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Search Results (3,161)

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30 pages, 28793 KiB  
Article
An Investigation of the SOCOLv4 Model’s Suitability for Predicting the Future Evolution of the Total Column Ozone
by Georgii Nerobelov, Yurii Timofeyev, Alexander Polyakov, Yana Virolainen, Eugene Rozanov and Vladimir Zubov
Atmosphere 2024, 15(12), 1491; https://doi.org/10.3390/atmos15121491 - 14 Dec 2024
Viewed by 226
Abstract
The anthropogenic impact on the ozone layer is expressed in anomalies in the total ozone content (TOC) on a global scale, with periodic enhancements observed in high-latitude areas. In addition, there are significant variations in TOC time trends at different latitudes and seasons. [...] Read more.
The anthropogenic impact on the ozone layer is expressed in anomalies in the total ozone content (TOC) on a global scale, with periodic enhancements observed in high-latitude areas. In addition, there are significant variations in TOC time trends at different latitudes and seasons. The reliability of the TOC future trends projections using climate chemistry models must be constantly monitored and improved, exploiting comparisons against available measurements. In this study, the ability of the Earth’s system model SOCOLv4.0 to predict TOC is evaluated by using more than 40 years of satellite measurements and meteorological reanalysis data. In general, the model overpredicts TOC in the Northern Hemisphere (by up to 16 DU) and significantly underpredicts it in the South Pole region (by up to 28 DU). The worst agreement was found in both polar regions, while the best was in the tropics (the mean difference constitutes 4.2 DU). The correlation between monthly means is in the range of 0.75–0.92. The SOCOLv4 model significantly overestimates air temperature above 1 hPa relative to MERRA2 and ERA5 reanalysis (by 10–20 K), particularly during polar nights, which may be one of the reasons for the inaccuracies in the simulation of polar ozone anomalies by the model. It is proposed that the SOCOLv4 model can be used for future projections of TOC under the changing scenarios of human activities. Full article
(This article belongs to the Special Issue Measurement and Variability of Atmospheric Ozone)
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Figure 1

Figure 1
<p>Global distribution of mean differences or MD (<b>a</b>), SDD (<b>b</b>), and correlation coefficients (<b>c</b>) between TOC by SOCOLv4 modeling and satellite observations (CAMS MSR for 1980–2022—<b>left</b>, IKFS-2 for 2015–2022—<b>middle</b>, IASI for 2008–2023—<b>right</b>).</p>
Full article ">Figure 2
<p>Seasonal global distribution of mean differences or MD (<b>left</b>), SDD (<b>center</b>), and correlation coefficients (<b>right</b>) between TOC by SOCOLv4 modeling and combined satellite observations in CAMS MSR dataset in winter (JJA, (<b>a</b>)), spring (MAM, (<b>b</b>)), summer (JJA, (<b>c</b>)) and autumn (SON, (<b>d</b>)) for 1980–2022.</p>
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<p>Monthly mean TOC averaged in zones 70–90° N (<b>a</b>) and 70–90° S (<b>b</b>) by SOCOLv4 modeling (ensemble member mean) and CAMS MSR dataset for 1980–2022 and their differences (SOCOLv4 minus obs.).</p>
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<p>Monthly mean TOC averaged in zones 70–90° N (<b>a</b>) and 70–90° S (<b>b</b>) by SOCOLv4 modeling (ensemble member mean) and satellite observations (IASI—2008–2023, IKFS-2—2015–2022) and their differences (SOCOLv4 minus obs.).</p>
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<p>Monthly and globally averaged mean TOCs from SOCOLv4 modeling (ensemble member mean) and CAMS MSR and their differences (SOCOLv4 minus CAMS MSR).</p>
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<p>Deseasonolized monthly and globally averaged mean TOCs from SOCOLv4 modeling (ensemble member mean) and CAMS MSR for 1980–1992 (<b>a</b>) and 1993–2022 (<b>b</b>) and their regression lines.</p>
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<p>Zonal distribution of mean difference ((<b>a</b>), MD), its SDD (<b>b</b>), and correlation (CC, (<b>c</b>)) between air temperature from SOCOLv4 and reanalysis (ERA5 on the left and MERRA2 on the right) data for 1980–2023; dots indicate statistically insignificant differences according to <span class="html-italic">t</span>-test (0.95 confidence level).</p>
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<p>Monthly mean air temperature averaged in zone 60–90° N at 100 hPa (<b>a</b>) and 1 hPa (<b>b</b>) by SOCOLv4 modeling (ensemble member mean) and reanalysis data (ERA5 and MERRA2) for DJF 1980–2023 and their differences (SOCOLv4 minus reanalysis).</p>
Full article ">Figure 8 Cont.
<p>Monthly mean air temperature averaged in zone 60–90° N at 100 hPa (<b>a</b>) and 1 hPa (<b>b</b>) by SOCOLv4 modeling (ensemble member mean) and reanalysis data (ERA5 and MERRA2) for DJF 1980–2023 and their differences (SOCOLv4 minus reanalysis).</p>
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<p>Zonal distribution of R<sup>2</sup> between air temperature from SOCOLv4 (<b>a</b>) and reanalysis data (ERA5—(<b>b</b>), MERRA2—(<b>c</b>)) and MLR model data for 1980–2022; black dots depict zones where MLR model is statistically significant at a 0.95 confidence level.</p>
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<p>Zonal distribution of decadal trend of deseasonalized air temperature from SOCOLv4 (<b>a</b>) and reanalysis data (ERA5—(<b>b</b>), MERRA2—(<b>c</b>)) for 1980–2022; dashed line depicts the area of R<sup>2</sup> ≥ 0.5 (between deseasonalized air temperature and linear regression).</p>
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<p>Time series of MLR predictors ((<b>a</b>)—CHC-11 content, (<b>b</b>)—ENSO parameter, (<b>c</b>)—QBO parameter, (<b>d</b>)—solar radiation in radio range, (<b>e</b>)—AOD).</p>
Full article ">Figure A2
<p>Zonal distribution of mean differences or MD, SDD of MD, and correlation coefficients between TOC from SOCOLv4 modelling and satellite observations (CAMS MSR for 1980–2022—(<b>a</b>), IKFS-2 for 2015–2022—(<b>b</b>), IASI for 2008–2023—(<b>c</b>)).</p>
Full article ">Figure A2 Cont.
<p>Zonal distribution of mean differences or MD, SDD of MD, and correlation coefficients between TOC from SOCOLv4 modelling and satellite observations (CAMS MSR for 1980–2022—(<b>a</b>), IKFS-2 for 2015–2022—(<b>b</b>), IASI for 2008–2023—(<b>c</b>)).</p>
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<p>Zonal distribution of mean difference (MD) between air temperature from SOCOLv4 and reanalysis data (ERA5 on the left, MERRA2 on the right) for winter (<b>a</b>), spring (<b>b</b>), summer (<b>c</b>), and autumn (<b>d</b>) 1980–2023; dots indicate statistical insignificant differences according to <span class="html-italic">t</span>-test (0.95 confidence level).</p>
Full article ">Figure A3 Cont.
<p>Zonal distribution of mean difference (MD) between air temperature from SOCOLv4 and reanalysis data (ERA5 on the left, MERRA2 on the right) for winter (<b>a</b>), spring (<b>b</b>), summer (<b>c</b>), and autumn (<b>d</b>) 1980–2023; dots indicate statistical insignificant differences according to <span class="html-italic">t</span>-test (0.95 confidence level).</p>
Full article ">Figure A4
<p>Zonal distribution of the SDD between air temperature from SOCOLv4 and reanalysis data (ERA5 on the left, MERRA2 on the right) for winter(<b>a</b>), spring (<b>b</b>), summer (<b>c</b>), and autumn (<b>d</b>) 1980–2023; dots indicate statistical insignificant differences according to <span class="html-italic">t</span>-test (0.95 confidence level).</p>
Full article ">Figure A4 Cont.
<p>Zonal distribution of the SDD between air temperature from SOCOLv4 and reanalysis data (ERA5 on the left, MERRA2 on the right) for winter(<b>a</b>), spring (<b>b</b>), summer (<b>c</b>), and autumn (<b>d</b>) 1980–2023; dots indicate statistical insignificant differences according to <span class="html-italic">t</span>-test (0.95 confidence level).</p>
Full article ">Figure A5
<p>Zonal distribution of the correlation coeffitients between air temperature from SOCOLv4 and reanalysis data (ERA5 on the left, MERRA2 on the right) for winter (<b>a</b>), spring (<b>b</b>), summer (<b>c</b>), and autumn (<b>d</b>) 1980–2023; dots indicate statistical insignificant differences according to <span class="html-italic">t</span>-test (0.95 confidence level).</p>
Full article ">Figure A5 Cont.
<p>Zonal distribution of the correlation coeffitients between air temperature from SOCOLv4 and reanalysis data (ERA5 on the left, MERRA2 on the right) for winter (<b>a</b>), spring (<b>b</b>), summer (<b>c</b>), and autumn (<b>d</b>) 1980–2023; dots indicate statistical insignificant differences according to <span class="html-italic">t</span>-test (0.95 confidence level).</p>
Full article ">Figure A6
<p>Monthly mean air temperature averaged in zone 60–90° N at 100 hPa (<b>a</b>) and 1 hPa (<b>b</b>) by SOCOLv4 modelling (ensemble member mean) and reanalysis data (ERA5 and MERRA2) for 1980–2023 and their differences (SOCOLv4 minus reanalysis).</p>
Full article ">Figure A6 Cont.
<p>Monthly mean air temperature averaged in zone 60–90° N at 100 hPa (<b>a</b>) and 1 hPa (<b>b</b>) by SOCOLv4 modelling (ensemble member mean) and reanalysis data (ERA5 and MERRA2) for 1980–2023 and their differences (SOCOLv4 minus reanalysis).</p>
Full article ">
16 pages, 1023 KiB  
Article
Life Cycle Assessment of the Gasoline Supply Chain in Sri Lanka
by Madhurika Geethani and Asela Kulatunga
Sustainability 2024, 16(24), 10933; https://doi.org/10.3390/su162410933 - 13 Dec 2024
Viewed by 333
Abstract
The Sri Lankan transport sector still depends predominantly on petroleum fuels, mainly diesel and gasoline. Gasoline holds the second highest market share, and with the increasing number of gasoline-fueled vehicles, its proportion in the transport fuel mix is continuously expanding. The main objective [...] Read more.
The Sri Lankan transport sector still depends predominantly on petroleum fuels, mainly diesel and gasoline. Gasoline holds the second highest market share, and with the increasing number of gasoline-fueled vehicles, its proportion in the transport fuel mix is continuously expanding. The main objective of this study is to assess the ecological burden associated with the gasoline supply chain in Sri Lanka by conducting a life cycle assessment from a ‘well-to-tank’ perspective. In the scenario analysis, the environmental impacts of four potential gasoline distribution scenarios were assessed and compared with the existing distribution model. According to the results, the refining process was predominant, contributing more than 50% to climate change, terrestrial acidification, marine and freshwater eutrophication, human toxicity, and water and marine ecotoxicities. Meanwhile, crude oil extraction dominates in its contribution to ozone depletion, photochemical oxidant formation, freshwater ecotoxicity, and fossil depletion. The results of the scenario analysis show a remarkable reduction in the environmental load when rail transport is solely used to transfer gasoline from bulk terminals to regional depots. The reduction is over 65% in most impact categories compared to the existing distribution method, which involves a combination of both road and rail transport. This study identifies the key areas that need to be further analyzed to lower the environmental impacts while also establishing a foundation for conducting comparative environmental assessments of alternative fuel options in the Sri Lankan context. Full article
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<p>System boundary for the gasoline supply chain.</p>
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<p>Contributions of subsystems in the gasoline supply chain to the various impact categories.</p>
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<p>Comparison of environmental impacts of different scenarios of fuel distribution.</p>
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16 pages, 574 KiB  
Article
Air Pollution’s Hidden Toll: Links Between Ozone, Particulate Matter, and Adolescent Depression
by Megan Waxman and Erika M. Manczak
Int. J. Environ. Res. Public Health 2024, 21(12), 1663; https://doi.org/10.3390/ijerph21121663 - 13 Dec 2024
Viewed by 297
Abstract
Rising rates of depression among youth present a growing mental health crisis. Despite growing concerns regarding the risks of air pollution exposure on youth mental and physical health, associations between ambient air pollutants and depression have been largely overlooked in youth. In this [...] Read more.
Rising rates of depression among youth present a growing mental health crisis. Despite growing concerns regarding the risks of air pollution exposure on youth mental and physical health, associations between ambient air pollutants and depression have been largely overlooked in youth. In this cross-sectional study, we investigated associations between ozone, particulate matter, and depressive symptoms in adolescents across 224 Colorado census tracts (average age of 14.45 years, 48.8% female, 48.9% of minority race/ethnicity). Students in participating schools reported depressive symptoms and demographic information, and school addresses were used to compute ozone and particulate matter levels per census tract. Possible confounding variables, including sociodemographic and geographic characteristics, were also addressed. Exploratory analyses examined demographic moderators of these associations. Census tracts with higher ozone concentrations had a higher percentage of adolescents experiencing depressive symptoms. Particulate matter did not emerge as a significant predictor of adolescent depressive symptoms. Secondary analyses demonstrated that associations with ozone were moderated by racial/ethnic and gender compositions of census tracts, with stronger effects in census tracts with higher percentages of individuals with marginalized racial/ethnic and gender identities. Ultimately, this project strengthens our understanding of the interplay between air pollution exposures and mental health during adolescence. Full article
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<p>Plot of standardized residuals of percentage of depressive symptoms and ozone levels per census tract, removing the effects of covariates (race, ethnicity, gender identity, age, asthma, low income, population density, elevation), and including a line of best fit.</p>
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25 pages, 1747 KiB  
Article
Life Cycle Assessment (LCA) of the Impact on the Environment of a Cosmetic Cream with Gold Nanoparticles and Hydroxylated Fullerene Ingredients
by Rebeka Rudolf, Peter Majerič, Zorka Novak Pintarič, Andrej Horvat and Damjan Krajnc
Appl. Sci. 2024, 14(24), 11625; https://doi.org/10.3390/app142411625 - 12 Dec 2024
Viewed by 400
Abstract
This review provides a comprehensive Life Cycle Assessment (LCA) of a cosmetic cream to assess the environmental impacts throughout its entire life cycle, from raw material extraction to disposal, using the methodology according to international standards. The LCA was performed using the OpenLCA [...] Read more.
This review provides a comprehensive Life Cycle Assessment (LCA) of a cosmetic cream to assess the environmental impacts throughout its entire life cycle, from raw material extraction to disposal, using the methodology according to international standards. The LCA was performed using the OpenLCA 2.0.1 software, with data from the Ecoinvent 3.8 database and relevant literature. The assessment focused on multiple impact categories, including climate change, acidification, eutrophication (freshwater, marine and terrestrial), ecotoxicity (freshwater), human toxicity (cancer and non-cancer), ionizing radiation, land use, ozone depletion, photochemical ozone formation, resource use (fossils, minerals and metals), and water use. The LCA of a cosmetic cream containing gold nanoparticles revealed significant environmental impacts across critical categories. The total climate change potential was 2596.95 kg CO2 eq., driven primarily by nanoparticle synthesis (60.7%) and electricity use (31.9%). Eutrophication of freshwater had the highest normalized result (3.000), with nanoparticle synthesis contributing heavily, indicating the need for improved wastewater treatment. The resource use (minerals and metals) scored 1.856, while the freshwater ecotoxicity reached 80,317.23 CTUe, both driven by the nanoparticle production. The human toxicity potentials were 1.39 × 10−6 CTUh (cancer) and 7.45 × 10−5 CTUh (non-cancer), linked to emissions from synthesis and energy use. The LCA of the cosmetic cream revealed several critical areas of environmental impact. The most significant impacts are associated with gold nanoparticle synthesis and electricity use. Addressing these impacts through optimized synthesis processes, improved energy efficiency, and alternative materials can enhance the product’s sustainability profile significantly. Full article
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<p>System boundaries of the cosmetic cream production life cycle.</p>
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<p>Normalized environmental impact assessment results.</p>
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<p>Most significant contributing processes to the environmental footprint of cosmetic cream.</p>
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<p>Single score results of the environmental impact assessment (values in points, Pt).</p>
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15 pages, 9277 KiB  
Article
Differential Responses of Tree Species to Elevated Ozone and Increasing Air Temperature: Implications for Foliar Functional Traits, Carbon Sequestration, and Their Relationship Under Mixed Planting
by Ruiting Wang, Sheng Xu, Qin Ping, Kexin Li, Kexin Gao and Xingyuan He
Forests 2024, 15(12), 2183; https://doi.org/10.3390/f15122183 - 12 Dec 2024
Viewed by 274
Abstract
Ozone pollution and global warming are affecting plant growth and ecosystem functions considerably. However, the information is limited on the effects of these factors on foliar traits and carbon sequestration (CS). This study evaluated the effects of elevated ozone (EO, ambient air +80 [...] Read more.
Ozone pollution and global warming are affecting plant growth and ecosystem functions considerably. However, the information is limited on the effects of these factors on foliar traits and carbon sequestration (CS). This study evaluated the effects of elevated ozone (EO, ambient air +80 ppb) and increased air temperature (IT, ambient air +2 °C) alone and the combination of these on foliar traits and CS in Quercus mongolica and Pinus tabuliformis under single (SP) and mixed planting (MP) conditions. The results showed that CS increased by 24.3% in Q. mongolica and decreased by 5.3% in P. tabuliformis under MP. EO decreased CS, while IT increased it (p < 0.05). Under MP, IT mitigated ozone’s negative impact on CS of P. tabuliformis, but exacerbated it on Q. mongolica. Structural equation modeling revealed that ozone reduced CS by reducing the photosynthesis rate (Pn) under SP and by reducing leaf length under MP in Q. mongolica. IT enhanced CS by increasing Pn, leaf thickness (LT) under SP, and LT under MP only in P. tabuliformis. Pn had the highest total effect. Overall, MP can modulate environmental stress effects on CS, but this varies by species. Future research should focus on long-term, cross-species studies to provide practical strategies for ecosystem management. Full article
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<p>Instruments in OTCs (<b>a</b>) and diagram of <span class="html-italic">Quercus mongolica</span> and <span class="html-italic">Pinus tabuliformis</span> (<b>b</b>).</p>
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<p>Carbon sequestration in <span class="html-italic">Quercus mongolica</span> and <span class="html-italic">Pinus tabuliformis</span> under single planting (SP) and mixed planting (MP) at 30 days, 60 days, and 90 days under ambient air (AA), elevated O<sub>3</sub> (EO), increasing temperature (IT), and increasing temperature and elevated O<sub>3</sub> (IT + EO). Small squares in the graphs represent mean values, and differences in lowercase letters above the boxes indicate significant differences in the amount of CS under the different treatments in the same period (<span class="html-italic">p</span> = 0.05).</p>
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<p>Differences in plant functional traits of <span class="html-italic">Quercus mongolica</span> and <span class="html-italic">Pinus tabuliformis</span> under single and mixed planting under ambient air (AA), elevated ozone (EO), increasing temperature (IT) and their combination (EO + IT). Uppercase letters indicate significant differences between treatments such as elevated ozone and increasing temperature under same planting pattern, while lowercase letters represent differences between single and mixed planting in the same tree species (<span class="html-italic">p</span> &lt; 0.05). (<b>a</b>) Photosynthesis rate, (<b>b</b>) transpiration rate, (<b>c</b>) intercellular CO<sub>2</sub> concentration, (<b>d</b>) water use efficiency, (<b>e</b>) leaf thickness, (<b>f</b>) leaf length, (<b>g</b>) specific leaf area, (<b>h</b>) specific leaf weight, (<b>i</b>) relative water content, (<b>j</b>) leaf dry matter content, (<b>k</b>) chlorophyll content.</p>
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<p>Comparing the effects of single planting and mixed planting in <span class="html-italic">Quercus mongolica</span> (<b>a</b>–<b>d</b>) and <span class="html-italic">Pinus tabuliformis</span> (<b>e</b>–<b>h</b>) functional traits on carbon sequestration under ambient air (AA), elevated ozone (EO), increasing temperature (IT) and their combination (EO + IT). Orange circles represent effect size in mixed planting, green circles effect size in single planting, and error lines 95% confidence intervals.</p>
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<p>Structural equation models explaining the direct and indirect effects of <span class="html-italic">Quercus mongolica</span> single planting (<b>a</b>) versus mixed planting (<b>b</b>) and <span class="html-italic">Pinus tabuliformis</span> single planting (<b>c</b>) versus mixed planting (<b>d</b>) with elevated O<sub>3</sub>, increasing temperature, plant functional traits on plant carbon sequestration. Red and black arrows represent positive and negative pathways, respectively (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001). The width of the arrows is proportional to the strength of the relationship, and the numbers next to the arrows are the standardized pathway coefficients, with the solid pathways being statistically significant and the dashed lines not.</p>
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<p>Total effects of elevated ozone, increasing temperature, and traits in structural equation models. (<b>a</b>) <span class="html-italic">Quercus mongolica</span> single planting, (<b>b</b>) <span class="html-italic">Quercus mongolica</span> mixed planting, (<b>c</b>) <span class="html-italic">Pinus tabuliformis</span> single planting, (<b>c</b>,<b>d</b>) <span class="html-italic">Pinus tabuliformis</span> mixed planting. Red represents a positive effect and blue represents a negative total effect.</p>
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16 pages, 2175 KiB  
Article
Antibiofilm, Anti-Inflammatory, and Regenerative Properties of a New Stable Ozone-Gel Formulation
by Carla Russo, Giuseppe Curcio, Alessandro Graziani, Antonella Mencacci and Donatella Pietrella
Pharmaceutics 2024, 16(12), 1580; https://doi.org/10.3390/pharmaceutics16121580 - 11 Dec 2024
Viewed by 451
Abstract
Background/Objectives: Chronic skin wounds are characterized by inflammation, persistent infections, and tissue necrosis. The presence of bacterial biofilms prolongs the inflammatory response and delays healing. Ozone is a potent antimicrobial molecule, and many formulations have been used in the advanced therapeutic treatment [...] Read more.
Background/Objectives: Chronic skin wounds are characterized by inflammation, persistent infections, and tissue necrosis. The presence of bacterial biofilms prolongs the inflammatory response and delays healing. Ozone is a potent antimicrobial molecule, and many formulations have been used in the advanced therapeutic treatment of chronic wounds. The aim of this work was to determine the antimicrobial, anti-inflammatory, and regenerative activity of a stable ozone-gel formulation over time. Methods: The antimicrobial property was assessed by measuring the minimal inhibitory concentration and the antibiofilm activity. The anti-inflammatory effect was evaluated by TNF-α determination, and the regenerative effect was measured by scratch assay. Results: The ozone gel demonstrated antimicrobial and antibiofilm activity in all ATCC microorganisms examined and on most clinical isolates. Higher concentrations of the ozone gel were also useful in the dispersion of preformed biofilm. The ozone gel also showed anti-inflammatory activity by reducing the production of TNF-α and regenerative activity in human fibroblasts and keratinocytes. Conclusions: Given all these antimicrobial, anti-inflammatory, and regenerative characteristics, the ozone gel could be, in this formulation, used in the treatment of wounds. The ozone-gel formulation described here retains stability for over 30 months, which facilitates its use compared to formulations that lose efficacy quickly. Full article
(This article belongs to the Special Issue Recent Advances in Biomaterials for Wound Healing)
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Graphical abstract

Graphical abstract
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<p>Cytotoxicity of ozone gel on human PBMC. Results are expressed as the percentage of live cells with respect to untreated cells, assumed to be 100. The results are expressed as mean ± standard deviation (SD) of two independent experiments conducted in triplicate. The statistical analysis was performed with a two-tailed Student’s <span class="html-italic">t</span>-test. ** <span class="html-italic">p</span> &lt; 0.01, ozone-gel-treated cells vs. untreated cells.</p>
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<p>Effect of ozone gel on TNF-α production by human PBMC. Cells were pre-stimulated with LPS and then treated with ozone gel or were co-stimulated. Data represent the mean ± SD of three independent experiments. The statistical analysis was performed with a two-tailed Student’s <span class="html-italic">t</span>-test. * <span class="html-italic">p</span> &lt; 0.05, LPS+ozone-gel-treated cells vs. LPS-treated cells.</p>
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<p>Regenerative effect of ozone gel on human dermal fibroblasts (<b>A</b>) and keratinocytes (<b>B</b>). The regenerative activity was performed by a scratch assay. The distance between the edges of the scratch was monitored under the microscope (20× magnification) for 2 or 3 days as indicated, and photos were taken. The distances were recorded, and the results are expressed as mean ± SD of the measurements by microscope (n = 6) carried out in two independent experiments.</p>
Full article ">Figure 3 Cont.
<p>Regenerative effect of ozone gel on human dermal fibroblasts (<b>A</b>) and keratinocytes (<b>B</b>). The regenerative activity was performed by a scratch assay. The distance between the edges of the scratch was monitored under the microscope (20× magnification) for 2 or 3 days as indicated, and photos were taken. The distances were recorded, and the results are expressed as mean ± SD of the measurements by microscope (n = 6) carried out in two independent experiments.</p>
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13 pages, 5244 KiB  
Article
Impact of Nitrogen Dioxide (NO2) Pollution on Asthma: The Case of Louisiana State (2005–2020)
by Keshav Bhattarai, Lok Lamsal, Madhu Gyawali, Sujan Neupane, Shiva P. Gautam, Arundhati Bakshi and John Yeager
Atmosphere 2024, 15(12), 1472; https://doi.org/10.3390/atmos15121472 - 10 Dec 2024
Viewed by 553
Abstract
This study explores the connection between tropospheric nitrogen dioxide (NO2) vertical column density levels and asthma hospitalization cases in Louisiana from 2005 to 2020. Utilizing NO2 data from NASA’s Ozone Measurement Instrument (OMI) aboard the Aura satellite, the research integrates [...] Read more.
This study explores the connection between tropospheric nitrogen dioxide (NO2) vertical column density levels and asthma hospitalization cases in Louisiana from 2005 to 2020. Utilizing NO2 data from NASA’s Ozone Measurement Instrument (OMI) aboard the Aura satellite, the research integrates these atmospheric measurements with socioeconomic data at the census tract level. This study employs a generalized linear mixed model (GLIMMIX) with a logit link and Beta distribution to analyze the relationship between seasonal NO2 levels and asthma hospitalization cases during winter, fall, spring, and summer. By analyzing OMI data, this research quantifies seasonal variations in NO2 levels and their corresponding impact on asthma hospitalizations. The findings reveal a relationship between NO2 levels and asthma hospitalizations, particularly in communities with high Black and/or low-income populations, with the strongest effects observed during winter. Specifically, the analysis shows that, for each unit increase in NO2 levels, the odds of asthma-related hospitalizations increase by approximately 26.3% (p < 0.0001), with a 95% confidence interval ranging from 23.3% to 29.5%. Assuming a causal link between NO2 and asthma, these findings suggest that reducing NO2 emissions could alleviate healthcare burdens associated with respiratory diseases such as asthma. Full article
(This article belongs to the Special Issue Remote Sensing and In Situ Measurements of Aerosols and Trace Gases)
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<p>Overview of demographic, socioeconomic, environmental, and health metrics by census tract (Louisiana; 2005–2020). (<b>a</b>) Average annual population (2005–2020). (<b>b</b>) Average annual White; and (<b>c</b>) Black population (2005–2020). (<b>d</b>) Average income (2005–2020). (<b>e</b>) Major roads, power plants, petroleum refineries, and natural gas processing plants. (<b>f</b>) Percentage of Asthma hospitalizations (average from 2005 to 2020).</p>
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<p>Seasonal distribution of tropospheric NO<sub>2</sub> columns over Louisiana, illustrating higher concentrations in urban and industrial areas, particularly during winter and fall, with spatial patterns resolved at a census tract scale in the lower row.</p>
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<p>Seasonal variation in tropospheric NO<sub>2</sub> column concentrations (10<sup>15</sup> molec cm⁻<sup>2</sup>) within and outside Louisiana’s petrochemical corridor from 2005 to 2020. The black bars depict NO<sub>2</sub> levels within the petrochemical corridor, while the dotted red line represents levels outside the corridor. The bar graphs are organized by season: Winter (December, January, February), Spring (March, April, May), Summer (June, July, August), and Fall (September, October, November), for each year within the study period. The dotted red line consistently parallels the black bars, reflecting lower NO<sub>2</sub> concentrations outside the corridor.</p>
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<p>Spatial analysis of tropospheric NO<sub>2</sub> column (10<sup>15</sup> molec cm<sup>−2</sup>) with demographic and socioeconomic characteristics (Louisiana; 2005–2020). (<b>a</b>) Level of tropospheric NO<sub>2</sub> column. (<b>b</b>) Distribution of the Black population. (<b>c</b>) Distribution of White population. (<b>d</b>) Distribution of income level. (<b>e</b>) Occurrence of asthma hospitalization cases.</p>
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21 pages, 4029 KiB  
Review
A Review of Atmospheric Deterioration and Sustainable Conservation of Calcareous Stone in Historical Buildings and Monuments
by Yu Yan and Yansong Wang
Sustainability 2024, 16(23), 10751; https://doi.org/10.3390/su162310751 - 7 Dec 2024
Viewed by 983
Abstract
Calcareous stones, such as marble and limestone, have been widely used in ancient architecture due to their durability, abundance, and ease of extraction and workability. However, their chemical nature renders them vulnerable to atmospheric pollutants. With industrialization and socio-economic growth, air pollution has [...] Read more.
Calcareous stones, such as marble and limestone, have been widely used in ancient architecture due to their durability, abundance, and ease of extraction and workability. However, their chemical nature renders them vulnerable to atmospheric pollutants. With industrialization and socio-economic growth, air pollution has severely impacted built heritage, including numerous historical buildings and monuments, particularly under changing climate and environmental conditions. Various forms of degradation, such as acid corrosion, mineral crystallization, and black crusts, are widespread and typically driven by atmospheric pollutants like sulfur dioxide (SO2), nitrogen oxides (NOX), ozone (O3), and particulates (PM), which accelerate the deterioration of stone surfaces. To develop sustainable mitigation strategies, it is essential to gain an in-depth understanding of these deterioration mechanisms and current technological advancements. This paper first reviews the influencing factors and underlying mechanisms of atmospheric deterioration of calcareous stones. Subsequently, it discusses the advantages and limitations of traditional and advanced conservation and restoration techniques at the micro-level, as well as pollution management strategies that can be adopted. Finally, the challenges of research in this field are highlighted, and directions for the sustainable conservation of calcareous stones are proposed. Full article
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<p>Examples of atmospheric deterioration of stone cultural heritage. (<b>a</b>,<b>b</b>) Black-crust-covered facade of the Wenzel Church in Naumburg. Limestone construction [<a href="#B33-sustainability-16-10751" class="html-bibr">33</a>]. (<b>c</b>,<b>d</b>) Dust and surface dissolution in the Dom of Cologne. Limestone construction [<a href="#B33-sustainability-16-10751" class="html-bibr">33</a>]. (<b>e</b>,<b>f</b>) Flaking laminar black crusts in an arch bridge pylon from rural area. Limestone construction [<a href="#B33-sustainability-16-10751" class="html-bibr">33</a>]. (<b>g</b>–<b>i</b>) Carved architectural elements and gravestones in the Monumental Cemetery in Bologna affected by sugaring and covered with black crusts. Marble construction [<a href="#B30-sustainability-16-10751" class="html-bibr">30</a>].</p>
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<p>Air pollutions associated with atmospheric deterioration of calcareous stone.</p>
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<p>The figures are derived from the acid immersion test results presented in reference [<a href="#B52-sustainability-16-10751" class="html-bibr">52</a>]. HRXCT analysis was employed to achieve high-resolution observations of microstructural changes in Savonnières limestone during early weathering stages. The Savonnières limestone samples originated from quarries in northeastern France. (<b>a</b>) 3D external visualization of samples prior to and after 1, 10, and 28 days in a mixed acid solution; (<b>b</b>) HRXCT 2D slices at about 1 mm depth, illustrating samples before, after 1 day, and after 28 days in a mixed acid solution.</p>
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<p>The figures are derived from the acid immersion test results presented in reference [<a href="#B52-sustainability-16-10751" class="html-bibr">52</a>]. HRXCT analysis was employed to achieve high-resolution observations of microstructural changes in Savonnières limestone during early weathering stages. The Savonnières limestone samples originated from quarries in northeastern France. (<b>a</b>) 3D external visualization of samples prior to and after 1, 10, and 28 days in a mixed acid solution; (<b>b</b>) HRXCT 2D slices at about 1 mm depth, illustrating samples before, after 1 day, and after 28 days in a mixed acid solution.</p>
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<p>Black crust and gypsum crystallization on limestone characterized with a polarizing optical microscope under (<b>a</b>) plane and (<b>b</b>) polarizing light. Limestone samples with black crusts were collected from the Workers’ Hospital in northwestern Madrid, Spain [<a href="#B96-sustainability-16-10751" class="html-bibr">96</a>]; (<b>c</b>) SOM image and (<b>e</b>) SEM images of the sugaring part of the naturally weathered sample collected from a gravestone in the Monumental Cemetery in Bologna, Italy [<a href="#B30-sustainability-16-10751" class="html-bibr">30</a>]; (<b>d</b>) SEM images of details of particles and gypsum crystals. Marble samples were collected from the Oceanus statue of the Fontana di Trevi (Rome) [<a href="#B32-sustainability-16-10751" class="html-bibr">32</a>].</p>
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<p>Laser cleaning marble sample used in the construction of the Soami Bagh Samadh temple, located in the outskirts of the city in DayalBagh, Agra (India) [<a href="#B40-sustainability-16-10751" class="html-bibr">40</a>]. (<b>a</b>) Photograph of a marble sculptures covered by soiling. (<b>b</b>) Femtosecond pulse laser cleaning of marble. (<b>c</b>) Magnification of the cleaned area showing undamaged minerals.</p>
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13 pages, 3521 KiB  
Article
Algae Removal and Release of Algal Organic Matter During Ozonation of Synechococcus sp.
by Yanting Zuo, Jiali Chen, Haolin Liu, Wei Liu, Shi Cheng, Huaicheng Zhang and Mingguo Peng
Water 2024, 16(23), 3522; https://doi.org/10.3390/w16233522 - 6 Dec 2024
Viewed by 540
Abstract
Pre-ozonation can enhance the removal of algae in source water during cyanobacterial blooms; however, little is known about the influence of the co-existing allochthonous natural organic matter (NOM) on algal removal and algal organic matter (AOM) behavior during ozonation. This study aims to [...] Read more.
Pre-ozonation can enhance the removal of algae in source water during cyanobacterial blooms; however, little is known about the influence of the co-existing allochthonous natural organic matter (NOM) on algal removal and algal organic matter (AOM) behavior during ozonation. This study aims to elucidate in the presence and absence of allochthonous NOM and the effects of varying ozone doses on Synechococcus sp. cell removal, membrane integrity, and dissolved organic matter (DOM) release and removal. The results indicate that ozone effectively disrupted algal cell membranes, reducing algal density; however, the presence of allochthonous NOM delayed cell rupture by competing for ozone due to aromatic humic-like substances. Pterin-like and protein-like fluorescent compounds were released upon cell disruption. Due to that, excess ozone led to the oxidation of the released pterin-like compounds, with characteristic fluorescence changes correlating to ozone dosage; these changes are potential to be used as an indicator to determine the optimized ozone dosage, avoiding more adverse release of intracellular AOM to form disinfection byproducts. Full article
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<p>Effects of ozone dosage on algal removal. Algal density: 6.5 × 10<sup>5</sup> cells/mL, SRNOM: 3 mg/L as DOC, pH: 7.2–7.4.</p>
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<p>Flow cytometry scatter plots of pure algal suspensions under various ozone dosages: (<b>a</b>) O<sub>3</sub> = 0 mg/L; (<b>b</b>) O<sub>3</sub> = 0.5 mg/L; (<b>c</b>) O<sub>3</sub> = 1.0 mg/L; (<b>d</b>) O<sub>3</sub> = 2.0 mg/L; (<b>e</b>) O<sub>3</sub> = 3.0 mg/L. Algal density: 6.5 × 10<sup>5</sup> cells/mL, pH: 7.2–7.4, SYTOX™ Green nucleic acid stain: 0.1 µmol/L.</p>
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<p>Effects of ozone dosage on DOC variations in different experimental groups. Algal density: 6.5 × 10<sup>5</sup> cells/mL, SRNOM: 3 mg/L as DOC, pH: 7.2–7.4.</p>
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<p>Effects of ozone dosage on UV<sub>254</sub> values of DOM in different experimental groups. Different lowercase letters (a, b, c, and d) above columns indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). Algal density: 6.5 × 10<sup>5</sup> cells/mL, SRNOM: 3 mg/L as DOC, pH: 7.2–7.4.</p>
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<p>Effects of ozone dosage on EEM spectra of DOM in different experimental groups. Algal density: 6.5 × 10<sup>5</sup> cells/mL, SRNOM: 3 mg/L as DOC, pH: 7.2–7.4.</p>
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<p>Specific fluorescence peak extracted from EEM spectra during ozone oxidation: (<b>a</b>) Protein-like fluorescence (Ex = 270 nm/Em = 310 nm); (<b>b</b>) Humic-like fluorescence (Ex = 320 nm/Em = 430 nm); (<b>c</b>) Humic-like fluorescence (Ex = 350 nm/Em = 450 nm). Algal density: 6.5 × 10<sup>5</sup> cells/mL, SRNOM: 3 mg/L as DOC, pH: 7.2–7.4.</p>
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<p>Mechanistic diagram of ozonation treatment of algae-laden water.</p>
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10 pages, 2360 KiB  
Communication
Assessment of Cytotoxicity and Genotoxicity of Plasma-Treated Perfluorooctanesulfonate Containing Water Using In Vitro Bioassays
by Markus Windisch, Roman Klymenko, Hannah Grießler and Clemens Kittinger
Toxics 2024, 12(12), 889; https://doi.org/10.3390/toxics12120889 - 6 Dec 2024
Viewed by 454
Abstract
The contamination of ground and surface waters with per- and polyfluoroalkyl substances (PFASs) is of major concern due to their potential adverse effects on human health. The carbon–fluorine bond makes these compounds extremely stable and hardly degradable by natural processes. Therefore, methods for [...] Read more.
The contamination of ground and surface waters with per- and polyfluoroalkyl substances (PFASs) is of major concern due to their potential adverse effects on human health. The carbon–fluorine bond makes these compounds extremely stable and hardly degradable by natural processes. Therefore, methods for PFAS removal from water are desperately needed. In this context, plasma treatment of water has been proposed as an effective method with reported removal rates exceeding 90%. However, the high reactivity of plasma discharge results in the formation of many reactive species, like radicals, ozone, or even solvated electrons, which lead to a complex reaction cascade and, consequently, to the generation of a wide variety of different chemical products. The toxicological properties of these PFAS breakdown products are largely unknown. The present study focuses on a toxicological assessment of PFAS-containing plasma-treated water samples. Aqueous solutions of long-chain perfluorooctanesulfonate (PFOS) were treated with various plasma-atmospheric regimes. Subsequently, plasma-treated water samples were subjected to in vitro bioassays. Cytotoxicity and genotoxicity were assessed with the MTS assay using human liver cells (HepG2) and the Ames MPFTM assay using Salmonella Typhimurium strains. Our results demonstrate varying cyto- and genotoxic properties of water containing PFAS breakdown products depending on the atmosphere present during plasma treatment. Based on the results of this study, the atmosphere used during plasma treatment affects the toxicological properties of the treated sample. Further studies are therefore needed to uncover the toxicological implications of the different treatment parameters, including the PFAS starting compound, the atmosphere during treatment, as well as the quantity of plasma energy applied. Full article
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<p>Hyperbolic vortex plasma reactor [<a href="#B17-toxics-12-00889" class="html-bibr">17</a>] during operation.</p>
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<p>PFOS degradation over time in hyperbolic vortex plasma reactor for three gas compositions: air, nitrogen, and argon.</p>
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<p>Degradation products of PFOS after treatment in hyperbolic vortex plasma reactor in concentrated samples for three gas compositions: air, nitrogen, and argon. Perfluorooctanoic acid (PFOA); perfluoroheptanoic acid (PFHpA); perfluorohexanoic acid (PFHxA); perfluoropentanoic acid (PFPeA); and perfluorobutanoic acid (PFBA).</p>
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<p>MTS results of PFOS-containing water after plasma treatment with different atmospheres. (<b>a</b>) Untreated PFOS control, (<b>b</b>) treatment with ambient air, (<b>c</b>) treatment with nitrogen, (<b>d</b>) treatment with argon. Error bars represent the standard deviation of three replicates.</p>
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<p>Results of the Ames MPF<sup>TM</sup> assay of PFOS-containing water after plasma treatment with different atmospheres. The red dotted line represents a 2-fold increase over baseline. A fold increase over the baseline of ≥2.0 is a positive response in the Ames MPF<sup>TM</sup> test. (<b>a</b>) Argon atmosphere; <span class="html-italic">S.</span> Typhimurium TA 98 w./w.o. S9 mix. (<b>b</b>) Argon atmosphere; <span class="html-italic">S.</span> Typhimurium TA 100 w./w.o. S9 mix. (<b>c</b>) Nitrogen atmosphere; <span class="html-italic">S.</span> Typhimurium TA 98 w./w.o. S9 mix. (<b>d</b>) Nitrogen atmosphere; <span class="html-italic">S.</span> Typhimurium TA 100 w./w.o. S9 mix. (<b>e</b>) Ambient air; <span class="html-italic">S.</span> Typhimurium TA 98 w./w.o. S9 mix. (<b>f</b>) Ambient air; <span class="html-italic">S.</span> Typhimurium TA 100 w./w.o. S9 mix. (<b>g</b>) Untreated PFOS control; <span class="html-italic">S.</span> Typhimurium TA 98 w./w.o. S9 mix. (<b>h</b>) Untreated PFOS control; <span class="html-italic">S.</span> Typhimurium TA 100 w./w.o. S9 mix. <span class="html-italic">t</span>-test: *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Results of the Ames MPF<sup>TM</sup> assay of PFOS-containing water after plasma treatment with different atmospheres. The red dotted line represents a 2-fold increase over baseline. A fold increase over the baseline of ≥2.0 is a positive response in the Ames MPF<sup>TM</sup> test. (<b>a</b>) Argon atmosphere; <span class="html-italic">S.</span> Typhimurium TA 98 w./w.o. S9 mix. (<b>b</b>) Argon atmosphere; <span class="html-italic">S.</span> Typhimurium TA 100 w./w.o. S9 mix. (<b>c</b>) Nitrogen atmosphere; <span class="html-italic">S.</span> Typhimurium TA 98 w./w.o. S9 mix. (<b>d</b>) Nitrogen atmosphere; <span class="html-italic">S.</span> Typhimurium TA 100 w./w.o. S9 mix. (<b>e</b>) Ambient air; <span class="html-italic">S.</span> Typhimurium TA 98 w./w.o. S9 mix. (<b>f</b>) Ambient air; <span class="html-italic">S.</span> Typhimurium TA 100 w./w.o. S9 mix. (<b>g</b>) Untreated PFOS control; <span class="html-italic">S.</span> Typhimurium TA 98 w./w.o. S9 mix. (<b>h</b>) Untreated PFOS control; <span class="html-italic">S.</span> Typhimurium TA 100 w./w.o. S9 mix. <span class="html-italic">t</span>-test: *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Ames MPF<sup>TM</sup> (<span class="html-italic">S.</span> Typhimurium TA 100, w.o. S9 mix) results of PFOS-containing water plasma-treated with argon atmosphere with a modified dose-range of 1 to 0.5% (<span class="html-italic">v</span>/<span class="html-italic">v</span>). The red dotted line represents 2-fold over baseline. A fold increase over baseline of ≥2.0 is a positive response in the Ames MPF<sup>TM</sup> test. <span class="html-italic">t</span>-test: * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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22 pages, 7309 KiB  
Article
Mechanism Analysis of Bubble Discharge Within Silicone Gels Under Pulsed Electric Field
by Dongxin He, Zhe Zhang, Guangzhu Wang, Keming Liu, Haochen Wang, Zhe Xu, Gilbert Teyssedre and Yuantao Zhang
Gels 2024, 10(12), 799; https://doi.org/10.3390/gels10120799 - 6 Dec 2024
Viewed by 312
Abstract
Silicone gel, used in the packaging of high-voltage, high-power semiconductor devices, generates bubbles during the packaging process, which accelerates the degradation of its insulation properties. This paper establishes a testing platform for electrical treeing in silicone gel under pulsed electric fields, investigating the [...] Read more.
Silicone gel, used in the packaging of high-voltage, high-power semiconductor devices, generates bubbles during the packaging process, which accelerates the degradation of its insulation properties. This paper establishes a testing platform for electrical treeing in silicone gel under pulsed electric fields, investigating the effect of pulse voltage amplitude on bubble development and studying the initiation and growth of electrical treeing in a silicone gel with different pulse edge times. The relationship between bubbles and electrical treeing in silicone gel materials is discussed. A two-dimensional plasma simulation model for bubble discharge in silicone gel under pulsed electric fields is developed, analyzing the internal electric field distortion caused by the response times of different ions and electrons. Additionally, the discharge current and its effects on silicone gel under pulsed electric fields are examined. By studying the influence of different pulse edge times, repetition frequencies, and temperatures on discharge current magnitude and ozone generation rates, the impact of electrical breakdown and chemical corrosion on the degradation of organic silicone gel under various operating conditions is analyzed. This study explores the macroscopic and microscopic mechanisms of dielectric performance degradation in organic silicone gel under pulsed electric fields, providing a basis for research on high-performance packaging materials and the development of high-voltage, high-power semiconductor devices. Full article
(This article belongs to the Special Issue Polymer-Based Dielectric Gels)
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<p>The variation law of bubble shape near the needle tip with the amplitude of pulse voltage.</p>
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<p>Dynamic process of electrical tree generation in silicone gel.</p>
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<p>(<b>a</b>) A schematic diagram of stress on bubbles in silicone gel; (<b>b</b>) a schematic diagram of bubble expansion inducing the internal electrical treeing process in silicone gel.</p>
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<p>The variation pattern of electrical treeing inception voltage in silicone gel with pulsed electric field edge time.</p>
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<p>Morphology of electrical tree branches under pulse electric fields with different edge times.</p>
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<p>Spatial and temporal evolution of (<b>a</b>–<b>c</b>) electron density (<b>d</b>–<b>f</b>) and positive ion density during discharge.</p>
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<p>Evolution of surface charges.</p>
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<p>Spatial and temporal evolution of electrical field intensity during discharge.</p>
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<p>(<b>a</b>) Average reaction rate of oxygen atoms and ozone molecules in air gap over 1.5 cycles; (<b>b</b>) average chemical reaction rate of ozone generation.</p>
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<p>Variation in total number of oxygen atoms and ozone molecules in air gap with time.</p>
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<p>Discharge results within half a cycle for edge times of 50 ns and 200 ns. (<b>a</b>) Discharge current; (<b>b</b>) breakdown voltage.</p>
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<p>Variation in discharge current and breakdown voltage with pulse edge time. (<b>a</b>) Discharge current; (<b>b</b>) breakdown voltage.</p>
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<p>Variation in number of ozone molecules with pulse edge time.</p>
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<p>Results within half a cycle for repetition frequencies of 5 kHz and 20 kHz. (<b>a</b>) Discharge current; (<b>b</b>) breakdown voltage.</p>
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<p>Variation in discharge current and breakdown voltage with pulse edge time. (<b>a</b>) Discharge current; (<b>b</b>) breakdown voltage.</p>
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<p>Variation in the number of ozone molecules with pulse repetition frequency.</p>
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<p>Discharge results in half a cycle for temperatures of 300 K and 450 K. (<b>a</b>) Discharge current; (<b>b</b>) breakdown voltage.</p>
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<p>Variation in discharge current and breakdown voltage with temperature. (<b>a</b>) Discharge current; (<b>b</b>) breakdown voltage.</p>
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<p>Variation in ozone molecule number with temperature.</p>
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<p>(<b>a</b>) Chemical equation for silicone hydrogenation reaction. (<b>b</b>) Silicone gel crosslinking system.</p>
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<p>Silicone gel electric tree mold.</p>
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<p>Silicone gel electrical treeing test platform under pulsed electric field.</p>
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<p>Geometry of simulation model.</p>
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15 pages, 1109 KiB  
Review
Edible Coating for Fresh-Cut Fruit and Vegetable Preservation: Biomaterials, Functional Ingredients, and Joint Non-Thermal Technology
by Mengjie Ma, Yueyue Liu, Shuaizhong Zhang and Yongkai Yuan
Foods 2024, 13(23), 3937; https://doi.org/10.3390/foods13233937 - 6 Dec 2024
Viewed by 749
Abstract
This paper reviews recent advances in fresh-cut fruit and vegetable preservation from the perspective of biomacromolecule-based edible coating. Biomaterials include proteins, polysaccharides, and their complexes. Compared to a single material, the better preservation effect was presented by complexes. The functional ingredients applied in [...] Read more.
This paper reviews recent advances in fresh-cut fruit and vegetable preservation from the perspective of biomacromolecule-based edible coating. Biomaterials include proteins, polysaccharides, and their complexes. Compared to a single material, the better preservation effect was presented by complexes. The functional ingredients applied in the edible coating are essential oils/other plant extracts, metals/metal oxides, and organic acids, the purposes of the addition of which are the improvement of antioxidant and antimicrobial activities and/or the mechanical properties of the coating. The application of edible coating with other preservation technologies is an emerging method, mainly including pulsed light, short-wave ultraviolet, modified atmosphere packaging, ozonation, and γ-irradiation. In the future, it is crucial to design coating formulations based on preservation goals and sensory characteristics. The combination of non-thermal preservation technology and edible coating needs to be strengthened in research on food preservation. The application of AI tools for edible coating-based preservation should also be focused on. In conclusion, edible coating-based preservation is promising for the development of fresh-cut fruits and vegetables. Full article
(This article belongs to the Special Issue Food Packaging: Materials, Novel Technologies, and Applications)
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<p>Statistics on edible coatings for fresh-cut fruit and vegetable preservation in Web of Science based on publication year.</p>
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<p>Schematic diagram of carboxymethyl chitosan coating infused with linalool-loaded molten globular β-Lactoglobulin nanoparticles for extended preservation of fresh-cut apples [<a href="#B41-foods-13-03937" class="html-bibr">41</a>].</p>
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<p>Illustration of the quercetin edible coating with photodynamic bacteria inactivation [<a href="#B98-foods-13-03937" class="html-bibr">98</a>].</p>
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11 pages, 5146 KiB  
Communication
Achieving Optical Ozone Sensing with Increased Response and Recovery Speed by Using Highly Dispersed CdSe/ZnS Quantum Dots in Porous Glass
by Masanori Ando, Hideya Kawasaki, Satoru Tamura and Yasushi Shigeri
Chemosensors 2024, 12(12), 254; https://doi.org/10.3390/chemosensors12120254 - 5 Dec 2024
Viewed by 669
Abstract
CdSe/ZnS quantum dots (QDs) that were highly dispersed in porous glass showed a rapid decrease in the intensity of their photoluminescence (PL) in response to ozone at concentrations of 0–200 ppm in air (at room temperature and atmospheric pressure), followed by a similarly [...] Read more.
CdSe/ZnS quantum dots (QDs) that were highly dispersed in porous glass showed a rapid decrease in the intensity of their photoluminescence (PL) in response to ozone at concentrations of 0–200 ppm in air (at room temperature and atmospheric pressure), followed by a similarly rapid recovery to full PL in air with no ozone. The response time of the PL quenching in the presence of ozone, and the recovery time to full PL in air after the ozone was removed, showed little dependence on the ozone concentration. Compared to conventional CdSe/ZnS QD films on planar glass substrates, the speed of ozone-induced decrease in the PL intensity of QDs increased, and the recovery speed of the PL intensity, once the ozone was removed from the air, was even more rapid compared to the recovery on planar glass. The 100% PL intensity recovery time in air was reduced to about 10% for CdSe/ZnS QDs that were dispersed in porous glass compared to CdSe/ZnS QD films on planar glass substrates. We hypothesize that this reflects the fact that ozone molecules that are adsorbed on the QD-layer-lined pore surfaces are quickly desorbed in ozone-free air, because the layer of CdSe/ZnS QDs is much thinner in the pores of porous glass than on a planar glass substrate. Thus, CdSe/ZnS QDs that were dispersed in porous glass showed a rapid response to ozone and a similarly rapid recovery in ozone-free air, which has not been seen in previous QD ozone gas sensors, indicating that they are promising as high-performance optical ozone sensor materials. Full article
(This article belongs to the Special Issue Functionalized Material-Based Gas Sensing)
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<p>SEM images of porous glass without CdSe/ZnS QDs at (<b>a</b>) low magnification and (<b>b</b>) high magnification.</p>
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<p>SEM images of porous glass with dispersed CdSe/ZnS QDs at (<b>a</b>) low magnification and (<b>b</b>) high magnification.</p>
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<p>Schematic diagram of porous glass with dispersed QDs showing reversible quenching of PL by ozone.</p>
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<p>(<b>a</b>) Photographs of porous glass with dispersed CdSe/ZnS QDs under room light, (<b>b</b>) porous glass with dispersed CdSe/ZnS QDs under UV irradiation at a wavelength of 365 nm, (<b>c</b>) porous glass with dispersed CdSe/ZnS QDs in an optical quartz gas cell under room light, and (<b>d</b>) porous glass with dispersed CdSe/ZnS QDs in an optical quartz gas cell under UV irradiation at a wavelength of 365 nm.</p>
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<p>PL spectra of porous glass with dispersed CdSe/ZnS QDs in (a) air, (b) air containing 0.5 ppm ozone, (c) air containing 20 ppm ozone, and (d) air containing 200 ppm ozone. Measurements were carried out at 25 °C and 1 atm.</p>
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<p>(<b>a</b>) Relative PL intensity of porous glass with dispersed CdSe/ZnS QDs in air or in air containing ozone (0.5–200 ppm) and (<b>b</b>) Stern–Volmer plot of porous glass with dispersed CdSe/ZnS QDs in air or in air containing ozone (0.5–200 ppm). Measurements were carried out at 25 °C and 1 atm.</p>
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<p>Time response of PL intensity of porous glass with dispersed CdSe/ZnS QDs when atmosphere was sequentially changed to (A) air, (B) air containing ozone (ozone concentrations: (a) 0.5 ppm, (b) 1 ppm, (c) 2 ppm, (d) 5 ppm, (e) 10 ppm, (f) 20 ppm, (g) 50 ppm, (h) 100 ppm, (i) 200 ppm). Measurements were carried out at 25 °C and 1 atm.</p>
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32 pages, 7134 KiB  
Article
Retention of Engineered Nanoparticles in Drinking Water Treatment Processes: Laboratory and Pilot-Scale Experiments
by Norbert Konradt, Laura Schneider, Stefan Bianga, Detlef Schroden, Peter Janknecht and Georg Krekel
Appl. Nano 2024, 5(4), 279-310; https://doi.org/10.3390/applnano5040018 - 5 Dec 2024
Viewed by 498
Abstract
While microparticles can be removed by a filtration step at a drinking water treatment plant (DWTP), engineered nanoparticles (ENPs), which are widely used in industry, commerce and households, pose a major problem due to their special properties, e.g., size, reactivity and polarity. In [...] Read more.
While microparticles can be removed by a filtration step at a drinking water treatment plant (DWTP), engineered nanoparticles (ENPs), which are widely used in industry, commerce and households, pose a major problem due to their special properties, e.g., size, reactivity and polarity. In addition, many ENPs exhibit toxic potential, which makes their presence in drinking water undesirable. Therefore, this study investigated the removal of ENPs in the laboratory and at a pilot-scale DWTP. Eight ENPs were synthesized and tested for stability in different types of water. Only three of them were stable in natural water: cetyltrimethylammonium bromide-coated gold (CTAB/AuNPs), polyvinylpyrrolidone-stabilized gold and silver nanoparticles (PVP/AuNPs, PVP/AgNPs). Their retention on quartz sand, silica gel and fresh anthracite was low, but CTAB/AuNPs could be retained on fresh river sand and thus should not overcome riverbank filtration, while PVP/AuNPs and PVP/AgNPs showed no retention and may be present in raw water. During ozonation, PVP/AuNPs remained stable while PVP/AgNPs were partially degraded. The advanced oxidation process (AOP) was less effective than ozone. PVP/AgNPs were almost completely retained on the pilot plant anthracite sand filter coated with manganese(IV) oxide and ferrihydrite from raw water treatment. PVP/AuNPs passed the filter with no retention. In contrast to PVP/AuNPs, PVP/AgNPs and CTAB/AuNPs were also retained on activated carbon. The integration of a flocculation step with iron(III) salts can improve ENP removal, with PVP/AuNPs requiring higher flocculant doses than PVP/AgNPs. PVP/AuNPs, in particular, are well-suited for testing the effectiveness of water treatment. Further data on the occurrence of stable ENPs in raw water and their behavior during water treatment are needed to perform a risk assessment and derive the measures. Full article
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<p>Classification of matter in water (green) and common separations methods (blue).</p>
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<p>(<b>a</b>) Trisodium citrate; (<b>b</b>) cetyltrimethylammonium bromide (CTAB); (<b>c</b>) polyvinylpyrrolidone (PVP).</p>
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<p>Schematic of the pilot plant with aeration, ozonation and anthracite sand filter with sampling points. A detailed description of the sampling points is provided in the <a href="#app1-applnano-05-00018" class="html-app">Supplementary Data, Section S4</a>.</p>
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<p>Breakthrough curve and determination of the 50% breakthrough time.</p>
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<p>UV-VIS spectra of CA/AuNPs (<b>a</b>) diluted in DI (green), DW (red) and RH (black); (<b>b</b>) CA/AuNPs dispersions diluted with DI, DW and RH (from left to right) with c(Au) = 17.9 mg L<sup>−1</sup>.</p>
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<p>UV-VIS absorption spectra of the diluted CTAB/AuNPs in DI (black), DW (red) and RH (green) with c(Au) = 10 mg L<sup>−1</sup>.</p>
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<p>UV-Vis absorption spectra of the diluted PVP/AuNPs in DI (black), DW (red) and RH (green) with c(Au) = 5.88 mg L<sup>−1</sup>.</p>
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<p>UV-Vis absorption spectra of the diluted PVP/AgNPs in DI (black), DW (red) and RH (green) with c(Ag) = 20.2 mg L<sup>−1</sup>.</p>
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<p>Adsorption isotherm data for PVP/AgNPs as Ag on sand (dots) with (<b>a</b>) Langmuir and (<b>b</b>) Freundlich regression lines.</p>
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<p>Adsorption isotherm data for PVP/AgNPs as Ag on silica gel (dots) with (<b>a</b>) Langmuir and (<b>b</b>) Freundlich regression lines.</p>
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<p>Breakthrough curves of stable ENPs in DW (flow rate 0.8 mL/min) for a 10 g quartz sand bed.</p>
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<p>Breakthrough curves of DW-stable ENPs in RH (flow rate 0.8 mL/min) for a 10 g non-treated Rhine sand bed.</p>
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<p>Breakthrough curves of stable NPs in RH (flow rate 2 mL/min) for a 0.5 g silica gel bed.</p>
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<p>Breakthrough curves of stable NPs in DW (flow rate 2.0 mL/min) for a 0.5 g activated carbon bed.</p>
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<p>Breakthrough curves of PVP-coated NPs in RH (flow rate 2 mL/min) for a fresh anthracite bed (3.15 g).</p>
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<p>Breakthrough curves of PVP-coated NPs in RH (flow rate 2 mL/min) for a used anthracite (3.40 g) from the pilot plant.</p>
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<p>Flocculation of ENPs. Error bars correspond to the relative combined uncertainty of ~7% (<a href="#app1-applnano-05-00018" class="html-app">Supplementary Data, Table S18</a>).</p>
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<p>Retention of PVP/AuNPs on a pilot scale with ozonation and anthracite sand filtration. The location of the sampling points is shown in <a href="#applnano-05-00018-f003" class="html-fig">Figure 3</a>. The data points of the same sampling points are connected to improve clarity.</p>
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<p>Retention of PVP/AgNPs at the pilot plant with ozonation and anthracite sand filtration. The data points of the same sampling points are connected to improve clarity.</p>
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15 pages, 415 KiB  
Article
The Association Between Air Pollution Exposure and White Blood Cell Counts: A Nationwide Cross-Sectional Survey in South Korea
by Jihye Lee and Hee-Young Yoon
J. Clin. Med. 2024, 13(23), 7402; https://doi.org/10.3390/jcm13237402 - 5 Dec 2024
Viewed by 347
Abstract
Background: The effect of air pollution, a major global health issue, on the immune system, particularly on white blood cell (WBC) counts, remains underexplored. Methods: This study utilized data from 54,756 participants in the Korean National Health and Nutrition Examination Survey to investigate [...] Read more.
Background: The effect of air pollution, a major global health issue, on the immune system, particularly on white blood cell (WBC) counts, remains underexplored. Methods: This study utilized data from 54,756 participants in the Korean National Health and Nutrition Examination Survey to investigate the effects of short- (day of examination and 7-day averages), mid- (30- and 90-day averages), and long-term (one-, three-, and five-year averages) air pollutant exposure on WBC counts. We assessed exposure to particulate matter (PM10, PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO). Results: Linear regression with log-transformed WBC counts, adjusted for confounders, showed that PM10 was positively associated with long-term exposure, PM2.5 was negatively associated with short- and mid-term exposures, SO2 was consistently negatively associated with short- and mid-term exposures, NO2 and CO were positive across most periods, and O3 was negatively associated with short- and mid-term exposures. Logistic regression analysis confirmed these findings, showing that short- and mid-term exposure to PM10, PM2.5, and SO2 was negatively associated with the risk of belonging to the high-WBC group, while long-term exposure to PM10, PM2.5, NO2, and CO showed positive associations with risk. Conclusions: Our findings highlight the time- and pollutant-specific associations between air pollution exposure and WBC counts, underscoring air pollution’s potential impact on systemic inflammation. Full article
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<p>Flow chart of patient enrollment.</p>
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