考虑气溶胶-气象反馈下河北地区霾污染关键源识别及贡献机制研究

Haze has been the most urgent air pollution problem that needs to be resolved in China. Hebei is the haziest province, which is partially due to the high density of emissions in local and the complicated regional emission environment. Source identification and contribution analysis are urgent needed to support the policy making over this area. This study, based on our previous reseaches, fully considering the characteristics of high haze frequency, extremely low visibility, complicated source contributions with high spatial and temporal variations in Hebei, will simulate the haze processes in a relatively long time using the WRF-CMAQ air quality modeling system with aerosol-meteorology feedback mechanism, to firstly identify the different characteristics and pollution patterns in Hebei, and quantify the influence of the aerosol-meteorology feedbacks. Then the contributions of the local and regional sources to the PM2.5 concentrations in Hebei will be assessed using the Brute Force method, and the key sources which have strong correlation, consistency and synchronization with the peak PM2.5 concentrations will be recognized using the sequential factorial analysis method. Third, the contribution mechanism of those key sources will be clarified using the process analysis tool to quantify the direct and in-direct contributions. Finally, the suggested air pollution control strategies for Hebei will be proposed base on the above findings, and the national, provincial, and local action plans.

霾已经成为我国最亟待解决的大气环境问题。河北是我国霾污染最严重的省份，这与该地区高强度的污染物排放以及周边复杂的排放环境有关，源识别和源贡献研究的需求十分迫切。本研究将在以往的研究基础上，针对这一地区严重霾污染频发、能见度极低、污染来源复杂、随时空多变的特征，在考虑气溶胶-气象反馈的情况下，应用WRF-CMAQ空气质量模拟系统对较长时间内该地区发生的霾污染过程展开模拟，识别不同的污染特征和污染模式，量化气溶胶-气象反馈在重污染形成过程中的作用；应用Brute Force方法计算本地及周边各类源对河北地区PM2.5的浓度贡献，并采用析因子分析法识别严重霾污染过程中与PM2.5浓度高峰强烈相关、具有高度一致性和同步性的关键源；应用过程分析工具解析关键源的贡献机制，明确直接和间接贡献的大小，以期为该地区的霾污染控制提供决策支持。