Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China.
Sci Total Environ. 2019 Feb 10;650(Pt 2):2021-2031. doi: 10.1016/j.scitotenv.2018.09.304. Epub 2018 Sep 24.
This study comprehensively investigated the impacts of demographic structure on CO emissions in China at the national level and the regional level for the first time. Panel cointegration modeling was employed to test the long-run relationships between CO emissions and six demographic structure variables, namely, dependency ratio, sex ratio, higher education ratio, industrial employment ratio, urbanization ratio, and average household size. The fully modified ordinary least squares method was then applied to estimate the long-run elasticity of CO emissions for the six demographic structure variables. The results suggested that long-run relationships between CO emissions and demographic structure existed at both the national level and the regional level. Dependency ratio was found to exert negative effects on CO emissions in China and its three sub-regions. Positive associations between sex ratio and CO emissions were revealed to exist in China and West China, and CO emissions elasticity for sex ratio was relatively high in West China. Higher education ratio had a positive effect on CO emissions in East China. Industrial employment ratio was found to positively correlate with CO emissions in China, East China, and Central China. Urbanization ratio was demonstrated to increase CO emissions at the national level and the regional level, and CO emissions elasticity for urbanization ratio decreased from West China to Central China, and then to East China. Negative correlations between average household size and CO emissions were detected at both the national level and the regional level. Based on the findings of this study, several practical recommendations were proposed, including optimizing age structure, promoting gender equality, advocating low-carbon lifestyles and low-carbon consumption patterns, promoting industrial upgrading and industrial structure optimization, building low-carbon cities and less carbon-intensive public infrastructure systems, and improving residential energy efficiency.
本研究首次综合考察了人口结构对中国国家和区域层面 CO 排放的影响。面板协整模型被用来检验 CO 排放与六个人口结构变量（抚养比、性别比、高等教育比例、工业就业比例、城市化率和平均家庭规模）之间的长期关系。然后，采用全修正最小二乘法估计了六个人口结构变量对 CO 排放的长期弹性。结果表明，CO 排放与人口结构之间存在长期关系，无论是在国家层面还是在区域层面。抚养比对中国及其三个子区域的 CO 排放产生负向影响。性别比对中国和西部地区的 CO 排放呈正相关，西部地区性别比与 CO 排放的弹性相对较高。高等教育比例对中国东部地区的 CO 排放有正向影响。工业就业比例与中国、中国东部和中国中部的 CO 排放呈正相关。城市化率在国家和区域层面都被证明会增加 CO 排放，城市化率与 CO 排放的弹性从西部地区到中部地区再到东部地区逐渐降低。平均家庭规模与 CO 排放之间在国家和区域层面都呈负相关。基于本研究的结果，提出了一些实际建议，包括优化年龄结构、促进性别平等、倡导低碳生活方式和低碳消费模式、推动产业升级和产业结构优化、建设低碳城市和减少碳排放的公共基础设施系统、提高居民能源效率。
