Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Si...Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions.We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration.Furthermore,we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation,and we used the Geographically and Temporally Weighted Regression(GTWR)model to analyze the influencing factors of carbon emissions at this scale.The results of this study are as follows:(1)from 2000 to 2019,the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease,with an average annual growth rate of 4.24%.However,in recent years,it has stabilized,and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration;(2)carbon emissions exhibited significant spatial clustering,with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration;(3)factors such as GDP,population(Pop),urbanization rate(Ur),and industrialization structure(Ic)all showed a significant influence on carbon emissions;(4)the spatial heterogeneity of each influencing factor was evident.展开更多
Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research probl...Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem.Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables.In this study,we propose a machine learning algorithm for carbon emissions,a Bayesian optimized XGboost regression model,using multi-year energy carbon emission data and nighttime lights(NTL)remote sensing data from Shaanxi Province,China.Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models,with an R^(2)of 0.906 and RMSE of 5.687.We observe an annual increase in carbon emissions,with high-emission counties primarily concentrated in northern and central Shaanxi Province,displaying a shift from discrete,sporadic points to contiguous,extended spatial distribution.Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns,with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering.Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissionsmore accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment.This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.展开更多
Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industr...Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industries.The global production of primary magnesium has reached approximately 1.2 million tons per year,with anticipated diversification in future applications and significant market demand.Nevertheless,approximately 80%of the world’s primary magnesium is still manufactured through the Pidgeon process,grappling with formidable issues including high energy consumption,massive carbon emission,significant resource depletion,and environmental pollution.The implementation of the relative vacuum method shows potential in breaking through technological challenges in the Pidgeon process,facilitating clean,low-carbon continuous magnesium smelting.This paper begins by introducing the principles of the relative vacuum method.Subsequently,it elucidates various innovative process routes,including relative vacuum ferrosilicon reduction,aluminum thermal reduction co-production of spinel,and aluminum thermal reduction co-production of calcium aluminate.Finally,and thermodynamic foundations of the relative vacuum,a quantitative analysis of the material,energy flows,carbon emission,and production cost for several new processes is conducted,comparing and analyzing them against the Pidgeon process.The study findings reveal that,with identical raw materials,the relative vacuum silicon thermal reduction process significantly decreases raw material consumption,energy consumption,and carbon dioxide emissions by 15.86%,30.89%,and 26.27%,respectively,compared to the Pidgeon process.The relative vacuum process,using magnesite as the raw material and aluminum as the reducing agent,has the lowest magnesium-to-feed ratio,at only 3.385.Additionally,its energy consumption and carbon dioxide emissions are the lowest,at 1.817 tce/t Mg and 7.782 t CO_(2)/t Mg,respectively.The energy consumption and carbon emissions of the relative vacuum magnesium smelting process co-producing calcium aluminate(12CaO·7Al_(2)O_(3),3CaO·Al_(2)O_(3),and CaO·Al_(2)O_(3))are highly correlated with the consumption of dolomite in the raw materials.When the reduction temperature is around 1473.15 K,the critical volume fraction of magnesium vapor for different processes varies within the range of 5%–40%.Production cost analysis shows that the relative vacuum primary magnesium smelting process has significant economic benefits.This paper offers essential data support and theoretical guidance for achieving energy efficiency,carbon reduction in magnesium smelting,and the industrial adoption of innovative processes.展开更多
Digital transformation,as a recent trend in socioeconomic development,is considered as a critical pathway for urban carbon reduction because of its potential to increase productivity and energy efficiency.However,few ...Digital transformation,as a recent trend in socioeconomic development,is considered as a critical pathway for urban carbon reduction because of its potential to increase productivity and energy efficiency.However,few studies have explored the relationship between urban digitalization and carbon emissions(CE).Therefore,this study systematically analyzed the spatiotemporal distribution and interaction mechanism between digitalization and CE in the Yangtze River Delta(YRD)urban agglomerations of China during 2006-2020 based on a multidimensional indicator system,including digitalization industry level,digitalization application level,and urban green digitalization willingness.The findings revealed that both digitalization and CE in the YRD exhibit a significant and synchronously evolving“core-periphery”spatial pattern.Core cities generated substantial positive spillover effect on periphery cities through technology diffusion and policy demonstration,advancing both regional digitalization and the collaborative governance of CE.However,digitalization had dual impact on CE.On the one hand,it promoted the reduction of CE by enhancing energy efficiency,optimizing industrial structures,and promoting the application of green technologies.On the other hand,the expansion of digital infrastructure introduced a potential risk of increased energy consumption.Therefore,targeted policy recommendations are proposed to facilitate the coordination of environmental sustainability and digitalization in the YRD.This study provides empirical support and policy insights for advancing the coordinated development of regional digital transformation and green low-carbon initiatives.展开更多
Sewage sludge in cities of Yangzi River Belt,China,generally exhibits a lower organic content and higher silt contentdue to leakage of drainage system,which caused low bioenergy recovery and carbon emission benefits i...Sewage sludge in cities of Yangzi River Belt,China,generally exhibits a lower organic content and higher silt contentdue to leakage of drainage system,which caused low bioenergy recovery and carbon emission benefits in conventional anaerobic digestion(CAD).Therefore,this paper is on a pilot scale,a bio-thermophilic pretreatment anaerobic digestion(BTPAD)for low organic sludge(volatile solids(VS)of 4%)was operated with a long-term continuous flow of 200 days.The VS degradation rate and CH_(4) yield of BTPAD increased by 19.93%and 53.33%,respectively,compared to those of CAD.The analysis of organic compositions in sludge revealed that BTPAD mainly improved the hydrolysis of proteins in sludge.Further analysis of microbial community proportions by high-throughput sequencing revealed that the short-term bio-thermophilic pretreatment was enriched in Clostridiales,Coprothermobacter and Gelria,was capable of hydrolyzing acidified proteins,and provided more volatile fatty acid(VFA)for the subsequent reaction.Biome combined with fluorescence quantitative polymerase chain reaction(PCR)analysis showed that the number of bacteria with high methanogenic capacity in BTPAD was much higher than that in CAD during the medium temperature digestion stage,indicating that short-term bio-thermophilic pretreatment could provide better methanogenic conditions for BTPAD.Furthermore,the greenhouse gas emission footprint analysis showed that short-term bio-thermophilic pretreatment could reduce the carbon emission of sludge anaerobic digestion system by 19.18%.展开更多
With the rapid development of aviation industry and its increasing impact on the global climate change,the contributions of carbon emissions frominternational flights are attracting more and more attention worldwide.T...With the rapid development of aviation industry and its increasing impact on the global climate change,the contributions of carbon emissions frominternational flights are attracting more and more attention worldwide.This study,taking Macao as the aviation hub,established the cross-border aviation carbon emission evaluation model to explore dynamic carbon emissions and net-zero path of international flights.The aviation hubmainly covers 58 routes and five types of civil aircraft from 12 countries or regions during 2000-2022.The results show that the aviation transportation in Macao emitted about 1.44 million tons CO_(2)eq in 2019,which is high 3.6 times that of 2000.The COVID-19 has led to a rapid decline in aviation carbon emissions in a short period of time,carbon emissions in 2020 decreased by 80%compared to 2019.In terms of cumulative carbon emissions from 2000 to 2019,the A321 and A320 Airbus contribute to 80%of carbon emissions.And the Chinese mainland(37%)and Taiwan(29%)are the main sources of emissions.In 2000-2019,the proportion of carbon emissions from China(including Taiwan and Hong Kong)decrease from 91%to 53%,while the contribution from Southeast Asia(from 5% to 26%),Japan and South Korea(from 2% to 19%)keep the growth trends.In the optimal scenario(B3C3),net zero emissions of cross-border aviation in Macao can be not achieved,and there is still only by removing 0.3 million tons CO_(2)eq.Emission reduction technology and new energy usage are priorities for the aviation emission reduction.展开更多
In the digital era,the development of the digital economy has gained significant practical importance for enhancing reductions in carbon dioxide(CO_(2))emissions.However,existing studies must clarify the key“hidden”...In the digital era,the development of the digital economy has gained significant practical importance for enhancing reductions in carbon dioxide(CO_(2))emissions.However,existing studies must clarify the key“hidden”mechanisms driving actual changes in CO_(2)emissions.Although both the digital economy and CO_(2)emissions are widely researched topics,previous literature has rarely provided an explicit examination of their underlying mechanisms.This study conducts a detailed literature review and finds that the digital economy affects CO_(2)emissions through four main channels:technical,structural,resource allocation,and spatial spillover.However,these channels should not be examined independently due to their interactive effects.Moreover,each of these four channels can be further subdivided,making it essential to explore the subpaths and interconnections among them.By offering a more nuanced understanding of how the digital economy contributes to CO_(2)emissions reduction,this study provides valuable insights that can inform strategic policy development.展开更多
Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing...Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.展开更多
Although currently,a large part of the existing buildings is considered inefficient in terms of energy,the ability to save energy consumption up to 80%has been proven in residential and commercial buildings.Also,carbo...Although currently,a large part of the existing buildings is considered inefficient in terms of energy,the ability to save energy consumption up to 80%has been proven in residential and commercial buildings.Also,carbon dioxide is one of the most important greenhouse gases contributing to climate change and is responsible for 60%of global warming.The facade of the building,as the main intermediary between the interior and exterior spaces,plays a significant role in adjusting the weather conditions and providing thermal comfort to the residents.In this research,715 different scenarios were defined with the combination of various types of construction materials,and the effect of each of these scenarios on the process of energy loss from the surface of the external walls of the building during the operation period was determined.In the end,these scenarios were compared during a one-year operation period,and the amount of energy consumption in each of these scenarios was calculated.Also,bymeasuring the amount of carbon emissions in buildings during the operation period and before that,let’s look at practical methods to reduce the effects of the construction industry on the environment.By comparing the research findings,it can be seen that the ranking of each scenario in terms of total energy consumption is not necessarily the same as the ranking of energy consumption for gas consumption or electricity consumption for the same scenario.That is,choosing the optimal scenario depends on the type of energy consumed in the building.Finally,we determined the scenarios with the lowest and highest amounts of embodied and operational carbon.In the end,we obtained the latent carbon compensation period for each scenario.This article can help designers and construction engineers optimize the energy consumption of buildings by deciding on the right materials.展开更多
Metallurgical slag is a waste or by-product of the metallurgical process,and its improper disposal can pose negative environmental impacts,including groundwater and soil contamination.The composition and properties of...Metallurgical slag is a waste or by-product of the metallurgical process,and its improper disposal can pose negative environmental impacts,including groundwater and soil contamination.The composition and properties of metallurgical slag are complex,which is usually difficult to use or process directly and requires special treatment and utilization methods.Taking converter slag and blast furnace slag as examples,the research frontiers and development potential were primarily discussed and analyzed in three aspects:the recycling within and outside metallurgical slag plants,the extraction and utilization of thermal energy from metallurgical slag,and the functionalization and social application of metallurgical slag.The metallurgical slag waste heat recovery includes chemical methods and physical methods.Among them,the physical method currently most used was centrifugal granulation to recover heat.Chemical laws could recover hydrogen through the waste heat of metallurgical slag,which could save fuel and reduce CO_(2) generated by fuel combustion.Metallurgical slag is rich in alkaline metal oxides,which can undergo a carbonation reaction with CO_(2) to achieve carbon sequestration in metallurgical slag.Elements such as iron,phosphorus,and silicon contained in metallurgical slag could be used in soil conditioners,cement raw materials,and wastewater treatment.For example,the phosphorus element in the slag could be extracted by melt modification followed by acid leaching and used as a raw material for phosphate fertilizer.Therefore,under the background of China’s carbon neutrality goal,it is important to develop the key technologies of waste heat utilization of metallurgical slag and carbon sequestration of metallurgical slag.展开更多
The transition of the Chinese iron and steel industry to ultralow emissions has accelerated the development of denitrification technologies.Considering the existing dual carbon targets,carbon emissions must be conside...The transition of the Chinese iron and steel industry to ultralow emissions has accelerated the development of denitrification technologies.Considering the existing dual carbon targets,carbon emissions must be considered as a critical indicator when comparing denitrification systems.Consequently,this study provided a comprehensive cost-benefit model for denitrification in the steel industry,encompassing additional carbon emissions resulting from the implementation of denitrification systems.Activated-carbon adsorption and selective catalytic reduction(SCR)systems are two efficient techniques for controlling NOx emissions during sintering.Based on thismodel,a cost-benefit analysis of these two typical systems was conducted,and the results indicated that the unit flue-gas abatement costs of SCR and activated-carbon adsorption systems were 0.00275 and 0.0126 CNY/m^(3),and the unit flue-gas abatement benefits were 0.0072 and 0.0179 CNY/m^(3),respectively.Additionally,the effect of operational characteristics on operating costs,including duration and material prices,was analyzed.When treating the flue gas,the two systems released 0.0020 and 0.0060 kg/m^(3) of carbon dioxide,respectively.The primary sources of carbon emissions from the SCR and activated-carbon adsorption systems are the production of reducing agents and system operations,respectively.Furthermore,considering the features of the activated carbon adsorption system for simultaneous desulfurization,a SCR-wet flue gas desulfurization(WFGD)technology route was developed for comparison with the activated carbon adsorption system.展开更多
Against the backdrop of regional coordinated development and China’s“dual carbon”strategic objectives,the Beijing-Tianjin-Hebei(BTH)region faces an urgent need to transition fromits traditional economic growth mode...Against the backdrop of regional coordinated development and China’s“dual carbon”strategic objectives,the Beijing-Tianjin-Hebei(BTH)region faces an urgent need to transition fromits traditional economic growth model,which is heavily reliant on resource consumption.This study investigates the decoupling dynamics among economic growth,energy consumption,and carbon emissions in the BTH region,along with the underlying driving forces,aiming to provide valuable insights for achieving the“dual carbon”targets and fostering high-quality regional development.First,the Tapio decoupling model is employed to analyze the decoupling relationships between economic growth,energy consumption,and carbon emissions in the BTH region from 2000 to 2021.Second,the Logarithmic Mean Divisia Index decomposition method is applied to identify the key driving factors of carbon emission reduction and quantify their respective contributions.Finally,targeted policy recommendations are proposed based on the empirical findings to support regional coordinated development.The results indicate that(1)all three sub-regions within the BTH region have demonstrated consistent improvements in energy utilization efficiency and a gradual decline in carbon emission intensity,although the degree of progress varies across regions;(2)differentiated decoupling states exist between carbon emissions and both economic growth and energy consumption,with Beijing showing significant decoupling,while Tianjin and Hebei Province experience a“rebound”phenomenon following a phase of decoupling;(3)energy consumption intensity and industrial structure optimization have notably positive effects on carbon emission reduction,whereas other factors contribute to varying degrees to the exacerbation of carbon emissions;(4)the impacts of driving factors on carbon emissions exhibit significant spatio-temporal disparities.Based on these findings,the study recommends enhancing fiscal incentives,optimizing industrial structures,improving energy efficiency,and establishing a coordinated regional governance framework to facilitate the BTH region’s low-carbon transition and sustainable development.展开更多
Under the background of resource shortage and global warming,it is of great significance to explore the status,influencing factors and carbon emission reduction effect of waste recycling in China after the implementat...Under the background of resource shortage and global warming,it is of great significance to explore the status,influencing factors and carbon emission reduction effect of waste recycling in China after the implementation of new waste classification policy for guiding waste classification and carbon emission accounting.In this research,the temporal and spatial changes and influencing factors of waste recycling were studied from subdistrict level,life-cycle carbon emission reduction was predicted and policy suggestions for waste recycling were proposed.The results showed that after the implementation of new waste classification policy,the amount of recycled waste and the proportion of low-value recycled waste increased by 420.93 t and 2.29%per month on average,respectively.The district center has the largest amount of recycled waste.Income was the main factors affecting waste recycling,and online shopping and takeout could become important sources of recyclable waste.Accounting cradle-to-grave life cycle carbon footprint,waste plastics takes up the most contribution,accounting for 39.11%,and nearly 391.68 Mt CO_(2eq) would be reduced by waste recycling in China by 2030.Therefore,in the process of waste classification,refining waste classification to increase the amount of low-value recyclables,and rationally deploying collection and transportation vehicles to ensure efficient waste recycling are of great significance to achieve the goal of“carbon peaking and carbon neutrality”.展开更多
This study explores the externalities caused by managerial myopia from the perspective of carbon emissions in urban areas.Using panel data from 194 Chinese cities and 1286 listed companies from 2012 to 2021,this study...This study explores the externalities caused by managerial myopia from the perspective of carbon emissions in urban areas.Using panel data from 194 Chinese cities and 1286 listed companies from 2012 to 2021,this study empirically examines the effect of managerial myopia on urban carbon emissions.We integrate the“1+N”policy framework under China’s dual-carbon goals of peaking emssions by 2030 and achieving carbon neutrality by 2060,and propose a dual governance framework.The results show that managerial shortsightedness significantly contributes to urban carbon emissions,and this effect is particularly pronounced in cities with higher levels of carbon emissions and in first-and second-tier central cities.The mediating effect analysis indicate that managerial shortsightedness increases urban carbon emissions by inhibiting corporate green technological innovation.The moderating effect analysis shows that public media attention and government environmental regulation effectively mitigate the adverse impact of managerial myopia on urban carbon emissions.Theoretically,this study reveals the mechanism by which managerial shortsightedness increases urban carbon emissions by inhibiting green technology innovation and emphasizes the key roles of public media attention and government environmental regulation in mitigating this negative effect.This study provides important implications for policy rationale,especially for developing countries,for promoting green innovation and strengthening environmental governance to reduce carbon emissions.展开更多
Wiping out poverty while controlling carbon emissions is a major challenge of our time.China eradicated extreme poverty in 2020 through the targeted poverty alleviation(TPA)strategy,providing a unique case to examine ...Wiping out poverty while controlling carbon emissions is a major challenge of our time.China eradicated extreme poverty in 2020 through the targeted poverty alleviation(TPA)strategy,providing a unique case to examine the poverty-carbon nexus at the subnational level.This paper investigates the nexus between county-level poverty reduction and carbon emissions in Hubei province during the TPA period.Our findings support the win-win hypothesis,indicating that poverty reduction and emissions control can be achieved simultaneously.CO_(2)sequestration through vegetation emerged as a key factor benefiting both objectives,with a 1% increase reducing poverty by 0.42% and lowering carbon emissions by 0.19%.Economic growth contributed to poverty alleviation but increased emissions:a 1% rise in GDP reduced poverty by 0.44% while raising emissions by 0.70%.Conversely,a 1% increase in electricity consumption raised poverty by 0.46% and lowered emissions by 0.12%.Agricultural development showed a 1%increase correlated with 0.52% higher poverty and 0.17% higher emissions.“Carbon Sink+”trading mechanisms facilitated ecological poverty alleviation in impoverished areas.Panel causality analysis confirms a bidirectional relationship between poverty reduction and carbon emissions.These findings highlight the potential for integrated strategies that advance both poverty alleviation and emissions reduction while considering the complex socioeconomic dynamics necessary to achieve sustainable development goals.展开更多
Taking 18 large-scale urban agglomerations(UAs)in China as the research objects,this study analyzes the characteristics of the spatiotemporal patterns of carbon emissions in UA areas in China and their impact mechanis...Taking 18 large-scale urban agglomerations(UAs)in China as the research objects,this study analyzes the characteristics of the spatiotemporal patterns of carbon emissions in UA areas in China and their impact mechanisms by citing Moran’s I and geographically weighted regression(GWR).The research findings are as follows:1)obvious differences are found in carbon emissions among different UAs.The cities with higher absolute carbon emissions are mainly distributed in the major cities of the Hohhot-Baotou-Ordos-Yulin UA.2)From 2011 to 2021,the carbon emission levels of China’s UAs grew obviously,but the spatial differences are pronounced,among which the Hohhot-Baotou-Ordos-Yulin UA and others had the highest growth rates.The carbon emission patterns of UAs also present obvious spatial clustering characteristics.The regions with the most obvious growth rates of carbon emissions at the urban scale are mainly distributed in the Hohhot-Baotou-Ordos-Yulin UA and Mid-Yangtze River UA.3)The value of secondary industry(X_(vsi)),number of urban enterprises(X_(nue)),public library holdings(X_(plh)),and urban passenger volume(X_(upv))have an obvious effect on carbon emissions.However,the regression cofficients exhibit obvious spatial variation.Among them,X_(vsi) has an obvious positive effect on carbon emissions,indicating that spatial agglomeration of the real economy substantially increases reginal carbon emission levels.The high X_(nue)regression coefficients are mainly distributed in Harbin-Changchun UA,indicating that the growth of enterprises in this region is still dominated by traditional high-carbon-emission enterprises,the urgent task of low-carbon transformation and upgrading for traditional industries in old industrial regions.The regression coefficients of X_(plh)and X_(upv) are generally negative,suggesting that improving public service facilities and strengthening regional transportation links can help to reduce the level of carbon emissions.展开更多
To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hyd...To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hydrogen integrated energy system(EHH-IES)optimal scheduling model considering carbon emission stream(CES)and wind-solar accommodation.First,the CES theory is introduced to quantify the carbon emission intensity of each energy conversion device and transmission branch by defining carbon emission rate,branch carbon intensity,and node carbon potential,realizing accurate tracking of carbon flow in the process of multi-energy coupling.Second,a stepped carbon pricing mechanism is established to dynamically adjust carbon trading costs based on the deviation between actual carbon emissions and initial quotas,strengthening the emission reduction incentive.Finally,a lowcarbon economic dispatch model is constructed with the objectives of minimizing operation cost,carbon trading cost,wind-solar curtailment penalty cost,and energy loss.Simulation results show that compared with the traditional economic dispatch scheme 3,the proposed schemel reduces carbon emissions by 53.97%and wind-solar curtailment by 68.89%with a 16.10%increase in total cost.This verifies that the model can effectively improve clean energy utilization and reduce carbon emissions,achieving low-carbon economic operation of EHH-IES,with CES theory ensuring precise carbon flow tracking across multi-energy links.展开更多
Accurate prediction of manufacturing carbon emissions is of great significance for subsequent low-carbon optimization.To improve the accuracy of carbon emission prediction with insufficient hobbing data,combining the ...Accurate prediction of manufacturing carbon emissions is of great significance for subsequent low-carbon optimization.To improve the accuracy of carbon emission prediction with insufficient hobbing data,combining the advantages of improved algorithm and supplementary data,a method of carbon emission prediction of hobbing based on cross-process data fusion was proposed.Firstly,we analyzed the similarity of machining process and manufacturing characteristics and selected milling data as the fusion material for hobbing data.Then,the adversarial learning was used to reduce the difference between data from the two processes,so as to realize the data fusion at the characteristic level.After that,based on Meta-Transfer Learning method,the carbon emission prediction model of hobbing was established.The effectiveness and superiority of the proposed method were verified by case analysis and comparison.The prediction accuracy of the proposed method is better than other methods across different data sizes.展开更多
Exploring the effective and efficient path of agricultural carbon emission reduction in Henan Province is of great significance to optimizing the strategic layout of China's agricultural emission reduction and car...Exploring the effective and efficient path of agricultural carbon emission reduction in Henan Province is of great significance to optimizing the strategic layout of China's agricultural emission reduction and carbon sequestration.Accordingly,the agricultural carbon emissions of each county were measured scientifically and then the spatial measurement model was utilized to clarify the spatial and temporal evolution trend and spatial effect mechanism of agricultural carbon emissions based on the county data of Henan Province from 2010 to 2020.The results showed that:(1)in 2020,the total agricultural carbon emissions were 134.7274 million tons,with the high distribution in the southeast and low distribution in the northwest;(2)the spatial dependence of agricultural carbon emissions showed a four-stage trend of fluctuating down-continuing up-plummeting-fluctuating up again,and the spatial heterogeneity was dominated by low-low agglomeration,followed by high-low agglomeration;(3)there was an inverted U curve relationship between the level of agricultural economic development and agricultural carbon emissions.The increase in the level of agricultural mechanization and urbanization rate significantly reduced agricultural carbon emissions.The opposite was true for the financial support for agriculture,the income level of rural residents and the structure of the agricultural industry;(4)in terms of spatial spillover effects,the increase in the level of agricultural development in neighbor counties first increased and then decreased agricultural carbon emissions in Henan Province.The mechanization level and urbanization rate of neighbor counties reduced agricultural carbon emissions in Henan Province,and the opposite was true for the income level of rural residents and the scale utilization of agricultural land.展开更多
China is currently the largest emitter of carbon dioxide globally.The nation,vulnerable to the imminent challenges of climate change and greenhouse gas emissions,is determined to reduce emissions.Thus,by adopting a sy...China is currently the largest emitter of carbon dioxide globally.The nation,vulnerable to the imminent challenges of climate change and greenhouse gas emissions,is determined to reduce emissions.Thus,by adopting a systemstheory approach,this study is aimed at examining how the agricultural lands,output values,production activities,and populations,as well as the economic factors,influence carbon emissions in Sichuan Province.To offer insights into the long-term agricultural carbon emission(ACE)trajectories,a system dynamics model is used to predict the emission trends from 2023 to 2040.The findings indicate the following:①policy regulation exerts influence on the ACE in the province.As per the simulation results,regulating the gross domestic product growth of the primary industry at 2.5%,5%,and 10%will only increase the carbon emissions by 0.24%,0.25%,and 0.53%,respectively,by 2040,indicating that effective policy regulations can decouple economic growth from substantial increases in emissions,thereby underscoring their pivotal role in emission control.②Regulating the agricultural-economy growth rate and policies can effectively reduce ACEs in the province.③While single policies exert limited influence,combining multiple measures significantly boosts carbon reduction.For example,comprehensive strategies,including reduced pesticide use and marginal farmland conversion,can lower agricultural land carbon emissions by 3.48%,5.30%,and 7.47%(by 2035)and 1.67%,2.76%,and 3.65%(by 2040).Overall,these results emphasize the effectiveness of coordinated policies,alongside market control and land-use adjustments,in advancing low-carbon agricultural development.展开更多
基金supported by the Humanities and Social Sciences Project of the Ministry of Education of the Peoples Republic(No.21YJCZH099)the National Natural Science Foundation of China(Nos.41401089 and 41741014)the Science and Technology Project of Sichuan Province(No.2023NSFSC1979).
文摘Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions.We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration.Furthermore,we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation,and we used the Geographically and Temporally Weighted Regression(GTWR)model to analyze the influencing factors of carbon emissions at this scale.The results of this study are as follows:(1)from 2000 to 2019,the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease,with an average annual growth rate of 4.24%.However,in recent years,it has stabilized,and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration;(2)carbon emissions exhibited significant spatial clustering,with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration;(3)factors such as GDP,population(Pop),urbanization rate(Ur),and industrialization structure(Ic)all showed a significant influence on carbon emissions;(4)the spatial heterogeneity of each influencing factor was evident.
基金supported by the Key Research and Development Program in Shaanxi Province,China(No.2022ZDLSF07-05)the Fundamental Research Funds for the Central Universities,CHD(No.300102352901)。
文摘Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem.Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables.In this study,we propose a machine learning algorithm for carbon emissions,a Bayesian optimized XGboost regression model,using multi-year energy carbon emission data and nighttime lights(NTL)remote sensing data from Shaanxi Province,China.Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models,with an R^(2)of 0.906 and RMSE of 5.687.We observe an annual increase in carbon emissions,with high-emission counties primarily concentrated in northern and central Shaanxi Province,displaying a shift from discrete,sporadic points to contiguous,extended spatial distribution.Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns,with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering.Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissionsmore accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment.This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.
基金supported by the China Postdoctoral Science Foundation(No.2023T160088)the Youth Fund of the National Natural Science Foundation of China(No.52304324).
文摘Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industries.The global production of primary magnesium has reached approximately 1.2 million tons per year,with anticipated diversification in future applications and significant market demand.Nevertheless,approximately 80%of the world’s primary magnesium is still manufactured through the Pidgeon process,grappling with formidable issues including high energy consumption,massive carbon emission,significant resource depletion,and environmental pollution.The implementation of the relative vacuum method shows potential in breaking through technological challenges in the Pidgeon process,facilitating clean,low-carbon continuous magnesium smelting.This paper begins by introducing the principles of the relative vacuum method.Subsequently,it elucidates various innovative process routes,including relative vacuum ferrosilicon reduction,aluminum thermal reduction co-production of spinel,and aluminum thermal reduction co-production of calcium aluminate.Finally,and thermodynamic foundations of the relative vacuum,a quantitative analysis of the material,energy flows,carbon emission,and production cost for several new processes is conducted,comparing and analyzing them against the Pidgeon process.The study findings reveal that,with identical raw materials,the relative vacuum silicon thermal reduction process significantly decreases raw material consumption,energy consumption,and carbon dioxide emissions by 15.86%,30.89%,and 26.27%,respectively,compared to the Pidgeon process.The relative vacuum process,using magnesite as the raw material and aluminum as the reducing agent,has the lowest magnesium-to-feed ratio,at only 3.385.Additionally,its energy consumption and carbon dioxide emissions are the lowest,at 1.817 tce/t Mg and 7.782 t CO_(2)/t Mg,respectively.The energy consumption and carbon emissions of the relative vacuum magnesium smelting process co-producing calcium aluminate(12CaO·7Al_(2)O_(3),3CaO·Al_(2)O_(3),and CaO·Al_(2)O_(3))are highly correlated with the consumption of dolomite in the raw materials.When the reduction temperature is around 1473.15 K,the critical volume fraction of magnesium vapor for different processes varies within the range of 5%–40%.Production cost analysis shows that the relative vacuum primary magnesium smelting process has significant economic benefits.This paper offers essential data support and theoretical guidance for achieving energy efficiency,carbon reduction in magnesium smelting,and the industrial adoption of innovative processes.
文摘Digital transformation,as a recent trend in socioeconomic development,is considered as a critical pathway for urban carbon reduction because of its potential to increase productivity and energy efficiency.However,few studies have explored the relationship between urban digitalization and carbon emissions(CE).Therefore,this study systematically analyzed the spatiotemporal distribution and interaction mechanism between digitalization and CE in the Yangtze River Delta(YRD)urban agglomerations of China during 2006-2020 based on a multidimensional indicator system,including digitalization industry level,digitalization application level,and urban green digitalization willingness.The findings revealed that both digitalization and CE in the YRD exhibit a significant and synchronously evolving“core-periphery”spatial pattern.Core cities generated substantial positive spillover effect on periphery cities through technology diffusion and policy demonstration,advancing both regional digitalization and the collaborative governance of CE.However,digitalization had dual impact on CE.On the one hand,it promoted the reduction of CE by enhancing energy efficiency,optimizing industrial structures,and promoting the application of green technologies.On the other hand,the expansion of digital infrastructure introduced a potential risk of increased energy consumption.Therefore,targeted policy recommendations are proposed to facilitate the coordination of environmental sustainability and digitalization in the YRD.This study provides empirical support and policy insights for advancing the coordinated development of regional digital transformation and green low-carbon initiatives.
基金supported by the National Key Research and Development Project (Nos.2020YFC1908702 and 2021YFC3200700)the National Natural Science Foundation of China (Nos.52192684 and 52192680).
文摘Sewage sludge in cities of Yangzi River Belt,China,generally exhibits a lower organic content and higher silt contentdue to leakage of drainage system,which caused low bioenergy recovery and carbon emission benefits in conventional anaerobic digestion(CAD).Therefore,this paper is on a pilot scale,a bio-thermophilic pretreatment anaerobic digestion(BTPAD)for low organic sludge(volatile solids(VS)of 4%)was operated with a long-term continuous flow of 200 days.The VS degradation rate and CH_(4) yield of BTPAD increased by 19.93%and 53.33%,respectively,compared to those of CAD.The analysis of organic compositions in sludge revealed that BTPAD mainly improved the hydrolysis of proteins in sludge.Further analysis of microbial community proportions by high-throughput sequencing revealed that the short-term bio-thermophilic pretreatment was enriched in Clostridiales,Coprothermobacter and Gelria,was capable of hydrolyzing acidified proteins,and provided more volatile fatty acid(VFA)for the subsequent reaction.Biome combined with fluorescence quantitative polymerase chain reaction(PCR)analysis showed that the number of bacteria with high methanogenic capacity in BTPAD was much higher than that in CAD during the medium temperature digestion stage,indicating that short-term bio-thermophilic pretreatment could provide better methanogenic conditions for BTPAD.Furthermore,the greenhouse gas emission footprint analysis showed that short-term bio-thermophilic pretreatment could reduce the carbon emission of sludge anaerobic digestion system by 19.18%.
基金supported by the Science and Technology Development Fund,Macao SAR,China(Nos.0033/2022/AFJ and 0011/2023/AMJ)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515012017).
文摘With the rapid development of aviation industry and its increasing impact on the global climate change,the contributions of carbon emissions frominternational flights are attracting more and more attention worldwide.This study,taking Macao as the aviation hub,established the cross-border aviation carbon emission evaluation model to explore dynamic carbon emissions and net-zero path of international flights.The aviation hubmainly covers 58 routes and five types of civil aircraft from 12 countries or regions during 2000-2022.The results show that the aviation transportation in Macao emitted about 1.44 million tons CO_(2)eq in 2019,which is high 3.6 times that of 2000.The COVID-19 has led to a rapid decline in aviation carbon emissions in a short period of time,carbon emissions in 2020 decreased by 80%compared to 2019.In terms of cumulative carbon emissions from 2000 to 2019,the A321 and A320 Airbus contribute to 80%of carbon emissions.And the Chinese mainland(37%)and Taiwan(29%)are the main sources of emissions.In 2000-2019,the proportion of carbon emissions from China(including Taiwan and Hong Kong)decrease from 91%to 53%,while the contribution from Southeast Asia(from 5% to 26%),Japan and South Korea(from 2% to 19%)keep the growth trends.In the optimal scenario(B3C3),net zero emissions of cross-border aviation in Macao can be not achieved,and there is still only by removing 0.3 million tons CO_(2)eq.Emission reduction technology and new energy usage are priorities for the aviation emission reduction.
基金financial support from the National Natural Science Foundation of China[Grant No.72274159].
文摘In the digital era,the development of the digital economy has gained significant practical importance for enhancing reductions in carbon dioxide(CO_(2))emissions.However,existing studies must clarify the key“hidden”mechanisms driving actual changes in CO_(2)emissions.Although both the digital economy and CO_(2)emissions are widely researched topics,previous literature has rarely provided an explicit examination of their underlying mechanisms.This study conducts a detailed literature review and finds that the digital economy affects CO_(2)emissions through four main channels:technical,structural,resource allocation,and spatial spillover.However,these channels should not be examined independently due to their interactive effects.Moreover,each of these four channels can be further subdivided,making it essential to explore the subpaths and interconnections among them.By offering a more nuanced understanding of how the digital economy contributes to CO_(2)emissions reduction,this study provides valuable insights that can inform strategic policy development.
基金National Natural Science Foundation of China,No.42230106,No.42171250State Key Laboratory of Earth Surface Processes and Resource Ecology,No.2022-ZD-04。
文摘Agriculture holds a pivotal position in the economic fabric of every nation,yet concerns about agricultural carbon emission intensity(ACI)have become a major hurdle to achieving global economic sustainability.Focusing on 31 provincial-level regions in China,this study uses the Exploratory Spatio-temporal Data Analysis(ESTDA)and Panel Quantile Regression(PQR)model to analyze the spatio-temporal interaction characteristics and influencing factors of ACI in China from 2004 to 2023.The findings are as follows:(1)ACI showed an overall downward trend,and the spatial distribution pattern was characterized by“high in the western region and low along the southeastern coast”.Although the overall disparity tended to converge,some high-carbon-intensity regions exhibited extreme trends.ACI displayed clear spatial directionality,with the spatial center shifting steadily toward the northeast.(2)Regions in the northwest,northeast,and central-south parts exhibited strong local spatial structural dynamics,and the local spatial dependence of ACI in each region showed a nonlinear trend.Generally speaking,the spatial association pattern demonstrated a certain degree of inertia in spatial transfer,reflecting strong path dependence or spatial lock-in characteristics.(3)Optimization of industrial structure and improvement in agricultural mechanization will increase ACI,while economic development can effectively reduce it.The impact of urbanization on ACI exhibits a nonlinear pattern.The coordinated development of economic growth and urbanization significantly reduces ACI,with a stronger emission reduction observed in regions with low ACI.The optimization of industrial structure,when combined with urbanization and environmental regulation,contributes to significant emission reductions particularly in high-ACI areas.Similarly,the synergy between agricultural mechanization and urbanization effectively lowers emissions in low-ACI regions,though this effect diminishes in areas with higher ACI.
文摘Although currently,a large part of the existing buildings is considered inefficient in terms of energy,the ability to save energy consumption up to 80%has been proven in residential and commercial buildings.Also,carbon dioxide is one of the most important greenhouse gases contributing to climate change and is responsible for 60%of global warming.The facade of the building,as the main intermediary between the interior and exterior spaces,plays a significant role in adjusting the weather conditions and providing thermal comfort to the residents.In this research,715 different scenarios were defined with the combination of various types of construction materials,and the effect of each of these scenarios on the process of energy loss from the surface of the external walls of the building during the operation period was determined.In the end,these scenarios were compared during a one-year operation period,and the amount of energy consumption in each of these scenarios was calculated.Also,bymeasuring the amount of carbon emissions in buildings during the operation period and before that,let’s look at practical methods to reduce the effects of the construction industry on the environment.By comparing the research findings,it can be seen that the ranking of each scenario in terms of total energy consumption is not necessarily the same as the ranking of energy consumption for gas consumption or electricity consumption for the same scenario.That is,choosing the optimal scenario depends on the type of energy consumed in the building.Finally,we determined the scenarios with the lowest and highest amounts of embodied and operational carbon.In the end,we obtained the latent carbon compensation period for each scenario.This article can help designers and construction engineers optimize the energy consumption of buildings by deciding on the right materials.
基金supported by the following funds:Guizhou Science and Technology Support Program Project[Grant No.Guizhou Science and Technology Cooperation Support(2025)General 079]Guizhou Provincial Department of Education’s"Top 100 Schools and Thousand Enterprises in Science andTechnology Research and Development"Project in 2025(Contract Number:Guizhou Education and Technology[2025]No.009)+6 种基金Hebei Province Innovation Ability Improvement Plan(No.23561001D)Hebei Provincial Natural Science Foundation(No.H2022209089)Open Fund Project of the Key Laboratory for Ferrous Metallurgy and Resources Utilization of Ministry of Education(Grant No.FMRUlab23-03)the National Natural Science Foundation of China(No.52074128)Basic Scientific Research Business Expenses of Colleges and Universities in Hebei Province(Nos.JYG2022001 and JQN2023008)Tangshan Talent Funding Project(No.A202202007),Natural Science Foundation of Hebei Province(No.E2023209107)Foundation of Tangshan Science and Technology Bureau(No.23150219A).
文摘Metallurgical slag is a waste or by-product of the metallurgical process,and its improper disposal can pose negative environmental impacts,including groundwater and soil contamination.The composition and properties of metallurgical slag are complex,which is usually difficult to use or process directly and requires special treatment and utilization methods.Taking converter slag and blast furnace slag as examples,the research frontiers and development potential were primarily discussed and analyzed in three aspects:the recycling within and outside metallurgical slag plants,the extraction and utilization of thermal energy from metallurgical slag,and the functionalization and social application of metallurgical slag.The metallurgical slag waste heat recovery includes chemical methods and physical methods.Among them,the physical method currently most used was centrifugal granulation to recover heat.Chemical laws could recover hydrogen through the waste heat of metallurgical slag,which could save fuel and reduce CO_(2) generated by fuel combustion.Metallurgical slag is rich in alkaline metal oxides,which can undergo a carbonation reaction with CO_(2) to achieve carbon sequestration in metallurgical slag.Elements such as iron,phosphorus,and silicon contained in metallurgical slag could be used in soil conditioners,cement raw materials,and wastewater treatment.For example,the phosphorus element in the slag could be extracted by melt modification followed by acid leaching and used as a raw material for phosphate fertilizer.Therefore,under the background of China’s carbon neutrality goal,it is important to develop the key technologies of waste heat utilization of metallurgical slag and carbon sequestration of metallurgical slag.
基金supported by the National Key Research and Development Program of China(No.2022YFC3703403)Zhejiang Provincial“LeadWild Goose”Research and Development Project(No.2022C03073).
文摘The transition of the Chinese iron and steel industry to ultralow emissions has accelerated the development of denitrification technologies.Considering the existing dual carbon targets,carbon emissions must be considered as a critical indicator when comparing denitrification systems.Consequently,this study provided a comprehensive cost-benefit model for denitrification in the steel industry,encompassing additional carbon emissions resulting from the implementation of denitrification systems.Activated-carbon adsorption and selective catalytic reduction(SCR)systems are two efficient techniques for controlling NOx emissions during sintering.Based on thismodel,a cost-benefit analysis of these two typical systems was conducted,and the results indicated that the unit flue-gas abatement costs of SCR and activated-carbon adsorption systems were 0.00275 and 0.0126 CNY/m^(3),and the unit flue-gas abatement benefits were 0.0072 and 0.0179 CNY/m^(3),respectively.Additionally,the effect of operational characteristics on operating costs,including duration and material prices,was analyzed.When treating the flue gas,the two systems released 0.0020 and 0.0060 kg/m^(3) of carbon dioxide,respectively.The primary sources of carbon emissions from the SCR and activated-carbon adsorption systems are the production of reducing agents and system operations,respectively.Furthermore,considering the features of the activated carbon adsorption system for simultaneous desulfurization,a SCR-wet flue gas desulfurization(WFGD)technology route was developed for comparison with the activated carbon adsorption system.
基金funded by the Science and Technology Project of State Grid Corporation of China(No.52018F240002)the National Natural Science Foundation of China(72403087)the National Natural Science Foundation of China(72173043).
文摘Against the backdrop of regional coordinated development and China’s“dual carbon”strategic objectives,the Beijing-Tianjin-Hebei(BTH)region faces an urgent need to transition fromits traditional economic growth model,which is heavily reliant on resource consumption.This study investigates the decoupling dynamics among economic growth,energy consumption,and carbon emissions in the BTH region,along with the underlying driving forces,aiming to provide valuable insights for achieving the“dual carbon”targets and fostering high-quality regional development.First,the Tapio decoupling model is employed to analyze the decoupling relationships between economic growth,energy consumption,and carbon emissions in the BTH region from 2000 to 2021.Second,the Logarithmic Mean Divisia Index decomposition method is applied to identify the key driving factors of carbon emission reduction and quantify their respective contributions.Finally,targeted policy recommendations are proposed based on the empirical findings to support regional coordinated development.The results indicate that(1)all three sub-regions within the BTH region have demonstrated consistent improvements in energy utilization efficiency and a gradual decline in carbon emission intensity,although the degree of progress varies across regions;(2)differentiated decoupling states exist between carbon emissions and both economic growth and energy consumption,with Beijing showing significant decoupling,while Tianjin and Hebei Province experience a“rebound”phenomenon following a phase of decoupling;(3)energy consumption intensity and industrial structure optimization have notably positive effects on carbon emission reduction,whereas other factors contribute to varying degrees to the exacerbation of carbon emissions;(4)the impacts of driving factors on carbon emissions exhibit significant spatio-temporal disparities.Based on these findings,the study recommends enhancing fiscal incentives,optimizing industrial structures,improving energy efficiency,and establishing a coordinated regional governance framework to facilitate the BTH region’s low-carbon transition and sustainable development.
基金supported by the Construction of Environmental Science and Engineering Discipline for the Goal of Carbon Peaking and Carbon Neutrality Funding comes from Beijing Forestry University(No.2022XKJS0207).
文摘Under the background of resource shortage and global warming,it is of great significance to explore the status,influencing factors and carbon emission reduction effect of waste recycling in China after the implementation of new waste classification policy for guiding waste classification and carbon emission accounting.In this research,the temporal and spatial changes and influencing factors of waste recycling were studied from subdistrict level,life-cycle carbon emission reduction was predicted and policy suggestions for waste recycling were proposed.The results showed that after the implementation of new waste classification policy,the amount of recycled waste and the proportion of low-value recycled waste increased by 420.93 t and 2.29%per month on average,respectively.The district center has the largest amount of recycled waste.Income was the main factors affecting waste recycling,and online shopping and takeout could become important sources of recyclable waste.Accounting cradle-to-grave life cycle carbon footprint,waste plastics takes up the most contribution,accounting for 39.11%,and nearly 391.68 Mt CO_(2eq) would be reduced by waste recycling in China by 2030.Therefore,in the process of waste classification,refining waste classification to increase the amount of low-value recyclables,and rationally deploying collection and transportation vehicles to ensure efficient waste recycling are of great significance to achieve the goal of“carbon peaking and carbon neutrality”.
基金supported by the Project of the Ministry of Education Humanities and Social Sciences Youth Fund[Grant No.24YJC 790245].
文摘This study explores the externalities caused by managerial myopia from the perspective of carbon emissions in urban areas.Using panel data from 194 Chinese cities and 1286 listed companies from 2012 to 2021,this study empirically examines the effect of managerial myopia on urban carbon emissions.We integrate the“1+N”policy framework under China’s dual-carbon goals of peaking emssions by 2030 and achieving carbon neutrality by 2060,and propose a dual governance framework.The results show that managerial shortsightedness significantly contributes to urban carbon emissions,and this effect is particularly pronounced in cities with higher levels of carbon emissions and in first-and second-tier central cities.The mediating effect analysis indicate that managerial shortsightedness increases urban carbon emissions by inhibiting corporate green technological innovation.The moderating effect analysis shows that public media attention and government environmental regulation effectively mitigate the adverse impact of managerial myopia on urban carbon emissions.Theoretically,this study reveals the mechanism by which managerial shortsightedness increases urban carbon emissions by inhibiting green technology innovation and emphasizes the key roles of public media attention and government environmental regulation in mitigating this negative effect.This study provides important implications for policy rationale,especially for developing countries,for promoting green innovation and strengthening environmental governance to reduce carbon emissions.
基金funded by the National Natural Science Foundation of China(Grant No.42230110)。
文摘Wiping out poverty while controlling carbon emissions is a major challenge of our time.China eradicated extreme poverty in 2020 through the targeted poverty alleviation(TPA)strategy,providing a unique case to examine the poverty-carbon nexus at the subnational level.This paper investigates the nexus between county-level poverty reduction and carbon emissions in Hubei province during the TPA period.Our findings support the win-win hypothesis,indicating that poverty reduction and emissions control can be achieved simultaneously.CO_(2)sequestration through vegetation emerged as a key factor benefiting both objectives,with a 1% increase reducing poverty by 0.42% and lowering carbon emissions by 0.19%.Economic growth contributed to poverty alleviation but increased emissions:a 1% rise in GDP reduced poverty by 0.44% while raising emissions by 0.70%.Conversely,a 1% increase in electricity consumption raised poverty by 0.46% and lowered emissions by 0.12%.Agricultural development showed a 1%increase correlated with 0.52% higher poverty and 0.17% higher emissions.“Carbon Sink+”trading mechanisms facilitated ecological poverty alleviation in impoverished areas.Panel causality analysis confirms a bidirectional relationship between poverty reduction and carbon emissions.These findings highlight the potential for integrated strategies that advance both poverty alleviation and emissions reduction while considering the complex socioeconomic dynamics necessary to achieve sustainable development goals.
基金Under the auspices of the National Social Science Foundation of China(No.23BJL133)。
文摘Taking 18 large-scale urban agglomerations(UAs)in China as the research objects,this study analyzes the characteristics of the spatiotemporal patterns of carbon emissions in UA areas in China and their impact mechanisms by citing Moran’s I and geographically weighted regression(GWR).The research findings are as follows:1)obvious differences are found in carbon emissions among different UAs.The cities with higher absolute carbon emissions are mainly distributed in the major cities of the Hohhot-Baotou-Ordos-Yulin UA.2)From 2011 to 2021,the carbon emission levels of China’s UAs grew obviously,but the spatial differences are pronounced,among which the Hohhot-Baotou-Ordos-Yulin UA and others had the highest growth rates.The carbon emission patterns of UAs also present obvious spatial clustering characteristics.The regions with the most obvious growth rates of carbon emissions at the urban scale are mainly distributed in the Hohhot-Baotou-Ordos-Yulin UA and Mid-Yangtze River UA.3)The value of secondary industry(X_(vsi)),number of urban enterprises(X_(nue)),public library holdings(X_(plh)),and urban passenger volume(X_(upv))have an obvious effect on carbon emissions.However,the regression cofficients exhibit obvious spatial variation.Among them,X_(vsi) has an obvious positive effect on carbon emissions,indicating that spatial agglomeration of the real economy substantially increases reginal carbon emission levels.The high X_(nue)regression coefficients are mainly distributed in Harbin-Changchun UA,indicating that the growth of enterprises in this region is still dominated by traditional high-carbon-emission enterprises,the urgent task of low-carbon transformation and upgrading for traditional industries in old industrial regions.The regression coefficients of X_(plh)and X_(upv) are generally negative,suggesting that improving public service facilities and strengthening regional transportation links can help to reduce the level of carbon emissions.
文摘To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hydrogen integrated energy system(EHH-IES)optimal scheduling model considering carbon emission stream(CES)and wind-solar accommodation.First,the CES theory is introduced to quantify the carbon emission intensity of each energy conversion device and transmission branch by defining carbon emission rate,branch carbon intensity,and node carbon potential,realizing accurate tracking of carbon flow in the process of multi-energy coupling.Second,a stepped carbon pricing mechanism is established to dynamically adjust carbon trading costs based on the deviation between actual carbon emissions and initial quotas,strengthening the emission reduction incentive.Finally,a lowcarbon economic dispatch model is constructed with the objectives of minimizing operation cost,carbon trading cost,wind-solar curtailment penalty cost,and energy loss.Simulation results show that compared with the traditional economic dispatch scheme 3,the proposed schemel reduces carbon emissions by 53.97%and wind-solar curtailment by 68.89%with a 16.10%increase in total cost.This verifies that the model can effectively improve clean energy utilization and reduce carbon emissions,achieving low-carbon economic operation of EHH-IES,with CES theory ensuring precise carbon flow tracking across multi-energy links.
基金Supported by National Natural Science Foundation of China(Grant No.52005062)Chongqing Municipal Natural Science Foundation of China(Grant No.CSTB2023NSCQ-MSX0390)。
文摘Accurate prediction of manufacturing carbon emissions is of great significance for subsequent low-carbon optimization.To improve the accuracy of carbon emission prediction with insufficient hobbing data,combining the advantages of improved algorithm and supplementary data,a method of carbon emission prediction of hobbing based on cross-process data fusion was proposed.Firstly,we analyzed the similarity of machining process and manufacturing characteristics and selected milling data as the fusion material for hobbing data.Then,the adversarial learning was used to reduce the difference between data from the two processes,so as to realize the data fusion at the characteristic level.After that,based on Meta-Transfer Learning method,the carbon emission prediction model of hobbing was established.The effectiveness and superiority of the proposed method were verified by case analysis and comparison.The prediction accuracy of the proposed method is better than other methods across different data sizes.
基金Supported by the Humanities and Social Sciences Planning Program of the Ministry of Education(23YJA790027)。
文摘Exploring the effective and efficient path of agricultural carbon emission reduction in Henan Province is of great significance to optimizing the strategic layout of China's agricultural emission reduction and carbon sequestration.Accordingly,the agricultural carbon emissions of each county were measured scientifically and then the spatial measurement model was utilized to clarify the spatial and temporal evolution trend and spatial effect mechanism of agricultural carbon emissions based on the county data of Henan Province from 2010 to 2020.The results showed that:(1)in 2020,the total agricultural carbon emissions were 134.7274 million tons,with the high distribution in the southeast and low distribution in the northwest;(2)the spatial dependence of agricultural carbon emissions showed a four-stage trend of fluctuating down-continuing up-plummeting-fluctuating up again,and the spatial heterogeneity was dominated by low-low agglomeration,followed by high-low agglomeration;(3)there was an inverted U curve relationship between the level of agricultural economic development and agricultural carbon emissions.The increase in the level of agricultural mechanization and urbanization rate significantly reduced agricultural carbon emissions.The opposite was true for the financial support for agriculture,the income level of rural residents and the structure of the agricultural industry;(4)in terms of spatial spillover effects,the increase in the level of agricultural development in neighbor counties first increased and then decreased agricultural carbon emissions in Henan Province.The mechanization level and urbanization rate of neighbor counties reduced agricultural carbon emissions in Henan Province,and the opposite was true for the income level of rural residents and the scale utilization of agricultural land.
文摘China is currently the largest emitter of carbon dioxide globally.The nation,vulnerable to the imminent challenges of climate change and greenhouse gas emissions,is determined to reduce emissions.Thus,by adopting a systemstheory approach,this study is aimed at examining how the agricultural lands,output values,production activities,and populations,as well as the economic factors,influence carbon emissions in Sichuan Province.To offer insights into the long-term agricultural carbon emission(ACE)trajectories,a system dynamics model is used to predict the emission trends from 2023 to 2040.The findings indicate the following:①policy regulation exerts influence on the ACE in the province.As per the simulation results,regulating the gross domestic product growth of the primary industry at 2.5%,5%,and 10%will only increase the carbon emissions by 0.24%,0.25%,and 0.53%,respectively,by 2040,indicating that effective policy regulations can decouple economic growth from substantial increases in emissions,thereby underscoring their pivotal role in emission control.②Regulating the agricultural-economy growth rate and policies can effectively reduce ACEs in the province.③While single policies exert limited influence,combining multiple measures significantly boosts carbon reduction.For example,comprehensive strategies,including reduced pesticide use and marginal farmland conversion,can lower agricultural land carbon emissions by 3.48%,5.30%,and 7.47%(by 2035)and 1.67%,2.76%,and 3.65%(by 2040).Overall,these results emphasize the effectiveness of coordinated policies,alongside market control and land-use adjustments,in advancing low-carbon agricultural development.
