2020-07-03 | Jun Liu
In July 2020, the MEIC research group published one research paper in the well-known international journal Atmospheric Chemistry and Physics, which for the first time utilized the bottom-up long-term sectoral emission inventory developed in the MEIC model to evaluate the decadal transition of source contributions driven by economic development and policy regulations. We estimated the contribution of five anthropogenic emitting sectors to ambient PM2.5 exposure and related premature mortality over China during 1990-2015, by using an integrated model framework of bottom-up emission inventory (MEIC), regional air quality model (WRF-CMAQ), and the Global Exposure Mortality Model (GEMM).
In the past decades, China has experienced unprecedented social and economic development, accompanied by the acceleration of urbanization and energy consumption, which resulted in resulting in serious air pollution and heavy burden of disease. From 1990 to 2005, the national anthropogenic PM2.5-related premature mortality rose from 1.26 million to 2.18 million; then, it decreased to 2.10 million in 2015. In 1990, the residential sector was the leading source of the PM2.5-related premature mortality (44%) in China, followed by industry (29%), power (13%), agriculture (9%) and transportation (5%). In 2015, the industrial sector became the largest contributor of PM2.5-related premature mortality (35%), followed by residential (25%), agriculture (23%), transportation (10%) and power (6%).
The study revealed that active control measures have successfully reduced pollution from the power sector, while the contribution from the industrial and transportation sectors continuously increased due to more prominent growth of activity rates. Transition in fuel consumption dominated the decrease of contribution from the residential sector. In the meanwhile, the contribution from the agriculture sector continuously increased due to persistent NH3 emissions and enhanced formation of secondary inorganic aerosols under an NH3 rich environment. This study is helpful for the identification of the key air pollution sources, which is of great importance for future targeted decision-making on air pollution prevention.