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Abstract\nNOVELTY STATEMENTUrbanization and industrialization are exponentially deteriorating air quality, ecosystems, and human health. Phytoremediation is cost cost-effective, sustainable, and nature-based solution against air pollution. This study is designed to evaluate four species, Chlorophytum comosum, Rhapis excelsa, Spathiphyllum wallisii, and Ficus benjamina for their phytoremediation potential. The experimental setup consisted of a sealed chamber to place potted plants and equipment, it was also connected to the vehicular exhaust pipe. The Air Pollution Tolerance Index was highest for F. benjamina (12.19) and lowest for Rhapis excels (8.58). C. comosum has the highest VOC removal efficiency (90%, 0.172 ppm h−1). NOx remediation was highest by F. benjamina with 0.057 ppm h−1 (77%) removal efficiency. SOx and CO were remediated more efficiently by C. comosum, as 89%, (0.18 ppm h−1) and 80% (0.23 ppm h−1), respectively. R. excelsa reduced a higher concentration of NH3 (77%, 0.06 ppm h−1) compared to other species. R. excelsa and S. wallisii may serve as bio-indicator species. These findings provide a sustainable, natural, economical, and eco-friendly way to mitigate air pollution. F. benjamina and C. comosum are suitable species for urban landscapes, green spaces, urban plantations, and green walls to curb air pollutants due to traffic and industries.Based on the air pollution tolerance index, this study concludes that Rhapis excels (APTI = 8.58) can be used as a bio-indicator species for pollution monitoring and evaluation. Whereas, Ficus benjamina (APTI = 12.2) and Chlorophytum comosum (APTI = 10.3) are the best options for urban landscapes, green belts, or green walls for air pollution combat and mitigation. [ABSTRACT FROM AUTHOR]

The widespread use of herbicides like dinitro-o-cresol (DNOC) and veterinary drugs such as furaltadone (FLT) has surged to meet agricultural and animal husbandry demands, raising significant health and environmental concerns due to their extensive use and unregulated disposal. To address this issue, herein, we developed an imidazole-functionalized metal–organic framework (MOF)-based fluorometric dual sensor for rapid and selective detection of these analytes in aqueous medium. The present MOF-based probe demonstrated 82% fluorescence quenching upon DNOC introduction, whereas 89% quenching occurred in the presence of FLT. The probe exhibited notably high sensitivity, with the lowest ever reported limit of detection (LOD) of 0.5 nM for DNOC and 1.1 nM for FLT. The highest reported Stern–Volmer quenching constant (KSV) value of 5 × 107 M−1 and 2 × 107 M−1 for DNOC and FLT, respectively, further indicates the extraordinary sensitivity of the sensor towards these targeted analytes. The MOF showed a rapid response time of 5 s for both DNOC and FLT. The sensor also demonstrated outstanding selectivity even in the presence of interfering substances, proving effective in various complex environments such as serum, urine, wastewater, and different pH media. We thoroughly investigated the sensor's working mechanisms using different advanced analytical techniques to understand its high selectivity towards the targeted analytes. These findings underscore the sensor's practical and potential real-world applications, offering a valuable tool for environmental pollution monitoring and public health protection. [ABSTRACT FROM AUTHOR]

Environmental pollution and human health are inextricably linked. As the number of environmental pollutants increases, it is increasingly important to develop unique, effective, and intelligent analytical devices to monitor them. Biosensors are devices that capture biological signals and convert them into audible electrical impulses. To detect and observe specific biological analytes, such as the interaction between antibodies and antigens, biological entities such as DNA, RNA, and proteins/enzymes must be integrated with electrochemical transducers. Variety of biosensors has lately gained prominence and is being employed as in situ, real-time, and cost-effective analytical devices for healthy environments. Continuous environmental monitoring necessitates the use of biosensing technologies that are portable, inexpensive, quick, and adaptive. Each sensor, on the other hand, stands apart in terms of selectivity, technique, sensitivity, detection restrictions, sensitizing materials, and speed. Each sensitive element has a distinct selectivity and detection limit based on its sensitivity. This review focuses on the distinguishing characteristics, efficient design, and effectiveness of several types of biosensors, with an emphasis on the detection of environmental contaminants. Accurate devices will also aid in the continuing, parallel investigation of the causes and discharge of environmental toxins from diverse industrial sectors. Furthermore, real-time monitoring has the added benefit of allowing on-site analysis of pollutant components before to discharge into the environment, which can assist reduce the waste of a variety of harsh chemicals and reagents. The goal of this review is to provide an overview of the most recent developments in the field of using biosensors to identify environmental pollutants. Biosensors based on enzymes, entire cells, antibodies, aptamers, DNA, and biomimetic sensors are described. We list their useful qualities as well as their relevance to the detection of various contaminants. Designing biosensors makes use of a number of detection principles, including amperometry, conductometry, luminescence, etc. They differ in terms of design, profitability, sensitivity, and quickness. Further research is necessary to create a powerful biosensor that can identify environmental contaminants in a multifaceted medium, with no prior time-consuming pretreatment or tedious preparation protocols. [ABSTRACT FROM AUTHOR]

To solve the difficult problems of tailings dam instability and environmental pollution, multisource information perception, prediction and early warning technology for tailings dams are investigated. Taking a tailings pond in China as an example, a three-dimensional visualization intelligent management platform based on the spatiotemporal fusion of multisource big data is established to realize intelligent real-time monitoring, prediction and early warning of tailings dams. A monitoring system for air-space-ground integration was developed via high-resolution optical image recording, unmanned aerial vehicles (UAVs), radar, video surveillance and displacement sensors. This approach can realize pollution monitoring and efficient identification of high-risk areas. In addition, a machine learning algorithm is used to mine spatiotemporal data in detail. The Alibaba cloud platform was adopted to develop a data integration framework. Multisensor spatiotemporal data from tailings dams and multisource monitoring data from the environment were integrated. The integrated management of tailings dam environmental monitoring, pollution and stability assessment is realized. A stability prediction model for tailings dams based on multisource data is proposed. The temporal and spatial information of various forms of data is analysed from multiple levels and perspectives. Rapid prediction of the disaster situation and stability of tailings ponds is realized. Moreover, a tailings pollution assessment model based on a neural network is integrated with multisource information to establish a multifactor environmental pollution neural network assessment model and a multilevel warning platform. This work can provide technical support for intelligent monitoring and early warning systems for tailings ponds. [ABSTRACT FROM AUTHOR]

Global concern about microplastic (MP) and nanoplastic (NP) particles is continuously rising with their proliferation worldwide. Effective identification methods for MP and NP pollution monitoring are highly needed, but due to different requirements and technical challenges, much of the work is still in progress. Herein, the advanced optical imaging systems that are successfully applied or have the potential for MP identification are focused on. Compared with chemical and thermal analyses, optical methods have the unique advantages of being nondestructive and noncontact and allow fast detection without complex sample preprocessing. Furthermore, they are capable of revealing the morphology, anisotropy, and material characteristics of MP for their quick and robust detection. This review aims to present a comprehensive discussion of the relevant optical imaging systems, emphasizing their operating principles, strengths, and drawbacks. Multiple comparisons and analyses among these technologies are conducted in order to provide practical guidelines for researchers. In addition, the combination of optical and other alternative technologies is described and the representative portable MP detection devices are highlighted. Together, they shed light on the prospects for long‐term MP pollution monitoring and environmental protection. [ABSTRACT FROM AUTHOR]

As plastic pollution exists in aquatic ecosystems globally, monitoring its abundance and distribution has become crucial for understanding transport pathways, sources, sinks, and impacts. Riverbanks are accumulation zones for plastic, but the selection of monitoring methods is constrained by research goals, available resources, and site-specific conditions. This diversity in approaches has led to disparate datasets, highlighting the need for standardized monitoring protocols. Here, we study the spatial distribution of plastic at the riverbank scale, quantify the uncertainty of existing riverbank methods, and provide recommendations for improved monitoring based on the balance between uncertainty loss and increase in effort. We measured riverbank plastic abundance at eight Dutch riverbanks, categorizing the items using 108 item categories (River-OSPAR). For every riverbank, an area of 100 by 25 meters was subdivided into five-by-five-meter squares, resulting in 100 individual monitored sub-areas. We found riverbank plastic exhibited high spatial variability, with deposition patterns ranging from parallel to the waterline to clustered, random, or uniform (Moran's I between -0.050 and 0.301). Individual measurements from diverse sampling protocols are 5-49 times less accurate than estimates derived from extensive sampling, highlighting the diminishing impact of specific methods with increased data collection. Lastly, our findings suggest that increasing the sampling area quickly reaches diminishing returns in terms of accuracy. Reducing the sampled area by 80% only increases the uncertainty in estimating the true plastic density by 20%. While standardized protocols are essential for data comparability, a rigid, uniform sampling approach may be less efficient and resource-intensive than a flexible (step-wise) strategy that adapts to local conditions. By demonstrating that extensive sampling can mitigate the differences between unique sampling protocols, this study promotes a shift towards flexible and efficient riverbank plastic monitoring, ultimately accelerating global efforts to combat plastic pollution. [ABSTRACT FROM AUTHOR]

Simple Summary: Recent awareness highlights the significant impact of contaminants on the Mediterranean marine ecosystem and fishery resources. Monitoring these pollutants is crucial due to their accumulation in marine organisms and the health risks they pose through consumption. This study examines the levels of total mercury and PAHs in the muscle tissue of European hake from an important fishing ground in the Adriatic Sea. Seasonal and gender patterns as well as correlations with somatic indexes were explored to provide cost-effective bioindicators for pollution monitoring and mitigation. This research investigates the dynamics of contaminant exposure in European hake (Merluccius merluccius, L. 1758) from the Adriatic Sea (Central Mediterranean Sea) by examining the levels of total mercury (THg) and polycyclic aromatic hydrocarbons (PAHs) in the muscle fish tissues. The study explores the correlations between these pollutants and somatic indexes to identify the early warning signals of pollution and ecological effects. The levels of pollutants are influenced by season and sex. Lipids appear to have a minimal effect on the PAH levels, whereas they exhibit a positive correlation with mercury levels in the muscle. No significant relationships between the pollutants and condition indexes were observed, except for a positive correlation between THg and the gonadosomatic index, indicating a potential impact on the reproductive health of fish. In contrast, PAHs showed no meaningful correlation with condition indexes. Differences in contaminant accumulations and lipid levels between sexes reflect variations in metabolic activity, reproductive costs, and adaptive strategies to seasonal changes and energy demands. This study highlights the importance of long-term monitoring to improve pollution management, environmental conservation, and the protection of marine organisms' health. [ABSTRACT FROM AUTHOR]

Selecting representative groundwater monitoring wells in polluted areas is crucial to comprehensively assess groundwater pollution, thereby ensuring effective groundwater remediation. However, numerous factors can affect the effectiveness of groundwater monitoring well network optimizations. A local sensitivity analysis method was used in this study to analyze the hydrogeological parameters of a simulation groundwater solute transport model. The results showed a strong effect of longitudinal dispersion and transverse dispersion on the output results of the simulation model, and a good fit between the backpropagation neural network (BPNN)-based alternative model's results and those obtained using the solute transport simulation model, accurately reflecting the input and output relationship of the simulation model. The optimized groundwater monitoring layout scheme consisted of four groundwater monitoring wells, namely no. 7, no. 16, no. 23, and no. 24. These wells resulted in a groundwater fluoride pollution rate of 98.44%, which was substantially higher than that obtained using the random layout scheme. In addition, statistical analysis of the fluoride groundwater pollution results obtained using the Monte Carlo random simulation highlighted continuous and high groundwater fluoride levels in the second and third pollution sources and their downstream groundwater. Therefore, more attention should be devoted to these sources to ensure the effective remediation of groundwater pollution in the study area. [ABSTRACT FROM AUTHOR]

Traditional approaches for monitoring aquatic pollution primarily rely on chemical analysis and the detection of pollutants in the aqueous environments. However, these methods lack realism and mechanistic insight and, thus, are increasingly supported by effect‐based methods, which offer sensitive endpoints. In this context, daphnids, a freshwater species used extensively in molecular ecotoxicology, offer fast and noninvasive approaches to assess the impact of pollutants. Among the phenotypic endpoints used, feeding rate is a highly sensitive approach because it provides evidence of physiological alterations even in sublethal concentrations. However, there has been no standardized method for measuring feeding rate in daphnids, and several approaches follow different protocols. There is a diversity among tests employing large volumes, extensive incubation times, and high animal densities, which in turn utilize measurements of algae via fluorescence, radiolabeling, or counting ingested cells. These tests are challenging and laborious and sometimes require cumbersome instrumentation. In the present study, we optimized the conditions of a miniaturized fast, sensitive, and high‐throughput assay to assess the feeding rate based on the ingestion of fluorescent microparticles. The protocol was optimized in neonates in relation to the concentration of microplastic and the number of animals to increase reproducibility. Daphnids, following exposures to nonlethal concentrations, were incubated with microplastics; and, as filter feeders, they ingest microparticles. The new approach revealed differences in the physiology of daphnids in concentrations below the toxicity limits for a range of pollutants of different modes of action, thus proving feeding to be a more sensitive and noninvasive endpoint in pollution assessment. Environ Toxicol Chem 2024;43:2211–2221. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

Skin exposome encapsulates all internal and environmental exposures that affect skin health. Of these, photo-pollution refers to the combined effect on human skin of the simultaneous exposure to solar radiation (especially UV) and air pollution. Providing personalised photo-pollution exposure warnings and dose monitoring to an individual through a smartphone app could help in reducing skin ageing and degradation as well as in managing skin conditions (for example Atopic Dermatitis). However, accurate monitoring is challenging without a potentially expensive or cumbersome sensor device. In this work we present an innovative satellite-based air pollutant monitoring software service, ExpoPol, developed by siHealth Ltd. ExpoPol synthesises several inputs including live satellite imagery in real-time into an artificial intelligence (AI) model to provide assessment of the exposure of a smartphone user to relevant air pollutants, such as nitrogen oxides (NOx), poly-aromatic hydrocarbons (PAH) and ozone (O3). When combined with siHealth's patented technology HappySun® for solar radiation monitoring, ExpoPol can effectively provide a sensor-less personal skin photo-pollution dosimetry. By downscaling satellite data using local geographic data, ExpoPol is capable of monitoring pollutants with street-level resolution and global coverage in near real-time. We evaluate the accuracy of ExpoPol against ground-station monitoring data for three pollutants across three continental regions (Europe, Asia, North America) and find R2 values of 0.62, 0.65, 0.74 for PM10, PM2.5, NO2 respectively. ExpoPol is shown to be significantly more accurate than a state-of-the-art global atmospheric forecasting system (CAMS) over the same ground-station dataset and provide data on much finer spatial resolutions. The presented system can support the real-time automatic assessment of the user's skin exposome, anywhere and anytime. This paves the way for the development of mobile applications empowering users and clinicians to make informed decisions about skin health, or assisting dermocosmetic manufacturers in the creation of personalised products for personal care (e.g., skin ageing prevention or hair care). [ABSTRACT FROM AUTHOR]

One of the most hazardous pollutants of natural water resources is lead -Pb (II)- which poses a significant threat to human health and environmental safety. The accumulation of this heavy metal in an organism affects a number of systems and is particularly dangerous for children. At low levels of intake over short periods, it induces diarrhea, abdominal pain, and renal damage, with the potential for fatal outcomes in extreme cases. The principal sources of lead pollution are industries, coal-fired power plants and motor vehicles. In response to the critical demand for effective lead detection, researchers have developed advanced Micro-Electromechanical Systems (MEMS) piezoresistive cantilever sensors that make use of the chelating properties of Ethylenediaminetetraacetic Acid (EDTA) and the superior electrical properties of reduced Graphene Oxide (rGO). It has been proven that this composite can be effectively immobilized on a MEMS cantilever surface, enabling the selective removal of Pb (II) ions from wastewater. This adsorption process exerts stress on the surface of the cantilever, resulting in variations in resistance that can subsequently be measured. A sensitive and selective MEMS piezoresistive cantilever sensor for Pb (II) has been developed, offering significant potential as a lead monitoring tool in water samples. The sensor demonstrated high sensitivity and selectivity, with a detection limit of 1 ppb and a linear response range of 10-100 ppb. This novel approach has the potential to significantly enhance pollution monitoring and provide substantial benefits for public health by enabling real-time, on-site mapping of lead contamination across aqueous environments. This technological advancement in the environmental surveillance domain offers a new perspective on the safety of water and the reduction of potential health hazards associated with lead consumption. [ABSTRACT FROM AUTHOR]

Microparticles of anthropogenic origin, such as microplastics and microfibers, are pervasive pollutants in the marine environment of the world. These microparticles pollute water and can be ingested by biota; however, while microplastics are often monitored, very few studies focus on microfibers. Coastal areas, such as beaches, are more vulnerable to pollution due to their location between terrestrial and marine environments and their recreational and touristic functions. In this study, microparticle occurrence frequency was investigated along the Calabria coast, Italy, in one touristic beach in comparison with an unpopular one. High amounts of microparticles of anthropogenic origin were found in all sediment samples, despite the evident different tourist exploitation of the two examined beaches. Sediments of the most touristic beach had values between 729.5 ± 212.3 and 1327 ± 125.8 items/kg, instead, the less popular beach between 606.3 ± 102.8 and 1116.5 ± 226.9 items/kg (average and st. dev). Microparticle abundance varied before and after the touristic summer season, increasing in the most popular beach and decreasing in the unpopular one. Differences in microparticle abundance between foreshore and backshore were present too; however, statistical analyses did not show evident relations between microparticle abundance and the distance from the see. Grain size influenced the abundance of microparticles in sediments. Our results improve knowledge on microparticle pollution in marine environments, highlighting information about micropollution in coastal areas. Future studies are needed to understand better microparticle dynamics and ecological impacts in marine and terrestrial systems, implementing new strategies to monitor pollution state, enhancing the natural intermediate environments, and providing useful and sustainable measure of conservation. [ABSTRACT FROM AUTHOR]

In the Trans-Baikal Territory, mining enterprises significantly pollute the environment with chemical elements. In these conditions, monitoring the state of the environment, including with the help of indicator plants, is of great importance. Among the woody plants, Gmelin larch (Larix gmelinii (Rupr.) Kuzen.) and silver birch (Betula pendula Roth.) are the most common in the region. Using the example of the Bystrinskoe Cu–Au–Fe skarnporphyry deposit, the concentrarion of 46 chemical elements in the needles of Gmelin larch and the leaves of silver birch, as well as the content of these elements in the soil, has been studied. The aim of the study is to identify plant species differences in the accumulation of elements and the prospect for using plants as indicators of environmental pollution. Scientific work has been carried out on 11 sample plots in natural plant communities near the enterprise’s facilities in August 2022. Soil and plant samples have been collected at the same time, at the same sites. The chemical analysis of the samples has been carried out using the “Methodology for measuring the metal content in solid objects by inductively coupled spectrometry” (FER 16.1:2.3:3.11–98). Differences in the concentration of elements in plants in relation to the clarke of terrestrial plants have been established. A statictically significant higher concentration of K, Ca, P, Mg, Fe, Ba, Zn, Na, Rb, Ni, Co, Ga, Sn, Y, Zr, Cd and Nb has been found in birch leaves compared to larch needles, and, conversely, a higher concentration of Sc, W and Hg – in larch needles than in birch leaves. Significant differences between plants have been established in the biological absorption coefficient of Se, P, Sn, Ca, Mn, Sr, Cd, Mg, K, W, Ni, Zn, Sc, Rb, Na and Nb. Knowledge about the peculiarities of accumulation of chemical elements in plant organs can be used for biomonitoring environmental pollution and, possibly, for phytoremediation of contaminated soils.

Strategies of outside air reduction, fan speed adjustments, and temporary system shutdowns can be effective ways to maintain or improve the preservation quality of a collection environment while reducing the financial burden and carbon footprint of a collecting institution. However, current criteria guiding safe implementation of energy-saving strategies focus on temperature and RH alone, which ignores risks posed by pollutants. This research aims to address this by monitoring indoor and outdoor-generated pollutants at four collecting institutions before and during implementing energy-saving strategies. Alongside temperature and RH loggers, continuous pollution monitors were located within the mechanical system and collection spaces. Additionally, energy monitors were installed on the mechanical systems serving the collection spaces to quantify the energy consumption prior to and during operation modifications. Initial results indicate pollutant levels remain stable during the test periods, and did not exceed baseline concentrations. In this paper, the lessons learned from this field research are addressed and practical implications for optimizing sustainable environmental controls are given. [ABSTRACT FROM AUTHOR]

The accuracy of pollution source identification significantly depends on the amount of effective information derived from monitoring data. Currently, most of the comprehensive studies on groundwater contamination source identification and optimal design of monitoring solutions are based on hypothetical cases, whereas relevant studies on actual cases only consider one characteristic of the pollution source (either locations or fluxes). An optimal monitoring network (OMN)-based pollution source characterisation framework that takes source locations and source fluxes into account is presented to enhance the accuracy of pollution source identification. The genetic algorithm (GA) and particle swarm optimization (PSO) were used to solve the optimization model of pollution source characteristics identification. The framework is applied to a landfill for waste located in Baicheng City, China. The results showed that the identification results based on OMN has a smaller mean relative error and higher accuracy, compared with those based on random monitoring network (RMN). This study shows that OMNs can provide more effective information for pollution source identification and effectively enhance the accuracy of the groundwater sources characteristics identification. [ABSTRACT FROM AUTHOR]

The green place-based policy is crucial for balancing economic competitiveness and environmental protection. However, there is scarce literature examining its impact on environmental pollution and the underlying mechanisms at the micro level. This paper treats China's National Demonstration Eco-Industrial Parks (EIP) as a quasi-natural experiment and systematically evaluates its effect on pollution using a difference-in-differences (DID) approach. With data from Chinese industrial firms and counties, this research reveals that the EIP leads to a significant reduction of 54.36% in firms' sulfur dioxide (SO 2) emissions. Moreover, increasing R&D investment, reducing SO 2 emission intensity, implementing production process pollution control, and dynamic adjustments of firm entry and exit are significant influencing mechanisms. Heterogeneity tests indicate a stronger SO 2 reduction effect of the EIP program on firms in eastern regions, capital-intensive industries, and non-state-owned enterprises. This study suggests that the Chinese government should support the establishment of EIP, conduct a coordinate system, strategically plan the industrial chain, establish a pollution monitoring and early warning system, enhance information disclosure, and give greater emphasis to the construction of EIPs in central and western China. [ABSTRACT FROM AUTHOR]

Introduction: Transboundary pollution is a major global challenge and monitoring beach litter along international borders can reveal some of the pathways by which litter enters water bodies, and hence advance the implementation of measures to prevent pollution emissions into international waters. Methods: In this paper, participatory mapping was used to detect beach litter in Imperial Beach, California, along the U.S.-Mexico international border. This study implemented a 3-step protocol including an introductory awareness workshop, a macro-debris survey to categorize and remove beach litter, and a qualitative assessment of pollution drivers. Results: Results show that plastic litter is the most dominant across all transects (304 debris, 52.6% of all litter observations), with an average density of 76 pieces/transect, with plastic being the most common material. Participants identified some of the major causes of pollution with paucity of waste management facilities, tourism activities near/on the beach, and inflow of pollution across the border. Discussion: The paper highlights the role of citizen science in monitoring pollution along large and border regions. Implications of this study include methodological and practical contributions to the study of marine pollution to supplement the current paucity of information on pollution movement and distribution. [ABSTRACT FROM AUTHOR]

Blockchain has emerged as a solution for ensuring accurate and truthful environmental variable monitoring needed for the management of pollutants and natural resources. The immutability property of blockchain helps protect the measured data on pollution and natural resources to enable truthful reporting and effective management and control of polluting agents. However, specifics on what to measure, how to use blockchain, and highlighting which blockchain frameworks have been adopted need to be explored to fill the research gaps. Therefore, we review existing works on the use of blockchain for monitoring and managing environmental variables in this paper. Specifically, we examine existing blockchain applications on greenhouse gas emissions, solid and plastic waste, food waste, food security, water usage, and the circular economy and identify what motivates the adoption of blockchain, features sought, used blockchain frameworks and consensus algorithms, and the adopted supporting technologies to complement data sensing and reporting. We conclude the review by identifying practical works that provide implementation details for rapid adoption and remaining challenges that merit future research. [ABSTRACT FROM AUTHOR]

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Plastic pollution, particularly in oceans, is a growing environmental threat. Monitoring this pollution is challenging due to the shortage of data and tools. Remote sensing offers a promising solution by using various types of satellite and aerial images to detect and track plastic waste movement. Purpose. The study aims to establish a plastic waste map using remote sensing technology, focusing on the case study of the coastal area of Thanh Hoa province, Vietnam. Methodology. The study involves several steps, including the collection of plastic waste data (samples in the case study and indices from remote sensing images) as well as topographic and base map collection, statistics of plastic samples, grid design, calculation, interpolation, accuracy assessment, and mapping. Field surveys involved taking pictures of plastic debris along designated routes and a grid system was used to classify and calculate waste samples. Satellite images, especially Sentinel-2 MSI optical satellite imagery, are utilized to identify water areas of high plastic concentration. Findings. A map of plastic wastes in coastal areas of Thanh Hoa was created, with indices like NDWI (Normalized Difference Water Index) and FDI (Floating Debris Index) helping identify potential plastic waste signals. The resulting map reveals high concentrations of plastic waste in sea areas near the major river mouths of the Ma River basin and tourist areas, which aligns with areas of high human activity. Originality. This is the first study of plastic waste in the coastal area using remote sensing data in Thanh Hoa province, Vietnam. Practical value. This study can contribute to the effective management of marine plastic waste in Thanh Hoa while opening up opportunities for applying the method to create marine plastic waste maps throughout Vietnam and foster long-term monitoring and management. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of NO2 emissions in Mashhad City utilizing statistical evaluations and the Cisco Network Model. The present study begins by evaluating NO2 emissions through statistical analysis, followed by the application of histograms and radar statistical appraisals. Subsequently, a model execution logic is developed using the Cisco Network Model to further understand the distribution and sources of NO2 emissions in the city. Additionally, the research incorporates managerial insights by employing Petri Net modeling, which enables a deeper understanding of the dynamic interactions within the air quality management system. This approach aids in identifying critical control points and optimizing response strategies, thus enhancing the overall effectiveness of urban air pollution mitigation efforts. The findings of this study provide valuable insights into the levels of NO2 pollution in Mashhad City and offer a structured approach to modeling NO2 emissions for effective air quality management strategies which can be extended to the other megacities as well. [ABSTRACT FROM AUTHOR]

In environmental studies, rhodamine dyes are commonly used to trace water movements and pollutant dispersion. Remote sensing techniques offer a promising approach to detecting rhodamine and estimating its concentration, enhancing our understanding of water dynamics. However, research is needed to address more complex environments, particularly optically shallow waters, where bottom reflectance can significantly influence the spectral response of the rhodamine. Therefore, this study proposes a novel approach: transferring pre-trained classifiers to develop a generalizable method across different environmental conditions without the need for in situ calibration. Various samples incorporating distilled and seawater on light and dark backgrounds were analyzed. Spectral analysis identified critical detection regions (400–500 nm and 550–650 nm) for estimating rhodamine concentration. Significant spectral variations were observed between light and dark backgrounds, highlighting the necessity for precise background characterization in shallow waters. Enhanced by the Sequential Feature Selector, classification models achieved robust accuracy (>90%) in distinguishing rhodamine concentrations, particularly effective under controlled laboratory conditions. While band transfer was successful (>80%), the transfer of pre-trained models posed a challenge. Strategies such as combining diverse sample sets and applying the first derivative prevent overfitting and improved model generalizability, surpassing 85% accuracy across three of the four scenarios. Therefore, the methodology provides us with a generalizable classifier that can be used across various scenarios without requiring recalibration. Future research aims to expand dataset variability and enhance model applicability across diverse environmental conditions, thereby advancing remote sensing capabilities in water dynamics, environmental monitoring and pollution control. [ABSTRACT FROM AUTHOR]

Microplastics (MPs), typically defined as plastic fragments smaller than 5 mm, are pervasive in terrestrial and marine ecosystems. There is a need for rapid, portable, low-cost detection systems to assess health and environmental risks. Fluorescent tagging with Nile Red (NR) has emerged as a popular detection method, but variations in fluorescent emissions based on NR solvent, plastic polymer, excitation wavelength, and additives complicate standardization. In this study, seven plastic samples stained with acetone-based NR were analyzed using a fluorescent spectrometer to identify optimal emission peaks across UV-Vis excitation wavelengths. These findings aid in selecting appropriate excitation wavelengths and optical filters for future detection systems. Additionally, a straightforward polymer identification scheme was validated against field-collected plastic samples, whose material composition was confirmed via Fourier Transform Infrared Spectroscopy. This work contributes towards developing accessible microplastic detection technologies by characterizing the fluorescent properties of NR-stained plastics and enhancing the capability for effective environmental monitoring. Future research will expand the dataset to include diverse plastics with varying additives and weathering, and incorporate computer-vision tools for automated data processing and polymer identification. [ABSTRACT FROM AUTHOR]

Coral reef ecosystems host diversified and highly productive communities, but corals are degrading in many places worldwide. Picking suitable locations to maximize coral conservation and restoration efforts is critical. From a mass balance point of view, the supply of new nutrients is crucial to support a productive and reef-building coral ecosystem. Quantifying and qualifying available nutrients provide information to set region-specific thresholds for anthropogenic pollution monitoring and to generate research hypotheses. Here, we report the inorganic and organic nutrient levels from twenty-three sampling sites in coral reefs and coastal waters covering regions from high to low coral coverage, including two remote islands, Dongsha Atoll and Taiping Island, in the South China Sea. Some of the surveyed reefs received external inorganic nutrient supply via upwelling or submarine groundwater discharge (SGD), suggesting sites potential for new production (i.e., reef-building). Production or removal of organic matter at various sites is evidenced by their elevated or depleted organic carbon and nitrogen concentrations, respectively. The degree of impact by the upwelling and SGD on various inorganic and organic nutrient distribution varies. Among all sites, organic nitrogen accounts for most of the total nitrogen and is potentially a significant nitrogen source for the environment. The highly correlated total organic nitrogen (TON) concentrations and their C-to-N ratios (C/N-TON) suggest the production of TON with low C/N-TON and preferential removal of N during remineralization processes, leaving "leftover" TON with high C/N ratios. Furthermore, we found that high coral diversity and coverage sites are featured in low organic matter with high C/N, while macroalgae-dominating sites had elevated organic matter. The new data are valuable to generate hypotheses for future research to test, for example, whether sites with low organic matter are more suitable for restoring reef-building corals than sites with high organic matter. [ABSTRACT FROM AUTHOR]

Over the past few decades, the rise in anthropogenic activities has led to environmental pollution. Heavy metals and metalloids like lead, arsenic, cadmium, mercury and aluminium are major pollutants hampering the harmony of the ecosystem. Biomonitoring describes various techniques and approaches for studying biological responses to pollution. The use of lichens in pollution monitoring proved to be an efficient method to curtail it. Representing a complex life form, lichens exist in a symbiotic association connecting algae and fungus. These biosensors are not only used to monitor environmental pollutants but have also been used medicinally since time immemorial. Lichens from Parmelia emerge as a valuable tool for monitoring pollution due to their unique capacity to accumulate heavy metals. Parmelia sulcata Taylor commonly known as shield lichen inhabited on trees, rocks and even on walls and is well distributed throughout the world from cold to temperate regions of the Northern and Southern hemispheres. For centuries, Parmelia sulcata has been used in traditional medicine to cure cranial disorders and also rubbed on the gums of teething babies to alleviate discomfort. It has been found that this lichen constitutes distinctive chemical constituents such as salazinic acid, atranorin, volatile oils, etc. contributing towards the anticancer, antioxidant, anti-microbial, anti-fungal and mosquitocidal potential. The prime objective of this current manuscript is to discuss the biomonitoring and pharmacological potential of Parmelia sulcata Taylor. [ABSTRACT FROM AUTHOR]

Phthalates (PAEs) are a class of organic pollutants that are continuously released and present in the environment and are listed as priority-controlled pollutants. Soil is one of the main final fates of PAEs in the environment, and China has fully launched investigations and controls on soil pollution of PAEs. Analysis is the foundation of environmental monitoring and scientific research, and the certified reference materials in soil are important means to ensure the accuracy and reliability of determination for soil. However, the existing relevant reference materials do not meet the actual needs of pollution monitoring in China. In this study, according to the characteristics of PAEs pollution and quality control requirements of actual samples, four certified reference materials for PAEs analysis in soils have been developed through the nine laboratories’ collaborative analysis. The candidates were mainly collected from agricultural soils, plastic film mulched soil, industrial soil, and plastic recycling station soil. After homogeneity and stability testing, the results show that both homogeneity and stability meet the requirements. During the certification process, in response to the difficulty of controlling the PAEs analysis blank, the pollution source of the blank was identified and confirmed, and strict quality control measures were formulated to ensure that the blank concentration throughout the entire process remained stable within a certain range. Nine laboratories used gas chromatography-mass spectrometry (GC-MS) to collaboratively determine the values of 4 PAEs and evaluated their uncertainty in soils. The certified values of 4 PAEs in soils ranging from 36µg/kg to 2.87mg/kg. The authoritative domestic laboratory used isotope dilution mass spectrometry to verify the accuracy of the certification results. This series of reference materials have been approved as a national first-class reference material, numbered from GBW07595 to GBW07598, which meets the requirements of PAEs analysis quality assurance and quality control, and provides technical support for ecological geological survey and evaluation. [ABSTRACT FROM AUTHOR]

Bivalves play a key role in aquatic ecosystems and are a valuable commercial resource. The prosperity of these aquatic organisms depends mainly on the effectiveness of their immune defense, in which the hemolymph plays a central role. Hemolymph may be used as an effective non-lethal criterion of health. However, the predictive value of hemolymph analysis depends on the comparison between the obtained results and reference data from healthy individuals living in natural aquatic environments. We collected hemolymph from 15 commercially important species from wild populations at stations located in non-impacted and impacted water areas of the Sea of Japan. Of the 11 hemolymph parameters we analyzed, the total hemocyte count, percentage of hemocyte types, phagocytic activity, presence of reactive oxygen species, and protein concentration differed significantly between populations from non-impacted and impacted water areas. The most responsive species to pollution were Magallana gigas, Crenomytilus grayanus, Mizuhopecten yessoensis, and Mactra chinensis. This work is the first to examine a large number of commercially important species simultaneously. The results of this study are the basis for establishing the health status criteria of commercial bivalves for veterinary control in aquaculture and biomonitoring. [ABSTRACT FROM AUTHOR]

Oil spills are a serious pollution problem in water ecosystems, causing significant damage to living things and the environment. The demand for devices to handle oil remediation is increasing due to the frequent occurrence of oil spills. To date, numerous works have been reported to address this pollution problem, but most of them do not utilize Internet of Things (IoT) technology. Having an IoT system of this kind would improve operational efficiency by providing real-time data, alerts, and notifications of oil pollution through monitoring systems. This study presents the development of an IoT-based automatic oil-water separator device to support an oil pollution monitoring system in water ecosystems. The built device consists of sensors, a microcontroller, and an actuator, with the capability to automatically detect oil pollution and perform water-oil separation. The device incorporates a monitoring system. The water-oil separation was carried out by applying semi-permeable membrane nanotechnology. Moreover, the device has undergone a series of oily-water separation experiments to simulate oil pollution, achieving an oil separation efficiency of 62.8% (on average) with good repeatability. Additionally, the automatic device is developed with IoT pairing with a website application for an online monitoring system. Users can monitor the process using a personal computer or smartphone via the web/mobile application at any time and from any place. It is of interest to explore this further since it offers an effective and implementable method to solve oil pollution problems in real-world applications. [ABSTRACT FROM AUTHOR]

Climate change may increase the vulnerability of aquifers to contamination through extreme precipitation and extended drought periods. Therefore, the understanding of groundwater ecosystem dynamics is crucial, with bacterial assemblages playing a major role in biogeochemical cycles. The present research describes a geospatial study targeting the bacterial community structure of groundwaters from the largest karst aquifer in Portugal (the Maciço Calcário Estremenho), integrating hydrogeochemical and bacterial diversity data. A total of 22 samples were analyzed from a set of 11 geographically sparsely distributed groundwater sources in dry vs. wet seasons. The 16S rRNA gene barcoding data revealed bacterial community variability across samples in space and time. The phylum Proteobacteria was dominant across all samples (from 44 to 92% of total sequence reads), mainly represented by the classes Alphaproteobacteria (orders Sphingomonadales, BD7–3, Rhizobiales and Rhodospirillales), Betaproteobacteria (orders Burkholderiales, Rhodocyclales, Nitrosomonadales), Gammaproteobacteria (orders Pseudomonadales, Xanthomonadales, Alteromonadales, Legionellales) and Deltaproteobacteria (orders Myxococcales, Spirobacillales). Variation in the bacterial community was primarily attributed to parameters such as redox conditions (DO, ORP), Fe, Mn, SO4, PO4, Sr and Cl, but also some minor and trace elements (Al, V, Cr, Cu, Pb). Our results provide novel insights into bacterial diversity in relation to groundwater hydrogeochemistry. The strong dominance of OTUs related to bacterial taxa associated with nitrification/denitrification also highlights a potentially important role of these assemblages on nutrients (nitrogen sources) and groundwater quality dynamics at this karstic aquifer system. Moreover, the integration of bacterial assemblages information is emphasized as central for water quality monitoring programs. [ABSTRACT FROM AUTHOR]

The concern about indoor air quality in various micro-environments has been on the rise as buildings are vulnerable to an array of contaminants generated from various sources. The study aims to investigate and highlight the pollutant sources and composition in middle-income residential spaces through a case study approach. With large migration from small towns and saturation of megacities, the middle-income population in tier-2 cities in India is on the rise, raising concern about the well-being of the dense urban population. It involves a careful selection of typical MIG housing to identify major pollution sources from outdoor and indoor environments. The focus lies in the findings stemming from continuous air quality monitoring of PM10, PM2.5, SO2, NO2, HCHO, TVOC, CO and C6H6 and an in-depth physio-chemical analysis facilitated by Fourier transform infrared (FTIR), Analytical Scanning Electron Microscope (A-SEM) and energy-dispersive X-ray (EDX) spectroscopy of settled household dust. Analysis unveiled indoor PM2.5 concentrations of 21.93 µg/m3, exceeding WHO standards, whereas, TVOC concentrations were higher indoors than outdoors. Stark disparities between indoor and outdoor dust compositions and sources were also observed. Despite limitations, it provides a portrait of middle-income housing conditions, offering insights for interventions and future research on indoor air quality challenges. [ABSTRACT FROM AUTHOR]

The problem of environmental pollution is one of the most important in the modern world. Pollution causes an increase in human diseases, the extinction of many species of plants and animals, global warming, and many weather anomalies. One of the great challenges for scientists is the development of methods for monitoring and removing the emerging pollutants. This review focuses on Metal–Organic Frameworks (MOFs) and their use as working material to construct different types of sensors for application in environmental pollution monitoring. In particular, the detection of heavy metals (mercury, lead, and arsenic) and organic compounds (drugs, biomolecules, and pesticides) are considered. The collected data show that photoelectrochemical (PEC) sensors based on MOFs are the most fascinating materials due to various combinations (e.g., surface modification) and operational possibilities. PEC sensors achieve enormous sensitivity, which increases even to the pico level, making it the best tool in sensing applications. This review also highlights the main sensor challenges. Most of them are concerned with the possibility of reusing the sensor, its regeneration, and safe disposal. In addition, more attention should be paid to the sensor manufacturing process, which often uses toxic compounds, and research to eliminate them in favor of non-toxic compounds. [ABSTRACT FROM AUTHOR]

Water bodies play a crucial role in supporting life, maintaining the environment, and preserving the ecology for the people of India. However, in recent decades, human activities have led to various alterations in aquatic environments, resulting in environmental degradation through pollution. The safety of utilizing surface water sources for drinking and other purposes has come under intense scrutiny due to rapid population growth and industrial expansion. Surface water pollution due to micro-plastics (MPs) (plastics < 5 mm in size) is one of the emerging pollutants in metropolitan cities of developing countries because of its utmost resilience and synthetic nature. Recent studies on the surface water bodies (river, pond, Lake etc.) portrait the correlation between the MPs level with different parameters of pollution such as specific conductivity, total phosphate, and biological oxygen demand. Fibers represent the predominant form of MPs discovered in surface water bodies, exhibiting fluctuations across seasons. Consequently, present study prioritizes understanding the adaptation, prevalence, attributes, fluctuations, and spatial dispersion of MPs in both sediment and surface water environments. Furthermore, the study aims to identify existing gaps in the current understanding and underscore opportunities for future investigation. From the present study, it has been reported that, the concentration of MPs in the range of 0.2–45.2 items/L at the Xisha Islands in the south China sea, whereas in India it was found in the range of 96 items/L in water samples and 259 items/kg in sediment samples. This would certainly assist the urban planners in achieving sustainable development goals to mitigate the increasing amount of emergent pollutant load. [ABSTRACT FROM AUTHOR]

Global concern about microplastic (MP) and nanoplastic (NP) particles is continuously rising with their proliferation worldwide. Effective identification methods for MP and NP pollution monitoring are highly needed, but due to different requirements and technical challenges, much of the work is still in progress. Herein, the advanced optical imaging systems that are successfully applied or have the potential for MP identification are focused on. Compared with chemical and thermal analyses, optical methods have the unique advantages of being nondestructive and noncontact and allow fast detection without complex sample preprocessing. Furthermore, they are capable of revealing the morphology, anisotropy, and material characteristics of MP for their quick and robust detection. This review aims to present a comprehensive discussion of the relevant optical imaging systems, emphasizing their operating principles, strengths, and drawbacks. Multiple comparisons and analyses among these technologies are conducted in order to provide practical guidelines for researchers. In addition, the combination of optical and other alternative technologies is described and the representative portable MP detection devices are highlighted. Together, they shed light on the prospects for long‐term MP pollution monitoring and environmental protection.

Research on the military-technogenic burden on the natural environment as a result of international conflicts is relevant since military operations cause catastrophic consequences for the environment and natural resources, which can lead to irreversible disturbances in ecosystems. The study is devoted to the examination of the impact of military-technogenic loads on the soils of military training grounds. The paper considers methods of soil sampling and their analysis for the content of heavy metals and other chemical compounds and determines the impact of this load on the ecosystem and possible consequences for human health. The influence of military activity on the soil quality of military training grounds, in particular in the Cherkasy region, is analysed. The study includes the determination by X-ray fluorescence and atomic emission method of the content of various elements in the soil. The results showed a substantial iron content, which may be due to the use of explosives in military exercises. It is noted that despite the fact that exceeding the norms of maximum permissible content concentration, no heavy metals were recorded in the examined soils, and the maximum lead content approached the maximum permissible concentration, which requires further monitoring and control of this parameter. Ph determination showed a slightly acidic soil condition in combat exercise sites, which can affect plant fertility and growth. The content of nitrogen, phosphorus, potassium, and boron was assessed, and the results showed a lack of these nutrients for normal plant development. It is established that soil damage as a result of military operations can have a long-term negative impact and pose a threat to residents and territories. The results of the tests indicate a slight technogenic load at the sites of military exercises. The detected contamination of the examined samples is insubstantial, which indicates that the impact of military activities on the soil condition is limited. The results of the study will help to understand the possible health risks for people living near military training grounds and respond appropriately to protect their health

Rotational and rovibrational spectra are a key in astrophysical studies, atmospheric science, pollution monitoring, and other fields of active research. The ab initio calculation of such spectra is fairly sensitive with respect to a multitude of parameters and all of them must be carefully monitored in order to yield reliable results. Besides the most obvious ones, i.e., the quality of the multidimensional potential energy surface and the vibrational wavefunctions, it is the representation of the μ-tensor within the Watson Hamiltonian, which has a significant impact on the desired line lists or simulated spectra. Within this work, we studied the dependence of high-resolution rovibrational spectra with respect to the truncation order of the μ-tensor within the rotational contribution and the Coriolis coupling operator of the Watson operator. Moreover, the dependence of the infrared intensities of the rovibrational transitions on an n-mode expansion of the dipole moment surface has been investigated as well. Benchmark calculations are provided for thioformaldehyde, which has already served as a test molecule in other studies and whose rovibrational spectrum was found to be fairly sensitive. All calculations rely on rovibrational configuration interaction theory and the discussed high-order terms of the μ-tensor are a newly implemented feature, whose theoretical basics are briefly discussed. [ABSTRACT FROM AUTHOR]

A novel calcium‐based metal‐organic framework (CaMOF@LSB) was designed and synthesized, exhibiting dual functionality for both selective detection and removal of Cu2+ ions from aqueous solutions. The framework's stability, including solvent and pH variations, was established with notable thermal resilience. Colorimetric Cu2+ detection (≥5 ppm) with a high capture capacity of 484.2 mg g−1 by CaMOF@LSB places this material among the few that ensure efficient colorimetric detection and high removal capabilities of Cu2+ ions. Batch adsorption experiments revealed pH‐dependent behavior and competitive interactions. Langmuir and pseudo‐second‐order kinetics models aptly described adsorption isotherms and kinetics, respectively. Thermodynamic assessments confirmed spontaneous and endothermic adsorption. Mechanistically, nanoparticle deposition contributes to the Cu2+ uptake. CaMOF@LSB also exhibited one of the best removal behaviour of Cu2+ by means of oxide formation on the surface. Regeneration of CaMOF@LSB was achieved by simple sonication in 0.1 M aqueous NaOH solution. The recyclability was also tested up to 5 cycles, and it exhibited a small decrease in adsorption capacity observed across the cycles. This research presents a promising avenue for addressing heavy metal pollution using metal‐organic frameworks, thereby offering potential applications in water purification and environmental pollution monitoring and remediation. [ABSTRACT FROM AUTHOR]

Air pollution, particularly particulate matter such as PM2.5 and PM10, has become a focal point of global concern due to its significant impact on air quality and human health. Macau, as one of the most densely populated cities in the world, faces severe air quality challenges. We leveraged daily pollution data from 2015 to 2023 and hourly meteorological pollution monitoring data from 2020 to 2022 in Macau to conduct an in-depth analysis of the temporal trends of and seasonal variations in PM2.5 and PM10, as well as their relationships with meteorological factors. The findings reveal that PM10 concentrations peak during dawn and early morning, whereas PM2.5 distributions are comparatively uniform. PM concentrations significantly increase in winter and decrease in summer, with relative humidity, temperature, and sea-level atmospheric pressure identified as key meteorological determinants. To enhance prediction accuracy, a Stacking-based ensemble learning model was developed, employing LSTM and XGBoost as base learners and LightGBM as the meta-learner for predicting PM2.5 concentrations. This model outperforms traditional methods such as LSTM, CNN, RF, and XGB across multiple performance metrics. [ABSTRACT FROM AUTHOR]

The Tisza River is the longest tributary of the Danube, draining the eastern part of the Carpathian Basin (Central Europe). Five countries share its catchment with different waste production and management practices. Large amounts of waste, including macroplastics (MaPs), are washed into the river. Some of the litter is trapped by the riparian vegetation forming litter accumulations. The study aimed to map the amount of litter by a citizen science program and remote sensing data and to compare the MaP data to the amount of microplastic fragments in sediments. Volunteers reported 3216 riverine litter accumulations from five countries along the entire length of the Tisza (2016–2022). The results suggest that low flow conditions (e.g., impoundment by dams) support litter and MaP trapping. The volume of large accumulations registered by the citizens showed a good correlation with the area of drifting litter revealed on Sentinel-2 images (2016–2022) using machine learning algorithms. Though the MaPs probably fragmentate during their fluvial transport, no clear connection was found between the volume of litter accumulations and the mean microplastic fragment content of sediments (2019–2022). The "Clean Tisza Map" reveals the high degree of stranded pollutants along rivers and supports public cleanup activities. [ABSTRACT FROM AUTHOR]

Fast and simple detection of toxic compounds in aqueous solutions is important for agriculture and pollution monitoring. Enzyme‐based electrochemical biosensors are a promising platform for this task, but they usually lack the ability to distinguish between toxicants if more than one toxicant is present in the sample. Herein, we propose a new method of detection of various toxic compounds in complex multi‐component water samples using an electrochemical biosensor and additional stages of enzyme reactivation. The biosensor is based on butyrylcholinesterase immobilized on the surface of conductometric transducers using glutaraldehyde cross‐linking. It was shown that the biosensor is sensitive to organophosphorus pesticides, heavy metals ions, glycoalkaloids, but has a limited sensitivity to mycotoxins and surfactants. We propose a procedure for the analysis of complex samples with several reactivation stages to be able to determine which category of toxicants is present. Glycoalkaloids are reversible inhibitors and biosensor's activity is restored by washing in working buffer; heavy metal ions and pesticides are irreversible inhibitors and biosensor's activity is restored by incubation in EDTA and PAM‐2 solutions, correspondingly. This biosensor can be used for the detection of separate toxicants or for analysis of their mixtures in aqueous samples. It can be also used for the evaluation of total toxicity of the samples and applied for water quality monitoring. [ABSTRACT FROM AUTHOR]

The escalating environmental concerns have stimulated the demand for NH3 gas sensors, which are indispensable for real‐time data collection in pollution monitoring. To address this need, optimized NH3 sensor based on femtosecond‐laser textured silicon decorated with Au nanoparticles (Au‐NP) is designed. The morphologies and microstructures of the fabricated samples are characterized by scanning electron microscopy (SEM) and X‐ray diffraction (XRD) technologies. The gas‐sensing results demonstrated that the modification of Au‐NPs significantly enhances the NH3 gas‐sensing performances. Specifically, the sensor based on the textured silicon decorated with Au NPs exhibits a remarkable response of 16.02% toward 20 ppm NH3, which is 4.7 times higher than that of the pristine textured silicon gas sensor at room temperature. In addition, it also demonstrates shortened response and recovery time (26 s/98 s), showing good selectivity and long‐term availability. The enhanced NH3‐sensing mechanism of the sensor is elucidated, mainly due to the synergistic effect of textured silicon and Au NPs. These contribute to the development of portable, wearable, and intelligent sensor equipment. [ABSTRACT FROM AUTHOR]

How do communities living with chronic environmental contamination cope with the social, political, and economic impacts of the contamination? This research employs a community-engaged oral history approach with participant observation and archival research to address this question. We focus on the case of Tallevast, Florida, where the local groundwater has been contaminated with chlorinated solvents for over 60 years and where cleanup is estimated to take another 100 years. In addition to concerns about health and wellness, we find that residents are also concerned about household displacement and the disruption of social networks, failed governance at the local and state levels, and financial stress from rising healthcare costs and declining property values. Coping strategies used by the community to address these issues include reliance on churches as community hubs, environmental justice organising to contest authority and advocate for local knowledge and equity in decision making, and civil legal action to seek financial relief. These strategies support efforts toward restorative justice that seeks to repair relationships and trust between stakeholders needed for community redevelopment and revitalisation by promoting equity in being able to contribute meaningfully to decisions that affect resident's health and the environment. [ABSTRACT FROM AUTHOR]

Background: Plastic pollution is a significant issue on the East Coast of Surabaya, emphasizing the need to develop microplastic monitoring programs. Barnacles became one of the potential microplastic bioindicator species on the East Coast of Surabaya. This study aimed to characterize the visual and polymers of microplastics found in barnacles and assess their potential as a bioindicator species for microplastic pollution on the East Coast of Surabaya. Methods: Microplastic polymer analysis was performed using ATR-FTIR. Results: A total of 196 microplastic particles were found in barnacles, water, and sediment. The size of microplastics in barnacles, water, and sediment varied, with the size in barnacles dominated by class 1 (1–10 µm), in water by class 2 (10–50 µm), and in sediments by class 3 (50–100 µm). Fragments dominated the shape of microplastics in barnacles, while water and sediment were dominated by fiber. The microplastic color in barnacles, water, and sediment was dominated by blue, and the microplastic polymer composition on barnacles, water, and sediments was dominated by cellophane (36%). Amphibalanus amphitrite was found to be predominant and identified as a potential microplastic bioindicator because it is a cosmopolitan species. Its population was found to correlate positively with cellophane (CP) accumulation. The Pearson's correlation test between barnacle length and microplastic length at a = 0.05 was inversely proportional to r = − 0.411 (p < 0.05), categorized as a strong enough correlation. These findings are essential in developing monitoring programs and mitigating the impact of microplastics on the marine environment. [ABSTRACT FROM AUTHOR]

Groundwater is essential to human well‐being and sustains a variety of aquatic ecosystems in both urban and rural settings. Yet, it is commonly overlooked in these contexts. As a result, groundwater may be very important to the development and well‐being of many nations if it is properly evaluated and utilized. Although the possibility for sustainable groundwater resource development is still debated in the literature, these issues still lack quantitative understanding. In order to assess groundwater potential in two different urbanized regions of "Northern Kerala, Southern India," this research uses the "Enhanced Fuzzy Analytic Hierarchy Process (E‐Fuzzy AHP) based Multi‐Criteria Decision Making (MCDM)‐Geospatial Framework employing Improved Particle Swarm Optimization (IPSO)". The study area is a coastal region that is quickly becoming urbanized and relies on groundwater resources to meet its basic needs. By incorporating both spatial and non‐spatial data into the Geographic Information System (GIS) platform, a groundwater potential zone map with an accurate integer value was created, known as the "groundwater potential index (GWPI)". The very excellent potential zone occupies 35% and 11%, respectively, of the "urban and peri‐urban zones," according to the final groundwater potential map, which employed the quantile technique to split the research territory into four zones. The statistical effectiveness and dependability of results in the overall decision‐making phase were examined in the validation study using the data on mean water depth level, and it was found that the reliability was well within the tolerance threshold. [ABSTRACT FROM AUTHOR]

River contamination by microorganisms, or another chemical source, poses a serious threat to both the environment and public health. Taking immediate and appropriate actions is essential to mitigate the contamination and prevent further spread. As such, regular monitoring of these pollution agents is essential to act in time and control its minor extension. However, there is a lack of commitment to this emergent concern and respective actions around the world. This work aims to study the contamination of a Portuguese river (Tinto River) within Porto city (a highly populated urban area) regarding the total aerobic microorganisms, coliforms, and Enterococcus (as colony-forming units (CFUs) using specific solid culture media) and total organic matter (TOC). Different locations were considered along the Tinto River course (i.e., 14 locations within 11 km) and samples were collected on distinct days throughout September 2022. The overall results showed microbial contamination of aerobic microorganisms (up to 2 × 105 CFU/100 mL), total coliforms (up to 7 × 104 CFU/100 mL), Escherichia coli (up to 9 × 103 CFU/100 mL), and Enterococcus (up to 8 × 103 CFU/100 mL). The results also surpassed the maximum recommended values (MRVs) described in Portuguese decree-law no. 236/98 for irrigation waters. Moreover, TOC was found in a range of 4.54 mg/L to 57.2 mg/L. This work highlights the dangerous microbial contamination and higher amount of organic matter than would be expected for a surface water resource. [ABSTRACT FROM AUTHOR]

This study investigated cadmium in urban sparrows from various Meknes zones with differing industrial and traffic intensities, compared to a rural site. Forty sparrows from industrial regions and ten from rural were analysed post-capture. Cadmium extraction used acid mineralisation, quantified via ICP. Findings revealed higher cadmium in sparrows' kidneys from industrial zones than the rural site, with an average of 1.25 µg/g wet weight, indicating urban and industrial impacts on metal accumulation. The kidneys showed notable vulnerability to cadmium. Statistical data highlighted significant concentration differences between zones. This research emphasises the need for environmental monitoring and pollution strategies in urban areas for safeguarding health. [ABSTRACT FROM AUTHOR]

Measuring the dynamics of microbial communities results in high-dimensional measurements of taxa abundances over time and space, which is difficult to analyze due to complex changes in taxonomic compositions. This paper presents a new method to investigate and visualize the intrinsic hierarchical community structure implied by the measurements. The basic idea is to identify significant intersection sets, which can be seen as sub-communities making up the measured communities. Using the subset relationship, the intersection sets together with the measurements form a hierarchical structure visualized as a Hasse diagram. Chemical organization theory (COT) is used to relate the hierarchy of the sets of taxa to potential taxa interactions and to their potential dynamical persistence. The approach is demonstrated on a data set of community data obtained from bacterial 16S rRNA gene sequencing for samples collected monthly from four groundwater wells over a nearly 3-year period (n = 114) along a hillslope area. The significance of the hierarchies derived from the data is evaluated by showing that they significantly deviate from a random model. Furthermore, it is demonstrated how the hierarchy is related to temporal and spatial factors; and how the idea of a core microbiome can be extended to a set of interrelated core microbiomes. Together the results suggest that the approach can support developing models of taxa interactions in the future. [ABSTRACT FROM AUTHOR]