Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Differential spatial-temporal responses of carbon dioxide emissions to economic development: empirical evidence based on spatial analysis
https://orcid.org/0000-0001-9357-6778
Abstract Despite the heated debate over the relationship between economic development and carbon dioxide ($ CO_{2} $) emissions, few studies have focused on the impact of spatial relationships between neighboring countries on $ CO_{2} $ emissions. Adopting the World Bank’s classification of income levels, this paper classifies 177 countries into four groups and then analyzes the spatial-temporal variations in $ CO_{2} $ emissions. Based on that analysis, the core task of our study is to estimate a carbon Kuznets curve (CKC) from two methods of traditional statistics and spatial econometrics. The main findings indicate that global $ CO_{2} $ emissions have significant spatial clustering characteristics, and the clustering types are closely linked to geographic location and income level. In addition, the existence of standard CKC and spatial CKC were confirmed. Countries with different income levels have different $ CO_{2} $ emission stages, and a country’s $ CO_{2} $ emissions are affected both directly by its own economy and indirectly by the economies of its neighbors. In this context, the mitigation and adaptation strategies for $ CO_{2} $ reduction are proposed as follows. (1) Neighboring countries must develop regional cooperative initiatives to reduce $ CO_{2} $ emissions. (2) Clarifying the emission stage of a country is an important basis for policymakers to formulate emission reduction strategies. (3) The economic development and $ CO_{2} $ emissions of neighboring countries are also important factors in formulating emission reduction plans.
Differential spatial-temporal responses of carbon dioxide emissions to economic development: empirical evidence based on spatial analysis
https://orcid.org/0000-0001-9357-6778
Abstract Despite the heated debate over the relationship between economic development and carbon dioxide ($ CO_{2} $) emissions, few studies have focused on the impact of spatial relationships between neighboring countries on $ CO_{2} $ emissions. Adopting the World Bank’s classification of income levels, this paper classifies 177 countries into four groups and then analyzes the spatial-temporal variations in $ CO_{2} $ emissions. Based on that analysis, the core task of our study is to estimate a carbon Kuznets curve (CKC) from two methods of traditional statistics and spatial econometrics. The main findings indicate that global $ CO_{2} $ emissions have significant spatial clustering characteristics, and the clustering types are closely linked to geographic location and income level. In addition, the existence of standard CKC and spatial CKC were confirmed. Countries with different income levels have different $ CO_{2} $ emission stages, and a country’s $ CO_{2} $ emissions are affected both directly by its own economy and indirectly by the economies of its neighbors. In this context, the mitigation and adaptation strategies for $ CO_{2} $ reduction are proposed as follows. (1) Neighboring countries must develop regional cooperative initiatives to reduce $ CO_{2} $ emissions. (2) Clarifying the emission stage of a country is an important basis for policymakers to formulate emission reduction strategies. (3) The economic development and $ CO_{2} $ emissions of neighboring countries are also important factors in formulating emission reduction plans.
Differential spatial-temporal responses of carbon dioxide emissions to economic development: empirical evidence based on spatial analysis
https://orcid.org/0000-0001-9357-6778
Abstract Despite the heated debate over the relationship between economic development and carbon dioxide ($ CO_{2} $) emissions, few studies have focused on the impact of spatial relationships between neighboring countries on $ CO_{2} $ emissions. Adopting the World Bank’s classification of income levels, this paper classifies 177 countries into four groups and then analyzes the spatial-temporal variations in $ CO_{2} $ emissions. Based on that analysis, the core task of our study is to estimate a carbon Kuznets curve (CKC) from two methods of traditional statistics and spatial econometrics. The main findings indicate that global $ CO_{2} $ emissions have significant spatial clustering characteristics, and the clustering types are closely linked to geographic location and income level. In addition, the existence of standard CKC and spatial CKC were confirmed. Countries with different income levels have different $ CO_{2} $ emission stages, and a country’s $ CO_{2} $ emissions are affected both directly by its own economy and indirectly by the economies of its neighbors. In this context, the mitigation and adaptation strategies for $ CO_{2} $ reduction are proposed as follows. (1) Neighboring countries must develop regional cooperative initiatives to reduce $ CO_{2} $ emissions. (2) Clarifying the emission stage of a country is an important basis for policymakers to formulate emission reduction strategies. (3) The economic development and $ CO_{2} $ emissions of neighboring countries are also important factors in formulating emission reduction plans.
Differential spatial-temporal responses of carbon dioxide emissions to economic development: empirical evidence based on spatial analysis
Wang, Ke (Autor:in) / Zhang, Jianjun (Autor:in) / Geng, Yuhuan (Autor:in) / Xiao, Lianxiang (Autor:in) / Xu, Ze (Autor:in) / Rao, Yongheng (Autor:in) / Zhou, Xiangli (Autor:in)
2019
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
BKL:
43.47
Globale Umweltprobleme
/
43.47$jGlobale Umweltprobleme
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