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Investigating the Changes in Air Pollutant Emissions over the Beijing-Tianjin-Hebei Region in February from 2014 to 2019 through an Inverse Emission Method
Authors:Xuechun LUO  Xiao TANG  Haoyue WANG  Lei KONG  Huangjian WU  Weiguo WANG  Yating SONG  Hongyan LUO  Yao WANG  Jiang ZHU  Zifa WANG
Affiliation:School of Earth Sciences,Yunnan University,Kunming 650500,China;LAPC& ICCES,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;LAPC& ICCES,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;Center for Excellence in Regional Atmospheric Environment,Institute of Urban Environment,Chinese Academy of Sciences,Xiamen 361021,China;School of Earth Sciences,Yunnan University,Kunming 650500,China;LAPC& ICCES,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;LAPC& ICCES,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;University of Chinese Academy of Sciences,Beijing 100049,China;LAPC& ICCES,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;University of Chinese Academy of Sciences,Beijing 100049,China;Center for Excellence in Regional Atmospheric Environment,Institute of Urban Environment,Chinese Academy of Sciences,Xiamen 361021,China
Abstract:In recent years, China has implemented several measures to improve air quality. The Beijing-Tianjin-Hebei (BTH) region is one area that has suffered from the most serious air pollution in China and has undergone huge changes in air quality in the past few years. How to scientifically assess these change processes remain the key issue in further improving the air quality over this region in the future. To evaluate the changes in major air pollutant emissions over this region, this paper employs ensemble Kalman filtering (EnKF) for integrating the national ground monitoring pollutant observation data and the Nested Air Quality Prediction Modeling System (NAQPMS) simulation data to inversely estimate the emission rates of SO2, NOX, CO, and primary PM2.5 over BTH region in February from 2014 to 2019. The results show that SO2, NOX, CO, and primary PM2.5 emissions in the BTH region decreased in February from 2014 to 2019 by 83%, 37%, 41%, and 42%, while decreases in Beijing during this period were 86%, 67%, 59%, and 65%, respectively. Compared with the prior emission inventory, the inversion emission inventory reduces the uncertainty of multi-pollutant simulation in the BTH region, with simulated root mean square errors of the monthly average concentrations of SO2, NOX, PM2.5, and CO reduced by 41%, 30%, 31%, and 22%, respectively. The average uncertainties of SO2, NOX, PM2.5, and CO inversion emissions in 2014–19 are ±14.03% yr–1, ±28.91% yr–1, ±126.15% yr–1, and ±43.58% yr–1. Compared with the uncertainty of MEIC emission, the uncertainties of all species changed by +2% yr–1, –2% yr–1, –26% yr–1, and –4% yr–1, respectively. The spatial distribution results illustrate that air pollutant emissions are mainly distributed over the eastern and southern BTH regions. The spatial gap between the inversion emissions and MEIC emissions was further closed in 2019 compared to 2014. The results of this paper can provide a new reference for assessing changes in air pollution emissions over the BTH region in recent years and validating a bottom-up emission inventory.
Keywords:emission inversion   emission trend   air pollutants   Beijing-Tianjin-Hebei
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