Using energy consumption and land use data of each region of China in 2007, this paper established carbon emission and carbon footprint model based on energy consumption and estimated the carbon emission amount of fos...Using energy consumption and land use data of each region of China in 2007, this paper established carbon emission and carbon footprint model based on energy consumption and estimated the carbon emission amount of fossil energy and rural biomass energy of dif- ferent regions of China in 2007. Through matching the energy consumption items with industrial spaces, this paper divided industrial spaces into five types： agricultural space, living ＆ industrial-commercial space, transportation industrial space, fishery and water conservancy space, and other industrial space. Then the author analyzed the carbon emission intensity and carbon footprint of each industrial space. Finally, advices of decreasing industrial carbon footprint and optimizing industrial space pattern were put forward. The main conclusions are as following： （1） Total amount of carbon emission from energy consumption of China in 2007 was about 1.65 GtC, in which the proportion of carbon emission from fossil energy was 89%. （2） Carbon emission intensity of industrial space of China in 2007 was 1.98 t/hm^2, in which, carbon emission intensity of living ＆ industrial-commercial space and of transportation industrial space was 55.16 t/hm^2 and 49.65 t/hm^2 respectively, they were high-carbon-emission industrial spaces among others. （3） Carbon footprint caused by industrial activities of China in 2007 was 522.34×10^6 hm^2, which brought about ecological deficit of 28.69×10^6 hm^2, which means that the productive lands were not sufficient to compensate for carbon footprint of industrial activities, and the compensating rate was 94.5%. As to the regional carbon footprint several regions have ecological profit while others have not. In general, the present ecological deficit caused by industrial activities was small in 2007. （4） Per unit area carbon footprint of industrial space in China was about 0.63 hm^2/hm^2 in 2007, in which that of living ＆ industrial-commercial space was the highest （17.5 hm^2/hm^2）. The per unit area carbon footprint of different industrial spaces all presented a declining trend from east to west of China.展开更多
Based on energy consumption data of each region in China from 1997 to 2009 and using ArcGIS9.3 and GeoDA9.5 as technical support, this paper made a preliminary study on the changing trend of spatial pattern at regiona...Based on energy consumption data of each region in China from 1997 to 2009 and using ArcGIS9.3 and GeoDA9.5 as technical support, this paper made a preliminary study on the changing trend of spatial pattern at regional level of carbon emissions from energy consumption, spatial autocorrelation analysis of carbon emissions, spatial regression analysis between carbon emissions and their influencing factors. The analyzed results are shown as follows. （1） Carbon emissions from energy consumption increased more than 148% from 1997 to 2009 but the spatial pattern of high and low emission regions did not change greatly. （2） The global spatial autocorrelation of carbon emissions from energy consumption in- creased from 1997 to 2009, the spatial autocorrelation analysis showed that there exists a ＂polarization＂ phenomenon, the centre of ＂High-High＂ agglomeration did not change greatly but expanded currently, the centre of ＂Low-Low＂ agglomeration also did not change greatly but narrowed currently. （3） The spatial regression analysis showed that carbon emissions from energy consumption has a close relationship with GDP and population, R-squared rate of the spatial regression between carbon emissions and GDP is higher than that between carbon emissions and population. The contribution of population to carbon emissions increased but the contribution of GDP decreased from 1997 to 2009. The carbon emissions spillover effect was aggravated from 1997 to 2009 due to both the increase of GDP and population, so GDP and population were the two main factors which had strengthened the spatial autocorrelation of carbon emissions.展开更多
基金National Social Science Foundation of China, No.10ZD＆M030 Non-profit Industry Financial Program of Ministry of Land and Resources of China, No.200811033 Environment Protection Scientific Foundation of Jiangsu Province, China, No.2009037Acknowledgements This paper obtained valuable revising comments and suggestions from reviewers. Dr. Zhang Xingyu and Dr. Jiao Shixing gave inspiring comments on paper ideas and calculation. Sun Zhenru helped to draw the illustrations. We would like to express our gratitude for their supports.
文摘Using energy consumption and land use data of each region of China in 2007, this paper established carbon emission and carbon footprint model based on energy consumption and estimated the carbon emission amount of fossil energy and rural biomass energy of dif- ferent regions of China in 2007. Through matching the energy consumption items with industrial spaces, this paper divided industrial spaces into five types： agricultural space, living ＆ industrial-commercial space, transportation industrial space, fishery and water conservancy space, and other industrial space. Then the author analyzed the carbon emission intensity and carbon footprint of each industrial space. Finally, advices of decreasing industrial carbon footprint and optimizing industrial space pattern were put forward. The main conclusions are as following： （1） Total amount of carbon emission from energy consumption of China in 2007 was about 1.65 GtC, in which the proportion of carbon emission from fossil energy was 89%. （2） Carbon emission intensity of industrial space of China in 2007 was 1.98 t/hm^2, in which, carbon emission intensity of living ＆ industrial-commercial space and of transportation industrial space was 55.16 t/hm^2 and 49.65 t/hm^2 respectively, they were high-carbon-emission industrial spaces among others. （3） Carbon footprint caused by industrial activities of China in 2007 was 522.34×10^6 hm^2, which brought about ecological deficit of 28.69×10^6 hm^2, which means that the productive lands were not sufficient to compensate for carbon footprint of industrial activities, and the compensating rate was 94.5%. As to the regional carbon footprint several regions have ecological profit while others have not. In general, the present ecological deficit caused by industrial activities was small in 2007. （4） Per unit area carbon footprint of industrial space in China was about 0.63 hm^2/hm^2 in 2007, in which that of living ＆ industrial-commercial space was the highest （17.5 hm^2/hm^2）. The per unit area carbon footprint of different industrial spaces all presented a declining trend from east to west of China.
基金Foundation： National Social Science Foundation of China, No.10ZD＆M030 Non-profit Industry Financial Program of Ministry of Land and Resources of China, No.200811033+2 种基金 A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions National Natural Science Foundation of China, No.40801063 No.40971104
文摘Based on energy consumption data of each region in China from 1997 to 2009 and using ArcGIS9.3 and GeoDA9.5 as technical support, this paper made a preliminary study on the changing trend of spatial pattern at regional level of carbon emissions from energy consumption, spatial autocorrelation analysis of carbon emissions, spatial regression analysis between carbon emissions and their influencing factors. The analyzed results are shown as follows. （1） Carbon emissions from energy consumption increased more than 148% from 1997 to 2009 but the spatial pattern of high and low emission regions did not change greatly. （2） The global spatial autocorrelation of carbon emissions from energy consumption in- creased from 1997 to 2009, the spatial autocorrelation analysis showed that there exists a ＂polarization＂ phenomenon, the centre of ＂High-High＂ agglomeration did not change greatly but expanded currently, the centre of ＂Low-Low＂ agglomeration also did not change greatly but narrowed currently. （3） The spatial regression analysis showed that carbon emissions from energy consumption has a close relationship with GDP and population, R-squared rate of the spatial regression between carbon emissions and GDP is higher than that between carbon emissions and population. The contribution of population to carbon emissions increased but the contribution of GDP decreased from 1997 to 2009. The carbon emissions spillover effect was aggravated from 1997 to 2009 due to both the increase of GDP and population, so GDP and population were the two main factors which had strengthened the spatial autocorrelation of carbon emissions.
