Pub Date : 2025-12-01DOI: 10.1016/j.envint.2025.109957
Yancong Wu , Quanxi Xu , Xuan Dai , Jiahui Nie , Yuhao Jia , Liuhui Wang , Yan Tao
Multifunctional reservoirs are critical environmental nexus points under constant threat from chemical contamination. In this study, the risks of neonicotinoid insecticides (NEOs) were investigated from a “One Health” perspective, linking agricultural pollution to human exposure via drinking water and fish consumption. Widespread contamination was confirmed across the water–sediment-fish system, with spatiotemporal dynamics mechanistically linked to compound-specific properties and seasonal agricultural inputs. Significant ecological risks were quantified (max ΣRQ = 18.77 in environmental media, max ΣRQ = 33.4 in fish), peaking in an agricultural tributary hotspot and wild catfish (Silurus glanis). A probabilistic human health risk assessment confirmed drinking water as the predominant exposure pathway, identifying children as the most vulnerable group. Crucially, advanced Piecewise SEM modeling delineated fundamentally divergent bioaccumulation drivers: accumulation in wild fish was governed by aqueous concentrations, whereas farmed fish exposure was dominated by Water Temperature and external, unmodeled inputs (commercial feed). This mechanistic divergence offers a refined, target-specific predictive tool for risk management. The findings provide a critical scientific basis for the implementation of season-specific monitoring and source regulation to protect both human health and vital ecosystem services.
{"title":"Bridging ecosystem and human health: distinct neonicotinoids accumulation drivers and human exposure pathways in a multifunctional reservoir","authors":"Yancong Wu , Quanxi Xu , Xuan Dai , Jiahui Nie , Yuhao Jia , Liuhui Wang , Yan Tao","doi":"10.1016/j.envint.2025.109957","DOIUrl":"10.1016/j.envint.2025.109957","url":null,"abstract":"<div><div>Multifunctional reservoirs are critical environmental nexus points under constant threat from chemical contamination. In this study, the risks of neonicotinoid insecticides (NEOs) were investigated from a “One Health” perspective, linking agricultural pollution to human exposure via drinking water and fish consumption. Widespread contamination was confirmed across the water–sediment-fish system, with spatiotemporal dynamics mechanistically linked to compound-specific properties and seasonal agricultural inputs. Significant ecological risks were quantified (max ΣRQ = 18.77 in environmental media, max ΣRQ = 33.4 in fish), peaking in an agricultural tributary hotspot and wild catfish (<em>Silurus glanis</em>). A probabilistic human health risk assessment confirmed drinking water as the predominant exposure pathway, identifying children as the most vulnerable group. Crucially, advanced Piecewise SEM modeling delineated fundamentally divergent bioaccumulation drivers: accumulation in wild fish was governed by aqueous concentrations, whereas farmed fish exposure was dominated by Water Temperature and external, unmodeled inputs (commercial feed). This mechanistic divergence offers a refined, target-specific predictive tool for risk management. The findings provide a critical scientific basis for the implementation of season-specific monitoring and source regulation to protect both human health and vital ecosystem services.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"206 ","pages":"Article 109957"},"PeriodicalIF":9.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567671","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}
Pub Date : 2025-12-01DOI: 10.1016/j.envint.2025.109959
Yanlin Li , Ting Zhang , Jinqian Ma , Rui Ma , Junxia Liu , Jian Xu , Sarah E. Rothenberg , Chong-Huai Yan , Jun Zhang , Zhong-Cheng Luo , Xiaobin Wang , Fengxiu Ouyang , for the Shanghai Birth Cohort
Background
Gestational diabetes mellitus (GDM) is a common metabolic complication during pregnancy which increase both maternal and fetal adverse outcomes. Selected heavy metal(loid)s may lead to insulin resistance and increase risk of GDM. We sought to investigate associations between maternal heavy metal(loid)s exposure, sea-fish consumption and GDM risk.
Methods
In 2174 women, including 686 with GDM, 48 with preexisting diabetes mellitus (PDM), and 1440 euglycemic pregnancies from the Shanghai Birth Cohort, we measured maternal whole blood concentrations of 13 metal(loid)s including mercury (Hg), arsenic, cadmium, lead, magnesium, calcium, manganese, iron, copper, zinc, selenium, rubidium, and strontium at early pregnancy. Logistic regressions were used to evaluate the associations of prenatal blood metal(loid)s with GDM and PDM, and linear regressions for plasma glucose (fasting, 1-hour, and 2-hour) during 75 g-oral glucose tolerance test (OGTT), with stratification by prenatal fish consumption and adjusting for pertinent covariates.
Results
Early pregnancy blood Hg concentrations were higher in women with GDM and PDM versus euglycemic (geometric mean was 1.88, and 2.18 versus 1.74 μg/L). Compared with the lowest quintile of Hg, the highest Hg quintile was associated with 1.66-fold higher odds of GDM (95 % CI: 1.17, 2.37, P < 0.01) and 7.10-fold higher odds (95 % CI: 1.82, 47.06, P < 0.05) of PDM. Consistently, blood Hg was also positively associated with higher plasma glucose at fasting, 1-hour, and 2-hour during OGTT. No significant associations were found between other measured metal(loid)s and GDM or PDM. The positive Hg-associations with GDM, PDM， and plasma glucoses were stronger among women with low fish intake (<1 time/week) and not statistically significant among higher sea-fish intake (interaction test P < 0.05).
Conclusions
In this prospective birth cohort, despite relatively low maternal Hg exposure, maternal Hg during early pregnancy was positively associated with increased risk of GDM and PDM, while higher sea-fish consumption showed counteracting effect.
背景妊娠期糖尿病（GDM）是妊娠期常见的代谢并发症，可增加母体和胎儿的不良结局。选择性重金属（样蛋白）可导致胰岛素抵抗，增加GDM的风险。我们试图调查母体重金属暴露、海鱼消费和GDM风险之间的关系。方法在2174名女性中，包括686名GDM患者，48名既往糖尿病（PDM）患者和1440名正常妊娠的上海出生队列中，我们测量了妊娠早期产妇全血中13种金属（样物质）的浓度，包括汞（Hg）、砷、镉、铅、镁、钙、锰、铁、铜、锌、硒、铷和锶。采用Logistic回归评估产前血金属（样蛋白）与GDM和PDM的关系，并在75 g-口服葡萄糖耐量试验（OGTT）期间对血浆葡萄糖（禁食、1小时和2小时）进行线性回归，并通过产前鱼类消费分层并调整相关协变量。结果妊娠早期GDM和PDM组血汞浓度高于正常血糖组（几何平均值分别为1.88和2.18 μg/L）。与汞含量最低的五分位数相比，汞含量最高的五分位数患GDM的几率高出1.66倍（95% CI: 1.17, 2.37, P < 0.01），患PDM的几率高出7.10倍（95% CI: 1.82, 47.06, P < 0.05）。与此一致的是，空腹、OGTT 1小时和2小时时血汞也与较高的血糖呈正相关。其他测量的金属（样蛋白）与GDM或PDM之间没有明显的关联。hg与GDM、PDM和血糖的正相关性在低鱼摄入量（1次/周）的女性中更强，而在高海鱼摄入量的女性中无统计学意义（交互作用检验P <； 0.05）。结论在本前瞻性出生队列中，尽管母体汞暴露相对较低，但妊娠早期母体汞与GDM和PDM的风险增加呈正相关，而较高的海鱼摄入量则具有抵消作用。
{"title":"Early pregnancy blood heavy metal(loid)s and low sea-fish consumption in relation to risk of gestational diabetes mellitus among Shanghai Birth cohort (SBC) women","authors":"Yanlin Li , Ting Zhang , Jinqian Ma , Rui Ma , Junxia Liu , Jian Xu , Sarah E. Rothenberg , Chong-Huai Yan , Jun Zhang , Zhong-Cheng Luo , Xiaobin Wang , Fengxiu Ouyang , for the Shanghai Birth Cohort","doi":"10.1016/j.envint.2025.109959","DOIUrl":"10.1016/j.envint.2025.109959","url":null,"abstract":"<div><h3>Background</h3><div>Gestational diabetes mellitus (GDM) is a common metabolic complication during pregnancy which increase both maternal and fetal adverse outcomes. Selected heavy metal(loid)s may lead to insulin resistance and increase risk of GDM. We sought to investigate associations between maternal heavy metal(loid)s exposure, sea-fish consumption and GDM risk.</div></div><div><h3>Methods</h3><div>In 2174 women, including 686 with GDM, 48 with preexisting diabetes mellitus (PDM), and 1440 euglycemic pregnancies from the Shanghai Birth Cohort, we measured maternal whole blood concentrations of 13 metal(loid)s including mercury (Hg), arsenic, cadmium, lead, magnesium, calcium, manganese, iron, copper, zinc, selenium, rubidium, and strontium at early pregnancy. Logistic regressions were used to evaluate the associations of prenatal blood metal(loid)s with GDM and PDM, and linear regressions for plasma glucose (fasting, 1-hour, and 2-hour) during 75 g-oral glucose tolerance test (OGTT), with stratification by prenatal fish consumption and adjusting for pertinent covariates.</div></div><div><h3>Results</h3><div>Early pregnancy blood Hg concentrations were higher in women with GDM and PDM versus euglycemic (geometric mean was 1.88, and 2.18 versus 1.74 μg/L). Compared with the lowest quintile of Hg, the highest Hg quintile was associated with 1.66-fold higher odds of GDM (95 % CI: 1.17, 2.37, P < 0.01) and 7.10-fold higher odds (95 % CI: 1.82, 47.06, P < 0.05) of PDM. Consistently, blood Hg was also positively associated with higher plasma glucose at fasting, 1-hour, and 2-hour during OGTT. No significant associations were found between other measured metal(loid)s and GDM or PDM. The positive Hg-associations with GDM, PDM， and plasma glucoses were stronger among women with low fish intake (<1 time/week) and not statistically significant among higher sea-fish intake (interaction test P < 0.05).</div></div><div><h3>Conclusions</h3><div>In this prospective birth cohort, despite relatively low maternal Hg exposure, maternal Hg during early pregnancy was positively associated with increased risk of GDM and PDM, while higher sea-fish consumption showed counteracting effect.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"206 ","pages":"Article 109959"},"PeriodicalIF":9.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145593320","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}
Pub Date : 2025-12-01DOI: 10.1016/j.envint.2025.109966
Jennifer L. Ish , Judy Y. Ou , Alison M. Rector-Houze , Nicole M. Niehoff , Jianzhao Bi , Joel D. Kaufman , Dale P. Sandler , Alexandra J. White
Background
Mounting evidence supports that air pollution is related to a higher breast cancer risk, yet the importance of exposure timing in this relationship remains unclear.
Methods
In the Sister Study, a United States-wide prospective cohort (n = 50,884, 2003–2009), we estimated time-varying annual concentrations of nitrogen dioxide (NO2) and fine particulate matter (PM2.5) from 1990 to 2017 at residential addresses using validated spatiotemporal models. Self-reported breast cancer diagnoses were validated using medical records. We used Cox proportional hazards regression to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) for breast cancer incidence in relation to air pollutant concentrations during predetermined windows of susceptibility. We also applied distributed lag non-linear models to estimate adjusted cumulative and lag-specific HRs and 95 % CIs for the association between air pollutants and breast cancer across a lag period of 0–15 years. We evaluated breast cancer overall and by estrogen receptor (ER) status and tumor extent [ductal carcinoma in situ (DCIS) versus invasive].
Results
We found limited evidence that air pollutant exposure during the time of a woman’s first birth, most recent birth, or menopause transition was associated with heightened risk for breast cancer. When examining exposure flexibly over the long-term, a 10-ppb increase in NO2 across lag years 1–11 significantly contributed to the risk of ER-positive (HRcumul = 1.14; 95 % CI: 1.03–1.27; n = 2619 cases) and DCIS (HRcumul = 1.27, 95 % CI: 1.04–1.54; n = 706 cases) breast cancer, whereas PM2.5 experienced during lag years 11–13 was associated with ER-negative breast cancer (e.g., HRLag12 = 1.36 per 10-µg/m3 increase, 95 % CI: 1.02–1.81; n = 448 cases).
Conclusions
We identified unique periods of susceptibility to NO2 and PM2.5 for breast cancer risk by ER status.
{"title":"Air pollution and breast cancer incidence in a United States-wide prospective cohort study: Examining sensitive periods of exposure","authors":"Jennifer L. Ish , Judy Y. Ou , Alison M. Rector-Houze , Nicole M. Niehoff , Jianzhao Bi , Joel D. Kaufman , Dale P. Sandler , Alexandra J. White","doi":"10.1016/j.envint.2025.109966","DOIUrl":"10.1016/j.envint.2025.109966","url":null,"abstract":"<div><h3>Background</h3><div>Mounting evidence supports that air pollution is related to a higher breast cancer risk, yet the importance of exposure timing in this relationship remains unclear.</div></div><div><h3>Methods</h3><div>In the Sister Study, a United States-wide prospective cohort (n = 50,884, 2003–2009), we estimated time-varying annual concentrations of nitrogen dioxide (NO<sub>2</sub>) and fine particulate matter (PM<sub>2.5</sub>) from 1990 to 2017 at residential addresses using validated spatiotemporal models. Self-reported breast cancer diagnoses were validated using medical records. We used Cox proportional hazards regression to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) for breast cancer incidence in relation to air pollutant concentrations during predetermined windows of susceptibility. We also applied distributed lag non-linear models to estimate adjusted cumulative and lag-specific HRs and 95 % CIs for the association between air pollutants and breast cancer across a lag period of 0–15 years. We evaluated breast cancer overall and by estrogen receptor (ER) status and tumor extent [ductal carcinoma <em>in situ</em> (DCIS) versus invasive].</div></div><div><h3>Results</h3><div>We found limited evidence that air pollutant exposure during the time of a woman’s first birth, most recent birth, or menopause transition was associated with heightened risk for breast cancer. When examining exposure flexibly over the long-term, a 10-ppb increase in NO<sub>2</sub> across lag years 1–11 significantly contributed to the risk of ER-positive (HR<sub>cumul</sub> = 1.14; 95 % CI: 1.03–1.27; n = 2619 cases) and DCIS (HR<sub>cumul</sub> = 1.27, 95 % CI: 1.04–1.54; n = 706 cases) breast cancer, whereas PM<sub>2.5</sub> experienced during lag years 11–13 was associated with ER-negative breast cancer (e.g., HR<sub>Lag12</sub> = 1.36 per 10-µg/m<sup>3</sup> increase, 95 % CI: 1.02–1.81; n = 448 cases).</div></div><div><h3>Conclusions</h3><div>We identified unique periods of susceptibility to NO<sub>2</sub> and PM<sub>2.5</sub> for breast cancer risk by ER status.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"206 ","pages":"Article 109966"},"PeriodicalIF":9.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145600224","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}
Pub Date : 2025-12-01DOI: 10.1016/j.envint.2025.109954
Shaorong Chen , Jie Xiong , Zijian Li
Amphibians are sensitive indicators of environmental contamination due to their permeable skin and dual aquatic–terrestrial life cycle. A physiologically based kinetic (PBK) model was developed to quantify the bioaccumulation of pesticides and per- and polyfluoroalkyl substances (PFAS) in amphibians, linking two chemical classes with contrasting environmental behaviors. The model integrates multiple exposure routes and connects aquatic and terrestrial phases within a unified framework. Simulations show that PFAS exhibit greater accumulation potential than herbicidal pesticides. Pesticide uptake occurs mainly via terrestrial ingestion and aquatic dermal absorption, while PFAS accumulation is dominated by aquatic dermal uptake. Pesticide residues are largely controlled by metabolic clearance, whereas PFAS retention depends on physicochemical partitioning, chain length, and protein-binding affinity. Short-chain PFAS penetrate skin readily but are rapidly cleared, whereas long-chain congeners persist in tissues. Model evaluation against empirical data showed good agreement for both chemical groups, with higher accuracy for pesticides. This PBK framework provides a route- and species-specific tool for predicting contaminant kinetics in amphibians and offers new insights into how biphasic ecology and chemical persistence shape bioaccumulation risk.
{"title":"Modeling pesticide and PFAS bioaccumulation in amphibians: integration of biphasic ecology and route specific uptake","authors":"Shaorong Chen , Jie Xiong , Zijian Li","doi":"10.1016/j.envint.2025.109954","DOIUrl":"10.1016/j.envint.2025.109954","url":null,"abstract":"<div><div>Amphibians are sensitive indicators of environmental contamination due to their permeable skin and dual aquatic–terrestrial life cycle. A physiologically based kinetic (PBK) model was developed to quantify the bioaccumulation of pesticides and per- and polyfluoroalkyl substances (PFAS) in amphibians, linking two chemical classes with contrasting environmental behaviors. The model integrates multiple exposure routes and connects aquatic and terrestrial phases within a unified framework. Simulations show that PFAS exhibit greater accumulation potential than herbicidal pesticides. Pesticide uptake occurs mainly via terrestrial ingestion and aquatic dermal absorption, while PFAS accumulation is dominated by aquatic dermal uptake. Pesticide residues are largely controlled by metabolic clearance, whereas PFAS retention depends on physicochemical partitioning, chain length, and protein-binding affinity. Short-chain PFAS penetrate skin readily but are rapidly cleared, whereas long-chain congeners persist in tissues. Model evaluation against empirical data showed good agreement for both chemical groups, with higher accuracy for pesticides. This PBK framework provides a route- and species-specific tool for predicting contaminant kinetics in amphibians and offers new insights into how biphasic ecology and chemical persistence shape bioaccumulation risk.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"206 ","pages":"Article 109954"},"PeriodicalIF":9.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567506","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}
Extreme heat ranks among the deadliest weather events globally. The number of heat-related deaths is expected to rise sharply as population ages and climate changes. In recent years, machine learning (ML) approaches have been increasingly used across a range of environmental and health fields, including heat-health studies. In this paper, we conducted a comprehensive literature review of the current ML applications for modelling the human health impacts of extreme heat. We searched for relevant scientific articles published in English in PubMed, Scopus and Web of Science databases from their inception to the search date of December 20, 2024. After screening titles, abstracts and full-texts, 25 papers were included in this review. We found that most of the studies were conducted in high-income countries such as Japan, Canada, South Korea or the United States. The studies primarily modelled a single health outcome, including all-cause mortality or heat-related illness, in the general population. The main predictors were maximum and mean air temperature, followed by relative humidity, and various temporal and socio-demographic variables. The most commonly used approach was Random Forest. Results were mixed regarding the optimal algorithm and the most important predictors. This review highlighted the strengths and limitations of current ML applications in heat-health studies. We propose recommendations to help guide the future development of these approaches to reduce the heat-related health burden globally. Future research should 1) study multiple health endpoints at the individual level in vulnerable populations, 2) leverage deep learning with spatiotemporal representations of environmental predictors, and 3) use data from multiple locations at a high spatial resolution to provide insights in data-scarce regions.
极端高温是全球最致命的天气事件之一。随着人口老龄化和气候变化，与高温相关的死亡人数预计将急剧上升。近年来，机器学习（ML）方法越来越多地应用于一系列环境和健康领域，包括热健康研究。在本文中，我们对当前ML应用于模拟极端高温对人类健康的影响进行了全面的文献综述。我们检索了PubMed、Scopus和Web of Science数据库中从建立到检索日期（2024年12月20日）的相关英文科学文章。经题目、摘要和全文筛选，共纳入25篇论文。我们发现，大多数研究都是在日本、加拿大、韩国或美国等高收入国家进行的。这些研究主要模拟了普通人群的单一健康结果，包括全因死亡率或与热有关的疾病。健康结果的主要预测因子是最高气温和平均气温，其次是相对湿度，以及各种时间和社会人口变量。最常用的方法是随机森林。关于最优算法和最重要的预测因子，结果是混合的。这篇综述强调了当前ML在热健康研究中的应用的优势和局限性。我们提出建议，以帮助指导这些方法的未来发展，以减少全球与热有关的健康负担。未来的研究应该1)在脆弱人群的个体水平上研究多个健康终点，2)利用深度学习与环境预测因子的时空表征，以及3)在高空间分辨率下使用来自多个地点的数据来提供数据稀缺地区的见解。
{"title":"Machine learning for modelling the health impacts of extreme heat: A comprehensive literature review","authors":"Jérémie Boudreault , Félix Lamothe , Céline Campagna , Fateh Chebana","doi":"10.1016/j.envint.2025.109965","DOIUrl":"10.1016/j.envint.2025.109965","url":null,"abstract":"<div><div>Extreme heat ranks among the deadliest weather events globally. The number of heat-related deaths is expected to rise sharply as population ages and climate changes. In recent years, machine learning (ML) approaches have been increasingly used across a range of environmental and health fields, including heat-health studies. In this paper, we conducted a comprehensive literature review of the current ML applications for modelling the human health impacts of extreme heat. We searched for relevant scientific articles published in English in PubMed, Scopus and Web of Science databases from their inception to the search date of December 20, 2024. After screening titles, abstracts and full-texts, 25 papers were included in this review. We found that most of the studies were conducted in high-income countries such as Japan, Canada, South Korea or the United States. The studies primarily modelled a single health outcome, including all-cause mortality or heat-related illness, in the general population. The main predictors were maximum and mean air temperature, followed by relative humidity, and various temporal and socio-demographic variables. The most commonly used approach was Random Forest. Results were mixed regarding the optimal algorithm and the most important predictors. This review highlighted the strengths and limitations of current ML applications in heat-health studies. We propose recommendations to help guide the future development of these approaches to reduce the heat-related health burden globally. Future research should 1) study multiple health endpoints at the individual level in vulnerable populations, 2) leverage deep learning with spatiotemporal representations of environmental predictors, and 3) use data from multiple locations at a high spatial resolution to provide insights in data-scarce regions.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"206 ","pages":"Article 109965"},"PeriodicalIF":9.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145593902","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}
Pub Date : 2025-11-29DOI: 10.1016/j.envint.2025.109967
Jeanette A. Stingone , Sofia Bengoa , Carolina Valle , James Masters , Tyrone Cadenhead , Alona Rabin , Paulo Pinheiro , Moira Bixby , Matthew Mazzella , Emily Spear , Henrique Santos , Chris Gennings , Deborah McGuinness , Patricia Kovatch , Nancy Mervish , Susan L. Teitelbaum
Implementation of the exposome paradigm is a critical aspect of the next generation of environmental health research studies. To spur exposomics research, the U.S.-based Human Health Exposure Analysis Resource (HHEAR) provided scientific investigators access to both laboratory and statistical analyses aimed at incorporating and expanding the breadth of biological markers of environmental exposures within their research. To extend the benefits of this program to the broader scientific community, the HHEAR Data Center established a public data repository to facilitate pooling and sharing of data generated by the HHEAR program. All HHEAR investigators deposited epidemiologic data on study participants, to accompany the biomarkers of exposure generated by the HHEAR laboratories. The latest semantic technologies are used to efficiently conduct data standardization across studies and promote data sharing by aligning the repository with the FAIR (Findable, Accessible, Interoperable, Reusable) data principles. This includes standardizing individual study data to a common ontology and representing data within a knowledge graph. A clear user interface enables search, construction, and download of customized datasets and maintenance of provenance through use of digital object identifiers. The repository will eventually contain information from 35,989 individuals across 55 environmental health studies, including data on biomarkers of environmental exposures, sociodemographics, health outcomes, and physical and mental assessments. All data are freely downloadable for reuse after a brief application for data access. Designed to support cutting-edge research and education, the HHEAR Data Repository provides a rich, harmonized resource of exposure biomarkers and corresponding health data from diverse study populations.
{"title":"The development of the Human Health Exposure Analysis Resource (HHEAR) Data Repository for environmental epidemiology research","authors":"Jeanette A. Stingone , Sofia Bengoa , Carolina Valle , James Masters , Tyrone Cadenhead , Alona Rabin , Paulo Pinheiro , Moira Bixby , Matthew Mazzella , Emily Spear , Henrique Santos , Chris Gennings , Deborah McGuinness , Patricia Kovatch , Nancy Mervish , Susan L. Teitelbaum","doi":"10.1016/j.envint.2025.109967","DOIUrl":"10.1016/j.envint.2025.109967","url":null,"abstract":"<div><div>Implementation of the exposome paradigm is a critical aspect of the next generation of environmental health research studies. To spur exposomics research, the U.S.-based Human Health Exposure Analysis Resource (HHEAR) provided scientific investigators access to both laboratory and statistical analyses aimed at incorporating and expanding the breadth of biological markers of environmental exposures within their research. To extend the benefits of this program to the broader scientific community, the HHEAR Data Center established a public data repository to facilitate pooling and sharing of data generated by the HHEAR program. All HHEAR investigators deposited epidemiologic data on study participants, to accompany the biomarkers of exposure generated by the HHEAR laboratories. The latest semantic technologies are used to efficiently conduct data standardization across studies and promote data sharing by aligning the repository with the FAIR (Findable, Accessible, Interoperable, Reusable) data principles. This includes standardizing individual study data to a common ontology and representing data within a knowledge graph. A clear user interface enables search, construction, and download of customized datasets and maintenance of provenance through use of digital object identifiers. The repository will eventually contain information from 35,989 individuals across 55 environmental health studies, including data on biomarkers of environmental exposures, sociodemographics, health outcomes, and physical and mental assessments. All data are freely downloadable for reuse after a brief application for data access. Designed to support cutting-edge research and education, the HHEAR Data Repository provides a rich, harmonized resource of exposure biomarkers and corresponding health data from diverse study populations.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 109967"},"PeriodicalIF":9.7,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145613744","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}
Pub Date : 2025-11-29DOI: 10.1016/j.envint.2025.109935
Kyle Morrison , Patrice Pottier , Pietro Pollo , Lorenzo Ricolfi , Coralie Williams , Yefeng Yang , Damien Beillouin , Simone Jaqueline Cardoso , Verónica Ferreira , Brian Gallagher , Jelaine L. Gan , Guang Hao , Mojtaba Keikha , Betina Kozlowsky-Suzuki , T.M. Kiran Kumara , Francesco Latterini , Alexandro B. Leverkus , Erin L. Macartney , Silvina Magdalena Manrique , April Robin Martinig , Shinichi Nakagawa
Meta-analysis is commonly a core component of systematic reviews and has become an important method to reconcile conflicting findings, increase statistical power, and chart new research directions. However, poor reporting practices make it challenging to evaluate the validity of meta-analyses. Despite the existence of reporting checklists, a specifically designed tool has yet to be developed to appraise the completeness with which a meta-analysis has been reported. To bridge this gap, we introduce the Meta-analysis Appraisal Tool for Environmental Sciences (MATES). To develop MATES, we adapted a Delphi process involving experts in meta-analysis methodologies, researchers with experience in guideline/appraisal tool development, and editors of relevant journals. The Delphi process had five steps, including three workshops (11–16 participants), a survey (193 participants), and a validation task (30 participants). This iterative development process resulted in a 14-item appraisal tool that reflects the environmental science and research syntheses community’s consensus on essential elements to appraise the completeness with which a meta-analysis has been reported. Validation across 50 meta-analyses demonstrated that the tool is repeatable (average agreement rate: 88.97 %) and time-efficient to implement (17.00 ± 12.23 min). We also outline guidance for interpreting MATES results, describe its potential applications, and reflect on the development process. The authors provide practical implementation guidance for each MATES item, illustrated with real examples in the supplementary material. We also report an extended development methodology to support reproducibility. Finally, we built created a ShinyApp that includes both a training module and an application tool to enhance the usability of MATES (https://kylemorrisonisshiny99.shinyapps.io/MATES_shiny/). Overall, MATES provides authors, readers, stakeholders, and editors with a reliable and accessible tool for appraising the completeness with which a meta-analysis in environmental sciences has been reported.
{"title":"MATES: A tool for appraising the completeness with which a meta-analysis has been reported","authors":"Kyle Morrison , Patrice Pottier , Pietro Pollo , Lorenzo Ricolfi , Coralie Williams , Yefeng Yang , Damien Beillouin , Simone Jaqueline Cardoso , Verónica Ferreira , Brian Gallagher , Jelaine L. Gan , Guang Hao , Mojtaba Keikha , Betina Kozlowsky-Suzuki , T.M. Kiran Kumara , Francesco Latterini , Alexandro B. Leverkus , Erin L. Macartney , Silvina Magdalena Manrique , April Robin Martinig , Shinichi Nakagawa","doi":"10.1016/j.envint.2025.109935","DOIUrl":"10.1016/j.envint.2025.109935","url":null,"abstract":"<div><div>Meta-analysis is commonly a core component of systematic reviews and has become an important method to reconcile conflicting findings, increase statistical power, and chart new research directions. However, poor reporting practices make it challenging to evaluate the validity of meta-analyses. Despite the existence of reporting checklists, a specifically designed tool has yet to be developed to appraise the completeness with which a meta-analysis has been reported. To bridge this gap, we introduce the Meta-analysis Appraisal Tool for Environmental Sciences (MATES). To develop MATES, we adapted a Delphi process involving experts in meta-analysis methodologies, researchers with experience in guideline/appraisal tool development, and editors of relevant journals. The Delphi process had five steps, including three workshops (11–16 participants), a survey (193 participants), and a validation task (30 participants). This iterative development process resulted in a 14-item appraisal tool that reflects the environmental science and research syntheses community’s consensus on essential elements to appraise the completeness with which a meta-analysis has been reported. Validation across 50 meta-analyses demonstrated that the tool is repeatable (average agreement rate: 88.97 %) and time-efficient to implement (17.00 ± 12.23 min). We also outline guidance for interpreting MATES results, describe its potential applications, and reflect on the development process. The authors provide practical implementation guidance for each MATES item, illustrated with real examples in the supplementary material. We also report an extended development methodology to support reproducibility. Finally, we built created a ShinyApp that includes both a training module and an application tool to enhance the usability of MATES (<span><span>https://kylemorrisonisshiny99.shinyapps.io/MATES_shiny/</span><svg><path></path></svg></span>). Overall, MATES provides authors, readers, stakeholders, and editors with a reliable and accessible tool for appraising the completeness with which a meta-analysis in environmental sciences has been reported.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 109935"},"PeriodicalIF":9.7,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145613676","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}
Pub Date : 2025-11-28DOI: 10.1016/j.envint.2025.109936
Ruoheng Ding , Yangxing Xie , Tian Xiao , Jingyuan Wang , Quan Chen , Yanyan Li , Junjie Qin , Huanxi Shen , Qian Bian
Microplastics (MPs) pollution has emerged as a critical environmental concern due to its ecological impacts and health hazards. Previous studies have confirmed the presence of MPs in various environmental media, including the atmosphere. However, research on airborne MPs contamination in occupational places, particularly in plastic manufacturing industry, remains limited. The objective of our research was to investigate and analyze the exposure characteristics of airborne MPs in the plastic manufacturing industry through pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS) and hyperspectral imaging (HSI) analysis. The analytical results revealed that the types of raw materials used in factory production were identified as the main components of airborne MPs, which predominantly existed as particulate matter, characterized by small sizes (<10 μm). In terms of concentration, the airborne MPs in the crushing workshop exhibited the highest (43.57 ± 39.85 μg/m3), followed by the injection molding workshop (19.37 ± 7.38 μg/m3), workshop office (9.96 ± 3.69 μg/m3), and outdoor residential area (8.00 ± 0.64 μg/m3). Crushing operators were identified as the high-exposure group in the traditional plastic processing industry. Their MPs 8-hour time-weighted average concentration (CTWA) was 61.16 μg/m3. It is estimated that male workers aged 18–44 in this crushing position could inhale approximately 117.03 mg/a MPs through occupational exposure. Taken together, occupational exposure is a significant source of MPs inhalation in humans, which is closely associated with production processes and raw materials. Our results provide valuable data for establishing occupational health standards, formulating preventive and control strategies and further studies on occupational health risks assessment of MPs.
{"title":"Airborne microplastics from plastic manufacturing industry: Concentrations and characterisation using Py-GC/MS and hyperspectral analysis","authors":"Ruoheng Ding , Yangxing Xie , Tian Xiao , Jingyuan Wang , Quan Chen , Yanyan Li , Junjie Qin , Huanxi Shen , Qian Bian","doi":"10.1016/j.envint.2025.109936","DOIUrl":"10.1016/j.envint.2025.109936","url":null,"abstract":"<div><div>Microplastics (MPs) pollution has emerged as a critical environmental concern due to its ecological impacts and health hazards. Previous studies have confirmed the presence of MPs in various environmental media, including the atmosphere. However, research on airborne MPs contamination in occupational places, particularly in plastic manufacturing industry, remains limited. The objective of our research was to investigate and analyze the exposure characteristics of airborne MPs in the plastic manufacturing industry through pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS) and hyperspectral imaging (HSI) analysis. The analytical results revealed that the types of raw materials used in factory production were identified as the main components of airborne MPs, which predominantly existed as particulate matter, characterized by small sizes (<10 μm). In terms of concentration, the airborne MPs in the crushing workshop exhibited the highest (43.57 ± 39.85 μg/m<sup>3</sup>), followed by the injection molding workshop (19.37 ± 7.38 μg/m<sup>3</sup>), workshop office (9.96 ± 3.69 μg/m<sup>3</sup>), and outdoor residential area (8.00 ± 0.64 μg/m<sup>3</sup>). Crushing operators were identified as the high-exposure group in the traditional plastic processing industry. Their MPs 8-hour time-weighted average concentration (<em>C</em><sub>TWA</sub>) was 61.16 μg/m<sup>3</sup>. It is estimated that male workers aged 18–44 in this crushing position could inhale approximately 117.03 mg/a MPs through occupational exposure. Taken together, occupational exposure is a significant source of MPs inhalation in humans, which is closely associated with production processes and raw materials. Our results provide valuable data for establishing occupational health standards, formulating preventive and control strategies and further studies on occupational health risks assessment of MPs.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 109936"},"PeriodicalIF":9.7,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145611527","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}
The oil and gas industry, coal mining, and coal-fired power plants, as well as geothermal energy plants, have been investigated in the past with respect to various aspects of naturally occurring radioactive materials (NORM). However, existing assessments are usually highly specific and often inconclusive due to differing perspectives, and an overview of NORM issues across these energy sectors is still missing.
The European data collected within the international RadoNorm project, and presented in this paper, have made it possible to identify common denominators related to the primordial source of radiation risk in these industrial sectors. Depending on the technological processes, radionuclides of natural origin (e.g., 226,228Ra, 228Th, 222Rn, 210Pb, 210Po, from 238U and 232Th decay chains) were found in a range of materials, such as scales, sludges, produced water, and liquid and gaseous discharges. Both radionuclides and materials may follow different pathways, leading to radiation exposure doses in various exposure scenarios for workers, the public, and the environment.
The novelty of this paper lies in the comparative qualitative and quantitative evaluation of radiation protection aspects across the entire sequence of energy generating processes, which includes the sourcing of raw materials, NORM generating processes, their fate and potential risks to humans and the environment, as well as a comparison of management, regulatory control, and existing challenges. The presented findings will support future international harmonization of decision-making processes during industrial operations, decommissioning activities or at legacy sites, which are often encountered in these energy generation sectors. Moreover, this information will be particularly valuable for countries worldwide that are still in the initial phase of NORM inventory characterization and/or legislation development.
{"title":"Naturally occurring radioactive materials (NORM) in energy production sectors: exposure, effective doses and regulatory challenges","authors":"Jelena Mrdakovic Popic , Nathalie Vanhoudt , Gennaro Venoso , Federica Leonardi , Hallvard Haanes , Alla Dvorzhak , Cristina Nuccetelli , Rosabianca Trevisi , Raffaella Ugolini , Flavio Trotti , Almudena Real , Danyl Pérez-Sánchez , Alicia Escribano , Joana Lourenco , Ruth Pereira , Laureline Fevrier , Boguslaw Michalik","doi":"10.1016/j.envint.2025.109958","DOIUrl":"10.1016/j.envint.2025.109958","url":null,"abstract":"<div><div>The oil and gas industry, coal mining, and coal-fired power plants, as well as geothermal energy plants, have been investigated in the past with respect to various aspects of naturally occurring radioactive materials (NORM). However, existing assessments are usually highly specific and often inconclusive due to differing perspectives, and an overview of NORM issues across these energy sectors is still missing.</div><div>The European data collected within the international RadoNorm project, and presented in this paper, have made it possible to identify common denominators related to the primordial source of radiation risk in these industrial sectors. Depending on the technological processes, radionuclides of natural origin (e.g.,<!--> <sup>226,228</sup>Ra, <sup>228</sup>Th,<!--> <sup>222</sup>Rn,<!--> <sup>210</sup>Pb,<!--> <sup>210</sup>Po, from <sup>238</sup>U and <sup>232</sup>Th decay chains) were found in a range of materials, such as scales, sludges, produced water, and liquid and gaseous discharges. Both radionuclides and materials may follow different pathways, leading to radiation exposure doses in various exposure scenarios for workers, the public, and the environment.</div><div>The novelty of this paper lies in the comparative qualitative and quantitative evaluation of radiation protection aspects across the entire sequence of energy generating processes, which includes the sourcing of raw materials, NORM generating processes, their fate and potential risks to humans and the environment, as well as a comparison of management, regulatory control, and existing challenges. The presented findings will support future international harmonization of decision-making processes during industrial operations, decommissioning activities or at legacy sites, which are often encountered in these energy generation sectors. Moreover, this information will be particularly valuable for countries worldwide that are still in the initial phase of NORM inventory characterization and/or legislation development.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 109958"},"PeriodicalIF":9.7,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145593313","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}
Pub Date : 2025-11-24DOI: 10.1016/j.envint.2025.109964
Rajat Gupta , Candace Chang , David H. Gonzalez , Priyansha Srivastava , Collin Le , Daniel P. Stefanko , Jocelyn A. Castellanos , Mohamad Navab , Srinivasa T. Reddy , Gregory A. Fishbein , Constantinos Sioutas , Jonathan P. Jacobs , Tzung Hsiai , Jesus A. Araujo
Air pollution exposure is associated with increased cardiovascular morbidity and mortality worldwide. Previous studies provide a causal relationship between exposure to particulate matter (PM) and atherosclerosis development. We have previously demonstrated increased aortic atherosclerosis and adverse metabolic effects in hyperlipidemic mice exposed to ambient ultrafine PM. However, the underlying mechanisms by which ambient PM promotes systemic effects leading to worsened atherosclerosis remain unknown. We have recently shown that the gut microbiota composition was altered in mice exposed to re-aerosolized PM in the ultrafine-size range for 10 weeks. We hypothesized that sub-chronic exposure to ultrafine PM induces gut dysbiosis in association with systemic prooxidative effects and atherosclerotic lesion development. Male apolipoprotein E knockout (ApoE-/-) mice were fed a chow diet and exposed to re-aerosolized PM, highly enriched in particles in the ultrafine-size range (ultrafine PM) vs. filtered air (FA) by inhalation (6 h/day, 3 days/week for 10 weeks). Ultrafine PM-exposed mice exhibited marked differences in the gut microbiota composition, which significantly associated with worsened atherosclerotic lesions in the innominate artery and aorta. Ultrafine PM-exposed mice also displayed significantly elevated levels of short chain fatty acids (SCFAs) in the feces, malondialdehyde (MDA) content in the liver and upregulation of hepatic antioxidant and endoplasmic reticulum (ER) stress response genes, all of which correlated with changes in the gut microbiota composition. In conclusion, inhaled PM in the ultrafine-size range induced changes in the gut microbiota composition and its metabolites, which correlated with systemic prooxidative effects, hepatic ER stress and worsened atherosclerosis.
{"title":"Ultrafine particulate matter exposure induces gut microbiota dysbiosis together with ER stress in the liver and worsened atherosclerosis","authors":"Rajat Gupta , Candace Chang , David H. Gonzalez , Priyansha Srivastava , Collin Le , Daniel P. Stefanko , Jocelyn A. Castellanos , Mohamad Navab , Srinivasa T. Reddy , Gregory A. Fishbein , Constantinos Sioutas , Jonathan P. Jacobs , Tzung Hsiai , Jesus A. Araujo","doi":"10.1016/j.envint.2025.109964","DOIUrl":"10.1016/j.envint.2025.109964","url":null,"abstract":"<div><div>Air pollution exposure is associated with increased cardiovascular morbidity and mortality worldwide. Previous studies provide a causal relationship between exposure to particulate matter (PM) and atherosclerosis development. We have previously demonstrated increased aortic atherosclerosis and adverse metabolic effects in hyperlipidemic mice exposed to ambient ultrafine PM. However, the underlying mechanisms by which ambient PM promotes systemic effects leading to worsened atherosclerosis remain unknown. We have recently shown that the gut microbiota composition was altered in mice exposed to re-aerosolized PM in the ultrafine-size range for 10 weeks. We hypothesized that sub-chronic exposure to ultrafine PM induces gut dysbiosis in association with systemic prooxidative effects and atherosclerotic lesion development. Male apolipoprotein E knockout (ApoE<sup>-/-</sup>) mice were fed a chow diet and exposed to re-aerosolized PM, highly enriched in particles in the ultrafine-size range (ultrafine PM) <em>vs.</em> filtered air (FA) by inhalation (6 h/day, 3 days/week for 10 weeks). Ultrafine PM-exposed mice exhibited marked differences in the gut microbiota composition, which significantly associated with worsened atherosclerotic lesions in the innominate artery and aorta. Ultrafine PM-exposed mice also displayed significantly elevated levels of short chain fatty acids (SCFAs) in the feces, malondialdehyde (MDA) content in the liver and upregulation of hepatic antioxidant and endoplasmic reticulum (ER) stress response genes, all of which correlated with changes in the gut microbiota composition. In conclusion, inhaled PM in the ultrafine-size range induced changes in the gut microbiota composition and its metabolites, which correlated with systemic prooxidative effects, hepatic ER stress and worsened atherosclerosis.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 109964"},"PeriodicalIF":9.7,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145593390","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}
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