Quantification and forecast of GHG emissions from municipal solid wastes by multi-expression programming method

Copyright © 2024 Elsevier Ltd. All rights reserved.

Bibliographische Detailangaben
Veröffentlicht in:Waste management (New York, N.Y.). - 1999. - 187(2024) vom: 01. Aug., Seite 225-234
1. Verfasser: Luo, Yuan-Yuan (VerfasserIn)
Weitere Verfasser: Yang, Yi-Xin, Zhou, Sheng, Meng, Long-Long, Bate, Bate
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:Waste management (New York, N.Y.)
Schlagworte:Journal Article Greenhouse Gases Solid Waste Air Pollutants
LEADER 01000caa a22002652 4500
001 NLM375547088
003 DE-627
005 20240811232255.0
007 cr uuu---uuuuu
008 240729s2024 xx |||||o 00| ||eng c
024 7 |a 10.1016/j.wasman.2024.07.027  |2 doi 
028 5 2 |a pubmed24n1498.xml 
035 |a (DE-627)NLM375547088 
035 |a (NLM)39067199 
035 |a (PII)S0956-053X(24)00417-3 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Luo, Yuan-Yuan  |e verfasserin  |4 aut 
245 1 0 |a Quantification and forecast of GHG emissions from municipal solid wastes by multi-expression programming method 
264 1 |c 2024 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 10.08.2024 
500 |a Date Revised 10.08.2024 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a Copyright © 2024 Elsevier Ltd. All rights reserved. 
520 |a The municipal solid waste (MSW) management is significantly contributing to global greenhouse gas (GHG) emissions. Analyzing the emission pattern of GHGs from MSW is essential for formulating appropriate carbon mitigation policies. Based on IPCC Models, GHG emissions from MSW were calculated in Chinese provinces from 2004 to 2021 by landfilling and incineration operations, separately. Landfilling and incineration generated approximately 1271 MtCO2-eq and 198 MtCO2-eq from 2004 to 2021, respectively. GHG emissions from landfilling increased from 2004 to 2020 and declined in 2021, while GHG emissions from incineration demonstrated an increasing trend with three distinct growth stages. A panel regression model was then employed to identify the key factors influencing GHG emissions. GDP and population are positively related to GHG emissions from landfills, while PCCE is negatively related to GHG emissions from landfills. GDP and PCCE have a positive impact on GHG emissions from incineration, while population showed no significant impact. Multi-expression programming was used to develop an explicit model, forecasting GHG emissions from MSW by 2030. From 2022 to 2024, GHG emissions from landfills will quickly decrease, while GHG emissions from incineration will rapidly increase. Subsequently, the GHG emission rate of incineration will slow down, and GHGs from landfilling will slowly decrease due to no MSW for landfill disposal. The methods and results provide insightful information for policy-makers and waste management sector 
650 4 |a Journal Article 
650 7 |a Greenhouse Gases  |2 NLM 
650 7 |a Solid Waste  |2 NLM 
650 7 |a Air Pollutants  |2 NLM 
700 1 |a Yang, Yi-Xin  |e verfasserin  |4 aut 
700 1 |a Zhou, Sheng  |e verfasserin  |4 aut 
700 1 |a Meng, Long-Long  |e verfasserin  |4 aut 
700 1 |a Bate, Bate  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Waste management (New York, N.Y.)  |d 1999  |g 187(2024) vom: 01. Aug., Seite 225-234  |w (DE-627)NLM098197061  |x 1879-2456  |7 nnns 
773 1 8 |g volume:187  |g year:2024  |g day:01  |g month:08  |g pages:225-234 
856 4 0 |u http://dx.doi.org/10.1016/j.wasman.2024.07.027  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 187  |j 2024  |b 01  |c 08  |h 225-234