Environmental Science and Pollution Research最新文献

The purpose of this research is to assess the quality of water in the Nesbit farm, which is located in the Major Land Resource Area (MLRA) in Mississippi, United States of America. This is a land resource area that faces a high risk of nutrient runoff. This research did an in-depth analysis of the quality of water in the Nesbit farm in the MLRA in Mississippi in the United States of America. This research will help to address the problems associated with the quality of water in this region by using physicochemical analysis, microbial community analysis, water quality index analysis, and geospatial analysis. The quality of water in this region, the problems associated with the quality of water in this region, and the microbial communities for grazing land management are taken into consideration in this research. The results for water temperature were obtained as (32.23 ± 0.39 °C), slightly acidic pH values ranging from (6.23-6.52), heavy metals were below the permissible limits for water as per the World Health Organization. Total dissolved solids were in the range of (1.4-1.6 mg/L), and the levels of dissolved oxygen were low (2.49-3.45 mg/L), indicating organic enrichment. Nitrate (0.11-6.36 mg/L), phosphate (0.03-0.15 mg/L) were high in concentration. The WQI of Nesbit farm water quality was 7.35, which shows that water quality is excellent in spite of localized stressors. The principal component analysis showed that the first two components explained 85.7% of the variance, and the major contributing parameters were chloride and pH. The Pearson correlation analysis indicated that there is a positive correlation between lead, total dissolved solids, chloride, and nitrate, which could be related to runoff. The metagenomics analysis indicated that Proteobacteria (30-35%) and Bacteroidetes (13-17%) are dominant species, which could be related to low organic matter. The study has provided valuable insight into water quality for Mississippi grazing land, which could be useful for effective management and conservation of natural resources.

Watercourses in agricultural areas often receive diffuse pesticide inputs through drift, runoff, infiltration, and erosion. We assessed the qualitative and quantitative response of the zooplankton community to pesticide exposure in the Estacas stream basin, Argentina, over two years at seven sites. Surface water and zooplankton were sampled every two months, and 125 pesticides were screened and classified by detection frequency. A total of 24 pesticides and the AMPA metabolite were detected. Dominant pesticides included atrazine, glyphosate, and AMPA in the first year, and metolachlor and S-metolachlor in the second. Sixty-three zooplankton taxa were identified, primarily rotifers (65%) and cladocerans (35%), with peak richness at one site during spring of the second year. Copepods were present but less frequent, with Cyclopoida being the most common. Microzooplankton dominated across sites, with higher densities in the first year. Canonical Correlation Analysis showed that glyphosate and atrazine were probably associated with microzooplankton abundance in the first year, while metolachlor and S-metolachlor were associated with copepod and rotifer populations in the second. This study represents the first report on zooplankton community responses to pesticide gradients in this basin, providing crucial information on this bioindicator's sensitivity to land use changes and pesticide application timing. These insights can help the development of environmentally sustainable agricultural practices.

The photocatalytic decomposition of naproxen, a widely used nonsteroidal anti-inflammatory drug, in aqueous wastewater was investigated using Ca₃Co₄O₉ and Sc-doped Ca₃Co₄O₉/chitosan nanocomposite films under visible-light irradiation. Chitosan, extracted from shrimp shells, was employed as a sustainable immobilization matrix for the synthesized photocatalysts. Ca₃Co₄O₉ and Sc-doped Ca₃Co₄O₉ photocatalysts were prepared via the Pechini method. The structural, morphological, and optical properties of the fabricated nanocomposites were characterized using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), transmission electron microscopy (TEM), and optical analyses. Naproxen was selected as a representative pharmaceutical contaminant to evaluate the photocatalytic efficiency of the developed nanocomposite films. A naproxen removal efficiency of 95% was achieved using the chitosan/Ca₃Co₃.₉₉Sc₀.₀₁O₉ nanocomposite film, and the photodegradation process followed pseudo-first-order kinetics. To elucidate the photocatalytic degradation mechanism of naproxen under light irradiation, the dominant reactive species involved in the (50/50) chitosan/Ca₃Co₃.₉₉Sc₀.₀₁O₉ nanocomposite film were systematically investigated. This was accomplished by introducing specific scavengers into the degradation system to quench superoxide radicals (O₂•⁻), photo-generated holes (h⁺), and hydroxyl radicals (•OH). In real pharmaceutical wastewater samples, the removal efficiencies of chemical oxygen demand (COD), biological oxygen demand (BOD), and total organic carbon (TOC) exceeded 85%. Furthermore, the nanocomposite film exhibited good reusability, retaining significant photocatalytic activity after five consecutive cycles, with only a 10% reduction in efficiency. A two-level factorial design was applied to evaluate the effects of the selected variables, with model validation and interpretation supported by diagnostic plots such as perturbation plots, analysis of variance (ANOVA), and Pareto charts.

Coal fires are pervasive global issues that affect the environment continuously, particularly in coal-rich regions; these fires can cause significant environmental damage, safety hazards, and economic losses. While numerous studies have investigated coal fires using remote sensing techniques, research integrating multisource remote sensing data for comprehensive coal fire zone detection and monitoring remains relatively limited. Current methods often analyze different data sources independently, limiting our understanding of the complex relationships between various surface manifestations of coal fires. This study presents a novel comprehensive analysis method employing multisource remote sensing technology to identify and monitor coal fires. Using 29 Landsat-8 images from Sulabulak fire area, we derived fractional vegetation cover (FVC) and land surface temperature (LST) parameters to identify vegetation loss patterns and thermal anomalies. In addition, 135 dual-polarized Sentinel-1A images were analyzed using small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) and persistent scatter interferometric synthetic aperture radar (PS-InSAR) techniques to obtain surface deformation data. The integration of these datasets, validated by field survey data, revealed a significant correlation between the identified coal fire zones and subsidence areas. Our results revealed an increase in sparse vegetation areas of 2.77 km², an expansion of high-temperature anomalies of 0.75 km², and a cumulative surface subsidence of -123.9 mm in the study area. These findings indicate ongoing and intensified coal fire combustion as well as an expansion of coal fire zones. The effectiveness of this method in identifying coal fire areas highlights its potential for enhancing coal fire monitoring and management strategies.

In this study, SnO₂/SnS₂ heterojunctions were successfully constructed in situ via a low-temperature solid-phase method using synthesized tin oxide hydroxide sulfate precursors and thiourea as raw materials. During heating, the precursors progressively transformed into SnS₂/SnO₂ heterojunctions while retaining their agglomerated structure. The regulatory role of NH₄Cl additive in product phase formation was systematically investigated. Furthermore, the structure-property relationship between microstructure, optical characteristics, and photocatalytic performance of the composite was elucidated. Phase and microstructure characterization (XRD, SEM, TEM, XPS, Raman) confirmed that introducing NH₄Cl promoted the close integration of SnO₂ and SnS₂ phases and heterojunction formation through a chemical vapor transport mechanism. The composite exhibited a hierarchical nanostructure, suitable mesoporous characteristics, and significant interfacial electron interaction. UV-Vis absorption spectroscopy and photoluminescence analysis indicated that the heterojunction effectively broadened the light response range and facilitated the separation of photogenerated carriers. Photocatalytic degradation experiments of MO demonstrated that the as-prepared SnS₂/SnO₂ composites exhibited good performance under both UV and visible light. The optimized composite (S2) achieved complete degradation of MO within 6 min under UV light and within 20 min under visible light. Free-radical trapping experiments confirmed that superoxide radicals (•O₂⁻) and hydroxyl radicals played dominant roles in the photocatalytic process.

The use of agrifood waste-based adsorbents for removing pesticides from contaminated water represents a promising and sustainable approach to address growing environmental and public health concerns. This review provides a comprehensive analysis of the capabilities of agrifood waste-derived materials in pesticide remediation, with a particular focus on surface modifications, structure-function relationships, and the mechanisms governing adsorption. Key factors influencing adsorption efficiency, such as pesticide type and concentration, pH, contact time, temperature, and adsorbent characteristics, are critically examined. Moreover, emerging technologies, including physical and chemical modification methods, electrospinning, and nanostructuring, are explored for their potential to enhance adsorbent surface area, porosity, and functional group availability. In addition, advanced data-driven approaches based on artificial intelligence and machine learning are discussed as tools for optimizing adsorption processes and predicting performance under complex, multicontaminant conditions. Despite technological progress, key challenges remain, including economic cost, limited regenerability, and reusability of bioadsorbents, as well as competing uses of agrifood residues in other valorization pathways. Understanding competitive adsorption mechanisms and ensuring scalability in real-world applications remain key priorities. By integrating technological innovations with sustainability considerations, this work provides a forward-looking perspective on scaling agrifood waste-based adsorbents for environmental remediation applications.