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.

Scenario analysis of the Indonesia carbon tax impact on carbon emissions using system dynamics modeling and STIRPAT model

This study aims to develop a system dynamic(SD)forecasting model based on the STIRPAT model to forecast the effect of an IDR 30 per kg CO_(2)e carbon tax on carbon emissions,estimate future carbon emissions under ten scenarios,without and with the carbon tax,and estimate the environmental Kuznets curve(EKC)to predict Indonesia’s carbon emission peak.Carbon emission drivers in this study are decomposed into several factors,namely energy structure,energy intensity,industrial structure,GDP per capita,population,and fixed-asset investment.This study included nuclear power utilization starting in 2038.The research gaps addressed by this study compared to previous research are(1)use of the ex-ante approach,(2)inclusion of nuclear power plants,(3)testing the EKC hypothesis,and(4)contribution to government policy.The simulation results show that under the carbon tax,carbon emissions can be reduced by improving renewable energy structures,adjusting industrial structures to green businesses,and emphasizing fixed asset investment more environmentally friendly.Moreover,the result approved the EKC hypothesis.It shows an inverse U-shaped curve between GDP per capita and CO_(2)emissions in Indonesia.Indonesia’s fastest carbon emission peak is under scenario seven and is expected in 2040.Although an IDR 30 per kg CO_(2)e carbon tax and nuclear power will take decades to reduce carbon emissions,the carbon tax can still be a reference and has advantages to implement.This result can be a good beginning step for Indonesia,which has yet to gain experience with a carbon tax that can be implemented immediately and is helpful to decision-makers in putting into practice sensible measures to attain Indonesia’s carbon emission peaking.This research provides actionable insights internationally on carbon tax policies,nuclear energy adoption,EKC dynamics,global policy implications,and fostering international cooperation for carbon emission reductions.

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.

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.

Decoding the Einstein-Type Formula for Reducing Energy Conversion to Carbon Emissions in Renewables Systems

This article explores the role of distributed energy resources such as efficient solar cells that drive carbon neutrality within the solar energy. For example, the perovskite solar cells offer high efficiency and potential for low-cost production. A novel theoretical model is discovered in distributed energy resources for power emissions and cost. The smart carbon neutrality approaches are analyzed in both theory and experiments. The advantages, current challenges, and future prospects of the related solutions are discussed methodically. By addressing stability and scalability issues, these approaches can contribute significantly to reducing carbon emissions and promoting sustainable energy solutions.

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.

Spatial Patterns and Driving Factors of Urban Residential Embedded Carbon Emissions: An Empirical Study in Kaifeng, China

With the continuous improvement in living standards and great changes in lifestyles, more attention is being paid to the embedded carbon emissions produced by human consumption. With large sample data and high-resolution remote sensing images, we explored the spatial differentiation and influencing factors of household embedded carbon emissions within the city fine scale using the EIO-LCA model, spatial autocorrelation analysis and standard deviation ellipse, quantile regression, etc. The results indicate that the spatial dependence is more obvious than the characteristics of spatial heterogeneity;the high-value area of household embedded carbon emissions gathers in new development zones in cities that are expanding rapidly, mainly with residents in large number of newly-built commercial housing families and the relative’s courtyard of institutions. The factors of family characteristics, housing characteristics, lifestyles, and consumption concept have significant effects on the embedded carbon emissions of each person. The influencing intensity of most factors showed an increasing trend with increased carbon emissions. The study verified the impact of urban sprawl on residential carbon emissions and the applicability of the situated lifestyles theory in the construction of urban low-carbon communities in China.

Carbon Dioxide Emissions and Energy Self-Sufficiency of Woody Biomass Utilization for Residential Heating: A Case Study of Nishiwaga, Japan

Renewable energy sources, including bioenergy, are presently attracting considerable attention as possible substitutes for fossil fuels. Among the various sources of bioenergy, biomass can arguably play a significant role in the reduction of greenhouse gases and the provision of a stable energy supply. However, the use of fossil fuels continues in the production of bioenergy. Consequently, the overall extent to which biomass utilization for energy can reduce carbon dioxide emissions as a substitute for fossil fuels and whether this can improve the energy self-sufficiency rate remains largely unknown. This study responds to these questions using a case of a Japanese rural community using firewood for residential heating. The results showed that woody biomass utilization for energy is able to both reduce the dependence on fossil fuels and mitigate climate change. These findings offer new insights into the development of sustainability in rural communities.

Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Carbon Emission Effects Driven by Evolution of Chinese Dietary Structure from 1987 to 2020

Exploring carbon emission effects based on the evolution of residents’ dietary structure to achieve the carbon neutrality goal and mitigate climate change is an important task.This study took China as the research object(data excluding Hong Kong,Macao and Taiwan) and used the carbon emission coefficient method to quantitatively measure the food carbon emissions from 1987–2020,then analyzed the carbon emission effects under the evolution of dietary structure.The results showed that during the study period,the Chinese dietary structure gradually changed to a high-carbon consumption pattern.The dietary structure of urban residents developed to a balanced one,while that of rural residents developed to a high-quality one.During the study period,the per capita food carbon emissions and total food consumption of Chinese showed an increasing trend.The per capita food carbon emissions of residents in urban and rural showed an overall upward trend.The total food carbon emissions in urban increased significantly,while that in rural increased first and then decreased.The influence of beef and mutton on carbon emissions is the highest in dietary structure.Compared with the balanced dietary pattern,the food carbon emissions of Chinese residents had not yet reached the peak,but were evolving to a high-carbon consumption pattern.

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.