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The conventional air conditioning system used in high-speed railways has limitations in heating performance and environmental impact, necessitating the exploration of alternative refrigerants. The transcritical CO 2 system has gained popularity due to its exceptional heating efficiency and environmental benefits. This study aims to evaluate the energy and environmental potentials for transcritical CO 2 systems in high-speed trains based on four-vertical-and-four-horizontal railway lines within different climatic regions of China. A high-fidelity transcritical CO 2 system model was first developed and validated through experiments. Then, a comprehensive energy and environmental evaluation method was proposed and applied to the four-vertical-and-four-horizontal railway lines. The results indicated that the transcritical CO 2 system had a superior heating performance and competitive cooling performance based on daily and annual operations. Furthermore, the transcritical CO 2 system exhibited significant environmental advantages with lower total life cycle climate performance for all lines, with an average emissions reduction ratio of 17.6% and a maximum emissions reduction ratio of 26.98%. These findings highlight the competitive energy performance and outstanding environmental benefits offered by transcritical CO 2 systems as promising alternatives to air conditioning systems in railway transportation. • This paper evaluates the potential of theCO 2 system in high-speed trains from an energy performance and environmental benefits perspective. • A high-fidelity model of the transcritical CO 2 system is developed and validated for effectiveness through experiments. • The energy and environmental evaluations are conducted based on China's four-vertical-and- four-horizontal railway lines. • The results indicate that the CO 2 system presents a competitive alternative for air conditioning systems in high-speed trains. [ABSTRACT FROM AUTHOR]

Mitigating greenhouse gas emissions is a significant global challenge, and precise prediction of carbon emissions holds the utmost importance for China to attain its dual carbon goal. To overcome the limitations of existing studies using a single forecasting method, based on quadratic exponential smoothing, multiple linear regression, and Gaussian process regression models, this paper constructs a carbon emission combination forecasting model with the generalized induced ordered weighted average (GIOWA) operator and analyzes carbon emission reduction performance. Empirical testing utilizing China's carbon emission data from 1980 to 2020 reveals the following findings: (1) The GIOWA combination forecasting model significantly enhances the accuracy of carbon emission forecasts, with an average accuracy exceeding 99.5% over the sample period, surpassing various single forecasting methods. (2) The carbon emission reduction target can be achieved under three different scenarios of low, average, and high GDP growth rates. Specifically, under the low growth rate scenario, China can achieve a 60% reduction in carbon intensity by 2025 and a 65% reduction by 2030. This study offers valuable decision support for the development of effective carbon reduction policies. [ABSTRACT FROM AUTHOR]

This paper investigates the decoupling of carbon dioxide (CO 2 ) emissions from agricultural economic growth in 30 Chinese provinces from 1997 to 2014. First, CO 2 emissions from agricultural production activities, farming, and livestock husbandry are computed. Then, this paper explores the spatial and temporal heterogeneity of CO 2 emissions and their intensity in China’s agricultural sector. Finally, this paper compares decoupling of China’s agricultural CO 2 emissions from agricultural output value across different regions and years. The results indicate that fertilizer, in-season rice cultivation, and cattle generated the most CO 2 emissions in the categories of agricultural production activities, farming, and livestock husbandry, respectively. The results also show that East China covered more periods of the strong decoupling of CO 2 emissions from agricultural output value between 1997 and 2014. To decrease CO 2 emissions, this paper suggests imposing a higher value-added tax on fertilizer producers, while waiving value-added tax for organic fertilizer and substituting animal manure for conventional fertilizers where possible. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2) is the primary greenhouse gas, with annual emissions reaching up to 54 billion tons globally, leading to an unprecedented acceleration of global warming. In conjunction with carbon capture, utilization, and storage (CCUS), which represents the most advanced and efficient technology for energy conservation and emission reduction, as well as the innovative concept of CO 2 storage in salt caverns, this paper investigates the industrial application potential of supercritical CO 2. Herein the feasibility of large-scale storage of supercritical CO 2 in salt caverns was investigated, focusing on the stability aspect associated with such storage. Specifically concentrating on the impact of upper and lower injection/production pressures and frequencies on the stability of carbon storage in salt caverns, this study utilizes numerical simulation methods to simulate the creep process that occurs in China's bedded salt formations. Numerical simulation results showed that: 1) From the perspective of salt cavern stability, the volume shrinkage, creep and damage degree of surrounding rock during operation all fall within an acceptable range. Consequently, it is feasible to implement carbon storage in these salt caverns for a during of 100 years. 2) Shortening the range of internal pressure will enhance the stability of salt cavern for carbon storage. Furthermore, different pressure intervals have an impact on the creep concentration position within the cavern, primarily resulting in a transformation between internal contraction of surrounding rock and sediment accumulation caused by floor creep by altering the lower pressure limit. 3) The injection and production frequency of salt cavern carbon storage (SCCS) is characterized by a low occurrence rate (<10 cycles). The stability of the cavern can be enhanced by increasing the injection and production frequency, nevertheless, it is important to note that internal pressure remains the primary factor influencing cavern stability compared to the injection and production frequency. • A digital model for supercritical CO2 storage in salt caverns is developed. • The operational parameters for SCCS are designed from the perspective of pressure intervals, injection and production frequencies. • The numerical simulation method is employed to simulate the dynamic change process of SCCS during 100 years of long-term operation, followed by a corresponding stability evaluation. • The alterations in cavity morphology and damage severity of salt caverns utilized for carbon storage are examined. [ABSTRACT FROM AUTHOR]

The cement manufacturing industry, a resource- and energy-intensive sector, took up more than 15% of total greenhouse gas emissions in China, thus finding a clean technology option for sustainable development is essential. CO 2 curing has emerged as a promising novel method for large-scale carbon sequestration and mechanical properties improvement of cement-based composites. Currently, a body of related works is mainly investigated in the laboratory, and understandings of the behaviors of CO 2 -cured cement-based composites are still less than complete, including, 1) the CO 2 storage potential has plenty of room for improvement due to the influence mechanism of variables factors remains unclear; 2) previous evaluations were mostly based on the subsets of individual result rather than an integrated dataset; 3) whether CO 2 curing is suitable for the manufacturing process of reinforced concrete. Therefore, this paper presents a comprehensive overview covering a wide range of parameters as well as fabrication, mechanical (compressive strength), and environmental (CO 2 uptake value) performances on the basis of a correct understanding of the differences between active and passive carbonation reactions. Notably, the influences of critical factors, including those less understood, e.g., types of curing setup (flow-able, enclosed, and others), components of binder, and aggregate/binder ratio, are also analyzed and the corresponding mechanisms discussed to achieve satisfied curing efficiency. Besides, corrosion-related challenges are also be pointed out to convince the widespread acceptance of this technology. Finally, based on this paper, limitations of existing research are identified and future scope on CO 2 curing regime is proposed. • 170 studies related to CO 2 /carbonation-cured cement-based composites are analyzed. • The differences between active/passive-carbonation together with reaction mechanisms are expounded. • Fabrication and influence factors on engineering and environmental properties are systematically reviewed. • CO 2 -cured cement-based composites exhibit excellent resistance to aggressive conditions. • The challenges and opportunities in the CO 2 curing method are innovatively discussed. [ABSTRACT FROM AUTHOR]

With rapid urbanization and industrialization, the number of light-duty gasoline vehicles (LDGVs) in China has continued to grow rapidly, leading to a significant increase in traffic pollution. Therefore, it is essential to accurately calculate the emission of LDGVs for air quality monitoring and management. Fortunately, Motor Vehicle Emission Simulator (MOVES) is a sophisticated model for estimating mobile source emissions with good prediction accuracy. However, the parameters of MOVES are based on the field tests in the US, which is worth exploring whether MOVES can be applied to other countries. Hence, in this paper, we used the portable emission measurement system (PEMS) to conduct real driving emission (RDE) tests of LDGVs, aiming to explore the possibility of the MOVES application in China. Based on the field tests, we modified basic parameters in the MOVES model, but unsatisfactory prediction performance was obtained. Existing research on improving MOVES performance mainly involved new binning of operating modes, but these methods had limited improvements. Though studies have also used machine learning methods for predicting LDGV emissions, they lacked comparison and integration with the MOVES model. To further improve the prediction accuracy, we proposed a novel road vehicle emission model that integrated the machine learning method and the MOVES to predict the road-level emission rates of NO and CO 2 emissions of LDGVs. In addition, we employed the Boruta algorithm to capture the key influencing factors and promote prediction performance. The enhanced model outperformed MOVES and achieved higher R2 values. On average, the improvement for CO 2 was 0.132, and for NO, it was 0.261. This work will provide references for MOVES improvements in practical scenarios and better predict pollutant emissions for LDGVs using limited resources of field tests in cities outside the US. • Integrating engine characteristics with the MOVES model can improve model performance. • Integrating machine learning with MOVES performs well in prediction of vehicle CO 2 and NO emission. • The proposed emission model provides a possibility for calculation rather than costly an experiment in countries outside the USA. [ABSTRACT FROM AUTHOR]

As the basic sector providing basic service and promoting economy development, the increment demand of transport sector has brought much more pressure on the environment. Beijing-Tianjin-Hebei region is the representative region of the advanced region of China and it is significant to analyze how to achieve the low-carbon transport development in Beijing-Tianjin-Hebei region, meanwhile provide reference of green development for other regions. Using the panel data from 1995 to 2016, the paper analyses the driving factor of carbon dioxide emissions from transport sector with two different analytical methods. The results of LMDI show that transportation energy intensity and economic effect is the main factor increasing the carbon dioxide emissions and the contributing factors to the carbon dioxide emissions reduction in the transport sector are the energy structure effect, the freight turnover of unit industrial output effect and the industrialization effect. In different subclasses divided by different threshold variables, industrialization has the positive impact while the coefficients vary, which indicates that appropriate development policies should be formulated in light of the development characteristics of different regions. [ABSTRACT FROM AUTHOR]

Understanding the causes of growing carbon transfers between developing countries is likely to be the first step in their mitigation. With this in mind, the current paper uses multi-regional input-output analysis to investigate CO 2 emissions and value-added embodied in China-Brazil trade. We propose the use of value-added exports, rather than gross exports, to more accurately estimate the economic benefits of trade. We find enormous increases in both CO 2 emissions and value-added embodied in exports for China and Brazil between 2000 and 2014. During this period, China's position as a net CO 2 emissions and net value-added exporter vis-à-vis Brazil deepens. Major sources of increasing embodied CO 2 exports for China were the basic materials and electricity industries and for Brazil were the basic materials, agriculture and mining industries. Estimates of net carbon intensities reveal advantages for China in electronics and for Brazil in agriculture and mining. Structural decomposition analysis shows that the changing consumption in China and Brazil as well as the changing structure of intermediate exports from China to Brazil were important sources of increasing embodied CO 2 emissions. This latter finding was possible due to the method proposed in this paper of decomposing the production structure into the domestic, export and import production structures. In line with the key findings, various implications and emission abatement policies are discussed. [ABSTRACT FROM AUTHOR]

Rapid economic development in China have resulted in the booming demand for comfortable and fast travel mode, and promoted the rapid development of aviation industry in recent years. As an important source of greenhouse gas emissions, airlines' operational efficiency and environmental issues have been widely concerned in achieving the goal of cleaner production of aviation industry. Due to the limitations of traditional DEA approach, which known as a black box, the specific reasons for the inefficiency of airlines cannot be explored. This paper contributed to current literature by introducing the two-stage undesirable Network Slack-Based Measure (NSBM) approach to explore Chinese airlines' multi-stage efficiency: production stage and profit stage, and try to open the black boxes and further explore the characteristics and driving forces of the operational performance in China's aviation industry. Meanwhile, this paper incorporates CO 2 emissions into the calculation by combining the undesirable Slack-Based Measure (SBM) approach and measure the energy efficiency and CO 2 emission efficiency to evaluate their environmental performance on the basis of the two-stage framework. The empirical results on nine listed Chinese airlines from 2013 to 2018 showed that all airlines perform better in earning economic profits from carrying capacity, while the low production efficiency in converting production factors into carrying capacity limits the operational efficiency of Chinese airlines. The energy efficiency of Chinese airlines ranks in line with CO 2 emission efficiency, while the economic and environmental performance of low-cost airlines remain the best. Further discussion indicated that smaller private airlines tend to achieved better economic and environmental performance through low-cost operations, while the top three airlines in market share need further improvement in operational efficiency and environmental performance. The former should pay attention to the upgrading of flights to ensure a certain market share while maintaining its low-cost operation mode, and the latter needs to improve its management and cost control level to achieve clean development. Image 1 • Total efficiency of China's aviation industry is decomposed into production and profit efficiency. • A two-stage undesirable SBM-NDEA model is employed to open the black box. • The main reason for the inefficiency of China's aviation industry is the low production efficiency. • The low-cost airlines remain the best in economic and environmental performance. [ABSTRACT FROM AUTHOR]

Applying a parameterized directional distance function approach, this paper estimates the regional eco-efficiency and pollutants' marginal abatement costs in China based on provincial panel data covering the years 2003–2012. We find that China could potentially save capital, labor, land, energy and water by 18.07%, 11.47%, 11.20%, 12.28% and 11.19%, and reduce emissions of carbon dioxide (CO 2 ), household refuse and waste water by 11.75%, 11.02% and 11.46%, respectively, on condition that all provinces produced fully efficiently, The south and east coastal areas were the most eco-efficient, while the middle Yangtze River and southwest areas performed relatively poor. For the whole country, the average shadow prices of CO 2 , household refuse and waste water were 717.27 Yuan/tonne, 42,936.98 Yuan/tonne and 306.65 Yuan/tonne, respectively. The shadow price of CO 2 revealed significant regional disparities and that of household refuse showed a rapid increase throughout the study period. Our estimates suggest that policymakers should take measures to avoid ineffective capital investment and improve economic output efficiency in inland provinces, especially in the middle Yangtze River, northwest and southwest areas, and facilitate technological cooperation between developed and undeveloped areas. The regional heterogeneity and flexible price mechanism of various pollutants should be taken into consideration when making the reduction allocations among different areas. [ABSTRACT FROM AUTHOR]

Forecasting CO 2 emissions in China always has been of great significance as it could help the government to improve energy policies and plans. To this end, a novel grey multivariable model is designed in this paper. Compared with the conventional grey multivariable model, which has certain drawbacks of inaccurate prediction and poor adaptability that restrict their applications in practical cases, the proposed model can make three improvements: first, an optimized grey model having a modified background value is proposed to predict the trends of the driving variables. Second, the novel grey multivariable model is established, combined with the changing trends of driving variables. Third, the adjustment coefficient in the new model is optimized to obtain optimal values for the time response function. To demonstrate its efficacy, the proposed model is employed to reproduce and predict the CO 2 emissions from fuel combustion compared with four benchmark models—the results show that the new model yields more accurate forecasting results than the competing models. Eventually, the new model will be used to quantify future Chinese CO 2 emissions from fuel combustion from 2014 to 2020, and the forecasted results can provide a solid basis for formulating environmental policies and energy consumption plans. [ABSTRACT FROM AUTHOR]

With the increasing number of large and medium-sized cities and the improvement of intercity transportation infrastructure, polycentric urban network is gradually emerging. Based on the strong link between urbanization and carbon dioxide emissions has been proven, using a panel data of 23 provinces of China over the period of 1997–2013, this paper explores the impact of polycentric structure on carbon dioxide emissions. The results reveal that there is a u-shaped relationship between polycentric structure and carbon dioxide emissions, and the relationship is obviously different between coastal and inland areas. At the same time, market integration can effectively reduce carbon dioxide emissions, and there is a substitution relationship between polycentric structure and market integration. In addition, urban distance and transportation infrastructure within provinces play a significant non-linear regulating effect on the relationship between polycentric structure and carbon dioxide emissions. The conclusion of this paper provides some empirical evidence for the coordinated development of China's future regional space planning and energy emission reduction. [ABSTRACT FROM AUTHOR]

The issue of climate change has become an increasing concern for the international community. At the same time, climate change and, particularly, global warming affects the amount of energy required in China and the structure of this demand, thereby influencing the amount of CO 2 (carbon dioxide) emissions produced. To investigate the possible influence of climate change on China's CO 2 emissions, this paper utilizes the degree-day method to calculate the heating degree days (HDD) and cooling degree days (CDD) in 29 provinces in China from 1995 to 2011. A series of appropriate econometric models are subsequently estimated to measure the impact of climate change on CO 2 emissions per capita. To enhance the explanatory power of the estimation results, several indicators, such as income per capita, industry structure, urbanization rate and population density, are incorporated in the estimation equations as control variables. The estimation results indicate that the feedback effect of climate change on China's carbon emissions is statistically significant but not large in magnitude. During the sample period between 1995 and 2011, approximately 1.687% of China's increased total CO 2 emissions could be attributed to climate change. Moreover, the impacts of climate change on different regions of China are notably different. For example, the influence of HDD on CO 2 emissions per capita are most significant in the middle and southern regions, while the impacts of CDD are most significant in the eastern and northern regions. However, there is no obvious evidence that climate change has affected CO 2 emissions in the western region. [ABSTRACT FROM AUTHOR]

Electric rubber tire container gantry cranes (ERTGs) have already been widely used to replace rubber tire container gantry cranes (RTGs) in many ports of the world, especially in China. ERTGs can reduce carbon dioxide emissions by shifting energy demand from diesel to electricity (energy replacement). It takes almost 6–12 months to change a RTG to an ERTG, and the changed yard cranes cannot work during the replacement phase due to the mechanical reformation and electrical power system construction etc. Therefore, the yard crane network will generate bottlenecks in the container flow and influence the service level when energy replacement happens. This paper focuses on the problem of allocating limited resources for yard cranes to reduce the carbon emissions. The main challenges are how to solve the energy replacement problem at a network level and how to cope with the high uncertainties in the container terminal transportation network. Therefore, we model the energy replacement problem with the purpose of minimizing the carbon emissions by combining an allocation resource mathematical model and a simulation model of the whole transportation network together. The first stage of the energy replacement problem is to make energy replacement decisions each year, while the second stage is to evaluate the value of a seaport's service level based on the realized decisions by running the simulation model. However, the service level indicator is a random variable dependent on the decisions in the mathematical model, which should be controlled to make the seaport work normally at a network level. As an example, the optimization and simulation procedures are applied to a major container terminal in China. The proposed model is general and can be applied to the energy replacement problem of any other seaport. [ABSTRACT FROM AUTHOR]

Cities consume large amounts of fossil fuels and this results in significant increase of global anthropogenic greenhouse gases. Using city-level carbon dioxide emission data from Shijiazhuang, a traditional heavy manufacturing city and one of the key cities in Jing-Jin-Ji urban agglomeration in Northern China, this paper employs logarithmic mean Divisia index decomposition method (LMDI) to explore the influence of energy intensity, consumption structure, industry structure, per capita Gross Domestic Product (GDP), and population on Shijiazhuang's total carbon dioxide emissions from 2005 to 2016. The LMDI method is further extended to analyze the impacts of above factors at the industry-segment level. This paper finds that the reduction of energy intensity is the major contributor of decreasing carbon dioxide emissions in Shijiazhuang, whereas the growth of per capita GDP is the main driving force for emission accretion. The dominant industrial segments contributing to increasing emissions in Shijiazhuang City from 2005 to 2016, have changed from CMD (coal mining and dressing), EPSH (electric power, steam and hot water production and supply) to SPFM (smelting and pressing of ferrous metals) and PPC (petroleum processing and coking). The CMD industrial segment shows a significant carbon reducing effort and indicates a strong decoupling status. However, the SPFM and PPC respectively show expansive negative decoupling and weak decoupling status, enlightening a change in the policy focus when Shijiazhuang formulates its emission-reduction plans in the future. This study provides important policy insights for the heavy manufacturing cities in other countries with similar industrial structure, as the industry-based carbon mitigation policies should always be adjusted in different stages of the cities' development according to the change of carbon emission driving industries. [ABSTRACT FROM AUTHOR]

In order to fill the research gap of CO 2 -fixing cementitious materials, and to deal with China's dual-carbon goal, first to use bacteria and steel slag powder to fix CO 2. The paper using untreated steel slag powder as control group, different CO 2 -fixing steel slag powder are compared, they are CO 2 treated steel slag and bacteria-CO 2 treated steel slag. The XRF and XRD results shows that the physicochemical properties of steel slag powder with different treatments are significantly different. Because the chemical composition and particle surface properties of steel slag powder are changed in the CO 2 fixing process due to the reactions. There are calcium carbonates formed in steel slag powder when cured by CO 2 from cement kiln tail gas. The SEM images show that the surface of steel slag powder has defects. Steel slag with bacteria will produce more calcium carbonates and its surface has more defects. Therefore, it will have an impact on the cement-based material fresh paste workability and hardened paste properties. The results of the fresh paste workability show that, the surface defects of steel slag powder have an adverse impact on the workability, because the defects increase the internal friction between particles. The results of hardened paste strength show that the cement-based materials mixed with SSLP-BC has the better mechanical properties. The XRD, FTIR, SEM, 1H NMR and X-CT results of hardened paste show that, the microstructure of cement-based materials mixed with SSLP-BC is denser. This may be caused by the nucleation of bacteria and calcium carbonate. Moreover, calcium carbonate may play an important role in hydration process, there is carboaluminates formed in the hardened paste that containing calcium carbonate, and it is beneficial for mechanical properties. Therefore, steel slag after bacteria-CO 2 treated can used as SCM, it has better social and environmental benefits. [ABSTRACT FROM AUTHOR]

Small and medium span bridges account for 86% of the bridges in China, and maintenance is necessary to ensure their safety and serviceability. The infrastructure sector causes substantial CO 2 emissions, and it is one of the most polluting sectors. Fly ash (FA) is often used in bridges to reduce CO 2 emissions. Moreover, the lack of temporal information is an important limitation of the life cycle CO 2 assessment of bridges. Taking the upper structure of small and medium span bridges as the research object, this paper proposes a Monte Carlo simulation-based life cycle multi-objective dynamic maintenance strategy optimization model to analyze the life-cycle carbon emissions, costs, and life cycle reliability of different preventive maintenance (PM) and essential maintenance (EM) methods of FA reinforced concrete (RC) beams. Considering the continuous effect of carbon emissions and the net present value of the cost, the time effect of carbon emissions and costs of maintenance and reinforcement at different times is analyzed. Through 50,000 simulations of the case beam, the parameter characteristics of different optimal reinforcement schemes and the relationship between the reliability, life cycle CO 2 emissions, and costs are studied. When introducing the discount rate, the essential maintenance with higher carbon emissions and costs has a marginal effect, i.e., the longer that future carbon emissions and costs occur, the smaller the net present value. The proposed method is demonstrated to be effective at supporting decision making for bridge managers. It would be helpful for identifying the effectiveness of PM and EM, selecting optimal maintenance time interval, and providing a rational estimate of the CO 2 emissions and costs of bridges. • A Multi-objective dynamic maintenance strategy optimization model is proposed. • The time effects of carbon emissions and costs are analyzed. • The parameter characteristics of the optimal maintenance of a T-beam are found. [ABSTRACT FROM AUTHOR]

The development of China's highway infrastructure has led to a rapid increase in carbon dioxide (CO 2) emissions while facilitating social and economic development. This paper introduces highway mileage and CO 2 emissions into the traditional production density model, using agglomeration as a mediating variable, to theoretically discuss the path through which highway infrastructure influences CO 2 emissions. We then use the spatial Durbin model (SDM) to verify the explanatory power of the expanded production density model based on panel data of China's 278 cities from 2003 to 2016. Empirical results indicate that (1) there is an inverted U-shaped relationship between highway infrastructure and CO 2 emissions in both local and peripheral cities; (2) highway infrastructure affects local CO 2 emissions through the agglomeration pathway but impacts CO 2 emissions in peripheral cities mainly through the spatial spillover effect of highway infrastructure; and (3) the U-shaped impact of highway infrastructure on CO 2 emissions in western China is diametrically opposed to the results for the east, the central region and the total sample. Therefore, China needs to fully consider the environmental effects of agglomeration to formulate a global emission reduction strategy when building highway infrastructure. Moreover, strategies based on the different stages of highway infrastructure development should be enacted and should be part of a spatially synergistic joint emission reduction mechanism while considering the characteristics of regional development. • The study extends the production density model and verifies the explanatory power. • The spatial correlation between variables is tested by the spatial Durbin model. • Regional heterogeneity is discussed, and the reasons for this are analysed. • The results are corrected using GS2SLS with slope as an instrumental variable. • Related policy recommendations are made for low carbon development in China. [ABSTRACT FROM AUTHOR]

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]

In order to ensure the implementation of the emission trading scheme (ETS), the allocation of CO 2 emission quotas in China's provinces is of significant importance. Unlike previous studies that allocated CO 2 emission quotas directly to Chinese provinces, we propose a two-step allocation scheme of "country to region" and "region to province" to formulate the provincial CO 2 emission quotas allocation. In the first step, considering the regional coordination development, the Shapley value method is used to assign the CO 2 emission quotas to China's eastern, central, and western regions by simulating the regional collaborative abatement. In the second step, we use the entropy method to obtain the initial CO 2 emission quotas for each province combining the principles of fairness, efficiency, feasibility, and sustainability. Then, a zero-sum gains data envelopment analysis (ZSG-DEA) model is applied to evaluate initial allocation efficiency and reallocate the CO 2 emission quotas to realize efficiency optimization within the region. The results show that the eastern region obtains the largest CO 2 emission quotas, followed by central and western regions. The energy-abundant and economic-prosperous provinces, such as Shandong, Hebei, Inner Mongolia, and Xinjiang, face great pressures on CO 2 reduction. Compared with existing literature, the proposed scheme's regional allocation results are more balanced, which will narrow the gaps of regional economic development. Since the emission reduction pressure varies in provinces, developing differentiated policies is critical to realizing China's reduction targets. By considering regional fairness, this paper provides a reference for allocating CO 2 emission quota among provinces to improve adaptability to the current conditions of China. [Display omitted] • The Shapley value method was used to allocate CO 2 emission quotas among China's regions. • We use the entropy method to allocate CO 2 emission quotas to province within each region. • A ZSG-DEA model was used to redistribute the CO 2 emission quotas across provinces. • The eastern China has the largest share of CO 2 emission quotas, followed by central and western. • Energy-abundant and economic-prosperous provinces have more pressures on CO 2 abatement. [ABSTRACT FROM AUTHOR]

An integrated approach is proposed in this paper to incorporate the group heterogeneity into the framework of natural disposability and managerial disposability, which allows evaluating the CO 2 emission performance under different mitigation strategies (scale-oriented strategy and innovation-oriented strategy). It is able to deal with the intertemporal incomparability when adopting a global technology. In the empirical study, we categorized China's 27 manufacturing sectors into five groups and evaluated their emission performance under different mitigation strategies during 2003–2016. According to the empirical results, we found that there is still much potential (about 70%–80%) for improving the CO 2 emission performance considering the entire manufacturing industry. From the perspective of different groups, the global technologies/innovators group shows the highest emission efficiency, while the energy-/resource-intensive commodities' group performed the worst. Besides, different sectors showed significant technology heterogeneity. Finally, the desirable CO 2 mitigation strategies varied with the different groups. For the labor-intensive tradables' group, we found that the desirable strategy is to decrease the input of energy and other production factors, i.e. scale-oriented strategy. For the regional processing group, the innovation-oriented strategy is more efficient. • Modified global meta-frontier non-radial DDF approach is proposed. • Group heterogeneity is incorporated in natural/managerial disposability framework. • CO 2 emissions performance for China's manufacturing sectors is measured. • Global technologies/innovators group performs best, while energy-/resource-intensive commodities group performs worst. • Desirable mitigation strategies varies with respect to technology heterogeneity of different groups. [ABSTRACT FROM AUTHOR]

Timely maintenance is crucial to ensure the long-term performance of asphalt pavements. Due to the large amount of greenhouse gases (GHG) emitted during construction, it is important to evaluate the environmental impacts of various maintenance technologies, so that the whole life impacts of asphalt pavements can be understood and reduced. This paper estimated the GHG emissions of 16 maintenance technologies in the four categories of surface seal or coating system, thin overlay system, hot recycling system and cold recycling system by using life cycle assessment (LCA), and identified the technologies and the combination of them that have the least GHG emissions. In order to compare the maintenance technologies on a level-playing basis, this study designed maintenance scenarios for the entire life cycle of the pavement, and established a system boundary where all maintenance scenarios are compared transparently for a defined functional unit. Results show that, among the preventive maintenance technologies, micro-surface and fog seal have the lowest GHG emissions. In order to meet the same performance requirements of highway pavement, cold recycling with extra overlay will generate more than twice GHG emissions that of hot recycling. Increasing the frequency of preventive maintenance, and reducing the occurrence of corrective maintenance can reduce GHGs emissions by 30%–45% in pavement life. Reasonably designed maintenance plan for the entire life cycle can significantly reduce the GHG emissions of asphalt pavements. • The CO 2 footprint of sixteen asphalt pavement maintenance technologies was analyzed. • Micro-surface and fog seal have the lowest GHG emissions. • Cold recycling with extra overlay will generate more than twice GHG emissions that of hot recycling. • Increasing the frequency of preventive maintenance can reduce the GHG emissions. [ABSTRACT FROM AUTHOR]

In China's low-carbon development progress, industrial sectors play a crucial role in reducing CO 2 emissions and maintaining economic growth targets. Because the Chinese government is promoting industrial structure transformation for "high-quality economic development," the dominant CO 2 emitters have changed in recent years. It is important to identify the trend evolution of industrial CO 2 emitters and implement targeted measures and policies for CO 2 emission control at the sector level. In this paper, a hybrid input–output model is adopted to assess the situation and trend of sectoral CO 2 emissions from 2002 to 2017 in China. Demand-side drivers of sectorial embodied CO 2 emissions are discussed. Based on the embodied CO 2 emission decomposition of 27 sectors, a CO 2 emission evaluation index is defined for CO 2 emission ranking and key sectors for embodied CO 2 emissions are identified. For the key CO 2 emitters, we provide targeted policy suggestions for CO 2 emission mitigation from the perspective of trend evolution and index ranking. The results indicate the following. (1) 2015 is a turning point for China's CO 2 emission mitigation progress, because the previously increasing embodied CO 2 begins to decrease from 2015 to 2017. (2) Although the Construction sector stimulates a large amount of CO 2 emissions at present, the major driving forces of CO 2 emissions have gradually changed from infrastructure construction to the increasing demand of consumer goods, service industry, and export of technology-intensive products. (3) The CO 2 emission intensity of the Electric Power and Heat Supply sector has increased, and promotion of renewable energy consumption is urgently needed. (4) From the demand-driven aspect, tertiary industry has greater CO 2 emission potential than heavy industry. • A turning point of embodied carbon dioxide of China appears in 2015. • Most sectors have reached the peak of embodied carbon dioxide by 2015. • Construction, Other Service Industry and Manufacture of Machinery are the top three embodied carbon dioxide emitters. • Electric Power and Heat Supply sector should be concerned for high embodied carbon dioxide intensity. • Sectors with great carbon dioxide emission potential change towards tertiary and high-tech industries. [ABSTRACT FROM AUTHOR]

China's iron and steel industry is the key industry for the state to conserve energy and control CO 2 emissions. In this paper, we divide China's administrative regions into three groups using cluster analysis. Then we use energy and carbon dioxide performance index to evaluate the static efficiency in iron and steel industry. After, meta-frontier non-radial Malmquist directional distance function is constructed to measure the dynamic energy and carbon dioxide emission performance. The dynamic indicator is decomposed into efficiency change, best practice gap change, and technology gap change. According to this study, the static energy and carbon dioxide efficiency in China's iron and steel industry still lags behind from 2000 to 2016. Group 1 (mainly eastern provinces of China) has the highest efficiency, followed by group 2, and group 3 (mainly western provinces of China) has the lowest efficiency. The technical efficiency and technical progress are driving factors improving energy and carbon dioxide performance, while the technology gap change does not help to improve the performance. Finally, we propose specific policy recommendations to promote the healthy development of the industry. • We estimate energy and CO 2 efficiency of China's iron and steel industry. • Efficiency performance in iron and steel industry experiences positive changes. • EC and BPC are driving factors for efficiency performance improvement. • Technology gap change does not help to improve the energy and CO 2 performance. [ABSTRACT FROM AUTHOR]

The Paris Agreement on climate change has calls for urgent, radical, and transformative actions in mitigation and adaptation, particularly in terms of reducing greenhouse gas (GHG) emission. There are many terms used to describe the process of reducing GHGs, including decarbonization, low carbon development (LCD) or low carbon transition (LCT). The conceptualization of these terms remains puzzling and there has not been any consensus to explain the meaning and their interrelationship. Clearer definition and conceptual boundaries are necessary to improve the coherence of overarching practices to cut CO 2 emission. The paper aims to review key concepts related to climate change mitigation related to the reduction of CO 2 and efforts toward net-zero emission in the academic literature, by (1) examining progress of the literature over time, (2) identifying geographical locus and sectoral focus of the literature, (3) determining the interrelationships between the key concepts. We use a Systematic Literature Review (SLR) method for data collection by selecting peer-reviewed literature from Scopus and analyzing the data with content analysis and bibliometric analysis. The findings are, firstly, the publications of the literature are influenced by global and national climate change policies and the interest of scholars affiliated to institutions from major emitter countries. Therefore, the literature is mostly originating from countries that emit the most CO 2 while also implement mitigations to reduce CO 2 emission. Secondly, China is the country where studies are mostly focused and also where the authors are affiliated/located. However, publications from the United Kingdom are cited the most. Thirdly, there are three clusters of literature found, namely that LCD and LCT are the terms used to identify visions for climate mitigation, while decarbonization is the actions and processes to achieve either LCD or LCT (as the visions). • The dynamic of climate change policies influence the literature trend. • The literature is mostly originating from major CO 2 emitter. • Low carbon development and low carbon transition are visional terms. • Decarbonization indicates the processes of decoupling CO 2 to achieve the visions. [ABSTRACT FROM AUTHOR]

The rapid growth of energy-intensive and high-emission industries has underpinned China's economic boom over the past few decades. Since her economic development entered the new normal phase in 2013, China has faced the challenge of mitigating greenhouse gas (GHG) emissions while achieving medium-high economic growth. Transforming the economic development pattern and restructuring the economy is a principal solution, and one important prerequisite is discerning great sectoral disparities of GHG emissions and corresponding environmental costs because the diversity of characteristics among different sectors causes the pollutants that are discharged to vary. Hence, this paper aims to assess the environmental costs of China's total and sectoral GHG emissions. Based on the System of Environmental and Economic Accounts and using the economic input-output life cycle assessment model, this study calculates the green GDP and green output value of 27 sectors to reflect the environmental costs of GHG emissions in China during 1991–2016. The findings are as follows: (1) while China's direct GHG emissions increased from 3,040.60 million tons of carbon dioxide equivalent (MtCO 2 eq) to 10,641.10 MtCO 2 eq during 1991–2014, declining trends were observed in the total and 16 sectors' direct GHG emissions in the subsequent two years; (2) although the ratios of direct GHG emissions to total GHG emissions in most sectors decreased, total GHG emissions in eight sectors rose first and then fell, and in 15 sectors continued to rise; (3) China's green GDP grew from 2,003.88 billion Chinese Yuan to 26,245.25 billion Chinese Yuan during 1991–2016, and the difference between China's GDP and green GDP decreased from 2.73% to 1.02%; and (4) differences between the output value and green output value decreased in over 20 sectors. Finally, some policy implications are given from the perspective of some key sectors of the Manufacturing industry, Agricultural sector, and Transport, storage, and post sector. • China's direct GHG emissions increased from 3,040.60 MtCO 2 eq to 10,641.10 MtCO 2 eq. • Total GHG emissions in 8 sectors rose and then fell, while that in 15 sectors grew. • China's green GDP grew from 2,003.88 billion CNY to 26,245.25 billion CNY. • Difference between China's GDP and green GDP decreased from 2.73% to 1.02%. • Difference between the output value and green output value fell in over 20 sectors. [ABSTRACT FROM AUTHOR]

The metallurgy industry that was crucial in developing Chinese economy also enhanced energy consumption and carbon emissions. This paper examines the impact of economic variables on carbon emissions from the metallurgy industry of China, where energy structure, energy intensity, carbon intensity, industrial structure, and labor productivity were utilized in analyzing carbon dioxide emissions within a quantile models framework. Quantile estimates unveiled varying effects of variables across spectrum of carbon emissions and averagely, a unit increase in the above economic variables will influence carbon emissions by 97.2 percent, 100.3 percent, 118.6 percent, 98.4 percent and 100.2 percent approximately. Across all quantiles, results showed that carbon intensity had the greatest impact on carbon dioxide emissions, then energy intensity, labor productivity, industrial structure, and energy structure, most but not all the industry was plagued by carbon intensity, while industrial scale should be minimized optimally, labor productivity should be improved too. Energy intensity is the most influencing factor, prompting an urgent need for technology advancement The uniqueness of the metallurgy industry must be considered when administering economic policies across the industry in China. The enhancement of clean energy technology and optimizing energy structure are crucial for carbon emissions reduction and a review of energy consumption by the industry to accommodate renewable energy is recommended. [ABSTRACT FROM AUTHOR]