文献类型：期刊文献

英文题名：Empirical assessment of carbon emissions in Guangdong Province within the framework of carbon peaking and carbon neutrality: a lasso-TPE-BP neural network approach

作者：Chen, Ruihan[1];Ye, Minhua[2];Li, Zhi[1];Ma, Zebin[1];Yang, Derong[1];Li, Sheng[1]

机构：[1]Guangdong Ocean Univ, Sch Math & Comp, Zhanjiang, Peoples R China;[2]Guangdong Ocean Univ, Coll Ocean Engn & Energy, Zhanjiang, Peoples R China

年份：2023

卷号：30

期号：58

起止页码：121647

外文期刊名：ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

收录：SCI-EXPANDED(收录号：WOS:001106302700004)、、EI(收录号：20234615062416)、Scopus(收录号：2-s2.0-85180003400)、WOS

基金：No Statement Available

语种：英文

外文关键词：Carbon emissions; Lasso regression; Tree-structured Parzen estimator; BP neural network; Scenario setting; Carbon peaking; Carbon neutrality

外文摘要：The escalating global greenhouse gas emission crisis necessitates a robust scientific carbon accounting framework and innovative development approaches. Achieving emission peaks remains the primary goal for emission reduction. Guangdong Province, a pivotal region in China, faces pressure to reduce carbon emissions. In this study, data was leveraged from the China Carbon Accounting Database (CEADS) and panel data from the "Guangdong Statistical Yearbook" spanning 1997 to 2022. Factors impacting carbon emissions were selected based on Guangdong Province's carbon reduction goals, macroeconomic development strategies, and economic-population dynamics. To address multicollinearity, lasso regression identified key factors, including population size, economic development level, energy intensity, and technology factors. A novel STIRPAT extended model, combined with the BP neural network optimized using the TPE algorithm, enhanced carbon emission predictions for Guangdong Province. Employing scenario analysis, five scenarios were generated in alignment with the planning policies of Guangdong Province, to forecast carbon emissions from 2020 to 2050. The results suggest that to achieve a win-win situation for both economic development and environmental protection, Guangdong Province should prioritize the energy-saving scenario (S2), which aligns with the "13th Five-Year Plan's" ecological and green development directives, to reach a projected carbon peak of 637.05Mt by 2030. In conclusion, recommendations for carbon reduction are proposed in the areas of low-carbon transformation for the population, sustainable economic development, and the development of low-carbon technologies.