Environmental Science Research Articles

Optimum ultrasonication duration for effective antimicrobial activity of Ti3C2-MXene

The characteristics of two-dimensional (2D) nanomaterials have attracted remarkable attention, particularly in the fields of environmental engineering, sciences and medicine. This study was focused on Ti3C2Tx-MXene, a novel 2D nanomaterial known for its antibacterial efficacy against both Gram-negative and Gram-positive bacteria. Our investigation has represented the initial exploration of the primary antifungal capabilities of Ti3C2Tx-MXene nanosheets, with variations in lateral size induced by ultrasonication time. The Ti3C2-MXene, characterized by negative surface potential, was tested against Staphylococcus aureus, Escherichia coli, Klebsiella pneumonia, Enterobacter cloacae and fungal strains of Candida albicans. Ultrasonication was employed without the use of any chemical intercalant for delamination, separation, and exfoliation. The optimal ultrasonication duration was determined, revealing the minimum inhibitory concentrations of 8 μl/mL and 4 μl/mL against E. coli and S. aureus, respectively, as observed through the broth dilution test. The antifungal activity against Candida albicans has been assessed using the well diffusion method, revealing a substantial zone of inhibition measuring 14 mm. The demonstrated antimicrobial efficacy of ultrasonicated MXene sheets has shown a huge potential for serving as an effective anti-biofouling material.

Visual framing during crisis: a 10-year systematic review

PurposeThis paper presents a 10-year systematic review of research on the visual framing of crises to identify the priorities, theories applied and trends in the scholarship of visual framing during crises. The gaps are analyzed to provide evidence-based recommendations for advancing future research.Design/methodology/approachA total of 269 articles published in 156 peer-reviewed communication journals between January 2014 to December 2023 were reviewed. Data were analyzed using open and axial qualitative coding. A codebook was developed for the quantitative coding and data were analyzed in SPSS descriptive statistics and chi-square tests to answer the research questions.FindingsThe proportion of visual framing of crises has remained the same in the last 10 years – there is significantly more research on the visual framing of non-crises. Overall, research on the visual framing of crises is largely exploratory/descriptive and could benefit from a research agenda that is more theory driven. Additionally, there is a skewed focus for research on North America compared to other regions, and for political communication and climate compared to other themes. Environmental sciences and engineering are the most widely investigated journal fields, while disaster is the most common typology studied when looking at the visual framing of crises.Research limitations/implicationsThe systematic literature review has some limitations – most particularly that the sample was drawn from a single publisher, which may not be exhaustive enough to represent the full population of articles in the field of visual communication. However, it is a systematic review of the publications that are officially aligned with three of the major communication organizations – the International Communication Association, National Communication Association and World Communication Association. However, future research considering the inclusion of an additional publishers, like Emerald, would further enrich scholarship in visual framing during crises. Second, manual coding of the articles could present potential differences in analysis and interpretation by other researchers. Despite the limitations, the study also provides some important insights into the present and future of the visual framing of crises.Practical implicationsAddressing gaps in the internationalization of visual crisis communication would expand studies for visual framing among underrepresented communities such as populations with low reading literacy, gender minorities and displaced communities and inform visual framing strategies for government and relevant institutions as primary information disseminators during crises.Social implicationsAddressing the gaps identified in this systematic literature review on the visual framing of crises is important for extending theory in this relatively nascent field and guiding crisis visual framing strategies to mitigate uncertainty and panic, threats to stakeholder relationships, social vulnerabilities and the visual framing of stakeholder-centric crisis responses.Originality/valueBased on available literature, this is the first systematic literature review investigating the use of all types of visuals used during all crisis typologies, reflecting the ubiquity of crises and the increased focus on the use of visuals in crisis communication in the last decade.

Atomic-Scale View of Water Chemistry on Nanostructured Iron Oxide Films.

The interaction of water with solid surfaces is crucial for a wide range of disciplines, including catalysis, environmental science, corrosion, geology, and biology. In this study, we present a combined experimental and theoretical investigation that elucidates the interaction of water with a model iron oxide surface under near ambient conditions (i.e., room temperature and water vapor in the mbar range). Our findings reveal that surface hydroxylation can be controlled at the nanoscale by the local properties of the oxide film, such as local rumpling and electrostatic potential. The iron oxide surface presents alternating hydrophilic and hydrophobic domains, creating after water exposure a hexagonal pattern with a pitch of approximately 3 nm, where the highly hydroxylated regions act as nucleation centers for nanoconfined water molecule clusters.

DNA Adductomics: A Narrative Review of Its Development, Applications, and Future.

DNA adductomics is the global study of all DNA adducts and was first proposed in 2006 by the Matsuda group. Its development has been greatly credited to the advances in mass spectrometric techniques, particularly tandem and multiple-stage mass spectrometry. In fact, liquid chromatography-mass spectrometry (LC-MS)-based methods are virtually the sole technique with practicality for DNA adductomic studies to date. At present, DNA adductomics is primarily used as a tool to search for DNA adducts, known and unknown, providing evidence for exposure to exogenous genotoxins and/or for the molecular mechanisms of their genotoxicity. Some DNA adducts discovered in this way have the potential to predict cancer risks and/or to be associated with adverse health outcomes. DNA adductomics has been successfully used to identify and determine exogenous carcinogens that may contribute to the etiology of certain cancers, including bacterial genotoxins and an N-nitrosamine. Also using the DNA adductomic approach, multiple DNA adducts have been observed to show age dependence and may serve as aging biomarkers. These achievements highlight the capability and power of DNA adductomics in the studies of medicine, biological science, and environmental science. Nonetheless, DNA adductomics is still in its infancy, and great advances are expected in the future.

Plasmonic Particle Integration into Near-Infrared Photodetectors and Photoactivated Gas Sensors: Toward Sustainable Next-Generation Ubiquitous Sensing.

Current challenges in environmental science, medicine, food chemistry as well as the emerging use of artificial intelligence for solving problems in these fields require distributed, local sensing. Such ubiquitous sensing requires components with 1) high sensitivity, 2) power efficiency, 3) miniaturizability, and 4) the ability to directly interface with electronic circuitry, i.e., electronic readout of sensing signals. Over the recent years, several nanoparticle-based approaches have found their way into this field and have demonstrated high performance. However, challenges remain, such as the toxicity of many of today's narrow bandgap semiconductors for NIR detection and the high energy consumption as well as low selectivity of state-of-the-art commercialized gas sensors. With their unique light-matter interaction and ink-based fabrication schemes, plasmonic nanostructures provide potential technological solutions to these challenges, leading also to better environmental performance. In this perspective recent approaches of using plasmonic nanoparticles are discussed for the fabrication of NIR photodetectors and light-activated, energy-efficient gas sensing devices. In addition, new strategies implying computational approaches are pointed out for miniaturizable spectrometers, exploiting the wide spectral tunability of plasmonic nanocomposites, and for selective gas sensors, utilizing dynamic light activation. The benefits of colloidal approaches for device fabrication are discussed with regard to technological advantages and environmental aspects, which are barely considered so far.

A novel statistical approach to COVID-19 variability using the Weibull-Inverse Nadarajah Haghighi distribution

Researchers have devoted decades to striving to create a plethora of distinctive distributions in order to meet specific objectives. The argument is that traditional distributions have typically been found to lack fit in real-world situations, which include pharmaceutical studies, the field of engineering, hydrology, environmental science, and a number of others. The Weibull-inverse Nadarajah Haghighi (WINH) distribution is developed by combining the Weibull and inverse Nadarajah Haghighi distributions. The proposed distribution's fundamental characteristics have been established and analyzed. Several plots of the distributional properties, notably probability density function (PDF) with corresponding cumulative distribution function (CDF) are displayed. The estimation of model parameter is performed via the MLE procedure. Simulation-based research is conducted to demonstrate the performance of proposed estimator’s using some measure, like the average bias, variance, and associated mean square error (MSE). Two real datasets represent the morality due to COVID 19 in France and Canada are illustrated to see the practicality of the recommended model.

Climate change and greenhouse gas emissions from soils under the winter wheat agroecosystem in Ukraine

The issue of global climate change is one of the most important challenges for modern environmental science. In this regard, assessment of greenhouse gas emissions from soils under agroecosystems is an extremely important task. The main purpose of the study was to assess the potential emissions of greenhouse gases (CO2 and N2O) from the soils under the winter wheat agroecosystem during its spring-summer growing season under the climate change in Ukraine. A comprehensive model of greenhouse gas emissions from agroecosystem soils was used as a theoretical basis. The study considered the main agroclimatic regions of Ukraine, such as Polissia, Forest-Steppe, Northern Steppe, and Southern Steppe. The modelling was performed for average long-term conditions of 1981–2020 and under scenario conditions (using the RCP4.5 climate scenario) for the decades of 2021–2030, 2031–2040, and 2041–2050. Estimates of CO2 emissions were obtained for the agroclimatic regions of Ukraine. According to the results, the largest CO2 emissions (0.886-0.940 t C-CO2/ha) will be expected when the average productive moisture supplies in the arable soil layer for the spring-summer period of winter wheat vegetation are 20–40 mm and the air temperature is 12–15 °C. Rise in the level of moisture reserves, averaged for the period, for more than 40 mm and the air temperature of 11–12 °C is accompanied by decrease in the level of CO2 emission (0.645–0.658 t C-CO2/ha). In arid conditions, with a decrease in the period-average moisture supplies in the arable soil layer to less than 20 mm and heightened average air temperatures (14.5–15.2 °C), a decrease in CO2 emissions is expected (0.755–0.770 t C-CO2/ha). The study showed that the highest N2O emission (1.087–1.703 kg N-N2O/ha) is expected at a high level of moistening (Md being equal to 0.474–0.713 relative units and air temperature – 11.3–13.0 °C) with a high intensity of nitrification and denitrification processes. Conditions characterizing the average level of N2O emission (0.657–0.890 kg N-N2O/ha) are formed under the moistening at a level of Md equaling 0.296–0.447 relative units and air temperature of 13.4–14.7 °C. There is a slowdown in denitrification processes and an increase in the share of emissions owing to nitrification. It has been found that the lowest N2O emission (0.508–0.537 kg N–N2O/ha) is expected under conditions of severe and very severe drought (according to the Md criterion), with a heightened temperature averaged at the level of 14.5–15.2 °C during the spring-summer period of winter wheat vegetation.

High-Performance Parallel Computing for Scientific Simulations

One essential strategy for overcoming the difficulties of contemporary scientific simulations is High-Performance Parallel Computing, or HPPC. In order to handle massive information and solve complicated equations, these simulations—which mimic complex phenomena like weather patterns, fluid dynamics, and biological systems—require enormous processing resources. By dividing tasks into smaller components and processing them concurrently, HPPC enables scientists to answer issues more quickly and precisely. Research in several disciplines, including biology, environmental science, engineering, and physics, is greatly advanced by this type of computer.

6th International conference on energy, materials and environmental science: enhancing thermal properties of wood–plastic composites through incorporation of phase change materials: a short review

6th International conference on energy, materials and environmental science: enhancing thermal properties of wood–plastic composites through incorporation of phase change materials: a short review

Carbon neutralization frontier tracking

This systematic study on the international research trends in carbon neutrality underscores its critical role in combating global warming and advancing sustainable development. By leveraging the “Web of Science Core Collection” databases and employing CiteSpace software for visual analysis, we examined 2223 research papers to track the influence and trends of key countries, institutions, and authors. Our results reveal a significant increase in publication volume, indicating a robust development potential for carbon neutrality research. The study also identifies environmental science, environmental research, and energy and fuel science as central interdisciplinary hubs, highlighting the importance of cross-disciplinary collaboration. Notably, China leads in publication output but has room for improvement in citation impact, suggesting a need for enhanced research quality and international visibility. The study's findings are instrumental for guiding future research directions, policy-making, and interdisciplinary cooperation, particularly in the fields of environmental science and energy, to accelerate progress towards carbon neutrality and global climate governance.

An Opportunity for Synergizing Desalination by Membrane Distillation Assisted Reverse-Electrodialysis for Water/Energy Recovery.

Industry, agriculture, and a growing population all have a major impact on the scarcity of clean-water. Desalinating or purifying contaminated water for human use is crucial. The combination of thermal membrane systems can outperform conventional desalination with the help of synergistic management of the water-energy nexus. High energy requirement for desalination is a key challenge for desalination cost and its commercial feasibility. The solution to these problems requires the intermarriage of multidisciplinary approaches such as electrochemistry, chemical, environmental, polymer, and materials science and engineering. The most feasible method for producing high-quality freshwater with a reduced carbon footprint is demanding incorporation of industrial low-grade heat with membrane distillation (MD). More precisely, by using a reverse electrodialysis (RED) setup that is integrated with MD, salinity gradient energy (SGE) may be extracted from highly salinized MD retentate. Integrating MD-RED can significantly increase energy productivity without raising costs. This review provides a comprehensive summary of the prospects, unresolved issues, and developments in this cutting-edge field. In addition, we summarize the distinct physicochemical characteristics of the membranes employed in MD and RED, together with the approaches for integrating them to facilitate effective water recovery and energy conversion from salt gradients and freshwater.

Extracting Semantic Frames from Specialized Corpora for Lexicographic Purposes

This paper focuses on Frame-based Terminology (FBT), a theoretical framework based on cognitive premises that underpin the representation of specialized objects and events. It demonstrates that specialized semantic frames can be inferred from lexical schemas and semantic annotation. This research used corpus techniques to collect data for the representation of multilingual semantic frames. The research focuses on deforestation within the domain of Environmental Science. The methodology involves the encapsulation of corpus queries and semantic annotation to guide the creation of specialized frames associated with the deforestation event. Although the creation of frame-based terminological resources can be time-consuming, our results show that it is facilitated by the use, of e-tools that extract the arguments of specialized predicates, which are often immersed in complex syntactic constructions.

What's in the Blood? Temporalities at Play in Diet-Related Risk Management Testing Practices

In this paper, I look at two different sets of practices that are part of the risk management apparatus in place in Québec & Canada to apprehend and control risks associated with food consumption. More specifically, I contrast diabetes and chemical contaminants risk management testing practices, so as to compare how both frame and approach risks, in a context where recent research in social sciences, epigenetics and environmental sciences increasingly points to “environmental” pathways of disease causation while many chronic conditions remain highly individualized in public and health discourses. The analysis pays close attention to the different temporalities discursively created, considered, and neglected in these practices in order to understand how risk is approached and worked on. This highlights the power relations that inform how we care (or not) for (certain) bodies, inflecting in particular ways their—uneven—becomings. I argue that the Canadian biotechnological apparatus of testing practices meant to apprehend and control diet-related risks contributes to foreclosing the temporalities of health and illness considered and acted upon. As such, the apparatus contributes to (re)producing inequalities, here mostly health related ones, as well as creating differentiated biological materialities.

Supporting the evaluation of authentic assessment in environmental sciences: a case study

Supporting the evaluation of authentic assessment in environmental sciences: a case study

STEM Enrollment Decision Trees as Graduation Predictors for Community College Students Enrolled in Remedial Mathematics

Objective/Research Question: Community college graduation rates are typically quite low, and developmental mathematics enrollment and coursetaking patterns may constrain academic outcomes. To identify ways in which community college graduation rates may be improved, decision trees were utilized to examine the STEM coursetaking patterns of N = 5,065 students who matriculated in remedial mathematics. Methods: The research design was guided by Tinto’s academic and social integration framework, which provided an analytical lens for identifying how decision trees facilitate academic decision making when academic and social integration is limited. Decision trees identified course sequence rules to predict graduation, which can be used to formulate course pathways for community college advisors and their students. Results: Nine rules from the decision tree were identified, which could be used to advise community college students in coursetaking that aligns with career aspirations. The most important variable predicting graduation was completing College-Level Mathematics, which included Algebra II, Statistics, Precalculus, and survey mathematics courses. General education sciences courses such as Astronomy, Geology, Environmental Science, and Marine Biology were the most important science courses predicting graduation. Conclusions/Contributions: Results suggest the importance of College-Level Mathematics in providing the skills necessary for students to be successful in subsequent STEM coursework and persist to graduation. Designating specific academic pathways may improve social and academic integration and graduation rates, providing continuity as students work with different advisors to choose majors and plan course sequences. Transparent, accessible enrollment planning fosters programmatic consistency and student agency in selecting coursework that will maximize their success.

Perspectives on the Toxic Effects of Micro- and Nanoplastics on the Environment: A Bibliometric Analysis of the 2014 to 2023 Period.

Over the past decade, micro- and nanoplastics (MNPs) have garnered significant attention due to their frequent detection in and potential toxic effects on the environment and organisms, making them a serious threat to human health. To comprehensively understand the research on MNPs' toxicity, we employed the R language-based Bibliometrix toolkit (version 4.3.0), VOSviewer (version 1.6.11) and CiteSpace (version 6.3.R1) to perform statistical and visual analyses of 3541 articles pertaining to MNPs' toxicity between 2014 and 2023, which were retrieved from the Web of Science Core Collection (WOSCC) database. The analysis revealed that research related to MNPs' toxicity has experienced a rapid increase in recent years. China's particularly prominent influence in the field of MNPs' toxicity is evidenced by its academic exchanges and the establishment of a mature cooperation system with other countries (regions), such as the USA and Germany. Studies related to MNPs' toxicity are primarily published in leading journals, including the Science of the Total Environment, Environmental Pollution, and the Journal of Hazardous Materials. The Chinese Academy of Sciences was identified as the leading institution in terms of research on MNPs' toxicity, contributing 203 papers to the total number of studies published. Keyword co-occurrence and burst analyses indicated that the current research on MNPs' toxicity mainly focuses on the toxic effects of MNPs on aquatic organisms, the combined toxicity of MNPs and other contaminants, and the toxic effects and mechanisms of MNPs. Future research should integrate computational toxicology and toxicomics to enhance our understanding of MNPs' toxicity mechanisms and assess the potential health risks posed by atmospheric MNPs.

ANTI-CANCEROUS POTENTIAL OF POLYSACCHARIDES DERIVED FROM WHEAT CELL CULTURE

There is a global need to discover effective anti-cancerous compounds from natural sources. Cultivated wheat cells can be a valuable source of non-toxic or low toxic plant-derived polysaccharides. In this study we evaluated the antitumor ability of seven fractions of wheat cell culture polysaccharides (WCCPSs) in the HCT-116 colon cancer cell line. Almost all (6/7) fractions had an inhibitory effect on the proliferation of colon cancer cells, and two fractions (A-b and A-f) had considerable therapeutic indexes. The WCCPS fractions induced cell cycle arrest in the G1 phase and induced different rates of apoptosis (<48%). Transmission and scanning electron microscopy revealed that WCCPS fractions caused apoptotic changes in the nucleus and cytoplasm, including damage to mitochondria and external morphological signs of apoptosis. In addition, the WCCPSs induced an increase in the levels of Bax, cytochrome c, caspases 8 and 3, indicating that cell death was assessed through intrinsic and extrinsic pathways of apoptosis. Furthermore, some fractions caused a significant decrease of c-Myc, b-catenin, NFkB2 and HCAM (CD 44) levels, indicating enhanced cell differentiation. Thus, for the first time, our results provide a proof of concept of the anti-cancer capacity of WCCPS fractions in colorectal cancer. This research was supported by the FEDER Operational Program 2020/Junta de Andalucía-Consejería de Economía y Conocimiento/ Project (B-CTS-562-UGR20) and the Chair “Doctors Galera-Requena in cancer stem cell research” (CMC-CTS963); Erasmus+ Mobility Program; “Bolashak” Presidential Scholarship of the Republic of Kazakhstan for scientific work abroad; Scottish Government’s Rural and Environment Science and Analytical Services (RESAS) division.

Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithm

AbstractSoil water content (SWC) estimation is important for many areas including hydrology, agriculture, soil science, and environmental science. Ground penetrating radar (GPR) is a promising geophysical method for SWC estimation. However, at present, most of the studies are based on partial information of GPR, like travel time or amplitude information, to invert the SWC. Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. The proposed scheme includes a petrophysical relationship to link the SWC with the relative dielectric permittivity, 1D GPR forward modeling, and a GWO optimization algorithm. First, numerical modeling was carried out, and the proposed scheme was applied to both noise‐free and noisy data to verify its applicability. Then, the proposed method was applied to data collected from a field experimental site. These results, derived from both synthetic and real datasets, show that the proposed inversion scheme resulted in a good match between the observed and calculated GPR data. In the numerical modeling, it was observed that the SWC could be inverted accurately, even when noise was present in the data. These demonstrate that the GWO method can be applied for the quantitative interpretation of GPR data. The proposed scheme shows potential for SWC estimation by using GPR full waveform data.

Unveiling The Potential of Microwave Plasma Treated Char For Sustainable Automotive Shredder Residue (ASR) Management and Reduced Ecological Risk Of Cadmium

Introduction: This study explores the effectiveness of microwave plasma pyrolysis in reducing heavy metal concentrations, specifically cadmium, in automobile shredder residue (ASR). METHOD: The ASR was subjected to plasma pyrolysis at microwave power levels ranging from 800 to 1000W, resulting in a significant decrease in heavy metal concentration in the char. Utilizing the Bureau Communautaire de Référence (BCR) sequential extraction method, a standardized procedure developed by the European Commission, we assessed the chemical speciation and matrix properties of the char. The results indicated that microwave plasma treatment effectively decreased the bioavailable forms of cadmium. After 6 minutes of pyrolysis at 1000W, the exchangeable and acid-soluble fractions (F1) dropped to 10%, while the reducible fraction (F2) fell to 12%. RESULT: This treatment resulted in a substantial increase in the oxidizable (F3) and residue (F4) fractions, which reached 27% and 51%, respectively. Importantly, the potential ecological risk of cadmium decreased significantly, with the risk index (Er) dropping from 164.91 to 28.45, aligning with Taiwan's regulatory standards for non-hazardous waste.CONCLUSION: These findings suggest that microwave plasma pyrolysis is a promising and sustainable approach for the disposal of ASR, offering an environmentally friendly alternative for waste management. This study provides valuable insights for policymakers, environmental scientists, and industries seeking effective solutions for ASR treatment.

Efficient Large-scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks

Spatial processes observed in various fields, such as climate and environmental science, often occur at large-scale and demonstrate spatial nonstationarity. However, fitting a Gaussian process with a nonstationary Matérn covariance is challenging, as it requires handling the complexity and computational demands associated with modeling the varying spatial dependencies over large and heterogeneous domains. Previous studies in the literature have tackled this challenge by employing spatial partitioning techniques to estimate the parameters that vary spatially in the covariance function. The selection of partitions is an important consideration, but it is often subjective and lacks a data-driven approach. To address this issue, in this study, we utilize the power of Convolutional Neural Networks (ConvNets) to derive subregions from the nonstationary data by employing a selection mechanism to identify subregions that exhibit similar behavior to stationary fields. We rely on the ExaGeoStat software for large-scale geospatial modeling to implement the nonstationary Matérn covariance for large-scale exact computation of nonstationary Gaussian likelihood. We also assess the performance of the proposed method with synthetic and real datasets at large-scale. The results revealed enhanced accuracy in parameter estimations when relying on ConvNet-based partition compared to traditional user-defined approaches.