The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering

Topic Information

Dear Colleagues,

In the face of escalating global climate change and the urgent need to achieve the United Nation’s Global Sustainable Development Goals (SDGs), the imperative for effective pollution control engineering has never been more pressing. The proliferation of various environmental pollutants, including natural pollutants from diverse sources, and the emergence of new contaminants underscore the complexity of the challenge. These pollutants interact dynamically with diverse environmental media, altering their toxicity, migration patterns, and transformation pathways, and posing multifaceted risks to the ecosystems and human health.

To address these challenges comprehensively, a concerted effort is required to advance environmental pollutant removal technologies. Conventional physical and chemical treatments must be augmented by cutting-edge approaches like nanotechnology, photocatalysis, and electrochemical remediation, offering more efficient and sustainable solutions. Furthermore, harnessing the potential of bioremediation and phytoremediation techniques can facilitate the degradation or sequestration of pollutants, contributing to environmental cleanup efforts.

However, effective pollution control extends beyond technological interventions alone. Integrating ecological protection and environmental restoration strategies is essential to mitigate the long-term impacts of pollution on biodiversity, ecosystem services, and natural habitats. This necessitates holistic approaches that consider not only pollutant removal but also habitat restoration, biodiversity conservation, and ecosystem resilience enhancement.

This topic seeks to delve into the intricate interplay between anthropic and natural pollutants, exploring the latest research findings, innovative technologies, and emerging trends in pollution control engineering. By fostering interdisciplinary collaboration and knowledge exchange, it aims to catalyze transformative solutions that safeguard the environment, promote sustainable development, and ensure the well-being of present and future generations.

We welcome all studies considering the monitoring of inland water quality and ecological status, including but not limited to the following: Agrochemicals; Environments; Water; Toxics; Soil Systems; Microplastics; Microorganisms; Sustainability.

Dr. Chenyang Zhang
Dr. Fujing Pan
Dr. Xiaoyu Gao
Prof. Dr. Weiqi Fu
Dr. Anxu Sheng
Dr. Zhiqiang Kong
Topic Editors

Dr. Lei He
Dr. Sining Zhong
Dr. Jie Chen
Co-Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Agrochemicals agrochemicals	-	-	2022	16.7 Days	CHF 1000	Submit
Environments environments	3.5	5.7	2014	22.8 Days	CHF 1800	Submit
Water water	3.0	5.8	2009	17.5 Days	CHF 2600	Submit
Toxics toxics	3.9	4.5	2013	18.3 Days	CHF 2600	Submit
Soil Systems soilsystems	2.9	5.3	2017	39.7 Days	CHF 1800	Submit
Microplastics microplastics	-	-	2022	27.5 Days	CHF 1000	Submit
Microorganisms microorganisms	4.1	7.4	2013	11.7 Days	CHF 2700	Submit
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400	Submit

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Published Papers (9 papers)

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All Agrochemicals Environments Water Toxics Soil Systems Microplastics Microorganisms Sustainability

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16 pages, 5717 KiB  

Open AccessArticle

Effects of Polystyrene Microplastic Exposure on Liver Cell Damage, Oxidative Stress, and Gene Expression in Juvenile Crucian Carp (Carassius auratus)

by Xiangtong Li, Yuequn Huang, Wenrong Li, Chaoyang Deng, Weiyuan Cao and Yi Yao

Toxics 2025, 13(1), 53; https://doi.org/10.3390/toxics13010053 - 12 Jan 2025

Viewed by 566

Abstract

A considerable quantity of microplastic debris exists in the environment and the toxicity of these materials has a notable impact on aquatic ecosystems. In this paper, 50–500 µm polystyrene microplastics (exposure concentrations were 200 µg/L, 800 µg/L, and 3200 µg/L concentrations) were selected [...] Read more.

A considerable quantity of microplastic debris exists in the environment and the toxicity of these materials has a notable impact on aquatic ecosystems. In this paper, 50–500 µm polystyrene microplastics (exposure concentrations were 200 µg/L, 800 µg/L, and 3200 µg/L concentrations) were selected to study the effects of polystyrene microplastics (PS-MPs) on cell morphology, detoxification enzyme activity, and mRNA expression in the liver tissues of crucian carp juveniles. The results demonstrated that: (1) Different concentrations of PS-MPs cause varying degrees of pathological and oxidative damage to liver tissue cells of crucian carp. The higher the concentration of microplastics, the lower the antioxidant enzyme (CAT, GST, SOD) activity and the greater the tissue cell damage. These results demonstrate a typical dose–effect relationship. (2) Principal component analysis and Spearman’s correlation analysis demonstrated that four components, namely glutathione S-transferase (GST) and its related genes (GSTpi, GSTα), along with catalase (CAT), contributed the most to the observed outcome. These four components demonstrated a relatively high level of responsiveness to PS-MP exposure and can be employed as ecotoxicological indicators of microplastics. (3) This experiment evaluated five genes in three treatments, which found that PS-MPs had different effects on gene expression in the liver and the tested genes were involved in different response pathways associated with virulence. In this study, the toxicity of PS-MPs to crucian carp was determined at the cellular, protein, and mRNA expression levels, and combined with principal component analysis and correlation analysis to identify response sensitivity indicators that provide a scientific basis for ecological risk assessment and the safe use of microplastics. Full article

(This article belongs to the Topic The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering)

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Figure 1

Figure 1
<p>Cellular morphology of liver tissue of juvenile crucian carp after 32 d of stress by PS-MPs: (<b>a</b>) blank control group; (<b>b</b>) low-concentration group; (<b>c</b>) medium-concentration group; (<b>d</b>) high-concentration group (Black arrows indicate cell congestion, red arrows indicate vacuolated cells, green arrows indicate off-center nuclei, and blue arrows indicate enlarged necrotic cells, Picture magnification is 40×).</p> Full article ">Figure 2
<p>Changes in antioxidant enzymes in liver tissues of juvenile crucian carp after 32 d of exposure to PS-MPs: (<b>a</b>) superoxide dismutase (SOD) activity, (<b>b</b>) glutathione S-transferase (GST) activity, (<b>c</b>) catalase (CAT) activity, (<b>d</b>) malondialdehyde (MDA) content. “*” indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05) and “**” indicates a highly significant difference (<span class="html-italic">p</span> &lt; 0.01).</p> Full article ">Figure 2 Cont.
<p>Changes in antioxidant enzymes in liver tissues of juvenile crucian carp after 32 d of exposure to PS-MPs: (<b>a</b>) superoxide dismutase (SOD) activity, (<b>b</b>) glutathione S-transferase (GST) activity, (<b>c</b>) catalase (CAT) activity, (<b>d</b>) malondialdehyde (MDA) content. “*” indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05) and “**” indicates a highly significant difference (<span class="html-italic">p</span> &lt; 0.01).</p> Full article ">Figure 3
<p>Changes in mRNA expression of antioxidant-related genes in liver tissues of juvenile crucian carp after 32 d of PS-MP exposure. “*” indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05) and “**” indicates a highly significant difference (<span class="html-italic">p</span> &lt; 0.01).</p> Full article ">Figure 4
<p>Principal component analysis of antioxidant enzymes and related genes in liver tissue of juvenile crucian carp after 32 d of PS-MP exposure.</p> Full article ">Figure 5
<p>Heatmap of correlation analysis of antioxidant enzymes and related genes in liver tissues of juvenile crucian carp after 32 d of PS-MP exposure. “*” indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05) and “**” indicates a highly significant difference (<span class="html-italic">p</span> &lt; 0.01).</p> Full article ">Figure 6
<p>Relationship between antioxidant enzymes and corresponding genes in juvenile crucian carp liver tissues after 32 d of PS-MP exposure: (<b>a</b>) Relationship between GST enzyme activity and <span class="html-italic">GSTpi</span> gene expression; (<b>b</b>) Relationship between GST enzyme activity and <span class="html-italic">GSTα</span> gene expression.</p> Full article ">Figure 7
<p>Trends of mRNA expression of antioxidant-related genes in liver tissues of juvenile crucian carp after 32 d of PS-MP exposure.</p> Full article ">

16 pages, 4538 KiB  

Open AccessArticle

Methodology for Analysis of Microplastics in Fine Fraction of Urban Solid Waste

by Katia Paola Avila-Escobedo, Karen Yazmín Moctezuma-Parra, Juan Carlos Alvarez-Zeferino, Rosa María Espinosa-Valdemar, Perla Xochitl Sotelo-Navarro, Alethia Vázquez-Morillas and Arely Areanely Cruz-Salas

Microplastics 2025, 4(1), 2; https://doi.org/10.3390/microplastics4010002 - 4 Jan 2025

Viewed by 1129

Abstract

This study addresses the pressing need for standardized methodologies to quantify microplastics (MPs) within the fine fraction of municipal solid waste (MSW), often overlooked despite its potential environmental impact. Five extraction protocols were evaluated to identify the most effective method for isolating MPs [...] Read more.

This study addresses the pressing need for standardized methodologies to quantify microplastics (MPs) within the fine fraction of municipal solid waste (MSW), often overlooked despite its potential environmental impact. Five extraction protocols were evaluated to identify the most effective method for isolating MPs in fine waste. These were specifically applied to samples from the Universidad Autónoma Metropolitana and one transfer station in Mexico City. A potassium hydroxide digestion protocol with subsequent flotation and centrifugation steps achieved optimal results, ensuring complete organic matter degradation and high microplastic recovery. Subsequent analyses revealed notable concentrations of MPs, primarily fragments and fibers, with higher abundance at the university site. Statistical tests confirmed significant differences between the sample sites. These findings highlight the vulnerability of MSW fine fractions to microplastic contamination and underline the importance of targeted waste management strategies. This research contributes to understanding microplastic behavior in waste management systems and emphasizes the need for mitigation efforts to prevent environmental contamination. Full article

(This article belongs to the Topic The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering)

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<p>The proportion of different urban solid waste at the two study sites. SMW ¹ = special management waste.</p> Full article ">Figure 2
<p>Box-and-whisker diagram of the four sampled sites. The vertical blue line inside the box represents the median, while the red cross is the mean. Data outside the graph represents outliers.</p> Full article ">Figure 3
<p>Box-and-whisker diagram for the abundance of microplastics in the fine fraction of the two sampled sites. The vertical blue line inside the box represents the median, while the red cross is the mean. Data outside the graph represents outliers.</p> Full article ">Figure 4
<p>Classification of microplastics: (<b>a</b>) size in millimeters, (<b>b</b>) shape, (<b>c</b>) color, and (<b>d</b>) polymer.</p> Full article ">Figure 5
<p>Examples of microplastics from TESPA 1.</p> Full article ">Figure 6
<p>Examples of microplastics from (<b>a</b>) TESPA 2, (<b>b</b>) UAM-A 1, and (<b>c</b>) UAM-A 2.</p> Full article ">

18 pages, 6313 KiB  

Open AccessArticle

Water Quality Characteristics and Seasonal Changes in Wastewater Treatment in the Southern Hebei Region by Branch

by Chao Qu, Weiyuan Cao, Kun Dong, Dunqiu Wang and Yi Yao

Toxics 2025, 13(1), 8; https://doi.org/10.3390/toxics13010008 - 25 Dec 2024

Viewed by 368

Abstract

This study analyzed three years of data (2021–2024) from three wastewater treatment plants (WWTPs), namely D, X, and T, in the main urban area of Handan, a typical city in the southern Hebei region, and investigated the influent characteristics and impact of temperature [...] Read more.

This study analyzed three years of data (2021–2024) from three wastewater treatment plants (WWTPs), namely D, X, and T, in the main urban area of Handan, a typical city in the southern Hebei region, and investigated the influent characteristics and impact of temperature on these wastewater treatment facilities. With 90% assurance, the overall influent conditions of the three WWTPs in this region were normal. However, Plant T operated more effectively with slightly lower BOD₅/COD_Cr (B/C), organic carbon/total phosphorus (C/TP), and organic carbon/total nitrogen (C/TN) ratios in the influent. Plant D consistently met the Level A standard, Plant X essentially reached the Level A standard, while Plant T attained the Level 2 standard prior to its upgrade. Following the upgrade, Plant T also steadily met the Level A standard. The effluent from all plants was relatively stable, primarily influenced by the influent characteristics and slightly influenced by temperature, but without having a noticeable impact on the effluent quality. Full article

(This article belongs to the Topic The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering)

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Figure 1
<p>Operating process of the three wastewater treatment plants.</p> Full article ">Figure 2
<p>Analysis of influent and effluent characteristics in three wastewater treatment plants ((<b>a</b>) Cumulative probability and distribution characteristics of influent BOD₅; (<b>b</b>) cumulative probability and distribution characteristics of influent COD_Cr; (<b>c</b>) temporal variation in influent and effluent BOD₅; (<b>d</b>) temporal variation in influent and effluent COD_Cr; (<b>e</b>) characteristics of influent B/C, C/TN, and C/TP ratios).</p> Full article ">Figure 2 Cont.
<p>Analysis of influent and effluent characteristics in three wastewater treatment plants ((<b>a</b>) Cumulative probability and distribution characteristics of influent BOD₅; (<b>b</b>) cumulative probability and distribution characteristics of influent COD_Cr; (<b>c</b>) temporal variation in influent and effluent BOD₅; (<b>d</b>) temporal variation in influent and effluent COD_Cr; (<b>e</b>) characteristics of influent B/C, C/TN, and C/TP ratios).</p> Full article ">Figure 2 Cont.
<p>Analysis of influent and effluent characteristics in three wastewater treatment plants ((<b>a</b>) Cumulative probability and distribution characteristics of influent BOD₅; (<b>b</b>) cumulative probability and distribution characteristics of influent COD_Cr; (<b>c</b>) temporal variation in influent and effluent BOD₅; (<b>d</b>) temporal variation in influent and effluent COD_Cr; (<b>e</b>) characteristics of influent B/C, C/TN, and C/TP ratios).</p> Full article ">Figure 3
<p>Analysis of influent and effluent characteristics in three wastewater treatment plants ((<b>a</b>) Cumulative probability and distribution characteristics of influent NH₄⁺-N; (<b>b</b>) cumulative probability and distribution characteristics of influent TN; (<b>c</b>) temporal variation in influent and effluent NH₄⁺-N; (<b>d</b>) temporal variation in influent and effluent TN).</p> Full article ">Figure 3 Cont.
<p>Analysis of influent and effluent characteristics in three wastewater treatment plants ((<b>a</b>) Cumulative probability and distribution characteristics of influent NH₄⁺-N; (<b>b</b>) cumulative probability and distribution characteristics of influent TN; (<b>c</b>) temporal variation in influent and effluent NH₄⁺-N; (<b>d</b>) temporal variation in influent and effluent TN).</p> Full article ">Figure 4
<p>Cumulative probability and distribution characteristics of influent SSs and TP in three wastewater treatment plants in Handan’s main urban area ((<b>a</b>) Cumulative probability and distribution characteristics of influent SSs; (<b>b</b>) cumulative probability and distribution characteristics of influent TP; (<b>c</b>) temporal variation in influent and effluent SSs; (<b>d</b>) temporal variation in influent and effluent TP).</p> Full article ">Figure 4 Cont.
<p>Cumulative probability and distribution characteristics of influent SSs and TP in three wastewater treatment plants in Handan’s main urban area ((<b>a</b>) Cumulative probability and distribution characteristics of influent SSs; (<b>b</b>) cumulative probability and distribution characteristics of influent TP; (<b>c</b>) temporal variation in influent and effluent SSs; (<b>d</b>) temporal variation in influent and effluent TP).</p> Full article ">Figure 5
<p>Correlation analysis of water in and out of three sewage treatment plants ((<b>a</b>) Plant D 2021–2024; (<b>b</b>) Plant X 2021–2024; (<b>c</b>) Plant X 2023; (<b>d</b>) Plant T 2021–2024; (<b>e</b>) Plant T 2023).</p> Full article ">Figure 5 Cont.
<p>Correlation analysis of water in and out of three sewage treatment plants ((<b>a</b>) Plant D 2021–2024; (<b>b</b>) Plant X 2021–2024; (<b>c</b>) Plant X 2023; (<b>d</b>) Plant T 2021–2024; (<b>e</b>) Plant T 2023).</p> Full article ">

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17 pages, 6721 KiB  

Open AccessArticle

Planted Citrus Regulates the Community and Networks of phoD-Harboring Bacteria to Drive Phosphorus Availability Between Karst and Non-Karst Soils

by Xuan Yu, Lulu Feng, Yuan Huang, Yueming Liang, Fujing Pan, Wei Zhang, Yuan Zhao and Yuexin Xiao

Microorganisms 2024, 12(12), 2582; https://doi.org/10.3390/microorganisms12122582 - 13 Dec 2024

Viewed by 503

Abstract

The phosphorus (P) availability in soils is influenced by microbes, particularly those containing the gene responsible for phosphate solubilization. The present study investigated the community structure, diversity, and co-occurrence networks of phoD-harboring bacteria in karst and non-karst citrus orchard soils across a [...] Read more.

The phosphorus (P) availability in soils is influenced by microbes, particularly those containing the gene responsible for phosphate solubilization. The present study investigated the community structure, diversity, and co-occurrence networks of phoD-harboring bacteria in karst and non-karst citrus orchard soils across a planting duration gradient, natural forests, and abandoned land, as well as the soil total P (TP) and available P (AP) contents and enzyme activities. The soil AP contents were lower in the karst regions than in the non-karst regions, while the soil organic carbon (C; SOC), exchangeable calcium, and microbial biomass nitrogen (N) contents; alkaline phosphatase (ALP) and β-Glucuronidase activities; and pH had the opposite trends. In addition, the soil AP and SOC contents and the ALP and acid phosphatase (ACP) activities in the karst regions decreased with an increase in the planting years, whereas the AP, TP, and microbial biomass P contents and ACP activities in the non-karst regions increased. The diversity indices and network complexity of phoD-harboring bacteria were higher in the karst regions than in the non-karst regions, with marked community differences between different planting years in the non-karst regions. The soil AP was significantly and positively correlated with the rare genera Pelagicola, Methylobacter, Streptomyces, and Micromonospora in the karst regions and Roseivivax, Collimonas, Methylobacterium, Ralstonia, and Phyllobacterium in the non-karst regions. Structural Equation Modeling showed that citrus cultivation altered the soil pH, SOC, and total N, and, in turn, the phoD-harboring bacterial community structure and diversity, which led to changes in the ALP activity and P availability. Thus, the rare genera of the phoD-harboring bacteria, influenced by the pH and SOC, highly regulated the availability of P in the karst and non-karst citrus orchard soils. Full article

(This article belongs to the Topic The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering)

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Figure 1
<p>Citrus sampling sites in karst and non-karst regions of Guilin, southwestern China.</p> Full article ">Figure 2
<p>The contents of soil organic carbon (SOC) (<b>a</b>), total P (TP) (<b>b</b>), microbial biomass P (MBP) (<b>c</b>), available P (AP) (<b>d</b>), as well as the activities of alkaline phosphatase (ALP) (<b>e</b>) and acid phosphatase (ACP) (<b>f</b>), in citrus orchards of different cultivation ages in the karst and non-karst regions. Different capital and lowercase letters indicate significant differences between different citrus plantation ages in karst and non-karst regions (<span class="html-italic">p</span> &lt; 0.05), respectively. NF, natural forest; AL, abandoned land; Y5, 5-years planting; Y10, 10-years planting; Y15, 15-years planting.</p> Full article ">Figure 3
<p>The relative abundance of <span class="html-italic">phoD</span>-harboring bacteria at order (<b>a</b>) and genus (<b>b</b>) levels in citrus orchards of different ages within karst and non-karst regions. NF, natural forest; AL, abandoned land; Y5, 5-years planting; Y10, 10-years planting; Y15, 15-years planting.</p> Full article ">Figure 4
<p>PCoA showed <span class="html-italic">phoD</span>-harboring bacterial community differed at different planting ages of citrus orchards in karst and non-karst regions. NF, natural forest; AL, abandoned land; Y5, 5-years planting; Y10, 10-years planting; Y15, 15-years planting.</p> Full article ">Figure 5
<p>The Richness (<b>a</b>), Chao 1 (<b>b</b>), Simpson (<b>c</b>), Shannon-Wiener (<b>d</b>), and Evenness (<b>e</b>) indices of the <span class="html-italic">phoD</span>-harboring bacteria in different planting ages of the citrus orchards in the karst and non-karst regions. Different capital and lowercase letters indicate significant differences between the different planting ages in the karst and non-karst regions (<span class="html-italic">p</span> &lt; 0.05), respectively. NF, natural forest; AL, abandoned land; Y5, 5-years planting; Y10, 10-years planting; Y15, 15-years planting.</p> Full article ">Figure 6
<p>Co-occurrence networks of the soil <span class="html-italic">phoD</span>-harboring bacterial community at the genus level in the karst (<b>a</b>) and non-karst (<b>b</b>) regions. A red line indicates a positive relation, and a green line indicates a negative relation.</p> Full article ">Figure 7
<p>Relationships between the relative abundance of bacterial communities and the soil physicochemical parameters in the karst (<b>a</b>) and non-karst (<b>b</b>) ecosystems using the Mantel test.</p> Full article ">Figure 8
<p>Ranking of important factors affecting available phosphorus (<b>a</b>,<b>b</b>) and <span class="html-italic">phoD</span>-harboring bacteria composition (<b>c</b>,<b>d</b>) in karst (<b>a</b>,<b>c</b>) and non-karst (<b>b</b>,<b>d</b>). ** <span class="html-italic">p</span> &lt; 0.01; * <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 9
<p>Correlation network between the <span class="html-italic">phoD</span>-harboring bacteria at the genus level and the soil P fractions and phosphatase activities. A green edge represents a negative interaction between two nodes, while a red edge represents a positive interaction between two nodes. (<b>a</b>) Karst; (<b>b</b>) non-karst.</p> Full article ">Figure 10
<p>The relative abundance of <span class="html-italic">phoD</span>-harboring bacteria at order (<b>a</b>) and genus (<b>b</b>) levels in citrus orchards of different ages within karst and non-karst regions. *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01; * <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">

15 pages, 3825 KiB  

Open AccessArticle

Rapid Screening of Etomidate and Its Analogs in Seized e-Liquids Using Thermal Desorption Electrospray Ionization Coupled with Triple Quadrupole Mass Spectrometry

by Meng Li, Bicheng Lin and Binling Zhu

Toxics 2024, 12(12), 884; https://doi.org/10.3390/toxics12120884 - 5 Dec 2024

Viewed by 673

Abstract

The growing popularity of e-cigarettes has raised significant concerns about the safety and potential abuse of these products. Compounds originally used in the medical field, such as etomidate, metomidate, and isopropoxate, have been illegally added to e-liquids, posing substantial risks to consumer health, [...] Read more.

The growing popularity of e-cigarettes has raised significant concerns about the safety and potential abuse of these products. Compounds originally used in the medical field, such as etomidate, metomidate, and isopropoxate, have been illegally added to e-liquids, posing substantial risks to consumer health, and facilitating the misuse of illicit drugs. To address these concerns, this study developed a rapid and efficient method for detecting etomidate, metomidate, and isopropoxate in e-liquids using thermal desorption electrospray ionization coupling triple quadrupole mass spectrometry (TD-ESI/MS/MS). The TD-ESI/MS/MS method exhibits high sensitivity, with detection limits for etomidate, metomidate, and isopropoxate reaching 3 ng/mL. Screening of 70 seized e-liquid samples from 12 cases using TD-ESI/MS/MS revealed that 46 samples contained only etomidate, 13 samples contained only isopropoxate, and 11 samples contained both etomidate and metomidate. The qualitative results obtained from TD-ESI/MS/MS were in complete agreement with those of GC-MS. Moreover, the TD-ESI/MS/MS method requires no pre-treatment steps and has a detection time of only 1 min, thereby saving experimental consumables and significantly reducing detection time. The method demonstrated high sensitivity, accuracy, and reproducibility, making it suitable for high-throughput screening in forensic and regulatory settings. Full article

(This article belongs to the Topic The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic diagram of the rapid screening of etomidate and its analogs in e-liquid by TD-ESI/MS/MS: (<b>a</b>,<b>b</b>) sampling, (<b>c</b>) TD-ESI-MS analysis.</p> Full article ">Figure 2
<p>MRM chromatograms of blank e-liquid samples (<b>a</b>–<b>c</b>), blank e-liquid samples added with 100 ng/mL etomidate (<b>d</b>), metomidate (<b>e</b>), and isopropoxate (<b>f</b>).</p> Full article ">Figure 3
<p>MRM chromatograms of etomidate, metomidate and isopropoxate in e-liquid samples at low (<b>a</b>), medium (<b>b</b>), and high concentrations (<b>c</b>).</p> Full article ">Figure 4
<p>MRM chromatograms of Sample 1 in case 12.</p> Full article ">Figure 5
<p>The TIC of Sample 1 in case 12.</p> Full article ">

16 pages, 1859 KiB  

Open AccessReview

The Environmental Hazards and Treatment of Ship’s Domestic Sewage

by Yanan Zhang, Bensen Xian, Wenkai Sun, Ruifang Lu, Qin Zhang, Mei Wang, Dandan Xu, Huili Liu, Shaoyuan Bai and Mingming Fu

Toxics 2024, 12(11), 826; https://doi.org/10.3390/toxics12110826 - 19 Nov 2024

Viewed by 1131

Abstract

With the rapid development of the modern shipping field, the damage caused by ship pollution to the global inland waterways and marine ecosystems has attracted extensive attention from the international community. However, there are fewer reviews on the environmental hazards of domestic ship [...] Read more.

With the rapid development of the modern shipping field, the damage caused by ship pollution to the global inland waterways and marine ecosystems has attracted extensive attention from the international community. However, there are fewer reviews on the environmental hazards of domestic ship sewage and its treatment, and a systematic summary of the environmental hazards posed by ship domestic sewage and its treatment is lacking. Based on summarizing the various environmental hazards brought about by a ship’s domestic sewage and the corresponding treatment methods, this study elaborates, in detail, on the specific hazards of the main toxic and hazardous substances contained in a ship’s domestic sewage on the environment and organisms, and the treatment methods of the ship’s domestic sewage and their treatment effects, such as membrane bioreactor (MBR). It is also pointed out that MBR has great potential in the direction of ship domestic sewage treatment, and the solution of its membrane pollution and other problems as well as the exploration of the combination of MBR and other treatment methods will become the focus of future research. A theoretical reference is provided for the study of environmental problems caused by domestic sewage from ships and their treatment options. Full article

(This article belongs to the Topic The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering)

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<p>Main sources of domestic sewage from ships.</p> Full article ">Figure 2
<p>Demand for international cruises (in millions).</p> Full article ">Figure 3
<p>Hazard of metal pollutants in ships’ domestic sewage to organisms.</p> Full article ">Figure 4
<p>Schematic diagram of the main flow of the AOA-MBR process for ship domestic sewage treatment.</p> Full article ">

15 pages, 863 KiB  

Open AccessReview

Overview of Methylation and Demethylation Mechanisms and Influencing Factors of Mercury in Water

by Wenyu Zhao, Runjie Gan, Bensen Xian, Tong Wu, Guoping Wu, Shixin Huang, Ronghua Wang, Zixuan Liu, Qin Zhang, Shaoyuan Bai, Mingming Fu and Yanan Zhang

Toxics 2024, 12(10), 715; https://doi.org/10.3390/toxics12100715 - 30 Sep 2024

Viewed by 1884

Abstract

Mercury, particularly in its methylated form, poses a significant environmental and health risk in aquatic ecosystems. While the toxicity and bioaccumulation of mercury are well documented, there remains a critical gap in our understanding of the mechanisms governing mercury methylation and demethylation in [...] Read more.

Mercury, particularly in its methylated form, poses a significant environmental and health risk in aquatic ecosystems. While the toxicity and bioaccumulation of mercury are well documented, there remains a critical gap in our understanding of the mechanisms governing mercury methylation and demethylation in aquatic environments. This review systematically examines the complex interplay of chemical, biological, and physical factors that influence mercury speciation and transformation in natural water systems. We provide a comprehensive analysis of methylation and demethylation processes, specifically focusing on the dominant role of methanogenic bacteria. Our study highlights the crucial function of hgcAB genes in facilitating mercury methylation by anaerobic microorganisms, an area that represents a frontier in current research. By synthesizing the existing knowledge and identifying key research priorities, this review offers novel insights into the intricate dynamics of mercury cycling in aquatic ecosystems. Our findings provide a theoretical framework to inform future studies and guide pollution management strategies for mercury and its compounds in aquatic environments. Full article

(This article belongs to the Topic The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering)

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<p>Mechanism of action of HgcAB gene pairs within anaerobic bacteria.</p> Full article ">Figure 2
<p>Mer-B and Mer-A genes dominate the demethylation process.</p> Full article ">

13 pages, 2609 KiB  

Open AccessArticle

Effect of Rotation Speed and Fulvic Acid Concentration on Biogenic Secondary High-Iron Mineral Synthesis

by Haitao Huang, Yichao Ji, Chong Wang, Kanghui Geng, Xianhui Wu and Caichun Wei

Water 2024, 16(15), 2092; https://doi.org/10.3390/w16152092 - 25 Jul 2024

Viewed by 846

Abstract

From an engineering standpoint, investigating the effects of rotation speed and fulvic acid concentration on the development of secondary high-iron minerals is crucial for treating acid mine drainage. The Fe²⁺ oxidation mechanism by Acidithiobacillus (A.) ferrooxidans to synthesise secondary high-iron [...] Read more.

From an engineering standpoint, investigating the effects of rotation speed and fulvic acid concentration on the development of secondary high-iron minerals is crucial for treating acid mine drainage. The Fe²⁺ oxidation mechanism by Acidithiobacillus (A.) ferrooxidans to synthesise secondary high-iron minerals was examined in this study using shaking flask tests under various conditions: fulvic acid concentrations of 0, 0.2, or 0.4 g/L and rotation speeds of 180 r/min or 100 r/min. The pH, Fe²⁺ oxidation rate, total iron precipitation rate, secondary high-iron mineral functional groups and ore equivalent indicators were also investigated. The results demonstrated that at a fulvic acid concentration of 0 g/L, the pH decreased from 2.5 to 2.17 at 180 r/min. At 0.2 g/L, it decreased from 2.5 to 2.05. Finally, at 0.4 g/L, it decreased from 2.5 to 2.07. Fe²⁺ was completely oxidised after 48 h, and the final total iron precipitation rate ranged from 26.2% to 33.4%. The synthesised secondary high-iron minerals were uniformly dispersed in the solution. When the rotation speed was 100 r/min, the pH reduced from 2.5 to 2.25 at a fulvic acid concentration of 0 g/L, from 2.5 to 2.14 at 0.2 g/L, and from 2.5 to 2.19 at 0.4 g/L. Notably, Fe²⁺ was completely oxidised within 72 h. The experiment’s final iron precipitation rate ranged from 23.6 to 29.6%. The synthesised secondary high-iron minerals were blocky and adhered to the bottom of the shaking flask. In summary, at a rotation speed of 180 r/min or 100 r/min, the Fe²⁺ oxidation rate and total iron precipitation rate of the experimental group with a fulvic acid concentration of 0.2 g/L were higher than those of the control group and the experimental group with a fulvic acid concentration of 0.4 g/L. A fulvic acid concentration of 0.2 g/L enhanced the activity of A. ferrooxidans. The minerals obtained from these experiments were characterised and identified as schwertmannite and jarosite. Full article

(This article belongs to the Topic The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering)

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<p>Changes in the pH of biosynthetic secondary high-iron mineral systems.</p> Full article ">Figure 2
<p>Changes in the Fe²⁺ oxidation rate of biosynthetic secondary high-iron mineral synthesis systems.</p> Full article ">Figure 3
<p>Changes in the TFe precipitation rate of biosynthetic secondary high-iron mineral synthesis systems.</p> Full article ">Figure 4
<p>Minerals in the final state of the reaction within the biosynthetic secondary high-iron mineral synthesis systems. ((<b>a</b>). FA-0 g/L. (<b>b</b>). FA-0.2 g/L. (<b>c</b>). FA-0.4 g/L).</p> Full article ">Figure 5
<p>XRD spectra of secondary high-iron minerals.</p> Full article ">Figure 6
<p>FTIR spectra of the secondary high-iron minerals.</p> Full article ">

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16 pages, 3015 KiB  

Open AccessArticle

Spatiotemporal Variations in Co-Occurrence Patterns of Planktonic Prokaryotic Microorganisms along the Yangtze River

by Wenran Du, Jiacheng Li, Guohua Zhang, Ke Yu and Shufeng Liu

Microorganisms 2024, 12(7), 1282; https://doi.org/10.3390/microorganisms12071282 - 24 Jun 2024

Viewed by 1235

Abstract

Bacteria and archaea are foundational life forms on Earth and play crucial roles in the development of our planet’s biological hierarchy. Their interactions influence various aspects of life, including eukaryotic cell biology, molecular biology, and ecological dynamics. However, the coexistence network patterns of [...] Read more.

Bacteria and archaea are foundational life forms on Earth and play crucial roles in the development of our planet’s biological hierarchy. Their interactions influence various aspects of life, including eukaryotic cell biology, molecular biology, and ecological dynamics. However, the coexistence network patterns of these microorganisms within natural river ecosystems, vital for nutrient cycling and environmental health, are not well understood. To address this knowledge gap, we systematically explored the non-random coexistence patterns of planktonic bacteria and archaea in the 6000-km stretch of the Yangtze River by using high-throughput sequencing technology. By analyzing the O/R ratio, representing the divergence between observed (O%) and random (R%) co-existence incidences, and the module composition, we found a preference of both bacteria and archaea for intradomain associations over interdomain associations. Seasons notably influenced the co-existence of bacteria and archaea, and archaea played a more crucial role in spring as evidenced by their predominant presence of interphyla co-existence and more species as keystone ones. The autumn network was characterized by a higher node or edge number, greater graph density, node degree, degree centralization, and nearest neighbor degree, indicating a more complex and interconnected structure. Landforms markedly affected microbial associations, with more complex networks and more core species found in plain and non-source areas. Distance-decay analysis suggested the importance of geographical distance in shaping bacteria and archaea co-existence patterns (more pronounced in spring). Natural, nutrient, and metal factors, including water temperature, NH₄⁺-N, Fe, Al, and Ni were identified as crucial determinants shaping the co-occurrence patterns. Overall, these findings revealed the dynamics of prokaryotic taxa coexistence patterns in response to varying environmental conditions and further contributed to a broader understanding of microbial ecology in freshwater biogeochemical cycling. Full article

(This article belongs to the Topic The Challenges and Future Trends in Anthropogenic and Natural Pollution Control Engineering)

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<p>Study area and the sampling sites. Detailed information is summarized in <a href="#app1-microorganisms-12-01282" class="html-app">Table S1</a>.</p> Full article ">Figure 2
<p>Metacommunity co-existence of planktonic prokaryotic taxa in the Yangtze River. (<b>a</b>) Bacterial and archaeal networks were constructed based on Spearman’s rank correlations between all the available OTUs in spring, autumn, or both seasons. Nodes are colored by modularity (upper panels) and phylum-level taxonomy (lower panels). Each connection stands for a strong (Spearman’s <span class="html-italic">r</span> &gt; 0.6) and significant (Benjamini–Hochberg corrected <span class="html-italic">p</span> &lt; 0.01) correlation. The size of each node is proportional to the degree. (<b>b</b>) Node degree distributions for the prokaryotic co-existence networks (in red) and the 1000 Erdös–Rényi random networks (in blue). Black solid lines denote the power law and Gaussian best fits (**** <span class="html-italic">p</span> &lt; 0.0001) for the degree distribution from the realistic networks and the equally sized Erdös–Rényi random networks, respectively.</p> Full article ">Figure 3
<p>Identification of the keystone taxa in bacterial and archaeal networks for two seasons (<b>a</b>) and spring (<b>b</b>). Dot and triangle plots show the node degree and betweenness centrality of bacterial and archaeal OTUs in the networks, respectively. OTUs with high node degrees (&gt;100) and low betweenness centrality values (&lt;5000) were considered the keystone taxa [<a href="#B10-microorganisms-12-01282" class="html-bibr">10</a>]. The dot and triangle points are colored by the phylum-level taxonomy, and their areas are proportional to the mean relative abundances of OTUs. The colored bar charts exhibit the number and relative abundances of the keystone taxa in each phylum for two seasons (<b>c</b>) and spring (<b>d</b>). “MEG”: miscellaneous Euryarchaeotal group; Group-E: marine benthic group-E.</p> Full article ">Figure 4
<p>Boxplots displaying the comparisons of network topological features between spring and autumn (<b>a</b>), among plateau, mountain/hill, basin, and plain regions (<b>b</b>), and between the source and non-source regions (<b>c</b>). All the asterisks denote the significance of Wilcoxon rank-sum tests (*** <span class="html-italic">p</span> &lt; 0.001, ** 0.001 &lt; <span class="html-italic">p</span> &lt; 0.01, and * 0.01 &lt; <span class="html-italic">p</span> &lt; 0.05). The “A” in the brackets means “average”.</p> Full article ">Figure 5
<p>(<b>a</b>) Heatmap showing the Spearman correlations between environmental factors and total relative abundance of each module in the co-occurrence network and network topological properties. (<b>b</b>) Distance-based redundancy analysis (db-RDA) reveals the relative importance of environmental factors shaping bacterial and archaeal OTUs that occur in the network. (<b>c</b>) Geodetic distance-decay curves of Bray–Curtis similarities were calculated based on all the selected network topological parameters across all the sites in two seasons. Mantel Spearman’s <span class="html-italic">r</span> and <span class="html-italic">p</span> values are stated. All the asterisks denote the significance of correlations (*** <span class="html-italic">p</span> &lt; 0.001, ** 0.001 &lt; <span class="html-italic">p</span> &lt; 0.01, and * 0.01 &lt; <span class="html-italic">p</span> &lt; 0.05).</p> Full article ">

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