Shu Lei, Wang Tijian, Liu Jane, Chen Zhixiong, Wu Hao, Qu Yawei, Li Mengmeng, Xie Min
Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, China.
School of Atmospheric Sciences, Nanjing University, Nanjing, China.
Sci Total Environ. 2024 Feb 20;912:169546. doi: 10.1016/j.scitotenv.2023.169546. Epub 2023 Dec 21.
Understanding the causes and sources responsible for severe fine particulate matter (PM) pollution episodes that occur under conducive synoptic weather patterns (SWPs) is essential for regional air quality management. The Yangtze River Delta (YRD) region in eastern China has experienced recurrent severe PM episodes during the winters from 2013 to 2017. In this study, we employed an objective classification approach, the self-organizing map, to investigate the underlying impact of predominant SWPs on PM pollution in the YRD. We further conducted a series of source apportionment simulations using the Particulate Source Apportionment Technology (PSAT) tool integrated within the Comprehensive Air Quality Model with Extensions (CAMx) to quantify the source contributions to PM pollution under different SWPs. Here we identified six predominant SWPs over the YRD that are robustly connected to the evolution of the Siberian High. Considering the regional average PM anomalies, our results show that polluted SWPs favourable for the occurrence of regional PM pollution account for 61-78 %. The most conducive SWP, associated with the highest regional exceedance (46 %) of PM levels, is characterized by noticeable cyclonic anomalies at 850 hPa and stagnant surface weather conditions. Our source apportionment analysis emphasizes the pivotal role of local emissions and intra-regional transport within the YRD in shaping PM pollution in representative cities. Local emissions have the most significant impact on PM levels in Shanghai (32-48 %), while PM pollution in Nanjing, Hangzhou, and Hefei is more influenced by intra-regional transport (33-61 %). Industrial and residential emissions are the dominant sources, contributing 32-41 % and 24-38 % to PM, respectively. Under specific SWPs associated with a stronger influence of inter-regional transport from northern China, there is a synchronously remarkable enhancement in the contribution of residential emissions. Our study pinpoints the opportunities for future air quality planning that would benefit from quantitative source attribution linked to prevailing SWPs.
了解在有利的天气形势（SWPs）下发生的严重细颗粒物（PM）污染事件的成因和来源，对于区域空气质量管控至关重要。中国东部的长江三角洲（YRD）地区在2013年至2017年冬季多次经历严重的PM污染事件。在本研究中，我们采用了一种客观分类方法——自组织映射，来探究主要天气形势对长三角地区PM污染的潜在影响。我们还使用了集成在扩展综合空气质量模型（CAMx）中的颗粒物源解析技术（PSAT）工具进行了一系列源解析模拟，以量化不同天气形势下PM污染的源贡献。在此，我们识别出了长三角地区六种与西伯利亚高压演变密切相关的主要天气形势。考虑到区域平均PM异常情况，我们的结果表明，有利于区域PM污染发生的污染性天气形势占61%-78%。最有利的天气形势与最高的区域PM超标率（46%）相关，其特征是850百帕处有明显的气旋异常和地面天气状况停滞。我们的源解析分析强调了长三角地区本地排放和区域内传输在塑造代表性城市PM污染方面的关键作用。本地排放对上海的PM水平影响最大（32%-48%），而南京、杭州和合肥的PM污染受区域内传输影响更大（33%-61%）。工业和居民排放是主要来源，分别占PM的32%-41%和24%-38%。在与来自中国北方的区域间传输影响更强相关的特定天气形势下，居民排放的贡献同步显著增加。我们的研究指出了未来空气质量规划的机会，这些机会将受益于与当前天气形势相关的定量源归因。
