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Airborne microorganisms (AM) have significant environmental and health implications. Extensive studies have been conducted to investigate the factors influencing the composition and diversity of AM. However, the knowledge of AM with anthropogenic activities has not reach a consensus. In this study, we took advantage of the dramatic decline of outdoor anthropogenic activities resulting from COVID-19 lockdown to reveal their associations. We collected airborne particulate matter before and during the lockdown period in two cities. The results showed that it was fungal diversity and communities but not bacteria obviously different between pre-lockdown and lockdown samples, suggesting that airborne fungi were more susceptible to anthropogenic activities than bacteria. However, after the implementation of lockdown, the co-occurrence networks of both bacterial and fungal community became more complex, which might be due to the variation of microbial sources. Furthermore, Mantel test and correlation analysis showed that air pollutants also partly contributed to microbial alterations. Airborne fungal community was more affected by air pollutants than bacterial community. Notably, some human pathogens like Nigrospora and Arthrinium were negatively correlated with air pollutants. Overall, our study highlighted the more impacts of anthropogenic activities on airborne fungal community than bacterial community and advanced the understanding of associations between anthropogenic activities and AM.

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Wetlands are highly diverse and productive and are among the three most important natural ecosystems worldwide, among which coastal wetlands are particularly valuable because they have been shown to provide important functions for human populations. They provide a wide variety of ecological services and values that are critical to humans. Their value may increase with increased use or scarcity owing to human progress, such as agriculture and urbanization. The potential assessment for one coastal wetland habitat to be substituted by another landscape depends on analyzing complex microbial communities including fungi, bacteria, viruses, and protozoa common in different wetlands. Moreover, the number and quality of resources in coastal wetlands, including nutrients and energy sources, are also closely related to the size and variety of the microbial communities. In this review, we discussed types of wetlands, how human activities had altered the carbon cycle, how climate change affected wetland services and functions, and identified some ways to promote their conservation and restoration that provide a range of benefits, including carbon sequestration. Current data also indicated that the coastal ocean acted as a net sink for atmospheric carbon dioxide in a post-industrial age and continuous human pressure would make a major impact on the evolution the coastal ocean carbon budget in the future. Coastal wetland ecosystems contain diverse microbial communities, and their composition of microbial communities will tend to change rapidly in response to environmental changes, as can serve as significant markers for identifying these changes in the future.

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Coastal areas are regions of active interaction between the sea and land and are highly sensitive to changes in heavy metal contamination caused by natural and anthropogenic activities. The contents of heavy metals in 80 surface sediments in the Qizhou Island sea area in the northeast of Hainan Island were determined to assess the contamination status, spatial distribution, sources, and ecological risks. The results indicate that the main factors influencing the distribution patterns and contents of heavy metals are hydrodynamic conditions and sources of materials. The accumulation of Cd and Pb in the sediments is attributed to the combined effects of natural sources and anthropogenic input. In addition to widespread anthropogenic influence, the enrichment of Cd in the southeastern outer shelf area of the study region may be controlled by biogenic carbonate rocks or enhanced input of near-source materials during the late Pleistocene low sea level period.

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Pollution control and environmental protection of the Yangtze River have received major attention in China. However, modeling the river's pollution load remains challenging due to limited monitoring and unclear spatiotemporal distribution of pollution sources. Specifically, anthropogenic activities' contribution to the pollution have been underestimated in previous research. Here, we coupled a hydrodynamic-based water quality (HWQ) model with a machine learning (ML) model, namely attention-based Gated Recurrent Unit, to decipher the daily pollution loads (i.e., chemical oxygen demand, COD; total phosphorus, TP) and their sources in the Middle-Lower Yangtze River from 2014 to 2018. The coupled HWQ-ML model outperformed the standalone ML model with KGE values ranging 0.77-0.91 for COD and 0.47-0.64 for TP, while also reducing parameter uncertainty. When examining the relative contributions at the Middle Yangtze River Hankou cross-section, we observed that the main stream and tributaries, lateral anthropogenic discharges, and parameter uncertainty contributed 15, 66, and 19% to COD, and 58, 35, and 7% to TP, respectively. For the Lower Yangtze River Datong cross-section, the contributions were 6, 69, and 25% for COD and 41, 42, and 17% for TP. According to the attention weights of the coupled model, the primary drivers of lateral anthropogenic pollution sources, in descending order of importance, were temperature, date, and precipitation, reflecting seasonal pollution discharge, industrial effluent, and first flush effect and combined sewer overflows, respectively. This study emphasizes the synergy between physical modeling and machine learning, offering new insights into pollution load dynamics in the Yangtze River.

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To address severe soil Pb and Cd contamination from anthropogenic activities, governments have implemented various environmental management measures. However, the extent to which these measures have constrained Pb and Cd accumulation in industrial and mining city soils remains unclear. Here, we investigated Pb and Cd accumulation patterns in soils of Panzhihua City, Southwest China, and determined their dominant anthropogenic drivers using Pb and Cd isotopes. Pb accumulation initially slowed and then increased, while Cd showed a continuous acceleration. Traffic and coal-burning power generation were the dominant anthropogenic forcings for Pb and Cd accumulation in the soils, respectively. Environmental protection measures, particularly the ban on leaded gasoline, significantly reduced Pb accumulation by decreasing traffic-related Pb contributions to soils from 1980 to 2008. However, environmental management measures could not practically mitigate Cd accumulation in the soils owing to the high Cd content in consumed coal, poor efficiency of air pollutant control measures, and steep rise in coal-burning power generation. This study thus indicates the criticality of controlling Cd emissions from thermal power generation. Additionally, the challenges faced by small industrial and mining cities during economic transformation and environmental policy implementation warrant more attention.

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A large volume of atmospheric microplastics (MPs) has been observed worldwide and is considered an emerging global environmental issue. Nevertheless, no significant assessment of the atmospheric deposition of MPs in Pakistan has been reported yet. The present study was designed to highlight the source, type, and spatial distribution of MPs in atmospheric fallout in Lahore, Pakistan. A total of 23 sites were sampled in Lahore with a heterogeneous background of human activities. All samples were collected in a box with a one-foot depth fitted with a steel tray of 0.1 m2 at the bottom. Fenton's reagent and hydrogen peroxide were used to remove organic matter, and sodium chloride for density separation, while the MPs were quantified through a stereomicroscope, and polymers were identified through ATR-FTIR spectroscopy. The highest deposition rate (particles/m2/day) was observed at Badami Bagh, i.e., 6819, followed by Mall Road 4414, and Chung 4263, while the lowest was in Sabzazaar (i.e., 524) and Township (1047) with an average deposition rate of 2340 ± 1392. Among the MPs, the major portion was fiber, i.e., 96%, while fragment was 1.9%, sheets 0.78%, foams 1.12%, beads 0.04%, and other MPs 0.06%. At all sampling sites, 20 different types of polymers were identified with different percentages, of which polyester fibers were predominant with an abundance of 96.09% associated with clothes and textiles. A high frequency of MPs was found in populated areas with dense traffic, plastic wastes, household plastic materials, and mismanagement of wastes, which accelerates the atmospheric deposition of airborne microplastics. Evaluation and characterization of MP help assess health and environmental impacts, cleanup efforts, and guiding regulations. It also provides valuable information for waste management innovation to reduce plastic pollution.

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The increasing levels of heavy metals in aquatic environments, driven by human activities, pose a critical threat to ecosystems' overall health and sustainability. This study investigates the bioaccumulation of heavy metals (Pb, Cu, Cr, and Cd) in water, sediment, and three fish species (Catla catla, Labeo rohita, Cirrhinus mrigala) of different feeding zones within Chashma Barrage, located in the Mianwali district of Punjab, Pakistan, on the Indus River. A comprehensive analysis, including an assessment of associated human health risks, was conducted. Thirty samples from all three sites for each fish species, with an average body weight of 160 ± 32 g, were collected from Chashma Barrage. Water quality parameters indicated suitability for fish growth and health. Heavy metal concentrations were determined using an atomic absorption spectrometer. Results indicated elevated levels of Cd, Cr, and Cu in sediment and Pb and Cd in water, surpassing WHO standard limits. Among the fish species, bottom feeder (C. mrigala) exhibited significantly (P < 0.05) higher heavy metal levels in its tissues (gills, liver, and muscle) compared to column feeder (L. rohita) and surface feeder (C. catla). Liver tissues across all species showed higher heavy metal bioaccumulation, followed by gills. Principal component analysis (PCA) revealed strong correlations among heavy metals in sediment, gills, muscle, and water in every fish species. However, the vector direction suggests that Cr was not correlated with other heavy metals in the system, indicating a different source. The human health risk analysis revealed lower EDI, THQ, and HI values (< 1) for the fish species, indicating no adverse health effects for the exposed population. The study emphasizes the bioaccumulation differences among fish species, underscoring the higher heavy metal concentrations in bottom feeder fish within Chashma Barrage.

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This study investigated land use and land cover changes in the Gauteng Province of South Africa with emphasis on wetland ecosystems. Using Landsat images and various image manipulation software such as ArcGIS and ENVI, this study conducted a predictive analysis of the potential state of wetland ecosystems in the Gauteng Province of South Africa by year 2040, using illegal dumping trends in the last 20 years. Based on this methodological framework, it is found that continued illegal dumping trends would lead to an almost total disappearance of wetlands in the study area by 2040. It is argued that despite the pro-environmental initiatives introduced in the early 2000s to conserve wetlands in South Africa, wetland deterioration has increased rapidly due to the associated methodological flaws, which further supports the findings of this study. Ultimately, it is recommended that a collaborative approach to wetland conservation, and a robust methodological shift are required to mitigate the threats faced by wetlands in the Gauteng Province of South Africa, and the model can be deployed across developing countries.

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Background: Developing nations have to overcome a number of obstacles to fulfill the Sustainable Development Goals. The Democratic Republic of Congo is one of the five poorest nations in the world and faces several challenges in combating problems related to poverty, health, and sanitation while linking the environment to anthropogenic activities. Methods: This study analyzes anthropogenic activities and their impact on the environment while providing access to the public health of the Congolese population based on the objectives of sustainable development. Thirty-five articles were selected for further analysis as well as relative data. Results: In 2022, 21 million cases of malaria were recorded by the national malaria control program, with 13,000 cases of death. The Democratic Republic of Congo has the highest typhoid incidence, with 315 cases per 100,000 people. A number of 31,342 cases of cholera were reported in 2023, according to multiple reports, with 230 deaths, mainly affecting children. In the same year, a triple epidemic of typhoid, shigellosis, and cholera was identified, with 2389 cases and 52 deaths. These observations cause a health emergency, which can be alleviated and resolved by the establishment of an adequate sanitation system. Waste can be recycled and returned to usable raw materials. Conclusion: Finally, it will be necessary to establish a water safety management plan to combat all diseases linked to the consumption of nonpotable water and improve national coverage on the treatment of recent cases to reduce and at best avoid observed cases of death.

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Understanding the spatiotemporal changes in net primary productivity (NPP) and the driving factors behind these changes in climate-vulnerable regions is crucial for ecological conservation. This study simulates the actual NPP (NPPA) and climate potential NPP (NPPC) in the Three-River Headwaters Region from 2000 to 2020. The Theil-Sen Median method and Mann-Kendall mutation analyses are employed to explore their spatiotemporal variation patterns, while geographic weighted regression and machine learning are used to investigate the influence of anthropogenic activities and climatic factors on NPPA, the results indicate that the average NPPA across the entire region over multiple years is 382.506 g C m - 2 yr - 1 , which is 0.132 times the average annual NPPC over the past 21 years, showing an overall distribution pattern of low in the northwest and high in the southeast. The annual increase in NPPA from 2000 to 2020 is approximately 1.034 g C m - 2 yr - 1 . The source region of the Yangtze River shows the largest improvement in vegetation, with 74.1% of the area showing improvement. Between 2002 and 2003, the annual NPPA in the Three-River Headwaters Region experienced a sudden change, lagging behind the NPPC change by 1 year, and after 2005, the upward trend in NPPA became more pronounced. The impact of anthropogenic activities on NPPA shifted from positive to negative to positive from 2000 to 2020, with significant impact areas mainly concentrated in the northeast and a few areas in the central and southern parts. The proportion of areas with extremely significant impact increased from 1.9% in 2000 to 3.7% in 2020. Over the past 21 years, the main factors influencing NPPA changes in the Three-River Headwaters Region have been soil moisture and precipitation, with the influence of different climate factors on NPP changing over time. Additionally, NPP is more sensitive to changes in altitude in low-altitude areas. This study can provide more accurate theoretical support for ecological environment assessment and subsequent protection efforts in the Three-River Headwaters Region.

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Microplastic records from lake cores can reconstruct the plastic pollution history. However, the associations between anthropogenic activities and microplastic accumulation are not well understood. Huguangyan Maar Lake (HML) is a deep-enclosed lake without inlets and outlets, where the sedimentary environment is ideal for preserving a stable and historical microplastic record. Microplastic (size: 10-500 µm) characteristics in the HML core were identified using the Laser Direct Infrared Imaging system. The earliest detectable microplastics appeared unit in 1955 (1.1 items g-1). The microplastic abundance ranged from n.d. to 615.2 items g-1 in 1955-2019 with an average of 134.9 items g-1. The abundance declined slightly during the 1970s and then increased rapidly after China's Reform and Opening Up in 1978. Sixteen polymer types were detectable, with polyethylene and polypropylene dominating, accounting for 23.5 and 23.3% of the total abundance, and the size at 10-100 µm accounted for 80%. Socioeconomic factors dominated the microplastic accumulation based on the random forest modeling, and the contributions of GDP per capita, plastic-related industry yield, and total crop yield were, respectively, 13.9, 35.1, and 9.3% between 1955-2019. The total crop yield contribution further increased by 1.7% after 1978. Coarse sediment particles increased with soil erosion exacerbated microplastics discharging into the sediment.

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In recent years, the effects of human activities and climate change on river flow patterns have become a major concern worldwide. This is particularly true in the southern Caspian Sea (SCS) region of Iran, where increasing water-intensive socio-economic development and climate change have significantly altered river flow regimes. To better understand these changes, this study employs two nonparametric methods, the modified Mann-Kendall method (MK3) and Innovative Trend Analysis (ITA), to examine spatial and temporal changes in hydrometeorological variables in the SCS. The study also evaluates the impact of human activities and climate change on river flow alteration using elasticity-based methods and the Budyko hypothesis in 40 rivers on the closest gauges to the Caspian Sea. The results indicate an alarming trend of increasing temperature, potential evapotranspiration, and decreasing river flows in the SCS region. In particular, human activities were found to be responsible for around 91.7 % of the change on average, resulting in a significant decline in inflow to the Caspian Sea by about 3216 MCM annually. This declining trend in inflow could potentially exacerbate the eutrophication conditions in the Sea and negatively impact its ecosystem and economics. Therefore, appropriate measures need to be taken to address these environmental and socio-economic issues in the southern Caspian Sea region.

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Although antibiotics are widely detected in river water, their quantitative relationships with influencing factors in rivers remain largely unexplored. Here, 15 widely used antibiotics were comprehensively analyzed in the Dongjiang River of the Pearl River system. The total antibiotic concentration in river water ranged from 13.84 to 475.04 ng/L, with fluoroquinolones increasing from 11 % in the upstream to 38 % in the downstream. The total antibiotic concentration was high downstream and significantly correlated with the spatial distribution of population density, animal production, and land-use type. The total risk quotient of antibiotics for algae was higher than that for crustaceans and fish. Based on the optimized risk quotient method, amoxicillin, ofloxacin, and norfloxacin were identified as priority antibiotics. The key predictors of antibiotic levels were screened through Mantel test, correlation analysis, and multiple regression models. Water physicochemical parameters significantly impacted antibiotics and could be used as easy-to-measure surrogates associated with elevated antibiotics. Cropland negatively affected fluoroquinolones and sulfonamides, whereas urban land exerted positive impacts on fluoroquinolones, ß-lactam, and sulfonamides. In the main stream, population, animal production, urbanization status, and economic development had key effects on the distribution of florfenicol, norfloxacin, ofloxacin, and sulfadiazine.

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Cabomba caroliniana A. Gray, an ornamental submerged plant indigenous to tropical America, has been introduced to numerous countries in Europe, Asia, and Oceania, impacting native aquatic ecosystems. Given this species is a popular aquarium plant and widely traded, there is a high risk of introduction and invasion into other environments. In the current study the potential global geographic distribution of C. caroliniana was predicted under the effects of climate change and human influence in an optimised MaxEnt model. The model used rigorously screened occurrence records of C. caroliniana from hydro informatic datasets and 20 associated influencing factors. The findings indicate that temperature and human-mediated activities significantly influenced the distribution of C. caroliniana. At present, C. caroliniana covers an area of approximately 1531×104 km2 of appropriate habitat, especially in the south-eastern parts of South, central and North America, Southeast Asia, eastern Australia, and most of Europe. The suitable regions are anticipated to expand under future climate scenarios; however, the dynamics of the changes vary between different extents of climate change. For example, C. caroliniana is expected to expand to higher latitudes, following global temperature increases under SSP1-2.6 and SSP2-4.5 scenarios, however, intolerance to temperature extremes may mediate invasion at higher latitudes under future extreme climate scenarios, e.g., SSP5-8.5. Owing to the severe impacts its invasion causes, early warning and stringent border quarantine processes are required to guard against the introduction of C. caroliniana especially in the invasion hotspots such as, Peru, Italy, and South Korea.

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Kathajodi, the principal southern distributary of the Mahanadi River, is the vital source of irrigation and domestic water use for densely populated Cuttack city which receives anthropogenic wastes abundantly. This study assesses the contamination level and primary health status of urban wastewater, and its receiving river Kathajodi based on the physicochemical quality indices employing inductively coupled plasma mass spectroscopy and aligning with guidelines from the United States Environmental Protection Agency (USEPA) and WHO. The high WQI, HPI, and HEI in the catchment area (KJ2, KJ3, and KJ4) indicate poor water quality due to the influx of domestic waste through the primary drainage system and effluents of healthcare units. A high BOD (4.33-19.66 mg L-1) in the catchment indicates high organic matter, animal waste, bacteriological contamination, and low DO, resulting in deterioration of water quality. CR values beyond limits (1.00E - 06 to 1.00E - 04) in three locations of catchment due to higher Cd, Pb, and As indicate significant carcinogenic risk, while high Mn, Cu, and Al content is responsible for several non-carcinogenic ailments and arsenic-induced physiological disorders. The elevated heavy metals Cd, Cu, Fe, Mn, Ni, and Zn, in Kathajodi, could be due to heavy coal combustion, vehicle exhaust, and industrial waste. On the other hand, Cu, Fe, K, and Al could be from agricultural practices, weathered rocks, and crustal materials. Positive significant (p ≤ 0.05) Pearson correlations between physicochemical parameters indicate their common anthropogenic origin and similar chemical characteristics. A strong correlation of PCA between elements and physiological parameters indicates their role in water quality deterioration. Assessing the surface water quality and heavy metal contents from this study will offer critical data to policymakers for monitoring and managing public health concerns.

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A methodological approach based on rare earth elements analysis was developed to observe human activities in the stratigraphic sequence of Alagankulam. The site was one of the main ancient ports in south-eastern India and one of the transoceanic connecting points between East and West during the Classical Period. The sampled sediments where collected from vertical profiles, areas with traces of firing activities and filled deposits. Major, minor and trace element concentrations were measured by the means of spectroscopic and spectrometric techniques. Data from multielemental analysis were then cross-referenced together with archaeological evidence to map the variability within the site and its association with the detected anthropic activities. The matching of the interpretation of the archaeological record and the analytical data has allowed a combined mapping of visible and invisible traces of human activities in the site, giving a deeper insight of the Alagankulam occupational history.

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Coal mining changes groundwater environment, results in deterioration of water quality and endangering human health in the mining area. However, the comprehensive study of groundwater evolution and its potential impact in mining area is still insufficient. In this study, 95 groundwater samples were collected from 2019 to 2020 in a typical mining area of China. Ion ratio coefficients, isotopic tracing technology, Entropy-weighted water quality index (EWQI) and human health risk assessment model (HHRA) were applicated to investigate the hydrochemical variation reasons, groundwater quality and its potential health risk in the study area. Results showed that the groundwater hydrochemical types changed from HCO3∙SO4-Ca∙Mg type to SO4-Ca∙Mg and SO4∙Cl-Ca∙Mg type. Water-rock interaction, agricultural activities, manure and sewage input, precipitation and evaporation controlled the groundwater hydrochemical composition. Groundwater quality showed a trend of fluctuation with an average EWQI of 59.23, 68.92, 63.75, 58.02 and 64.92, respectively. 91.6% of the water samples was fair and acceptable for drinking. The groundwater health risk of nitrate in the study area ranged from 0.03 to 17.80. Infants had the highest health risk and nitrate concentration was the most sensitive parameter. The results will present a comprehensive research of groundwater evolution and potential impacts through a typical mining area example. Thereby offering valuable insights into the influencing factors identification, hydrochemical processes evolution, protection and utilization of groundwater in global mining areas.

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The characteristics of the vegetation fire (VF) regime are strongly influenced by geographical variables such as regional physiographic settings, location, and climate. Understanding the VF regime is extremely important for managing and mitigating the impacts of fires on ecosystems, communities, and human activities in forest fire-prone regions. The present study thereby aimed to explore the potential effects of the confounding factors on VF in India to offer actionable and achievable solutions for mitigating this concurring environmental issue sustainably. A global burn area (250 m) data (Fire-CCIv5.1) and fire radiative power (FRP) were used to investigate the dynamics of VF across seven different divisions in India. The study also used the maximum and minimum temperatures, precipitation, population density, and intensity of human modification to model forest burn areas (including grassland). The Coupled Model Intercomparison Project-6 (CMIP6) was used to predict the burn area for 2030 and 2050 future climate scenarios. The present study accounted for a sizable increasing trend of VF during 2001-2019 period. The highest increasing trend was found in central India (513 and 343 km2 year-1 in the forest and crop fire, respectively), followed by southern India (364 km2 year-1 in forest fire), and upper Indo-Gangetic plain (128 km2 year-1 in crop fire). The FRP has varied significantly across the divisions, with the north-eastern Himalayas exhibiting the highest FRP hotspot. The maximum and minimum temperatures have the greatest influence on forest fires, according to Random Forest (RF) modeling. The estimated pre-monsoonal burn area for 2050 and 2050 future scenarios suggested a more frequent forest fire occurrence across India, particularly in southern and central India. A comprehensive forest fire control policy is therefore essential to safeguard and conserve forest cover in the regions, affected by forest fire periodically.

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Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 °C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R2 = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70-85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state.

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Understanding the processes of mobility and availability of potentially toxic elements in soil is crucial for informed decision-making in the development of public policies aimed at minimizing environmental impacts. Monitoring, in combination with the determination of natural concentrations, can provide effective tools for controlling pollution sources. In this study, enrichment, pollution, and ecological risk indices were used for some potentially toxic elements in an anthropogenically influenced watershed in southwestern Bahia, Brazil. The study involved 63 composite surface soil samples collected from areas with natural forest, crops, pastures, and urbanization. The samples were analyzed for fertility and particle size. Metal extraction followed the EPA 3051A method, and element determination was carried out via ICP-OES. The soils in the Verruga River watershed exhibit a high variability in fertility and granulometric attributes. The Kruskal-Wallis test at a 5% significance level was employed to assess the impact of land management on the availability of elements (As, Co and Pb), while Spearman's correlation, along with hierarchical clustering analysis, was used to comprehend element dynamics. Geostatistics were applied to identify pollution hotspots. Consequently, it became evident that potentially toxic elements can accumulate in the soil depending on land use and management practices (As, Co, and Pb), as well as the weathering process linked to the type of source material, such as diamictite deposits (Ni and Co). Soils in the Verruga River watershed qualify as having minimal enrichment, low pollution levels, and individual ecological risk concerning Cd. The percentage of samples enriched with Cu, As, Zn, and Cd exceeded 67%, with agricultural activities being the primary source of pollution. Meanwhile, in pasture and urban areas, Co and Pb were notably prominent, respectively.

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