Environmental Monitoring and Assessment最新文献

Sewage water (SW) use is a common practice for crop production in peri-urban areas globally, especially in arid and semi-arid environments. While it enhances crop yields, it also raises potential ecological and health risks from heavy metals (HMs) contamination, requiring effective management strategies. The study examined the long-term (> 20 years) impact of SW irrigation on HM contamination in the water-soil-fodder-livestock continuum in central India. Samples of SW, groundwater (GW) (pre-monsoon, monsoon, and post-monsoon seasons), soil, fodder, and milk were collected over three years (2018–2021) to evaluate HMs levels, fodder quality, soil pollution indices, and livestock health risks. Findings revealed elevated HMs concentrations in SW, especially during the pre-monsoon. The SW irrigation improved soil fertility (SOC, N, P and K, ~ 14%, ~ 8%, ~ 44% and ~ 12%, respectively) and fodder quality over GW. Soils in Bhopal recorded the highest Cr (51.47 mg kg⁻¹) and Ni (55.35 mg kg⁻¹), while Cd (1.34 mg kg⁻¹), Pb (26.41 mg kg⁻¹) were highest in soils from Varanasi and Kanpur, respectively. Cr and Pb levels exceeded permissible limits. Fodder irrigated with SW showed significantly higher HM accumulation (Cd: ~ 27%, Ni: ~ 44%, Pb: ~ 42%) than with GW. Milk samples exceeded safe limits for Cr, Cd, and Pb, indicating human health risks. Soil indices identified Cd as the primary ecological risk. Although metal transfer factors were < 1.0, Ni and Pb health risk indices surpassed safe thresholds, potentially impairing livestock immunity and productivity. The study underscores the urgent need for regulated SW reuse, farmer education, and policy intervention to ensure sustainable livestock systems.

Urban rivers worldwide are increasingly exposed to multiple stressors from industrial, agricultural, and domestic activities; however, sensitive indicators to assess their ecological status remain limited. This study evaluated the potential of natural biofilms as bioindicators of environmental quality in two impacted river basins in Argentina: the Luján and Reconquista rivers. Biofilm and water samples were collected from upstream, urban, and industrial sites, and from controlled outdoor ponds used as a control. We analysed water physicochemical parameters, biofilm community composition, oxidative stress biomarkers (reduced glutathione, GSH; catalase, CAT; glutathione S-transferase, GST; and thiobarbituric acid reactive substances, TBARS), and extracellular enzyme activities (alkaline phosphatase, β-glucosidase). Results revealed clear water quality gradients, with downstream Luján sites and the mid-Reconquista showing severe deterioration, nutrient enrichment, hypoxia, and heavy metal exceedances. Biofilm communities mirrored these conditions: diverse and balanced assemblages dominated reference sites, while degraded ones showed reduced richness and tolerant taxa dominance. Biomarker responses also displayed consistent alterations, with high CAT activity (11,87 mmoles H₂O₂ cons x min⁻¹ × mg prot⁻¹ in L3 and 16,04 in R2), reduced GSH (0,007 mmoles GSH x g ww⁻¹ in R2), and imbalances in GST and TBARS, indicating enhanced oxidative stress. Multivariate analyses integrated these datasets, consistently separating less-impacted from highly degraded sites. Overall, biofilms proved to be sensitive and cost-effective indicators, integrating structural and functional responses to contamination gradients, and offering a robust tool for monitoring urban rivers.

Roadside areas have become obvious sinks of waste dumping and deposition of emissions, wear and tear of vehicular parts in urban industrial areas in India, and exposure to metal-polluted roadside dust (RSD) poses a serious threat to human health and the environment. Here, RSD of the Singrauli power belt in Central India was investigated to assess metal pollution and human health risks. Metals were significantly elevated in RSD compared to the background local surface sediments (LSS). Average enrichment ratio (ER:Sample/LSS) varied in the order: Pb(4.5) > Cr(3.6) > Zn(2.5) > Cu(2.3) > Co(2.0) > Mn(1.7) > Ni(1.2). Compared to the coarse size fraction (> 63 µm), the finer fraction (< 63 µm) constituted 18–27% of the total mass of RSD but accounted for > 75% of total metal contents and exhibited a high metal ER in the range of 1.3–2.2 for all metals. Spatial metal distribution was wide spread in the area, with certain hotspots in/around the close proximity to industrial operations and mining. Contamination factor, pollution load index, and geo-accumulation index suggested that the RSD were moderately to heavily polluted for Cr, Cu, Pb, and Zn. Multivariate statistical analysis suggested that Zn, Pb, Cr, and Cu were strongly linked to anthropogenic sources, while Ni and Co were ascribed to both anthropogenic and lithogenic sources. The hazard index of metals indicated a high degree of non-carcinogenic health risk of Cr and Pb to children. Carcinogenic risk was greater than the acceptable level, with ingestion as the major pathway. Chromium posed the highest carcinogenic risk. Contaminated RSD could be a potential source of metals in soil and water over time and changing environmental conditions.

Between 2018 and 2024, a renewed and persistent decline in water level was observed in the Mar Chiquita Lagoon, Córdoba Province, Argentina. This prompted an investigation into how this intensified decrease affected the frequency of salt dust storm occurrences. In this study, we analyze events from this period and compare them with those documented during the previous interval (2004–2013). Approximately 200 salt dust storms were identified between 2004 and 2024. These events originate from saline deposits exposed along the lagoon’s shorelines as a result of sustained water-level lowering since 2003, which has generated extensive areas of wind-erodible saline sediments. The objective of this work is to examine the frequency and characteristics of these storms using satellite imagery and hydrometeorological data. Occurrence conditions and spatial extent were assessed as a function of event frequency, wind speed and direction, water levels, and available coastal surface area. The highest storm frequency was recorded during winter (June–September) under wind speeds exceeding 30 km·h⁻¹. The most common plume length was approximately 150 km in both the northern and southern directions, with a maximum extent of 580 km to the south. Additionally, two selected events were simulated using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to characterize PM10 dispersion and concentration patterns. Satellite imagery was used to compare with the simulated plume evolution, and observations from an air-quality monitoring station served to validate the model output. Overall, simulations showed good first-order agreement with observed events.

Air quality monitoring was carried out in Agartala, Northeast India, over a 5-day period (2 days pre-Diwali, 1 day during Diwali, and 2 days post-Diwali) during October–November (2018)–2020. Continuous 24-h sampling was conducted at four key locations using high-volume air samplers, along with detailed SEM–EDX particle characterization. Criteria air pollutants showed statistically significant increases (p < 0.001) following Diwali celebrations. Particulate matter rose by 17–159%, SO₂ showed variable changes from a 7% decrease to an 86% increase, and NO₂ varied between a 32% decrease and a 96% increase compared to pre-Diwali levels. Meteorological conditions were stagnant, with low wind speeds (1.63–1.93 m/s) and shallow boundary layer heights (750–1250 m), while back-trajectory analysis confirmed mainly local emission sources. Peak concentrations in 2020 reached PM₁₀: 124.17 ± 10.75 μg/m³ and PM₂.₅: 92.15 ± 11.39 μg/m³, exceeding WHO guidelines by 4–18 times. EDX identified fourteen elements, with silver showing the highest 12.3-fold increase (148 ng/m³), followed by lead (2.9-fold) and chromium (2.7-fold), all linked to firework emissions. Spatial correlation analysis indicated moderate positive correlations for PM₂.₅ (r = 0.38–0.59), suggesting regional-scale dispersion, whereas gaseous pollutants exhibited weak or negative correlations, pointing to localized sources. SEM analysis revealed a shift from irregular crustal particles to predominantly spherical combustion-derived particles (0.1–30 μm) during festivities, confirming pyrotechnic origins. Health risk assessment showed concerning results: the cumulative non-carcinogenic risk (hazard index = 1.82) exceeded safe limits, and the carcinogenic risk (3.5 × 10⁻⁵) was 2.69 times above the acceptable threshold, mainly due to chromium and lead. Air Quality Index values consistently worsened across sites, changing from “Satisfactory” (57–92) to “Moderate” (139–197), with PM₂.₅ as the dominant pollutant.

Assessing changes in mean sea level (MSL) has become increasingly critical due to the significance of climate changes. Soft computing techniques are now widely used to reduce the time and cost associated with traditional MSL estimation methods. Historical MSL data is frequently used to predict future values, yet the application of soft computing models to analyze climate change’s impact on MSL remains relatively unexplored. This study aims to develop and compare various soft computing techniques for modeling MSL fluctuations using meteorological data. Random forest (RF), support vector regression (SVR), K-nearest neighbors (KNN) regression, deep neural network (DNN), Gaussian process regression (GPR), and stacked ensemble methods are employed in this study. The newly developed models are statistically assessed for their effectiveness in modeling MSL at Damietta station, Egypt. Variables environmental data such as surface water temperature, pressure, air temperature (average air temperature, dewpoint, wet-bulb, and heat index), and humidity and wind attributes (speed and direction) are utilized and evaluated in modeling MSL. The results indicate that RF, KNN, and GP outperformed other proposed models in modeling MSL during both training and testing phases. The developed weighted stacked ensemble model, integrating RF, KNN, and GPR, outperformed the base models with a correlation coefficient (R) of 0.88 and normalized root mean square error (RMSE) of 0.056 m. MSL modeling at the study station was particularly sensitive to variations in water temperature, wind speed and direction, and atmospheric pressure. This methodology serves as a valuable framework for climate-driven MSL forecasting in developing coastal regions lacking long-term tide records, directly contributing to UNESCO’s Ocean Decade Challenge 5 on coastal resilience.

Artificial wrecks (AWs), which are intentionally submerged structures to promote marine biodiversity and support recreational diving, have gained increasing prominence on a global scale. Nevertheless, concerns regarding their environmental safety persist, especially in regions where regulatory oversight is limited. This study examines the ecological and human health risks posed by two artificial wrecks (“Alaybey” and “9 Eylül”) deployed in the Karaburun Peninsula, Northeast Mediterranean, Türkiye, compared to a no-wreck site (Aslan Kayası). Despite rigorous pre-sinking protocols to remove fuels and oils, critical pollutants—such as antifouling paint residues containing Cu, Zn, Pb, and PCBs—persist due to incomplete cleaning. Over two years, seasonal sampling of sediments, mussels (Mytilus galloprovincialis), and fish (Diplodus vulgaris) revealed alarming trends. Sediments near AWs showed enrichment of Pb (EF: 37.2–92.1) and Cd (EF: 9.3–16.0) from significant to extremely high enrichment. The Potential Ecological Risk Index (PERI) reached > 1,000 at the “9 Eylül” wreck, classifying it as "extremely high risk." Mussels on AWs bioaccumulated Cd and Pb above EU safety thresholds, while fish on AWs exhibited Pb levels of 236–340 fold over limits. Notably, Hg contamination in fish samples obtained from the no-wreck site (1.2 mg kg⁻¹) was traced to historic mining activities, underscoring region-wide pollution. These findings challenge the assumption that "cleaned" AWs are environmentally benign and highlight systemic gaps in pollutant mitigation, particularly for toxic coatings. The study advocates for stringent pre-deployment protocols, including paint stripping and PCB screening, to align AWs projects with global sustainability goals.

Peat smouldering leads to smoke emissions, which can subsequently have an effect on the soil, causing pollution by deposition and smog. As a consequence, there may be a change in the biological properties of soils, which influences soil fertility. To study the effects of gaseous substances on soil, several laboratory experiments (modelling the potential effects of smoke on soil) were carried out. As a result of the research, the activity of soil enzymes, class of oxidoreductases (catalase, peroxidase, polyphenoloxidase) was decreased after 30–120 min of soil treatment with peat smoke. Meanwhile, the enzymes of the hydrolase class (invertase, phosphatase) remained basically unchanged. The pH of soil suspension after smoke exposure decreased by 0.28 units after the first and second experiments. Polycyclic aromatic hydrocarbons (PAHs) such as naphthalene, biphenyl, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benzo[a]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene and dibenzo[a,h]anthracene were found in soil samples. Some of the substances in the experimental (smoke-treated) samples exceeded background (non-smoked) samples. The total amount of the analysed substances was 493.92 ng/g.

In our study, a rapid, low-cost analytical method was developed for the colorimetric determination of Sn(IV) using silver nanoparticles (AgNPs) synthesized with clove extract. The AgNPs synthesized have a surface plasmon resonance peak at 425 nm. When Sn(IV) standards at increasing concentrations are added to samples containing AgNPs, a color change proportional to the analyte concentration occurs. With increasing Sn(IV) concentration, the absorbance of the AgNPs decreases. In the analyses, the absorbance change based on analyte concentration was monitored. The detection limit of the developed method was calculated as 7.9 µM with the linear range as 20–300 µM. The analytical performance of the method in complex matrix media was demonstrated by conducting recovery experiments in tap water. Our percentage recovery value varies between 97% and 118.0%. The toxicological behavior of the AgNPs were also evaluated in Daphnia magna (D. magna) to justify the safety and ecotoxicity of the synthesized nanoparticles. According to the results, LC₅₀ was calculated as 0.2 mg L⁻¹ for 96 h.

This study comprehensively evaluates the dissipation dynamics, environmental persistence, dietary exposure, and ecotoxicological risks associated with the application of carbendazim (CBZ) and chlorantraniliprole (CAP) in Solanaceous cropping systems, specifically brinjal (Solanum melongena) and tomato (Solanum lycopersicum). Residue quantification was performed using a highly sensitive and validated liquid chromatography-tandem mass spectrometry (LC–MS/MS) method to ensure precise detection at trace levels. Initial concentration of CBZ in brinjal fruit (1.159‒2.110 mg/kg) declined substantially over 15 days, with 96.68–98.27% dissipation observed. Soil residues of carbendazim showed a comparable reduction of 96.09–97.03%. In tomato fruits, the dissipation ranged from 96.87 to 97.31% and from 95.15 to 95.24% in soil. For CAP, residue levels in brinjal fruits (1.110–2.100 mg/kg) dissipated by 96.43–97.30%, while soils demonstrated 95.34–96.82% reduction. Tomato fruits displayed higher dissipation of 98.47–99.53%, and soils showed 98.79–98.98% reduction. Both pesticides followed first-order dissipation kinetics, with calculated half-lives (t_1/2) ranging from 1.90 to 3.53 days. Probabilistic acute dietary exposure assessments, stratified by rural and urban dietary patterns, revealed that the estimated daily intakes of CBZ and CAP remained well within the acceptable daily intake (ADI) limits established by regulatory agencies, particularly following adherence to the recommended pre-harvest intervals (PHIs). Ecotoxicological risk assessment, based on risk quotient (RQ) values for representative non-target soil organisms, including earthworms and arthropods, demonstrated a transient risk immediately post-application especially under T2, which attenuated to acceptable levels within 15 days post-treatment. A computational study was used for chlorantraniliprole and carbendazim. The findings affirm that, when applied in accordance with good agricultural practices (GAPs), both CBZ and CAP pose minimal residual and ecological risk, thereby supporting their continued use in integrated pest management (IPM) frameworks. The findings of this investigation may serve as a valuable reference for the safe and judicious application of chlorantraniliprole (CAP) and carbendazim (CBZ) in brinjal and tomato cultivation.