An Integrated Analysis on the Synergistic Reduction of Carbon and Pollution Emissions from China’s Iron and Steel Industry

Decarbonization and decontamination of the iron and steel industry(ISI),which contributes up to 15%to anthropogenic CO_(2) emissions(or carbon emissions)and significant proportions of air and water pollutant emissions in China,are challenged by the huge demand for steel.Carbon and pollutants often share common emission sources,indicating that emission reduction could be achieved synergistically.Here,we explored the inherent potential of measures to adjust feedstock composition and technological structure and to control the size of the ISI to achieve carbon emission reduction(CER)and pollution emission reduction(PER).We investigated five typical pollutants in this study,namely,petroleum hydrocarbon pollutants and chemical oxygen demand in wastewater,particulate matter,SO_(2),and NO_(x) in off gases,and examined synergies between CER and PER by employing cross elasticity for the period between 2022 and 2035.The results suggest that a reduction of 8.7%-11.7%in carbon emissions and 20%-31%in pollution emissions(except for particulate matter emissions)could be achieved by 2025 under a high steel scrap ratio(SSR)scenario.Here,the SSR and electric arc furnace(EAF)ratio serve critical roles in enhancing synergies between CER and PER(which vary with the type of pollutant).However,subject to a limited volume of steel scrap,a focused increase in the EAF ratio with neglection of the available supply of steel scrap to EAF facilities would lead to an increase carbon and pollution emissions.Although CER can be achieved through SSR and EAF ratio optimization,only when the crude steel production growth rate remains below 2.2%can these optimization measures maintain the emissions in 2030 at a similar level to that in 2021.Therefore,the synergistic effects between PER and CER should be considered when formulating a development route for the ISI in the future.

Prospects for green steelmaking technology with low carbon emissions in China

The steel industry is a major source of CO_(2) emissions,and thus,the mitigation of carbon emissions is the most pressing challenge in this sector.In this paper,international environmental governance in the steel industry is reviewed,and the current state of development of low-carbon technologies is discussed.Additionally,low-carbon pathways for the steel industry at the current time are proposed,emphasizing prevention and treatment strategies.Furthermore,the prospects of low-carbon technologies are explored from the perspective of transitioning the energy structure to a“carbon-electricity-hydrogen”relationship.Overall,steel enterprises should adopt hydrogen-rich metallurgical technologies that are compatible with current needs and process flows in the short term,based on the carbon substitution with hydrogen(prevention)and the CCU(CO_(2) capture and utilization)concepts(treatment).Additionally,the capture and utilization of CO_(2) for steelmaking,which can assist in achieving short-term emission reduction targets but is not a long-term solution,is discussed.In conclusion,in the long term,the carbon metallurgical process should be gradually supplanted by a hydrogen-electric synergistic approach,thus transforming the energy structure of existing steelmaking processes and attaining near-zero carbon emission steelmaking technology.

Synergistic dance of digital economy and green finance on carbon emissions:Insights from China

China has recently implemented a dual-carbon strategy to combat climate change and other environmental issues and is committed to modernizing it sustainably.This paper supports these goals and explores how the digital economy and green finance intersect and impact carbon emissions.Using panel data from 30 Chinese provinces over the period 2011-2021,this paper finds that the digital economy and green finance can together reduce carbon emissions,and conducts several robustness tests supporting this conclusion.A heterogeneity analysis shows that these synergistic effects are more important in regions with low levels of social consumption Meanwhile,in the spatial dimension,the synergistic effect of the local digital economy and green finance adversely impacts the level of carbon emissions in surrounding areas.The findings of this paper provide insights for policymakers in guiding capital flow and implementing carbon-reduction policies while fostering the growth of China’s digital economy and environmental sustainability.

Rolling Decision Model of Thermal Power Retrofit and Generation Expansion Planning Considering Carbon Emissions and Power Balance Risk

With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,methods for quantifying and assessing carbon emissions and operational risks are lacking.It results in excessive carbon emissions and frequent load-shedding on some days,although meeting annual carbon emission reduction targets.First,in response to the above problems,carbon emission and power balance risk assessment indicators and assessment methods,were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios,considering power supply regulation and renewable energy fluctuation characteristics.Secondly,building on traditional two-tier models for low-carbon power planning,including investment decisions and operational simulations,considering carbon emissions and power balance risks in lower-tier operational simulations,a two-tier rolling model for thermal power retrofit and generation expansion planning was established.The model includes an investment tier and operation assessment tier and makes year-by-year decisions on the number of thermal power units to be retrofitted and the type and capacity of units to be commissioned.Finally,the rationality and validity of the model were verified through an example analysis,a small-scale power supply system in a certain region is taken as an example.The model can significantly reduce the number of days of carbon emissions risk and ensure that the power balance risk is within the safe limit.

Spatiotemporal Differentiation of Urban Spatial Form and Carbon Emissions in Poyang Lake City Group

In response to the inherent requirements of low-carbon land spatial planning in Jiangxi Province and the lack of existing research,this paper explored the mechanism of spatial form elements of Poyang Lake urban agglomeration on urban carbon emissions.Based on generalized linear regression and geographically weighted regression models,this paper analyzed the spatiotemporal distribution characteristics of carbon emissions,the spatiotemporal relationship between urban form index and carbon emissions,and the spatial differentiation of the intensity of dominant factors from 63 county-level administrative units in the Poyang Lake city group from 2005 to 2020.The results showed that:①The carbon emissions of urban agglomerations around Poyang Lake are generally increasing,and the spatial distribution of carbon emissions is characterized by high-value concentration in the middle and low-value agglomeration in pieces;②The main driving factor for the spatial heterogeneity of carbon emissions was the expansion of built-up area;③Improving urban compactness and optimizing urban form could effectively reduce urban carbon emissions.The results showcased the correlation between urban spatial landscape pattern and the spatiotemporal distribution of carbon emissions,which could make the low-carbon land spatial planning in the Poyang Lake city group more reasonable and practical.

Rural Carbon Emissions Based on Community Management

Rural community is an effective way to simultaneously achieve manage- ment of ecological resources and protection of natural resources, depending on its management mode based on cooperation, motivation, local experiences and extensi- ble boundary. In the research, carbon emission in community is a kind of ecological resources and negative externality is the cause of increase of rural carbon emission. Compared with governmental ruling and marketing approach, community manage- ment mode proves more effective to solve the problem of negative externality of carbon emission in community. Furthermore, rural carbon, emission was analyzed in detail on basis of community management mode and extending mode of carbon emis- sion in rural areas. In addition, some policies and suggestions were proposed to im- prove community management of carbon emission in rural areas, providing an ef- fective way for low-carbon economy in rural areas.

Research on Spatial-Temporal Characteristics and Driving Factor of Agricultural Carbon Emissions in China

Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 kinds of major carbon emission sources including agricultural materials inputs, paddy ifeld, soil and livestock breeding, this paper ifrstly calculated agricultural carbon emissions from 1995 to 2010, as well as 31 provinces and cities in 2010 in China. We then made a decomposed analysis to the driving factors of carbon emissions with logarithmic mean Divisia index （LMDI） model. The results show：（1） The amount of agricultural carbon emissions is 291.1691 million t in 2010. Compared with 249.5239 million t in 1995, it increased by 16.69%, in which, agricultural materials inputs, paddy ifeld, soil, enteric fermentation, and manure management accounted for 33.59, 22.03, 7.46, 17.53 and 19.39%of total agricultural carbon emissions, respectively. Although the amount exist ups and downs, it shows an overall trend of cyclical rise; （2） There is an obvious difference among regions：the amount of agricultural carbon emissions from top ten zones account for 56.68%, while 9.84%from last 10 zones. The traditional agricultural provinces, especially the major crop production areas are the main source regions. Based on the differences of carbon emission rations, 31 provinces and cities are divided into ifve types, namely agricultural materials dominant type, paddy ifeld dominant type, enteric fermentation dominant type, composite factors dominant type and balanced type. The agricultural carbon emissions intensity in west of China is the highest, followed by the central region, and the east zone is the lowest; （3） Compared with 1995, efifciency, labor and structure factors cut down carbon emissions by 65.78, 27.51 and 3.19%, respectively;while economy factor increase carbon emissions by 113.16%.

Distributional dynamic and trend evolution of China's agricultural carbon emissions-an analysis on panel data of 31 provinces from 2002 to 2011

Researching the dynamic distribution characteristics and trend evolution of agricultural carbon emissions is of considerable significance in formulating an effective agricultural carbon reduction policy.Based on measurement of agricultural carbon emissions of 31 provinces over the period 2002-2011,the study observed regional differences and the dynamic evolution of distribution of agricultural carbon emissions using agricultural carbon intensity as the indicator,accompanied by Gini coefficients and the kernel density estimation method.The results demonstrate first that agricultural carbon emissions for China show an obvious nonequilibrium nature in regard to spatial distribution.According to the differences in agricultural carbon emissions dynamic trends,we divided the 31 regions into four types- continuous decline,fluctuating decline,continuous increase,and fluctuating increase.Further,agricultural carbon emissions intensity showed a downward trend with significant differences in the research areas.Second,the gap in spatial distribution of national agricultural carbon emissions is gradually expanding based on the results calculated by Gini coefficient.From the perception of regional differences in agricultural carbon emissions,the eastern region showed an average level,the gap was more obvious in the central region,while western region showed a trend of fluctuating downward.Third,according to estimation by kernel density,the regional disparity in agricultural carbon emissions had a downward,but limited,trend.In regard to agricultural carbon emissions over the three areas,the regional gap not only tended to decrease but also showed a "four way" differentiation phenomenon in the eastern region.The difference in the central region difference was narrower.On the whole,the gap for the western region reduced steadily over a small range.

A major pathway for carbon and nitrogen losses-Gas emissions during storage of solid pig manure in China

This study investigated the carbon(C) and nitrogen(N) gas emissions(N_2O,NH_3,CO_2 and CH_4) from solid pig manure management in China.Gas emissions were quantified from static piles over 60 days during summer in China's Yangtze River Basin,using Drager-Tube and static chamber-gas chromatography techniques.High emissions of NH_3 and N_2 O were observed at the early stage of storage,but high emission of CH_4 occured later during storage.Overall,62% of the total C in the original pile was lost; CO_2 and CH_4 emissions accounted for 57 and 0.2% of C lost respectively.Over the same time,41% of the total N in the original pile was lost; NH_3 and N_2 O emissions accounted for 15 and 0.3% of N lost respectively.The volatilization of NH_3 during storage in summer was 4.56 g NH_3 per kg dry weight.The total greenhouse gas(GHG) emissions during storage accounted for 67.93 g CO_2 equivalent per kg dry weight; N_2 O and CH_4 contributed to 46 and 55% of total GHG emissions respectively.Given China's major role in pig production,further attention should given to pig manure management to mitigate its contribution to atmospheric pollution.

International trade,carbon leakage,and CO_2 emissions of manufacturing industry

Foreign trade drives China's growth,but as the trade scale continues to expand,the carbon emissions also increase quickly.Based on the industry panel data from 1996 to 2010,this paper calculates carbon emissions of 27manufacturing industries.According to the intensity of carbon emissions,this paper divides the manufacturing sectors into low carbon and high carbon manufacturing industry and then analyzes the carbon emission trends.Next,the paper uses the feasible generalized least square regression to verify the existence of environmental Kuznets curve(EKC)of the manufacturing industry's carbon.In order to investigate the carbon leakage problem,the regression also includes the interaction term between trade and industrial value added.Our findings are as follows:the carbon emissions of the whole manufacturing industry and low carbon manufacturing industry accord with the EKC curve,but have a linear relationship with the high carbon manufacturing industry;trade reduces the carbon emissions of the whole manufacturing industry and low carbon manufacturing industry,but it increases those of the high carbon manufacturing industry;for the whole manufacturing industry and low carbon manufacturing industry,there is no carbon leakage,but it exists in the high carbon manufacturing industry.On the whole,pollution haven hypothesis does not hold up in China,and China does not need to limit industry foreign trade to reduce the emission of CO_2.But the manufacturing industry will still be the main engine of the economic growth,and therefore our country should make an effective low-carbon policy,introduce advanced technology,increase R&D investment into lowcarbon technologies,and upgrade and transform the original equipment to change the backward mode of production.

Optimization of Cutting Parameters for Trade-off Among Carbon Emissions, Surface Roughness, and Processing Time

As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is crucial for automobile panel dies in order to achieve synergistic minimization of the environment impact, product quality, and processing efficiency. This paper presents a processing task-based evaluation method to optimize the cutting parameters, considering the trade-off among carbon emissions, surface roughness, and processing time. Three objective models and their relationships with the cutting parameters were obtained through input–output, response surface, and theoretical analyses, respectively. Examples of cylindrical turning were applied to achieve a central composite design(CCD), and relative validation experiments were applied to evaluate the proposed method. The experiments were conducted on the CAK50135 di lathe cutting of AISI 1045 steel, and NSGA-Ⅱ was used to obtain the Pareto fronts of the three objectives. Based on the TOPSIS method, the Pareto solution set was ranked to find the optimal solution to evaluate and select the optimal cutting parameters. An S/N ratio analysis and contour plots were applied to analyze the influence of each decision variable on the optimization objective. Finally, the changing rules of a single factor for each objective were analyzed. The results demonstrate that the proposed method is effective in finding the trade-off among the three objectives and obtaining reasonable application ranges of the cutting parameters from Pareto fronts.

Factors affecting the pilot trading market of carbon emissions in China

Climate change and carbon emissions are major problems which are attracting worldwide attention. China has had its pilot carbon emission trading markets in seven regions for more than 3 years. What affects carbon emission trading market in China is a big question. More attention is paid to how China promotes the carbon emission trading schemes in the whole country. This paper addresses concerns about the functioning of carbon emission trading schemes in seven pilot regions and takes the weekly data from November 25, 2013, to March 19, 2017. We employ a vector autoregressive model to study how coal price, oil price and stock index have affected the carbon price in China. The results indicate that carbon price is mainly affected by its own historical price; coal price and stock index have negative effects on carbon price, while oil price has a negative effect on carbon price during the first 3 weeks and then has a positive effect on carbon price. More regulatory attention and economic measures are needed to improve market efficiency, and the mechanisms of carbon emission trading schemes should be improved.

Effects of silviculture treatments in a hurricane-damaged forest on carbon storage and emissions in central Hokkaido, Japan

Hurricanes cause abrupt carbon reduction in forests, but silviculture treatment can be an effective means of quickly regenerating and restoring hurricane-damaged sites. This study assessed how silviculture treatments affect carbon balance after hurricane damage in central Hokkaido, Japan. We examined carbon storage in trees and underground vegetation as well as carbon emissions from silviculture operations in 25-year-old stands, where scarification and plantation occurred just after hurricane damage. The amount of carbon stored varied according to silviculture treatment. Among three scarification treatments, a scarified depth of 0 cm （understory vegetation removal） led to the largest amount of carbon stored （64.7 t·ha^-1 C）. Among four plantation treatments, the largest amount of carbon was stored in a Larix hybrid （L. gmelinii var. japonica × L. kaempferi） plantation （80.3 t·ha^-1 C）. The plantation of Abies sachalinensis was not successful at accumulating carbon （40.5·ha^-1 C）. The amount of carbon emitted from silviculture operations was 0.05-0.14 t·ha^-1 C, and it marginally affected the net carbon balance of the silviculture project. Results indicate that silviculture treatments should beperformed in an appropriate way to effectively recover the ability of carbon sequestration in hurricane-damaged forests.

Analysis of transportation carbon emissions and its potential for reduction in China

The transportation industry is an essential sector for carbon emissions mitigation.This paper firstly used the LMDI(Logarithmic Mean Divisia Index)decomposition method to establish factors decomposition model on China's transportation carbon emission.Then,a quantitative analysis was performed to study the factors influencing China's transportation carbon emissions from 1991 to 2008,which are identified as transportation energy efficiency,transportation structure and transportation development.The results showed that:(1)The impact of transportation development on transportation carbon emissions showed pulling function.Its contribution value to carbon emissions remained at high growth since 1991 and showed an exponential growth trend.(2)The impact of transportation structure on transportation carbon emissions showed promoting function in general,but its role in promoting carbon emissions decreased year by year.And with the continuous optimization of transportation structure,the promoting effect decreased gradually and showed the inversed"U"trend.(3)The impact of transportation energy efficiency on transportation carbon emissions showed a function of inhibition before pulling.In order to predict the potential of carbon emission reduction,three scenarios were set.Analysis of the scenarios showed that if greater intensity emission reduction measures are taken,the carbon emissions will reduce by 31.01 million tons by 2015 and by 48.81 million tons by 2020.

Analysis and forecast of residential building energy consumption in Chongqing on carbon emissions

Carbon emissions mainly result from energy consumption. Carbon emissions inevitably will increase to some extent with economic expansion and rising energy consumption. We introduce a gray theory of quantitative analysis of the energy consumption of residential buildings in Chongqing,China,on the impact of carbon emission factors. Three impacts are analyzed,namely per capita residential housing area,domestic water consumption and the rate of air conditioner ownership per 100 urban households. The gray prediction model established using the Chongqing carbon emission-residential building energy consumption forecast model is sufficiently accurate to achieve a measure of feasibility and applicability.

Carbon dioxide emissions from cities in China based on high resolution emission gridded data

Based on the China high resolution emission gridded data （I km spatial resolution）, this article is aimed to create a Chinese city carbon dioxide （CO2） emission data set using consolidated data sources as well as normalized and standardized data processing methods. Standard methods were used to calculate city CO2 emissions, including scope I and scope 2. Cities with higher CO2 emissions are mostly in north, northeast, and eastern coastal areas. Cities with lower CO2 emissions are in the western region. Cites with higher CO2 emissions are clustered in the Jing-Jin-Ji Region （such as Beijing, Tianjin, and Tangshan）, and the Yangtze River Delta region （such as Shanghai and Suzhou）. The city per capita CO2 emission is larger in the north than the south. There are obvious aggregations of cities with high per capita CO2 emission in the north. Four cities among the top 10 per capita emissions （Erdos, Wuhai, Shizuishan, and Yinchuan） cluster in the main coal production areas of northern China. This indicates the significant impact of coal resources endowment on city industry and CO2 emissions. The majority （77%） of cities have annual CO2 emissions below 50 million tons. The mean annual emission, among all cities, is 37 million tons. Emissions from service-based cities, which include the smallest number of cities, are the highest. Industrial cities are the largest category and the emission distribution from these cities is close to the normal distribution. Emissions and degree of dispersion, in the other cities （excluding industrial cities and service-based cities）, are in the lowest level. Per capita CO2 emissions in these cities are generally below 20 t/person （89%） with a mean value of 11 t/person. The distribution interval of per capita CO2 emission within industrial cities is the largest among the three city categories. This indicates greater differences among per capita CO2 emissions of industrial cities. The distribution interval of per capita CO2 emission of other cities is the lowest, indicating smaller differences of per capita CO2 emissions among this city category. Three policy suggestions are proposed： first, city CO2 emission inventory data in China should be increased, especially for prefecture level cities. Second, city responsibility for emission reduction, and partition- ing the national goal should be established, using a bottom-up approach based on specific CO2 emission levels and potential for emission reductions in each city. Third, comparative and bench- marking research on city CO2 emissions should be conducted, and a Top Runner system of city CO2 emission reduction should be established.

Decomposition of factors influencing carbon emissions in the region of Beijing-Tianjin-Hebei,based on the perspective of terminal energy consumption

In order to analyze the factors influencing carbon emissions in the region of Beijing-Tianjin-Hebei and to explore the pathways to developing a low-carbon economy,this paper begins with the terminal energy consumption of three industries and residential consumption,and constructs an identical equation which is composed of population size,level of economic development,energy intensity,the proportion of energy consumption,energy structure,and the coefficient of carbon emissions.Based on the data of terminal energy consumption during 2000-2012,various factors are analyzed and their contribution is measured by Logarithmic Mean Divisia Index(LMDI).The results show that the levels of population and economy have a positive driving effect while energy intensity,energy structure,and carbon intensity have a negative driving effect;the proportion of energy consumption had a negative driving effect prior to 2006,then changed to positive.Among suggestions for a low-carbon economy are controlling population size,improving the quality of economic development,supporting research into new energy technology,accelerating regional integration and optimizing industrial structure,and enhancing environmental protection and spreading the concept of a low-carbon economy.

Spatial-temporal Evolution Characteristics and Decoupling Analysis of Influencing Factors of China’s Aviation Carbon Emissions

The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provincial level is still incomplete. This paper firstly uses Stochastic Impacts by Regression on Population, Affluence and Technology model(STIRPAT) model to analyze the time series evolution of China’s aviation carbon emissions from 2000 to 2019. Secondly, it uses the Logarithmic Mean Divisia Index(LDMI) model to analyze the influencing characteristics and degree of four factors on China’s aviation carbon emissions, which are air transportation revenue, aviation route structure, air transportation intensity and aviation energy intensity. Thirdly, it determines the various factors’ influencing direction and evolution trend of 31 provinces’ aviation carbon emissions in China(not including Hong Kong, Macao, Taiwan of China due to incomplete data). Finally, it derives the decoupling effort model and analyzes the decoupling relationship and decoupling effort degree between air carbon emissions and air transportation revenue in different provinces. The study found that from 2000 to2019, China’s total aviation carbon emissions continued to grow, while the growth rate of aviation carbon emissions showed a fluctuating downward trend. Air transportation revenue and aviation route structure promote the growth of total aviation carbon emissions, and air transportation intensity and aviation energy intensity have a restraining effect on the growth of total aviation carbon emissions. The scope of negative driving effect of air transportation revenue and air transportation intensity on total aviation carbon emissions in various provinces has increased. While the scope of positive driving influence of aviation route structure on total aviation carbon emissions of various provinces has increased, aviation energy intensity mainly has negative driving influence on total aviation carbon emissions of each province. Overall, the emission reduction trend in the areas to the west and north of the Qinling-Huaihe River Line is obvious. The decoupling mode between air carbon emissions and air transportation revenue in 31 provinces is mainly expansion negative decoupling.The air transportation intensity effect shows strong decoupling efforts in most provinces, the decoupling effort of aviation route structure effect and aviation energy intensity effect is not prominent.

Modeling of the effect of hydrogen injection on blast furnace operation and carbon dioxide emissions

The effect of hydrogen injection on blast furnace operation and carbon dioxide emissions was simulated using a 1D steady-state zonal model.The maximum hydrogen injection rate was evaluated on the basis of the simulation of the vertical temperature pattern in the blast furnace with a focus on the thermal reserve zone.The effects of blast temperature and oxygen enrichment were also examined to estimate coke replacement ratio,productivity,hydrogen utilization efficiency,and carbon dioxide emission reduction.For blast temperature of 1200℃,the maximum hydrogen injection rate was 19.0 and 28.3 kg of H_(2)/t of hot metal(HM)for oxygen enrichment of 2vol%and 12vol%,respectively.Results showed a coke replacement ratio of 3-4 kg of coke/kg of H_(2),direct CO_(2) emission reduction of 10.2%-17.8%,and increased productivity by up to 13.7%depending on oxygen enrichment level.Increasing blast temperature further reduced the direct CO_(2) emissions.Hydrogen utilization degree reached the maximum of 0.52-0.54 H_(2)O/(H_(2)O+H_(2)).The decarbonization potential of hydrogen injection was estimated in the range from 9.4 t of CO_(2)/t of H_(2) to 9.7 t of CO_(2)/t of H_(2).For economic feasibility,hydrogen injection requires revolutionary progress in terms of low-cost H_(2) generation unless the technological change is motivated by the carbon emission cost.Hydrogen injection may unfavorably affect the radial temperature pattern of the raceway,which could be addressed by adopting appropriate injection techniques.

Estimate of China's energy carbon emissions peak and analysis on electric power carbon emissions

China＇s energy carbon emissions are projected to peak in 2030 with approximately 110% of its 2020 level under the following conditions： 1） China＇s gross primary energy consumption is 5 Gtce in 2020 and 6 Gtce in 2030; 2） coal＇s share of the energy consumption is 61% in 2020 and 55% in 2030; 3） non-fossil energy＇s share increases from 15% in 2020 to 20% in 2030; 4） through 2030, China＇s GDP grows at an average annual rate of 6%; 5） the annual energy consumption elasticity coefficient is 0.30 in average; and 6） the annual growth rate of energy consumption steadily reduces to within 1%. China＇s electricity generating capacity would be 1,990 GW, with 8,600 TW h of power generation output in 2020. Of that output 66% would be from coal, 5% from gas, and 29% from non-fossil energy. By 2030, electricity generating capacity would reach 3,170 GW with 11,900 TW h of power generation output. Of that output, 56% would be from coal, 6% from gas, and 37% from non-fossil energy. From 2020 to 2030, CO2 emissions from electric power would relatively fall by 0.2 Gt due to lower coal consumption, and rela- tively fall by nearly 0.3 Gt with the installation of more coal-fired cogeneration units. During 2020--2030, the portion of carbon emissions from electric power in China＇s energy consumption is projected to increase by 3.4 percentage points. Although the carbon emissions from electric power would keep increasing to 118% of the 2020 level in 2030, the electric power industry would continue to play a decisive role in achieving the goal of increase in non-fossil energy use. This study proposes countermeasures and recommendations to control carbon emissions peak, including energy system optimization, green-coal-fired electricity generation, and demand side management.