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1.
基于能源消费的中国不同产业空间的碳足迹分析 总被引：10，自引：2，他引：8
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 indus-trial 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/hm2,in which,carbon emission intensity of living & industrial-commercial space and of transportation in-dustrial space was 55.16 t/hm2 and 49.65 t/hm2 respectively,they were high-carbon-emission industrial spaces among others.(3) Carbon footprint caused by industrial activities of China in 2007 was 522.34 106 hm2,which brought about ecological deficit of 28.69 106 hm2,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 ecologi-cal deficit caused by industrial activities was small in 2007.(4) Per unit area carbon footprint of industrial space in China was about 0.63 hm2/hm2 in 2007,in which that of living & indus-trial-commercial space was the highest (17.5 hm2/hm2).The per unit area carbon footprint of different industrial spaces all presented a declining trend from east to west of China. 相似文献
2.
In order to provide better services to the members of Geographical Society of China （GSC） and geographers and engineers in China, and improve GSC＇s ability in hosting comprehensive aca- demic conferences, with the support of China Association for Science and Technology （CAST）, GSC established 7 regional divisions, representing different regions of China. In addition, GSC revised the annual conference organizing policies by hosting the comprehensive national aca- demic conference biannually. Instead of hosting annual national conferences, GSC organizes regional academic conferences. The new policy was initiated and executed in 2013. Up to now, 7 regional conferences have been successfully organized by the regional divisions in their areas. The 7 regional divisions are： Northern China Division, Northwest China Division, Northeast China Division, Southwest China Division, Central China Division, Southern China Division and Eastern China Division. The regional divisions promote the objectives of GSC through regional conferences and activities in their respective areas. The purpose is to build platforms extensively for academic exchange between geographers; collaborate with local geographical societies and integrate local resources; and unite all the regional academic organizations. 相似文献
3.
Spatial-temporal characteristics and decoupling effects of China’s carbon footprint based on multi-source data 总被引：1，自引：1，他引：0
In 2007, China surpassed the USA to become the largest carbon emitter in the world. China has promised a 60%–65% reduction in carbon emissions per unit GDP by 2030, compared to the baseline of 2005. Therefore, it is important to obtain accurate dynamic information on the spatial and temporal patterns of carbon emissions and carbon footprints to support formulating effective national carbon emission reduction policies. This study attempts to build a carbon emission panel data model that simulates carbon emissions in China from 2000–2013 using nighttime lighting data and carbon emission statistics data. By applying the Exploratory Spatial-Temporal Data Analysis(ESTDA) framework, this study conducted an analysis on the spatial patterns and dynamic spatial-temporal interactions of carbon footprints from 2001–2013. The improved Tapio decoupling model was adopted to investigate the levels of coupling or decoupling between the carbon emission load and economic growth in 336 prefecture-level units. The results show that, firstly, high accuracy was achieved by the model in simulating carbon emissions. Secondly, the total carbon footprints and carbon deficits across China increased with average annual growth rates of 4.82% and 5.72%, respectively. The overall carbon footprints and carbon deficits were larger in the North than that in the South. There were extremely significant spatial autocorrelation features in the carbon footprints of prefecture-level units. Thirdly, the relative lengths of the Local Indicators of Spatial Association(LISA) time paths were longer in the North than that in the South, and they increased from the coastal to the central and western regions. Lastly, the overall decoupling index was mainly a weak decoupling type, but the number of cities with this weak decoupling continued to decrease. The unsustainable development trend of China's economic growth and carbon emission load will continue for some time. 相似文献
4.
中国能源消费碳排放的空间计量分析(英文) 总被引：8，自引：3，他引：5
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 con-sumption,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 in-creased 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. 相似文献
5.
International trade is an important impact factor to the carbon emissions of a country.As the rapid development of Chinese foreign trade since its entry into the WTO in 2002,the effects of international trade on carbon emissions of China are more and more significant.Using the recent available input-output tables of China and energy consumption data,this study estimated the effects of Chinese foreign trade on carbon emissions and the changes of the effects by analyzing the emissions embodied in trade between 2002 and 2007.The re-sults showed a more and more significant exporting behavior of embodied carbon emissions in Chinese international trade.From 2002 to 2007,the proportion of net exported emissions and domestic exported emissions in domestic emissions increased from 18.32% to 29.79% and from 23.97% to 34.76%,respectively.In addition,about 22.10% and 32.29% of the total imported emissions were generated in processing trade in 2002 and 2007,respectively,which were imported and later exported emissions.Although,most of the sectors showed a growth trend in imported and exported emissions,sectors of electrical machinery and communication electronic equipment,chemical industry,and textile were still the biggest emission exporters,the net exported emissions of which were also the largest.For China and other developing countries,technology improvement may be the most favorable and acceptable ways to re-duce carbon emissions at present stage.In the future negotiations on emissions reduction,it would be more fair and reasonable to include the carbon emissions embodied in international trade when accounting the total emissions of an economy. 相似文献
6.
Climate change resulting from CO_2 emissions has become an important global environmental issue in recent years.Improving carbon emission performance is one way to reduce carbon emissions.Although carbon emission performance has been discussed at the national and industrial levels,city-level studies are lacking due to the limited availability of statistics on energy consumption.In this study,based on city-level remote sensing data on carbon emissions in China from 1992–2013,we used the slacks-based measure of super-efficiency to evaluate urban carbon emission performance.The traditional Markov probability transfer matrix and spatial Markov probability transfer matrix were constructed to explore the spatiotemporal evolution of urban carbon emission performance in China for the first time and predict long-term trends in carbon emission performance.The results show that urban carbon emission performance in China steadily increased during the study period with some fluctuations.However,the overall level of carbon emission performance remains low,indicating great potential for improvements in energy conservation and emission reduction.The spatial pattern of urban carbon emission performance in China can be described as"high in the south and low in the north,"and significant differences in carbon emission performance were found between cities.The spatial Markov probabilistic transfer matrix results indicate that the transfer of carbon emission performance in Chinese cities is stable,resulting in a"club convergence"phenomenon.Furthermore,neighborhood backgrounds play an important role in the transfer between carbon emission performance types.Based on the prediction of long-term trends in carbon emission performance,carbon emission performance is expected to improve gradually over time.Therefore,China should continue to strengthen research and development aimed at improving urban carbon emission performance and achieving the national energy conservation and emission reduction goals.Meanwhile,neighboring cities with different neighborhood backgrounds should pursue cooperative economic strategies that balance economic growth,energy conservation,and emission reductions to realize low-carbon construction and sustainable development. 相似文献
7.
The Chinese government ratified the Paris Climate Agreement in 2016.Accordingly,China aims to reduce carbon dioxide emissions per unit of gross domestic product(carbon intensity)to 60%–65%of 2005 levels by 2030.However,since numerous factors influence carbon intensity in China,it is critical to assess their relative importance to determine the most important factors.As traditional methods are inadequate for identifying key factors from a range of factors acting in concert,machine learning was applied in this study.Specifically,random forest algorithm,which is based on decision tree theory,was employed because it is insensitive to multicollinearity,is robust to missing and unbalanced data,and provides reasonable predictive results.We identified the key factors affecting carbon intensity in China using random forest algorithm and analyzed the evolution in the key factors from 1980 to 2017.The dominant factors affecting carbon intensity in China from 1980 to 1991 included the scale and proportion of energy-intensive industry,the proportion of fossil fuel-based energy,and technological progress.The Chinese economy developed rapidly between 1992 and 2007;during this time,the effects of the proportion of service industry,price of fossil fuel,and traditional residential consumption on carbon intensity increased.Subsequently,the Chinese economy entered a period of structural adjustment after the 2008 global financial crisis;during this period,reductions in emissions and the availability of new energy types began to have effects on carbon intensity,and the importance of residential consumption increased.The results suggest that optimizing the energy and industrial structures,promoting technological advancement,increasing green consumption,and reducing emissions are keys to decreasing carbon intensity within China in the future.These approaches will help achieve the goal of reducing carbon intensity to 60%–65%of the 2005 level by 2030. 相似文献
8.
经验模态分解下中国气温变化趋势的区域特征 总被引：3，自引：1，他引：2
By the Empirical Mode Decomposition method, we analyzed the observed monthly average temperature in more than 700 stations from 1951-2001 over China. Simultaneously, the temperature variability of each station is calculated by this method, and classification chart of long term trend and temperature variability distributing chart of China are obtained, supported by GIS, 1 kmxl km resolution. The results show that： in recent 50 years, the temperature has increased by more than 0.4~C/10a in most parts of northern China, while in Southwest China and the middle and lower Yangtze Valley, the increase is not significant. The areas with a negative temperature change rate are distributed sporadically in Southwest China. Meanwhile, the temperature data from 1881 to 2001 in nine study regions in China are also analyzed, indicating that in the past 100 years, the temperature has been increasing all the way in Northeast China, North China, South China, Northwest China and Xinjiang and declining in Southwest China. An inverse ‘V-shaped’ trend is also found in Central China. But in Tibet the change is less significant. 相似文献
9.
《地理学报(英文版)》2016,(2)
Elucidating the complex mechanism between urbanization,economic growth,carbon dioxide emissions is fundamental necessary to inform effective strategies on energy saving and emission reduction in China. Based on a balanced panel data of 31 provinces in China over the period 1997–2010,this study empirically examines the relationships among urbanization,economic growth and carbon dioxide(CO2) emissions at the national and regional levels using panel cointegration and vector error correction model and Granger causality tests. Results showed that urbanization,economic growth and CO2 emissions are integrated of order one. Urbanization contributes to economic growth,both of which increase CO2 emissions in China and its eastern,central and western regions. The impact of urbanization on CO2 emissions in the western region was larger than that in the eastern and central regions. But economic growth had a larger impact on CO2 emissions in the eastern region than that in the central and western regions. Panel causality analysis revealed a bidirectional long-run causal relationship among urbanization,economic growth and CO2 emissions,indicating that in the long run,urbanization does have a causal effect on economic growth in China,both of which have causal effect on CO2 emissions. At the regional level,we also found a bidirectional long-run causality between land urbanization and economic growth in eastern and central China. These results demonstrated that it might be difficult for China to pursue carbon emissions reduction policy and to control urban expansion without impeding economic growth in the long run. In the short-run,we observed a unidirectional causation running from land urbanization to CO2 emissions and from economic growth to CO2 emissions in the eastern and central regions. Further investigations revealed an inverted N-shaped relationship between CO2 emissions and economic growth in China,not supporting the environmental Kuznets curve(EKC) hypothesis. Our empirical findings have an important reference value for policy-makers in formulating effective energy saving and emission reduction strategies for China. 相似文献
10.
ZHAO Rongqin HUANG Xianjin LIU Ying ZHONG Taiyang DING Minglei CHUAI Xiaowei 《地理学报(英文版)》2014,24(1):159-176
Urban carbon footprint reflects the impact and pressure of human activities on ur- ban environment. Based on city level, this paper estimated carbon emissions and carbon footprint of Nanjing city, analyzed urban carbon footprint intensity and carbon cycle pressure and discussed the influencing factors of carbon footprint through LMDI decomposition model. The main conclusions are as follows： （1） The total carbon emissions of Nanjing increased rapidly since 2000, in which the carbon emission from the use of fossil energy was the largest Meanwhile, carbon sinks of Nanjing presented a declining trend since 2000, which caused the decrease of carbon compensation rate and the increase of urban carbon cycle pressure. （2） The total carbon footprint of Nanjing increased rapidly since 2000, and the carbon deficit was more than ten times of total land areas of Nanjing in 2009, which means Nanjing confronted high carbon cycle pressure. （3） Generally, carbon footprint intensity of Nanjing was on de- crease and the carbon footprint productivity was on increase. This indicated that energy utilization rate and carbon efficiency of Nanjing was improved since 2000, and the policy for energy conservation and emission reduction taken by Nanjing＇s government received better effects. （4） Economic development, population and industrial structure are promoting factors for the increase of carbon footprint of Nanjing, while the industrial carbon footprint intensity was inhibitory factor. （5） Several countermeasures should be taken to decrease urban carbon footprint and alleviate carbon cycle pressure, such as： improvement of the energy efficiency, industrial structure reconstruction, afforestation and environmental protection and land use control. Generally, transition to low-carbon economy is essential for Chinese cities to realize sustainable development in the future. 相似文献
11.
Study on regional carbon emission is one of the hot topics under the background of global climate change and low-carbon economic development, and also help to establish different low-carbon strategies for different regions. On the basis of energy consumption and land use data of different regions in China from 1999 to 2008, this paper established carbon emission and carbon footprint models based on total energy consumption, and calculated the amount of carbon emissions and carbon footprint in different regions of China from 1999 to 2008. The author also analyzed carbon emission density and per unit area carbon footprint for each region. Finally, advices for decreasing carbon footprint were put forward. The main conclusions are as follows: (1) Carbon emissions from total energy consumption increased 129% from 1999 to 2008 in China, but its spatial distribution pattern among different regions just slightly changed, the sorting of carbon emission amount was: Eastern China > Northern China > Central and Southern China > Southwest China > Northwest China. (2) The sorting of carbon emission density was: Eastern China > Northeast China > Central and Southern China > Northern China > Southwest China > Northwest China from 1999 to 2003, but from 2004 Central and Southern China began to have higher carbon emission density than Northeast China, the order of other regions did not change. (3) Carbon footprint increased significantly since the rapid increasing of carbon emissions and less increasing area of productive land in different regions of China from 1999 to 2008. Northern China had the largest carbon footprint, and Northwest China, Eastern China, Northern China, Central and Southern China followed in turn, while Southwest China presented the lowest area of carbon footprint and the highest percentage of carbon absorption. (4) Mainly influenced by regional land area, Northern China presented the highest per unit area carbon footprint and followed by Eastern China, and Northeast China; Central and Southern China, and Northwest China had a similar medium per unit area carbon footprint; Southwest China always had the lowest per unit area carbon footprint. (5) China faced great ecological pressure brought by carbon emission. Some measures should be taken both from reducing carbon emission and increasing carbon absorption. 相似文献
12.
中国各省区碳足迹与碳排放空间转移 总被引：12，自引：3，他引：9
减排责任的区域分解需要科学评价各地区的排放责任。碳足迹可以全面客观地评价为满足消费而进行的生产的生命周期碳排放水平, 除了生产过程的直接碳排放, 也包括生产过程中所消耗的中间产品的隐含碳排放。应用2007 年各省区投入产出模型和2002 年中国省区间投入产出模型, 定量测算了各省区的碳足迹和省区间的碳排放转移。结果显示, 各省区之间碳足迹和人均碳足迹存在显著的差异。碳足迹较大的省份为经济大省, 主要分布在北方地区;人均碳足迹较高的省份主要是北京、上海等中心城市和能源富集区域及重化工基地;中国存在着从能源富集区域和重化工基地分布区域向经济发达区域和产业结构不完整的欠发达区域的碳排放空间转移。上述结果表明, 人均碳足迹高的经济发达省份应承担较大的减排责任, 能源富集区域和重化工基地分布区域有相当一部分的碳排放是为沿海发达省份和产业结构不完整的欠发达省份提供电力、原材料等高碳产品所致, 减排责任的区域分解需要考虑碳排放空间转移的因素, 适当减轻能源富集区域和重化工基地分布区域的减排责任, 或使沿海发达省份向能源富集区域和重化工区域提供资金和技术上的扶持, 帮助这些区域提高能源利用效率, 减少碳排放。 相似文献
13.
基于能源消费的江苏省土地利用碳排放与碳足迹 总被引：35，自引：5，他引：30
采用2003~2007年江苏省能源消费和土地利用等数据,通过构建能源消费的碳排放模型,对江苏省5年来能源消费碳排放进行了核算,并通过土地利用类型和碳排放项目的对应,对不同土地利用方式的碳排放及碳足迹进行了定量分析。结论如下:(1)江苏省能源消费碳排放总量从2003年的8794.24万t上升到2007年的16329.85万t,涨幅达86%。其中,终端能源消费碳排放占53.6%。(2)江苏全省土地单位面积碳排放从2003年8.24t/hm2上升到2007年15.53 t/hm2,增幅为88.5%。其中,居民点及工矿用地单位面积碳排放最大,为95.62 t/hm2。(3)江苏全省能源消费碳足迹大于生产性土地的实际面积,由此造成的生态赤字达1351.285万hm2。(4)不同土地利用类型的碳足迹大小顺序为:居民点及工矿用地＞交通用地＞未利用地及特殊用地＞农用地和水利用地,其中居民点及工矿用地的碳足迹高达10.89 hm2/ hm2。(5)江苏全省单位面积碳足迹也呈明显的扩大趋势,从2003年的0.938 hm2/ hm2上升到2007年的1.769 hm2/ hm2。 相似文献
14.
中国能源碳足迹时空格局演化及脱钩效应 总被引：12，自引：5，他引：7
利用DMSP-OLS夜间灯光数据和碳排放统计数据,构建碳排放面板数据模型,模拟了2000—2013年中国的碳排放量。运用探索性时空数据分析（ESTDA）框架体系,从时空交互视角分析2001—2013年碳足迹的空间格局和时空依赖动态演化;利用改进的Tapio脱钩模型对3个时间段336个地级单元环境碳负荷与经济增长之间的脱钩效应进行综合分析。研究表明：① 2000—2013年,中国的碳排放在时空演变上既表现出稳中有进的总体特征,也存在快速增长的阶段特征。② 碳足迹和碳赤字均呈逐年增长趋势,年均增长率分别为4.82%和5.72%;碳足迹和碳赤字整体北方大于南方,不同的行政单元尺度下碳足迹和碳赤字空间异质性特征明显。各地级单元碳足迹变异系数逐步增大,存在极为显著的空间自相关特征。③ LISA时间路径相对长度北方大于南方,且呈由沿海地区向中西部地区递增的趋势;LISA时间路径弯曲度整体上则由沿海地区向内陆地区递减。④ 综合脱钩指数整体以弱脱钩型为主,但弱脱钩型城市数量持续减少,扩张连接、扩张负脱钩区域数量逐渐增多且向中西部及东北地区聚集分布;全国平均脱钩弹性值逐步增长,变异系数持续下降。 相似文献
15.
The landscape fragmentation caused by road construction has many direct and indirect impacts on wildlife and ecosystems. By using the GIS and statistic software of fragmentation computation, a comprehensive index, road-induced landscape fragmentation index (RLFI), is proposed to quantify the degree of landscape fragmentation resulting from different levels of road constructions. The results show that road-induced fragmentation index in China ranges from 0.987 to 3.357, with a mean of 1.846 in 2002. The regional differences of landscape fragmentation are obvious and scoring sequence is: North China (2.65) > East China (2.62) > Central China (2.60) > South China (2.51) > Southwest China (2.34) > Northeast China (2.19) > Inner Mongolia (1.88) > Northwest China (1.67) > Qinghai-Tibet Plateau (1.65). The anisotropic analysis indicates that the variation of fragmentation index in east-west direction is larger than that in south-north direction. 相似文献
16.
Interdecadal fluctuation of dry and wet climate boundaries in China in the past 50 years 总被引：2，自引：0，他引：2
Based on the mean yearly precipitation and the total yearly evaporation data of 295 meteorological stations in China in 1951–1999,
the aridity index is calculated in this paper. According to the aridity index, the climatic regions in China are classified
into three types, namely, arid region, semi-arid region and humid region. Dry and wet climate boundaries in China fluctuate
markedly and differentiate greatly in each region in the past 50 years. The fluctuation amplitudes are 20–400 km in Northeast
China, 40–400 km in North China, 30–350 km in the eastern part of Northwest China and 40–370 km in Southwest China. Before
the 1980s (including 1980), the climate tended to be dry in Northeast China and North China, to be wet in the eastern part
of Northwest China and very wet in Southwest China. Since the 1990s there have been dry signs in Southwest China, the eastern
part of Northwest China and North China. The climate becomes wetter in Northeast China. Semi-arid region is the transitional
zone between humid and arid regions, the monsoon edge belt in China, and the susceptible region of environmental evolution.
At the end of the 1960s dry and wet climate in China witnessed abrupt changes, changing wetness into dryness. Dry and wet
climate boundaries show the fluctuation characteristics of the whole shifts and the opposite fluctuations of eastward, westward,
southward and northward directions. The fluctuations of climatic boundaries and the dry and wet variations of climate have
distinctive interdecadal features. 相似文献
17.
我国西北地区经济发展、居民生活水平和碳排放均低于全国平均水平，随着国家政策倾斜，居民生活条件逐步改善，居民生活碳排放量提升空间较大，排放格局将受影响，这对西北地区本就脆弱的生态环境更加不利。目前有关居民碳排放的研究多集中在人类活动频繁、碳排放量大的我国东、南部地区，较少关注西北地区，但碳排放增加、环境成本加重对于欠发达地区的影响更加深远。其次，研究者关注居民碳排放预测时，通常着眼于数量预测，忽视了空间格局预测，不利于区域间协同发展。基于1997—2016年西北五省居民能源消耗和消费支出数据，首先利用直接系数法和投入产出法测算了1997—2016年西北地区居民生活碳排放，对其现状进行分析；第二，基于标准差椭圆和ARIMA模型从数量和空间格局上对2017—2021年西北居民生活碳排放进行预测。结果表明：1997—2016年，西北居民生活碳排放呈先缓慢后快速的上升趋势。直接碳排放稳定在0.3～0.4×108 t；间接碳排放达到2.38×108 t；空间分布总体稳定，呈西北—东南分布，移动趋势为西北—东南—西北，标准差椭圆中心在（99.07°E,38.19°N）附近移动。2017—2021年，直接碳排放达到0.543×108 t；间接碳排放为3.631×108 t；主体区域沿X轴发散，Y轴收敛，旋转轴变化小，随着西部大开发和脱贫的推进，新疆排放量次于陕西，增速较快，推动碳排放主体区域向西北移动。旨在为实现西北地区人口、消费、环境协调发展、引导居民树立低碳消费的价值理念建言献策。 相似文献
18.
基于SBM-DEA模型湖南省碳排放效率时空差异及影响因素分析 总被引：2，自引：4，他引：2
以中部湖南省为研究区域,利用超效率SBM-DEA模型与Malmquist指数对2010~2016年湖南省14个市（州）碳排放效率和环境效率进行测度和空间差异分析,结果发现：① 从时间序列演化特征来看,除长沙市、常德市外,湖南省大部分市（州）的碳排放效率和环境效率偏低,纯技术效率的贡献较大,技术效率和规模效率发挥不足,部分地区在2010~2016年间的碳排放效率有所提高,但均低于10%的增长水平;② 从空间格局分布来看,湖南省14市（州）的效率水平差异显著,表现为碳排放效率由中部地区逐步向边缘地区进行转移和提升,而环境效率的波动性较大,整体呈现出“分散-集聚-分散”的趋势。五大能源区域中湘东地区的效率水平较高,其次为湘北地区,湘南地区与湘西地区表现为空间互补型区域,湘中地区的效率水平提升则相对滞后;③ 从影响因素的分析来看,二、三产业的作用效果不显著,生态环境、工业产业集聚和对外依存度对碳排放效率具有负向作用,技术进步则表现出积极的正向影响。最后,提出结合现有的政策引导和技术水平发展,充分发挥好各地区经济规模效应,促进生产要素在区域间的快速流动,推动技术进步成为节能减排的主要驱动等建议。 相似文献
19.
中国区域农业生态效率空间演化及其驱动因素——水足迹与灰水足迹视角 总被引：3，自引：0，他引：3
将水足迹与灰水足迹指标纳入农业生态效率指标体系,运用基于非期望产出的SBM模型和Tobit面板模型对1990—2016年中国农业生态效率空间演化特征及驱动因素进行实证分析,结论如下：① 1990—2016年,中国农业水足迹和灰水足迹明显上升;中国高农业水足迹的区域重心北移,主要由长江流域转移至黄河下游地区。中国高灰水足迹地域范围明显扩大,整体由西南向东北方向移动;② 中国农业生态效率明显降低。中国农业生态效率存在明显的区域特征。华南区的农业生态效率最高。东北区、西北及长城沿线区、青藏区和西南区的农业生态效率较低,这些区域是中国农业污染治理防控的重点区;③ 中国省域农业生态效率呈现显著的空间自相关且空间上越来越趋于集聚。中国农业生态效率的空间集聚格局较为稳定,呈空间依赖与路径锁定特征;④ 中国七大区域农业生态效率演变的驱动因素存在异质性。提出中国提高农业生态效率要因地制宜采取差异化的发展策略,为促进中国农业生态效率提升和可持续发展提供科学参考。 相似文献