二氧化碳排放的时空异质性:中国高速铁路运营的证据

Wenming Shi, Fuyong Yang, Xuehao Feng, Yiyang Liu, M. Jin
{"title":"二氧化碳排放的时空异质性:中国高速铁路运营的证据","authors":"Wenming Shi, Fuyong Yang, Xuehao Feng, Yiyang Liu, M. Jin","doi":"10.1177/03611981231214522","DOIUrl":null,"url":null,"abstract":"Carbon dioxide (CO2) emissions reduction has become an ever-growing concern in China and the government has proposed the goals of carbon peak and carbon neutrality. To better address this concern, this work pays particular attention to high-speed railway (HSR) operations and examines their spatiotemporal effects and potential mechanism on CO2 emissions. Using a geographically and temporally weighted regression (GTWR) model to fit a balanced panel dataset from the period 2008 to 2018, we have the following main findings. First, the GTWR model performs better than the pooled panel regression model as it considers temporal and spatial variations in factors of CO2 emissions simultaneously. Second, the temporally varying coefficients of HSR operations indicate their consistent contributions to emissions reduction, suggesting that the national development of HSRs can provide significant emissions reduction benefits. Third, as revealed by the spatially varying coefficients of HSR operations, most provinces can mitigate CO2 emissions by promoting HSRs, particularly in Shanxi, Hebei, and Shaanxi, owing to the larger contributions of HSR operations to CO2 emissions reduction. Finally, the contributions of HSR operations to emissions reduction can be transmitted through the mechanism of technological progress. These findings can offer valuable insights into cross-collaborative and province-specific policymaking for mitigating CO2 emissions.","PeriodicalId":309251,"journal":{"name":"Transportation Research Record: Journal of the Transportation Research Board","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatiotemporal Heterogeneity of Carbon Dioxide Emissions: Evidence from High-Speed Railway Operations in China\",\"authors\":\"Wenming Shi, Fuyong Yang, Xuehao Feng, Yiyang Liu, M. Jin\",\"doi\":\"10.1177/03611981231214522\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Carbon dioxide (CO2) emissions reduction has become an ever-growing concern in China and the government has proposed the goals of carbon peak and carbon neutrality. To better address this concern, this work pays particular attention to high-speed railway (HSR) operations and examines their spatiotemporal effects and potential mechanism on CO2 emissions. Using a geographically and temporally weighted regression (GTWR) model to fit a balanced panel dataset from the period 2008 to 2018, we have the following main findings. First, the GTWR model performs better than the pooled panel regression model as it considers temporal and spatial variations in factors of CO2 emissions simultaneously. Second, the temporally varying coefficients of HSR operations indicate their consistent contributions to emissions reduction, suggesting that the national development of HSRs can provide significant emissions reduction benefits. Third, as revealed by the spatially varying coefficients of HSR operations, most provinces can mitigate CO2 emissions by promoting HSRs, particularly in Shanxi, Hebei, and Shaanxi, owing to the larger contributions of HSR operations to CO2 emissions reduction. Finally, the contributions of HSR operations to emissions reduction can be transmitted through the mechanism of technological progress. These findings can offer valuable insights into cross-collaborative and province-specific policymaking for mitigating CO2 emissions.\",\"PeriodicalId\":309251,\"journal\":{\"name\":\"Transportation Research Record: Journal of the Transportation Research Board\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Record: Journal of the Transportation Research Board\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/03611981231214522\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Record: Journal of the Transportation Research Board","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/03611981231214522","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

二氧化碳(CO2)减排已成为中国政府日益关注的问题,并提出了碳峰值和碳中和的目标。为了更好地应对这一问题,本研究特别关注高速铁路(高铁)的运营,并研究其对二氧化碳排放的时空影响和潜在机制。我们使用地理和时间加权回归(GTWR)模型来拟合 2008 年至 2018 年期间的平衡面板数据集,得出以下主要结论。首先,GTWR 模型比集合面板回归模型表现更好,因为它同时考虑了二氧化碳排放因素的时空变化。第二,高铁运营的时空变化系数表明其对减排的贡献是一致的,这表明国家发展高铁可以带来显著的减排效益。第三,从高铁运营的空间变化系数来看,大多数省份都可以通过推广高铁来减少二氧化碳排放,尤其是山西、河北和陕西,因为高铁运营对二氧化碳减排的贡献较大。最后,高铁运营对减排的贡献可以通过技术进步机制进行传递。这些发现可为跨省合作、因省而异的二氧化碳减排政策制定提供有价值的启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Spatiotemporal Heterogeneity of Carbon Dioxide Emissions: Evidence from High-Speed Railway Operations in China
Carbon dioxide (CO2) emissions reduction has become an ever-growing concern in China and the government has proposed the goals of carbon peak and carbon neutrality. To better address this concern, this work pays particular attention to high-speed railway (HSR) operations and examines their spatiotemporal effects and potential mechanism on CO2 emissions. Using a geographically and temporally weighted regression (GTWR) model to fit a balanced panel dataset from the period 2008 to 2018, we have the following main findings. First, the GTWR model performs better than the pooled panel regression model as it considers temporal and spatial variations in factors of CO2 emissions simultaneously. Second, the temporally varying coefficients of HSR operations indicate their consistent contributions to emissions reduction, suggesting that the national development of HSRs can provide significant emissions reduction benefits. Third, as revealed by the spatially varying coefficients of HSR operations, most provinces can mitigate CO2 emissions by promoting HSRs, particularly in Shanxi, Hebei, and Shaanxi, owing to the larger contributions of HSR operations to CO2 emissions reduction. Finally, the contributions of HSR operations to emissions reduction can be transmitted through the mechanism of technological progress. These findings can offer valuable insights into cross-collaborative and province-specific policymaking for mitigating CO2 emissions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Automatic Traffic Safety Analysis using Unmanned Aerial Vehicle Technology at Unsignalized Intersections in Heterogeneous Traffic Role of Bystanders on Women’s Perception of Personal Security When Using Public Transport Comprehensive Investigation of Pedestrian Hit-and-Run Crashes: Applying XGBoost and Binary Logistic Regression Model Insights for Sustainable Urban Transport via Private Charging Pile Sharing in the Electric Vehicle Sector Correlates of Modal Substitution and Induced Travel of Ridehailing in California
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1