Abstract
With the increase of population and the improvement of people’s living standards, the amount of municipal solid waste (MSW) increases rapidly. It is a challenge for the cities in developing countries to deal with these MSW economically and environmentally. This paper proposed an integrated framework which combines the grey system theory and mathematical programming model to deal with MSW management. First, the factors affecting MSW generation are analyzed and screened out by grey correlation analysis. The factors with higher priority are selected to perform the regression analysis. The generation of MSW is predicted based on the grey model GM (1,1). Second, a multi-period planning model is proposed to optimize MSW management of Qingdao City, China. The model is formulated as mixed integer nonlinear programming (MINLP) model for the scenario with variable capacities of treatment plants and mixed integer linear programming (MILP) for the scenario with given capacities of treatment plants. Four different scenarios are considered: minimum cost scenario with and without variable capacities, minimum carbon emissions with and without variable capacities. The results indicate that the average cost of MSW treatment for the minimum cost scenario with and without variable capacities is 28.32$/t and 27.92 $/t, respectively. The average carbon emission for the minimum emission scenario with and without variable capacities is 0.751 t CO2/t MSW and 0.721 t CO2/t MSW, respectively. This shows the variable expansion capacities of disposal technologies could reduce the cost and carbon emission of MSW treatment compared with the scenario with given capacities. The findings are useful for the decision-maker to adopt effective policy for MSW management. It provides a systematic method for MSW management for other developing countries.
Similar content being viewed by others
Data Availability
All data are provided in the manuscript.
Abbreviations
- j:
-
MSW treatment technology
- t:
-
The period of MSW planning
- \(\gamma\) :
-
The proportion of waste generated during compost process
- \(\varphi\) :
-
The proportion of ash generated in incineration plant
- \(\mu\) :
-
The retention rate of the capacity of incineration facilities
- \(\upomega\) :
-
The retention rate of the capacity of compositing plant
- \(\theta\) :
-
The lower bound of the ratio of MSW treated by incineration plant
- \(\delta\) :
-
The upper bound of the ratio of MSW treated by landfilling site
- \({\beta }_{t}\) :
-
The sorting rate of MSW at period t
- \({\alpha }_{re,t}\) :
-
The proportion of recyclable waste in waste at period t
- \({\alpha }_{org,t}\) :
-
The proportion of food waste in total waste at period t
- \({\beta }_{t}\) :
-
Garbage classification recovery at period t
- \({M}_{t}\) :
-
The total amount of waste generated at period t
- \({MRFC}_{t}\) :
-
The unit operating cost of MSW treated by 3R at period t
- \({WTEC}_{t}\) :
-
The unit operating cost of MSW treated by incineration at period t
- \({COMPC}_{t}\) :
-
The unit operating cost of MSW treated by composting at period t
- \({LFC}_{t}\) :
-
The unit operating cost of MSW treated by landfilling at period t
- \({CCLF}_{t}\) :
-
The unit capital cost of MSW treated by landfilling at period t
- \({CCCOMP}_{t}\) :
-
The unit capital cost of MSW treated by composting at period t
- \({CCWTE}_{t}\) :
-
The unit capital cost of MSW treated by incineration plant at period t
- \({RLF}_{t}\) :
-
The revenue per unit MSW treated by landfilling at period t
- \({RMRF}_{t}\) :
-
The revenue per unit MSW treated by 3R at period t
- \({RWTE}_{t}\) :
-
The revenue per unit MSW treated by incineration plant at period t
- \({RCOMP}_{t}\) :
-
The revenue per unit MSW treated by composting at period t
- \({SC}_{t}\) :
-
The unit cost of MSW sorting at period t
- \({UTC}_{t}\) :
-
The unit cost of MSW transporting at period t
- \({CELF}_{t}\) :
-
The carbon emission per unit MSW treated by landfilling at period t
- \({CEWTE}_{t}\) :
-
The carbon emission per unit MSW treated by incineration at period t
- \({CECOMP}_{t}\) :
-
The carbon emission per unit MSW treated by composting at period t
- \({Q}_{nre,t}\) :
-
The amount of non-recyclable waste generated at period t
- \({Q}_{org,t}\) :
-
The amount of food waste produced at period t
- \({Q}_{re,t}\) :
-
The amount of recyclable waste generated at period t
- \({TQMRF}_{t}\) :
-
The total amount of recyclable waste treated by 3R facility at period t
- \({TQCOMP}_{t}\) :
-
The total amount of waste treated by compost facility at period t
- \({TQWTE}_{t}\) :
-
The total amount of waste treated by incineration facility at period t
- \({TQLF}_{t}\) :
-
The total amount of waste treated by landfill plant at period t
- \({QNRE}_{j,t}\) :
-
The amount of non-recyclable waste treated by technology j at period t
- \({QORG}_{j,t}\) :
-
The amount of organic waste treated by technology j at period t
- \({QCOMP}_{j,t}\) :
-
The amount of waste generated at compost facilities treated by technology j at period t
- \({QWTE}_{j,t}\) :
-
The amount of ash generated at incineration facilities treated by technology j at period t
- \({CWTE}_{t}\) :
-
The capacity of incineration facilities at period t
- \({CCOMP}_{t}\) :
-
The capacity of compost facilities at period t
- \({CLF}_{t}\) :
-
The capacity of landfill plant at period t
- \({NCWTE}_{t}\) :
-
The expanded capacity of incineration plant at period t
- \({NCCOMP}_{t}\) :
-
The expanded capacity of compost plant at period t
- \({NCLF}_{t}\) :
-
The expanded capacity of landfill plant at period t
- \({TOC}_{t}\) :
-
The total operating cost at period t
- \({TCC}_{t}\) :
-
The total capital cost at period t
- \({TSC}_{t}\) :
-
The total cost of MSW sorting at period t
- \({TTC}_{t}\) :
-
The total cost of MSW transportation at period t
- TCE :
-
The total cost of MSW system for the time horizon of interest
- \({x}_{t}\) :
-
The binary decision variable to decide whether the incineration plant is expanded or not at period t. If the facility is expanded, its value is 1; otherwise, it is 0.
- \({y}_{t}\) :
-
The binary decision variable to decide whether the compost facility is expanded or not at period t. If the facility is expanded, its value is 1; otherwise, it is 0.
- \({z}_{t}\) :
-
The binary decision variable to decide whether the landfill facility is expanded or not at period t. If the facility is expanded, its value is 1; otherwise, it is 0
References
Abdallah M, Hamdan S, Shabib A (2021) A multi-objective optimization model for strategic waste management master plans. J Clean Prod 284:124714. https://doi.org/10.1016/j.jclepro.2020.124714
Alam P, Sharholy M, Khan AH, Ahmad K, Alomayri T, Radwan N, Aziz A (2022) Energy generation and revenue potential from municipal solid waste using system dynamic approach. Chemosphere 299:134351. https://doi.org/10.1016/j.chemosphere.2022.134351
Anwar S, Elagroudy S, Abdel Razik M, Gaber A, Bong CPC, Ho WS (2018) Optimization of solid waste management in rural villages of developing countries. Clean Techn Environ Policy 20:489–502. https://doi.org/10.1007/s10098-018-1485-7
Assamoi B, Lawryshyn Y (2012) The environmental comparison of landfilling vs. incineration of MSW accounting for waste diversion. Waste Manage 32(5):1019–1030. https://doi.org/10.1016/j.wasman.2011.10.023
Chen S, Wang X, Tang H, Liang G (2020) Social cost and benefits accounting for municipal solid waste management. Regenerated Resources and Circular Economy 13(6):11–15. https://doi.org/10.3969/j.issn.1674-0912.2020.06.006 [In Chinese]
Deng J (1987) Three properties of Grey Forecasting Model GM (1,1)- the issue on the optimization structure and optimization information volume of grey predictive control. Journal of Huazhong Univ Sci Technol 05:1–6 [In Chinese]
Dhar H, Kumar P, Kumar S, Mukherjee S, Vaidya AN (2016) Effect of organic loading rate during anaerobic digestion of municipal solid waste. Bioresource Technol 217:56–61. https://doi.org/10.1016/j.biortech.2015.12.004
Diaz-Barriga-Fernandez AD, Santibañez-Aguilar JE, Radwan N, Nápoles-Rivera F, El-Halwagi MM, Ponce-Ortega JM (2017) Strategic planning for managing municipal solid wastes with consideration of multiple stakeholders. ACS Sustain Chem Eng 5(11):10744–10762. https://doi.org/10.1021/acssuschemeng.7b02717
Dijkgraaf E, Vollebergh H (2004) Burn or bury? A social cost comparison of final waste disposal methods. Ecol Econ 50(3–4):233–247. https://doi.org/10.1016/j.ecolecon.2004.03.029
Fan YV, Klemeš JJ, Lee CT, Perry S (2018) Anaerobic digestion of municipal solid waste: energy and carbon emission footprint. J Environ Manage 223:888–897. https://doi.org/10.1016/j.jenvman.2018.07.005
Farrell M, Jones DL (2009) Critical evaluation of municipal solid waste composting and potential compost markets. Biores Technol 100(19):4301–4310. https://doi.org/10.1016/j.biortech.2009.04.029
Gao J, Jiang Q, Nie Z, Cai Z, Cai Y (2018) Business accounting and prediction of the total cost of domestic garbage treatment in Shenzhen. Math Model Appl 7(2):59–68. https://doi.org/10.3969/j.issn.2095-3070.2018.02.008 [In Chinese]
Ghosh P, Thakur IS, Kaushik A (2017) Bioassays for toxicological risk assessment of landfill leachate: a review. Ecotox Environ Safe 141:259–270. https://doi.org/10.1016/j.ecoenv.2017.03.023
He J, Lin B (2019) Assessment of waste incineration power with considerations of subsidies and emissions in China. Energ Policy 126:190–199. https://doi.org/10.1016/j.enpol.2018.11.025
He P, Chen L, Shao L, Zhang H, Lü F (2019) Municipal solid waste (MSW) landfill: a source of microplastics? -Evidence of microplastics in landfill leachate. Water Res 159:38–45. https://doi.org/10.1016/j.watres.2019.04.060
Jara-Samaniego J, Pérez-Murcia MD, Bustamante MA, Pérez-Espinosa A, Paredes C, López M, López-Lluch DB, Gavilanes-Terán I, Moral R (2017) Composting as sustainable strategy for municipal solid waste management in the Chimborazo Region, Ecuador: suitability of the obtained composts for seedling production. J Clean Prod 141:1349–1358. https://doi.org/10.1016/j.jclepro.2016.09.178
Jia X, Wang S, Li Z, Wang F, Tan RR, Qian Y (2018) Pinch analysis of GHG mitigation strategies for municipal solid waste management: a case study on Qingdao City. J Clean Prod 174:933–944. https://doi.org/10.1016/j.jclepro.2017.10.274
Jiang J, Liao L, Bi S (2012) Cost-benefit analysis of domestic waste classification in Shenzhen City. Environmental Sanitation Engineering 20(1):20–23. https://doi.org/10.3969/j.issn.1005-8206.2012.01.006[InChinese]
Kundariya N, Mohanty SS, Varjani S, Ngo HH, Wong JW, Taherzadeh MJ, Chang JS, Ng HY, Kim SH, Bui XT (2021) A review on integrated approaches for municipal solid waste for environmental and economical relevance: monitoring tools, technologies, and strategic innovations. Bioresour Technol 125982. https://doi.org/10.1016/j.biortech.2021.125982
Li Z, Jia X, Foo DCY, Tan RR (2016) Minimizing carbon footprint using pinch analysis: the case of regional renewable electricity planning in China. Appl Energy 184:1051–1062. https://doi.org/10.1016/j.apenergy.2016.05.031
Li Z, Jia X, Jin H, Ma L, Xu C, Wei H (2021) Determining optimal municipal solid waste management scenario based on best-worst method. J Environ Eng Land Manage 29(2):150–161. https://doi.org/10.3846/jeelm.2021.14843
Li Z, Huang T, Lee YJ, Wang TH, Wang S, Jia X, Chen CL, Zhang D (2022) Crisp and fuzzy optimization models for sustainable municipal solid waste management. J Clean Prod 370:133536. https://doi.org/10.1016/j.jclepro.2022.133536
Mavrotas G, Florios K (2013) An improved version of the augmented ε-constraint method (AUGMECON2) for finding the exact Pareto set in multi-objective integer programming problems. Appl Math Comput 219(18):9652–9669. https://doi.org/10.1016/j.amc.2013.03.002
Mirdar Harijani A, Mansour S, Karimi B, Lee C-G (2017) Multi-period sustainable and integrated recycling network for municipal solid waste – a case study in Tehran. J Clean Prod 151:96–108. https://doi.org/10.1016/j.jclepro.2017.03.030
Mohammadi M, Jämsä-Jounela S-L, Harjunkoski I (2019) Sustainable supply chain network design for the optimal utilization of municipal solid waste. AIChE J 65(7):e16464. https://doi.org/10.1002/aic.16464
Mostafayi Darmian S, Moazzeni S, Hvattum LM (2020) Multi-objective sustainable location-districting for the collection of municipal solid waste: two case studies. Comput Ind Eng 150:106965. https://doi.org/10.1016/j.cie.2020.106965
National Bureau of Statistics (2021) China Statistical Yearbook 2021. http://www.stats.gov.cn/tjsj/ndsj/2021/indexch.htm. Accessed 30/4/2022
QDRC (2017) Middle- and long term planning of municipal solid waste for incineration in Qingdao. www.dpc.qingdao.gov.cn/upload/211029090523171105/211029090839780070.pdf (Available at 30/4/2022)
Qingdao Municipal Statistics Bureau (2021) Qingdao Statistical Yearbook 2021. Available at http://qdtj.qingdao.gov.cn/tongjisj/tjsj_tjnj/tjnj_2021/202112/P020220415351177064949.pdf (Accessed at 30/4/2022)
Ren X, Che Y, Yang K, Tao Y (2016) Risk perception and public acceptance toward a highly protested waste-to-energy facility. Waste Manage 48:528–539. https://doi.org/10.1016/j.wasman.2015.10.036
Safar KM, Bux MR, Faria U, Pervez S (2021) Integrated model of municipal solid waste management for energy recovery in Pakistan. Energy 219:119632. https://doi.org/10.1016/j.energy.2020.119632
Sánchez-Monedero MA, Fernández-Hernández A, Higashikawa FS, Cayuela ML (2018) Relationships between emitted volatile organic compounds and their concentration in the pile during municipal solid waste composting. Waste Manage 79:179–187. https://doi.org/10.1016/j.wasman.2018.07.041
Sauve G, Van Acker Karel (2020) The environmental impacts of municipal solid waste landfills in Europe: A life cycle assessment of proper reference cases to support decision making. J Environ Manage 261:110216. https://doi.org/10.1016/j.jenvman.2020.110216
Singh A (2019) Solid waste management through the applications of mathematical models. Resour Conserv Recy 151:104503. https://doi.org/10.1016/j.resconrec.2019.104503
Song J, Sun Y, Jin L (2017a) PESTEL analysis of the development of the waste-to-energy incineration industry in China. Renew Sustain Energy Rev 80:276–289. https://doi.org/10.1016/j.rser.2017.05.066
Song G, Sun Y, Zhao C, Liu C, Wang Y (2017b) Social cost accounting for municipal solid waste incineration in Beijing. China Popula, Res Environ 27(8):17–27. https://doi.org/10.12062/cpre.20170413
Trindade AB, Palacio JCE, González AM, Rúa Orozco DJ, Lora EES, Renó MLG, del Olmo OA (2018) Advanced exergy analysis and environmental assessment of the steam cycle of an incineration system of municipal solid waste with energy recovery. Energ Convers Manage 157:195–214. https://doi.org/10.1016/j.enconman.2017.11.083
Vasco-Correa J, Khanal S, Manandhar A, Shah A (2018) Anaerobic digestion for bioenergy production: global status, environmental and techno-economic implications, and government policies. Bioresource Technol 247:1015–1026. https://doi.org/10.1016/j.biortech.2017.09.004
Vavva C, Voutsas E, Magoulas K (2017) Process development for chemical stabilization of fly ash from municipal solid waste incineration. Chem Eng Res Des 125:57–71. https://doi.org/10.1016/j.cherd.2017.06.021
Wang Z, Geng L (2015) Carbon emissions calculation from municipal solid waste and the influencing factors analysis in China. J Clean Prod 104:177-18410. https://doi.org/10.1016/j.jclepro.2015.05.062
Wei Y, Li J, Shi D, Liu G, Zhao Y, Shimaoka T (2017) Environmental challenges impeding the composting of biodegradable municipal solid waste: a critical review. Resour Conserv Recy 122:51–65. https://doi.org/10.1016/j.resconrec.2017.01.024
Wienchol P, Szlęk A, Ditaranto M (2020) Waste-to-energy technology integrated with carbon capture – challenges and opportunities. Energy 198:117352. https://doi.org/10.1016/j.energy.2020.117352
Yang N, Zhang H, Shao LM, Lü F, He PJ (2013) Greenhouse gas emissions during MSW landfilling in China: Influence of waste characteristics and LFG treatment measures. J Environ Manage 129:510–521. https://doi.org/10.1016/j.jenvman.2013.08.039
Zhao R, Liu J, Jie F, Li X, Li B (2021) Microbial community composition and metabolic functions in landfill leachate from different landfills of China. Sci Total Environ 767:144861. https://doi.org/10.1016/j.scitotenv.2020.144861
Funding
This research was supported by the National Natural Science Foundation of China (52100072, 52100213), the Scientific Research Common Program of Beijing Municipal Commission of Education (KM202010017006), the Beijing Natural Science Foundation (8214056), the Fundamental Research Funds for the Central Universities (no. JZ2021HGTA0159 and no. JZ2021HGQA0212), and the Open Project of Key Laboratory of Green Chemical Engineering Process of Ministry of Education (no. GCP202109).
Author information
Authors and Affiliations
Contributions
Sgufen Zhao: conceptualization, methodology, data curation, writing—original draft preparation, and editing.
Tiantian Ren: visualization, writing—reviewing and editing.
Lei Ma: visualization, writing—reviewing and editing.
Zhiwei Li: supervision, software, investigation, data curation, validation, visualization, writing—reviewing and editing.
Corresponding author
Ethics declarations
Ethics Approval
The contents of this manuscript are not now under consideration for publication elsewhere. The contents of this manuscript have not been copyrighted or published previously. The contents of this manuscript will not be copyrighted, submitted, or published elsewhere, while acceptance by the journal is under consideration.
Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Conflict of Interest
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zhao, S., Ren, T., Ma, L. et al. Multi-period Planning of Municipal Solid Waste Management: a Case Study in Qingdao. Process Integr Optim Sustain 7, 107–126 (2023). https://doi.org/10.1007/s41660-022-00279-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41660-022-00279-7