中文关键词天津PM_2.5在线观测污染特征来源解析 英文关键词TianjinPM_2.5online observationpollution characterizationsource apportionment

作者	单位	E-mail
肖致美	天津市生态环境监测中心, 天津 300191	xiaozhimei01@163.com
徐虹	天津市生态环境监测中心, 天津 300191
李立伟	天津市生态环境监测中心, 天津 300191
李鹏	天津市生态环境监测中心, 天津 300191
元洁	天津市生态环境监测中心, 天津 300191
唐邈	天津市生态环境监测中心, 天津 300191	tangmiao32@163.com
杨宁	天津市生态环境监测中心, 天津 300191
郑乃源	天津市生态环境监测中心, 天津 300191
陈魁	天津市生态环境监测中心, 天津 300191

中文摘要 为了解天津市PM_2.5的污染特征及来源，基于2017~2019年高时间分辨率的在线监测数据，对PM_2.5浓度、化学组分和来源进行了分析.结果表明，2017~2019年，天津PM_2.5平均浓度为61 μg ·m^-3，PM_2.5中主要化学组分为NO₃^-、OC、NH₄⁺、SO₄^2-、EC和Cl^-，在PM_2.5中占比分别为17.7%、12.6%、11.5%、10.7%、3.4%和3.1%.从年分布上看，PM_2.5及主要化学组分浓度均呈现下降趋势，NO₃^-和NH₄⁺在PM_2.5中占比上升，SO₄^2-、OC和EC在PM_2.5中占比下降，Cl^-在PM_2.5中占比略上升，其他组分K⁺、Ca²⁺和Na⁺浓度及在PM_2.5中占比均上升.PM_2.5及主要组分浓度在采暖季相对较高，非采暖季相对较低，夏秋季SOR和NOR较高，二次转化强，PM_2.5中二次无机离子（NO₃^-、NH₄⁺和SO₄^2-）占比相对较高.当PM_2.5浓度为优良级别时，PM_2.5中二次无机离子占比较低，OC占比较高，SOC生成较高，Ca²⁺和Na⁺占比相对较高；PM_2.5浓度为轻度及以上污染级别时，随着污染程度加重，PM_2.5中二次无机离子占比明显上升，OC占比基本稳定，EC和Cl^-占比略升，K⁺、Ca²⁺和Na⁺等离子占比下降.PM_2.5浓度处于中度及以上污染级别时，机动车影响明显增加.PMF解析结果表明，2017~2019年，天津市PM_2.5的主要来源为二次源、机动车排放、工业和燃煤排放以及扬尘.其中机动车排放的贡献分担率上升，二次源、扬尘的贡献分担率略升，工业和燃煤源的贡献分担率略降.对天津来说，机动车、燃煤和工业排放始终是PM_2.5最主要的一次污染来源，产业结构和能源结构的调整以及机动车的管控是大气污染防治的主要方向. 英文摘要 To study the characterization and source apportionment of PM_2.5 in Tianjin, based on high-resolution online monitoring data from 2017 to 2019, the concentrations and its chemical compositions and sources of PM_2.5 were analyzed. The results showed that the average concentration of PM_2.5 was 61 μg ·m^-3. The primary chemical compositions of PM_2.5 were nitrate, organic carbon (OC), ammonium, sulfate, elemental carbon (EC), and Cl^- and their corresponding mass percentages to PM_2.5 were 17.7%, 12.6%, 11.5%, 10.7%, 3.4%, and 3.1%, respectively. From 2017 to 2019, the concentrations of PM_2.5 and its main chemical compositions exhibited a decreasing trend; the mass ratios of NO₃^- and NH₄⁺ to PM_2.5 exhibited an increasing trend, while the mass ratios of SO₄^2-, OC, and EC to PM_2.5 exhibited a decreasing trend; further, the mass ratio of Cl^- exhibited a slight increasing trend. The concentrations of K⁺, Ca²⁺, and Na⁺ and their mass percentages to PM_2.5 increased. The concentrations of PM_2.5 and its primary components were relatively higher during heating season, and relatively lower during non-heating season. High values of SOR and NOR indicated that the secondary transformation of nitrate and sulfate played an important role during summer and autumn, which resulted in higher mass percentages of secondary inorganic ions (NO₃^-, SO₄^2-, and NH₄⁺) to PM_2.5 during summer and autumn. When the PM_2.5 concentrations were at excellent levels, the mass ratios of the secondary inorganic ions to PM_2.5 were relatively lower, the mass ratios of OC, Ca²⁺, and Na⁺ to PM_2.5 were relatively higher, and secondary organic carbon (SOC) was high. When the PM_2.5 concentrations were between light pollution to heavy pollution levels, as the pollution levels increased, the mass percentages of secondary inorganic ions, OC, EC, and Cl^-, and other components (K⁺, Ca²⁺, and Na⁺) showed a significant increasing trend, relatively stable level, slightly increasing trend, and decreasing trend, respectively. When PM_2.5 concentrations were between moderate pollution to heavy pollution levels, the influence of vehicle emission increased significantly. The source apportionment of PM_2.5 were analyzed using the positive matrix factorization model. The major sources of PM_2.5 in Tianjin were secondary source, vehicle exhaust, industrial and coal combustion emissions, and crustal dust. From 2017 to 2019, the contribution of vehicle exhaust increased, and the contribution of secondary source and crustal dust showed a slight increasing trend, while the contribution of industrial and coal combustion emissions decreased. For Tianjin, vehicle exhaust and industrial and coal combustion emissions were the primary sources of PM_2.5. The adjustment of industrial and energy structure and management and control of vehicle exhaust are the main directions for air pollution control in Tianjin.

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