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Environmental Behavior, Ecological Effects and Health Risks of Pollutants in...
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Environmental Behavior, Ecological Effects and Health Risks of Pollutants in Aquatic Ecosystems

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Quality and Contamination".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 5902

Special Issue Editors

Dr. Qiuheng Zhu

E-Mail Website
Guest Editor
Center for Eco-Environment Research, Nanjing Hydraulic Research Institute, Nanjing 210098, China
Interests: emerging contaminants; environmental behavior; ecotoxicology; ecological engineering; environmental remediation; environmental microorganisms; risk assessment
Special Issues, Collections and Topics in MDPI journals
Dr. Meiling Xu

E-Mail Website
Guest Editor
College of Environmental Science and Engineering, Yangzhou University, Yangzhou 225127, China
Interests: ecological effects; emerging contaminants; climate change; groundwater remediation; environmental microorganisms; environmental behavior; lysimeter study

Special Issue Information

Dear Colleagues,

This Special Issue will explore the environmental behavior of pollutants in aquatic ecosystems, the interactions between pollutants and aquatic organisms, and the environmental health risks caused by pollutants. This Special Issue will provide an in-depth and systematic interdisciplinary study and analysis of the ecological impacts of water pollutants (including aspects of environmental science and engineering, ecology, Earth science, and environmental chemistry). Studies should provide a scientific basis and theoretical support for the evaluation of the potential ecological risks of pollutants. This Special Issue will focus on the assessment of the ecological impacts of water pollutants, including (but not limited to) the following topics:

  • Assessment of nutrient elements such as carbon, nitrogen, and phosphorus;
  • Assessment of emerging contaminants, heavy metals, and toxic and hazardous substances;
  • Environmental behaviors, such as the transport and transformation of pollutants in water ecosystems;
  • The relationship between pollutant stress and aquatic ecological conditions, particularly the effects of algal blooms.

Dr. Qiuheng Zhu
Dr. Meiling Xu
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. Water is an international peer-reviewed open access semimonthly 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 2600 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

  • environmental pollutants
  • aquatic organisms
  • environmental behavior
  • water ecological effects
  • health risks

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Published Papers (5 papers)

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Research

18 pages, 9579 KiB  
Article
Remote Sensing Identification of Harmful Algae in Ulansuhai Lake with Machine Learning
by Jianglong Cui, Xiaodie Zhang, Caili Du and Guowen Li
Water 2025, 17(1), 50; https://doi.org/10.3390/w17010050 - 28 Dec 2024
Viewed by 580
Abstract
Frequent algal blooms in lakes pose a serious threat to aquatic ecosystems. It is of great significance to quickly and accurately monitor the distribution of algae in lakes for the regulation of algal blooms. While remote sensing techniques and machine learning methods can [...] Read more.
Frequent algal blooms in lakes pose a serious threat to aquatic ecosystems. It is of great significance to quickly and accurately monitor the distribution of algae in lakes for the regulation of algal blooms. While remote sensing techniques and machine learning methods can be used in combination to identify algae and analyze their spatial and temporal distribution, these methods still face challenges in practical applications due to uncertainties in lake boundaries and imbalances between algae and non-algae. In order to overcome these difficulties, we studied the dynamic open water range of Ulansuhai Lake and used a non-equilibrium data processing method to identify its algae. We also performed a spatiotemporal analysis of the algal range over a long time series. The results show that (1) the spectral characteristics of Landsat 8 images are very suitable for algal identification based on remote sensing, especially in the random forest method, where the fourth band plays an important role. (2) Among various machine learning methods, the accuracy of the random forest method on the training set and validation set is more than 90%. This indicates that the random forest method is suitable for the long-term monitoring of algal blooms. This study provides scientific and technical support for the management of Ulansuhai Lake, which will be helpful in guiding future management and control work. Full article
(This article belongs to the Special Issue Environmental Behavior, Ecological Effects and Health Risks of Pollutants in Aquatic Ecosystems)
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16 pages, 7229 KiB  
Article
How Has the Source Apportionment of Heavy Metals in Soil and Water Evolved over the Past 20 Years? A Bibliometric Perspective
by Huading Shi, Zexin He, Chenning Deng, Anfu Liu, Yao Feng, Li Li, Guohua Ji, Minghui Xie and Xu Liu
Water 2024, 16(22), 3171; https://doi.org/10.3390/w16223171 - 6 Nov 2024
Viewed by 1182
Abstract
Exploring soil heavy metal sources is of great significance for ensuring the safety of ecological environments and agricultural product safety, as well as for guiding pollution control and management policies. This paper retrieved 452 research papers on soil heavy metal source analysis published [...] Read more.
Exploring soil heavy metal sources is of great significance for ensuring the safety of ecological environments and agricultural product safety, as well as for guiding pollution control and management policies. This paper retrieved 452 research papers on soil heavy metal source analysis published over the 2004–2024 period from the Web of Science database. The collected literature was subjected to multidimensional bibliometric analysis using the CiteSpace 6.3.R1. The results showed significantly increasing trends in the scientific outputs and the number of papers on heavy metal source analysis in soils and water over the study period. In addition, related research topics have expanded from single to multiple heavy metal elements in environmental media and have increasingly recognized the impact of water pollution on soil contamination. Research methods have also evolved from basic statistical analysis to complex spatial analysis techniques, covering agricultural and urban soils. Previous related studies have focused on heavy metal pollution in different areas, and related research on heavy metal source analysis has now extended from ecological environments to associated human health risks. The present study provides directions for future related research and guidance for ensuring effective source control of heavy metal pollution and safe utilization of land and water resources. Full article
(This article belongs to the Special Issue Environmental Behavior, Ecological Effects and Health Risks of Pollutants in Aquatic Ecosystems)
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12 pages, 6472 KiB  
Article
Relationship Between Aquatic Factors and Sulfide and Ferrous Iron in Black Bloom in Lakes: A Case Study of a Eutrophic Lake in Eastern China
by Liang Wang, Changlin Xu, Hao Niu, Nian Liu, Meiling Xu, Yulin Wang and Jilin Cheng
Water 2024, 16(21), 3120; https://doi.org/10.3390/w16213120 - 1 Nov 2024
Viewed by 828
Abstract
Black bloom is a very serious water pollution phenomenon in eutrophic lakes, with Fe(II) and S(−II) being the key limiting factors for this problem. In this paper, three different machine learning methods, namely, Random Forest (RF), Gaussian Mixture Model (GMM), and Bayesian Network [...] Read more.
Black bloom is a very serious water pollution phenomenon in eutrophic lakes, with Fe(II) and S(−II) being the key limiting factors for this problem. In this paper, three different machine learning methods, namely, Random Forest (RF), Gaussian Mixture Model (GMM), and Bayesian Network (BN), were used to explore the complex interactions among Fe(II), S(−II), and other aquatic factors in the estuary of Chaohu Lake to better characterize and monitor water degradation by black bloom. The results of RF showed that total nitrogen (TN), ammonia, total phosphorous (TP), suspended sediment concentration (SSC), and oxidation–reduction potential (ORP), which were chosen from 11 factors, had the most important relationships with Fe(II) and S(−II). The 69 sampling sites were divided in three groups identified as worst, worse, and bad according to the observed values of seven factors using the GMM. Then, the BN model was applied to three observation groups. The results showed that the structures of the interaction networks were different between the groups. S(−II) controlled only SSC production in the bad and worse group sites, while SSC was determined by both S(−II) and Fe(II) in the worst group. Ammonia and TN exhibited the most direct importance for S(−II) and Fe(II) production in all observation groups. According to the indications from the BNs, potential management strategies for different water pollution conditions were developed. Finally, the threshold values of Fe(II), S(−II), TP, ammonia, TN, SSC, and ORP, which were 0.80 mg/L, 0.04 mg/L, 0.45 mg/L, 3.44 mg/L, 4.15 mg/L, 55 mg/L, and 135 mv, respectively, were determined on the basis of the BN models. These values will be helpful to develop accurate strategies of oxygenation to quickly eliminate black bloom in the lake. Full article
(This article belongs to the Special Issue Environmental Behavior, Ecological Effects and Health Risks of Pollutants in Aquatic Ecosystems)
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17 pages, 2545 KiB  
Article
Mechanisms of Irrigation Water Levels on Nitrogen Transformation and Microbial Activity in Paddy Fields
by Yunqing Fang, Jiangping Qiu and Xudong Li
Water 2024, 16(21), 3021; https://doi.org/10.3390/w16213021 - 22 Oct 2024
Viewed by 1185
Abstract
Nitrogen is a vital nutrient for rice growth; however, its inefficient use often results in nutrient loss, environmental degradation, and the emission of greenhouse gases. In this study, a rice paddy simulation was conducted under different water levels (1–4 cm), incorporating a comprehensive [...] Read more.
Nitrogen is a vital nutrient for rice growth; however, its inefficient use often results in nutrient loss, environmental degradation, and the emission of greenhouse gases. In this study, a rice paddy simulation was conducted under different water levels (1–4 cm), incorporating a comprehensive analysis of nitrogen dynamics, environmental factors, and microbial communities to evaluate the impact of water levels on nitrogen concentrations and microbial composition. The results indicated that the water level had a greater impact on nitrogen concentrations in surface water than in soil water. Compared to low water level conditions (1 cm), the average concentrations of ammonium nitrogen, nitrate nitrogen, and nitrite nitrogen in surface water under 2–4 cm water levels decreased by approximately 53.8%, 36.7%, and 78.9%, respectively. Water levels also influenced the microbial composition and nitrogen cycling in paddy soil, with lower water levels promoting aerobic processes such as nitrification, while higher water levels facilitated anaerobic processes such as denitrification and dissimilatory nitrate reduction to ammonium. Correspondingly, microbial composition shifted, with aerobic bacteria predominating in shallow water conditions and anaerobic bacteria flourishing under deeper water. These findings suggest that optimized water management, particularly through shallow irrigation, may mitigate nitrogen loss and improve nitrogen use efficiency. Nevertheless, additional field studies are necessary to validate these results and explore their interaction with other agricultural practices. Full article
(This article belongs to the Special Issue Environmental Behavior, Ecological Effects and Health Risks of Pollutants in Aquatic Ecosystems)
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18 pages, 3532 KiB  
Article
Health Risk of Heavy Metals in Drinking Water Sources of Water-Carrying Lakes Affected by Retreating Polder: A Case Study of Luoma Lake
by Jindong Wang, Xiaolong Zhu, Yicong Dai, Minyue Xu, Dongmei Wang, Yingcai Han, Wenguang Liang, Yifan Shi, Fanhao Song, Li Yao, Yiming Zhen and Qiuheng Zhu
Water 2024, 16(18), 2699; https://doi.org/10.3390/w16182699 - 23 Sep 2024
Viewed by 1715
Abstract
Heavy metal pollution is a critical issue affecting the safety of drinking water sources. However, the impact of human activities on heavy metal risk levels in water-carrying lakes remains unclear. This study aims to explore the risk mechanisms of heavy metals in Luoma [...] Read more.
Heavy metal pollution is a critical issue affecting the safety of drinking water sources. However, the impact of human activities on heavy metal risk levels in water-carrying lakes remains unclear. This study aims to explore the risk mechanisms of heavy metals in Luoma Lake, an important water-carrying lake for the South-to-North Water Diversion Project. We explored the spatial and temporal differences in the distribution of heavy metals in Lake Luoma using methods such as the heavy metal pollution index (HPI) and assessed the risk variations using a health assessment model. The results indicated that heavy metal concentrations in water-carrying lakes generally decreased during the dry season, with Mn and Zn levels decreasing by 89.3% and 56.2%, respectively. The comprehensive score of HPI decreased by 13.16% following the retreating polder compared to the control area (Non-retreating polder area). Furthermore, the HPI at the drinking water intake was lower, which is closely associated with the elevated dissolved oxygen (DO) and oxidation–reduction potential (ORP) resulting from water diversion. The annual average health risk across the entire lake was not significant, with higher levels observed in the control area. The annual non-carcinogenic risk levels of Mn, Ni, Cu, Zn, and Pb range from 10−13 to 10−9, which are considered negligible risk levels. Notably, the carcinogenic risk posed by arsenic (As) through the drinking pathway reached 10−5 a−1, exceeding the maximum levels recommended by certain organizations. These findings provide a critical foundation for managing heavy metals in water-carrying drinking water sources. Full article
(This article belongs to the Special Issue Environmental Behavior, Ecological Effects and Health Risks of Pollutants in Aquatic Ecosystems)
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