基于超级站数据的南通区域大气PM2.5化学组分来源解析

doi:10.19741/j.issn.1673-4831.2021.0682

摘要/Abstract

摘要： 基于超级站高时间分辨率观测数据,多尺度对南通市2020年的PM_2.5进行来源解析,分析了PM_2.5化学组成特征、相关性、行业贡献和分季节PM_2.5内外源贡献,同时采用WRF-CMAQ模型构建气象场和污染物场,模拟研究了南通市2020年1、4、7、10月的环境空气质量状况。结果显示,二次无机盐(SNA)是南通市PM_2.5的最主要组成成分,且其浓度季节差异明显。硝酸盐浓度大幅升高是南通市PM_2.5污染加剧的重要原因。冬季PM_2.5污染水平加剧受机动车尾气排放的影响较大。从2020年整体来看,不同季节由于气象条件、污染发生类型的差异,各污染来源所占比例也不相同。南通市PM_2.5本地排放贡献约为61%,其次为北方长距离传输,约为17%,长三角及苏南地区输送比例为18%。空气质量模型校验结果表明,所有污染物的模拟均能较好地代表污染物的变化趋势,在量级上虽与观测值有一定差距,但处在合理接受范围内。总体而言,模拟结果可信且可在后续研究中使用。

关键词: 超级站, 南通, PM_2.5, 来源解析, WRF-CMAQ模型

Abstract: For exploring the source of PM_2.5 of Nantong in 2020, the characteristics, correlation and industrial contribution of chemical components of PM_2.5, and the internal and external seasonal contribution of PM_2.5 were analyzed based on the high time resolution observation data of super stations. At the same time, WRF-CMAQ model was used to construct meteorological field and pollutant field for the simulation of the ambient air quality of Nantong in January, April, July and October of 2020. The results show that the secondary inorganic ion is the main component of PM_2.5 in Nantong City, and their concentrations have obvious seasonal difference. The sharp increase of nitrate concentration is an important reason for the aggravation of PM_2.5 pollution in Nantong city. The aggravation of PM_2.5 pollution level in winter was affected mainly by vehicle exhaust emission. From the perspective of 2020 as a whole, according to different meteorological conditions and pollution types in different seasons, the proportions of the pollution sources were also different. The local emission contribution of PM_2.5 in Nantong is about 61%, followed by long-distance transmission from the north (17%), and from the Yangtze River Delta and southern Jiangsu (18%). The verification on the simulation of all pollutants in the air quality model can well represent the change trend of pollutants. Although, there is a certain gap between the simulated value and the observed value, it is still within a reasonable and acceptable range. The results worked out by the model are reliable and can be used in subsequent researches.

Key words: super station, Nantong, PM_2.5, source resolution, WRF-CMAQ model

中图分类号:

X823

张翔, 曹志刚, 崔萍. 基于超级站数据的南通区域大气PM_2.5化学组分来源解析[J]. 生态与农村环境学报, 2023, 39(2): 184-189.

ZHANG Xiang, CAO Zhi-gang, CUI Ping. Source Analysis of Chemical Components of Atmospheric PM_2.5 in Nantong Region Based on Super Station Data[J]. Journal of Ecology and Rural Environment, 2023, 39(2): 184-189.

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