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Correlations between air pollutant emission, logistic services, GDP, and urban population growth from vector autoregressive modeling: a case study of Beijing

Xiaopeng Guo (), Jiaxing Shi (), Dongfang Ren (), Jing Ren () and Qilin Liu ()
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Xiaopeng Guo: North China Electric Power University
Jiaxing Shi: North China Electric Power University
Dongfang Ren: North China Electric Power University
Jing Ren: North China Electric Power University
Qilin Liu: University of Pittsburgh

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2017, vol. 87, issue 2, 885-897

Abstract: Abstract Logistics in China has grown rapidly; in 2015, the freight volume has reached 41 billion ton, increasing by 4.4% year-on-year. At the same time, the pollutant emissions from freight cars account for 70% of total emissions of motor vehicles, which severely affected the air quality. The purpose of this paper is to investigate the effect of logistics on air pollution; we used a new methodology based on vector autoregression of freight turnover, gross domestic product, and urban population. We selected Beijing as our test and created a model using time series data for the period 2000–2014. In this model, permanent residents, freight turnover, and SO2 emission were used as proxies for population size, logistic services, and degree of air pollution. Our analyses showed that the expansion of logistic services had the biggest effect on air pollution. Moreover, impulse response analysis revealed that logistic growth caused more serious air pollution over a short time, with an ongoing negative effect. GDP growth was only weakly correlated with air pollution, while urban population growth appeared to have little effect.

Keywords: Air pollutant emission; Logistics; Vector autoregression (search for similar items in EconPapers)
Date: 2017
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