The current study’s objective is to use Manila Tamarind Shell Copper Nanoparticles (MTSCuNPs as adsorbents in a batch process to remove Methylene Blue dye from their wastewater. Contact time, solution pH, initial Methylene blue dye concentration, adsorbent dosage, and temperature were the factors that were examined in batch research. The maximum removal efficiency was predicted to be 96.37% at a temperature of 318 K, a solution pH of 7, an initial dye concentration of 10 mg.L-1, and an adsorbent dosage of 0.5 g.L-1. The Freundlich isotherm model best describes Methylene Blue removal adsorption data at 303 K, with a correlation coefficient of 0.9975, while the Temkin and Langmuir isotherms have correlation coefficients of 0.8901 and 0.8656, respectively. The kinetics study analyzed adsorption data using pseudo-first order, pseudo-second order, Elovich, and intraparticle diffusion models. Pseudo-second-order kinetics for methylene blue showed close applicability, confirming chemisorption as the rate-limiting step. The pseudo-second-order kinetics model best describes Methylene Blue removal adsorption data at 10 mg.L-1 with a correction coefficient of 0.9988, while the pseudo-first-order, Elovich model, and intra-particle diffusion model have correction coefficients of 0.9876, 0.9704, and 0.9174, respectively. The thermodynamic study found that the adsorption process is spontaneous and physisorption is dominant, with Gibbs free energy values ranging from -20 to 0 kJ.moL-1. Endothermic adsorption and an activated complex formation are associated with the process. In this study, determine the ΔH0 , ΔS0 , and ΔG0 at 303K with values of 25.766 kJ.moL-1, 114.12 J.moL-1, and -8.8003, respectively.

Plastic waste has become a complex issue in the Boyolali district, where much of it is either burned by the community or contributes to environmental pollution. Pyrolysis technology offers a solution by converting plastic waste into renewable and sustainable fuel. This research aims to evaluate the management system of plastic waste and its alternative utilization through pyrolysis technology. The research method for evaluating plastic waste is conducted using a descriptive qualitative approach, while the pyrolysis study is carried out experimentally. Renewable energy-based technologies, such as pyrolysis, are needed to convert plastic waste into high-calorific fuel. The lower heating value (LHV) of Pyrolysis Fuel Oil (PFO) is 9,240 Kcal/kg, with a density of 0.795, giving it high energy potential, making it a suitable candidate for renewable fuel. The pyrolysis process lasts for 7 hours per batch, resulting in a total monthly output of 1,625 L, which consists of 1,125 L of diesel, 250 L of kerosene, and 250 L of gasoline. To operate this process, four workers are required, with a monthly electricity consumption of 350 kWh. Pyrolysis technology offers a sustainable solution to reduce waste and decrease dependence on fossil fuels.

The study offers a comprehensive analysis of stormwater management durability in Chandigarh, India, primarily focusing on employing the Internet of Things (IoT). Eleven key stormwater management indices were examined, and their data sources and methodologies were detailed. The investigation independently evaluates the urban areas’ durability, emphasizing the singular indicators’ worth, and their consequences. Moreover, a consolidated comprehensive system durability indicator was computed utilizing the Analytical Hierarchy Method (AHM), offering a holistic viewpoint on stormwater administration. Chandigarh’s stormwater management uses a 100% weighted approach, this 100% weighted approach allows stakeholders to make informed decisions about stormwater management sustainability, ensuring the city’s water quality and effectiveness in mitigating flooding. Their findings showed a moderate overall sustainability index of 0.761, indicating challenges like waterlogging and limited drainage coverage. The outcomes provide perspectives into Chandigarh’s tenacity and durability in metropolitan water administration over a decade, highlighting the ever-changing character of urban growth and the requirement for flexible resolutions.

Palladium Nanoparticles (PdNPs) are considered significant catalytic agents, along with a wide range of applications, mainly hydrogen storage and sensing, biomedical imaging, and remediation strategies. Extensive studies are being carried out on the formation of PdNPs (PdNPs) worldwide, showing the predominance of the chemical approach among various technologies for the synthesis. The traditional chemical method employed in the formulation of PdNPs contains certain limitations that have been overcome by the use of the alternative biological method, as they are meek, low-cost, and benign to ecosystems. Therefore, the present review provides an overview of the modernized techniques involved in the biological approach for PdNPs formation by utilizing various natural origins, for example, plants as well as microbes, for their enhanced stability and applications in fields of the environment. Various mechanisms and parameters involved, along with approaches utilized for the characterization of bioPdNPs, are described, with an insight being delivered on the utility of biologically synthesized palladium nanoparticles. Recovery of PdNPs to achieve a circular economy is also being focused. In addition, the future prospectus on palladium nanoparticle research is also summarized.

The fecundity of fish can be utilized to predict the fish catch in the future becoming to be the most vulnerable to the negative impact of global warming. This study aimed to determine the effect of heat index on the growth and fecundity of D. macrosoma “Budloy” from the selected locations of marine waters in the Caraga region. The study was conducted at Buenavista, Agusan del Norte, Placer Surigao del Norte, and Tandag Surigao del Sur, where Shortfin scad is common. This study used Stratification random sampling to collect the samples. To calculate the present heat index of the sampling areas, present temperature, and humidity during the capture of fish samples were determined. To determine the fecundity, six parameters of D. macrosoma were calculated: length, body weight, total weight of ovary, weight of ovary samples, number of eggs, and maturity stage of D. macrosoma ovaries. In terms of the correlational analysis between heat index and length of D. macrosoma, results showed that there is a moderate positive correlation, with r = .55, p = .000, for heat index and weight, results were found to have a strong positive correlation, with r = .71, p = .000. Based on the findings on the correlation between heat index and fecundity, with r =.007, p = .959, results indicate that although there is a positive correlation between heat index and growth, there is no significant relationship between heat index and fecundity. Based on the computed values of the heat index, growth, and fecundity of D. macrosoma samples in all sites, it is concluded that Buenavista waters have the highest numerical value of the reproductive potential of D. macrosoma as the basis for predicting the fish catch in the future.

Phosphorus (P) is a vital macronutrient for plant growth. The bioavailability of P in soils is limited due to the insolubility of P. This study aimed to isolate and characterize Phosphate Solubilizing Bacteria (PSB) strains and determine their efficiency of phosphate solubilization and their effect on plant growth. pH, Electrical Conductivity (EC), Total Organic Carbon (TOC), organic nitrogen, and available phosphorus in soil were analyzed. Pikovskaya’s Agar (PKV) was used to isolate PSB strains and identified through biochemical tests and 16S rRNA gene sequencing. The solubilization efficiency of the isolates was assessed in PVK broth supplemented with 0.5% tricalcium phosphate (TCP), and their effect on plant growth was evaluated in pot experiments. Mung bean (Vigna radiata) was selected as the experimental plant. Five Bacillus strains were identified, and the genotypic test was confirmed as Bacillus pumilus strain PRE14, Bacillus altitudinis 41KF2b, Bacillus cereus ATCC 14579, Bacillus siamensis strain KCTC 13613, and Bacillus subtilis strain NCIB 3610. All isolated strains were positive for the catalase test, gram staining, motility test, starch hydrolysis test, and spore staining test. The citrate utilization test and the spot test for indole production were negative for isolated PSB strains. B. siamensis strain KCTC 13613 showed the highest phosphate solubilizing efficiency with the maximum phosphorus concentration of 9.17±0.07 mg/kg recorded after 6 days of incubation. Pot experiments revealed that potting media inoculated with B. siamensis strain KCTC 13613 exhibited the highest shoot length (mean increase of 16.77 ± 0.74 cm), root length (mean increase of 10.99 ± 0.41 cm), and wet weight (mean increase of 0.60 ± 0.08 g) compared to other isolated PSB strains. All isolated Bacillus spp. Strains demonstrated a significant difference (n=9, P < 0.05) in measured growth parameters compared to plants grown under the control potting media. Soil pH increased post-germination, with the lowest pH recorded at 7.40±0.09 for media inoculated with B. siamensis strain KCTC 13613, indicating organic acid production. These findings reveal the potential of Bacillus spp. as bio-inoculants to promote sustainable agriculture by enhancing phosphorus availability and plant growth.

Advanced applications of artificial intelligence and geographic information systems (GIS) techniques are used to monitor plant growth across their vegetation seasons using morphological parameters. This research presents novel measurements to determine the concentrations of elements such as carbon (C), nitrogen (N), hydrogen (H), lead (Pb), and cadmium (Cd) in the mushroom “Agaricus bisporus” and in the surrounding soil and air. These data are spatially analyzed to contribute to long-term predictions of pollution index and future ecosystem risks. Pollution and element accumulation in the mushroom, soil, and surrounding air were monitored using data accompanied by a geographic map. Pollution was assessed by transforming the system and adopting a methodology that integrates traditional methods with artificial intelligence, aiming to address the challenges with greater efficiency and accuracy. Input parameters were used to develop models using artificial intelligence and statistical methods to detect metal accumulation, and monitor carbon, hydrogen, nitrogen, and seasonal changes. The response of plants to heavy metals (lead and cadmium) in soil and air and their impact on their growth and development, were analyzed. The techniques showed a significant reduction in the error rate when using fungi as an indicator to predict dietary heavy metal concentrations, as the accuracy of artificial intelligence was remarkable in estimating the concentration of elements and their transfer from soil to plant. The integration of artificial intelligence, machine learning, and GIS technologies enhances environmental management, as it provides the ability to monitor, predict, and provide sustainable assessments. This study provides insights to improve plant growth, reduce pollution, and support long-term food security at a lower cost and with greater accuracy in assessing environmental impacts.

Wastewater from several businesses that produce paints, steel, tannery products, dyes, and chrome-plated items contains hexavalent chromium [Cr(VI)]. The main contributing factor to pollution concentrations in water bodies is the wastewater that tannery businesses dump, which includes organic pollutants and heavy metals, particularly Cr(VI). The harmful consequences of Cr(VI) on humans include eczema, allergies, ulceration, respiratory tract problems, lung cancer, as well as genotoxic and mutagenic effects. Using bacteria to biotransform hexavalent chromium to trivalent chromium [(Cr(III)] is a practical strategy with proven viability in bioremediation. Following their isolation from the tannery industry’s raw effluent, bacterial strains were investigated biochemically and molecularly. Based on this study, it was concluded that the microorganisms resistant to Cr(VI) were Bacillus albus and Bacillus australimaris. In a two-chambered microbial fuel cell reactor, the isolated Cr(VI) resistant bacteria will be employed as electrogenic bacteria with SPEEK (Sulphonated polyether ether ketone) as PEM (proton exchange membrane), which can synergistically aid in the reduction of hexavalent chromium and green energy generation.

Efficient management of municipal solid waste is essential to fostering sustainable urban growth, especially in rapidly urbanizing countries such as India. This study conducts a comparative analysis of waste collection patterns in Mysuru and Tiruchirappalli, two major cities in India. The study specifically examines temporal shifts and seasonal variations. A study of daily waste collection data over six years indicates apparent differences among the cities. Mysuru has a greater average daily waste collection of 481.82 tons compared to Tiruchirappalli’s 445.68 tons. A two-sample t-test assuming unequal variances indicates that this difference is statistically significant with a p-value of 0.0423. However, a more thorough analysis of seasonal patterns uncovers significant deviations. Mysuru exhibits elevated waste generation during the dry summer and wet winter seasons, whereas Tiruchirappalli encounters a surge in waste generation during the wet summer and wet winter periods. The seasonal variations highlight the impact of climate-related factors and consumption habits on waste generation. This study offers valuable insights into the intricacies of urban waste management in India, highlighting the importance of customized strategies that consider both temporal and seasonal fluctuations to improve the sustainability and resilience of waste management systems in rapidly developing urban areas.

The study investigates the environmental impact of oil pollution in the vicinity of the Dora Refinery, with a particular focus on its effects on local flora. The research utilizes selected plant species such as Salvia rosmarinus, Eucalyptus globulus, Ficus nitida, Conocarpus lancifolius, Nerium, Eucalyptus camaldulensis and Dodonaea viscosa as biological indicators to assess the extent of contamination and the plants’ adaptive responses to polluted conditions. Oil pollution is identified as a significant environmental issue in the Dora Refinery area, contributing to severe soil degradation and posing challenges to plant survival. The primary objective of this study is to evaluate the physiological and biochemical responses of these plant species to oil-contaminated soils, including growth performance, stress response mechanisms, and their potential role in environmental monitoring and land reclamation. The methodology involved selecting both polluted and non-polluted sites in proximity to the refinery. Soil samples were collected from these locations and used to cultivate the target plant species under controlled conditions. Growth rates were recorded, and several biomarkers associated with oil pollution exposure were analyzed. These included measurements of soil hydrocarbon content, chlorophyll concentration, antioxidant enzyme activities, and the accumulation of heavy metals and hydrocarbon pollutants in plant tissues. Results revealed that plants grown in polluted soils exhibited significantly reduced growth rates compared to those in uncontaminated environments. Notably, Salvia rosmarinus and Dodonaea viscosa demonstrated substantial accumulation of hydrocarbon pollutants, indicating their high sensitivity to contamination. In contrast, Eucalyptus globulus and Conocarpus lancifolius showed greater resilience, maintaining relatively stable growth and physiological parameters under stress. Polluted plants also exhibited clear signs of environmental stress, including decreased chlorophyll content and elevated antioxidant enzyme activity, reflecting their biochemical response to oxidative stress induced by pollutants. These findings suggest that the studied species vary in their tolerance to oil pollution, making them valuable bioindicators for environmental assessment. In conclusion, the physiological traits of these plant species significantly influence their susceptibility to oil pollutants. Their differential responses provide critical insights for environmental monitoring programs and offer promising avenues for the development of phytoremediation and land management strategies in oil-contaminated regions.