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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]

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]

In order to explore the comprehensive assessment method of air quality of pollutant emission of energy consumption in China's urban internal industrial parks, based on the full consideration of the actual situation of air pollution control in Nanjing HX Industry Park, this paper selects 15 air quality assessment indicators. According to the national air quality standard, the air quality standard of Nanjing and the air quality standard of Nanjing HX Industry Park, the air quality assessment standard is determined about pollutant emission of energy consumption in Nanjing HX Industry Park. Through the technical treatment of the selected assessment indicators, the niche suitability model is introduced, and based on this, the spatial niche suitability model is reconstructed to comprehensively assess the air quality of pollutant emission of energy consumption in Nanjing HX Industry Park. The study found that the air quality of Nanjing HX Industry Park has been improved from level III in 2012 to level I in 2020. According to the assessment results, the differences of assessment results of different niche suitability models are discussed, which fully reflects the advantages of spatial niche assessment methods. The change law and influencing factors of the assessment results are further discussed. [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 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]

Over the past decades, China's vast regional disparities in resource endowment, economic development, and industrial structure have driven large-scale relocations of high energy-consuming industries (RHEIs). Despite extensive research on broad-based industrial relocation and emission transfer, the trend, structure and environmental impact of China's RHEIs need further investigation. This paper employs the multi-regional input-output model (MRIO) to calculate the trend, scale, and structure of the RHEIs among China's 30 provinces. Additionally, we investigate the RHEIs' effect on green total factor energy efficiency (GEE) and its heterogeneity. Our results indicate that the net inflow of high energy-consuming industries decreases GEE, with a more noticeable effect observed in central provinces and after the execution of the Belt and Road Initiative (BRI). However, the positive effect of RHEIs on GEE in outflow areas is more substantial than their negative impact in inflow areas, suggesting that RHEIs can enhance overall efficiency. This study contributes to the understanding of China's industrial relocation by providing valuable insights into China's RHEIs. • China has a large-scale relocation of high energy-consuming industries. • The relocation of China's high energy-consuming industries is calculated. • The relocation's impact on green total factor energy efficiency is analyzed. • Regional heterogeneity is found among different provinces. [ABSTRACT FROM AUTHOR]

This study explores how an institutional innovation in the 20th Century – Coasean bargaining - could contribute to build a low carbon China in the 21st Century. China has surpassed all nations and become the world's largest emitter of CO 2 since 2007. A time-series analysis has revealed that crude oil and coal consumption, inter alia, are the primary factors contributing to the variations in CO 2 emissions in China. To honour China's commitments in the Paris Agreement 2015, this paper, with reference to the empirical results, estimates the impacts on various sources of energy consumption before 2030. Developed upon the Coasean bargaining framework (1960), the cap-and-trade (CAT) markets have contributed to reduce the pollutants and greenhouse gas emissions in the US and EU. This paper will illustrate how the CAT market can be complementary to administrative measures for CO 2 reduction in China. It will also discuss the institutional settings and constraints of the 7 pilot CAT markets in China, and also the national one to be rolled out in 2017. [ABSTRACT FROM AUTHOR]

• A dynamic time-delay calculation algorithm based on MI and adaptive sliding window (MIDTA) is proposed. • MIDTA algorithm is used to solve the problem of long time-delay of cement kiln. • An algorithm of residual network and bidirectional novel gated recurrent unit (ResNet-BiNGRU) is proposed. • A Gaussian-weighted multi-model fusion method is proposed. • MIDTA-ResNet-BiNGRU multi-model fusion algorithm can be used to measure the temperature of cement rotary kiln with high precision. China's cement production energy consumption accounts for more than 10% of the country's total energy consumption, and its emissions account for about 60% of the country's industrial emissions. The temperature of a cement rotary kiln directly affects the quality of the final product, the energy consumption of a plant, and emissions. Therefore, it is necessary to measure, to a high degree of accuracy, the temperature of a cement rotary kiln to reduce energy consumption, emissions, and improve product quality. However, the conditions in cement kilns are complex and variable; and there are large time-delays, while temperatures are affected by historical working conditions, making temperature measurement extremely difficult. In this paper, a modelling algorithm with a residual network and a bidirectional novel gated cycle unit is used to predict the clinker exit temperature of the rotary kiln. In addition, to solve the problem of large time-delays in cement kilns, a dynamic time-delay calculation algorithm based on Mutual information and adaptive sliding windows is proposed for time series data reconstruction, and finally a Gaussian-weighted multi-model fusion is applied to the prediction results for cement rotary kilns that produce a wide range of working conditions. To verify the advantages and feasibility of the proposed method, experimental validation is carried out using original production data from a large cement manufacturing enterprise in South China. The results demonstrate that the single step prediction time of the presented approach is 0.66 s, which can predict cement kiln temperatures quickly and accurately, compared to a single conventional forecasting algorithm, the average temperature difference dropped from 11.76 °C to 3.51 °C, R2 increased from 0.43 to 0.89, 94% of the depicted temperature errors are at ± 10 °C This will provide an effective solution for online decision-making during actual cement production. [ABSTRACT FROM AUTHOR]

Abstract: With increasing attention on energy shortage and global warming, bioenergy is a promising alternative energy to mitigate CO 2 emissions. Despite the environmental friendly potential, a certain quantity of bioenergy-related CO 2 is still emitted in China. This paper investigates the temporal dynamics of bioenergy-related CO 2 emissions in 2000–2010 in China, and explores the underlying influence factors based on logarithmic mean Divisia index (LMDI). Then the core results are verified with a GIS-based approach from a spacial perspective. The results show that four impact factors: emission intensity, energy structure, energy efficiency and economic development have different impacts on bioenergy-related CO 2 emissions, of which economic development is the major factor contributing to its increase, while energy efficiency is the major determinant for the decline. Per capita bioenergy-related CO 2 emissions in different areas are verified in accordance with either economic development factor or energy efficiency factor to some extent. To achieve the dual purpose of sustainable development and CO 2 emissions reduction, this paper provides a practical policy framework for rural bioenergy and economic development. [ABSTRACT FROM AUTHOR]

An improvement in industrial carbon emission efficiency is crucial for achieving both reductions in carbon emissions and sustainable economic growth. In this paper, we use an improved non-radial directional distance function (NDDF) to construct a new meta-frontier total-factor carbon emission efficiency index ( TCEI ) with which we estimate the meta-frontier TCEI of China's 30 provincial industrial sectors in 2005–2015 and analyze their dynamic evolution. The results show that compared to traditional NDDF, the improved NDDF has more advantages in measuring both carbon emission efficiency and the technology gap ratio. For the study period, China's industrial meta-frontier TCEI is low, indicating that the industrial TCEI of many provinces still has much room for improvement. The meta-frontier TCEI has significant inter-group heterogeneity, with Eastern China having the largest carbon emission efficiency, followed by Central China, and Western China having the lowest. China's industrial meta-frontier TCEI increased significantly during the study period with technical progress playing a major role in promoting it. Over time, however, the meta-frontier TCEI growth rate decreased significantly as the deterioration in technological efficiency and the expansion of the technology gap have jointly inhibited the growth of carbon emissions efficiency. Carbon emission performance in various regions over different periods exhibit differing characteristics, that is, the carbon emission performance has significant spatial heterogeneity and period heterogeneity. [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]

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]

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]

Abstract: This paper analyzed the interactions among China’s economic growth and its energy consumption, air emissions and air environmental protection investment during 2000–2007. Conventional energy and emergy are applied to quantify energy consumption and emissions’ impact, respectively. The five indicators based on money, energy and emergy, including ratio of nonrenewable energy to renewable energy (RNR), energy use per unit GDP (EUPG), environmental cost per unit GDP (ECPG), impact of emissions per unit energy consumption (IEPEC), and environmental benefit per unit environmental protection investment (EBPEI), are presented to depict the relationships among economic growth and energy consumption and impact of air emissions and air environmental protection investment. The results show that energy consumption rapidly rises with China’s fast economic growth; however, energy efficiency and environmental loading intensity from energy consumption are reduced simultaneously but their improvements fall far behind economic growth rate. Impact of air emissions, mainly composed of impact of emissions on human health (especially dust), is slightly decreased. The performance of air environmental protection investment is obviously declined in the study period. Generally speaking, the conflict among economy, energy and air environment protection is slightly mitigated but still acute due to great dependence of China’s economy on fossil energy and inefficient environmental protection measures. Finally, this paper discusses the corresponding issues, and then puts forward some related suggestions. [Copyright &y& Elsevier]

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]

China is one of the largest energy consumers and CO emitters globally. The growth rate of energy consumption in China is about 6 % per year, and it consumed 21 % of the world's total energy in 2012. In recent years, the Chinese government decided to introduce several energy policy instruments to promote energy efficiency. For instance, the reduction targets for the level of energy intensity have been defined for provinces in China. However, energy intensity is not an accurate proxy for energy efficiency because changes in energy intensity are a function of changes in several socioeconomic factors. In this paper, we present an empirical analysis on the estimation of the persistent and transient energy efficiency of Chinese provinces by employing a log-log aggregate energy demand frontier model. The model is estimated by using data on 29 provinces observed over the period 2003 to 2012. Several econometric model specifications for panel data are used: the random effects model and the true random effects model along with other versions of these models. Our analysis shows that energy intensity cannot measure accurately the level of efficiency in the use of energy in Chinese provinces. Further, our empirical analysis shows that the average value of the persistent energy efficiency is around 0.81 whereas the average value of the transient energy efficiency is relatively high and shows a value of approximately 0.97. By improving the level of efficiency in the use of energy to 100 %, the total energy consumption in China would decrease by approximately 1000 Mtce, which corresponds to 25 % of total energy consumption in 2012. [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]

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]

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]

The issue of China's CO2 emissions has become a major focus of the growing concerns, globally, for its potential impact on Climate Change. In this paper, supply chain paths that drive changes in life cycle CO2 emissions in China from 1992 to 2007 were identified, based on SPD (structural path decomposition) analysis of China's input–output tables and energy demand changes, over this study period. The study period was divided into three stages: 1992–1997, 1997–2002 and 2002–2007. The influence on changes of CO2 emissions derived from final demand was divided into six factors: direct CO2 emission intensity (e); industrial structure (A); product structure of final demand (ψ); category composition of final demand (Δ); per capita final demand (Y), and population (P). The detailed analysis reveals that direct CO2 emissions intensity (e) was the dominant factor in reducing China's CO2 emissions, while per capita final demand (Y) was the major single factor increasing the emissions. The largest influence on CO2 emissions from the viewpoint of supply chain paths was found to be “Chemical industry → exports”. The supply chain paths with high emissions at different stages during the study were “Metal smelting → exports”, “Nonmetallic products → fixed capital” and “Metal smelting → fixed capital”, respectively. [ABSTRACT FROM AUTHOR]

To mitigate the climate change and reduce energy consumption, the Chinese government has applied a variety of polices during the last two decades. Based on data from Industrial enterprises emission and pollution database (IEPED) and Annual Survey of Industrial Firms (ASIF), this study takes Energy Saving and Emission Reduction Plan (ESER) since 2006 as a policy shock to explore the impact of the ESER on industrial firms' energy consumption behavior. The result shows: Firstly, ESER encourages industrial firms to consume less coal, petroleum and natural gas on average. Secondly, by dividing the firms into several groups by the ownership structure, the firm size and the firm age, this paper finds different firms have different strategies in terms of changing their energy consumption to respond ESER. For example, public firms work harder on reducing coal and petroleum consumption per production while private firms prefer to use more natural gas per production. Thirdly, the dynamic effect analysis portrays that traditional fossil fuel intensity declines immediately after energy conversation policy, while the negative effect on industrial firms' natural gas intensity could occur with some delay. Lastly, in terms of total energy consumption, average coal and petroleum consumption of polluted industries and that of non-polluted industries have no difference after the policy. In addition, ESER only has a short-term effect on energy consumption. These results are helpful in understanding how to design an efficient environmental regulation system and protect the environment simultaneously. • This study explores the impacts of the Energy Saving and Emission Reduction Plan (ESER) on firms' energy consumption behavior based on industrial firm data. • ESER encourages firms to consume less traditional energy (coal and fossil fuels) and clean gas. For different firms, their energy intensity changes distinctively in response to ESER. • The dynamic effect analysis portrays that traditional fossil fuel intensity declines immediately after energy conversation policy, while the negative effect on clean gas intensity occur with some delay. • ESER has a short-term and lagged effect on total energy consumption. [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]

Abstract: This paper employs a spatial dynamic panel model to forecast China's energy consumption in 2011–2020. We find that energy consumption would continue to increase at least till 2020, with annual growth rates of 10% in 2011–2015 and 6% in 2016–2020. A higher proportion of service sectors in the economy and technological progress reduce energy demand. However, the latter appears to have dwindled impact since 2001. Strong spatial dependence implies copying behaviour in energy consumption across regions. Therefore, more efficient energy control at the disaggregated level can have multiplied impact on the country's goal in energy saving and carbon emission reducing. [Copyright &y& Elsevier]

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]

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]

Abstract: Road transport today is responsible for a significant and growing share of anthropogenic emissions and energy consumption. This paper attempts to address the possible policy measures to reduce the energy consumption and mitigate the harmful emissions, especially greenhouse gas (GHG) from China''s road transportation sector. Five scenarios, which assess electric or/and hybrid vehicles, are designed and examined to estimate the potentials for reducing consumption and emissions. It is concluded that comprehensive and appropriate strategies be promoted to minimize the adverse impacts of China''s road vehicles on energy demand and environmental sustainability. For future policy implementation, it is appropriate to promote both high-efficient pure electric and hybrid vehicles simultaneously and improve shares of both types by a wide margin. To be more specific, significant energy saving and emissions reduction can be achieved by promoting electric vehicles in some subsectors (such as Passenger vehicle (PV), Light truck (LT), Bus and Motorcycle (MC)), and by promoting hybrid vehicles in other subsector (Heavy truck (HT)). Our results can provide better insights for both policy makers and practitioners in the field. [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: The biogas-linked agriculture has experienced a rapid development in recent years in rural China, which serves both as part of the country''s developmental strategies of cleaner energy and an important reaction to sustainable agriculture call. This paper provides an overview of the economic and environmental performance of biogas-linked agrosystem (BLAS) in China by focusing on efficiency, emission mitigation effect and sustainability. An emergy synthesis combing emergy accounting and emergetic ternary diagram are utilized to evaluate the overall BLAS and its four subsystems (i.e., planting subsystem, breeding subsystem, aquaculture subsystem and biogas subsystem) in terms of current status and future development. Our findings indicate that despite a high energy transformity at system scale and a great dependence on economic input, BLAS advantages itself with high biogas production efficiency and significant emission mitigation effect. Furthermore, the sustainability zone analysis shows that the overall BLAS, planting and aquaculture subsystems maintain medium-term sustainability under all policy scenarios, despite the fact that breeding and biogas subsystems stay in an unsustainable situation due to their relatively severe environmental load. Among all the studied future options, continual biogas construction and effective technological revolution instead of expanding investment in traditional agriculture are preferable routes to further improve the system performance. Last but not least, emissions mitigation, energy efficiency and system sustainability are unveiled to be positively correlated within BLAS, which entitles it a promising energy alternative to enhance biogas energy utilization in the local agriculture in face of today''s energy crisis. [Copyright &y& Elsevier]

Abstract: With the intensification of global warming, the issue of carbon emissions causes more and more attention in recent years. In this paper, China’s 30 provincial-level administrative units are divided into five emission regions according to the annual average value of provincial CO2 emissions per capita during 1990 and 2010. The regional differences in impact factors on CO2 emissions are discussed using STIRPAT (stochastic impacts by regression on population, affluence, and technology) model. The results indicate that although GDP (Gross domestic product) per capita, industrial structure, population, urbanization and technology level have different impacts on CO2 emissions in different emission regions, they are almost always the main factors in all emission regions. In most emission regions, urbanization and GDP per capita has a bigger impact on CO2 emissions than other factors. Improving technology level produces a small reduction in CO2 emissions in most emission regions, but it is still a primary way for CO2 reduction in China. It’s noteworthy that industrial structure isn’t the main factor and improving technology level increases CO2 emissions in high emission region. Different measures should be adopted for CO2 reductions according to local conditions in different regions. [Copyright &y& Elsevier]

Abstract: The interplays among economy and energy and environment have been widely concerned. This paper put forward several indicators to quantify the relationships among economic growth and energy consumption and CO2 emission. As an example, these indicators were applied to evaluate the comprehensive performances of China during 1990–2007. The results show that Chinese people has been living a better life with Chinese rapid economic growth but not synchronously in urban and rural areas. Non-carbon energy resources share has increased; however, fossil energy resources have still acted as the main driver for Chinese economic growth during this period. Technical progress has improved the fossil energy efficiency of Chinese economic activity, which leads to CO2 emission per unit GDP and CO2 emission per capita unit GDP dropping simultaneously; however, the two indicators’ annual decline rates become smaller and smaller, which reflects that technical progress’ role is dropping and economic scale''s effect is climbing. People''s survival has a rising contribution to CO2 emission. CO2 emission per capita has increased, which shows that economic scale has greater impact on CO2 emission than technical progress does. Relatively speaking, Chinese development patterns have become more and more sustainable during this period. Finally, based on the related issues being discussed, some corresponding suggestions are put forward for Chinese government to further coordinate the relationship among economic development and energy consumption and CO2 emission. The proposed indicators can form a set of useful tool for policy-makers to promote the harmonious development of economy and energy and environment in different regions and countries. [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]

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]

Abstract: This paper addresses the impact of both economic growth and financial development on environmental degradation using a panel cointegration technique for the period between 1980 and 2007, except for Russia (1992–2007). In long-run equilibrium, CO2 emissions appear to be energy consumption elastic and FDI inelastic, and the results seem to support the Environmental Kuznets Curve (EKC) hypothesis. The causality results indicate that there exists strong bidirectional causality between emissions and FDI and unidirectional strong causality running from output to FDI. The evidence seems to support the pollution haven and both the halo and scale effects. Therefore, in attracting FDI, developing countries should strictly examine the qualifications for foreign investment or to promote environmental protection through the coordinated know-how and technological transfer with foreign companies to avoid environmental damage. Additionally, there exists strong output-emissions and output-energy consumption bidirectional causality, while there is unidirectional strong causality running from energy consumption to emissions. Overall, the method of managing both energy demand and FDI and increasing both investment in the energy supply and energy efficiency to reduce CO2 emissions and without compromising the country’s competitiveness can be adopted by energy-dependent BRIC countries. [ABSTRACT FROM AUTHOR]

Abstract: The automobile industry in China has rapidly developed in recent years which resulted in an increase in gasoline usage and greenhouse gas (GHG) emissions. Focus on climate change has also accelerated to grow pressure on reducing vehicle weight and improving fuel efficiency. Aluminum (Al) as a light metal has demonstrated a great potential for weight savings in applications such as engine blocks, cylinder heads, wheels, hoods, tailgates etc. However, primary Al production requires intensive energy and the cost of Al is more than traditional steel, which may affect the total benefits realized from using Al in automobiles. Therefore, it is very essential to conduct a study to quantify the life cycle GHG emissions and energy consumption if the plan is to achieve fleet-wide Al intensive vehicles. This paper describes a life cycle assessment (LCA) methodology and the general modeling assumptions used to evaluate the impact of Al intensive vehicle on GHG emissions and energy consumption. The results indicated that the reductions in life cycle GHG emissions and energy consumption were not significant when the maximum Al content in an automobile is 145 kg, which is the average level of Al usage in automobiles in North America. A neural network methodology was used to forecast the vehicle stock in China from 2010 to 2020 and a vehicle fleet model was established to track GHG emissions and energy consumption of the vehicle fleet. A material availability factor was also introduced into the LCA methodology to further assist decision makers in providing rational proposals for a widespread implementation of Al in automobiles. A sensitivity analysis was also conducted to study the impact of the Al content in a vehicle on the final outcomes. The GHG emissions and energy consumption could be further reduced when the Al content in an automobile increases. [ABSTRACT FROM AUTHOR]

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]

Abstract: The aim of this paper is to compare different end-of-life tire (ELT) treatment technologies in China from an environmental and economic perspective. Four treatment technologies were evaluated: ambient grinding, devulcanization, pyrolysis and illegal tire oil extraction. Life cycle assessment (LCA) was applied to evaluate the potential environmental impact of each treatment based on the Eco-indicator 99 (Hierarchist approach) method provided by GaBi 4 software. The final result shows that pyrolysis represents the environmentally benign option while illegal tire oil extraction caused the worst damages. For the three legal treatments, although high credit was obtained when considering avoided impacts from recycled materials and energy, they have great impact as to respiratory effects (inorganic) dominantly contributed by energy production stage, which implies that the emphasis on environmental policies related to ELT treatment should shift from the control of emissions from treatment process to the reduction of energy consumption. A simplified comparison of net benefits and total impacts shows that the most eco-effective ELT treatment technology is pyrolysis, followed by dynamic devulcanization and ambient grinding. The illegal tire oil extraction, however, must be prohibited immediately because of its highest environmental pollution and lowest net benefit. [ABSTRACT FROM AUTHOR]

Abstract: As a physical assessment of the sustainability of the China society, presented in this paper is an exergy-based systems account for resources use and environmental emissions of the China society in 2006 as the most recent year with statistics availability. Exergy analysis is applied to elucidate the resources flows from the natural environment into the society, between other countries or regions and the society, between the sectors of the society, and the emissions outflows into the natural environment from different sectors. For the China society broken down into seven sectors (i.e., extraction, conversion, agriculture, industry, transportation, tertiary and households) as one of the most complicated cases, systems account of environmental emissions as greenhouse gases and “three wastes” is carried out for the first time, combined with an updated resources account. The total societal exergy consumption amounts to 101.1EJ, of which 93.6% is due to resources use accounted as 94.6EJ, of which 23.2% is by the industry sector, 22.8% by conversion, 20.4% by households, 12.3% by agriculture, 9.0% by tertiary, 6.9% by extraction and 5.4% by transport, and 6.4% due to environmental emissions accounted as 6481.6PJ, including greenhouse gas emissions of 5706.1PJ, with the highly remarkable fraction of 49.05% from CH4 of the same importance as 50.91% from CO2 and only 0.04% from N2O, and “three wastes” emissions of only 775.5PJ. The extraction sector is shown as the leading emitter with 32.6% of the total emissions, followed by the industry with 20.0%, agriculture with 17.3%, and conversion sector with 16.8%. To characterize the network performance in context of environmental resources from a systems ecological perspective, exergy-based ecological efficiency and resources conversion coefficient are found as 88.8% and 91.3% for the extraction sector, 29.0% and 30.0% for the conversion sector, 31.5% and 33.5% for the agriculture sector, 34.8% and 36.1% for the industry sector, 16.3% and 17.3% for the transportation sector, 38.4% and 38.5% for the tertiary sector, and only 1.3% and 1.3% for the households sector, respectively. Comparisons with other societies and with China society in previous years are made to further illustrate the physical sustainability of the societal system on the international and development horizons. [Copyright &y& Elsevier]

Abstract: Knowledge of influencing factors of industrial carbon emissions (ICE) is crucial to the efforts of reducing anthropogenic greenhouse gas emissions. In this paper, main factors responsible for the ICE in Shanghai between 1996 and 2007 were identified and quantitatively analyzed using the Log-Mean Divisia Index method. It was found that the industrial output was the main driving force of ICE. The decline in energy intensity and the adjustment of energy and industrial structure are major determinants for reduction of ICE, with the former alone accounting for 90% of the reduction. To better investigate the relative contribution of different industrial sectors and their changes over time, we divided the study period into two equal time intervals and analyzed some high-carbon emission sectors. The results suggested that the intensity of energy use should be reduced further, for it was far higher than the world average. Adjustment of industrial structure by developing low-carbon emission industries is more crucial than energy mix. [Copyright &y& Elsevier]