Forecasting Municipal Solid Waste Removal Volume Based on Socioeconomic Indicators for Carbon Reduction Strategy in Beijing’s Waste Management 

Municipal solid waste (MSW) management poses a significant challenge amidst global population growth and urbanization. With Beijing as a focal point due to its substantial contribution to MSW generation and greenhouse gas (GHG) emissions, this study employs two-stage Bayesian-optimized Artificial Ne...

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Main Authors: Yaxin Cui, Min Yee Chin, Hong Sheng Loh, Chew Tin Lee, Pei Ying Ong, Yee Van Fan, Kok Sin Woon
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2024-12-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/14981
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author Yaxin Cui
Min Yee Chin
Hong Sheng Loh
Chew Tin Lee
Pei Ying Ong
Yee Van Fan
Kok Sin Woon
author_facet Yaxin Cui
Min Yee Chin
Hong Sheng Loh
Chew Tin Lee
Pei Ying Ong
Yee Van Fan
Kok Sin Woon
author_sort Yaxin Cui
collection DOAJ
description Municipal solid waste (MSW) management poses a significant challenge amidst global population growth and urbanization. With Beijing as a focal point due to its substantial contribution to MSW generation and greenhouse gas (GHG) emissions, this study employs two-stage Bayesian-optimized Artificial Neural Network models to forecast MSW removal volume and evaluate associated GHG emissions in Beijing. The analysis integrates socioeconomic indicators, including population and GDP, to elucidate the complex relationship between MSW generation and economic development. Various MSW treatment scenarios are assessed by alternating the configuration of sanitary landfills, incineration, and composting. Results indicate a projected MSW removal volume of approximately 14 Mt by 2060, a 63.16 % reduction compared to 2023. Scenario 2 (50 % incineration and 50 % composting) demonstrates the potential to reduce GHG emissions by approximately 4.11 Mt of CO2e compared to the current practice. The findings underscore the need for comprehensive waste management strategies integrating waste segregation, incineration, and composting to achieve sustainable MSW treatment.
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institution DOAJ
issn 2283-9216
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publishDate 2024-12-01
publisher AIDIC Servizi S.r.l.
record_format Article
series Chemical Engineering Transactions
spelling doaj-art-5b15fcf6bb894f85b8ed062819a7071c2025-08-20T02:39:19ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162024-12-01114Forecasting Municipal Solid Waste Removal Volume Based on Socioeconomic Indicators for Carbon Reduction Strategy in Beijing’s Waste Management Yaxin CuiMin Yee ChinHong Sheng LohChew Tin LeePei Ying OngYee Van FanKok Sin WoonMunicipal solid waste (MSW) management poses a significant challenge amidst global population growth and urbanization. With Beijing as a focal point due to its substantial contribution to MSW generation and greenhouse gas (GHG) emissions, this study employs two-stage Bayesian-optimized Artificial Neural Network models to forecast MSW removal volume and evaluate associated GHG emissions in Beijing. The analysis integrates socioeconomic indicators, including population and GDP, to elucidate the complex relationship between MSW generation and economic development. Various MSW treatment scenarios are assessed by alternating the configuration of sanitary landfills, incineration, and composting. Results indicate a projected MSW removal volume of approximately 14 Mt by 2060, a 63.16 % reduction compared to 2023. Scenario 2 (50 % incineration and 50 % composting) demonstrates the potential to reduce GHG emissions by approximately 4.11 Mt of CO2e compared to the current practice. The findings underscore the need for comprehensive waste management strategies integrating waste segregation, incineration, and composting to achieve sustainable MSW treatment.https://www.cetjournal.it/index.php/cet/article/view/14981
spellingShingle Yaxin Cui
Min Yee Chin
Hong Sheng Loh
Chew Tin Lee
Pei Ying Ong
Yee Van Fan
Kok Sin Woon
Forecasting Municipal Solid Waste Removal Volume Based on Socioeconomic Indicators for Carbon Reduction Strategy in Beijing’s Waste Management 
Chemical Engineering Transactions
title Forecasting Municipal Solid Waste Removal Volume Based on Socioeconomic Indicators for Carbon Reduction Strategy in Beijing’s Waste Management 
title_full Forecasting Municipal Solid Waste Removal Volume Based on Socioeconomic Indicators for Carbon Reduction Strategy in Beijing’s Waste Management 
title_fullStr Forecasting Municipal Solid Waste Removal Volume Based on Socioeconomic Indicators for Carbon Reduction Strategy in Beijing’s Waste Management 
title_full_unstemmed Forecasting Municipal Solid Waste Removal Volume Based on Socioeconomic Indicators for Carbon Reduction Strategy in Beijing’s Waste Management 
title_short Forecasting Municipal Solid Waste Removal Volume Based on Socioeconomic Indicators for Carbon Reduction Strategy in Beijing’s Waste Management 
title_sort forecasting municipal solid waste removal volume based on socioeconomic indicators for carbon reduction strategy in beijing s waste management
url https://www.cetjournal.it/index.php/cet/article/view/14981
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