jurnal lingkungan

dhi

C

t of

ec15

Life cycle assessment (LCA) methodology was used to determine the optimum municipal solid waste (MSW) management strategy for

Solid waste management is a complex and multidisci-

perspective (Gottinger, 1988), models that includedrecycling and other waste management methods were

developed in recent years have taken an integrated solid

of waste management. To demonstrate the performance ofmanagement alternatives in the decision-making process,authorities, communities, industry and waste managementcompanies should consider environmental aspects in addi-tion to the evaluation of technical and economic aspects. Itis accepted that life cycle assessment (LCA) concepts and

* Corresponding author. Tel.: +90 222 3213550x6400; fax: +90 2223239501.

E-mail address: [email protected] (M. Banar).

Available online at www.sciencedirect.com

Waste Managementplinary problem that should be considered from technical,economic and social aspects on a sustainability basis. For ahealthy environment, both municipal and industrial wastesshould be managed according to the solid waste manage-ment hierarchy (prevention/minimization/recovery/incin-eration/landlling). For this purpose, dierent techniquescan be used. Studies on modeling of solid waste manage-ment systems were started in the 1970s and were increasedwith the development of computer models in 1980s. Whilemodels in the 1980s were generally based on an economic

waste management approach, and included both economicand environmental analyses. Models have included linearprogramming with Excel-Visual Basic (Abou Najm andEl-Fadel, 2004), Decision Support Systems (Fiorucciet al., 2003; Haastrup et al., 1998), fuzzy logic (Changand Wang, 1997) and Multi Criteria Decision-Makingtechniques (Hokkanen and Salminen, 1997).

One important aspect of waste management planning isto ensure the identication of areas in which specic mea-sures should be taken to reduce the environmental impactsEskisehir city. Eskisehir is one of the developing cities of Turkey where a total of approximately 750 tons/day of waste is generated. Aneective MSW management system is needed in this city since the generated MSW is dumped in an unregulated dumping site that has noliner, no biogas capture, etc. Therefore, ve dierent scenarios were developed as alternatives to the current waste management system.Collection and transportation of waste, a material recovery facility (MRF), recycling, composting, incineration and landlling processeswere considered in these scenarios. SimaPro7 libraries were used to obtain background data for the life cycle inventory. One ton of muni-cipal solid waste of Eskisehir was selected as the functional unit. The alternative scenarios were compared through the CML 2000 methodand these comparisons were carried out from the abiotic depletion, global warming, human toxicity, acidication, eutrophication andphotochemical ozone depletion points of view. According to the comparisons and sensitivity analysis, composting scenario, S3, is themore environmentally preferable alternative.

In this study waste management alternatives were investigated only on an environmental point of view. For that reason, it might besupported with other decision-making tools that consider the economic and social eects of solid waste management. 2008 Elsevier Ltd. All rights reserved.

1. Introduction developed for planning of municipal solid waste manage-ment systems in the 1990s (MacDonald, 1996). ModelsLife cycle assessment of solifor Eskise

Mude Banar *, Zerrin

Anadolu University, Faculty of Engineering and Architecture, Departmen

Accepted 3 DAvailable online

Abstract0956-053X/$ - see front matter 2008 Elsevier Ltd. All rights reserved.doi:10.1016/j.wasman.2007.12.006waste management optionsr, Turkey

okaygil, Aysun Ozkan

Environmental Engineering, Iki Eylul Campus, 26555 Eskisehir, Turkey

ember 2007February 2008

www.elsevier.com/locate/wasman

29 (2009) 5462

aluminum, respectively) are sent directly to the reprocess-ing facility. The restwaste (97%) is collected from curbsidecollection points and taken to the unregulated dumping

Table 1Composition of MSW in Eskisehir

Component Composition (wt.%)

Papercardboard 10.07Metala 1.26Glass 2.49Plastic 5.62Food 67.04Ash 3.87Othersb 9.65Total 100.00

Source: Personal communication with submunicipalities.a It was assumed that all metals are aluminum cans.b This component includes predominantly yard wastes.

Parameters (mg/l leachate)

Suspended solids 2080COD 4418BOD5 3044N-org 255NO3 1361Cl 9150Na+ 132K+ 725Ca+2 450SO4 2000Fe 8.08Zn 0.59Cu 5.63Ni 0.95Cd 0.06

anagement 29 (2009) 5462 55techniques provide solid waste planners and decision mak-ers with an excellent framework to evaluate MSW manage-ment strategies (Obersteiner et al., 2007).

Environmental LCA is a system analysis tool. It wasdeveloped rapidly during the 1990s and has reached a cer-tain level of harmonization and standardization. An ISOstandard has been developed, as well as several guidelines.

LCA studies the environmental aspects and potentialimpacts throughout a product life (i.e., cradle-to-grave)from raw material acquisition through production, useand disposal. This is done by compiling an inventory of rel-evant inputs and outputs of a system (the inventory analy-sis), evaluating the potential impacts of those inputs andoutputs (the impact assessment), and interpreting theresults (the interpretation) in relation to the objectives ofthe study (dened in the goal and scope denition at thebeginning of a study).

In the denition of LCA, the term product includes notonly product systems but can also include service systems,for example waste management systems. LCA is currentlybeing used in several countries to evaluate treatmentoptions for specic waste fractions (Obersteiner et al.,2007; Buttol et al., 2007; Boer et al., 2007; Winkler andBilitewski, 2007; Borghi et al., 2007; Finnveden, 1999;Ozeler et al., 2006).

So, in the study presented in this paper, LCA methodol-ogy was used to analyze and to evaluate dierent alterna-tives that can be implemented to enable the targetsrequired by the European Landll and Packaging andPackaging Waste Directives for solid waste managementin the city of Eskisehir, Turkey. The European LandllDirective (1999) and the Packaging and Packaging WasteDirective (2004) aim to reduce the amount of biodegrad-able municipal wastes going to landll. Therefore in thisstudy, SimaPro7 (2006) software has been applied to modelthe dierent waste management scenarios. All of the dataneeded for the life cycle inventory was gathered from theliterature, the database of the software and thesubmunicipalities.

2. Description of the scenarios

Because of increasing population and developing indus-try in Eskisehir, the quantities of municipal and industrialsolid waste in the city are rising rapidly. Approximately750 tons of MSW is generated daily in Eskisehir. Two pri-vate companies are employed by the two submunicipalities(Tepebasi and Odunpazari) to collect the municipal solidwastes. Vehicles collect wastes in plastic bags that are dis-carded and piled up on the streets by the residents, andtransport the wastes to the unregulated dumping site todumped there at all hours of the day in an uncontrolledmanner.

The composition of the Eskisehir MSW is given inTable 1. Recyclables (paper/cardboard, glass and alumi-

M. Banar et al. /Waste Mnum) have been separated by scavengers and these materi-als (2.04%, 0.71% and 0.25% of paper/cardboard, glass andsite. This unregulated dumping site is an open area wherethe recyclable components of the waste are partially sepa-rated (7%) manually under unhygienic conditions and piledup there to recycle. Then, all of the recyclable materials aresent to the recycling facilities that are in other cities. Thecomposition of the leachate from the current unregulateddumping site is given in Table 2 (Banar et al., 2006).

Wastes have been dumped in a natural valley as con-trolled sustainable MSW management systems are notpracticed in this city. Therefore, in this study, ve alterna-tive scenarios to the current waste management system inEskisehir were developed, and these scenarios were evalu-ated by the means of LCA. Flowcharts of the scenariosare given in Fig. 1ae.

Scenario 1: This scenario was based on the current wastemanagement system, incorporating some improvements. Inthis scenario, a material recovery facility (MRF) and alandll were added to the system. The percentages of recy-cling and landlling are same as for the current waste man-agement system. The recyclable fraction (3%) collected by

Table 2Composition of leachate at Eskisehir dumpsitePb 0.65

Source: Banar et al., 2006.

97 % Scavengers, 3 %

MRF

MSW100 %

Paper-cardboard2.04 %

Others, mix 97 %

LandfillRecycling

(in other city)

Landfill(in other city)

Papercardboard3.40 %

Plastic2.00 %

Aluminum0.42 %

Others90 %


Glass0.71 %

Aluminum0.25 %

Glass1.18 %

Glass0.71 %

Aluminum0.25 %

90.28 %Source separation, 9.72 %

MRF

MSW100 %


Others, mix 90.28 %

LandfillRecycling

(in other city)



Plastic2.53%

Aluminum0.57 %

Others81.53 %

Paper-cardboard5.04%

Plastic2.81%

Glass1.25 %

Aluminum0.63 %

Glass1.12 %

Glass1.25 %

Aluminum0.63 %

Plastic2.81 %

a

b

Fig. 1. Flowcharts of the scenarios (after eciencies). (a) Scenario 1 (S1): 7.5% recycling + 92.5% landlling. (b) Scenario 2 (S2): 15% recycling + 85%landlling. (c) Scenario 3 (S3): 15% recycling + 77% composting + 8% landlling. (d) Scenario 4 (S4): 15% recycling + 85% incineration and (e) Scenario 5(S5): 100% incineration. (The percentages represent the proportion of the total municipal solid waste stream.)

56 M. Banar et al. /Waste Management 29 (2009) 5462

90.28 %Source separation, 9.72 %

MRF

MSW100 %

Landfill

Others4.84 %

Organics76.69 %

Composting

Residuals


Others, mix 90.28 %

Glass1.25 %

Aluminum0.63 %

Plastic2.81 %


Plastic2.53%

Aluminum0.57 %


Plastic2.81%

Glass1.25 %

Aluminum0.63 %

Glass1.12 %

Recycling(in other city)


90.28 %Source separation, 9.72%

MRF

MSW100 %

Incineration

Others81.53 %

Landfill

Residuals


Others, mix 90.28 %

Glass1.25 %

Aluminum0.63 %

Plastic2.81 %


Plastic2.53%

Aluminum0.57 %


Plastic2.81%

Glass1.25 %

Aluminum0.63 %

Glass1.12 %

Recycling(in other city)


c

d

Incineration(100 %)

LandfillResiduals

MSW (100 %)

e

Fig. 1 (continued)

M. Banar et al. /Waste Management 29 (2009) 5462 57

scavengers is sent to the MRF, which was located on thelandll site. The rest of the recyclables (4.30%) was sepa-rated in the MRF. These two parts were processed sepa-rately since their qualities are dierent. After separation,recyclable materials are sent to the recycling facilitieslocated in other cities. Recycling eciencies for these mate-rials are 80% and 70% for the materials brought by scav-engers and those separated in the MRF, respectively. Theresiduals after the recycling process were landlled in thecity where the recycling was undertaken. The restwaste(92.70%) was landlled in Eskisehir.

Scenario 2: In this scenario a source separation systemwith eciency of 50% was added as an improvement toScenario 1. The recyclables obtained from source separa-tion (9.72%) were sent to the MRF, and after processing

major stages: goal and scope denition, life cycle inventory,life cycle impact analysis and interpretation of the results.

3.1. Goal and scope denition

The aim of this study is to select an optimum waste man-agement system for Eskisehir by evaluating, from an envi-ronmental point of view, alternatives to the existing system.It is thought that the results of the study would be helpfulfor the Metropolitan municipality and submunicipalities ofEskisehir.

3.1.1. Functional unit

The functional unit selected for the comparison of thealternative scenarios is the management of 1 ton of munici-

ratio

58 M. Banar et al. /Waste Management 29 (2009) 5462they were sent to the recycling facilities in other cities torecycle, at an eciency of 92%. The recyclables mixed inorganic waste were also processed and sent to the recyclingfacility with an eciency of 70%. After the recycling pro-cess, residuals are sent to the landlls.

Scenario 3: This scenario emphasizes the recovery of thebiologically degradable fraction. The ow of the system issimilar to Scenario 2 for recyclable materials, while organicfraction (77%) from the MRF is transported to the compo-sting facility. The residue from the MRF is sent to the land-ll (8.24%).

Scenario 4: An incineration process was added to systeminstead of a composting facility. In this case, all organicwastes and the wastes from the separated recyclables aretransported to the incinerator (85%).

Scenario 5: In this scenario it was considered that allMSW is sent to the incineration facility (100%).

3. Methodology

The LCA methodology has been used to conduct anenvironmental comparison of the alternative scenarios tothe current waste management system. This evaluationwas conducted according to TSE EN ISO 14040 (1996).According to TSE ISO 14040, an LCA comprises four

Waste source

Composting Incine

Landfilling

MRF

Compost

Raw Materials

Energy

TransportFig. 2. Systempal solid waste of Eskisehir.

3.1.2. System boundaries

The system of the study starts with collection of MSWfrom residential areas and includes waste transport, wastetreatment alternatives (recycling, composting and incinera-tion) and landlling of waste. The system was limited at thelandlling of residual materials after treatment processes.Life cycle analyses of the secondary materials obtainedfrom the recycling and composting processes were not con-sidered. Fig. 2 shows the system boundaries.

3.2. Life cycle inventory

The data for life cycle inventory was gathered fromactual applications in Eskisehir, literature and the databaseof the SimaPro7. The database of the software wasadjusted to the conditions in Turkey. The DQI (Data Qual-ity Indicators) option of the software was used to select themost suitable system for data quality indicators such astime, geography, technology and representativeness.

3.2.1. Collection and transportThere are two submunicipalities in Eskisehir; Tepebasi

and Odunpazari. Tepebasi and Odunpazari were divided

Recycling facility / facilities

n Energy

Energy

Solid emissions

Transport

Transport

Atmosphericemissions

Waterbormeemissions

Residualsboundaries.

into 26 and 25 districts, respectively, according to the datagathered from these submunicipalities. Half of the MSW inOdunpazari is collected on even days and the other part iscollected on single days of the week; the district where thewaste generation is high is collected every night. The MSWis collected every day in Tepebasi.

In this study, new infrastructure was considered to belocated at the same site to take advantage of economicand environmental cost savings; therefore, it was assumedthat the MRF, compost facility, incinerator and landllwere at the same site, which would decrease the environ-mental and economic eects of transport.

Private recycling facilities licensed by the Turkey Min-istry of Environment and Forestry were investigated, andthe closest recycling facilities were selected since there areno facilities of this type in Eskisehir. The recycling facil-ities in Ankara city (233 km) were selected for paper,plastic and aluminum recycling, while Kocaeli city(219 km) was selected for glass recycling. The calculatedtotal recycling rates and transport distances are given inTable 3.

3.2.2. Electrical energy

The source ratios used in electric generation in Turkeyare given in the Table 4, according to the 2006 programof TEIAS (The Transmission System Operator of Turkey).A medium voltage mixed electricity prole of the city has

M. Banar et al. /Waste Manabeen created by using Buwal 250 (2004) and ETH-ESU

Table 3Total recycling rates and transport distances for the scenarios

Collection (km/ton MSW)

Transport for recycling

Total recyclingrates (%)

Transportdistance (km)

Scenario 1 4.11 Papercardboard

5.44 233

Plastic 2.00 233Glass 1.89 219Aluminum 0.67 233

Scenarios2/3/4

4.11 Papercardboard

10.07 233

Plastic 5.62 233Glass 2.49 219Aluminum 1.26 233

Scenario5 4.11

Return of the collection vehicle from the waste area was not considered.

Table 4Electrical energy sources and their contributions in Turkey

Energy sources Contribution of energy sources (%)

Fuel-oil 2.9Coal 7.6Lignite 21.8Natural gas 44.7Hydraulic energy 23.0

Total 100.0

Source: calculated from 2006 program of TEIAS.96 (2004) data for Turkey in collaboration with theseratios. This average data was also used to calculate theemissions saved by energy displaced by energy from waste,i.e. landll gas and incineration.

3.2.3. Recycling and material recovery facility (MRF)Mixed recyclables and separated recyclables (depending

on the scenario) were sent to a MRF. Electricity consump-tion of the MRF for sorting equipment and compressingbales was 0.059 kW h/ton (Bovea and Powell, 2006).

It was considered that processes before recycling werecarried out in three ways scavengers, source separationand MRF. Recycling data was obtained from the Buwal250 library of the SimaPro7. Also, dierent eciencies thatwere used for dierent collection types are given as

Source separation of recyclables: 50%. Separation of recyclables from mixed waste: 70%. Recycling of recyclables after source separation: 92%. Recycling of recyclables collected by scavengers: 80%. Recycling of recyclables after separation of recyclablesfrom mixed waste: 70%.

3.2.4. Composting

A chemical formula (C333H528O195N16PS) for composta-ble waste (that includes food and yard waste) based on theEskisehir MSW composition was formed by using elemen-tal analysis (C,H,O,N,S,P) results taken from Tchoba-noglous et al. (1993). Furthermore, N and P values forthe compost produce were calculated by using this chemicalformula (28.2 kg N/ton waste; 3.9 kg P/ton waste). Theorganic material obtained from the composting process isused as a fertilizer. The avoided material is a chemical fer-tilizer containing an equivalent amount of nutrients (N andP). Also, CO2 and NH3 emissions after composting werecalculated by using the same chemical formula (1.85 tonCO2/ton waste; 0.37 ton NH3/ton waste).

The life cycle inventory data for the chemical N and Pfertilizer avoided is obtained from the IDEMAT 2001library of the SimaPro7. According to Bovea and Powell(2006), the energy consumption during the compostingprocess is due to electricity demand (54.4 MJ/ton of inputto the composting process) and the consumption of dieselin the wheel loader, mills and strainers (555.5 MJ/ton ofinput to the composting process).

3.2.5. Incineration

The incineration process was considered in scenarios 4and 5. Scenario 5 does not have a recycling process. TheBuwal 250 library for the 2000 data was used for incinera-tion of plastic, glass, paper and aluminum. Buwal 250(2000) data reects the future technology, and the inciner-ator of the year 2000 has a more advanced ue gas treat-ment and mainly catalytic deNOx treatment. It was

gement 29 (2009) 5462 59determined that the incinerator of the year 2000 suppliesthe requirements of 2007.

Atmospheric emissions from the incineration of organicwaste were calculated by using the chemical formula(C333H528O195N16PS) of the organic fraction of MSW.

3.2.6. Landlling

Landll processes for the scenarios were performed byusing the Buwal 250 library of the SimaPro7. In these land-ll processes, production of biogas is at 200 m3/ton wastes(47% methane, 37% carbon dioxide, 13% nitrogen); 47% isdirectly emitted into the air and 53% is combusted. Energyproduction from biogas combustion is regarded as a co-product without emissions. The use of methane producedby the landll is 31% of the total gas production for pro-

of 100 years (GWP100), in kg carbon dioxide/kg emission(Goedkoop et al., 2004).

3.3.3. Human toxicity

Characterization factors, expressed as Human ToxicityPotentials (HTP), are calculated with USES-LCA, describ-ing fate, exposure and eects of toxic substances for an in-nite time horizon. For each toxic substance, HTPs areexpressed as 1,4-dichlorobenzene equivalents/kg emission(Goedkoop et al., 2004).

3.3.4. Acidication

The major acidifying pollutants are SO , NO , HCl and

S

6

4

3

60 M. Banar et al. /Waste Management 29 (2009) 5462duction of electricity and heat. The nal eciency is only11% of the total energy content of the gas produced. Theenergy production is deducted in the energy use of the totalsystem and is product specic allocated, depending on thedegradability of the materials.

3.3. Life cycle impact assessment

In this study, six impact categories included by theCML 2000 method (CML 2 baseline 2000 method isan update from the CML 1992 method) were investi-gated: abiotic depletion, global warming, human toxicity,acidication, eutrophication, and photochemical oxida-tion. Characteristics of the impact categories are dis-cussed below.

3.3.1. Depletion of abiotic resourcesThis impact category indicator is related to extraction of

minerals and fossil fuels due to inputs in the system. TheAbiotic Depletion Factor (ADF) is determined for eachextraction of minerals and fossil fuels (kg antimony equiv-alents/kg extraction) based on concentration of reservesand rate of deaccumulation (Goedkoop et al., 2004).

3.3.2. Climate changeThe characterization model as developed by the Inter-

governmental Panel on Climate Change (IPCC) is selectedfor development of characterization factors. Factors areexpressed as Global Warming Potential for time horizon

Table 5Characterization results

Scenarios S1

Abiotic depletion 0.437(kg Sb eq/ton waste managed)

Global warming (GWP100) 6990(kg CO2 eq/ton waste managed)

Human toxicity 135(kg 1.4DB eq/ton waste managed)

Acidication 43.6(kg SO2 eq/ton waste managed)

Eutrophication 37.9(kg PO34 eq/ton waste managed)Photochemical oxidation 1.63 1(kg C2H4/ton waste managed)2 x

NH3. What acidifying pollutants have in common is thatthey form acidifying H+ ions. A pollutants potential foracidication can thus be measured by its capacity to formH+ ions. The acidication potential is dened as the num-ber of H+ ions produced per kg substance relative to SO2(Bauman and Tillman, 2004).

3.3.5. Eutrophication

Eutrophication is a phenomenon that can inuence ter-restrial as well as aquatic ecosystems. Nitrogen (N) andphosphorus (P) are the two nutrients most implicated ineutrophication. Eutrophication potentials are oftenexpressed as PO34 equivalents (Bauman and Tillman,2004).

3.3.6. Photochemical oxidation

This impact indicator denes substances with the poten-tial to contribute to photochemical ozone formation as vol-atile organic compounds (VOCs), which contain hydrogen(not fully substituted) and/or double bond (s) (unsatu-rated). The impact potentials are expressed as an equiva-lent emission of the reference substance ethylene, C2H4(Hauschild and Wenzel, 1998).

4. Results

The results of the characterization analysis per func-tional unit (1 ton of MSW managed) for each impact cate-gory for each scenario are reported in Table 5. As shown in

2 S3 S4 S5

1.11 1.08 1.15 0.16

950 1360 1370 1510

271 269 182 91.9

2.6 41.4 36.7 38.3

7.8 9.13 9.89 9.98.57 0.0857 2.06 2.14

the table, the investigated results for each impact category

E

alys

anaare as follows:Abiotic depletion: S5 is higher than the other scenarios;

S2, S3 and S4 are lower due to avoided raw material usagethrough the recycling process.

Global warming: Methane is the most important impactfor landll scenarios (S1 and S2). The global warming eectfor S4 and S5 mostly results from CO2. S3 is the best sce-nario for this impact category.

Human toxicity: S5 has the highest human toxicity eectdue to nitrogen oxide, with a contribution of 100%. Thescenarios that include recycling (S2, S3 and S4) are betterthan the others; when the background of the softwarewas investigated, it was seen that the avoided human toxic-ity eect resulted from the recycling of aluminum.

Acidication: All of the scenarios except S3 show approx-imately same trend for acidication from ammonia andnitrogen dioxide in the air. S3 is the best scenario for thisimpact category because of the displacement with fertilizer.

Eutrophication: The contribution to eutrophicationeect for S1 and S2 is shared by chemical oxygen demand(COD) and ammonia at the rates of 74% and 25%, respec-tively. Nitrogen dioxide is the dominant substance for theeutrophication eect of S4 and S5. S3 has the lowest valuefor this impact category due mostly to ammonia in the air.

Photochemical ozone depletion: S3 is the best scenarioin this impact category. Photochemical ozone depletioneect for S1 and S2 results from methane. S4 and S5 havehigher values than S1 and S2 because of NO2 emissions.1

10

100

1000

EI99

Fig. 3. Results of sensitivity an

M. Banar et al. /Waste M5. Discussion and conclusion

In compliance with ISO 14042, a sensitivity analysis wasperformed and three dierent impact assessment methods(EcoIndicator95, EcoIndicator99 and EPS00) wereapplied to analyze their inuence on the results. Resultsare presented as points (Pt) on a logarithmic scale (seeFig. 3). According to this gure, the order of alternativescenarios from better to worse from the environmentalpoint of view is as follows:

EcoIndicator99: S3, S2, S1, S4, S5; EcoIndicator95: S3, S4, S5, S2, S1; EPS00: S3, S4, S5, S2, S1.These orders show that the composting scenario, S3, isthe more environmentally preferable. EPS00 and EI95show the same order, while EI99 has other results forS1, S2 and for S4, S5.

In this study, waste management alternatives were inves-tigated from only an environmental point of view. For thatreason, it might be supported with other decision-makingtools that consider the economic and social eects of solidwaste management.

References

Abou Najm, M., El-Fadel, M., 2004. Computer-based interface for an

integrated solid waste optimization model. Environmental Modelling

and Software 19, 11511164.

Bovea, M.D., Powell, J.C., 2006. Alternative scenarios to meet the

demands of sustainable waste management. Journal of Environmental

Management 79, 115132.

Banar, M., Ozkan, A., Kurkcuoglu, M., 2006. Characterization of the

leachate in an urban landll by physicochemical analysis and solid

phase microextraction-GC/MS. Environmental Monitoring and

Assessment 121, 439459.

Bauman, H., Tillman, A., 2004. The Hitch Hikers Guide to LCA.

Studentlitteratur AB, Sweden.

Boer, J., Boer, E., Jager, J., 2007. LCA-IWM: A decision support tool for

sustainability assessment of waste management systems. Waste Man-

agement 27, 10321045.

Borghi, A., Binaghi, L., Borghi, M.G.M., 2007. The application of the

environmental product declaration to waste disposal in a sanitary

landll. International Journal of LCA 12 (1), 4049.

Buttol, P., Masoni, P., Bonoli, A., Goldoni, S., Belladonna, V., Cavazzuti,

C., 2007. LCA of integrated MSW management systems: case study of

the Bologna district. Waste Management 27, 10591070.

Chang, N., Wang, S.F., 1997. A fuzzy goal programming approach for the

PS EI95

es using three LCIA methods.

gement 29 (2009) 5462 61optimal planning of metropolitan solid waste management systems.

European Journal of Operational Research 99, 303321.

European Union. 1999. 99/31/EC: European Landll Directive.

European Union. 2004. 2004/12/EC: European Packaging and Packaging

Waste Directive.

Finnveden, G., 1999. Methodological aspects of life cycle assessment of

integrated solid waste management systems. Resources, Conservation

and Recycling 26, 173177.

Fiorucci, P., Minciardi, R., Robba, M., Sacile, R., 2003. Solid waste

management in urban areas development and application of a

decision support system. Resources Conservation and Recycling

37, 301328.

Goedkoop, M., Oele, M., Eting, S., 2004. SimaPro Database Manual

Methods library. PRe Consultants, Netherlands.

Gottinger, H.W., 1988. A computational model for solid waste manage-

ment with application. European Journal of Operational Research 35,

350364.

Haastrup, P.,Maniezzo, V.,Mattarelli,M.,MazzeoRinaldi, F.,Mendes, I.,

Parruccini, M., 1998. A decision support system for urban waste

management. European Journal of Operational Research 109, 330341.

Hauschild, M., Wenzel, H., 1998. Environmental Assessment of Products.

Scientic background, vol. 2. Chapman & Hall, UK.

Hokkanen, J., Salminen, P., 1997. Choosing a solid waste management

system using multicriteria decision analysis. European Journal of

Operational Research 98, 1936.

MacDonald, M., 1996. Solid waste management models: a state of the art

review. Journal of SolidWasteTechnologyandManagement 23 (2), 7383.

Obersteiner, G., Binner, E., Mostbauer, P., Salhofer, S., 2007. Land ll

modelling in LCA a contribution based on empirical data. Waste

Management 27, S58S74.

Ozeler, D., Yetis, U., Demirer, G.N., 2006. Life cycle assessment of

municipal solid waste management methods: Ankara case study.

Environment International 32, 405411.

Personal communication with CEVKO-Turkish Authorized Recovery

Organization.

Tchobanoglous, G., Theisen, H., Vigil, S.A., 1993. Integrated Solid Waste

Management. McGraw-Hill, Singapore.

Turkish Standards Institution (TSE), 1996. TSE EN ISO 14040: environ-

mental management: life cycle assessment: principles and guidelines

(Turkish Standard).

Winkler, J., Bilitewski, B., 2007. Comparative evaluation of life cycle

assessment models for solid waste management. Waste Management

27, 10211031.

62 M. Banar et al. /Waste Management 29 (2009) 5462

Life cycle assessment of solid waste management options for Eskisehir, TurkeyIntroductionDescription of the scenariosMethodologyGoal and scope definitionFunctional unitSystem boundaries

Life cycle inventoryCollection and transportElectrical energyRecycling and material recovery facility (MRF)CompostingIncinerationLandfilling

Life cycle impact assessmentDepletion of abiotic resourcesClimate changeHuman toxicityAcidificationEutrophicationPhotochemical oxidation

ResultsDiscussion and conclusionReferences

jurnal lingkungan

Documents