2014—2016年荆州城区空气质量与气象要素的关系分析
Correlation Analysis of the Air Quality and the Meteorological Elements in Jingzhou from 2014－2016
中文摘要：
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PM10、PM2.5、SO2、NO2、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。
中文关键词：
AQI，污染物浓度，气象要素，相关分析，回归方程
KeyWords：
AQI, pollutant concentration, meteorological element, correlation analysis, regression model
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.