Temporal And Spatial Distribution Characteristics Of PM_2.5 Concentrations And Meteorological Influencing Factors In The Economic Zone Of The Northern Slope Of Tianshan Mountains In 2018

The atmosphere is one of the basic conditions for human survival and development.however,with the rapid development of social economy and the continuous acceleration of urbanization,regional air pollution,especially fine particulate matter pollution,has become one of the major problems that threaten people's health and social sustainable development.In recent years,the regionalization characteristics of PM_2.5pollution in China have become more and more obvious.Under above background,in-depth analysis of the temporal and spatial variation characteristics of atmospheric particulate matter concentration and its influencing factors,which can provide strong theoretical and methodological support for the comprehensive control of particulate matter pollution and the formulation of regional joint prevention and control policies.In this paper,the economic belt on the north slope of Tianshan,the largest urban economic belt in northwest China,is selected as the research object.Using year 2018 as the research period.Based on 18 ground PM_2.5concentration monitoring data,average boundary layer height data,atmospheric relative humidity data,air temperature data,precipitation data,wind speed data and air pressure data,statistical analysis and variance analysis are taken as the main research methods.The time series variation characteristics of PM_2.5concentration in the study area were discussed on the time scales of hour,day,week,month and season,respectively.Taking month as the time scale,based on the inversion results of geographically weighted regression(geographically weighted regression,GWR)model,the spatial distribution characteristics of PM_2.5concentration in the study area are discussed,and the relationship between PM_2.5concentration and meteorological conditions:atmospheric relative humidity,air temperature,precipitation,wind speed and air pressure in the study area is analyzed by using correlation analysis,GWR model,standard coefficient method,.The main results are as follows:(1)In 2018,the PM_2.5pollution degree of the economic belt on the north slope of Tianshan Mountain is generally good,in the order of Wujiaqu,Shihezi,Changji,Urumqi,Karamay,Fukang.On the hourly scale,the diurnal variation curves of Changji and Shihezi showed the characteristics of double peaks and double valleys.The PM_2.5concentration in Wujiaqu showed intermittent fluctuation from 1:00 to 12:00 and"V-shaped"from 12:00 to 1:00 on the next day.The diurnal variation curve of PM_2.5concentration in Urumqi showed the characteristic of single peak and single valley,and that of Karamay and Fukang showed no peak.On the daily scale,the days of light pollution and above accounted for 25.753-34.521%of the whole year in Urumqi,Wujiaqu,Changji and Shihezi,followed by Karamay,which accounted for only 7.397%of the whole year,and mainly concentrated from the middle of November to the end of February.The average daily concentration of PM_2.5in Fukang exhibits little fluctuation,and the number of days of light pollution level is only 2 days.On the weekly scale,the PM_2.5concentration on weekends is slightly higher than that on working days,and there is a certain difference between them.The weekend effect is the most significant in Urumqi and Wujiaqu,but not in other cities.On the monthly scale,the PM_2.5concentration in the study area generally show"concave"monthly variation,with a low and small fluctuation from March to October,a sharp decline period from January to March,and a sharp rise period from October to December.On the seasonal scale,the PM_2.5concentration in the main cities of the study area showed the seasonal distribution characteristics,which in the order of winter,autumn,spring,summer except Fukang,and the PM_2.5concentration in winter was much higher than that in spring,summer and autumn.(2)Compared with the multiple linear regression(multiple linear regression,MLR)model,the GWR model is more effective in inversing the continuous spatial distribution of PM_2.5concentration in the economic belt on the north slope of Tianshan Mountain.The ground PM_2.5concentration R²estimated by GWR Model is 0.783,MAE is 10.489?g/m³,RMSE is 19.010?g/m³,R²of MLR model is 0.729,which is 0.054 lower than GWR Model,MAE and RMSE are11.171?g/m³and 21.279?g/m³respectively,which are 0.682?g/m³and 2.269?g/m³higher than GWR Model,respectively,indicating that the PM_2.5concentration retrieved by GWR Model is more consistent with ground monitoring PM_2.5concentration,and the error is smaller.(3)On the whole,the PM_2.5concentration in the study area showed the spatial distribution characteristic of"high value in the southeast and low value in the northwest",and two pollution centers were in the east and middle:the eastern pollution center dominated by Urumqi,Wujiaqu,the central pollution center dominated by Shihezi,Manas and Hutubi.The PM_2.5concentration gradually decreased from the two pollution centers to the surroundings.The PM_2.5pollution in the western region is generally light.On the monthly scale,PM_2.5pollution was the most serious in December and January,and its concentration was more than 75?g/m³in almost the whole study area.From February to May,PM_2.5concentration first began to decline from the northwest of Karamay,and the downward trend continuously strengthen.Until June and July,the PM_2.5concentration in most areas of the study area decreased to a lower level,and after August,PM_2.5concentration first began to rise from the southeast of the study area.And its concentration value and high value distribution range increased and expanded continuously,until December,the PM_2.5concentration in most areas of the study area reached a high level.(4)During the study period,meteorological conditions have a significant influence on the change of PM_2.5concentration in the economic belt on the north slope of Tianshan Mountain.Among them,there is an extremely significant positive correlation between atmospheric relative humidity,precipitation and PM_2.5concentration,an extremely significant negative correlation between air temperature and PM_2.5concentration,and an extremely significant negative correlation between wind speed and PM_2.5concentration.But in April,the wind speed in the central and western parts of the study area showed an opposite positive correlation with PM_2.5concentration,while air pressure showed no significant negative correlation with PM_2.5concentration.After an in-depth study of the spatial differences of the effects of various meteorological factors on PM_2.5concentration,it is found that the effects of four meteorological factors on PM_2.5concentration decrease from northwest to southeast,in which the precipitation in January is the smallest and other meteorological factors are relatively large,and the effects of meteorological factors on PM_2.5concentration in April have large spatial differences.In July,on the contrary,the spatial differences of the effects of various meteorological factors on PM_2.5concentration are relatively small;in October,precipitation and air pressure are slightly larger,atmospheric relative humidity,air temperature and wind speed are relatively small.