Emerging Pollutants in Environment: Occurrence, Monitoring, Fate and Risk Assessment

A special issue of Toxics (ISSN 2305-6304). This special issue belongs to the section "Emerging Contaminants".

Deadline for manuscript submissions: closed (20 March 2023) | Viewed by 3681

Special Issue Editor


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Guest Editor
Department of Environmental Health Sciences, School of Public Health, University at Albany, Albany, NY 12222, USA
Interests: analytical toxicology; environmental contamination; volatile and semivolatile organic compounds; steroids; illicit drugs; cannabinoids; opioids

Special Issue Information

Dear Colleagues,

In recent years, emerging contaminants (ECs), including a diverse array of pharmaceuticals, antibiotics, hormones, personal care products, synthetic dyes, industrial compounds, pesticides, and trace elements, have become environmental pollutants of concern. Many ECs and their metabolites in wastewater and surface water are refractory to current water treatment methods. The problem of ECs is ever changing, as new chemicals are continually being produced, some with adverse effects on environmental and human health, and many ultimately contaminate our environment. An example is the phasing out of legacy per- and polyfluoroalkyl substances (PFAS), which led to their replacement with GenX and other polyfluoroether acids, compounds that are now commonly found in the global environment. The extended use of pesticides, antibiotics, pharmaceuticals, and hormones in agriculture compound the problem of ECs. Analytical methods for the vast number of ECs must be sensitive, specific, robust, and versatile, and should incorporate tandem mass spectrometry often. Absorption and bioremediation are among the approaches that are in development to remove numerous ECs from water.

This Special Issue will accept original research papers, reviews, and commentaries on the problem of ECs, including on the identification of novel ECs and their sources, analytical methods for the detection and quantitation of ECs, human and ecotoxicology, risk assessment, biotransformation, and methods for the remediation and removal of ECs from water and wastewater.

Prof. Dr. David C. Spink 
Guest Editor

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Keywords

  • emerging contaminants
  • environmental contamination
  • human toxicology
  • ecotoxicology
  • risk assessment
  • bioremediation
  • environmental chemical analysis

Published Papers (2 papers)

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Research

14 pages, 1690 KiB  
Article
Ecotoxicological Differences of Antimony (III) and Antimony (V) on Earthworms Eisenia fetida (Savingy)
by Jing Bai, Dan Lu, Linyu Chen, Weiying Liu, Yu Zheng, Guohong Xiang, Guiyuan Meng, Zhong Lin and Renyan Duan
Toxics 2023, 11(3), 230; https://doi.org/10.3390/toxics11030230 - 27 Feb 2023
Cited by 1 | Viewed by 1044
Abstract
In this study, we assessed the acute and chronic toxic effects of Sb (III) and Sb (V) on Eisenia fetida (Savingy) (E. fetida) by applying the filter paper contact method, aged soil treatment, and avoidance test experiment. In the acute filter [...] Read more.
In this study, we assessed the acute and chronic toxic effects of Sb (III) and Sb (V) on Eisenia fetida (Savingy) (E. fetida) by applying the filter paper contact method, aged soil treatment, and avoidance test experiment. In the acute filter paper contact test, the LC50 values for Sb (III) were 2581 mg/L (24 h), 1427 mg/L (48 h), and 666 mg/L (72 h), which were lower than Sb (V). In the chronic aged soil exposure experiment, when the Sb (III)-contaminated soil was aged 10 d, 30 d, and 60 d after exposure for 7 d, the LC50 value of E. fetida was 370, 613, and >4800 mg/kg, respectively. Compared to Sb (V) spiked soils aged only for 10 d, the concentrations causing 50% mortality significantly increased by 7.17-fold after 14 days of exposure in soil aged for 60 d. The results show that Sb (III) and Sb (V) could cause death and directly affect the avoidance behavior of E. fetida; yet, the toxicity of Sb (III) was higher than that of Sb (V). Consistent with the decrease in water-soluble Sb, the toxicity of Sb to E. fetida was greatly reduced with time. Therefore, in order to avoid overestimating the ecological risk of Sb with varying oxidative states, it is important to consider the forms and bioavailability of Sb. This study accumulated and supplemented the toxicity data, and provided a more comprehensive basis for the ecological risk assessment of Sb. Full article
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14 pages, 2590 KiB  
Article
In Silico Prediction of the Toxicity of Nitroaromatic Compounds: Application of Ensemble Learning QSAR Approach
by Amirreza Daghighi, Gerardo M. Casanola-Martin, Troy Timmerman, Dejan Milenković, Bono Lučić and Bakhtiyor Rasulev
Toxics 2022, 10(12), 746; https://doi.org/10.3390/toxics10120746 - 01 Dec 2022
Cited by 10 | Viewed by 2236
Abstract
In this work, a dataset of more than 200 nitroaromatic compounds is used to develop Quantitative Structure–Activity Relationship (QSAR) models for the estimation of in vivo toxicity based on 50% lethal dose to rats (LD50). An initial set of 4885 molecular [...] Read more.
In this work, a dataset of more than 200 nitroaromatic compounds is used to develop Quantitative Structure–Activity Relationship (QSAR) models for the estimation of in vivo toxicity based on 50% lethal dose to rats (LD50). An initial set of 4885 molecular descriptors was generated and applied to build Support Vector Regression (SVR) models. The best two SVR models, SVR_A and SVR_B, were selected to build an Ensemble Model by means of Multiple Linear Regression (MLR). The obtained Ensemble Model showed improved performance over the base SVR models in the training set (R2 = 0.88), validation set (R2 = 0.95), and true external test set (R2 = 0.92). The models were also internally validated by 5-fold cross-validation and Y-scrambling experiments, showing that the models have high levels of goodness-of-fit, robustness and predictivity. The contribution of descriptors to the toxicity in the models was assessed using the Accumulated Local Effect (ALE) technique. The proposed approach provides an important tool to assess toxicity of nitroaromatic compounds, based on the ensemble QSAR model and the structural relationship to toxicity by analyzed contribution of the involved descriptors. Full article
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