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Environments
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Environmental Risk Assessment of Aquatic Ecosystem
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Environmental Risk Assessment of Aquatic Ecosystem

A special issue of Environments (ISSN 2076-3298).

Deadline for manuscript submissions: 20 August 2024 | Viewed by 8575

Special Issue Editors

Dr. Qi Wang

E-Mail Website
Guest Editor
State Key Laboratory of Marine Pollution and Department of Chemistry, City University of Hong Kong, Hong Kong SAR, China
Interests: emerging pollutants; risk assessment; marine environment
Dr. Huiju Lin

E-Mail Website
Guest Editor
School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China
Interests: environmental analysis; wastewater; atmospheric modelling
Dr. Mengyang Liu

E-Mail Website
Guest Editor
State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong SAR, China
Interests: marine environmental chemistry; persistent organic pollutants; biogeo-chemistry

Special Issue Information

Dear Colleagues,

Aquatic ecosystems are the most diverse and important ecosystems. With the development of human society, numerous pollutants have been manufactured and released into the water environment, which could pose potential risks to aquatic ecosystems. Conducting environmental risk assessments regarding the aquatic ecosystem could avoid the adverse effects on water and prevent the irreversible damage to the aquatic ecosystems caused by human activity.

The Special Issue entitled "Environmental Risk Assessment of Aquatic Ecosystem" aims to gather the latest research, innovations, and advances in risk assessment in the aquatic environment. We welcome the submission of papers that attend to various topics of interest, including the field investigation of the occurrence and environmental behavior of pollutants in the aquatic environment, toxicokinetic and toxicology studies regarding contaminants on the aquatic species, and the potential ecological risk brought by the change in environmental factors. Additionally, submissions that consider the novel risk assessment method based on the existing database and environmental and economic impacts on the aquatic ecosystems are also welcomed.

This Special Issue will provide valuable insights into the risk assessment of aquatic ecosystems, which is a critical environmental challenge many countries worldwide face. This Issue also matches well with the UNEP Sustainable Development Goal 3: Good health and well-being, 6: Clean water and sanitation, and 14: Life below water. We invite authors to submit contributions that will enhance our understanding of the current potential risks in aquatic ecosystems.

Dr. Qi Wang 
Dr. Huiju Lin
Dr. Mengyang Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Environments is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • risk assessment
  • aquatic environment
  • pollutants
  • environmental factors
  • toxicology
  • water
  • POPs
  • health
  • emerging contaminants

Published Papers (4 papers)

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Research

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9 pages, 740 KiB  
Article
Development of an Environmental DNA Assay for Prohibited Matter Weed Amazon Frogbit (Limnobium laevigatum)
by Xiaocheng Zhu, Karen L. Bell, Hanwen Wu and David Gopurenko
Environments 2024, 11(4), 66; https://doi.org/10.3390/environments11040066 - 28 Mar 2024
Viewed by 785
Abstract
Environmental DNA (eDNA) is widely used for detecting target species, including monitoring endangered species and detecting the presence of invasive species. Detecting targeted species using the eDNA approach is typically carried out with species-specific qPCR assays. Amazon frogbit (Limnobium laevigatum) is [...] Read more.
Environmental DNA (eDNA) is widely used for detecting target species, including monitoring endangered species and detecting the presence of invasive species. Detecting targeted species using the eDNA approach is typically carried out with species-specific qPCR assays. Amazon frogbit (Limnobium laevigatum) is classified as a State-Prohibited Matter Weed in NSW, Australia. It is a fast-growing perennial aquatic weed that outcompetes native aquatic plants, leading to a reduction in the habitats of aquatic animals. Early detection is crucial for the effective management of this species. In this study, we developed a qPCR assay for L. laevigatum based on the rpoB gene sequence. This assay was validated against 25 non-target aquatic and terrestrial species. It was found to be species-specific, with the positive signal exclusively detected in L. laevigatum. The assay was highly sensitive with the modelled detection limits of 3.66 copies of DNA/µL. Furthermore, our assay was validated using environmental samples collected from field sites with and without the presence of L. laevigatum. Our assay is an effective tool for targeted eDNA detection of L. laevigatum, which will enhance efforts to monitor and control this invasive aquatic weed. Full article
(This article belongs to the Special Issue Environmental Risk Assessment of Aquatic Ecosystem)
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16 pages, 1242 KiB  
Article
A Dynamic Multiple Reaction Monitoring Analytical Method for the Determination of Fungicide Residues in Drinking Water
by Aggelos Arvanitidis, George S. Adamidis, Paraskevas Parlakidis, Georgios D. Gikas, Christos Alexoudis and Zisis Vryzas
Environments 2024, 11(1), 5; https://doi.org/10.3390/environments11010005 - 26 Dec 2023
Viewed by 1555
Abstract
The extensive use of fungicides causes their continuous release into the environment through spraying, soil seepage, leaching, and runoff. It has been observed that their residues can be found in foods and a variety of environmental compartments, such as wastewater, lakes, rivers, sediments, [...] Read more.
The extensive use of fungicides causes their continuous release into the environment through spraying, soil seepage, leaching, and runoff. It has been observed that their residues can be found in foods and a variety of environmental compartments, such as wastewater, lakes, rivers, sediments, drinking water sources (groundwater and surface water), treated water, and drinking water. A sensitive GC-MS/MS, using dynamic multiple reaction monitoring, an analytical method was developed to determine 10 fungicides (azoxystrobin, boscalid, captan, cyproconazole, cyprodinil, hexaconazole, metalaxyl, myclobutanil, paclobutrazol, and prochloraz) in drinking water. A solid-phase extraction method for sample preparations and validations was performed according to SANTE 2019 guidelines. All fungicides demonstrated mild or medium matrix effects (ME) ranging from 40.1% to 11.2%. Their recoveries ranged between 60% and 110%. The limits of detection were equal to or higher than 0.01 μg/L. The method was employed on 18 drinking water samples collected from public taps in Northern Evros, Greece, distributed in six sampling sites. Azoxystrobin, boscalid, cyproconazole, cypronidil, metalaxyl, and paclobutrazol mean concentrations did not surpass the allowable limit of 0.1 μg/L set by EU in any sampling site. Hexaconazole mean concentrations were higher than 0.1 μg/L in one sampling site, while prochloraz mean concentration showed limit exceedances in all sampling sites. Captan was not detected in any sampling site, and myclobutanil mean concentrations demonstrated exceedances of the permissible limit in four sampling sites. The presence of fungicide residues in the studied area is mainly due to the occasional point-sources pollution and preferential flow. Additionally, through the use of water, the risk of pesticides to human health was assessed for two different age groups. The sum of the hazard quotient values in each of the studied drinking water was less than unity. Consequently, the acute risk assessment procedure regards the examined drinking water as safe. Nevertheless, as prochloraz carcinogenic risk values were higher than the safe limit suggested by USEPA for both age groups, the existence of prochloraz residues raises concerns about chronic toxicity. Full article
(This article belongs to the Special Issue Environmental Risk Assessment of Aquatic Ecosystem)
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29 pages, 53471 KiB  
Article
A Deep Survey of Fish Health for the Recognition of Useful Biomarkers to Monitor Water Pollution
by Graziella Orso, Roberta Imperatore, Elena Coccia, Gianluca Rinaldi, Domenico Cicchella and Marina Paolucci
Environments 2023, 10(12), 219; https://doi.org/10.3390/environments10120219 - 11 Dec 2023
Viewed by 1890
Abstract
The aim of the present study was to evaluate the wild freshwater fish health status using a vast array of biomarkers as predictive factors of pollutant exposure. The European eel (Anguilla anguilla) and brown trout (Salmo trutta fario), resident [...] Read more.
The aim of the present study was to evaluate the wild freshwater fish health status using a vast array of biomarkers as predictive factors of pollutant exposure. The European eel (Anguilla anguilla) and brown trout (Salmo trutta fario), resident in rivers with different degrees of pollution in the South of Italy (Picentino River with good environmental quality and Tusciano River with low environmental quality), were examined using biometric parameters, histopathological and immunohistochemical biomarkers to evaluate the health status and a possible correlation with the water quality. Several alterations identified in the liver positively correlated with water and soil pollutants: hemorrhage (p ≤ 0.05), cytoplasmic vacuolization (p ≤ 0.01), hemosiderosis (p ≤ 0.05), irregular arrangement of hepatocytes (p ≤ 0.01), lipid accumulation (p ≤ 0.05), necrosis (p ≤ 0.01), cellular hyperplasia (p ≤ 0.05), leukocyte infiltration (p ≤ 0.01) and melanomacrophages centers (MMC) (p ≤ 0.01). In the spleen, only hemosiderosis correlated with water and soil pollutants (p ≤ 0.05). The inflammatory biomarker tumor necrosis factor α (TNFα) and ciclooxigenase 2 (COX2) responded to the environmental pollution, as well as the oxidative stress biomarkers superoxide dismutase (SOD2) and 8-Hydroxy-2′-deoxyguanosine (8-OHdG). Erythrocytic nuclear abnormalities and erythrocytic cellular abnormalities were found to be significantly higher in the blood of both the European eel (p < 0.0001) and brown trout (p < 0.001) in the Tusciano River compared with the Picentino River. Taken together, these results outline the need to increase the number of suitable biomarkers to assess fish health and reinforce the importance of employing additional biomarkers in biomonitoring programs that can be applied to evaluate water quality and in environmental assessment around the world. Full article
(This article belongs to the Special Issue Environmental Risk Assessment of Aquatic Ecosystem)
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Review

Jump to: Research

47 pages, 3285 KiB  
Review
Meta-Analysis of Satellite Observations for United Nations Sustainable Development Goals: Exploring the Potential of Machine Learning for Water Quality Monitoring
by Sabastian Simbarashe Mukonza and Jie-Lun Chiang
Environments 2023, 10(10), 170; https://doi.org/10.3390/environments10100170 - 02 Oct 2023
Cited by 4 | Viewed by 3398
Abstract
This review paper adopts bibliometric and meta-analysis approaches to explore the application of supervised machine learning regression models in satellite-based water quality monitoring. The consistent pattern observed across peer-reviewed research papers shows an increasing interest in the use of satellites as an innovative [...] Read more.
This review paper adopts bibliometric and meta-analysis approaches to explore the application of supervised machine learning regression models in satellite-based water quality monitoring. The consistent pattern observed across peer-reviewed research papers shows an increasing interest in the use of satellites as an innovative approach for monitoring water quality, a critical step towards addressing the challenges posed by rising anthropogenic water pollution. Traditional methods of monitoring water quality have limitations, but satellite sensors provide a potential solution to that by lowering costs and expanding temporal and spatial coverage. However, conventional statistical methods are limited when faced with the formidable challenge of conducting pattern recognition analysis for satellite geospatial big data because they are characterized by high volume and complexity. As a compelling alternative, the application of machine and deep learning techniques has emerged as an indispensable tool, with the remarkable capability to discern intricate patterns in the data that might otherwise remain elusive to traditional statistics. The study employed a targeted search strategy, utilizing specific criteria and the titles of 332 peer-reviewed journal articles indexed in Scopus, resulting in the inclusion of 165 articles for the meta-analysis. Our comprehensive bibliometric analysis provides insights into the trends, research productivity, and impact of satellite-based water quality monitoring. It highlights key journals and publishers in this domain while examining the relationship between the first author’s presentation, publication year, citation count, and journal impact factor. The major review findings highlight the widespread use of satellite sensors in water quality monitoring including the MultiSpectral Instrument (MSI), Ocean and Land Color Instrument (OLCI), Operational Land Imager (OLI), Moderate Resolution Imaging Spectroradiometer (MODIS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and the practice of multi-sensor data fusion. Deep neural networks are identified as popular and high-performing algorithms, with significant competition from extreme gradient boosting (XGBoost), even though XGBoost is relatively newer in the field of machine learning. Chlorophyll-a and water clarity indicators receive special attention, and geo-location had a relationship with optical water classes. This paper contributes significantly by providing extensive examples and in-depth discussions of papers with code, as well as highlighting the critical cyber infrastructure used in this research. Advances in high-performance computing, large-scale data processing capabilities, and the availability of open-source software are facilitating the growing prominence of machine and deep learning applications in geospatial artificial intelligence for water quality monitoring, and this is positively contributing towards monitoring water pollution. Full article
(This article belongs to the Special Issue Environmental Risk Assessment of Aquatic Ecosystem)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Development of environmental DNA assays for two aquatic weeds Amazon frogbit (Limnobium laevigatum) and yellow burrhead (Limnocharis flava)

Authors: Xiaocheng Zhu; Karen Bell; Hanwen Wu and David Gopurenko 

Abstract: Environmental DNA (eDNA) is widely used for species monitoring, including endanger species monitoring and invasive species detection. Targeted species detection using eDNA approach usually conducted with species-specific qPCR assays. Amazon frogbit (Limnobium laevigatum) and yellow burrhead (Limnocharis flava) are listed as State Prohibited Matter weeds in NSW, Australia. They are fast-growing perennial aquatic weeds that outcompete native aquatic plants and reduce habitats of aquatic animals. Early detection is the key for management of these species. In this study, we have developed two assays for Limnobium laevigatum and Limnocharis flava based on rpoB and rpoC2 sequences, respectively. Both assays were validated against 34 co-existing aquatic and terrestrial species. The assays were species specific, and the positive signal was exclusively detected in the targeted species. The assays are highly sensitive with the detection limits of 1 copy DNA/µL. These two assays were also validated against environmental samples where the weeds are present. Our assays are effective tools for targeted aquatic weed detection, which will likely be adopted for Limnobium laevigatum and Limnocharis flava monitoring and management.

Keywords: prohibited matter weed; eDNA; biosecurity; quantitative PCR; aquatic weed;

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