Abstract:

To analyze temporal and spatial variations and factors influencing secondary components of Ji’nan’s M_2.5, continuous PM_2.5 sampling was conducted in spring (May 16-25, 2019), autumn (October 15-24, 2019) and winter (December 17-January 16, 2020) at four typical sites in Ji’nan. Water-soluble ion, organic carbon (OC), and elemental carbon (EC) content in PM_2.5 were determined. The results showed that the concentration of secondary components was the highest (56.13 μg·m^-3) in logistics and transportation areas. Concentrations of secondary components in iron and steel industrial areas were higher than those in urban areas, but the proportions of secondary components were lower. The cleaning control sites had the lowest concentrations and proportions. SO₄^2- and NO₃^- conversion rates in the four functional areas of Ji’nan were all higher than 0.1, and SO₄^2- conversion rates were significantly higher than NO₃^- conversion rates in urban areas, iron and steel industrial areas, and logistics and transportation areas, but not at the cleaning control sites. In Ji’nan, ρ_(NO3-)/ρ_(SO42-) values in spring, autumn and winter were 0.67, 2.57 and 1.98, respectively. In spring, the PM_2.5 concentration was mainly determined by fixed sources, while in autumn and winter, it was mainly attributed to mobile sources. The ISORROPIA thermodynamic model was used to analyze the effects of water content and pH on the secondary component formation. The water content increased as pollution rose. Both the acidity and the water content affected the secondary inorganic component transformation mechanism. Acidity inhibited secondary inorganic component formation, whereas water content promoted it. The back trajectory cluster analysis results showed that the track with the highest proportion (29.2%) came from Binzhou and Dongying in the northeast. Based on the weight potential source contribution factor (WPSCF) and weight-analyzed concentration weight trajectory (WCWT), the potential pollution source area of the secondary component mass concentration in PM_2.5 was analyzed. SO₄^2- was the main contribution of the source area in Jiyang area in the north of Ji’nan city, and the northeast of Binzhou and Dongying. The main contribution sources of NO₃^- and NH₄⁺ are Jiyang District in the north of Jinan City, Zhangqiu District in the northeast, and Laiwu District in the south. The results of this study can provide data support and theoretical basis for further governance and prevention of fine particulate matter in northern Chinese cities..

Key words: PM_2.5, secondary component, spatiotemporal variation, pollution characteristics, influencing factors

摘要：

为分析济南市PM_2.5中二次组分的时空变化和影响因素,对济南市春季（2019年5月16—25日）、秋季（2019年10月15—24日）和冬季（2019年12月17—2020年1月16日）4个典型点位的PM_2.5样品进行连续采样,并测定了PM_2.5中水溶性离子、有机碳（OC）和元素碳（EC）的含量。结果表明：物流交通区的二次组分质量浓度最高（56.13 μg∙m^-3）,钢铁工业区的二次组分浓度比城市市区高,但是二次组分占比较城市市区低,清洁对照点的浓度和占比最低;济南市4个功能区SO₄^2-和NO₃^-转化率均高于0.1,除清洁对照点外,城市市区、钢铁工业区和物流交通区的SO₄^2-转化率明显高于NO₃^-转化率;济南市春季、秋季和冬季的ρ_(NO3-)/ρ_(SO42-)分别为0.67、2.57和1.98,春季PM_2.5浓度以固定源贡献为主,秋季和冬季以移动源贡献为主;运用ISORROPIA热力学模型分析了含水量和pH对二次组分生成的影响,含水量会随着污染增大而增大,酸度和含水量对二次无机组分的转化机理产生影响,酸度会抑制二次无机组分的生成,而含水量会促进二次组分的生成;后向轨迹聚类分析结果表明,占比最高的轨迹（29.2%）来自东北方向的滨州和东营,基于潜在源贡献因子（WPSCF）和浓度权重轨迹（WCWT）分析PM_2.5中二次组分质量浓度的潜在污染源区域,SO₄^2-的主要贡献源区在济南市区北部的济阳区和东北方向的滨州、东营等,NO₃^-和NH₄⁺的主要贡献源区在济南市区北方向的济阳区、东北方向的章丘区和南方向的莱芜区等。该研究结果可为中国北方城市细颗粒物进一步的治理和防控提供数据支撑和理论依据。

关键词: PM_2.5, 二次组分, 时空变化, 污染特征, 影响因素