Study On The Influence Factors And Spatial Spillover Effects Of Haze Pollution In Beijing Tianjin Hebei Region

As an important core area of China’s northern economy,the smog pollution problem in the Beijing-Tianjin-Hebei region has been receiving widespread attention from all walks of life.In recent years,large-scale and long-term smog pollution in the Beijing-Tianjin-Hebei region has resulted from the large increase in industrial pollution,motor vehicle emissions,and rapid population growth,and the smog pollution has the characteristics of diffuse transmission between regions.Although various relevant departments have already taken a series of measures to alleviate the smog pollution problem,the smog pollution in the Beijing-Tianjin-Hebei region is still very serious.In order to manage smog scientifically and effectively,this study uses Lasso regression on the driving factors of smog pollution,calculates the influence direction and degree of each factor on urban smog,and uses the threshold model to further empirically analyze the threshold of smog pollution by economic growth.effect.On this basis,the Granger causality test and impulse response function are combined to analyze the spillover effects and magnitudes of haze pollution between regions,and to propose countermeasures and suggestions for the causes of haze pollution in various regions,and to control haze pollution from the source.The main research conclusions are as follows:By analyzing the average annual and monthly concentrations of air pollutants in the Beijing-Tianjin-Hebei region,it was found that several types of air pollutants reached their peaks around 2013,and then showed a downward trend,showing the highest monthly changes in winter and the lowest changes in summer.law.The spatial distribution of smog pollution shows a large difference,and has the characteristics of "north-north difference".By analyzing the causes of smog in the Beijing-Tianjin-Hebei region,it was found that the increase in the number of motor vehicles and the increase in vehicle exhaust caused by road congestion have adversely affected the management of smog;cities with more developed heavy industries or cities that undertake industrial transfer account for a higher proportion of secondary industries Is an important factor that leads to the deterioration of air quality;the structural problems of energy consumption in Hebei Province are prominent,and high energy consumption and high pollution production methods have led to continuous deterioration of air quality.Lasso regression was used to screen the main factors of smog pollution in Beijing,Tianjin,and Hebei,and the indicators that exacerbated the smog pollution in Beijing are: per capita regional GDP,electricity consumption per unit of GDP,energy intensity,the proportion of GDP in the secondary industry,GDP,energy consumption structure,energy industry investment,liquefaction The total supply of LPG;the indicators to reduce the degree of smog pollution in Beijing are: road cleaning area,and investment in environmental pollution treatment as a percentage of GDP.The indicators that aggravate the degree of smog pollution in Tianjin are: energy industry investment,investment in petroleum and coking processing industries,total liquefied petroleum gas supply,and construction area;the indicators to reduce the smog pollution degree in Tianjin are: 10,000 people have public transportation vehicles,Forest coverage,investment in environmental pollution control as a percentage of GDP,and investment in industrial pollution control completed.The indicators that intensify the degree of smog pollution in Hebei Province are: the proportion of highway passenger traffic in the total passenger transport,the output value of the secondary industry in GDP,the energy consumption structure,investment in petroleum and coking processing industries;the indicators to reduce the smog pollution degree in Hebei Province are : 10,000 people own public transportation vehicles,per capita park green space,environmental pollution treatment investment as a percentage of GDP,industrial pollution treatment completed investment,and waste gas treatment completed investment.The panel threshold regression model is used to study the nonlinear relationship between economic growth and smog pollution under the influence of different threshold variables.The four threshold variables of population density,energy consumption structure,energy industry investment,and forest coverage have passed the significance test of the threshold model.Among them,energy consumption structure and energy industry investment have a significant single threshold effect,and forest coverage has a significant double threshold effect There is a significant triple threshold effect on population density.