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Spatial And Temporal Distribution Of Air Pollution In Harbin Under The Background Of Big Data

Posted on:2018-08-10Degree:MasterType:Thesis
Country:ChinaCandidate:T GeFull Text:PDF
GTID:2321330542983363Subject:Cartography and Geographic Information System
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In recent years,with the rapid development of industrialization in Harbin,the air pollution problems has become worse and worse.The government and inhabitants have the urge demand of improving the air quality and environment,so the measures should be taken to improve the condition quickly.Air pollution is the main urban environmental problems that affect the people's life and development,even the concentration of major pollutants in the air quality has been draw more and more attention and regarded as an important indicator of whether the urban air is good or not.In this article,the author takes the eight districts?Daoli District,DaoWai District,Nangang District,Xiangfang District,Cottage District,Songbei District,Hulan District,A C ity?of Harbin as the research area,use the Monitoring data of six major air pollutants from twelve Air Quality Monitoring points?Lingbei,Songbei commercial university,Ahcheng Huining,Nangang Xuefu Road,Taiping Hongwei park,Daowai the Chengde Plaza,Xiangfang Hongqi Street,Dongli peace road,Daoli Jianguo street,PingfangDongqingfactory,Hulannormalspecialisedpostsecondary college,Heilongjiang Academy of Agricultural Sciences?of Harbin Environment Monitoring Station and the ground.Meteorological date obtained from C hina Meteorological Data Network during 2013 to 2016 as the research objects to evaluate the environment quality ofHarbin built areas through the average value calculated year by year,month by Month,day by day,even hour by hour,with the help of Arc GIS spatial analyze tool,the author try to do some research for the differences and Rules of air quality by using the spatial interpolation and superposition analyze.through programming the R language correlation analyses date to study with the relationship between the pollutants and the meteorological factors.Through the data analysis to show the cause of regional pollution And show the transformation rule,which provide the research reference for Harbin air pollution prevention in the future.The results show,On the time scale,the air quality of Harbin has been improving and the number of good air quality has been increasing year by year,from the year of2013 to the year of 2016.The AQI index of January to March is gradually becoming low,and the AQI index can be c lose to the lowest figure for a few months in the non-heating period,from October to December,the AQI index gradually becomes higher and higher month by month.In the heating and non-heating periods,the daily hourly pollutant concentration has obvious time distribution.From 8:00 am to 9:00 am and20:00 to 21:00,the highest concentration of pollutants in the day is the reason for the morning Heating or production of boilers due to furnace,the evening caused by the increase in urban motor vehicle traffic caused by emissions.O n the spatial scale,there are regional differences in air pollution in Harbin,regional pollution is more serious and takes place frequently heavy pollution of the weather area for the Nangang Xuefu Road site area and Taiping Hongwei park s ite area near.The severity of regional air pollution has a strong relationship with the main pollutants in the atmosphere and the sources of pollution such as straw burning.the relativity between the main pollutants and meteorological factors,and they will become more relevant to each other during the winter heating period,during that time,temperature inversion and the high humidity are the main causes of heavy pollution weather.The pollutant concentration is negatively correlated with the wind speed.The correlation coefficient between NO2 and wind speed is the most relevant,the correlation coefficient is-0.66,the correlation coefficient of PM2.5 and wind speed is-0.59.PM2.5 was the main pollutant in the pollutants influencing AQI index,and the influence degree was PM2.5>PM10>NO2>CO>SO2>O3.
Keywords/Search Tags:Air quality, Air pollutants, R Language, correlation, Temporal-spatial distribution
PDF Full Text Request
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