| 气象、本地光化学生成和外围传输对长沙市2018~2020年臭氧污染趋势变化影响的识别 |
| 摘要点击 1487 全文点击 486 投稿时间：2022-07-27 修订日期：2022-09-26 |
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| 中文关键词 臭氧 气象校正 本地排放影响 外围传输 主控因素 |
| 英文关键词 ozone (O3) meteorological adjustment local impacts nonlocal driving factors |
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| 中文摘要 |
| 针对湖南省臭氧（O3）污染加剧但是相关的研究较为缺乏的现状，以长沙市为研究区域，基于观测数据，结合气象校正、基于经验的模型（EOF）和绝对得分受体模型（APCs），识别量化了2018~2020年气象、本地光化学生成和外围传输对O3污染相对贡献的影响，分析了2018~2019年和2019~2020年O3趋势变化的主控因素.结果表明，短期范围内，气象条件是O3污染事件发生的重要诱发因素.对长沙市整体来说，在时间上，2018~2019年期间，气象和本地前体物排放影响作用的增强是O3浓度升高的关键驱动因子.2019~2020年期间，气象、本地前体物排放和外围传输影响均呈现下降的趋势，是导致O3浓度降低的重要影响因素.空间上，2018~2020年时间段，气象、本地前体物排放和外围传输主要影响区域分别为长沙市偏东、偏北和偏南部区域.其中，外围传输的作用持续减弱，2018~2019年期间，长沙市北部天然源排放水平的升高使得O3浓度上升，南部区域NOx排放量升高导致滴定作用加强，使得O3浓度降低，在此期间气象条件对整个区域的影响作用增强.2019~2020年期间，本地前体物排放水平不同的变化趋势使得对长沙市O3浓度的影响与2018~2019年状况相反，在此期间气象条件的影响作用减弱. |
| 英文摘要 |
| Ozone (O3) pollution in Hunan province has become the most important factor among the six common conventional pollutants (i.e., NO2, SO2, CO, O3, PM10, and PM2.5) in the atmospheric environment. Further investigation has indicated that the relevant studies of O3 are insufficient. Therefore, it is essential to clarify the key driving factors of O3 variations for government regulators. In this study, a combined method consisting of a generalized additive model (GAM), empirical orthogonal function (EOF), and absolute principal component scores (APCs) model was employed to identify and quantify the impacts of meteorology and local photochemical generation (local) and that transported from outside (nonlocal) on O3 variations from 2018-2020. Simultaneously, the driving factors of O3 annual values from 2018 to 2019 and from 2019 to 2020 in Changsha were analyzed. The results showed that O3 episodes were commonly caused by meteorology when the relative contribution from precursors was high, on the short-term time scale. Overall, on the temporal scale, meteorology and local were the driving factors for the increasing annual O3 from 2018 to 2019. Additionally, the contribution from meteorology, local, and nonlocal decreased from 2019 to 2020, leading to a lower level of O3 concentration in 2020. Geographically, the east, north, and south of Changsha were mainly affected by meteorology, local, and nonlocal, respectively. Throughout the three years, nonlocal exhibited a sustained decreasing trend, whereas the tendencies from meteorology and local varied by year and geography. Local contribution in the north of Changsha increased from 2018 to 2019, which was likely attributed to the increasing biogenic volatile organic compound emission (BVOCs), and it became lower in the south owing to the strengthened consumption by NOx. Impacts from meteorology on O3 in all sites were enhanced from 2018 to 2019. By contrast, local contribution decreased in the north and increased in the south with the decline in BVOC and NOx emissions from 2019 to 2020, when the meteorological impacts on O3 in the whole area became weak. |
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