摘要
论文基于资源环境视角,通过构建绿色GDP核算体系对1997—2013年中国及大陆31个省(市、自治区)的绿色GDP进行核算,并进一步通过人均绿色GDP及绿色GDP指数揭示地区绿色发展现状差异。研究结果表明:1)中国在1997—2013年间绿色GDP指数为78.99~87.06,经济发展对自然资源尤其是能源资源依赖度较高。指数呈波动上升趋势,资源节约效果显著,环境污染管治仍需加强。2)区域差异上,人均绿色GDP与绿色GDP指数均呈东部地区>中部地区>西部地区的格局,即经济发展水平较好地区其资源环境依赖性也较低。3)将全国进行绿色发展分区后,处于健康区的省市有10个,潜力区5个,高危区10个,警戒区6个。绿色发展健康区主要覆盖于东部沿海地区,而中西部内陆省市为绿色发展高危区的主要覆盖区。
In the view of natural resources and environment, a green GDP index system was constructed, and the green GDP in the mainland of China from 1997 to 2013 was calculated on the national and provincial levels. Furthermore, through the per capita green GDP and green GDP index, the regional differences of green development were revealed. The results showed that the green GDP index was 78.99-87.06 in China from 1997 to 2013. Economic development depended greatly on natural resources, especially energy resources. The index appeared a rising trend showing remarkable resource saving effect. However, environmental pollution governance still needs to be strengthened. From the view of regions, the per capita green GDP and green GDP index presented the same pattern of spatial difference which is East ChinaCentral ChinaWest China. It meant that the more developed regions depended less on resources and environment. Dividing provinces into groups with green development, there were 10 healthy provinces, 5 potential provinces, 10 high-risk provinces and 6 provinces on alert.Health provinces mainly distribute in the eastern coastal regions, while high-risk provinces are mainly in the inland area in the midwest.
作者
沈晓艳
王广洪
黄贤金
SHEN Xiao-yan WANG Guang-hong HUANG Xian-jin(School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China The Research Base of Jiangsu Green Development, Nanjing University, Nanjing 210023, China)
出处
《自然资源学报》
CSSCI
CSCD
北大核心
2017年第10期1639-1650,共12页
Journal of Natural Resources
基金
国家自然科学基金项目(41571162)
江苏高校人文社会科学研究重点项目(2014ZDAM001)
中国清洁发展机制基金赠款项目(1214073)~~
关键词
绿色GDP
核算体系
资源环境损失
区域差异
中国
green GDP
accounting system
losses of resources and environment
spatial pattern
China