{"title":"Prediction and Analysis of Carbon Emissions under Specific Regional Scenarios in Anhui Province based on the STIRPAT Model","authors":"Z. Song, Tingting Zhu, Shihan Yang, Huiqin Zong","doi":"10.54097/jid.v3i2.9147","DOIUrl":null,"url":null,"abstract":"In order to achieve the goal of reaching carbon peak by 2030, the STIRPAT model is used to predict carbon emissions under three simulation scenarios: baseline, optimization, and strict control of carbon emissions. Taking Anhui Province as an example, fully considering the impact of factors such as population, per capita GDP, carbon emission intensity, energy consumption intensity, energy structure, and industrial structure on carbon emissions, ridge regression and partial least squares regression were conducted respectively. Finally, the partial least squares regression method with a lower average error rate was selected to predict the model coefficients. The results show that all three model scenarios can achieve the carbon peak target by 2030, and the factors that have the greatest impact on carbon emissions are carbon emission intensity, energy consumption intensity, and per capita GDP.","PeriodicalId":45705,"journal":{"name":"International Journal of Innovation and Sustainable Development","volume":"37 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovation and Sustainable Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54097/jid.v3i2.9147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
In order to achieve the goal of reaching carbon peak by 2030, the STIRPAT model is used to predict carbon emissions under three simulation scenarios: baseline, optimization, and strict control of carbon emissions. Taking Anhui Province as an example, fully considering the impact of factors such as population, per capita GDP, carbon emission intensity, energy consumption intensity, energy structure, and industrial structure on carbon emissions, ridge regression and partial least squares regression were conducted respectively. Finally, the partial least squares regression method with a lower average error rate was selected to predict the model coefficients. The results show that all three model scenarios can achieve the carbon peak target by 2030, and the factors that have the greatest impact on carbon emissions are carbon emission intensity, energy consumption intensity, and per capita GDP.
期刊介绍:
The IJISD focuses on broad aspects of innovation and sustainable development. It fosters discussion not only on technological innovation but on new ways of thinking about the complex and contested issues of sustainable development. Innovative thinking and practices in areas of economics, policy-making, legislation, health, education and the institutional barriers to sustainable development form the basis of the discourse to be fostered.