The increased use of metallic nanoparticles has led to concern for environmental contamination and disruption in water quality. Therefore, effective screening of metallic nanoparticles is important for detecting metallic nanoparticles in aquatic environments. Biosensors offer several advantages, including high sensitivity to pollutants, short response time, energy efficiency, and low waste generation. In this study, a whole-cell biosensor was developed using microalga Chlorella vulgaris as a recognition element, and its fluorescence response was used as a measuring parameter for detecting the presence of titanium dioxide (TiO2) and silver (Ag) nanoparticles in water. The responses of C. vulgaris at the lag, exponential, and stationary phases to different concentrations of TiO2 and Ag nanoparticles were studied. The results showed that in TiO2 and Ag nanoparticles exposures, the highest fluorescence change (50-150%) was observed at the lag phase, whereas the lowest fluorescence change (40-75%) was observed at the stationary phase. A significant fluorescence change was observed in 15 min. The immobilized C. vulgaris under TiO2 and Ag nanoparticles exposures showed 30-180% higher fluorescence change than the negative control, indicating the potential of C. vulgaris as a biosensor for rapid detection of TiO2 and Ag nanoparticles in water. The mathematical modeling of the responses of C. vulgaris to TiO2 and Ag nanoparticles at 15 min of exposure with high R2 indicated that this biosensor is sensitive to the concentration tested (0.010–10.000 mg.L-1). Taken together, these results reveal that, for the first time, it is possible to detect TiO2 and Ag nanoparticles in water within a very short time using a microalgae-based biosensor. Moreover, no genetic engineering requirement makes this biosensor simple, economical, and free from the restriction on genetically modified microorganisms for environmental applications.

Chromium contamination in water bodies poses severe risks to both the environment and human health. This research introduces an innovative solution to this challenge by creating a vapor-activated carbosorbent from biodegradable household waste. The efficacy of this adsorbent in removing total chromium through batch methods from aqueous solutions was investigated. Surface analysis using scanning electron microscopy (SEM) exhibited a porous structure, while Fourier-transform infrared spectroscopy (FTIR) identified distinct functional groups on the surface. The point of zero charge (PZC), determined at 6.95, revealed the adsorbent’s surface chemistry. Impressively, the synthesized carbosorbent exhibited significant adsorption capacities of 23.08 mg.g-1 for Cr(III) and 24.84 mg.g-1 for Cr(VI) under optimal conditions. The Langmuir isotherm model illustrated a monolayer adsorption mechanism aligned with the pseudo-second-order kinetic model, confirming chemisorption. Thermodynamic analysis disclosed favorable and spontaneous chromium adsorption. Negative ΔG° values affirmed the spontaneity, while the exothermic nature of the process was signified by the positive ΔH° value, indicating heat release. Increased randomness at the solid-liquid interface, indicated by the positive ΔS° value, underscored the enhanced affinity between the adsorbent and adsorbate. This study exemplifies the potential of the vapor-activated carbosorbent as an efficient and sustainable remedy for chromium-contaminated water bodies.

This article is oriented to the degradation of nickel in an ionic state at laboratory level from synthetic water made with nickel sulfate, using the electrocoagulation process with aluminum cathodes and modifying this process by the addition of the Fenton reagent, which results from the combination of hydrogen peroxide (H2O2) and ferrous sulfate (FeSO4) being this reagent a catalyst and oxo-coagulant agent, The efficiency of this reagent will be compared with the typical treatment with aluminum sulfate, which is a typical process based on ion exchange/coagulation at the same percentage concentrations as the Fenton reagent. For this purpose, the optimum conditions of the advanced electrocoagulation process were determined, which consisted of determining the concentrations of Fenton’s reagent at concentrations of 150 ppm, 300 ppm, and 450 ppm, in addition to the operating variables such as pH of 8 and 10, voltage of 17.5 V and 19 V and their reaction time, which were compared with aluminum sulfate at 300 ppm, 600 ppm, and 900 ppm. The results obtained with respect to the typical treatment were 0% nickel degradation. However, with the advanced oxidation treatment, an average reduction of 97.5% was found at the conditions of 19 V, pH 10, and Fenton 150 ppm in a time of 30 min.

With the rapid advancement of Remote Sensing Technology, monitoring the agricultural land has become a facile task. To surveil the growth of paddy crops and provide detailed information regarding monitoring soil, drought, crop type, crop growth, crop health, crop yield, irrigation, and fertilizers, different types of remote sensing satellites are used like Landsat 8, Sentinel 2, and MODIS satellite. The main aim of Landsat 8, Sentinel 2 and MODIS satellites is to monitor the land and vegetation area and to provide data regarding agricultural activities. Each of these satellites possesses a different spectral band, resolution, and revisit period. By using the remote sensing spectral indices, different types of vegetation indices are calculated. This survey paper provides comprehensive about Remote Sensing and the major parameters that influence for growth of paddy crops, like soil and water, and the future scope of agriculture and its demand in research is discussed.

The consumption of contaminated fruits and vegetables is the prime cause of outbreaks of various human diseases. Although fruits and vegetables have high nutritional value, today because of their contamination during handling while performing harvesting and post-harvesting techniques, they are harmful to human health. Most of them are eaten raw without being washed or without providing any treatment. Vegetables and fruits, being rich nutritional sources, can act as carriers or vectors of pathogenic microorganisms, which can create a serious issue for the health of the community targeted. This entire research is based on an emerging field of Forensic Microbiology. Various types of microbial agents can be utilized as bioweapons to conduct the bio crime or bioterrorism through food and water. This research also represents that the identification of microbial agents is very much necessary for the welfare of humans. Identification and isolation of different pathogenic bacteria from raw vegetables and fruits can also shed some light on the terms of the necessity of Forensic Microbiology.

This study explores the electrochemical reduction of carbon dioxide (CO2) using tin (Sn) and zinc (Zn) catalyst-loaded gas diffusion electrodes (GDEs). The research explores the influence of electrolytic potential and catalyst loading on the efficiency of CO2 conversion to valuable chemicals, specifically formic acid and carbon monoxide. The best Sn loading for Sn-loaded GDEs, according to the morphological study, is 7 mg.cm-2, which results in higher current density (0.33 mA.cm-2) and current efficiency (36%). An electrolytic potential of -1.3 V Vs. Ag/AgCl is identified as optimal for Sn GDEs, offering a balance between high current efficiency (35%) and controlled current density. For Zn-loaded GDEs, an optimal loading of 5 mg.cm²- yields the highest current efficiency of 19.4% and a peak current density of 0.28 mA.cm²- at an electrolytic potential of -1.55 V Vs. Ag/AgCl, in addition to highlighting the crucial role that catalyst loading and electrolytic potential play in enhancing CO2 reduction efficiency, this research offers insightful information for environmentally friendly CO2 conversion technology.

Sustainable development is a global policy that requires the collective effort of the actors present in each territory. In this sense, an energy renewal intervention model is presented at the Juan XXIII Educational Institution in the city of Monteria, Córdoba, Colombia, which results from alliances between international, national, and regional actors, becoming a reference that could serve as a basis. To be replicated in other institutions with characteristics similar to those described in this case. The model generally describes the entire process carried out in the intervention and focuses on the benefits generated for the educational community. Among the main results, the increase in thermal, lighting, and acoustic comfort of the educational community stands out, according to a survey and semi-structured interviews carried out. A fact that could be attributed to the perception of increased comfort in the community is the increase in the student population in 2022, going from 1,478 in 2019 to 1,909 in 2022, with a growth of approximately 29%. Energy renovation also resulted in the improvement of the indoor climate of the classrooms (from 35°C to 27°C), the improvement in the physical infrastructure of the institution, the integration of photovoltaic solar energy, and the subsequent reduction of energy cost.

The rapid consumption of fossil fuels has led to calls to switch from non-renewable to renewable energy sources. Microbial fuel cells are a promising technology that simultaneously treats wastewater and produces power. This study used the Taguchi Experimental method to optimize anode thickness and pH to obtain the maximum power density of an air-cathode microbial fuel cell (ACMFC). The graphene-sponge (G-S) anode thickness and chamber pH were selected as operating parameters, with their corresponding levels. The L9 orthogonal array was chosen for the experimental design. According to the Taguchi Method, the optimum G-S anode thickness and chamber pH were determined to be 1.0 cm and 8.0, respectively. A confirmatory run was performed under these optimum conditions, and the maximum power density observed was 707.75 mW·m−3. Analysis of variance (ANOVA) was conducted to identify the percentage contributions of the operating parameters to the process, which were found to be 30.66% for pH and 69.34% for anode thickness.

This detailed study assessed heavy metal contamination of sediments/soil near central India’s largest copper mining area using 38 sampling sites within 10 km of the mine using atomic absorption spectroscopy. This study utilized multivariate pattern recognition methods, namely hierarchical clustering analysis (HCA) and principal component analysis (PCA), for source identification. Twelve parameters, i.e., copper (Cu), manganese (Mn), cobalt (Co), zinc (Zn), nickel (Ni), lead (Pb), organic matter (OM), cation exchange capacity (CEC), soil pH, distance (D), and elevation (E) were analyzed. The hierarchical cluster analysis (HCA) was used to analyze the sample sites with similar metal contamination and principal component analysis (PCA) was used to analyze the relationship between the parameters as well as to identify sources of heavy metal pollution. Three major pollution hotspots were detected by AHC and were classified as unpolluted/low pollution sites (UPS: mean concentration factor of 1.35 for Cu), highly polluted sites (HPS: mean concentration factor of 22 for Cu), and extremely polluted sites (EPS: mean concentration factor of 74 for Cu). PCA revealed three hidden factors/components, namely PC1 (explaining 38% of the variability), PC2 (18% of the variability), and PC3 (14% of the variability). Metals showed strong positive loading in PC1, explaining the highest variability. The mean content of Cu in soil/sediment samples was 502.526 mg/kg. The mean copper content was 10 times higher than the natural crustal value of 45mg/kg, indicating severe pollution in several sites around the study area. Mapping of copper contamination was conducted to reveal the spatial distribution of copper contamination using QGIS. This study exposes the heavy metal contamination level in surface sediments/soil and the effectiveness of pattern recognition techniques for the assessment of multivariate datasets in discerning spatial disparities and identifying the contamination causes.

Mung bean is recognized for its abundant high-quality protein content. For human consumption, it is a high-quality protein source and also serves various purposes crops, its arvested residue is used for green manuring and also used for fodder purposes. The research aimed to assess the impact of foliar micronutrient application on primed mung bean (Vigna radiata). The experimental procedures were executed in the sandy loam soil prevalent in the central plain region of Punjab. The investigation was conducted during the Zaid season 2022, focusing on the (SML-1827) mung bean variety. Specifically, the research assessed the impact of foliar micronutrient applications involving zinc and boron at 15 and 45 days after sowing (DAS) on primed mung bean growth characteristics. The experimental design employed a Randomized Block Design, incorporating 11 distinct treatment combinations, each replicated thrice. The investigation revealed that foliar micronutrient treatment on primed mung bean substantially influenced growth and yield parameters. Growth indicators for mung bean exhibited a positive trend when zinc and boron were jointly applied to primed seeds with gibberellic acid, followed by a decline in the control group, which experienced typical growth conditions devoid of growth regulators and micronutrients. Specifically, the highest recorded plant height was 70.1 cm in the T9 (GA(50 mg.L-1) + ZnSO4 (0.5%) + B (1%)) treatment, while the lowest height was 58 cm in the T0 (control) treatment. Similarly, the most significant fresh weight was observed in T9 (GA(50 mg.L-1) + ZnSO4 (0.5%)+ B (1%)) treatments at 136.8 g, with the lowest weight recorded in T0 (control) treatments at 86.6g. the most significant grain yield was achieved in T9 112 g.m-2, followed by T10 (SA(150 mg.L-1)+ ZnSO4 (0.5%)+B (1%)) at 105.7 g.m-2. This study suggests micronutrients and growth regulators can be sustainable agricultural inputs to enhance soil health and productivity.