Changing climate conditions are known to influence forest tree growth response and the CO2 cycle. Dendroclimatological research has shown that the climate signal, species composition, and growth trends have changed in...Changing climate conditions are known to influence forest tree growth response and the CO2 cycle. Dendroclimatological research has shown that the climate signal, species composition, and growth trends have changed in different types of forest ecosystems during the last century. Under current and demonstrated changes in climate variability at the geographic, regional, and local levels tree growth shows also variability and trends that can be non-stationary during time even at relatively short distance between sites. In forest planning and management, yield tables, site quality indices, age class, rate of growth, and spatial distribution are some of the most used tools and parameters. However, these methods do not involve climate variability during time although climate is the main driver in trends of forest and tree growth. Previous research warns about the risk that forest management under changing climatic conditions could amplify their negative effects. For example, changing climate conditions may impact on temperature and/or precipitation thresholds critical to forest tree growth. Forest biomass, resilience, and CO2 storage may be damaged unless forest planning and management implement the relationships between climate variability and trends of tree growth. A positive aspect is that, periods of favorable climate conditions may allow harvesting higher amount of wood mass and storing more CO2 than traditional planning methods. And, the average length of both favorable and adverse periods appears to occur within the validity period of a forest management plan. Here, we show a conceptual development to implement climate variability in forest management in the view of continuing the research.展开更多
Latent heat thermal energy storage(TES)effectively reduces the mismatch between energy supply and demand of renewable energy sources by the utilization of phase change materials(PCMs).However,the low thermal conductiv...Latent heat thermal energy storage(TES)effectively reduces the mismatch between energy supply and demand of renewable energy sources by the utilization of phase change materials(PCMs).However,the low thermal conductivity and poor shape stability are the main drawbacks in realizing the large-scale application of PCMs.Promisingly,developing composite PCM(CPCM)based on porous supporting mate-rial provides a desirable solution to obtain performance-enhanced PCMs with improved effective thermal conductivity and shape stability.Among all the porous matrixes as supports for PCM,three-dimensional carbon-based porous supporting material has attracted considerable attention ascribing to its high ther-mal conductivity,desirable loading capacity of PCMs,and excellent chemical compatibility with various PCMs.Therefore,this work systemically reviews the CPCMs with three-dimensional carbon-based porous supporting materials.First,a concise rule for the fabrication of CPCMs is illustrated in detail.Next,the experimental and computational research of carbon nanotube-based support,graphene-based support,graphite-based support and amorphous carbon-based support are reviewed.Then,the applications of the shape-stabilized CPCMs including thermal management and thermal conversion are illustrated.Last but not least,the challenges and prospects of the CPCMs are discussed.To conclude,introducing carbon-based porous materials can solve the liquid leakage issue and essentially improve the thermal conductivity of PCMs.However,there is still a long way to further develop a desirable CPCM with higher latent heat capacity,higher thermal conductivity,and more excellent shape stability.展开更多
Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regime...Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.展开更多
BACKGROUND Atypical optic neuritis,consisting of neuromyelitis optica spectrum disorders(NMOSD)or myelin oligodendrocyte glycoprotein antibody disease(MOGAD),has a very similar presentation but different prognostic im...BACKGROUND Atypical optic neuritis,consisting of neuromyelitis optica spectrum disorders(NMOSD)or myelin oligodendrocyte glycoprotein antibody disease(MOGAD),has a very similar presentation but different prognostic implications and longterm management strategies.Vascular and metabolic factors are being thought to play a role in such autoimmune neuro-inflammatory disorders,apart from the obvious immune mediated damage.With the advent of optical coherence tomography angiography(OCTA),it is easy to pick up on these subclinical macular microvascular and structural changes.AIM To study the macular microvascular and structural changes on OCTA in atypical optic neuritis.METHODS This observational cross-sectional study involved 8 NMOSD and 17 MOGAD patients,diagnosed serologically,as well as 10 healthy controls.Macular vascular density(MVD)and ganglion cell+inner plexiform layer thickness(GCIPL)were studied using OCTA.RESULTS There was a significant reduction in MVD in NMOSD and MOGAD affected as well as unaffected eyes when compared with healthy controls.NMOSD and MOGAD affected eyes had significant GCIPL thinning compared with healthy controls.NMOSD unaffected eyes did not show significant GCIPL thinning compared to healthy controls in contrast to MOGAD unaffected eyes.On comparing NMOSD with MOGAD,there was no significant difference in terms of MVD or GCIPL in the affected or unaffected eyes.CONCLUSION Although significant microvascular and structural changes are present on OCTA between atypical optic neuritis and normal patients,they could not help in differentiating between NMOSD and MOGAD cases.展开更多
The toxicity of PM_(2.5)does not necessarily change synchronously with its mass concentration.In this study,the chemical composition(carbonaceous species,water-soluble ions,and metals)and oxidative potential(dithiothr...The toxicity of PM_(2.5)does not necessarily change synchronously with its mass concentration.In this study,the chemical composition(carbonaceous species,water-soluble ions,and metals)and oxidative potential(dithiothreitol assay,DTT)of PM_(2.5)were investigated in 2017/2018 and 2022 in Xiamen,China.The decrease rate of volume-normalized DTT(DTTv)(38%)was lower than that of PM_(2.5)(55%)between the two sampling periods.However,the mass-normalized DTT(DTTm)increased by 44%.Clear seasonal patterns with higher levels in winter were found for PM_(2.5),most chemical constituents and DTTv but not for DTTm.The large decrease in DTT activity(84%−92%)after the addition of EDTA suggested that watersoluble metals were the main contributors to DTT in Xiamen.The increased gap between the reconstructed and measured DTTv and the stronger correlations between the reconstructed/measured DTT ratio and carbonaceous species in 2022were observed.The decrease rates of the hazard index(32.5%)and lifetime cancer risk(9.1%)differed from those of PM_(2.5)and DTTv due to their different main contributors.The PMF-MLR model showed that the contributions(nmol/(min·m^(3)))of vehicle emission,coal+biomass burning,ship emission and secondary aerosol to DTTv in 2022 decreased by 63.0%,65.2%,66.5%,and 22.2%,respectively,compared to those in 2017/2018,which was consistent with the emission reduction of vehicle exhaust and coal consumption,the adoption of low-sulfur fuel oil used on board ships and the reduced production of WSOC.However,the contributions of dust+sea salt and industrial emission increased.展开更多
Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustaina...Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management.In this study,we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm(Helicoverpa armigera)in the adaptation to local environments and resilience to future climate change.Notably,the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades.Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm.Approximately 19,000 years ago,the cotton bollworm expanded from its ancestral African population,followed by gradual occupations of the European,Asian,Oceanian,and American continents.Furthermore,we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential.Additionally,a large number of candidate genes and SNPs linked to climatic adaptation were mapped.These findings could inform sustainable pest management strategies in the face of climate change,aiding future pest forecasting and management planning.展开更多
Gas-bearing shales have become a major source of future natural gas production worldwide.It has become increasingly urgent to develop a reliable prediction model and corresponding workflow for identifying shale gas sw...Gas-bearing shales have become a major source of future natural gas production worldwide.It has become increasingly urgent to develop a reliable prediction model and corresponding workflow for identifying shale gas sweet spots.The formation of gas-bearing shales is closely linked to relative sealevel changes,providing an important approach to predicting sweet spots in the Wufeng-Longmaxi shale in the southern Sichuan Basin,China.Three types of marine shale gas sweet spots are identified in the shale based on their formation stages combined with relative sea-level changes:early,middle,and late transgression types.This study develops a prediction model and workflow for identifying shale gas sweet spots by analyzing relative sea-level changes and facies sequences.Predicting shale gas sweet spots in an explored block using this model and workflow can provide a valuable guide for well design and hydraulic fracturing,significantly enhancing the efficiency of shale gas exploration and development.Notably,the new prediction model and workflow can be utilized for the rapid evaluation of the potential for shale gas development in new shale gas blocks or those with low exploratory maturity.展开更多
As global greenhouse gases continue rising,the urgency of more ambitious action is clearer than ever before.China is the world’s biggest emitter of greenhouse gases and one of the countries affected most by climate c...As global greenhouse gases continue rising,the urgency of more ambitious action is clearer than ever before.China is the world’s biggest emitter of greenhouse gases and one of the countries affected most by climate change.The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts.展开更多
Terrestrial ecosystems heavily depend on vegetation,which responds to carbon dioxide(CO_(2))fertilization in hot and humid regions.The subtropical humid karst region is a hot and humid region;whether and to what exten...Terrestrial ecosystems heavily depend on vegetation,which responds to carbon dioxide(CO_(2))fertilization in hot and humid regions.The subtropical humid karst region is a hot and humid region;whether and to what extent CO_(2)fertilization affects vegetation changes in such regions remains unclear.In this study,we investigated the degree to which CO_(2)fertilization influences vegetation changes,along with their spatial and temporal differences,in the subtropical humid karst region using time-lag effect analysis,a random forest model,and multiple regression analysis.Results showed that CO_(2)fertilization plays an important role in vegetation changes,exhibiting clear spatial variations across different geomorphological zones,with its degree of influence ranging mainly between 11%and 25%.The highest contribution of CO_(2)fertilization was observed in the karst basin and non-karstic region,whereas the lowest contribution was found in the karst plateau region.Previous studies have primarily attributed vegetation changes in subtropical humid karst region to ecological engineering,leading to an overestimation of its contribution to these changes.The findings of this study enhance the understanding of the mechanism of vegetation changes in humid karst region and provide theoretical and practical insights for ecological and environmental protection in these regions.展开更多
We adopted the solution impregnation route with aluminum dihydrogen phosphate solution as liquid medium for effective surface modification on graphite substrate.The mass ratio of graphite to Al(H_(2)PO_(4))_(3) change...We adopted the solution impregnation route with aluminum dihydrogen phosphate solution as liquid medium for effective surface modification on graphite substrate.The mass ratio of graphite to Al(H_(2)PO_(4))_(3) changed from 0.5:1 to 4:1,and the impregnation time changed from 1 to 7 h.The typical composite phase change thermal storage materials doped with the as-treated graphite were fabricated using form-stable technique.To investigate the oxidation and anti-oxidation behavior of the impregnated graphite at high temperatures,the samples were put into a muffle furnace for a cyclic heat test.Based on SEM,EDS,DSC techniques,analyses on the impregnated technique suggested an optimized processing conditions of a 3 h impregnation time with the ratio of graphite:Al(H_(2)PO_(4))_(3) as 1:3 for graphite impregnation treatment.Further investigations on high-temperature phase change heat storage materials doped by the treated graphite suggested excellent oxidation resistance and thermal cycling performance.展开更多
Climate change and anthropogenic activities have driven significant terrestrial water storage changes(TWSC)in the Three Rivers Source Region(TRSR),exerting profound impacts on freshwater availability across China and ...Climate change and anthropogenic activities have driven significant terrestrial water storage changes(TWSC)in the Three Rivers Source Region(TRSR),exerting profound impacts on freshwater availability across China and broader Asia.However,long-term TWSC characterization remains challenging due to limited observational data in this alpine region.Here,we integrate GRACE observations(2002-2020),ERA5-Land reanalysis,and GLDAS data to reconstruct TWSC using two methods:(1)the water balance method(PER)and(2)the component summation method(SS),applied to three input datasets(ERA5-Land,GLDAS,and their average,GLER).Comparative analysis reveals that the SS method applied to GL-ER yields the highest consistency with GRACE-derived TWSC.Using this optimal approach,we extend the analysis to 1951~2020,uncovering spatiotemporal TWSC patterns.Although annual TWSC trends appear negligible due to strong seasonality,we introduce the intra-year TWSC fluctuation(TWSCF)index to quantify cumulative variability.A significant(p<0.05)transition occurred in 1980,with TWSCF shifting from a declining trend(-0.39 mm/yr)to an increasing trend(0.56 mm/yr),primarily driven by soil moisture changes.However,Hurst exponent analysis suggests this upward trend may not persist.Drought and vegetation assessments indicate concurrent wetting and greening in the TRSR.TWSC correlates strongly with meteorological drought,acting as a reliable drought indicator while its linkage with vegetation dynamics suggests a potential contribution to greening.Our findings provide a robust framework for understanding long-term TWSC evolution and its hydrological-ecological interactions under climate change.展开更多
BACKGROUND Dyslipidemia was strongly linked to stroke,however the relationship between dyslipidemia and its components and ischemic stroke remained unexplained.AIM To investigate the link between longitudinal changes ...BACKGROUND Dyslipidemia was strongly linked to stroke,however the relationship between dyslipidemia and its components and ischemic stroke remained unexplained.AIM To investigate the link between longitudinal changes in lipid profiles and dyslipidemia and ischemic stroke in a hypertensive population.METHODS Between 2013 and 2014,6094 hypertension individuals were included in this,and ischemic stroke cases were documented to the end of 2018.Longitudinal changes of lipid were stratified into four groups:(1)Normal was transformed into normal group;(2)Abnormal was transformed into normal group;(3)Normal was transformed into abnormal group;and(4)Abnormal was transformed into abnormal group.To examine the link between longitudinal changes in dyslipidemia along with its components and the risk of ischemic stroke,we utilized multivariate Cox proportional hazards models with hazard ratio(HR)and 95%CI.RESULTS The average age of the participants was 62.32 years±13.00 years,with 329 women making up 54.0%of the sample.Over the course of a mean follow-up of 4.8 years,143 ischemic strokes happened.When normal was transformed into normal group was used as a reference,after full adjustments,the HR for dyslipidemia and ischemic stroke among abnormal was transformed into normal group,normal was transformed into abnormal group and abnormal was transformed into abnormal Wei CC et al.Dyslipidemia changed and ischemic stroke WJCC https://www.wjgnet.com 2 February 6,2025 Volume 13 Issue 4 group were 1.089(95%CI:0.598-1.982;P=0.779),2.369(95%CI:1.424-3.941;P<0.001)and 1.448(95%CI:1.002-2.298;P=0.047)(P for trend was 0.233),respectively.CONCLUSION In individuals with hypertension,longitudinal shifts from normal to abnormal in dyslipidemia-particularly in total and low-density lipoprotein cholesterol-were significantly associated with the risk of ischemic stroke.展开更多
Oriented graphene aerogels have limited applica-tions because the flexibility of their graphene sheets and mi-crostructure give them a low skeleton strength,insufficient compression resilience,and poor flexibility.We ...Oriented graphene aerogels have limited applica-tions because the flexibility of their graphene sheets and mi-crostructure give them a low skeleton strength,insufficient compression resilience,and poor flexibility.We report the preparation of novel aerogel materials with a much better per-formance.Using the driving force of graphene oxide(GO)self-assembly andπ-πinteractions,carbon nanotubes(CNTs)were attached to the GO sheets,and an oriented composite carbon skeleton was constructed using“hydro-plastic foam-ing”.The introduction of CNTs significantly increased the strength of the skeleton and gave the aerogel an excellent re-versible compressibility.The innovative use of cold pressing greatly improved the thermal conductivity and flexibility of the aerogel,providing new ideas for the development of high-performance aerogels.Tests show that the obtained graphene composite aerogel has a reversible compressive strain of over 90%and can withstand 500 compression cycles along the direc-tion of pore accumulation.It can endure more than 10000 bending cycles perpendicular to the direction of composite carbon layer stacking,and its in-plane thermal conductivity reaches 64.5 W·m^(-1)·K^(-1).When filled with phase change materials,the high porosity of the carbon skeleton enables the material to have a high phase change filling rate,and its phase change enthalpy is greater than 150 J/g.Thanks to the exceptional flexibility of the carbon skeleton,the macrostructure of phase change materials can be bent as needed to adapt to thermal management scenarios and conform to device shapes.This significantly enhances practical application compatibility,providing flexible support for temperature control and thermal management across diverse device forms.展开更多
Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accura...Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.展开更多
We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other ...We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other countries will require the rapid construction of communities capable of supporting them, their families, businesses and farms. However, different political-economic conditions are found across the areas which can serve as locations for these Climate Change Haven Communities. We develop funding and construction strategies for the United States (free-market capitalism), France and Spain (European Union supported economies), and Taiwan region (state-directed economy). The proposals for the Taiwan region should also be applicable to the rest of China.展开更多
To address climate change and highlight its global nature,the United Nations Framework Convention on Climate Change(UNFCCC)was adopted for the first time in history within the UN framework on May 9,1992,clearly establ...To address climate change and highlight its global nature,the United Nations Framework Convention on Climate Change(UNFCCC)was adopted for the first time in history within the UN framework on May 9,1992,clearly establishing the obligations of developed countries to take the lead in emission reduction and provide financial,technological,and capacity-building support to developing countries.Particularly since the 2015 Paris Agreement,successive UN climate conferences have placed high emphasis on financial and technological matters,with financial arrangements demonstrating an increasingly specific trend in recent years.The Glasgow Climate Pact adopted in 2021 urges developed country Parties to deliver on their commitment to the goal of providing USD 100 billion to developing country prties,while also urging developed country parties to at least double their provision of climate finance to developing country parties by 2025 compared to 2019 levels.展开更多
Low-carbon urban development in China can pave the way to achieve the dualcarbon goal.Exploring how land use changes(LUCs)impact carbon storage(CS)under multi-climate scenarios in different urban agglomerations helps ...Low-carbon urban development in China can pave the way to achieve the dualcarbon goal.Exploring how land use changes(LUCs)impact carbon storage(CS)under multi-climate scenarios in different urban agglomerations helps to formulate differential scientific carbon mitigation policies.In this regard,this study constructs an integrated model of SD-PLUS-InVEST to simulate LUCs and CS changes under multi-climate change-based scenarios(SSP126,SSP245,SSP585)for three major urban agglomerations(3UAs)in the Yangtze River Economic Belt.Results demonstrate that land use demand in the 3UAs changes considerably in each scenario.Construction land in the 3UAs remains the most important growth category for the coming decade,but its increase varies in different scenarios.CS in the Yangtze River Delta Urban Agglomeration(YRDUA)and Mid-Yangtze River Urban Agglomeration(MYRUA)shows a similar downward trend under different scenarios,with scenario SSP245 decreasing the most,to 184,713.526 Tg and 384,459.729 Tg,respectively.CS in the Cheng-Yu(Chengdu-Chongqing)Urban Agglomeration(CYUA)exhibits the opposite upward trend,with scenario SSP126 increasing the most to 153,007.973 Tg.The major cause of CS loss remains the conversion of forest land to construction land in the YRDUA and MYRUA under different scenarios.However,in the CYUA,the conversion of forest land to cultivated land is the major driver of CS loss under scenario SSP126.In contrast,the conversion of cultivated land to construction land dominantly drives CS loss under scenarios SSP245 and SSP585.The conversion of water body to other land use types is the major cause of CS gain in the YRDUA and MYRUA under different scenarios.At the same time,in the CYUA,the driver is the conversion of cultivated land to forest land.These findings demonstrate the significance of the low-carbon development in urban agglomerations at different development stages at home and abroad.展开更多
Climate warming and humidification trends have significantly influenced vegetation growth patterns in Chinese semi-arid areas.Exploring vegetation dynamics is crucial for understanding regional ecosystem structure and...Climate warming and humidification trends have significantly influenced vegetation growth patterns in Chinese semi-arid areas.Exploring vegetation dynamics is crucial for understanding regional ecosystem structure and improving the efforts of ecosystem restoration.However,the applicability of various vegetation indices(VIs)in these arid areas remains uncertain.Evaluating the applicability of multiple VIs for vegetation monitoring can elucidate the variability of VIs performance at regional scale.Therefore,this study selected the Zuli River Basin(ZLRB),a typical loess hilly watershed in the semi-arid areas of China.Using Landsat data,we calculated the Normalized Difference Vegetation Index(NDVI),Enhanced Vegetation Index(EVI),and kernel NDVI(kNDVI)for the ZLRB from 1990 to 2020.We analyzed the spatiotemporal variations of these VIs using trend analysis and the Mann-Kendall test,and quantified the contributions of climate change(considering time-lag effects)and human activities to VIs changes through wavelet and residual analyses.Results indicated that VIs generally exhibited an upward trend in the ZLRB,with significant improvements observed in 54.91% of the area for NDVI,31.69% for EVI,and 33.71% for kNDVI.Among them,NDVI outperformed EVI and kNDVI in capturing vegetation changes in the semi-arid area.VIs responded to precipitation with 1-month time lag and no time lag to temperature during growing season.Moreover,precipitation had a stronger positive correlation with VIs than temperature.Climate change was identified as the dominant driver of vegetation dynamics in the ZLRB,accounting for 93.12% of NDVI variation,while human activities contributed only 6.88%.Comparative analysis of VIs suggests that NDVI was more suitable for describing vegetation changes in the typical arid area of the ZLRB.Our findings underscore the importance of selecting appropriate VIs for targeted ecological restoration and sustainable land management.展开更多
There have been an increasing number of studies on climate change and population health over the past 20 years,with most focusing on health risk assessment,targeting different locations and populations with various di...There have been an increasing number of studies on climate change and population health over the past 20 years,with most focusing on health risk assessment,targeting different locations and populations with various diseases[1−2].While these studies have provided the necessary epidemiological evidence for health authorities in policymaking,it is time to develop and implement tailored health interventions to protect the health and well-being of communities,and particularly that of vulnerable groups.展开更多
文摘Changing climate conditions are known to influence forest tree growth response and the CO2 cycle. Dendroclimatological research has shown that the climate signal, species composition, and growth trends have changed in different types of forest ecosystems during the last century. Under current and demonstrated changes in climate variability at the geographic, regional, and local levels tree growth shows also variability and trends that can be non-stationary during time even at relatively short distance between sites. In forest planning and management, yield tables, site quality indices, age class, rate of growth, and spatial distribution are some of the most used tools and parameters. However, these methods do not involve climate variability during time although climate is the main driver in trends of forest and tree growth. Previous research warns about the risk that forest management under changing climatic conditions could amplify their negative effects. For example, changing climate conditions may impact on temperature and/or precipitation thresholds critical to forest tree growth. Forest biomass, resilience, and CO2 storage may be damaged unless forest planning and management implement the relationships between climate variability and trends of tree growth. A positive aspect is that, periods of favorable climate conditions may allow harvesting higher amount of wood mass and storing more CO2 than traditional planning methods. And, the average length of both favorable and adverse periods appears to occur within the validity period of a forest management plan. Here, we show a conceptual development to implement climate variability in forest management in the view of continuing the research.
基金supported by the National Natural Science Foundation of China(No.52127816),the National Key Research and Development Program of China(No.2020YFA0715000)the National Natural Science and Hong Kong Research Grant Council Joint Research Funding Project of China(No.5181101182)the NSFC/RGC Joint Research Scheme sponsored by the Research Grants Council of Hong Kong and the National Natural Science Foundation of China(No.N_PolyU513/18).
文摘Latent heat thermal energy storage(TES)effectively reduces the mismatch between energy supply and demand of renewable energy sources by the utilization of phase change materials(PCMs).However,the low thermal conductivity and poor shape stability are the main drawbacks in realizing the large-scale application of PCMs.Promisingly,developing composite PCM(CPCM)based on porous supporting mate-rial provides a desirable solution to obtain performance-enhanced PCMs with improved effective thermal conductivity and shape stability.Among all the porous matrixes as supports for PCM,three-dimensional carbon-based porous supporting material has attracted considerable attention ascribing to its high ther-mal conductivity,desirable loading capacity of PCMs,and excellent chemical compatibility with various PCMs.Therefore,this work systemically reviews the CPCMs with three-dimensional carbon-based porous supporting materials.First,a concise rule for the fabrication of CPCMs is illustrated in detail.Next,the experimental and computational research of carbon nanotube-based support,graphene-based support,graphite-based support and amorphous carbon-based support are reviewed.Then,the applications of the shape-stabilized CPCMs including thermal management and thermal conversion are illustrated.Last but not least,the challenges and prospects of the CPCMs are discussed.To conclude,introducing carbon-based porous materials can solve the liquid leakage issue and essentially improve the thermal conductivity of PCMs.However,there is still a long way to further develop a desirable CPCM with higher latent heat capacity,higher thermal conductivity,and more excellent shape stability.
基金supported by the funding Riset Unggulan Daerah 2022 of the Bureau of Development Planning and Research in Central Java Province(BAPPEDA Provinsi Jawa Tengah).
文摘Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.
文摘BACKGROUND Atypical optic neuritis,consisting of neuromyelitis optica spectrum disorders(NMOSD)or myelin oligodendrocyte glycoprotein antibody disease(MOGAD),has a very similar presentation but different prognostic implications and longterm management strategies.Vascular and metabolic factors are being thought to play a role in such autoimmune neuro-inflammatory disorders,apart from the obvious immune mediated damage.With the advent of optical coherence tomography angiography(OCTA),it is easy to pick up on these subclinical macular microvascular and structural changes.AIM To study the macular microvascular and structural changes on OCTA in atypical optic neuritis.METHODS This observational cross-sectional study involved 8 NMOSD and 17 MOGAD patients,diagnosed serologically,as well as 10 healthy controls.Macular vascular density(MVD)and ganglion cell+inner plexiform layer thickness(GCIPL)were studied using OCTA.RESULTS There was a significant reduction in MVD in NMOSD and MOGAD affected as well as unaffected eyes when compared with healthy controls.NMOSD and MOGAD affected eyes had significant GCIPL thinning compared with healthy controls.NMOSD unaffected eyes did not show significant GCIPL thinning compared to healthy controls in contrast to MOGAD unaffected eyes.On comparing NMOSD with MOGAD,there was no significant difference in terms of MVD or GCIPL in the affected or unaffected eyes.CONCLUSION Although significant microvascular and structural changes are present on OCTA between atypical optic neuritis and normal patients,they could not help in differentiating between NMOSD and MOGAD cases.
基金supported by the Science and Technology Program of Fujian Province,China(No.2023R1014002)the National Natural Science Foundation of China(No.41471390).
文摘The toxicity of PM_(2.5)does not necessarily change synchronously with its mass concentration.In this study,the chemical composition(carbonaceous species,water-soluble ions,and metals)and oxidative potential(dithiothreitol assay,DTT)of PM_(2.5)were investigated in 2017/2018 and 2022 in Xiamen,China.The decrease rate of volume-normalized DTT(DTTv)(38%)was lower than that of PM_(2.5)(55%)between the two sampling periods.However,the mass-normalized DTT(DTTm)increased by 44%.Clear seasonal patterns with higher levels in winter were found for PM_(2.5),most chemical constituents and DTTv but not for DTTm.The large decrease in DTT activity(84%−92%)after the addition of EDTA suggested that watersoluble metals were the main contributors to DTT in Xiamen.The increased gap between the reconstructed and measured DTTv and the stronger correlations between the reconstructed/measured DTT ratio and carbonaceous species in 2022were observed.The decrease rates of the hazard index(32.5%)and lifetime cancer risk(9.1%)differed from those of PM_(2.5)and DTTv due to their different main contributors.The PMF-MLR model showed that the contributions(nmol/(min·m^(3)))of vehicle emission,coal+biomass burning,ship emission and secondary aerosol to DTTv in 2022 decreased by 63.0%,65.2%,66.5%,and 22.2%,respectively,compared to those in 2017/2018,which was consistent with the emission reduction of vehicle exhaust and coal consumption,the adoption of low-sulfur fuel oil used on board ships and the reduced production of WSOC.However,the contributions of dust+sea salt and industrial emission increased.
基金funded by the National Natural Science Foundation of China(32372546)Shenzhen Science and Technology Program(KQTD20180411143628272)+1 种基金the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences and STI 2030-Major Projects(2022ZD04021)the National Key Research and Development Program of China(2023YFD2200700)。
文摘Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management.In this study,we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm(Helicoverpa armigera)in the adaptation to local environments and resilience to future climate change.Notably,the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades.Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm.Approximately 19,000 years ago,the cotton bollworm expanded from its ancestral African population,followed by gradual occupations of the European,Asian,Oceanian,and American continents.Furthermore,we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential.Additionally,a large number of candidate genes and SNPs linked to climatic adaptation were mapped.These findings could inform sustainable pest management strategies in the face of climate change,aiding future pest forecasting and management planning.
文摘Gas-bearing shales have become a major source of future natural gas production worldwide.It has become increasingly urgent to develop a reliable prediction model and corresponding workflow for identifying shale gas sweet spots.The formation of gas-bearing shales is closely linked to relative sealevel changes,providing an important approach to predicting sweet spots in the Wufeng-Longmaxi shale in the southern Sichuan Basin,China.Three types of marine shale gas sweet spots are identified in the shale based on their formation stages combined with relative sea-level changes:early,middle,and late transgression types.This study develops a prediction model and workflow for identifying shale gas sweet spots by analyzing relative sea-level changes and facies sequences.Predicting shale gas sweet spots in an explored block using this model and workflow can provide a valuable guide for well design and hydraulic fracturing,significantly enhancing the efficiency of shale gas exploration and development.Notably,the new prediction model and workflow can be utilized for the rapid evaluation of the potential for shale gas development in new shale gas blocks or those with low exploratory maturity.
基金supported by the National Natural Science Foundation of China(No.82025030,No.72394404)the National Key Research and Development Program of China(No.2022YFC3702700)the National Research Program for Key Issues in Air Pollution Control of China(No.DQGG0401).
文摘As global greenhouse gases continue rising,the urgency of more ambitious action is clearer than ever before.China is the world’s biggest emitter of greenhouse gases and one of the countries affected most by climate change.The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts.
基金National Natural Science Foundation of China,No.41761003The Karst Science Research Center of Guizhou Province,No.U1812401。
文摘Terrestrial ecosystems heavily depend on vegetation,which responds to carbon dioxide(CO_(2))fertilization in hot and humid regions.The subtropical humid karst region is a hot and humid region;whether and to what extent CO_(2)fertilization affects vegetation changes in such regions remains unclear.In this study,we investigated the degree to which CO_(2)fertilization influences vegetation changes,along with their spatial and temporal differences,in the subtropical humid karst region using time-lag effect analysis,a random forest model,and multiple regression analysis.Results showed that CO_(2)fertilization plays an important role in vegetation changes,exhibiting clear spatial variations across different geomorphological zones,with its degree of influence ranging mainly between 11%and 25%.The highest contribution of CO_(2)fertilization was observed in the karst basin and non-karstic region,whereas the lowest contribution was found in the karst plateau region.Previous studies have primarily attributed vegetation changes in subtropical humid karst region to ecological engineering,leading to an overestimation of its contribution to these changes.The findings of this study enhance the understanding of the mechanism of vegetation changes in humid karst region and provide theoretical and practical insights for ecological and environmental protection in these regions.
基金Funded by Scientific and Technological Innovation Project of Carbon Emission Peak and Carbon Neutrality of Jiangsu Province(No.BE2022028-4)。
文摘We adopted the solution impregnation route with aluminum dihydrogen phosphate solution as liquid medium for effective surface modification on graphite substrate.The mass ratio of graphite to Al(H_(2)PO_(4))_(3) changed from 0.5:1 to 4:1,and the impregnation time changed from 1 to 7 h.The typical composite phase change thermal storage materials doped with the as-treated graphite were fabricated using form-stable technique.To investigate the oxidation and anti-oxidation behavior of the impregnated graphite at high temperatures,the samples were put into a muffle furnace for a cyclic heat test.Based on SEM,EDS,DSC techniques,analyses on the impregnated technique suggested an optimized processing conditions of a 3 h impregnation time with the ratio of graphite:Al(H_(2)PO_(4))_(3) as 1:3 for graphite impregnation treatment.Further investigations on high-temperature phase change heat storage materials doped by the treated graphite suggested excellent oxidation resistance and thermal cycling performance.
基金funded by the Postdoctoral Research Startup Foundation of University of Jinan(Grant No.100389917).
文摘Climate change and anthropogenic activities have driven significant terrestrial water storage changes(TWSC)in the Three Rivers Source Region(TRSR),exerting profound impacts on freshwater availability across China and broader Asia.However,long-term TWSC characterization remains challenging due to limited observational data in this alpine region.Here,we integrate GRACE observations(2002-2020),ERA5-Land reanalysis,and GLDAS data to reconstruct TWSC using two methods:(1)the water balance method(PER)and(2)the component summation method(SS),applied to three input datasets(ERA5-Land,GLDAS,and their average,GLER).Comparative analysis reveals that the SS method applied to GL-ER yields the highest consistency with GRACE-derived TWSC.Using this optimal approach,we extend the analysis to 1951~2020,uncovering spatiotemporal TWSC patterns.Although annual TWSC trends appear negligible due to strong seasonality,we introduce the intra-year TWSC fluctuation(TWSCF)index to quantify cumulative variability.A significant(p<0.05)transition occurred in 1980,with TWSCF shifting from a declining trend(-0.39 mm/yr)to an increasing trend(0.56 mm/yr),primarily driven by soil moisture changes.However,Hurst exponent analysis suggests this upward trend may not persist.Drought and vegetation assessments indicate concurrent wetting and greening in the TRSR.TWSC correlates strongly with meteorological drought,acting as a reliable drought indicator while its linkage with vegetation dynamics suggests a potential contribution to greening.Our findings provide a robust framework for understanding long-term TWSC evolution and its hydrological-ecological interactions under climate change.
文摘BACKGROUND Dyslipidemia was strongly linked to stroke,however the relationship between dyslipidemia and its components and ischemic stroke remained unexplained.AIM To investigate the link between longitudinal changes in lipid profiles and dyslipidemia and ischemic stroke in a hypertensive population.METHODS Between 2013 and 2014,6094 hypertension individuals were included in this,and ischemic stroke cases were documented to the end of 2018.Longitudinal changes of lipid were stratified into four groups:(1)Normal was transformed into normal group;(2)Abnormal was transformed into normal group;(3)Normal was transformed into abnormal group;and(4)Abnormal was transformed into abnormal group.To examine the link between longitudinal changes in dyslipidemia along with its components and the risk of ischemic stroke,we utilized multivariate Cox proportional hazards models with hazard ratio(HR)and 95%CI.RESULTS The average age of the participants was 62.32 years±13.00 years,with 329 women making up 54.0%of the sample.Over the course of a mean follow-up of 4.8 years,143 ischemic strokes happened.When normal was transformed into normal group was used as a reference,after full adjustments,the HR for dyslipidemia and ischemic stroke among abnormal was transformed into normal group,normal was transformed into abnormal group and abnormal was transformed into abnormal Wei CC et al.Dyslipidemia changed and ischemic stroke WJCC https://www.wjgnet.com 2 February 6,2025 Volume 13 Issue 4 group were 1.089(95%CI:0.598-1.982;P=0.779),2.369(95%CI:1.424-3.941;P<0.001)and 1.448(95%CI:1.002-2.298;P=0.047)(P for trend was 0.233),respectively.CONCLUSION In individuals with hypertension,longitudinal shifts from normal to abnormal in dyslipidemia-particularly in total and low-density lipoprotein cholesterol-were significantly associated with the risk of ischemic stroke.
文摘Oriented graphene aerogels have limited applica-tions because the flexibility of their graphene sheets and mi-crostructure give them a low skeleton strength,insufficient compression resilience,and poor flexibility.We report the preparation of novel aerogel materials with a much better per-formance.Using the driving force of graphene oxide(GO)self-assembly andπ-πinteractions,carbon nanotubes(CNTs)were attached to the GO sheets,and an oriented composite carbon skeleton was constructed using“hydro-plastic foam-ing”.The introduction of CNTs significantly increased the strength of the skeleton and gave the aerogel an excellent re-versible compressibility.The innovative use of cold pressing greatly improved the thermal conductivity and flexibility of the aerogel,providing new ideas for the development of high-performance aerogels.Tests show that the obtained graphene composite aerogel has a reversible compressive strain of over 90%and can withstand 500 compression cycles along the direc-tion of pore accumulation.It can endure more than 10000 bending cycles perpendicular to the direction of composite carbon layer stacking,and its in-plane thermal conductivity reaches 64.5 W·m^(-1)·K^(-1).When filled with phase change materials,the high porosity of the carbon skeleton enables the material to have a high phase change filling rate,and its phase change enthalpy is greater than 150 J/g.Thanks to the exceptional flexibility of the carbon skeleton,the macrostructure of phase change materials can be bent as needed to adapt to thermal management scenarios and conform to device shapes.This significantly enhances practical application compatibility,providing flexible support for temperature control and thermal management across diverse device forms.
文摘Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.
文摘We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other countries will require the rapid construction of communities capable of supporting them, their families, businesses and farms. However, different political-economic conditions are found across the areas which can serve as locations for these Climate Change Haven Communities. We develop funding and construction strategies for the United States (free-market capitalism), France and Spain (European Union supported economies), and Taiwan region (state-directed economy). The proposals for the Taiwan region should also be applicable to the rest of China.
文摘To address climate change and highlight its global nature,the United Nations Framework Convention on Climate Change(UNFCCC)was adopted for the first time in history within the UN framework on May 9,1992,clearly establishing the obligations of developed countries to take the lead in emission reduction and provide financial,technological,and capacity-building support to developing countries.Particularly since the 2015 Paris Agreement,successive UN climate conferences have placed high emphasis on financial and technological matters,with financial arrangements demonstrating an increasingly specific trend in recent years.The Glasgow Climate Pact adopted in 2021 urges developed country Parties to deliver on their commitment to the goal of providing USD 100 billion to developing country prties,while also urging developed country parties to at least double their provision of climate finance to developing country parties by 2025 compared to 2019 levels.
基金Key Project of National Social Science Fund,No.23AZD032National Natural Science Foundation of China No.42371258Program of China Scholarship Council No.202306850036。
文摘Low-carbon urban development in China can pave the way to achieve the dualcarbon goal.Exploring how land use changes(LUCs)impact carbon storage(CS)under multi-climate scenarios in different urban agglomerations helps to formulate differential scientific carbon mitigation policies.In this regard,this study constructs an integrated model of SD-PLUS-InVEST to simulate LUCs and CS changes under multi-climate change-based scenarios(SSP126,SSP245,SSP585)for three major urban agglomerations(3UAs)in the Yangtze River Economic Belt.Results demonstrate that land use demand in the 3UAs changes considerably in each scenario.Construction land in the 3UAs remains the most important growth category for the coming decade,but its increase varies in different scenarios.CS in the Yangtze River Delta Urban Agglomeration(YRDUA)and Mid-Yangtze River Urban Agglomeration(MYRUA)shows a similar downward trend under different scenarios,with scenario SSP245 decreasing the most,to 184,713.526 Tg and 384,459.729 Tg,respectively.CS in the Cheng-Yu(Chengdu-Chongqing)Urban Agglomeration(CYUA)exhibits the opposite upward trend,with scenario SSP126 increasing the most to 153,007.973 Tg.The major cause of CS loss remains the conversion of forest land to construction land in the YRDUA and MYRUA under different scenarios.However,in the CYUA,the conversion of forest land to cultivated land is the major driver of CS loss under scenario SSP126.In contrast,the conversion of cultivated land to construction land dominantly drives CS loss under scenarios SSP245 and SSP585.The conversion of water body to other land use types is the major cause of CS gain in the YRDUA and MYRUA under different scenarios.At the same time,in the CYUA,the driver is the conversion of cultivated land to forest land.These findings demonstrate the significance of the low-carbon development in urban agglomerations at different development stages at home and abroad.
基金funded by the National Natural Science Foundation of China(U21A2011).
文摘Climate warming and humidification trends have significantly influenced vegetation growth patterns in Chinese semi-arid areas.Exploring vegetation dynamics is crucial for understanding regional ecosystem structure and improving the efforts of ecosystem restoration.However,the applicability of various vegetation indices(VIs)in these arid areas remains uncertain.Evaluating the applicability of multiple VIs for vegetation monitoring can elucidate the variability of VIs performance at regional scale.Therefore,this study selected the Zuli River Basin(ZLRB),a typical loess hilly watershed in the semi-arid areas of China.Using Landsat data,we calculated the Normalized Difference Vegetation Index(NDVI),Enhanced Vegetation Index(EVI),and kernel NDVI(kNDVI)for the ZLRB from 1990 to 2020.We analyzed the spatiotemporal variations of these VIs using trend analysis and the Mann-Kendall test,and quantified the contributions of climate change(considering time-lag effects)and human activities to VIs changes through wavelet and residual analyses.Results indicated that VIs generally exhibited an upward trend in the ZLRB,with significant improvements observed in 54.91% of the area for NDVI,31.69% for EVI,and 33.71% for kNDVI.Among them,NDVI outperformed EVI and kNDVI in capturing vegetation changes in the semi-arid area.VIs responded to precipitation with 1-month time lag and no time lag to temperature during growing season.Moreover,precipitation had a stronger positive correlation with VIs than temperature.Climate change was identified as the dominant driver of vegetation dynamics in the ZLRB,accounting for 93.12% of NDVI variation,while human activities contributed only 6.88%.Comparative analysis of VIs suggests that NDVI was more suitable for describing vegetation changes in the typical arid area of the ZLRB.Our findings underscore the importance of selecting appropriate VIs for targeted ecological restoration and sustainable land management.
文摘There have been an increasing number of studies on climate change and population health over the past 20 years,with most focusing on health risk assessment,targeting different locations and populations with various diseases[1−2].While these studies have provided the necessary epidemiological evidence for health authorities in policymaking,it is time to develop and implement tailored health interventions to protect the health and well-being of communities,and particularly that of vulnerable groups.
