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In 2017, a carbon emissions trading market will be launched nationwide by the China government. Calculating the enterprise carbon emissions is an important prerequisite and basis for trading. This paper discussed types of greenhouse gases, calculation boundaries and methods, energy consumption, carbon emissions, and intensity of a representative integrated pulp and paper mill in China based on China Guidance and Greenhouse Gas Protocol Tools. The results showed that there were 435,000 tonnes (t) of CO2 emissions from that mill in 2014 that did not contain emissions of biomass energy, which was 8 times higher than that of fossil energy. The pulp carbon intensity based on the mill was 0.230 t CO2/Adt, which accounted for 7.50% to 57.4% in other pulps' based on the product. Intensity based on Gross Domestic Product (GDP) was 1.090 t CO2e/1000 USD and accounted for 56.8% intensity in the China paper industry. The intensity based on sales accounted for 52.6% in the firstclass enterprise in the developed country. It also showed that intensity was influenced by the species of raw material, energy, and products, which provided the mill with measures for energy saving and emissions reduction to obtain the redundant carbon emissions in the trading. [ABSTRACT FROM AUTHOR]

Energy is known as the lifeline of national development, and from the last decade or so, the security of human energy supply has been frequently disturbed by natural disasters due to global warming and frequent geological activities. In this paper, by combing the literature, we found that the past literature on the relationship between energy and natural disasters mainly focused on measuring energy consumption under natural disasters, but less on the integrated evaluation of human economic activities, energy security and natural disasters, and less on the evaluation of the energy governance efficiency of each provincial, municipal, and autonomous region government in preventing and managing exposure to natural disasters from the perspective of Chinese provinces. Therefore, in order to fill the gap in the literature in this field, this paper collects panel data of energy consumption efficiency stages and natural disaster treatment stages from 2013 to 2017 for 30 provinces in China (excluding Hong Kong, Macao and Taiwan as well as Tibet Autonomous Region) and uses the two-stage undesirable dynamic DDF model as a framework to study the relationship between economic, environmental pollution and natural disasters for the sample data and to analyze the phase-by-phase evaluation of energy and natural disaster efficiency and make corresponding policy recommendations. The following conclusions are drawn: (1) The overall efficiency of China's eastern coastal provinces is higher than that of the central and western provinces. (2) The first-stage efficiency of Chinese provinces is better than the second stage, and the difference in efficiency of the first stage of each province is smaller than that of the second stage. (3) In terms of the efficiency of disaster prevention and relief inputs, the efficiency values are generally lower in most regions of China. (4) Finally, the annual efficiency of natural disaster losses is not high in all regions, and the efficiency values are higher in the eastern coastal regions than in the central and western regions. Accordingly, this paper proposes that each province should formulate relevant disaster prevention and economic development strategies according to regional characteristics, while the central government should also propose locally appropriate coordinated governance policies to effectively control carbon dioxide emissions and air pollution, as well as increase disaster prevention publicity and incorporate disaster prevention education-related work into the performance assessment mechanism of local governments to promote the interactive development of the two. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to reveal the mechanism and process of the dynamic evolution of the economy-energy-environment (EEE) system and study the variables that determine the speed of system evolution and development. The innovation is to overcome the defect of single index by constructing a system evaluation index and reveal the regional EEE system's evolution mechanism based on Haken's synergetic theory to supplement a systematic perspective's empirical evidence. It selects 30 provinces, municipalities, and autonomous regions in China to empirically analyse the evolution mechanism of the EEE system from 2005 to 2019. The empirical results show that economic development is the order parameter of the evolution and development of the EEE system. In the process of system evolution, the economic development subsystem is the decisive factor in EEE system evolution. In terms of the positive feedback mechanism of order parameter combination, the EEE system forms a positive feedback mechanism for increasing economic development in the stage of evolution and development. The negative feedback mechanism of decreasing environmental pollution emissions is formed in the EEE system. The increase in pollutant emissions has a certain inhibitory effect on economic growth. The improvement in the economic development level has no promoting effect on pollutants, and economic development, in turn, reduces environmental pollution. [ABSTRACT FROM AUTHOR]

The industrial sector is China's major element of energy consumption and carbon emissions, and carbon emissions reduction in industrial parks has become an important foothold in carbon reduction work. Predicting the future evolution trend of carbon emissions in industrial parks under different policy orientations is of great significance for China to achieve the carbon emissions peaking and carbon neutrality goals. Based on the current status of electricity consumption and carbon emissions in industrial parks, this paper takes a light industrial park as the research object, analyzes the source of carbon emissions in this park, combines the characteristics of resource endowment and industrial structure, and considers the factors influencing society, load curve, energy supply and carbon sink, thus constructing a system dynamics model of carbon emission evolution for this park. Different influencing factors are selected to set multiple target scenarios, and the GDP, carbon emissions, carbon emissions reduction and near‐zero carbon evaluation coefficient of light industrial parks are used as characterization indicators for simulation analysis. The analysis results revealed that the comprehensive scenario set by increasing the maximum installed capacity of renewable energy units and raising the proportions of environmental and science and technology inputs while adjusting the industrial growth rate of the park performed best. In this scenario, the economic development of the park and the process of carbon emissions reduction are considered. [ABSTRACT FROM AUTHOR]

The excessive carbon emissions not only intensify the global climate change, but also seriously restrict the sustainable development of social economy. However, improving industrial carbon emissions efficiency is the most directly effective way to reduce emissions. Therefore, accurate measurement and analysis of carbon emissions efficiency and evolution characteristics of China's industrial system is the basis for China to improve carbon emissions efficiency. Based on this, we adopted energy consumption method and input-output method to calculate and analyze the industrial carbon emissions efficiency and evolution characteristics of China from 2002 to 2015. The results show that (1) If carbon emissions from cement production are ignored and only energy-related carbon emissions are considered, the calculation results of carbon emissions efficiency of heavy industry will be overestimated about 30%. (2) Compared with 2002, China's industrial carbon emissions efficiency increased by about twice in 2015. Specifically, the optimization of carbon emissions efficiency in agriculture, construction, light industry and service industry is very obvious, which has increased by 5.65, 5.00, 4.69 and 4.68 times respectively; The optimization of carbon emissions efficiency in power sector, heavy industry, transportation and chemical industry was obvious, which increased by 2.55, 2.01, 1.86 and 1.47 times respectively; The carbon emissions efficiency of the fossil energy sector has decreased by 0.36 times. (3) The carbon emissions efficiency of various industries has significant differences. Among them, agriculture, service industry, light industry and construction industry are generally industries with higher carbon emissions efficiency, while power sector, fossil energy sector, transportation industry, chemical industry and heavy industry are generally industries with lower carbon emissions efficiency, especially power and fossil energy sectors. Based on these, this paper provides policy implications and scientific evidence for accurately improving carbon emissions efficiency from the perspective of carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

Combined decomposition of relative productivity growth and absolute changes in input/output variables helps to identify the driving forces of energy conservation and emission reduction. This paper proposes a framework based on the Luenberger productivity indicator (LPI) and the logarithmic mean Divisia index (LMDI) approach to analyze the energy–economy–environment nexus. The empirical case of the China's industrial sector for 2006–2014 is analyzed. Following this approach, we present a variable‐specific decomposition framework which attributes the overall productivity change and its sources to individual input/output variables. Empirically, we examine the relationships between the productivity growth and energy consumption within the LPI–LMDI framework across China's province‐level regions. The results show important spatial variation in the productivity measures. The LPI–LMDI decomposition implies that the industrial energy consumption increased with productivity growth appearing as the only mitigating factor. As regards the industrial SO2 emission, the individual productivity growth effect and the efficiency change effect remained as suppressing factors for emission abatement. These results can be used for evidence‐based decision making. [ABSTRACT FROM AUTHOR]

In the context of promoting high-quality development in the Yellow River Basin (YRB) of China, urgent action is needed to achieve the “Dual Carbon” goal through energy savings, emission reductions, and industrial upgrading. This study measures carbon emissions from eight types of energy consumption across 43 industries from 2000 to 2019. Using the KayaLMDI model, factors affecting carbon emissions are analyzed, and the relationship between industrial structure and carbon emissions is explored through the coefficient of variation (CV). The findings reveal that coal consumption remains significantly higher than other energy sources, and the effect of energy structure adjustment on carbon emission reduction is limited compared to the impact of energy consumption increase on carbon emission growth. Moreover, the economic output effect is identified as the primary driving factor of carbon emissions, while energy utilization rate is crucial in achieving energy savings and emission reductions. Finally, the CV of carbon emissions across 43 industries is increasing. Based on these results, we suggest several policy recommendations, including prioritizing ecological concerns, developing comprehensive and scientifically sound plans, optimizing energy consumption structure, improving energy utilization efficiency, and adjusting industrial structure to promote sustainable development in the YRB. [ABSTRACT FROM AUTHOR]

The rapid economic growth after the new millennium could be characterized by the reappearance of heavy industrialization and land urbanization. In the literatures, extensive studies have examined the impact of energy and emissions on the growth quality during the heavy industrialization process, but few have paid attention to the land dimension. This paper aims at studying the role of land use in changing the total-factor efficiency (TFE) in China's regional economy, together with the energy factors. The basic conclusions obtained are as follows: (1) the land and energy factors do have a statistically significant influence on the total-factor integrated efficiency (TFIE), leading to a much lower and not improved efficiency performance in the sample period. The integrated efficiency is dominated by the land factor rather than energy ones; and (2) the total-factor land efficiency (TFLE) is lower than the energy efficiency and has more room to improve. The land factor has a statistically significant influence on the total-factor energy efficiency (TFEE) but not vice versa. As compared to single-factor efficiency, the total-factor energy/land efficiency provides us a more precise measure of factor efficiency in China. [ABSTRACT FROM AUTHOR]

In the face of global warming, energy depletion, and air pollution, controlling greenhouse gas and air pollutant emissions has become an urgent task for an emerging economy. Therefore, this study investigates the synergistic relationship between haze decoupling and carbon emission decoupling in China, one representative emerging economy. Effect of synergistic decoupling is explored by decomposition model. Based on Geographically and Temporally Weighted Regression, this study also investigates spatiotemporal variation of the synergistic relationship between the two decoupling indices and the synergy effect of various factors. The main results are as follows. (1) Technological progress in CO2 is the main negative driving factor, and the ratio of potential CO2 to potential haze (potential ratio) is the main positive driving factor in the synergistic decoupling. (2) There is a synergy effect between two decoupling indices, and in the later period, the value of synergy effects tends to be flat. (3) The emission factor has the largest synergy effect. In the short term, the synergy effect of the population is greater than the energy intensity, but in the long run, the synergy effect of the energy intensity is greater than the population. These novel findings not only contribute to advancing the existing literature on synergistic emission reduction of environmental pollutions, but also merit particular attention from policy makers in the emerging economy. [ABSTRACT FROM AUTHOR]

This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40–45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China’s low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance. [ABSTRACT FROM AUTHOR]

Based on the logarithmic mean Divisia index (LMDI) approach, this paper presents a decomposition analysis of China's energy-related industrial CO2 emissions from 1985 to 2007, as well as a comparative analysis of differential influences of various factors on six sectors. Via the decomposition, five categories of influencing factors are included: (1) Per capita GDP (PCG) was the largest positive driving factor for industrial CO2 emissions growth for all sectors in China, with the largest cumulative contribution value; Population (P), economic structure (YS) and energy structure (ES) also played a positive driving role, but with weak contributions. As the only negative inhibiting factor, energy intensity (EI) significantly reduced the energy-related CO2 emissions from industrial sectors. Meanwhile, CO2 emissions reduction based on the efficiency of energy use still held a large space. (2) Various influencing factors imposed differential impacts on CO2 emissions of six sectors. [ABSTRACT FROM AUTHOR]

As the energy supply shortage and environmental pollution have increasingly become the major obstacles to China's economic development, the Chinese government has proposed various policies to reduce energy consumption, one of which is to implement a differentiated electric power price scheme (DEPP) on the energy-intensive industries (EIs). Although it is only imposed on EIs, its indirect impact on other sectors or national economy could be profound. This paper applies an input-output (IO) model, which composes 42 sectors calibrated with data in 2002 to examine the potential impact of DEPP. The results show that DEPP would result in significant energy savings at the expense of declines in gross domestic product (GDP) and increases in consumer price index (CPI). The ancillary benefits include reduction of emissions from the energy-intensive sector. [ABSTRACT FROM AUTHOR]

Nighttime light data can characterize urbanization, economic development, population density, energy consumption and other human activities. Additionally, carbon dioxide (CO2) emissions are closely related to the scope and intensity of human activities. In this study, we assess the utility of nighttime light data as a powerful tool to reflect CO2 emissions from energy consumption, analyze the uncertainty associated with different nighttime light data for modeling CO2 emissions, and provide guidance and a reference for modeling CO2 emissions based on nighttime light data. In this paper, Mainland China was taken as a case study, and nighttime light datasets (the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data) as well as a global gridded CO2 emissions dataset (PKU-CO2) were used to perform simple regressions at provincial, prefectural and 0.1° × 0.1° grid levels, respectively. The analyses are aimed at exploring the accuracy and uncertainty of DMSP-OLS and NPP-VIIRS nighttime light data in modeling CO2 emissions at different spatial scales. The improvement of nighttime light index and the potential factors influencing the effects of modeling CO2 emissions based on nighttime light datasets were also explored. The results show that DMSP-OLS is superior to NPP-VIIRS in modeling CO2 emissions at all spatial scales, and the bigger the scale, the more evident the advantages of DMSP-OLS. When modeling CO2 emissions with nighttime light datasets, not only the total amount of lights within a given statistical unit but also the agglomeration degree of lights should be taken into account. Furthermore, the geographical location and socio-economic conditions at the study site, such as gross regional product per capita (GRP per capita), population, and urbanization were shown to have an impact on the regression effect of the nighttime lights-CO2 emissions model. The regression effect was found to be better at higher latitude and longitude areas with higher GRP per capita and higher urbanization, while population showed little effect on the regression effect of the nighttime lights - CO2 emissions model. The limitation of this study is that the thresholds of potential factors are unclear and the quantitative guidance is insufficient. [ABSTRACT FROM AUTHOR]

With the growth of global population and economic development, people are facing the problem of increasing scarcity of renewable energy and unsustainable energy use. To achieve the sustainable development goals (SDGs) proposed by the United Nations, research on energy consumption efficiency has become particularly important. This research evaluates the energy consumption efficiency of 270 cities in China through an improved EBM model and finds a common phenomenon of low energy consumption efficiency in the cities, with the highest efficiency in northeast China and the lowest efficiency in eastern China. In addition, the efficiency of industrial exhaust emissions most significantly positively correlates with the efficiency of employed population and total energy consumption efficiency, while the efficiency of regional GDP does not significantly correlate with the efficiency of the two input variables. Using the LMDI method to decompose the driving factors of energy consumption efficiency in the cities, we find that the most important factor affecting energy consumption efficiency is their own energy endowment. Therefore, to improve the energy consumption efficiency of its cities, the China government should comprehensively consider factors such as regional economic development level, industrial structure, and technological level differences, formulate relevant energy-saving and emission-reduction policies, focus on optimizing the energy consumption structure, encourage technological progress and innovation, and help increase investment in science and technology. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we give an overview of the situation of CO2 emissions in both Beijing and Tokyo and discuss and compare the causes for their emission changes according to decomposition based on both social activities and fuel varieties. We find that in order to enjoy a sustainable development, Beijing needs to learn from Tokyo especially in energy consumption area. At the end of the paper, the cooperation between these two metropolises is summarized. [Copyright &y& Elsevier]

Abstract: This paper, by adopting the carbon emission calculating method for all kinds of energy proposed by IPCC in 2006, calculates the amount of carbon emissions of Shandong province. It turns out that carbon emissions in Shandong increased 2.63 times, carbon emission intensity increased 2.45 times and the carbon emission intensity and the energy intensity by GDP is obvious higher than the average level of China from 1997 to 2008.Taking into account the characteristics of carbon emissions in Shandong Province, the paper tries to propose the corresponding strategies to develop low-carbon economy. [Copyright &y& Elsevier]

Abstract: Making new coal-fired power plants carbon capture ready (Carbon Capture Ready) in China has been recognised as a crucial by a number of stakeholders academics, energy companies and regional government, based on a study in EU-UK-China NZEC project. A number of publications have investigated the definition, engineering requirements, economic and finance of CCR for China. However there remain a number of questions regarding the extent to which a plant’s physical location might constrain the feasibility of CCS retrofit. To address this issue, a Geographical Information System (GIS) has been used as a tool for mapping current and planned large carbon dioxide sources in Guangdong, also illustrating potential storage sites and calculating possible carbon dioxide transportation route. This paper investigates the location factors that should be considered when locating new build CCR power plants and demonstrates the methodology of using GIS software with spatial analysis in planning new build power plant in Guangdong. A preliminary study has identified over 30 large power plants within the region, with plant locations and historical emission data collected and presented in ArcGIS. Factors such as distance to potential storage site, route of CO2 pipeline, extra space on site and potential development plan etc. were investigated in the modelling and calculated the potential source and sink solution. The study then moves on to suggest possible new build plant locations which can be easily fitted in to the current network, based on economic optimisation. The scope for future coal plant development combined with a possible nuclear plant siting plan is discussed towards the end of the paper. Guangdong province, which owns the third largest coal-fired power installed capacity out of 31 provinces, generated over 8% of China’s total electricity every year for the past 15 years. CO2 storage opportunities could be found in the surrounding South China Sea, where Guangdong has a total of 4,300 km of coastline and some small scale oil fields on shore within the region. It is also among the first places to start the national open and reform policy in China. The province is one of the richest in China, with the highest GDP among all other provinces since 1989, and the foreign trade accounts for more than a quarter of China’s total amount. It also contributes around 12 of the total national economic output. Currently, the provincial government is proposing a low carbon roadmap, which is the first of its kind in China. The work has created a totally new thinking on capture ready power plant planning. This differs from existing studies (e.g., which aim to investigate the existing carbon dioxide emission sources at specified location and provide source and sink matching analysis. Instead the study focuses on policy implementation for new build capture ready power plants. Three clusters within Guangdong province are identified as potential temporary CO2 storage hubs before transporting the gas to a long term storage site. When officials are planning new power plant locations from a capture ready perspective, the plants should not necessarily be close to storage sites in straight line, but rather should be within a reasonable distance of a cluster. Transport of the captured CO2 will not be limited to pipelines, but could be extended to road and rail tankers. Power plant parameters and storage site data were collected for this research. Public transportation, utilities, landscapes, river, land used and population data were referenced from various sources; therefore, some of the data could be out of date. Nevertheless, it should still provide enough information when deciding the location of the transport cluster. Any future work could build on the existing model with updated data. Moreover, it could fit in with the national natural gas transportation network and utility planning network to provide long term integrated energy system analysis. The paper could provide policy makers, investors and urban planning officials with a view on how conventional thermal power plant investment and planning could be optimised, using Carbon Capture Ready designs, to keep the CCS retrofitting option open. [Copyright &y& Elsevier]

Household carbon emissions are important components of total carbon emissions. The consumer side of energy-saving emissions reduction is an essential factor in reducing carbon emissions. In this paper, the carbon emissions coefficient method and Consumer Lifestyle Approach (CLA) were used to calculate the total carbon emissions of households in 30 provinces of China from 2006 to 2015, and based on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the factors influencing the total carbon emissions of households were analyzed. The results indicated that, first, over the past ten years, the energy and products carbon emissions from China's households have demonstrated a rapid growth trend and that regional distributions present obvious differences. Second, China's energy carbon emissions due to household consumption primarily derived from the residents' consumption of electricity and coal; China's products household carbon emissions primarily derived from residents' consumption of the high carbon emission categories: residences, food, transportation and communications. Third, in terms of influencing factors, the number of households in China plays a significant role in the total carbon emissions of China's households. The ratio of children 0–14 years old and gender ratio (female = 100) are two factors that reflect the demographic structure, have significant effects on the total carbon emissions of China's households, and are all positive. Gross Domestic Product (GDP) per capita plays a role in boosting the total carbon emissions of China's households. The effect of the carbon emission intensity on total household carbon emissions is positive. The industrial structure (the proportion of secondary industries' added value to the regional GDP) has curbed the growth of total carbon emissions from China's household consumption. The results of this study provide data to support the assessment of the total carbon emissions of China's households and provide a reasonable reference that the government can use to formulate energy-saving and emission-reduction measures. [ABSTRACT FROM AUTHOR]

The inter-provincial inequality of per capita CO 2 emissions in China's electricity sector means that their responsibilities for CO 2 emission reduction are different. Considering the spatial separation of CO 2 emissions in power production and consumption, with respect to the large scale inter-provincial electricity trade in China, this paper innovatively investigates the sub-national inequality and polarization degree of per capita CO 2 emissions in China's electric power sector from the perspectives of both production and consumption. The overall tendencies of the sub-national polarization degrees of per capita CO 2 emissions embodied in the both electric power consumption and production in China show an increasing trend. The results indicate that the polarization distribution of per capita CO 2 emissions is still one of the important factors leading to difficulties in achieving the new reduction arrangements. The evolution of the bi-polarization analysis shows that the grouping results of per capita CO 2 emissions are different from production and consumption perspectives, as well as the high- and low-emission groups have significantly different characteristics. The inequality and polarization degree of per capita CO 2 emissions in China's electric power sector have changed as the CO 2 emissions embodied in the electricity trade had been taken into account. One-Size-Fits-All Strategies are unlikely to be successful in advancing the provincial cooperation on CO 2 emissions reduction. [ABSTRACT FROM AUTHOR]

The heat source types in China were not limited to the coal, other types of energy were introduced into the heating energy consumption in recent years, and therefore the specific regional impact of the heating emissions could not be obtained accurately according to the current achievement. Based on this, this study aimed to quantify the impact of the heating emissions on the air quality in an efficient and accurate way. A new method was proposed for investigating the quantitative impact of the heating emissions on the air quality index in this paper and its assumptions and accuracy were verified as well. The data employed in this method is extracted from Ministry of Environmental Protection Data Centre, Qingyue open source and Shanghai Central Meteorological Observatory. The key prerequisites of the proposed method were discussed in this study. By calculating, the averaged absolute difference of the meteorological parameters, namely Clo, WD, WS and P, is 3.58%, 2.40%, 3.21% and 3.94%, respectively. The difference ratio of the industrial emissions relative to the total emissions is as low as 4.3%. The optimal principal component number is six for the proposed method, which can satisfy the accuracy requirement with minimum workload. Compared with the results in previous similar studies, the proposed method showed excellent performance in analyzing the regional impact of the heating emissions on ambient air quality in China. Moreover, a total of 64 North cities in China were analyzed based on the proposed method to promote the knowledge on the influence of heating emissions on the environmental quality and the related parameters were provided in this study. [ABSTRACT FROM AUTHOR]

Improving energy efficiency has been recognized as the most effective way to reduce the greenhouse effect and achieve sustainable development. From the perspective of air emissions, this paper adopts data envelopment analysis approach to evaluate the energy efficiency in China’s coastal areas over the period of 2000–2012. Carbon dioxide, sulfur dioxide and nitrogen oxide are treated as undesirable outputs of energy consumptions. The proposed global Epsilon-based measure is used to estimate the static energy efficiency with an annual cross-section of data. The weights of the three undesirable outputs are determined according to their treatment costs. A global Malmquist-Luenberger productivity index based on directional distance function is employed to dynamically evaluate the energy efficiency. The results indicate the following in China’s coastal areas: (1) the level of economic development is positively related to energy efficiency scores; (2) energy efficiency scores decrease when considering undesirable outputs except Beijing and Hainan; (3) the Circum-Bohai Sea Economic Region greatly improves energy efficiency and has great potential of air emission; (4) the annual growth rate of Malmquist-Luenberger productivity index change is overestimated; (5) energy efficiency improvement is mainly driven by technological improvement, and scale efficiency and management level are the main obstacles. [ABSTRACT FROM AUTHOR]

Air pollution is increasingly a focus of concern worldwide due to its adverse impacts on human health and profound influences on global ecosystem. Although the existing studies have paid much attention to the causes of pollutant emissions, they fail to distinguish between direct and indirect factors, yielding the mixed results. Direct causes denote energy-related factors, as air pollutants are mainly produced by energy utilization directly, while indirect elements refer to socio-economic factors, as these factors act on pollutant emissions through affecting energy-related aspects. This paper investigated the impacts of three dominant direct factors: total energy consumption (EC), energy structure (ES) and treatment technology (TT) on sulfur dioxide (SO 2 ) emissions in China during 1995–2014 using the logarithmic mean Divisia Index method. Distinguished from the previous studies which took particular interest in SO 2 emissions from the industrial sector, this study put the total amount of SO 2 emissions as the target. The results show that increased EC was the main reason for SO 2 enhancement, while increasingly advanced TT played a dominant role in inhibiting the emissions throughout the study period. In contrast, ES had an unusually slight effect on SO 2 emissions due to its minor variation in the meantime. On regional scale, the differences in relative contribution rates (RCRs) of EC, ES and TT among the eastern, central and western regions all gradually decreased over time; EC in central region had the largest improved effect, ES in eastern region held the greatest reduction effect, and TT in western region got the biggest inhibitory effect. At provincial level, most provinces (60%) had relatively quick EC growth and slow ES adjustment (i.e., reducing the coal consumption rate); only Beijing, Tianjin, Shanghai and Sichuan had a relatively slow growth of EC and quick decrease in the percentage of coal consumption. Further, the projection of SO 2 emissions in four scenarios from 2015 to 2020 based on a grey projection model indicated that controlling both EC and ES would be the most efficient approach to SO 2 abatement followed by individually controlling EC and ES. [ABSTRACT FROM AUTHOR]

Municipal heating by coal contributes considerably to the haze pollution in Chinese cities during cold period, e.g., Beijing 53%. It is widely considered that, as a supplement of natural gas, the use of coal-based synthetic natural gas (SNG) to replace coal for municipal heating is conductive to mitigate the haze pollution in metropolitan areas. Would it still be a good alternative if the whole life cycle of SNG were taken into consideration? In this study, SNG as an alternative for municipal heating is analyzed in comparison with coal. To target cleaner production, life cycle assessment methodology is used to analyze SNG contribution to haze pollutants and greenhouse gases (GHGs) emissions, as well as energy consumption. Compared to coal heating route, SNG heating route could reduce 44% of the haze pollutants emissions from life cycle perspective and up to 98% of the emissions in urban area. Thus, if municipal heating were entirely supplied by natural gas and SNG, there would be 52% less haze pollutants emissions in winter of Beijing. However, this “good” performance is at the cost of transferring haze pollutants emissions from urban areas to SNG-producing regions. It is also at the cost of consuming 90% more coal and emitting 65% more GHGs than the coal heating route from life cycle point of view. To tackle the problems of haze pollutants transfer and the increase of GHGs emissions, the paper suggests implementing ecological compensation and carbon tax policies in the coal-based SNG industry. [ABSTRACT FROM AUTHOR]

Pollution emissions have become a matter of public concern in recent years. However, the vast majority of existing researches on PM 2.5 pollution are from the natural science perspective, and few studies have been conducted from an economic point of view. This paper adopts provincial panel data from 2001 to 2012 and panel data models to analyze the key driving forces of PM 2.5 emissions at the regional level in China. The results show that economic growth is a decisive factor of PM 2.5 emissions. The impacts of urbanization on PM 2.5 emissions vary across regions and decrease continuously from the central region to the western and eastern regions. The effects of private cars and coal consumption on PM 2.5 emissions in the eastern region are greater than that in the central and western regions because of significant differences in R&D investment, private car ownership and total coal consumption. Energy efficiency improvement has greater potential to mitigate PM 2.5 emissions in the central and western regions than that in the eastern region due to its low level of technology. Hence, in order to effectively reduce emissions, the Chinese government should consider all these factors as well as regional heterogeneity in developing appropriate mitigation policies. [ABSTRACT FROM AUTHOR]

As an effective technology to reduce traffic pollution emissions, the new energy vehicle industry has developed rapidly in recent years, and the sales of new energy vehicles have doubled in 2021. Accurately forecasting methods provide important references for industrial policy deployment, infrastructure construction and energy demand estimation. In order to predict the development trend of China's new energy vehicle industry under the limited data samples, this paper proposes an optimized discrete grey power model to fit the nonlinear relationship between grey information factor and temporal factor. Firstly, the grey differential equation and its discrete form are directly constructed by using power accumulated data, which simplifies the integral solution process of the traditional grey power model. Secondly, fractional accumulation operator is introduced into the discrete model to ensure the new information priority of the original data. Then, the heuristic algorithm is used to accurately estimate the new parameters of the proposed model. Thirdly, the proposed discrete model is the unified form of two existing discrete grey power models, which expands the scope of modeling and has higher adaptability. Simulation experiments and two numerical cases are used to verify the effectiveness of the proposed method. Finally, the proposed method is used to predict the annual sales and ownership of new energy vehicles in China. The predicted results show that by 2025, China's new energy vehicle sales will reach 8.84 million, accounting for about 24% of the total vehicle sales, surpassing the industry development target (20%) set by the Chinese government. [ABSTRACT FROM AUTHOR]

Protecting our environment while maintaining economic growth, requires a delicate balance among interlinked sustainable development policies. In this paper, we examine China's economic industries, including a high-resolution of the country's electricity sector during 2020–2030, using a multi-objective optimization model based on Input-Output analysis. This model, investigates the synergy and trade-offs of sustainable development goals in maximizing employment and GDP while minimizing energy and water consumption, CO 2 emissions, and five major pollutants to advance a sustainable industrial structure adjustment pathway for China. Our results reveal that there exists both synergies and trade-offs among multiple objectives, e.g., synergy among goals of minimizing air pollutant emissions and trade-offs between minimizing energy consumption and maximizing employment. Through the planned industrial restructuring period (2020–2030), the GDP, employment, carbon emission, and energy consumption will increase respectively by, 96.1%, 7.2%, 16.8%, 16.8%, and 6.3%, while pollutant emissions would decrease. Moreover, our research indicates that energy and water conservation should be prioritized in industrial structure adjustment strategies and policies. Our model demonstrates how the synergies and trade-offs among multiple policy targets can empower policy-makers, especially in developing nations, to make more informed and optimized industrial structure adjustment policies for sustainable development. • A multi-objective optimization model based on the Input-Output model is proposed. • Synergies and trade-offs among policy targets are examined. • The structural adjustment of economic sectors with fine-resolution power sectors is investigated. • The compromise solution and the most recommended policy priority are explored. [ABSTRACT FROM AUTHOR]

China's construction industry makes important contributions to energy consumption and pollution emissions. It is significant to improve energy efficiency in the construction industry. Since 2011, the introduction of China's carbon emission trading policy has had a great impact on energy conservation and emission reduction. The implementation of the carbon emission trading policy provides us with an opportunity to find solutions to improve the energy efficiency of the construction industry (EECI) in China. In this article, the implementation of carbon emission trading is regarded as a quasi-natural experiment, and the impact of the carbon emission trading policy on the energy efficiency of the construction industry is evaluated by analyzing the panel data related to the energy of the construction industry in 30 provincial regions from 2008 to 2016 through a difference-in-differences method. The main conclusions are as follows. First, the carbon emission trading policy can improve EECI. Second, the carbon emission trading policy can achieve the policy effect of improving EECI by optimizing the allocation of construction machinery resources and enhancing regional technical innovation. At the same time, strengthening government environmental regulation can strengthen the policy effect as well. Finally, some policy implications based on the study are proposed. [ABSTRACT FROM AUTHOR]

Analyzing the driving factors of PM2.5 pollution in different industries is of great significance for developing energy conservation and emission reduction policies in China's industries. In this study, the consumption-based PM2.5 emissions of China's industries are estimated by using an input–output model; on this basis, the generalized Divisia index method (GDIM) is used to measure the contributions of driving factors to the changes in PM2.5 emissions from China's six major industries. The results show that China's consumption-based PM2.5 emissions presented a downward trend from 2007 to 2015, the changes in industrial PM2.5 emissions had a much higher impact on China's total PM2.5 emissions changes than other industries and occupied a dominant position. The generalized Divisia index decomposition analysis results show that investment, output and energy consumption scale were the primary contributors to the increase of PM2.5 emissions in six sectors, with investment scale contributing the most. The investment PM2.5 emission intensity, output PM2.5 emission intensity and energy consumption PM2.5 intensity play a major role in suppressing PM2.5 emissions, while investment efficiency and energy intensity have a smaller inhibitory effect. Therefore, the government should guide investments to more high-end, low-emission industries and encourage companies to increase green investments and use renewable energy and clean energy. Avoiding excessive investments and improving investment efficiency in related industries can also effectively alleviate PM2.5 emissions. [ABSTRACT FROM AUTHOR]

Carbon Capture and Storage (CCS) has been viewed as an emission abatement option with great potential in China as coal has dominated China's energy consumption. China has already started to pay attention to CCS, as well as to the proposed the concept of ‘CCUS’ (which adds CO 2 Utilization into the chain of capture, transportation and storage). However, CCS is still in the early stages of its technological development, and the high cost, with several internal and external uncertainties make the role that CCS can play in China's future emission reduction unclear. From the perspective of general equilibrium analysis, this paper introduces CCS into a regional energy–economy–environment integrated assessment model, and makes a comprehensive evaluation of CCS's potential for future development and contribution to emission abatement in China. At climate policy level, the potential contribution of CCS in emission abatement has been evaluated against different future emission constraint scenarios in China. At technological level, the effects of endogenous learning and policy incentives on CCS have been investigated, and the substitution capacities of CCS and Non-hydro renewables to fossil energy have been discussed, as well as their technology penetration rates. Furthermore, the impact of CO 2 utilization on the development of CCS has also been discussed. [ABSTRACT FROM AUTHOR]

China is currently experiencing rapid urbanization. The building sector plays an important role in China's energy conservation and emission reduction. An increasing amount of energy will be steadily consumed in the building sector as the urbanization process accelerates. China's government attaches great importance to building energy efficiency (BEE). How does the urbanization process affect building energy consumption (BEC)? How much energy can be saved in the building sector through implementation of energy polices? These questions are critical for government development strategies and planning. Thus, in this paper, an econometric model (co-integration technique) is developed to analyze how China's BEC is affected by macroeconomic variables in the context of urbanization, and also forecast the BEC and BEE potential until 2020 under different scenarios. The research result shows that occupants’ lifestyles, residents’ living standards, and energy price have significant influences on BEC. The building sector is likely to contribute approximately 20% to China's energy conservation through electricity pricing reform. [ABSTRACT FROM AUTHOR]

The growing conflict between economic growth, energy and environment in China has restrained the country's economic development. In this work we investigated the interaction among the Chinese economy, energy production and consumption and the impacts of concomitant air emissions from 2000 to 2011, using an indicator system based on energy, emergy and money units. The results show that China's rapid economic growth has promoted tremendous expansion in energy production and consumption, which have led to increasing the impact of emissions in this study period. During the time examined, energy production and use efficiencies and the structure of the energy sector improved slightly; the self-sufficiency of energy use fluctuated, as petroleum took on an increasingly strong dependence on imports; fossil energy, mainly coming from coal, still has a majority share in energy production and consumption of the nation; the environmental loading intensity of energy consumption decreased slightly while that of energy production increased; most of the impacts of energy-related emissions are derived from their impact on human health; the impact of emissions from energy production made an increasing contribution to the total impact. Generally speaking, China's economic growth still heavily depends on energy-intensive industries that put great pressure on energy supply and pollution control. Although China has made obvious progress in energy mix optimization to save energy and reduce emissions, the pace of improvement still fell behind that of economic growth. Finally, this paper discussed some related issues and presented corresponding suggestions to further coordinate the relationship between the economy, energy production and consumption and the environment. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports China''s eco-efficiency trends and the cause of their dynamic behavior during the period 1978–2010. We show three main results. First, in general, eco-efficiency indicators increased for resource utilization, energy consumption and emissions for air and water, and relative decoupling occurred in China at a high level in the global context. Second, decoupling from economic growth has been absolute for the discharge of soot, chemical oxygen demand (COD) and ammonia nitrogen. Third, during the years 2001–2010, the decoupling level was very low, and resource utilization was almost coupled with GDP due to the high consumption and dramatic increase of mineral extraction. The causes of the observed dynamics of eco-efficiency and decoupling were also explored, with the conclusion drawn that the effect of technology was the predominant positive factor while structure effects were the negative factors for resource and energy efficiency; the technological effect of pipe-end treatment played a dominant role in the improving eco-efficiency of pollutant emissions and decoupling from economic growth. Furthermore, implications for further policymaking to setting proper targets for the relative decoupling of resource use, especially for mineral resource use and economic growth, are suggested. [Copyright &y& Elsevier]

Abstract: This paper analyzes the interactions among China''s economic growth and energy consumption and emissions during 1978–2007. Conventional energy and emergy are applied to quantify energy consumption and emissions’ impact respectively. Several indicators, based on emergy, energy and monetary units, are applied to depict the relationships among economic growth and energy consumption and emissions’ impact. The results show that energy consumption and emissions’ impact rise simultaneously. Therein, nonrenewable energy resources possess absolute share in total energy consumption and undertake primary responsibility for increasing emissions’ impact, and NH3–N in wastewater leads to the most emissions’ impact on environment. Energy mix and energy efficiency and pollution control make some achievements, but their improvements fall far behind economic growth rate. As a result, the structure of China''s economy has been obviously optimized; however, the improvement of the relationship between China''s economy, energy and environment is far behind that of its economic structure in this period. Therefore, China will continue to face huge pressure on resources and environment its rapid economic growth brings about in future. Those study results imply that enhancing energy efficiency, optimizing economic structure and strengthening pollution control will still be the main tasks for China''s governments in future. [Copyright &y& Elsevier]

This paper employs an extended Kaya identity as the scheme and utilizes the Logarithmic Mean Divisia Index (LMDI II) as the decomposition technique based on analyzing CO2 emissions trends in China. Change in CO2 emissions intensity is decomposed from1995 to 2010 and includesmeasures of the effect of Industrial structure, energy intensity, energy structure, and carbon emission factors. Results illustrate that changes in energy intensity act to decrease carbon emissions intensity significantly and changes in industrial structure and energy structure do not act to reduce carbon emissions intensity effectively. Policy will need to significantly optimize energy structure and adjust industrial structure if China's emission reduction targets in 2020 are to be reached. This requires a change in China's economic development path and energy consumption path for optimal outcomes. [ABSTRACT FROM AUTHOR]

Abstract: In order to further study the realization of carbon intensity target, find the key influencing factors of CO2 emissions, and explore the path of developing low-carbon economy, this paper empirically studied the influences of urbanization level, economic level, industry proportion, tertiary industry proportion, energy intensity and R&D output on CO2 emissions in Beijing using improved STIRPAT (stochastic impacts by regression on population, affluence and technology) model. The model is examined using partial least square regression. Results show that urbanization level, economic level and industry proportion positively influence the CO2 emissions, while tertiary industry proportion, energy intensity and R&D output negatively do. Urbanization level is the main driving factor of CO2 emissions, and tertiary industry proportion is the main inhibiting factor. In addition, along with the growth of per capita GDP, the increase of CO2 emissions does not follow the Environmental Kuznets Curve model. Based on these empirical findings and the specific circumstances of Beijing, we provide some policy recommendations on how to reduce carbon intensity. Beijing should pay more attention to tertiary industry and residential energy consumption for carbon emission reduction. It is necessary to establish a comprehensive evaluation index of social development. Investing more capital on carbon emission reduction science and technology, and promoting R&D output is also an efficient way to reduce CO2 emissions. [Copyright &y& Elsevier]

Abstract: This paper uses nonparametric efficiency analysis technique to estimate the energy efficiency, potential emission reductions and marginal abatement costs of energy-related CO2 emissions in China. We employ a non-radial slacks-based data envelopment analysis (DEA) model for estimating the potential reductions and efficiency of CO2 emissions for China. The dual model of the slacks-based DEA model is then used to estimate the marginal abatement costs of CO2 emissions. An empirical study based on China’s panel data (2001–2010) is carried out and some policy implications are also discussed. [Copyright &y& Elsevier]

Abstract: Reducing environmental pressure is a major concern for China but despite the improvements in energy efficiency, its gross carbon dioxide (CO2) emissions have maintained an upward trend, consistent with the Jevons Paradox. A fundamental shift is thus needed at all levels, including the household. This paper explores the embedded carbon footprint (ECF) of Chinese urban households associated with activities, such as food, personal transport, communications, education, recreation, health and hygiene. It uses an input–output model for carbon emissions and 2003–2009 urban household data. The results show that the total ECF emission intensity increases when an individual''s consumption is higher than 10,000 Yuan (¥). Structural changes are further observed with consumption expenditure above ¥10,000: food, clothing and other survival-oriented emissions intensities as well as education, health and development-oriented emissions intensities reduce; transport, recreation, housing and enjoyment-oriented emissions intensities increase or remain stable and the total emissions intensity increases. Currently per capita consumption expenditure of Chinese urban residents exceeds ¥10,000 and as income continues to rise, China will remain on a high-carbon track. There is a need for better policies, management and behavioural change and the study provides some policy suggestions, including a carbon quota system to guide individual consumption. [Copyright &y& Elsevier]

Abstract: Civil aviation in China has developed rapidly in recent years, and the effects of civil aviation emissions on the atmospheric environment should not be neglected. The establishment of emission inventories of atmospheric pollutants from civil aviation contributes to related policy formation and pollution control. According to the 2010’s China flight schedules, aircraft/engine combination information and revised emission indices from the International Civil Aviation Organization emission data bank based on meteorological data, the fuel consumption and HC, CO, NO x , CO2, SO2 emissions from domestic flights of civil aviation in China (excluding Taiwan Province) in 2010 are estimated in this paper. The results show that fuel consumption in 2010 on domestic flights in China is 12.12 million tons (metric tons), HC, CO, NO x , CO2 and SO2 emissions are 4600 tons, 39,700 tons, 154,100 tons, 38.21 million tons and 9700 tons, respectively. The fuel consumption and pollutant emissions of China Southern Airline are responsible for the largest national proportion of each, accounting for 27% and 25–28%, respectively. [Copyright &y& Elsevier]

Abstract: This paper examines the driving forces for reducing China’s CO2 emission intensity between 1998 and 2008, utilizing the logarithmic mean divisia index (LMDI) technique. By first grouping the CO2 emissions into two categories, those arising from activities related to the electric power industry and those from other sources, emission intensity is further broken down into the effects of the CO2 emission coefficient, energy intensity of power generation, power generation and consumption ratio, electricity intensity of the gross domestic product (GDP), provincial structural change, and the energy intensity of the GDP for other activities. The decomposition results show that improvements in the energy intensity of power generation, electricity intensity of GDP, and energy intensity of GDP for other activities were mainly responsible for the success in reducing China’s CO2 emission intensity and that activities related to the electric power industry played a key role. It is also revealed that performance varied significantly at the individual province level. The provinces with higher emission levels contributed the most to China’s improvements in CO2 emission intensity. [Copyright &y& Elsevier]

Abstract: In China, Rapid economic growth has stimulated fast urban expansion and rural household income and consumption expenditure. In current paper, an input–output method is used to determine the impact of China’s increased urban and rural household consumption on carbon emissions. The results shows that the direct and indirect CO2 emission from household consumption accounted for more than 40% of total carbon emissions from primary energy utilization in China in 1992–2007. The population increase, expansion of urbanization and the increase of household consumption per capita all contribute to an increase of indirect carbon emissions, while carbon intensity decline mitigates the growth of carbon emissions. Therefore, at the domestic level, household consumption is of great significance for CO2 emission, which could be mitigated through changing the composition of goods and services consumed by households, and switching to consumption pattern of less carbon-intensive products. The government must consider the substantial contribution of household consumption to carbon emissions when China is encouraging consumption in order to address the current global financial crisis. [Copyright &y& Elsevier]

Abstract: Low carbon economy has become a worldwide trend, many countries are seeking low carbon means to achieve environmentallyfriendly economy growth. However, various Greenhouse gases species in different industries, as well as various detection technology development levels in different countries lead to different carbon emissions accounting results eventually. So the accurate micro-level accounting on carbon dioxide emission is difficult to achieve while in the mean time, it is the basis for subsequent scenario analysis, which plays a crucial role in carbon pricing and carbon credits market promotion. That''s why the regional carbon dioxide emission accounting is a hot issue in low-carbon economy. Nowadays, automotive manufacturing industry has become a big fuel consumer in China and an important source of air pollution. So an accounting method focused on carbon dioxide emission in Chinese automotive industry is essential and practical significant. This paper proposed a whole-life cycle carbon emissions methodology to account carbon dioxide emission in Chinese automotive manufacturing industry, which is based on GREET and MOBILE model. And then the feasibility is verified through application in the automotive industry in Chongqing, China. [Copyright &y& Elsevier]

Abstract: Urban building system assumes significant environmental and ecological implications in terms of a contribution of emissions of CO2 and other greenhouse gases. In order to understand the roles of urban building system in the global and regional climate changes, we set up an integrated model to analyze the carbon emissions of urban building system during its life cycle in this paper, which is called LCCE Model. The further analysis is made to examine the sources of CO2 emissions and the life cycle characteristics of typical architectural structures as masonry-concrete and steel-concrete. We first identified four major sources of CO2 emissions during the whole life cycle of urban building system, which are industrial process emissions, energy consumption emissions, fugitive emissions and land footprint emissions. Given an assumption of a building life cycle of 50years, we took urban residential buildings as an example and calculated CO2 emissions in the main five phases of an overall life cycle of a residential building system, including constructive materials preparation, building construction and reformation, building operation, building demolition as well as wastes treatment and recycling. A comparison was made to examine the differences of CO2 emissions among buildings with two typical architectural structures as masonry-concrete and steel-concrete. The results show that the latter produces less CO2 emission than the former per unit area. Specifically, the amount of CO2 emission is 329.61t for masonry-concrete buildings and 315.79t for steel-concrete buildings per 100m2. Most emissions come from energy consumption and land footprint, accounting for 78–83% and 13–20% of the total emissions respectively. According to our LCCE model, there is a great potential of reducing carbon emissions in urban building system. The key to reduce carbon emissions during the life cycle of urban buildings is directed to building wastes recycling, improvement of consumption patterns of energy and materials, preferential use of buildings with a moderate floor area ratio and effective utilization of natural energy and ecologically friendly building materials according to the characteristics of local urban development. [Copyright &y& Elsevier]

Abstract: From the time of reform and opening up, China''s rapid economic growth attracts worldwide attention, which also brings the accompanying problems that high energy consumption, high pollution and high emission are more prominent. Therefore, the low carbon economy development model has become an inevitable choice for China''s sustainable economic development. However, the stage of economic development is insurmountable and the continuing growth and the disadvantaging structure of energy consumption will become a serious obstacle for China''s low-carbon economy. Selecting the relevant data from 1980 to 2009, and using not only Hebei Province as its study area but also the whole country as its reference region, this paper analyzes the relationship between the changes in energy consumption structure and the carbon emissions in Hebei Province, and basing on which predicts the energy consumption and carbon emissions in the future in order to provide policy recommendations for the optimization of energy consumption structure, the upgrade of industrial structure, and the development of carbon economy [Copyright &y& Elsevier]

Abstract: Based on 1992-2005 input-output tables at comparable price and using structural decomposition method (SDA), the paper decomposes carbon emissions growth from energy consumption in China into 4 categories of factors: carbon emissions intensity, technology, domestic final demand and trade. Carbon emissions have a trend of accelerated growth and the decisive factor is domestic final demand, not trade. Intensity of carbon emissions plays a significant restrain effect, entirely benefit from energy efficiency, rather than energy substitution. The effect of technical change leads to the growth of carbon emissions, reflecting the technology structure developed towards high energyconsumption and emissions. [Copyright &y& Elsevier]

Abstract: As one of the world''s top energy consumers and carbon emitters, China attracts extensive attention to its energy issues. Based on the hybrid energy input-output model, this paper forecasts the direct and indirect household energy demand growth caused by higher living standards in China with reference to a national well-off goal by 2020. Results show that such rigid energy demand will increase 1.55 billion tce by 2020 with average growth rate of 5.2% on static assumption, or 1.3 billion tce if energy conversion efficiency changes from 69% to 71.6%. If unchanged household energy consumption structure is assumed, total energy demand could decline from 5.5 billion tce to 4.9 billion tce by 2020. [Copyright &y& Elsevier]

Abstract: The “low-hanging fruits” (LHF) (or cream-skimming) problem receives some attention in recent years. However, few studies provide formal analysis on the LHF problem and other flaws based on economic theory. This paper investigates the LHF problem of Clean Development Mechanism (CDM) in China. The energy consumption and the Green House Gas (GHG) emission in China are outlined. The details of the CDM projects, including their distribution in China, and the types of projects are summarized. In order to test whether there were LHF problems in China, a simple statistical model is developed. The statistical analysis provides an indirect evidence that the LHF problem exists in China. The results indicate that areas with higher emission of GHG and low level of GDP per capita attract more CDM projects with higher amount of Certified Emission Reductions (CERs). The results are robust after eliminating HFC-23 decomposition projects from the sample. [Copyright &y& Elsevier]

Abstract: Energy-saving and emission-reduction are the major challenge to the development of countries in the world. When it comes to China, it refers to properly handle the regional issues. According to the common trends of the average industrial SO2 emission per square kilometer in three developed regions (Yangtze River Delta, Pearl River Delta and Bohai Economic Circle) and the remaining regions in the east, the middle and the west, this paper conducts an empirical analysis on the issue of pollution emission spilled from the developed regions to the remaining provinces. The result shows that the pollution emission in developed regions significantly demonstrates the role-model effect to the remaining provinces, and the effect will be weaken as the distance from the remaining provinces to three developed regions increases, which somewhat interprets the common trend of pollution emission among regions. Meanwhile, the role-model effect gives us the policy recommendation that China shall pay full attention to the exemplary role played by the developed regions on the issue of energy-saving and emission-reduction. [Copyright &y& Elsevier]

Abstract: This paper presents an overview of some recent CO2 storage capacity assessments in the Songliao and Subei Basins in China, and a discussion of some of the specific challenges that must be addressed to further assess the feasibility of CO2 storage in China. Geological CO2 storage associated with CO2-EOR is of significant interest in these basins as it offers potential to increase oil production and provide additional fuel to meet China’s increasing energy consumption. Although some CO2 is stored during such flooding projects, the greatest storage potential is only realised at the end of a field’s productive life, when a depleted field can be used as a dedicated CO2 storage reservoir. The Songliao Basin, in North-eastern China has been the largest oil and gas producing province in China. The oilfields of the Daqing and Jilin oil provinces are estimated to have effective CO2 storage capacities of 593 Mt and 71.2 Mt respectively. Extrapolation of data from around the oilfields to the whole basin suggests that the most promising saline aquifer in the basin has a theoretical storage capacity of 692 Mt CO2: Its effective storage capacity (which cannot be estimated due to lack of data) is likely to be considerably smaller however. Limited data availability means the estimate of storage capacity in this saline aquifer is based on gross simplifications and extrapolation across large areas (e.g. basin-scale) but could provide a basis for comparison with the potential for CO2 storage in other regions in China, or to help prioritise more detailed analysis. Although smaller, the onshore oilfields of the Subei-Yellow Sea Basin were also assessed, as the presence of mature oil and gas fields and natural CO2 accumulations, suggest suitable targets for storage may be found. The total effective storage capacity of the 108 hydrocarbon fields in this basin are estimated to be only 21 Mt CO2. While small, these fields may offer niche storage options for smaller industrial CO2 sources, but if CCS is to contribute to reducing China’s growing CO2 emissions, then further evaluation and development of storage in saline aquifers is likely to be needed at the same time as storage in oil or gas fields. [Copyright &y& Elsevier]

Abstract: This paper uses the methods of co-integration analysis and Granger Causality test, analyses the relationship between energy consumption and economic growth of Hebei Province from 1980 to 2008. The empirical results show that there is a stable causal relation between TEC and GDP in the long run. Hebei''s economic growth contributes to energy consumption growth. To change economic development mode and save energy, reduction of pollutant emission will not only impact the economic growth, but also achieve energy-saving, emission reduction and sustainable development. [Copyright &y& Elsevier]

Abstract: This paper uses multivariate co-integration Granger causality tests to investigate the correlations between carbon dioxide emissions, energy consumption and economic growth in China. Some researchers have argued that the adoption of a reduction in carbon dioxide emissions and energy consumption as a long term policy goal will result in a closed-form relationship, to the detriment of the economy. Therefore, a perspective that can make allowances for the fact that the exclusive pursuit of economic growth will increase energy consumption and CO2 emissions is required; to the extent that such growth will have adverse effects with regard to global climate change. [ABSTRACT FROM AUTHOR]