阿拉尔市2021年度大气颗粒物的污染特征研究
Research on the Pollution Characteristics of Atmospheric Particulate Matter in Alar City in 2021

为了解阿拉尔市大气颗粒物PM₁₀、PM_2.5污染情况，本文基于阿拉尔市2021年度环境空气质量自动监测站的监测数据，探究了大气颗粒物质量浓度的月份、季节、年度变化特征，分析了大气颗粒物质量浓度与其他污染物浓度、气象参数之间的关系。研究结果表明：阿拉尔市的大气环境质量主要受颗粒物PM₁₀影响为主，年度污染天数占比较大，颗粒物年均质量浓度较高，污染形势依然严峻。PM₁₀和PM_2.5的月平均质量浓度出现两个峰值、一个谷值。大气颗粒物浓度的变化具有明显的季节性，PM₁₀和PM_2.5的浓度变化在四季中排名为：春季 > 秋季 > 冬季 > 夏季。PM₁₀与SO₂呈现极显著的正相关，与O₃呈现极显著的负相关，与NO₂呈现显著正相关。PM_2.5与其他污染物的关系与PM₁₀基本一致。PM₁₀与风速呈现显著负相关，与气温、湿度呈现极显著负相关，与气压呈现极显著正相关；PM_2.5与风速、气温呈现极显著负相关，与气压呈现极显著正相关。本研究结果可为阿拉尔市大气颗粒物污染的环境治理提供技术参考。
To understand the pollution situation of atmospheric particulate matter PM₁₀ and PM_2.5 in Alar City, this work explores the monthly, seasonal, and annual variation characteristics of atmospheric particulate matter concentration based on the data of Alar City in 2021 from the Environmental Air Quality Automatic Monitoring Station, and analyzes the relationship between atmospheric particulate matter concentration and other pollutant concentrations and meteorological parame-ters. The research results indicate that the atmospheric environment quality in Alar City is mainly affected by particulate matter PM₁₀, with a relatively large proportion of annual pollution days. The average annual mass concentration of particulate matter is relatively high, and the pollution situation is still severe. The monthly average mass concentrations of PM₁₀ and PM_2.5 show two peaks and one valley. The changes in atmospheric particulate matter concentration have obvious seasonality, with the concentrations of PM₁₀ and PM_2.5 ranking in the four seasons as follows: spring > autumn > winter > summer. PM₁₀ shows a highly significant positive correlation with SO₂, a highly significant negative correlation with O₃, and a significant positive correlation with NO₂. The relationship between PM_2.5 and other pollutants is basically consistent with PM₁₀. PM₁₀ shows a significant negative correlation with wind speed, a highly significant negative correlation with temperature and humidity, and a highly significant positive correlation with air pressure. PM_2.5 shows a highly significant negative correlation with wind speed and temperature, and a highly significant positive correlation with air pressure. The results of this study can provide technical reference for the environmental control of atmospheric