Analysis of the environmental and economic performance of fishing vessels has received limited attention compared with other ship types despite their notable contribution to global greenhouse gas(GHG)emissions.This st...Analysis of the environmental and economic performance of fishing vessels has received limited attention compared with other ship types despite their notable contribution to global greenhouse gas(GHG)emissions.This study evaluates the carbon footprint(CF)and economic viability of a liquefied natural gas(LNG)-fueled fishing vessel,using real engine operation simulations to provide precise and dynamic evaluation of fuel consumption and GHG emissions.Operational profiles are obtained through the utilization of onboard monitoring systems,whereas engine performance is simulated using the 1D/0D AVL Boost^(TM)model.Life cycle assessment(LCA)is conducted to quantify the environmental impact,whereas life cycle cost assessment(LCCA)is performed to analyze the profitability of LNG as an alternative fuel.The potential impact of the future fuel price uncertainties is addressed using Monte Carlo simulations.The LCA findings indicate that LNG has the potential to reduce the CF of the vessel by 14%to 16%,in comparison to a diesel power system configuration that serves as the baseline scenario.The LCCA results further indicate that the total cost of an LNG-powered ship is lower by 9.5%-13.8%,depending on the share of LNG and pilot fuels.This finding highlights the potential of LNG to produce considerable environmental benefits while addressing economic challenges under diverse operational and fuel price conditions.展开更多
Accurate quantification of life-cycle greenhouse gas(GHG)footprints(GHG_(fp))for a crop cultivation system is urgently needed to address the conflict between food security and global warming mitigation.In this study,t...Accurate quantification of life-cycle greenhouse gas(GHG)footprints(GHG_(fp))for a crop cultivation system is urgently needed to address the conflict between food security and global warming mitigation.In this study,the hydrobiogeochemical model,CNMM-DNDC,was validated with in situ observations from maize-based cultivation systems at the sites of Yongji(YJ,China),Yanting(YT,China),and Madeya(MA,Kenya),subject to temperate,subtropical,and tropical climates,respectively,and updated to enable life-cycle GHG_(fp)estimation.The model validation provided satisfactory simulations on multiple soil variables,crop growth,and emissions of GHGs and reactive nitrogen gases.The locally conventional management practices resulted in GHG_(fp)values of 0.35(0.09–0.53 at the 95%confidence interval),0.21(0.01–0.73),0.46(0.27–0.60),and 0.54(0.21–0.77)kg CO_(2)e kg~(-1)d.m.(d.m.for dry matter in short)for maize–wheat rotation at YJ and YT,and for maize–maize and maize–Tephrosia rotations at MA,respectively.YT's smallest GHG_(fp)was attributed to its lower off-farm GHG emissions than YJ,though the soil organic carbon(SOC)storage and maize yield were slightly lower than those of YJ.MA's highest SOC loss and low yield in shifting cultivation for maize–Tephrosia rotation contributed to its highest GHG_(fp).Management practices of maize cultivation at these sites could be optimized by combination of synthetic and organic fertilizer(s)while incorporating 50%–100%crop residues.Further evaluation of the updated CNMM-DNDC is needed for different crops at site and regional scales to confirm its worldwide applicability in quantifying GHG_(fp)and optimizing management practices for achieving multiple sustainability goals.展开更多
China is the most important steel producer in the world,and its steel industry is one of themost carbon-intensive industries in China.Consequently,research on carbon emissions from the steel industry is crucial for Ch...China is the most important steel producer in the world,and its steel industry is one of themost carbon-intensive industries in China.Consequently,research on carbon emissions from the steel industry is crucial for China to achieve carbon neutrality and meet its sustainable global development goals.We constructed a carbon dioxide(CO_(2))emission model for China’s iron and steel industry froma life cycle perspective,conducted an empirical analysis based on data from2019,and calculated the CO_(2)emissions of the industry throughout its life cycle.Key emission reduction factors were identified using sensitivity analysis.The results demonstrated that the CO_(2)emission intensity of the steel industry was 2.33 ton CO_(2)/ton,and the production and manufacturing stages were the main sources of CO_(2)emissions,accounting for 89.84%of the total steel life-cycle emissions.Notably,fossil fuel combustion had the highest sensitivity to steel CO_(2)emissions,with a sensitivity coefficient of 0.68,reducing the amount of fossil fuel combustion by 20%and carbon emissions by 13.60%.The sensitivities of power structure optimization and scrap consumption were similar,while that of the transportation structure adjustment was the lowest,with a sensitivity coefficient of less than 0.1.Given the current strategic goals of peak carbon and carbon neutrality,it is in the best interest of the Chinese government to actively promote energy-saving and low-carbon technologies,increase the ratio of scrap steel to steelmaking,and build a new power system.展开更多
Agricultural practices significantly contribute to greenhouse gas(GHG)emissions,necessitating cleaner production technologies to reduce environmental pressure and achieve sustainable maize production.Plastic film mulc...Agricultural practices significantly contribute to greenhouse gas(GHG)emissions,necessitating cleaner production technologies to reduce environmental pressure and achieve sustainable maize production.Plastic film mulching is commonly used in the Loess Plateau region.Incorporating slow-release fertilizers as a replacement for urea within this practice can reduce nitrogen losses and enhance crop productivity.Combining these techniques represents a novel agricultural approach in semi-arid areas.However,the impact of this integration on soil carbon storage(SOCS),carbon footprint(CF),and economic benefits has received limited research attention.Therefore,we conducted an eight-year study(2015-2022)in the semi-arid northwestern region to quantify the effects of four treatments[urea supplied without plastic film mulching(CK-U),slow-release fertilizer supplied without plastic film mulching(CK-S),urea supplied with plastic film mulching(PM-U),and slow-release fertilizer supplied with plastic film mulching(PM-S)]on soil fertility,economic and environmental benefits.The results revealed that nitrogen fertilizer was the primary contributor to total GHG emissions(≥71.97%).Compared to other treatments,PM-S increased average grain yield by 12.01%-37.89%,water use efficiency by 9.19%-23.33%,nitrogen accumulation by 27.07%-66.19%,and net return by 6.21%-29.57%.Furthermore,PM-S decreased CF by 12.87%-44.31%and CF per net return by 14.25%-41.16%.After eight years,PM-S increased SOCS(0-40 cm)by 2.46%,while PM-U decreased it by 7.09%.These findings highlight the positive effects of PM-S on surface soil fertility,economic gains,and environmental benefits in spring maize production on the Loess Plateau,underscoring its potential for widespread adoption and application.展开更多
To make agricultural systems sustainable in terms of their greenness and efficiency,optimizing the tillage and fertilization practices is essential.To assess the effects of tilling and fertilization practices in wheat...To make agricultural systems sustainable in terms of their greenness and efficiency,optimizing the tillage and fertilization practices is essential.To assess the effects of tilling and fertilization practices in wheat-maize cropping systems,a three-year field experiment was designed to quantify the carbon footprint(CF)and energy efficiency of the cropping systems in the North China Plain.The study parameters included four tillage practices(no tillage(NT),conventional tillage(CT),rotary tillage(RT),and subsoiling rotary tillage(SRT))and two fertilizer regimes(inorganic fertilizer(IF)and hybrid fertilizer with organic and inorganic components(HF)).The results indicated that the most prominent energy inputs and greenhouse gas(GHG)emissions could be ascribed to the use of fertilizers and fuel consumption.Under the same fertilization regime,ranking the tillage patterns with respect to the value of the crop yield,profit,CF,energy use efficiency(EUE)or energy productivity(EP)for either wheat or maize always gave the same sequence of SRT>RT>CT>NT.For the same tillage,the energy consumption associated with HF was higher than IF,but its GHG emissions and CF were lower while the yield and profit were higher.In terms of overall performance,tilling is more beneficial than NT,and reduced tillage practices(RT and SRT)are more beneficial than CT.The fertilization regime with the best overall performance was HF.Combining SRT with HF has significant potential for reducing CF and increasing EUE,thereby improving sustainability.Adopting measures that promote these optimizations can help to overcome the challenges posed by a lack of food security,energy crises and ecological stress.展开更多
Erratumto:Journal of Earth Science https://doi.org/10.1007/s12583-023-1946-6 The original version of this article unfortunately contained three mistakes.1.The presentation of Equation(4)was incorrect.The corrected one...Erratumto:Journal of Earth Science https://doi.org/10.1007/s12583-023-1946-6 The original version of this article unfortunately contained three mistakes.1.The presentation of Equation(4)was incorrect.The corrected one is given below.展开更多
Tourism-oriented livelihoods represent a significant avenue for transforming traditional agricultural practices.Analyzing their environmental impacts offers a novel perspective for exploring the complex interplay amon...Tourism-oriented livelihoods represent a significant avenue for transforming traditional agricultural practices.Analyzing their environmental impacts offers a novel perspective for exploring the complex interplay among human production,consumption,and the ecological environment at a micro level.In this study,Shaanxi Province farmers were selected as field survey participants.Based on a quantitative assessment of farmers’ecological footprints within the study area,how their participation in rural tourism affected ecological footprints was analyzed using the propensity score matching model,and the heterogeneity of the impact and underlying mechanisms were further explored.Results indicate that the ecological footprint of farmers varies significantly across land-use types and consumption categories.Moreover,the spatial distribution of the ecological footprints exhibits a distinct“high at both ends and low in the middle”pattern.Participation in rural tourism significantly reduces the ecological footprint,particularly among farmers with higher levels of social trust or lower economic status.Further analysis shows that habitat quality and vegetation coverage are key ecological indicators that exert a significant positive moderating effect on the negative impact of rural tourism participation on farmers’ecological footprints.These findings highlight the importance of integrating ecological conservation with economic development.Accordingly,tailored policies,improved ecological service systems,and enhanced regional ecological quality are recommended to increase resource-use efficiency and promote a virtuous cycle between environmental sustainability and rural economic growth.展开更多
Global livestock production is a major driver of climate change.Lumping beef and pork together as red meat masks important differences in their carbon footprints,land uses,and social status.These two red meat choices ...Global livestock production is a major driver of climate change.Lumping beef and pork together as red meat masks important differences in their carbon footprints,land uses,and social status.These two red meat choices in Canada were compared by using a meta-model of the Unified Livestock Industry and Crop Emissions Estimation System(ULICEES).ULICEES calculated fossil CO_(2),N_(2)O and CH_(4) emissions for beef,dairy,pork,poultry,and sheep production in Canada,based on both the livestock and their supporting land base in 2001.The dynamic drivers of the meta-model were crop yields,breeding female populations,tillage practices,nitrogen fertilizer use,and the crop complex of each livestock industry.When the potential carbon sequestration in the land growing harvested perennial forage is credited to beef production,the CO_(2)e emissions offset does not reduce the carbon footprint of beef enough to match the lower carbon footprint of pork.Most of the land required to grow hay for beef would not be needed to feed a protein-equivalent pig population.In a hypothetical conversion of all beef production to pork production for 2021,4.5 Mha of land under perennial forage was freed and 10.0 MtCO_(2)e per year was mitigated when that area was re-cultivated for annual crops—a GHG mitigation equal to 12%of the GHG emissions budget of Canadian agriculture.Leaving that area under a perennial ground cover mitigated 19.8 MtCO_(2)e per year,the equivalent of 23%of the sector’s GHG emissions budget.展开更多
The authors are very sorry for their carelessness that a wrong Fig.9 was uploaded,and a corrected one has been shown below:This corrigendum does not affect the overall structure and analysis process of the study.The a...The authors are very sorry for their carelessness that a wrong Fig.9 was uploaded,and a corrected one has been shown below:This corrigendum does not affect the overall structure and analysis process of the study.The authors would like to apologize for any inconvenience caused.展开更多
Grasslands are among the world's most threatened ecosystems, and steppe birds face increasing risks from human activities. This study investigates how human impacts affect the distribution and community structure ...Grasslands are among the world's most threatened ecosystems, and steppe birds face increasing risks from human activities. This study investigates how human impacts affect the distribution and community structure of breeding steppe birds in Inner Mongolia, a biodiversity hotspot in Asia. We conducted standardized point-count surveys across a gradient from intact grasslands to urbanized areas, integrating species occurrence data, functional traits and the Human Footprint Index (HFI). Using Generalized Linear Models (GLMs) and Conditional Random Fields (CRFs), we assessed trait-environment interactions and shifts in species associations. Our results indicate that the HFI significantly affects bird communities. Habitat specialists, such as Mongolian Lark (Melanocorypha mongolica), showed negative responses, whereas generalists like Eurasian Tree Sparrow (Passer montanus) thrived in disturbed areas. Trait-based analysis showed that species with larger body mass and specialized diets were negatively associated with HFI, whereas those linked to human-modified habitats exhibiting strong positive associations. In areas with high human footprint, co-occurrence networks grew more polarized: specialists faced intensified competition, while species with positive HFI responses formed stronger positive associations. CRF models indicated that human activities restructure species interactions, favoring generalists and simplifying community dynamics. These findings highlight the dual role of human impact in supporting some species while threatening specialists, potentially driving biotic homogenization. Our study emphasizes the need for conservation strategies that protect vulnerable species and manage those that thrive in human-altered environments. By linking traits and interactions to human impacts, this study provides a framework for identifying at-risk species and guiding conservation in the Anthropocene.展开更多
While algorithms have been created for land usage in urban settings,there have been few investigations into the extraction of urban footprint(UF).To address this research gap,the study employs several widely used imag...While algorithms have been created for land usage in urban settings,there have been few investigations into the extraction of urban footprint(UF).To address this research gap,the study employs several widely used image classification method classified into three categories to evaluate their segmentation capabilities for extracting UF across eight cities.The results indicate that pixel-based methods only excel in clear urban environments,and their overall accuracy is not consistently high.RF and SVM perform well but lack stability in object-based UF extraction,influenced by feature selection and classifier performance.Deep learning enhances feature extraction but requires powerful computing and faces challenges with complex urban layouts.SAM excels in medium-sized urban areas but falters in intricate layouts.Integrating traditional and deep learning methods optimizes UF extraction,balancing accuracy and processing efficiency.Future research should focus on adapting algorithms for diverse urban landscapes to enhance UF extraction accuracy and applicability.展开更多
The NdFeB scrap,as a representative solid waste of rare earths,possesses significant recyclable value.This study focused on NdFeB waste and investigated the environmental impacts of pyro-and hydro-metallurgical proces...The NdFeB scrap,as a representative solid waste of rare earths,possesses significant recyclable value.This study focused on NdFeB waste and investigated the environmental impacts of pyro-and hydro-metallurgical process(PH-M process)and its improved version,the pyro-and hydro-metallurgical improvement process(PH-Mi process).The results demonstrate that,although the PH-Mi process consumes higher amounts of energy,electricity,and chemicals compared to the PH-M process,it is more environmentally friendly and economically efficient(i.e.,net profit increased by 34.12%).To quantify and compare the environmental performance of the two scenarios,life cycle assessment methodology was applied.It is concluded that the PH-Mi process is superior to the PH-M process for eutrophication potential(EP)and the total environmental impacts.In comparison with PH-Mi process,PH-M process exhibits a certain advantage in terms of carbon footprint due to increased consumption of electricity and chemicals after the technological upgrade.展开更多
Reducing greenhouse gas(GHG)emissions to address climate change is a global consensus,and municipal wastewater treatment plants(MWWTPs)should lead the way in low-carbon sustainable development.However,achieving efflue...Reducing greenhouse gas(GHG)emissions to address climate change is a global consensus,and municipal wastewater treatment plants(MWWTPs)should lead the way in low-carbon sustainable development.However,achieving effluent discharge standards often requires considerable energy and chemical consumption during operation,resulting in significant carbon footprints.In this study,GHG emissions are systematically accounted for,and the driving factors of carbon footprint growth in China’s MWWTPs are explored.In 2020,a total of 41.9 million tonnes(Mt)of carbon dioxide equivalent(CO_(2)-eq)were released by the sector,with nearly two-thirds being indirect emissions resulting from energy and material usage.The intensity of electricity,carbon source,and phosphorus removing agent consumption increasingly influence carbon footprint growth over time.Through statistical inference,benchmarks for electricity and chemical consumption intensity are established across all MWWTPs under various operational conditions,and the potential for mitigation through more efficient energy and material utilization is calculated.The results suggest that many MWWTPs offer significant opportunities for emission reduction.Consequently,empirical decarbonization measures,including intelligent device control,optimization of aeration equipment,energy recovery initiatives,and other enhancements to improve operational and carbon efficiency,are recommended.展开更多
To mitigate the catastrophic impacts of climate change,many measures and strategies have been designed and implemented to encourage people to change their daily behaviors for a low-carbon society transition.However,mo...To mitigate the catastrophic impacts of climate change,many measures and strategies have been designed and implemented to encourage people to change their daily behaviors for a low-carbon society transition.However,most people generate carbon emissions through their daily activities in space and time.They are also exposed to multiple environmental factors(e.g.,air pollution,noise,and greenspace).Changing people’s behaviors to reduce carbon emissions can also influence their multiple environmental exposures and further influence their health outcomes.Thus,this study seeks to examine the associations between individuals’daily carbon footprints and their exposures to multiple environmental factors(i.e.,air pollution,noise,and greenspace)across different spa-tial and temporal contexts using individual-level data collected by portable real-time sensors,an activity-travel diary,and a questionnaire from four communities in Hong Kong.The results first indicated that individuals’car-bon footprints of daily activities varied across different spatial and temporal contexts,with home and nighttime having the highest estimated carbon footprints.We also found that activity carbon footprints have a positive asso-ciation with PM2.5,which is particularly strong at home and from morning to nighttime,and mixed associations with noise(positive at home and nighttime,while negative in other places and during travel,from morning to afternoon).Besides,carbon footprints also have consistent negative associations with shrubland and woodland across different spatial and temporal contexts.The findings can provide essential insights into effective measures for promoting the transition to a low-carbon society.展开更多
The new edition of the International Production Cost Comparison (IPCC) from ITMF has been published.The report benchmarks manufacturing costs for a range of textile products along the primary textile value chain,disag...The new edition of the International Production Cost Comparison (IPCC) from ITMF has been published.The report benchmarks manufacturing costs for a range of textile products along the primary textile value chain,disaggregated by key cost components at each production stage.展开更多
Driven by the goal of carbon neutrality,prefabricated buildings,as an important form of green construction,have become a key focus in the study of lifecycle carbon footprint management.Based on this,this paper starts ...Driven by the goal of carbon neutrality,prefabricated buildings,as an important form of green construction,have become a key focus in the study of lifecycle carbon footprint management.Based on this,this paper starts from the perspective of carbon footprint and combines the digital and visual advantages of BIM technology to construct a green evaluation system for prefabricated buildings.It explores the carbon emissions in each stage of the building and proposes corresponding improvement measures,aiming to provide necessary references for the low-carbon transformation of prefabricated buildings.展开更多
Low levels of environmental education,energy consumption,and other anthropogenic factors strongly contribute to the rising temperature in the world's atmosphere.As such,this study reveals how energy consumption an...Low levels of environmental education,energy consumption,and other anthropogenic factors strongly contribute to the rising temperature in the world's atmosphere.As such,this study reveals how energy consumption and education affect the ecological footprint(EF)and also determines the education thresholds for EF sustainability in sub-Saharan Africa(SSA).The estimation methods in this study are strictly second-generation econometric techniques because of the problems of slope heterogeneity and cross-sectional dependence discovered in the preliminary analysis.The results confirm cointegration,warranting the need for long-run parameter estimators.The Augment Mean Group estimator suggests that natural resources,non-renewable energy consumption(NRE),and economic growth increase the EF.Although renewable energy consumption(REN)and globalization reduce the EF,these indicators are insignificant.The results of the Method of Moment Quantile Regression(MMQR)reveal that REN exacts an indirect effect on the EF via education.Furthermore,the education thresholds required for ecological sustainability have been established.In line with these outcomes,it is proposed that the region redesign its energy policy to encourage eco-friendly consumption by leaning more on pro-environmental strategies and tightening environmental regulations.展开更多
The agricultural water footprint(AWF)is intricately linked to water-related Sustainable Development Goals(SDGs).This study developed a multi-dimensional indicator framework integrating AWF with social,economic,and eco...The agricultural water footprint(AWF)is intricately linked to water-related Sustainable Development Goals(SDGs).This study developed a multi-dimensional indicator framework integrating AWF with social,economic,and ecological metrics to elucidate the spatiotemporal evolution of agricultural water sustainability in Guangdong Province,China,from 2010 to 2020.By disaggregating AWF into green(soil moisture),blue(surface/groundwater),and grey(pollution-related)components,we identified the dominate drivers of sustainability transitions and proposed context-specific policy interventions.Key findings include:1)a 6.98%reduction in total AWF(from 19.35 to 18.00 km^(3))was detected,accompanied by a 14.46%improvement in the agricultural water sustainability level.2)Green water dominated(78.28%of total footprint)the AWF,while blue(19.29%)and grey water(2.43%)contributed less and exhibited lowered degree of spatial variability;3)Within the crop system,rice(Oryza sativa)accounted for nearly 60%of the AWF,and veget-ables(Vegetabilia)shared around 20%,while the rest three crops(peanut(Arachis hypogaea),banana(Musa acuminata)and oranges(Citrus sinensis))contributed another 20%.4)Western Guangdong consumed higher AWF per area,reaching 1.59 times the provincial average due to the climate and cropping system,whereas eastern regions consumed disproportionate blue water,around 1.76 times the provincial average for irrigated crop production.Optimizing AWF governance strengthens food security by enhancing blue water utiliz-ation efficiency in rice production is recommended,especially in eastern Guangdong.The formulation of rice-specific AWF bench-marks facilitates data-driven water resource policies,while strategic greywater management interventions would effectively reduce en-vironmental burdens.Context-specific strategies,such as incorporating organic fertilizer promotion,integrating constructed wetlands,rainwater capture infrastructure,and market-based regulatory tools would synergistically improve crop productivity,diminish pollutant loads,and bolster agricultural water sustainability.展开更多
This study investigates the adoption of carbon footprint tracking apps(CFAs)among Thai millennials,a critical element in addressing climate change.CFAs have yet to gain significant traction among users despite offerin...This study investigates the adoption of carbon footprint tracking apps(CFAs)among Thai millennials,a critical element in addressing climate change.CFAs have yet to gain significant traction among users despite offering personalized missions.Employing an extended Technology Acceptance Model(TAM)framework,we examine factors influencing CFA adoption intentions based on a sample of 30 environmentally conscious Thai millennials.Our findings indicate that perceived ease of use and enjoyment are crucial drivers of CFA adoption.Trust significantly impacts perceived usefulness,while enjoyment influences perceived ease of use.The study underscores the importance of user experience(UX)and enjoyment in driving adoption,highlighting the need for intuitive interfaces and engaging features.This research provides comprehensive insights into CFA adoption in Thailand by integrating TAM with external trust and perceived enjoyment factors.These findings offer valuable guidance for app developers,policymakers,and marketers,emphasizing the critical role of user experience and fun in fostering widespread CFA adoption.We discuss implications for stakeholders and suggest directions for future research,including larger-scale studies and cross-cultural comparisons within Southeast Asia.This research contributes to SDG 13(Climate Action)and SDG 12(Responsible Consumption and Production).展开更多
文摘Analysis of the environmental and economic performance of fishing vessels has received limited attention compared with other ship types despite their notable contribution to global greenhouse gas(GHG)emissions.This study evaluates the carbon footprint(CF)and economic viability of a liquefied natural gas(LNG)-fueled fishing vessel,using real engine operation simulations to provide precise and dynamic evaluation of fuel consumption and GHG emissions.Operational profiles are obtained through the utilization of onboard monitoring systems,whereas engine performance is simulated using the 1D/0D AVL Boost^(TM)model.Life cycle assessment(LCA)is conducted to quantify the environmental impact,whereas life cycle cost assessment(LCCA)is performed to analyze the profitability of LNG as an alternative fuel.The potential impact of the future fuel price uncertainties is addressed using Monte Carlo simulations.The LCA findings indicate that LNG has the potential to reduce the CF of the vessel by 14%to 16%,in comparison to a diesel power system configuration that serves as the baseline scenario.The LCCA results further indicate that the total cost of an LNG-powered ship is lower by 9.5%-13.8%,depending on the share of LNG and pilot fuels.This finding highlights the potential of LNG to produce considerable environmental benefits while addressing economic challenges under diverse operational and fuel price conditions.
基金jointly supported by the National Key R&D Program of China(Grant No.2022YFE0209200)the National Natural Science Foundation of China(Grant Nos.U22A20562,42330607 and 41761144054)the National Large Scientific and Technological Infrastructure“Earth System Science Numerical Simulator Facility”(Earth-Lab)(https://cstr.cn/31134.02.EL)。
文摘Accurate quantification of life-cycle greenhouse gas(GHG)footprints(GHG_(fp))for a crop cultivation system is urgently needed to address the conflict between food security and global warming mitigation.In this study,the hydrobiogeochemical model,CNMM-DNDC,was validated with in situ observations from maize-based cultivation systems at the sites of Yongji(YJ,China),Yanting(YT,China),and Madeya(MA,Kenya),subject to temperate,subtropical,and tropical climates,respectively,and updated to enable life-cycle GHG_(fp)estimation.The model validation provided satisfactory simulations on multiple soil variables,crop growth,and emissions of GHGs and reactive nitrogen gases.The locally conventional management practices resulted in GHG_(fp)values of 0.35(0.09–0.53 at the 95%confidence interval),0.21(0.01–0.73),0.46(0.27–0.60),and 0.54(0.21–0.77)kg CO_(2)e kg~(-1)d.m.(d.m.for dry matter in short)for maize–wheat rotation at YJ and YT,and for maize–maize and maize–Tephrosia rotations at MA,respectively.YT's smallest GHG_(fp)was attributed to its lower off-farm GHG emissions than YJ,though the soil organic carbon(SOC)storage and maize yield were slightly lower than those of YJ.MA's highest SOC loss and low yield in shifting cultivation for maize–Tephrosia rotation contributed to its highest GHG_(fp).Management practices of maize cultivation at these sites could be optimized by combination of synthetic and organic fertilizer(s)while incorporating 50%–100%crop residues.Further evaluation of the updated CNMM-DNDC is needed for different crops at site and regional scales to confirm its worldwide applicability in quantifying GHG_(fp)and optimizing management practices for achieving multiple sustainability goals.
基金supported by Ningbo’s major scientific and technological breakthrough project“Research and Demonstration on the Technology of Collaborative Disposal of Secondary Ash in Typical Industrial Furnaces” (No.20212ZDYF020047)the central balance fund project“Research on Carbon Emission Accounting and Emission Reduction Potential Assessment for the Whole Life Cycle of Iron and Steel Industry” (No.2021-JY-07).
文摘China is the most important steel producer in the world,and its steel industry is one of themost carbon-intensive industries in China.Consequently,research on carbon emissions from the steel industry is crucial for China to achieve carbon neutrality and meet its sustainable global development goals.We constructed a carbon dioxide(CO_(2))emission model for China’s iron and steel industry froma life cycle perspective,conducted an empirical analysis based on data from2019,and calculated the CO_(2)emissions of the industry throughout its life cycle.Key emission reduction factors were identified using sensitivity analysis.The results demonstrated that the CO_(2)emission intensity of the steel industry was 2.33 ton CO_(2)/ton,and the production and manufacturing stages were the main sources of CO_(2)emissions,accounting for 89.84%of the total steel life-cycle emissions.Notably,fossil fuel combustion had the highest sensitivity to steel CO_(2)emissions,with a sensitivity coefficient of 0.68,reducing the amount of fossil fuel combustion by 20%and carbon emissions by 13.60%.The sensitivities of power structure optimization and scrap consumption were similar,while that of the transportation structure adjustment was the lowest,with a sensitivity coefficient of less than 0.1.Given the current strategic goals of peak carbon and carbon neutrality,it is in the best interest of the Chinese government to actively promote energy-saving and low-carbon technologies,increase the ratio of scrap steel to steelmaking,and build a new power system.
基金supported by the National Natural Science Foundation of China(No.32071980)the Key Projects of Shaanxi Agricultural Collaborative Innovation and Extension Alliance(No.LMZD202201)+1 种基金the Key R&D Project in Shaanxi Province(No.2021LLRH-07)Shaanxi Natural Scientific Basic Research Program project(No.2022JQ-157).
文摘Agricultural practices significantly contribute to greenhouse gas(GHG)emissions,necessitating cleaner production technologies to reduce environmental pressure and achieve sustainable maize production.Plastic film mulching is commonly used in the Loess Plateau region.Incorporating slow-release fertilizers as a replacement for urea within this practice can reduce nitrogen losses and enhance crop productivity.Combining these techniques represents a novel agricultural approach in semi-arid areas.However,the impact of this integration on soil carbon storage(SOCS),carbon footprint(CF),and economic benefits has received limited research attention.Therefore,we conducted an eight-year study(2015-2022)in the semi-arid northwestern region to quantify the effects of four treatments[urea supplied without plastic film mulching(CK-U),slow-release fertilizer supplied without plastic film mulching(CK-S),urea supplied with plastic film mulching(PM-U),and slow-release fertilizer supplied with plastic film mulching(PM-S)]on soil fertility,economic and environmental benefits.The results revealed that nitrogen fertilizer was the primary contributor to total GHG emissions(≥71.97%).Compared to other treatments,PM-S increased average grain yield by 12.01%-37.89%,water use efficiency by 9.19%-23.33%,nitrogen accumulation by 27.07%-66.19%,and net return by 6.21%-29.57%.Furthermore,PM-S decreased CF by 12.87%-44.31%and CF per net return by 14.25%-41.16%.After eight years,PM-S increased SOCS(0-40 cm)by 2.46%,while PM-U decreased it by 7.09%.These findings highlight the positive effects of PM-S on surface soil fertility,economic gains,and environmental benefits in spring maize production on the Loess Plateau,underscoring its potential for widespread adoption and application.
基金supported by research grants from the Natural Science Foundation of Shandong Province,China(ZR2020MC092)the Key Research and Development Project of Shandong Province,China(2019TSCYCX-33)the Key Research and Development Project of Shandong Province,China(LJNY202025).
文摘To make agricultural systems sustainable in terms of their greenness and efficiency,optimizing the tillage and fertilization practices is essential.To assess the effects of tilling and fertilization practices in wheat-maize cropping systems,a three-year field experiment was designed to quantify the carbon footprint(CF)and energy efficiency of the cropping systems in the North China Plain.The study parameters included four tillage practices(no tillage(NT),conventional tillage(CT),rotary tillage(RT),and subsoiling rotary tillage(SRT))and two fertilizer regimes(inorganic fertilizer(IF)and hybrid fertilizer with organic and inorganic components(HF)).The results indicated that the most prominent energy inputs and greenhouse gas(GHG)emissions could be ascribed to the use of fertilizers and fuel consumption.Under the same fertilization regime,ranking the tillage patterns with respect to the value of the crop yield,profit,CF,energy use efficiency(EUE)or energy productivity(EP)for either wheat or maize always gave the same sequence of SRT>RT>CT>NT.For the same tillage,the energy consumption associated with HF was higher than IF,but its GHG emissions and CF were lower while the yield and profit were higher.In terms of overall performance,tilling is more beneficial than NT,and reduced tillage practices(RT and SRT)are more beneficial than CT.The fertilization regime with the best overall performance was HF.Combining SRT with HF has significant potential for reducing CF and increasing EUE,thereby improving sustainability.Adopting measures that promote these optimizations can help to overcome the challenges posed by a lack of food security,energy crises and ecological stress.
文摘Erratumto:Journal of Earth Science https://doi.org/10.1007/s12583-023-1946-6 The original version of this article unfortunately contained three mistakes.1.The presentation of Equation(4)was incorrect.The corrected one is given below.
基金supported by the National Natural Science Foundation of China[Grant No.42171281,72442020]the Shaanxi Provincial Social Science Fund Project[Grant No.2024ES04]Shaanxi Province Postdoctoral Science Foundation[Grant No.2024BSHSDZZ013].
文摘Tourism-oriented livelihoods represent a significant avenue for transforming traditional agricultural practices.Analyzing their environmental impacts offers a novel perspective for exploring the complex interplay among human production,consumption,and the ecological environment at a micro level.In this study,Shaanxi Province farmers were selected as field survey participants.Based on a quantitative assessment of farmers’ecological footprints within the study area,how their participation in rural tourism affected ecological footprints was analyzed using the propensity score matching model,and the heterogeneity of the impact and underlying mechanisms were further explored.Results indicate that the ecological footprint of farmers varies significantly across land-use types and consumption categories.Moreover,the spatial distribution of the ecological footprints exhibits a distinct“high at both ends and low in the middle”pattern.Participation in rural tourism significantly reduces the ecological footprint,particularly among farmers with higher levels of social trust or lower economic status.Further analysis shows that habitat quality and vegetation coverage are key ecological indicators that exert a significant positive moderating effect on the negative impact of rural tourism participation on farmers’ecological footprints.These findings highlight the importance of integrating ecological conservation with economic development.Accordingly,tailored policies,improved ecological service systems,and enhanced regional ecological quality are recommended to increase resource-use efficiency and promote a virtuous cycle between environmental sustainability and rural economic growth.
文摘Global livestock production is a major driver of climate change.Lumping beef and pork together as red meat masks important differences in their carbon footprints,land uses,and social status.These two red meat choices in Canada were compared by using a meta-model of the Unified Livestock Industry and Crop Emissions Estimation System(ULICEES).ULICEES calculated fossil CO_(2),N_(2)O and CH_(4) emissions for beef,dairy,pork,poultry,and sheep production in Canada,based on both the livestock and their supporting land base in 2001.The dynamic drivers of the meta-model were crop yields,breeding female populations,tillage practices,nitrogen fertilizer use,and the crop complex of each livestock industry.When the potential carbon sequestration in the land growing harvested perennial forage is credited to beef production,the CO_(2)e emissions offset does not reduce the carbon footprint of beef enough to match the lower carbon footprint of pork.Most of the land required to grow hay for beef would not be needed to feed a protein-equivalent pig population.In a hypothetical conversion of all beef production to pork production for 2021,4.5 Mha of land under perennial forage was freed and 10.0 MtCO_(2)e per year was mitigated when that area was re-cultivated for annual crops—a GHG mitigation equal to 12%of the GHG emissions budget of Canadian agriculture.Leaving that area under a perennial ground cover mitigated 19.8 MtCO_(2)e per year,the equivalent of 23%of the sector’s GHG emissions budget.
文摘The authors are very sorry for their carelessness that a wrong Fig.9 was uploaded,and a corrected one has been shown below:This corrigendum does not affect the overall structure and analysis process of the study.The authors would like to apologize for any inconvenience caused.
基金funded by the China Postdoctoral Science Foundation(2024M760408)National Natural Science Foundation of China(No.32201304)+1 种基金the Fundamental Research Funds for the Central Universities(No.2412024QD0212412022QD026).
文摘Grasslands are among the world's most threatened ecosystems, and steppe birds face increasing risks from human activities. This study investigates how human impacts affect the distribution and community structure of breeding steppe birds in Inner Mongolia, a biodiversity hotspot in Asia. We conducted standardized point-count surveys across a gradient from intact grasslands to urbanized areas, integrating species occurrence data, functional traits and the Human Footprint Index (HFI). Using Generalized Linear Models (GLMs) and Conditional Random Fields (CRFs), we assessed trait-environment interactions and shifts in species associations. Our results indicate that the HFI significantly affects bird communities. Habitat specialists, such as Mongolian Lark (Melanocorypha mongolica), showed negative responses, whereas generalists like Eurasian Tree Sparrow (Passer montanus) thrived in disturbed areas. Trait-based analysis showed that species with larger body mass and specialized diets were negatively associated with HFI, whereas those linked to human-modified habitats exhibiting strong positive associations. In areas with high human footprint, co-occurrence networks grew more polarized: specialists faced intensified competition, while species with positive HFI responses formed stronger positive associations. CRF models indicated that human activities restructure species interactions, favoring generalists and simplifying community dynamics. These findings highlight the dual role of human impact in supporting some species while threatening specialists, potentially driving biotic homogenization. Our study emphasizes the need for conservation strategies that protect vulnerable species and manage those that thrive in human-altered environments. By linking traits and interactions to human impacts, this study provides a framework for identifying at-risk species and guiding conservation in the Anthropocene.
文摘While algorithms have been created for land usage in urban settings,there have been few investigations into the extraction of urban footprint(UF).To address this research gap,the study employs several widely used image classification method classified into three categories to evaluate their segmentation capabilities for extracting UF across eight cities.The results indicate that pixel-based methods only excel in clear urban environments,and their overall accuracy is not consistently high.RF and SVM perform well but lack stability in object-based UF extraction,influenced by feature selection and classifier performance.Deep learning enhances feature extraction but requires powerful computing and faces challenges with complex urban layouts.SAM excels in medium-sized urban areas but falters in intricate layouts.Integrating traditional and deep learning methods optimizes UF extraction,balancing accuracy and processing efficiency.Future research should focus on adapting algorithms for diverse urban landscapes to enhance UF extraction accuracy and applicability.
基金supported by the National Key R&D Program of China(No.2020YFC1909005).
文摘The NdFeB scrap,as a representative solid waste of rare earths,possesses significant recyclable value.This study focused on NdFeB waste and investigated the environmental impacts of pyro-and hydro-metallurgical process(PH-M process)and its improved version,the pyro-and hydro-metallurgical improvement process(PH-Mi process).The results demonstrate that,although the PH-Mi process consumes higher amounts of energy,electricity,and chemicals compared to the PH-M process,it is more environmentally friendly and economically efficient(i.e.,net profit increased by 34.12%).To quantify and compare the environmental performance of the two scenarios,life cycle assessment methodology was applied.It is concluded that the PH-Mi process is superior to the PH-M process for eutrophication potential(EP)and the total environmental impacts.In comparison with PH-Mi process,PH-M process exhibits a certain advantage in terms of carbon footprint due to increased consumption of electricity and chemicals after the technological upgrade.
基金supported by the National Natural Science Foundation of China(52200228 and 72022004)the National Key Research and Development Program of China(2021YFC3200205 and 2022YFC3203704).
文摘Reducing greenhouse gas(GHG)emissions to address climate change is a global consensus,and municipal wastewater treatment plants(MWWTPs)should lead the way in low-carbon sustainable development.However,achieving effluent discharge standards often requires considerable energy and chemical consumption during operation,resulting in significant carbon footprints.In this study,GHG emissions are systematically accounted for,and the driving factors of carbon footprint growth in China’s MWWTPs are explored.In 2020,a total of 41.9 million tonnes(Mt)of carbon dioxide equivalent(CO_(2)-eq)were released by the sector,with nearly two-thirds being indirect emissions resulting from energy and material usage.The intensity of electricity,carbon source,and phosphorus removing agent consumption increasingly influence carbon footprint growth over time.Through statistical inference,benchmarks for electricity and chemical consumption intensity are established across all MWWTPs under various operational conditions,and the potential for mitigation through more efficient energy and material utilization is calculated.The results suggest that many MWWTPs offer significant opportunities for emission reduction.Consequently,empirical decarbonization measures,including intelligent device control,optimization of aeration equipment,energy recovery initiatives,and other enhancements to improve operational and carbon efficiency,are recommended.
基金supported by grants from the Hong Kong Re-search Grants Council(General Research Fund Grants No.14605920,14611621,14606922,14603724Collaborative Research Fund Grant No.C4023-20GF+3 种基金Research Matching Grants RMG 8601219,8601242,3110151)RGC Postdoctoral Fellowship No.PDFS2425-4H01)a grant from the Research Committee on Research Sustainability of Major Re-search Grants Council Funding Schemes(Grant No.3133235)of the Chinese University of Hong Kong(CUHK)grant from the Vice-Chancellor’s One-offDiscretionary Fund(Smart and Sustainable Cities:City of Commons)(4930787)of CUHK.
文摘To mitigate the catastrophic impacts of climate change,many measures and strategies have been designed and implemented to encourage people to change their daily behaviors for a low-carbon society transition.However,most people generate carbon emissions through their daily activities in space and time.They are also exposed to multiple environmental factors(e.g.,air pollution,noise,and greenspace).Changing people’s behaviors to reduce carbon emissions can also influence their multiple environmental exposures and further influence their health outcomes.Thus,this study seeks to examine the associations between individuals’daily carbon footprints and their exposures to multiple environmental factors(i.e.,air pollution,noise,and greenspace)across different spa-tial and temporal contexts using individual-level data collected by portable real-time sensors,an activity-travel diary,and a questionnaire from four communities in Hong Kong.The results first indicated that individuals’car-bon footprints of daily activities varied across different spatial and temporal contexts,with home and nighttime having the highest estimated carbon footprints.We also found that activity carbon footprints have a positive asso-ciation with PM2.5,which is particularly strong at home and from morning to nighttime,and mixed associations with noise(positive at home and nighttime,while negative in other places and during travel,from morning to afternoon).Besides,carbon footprints also have consistent negative associations with shrubland and woodland across different spatial and temporal contexts.The findings can provide essential insights into effective measures for promoting the transition to a low-carbon society.
文摘The new edition of the International Production Cost Comparison (IPCC) from ITMF has been published.The report benchmarks manufacturing costs for a range of textile products along the primary textile value chain,disaggregated by key cost components at each production stage.
文摘Driven by the goal of carbon neutrality,prefabricated buildings,as an important form of green construction,have become a key focus in the study of lifecycle carbon footprint management.Based on this,this paper starts from the perspective of carbon footprint and combines the digital and visual advantages of BIM technology to construct a green evaluation system for prefabricated buildings.It explores the carbon emissions in each stage of the building and proposes corresponding improvement measures,aiming to provide necessary references for the low-carbon transformation of prefabricated buildings.
文摘Low levels of environmental education,energy consumption,and other anthropogenic factors strongly contribute to the rising temperature in the world's atmosphere.As such,this study reveals how energy consumption and education affect the ecological footprint(EF)and also determines the education thresholds for EF sustainability in sub-Saharan Africa(SSA).The estimation methods in this study are strictly second-generation econometric techniques because of the problems of slope heterogeneity and cross-sectional dependence discovered in the preliminary analysis.The results confirm cointegration,warranting the need for long-run parameter estimators.The Augment Mean Group estimator suggests that natural resources,non-renewable energy consumption(NRE),and economic growth increase the EF.Although renewable energy consumption(REN)and globalization reduce the EF,these indicators are insignificant.The results of the Method of Moment Quantile Regression(MMQR)reveal that REN exacts an indirect effect on the EF via education.Furthermore,the education thresholds required for ecological sustainability have been established.In line with these outcomes,it is proposed that the region redesign its energy policy to encourage eco-friendly consumption by leaning more on pro-environmental strategies and tightening environmental regulations.
基金Under the auspices of the National Natural Science Foundation of China(No.42271311)Open Project of State Key Laboratory of Estuarine and Coastal Sciences(No.SKLEC-KF202204)。
文摘The agricultural water footprint(AWF)is intricately linked to water-related Sustainable Development Goals(SDGs).This study developed a multi-dimensional indicator framework integrating AWF with social,economic,and ecological metrics to elucidate the spatiotemporal evolution of agricultural water sustainability in Guangdong Province,China,from 2010 to 2020.By disaggregating AWF into green(soil moisture),blue(surface/groundwater),and grey(pollution-related)components,we identified the dominate drivers of sustainability transitions and proposed context-specific policy interventions.Key findings include:1)a 6.98%reduction in total AWF(from 19.35 to 18.00 km^(3))was detected,accompanied by a 14.46%improvement in the agricultural water sustainability level.2)Green water dominated(78.28%of total footprint)the AWF,while blue(19.29%)and grey water(2.43%)contributed less and exhibited lowered degree of spatial variability;3)Within the crop system,rice(Oryza sativa)accounted for nearly 60%of the AWF,and veget-ables(Vegetabilia)shared around 20%,while the rest three crops(peanut(Arachis hypogaea),banana(Musa acuminata)and oranges(Citrus sinensis))contributed another 20%.4)Western Guangdong consumed higher AWF per area,reaching 1.59 times the provincial average due to the climate and cropping system,whereas eastern regions consumed disproportionate blue water,around 1.76 times the provincial average for irrigated crop production.Optimizing AWF governance strengthens food security by enhancing blue water utiliz-ation efficiency in rice production is recommended,especially in eastern Guangdong.The formulation of rice-specific AWF bench-marks facilitates data-driven water resource policies,while strategic greywater management interventions would effectively reduce en-vironmental burdens.Context-specific strategies,such as incorporating organic fertilizer promotion,integrating constructed wetlands,rainwater capture infrastructure,and market-based regulatory tools would synergistically improve crop productivity,diminish pollutant loads,and bolster agricultural water sustainability.
文摘This study investigates the adoption of carbon footprint tracking apps(CFAs)among Thai millennials,a critical element in addressing climate change.CFAs have yet to gain significant traction among users despite offering personalized missions.Employing an extended Technology Acceptance Model(TAM)framework,we examine factors influencing CFA adoption intentions based on a sample of 30 environmentally conscious Thai millennials.Our findings indicate that perceived ease of use and enjoyment are crucial drivers of CFA adoption.Trust significantly impacts perceived usefulness,while enjoyment influences perceived ease of use.The study underscores the importance of user experience(UX)and enjoyment in driving adoption,highlighting the need for intuitive interfaces and engaging features.This research provides comprehensive insights into CFA adoption in Thailand by integrating TAM with external trust and perceived enjoyment factors.These findings offer valuable guidance for app developers,policymakers,and marketers,emphasizing the critical role of user experience and fun in fostering widespread CFA adoption.We discuss implications for stakeholders and suggest directions for future research,including larger-scale studies and cross-cultural comparisons within Southeast Asia.This research contributes to SDG 13(Climate Action)and SDG 12(Responsible Consumption and Production).
