In The Science of the total environment
Municipal solid waste (MSW) without proper managements could be a significant source of greenhouse gas (GHG) emissions. MSW incineration with electricity recovery (MSW-IER) is recognized as a sustainable way to utilize waste, but its effectiveness on reducing GHG emissions at the city scale in China remain unclear due to limited data of MSW compositions. The aim of the study is to investigate reduction potential of GHG from MSW-IER in China. Based on the MSW compositions covering 106 Chinese prefecture-level cities during the period of 1985 to 2016, random forest models were built to predict MSW compositions in Chinese cities. MSW compositions in 297 cities of China from 2002 to 2017 were predicted using the model trained by a combination of socio-economic, climate and spatiotemporal factors. Spatiotemporal and climatic factors (such as economic development level, precipitation) accounted for 6.5 %-20.7 % and 20.1 %-37.6 % to total contributions on MSW composition, respectively. The GHG emissions from MSW-IER in each Chinese city were further calculated based on the predicted MSW compositions. The plastic is the main GHG emission source, accounting for over 91 % of the total emission during 2002-2017. Compared to baseline (landfill) emission, the GHG emission reduction from MSW-IER was 12.5 × 107 kg CO2-eq in 2002 and 415 × 107 kg CO2-eq in 2017, with an average annual growth rate of 26.3 %. The results provide basic data for estimating GHG emission in MSW management in China.
Zhao Qing, Tang Weihao, Han Mengjie, Cui Wenjing, Zhu Lei, Xie Huaijun, Li Wei, Wu Fengchang
2023-Mar-07
Green energy, Greenhouse gas reduction emission, Incineration, Machine-learning, Municipal solid waste
