资源环境科技发展态势分析平台

Aerosol composition and sources have been extensively studied in developed regions in China. However, aerosol chemistry in coastal regions of eastern China with high industrial emissions remains poorly characterized. Here we present a comprehensive characterization of aerosol composition and sources near two large steel plants in a coastal city in Shandong in fall and spring using a PM2.5 time-of-flight aerosol chemical speciation monitor. The average (+/- 1 sigma) mass concentration of PM2.5 in spring 2019 (54 +/- 44 mu g m(-3)) was approximately twice that (26 +/- 23 mu g m(-3)) in fall 2018. Aerosol composition was substantially different between the two seasons. While organics accounted for similar to 30% of the total PM2.5 mass in both seasons, sulfate showed a considerable decrease from 28% in September to 16% in March, which was associated with a large increase in nitrate contribution from 17% to 32 %. Positive matrix factorization analysis showed that secondary organic aerosol (SOA) dominated the total OA in both seasons, accounting on average for 92% and 86 %, respectively, while the contribution of traffic-related hydrocarbon-like OA was comparable (8 %-9 %). During this study, we observed significant impacts of steel plant emissions on aerosol chemistry nearby. The results showed that aerosol particles emitted from the steel plants were overwhelmingly dominated by ammonium sulfate and/or ammonium bisulfate with the peak concentration reaching as high as 224 mu g m(-3). Further analysis showed similar mass ratios for NOx/CO (0.014) and NOx/SO2 (1.24) from the two different steel plants, which were largely different from those during periods in the absence of industrial plumes. Bivariate polar plot analysis also supported the dominant source region of ammonium sulfate, CO, and SO2 from the southwest steel plants. Our results might have significant implications for better quantification of industrial emissions using ammonium sulfate and the ratios of gaseous species as tracers in industrial regions and nearby in the future.