中国能源消费碳排放的空间计量分析(英文)

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.     

Carbon neutrality and mitigating contribution of terrestrial carbon sink on anthropogenic climate warming in China,the United States,Russia and Canada

Carbon dioxide(CO_2) is a major climate forcing factor, closely related to human activities. Quantifying the contribution of CO_2 emissions to the global radiative forcing(RF) is therefore important to evaluate climate effects caused by anthropogenic and natural factors. China, the United States(USA), Russia and Canada are the largest countries by land area, at different levels of socio-economic development. In this study, we used data from the CarbonTracker CO_2 assimilation model(CT2017 data set) to analyze anthropogenic CO_2 emissions and terrestrial ecosystem carbon sinks from 2000 to 2016. We derived net RF contributions and showed that anthropogenic CO_2 emissions had increased significantly from 2000 to 2016, at a rate of 0.125 PgC yr~(-1). Over the same period, carbon uptake by terrestrial ecosystems increased at a rate of 0.003 PgC yr~(-1). Anthropogenic CO_2 emissions in China and USA accounted for 87.19% of the total, while Russian terrestrial ecosystems were the largest carbon sink and absorbed 14.69 PgC. The resulting cooling effect was-0.013 W m~(-2) in 2016, representing an offset of-45.06% on climate warming induced by anthropogenic CO_2. This indicates that net climate warming would be significantly overestimated if terrestrial ecosystems were not included in RF budget analyses. In terms of cumulative effects, we analyzed RFs using reference atmospheres of 1750, at the start of the Industrial Revolution, and 2000, the initial year of this study. Anthropogenic CO_2 emissions in the study area contributed by + 0.42 W m~(-2) and +0.32 W m~(-2) to the global RF, relative to CO_2 levels of 1750 and 2000, respectively. We also evaluated correlations between global mean atmospheric temperature and net, anthropogenic and natural RFs. We found that the combined(net) RF caused by CO_2 emissions accounted for 30.3% of global mean temperature variations in 2000–2016.     

中国城市碳排放强度的空间溢出效应及驱动因素探究（英文）

In this study, we adopt kernel density estimation, spatial autocorrelation, spatial Markov chain, and panel quantile regression methods to analyze spatial spillover effects and driving factors of carbon emission intensity in 283 Chinese cities from 1992 to 2013. The following results were obtained.(1) Nuclear density estimation shows that the overall average carbon intensity of cities in China has decreased, with differences gradually narrowing.(2) The spatial autocorrelation Moran's I index indicates significant spatial agglomeration of carbon emission intensity is gradually increasing; however, differences between regions have remained stable.(3) Spatial Markov chain analysis shows a Matthew effect in China's urban carbon emission intensity. In addition, low-intensity and high-intensity cities characteristically maintain their initial state during the transition period. Furthermore, there is a clear "Spatial Spillover" effect in urban carbon emission intensity and there is heterogeneity in the spillover effect in different regional contexts; that is, if a city is near a city with low carbon emission intensity, the carbon emission intensity of the first city has a higher probability of upward transfer, and vice versa.(4) Panel quantile results indicate that in cities with low carbon emission intensity, economic growth, technological progress, and appropriate population density play an important role in reducing emissions. In addition, foreign investment intensity and traffic emissions are the main factors that increase carbon emission intensity. In cities with high carbon intensity, population density is an important emission reduction factor, and technological progress has no significant effect. In contrast, industrial emissions, extensive capital investment, and urban land expansion are the main factors driving the increase in carbon intensity.     

中国城市能源消费碳排放的区域差异、空间溢出效应及影响因素分析（英文）

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.     

Analysis and prediction of household carbon emission in northwest China北大核心CSCD

The economic development, living standard of residents and carbon emissions in Northwest China are lower than the national average. However,with the favorable policies the economic development is being improved and the household living standard is gradually raised up which will lead to an increase of the residents living carbon emissions, and the emission pattern will also be affected. This is detrimental to the fragile ecological environment of the Northwest China. At present, most of the researches on residents' carbon emissions are focused on the eastern and southern regions of China where there are frequent and significant human activities and high carbon emissions, and less attention has been paid to the northwest region, but the increase of carbon emissions and the increase of environmental costs have a more far-reaching impact on the less developed areas. In addition, when researchers pay attention to the prediction of residents' carbon emissions, they usually focus on the quantitative prediction and ignore the spatial pattern prediction, which is not conducive to the coordinated development between regions. Based on the data of energy consumption and consumption expenditure in the five provinces of Northwest China, including Shaanxi, Gansu, Qinghai, Ningxia and Xinjiang from 1997 to 2016, this paper firstly used the direct coefficient method to measure the residents' direct carbon emissions, and the input-output method to calculate the indirect carbon emissions of the residents and analyzes the present situation of residents' carbon emissions in the northwest region. Secondly, based on standard deviation ellipse and Autoregressive Integrated Moving Average Model, the carbon emissions of residents in Northwest China were predicted in terms of quantity and spatial pattern from 2017 to 2021. Major results are listed as follows: From 1997 to 2016, household carbon emissions in Northwest China showed a rising trend with an initial slow pace followed by a quick pace. The direct carbon emissions were stabilized in the range from 0. 3 × 108 t to 0. 4 × 108 t,and the indirect carbon emissions reached 2. 38 × 108 t. The spatial distribution of household carbon emissions in Northwest China was generally steady with a direction pattern from northwest to southeast. And the moving trend of standard deviation ellipse was from northwest to southeast to northwest, and the center of standard deviation ellipse moved around the point of (99. 07 °E,38. 19°N). From 2017 to 2021, the direct household carbon emissions in Northwest China reach to 0.543 × 108 t and the indirect carbon emissions are 3. 631 × 108 t by 2021. With the development of the western region in China and the promotion of poverty alleviation,Xinjiang Province had a lower emission than Shaanxi,but it had the higher growth rate than Shaanxi. These factors are all driving the main areas of carbon emission northwestward. The purpose of this paper is to recommend how to coordinate between the population and consumption and the environment, leading citizens to establish the value of low-carbon consumption. © 2019 Science Press (China). All rights reserved.     

中国能源消费碳排放强度及其影响因素的空间计量(英文)

The sustainable development has been seriously challenged by global climate change due to carbon emissions. As a developing country, China promised to reduce 40%–45% below the level of the year 2005 on its carbon intensity by 2020. The realization of this target depends on not only the substantive transition of society and economy at the national scale, but also the action and share of energy saving and emissions reduction at the provincial scale. Based on the method provided by the IPCC, this paper examines the spatiotemporal dynamics and dominating factors of China's carbon intensity from energy consumption in 1997–2010. The aim is to provide scientific basis for policy making on energy conservation and carbon emission reduction in China. The results are shown as follows. Firstly, China's carbon emissions increased from 4.16 Gt to 11.29 Gt from 1997 to 2010, with an annual growth rate of 7.15%, which was much lower than that of GDP(11.72%). Secondly, the trend of Moran's I indicated that China's carbon intensity has a growing spatial agglomeration at the provincial scale. The provinces with either high or low values appeared to be path-dependent or space-locked to some extent. Third, according to spatial panel econometric model, energy intensity, energy structure, industrial structure and urbanization rate were the dominating factors shaping the spatiotemporal patterns of China's carbon intensity from energy consumption. Therefore, in order to realize the targets of energy conservation and emission reduction, China should improve the efficiency of energy utilization, optimize energy and industrial structure, choose the low-carbon urbanization approach and implement regional cooperation strategy of energy conservation and emissions reduction.     

Carbon emissions trends with optimal balanced economic growth of China and the USA and some abatement options for China

It is believed that the global CO2 emissions have to begin dropping in the near fu- ture to limit the temperature increase within 2 degrees by 2100. So it is of great concern to environmentalists and national decision-makers to know how the global or national CO2 emissions would trend. This paper presented an approach to project the future CO2 emissions from the perspective of optimal economic growth, and applied this model to the cases of China and the United States, whose CO2 emissions together contributed to more than 40% of the global emissions. The projection results under the balanced and optimal economic growth path reveal that the CO2 emissions will peak in 2029 for China and 2024 for the USA owing to their empirically implied pace of energy efficiency improvement. Moreover, some abatement options are analyzed for China, which indicate that 1） putting up the energy price will de- crease the emissions at a high cost; 2） enhancing the decline rate of energy intensity can significantly mitigate the emissions with a modest cost; and 3） the energy substitution policy of replacing carbon intensive energies with clean ones has considerable potential to alleviate emissions without compromising the economic development.     

CO2 emissions and their bearing on China＇s economic development： the long view

Greenhouse-gas (GHG) emissions in China have aroused much interest, and not least in recent evidence of their reduction. Our intent is to place that reduction in a larger context, that of the process of industrialization. A lengthy time perspective is combined with a cross-sectional approachChina plus five other countries-and addressed through two general models. The findings are salutary. First, they suggest that a diversified economic structure is consistent with diminished intensity in energy use. Secondly, and the obverse of the first, they imply that a diversified energy structure promotes reductions in CO2 emissions. Finally, one is led inevitably to the conclusion that, together, the findings point to a path for countries to transform their economies while at the same time undertaking to drastically moderate their energy use, switching from a pattern of heavy carbon emissions to one in which lighter carbon emissions prevail. The implications of such findings for environmental management are enormous.     

Driving forces analysis of reservoir wetland evolution in Beijing during 1984–2010

The reservoir wetland, which is the largest artificial wetland in Beijing, constitutes one of the important urban ecological infrastructures. Considering two elements of natural environment and socio-economy, this paper established the driving factor indexing system of Beijing reservoir wetland evolution. Natural environment driving factors include precipitation, temperature, entry water and groundwater depth; social economic driving factors include resident population, urbanization rate and per capita GDP. Using multi-temporal Landsat TM images from 1984 to 2010 in Beijing, the spatial extent and the distribution of Beijing reservoir wetlands were extracted, and the change of the wetland area about the three decade years were analyzed. Logistic regression model was used to explore for each of the three periods： from 1984 to 1998, from 1998 to 2004 and from 2004 to 2010. The results showed that the leading driving factors and their influences on reservoir wetland evolution were different for each period. During 1984-1998, two natural environment indices： average annual precipitation and entry water index were the major factors driving the increase in wetland area with the contribution rate of Logistic regression being 5.78 and 3.50, respectively, and caused the wetland growth from total area of 104.93 km 2 to 219.96 km 2 . From 1998 to 2004, as the impact of human activities intensified the main driving factors were the number of residents, groundwater depth and urbanization rate with the contribution rate of Logistic regression 9.41, 9.18, and 7.77, respectively, and caused the wetland shrinkage rapidly from the total area of 219.96 km 2 to 95.71 km 2 . During 2004-2010, reservoir wetland evolution was impacted by both natural and socio-economic factors, and the dominant driving factors were urbanization rate and precipitation with the contribution rate of 6.62 and 4.22, respectively, and caused the wetland total area growth slightly to 109.73 km 2 .     

中国旅游业能源消耗与二氧化碳排放量估算(英文)

In 2009, nearly 900 million international tourist arrivals were counted worldwide. A global activity of this scale can be assumed to have a substantial impact on the environment. In this contribution, five major aspects such as the change of LUCC and the use of energy and its associated impacts had been recognized. Recently, the impact of tourism on environment and climate attracts the attention of international organizations and societies in pace with rapid development of tourism industry. Energy consumption and CO2 emissions in tourism sector are becoming a hot spot of international tourism research in recent five years. The use of energy for tourism can be divided according to transport-related purposes (travel to, from and at the destination) and destination-related purposes excluding transports (accommodation, food, tourist activities, etc.). In addition, the transports, accommodation and foods are related to many other industries which are dependent on energy. Thus, the estimations of energy consumption and CO2 emissions in tourism sector have become a worldwide concern. Tourism in China grows rapidly, and the number of domestic tourists was 1902 million in 2009. Energy use and its impact on the environment increase synchronously with China’s tourism. It is necessary to examine the relationship between energy use and CO2 emissions. In this article, a preliminary attempt was applied to estimate the energy consumption and CO2 emissions from China’s tourism sector in 2008. Bottom-up approach, literature research and mathematical statistics technology were also adopted. According to the calculations, Chinese tourism-related may have consumed approximately 428.30 PJ of energy in 2008, or about 0.51% of the total energy consumptions in China. It is estimated that CO2 emissions from tourism sector amounted to 51.34 Mt, accounting for 0.86% of the total in China. The results show that tourism is a low-carbon industry and also a pillar industry coping with global climate change, energy-saving and CO2 emission reduction. Based on this, the authors suggested that tourism should become an important field in low-carbon economic development.     

中国碳排放对国际贸易影响的经验分析(英文)

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.     

Urban carbon footprint and carbon cycle pressure: The case study of Nanjing简

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.     

长江口外海域沉积物中有机物的来源及分布

The spatial distribution patterns of total organic carbon and total nitrogen show significant correlations with currents of the East China Sea Shelf. Corresponding to distributions of these currents, the study area could be divided into four different parts. Total organic carbon, total nitrogen, and organic carbon and nitrogen stable isotopes in sediments show linear correlations with mean grain size, respectively, thus ＂grain size effect＂ is an important factor that influences their distributions. C/N ratios can reflect source information of organic matter to a certain degree. In contrast, nitrogen stable isotope shows different spatial distribution patterns with C/N and organic carbon stable isotope, according to their relationships and regional distributions. The highest contribution （up to 50%） of terrestrial organic carbon appears near the Changjiang Estuary with isolines projecting towards northeast, indicating the influence of the Changjiang dilution water. Terrestrial particulate organic matter suffers from effects of diagenesis, benthos and incessant inputting of dead organic matter of plankton, after depositing in seabed. Therefore, the contribution of terrestrial organic carbon to particulate organic matter is obviously greater than that to organic matter in sediments in the same place.     

中国边境地区城镇化时空格局及其驱动力

Border area is not only an important gateway for inland opening-up,but also an important part of completing the building of a moderately prosperous society and optimizing national urban spatial pattern in China.Due to the location,natural resources endowment,and traffic accessibility,the urbanization speed is relatively slow in border areas.Therefore,it is a special area that needs to pay close attention to,especially under the background of the Belt and Road Initiative and China's regional coordinated development program.Based on the county-level data from 2000 to 2015,this paper tries to analyze the spatio-temporal pattern of urbanization in 134 border counties,and applies geographical detector method to study the driving forces of urbanization in border areas.Conclusions are as follows:(1)From 2000 to 2015,urbanization rate in border areas has been lower than the national average,and the gap has been widening.Some border counties in southern Xinjiang,Tibet,northeast of Inner Mongolia,and Yunnan,are even facing the problem of population loss.(2)In the same period,urbanization rate in the northwestern and southwestern border is low,while their urbanization rate grows relatively faster comparing with other border counties;urbanization rate in Tibet border is the lowest and grows relatively slowly;urbanization rate in the northeastern and northern border is slightly higher,but it grows slowly or even stagnates.(3)Transportation and industry are the important driving forces of urbanization in border areas,while the driving forces of market is relatively weak.And there are obvious mutual reinforcements among the driving forces,while the effort and explanatory power of resource force increases obviously after interaction.(4)Urbanization rate in the northwestern and southwestern border areas grows relatively fast,with industrial force and transportation force,market force and administrative force as the main driving forces respectively.Tibet border area has the lowest urbanization rate and growth rate,as the driving force of urbanization with strong contribution has not yet formed in Tibet.In the northeastern and northern border areas,the contribution of transportation force to urbanization is greater than other forces,and its interaction with market and industry has obvious effects.     

中国在气候变化下碳排放、能源消费与低碳经济领域的研究进展综述（英文）

Accompanying the rapid growth of China's population and economy, energy consumption and carbon emission increased significantly from 1978 to 2012. China is now the largest energy consumer and CO2 emitter of the world, leading to much interest in researches on the nexus between energy consumption, carbon emissions and low-carbon economy. This article presents the domestic Chinese studies on this hotpot issue, and we obtain the following findings. First, most research fields involve geography, ecology and resource economics, and research contents contained some analysis of current situation, factors decomposition, predictive analysis and the introduction of methods and models. Second, there exists an inverted "U-shaped" curve connection between carbon emission, energy consumption and economic development. Energy consumption in China will be in a low-speed growth after 2035 and it is expected to peak between 6.19–12.13 billion TCE in 2050. China's carbon emissions are expected to peak in 2035, or during 2020 to 2045, and the optimal range of carbon emissions is between 2.4–3.3 PgC/year(1 PgC=1 billion tons C) in 2050. Third, future research should be focused on global carbon trading, regional carbon flows, reforming the current energy structure, reducing energy consumption and innovating the low-carbon economic theory, as well as establishing a comprehensive theoretical system of energy consumption, carbon emissions and low-carbon economy.     

Spatiotemporal evolution of urban carbon emission performance in China and prediction of future trends

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.     

中国城镇化水平、经济增长和二氧化碳排放的面板协整和因果分析（英文）

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.     

城市能源利用与CO_2排放的多尺度综合评价(英文)

Accurate and detailed accounting of energy-induced carbon dioxide(CO2) emissions is crucial to the evaluation of pressures on natural resources and the environment, as well as to the assignment of responsibility for emission reductions. However, previous emission inventories were usually production- or consumption-based accounting, and few studies have comprehensively documented the linkages among socio-economic activities and external transaction in urban areas. Therefore, we address this gap in proposing an analytical framework and accounting system with three dimensions of boundaries to comprehensively assess urban energy use and related CO2 emissions. The analytical framework depicted the input, transformation, transfer and discharge process of the carbon-based(fossil) energy flows through the complex urban ecosystems, and defined the accounting scopes and boundaries on the strength of ‘carbon footprint' and ‘urban metabolism'. The accounting system highlighted the assessment for the transfer and discharge of socio-economic subsystems with different spatial boundaries. Three kinds methods applied to Beijing City explicitly exhibited the accounting characteristics. Our research firstly suggests that urban carbon-based energy metabolism can be used to analyze the process and structure of urban energy consumption and CO2 emissions. Secondly, three kinds of accounting methods use different benchmarks to estimate urban energy use and CO2 emissions with their distinct strength and weakness. Thirdly, the empirical analysis in Beijing City demonstrate that the three kinds of methods are complementary and give different insights to discuss urban energy-induced CO2 emissions reduction. We deduce a conclusion that carbon reductions responsibility can be assigned in the light of production, consumption and shared responsibility based principles. Overall, from perspective of the industrial and energy restructuring and the residential lifestyle changes, our results shed new light on the analysis on the evolutionary mechanism and pattern of urban energy-induced CO2 emissions with the combination of three kinds of methods. And the spatial structure adjustment and technical progress provides further elements for consideration about the scenarios of change in urban energy use and CO2 emissions.     

北京城市湿地时空演变及驱动力定量分析(英文)

The decision tree and the threshold methods have been adopted to delineate boundaries and features of water bodies from LANDSAT images. After a spatial overlay analysis and using a remote sensing technique and the wetland inventory data in Beijing, the water bodies were visually classified into different types of urban wetlands, and data on the urban wetlands of Beijing in 1986, 1991, 1996, 2000, 2002, 2004 and 2007 were obtained. Thirteen driving factors that affect wetland change were selected, and gray correlation analysis was employed to calculate the correlation between each driving factor and the total area of urban wetlands. Then, six major driving factors were selected based on the correlation coefficient, and the contribution rates of these six driving factors to the area change of various urban wetlands were calculated based on canonical correlation analysis. After that, this research analyzed the relationship and mechanism between the main driving factors and various types of wetlands. Five conclusions can be drawn. (1) The total area of surface water bodies in Beijing increased from 1986 to 1996, and gradually decreased from 1996 to 2007. (2) The areas of the river wetlands, water storage areas and pool and culture areas gradually decreased, and its variation tendency is consistent with that of the total area of wetlands. The area of the mining water areas and wastewater treatment plants slightly increased. (3) The six factors of driving forces are the annual rainfall, the evaporation, the quantity of inflow water, the volume of groundwater available, the urbanization rate and the daily average discharge of wastewater are the main factors affecting changes in the wetland areas, and they correlate well with the total area of wetlands. (4) The hydrologic indicators of water resources such as the quantity of inflow water and the volume of groundwater are the most important and direct driving forces that affect the change of the wetland area. These factors have a combined contribution rate of 43.94%. (5) Climate factors such as rainfall and evaporation are external factors that affect the changes in wetland area, and they have a contribution rate of 36.54%. (6) Human activities such as the urbanization rate and the daily average quantity of waste-water are major artificial driving factors. They have an influence rate of 19.52%.     

Spatio-temporal variations and influencing factors of energy-related carbon emissions for Xinjiang cities in China based on time-series nighttime light data

This essay combines the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS) nighttime light data and the Visible Infrared Imaging Radiometer Suite(VIIRS) nighttime light data into a “synthetic DMSP” dataset, from 1992 to 2020,to retrieve the spatio-temporal variations in energy-related carbon emissions in Xinjiang,China. Then, this paper analyzes several influencing factors for spatial differentiation of carbon emissions in Xinjiang with the application of geographical...