An integrated chemical mass balance and source emission inventory model for the source apportionment of PM2.5 in typical coastal areas
Sujing Li , Nana Cheng , Cheng Zhang , Deji Jing , Wei Li , Tianjiao Guo , Qiaoli Wang
DOI:10.1016/j.jes.2020.01.018
Received November 08, 2019,Revised , Accepted January 19, 2020, Available online February 05, 2020
Volume 32,2020,Pages 118-128
The source apportionment of PM2.5 is essential for pollution prevention. In view of the weaknesses of individual models, we proposed an integrated chemical mass balance-source emission inventory (CMB-SEI) model to acquire more accurate results. First, the SEI of secondary component precursors (SO2, NOx, NH3, and VOCs) was compiled to acquire the emission ratios of these sources for the precursors. Then, a regular CMB simulation was executed to obtain the contributions of primary particle sources and secondary components (SO42−, NO3-, NH4+, and SOC). Afterwards, the contributions of secondary components were apportioned into primary sources according to the source emission ratios. The final source apportionment results combined the contributions of primary sources by CMB and SEI. This integrated approach was carried out via a case study of three coastal cities (Zhoushan, Taizhou, and Wenzhou; abbreviated WZ, TZ, and ZS) in Zhejiang Province, China. The regular CMB simulation results showed that PM2.5 pollution was mainly affected by secondary components and mobile sources. The SEI results indicated that electricity, industrial production and mobile sources were the largest contributors to the emission of PM2.5 gaseous precursors. The simulation results of the CMB-SEI model showed that PM2.5 pollution in the coastal areas of Zhejiang Province presented complex pollution characteristics dominated by mobile sources, electricity production sources and industrial production sources. Compared to the results of the CMB and SEI models alone, the CMB-SEI model completely apportioned PM2.5 to primary sources and simultaneously made the results more accurate and reliable in accordance with local industrial characteristics.
