| 天津市应急响应期间VOCs污染特征及来源解析 |
| 摘要点击 2579 全文点击 521 投稿时间：2023-08-14 修订日期：2023-11-02 |
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| 中文关键词 应急响应 挥发性有机化合物（VOCs） 正定矩阵因子分解（PMF） 二元条件概率函数（CBPF） 来源解析 |
| 英文关键词 emergency response volatile organic compounds （VOCs） positive matrix factorization （PMF） conditional bivariate probability function （CBPF） source analysis |
| DOI 10.13227/j.hjkx.20240808 |
| 作者 | 单位 | E-mail | | 姚璐 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | yaolu0612@163.com | | 罗忠伟 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | | | 华琨 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | | | 李亚菲 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | | | 顾瑶 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | | | 宋立来 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | | | 毕申雨 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | | | 尹思涵 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | | | 寇鸣琦 | 天津市津南区生态环境监测中心, 天津 300350 | | | 毕晓辉 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | | | 张裕芬 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | zhafox@nankai.edu.cn | | 冯银厂 | 南开大学环境科学与工程学院, 中国气象局-南开大学大气环境与健康研究联合实验室, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350 | |
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| 中文摘要 |
| 为探究重污染天气污染过程VOCs化学组分特征及主要来源,利用2019~2020年天津市11次重污染天气预警及应急响应前后逐小时VOCs在线数据,分析环境受体中VOCs化学组分变化特征,并利用正定矩阵因子分解（PMF）模型及二元条件概率函数（CBPF）解析其来源.结果表明,在重污染天气预警及应急响应期间,观测点φ（VOCs）均值为35.7×10-9.冬季应急响应期间VOCs体积分数较秋季有所增加,其中烯烃增加48%,烷烃增加4%.重污染天气预警及应急响应期间污染累积阶段,不同VOCs组分其变化幅度有明显差异,橙色预警期间,烷烃占比增加36%,乙炔占比下降32%；黄色预警期间,烷烃占比增长14%,乙炔占比下降5%.重污染天气预警及应急响应期间,机动车排放源、天然气挥发源及溶剂使用源是环境受体中VOCs主要贡献源,贡献率分别为17.5%、 15.4%和15.2%.相比应急响应前,黄色预警期间机动车排放源和柴油挥发源对环境受体中VOCs的贡献率分别减少2.0%~5.5%和2.1%~6.6%,溶剂使用源贡献率减少0.2%~2.4%；橙色预警期间,机动车排放源贡献率减少0.1%~8.3%,溶剂使用源贡献率减少0.5%~6.2%. |
| 英文摘要 |
| To elucidate the characteristics of VOCs chemical components during heavy pollution episodes, hourly online VOCs data derived from 11 heavy pollution events in Tianjin from 2019 to 2020 were employed. The positive matrix factorization （PMF） and conditional bivariate probability function （CBPF） were employed to analyze the sources of VOCs during heavy pollution episodes. The results indicated that the average VOCs volume fraction during these episodes was recorded at 35.7×10-9. Furthermore, it was observed that during the winter emergency response period, there was a discernible increase in the volume fraction of VOCs when compared to that during the autumn season. Specifically, there was a notable upswing of 48% in the olefins category, whereas alkanes registered a 4% increase. Additionally, the VOCs component structure changed significantly during the heavy pollution episodes. During the orange warning period, the proportion of alkanes increased by 36%, and the proportion of acetylene decreased by 32%. During the yellow warning period, the proportion of alkanes increased by 14%, and the proportion of acetylene decreased by 5%. During the emergency response period, motor vehicle emission sources, natural gas evaporative sources, and solvent use sources were the main contributors of VOCs in environmental receptors, contributing 17.5%, 15.4%, and 15.2%, respectively. Compared with that during the period antecedent to the emergency response, the contribution of vehicle emission sources and diesel volatile sources to VOCs in environmental receptors decreased by 2.0% to 5.5% and 2.1% to 6.6%, respectively, and the contribution of solvent use sources decreased by 0.2% to 2.4% during the yellow warning period. During the orange warning period, the contribution of motor vehicle emission sources was reduced by 0.1% to 8.3%, and the contribution of solvent use sources was reduced by 0.5% to 6.2%. |
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