Impact of Economic Agglomeration on Carbon Emission Intensity in China ―A Spatial Analysis Using Provincial Panel Data―
0
조회
0
다운로드
2
인용
0
참고문헌
키워드
초록
Global warming and its far-reaching impacts have sparked intense global discussions about carbon emissions and raised a need for ambitious actions and commitments of major economies. In this context, China currently faces the dual challenge of maintaining economic growth and stability while transitioning to low-carbon society. In China, economic agglomeration, including both industrial and urban population agglomeration, has been intensified as a strategic approach to stimulate regional growth. However, existing research does not adequately explore the relationship between industrial and population agglomeration and carbon emissions. To fill this research gap, we analyze panel data from 30 Chinese provinces from 2003 to 2019, employing a Spatial Durbin Model (SDM) to examine the impact of population and industrial agglomeration on carbon emission intensity considering spatial effects. Our empirical results reveal an inverted U-shaped relationship between industrial agglomeration and carbon emission intensity, whereas population agglomeration exhibits a U-shaped correlation. Both demonstrate significant spatial spillover effects. Based on these findings, our study underscores the need for a clear understanding of the complex interplay between industrial activities, population dynamics, and technological advancements in shaping carbon emissions, in order to design more effective policies to promote low-carbon economic development in China.
Abstract
Global warming and its far-reaching impacts have sparked intense global discussions about carbon emissions and raised a need for ambitious actions and commitments of major economies. In this context, China currently faces the dual challenge of maintaining economic growth and stability while transitioning to low-carbon society. In China, economic agglomeration, including both industrial and urban population agglomeration, has been intensified as a strategic approach to stimulate regional growth. However, existing research does not adequately explore the relationship between industrial and population agglomeration and carbon emissions. To fill this research gap, we analyze panel data from 30 Chinese provinces from 2003 to 2019, employing a Spatial Durbin Model (SDM) to examine the impact of population and industrial agglomeration on carbon emission intensity considering spatial effects. Our empirical results reveal an inverted U-shaped relationship between industrial agglomeration and carbon emission intensity, whereas population agglomeration exhibits a U-shaped correlation. Both demonstrate significant spatial spillover effects. Based on these findings, our study underscores the need for a clear understanding of the complex interplay between industrial activities, population dynamics, and technological advancements in shaping carbon emissions, in order to design more effective policies to promote low-carbon economic development in China.
참고문헌 (34)
- Al-mulali, U., "Factors affecting CO₂ emission in the Middle East : A panel data analysis", Energy, 44(1), pp.564~569 (2012)
- Andreoni, V., "Drivers in CO₂ emissions variation : A decomposition analysis for 33 world countries", Energy, 103, pp.27~37 (2016)
- Cheng, Y., "Spatiotemporal dynamics of carbon intensity from energy consumption in China", Journal of Geographical Sciences, 24, pp.631~650 (2014)
- Dai, J., "Analysis of environment influencing factors in China based on STIRPAT model", The Studies in Regional Development, 51(2), pp.41~54 (2019)
- Dietz, T., "Rethinking the environmental impacts of population, affluence and technology", Human Ecology Review, 1(2), pp.277~300 (1994)
- Dong, F., "Determinants of haze pollution : An analysis from the perspective of spatiotemporal heterogeneity", Journal of Cleaner Production, 222, pp.768~783 (2019)
- Ehrlich, P. R., "Impact of Population Growth : Complacency concerning this component of man's predicament is unjustified and counterproductive", Science, 171(3977), pp.1212~1217 (1971)
- Elhorst, J. P., "Spatial Econometrics: From Cross-sectional Data to Spatial Panels" (2014), Springer
- Frank, A. A. M. D. L., "Urban air quality in larger conurbations in the European Union", Environmental Modelling and Software, 16(4), pp.399~414 (2001)
- Gaigné, C., "Are compact cities environmentally friendly?", Journal of Urban Economics, 72(2-3), pp.123~136 (2012)
- Hu, Z., "Factor analysis and enlightenment of household carbon emissions in Japan based on IPAT-LMDI extension model", Resources Science, 40(9), pp.1831~1842 (2018)
- Lin, X. Q., "Research Progress on the eco-environmental effect of industry agglomeration in city group", Progress in Geography, 27(3), pp.110~118 (2008)
- Luo, Z. X., "The nonlinear effect of population aging and socio-economic conditions on carbon emission: An empirical analysis of 30provinces and regions in China", Journal of the Korean Data Analysis Society, 25(3), pp.883~902 (2023)
- Moran, P. A., "The interpretation of statistical maps", Journal of the Royal Statistical Society. Series B (Methodological), 10(2), pp.243~251 (1948)
- Petrović, P., "The impact of R&D expenditures on CO₂emissions : evidence from sixteen OECD countries", Journal of Cleaner Production, 248, pp.119187~ (2020)
- Qin, B., "Does urban concentration mitigate CO₂ emissions? Evidence from China 1998–2008", China Economic Review, 35, pp.220~231 (2015)
- Qin, H., "The association between rural-urban migration flows and urban air quality in China", Regional Environmental Change, 16, pp.1375~1387 (2016)
- Rahman, M. M., "Renewable energy, energy intensity and carbon reduction: Experience of large emerging economies", Renewable Energy, 184, pp.252~265 (2022)
- Shao, S., "Effects of economic agglomeration on energy saving and emission reduction : Theory and empirical evidence from China", Management World, 35(01), pp.36~60 (2019)
- Shim, G. E., "The relationship between the characteristics of transportation energy consumption and urban form", The Annals of Regional Science, 40, pp.351~367 (2006)
- Vujović, T., "Economic growth based in carbon dioxide emission intensity", Physica A : Statistical Mechanics and its Applications, 506, pp.179~185 (2018)
- Wang, S., "Urbanization, economic growth, energy consumption, and CO₂ emissions : Empirical evidence from countries with different income levels", Renewable and Sustainable Energy Reviews, 81, pp.2144~2159 (2018)
- Xie, B., "Industrial agglomeration, foreign direct investment and carbon emission reduction: Based on the mediation effect and threshold model analysis", Technology Economics, 38(12), pp.120~125 (2019)
- Yan, F. Z., "The exploration of the relationship between the industrial agglomreation’s developments and the environmental pollution-the evidence from the manufacturing in China", Studies in Science of Science, 29(01), pp.79~83 (2011)
- Yuan, D. L., "Analysis of the Distribution Pattern of Urban Shrinkage in China using GeoDetector and Gray Model", The Studies in Regional Development (SRD), 55(2) (2023)
- Yuan, X. H., "Does industrial agglomeration aggravate environmental pollution: From a perspective of foreign direct investment", Resources and Environment in the Yangtze Basin, 28(04), pp.794~804 (2019)
- Zhang, K., "The interaction and spatial spillover between agglomeration and pollution", China Industrial Economics, 06, pp.70~82 (2014)
- Zhang, W., "The effect of innovative human capital on green total factor productivity in the Yangtze River Delta", China Population, Resources and Environment, 30(9), pp.106~120 (2020)
- Zheng, W., "Economic growth, urbanization and energy consumption-A provincial level analysis of China", Energy Economics, 80, pp.153~162 (2019)
- "Database. Carbon dioxide emissions by region across China" (2023)[URL]
- "Creating a better energy future" (2023)[URL]
- "COP26: Together for our planet" (2023)[URL]
- "National Bureau of Statistics of China" (2023)[URL]
- "Tackling Climate Change" (2023)[URL]