• 关键词：PM_2.5  SNA  二次转化率  后向轨迹  区域传输

• 基金项目：国家重点研发计划课题（No.2018YFC0213206）；北京市科技计划课题（No.Z181100005418017）

• 王传达
• 北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124

• 周颖
• 北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124

• 程水源
• 北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124

• 王晓琦
• 北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124

• 摘要：基于北京、石家庄2017、2018年的1月和7月PM_2.5样品采集，研究两地采暖期、非采暖期及典型重污染过程的PM_2.5、SNA污染特征及二次转化特征.应用TrajStat模型，结合浓度权重轨迹分析法（CWT），分析两地PM_2.5气流输送路径以及潜在源区.利用WRF-CAMx模式定量分析两地重污染月份（2017年1月）PM_2.5、硫酸盐及硝酸盐的区域传输贡献.结果表明， 2017年1月北京和石家庄均存在重污染过程，两年1月石家庄市PM_2.5浓度均高于北京； SNA占PM_2.5所有组分的34.11%~51.68%，对PM_2.5浓度有重要贡献，其中北京NO₃^-浓度最高，石家庄SO₄^2-浓度最高， SO₄^2-/NO₃^-夏季高于冬季；北京SOR高于石家庄，石家庄NOR高于北京，重污染期间两城市硫酸盐、硝酸盐、铵盐质量浓度、SOR与NOR明显升高；两地冬季气流主要受俄罗斯、蒙古、内蒙戈壁等地区的西北方向远距离输送影响，另外北京两年冬季均存在西南传输通道，石家庄重污染期间受冀南和鲁西北重工业城市群潜在贡献较高，两市夏季受东南季风影响，污染轨迹多来自渤海湾和山东等地区； 2017年1月，北京、石家庄PM_2.5受周边区域传输贡献分别为33.80%、22.54%，其中河北南部分别贡献14.86%， 17.21%，二次离子中NO₃^-的传输作用比SO₄^2-更加突出.从PM_2.5本地源来看，北京主要来源为移动源和扬尘源，分别占比43.30%、20.10%，石家庄为工业、燃煤和扬尘，分别占比26.40%、24.82%、22.50%.

• Abstract：A sampling campaign of PM_2.5 was conducted during January and July of 2017 and 2018 in Beijing and Shijiazhuang. The characteristics of PM_2.5, SNA and secondary conversion degree during heating, non-heating and typical heavy pollution periods were investigated. The transport pathway and potential sources of two cities were discussed based on CWT by applying the TrajStat model. A WRF-CAMx modeling system was utilized to recognize the regional transport contribution to PM_2.5, SO₄^2- and NO₃^- during January of 2017 in two cities. Results indicated that heavy pollution occurred during January of 2017 in both cities. The concentration of PM_2.5 in Shijiazhuang was larger than Beijing in January of 2017 and 2018. SNA were major components of PM_2.5, accounting for 34.11%~51.68% in two cities. Among that, NO₃^- was larger than SO₄^2- and NH₄⁺ in Beijing, while SO₄^2- was largest in Shijiazhuang. SO₄^2-/ NO₃^- was much larger in summer than winter in both cities. SOR and NOR of Beijing were higher and lower than that of Shijiazhuang in respective. The concentration of SNA, SOR and NOR increased obviously during heavy pollution periods in two cities. They were both affected by the airflow transported from Russia, Mongolia, Inner Mongolia Gobi located in the northwest directions in winter. Beijing was also affected by southwest transport pathways which had significant potential contributions to air pollution in both years. As for Shijiazhuang, the cities located in south of Hebei and northwest of Shandong were the potential contributors. However, the backward trajectories were mainly from Bohai Bay and Shandong in summer, which was affected by southeast monsoon. The WRF-CAMx modeling results showed that, regional transport contributed 33.80% and 22.54% to total PM_2.5 in Beijing and Shijiazhuang during January of 2017 in respective. And the contributions of southern Hebei were 14.86% and 17.21%. NO₃^- was affected more obviously by regional transport than SO₄^2-. Local sources analysis indicated that mobile and dust were dominant contributors to Beijing's PM_2.5, accounting for 43.30% and 20.10%. As for Shijiazhuang, the industry, coal combustion and dust were major sources, accounting for 26.40%, 24.82% and 22.50%.

• Key words：PM_2.5  SNA  secondary conversion rate  backward trajectory  regional transport

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