Update of SO2 emission inventory in the Megacity of Chongqing, China by inverse modeling

Chongqing, a metropolitan with over 32 million residents in southwest China, has suffered from SO2 pollution since 1980s. The emission inventory is an important tool to evaluate the SO2 pollution and to design the effective emission reduction policies. The present work developed a scheme to update the obsolescent SO2 emission inventory in Chongqing obtained from Multi-resolution Emission Inventory for China in 2008 (MEIC2008). The updated emission inventory was estimated by integrating the a priori knowledge of the baseline emissions and the current observations based on Bayesian inference, in which the source-receptor sensitivities were calculated by the Decoupled Direct Method in Three Dimensions in the Community Multiscale Air Quality Modeling System (CMAQ DDM-3D). An analytical solution of the Bayesian theorem was derived based on the linear response assumption and applied to estimate the actual SO2 emissions. The updated emission inventory was comparable with the most recent MEIC emission inventory in 2016 and 2017, and was in line with the decline trend of SO2 emissions in Chongqing in the last decade. The adjustment of the emissions improved the accuracy in predicting SO2 concentrations with the developed method.

Automated summary

This study developed a method to update the SO2 emission inventory in Chongqing, which is useful for evaluating the SO2 pollution and designing effective emission reduction policies. The updated emission inventory was estimated by integrating the a priori knowledge of the baseline emissions and the current observations using Bayesian inference. The adjustment of the emissions improved the accuracy in predicting SO2 concentrations with the developed method.