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中文摘要：
目的基于蚌埠市空气污染问题现状,调查蚌埠市市区各类空气污染物浓度,分析蚌埠市空气质量主要污染源及其分布情况。方法在空气质量监测局网站上,查找到蚌埠市近几个月内的空气质量指数与6类常见大气污染物的浓度数据,使用相关性分析、多元线性回归等方法,分别构建相关性分析模型、多元线性回归模型、主因素分析等模型,使用MATLAB、EVIEWS软件进行编程,给出定量计算过程和计算结果,分析其结果代表的意义。结果空气质量指数AQI与6个基本监测指标SO2、NO2、PM10、PM2.5、O3和CO的相关系数分别为0.913 3,0.312 8,0.637 3,0.989 9,0.436,0.065;监测淮上区政府、百货大楼、二水厂、工人疗养院、蚌埠学院及高新区6个监测站的PM2.5浓度变化数据。监测结果为百货大楼,淮上区政府两地PM2.5浓度最高,向周边地区有递减的趋势;蚌埠市一天中PM2.5浓度值多在傍晚达到峰值,且在一年中冬季污染最为严重。结论蚌埠市空气质量指数影响因素主要为PM2.5,而PM2.5与CO之间相关关系较显著,蚌埠市人们的乘车出行对蚌埠市污染物浓度的影响最为显著。且冬季PM2.5含量相对春季、夏季较高。由此,控制人们日常生活中燃料燃烧和机动车尾气的排放可以有效地改善本区域的空气质量。
英文摘要：
Objective Based on the current situation of air pollution in Bengbu,to investigate various concentrations of air pollutants in the urban area of Bengbu and analyze the main pollution sources and their distribution.Methods On the website of Air Quality Monitoring Bureau, the air quality index of Bengbu city in recent months and the concentration data of six kinds of common air pollutants were found. By using correlation analysis, multiple linear regression, the correlation analysis model, multiple linear regression model,the main factor analysis and so on were built.EVIEWS and MATLAB software were used to program, obtaining the quantitative calculation process, the calculation results and their signifi-cance.Results The correlation coefficients of the air quality index AQI and the six basic monitoring of NO2,CO,PM10,PM2.5,O3 and SO2 indexes were 0.913 3,0.312 8,0.637 3,0.989 9,0.436, 0.065,respectively;according to PM2.5 concentration change data form the six monitoring stations (Huaishang Government,Department Store,The Second Water Plant,Workers’Sanatorium,Bengbu College and High-Tech Zone), the highest concentration of PM2.5 was found at Department Store and Huaishang Government,and had a decreasing trend to the surrounding areas;the highest concentration of PM2.5 was found in the evening of the day in Bengbu city and the most polluted season was winter. Conclusion PM2.5 is the main influencing factor of air quality index in Bengbu City,and significant cor-relation was found between PM2.5 and CO.In addition,the concentration of PM2.5 in winter was higher
than those in spring and summer. Accordingly, controlling the combustion of fuel in people’s daily life and the emissions from motor vehicle exhaust might effectively improve the air quality in our residential ar-ea.The people’s travel by car has the highest impact for the concentration of PM2.5.
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