Environmental science. Advances最新文献

Stormwater ponds (SWPs) alter the export of the macronutrient phosphorus (P) from urban landscapes, hence impacting the trophic state and water quality of downstream aquatic environments. Despite an increasing number of studies reporting P load reduction by SWPs, the mechanisms responsible for P retention remain unclear. We analyzed P chemical speciation and fluxes in the inflow and outflow of a SWP in the Toronto metropolitan area. In addition, we collected sediment cores to determine under what forms P accumulates in the SWP. The resulting P mass balance for the SWP yielded an average annual retention of 62% for total P (TP). Retention efficiencies varied significantly among the various TP fractions, however: 53% for particulate P (PP), 67% for total dissolved P (TDP), 66% for dissolved unreactive P (DUP), and >80% for dissolved reactive P (DRP), with DRP representing the most bioavailable TP fraction. Sequential chemical extractions performed on the sediment cores indicate that, with increasing sediment depth, the concentration of mineral-bound P increases while that of organic P decreases. We therefore attribute the efficient retention of DRP to biosynthesis of P-containing organic compounds followed by their post-depositional degradation and sequestration of the released phosphate ions by in situ precipitation of inorganic phases, primarily calcium (Ca) minerals. The conditions in the SWP are favorable to the formation of common Ca minerals, such as hydroxyapatite and calcite, including near-neutral to moderately alkaline pH values and high dissolved Ca²⁺ concentrations. In areas where urban runoff does not meet these conditions, interventions that stimulate P-containing mineral formation in SWPs may help reduce the export of DRP, hence, protecting receiving water bodies from eutrophication.

Nitrophenol wastewater treatment and extracting and reusing precious metals from electronic wastewater have recently gained considerable attention. In this study, polyaniline-based membranes showcased remarkable gold recovery capability from electronic wastewater, effectively reclaiming 100% of gold on the membrane surface even in the presence of competing metal cations. The prepared Au@PmPD membrane, characterized by its high specific surface area and abundant Au nanoparticles (NPs), demonstrated excellent catalytic activity and stability, maintaining near 100% conversion efficiency in reducing 4-NP to 4-AP in the presence of NaBH₄ over extended durations. Compared with the conventional physical mixing method, our in situ formation of the Au@PmPD membrane highlights the superior distribution of Au NPs and active sites for enhanced catalytic efficiency. It eliminates the need for additional steps to load Au NPs onto the membrane, resulting in a more straightforward and efficient process. Overall, this research provides a sustainable approach to repurposing waste into precious resources and offers a promising solution for the efficient treatment of persistent organic pollutants in wastewater, aligning with the principles of a circular economy.

Polycyclic aromatic hydrocarbons (PAHs) pose health risks to children, potentially resulting in stunted growth, obesity, and cognitive deficits, but lack of reliable and noninvasive means to measure PAHs results in poor understanding of exposure patterns and sources in this vulnerable population. In this study, 24 children aged ∼7 years (9 boys and 15 girls) from Montevideo, Uruguay wore silicone wristbands for 8 days to monitor the exposure of 27 PAHs. Wristbands were extracted using a modified ethyl acetate tandem solid phase extraction clean up and then analyzed via gas chromatography with tandem mass spectrometry. This analysis has reported LODs for 27 PAHs between 0.05 and 3.91 μg L⁻¹. Eighteen PAHs were detected in >50% of the samples with concentration medians ranging 1.2–16.3 ng g⁻¹ of wristband. Low molecular weight PAHs (2–3 rings) such as naphthalene and its alkyl derivatives were highly correlated (0.7–0.9) in the wristbands, suggesting exposure from related sources. Exposure source exploration focused on secondhand tobacco smoke, potentially through caregivers who reported on smoking habits in an associated survey. A principal components analysis (PCA) was conducted to examine patterns in PAH compounds detected in the wristbands; subsequently, the resulting components were compared according to current smoking among caregivers. The PCA analysis revealed a grouping of participants based on higher exposure of 1-methyl naphthalene, pyrene, fluoranthene, 1-methylphenanthrene, dibenzothiophene and 2-phenyl naphthalene. The derived components did relate with parental smoking, suggesting that some participants experienced exposure to a common source of certain PAHs outside of parental smoking. This is the first study to assess PAH exposure in young children from South America. Using wristbands, our study indicates exposure to multiple, potentially harmful chemicals. Wristbands could provide a comprehensive picture of PAH exposure in children, complementing other non-invasive biomonitoring approaches.

Organisms and humans are exposed to a “cocktail” of contaminants in the environment, but methods for mixture assessment, untargeted analysis, and source identification (fingerprinting) are still lagging, which is critically reviewed in this article. Firstly, this paper briefly summarized both the direct and indirect effects of chemical contaminants at multiple levels on the biological responses of wild organisms. Secondly, the choice of a predictive model for chemical mixture assessment can greatly influence the outcome. Therefore, this review emphasizes the limitation of the main methodologies of risk assessments for chemical mixtures. Thirdly, since current environmental toxicology approaches face barriers to realizing the true potential of advances in analytical chemistry for human health or ecology risk assessment, bioanalytical methods, to screen toxic chemicals or identify unknown chemicals at environmentally relevant levels are reviewed. Lastly, Recently developed machine learning models, incorporating non-targeted screening analysis for the suspect and unknown chemicals and machine learning methods, can be trained on complex datasets to better predict interactions among identified chemicals with random combinations, quantification of similar structural chemicals without the presence of analytical standards, and transfer of chemicals based on their physicochemical properties in human tissues. To perform risk assessments for a variety of chemicals, we propose employing a framework that makes use of a range of methods from the toolbox summarized in this review.

Optically active components, namely marine chromophoric DOM (CDOM) and fluorescent DOM (FDOM), have been used as proxies for refractory DOM (RDOM) in the world's oceans, and numerous studies using ultrahigh resolution mass spectrometry (HRMS) approaches have supplied a tremendous amount of data on the chemical complexity and diversity of DOM. Here, we collected and analyzed high-resolution depth profiles of DOM throughout the water column in the North Atlantic Gyre at the Bermuda Atlantic Time-series Study (BATS) station in August 2019 and in the North Pacific Gyre at station ALOHA (A Long-term Oligotrophic Habitat Assessment) used by the Hawaii Ocean Time-series (HOT) in July 2021. Water samples were collected at 200 m depth intervals from 4530 m at BATS and 4700 m at ALOHA up to the surface and DOM was isolated by solid-phase extraction (SPE). Parallel factor analysis modeled EEM fluorescence revealed changes of “humic-like” and “protein-like” FDOM (FDOM_H and FDOM_P, respectively) in SPE-DOM throughout the water column with higher fluorescence intensities present at ALOHA. Dissolved organic phosphorous (DOP) and dissolved organic sulfur (DOS) concentrations were always higher in SPE-DOM at BATS than at ALOHA, except for DOP in the surface at ALOHA. Negative mode electrospray ionization (ESI) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) data also revealed fundamental differences between BATS and ALOHA. A novel machine learning algorithm (SOFAR) was implemented and revealed much higher overall oxygen to carbon (O/C) ratio molecular signatures at BATS as the major difference and also much more DOS signatures at BATS when compared to ALOHA. Furthermore, we extracted for the first-time weak anion exchange (WAX) amendable DOM, and the results also showed drastic differences between the two stations. The optical and FT-ICR MS data, converged and supported the idea that DOM in the Atlantic and Pacific basins are fundamentally different when looked at through these analytical windows, at least at these long-term monitoring stations. This finding suggests that the marine DOM is likely turning over at different rates at ALOHA versus BATS and that geographical differences in DOM composition are likely a compounding factor in DOM reactivity.

In this research, activated carbon (AC) was prepared from date seed (DS) biomass using a chemical activation method for the removal of the Bismarck Brown R (BBR) dye and zinc metal ions from water. As-prepared AC was characterized using thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and Brunauer–Emmett–Teller (BET) analysis for understanding the porous carbon surface and pore structure, which are essential properties for removing organic and inorganic pollutants. DSs are complex and were selected to prepare AC as they can yield hard activated carbon and perform better in packed-bed and fluidized-bed adsorption columns. AC samples were prepared at different soaking temperatures, specifically at 45 °C, 55 °C, and 65 °C, and subsequently tested for the removal of both the BBR dye and Zn ions. Various parameters were studied to complete the batch adsorption process, including solution pH, initial concentration (BBR: 100–500 mg L⁻¹; Zn ions: 10–50 mg L⁻¹), contact time (0–240 min), and temperature (30–60 °C). The maximum monolayer adsorption capacity for BBR and Zn metal ions were found to be 192.31 mg g⁻¹ and 15.55 mg g⁻¹, respectively. The data was most accurately described by the pseudo-second-order and Elovich kinetics models. Analysis using the particle diffusion model indicated that both film-diffusion and pore-diffusion mechanisms governed adsorption. Thermodynamic assessments revealed the endothermic behavior of BBR dye adsorption and the exothermic behavior of Zn metal ion adsorption.

Concerns over environmental impacts resulting from the use of zinc oxide containing medicines for weaning piglets led to the withdrawal of the authorisations for these products in the EU. In order to better understand these issues more detailed assessments were conducted for the UK, taking account of the fate of zinc in the environment and its bioavailability to ecological receptors. Four regional scenarios covered the main pig farming areas in the UK and the emission scenario was based on current agricultural practices in the UK. The fate and transport of zinc in the environment was modelled using the Intermediate Dynamic Model for Metals, and the toxicity of zinc in the environment was assessed based on current UK regulatory practices. The model takes account of historic additions of metals to the soils to calculate current and future metal levels in the environment. Whilst three of the four regional scenarios predicted a marginal risk, or no risk, to soils after 50 years of use one of the scenarios indicated a risk to surface waters prior to the use of zinc oxide medicated treatments for weaning piglets, and risks to local soils within 10 years of use. Further site-specific assessments were conducted for this region and one of the other regions, based on site specific emission scenarios, soil and surface waters characteristics. These two site-specific assessments revealed that the modelling results were accurate or conservative depending on the assumptions made about historic inputs of metals to agricultural soils from manure spreading, and that the regional scenario that resulted in significant predicted risks to surface waters did not reflect the actual conditions at the local pig farming sites considered. Comparisons between measured concentrations of copper and zinc at pig farming sites suggest that historic agricultural inputs have been an important source of these metals to agricultural soils at some sites. The limited data available for validation suggest that the IDMM is able to provide accurate predictions of metal levels in both soils and surface waters, but that there is significant uncertainty associated with historic inputs of metals to the soils.

Air pollution is a major risk factor for neurological disorders. Both indoor and outdoor dusts comprise different types of iron oxides in the nano-scale range. Due to their small size and unique physico-chemical properties, iron oxide nanoparticles (IONPs) adopt the intracellular path to agglomerate inside the cell cytoplasm. Moreover, they can cross the blood–brain barrier to invade cortical tissues in the brain and impair neuronal functions. Hence, analysis of the effects of IONPs on the Central Nervous System (CNS) structure and functions is indispensable from medical perspective. A literature search was performed using three scientific databases: ScienceDirect, PubMed, and Google Scholar. Articles published till December, 2023 were screened for their relevancy. Analyses of the appropriate literature have revealed that IONPs are being employed in drug delivery systems and diagnosis of CNS-related ailments that favor neuroprotection. However, the inhalation of IONPs from air and other sources can lead to excessive accumulation of iron in the neuronal tissues, leading to a disturbance in neuronal signaling and augmenting the onset of neurodegenerative disorders. Therefore, it is essential to monitor and control the abundance of IONPs in the environment to combat adverse impacts on the human nervous system.

Poly- and perfluoroalkyl substances are a ubiquitous class of compounds which are considered persistent organic pollutants. Many of these compounds are unregulated and understudied but are still widely used. One group of these compounds are fluorotelomer ethoxylates, which recently emerged as compounds of interest following their detection in the environment. To determine the health impacts of these persistent compounds, healthy pregnant CD-1 mice were exposed to 0 ng L⁻¹ (n = 8), 5 ng L⁻¹ (n = 8), or 100 ng L⁻¹ (n = 7) fluorotelomer ethoxylates in drinking water throughout gestation. At gestational day 17.5 (term is 18.5 days), high-frequency ultrasound was performed to investigate the placental and fetal hemodynamic responses following exposure. Maternal exposure to fluorotelomer ethoxylates showed evidence of placental insufficiency, with a significant increase in placental weights (p < 0.05), a decrease in the umbilical artery blood flow (p < 0.01) and vasodilation of the cerebral circulation (p < 0.01), consistent with brain sparing to preserve oxygen delivery to the brain. These results demonstrate that fluorotelomer ethoxylates cause developmental toxicity and motivate further work to evaluate the risk to human pregnancies and other vulnerable populations.

Humans and other living species of the ecosystem are constantly exposed to a wide range of chemicals of natural as well as synthetic origin. A multitude of compounds exert profound long-term detrimental health effects. The chronic toxicity profile of chemicals is of utmost importance for long-term risk assessment. Experimental testing of the chronic toxicity of compounds is not always a feasible option considering the magnitude of the number of chemicals, resource intensiveness in terms of time, limited availability of experimental data, and associated cost, which therefore necessitates the use of in silico approaches to overcome the associated limitations. In this work, QSAR (quantitative structure–activity relationship) models were developed employing the regression-based PLS method with strict adherence to OECD guidelines. For this study, chronic and sub-chronic toxicity datasets with LOEL (lowest observed effect levels) and NOEL (no observed effect level) as endpoints were used for model development. The validated models are robust, reliable, and predictable. The statistical results of the models are as follows: R²: 0.6–0.71, Q_LOO²: 0.51–0.635, and Q_F1²: 0.52–0.658. From the validated models, it was concluded that lipophilicity, electronegativity, the presence of aromatic ethers or aliphatic oxime groups, the presence of complexity in structures, the state of unsaturation in molecules, and the presence of halogen and heavy atoms (phosphate, sulphur, etc.) are responsible for chronic/sub-chronic toxicity. The QSAR models developed in our study can be utilized for the effective gap-filling of toxicity data sets, categorization, and prioritization of chemicals, along with chronic toxicity prediction of new synthetic compounds. Furthermore, we used 2568 approved drugs from the DrugBank and PPDB databases for screening purposes using the validated models, which further corroborated the developed models based on the available toxicity data.