成都市气态污染物NO_2、SO_2与大气颗粒物相关性分析
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摘要
以成都市为例,研究气态污染物NO_2、SO_2与大气颗粒物之间的相关性。以2014—2016年成都市8个监测站3种污染物(PM_(2. 5)、NO_2、SO_2)的监测数据做统计数据分析,包括趋势分析和相关性分析。分析结果表明:PM_(2. 5)与SO_2和NO_2的关系密切,3种污染物之间总体呈现一致的季节性变化规律,即春、冬高,夏、秋低,且呈现不同的空间变化规律;在重度雾霾条件下,PM_(2. 5)与SO_2的关系较其他污染物密切,但在空气质量条件较好的情况下,PM_(2. 5)与NO_2的关系较其他污染物密切。这说明SO_2对雾霾的形成有着关键作用,特别是在SO_2突然变化的情况下更为明显。因此,未来研究需重点关注SO_2的来源及其清单的准确估算,这对于雾霾的控制异常关键。
The purpose of this study is to analyze the relationships of gaseous pollutants NO_2 and SO_2 with atmospheric particles in Chengdu. The monitoring data of the three pollutants( PM_(2. 5),NO_2 and SO_2) from eight environmental monitoring stations of Chengdu from 2014 to 2016 was used for trend and correlation analysis. Results showed that: PM_(2. 5) concentration was closely connected with NO_2 and SO_2 concentrations in the atmosphere,all of the three pollutants showed similar seasonal variation patterns with higher concentrations in spring and winter and lower concentrations in summer and autumn,however,all of the three pollutants showed different spatial variation patterns; under severe haze conditions,the correlation coefficient between PM_(2. 5) and SO_2 was much higher than that between PM_(2. 5) and NO_2,but much lower under excellent air quality conditions. This implied that SO_2 played a key role in PM formation,especially when SO_2 concentration changed abruptly.Thus,in the future study,it is necessary to focus on the sources of SO_2 emission and the accurate estimation of their list,which is very important for haze control.
The purpose of this study is to analyze the relationships of gaseous pollutants NO_2 and SO_2 with atmospheric particles in Chengdu. The monitoring data of the three pollutants( PM_(2. 5),NO_2 and SO_2) from eight environmental monitoring stations of Chengdu from 2014 to 2016 was used for trend and correlation analysis. Results showed that: PM_(2. 5) concentration was closely connected with NO_2 and SO_2 concentrations in the atmosphere,all of the three pollutants showed similar seasonal variation patterns with higher concentrations in spring and winter and lower concentrations in summer and autumn,however,all of the three pollutants showed different spatial variation patterns; under severe haze conditions,the correlation coefficient between PM_(2. 5) and SO_2 was much higher than that between PM_(2. 5) and NO_2,but much lower under excellent air quality conditions. This implied that SO_2 played a key role in PM formation,especially when SO_2 concentration changed abruptly.Thus,in the future study,it is necessary to focus on the sources of SO_2 emission and the accurate estimation of their list,which is very important for haze control.
引文
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[3]赵雪艳,谷超,杨焕明,等.新疆奎独乌区域冬季大气重污染过程PM2. 5组成特征及来源解析[J].环境科学研究,2017,30(10):1515-1522.
[4]林瑜,叶芝祥,杨怀金,等.成都市西南郊区春季大气PM2. 5的污染水平及来源解析[J].环境科学,2016,37(5):1630-1638.
[5]张彩艳,吴建会,张普,等.成都市冬季大气颗粒物组成特征及来源变化趋势[J].环境科学研究,2014,27(7):782-789.
[6]张智胜,陶俊,谢绍东,等.成都城区PM2. 5季节污染特征及来源解析[J].环境科学学报,2013,33(11):2947-2952.
[7]佟洪金,袁小燕,钱骏,等.成都市冬季一次重污染过程污染特征分析[J].环境工程,2017,35(增刊1):35-40.
[8]王明莹,庄惠生.上海大气PM2. 5污染特征及相关因素分析[J].科学技术与工程,2017,7(17):1671-1677.
[9]区宇波,岳玎利,张涛,等.珠三角秋冬季节长时间灰霾污染特性与成因[J].中国环境监测,2014,30(5):16-20.
[10]吴兑,廖碧婷,陈慧忠,等.珠江三角洲地区的灰霾天气研究进展[J].气候与环境研究,2014,19(2):248-264.
[11]史凯.成都市一次重度灰霾期间大气PM2. 5的自组织临界特性[J].环境科学学报,2014,34(10):2645-2653.
[12] Shi K,Liu C Q. Self-organized criticality of air pollution[J].Atmospheric Environment,2009,43:3301-3304.
[13]中国气象局.地面气象观测规范[M].北京:气象出版社,2005.
[14]中国环境保护局.HJ 633—2012:环境空气质量指数(AQI)技术规定[S].北京:中国环境科学出版社,2012.
[15] Jerome L M,Arnold D W. Research Design and Statistical Analysis[M]. Second Edition,London:Lawrence Erlbaum,2003.
[16]张凯山.统计学在环境科学与工程中的应用[M].北京:科学出版社,2012.
[17]四川省环保厅.川西平原城市群大气污染(灰霾)特征和成因研究[R].2013HBZX01,2014.
[18]成都市统计局.成都市2014年统计年鉴[M].北京:中国统计出版社,2014.
[19]成都市统计局.成都市2015年统计年鉴[M].北京:中国统计出版社,2015.
[20]成都市统计局.成都市2016年统计年鉴[M].北京:中国统计出版社,2016.
[21] Larsen R KⅢ,Baker J E. Source apportionment of polycyclic aromatic hydrocarbons in the urban atmosphere:a comparison of three methods[J]. Environmental Science&Technology,2003,37(9):1873-1881.