Research on optimizing air pollutant emission inventory based on electricity consumption data
ZHOU Wei-qing1, LI Peng1, WU Hua-cheng1, HE Xue-juan2, SUN Shi-da2, BO Yu2,3, HE Ke-bin3
1. Jibei Electric Power Research Institute, State Grid Jibei Electric Power Co., Ltd., (North China Electric Power Research Institute Company Limited), Beijing 100045, China; 2. Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Department of Earth System Science, Tsinghua University, Beijing 100084, China; 3. State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
Abstract：In order to improve the spatial and temporal resolution of the air pollutant emission inventory in the industrial sector, the method of optimizing the time and spatial distribution in the industrial sector based on the electricity consumption data was proposed, and taken Tangshan city, Hebei province as an example, the basic emission inventory and the optimized emission inventory were input into the WRF-CMAQ model to verify its optimization effect. The results showed that the WRF-CMAQ model well simulated the temporal variation and spatial distribution of pollutant concentrations in Tangshan in January, April, July and October 2019. Compared with the basic emission inventory, the correlation between the annual average simulation value and the monitoring value of PM2.5 in the optimized emission inventory increased by 3.3%, with the best improvement effect on NO2. The improvement effect was the most obvious in October, with the DR2 of PM2.5, PM10 and CO exceeded 1.4. The change of PM2.5 concentration in the optimized emission inventory had more obvious regional characteristics, with high value areas of difference appeared in some areas, such as Qianxi county and Zunhua city. The optimized emission inventory improved the accuracy of spatial simulation to a certain extent, and can better reflect the changes of pollutant emissions in the industrial sector.
周卫青, 李朋, 吴华成, 何学娟, 孙世达, 薄宇, 贺克斌. 基于电力数据优化大气污染物排放清单[J]. 中国环境科学, 2023, 43(7): 3350-3359.
ZHOU Wei-qing, LI Peng, WU Hua-cheng, HE Xue-juan, SUN Shi-da, BO Yu, HE Ke-bin. Research on optimizing air pollutant emission inventory based on electricity consumption data. CHINA ENVIRONMENTAL SCIENCECE, 2023, 43(7): 3350-3359.
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