PDF《的关系分析》

67 2014―2016年荆州城区空气质量与气象要素 的关系分析 邓艳君1,

2 赵卓勋1 李玲3 张伦瑾1 (1荆州市气象局,荆州 434020;

2 江汉平原生态气象遥感监测技术协同创新中心,荆州 434025;

3 荆州市环境保护监测站,荆州 434000) 摘要:利用2014年1月1日―2016年12月31日荆州城区逐日空气质量数据和同期地面气象要素逐日观测资料,分析了荆 州城区空气质量状况、变化特征及其与气象要素的相关性.

结果表明,荆州城区优良日数偏少,但2014―2016年荆州 城区空气质量略有改善,首要污染物为PM2.5;

AQI和PM

10、PM2.

5、SO

2、NO

2、CO的月变化规律一致,呈V型分布,冬 季空气污染最严重,夏季空气污染相对较轻,O3的变化规律则相反,呈反V型分布;

除O3外,AQI和其他污染物浓度与 前一日AQI、气压呈正相关关系,与气温、水汽压、湿度、云量、降水、风速呈负相关关系,据此建立了AQI和各污染 物浓度的回归预报方程;

进一步分析了2014年1月严重污染天气的成因,本地污染物的分布、外地污染物的输入和气象 扩散条件是影响空气质量的主要因素. 关键词:AQI,污染物浓度,气象要素,相关分析,回归方程 DOI:10.3969/j.issn.2095-1973.2018.05.010 Correlation Analysis of the Air Quality and the Meteorological Elements in Jingzhou from 2014-2016 Deng Yanjun1,

2 , Zhao Zhuoxun1 , Li Ling3 , Zhang Lunjin1 (1 Jingzhou Meteorological Bureau, Jingzhou

434020 2 Collaborative Innovation Center of Remote Sensing Technology in Ecological and Meteorological Monitoring in the Jianghan Plain, Jingzhou

434025 3 Jingzhou Environment Protection Monitoring Station, Jingzhou 434000) Abstract: The daily air quality data in Jingzhou city from January 1,

2014 - December 31,

2016 and the daily observation data of ground meteorological elements in the same period were used to analyze the air quality status, variation characteristics and the correlation-ships with meteorological elements in Jingzhou. The results show that the air quality in Jingzhou was slightly improved during the period from

2014 to

2016 and less pollution occurred on fine days. The primary pollutant was PM2.5. The monthly AQI, PM10, PM2.5, SO2, NO2, and CO has a '

V'

shape variation, while O3 reverses. The air pollution was the most serious in winter and relatively light in summer. The AQI and the concentration of pollutants except O3 are positively related to the AQI and air pressure on previous day, and are negatively related to the temperature, aqueous vapor pressure, humidity, cloud amount, precipitation and wind speed. The regressive prediction models of AQI and the concentration of pollutants are established based on the analysis. The cause of a serious weather pollution case in January

2014 is further analyzed: the distribution of local pollutants, the importing pollutants and the meteorological diffusion condition are the main factors affecting the air quality in that month. Keywords: AQI, pollutant concentration, meteorological element, correlation analysis, regression model

0 引言 随着城市社会经济快速发展,荆州的工业化、 城镇化水平不断提高,城市空气污染日趋严重,空气 污染、雾霾天气时有发生.近年来,人们生活水平 提高,人们对生活环境质量的要求也越来越高,控制 空气污染、改善空气质量的需求越发强烈,因此对城 市空气质量进行全面、客观的认识和评价,根据本地 实际情况准确预测空气污染气象扩散条件,为环境管 理提供决策依据,预防严重污染事件的发生具有重要 意义. 目前,国内学者对空气质量、大气污染物的时空 分布特征、空气污染与气象要素的关系、污染天气空 气质量的预报等方面做了大量研究.例如,建立了城 市空气污染数值预报系统(CAPPS)[1-2] ,北京[3] 、广 收稿日期 :