Environmental science. Advances最新文献

{"title":"Spectroscopic investigation of the effects of simulated open waste burning on the functional and surface chemistry of commercial polystyrene","authors":"Maycee Hurd, Xuewen Wang, Angelica Benavidez, Allyson L. McGaughey, Michael Spilde, José M. Cerrato, Jorge Gonzalez-Estrella and Eliane El Hayek","doi":"10.1039/D5VA00291E","DOIUrl":"10.1039/D5VA00291E","url":null,"abstract":"<p >We studied the spectroscopic changes of polystyrene (PS) plastic used for commercial food packaging after thermal oxidation. Thermal oxidation of plastic in the environment occurs during open waste burning (OWB), urban wildfires, and even the serving of hot food. Environmental thermally oxidized plastics are understudied and display unique functional and surface chemistry compared to plastics exposed to other environmental weathering processes. Near-surface X-ray photoelectron spectroscopy (XPS) C 1s high resolution analyses show an increase in the intensity of peaks greater than 285 eV, corresponding to C/O bonds after burning of PS at 350 and 425 °C. Bulk analyses using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy show that thermal oxidation decreased the alkene (3040–3000 cm<small>⁻¹</small>) and alkane (3000–2850 cm<small>⁻¹</small>) C–H stretch signals, suggesting PS chain scission. Morphology defects and fractures were observed in scanning electron microscopy (SEM) images, indicating that the degradation of PS can lead to fragmentation after burning. The outcome of this study furthers the understanding of the thermal oxidative degradation mechanisms during incineration of commercial PS materials, which can inform future risk assessments of public and environmental health associated with OWB.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1050-1059"},"PeriodicalIF":4.4,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12970243/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147438112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Liver-related biomarkers mediate the potential effect of volatile organic compounds on an anti-aging hormone: a cross-sectional study","authors":"Shuaifei Ji, Yiming Bi, Bochen An, Jingcheng Zhou, Lixin Yu and Ding Zeng","doi":"10.1039/D5VA00270B","DOIUrl":"https://doi.org/10.1039/D5VA00270B","url":null,"abstract":"<p >Volatile Organic Compounds (VOCs) are a class of air pollutants that have adverse metabolic and endocrine effects. α-Klotho, an anti-aging hormone, is susceptible to environmental pollution. This study aimed to explore the association between urinary VOCs and serum α-Klotho levels and the underlying molecular mechanisms. 1680 individuals from the U.S. were included. The association between VOCs and α-Klotho was explored using multivariate linear regression. Weighted quantile sum (WQS) regressions were used to identify the important distribution of VOCs on α-Klotho, and Bayesian kernel machine regressions (BKMR) were implemented to assess the joint and univariate effects of all VOCs on α-Klotho. Mediation analyses of liver-related biomarkers in the effects of mixed and single VOCs on α-Klotho were also performed. The multivariate linear regression model showed that multiple VOCs were negatively associated with α-Klotho. The WQS models ascertained that <em>N</em>-acetyl-<em>S</em>-(2-carboxyethyl)-<small>L</small>-cysteine (CEMA), <em>N</em>-acetyl-<em>S</em>-(2-cyanoethyl)-<small>L</small>-cysteine (CYMA), and 2-aminothiazoline-4-carboxylic acid (ATCA) play dominant roles. In the BKMR model, we found that the joint effects of mixed VOCs were negatively associated with α-Klotho in the general population (40–79 years) and middle-aged population (40–59 years). Finally, mediation analyses showed that liver-related biomarkers exhibited a substantial mediation effect in the single ATCA on α-Klotho, with a proportion as high as 31.6% in the middle-aged population. Our study demonstrated that liver-related biomarkers mediate the influence of VOCs, especially ATCA, on α-Klotho. Our findings suggest that reducing VOC exposure may be a potential strategy to maintain α-Klotho levels.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1189-1202"},"PeriodicalIF":4.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2026/va/d5va00270b?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147620992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of explainable artificial intelligence and machine learning in predicting wastewater treatment plant variables: a comparative study of small- and large-scale treatment plants","authors":"Fuad Bin Nasir and Jin Li","doi":"10.1039/D5VA00408J","DOIUrl":"https://doi.org/10.1039/D5VA00408J","url":null,"abstract":"<p >Explainable artificial intelligence (XAI) can play a significant role in the application of machine learning (ML) in wastewater treatment plants (WWTPs). The present research focuses on evaluating the performance and generalizability of widely used ML models for predicting key effluent quality variables at multiple WWTPs. Effluent variables including ammonia nitrogen (NH<small>₃</small>–N), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total phosphorus (TP), and total suspended solids (TSS) were predicted using eXtreme Gradient Boosting (XGBoost) and Random Forest (RF) models. Several feature selections (FS) and XAI tools were used to understand the influence of input variables on target variables and the impact of input variables on model performance. The study demonstrates that XAI can enhance the understanding of model behavior by identifying key input variables, thereby supporting more informed and transparent decision-making at WWTPs. The study finds that XAI methods are effective in capturing the influence of variables regardless of the choice of model for variable prediction. XAI tools, SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME), are successful in providing deeper understanding of the key factors influencing ML model performance. The findings of this research could facilitate WWTP operation with better decision-making in choosing ML models to optimize treatment performance and improve environmental sustainability.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1174-1188"},"PeriodicalIF":4.4,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2026/va/d5va00408j?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147620997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the impacts of feed and species composition on greenhouse gas emission from freshwater aquaculture systems in Bangladesh","authors":"K. R. Luba, H. Rashid, M. S. Islam, M. Akter, R. Khatun, M. Zaman and M. M. R. Jahangir","doi":"10.1039/D5VA00215J","DOIUrl":"https://doi.org/10.1039/D5VA00215J","url":null,"abstract":"<p >Bangladesh, a major global aquaculture producer, is potentially a notable source of greenhouse gas (GHG) emissions from aquaculture, but no measured data have yet been reported. This study investigates hydrochemistry, dissolved GHG concentrations in water and GHG (CO<small>₂</small>, CH<small>₄</small>, and N<small>₂</small>O) emissions from four prevalent freshwater aquaculture systems in Mymensingh, Bangladesh, focusing on Indian major carps (IMCs), Pangasius catfish (PG), Climbing perch (CP) and Tilapia (T), along with the feed loads. Semi-structured interviews with farm managers yielded key feed input parameters, including consumption rates, protein levels, and feed conversion ratios. Dissolved GHG concentrations and atmospheric emissions were measured during 2023 to 2024 (spanning from the dry winter to the pre-monsoon season, with biweekly sampling) using the headspace extraction for dissolved gases and a 40 × 40 × 50 cm<small>³</small> acrylic floating chamber for surface fluxes, with gas chromatography. The results revealed that PG systems exhibited significantly higher CH<small>₄</small>, N<small>₂</small>O and CO<small>₂</small> emissions by 89–96, 59–75 and 66–78% than IMC and T systems, likely due to intensive sinking-feed use causing low dissolved oxygen, high electrical conductivity and mineral nitrogen, thereby promoting anaerobic conditions and enhanced methanogenesis and denitrification. In contrast, the IMC and T systems, utilizing more efficient floating feeds, showed comparatively lower emissions. The dissolved gas concentration analysis further complemented the surface gas emissions data, offering a holistic understanding of emissions from aquaculture ponds. The results suggest that optimizing feed composition and management can substantially reduce the aquaculture sector's impacts on climate change. By providing a detailed understanding of the GHG emissions from different aquaculture systems, this research contributes valuable insights for policymakers, industry stakeholders, and environmental scientists.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1130-1140"},"PeriodicalIF":4.4,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2026/va/d5va00215j?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147621003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Oxidation of TcO2 and UO2 by aqueous Mn(iii)-citrate and Mn(iii)-tartrate under anoxic conditions: implications for technetium and uranium fate and transport","authors":"Zachary Murphy, Zachary Ronchetti, Cassandra Munoz, David Rai and Vasileios Anagnostopoulos","doi":"10.1039/D5VA00264H","DOIUrl":"https://doi.org/10.1039/D5VA00264H","url":null,"abstract":"<p >There are several United States Department of Energy (DOE) sites that have been dealing with the problem of legacy nuclear waste in the environment for many generations. Two major risk-driving radionuclides in this legacy waste are uranium and technetium-99. Due to their radioactivity, the increase in concentration of these radionuclides in the environment represents a significant concern to environmental health and safety. Uranium and technetium both have increased solubility and mobility in the environment when oxidized from U(<small>IV</small>) to U(<small>VI</small>) and from Tc(<small>IV</small>) to Tc(<small>VII</small>), respectively. This project investigated the role of Mn(<small>III</small>)-tartrate and Mn(<small>III</small>)-citrate in influencing the redox behavior and stability of uranium, from uranium dioxide (UO<small>₂</small>), and technetium, from technetium oxide (TcO<small>₂</small>). For each radionuclide, anaerobic batch kinetic experiments of UO<small>₂</small> and TcO<small>₂</small> in the presence of these Mn(<small>III</small>)-ligands were conducted at pH 8 and 10, and the radionuclide concentration in the aqueous phase was monitored over time. Both the Mn(<small>III</small>)-tartrate and Mn(<small>III</small>)-citrate complexes effectively induced dissolution of uranium and technetium, however, differences were seen with increasing ligand concentration and pH. Higher concentrations of the Mn(<small>III</small>)-ligand complexes resulted in higher concentrations of aqueous uranium or technetium over time, supporting Mn(<small>III</small>) induced oxidation of these radionuclides. Additionally, the Mn(<small>III</small>)-tartrate complex resulted in more oxidation at pH 8 for both uranium and technetium while the Mn(<small>III</small>)-citrate ligand provided more oxidation at pH 10 for uranium and was comparable for technetium. The data presented in this study is useful for creating expected uranium and technetium transport models based on the abundance of naturally occurring manganese species.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1106-1115"},"PeriodicalIF":4.4,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2026/va/d5va00264h?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147621007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of deprivation and socioeconomic factors on inequalities in volatile organic compound emissions in communities in England","authors":"Connor J. Young, Rebecca L. Cordell and Paul S. Monks","doi":"10.1039/D6VA00041J","DOIUrl":"https://doi.org/10.1039/D6VA00041J","url":null,"abstract":"<p >Poor air quality is one of the leading environmental threats to global public health; deprived communities endure disproportionately higher ambient concentrations of primary pollutants such as NO<small>_<em>x</em></small> and PM<small>_2.5</small>. Volatile organic compounds (VOCs) are ubiquitous in the indoor and outdoor environment and can be harmful to human health, yet their relationship with deprivation has not been widely explored. Modelled emissions of VOCs from 2019 across England are linked to indices of multiple deprivation (IMD), land classification, and ethnicity data, to explore the spatial relationship between VOCs, deprivation and social parameters within English communities. VOC emissions are shown to increase as deprivation increases across London and the rest of England, with higher emissions rates in London. Solvent emissions are the dominant source of VOCs across England, and the only source which exhibits a relationship with deprivation. Urban settings demonstrate a higher inequality in emissions in deprived communities, with relative contribution of different sources dependent on geographical location. Population density and minority ethnicity—both proxies for deprivation—correlate with higher VOC emissions, particularly in densely settled minority communities. This research identifies an association between VOC emissions and deprivation in England which has not been seen before. Communities at risk of environmental inequality from VOC emissions are areas of higher ethnic minority populations and increased population density. The relationship with solvent emissions helps to understand the emission sources within these communities, to try to reduce emissions and tackle inequality of air pollution.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1095-1105"},"PeriodicalIF":4.4,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2026/va/d6va00041j?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147621008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chronic PFOA and PFOS exposure triggers cellular oxidative stress and alters lipid levels as revealed through multi-omics analysis","authors":"Jenise Z. Paddayuman, Judith R. Cristobal, Luane J. B. Landau, Ashleigh L. Gagnon, Omer Gokcumen, Diana S. Aga and G. Ekin Atilla-Gokcumen","doi":"10.1039/D5VA00353A","DOIUrl":"10.1039/D5VA00353A","url":null,"abstract":"<p >Per- and polyfluoroalkyl substances (PFAS), or “forever chemicals,” are linked to metabolic, immune, and neurotoxic disorders, yet their long-term cellular effects remain unclear. Using a 24 week chronic exposure model with non-transformed human epithelial cells, we examined responses to low, environmentally relevant concentrations of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS). Integrated transcriptomic and lipidomic analyses revealed that despite minimal cellular accumulation, molecular changes emerged around week 17, marked by transcriptional signatures indicative of oxidative stress responses, cell survival pathways, and lipid metabolism. Our data suggests a multi-faceted model in which long-term PFOA and PFOS exposure induces oxidative stress mediated by SESN2 and SOD3, increases lipid biosynthesis <em>via</em> SREBP pathway, and causes compound-specific disruptions of membrane lipids. These findings highlight the importance of multi-omic, time-resolved approaches in uncovering the mechanisms of chronic low-dose chemical exposure and provide a foundation for future <em>in vivo</em> studies.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1081-1094"},"PeriodicalIF":4.4,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12951838/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147349898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High resolution porewater profiling of methylmercury with a novel equilibrium passive sampler","authors":"Jada C. Damond, Cynthia C. Gilmour and Upal Ghosh","doi":"10.1039/D5VA00492F","DOIUrl":"10.1039/D5VA00492F","url":null,"abstract":"<p >Accurate quantification of sediment porewater methylmercury (MeHg) profiles is critical for understanding Hg fate, transport, and informing remediation design, yet direct porewater profiling remains challenging. Equilibrium-based passive samplers (EqPS) offer an alternative, providing fine-scale, time-integrated measurements and convenience. In this study, we deployed an EqPS consisting of activated carbon suspended in agarose gel (ag+AC) in estuarine and freshwater sediment microcosms to obtain porewater MeHg profiles at 0.5 cm vertical resolution. Our objectives were to evaluate whether ag+AC samplers could reproduce porewater MeHg profile shapes and concentrations across redox gradients and contrasting geochemical conditions. Following 4 week deployments across the sediment–water interface ag+AC samplers produced distinct depth profiles that corresponded closely with directly measured porewater profiles and exhibited maxima at redox transition zones where net methylation is most likely. Using a previously derived equilibrium partition coefficient (10<small>²</small>·<small>⁹⁶</small> L kg<small>⁻¹</small>) ag+AC samplers predicted, on average, directly measured porewater MeHg concentrations to within a factor of about two. Across both sediment types, porewater MeHg alone explained ∼65% of the variability in passive sampler MeHg despite wide ranges in DOC, sulfide, iron, and salinity. These results demonstrate ag+AC EqPS can provide fine-scale porewater MeHg profiles and accurate concentration estimates across diverse sedimentary environments.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1070-1080"},"PeriodicalIF":4.4,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12947745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Information-based approach to PM2.5 estimation and air quality assessment using statistical and deep learning models","authors":"Sehrish Khan, Maqbool Ahmad, Bahadar Zeb, Shahla Nazneen, Beenish Ali, Mubarak Ahmad, Khan Alam and Allah Ditta","doi":"10.1039/D5VA00383K","DOIUrl":"https://doi.org/10.1039/D5VA00383K","url":null,"abstract":"<p >In Pakistan, Peshawar City is persistently experiencing high concentrations of fine particulate matter (PM<small>_2.5</small>), frequently surpassing national as well as international air quality standards. For this purpose, the present study aims to enhance the accuracy of PM<small>_2.5</small> estimation at the city scale through a data-driven and interdisciplinary modeling framework. To achieve this, a series of predictors, such as air pollutants (nitrogen dioxide (NO<small>₂</small>) and sulphur dioxide (SO<small>₂</small>)), meteorological conditions (temperature, wind speed, humidity), and satellite-based aerosol optical depth (AOD), were used to construct a multiple linear regression (MLR) model. Similarly, the Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) were modeled to estimate PM<small>_2.5</small> using historical ground-level PM<small>_2.5</small> data in the year 2021, leveraging their capabilities to model temporal trends. The results revealed that estimated PM<small>_2.5</small> levels using the CNN model were almost in the same range as the available measured concentrations, whereas MLR and LSTM models showed some variations against measured values. The insights about their comparative analysis showed that the CNN model could achieve better estimation than MLR and LSTM models. The CNN model achieved a root mean square error (RMSE) of 34.89 µg m<small>⁻³</small> and coefficient of determination (<em>R</em><small>²</small>) of 0.79, indicating higher estimation accuracy. Both the LSTM (<em>R</em><small>²</small> = 0.74 and RMSE = 51.93 µg m<small>⁻³</small>) and MLR (<em>R</em><small>²</small> = 0.46 and RMSE = 44.35 µg m<small>⁻³</small>) models underperformed. Based on the air quality index (AQI), the study region has experienced extremely unhealthy and healthy conditions, which may lead to the formation of visible haze and ultimately to the particulate component of smog. Generally, this study highlights the superior performance of deep learning approaches for urban air quality assessment. In conclusion, this study breaks new ground by applying and integrating MLR, CNN, and LSTM models in the study region. It will help in opening a promising direction for city-specific air quality modeling in any regional or local urban environment.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1116-1129"},"PeriodicalIF":4.4,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2026/va/d5va00383k?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147620999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metastatic impact of perfluorooctanoic acid on liver cancer: insights from HepG2 cells and zebrafish xenograft models","authors":"Kayla E. Hawn, Emma Kenyon, Gregory Buck and Wei Xu","doi":"10.1039/D5VA00491H","DOIUrl":"https://doi.org/10.1039/D5VA00491H","url":null,"abstract":"<p >Widely used in consumer products for its water- and grease-resistant properties, perfluorooctanoic acid (PFOA), a legacy per- and polyfluoroalkyl substance (PFAS), has been increasingly implicated in liver carcinogenesis. Long-term or high-level PFAS exposures have been found to be associated with an increased incidence of several types of cancers, including liver, kidney, and breast cancers. Despite mounting evidence linking PFAS exposure to hepatotoxicity and cancer, experimental models that enable real-time visualization of PFOA-induced carcinogenicity remain limited. To address this gap, we aimed to develop a liver tumor xenograft model using zebrafish (<em>Danio rerio</em>) embryos for the investigation of the carcinogenic effects of PFOA on human liver cells. To create the xenograft model with zebrafish embryos, human hepatic HepG2 cells were labeled with living cell imaging dyes and engrafted into fish embryos at one day post-fertilization. The embryos were then exposed to PFOA at concentrations of 0.1, 1.0, and 10 ppm for 24–96 hours. The <em>in vivo</em> cell proliferation was confirmed by quantifying the expression levels of a HepG2 housekeeping gene, hypoxanthine-guanine phosphoribosyltransferase 1 (hprt1). The expression profiles of two metastasis markers, <em>cdh1</em> and <em>mmp9</em>, suggested the induction of HepG2 cell metastasis by PFOA. The PFOA-triggered metastatic changes in HepG2 cells were also confirmed by the observation of cell migration inside the zebrafish embryos. Two polycyclic aromatic hydrocarbon (PAH) chemicals, anthracene and naphthalene (0.1–1.0 ppm), were used as both of them were reported to damage hepatic cells through activating the aryl hydrocarbon receptor (AhR) pathway. Although both PAH compounds altered the expression patterns of <em>cdh1</em> and <em>mmp9</em> in HepG2 cells, their capabilities to enhance the HepG2 proliferation <em>in vivo</em> were less significant compared to PFOA. The results demonstrated that prolonged chemical exposure to PFOA can promote HepG2 cell survival, proliferation, and metastasis <em>in vivo</em>. This zebrafish xenograft model provides a dependable and robust platform for mechanistic toxicology studies and is a mid-to high-throughput screening tool for environmental carcinogens and anti-cancer drug selection.</p>","PeriodicalId":72941,"journal":{"name":"Environmental science. Advances","volume":" 4","pages":" 1039-1049"},"PeriodicalIF":4.4,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2026/va/d5va00491h?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147620998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}