Environmental Monitoring and Assessment最新文献

This study investigates the role of secondary metabolites in the phytoremediation of cadmium-contaminated water using Pontederia parviflora and Salvinia auriculata. Unlike previous studies, which primarily focus on the physical removal of heavy metals by plants, our research explores the biochemical interactions between these plants secondary metabolites and cadmium ions. We employed liquid chromatography-diode array detector-mass spectrometry (LC-DAD-MS) to analyze the chemical composition of the plant extracts and assessed the impact of these metabolites on cadmium accumulation and removal efficiency. Our findings reveal that the removal of secondary metabolites from plant biomass did not significantly alter the cadmium removal efficiency, challenging the commonly held belief that these metabolites play a central role in heavy metal sequestration. Additionally, our results indicate that cadmium uptake is more closely associated with structural components of plant tissues rather than the presence of specific secondary metabolites. This study provides new insights into the mechanisms of phytoremediation and suggests that the optimization of plant selection for remediation efforts should focus on the structural properties of plant tissues rather than secondary metabolite content.

Water scarcity remains a significant challenge to agricultural sustainability in semi-arid and Mediterranean regions, with Kermanshah Province, Iran, exemplifying this issue. This study evaluates water resource dependency and water stress in Kermanshah's agricultural sector from 2010 to 2019, using comprehensive water footprint indicators, including the Water Stress Index (WSI), Agricultural Water Stress Index (AWSI), Blue Water Scarcity Index (BWS), and Regional Agricultural Water Footprint Intensity (AWFI). Plant-related data, such as evapotranspiration, effective rainfall, crop water requirements, and irrigation needs, were estimated using NETWAT (Network for Water and Agriculture Technologies) software alongside the FAO-Penman–Monteith (Food and Agriculture Organization)-Penman–Monteith equation. The results reveal that producing 26.62 million tons of crops (field and orchard crops) required a total water footprint of 159.8 Gm³, with field crops contributing over 90% of the total. Blue water, representing surface and groundwater resources, was the largest component (71.99%), followed by green water (16.86%) and gray water (11.14%). Among orchard crops, walnuts exhibited the highest total water footprint (4,079.75 m³/ton) under irrigated conditions, while, grapes had a total water footprint of 626.63 m³/ton. For field crops, chickpeas demonstrated a high-water footprint due to irrigation demand and fertilizer use, with a total of 4,646 m³/ton. Water stress indices showed persistent resource pressure. The BWS index exceeded 0.8 in all years, peaking at 0.93 in 2016, while the AWSI peaked at 0.87 in 2013, highlighting severe agricultural water scarcity. Water deprivation reached a maximum of 8,380 MCM in 2014, driven by low rainfall and overextraction of water resources. Although precipitation improvements in 2018–2019 slightly alleviated pressure, increased agricultural demand prevented significant recovery. The findings underscore the urgent need for sustainable water management strategies, including advanced irrigation technologies, optimized fertilizer application, and cultivation of high-yield, water-efficient crops.

Industrial wastewater treatment is crucial for environmental protection and public health. This study aimed to investigate the efficiency of the coagulation-flocculation-aided adsorption (C/F-A) system utilizing aluminum salt (AS) coagulant and characterized acid-activated kaolin clay adsorbent (KC) for the removal of pollutants from vegetable oil processing industrial wastewater (VOPIW). The objectives were to optimize the operational parameters of the C/F-A system, evaluate the adsorption capacity of KC, analyze the removal mechanisms, and assess the feasibility of scale-up for industrial applications. Batch experiments were conducted at 25 °C and pH 6–8 to determine optimal conditions for turbidity and total suspended solids (TSS) removal. The Smoluchoski kinetic model and various isotherms (Redlich-Peterson, Elovich, and Dubinin-Radushkevich) were employed for mechanistic analysis. Optimal conditions of 0.2 g/L dosage, pH 6, and 12 min settling time resulted in 96% turbidity and 97% TSS removals. Significant reductions were achieved for various pollutants, including Cu (84%), Fe (80%), Mn (85%), Pb (71%), and Al (98%). The sorption capacities of KC for various pollutants were determined, with the highest recorded for Cu at 35.47 mg/g C. Scale-up analysis was conducted to meet WHO effluent discharge requirements resulting in organic loading corresponding to TDS (2.94 × 10⁹ mg/day), DO (5.1 × 10⁸ mg/day), BOD (4.33 × 10⁸ mg/day), and COD (3.99 × 10⁸ mg/day). The mechanistic parameters confirmed an optimum sweep-flocculation constant, 6.2 × 10⁻³ L/g·min, and half-life, 101 min⁻¹. The study highlighted the effectiveness of the C/F-A system using KC for removing contaminants from VOPIW, suggesting its potential as a cost-effective and sustainable method for industrial wastewater treatment, thereby aiding environmental protection.

Graphical Abstract

In the lush tea estates of Northeast India, the growth of the tea plant (Camellia sinensis L.) hinges on the intricate dance of soil properties. This present study delves into the soil characteristics of sixteen tea estates, situated spanning the verdant landscapes of Assam and the enchanting Darjeeling hills in West Bengal. We meticulously analyzed soil pH, organic carbon (OC) content, texture, available nitrogen, phosphorus, potassium, sulfur, exchangeable calcium, and magnesium using rigorous standard methods. In our analysis, we also investigated various forms of soil acidity. These include exchangeable acidity (EA), exchangeable aluminum (EAl), exchangeable hydrogen (EH), extractable acidity (ExtA), hydrolytic acidity (HA), non-exchangeable aluminum (NEA), pH-dependent acidity (pHDA), total acidity (TA), and total potential acidity (TPA). The findings revealed that most of the estates have soil with acidity levels below 4.50 rendering it unsuitable for tea cultivation. The various acidity fractions exhibited specific ranges for different soil components, with pH-dependent acidity emerging as the primary contributor to TPA, and EAl, exerting the most significant influence on TA in the soils being investigated. The study also demonstrated a strong inverse relationship between pH and all forms of acidity, except for non-exchangeable acidity and hydrolytic acidity. Furthermore, the presence of OC was found to have a substantial impact on soil acidity, displaying a notably strong positive association with EA, pHDA, and TPA. Canonical correlation analysis (CCA) revealed the relationship between soil acidity and its physical and chemical properties. The principal component analysis (PCA) showed that the first six PCs accounted for over 80% of the variability, with PC-1, PC-2, and PC-3 describing 31.86, 20.78, and 14.13% respectively. These results highlight the urgent need for soil amendments and better field management practices to combat soil acidity for sustainable tea cultivation.

Coal resource–based cities were once pillars of significant economic and social development, but after resource exhaustion, these cities are at a critical crossroads and need to transition towards sustainable development and ecological urban renewal. The unique landscape patterns of these cities are associated with extensive coal mining, and their dynamic changes are intrinsically linked to habitat quality. However, this relationship has not been fully explored in existing research. Additionally, the spatial–temporal dynamics and non-stationary scale effects of landscape patterns on habitat quality are often overlooked. This study selects Jiawang, a typical coal resource–exhausted city in eastern China, as a case study. We focus on the ecological transition period from 2000 to 2020. Based on land cover data, the study quantitatively describes the spatiotemporal evolution of landscape patterns and habitat quality. A novel multiscale geographically and temporally weighted regression (MGTWR) model is used to analyze and quantify the complex effects of landscape patterns on habitat quality at different spatiotemporal scales. The study further elucidates the dynamic interaction between landscape patterns and habitat quality, emphasizing key non-stationary scale effects. The findings provide insights for strategic ecosystem management and spatial planning, offering a blueprint for the sustainable transformation of coal resource-exhausted cities.

Soil quality is essential for sustaining agricultural productivity, globally. Hence, this study evaluated the effects of elevation gradients and soil depths on agricultural land quality in the Seti River watershed, Pokhara Metropolitan City (PMC), Nepal. Using a stratified random sampling method, 60 samples were collected across three elevation gradients (500–700 m, 700.1–900 m, 900.1–1100 m) at depths of 0–15 cm and 15–30 cm. The soil quality index (SQI) revealed good soil quality across all elevations, with values of 0.88, 0.86, and 0.82 for lower, mid, and higher elevations, respectively, despite variations in individual nutrient levels. Elevated nitrogen (N) and phosphorus (P) levels highlighted the need for regulated fertilizer application. Kruskal–Wallis test identified significant decreases in soil organic matter (SOM) and soil organic carbon (SOC) with increasing elevation. Depth-wise analysis showed that the potential of hydrogen (pH) in the topsoil (0–15 cm) was nearly neutral, while the subsoil (15–30 cm) exhibited weak acidity. Nutrient concentrations, including N, P, and potassium (K), were significantly higher in the topsoil than in deeper layers, indicating a need for prudent nutrient management to minimize leaching and maintain soil health. Accordingly, PMC soils can be considered favorable for agricultural productivity; however, site-specific management strategies should performed. Reducing excessive fertilizer use in low-elevation areas can prevent nutrient imbalances while monitoring and enhancing SOM in higher elevations through compost or green manure application is recommended. These actions can enhance soil fertility, reduce environmental impacts, and promote agricultural resilience.

The Himalayan rivers are the major source of freshwater resources and have a tremendous potential for hydroelectric generation. However, assessing the water availability under climate change is challenging due to data scarcity, undulating topography, and complex climatic conditions. SWAT modeling investigates all potential consequences of variations in climate on the hydrological fluxes in the Upper Bhagirathi River Basin. Two global circulation models (GCMs) with three different climatic scenarios were employed. Quantile mapping has been used to correct the bias of GCM data. The developed model accurately simulated streamflow during calibration and validation at daily (NSE = 0.79 − 0.74, r = 0.89–0.87, and RMSE = 61.95 m³/s–79.75 m³/s) and monthly (NSE = 0.92 − 0.93, r = 0.96–0.97, and RMSE = 34.19 m³/s–37.39 m³/s) time steps. The analysis of the outcomes from MIROC6 and NorESM2-LM revealed that the rise in streamflow, surface runoff, lateral flow, and baseflow is more pronounced in MIROC6 across all three climatic scenarios. Under all scenarios, both MIROC6 and NorESM2-LM models show significant variations in snowfall and snowmelt patterns, with the area under snowfall reaching up to 51.65% for MIROC6 under SSP1-2.6 and snowmelt area peaking at 64.30% for MIROC6 under SSP2-4.5. This study’s findings will offer essential insights for policymakers, practitioners, and water resource managers in developing climate-resilient strategies for sustainable water management in Himalayan catchments.

The construction land expansion (CLE) in China, based on the occupation of cultivated land, has resulted in a notable alteration of the landscape of cultivated land, leading to an increase in cultivated land fragmentation (CLF) in China. However, previous studies have devoted minimal attention to CLF due to CLE, thereby constraining the coordination of CLE and cultivated land conservation. Accordingly, the study examined the impact mechanism of CLE on CLF utilizing land use/cover datasets and the geographically weighted regression model from 2000 to 2020 in China. The findings indicate that a considerable amount of cultivated land was converted into construction land. The extent of CLF increased from 0.352 in 2000 to 0.383 in 2020, with the majority of this expansion occurring in the urban–rural fringe. CLE, in conjunction with the expansion of construction land in terms of both area and shape, has evolved from a phenomenon confined to individual cities to one that is characterized by regional expansion. The impact of CLE on CLF was found to be spatially heterogeneous over the study period, with an overall weakening trend. In highly urbanized areas, CLE typically promoted CLF, in contrast to low urbanized areas. The area growth and form complexity of the construction land caused by CLE promoted CLF over most regions. Different levels of land urbanization were identified as the primary contributor to the above results. The study findings support decision-making on food production improvement and construction land control.

Global land use and land cover changes (LULCC), driven by natural and anthropogenic factors, are threatening biodiversity and ecological stability in important reserves worldwide, such as the Khangchendzonga Biosphere Reserve (KBR) in the Indian Himalayas. KBR, the third-highest peak in the world, is renowned for its numerous glaciers and rich biodiversity, which includes a wide variety of flora and fauna. This study aims to analyze LULCC for the years 1992, 2002, 2012, and 2022 within the KBR and forecast future trends up to 2032. This study utilized Landsat imagery and the Cellular Automata-Markov (CA-Markov) model, while the support vector machine (SVM) technique was employed for image classification. The validation of the CA–Markov model was conducted using the receiver operating characteristic (ROC) curve. Results reveal a 15% reduction in dense forest cover and a 20% increase in open forests and rocky areas over the past three decades, indicative of the impacts from both human activities and natural disturbances. Projections suggest a further 10% decline in dense forests and a 12% increase in open forests and rocky areas over the next decade. Additionally, a 5% increase in agricultural land and a 3% rise in built-up areas are anticipated. The model’s accuracy, as validated by the ROC curve, reached 85%. Future research should aim to enhance model accuracy and incorporate the effects of climate change to improve LULCC projections. This comprehensive assessment underscores the importance of proactive strategies in balancing development with ecological preservation, serving as a crucial resource for policymakers and conservationists in the KBR region.

Graphical Abstract

Identifying dominant sources and distribution of potentially toxic elements (PTEs) in soils is vital for environmental protection. However, detailed data on the ecological risks posed by PTEs are still limited in Bosnia and Herzegovina (BiH). This research aimed to fill that gap by examining the distribution and pollution levels of nickel (Ni), zinc (Zn), copper (Cu), and lead (Pb) in agricultural soils across three geomorphological units in the northwestern region of BiH. The study involved analyzing 338 soil samples collected from 169 sites at two soil depths: the arable layer (0–25 cm) and the sub-arable layer (25–50 cm). The average PTE contents across the entire study area followed the increasing order: Cu < Pb < Zn < Ni. Notably, the total Ni content exceeded the allowed maximum in 65.4% of the analyzed soils, with the highest exceedance in unit I (80.0%), followed by unit II (57.4%) and unit III (44.3%). Conversely, the total contents of Zn, Cu, and Pb were predominantly below the permissible maximum, with over 98% of the samples within safe limits. The study also found a homogeneous vertical distribution of all elements across different soil depths and an absence of significant ecological risk according to applied criteria: geo-accumulation index (Igeo), pollution index (PI), and pollution load index (PLI). These findings collectively suggest the dominance of natural (geochemical) sources of examined PTEs in the soils of this region. In addition to valuable insights into the soil environmental quality, this research underscores the importance of ongoing monitoring and risk assessment to protect soil health.