气象和排放变化对PM2.5污染的定量影响

基于WRF-CMAQ模型系统定量分析了气象和排放因素对全国及重点区域PM_2.5污染影响程度.从年度特征来看，与2015年相比，2016年、2017年全国空气质量明显改善，PM_2.5年均浓度分别下降7%和14%；2016年气象条件总体转好，气象因素和排放因素变化导致全国PM_2.5年均浓度下降幅度分别为4%和3%；2017年全国气象条件与2015年相比基本持平，大气污染物排放量下降是PM_2.5污染减轻的决定因素.除汾渭平原外，京津冀及周边地区"2+26"城市、长三角、成渝地区空气中的PM_2.5年均浓度持续下降；珠三角气象条件变化对PM_2.5影响较大，2017年导致PM_2.5浓度上升了29%；除汾渭平原外，其他4个重点地区的污染物排放变化导致PM_2.5年均浓度下降且2017年的下降幅度进一步加大，说明污染管控措施的环境效益明显.从季节特征来看，气象影响值的区域性差异明显.本文分析方法可用于制定空气质量目标或者评估污染控制方案的环境效果.

Impact of meteorological conditions and emission change on PM2.5 pollution in China

The WRF-CMAQ modeling system was employed to investigate the impact of meteorological conditions and emission reduction on PM_2.5 pollution in China. The results indicate that the PM_2.5 concentration observed in 2016 and 2017 decreased by 7% and 14%, respectively compared with that in 2015, indicating an evident improvement in air quality. In 2016, the decrease in PM_2.5 concentration owning to meteorological factor and emission reduction were estimated to be 4% and 3%, respectively. The impact of meteorological factors in 2017 showed little difference compared with that in 2015, which implied that the decrease of emissions was the decisive factor to PM_2.5 decline. In the key regions except for the Fenwei Plain, such as Beijing-Tianjin-Hebei and surrounding region (‘2+26’ region), the Yangtze River Delta (YRD), the Pearl River Delta (PRD) region and the Chengdu-Chongqing (CYB) region, the observational concentration decreased steadily. In the PRD region, an increase of 29% in PM_2.5 concentration in 2017 could be attributed to the variations of meteorological conditions. Except for the FenWei plain, the decrease of emissions contributed to a larger drop in PM_2.5 concentration in 2017 in the other key regions. The results indicated that the emission cuts generally improved the air quality. The analytical methods presented in this paper could be referred when setting air quality goals or estimating environmental benefit of pollution control plans.