4.7 Article

Carbon sources/sinks analysis of land use changes in China based on data envelopment analysis

期刊

JOURNAL OF CLEANER PRODUCTION
卷 204, 期 -, 页码 702-711

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.08.341

关键词

Carbon emission efficiency; Land use changes; DEA; China

资金

  1. National Key Research and Development Program of China [2016YFA0602500]
  2. National Natural Science Foundation of China [41601175]
  3. key scientific research project of Henan province [16A610001]
  4. Program for Innovative Research Team (in Science and Technology) in University of Henan Province [16IRTSTHN012]

向作者/读者索取更多资源

China's recent rapid socioeconomic development has caused its land use patterns to evolve rapidly. Land use changes are significantly influencing carbon emissions in China. Thus, assessing carbon emissions from land use change patterns is significant for sustainable socioeconomic and ecological development. This study applied a geographic information system and data envelopment analysis (DEA) to estimate provincial-level carbon emission efficiency in China during 1999-2014. The results indicate that China's total carbon emissions and carbon sequestration from land use showed annual rising trends but with an increasing difference in growth. At provincial level, the highest provincial emissions were 3-4 times greater than the lowest. In addition, carbon sources increased 20 times faster than carbon sinks. The contribution of carbon emissions from construction land to total carbon emissions was greater than 90%, also, the contribution of carbon sinks from forest land to total carbon sinks was greater than 90%; Carbon emissions were most intensive in Northeast China, and they gradually decreased in a radiating pattern to the north, west, and south. Among 31 provinces, only Qinghai, Inner Mongolia, Yunnan, Guangxi, and Heilongjiang showed effective reductions in carbon emissions. The spatial disparities in carbon emissions were likely due to differences in technological efficiency and scale of operation. (C) 2018 Elsevier Ltd. All rights reserved.

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