Spatio-temporal distribution characteristics and reduction potentials of China's MSW-related GHG emissions
Landfilling,incineration,and other waste disposal methods,are major contributors to greenhouse gas emissions,particularly methane.Using the IPCC method,this study examined MSW treatment structures and GHG emissions in 297 prefecture-level cities in China from 2006 to 2021.Additionally,the study predicted MSW-related GHG emissions for 2030 and 2060 by employing a grey fore-casting model.The findings revealed that:① Most cities were transitioning from landfilling to incineration as the predominant waste dis-posal method.② Total MSW-related carbon emissions in China showed rapid growth,stabilizing after reaching 79.41 million tons in 2019,with mega-cities such as Beijing,Shanghai,and Shenzhen exhibiting the highest emissions.Meanwhile,net carbon emissions from MSW treatment experienced an initial increase followed by a decline,with higher-emission regions shifting towards third-and fourth-tier cities.Carbon emissions from MSW treatment would increase with the expansion of urban population and the improvement of economic development level.③ The forecast results indicated that China's total MSW-related GHG emissions would range from 65.75 to 99.42 million tons by 2030.Among 31 cities,only Lanzhou was projected to achieve peak carbon emissions in waste treatment.Waste classification would significantly impact achieving carbon neutrality,and most cities could attain it with effective waste sorting measures.Finally,this study proposes a'three-step'hierarchical strategy for MSW management.For cities still relying on landfilling,efforts should be made to transition from landfilling to incineration.For cities that have achieved zero landfilling,waste classification is necessary.For cities that have already implemented waste classification policies,the implementation of source reduction measures is es-sential.
'dual carbon' goalsmunicipal solid wastespatio-temporal distribution characteristicscarbon emission reduction poten-tialsgreen and low-carbon development
万方数据
维普
