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The aim of this concept paper is the description of a new tool to support institutions in the implementation of targeted countermeasures, based on quantitative and multi-scale elements, for the fight and prevention of emergencies, such as the current COVID-19 pandemic. The tool is a cloud-based centralized system; a multi-user platform that relies on artificial intelligence (AI) algorithms for the processing of heterogeneous data, which can produce as an output the level of risk. The model includes a specific neural network which is first trained to learn the correlations between selected inputs, related to the case of interest: environmental variables (chemical–physical, such as meteorological), human activity (such as traffic and crowding), level of pollution (in particular the concentration of particulate matter) and epidemiological variables related to the evolution of the contagion. The tool realized in the first phase of the project will serve later both as a decision support system (DSS) with predictive capacity, when fed by the actual measured data, and as a simulation bench performing the tuning of certain input values, to identify which of them led to a decrease in the degree of risk. In this way, we aimed to design different scenarios to compare different restrictive strategies and the actual expected benefits, to adopt measures sized to the actual needs, adapted to the specific areas of analysis and useful for safeguarding human health; and we compared the economic and social impacts of the choices. Although ours is a concept paper, some preliminary analyses have been shown, and two different case studies are presented, whose results have highlighted a correlation between NO 2 , mobility and COVID-19 data. However, given the complexity of the virus diffusion mechanism, linked to air pollutants but also to many other factors, these preliminary studies confirmed the need, on the one hand, to carry out more in-depth analyses, and on the other, to use AI algorithms to capture the hidden relationships among the huge amounts of data to process. [ABSTRACT FROM AUTHOR]

Karst groundwater is an important water supply, especially in northern China. With the rapid development of China's economy, anthropogenic activities have had a significant impact on karst groundwater formation, circulation and other processes. In this paper, the Baotu spring basin, which is closely related to anthropogenic activities, was selected as the research object to carry out a study of water chemical characteristics and evolutionary processes. And, mathematical statistics, Piper trilinear diagram, Gibbs diagram, and ion ratio methods were used to analyze the characteristics and evolution processes of groundwater. The results of this study show that the hydrogeochemical components of karst groundwater are mainly controlled by the weathering of rocks, mainly by the dissolution of carbonate rocks and silicates with the dominant cation of Ca2+ and the dominant anion of HCO3−. Considering the role of anthropogenic activities, including agricultural and industrial activities, the evolution process of karst groundwater is mainly controlled by hydrogeochemical effects such as mineral dissolution and filtration, the mixing of multiple water bodies, anthropogenic activities (domestic sewage, industrial and agricultural wastes), oxidation–reduction and cation alternating adsorption. Moreover, the influence of anthropogenic activities on the formation and evolution of karst groundwater gradually increases, leading to the rise in nitrate content in karst groundwater and accelerating carbonate rock dissolution. The research results of this paper can provide a favorable reference for environmental protection and research on karst groundwater in areas of intensive anthropogenic activity. [ABSTRACT FROM AUTHOR]

Globally, forest ecosystems, especially subtropical forests, play a central role in biogeochemical cycles and climate regulation, demonstrating their irreplaceable function. The subtropical region of China, characterized by its unique forest ecosystem, complex terrain, climate heterogeneity, diverse vegetation types, and frequent human activities, underscores the importance of the in-depth study of its net primary productivity (NPP). This paper employs the eddy covariance–light use efficiency (EC-LUE) model to quantitatively estimate the gross primary productivity (GPP) of this region from 2001 to 2018, followed by an estimation of the actual net primary productivity (ANPP) using the carbon use efficiency (CUE). The results showed that over these 18 years, the annual average ANPP was 677.17 gC m−2 a−1, exhibiting an overall increasing trend, particularly in mountainous areas, reserves, and the cultivated lands of the northeastern plains, whereas a significant decrease was observed around the urban agglomerations on the southeast coast. Furthermore, the Thornthwaite memorial model was applied to calculate the potential net primary productivity (PNPP), and diverse scenarios were set to quantitatively evaluate the impact of climate change and human activities on the vegetation productivity in the study area. It was found that in areas where the ANPP increased, both human activities and climate change jointly influenced ANPP dynamics; in areas with a decreased ANPP, the impact of human activities was particularly significant. Additionally, the heterogeneous distribution of ANPP across different altitudinal gradients and the driving effects of various climatic factors were analyzed. Finally, a partial correlation analysis was used to examine the relationships between the temperature, precipitation, and ANPP. This study indicated that temperature and precipitation have a substantial impact on the growth and distribution of vegetation in the region, yet the extent of this influence shows considerable variation among different areas. This provides a robust scientific basis for further research and understanding of the carbon dynamics of subtropical forest ecosystems and their role in the global carbon cycle. [ABSTRACT FROM AUTHOR]

The regions near the Tropic of Cancer are a latitudinal geographical zone with typical climatic, topographic, and human landscape features. It is necessary to explore the region's net primary productivity (NPP) dynamics as it combines complex topography, various vegetation types, and intense human activities. The study sets the transect near the Tropic of Cancer (TCT) and uses the Carnegie–Ames–Stanford (CASA) model to estimate the NPP from 2000 to 2020. After using the RESTREND method, the paper calculates and compares the relative contributions of climate variability and anthropogenic activities to NPP changes. Finally, the geographical detector (Geodetector) model is applied to evaluate how anthropogenic and natural factors affect spatial distribution patterns and NPP changes. The results indicated that the average annual NPP is 820.39 gC·m−2·yr−1 during the 21 years. In addition, when the NPP varies, it increases over the entire study area, with a slope of 4.81 gC·m−2·yr−1, particularly in the western region. Across the entire research area, 63.39% and 77.44% of the total pixels positively contribute to climate variability and human activities in NPP, with a contribution of 0.90 and 3.91 gC·m−2·yr−1, respectively. Within the western, central, and eastern regions, anthropogenic activities have a stronger impact on NPP than climate variability, particularly pronounced in the eastern region. Furthermore, vegetation cover is the dominant factor in the spatial patterns and NPP trends across the TCT and the three regions. In contrast, climate factors are shown to be less influential in NPP distribution than in the western region. The results also demonstrated that the effect of population density and the GDP on NPP gradually rises. Two-factor interaction is much larger than any individual factor, with the dominant interaction factor being vegetation cover with climatic factors. Lastly, the findings revealed that anthropogenic activities positively promote NPP accumulation across the TCT, thus highlighting the importance of human activity-led ecological restoration and ecological protection measures that contribute to regional carbon sequestration and carbon balance. [ABSTRACT FROM AUTHOR]

Beaches are ecologically valuable ecosystems and sites that attract many tourists from all over the world, therefore, knowledge of their environmental conditions to establish sound management strategies is of extreme relevance. This study aims to assess and classify 50 beaches through an innovative coastal management approach called "Sector Analysis", which integrates Litter grading, the coastal scenic quality and beach typology in order to classify sites into one of three sectors: Green (high value sites), Red (low value sites) and Yellow (sites with contradictory values). Litter Grade makes it possible to classify a site according to the quantity of litter using four grades from "A" (low) to "D" (high amount). The Coastal Scenic Evaluation System (CSES) allows to classify sites into five classes, ranging from extremely attractive natural sites (Class I) to unattractive degraded and urbanized sites (Class V). This innovative methodology for sustainable coastal area management can be easily applied to any beach in the world. The results on Litter Grade and CSES considered in this paper were obtained from previous studies and used to obtain the Sector Analysis that showed only 8 sites (16%) are in the Green sector, 18 sites (36%) in the Red sector and 24 sites (48%) in the Yellow sector. The significant percentage of sites in the Red sector (one third of the sites studied) clearly indicates the degradation that the Moroccan Mediterranean coast has undergone due to considerable anthropogenic activities and the lack of adequate coastal management programs. In this study, various management interventions were proposed to conserve and improve the aesthetic quality of beaches and reduce the impact and presence of litter in the coastal areas. [ABSTRACT FROM AUTHOR]

The water supply system plays a major role in the community. The water source is carefully selected based on quality, quantity, and reliability. The quality of water at its sources is continuously deteriorating due to various anthropogenic activities and is a major concern to public health as well. The Kalu River is one of the major water resources in Sri Lanka that supplies potable water to the Kalutara district (a highly populated area) and Rathnapura district. But, there has been no significant research or investigation to examine anthropogenic activities in the river. Due to this, it is difficult to find any proper study related to the overall water quality in the Kalu River. Therefore, this study covers a crucial part related to the water quality of the Kalu River. The spatiotemporal variation of river water quality is highly important not only to processing any treatment activities but also to implementing policy decisions. In this context, water quality management is a global concern as countries strive to meet the United Nations Sustainable Development Goal 6, which aims to ensure the availability and sustainable management of water and sanitation for all. Poor water quality can have severe consequences on human health, ecosystems, and economies. Contaminated water sources pose risks of waterborne diseases, reduced agricultural productivity, and ecological imbalances. Hence, assessing and improving water quality is crucial for achieving sustainable development worldwide. Therefore, this paper presents a comprehensive analysis of spatiotemporal analysis of the water quality of the Kalu River using the water quality data of eight locations for 6 years from 2017 to 2023. Nine water quality parameters, including the pH, electrical conductivity, temperature, chemical oxygen demand, biological oxygen demand, total nitrate, total phosphate, total sulfate, total chlorine, and hardness, were used to develop a simple equation to investigate the water quality index (WQI) of the river. Higher WQI values were not recorded near the famous Kalutara Bridge throughout the years, even though the area is highly urbanized and toured due to religious importance. Overall, the water quality of the river can be considered acceptable based on the results of the WQI. The country lockdowns due to COVID-19 might have impacted the results in 2020; this can be clearly seen with the variation of the annual WQI average, as it clearly indicates decreased levels of the WQI in the years 2020 and 2021, and again, the rise of the WQI level in 2022, as this time period corresponds to the lockdown season and relaxation of the lockdown season in the country. Somehow, for most cases in the Kalu River, the WQI level is well below 25, which can be considered acceptable and suitable for human purposes. But, it may need some attention towards the areas to find possible reasons that are not in the range. Nevertheless, the results suggest the importance of continuous water quality monitoring in the Kalu River. [ABSTRACT FROM AUTHOR]

Large marginal sandbanks in tidal rivers experience periodic splitting processes. In this paper, the morphodynamic evolution of Jingjiang Beach, a sandbank on the Yangtze tidal river, has been investigated based on measured data. The results show that the duration of the splitting process in the middle and lower sections of Jingjiang Beach is 4–6 years. The periodical evolution occurred both in flood season and dry season, with a slight difference in the initial stage of splitting. This paper focuses on the evolution characteristics related to strong human activities since 2003. Ever since the second stage of the 12.5 m Deepwater Channel Project (DCP), the volumes above the 10 m and 12.5 m isobaths of Jingjiang Beach have been generally decreasing. The elevation data in recent years have demonstrated that the upper section, and nearshore side of the middle section, of Jingjiang Beach have tended to be stable. Moreover, the migration distance for a splitting sand body at the tail of Jingjiang Beach appears to have shortened. With the operation of the Three Gorges Reservoir, the number of days with discharge less than 15,000 m3/s has shown a decreasing trend; thus, the development scale of Jingjiang Beach could decline in the future. [ABSTRACT FROM AUTHOR]

Wetlands are simply areas that are fully or partially saturated with water. Not much attention has been given to wetlands in the past, due to the unawareness of their value to the general public. However, wetlands have numerous hydrological, ecological, and social values. They play an important role in interactions among soil, water, plants, and animals. The rich biodiversity in the vicinity of wetlands makes them invaluable. Therefore, the conservation of wetlands is highly important in today's world. Many anthropogenic activities damage wetlands. Climate change has adversely impacted wetlands and their biodiversity. The shrinking of wetland areas and reducing wetland water levels can therefore be frequently seen. However, the opposite can be seen during stormy seasons. Since wetlands have permissible water levels, the prediction of wetland water levels is important. Flooding and many other severe environmental damage can happen when these water levels are exceeded. Therefore, the prediction of wetland water level is an important task to identify potential environmental damage. However, the monitoring of water levels in wetlands all over the world has been limited due to many difficulties. A Scopus-based search and a bibliometric analysis showcased the limited research work that has been carried out in the prediction of wetland water level using machine-learning techniques. Therefore, there is a clear need to assess what is available in the literature and then present it in a comprehensive review. Therefore, this review paper focuses on the state of the art of water-level prediction techniques of wetlands using machine-learning techniques. Nonlinear climatic parameters such as precipitation, evaporation, and inflows are some of the main factors deciding water levels; therefore, identifying the relationships between these parameters is complex. Therefore, machine-learning techniques are widely used to present nonlinear relationships and to predict water levels. The state-of-the-art literature summarizes that artificial neural networks (ANNs) are some of the most effective tools in wetland water-level prediction. This review can be effectively used in any future research work on wetland water-level prediction. [ABSTRACT FROM AUTHOR]

Anthropogenic activities often compromise the water quality of natural water systems, rendering it unfit for domestic and agricultural use. This paper evaluates the effects of anthropogenic activities on the water quality of Ngong River in Nairobi County, Kenya. It aimed to assess the river's physico-chemical parameters, identify major anthropogenic activities that act as pollutant sources and establish the relationship between the anthropogenic activities and water quality along the Ngong River. Twelve water samples were systematically collected in each of the twelve study sites in April and August 2021 and analyzed in the laboratory for various water quality parameters. The accumulation factor (AF) indicated that E. coli, total coliforms, BOD and COD were found to significantly build up downstream of Ngong River. The ANOVA test results showed that all the physicochemical parameters studied (BOD, E. coli, pH, total suspended solids, total coliforms, turbidity, conductivity, nitrates, oil and grease and TDS), except COD, were not significantly different (p ≤ 0.05) for the different sites. Measured heavy metals, such as lead (Pb) levels at different sampled points, were all found to be below the detectable limit (0.001 ppm) for both seasons. Cadmium (Cd) was detectable during the dry season with the highest levels (0.113 ppm) being recorded at Ngong Forest Boundary. The findings of this study revealed that anthropogenic activities, such as raw sewage disposal, industrial activities, solid waste dumping and small-scale agriculture, had adverse effects on Ngong River's water quality. The study recommends a need to closely monitor anthropogenic activities along Ngong River to reduce their probable pollution of the water in the River basin. This will ensure the sustainability of the water resources. [ABSTRACT FROM AUTHOR]

The intensification of anthropogenic activities (agriculture, industry, and exploitation of water resources) during urbanization has posed significant challenges to the aquatic environment, particularly in karst regions. Karst aquifers are highly susceptible to surface contaminants and exhibit minimal natural remediation capabilities. Our understanding of the anthropogenic activities involved in these sensitive karst systems remains limited. To address this gap, we conducted a comprehensive study, collecting 285 groundwater samples in Feicheng, northern China, from 1996 to 2015. The overexploitation of karst groundwater has resulted in several concerns. The whole dataset was classified into four groups according to land use. Water quality assessments revealed a yearly decline, particularly in industrial and agricultural areas. The water chemistry transitioned from Ca-Mg-HCO3 to Ca-Mg-HCO3-SO4. Such evolution was attributed to natural hydrogeochemical processes, atmospheric precipitation, and anthropogenic inputs. Natural factors included water-rock interactions (the mineral dissolution) and ion exchange. Absolute principal component scores with multiple linear regression (APCS-MLR) were used to quantitatively estimate the sources of pollution. The results showed that hydrogeological settings (recharge, runoff, and discharge) were crucial in the hydrochemistry evolution of karst groundwater systems. In agricultural areas, it is recognized that much of the NO3− accumulation in aquifers came from upstream inputs in the groundwater system, not just irrigation and fertilization. Urban areas were affected by Cl− pollution, primarily due to domestic waste. Industrial regions of recharge zones were more susceptible to atmospheric precipitation and industrial waste, with pollutants infiltrating through rainfall and degrading water quality. Mining areas exhibit higher SO42− and lower pH due to the oxidation of sulfur-containing minerals. Therefore, the rapid response and low self-purification capacity of groundwater in karst regions necessitate caution in urban planning to mitigate impacts on these fragile systems. [ABSTRACT FROM AUTHOR]

Transitional waters (TWs) are relevant ecological and economical ecosystems that include estuaries, deltas, bays, wetlands, marshes, coastal lakes, and coastal lagoons and play a central role in providing food, protecting coastal environments, and regulating nutrients. However, human activities such as industrialization, urbanization, tourism, and agriculture are threatening these ecosystems, which results in contamination and habitat degradation. Therefore, it is essential to evaluate contamination in TW to develop effective management and protection strategies. This study analyses the application of geospatial technologies (GTS) for monitoring and predicting contaminant distribution in TW. Cartography, interpolation, complex spatial methods, and remote sensing were applied to assess contamination profiles by heavy metals, and persistent organic compounds, and analyze contamination indices or some physicochemical water parameters. It is concluded that integrating environmental and demographic data with GTS would help to identify critical points of contamination and promote ecosystem resilience to ensure long-term health and human well-being. This review comprehensively analyzes the methods, indicators, and indices used to assess contamination in transitional waters in conjunction with GTS. It offers a valuable foundation for planning future research on pollution in these types of waters or other similar water bodies worldwide. [ABSTRACT FROM AUTHOR]

In recent decades, the depletion of surface water resources within the Lake Urmia Basin (LUB), Iran, has emerged as a significant environmental concern. Both anthropogenic activities and climate change have influenced the availability and distribution of surface water resources in this area. This research endeavors to provide a comprehensive evaluation of the impacts of climate change and anthropogenic activities on surface water resources across the LUB. Various critical climatic and anthropogenic factors affecting surface water bodies, such as air temperature (AT), cropland (CL), potential evapotranspiration (PET), snow cover, precipitation, built-up areas, and groundwater salinity, were analyzed from 2000 to 2021 using the Google Earth Engine (GEE) cloud platform. The JRC-Global surface water mapping layers V1.4, with a spatial resolution of 30 m, were employed to monitor surface water patterns. Additionally, the Mann–Kendall (MK) non-parametric trend test was utilized to identify statistically significant trends in the time series data. The results reveal negative correlations of −0.56, −0.89, −0.09, −0.99, and −0.79 between AT, CL, snow cover, built-up areas, and groundwater salinity with surface water resources, respectively. Conversely, positive correlations of 0.07 and 0.12 were observed between precipitation and PET and surface water resources, respectively. Notably, the findings indicate that approximately 40% of the surface water bodies in the LUB have remained permanent over the past four decades. However, there has been a loss of around 30% of permanent water resources, transitioning into seasonal water bodies, which now account for nearly 13% of the total. The results of our research also indicate that December and January are the months with the most water presence over the LUB from 1984 to 2021. This is because these months align with winter in the LUB, during which there is no water consumption for the agriculture sector. The driest months in the study area are August, September, and October, with the presence of water almost at zero percent. These months coincide with the summer and autumn seasons in the study area. In summary, the results underscore the significant impact of human activities on surface water resources compared to climatic variables. [ABSTRACT FROM AUTHOR]

Influences of the increasing pressure of climate change and anthropogenic activities on wetlands ecosystems and agriculture are significant around the world. This paper assessed the spatiotemporal land use and land cover changes (LULCC), especially for conversion from marshland to other LULC types (e.g., croplands) over the Songnen and Sanjiang Plain (SNP and SJP), northeast China, during the past 35 years (1980-2015). The relative role of human activities and climatic changes in terms of their impacts on wetlands and agriculture dynamics were quantitatively distinguished and evaluated in different periods based on a seven-stage LULC dataset. Our results indicated that human activities, such as population expansion and socioeconomic development, and institutional policies related to wetlands and agriculture were the main driving forces for LULCC of the SJP and SNP during the past decades, while increasing contributions of climatic changes were also found. Furthermore, as few studies have identified which geographic regions are most at risk, how the future climate changes will spatially and temporally impact wetlands and agriculture, i.e., the suitability of wetlands and agriculture distributions under different future climate change scenarios, were predicted and analyzed using a habitat distribution model (Maxent) at the pixel-scale. The present findings can provide valuable references for policy makers on regional sustainability for food security, water resource rational management, agricultural planning and wetland protection as well as restoration of the region. [ABSTRACT FROM AUTHOR]

In recent decades, China has experienced substantial climate change and significant vegetation greenness due to the extensive implementation of artificial ecological restoration programs. However, the quantitative contributions of climatic and anthropogenic drivers to the national variations in associated evapotranspiration (ET) and gross primary productivity (GPP) over China at different climate zoning sub-regions remain unclear. Based on the analysis of climate factor and vegetation disturbance trends created by anthropogenic activities, this study constructed a remote sensing-based ecological model consisting of Penman–Monteith–Leuning (PML) and light use efficiency (LUE) components. The proposed model simulated the spatiotemporal changes in ET and GPP between 1999 and 2018 over China. The contributions of climatic factors and anthropogenic activities to ET and GPP variations were quantitatively calculated by ridge regression. The results show that (1) both interannual ET and GPP markedly increased, by 1.32 mm yr−1 and 8.01 g C m−2 yr−1, respectively; (2) vegetation changes due to anthropogenic disturbance made the dominant contribution to GPP variations over China, while the dominant factor influencing ET changes differed by sub-region due to the joint effects of vegetation and climate; (3) temperature and precipitation positively affected ET, while wind speed, humidity, and solar radiation negatively contributed to ET in most parts of Mainland China. These findings may provide a workable, scientific reference for further ecological restoration decision-making processes in China. [ABSTRACT FROM AUTHOR]

Groundwater storage (GWS) in confined aquifer systems is often influenced by climate variability and anthropogenic activities, and it is vital to quantify their contributions for the purpose of groundwater management and surface water allocation plans. In this study, we characterize the spatiotemporal evolution of the GWS in confined aquifer systems across Hengshui, North China Plain, and investigate its relationships with changing climate conditions and human activities through the integration of InSAR-derived surface displacements with hydraulic head observations and precipitation data, during 2004–2010 and 2016–2020. Our results indicate that the GWS in confined aquifer systems decreased markedly by 4.59 ± 0.35 km3 with an accelerating trend during the study period. The GWS variations show a strong correlation with precipitation during irrigation periods (March to July), and hence, the climate and anthropogenic-driven GWS variations can be separated from each other with a linear model. We find that the GWS depletion caused by climate variability and anthropogenic activities were −0.31 ± 0.10 km3 and −4.28 ± 0.40 km3, respectively, during the study period. The mean contribution of anthropogenic activities to the GWS variations was −71.9%, implying that the GWS variations in confined aquifer systems were primarily anthropogenic driven. It is also found that the well observations alone poorly characterize the spatiotemporal evolution of the GWS due to their limited spatial density, and the integrated InSAR/well approach appears to be promising for overcoming this challenge. [ABSTRACT FROM AUTHOR]

This paper proposes a pragmatic approach for rapid assessment of the weighted contribution of the main waste streams contributing to pollution of surface water bodies. A case study was conducted on Lake Burullus in Egypt. The lake suffers from pollution due to many human-based activities around the lake, such as domestic, industrial, agriculture, fish farming, and solid wastes. The weighted contribution of these activities was assessed in terms of chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). The results showed that the highest organic load is due to the domestic wastewater pollution component (63.2% of COD load), followed by fish aquaculture (35.4%). The highest TN (43.9%) and TP (58.3%) pollutant loads to Lake Burullus are due to the agricultural pollution component, followed by fish aquaculture with pollutant loads of 28.5% and 25.3%, respectively. The industrial wastewater pollution component has a very small effect on the pollution of Lake Burullus. The assessment of this study will help identify and magnify the key polluters and thus guide the decision-makers to prioritize investment planning for depollution intervention projects. For example, if the target is to reduce COD loads, investments must be directed toward the rehabilitation and expansion of wastewater treatment plants (WWTPs). [ABSTRACT FROM AUTHOR]

An increasing trend of anthropogenic activities such as urbanization and industrialization has resulted in induction and accumulation of various kinds of heavy metals in the environment, which ultimately has disturbed the biogeochemical balance. Therefore, the present study was conducted to probe the efficiency of conocarpus (Conocarpus erectus L.) waste-derived biochar and its modified derivatives for the removal of lead (Pb), cadmium (Cd), copper (Cu), and zinc (Zn) from aqueous solutions. Biochar was produced at 600 °C and modified with humic acid (1:10 w/v ratio) and rock phosphate (0.5:1 w/w ratio). Additionally, produced biochar, as well as humic acid and rock phosphate-modified biochars, were subjected to ball milling separately. Equilibrium and kinetics batch experiments were conducted to investigate heavy metals adsorption on synthesized adsorbents. Adsorption isotherms and kinetics models were employed to explore the adsorption efficiency of produced materials for metals adsorption. Among all the applied adsorbents, ball-milled biochars showed comparatively higher adsorption compared to un-milled biochars. Humic acid and rock phosphate-modified milled biochar showed the highest adsorption capacity for Pb (18.85 mg g−1), while rock phosphate-modified milled biochar showed the highest adsorption capacity for Cu and Zn (24.02 mg g−1 and 187.14 mg g−1), and humic acid modified biochar adsorbed maximum Cd (30.89 mg g−1). Adsorption isotherm study confirmed Freundlich as the best-suited model (R2 = 0.99), while kinetics adsorption was well described by the pseudo-second-order (R2 = 0.99). Hence, it was concluded that ball-milled biochar modified with humic acid and rock phosphate could potentially remove heavy metals from contaminated water. [ABSTRACT FROM AUTHOR]

Global dryland areas are vulnerable to climate change and anthropogenic activities, making it essential to understand the primary drivers and quantify their effects on vegetation growth. In this study, we used the Time Series Segmented Residual Trends (TSS-RESTREND) method to attribute changes in vegetation to CO 2 , land use, climate change, and climate variability in Chinese and American dryland areas. Our analysis showed that both Chinese and American drylands have undergone a greening trend over the past four decades, with Chinese greening likely linked to climatic warming and humidification of Northwest China. Climate change was the dominant factor driving vegetation change in China, accounting for 48.3%, while CO 2 fertilization was the dominant factor in American drylands, accounting for 47.9%. However, land use was the primary factor resulting in desertification in both regions. Regional analysis revealed the importance of understanding the drivers of vegetation change and land degradation in Chinese and American drylands to prevent desertification. These findings highlight the need for sustainable management practices that consider the complex interplay of climate change, land use, and vegetation growth in dryland areas. [ABSTRACT FROM AUTHOR]

Our transformation of global environments into human-dominated landscapes has important consequences for wildlife. Globally, wildlife is interacting with humans or impacted by human activities, which often results in negative outcomes such as population declines, disruption of social bonds, biodiversity loss, imperilment of threatened species, and harm to individual animals. Human and non-human threats to wildlife can be challenging to quantify and tend to be poorly understood especially over large spatial scales and in urban environments. The extent to which such damage is mitigated by reactive approaches (e.g., wildlife rescue) is also not well understood. We used data from the main state-based Wildlife Emergency Response Services (WERS) in Victoria, Australia to address these issues. The data, which describe tens of thousands of cases of threats to wildlife annually over a ten-year period, allowed a detailed characterisation of the type and extent of threats in the state. We identified the main common and threatened species impacted by various threats and showed that the vast majority of them were anthropogenic (e.g., vehicle collisions, cat attacks, and entanglements). The extent to which different taxonomic groups and species were impacted by various threats differed and threats were dependent on locations. The Greater Melbourne area was identified as a hotspot for threats to wildlife. The WERS was able to source service providers for thousands of animals annually, facilitating their assessment, release into the wild and rehabilitation. However, every year, thousands of animals died or were euthanased and thousands more were left unattended. WERS case reports are increasing and there is a growing service–demand gap. Whilst studies reporting on the demand and response of WERS are rare, situations in other parts of Australia and the world might be similar. This highlights the urgent need to understand and mitigate human and non-human threats to wildlife, particularly in urban environments, where the rate of biodiversity loss is high. We discuss opportunities and barriers to doing so. [ABSTRACT FROM AUTHOR]

We investigated the effect of land use based on the dominant phytoplankton and physical-chemical variables in the different areas of the Tigris River, within the city of Mosul. Agricultural and urban activities have a significant impact on the water quality of the river. Regardless of physical and chemical variables, phytoplankton act as a bio-indicator of water quality due to their fast and sensitive response to changes in the environment. Our research was conducted in the Tigris River within the city of Mosul by examining the phytoplankton species and the physical-chemical variables at 16 sites during each vegetation period. Point and non-point source pollutants have affected the Tigris River within the city of Mosul, getting into the river from upstream through agricultural activities and by urban activities in the middle section of the city, respectively from both banks. Based on our results, we observed the highest phytoplankton abundance during the October sampling periods, while the lowest occurred during the July sampling period, which was associated with maximum water temperature and absence of rain. According to our study, land use (e.g., agricultural, and urban activities) greatly affected the dominant phytoplankton species and physical-chemical variables of the Tigris River. Oscillatoria sp. dominated all seasons in the agricultural region, while at the same time, we observed an increase in the number of phytoplankton species caused by the nutrient availability upstream on the river. The effects of climate have very significant and characteristic effects in this area, which basically determine the community of organisms and the water quality; the effects resulting from anthropogenic activity significantly modify this. Based on our investigation, in the part of the Tigris River connected to Mosul, we found a clear connection between the pollution caused and the effects of different land uses, through the examination of the algal community and physical-chemical variables in different periods of the year. [ABSTRACT FROM AUTHOR]

Understanding the impact of natural processes and anthropogenic activities on geochemical evolution is vital for groundwater protection and utilization. This research was devoted to identifying the water quality status and the main controlling factors of the hydrochemical evolution of karst groundwater by combining hydrogeochemical indicators with multi-isotope analysis techniques in the Heilongdong Spring Basin, North China. The results showed that the karst groundwater in the area was of meteoric origin, and the dissolution of carbonate minerals was dominant in water–rock interactions. Meanwhile, the positive and negative cation exchange occurred in the process. The main hydrochemical types of karst groundwater were HCO3-Ca·Mg and HCO3-Ca in the recharge area, while the predominant hydrochemical types were the HCO3·SO4-Ca·Mg and HCO3·SO4-Ca in the runoff and discharge area. Under the influence of coal mining and other factors, the average concentrations of major ions kept rising in the runoff area where coal mines were distributed, and the SO42− concentrations of the karst groundwater changed the most in the study area. In addition, sewage from agricultural production and domestic sources had also negatively impacted the quality of regional groundwater in the runoff and discharge area, as evidenced by the increasing NO3− and Cl− contents in the Quaternary sediment groundwater, Permian bedrock groundwater and a small portion of karst groundwater. These results were helpful to explain the mechanism of gradual hydrogeochemical changes and provided a scientific basis for the effective management and utilization of karst groundwater. [ABSTRACT FROM AUTHOR]

Salinity is a decisive abiotic factor that modulates the physiology of aquatic organisms. Salinity itself is modulated by various factors—most notably by anthropogenic factors. In coastal regions, increasing salinity is observed mostly due to the elevated rate of evaporation under high temperatures, especially under global warming. In addition, many other anthropogenic factors, climatic factors, chemicals, etc., also contribute to the changes in salinity in coastal water. Some of these include rainfall, regional warming, precipitation, moisture, thermohaline circulation, gaseous pollutants, dissolved chemicals, wind flow, and biocrusts. Salinity has been found to regulate the osmotic balance and, thus, can directly or indirectly influence the biomarkers of oxidative stress (OS) in aquatic organisms. Imbalances in OS potentially affect the growth, production, and reproduction of organisms; therefore, they are being studied in organisms of economic or aquacultural importance. Salinity-modulated OS and redox regulation as a function of phylum are covered in this review. The literature from 1960 to 2021 indicates that the altered OS physiology under changing salinity or in combination with other (anthropogenic) factors is species-specific, even within a particular phylum. Thus, knowing the response mechanisms of such organisms to salinity may be useful for the management of specific aquatic animals or their habitats. [ABSTRACT FROM AUTHOR]

To better understand the seasonal variation characteristics and trend of water quality in Lake Yilong, we monitored water quality parameters and measured nutrients, including the water temperature (WT), Chlorophyll-a (Chl-a), dissolved oxygen (DO) and pH from September 2016 to May 2020, total nitrogen (TN) and total phosphorus (TP) from October 2016 to August 2018. The results showed that the lake water was well mixed, resulting in no significant thermal stratification. The DO content was decreased in the northwest part of the lake during September and October, resulting in a hypoxic condition. It also varied at different locations of the lake and showed a high heterogeneity and seasonal variability. The Chl-a concentration in Lake Yilong demonstrated seasonal and spatial changes. It was maximum at the center and southwest area of the lake in January. However, in the northwest part of the lake, the maximum value appeared in September and October. The content of TN in the rainy season increased by 75% compared with that in dry season and TP content show a downward trend (from 0.11 mg/L to 0.05 mg/L). The comprehensive nutrition index evaluation shows that the water quality of Lake Yilong in 2016 was middle eutrophic (TLI = 60.56), and that in 2017 (TLI = 56.05) and 2018 (TLI = 56.38) was weak eutrophic, showing that the nutritional status has improved. TN remained at a high level (2.15 ± 0.48 mg/L), water quality needs further improvement. Based on our monitoring and analysis, it is recommended that human activities in the watershed of the lake should be constrained and managed carefully to maintain the water quality of the lake and adopt effective water quality protection and ecological restoration strategies and measures to promote continuous improvement of water quality, for a sustainable social development. [ABSTRACT FROM AUTHOR]

Climate change and human activities significantly affected environmental changes in drylands. However, the relative roles remain unclear regarding these factors' effects on environment changes in drylands. Herein, we analyzed vegetation change trends using remote-sensing datasets to determine the interactions of vegetation, climate, and anthropogenic activities in an arid region of China, Kubuqi Desert. Our study showed that 67.64% of the pixels of fractional vegetation coverage (FVC) increased in 2020 in comparison with those of 1986. The FVC exhibited a significant greening trend (0.0011/yr, p < 0.05) in 1986–2020 as a whole. This greening trend revealed two distinct periods separated by a turning point in 2001. There was no clear trend of FVC before 2001, and then there was a dramatically greening trend since 2001 in most regions of the study area. The increasing rate (0.0036/yr) in the later period was three times higher than the entire period. The accelerated increasing trend was due to the variable compound effects of climate and human activities. The correlation between FVC and precipitation was mainly positive, which outweighs the significantly negative correlation between vegetation and temperature. However, both climatic factors cannot well explain the trends of vegetation dynamics, implying a possible role for human activities. Generally, climate change and anthropogenic activities contributed 42.15% and 57.85% to the overall vegetation variations in 1986–2020. Specifically, the relative role of the two factors was vastly different in two distinct periods. Climate change led the dominant roles (58.68%) in the vegetation variations in 1986–2001, while anthropogenic activities dominated (86.79%) in driving vegetation recovery in the period after 2001. Due to the massive ecological conservation programs such as the Grain for Green Project launched in 2001, substantial deserts have been transformed into grasslands and forests. This analysis highlights the ecological policies largely responsible for vegetation restoration and provides references for ecological protection and sustainable development in eco-fragile ecosystems. [ABSTRACT FROM AUTHOR]

Climate change, combined with ever-increasing anthropogenic activities, has had significant impacts on the vegetation of the Qinghai–Tibet Plateau (QTP). This study quantitatively analyzed the impacts of climate change and human activities on vegetation variation on the QTP from 1982 to 2019 based on AVHRR NDVI data and the residual trend method. The main results were as follows: (1) From 1982 to 2000, the vegetation of the QTP had an obvious restoration process, whereby 67.8% of vegetation coverage areas experienced an increasing trend, while it had a large range of degradation during 2001–2019, especially in the central QTP. (2) The positive effect of climate change on the vegetation of the QTP decreased, and the negative impact increased. The area of positive impact decreased from 68.54% in 1982–2000 to 47.13% in 2001–2019, while the negative-impact area increased from 31.46% to 52.87%. (3) The area negatively affected by human activities increased from 57.68% in 1982–2000 to 79.46% in 2001–2019 and was mainly concentrated in the grassland of the central QTP. The findings of this study provide a scientific basis for vegetation restoration and management in the QTP region. [ABSTRACT FROM AUTHOR]

As an important part of the global ecosystem, wetlands and their dynamics greatly influence regional eco-environment systems. To understand the distributions, change processes and temporal-spatial characteristics of the wetlands of the inland river basin in an arid region (Heihe River Basin, HRB), this paper employed multi-source remote sensing data to facilitate multi-temporal monitoring of the HRB wetland using a wetland information extraction method. First, we performed monitoring of these wetlands for the years 2000, 2007, 2011 and 2014; then, we analyzed the variation characteristics of the spatial-temporal dynamics of the wetlands in the HRB over the last 15 years via the landscape dynamic change model and the transformation matrix. In addition, we studied the possible driving mechanisms of these changes. The research results showed that the total area of the HRB wetlands had decreased by 2959.13 hectares in the last 15 years (Since 2000), and the annual average loss was 1.09%. The dynamics characterizing the HRB wetlands generally presented a trend of slow increase after an initial decrease, which can be classified into three stages. From 2000 to 2007, the total wetland area rapidly decreased; from 2007 to 2011, the area slowly decreased; and from 2011 to 2014, the area gradually increased. The dynamic changing processes characterizing the wetland resources were ascribed to a combination of natural processes and human activities. The main driving mechanisms of wetland dynamic changes include climatic conditions, upper reach water inflows, population, water resources, cultivated area, and policy. The findings of this study can served as reference and support for the conservation and management of wetland resources in the HRB. [ABSTRACT FROM AUTHOR]

Artisanal and small-scale mining is a widespread economic sector in the African Great Lakes Region, where it has an adverse impact on the population's environment. The purpose of this paper is to summarize and consider the typology of the environmental impacts of artisanal and small-scale mining, in particular, the anthropogenic influences on topography with regard to the methods used in raw material mining. Among the most significant environmental aspects related to artisanal and small-scale mining are deforestation, changes in landscape structure, influence over geomorphological processes and hydrological river regime, chemical pollution of soil and watercourses, influencing soil production capacity. The aforementioned factors can cause health problems such as silicosis, poisoning by methyl orthophosphate, or injury during the mining activity itself. Artisanal and small-scale mining could initiate new geomorphological processes or modify naturally occurring geomorphological processes. These dynamic processes are influenced by the topography of the relief, soil properties, and rock composition. Anthropogenic activity in these cases may lead to faster reshaping (degradation or abrasion) of soil shapes. This study covers a broad understanding of environmental impacts of artisanal and small-scale mining with a focus on anthropogenic influencing. [ABSTRACT FROM AUTHOR]

River water quality is a serious concern among scientist and government agencies due to increasing anthropogenic activities and uncontrolled industrial discharge to rivers. The present study was conducted near the river mouth of the Kerian River to assess heavy metal pollution during COVID-19 pandemic-lockdown conditions and post-COVID-19 pandemic-unlock conditions. Twelve samples of shallow, middle, and bottom depths were collected at four locations along a 9.6 km reach. A concentration of eight heavy metals including Cadmium, Chromium, Copper, Iron, Manganese, Nickel, Lead, and Zinc were extracted through atomic absorption spectrometry. Total suspended solid was measured during laboratory experimentation. The results showed that, during the pandemic, concentrations of Nickel, Zinc, and Iron were high at shallow, middle, and bottom depths, respectively. Decreasing orders of heavy metal concentration are variable at different depths due to either their high sinking tendency with other existing components of water matrix or the anthropogenic source. However, almost all values of heavy metals are under the permissible limit of National Water Quality Standards of Malaysia and Food and Drug Administration. A possible reason for the lack of heavy metal pollution may be the restriction of anthropogenic activities during the COVID-19 pandemic. Additionally, no significant differences were observed in total suspended solid. [ABSTRACT FROM AUTHOR]

An accurate assessment of the stocking rate is crucial for maintaining the stable function and the sustainable use of the alpine grassland ecosystem. A new scenario design method to evaluate the reasonable stocking rate is presented in the current work. First, climate change is quantified by potential net primary productivity ( NPP p ) and measured by adopting the Zhou Guangsheng model, and the NPP generated by anthropogenic activities ( NPP h ) is estimated by the distinction between NPP p and actual NPP ( NPP a ) calculated with the application of the Carnegie–Ames–Stanford Approach (CASA) model. Second, using the NPP h and actual grassland productivity consumed by livestock ( NPP ac ), the reasonable stocking rate is obtained. Finally, the driving factors of NPP change in alpine grassland and the reasonable stocking rate are clarified in Qinghai Province during 2005–2018. The results reveal that the temperature of alpine grassland in Qinghai Province has a slight upward trend from 2005 to 2018, and precipitation displays a downward trend. The overall NPP p of alpine grassland demonstrated a downward trend, and precipitation is regarded as the major influencing factor. In addition, the overall NPP h of alpine grassland exhibited a downward trend. The NPP a demonstrated an overall upward trend, where 58.32% of the regional NPP a is in a state of growth, and 41.68% of the regional NPP a is in a state of degradation. According to contribution analysis, anthropogenic activities provided the primary driving factor to promote the restoration of alpine grassland in Qinghai Province. Moreover, the stocking rate must be reduced in 60.77% of the alpine grasslands in Qinghai Province, mostly situated in the eastern and southwestern parts of Qinghai Province, and the other areas must not increase future stocking rates. The current study can theoretically and technically support the construction of Qinghai as the green organic agricultural and livestock product demonstration province and the creation of an ecological civilization highland. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, urbanization and industrialization gradually become an important driving force of groundwater chemical evolution. In this study, Lanzhou City, which is one of the biggest industrial cities in northwest China, was selected to investigate the impacts of city development on groundwater quality. Several hydrochemical methods together with principal component analysis (PCA) were used for the hydrochemistry evolution characteristics and sensitive factors of groundwater chemistry in different urban functional areas of Lanzhou City. The results show that 96% of the groundwater in the study area cannot meet the groundwater quality standards of China. The main factors affecting the quality are SO42−, TDS, total hardness, Mg2+ and Na+. Urbanization and industrialization lead to further deterioration of the already naturally high TDS groundwater. NO3−, Cl− and NH4+ are the characteristic factors of human input sources for commercial residential areas; total Fe and NO3− are the characteristic factors of new urban areas in the urban-rural junction; and SO42−, NO3−, Cl−, Total Fe, Mn2+, F−, I−, Pb2+, Cr6+ and As3+ are the characteristic factors of industrial areas. Domestic sewage infiltration and manure infiltration are the main driving factors of groundwater quality deterioration in commercial residential areas. Nitrate fertilizer infiltration and sewage irrigation are the main factors leading to the increase in nitrate nitrogen in groundwater in the new urban area. Industrial wastewater leakage and organic pollution that promote the dissolution of minerals in the aquifer (the dissolution of fluorine-containing minerals and reductive dissolution of iron manganese oxides) are the main driving factors for the deterioration of groundwater quality in the petrochemical industrial area. [ABSTRACT FROM AUTHOR]

Soil plays many critical roles in ecosystem health. As urbanization expands into once industrial and commercial lands, there is increased potential for human exposure to soil contaminants, including heavy metals introduced by past anthropogenic activities. Thus, it is important to assess soil contamination in such areas for public health concerns. In this study, we investigated the physico-chemical characteristics of soils from an abandoned hospital complex on Ellis Island, New York (NY) - New Jersey (NJ) to assess the geochemical conditions of the local soil environment and metal contamination from historical activities, including coal-burning and use of lead arsenate insecticide and lead paint. The soil texture, nutrient content and heavy metal (As, Pb, Cr, Cd, Cu and Hg) concentrations were determined and their impact was evaluated. Soils were mostly sandy loam with C:N ratios of about 20:1. Heavy metals were elevated compared to background soils. Concentrations of acid extractable As and Pb ranged from 8.12 to 26.3 mg·kg-1 and 257 to 1008 mg·kgkg-1, respectively. Total-Hg concentrations varied from 0.191 to 0.899 mg·kg-1, with the higher levels likely from local coal-burning and deposition from the prevailing westerly winds. Overall, we find that even after 60 years of abandonment, the impact to Ellis Island soil from past human activities can still be observed. [ABSTRACT FROM AUTHOR]

On 3 April 2017, a Mw 6.5 earthquake occurred in Botswana, representing the second-strongest earthquake registered since 1949. Such an intraplate event occurred in a low seismic hazard area and was suspected to be an artificial earthquake induced by nearby anthropogenic activities (gas extraction). The possible relation between anthropogenic activities and the earthquake occurrence has been qualitatively investigated. We estimated the geometric and kinematic characteristics of the causative fault from the modeling of Sentinel-1 InSAR interferograms. Our best-fit solution for the main shock is represented by a normal fault located at a depth greater than 20 km, dipping 65° northeast, with a right-lateral component, and a mean slip of 2.7 m. The retrieved fault geometry and mechanism are incompatible with the hypothetical stress perturbation caused by the anthropogenic activities performed in the area. Therefore, the 3 April 2017 Botswana earthquake can be classified as a natural intraplate earthquake can be classified as a natural intraplate earthquake. [ABSTRACT FROM AUTHOR]

Lake Urmia, the second largest saline Lake on earth and a highly endangered ecosystem, is on the brink of a serious environmental disaster similar to the catastrophic death of the Aral Sea. Progressive drying has been observed during the last decade, causing dramatic changes to Lake Urmia's surface and its regional water supplies. The present study aims to improve monitoring of spatiotemporal changes of Lake Urmia in the period 1975-2015 using the multi-temporal satellite altimetry and Landsat (5-TM, 7-ETM+ and 8-OLI) images. In order to demonstrate the impacts of climate change and human pressure on the variations in surface extent and water level, Lake Sevan and Van Lake with different characteristics were studied along with the Urmia Lake. Normalized Difference Water Index-Principal Components Index (NDWI-PCs), Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Normalized Difference Moisture Index (NDMI),Water Ratio Index (WRI), Normalized Difference Vegetation Index (NDVI), AutomatedWater Extraction Index (AWEI), and MultiLayer Perceptron Neural Networks (MLP NNs) classifier were investigated for the extraction of surface water from Landsat data. The presented results revealed that MLP NNs has a better performance in the cases where the other models generate poor accuracy. The results show that the area of Lake Sevan and Van Lake have increased while the area of Lake Urmia has decreased by ~65.23% in the past decades, far more than previously reported (~25% to 50%). Urmia Lake's shoreline has been receding severely between 2010 and 2015 with no sign of recovery, which has been partly blamed on prolonged droughts, aggressive regional water resources development plans, intensive agricultural activities, and anthropogenic changes to the system. The results also indicated that (among the proposed factors) changes in inflows due to overuse of surface water resources and constructing dams (mostly during 1995-2005) are the main reasons for Urmia Lake's shoreline receding. The model presented in this manuscript can be used by managers as a decision support system to find the effects of building new dams or other infrastructures. [ABSTRACT FROM AUTHOR]

Anthropogenic activities and climate change affect the type, structure and function of ecosystems, resulting in important changes in vegetation net primary productivity (NPP). Therefore, in this study we used the vegetation photosynthesis model (VPM) to reveal the spatiotemporal variations in NPP in Xinjiang from 2000 to 2019. The impacts of climate change and anthropogenic activities on NPP changes were quantified and separated by the residual analysis-control variables (RES-CON) method. The results showed that the average NPP in Xinjiang increased by 17.77% from 2000 to 2019. Anthropogenic activities and climate change generally had a positive impact on NPP from 2000 to 2019. The most important anthropogenic activity was land use and land cover (LULC) transformation from grass to arable land, which significantly increased vegetation productivity. Regarding climate change, precipitation has played a significant role in promoting the productivity of vegetation. Overall, the average contribution of climate change (temperature and precipitation) to NPP variation (21.44%) is much greater than the contribution of anthropogenic activities (3.46%), but in areas where anthropogenic activities occur, the average contribution of anthropogenic activities to NPP variation (75.01%) is much greater than the average contribution of climate change (15.53%). Where there are no anthropogenic activities, the average contribution of climate change to NPP variation is 21.72%. In summary, anthropogenic activities are the main driver of NPP variation in areas where anthropogenic activities occur, while the total area in Xinjiang where climate change is the most important driver is larger than the total area where anthropogenic activities are the dominant driver. [ABSTRACT FROM AUTHOR]

The concentration of nitrogen dioxide (NO2) is worsening across the globe alongside growth in industrial and general anthropogenic activities. Due to its serious health implications with long-term exposure, studies on NO2 concentration have gained space in the academic literature. In this study, awareness is created on the levels of NO2 across four (4) locations within the Tema Metropolitan area, with specific interest in selecting locations and periods significantly saturated with NO2 within the study area. NO2 was measured using RKI Eagle, an instrument with a built-in sensor for a specific gas measurement. Measurements were taken day and night at sampling points around 100 meters apart in each location. Data collection was performed over a nine (9)-month period. The Generalized Linear model is explored for selecting locations and periods significantly affected by NO2. From the results, the fourth week (26th–31st) of July 2020, the fourth week (27th–31st) of December 2020, the first week (1st–7th) of January 2021, and the fourth week (24th–31st) of January 2021 recorded severe concentrations of NO2. Additionally, the lives of residents in the Oil Jetty and the VALVO hospital areas were found to be the most endangered, as they recorded significantly high concentrations of NO2. In a developing country such as Ghana, this study is useful for monitoring NO2 concentrations in similar areas to inform decision making and environmental policy formulation. [ABSTRACT FROM AUTHOR]

Climate change and anthropogenic activities are widely considered the main factors affecting vegetation growth. However, their relative contributions are under debate. Within the non-climatic impact, detailed human activities, particularly government policy adjustments, are less investigated. In this study, we develop a fractional vegetation coverage (FVC) extraction method based on MODIS-EVI satellite data to analyze the spatiotemporal variation of vegetation and its attributions in the China–Mongolia–Russia Economic Corridor (CMREC). The average FVC has improved, with a general increase of 0.02/10a from 2000 to 2020. We construct a driving factor identification system for FVC change, based on partial and multiple correlation coefficients, and we divide the driving forces of FVC changes into seven climate-driven types and one non-climate-driven type. The results reveal that FVC changes caused by climatic factors account for 28.2% of CMREC. The most prominent greening (19.5%) is precipitation-driven, and is extensively distributed in Khentii Aimag, Mongolia; southeast Inner Mongolia; west Jilin Province; and southwest Heilongjiang Province, China. Moreover, we quantify the relative contribution of climatic and non-climatic factors to significant FVC change using the first-difference multivariate regression method. The results indicate that the effects of non-climatic factors on vegetation change outweigh those of climatic factors in most areas. According to the land cover change and regional policy adjustment, anthropogenic activities such as afforestation, reclamation, and planting structure adjustment explain most vegetation improvement in the Northeast Plain; eastern Inner Mongolia; and the Hetao Irrigation District, China. Meanwhile, both vegetation improvement and degradation disperse concurrently in the Mongolian and Russian parts of CMREC, where climate change and anthropogenic activities positively and negatively affect vegetation change, respectively. Despite the greening in most CMREC, it must be noted that human-induced greening is unsustainable to some degree. The overdevelopment of black soil area and sandy land, adverse effects of afforestation projects, and natural hazards related to weather and climate extremes altogether threaten the local ecological security in the long run. Therefore, governments should develop new desertification countermeasures in accordance with the laws of nature, and enhance international cooperation to guarantee the ecological safety of CMREC. [ABSTRACT FROM AUTHOR]

The deterioration signs of water quality in the Hau River are apparent. The present study analyzed the surface water quality of the Hau River using multivariate statistical techniques, including principal component analysis (PCA) and Cluster Analysis (CA). Eleven water quality parameters were analyzed at 19 different sites in An Giang and Can Tho Provinces for 12 months from January to December 2019. The findings show high levels of Biological Oxygen Demand (BOD), Total Soluble Solids (TSS), and total coliform, all year round. The PCA revealed that all the water quality parameters influenced the water quality of the Hau River, hence the relevance for water sample scrutiny. The dendrogram of similarity between sampling sites showed a maximum similarity of 95.6%. The Accumulation Factor (AF) trend showed that the concentrations/values of TSS, BOD, and phosphate (PO43−) in the downstream were 1.29, 1.53, and 1.52 times, respectively, greater than the upstream levels. Despite most of the parameters analyzed supporting aquaculture production, caution is needed in the regulation of pollution point sources to undertake sustainable aquaculture production. [ABSTRACT FROM AUTHOR]

Antibiotics revolutionized modern medicine and have been an excellent tool to fight infections. However, their overuse and misuse in different human activities such as health care, food production and agriculture has resulted in a global antimicrobial resistance crisis. Some regions such as Latin America present a more complex scenario because of the lack of resources, systematic studies and legislation to control the use of antimicrobials, thus increasing the spread of antibiotic resistance. This review aims to summarize the state of environmental antibiotic resistance in Latin America, focusing on water resources. Three databases were searched to identify publications on antimicrobial resistance and anthropogenic activities in relation to natural and artificial water ecosystems. We found that antibiotic resistant bacteria, mainly against beta lactam antibiotics, have been reported in several Latin American countries, and that resistant bacteria as well as resistant genes can be isolated from a wide variety of aquatic environments, including drinking, surface, irrigation, sea and wastewater. It is urgent to establish policies and regulations for antibiotic use to prevent the increase of multi-drug resistant microorganisms in the environment. [ABSTRACT FROM AUTHOR]

Recognition of sustainability issues around water resource consumption is gaining traction under global warming and land utilization complexities. These concerns increase the challenge of gaining an appropriate comprehension of the anthropogenic activities and natural processes, as well as how they influence the quality of surface water and groundwater systems. The characteristics of water resources cause difficulties in the comprehensive assessment regarding the source types, pathways, and pollutants behaviors. As the behavior and prediction of widely known contaminants in the water resources remain challenging, some new issues have developed regarding heavy metal pollutants. The main aim of this review is to focus on certain essential pollutants' discharge from anthropogenic activities categorized based on land-use sectors such as industrial applications (solid/liquid wastes, chemical compounds, mining activities, spills, and leaks), urban development (municipal wastes, land use practices, and others), and agricultural practices (pesticides and fertilizers). Further, important pollutants released from natural processes classified based on climate change, natural disasters, geological factors, soil/matrix, and hyporheic exchange in the aquatic environment, are also discussed. Moreover, this study addresses the major inorganic substances (nitrogen, fluoride, and heavy metals concentrations). This study also emphasizes the necessity of transdisciplinary research and cross-border communication to achieve sustainable water quality using sound science, adaptable legislation, and management systems. [ABSTRACT FROM AUTHOR]

The Tlemcen region is characterized by very diverse and steep areas exposed to gravity hazards, especially in high and medium mountain areas. Tlemcen National Park was chosen for this study, the main objective of which is to map fragile areas in close relation to reduced vegetation cover due to land-use changes and forest fires. Multi-source data were used to monitor land use/land cover (LULC)patterns in the study area between 1987 and 2017. The methodology is based on an object-oriented classification of the Landsat images, using the K nearest neighbor method for mapping the major LULC classes at the national park level. The results show that LULC is constantly changing in the study area. In 1987, the landscape was made up of (16.5%) oak forests (holm oak, cork oak, zean oak) and Aleppo pine, which then deteriorated following repeated fires in the nineties to barely represent 7.22% of the surface in 1995, followed by a fast forest reclamation, with the forest area doubling in 10 years (13.46% of the area in 2005), and a near stabilization of the forest cover in 2017 with 14.68% of the area. These mutations are mainly due to fluctuations in anthropogenic action. Despite past declines and disturbances, the current forested area in the Tlemcen area represents significant forest capital classified as a national park to be protected and developed. [ABSTRACT FROM AUTHOR]

Microplastic is an emerging global pollutant that have attracted a great deal of attention from researchers and the public. Guangdong Province has a large population and a relatively well-developed economy, but lacks a modern pollution control system. Guangdong has a long coastline with varying levels of pollution, and little research has been conducted on microplastics. Therefore, we investigated the level of microplastic pollution in coastal areas of Guangdong Province, and the abundance of microplastics in surface waters and sediments at 13 sampling sites. The abundance of microplastics in surface water and sediment samples ranged from 850 to 3500 items/L and 433.3 to 4166.3 items/kg, respectively. Fiber is the main type of microplastics in both surface water and sediment. The sampled microplastics were typically transparent. Raman results show that the surface water sample mainly includes rayon (38.2%), polyethylene terephthalate (16.4%), and ethylene/vinyl acetate copolymer (12.7%). This study used the pollution load index method to evaluate the pollution risk of microplastics along the coast of Guangdong, and provided the basis for the formulation of environmental policy. [ABSTRACT FROM AUTHOR]

The major lockdown due to the COVID-19 pandemic has affected the socio-economic development of the world. On the other hand, there are also reports of reduced pollution levels. In this study, an indicative analysis is adopted to understand the effect of lockdown on the changes in the water quality parameters for Lake Hussain Sagar using two remote sensing techniques: (i) spectral reflectance (SR) and (ii) chromaticity analysis (Forel-Ule color Index (FUI) and Excitation Purity). The empirical relationships from earlier studies imply that (i) increase in SR values (band B2) indicates a reduction in Chlorophyll-a (Chl-a) and Colored Dissolved Organic Matter (CDOM) concentrations, and (ii) increase in FUI indicates an increase in Total Suspended Solids (TSS). The Landsat 8 OLI satellite images are adopted for comparison between (i) January to May of year 2020: the effect of lockdown on water quality, and (ii) March and April for years 2015 to 2020: historical variations in water quality. The results show notable changes in SR values and FUI due to lockdown compared to before lockdown and after unlock suggesting a significant reduction in lake water pollution. In addition, the historical variations within April suggest that the pollution levels are least in the year 2020. [ABSTRACT FROM AUTHOR]

The formation of sinkholes in Winkler County, Texas is concerning due to the amount of oil and gas infrastructure and the potential for catastrophic losses. Evidences of new and potential sinkholes have been documented, and determining the cause of these sinkholes is paramount to mitigate the devastating consequences thereof. Studies have shown that the Wink sinkholes result from both natural and anthropogenic influences. Data depicting land-cover changes, alterations in the hydrologic systems, climate changes, and oil and gas activity were analyzed in an effort to better understand the link between these processes and sinkhole formation. Results indicate that the combination of these processes lead to the current state. Land cover changes were highest in shrub versus grasses, undeveloped to developed and croplands. Rises in temperature and a decrease in precipitation indicate a shift towards a more arid climate. Changes to the hydraulic system are a direct result of these land cover changes while the groundwater quality depicts an environment prone to dissolution. Historical oil and gas activities have created pathways of meteoric water infiltration to the underlying limestone and evaporite formation. The combination of these processes create an environment that accelerates sinkhole formations. Understanding these processes allows for the development and implementation of better land practices, better groundwater protections, and the need for monitoring and maintaining aging oil and gas infrastructure. [ABSTRACT FROM AUTHOR]

In order to protect the water environment in seriously polluted basins, the impacts of anthropogenic activities (sewage outfalls and land use) on water quality should be assessed. The Bayesian network (BN) provides a convenient way to model these complex processes. In this study, anthropogenic impacts on chemical oxygen demand (COD) and biochemical oxygen demand (BOD) were evaluated in the Huaihe River basin (HRB) considering dry and wet seasons and different spatial scales. The results showed that anthropogenic activities had the most significant impacts on COD and BOD at the catchment scale. In dry seasons, sewage outfalls played an important role in organic pollution. Farmland became the most important source in wet seasons although it had a "sink" process in dry seasons. Intensive human activities in urban made significant contributions to increased COD levels. Grassland had a negative relationship with organic pollution, especially in dry seasons. Therefore, governments should implement strategies to control organic matters transported from urban and farmland regions. Increasing the efficiency of wastewater treatments and the percentage of grassland in the riparian zone could improve water quality. These results can enhance understanding of anthropogenic impacts on water quality and contribute to efficient management for river basins. [ABSTRACT FROM AUTHOR]

During the past 20 years, the ecological environment of Dianchi Lake has been adversely affected by climate change and human activities, which directly affected the ecosystem and biodiversity of the Dianchi Lake watershed. Analyzing the spatiotemporal variation of chlorophyll a (Chla) concentration of Dianchi Lake and exploring the internal and external factors effect on Chla concentration is the basis for controlling and improving the water ecological environment of Dianchi Lake, and it is also the key to prevent and control the water pollution of Dianchi Lake. In this study, the water quality of Dianchi Lake was examined using 12 water quality indicators from 10 water quality monitoring sites for the duration between 2000 to 2017. The changing characteristics of Chla in the context of internal and external factors were analyzed. The spatiotemporal evolution process of Chla concentration in the past 20 years was also evaluated. The results indicated that Chla concentration was significantly and positively correlated with the chemical oxygen demand (CODCr), the Dianchi Lake watershed gross domestic product (GDP), and the impervious surface area (ISA) of the watershed, in addition to the total phosphorus (TP), biochemical oxygen demand (BOD5), ammonia hydrogen (NH3-N), water temperature (WT), and civil vehicle ownership. Moreover, a significant and negative correlation was noticed between Dianchi Lake watershed GDP and NH3-N, BOD5, TP, total nitrogen (TN), and comprehensive nutrition state index (TLI). The Dianchi Lake population was negatively correlated with TP, TLI, and BOD5. The concentration of Chla in Dianchi Lake was affected by both internal factors, and external factors such as anthropogenic activities, the latter of which was the main cause of the continuous deterioration of the lake water quality. [ABSTRACT FROM AUTHOR]

Karst aquifers are prominent sources of water worldwide; they store large amounts of water and are known for their beautiful springs. However, extensive groundwater development and climate variation has resulted in a decline in the flow of most karst springs; some have even dried up. In order to obtain a better understanding of the factors contributing to this development, this study introduced grey system models, which quantified spring flow, taking Jinci Springs (China), which dried up in May 1994, as an example. Based on the characteristics of Jinci Springs, spring flow was divided into two stages: first (1954–1960), when the spring flow was affected only by climate variation; and second (1961–1994), when the flow was impacted by both climate variation and anthropogenic activities. The results showed that Jinci Springs flow had a strong relationship with precipitation occurring one year and three years earlier in the first stage. Subsequently, a grey system GM (1,3) model with one-year and three-year lags was set up for the first stage. By using the GM (1,3) model, we simulated the spring flow in the second stage under effects of climate variation only. By subtracting the observed spring flow from the simulated flow, we obtained the contribution of anthropogenic activities to Jinci Springs' cessation. The contribution of anthropogenic activities and climate variation to the decline was 1.46 m3/s and 0.62 m3/s, respectively. Finally, each human activity that caused the decline was estimated. The methods devised herein can be used to describe karst hydrological processes that are under the effects of anthropogenic activities and climate variation. [ABSTRACT FROM AUTHOR]

Anthropogenic activities have had diversiform impacts on the surrounding river and environments. A study on the surface water of the Lhasa River Basin was undertaken to assess its hydrogeochemical characteristics under the influence of anthropogenic activities. A total of 16 samples collected from the Lhasa River were analyzed for pH, electric conductivity (EC), oxidation-reduction potential (ORP), total dissolved solids (TDS), major cations (K+, Na+, Ca2+, and Mg2+), major anions (Cl−, SO42−, HCO3−, and NO3−), and trace metals. The pH of the analyzed water samples varied from 6.40 to 9.10, indicating alkaline in nature. The EC values varied from 77.3 to 213 μs/cm while the TDS values varied from 73.37 to 217.55 mg/L. HCO3− and SO42− are the dominant anions while Ca2+ and Na+ are the dominant cations in the river water. The concentration of alkaline earth metals (Ca2+ + Mg2+) exceed the alkali metals (Na+ + K+) and HCO3− dominates over SO42− + Cl− concentrations in the majority of the surface water samples. Ca2+-Mg2+-HCO3− and Ca2+-Mg2+-Cl− are the dominant hydrogeochemical facies in the surface water of the area. The water chemistry is mainly controlled by rock weathering with secondary contribution from anthropogenic sources. The content of trace elements in the Lhasa River is low, basically at the natural background value. The high content of individual elements is mainly due to the mineral resource exploitation and geothermal resources in the basin. Countermeasures and attention should be payed to these aspects, such as the construction of water conservancy facilities, urban economic development, the development of mining activities, and sewage and wastewater discharge, so as to protect the water quality and sustainable development of the Lhasa River Basin. [ABSTRACT FROM AUTHOR]

Understanding the interaction of surface water and groundwater affected by anthropogenic activities is of great importance for water resource and water quality management. The Xiong'an New Area, located in the North China Plain, has been designated a new building area by China's government. Groundwater has been over pumped and artificial water was transferred to meet the water supply in this region. Therefore, the natural interaction of surface water and groundwater has been greatly changed and there has been a complex impact of the groundwater from anthropogenic activities. In this study, we used water chemical ions and stable isotopes of δ2H and δ18O to assess the interaction of surface water and groundwater in the Xiong'an New Area. We carried out field surveys and water sampling of the Fu River (domestic waste water discharge), Lake Baiyangdian (artificial water transfer), and the underlying groundwater along the water bodies. Results show that the artificial surface water (discharged and transferred) became the major recharge source for the local groundwater due to the decline of groundwater table. We used groundwater table observations, end-member mixing analysis of the stable isotopic composition and chloride tracers to estimate the contributions of different recharge sources to the local groundwater. Due to the over pumping of groundwater, the lateral groundwater recharge was dominant with a contribution ratio ranging from 12% to 78% in the upper reach of the river (Sections 1–3). However, the contribution of lateral groundwater recharge was estimated to be negligible with respect to the artificial water recharge from Lake Baiyangdian. Seepage from the Fu River contributed a significant amount of water to the connecting aquifer, with a contribution ranging from 14% to 75% along the river. The extent of the river influence into the aquifer ranges as far as 1400 m to the south and 400 m to the north of the Fu River. Estimations based on isotopic fractionation shows that about 22.3% of Lake Baiyangdian water was lost by evaporation. By using the stable isotopes of oxygen and hydrogen in the lake water, an influencing range of 16 km west of the lake was determined. The interaction of the surface water and groundwater is completely changed by anthropogenic activities, such as groundwater over pumping, waste water discharge and water transfer. The switched interaction of surface water and groundwater has a significant implication on water resources management. [ABSTRACT FROM AUTHOR]

Following a targeted campaign of violence by Myanmar military, police, and local militias, more than half a million Rohingya refugees have fled to neighboring Bangladesh since August 2017, joining thousands of others living in overcrowded settlement camps in Teknaf. To accommodate this mass influx of refugees, forestland is razed to build spontaneous settlements, resulting in an enormous threat to wildlife habitats, biodiversity, and entire ecosystems in the region. Although reports indicate that this rapid and vast expansion of refugee camps in Teknaf is causing large scale environmental destruction and degradation of forestlands, no study to date has quantified the camp expansion extent or forest cover loss. Using remotely sensed Sentinel-2A and -2B imagery and a random forest (RF) machine learning algorithm with ground observation data, we quantified the territorial expansion of refugee settlements and resulting degradation of the ecological resources surrounding the three largest concentrations of refugee camps—Kutupalong–Balukhali, Nayapara–Leda and Unchiprang—that developed between pre- and post-August of 2017. Employing RF as an image classification approach for this study with a cross-validation technique, we obtained a high overall classification accuracy of 94.53% and 95.14% for 2016 and 2017 land cover maps, respectively, with overall Kappa statistics of 0.93 and 0.94. The producer and user accuracy for forest cover ranged between 92.98–98.21% and 96.49–92.98%, respectively. Results derived from the thematic maps indicate a substantial expansion of refugee settlements in the three refugee camp study sites, with an increase of 175 to 1530 hectares between 2016 and 2017, and a net growth rate of 774%. The greatest camp expansion is observed in the Kutupalong–Balukhali site, growing from 146 ha to 1365 ha with a net increase of 1219 ha (total growth rate of 835%) in the same time period. While the refugee camps’ occupancy expanded at a rapid rate, this gain mostly occurred by replacing the forested land, degrading the forest cover surrounding the three camps by 2283 ha. Such rapid degradation of forested land has already triggered ecological problems and disturbed wildlife habitats in the area since many of these makeshift resettlement camps were set up in or near corridors for wild elephants, causing the death of several Rohingyas by elephant trampling. Hence, the findings of this study may motivate the Bangladesh government and international humanitarian organizations to develop better plans to protect the ecologically sensitive forested land and wildlife habitats surrounding the refugee camps, enable more informed management of the settlements, and assist in more sustainable resource mobilization for the Rohingya refugees. [ABSTRACT FROM AUTHOR]