{"title":"中国省际交通碳排放特征探究:中国省际交通碳排放特征探究:以区域交通碳减排的类型学战略为目标","authors":"Yuhao Yang, Fengying Yan","doi":"10.3390/land13010015","DOIUrl":null,"url":null,"abstract":"The low-carbon development of the transportation sector is crucial for China to achieve its national goals of carbon peaking and carbon neutrality. Since China is a vast country with unbalanced regional development, there are considerable differences in the levels of carbon dioxide emissions from the transportation sector across regions. Therefore, revealing the influencing factors that shape the characteristics of transportation carbon dioxide emissions (TCO2) can inform tailored sub-national carbon reduction strategies based on local conditions, which is an important technical approach for achieving national goals. Based on an extended Kaya identity, we derived indicators of the impacts on provincial TCO2 from factors such as economic development, population density, energy structure, transportation efficiency, technology research and development (R&D), infrastructure construction, transportation operation conditions, and residents’ transportation behavior. Using a multi-indicator joint characterization method, we explored the characteristics of provincial TCO2 in China in 2019. By applying Ward’s method to hierarchical clustering, the thirty provinces of China were classified into six characteristic types (Types I to VI). Based on the total TCO2 (TC), the intensity of TCO2 (TI), and the per capita TCO2 (TP) calculated for each province in 2019, the priority control directions and indicators for carbon reduction in each type were obtained through relative relationships with provincial averages and correlation analysis with the indicators. Specifically, Type I and Type IV can be categorized as TP-controlled, Type II and Type III as TC-controlled, and Type V and Type VI as TI-controlled. Finally, we provided typological strategies and key performance indicators (KPIs) relevant to local governments to better achieve carbon reduction goals in each provincial type. It can promote cooperative development and collaborative governance in carbon reduction across regions and the unified implementation of China’s dual-carbon goals.","PeriodicalId":37702,"journal":{"name":"Land","volume":"108 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Inquiry into the Characteristics of Carbon Emissions in Inter-Provincial Transportation in China: Aiming to Typological Strategies for Carbon Reduction in Regional Transportation\",\"authors\":\"Yuhao Yang, Fengying Yan\",\"doi\":\"10.3390/land13010015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The low-carbon development of the transportation sector is crucial for China to achieve its national goals of carbon peaking and carbon neutrality. Since China is a vast country with unbalanced regional development, there are considerable differences in the levels of carbon dioxide emissions from the transportation sector across regions. Therefore, revealing the influencing factors that shape the characteristics of transportation carbon dioxide emissions (TCO2) can inform tailored sub-national carbon reduction strategies based on local conditions, which is an important technical approach for achieving national goals. Based on an extended Kaya identity, we derived indicators of the impacts on provincial TCO2 from factors such as economic development, population density, energy structure, transportation efficiency, technology research and development (R&D), infrastructure construction, transportation operation conditions, and residents’ transportation behavior. Using a multi-indicator joint characterization method, we explored the characteristics of provincial TCO2 in China in 2019. By applying Ward’s method to hierarchical clustering, the thirty provinces of China were classified into six characteristic types (Types I to VI). Based on the total TCO2 (TC), the intensity of TCO2 (TI), and the per capita TCO2 (TP) calculated for each province in 2019, the priority control directions and indicators for carbon reduction in each type were obtained through relative relationships with provincial averages and correlation analysis with the indicators. Specifically, Type I and Type IV can be categorized as TP-controlled, Type II and Type III as TC-controlled, and Type V and Type VI as TI-controlled. Finally, we provided typological strategies and key performance indicators (KPIs) relevant to local governments to better achieve carbon reduction goals in each provincial type. 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引用次数: 0
摘要
交通运输业的低碳发展对于中国实现碳封顶和碳中和的国家目标至关重要。中国幅员辽阔,地区发展不平衡,各地区交通运输业二氧化碳排放水平存在较大差异。因此,揭示形成交通二氧化碳排放(TCO2)特征的影响因素,可以为因地制宜的国家以下碳减排战略提供依据,是实现国家目标的重要技术手段。基于扩展的 Kaya 特性,我们从经济发展、人口密度、能源结构、运输效率、技术研发(R&D)、基础设施建设、交通运行状况和居民交通行为等因素中推导出了对各省 TCO2 的影响指标。我们采用多指标联合表征方法,探讨了 2019 年中国省级总二氧化碳排放量的特征。运用沃德方法进行分层聚类,将中国 30 个省份划分为六种特征类型(类型 I 至 VI)。根据计算出的各省 2019 年总二氧化碳排放量(TC)、总二氧化碳强度(TI)和人均总二氧化碳排放量(TP),通过与各省平均值的相对关系以及与指标的相关性分析,得出各类型的重点控制方向和减碳指标。具体来说,Ⅰ型和Ⅳ型可归为TP控制型,Ⅱ型和Ⅲ型可归为TC控制型,Ⅴ型和Ⅵ型可归为TI控制型。最后,我们提供了与地方政府相关的类型化策略和关键绩效指标(KPI),以更好地实现各省级类型的碳减排目标。这将促进跨区域碳减排的协同发展和协同治理,推动中国双碳目标的统一实施。
An Inquiry into the Characteristics of Carbon Emissions in Inter-Provincial Transportation in China: Aiming to Typological Strategies for Carbon Reduction in Regional Transportation
The low-carbon development of the transportation sector is crucial for China to achieve its national goals of carbon peaking and carbon neutrality. Since China is a vast country with unbalanced regional development, there are considerable differences in the levels of carbon dioxide emissions from the transportation sector across regions. Therefore, revealing the influencing factors that shape the characteristics of transportation carbon dioxide emissions (TCO2) can inform tailored sub-national carbon reduction strategies based on local conditions, which is an important technical approach for achieving national goals. Based on an extended Kaya identity, we derived indicators of the impacts on provincial TCO2 from factors such as economic development, population density, energy structure, transportation efficiency, technology research and development (R&D), infrastructure construction, transportation operation conditions, and residents’ transportation behavior. Using a multi-indicator joint characterization method, we explored the characteristics of provincial TCO2 in China in 2019. By applying Ward’s method to hierarchical clustering, the thirty provinces of China were classified into six characteristic types (Types I to VI). Based on the total TCO2 (TC), the intensity of TCO2 (TI), and the per capita TCO2 (TP) calculated for each province in 2019, the priority control directions and indicators for carbon reduction in each type were obtained through relative relationships with provincial averages and correlation analysis with the indicators. Specifically, Type I and Type IV can be categorized as TP-controlled, Type II and Type III as TC-controlled, and Type V and Type VI as TI-controlled. Finally, we provided typological strategies and key performance indicators (KPIs) relevant to local governments to better achieve carbon reduction goals in each provincial type. It can promote cooperative development and collaborative governance in carbon reduction across regions and the unified implementation of China’s dual-carbon goals.
LandENVIRONMENTAL STUDIES-Nature and Landscape Conservation
CiteScore
4.90
自引率
23.10%
发文量
1927
期刊介绍:
Land is an international and cross-disciplinary, peer-reviewed, open access journal of land system science, landscape, soil–sediment–water systems, urban study, land–climate interactions, water–energy–land–food (WELF) nexus, biodiversity research and health nexus, land modelling and data processing, ecosystem services, and multifunctionality and sustainability etc., published monthly online by MDPI. The International Association for Landscape Ecology (IALE), European Land-use Institute (ELI), and Landscape Institute (LI) are affiliated with Land, and their members receive a discount on the article processing charge.