2018
DOI: 10.1155/2018/2148318
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Effect of Energy Development and Technological Innovation on PM2.5 in China: A Spatial Durbin Econometric Analysis

Abstract: Using the panel data of 29 provinces and regions in China, this paper analyzes the temporal and spatial characteristics of PM2.5 concentration. The spatial Durbin model is used to empirically examine the impact of energy development and technological innovation on PM2.5. The results show that the interprovincial PM2.5 in China showed an inverted “N” trend. There is a spatial agglomeration of interprovincial PM2.5, and the spatial autocorrelation is significant. The spatial autoregression coefficients of adjace… Show more

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Cited by 6 publications
(3 citation statements)
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References 28 publications
(26 reference statements)
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“…The results showed that technological innovation can not only reduce the province's Haze pollution can also indirectly lead to a decrease in the degree of haze pollution in neighboring provinces through knowledge spillover effects. Liu (2018b) used the spatial Dubin model to analyze the impact of technological innovation on China's PM2.5. The empirical results showed that technological innovation could significantly reduce PM2.5 emissions in the region, neighboring regions, and the world.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The results showed that technological innovation can not only reduce the province's Haze pollution can also indirectly lead to a decrease in the degree of haze pollution in neighboring provinces through knowledge spillover effects. Liu (2018b) used the spatial Dubin model to analyze the impact of technological innovation on China's PM2.5. The empirical results showed that technological innovation could significantly reduce PM2.5 emissions in the region, neighboring regions, and the world.…”
Section: Literature Reviewmentioning
confidence: 99%
“…e works of Anselin and Elhorst have played a fundamental role in modelling the spatial econometric models theoretically [2][3][4][5]. e spatial model mainly includes the spatial lag model (SLM), spatial error model (SEM), and Spatial Durbin Model (SDM) [6,7]. LeSage and Pace proved that the spatial lag and spatial error model are special cases of the Spatial Durbin Model [8].…”
Section: Introductionmentioning
confidence: 99%
“…Some scientific research shows that nitrogen oxides and sulfur dioxide emissions may be separately transformed to PM 2.5 nitrate ion and sulfate ion in particular environmental conditions. Human exposure to PM 2.5 can lead to a variety of adverse health impacts, such as cardiovascular and respiratory problems [1][2][3]. Based on the effect on environment and human health, PM 2.5 pollution hierarchies have been divided into six grades from excellent to serious pollution, which are described in Table 1.…”
Section: Introductionmentioning
confidence: 99%