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基于PM2.5污染—气象综合指数的2014~2020年中国中东部冬季PM2.5污染气象条件分析

Analysis of Variations and Impacts of PM2.5 Pollution Meteorological Conditions in Central-East China during Winter from 2014 to 2020 Based on PM2.5 Pollution-Meteorological Index

  • 摘要: 基于中国生态环境部逐小时细颗粒物(PM2.5)浓度数据以及NCEP FNL气象再分析资料,通过相关分析构建了PM2.5污染—气象综合指数(Pollution Meteorological Index, PMI),分析了2014~2020年冬季中国中东部四个典型地区(京津冀、汾渭平原、长三角和珠三角)PM2.5污染气象条件变化及其对PM2.5浓度的影响。PM2.5浓度变化分析表明,2014~2020年冬季,中国中东部96.5%(305/315)的站点近地面PM2.5浓度下降,89%(251/282)的站点PM2.5重污染天数减少。PM2.5浓度在京津冀、长三角和珠三角地区下降速率依次为9.3、6.3和2.9 µg m−3 a−1,在汾渭平原2014~2016年冬季上升,之后下降。构建的PMI和2014~2020年冬季区域平均的PM2.5浓度呈较强正相关关系,在京津冀、汾渭平原、长三角和珠三角地区的相关系数分别为0.71、0.71、0.71和0.61,说明PMI具有较好的可靠性。PMI变化分析显示,2014~2020年冬季京津冀、汾渭平原和珠三角影响PM2.5的气象条件无显著趋势变化,而长三角地区明显好转(PMI每年下降0.33)。PM2.5浓度、PMI及污染物人为源排放变化对比分析结果表明,京津冀和珠三角地区2014~2020年冬季近地面PM2.5浓度下降主要归因于人为源排放减小,而长三角地区还受到气象条件好转的影响。2014~2016年冬季汾渭平原近地面PM2.5浓度上升是气象条件恶化的结果。

     

    Abstract: Based on the hourly PM2.5 concentration data from the Ministry of Ecology and Environment of China and the NCEP FNL meteorological reanalysis data, this study constructed a PM2.5 Pollution Meteorological Index (PMI) through correlation analysis and examined the changes in PM2.5 pollution meteorological conditions and their impacts on PM2.5 concentration in four typical regions in Central-East China (Beijing–Tianjin–Hebei, Fenwei Plain, Yangtze River Delta, and Pearl River Delta) during winter from 2014 to 2020. The analysis of PM2.5 concentration changes showed that during the winters of 2014–2020, the near-surface PM2.5 concentration decreased at 96.5% (305/315) of the sites in Central-East China, and the number of heavily polluted days with PM2.5 reduced at 89% (251/282) of the sites. The decline rates of PM2.5 concentration in the Beijing–Tianjin–Hebei, Yangtze River Delta, and Pearl River Delta regions were 9.3, 6.3, and 2.9 µg m3 a1, respectively. In the Fenwei Plain, the PM2.5 concentration increased during the winters of 2014–2016 and then decreased during the winters of 2017–2020. The constructed PMI showed a strong positive correlation with the regional average PM2.5 concentration during the winters of 2014–2020, with correlation coefficients of 0.71, 0.71, 0.71, and 0.61 for the Beijing–Tianjin–Hebei, Fenwei Plain, Yangtze River Delta, and Pearl River Delta regions, respectively, indicating the reliability of the PMI. The analysis of PMI changes indicated that during the winters of 2014–2020, no significant trend in the meteorological conditions affecting PM2.5 occurred in the Beijing–Tianjin–Hebei, Fenwei Plain, and Pearl River Delta regions, while the meteorological conditions in the Yangtze River Delta region improved significantly (with a PMI decrease of 0.33/a). Comparative analysis of the PM2.5 concentration, PMI, and changes in anthropogenic emissions showed that the decline in near-surface PM2.5 concentration in the Beijing–Tianjin–Hebei and Pearl River Delta regions during the winters of 2014–2020 was mainly due to the reduction of anthropogenic emissions and that the Yangtze River Delta region was affected by the improved meteorological conditions. The increase in near-surface PM2.5 concentration in the Fenwei Plain during the winters of 2014–2016 was a result of deteriorating meteorological conditions.

     

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