Waste Management 34 (2014) 2382–2392

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Waste Management

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A holistic life cycle analysis of waste management scenarios atincreasing source segregation intensity: The case of an Italian urban area

http://dx.doi.org/10.1016/j.wasman.2014.06.0070956-053X/� 2014 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +39 075 5853738; fax: +39 0755753736.E-mail address: francesco.dimaria@unipg.it (F. Di Maria).

Francesco Di Maria ⇑, Caterina MicaleLAR Laboratory – Dipartimento di Ingegneria, Università di Perugia, Italy

a r t i c l e i n f o

Article history:Received 26 February 2014Accepted 12 June 2014Available online 5 July 2014

Keywords:Life cycle analysisSource segregationUrban areaWaste management

a b s t r a c t

Life cycle analysis of several waste management scenarios for an Italian urban area was performed on thebasis of different source segregation collection (SS) intensities from 0% up to 52%. Source segregated wastewas recycled and or/recovered by composting. Residual waste management options were by landfilling,incineration with energy recovery or solid recovered fuel (SRF) production to substitute for coal. Theincrease in fuel and materials consumption due to increase in SS had negligible influence on the environ-mental impact of the system. Recycling operations such as incineration and SRF were always advantageousfor impact reduction. There was lower impact for an SS of 52% even though the difference with the SSintensity of 35% was quite limited, about 15%. In all the configurations analyzed, the best environmentalperformance was achieved for the management system producing SRF by the biodrying process.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Waste recycling and reuse is the main goal imposed by the lat-est EU Waste Framework Directive (2008/98/EC) in waste manage-ment. Starting in 2020 at least 50% of plastics, paper and cardboard,glass and metals must be prepared for reuse or be recycled.Furthermore, dedicated collection systems including organic wastehave to be implemented for these waste categories. The achieve-ment of these goals involves different and complex social, techni-cal, economic and environmental aspects greatly influenced bylocal factors. This has stimulated an important debate on whatthe most sustainable waste management configuration could bein order to fulfill this mandate.

Municipal solid waste (MSW) management can be separatedinto three main activities: collection, treatment and disposal.Waste management configuration means how these activities areperformed and combined for managing a single tonne of MSW.Efficient source segregation (SS) collection can contribute signifi-cantly to maximizing waste material recycling, but can representup to 70% of the entire cost of MSW management (Dogan andDuleyman, 2003; Ghose et al., 2006; Tavares et al., 2009). Differentaspects concerning SS intensity, fuel consumption, costs and envi-ronmental impact have been investigated by several researchers(de Oliveiera and Borenstein, 2007; Di Maria et al., 2013a;Everett et al., 1998a,b; Iriarte et al., 2009; Johansson, 2006). Results

show that high SS intensity, together with door-to-door collection,is expensive, and also requires the largest consumption of fuel andmaterials. Iriarte et al. (2009) analyzed three different collectionsystems and found that the multi-container one gave the lowestimpact compared to door-to-door and mobile pneumatic.

Pre-treatment of MSW before landfilling can contribute to envi-ronmental impact reduction (De Gioannis et al., 2009; Di Mariaet al., 2013b; Komilis et al., 1999; van Praagh et al., 2009) due tolower gas generation and leachate pollutant concentration.Mechanical pre-treatments are a suitable solution for extractinga fraction of recyclables from commingled or residual waste (DiMaria et al., 2013c). Similarly, organic fertilizer production fromthe organic fraction (OF) of MSW shows positive figures comparedto other management options (Blengini, 2008; Lundie and Peters,2005).

Assamoi and Lawryshyn (2012) demonstrated that incinerationis more environmentally sound than landfilling even though treat-ment costs are higher, whereas Ruth (1998) showed that fuel fromMSW can successfully substitute for coal in thermal electric powerplants. Several life cycle assessment (LCA) analyses have also beenperformed for different management options for paper, plastic andglass (Blengini et al., 2012; Moberg et al., 2005; Wang et al., 2012;Villanueva and Wenzel, 2007), showing that recycling remains themost environmentally sound method.

Zhao et al. (2009), Antonopoulos et al. (2013) proposed LCAanalysis for different waste management options at the urbanand regional scale. They compared different disposal and treat-ment alternatives along with recycling of given amounts of wastes.

Table 1MSW composition.

Component (%w/w)

Glass 7.00Textile 1.50Plastics 12.6Organic 20.3Paper and cardboard 35.5Wood 3.60Metals 6.50Other 12.7

Table 2MSW chemical characterization (mg/kg).

Parameter Value Parameter Value

Heavy hydrocarbons (C10-C40) <5 Tellurium N.D.Arsenic N.D. Nickel 5.43Mercury N.D. Zinc 56.0Chrome VI <1 Benzene <5Total copper 20.3 Toluene <5Lead 18.8 Ethylbenzene <5Cadmium 1 Xylene <5Thallium N.D. BTEX <5Beryllium N.D. Chlorinated solvents <5Antimony N.D. Other organic solvents <5Selenium N.D.

Legend: N.D.=below the limit of detection.

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The main findings of these studies confirmed the positive effect ofrecycling along with the positive role played by incineration andanaerobic digestion (AD).

All these results agree with the review of Laurent et al. (2014a).Nevertheless, some aspects concerning waste management requirefurther analysis due to the limited number of scientific papers. Inparticular, an increase in SS intensity leads to an increase in recy-cling operations, but also to possible different options to recoverand dispose of the organic fraction and residual waste. For exam-ple, there are only a few studies (Laurent et al., 2014a) that havecompared the different possible options for managing the organicfraction and paper (e.g. composting, AD, landfill, incineration).

In the present study a holistic LCA of the waste managementsystem of a given urban area (Di Maria and Micale, 2013a) locatedin central Italy was performed for different SS intensities. Startingfrom bins, liners and waste collection vehicles (WCV), differentrecycling, treatment and disposal options were analyzed. The LCAmodel was set up using specific data, when available, for some pro-cesses exploited in the different scenarios.

2. Materials and methods

The present LCA study was performed according to ISO 14040(2006) methodology also following the indications of the ILCDHandbook guidelines (EC, 2010) and the methodology specifiedby Laurent et al. (2014b).

2.1. Goal definition

The intended application of the present study is assessment ofthe impact of different waste management options in an urbanarea in central Italy. The urban area is located in a region wherethere are no incineration facilities. Mechanical biological treatment(MBT) plants are used, where recyclable material is extracted fromresidual MSW (RMSW) and its biological reactivity is reducedbefore landfilling.

For this reason the results reported are greatly dependent onthe features of the area considered, even if some extrapolationscan be made to other similar areas.

Starting from the mandatory necessity of achieving the goalsimposed by the EU Waste Framework Directive (2008/98/EC),there is a big debate on determining the most socially, economi-cally and environmentally sustainable waste management system.The last aspect is the driver of the present study. Hence the targetaudience is not only the scientific community but also all the inter-ested stakeholders and decision makers such as the public admin-istration charged with planning the waste management system inthe area considered and in other similar areas. Finally, the presentstudy is a part of the activities concerning the Life +12 ENV/IT/000411 project EMaRES financed by the European Commission.

2.1.1. Context situationsAs described in Section 2.1, the present LCA analysis can be used

for supporting decisions for the waste management system in thearea considered. The foreground system varies depending on themanagement system, whereas the background system consideredin this study is not significantly affected by that of the foreground.In agreement with the ILCD Handbook (EC, 2010), the resultingcontext corresponds to a system in expansion. In particular thebackground considered in this study are average values resultingfrom the market mix.

2.2. Definition of the scope

When applying LCA to waste management, the classicalcradle-to-grave approach has to be modified to gate-to-cradle or

gate-to-grave (Blengini et al., 2012), depending on if recycling ordisposal operations are analyzed.

As far as waste management is concerned, the input material iswaste, which can either be disposed of or re-enter further lifecycles in substitution of virgin material. Substitution mean avoid-ing the manufacturing of products from primary sources by usingsecondary material gathered from recovery and recycling. The sys-tem that recycles waste into a valuable product is credited with theenvironmental burdens of the corresponding primary production,but is charged with energy and ancillary materials used for therecycling process. In particular in the present work, the wastemanagement options, including recycling, recovery and disposalafter collection are influenced by SS intensity.

2.2.1. Functional unitThe functional unit (FU) is a quantified description of the prod-

uct systems’ performances (ISO, 2006). In this case the environ-mental performances of different waste management schemesrelated to the management of the MSW generated in the area con-sidered are compared.

For this reason the FU chosen was 1 tonne of MSW with thecomposition and the chemical characterization reported, respec-tively, in Tables 1 and 2. These data represent the average valueswith respect to waste samples in different periods of the year. Inthis study the FU is also the reference flow on which the analysiswas performed.

2.2.2. Life Cycle Inventory modelling framework and systemboundaries

Several components and processes of the system analyzed,composting, AD, incineration, MBT, are characterized by a moreor less relevant multi-functionality. Nevertheless these processesoccur on the different waste streams as they are delivered aftercollection. Considering the FU chosen and that the amount ofwaste entering the system was assumed to be constant, the LifeCycle Inventory (LCI) modelling framework chosen was thereforethe attributional one. On the basis of the SS intensity, the single

Fig. 1. System boundary.

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tonne of MSW was split into different streams (e.g. glass, organic,residual . . .) and consequently both the waste mass rate as thebackground related to the single processes exploited in the sys-tem varies.

Fig. 1 reports the system boundary. The background is repre-sented by energy, fuel and the materials necessary for differentprocesses. The Italian energetic mix was considered in the analysis.The Italian electricity grids are connected to surrounding countriesand the fraction of imported energy is about 2% of the total con-sumption. The remaining amount is mainly produced by fossilfuels such as coke, about 19%, and natural gas, about 43%(Ministero dello Sviluppo Economico, 2011). Hydro contributesabout 19%, whereas renewable contributes about 8.5% from windand photovoltaic, about 2.5% comes from geothermal and wasteeach and about 4.4% is from biomass.

Notwithstanding the SS intensity, the different waste streamsfollow two main different patterns (Fig. 1):

(1) Mandatory patterns, represented by the continuous line.(2) Alternative patterns, represented by the dashed line.

The mandatory fate of recyclables is recycling, whereas for theSSOF it is material recovery for fertilizer production. Instead RMSWand other non-recyclables can undergo different treatment anddisposal processes (i.e. alternative patterns). The foreground ofthe system is represented by energy generated by incineration,AD and landfill gas, emissions arising from energy consumption,processes and treatments, and materials delivered for recycling.In particular recycling processes are limited to the preparation ofmaterials for their reintroduction into production cycles. No inves-tigation was performed on the efficiency of production cyclesexploiting the recycled materials. SS intensity was varied from0% to 52% (Table 3). Different waste management options wereinvestigated for each SS intensity, as reported in Table 3 (Fig. 1).In all the scenarios marked with 0.1, RMSW was directly landfilled,

whereas those marked with 0.2 were incineration with slag beingsuccessively landfilled. In the scenarios marked with 0.3–0.5,mechanical pre-treatments were conducted. In 0.3 MBT, recycla-bles were extracted and RMSW mass and reactivity were reducedbefore landfilling. In 0.4, MBT was also aimed at producing SRFfor coal substitution, and in 0.5, the aim of MBS was the same goal.In both cases residuals from pre-treatments were disposed of bylandfilling. When SS was P30% in the scenarios marked from 0.1to 0.5 the composting process was also introduced for the SSOF.Scenarios from 0.6 to 0.10 report the same RMSW treatmentoptions as for 0.1–0.5 but AD was also conducted for processingthe SSOF.

In the scenario with SS = 0% the recycling operation refers onlyto metals extracted from MBT. Mechanical and physical separation(MPS), aimed at extracting recyclables from commingled waste,such as light packaging, was introduced starting from SS P 25%.

2.2.3. Waste collectionThe first component of the waste management system was the

collection activity (Fig. 1) involving bins, liners and waste collec-tion vehicles (WCV). The scenario considered was an existing res-idential urban area consisting of seven different collection routes(Di Maria et al., 2013a). In the reference configuration (i.e.SS = 0%), total driving distance was about 190 km/day and theaverage daily MSW production was about 35.8 tonnes with 342collection points (CP) (Table 4). The resident population was about24,000 inhabitants. Starting from the existing collection configura-tion, Di Maria et al. (2013a) performed different analyses by vary-ing the SS intensity hence passing from road to door-to-doorcollection. Number, volume and positions of bins and liners wereevaluated for each SS value together with number, size and fuelconsumption of WCV (Table 4). CP corresponds to number of binsand number of liners. There was a significant increase in these col-lection system components going from a SS of 35% to 52% alongwith a relevant increase in the distances driven daily. LCI of bin

Table 3Waste management combinations after collection for the different scenarios analyzed.

SS (%) Scenario N� Recycling MBT MBS MPS Incineration Landfill SRF Compost AD

0 0.1 X0 0.2 X X0 0.3 Xa X X0 0.4 Xa X X X0 0.5 Xa X X X25 25.1 Xa,b X X25 25.2 Xa,b X X X25 25.3 Xa,b X X X25 25.4 Xa,b X X X X25 25.5 Xa,b X X X X30/35/52 30/35/52.1 Xa,b X X X30/35/52 30/35/52.2 Xa,b X X X X30/35/52 30/35/52.3 Xa,b X X X X30/35/52 30/35/52.4 Xa,b X X X X X30/35/52 30/35/52.5 Xa,b X X X X X30/35/52 30/35/52.6 Xa,b X X X X30/35/52 30/35/52.7 Xa,b X X X X X30/35/52 30/35/52.8 Xa,b X X X X X30/35/52 30/35/52.9 Xa,b X X X X X X30/35/52 30/35/52.10 Xa,b X X X X X X

a Metals from MBT/MBS.b Materials from SS collection and MPS.

Table 4Fractions of source segregated waste material, bin volume, collection points, daily distances and WCV fuel consumption for different SS intensities (Di Maria and Micale, 2013a).

SS (%) Material (%w/w) Bin (L) CP N� bins Distance (km/day) Fuel consumption (L/tonne)c

0 MSW (100) 2400–1000 342 193 2.98

25 RMSW (74.6) 2400–1000 342 193 3.33Paper (19.0) 770–1000–2400 342 193Packaginga (6.40) 770–1000–2400 342 193

30 RMSW (69.6) 2400–1000 342 193 3.57Paper (19.0) 770–1000–1,200 342 193Packaginga (6.40) 770–1000–1200 342 193Organic (5.00) 120 342 193

35 RMSW (64.9) 2400–1000–1200 342 193 3.79Paper (19.0) 770–1000 342 193Light Packaginga (6.40) 770–1000 342 193Organic (5.00) 120 342 193Glass (4.70) 3200 98 193

52 RMSW (51.9) 2400–1000–770 342 193 3.80Paper (11.6) Liner 1066 403Light packaginga (12.1) Liner 1066 445Organic (17.9) Liner 1066 208Glass (3.30) Liner 1066 184Metalsb (3.20) Liner 1066 268

a Commingled plastics light packaging.b 50:50 Aluminum and steel.c Mean weighted values.

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production, maintenance and substitution every 5 years weretaken into consideration according to Roves et al. (2010), whereasliners were considered biodegradable only for the SSOF and singleuse. Similarly, on the basis of the respective size, WCV constructionand maintenance was included assuming an average life of10 years.

LCI for WCV was retrieved from the Ecoinvent v2.2 database(Hischier et al., 2010), reporting data related to a Germanmanufacturer.

2.2.4. Light packaging processingLight packaging includes the packaging usually used for food

and beverages. It is mainly plastics, aluminum, tins and cans thatare collected in a commingled way (Table 4).

Based on Rigamonti and Grosso (2009) composition by weightof light packaging was assumed to be 15.2% metals, 5.5% alumi-num, 15.9% high density polyethylene (HDPE), 43.6% polyethyleneterephthalate (PET) and 19.8% plastic mix in which other impuri-

ties are also included. The screening of these materials after SS col-lection was performed in MPS facilities (Table 5) consisting of acombination of mechanical (i.e. sieving, ballistic, aeraulic) separa-tors, magnets and eddy currents extractors and near infra-redselectors (Di Maria et al., 2013c). The screening efficiency wasassumed to be 100% and relative mass balances are reported inTable 6. HDPE, PET and metals were recycled whereas plastic mixwas recovered by SRF production or alternatively disposed of bylandfilling or incineration (Table 3) (Fig. 1). The substitution frac-tion for recycled plastics was assumed to be 81%. Energy for recy-cling 1 tonne of HDPE and PET was split into electricity and fossilfuel mix (Table 5). Other data for the LCI of plastic recycling wereobtained from the USLCI database (2012), reporting average datafor North America.

The LCI for the production of HDPE and PET from virgin materi-als was obtained from Ecoinvent v2.2 (Hischier et al., 2010), report-ing average data related to a European manufacturer. Even thoughthe two databases are related to different geographical areas, the

Table 5Energy consumption for treatment and recycling operations per tonne of waste material.

Operation Energy References

Steel recycling Hischier et al., 2010Fossil fuel (diesel) (Pre-treatment) 100 MJElectricity (Pre-treatment) 10 kW hElectricity 423.61 kW hHard coal 404.62 MJNatural gas 975 MJAluminum recycling Hischier et al., 2010Electricity (Pre-treatment) 64 kW hHeavy and light fuel oil (Pre-treatment) 201.4 MJNatural gas (Pre-treatment) 1020 MJElectricity 288 kW hHeavy and light fuels 513.1 MJNatural gas 8270 MJHDPE recycling Hischier et al., 2010Electricity 490 kW hFossil fuel (diesel, natural gas, liq. petr. gas) 318.2 MJPET recycling Hischier et al., 2010Electricity 940.6 kW hFossil fuel (Natural gas, liq. petr. gas) 2765.2 MJGlass recycling Hischier et al., 2010Electricity (Pre-treatment) 22 kW hElectricity 244 kW hHeavy and light fuel oil 3521.1 MJNatural gas 3570 MJPaper and cardboard recycling Rigamonti and Grosso, 2009; Hischier et al., 2010Electricity 42 kW hNatural gas 8710 MJMBT Di Maria, 2012Electricity 33 kW hMBT with SRF Di Maria, 2012Electricity 45 kW hMBS Di Maria, 2012Electricity 45 kW hMPS Di Maria et al., 2013cElectricity 30 kW hComposting Hischier et al., 2010Electricitya 11.8 kW h

Legend: ‘‘Plant’’ = data measured on full-scale facilities.a Per tonne of compost.

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technological and environmental protection levels are comparable.For these reasons the choice was considered consistent with thestudy.

2.2.5. Source segregated organic fraction treatmentThe SS OF is processed with the aim of recovering material for

the production of an organic fertilizer for agricultural use.This aim can be achieved by aerobic treatment (i.e. composting)

alone or by the combination of AD followed by a successive aerobictreatment of the digestate.

Composting is a complex biological process leading to signifi-cant bio-chemical and physical transformations of the OF. Further-more, the production of a high quality organic fertilizer alsorequires physical and mechanical treatments for refining thismaterial in order to comply with the required legal and commer-cial standards. The concentration of impurities such as plastics,metals and other bulky components must be lower than the estab-lished limits imposed by the single EU states. This means that evenif SS is conducted with a high efficiency, the mass of compost pro-duced is usually significantly lower than the treated mass of OF.This difference can be greatly influenced by local situations, collec-tion methods and also by the technology used. For this reason amass balance was performed on the composting facility operatingin the collection area, which processes about 4500 tonnes/year ofSS OF. Considering 1 tonne of OF at the plant inlet, for the periodranging from 2006 to 2010, results show that 600 kg were processlosses, 270 kg were process waste and 130 kg were high quality

compost (Table 6). Each tonne of high quality compost corre-sponded to 23 kg N, 9 kg K2O and 9.5 kg P2O5, hence eliminatingthe need for artificial production of these nutrients. Table 5 reportsthe amount of energy required to produce 1 tonne of final compost.The LCI for this process was retrieved from Ecoinvent v2.2(Hischier et al., 2010), using average data for composting facilitiesoperating in Switzerland. Considering the technological level ofthese facilities the assumptions are consistent with the presentstudy.

The same amount of compost produced per tonne of OF wasassumed in the scenario with AD (Table 6).

The technology adopted for this study is based on the dry pro-cess (Bolzonella et al., 2006), which is the currently most diffusedtechnological solution for organic waste management. Based on aprevious study on the dry AD of the OF arising from the same col-lection area there was an energy potential of about 220 kW h/OFtonne (Di Maria, 2012). Due to the impossibility of using the liquidfraction of the digestate on agricultural fields in the area consid-ered, purification in a waste water treatment plant (WWTP) wasincluded. In accordance with Bolzonella et al. (2006) the amountof liquid to be processed in a WWTP was assumed to be 0.45 m3/OF tonne. Construction and commissioning of these facilities wasincluded in the analysis. Ecoinvent v2.2 (Hischier et al., 2010) data-base data, reporting average values for dry AD operating in Swit-zerland, were used for the LCI of this process. For the samereasons concerning the composting process, this assumption wastechnologically consistent with the present study.

Table 6Mass balance (%w/w) and main output product features with respect to 1 tonne of waste processed in the facilities of the different systems.

Treatment Losses Metals Output SRF Renew. Disposal LHV (kJ/kg) LFG (NL/kg)

MBT 25.0 3a–0.3b 40.7c 60 31.0 13.800c 54d

MBS 30.3 3a–0.3b 57.0c 60 9.40 13.800c 54d

Composting 60.0 – 13.0e – 27.0 – 54d

Incineration 80.0 – 500f 51g 20.0 – 0MPS 0 15.2h–5.5b 15.9i–43.6l 0 19.5m 13.800m 0AD – – 13.0e/220f – 27.0–0.45n – 54d

a Steel.b Aluminum.c SRF.d Disposal in landfill.e Organic fertilizer.f kW h/tonne.g RMSW.h Metals.i HDPE.l PET.

m Plastic mix.n m3 Of liquid to WWTP.

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2.2.6. Residual MSW processingRMSW is the waste fraction that can undergo the most varied

treatment and disposal operations. It can be incinerated, processedin MBT or in MBS for maximizing SRF production and it can be dis-posed of directly by landfilling, even if this option is in contrastwith the waste management hierarchy (WFD 2008/98/EC) (Fig. 1).

All these alternatives have multi-functionality and were consid-ered in the study. LCI of these processes were realized adoptingavailable databases eventually adjusted with specific data. Themodel was chosen by verifying the consistency with the technolog-ical and environmental legislation level of the area considered.

2.2.6.1. Landfill. With the exception of the scenarios in which anincinerator was used, the landfill was assumed to be equipped withan energy recovery system as in the reference scenario. Theamount of energy recoverable was based on a previous study con-cerning the landfilling of the RMSW arising from the same man-agement area (Di Maria et al., 2013b). The study reports that theamount of electrical energy recoverable from the landfill gas(LFG) was 62 kW h/tonne for untreated RMSW, whereas it was of33.5 kW h/tonnes for RMSW pre-treated in an MBT facility. The lastvalue was also assumed for the landfilled residuals from MBS. LFGcollected but not exploitable for energy production was assumedto be flared, whereas the uncollected LFG was assumed to be par-tially oxidized by the top layer of the landfill (Di Maria et al.,2013b; De Gioannis et al., 2009).

Both flare and internal combustion engine emissions arereported in Table 7 considering that the CH4 concentration inLFG ranges from about 50% to 55% (Beylot et al., 2013; Di Mariaet al., 2013b). Other data used for landfill LCI refer to EU-27 asreported in the ELCD 2.0 database (EC, 2008).

Table 7Default inventory data for the emissions for the flare and internal combustion engine.

Emission Value

Flare Internal combus.

NOx 0.631 11.60CO 0.737 8.460PM 0.238 0.232Dioxins/furans 6.7E�9 –SOx (as SO2) 80 100HCl 40 9HF 8 10Gas NMVOCs 99.23 97.15

2.2.6.2. Incineration. As quite diffused in Italy, the RSMW incinera-tor was assumed to be equipped for recovering only electricalenergy, about 500 kW h/tonne (ISPRA, 2013), which is the averagevalue for facilities in northern Italy. The slag arising from the com-bustion process was assumed to be 20% by weight of the treatedmass of RMSW and was disposed of in landfill. Main mass balancesand output streams are reported in Table 6. The 51% w/w of RMSWburned in incinerators was assumed to be renewable (Table 1).

Construction and decommissioning after 40 years of the incin-eration facility was also included in the study. The data for theLCI were related to average values for incineration facilities cur-rently operating in Switzerland, as reported in the Ecoinvent v2.2database (Hischier et al., 2010).

2.2.6.3. Mechanical and biological treatments. In various EU areasMBT plays an important role as an alternative to incineration. Evenwith lower effectiveness, MBT can reduce RMSW reactivity andmass before disposal. Recyclable materials can also be extractedby MBT and lead to SRF production.

Depending on the main aim, MBT can be divided into the fol-lowing two main groups:

(1) Facilities aimed at increasing the amount of SRF producible.(2) Facilities aimed at increasing the amount of material recov-

ered together with mass reduction and stabilization, as inthe reference scenario.

In the first case the MBT operates according to the MBS process(Wiemer and Kern, 1995). In this method the RMSW is first biolog-ically dried and then mechanically refined. In the second caseRMSW undergoes mechanical processing such as shredding,

Unit References

eng.

g/N m3 CH4 USEPA (2008)g/N m3 CH4

g/N m3 CH4

g/N m3 CH4

g/tonne of waste NSCA (2002)g/tonne of wasteg/tonne of waste% Removal USEPA (2008)

Table 8Environmental impact category, weight and normalization factors (CML, 2001; Stranddorf et al., 2005).

Impact category Unit Normalization factor Unit Weight

Antonopoulos et al. (2013) EDIP97 EU-15

GWP100 kg CO2 eq. 4.15E+13 kg CO2 eq./a 3 1.3 1.05AP kg SO2 eq. 3.22E+11 kg SO2 eq./a 2 1.3 1.27EP kg PO4 eq. 1.32E+11 kg PO4 eq. 2 1.2 1.22POCP kg C2H2 eq. 9.69E+10 kg C2H2 eq./a 1 1.2 1.33HTP kg 1,4-DB eq. 5.71E+13 kg 1,4-DB eq./a 2 2.23a 1.31a

TEP kg 1,4-DB eq. 2.69E+11 kg 1,4-DB eq./a 1 2.36a 1.10a

ADP kg Sb eq. 1.56E+11 kg Sb eq./a 1 1b 1b

OLDP kg CFC-11 eq. 5.15E+8 kg CFC-11 eq./a 1 23 2.46

a Average among Human Toxicity via air, via water and via soil.b Not considered in EDIP97 and EU-15 but assumed in this study.

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screening and metal sorting, aimed at separating the organic frac-tion from the other recyclable material and components withhigher calorific value. The mechanically sorted organic fraction isthen biologically pretreated to reduce its reactivity and massbefore being disposed of. Reduction in the biological reactivity ofthe waste also reduces LFG generation (Di Maria et al., 2013b).The other sorted fractions can be exploited for SRF productionand/or for other recovery aims or at least landfilled.

On the basis of previous experimental and full-scale analyses(Di Maria, 2012; Di Maria et al., 2013b), MBT and MBS energy con-sumption (Table 5), mass balances and residual fractions and LFGgeneration potential were assumed (Table 6). The concentrationof renewable materials in the SRF, about 60% w/w, was assumedon the basis of the MSW composition (Table 1) and on the basisof direct observations for full-scale MBT. Due to the lack of specificinformation, construction and decommissioning of MBT and MBSfacilities was considered equivalent to that of the composting facil-ity (see Section 2.2.5).

If produced, SRF was assumed to be mandatorily exploited forcoal substitution in cement kilns at a ratio of 2:1. The LCI for SRFcombustion was appropriately realized by adopting the datarelated to combustion of the single waste materials present in itscomposition. The LCI for coke substitution was obtained by consid-ering the emissions from hard coal burned in an industrial furnaceincluding waste disposal with the exclusion of the infrastructure.Both models were realized adjusting data reported in the Ecoin-vent v2.2 database (Hischier et al., 2010).

2.2.6.4. Other recyclables. Other recyclable waste streams are frompaper and cardboard, metals (i.e. steel and aluminum) and glass.Generally paper and cardboard and glass arise from SS collection,whereas metals also come from MBT, MBS or MPS treatments.The energy consumption required for recycling operations of met-als and glass were derived from the Ecoinvent v2.2 database(Hischier et al., 2010) (Table 5), whereas that for paper and card-board came from Rigamonti and Grosso (2009) related to averageEuropean data. These energetic consumptions were divided byenergy sources (e.g. electricity and different fossil fuels). The sub-stitution ratio for recycled metals and glass was assumed to be1:1 whereas for paper and cardboard it was assumed to be 83%(Rigamonti and Grosso, 2009). The LCI for production from virginmaterials was obtained from average European manufacturer dataas reported in the Ecoinvent v2.2 database (Hischier et al., 2010).

2.3. Selection of environmental indicators, normalization andweighting

Environmental indicators were chosen using a top–downapproach (Blengini et al., 2012) according to ISO (2006)recommendations (Table 8). These indicators are internationallyrecognized and widely exploited in LCA analysis (Blengini et al.,2012; Iriarte et al., 2009; Wang et al., 2012). In particular they

are: Global Warming Potential at 100 years (GWP100), Acidificat-ion Potential (AP), Eutrophication Potential (EP); PhotochemicalOzone Creation Potential (POCP); Ozone Layer Depletion Potential(OLDP), Abiotic Depletion Potential (ADP), Human Toxicity Poten-tial (HTP) and Terrestrial Ecotoxicity Potential (TEP) (Table 4).The impact associated with each scenario can be evaluated by add-ing the respective impact category after the normalization andweighting procedure.

To provide an impression of the relative magnitude of thepotential impacts and resource consumptions, the impact catego-ries can be related to reference information. In CML (2001) normal-ization factors (Table 8) are taken from the world emissions relatedto the year 1995.

To evaluate the impact of a give scenario, the different normal-ized impact categories can be aggregated after a specific weightingprocedure. As also reported in the ILDC Handbook (EC, 2010), theweighting procedure is an optional step and many authors suggeststopping the LCA analysis at the impact category assessment. Infact this aspect is very controversial due to the difficulty of estab-lishing a universally shared procedure for determining weightingfactors. A possible approach in evaluating these parameters couldbe by the distance-to-target method (Seppala and Hamalainen,2001). By this method the weighting factors can be determinedfrom the distance existing between a political, environmental, eco-nomical, or other relevant stakeholder targets and the actual val-ues. Usually a reference year is defined, to which the targets arerelated and a target year, to which the targets have to be achieved.

Due to the interest of obtaining an impact assessment for eachscenario examined, to compare the environmental burden of thedifferent combinations of waste management options, a sensitivityanalysis was introduced based on the weighting factors.

Three different weighting factors were adopted (Table 8), assuggested by Antonopoulos et al. (2013), by the EDIP97 and bythe EU-15 (Stranddorf et al., 2005). Antonopoulos et al. (2013)adopted the weight reported in Table 8 for assessing the impactof different waste management options in a given Greek area. Itis worth noting the importance given to GWP100 by a weight fac-tor of 3. The EDIP97 and EU-15 weights were determined on thebasis of the distance to target and in some cases they differed sig-nificantly, also from those of Antonopoulos et al. (2013). Amongthe impact categories considered in the present study, neitherthe EDIP97 nor the EU-15 includes the ADP. For this reason thisimpact category was not used for the sensitivity analysis by main-taining the related weight constant to 1.

2.4. Software used for modelling

The LCA model was implemented using the SimaPro8 software(Prè Consultants, 2013). In agreement with Rigamonti et al. (2009),who analyzed a similar aspect for a northern Italian area, theimpact assessment method chosen was the CML2 (CML, 2001).

353025SS (%)

GWP

0/25.1 0/25.2 0/25.3 0/25.4 0/25.5

30/35/52.1 30/35/52.2 30/35/52.3 30/35/52.4 30/35/52.5

30/35/52.6 30/35/52.7 30/35/52.8 30/35/52.9 30/35/52.10

0 52SS (%)

AP 0/25.1 0/25.2 0/25.3 0/25.4 0/25.5

30/35/52.1 30/35/52.2 30/35/52.3 30/35/52.4 30/35/52.5

30/35/52.6 30/35/52.7 30/35/52.8 30/35/52.9 30/35/52.10

35 5230250

30/35/52.1 30/35/52.2 30/35/52.3 30/35/52.4 30/35/52.5

30/35/52.6 30/35/52.7 30/35/52.8 30/35/52.9 30/35/52.10

0/25.1 0/25.2 0/25.3 0/25.4 0/25.5

SS (%)

ADP

35 5230250

SS (%)

EP

0/25.1 0/25.2 0/25.3 0/25.4 0/25.5

30/35/52.1 30/35/52.2 30/35/52.3 30/35/52.4 30/35/52.5

30/35/52.6 30/35/52.7 30/35/52.8 30/35/52.9 30/35/52.10

35 5230250

SS (%)

HTP

0/25.1 0/25.2 0/25.3 0/25.4 0/25.5

30/35/52.1 30/35/52.2 30/35/52.3 30/35/52.4 30/35/52.5

30/35/52.6 30/35/52.7 30/35/52.8 30/35/52.9 30/35/52.10

35 5230250SS (%)

OLDP

0/25.1 0/25.2 0/25.3 0/25.4 0/25.5

30/35/52.1 30/35/52.2 30/35/52.3 30/35/52.4 30/35/52.5

30/35/52.6 30/35/52.7 30/35/52.8 30/35/52.9 30/35/52.10

35 5230250

SS (%)

POCP

0/25.1 0/25.2 0/25.3 0/25.4 0/25.5

30/35/52.1 30/35/52.2 30/35/52.3 30/35/52.4 30/35/52.5

30/35/52.6 30/35/52.7 30/35/52.8 30/35/52.9 30/35/52.10

35 5230250

SS (%)

TEP

0/25.1 0/25.2 0/25.3 0/25.4 0/25.5

30/35/52.1 30/35/52.2 30/35/52.3 30/35/52.4 30/35/52.5

30/35/52.6 30/35/52.7 30/35/52.8 30/35/52.9 30/35/52.10

523530250

-500-400-300-200-100

0100200300400500600700

kg C

O2e

q/t M

SW

-7,5-7,0-6,5-6,0-5,5-5,0-4,5-4,0-3,5-3,0-2,5-2,0-1,5-1,0-0,50,00,5

kg S

b eq/t M

SW

-1050

-900

-750

-600

-450

-300

-150

0

150

300

kg 1

,4-D

B eq/t M

SW

-0,35

-0,30

-0,25-0,20

-0,15

-0,10

-0,05

0,00

0,05

0,10

0,15

kg C

2H

4/t M

SW

-8,0-7,5-7,0-6,5-6,0-5,5-5,0-4,5-4,0-3,5-3,0-2,5-2,0-1,5-1,0-0,50,00,5

kg S

O2e

q/t M

SW

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

2,5

3,0

kg P

O= 4/t M

SW

-3,25x10-5-3,00x10-5-2,75x10-5-2,50x10-5-2,25x10-5-2,00x10-5-1,75x10-5-1,50x10-5-1,25x10-5-1,00x10-5-7,50x10-6-5,00x10-6-2,50x10-6

0,002,50x10-6

kg C

FC-1

1 eq/t M

SW

-2,5

-2,0

-1,5

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

kg 1

,4-D

B eq/t M

SW

Fig. 2. Comparison of the impact categories for the different scenarios evaluated.

F. Di Maria, C. Micale / Waste Management 34 (2014) 2382–2392 2389

2390 F. Di Maria, C. Micale / Waste Management 34 (2014) 2382–2392

3. Results

LCA shows that the higher is the SS intensity, the lower are thevalues of the impact categories (Fig. 2). Higher impact is generallyachieved for the scenario with SS = 0%, exploiting only landfilling(i.e. 0.1). For the same SS intensity of 0%, the adoption of incinera-tion, scenario 0.2, leads to an overall reduction of the impact cate-gories except for HTP. As expected GWP and EP were significantlylower than the values of scenario 0.1, mainly due to lower green-house gas emission (GHG) (e.g. CO2, CH4 and N2O) and leachategeneration. Similarly POCP and OLDP show environmental gaindue to incineration, whereas there was a positive impact for land-filling. Even if the amount of renewable energy generated by incin-eration was higher than that recoverable from landfilling per 1tonne of MSW, the higher di-chlorine-benzene equivalent com-pounds produced during waste incineration caused higher valuesof HTP. The adoption of MBT in scenario 0.3 improved the environ-mental performances compared to scenario 0.1, but in general gavehigher impact values compared to scenario 0.2. Also in this caseHTP was an exception. In general with MBT, metals are recoveredbut require energy for mechanical screening and biological stabil-ization of the waste. Furthermore, the positive effect of renewableenergy production from LFG was reduced with respect to scenario0.1 due to the bio-stabilization process. The combination of lowerrenewable energy recovery along with the increase of energyneeded for the reintroduction of iron into the industrial processcaused higher values for OLDP and TEP.

Coal substitution by SRF gave important environmental benefitscompared to scenarios 0.1, 0.2 and 0.3. The MBS (0.5) method gavegreater benefits compared to MBT (0.4) mainly due to the largeamount of SRF generated and lesser amount of landfill needed(Table 6). In particular the greater need for landfill is the main rea-son for the slightly positive values assumed by the EP for the 0.4scenario. Other impact categories were largely negative exceptfor TEP and OLDP. This is a consequence of the electrical energyconsumption necessary for MBS and MBT treatment, not com-pletely compensated for by the benefits due to coal substitution.

The impact of collection activity, obtained by the aggregationprocedure (Table 8), related to SS intensity is shown in Fig. 3.The impact of this activity per tonne of MSW increased by about50% when SS went from 0% to 52%. Different trends are shownfor each collected waste. The RMSW impact decreased as SSincreased due to reduction in the amount of RMSW collected. ForSS ranging from 25% to 35%, the impact of paper and cardboard,light packaging and OF collection remained quite constant. Onthe contrary when SS reached 52%, the increase in the number of

0,00E+0002,50E-0135,00E-0137,50E-0131,00E-0121,25E-0121,50E-0121,75E-0122,00E-0122,25E-0122,50E-0122,75E-0123,00E-0123,25E-012

Antonopoulos et al.(2013) EDIP97 EU-15

Residual Paper Light packaging/plastics OF Glass Metals Collection

52353025

Impa

ct

% SS0

Fig. 3. Impact of collection activity for each type of collected waste with respect toSS intensity for different weighting procedures.

smaller size WCV along with the increase in the distance drivencaused an increase in the impact, in particular for OF and lightpackaging (Di Maria and Micale, 2013c). In general the weightexploited for the analysis of the collection shows that the ones pro-posed by Antonopoulos et al. (2013) led to the higher values. This isa consequence of the value assigned to the weight of GWP. In fact,due to the inevitable increase in fuel and materials consumption byincreasing SS, the emission of equivalent CO2 per tonne of MSWwas consequently increased. For the same reason the collectionimpact evaluated by EDIP97 weight shows higher values than thatevaluated by the EU-15, but lower values than that evaluated usingthe weight of Antonopoulos et al. (2013).

Even with these aspects, collection activity played a negligiblerole both for the impact categories and for the impact determina-tion of the different scenarios.

HTP, OLDP and TEP were significantly reduced when SS wentfrom 35% to 52%. The benefits due to the increase in the amountof materials recycled prevails over all the other potentially nega-tive effects. There was an opposite trend for AP, which expressesthe amount of equivalent kg of SO2 generated per tonne of MSWmanaged, in particular, for the scenario with SRF production. Infact, the higher is the SS intensity, the lower is the amount ofSFR produced per tonne of MSW. This reduces the benefit due tocoal substitution, whereas the larger amount of SSOF requiresmore energy for processing it. Benefits due to the adoption of ADand composting instead of composting alone were reduced bythe greater incidence of materials and energy requirements forthe construction and maintenance of the AD facility. Finally themaximum benefits related to GWP, ADP and POCP impact catego-ries were achieved for the scenario with SRF and are quite similarfor the different SS intensities.

The impact values reported in Fig. 4 confirm that scenarios withlandfilling were the worst, followed in order by MBT and incinera-tion (i.e. 0.1, 0.3, 0.2 and 0.6, 0.8, 0.7). This result was confirmed forall the weighting procedures (Table 8). The best environmentalresults were obtained from SRF production preferably adoptingthe MBS method. Increase in SS intensity from 25% up to 35%had negligible effects on the improvement of the environmentalimpact of the management systems. Further efforts to increase SSintensity up to 52% produced relevant benefits for the scenarioswithout SRF, whereas for the scenario with SRF, a further reductionof the impact was about 17%.

The sensitivity analysis related to the adoption of differentweighting procedures confirms the general relevance of the weightassigned to the GWP. In the aggregation procedure the environ-mental gain or burden associated with the normalized impact

0 25 30 35 52-1,75x10-10

-1,50x10-10

-1,25x10-10

-1,00x10-10

-7,50x10-11

-5,00x10-11

-2,50x10-11

0,002,50x10-11

5,00x10-11

7,50x10-11

1,00x10-10 0/25.1 0/25.2 0/25.3 0/25.4 0/25.5

Impa

ct

% SS

Antonoupolos et al. EDIP97 EU-15

30/35/52.1 30/35/52.2 30/35/52.3 30/35/52.4 30/35/52.5

30/35/52.6 30/35/52.7 30/35/52.8 30/35/52.9 30/35/52.10

Fig. 4. Impact for the different scenarios evaluated by different weightingprocedures.

F. Di Maria, C. Micale / Waste Management 34 (2014) 2382–2392 2391

category (Table 8) was emphasized by the values assigned to therelative weight. In general the GWP plays a prominent role in thedetermination of the impact of the different scenarios leading tothe maximum gain or burden for the weighting procedure pro-posed by Antonopoulos et al. (2013) (Fig. 4).

4. Discussion

The positive effect of recycling has been assessed by severalresearchers (Moberg et al., 2005; Wang et al., 2012) concerningpaper, cardboard and plastics. Substitution of raw materials isenvironmentally more advantageous than other managementoptions such as incineration and landfilling with energy recovery.

The positive effect of recycling on the environmental perfor-mance in the waste management system was also demonstratedby Rigamonti et al. (2009). With respect to a northern Italian area,if SS was performed with high efficiency, maximizing the amountof recyclable materials from waste, the optimum intensity was60%. If the concentration of non-compatible components in theSS waste increased, the optimum SS intensity was 50%. In any casegoing from an SS intensity of 35% to 50%, the environmental impactcategories were reduced by about 1–12%.

Among the possible treatments for RMSW, the positive effectthat incineration can play in waste management has been dis-cussed by several authors. Assamoi and Lawryshyn (2012) showedhigh potential benefits from incineration compared to landfillingwith respect to GWP, AP and EP impacts. Buttol et al. (2007)showed that the introduction of new incinerators had positiveeffects on the environmental impact of waste management in theBologna district (Italy). For a northern Italian waste managementsystem, Rigamonti et al. (2009) showed that energy productionby RMSW incineration had positive effects in comparison to thesame amount of fossil fuel exploited in conventional thermalpower plants. Similarly Di Maria and Fantozzi (2004), Di Mariaet al. (2003) demonstrated the positive effect of thermal treatmentof waste aimed at energy recovery in a given Italian area.Antonopoulos et al. (2013) reported that the adoption of incinera-tion together with anaerobic digestion for waste management inthe Peloponnese (Greece) region led to the greatest benefits incomparison to the other options. According to Rigamonti et al.(2009), processing SSOF by composting is quite neutral from theenvironmental point of view because environmental benefits arecompromised by the energy consumption required. Similar resultswere obtained in this study when SSOF was processed in an ADfacility followed by composting. A critical aspect influencing thisis the amount of energy producible per tonne of OF assumed in thiswork (i.e. 220 kW h/tonne) along with landfilling of the residuals(Fig. 1). An improvement of these values can have significantlypositive effects on environmental performances.

All these results demonstrate that the local conditions can sig-nificantly influence the results of LCA analysis. Among these condi-tions the energetic mix used in the area considered can affect manyof the impact categories adopted for impact assessment. The Italianenergetic mix leads to particularly high advantages when fossilfuel is substituted by renewable ones. This is the main reason forthe particularly high positive effect detected in the scenarios inwhich SRF is used to substitute for coal in cement kilns and forthe positive effect that incineration has with respect to otherRMSW management solutions. Other processes able to producerenewable energy can have limited or negative environmental per-formances if their operation, construction and maintenancerequire significant amounts of energy per tonne of waste pro-cessed. The sensitivity analysis performed by the adoption of dif-ferent weighting procedures (Table 8) shows that the generaltrend of the impact is substantially confirmed. Depending on theweight values assigned to the most relevant impact categories,

the impact assessment can lead to emphasizing environmentalgain or burden, but the trend related to the different SS intensityscenarios does not seem to change significantly.

5. Conclusions

In general the recycling of waste material has positive effectsfor reducing the environmental impact in waste management.The higher fuel and material consumption required to increasesource segregation intensity was largely compensated for by thebenefits of recycling even if drastic increases in SS produced fur-ther limited positive effects. Local conditions significantly influ-ence the quantification of the different impact categories and inparticular the energetic mix of the area considered. In fact, dueto the Italian energetic mix, all the management operations leadingto energy production from waste and hence fossil fuel substitutionhave relevant positive effects. Incineration of residual waste showspositive effects even if the best performances were achieved for thescenarios producing solid recovered fuel for coal substitution. Theenergetic consumption related to the operation and maintenanceof composting and AD facilities, along with the energetic potentialdetermined for the organic fraction collected in the area consid-ered, make these two processes quite neutral from the environ-mental point of view. The adoption of different weightingprocedures for the aggregation of the normalized impact categorieseven though leading to differences in the impact values did notchange the general trend of the analysis.

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