Study On The Characteristics And Driving Factors Of PM_2.5 Pollution In Shandong Province

As the important gateway of the Yellow River Basin and the land-sea transportation hub of the One Belt and One Road,Shandong Province not only had established an integrated industrial system composed of all industrial sectors but also produced high output value,whose provincial GDP reached to（?）7312.9 billion and ranks 3rd among all the provinces of China.However,economic prosperity and industry agglomeration of Shandong have also come at the cost of resources and environment.Its heavy industry-oriented industry structure led to large amounts of fuel energy consumption and gigantic atmospheric pollutants emission,and five cities among the total seventeen prefecture cities of Shandong were listed in the top 20 most polluted cities of China in 2020.Although great efforts have been made to improve the air quality of Shandong province in recent years,the problems of PM_2.5 pollution still remain unresolved.The development demands of the new era,characterized by green and high quality,will certainly lead to new breakthroughs in development methods and governance models,and the prevention and control of ecological and environmental pollution will enter a new stage.In this context,scientific and accurate clarification of the spatial and temporal patterns and changes in PM_2.5 pollution in Shandong Province,investigation of PM_2.5 drivers and mechanisms,and assessment of pollution control efficiency,could enrich and expand the existing PM_2.5 pollution control research results and provided theoretical and policy recommendations for local governments,which was of great significance to improve the air environment quality and enhance green development in Shandong Province.Based on the basic theories of environmental economics,economic geography and spatial econometrics,spatial econometric analysis was applied to reveal the dynamic evolution of PM_2.5 pollution in Shandong Province at different spatial and temporal scales,including temporal evolution,spatial and temporal differentiation,spatial agglomeration and spatial correlation.Further,spatial panel models were used to screen and quantify the contribution of natural and human factors to pollution and spatial spillover effects from a global perspective.And the static and dynamic pollution control efficiency was measured.Its causes and internal mechanisms were discussed in depth based on the DEA model and Malmquist index.The main research conclusions were as follows:（1）PM_2.5 pollution in Shandong Province has improved gradually.The annual average PM_2.5 concentration in 17 cities decreased from 79.85μg/m³in 2014 to 46.05μg/m³in 2020,but the rate of improvement and the trend of narrowing differences between cities were slowing down.Due to heating and pollution diffusion conditions,the monthly average PM_2.5concentration showed a"U-shaped"distribution,with the most severe pollution in December and January.The percentage of daily average PM_2.5 values meeting secondary air quality standards had increased year on year,but moderate and heavy pollution still occured in winter.As a result of changing meteorological conditions,human production and living patterns,PM_2.5concentrations had"N"and"W"shaped daily variation patterns,with average PM_2.5concentrations higher on weekends than on weekdays.（2）There were obvious regional differences in PM_2.5 pollution,with PM_2.5 concentrations in the western region higher than the eastern region.From the spatial distribution of annual average concentrations,all municipalities have seen a reduction in PM_2.5 concentrations during the study period,with the central and western regions experiencing a greater reduction and a significant improvement in pollution,but the situation was still critical,while the peninsula had basically reached a lower concentration level despite a smaller reduction.The seasonal distribution showed that regional differences in PM_2.5 concentrations were greatest in winter,with high pollution areas distributed in western cities;in summer the differences between regions were smaller,and the overall air quality was better.In December-January,PM_2.5pollution in western cities was the most severe.（3）There was a significant spatial autocorrelation of PM_2.5 pollution in Shandong Province,with significant local clustering characteristics.The low-low agglomeration was stable on the peninsula,while the high-high agglomeration was scattered in the central and western regions.The results of the estimation of the SDM model and the decomposition of the effects indicated that the various factors,natural factors such as temperature,relative humidity and wind speed had a greater impact than socio-economic factors on PM_2.5 pollution.And the indirect effect of the same factor was generally stronger than the direct effect,indicating that surrounding cities could not be ignored.（4）After excluding the effects of environmental variables and random errors,the static pollution control efficiency of PM_2.5 in 17 cities in Shandong Province had increased and decreased,but overall the external environment in Shandong Province was favourable to pollution control.The assessment of dynamic efficiency found that technological progress had a greater impact on efficiency,with only four cities reaching an efficiency index of 1.00.Cities below 1.00 were classified into three categories limited by technological progress,technical efficiency and both factors,respectively.A comparison of static and dynamic efficiency showed that both increased in the period 2014-2018 and decreased in the period 2018-2020,with only four effective cities and differences in efficiency levels in other cities.