Research On The Relationship Between PM_2.5 And Energy Consumption Structure In Beijing Tianjin Hebei Region And The Realization Of Network Service System

With the rapid development of China's economy,the pollution of the environment is becoming more and more serious,especially the atmospheric environment.In recent years,most areas of our country experienced serious haze weather,the main component of haze is PM_2.5,PM_2.5 is the fine particles which diameter is less than 2.5 microns,it can absorb large amounts of toxic and harmful substances,stay for a long time in the atmosphere,and affect the health of people and travel.China is a big country of energy consumption,the influence of excessive energy consumption on PM_2.5 concentration is very considerable.Therefore,it is of great significance to study the relationship between energy consumption structure and PM_2.5 concentration in order to find out the reasons for the increase of PM_2.5 concentration.In recent years,the Beijing Tianjin Hebei region has become one of the most polluted area by PM_2.5 and one of the largest consumed area in energy,in order to find out the reasons why PM_2.5 pollution in Beijing Tianjin Hebei region increased,this paper firstly studies the correlation between energy consumption structure and the concentration of PM_2.5 in Beijing Tianjin Hebei region and analyze its reason,then build the PM_2.5 prediction model based on the correlation to predict PM_2.5 concentration.Finally,in order to display,analysis and predict PM_2.5 data more intuitively,this paper developed a PM_2.5 network service system based on WebGIS technology to provide map-visualization,spatial analysis and prediction for users.The main contents of this paper are as follows:1)First of all,this paper introduces the related theory and technology of WebGIS,including related technology of GIS,foundation of WebGIS,ArcGIS API for JavaScript which is the implementation technology of WebGIS;2)The paper explores the impact of energy consumption structure on PM_2.5concentration,the results are as follows: the higher the proportion of coal consumption in the energy consumption structure means the higher the PM_2.5 concentration,the higher the proportion of natural gas means the lower the PM_2.5 concentration.Therefore,it is important to reduce the consumption of coal and increase the use of natural gas for controlling the concentration of PM_2.5.Second,building the PM_2.5 prediction model based on the correlation to predict PM_2.5 concentration.The error rate of the prediction results is 8%,so it can be used to predict the real situation;3)Finally this paper use ArcGIS API for JavaScript technology to develop PM_2.5 dataservice system based on ArcGIS Server platform,this paper design and implement system to acquisit data,operate map,process data,query data,spatially analysis,forecast and warning,The system can meet user's business needs such as querying PM_2.5 historical data,spatially analysising and forecasting;4)After the test of the system,the functions are running well,and the expected results are achieved.