David Lutes, Andrew Boyd, Lachlan J. Jekimovs, Brett R. Hamilton, Jochen F. Mueller, Richard Arnseth, Ian Ross, Jinxia Liu
The widespread use of aqueous film-forming foams (AFFFs) in firefighting has led to significant contamination by per- and polyfluoroalkyl substances (PFAS), including in building materials like concrete. This study investigated the initial phase of PFAS contamination in concrete, focusing on factors influencing PFAS retention and penetration. Laboratory experiments assessed the uptake kinetics of PFAS into concrete over one year, revealing that PFAS penetrated beyond surface layers, as confirmed by high-resolution mass spectrometry and desorption electrospray ionization mass spectrometry imaging. PFAS mass loss into the concrete was limited, with 0.99% to 18.5% (mean 6.6%) of initial spiked PFAS being retained. Uptake behaviors were influenced by PFAS chain length and chemistry, concrete surface characteristics, as well as wetting/drying cycles, which accelerated PFAS penetration through the wick effect. Damaged concrete surfaces also showed faster PFAS penetration due to the exposed interfacial transition zones. Field-impacted concrete samples from Canada revealed some similar migration trends with lab-exposed concrete, with shorter-chain PFAS exhibiting greater mobility in the concrete matrix, though notable differences were observed between field and lab samples. These findings highlight the complex dynamics of PFAS contamination in concrete and provide insights into factors affecting PFAS penetration and retention.
{"title":"Uptake of Per- and Polyfluoroalkyl Substances into Concrete from Aqueous Film-Forming Foams: Experimental Investigations and Comparison to Field-Impacted Samples","authors":"David Lutes, Andrew Boyd, Lachlan J. Jekimovs, Brett R. Hamilton, Jochen F. Mueller, Richard Arnseth, Ian Ross, Jinxia Liu","doi":"10.1021/acs.est.4c12878","DOIUrl":"https://doi.org/10.1021/acs.est.4c12878","url":null,"abstract":"The widespread use of aqueous film-forming foams (AFFFs) in firefighting has led to significant contamination by per- and polyfluoroalkyl substances (PFAS), including in building materials like concrete. This study investigated the initial phase of PFAS contamination in concrete, focusing on factors influencing PFAS retention and penetration. Laboratory experiments assessed the uptake kinetics of PFAS into concrete over one year, revealing that PFAS penetrated beyond surface layers, as confirmed by high-resolution mass spectrometry and desorption electrospray ionization mass spectrometry imaging. PFAS mass loss into the concrete was limited, with 0.99% to 18.5% (mean 6.6%) of initial spiked PFAS being retained. Uptake behaviors were influenced by PFAS chain length and chemistry, concrete surface characteristics, as well as wetting/drying cycles, which accelerated PFAS penetration through the wick effect. Damaged concrete surfaces also showed faster PFAS penetration due to the exposed interfacial transition zones. Field-impacted concrete samples from Canada revealed some similar migration trends with lab-exposed concrete, with shorter-chain PFAS exhibiting greater mobility in the concrete matrix, though notable differences were observed between field and lab samples. These findings highlight the complex dynamics of PFAS contamination in concrete and provide insights into factors affecting PFAS penetration and retention.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"52 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546060","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}
Wietse Wiersma, Elise van Eynde, Rob N. J. Comans, Jan E. Groenenberg
Geochemical multisurface models and their generic parameters for the solid-solution partitioning and speciation of metals have been used for decades. For soils the collective uncertainty and sensitivity of model parameters and soil-specific reactive surface properties has been insufficiently evaluated. We used statistical tools and data of diverse soils to quantify for Cd, Cu and Zn the uncertainty of model parameters and input values of the nonideal competitive adsorption (NICA)-Donnan model for organic matter (OM) coupled with the generalized two-layer model for metal-oxides. Subsequently, we quantified the uncertainty of speciation predictions and the sensitivity to model parameters and input values. Importantly, we established new generic NICA-Donnan parameters that substantially improved model accuracy, especially for Zn. Uncertainties generally followed Cu < Cd < Zn. With OM being the major binding surface across most soils, the affinity parameters (log Ki) were most influential. Compared to a “best-case” scenario with all relevant soil properties measured, a “simplified” scenario with assumptions about OM fractionation and metal-oxide specific surface area could be employed with a negligible effect on model accuracy and uncertainty. Our study provides a reference work with quantitative measures of model performance, which facilitates broader adoption of mechanistic multisurface models in addressing environmental challenges.
{"title":"Quantifying the Accuracy, Uncertainty, and Sensitivity of Soil Geochemical Multisurface Models","authors":"Wietse Wiersma, Elise van Eynde, Rob N. J. Comans, Jan E. Groenenberg","doi":"10.1021/acs.est.4c04812","DOIUrl":"https://doi.org/10.1021/acs.est.4c04812","url":null,"abstract":"Geochemical multisurface models and their generic parameters for the solid-solution partitioning and speciation of metals have been used for decades. For soils the collective uncertainty and sensitivity of model parameters and soil-specific reactive surface properties has been insufficiently evaluated. We used statistical tools and data of diverse soils to quantify for Cd, Cu and Zn the uncertainty of model parameters and input values of the nonideal competitive adsorption (NICA)-Donnan model for organic matter (OM) coupled with the generalized two-layer model for metal-oxides. Subsequently, we quantified the uncertainty of speciation predictions and the sensitivity to model parameters and input values. Importantly, we established new generic NICA-Donnan parameters that substantially improved model accuracy, especially for Zn. Uncertainties generally followed Cu < Cd < Zn. With OM being the major binding surface across most soils, the affinity parameters (log <i>K</i><sub><i>i</i></sub>) were most influential. Compared to a “best-case” scenario with all relevant soil properties measured, a “simplified” scenario with assumptions about OM fractionation and metal-oxide specific surface area could be employed with a negligible effect on model accuracy and uncertainty. Our study provides a reference work with quantitative measures of model performance, which facilitates broader adoption of mechanistic multisurface models in addressing environmental challenges.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"16 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560775","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}
Marek Let, Kateřina Grabicová, Paride Balzani, Martin Musil, Sara Roje, Martin Bláha
The bioaccumulation of 80 pharmaceutically active compounds (PhACs) was examined in larvae, pupae, and (sub)adults of three groups of aquatic insects (caddisflies Oligotricha striata and Limnephilus spp. and mayfly Siphlonurus aestivalis) reared in laboratory conditions, with their larvae exposed to a treated urban wastewater for up to 3 months and fed with uncontaminated food. The probability of PhAC detection (above limits of quantification) in larvae was relatively constant throughout the exposure time, while in adults, it was lower at the beginning with a subsequent increase. The total concentration of detected PhACs was highest in larvae of Limnephilus spp. and lowest in larvae of S. aestivalis, decreasing similarly in the adults of all three species. Significant differences in the composition of PhACs with different levels of changes after emergence were detected between species. Only telmisartan was detected in all species and life stages. Sertraline and its active metabolite norsertraline exhibited significantly higher relative concentrations in caddisfly adults compared to larvae. Apart from the bioconcentration factor, increasing biodegradation half-life was the second-best predictor of increased PhAC concentration in adults compared to larvae. At the same time, log Kow, commonly associated with bioaccumulation, was not found to be a good predictor of this relationship. The present study provides valuable insights into the bioaccumulation patterns and potential transfer of PhACs from aquatic to terrestrial ecosystems.
{"title":"Bioaccumulation of Pharmaceutically Active Compounds from Treated Urban Wastewaters in Aquatic Insect Larvae and Aerial Adults","authors":"Marek Let, Kateřina Grabicová, Paride Balzani, Martin Musil, Sara Roje, Martin Bláha","doi":"10.1021/acs.est.4c13781","DOIUrl":"https://doi.org/10.1021/acs.est.4c13781","url":null,"abstract":"The bioaccumulation of 80 pharmaceutically active compounds (PhACs) was examined in larvae, pupae, and (sub)adults of three groups of aquatic insects (caddisflies <i>Oligotricha striata</i> and <i>Limnephilus</i> spp. and mayfly <i>Siphlonurus aestivalis</i>) reared in laboratory conditions, with their larvae exposed to a treated urban wastewater for up to 3 months and fed with uncontaminated food. The probability of PhAC detection (above limits of quantification) in larvae was relatively constant throughout the exposure time, while in adults, it was lower at the beginning with a subsequent increase. The total concentration of detected PhACs was highest in larvae of <i>Limnephilus</i> spp. and lowest in larvae of <i>S. aestivalis</i>, decreasing similarly in the adults of all three species. Significant differences in the composition of PhACs with different levels of changes after emergence were detected between species. Only telmisartan was detected in all species and life stages. Sertraline and its active metabolite norsertraline exhibited significantly higher relative concentrations in caddisfly adults compared to larvae. Apart from the bioconcentration factor, increasing biodegradation half-life was the second-best predictor of increased PhAC concentration in adults compared to larvae. At the same time, log Kow, commonly associated with bioaccumulation, was not found to be a good predictor of this relationship. The present study provides valuable insights into the bioaccumulation patterns and potential transfer of PhACs from aquatic to terrestrial ecosystems.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"86 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560782","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}
Endocrine-disrupting chemicals (EDCs) can interfere with multiple pathways and trigger different modes of action. Thus, the traditional EDC in vitro screening processes often require a battery of bioassays to cover multiple target pathways. Here we developed an endocrine-enhanced reduced human transcriptome (ERHT) focused on hormone receptor signaling induced by the EDCs regulating specific genes. ERHT was developed based on 1200 prioritized genes covering 110 endocrine-related biological pathways across eight potential adverse outcomes. The ability of this approach to identify EDCs was derived from machine learning of 1068 dose-dependent transcriptome profiles and enhanced by quantifying chemical-induced critical pathway responses, and thus, it demonstrated excellent classification performance (AUC = 0.84 ± 0.03) in internal cross-validation. We ultimately applied this approach to known EDCs and inactive substances to validate the reliability of this approach. Through external validation on 210 chemicals, the extrapolation accuracy exceeded 80%, demonstrating the outstanding practical performance of this approach. Meanwhile, the pathway responses induced by the same chemical were consistent with the experimental results reported by multiple sequencing platforms, highlighting the robustness of this approach. The above results demonstrate that this approach can provide novel insights for EDCs’ high-throughput screening and comprehensive toxic mechanisms through biological pathways.
{"title":"Novel Approach to Screen Endocrine-Disrupting Chemicals via Endocrine-Enhanced Reduced Human Transcriptome","authors":"Tianle Fan, Tianhao Han, Aoran Gu, Jinsha Jin, Qian Cui, Jing Guo, Xiaowei Zhang, Hongxia Yu, Wei Shi","doi":"10.1021/acs.est.4c13159","DOIUrl":"https://doi.org/10.1021/acs.est.4c13159","url":null,"abstract":"Endocrine-disrupting chemicals (EDCs) can interfere with multiple pathways and trigger different modes of action. Thus, the traditional EDC in vitro screening processes often require a battery of bioassays to cover multiple target pathways. Here we developed an endocrine-enhanced reduced human transcriptome (ERHT) focused on hormone receptor signaling induced by the EDCs regulating specific genes. ERHT was developed based on 1200 prioritized genes covering 110 endocrine-related biological pathways across eight potential adverse outcomes. The ability of this approach to identify EDCs was derived from machine learning of 1068 dose-dependent transcriptome profiles and enhanced by quantifying chemical-induced critical pathway responses, and thus, it demonstrated excellent classification performance (AUC = 0.84 ± 0.03) in internal cross-validation. We ultimately applied this approach to known EDCs and inactive substances to validate the reliability of this approach. Through external validation on 210 chemicals, the extrapolation accuracy exceeded 80%, demonstrating the outstanding practical performance of this approach. Meanwhile, the pathway responses induced by the same chemical were consistent with the experimental results reported by multiple sequencing platforms, highlighting the robustness of this approach. The above results demonstrate that this approach can provide novel insights for EDCs’ high-throughput screening and comprehensive toxic mechanisms through biological pathways.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"29 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546059","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}
Natalie Szponar, Claudia M. Vega, Jacqueline Gerson, David Scott McLagan, Martin Pillaca, Shamir Delgado, Domenica Lee, Nabila Rahman, Luis E. Fernandez, Emily S. Bernhardt, Adam M. Kiefer, Carl P. J. Mitchell, Frank Wania, Bridget A. Bergquist
Artisanal and small-scale gold mining (ASGM) is one of the largest primary sources of mercury (Hg) pollution in the atmosphere globally; however, there is a paucity of atmospheric Hg data in ASGM areas. We measured atmospheric gaseous elemental mercury (GEM) concentrations and stable Hg isotopes at fine spatial resolution in the Madre de Dios region of Peru, where ASGM is a major source of Hg. This study employed new passive air samplers that overcome logistical challenges in measuring atmospheric Hg in remote locations. Regional GEM concentrations were elevated (∼1.3 to 11 ng m–3) compared to the background (<1 ng m–3), with very high GEM levels (∼10 to >5000 ng m–3) associated with mining areas and gold shops. Because ASGM-derived GEM is isotopically distinct, its contribution to regional and local atmospheric Hg was estimated using an isotope mixing model and found to be generally over 70%. We also show that vegetation is taking up ASGM-derived GEM, affecting both the concentrations and isotope compositions of GEM as well as in foliage and litter samples. This supports vegetation uptake as a key removal process of GEM from the atmosphere and therefore a major source of Hg to terrestrial ecosystems and soils, which is heightened in ASGM regions.
{"title":"Tracing Atmospheric Mercury from Artisanal and Small-Scale Gold Mining","authors":"Natalie Szponar, Claudia M. Vega, Jacqueline Gerson, David Scott McLagan, Martin Pillaca, Shamir Delgado, Domenica Lee, Nabila Rahman, Luis E. Fernandez, Emily S. Bernhardt, Adam M. Kiefer, Carl P. J. Mitchell, Frank Wania, Bridget A. Bergquist","doi":"10.1021/acs.est.4c10521","DOIUrl":"https://doi.org/10.1021/acs.est.4c10521","url":null,"abstract":"Artisanal and small-scale gold mining (ASGM) is one of the largest primary sources of mercury (Hg) pollution in the atmosphere globally; however, there is a paucity of atmospheric Hg data in ASGM areas. We measured atmospheric gaseous elemental mercury (GEM) concentrations and stable Hg isotopes at fine spatial resolution in the Madre de Dios region of Peru, where ASGM is a major source of Hg. This study employed new passive air samplers that overcome logistical challenges in measuring atmospheric Hg in remote locations. Regional GEM concentrations were elevated (∼1.3 to 11 ng m<sup>–3</sup>) compared to the background (<1 ng m<sup>–3</sup>), with very high GEM levels (∼10 to >5000 ng m<sup>–3</sup>) associated with mining areas and gold shops. Because ASGM-derived GEM is isotopically distinct, its contribution to regional and local atmospheric Hg was estimated using an isotope mixing model and found to be generally over 70%. We also show that vegetation is taking up ASGM-derived GEM, affecting both the concentrations and isotope compositions of GEM as well as in foliage and litter samples. This supports vegetation uptake as a key removal process of GEM from the atmosphere and therefore a major source of Hg to terrestrial ecosystems and soils, which is heightened in ASGM regions.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"67 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560776","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}
Gabrielle P. Black, Berkley N. Anderson, Luann Wong, Christopher P. Alaimo, Guochun He, Michael S. Denison, Deborah H. Bennett, Daniel Tancredi, Blythe Durbin-Johnson, Bruce D. Hammock, Pujeeta Chowdhary, Rainbow Rubin, Thomas M. Young
To explore the hypothesis that differential exposures to estrogen active chemicals may contribute to regional disparities in cancer incidence, a comprehensive targeted and nontargeted analysis was conducted over two seasons (2020) for drinking water samples from 120 households served by 8 public water systems (4 with historically elevated breast cancer incidence) and from 15 brands of retail water. All samples were analyzed using gas and liquid chromatography with high-resolution mass spectrometry and a bioassay for estrogen receptor agonism. Target compounds included disinfection byproducts, per- and polyfluoroalkyl substances (PFAS), trace elements, and compounds selected for their possible relation to breast cancer. Over 7500 GC and LC nontargeted molecular features passed all quality control filters in each sampling season and were prioritized for identification if they were related to measured estrogen receptor agonism or were present at higher levels in areas with high breast cancer incidence (n = 1036). Benzothiazole-2-sulfonic acid, acetyl tributyl citrate, and diphenyl sulfone were among the prioritized and confirmed nontarget compounds. Nine polycyclic aromatic hydrocarbons and two ketone derivatives displayed significant negative correlations with estrogen receptor agonism. Many prioritized compounds remained unidentified, as 84.4% of the LC features and 77.5% of the GC features could not be annotated with high confidence.
{"title":"Comprehensive Nontargeted Analysis of Drinking Water Supplies to Identify Chemicals Associated with Estrogen Receptor Agonism or Present in Regions of Elevated Breast Cancer Occurrence","authors":"Gabrielle P. Black, Berkley N. Anderson, Luann Wong, Christopher P. Alaimo, Guochun He, Michael S. Denison, Deborah H. Bennett, Daniel Tancredi, Blythe Durbin-Johnson, Bruce D. Hammock, Pujeeta Chowdhary, Rainbow Rubin, Thomas M. Young","doi":"10.1021/acs.est.4c12204","DOIUrl":"https://doi.org/10.1021/acs.est.4c12204","url":null,"abstract":"To explore the hypothesis that differential exposures to estrogen active chemicals may contribute to regional disparities in cancer incidence, a comprehensive targeted and nontargeted analysis was conducted over two seasons (2020) for drinking water samples from 120 households served by 8 public water systems (4 with historically elevated breast cancer incidence) and from 15 brands of retail water. All samples were analyzed using gas and liquid chromatography with high-resolution mass spectrometry and a bioassay for estrogen receptor agonism. Target compounds included disinfection byproducts, per- and polyfluoroalkyl substances (PFAS), trace elements, and compounds selected for their possible relation to breast cancer. Over 7500 GC and LC nontargeted molecular features passed all quality control filters in each sampling season and were prioritized for identification if they were related to measured estrogen receptor agonism or were present at higher levels in areas with high breast cancer incidence (<i>n</i> = 1036). Benzothiazole-2-sulfonic acid, acetyl tributyl citrate, and diphenyl sulfone were among the prioritized and confirmed nontarget compounds. Nine polycyclic aromatic hydrocarbons and two ketone derivatives displayed significant negative correlations with estrogen receptor agonism. Many prioritized compounds remained unidentified, as 84.4% of the LC features and 77.5% of the GC features could not be annotated with high confidence.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"6 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143545909","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}
Haojie Shen, Yuqi Zhou, Jiahui Lin, Yu Huang, Zhongmin Dai, Saiqi Zeng, Yong Li, Randy A. Dahlgren, Jianming Xu
Frequent wildfires pose a serious threat to carbon (C) dynamics of forest ecosystems under a warming climate. Yet, how wildfires alter the temperature sensitivity (Q10) of soil heterotrophic respiration (Rh) as a critical parameter determining the C efflux from burned landscapes remains unknown. We conducted a field survey and two confirmatory experiments in two fire-prone regions of China at <1, 3, 6, and 12 months after wildfires (n = 160 soil samples). We found that wildfire generally reduced the Q10 for soil organic and mineral horizons within the first year after wildfire mainly due to substrate depletion, which was confirmed by a uniform inoculation experiment. Mineral protection of organic matter in the mineral horizon rich in iron/aluminum (hydr)oxides and a near-neutral pH in organic horizons of postfire soils further suppressed the Q10. Decreased Q10 persisted in organic horizons even after removing substrate limitation, reflecting the dominance of a thermally adapted, r-strategist microbial community in postfire soils. Moreover, fire-induced low C quality increased Q10, which supported the C quality-temperature hypothesis, but a C-limited condition restricted this stimulatory effect. This study illustrates that a thermal compensatory response of Rh will help maintain C stocks in forest ecosystems after wildfires in a warming world.
{"title":"Thermal Compensatory Response of Soil Heterotrophic Respiration Following Wildfire","authors":"Haojie Shen, Yuqi Zhou, Jiahui Lin, Yu Huang, Zhongmin Dai, Saiqi Zeng, Yong Li, Randy A. Dahlgren, Jianming Xu","doi":"10.1021/acs.est.4c11833","DOIUrl":"https://doi.org/10.1021/acs.est.4c11833","url":null,"abstract":"Frequent wildfires pose a serious threat to carbon (C) dynamics of forest ecosystems under a warming climate. Yet, how wildfires alter the temperature sensitivity (<i>Q</i><sub>10</sub>) of soil heterotrophic respiration (<i>R</i><sub>h</sub>) as a critical parameter determining the C efflux from burned landscapes remains unknown. We conducted a field survey and two confirmatory experiments in two fire-prone regions of China at <1, 3, 6, and 12 months after wildfires (<i>n</i> = 160 soil samples). We found that wildfire generally reduced the <i>Q</i><sub>10</sub> for soil organic and mineral horizons within the first year after wildfire mainly due to substrate depletion, which was confirmed by a uniform inoculation experiment. Mineral protection of organic matter in the mineral horizon rich in iron/aluminum (hydr)oxides and a near-neutral pH in organic horizons of postfire soils further suppressed the <i>Q</i><sub>10</sub>. Decreased <i>Q</i><sub>10</sub> persisted in organic horizons even after removing substrate limitation, reflecting the dominance of a thermally adapted, r-strategist microbial community in postfire soils. Moreover, fire-induced low C quality increased <i>Q</i><sub>10</sub>, which supported the C quality-temperature hypothesis, but a C-limited condition restricted this stimulatory effect. This study illustrates that a thermal compensatory response of <i>R</i><sub>h</sub> will help maintain C stocks in forest ecosystems after wildfires in a warming world.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"11 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560779","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}
Pharmaceuticals and their transformation products (TPs) in wastewater are emerging contaminants that pose risks to ecosystems and human health. Here, a typical period marked by the easing of the “zero-COVID” policy in December 2022, resulting in unprecedented infections in China, was chosen to illustrate the environmental impact of pharmaceutical usage during the COVID-19 pandemic. A suspect screening workflow was developed to identify pharmaceuticals and transformation products (TPs) in wastewater influent and effluent from a wastewater treatment plant (WWTP) during the peak and postpeak periods of COVID-19, integrating medication recommendations and TPs’ prediction. A total of 114 pharmaceuticals and TPs were identified (13 TPs were detected for the first time in WWTP) by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). Wastewater-based epidemiology analysis showed that the most predominant pharmaceuticals were nonsteroidal anti-inflammatory drugs. Interestingly, the consumption of propafenone increased after the infection peak, possibly linked to long COVID-19 symptoms. Risks were further evaluated based on concentration, detection frequency, and PMT (persistence, mobility, and toxicity) properties, revealing that TPs of aminopyrine, acetaminophen, etc. showed even greater ToxPi scores than their parent compounds. This study highlights the elevated risks posed by pharmaceutical discharge during epidemics and the necessity for TPs’ monitoring.
{"title":"Suspect Screening of Pharmaceuticals and Their Transformation Products (TPs) in Wastewater during COVID-19 Infection Peak: Identification of New TPs and Elevated Risks","authors":"Lihua Yu, Yongfeng Lin, Jingjing Li, Chunyan Deng, Rui Zhang, Aifeng Liu, Ling Wang, Yiling Li, Xiaoran Wei, Dawei Lu, Wei Gao, Yuxin Zheng","doi":"10.1021/acs.est.5c00125","DOIUrl":"https://doi.org/10.1021/acs.est.5c00125","url":null,"abstract":"Pharmaceuticals and their transformation products (TPs) in wastewater are emerging contaminants that pose risks to ecosystems and human health. Here, a typical period marked by the easing of the “zero-COVID” policy in December 2022, resulting in unprecedented infections in China, was chosen to illustrate the environmental impact of pharmaceutical usage during the COVID-19 pandemic. A suspect screening workflow was developed to identify pharmaceuticals and transformation products (TPs) in wastewater influent and effluent from a wastewater treatment plant (WWTP) during the peak and postpeak periods of COVID-19, integrating medication recommendations and TPs’ prediction. A total of 114 pharmaceuticals and TPs were identified (13 TPs were detected for the first time in WWTP) by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). Wastewater-based epidemiology analysis showed that the most predominant pharmaceuticals were nonsteroidal anti-inflammatory drugs. Interestingly, the consumption of propafenone increased after the infection peak, possibly linked to long COVID-19 symptoms. Risks were further evaluated based on concentration, detection frequency, and PMT (persistence, mobility, and toxicity) properties, revealing that TPs of aminopyrine, acetaminophen, etc. showed even greater ToxPi scores than their parent compounds. This study highlights the elevated risks posed by pharmaceutical discharge during epidemics and the necessity for TPs’ monitoring.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"24 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546062","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}
Estuarine and bay environments, which can act as sediment traps along the inner parts of continental shelves, may host significant depositional hotspots for plastic debris. This research targets Texas coastal bays (Matagorda and San Antonio), to better understand microplastic contamination in sediments and provide insight into the processes controlling its distribution. Microplastic extraction and quantification methods employed include sediment sieving, elutriation, microscopy, and spectroscopy. This study found low concentrations (ca. 10s–100s particles kilogram–1 sediment or 20–200 × 104 items meter–3 wet sediment) and negligible correlations between analyzed deposit constituents (R2 for grain size = −0.14 to 0.12, organic content = 0.08, water depth = −0.11, distance to shore = −0.14). The highly dynamic role of wind-driven mixing and openness to the Gulf of Mexico leads to the high flushing rate of sediment and microplastics out of the bays. Larger microplastic particles (fragments: 178 ± 93 μm, fibers: 0.5 to 2.0 mm) were consistently deposited with finer sediments, indicating high transportability. Microplastic resuspension into bay waters has significant implications for limiting microplastic accumulation within bay sediments. This work provides a baseline for future studies quantifying the roles of wind and residence time on microplastics in coastal environments.
{"title":"Microplastics in Bays along the Central Texas Coast","authors":"William S. Bailey, Cornel Olariu, David Mohrig","doi":"10.1021/acs.est.4c12622","DOIUrl":"https://doi.org/10.1021/acs.est.4c12622","url":null,"abstract":"Estuarine and bay environments, which can act as sediment traps along the inner parts of continental shelves, may host significant depositional hotspots for plastic debris. This research targets Texas coastal bays (Matagorda and San Antonio), to better understand microplastic contamination in sediments and provide insight into the processes controlling its distribution. Microplastic extraction and quantification methods employed include sediment sieving, elutriation, microscopy, and spectroscopy. This study found low concentrations (ca. 10s–100s particles kilogram<sup>–1</sup> sediment or 20–200 × 10<sup>4</sup> items meter<sup>–3</sup> wet sediment) and negligible correlations between analyzed deposit constituents (<i>R</i><sup>2</sup> for grain size = −0.14 to 0.12, organic content = 0.08, water depth = −0.11, distance to shore = −0.14). The highly dynamic role of wind-driven mixing and openness to the Gulf of Mexico leads to the high flushing rate of sediment and microplastics out of the bays. Larger microplastic particles (fragments: 178 ± 93 μm, fibers: 0.5 to 2.0 mm) were consistently deposited with finer sediments, indicating high transportability. Microplastic resuspension into bay waters has significant implications for limiting microplastic accumulation within bay sediments. This work provides a baseline for future studies quantifying the roles of wind and residence time on microplastics in coastal environments.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"30 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560780","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}
Yunyi Zhu, Yuan Wang, Elisabeth Zhu, Zeyu Ma, Hanchen Wang, Chunsheng Chen, Jing Guan, T. David Waite
Membrane fouling remains a significant challenge in the operation of membrane bioreactors (MBRs). Plant operators rely heavily on observations of filtration performance from noisy sensor data to assess membrane fouling conditions and lab-based protocols for plant maintenance, often leading to inaccurate estimations of future performance and delayed membrane cleaning. This challenge is further compounded by the difficulty in integrating existing complex mechanistic models with the Internet of Things (IoT) systems of wastewater treatment plants (WWTPs). By harnessing data obtained from WWTPs, along with innovative data denoising and model training strategies, we developed a machine learning application (MBR-Net) that is capable of forecasting membrane fouling, as indicated by permeability, for a full-scale submerged MBR plant in real time. We show that the trained model can effectively predict one-day-ahead changes in irreversible fouling under different desired fluxes, cleaning conditions and feedwater conditions (with MAPE < 6.45%, MAE < 3.71 LMH bar–1, and R2 > 0.87 on two independent testing sets). Although data availability presented certain limitations in the model development process, the current results demonstrate the significant value of machine learning in membrane fouling predictions and in providing decision support for fouling mitigation strategies in full-scale WWTPs.
{"title":"Predicting Membrane Fouling of Submerged Membrane Bioreactor Wastewater Treatment Plants Using Machine Learning","authors":"Yunyi Zhu, Yuan Wang, Elisabeth Zhu, Zeyu Ma, Hanchen Wang, Chunsheng Chen, Jing Guan, T. David Waite","doi":"10.1021/acs.est.4c12835","DOIUrl":"https://doi.org/10.1021/acs.est.4c12835","url":null,"abstract":"Membrane fouling remains a significant challenge in the operation of membrane bioreactors (MBRs). Plant operators rely heavily on observations of filtration performance from noisy sensor data to assess membrane fouling conditions and lab-based protocols for plant maintenance, often leading to inaccurate estimations of future performance and delayed membrane cleaning. This challenge is further compounded by the difficulty in integrating existing complex mechanistic models with the Internet of Things (IoT) systems of wastewater treatment plants (WWTPs). By harnessing data obtained from WWTPs, along with innovative data denoising and model training strategies, we developed a machine learning application (MBR-Net) that is capable of forecasting membrane fouling, as indicated by permeability, for a full-scale submerged MBR plant in real time. We show that the trained model can effectively predict one-day-ahead changes in irreversible fouling under different desired fluxes, cleaning conditions and feedwater conditions (with MAPE < 6.45%, MAE < 3.71 LMH bar<sup>–1</sup>, and <i>R</i><sup>2</sup> > 0.87 on two independent testing sets). Although data availability presented certain limitations in the model development process, the current results demonstrate the significant value of machine learning in membrane fouling predictions and in providing decision support for fouling mitigation strategies in full-scale WWTPs.","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"47 1","pages":""},"PeriodicalIF":9.028,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560781","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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