Based on the theory of emergy analysis,a modified model of ecological footprint accounting,termed emergetic ecological footprint(EMEF)in contrast to the conventional ecological footprint(EF)model,is formulated and app...Based on the theory of emergy analysis,a modified model of ecological footprint accounting,termed emergetic ecological footprint(EMEF)in contrast to the conventional ecological footprint(EF)model,is formulated and applied to a case study of Jiangsu cropland,China.Comparisons between the EF and the EMEF with respect to grain,cotton,and food oil were outlined.Per capita EF and EMEF of cropland were also presented to depict the resources consumption level by comparing the biocapacity(BC)or emergetic biocapacity(EMBC,a new BC calculation by emergy analysis) of the same area.In the meanwhile,the ecological sustainability index(ESI),a new concept initiated by the authors, was established in the modified model to indicate and compare the sustainability of cropland use at different levels and between different regions.The results from conventional EF showed that per capita EF of the cropland has exceeded its per capita BC in Jiangsu since 1986.In contrast,based on the EMBC,the per capita EMEF exceeded the per capita EMBC 5 years earlier.The ESIs of Jiangsu cropland use were between 0.7 and 0.4 by the conventional method,while the numbers were between 0.7 and 0.3 by the modified one.The fact that the results of the two methods were similar showed that the modified model was reasonable and feasible,although some principles of the EF and EMEF were quite different. Also,according to the realities of Jiangsu cropland use,the results from the modified model were more acceptable.展开更多
The Ecological Footprint(EF) equation provides useful accounting to analyze the relationship between human activities and the environment.Knowledge of the specific forces driving EF is not fully understood but the STI...The Ecological Footprint(EF) equation provides useful accounting to analyze the relationship between human activities and the environment.Knowledge of the specific forces driving EF is not fully understood but the STIRPAT model provides a simple framework for decomposing the impact of human activities on environment.We applied the EF model in Sichuan Province,China to assess the impact of human activities.The per capita EF increased by 2 fold in the 14 years between 1995 and 2008,but ecological capacity decreased in the same period,suggesting that the biologically productive area of Sichuan Province is inadequate to sustain human activities.According to the refined STIRPAT model,the hypothesized driving forces of EF include population size(P),GDP per capita(A1),quadratic term of GDP per capita(A2),percentage of GDP from industry(T1) and urbanization rate(T2).However,the multi-collinearity among these drivers could be a substantial problem which may reveal negative effect in the final results.Application of the Ridge Regression(RR) method to fit the STIRPAT model had the advantage of being able to avoid the collinearity among independent variables.The results showed that population is the principal driving force of EF variation in Sichuan Province and that urbanization and industrialization also have a positive association with the EF.Analysis of affluence elasticity(EEA) showed that the relationship betweenEF and economic growth was not curvilinear,suggesting that variation of EF does not follow an Environmental Kuznets Curve relative to economic growth in Sichuan Province.展开更多
Global warming has been one of the major concerns behind the world＇s high-speed economic growth. How to implement the coordinated development of the carbon footprint and the economy will be the core issue of the worl...Global warming has been one of the major concerns behind the world＇s high-speed economic growth. How to implement the coordinated development of the carbon footprint and the economy will be the core issue of the world＇s economic and social development, as well as the heated debate of the research at home and abroad in recent years. Based on the energy consumption, integrated with the ＂Top-Down＂ life cycle approach and geographically weighted regression （GWR） model, this paper analyzed the spatial differences and multi-mechanism of carbon footprint in provincial China in 2010. Firstly, this study calculated the amount of carbon footprint of each province using ＂Top-Down＂ life cycle approach and found that there were significant differences of carbon footprint and per capita carbon footprint in provincial China. The provinces with higher carbon footprint, mainly located in northern China, have large economic scales; the provinces with higher per capita carbon footprint are mainly distributed in central cities such as Beijing, Shanghai and energy-rich regions and heavy chemical bases. Secondly, with the aid of GIS and spatial analysis model （GWR model）, this paper had unfolded that the expansion of economic scale is the main driver of the rapid growth of carbon footprint. The growth of population and urbanization also acted as promoting factors for the increase of the carbon footprint. Energy structure had no considerable promoting effect for the increase of the carbon footprint. Improving energy efficiency is the most important factor to inhibit the growing carbon footprint. Thirdly, developing low-carbon economies and low-carbon industries, as well as advocating low-carbon city construction and improving carbon efficiency would be the primary approaches to inhibit the rapid growth of carbon footprint. Moderately controlling the economic scale and population size would also be required to alleviate carbon footprint. Meanwhile, environmental protection and construction of low-carbon cities would evoke extensive attention in the process of urbanization.展开更多
In the urbanizing world,the Yangtze Delta Region （YDR） as one of the most developed regions in China,has drawn a lot of the world＇s attention for the remarkable economic development achieved in the past decades.Nev...In the urbanizing world,the Yangtze Delta Region （YDR） as one of the most developed regions in China,has drawn a lot of the world＇s attention for the remarkable economic development achieved in the past decades.Nevertheless,the rapid economic development was certain to be accompanied by unprecedented consumption and loss of natural resources.Therefore,the analysis of the ecological situation and driving factors of environmental impact was of great significance to serve the local sustainable development decision-making and build a harmonious society.In this paper,the ecological footprint （EF） was taken as the index of the ecological environmental impact.With the help of Geographic Information System （GIS）,we studied the spatiotemporal change of ecological footprint at two scales （region and city） and assessed urban sustainable development ability in YDR.Then we discussed the driving factors that affected the change of ecological footprint by the Stochastic Impacts by Regression on Population,Affluence,and Technology （STIRPAT） model.The results showed that increasing trends of regional ecological footprint during 1998-2008 （1.70-2.53 ha/cap） were accompanied by decreasing ecological capacity （0.31-0.25 ha/cap） but expanding ecological deficit （1.39-2.28 ha/cap）.The distribution pattern of ecological footprint and the degree of sustainable development varied distinctly from city to city in YDR.In 2008,the highest values of ecological footprint （3.85 ha/cap） and the lowest one of sustainable development index （SDI=1） in YDR were both presented in Shanghai.GDP per capita （A） was the most dominant driving force of EF and the classical EKC hypothesis did not exist between A and EF in 1998-2008.Consequently,increasing in ecological supply and reducing in human demand due to technological advances or other factors were one of the most effective ways to promote sustainable development in YDR.Moreover,importance should be attached to change our definition and measurement of prosperity and success.展开更多
A nonlinear dynamic simulative model has been discussed with variable cycles of entire world per capita ecological footprint taken from 1961 to 2003. The model was further classified and decomposed and extracted by th...A nonlinear dynamic simulative model has been discussed with variable cycles of entire world per capita ecological footprint taken from 1961 to 2003. The model was further classified and decomposed and extracted by the empirical mode decomposition (EMD) method. To deal with the problems proposed in the Living Planet Report 2006, three ecological footprint scenarios are presented. Simulative numerical values of the three global per capita (GPC) ecological footprint scenarios are also analyzed based on the simulative model. The results show that: 1) The clear varying cycle of global per capita EF growth is 4.6 years, 9.5 years, 19.5 years and 41 years over the last 42 years;2) According to the business-as-usual scenario, if the global per capita increases positively with the constant growth, it is expected that GPC EF would be 3.262 gha in 2050. Assuming global per capita biocapacity (BC) to be 1.236 gha, global per capita ecological deficit (ED) would increase from 0.4 gha in 2003 to 2.026 gha in 2050;3) The slow-shift scenario shows global per capita EF would decrease from 2.23 gha in 2003 to 1.619 gha in 2080 and 1.406 gha in 2100, if the negative annual change rate of it is 0.447 percent. Global per capita ED would decrease from 0.4 gha in 2003 to 0.222 gha in 2080 and 0.038 gha in 2100, if global per capita BC is 1.397 gha;4) The rapid-reduction scenario depicts global per capita EF would decrease to 1.414 gha in 2050, if the negative annual change rate is 0.842% from 2003 to 2050. Assuming global per capita BC to be 1.461 gha, global per capita ecological reserve (ER) would be 0.047 gha, and overshoot would be eliminated in 2050. Global per capita EF would decrease to 1.054 gha in 2100, if the negative annual change rate is 0.438% from 2050 to 2100. Assuming global per capita BC to be 1.474 gha, GPC ER would be 0.420 gha. Then, wild species of the planet will be allocated nearly 28.5% of the planet’s biological productivity, which coincides with the results of Living Planet Report 2006.展开更多
Heat flux data collected from the Baiyangdian Heterogeneous Field Experiment were analyzed using the footprint method. High resolution （25 m） Landsat-5 satellite imaging was used to determine the land cover as one o...Heat flux data collected from the Baiyangdian Heterogeneous Field Experiment were analyzed using the footprint method. High resolution （25 m） Landsat-5 satellite imaging was used to determine the land cover as one of four surface types： farmland, lake, wetland, or village. Data from two observation sites in September 2005 were used. One site （Wangjiazhai） was characterized by highly heterogeneous surfaces in the central area of the Baiyangdian： lake/wetland. The other site （Xiongxian） was on land with more uniform surface cover. An improved Eulerian analytical flux footprint model was used to determine “source areas” of the heat fluxes measured at towers located at each site from surrounding landscapes of mixed surface types. In relative terms results show that wetland and lake areas generally contributed most to the observed heat flux at Wangjiazhai, while farmland contributed most at Xiongxian. Given the areal distribution of surface type contributions, calculations were made to obtain the magnitudes of the heat flux from lake, wetland and farmland to the total observed flux and apportioned contributions of each surface type to the sensible and latent heat fluxes. Results show that on average the sensible heat flux from wetland and farmland were comparable over the diurnal cycle, while the latent heat flux from farmland was somewhat larger by about 30-50 W m-2 during daytime. The latent and sensible fluxes from the lake source in daytime were about 50 W m-2 and 100 W m-2 less, respectively, than from wetland and farmland. The results are judged reasonable and serve to demonstrate the potential for flux apportionment over heterogeneous surfaces.展开更多
基金the National Natural Science Foundation of China(No.40401059)the Natural Science Foundation of the Education Department of Jiangsu Province(No.07KJD170123)the Natural Science Foundation of Nanjing Xiaozhuang University(No.2007NXY06)
文摘Based on the theory of emergy analysis,a modified model of ecological footprint accounting,termed emergetic ecological footprint(EMEF)in contrast to the conventional ecological footprint(EF)model,is formulated and applied to a case study of Jiangsu cropland,China.Comparisons between the EF and the EMEF with respect to grain,cotton,and food oil were outlined.Per capita EF and EMEF of cropland were also presented to depict the resources consumption level by comparing the biocapacity(BC)or emergetic biocapacity(EMBC,a new BC calculation by emergy analysis) of the same area.In the meanwhile,the ecological sustainability index(ESI),a new concept initiated by the authors, was established in the modified model to indicate and compare the sustainability of cropland use at different levels and between different regions.The results from conventional EF showed that per capita EF of the cropland has exceeded its per capita BC in Jiangsu since 1986.In contrast,based on the EMBC,the per capita EMEF exceeded the per capita EMBC 5 years earlier.The ESIs of Jiangsu cropland use were between 0.7 and 0.4 by the conventional method,while the numbers were between 0.7 and 0.3 by the modified one.The fact that the results of the two methods were similar showed that the modified model was reasonable and feasible,although some principles of the EF and EMEF were quite different. Also,according to the realities of Jiangsu cropland use,the results from the modified model were more acceptable.
基金funded by the Knowledge Innovation Project of the Chinese Academy of Sciences(Grant No.KZCX2-YW-333)the National Natural Science Foundation of China(Grant No.40901299)
文摘The Ecological Footprint(EF) equation provides useful accounting to analyze the relationship between human activities and the environment.Knowledge of the specific forces driving EF is not fully understood but the STIRPAT model provides a simple framework for decomposing the impact of human activities on environment.We applied the EF model in Sichuan Province,China to assess the impact of human activities.The per capita EF increased by 2 fold in the 14 years between 1995 and 2008,but ecological capacity decreased in the same period,suggesting that the biologically productive area of Sichuan Province is inadequate to sustain human activities.According to the refined STIRPAT model,the hypothesized driving forces of EF include population size(P),GDP per capita(A1),quadratic term of GDP per capita(A2),percentage of GDP from industry(T1) and urbanization rate(T2).However,the multi-collinearity among these drivers could be a substantial problem which may reveal negative effect in the final results.Application of the Ridge Regression(RR) method to fit the STIRPAT model had the advantage of being able to avoid the collinearity among independent variables.The results showed that population is the principal driving force of EF variation in Sichuan Province and that urbanization and industrialization also have a positive association with the EF.Analysis of affluence elasticity(EEA) showed that the relationship betweenEF and economic growth was not curvilinear,suggesting that variation of EF does not follow an Environmental Kuznets Curve relative to economic growth in Sichuan Province.
基金National Natural Science Foundation of China, No.41371177 Major Program of National Social Science Foundation of China, No. 13＆ZD027
文摘Global warming has been one of the major concerns behind the world＇s high-speed economic growth. How to implement the coordinated development of the carbon footprint and the economy will be the core issue of the world＇s economic and social development, as well as the heated debate of the research at home and abroad in recent years. Based on the energy consumption, integrated with the ＂Top-Down＂ life cycle approach and geographically weighted regression （GWR） model, this paper analyzed the spatial differences and multi-mechanism of carbon footprint in provincial China in 2010. Firstly, this study calculated the amount of carbon footprint of each province using ＂Top-Down＂ life cycle approach and found that there were significant differences of carbon footprint and per capita carbon footprint in provincial China. The provinces with higher carbon footprint, mainly located in northern China, have large economic scales; the provinces with higher per capita carbon footprint are mainly distributed in central cities such as Beijing, Shanghai and energy-rich regions and heavy chemical bases. Secondly, with the aid of GIS and spatial analysis model （GWR model）, this paper had unfolded that the expansion of economic scale is the main driver of the rapid growth of carbon footprint. The growth of population and urbanization also acted as promoting factors for the increase of the carbon footprint. Energy structure had no considerable promoting effect for the increase of the carbon footprint. Improving energy efficiency is the most important factor to inhibit the growing carbon footprint. Thirdly, developing low-carbon economies and low-carbon industries, as well as advocating low-carbon city construction and improving carbon efficiency would be the primary approaches to inhibit the rapid growth of carbon footprint. Moderately controlling the economic scale and population size would also be required to alleviate carbon footprint. Meanwhile, environmental protection and construction of low-carbon cities would evoke extensive attention in the process of urbanization.
基金National Natural Science Foundation of China for Young Scholars, No.50808048 The Humanities and Social Science Research Projects of the Ministry of Education, No.07JA630036
文摘In the urbanizing world,the Yangtze Delta Region （YDR） as one of the most developed regions in China,has drawn a lot of the world＇s attention for the remarkable economic development achieved in the past decades.Nevertheless,the rapid economic development was certain to be accompanied by unprecedented consumption and loss of natural resources.Therefore,the analysis of the ecological situation and driving factors of environmental impact was of great significance to serve the local sustainable development decision-making and build a harmonious society.In this paper,the ecological footprint （EF） was taken as the index of the ecological environmental impact.With the help of Geographic Information System （GIS）,we studied the spatiotemporal change of ecological footprint at two scales （region and city） and assessed urban sustainable development ability in YDR.Then we discussed the driving factors that affected the change of ecological footprint by the Stochastic Impacts by Regression on Population,Affluence,and Technology （STIRPAT） model.The results showed that increasing trends of regional ecological footprint during 1998-2008 （1.70-2.53 ha/cap） were accompanied by decreasing ecological capacity （0.31-0.25 ha/cap） but expanding ecological deficit （1.39-2.28 ha/cap）.The distribution pattern of ecological footprint and the degree of sustainable development varied distinctly from city to city in YDR.In 2008,the highest values of ecological footprint （3.85 ha/cap） and the lowest one of sustainable development index （SDI=1） in YDR were both presented in Shanghai.GDP per capita （A） was the most dominant driving force of EF and the classical EKC hypothesis did not exist between A and EF in 1998-2008.Consequently,increasing in ecological supply and reducing in human demand due to technological advances or other factors were one of the most effective ways to promote sustainable development in YDR.Moreover,importance should be attached to change our definition and measurement of prosperity and success.
文摘A nonlinear dynamic simulative model has been discussed with variable cycles of entire world per capita ecological footprint taken from 1961 to 2003. The model was further classified and decomposed and extracted by the empirical mode decomposition (EMD) method. To deal with the problems proposed in the Living Planet Report 2006, three ecological footprint scenarios are presented. Simulative numerical values of the three global per capita (GPC) ecological footprint scenarios are also analyzed based on the simulative model. The results show that: 1) The clear varying cycle of global per capita EF growth is 4.6 years, 9.5 years, 19.5 years and 41 years over the last 42 years;2) According to the business-as-usual scenario, if the global per capita increases positively with the constant growth, it is expected that GPC EF would be 3.262 gha in 2050. Assuming global per capita biocapacity (BC) to be 1.236 gha, global per capita ecological deficit (ED) would increase from 0.4 gha in 2003 to 2.026 gha in 2050;3) The slow-shift scenario shows global per capita EF would decrease from 2.23 gha in 2003 to 1.619 gha in 2080 and 1.406 gha in 2100, if the negative annual change rate of it is 0.447 percent. Global per capita ED would decrease from 0.4 gha in 2003 to 0.222 gha in 2080 and 0.038 gha in 2100, if global per capita BC is 1.397 gha;4) The rapid-reduction scenario depicts global per capita EF would decrease to 1.414 gha in 2050, if the negative annual change rate is 0.842% from 2003 to 2050. Assuming global per capita BC to be 1.461 gha, global per capita ecological reserve (ER) would be 0.047 gha, and overshoot would be eliminated in 2050. Global per capita EF would decrease to 1.054 gha in 2100, if the negative annual change rate is 0.438% from 2050 to 2100. Assuming global per capita BC to be 1.474 gha, GPC ER would be 0.420 gha. Then, wild species of the planet will be allocated nearly 28.5% of the planet’s biological productivity, which coincides with the results of Living Planet Report 2006.
文摘Heat flux data collected from the Baiyangdian Heterogeneous Field Experiment were analyzed using the footprint method. High resolution （25 m） Landsat-5 satellite imaging was used to determine the land cover as one of four surface types： farmland, lake, wetland, or village. Data from two observation sites in September 2005 were used. One site （Wangjiazhai） was characterized by highly heterogeneous surfaces in the central area of the Baiyangdian： lake/wetland. The other site （Xiongxian） was on land with more uniform surface cover. An improved Eulerian analytical flux footprint model was used to determine “source areas” of the heat fluxes measured at towers located at each site from surrounding landscapes of mixed surface types. In relative terms results show that wetland and lake areas generally contributed most to the observed heat flux at Wangjiazhai, while farmland contributed most at Xiongxian. Given the areal distribution of surface type contributions, calculations were made to obtain the magnitudes of the heat flux from lake, wetland and farmland to the total observed flux and apportioned contributions of each surface type to the sensible and latent heat fluxes. Results show that on average the sensible heat flux from wetland and farmland were comparable over the diurnal cycle, while the latent heat flux from farmland was somewhat larger by about 30-50 W m-2 during daytime. The latent and sensible fluxes from the lake source in daytime were about 50 W m-2 and 100 W m-2 less, respectively, than from wetland and farmland. The results are judged reasonable and serve to demonstrate the potential for flux apportionment over heterogeneous surfaces.
