Global warming is recently an urgent issue worldwide. The increase of carbon emissions induced by human economic activi- ties has become a major driving force behind global climate change. Thus, as a matter of social ...Global warming is recently an urgent issue worldwide. The increase of carbon emissions induced by human economic activi- ties has become a major driving force behind global climate change. Thus, as a matter of social responsibility, reasonable carbon con- straints should be implemented to ensure environmental security and sustainable development for every country. Based on a summary of studies that examined the relationship between carbon emissions and regional development, this paper shows that human activity-led carbon emission is caused by the combination of several influencing factors, including population size, income level, and technical pro- gress. Thus, a quantitative model derived from IPAT-ImPACT-Kaya series and STIRPAT models was established. Empirical analysis using multivariate nonlinear regression demonstrated that the origins of growing global carbon emission included the increasing influ- encing elasticity of the population size and the declining negative effect of technical progress. Meanwhile, in context of classification of country groups at different income levels, according to the comparison of fluctuating patterns of the influencing elasticity, technical progress was found as the main factor influencing carbon emission levels in high-income countries, and population size might he the controlling factor in middle-income countries. However, for low-income countries, the nonlinear relationship between carbon emission and its influencing factors was not significant, whereas population growth was identified as an important potential driving force in future carbon emissions. This study can therefore provide a reference for the formulation of policies on carbon constraints, especially to de- velop more efficient carbon mitigating policies for countries at different income levels.展开更多
基金Under the auspices of Major State Basic Research Development Program of China(No.2012CB955802)National Natural Science Foundation of China(No.41171099)Strategy of Public Participation of Low Carbon Development in China(No.201315)
文摘Global warming is recently an urgent issue worldwide. The increase of carbon emissions induced by human economic activi- ties has become a major driving force behind global climate change. Thus, as a matter of social responsibility, reasonable carbon con- straints should be implemented to ensure environmental security and sustainable development for every country. Based on a summary of studies that examined the relationship between carbon emissions and regional development, this paper shows that human activity-led carbon emission is caused by the combination of several influencing factors, including population size, income level, and technical pro- gress. Thus, a quantitative model derived from IPAT-ImPACT-Kaya series and STIRPAT models was established. Empirical analysis using multivariate nonlinear regression demonstrated that the origins of growing global carbon emission included the increasing influ- encing elasticity of the population size and the declining negative effect of technical progress. Meanwhile, in context of classification of country groups at different income levels, according to the comparison of fluctuating patterns of the influencing elasticity, technical progress was found as the main factor influencing carbon emission levels in high-income countries, and population size might he the controlling factor in middle-income countries. However, for low-income countries, the nonlinear relationship between carbon emission and its influencing factors was not significant, whereas population growth was identified as an important potential driving force in future carbon emissions. This study can therefore provide a reference for the formulation of policies on carbon constraints, especially to de- velop more efficient carbon mitigating policies for countries at different income levels.
