Search Results (198)

The contamination due to coastal landfill is a growing environmental concern, particularly in fragile marine ecosystems, where leachate can mobilize toxic elements into soil, water, air, and sediment. This study aims to assess the impact of a coastal landfill in Al-Qunfudhah, western Saudi Arabia, on nearby coastal sediments by identifying the concentration, distribution, and ecological risk of potentially toxic elements (PTEs) using geospatial and multivariate analysis tools. The results indicate significant accumulation of Pb, Zn, Cu, and Fe, with Pb reaching alarming levels of up to 1160 mg/kg in the landfill area, compared to 120 mg/kg in the coastal sediments. Zn contamination also exhibited substantial elevation, with values reaching 278 mg/kg in landfill soil and 157 mg/kg in coastal sediment. The enrichment factor values indicate moderate to severe enrichment for Pb (up to 73.20) and Zn (up to 6.91), confirming anthropogenic influence. The contamination factor analysis categorized Pb contamination as very high (CF > 6), suggesting significant ecological risk. Comparison with sediment quality guidelines suggest that Pb, Zn, and Cu concentrations exceeded threshold effect levels (TEL) in some samples, posing potential risks to marine organisms. The spatial distribution maps revealed pollutant migration from the landfill toward the coastal zone, emphasizing the necessity of monitoring and mitigation strategies. As the first comprehensive study on landfill-induced PTEs contamination in Al-Qunfudhah, these findings provide essential insights for environmental management and pollution control policies along the Red Sea coast. Full article

Environmental contaminants exhibit heterogeneous neurotoxicity profiles, yet systematic comparisons between legacy neurotoxicants and emerging pollutants remain scarce. To address this gap, we implemented an integrative transcriptome meta-analysis framework that harmonized eight transcriptomic datasets spanning in vivo and in vitro neural models exposed to two legacy neurotoxicants (bisphenol A [BPA], 2, 2′, 4, 4′-tetrabromodiphenyl ether [BDE-47]) and polystyrene nanoplastics (PSNPs) as an emerging contaminant. Our analysis revealed a substantial overlap (68% consistency) in differentially expressed genes (DEGs) between BPA and PSNPs, with shared enrichment in extracellular matrix disruption pathways (e.g., “fibronectin binding” and “collagen binding”, p < 0.05). Network-based toxicogenomic mapping linked all three contaminants to six neurological disorders, with BPA showing the strongest associations with Hepatolenticular Degeneration. Crucially, a sex-stratified analysis uncovered male-specific transcriptional responses to BPA (e.g., lipid metabolism and immune response dysregulation), whereas female models showed no equivalent enrichment. This highlights the sex-specific transcriptional characteristics of BPA exposure. This study establishes a novel computational toxicology workflow that bridges legacy and emerging contaminant research, providing mechanistic insights for chemical prioritization and gender-specific risk assessment. Full article

Variable-rate nitrogen (VR-N) application allows farmers to optimize nitrogen (N) input site-specifically within field boundaries, enhancing both economic efficiency and environmental sustainability. In this study, VR-N technology was applied to durum wheat in two small-scale commercial fields (3–4 ha each) located in distinct agro-climatic zones of Thessaly, central Greece. A real-time VR-N application algorithm was used to calculate N rates based on easily obtainable near-real-time data from unmanned aerial vehicle (UAV) imagery, tailored to the crop’s actual needs. VR-N implementation was carried out using conventional fertilizer spreaders equipped to read prescription maps. Results showed that VR-N reduced N input by up to 49.6% compared to the conventional uniform-rate N (UR-N) application, with no significant impact on wheat yield or grain quality. In one of the fields, the improved gain of VR-N when compared to UR-N was 7.2%, corresponding to an economic gain of EUR 163.8 ha⁻¹, while in the second field—where growing conditions were less favorable—no considerable VR-N economic gain was observed. Environmental benefits were also notable. The carbon footprint (CF) of the wheat crop was reduced by 6.4% to 22.0%, and residual soil nitrate (NO₃⁻) levels at harvest were 13.6% to 36.1% lower in VR-N zones compared to UR-N zones. These findings suggest a decreased risk of NO₃⁻ leaching and ground water contamination. Overall, the study supports the viability of VR-N as a practical and scalable approach to improve N use efficiency (NUE) and reduce the environmental impact of wheat cultivation which could be readily adopted by farmers. Full article

Dissolved arsenic in private bedrock drinking water wells is a problem in eastern Wisconsin. Previous studies have identified bedrock sources of arsenic as discrete intervals within the local Paleozoic sedimentary section and have also identified release mechanisms causing arsenic to enter well boreholes. However, widespread contamination modeling is hindered by a lack of 3-D knowledge constraining the depth of the arsenic-bearing units in the subsurface. The growth and improvement of 3-D geologic mapping provides an opportunity to improve predictive models. This study in eastern Wisconsin, USA, uses a multivariate binary logistic regression analysis combined with 3-D geologic mapping to both assess various geologic and well construction factors that impact arsenic occurrence, and improve the ability to predict contamination risk. We find well construction characteristics, the stratigraphic unit within the open interval of a well, and the proximity to fold axes/fault zones are all statistically significant variables that impact the probability of a well exceeding either 2 or 10 µg/L dissolved arsenic. We apply these results by using 3-D mapping to determine the geologic unit present within the open interval of thousands of untested wells and use the logistic regression results to calculate contamination probability. This allows arsenic risk to be rapidly estimated for thousands of individual groundwater wells, and models of potential casing regulations to be assessed. Full article

Microplastics (MPs) and cadmium (Cd) in the soil environment are expected to pose a serious threat to agricultural production. However, the effect of the interaction between them on the soil–plant system and the mechanism of MPs on plant Cd uptake are still unclear. Therefore, the effects of different concentrations of polyethylene (PE-MPs, 0, 1.0% and 2.0%), alone or combined with Cd, on soil properties, plant growth and Cd uptake were investigated through pot experiments. The results showed that the single contamination of MPs and Cd and their interaction (MPs + Cd) significantly decreased soil moisture and pH; however, it increased soil organic matter (SOM) and total nitrogen (TN). Soil urease and catalase activities were significantly decreased and sucrase and alkaline phosphatase activities were increased with or without Cd addition. The exposure of PE and Cd, alone or combined, significantly and negatively affected plant biomass, photosynthetic parameters, and caused oxidative damage to plants, and the overall toxicity to plants increases with the increase in PE concentration. Moreover, co-pollution causes greater plant toxicity than the individual pollution of PE or Cd. Plants can resist oxidative stress by increasing superoxide dismutase (SOD) and peroxidase (POD) activities. The heat map showed that soil environmental factors were significantly correlated with plant growth; and the results of redundancy analysis (RDA) indicated that for plant physiological characteristics, soil properties under PE, alone or co-contaminated with Cd, explained a total of 85.77% and 97.45%, respectively. This indicated that the alteration of the soil microenvironment is the key factor influencing plant growth. The results of the partial least squares path model (PLS-PM) indicated that plant oxidative damage and biomass had significant positive and negative direct effects on plant Cd uptake, respectively. The linear model of relative importance (%) further revealed in depth that soil moisture (relative importance: 33.60%) and plant biomass (relative importance: 20.23%) were, respectively, regarded as the most important soil environmental factors and plant indicators affecting their Cd uptake. This study provided theoretical support for assessing the risks of MPs and Cd co-pollution to agricultural ecosystems. Full article

Mining activities in Pakistan’s mineral-rich provinces threaten freshwater security through groundwater depletion, contamination, and flood-induced pollution. This study develops an Inclusive Disaster Risk Reduction (IDRR) framework integrating governance, social, environmental, and technical (GSET) dimensions to holistically assess mining-induced water hazards across Balochistan, Khyber Pakhtunkhwa, and Punjab. Using GIS-based spatial risk mapping with multi-layer hydrological modeling, we combine computational analysis and participatory validation to identify vulnerability hotspots and prioritize high-risk mines. Community workshops involving women water collectors, indigenous leaders, and local experts enhanced map accuracy by translating indigenous knowledge into spatially referenced mitigation plans and integrating gender-sensitive metrics to address gendered water access disparities. Key findings reveal severe groundwater depletion, acid mine drainage, and gendered burdens near Saindak and Cherat mines. Multi-sectoral engagements secured corporate commitments for water stewardship and policy advances in inclusive governance. The framework employs four priority-ranked risk categories (Governance-Economic 15%, Social-Community 30%, Environmental 40%, Technical-Geological 15%) derived via local stakeholder collaboration, enabling context-specific interventions. Despite data limitations, the GIS-driven methodology provides a scalable model for regions facing socio-environmental vulnerabilities. The results demonstrate how community participation directly shaped village-level water management alongside GSET analysis to craft equitable risk reduction strategies. Spatially explicit risk maps guided infrastructure upgrades and zoning regulations, advancing SDG 6 and 13 progress in Pakistan. This work underscores the value of inclusive, weighted frameworks for sustainable mining–water nexus management in Pakistan and analogous contexts. Full article

This study was conducted in the Harran Plain within the framework of the Southeastern Anatolia Project (GAP) in Türkiye to evaluate the vulnerability of groundwater to contamination, with a special emphasis on the high salinity conditions attributed to agricultural and rural practices. The region is notably challenged by salinization resulting from intensive irrigation and insufficient drainage systems. The DRASTIC framework was used to assess groundwater contamination vulnerability. The DRASTIC framework parameters were numerically integrated using both the original DRASTIC framework and its modified version, serving as the basis for subsequent predictive analytics and soft computing model development. The primary aim was to determine the most effective predictive model for groundwater contamination vulnerability in salinity-affected areas. In this context, various models were implemented and evaluated, including artificial neural networks (ANNs) with varied hidden layer configurations, four different regression-based methods (MARS, TreeNet, GPS, and CART), and three classical regression analysis approaches. The modeling process utilized 24 adjusted vulnerability indices (AVIs) as target variables, with the dataset partitioned into 58.34% for training, 20.83% for validating, and 20.83% for testing. Model performance was rigorously assessed using various statistical indicators such as mean absolute error, root mean square error, and the Nash–Sutcliffe efficiency coefficient, in addition to evaluating the predictive AVIs through spatial mapping. The findings revealed that the ANNs and TreeNet models offered superior performance in accurately predicting groundwater contamination vulnerability, particularly by delineating the spatial distribution of risk in areas experiencing intensive agricultural pressure. Full article

Groundwater nitrate (NO₃⁻) contamination has emerged as a critical global environmental issue, posing serious human health risks. This study systematically investigated the hydrochemical processes, sources of NO₃⁻ pollution, the impact of land use on NO₃⁻ pollution, and drinking water safety in an urban area of southwestern China. Thirty-one groundwater samples were collected and analyzed for major hydrochemical parameters and dual isotopic composition of NO₃⁻ (δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻). The groundwater samples were characterized by neutral to slightly alkaline nature, and were dominated by the Ca-HCO₃ type. Hydrochemical analysis revealed that water–rock interactions, including carbonate dissolution, silicate weathering, and cation exchange, were the primary natural processes controlling hydrochemistry. Additionally, anthropogenic influences have significantly altered NO₃⁻ concentration. A total of 19.35% of the samples exceeded the Chinese guideline limit of 20 mg/L for NO₃⁻. Isotopic evidence suggested that primary sources of NO₃⁻ in groundwater include NH₄⁺-based fertilizer, soil organic nitrogen, sewage, and manure. Spatial distribution maps indicated that the spatial distribution of NO₃⁻ concentration correlated strongly with land use types. Elevated NO₃⁻ levels were observed in areas dominated by agriculture and artificial surfaces, while lower concentrations were associated with grass-covered ridge areas. The unabsorbed NH₄⁺ from nitrogen fertilizer entered groundwater along with precipitation and irrigation water infiltration. The direct discharge of domestic sewage and improper disposal of livestock manure contributed substantially to NO₃⁻ pollution. The nitrogen fixation capacity of the grassland ecosystem led to a relatively low NO₃⁻ concentration in the ridge region. Despite elevated NO₃⁻ and F⁻ concentrations, the entropy weighted water quality index (EWQI) indicated that all groundwater samples were suitable for drinking. This study provides valuable insights into NO₃⁻ source identification and hydrochemical processes across varying land-use types. Full article

Morocco’s Témara Plain relies heavily on its aquifer system as a critical resource for drinking water, irrigation, and industrial activities. However, this essential groundwater reserve is increasingly threatened by over-extraction, seawater intrusion, and complex hydrogeochemical processes driven by the region’s geological characteristics and anthropogenic pressures. This study aims to assess groundwater quality and its vulnerability to pollution risks and map the spatial distribution of key hydrochemical processes through an integrated approach combining Geographic Information System (GIS) techniques and multivariate statistical analysis, as well as applying the DRASTIC model to evaluate water vulnerability. A total of fifty-eight groundwater samples were collected across the plain and analyzed for major ions to identify dominant hydrochemical facies. Spatial interpolation using Inverse Distance Weighting (IDW) within GIS revealed distinct patterns of sodium chloride (Na-Cl) facies near the coastal areas with chloride concentrations exceeding the World Health Organization (WHO) drinking water guideline of 250 mg/L—indicative of seawater intrusion. In addition to marine intrusion, agricultural pollution constitutes a major diffuse pressure across the aquifer. Shallow groundwater zones in agricultural areas show heightened vulnerability to salinization and nitrate contamination, with nitrate concentrations reaching up to 152.3 mg/L, far surpassing the WHO limit of 45 mg/L. Furthermore, other anthropogenic pollution sources—such as wastewater discharges from septic tanks in peri-urban zones lacking proper sanitation infrastructure and potential leachate infiltration from informal waste disposal sites—intensify stress on the aquifer. Principal Component Analysis (PCA) identified three key factors influencing groundwater quality: natural mineralization due to carbonate rock dissolution, agricultural inputs, and salinization driven by seawater intrusion. Additionally, The DRASTIC model was used within the GIS environment to create a vulnerability map based on seven key parameters. The map revealed that low-lying coastal areas are most vulnerable to contamination. Full article

Listeria monocytogenes (Lm) represents a considerable hazard in ready-to-eat (RTE) foods, particularly for susceptible individuals. This study investigated the survival of Lm in modified atmosphere-packaged (MAP) semi-hard sliced Greek cheese, comparing full-fat and light varieties. Challenge testing was conducted, and key product characteristics, including MAP gas composition, background microbiota, sodium chloride concentration, fat content, water activity, and pH, were determined. While the tested sliced cheeses, under specific MAP and storage conditions, met EU regulatory criteria for RTE foods unable to support Lm growth, the pathogen persisted at low levels throughout the 6-month shelf life. This finding underscores a potential risk associated with temperature abuse or compromised packaging integrity, which could facilitate Lm proliferation. The observed survival highlights the importance of growth potential assessment, even in food matrices seemingly non-supportive of Lm. Given that post-pasteurization processing steps like slicing and MAP packaging can introduce contamination risks for vulnerable consumers, this study emphasizes the necessity of stringent hygienic practices to prevent Lm contamination. Food business operators (FBOs) must rigorously implement food safety protocols, including controlled storage temperatures, robust hygiene measures, and effective cross-contamination prevention strategies between raw and RTE products, to safeguard public health, protect brand integrity, and mitigate economic losses. Full article

Polycyclic aromatic hydrocarbons (PAHs) and their substituted derivatives (SPAHs) are persistent organic pollutants derived from incomplete combustion of fossil fuels and industrial processes. These compounds are of global concern due to their carcinogenicity and environmental persistence. This study provides the first comprehensive analysis of PAH and SPAH contamination in Suzhou’s rapidly urbanizing watersheds, integrating ultra-high-performance liquid chromatography and high-resolution mass spectrometry with multidimensional risk assessment to address critical gaps in understanding pollutant dynamics in urban aquatic systems. Key findings reveal that SPAHs were significantly more abundant than parent PAHs (mean ∑19 SPAHs = 107.43 ng/L vs. ∑8 PAHs = 48.05 ng/L), with hydroxylated derivatives accounting for 67.9% of the total SPAHs, indicating active environmental transformation processes. Source apportionment identified coal combustion and industrial emissions as the dominant contributors (58.2% of PAHs), directly linking contamination patterns to localized anthropogenic activities. Notably, industrial zones exhibited unexpected toxicity hotspots, where SPAH toxicity equivalents (e.g., 3-OH-BaP) surpassed parent PAHs 2–5-fold, demonstrating substituent-driven toxicity enhancement—a critical finding for regulatory prioritization. This study advances the field by uncovering SPAHs as emerging risks in urban waterways, challenging traditional PAH-centric monitoring frameworks, and providing a novel integration of analytical chemistry and spatial risk mapping to guide targeted pollution control (e.g., prioritizing industrial discharges and non-exhaust traffic emissions). Furthermore, it highlights the urgent need for updated toxicological databases to account for substituted PAH derivatives and advocates for the regulatory inclusion of SPAHs. These insights underscore the necessity of adapting environmental policies to address complex pollutant mixtures in rapidly developing regions, emphasizing the replicability of the proposed framework for urban watershed management. Full article

Environmental risks often stem from contamination driven by chemical stressors introduced from multiple sources, either geogenic or anthopogenic. Differentiating between anthropogenic chemical anomalies and those inherent to the environment is crucial. This distinction is essential for defining feasible remediation objectives. This study applied univariate and multivariate statistical techniques to analyse geochemical data from over 7000 topsoil samples in Campania (Southern Italy), over an area of approximately 13,600 km². A key step in the methodology was applying Normal Score Transformation (NST), which stabilized the variance of the dataset, pulling the extreme outliers back to normal ranges, making it more suitable for multivariate analysis. Principal Component Analysis (PCA) was performed, and four components were selected; the spatialization of their scores revealed four primary independent sources controlling geochemical variability across the region. Specifically, two distinct volcanic districts were identified, plus a siliciclastic and an anthropogenic component. The integration of RGB composite maps further refined this differentiation, emphasising the coexistence or the predominance of one component over the other. The methodological approach demonstrated here provides valuable insights for environmental risk assessment and remediation planning in geochemically complex and anthropized regions. Full article

Diffuse agricultural pollution is a leading contributor to surface water degradation, particularly in regions undergoing rapid land use change and agricultural intensification. In many developing countries, conventional assessment approaches fall short of capturing the spatial complexity and cumulative nature of multiple environmental drivers that influence surface water vulnerability. This study addresses this gap by introducing the Integral Index of Vulnerability to Diffuse Contamination (IIVDC), a spatially explicit, multi-criteria framework that combines the Analytical Hierarchy Process (AHP) with Geographic Information Systems (GIS). The IIVDC integrates six key indicators—slope, soil erodibility, land use, runoff potential, hydrological connectivity, and observed water quality—weighted through expert elicitation and mapped at high spatial resolution. The methodology was applied to the Guachal River watershed in Valle del Cauca, Colombia, where agricultural pressures are pronounced. Results indicate that 33.0% of the watershed exhibits high vulnerability and 4.3% very high vulnerability, with critical zones aligned with steep slopes, limited vegetation cover, and strong hydrological connectivity to cultivated areas. By accounting for both biophysical attributes and pollutant transport pathways, the IIVDC offers a replicable tool for prioritizing land management interventions. Beyond its technical application, the IIVDC contributes to sustainability by enabling evidence-based decision-making for water resource protection and land use planning. It supports integrated, spatially targeted actions that can reduce long-term contamination risks, guide sustainable agricultural practices, and improve institutional capacity for watershed governance. The approach is particularly suited for contexts where data are limited but spatial planning is essential. Future refinement should consider dynamic water quality monitoring and validation across contrasting hydro-climatic regions to enhance transferability. Full article

Polychlorinated biphenyls (PCBs) are synthetic organic compounds that were widely used in industrial applications throughout the 20th century. Due to their chemical stability, resistance to degradation and ability to bioaccumulate and biomagnify through food chains, PCBs pose long-term environmental and health risks. Due to these characteristics, PCBs have been globally regulated as persistent organic pollutants (POPs), despite being banned from production in most countries decades ago. This study investigates temporal trends in PCB contamination in urban soils of Bucharest over a 20-year period (2002–2022), focusing on six principal congeners (PCB 28, 52, 101, 138, 153, and 180) sampled from 13 locations, including roadsides and urban parks. Gas chromatography and spatial analysis using inverse distance weighting (IDW) revealed a marked reduction in Σ6PCB concentrations, declining from 0.0159 mg/kg in 2002 to 0.0065 mg/kg in 2022, with statistically significant differences confirmed by Kruskal–Wallis analysis (p < 0.05). This decline is primarily attributed to reduced emissions, source control measures, and natural attenuation. However, the persistence of PCBs in localized hotspots is influenced by secondary dispersion mechanisms, such as atmospheric deposition and surface runoff, which redistribute contaminants rather than eliminate them. Health risk assessments via ingestion, dermal absorption, and inhalation routes confirmed negligible carcinogenic risk for both adults and children. Although measurable progress has been achieved, the persistence of localized contamination underscores the need for targeted remediation strategies and sustained environmental monitoring to protect vulnerable urban areas from recontamination. Full article

Dechlorane Plus (DP), an emerging type of persistent organic pollutant (POP), poses potential harmful effects on plants, animals, and humans alike, garnering increasing attention. Urban surface soil is easily accessible to urban residents, and its environmental conditions have a more significant impact on urban residents. However, there are few studies on related DP contamination. In this study, the contamination of DP in surface soil from Shenyang City, Liaoning Province, China, was investigated. Soil samples were collected from 33 different locations in May and June 2023. The total DP (∑DP), anti-DP, and syn-DP were determined by gas chromatography and ranged from not detected (ND) to 77.80 ng/g, from ND to 61.50 ng/g, and from ND to 16.30 ng/g, respectively. The mean values were 33.60 ± 18.93 ng/g, 27.01 ± 14.32 ng/g, and 8.57 ± 4.55 ng/g. The findings indicate that anti-DP is more readily detectable than syn-DP, attributable to the lower proportion of syn-DP in the overall DP production and the distinct physicochemical properties of DP isomers. The fsyn [syn-DP/(anti-DP + syn-DP)] is 0.14–0.40, with a mean value of 0.22. This aligns closely with the values observed in commercial DP formulations, suggesting that the primary sources are derived from commercial DP products. Contour maps show that DP concentrations are influenced by urban land use and DP production. Based on the Tyson polygon method, the DP inventory was calculated at approximately 1.18 tons, with the unit area load exceeding previously reported values. The results also show that the health risks of DP are minimal, but children are more susceptible to the impacts of DP than adults, and oral ingestion is a more critical exposure pathway. Full article