A Spatial Analysis of the Causal Factors Influencing China’s Air Pollution

• Main Authors: Yoomi Kim, Katsuya Tanaka, Xinxin Zhang
• Format: Article
• Language: English
• Published: Asian Association for Atmospheric Environment 2017-09-01
• Series: Asian Journal of Atmospheric Environment
• Subjects: air pollution; china; city-level panel data; green space; spatial analysis
• Online Access: http://asianjae.org/_common/do.php?a=full&b=11&bidx=1457&aidx=18773
• ISSN: 1976-6912; 2287-1160

This study investigates the factors that affect China’s air pollution using city-level panel data and spatial econometric models. We address three air pollutants (PM10, SO2, and NO2) present in 30 cities in China between 2004-2012 using global OLS and spatial models. To develop the spatial econometric analysis, we create a spatial weights matrix to define spatial patterns based on two neighborhood criteria-the queen contiguity and k nearest neighbors. The results show that the estimated coefficients are relatively consistent across different spatial weight criteria. The OLS models indicate that the effect of green spaces is statistically significant in decreasing the concentrations of all air pollutants. In the PM10 and SO2 analyses, the OLS models find that the number of buses and population density are also positively related to a reduction in the concentration of air pollutants. In addition, an increase in the temperature and the presence of secondary industries increase SO2 and NO2 concentrations, respectively. All spatial models capture a positive and significant effect of green spaces on reducing the concentration of each air pollutant. Our results suggest that green spaces in cities should receive priority consideration in local planning aimed at sustainable development. Furthermore, policymakers need to be able to discern the differences among pollutants when establishing environmental policies.