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Formation Mechanism of Heavy PM2.5 Pollution in Harbin in January 2020
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摘要: 分析2020年1月哈尔滨重污染事件期间PM2.5的化学组成和影响因素, 采用后向轨迹聚类和权重潜在源贡献因子法定量评估区域传输对PM2.5的贡献, 讨论该重污染事件的形成机制。结果表明: PM2.5重污染事件主要来源于一次排放, 其中生物质燃烧的贡献显著, 而极低气温(-18.0 ℃)和高相对湿度(80.0%)条件可显著促进二次气溶胶的生成。基于气团后向轨迹以及权重潜在源贡献因子研究发现, 绥化、大庆、长春和松原等周边城市的区域传输对哈尔滨空气质量的影响也不可忽视。Abstract: In the context of China's commitment to improve air quality enhancement, cities within severe cold climate zones, exemplified by Harbin continue to confront the exigent issue of fine particulate matter (PM2.5) pollution, notably during winter. Despite nationwide initiatives aimed at mitigating air pollution, Harbin's unique geographical and climatic conditions, combined with its predominant economic activities, have led to consistently high levels of PM2.5 during winter. An episode of severe PM2.5 pollution is observed in January 2020, with the monthly average mass concentration of PM2.5 peaking at 155.0 μg·m-3, significantly surpassing national standards. To explore the mechanism of this severe PM2.5 pollution episode, an integrated analysis of chemical compositions and influencing factors is conducted during this period. In the meantime, methods of backward trajectory clustering and the weighted potential source contribution function (WPSCF) are employed to investigate source areas and transport pathways of air pollutants. Results indicate that the severe PM2.5 pollution in Harbin mainly originates from primary emissions, with biomass burning contributing significantly. During the observation period, the concentration of levoglucosan in PM2.5, a common tracer of biomass burning, reaches as high as 1.1 μg·m-3, which is 3.7 to 5.5 times higher than that in other regions experiencing severe biomass burning pollution during winter. Furthermore, research findings indicate that meteorological conditions play a significant role in exacerbating PM2.5 pollution in Harbin. High relative humidity (averaging at 80.0%) combined with extremely low temperatures (averaging at -18.0 ℃) provided favorable conditions for secondary aerosol formation. Under such low-temperature and high-humidity conditions, the average sulfur oxidation rate reaches as high as 25.6%, and the nitrogen oxidation rate reaches 10.8%. It significantly increases the contribution of secondary aerosols to PM2.5 in Harbin. Additionally, this study also reveals the impact of regional transportation on the air quality of Harbin. It indicates that the air quality of Harbin is influenced not only by local emissions but also by the transportation of pollutants from neighboring cities such as Suihua, Daqing, Changchun, and Songyuan. The inter-city transfer of pollution highlights the close connection of air pollution issues within the region. Through the comprehensive analysis of causes of a severe PM2.5 pollution event in Harbin during winter from multiple perspectives, a scientific basis is provided for understanding causes for air pollution in similar cold climate.
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Key words:
- cold climate;
- biomass burning;
- humidity;
- PM2.5;
- regional transmission
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图 1 2020年1月哈尔滨重构的PM2.5质量浓度和气象因素逐日变化
Fig. 1 Daily variations of reconstructed PM2.5 concentration and meteorological factors of Harbin in Jan 2020
图 2 2020年1月哈尔滨二次无机离子在重构的PM2.5质量浓度中的占比
Fig. 2 Proportions of secondary inorganic ions in reconstructed PM2.5 concentrations of Harbin in Jan 2020
图 3 2020年1月哈尔滨SOR和NOR的逐日变化
(1月21日数据缺失)
Fig. 3 Daily variation of SOR and NOR of Harbin in Jan 2020
(data missing on 21 Jan)
图 4 2020年1月哈尔滨PM2.5中OC、EC质量浓度及其比值逐日变化
Fig. 4 Daily variations of OC, EC concentrations with their ratio in PM2.5 of Harbin in Jan 2020
图 5 2020年1月哈尔滨LG质量浓度与重构的PM2.5质量浓度(a)和OC质量浓度(b)的相关性
Fig. 5 Relationship of LG concentration to concentrations of reconstructed PM2.5(a) and OC(b) of Harbin in Jan 2020
图 6 2020年1月哈尔滨气团后向轨迹聚类图
(742条起始高度为100 m的24 h后向气团轨迹)
Fig. 6 Backward airmass trajectory clusters of Harbin in Jan 2020
(clustered from 742 paths of 24 h backward trajectories with height of 100 m)
图 7 2020年1月哈尔滨PM2.5及其主要化学成分的潜在源区
Fig. 7 Potential source areas of PM2.5 with its main chemical components of Harbin in Jan 2020
表 1 2020年1月影响哈尔滨的5类气团轨迹
Table 1 Five types of airmass trajectories affecting Harbin in Jan 2020
聚类 轨迹数量 轨迹数量占比/% 平均质量浓度/(μg·m-3) 1 121 17.0 211.3 2 175 24.6 190.8 3 292 41.1 157.8 4 103 14.5 99.0 5 20 2.8 16.5 
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