应用有机示踪物研究四川盆地灰霾天气下大气PM2.5的污染特征和灰霾的形成机制

项目名称： 应用有机示踪物研究四川盆地灰霾天气下大气PM2.5的污染特征和灰霾的形成机制

项目编号： No.41205095

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 大气科学学科

项目作者： 李云春

作者单位： 四川农业大学

项目金额： 25万元

中文摘要： 本项目选择灰霾多发、且大气细颗粒物（PM2.5）及其有机物研究几乎空白的四川盆地，采集一年四季灰霾、非灰霾和特殊时期天气下白天和黑夜的PM2.5对照样品，分析PM2.5及其组分的浓度，重点分析具有独特来源的一次和二次有机示踪物。研究PM2.5及其组分的污染水平、日变化和季节变化规律；创新性的把一次和二次有机示踪物用于正矩阵因数分解受体模型对PM2.5和有机碳进行源解析，并与化学质量平衡源解析结果相比较；结合气象条件、大气环境监测数据、PM2.5、有机示踪物等参数，应用正矩阵因数分解和主成份分析探讨灰霾的形成机制以及二次有机物对灰霾的影响规律。为有针对性地制定大气污染控制策略、尽快达到新标准提供基础研究。

中文关键词： PM2.5；四川盆地；餐饮源；能见度；污染特征

英文摘要： Sichuan Basin, which is the mostly occurred gray haze area but lack of research about fine particle (PM2.5) and its organic compounds, is selected in this project. For comparison purpose, we plan to collect day and night PM2.5 samples on haze and non-haze days, as well as special days in the whole year. Concentrations of PM2.5 and its major components, especially primary and secondary organic tracers will be analyzed. This study will discuss the pollution levels, diurnal and seasonal fluctuations of PM2.5 and its components. Innovatively taking primary and secondary organic tracers as inputting data in positive matrix factorization receptor model to do source apportionment analysis of PM2.5 and organic carbon, and compare the results with those of chemical mass balance model. Exploring the formation mechanism of gray haze and the effect of secondary organic compounds on it will also be conducted with positive matrix factorization and principle component analysis methods, as well as weather conditions, environmental monitoring data, PM2.5, organic tracers, et al. parameters. The results of this project are necessary to generate strategies to effectively control air pollution.

英文关键词： PM2.5；Sichuan Basin；Cooking sources；Visibility；Pollution property