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A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China

机译:对中国人均家庭二氧化碳排放量(HCE)多个贡献者的混合研究

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摘要

Given the large expenditures by households on goods and services that contribute a large proportion of global CO2 emissions, increasing attention has been paid to household CO2 emissions (HCEs). However, compared with industrial CO2 emissions, efforts devoted to mitigating HCEs are relatively small. A good understanding of the effects of some driving factors (i.e., urbanization rate, per capita GDP, per capita income/disposable income, Engel coefficient, new energy ratio, carbon intensity, and household size) is urgently needed prior to considering policies for reducing HCEs. Given this, in the study, the direct and indirect per capita HCEs were quantified in rural and urban areas of China over the period 2000-2012. Correlation analysis and gray correlation analysis were initially used to identify the prime drivers of per capita HCEs. Our results showed that per capita income/disposable income, per capita GDP, urbanization rate, and household size were the most significantly correlated with per capita HCEs in rural areas. Moreover, the conjoint effects of the potential driving factors on per capita HCEs were determined by performing principal component regression analysis for all cases. Based on the combined analysis strategies, alternative polices were also examined for controlling and mitigating HCEs growth in China.
机译:鉴于家庭在商品和服务上的大量支出占全球CO2排放量的很大比例,人们对家庭CO2排放量(HCE)的关注日益增加。但是,与工业CO2排放相比,致力于减少HCE的努力相对较小。在考虑采取减少排放的政策之前,迫切需要对一些驱动因素(例如,城市化率,人均GDP,人均收入/可支配收入,恩格尔系数,新能源比率,碳强度和家庭规模)的影响有充分的了解。 HCE。鉴于此,在本研究中,对2000-2012年期间中国农村和城市地区的直接和间接人均HCE进行了量化。最初使用相关分析和灰色相关分析来确定人均HCE的主要驱动因素。我们的结果表明,农村地区的人均收入/可支配收入,人均GDP,城市化率和家庭规模与人均HCE关联最密切。此外,通过对所有病例进行主成分回归分析,确定了潜在驱动因素对人均HCE的联合影响。在综合分析策略的基础上,还研究了替代策略,以控制和缓解中国HCE的增长。

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