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China is currently focusing on the cooperative control of air pollution and CO2 emissions, as well as the mitigation of economic policy uncertainty (EPU). By using panel data from 282 cities spanning from 2003 to 2017 and a newly constructed city-level EPU index, a spatial Durbin, two-way fixed-effects model is employed, with the aim of estimating the impact of EPU on the synergistic emissions intensity (SEI) of air pollutants and CO2. Additionally, this paper investigates the potential channels through which EPU influences SEI. It also explores how pressures related to environmental protection and economic development affect the impact of EPU on SEI. The results indicate that a unit increase in EPU will result in a rise in the SEI of local cities, adjacent cities, and total cities by 930.9%, 69,162.7%, and 70,093.6%, respectively. Moreover, the channel analysis suggests that EPU exacerbates SEI by undermining the upgrading of the industrial structure, augmenting industrial structure distortion, and escalating labor market distortion. Furthermore, the effect of EPU on SEI may be lessened by an increase in environmental protection pressure, while an increase in economic development pressure may exert a positive influence. Finally, this paper concludes by recommending that policymakers should prioritize the maintenance and stability of economic policies, facilitate the advancement of the industrial structure, enhance the efficiency of labor resource allocation, and underscore the significance of managing urban air pollution and CO2 emissions. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, China has become the world's largest carbon emitter. China not only has an obvious growth rate of industrial carbon emissions but also the intensity of agricultural carbon emissions is hovering at a high level. The development of China's agricultural economy has largely come at the expense of high emissions. Currently, under the background of global warming and difficulty in controlling greenhouse gas emissions, the development of low-carbon agriculture is an important way to realize the harmonious development of the ecological environment and economic growth and to promote the sustainable development of agriculture. The agricultural production efficiency is the main factor affecting the intensity of agricultural carbon emissions. Based on provincial panel data of China from 2010 to 2019, this paper establishes an indicator system and uses the super-efficiency SBM model to measure agricultural production efficiency. The regional agricultural carbon emissions were estimated using carbon-emission-related agricultural production activities. In order to study the nonlinear relationship between agricultural production efficiency and agricultural carbon emission intensity in the narrow sense, this paper uses a threshold regression model with agricultural carbon emissions as the threshold variable. Based on the analysis of China's agricultural production efficiency and agricultural carbon emissions from 2010 to 2019, an empirical test is conducted through a threshold regression model. The results show an "inverted U-shaped" relationship between agricultural production efficiency and agricultural carbon emission intensity. In areas with high agricultural production efficiency, the improvement of production efficiency can suppress the intensity of agricultural carbon emissions; in areas with low agricultural production efficiency, the improvement of production efficiency increases the intensity of agricultural carbon emissions. Finally, based on the research conclusions, this paper provides feasible suggestions and countermeasures for China's agricultural carbon emission reduction and improvement of agricultural production efficiency. [ABSTRACT FROM AUTHOR]

Against the backdrop of China's carbon emission reduction targets and the promotion of the construction of a unified domestic market, what kind of carbon emission effect has market integration had in weakening regional barriers and optimizing resource allocation? This paper adopts a two-way fixed effects analysis based on China's provincial panel data from 2003 to 2019. It uses a mediation model to explore the relationship between market integration and carbon emissions. Furthermore, industrial rationalization and upgrade are the basis for examining whether a competitive or cooperative relationship exists between the carbon emission effects generated and promoting market integration between regions. The study finds a negative relationship between market integration and carbon emissions. In addition, there is significant heterogeneity in the effect of market integration on carbon emissions, and the influence effect is mainly in central China; industrial rationalization can play an enhanced role in the process of the negative impact of market integration on carbon emissions, further enhancing the negative contribution of market integration to carbon emissions. However, market integration can weaken its negative impact on carbon emissions with the industrial upgrade, and there may still be invisible barriers between regions in promoting market integration barriers. [ABSTRACT FROM AUTHOR]

In this paper, the Long-range Energy Alternatives Planning (LEAP) model is constructed to simulate six scenarios for forecasting national electricity demand in China. The results show that in 2020 the total electricity demand will reach 6407.9~7491.0 billion KWh, and will be 6779.9~10,313.5 billion KWh in 2030. Moreover, under the assumption of power production just meeting the social demand and considering the changes in the scale and technical structure of power industry, this paper simulates two scenarios to estimate carbon emissions and carbon intensity till 2030, with 2012 as the baseline year. The results indicate that the emissions intervals are 4074.16~4692.52 million tCO2 in 2020 and 3948.43~5812.28 million tCO2 in 2030, respectively. Carbon intensity is 0.63~0.64 kg CO2/KWh in 2020 and 0.56~0.58 kg CO2/KWh in 2030. In order to accelerate carbon reduction, the future work should focus on making a more stringent criterion on the intensity of industrial power consumption and expanding the proportion of power generation using clean energy, large capacity, and high efficiency units. [ABSTRACT FROM AUTHOR]

China-the largest developing country in the world-is experiencing both rapid economic maturation and large-scale urbanization. These situations have led to waste disposal problems, and the need to identify alternative energy sources. Waste-to-energy (WTE) conversion processes, a source of renewable energy, are expected to play an increasingly important role in China's sustainable management of municipal solid waste (MSW). The purpose of this research is to investigate the key problems and opportunities associated with WTE, to provide recommendations for the government. This paper begins by describing China's current MSW management situation and analyzing its waste disposal problems. The major challenges associated with China's WTE incineration are then discussed from economic, environmental and social points of view. These include the high costs associated with constructing necessary facilities, the susceptibility of facilities to corrosion, the lower heating value of China's MSW, air pollutant emissions and especially public opposition to WTE incineration. Since discarded waste can be used to produce energy for electricity and heat-thus reducing its volume and the production of greenhouse gas (GHG) emissions-with government policies and financial incentives, the use of WTE incineration as a renewable energy source and part of a sustainable waste management strategy will be of increasing importance in the future. The paper concludes by summarizing the management, economic and social benefits that could be derived from developing the country's domestic capacity for producing the needed incineration equipment, improving source separation capabilities, standardizing regulatory and legal responsibilities and undertaking more effective public consultation processes. [ABSTRACT FROM AUTHOR]

In this paper, we used the life-cycle analysis (LCA) method to evaluate the energy consumption and greenhouse gas (GHG) emissions of natural gas (NG) distributed generation (DG) projects in China. We took the China Resources Snow Breweries (CRSB) NG DG project in Sichuan province of China as a base scenario and compared its life cycle energy consumption and GHG emissions performance against five further scenarios. We found the CRSB DG project (all energy input is NG) can reduce GHG emissions by 22%, but increase energy consumption by 12% relative to the scenario, using coal combined with grid electricity as an energy input. The LCA also indicated that the CRSB project can save 24% of energy and reduce GHG emissions by 48% relative to the all-coal scenario. The studied NG-based DG project presents major GHG emissions reduction advantages over the traditional centralized energy system. Moreover, this reduction of energy consumption and GHG emissions can be expanded if the extra electricity from the DG project can be supplied to the public grid. The action of combining renewable energy into the NG DG system can also strengthen the dual merit of energy conservation and GHG emissions reduction. The marginal CO2 abatement cost of the studied project is about 51 USD/ton CO2 equivalent, which is relatively low. Policymakers are recommended to support NG DG technology development and application in China and globally to boost NG utilization and control GHG emissions. [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]

Transportation is an important source of carbon emissions in China. Reduction in carbon emissions in the transportation sector plays a key role in the success of China's energy conservation and emissions reduction. This paper, for the first time, analyzes the drivers of carbon emissions in China's transportation sector from 2000 to 2015 using the Generalized Divisia Index Method (GDIM). Based on this analysis, we use the improved Tapio model to estimate the decoupling elasticity between the development of China's transportation industry and carbon emissions. The results show that: (1) the added value of transportation, energy consumption and per capita carbon emissions in transportation have always been major contributors to China's carbon emissions from transportation. Energy carbon emission intensity is a key factor in reducing carbon emissions in transportation. The carbon intensity of the added value and the energy intensity have a continuous effect on carbon emissions in transportation; (2) compared with the increasing factors, the decreasing factors have a limited effect on inhibiting the increase in carbon emissions in China's transportation industry; (3) compared with the total carbon emissions decoupling state, the per capita decoupling state can more accurately reflect the relationship between transportation and carbon emissions in China. The state of decoupling between the development of the transportation industry and carbon emissions in China is relatively poor, with a worsening trend after a short period of improvement; (4) the decoupling of transportation and carbon emissions has made energy-saving elasticity more important than the per capita emissions reduction elasticity effect. Based on the conclusions of this study, this paper puts forward some policy suggestions for reducing carbon emissions in the transportation industry. [ABSTRACT FROM AUTHOR]

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

In this paper, a collaborative power dispatching system (CPDS) was developed to maximize the profit of a regional biomass power system consisting of an independent power grid. A power generating, dispatching and carbon emissions trading system (CETS) could be engaged in joint strategic planning and operational execution. The principal of CPDS is interactive planning of generating units in power generation and carbon emissions trading. An efficient carbon emissions trading plan for a CPDS would lead to optimized power generation levels under available power production capacities and carbon emissions. In a case study, four generator policies are proposed by considering basic CETSs to comparatively analyze the function of each generator in the CPDS. Results of four scenarios are compared, showing that biomass energy could replace thermal units to a certain extent, the carbon emissions and coal consumption of the CPDS would lie at a lower level, and a pumped storage unit could adjust the load fluctuations. The results of a carbon trading analysis show that the CETS has no significant impact on the CPDS, but along with the increase in trading price or the decrease in the free quota, the economic interests of power plants will be reduced accordingly. This may lead to carrying out low-carbon projects and reducing carbon emissions. Therefore, it is imperative to reduce carbon emissions by replacing power units with high energy consumption, and improve the consumption capacity of renewable energy. [ABSTRACT FROM AUTHOR]

The adoption of emissions trading scheme (ETS) and renewable energy sources (RES) policies have been essential to achieving China's national targets for reducing CO2 emissions and developing non-fossil energy sources. The combination of ETS and RES policies raises an important issue: What is the effect of combining ETS and RES policies on the existing carbon market and economy? Focusing on the design of the nationwide carbon market, this paper uses a multi-regional computable general equilibrium (CGE) model to analyze the economic impacts of ETS policy when combined with RES policies in China. The results show that China's annual ETS emissions cap should decrease by 0.3% to maintain stable CO2 prices and achieve the targets in China's intended nationally determined contribution (INDC). It is estimated that the CO2 price on the nationwide carbon market would decrease by 11-64% when the renewable energy subsidy rate increases from 20 to 100%, and the total trading volume would decrease by 3-25%. The results also show that the combination of an ETS and a feed-in tariff (FIT) results in greater GDP cost and welfare loss in all Chinese regions, increasing the total social cost by 0.01-0.06%. [ABSTRACT FROM AUTHOR]

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

Rapid economic growth in Northwest China has been accompanied by a dramatic increase in carbon emissions. Based on the two-level Logarithmic Mean Divisia Index (LMDI) method, this study decomposes changes in energy-related carbon emissions in Northwest China during 1995-2012 from the regional and provincial perspectives. Further, by constructing an expanded decomposition model of the decoupling index, this paper quantitatively analyzes delinking indicators of economic activity and environmental pressure in Northwest China. The results indicate that: (1) at both regional and provincial levels, economic activity effects play a crucial role in increasing carbon emissions, whereas improvements of energy efficiency appear as the main factor in curbing carbon missions; (2) the significance of influencing factors of CO2 emissions varies across provinces. The role of economic activity in Shannxi is more pronounced compared to that of the other four provinces, as well as the role of population in Xinjiang; (3) when the decoupling relationship is considered, "relative decoupling" and "no decoupling" are the main characteristics under investigation during the examined period. Whereas "strong decoupling" was only identified in 2007 and 2009; (4) the current extensive pattern of economic growth in Northwest China poses a serious threat to the decoupling process. Furthermore, the coal-based energy structure also hinders the decoupling process. According to these results, some policy recommendations are proposed. [ABSTRACT FROM AUTHOR]

In the context of global warming and energy shortage, this paper discusses the techno-economic feasibility of a residential household based on 100% renewable energy in China. The energy storage life, equipment's residual value, system shortage capacity and atmospheric pollution emissions were considered comprehensively. A life cycle evaluation model based on the net present value (NPV) was built. Taking a real household as an example, the levelised cost of energy (LCOE) is 0.146 $/kW and the unmet load is only 0.86%, which has a big economic advantage when compared with diesel generators. If grid-connected, the system can bring $8079 in 25 years when the LCOE is −0.062 $/kW. The effects of the allowed shortage capacity, renewable energy resources, battery price and the allowed depth of discharge on the economy and energy structure were examined. For example, due to the features of the residential load, the influence of wind resource richness is more obvious than the irradiance. The maximum depth of discharge has less impact on the economy. This paper verifies the techno-economic rationality and feasibility of 100% renewable energy for a household. [ABSTRACT FROM AUTHOR]

This paper considers the Global Thermodynamic Potential (GTP) indicator to perform a unified assessment of greenhouse gas (GHG) emissions, and to systematically reveal the emission embodiment in the production, consumption, and international trade of the Chinese economy in 2007 as the most recent year available with input-output table and updated inventory data. The results show that the estimated total direct GHG emissions by the Chinese economy in 2007 amount to 10,657.5 Mt CO2-eq by the GTPs with 40.6% from CH4 emissions in magnitude of the same importance as CO2 emissions. The five sectors of Electric Power/Steam and Hot Water Production and Supply, Smelting and Pressing of Ferrous and Nonferrous Metals, Nonmetal Mineral Products, Agriculture, and Coal Mining and Dressing, are responsible for 83.3% of the total GHG emissions with different emission structures. The demands of coal and coal-electricity determine the structure of emission embodiment to an essential extent. The Construction sector holds the top GHG emissions embodied in both domestic production and domestic consumption. The GHG emission embodied in gross capital formation is more than those in other components of final demand characterized by extensive investment and limited household consumption. China is a net exporter of embodied GHG emissions, with a remarkable share of direct emission induced by international trade, such as textile products, industrial raw materials, and primary machinery and equipment products exports. The fractions of CH4 in the component of embodied GHG emissions in the final demand are much greater than those fractions calculated by the Global Warming Potentials, which highlight the importance of CH4 emissions for the case of China and indicate the essential effect of CH4 emissions on global climate change. To understand the full context to achieve GHG emission mitigation, this study provides a new insight to address China's GHG emissions status and hidden emission information induced by the final demand to the related policy-makers. [ABSTRACT FROM AUTHOR]

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

Green innovation has been identified as a viable strategy to mitigate the tension between industrial change and pollutant emissions. Relevant research should focus more on the impact of eco-friendly innovations on carbon emissions. Consequently, using a panel data set that covers 30 Chinese provinces from 2005 to 2020, we examine whether there is a carbon-abatement effect of green innovation in the construction sector. According to the findings of a two-way fixed-effects model, green innovation substantially positively influences reduction in dioxide emissions in the Chinese construction industry. The results of a panel threshold model show a significant non-linear relationship between green innovation and carbon emissions when the environmental regulation intensity is used as the threshold variable. Furthermore, we discovered that green innovation cuts carbon emissions considerably through environmental regulation. Finally, the impact of abatement varies significantly between regions, innovation elements, and types of development. [ABSTRACT FROM AUTHOR]

Industry is widely valued as an important contributor to carbon emissions. Therefore, it is of great significance to analyze the industrial carbon emissions (ICE) in Guangdong, the strongest industrial province in China. We have adopted the carbon emission accounting model and standard deviational ellipse analysis model to analyze the temporal and spatial characteristics and evolution trends of the industry carbon emission amount and intensity in Guangdong from 1998 to 2013. The study results include: (1) Due to the rapid development of industry, Guangdong's ICE showed a steady growth trend; (2) The distribution characteristics of ICE were characterized by the trend of taking the Pearl River Delta (PRD) region as the center and gradually spreading to the surrounding areas. From the perspective of industrial sectors, it can be divided into steady growth type, fluctuant growth type, basically stable type, and decrease type; (3) The spatial pattern of the ICE in Guangdong is basically the same as that of the total industrial output value, that is, the southwest-northeast pattern. This work is helpful for China's carbon peak, especially for the formulation of industrial carbon peak policy and the sustainable development of the environment. [ABSTRACT FROM AUTHOR]

Residential coal combustion is a major source of air pollution in developing countries, including China. Indeed, precisely measuring the real-time emission of major air pollutants is often challenging and can hardly be repeated at a lab-scale. In this study, for the first time, two clean coals initiated from raw bituminous coal were burned for real-time estimation of air pollution characteristics and their thermal efficiencies in different stoves. Moreover, thermodynamic equilibrium simulations were investigated for slagging parameters using Factsage 7.1 at reaction temperature 800~1600 °C. Results revealed that the firepower of clean coals (Briquetted coal and Semi-coke) was much higher (2.2 kW and 2.1 kW) than raw coal (1.8 kW) in a traditional stove. However, the thermal efficiencies were remarkably increased (13.3% and 13.5%) in an improved stove for briquetted coal and semi-coke, respectively. The emission of major air pollutants including carbon monoxide (CO), sulfur dioxide (SO2), particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), non-methane hydrocarbons (NMHCs) from both coal and semi-coke was significantly reduced. Thermodynamic equilibrium calculations indicate that briquetted coal is not susceptible to slagging under the reaction conditions in the household stove. The current study provides guidance for the selection of alternative and efficient clean coal fuels in rural areas for household purposes coupled with public health and safety. [ABSTRACT FROM AUTHOR]

In China, environmental pollution responsibilities are divided according to administrative regions. However, because of the strong externality of environmental pollution, the movement of environmental pollution undoubtedly increases the complexity of pollution governance. To divide the responsibility of environmental pollution governance in each province, we effectively quantify the unequal relationship between environmental pollution costs and economic benefits in each province to understand the mechanism and characteristics of inter-provincial environmental pollution movement. Based on the regional input–output model and an inventory we compiled of sulfur dioxide(SO2) emissions of air pollutants in 2012, we calculate the implied inter-provincial environmental pollution emissions and economic benefits from trade, based on production and consumption (supply-side and demand-side). In addition, the movement relationship is explored, and the cost and economic value-added indexes of air pollution control are further constructed to provide effective evidence for a reasonable division of responsibility for environmental pollution control. The results show that there are obvious environmental inequities in the regional trade process in each province, indicating that environmental pollution has been moved. Developed provinces have more economic benefits but pay less in the process of trading goods with less-developed provinces due to the advantages of their industrial structure, while the opposite is true for less-developed provinces. Finally, we propose corresponding policy recommendations to change this condition. [ABSTRACT FROM AUTHOR]

Construction land expansion significantly affects energy-related carbon emissions. This paper analyzed the effect of construction land expansion on energy-related carbon emissions in China and its provinces from 2001 to 2011 by using the logarithmic mean Divisia index method. We divided the study into two intervals (2001-2006 and 2006-2011) and categorized the 30 provinces of China into eight zones. Results indicated that construction land expansion exerted the second largest positive effect on carbon emission growth in China and in the 30 provinces from 2001 to 2011. The north, east, and south coastal regions as well as the middle Yellow River region, were the highly affected regions in the same period. Between the two study intervals, the effect of construction land expansion on carbon emissions decreased in China and in the coastal regions, but increased in inland regions. The Hebei, Shandong, Jiangsu, Zhejiang, Fujian, Guangdong, Yunnan, Chongqing, Ningxia, and Xinjiang provinces, which are concentrated in the north, east, and south coastal regions, were selected for the reduction of carbon emissions by controlling construction land expansion. [ABSTRACT FROM AUTHOR]

Currently, there are considerable discrepancies between China's central government and some local governments in attitudes towards coal to liquids (CTL) technology. Energy return on investment (EROI) analysis of CTL could provide new insights that may help solve this dilemma. Unfortunately, there has been little research on this topic; this paper therefore analyses the EROI of China's Shenhua Group Direct Coal Liquefaction (DCL) project, currently the only DCL commercial project in the world. The inclusion or omission of internal energy and by-products is controversial. The results show that the EROIstnd without by-product and with internal energy is 0.68-0.81; the EROIstnd (the standard EROI) without by-product and without internal energy is 3.70-5.53; the EROIstnd with by-product and with internal energy is 0.76-0.90; the EROIstnd with by-product and without internal energy is 4.13-6.14. Furthermore, it is necessary to consider carbon capture and storage (CCS) as a means to control the CO2 emissions. Considering the added energy inputs of CCS at the plant level, the EROIs decrease to 0.65-0.77, 2.87-3.97, 0.72-0.85, and 3.20-4.40, respectively. The extremely low, even negative, net energy, which may be due to high investments in infrastructure and low conversion efficiency, suggests CTL is not a good choice to replace conventional energy sources, and thus, Chinese government should be prudent when developing it. [ABSTRACT FROM AUTHOR]

Increasing awareness of climate change has induced demand for action most notably. As public demand for action on climate change increases, conversion to energy sources with lower greenhouse gas (GHG) intensity will accelerate. Experience during the COVID-19 pandemic provided insight into how atmospheric conditions will respond to lower GHG emissions. A low-carbon future will require decarbonization of the energy supply mix for electrical production and industrial processes. Coal demand likely will decrease more rapidly than other fossil energy sources, replaced by natural gas and renewable energy sources that have lower GHG intensity and that will be available readily and economically. This decline will accelerate as China focuses on its carbon neutrality goals, the U.S. re-engages in the Paris Agreement, and India moves to a lower carbon future. However, perturbations in the decline will inevitably occur in response to global issues (e.g., pandemic, military conflict). Carbon capture, utilization, and storage (CCUS) technologies can reduce GHG emissions from coal as an energy source, but the capital and operation costs of CCUS remain high, which translates to slow commercial deployment. In this study, a literature review and interviews with industry experts and business leaders were conducted to understand the current and projected role of fossil fuels, primarily coal, in the global energy matrix; present their contributions to GHGs; analyze the effects of social expectations and climate policy on energy choices and coal demand; and describe the expected impacts on coal production for decades to come. [ABSTRACT FROM AUTHOR]

Carbon capture and storage (CCS) technology is an attractive technique to help power enterprises with carbon emission reduction. In this paper, a two-stage CCS retrofit investment in an existing coal-fired power plant in China including the first stage (demonstration project) and second stage (commercial operation) is taken as a case to decide when and whether to invest. Distinguished from previous models, a binomial lattice compound real options model including the options to defer and expand is established. Further, the accounting approaches to certified emission reductions (CERs) based on the thermodynamics principle are first proposed concerning this model. We find the total invest value under compound options model is less than zero, although greater than that by NPV method. The results indicate carbon prices and subsidy policy, respectively, play a dominating role in initiating the CCS investment at the first and second stage. The growth in government subsidy at the first stage has obviously greater effects on decreasing critical carbon trading prices. Besides, the minimum critical carbon price is 87.09 RMB/ton with full subsidy, greater than the current price (56 RMB/ton). This also illustrates it is not the optimal occasion to invest in a CCS retrofit project for power enterprises. [ABSTRACT FROM AUTHOR]

Climate change has gained widespread attention, and the rapid growth of the economy in China has generated a considerable amount of carbon emissions. Zhejiang Province was selected as a study area. First, the energy-related carbon emissions from 2000 to 2014 were accounted for, and then the Logarithmic Mean Divisia Index (LMDI) decomposition model was applied to analyse the driving factors underlying the carbon emissions. Finally, three scenarios (inertia, comparative decoupling and absolute decoupling) for 2020 and 2030 were simulated based on the low-carbon city and Human Impact Population Affluence Technology (IPAT) models. The results showed (1) carbon emissions increased by 1.66 times from 2000 to 2014, and trends of carbon emissions were used to divide the study period into three phases (rapid, medium growth and slow decrease phases, with annual growth rates of 12.60%, 4.77% and -1.24%, respectively); (2) the energy intensity effect from 2000-2011 inhibited carbon emissions but was exceeded by the economic output effect, which increased emissions, whereas the energy intensity effect from 2011-2014 outweighed the economic output effect; (3) the scenario analyses revealed that both the comparative and absolute decoupling scenarios would remain consistent with the carbon emissions boundaries in 2020 and 2030, but the comparative decoupling scenario was more reasonable for sustainable development. In addition, appropriate design of emission trading scheme could help to achieve the comparative decoupling by financial incentives. [ABSTRACT FROM AUTHOR]

China has become the world's largest carbon dioxide (CO2) emitter. Sectoral production activities promote economic development while also adding considerably to national CO2 emissions. Due to their different sectoral structures, each region shows different levels of economic development and CO2 emissions. The Chinese government hopes to achieve the dual objectives of economic growth and CO2 emissions reduction by encouraging those sectors that have high economic influence and low environmental influence. Based on the above background, this study constructed an inter-regional sectoral economic influence coefficient (REIC) and a CO2 emissions influence coefficient (RCIC) based on the basic multi-regional input-output (MRIO) model to analyse the economy-carbon nexus of 17 sectors in 30 regions in China in 2010. The results showed that most Chinese sectors and regions had low CO2 emissions influences in 2010. However, some sectors showed negative environmental influences. Specifically, the mining-related sectors showed high CO2 emissions influence with low economic influence. It is encouraging that some light industry and high-end equipment manufacturing sectors had low CO2 emissions influence with high economic influence. For regions, geographic location and past preferential policies are the most important factors influencing local economic growth and CO2 emissions reduction. Most inland regions have low economic influence with high or low CO2 emissions influence. Meanwhile, most coastal regions showed high economic influence with low CO2 emissions influence. Finally, we propose some policy implications for sectors and regions. [ABSTRACT FROM AUTHOR]

As a less-developed province that has been chosen to be part of a low-carbon pilot project, Yunnan faces the challenge of maintaining rapid economic growth while reducing CO2 emissions. Understanding the drivers behind CO2 emission changes can help decouple economic growth from CO2 emissions. However, previous studies on the drivers of CO2 emissions in less-developed regions that focus on both production and final demand have been seldom conducted. In this study, a structural decomposition analysis-logarithmic mean Divisia index (SDA-LMDI) model was developed to find the drivers behind the CO2 emission changes during 1997-2012 in Yunnan, based on times series energy consumption and input-output data. The results demonstrated that the sharp rise in exports of high-carbon products from the metal processing and electricity sectors increased CO2 emissions, during 2002-2007. Although increased investments in the construction sector also increased CO2 emissions, during 2007-2012, the carbon intensity of Yunnan's economy decreased substantially because the province vigorously developed hydropower and improved energy efficiency in energy-intensive sectors. Construction investments not only carbonized the GDP composition, but also formed a carbon-intensive production structure because of high-carbon supply chains. To further mitigate CO2 emissions in Yunnan, measures should promote the development and application of clean energy and the formation of consumption-based economic growth. [ABSTRACT FROM AUTHOR]

The promotion of hybrid and electric vehicles (EVs) has been proposed as one promising solution for reducing transport energy consumption and mitigating vehicular emissions in China. In this study, the energy and environmental impacts of hybrid and EVs during 2010-2020 were evaluated through an energy conversion analysis and a life cycle assessment (LCA), and the per-kilometer energy consumptions of gasoline, coal, natural gas (NG), oil, biomass, garbage and electricity for EVs and HEVs were estimated. Results show that the EVs and HEVs can reduce the energy consumption of vehicles by national average ratios of 17%-19% and 30%-33%, respectively. The study also calculated the detailed emission factors of SO2, NOX, VOC, CO, NH3, PM10, PM2.5, OC, EC, CO2, N2O, CH4, Pb and Hg. It is indicated that the HEVs can bring significant reductions of NOX, VOC and CO emissions and lesser decreases of SO2 and CO2 for a single vehicle. The EVs could decrease many of the VOC, NH3, CO and CO2 emissions, but increase the SO2, NOX and particles by 10.8-13.0, 2.7-2.9 and 3.6-11.5 times, respectively. In addition, the electricity sources had significant influence on energy consumption (EC) and emissions. A high proportion of coal-fired energy resulted in large ECs and emission factors. The total energy consumption and pollutants emission changes in 2015 and 2020 were also calculated. Based on the energy use and emission analysis of HEVs and EVs, it is suggested that EVs should be promoted in the regions with higher proportions of 2664 hydropower, natural gas-fired power and clean energy power, while HEVs can be widely adopted in the regions with high coal-fired power ratios. This is to achieve a higher energy consumption reduction and pollutant emission mitigation. Moreover, the results can also provide scientific support for the total amount control of regional air pollutants in China. [ABSTRACT FROM AUTHOR]

In view of the great contribution of coal-fired units to CO2 emissions, the coupled coal and power system with consideration of CO2 mitigation is a typical sub-system of the highly emitting Chinese energy system for low-carbon studies. In this study, an inexact mix-integer two-stage programming (IMITSP) model for the management of low-carbon energy systems was developed based on the integration of multiple inexact programming techniques. Uncertainties and complexities related to the carbon mitigation issues in the coupled coal and power system can be effectively reflected and dealt with in this model. An optimal CO2 mitigation strategy associated with stochastic power-generation demand under specific CO2 mitigation targets could be obtained. Dynamic analysis of capacity expansion, facility improvement, coal selection, as well as coal blending within a multi-period and multi-option context could be facilitated. The developed IMITSP model was applied to a semi-hypothetical case of long-term coupled management of coal and power within a low-carbon energy system in north China. The generated decision alternatives could help decision makers identify desired strategies related to coal production and allocation, CO2 emission mitigation, as well as facility capacity upgrade and expansion under various social-economic, ecological, environmental and system-reliability constraints. It could also provide interval solutions with a minimized system cost, a maximized system reliability and a maximized power-generation demand security. Moreover, the developed model could provide an in-depth insight into various CO2 mitigation technologies and the associated environmental and economic implications under a given reduction target. Tradeoffs among system costs, energy security and CO2 emission reduction could be analyzed. [ABSTRACT FROM AUTHOR]

Carbon emissions and environmental protection issues have brought pressure from the international community during Chinese economic development. Recently, Chinese Government announced that carbon emissions per unit of GDP would fall by 60–65% compared with 2005 and non-fossil fuel energy would account for 20% of primary energy consumption by 2030. The Beijing-Tianjin-Hebei region is an important regional energy consumption center in China, and its energy structure is typically coal-based which is similar to the whole country. Therefore, forecasting energy consumption related carbon emissions is of great significance to emissions reduction and upgrading of energy supply in the Beijing-Tianjin-Hebei region. Thus, this study thoroughly analyzed the main energy sources of carbon emissions including coal, petrol, natural gas, and coal power in this region. Secondly, the kernel function of the support vector machine was applied to the extreme learning machine algorithm to optimize the connection weight matrix between the original hidden layer and the output layer. Thirdly, the grey prediction theory was used to predict major energy consumption in the region from 2017 to 2030. Then, the energy consumption and carbon emissions data for 2000–2016 were used as the training and test sets for the SVM-ELM (Support Vector Machine-Extreme Learning Machine) model. The result of SVM-ELM model was compared with the forecasting results of SVM (Support Vector Machine Algorithm) and ELM (Extreme Learning Machine) algorithm. The accuracy of SVM-ELM was shown to be higher. Finally, we used forecasting output of GM (Grey Prediction Theory) (1, 1) as the input of the SVM-ELM model to predict carbon emissions in the region from 2017 to 2030. The results showed that the proportion of energy consumption seriously affects the amount of carbon emissions. We found that the energy consumption of electricity and natural gas will reach 45% by 2030 and carbon emissions in the region can be controlled below 96.9 million tons. Therefore, accelerating the upgradation of industrial structure will be the key task for the government in controlling the amount of carbon emissions in the next step. [ABSTRACT FROM AUTHOR]