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Environments, Volume 11, Issue 11 (November 2024) – 34 articles

Cover Story (view full-size image): Today’s wastewater treatment plants reduce nitrogen and phosphorus significantly but do not address the targeted removal of micropollutants and microplastics. Nevertheless, the remaining N and P compounds can still contribute to the eutrophication of water bodies. Our study presents the results of a pilot plant operation (ozonation followed by a granular activated carbon filter). The results show a reduction of over 80% for almost all micropollutants investigated and over 90% for microplastics. The concentration of nitrite, ammonium and phosphorous decreased throughout the process, whereas nitrate’s concentration increased. Thus, the ozonation/activated carbon filtration combination is very promising for effective protection of the aquatic environment addressing different substances. View this paper
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13 pages, 655 KiB  
Article
Economic Values for Coral Reef Conservation and Restoration in Florida
by Kristy Wallmo and Mary E. Allen
Environments 2024, 11(11), 261; https://doi.org/10.3390/environments11110261 - 20 Nov 2024
Viewed by 902
Abstract
Florida’s coral reef is the third-largest barrier reef system in the world and provides valuable ecosystem services, such as recreation and tourism, erosion protection, and other services. Florida’s reefs have been declining due to impacts from climate change, pollution, and other pressures. In [...] Read more.
Florida’s coral reef is the third-largest barrier reef system in the world and provides valuable ecosystem services, such as recreation and tourism, erosion protection, and other services. Florida’s reefs have been declining due to impacts from climate change, pollution, and other pressures. In response, various conservation strategies have been implemented, including education and outreach, growing corals in nurseries and transplanting them to degraded reef sites, and deploying artificial reefs. However, few studies have estimated an explicit value for different strategies to attain conservation goals. Understanding economic values for reef restoration and enhancement is needed to help inform decision-making and support marine policy. This study conducted a stated preference choice experiment survey to examine the way U.S. residents make economic trade-offs among different restoration strategies, including increasing coral cover, deploying artificial reefs, and limiting visitor access to reef sites. The results suggest that, on average, the economic value of increasing coral cover is about twice as high as the value of increasing the number of artificial reef sites. Economic values for reducing visitation were similar to values for increasing the number of artificial reefs. These results provide essential information to policy analysts concerning reef use, reef importance, and economic values for reef restoration. Full article
(This article belongs to the Special Issue Ecological Restoration in Marine Environments)
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<p>Map of South Florida counties and nearby coral reefs (highlighted in red).</p>
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<p>Example of a choice task question.</p>
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23 pages, 6263 KiB  
Article
Submerged Membrane Bioreactor Configurations for Biological Nutrient Removal from Urban Wastewater: Experimental Tests and Model Simulation
by Javier A. Mouthón-Bello, Oscar E. Coronado-Hernández and Vicente S. Fuertes-Miquel
Environments 2024, 11(11), 260; https://doi.org/10.3390/environments11110260 - 20 Nov 2024
Viewed by 677
Abstract
Pilot-scale experimental measurements and simulations were utilised to evaluate the nutrient removal efficiency of three submerged membrane bioreactor designs. This study compared setups with post- and pre-denitrification processes. A 625 L pilot plant for treating primary effluent provided the operational data necessary for [...] Read more.
Pilot-scale experimental measurements and simulations were utilised to evaluate the nutrient removal efficiency of three submerged membrane bioreactor designs. This study compared setups with post- and pre-denitrification processes. A 625 L pilot plant for treating primary effluent provided the operational data necessary for calibrating the activated sludge model, specifically for chemical oxygen demand and nitrogen removal under steady-state flow. Identical influent conditions were maintained for all configurations while varying the sludge retention times (from 5 to 100 d), hydraulic retention times (ranging from 4 to 15 h), return activated sludge flow rates (between 0.1 and 3.0), and aerobic volume fractions (from 0.3 to 1.0). The pilot plant tests showed high COD and ammonia removal (above 90%) but moderate total nitrogen removal (above 70%). The simulation results successfully forecasted the effluent concentrations of COD and nitrogen for each configuration. There were noticeable variations in the kinetic parameters, such as mass transfer coefficients and biomass decay rates, related to the activated sludge model. However, increasing the sludge retention time beyond 20 d, hydraulic retention time beyond 8 h, return activated sludge rates above 2.0, or aerobic volume fractions beyond 0.4 did not significantly enhance nutrient removal. The post-denitrification setup showed a clear benefit in nitrogen removal but required a greater oxygen supply. Full article
(This article belongs to the Special Issue Advanced Research on Micropollutants in Water)
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<p>Schematic of the ASM model setup in GPS-X for Configurations (<b>a</b>) No. 1, (<b>b</b>) No. 2, and (<b>c</b>) No. 3.</p>
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<p>Configurations and runs of unit processes: (<b>a</b>) Configuration No. 1—Run 1; (<b>b</b>) Configuration No. 2—Run 2; (<b>c</b>) Configuration No. 2—Run 3; and (<b>d</b>) Configuration No. 3—Run 4.</p>
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<p>Effect of sludge retention time on simulated: (<b>a</b>) NH<sub>3</sub> effluent; (<b>b</b>) total heterotrophic biomass; (<b>c</b>) NO<sub>3</sub><sup>−</sup> effluent; and (<b>d</b>) total autotrophic biomass.</p>
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<p>Effect of sludge retention time on simulated: (<b>a</b>) oxygen uptake; (<b>b</b>) nitrification; and (<b>c</b>) denitrification.</p>
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<p>Effect of sludge retention time on simulated: (<b>a</b>) oxygen uptake; (<b>b</b>) nitrification; and (<b>c</b>) denitrification.</p>
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<p>Effect of hydraulic retention time on simulated: (<b>a</b>) NH<sub>3</sub> effluent; (<b>b</b>) total heterotrophic biomass; (<b>c</b>) NO<sub>3</sub><sup>−</sup> effluent; and (<b>d</b>) total autotrophic biomass.</p>
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<p>Effect of hydraulic retention time on simulated: (<b>a</b>) oxygen uptake; (<b>b</b>) nitrification; and (<b>c</b>) denitrification.</p>
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<p>Effect of hydraulic retention time on simulated: (<b>a</b>) oxygen uptake; (<b>b</b>) nitrification; and (<b>c</b>) denitrification.</p>
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<p>Effect of return activated sludge on simulated: (<b>a</b>) NH<sub>3</sub> effluent; (<b>b</b>) total heterotrophic biomass; (<b>c</b>) NO<sub>3</sub><sup>−</sup> effluent; and (<b>d</b>) total autotrophic biomass.</p>
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<p>Effect of return activated sludge on simulated: (<b>a</b>) oxygen uptake; (<b>b</b>) nitrification; and (<b>c</b>) denitrification.</p>
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<p>Effect of return activated sludge on simulated: (<b>a</b>) oxygen uptake; (<b>b</b>) nitrification; and (<b>c</b>) denitrification.</p>
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<p>Effect of aerobic fraction on simulated: (<b>a</b>) NH<sub>3</sub> effluent; (<b>b</b>) total heterotrophic biomass; (<b>c</b>) NO<sub>3</sub><sup>−</sup> effluent; and (<b>d</b>) total autotrophic biomass.</p>
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<p>Effect of aerobic fraction on simulated: (<b>a</b>) oxygen uptake; (<b>b</b>) nitrification; and (<b>c</b>) denitrification.</p>
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<p>Effect of aerobic fraction on simulated: (<b>a</b>) oxygen uptake; (<b>b</b>) nitrification; and (<b>c</b>) denitrification.</p>
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16 pages, 4942 KiB  
Article
Differential Cytotoxicity, Inflammatory Responses, and Aging Effects of Human Skin Cells in Response to Fine Dust Exposure
by Tae Eun Kim, Jun Woo Lim, Jae Hyun Jeong and Hee Wook Ryu
Environments 2024, 11(11), 259; https://doi.org/10.3390/environments11110259 - 19 Nov 2024
Viewed by 591
Abstract
Airborne fine dust pollution poses a significant threat to both respiratory and skin health, yet the skin’s physiological response to such exposure has been underexplored. This study investigates the impact of fine dust on skin cells, focusing on their metabolic activity, inflammatory responses, [...] Read more.
Airborne fine dust pollution poses a significant threat to both respiratory and skin health, yet the skin’s physiological response to such exposure has been underexplored. This study investigates the impact of fine dust on skin cells, focusing on their metabolic activity, inflammatory responses, and aging-related changes. We found that exposure to fine dust model compounds led to dose-dependent cytotoxicity, with PM2.5-Ions exhibiting higher toxicity compared to PM10-PAHs. Human epithelial keratinocytes (HEKn) showed heightened sensitivity to fine dust, marked by increased inflammation, particularly with elevated IL-8 expression in response to PM2.5-Ions. Additionally, fine dust exposure resulted in reduced cell density, slower proliferation, and decreased migration, notably at higher concentrations of PM2.5-Ions. These changes are indicative of accelerated aging processes, including compromised cell function and structural integrity. Live cell imaging and correlation analyses highlighted significant links between metabolic activity, cell morphology, and IL-8 secretion. These findings provide critical insights into the differential impacts of fine dust components on skin cells, emphasizing the potential acceleration of aging processes and underscoring the need for further research on cellular responses to environmental stress and the development of protective measures against urban fine dust exposure. Overall, this study, which contributes to addressing the skin health risks posed by air pollutants, could be actively used in environmental science, dermatology, and public health. Full article
(This article belongs to the Special Issue Air Quality, Health and Climate)
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<p>Cytotoxicity characterization of human dermal Fibroblasts (HDFn) by particulate matters. (<b>a</b>) Bright-field images of HDFn cells treated with 50 μg/mL of PMs before and after the MTT assay. (<b>b</b>) Cellular metabolic activity measured at each time, normalized to the metabolic activity characterized right after cell stabilization in the well. (<b>c</b>) Cell viability measured at each time, normalized to the characterized pure medium group at each time, comparing different concentrations of (<b>c</b>) PAHs, (<b>d</b>) Trace, and (<b>e</b>) Ions (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005).</p>
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<p>Cytotoxicity characterization of human epidermal keratinocytes (HEKn) by particulate matters. (<b>a</b>) Bright-field images of HEKn cells treated with 50 μg/mL of PMs before and after the MTT assay. (<b>b</b>) Cellular metabolic activity measured at each time, normalized to the metabolic activity characterized right after cell stabilization in the well. (<b>c</b>) Cell viability measured at each time, normalized to the characterized pure medium group at each time, comparing different concentrations of (<b>c</b>) PAHs, (<b>d</b>) Trace, and (<b>e</b>) Ions (*** <span class="html-italic">p</span> &lt; 0.0005).</p>
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<p>Assessing the impact of cells on particulate matters. Compare cell viability with each type of fine dust concentration after 48 h in (<b>a</b>) HDFn and (<b>b</b>) HEKn.</p>
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<p>Assessing metabolic activity induced by particulate matters. Expression levels of the particulate matter-induced pro-inflammatory cytokine IL-8 in (<b>a</b>) HDFn and (<b>b</b>) HEKn cells. IL-8 expression was assessed after treatment with 50 μg/mL of particulate matter and expressed IL-8 levels were evaluated per cell.</p>
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<p>Characterization of HEKn proliferation rate induced by fine dusts. HEKn cells were imaged using live cell imaging and analyzed with ImageJ. Each fine dust material was treated at concentrations of (<b>a</b>) 2 μg/mL and (<b>b</b>) 50 μg/mL, then compared to the control. (<b>c</b>) Proliferation rates of HEKn cells at 48 h were assessed (*** <span class="html-italic">p</span> &lt; 0.0005).</p>
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<p>Analysis of the behavior of HEKn affected by particulate matter. (<b>a</b>) HEKn activity in each fine dust component was analyzed by ImageJ. (<b>b</b>) The migration distance of HEKn treated with each particulate matter was analyzed compared to the control. HEKn were treated with 2 μg/mL and 50 μg/mL concentrations of each particulate matter for 48 h and analyzed (*** <span class="html-italic">p</span> &lt; 0.0005). The hourly proliferation instantaneous rate of HEKn by particulate matter was evaluated by treating (<b>c</b>) 2 μg/mL and (<b>d</b>) 50 μg/mL of each material. The asterisks in (<b>d</b>) indicate statistical significance compared to the 2 µg/mL group (*** <span class="html-italic">p</span> &lt; 0.0005).</p>
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<p>Correlation between metabolic activity toward fine dust and morphological analysis of HEKn. (<b>a</b>) Proliferation rate and cell survival rate. (<b>b</b>) Correlation between cell migration speed and proliferation rate and IL-8 secretion. The correlation between metabolic activity and morphological analysis of HEKn responding to particulate matter was evaluated. The injection amount of each PM was 50 μg/mL, and each analysis item was evaluated for 48 h.</p>
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<p>Specific growth rate of HEKn cells according to changes in PM concentration (<b>a</b>), plot of [<span class="html-italic">I</span>] and 1/<span class="html-italic">μ</span> by non-competitive inhibition model (<b>b</b>) and normalized cell viability with the reduced PMs (<b>c</b>) (from <a href="#environments-11-00259-f003" class="html-fig">Figure 3</a>b).</p>
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<p>Normalized cellular viability of HEKn cells according to changes in the concentration of Seoul-PMs. (<b>a</b>) PMs concentration and (<b>b</b>) the reduced PMs as PM<sub>2.5</sub>-Ions.</p>
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12 pages, 630 KiB  
Article
Environmental Risk Assessment of Glyphosate and Aminomethylphosphonic Acid (AMPA) in Portuguese Groundwater Ecosystems
by Santos Inês, Lopes Ana and Silva Emília
Environments 2024, 11(11), 258; https://doi.org/10.3390/environments11110258 - 19 Nov 2024
Viewed by 654
Abstract
The aim of the present study was to assess the risk related to the exposure of groundwater ecosystems to herbicide glyphosate and its non-relevant metabolite aminomethylphosphonic acid (AMPA) based on the quotient between measured concentrations gathered from the Water Resources Information System of [...] Read more.
The aim of the present study was to assess the risk related to the exposure of groundwater ecosystems to herbicide glyphosate and its non-relevant metabolite aminomethylphosphonic acid (AMPA) based on the quotient between measured concentrations gathered from the Water Resources Information System of Portugal, and groundwater quality standards set in legislation and estimated from environmental quality standards in surface waters. Glyphosate was analyzed in 103 groundwater samples collected from 80 wells located in 21 aquifer systems from the four hydrogeological units of mainland Portugal, between 2019 and 2021. It was detected in 14% of the total samples; however, only 10% presented concentration levels above 0.1 µg/L, the groundwater quality standard, and none of these values exceeded the value of 8.67 μg/L estimated from the annual average environmental quality standard proposed for glyphosate in surface waters. In comparison, AMPA was detected in only 5% of 63 groundwater samples, in four dug wells. In both compounds, the maximum concentration level was quantified in a dug well located in the O25-Torres Vedras aquifer system, from the Western unit, with 4.69 and 4.24 μg/L for glyphosate and AMPA, respectively. The results of this study demonstrate that it is extremely important to raise awareness and offer training to farmers on the sustainable use of plant protection products and good agricultural practices, in order to prevent groundwater contamination and improve its quality. There is also an urgent need to carry out ecotoxicological tests with further groundwater species from different functional groups in order to obtain a quality standard that accurately represents the groundwater communities. Full article
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<p>Locations of the 80 sites sampled in mainland Portugal.</p>
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31 pages, 4631 KiB  
Article
Environmental Impact of Wind Farms
by Mladen Bošnjaković, Filip Hrkać, Marija Stoić and Ivan Hradovi
Environments 2024, 11(11), 257; https://doi.org/10.3390/environments11110257 - 16 Nov 2024
Cited by 1 | Viewed by 2186
Abstract
The aim of this article is to analyse the global environmental impact of wind farms, i.e., the effects on human health and the local ecosystem. Compared to conventional energy sources, wind turbines emit significantly fewer greenhouse gases, which helps to mitigate global warming. [...] Read more.
The aim of this article is to analyse the global environmental impact of wind farms, i.e., the effects on human health and the local ecosystem. Compared to conventional energy sources, wind turbines emit significantly fewer greenhouse gases, which helps to mitigate global warming. During the life cycle of a wind farm, 86% of CO2 emissions are generated by the extraction of raw materials and the manufacture of wind turbine components. The water consumption of wind farms is extremely low. In the operational phase, it is 4 L/MWh, and in the life cycle, one water footprint is only 670 L/MWh. However, wind farms occupy a relatively large total area of 0.345 ± 0.224 km2/MW of installed capacity on average. For this reason, wind farms will occupy more than 10% of the land area in some EU countries by 2030. The impact of wind farms on human health is mainly reflected in noise and shadow flicker, which can cause insomnia, headaches and various other problems. Ice flying off the rotor blades is not mentioned as a problem. On a positive note, the use of wind turbines instead of conventionally operated power plants helps to reduce the emission of particulate matter 2.5 microns or less in diameter (PM 2.5), which are a major problem for human health. In addition, the non-carcinogenic toxicity potential of wind turbines for humans over the entire life cycle is one of the lowest for energy plants. Wind farms can have a relatively large impact on the ecological system and biodiversity. The destruction of animal migration routes and habitats, the death of birds and bats in collisions with wind farms and the negative effects of wind farm noise on wildlife are examples of these impacts. The installation of a wind turbine at sea generates a lot of noise, which can have a significant impact on some marine animals. For this reason, planners should include noise mitigation measures when selecting the site for the future wind farm. The end of a wind turbine’s service life is not a major environmental issue. Most components of a wind turbine can be easily recycled and the biggest challenge is the rotor blades due to the composite materials used. Full article
(This article belongs to the Collection Trends and Innovations in Environmental Impact Assessment)
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<p>Average emissions of CO<sub>2</sub> eq.kg/MWh.</p>
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<p>Water footprint for different electricity generation technologies. The red line represents the range and the circle represents the median.</p>
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<p>Lifecycle human toxicity potential, non-carcinogenic. The red line represents the range and the circle represents the median.</p>
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<p>Lifecycle human toxicity potential, carcinogenic. The red line represents the range and the circle represents the median.</p>
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<p>Illustration of the noise level of wind turbines as a function of distance.</p>
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<p>Illustration of the flickering shadow effect, with permission of WKC Group.</p>
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<p>Share of land used by wind power.</p>
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<p>Development of the offshore wind farm project over time [<a href="#B124-environments-11-00257" class="html-bibr">124</a>].</p>
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<p>Sound transmission path of an offshore windturbine.</p>
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36 pages, 4952 KiB  
Review
Microplastics in Urban Ambient Air: A Rapid Review of Active Sampling and Analytical Methods for Human Risk Assessment
by Inkyu Han, Chanmi Lee, Caesar Belchez, Andrea Goldstein Shipper and Kirsten E. Wiens
Environments 2024, 11(11), 256; https://doi.org/10.3390/environments11110256 - 16 Nov 2024
Viewed by 1226
Abstract
This study conducted a rapid review to evaluate active air sampling and analytical methods for characterizing outdoor air microplastics in urban areas. We synthesized information from 35 peer-reviewed journal articles. Studies utilizing active sampling methods were able to provide detailed data on inhalation [...] Read more.
This study conducted a rapid review to evaluate active air sampling and analytical methods for characterizing outdoor air microplastics in urban areas. We synthesized information from 35 peer-reviewed journal articles. Studies utilizing active sampling methods were able to provide detailed data on inhalation concentrations and doses. The analytical techniques reviewed were categorized into microscopy, Fourier Transform Infrared (FTIR) spectroscopy, Raman spectroscopy, scanning electron microscopy (SEM), and mass spectrometry, including pyrolysis–gas chromatography (Py-GC). While conventional FTIR and Raman spectroscopy can identify microplastics in total suspended particles, advanced instruments such as µRaman and SEM are crucial for analyzing inhalable microplastics (e.g., particles smaller than 10 µm). Characterizing the shapes and colours of microplastics can provide qualitative estimates of their sources, with fibres and the colour black being the most predominant characteristics. Establishing dose–response relationships for health effects requires quantitative analyses; thus, combining techniques like µRaman with Py-GC is essential for comprehensive human risk assessments. Future studies should focus on identifying and quantifying inhalable microplastic compounds that are relevant to human health. Full article
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<p>Screening of peer-reviewed articles in this study.</p>
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<p>A total of 35 peer-reviewed publications are identified for full-text review. Please note that the number of publications in 2024 includes articles published or in press as of January 2024.</p>
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<p>Countries with two or more studies are labelled with numbers, while countries with only one study are shaded in light green.</p>
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<p>Overview of possible sampling, treatment, and analytical methods for airborne microplastics. Quartz Fiber Filter (QFF), scanning electron microscope (SEM), energy dispersive X-ray (EDX), and micro Fourier Transform Infrared (µFTIR). Coloured cells indicate the range of microplastic sizes detectable by each instrument. Colour (C), shape (S), number (N), polymer identification (P), and microplastics mass analysis (M).</p>
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<p>Studies characterizing the physical characteristics of airborne microplastics: (<b>a</b>) shows the number of studies identifying the colours of microplastics; (<b>b</b>) shows studies classifying the shapes of microplastics.</p>
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<p>Number of studies reporting the chemical composition of microplastics. Polytetrafluoroethylene (PTFE); polyvinyl alcohol (PVA); polyacrylonitrile (PAN); polyether sulphone (PES); acryl; polyurethane (PU); cellulose; polymethyl methacrylate (PMMA); nylon; polyvinyl chloride (PVC); polyamide (PA); polystyrene (PS); polypropylene (PP); polyethylene terephthalate (PET); polyethylene (PE).</p>
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<p>A comparison of the airborne microplastics number concentrations of different studies. The reference numbers shown in this figure correspond to the numbers cited in the References section. Ref [<a href="#B20-environments-11-00256" class="html-bibr">20</a>]—Abbasi 2023; Ref [<a href="#B27-environments-11-00256" class="html-bibr">27</a>]—Liu 2019; Ref [<a href="#B41-environments-11-00256" class="html-bibr">41</a>]—Yuan 2023; Ref [<a href="#B42-environments-11-00256" class="html-bibr">42</a>]—Yuan 2023; Ref [<a href="#B51-environments-11-00256" class="html-bibr">51</a>]—Shruti 2022; Ref [<a href="#B35-environments-11-00256" class="html-bibr">35</a>]—Romarate 2023; Ref [<a href="#B39-environments-11-00256" class="html-bibr">39</a>]—Syafina 2022; Ref [<a href="#B22-environments-11-00256" class="html-bibr">22</a>]—Chang 2023; Ref [<a href="#B34-environments-11-00256" class="html-bibr">34</a>]—Choi 2022; Ref [<a href="#B21-environments-11-00256" class="html-bibr">21</a>]—Akhbarizade 2021; Ref [<a href="#B31-environments-11-00256" class="html-bibr">31</a>]—Narmadha 2020; Ref [<a href="#B50-environments-11-00256" class="html-bibr">50</a>]—Amato-Lour 2023; Ref [<a href="#B49-environments-11-00256" class="html-bibr">49</a>]—Rosso 2023; Ref [<a href="#B30-environments-11-00256" class="html-bibr">30</a>]—Luo 2024; Ref [<a href="#B46-environments-11-00256" class="html-bibr">46</a>]—González-Pleiter 2021; Ref [<a href="#B40-environments-11-00256" class="html-bibr">40</a>]—Yoo 2023; Ref [<a href="#B43-environments-11-00256" class="html-bibr">43</a>]—Zhu 2021; Ref [<a href="#B36-environments-11-00256" class="html-bibr">36</a>]—Sarathana 2023; Ref [<a href="#B25-environments-11-00256" class="html-bibr">25</a>]—Li 2020; and Ref [<a href="#B29-environments-11-00256" class="html-bibr">29</a>]—Liu 2022.</p>
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<p>The relative percentage of colours in airborne microplastics was estimated from existing studies. The cited reference numbers correspond to those listed in the references. Ref [<a href="#B27-environments-11-00256" class="html-bibr">27</a>]—Liu 2020; Ref [<a href="#B53-environments-11-00256" class="html-bibr">53</a>]—Gaston 2020; Ref [<a href="#B34-environments-11-00256" class="html-bibr">34</a>]—Rao 2024; Ref [<a href="#B24-environments-11-00256" class="html-bibr">24</a>]—Jiang 2024; Ref [<a href="#B28-environments-11-00256" class="html-bibr">28</a>]—Liu 2019; Ref [<a href="#B31-environments-11-00256" class="html-bibr">31</a>]—Narmadha 2020; Ref [<a href="#B46-environments-11-00256" class="html-bibr">46</a>]—González-Pleiter 2021; Ref [<a href="#B21-environments-11-00256" class="html-bibr">21</a>]—Akhbarizadeh 2023; Ref [<a href="#B39-environments-11-00256" class="html-bibr">39</a>]—Syafina 2022; Ref [<a href="#B51-environments-11-00256" class="html-bibr">51</a>]—Shruti 2022; Ref [<a href="#B47-environments-11-00256" class="html-bibr">47</a>]—Kernchen 2022; Ref [<a href="#B33-environments-11-00256" class="html-bibr">33</a>]—Perera 2022; Ref [<a href="#B44-environments-11-00256" class="html-bibr">44</a>]—Boakes 2023; Ref [<a href="#B35-environments-11-00256" class="html-bibr">35</a>]—Romarate 2023; Ref [<a href="#B41-environments-11-00256" class="html-bibr">41</a>]—Yuan 2023; Ref [<a href="#B20-environments-11-00256" class="html-bibr">20</a>]—Abbasi 2023.</p>
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<p>Proportion of microplastic shapes in the air as reported in existing studies. The cited reference numbers correspond to those listed in the references. Ref [<a href="#B26-environments-11-00256" class="html-bibr">26</a>]—Liao 2021; Ref [<a href="#B27-environments-11-00256" class="html-bibr">27</a>]—Liu 2020; Ref [<a href="#B53-environments-11-00256" class="html-bibr">53</a>]—Gaston 2020; Ref [<a href="#B36-environments-11-00256" class="html-bibr">36</a>]—Sarathana 2023; Ref [<a href="#B34-environments-11-00256" class="html-bibr">34</a>]—Rao 2024; Ref [<a href="#B30-environments-11-00256" class="html-bibr">30</a>]—Luo 2024; Ref [<a href="#B24-environments-11-00256" class="html-bibr">24</a>]—Jiang 2024; Ref [<a href="#B22-environments-11-00256" class="html-bibr">22</a>]—Chang 2023; Ref [<a href="#B28-environments-11-00256" class="html-bibr">28</a>]—Liu 2019; Ref [<a href="#B31-environments-11-00256" class="html-bibr">31</a>]—Narmadha 2020; Ref [<a href="#B46-environments-11-00256" class="html-bibr">46</a>]—González-Pleiter 2021; Ref [<a href="#B21-environments-11-00256" class="html-bibr">21</a>]—Akhbarizadeh 2023; Ref [<a href="#B51-environments-11-00256" class="html-bibr">51</a>]—Shruti 2022; Ref [<a href="#B32-environments-11-00256" class="html-bibr">32</a>]—Pandey 2022; Ref [<a href="#B47-environments-11-00256" class="html-bibr">47</a>]—Kernchen 2022; Ref [<a href="#B33-environments-11-00256" class="html-bibr">33</a>]—Perera 2022; Ref [<a href="#B44-environments-11-00256" class="html-bibr">44</a>]—Boakes 2023; Ref [<a href="#B35-environments-11-00256" class="html-bibr">35</a>]—Romarate 2023.</p>
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<p>Estimated relative abundance of polymer types identified in airborne microplastics from existing studies. The cited reference numbers correspond to those listed in the references. Ref [<a href="#B26-environments-11-00256" class="html-bibr">26</a>]—Liao 2021; Ref [<a href="#B27-environments-11-00256" class="html-bibr">27</a>]—Liu 2020; Ref [<a href="#B53-environments-11-00256" class="html-bibr">53</a>]—Gaston 2020; Ref [<a href="#B42-environments-11-00256" class="html-bibr">42</a>]—Yuan 2023; Ref [<a href="#B34-environments-11-00256" class="html-bibr">34</a>]—Rao 2024; Ref [<a href="#B30-environments-11-00256" class="html-bibr">30</a>]—Luo 2024; Ref [<a href="#B24-environments-11-00256" class="html-bibr">24</a>]—Jiang 2024; Ref [<a href="#B22-environments-11-00256" class="html-bibr">22</a>]—Chang 2023; Ref [<a href="#B28-environments-11-00256" class="html-bibr">28</a>]—Liu 2019; Ref [<a href="#B46-environments-11-00256" class="html-bibr">46</a>]—González-Pleiter 2021; Ref [<a href="#B21-environments-11-00256" class="html-bibr">21</a>]—Akhbarizadeh 2023; Ref [<a href="#B43-environments-11-00256" class="html-bibr">43</a>]—Zhu 2021; Ref [<a href="#B51-environments-11-00256" class="html-bibr">51</a>]—Shruti 2022; Ref [<a href="#B48-environments-11-00256" class="html-bibr">48</a>]—Kirchsteiger 2023; Ref [<a href="#B47-environments-11-00256" class="html-bibr">47</a>]—Kernchen 2022; Ref [<a href="#B33-environments-11-00256" class="html-bibr">33</a>]—Perera 2022; Ref [<a href="#B23-environments-11-00256" class="html-bibr">23</a>]—Choi 2022; Ref [<a href="#B50-environments-11-00256" class="html-bibr">50</a>]—Amato-Lourenco 2022; Ref [<a href="#B29-environments-11-00256" class="html-bibr">29</a>]—Liu 2022; Ref [<a href="#B35-environments-11-00256" class="html-bibr">35</a>]—Romarate 2023; Ref [<a href="#B49-environments-11-00256" class="html-bibr">49</a>]—Rosso 2023; Ref [<a href="#B41-environments-11-00256" class="html-bibr">41</a>]—Yuan 2023; Ref [<a href="#B20-environments-11-00256" class="html-bibr">20</a>]—Abbasi 2023.</p>
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16 pages, 2821 KiB  
Article
Droplet-Based Microfluidic Photobioreactor as a Growth Optimization Tool for Cyanobacteria and Microalgae
by Nadia Prasetija, Steffen Schneider, Ting Xie and Jialan Cao
Environments 2024, 11(11), 255; https://doi.org/10.3390/environments11110255 - 15 Nov 2024
Viewed by 778
Abstract
Microalgae and cyanobacteria are photosynthetic microorganisms with significant biotechnological potential for the production of bioactive compounds, making them a promising resource for diverse industrial applications. This study presents the development and validation of a modular, droplet-based microfluidic photobioreactor (µPBR) designed for high-throughput screening [...] Read more.
Microalgae and cyanobacteria are photosynthetic microorganisms with significant biotechnological potential for the production of bioactive compounds, making them a promising resource for diverse industrial applications. This study presents the development and validation of a modular, droplet-based microfluidic photobioreactor (µPBR) designed for high-throughput screening and cultivation under controlled light conditions. The µPBR, based on polytetrafluoroethylene (PTFE) tubing and a 4-channel LED illumination system, enables precise modulation of light intensity, wavelength, and photoperiod, facilitating dose–response experiments. Synechococcus elongatus UTEX 2973 and Chlorella vulgaris were used to demonstrate the system’s capacity to support photosynthetic growth under various conditions. The results indicate that continuous illumination, particularly under blue and mixed blue-red light, promotes higher autofluorescence and chlorophyll a content in cyanobacteria Synechococcus elongatus UTEX2973, while Chlorella vulgaris achieved optimal growth under a 16:8 light-dark cycle with moderate light intensity. This µPBR offers not only a flexible, scalable platform for optimizing growth parameters but also allows for the investigation of highly resolved dose response screenings of environmental stressors such as salinity. The presented findings highlight its potential for advancing microalgal biotechnology research and applications. Full article
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<p>The detail construction of the µ-photobioreactor in microtiter plate format with an aluminum housing featuring cooling slots includes the following: (<b>a</b>) µ-photobioreactor in realization; (<b>b</b>) an overview; (<b>c</b>) an aluminum lid; (<b>d</b>) a holder for 2 meters of PTFE tubing for incubation and microscopy; and (<b>e</b>) the circuit board layout for the 4-block lighting unit and two diffuser plates (2 mm and 3 mm) made of polycarbonate..</p>
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<p>Droplet generation setup: computer-controlled syringe pump system with a 6-port manifold for droplet generation. The detection system: the aqueous segments (medium, effector, and cells) separated by carrier liquid were pumped through a transparent FEP tube into a multi-channel detection unit for photometric and fluorometric measurements using a computer-controlled syringe pump system. The incubation tubing is made of PTFE with an inner diameter of 0.5 mm and an outer diameter of 1.0 mm. The length of the is 2.20 m. Approximately 28 droplets per row with a ca. 4 mm gap between droplets could be cultivated per run or up to 450 droplets.</p>
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<p>(<b>a</b>) Operation of the syringe pump system and composition of a segment in a dose–response screening and (<b>b</b>) syringe program for dose–response screening with four different illuminations.</p>
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<p>Temperature development of the light system at 120 µmol photon m<sup>−2</sup> s<sup>−1</sup> (<b>a</b>) and 300 µmol photon m<sup>−2</sup> s<sup>−1</sup> (<b>b</b>) up to 300 minutes. <span class="html-italic">n</span> = 6 and error bars represent the standard deviation.</p>
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<p><span class="html-italic">Chlorella vulgaris</span> in BG11 medium on the sixth day of cultivation in 500 nL droplets. The droplets were cultivated with three different wavelengths (470 nm, 660 nm, mix 470 nm + 660 nm) and a white light (4000 K) and lighting modes 16:8 light-dark cycle (<b>a</b>–<b>c</b>), and continuous illumination (<b>d</b>–<b>f</b>). For the data evaluation, non-specific autofluorescence was measured using a 405 nm laser diode and a 425 nm LP emission filter (<b>a</b>,<b>d</b>). For the detection of Chl a, a 470 nm excitation with a 515 nm SP filter and a 650 nm LP emission filter were used (<b>b</b>,<b>e</b>). Optical density at 750 nm was used as the growth parameters (<b>c</b>,<b>f</b>).</p>
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<p>Microscopic representation of <span class="html-italic">Synechococcus elongatus</span> UTEX2973 in BG11 medium on the sixth day of cultivation with 200× magnification. The droplets were cultivated different wavelengths at 470 nm (<b>a</b>,<b>e</b>), 660 nm (<b>b</b>,<b>f</b>), mix 470 nm + 660 nm (<b>c</b>,<b>g</b>) and a white light 4000 K (<b>d</b>,<b>h</b>). Two lighting modes were employed for cultivation: (<b>a</b>–<b>d</b>) 16:8 light-dark cycle, (<b>e</b>–<b>h</b>) continuous illumination.</p>
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<p>Multiparameter determination of the growth of <span class="html-italic">Synechococcus elongatus</span> UTEX2973 in BG11 medium on the sixth day of cultivation in 500 nL droplets. The droplets were cultivated with three different wavelengths (470 nm, 660 nm, mix 470 nm + 660 nm) and a white light (4000 K) and lighting modes 16:8 light-dark cycle (<b>a</b>–<b>c</b>) and continuous illumination (<b>d</b>–<b>f</b>).</p>
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<p>Dose–response curves of <span class="html-italic">Synechococcus elongatus</span> UTEX2973 against NaCl (0–0.6 M). The cultures were measured on the sixth day of cultivation in 500 nL droplets. The cultivation temperature was 32 ± 0.5 °C. The unspecific autofluorescence measurement was performed with a 405 nm laser diode and an LP emission filter of 425 nm. The droplets were cultivated with three different wavelengths (470 nm, 660 nm, mix 470 nm + 660 nm) and a white light (WL 4000 K) with continuous illumination.</p>
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12 pages, 5357 KiB  
Article
Microbial Contamination and Sterilization Methods in an Air Circulation-Type Geothermal Ventilation System
by Hyuntae Kim
Environments 2024, 11(11), 254; https://doi.org/10.3390/environments11110254 - 14 Nov 2024
Viewed by 559
Abstract
A simulated system was created to evaluate an air circulation-type geothermal ventilation system, focusing on measuring microbial contamination levels on the surface of the heat exchange unit. Additionally, this study examined sterilization methods using UV lamps on the surface of the heat exchanger. [...] Read more.
A simulated system was created to evaluate an air circulation-type geothermal ventilation system, focusing on measuring microbial contamination levels on the surface of the heat exchange unit. Additionally, this study examined sterilization methods using UV lamps on the surface of the heat exchanger. The fungal concentration on the surface of the heat exchanger showed a tendency to increase over time. Although direct comparison is challenging due to the varying concentrations of outdoor air fungi at different measurement times, the surface fungal concentration was highest at a minimum airflow rate of 150 m3/h compared to other conditions. However, since the adhesion of contaminants from outdoor air to the surface of the heat exchanger is influenced not only by airflow but also by outdoor temperature and relative humidity conditions, future research needs to consider these factors. According to the ATP measurement results, microbial contamination was evaluated as “slightly dirty” after 24 h and “dirty” after 48 h of operating the experimental apparatus. Therefore, it is advisable to clean the internal surfaces of the geothermal ventilation system every 1–2 days. The results of the sterilization experiments using UV lamps indicated that irradiation for approximately 30 min inactivated 94.5%-to-96.1% of microorganisms derived from outdoor air. However, since the sterilization dose varies depending on the type of microorganism, it is necessary to determine the optimal irradiation time based on the target microorganisms and the UV lamp’s irradiation intensity. Full article
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<p>The floor plan and the A–A′ cross-sectional view of the laboratory.</p>
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<p>The detailed cross-sectional view of the simulated geothermal heat exchange unit.</p>
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<p>The photographs of the experimental apparatus.</p>
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<p>The measurement instruments and the measurement process.</p>
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<p>The measurement points on the aluminum plate.</p>
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<p>The actual photos of the aluminum plate.</p>
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<p>The fungal concentration in outdoor air under various conditions.</p>
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<p>The temporal change in fungal concentration on the surface of aluminum plates.</p>
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<p>The temporal change in ATP measurements on the surface of aluminum plates.</p>
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<p>The correlation between surface fungal counts (cfu/25 cm<sup>2</sup>) and ATP measurements (RLU/25 cm<sup>2</sup>).</p>
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<p>The measurement positions and photos of the UV intensity measurement.</p>
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<p>The changes in fungal count and ATP concentration due to sterilization.</p>
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<p>The photographs of fungal cultures.</p>
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20 pages, 5042 KiB  
Article
Advancing Water Security and Agricultural Productivity: A Case Study of Transboundary Cooperation Opportunities in the Kabul River Basin
by Yar M. Taraky, Ed McBean, Andrew Binns and Bahram Gharabaghi
Environments 2024, 11(11), 253; https://doi.org/10.3390/environments11110253 - 13 Nov 2024
Viewed by 842
Abstract
The Kabul River Basin (KRB) is witnessing frequent flood and drought events that influence food production and distribution. The KRB is one of the world’s poorest regions regarding food security. Food security issues in the KRB include shifts in short-term climate cycles with [...] Read more.
The Kabul River Basin (KRB) is witnessing frequent flood and drought events that influence food production and distribution. The KRB is one of the world’s poorest regions regarding food security. Food security issues in the KRB include shifts in short-term climate cycles with significant river flow variations that result in inadequate water distribution. Due to the lack of hydro-infrastructure, low irrigation efficiency, and continuing wars, the Afghanistan portion of the KRB has experienced low agricultural land expansion opportunities for food production. This research assesses the relationship between flood mitigation, flow balances, and food production and, cumulatively, assesses the social and economic well-being of the population of the KRB. SWAT modeling and climate change (CCSM4) implications are utilized to assess how these relationships impact the social and economic well-being of the population in the KRB. The intricacies of transboundary exchange and cooperation indicate that the conservation of ~38% of the water volume would nearly double the low flows in the dry season and result in the retention of ~2B m3/y of water for agricultural developmental use. Results show that the peak flood flow routing in reservoirs on the Afghanistan side of the KRB would have a substantial positive impact on agricultural products and, therefore, food security. Water volume conservation has the potential to provide ~44% more arable land with water, allowing a ~51% increase in crop yield, provided that improved irrigation efficiency techniques are utilized. Full article
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<p>Location of the Kabul River Basin.</p>
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<p>(<b>a</b>) The KRB’s administrative and economic regions; (<b>b</b>) the study area and the flow direction.</p>
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<p>The Kabul River’s schematic direction and its tributaries.</p>
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<p>Flow volume conservation potentials under (<b>a</b>) minimum, (<b>b</b>) average, and (<b>c</b>) maximum flow conditions at Dakah Station. The volume of water that can be conserved under future conditions is shaded in blue.</p>
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<p>The KRB’s estimated agricultural land increase (ha) (1960–2050).</p>
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<p>FAO food price index [<a href="#B14-environments-11-00253" class="html-bibr">14</a>].</p>
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<p>KRB aridity map with all of the semi-arid and dry sub-humid areas that have a land productivity rating of &gt;2; all of the other areas have a land productivity rating of &lt;2.</p>
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13 pages, 1825 KiB  
Article
Conceptual Design of an Urban Pocket Park Located in the Site of the Occurrence of a Nineteenth-Century Chapel Using Representatives of Local Xerothermic Vegetation
by Weronika Kopeć, Ewa Hanus-Fajerska and Leszek Bylina
Environments 2024, 11(11), 252; https://doi.org/10.3390/environments11110252 - 13 Nov 2024
Viewed by 587
Abstract
The 19th century neo-Gothic chapel located in the Stradom district of Czestochowa, Southern Poland and built at the intersection of the main streets is a recognizable landmark of great historical value. Unfortunately, the current condition of the surroundings depreciates the charm of such [...] Read more.
The 19th century neo-Gothic chapel located in the Stradom district of Czestochowa, Southern Poland and built at the intersection of the main streets is a recognizable landmark of great historical value. Unfortunately, the current condition of the surroundings depreciates the charm of such a chapel, and thus does not encourage people to admire it. Therefore, in order to expose such a valuable object, we planned to create a conceptual design of a pocket park around this cultural monument. When choosing the location of any park, it is recommended to know the needs of the local residents, so we conducted a survey regarding their wishes. When designing the area, we intended to use species representing the vegetation characteristic of the Krakow–Czestochowa Upland located in Southern Poland. At the same time, we used a material typical of the area, namely limestone. Design principles around the chapel were taken into account, separating the sacred and profane zones with the intention of giving this site a unique character and creating the first urban pocket park of this kind. Full article
(This article belongs to the Special Issue Carbon Sequestration Potential of Urban Parks)
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<p>Photograph of the chapel in the Stradom district of Czestochowa taken in 1905.</p>
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<p>The inventory of an area under consideration in the Czestochowa city, Southern Poland (from left to right side: view of the area from Kosynierska Street; view of the chapel and cross in front of it; view of intersection of Piastowska and Sabinowska streets in the Czestochowa Stradom district).</p>
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<p>The dendrological inventory map: (<b>1</b>) Analysis of functional zones; (<b>2</b>) Analysis of the basic communication system (<b>3</b>) of the area under consideration in the Czestochowa city−the layout is visible from left to right.</p>
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<p>Distinctive crown of <span class="html-italic">Ulmus glabra</span> ‘Camperdownii’.</p>
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14 pages, 6830 KiB  
Article
Assessment of the Trophic Status and Trend Using the Transitional Water Eutrophication Assessment Method: A Case Study from Venice Lagoon
by Emanuele Ponis, Federica Cacciatore, Valentina Bernarello, Rossella Boscolo Brusà, Marta Novello, Adriano Sfriso, Fabio Strazzabosco, Michele Cornello and Andrea Bonometto
Environments 2024, 11(11), 251; https://doi.org/10.3390/environments11110251 - 12 Nov 2024
Viewed by 760
Abstract
The Transitional Water Eutrophication Assessment Method (TWEAM) is a multi-index set up for assessing the eutrophication risk and trend in transitional waters. It includes a selection of environmental variables, an ecological status indicator (i.e., Macrophyte Quality Index, MaQI) and the Transitional Water Quality [...] Read more.
The Transitional Water Eutrophication Assessment Method (TWEAM) is a multi-index set up for assessing the eutrophication risk and trend in transitional waters. It includes a selection of environmental variables, an ecological status indicator (i.e., Macrophyte Quality Index, MaQI) and the Transitional Water Quality Index (TWQI). Possible outcomes of the TWEAM include three trophic classes in terms of eutrophication risk: (i) eutrophic; (ii) non-eutrophic; (iii) mesotrophic. The method was applied on data collected at 28 stations in the Venice Lagoon over four triennial monitoring cycles (MC I-IV) in the period 2011–2022. The spatial variability and medium-term trend of eutrophication risk were investigated, highlighting a general improvement in trophic conditions over time, with a decrease in mesotrophic stations (representing 46% of total in MC-I and 25% in MC-IV) in favor of non-eutrophic stations (46% of total in MC-I and 73% in MC-IV). The main driver of observed positive changes is related to the colonization of sensitive macroalgae and aquatic angiosperms, resulting in an increase in the percentage of stations with MaQI in good/high ecological status from 25% in MC-I to 54% in MC-IV. Eutrophic sites showed a non-linear trend, particularly in choked areas of the central lagoon, with anthropogenic disturbances and low water renewal. Full article
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<p>Map of the stations sampled in the Venice Lagoon during the period 2011–2022. Natural water bodies, according to WFD, are also indicated.</p>
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<p>Distribution (%) of the TWEAM trophic classes for each triennial monitoring cycle (MC). (<b>A</b>): data grouped per water body (WB); (<b>B</b>): data grouped per station (ST).</p>
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<p>Eutrophic status assessment using the TWEAM in Venice Lagoon WBs (background color) and stations (dot color) during the first (<b>A</b>: 2011–2013) and last (<b>B</b>: 2020–2022) MC. Green = non-eutrophic; beige = mesotrophic; red = eutrophic.</p>
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<p>Box plots of the scores of TWEAM metrics resulted at the 28 stations in the Venice Lagoon: (<b>A</b>) Dissolved Inorganic Nitrogen (DIN) (μM); (<b>B</b>) Orthophosphate (P-PO<sub>4</sub>) (μM); (<b>C</b>) MaQI index; (<b>D</b>) TWQI index. Data are grouped per monitoring cycle (MC). Dotted lines indicate the boundaries among ecological quality classes: H = high; G = good; M = moderate; P = poor; B = bad.</p>
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<p>PCA biplot of the two main components for the whole dataset, including the TWEAM metrics as variables and TWEAM scores as supplementary quantitative variables. The data of the four cycles are grouped per TWEAM class. For each group, the centroids and the confidence ellipses (95% of samples) are shown.</p>
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14 pages, 6173 KiB  
Article
Enhancing Cover Management Factor Classification Through Imbalanced Data Resolution
by Kieu Anh Nguyen and Walter Chen
Environments 2024, 11(11), 250; https://doi.org/10.3390/environments11110250 - 12 Nov 2024
Cited by 1 | Viewed by 721
Abstract
This study addresses the persistent challenge of class imbalance in land use and land cover (LULC) classification within the Shihmen Reservoir watershed in Taiwan, where LULC is used to map the Cover Management factor (C-factor). The dominance of forests in the LULC categories [...] Read more.
This study addresses the persistent challenge of class imbalance in land use and land cover (LULC) classification within the Shihmen Reservoir watershed in Taiwan, where LULC is used to map the Cover Management factor (C-factor). The dominance of forests in the LULC categories leads to an imbalanced dataset, resulting in poor prediction performance for minority classes when using machine learning techniques. To overcome this limitation, we applied the Synthetic Minority Over-sampling Technique (SMOTE) and the 90-model SMOTE-variants package in Python to balance the dataset. Due to the multi-class nature of the data and memory constraints, 42 models were successfully used to create a balanced dataset, which was then integrated with a Random Forest algorithm for C-factor classification. The results show a marked improvement in model accuracy across most SMOTE variants, with the Selected Synthetic Minority Over-sampling Technique (Selected_SMOTE) emerging as the best-performing method, achieving an overall accuracy of 0.9524 and a sensitivity of 0.6892. Importantly, the previously observed issue of poor minority class prediction was resolved using the balanced dataset. This study provides a robust solution to the class imbalance issue in C-factor classification, demonstrating the effectiveness of SMOTE variants and the Random Forest algorithm in improving model performance and addressing imbalanced class distributions. The success of Selected_SMOTE underscores the potential of balanced datasets in enhancing machine learning outcomes, particularly in datasets dominated by a majority class. Additionally, by addressing imbalance in LULC classification, this research contributes to Sustainable Development Goal 15, which focuses on the protection, restoration, and sustainable use of terrestrial ecosystems. Full article
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<p>Map of LULC distribution and corresponding C-factors.</p>
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<p>Comparison of sensitivity and Kappa Coefficient between SMOTE variants (blue crosses) and the baseline reduced dataset model (red cross) using a scatter plot.</p>
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<p>Producer’s accuracy (sensitivity) between the baseline reduced dataset model (imbalanced dataset) and Selected_SMOTE model.</p>
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9 pages, 475 KiB  
Article
Long-Term Investigation (1968–2023) of 137Cs in Apples
by Branko Petrinec, Tomislav Bituh, Zdenko Franić, Branimir Zauner and Dinko Babić
Environments 2024, 11(11), 249; https://doi.org/10.3390/environments11110249 - 12 Nov 2024
Viewed by 507
Abstract
Due to the consequences of nuclear and/or radiological accidents in the past (Chernobyl, Fukushima, etc.), and potential future events of that kind, the constant monitoring of environmental radioactivity is important. There are different pathways of the transfer of radionuclides from environment to humans [...] Read more.
Due to the consequences of nuclear and/or radiological accidents in the past (Chernobyl, Fukushima, etc.), and potential future events of that kind, the constant monitoring of environmental radioactivity is important. There are different pathways of the transfer of radionuclides from environment to humans (ingestion, inhalation and external). Food ingestion greatly contributes to the total effective dose; hence, it is of great importance to investigate exposure to radionuclides through food. This paper presents the results of a long-term investigation of 137Cs activity concentration in apples in northwestern Croatia for the period 1968–2023. The highest 137Cs activity concentration in apples was measured in 1986, decreasing exponentially ever since. The Fukushima-Daiichi accident in 2011 did not cause a significant increase in 137Cs activity concentration, although the presence of the consequent fallout was detected via the appearance of 134Cs in some parts of the environment. The observed residence time for 137Cs in apples was estimated to be 4.5 and 3.9 years for the pre-Chernobyl and post-Chernobyl periods, respectively. The correlation between 137Cs in fallout and apples is very good, the correlation coefficients being 0.99, which indicates that fallout is the main source of contamination. The estimated effective dose received by adult members of the Croatian public due to intake of radiocaesium from apples over the overall observed period is 6.4 µSv. Therefore, the consumption of apples was not a critical pathway for the transfer of radiocaesium to humans. Full article
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<p><sup>137</sup>Cs activity concentration in apples (Bq kg<sup>−1</sup>) for the pre- and post-Chernobyl periods. The dotted line represents the exponential trendline for two periods. Error bars represent standard deviations of results for samples collected within a given year. (The data for the years 1987–1995, 1998 and 2000 are approximated).</p>
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18 pages, 3908 KiB  
Article
Comparative Life Cycle Assessment of Landfilling with Sustainable Waste Management Methods for Municipal Solid Wastes
by Angelika Sita Ouedraogo, Ajay Kumar, Robert Frazier and Khaled A. Sallam
Environments 2024, 11(11), 248; https://doi.org/10.3390/environments11110248 - 11 Nov 2024
Viewed by 1398
Abstract
Municipal solid waste (MSW) generation continues to increase exponentially, leading to the need for better disposal methods. Approximately 50% of the MSW is landfilled in the United States (US). Landfilling is known for its negative effects on the environment and human health. The [...] Read more.
Municipal solid waste (MSW) generation continues to increase exponentially, leading to the need for better disposal methods. Approximately 50% of the MSW is landfilled in the United States (US). Landfilling is known for its negative effects on the environment and human health. The objective of this study was to conduct a life cycle assessment (LCA) of some of the most common waste treatment methods and propose an alternative and environmentally friendly integrated waste management method (IWM). The LCA was conducted using OpenLCA. Replacing landfilling, incineration, and composting with recycling, gasification, and anaerobic digestion (IWM) reduced the global warming potential from 899 kg CO2 eq to −14.6 kg CO2 eq. The same trend was observed for acidification (from 0.21 kg SO2 eq to −1.1 kg SO2 eq), ecotoxicity (from 2363.8 CTUe to 1.22 CTUe), eutrophication (from 0.5 kg N eq to 0.3 kg N eq), smog formation (from 4.4 kg O3 eq to 1.85 kg O3 eq), ozone depletion (from 2.1 × 10−5 kg CFC-11 eq to 0 kg CFC-11 eq), respiratory effects (from 2.8 × 10−3 kg PM2.5 eq to −7.25 × 10−3 kg PM2.5 eq), cancer (from 2 × 10−5 CTUh to 1.2 × 10−7 CTUh), and non-cancer effects (from 6 × 10−5 to 1.4 × 10−5 CTUh). The results show that an integrated waste management approach with recycling, gasification, and anaerobic digestion can dramatically reduce the environmental and health impacts of municipal solid waste disposal. Policy reforms, technical innovation, economic investment, and social engagement are needed to change waste management paradigm. Full article
(This article belongs to the Special Issue Waste Management and Life Cycle Assessment)
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<p>Landfilling scenarios’ flow diagram and boundary.</p>
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<p>Single-stream recycling flow diagram and boundary.</p>
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<p>Incineration flow diagram and boundary.</p>
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<p>Windrow composting flow diagram and system boundary.</p>
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<p>Anaerobic digestion flow diagram and system boundary.</p>
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<p>Gasification flow diagram and system boundary.</p>
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<p>(<b>a</b>) Conventional treatment of MSW. (<b>b</b>) Sustainable and integrated waste management system.</p>
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<p>Impact assessment of conventional MSW treatment and integrated treatment.</p>
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18 pages, 2878 KiB  
Article
The Impact of War on Heavy Metal Concentrations and the Seasonal Variation of Pollutants in Soils of the Conflict Zone and Adjacent Areas in Mosul City
by Zena Altahaan and Daniel Dobslaw
Environments 2024, 11(11), 247; https://doi.org/10.3390/environments11110247 - 7 Nov 2024
Viewed by 884
Abstract
The present study addresses the war-related soil contamination with heavy metals in the urban area of Mosul/Iraq as a result of the war of liberation from ISIS (2014–2017). In order to cover seasonal influences, a total of eight sample sets from soils in [...] Read more.
The present study addresses the war-related soil contamination with heavy metals in the urban area of Mosul/Iraq as a result of the war of liberation from ISIS (2014–2017). In order to cover seasonal influences, a total of eight sample sets from soils in the conflict area and adjacent areas were collected over the course of the year in two three-month test series, and the parameters pH, E.C., salinity and the heavy metals Cd, Pb, Zn, Cr and Ni were taken as indicators for contamination. Results showed average heavy metal levels in the conflict areas above the global average limits, with some limits also being exceeded in the adjacent areas. All sampling sites were highly contaminated with Cd and moderately contaminated with Pb. The Igeo contamination factors indicated that the sampling sites in the conflict area were moderately to heavily contaminated with Cd, Pb, Zn, Cr and Ni, while the pollution load index indicated that all sites in the conflict zone were extremely to heavily contaminated with heavy metals. The study data give cause for concern that heavy metals may be released into other ecosystems. Full article
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<p>Sampling sites map.</p>
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<p>Seasonal differences in absolute values (in ppm) of heavy metal concentrations in soils by sampling sites; Series 1 (winter and spring), Series 2 (summer and fall).</p>
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17 pages, 1561 KiB  
Article
Scrutinizing the Statistical Distribution of a Composite Index of Soil Degradation as a Measure of Early Desertification Risk in Advanced Economies
by Vito Imbrenda, Marco Maialetti, Adele Sateriano, Donato Scarpitta, Giovanni Quaranta, Francesco Chelli and Luca Salvati
Environments 2024, 11(11), 246; https://doi.org/10.3390/environments11110246 - 6 Nov 2024
Viewed by 736
Abstract
Using descriptive and inferential techniques together with simplified metrics derived from the ecological discipline, we offer a long-term investigation of the Environmental Sensitive Area Index (ESAI) as a proxy of land degradation vulnerability in Italy. This assessment was specifically carried out on a [...] Read more.
Using descriptive and inferential techniques together with simplified metrics derived from the ecological discipline, we offer a long-term investigation of the Environmental Sensitive Area Index (ESAI) as a proxy of land degradation vulnerability in Italy. This assessment was specifically carried out on a decadal scale from 1960 to 2020 at the province (NUTS-3 sensu Eurostat) level and benefited from a short-term forecast for 2030, based on four simplified assumptions grounded on a purely deterministic (‘what … if’) approach. The spatial distribution of the ESAI was investigated at each observation year (1960, 1970, 1980, 1990, 2000, 2010, 2020, 2030) calculating descriptive statistics (central tendency, variability, and distribution shape), deviation from normality, and the increase (or decrease) in diversification in the index scores. Based on nearly 300 thousand observations all over Italy, provinces were considered representative spatial units because they include a relatively broad number of ESAI measures. Assuming a large sample size as a pre-requisite for the stable distribution of the most relevant moments of any statistical distribution—because of the convergence law underlying the central limit theorem—we found that the ESAI scores have increased significantly over time in both central values (i.e., means or medians) and variability across the central tendency (i.e., coefficient of variation). Additionally, ecological metrics reflecting diversification trends in the vulnerability scores delineated a latent shift toward a less diversified (statistical) distribution with a concentration of the observed values toward the highest ESAI scores—possibly reflecting a net increase in the level of soil degradation, at least in some areas. Multiple exploratory techniques (namely, a Principal Component Analysis and a two-way hierarchical clustering) were run on the two-way (data) matrix including distributional metrics (by columns) and temporal observations (by rows). The empirical findings of these techniques delineate the consolidation of worse predisposing conditions to soil degradation in recent times, as reflected in a sudden increase in the ESAI scores—both average and maximum values. These trends underline latent environmental dynamics leading to an early desertification risk, thus representing a valid predictive tool both in the present conditions and in future scenarios. A comprehensive scrutiny of past, present, and future trends in the ESAI scores using mixed (parametric and non-parametric) statistical tools proved to be an original contribution to the study of soil degradation in advanced economies. Full article
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<p>Examples of degraded landscapes reflecting a progressive phenomenon of soil depletion in Southern Italy: (<b>left</b>) natural processes in badlands Italy; (<b>right</b>) human-driven degradation because of overgrazing in ecologically fragile environments).</p>
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<p>Elementary variables, partial indicators, and the composite Environmentally Sensitive Area Index (ESAI).</p>
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<p>The spatial distribution of the ESAI score observed all over Italy at the beginning (1960, (<b>left</b>)) and the end (2020, (<b>right</b>)) of the observation period.</p>
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<p>Mean and whisker plot of the ESAI score distribution over Italian provinces (NUTS-3 level, n = 110) by year (1960–2020) and scenario (S1–S4) for 2030.</p>
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<p>A biplot illustrating the main results (axis 1 vs. axis 2) of a Principal Component Analysis (PCA) on the integrated data matrix containing descriptive statistics, inferential tests, and ecological metrics run on the statistical distribution of the ESAI scores at the province scale (NUTS-3 level, n = 110) in Italy, by year (1960–2020), and the 2030 scenario (S1 to S4).</p>
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<p>Results of a two-way clustering based on Ward’s agglomeration method on the integrated data matrix containing descriptive statistics, inferential tests, and ecological metrics run on the statistical distribution of the ESAI score at the province scale (NUTS-3 level, n = 110) in Italy, by year (1960–2020), and the 2030 scenario (S1 to S4).</p>
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18 pages, 3636 KiB  
Article
How Much Hatchery-Reared Brown Trout Move in a Large, Deep Subalpine Lake? An Acoustic Telemetry Study
by Stefano Brignone, Luca Minazzi, Christophe Molina, Tiziano Putelli and Pietro Volta
Environments 2024, 11(11), 245; https://doi.org/10.3390/environments11110245 - 6 Nov 2024
Viewed by 1408
Abstract
Fish movement into large, deep lakes has been rarely investigated due to the complexity and extent of such ecosystems. Among the different monitoring methods available, acoustic telemetry enables the study of the spatial ecology and behavior of aquatic organisms in lentic environments. In [...] Read more.
Fish movement into large, deep lakes has been rarely investigated due to the complexity and extent of such ecosystems. Among the different monitoring methods available, acoustic telemetry enables the study of the spatial ecology and behavior of aquatic organisms in lentic environments. In this study, the movement of 69 hatchery-reared adult brown trout (size 43–61 cm) marked with acoustic transmitters was monitored in the large and deep subalpine Lake Lugano (Switzerland and Italy). Trout were tracked for six consecutive months by seven acoustic receivers (March–August 2022), positioned in a non-overlapping array. Trout movement was reconstructed using R packages specific for acoustic telemetry (actel and RSP), which also allowed us to translate tracking information into utilization distribution (UD) areas for each fish. The effects of different environmental variables (rainfall, water discharge of the two main tributaries of Lake Lugano, atmospheric pressure, cloud coverage, and moon phases) on trout movement were tested, but none of these variables seemed to significantly correlate with fish movement. After release, most of the tagged fish exhibited reiterative movements during the initial month, with some maintaining this behavior throughout the entire study period. This spatial behavior can be particularly evident in hatchery-reared fish due to their aggressive and bold attitude. The association of these behavioral traits, shaped by domestication, could expose hatchery-reared fish to high risks and post-release mortality in the wild. Indeed, within a few months after the release, most of the tagged fish were no longer detected by the acoustic receivers. In addition, 26% of the total tagged fish were caught by recreational or professional fishermen. Full article
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<p>Map of the study area. The four fish release points (1: Ponte Tresa; 2: Agno; 3: Brusimpiano; 4: Capo San Martino) and the seven acoustic receivers with their average detection range are shown.</p>
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<p>Example of movement profile and a fish performing reiterative movements during the first month.</p>
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<p>The two groups (<b>a</b>,<b>b</b>) identified by the cluster analysis, each consisting of multiple individuals (indicated by their respective tag numbers in the rectangular boxes). To improve clarity and readability, fish of each group are shown separately.</p>
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<p>Size distribution (total length) of fish forming the 7 groups identified by the cluster analysis.</p>
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<p>On the left, a fish marked on 9 March 2022 with an acoustic transmitter and released in Lake Lugano; on the right, the same fish recaptured on 30 December 2022 (9 months later) by a recreational angler.</p>
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19 pages, 2889 KiB  
Article
Simulating Agricultural Water Recycling Using the APEX Model
by Luca Doro, Xiuying Wang and Jaehak Jeong
Environments 2024, 11(11), 244; https://doi.org/10.3390/environments11110244 - 6 Nov 2024
Viewed by 641
Abstract
Irrigation plays a vital role in many agricultural crop production regions. Drainage water recycling (DWR) is a popular irrigation water management system that collects excess water drained from cropland fields and stores it in on-site reservoirs for reuse. The efficacy of these systems [...] Read more.
Irrigation plays a vital role in many agricultural crop production regions. Drainage water recycling (DWR) is a popular irrigation water management system that collects excess water drained from cropland fields and stores it in on-site reservoirs for reuse. The efficacy of these systems varies by location, climate, irrigation frequency, and crop demands. Simulating this system would be beneficial for assessing the impact of water and land management practices on agriculture and natural resources. This study presents the development of computational algorithms for DWR simulation with the Agricultural Policy Environmental eXtender (APEX) model, along with the results for 39 testing sites where both reservoir and drainage systems are adopted. Simulating a DWR system with the revised reservoir module, the APEX model simulates irrigation water reuse ranging between 29% and 93%; sediment reduction of around 66%; nitrogen loss reduction of 23% and 73% for the mineral and organic forms, respectively; and phosphorus loss reduction of 22% and 79% for the soluble and sediment-transported forms, respectively. In conclusion, the results provided by the APEX model for sediment loss reduction align with field data, but discrepancies for nitrogen and phosphorus losses emerged from this test. Full article
(This article belongs to the Special Issue Hydrological Modeling and Sustainable Water Resources Management)
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<p>Graphical representation of the water flows in relation to soil and channel simulated by the APEX model.</p>
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<p>Flowchart of the processes involved in the reservoir simulation.</p>
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<p>Simulation sites (some points overlap each other).</p>
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<p>Simulated and observed average crop yield (standard deviation reported in error bars).</p>
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<p>Sediment loss with and without a reservoir in the model setting. Opaque bars indicate simulation sites where the original model produced unrealistic results.</p>
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<p>Total phosphorus loss with and without a reservoir in the model setting. Opaque bars indicate simulation sites where the original model produced unrealistic results.</p>
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<p>Average annual total irrigation and recycled water use.</p>
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<p>Sediment (<b>top</b>), total nitrogen (<b>middle</b>), and total phosphorus (<b>bottom</b>) losses were simulated with the revised APEX model for the three scenarios. Highlighted in red is the only site where the revised model showed higher sediment losses in the noIrr-Res scenario and increased total N losses under the Irr-Res scenario.</p>
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<p>Sediment (<b>top</b>), total N (<b>middle</b>), and total P (<b>bottom</b>) losses were simulated for the three scenarios with the revised APEX model.</p>
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<p>Mineral (<b>top</b>) and organic (<b>bottom</b>) average N losses for the three scenarios.</p>
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<p>Mineral (<b>top</b>) and organic (<b>bottom</b>) average P losses for the three scenarios.</p>
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16 pages, 2974 KiB  
Article
Atlantic Forest Regeneration Dynamics Following Human Disturbance Cessation in Brazil
by Deicy Carolina Lozano Sivisaca, Celso Anibal Yaguana Puglla, José Raimundo de Souza Passos, Renata Cristina Batista Fonseca, Antonio Ganga, Gian Franco Capra and Iraê Amaral Guerrini
Environments 2024, 11(11), 243; https://doi.org/10.3390/environments11110243 - 2 Nov 2024
Viewed by 1256
Abstract
The Brazilian Atlantic Forest (BAF) is one of the most important biodiversity hotspots and species-rich ecosystems globally. Due to human activities, it has been significantly reduced and fragmented. This study examined both biotic (floristic composition, diversity, and structure) and abiotic (topographic and soil) [...] Read more.
The Brazilian Atlantic Forest (BAF) is one of the most important biodiversity hotspots and species-rich ecosystems globally. Due to human activities, it has been significantly reduced and fragmented. This study examined both biotic (floristic composition, diversity, and structure) and abiotic (topographic and soil) factors in BAF fragments undergoing varying levels and durations of human disturbance cessation: approximately 20 years (20 y), ~30 years (30 y), and over 40 years (>40 y). We aimed to understand the recovery dynamics of floristic composition, diversity, and structure in BAF fragments in relation to abiotic factors. Several statistical tools were employed to examine similarities/differences and relationships. Forests of the 30 y group exhibit significantly greater homogeneity in terms of floristic composition, while forests of the 20 y group are characterized by lower species abundance and diversity. The floristic composition was primarily influenced by soil features and the time of disturbance. Under “Environmental Protection Areas”, soil–vegetation recovery can occur more swiftly than usually observed for BAF. A significant BAF recovery was observed approximately 40 years after the end of human disturbance. A partial recovery featured 30 y disturbed areas, while in 20 y forests, recovery is in its early stages. Human-disturbed BAF can gradually rebound when effective management practices are implemented. Full article
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<p>Study area and BAF fragment locations (“Edgardia and Lageado” Experimental Farm, University of São Paulo State (UNESP), Botucatu, São Paulo State). Sentinel-2 cloudless—<a href="https://s2maps.eu" target="_blank">https://s2maps.eu</a> by EOX IT Services GmbH, (accessed on 31 August 2024). (Contains modified Copernicus Sentinel data 2016 and 2017). License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a>, accessed on 10 September 2024.</p>
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<p>Non-metric multidimensional scaling (NMDS, Stress: 0.13; <span class="html-italic">p</span> &lt; 0.01) revealed the distribution of 2000 m<sup>2</sup> plots based on Bray–Curtis similarity indices of floristic composition within the investigated BAF fragments.</p>
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<p>Integrated rarefaction/extrapolation curves, plotted as a function of the number of individuals in three BAF fragments: human disturbance ceased over 40 (&gt;40 y), approximately 30 (30 y), and ~20 (20 y) years ago. q<sup>0</sup>: species richness (effective number of species), q<sup>1</sup>: Shannon diversity exponent, q<sup>2</sup>: inverse Simpson’s diversity index (solid lines: interpolation; dashed lines: extrapolation; shaded area: 95% confidence intervals).</p>
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<p>Comparison of structural variables among different BAF fragments. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) among BAF fragments based on the Generalized Linear Model (GLM) analysis and Tukey–Kramer test. &gt;40 y, 30 y, 20 y: human disturbance ceased over 40, approximately 30, and ~20 years ago, respectively.</p>
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<p>Basal area distribution per hectare (<b>A</b>) and total number of individuals per hectare (<b>B</b>) by diameter class for trees ≥ 5 cm DBH. &gt;40 y, 30 y, 20 y: human disturbance ceased over 40, approximately 30, and ~20 years ago, respectively. Different letters derived from the generalized linear model (GLM) analysis and the Tukey–Kramer test, <span class="html-italic">p</span> &lt; 0.05, indicate significant statistical differences between the areas per diameter class.</p>
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<p>Canonical Correspondence Analysis (CCA) of factors influencing species distribution among the investigated BAF fragments. Colored points represent forest areas: &gt;40 y (green), 30 y (yellow), 20 y (blue): human disturbance ceased over 40, approximately 30, and ~20 years ago, respectively. Arrows indicate factors with a significant correlation (<span class="html-italic">p</span> &lt; 0.05) with the floristic composition of the sampled units. CEC: cation-exchange capacity; TMI: topographic moisture index; EStime: age of forest areas.</p>
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19 pages, 942 KiB  
Article
Eco-Friendly Detergent Based on Exhausted Edible Vegetable Oils: Impact on Marine and Freshwater Environments, a Case Study Focusing on SARS-CoV-2
by Karin Schlappa, Tecla Bentivoglio, Francesca Provenza, Serena Anselmi, Manuela Piccardo and Monia Renzi
Environments 2024, 11(11), 242; https://doi.org/10.3390/environments11110242 - 31 Oct 2024
Viewed by 1595
Abstract
On 30 January 2020, the World Health Organization declared a public health emergency of international concern due to the rapid spread among humans, on a global scale, of SARS-CoV-2, the virus responsible for COVID-19. Although international authorities have recommended the use of common [...] Read more.
On 30 January 2020, the World Health Organization declared a public health emergency of international concern due to the rapid spread among humans, on a global scale, of SARS-CoV-2, the virus responsible for COVID-19. Although international authorities have recommended the use of common detergents known to be effective against coronaviruses, one of the practices implemented to control the expansion of the virus has been the massive use of disinfectants on indoor and outdoor surfaces, a modality that has raised concern in the scientific community because of its impact on the aquatic environment. Considering possible future scenarios related to ongoing global change, in which further public health emergencies may become more frequent, and given the need to contribute to the identification of eco-friendly alternatives or strategies to mitigate the environmental and human health impacts of the massive use of disinfectants, the aim of this study was to quantify the effects of a liquid surface detergent based on exhausted edible oils of vegetable origin (eco-product). This was done by exposing organisms representing the main trophic levels of the marine and freshwater environment to the eco-detergent before and after a five-day biodegradation process, together with studies on biological oxygen demand and microbiology. The results indicated that the eco-product has potential antimicrobial activity and can be considered as a suitable alternative, although the use of a standardized agent for the production phase of the eco-product in liquid form is recommended to further reduce the impact on the aquatic environment. However, massive and indiscriminate use is a behavior to be discouraged, and limited and restricted use to appropriate areas and contexts is recommended. Full article
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<p>Biological response (%) measured as a function of tested concentrations (mg/L) of <span class="html-italic">eco</span> and <span class="html-italic">eco</span> BOD<sub>5</sub> for each battery organism representing the marine system. Significant differences detected between treatments (and the level of significance) are asterisked. <span class="html-italic">A. fischeri</span> is considered both a marine and freshwater indicator. The green box indicates the estimated Hazard Quotient (HQ<sub>x</sub>) values for both treatments (<span class="html-italic">eco</span>/<span class="html-italic">eco</span> BOD<sub>5</sub>), at 100.0 mg/L, corresponding to a low level of hazard for the marine system.</p>
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<p>EC<sub>x</sub> values (mg/L) calculated for each multi-species marine and freshwater battery exposed to the <span class="html-italic">eco</span>/<span class="html-italic">eco</span>-product BOD<sub>5</sub>; <span class="html-italic">D. magna</span> was exposed to both the <span class="html-italic">eco</span>-product prepared with tap water (100% immobility and no detectable EC<sub>x</sub> value) and the <span class="html-italic">eco</span>-product prepared with standard artificial freshwater (<span class="html-italic">D. magna</span> AFW).</p>
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<p>Biological response (%) as a function of <span class="html-italic">eco</span>/<span class="html-italic">eco</span> BOD<sub>5</sub> concentrations (mg/L) tested on representative freshwater organisms. Significant differences detected (and the level of significance) are asterisked. The response of <span class="html-italic">D. magna</span> is reported according to the treatments performed (tap water: <span class="html-italic">eco/eco</span> BOD<sub>5</sub>; standard artificial freshwater: <span class="html-italic">eco</span> AFW/<span class="html-italic">eco</span> AFW BOD<sub>5</sub>); of all the organisms in the batteries tested, only <span class="html-italic">D. magna</span> was exposed to the <span class="html-italic">eco</span>-product prepared with AFW. Estimated hazard index (TBI) is given for each treatment: heavy hazard is observed for the <span class="html-italic">eco</span> and <span class="html-italic">eco</span> BOD<sub>5</sub> treatments, moderate hazard for the <span class="html-italic">eco</span> AFW treatment, and high hazard for the <span class="html-italic">eco</span> AFW BOD<sub>5</sub> treatment. A conservative worst-case approach was used to estimate the index to the environment under consideration (100.0 mg/L of <span class="html-italic">eco</span>-product). The ecotoxicological hazard scale defined according to the TBI is reported in <a href="#environments-11-00242-t002" class="html-table">Table 2</a>.</p>
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38 pages, 2806 KiB  
Article
Removal of Organic Micropollutants and Microplastics via Ozonation Followed by Granular Activated Carbon Filtration
by Zoé Béalu, Johanna Walther, Attaallah Abusafia, Korinna Altmann, Maren Meurer, Oliver Gretzschel, Michael Schäfer and Heidrun Steinmetz
Environments 2024, 11(11), 241; https://doi.org/10.3390/environments11110241 - 31 Oct 2024
Viewed by 1457
Abstract
Discharge from Wastewater Treatment Plants (WWTPs) can result in the emission of organic micropollutants (OMPs) and microplastics (MPs) into the aquatic environment. To prevent this harmful release, a pilot plant consisting of an ozonation followed by a granular activated carbon (GAC) filter was [...] Read more.
Discharge from Wastewater Treatment Plants (WWTPs) can result in the emission of organic micropollutants (OMPs) and microplastics (MPs) into the aquatic environment. To prevent this harmful release, a pilot plant consisting of an ozonation followed by a granular activated carbon (GAC) filter was operated at a WWTP in Germany, and its side-effects on the concentrations of nitrogen (N) and phosphorous (P) compounds were measured. Over 80% of OMPs and transformation products were removed during the operating time (around 6000 bed volumes) no matter the ozone dose (from around 0.1 to 0.5 mgO3/mgDOC), except for Diatrizoic acid, whose breakthrough appeared at 3500 BV. Formation of the oxidation by-product, NDMA, increased with higher ozone doses, but the concentration remained below 100 ng/L. Bromate was formed at a higher ozone dose (>0.4 mgO3/mgDOC) but at a low concentration—below 10 µg/L. The MP particles detected in the inflow (PE, SBR, PP, and PS) were effectively eliminated to a high degree, with a removal rate of at least 92%. Carbon parameters (COD, DOC, and SAC254) were removed further by the pilot plant, but to different extents. As expected, nitrate was formed during ozonation, while nitrite’s concentration decreased. Further, nitrite decreased and nitrate increased within the GAC filter, while ammonium was eliminated by at least 90%. Total P concentration decreased after the pilot, but the concentration of PO4-P increased. Full article
(This article belongs to the Special Issue Advanced Technologies of Water and Wastewater Treatment (2nd Edition))
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<p>Scheme of pilot plant steps. A, B, C, D, and E designate the sampling points.</p>
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<p>Decision matrix for the selection of organic micropollutants for regular screening in the pilot plant with ozonation and GAC filtration (short list) based on a broader micropollutant screening and literature data. LOQ: limit of quantification.</p>
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<p>Elimination of organic micropollutants through ozonation depending on the specific ozone dose. An average of four samples was taken for each specific ozone dose with their standard deviation (<span class="html-italic">n</span> = 4 for each specific ozone dose, except for Iopromide, which could not be found in the four samples and had too-small concentrations for calculation of elimination in two samples (0.1: <span class="html-italic">n</span> = 1; 0.2: <span class="html-italic">n</span> = 3; 0.5: <span class="html-italic">n</span> = 2). Averages calculated from the mean eliminations of all OMP and for each substance group (pharmaceuticals and metabolites, corrosion inhibitors, X-ray contrast media). DCBZ= 10,11-Dihydro-10,11-Dihydroxycarbamazepine.</p>
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<p>Breakthrough curves of X-ray contrast media, after ozonation and additional GAC filtration. Various ozone doses (0.1 to 0.5 mg<sub>O3</sub>/mg<sub>DOC</sub>) and different EBCTs (from 27 to 40 min) have been applied.</p>
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<p>Concentrations of all detected polymers within their size fractions in the effluent of secondary clarifiers and GAC filter, cycles 1 and 2 [µg/m<sup>3</sup>].</p>
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<p>Elimination of dissolved organic carbon (DOC) depending on the ozone dose and weather condition. DW = dry weather; RW = rainy weather.</p>
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<p>Breakthrough curve of DOC in the combination ozonation and GAC filtration over time. Results of the pilot plant with varying specific ozone doses (0.1–0.5 mg<sub>O3</sub>/mg<sub>DOC</sub>) and EBCT between 27 and 40 min. Rhombus = 0.5 mg<sub>O3</sub>/mg<sub>DOC</sub>; circle = 0.2 mg<sub>O3</sub>/mg<sub>DOC</sub>; square = 0.1 mg<sub>O3</sub>/mg<sub>DOC</sub>.</p>
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<p>Correlation of arithmetic mean of all measured organic micropollutants (OMPs) and the removal of Spectral Absorption Coefficient at 254 nm (SAC<sub>254</sub>) through ozonation and ozonation and GAC in combination.</p>
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24 pages, 5860 KiB  
Article
Temporal and Spatial Variations in Microplastic Concentrations in Small Headwater Basins in the Southern Blue Ridge Mountains, North Carolina, USA
by Jerry Miller, Nathaniel Barrett, Jason Love, Austin Gray, Robert Youker, Chloe Hall, Noa Meiri, Megan Gaesser, Georgeanna Randall, Reagan Jarrett and Juliet Spafford
Environments 2024, 11(11), 240; https://doi.org/10.3390/environments11110240 - 30 Oct 2024
Cited by 1 | Viewed by 1777
Abstract
Microplastics (MPs) are ubiquitous contaminants of emerging concern that require additional study in freshwater streams. We examined the spatial-temporal variations in MP concentrations and characteristics within two headwater basins in the Southern Appalachian Mountains of western North Carolina over ~1 year. Atmospheric samples [...] Read more.
Microplastics (MPs) are ubiquitous contaminants of emerging concern that require additional study in freshwater streams. We examined the spatial-temporal variations in MP concentrations and characteristics within two headwater basins in the Southern Appalachian Mountains of western North Carolina over ~1 year. Atmospheric samples were also collected to determine the significance of atmospheric MP deposition to these relatively small streams. MP concentrations in both basins were within the upper quartile of those reported globally, reaching maximum values of 65.1 MPs/L. Approximately 90% of MPs were fibers. MP composition was dominated by polystyrene, polyamides, and polyethylene terephthalate. Spatially, concentrations were highly variable and increased with development, indicating anthropogenic inputs from urbanized areas. MP concentrations were also elevated in forested tributary subbasins with limited anthropogenic activity, suggesting atmospheric deposition was an important MPs source. Significant atmospheric inputs are supported by high atmospheric depositional rates (ranging between 7.6 and 449.8 MPs/m2/day across our study sites) and similarities in morphology, color, and composition between atmospheric and water samples. Temporally, MP concentrations during storm events increased, decreased, or remained the same in comparison to base flows, depending on the site. The observed spatial and temporal variations in concentrations appear to be related to the complex interplay between precipitation and runoff intensities, channel transport characteristics, and MP source locations and contributions. Full article
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<p>(<b>a</b>) Location of study basins within the eastern U.S.; (<b>b</b>) map of the Richland Creek study basin showing the distribution of sampling sites within the watershed; (<b>c</b>) location of the sampling sites of the Cullasaja River Basin.</p>
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<p>Schematic diagram of the steps used to analyze microplastics in water.</p>
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<p>Composition of MPs extracted from atmospheric, baseflow, and stormflow samples.</p>
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<p>Summary of particle morphology and color within the Richland Creek (<b>a</b>,<b>b</b>) and Cullasaja River (<b>c</b>,<b>d</b>) basins.</p>
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<p>Box and Whisker plots showing MP concentrations at each of the monitoring sites along Richland Creek during baseflow (<b>a</b>) and stormflows (<b>b</b>). Red line shows the areas of high- to medium-intensity development within the basin upstream of the monitoring site. The sites are ordered with respect to the area of upstream development. Note that Sites 2 and 4 are located on tributaries near their confluence with the axial channel of Richland Creek. BF—baseflow; SF—stormflow.</p>
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<p>Spatial trends in the concentration of MPs within the Richland Creek Basin during baseflow conditions. Sites are ordered with respect to the increasing basin development.</p>
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<p>Comparison of particle concentrations between base- and stormflows. Baseflow concentrations shown in blue; stormflow concentrations shown in green. * Significant difference at <span class="html-italic">p</span> &lt; 0.1 level; ** Significant difference at <span class="html-italic">p</span> &lt; 0.05 level. BF—baseflow; SF—stormflow.</p>
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<p>Relationships between wet and total atmosphere deposition at Coweeta (<b>A</b>,<b>B</b>), Highlands Biological Station, HBS (<b>C</b>,<b>D</b>), and Iron Duff (<b>E</b>,<b>F</b>).</p>
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<p>MP color (<b>a</b>) and morphology (<b>b</b>) in atmospheric samples from Coweeta, Highlands Biological Station, HBS, and Iron Duff.</p>
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<p>Range of mean and maximum MP concentrations reported in the literature for river and lakes. Data updated and replotted from Lu et al. [<a href="#B10-environments-11-00240" class="html-bibr">10</a>].</p>
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<p>Comparison of MP color (<b>a</b>) and morphology (<b>b</b>) between atmospheric and water samples. Bar color matches particle color.</p>
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31 pages, 1849 KiB  
Review
Reviewing Digestate Thermal Valorization: Focusing on the Energy Demand and the Treatment of Process Water
by Ebtihal Abdelfatah-Aldayyat, Silvia González-Rojo and Xiomar Gómez
Environments 2024, 11(11), 239; https://doi.org/10.3390/environments11110239 - 29 Oct 2024
Viewed by 1169
Abstract
Anaerobic digestion is a feasible solution for the treatment of organic wastes. The process can reduce the amount of biowaste by stabilizing the organic material and producing biogas susceptible to energetic valorization. However, the digestate needs further valorization when land application is considered [...] Read more.
Anaerobic digestion is a feasible solution for the treatment of organic wastes. The process can reduce the amount of biowaste by stabilizing the organic material and producing biogas susceptible to energetic valorization. However, the digestate needs further valorization when land application is considered unfeasible. Thermal treatments, such as gasification, pyrolysis, and hydrothermal carbonization, are alternatives capable of transforming this material into valuable syngas, obtaining, in many cases, a carbonized stream known as biochar. The feasibility of the process depends on the energy demand for the drying stage and the treatments available for removing contaminants from the syngas, attaining high-quality products, and treating the process-derived water. In the present manuscript, these critical aspects were reviewed considering the characteristics of digestates based on their origin, the modifications of this material during anaerobic digestion, and the way digestate structure affects the final thermal valorization outcome. Emphasis was placed on the energy demand of the global approach and byproduct treatments. Full article
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<p>Scheme representing the primary substrates used in anaerobic digestion and main process parameter.</p>
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<p>Thermal alternatives currently available for digestate valorization.</p>
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<p>Schematic representation of the different types of gasifiers.</p>
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20 pages, 2702 KiB  
Review
Lost in the Dark: Current Evidence and Knowledge Gaps About Microplastic Pollution in Natural Caves
by Manuela Piccardo and Stanislao Bevilacqua
Environments 2024, 11(11), 238; https://doi.org/10.3390/environments11110238 - 29 Oct 2024
Viewed by 929
Abstract
In this study, a systematic review of the scientific literature was carried out to summarize the emerging evidence on microplastic pollution in natural caves. After the screening of 655 papers on the topic from a combined search on the Web of Knowledge and [...] Read more.
In this study, a systematic review of the scientific literature was carried out to summarize the emerging evidence on microplastic pollution in natural caves. After the screening of 655 papers on the topic from a combined search on the Web of Knowledge and the Scopus databases, we found only 14 studies reporting quantitative data on microplastics from a total of 27 natural caves. Most of the assessments focused on water and sediment, with very limited investigations concerning the cave biota. Overall, the most common types of particles found in caves were small (<1 mm) fibers (~70–90% of items), transparent or light-colored, mostly made of polyethylene and polyethylene terephthalate. Anthropogenic cellulosic materials, however, represented a non-negligible portion of particles (i.e., ~20–30%). Microplastic concentrations in caves varied between 0.017 and 911 items/L for water and 7.9 and 4777 items/kg for sediment, thus falling within the levels of microplastic pollution found in other terrestrial, freshwater, and marine environments. Levels of microplastic pollution appear largely variable among caves, stressing the need to extend the geographic and environmental ranges of the assessments, which are currently concentrated on Italian caves on land, with very few case studies from other regions of the world and from marine caves. Despite their putative isolation, natural caves have a high vulnerability to microplastic contamination, requiring much more research effort to understand the potential risk that plastics pose to these fragile ecosystems. Full article
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<p>PRISMA 2020 flow diagram adopted for the systematic review presented [<a href="#B22-environments-11-00238" class="html-bibr">22</a>].</p>
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<p>Identikit of the most representative micro-particles detected in water samples collected in natural caves according to the (<b>a</b>) type, (<b>b</b>) polymer (anthropogenic cellulose = natural cellulose with the presence of chemicals such as dyes, PE = polyethylene, PP = polypropylene, PET = polyethylene terephthalate, PVC = polyvinyl chloride, polyester), (<b>c</b>) color, and (<b>d</b>) class of size. na = not available. Graphs created with Infogram (<a href="https://infogram.com/" target="_blank">https://infogram.com/</a>, accessed on 20 October 2024).</p>
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<p>Identikit of the most representative micro-particles detected in sediment samples collected in natural caves according to the (<b>a</b>) type, (<b>b</b>) polymer (anthropogenic cellulose, PE = polyethylene, PP = polypropylene, PET = polyethylene terephthalate, copolymer), (<b>c</b>) color, and (<b>d</b>) class of size. na = not available. Graphs created with Infogram (<a href="https://infogram.com/" target="_blank">https://infogram.com/</a>, accessed on 20 October 2024).</p>
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<p>Maximum levels of micro-particle/plastic pollution in (<b>a</b>) sediment and (<b>b</b>) water collected worldwide in cave systems. For the correct interpretation of the reference ID, refer to <a href="#environments-11-00238-t001" class="html-table">Table 1</a>.</p>
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<p>Geographical distribution of studies performed on microplastics in cave systems. A special focus on the Italian and Slovenian Karst regions (the most studied areas). Data are shown as percentage of contamination with respect to the maximum (for sediments: Balestra et al. 2024b [<a href="#B32-environments-11-00238" class="html-bibr">32</a>], reference ID = 10; for waters: Sforzi et al. 2024 [<a href="#B24-environments-11-00238" class="html-bibr">24</a>], reference ID = 2). The graphs have been placed inside boxes of different colors, corresponding to the different sub-regions. Numbers in the global map and in bar plots refer to paper ID in <a href="#environments-11-00238-t001" class="html-table">Table 1</a>.</p>
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<p>Ranges (min–max) of particle concentrations in water and sediment from marine (including brackish and estuarine systems), lake (including lakes, ponds, and reservoirs), riverine (including canal, streams, and rivers), soil (water: groundwater including aquifer and wells; sediment: agricultural, urban, and rural soil), and cave environmental compartments. Numbers in brackets indicate the approximate average concentration. For each environmental matrix in each compartment, the most common type of particles, polymers, and colors are also shown (for types of particles and colors, two symbols indicate an almost equal contribution). Data are from the following sources—marines: [<a href="#B48-environments-11-00238" class="html-bibr">48</a>,<a href="#B50-environments-11-00238" class="html-bibr">50</a>,<a href="#B51-environments-11-00238" class="html-bibr">51</a>,<a href="#B52-environments-11-00238" class="html-bibr">52</a>,<a href="#B53-environments-11-00238" class="html-bibr">53</a>,<a href="#B54-environments-11-00238" class="html-bibr">54</a>,<a href="#B55-environments-11-00238" class="html-bibr">55</a>,<a href="#B56-environments-11-00238" class="html-bibr">56</a>,<a href="#B57-environments-11-00238" class="html-bibr">57</a>,<a href="#B58-environments-11-00238" class="html-bibr">58</a>]; lakes: [<a href="#B48-environments-11-00238" class="html-bibr">48</a>,<a href="#B51-environments-11-00238" class="html-bibr">51</a>,<a href="#B59-environments-11-00238" class="html-bibr">59</a>,<a href="#B60-environments-11-00238" class="html-bibr">60</a>,<a href="#B61-environments-11-00238" class="html-bibr">61</a>]; rivers: [<a href="#B48-environments-11-00238" class="html-bibr">48</a>,<a href="#B51-environments-11-00238" class="html-bibr">51</a>,<a href="#B58-environments-11-00238" class="html-bibr">58</a>,<a href="#B60-environments-11-00238" class="html-bibr">60</a>,<a href="#B61-environments-11-00238" class="html-bibr">61</a>,<a href="#B62-environments-11-00238" class="html-bibr">62</a>,<a href="#B63-environments-11-00238" class="html-bibr">63</a>,<a href="#B64-environments-11-00238" class="html-bibr">64</a>]; soil: [<a href="#B48-environments-11-00238" class="html-bibr">48</a>,<a href="#B49-environments-11-00238" class="html-bibr">49</a>,<a href="#B51-environments-11-00238" class="html-bibr">51</a>,<a href="#B65-environments-11-00238" class="html-bibr">65</a>,<a href="#B66-environments-11-00238" class="html-bibr">66</a>,<a href="#B67-environments-11-00238" class="html-bibr">67</a>,<a href="#B68-environments-11-00238" class="html-bibr">68</a>]; caves: this study.</p>
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14 pages, 5639 KiB  
Article
Evaluating Indoor Air Quality in Residential Environments: A Study of PM2.5 and CO2 Dynamics Using Low-Cost Sensors
by Kabir Bahadur Shah, Dylan Kim, Sai Deepak Pinakana, Mkhitar Hobosyan, Armando Montes and Amit U. Raysoni
Environments 2024, 11(11), 237; https://doi.org/10.3390/environments11110237 - 28 Oct 2024
Viewed by 1508
Abstract
Indoor air quality (IAQ) poses a significant public health concern, and exposures to high levels of fine particulate matter (PM2.5) and carbon dioxide (CO2) could have detrimental health impacts. This study focused on assessing the indoor air pollutants in [...] Read more.
Indoor air quality (IAQ) poses a significant public health concern, and exposures to high levels of fine particulate matter (PM2.5) and carbon dioxide (CO2) could have detrimental health impacts. This study focused on assessing the indoor air pollutants in a residential house located in the town of Mission, Hidalgo County, South Texas, USA. The PM2.5 and CO2 were monitored indoors: the kitchen and the bedroom. This investigation also aimed to elucidate the effects of household activities such as cooking and human occupancy on these pollutants. Low-cost sensors (LCSs) from TSI AirAssure™ were used in this study. They were deployed within the breathing zone at approximately 1.5 m above the ground. Calibration of the low-cost sensors against Federal Equivalent Method (FEM) instruments was undertaken using a multiple linear regression method (MLR) model to improve the data accuracy. The indoor PM2.5 levels were significantly influenced by cooking activities, with the peak PM2.5 concentrations reaching up to 118.45 μg/m3. The CO2 levels in the bedroom increased during the occupant’s sleeping period, reaching as high as 1149.73 ppm. The health risk assessment was assessed through toxicity potential (TP) calculations for the PM2.5 concentrations. TP values of 0.21 and 0.20 were obtained in the kitchen and bedroom, respectively. The TP values were below the health hazard threshold (i.e., TP < 1). These low TP values could be attributed to the use of electric stoves and efficient ventilation systems. This research highlights the effectiveness of low-cost sensors for continuous IAQ monitoring and helps promote better awareness of and necessary interventions for salubrious indoor microenvironments. Full article
(This article belongs to the Special Issue Air Quality, Health and Climate)
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<p>Location of the study site and the nearest TCEQ C-43.</p>
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<p>Floor plan of the residence, along with the installation of the low-cost sensors in the bedroom and kitchen.</p>
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<p>FEM instruments used for the colocation with the LCSs during the calibration period: (<b>a</b>) Q-Trak™ Indoor Air Quality Monitor, Model: 7575 [<a href="#B56-environments-11-00237" class="html-bibr">56</a>]; and (<b>b</b>) GRIMM Portable Aerosol Spectrometer, Model: 11-D [<a href="#B57-environments-11-00237" class="html-bibr">57</a>].</p>
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<p>(<b>a</b>) Scatterplots showing the comparison between the 1 h PM<sub>2.5</sub> (μg/m<sup>3</sup>) from GRIMM (<span class="html-italic">X</span>-axis) and TSI AirAssure (<span class="html-italic">Y</span>-axis). (<b>b</b>) Scatterplots showing the comparison between the 1 h CO<sub>2</sub> (ppm) from Q-Trak (<span class="html-italic">X</span>-axis) and TSI AirAssure (<span class="html-italic">Y</span>-axis).</p>
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<p>Time series of the PM<sub>2.5</sub> and CO<sub>2</sub> concentrations during the calibration period: comparison of LCS, FEM (GRIMM, Q-Trak), and corrected values.</p>
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<p>Time series showing the 1 h averaged PM<sub>2.5</sub> and CO<sub>2</sub> for the kitchen and bedroom obtained from the LCSs during a 1-month study period. The highlighted section represents the days when the house was unoccupied.</p>
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<p>Hourly boxplots of the PM<sub>2.5</sub> and CO<sub>2</sub> for the kitchen and bedroom, including the primary sources during the 1-month study period.</p>
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<p>Time series showing the 1 h averaged PM<sub>2.5</sub> for the kitchen and bedroom during the 1-month study period, including the ambient PM<sub>2.5</sub> obtained from Mission C-43 (Note: C-43 does not monitor CO<sub>2</sub>). The highlighted section represents the days when the house was unoccupied.</p>
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3 pages, 157 KiB  
Editorial
Innovations in Wastewater Treatment
by Simeone Chianese and Dino Musmarra
Environments 2024, 11(11), 236; https://doi.org/10.3390/environments11110236 - 25 Oct 2024
Viewed by 775
Abstract
The rapid growth of the world population and climate change are two key factors that immensely affect freshwater availability [...] Full article
3 pages, 148 KiB  
Editorial
Pathways to Net-Zero—Innovations and Challenges in Achieving Carbon Neutrality
by Shu-Yuan Pan
Environments 2024, 11(11), 235; https://doi.org/10.3390/environments11110235 - 25 Oct 2024
Viewed by 798
Abstract
The global pursuit of net-zero carbon emissions has become one of the most critical challenges of the 21st century, as extreme climate events, rising temperatures, and environmental degradation force a reckoning with the carbon-intensive practices that define many of our industrial, agricultural, and [...] Read more.
The global pursuit of net-zero carbon emissions has become one of the most critical challenges of the 21st century, as extreme climate events, rising temperatures, and environmental degradation force a reckoning with the carbon-intensive practices that define many of our industrial, agricultural, and energy systems [...] Full article
(This article belongs to the Special Issue Net-Zero Principles and Practices)
13 pages, 2193 KiB  
Technical Note
A Method to Quantify the Drainage Basin Contributions to Transitional Water Bodies: Numerical Modeling Applied to the Case Study of Venice Lagoon
by Alessandra Feola, Andrea Bonometto, Devis Canesso, Andrea Pedroncini, Federica Cacciatore, Marta Novello, Alessandra Girolimetto, Massimo Zorzi and Rossella Boscolo Brusà
Environments 2024, 11(11), 234; https://doi.org/10.3390/environments11110234 - 24 Oct 2024
Viewed by 1087
Abstract
The trophic, chemical and ecological state of a lagoon is strongly influenced by numerous aspects, among which the quantity and quality of the water coming from its drainage basin are a priority. The Source-to-Sea approach directly addresses the linkages between land, water, delta, [...] Read more.
The trophic, chemical and ecological state of a lagoon is strongly influenced by numerous aspects, among which the quantity and quality of the water coming from its drainage basin are a priority. The Source-to-Sea approach directly addresses the linkages between land, water, delta, estuary, coast, nearshore and ocean ecosystems to identify appropriate courses of action to address alterations of key flows, resulting in economic, social and environmental benefits. Hydrodynamic modeling has become a fundamental tool for describing the dynamics of marine environments, and a specific field of development of ongoing research is a detailed representation of the land–coastal–sea fluxes. In the present study, a numerical modeling tool was used in the Venice Lagoon to assess and quantify dominant contributions from the river basin within specific areas of the lagoon. An advective–diffusive model was used to reproduce the transport of passive tracers. The results were analyzed using an automated computational tool, obtaining the average percentage contribution of each input from the drainage basin and mean concentrations of tracer in the different water bodies. Through the proposed methodology, it is possible to support the planning of specific measures, identifying priorities of management intervention and preliminarily exploring different scenarios. Full article
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<p>Lagoon of Venice (Italy, Veneto Region) with drainage basin inputs. Water bodies (WBs) according to the Water Framework Directive and bathymetry (data by Interregional Superintendency for Public Works in Veneto) are also reported. See the red box for zoomed-in details.</p>
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<p>Computational mesh, with around 100,500 elements and 61,000 nodes and a resolution ranging from 250 m at the sea boundary to around 75 m in the inner parts of the lagoon, is represented (see the red box for a zoomed detail). VLCS and VLN, heavily modified WBs, are excluded from the computational mesh.</p>
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<p>Dominant tributaries of the drainage basin with the maximum permanence of the highest concentration among all the tributaries.</p>
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<p>The percentage of time that the tracer, introduced from the dominant tributary remains higher than others. (WB acronyms: P = Polyhaline, E = Euhaline, C = choked, NC = not choked).</p>
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17 pages, 6068 KiB  
Article
Multi-Index Drought Analysis in Choushui River Alluvial Fan, Taiwan
by Youg-Sin Cheng, Jiay-Rong Lu and Hsin-Fu Yeh
Environments 2024, 11(11), 233; https://doi.org/10.3390/environments11110233 - 24 Oct 2024
Cited by 1 | Viewed by 785
Abstract
In recent years, increasing drought events due to climate change have led to water scarcity issues in Taiwan, severely impacting the economy and ecosystems. Understanding drought is crucial. This study used Landsat 8 satellite imagery, rainfall, and temperature data to calculate four drought [...] Read more.
In recent years, increasing drought events due to climate change have led to water scarcity issues in Taiwan, severely impacting the economy and ecosystems. Understanding drought is crucial. This study used Landsat 8 satellite imagery, rainfall, and temperature data to calculate four drought indices, including the Temperature Vegetation Dryness Index (TVDI), improved Temperature Vegetation Dryness Index (iTVDI), Normalized Difference Drought Index (NDDI), and Standardized Precipitation Index (SPI), to investigate spatiotemporal drought variations in the Choushui River Alluvial Fan over the past decade. The findings revealed differences between TVDI and iTVDI in mountainous areas, with iTVDI showing higher accuracy based on soil moisture data. Correlation analysis indicated that drought severity increased with decreasing rainfall or vegetation. The study highlights the significant role of vegetation and precipitation in influencing drought conditions, providing valuable insights for water resource management. Full article
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<p>Geographic location of the Choushui River Alluvial Fan.</p>
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<p>The Sentinel-2 satellite images were used to classify and map the land use and cover in the study area.</p>
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<p>The satellite images from TerraClimate were used to classify and map the soil moisture in the study area from 2013 to 2022.</p>
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<p>The parameters needed for calculating drought indices using remote sensing technology.</p>
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<p>The scatter diagram and dry/wet edges of NDVI with LST in the dry/wet seasons.</p>
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<p>The TVDI distribution over the Choushui River Alluvial Fan was mapped using Landsat 8 satellite images from 2013 to 2022.</p>
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<p>The iTVDI distribution over the Choushui River Alluvial Fan was mapped using Landsat 8 satellite images from 2013 to 2022.</p>
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<p>The differences in the distribution of TVDI and iTVDI over the Choushui River Alluvial Fan were mapped using Landsat 8 satellite images from 2013 to 2022.</p>
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<p>The NDDI distribution over the Choushui River Alluvial Fan was mapped using Landsat 8 satellite images from 2013 to 2022.</p>
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<p>The SPI analysis results from May 2013 to December 2022. SPI less than −1.5 indicates severe drought.</p>
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<p>The correlation between TVDI, iTVDI, NDDI, and soil moisture in 2013 and 2019.</p>
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<p>The correlation between iTVDI and drought indices in 2015.</p>
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28 pages, 3510 KiB  
Review
Harnessing Ascidians as Model Organisms for Environmental Risk Assessment
by Amalia Rosner and Baruch Rinkevich
Environments 2024, 11(11), 232; https://doi.org/10.3390/environments11110232 - 23 Oct 2024
Viewed by 1139
Abstract
Environmental Risk Assessment (ERA) often relies on a restricted set of species as bio-indicators, introducing uncertainty when modeling complex environmental variables. This may lead to oversimplified or erroneous risk assessments. Ascidians, marine filter-feeding sessile chordates, are valuable models for scientific research in various [...] Read more.
Environmental Risk Assessment (ERA) often relies on a restricted set of species as bio-indicators, introducing uncertainty when modeling complex environmental variables. This may lead to oversimplified or erroneous risk assessments. Ascidians, marine filter-feeding sessile chordates, are valuable models for scientific research in various biological fields such as stem cell biology, embryogenesis, regeneration, innate immunity, and developmental biology. Their global distribution, sensitivity to pollutants, high abundance, mass sexual reproduction, and habitation in coastal areas impacted by anthropogenic pollution make them excellent indicators for monitoring marine pollution and global environmental changes, including biological invasions and species diversity diminution cases. Despite their potential as environmental bioindicators, ascidians remain underutilized in ERAs (≤0.13% of ERA studies), particularly in the field of chemical pollution impact assessment, primarily due to a lack of standardization. This underrepresentation poses a challenge for accurate modeling, especially in models relying on a broad range of species (e.g., Species Sensitivity Distributions). Given these constraints, expanding the use of ascidians in ERAs could improve the comprehension and precision of environmental changes and their assessments. This underscores the necessity for future research to establish standardized testing protocols and choose the most suitable ascidian species for inclusion in ERAs. Full article
(This article belongs to the Special Issue Environmental Risk Assessment of Aquatic Ecosystem)
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<p>Phylogenetic tree based on 18S ribosomal RNA (18S rRNA) gene fragments of ascidian species reviewed in this study. A few species are not represented due to the absence of their 18S gene sequences in the database. The taxonomic order of the species is depicted, illustrating the clustering of species within the same order. The analysis was conducted using the EMBL-EBI T-Coffee program [<a href="#B33-environments-11-00232" class="html-bibr">33</a>]. The NCBI GenBank accession numbers for the 18S rRNA gene sequences used are as follows: <span class="html-italic">Ascidiella scabra</span> (AB811928.1), <span class="html-italic">Botrylloides leachi</span> (JN573237.1), <span class="html-italic">Botrylloides_violaceus</span> (AY903927.1), <span class="html-italic">Botryllus_schlosseri</span> (FM244858.1), <span class="html-italic">Ciona intestinalis</span> (AB013017.1), <span class="html-italic">Ciona savignyi</span> (LC547329.1), <span class="html-italic">Didemnum molle</span> (AB211071.1), <span class="html-italic">Didemnum vexillum</span> (JF738071.1), <span class="html-italic">Halocynthia roretzi</span> (AB013016.1), <span class="html-italic">Herdmania momus</span> (AF165827.1), <span class="html-italic">Microcosmus exasperates</span> (XR005567858.1), <span class="html-italic">Molgula manhattensis</span> (L12426.2), <span class="html-italic">Phallusia nigra</span> (FM244845.1), <span class="html-italic">Polycarpa mytiligera</span> (FM244860.1), <span class="html-italic">Styela clava</span> (XR_005567858.1), <span class="html-italic">Styela_plicata</span> (L12444.2).</p>
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<p>Modes of life cycles in two ascidian model species: (<b>a</b>) a solitary ascidian (<span class="html-italic">Ciona</span> spp.) revealing classical sexual reproduction progressions of a broadcasting species; (<b>b</b>) asexual (outer cycle in the diagram) and sexual phases in a colonial ascidian (<span class="html-italic">Botryllus schlosseri</span>) highlighted by weekly astogenic rounds of zooidal life and death (each cycle is called blastogenesis). Each blastogenic cycle is divided into four stages (A–D) where three generations of colonial modules (the functional zooids and two cohorts of developing buds, primary and secondary buds) coexist side by side, depicting highly synchronized developmental statuses as the colony progresses through blastogenesis. At stage D, the functional zooids start their degeneration, first by closing the siphons, where simultaneously all zooids undergo cell apoptosis and phagocytosis processes within the next 24–36 h and are morphologically absorbed, while the primary buds mature to the zooidal level of development. Subsequently, stage A of the following blastogenic cycle begins as primary buds complete their development into zooids by opening the inhalant siphons and resuming water filtration, while secondary buds (budlets) develop to the primary bud’s state, starting the generation of new sets of secondary buds. Gametogenesis is highly synchronized with the blastogenic cycle among modules of the same generation. The sexual cycle is typified as brooding, where gametes start differentiation within the budlets. Gametes maturation and egg fertilization occur within the zooids (at the onset of stage A). Embryos differentiation is synchronized with the blastogenic stage and continues within the zooids (inner cycle; showing for each blastogenic stage a single large zooid with its bud/s and budlet/s), culminating in the release of the larvae into the surrounding waters at late blastogenic stage C. The larvae swim for a very short period until they settle, undergo metamorphosis starting with the absorption of the tail, and new juveniles (oozooids) are formed, and a colony is formed by repeated blastogenic cycles.</p>
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<p>Pie charts depicting taxa percentages for search hits in the ‘Web of Science’ and ‘Google Scholar’ databases, filtered by the terms ‘environmental risk assessments’ and ‘marine’ environment, as compared to the total hits for ‘environmental risk assessment’ (marine and terrestrial). Each taxon (a group of different bioindicators) is represented by a specific-colored descriptor detailed in the caption. The black sections encompass the residual hits for taxa with the smaller number of hits. The magnified pie sections on the right provide a detailed breakdown for some of these taxa. <a href="#app1-environments-11-00232" class="html-app">Supplementary Table S1</a> details the specific queries used to obtain the data for each taxon.</p>
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<p>Commonly used model ascidians: the solitary ascidians (<b>a</b>) <span class="html-italic">Ciona robusta</span> and (<b>b</b>) <span class="html-italic">Ciona intestinalis</span> (by John Bishop from the Marine Biological Association of the United Kingdom), once considered as a single species; (<b>c</b>,<b>d</b>) different color morphs of the colonial ascidian <span class="html-italic">Botryllus schlosseri</span>. (<b>c</b>) A colony reared in the laboratory at the Israel Oceanography and Limnological Research, Haifa, and maintained at a constant temperature of 20 °C with a regimen of 12:12 light:dark hours. This colony is a descendant of the Monterey, California, population; (<b>d</b>) a colony from New Zealand reared on a glass slide.</p>
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<p>Pictures of additional solitary (<b>a</b>–<b>c</b>) and colonial ascidian (<b>d</b>–<b>f</b>) used in toxicity, environmental pollution monitoring tests, and biological invasions. (<b>a</b>) <span class="html-italic">Phallusia</span> spp.; (<b>b</b>) <span class="html-italic">Polycarpa</span> spp.; (<b>c</b>) <span class="html-italic">Halocynthia</span> spp.; (<b>d</b>) <span class="html-italic">Botrylloides</span> spp.; (<b>e</b>) <span class="html-italic">Didemnum</span> spp.; (<b>f</b>) <span class="html-italic">Didemnum vexillum</span>.</p>
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<p>Pie charts depicting taxa percentages for search hits in ‘Google Scholar’ databases, filtered by the terms: (<b>a</b>) ‘environmental risk assessment’ and ‘marine’ environment, and ‘invasion’ (61.5% of hits) as compared to the total hits for ‘environmental risk assessments’ and ‘invasion’ (100%). The total number of hits involving individual taxa exceeds the number of hits for ‘environmental risk assessment’, ‘marine’ environment, and ‘invasion’, as many publications examine multiple taxa; (<b>b</b>) ‘environmental risk assessment’ and ‘marine’ environment, and ‘biodiversity’ (62.6%) as compared to the total hits for ‘environmental risk assessments’ and ‘biodiversity’ (100%). The total number of hits involving individual taxa exceeds the number of hits for ‘environmental risk assessment’ and ‘marine’ environment and ‘biodiversity’, as many publications examine multiple taxa. Each taxon is represented by a specific-colored descriptor detailed in the caption. The magnified pie sections on the right are for categories with smaller numbers of hits. <a href="#app1-environments-11-00232" class="html-app">Supplementary Table S2</a> details the specific queries used to obtain the data for each taxon.</p>
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<p>A graphical representation illustrating the potential applications of ascidian-based bioassays within the framework of ERA. The bioassays utilize both solitary and colonial ascidians, which may offer unique advantages for studying different environmental impacts. MCR—multiple clonal ramets; Blue arrows indicate bioassays that have already been successfully employed in toxicity testing; Red arrows represent potential applications that have yet to be widely explored.</p>
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