大气与环境光学学报 ›› 2026, Vol. 21 ›› Issue (3): 455-469.doi: 10.3969/j.issn.1673-6141.2026.03.008

• 环境光学监测技术 • 上一篇    下一篇

泰州市2021年四季大气细颗粒物污染特征及来源解析(封面文章)

陈诚 1,2, 杨栋森 2, 任华荣 2, 高洪亮 2, 吴莹 3*, 孙鹏 1, 郑军 4   

  1. 1 江苏省环境监测中心, 江苏 南京 210036; 2 江苏省苏力环境科技有限责任公司, 江苏 南京 210019; 3 江苏省泰州环境监测中心, 江苏 泰州 225300; 4 南京信息工程大学环境科学与工程学院, 江苏 南京 210044
  • 收稿日期:2023-08-11 修回日期:2023-10-16 接受日期:2023-11-06 出版日期:2026-05-28 发布日期:2026-05-28
  • 通讯作者: E-mail: designwuying@163.com E-mail:designwuying@163.com
  • 作者简介:陈诚 (1980- ), 江苏南京人, 硕士, 高级工程师, 主要从事大气环境监测方面的研究。E-mail: cc@jshb.gov.cn
  • 基金资助:
    科技部国家重点研发计划 (2022YFC3700202), 青年科学基金项目 (42105096)

The pollution characteristics and source apportionment of atmospheric fine particles in Taizhou in four seasons of 2021(Cover Paper)

CHEN Cheng1,2, YANG Dongsen2, REN Huarong2, GAO Hongliang2, WU Ying3*, SUN Peng1, ZHENG Jun4   

  1. 1 Jiangsu Environmental Monitoring Center, Nanjing 210036, China; 2 Jiangsu Suli Environmental Technology Co., Ltd., Nanjing 210019, China; 3 Taizhou Environmental Monitoring Center of Jiangsu Province, Taizhou 225300, China; 4 School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Received:2023-08-11 Revised:2023-10-16 Accepted:2023-11-06 Online:2026-05-28 Published:2026-05-28
  • Contact: Wu -Ying E-mail:designwuying@163.com

摘要: 为探究泰州市不同季节细颗粒物 (PM2.5) 的化学组分变化规律及其污染来源特征, 本研究自2021 年1 月起, 针对泰州市大气细颗粒物进行了为期15 个月的膜采样, 得到该市研究期间环境大气中PM2.5的水溶性离子、有机碳 (OC) 及元素碳 (EC)、金属元素等化学组分的浓度, 并通过正交矩阵因子 (PMF) 模型对其来源进行解析。观测结果显 示, 在研究期间该市的PM2.5中有机物与硝酸盐占主导地位, 且PM2.5整体浓度呈现出春夏较低、秋冬较高的季节性特 征。其中, 夏季硝酸盐占比显著低于冬季, 主要原因是硝酸盐对温度较为敏感, 在夏季高温条件下易分解并挥发, 而 冬季低温条件则更有利于硝酸盐的冷凝增长, 同时还会促进气态氮氧化物通过非均相化学反应生成硝酸盐。此外, 冬季一次污染源排放强度的增加也导致以硝酸盐、硫酸盐、铵盐为主的无机盐浓度显著升高。源解析结果表明, 泰州 市PM2.5主要来源于5 个方面: 二次源、工业源、燃烧源、扬尘源和交通源。其中, 二次源始终占主导地位, 燃烧源、工业 源和扬尘源为第二梯队的主要污染源,而交通源的贡献相对较低。进一步分析发现, 冬季清洁天与污染天的细颗粒物 来源贡献占比存在显著差异。清洁天中二次源占比为34.2%, 而污染天中二次源占比升高至48.7%。相比之下, 一次 源中仅交通源及其他未知来源在污染天的占比略有提升。这表明二次污染是导致泰州市大气污染的主要因素, 因此, 采取针对二次污染源气态前体物的减排措施是控制该市大气细颗粒物污染的关键。

关键词: PM2.5, 来源解析, 二次污染源

Abstract: Objective Over the past decade, the concentrations of particulate matter (PM2.5, PM10) and gaseous primary pollutants (SO2, NO2, etc.) in China have decreased significantly. However, secondary pollution represented by ozone has become increasingly prominent, and secondary aerosols generated through processes such as photo-oxidation have become a major source of urban atmospheric particulate matter. Taizhou, located in central Jiangsu, is a typical industrialized city. To achieve sustained reduction in PM2.5 concentrations, it is urgent to formulate locally tailored air-pollution response plans, based on scientific evidence regarding local PM2.5 composition and pollution sources. Nevertheless, systematic research on PM2.5 characteristics and sources in Taizhou remains limited. Therefore, investigating the pollution characteristics and sources of PM2.5 in Taizhou has important demonstration and reference significance for precise air-pollution control in the Yangtze River Delta region. For this purpose, this study conducted a full-year collection of PM2.5 filter samples in Taizhou during 2021, analyzed their chemical composition and seasonal variation patterns, and quantified the contribution of different pollution sources and their seasonal characteristics. Methods The sampling site was located at the Taizhou Municipal Bureau of Justice, approximately 200 m from Taizhou Lianhua National Automatic Monitoring Station. Meteorological parameters (temperature, relative humidity, wind direction, and wind speed), PM2.5 and PM10 concentrations, and conventional gaseous pollutants (O3, NO2, SO2, and CO) concentrations from Taizhou Lianhua National Automatic Monitoring Station were used for data analysis. The sampling site is surrounded by residential areas and is representative of a typical urban setting. Moreover, there are no large industrial sources within a 2 km radius of the site. A Thermo Fisher Scientific 2000i atmospheric particulate matter sampler was used to collect PM2.5 samples. The sampling period was from January 1, 2021, to March 31, 2022. Daily sampling duration was 23 hours, and samples were collected every 3 days, so in total, 152 filter samples were manually collected. After extraction from the filters, the water-soluble ionic components in PM2.5 were analyzed using a Metrohm 940 (Switzerland), including five cations (NH4 +, Na+, K+, Ca2+, and Mg2+) and four anions (NO3−, SO4 2−, F−, and Cl−). Organic carbon (OC) and elemental carbon (EC) in PM2.5 were analyzed using a Desert Research Institute (DRI) 2015 instrument (USA) via the thermal oxidation method. Trace elements in PM2.5 were analyzed using a BRUKER S8 Tiger (Germany), yielding 24 elements including Na, K, Mg, Ca, Ba, Cd, Sn, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Pb, Al, S, Cl, Sb, and Si. Source apportionment of PM2.5 filter samples was conducted using Positive Matrix Factorization (PMF) 5.0 of U.S. Environmental Protection Agency (USEPA). In the PMF calculations, the number of factors k was tested sequentially from 3 to 10, and five factors were ultimately selected. Results and Discussion (1) PM2.5 pollution in Taizhou exhibits distinct seasonal characteristics that the concentrations of PM2.5 are higher in spring and winter, with water-soluble inorganic salts and organic matter as the dominant chemical components. Seasonal comparisons show that the proportion of nitrate increases in winter and decreases in summer, whereas sulfate shows the opposite trend. On polluted days (daily PM2.5 concentration > 35 μg/m³), nitrate increases significantly and becomes the primary component. (2) PMF source apportionment identifies five major sources of PM2.5, including secondary sources, industrial sources, combustion sources, dust sources, and traffic sources. Secondary sources are dominated by secondary inorganic salts. Industrial sources are characterized by metals such as Ba, Cd, and V. Combustion sources are traced according to species including K+ and Cl− , with primary contributions from fireworks and biomass burning. Dust sources are mainly composed of crustal elements (e.g., Ca2+ and Al). Traffic sources make a prominent contribution to EC. Pollution sources such as regional transport, local vegetation emissions, and residential cooking emissions are categorized as "other sources". (3) Seasonal source apportionment results indicate that secondary sources dominate throughout the year, with the highest contribution in winter (44.0%) and a decrease in summer (36.7%). Industrial sources and dust sources show similar seasonal trends, with their proportions increasing in summer. Combustion sources are more significant in autumn and winter, associated with straw burning and heating activities. Due to the promotion of new energy vehicles and pollution prevention and control measures in recent years, contributions from traffic sources and other sources remain below 10%. (4) Winter pollution analysis shows that the contribution of secondary sources on polluted days is significantly higher than that on clean days (48.7% vs. 34.2%), indicating that secondary transformation is the key process leading to severe pollution. Besides secondary sources, combustion sources, dust sources, and industrial sources each contribute over 15% on clean days. In contrast, on polluted days, contributions from dust sources and industrial sources decrease markedly, both falling below 10%. (5) Compared with the previous winter, the contributions of combustion sources and dust sources increased in the winter of 2022, whereas those of industrial sources and secondary sources decreased slightly. Conclusions (1) Increases in gaseous precursors such as NO2 and SO2 provide necessary conditions for generating more secondary particulate matter. (2) The main components of PM2.5 in Taizhou are organic matter, NO3− , SO4 2− , NH4 + , and mineral components. Organic matter and sulfate exhibit the highest proportions in summer and the lowest in winter, while nitrate shows the opposite pattern. In summer, intense sunlight promotes O3 formation via NO2 photolysis, increasing atmospheric oxidation capacity and favoring the formation of secondary aerosols such as secondary organic aerosols and sulfates. Therefore, coordinated control of PM2.5 and O3 pollution is necessary to address air pollution in Taizhou. (3) PMF analysis identified six pollution-source categories. During the sampling period, the average contribution rates of secondary sources, industrial sources, combustion sources, dust sources, traffic sources, and other sources were 40.4%, 13.5%, 15.3%, 14.9%, 7.9%, and 7.8%, respectively. Secondary sources always dominated, while traffic sources and other sources contributed the least. In addition, combustion and dust contributions in Taizhou were relatively significant, whereas the proportion of industrial sources in the urban area was relatively low.

Key words: fine particulate matters, source apportionment, secondary sources

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