摘要
分析和掌握大气中PM_(2.5)的污染特征,对控制PM_(2.5)的排放和改善空气质量具有十分重要意义。依据西安市连续2年多的空气质量监测数据,对AQI监测指标进行相关性分析,还从季节平均、月平均和日平均变化分析了PM_(2.5)随时间的分布特征,并应用MATLAB软件依据griddata插值算法绘制出了PM_(2.5)的空间分布图,直观地显示了PM_(2.5)污染在空间上的分布特征,突出了污染治理的重要季节和重点地区。研究结果表明:空气质量指数中的6项指标之间存在一定的相关性,PM_(2.5)与PM10的相关性最大,且PM_(2.5)污染呈季节性变化,春季污染最为严重,其次是冬季和秋季,夏季污染最轻;西安市的PM_(2.5)污染主要来源于燃烧、扬尘、尾气排放等过程,污染区域呈现北高南低的特征,污染源除人为源以外,周边污染扩散迁移也有较大影响。
Analyzing PM_（2.5）atmospheric pollution characteristics is of very vital importance for controlling PM_（2.5）emissions and improving air quality.According to the air quality monitoring data of Xi＇an City for more than two years,the AQI monitoring indicator relevance was analyzed.Then the distribution of PM_（2.5）over time is obtained from the change in season average,monthly average and daily average.Finally,this paper uses griddate interpolation applying MATLAB software to draw spatial distribution of PM_（2.5）.The map visually shows PM_（2.5）pollution distribution in space and highlights the important seasons and key areas in pollution management.The result shows that there is a certain correlation among the six indicators of air quality index,with the most significant correlation between PM_（2.5）and PM_（10）.PM_（2.5）pollution shows seasonal change,and spring is the most seriously polluted season,followed by winter,autumn and summer.PM_（2.5）pollution of Xi＇an is mainly from process such as fire,dust and exhaust emissions.Pollution level of polluted area is high in the north and low in the south.Man-made source is not the only pollution source,the diffusion and migration of surrounding pollution also counts.
出处
《环境科学与技术》
CAS
CSCD
北大核心
2016年第8期89-93,98,共6页
Environmental Science & Technology
基金
江西理工大学研究生创新基金(YC2014-X05)
