温室气体
环境科学
环境工程
发射强度
污水处理
流出物
电
生命周期评估
数据包络分析
废物管理
工程类
生产(经济)
生态学
数学
生物
电气工程
数学优化
宏观经济学
激发
经济
作者
Jiarui Xi,Hui Gong,Ru Guo,Ling Chen,Xiaohu Dai
标识
DOI:10.1016/j.jclepro.2023.136829
摘要
The reduction of greenhouse gas (GHG) and achieving carbon neutrality in wastewater treatment plants (WWTPs) has gained significant research attention due to China's dual carbon goals. However, the temporal and spatial characteristics of GHG emissions and the reduction potential regarding GHG emissions from WWTPs in China remain significant uncertainties. This study aims to evaluate GHG emissions characteristics over the years using a set of computational methods, and assess the reduction potential from WWTPs based on operational parameters and economic considerations. This study evaluated GHG emissions of more than 1000 WWTPs in China from 2009 to 2016 using operational data integrated methods (ODIM) and emission factors method to estimate direct N2O, direct CH4 emissions and indirect electricity-induced GHG emissions. GHG emissions were analyzed from temporal, spatial and operational parameters aspects. Besides, data envelopment analysis (DEA) was used to analyze WWTPs' efficiency in 2017. The results show that GHG emissions increased from 8163 Gg in 2009 to 14,008 Gg in 2016, with emission intensity maintained in the range of 0.266 kgCO2-eq/m3 to 0.298 kgCO2-eq/m3. Indirect GHG emissions from electricity consumption were the main source, which accounted for 72%–80% of the total emissions. Remarkable differences in GHG emissions were observed among six different regions and 31 provinces. WWTPs with AAO process, large treatment capacity, high loading, low influent COD concentration and high effluent NH3–N concentration contributed to lower GHG emission intensity. Furthermore, the treatment process was correlated significantly with GHG emission intensity, whereas influent COD concentration had the least influence from regression analysis results. DEA evaluation indicated that the average efficiency score in 2016 was only up to 0.240 with 27 WWTPs reaching a full efficiency score (efficiency score above 1.000). Electricity consumption and ammonia nitrogen reduction were the most prioritized indicators which could be changed by −53.55% and 592.60%, respectively, to achieve a full efficiency score. The study provides a valuable reference for policymakers and stakeholders to reduce GHG emissions and achieve carbon neutrality in WWTPs, thus contributing to the larger goal of reducing GHG and mitigating climate change.
科研通智能强力驱动
Strongly Powered by AbleSci AI