Environmental Monitoring and Assessment最新文献

{"title":"Climate-induced hydraulic stress and geomorphological changes: an assessment of vulnerability of critical river infrastructure in the data-scarce basin, India","authors":"Arnab Ghosh,&nbsp;Moumita Kundu,&nbsp;Ellora Padhi","doi":"10.1007/s10661-026-16013-6","DOIUrl":"10.1007/s10661-026-16013-6","url":null,"abstract":"<div><p>Climate non-stationarity increasingly threatens river infrastructure, yet its quantified impact on bridge pier scour in data-scarce tropical basins remains poorly constrained. The study evaluates the climate-induced modification of the river hydrology, hydraulics and channel behaviour of the data-scarce Rupnarayan river basin in the peri-urban zone of eastern India using a case study of the Kolaghat Bridge. A high-resolution model, the Max Planck Institute Earth System Model version 1.2 Higher Resolution (MPI-ESM1-2-HR), was downscaled, bias-corrected, and coupled with a Soil and Water Assessment Tool (SWAT) model giving good skills (NSE = 0.90; <i>R</i>² = 0.86) for discharge well. Three Shared Socioeconomic Pathways (SSP245, SSP370, SSP585) were used to project flow and sediment series which were used as input to a Hydrologic Engineering Center River Analysis System (HEC-RAS) 2D model that computed water-surface elevation (WSE), energy gradient and bed shear stress for 2- to 100-year return periods. The observed record (1960–2020) has no significant trend, but each pathway exhibits a large difference: mean annual temperature and rainfall increase by + 1.31 °C and + 22.1% by 2100 under SSP585. The three-model comparison shows an increase of 11–18% in critical shear stress and energy gradient at this bridge (~ 15% for MPI-ESM1-2-HR model). The HEC-18 analysis results indicate that total pier scour increased from ~ 6.07 m to ~ 10.93 m (~ 80%), which would diminish foundation safety margins, while the reduced high-frequency variability in WSE suggests increased sedimentation, channel narrowing, and overall channel sinuosity (1.08 to 1.67). In summary, under the high-emission SSP585 pathway by 2100 the critical shear stress at the Kolaghat Bridge rises by 11 to 18 per cent and total pier scour increases by about 80 per cent, from about 6.07 to about 10.93 m, which erodes the foundation safety margin below the code threshold and makes a clear case for climate-adjusted hydraulic design loads together with regular bathymetric monitoring and planned dredging.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heavy metal contamination in soil and vegetables: a health risk assessment from urban areas of Sylhet, Bangladesh","authors":"Rasendra Talukder,&nbsp;Palash Mandal,&nbsp;Amdadul Haque Shaon,&nbsp;Jarin Tasnim,&nbsp;Durjoy Hur,&nbsp;Saniya Afrin Swarna,&nbsp;Hirajan Hamal,&nbsp;Ashutus Singha","doi":"10.1007/s10661-026-15996-6","DOIUrl":"10.1007/s10661-026-15996-6","url":null,"abstract":"<div><p>Rapid industrialization, urban expansion, and inadequate waste management in the peri-urban areas of Sylhet city, Bangladesh, have raised concerns regarding heavy metal accumulation in agricultural soils and vegetables and their potential implications for human health. However, information on heavy metal transfer from soil to edible crops and the associated health risks in this rapidly developing region remains limited. This study assessed heavy metal concentrations in peri-urban agricultural soils and commonly consumed vegetables and evaluated their potential human health risks. A total of 60 composite soil and vegetable samples were collected from 21 locations around Sylhet city during the Rabi season (January–March 2024). Concentrations of cadmium (Cd), lead (Pb), nickel (Ni), zinc (Zn), copper (Cu), chromium (Cr), iron (Fe), and manganese (Mn) were determined using inductively coupled plasma mass spectrometry (ICP–MS). In both soils and vegetables, Fe and Mn were the predominant metals, whereas Cd and Pb occurred at the lowest concentrations. Bioconcentration factor (BCF) values for Cd exceeded 1 at three locations (up to 5.8), indicating a potential risk of Cd accumulation in vegetables, while Cu exhibited a BCF greater than 1 at one location. Brinjal (<i>Solanum melongena</i> L.) showed the highest accumulation capacity among the investigated vegetables. Hazard index (HI) values ranged from 0.44 to 2.02, with seven sampling sites exceeding the safety threshold (HI &gt; 1). The highest HI values were observed in cabbage (2.02), red amaranth (1.89), and tomato and gourd samples from specific locations, indicating potential non-carcinogenic health risks from long-term consumption. These results highlight a possible cumulative non-carcinogenic health risk for peri-urban consumers who depend on locally grown vegetables in Sylhet and emphasize the need for regular heavy metal monitoring and better soil management in this area.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonality and maximum wind gusts correlate with microplastic concentrations in a freshwater stream system","authors":"Chloe Mattie\u0000,&nbsp; Isabella\u0000 Ashman,&nbsp;Megan Fork,&nbsp;T. Elliott Arnold","doi":"10.1007/s10661-026-15985-9","DOIUrl":"10.1007/s10661-026-15985-9","url":null,"abstract":"<div><p>We evaluate how meteorological and environmental variables relate to stream microplastic concentrations using regression-based models. Forty-nine water column samples were collected bimonthly over an annual cycle (September 2024–September 2025) from a stream in southeastern Pennsylvania, USA. Microplastic particles were isolated and quantified by light microscopy, and polymer types were characterized using scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDS) and Fourier transform infrared spectroscopy (FTIR). Results from three separate multiple linear regression models (stepwise selection, LASSO, and elastic net) demonstrate high variability in microplastic counts, including pronounced seasonal variability (mean = 7.6 particles L⁻¹, <i>n</i> = 49, 1σ = 4.9 particles L⁻¹). All regression approaches identified colder temperatures and stronger wind gusts as important predictors of elevated microplastic concentrations. Repeated tenfold cross-validation indicated that models incorporating these variables explained approximately 80% of the variability in microplastic concentrations within this relatively small dataset (<i>n</i> = 49), highlighting their importance as the dominant environmental controls on microplastic abundance in Plum Run. When scaled by riparian area, the wind-sensitive component of the stream plastic flux is consistent with physically plausible atmospheric deposition rates. These results provide an indirect inference that environmental factors enhance transport of microplastics into waterways. Qualitative data from EDS and FTIR spectra indicate that polyester fibers comprise the majority of microplastic pollution in Plum Run. From this, we infer that increased laundering and shedding of synthetic clothing during winter may be a primary driver of higher pollution in winter months.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10661-026-15985-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement uncertainty of fluoride determination in vegetation: contributions from sampling and analysis","authors":"E. Antonsson,&nbsp;E. I. Eyjólfsdóttir,&nbsp;K. Gíslason","doi":"10.1007/s10661-026-15981-z","DOIUrl":"10.1007/s10661-026-15981-z","url":null,"abstract":"<div><p>Accumulation of fluoride in vegetation can have ecological and toxicological implications not only for the plants themselves, but for other organisms higher up the food chain. Assessment of fluoride concentration in vegetation requires reliable estimates of the associated measurement uncertainty. We investigate the fluoride concentration in three types of vegetation in Iceland (grass, downy birch, and rowan) and evaluate the contributions of both sampling and chemical analysis to the measurement uncertainty. Sampling of vegetation is performed following a standardized protocol at predetermined locations in the vicinity of aluminum smelters in Iceland, with subsequent determination of fluoride using ion selective electrodes. Measurement uncertainty arising from sampling and analysis was evaluated using an approach that couples duplicate sampling with duplicate analysis. The results of this analysis indicate that sampling contributes substantially to the measurement uncertainty, dominating the uncertainty budget for grass and downy birch, while analytical and sampling uncertainty was found to be of comparable magnitude for rowan. These findings demonstrate that estimates of measurement uncertainty that are based solely on data from the chemical analysis part severely underestimate the total measurement uncertainty. When expressed as relative expanded measurement uncertainty, the measurement uncertainty of fluoride content in vegetation is found to be 43%, 45%, and 13% for grass, downy birch, and rowan, respectively. The approach applied here and the obtained results provides a reliable way to incorporate contributions from sampling into assessment of measurement uncertainty in environmental monitoring using vegetation. The results are expected to allow for meaningful interpretation of fluoride data in vegetation when comparing them to limit values in permits or to species-specific damage thresholds of vegetation.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long‑term trends and seasonal variability of particulate matter (PM10 and PM2.5) in Volta Redonda (RJ), Brazil: a 15‑year temporal analysis","authors":"Bruno Cesar Silva Rocha,&nbsp;Jackson Porto Cardoso,&nbsp;Jéssica de Medeiros Soares,&nbsp;Libério Junio da Silva,&nbsp;Nivia de Mello Nascimento,&nbsp;Adriana Gioda,&nbsp;Marcelo Correa Bernardes","doi":"10.1007/s10661-026-15988-6","DOIUrl":"10.1007/s10661-026-15988-6","url":null,"abstract":"<div><p>Air quality in Volta Redonda, Rio de Janeiro, Brazil, is influenced by industrial activities and meteorological conditions, but its temporal evolution and spatial variability require systematic assessment. This study evaluated PM₁₀ and PM_2.5 concentrations from 2010 to 2024, investigating temporal trends, spatial and seasonal differences, and their relationships with meteorological variables. The Mann–Kendall test and Theil–Sen estimator were applied to assess trends, Mann–Whitney tests to compare periods and seasons, Kruskal–Wallis tests to evaluate spatial differences, and Spearman correlations to assess meteorological relationships, complemented by pollution roses and concentration-weighted trajectory (CWT) analysis. Annual PM₁₀ concentrations exceeded the World Health Organization annual guideline of 15 µg m⁻³ at all stations and in all analyzed years, while PM_2.5 exceeded 5 µg m⁻³ in all years at the Volta Grande station. In 2024, 36% of PM₁₀ measurements exceeded the national standard of 35 µg m⁻³, with annual means of 44 ± 22 µg m⁻³ at Conforto and 44 ± 12 µg m⁻³ at Siderville. No significant long-term monotonic trends were identified for PM₁₀ or PM_2.5; for PM_2.5, the Theil–Sen slope was −0.346 µg m⁻³ year⁻¹ (<i>p</i> = 0.0866). Concentrations were higher in winter than in summer for PM₁₀ (<i>p</i> = 0.002) and PM_2.5 (<i>p</i> = 0.001), while PM₁₀ showed negative correlations with precipitation (<i>r</i> =  −0.66) and temperature (<i>r</i> =  −0.46). CWT analysis indicated potential contribution regions predominantly west and northwest of the receptor stations.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing mangrove sensitivity to thermal variations through a satellite-based analysis on the southern São Paulo coast, Brazil","authors":"Jakeline Baratto,&nbsp;Paulo Miguel de Bodas Terassi,&nbsp;Nádia Gilma Beserra de Lima,&nbsp;Emerson Galvani","doi":"10.1007/s10661-026-16005-6","DOIUrl":"10.1007/s10661-026-16005-6","url":null,"abstract":"<div><p>Mangroves near subtropical range limits may benefit from fewer cold constraints, yet warmer conditions can also increase atmospheric water demand. These competing possibilities were examined in the Cananéia-Iguape Coastal System, southeastern Brazil, by combining ERA5 2 m air temperature with MODIS normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and leaf area index (LAI). Air-temperature trends were assessed for 1979–2019 with the Mann-Kendall test and Sen’s slope. Temperature-vegetation associations were calculated for 2003–2019 from mangrove-wide means and from individual grid cells at annual, monthly, and fixed calendar-quarter scales. Mean annual air temperature increased by about 0.02 °C year⁻¹; the highest quarter-scale rate occurred in July–September (0.03 °C year⁻¹). Annual temperature correlated positively with NDVI (<i>r</i> = 0.61, <i>R</i>² = 0.38, <i>p</i> = 0.009) and EVI (<i>r</i> = 0.55, <i>R</i>² = 0.30, <i>p</i> = 0.022), whereas the LAI relationship was not significant (<i>r</i> = 0.27, <i>R</i>² = 0.07, <i>p</i> = 0.304). The sign of the association changed within the year: NDVI and EVI were negative in July–September, while positive EVI and LAI relationships occurred in October-December. Significant grid-cell relationships occupied limited and discontinuous areas. The temperature record shows regional warming, whereas canopy associations vary among metrics, periods, and locations. Given the bivariate design and coarse ERA5 grid, these associations should not be interpreted as causal or as responses to temperature alone.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10661-026-16005-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"YOLO-CSM: an enhanced YOLOv11n-based framework for efficient microplastic detection in environmental monitoring","authors":"Songzhuang Yang,&nbsp;Yu Gao,&nbsp;Zhuoran Wang,&nbsp;Xuzhu Dong,&nbsp;Wenjun Zhou","doi":"10.1007/s10661-026-15983-x","DOIUrl":"10.1007/s10661-026-15983-x","url":null,"abstract":"<div><p>As an emerging environmental pollutant, the potential toxic effects of microplastics have become a topic of global concern. To address the issues with traditional detection methods— such as cumbersome operations, time-consuming processes, and reliance on human expertise—this study proposes an improved model based on YOLOv11n, named YOLO-CSM, for the efficient detection and classification of microplastics. First, partial multiscale convolutional modules (CSP-P) are introduced into the backbone and neck networks. By utilizing multiscale convolutional kernels and a cross-stage feature fusion mechanism, the model’s ability to extract fine-grained features and detect minute objects is enhanced. Second, an SKFP module based on shared and dilated convolutions is designed to expand the receptive field and improve multiscale feature representation capabilities. Finally, the MSR module in the detection head dynamically adjusts feature weights via an adaptive average pooling layer and combines this with fully connected layers to strengthen cross-scale feature fusion, thereby improving the model’s ability to recognize targets in complex backgrounds. Experimental results show that the improved model achieves mAP50 and mAP50–95 values of 92.06% and 44.08%, respectively. The complete model required 8.7 GFLOPs and achieved an inference speed of 143.85 FPS, indicating that it retained real-time detection capability despite the increase in computational complexity. Its overall performance surpasses that of the baseline YOLOv11n and other mainstream models, providing an efficient and reliable visual method for microplastic detection.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal dynamics of heavy metal concentrations from municipal solid waste landfill leachate in Varanasi: impact on groundwater quality and human health","authors":"Katina Chachei,&nbsp;Kirpa Ram","doi":"10.1007/s10661-026-16004-7","DOIUrl":"10.1007/s10661-026-16004-7","url":null,"abstract":"<div><p>Landfills remain a widely used and cost-effective method for municipal solid waste (MSW) disposal; however, they impose substantial environmental impacts through the release of contaminants into surrounding soil, water bodies including groundwater. This study investigated the seasonal dynamics of physico-chemical and heavy metals (HMs) in leachate (<i>n</i> = 26 each for raw and treated leachate) and nearby groundwater (<i>n</i> = 24) at a MSW landfill in Varanasi, India, during 2023–2024. Pollution indices, potential sources and human health risks were evaluated for populations residing within 1.5 km of the landfill. Most parameters in treated leachate complied with effluent discharge limit, except COD and Pb. However, elevated level of leachate pollution index (LPI) was observed in both raw (mean = 18.0) and treated leachate (mean = 9.7), exceeding the permissible limit of 7.5. In groundwater, most HMs, except Cu and Zn, exceeded drinking water standards, resulting in “very poor” water quality (WQI ≥ 200–300) and “high” heavy metal pollution (HPI &gt; 55) during monsoon and post-monsoon seasons. Health risks assessment indicated potential non-carcinogenic risk (HI &gt; 1) through ingestion for both adults (HI = 1.28) and children (HI = 2.94), while carcinogenic risks remained within acceptable range. Significant seasonal variation in Cu, Cr and Ni concentrations in raw leachate suggested metal-specific responses to local hydrogeological and climatic conditions, whereas groundwater showed stable concentrations (<i>p</i> &gt; 0.05). Principal component analysis indicated that HMs primarily originated from anthropogenic waste and agricultural activities. These findings underscore the need for long-term monitoring including seasonal variability to understand the fate, migration and impacts of MSW related HMs into the surrounding ecosystem.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting soil recovery timelines in degraded mine lands using tree-based soil quality indices and asymptotic growth model","authors":"Abhishek Maitry,&nbsp;Gunjan Patil,&nbsp;Manoj Kumar Jhariya","doi":"10.1007/s10661-026-15972-0","DOIUrl":"10.1007/s10661-026-15972-0","url":null,"abstract":"<div><p>Ecological restoration of degraded mine soils remains a challenge in restoration processes. Precisely identifying the restoration trajectory is crucial for evaluating reclamation success, informing adaptive management decisions, and predicting the ecosystem’s future. This research suggests using a combined approach involving a tree-based Reclaimed Mine Soil Quality Index (RMSQI) and an asymptotic growth model to predict reclamation age in degraded mine soils. The study examined the soil physical and chemical conditions, biological activity, and enzymatic parameters under four dominant tree species: <i>Dalbergia sissoo</i>, <i>Azadirachta indica</i>, <i>Tectona grandis</i>, and <i>Albizia procera</i>. This was done at 5, 15, and 25 years after reclamation, along with assessments of non-planted soil and reference normal soil (RNS). As the age of the plantations increased, the RMSQI values rose from 0.230–0.249 at 5 years to 0.607–0.627 at 25 years. These values approached the RNS value of 0.656. Among the models used to predict RMSQI trends, the asymptotic growth model was the most accurate, with <i>R</i>² values over 0.99. Monte Carlo simulations indicated the median recovery period could range from 29 to 34 years to reach the reference soil condition. <i>D. sissoo</i> showed the quickest recovery time, while <i>T. grandis</i> demonstrated high variability in recovery duration. These findings provide a solid foundation for predicting reclamation timeframes and choosing suitable species for successful mine rehabilitation projects.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environmental occurrence, spatial distribution, and probabilistic dietary risk assessment of cypermethrin and glyphosate residues in agricultural ecosystems of southwestern Nigeria","authors":"Omolara Jemimah Ojezele,&nbsp;Matthew Obaineh Ojezele","doi":"10.1007/s10661-026-15973-z","DOIUrl":"10.1007/s10661-026-15973-z","url":null,"abstract":"<div><p>Pesticide use in vegetable production raises concerns regarding environmental contamination, food safety, and human health, particularly where pesticide stewardship is inadequate. This study investigated the occurrence, spatial distribution, environmental partitioning, and dietary health risks of cypermethrin and glyphosate in water, sediment, soil, and <i>Amaranthus cruentus </i>collected from 30 sampling sites across three major vegetable-producing settlements in Oyo State, southwestern Nigeria. A total of 240 matrix-season samples were analysed using validated chromatographic methods, generating 480 independent pesticide-specific sample-level observations after analytical duplicates were averaged. Residue data were evaluated using hierarchical mixed-effects modelling, principal component analysis, Moran’s <i>I</i> spatial autocorrelation analysis, deterministic dietary risk assessment, empirical Monte Carlo simulation with 10,000 iterations, and a structured survey of vegetable farmers. Glyphosate predominated in soil and sediment, whereas cypermethrin occurred at comparatively higher concentrations in <i>A. cruentus</i>. Significant spatial autocorrelation was detected specifically for glyphosate in sediment (Moran’s <i>I </i>= 0.783, <i>p</i> = 0.0003). Deterministic assessment indicated acceptable dietary risk for adults for both pesticides and for glyphosate in children, whereas cypermethrin exceeded the hazard threshold in children (HQ = 1.818). Monte Carlo simulation showed HQ &gt; 1 in 15.09% of adult and 70.47% of child cypermethrin exposure scenarios, while no simulated glyphosate exposure exceeded this threshold. Despite substantial exceedance of selected EU spinach maximum-residue-limit benchmarks, farmer practices indicated limited pesticide stewardship and short pre-harvest intervals. These findings support strengthened pesticide stewardship, residue surveillance, farmer education, and regulatory oversight to improve food safety.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 11","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149132849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}