首页 > 最新文献

环境科学与生态学最新文献

英文 中文
IF:
Legacy effects control root elemental composition and stoichiometry in subtropical forests: Empirical support for the biogeochemical niche hypothesis
IF 5.5 1区 环境科学与生态学 Q1 ECOLOGY Pub Date : 2025-03-20 DOI: 10.1111/1365-2745.70031
Mingyan Hu, Yang Chen, Jordi Sardans, Josep Peñuelas, Han Y. H. Chen, Chengjin Chu, Zilong Ma

CONFLICT OF INTEREST STATEMENT

The authors declare no competing interests.

{"title":"Legacy effects control root elemental composition and stoichiometry in subtropical forests: Empirical support for the biogeochemical niche hypothesis","authors":"Mingyan Hu, Yang Chen, Jordi Sardans, Josep Peñuelas, Han Y. H. Chen, Chengjin Chu, Zilong Ma","doi":"10.1111/1365-2745.70031","DOIUrl":"https://doi.org/10.1111/1365-2745.70031","url":null,"abstract":"<h2> CONFLICT OF INTEREST STATEMENT</h2>\u0000<p>The authors declare no competing interests.</p>","PeriodicalId":191,"journal":{"name":"Journal of Ecology","volume":"25 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143660632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
引用次数: 0
Integrating Dual-Stage Gas Permeable Membranes and Humic Acid Recovery to Optimize Fenton Oxidation of Landfill Leachate: Insights into Full-Process Performance and DOM Molecular-Level Transformation
IF 12.8 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-03-20 DOI: 10.1016/j.watres.2025.123525
Linjun Wu, Huan Li, Yanyue Gu, Zhiqiang Shen, Yuexi Zhou, Jiane Zuo
This research introduces an innovative full-process treatment technology that integrates dual-stage gas permeable membranes (GPM) and humic acid (HA) recovery to enhance Fenton oxidation of landfill leachate (LFL). In terms of full-process performance, this integrated approach (LFL-GPM-HA (Fenton)) synergistically combines LFL concentration, ammonia recovery, HA recovery, purified water reclamation, and efficient Fenton oxidation, thereby achieving holistic minimization, detoxification, and resource recovery of LFL. Specifically, under the conditions of low-intensity aeration and a temperature gradient of 65-55-25°C, the GPM achieved an ammonia recovery rate exceeding 96%, while the LFL was concentrated by a factor of 4.72 within 12 hours. During HA recovery at pH 2, the HA yield from the concentrated LFL reached 3.68 g/L, representing an 88.72% increase compared to the raw LFL. Due to the significant consumption of bicarbonate alkalinity during the GPM process, the required dosage of H₂SO₄ per gram of HA recovered was reduced by 86.72%. Under different dimensionless oxidant dosages, the LFL-GPM-HA (Fenton) demonstrated a significant improvement in COD removal efficiency compared to standalone Fenton oxidation. In terms of dissolved organic matter (DOM) molecular-level transformation, ESI FT-ICR-MS analysis showed a significant enhancement in the removal of CHOS and CHONS in LFL-GPM-HA (Fenton), with a concurrent reduction in the produced sulfurous byproducts. Additionally, the LFL-GPM-HA (Fenton) notably increased the frequency of decarboxylation, desulfurization, and dealkylation reactions. In terms of operational stability and economic feasibility, this integrated system demonstrates excellent long-term stability and robust membrane fouling-cleaning recovery properties, achieving LFL treatment at a cost of approximately 12.142 $/m³, which is significantly more cost-effective than conventional full-process advanced treatment technologies (20-30 $/m³). In conclusion, the findings offer a pathway for developing more efficient and cost-effective strategies for LFL management.
{"title":"Integrating Dual-Stage Gas Permeable Membranes and Humic Acid Recovery to Optimize Fenton Oxidation of Landfill Leachate: Insights into Full-Process Performance and DOM Molecular-Level Transformation","authors":"Linjun Wu, Huan Li, Yanyue Gu, Zhiqiang Shen, Yuexi Zhou, Jiane Zuo","doi":"10.1016/j.watres.2025.123525","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123525","url":null,"abstract":"This research introduces an innovative full-process treatment technology that integrates dual-stage gas permeable membranes (GPM) and humic acid (HA) recovery to enhance Fenton oxidation of landfill leachate (LFL). In terms of full-process performance, this integrated approach (LFL-GPM-HA (Fenton)) synergistically combines LFL concentration, ammonia recovery, HA recovery, purified water reclamation, and efficient Fenton oxidation, thereby achieving holistic minimization, detoxification, and resource recovery of LFL. Specifically, under the conditions of low-intensity aeration and a temperature gradient of 65-55-25°C, the GPM achieved an ammonia recovery rate exceeding 96%, while the LFL was concentrated by a factor of 4.72 within 12 hours. During HA recovery at pH 2, the HA yield from the concentrated LFL reached 3.68 g/L, representing an 88.72% increase compared to the raw LFL. Due to the significant consumption of bicarbonate alkalinity during the GPM process, the required dosage of H₂SO₄ per gram of HA recovered was reduced by 86.72%. Under different dimensionless oxidant dosages, the LFL-GPM-HA (Fenton) demonstrated a significant improvement in COD removal efficiency compared to standalone Fenton oxidation. In terms of dissolved organic matter (DOM) molecular-level transformation, ESI FT-ICR-MS analysis showed a significant enhancement in the removal of CHOS and CHONS in LFL-GPM-HA (Fenton), with a concurrent reduction in the produced sulfurous byproducts. Additionally, the LFL-GPM-HA (Fenton) notably increased the frequency of decarboxylation, desulfurization, and dealkylation reactions. In terms of operational stability and economic feasibility, this integrated system demonstrates excellent long-term stability and robust membrane fouling-cleaning recovery properties, achieving LFL treatment at a cost of approximately 12.142 $/m³, which is significantly more cost-effective than conventional full-process advanced treatment technologies (20-30 $/m³). In conclusion, the findings offer a pathway for developing more efficient and cost-effective strategies for LFL management.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"1 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143660641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
引用次数: 0
Urban change detection: assessing biophysical drivers using machine learning and Google Earth Engine
IF 2.9 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Pub Date : 2025-03-20 DOI: 10.1007/s10661-025-13863-4
Olufemi Sunday Durowoju, Rotimi Oluseyi Obateru, Samuel Adelabu, Adeyemi Olusola

Urban areas are experiencing rapid transformations, driven by population growth, economic development, and policy changes. Understanding and monitoring these dynamic changes is crucial for sustainable urban planning and management. This study leverages machine learning and Google Earth Engine to investigate urban dynamics and its interactions with biophysical conditions in the Kaduna River Basin (KRB), Nigeria. This study utilized a dataset of 192 points, initially extracted from Google Earth Engine, to analyze urban transitions between 1987 and 2020, incorporating biophysical and environmental variables such as population density, precipitation, and surface temperature. The dataset was processed in R using the CARET package, with missing data imputed via K-nearest neighbors (KNN), categorical variables transformed using One-Hot Encoding, and numerical variables rescaled for consistency. A tenfold cross-validation approach was used to train and validate machine learning models, including random forest, support vector machine, KNN, and multivariate adaptive regression splines, ensuring optimal model performance. Model evaluation metrics such as overall accuracy, kappa, F1 score, and area under the curve confirmed the reliability of the models in identifying the biophysical factors influencing urban changes. The findings revealed overall accuracy of 0.80, 0.73, 0.71, and 0.72 and kappa statistics of 0.60, 0.46, 0.42, and 0.45 for random forest (RF), multivariate adaptive regression splines, support vector machine, and KNN, respectively, with RF emerging as the most accurate model (80%) for predicting urban change patterns in KRB. Land cover changes reveal rapid urban expansion (154.81%), declining water bodies (− 95.79%), and vegetation growth (174%). Machine learning models identify population density and water stress index as key urban change drivers, with climate factors like temperature and precipitation playing crucial roles. The results of this study offer valuable insights into the processes driving urban transformation and present a robust methodology for monitoring and predicting future urban development. This study aids in the creation of strategies for sustainable urban growth and the mitigation of adverse environmental impacts.

{"title":"Urban change detection: assessing biophysical drivers using machine learning and Google Earth Engine","authors":"Olufemi Sunday Durowoju,&nbsp;Rotimi Oluseyi Obateru,&nbsp;Samuel Adelabu,&nbsp;Adeyemi Olusola","doi":"10.1007/s10661-025-13863-4","DOIUrl":"10.1007/s10661-025-13863-4","url":null,"abstract":"<div><p>Urban areas are experiencing rapid transformations, driven by population growth, economic development, and policy changes. Understanding and monitoring these dynamic changes is crucial for sustainable urban planning and management. This study leverages machine learning and Google Earth Engine to investigate urban dynamics and its interactions with biophysical conditions in the Kaduna River Basin (KRB), Nigeria. This study utilized a dataset of 192 points, initially extracted from Google Earth Engine, to analyze urban transitions between 1987 and 2020, incorporating biophysical and environmental variables such as population density, precipitation, and surface temperature. The dataset was processed in R using the CARET package, with missing data imputed via K-nearest neighbors (KNN), categorical variables transformed using One-Hot Encoding, and numerical variables rescaled for consistency. A tenfold cross-validation approach was used to train and validate machine learning models, including random forest, support vector machine, KNN, and multivariate adaptive regression splines, ensuring optimal model performance. Model evaluation metrics such as overall accuracy, kappa, F1 score, and area under the curve confirmed the reliability of the models in identifying the biophysical factors influencing urban changes. The findings revealed overall accuracy of 0.80, 0.73, 0.71, and 0.72 and kappa statistics of 0.60, 0.46, 0.42, and 0.45 for random forest (RF), multivariate adaptive regression splines, support vector machine, and KNN, respectively, with RF emerging as the most accurate model (80%) for predicting urban change patterns in KRB. Land cover changes reveal rapid urban expansion (154.81%), declining water bodies (− 95.79%), and vegetation growth (174%). Machine learning models identify population density and water stress index as key urban change drivers, with climate factors like temperature and precipitation playing crucial roles. The results of this study offer valuable insights into the processes driving urban transformation and present a robust methodology for monitoring and predicting future urban development. This study aids in the creation of strategies for sustainable urban growth and the mitigation of adverse environmental impacts.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10661-025-13863-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655204","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}
引用次数: 0
Influences of anaerobic treatment on chemical oxygen demand removal behavior of tannery wastewater
IF 2.9 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Pub Date : 2025-03-20 DOI: 10.1007/s10661-025-13905-x
Venkatesh Rathinavelu, Viyat Varun Upadhyay, Rakesh Kumar, Vinayagam Mohanavel, Nagabhooshanam Nagarajan, Dhaval Rabadiya, Manzoore Elahi Mohammed Soudagar, Sami Al Obaid, Saleh Hussein Salmen

Syngas are produced from wastewater through anaerobic reactions and thermochemical processes, using a catalyst that modifies the gas composition, reduces methane production, and achieves partial COD reduction. The current research is attempting to treat the tannery wastewater via an anaerobic process configured with 0.25, 0.3, and 0.35 volume units of granular activated carbon (GAC) with 10 nm size to minimize the concentration of chemical oxygen demand (COD) and improve the biological methane yield. During this anaerobic process, the up-flow anaerobic sludge blanket (UASB) reactor supports to enhance the bio-methane production and handle the high rate of organic load. Influences of GAC units and operating time (days) on COD and biological methane yield of an anaerobic system for tannery wastewater treatment are studied and measured in their value. The output results of COD and biological methane yield are compared, and it was spotted that the tannery water process with 0.3 volume units of GAC owns 87% of COD removal with biological methane yield of 66.3 mL/day (7.2 mL/g COD removed) and end of 30th day found 1939 mL.

{"title":"Influences of anaerobic treatment on chemical oxygen demand removal behavior of tannery wastewater","authors":"Venkatesh Rathinavelu,&nbsp;Viyat Varun Upadhyay,&nbsp;Rakesh Kumar,&nbsp;Vinayagam Mohanavel,&nbsp;Nagabhooshanam Nagarajan,&nbsp;Dhaval Rabadiya,&nbsp;Manzoore Elahi Mohammed Soudagar,&nbsp;Sami Al Obaid,&nbsp;Saleh Hussein Salmen","doi":"10.1007/s10661-025-13905-x","DOIUrl":"10.1007/s10661-025-13905-x","url":null,"abstract":"<div><p>Syngas are produced from wastewater through anaerobic reactions and thermochemical processes, using a catalyst that modifies the gas composition, reduces methane production, and achieves partial COD reduction. The current research is attempting to treat the tannery wastewater via an anaerobic process configured with 0.25, 0.3, and 0.35 volume units of granular activated carbon (GAC) with 10 nm size to minimize the concentration of chemical oxygen demand (COD) and improve the biological methane yield. During this anaerobic process, the up-flow anaerobic sludge blanket (UASB) reactor supports to enhance the bio-methane production and handle the high rate of organic load. Influences of GAC units and operating time (days) on COD and biological methane yield of an anaerobic system for tannery wastewater treatment are studied and measured in their value. The output results of COD and biological methane yield are compared, and it was spotted that the tannery water process with 0.3 volume units of GAC owns 87% of COD removal with biological methane yield of 66.3 mL/day (7.2 mL/g COD removed) and end of 30th day found 1939 mL.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655285","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}
引用次数: 0
Sulfide intrusion of seagrass Thalassia hemprichii along a eutrophication gradient with carbonate and terrigenous sediments in tropical coastal sea
IF 13.6 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-03-20 DOI: 10.1016/j.jhazmat.2025.138005
Wenqian Qi, Yijun Liu, Zhijian Jiang, Xu Long, Yang Fang, Uditha Thejan Egodauyana, Yunchao Wu, Songlin Liu, Xiaoping Huang
Seagrasses growing in different eutrophic states in carbonate and terrigenous sediments may exhibit contrasting sulfide intrusion and responses; however, limited information is available. In this study, sulfide intrusion in the tropical typical seagrass Thalassia hemprichii along a eutrophication gradient in carbonate and terrigenous sediments on Hainan Island, South China Sea, was investigated using combined elements, stable isotopes, and photobiology. The sediment porewater sulfide concentration increased with rising nutrient levels, with porewater sulfide as 223.92±25.34 μmol/L when the dissolved inorganic nitrogen concentration was 10.83±0.60 μmol/L and the dissolved inorganic phosphate concentration was 0.39±0.01 μmol/L. The nutrient input significantly enhanced sulfide intrusion in seagrass, resulting in reduced δ34S values in roots from 12.78±1.16 to 2.69±0.46‰, with leaf δ15N as the greatest explanatory factor. In addition, sulfide intrusion inhibited photosynthesis more strongly in seagrass growing in carbonate sediments than in terrigenous sediments because of the low iron content in carbonate sediments (almost 50% of the iron content in terrigenous sediments), reducing rETRmax and Ek by 43.08% and 36.42%, respectively. Therefore, the synergistic effects of nutrient input, sulfide concentration, sediment substrate, and iron content affected the sulfide intrusion in seagrass.
{"title":"Sulfide intrusion of seagrass Thalassia hemprichii along a eutrophication gradient with carbonate and terrigenous sediments in tropical coastal sea","authors":"Wenqian Qi, Yijun Liu, Zhijian Jiang, Xu Long, Yang Fang, Uditha Thejan Egodauyana, Yunchao Wu, Songlin Liu, Xiaoping Huang","doi":"10.1016/j.jhazmat.2025.138005","DOIUrl":"https://doi.org/10.1016/j.jhazmat.2025.138005","url":null,"abstract":"Seagrasses growing in different eutrophic states in carbonate and terrigenous sediments may exhibit contrasting sulfide intrusion and responses; however, limited information is available. In this study, sulfide intrusion in the tropical typical seagrass <em>Thalassia hemprichii</em> along a eutrophication gradient in carbonate and terrigenous sediments on Hainan Island, South China Sea, was investigated using combined elements, stable isotopes, and photobiology. The sediment porewater sulfide concentration increased with rising nutrient levels, with porewater sulfide as 223.92±25.34 μmol/L when the dissolved inorganic nitrogen concentration was 10.83±0.60 μmol/L and the dissolved inorganic phosphate concentration was 0.39±0.01 μmol/L. The nutrient input significantly enhanced sulfide intrusion in seagrass, resulting in reduced δ<sup>34</sup>S values in roots from 12.78±1.16 to 2.69±0.46‰, with leaf δ<sup>15</sup>N as the greatest explanatory factor. In addition, sulfide intrusion inhibited photosynthesis more strongly in seagrass growing in carbonate sediments than in terrigenous sediments because of the low iron content in carbonate sediments (almost 50% of the iron content in terrigenous sediments), reducing rETR<sub>max</sub> and E<sub>k</sub> by 43.08% and 36.42%, respectively. Therefore, the synergistic effects of nutrient input, sulfide concentration, sediment substrate, and iron content affected the sulfide intrusion in seagrass.","PeriodicalId":361,"journal":{"name":"Journal of Hazardous Materials","volume":"20 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143660459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
引用次数: 0
Sulfur's Long Game: 145 Years of Soil Sulfur Speciation in the World's Oldest Agricultural Experiments
IF 11.6 1区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION Pub Date : 2025-03-20 DOI: 10.1111/gcb.70136
Meghan Barnard, Brigid A. McKenna, Ram C. Dalal, Steve P. McGrath, Zhe H. Weng, Jeremy L. Wykes, Peter M. Kopittke
Sulfur (S) is an essential plant nutrient, but ongoing decreases in inorganic S inputs to soil continue to reduce S availability in agricultural soils globally. This study investigated long-term trends in soil S speciation after land use change and the application of different soil amendments using the world's longest-running agricultural experiments at the Rothamsted Research Centre, UK. Soil samples spanning 145 years were obtained from the Broadbalk Wheat Experiment (continuous cropping with different amendments) and two Wilderness sites, Broadbalk Wilderness and Geescroft Wilderness (cropping land left to rewild) and analysed using synchrotron-based x-ray absorption near-edge structure (XANES) spectroscopy. It was found that changes in S speciation were linked to changes in soil organic carbon (SOC). In the Broadbalk Winter Wheat experiment, farmyard manure applications increased the proportion of reduced C-bonded S by 40% over 145 years, while the S speciation in the inorganic fertiliser (NPKMgS) and Control treatments remained unchanged and was comprised of ~48% oxidised S. In the Wilderness sites (cropping ceased 143–146 years from present), SOC accumulation during rewilding generally increased the proportions of reduced organic S. However, soil acidification at the Geescroft site initially increased the average oxidation state of S (from +3.7 in 1883 to +4.4 in 1965) despite increasing SOC. Thus, whilst SOC is important in controlling S speciation, soil pH also has a central effect. These findings provide new insights into the long-term dynamics of S speciation under different agricultural practices and land-use changes and contribute to our understanding of S and its availability in cropping systems.
{"title":"Sulfur's Long Game: 145 Years of Soil Sulfur Speciation in the World's Oldest Agricultural Experiments","authors":"Meghan Barnard, Brigid A. McKenna, Ram C. Dalal, Steve P. McGrath, Zhe H. Weng, Jeremy L. Wykes, Peter M. Kopittke","doi":"10.1111/gcb.70136","DOIUrl":"https://doi.org/10.1111/gcb.70136","url":null,"abstract":"Sulfur (S) is an essential plant nutrient, but ongoing decreases in inorganic S inputs to soil continue to reduce S availability in agricultural soils globally. This study investigated long-term trends in soil S speciation after land use change and the application of different soil amendments using the world's longest-running agricultural experiments at the Rothamsted Research Centre, UK. Soil samples spanning 145 years were obtained from the Broadbalk Wheat Experiment (continuous cropping with different amendments) and two Wilderness sites, Broadbalk Wilderness and Geescroft Wilderness (cropping land left to rewild) and analysed using synchrotron-based x-ray absorption near-edge structure (XANES) spectroscopy. It was found that changes in S speciation were linked to changes in soil organic carbon (SOC). In the Broadbalk Winter Wheat experiment, farmyard manure applications increased the proportion of reduced C-bonded S by 40% over 145 years, while the S speciation in the inorganic fertiliser (NPKMgS) and Control treatments remained unchanged and was comprised of ~48% oxidised S. In the Wilderness sites (cropping ceased 143–146 years from present), SOC accumulation during rewilding generally increased the proportions of reduced organic S. However, soil acidification at the Geescroft site initially increased the average oxidation state of S (from +3.7 in 1883 to +4.4 in 1965) despite increasing SOC. Thus, whilst SOC is important in controlling S speciation, soil pH also has a central effect. These findings provide new insights into the long-term dynamics of S speciation under different agricultural practices and land-use changes and contribute to our understanding of S and its availability in cropping systems.","PeriodicalId":175,"journal":{"name":"Global Change Biology","volume":"19 1","pages":""},"PeriodicalIF":11.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143660624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
引用次数: 0
Ambient exposure to nitrogen dioxide and lung function: a multi-metric approach
IF 2.9 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Pub Date : 2025-03-20 DOI: 10.1007/s10661-025-13871-4
Carmel Raz-Maman, Nili Borochov-Greenberg, Rafael Y. Lefkowitz, Boris A. Portnov

Most studies evaluating chronic ambient exposure to nitrogen dioxide (NO2) have used averages as the exclusive exposure metric. However, this approach may lead to an underestimation of potential health effects. The objective of this study is to evaluate the association between ambient exposure to NO2 assessed by various metrics, and lung function in a cohort of healthy male youth. A cross-sectional analysis of 5,462 subjects was conducted using multivariate linear regression. Exposure to NO₂ was assessed by spatial interpolation using Empirical Bayesian Kriging (EBK). Five different exposure metrics were evaluated over two years, including average concentration, the number and intensity of exceedances of the 24-h NO2 World Health Organization air quality guideline (AQG), and the number and intensity of 1-h NO2 peaks. Lung function indices, including percent predicted forced expiratory volume in one second (FEV1), forced vital capacity (FVC), forced expiratory flow between 25% and 75% of vital capacity (FEF25-75), and FEV1/FVC ratio, were assessed. The intensity of the 24-h AQG exceedances was associated with the largest reductions in FEV1 (-0.82%, 95% CI: -1.61%, -0.03%) and FVC (-1.03%, 95% CI: -1.86%, -0.20%), while FEF25-75 showed a significant decline only with the 1-h peak intensity metric (-2.78%, 95% CI: -5.02%, -0.54%). The study results support integrating diverse exposure metrics as part of NO2 chronic exposure assessment, as these metrics may capture a wider range of potential health effects that could be underestimated or overlooked when relying only on average concentrations.

{"title":"Ambient exposure to nitrogen dioxide and lung function: a multi-metric approach","authors":"Carmel Raz-Maman,&nbsp;Nili Borochov-Greenberg,&nbsp;Rafael Y. Lefkowitz,&nbsp;Boris A. Portnov","doi":"10.1007/s10661-025-13871-4","DOIUrl":"10.1007/s10661-025-13871-4","url":null,"abstract":"<div><p>Most studies evaluating chronic ambient exposure to nitrogen dioxide (NO<sub>2</sub>) have used averages as the exclusive exposure metric. However, this approach may lead to an underestimation of potential health effects. The objective of this study is to evaluate the association between ambient exposure to NO<sub>2</sub> assessed by various metrics, and lung function in a cohort of healthy male youth. A cross-sectional analysis of 5,462 subjects was conducted using multivariate linear regression. Exposure to NO₂ was assessed by spatial interpolation using Empirical Bayesian Kriging (EBK). Five different exposure metrics were evaluated over two years, including average concentration, the number and intensity of exceedances of the 24-h NO<sub>2</sub> World Health Organization air quality guideline (AQG), and the number and intensity of 1-h NO<sub>2</sub> peaks. Lung function indices, including percent predicted forced expiratory volume in one second (FEV<sub>1</sub>), forced vital capacity (FVC), forced expiratory flow between 25% and 75% of vital capacity (FEF<sub>25-75</sub>), and FEV<sub>1</sub>/FVC ratio, were assessed. The intensity of the 24-h AQG exceedances was associated with the largest reductions in FEV<sub>1</sub> (-0.82%, 95% CI: -1.61%, -0.03%) and FVC (-1.03%, 95% CI: -1.86%, -0.20%), while FEF<sub>25-75</sub> showed a significant decline only with the 1-h peak intensity metric (-2.78%, 95% CI: -5.02%, -0.54%). The study results support integrating diverse exposure metrics as part of NO<sub>2</sub> chronic exposure assessment, as these metrics may capture a wider range of potential health effects that could be underestimated or overlooked when relying only on average concentrations.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10661-025-13871-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655202","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}
引用次数: 0
Periods of susceptibility for associations between phthalate exposure and preterm birth: Results from a pooled analysis of 16 US cohorts
IF 11.8 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Pub Date : 2025-03-20 DOI: 10.1016/j.envint.2025.109392
Alexa Friedman, Barrett M. Welch, Alexander P. Keil, Michael S. Bloom, Joseph M. Braun, Jessie P. Buckley, Dana Dabelea, Pam Factor-Litvak, John D. Meeker, Karin B. Michels, Vasantha Padmanabhan, Anne P. Starling, Clarice R. Weinberg, Jenny Aalborg, Akram N. Alshawabkeh, Emily S. Barrett, Alexandra M. Binder, Asa Bradman, Nicole R. Bush, Antonia M. Calafat, Kelly K. Ferguson

Background

Phthalate exposure during pregnancy has been associated with preterm birth, but mechanisms of action may depend on the timing of exposure.

Objective

Investigate critical periods of susceptibility during pregnancy for associations between urinary phthalate metabolite concentrations and preterm birth.

Methods

Individual-level data were pooled from 16 US cohorts (N = 6045, n = 539 preterm births). We examined trimester-averaged urinary phthalate metabolite concentrations. Most phthalate metabolites had 2248, 3703, and 3172 observations in the first, second, and third trimesters, respectively. Our primary analysis used logistic regression models with generalized estimating equations (GEE) under a multiple informant approach to estimate trimester-specific odds ratios (ORs) of preterm birth and significant (p < 0.20) heterogeneity in effect estimates by trimester. Adjusted models included interactions between each covariate and trimester.

Results

Differences in trimester-specific associations between phthalate metabolites and preterm birth were most evident for di-2-ethylhexyl phthalate (DEHP) metabolites. For example, an interquartile range increase in mono (2-ethylhexyl) phthalate (MEHP) during the first and second trimesters was associated with ORs of 1.15 (95 % confidence interval [CI]: 0.99, 1.33) and 1.11 (95 % CI: 0.97, 1.28) for preterm birth, respectively, but this association was null in the third trimester (OR = 0.91 [95 % CI: 0.76, 1.09]) (p-heterogeneity = 0.03).

Conclusion

The association of preterm birth with gestational biomarkers of DEHP exposure, but not other phthalate metabolites, differed by the timing of exposure. First and second trimester exposures demonstrated the greatest associations. Our study also highlights methodological considerations for critical periods of susceptibility analyses in pooled studies.
{"title":"Periods of susceptibility for associations between phthalate exposure and preterm birth: Results from a pooled analysis of 16 US cohorts","authors":"Alexa Friedman, Barrett M. Welch, Alexander P. Keil, Michael S. Bloom, Joseph M. Braun, Jessie P. Buckley, Dana Dabelea, Pam Factor-Litvak, John D. Meeker, Karin B. Michels, Vasantha Padmanabhan, Anne P. Starling, Clarice R. Weinberg, Jenny Aalborg, Akram N. Alshawabkeh, Emily S. Barrett, Alexandra M. Binder, Asa Bradman, Nicole R. Bush, Antonia M. Calafat, Kelly K. Ferguson","doi":"10.1016/j.envint.2025.109392","DOIUrl":"https://doi.org/10.1016/j.envint.2025.109392","url":null,"abstract":"<h3>Background</h3>Phthalate exposure during pregnancy has been associated with preterm birth, but mechanisms of action may depend on the timing of exposure.<h3>Objective</h3>Investigate critical periods of susceptibility during pregnancy for associations between urinary phthalate metabolite concentrations and preterm birth.<h3>Methods</h3>Individual-level data were pooled from 16 US cohorts (N = 6045, n = 539 preterm births). We examined trimester-averaged urinary phthalate metabolite concentrations. Most phthalate metabolites had 2248, 3703, and 3172 observations in the first, second, and third trimesters, respectively. Our primary analysis used logistic regression models with generalized estimating equations (GEE) under a multiple informant approach to estimate trimester-specific odds ratios (ORs) of preterm birth and significant (p &lt; 0.20) heterogeneity in effect estimates by trimester. Adjusted models included interactions between each covariate and trimester.<h3>Results</h3>Differences in trimester-specific associations between phthalate metabolites and preterm birth were most evident for di-2-ethylhexyl phthalate (DEHP) metabolites. For example, an interquartile range increase in mono (2-ethylhexyl) phthalate (MEHP) during the first and second trimesters was associated with ORs of 1.15 (95 % confidence interval [CI]: 0.99, 1.33) and 1.11 (95 % CI: 0.97, 1.28) for preterm birth, respectively, but this association was null in the third trimester (OR = 0.91 [95 % CI: 0.76, 1.09]) (p-heterogeneity = 0.03).<h3>Conclusion</h3>The association of preterm birth with gestational biomarkers of DEHP exposure, but not other phthalate metabolites, differed by the timing of exposure. First and second trimester exposures demonstrated the greatest associations. Our study also highlights methodological considerations for critical periods of susceptibility analyses in pooled studies.","PeriodicalId":308,"journal":{"name":"Environment International","volume":"37 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143660637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
引用次数: 0
Machine learning–based habitat mapping of the invasive Prosopis juliflora in Sharjah, UAE
IF 2.9 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Pub Date : 2025-03-20 DOI: 10.1007/s10661-025-13876-z
Alya Almaazmi, Rami Al-Ruzouq, Abdallah Shanableh, Ali El-Keblawy, Ratiranjan Jena, Mohamed Barakat A. Gibril, Nezar Atalla Hammouri, Manar Abu Talib

Prosopis juliflora, one of the most invasive trees, adversely affects the ecosystem and native plant communities in arid lands. This disrupts biodiversity and depletes water resources, posing significant ecological and economic challenges. Several attempts have been made to control this species in the United Arab Emirates (UAE) deserts but with little success. This study identifies and maps environmental variables influencing P. juliflora habitats using machine learning (ML); employs maximum entropy (MaxEnt) and statistical techniques to estimate its presence in Sharjah, UAE, home to one of its most intense populations; and conducts validation and sensitivity analysis. Eleven environmental variables representing geological, geomorphological, hydrological, eco-indicators, and climatological factors were selected to map the spread of the associated P. juliflora hazard. Variables were selected using collinearity and variance inflation factor (VIF) to eliminate bias, and ML techniques assigned weights based on overall accuracy (OA) and the Kappa coefficient before model implementation. Finally, a statistical comparison with MaxEnt was conducted to map P. juliflora habitats, classifying suitability as very high, high, low, and very low while estimating model accuracy. The results indicated that MaxEnt achieved a higher area under the curve (AUC 0.98) and more logical outcomes than statistical models (AUC 0.85) due to its superior handling of collinearity, complex environmental interactions, and capability of minimizing overfitting. The main findings show that the variable weights for MaxEnt and statistical models are primarily influenced by precipitation (27.0% and 18.18%), groundwater depth (14.9% and 26.8%), and total dissolved solids (TDS) (20.9% and 26.22%), respectively, indicating a shift in habitat distribution towards the eastern regions of the study area. Habitat mapping of P. juliflora is essential for local stakeholders and policymakers in decision-making regarding species conservation, sustainable land use, and climate adaptation. The findings conclude that ML offers a viable approach for habitat modeling of invasive species in similar arid regions worldwide.

{"title":"Machine learning–based habitat mapping of the invasive Prosopis juliflora in Sharjah, UAE","authors":"Alya Almaazmi,&nbsp;Rami Al-Ruzouq,&nbsp;Abdallah Shanableh,&nbsp;Ali El-Keblawy,&nbsp;Ratiranjan Jena,&nbsp;Mohamed Barakat A. Gibril,&nbsp;Nezar Atalla Hammouri,&nbsp;Manar Abu Talib","doi":"10.1007/s10661-025-13876-z","DOIUrl":"10.1007/s10661-025-13876-z","url":null,"abstract":"<div><p><i>Prosopis juliflora</i>, one of the most invasive trees, adversely affects the ecosystem and native plant communities in arid lands. This disrupts biodiversity and depletes water resources, posing significant ecological and economic challenges. Several attempts have been made to control this species in the United Arab Emirates (UAE) deserts but with little success. This study identifies and maps environmental variables influencing <i>P. juliflora</i> habitats using machine learning (ML); employs maximum entropy (MaxEnt) and statistical techniques to estimate its presence in Sharjah, UAE, home to one of its most intense populations; and conducts validation and sensitivity analysis. Eleven environmental variables representing geological, geomorphological, hydrological, eco-indicators, and climatological factors were selected to map the spread of the associated <i>P. juliflora</i> hazard. Variables were selected using collinearity and variance inflation factor (VIF) to eliminate bias, and ML techniques assigned weights based on overall accuracy (OA) and the Kappa coefficient before model implementation. Finally, a statistical comparison with MaxEnt was conducted to map <i>P. juliflora</i> habitats, classifying suitability as very high, high, low, and very low while estimating model accuracy. The results indicated that MaxEnt achieved a higher area under the curve (AUC 0.98) and more logical outcomes than statistical models (AUC 0.85) due to its superior handling of collinearity, complex environmental interactions, and capability of minimizing overfitting. The main findings show that the variable weights for MaxEnt and statistical models are primarily influenced by precipitation (27.0% and 18.18%), groundwater depth (14.9% and 26.8%), and total dissolved solids (TDS) (20.9% and 26.22%), respectively, indicating a shift in habitat distribution towards the eastern regions of the study area. Habitat mapping of <i>P. juliflora</i> is essential for local stakeholders and policymakers in decision-making regarding species conservation, sustainable land use, and climate adaptation. The findings conclude that ML offers a viable approach for habitat modeling of invasive species in similar arid regions worldwide.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655201","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}
引用次数: 0
The tolerance mechanism of diarrhetic shellfish toxins mediated by the extracellular regulated protein kinase (ERK) pathway in the mussel Perna viridis
IF 13.6 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Pub Date : 2025-03-20 DOI: 10.1016/j.jhazmat.2025.138006
Jin-jin Lv, Yu-jie Liu, Yan-hang Mo, Li-yan Deng, Yang Liu, Hong-ye Li, Li Zhang, Wei-dong Yang
Diarrheic shellfish toxins (DSTs) are a class of lipophilic algal toxins that accumulate excessively in bivalves following harmful algal blooms. Bivalves exhibit tolerance to DSTs, which make people ignore or underestimate the risk of DSTs, leading to the occurrence of seafood poisoning incidents. However, the tolerance mechanism remains unclear in bivalves. We investigated the role of extracellular-regulated protein kinase (ERK) in DSTs tolerance, observed that the ERK inhibitor PD98059 exacerbated damage of DSTs to the digestive tubules. PD98059 induced the TUNEL fluorescence intensity, and caspase-3 activity inhibited by DSTs were restored to the control. PD98059 enhanced the fluorescence intensity of extracellular Ca-AM and increased the accumulation of esterified DSTs. Transcriptome analysis revealed that PD98059 affected the genes expression related to apoptosis, ABC transporters, and lipid metabolism. qPCR analysis demonstrated that PD98059 down-regulated the DSTs-induced iap and ABCC10 (p = 0.063), and up-regulated ABCB1-like1, ABCC1, ABCC1-like1, and ABCC9. Molecular docking suggested that ABCC10 exhibited high affinity for esterified okadaic acid. Overall, ERK plays a crucial role in DSTs tolerance by regulating the anti-apoptotic system and ABC transporters in bivalves. Our study is of great significance to understand the tolerance mechanism in bivalves and the safety risk caused by DSTs.
{"title":"The tolerance mechanism of diarrhetic shellfish toxins mediated by the extracellular regulated protein kinase (ERK) pathway in the mussel Perna viridis","authors":"Jin-jin Lv, Yu-jie Liu, Yan-hang Mo, Li-yan Deng, Yang Liu, Hong-ye Li, Li Zhang, Wei-dong Yang","doi":"10.1016/j.jhazmat.2025.138006","DOIUrl":"https://doi.org/10.1016/j.jhazmat.2025.138006","url":null,"abstract":"Diarrheic shellfish toxins (DSTs) are a class of lipophilic algal toxins that accumulate excessively in bivalves following harmful algal blooms. Bivalves exhibit tolerance to DSTs, which make people ignore or underestimate the risk of DSTs, leading to the occurrence of seafood poisoning incidents. However, the tolerance mechanism remains unclear in bivalves. We investigated the role of extracellular-regulated protein kinase (ERK) in DSTs tolerance, observed that the ERK inhibitor PD98059 exacerbated damage of DSTs to the digestive tubules. PD98059 induced the TUNEL fluorescence intensity, and caspase-3 activity inhibited by DSTs were restored to the control. PD98059 enhanced the fluorescence intensity of extracellular Ca-AM and increased the accumulation of esterified DSTs. Transcriptome analysis revealed that PD98059 affected the genes expression related to apoptosis, ABC transporters, and lipid metabolism. qPCR analysis demonstrated that PD98059 down-regulated the DSTs-induced <em>iap</em> and <em>ABCC10</em> (<em>p</em> = 0.063), and up-regulated <em>ABCB1-like1</em>, <em>ABCC1</em>, <em>ABCC1-like1</em>, and <em>ABCC9</em>. Molecular docking suggested that ABCC10 exhibited high affinity for esterified okadaic acid. Overall, ERK plays a crucial role in DSTs tolerance by regulating the anti-apoptotic system and ABC transporters in bivalves. Our study is of great significance to understand the tolerance mechanism in bivalves and the safety risk caused by DSTs.","PeriodicalId":361,"journal":{"name":"Journal of Hazardous Materials","volume":"88 1","pages":""},"PeriodicalIF":13.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143660464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
引用次数: 0
期刊
全部 ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Conserv. Lett. Ecol. Lett. Front. Ecol. Environ. Funct. Ecol. Global Change Biol. Global Ecol. Biogeogr. J. Ecol. Methods Ecol. Evol. Aquat. Toxicol. Atmos. Environ. Chemosphere CURR OPIN ENV SUST ECOTOX ENVIRON SAFE Environ. Int. Environ. Model. Softw. Environ. Pollut. Environ. Res. Environ. Sci. Policy J. Cleaner Prod. J. Environ. Manage. J. Hazard. Mater. Sci. Total Environ. Water Res. Ambio B ENVIRON CONTAM TOX Chemoecology CURR POLLUT REP ENVIRON DEV SUSTAIN Environ. Chem. Lett. Environ. Earth Sci. ENVIRON MANAGE Environ. Monit. Assess. Environ. Sci. Pollut. Res. Environ. Sci. Eur. Int. J. Environ. Sci. Technol. J ENVIRON HEALTH SCI J. Mater. Cycles Waste Manage. REV ENVIRON SCI BIO Aerosol Air Qual. Res. Aerosol Sci. Technol. Adv. Water Resour. AEROBIOLOGIA Afr. J. Ecol. Afr. J. Aquat. Sci. ANN LIMNOL-INT J LIM APPL ECOL ENV RES Annu. Rev. Environ. Resour. Aquat. Microb. Ecol. AQUAT INVASIONS Aquat. Ecosyst. Health Manage. Arch. Environ. Occup. Health Aquat. Ecol. ARCH ENVIRON PROT Appl. Water Sci. ARCH ENVIRON CON TOX Atmos. Pollut. Res. Austral Ecol. Basic Appl. Ecol. Biochar Behav. Ecol. Biodivers. Conserv. BIOGEOCHEMISTRY Biorem. J. BIOTROPICA Biol. Invasions Bird Conserv. Int. Chem. Ecol. Clean-Soil Air Water Clean Technol. Environ. Policy Clim. Change Communications Earth & Environment COMP BIOCHEM PHYS C Conserv. Genet. Resour. Conserv. Biol. CRIT REV ENV SCI TEC ECOSYSTEMS Ecol. Processes Ecol. Res. Ecol. Indic. ECOLOGY Ecol. Eng. ECOL RESTOR ECOTOXICOLOGY Ecol. Monogr. Energy Ecol Environ ENG SANIT AMBIENT Energy Environ. Environ. Eng. Manage. J. ENVIRON HEALTH-GLOB ENVIRONMENT Environ. Prog. Sustainable Energy Environ. Eng. Res. Environ. Prot. Eng. Environ. Chem. Environ. Technol. Innovation Environ. Educ. Res, Environ. Res. Lett. Environ. Geochem. Health
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1