 -1.15E-01 1.88E-03 1.35E-01 17.74 7.59E-01
Marine eutrophication kg N eq. 1.39E+01 5.42E-01 2.55E-01 1.47E+01 68.9 4.00E-02 2.49E+00 1.32E+00 3.85E+00 18.0 2.88E+00 -1.30E-01 4.69E-02 2.80E+00 13.11 2.13E+01
Freshw ater ecotoxicity CTUe 8.47E+03 9.87E+03 1.64E+03 2.00E+04 59.1 7.05E+02 3.55E+03 3.75E+03 8.01E+03 23.7 1.65E+03 2.73E+03 1.45E+03 5.83E+03 17.24 3.38E+04
Land use kg C deficit 1.73E+04 1.51E+03 3.22E+02 1.92E+04 62.0 2.86E+01 8.05E+03 3.36E+03 1.14E+04 37.0 4.02E+02 -1.28E+02 6.46E+01 3.38E+02 1.09 3.09E+04
Water resource depletion m3 w ater eq. 1.16E+02 5.16E+02 1.17E+02 7.49E+02 57.6 8.59E+00 3.95E+02 3.17E+02 7.21E+02 55.5 3.13E+01 -2.13E+02 1.04E+01 -1.71E+02 -13.17 1.30E+03
Mineral, fossil & ren resource depletion kg Sb eq. 1.82E-02 1.37E-01 1.61E-02 1.71E-01 54.6 3.28E-03 2.43E-02 2.79E-02 5.55E-02 17.7 2.71E-03 8.39E-02 2.14E-04 8.68E-02 27.70 3.13E-01
Impact Category Unit
Production Use EoL
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Other relevant impact categories are marine and terrestrial eutrophication, acidification, freshwater ecotoxicity
and water resource depletion.
Results of normalization for BoP food for some impact categories are higher than the total impacts attributed
to an average EU-27 citizen. This can be due to the basic difference between the results of a process-based
LCA of a set of products and the overall impact of domestic emissions and resource extraction over a year in
the EU-27.
Given the relevance of the agricultural stage for the BoP food, inherent to FSCs specific features, it is important
to distinguish LCA results among a broader range of life cycle stages than only the three used for the other
baskets.
According to the hotspots analysis, targets for improvements in FSC aimed at reducing impacts have been
defined. The main areas of improvement are: i) an environmentally sustainable increase in agricultural
productivity coupled with measures aimed at reducing emissions to air, to water and to soil, ii) dietary changes
on the consumption side (e.g. reducing the consumption of meat and dairy products), iii) higher efficiency in
reducing food losses and managing food waste (e.g. through improved rate of food waste recovery). The
analysis of documentation on possible improvements in the food sector has shown that lot of research is
available about improvements and suggested eco-innovations. Given that most of the studies are oriented to
assess the effects of single improvements rather than defining targets at sector level, our first focus has been
on documents developed in the policy support context, such as IMPRO (Tukker et al, 2009; Weidema et al, 2008)
and BAT documents on food sectors (EC, 2005; EC, 2006; EC-JRC, 2013).
6.2 Perspectives on methodological issues
The next paragraphs should be regarded as an attempt to formulate some recommendations for improvements
of robustness and usefulness of the BoP indicators, based on the learning and insights from the indicators so
far calculated. These are mainly methodological recommendations focused on a number of identified key
aspects such as the definition of representative baskets, the robustness of the environmental assessment, the
coverage/quality of the input data.
6.2.1 Definition of the current basket: consistency/overlap + bringing in a range
A crucial phase in the development of the BoP indicators was the initial definition of the three selected basket
categories (food, mobility and shelter) and the population of the three baskets, i.e. the identification of the
representative products to be included in each basket. Given the profound importance of this phase for the
subsequent quantification of the potential environmental impacts associated with each basket, a number of
considerations/recommendations can be formulated:
1. The robustness of the selection of the representative products to be included in each basket should
be more carefully checked in order to (1) identify and avoid any possible overlaps among product
groups, (2) identify and avoid any gaps, i.e. relevant groups that have not been included in the
calculation exercise presented in this report.
2. The robustness of the selection of the representative products to be included in each basket could be
also improved by projecting/including in each basket also those products that will become relevant in
the (near) future. This calls for development and consideration of scenarios for the definition of “future
baskets” that would be useful and needed for developing time series of BoP indicators.
3. In connection to the previous point, towards further development of the LC Indicators it seems very
relevant to define and consider not just one basket for each category (e.g. one basket of products for
the category food), but – ideally - a range of different baskets from the “best performing” (from an
environmental view point) one to the “worst performing” one.
4. The development of country-specific baskets should also be explored via e.g. an ad-hoc feasibility
study on the availability of the necessary country-specific data. While developing 100% country-
specific baskets may not yet be viable, it would be certainly possible to progressively adapt the baskets
including more and more country-specific datasets.
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6.2.2 Representativeness/quality (data): country specific vs. European average
An increased availability of high quality LCI-data would of course help increasing comprehensiveness and
robustness of the assessment. This being said, a number of considerations can be formulated in regards to
possible improvements of the underlying data:
1. In order to limit the data collection efforts for a future refinement of the BoP indicators, the present
calculations should be carefully checked (via e.g. sensitivity analysis) to identify some key hotspot /
product groups / part of the system that are most relevant in that they influence the most the
environmental performance. Data collection efforts could then initially be limited to these identified
components.
2. A better integration of existing data with Input/Output (IO) data seems relevant, as these data are
luckily to already include country-specific and lifecycle-stage specific information, which is seen as
important for developing further the indicators.
3. IO data could also be used to (1) cross check the results obtained so far without using I/O data, and
(2) calculate benchmarks, e.g. - in relation to point 3 under “definition of current baskets” - benchmarks
for the average performing and best/worst performing basket for each category (from an
environmental view point).
6.2.3 Impact categories: comprehensiveness/relevance of impact categories –
inserting accounting (pressure indicators) before coming to impacts
It is noted that a meaningful way to further advance the calculation of the BoP Indicators is to differentiate
the selected impact categories “per basket”. In fact, while some impact categories could be calculated as default
for all baskets, e.g. climate change, others could become basket-specific. This calls for the definition of relevant
criteria for the attribution of impact categories to the three specific baskets, which could be based on the
results (i.e. on the impact potentials) so far obtained. Beyond the ILCD-recommended impact categories,
additional relevant environmental information (as defined in the EC PEF method) could be considered for a
more comprehensive and meaningful interpretation of results (e.g. qualitative/quantitative aspects relative to
GMO use for the food basket).
6.2.4 Basket of Products extension
The current study considered three key BoPs. However, it is clear that other consumption activities contribute
to the impacts as well. To further complete the impact profile of consumption by the EU citizen, an extension
with other consumption categories can be explored. First, when it comes to the basic needs the current set of
food, housing and mobility might be expanded with health care products and services. Further on, other but
less basic needs could be considered: communication and information products and services and leisure
activities like tourism.
6.2.5 Target methodology
The application of the target methodology to BoP food helped to identify hotspots. Through normalization of
the LCA results, the hotspots proved to be in line with those spotted by the review of the existing literature,
except for the contribution of food losses, which are embedded in each phase, hence more difficult to be
identified as a hotspot. In general, the methodology can be considered useful for the identification of hotspots
of the BoPs and the contribution analysis for life cycle stages and product categories in the BoP.
There are some limitations in the use of normalization reference based on production approach (domestic
emissions and resource extraction) when consumption-based LCA is carried out.
Moreover, the use of three different sets of NFs (the one for the status quo and the two about desirable status
quo) did not show relevant differences in the identification of the most relevant impact categories.
The application of the methodology to the BoP food has highlighted the need of a complementary approach,
in which literature review on hotspot is coupled with LCA. In literature, the majority of study focus on energy
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and climate related impacts of FSC (e.g. Garnett 2011) whereas the LCA applied to the BoP simultaneously
accounting for different impact categories support a more comprehensive hotspot analysis. Indeed, LCA may
give broader and multi-criteria assessment of BoP while missing some impact due to the variability in specific
life cycle stage, e.g. consumers’ habits in the use phase. Therefore, a sensitivity analysis about the main
assumptions made in BoP LCA is needed in support to the definition of targets (e.g. to test the robustness of
hotspots results).
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