| 济南市城区夏季臭氧污染过程及来源分析 |
| 摘要点击 4110 全文点击 1236 投稿时间：2021-06-08 修订日期：2021-07-27 |
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| 中文关键词 济南 臭氧(O3) 敏感性分析 相对增量反应活性(RIR) VOCs来源解析 |
| 英文关键词 Ji'nan ozone(O3) sensitivity analysis relative incremental reactivity(RIR) VOCs source apportionment |
| 作者 | 单位 | E-mail | | 孙晓艳 | 山东省济南生态环境监测中心, 济南 250101 | xiaoyan_sun1983@126.com | | 赵敏 | 山东大学环境研究院, 青岛 266237 | | | 申恒青 | 山东大学环境研究院, 青岛 266237 | | | 刘杨 | 山东省济南生态环境监测中心, 济南 250101 | | | 杜明月 | 山东省济南生态环境监测中心, 济南 250101 | | | 张文娟 | 山东省济南生态环境监测中心, 济南 250101 | | | 许宏宇 | 山东省济南生态环境监测中心, 济南 250101 | | | 范国兰 | 山东省济南生态环境监测中心, 济南 250101 | | | 公华林 | 山东省济南生态环境监测中心, 济南 250101 | | | 李青松 | 山东省济南生态环境监测中心, 济南 250101 | | | 李大秋 | 山东省济南生态环境监测中心, 济南 250101 | | | 高晓梅 | 济南大学水利与环境学院, 济南 250024 | stu_gaoxm@ujn.edu.cn | | 张丽娜 | 德州市生态环境局乐陵分局, 乐陵 253600 | |
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| 中文摘要 |
| 2019年夏季，在济南市城区开展了大气臭氧（O3）及其前体物[挥发性有机物（VOCs）和氮氧化物（NOx）]的综合观测研究，观测发现，日最大8h φ（O3）均值为（103.0±14.5）×10-9，φ（NOx）平均值为（16.7±11.3）×10-9，VOCs的体积分数和活性水平分别为（22.4±9.4）×10-9和（9.6±3.8）s-1.利用局地O3化学收支分析，发现济南具有较高的局地O3生成潜势，白天局地O3平均生成速率为35.6×10-9 h-1.运用基于观测的盒子模型（OBM）和PMF受体模型对济南O3生成的控制因素、关键VOCs来源进行了分析，结果表明济南市城区O3生成总体处于人为源VOCs敏感区，且对烯烃的敏感性最强.O3生成机制由早晨的VOCs敏感区向午后的VOCs-NOx过渡区转变，相应地O3生成效率由18.3×10-9 h-1提高到29.6×10-9 h-1.机动车尾气排放和汽油挥发是城市VOCs的主要来源，对O3生成贡献明显. |
| 英文摘要 |
| In the summer of 2019, field measurements of ozone (O3) and its precursors[volatile organic compounds (VOCs) and nitrogen oxides (NOx)] were carried out at an urban site in Ji'nan. We found that the daily maximum 8-hour averages φ(O3) were (103.0±14.5)×10-9. The average φ(NOx) and φ(VOCs), which are ozone precursors, were (16.7±11.3)×10-9and (22.4±9.4)×10-9, respectively. The ·OH reactivity of VOCs was determined (9.6±3.8) s-1. Ji'nan suffered from serious O3 pollution. An observation-constrained chemical box model was deployed to evaluate in situ photochemical O3 production, which indicated that chemical reactions made positive contributions to O3 production rates between 07:00 and 19:00 LT, with the average hourly O3 production rate of 35.6×10-9 h-1. To evaluate the effectiveness of various ozone precursor control strategies in reducing ozone pollution, we combined the observation-based model (OBM) with the relative incremental reactivity (RIR) method. The key indicators that affect the local ozone production rate were identified. Ji'nan was under VOC-limited conditions and the key VOC precursors were alkenes. The O3 formation mechanism changed from the VOC-limited regime in the morning to the transitional regime in the afternoon. Correspondingly, the simulated local O3 production rate was increased from 18.3×10-9 h-1 to 29.6×10-9 h-1. To further explore the role of anthropogenic emissions in ozone pollution, we used the positive matrix factorization (PMF) model to identify the major sources contributing to VOCs. The major sources in Ji'nan were vehicular exhaust and gasoline evaporation, accounting for more than 50% of the observed VOCs. Therefore, constraints on vehicular emissions is the most effective strategy to control O3 pollution in Ji'nan. |
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