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宿兴涛, 冯静, 安豪, 等. 2023. 2015~2021年京津冀典型城市PM2.5和O3污染趋势变化分析[J]. 大气科学, 47(5): 1641−1653. DOI: 10.3878/j.issn.1006-9895.2307.22240
引用本文: 宿兴涛, 冯静, 安豪, 等. 2023. 2015~2021年京津冀典型城市PM2.5和O3污染趋势变化分析[J]. 大气科学, 47(5): 1641−1653. DOI: 10.3878/j.issn.1006-9895.2307.22240
SU Xingtao, FENG Jing, AN Hao, et al. 2023. Trends Analysis of Fine Particulate Matter and Ozone Pollution in Typical Cities in the Beijing–Tianjin–Hebei Region during 2015–2021 [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(5): 1641−1653. DOI: 10.3878/j.issn.1006-9895.2307.22240
Citation: SU Xingtao, FENG Jing, AN Hao, et al. 2023. Trends Analysis of Fine Particulate Matter and Ozone Pollution in Typical Cities in the Beijing–Tianjin–Hebei Region during 2015–2021 [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(5): 1641−1653. DOI: 10.3878/j.issn.1006-9895.2307.22240

2015~2021年京津冀典型城市PM2.5和O3污染趋势变化分析

Trends Analysis of Fine Particulate Matter and Ozone Pollution in Typical Cities in the Beijing–Tianjin–Hebei Region during 2015–2021

  • 摘要: 大气细颗粒物(PM2.5)和臭氧(O3)的污染趋势变化受气象条件和污染源排放共同影响。基于国家空气环境监测数据和ERA5再分析资料,本文分析了京津冀地区典型城市(包括北京、天津、保定和石家庄)2015~2021年大气PM2.5和O3与气象因子间的关联性,并结合随机森林算法定量评估减排和气象条件对PM2.5和O3年际趋势变化的贡献。结果表明,除夏季外,日均PM2.5与相对湿度和边界层高度均分别呈良好正和负相关;夏季日均PM2.5与O3和温度均呈良好正相关。分析PM2.5和O3不同污染类型天气中的气象条件变化特征发现,冬季和夏季PM2.5单污染天均主要受不利大气扩散条件作用的影响。在PM2.5和O3双污染天,冬季强大气氧化性和高相对湿度条件是加剧PM2.5污染的重要条件,而夏季高温和强太阳辐射条件是促进PM2.5和O3协同污染的重要气象条件。随机森林趋势分析发现,典型城市PM2.5浓度呈下降趋势(−5.0~−10.8 µg m−3 a−1),减排主导了其趋势变化,相对贡献为84%~95%。O3浓度在2015~2018年呈升高趋势,而在2018年后呈下降趋势(−3.4~−6.4 µg m−3 a−1),其中天津、保定和石家庄排放对趋势变化的相对贡献约为18%~34%,反映出近年减排措施对O3污染治理产生有效作用。

     

    Abstract: Atmospheric fine particulate matter (PM2.5) and ozone (O3) pollution are influenced by meteorological conditions and emissions from pollution sources. Based on the data from China’s national air quality monitoring stations and fifth-generation reanalysis data from the European Centre for Medium-Range Weather Forecasts, the relationships of atmospheric PM2.5 and O3 with major meteorological factors in typical cities in the Beijing–Tianjin–Hebei region, including Beijing, Tianjin, Baoding, and Shijiazhuang, during 2015–2021 were investigated in this study. Moreover, the contribution of emission reduction to the annual trend of PM2.5 and O3 was quantitatively evaluated using the random forest algorithm. Excluding summer, daily PM2.5 was positively and negatively correlated with relative humidity and boundary layer height, respectively. Meanwhile, daily PM2.5 was positively correlated with O3 and temperature in summer. Combined with the analysis of the variation characteristics of meteorological conditions associated with different concentration levels of PM2.5 and O3, it was found that adverse atmospheric diffusion conditions primarily affected the individual pollution days in terms of PM2.5 in winter and summer. On PM2.5 and O3 pollution days, strong atmospheric oxidation and high relative humidity conditions critically aggravated PM2.5 pollution in winter, while high temperature and strong solar radiation were important meteorological conditions responsible for increased PM2.5 and O3 co-pollution in summer. Quantitative trend analysis revealed that emission reduction was the driving factor leading to the annual change in PM2.5 and O3, and the contribution to the annual decrease in PM2.5 was 84%–95%. O3 showed an increasing trend from 2015 to 2018 but decreased after 2018 (−3.4 to −6.4 µg m−3 a−1). Furthermore, the trend of O3 was overall consistent with the difference between the observed value and the prediction value obtained from the random forest algorithm. The contribution of emissions in Tianjin, Baoding, and Shijiazhuang to the trends was 18%–34%, indicating that the recent emission reduction measures may have had a certain effect on controlling O3 pollution.

     

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