Environmental Monitoring and Assessment最新文献

{"title":"Neurophysiological responses to neighbor noise in high-density residential environments: a study on noise sensitivity and cognitive impact in university dormitories","authors":"Meng Zhen,&nbsp;Xiaoyi She,&nbsp;Haijuan Liang","doi":"10.1007/s10661-025-14655-6","DOIUrl":"10.1007/s10661-025-14655-6","url":null,"abstract":"<div><p>This study investigates the effects of neighbor noise on cognitive performance and α-EEG responses in noise-sensitive individuals within high-density university dormitories. This research not only addresses the gap in understanding how neighborhood sounds influence cognitive function and brain activity in noise-sensitive individuals but also provides novel evidence of region-specific α-EEG responses (especially in the Temporal and Parietal regions). Moreover, the findings highlight potential cross-cultural implications, as noise sensitivity varies across different urban living contexts worldwide. The study simulated neighborhood noise in a laboratory environment, using a range of sounds, including music, speech, footsteps, and combinations of footsteps with other sounds. Results showed that noise-sensitive individuals had significantly higher α-EEG activity in response to music, speech, and footsteps compared to non-noise-sensitive individuals. Furthermore, significant differences were observed across brain regions, with the strongest α-EEG activity localized in the Temporal and Parietal regions, indicating these areas as key neural correlates of noise sensitivity. In the initial stages of sound exposure, both groups showed an increase in α-EEG to music. The study demonstrated significant differences between sound sources and highlighted that α-EEG responses differed between the resting and task conditions, with varying responses between the two groups. This study contributes new neurophysiological evidence on how common neighbor noises affect sensitive individuals in shared living environments, and suggests that α-EEG can serve as a reliable biomarker to inform cross-cultural noise management, dormitory design, and urban housing policies aimed at improving mental health and productivity.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297936","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":"Multi-dimensional Attention-Based MOSSM Model for Marine Oil Spill Monitoring in SAR image Remote Sensing","authors":"Junwei Liao,&nbsp;Zhenpei Li,&nbsp;Xiangwei Tang,&nbsp;Qi Huo,&nbsp;Xing Tong","doi":"10.1007/s10661-025-14676-1","DOIUrl":"10.1007/s10661-025-14676-1","url":null,"abstract":"<div><p>Marine oil spills pose severe threats to marine ecosystems, where rapid and accurate oil spill region segmentation is crucial for emergency response to disasters. Synthetic Aperture Radar (SAR), with its all-weather and day-night observation capabilities, serves as a vital data source for oil spill monitoring. However, SAR images are susceptible to the interference of speckle noise and complex background, limiting the accuracy of traditional segmentation methods. Therefore, this paper based on DeepLabV3 + proposes an enhanced model—Marine Oil Spill Segmentation Model (MOSSM). Firstly, the SE (Squeeze-and-Excitation) channel attention mechanism is introduced into the Bottleneck structure of ResNet50 to enhance the ability to extract critical features in oil spill regions by dynamically adjusting feature channel weights. Secondly, a High-Low Feature Fusion Module (HLFusion) is designed with spatial, channel, and pixel attention mechanisms incorporated to optimize detail preservation during high-low feature fusion. It effectively mitigates the interference between SAR image noise and background. Experiments based on the SOS oil spill dataset (containing 8,070 SAR images of 256 × 256 pixels) demonstrate that the indexes of MOSSM, including Intersection over Union (IoU) (74.47%), pixel accuracy (91.74%), and recall (85.91%), significantly outperform those of U-Net, FCN, SegNet, and the original DeepLabV3 + . The model particularly excels in segmenting complex oil spill boundaries and scattered oil slicks. This research provides a higher-precision and more robust segmentation method for SAR image oil spill monitoring, offering significant application value for marine environmental disaster warning and emergency decision-making.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297958","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":"Thematically weighted regression models for identification of important drivers of environmental trends in lake survey data","authors":"Claudia von Brömssen,&nbsp;Jens Fölster,&nbsp;Karin Eklöf","doi":"10.1007/s10661-025-14611-4","DOIUrl":"10.1007/s10661-025-14611-4","url":null,"abstract":"<div><p>The processes that drive environmental change are complex and often interwoven. Monitoring such processes and their effects on environmental variables is, at best, spatially and temporally incomplete. The Swedish Lake survey consists of several thousands of randomly selected lakes stretching over a wide range of potential influences, including regional and local scale pressures, such as recovery from acidification, changes in climate, and effects from various catchment characteristics. The main drawback for this monitoring data is that the temporal resolution is low and does not allow for the use of traditional trend evaluation methods at individual stations, much less the attribution of important drivers. In this study, we present a method that enables an evaluation of important drivers of change by defining trend coefficients as smoothed estimates over lakes that exhibit similar attributes, e.g., comparable levels or similar temporal changes in selected explanatory variables. The principles are the same as geographically weighted regression but replace the geographic coordinate system with a thematic one, based on principal (PCA) or partial least squares (PLS) components. We illustrate this method by evaluating trends in pH in Sweden from 2012 to 2023 and detected several regions where pH is decreasing, mainly in relation to changes in calcium.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10661-025-14611-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145306759","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":"Spatial variation of water quality in selected rivers in Penang, Malaysia, in relation to tidal dynamics authors","authors":"Yusuf Abdullahi,&nbsp;Wan Maznah Binti Wan Omar,&nbsp;Sazlina Salleh","doi":"10.1007/s10661-025-14566-6","DOIUrl":"10.1007/s10661-025-14566-6","url":null,"abstract":"<p>This study aims to evaluate the spatial variation of water quality in three short rivers on Penang Island in relation to tidal dynamics and seawater intrusion from the Strait of Malacca. Sungai Tukun, located within a national park, served as a reference site. Ten sampling stations were established across upstream, midstream, and downstream segments of the rivers, with an additional site in Sungai Batu Ferringhi to capture anthropogenic influences. Water sampling and in situ measurements were conducted during spring and neap tides and analysed using the standard method (APHA, 2017). The Kruskal–Wallis H test revealed significant spatial variations (<i>p</i> &lt; 0.05) in multiple parameters, including pH, total dissolved solids, salinity, Secchi depth, ammonium, nitrate, chlorophyll-a, orthophosphate, and discharge. The Mann–Whitney <i>U</i> test showed significant differences (<i>p</i> &lt; 0.01) in water temperature, pH, salinity, total dissolved solids, ammonium, discharge, and euphotic depth between high and low tides at downstream stations. Significant vertical stratification in salinity and Secchi disk depth was also observed at downstream segments (<i>p</i> &lt; 0.01). Principal component analysis (PCA) indicated that PC1, dominated by salinity, water temperature, and total dissolved solids, accounted for 28.80%, 30.88%, and 27.02% of the total variance in Sungai Batu Ferringhi, Sungai Tukun, and Sungai Keluang, respectively, indicating tidal influence. PC2 was mainly associated with nutrient-related variables. The findings revealed distinct spatial variation in water quality and nutrient distribution among the three short rivers of Penang Island, with tidal dynamics contributing to these patterns and informing sustainable freshwater management in tidal-influenced catchments.</p>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297885","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":"Post ferric-substitution detection method optimization for Ni(II)-organic complexes measurement: Simulation, experimentation, and modeling","authors":"Wei Deng,&nbsp;Xiaoli Lv,&nbsp;Cheng Lu,&nbsp;Ke Liu,&nbsp;Kaiyuan Zheng,&nbsp;Jibo Xiao,&nbsp;Min Zhao,&nbsp;Xianfeng Huang","doi":"10.1007/s10661-025-14658-3","DOIUrl":"10.1007/s10661-025-14658-3","url":null,"abstract":"<div><p>Nickel (Ni(II)) complexes, especially those formed with strong ligands such as ethylenediaminetetraacetic acid (EDTA), are difficult to quantify due to their low environmental concentrations and weak ultraviolet (UV) absorbance. These characteristics limit the effectiveness of conventional spectrophotometric methods. Among indirect detection strategies, Fe(III) substitution methods has emerged as a viable approach. However, the associated parameters have not been systematically optimized, resulting in limited sensitivity and practical application. In this study, we systematically refine the Fe(III) substitution approach by simulation-guided experimental design, machine-learning based variables importance analysis, and predictive modeling analysis. Thermodynamic simulations and density functional theory (DFT) calculations guided experimental design. Under optimized conditions, the method achieved a detection limit as low as 1 × 10⁻³ mM for Ni-EDTA. Application in surface water, groundwater, and electroplating wastewater showed strong linearity (R² &gt; 0.96) and good matrix tolerance. In addition, machine learning models were utilized to interpret variable importance and predict recovery performance. Notably, Random Forest Regression (RFR) model demonstrated superior predictive performance (R² = 0.951) and revealed that both pH and water bath duration are critical factors. This research successfully develops and optimizes a reliable Fe(III) substitution method for environmental monitoring of Ni complexes. The combined approach represents a significant advancement in water quality analysis and provides a promising strategy for addressing the challenges posed by Ni(II) complexes in complex aqueous environments.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145290613","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":"An integrated model of log-normal ordinary Kriging interpolation-based source-specific human health risk assessment (LSR) for soil heavy metal pollution: insights from an abandoned industrial area in China","authors":"Shuai Li,&nbsp;Yimei Zhang","doi":"10.1007/s10661-025-14635-w","DOIUrl":"10.1007/s10661-025-14635-w","url":null,"abstract":"<div><p>Soil heavy metal (SHM) accumulation is a major global concern in environmental protection and public health, and accurate source-specific human health risk assessment is essential for effective risk control of SHM pollution. In this study, we developed an integrated LSR model that combines log-normal ordinary Kriging (LOK), source apportionment, and human health risk assessment. The model was applied to a multi-source contaminated site in southern Jiangsu Province, China. Statistical analysis shows that the mean values of Cd, Cr, Ni, Pb, and Zn are higher than the local background value (BV). Significant spatial variations of As, Cd, Cr, Pb, and Zn are also determined by their high coefficients of variation (CV). Cross-validation further shows that LOK performs better than ordinary Kriging (OK) methods in interpolation accuracy, especially under conditions of high variation coefficients of SHM contents. The reliability of source apportionment and human health risk assessment was confirmed by bootstrap and Monte Carlo simulation, respectively. The estimated 95th percentile total non-cancer (1.87) and cancer health risks (1.73 × E-3) for children were high, indicating elevated health risk for this population group. Source-specific risk estimates based on the LSR model showed that industrial and agricultural sources contributed 69.8% and 87.8% to the total non-cancer and cancer risks, respectively. These findings underscore that the LSR model could provide a reliable and cost-efficient way for quantifying sources related to human health risks, and support the decision-making in SHM pollution control.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297956","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":"Multiscale analysis of statistical trends in water quality across land use gradients in the Najafgarh Drain, Delhi","authors":"Mansi Vaid,&nbsp;Shipra Tyagi,&nbsp;Anshu Gupta,&nbsp;Kiranmay Sarma","doi":"10.1007/s10661-025-14624-z","DOIUrl":"10.1007/s10661-025-14624-z","url":null,"abstract":"<div><p>Aquatic systems are known to be affected by LULC prevailing in their proximity at various spatial scales and configurations. This study investigates such associations for the Najafgarh drain in the Delhi megacity (Northern India) at two spatial scales (reach and riparian) and two seasons (pre- and post-monsoon) for the year 2019. LULC mapping within a 5 km buffer of the drain, conducted using on-screen visual interpretation, revealed a dominance of built-up areas (46.8%) followed by fallowland (27.3%), together comprising 74% of the total area. A comparison with 1999 data indicated a 20.5% increase in built-up areas over two decades, primarily replacing agriculture, fallowland, and vegetation. To examine LULC–water quality relationships, reach and riparian scale buffer analyses of varying widths were delineated, and landscape metrics were derived using FRAGSTATS. Statistical analyses, including Pearson correlation, principal component analysis, and multiple regression, showed that most of the water quality variables were positively correlated with built-up areas and negatively correlated with agriculture and fallowland. These associations became more pronounced with increasing buffer width, especially in the post-monsoon season. Reach-scale buffers effectively captured localized pollutant sources, while riparian-scale buffers were more useful for broader area management. The expansion of built-up areas and corresponding decline in natural and semi-natural land covers over 1999–2019 highlights the intensity of urban development in Delhi. This study provides a valuable database for policymakers and stakeholders involved in managing and improving water quality in urban aquatic systems such as the Najafgarh drain.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297870","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":"Monitoring and assessment of a novel halophyte-based two-stage electroecological system for remediation of brackish sewage","authors":"Meena Choudhary,&nbsp;Biswajit Swain,&nbsp;Gopi Satasiya,&nbsp;Monali Muduli,&nbsp;Sanak Ray","doi":"10.1007/s10661-025-14626-x","DOIUrl":"10.1007/s10661-025-14626-x","url":null,"abstract":"<div><p>This study examines the performance of an innovative electroecological system for treating brackish sewage in five cycles with different salinity concentrations. Two systems were designed: a control and electroecological system using a halophytic-constructed wetland (<i>Juncus rigidus</i>, retention time 96 h) and an electrolytic cell (graphite electrode, external electric potential of 12 V applied for 8 h). The system effectively removed pollutants such as salinity (48–61.94%), COD (83.56–87.76%), BOD₅ (94.90–96.55%), TSS (90–92%), PO₄³⁻-P (98.46–99.6%), NH₄⁺-N (99.65%), NO₃⁻-N (71.94–91.96%), and NO₂⁻-N (79.66–86.88%) were achieved along with heavy metals like Cr (99.9%), Mn (47–55.97%), Mo (60.14–99.9%), Cd (30.77–99.9%), Zn (11.21–18.78%), and Al (14.93–99.9%) from wastewater and followed first-order kinetics. The electroecological system’s effectiveness was validated using statistical techniques like PCA and the Mann–Whitney <i>U</i> test. Pathogens, including <i>Vibrio</i>,<i> E. coli</i>,<i> Pseudomonas</i>, fecal <i>Coliform</i>, and <i>Aeromonas</i>, were nearly 99.9% removed, along with 99% of organic compounds, including emerging pollutants. Ion chromatography and inductively coupled plasma were used to study the accumulation of ions (Cl⁻, SO₄²⁻, Na⁺, K⁺, Mg²⁺, and Ca²⁺) in <i>Juncus</i> and their removal in water (around 83.15% K⁺, 30.53% SO₄²⁻, 29.53% Cl⁻, 26.45% Mg²⁺, 13.58% Na⁺, and 9.50% Ca²⁺). <i>Juncus</i> was efficient in accumulating K⁺ (66.99%) and Mg²⁺ (42.32%) ions. The electroecological system’s physical and biochemical analysis shows no salinity stress, showing potential for treating brackish sewage. No research has been reported on treating brackish sewage using a <i>Junucs</i>-based CW-electrolytic cell in the literature. It is a novel approach for independent wastewater treatment in coastal, remote, and rural areas.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297898","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":"Deep learning simulation and decision support system for groundwater salinity risk assessment in the lower Chao Phraya River Basin, Thailand","authors":"Mojtaba Heydarizad,&nbsp;Zhongfang Liu,&nbsp;Nathsuda Pumijumnong,&nbsp;Hamid Ghalibaf Mohammadabadi","doi":"10.1007/s10661-025-14681-4","DOIUrl":"10.1007/s10661-025-14681-4","url":null,"abstract":"<div><p>Groundwater salinization poses a critical threat to freshwater security in coastal regions, particularly under intensified extraction and evolving hydroclimatic conditions. This study examines the spatial and temporal evolution of salinity in the lower Chao Phraya River Basin during 2008 and 2020 using a multi-method machine learning framework. SHAP-based feature attribution analysis identified groundwater extraction as the most influential driver of salinity dynamics. A Gaussian copula model was employed to quantify the conditional probability of salinity threshold exceedance under varying extraction pressures, capturing nonlinear dependence structures between total dissolved solids (TDS) and groundwater extraction. A Graph Neural Network (GNN) model was developed to simulate TDS concentrations at 212 monitoring stations, demonstrating high predictive performance across both periods. To translate model outputs into actionable insights, a scenario-based Decision Support System (DSS) was implemented, enabling interactive visualization of salinity risk zones under 20% and 40% increases in groundwater withdrawal. Results reveal a pronounced expansion of high-salinity areas over time, largely driven by anthropogenic factors. By fusing explainable machine learning with probabilistic analysis and decision support, this framework provides a novel, scalable tool for real-time groundwater salinity risk assessment and supports evidence-based management in data-scarce coastal aquifers.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145290649","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":"Adsorption–desorption behaviour of mesosulfuron methyl and iodosulfuron methyl across soils with varying texture, organic carbon and pH","authors":"Harshdeep Kaur,&nbsp;Pervinder Kaur","doi":"10.1007/s10661-025-14647-6","DOIUrl":"10.1007/s10661-025-14647-6","url":null,"abstract":"<div><p>Mesosulfuron methyl and iodosulfuron methyl are sulfonylurea herbicides widely used for weed control in cereal crops. Despite their low mammalian toxicity, their high-water solubility and weakly acidic nature suggest potential risks regarding their environmental mobility and persistence in diverse agricultural soils, particularly those that are alkaline. Since adsorption–desorption dynamics strongly influence their transport and bioavailability, the study aims to quantify and compare their adsorption–desorption behaviour in five agricultural soils differing in texture, organic carbon content and pH. Adsorption kinetics followed a two-stage process, with rapid adsorption during the initial hours, reaching equilibrium within 24 h. The pseudo-second-order kinetic model provided the best fit for experimental data. The adsorption isotherms exhibited C-type behaviour, with data fitting well to both the Freundlich and Langmuir models, indicating heterogeneous adsorption sites with a high correlation to soil composition. <i>K</i>_Fads of mesosulfuron methyl and iodosulfuron methyl were 1.811 ± 0.012 to 9.954 ± 0.056 and 1.068 ± 0.011 to 8.941 ± 0.078 µg¹⁻ⁿ g⁻¹mLⁿ, indicating weak adsorption of iodosulfuron methyl as compared to mesosulfuron methyl on the studied soils. <i>K</i>_Fads of acidic loam 1 soil (<i>K</i>_Fads = 8.941 ± 0.078 to 9.954 ± 0.056 µg¹⁻ⁿ g⁻¹mLⁿ) was about 5.49 to 8.37-fold higher as compared to alkaline loamy sand soil (1.068 ± 0.011 to 1.811 ± 0.012 µg¹⁻ⁿ g⁻¹mLⁿ) and the adsorption of herbicides follows the trend as loam 2 &gt; clay loam &gt; sandy loam &gt; loamy sand. Adsorption decreased with increasing temperature, highlighting the exothermic nature of the process. Desorption studies showed that mesosulfuron methyl exhibited higher retention than iodosulfuron methyl, with desorption being more prominent in alkaline soils due to electrostatic repulsion and entrapment in soil nanopores. These findings contribute to understanding the environmental fate of mesosulfuron methyl and iodosulfuron methyl and may help in predicting their mobility and persistence in agricultural soils.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297798","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}