Search

AbstractWater quality assessment is crucial for public and ecosystem health, yet traditional approaches often overlook the nutritional aspects of drinking water. This study introduces the Drinking Water Nutritional Quality Index (DWNQI) to Africa, presenting its first application in the continent. The research evaluated the nutritional status of drinking water resources in semi-urban areas of Southeast Nigeria, shifting from a contaminant-focused paradigm. Water samples were strategically collected from various drinking water sources. Five key elements (Na+, Mg2+, Ca2+, Mn2+, and Zn2+) that play crucial roles in both human health and environmental processes were considered. The DWNQI model revealed a concerning nutritional trend, with DWNQI scores ranging from 9.76 to 78.54 (average 32.02). The analysis showed that 73.33% of samples fell within the “Poor” category, 13.33% in “Marginal,” 6.67% in “Fair,” and 6.67% in “Good” categories, with no samples reaching the excellent range, indicating a low nutritional water quality trend in the area. Sensitivity analysis reveal that Mg2+and Ca2+ exerted the most influence on the DWNQI scores for the studied water samples. Removal of Mg2+ from the index resulted in a 23.77% decrease in the average DWNQI score, while removal of Ca2+ led to a 23.42% decrease. Key recommendations include implementing targeted mineral enrichment programs and developing public health initiatives to address potential mineral deficiencies. This research contributes to environmental sustainability and public health by providing a new perspective of water quality, potentially informing water management policies and guiding public health interventions in African settings and beyond. [ABSTRACT FROM AUTHOR]

A novel inorganic nonmetallic material boron carbide (B4C) was applied in paper spray ionization to analyze organic molecules in both negative and positive modes. The utilization of B4C has led to a notable enhancement in signal responses for various molecules, including bisphenols and drugs, by approximately two to four times. The limit of detection (LOD) of bisphenol AF and nilotinib standard solutions can reach 1 and 0.5 μg/mL, respectively. Moreover, linear relationships for bisphenol AF was established within the concentration range of 1–100 μg/mL, exhibiting strong correlation coefficients. Recovery experiments for BPAF in water samples from the inlet and outlet of a sewage treatment plant, conducted without any pretreatment, achieved a maximum recovery rate of 98.8% and an RSD below 9.78%. [ABSTRACT FROM AUTHOR]

The air quality index (AQI) is a commonly employed metric for evaluating air quality across diverse locations and temporal spans. Similar to other environmental datasets, AQI data can exhibit outliers data points markedly divergent from the norm, signifying instances of exceptionally favorable or adverse air quality. This becomes crucial in identifying and comprehending severe pollution episodes with far‐reaching environmental and public health implications. This study utilizes air quality data from January 1, 2014, to January 31, 2021, collected at daily intervals in Shanghai City, China, as the experimental dataset. The dataset includes daily AQI measurements, along with six pollutant concentrations: particulate matter (PM2.5 and PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO). Each pollutant's concentration is measured in micrograms per cubic meter (μ$$ \upmu $$g/m 3$$ {}^3 $$). The dataset is then preprocessed by cleaning and normalizing it before using K‐means clustering to discover different patterns. A stacked ensemble machine learning model that incorporates K‐means clustering, random forest (RF) and gradient boosting classifier (GBC) is developed and compared to decision tree, support vector machine, K‐nearest neighbor and Naive Bayes algorithms to evaluate its performance in identifying outliers using accuracy, precision, recall, and F1‐score. The stacked model outperformed all other established models based on the accuracy, precision, recall, and F1‐score of 0.99, 0.99, 0.97, and 0.99, respectively. [ABSTRACT FROM AUTHOR]

The increasing manufacturing of tires, driven by the automotive sector, has led to various sustainability and waste management issues. Consequently, it is necessary to explore alternatives for the reuse of these wastes. Rubber has demonstrated properties that could make it an attractive material for use as a granular aggregate. The aim of this study is to evaluate the influence of crumb rubber (CR) on the mechanical behavior of a granular subbase (GSB) by replacing fine CR at 10% and 15%. An environmental analysis of the proposal was conducted using the SimaPro tool, and a series of laboratory tests were performed to assess physical and mechanical characteristics. The strength results indicate a decreasing trend as the CR content in the GSB increases. Specifically, in abrasion tests, the natural material showed an average result of 30.86%, while the mixes with 10% and 15% CR exceeded the maximum limit (50%), achieving results of 59.24% and 53.98%, respectively. In terms of the California Bearing Ratio (CBR), only the natural samples compacted at maximum energy exceeded the minimum requirements for low and medium traffic levels (30%). The highest CBR value for samples containing CR was 5%, whereas the natural GSB reached a maximum CBR of 33%. A similar trend is observed in environmental outcomes, with increases of up to 17% in abiotic depletion for the sample with 15% CR. Overall, the environmental analysis suggests that incorporating CR into the GSB could lead to an increase in various environmental impacts. [ABSTRACT FROM AUTHOR]

Toxic metals and metalloids pollution is a major ecological and human health issue, yet classical detection methods are limited. Here we review surface-enhanced Raman spectroscopy-based sensors using nanomaterial-based substrates for metal detection, with emphasis on substrate composition, functionalization, and assembly; metal sensing strategies; and analytical performance. Substrates include nobel metals, semiconductors, and composites. Substrate assembly can be done in solution or on solid supports. Sensing strategies comprise direct sensing, reporter recognition, reporter migration, substrate aggregation, and substrate modification. In general, the physicochemical properties of the substrates determine sensor sensitivity through electromagnetic and chemical enhancements of Raman scattering, whereas substrate surface functionalization, or lack thereof, determines sensor selectivity and the sensing mechanism. The main elements analyzed are mercury, lead, copper, arsenic, and chromium. [ABSTRACT FROM AUTHOR]

This study introduces a novel approach for transforming the cationic surfactant, cetyltrimethylammonium bromide (CTAB), into fluorescent carbon dots (CDs) capable of detecting cadmium ions at ultralow concentrations. The current approach involves preparing CDs through hydrothermal process at various pH levels. The CDs synthesized using pH 10, CTAB-CDs-10, exhibited the highest fluorescence quantum yield (QY), 14.22%. UV-Vis spectroscopy helped identify specific peaks between 210 and 300 nm, corresponding to the π–π* transitions of the aromatic C=C bonds. Transmission electron microscopic (TEM) analysis verified the uniform spherical morphology with a particle size < 2.45 nm. FT-IR analysis confirmed the presence of C=C stretching vibrations. The Box–Behnken (BB) Design was used to reconnoiter the influence of three variables on the response parameter: the F0/F ratio. The best performance could be achieved at a pH of 9, after only 300 s, and a temperature of 50 °C. The developed CTAB-CDs-based nanoprobe showed an ON–OFF behavior when came in contact with cadmium (II) and demonstrated high sensitivity with a limit of detection as low as 0.06 µM (0.007 ppm) over a wide linear range of 2–103 µM. Validation tests confirmed the applicability of the CTAB-CDs-based nanoprobe for detecting cadmium (II) in tap and drinking waters with high accuracy and precision. [ABSTRACT FROM AUTHOR]

The increasing energy demand, the reduction of non-renewable resources, and the increase in environmental damage factors have drawn attention to energy supply through multi-generation systems. This study proposes a multi-generation system based on the Allam cycle, integrated with geothermal energy, with the aim of minimizing natural gas fuel consumption. This system includes the main sub-systems: an electrolyzer unit, a reverse osmosis unit, an organic Rankine cycle, a hydrogen engine, an absorption chiller, and a compression chiller. The proposed multi-generation system provides the hourly demands of freshwater, cooling, heating and electricity of a residential building located in the city of St. Petersburg (in Russia). For the purpose of feasibility, the system is studied from the thermodynamic, environmental, and economic points of view. The results of the thermodynamic analysis showed that the system has maximum energy and exergy efficiency of 29.759 and 25.879% respectively. The use of geothermal energy reduced CO2 emissions to a maximum of 1895043 gr. Calculation of the NPV index for interest rates of 15 to 30% showed that this system will be profitable in the twelfth year at most. [ABSTRACT FROM AUTHOR]

The circular economy, as a new model of waste management through energy self-sufficiency and valorisation, can be applied to wastewater treatment plants (WWTPs). Screening waste from WWTP pretreatment is the only waste that is not energetically recovered and thus constrains the achievement of zero waste. Previous studies demonstrated the technical feasibility of producing solid recovered fuel (SRF) from this waste. Environmental benefits, including waste reduction, resource conservation, or reduced greenhouse gas emissions are analysed in this work. Environmental impact is quantified using the life cycle assessment (LCA) methodology through the SimaPro 9.2. software and the CML-IA baseline v3.08 impact methodology, that propose 11 impact categories. Five scenarios were established to compare current landfill disposal with the production of densified and non-densified SRF using solar and thermal drying. Within the system boundaries studied, from waste generation to SRF production, results show that landfill is the most environmentally damaging option while producing non-densified SRF using solar drying is the most environmentally viable scenario. [ABSTRACT FROM AUTHOR]

Automated analysis of microplastics is essential due to the labor-intensive, time-consuming, and error-prone nature of manual methods. Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy offers valuable molecular information about microplastic composition. However, efficient data analysis tools are required to effectively differentiate between various types of microplastics due to the large volume of spectral data generated by ATR-FTIR. In this study, we propose a machine learning (ML) approach utilizing ATR-FTIR spectroscopy data for accurate and efficient classification of undegraded and aged polyethylene terephthalate (PET) microplastics (MPs). We evaluate seven ML algorithms, including Random Forest (RF), Gradient Boosting (GB), Decision Tree (DT), k-Nearest Neighbors (k-NN), Logistic Regression (LR), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP), to assess their performance. The models were optimized using fivefold cross-validation and evaluated using multiple metrics such as confusion matrix, accuracy, precision, recall (sensitivity), and F1-score. The experimental results demonstrate exceptional performance by RF, GB, DT, and k-NN models, achieving an accuracy of 99% in correctly classifying undegraded and aged PET MPs. The proposed approach capitalizes on the potential of ATR-FTIR spectra to discern distinct chemical signatures of undegraded and aged PET particles, enabling precise and reliable classification. Furthermore, the method offers the benefit of automating the classification process, streamlining the analysis of environmental samples. It also presents the advantage of providing an effective means for method standardization, facilitating more automated and optimized extraction of information from spectral data. The method's versatility and potential for large-scale application make it a valuable contribution to the field of MP environmental research. [ABSTRACT FROM AUTHOR]

The sedimentary fill of Gale crater on Mars is dominated by lacustrine strata that are the focus of investigations into surface processes, climate change and habitability early in the planet's history. This study focuses on the lower part of the explored portion of the Murray formation on Aeolis Mons (Mount Sharp) in the Pahrump Hills and Hartmann's Valley field areas. At Pahrump Hills, sedimentary features and geochemical attributes of exposed mudstones suggest accumulation in an underfilled lake basin in which lake levels, shorelines and salinities fluctuated greatly at various temporal scales. The immediately superjacent stratigraphic interval, designated by the rover team as the Hartmann's Valley member, has previously been interpreted as an aeolian‐deposited sandstone interval. This fresh examination of all available data, however, suggests that the Hartmann's Valley member is strongly dominated by the same mudstone facies that compose most of the underlying Pahrump Hills member. The one novel facies element encountered in the Hartmann's Valley member are undulose bedded to convex bodies of mudstone that are oriented roughly north–south, suggestive of sediment supply from a northern fluvial source. Mudstones analogous in scale and character to these undulose mudstones occur on Earth in multiple modern and ancient lacustrine successions, and are related to deposition of prodelta mud lobes. The mudstones of the Hartmann's Valley member record a continuation of the underfilled evaporitive lake system proposed previously for the underlying Pahrump Hills member but with somewhat more variable environmental conditions. Hartmann's Valley mudstones contain more abundant matrix CaSO4, suggesting more severe evaporitic conditions, whereas the interbedded undulose bedded mudstones signify intermittent freshening and buildout of mud‐dominated deltas into the lake. The textural similarities between Pahrump Hills and Hartmann's Valley strata suggest that the Gale lacustrine system operated at a stable depositional mode with similar environmental parameters during both stratigraphic intervals. [ABSTRACT FROM AUTHOR]

Chemosensing of ions has gained considerable attention by chemists. Insight into the mechanism involved between sensors and ions always fascinates researchers to develop economical, sensitive, selective, and robust sensors. This review comprehensively explores the mechanism of interaction between Imidazole sensors and anions. With most of the research concentrating only on fluoride and cyanide, this review has highlighted a large gap in various anions detection including SCN−, Cr2O72−, CrO42−, H2PO4−, NO2−, and HSO4−.This study also includes a critical analysis of different mechanisms and their respective limits of detection, with a discussion of the reported results. [ABSTRACT FROM AUTHOR]

Owing to the far-reaching environmental consequences of agriculture and food systems, such as their contribution to climate change, there is an urgent need to reduce their impact. International and national governments set sustainability targets and implement corresponding measures. Nevertheless, critics of the globalized system claim that a territorial administrative scale is better suited to address sustainability issues. Yet, at the sub-national level, local authorities rarely apply a systemic environmental assessment to enhance their action plans. This paper employs a territorial life cycle assessment methodology to improve local environmental agri-food planning. The objective is to identify significant direct and indirect environmental hotspots, their origins, and formulate effective mitigation strategies. The methodology is applied to the administrative department of Finistere, a strategic agricultural region in North-Western France. Multiple environmental criteria including climate change, fossil resource scarcity, toxicity, and land use are modeled. The findings reveal that the primary environmental hotspots of the studied local food system arise from indirect sources, such as livestock feed or diesel consumption. Livestock reduction and organic farming conversion emerge as the most environmentally efficient strategies, resulting in a 25% decrease in the climate change indicator. However, the overall modeled impact reduction is insufficient following national objectives and remains limited for the land use indicator. These results highlight the innovative application of life cycle assessment led at a local level, offering insights for the further advancement of systematic and prospective local agri-food assessment. Additionally, they provide guidance for local authorities to enhance the sustainability of planning strategies.

The article explores the connection between melting permafrost and heavy metals in mountain lakes. It explains that as permafrost melts and glaciers retreat, heavy metals can become more concentrated in streams and lakes, especially in areas with sulfide-containing bedrock. This is due to acid mine drainage, which lowers the pH of the water and causes heavy metals to dissolve. The article also presents a series of experiments that can be used in classrooms to demonstrate the effects of acid mine drainage on water quality. These experiments allow students to observe the pH changes and increased copper content in water samples exposed to pyrite. The experiments provide a hands-on learning experience for high school chemistry and environmental science classes. [Extracted from the article]

The demand for hydrogen in South Korea is projected to reach 3.9 Mt by 2030, of which 2.96 Mt clean hydrogen is aimed by 2030. As such, we conduct an economic analysis of a low greenhouse gas emission hydrogen supply chain in South Korea using several H 2 transportation methods in this study. The types of supply chains considered are green and blue ammonia; green and blue liquid hydrogen (LH 2) imported from the Gulf Cooperation Council (GCC) region; and blue hydrogen produced in South Korea. A base-case analysis shows that the imported blue ammonia scenario is the most cost-effective option with 3.40 USD/kg H2 , followed by the domestic blue hydrogen with 4.33 USD/kg H2, and imported green ammonia with 4.56 USD/kg H2. In environmental analysis, imported green ammonia shows the lowest CO 2 footprint with 4.20 kg CO2 /kg H2 , followed by imported green LH 2 with 6.26 kg CO2 /kg H2 , and domestic blue hydrogen with 7.34 kg CO2 /kg H2. • Imported blue ammonia scenario is the most cost-effective option at 3.40 USD/kg H2 • Cost reduces further when ammonia is used for power generation or as a marine fuel • Imported blue and green LH 2 show a far higher hydrogen supply cost than the others • Electrolysis has largest portion of hydrogen supply cost • Imported green ammonia shows the lowest CO 2 footprint with 4.20 kg CO2 /kg H2 [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Inorganic Analytical Chemistry / Zhongguo Wuji Fenxi Huaxue is the property of Beijing Research Institute of Mining & Metallurgy Technology Group and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Different approaches continue to be used to evaluate the environmental and financial impacts of road pavements throughout their life cycle. This paper aims to provide a methodological review of published studies of asphalt pavement Life Cycle Assessment (LCA) and Life Cycle Cost Analysis (LCCA) and make recommendations for future studies. The results indicate that LCA studies limitations are related to functional units (FUs), chosen life cycle phases, maintenance schedules decision, and uncertainty. In comparison, the use of LCCA is limited to assessing maintenance strategies, is largely focused on agency cost, and usually ignores the possibility of current or future uncertainty. Accordingly, it is recommended to incorporate both LCA and LCCA, define a standard set of FUs, include the complete life cycle (including for new materials), consider pavement performance predictions in determining realistic maintenance schedules, include both short- and long-term costs and environmental impacts, and emphasise on probabilistic analysis of uncertainty. [ABSTRACT FROM AUTHOR]

Introducing a cutting-edge technique, we have harnessed the exceptional properties of 1-(2-arsonophenylazo)2-naphthol (APAN) as a highly sensitive reagent, expertly immobilized within a sol-gel thin film. Our revolutionary optical test strip now enables swift and accurate detection of Th(IV) in aqueous solutions, eliminating the need for cumbersome extraction processes. A comprehensive exploration of vital experimental parameters, including membrane composition, pH variations, and the type and concentration of regenerating reagents, has been meticulously undertaken to optimize performance. Innovatively designed with a square-sensing zone measuring 1.0 cm × 1.0 cm, our test strip encompasses the essential APAN reagent, capable of promptly responding to even minute traces of thorium. The dynamic response exhibited a remarkable linearity within the Th(IV) concentration range of 10–235 ng ml−1, granting calculated detection and quantification limits of 3.0 and 9.9 ng ml−1, respectively. A mere 3-min response time, coupled with the ideal pH of 3.25, contributes to unparalleled measurement repeatability and sensor-to-sensor reproducibility, exemplifying the excellence of our methodology with a mere 1.75% relative standard deviation (RSD). Our unwavering commitment to selectivity shines through in comprehensive interference investigations, showcasing the proficient trapping of APAN within the sol-gel matrix, deftly tailored for Th(IV) assessments. The sensor's prowess surpasses its contemporaries, confidently validated in discerning Th(IV) levels across diverse environmental samples, rendering satisfactory outcomes. In the pursuit of innovation, our novel approach exemplifies a harmonious blend of professionalism and creativity, promising transformative advancements in Th(IV) detection methodologies. Highlights: The color changes due to Th4+ uptake in fabricated sensor entrapment with APAN. A dynamic range of 10–235 ng ml−1 and a detection limit of 3.0 ng ml−1 was obtained. The quantification limit of the optode film was found to be 9.9 ng ml−1 Th4+. The optode sensor developed was tested in real and environmental samples. [ABSTRACT FROM AUTHOR]

In response to escalating concerns about climate change, there is a growing imperative to prioritize the decarbonization of the telecom sector and effectively reduce its carbon emissions. This study presents a thorough techno-economic optimization framework for implementing renewable-dominated hybrid standalone systems for the base transceiver station (BTS) encapsulation telecom sector in Pakistan. It is noted that from the results obtained from 42 BTS sites overall, 21 BTS sites had a feasible combination of a photovoltaic battery system, having a diesel generator as a backup source with an average LCOE of 0.1246 USD/kWh to 0.2325 USD/kWh. Thus, seven BTS sites had an optimal combination of biomass, with photovoltaic and battery storage systems and with a varied LCOE of 0.1175 USD/kWh to 0.1318 USD/kWh. Moreover, due to the high flow of hydro water in the north region, five BTS sites presented an ideal configuration of a hydro system coupled with a photovoltaic, wind, and battery storage system, with a varied LCOE of 0.04547 USD/kWh to 0.07419 USD/kWh. Wind energy systems are dominant in the southern region; therefore, five BTS sites presented an ideal combination of a wind energy system coupled with a photovoltaic battery storage system, having DGs as backup sources for sustainability and with a varied LCOE of 0.1096 USD/kWh to 0.1294 USD/kWh. In addition, 02 BTSs had an optimal combination of photovoltaic systems coupled with hydro and wind systems, with diesel generators having a varied LCOE of 0.07618 USD/kWh to 0.04575 USD/kWh. The remaining 02 BTS sites had a feasible combination of wind–hydro-battery and diesel generator–photovoltaic–hydro-battery systems, with an LCOE of 0.7035 USD/kWh and 0.1073 USD/kWh, respectively. Finally, an environmental analysis based on carbon emissions, as well as sensitivity analyses based on different uncertainties, i.e., wind speed, solar irradiance, inflation rate, discount rate, and load demand, was performed to evaluate the behavior of the proposed systems. The optimization of these systems and comparative study findings indicate that the hybrid BTS system is the best option, better than conventional diesel-operated BTS systems in terms of cost-effectiveness, environmental friendliness, and sustainability. [ABSTRACT FROM AUTHOR]

The production, optimisation, physicochemical, and electroanalytical characterisation of a low-cost electrically conductive additive manufacturing filament made with recycled poly(lactic acid) (rPLA), castor oil, carbon black, and graphite (CB-G/PLA) is reported. Through optimising the carbon black and graphite loading, the best ratio for conductivity, low material cost, and printability was found to be 60% carbon black to 40% graphite. The maximum composition within the rPLA with 10 wt% castor oil was found to be an overall nanocarbon loading of 35 wt% which produced a price of less than £0.01 per electrode whilst still offering excellent low-temperature flexibility and reproducible printing. The additive manufactured electrodes produced from this filament offered excellent electrochemical performance, with a heterogeneous electron (charge) transfer rate constant, k0 calculated to be (2.6 ± 0.1) × 10−3 cm s−1 compared to (0.46 ± 0.03) × 10−3 cm s−1 for the commercial PLA benchmark. The additive manufactured electrodes were applied to the determination of β-estradiol, achieving a sensitivity of 400 nA µM−1, a limit of quantification of 70 nM, and a limit of detection of 21 nM, which compared excellently to other reports in the literature. The system was then applied to the detection of ß-estradiol within four real water samples, including tap, bottled, river, and lake water, where recoveries between 95 and 109% were obtained. Due to the ability to create high-performance filament at a low material cost (£0.06 per gram) and through the use of more sustainable materials such as recycled polymers, bio-based plasticisers, and naturally occurring graphite, additive manufacturing will have a permanent place within the electroanalysis arsenal in the future. [ABSTRACT FROM AUTHOR]

An environmentally conscious methodology is investigated for the precise and discerning identification of trace concentrations of gold ions in diverse matrices. A novel optical sensor membrane is proposed for the determination of Au3+ ions, utilizing the immobilization of β-2-hydroxybenzyl-3-methoxy-2-hydroxyazastyrene (HMHS) entrapped in polyvinyl chloride (PVC). The sensor incorporates sodium tetraphenylborate (Na-TPB) as the ionic additive and dibutyl phthalate (DBP) as a plasticizer. Under optimal conditions, the suggested sensor exhibits a linear calibration response to Au3+ ions within a concentration range of 5.0 to 165 ng mL−1. Detection and quantification limits are specified as 1.5 and 4.8 ng mL−1, respectively, with a rapid response time of 5.0 min. Upon presentation, this optical sensor not only affirms high reproducibility, stability, and an extended operational lifespan but also showcases exceptional selectivity for Au3+ ions. Notably, no discernible interference is observed when assessing the potential influence of other cations and anions on Au3+ ion detection. The adaptability of this optical sensor is validated through its successful application in determining Au3+ ion concentrations across various sample types, including water, environmental, cosmetics, and soil matrices. [ABSTRACT FROM AUTHOR]

The measurement uncertainty (MU) in environmental analyses is usually considered as a combination of the additive contributions from sampling, sample preparation and analytical measurement (usually instrumental). The target MU for such studies is usually relatively high due to the natural sample heterogeneity and/or the complicated pretreatment procedure required. In the analytical practice, the contribution of the sample preparation to MU is rarely evaluated. Thus, it remains a hidden part of the one related to the analysis. However, the knowledge for the contribution of sample preparation might provide important information and further possibility for optimization of the entire analytical procedure and reduction of the expanded MU of the analytical result. From statistical point of view, the separation of uncertainty contributions from the different steps is, generally, not a trivial task. Selection of the proper statistical approach depends on the data structure and quality, variables distribution, etc. In the present study, three different statistical methods for evaluation of the uncertainty contribution of the sample preparation were applied, compared, and discussed. The considered approaches are based on, both, classical and robust analysis of variances (ANOVA) applied to data from instrumental analysis of marine algae and bee honey samples, undergoing microwave digestion. Some general recommendations on the statistical approach selection are revealed based on real experimental data set. [ABSTRACT FROM AUTHOR]

Monitoring and measuring pharmaceutical pollutants in environmental samples is a vital and complex task due to their potential detrimental effects on human health, even at low levels. Using capillary zone electrophoresis (CZE) and ultra-high-performance liquid chromatography (UHPLC), it was possible to separate and measure three commonly used antipsychotic drugs, chlorpromazine (CPZ), haloperidol (HAL), and risperidone (RIS), in wastewater of the pharmaceutical industry. The technique of solid-phase extraction (SPE) was developed and implemented as a very effective method for preparing samples prior to analysis. The settings of the capillary electrophoretic and chromatographic techniques were adjusted to obtain the most efficient separation profile for the medications being studied. The concentration of all the medicines being investigated ranged from 0.5 to 50 µg/mL. SPE was used to treat real wastewater samples after a thorough validation process that followed the rules set by ICH-Q2B. The developed assays were then effectively employed to identify the tested antipsychotic substances in the real wastewater samples. The provided methodologies may be efficiently utilized to monitor the extent of environmental contamination caused by the investigated pharmaceuticals. [ABSTRACT FROM AUTHOR]

• Hazardous asbestos cement waste has been inertized. • Statistical mixture design was employed as a dosing method. • Asbestos cement waste increased yield stress, reducing set time. • Compressive strengths over 60 MPa have been obtained. • Asbestos cement waste reduced CO 2 emissions by ∼ 5 %. This article explores the impact of thermally treated asbestos-cement waste (ACW T) on metakaolin-based geopolymers, using liquid sodium silicate (LSS) and liquid potassium silicate (LKS) as alkali activators. Through statistical mixture design, various formulations were tested for rheological parameters, mineralogical composition, efflorescence mass, electrical conductivity, compressive strength, and CO 2 emissions. Formulations with sodium silicate exhibited higher yield stress compared to those with potassium silicate, while flash setting occurred in LKS-activated mixtures with high ACW T content. Alkali activator content significantly affected mechanical strength and leachate electrical conductivity. CO 2 emissions were higher for LKS-activated formulations but lower for those with more ACW T. Finally, by incorporating ACW T , it was possible to optimize the formulations, resulting in high compressive strength, reduced free ions, and reduced negative environmental impact. [ABSTRACT FROM AUTHOR]

Floating Photovoltaic (FPV) systems are gradually becoming more desirable due to a multitude of reasons, encompassing proximity to urban water reservoirs (facilitating city access) and their technical advantages. Climate change potentially presents risks of drought and FPV can potentially benefit by providing clean energy as well as saving water from evaporation. However, detailed studies are required to comprehensively evaluate the potential of FPV considering not only the technical parameters but evaluating the climatic effects as well. This paper presents an integrated multi-dimensional framework for the analysis of 2.5 MW grid-connected FPV systems over different climatic zones. In the first layer, a techno-economic and performance evaluation is carried out by fine-tuning different inputs of systems to make it ideal for proposed analyses under actual FPV conditions. Similarly, in the second layer environmental along with forest absorbing carbon analyses are performed. While socio analysis observed in the third fold is based on various SDGs and their indicators. Results reveal that the Dam with cold in winter and hot in summer climate conditions observed a most feasible site with a Levelized cost of energy (LCOE) of $0.047/kWh and a Net present value (NPV) of million $1.7705, respectively. In contrast, a Dam with mild cold climate conditions proves the least feasible site with LCOE of $0.057/kWh and NPV of million $1.0256, respectively. Similarly, the former Dam saved 20.50% higher CO2 emissions as compared to the latter, as well as required hectares of forest absorbing carbon. A comparative analysis observes a capacity factor of 22% and a performance ratio (PR) of 5%-10% higher as compared to solar photovoltaic (SPV) for dams with extreme weather. [ABSTRACT FROM AUTHOR]

Transcription factors are a class of proteins that regulate gene expression in cells by directing RNA polymerases to bind to specific DNA sequences. Transcription factors, as important regulatory proteins for prokaryotes to adapt to the natural environment, can specifically sense ligand molecules in environmental media. By coupling with different signal transduction and amplification systems, biosensing systems with transcription factors as recognition elements can construct flexible sensing strategies in whole-cell system, cell-free system and in vitro reaction systems. The transcription factor-based biosensors（TFBBs）have the advantages of high sensitivity, small size, low-cost, and on-site monitoring, showing great potential in the analysis of environmental pollutants. This paper introduces the reaction system types, core component compositions and working principle of TFBBs, as well as lists their application progress in the detection of environmental pollutants including heavy metal ions, aromatic compounds and antibiotics. On this basis, the opportunities and challenges for TFBBs in the detection of environmental pollutants are discussed, and the development trend of TFBBs is prospected. It points out that the rapid development of interdisciplinary emerging technologies such as synthetic biology and artificial intelligence will promote the artificial design and sensing performance improvement of TFBBs, making them applicable in a wider range of fields. [ABSTRACT FROM AUTHOR]

In the present investigation, thermodynamic/eco/environmental analysis of the relationship between time-dependent particle deposition and thermal-based losses and incident solar radiation intensity on the PV front cover glass during the months with the least precipitation in the city of Samsun (Turkey) was performed. To evaluate the effect of dust accumulation, controlled experiments were carried out where the surface of one set of PV panels was periodically cleaned with water and the other one was left to natural contamination. The results showed that over three months, the difference in energy loss rates between cleaned and uncleaned PV arrays ranged from 2.53% to 8.1%, with the exergy efficiency difference measured at 1.3%–2.44%. According to the energy-based analyzes, August was the most effective month, with cleaned PV arrays reducing CO2 emissions by 401.5 kg and saving $6.02, compared to uncleaned PV arrays which reduced emissions by 362.21 kg and cost $5.43, respectively. Similarly, in the exergy-based evaluation, August was the most efficient month, with cleaned PV arrays decreasing CO2 emissions by 401.5 kg and saving $6.02, compared to uncleaned PV arrays, which dropped CO2 emissions by 362.21 kg and costing $5.43, respectively. While the cleaned surfaces were initially positive, a decrease was observed over time. However, the efficiency of PV decreased with increasing panel temperature. The study concludes that PV surfaces need to be cleaned at certain intervals, depending on the location's weather conditions. [ABSTRACT FROM AUTHOR]

There has been rapid progress in the development of fast, sensitive, cheap and low-cytotoxicity micro-molecule fluorescent probes for application in various fields, including disease diagnosis, food safety and environmental safety. As an analytical tool, dual-function fluorescent probes with dual-emission responses have attracted considerable attention due to their cost-effectiveness and efficiency over single-function sensors. This review primarily describes research progress on multifunctional probes in terms of the reaction type and coordination type, as well as the general design principles of probes. The analytes include reactive oxygen species (ROS), reactive sulfur species (RSS), harmful cations and anions, etc. Multifunctional probes for food, medical and environmental applications are listed for future research. To improve the development of rapid detection methods, trends and strategies in the development of multifunctional fluorescent probes are also discussed. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) play a crucial role in tertiary sectors due to their eco-friendliness and sustainability when powered by clean energy. Integrating EV charging stations with renewable energy systems is essential to alleviate energy issues and grid pressure. Exploring this integration's feasibility is imperative for sustainable transportation. This study aims to provide a clear approach and methodology for examining the potential of integrating renewable energy technologies with EV charging stations at the district level. Additionally, the study investigates the energy, economic, and environmental benefits of an integrated system comprising photovoltaic/wind turbines (PV/WTs) connected to the electricity grid to meet the energy demand of a tertiary district consisting of five hotels in Egypt. Through the development of a simulation model, the paper verifies whether the proposed energy system can meet the district's energy demand. In addition, the simulation model has been employed to conduct a sensitivity analysis for investigating the impact of different charging rates on economic feasibility. The results indicate that a hybrid renewable energy system (HRES) integrated with an EV charging station can effectively relieve pressure on the electricity grid and provide electricity at competitive prices compared to the national grid. Moreover, the proposed energy system significantly reduces environmental emissions by up to 510 tons of CO2 per year and has the potential to decrease fossil fuel usage by 248 tons per year. Sensitivity analysis highlights the significant impact of charging prices on project profitability. [ABSTRACT FROM AUTHOR]

The goal of this work is to investigate the influence of SiO2 nanoparticles having different particle sizes (15 nm, 22 nm, and 75 nm) added to the traditional diesel fuel in a single-cylinder, four-stroke, direct injection, water-cooled, CI engine in terms of thermodynamic, environmental, sustainability, and economic perspectives. In the test engine, experiments were carried out at a constant speed (1500 rpm) and four ranging loads (25%, 50%, 75%, and 100%). On this basis, thermal efficiency and heat losses were determined by energy analysis. In the exergy analysis, fuel exergy, exergy transferred to the cooling water, exhaust exergy, exergy destroyed, and exergy efficiency were taken into consideration. The cost of the power taken from the crankshaft and the cost of exergy losses were found by exergoeconomic analysis. Besides that, the usability of the test fuels in the diesel engine was displayed by calculating the sustainability parameters. The addition of SiO2 nanoparticles of different sizes to the fuel blends did not cause a noticeable decrease in thermal efficiency. At 100% engine load, the thermal efficiency of D100, DSi-22, and DSi-75 fuels is 25.724%, 25.640%, and 25.325%, respectively. As the size of SiO2 nanoparticles added to fuel blends increases, the decrease in exergy efficiency becomes more noticeable. At 100% engine load, the exergy efficiency of D100, DSi-22, and DSi-75 fuels was determined as 23.96%, 22.78%, and 22.50%, respectively. Adding SiO2 nanoparticles into fuel blends increased exergy destruction. If the engine load is 10%, the exergy destruction in D100, DSi-15, DSi-22, and DSi-75 fuels is 13.649 kW, 14.678 kW, 14.75 kW, and 15.043 kW, respectively. The addition of SiO2 nanoparticles into diesel fuel is positive in terms of sustainability analysis. The lowest sustainability indices occurred at 25% engine load and are in the range of 1.175–1.19 for D100, DSi-15, DSi-22, and DSi-75 fuels, respectively. These values meet the condition of SI > 1. The addition of SiO2 in fuel blends increases fuel consumption, CO2 emissions, O2 emissions, fuel energy, fuel exergy, exhaust exergy, the exergy of thermal losses, and exergy destruction and reduces CO emissions, thermal efficiency, and exergetic efficiency. In addition, as the size of SiO2 used in fuel blends increases, fuel consumption, CO2 emissions, fuel energy, and fuel exergy increase. On the other hand, CO emission, thermal efficiency, and exergy efficiency decrease. [ABSTRACT FROM AUTHOR]

Matrix effects are a recent remarkable feature in quantitative LC-MS/MS analysis. In this work, the matrix effects of a multiclass mixture of 46 analytes - pesticides, pharmaceuticals and perfluoroalkylsubstances in different types of natural groundwater were studied. Groundwater samples were spiked with different standards from different chemical groups and determined by direct injection and liquid chromatography coupled to tandem mass spectrometry. Matrix effects were assessed by matrix factors calculated using the slope ratio technique. Groundwater samples were sampled in different boreholes in several places in Slovakia. The relationship with the various detected inorganic parameters was investigated and discussed. Most of the studied analytes showed negative matrix effects. Some analytes showed weak negative or positive matrix effects. The results show that average matrix factors obtained from different sampling sites are not a reliable tool and matrix effects need to be monitored depending on the sampling location. Only weak or no correlation of the matrix factors with the determined inorganic parameters was found. Geochemical composition of boreholes samples was determined and the differences in the macrochemical composition of the samples was evaluated. Model samples of ultrapure water enriched with NaCl, Na2CO3 and NaNO3 at various concentration levels were tested and the matrix effects were not observed. Other content of sample than cations Na+ were responsible for the matrix effects. It was found that the most affected compounds are sulfamethoxazole, sulfadiazine, metamitron, chloridazon and also caffeine. The results show that the detailed study is suitable as a tool for a deeper understanding of matrix effects in different types of groundwater. The proper ground water sample must be selected for reliable results of quantitative analysis. [ABSTRACT FROM AUTHOR]

Abstract The air quality index (AQI) is a commonly employed metric for evaluating air quality across diverse locations and temporal spans. Similar to other environmental datasets, AQI data can exhibit outliers data points markedly divergent from the norm, signifying instances of exceptionally favorable or adverse air quality. This becomes crucial in identifying and comprehending severe pollution episodes with far‐reaching environmental and public health implications. This study utilizes air quality data from January 1, 2014, to January 31, 2021, collected at daily intervals in Shanghai City, China, as the experimental dataset. The dataset includes daily AQI measurements, along with six pollutant concentrations: particulate matter (PM2.5 and PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO). Each pollutant's concentration is measured in micrograms per cubic meter (μg/m 3). The dataset is then preprocessed by cleaning and normalizing it before using K‐means clustering to discover different patterns. A stacked ensemble machine learning model that incorporates K‐means clustering, random forest (RF) and gradient boosting classifier (GBC) is developed and compared to decision tree, support vector machine, K‐nearest neighbor and Naive Bayes algorithms to evaluate its performance in identifying outliers using accuracy, precision, recall, and F1‐score. The stacked model outperformed all other established models based on the accuracy, precision, recall, and F1‐score of 0.99, 0.99, 0.97, and 0.99, respectively.

Jet impingement cooling enhances photovoltaic (PV) system efficiency by using high-speed fluid jets to reduce panel temperatures, improving performance and longevity. The effectiveness depends on factors like fluid flow rate, nozzle placement, and distance from the panel. While it boosts energy output, it may increase energy use for fluid circulation and add complexity to the system. This research explores a groundbreaking approach to enhancing the efficiency of bifacial photovoltaic thermal (BPVT) systems by integrating jet impingement technology. A novel design featuring a jet plate reflector is introduced, offering the dual benefit of cooling the PV panels while simultaneously reflecting light to optimize energy capture. The study comprehensively analyses the system’s performance, including energy output and a detailed techno-economic and environmental-economic evaluation. The modelling in this study was validated and reasonably consistent with experimental results. The system's output air temperature and thermal efficiency are 302.07–318.75 K and 33.83–62.28 %, respectively. The temperature and electrical efficiency range for PV systems are 304.39–339.54 K and 9.39–11.22 %. Reduced mass flow rate and increased solar irradiation are the most economically advantageous operating parameters for the proposed system, resulting in lower annual pumping costs and more significant annual energy gains for the system. CBR variations range from 0.1363 to 9.3445, with an average of 2. Additionally, by using BPVT with jet impingement to generate electricity rather than fossil fuels, it is possible to reduce annual carbon dioxide emissions by approximately 1.61 tons and save RM93.51 annually. In general, the proposed method should be used to minimize environmental pollution.

This work showcases a novel application of biochar for analytical sample treatment. The carbonaceous material, obtained by pyrolysis of orange peel waste (550°C) without any post-synthesis treatment or functionalization, was thoroughly characterized and easily immobilized on the inner wall of sampling tubes in order to perform a sort of “in-vial” solid-phase extraction (SPE). The as-obtained device was tested for the extraction of seven sexual steroids, as probe water pollutants, from tap, lake, river water and wastewater treatment plant effluent samples spiked with 0.2-5 µg L−1 of each compound. The sorption kinetics profiles showed quantitative uptake from the sample (25 mL) in 20 min contact time, followed by complete elution in pure ethanol (2 mL, 15 min), thanks to the proper balance between sorption affinity and ease of elution. Under the selected conditions, recovery was in the range 60-123 %, with good inter-day precision (RSD 10-18 %, n=3). As evidence of the excellent reproducibility, an overall RSD below 15 % was observed from inter-day inter-batch recovery tests on three individually prepared sampling tubes. The procedure, carried out on a roller mixer, allows 10 samples to be extracted simultaneously, improving the sample throughput. Moreover, reusability tests showed that the same device maintains its efficiency for 10 consecutive sorption/desorption cycles. The greenness assessment, carried out by two dedicated software, further supported the sustainability of this biochar-based sample preparation as an alternative SPE.

As the potential risks on human and aquatic animal exposed to the glucocorticoids in environment, it is essential to detect anti-epidemic pharmaceutical in real water samples. In this work, a core-shell shape, magnetic suspension particle sorbents of Fe3O4@oleic acid@polydopamine (Fe3O4@OA@PDA) were synthesized for magnetic dispersive solid phase microextraction (MDSPME), which possessed considerable dispersibility in water samples and extracted three glucocorticoids through hydrogen bonding with high detection sensitivity. The adsorption process of MDSPME was investigated by thermodynamic and kinetic theory, which demonstrated that the kinetic processes of adsorption were in accordance with the quasi second order kinetic model, and the adsorption isotherm was in accordance with the Freundich model. Combined with high performance liquid chromatography-Ultraviolet spectrophotometer detector, the proposed method had a linear range of 5–200 μg/L with an ultra-low detection limit down to 0.5–1.1 μg/L. The Green Analytical Greenness Metric (AGREE) software was employed to evaluate the greenness of the analytical method. This work presented an effective strategy for creating ultrasensitive and cost-effective probe for detection in anti-epidemic drugs.

Global warming and increased air-conditioning demand drive up energy use. A passive cooling system for the building's roofs is one solution to this problem. The current study intends to provide a unique evaporative cooling concept for cooling building roofs that use significantly less water than prior approaches. To reduce room temperature, saturated-activated alumina beds with 2, 4, and 6 cm thicknesses were put over the roof. Pure and 35 PPT saline water were utilised to evaluate system performance and sustainability. The device successfully reduced rooftop temperatures by 84 % and 70.9 % after 24 h of testing (6 h during daytime and 18 h at night) under heat loads of 800 and 1000 W/m2. The findings show that salt water is a feasible alternative to freshwater that does not sacrifice cooling efficiency. From an environmental standpoint, compared to a bare roof, a 6-cm layer of saturated activated alumina tables can reduce annual carbon dioxide emissions by 71.3 tCO2/m2 and 92 tCO2/m2 for roof areas subjected to daily solar radiation of 6000 W h/day and 4800 W h/day, respectively.

Salicylic acid (SA) is widely used in food storage, preservatives, additives, healthcare, and the pharmaceutical industry. However, various poisoning symptoms are frequently reported upon ingestion of a large amount of SA. Therefore, discovering new tools for sensing SA with fast, simple, and portable performance is imperative. Herein, five rhodamine-based fluorescent sensors were constructed, and investigated their SA detection profiles. Probe 1 was excellent selective with a rapid response, highly sensitive (LOD = 2.5 μM), good interference resistance, and unaided eye recognition. The spray experiment and paper-based test strips indicating that probe 1 enables to the on-site and quantitatively detect SA on actual food surfaces by using a smartphone identifying the RGB values. The sensing performance was validated in soil samples, water, and various agricultural food samples. Overall, the constructed SA sensor can function as a promising, convenient, and affordable tool for point-of-care detection of SA in diversiform environmental samples.

We used a microfluidic paper-based analytical device (μPAD) to investigate the influence that zinc reduction exerts on the determination of nitrite and nitrate ions in natural water samples. The μPAD consists of layered channels for the reduction of nitrate to nitrite with zinc powder and the subsequent detection of nitrite with Griess reagent. The amount of zinc, number of layers, and reaction time for the reduction were optimized to obtain an intense signal for nitrate. Initially, the sensitivity to nitrate corresponded to 55% that of nitrite, which implied an incomplete reduction. We found, however, that zinc decreased the sensitivity to nitrite in both the μPAD and spectrophotometry. The sensitivity to nitrite was decreased by 48% in spectrophotometry and 68% in the μPAD following the reaction with zinc. One of the reasons for the decreased sensitivity is attributed to the production of ammonia, as we elucidated that both nitrite and nitrate produced ammonia via the reaction with zinc. The results suggest that the total concentration of nitrite and nitrate must be corrected by constructing a calibration curve for nitrite with zinc, in addition to developing curves for nitrate with zinc and for nitrite without zinc. Using these calibration curves, the absorbance at different concentration ratios of nitrite and nitrate ions could be reproduced via calculation using the calibration curves with zinc for nitrite and nitrate. Eventually, the developed μPAD was applied to the determination of nitrite and nitrate ions in natural water samples, and the results were compared with those using a conventional spectrophotometric method. The results of the μPAD are in good agreement with those of conventional spectrophotometry, which suggests that the μPAD is reliable for the measurement of nitrite and nitrate ions in natural water samples.

The research aimed to diagnose the reality of the scientific research system and its funding sources in Egyptian universities, identify the challenges they face, and propose a set of planning indicators for research chairs as alternative sources of sustainable funding for scientific research in Egyptian universities. The descriptive approach was used due to its suitability to the nature of the research area as well as one of the main methods of strategic planning, which is the environmental analysis method (SWOT analysis). The most important results of the research were the need for Egyptian universities to find alternative sources to finance their scientific research. As a result of weak and often nonexistent funding. Research chairs are considered one of the important methods that have been adopted to contribute to financing scientific research and have spread in many global and regional universities, in addition to developing a vision for planning indicators related to research chairs that can help decisionmakers and strategic goal-makers in universities target alternative sources of sustainable funding for research. So, it has a major role in improving the scientific research system, possessing a competitive advantage that makes it a device for change and progression of society within global competitiveness indicators, and providing a stimulating environment for the scientific leadership that Egypt adopts. [ABSTRACT FROM AUTHOR]