| Literature DB >> 28688306 |
Jianlei Lang1, Ying Zhou2, Dongsheng Chen3, Xiaofan Xing2, Lin Wei2, Xiaotong Wang2, Na Zhao2, Yanyun Zhang2, Xiurui Guo2, Lihui Han2, Shuiyuan Cheng2.
Abstract
Many studies have been conducted focusing on the contribution of land emission sources to PM2.5 in China; however, little attention had been paid to other contributions, especially the secondary contributions from shipping emissions to atmospheric PM2.5. In this study, a combined source apportionment approach, including principle component analysis (PCA) and WRF-CMAQ simulation, was applied to identify both primary and secondary contributions from ships to atmospheric PM2.5. An intensive PM2.5 observation was conducted from April 2014 to January 2015 in Qinhuangdao, which was close to the largest energy output port of China. The chemical components analysis results showed that the primary component was the major contributor to PM2.5, with proportions of 48.3%, 48.9%, 55.1% and 55.4% in spring, summer, autumn and winter, respectively. The secondary component contributed higher fractions in summer (48.2%) and winter (36.8%), but had lower percentages in spring (30.1%) and autumn (32.7%). The hybrid source apportionment results indicated that the secondary contribution (SC) of shipping emissions to PM2.5 could not be ignored. The annual average SC was 2.7%, which was comparable to the primary contribution (2.9%). The SC was higher in summer (5.3%), but lower in winter (1.1%). The primary contributions to atmospheric PM2.5 were 3.0%, 2.5%, 3.4% and 2.7% in spring, summer, autumn and winter, respectively. As for the detailed chemical components, the contributions of shipping emissions were 2.3%, 0.5%, 0.1%, 1.0%, 1.7% and 0.1% to elements & sea salt, primary organic aerosol (POA), element carbon (EC), nitrate, sulfate and secondary organic carbon (SOA), respectively. The results of this study will further the understanding of the implications of shipping emissions in PM2.5 pollution.Entities:
Keywords: Fine particle; PCA; Qinhuangdao; Shipping emissions; Source apportionment; WRF-CMAQ
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Year: 2017 PMID: 28688306 DOI: 10.1016/j.envpol.2017.06.087
Source DB: PubMed Journal: Environ Pollut ISSN: 0269-7491 Impact factor: 8.071