State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China.
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China.
Sci Total Environ. 2019 Mar 15;656:977-985. doi: 10.1016/j.scitotenv.2018.11.365. Epub 2018 Nov 29.
Associated with its modernization, Beijing has experienced significant fine particulate matter (PM) pollution, especially in winter. In 2016, severe PM pollution (PM > 250 μg/m) lasted over 6 days and affected over 23 million people. A major challenge in dealing with this issue is the uncertainty regarding the influence of individual meteorological factors to the overall PM concentration in Beijing. Thus, applying an empirical regression method to long-term ground-based PM data and meteorological sounding measurements, we attempted to analyze the influence of individual meteorological factors on PM pollution during winters in Beijing. We found that horizontal dilution and vertical aggregation plays a major role in PM pollution during the winter of 2016. The impact of horizontal wind on PM concentration in Beijing was mainly from its dilution, the dilution of northerly wind contributed 27.8% in 2016, far below its contribution in 2015 (32.2%). The contribution from the growing vertical aggregation observed in 2016 was mainly the result of both the lower height of the planetary boundary layer and the greater depth of the temperature inversion. The dilution of the planetary boundary layer height contributed 9.8% to PM pollution in 2016, 5.4% lower than that in 2017. Compared with the temperature difference of the inversion layer, the temperature inversion depth better reflects the aggregated impact of temperature inversions to PM, which was 10.9% in 2015, and the ratio rose to 14.3% in 2016. Relative humidity is also an important impacting factor, which contributed 41.0%, far higher than the ratio in 2017 (26.7%). Such results imply that we should focus on not only local emission control, but also horizontal atmospheric transport and meteorological conditions in order to provide a more accurate analysis of pollution mechanisms, conductive to air pollution governance in Beijing.
伴随北京的现代化进程，其细颗粒物（PM）污染尤其在冬季变得严重。2016 年，北京遭遇严重的 PM 污染（PM>250μg/m），持续超过 6 天，影响超过 2300 万人。应对这一问题的主要挑战是，难以确定个别气象因素对北京整体 PM 浓度的影响。因此，我们应用经验回归方法，结合长期地面 PM 数据和气象探空测量，分析了个别气象因素对 2016 年冬季北京 PM 污染的影响。结果表明，水平稀释和垂直聚集在 2016 年冬季 PM 污染中起主要作用。北风对北京 PM 浓度的影响主要来自于稀释作用，2016 年北风的稀释作用贡献了 27.8%，远低于 2015 年的贡献（32.2%）。2016 年观测到的垂直聚集增长主要是由于行星边界层高度降低和逆温层深度增加。行星边界层高度稀释对 2016 年 PM 污染的贡献为 9.8%，比 2017 年低 5.4%。与逆温层温差相比，逆温层深度更能反映逆温对 PM 的聚集影响，2015 年为 10.9%，2016 年这一比值上升至 14.3%。相对湿度也是一个重要的影响因素，其贡献为 41.0%，远高于 2017 年的比例（26.7%）。这些结果表明，我们不仅要关注本地排放控制，还要关注水平大气传输和气象条件，以便更准确地分析污染机制，为北京的空气污染治理提供帮助。
