Pub Date : 2026-01-19DOI: 10.1016/j.envint.2026.110086
Jianshuo Qian , Yanyu Li , Jinnan Chen , Junhao Huang , Liuyong Ding , Dekui He
Effective aquatic biomonitoring requires understanding how flow conditions influence the efficiency of environmental DNA (eDNA) sampling, particularly where conventional filtration is slow or impractical. Passive eDNA samplers (PEDS), which accumulate DNA on submerged substrates, offer a low-effort alternative, yet their performance across flow conditions remains poorly quantified. Guided by a flow–adsorption framework, we combined controlled flume experiments with field comparisons to test how flow affects passive eDNA capture. In flumes, glass fiber (GF) membranes accumulated eDNA rapidly and surpassed a 2 L filtration benchmark within 30 min at high velocity, as measured by droplet digital PCR. In field deployments across 21 lentic and lotic sites, metabarcoding showed that GF achieved the highest amplicon sequence variant (ASV) richness, outperforming filtration in running waters and equalling it in still waters. Together, these findings indicate that water movement enhances passive adsorption and that short immersions can suffice in swift rivers, whereas longer soaks are needed in lakes. GF-based PEDS are therefore a robust, low-effort, and scalable approach for standardized aquatic biodiversity monitoring, particularly in lotic systems.
{"title":"Flow conditions govern the efficiency of passive environmental DNA sampling","authors":"Jianshuo Qian , Yanyu Li , Jinnan Chen , Junhao Huang , Liuyong Ding , Dekui He","doi":"10.1016/j.envint.2026.110086","DOIUrl":"10.1016/j.envint.2026.110086","url":null,"abstract":"<div><div>Effective aquatic biomonitoring requires understanding how flow conditions influence the efficiency of environmental DNA (eDNA) sampling, particularly where conventional filtration is slow or impractical. Passive eDNA samplers (PEDS), which accumulate DNA on submerged substrates, offer a low-effort alternative, yet their performance across flow conditions remains poorly quantified. Guided by a flow–adsorption framework, we combined controlled flume experiments with field comparisons to test how flow affects passive eDNA capture. In flumes, glass fiber (GF) membranes accumulated eDNA rapidly and surpassed a 2 L filtration benchmark within 30 min at high velocity, as measured by droplet digital PCR. In field deployments across 21 lentic and lotic sites, metabarcoding showed that GF achieved the highest amplicon sequence variant (ASV) richness, outperforming filtration in running waters and equalling it in still waters. Together, these findings indicate that water movement enhances passive adsorption and that short immersions can suffice in swift rivers, whereas longer soaks are needed in lakes. GF-based PEDS are therefore a robust, low-effort, and scalable approach for standardized aquatic biodiversity monitoring, particularly in lotic systems.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110086"},"PeriodicalIF":9.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146001222","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 : 2026-01-19DOI: 10.1016/j.envint.2026.110077
Kehao Liu , Xuehui Hu , Mingcong Yang , Tao Chen, Qi Huang, Ying Xie, He Zhang, Yuzhou Li, Sheng Yang
Environmental pollutants are increasingly linked to sleep disorders (SD), affecting 27% of people globally, yet their synergistic effects remain understudied. Network toxicology identified 252 shared targets between sleep-related environmental pollutants (SREPs: NO2, formaldehyde, benzene) and SD. PPI network and diagnostic model identified four hub genes (HSP90AA1, RELA, PTGS2, MMP9) with moderate-to-high predictive value (AUC: 0.708–0.979). Immune infiltration analysis showing elevated T cells and reduced astrocytes and neurons in patients with SD. Molecular simulations confirmed stable SREP-hub protein binding, with benzene exhibiting the highest affinity. Crucially, mixed SREPs exposure induced more severe toxicity than individual pollutants, demonstrating true synergistic disruption. In vivo, SREPs metabolites disrupted sleep architecture, impaired the blood–brain barrier (BBB), and induced neurobehavioral deficits. In vitro studies using brain endothelial cells (BMVECs) revealed that SREPs directly increase permeability, suppress tight junctions, and activate a pro-inflammatory cascade involving NF-κB signaling, enhanced MMP9 activity, and prostaglandin E2 synthesis. Curcumin intervention effectively counteracted these effects, restoring BBB integrity, normalizing sleep patterns, and suppressing hub gene expression and neuroinflammation in vivo and in vitro by targeting the identified hub gene network. Our integrated computational-experimental strategy establishes a novel “pollutant-BBB-neuroimmune-sleep” axis, providing a mechanistic framework for assessing cumulative environmental risks and advancing targeted interventions.
{"title":"Synergistic disruption of blood-brain barrier and neuroimmune homeostasis by sleep-related environmental pollutants drives sleep disorders: an integrated computational and experimental study","authors":"Kehao Liu , Xuehui Hu , Mingcong Yang , Tao Chen, Qi Huang, Ying Xie, He Zhang, Yuzhou Li, Sheng Yang","doi":"10.1016/j.envint.2026.110077","DOIUrl":"10.1016/j.envint.2026.110077","url":null,"abstract":"<div><div>Environmental pollutants are increasingly linked to sleep disorders (SD), affecting 27% of people globally, yet their synergistic effects remain understudied. Network toxicology identified 252 shared targets between sleep-related environmental pollutants (SREPs: NO<sub>2</sub>, formaldehyde, benzene) and SD. PPI network and diagnostic model identified four hub genes (<em>HSP90AA1</em>, <em>RELA</em>, <em>PTGS2</em>, <em>MMP9</em>) with moderate-to-high predictive value (AUC: 0.708–0.979). Immune infiltration analysis showing elevated T cells and reduced astrocytes and neurons in patients with SD. Molecular simulations confirmed stable SREP-hub protein binding, with benzene exhibiting the highest affinity. Crucially, mixed SREPs exposure induced more severe toxicity than individual pollutants, demonstrating true synergistic disruption. <em>In vivo</em>, SREPs metabolites disrupted sleep architecture, impaired the blood–brain barrier (BBB), and induced neurobehavioral deficits. <em>In vitro</em> studies using brain endothelial cells (BMVECs) revealed that SREPs directly increase permeability, suppress tight junctions, and activate a pro-inflammatory cascade involving NF-κB signaling, enhanced MMP9 activity, and prostaglandin E2 synthesis. Curcumin intervention effectively counteracted these effects, restoring BBB integrity, normalizing sleep patterns, and suppressing hub gene expression and neuroinflammation in vivo and <em>in vitro</em> by targeting the identified hub gene network. Our integrated computational-experimental strategy establishes a novel “pollutant-BBB-neuroimmune-sleep” axis, providing a mechanistic framework for assessing cumulative environmental risks and advancing targeted interventions.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110077"},"PeriodicalIF":9.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146001228","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 : 2026-01-18DOI: 10.1016/j.envint.2026.110084
Xiaoliu Shi , Lingbing Jin , Xiaochun Ma , Qianyi Shen , Jiafan Feng , Ying Liu , Yixiang Wang , Quan Zhang , Cui Wang
As hepatic steatosis driven by environmental exposures increasingly contributes to the global burden of metabolic disease, identifying and prioritizing high-potency steatogenic chemicals is critical for enabling risk-oriented toxicological and environmental regulation. Leveraging the well-established adverse outcome pathway framework for hepatic steatosis, we integrated ToxPi scores derived from 14 molecular initiating events in the ToxCast™ database with in vivo validation in zebrafish. This integrated approach enabled the construction of a training set comprising chemicals with distinct steatogenic potency. Feature selection via Kruskal-Wallis test identified 11 key bioassays, with OT_FXR_FXRSRC1_0480 and NVS_NR_hGR contributing most to model performance. Using leave-one-out cross-validation, the SVM model achieved 91.7% accuracy in the training set. External validation on 35 compounds, although based on binary activity labels, resulted in 77.1% accuracy, indicating moderate but promising generalizability. Final predictions on 345 curated ToxCast™ chemicals (from a total of 9924) were categorized as high- (37.97%), moderate- (18.84%), and null-effect (43.19%) on steatogenic potence by Random Walk with Restart algorithm. In vivo validation of 14 predicted compounds confirmed the model’s robustness, and in vitro lipid staining assays in HepG2 cells further demonstrated concordance. This study revealed that several emerging contaminants, including isodecyl diphenyl phosphate, 3,3′-dimethylbisphenol A, tetrabutyltin, tetrabromobisphenol A bis(2-hydroxyethyl) ether, trixylyl phosphate and quinoxyfen, exert high steatogenic potency. These findings underscore the utility of integrating high-throughput data with predictive modeling and experimental validation to prioritize high-potent steatogenic chemicals.
{"title":"Prioritizing steatogenic chemicals through integration ToxCast™ data, machine learning, and experimental validation","authors":"Xiaoliu Shi , Lingbing Jin , Xiaochun Ma , Qianyi Shen , Jiafan Feng , Ying Liu , Yixiang Wang , Quan Zhang , Cui Wang","doi":"10.1016/j.envint.2026.110084","DOIUrl":"10.1016/j.envint.2026.110084","url":null,"abstract":"<div><div>As hepatic steatosis driven by environmental exposures increasingly contributes to the global burden of metabolic disease, identifying and prioritizing high-potency steatogenic chemicals is critical for enabling risk-oriented toxicological and environmental regulation. Leveraging the well-established adverse outcome pathway framework for hepatic steatosis, we integrated ToxPi scores derived from 14 molecular initiating events in the ToxCast™ database with in vivo validation in zebrafish. This integrated approach enabled the construction of a training set comprising chemicals with distinct steatogenic potency. Feature selection via Kruskal-Wallis test identified 11 key bioassays, with OT_FXR_FXRSRC1_0480 and NVS_NR_hGR contributing most to model performance. Using leave-one-out cross-validation, the SVM model achieved 91.7% accuracy in the training set. External validation on 35 compounds, although based on binary activity labels, resulted in 77.1% accuracy, indicating moderate but promising generalizability. Final predictions on 345 curated ToxCast™ chemicals (from a total of 9924) were categorized as high- (37.97%), moderate- (18.84%), and null-effect (43.19%) on steatogenic potence by Random Walk with Restart algorithm. In vivo validation of 14 predicted compounds confirmed the model’s robustness, and in vitro lipid staining assays in HepG2 cells further demonstrated concordance. This study revealed that several emerging contaminants, including isodecyl diphenyl phosphate, 3,3′-dimethylbisphenol A, tetrabutyltin, tetrabromobisphenol A bis(2-hydroxyethyl) ether, trixylyl phosphate and quinoxyfen, exert high steatogenic potency. These findings underscore the utility of integrating high-throughput data with predictive modeling and experimental validation to prioritize high-potent steatogenic chemicals.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110084"},"PeriodicalIF":9.7,"publicationDate":"2026-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145995909","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 : 2026-01-18DOI: 10.1016/j.envint.2026.110082
Christine G. Parks , Qian Xiao , Jesse Wilkerson , Jonathan N. Hofmann , Laura E. Beane Freeman , Dale P. Sandler
Background
Growing evidence suggests pesticides may increase risk of type 2 diabetes, but data are limited on many specific chemicals.
Methods
In 29,527 private pesticide applicators in the Agricultural Health Study cohort (enrolled 1993–1997 in Iowa and North Carolina), 3,847 incident diabetes cases were identified by self-report during follow-up surveys in 1999–2003, 2005–2010, 2013–2015, and 2019–2021. We examined 50 pesticides reported at enrollment, updated in 1999–2003 or 2005–2010, prior to diabetes diagnosis or end of follow-up, using log-binomial regression to calculate relative risks (RR) and 95% confidence intervals (CI) for ever-use and intensity-weighted lifetime days (IWLD) use (tertiles, T1-3), adjusting for covariates and correlated pesticides.
Findings
Greater diabetes risk was associated with 7 organochlorine insecticides: ever-use of DDT, aldrin, dieldrin, chlordane, heptachlor, and toxaphene (RRs 1.08–1.31), without monotonic exposure–response trends, and lower IWLD of lindane use (T1RR=1.32; 95%CI 1.12–1.57). Risk was associated with 5 organophosphate or carbamate insecticides: ever-use of diazinon and carbofuran, and exposure–response trends for malathion (T3RR=1.13;95%CI 1.02–1.25, p-trend=0.025), phorate (T3RR=1.22;95%CI 1.08–1.39, p-trend=0.001), and carbaryl (T3RR=1.26;95%CI 1.11–1.43, p-trend=0.005). Risk was associated with 2 phenoxy herbicides, 2,4,5-T (ever-use RR=1.25;95%CI 1.14–1.37) and 2,4,5-TP (T1RR=1.35;95%CI 1.04–1.76), and 3 other herbicides [butylate (T3RR=1.26;95%CI 1.10–1.44, p-trend<0.001), metribuzin (T3RR=1.16;95%CI 1.16–1.32, p-trend=0.022), chlorimuron ethyl (T3RR=1.16;95%CI 1.02–1.31, p-trend=0.033)], and the fumigant carbon tetrachloride/disulfide (RR=1.16;95%CI 1.02–1.33). Associations were not confounded by BMI and weight gain.
Conclusions
These results show greater diabetes risk associated with use of persistent organochlorine insecticides and banned phenoxy herbicides. Novel findings for widely used insecticides and other pesticides warrant further investigation.
{"title":"Pesticides associated with incident diabetes among licensed private pesticide applicators in the Agricultural Health Study cohort (1993–2021)","authors":"Christine G. Parks , Qian Xiao , Jesse Wilkerson , Jonathan N. Hofmann , Laura E. Beane Freeman , Dale P. Sandler","doi":"10.1016/j.envint.2026.110082","DOIUrl":"10.1016/j.envint.2026.110082","url":null,"abstract":"<div><h3>Background</h3><div>Growing evidence suggests pesticides may increase risk of type 2 diabetes, but data are limited on many specific chemicals.</div></div><div><h3>Methods</h3><div>In 29,527 private pesticide applicators in the Agricultural Health Study cohort (enrolled 1993–1997 in Iowa and North Carolina), 3,847 incident diabetes cases were identified by self-report during follow-up surveys in 1999–2003, 2005–2010, 2013–2015, and 2019–2021. We examined 50 pesticides reported at enrollment, updated in 1999–2003 or 2005–2010, prior to diabetes diagnosis or end of follow-up, using log-binomial regression to calculate relative risks (RR) and 95% confidence intervals (CI) for ever-use and intensity-weighted lifetime days (IWLD) use (tertiles, T1-3), adjusting for covariates and correlated pesticides.</div></div><div><h3>Findings</h3><div>Greater diabetes risk was associated with 7 organochlorine insecticides: ever-use of DDT, aldrin, dieldrin, chlordane, heptachlor, and toxaphene (RRs 1.08–1.31), without monotonic exposure–response trends, and lower IWLD of lindane use (<sub>T1</sub>RR=1.32; 95%CI 1.12–1.57). Risk was associated with 5 organophosphate or carbamate insecticides: ever-use of diazinon and carbofuran, and exposure–response trends for malathion (<sub>T3</sub>RR=1.13;95%CI 1.02–1.25, p-trend=0.025), phorate (<sub>T3</sub>RR=1.22;95%CI 1.08–1.39, p-trend=0.001), and carbaryl (<sub>T3</sub>RR=1.26;95%CI 1.11–1.43, p-trend=0.005). Risk was associated with 2 phenoxy herbicides, 2,4,5-T (ever-use RR=1.25;95%CI 1.14–1.37) and 2,4,5-TP (<sub>T1</sub>RR=1.35;95%CI 1.04–1.76), and 3 other herbicides [butylate (<sub>T3</sub>RR=1.26;95%CI 1.10–1.44, p-trend<0.001), metribuzin (<sub>T3</sub>RR=1.16;95%CI 1.16–1.32, p-trend=0.022), chlorimuron ethyl (<sub>T3</sub>RR=1.16;95%CI 1.02–1.31, p-trend=0.033)], and the fumigant carbon tetrachloride/disulfide (RR=1.16;95%CI 1.02–1.33). Associations were not confounded by BMI and weight gain.</div></div><div><h3>Conclusions</h3><div>These results show greater diabetes risk associated with use of persistent organochlorine insecticides and banned phenoxy herbicides. Novel findings for widely used insecticides and other pesticides warrant further investigation.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110082"},"PeriodicalIF":9.7,"publicationDate":"2026-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145995827","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 : 2026-01-18DOI: 10.1016/j.envint.2026.110078
Annetrude Boeije, S. Henrik Barmentlo, Martina G. Vijver, Laura Scherer
Current approaches for estimating the effects of chemical exposure commonly rely on species sensitivity distributions, which are well-established in ecotoxicological assessments for chemical registration and authorisation. However, this method does not consider the functional roles of species within ecosystems, an aspect captured by functional diversity. In this paper, we present a method to estimate the toxic effects of chemicals on functional diversity, with an emphasis on functional richness. Our approach integrates ecotoxicity data with abundance and trait data to determine the potentially affected fraction of functional diversity across chemical concentrations. For this purpose, we fitted a functional sensitivity distribution, similar to a species sensitivity distribution, and derived the concentration–response slope factor for a given species group and chemical. We demonstrate our method using the terrestrial plant order Poales (including grasses such as wheat) and the aquatic fish order Cypriniformes (ray-finned fish such as carp). Our results show increasing negative effects on both functional and species richness with increasing chemical concentrations. Notably, a toxic effect on species richness did not always lead to an effect on functional richness, highlighting the added value of considering functional traits. A key challenge of this method is the limited availability of trait and ecotoxicity data for many species and chemicals. Nevertheless, as data availability improves, integrating functional sensitivity distributions into chemical risk assessment offers a promising tool for evaluating chemical-induced ecological effects, supporting authorisation and registration decisions, and triggering risk management measures for chemicals already on the market.
{"title":"Ecotoxicity effects on functional diversity – A proof of concept using a sensitivity distribution approach","authors":"Annetrude Boeije, S. Henrik Barmentlo, Martina G. Vijver, Laura Scherer","doi":"10.1016/j.envint.2026.110078","DOIUrl":"10.1016/j.envint.2026.110078","url":null,"abstract":"<div><div>Current approaches for estimating the effects of chemical exposure commonly rely on species sensitivity distributions, which are well-established in ecotoxicological assessments for chemical registration and authorisation. However, this method does not consider the functional roles of species within ecosystems, an aspect captured by functional diversity. In this paper, we present a method to estimate the toxic effects of chemicals on functional diversity, with an emphasis on functional richness. Our approach integrates ecotoxicity data with abundance and trait data to determine the potentially affected fraction of functional diversity across chemical concentrations. For this purpose, we fitted a functional sensitivity distribution, similar to a species sensitivity distribution, and derived the concentration–response slope factor for a given species group and chemical. We demonstrate our method using the terrestrial plant order Poales (including grasses such as wheat) and the aquatic fish order Cypriniformes (ray-finned fish such as carp). Our results show increasing negative effects on both functional and species richness with increasing chemical concentrations. Notably, a toxic effect on species richness did not always lead to an effect on functional richness, highlighting the added value of considering functional traits. A key challenge of this method is the limited availability of trait and ecotoxicity data for many species and chemicals. Nevertheless, as data availability improves, integrating functional sensitivity distributions into chemical risk assessment offers a promising tool for evaluating chemical-induced ecological effects, supporting authorisation and registration decisions, and triggering risk management measures for chemicals already on the market.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110078"},"PeriodicalIF":9.7,"publicationDate":"2026-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145995907","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 : 2026-01-17DOI: 10.1016/j.envint.2026.110073
Qiuting Yang , Lili Yang , Jianghui Yun , Yuxiang Sun , Lingna Zheng , Meng Wang , Haiying Yu , Junhao Tang , Yujue Yang , Guorui Liu
Rare Earth Elements (REEs) are toxic and pose environmental and exposure hazards. Limited research has analyzed REE mass concentrations during some industrial emissions currently. Nonetheless, the toxicity of REEs-containing nanoparticles (NPs) is predominantly governed by particle size and particle number concentrations (PNCs), surpassing the influence of mere mass concentration. Knowledge pertaining to the emissions of REE-containing NPs and their PNCs is lacking. In this study, REE-containing NP emissions from 132 industrial PM samples, spanning 13 categories of industrial sectors, were quantified. Ce and La were the most abundant elements across these 13 industrial sources. Among the 13 sources investigated, coal-fired power plants (CFPP) consistently exhibited the highest PNCs in most cases. CFPP had the highest particulate number concentrations of Ce-containing NPs, with a mean value of 1.9 × 1010 particles/g. In terms of atmospheric Ce- and La-containing NPs, CFPP, cement kiln co-processing of solid waste (CK), coking production, and blast furnace pig iron steelmaking were significant industrial emitters both in China and globally. Emissions from the 13 industrial sources significantly increased the atmospheric steady-state concentrations of both La- and Ce-containing NPs, with La rising by approximately 105 particles/m3 and Ce by 106 particles/m3, respectively. Consequently, the lifetime average daily dose (LADD) of La- and Ce-containing NPs for adults, via inhalation and dermal exposure, is calculated to be 2.0 × 105 particles/(day·kg) and 8.1 × 105 particles/(day·kg), respectively. These findings highlight the importance of assessing REE-containing NP emissions and advancing sustainable global industrial development.
{"title":"Atmosphere profiles and spatial distributions of rare earth element-containing nanoparticles released from multiple industries in China","authors":"Qiuting Yang , Lili Yang , Jianghui Yun , Yuxiang Sun , Lingna Zheng , Meng Wang , Haiying Yu , Junhao Tang , Yujue Yang , Guorui Liu","doi":"10.1016/j.envint.2026.110073","DOIUrl":"10.1016/j.envint.2026.110073","url":null,"abstract":"<div><div>Rare Earth Elements (REEs) are toxic and pose environmental and exposure hazards. Limited research has analyzed REE mass concentrations during some industrial emissions currently. Nonetheless, the toxicity of REEs-containing nanoparticles (NPs) is predominantly governed by particle size and particle number concentrations (PNCs), surpassing the influence of mere mass concentration. Knowledge pertaining to the emissions of REE-containing NPs and their PNCs is lacking. In this study, REE-containing NP emissions from 132 industrial PM samples, spanning 13 categories of industrial sectors, were quantified. Ce and La were the most abundant elements across these 13 industrial sources. Among the 13 sources investigated, coal-fired power plants (CFPP) consistently exhibited the highest PNCs in most cases. CFPP had the highest particulate number concentrations of Ce-containing NPs, with a mean value of 1.9 × 10<sup>10</sup> particles/g. In terms of atmospheric Ce- and La-containing NPs, CFPP, cement kiln co-processing of solid waste (CK), coking production, and blast furnace pig iron steelmaking were significant industrial emitters both in China and globally. Emissions from the 13 industrial sources significantly increased the atmospheric steady-state concentrations of both La- and Ce-containing NPs, with La rising by approximately 10<sup>5</sup> particles/m<sup>3</sup> and Ce by 10<sup>6</sup> particles/m3, respectively. Consequently, the lifetime average daily dose (LADD) of La- and Ce-containing NPs for adults, via inhalation and dermal exposure, is calculated to be 2.0 × 10<sup>5</sup> particles/(day·kg) and 8.1 × 10<sup>5</sup> particles/(day·kg), respectively. These findings highlight the importance of assessing REE-containing NP emissions and advancing sustainable global industrial development.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110073"},"PeriodicalIF":9.7,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145993130","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 : 2026-01-16DOI: 10.1016/j.envint.2026.110067
Xuan Chen , Gerard Hoek , Paul Frijters , Georgia M.C. Dyer , Stefan Gössling , Sasha Khomenko , Haneen Khreis , Eline Kolb , Natalie Mueller , Brigit Staatsen , Rafael Costa Simões De Vasconcelos , Daniel Saldanha Resendes , Elise van Kempen , Mathew P. White , Roel Vermeulen , Mark Nieuwenhuijsen , Ulrike Gehring
Introduction
Environmental Health Impact Assessments (HIAs) can inform decisions about the health effects of policy-related changes in environmental exposures. Conventional health impact metrics, focusing on mortality, morbidity, and disability, neglect subjective well-being. We explored the need and feasibility of integrating well-being indicators such as happiness and life satisfaction into quantitative environmental HIAs.
Methods
Building on a multidisciplinary expert workshop and existing literature, we addressed (1) definitions and indicators of well-being, (2) pathways linking environmental exposures (air pollution, noise, extreme temperatures, and green space) to well-being, and (3) the strength of epidemiological evidence for these associations. We evaluated the challenges of integrating well-being indicators into environmental HIAs, and provided an exploratory example.
Results
We argue that including well-being in HIAs offers a more comprehensive view of health, aligning with policy goals focused on enhancing citizen’s well-being. The literature identifies plausible pathways linking exposures to well-being, whilst epidemiological evidence for associations between environmental exposures and well-being is limited, but suggestive. We propose conducting exploratory HIAs integrating well-being, especially for green space (n = 16 epidemiological studies) and air pollution (n = 18). We outline two practical integration strategies: (1) report well-being impacts separately as Well-being-Adjusted Life Years, and (2) incorporate well-being into existing health indicators such as Quality-Adjusted Life Years or Disability-Adjusted Life Years.
Conclusions
Inclusion of well-being into quantitative environmental HIAs presents a more comprehensive representation of health and well-being beyond indicators focusing on morbidity and mortality. However, the epidemiological evidence base regarding environmental exposures and well-being warrants further expansion.
{"title":"Toward integrating subjective well-being in environmental health impact assessments for healthy urban living: a conceptual and methodological exploration","authors":"Xuan Chen , Gerard Hoek , Paul Frijters , Georgia M.C. Dyer , Stefan Gössling , Sasha Khomenko , Haneen Khreis , Eline Kolb , Natalie Mueller , Brigit Staatsen , Rafael Costa Simões De Vasconcelos , Daniel Saldanha Resendes , Elise van Kempen , Mathew P. White , Roel Vermeulen , Mark Nieuwenhuijsen , Ulrike Gehring","doi":"10.1016/j.envint.2026.110067","DOIUrl":"10.1016/j.envint.2026.110067","url":null,"abstract":"<div><h3>Introduction</h3><div>Environmental Health Impact Assessments (HIAs) can inform decisions about the health effects of policy-related changes in environmental exposures. Conventional health impact metrics, focusing on mortality, morbidity, and disability, neglect subjective well-being. We explored the need and feasibility of integrating well-being indicators such as happiness and life satisfaction into quantitative environmental HIAs.</div></div><div><h3>Methods</h3><div>Building on a multidisciplinary expert workshop and existing literature, we addressed (1) definitions and indicators of well-being, (2) pathways linking environmental exposures (air pollution, noise, extreme temperatures, and green space) to well-being, and (3) the strength of epidemiological evidence for these associations. We evaluated the challenges of integrating well-being indicators into environmental HIAs, and provided an exploratory example.</div></div><div><h3>Results</h3><div>We argue that including well-being in HIAs offers a more comprehensive view of health, aligning with policy goals focused on enhancing citizen’s well-being. The literature identifies plausible pathways linking exposures to well-being, whilst epidemiological evidence for associations between environmental exposures and well-being is limited, but suggestive. We propose conducting exploratory HIAs integrating well-being, especially for green space (n = 16 epidemiological studies) and air pollution (n = 18). We outline two practical integration strategies: (1) report well-being impacts separately as Well-being-Adjusted Life Years, and (2) incorporate well-being into existing health indicators such as Quality-Adjusted Life Years or Disability-Adjusted Life Years.</div></div><div><h3>Conclusions</h3><div>Inclusion of well-being into quantitative environmental HIAs presents a more comprehensive representation of health and well-being beyond indicators focusing on morbidity and mortality. However, the epidemiological evidence base regarding environmental exposures and well-being warrants further expansion.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110067"},"PeriodicalIF":9.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145995541","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 : 2026-01-16DOI: 10.1016/j.envint.2026.110079
Melissa Fiffer , Mercedes A. Bravo , Dominique Zephyr , Joshua L. Tootoo , Charlotte Roscoe , Grete Wilt , Rafiga Gasymova , Peter James , Marie Lynn Miranda
Introduction
Studies show that prenatal neighborhood greenness is positively associated with birthweight. However, few go beyond a pregnancy-long greenness average or consider air pollution co-exposures. We used time-varying greenness and air pollution estimates to explore sensitive windows and subpopulations.
Methods
We examined Michigan (U.S.) birth records between 2007 and 2016 (n = 798,071). We derived the Normalized Difference Vegetation Index (NDVI) from Landsat images (30 m2 resolution) to estimate greenness within 270 m and 1230 m radial buffers around each mother’s address, to represent greenness immediately surrounding addresses and within a short walk, respectively, in the three seasons before birth. We joined estimated weekly 1 km2 gridded PM2.5, NO2, and O3 concentrations, and fit distributed lag models to assess trimester-specific greenness, weekly air pollution, and birthweight, adjusting for temperature, seasonality, maternal factors, and gestational age. We examined whether the NDVI-birthweight association varied by socioeconomic status, and whether the air pollution-birthweight association varied by NDVI tertile.
Results
In adjusted models, an IQR (0.2 unit) increase in NDVI within a 270 m buffer was associated with a 12.3 g (95% CI: 9.7 g, 15.0 g) higher birthweight. Positive associations were observed in all trimesters, and across all maternal education and neighborhood median household income levels. PM2.5-birthweight associations (IQR = 5 μg/m3) were largest in the lowest NDVI tertile (PM2.5: −21.3 g, 95% CI: −31.1 g, −11.5 g).
Conclusions
Birthweight is positively associated with residential greenness in all trimesters after co-adjusting for air pollutants. Addresses surrounded by the least greenness had the strongest inverse PM2.5-birthweight association. Nature-based solutions may attenuate air pollution’s negative impacts.
{"title":"Prenatal greenness, air pollution, and birthweight: Assessing sensitive windows of exposure and sub-populations in a multi-exposure setting","authors":"Melissa Fiffer , Mercedes A. Bravo , Dominique Zephyr , Joshua L. Tootoo , Charlotte Roscoe , Grete Wilt , Rafiga Gasymova , Peter James , Marie Lynn Miranda","doi":"10.1016/j.envint.2026.110079","DOIUrl":"10.1016/j.envint.2026.110079","url":null,"abstract":"<div><h3>Introduction</h3><div>Studies show that prenatal neighborhood greenness is positively associated with birthweight. However, few go beyond a pregnancy-long greenness average or consider air pollution co-exposures. We used time-varying greenness and air pollution estimates to explore sensitive windows and subpopulations.</div></div><div><h3>Methods</h3><div>We examined Michigan (U.S.) birth records between 2007 and 2016 (n = 798,071). We derived the Normalized Difference Vegetation Index (NDVI) from Landsat images (30 m<sup>2</sup> resolution) to estimate greenness within 270 m and 1230 m radial buffers around each mother’s address, to represent greenness immediately surrounding addresses and within a short walk, respectively, in the three seasons before birth. We joined estimated weekly 1 km<sup>2</sup> gridded PM<sub>2.5</sub>, NO<sub>2</sub>, and O<sub>3</sub> concentrations, and fit distributed lag models to assess trimester-specific greenness, weekly air pollution, and birthweight, adjusting for temperature, seasonality, maternal factors, and gestational age. We examined whether the NDVI-birthweight association varied by socioeconomic status, and whether the air pollution-birthweight association varied by NDVI tertile.</div></div><div><h3>Results</h3><div>In adjusted models, an IQR (0.2 unit) increase in NDVI within a 270 m buffer was associated with a 12.3 g (95% CI: 9.7 g, 15.0 g) higher birthweight. Positive associations were observed in all trimesters, and across all maternal education and neighborhood median household income levels. PM<sub>2.5</sub>-birthweight associations (IQR = 5 μg/m<sup>3</sup>) were largest in the lowest NDVI tertile (PM<sub>2.5</sub>: −21.3 g, 95% CI: −31.1 g, −11.5 g).</div></div><div><h3>Conclusions</h3><div>Birthweight is positively associated with residential greenness in all trimesters after co-adjusting for air pollutants. Addresses surrounded by the least greenness had the strongest inverse PM<sub>2.5</sub>-birthweight association. Nature-based solutions may attenuate air pollution’s negative impacts.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110079"},"PeriodicalIF":9.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145995534","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 : 2026-01-16DOI: 10.1016/j.envint.2026.110070
Benjamin Sachse , Sebastian Schmeisser , Jan van Benthem , Raffaella Corvi , Eugenia Dogliotti , Norman Ertych , Roland Frötschl , Ulrike Gündel , Kristin Herrmann , George Johnson , Carsten Kneuer , Jeannette König , Hans-Jörg Martus , Stefan Pfuhler , Stephanie Smith-Roe , Helga Stopper , Paul White , Tanja Schwerdtle , Andreas Hensel , Tewes Tralau
Genotoxicity plays an important role in chemical safety assessment, as genetic alterations can lead to severe and irreversible health consequences. To date, the assessment of genotoxicity has mostly been limited to hazard identification, followed by rigorous risk mitigation measures if a substance is found to be mutagenic, regardless of potency, the underlying mechanism, and cellular biology. While this regulatory hazard-based approach is straightforward, it is unsatisfactory when exposure to genotoxic substances cannot be completely avoided and/or regulatory measures lead to misperceptions of risk and undesirable socioeconomic side effects. The latter becomes particularly obvious in light of natural genotoxicants, e.g. occurring in plant-based food, and for substances that are difficult to replace but come with a high socioeconomic value but little potency and exposure. Hence, there is an increasing demand for a paradigm shift towards a quantitative interpretation of genotoxicity data in regulatory risk assessment. However, moving away from the traditional hazard-based assessment and doing so safely requires a collective effort of all relevant stakeholders. To this end, the German Federal Institute for Risk Assessment (BfR) organised an international symposium, at which experts from regulatory authorities, academia and industry discussed the opportunities and challenges involved. Here, we present key issues to be considered for a successful implementation of quantitative approaches. In situations where exposure to genotoxic substances cannot be completely avoided, e.g. occurrence of contaminants, quantitative approaches offer the opportunity to better characterise the associated risks and thus enable risk managers to make more informed decisions.
{"title":"Quantitative evaluation of genotoxicity data for risk assessment and regulatory decision-making: Time for a paradigm shift","authors":"Benjamin Sachse , Sebastian Schmeisser , Jan van Benthem , Raffaella Corvi , Eugenia Dogliotti , Norman Ertych , Roland Frötschl , Ulrike Gündel , Kristin Herrmann , George Johnson , Carsten Kneuer , Jeannette König , Hans-Jörg Martus , Stefan Pfuhler , Stephanie Smith-Roe , Helga Stopper , Paul White , Tanja Schwerdtle , Andreas Hensel , Tewes Tralau","doi":"10.1016/j.envint.2026.110070","DOIUrl":"10.1016/j.envint.2026.110070","url":null,"abstract":"<div><div>Genotoxicity plays an important role in chemical safety assessment, as genetic alterations can lead to severe and irreversible health consequences. To date, the assessment of genotoxicity has mostly been limited to hazard identification, followed by rigorous risk mitigation measures if a substance is found to be mutagenic, regardless of potency, the underlying mechanism, and cellular biology. While this regulatory hazard-based approach is straightforward, it is unsatisfactory when exposure to genotoxic substances cannot be completely avoided and/or regulatory measures lead to misperceptions of risk and undesirable socioeconomic side effects. The latter becomes particularly obvious in light of natural genotoxicants, <em>e.g.</em> occurring in plant-based food, and for substances that are difficult to replace but come with a high socioeconomic value but little potency and exposure. Hence, there is an increasing demand for a paradigm shift towards a quantitative interpretation of genotoxicity data in regulatory risk assessment. However, moving away from the traditional hazard-based assessment and doing so safely requires a collective effort of all relevant stakeholders. To this end, the German Federal Institute for Risk Assessment (BfR) organised an international symposium, at which experts from regulatory authorities, academia and industry discussed the opportunities and challenges involved. Here, we present key issues to be considered for a successful implementation of quantitative approaches. In situations where exposure to genotoxic substances cannot be completely avoided, <em>e.g.</em> occurrence of contaminants, quantitative approaches offer the opportunity to better characterise the associated risks and thus enable risk managers to make more informed decisions.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110070"},"PeriodicalIF":9.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145993405","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 : 2026-01-16DOI: 10.1016/j.envint.2026.110071
Kara L. Fry, Xiaochi Liu, Maryam Moslehi, John Leeder, Mark Patrick Taylor, Jennifer Martin, Antti T. Mikkonen
{"title":"Chemicals in homes and gardens: understanding sources, exposure and risk","authors":"Kara L. Fry, Xiaochi Liu, Maryam Moslehi, John Leeder, Mark Patrick Taylor, Jennifer Martin, Antti T. Mikkonen","doi":"10.1016/j.envint.2026.110071","DOIUrl":"https://doi.org/10.1016/j.envint.2026.110071","url":null,"abstract":"","PeriodicalId":308,"journal":{"name":"Environment International","volume":"40 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145995535","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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