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Spatial analysis on China's regional air pollutants and CO2 emissions: Emission pattern and regional disparity

Liang Dong, Hanwei Liang*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

China has suffered from serious air pollution and CO2 emission. Challenges of emission reduction policy not only come from technology advancement, but also generate from the fact that, China has pronounced disparity between regions, in geographical and socioeconomic. How to deal with regional disparity is important to achieve the reduction target effectively and efficiently. This research conducts a spatial analysis on the emission patterns of three air pollutants named SO2, NOx and PM2.5, and CO2, in China's 30 provinces, applied with spatial auto-correlation and multi regression modeling. We further analyze the regional disparity and inequity issues with the approach of Lorenz curve and Gini coefficient. Results highlight that: there is evident cluster effect for the regional air pollutants and CO2 emissions. While emission amount increases from western regions to eastern regions, the emission per GDP is in inverse trend. The Lorenz curve shows an even larger unequal distribution of GDP/emissions than GDP/capita in 30 regions. Certain middle and western regions suffers from a higher emission with lower GDP, which reveal the critical issue of emission leakage. Future policy making to address such regional disparity is critical so as to promote the emission control policy under the "equity and efficiency" principle. 
Original languageEnglish
Pages (from-to)280-291
JournalAtmospheric Environment
Volume92
Online published19 Apr 2014
DOIs
Publication statusPublished - Aug 2014
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 1 - No Poverty
    SDG 1 No Poverty
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Research Keywords

  • Air pollutants
  • Regional disparity
  • Spatial analysis

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