Department of Geography, Key Laboratory of Geo-information of the Ministry of Education, East China Normal University, Shanghai 200062, China; Anhui Key Laboratory of Natural Disasters Process and Prevention, College of Territorial Resource and Tourism, Anhui Normal University, Wuhu 241003, China.
Department of Geography, Key Laboratory of Geo-information of the Ministry of Education, East China Normal University, Shanghai 200062, China.
Environ Pollut. 2016 Nov;218:118-128. doi: 10.1016/j.envpol.2016.08.037. Epub 2016 Aug 20.
Polycyclic aromatic hydrocarbons (PAHs) were studied in 230 daily fine particulate matter (PM2.5) samples collected in four seasons at urban and suburban sites of Shanghai, China. This study focused on the emission sources of PAHs and its dynamic results under different weather conditions and pollution levels and also emphasized on the spatial sources of PM2.5 and PAHs at a regional level. Annual concentrations of PM2.5 and 16 EPA priority PAHs were 53 μg/m and 6.9 ng/m, respectively, with highest levels in winter. Positive matrix factorization (PMF) modeling identified four sources of PAHs: coal combustion, traffic, volatilization and biomass combustion, and coking, with contributions of 34.9%, 27.5%, 21.1% and 16.5%, respectively. The contribution of traffic, a local-indicative source, increased from 17.4% to 28.7% when wind speed changed from >2m/s to <2m/s, and increased from 18.3% to 31.3% when daily PAH concentrations changed from below to above the annual mean values. This indicated that local sources may have larger contributions under stagnant weather when poorer dispersion conditions and lower wind speed led to the accumulation of local-emitted pollutants. The trajectory clustering and potential source contribution function (PSCF) and concentration weighted trajectory (CWT) models showed clearly that air parcels moved from west had highest concentrations of PM2.5, total PAHs and high molecular weight (HMW) PAHs. While small differences were found among all five clusters in low molecular weight (LMW) PAHs. Sector analyses determined that regional transport source contributed 39.8% to annual PM2.5 and 52.5% to PAHs, mainly from western regions and varying with seasons. This work may make contribution to a better understanding and control of the increasingly severe air pollution in China as well as other developing Asian countries.
多环芳烃（PAHs）在四个季节的上海城市和郊区采集的 230 个每日细颗粒物（PM2.5）样本中进行了研究。本研究重点关注 PAHs 的排放源及其在不同天气条件和污染水平下的动态结果，同时强调了区域水平上 PM2.5 和 PAHs 的空间来源。PM2.5 和 16 种 EPA 优先 PAHs 的年浓度分别为 53μg/m 和 6.9ng/m，冬季浓度最高。正矩阵因子化（PMF）模型识别出 PAHs 的四个来源：煤炭燃烧、交通、挥发和生物质燃烧以及炼焦，其贡献率分别为 34.9%、27.5%、21.1%和 16.5%。当风速从>2m/s 变为<2m/s 时，交通源（局部指示源）的贡献从 17.4%增加到 28.7%，当每日 PAH 浓度从低于年平均值变为高于年平均值时，其贡献从 18.3%增加到 31.3%。这表明，在停滞天气下，当地源的贡献可能更大，因为较差的扩散条件和较低的风速导致当地排放污染物的积累。轨迹聚类和潜在源贡献函数（PSCF）和浓度加权轨迹（CWT）模型清楚地表明，空气团从西部移动时，PM2.5、总 PAHs 和高分子量（HMW）PAHs 的浓度最高。而在低分子量（LMW）PAHs 中，所有五个聚类之间的差异较小。扇形分析确定，区域传输源对 PM2.5 的年贡献率为 39.8%，对 PAHs 的贡献率为 52.5%，主要来自西部地区，且随季节变化。这项工作可能有助于更好地理解和控制中国乃至其他亚洲发展中国家日益严重的空气污染。
