Interactions among ecosystem services(ESs)are spatially heterogeneous,shaped by both stable(unidirectional)and unstable(context-dependent)influences of socio-economic development and climate change.These complexities ...Interactions among ecosystem services(ESs)are spatially heterogeneous,shaped by both stable(unidirectional)and unstable(context-dependent)influences of socio-economic development and climate change.These complexities pose significant challenges for spatially adaptive ecosystem management.Ecosystem service bundles(ESBs),as recurring combinations of ESs,offer a valuable framework to capture such interactions.Here,we proposed an integrated analytical framework that combines K-means clustering,the geographical detector(GD)model,and geographically and temporally weighted regression(GTWR)models to evaluate how socio-economic and climatic drivers influence ESBs across space and time.Using Hanshui River Basin(HRB)in central China as a case study,we quantified ES dynamics from 2000 to 2020,identified ESBs and stable and unstable effects of multiple drivers.The results showed that carbon sequestration(CS),water yield(WY),and aesthetic landscape(AL)increased by 32.80%,9.00%,and 7.34%,respectively,while soil retention(SR)and food supply(FS)declined by 8.38%and 5.36%.Five distinct ESBs were identified,namely ecologically fragile bundle(EFB),agricultural production bundle(APB),water supply bundle(WSB),forest ecological bundle(FEB),and ecological conservation bundle(ECB).Among these,FEB expanded to more than 35.75%of the HRB,and APB exhibited the sharpest decline(-28.64%).Land use intensity(LUI)was the primary driver of the spatial heterogeneity of ESBs,while synergistic and nonlinear interactions among multiple factors increasingly amplified their effects over time.Notably,annual precipitation(AP)emerged as the only stable basin-scale driver,consistently enhancing ES performance,while gross domestic product(GDP)and normalized difference vegetation index(NDVI)had stable yet spatially differentiated effects across bundles.Our findings highlight the significance of distinguishing stable/unstable driver effects on ES dynamics to inform regionally adaptive ecosystem governance.The proposed framework provides valuable insights into ES interactions,identify spatial priorities,and support policy interventions that balance ecological conservation with socio-economic development.展开更多
On October 9, Tianyang County’s government and Guangxi Baise Guangyin Aluminum Co., Ltd. signed an agreement on an aluminum processing project with an annual output
Human well-being and livelihoods depend on natural ecosystem services(ESs).Following the increment of population,ESs have been deteriorated over time.Ultimately,land use/land cover(LULC)changes have a profound impact ...Human well-being and livelihoods depend on natural ecosystem services(ESs).Following the increment of population,ESs have been deteriorated over time.Ultimately,land use/land cover(LULC)changes have a profound impact on the change of ecosystem.The primary goal of this study is to determine the impacts of LULC changes on ecosystem service values(ESVs)in the upper Gilgel Abbay watershed,Ethiopia.Changes in LULC types were studied using three Landsat images representing 1986,2003,and 2021.The Landsat images were classified using a supervised image classification technique in Earth Resources Data Analysis System(ERDAS)Imagine 2014.We classified ESs in this study into four categories(including provisioning,regulating,supporting,and cultural services)based on global ES classification scheme.The adjusted ESV coefficient benefit approach was employed to measure the impacts of LULC changes on ESVs.Five LULC types were identified in this study,including cultivated land,forest,shrubland,grassland,and water body.The result revealed that the area of cultivated land accounted for 64.50%,71.50%,and 61.50%of the total area in 1986,2003,and 2021,respectively.The percentage of the total area covered by forest was 9.50%,5.90%,and 14.80%in 1986,2003,and 2021,respectively.Result revealed that the total ESV decreased from 7.42×10^(7) to 6.44×10^(7) USD between 1986 and 2003.This is due to the expansion of cultivated land at the expense of forest and shrubland.However,the total ESV increased from 6.44×10^(7) to 7.76×10^(7) USD during 2003-2021,because of the increment of forest and shrubland.The expansion of cultivated land and the reductions of forest and shrubland reduced most individual ESs during 1986-2003.Nevertheless,the increase in forest and shrubland at the expense of cultivated land enhanced many ESs during 2003-2021.Therefore,the findings suggest that appropriate land use practices should be scaled-up to sustainably maintain ESs.展开更多
The process of including renewable energy sources in power networks is moving quickly,so the need for innovative configuration solutions for grid-side ESS has grown.Among the new methods presented in this paper is GA-...The process of including renewable energy sources in power networks is moving quickly,so the need for innovative configuration solutions for grid-side ESS has grown.Among the new methods presented in this paper is GA-OCESE,which stands for Genetic Algorithm-based Optimization Configuration for Energy Storage in Electric Networks.This is one of the methods suggested in this study,which aims to enhance the sizing,positioning,and operational characteristics of structured ESS under dynamic grid conditions.Particularly,the aim is to maximize efficiency.A multiobjective genetic algorithm,the GA-OCESE framework,considers all these factors simultaneously.Besides considering cost-efficiency,response time,and energy use,the system also considers all these elements simultaneously.This enables it to effectively react to load uncertainty and variations in inputs connected to renewable sources.Results of an experimental assessment conducted on a standardized grid simulation platform indicate that by increasing energy use efficiency by 17.6%and reducing peak-load effects by 22.3%,GA-OCESE outperforms previous heuristic-based methods.This was found by contrasting the outcomes of the assessment with those of the evaluation.The results of the assessment helped to reveal this.The proposed approach will provide utility operators and energy planners with a decision-making tool that is both scalable and adaptable.This technology is particularly well-suited for smart grids,microgrid systems,and power infrastructures that heavily rely on renewable energy.Every technical component has been carefully recorded to ensure accuracy,reproducibility,and relevance across all power systems engineering software uses.This was done to ensure the program’s relevance.展开更多
This article proposes a multi-tiered fault detection system for series-connected lithium-ion battery modules.Improper use of batteries can lead to electrolyte decomposition,resulting in the formation of lithium dendri...This article proposes a multi-tiered fault detection system for series-connected lithium-ion battery modules.Improper use of batteries can lead to electrolyte decomposition,resulting in the formation of lithium dendrites.These dendrites may pierce the separator,leading to the failure of the insulation layer between electrodes and causing micro short circuits.When a micro short circuit occurs,the electrolyte typically undergoes exothermic reactions,leading to thermal runaway and posing a safety risk to users.Relying solely on temperature-based judgment mechanisms within the battery management system often results in delayed intervention.To address this issue,the article develops a multi-tiered fault detection algorithm for series-connected lithium-ion batteries.This algorithm can effectively diagnose micro short circuits,aging,and normal batteries using minimal battery data,thereby improving diagnostic accuracy and enhancing the flexibility of fault detection.Simulations and experiments conducted under various levels of micro short circuits validate the effectiveness of the algorithm,demonstrating its ability to distinguish between short-circuited,aged,and normal batteries under different conditions.This technology can be applied to electric vehicles and energy storage systems,enabling early warnings to ensure safety and prevent thermal runaway.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.42171414)。
文摘Interactions among ecosystem services(ESs)are spatially heterogeneous,shaped by both stable(unidirectional)and unstable(context-dependent)influences of socio-economic development and climate change.These complexities pose significant challenges for spatially adaptive ecosystem management.Ecosystem service bundles(ESBs),as recurring combinations of ESs,offer a valuable framework to capture such interactions.Here,we proposed an integrated analytical framework that combines K-means clustering,the geographical detector(GD)model,and geographically and temporally weighted regression(GTWR)models to evaluate how socio-economic and climatic drivers influence ESBs across space and time.Using Hanshui River Basin(HRB)in central China as a case study,we quantified ES dynamics from 2000 to 2020,identified ESBs and stable and unstable effects of multiple drivers.The results showed that carbon sequestration(CS),water yield(WY),and aesthetic landscape(AL)increased by 32.80%,9.00%,and 7.34%,respectively,while soil retention(SR)and food supply(FS)declined by 8.38%and 5.36%.Five distinct ESBs were identified,namely ecologically fragile bundle(EFB),agricultural production bundle(APB),water supply bundle(WSB),forest ecological bundle(FEB),and ecological conservation bundle(ECB).Among these,FEB expanded to more than 35.75%of the HRB,and APB exhibited the sharpest decline(-28.64%).Land use intensity(LUI)was the primary driver of the spatial heterogeneity of ESBs,while synergistic and nonlinear interactions among multiple factors increasingly amplified their effects over time.Notably,annual precipitation(AP)emerged as the only stable basin-scale driver,consistently enhancing ES performance,while gross domestic product(GDP)and normalized difference vegetation index(NDVI)had stable yet spatially differentiated effects across bundles.Our findings highlight the significance of distinguishing stable/unstable driver effects on ES dynamics to inform regionally adaptive ecosystem governance.The proposed framework provides valuable insights into ES interactions,identify spatial priorities,and support policy interventions that balance ecological conservation with socio-economic development.
文摘On October 9, Tianyang County’s government and Guangxi Baise Guangyin Aluminum Co., Ltd. signed an agreement on an aluminum processing project with an annual output
文摘Human well-being and livelihoods depend on natural ecosystem services(ESs).Following the increment of population,ESs have been deteriorated over time.Ultimately,land use/land cover(LULC)changes have a profound impact on the change of ecosystem.The primary goal of this study is to determine the impacts of LULC changes on ecosystem service values(ESVs)in the upper Gilgel Abbay watershed,Ethiopia.Changes in LULC types were studied using three Landsat images representing 1986,2003,and 2021.The Landsat images were classified using a supervised image classification technique in Earth Resources Data Analysis System(ERDAS)Imagine 2014.We classified ESs in this study into four categories(including provisioning,regulating,supporting,and cultural services)based on global ES classification scheme.The adjusted ESV coefficient benefit approach was employed to measure the impacts of LULC changes on ESVs.Five LULC types were identified in this study,including cultivated land,forest,shrubland,grassland,and water body.The result revealed that the area of cultivated land accounted for 64.50%,71.50%,and 61.50%of the total area in 1986,2003,and 2021,respectively.The percentage of the total area covered by forest was 9.50%,5.90%,and 14.80%in 1986,2003,and 2021,respectively.Result revealed that the total ESV decreased from 7.42×10^(7) to 6.44×10^(7) USD between 1986 and 2003.This is due to the expansion of cultivated land at the expense of forest and shrubland.However,the total ESV increased from 6.44×10^(7) to 7.76×10^(7) USD during 2003-2021,because of the increment of forest and shrubland.The expansion of cultivated land and the reductions of forest and shrubland reduced most individual ESs during 1986-2003.Nevertheless,the increase in forest and shrubland at the expense of cultivated land enhanced many ESs during 2003-2021.Therefore,the findings suggest that appropriate land use practices should be scaled-up to sustainably maintain ESs.
文摘The process of including renewable energy sources in power networks is moving quickly,so the need for innovative configuration solutions for grid-side ESS has grown.Among the new methods presented in this paper is GA-OCESE,which stands for Genetic Algorithm-based Optimization Configuration for Energy Storage in Electric Networks.This is one of the methods suggested in this study,which aims to enhance the sizing,positioning,and operational characteristics of structured ESS under dynamic grid conditions.Particularly,the aim is to maximize efficiency.A multiobjective genetic algorithm,the GA-OCESE framework,considers all these factors simultaneously.Besides considering cost-efficiency,response time,and energy use,the system also considers all these elements simultaneously.This enables it to effectively react to load uncertainty and variations in inputs connected to renewable sources.Results of an experimental assessment conducted on a standardized grid simulation platform indicate that by increasing energy use efficiency by 17.6%and reducing peak-load effects by 22.3%,GA-OCESE outperforms previous heuristic-based methods.This was found by contrasting the outcomes of the assessment with those of the evaluation.The results of the assessment helped to reveal this.The proposed approach will provide utility operators and energy planners with a decision-making tool that is both scalable and adaptable.This technology is particularly well-suited for smart grids,microgrid systems,and power infrastructures that heavily rely on renewable energy.Every technical component has been carefully recorded to ensure accuracy,reproducibility,and relevance across all power systems engineering software uses.This was done to ensure the program’s relevance.
文摘This article proposes a multi-tiered fault detection system for series-connected lithium-ion battery modules.Improper use of batteries can lead to electrolyte decomposition,resulting in the formation of lithium dendrites.These dendrites may pierce the separator,leading to the failure of the insulation layer between electrodes and causing micro short circuits.When a micro short circuit occurs,the electrolyte typically undergoes exothermic reactions,leading to thermal runaway and posing a safety risk to users.Relying solely on temperature-based judgment mechanisms within the battery management system often results in delayed intervention.To address this issue,the article develops a multi-tiered fault detection algorithm for series-connected lithium-ion batteries.This algorithm can effectively diagnose micro short circuits,aging,and normal batteries using minimal battery data,thereby improving diagnostic accuracy and enhancing the flexibility of fault detection.Simulations and experiments conducted under various levels of micro short circuits validate the effectiveness of the algorithm,demonstrating its ability to distinguish between short-circuited,aged,and normal batteries under different conditions.This technology can be applied to electric vehicles and energy storage systems,enabling early warnings to ensure safety and prevent thermal runaway.
