Analysis of Influencing Factors and Trend Forecast of CO 2 Emission in Chengdu-Chongqing Urban Agglomeration

Huibin Zeng, Bilin Shao, Genqing Bian, Hongbin Dai and Fangyu Zhou
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Huibin Zeng: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
Bilin Shao: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
Genqing Bian: School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China
Hongbin Dai: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
Fangyu Zhou: School of Applied English, Chengdu Institute Sichuan International Studies University, Chengdu 611844, China

Sustainability, 2022, vol. 14, issue 3, 1-30

Abstract: Urban agglomeration is a primary source of global energy consumption and CO 2 emissions. It is employed as a major means of modern economic and social activities. Analysis of the temporal and spatial characteristics of CO 2 emissions in urban agglomerations and prediction of the future trends of CO 2 emissions in urban agglomerations will help in the implementation of CO 2 reduction policies within region-wide areas. So, based on that, this study contains four aspects. Firstly, it calculates the energy CO 2 emissions of China’s Chengdu-Chongqing urban agglomeration. Secondly, it analyzes the time and space changes in the area by using ArcGIS. Then, the STIRPAT model is used to investigate the factors influencing CO 2 emissions, and the elasticity coefficient of the influencing factors is estimated using the ridge regression method, and the important influencing factors are screened on the basis of the estimated results, which are then used as input features for prediction. Finally, a combined prediction model based on the improved GM (1, N) and SVR models is constructed, and then the optimal solution is found through the particle swarm optimization algorithm. It sets up different CO 2 emission scenarios to predict the energy CO 2 emission of the region and its cities. The results show that, first, the CO 2 emissions of the Chengdu-Chongqing urban agglomeration have accumulated year by year, but by 2030, as predicted, it will not reach its peak. The spatial layout of CO 2 emissions in this region is not expected to undergo major changes by 2030. Second, population, GDP, gas and electricity consumption, and industrial structure have served as important factors affecting energy CO 2 emissions in the region. Third, on the basis of the prediction results for different scenarios, the CO 2 emissions in the baseline scenario are low in the short term, but the CO 2 emissions in the low-carbon scenario are low in the long run. This study also puts forward some policy recommendations on how to reduce CO 2 emissions.

Keywords: CO 2 emissions; Chengdu-Chongqing urban agglomeration; scenario prediction; influencing factor analysis; temporal and spatial characteristics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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