Abstract

Anthropogenic emissions in China have been controlled for years to improve ambient air quality. However, severe haze events caused by atmospheric aerosols with aerodynamic diameter less than or equal to 2.5 μm (PM2.5) have continued to occur, especially in the Beijing–Tianjin–Hebei (BTH) region. The Chinese government has set an ambitious goal to reduce urban PM2.5 concentrations by 25% in BTH by 2017 relative to the 2012 levels. Source apportionment (SA) is necessary to the development of the effective emission control strategies. In this work, the Comprehensive Air Quality Model with extensions (CAMx) with the Particulate Source Apportionment Technology (PSAT) is applied to the China domain for the years 2006 and 2013. Ambient surface concentrations of PM2.5 and its components are generally well reproduced. To quantify the contributions of each emission category or region to PM2.5 in BTH, the total emissions are divided into 7 emission categories and 11 source regions. The source contributions determined in this work are generally consistent with results from previous work. In 2013, the industrial (44%) and residential (27%) sectors are the dominant contributors to urban PM2.5 in BTH. The residential sector is the largest contributor in winter; the industry sector dominates in other seasons. A slight increasing trend (+3% for industry and +6% for residential) is found in 2013 relative to 2006, necessitating more attention to these two sectors. Local emissions make the largest contribution (40%–60%) for all receptors. Change of source contribution of PM2.5 in Beijing and northern Hebei are dominate by change of local emission. However, for Tianjin, and central and southern Hebei, change of meteorology condition are as important as change of emission, because regional inflow in these areas is more important than in Beijing and northern Hebei and can increase under unfavorable weather conditions, indicating a strong need for regional joint emission control efforts. The results in this study enhance the quantitative understanding of the source–receptor relationships and provide an important basis for policymaking to advance the control of PM2.5 pollution in China.

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