Waste Management & Research2014, Vol. 32(8) 763 –771© The Author(s) 2014Reprints and permissions: sagepub.co.uk/journalsPermissions.navDOI: 10.1177/0734242X14542683wmr.sagepub.com

Introduction

Various risks posed by hazardous wastes (HWs) require the establishment of management systems that will ensure their proper handling from the point of generation to final disposal. Although the quantities of HWs are lower compared to non-HWs, properly managing these wastes demands higher invest-ment costs and a higher level of safety (Turkish Ministry of Environment and Urbanization (MoEU), 2005). Ideally, planning and decision-making processes should be based on detailed anal-ysis of HW generation data, their industrial and geographic dis-tribution, and anticipated future trends whenever possible. National inventory for hazardous wastes is regarded as an indis-pensible preliminary step for the development of national man-agement policy for such wastes and implementation of the Basel Convention on the Control of Transboundary Movements of Hazardous Wastes and their Disposal (Secretariat of Basel Convention, 2000).

Results of a national hazardous waste inventory obtained on a regular basis can be used to:

• follow up- or downward trends of total waste generation and disposal (U.S. EPA 2012);

• collect information on quantities of hazardous waste man-aged through recycling, energy recovery and treatment (U.S. EPA, 2012);

• analyse waste management trends within the sectors and determine priority sectors (U.S. EPA, 2012).

• obtain information on newly implemented source reduction activities (U.S. EPA, 2012);

Use of theoretical waste inventories in planning and monitoring of hazardous waste management systems

Ozge Yilmaz1, Zehra S Can2, Ismail Toroz3, Ozgur Dogan4, Salim Oncel5, Emre Alp6, Filiz B Dilek6, Tanju Karanfil1 and Ulku Yetis6

AbstractHazardous waste (HW) generation information is an absolute necessity for ensuring the proper planning, implementation, and monitoring of any waste management system. Unfortunately, environmental agencies in developing countries face difficulties in gathering data directly from the creators of such wastes. It is possible, however, to construct theoretical HW inventories using the waste generation factors (WGFs). The objective of this study was to develop a complete nationwide HW inventory of Turkey that relies on nation-specific WGFs to support management activities of the Turkish Ministry of Environment and Urbanization (MoEU). Inventory studies relied on WGFs from: (a) the literature and (b) field studies and analysis of waste declarations reflecting country-specific industrial practices. Moreover, new tools were introduced to the monitoring infrastructure of MoEU to obtain a comprehensive waste generation data set. Through field studies and a consideration of country specific conditions, it was possible to more thoroughly elucidate HW generation trends in Turkey, a method that was deemed superior to other alternatives. Declaration and literature based WGFs also proved most helpful in supplementing field observations that could not always be conducted. It was determined that these theoretical inventories could become valuable assets in supporting regulating agencies in developing countries for a more thorough implementation of HW management systems.

KeywordsHazardous waste, management, waste generation factor, monitoring, disposal, field study

1 Environmental Engineering and Earth Sciences Department, Clemson University, Anderson, SC, USA

2 Environmental Engineering Department, Marmara University, Göztepe Kampüsü Kadıkoy, Istanbul, Turkey

3 Environmental Engineering Department, Istanbul Technical University, Maslak, Istanbul, Turkey

4Tubitak Marmara Research Centre, Gebze, Kocaeli, Turkey5 Environmental Engineering Department, Gebze Institute of Technology, Gebze, Kocaeli, Turkey

6 Environmental Engineering Department, Middle East Technical University, Ankara, Turkey

Corresponding author:Ulku Yetis, Environmental Engineering Department, Middle East Technical University, 06800, Ankara, Turkey. Email: uyetis@metu.edu.tr

542683WMR0010.1177/0734242X14542683Waste Management & ResearchYilmaz et al.research-article2014

Original Article

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• comply with reporting requirements of the Basel Convention (Ministry of Environment and Forests (MoEF), 2010) or the European Union (EU) legislation;

• locate facilities required for managing hazardous wastes and determine their size and capacity by means of geographical distribution of wastes (MoEF 2010);

• support enforcement of related environmental regulations.

From the point of regulatory stakeholders, the most desirable strategy would be to gather generation data directly from waste generators through a mandatory waste declaration system such as the Toxic Release Inventory (TRI) Program in the United States or the European Pollutant Release and Transfer Register (E-PRTR) in the EU (EC, 2013; U.S. EPA, 2013). In these pro-grams, emission data is collected effectively from each waste generator on a periodical basis. The main challenges of this type of data collection are to ensure the participation of all generators regularly and to verify the accuracy of submitted declarations. One alternative method to acquiring the HW gen-eration data directly may be through statistical studies. However, the data collected for such studies may not be condu-cive and detailed enough for HW management systems (HWMSs).

Developing countries face important difficulties in terms of obtaining detailed and accurate waste generation data generally due to absence of strong regulatory enforcement (Secretariat of Basel Convention, 2010). According to the UN Statistics Division (2009) only 10% of the 87 countries examined presented HW generation data sets regularly between 1995 and 2007, while 31% of countries provided only a single set of data for the same period. Such countries require a secondary source of information to compensate for the missing data and to use as a tool to verify the generators’ declarations.

Without direct information, HW production data may be theo-retically estimated. For this purpose, waste generation factors (WGFs), which are multipliers to predict waste generation from a production unit, number of employees, or an economic unit, are used. WGFs can be obtained from the literature, field studies or by analysing waste declaration information. Although the basic principle behind the theoretical approach is simple, it is impor-tant to note that WGFs may vary depending upon (a) the type of processes used in a particular industry and (b) the country spe-cific nature of some industrial practices (e.g. reliance on labour vs automation).

As a developing country, Turkey is currently establishing an effective HWMS. It is a signatory to the Basel Convention and the legislative framework for HW management follows EU environmental acquis. The core legislative document that con-cerns hazardous and non-hazardous waste management is The Regulation on General Principles of Waste Management (MoEU, 2008a). The identification system, covered by this regulation, is in line with the European six-digit code structure assigned to separate waste streams. This system is based on classification of HWs under possible economic activities or general waste classes. Furthermore, similar to classification in

the EU, absolute and mirror wastes are identified (Yilmaz et al., 2011).

Two existing sources for waste generation data include the Turkish Statistical Institute (TurkStat) and MoEU. Publicly avail-able HW generation data from TurkStat includes total quantities, possible destinations for HWs, and waste distribution based on a coarse sectoral classification, which is not detailed enough to be used for planning purposes. According to these biannual statis-tics, hazardous waste generation decreased from 1.2 to 0.81 mil-lion metric tonnes per year (t yr−1) from 2004 to 2012 (TurkStat, 2014). On the other hand, in 2008, MoEU estimated hazardous waste generation as 4.6 million t yr−1 (MoEU, 2009a). Values reported by TurkStat and MoEU were contradictory and raised questions on reliability of both data sets. In both cases, unfortu-nately, the gaps in information regarding the quantity of waste and its distribution have prevented a complete inventory. The aim of this study was to obtain a national HW inventory to support the planning of HW disposal operations and monitoring activities of the MoEU. The approach and experiences presented in this paper are expected to provide guidance to other developing countries trying to set up national inventories to support the establishment of HWMSs.

Methodology

According to the Secretariat of Basel Convention (2000), the methodology for building and maintaining a national inventory of HWs should involve (a) preparation of inventory, (b) incorpo-ration of first results, and (c) maintenance of inventory. During inventory development, preference could initially be given to sectors of economic activity and the HWs considered to be a priority.

It is suggested that as a first step, a modelling or an indirect method can be used. This approach would enable useful results with relatively little effort and lead to identification of sectors and HWs to be given priority. Next, by utilizing a more direct approach, initial results should be validated. The direct method involves technical visits to HW generating establishments (Secretariat of Basel Convention, 2010).

In this study, we followed a similar approach that included three phases (Figure 1). In the first phase, the goal was to develop a basic understanding of waste generation trends in Turkey by using the WGFs from the literature (indirect approach). In the second phase, WGFs were obtained by creating an inventory based on field studies and analyses of waste declarations submit-ted to the MoEU (direct approach). The last phase of the study was carried out for validation purposes. It also focused on improving the national Hazardous Waste Declaration System (HWDS), which is a web-based information management system used by waste generators to submit annual declarations to the MoEU.

Furthermore, the data generated throughout the inventory phases were analysed in terms of industrial and geographic distri-bution to support informed decision-making process regarding HW disposal facilities.

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Phase I: WGFs from the literature (Inventory A)

WGFs developed by international organizations are available through many different sources (U.S. EPA, 2011; IFC 2013; JRC, n.d.). The suitability of using the literature WGFs must be deter-mined, however. The representativeness of WGFs in terms of national and/or industry specific conditions and their limited availability are the two of the most important bottlenecks hinder-ing their full use.

To predict HW generation in Turkey, 120 WGFs were initially obtained. A sample list of WGFs is presented in Table S.1 in the Supporting Information (SI). These different waste streams origi-nate from the industrial sectors listed in Figure 2, and the selected industries were mostly determined by the availability of WGFs. For every industrial sector, production processes, and HW gen-eration were identified. The geographical distribution of indus-trial production was obtained from an industrial database (TOBB, 2008) and the Turkish Ministry of Development (MoD, 2008). Other relevant statistical information (population, number of vehicles, etc.) was available from TurkStat (2010).

Phase II: WGFs from waste declarations and field studies (Inventory B)

WGF and inventory development in the second phase relied on direct information. The field studies took precedence over waste declaration analysis as fieldwork better elucidates the HW

generation at the plant level and represents relevant country-spe-cific conditions.

We started this phase by choosing the priority sectors in terms of waste generation based on the results of Phase I as well as previous inventory studies (Yilmaz, 2006; MoEU, 2009b; TurkStat, 2010). These sectors listed in Figure 2 were expected to have significant contribution to overall HW generation. In Turkey, the most important sectors under the manufacturing industry in terms of added value are basic metal, food, textile, automotive, and chemical industries (Kucukkiremitci, 2012). There is a resemblance between industrial structure and waste generation patterns, as the highest hazardous waste generating industries are also the major contributors in terms of added value to the economy.

The methodology followed through this part of the study can be seen in Figure 3. In the preparatory stage, requisite informa-tion on process alternatives, material inputs–outputs, and possi-ble waste streams were obtained. This stage was followed by on-site assessments and mass balance analyses to link the quanti-ties of waste to capacity or production. Whenever possible, stud-ies were carried out in more than one plant for verification purposes with the secondary purpose of investigating multiple process alternatives to extend the coverage of WGFs. Outputs of the mass balance studies were the range of WGFs for each waste stream (i.e. the six-digit code) occurring in the plant.

Industrial plants employ a variety of main process alternatives and auxiliary processes. Although these side processes create

Figure 1. Progress of inventory studies.

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HWs, they will not necessarily be generated in every establish-ment. In our plants under study, we also observed the occurrence of waste production from non-process specific sources, such as kitchens, offices, or infirmaries. From these discrete sources, waste streams were classified consequently as (a) process, (b) auxiliary process (AP), and (c) non-process (NP). Process wastes resulting from core production processes are expected from every industrial establishment, whereas AP wastes are expected only if certain side processes are applied within that industrial establish-ment. Occurrence of NP wastes was also expected, with their WGFs usually site specific. AP and NP waste streams were iden-tified for each plant and production route.

In the verification stage, all WGFs were analysed to ensure that factors obtained from different establishments (having the same process) are comparable. Subsequent studies were con-ducted in plants to increase data quality as necessary, and a set of process based WGFs were obtained that were specific to each industry.

Although the development of WGFs through pilot plant stud-ies is more desirable, it was not practically feasible to investigate all industrial sectors with field studies (due to limitations in time, labour, and willingness to participate, etc.). We extended the cov-erage of the study to additional sectors so that results would rep-resent a higher percentage of national HW production. For the additional sectors given in Figure 2, a mixed strategy that involved development of WGFs from field studies and waste declarations was adopted.

Collected annually in most countries, waste declarations pro-vide continuous input on the temporal variations in HW genera-tion. In order to obtain WGFs from waste declarations, it was necessary to gather production figures/capacity and quantities of HW streams at the producer or regional level. However, process-ing data at the regional level prevents the allocation of waste gen-eration between different production alternatives or process/AP/NP wastes. For this reason, WGFs were developed on a genera-tor-basis as much as possible. Similar to Inventory A, capacity information was obtained from TOBB (2008) and MoD (2008). Though not as detailed as field studies, we nonetheless acquired valuable country-specific waste generation information through declarations that was immensely useful in the development of WGFs for additional sectors.

More than 500 WGFs were obtained from field studies con-ducted in 32 pilot plants and from analyses of waste declarations. Of these pilot plants, 23 belong to priority sectors and the rest

Figure 2. Sectors covered under Inventories A and B. (Underlined items under Inventory B are the priority sectors, while rest are classified as additional sectors for this study.)

Figure 3. Methodology followed for field studies.

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operate under additional sectors. Further distribution of these plants is presented in the SI. While we tried to maximize the number of the establishments in which field studies were con-ducted, the selection of these plants was limited by willingness, as the participation was on voluntary basis. As will be explained in more detail in Section 3.2, these WGFs will be used exclu-sively by the MoEU for monitoring purposes. Therefore, only a selection of WGFs was presented in Table S.2 in the SI.

Phase III: Improvement of HWDS

According to the methodology laid down by the Secretariat of Basel Convention (2010), following incorporation of the initial results, the national inventory should be maintained. Although the field studies provided invaluable insight to hazardous waste generation, maintenance should be achieved through periodical input of waste generators via a mandatory waste tracking system (HWDS in our case).

The main objective of the third phase was to ensure validation of the waste generation data collected through HWDS in two ways. First, we aimed to verify the accuracy of waste declara-tions by using WGFs obtained in previous phases. Second, WGFs themselves should be validated, for which we incorporated a sta-tistical analysis tool.

Based on the needs of the MoEU, (a) waste lists, (b) WGFs, and (c) a statistical analysis tool were added to the system. Past experiences showed that during identification of their wastes, generators were struggling with high numbers of six-digit codes listed in the regulations. In order to simplify this task, HWDS was restructured to compile lists of possible waste streams based upon main process alternatives and auxiliary processes utilized by generators. Tentative lists of process/AP/NP wastes were planned to provide guidance to waste generators when crafting their declarations.

Ranges of WGFs developed for different sectors in the second phase were introduced to the system. These factors, visible only to the MoEU officials, will be used to calculate the minimum and maximum possible waste production from a generator based on the production/capacity of the establishment. By comparing the declarations with the range of expected waste generation, MoEU will be able to spot faulty reports and take action.

For this system to work properly, it was also necessary to vali-date the WGFs as well. For this purpose, we incorporated a sta-tistical tool to the HWDS, which would fine-tune the range of WGFs regularly. Based on available WGFs, we have determined that a 68% confidence interval was suitable for establishing mini-mum and maximum boundaries for WGFs. (Further details pro-vided in the SI.) The statistical tool operated at the end of the reporting period will calculate the range of WGFs to be utilized for verification purposes. For the first year, the WGF dataset was the one obtained at the end of Phase II. Additional WGFs will be calculated by the system based on waste declarations. These new WGFs will be added to the dataset and a new dataset will be obtained at the end of each reporting year that will include both previous and new WGFs. In this sense, the statistical tool will

enable a dynamic dataset and compensate for the missing WGFs. This loop process of fine-tuning is also in accordance with the Secretariat of Basel Convention’s recommendations.

ResultsInventory results (Phases I and II) and their usefulness in planning activities

Total HW generation in Turkey is estimated to be 1.38 million t yr−1 in Inventory A and 1.21 million t yr−1 in Inventory B. Since neither of the inventories covered all industrial sources, these numbers present the minimum HW generation potential. Despite the differences in industrial coverage between the two invento-ries (Figure 2), both were consistent with the estimates of TurkStat (2010), in terms of total generation.

The highest amount of HW generated in Turkey falls under the aegis of waste oil, as Table 1 indicates, with metal coating and pharmaceutical manufacturers the prime contributors in both inventories. While Inventory A underestimated waste generation from iron and steel, iron casting, and plastic products manufac-turing, it overestimated waste quantities arising from organic bio-cide/pesticide, paint, ink, and adhesive manufacturers. Beside these discrepancies, no AP waste generation could be obtained by using WGFs from the literature, because, most of these WGFs focus on primary and not auxiliary production processes. Thus, it is imperative to conduct field studies encompassing the entire range of both AP and NP waste streams.

The success of every national HWMS depends upon the pres-ence of fully functional waste disposal facilities at proper loca-tions and having sufficient capacities to both ensure proximity and self-sufficiency (Secretariat of Basel Convention, 1989). Considering their key role in public safety and high investment costs, obtaining accurate spatial and sectoral distribution of waste generation is of the utmost importance during the planning of any HWMS.

The regional distribution of HW generation in Turkey is shown in Figure 4. The darker colours represent the greater con-centration HW generation from industrial facilities. The eastern regions of the country with relatively insignificant rates of waste generation are represented by the lighter colours. In this sense, the generation of these wastes exhibits a similar trend to the GDP share of each individual province, which can be used to verify inventory outputs (TurkStat, 2011).

To assess adequacy of waste disposal operations each waste stream was assigned to one of the waste processing alternatives based on their properties. If a waste stream was found to be suit-able for more than one alternative, they were allocated to suitable destinations based upon assumed percentages that reflect current waste disposal practices in Turkey.

Our results, summarized in Table 2, show a variation in inven-tories, particularly in terms of treatment and incineration require-ments. According to Inventory A, more than 40% of wastes generated throughout Turkey should be sent to incineration, unlike in Inventory B, which resulted in a much lower amount of

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combustible wastes. In contrast, the limited data available in Inventory A led to an underestimation of treatable wastes (Figure 4). In our field studies, we more thoroughly elucidated the liquid hazardous wastes that are occasionally discharged as industrial wastewater.

In Table 2, inventory results are also compared with current HW handling capacities in Turkey. Although Inventory B indi-cated the generation of high quantities of treatable HWs, there is no designated treatment plant in Turkey for these types of wastes, which should clearly be a priority when planning new facilities. Furthermore, the available capacities of all other handling opera-tions are below the estimated HW generation. Clearly, additional incineration and landfills designated for HW management are required. The difference between required and available capaci-ties combined with geographic distribution can be used to develop business plans to expand existing facilities or build new ones. Yilmaz (2011) used results of Inventory A as a decision

variable for a multi-objective linear programming model that aims to locate HW facilities under cost and risk considerations.

In order to understand specific handling requirements, we fur-ther analysed our results in Inventory B (Figure 5). From this analysis, we determined that the majority of waste oils and wastes from organic chemical industries were suitable for recovery and incineration. From this data, we recommend locating recovery and incineration facilities close to high capacity plants to avoid possible HW incidents that may occur with the transportation of such wastes.

Through our data, we also determined that the metal industry generates substantial wastes that often end up in landfills, which, according to the waste hierarchy principle, is the least desired option among disposal alternatives. Consequently, setting up pro-grams to minimize these wastes should be a high priority for the Turkish government and for the manufacturers of these products.

Table 1. Sectoral HW generation (t yr−1).

Industrial sectors/Waste types Inventory A % Inventory B %

Process wastes

NP wastesa

Totalb Process wastes

AP wastesa

NP wastesa

Totalb

Waste oils 344,680 25.94 229,706 18.92Metal coating 159,300 2,736 162,037 11.72 130,152 32,826 36,569 199,547 16.43Iron casting 0 5,468 5,468 0.40 142,740 9,213 4,783 156,736 12.91Plastic products 0 9,290 9,290 0.67 41,584 11,546 94,409 147,538 12.15Pharmaceuticals 145,680 218 145,898 10.56 132,610 N/A 2,368 134,978 11.12Iron and steel 0 9,290 9,290 0.67 0 105,866 27,952 133,818 11.02Automotive industry 1,076 8,897 9,973 0.72 24,173 462 15,036 39,670 3.27Organic biocides and pesticides 124,949 14,399 139,348 10.08 31,894 N/A 0 31,894 2.63Paint, ink, and adhesives 107,806 611 108,418 7.84 19,390 N/A 7,389 26,779 2.21Petroleum refining 29,053 0 29,053 2.10 25,347 N/A 253 25,600 2.11Healthcare centres 41,198 218 41,416 3.00 24,109 N/A 65 24,174 1.99Household appliances 166 218 384 0.03 15,263 N/A 1,751 17,013 1.40Batteries and accumulators 26,434 23,743 50,177 3.63 13,590 N/A 200 13,790 1.14Leather industry 0 384 384 0.03 10,579 N/A 2,716 13,295 1.09Petrochemical industry 52,863 1,000 53,864 3.90 9,843 N/A 371 10,214 0.84Aluminium production 24,878 218 25,096 1.82 7,432 0 0 7,432 0.61End of life vehicles 0 218 218 0.02 1,957 N/A 0 1,957 0.16Secondary copper production 27,475 1,218 28,693 2.08 92 1 37 131 0.01WEEE – 69 0.01Energy production 105,021 N/A 105,021 7.60 – Household hazardous wastes 50,902 3.68 – Soap, grease, and detergents 16,192 N/A 16,192 1.17 – Waste solvents 13,587 0.98 – Waste treatment 12,894 0.93 – Inorganic chemical production and use

10,497 N/A 10,497 0.76 –

Printing 3,397 N/A 3,397 0.25 – Dry cleaning 3,190 N/A 3,190 0.23 – Wood preservation 2,842 N/A 2,842 0.21 – Total 1,382,210 1,214,340

aN/A: No waste stream was identified as AP/NP waste for that sector.b – : Waste generation could not be estimated due to absence of the Literature WGF, field studies, and/or waste declarations. Single entry under Total column indicates process, AP, and NP classifications are not applicable for that sector/waste type (e.g. waste oils).

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Use of inventory results in monitoring activities (Phase III)

Another component of any effective HWMS in which findings of our current study are of use were the monitory activities under-taken by regulatory agencies. Today, when waste generation pro-fessionals log into the HWDS, they are asked to identify their industrial activities and complete a sector-specific survey to reveal their core and auxiliary processes. At the end of the survey, they are provided with tentative waste lists for their core and aux-iliary activities. These lists provide guidance to waste profession-als for the selection of proper waste types and codes in their declarations.

Furthermore, the WGFs obtained in Inventory B were incor-porated into HWDS to strengthen both monitoring and enforce-ment activities. Based upon the production capacity reported by waste generators and WGFs, the system determines the amount of waste streams expected from these generators. In order to

account for uncertainties, we decided to keep the range for the WGFs instead of the mean values used in Inventory B. The val-ues either below the minimum or above the maximum level are reported to administrative staff. Using this procedure, MoEU officials now have the ability to check the declarations and take the necessary actions. Although more than 500 WGFs were sub-mitted to the MoEU, Inventory B did not encompass all indus-tries within Turkey. In order to compensate for the missing data, WGFs calculated from declarations during time will be analysed to obtain a statistical distribution. This statistical distribution will help to calculate the missing WGFs and also refine the range of those WGFs in the system.

Concluding remarks

A systematic study was conducted to obtain a national HW inventory in Turkey. The results indicated a minimum estimate generation of 1.2–1.4 million t yr−1of HW in Turkey. Important

Figure 4. Geographical distribution of hazardous waste generation according to (a) Inventory A and (b) Inventory B.

Table 2. Waste generation potential in terms of disposal requirement.

Inventory A Inventory B Established capacity

Amount (t yr−1) % Amount (t yr−1) % (MoEU, 2008b)

Recovery 391,128 28.3 388,781 32.0 263,660 t yr−1

Treatment 53,257 3.8 231,212 19.0 –Incineration 576,466 41.7 286,844 23.7 147,750 t yr−1a

Landfilling 361,359 26.2 307,273 25.3 4,135,000 m3

Total 1,382,210 100.0 1,214,340 100.0

aIncluding incineration, gasification, co-incineration.

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contributors to this waste stream were metal manufacturers (iron and steel, iron casting, metal coating sectors) and the chemical industry (pharmaceutical and plastic products manufacturers). The types of waste streams were also analysed in terms of their geographical distribution and suitability to waste disposal alter-natives. To improve both the monitoring and enforcement of current waste management systems, WGFs and tentative secto-ral waste lists were created to provide guidance regarding how to craft declarations and verify them.

Literature WGFs were employed in Inventory A, while con-ducting field studies and analysis of waste declarations were the main approaches used to develop country specific WGFs in Inventory B. Similar outputs were obtained in both inventories in terms of total waste generation and geographic distribution. However, similar predictions of waste generation may not be possible in other case studies depending upon the WGFs availa-ble. Considering the fact that overestimated quantities were cor-rected and data gaps were filled, clearly Inventory B provided a more realistic picture for Turkey.

The main advantage of using field studies to develop WGFs was the ability to obtain country specific waste generation infor-mation in great detail and to observe variations in waste produc-tion from different process alternatives (e.g. AP or mirror wastes). In addition, unlike attempting to verify WGFs in the literature, which is not possible without background information on plants and processes, here we verified sectoral WGFs and their suitabil-ity to country specific conditions through our observations at multiple plants.

Although field studies provided in-depth knowledge on national generation trends, detailed process and mass balance studies in multiple installations demand extensive efforts and industry collaboration. Industrial participation in this study was voluntary, and the willingness to share information on production processes and mass flows played a very important role for the successful development of Inventory B. The level of industrial participation and collaboration may create a bottleneck for other inventory studies, however.

While the waste declarations of our industry participants were helpful in understanding country-specific HW production, a thor-ough understanding of the volume and content of the HWs gener-ated in Turkey is only possible after verification of these declarations through field studies or statistical methods. Although convenient, literature WGFs may lack availability and have lim-ited suitability to all cases, which may result in over- and under-estimation of important industrial sectors.

Our WGFs obtained from the literature provided only a basic understanding of waste generation trends and were insufficient for satisfying the data demands of the Turkish environmental authorities. Should they have more resources and time allocated for such work, field studies provide an invaluable source of infor-mation to improve the quality of theoretical data. Based on the extensive case study presented in this article, we propose the use of field studies as much as possible in combination with the sta-tistical analysis of existing waste declarations, if full coverage cannot be achieved. It is possible to correctly estimate the amount of HWs generated in developing nations in lieu of using of WGFs. We found that our resulting data sets were quite useful to support planning, implementation and monitoring of national HWMSs.

As a final remark, HW management professionals in develop-ing countries can benefit from the detailed account of the steps taken in this work to implement the Secretariat of Basel Convention’s methodology. Despite the fact that care should be taken while employing the WGFs of this study in other countries due to their country-specific nature, comparison of various approaches and identification of bottlenecks would guide our colleagues while establishing national inventories in other devel-oping countries.

AcknowledgementsOur appreciation goes to Ms. Betul Dogru, head of the Industrial Waste Management Department of the MoEU, and its officials, who provided invaluable support for this research. We also wish to grate-fully acknowledge the assistance of all the members of our research

Figure 5. Waste disposal operations suitable for industrial sectors (Inventory B).

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group and industrial representatives that agreed to participate in the study and provided invaluable feedback.

Declaration of conflicting interestsThe authors declare that there is no conflict of interest.

FundingThis work was supported by the Turkish Scientific and Technological Research Council (TUBITAK) as a part of the “Hazardous Waste Management In Compliance With European Union Environmental Regulations In Turkey” [107G126] Project.

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