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北京、石家庄2017-2018年PM2.5与SNA组分特征及典型重污染分析 认领 被引量:1

Characteristics of PM2.5 and SNA composition and typical heavy pollution analysis in Beijing and Shijiazhuang from 2017 to 2018
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摘要 基于北京、石家庄2017、2018年的1月和7月PM2.5样品采集,研究两地采暖期、非采暖期及典型重污染过程的PM2.5、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PM2.5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)PM2.5、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PM2.5浓度均高于北京;SNA占PM2.5所有组分的34.11%~51.68%,对PM2.5浓度有重要贡献,其中北京NO-3浓度最高,石家庄SO4^2-浓度最高, SO4^2-/NO-3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PM2.5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NO-3的传输作用比SO4^2-更加突出.从PM2.5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%. A sampling campaign of PM2.5 was conducted during January and July of 2017 and 2018 in Beijing and Shijiazhuang. The characteristics of PM2.5, 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 PM2.5, SO4^2- and NO-3 during January of 2017 in two cities. Results indicated that heavy pollution occurred during January of 2017 in both cities. The concentration of PM2.5 in Shijiazhuang was larger than Beijing in January of 2017 and 2018. SNA were major components of PM2.5, accounting for 34.11%~51.68% in two cities. Among that, NO-3 was larger than SO4^2- and NH+4 in Beijing, while SO4^2- was largest in Shijiazhuang. SO4^2-/NO-3 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 PM2.5 in Beijing and Shijiazhuang during January of 2017 in respective. And the contributions of southern Hebei were 14.86% and 17.21%. NO-3 was affected more obviously by regional transport than SO4^2-. Local sources analysis indicated that mobile and dust were dominant
作者 王传达 周颖 程水源 王晓琦 WANG Chuanda;ZHOU Ying;CHENG Shuiyuan;WANG Xiaoqi(Key Laboratory of Beijing on Regional Air Pollution Control,College of Environmental and Engineering,Beijing University,Beijing 100124)
出处 《环境科学学报》 CAS CSCD 北大核心 2020年第4期1340-1350,共11页 Acta Scientiae Circumstantiae
基金 国家重点研发计划课题(No.2018YFC0213206) 北京市科技计划课题(No.Z181100005418017)。
关键词 PM2.5 SNA 二次转化率 后向轨迹 区域传输 PM2.5 SNA secondary conversion rate backward trajectory regional transport
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