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Elucidating the complex mechanism between urbanization, economic growth, car- bon 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 re- gional levels using panel cointegration and vector error correction model and Granger cau- sality tests. Results showed that urbanization, economic growth and CO2 emissions are inte- grated 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 re- gions. 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, in- dicating 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 re- lationship between CO2 emissions and economic growth in China, not supporting the envi- ronmental Kuznets curve （EKC） hypothesis. Our empirical findings have an important refer- ence value for policy-makers in formulating effective energy saving and emission reduction strategies for China.

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.

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.

The global steel production has been growing for the last 50 years, from 200 Mt in 1950s to 1 240 Mt in 2006. Iron and steel making industry is one of the most energy-intensive industries, with an annual energy consumption of about 24 EJ, 5% of the world＇s total energy consumption. The steel industry accounts for 3%-4% of totat world greenhouse gas emissions. Enhancing energy efficiency and employing energy saving/recovering technologies such as coke dry quechning （CDQ） and top pressure recovery turbine （TRT） can be short-term approaches to the steel industry to reduce greenhouse gas emission. The long-term approaches to achieving a significant reduction in CO2 emissions from the steel industry would be through developing and applying CO2 breakthrough technologies for iron and steel making, and：through increasing use of renewable energy for iron and steel making. Thus, an overview of new CO2 breakthrough technologies for iron and steel making was made.

In recent decades, there have been a number of debates on climate warming and its driving forces. Based on an extensive literature review, we suggest that （1） climate warming occurs with great uncertainty in the magnitude of the temperature increase; （2） both human activities and natural forces contribute to climate change, but their relative contributions are difficult to quan- tify; and （3） the dominant role of the increase in the atmospheric concentration of greenhouse gases （including CO2） in the global warming claimed by the Intergovernrnental Panel on Climate Change （IPCC） is questioned by the scientific communities because of large uncertainties in the mechanisms of natural factors and anthropogenic activities and in the sources of the increased atmospheric CO2 concentration. More efforts should be made in order to clarify these uncertainties.

Analysis of carbon emission mechanism based on regional perspectives is an im- portant research method capable of achieving energy savings and emission reductions. Xin- jiang, an important Chinese energy production base, is currently going through a period of strategic opportunities for rapid development. Ensuring stable socio-economic development while achieving energy savings and meeting emission reductions targets, is the key issue currently facing the region. This paper is based on the input-output theory, and conducts a structural decomposition analysis on the factors affecting energy-related carbon emissions in Xinjiang from 1997 to 2007; this analysis employs a hybrid input-output analysis framework of ＂energy - economy - carbon emissions＂. （1） Xinjiang＇s carbon emissions from energy con- sumption increased from 20.70 million tons in 1997 to 40.34 million tons in 2007; carbon emissions growth was mainly concentrated in the production and processing of energy re- sources, the mining of mineral resources, and the processing industry. （2） The analysis of the direct effects of the influencing factors on carbon emissions showed that the change in per capita GDP, the final demand structure, the population scale, and the production structure were the important factors causing an increase in carbon emissions, while the decrease in carbon emission intensity during this period was the important influencing factor in stopping the growth of carbon emissions. This showed that while the sizes of Xinjiang＇s economy and population were growing, the economic structure had not been effectively optimized and the production technology had not been efficiently improved, resulting in a rapid growth of carbon emissions from energy consumption. （3） The analysis of the indirect effects of the influencing factors of carbon emission showed that the inter-provincial export, fixed capital formation, and the consumption by urban residents had significant influence on the changes in carbon emissions from energy consumption in Xinjiang. （4） The growth of investments in fixed assets of carbon intensive industry sectors, in addition to the growth of inter-provincial exports ofenergy resource products, makes the transfer effect of inter-provincial ＂embodied carbon＂ very significant.

Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.

Aiming at the current characteristics of blast furnace （BF） process, carbon saving potential of blast furnace was investigated from the perspective of the relationship between degree of direct reduction and carbon consumption. A new relationship chart between carbon consumption and degree of direct reduction, which can reflect more real situation of blast furnace operation, was established. Further- more, the carbon saving potential of hydrogen-rich oxygen blast furnace （OBF） process was ana- lyzed. Then, the policy implications based on this relationship chart established were suggested. On this basis, the method of improving the carbon saving potential of blast furnace was recycling the top gas with removal of CO2 and H2O or increasing hydrogen in BF gas and full oxygen blast. The results show that the carbon saving potential in traditional blast furnace （TBF） is only 38 56 kg · t ^-1 while that in OBF is 138 kg · t ^-1. Theoretically, the lowest carbon consumpt!on of OBF is 261 kg · t ^-1 and the corresponding degree of direct reduction is 0.04. In addition, the theoretical lowest carbon consumption of hydrogen-rich OBF is 257 kg · t ^-1. The modeling analysis can be used to estimate the carbon savings potential in new ironmaking process and its related CO2 emissions.

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.

The rapid urbanization of China has increased pressure on its environmental and ecological well being. In this study, the temporal and spatial profiles of China＇s carbon dioxide emissions are analyzed by taking heterogeneities into account based on an integration of the extended stochastic impacts using a geographically and temporally weighted regression model on population, affluence, and technology. Population size, urbanization rate, GDP per capita, energy intensity, industrial structure, energy consumption pattern, energy prices, and economy openness are identified as the key driving factors of regional carbon dioxide emissions and examined through the empirical data for 30 provinces during 2006-2010. The results show the driving factors and their spillover effects have distinct spatial and temporal heterogeneities. Most of the estimated time and space coefficients are consistent with expectation. According to the results of this study, the heterogeneous spatial and temporal effects should be taken into account when designing policies to achieve the goals of carbon dioxide emissions reduction in different regions.