Pub Date : 2026-01-10DOI: 10.1016/j.envint.2026.110061
Lei Zhang , Liang Xu , Yongfeng Sun , Jianguo Liu
Spatial localization and distribution of leaked gases are critical for environmental monitoring and emergency management. Infrared remote sensing is widely used for gas leak detection because of its unique advantages. However, a single infrared remote sensing system only measures the two-dimensional projection of gas concentration. Most methods for spatial localization and distribution reconstruction of gas plumes require data from multiple instruments or multi-angle measurements, which increases deployment costs and complicates reconstruction processes in practice. Additionally, the resolution of infrared remote sensing instruments and computer storage capacity limit the achievable spatial resolution of gas plume reconstructions. To address these challenges, this paper proposes a deep learning-based generative network for three-dimensional gas plume reconstruction. The network employs an octree representation to model the sparse three-dimensional distribution of gas plumes. It generates outputs from coarse to fine scales while requiring minimal computational and memory resources. The network takes measurements from a single remote sensing system and predicts a finer octree structure of the gas plume. Field experiments demonstrate that this method can determine the spatial location and distribution of leaked gas plumes, providing effective support for air pollution control efforts.
{"title":"Spatial location and distribution reconstruction of the leaking gas plume via a single infrared remote sensing system","authors":"Lei Zhang , Liang Xu , Yongfeng Sun , Jianguo Liu","doi":"10.1016/j.envint.2026.110061","DOIUrl":"10.1016/j.envint.2026.110061","url":null,"abstract":"<div><div>Spatial localization and distribution of leaked gases are critical for environmental monitoring and emergency management. Infrared remote sensing is widely used for gas leak detection because of its unique advantages. However, a single infrared remote sensing system only measures the two-dimensional projection of gas concentration. Most methods for spatial localization and distribution reconstruction of gas plumes require data from multiple instruments or multi-angle measurements, which increases deployment costs and complicates reconstruction processes in practice. Additionally, the resolution of infrared remote sensing instruments and computer storage capacity limit the achievable spatial resolution of gas plume reconstructions. To address these challenges, this paper proposes a deep learning-based generative network for three-dimensional gas plume reconstruction. The network employs an octree representation to model the sparse three-dimensional distribution of gas plumes. It generates outputs from coarse to fine scales while requiring minimal computational and memory resources. The network takes measurements from a single remote sensing system and predicts a finer octree structure of the gas plume. Field experiments demonstrate that this method can determine the spatial location and distribution of leaked gas plumes, providing effective support for air pollution control efforts.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110061"},"PeriodicalIF":9.7,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956873","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 : 2026-01-09DOI: 10.1016/j.envint.2026.110057
Paula Scharlach , Gustaf Boström , Jörg Klasmeier , Amelie Leonardi , Andreas Focks
Plant protection products are integral to European agriculture but can cause unwanted environmental impacts. Before authorisation, predicted concentrations in environmental compartments are compared with effect thresholds in a regulatory risk assessment. This study evaluates the agreement between predicted and measured concentrations for the established FOCUS surface water models (Steps 1–3) and the recently published PEC-CKB model. Model results were compared with monitoring data from lowland streams in Germany, and particular attention was paid to the models’ conservatism. The conservative character of FOCUS Step 1 can be confirmed, but underestimations were observed for FOCUS Step 2 and 3 models. PEC-CKB results are similar to those of the higher-tier FOCUS models, while having lower model complexity and requiring less input data. Using real application rates and landscape information generally improved model predictions by nearly halving the bias, but led to increased underestimations of measured concentrations. Linking prospective and retrospective environmental risk assessment (ERA) by incorporating real data can make prospective ERA more realistic and identify opportunities for simplification. Finally, we discuss the challenges in evaluating prediction models for pesticide concentrations in surface waters, particularly with regard to the environmental variability of measured concentrations.
{"title":"Confronting pesticide exposure predictions from different models to observations from a monitoring study in small freshwater streams in Germany","authors":"Paula Scharlach , Gustaf Boström , Jörg Klasmeier , Amelie Leonardi , Andreas Focks","doi":"10.1016/j.envint.2026.110057","DOIUrl":"10.1016/j.envint.2026.110057","url":null,"abstract":"<div><div>Plant protection products are integral to European agriculture but can cause unwanted environmental impacts. Before authorisation, predicted concentrations in environmental compartments are compared with effect thresholds in a regulatory risk assessment. This study evaluates the agreement between predicted and measured concentrations for the established FOCUS surface water models (Steps 1–3) and the recently published PEC-CKB model. Model results were compared with monitoring data from lowland streams in Germany, and particular attention was paid to the models’ conservatism. The conservative character of FOCUS Step 1 can be confirmed, but underestimations were observed for FOCUS Step 2 and 3 models. PEC-CKB results are similar to those of the higher-tier FOCUS models, while having lower model complexity and requiring less input data. Using real application rates and landscape information generally improved model predictions by nearly halving the bias, but led to increased underestimations of measured concentrations. Linking prospective and retrospective environmental risk assessment (ERA) by incorporating real data can make prospective ERA more realistic and identify opportunities for simplification. Finally, we discuss the challenges in evaluating prediction models for pesticide concentrations in surface waters, particularly with regard to the environmental variability of measured concentrations.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110057"},"PeriodicalIF":9.7,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976158","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 : 2026-01-09DOI: 10.1016/j.envint.2026.110052
Guoqi Yu , Xi Meng , Yue Qian Tan , Shuman Li , Xin Yin , Wei Wei Pang , Claire Guivarch , Jiaxi Yang , Michelle A. Williams , Cuilin Zhang
<div><h3>Background</h3><div>Small vulnerable newborns (SVNs), defined as babies affected by preterm birth (PTB), small for gestational age (SGA), or low birth weight (LBW), face a substantially increased risk of chronic diseases over their lifespan and premature mortality. Gestational exposure to heavy metals may play a role in the aetiology of SVNs. Although previous limited systematic reviews have examined individual metal(loid)s and single SVN outcomes, their findings remain inconclusive. Given the recent surge in studies, the use of diverse biospecimens, and the narrow scope of prior search strategies, our study aims to addresses these gaps by comprehensively synthesizing evidence across multiple metal(loid)s, SVN outcomes, and biospecimen types, providing a more complete and up-to-date assessment.</div></div><div><h3>Methods</h3><div>We conducted a comprehensive search in three databases—PubMed, Web of Science, and Embase—for relevant articles published before 9th December 2025, investigating the associations between gestational exposure to metal(loid)s and outcomes of SVNs. Observational studies, including prospective and retrospective cohort studies, case–control studies, and cross-sectional studies, were included. Data were extracted from studies that assessed toxicologically relevant metal burdens using biomonitoring measurements. Meta-analysis was conducted and pooled odds ratios (ORs) and confidence intervals (CIs) were calculated using both fixed-effect and random-effects models, with further analyses stratified by biospecimen types. Two-stage dose–response analyses were performed. Publication bias and heterogeneity were assessed. The protocol was registered with PROSPERO, CRD42024571198.</div></div><div><h3>Findings</h3><div>Of the 43,695 publications identified and 102 studies with a total of 325,705 live births involving 20 heavy metals and either of SVNs outcomes met the inclusion criteria for final <em>meta</em>-analysis. Barium (Ba, n = 4541), Higher maternal Cadmium (Cd, n = 31,651), Mercury (Hg, n = 18,962), and lead (Pb, n = 92,082) exposure, defined based on study-specific exposure contrasts, were significantly related to increased risk of PTB, with pooled ORs (95% CIs) of 1.12 (1.01, 1.24) for Ba, 1.23 (1.10, 1.38) for Cd, 1.05 (1.01, 1.08) for Hg, and 1.27 (1.09, 1.48) for Pb. Additionally, higher Cd and Hg were significantly associated with an increased risk of LBW, with ORs of 1.12 (1.06, 1.18) and 1.09 (1.04, 1.14), respectively. Higher As, Cd and Pb were also significantly associated with increased risk of SGA, with corresponding ORs (95% CIs) of 1.04 (1.01, 1.07), 1.12 (1.07, 1.16), and 1.19 (1.12, 1.27), respectively. The significant associations between metal exposures and increased risk of SVNs persisted or became more pronounced with specific biospecimen types. Particularly, elevated blood Arsenic (As), Cd, Molybdenum (Mo), Pb and urinary Cd, Cobalt (Co), chromium (Cr), copper (Cu), Hg, and Nickel (Ni) were assoc
{"title":"Gestational exposure to metals and small vulnerable newborns: a systematic review and meta-analysis","authors":"Guoqi Yu , Xi Meng , Yue Qian Tan , Shuman Li , Xin Yin , Wei Wei Pang , Claire Guivarch , Jiaxi Yang , Michelle A. Williams , Cuilin Zhang","doi":"10.1016/j.envint.2026.110052","DOIUrl":"10.1016/j.envint.2026.110052","url":null,"abstract":"<div><h3>Background</h3><div>Small vulnerable newborns (SVNs), defined as babies affected by preterm birth (PTB), small for gestational age (SGA), or low birth weight (LBW), face a substantially increased risk of chronic diseases over their lifespan and premature mortality. Gestational exposure to heavy metals may play a role in the aetiology of SVNs. Although previous limited systematic reviews have examined individual metal(loid)s and single SVN outcomes, their findings remain inconclusive. Given the recent surge in studies, the use of diverse biospecimens, and the narrow scope of prior search strategies, our study aims to addresses these gaps by comprehensively synthesizing evidence across multiple metal(loid)s, SVN outcomes, and biospecimen types, providing a more complete and up-to-date assessment.</div></div><div><h3>Methods</h3><div>We conducted a comprehensive search in three databases—PubMed, Web of Science, and Embase—for relevant articles published before 9th December 2025, investigating the associations between gestational exposure to metal(loid)s and outcomes of SVNs. Observational studies, including prospective and retrospective cohort studies, case–control studies, and cross-sectional studies, were included. Data were extracted from studies that assessed toxicologically relevant metal burdens using biomonitoring measurements. Meta-analysis was conducted and pooled odds ratios (ORs) and confidence intervals (CIs) were calculated using both fixed-effect and random-effects models, with further analyses stratified by biospecimen types. Two-stage dose–response analyses were performed. Publication bias and heterogeneity were assessed. The protocol was registered with PROSPERO, CRD42024571198.</div></div><div><h3>Findings</h3><div>Of the 43,695 publications identified and 102 studies with a total of 325,705 live births involving 20 heavy metals and either of SVNs outcomes met the inclusion criteria for final <em>meta</em>-analysis. Barium (Ba, n = 4541), Higher maternal Cadmium (Cd, n = 31,651), Mercury (Hg, n = 18,962), and lead (Pb, n = 92,082) exposure, defined based on study-specific exposure contrasts, were significantly related to increased risk of PTB, with pooled ORs (95% CIs) of 1.12 (1.01, 1.24) for Ba, 1.23 (1.10, 1.38) for Cd, 1.05 (1.01, 1.08) for Hg, and 1.27 (1.09, 1.48) for Pb. Additionally, higher Cd and Hg were significantly associated with an increased risk of LBW, with ORs of 1.12 (1.06, 1.18) and 1.09 (1.04, 1.14), respectively. Higher As, Cd and Pb were also significantly associated with increased risk of SGA, with corresponding ORs (95% CIs) of 1.04 (1.01, 1.07), 1.12 (1.07, 1.16), and 1.19 (1.12, 1.27), respectively. The significant associations between metal exposures and increased risk of SVNs persisted or became more pronounced with specific biospecimen types. Particularly, elevated blood Arsenic (As), Cd, Molybdenum (Mo), Pb and urinary Cd, Cobalt (Co), chromium (Cr), copper (Cu), Hg, and Nickel (Ni) were assoc","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110052"},"PeriodicalIF":9.7,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146008289","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 : 2026-01-06DOI: 10.1016/j.envint.2026.110053
Joseph Saenz , Emma Aguila , Laura Tanner , Brian Downer , Jorge Peniche , Rebeca Wong
Drought represents a climate-related exposure impacting communities across the globe. Drought exposure has been linked with adverse human health, including poorer mental health and nutritional outcomes. It is unknown whether drought exposure relates to cognitive function. We evaluated cognitive function in adults aged 50+ by length of exposure to a major drought occurring between 2010 and 2012 in Mexico. We used individual-level data from the Mexican Health and Aging Study (n = 6988), drawing from pre-drought (2003) and post-drought (2012) waves, linked with monthly municipality-level information from the Mexican Drought Monitor on drought exposure produced by the Mexican National Water Commission. We employ multilevel regression models, with inverse probability of attrition weighting, to examine how length of drought exposure is related with post-drought cognition, controlling for pre-drought cognition and nutritional/mental health covariates. Whether quantified as the total number of months of drought exposure or the longest streak of consecutive months of drought exposure, longer drought exposure was negatively related with Verbal Learning and Verbal Recall performance over time but exhibited an inverse U-shaped association with Verbal Fluency. Findings were similar when using various thresholds of drought severity (i.e., severe to exceptional drought). Associations between drought and cognition were not explained by nutrition or mental health covariates. Public health and policy efforts should seek to build community-level resilience and infrastructure to enable effective coping with persistent environmental stressors, especially among older adults, to mitigate effects on health and well-being.
{"title":"Drought and cognitive function in older adults: results from the Mexican health and aging study","authors":"Joseph Saenz , Emma Aguila , Laura Tanner , Brian Downer , Jorge Peniche , Rebeca Wong","doi":"10.1016/j.envint.2026.110053","DOIUrl":"10.1016/j.envint.2026.110053","url":null,"abstract":"<div><div>Drought represents a climate-related exposure impacting communities across the globe. Drought exposure has been linked with adverse human health, including poorer mental health and nutritional outcomes. It is unknown whether drought exposure relates to cognitive function. We evaluated cognitive function in adults aged 50+ by length of exposure to a major drought occurring between 2010 and 2012 in Mexico. We used individual-level data from the Mexican Health and Aging Study (n = 6988), drawing from pre-drought (2003) and post-drought (2012) waves, linked with monthly municipality-level information from the Mexican Drought Monitor on drought exposure produced by the Mexican National Water Commission. We employ multilevel regression models, with inverse probability of attrition weighting, to examine how length of drought exposure is related with post-drought cognition, controlling for pre-drought cognition and nutritional/mental health covariates. Whether quantified as the total number of months of drought exposure or the longest streak of consecutive months of drought exposure, longer drought exposure was negatively related with Verbal Learning and Verbal Recall performance over time but exhibited an inverse U-shaped association with Verbal Fluency. Findings were similar when using various thresholds of drought severity (i.e., severe to exceptional drought). Associations between drought and cognition were not explained by nutrition or mental health covariates. Public health and policy efforts should seek to build community-level resilience and infrastructure to enable effective coping with persistent environmental stressors, especially among older adults, to mitigate effects on health and well-being.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110053"},"PeriodicalIF":9.7,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146008298","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 : 2026-01-02DOI: 10.1016/j.envint.2025.110043
Yue Xi , Susanne Breitner-Busch , Qiuling Dong , Kathrin Wolf , Marco Dallavalle , Nikolaos Nikolaou , Josef Cyrys , Harald Grallert , Birgit Linkohr , Wolfgang Rathmann , Christian Herder , Lars Schwettmann , Barbara Thorand , Reiner Jumpertz von Schwartzenberg , Annette Peters
Objective
To examine the association between environmental exposures and specific type 2 diabetes (T2D) subphenotypes.
Research design and methods
We categorized T2D participants from the KORA F4 (2006–2008) and FF4 (2013–2014) study waves into three phenotypes using k-means clustering: Cluster A (insulin deficiency); Cluster B (age-related diabetes); and Cluster C (higher insulin resistance). The annual averages of fine particulate matter (PM2.5) and PM2.5 absorbance (PM2.5abs), annual air temperature mean (Tm) and standard deviations (Tsd), and greenness (NDVI), were assessed at participants’ residences. Covariate-adjusted mixed multinomial logistic regression models were fitted to examine the effects of environmental exposures on diabetes subphenotypes. We also calculated joint odds ratios (ORs) to estimate the additive effects of exposure mixtures.
Results
The longitudinal analysis showed that interquartile range (IQR) increases in PM2.5 (OR = 1.29, 95 % confidence interval [CI]: 1.01, 1.64) and PM2.5abs (OR = 1.30, 95 % CI: 1.01, 1.67) were associated with higher odds of being in T2D Cluster C, compared to normoglycemic individuals. Furthermore, we found that IQR increases in PM2.5 and Tsd, alongside with decreases in NDVI and Tm increased the odds of being in Cluster B (joint OR = 1.41, 95 % CI: 1.03, 1.93) and Cluster C (joint OR = 1.55, 95 % CI: 1.02, 2.36), while the combination of PM2.5abs with other exposures increased the odds of Cluster C (joint OR = 1.54, 95 % CI: 1.01, 2.33).
Conclusions
Our study contributes to an enhanced understanding of the associations between environmental exposures and diabetes, indicating increased risks for age-related and insulin-resistant diabetes.
{"title":"Longitudinal associations of long-term exposure to ambient air pollution, residential greenness, and air temperature with type 2 diabetes subphenotypes: Results from the KORA cohort study","authors":"Yue Xi , Susanne Breitner-Busch , Qiuling Dong , Kathrin Wolf , Marco Dallavalle , Nikolaos Nikolaou , Josef Cyrys , Harald Grallert , Birgit Linkohr , Wolfgang Rathmann , Christian Herder , Lars Schwettmann , Barbara Thorand , Reiner Jumpertz von Schwartzenberg , Annette Peters","doi":"10.1016/j.envint.2025.110043","DOIUrl":"10.1016/j.envint.2025.110043","url":null,"abstract":"<div><h3>Objective</h3><div>To examine the association between environmental exposures and specific type 2 diabetes (T2D) subphenotypes.</div></div><div><h3>Research design and methods</h3><div>We categorized T2D participants from the KORA F4 (2006–2008) and FF4 (2013–2014) study waves into three phenotypes using k-means clustering: Cluster A (insulin deficiency); Cluster B (age-related diabetes); and Cluster C (higher insulin resistance). The annual averages of fine particulate matter (PM<sub>2.5</sub>) and PM<sub>2.5</sub> absorbance (PM<sub>2.5</sub>abs), annual air temperature mean (T<sub>m</sub>) and standard deviations (T<sub>sd</sub>), and greenness (NDVI), were assessed at participants’ residences. Covariate-adjusted mixed multinomial logistic regression models were fitted to examine the effects of environmental exposures on diabetes subphenotypes. We also calculated joint odds ratios (ORs) to estimate the additive effects of exposure mixtures.</div></div><div><h3>Results</h3><div>The longitudinal analysis showed that interquartile range (IQR) increases in PM<sub>2.5</sub> (OR = 1.29, 95 % confidence interval [CI]: 1.01, 1.64) and PM<sub>2.5</sub>abs (OR = 1.30, 95 % CI: 1.01, 1.67) were associated with higher odds of being in T2D Cluster C, compared to normoglycemic individuals. Furthermore, we found that IQR increases in PM<sub>2.5</sub> and T<sub>sd</sub>, alongside with decreases in NDVI and T<sub>m</sub> increased the odds of being in Cluster B (joint OR = 1.41, 95 % CI: 1.03, 1.93) and Cluster C (joint OR = 1.55, 95 % CI: 1.02, 2.36), while the combination of PM<sub>2.5</sub>abs with other exposures increased the odds of Cluster C (joint OR = 1.54, 95 % CI: 1.01, 2.33).</div></div><div><h3>Conclusions</h3><div>Our study contributes to an enhanced understanding of the associations between environmental exposures and diabetes, indicating increased risks for age-related and insulin-resistant diabetes.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"208 ","pages":"Article 110043"},"PeriodicalIF":9.7,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145895272","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 : 2026-01-01DOI: 10.1016/j.envint.2025.110038
Wendong Ge , Di Wang , Yang Ren , Yuhan Zhou , Xinyang Liu , Dongting Wei , Junfeng Liu
With the increasing ozone (O3) pollution and slowing down trend of fine particulate matter (PM2.5) reduction in China in recent years, volatile organic compounds (VOCs) as common precursors are playing a more important role, with stronger demand to clarify their emissions, verify their simulations and evaluate their regional influences. This study aims to introduce a comprehensive anthropogenic non-methane VOCs (NMVOCs) emission inventory in China in 2019, comprehensively assess the impact on NMVOCs, O3 and PM2.5 simulations, and investigate the effect of recent VOCs-related industrial policies and technologies at a regional scale using the Community Earth System Model version 2 (CESM2). The results show that Jiangsu, Shandong, Zhejiang and Guangdong provinces account for the largest anthropogenic emissions (44 % collectively), and solvent utilization and industrial processes are two dominated sectors of NMVOCs emission sources (>70 % collectively). The hydrocarbon simulations are closer to observations with updated emission inventories. The implementation of NMVOCs emission reduction technologies can effectively reduce most components of NMVOCs in China by over 12 %, and is beneficial to the coordinated control of PM2.5 (9 % reduction nationally) and O3 pollutions (2 % reduction nationally) in most regions of China as well as co-benefits for neighboring countries and regions (1 %∼10 % pollutant reductions). This study suggested that the future VOCs control in China needs to focus more on aromatics and alkenes in the Yangtze River Delta and parts of the North China Plain.
{"title":"A new NMVOCs emission inventory for China: Impact on O3 and PM2.5 regional simulations and assessment of recent industrial NMVOCs emission abatement policies","authors":"Wendong Ge , Di Wang , Yang Ren , Yuhan Zhou , Xinyang Liu , Dongting Wei , Junfeng Liu","doi":"10.1016/j.envint.2025.110038","DOIUrl":"10.1016/j.envint.2025.110038","url":null,"abstract":"<div><div>With the increasing ozone (O<sub>3</sub>) pollution and slowing down trend of fine particulate matter (PM<sub>2.5</sub>) reduction in China in recent years, volatile organic compounds (VOCs) as common precursors are playing a more important role, with stronger demand to clarify their emissions, verify their simulations and evaluate their regional influences. This study aims to introduce a comprehensive anthropogenic non-methane VOCs (NMVOCs) emission inventory in China in 2019, comprehensively assess the impact on NMVOCs, O<sub>3</sub> and PM<sub>2.5</sub> simulations, and investigate the effect of recent VOCs-related industrial policies and technologies at a regional scale using the Community Earth System Model version 2 (CESM2). The results show that Jiangsu, Shandong, Zhejiang and Guangdong provinces account for the largest anthropogenic emissions (44 % collectively), and solvent utilization and industrial processes are two dominated sectors of NMVOCs emission sources (>70 % collectively). The hydrocarbon simulations are closer to observations with updated emission inventories. The implementation of NMVOCs emission reduction technologies can effectively reduce most components of NMVOCs in China by over 12 %, and is beneficial to the coordinated control of PM<sub>2.5</sub> (9 % reduction nationally) and O<sub>3</sub> pollutions (2 % reduction nationally) in most regions of China as well as co-benefits for neighboring countries and regions (1 %∼10 % pollutant reductions). This study suggested that the future VOCs control in China needs to focus more on aromatics and alkenes in the Yangtze River Delta and parts of the North China Plain.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 110038"},"PeriodicalIF":9.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145909642","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 : 2026-01-01DOI: 10.1016/j.envint.2025.110017
Jixing Zhou , Juan Tong , Chunmei Liang , Jie Sheng , Xiaoyan Wu , Guopeng Gao , Shuangqin Yan , Fangbiao Tao , Kun Huang
Prenatal metal exposure can disrupt the homeostasis of foetal thyroid function. Drawing on data from 2,444 mother–child pairs involved in Ma’anshan birth cohort (MABC) study, we explored the associations of prenatal fourteen metals [arsenic (As), cadmium (Cd), mercury (Hg), lead (Pb), manganese (Mn), thallium (Tl), zinc (Zn), selenium (Se), vanadium (V), cobalt (Co), barium (Ba), molybdenum (Mo), iron (Fe), copper (Cu)] exposure and placental transfer efficiency (PTE) of these metals with thyroid function in newborns by analysing three types of biological samples. We calculated the PTE of metals and performed statistical analysis using multiple linear regression, and weighted quantile sum (WQS), interaction and marginal effects models. Results indicated that the PTE of metals (As, Hg, Mn, Zn, Se, Co, Cu and Fe), maternal Cd, and cord metals (As, Mn, Zn, Se, Co, Cu, and Fe) were positively associated with neonatal thyroid-stimulating hormone (TSH) levels in the adjusted model. The PTE of metals (Mn, Cu, and Fe), maternal Tl, cord metals (Mn, Cu, and Fe) were negatively associated with neonatal free thyroxine (FT4) levels. The WQS of the metal mixture, measured in both maternal blood and cord blood, as well as the PTE of metals, demonstrated a significant inverse association with FT4. Among these, maternal Tl and As, cord Cu, and the PTE of Cu made the most substantial contributions to these associations. Potential interactions between maternal vitamin D levels and some metals (PTE of Hg and Fe, maternal Hg, Mn and Fe, cord Tl and Ba) on neonatal TSH and FT4 were observed. Notably, Hg and Fe exposure were almost significantly associated with neonatal TSH and FT4 only in the group with maternal vitamin D deficiency.This study reveals that both single and mixed exposures to multiple metals during the prenatal period may affect the thyroid function of the fetus in utero, and highlights the potential key role of the relatively high metal transport efficiency between the mother and the fetus.
{"title":"The impact of prenatal maternal-fetal metal levels and placental transfer efficiency of metals on neonatal thyroid function: The modulatory role of maternal vitamin D levels in pregnancy","authors":"Jixing Zhou , Juan Tong , Chunmei Liang , Jie Sheng , Xiaoyan Wu , Guopeng Gao , Shuangqin Yan , Fangbiao Tao , Kun Huang","doi":"10.1016/j.envint.2025.110017","DOIUrl":"10.1016/j.envint.2025.110017","url":null,"abstract":"<div><div>Prenatal metal exposure can disrupt the homeostasis of foetal thyroid function. Drawing on data from 2,444 mother–child pairs involved in Ma’anshan birth cohort (MABC) study, we explored the associations of prenatal fourteen metals [arsenic (As), cadmium (Cd), mercury (Hg), lead (Pb), manganese (Mn), thallium (Tl), zinc (Zn), selenium (Se), vanadium (V), cobalt (Co), barium (Ba), molybdenum (Mo), iron (Fe), copper (Cu)] exposure and placental transfer efficiency (PTE) of these metals with thyroid function in newborns by analysing three types of biological samples. We calculated the PTE of metals and performed statistical analysis using multiple linear regression, and weighted quantile sum (WQS),<!--> <!-->interaction and marginal effects models. Results indicated that the PTE of metals (As, Hg, Mn, Zn, Se, Co, Cu and Fe), maternal Cd, and cord metals (As, Mn, Zn, Se, Co, Cu, and Fe) were positively associated with neonatal thyroid-stimulating hormone (TSH) levels<!--> <!-->in the adjusted model. The PTE of metals (Mn, Cu, and Fe), maternal Tl, cord metals (Mn, Cu, and Fe) were negatively associated with neonatal free thyroxine (FT<sub>4</sub>) levels. The WQS of the metal mixture, measured in both maternal blood and cord blood, as well as the PTE of metals, demonstrated a significant inverse association with FT<sub>4</sub>. Among these, maternal Tl and As, cord Cu, and the PTE of Cu made the most substantial contributions to these associations. Potential interactions between maternal vitamin D levels and some metals (PTE of Hg and Fe, maternal Hg, Mn and Fe, cord Tl and Ba) on neonatal TSH and FT<sub>4</sub> were observed. Notably, Hg and Fe exposure were almost significantly associated with neonatal TSH and FT<sub>4</sub> only in the group with maternal vitamin D deficiency.This study reveals that both single and mixed exposures to multiple metals during the prenatal period may affect the thyroid function of the fetus in utero, and highlights the potential key role of the relatively high metal transport efficiency between the mother and the fetus.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 110017"},"PeriodicalIF":9.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796386","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 : 2026-01-01DOI: 10.1016/j.envint.2026.110062
Shaoyang Li , Wenxuan Luo , Zhile Pan , Junjie Li , Xinyu Ma , Yanran Dong , Kuo Zhang , Weiling Sun , Nan Xu
The increasing use of fluorinated pesticides and pharmaceuticals has raised global concerns. Among them, substances containing –CF3 group are referred to as PFAS pesticides and pharmaceuticals (PFAS PPs) in this study and exhibit higher bioaccumulation and persistence. Moreover, their transformation products (TPs) may enhance their hazards. In this study, actual field monitoring and laboratory simulation experiments were conducted to reveal the occurrence, removal, risk, and trifluoroacetic acid (TFA) formation potential of PFAS PPs and TPs in wastewater treatment plants (WWTPs). Five PFAS PPs and twelve TPs were identified in wastewater, among which 7 TPs were detected for the first time in the environment. PFAS pharmaceuticals showed the highest average concentrations (127 ng/L) among 33 classes of PFAS detected in influent. Average removal rates of 17 PFAS PPs and TPs ranged from −76.6% to 81.5%. Activated sludge assays revealed that the negative removal of PFAS PPs was attributed to reconversion of their human metabolites. TPs of PFAS pesticides and PFAS pharmaceuticals exhibited higher bioaccumulation and mobility, respectively. TFA molar yields of the seven PFAS PPs and TPs ranged from 4.7% to 19.8% in the total oxidation precursor assays. However, no TFA formation was observed after biodegradation of the seven PFAS PPs and TPs by activated sludge simulating real conditions, indicating that they are unlikely to be transformed into TFA in real WWTPs. These results reveal the significance of unconventional PFAS PPs and TPs for overall PFAS in wastewater, highlighting the need to move beyond conventional PFAS toward the fast-growing PFAS PPs.
{"title":"Non-target screening and laboratory experiments reveal the transformation products and negligible trifluoroacetic acid formation potential of PFAS pesticides and pharmaceuticals in wastewater treatment plants","authors":"Shaoyang Li , Wenxuan Luo , Zhile Pan , Junjie Li , Xinyu Ma , Yanran Dong , Kuo Zhang , Weiling Sun , Nan Xu","doi":"10.1016/j.envint.2026.110062","DOIUrl":"10.1016/j.envint.2026.110062","url":null,"abstract":"<div><div>The increasing use of fluorinated pesticides and pharmaceuticals has raised global concerns. Among them, substances containing –CF<sub>3</sub> group are referred to as PFAS pesticides and pharmaceuticals (PFAS PPs) in this study and exhibit higher bioaccumulation and persistence. Moreover, their transformation products (TPs) may enhance their hazards. In this study, actual field monitoring and laboratory simulation experiments were conducted to reveal the occurrence, removal, risk, and trifluoroacetic acid (TFA) formation potential of PFAS PPs and TPs in wastewater treatment plants (WWTPs). Five PFAS PPs and twelve TPs were identified in wastewater, among which 7 TPs were detected for the first time in the environment. PFAS pharmaceuticals showed the highest average concentrations (127 ng/L) among 33 classes of PFAS detected in influent. Average removal rates of 17 PFAS PPs and TPs ranged from −76.6% to 81.5%. Activated sludge assays revealed that the negative removal of PFAS PPs was attributed to reconversion of their human metabolites. TPs of PFAS pesticides and PFAS pharmaceuticals exhibited higher bioaccumulation and mobility, respectively. TFA molar yields of the seven PFAS PPs and TPs ranged from 4.7% to 19.8% in the total oxidation precursor assays. However, no TFA formation was observed after biodegradation of the seven PFAS PPs and TPs by activated sludge simulating real conditions, indicating that they are unlikely to be transformed into TFA in real WWTPs. These results reveal the significance of unconventional PFAS PPs and TPs for overall PFAS in wastewater, highlighting the need to move beyond conventional PFAS toward the fast-growing PFAS PPs.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 110062"},"PeriodicalIF":9.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956870","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 : 2026-01-01DOI: 10.1016/j.envint.2025.110003
L. Villain , S. Schaller , D. Lefaudeux , L.S. Lautz , M. Siccardi , D. Heckmann
Environmental risk assessment (ERA) necessitates the evaluation of numerous species that cannot be directly tested due to ethical and resource limitations. Thus, cross-species extrapolation of experimental data is essential for ERA, especially in the context of mechanistically informed (next generation) risk assessments. Physiologically based Kinetic (PBK) models allow for cross-species extrapolation of toxicokinetic (TK) data in ecotoxicology, but a systematic evaluation of performance and data requirements for this application is lacking. This study aimed to assess the data requirements and performance of PBK models when extrapolating TK data among small mammals. We parameterized PBK models for three mammal species (Rattus norvegicus, Mus musculus, Oryctolagus cuniculus) in the PK-Sim software and performed cross-species extrapolations for nine compounds, all six possible reference-target species combinations, while systematically omitting available (in vitro) data.
The results indicate a substantial improvement in prediction performance over bodyweight-scaled models, with clearance data contributing most significantly to performance. Notably, a limited in vitro dataset can enable robust extrapolation that approaches the accuracy of a direct fit to the target data. Data from Rattus norvegicus, a common reference species in ecotoxicology, yielded good performance when extrapolating to the other two species. For all three species, prediction accuracy may decline when extrapolating beyond the dose range of the reference dataset or in the presence of saturation effects. The established framework and codebase can be expanded to include additional compounds, species, and administration routes, facilitating a data-efficient ERA with mechanistic models.
{"title":"Physiologically based kinetic modelling for species extrapolation of toxicokinetic data between small mammals: A systematic evaluation","authors":"L. Villain , S. Schaller , D. Lefaudeux , L.S. Lautz , M. Siccardi , D. Heckmann","doi":"10.1016/j.envint.2025.110003","DOIUrl":"10.1016/j.envint.2025.110003","url":null,"abstract":"<div><div>Environmental risk assessment (ERA) necessitates the evaluation of numerous species that cannot be directly tested due to ethical and resource limitations. Thus, cross-species extrapolation of experimental data is essential for ERA, especially in the context of mechanistically informed (next generation) risk assessments. Physiologically based Kinetic (PBK) models allow for cross-species extrapolation of toxicokinetic (TK) data in ecotoxicology, but a systematic evaluation of performance and data requirements for this application is lacking. This study aimed to assess the data requirements and performance of PBK models when extrapolating TK data among small mammals. We parameterized PBK models for three mammal species (<em>Rattus norvegicus</em>, <em>Mus musculus, Oryctolagus cuniculus</em>) in the PK-Sim software and performed cross-species extrapolations for nine compounds, all six possible reference-target species combinations, while systematically omitting available (in vitro) data.</div><div>The results indicate a substantial improvement in prediction performance over bodyweight-scaled models, with clearance data contributing most significantly to performance. Notably, a limited in vitro dataset can enable robust extrapolation that approaches the accuracy of a direct fit to the target data. Data from <em>Rattus norvegicus</em>, a common reference species in ecotoxicology, yielded good performance when extrapolating to the other two species. For all three species, prediction accuracy may decline when extrapolating beyond the dose range of the reference dataset or in the presence of saturation effects. The established framework and codebase can be expanded to include additional compounds, species, and administration routes, facilitating a data-efficient ERA with mechanistic models.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 110003"},"PeriodicalIF":9.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145909581","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 : 2026-01-01DOI: 10.1016/j.envint.2025.110009
Michael Bauer , Jay G. Slowik , Marta Via , Peeyush Khare , Benjamin Chazeau , Kristina Glojek , Manousos Manousakas , Zachary C.J. Decker , Asta Gregorič , Almir Bijedić , Enis Krečinić , Griša Močnik , Katja Džepina , André S.H. Prévôt
Particulate air pollution is the leading environmental risk factor, contributing substantially to global morbidity and mortality. In the Western Balkans, air quality during winter months is among the poorest observed in Europe. Nevertheless, detailed chemical characterization of air pollution in the region remains limited, although such information is essential for identifying emission sources and supporting effective mitigation strategies. Therefore, a mobile measurement campaign was conducted in Sarajevo (Bosnia and Herzegovina) in January 2023 as part of the SArajevo AEROsol Experiment (SAAERO). The spatial distribution and chemical composition of particle- and gas-phase pollutants were investigated using multiple high-resolution instruments. Organic aerosol (OA), as a key component, accounted for 59% of the total submicron particulate matter (PM1). Source apportionment of the OA using Positive Matrix Factorization (PMF) resolved five distinct sources: two solid fuel combustion sources (SFC1 and SFC2), traffic (HOA), cooking (COA), and oxygenated OA (OOA). While daytime variation across the city was limited, an east–west pollution gradient emerged during evening hours, largely driven by SFC. SFC contributions to OA ranged from 45 to 54 % in predominantly residential areas outside the city center and amounted to 35 % in the center. In contrast, COA was highest in the center (14%), spatially aligned with restaurant locations.
These findings show that pollution sources contribute non-uniformly in different parts of Sarajevo especially during evening hours. By combining spatially resolved measurements with source apportionment, this study provides valuable insights into pollution sources and their chemical composition in Sarajevo, a highly polluted but still largely understudied area in Europe.
{"title":"Assessing the severe urban pollution crisis in Sarajevo, Bosnia and Herzegovina: mobile measurements and source characterization","authors":"Michael Bauer , Jay G. Slowik , Marta Via , Peeyush Khare , Benjamin Chazeau , Kristina Glojek , Manousos Manousakas , Zachary C.J. Decker , Asta Gregorič , Almir Bijedić , Enis Krečinić , Griša Močnik , Katja Džepina , André S.H. Prévôt","doi":"10.1016/j.envint.2025.110009","DOIUrl":"10.1016/j.envint.2025.110009","url":null,"abstract":"<div><div>Particulate air pollution is the leading environmental risk factor, contributing substantially to global morbidity and mortality. In the Western Balkans, air quality during winter months is among the poorest observed in Europe. Nevertheless, detailed chemical characterization of air pollution in the region remains limited, although such information is essential for identifying emission sources and supporting effective mitigation strategies. Therefore, a mobile measurement campaign was conducted in Sarajevo (Bosnia and Herzegovina) in January 2023 as part of the SArajevo AEROsol Experiment (SAAERO). The spatial distribution and chemical composition of particle- and gas-phase pollutants were investigated using multiple high-resolution instruments. Organic aerosol (OA), as a key component, accounted for 59% of the total submicron particulate matter (PM<sub>1</sub>). Source apportionment of the OA using Positive Matrix Factorization (PMF) resolved five distinct sources: two solid fuel combustion sources (SFC1 and SFC2), traffic (HOA), cooking (COA), and oxygenated OA (OOA). While daytime variation across the city was limited, an east–west pollution gradient emerged during evening hours, largely driven by SFC. SFC contributions to OA ranged from 45 to 54 % in predominantly residential areas outside the city center and amounted to 35 % in the center. In contrast, COA was highest in the center (14%), spatially aligned with restaurant locations.</div><div>These findings show that pollution sources contribute non-uniformly in different parts of Sarajevo especially during evening hours. By combining spatially resolved measurements with source apportionment, this study provides valuable insights into pollution sources and their chemical composition in Sarajevo, a highly polluted but still largely understudied area in Europe.</div></div>","PeriodicalId":308,"journal":{"name":"Environment International","volume":"207 ","pages":"Article 110009"},"PeriodicalIF":9.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785433","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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