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Prediction on the Level of Toxicity in Fruits and Vegetables Based on PAHs Using Machine Learning

This study focuses on assessing the toxicity levels in fruits and vegetables based on the presence of polycyclic aromatic hydrocarbons (PAHs), particularly in regions affected by industrial and vehicular pollution where the particulate matter deposits on the plant surfaces. Traditional methods, including Gas Chromatography/Mass Spectrometry (GC/MS) and HighPerformance Liquid Chromatography (HPLC), are used to measure PAH levels in fruits and vegetables, which are found to be valuable but expensive and time-consuming. However, the detection of toxicity relies on either expert knowledge or experimental analysis when compared with the limitations set by EFSA (European Food Safety Authority). Therefore, in this study, artificial intelligence techniques have been employed to evaluate the toxicity levels based on 16 PAHs. The PAH concentrations in fruits and vegetables were collected from different articles corresponding to safe and unsafe datasets and then validated through statistical analysis. The validated dataset is classified using different machine learning algorithms. Based on the output from the neural network, the level of toxicity is also scaled and compared with the targeted outputs. The promising results of the classification of toxicity using artificial intelligence methods are substantiated by an experimental study and validated through statistical methods. From the results, it can be observed that the machine learning algorithm has given classification accuracy of more than 90% along with their degree of harmfulness. This research holds implications for food safety and public health, offering a novel approach to the interdisciplinary understanding of climate change by addressing the impact of environmental contaminants on the edibility of fruits and vegetables.

Staphney Texina , Sathees Kumar Nataraj , Alagammai Renganathan and Kavitha Vasantha

Agrivoltaics: Dual Use of Land for Energy and Food Sustainability

Renewable energy has been of prime importance in the present era in meeting energy demand across all sectors. To meet this demand, solar energy has become a plausible option among scientists to reduce the fossil fuel effect and find an alternative solution. The main concern about large renewable energy installations on open land, mostly used for agricultural practices, is that they can displace different land uses and instigate the feed vs. fuel controversy in the long run. The current study reviewed the installation of solar panels on farmland’s benefits and challenges. The present study also reviewed the effect of solar panels on agricultural crop microclimate, soil, water condition, and crop growth and yields. Crop production and solar PV electricity generation from the same land space have numerous benefits, such as improving land productivity, reducing irrigation, managing soil, protecting crops from adverse climatic conditions (heat, frost, rainfall, etc.), increasing PV panel efficiency, and meeting house and farm electricity needs. Fewer demerits of agrivoltaics are to be studied in the future, such as keeping a suitable crop cycle, limited crop suitability, high expenses, and a lack of technical expertise. A big change to meet future energy demand without much impact on the environment is the dual use of open land for crop production and solar energy generation. To maximize crop yield, the impact of solar panels on crop yields has not been studied for numerous crops. We found that the optimum arrangement of solar panels admits varying levels of solar radiation according to crop needs. Sustainable agriculture and efficient solar energy generation can be possible in the same field by perfecting shade design and selecting suitable crops.

Aminul Islam, Krishna Kishore Satapathy, Sushil Kumar Kothari, Biswajit Ghosh and Shankha Koley

The Study of Coastal Vulnerability in South Central Timor Regency, East Nusa Tenggara Province

The presence of anthropogenic activities in the coastal areas of the South Central Timor (SCT) Regency has weakened coastal resilience, which may exacerbate the impact of rising sea levels. One important factor that needs to be analyzed is the vulnerability assessment. This study, conducted from July to September 2024, aimed to determine the spatial distribution and variables that can influence the vulnerability in the coastal areas. The methods used were the Coastal Vulnerability Index (CVI) and the Social Vulnerability Index (SoVI), which then used Multi Criteria Analysis (MCA) to perform the standardization value. The integrated index values were then integrated into the Geographic Information System (GIS) for comprehensive spatial information. The results showed that, in general, the coastal areas of the SCT Regency were in the low (35%), medium (48%), and high (66%) risk categories. Areas of high physical vulnerability were alluvial lowland areas and those near hills. The karst hills that are characteristic of the coastal areas of the SCT regency have become a threat to the lives of coastal communities. Communities living in coastal hill areas, including the Kolbano and Oetuke coasts, and in the alluvial lowlands like the Tuafanu, Kualin, and Oni coasts, need to be the focus and priority areas for recovery efforts. This is due to the high level of vulnerability, both physically and socio-economically. Geomorphology is the primary contributor to physical vulnerability because these coastal hills and lowlands are prone to erosion and land degradation caused by waves, tides, and human activities. On the socio-economic side, land use, particularly mining activities, increases vulnerability by degrading the environment and threatening the livelihood of coastal communities. Key recovery efforts should focus on revegetation, which can help stabilize the soil, reduce erosion, and restore ecological balance while offering sustainable economic benefits to the local population.

Ludgardis Ledheng, Emanuel Maria Yosef Hano’e and Marce Sherly Kase

Evaluating Phytoremediation Approaches for the Restoration of Degraded Ecosystems in India

Plant stresses are the conditions that adversely affect the growth, development, or productivity of plants/trees and can be caused by various physical, chemical, and biological factors. On the other hand, stress brought on by heavy metal exposure significantly impairs plant development and output. These heavy metal contaminations are responsible for the harmful effects on biotic (plants and associated organisms) and the abiotic (soil, water, and air) environment. Mining operations are thought to be the main cause of heavy metal pollution in the environment if they are not adequately controlled. Phytoremediation provides an efficient, carbon-neutral, and environmentally friendly way to remove dangerous heavy metal contamination from various settings. It can efficiently treat a broad spectrum of heavy metal contaminants. Phytoremediation enhances the development and growth of plants and nourishes the environment, resulting in the ill effects of climate extremes in disturbed areas and hence mitigating the impacts of climate change. Although phytoremediation has been extensively researched for the treatment of heavy metal stress in India’s degraded ecosystems, where it is most needed, it has not yet reached economic viability. Through this article, we tried to minimize this gap by reviewing some important phytoremediation studies in India that successfully reduced the negative impacts of heavy metals in different degraded ecosystems. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) review principles were used to outline the selected studies giving a knowledge that most of the phytoremediation works in India have been performed on Shrubs (28.40%) closely followed by Tree species (26.28%) then in Herbs (17.65%), Grasses (17.25%) and Aquatic Plants (10.43%). Also, the trend has seen a spike after 2018 with most phytoremediation studies in the states of West Bengal. The studies reviewed in this article show us a pathway for implementing and managing remediation methods to reduce the heavy metal stress exerted on plants and enhance the metabolic and physiochemical processes of the plant.

Abhishek Maitry, Gunjan Patil and Preety Dubey

Comparative Analysis of Mulching and Weed Management Practices on Nutrient and Weed Dynamics of Kharif Sorghum (Sorghum bicolor L.)

The present field study was conducted to evaluate the effects of mulching and weed control methods on the nutrient and weed dynamics of Kharif Sorghum. The research was conducted in the Agronomy farm of Lovely Professional University in Phagwara, Punjab, during the summer of 2023. The experiment utilized a randomized block design with three replications. A total of six treatments were used, each with different amounts of treatment applied to assess the effects on the growth, yield, and weed characteristics of sorghum. The growth metrics, including plant height, leaf count, stem circumference, leaf area index, and chlorophyll content, saw significant improvement as a result of the amplified influence of mulching and weed management. Treatment T1, which excluded weeds, yielded the greatest plant height (134.69 cm), number of leaves (8.73), stem girth (10.14 cm) at harvest, leaf area index (7.78), and chlorophyll content (53.74) at 90 days after sowing (DAS). The T1 treatment, which was free of weeds, had the most favorable production characteristics. The grain yield was recorded at 2.15 t.ha-1, the straw yield at 4.59 t.ha-1, and the harvest index at 22.54%. The highest protein concentration was observed as 10.84% in T1 (Weed free) and 10.73% in T2 (Sugarcane trash). In addition, the characteristics of the weed, including the number of weeds, the effectiveness of weed management, and the weight of the weeds, were shown to be highest in dicots at 120 days after sowing (DAS). Treatment T1, which involved the complete removal of weeds, exhibited no weed population and achieved the maximum level of weed control effectiveness and dry weight. The study’s findings indicated that the use of T1 (Weed-free) treatment had a substantial influence on different growth, yield, and weed characteristics. Effective management of essential inputs, such as cultivation, fertilizers, and weed management, is vital for improving overall productivity and stability

Abhinav Thakur, Hina Upadhyay, Lalit Saini, Tarun Sharma and Himanshu Saini

A Review of Environmental Monitoring for Land Desertification Using Geospatial Analysis and Remote Sensing

Studying and evaluating desertification is essential due to its potential occurrence as a result of both natural and anthropogenic processes. Precise forecasting of forthcoming climate change perils is crucial for devising policies, action strategies, and mitigation measures at both the local and global scales. Remote sensing facilitates the examination, monitoring, and forecasting of several aspects of desertification. Throughout the years, many methodologies have been employed to investigate desertification through the utilization of Remote Sensing (RS). This study investigated the worldwide prevalence and temporal sequence of research that utilized remote sensing (RS) to investigate desertification. In addition, the study assessed the primary approaches and factors employed in the examination of desertification through the analysis of remote sensing data. The application of remote sensing (RS) in the investigation of desertification can be traced back to 1991. Between 2015 and 2020, an annual average of over 40 publications were published, indicating a substantial rise in the utilization and accessibility of remote sensing (RS) technology to monitor desertification. However, there is a significant disparity in the amount of research conducted in different fields. Asia demonstrates a substantially higher quantity of studies in contrast to America or Africa. China has conducted the highest number of research on desertification using remote sensing (RS) techniques. The Thematic Mapper (TM) sensor is the principal source of satellite data, specifically Landsat pictures. The primary techniques utilized for studying desertification are classification and monitoring of alterations. Furthermore, remote sensing methods commonly employ land cover/land use change and vegetation, together with its attributes such as the Normalised Difference Vegetation Index (NDVI), as the primary factors for studying desertification.

Ghaidaa Sabah Yousef, Hayder Dibs and Ahmed Samir Naje

Sustainable Phosphate Removal with Acid-Modified Fly Ash: Kinetic, Isothermal, and Thermodynamic Insights

The removal of pollutants from water bodies has emerged as a pressing global concern. Discharging untreated wastewater into the environment poses a significant threat due to the presence of hazardous substances like nitrate and phosphate, contributing to the widespread issue of eutrophication. This study focused on investigating the adsorption of phosphate from a synthetic solution using fly ash, an industrial by-product. To enhance the efficiency of coal fly ash, acid treatment was employed. Batch experiments were conducted to examine the influence of different factors, including pH, adsorbent dosage, initial phosphate ion concentration, contact time, and temperature. Surface electron microscopy (SEM) explained the morphology of the adsorbent, and Fourier Transform Infrared Spectroscopy (FTIR) analysis was performed to analyze the adsorbent pre and post-adsorption, allowing for the identification of functional groups tangled in the adsorption process. The major functional groups observed were hydroxyl, carboxylic acid, amines, and nitrile groups, all contributing to the adsorption process. Acid-modified fly ash (AMFA) demonstrated favorable results in terms of phosphate removal, particularly at a pH of 5.0 and an initial phosphate concentration of 50 ppm. Equilibrium in adsorption was achieved within 30 min at a temperature of 15°C with constant stirring of 100 rpm, resulting in a high phosphate removal rate of 91%. Freundlich isotherm was found to contribute a better fit for the adsorption data compared to the Langmuir isotherm. Pseudo-second-order kinetic model, with a high R2 value of 0.998, exhibited excellent agreement with the adsorption data for acid-modified fly ash. Thermodynamic study indicated that the adsorption process was heat absorbing (endothermic) and non-spontaneous at low temperatures. Overall, the results of the experimental study highlighted the promising adsorption potential of acid-modified fly ash as an effective adsorbent for phosphate removal in water treatment applications.

Renu Bala, Rajesh Dhankhar and Sunil Kumar Chhikara

Changes in Land Use Land Cover and its Resultant Impacts on the Urban Thermal Environment of Chattogram City: A Spatio-Temporal Analysis Based on Remote Sensing and GIS Techniques

The present study assessed the changes in land use and land cover to correlate the variations in the land surface temperature of Chattogram City. To analyze land use land cover (LULC) change and determine its effects on land surface temperature in the city area, temporal Landsat (5,7 ETM+ and 8,9 OLI) imageries from four time periods (2007, 2012, 2017, and 2022) were used. To assess the correctness of the picked random pixels, current ground truth data gathered from several sources was applied. Raster data has been utilized to identify the places that are influenced year-round in the green space (i.e., vegetation cover) and to examine the remote sensing image categorization for the green area using satellite images. These enable the study to explain the causes of the degradation and alteration of green space throughout time. The study identified that urbanization has resulted in a significant rise (about 2840 hectares, 16.74%) in urban land between 2007 and 2022, causing a loss of vegetative land (about 656 hectares, 3.85%). Additionally, the research concentrated on the actual affected area and attempted to forecast the cities’ land use in 2037, which revealed a large loss of vegetation by that year. The research has the potential to be utilized as a reference in the future.

Sagar Mozumder, Mahfuza Parveen and A.B.M. Kamal Pasha

A Complete Review on Ericoid Mycorrhiza: An Understudied Fungus in the Ericaceae Family

Ericoid mycorrhiza (ErM) is an unexplored and understudied member of the mycorrhizal world, surprisingly belonging to Ascomycota and Basidiomycota instead of Glomeromycota (the phylum comprising fungi forming associations with higher plants). ErM obtained its etymology due to its symbiotic relationship with members of the Ericaceae Family. Just like any other mycorrhiza, ErM also helps its hosts through nitrogen uptake and phosphorus bioavailability and provides defense to host plants against various phytopathogens. It also takes part in the decomposition of organic matter and depolymerization of complex substances. These mycorrhizae are distributed across all continents except Antarctica. The majority of culturable ErM is spread across England, Australia, Canada, the United States etc. This review focuses on the literature survey on ErM, its taxonomy, and diversity alongside its functions. Our review also sheds light on the host range of the ericoid fungi, wherein, out of all the hosts, Salal (Gautheria shallon) has been identified as one of the most promising ones

Malini Ray, Sneha Choudhary,, Abisma K Jose, Vikash Kumar, Aakash Gupta and Sonali Bhagat

Delineation of Potential Groundwater Zones Using GIS-based Fuzzy AHP Technique for Urban Expansion in the Southwestern Fringe of Guwahati City, India

Due to unprecedented urban growth many localities within the heart of Guwahati city witness groundwater scarcity, mainly during the dry seasons. This study aims to identify potential groundwater zones in the southwestern fringe of the city where the Guwahati Metropolitan Development Authority (GMDA) has adopted plans for future expansion. Rani and Chayani Barduar are two administrative blocks adjacent to the city, possessing a vast tract of unsettled agricultural land ideal for future township development. Multi-criteria decisionmaking technique using a Fuzzy Analytical Hierarchy Process (FAHP) in a Remote Sensing and Geographic Information System (GIS) environment is used to produce the groundwater potential map. A total of eight thematic layers important for groundwater recharge: lithology, geomorphology, slope, rainfall, lineament density, soil, drainage density, and Land Use Land Cover are prepared using satellite data, fieldwork, and other suitable techniques and used as input. The study area is classified into five groundwater potential zones – very high (42.52 %), high (28.67 %), moderate (17.23%), poor (10.21 %), and very poor (1.37%). Validation of the result using a yield map derived from the exploratory wells of the Central Ground Water Board (CGWB) shows strong agreement with the prediction accuracy (AUC = 73.36%). Field-derived water level data also show a high negative correlation (R2 = 0.71) with yield data indicating high specific yield in wells with shallow water levels. The study results will help planners and policymakers with future urban development strategies and sustainable groundwater management practices.

Rakesh Kumar Sarmah and Santanu Sarma

Evaluating the Impact of Community Attitudes on the Sustainability of 3R Temporary Waste Disposal Sites Using Structural Equation Modeling-Partial Least Square (SEM-PLS) in Sukoharjo

In 2023, the waste management situation in Sukoharjo showed a combination of achievements and difficulties. Out of the 12 Temporary Waste Disposal Sites with 3R (Reduce, Reuse, Recycle) facilities, only 4, including Temporary Waste Disposal Sites with 3R (Temporary Waste Disposal Sites 3R) Anugrah Palur, were functioning at their best. This study examines the factors that impact the establishment and long-term viability of these facilities, employing a combination of research methods that incorporates RAP-Temporary Waste Disposal Sites 3R analysis, partial least squares (SEM-PLS), observations, and interviews. The results emphasize that attitude is the most influential component in supporting the growth of Temporary Waste Disposal Sites with 3R, as indicated by a p-value of 0.000. On the other hand, knowledge (0.052) and behavior (0.279) are identified as the least important aspects that hinder development. The Temporary Waste Disposal Sites with 3R have an overall sustainability rating of 72.79, which classifies them as ‘very sustainable.’ The environmental component achieved a score of 79.54, the social dimension scored 72.88, the management and infrastructure dimension scored 71.30, and the economic dimension scored 65.44. These findings emphasize the crucial importance of community attitudes in promoting sustainable waste management practices. They also highlight specific areas that can be improved to enhance the effectiveness and sustainability of Temporary Waste Disposal Sites with 3R facilities.

Wahyu Kisworo, Sapta Suhardono, Irfan AN and I Wayan Koko Suryawan

Analysis of Plants, Helianthus annuus (Sunflower) and Gossypium herbaceum (Cotton), for the Control of Heavy Metals Chromium and Arsenic Using Phytoremediation Techniques

Heavy metal pollution released into the surface environment poses a significant threat, being hazardous to both the environment and living organisms. Phytoremediation thus appears as a viable technique to address heavy metal pollution in soils impacted by industrial effluents. To identify the growth performance of sunflower and cotton seeds under various concentrations of arsenic and chromium present in the tannery industrial wastewater in the Chengalpattu region, and to identify the accumulation of Arsenic(As)As and chromium (Cr) in the roots, shoots, and soil of these plants. This paper examined the usefulness of sunflower (Helianthus annuus) and cotton (Gossypium herbaceum) in eradicating Cr and As-polluted soils originating from tannery wastewater. In this experiment, Completely Randomized Block Design (CBRD) testing was performed, and the samples were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The accumulation of Cr in sunflowers was 120 mg.kg-1 in the roots and 25 mg.kg-1 in the above-ground parts. As accumulated to 85 mg.kg-1 in the roots and 15 mg.kg-1 in the above-ground parts. Similarly, cotton plants accumulated 90 mg.kg-1 of Cr in the roots and 20 mg.kg-1 in the above-ground parts. As accumulation in cotton plants was 100 mg.kg-1 in the roots and 30 mg.kg-1 in the aboveground parts. The study inferred that, in comparison to the other plants, the concentrations of Cr in sunflower roots were significantly higher, but cotton was found to have a better ability to take up As in the roots as well as in the aerial parts of the plant. It hence demonstrates the applicability of sunflower and cotton to support phytoremediation efforts sustainably within industrial environments to mitigate pollution and improve the quality of the soil.

S. Monisha and S. P. Sangeetha

Mapping of Groundwater Potential Zones Using Fuzzy Logic Technique at Kadamaian Basin, Kota Belud, Sabah, Malaysia

This research was initiated to study the groundwater potential zones using the Fuzzy logic technique at Lembangan Kadamaian, Kota Belud, Sabah, and its surroundings. The lithological units of this study mainly focus on the sedimentary rock of Wariu Formation, Crocker Formation, and Trusmadi Formation, including the quaternary alluvium deposition unit of Kota Belud. Based on the structural geology analysis results, the deformation trends are in the northwest-southeast direction. The interpretation of groundwater potential zones was made by using the ArcGIS Pro, R-studio Global Mapper, and several other mappingrelated software. Ten thematic maps that have been produced are lithological map, lineament density map, rainfall map, distant from river map, distant from lineament map, drainage density map, landform, and land cover map, Topographic Wetness Index (TWI) map, rock porosity map, curvature map, and slope steepness map. GIS techniques were used during the spatial analysis stage. All thematic maps have their class values and are based on field data, relevant department data, and remote sensing data. Further processes were done using R-studio, Fuzzy Toolset, and Raster Calculator. This process afterward will produce the groundwater potential map of the study area. The final result has been supported by the data of tube wells from the Department of Minerals and Geosciences, Sabah, and was validated using the ROC and AUC curve validation technique.

Evienstein Wilfred and Zulherry Isnain

A Comparative Study of Sustainable Bacteria-Alccofine Concrete: Environmental Benefits and SEM Analysis

The potential for creating unique, environmentally friendly, and cost-effective concrete via biomineralization is discussed in this research. Cement, a necessary component of concrete, is expensive and emits between 8 and 10% of the world’s CO2 emissions. Researchers have significant effects to identify alternatives that can reduce the burden of high costs, excessive energy use, and environmental repercussions. Manufactured sand (M-sand) completely replaced fine aggregate, and cement was replaced with alternatives such as Alccofine (AF) and Silica Fume (SF). The percentage at which it can be substituted for cement is, however, somewhat small. The goal of this study is to create an environmentally friendly AF and SF concrete mix by incorporating bacteria with the highest possible cell concentration. To evaluate the mechanical properties, concrete samples were tested for flexural strength, split tensile strength, and compressive strength at 7, 14 and 28 days postcuring. The microstructural analysis of sustainable concrete was performed using scanning electron microscopy (SEM) techniques. It was determined that 10% alccofine and 15% silica fume by volume of cement in the binary cementitious system provided the best mechanical characteristics for bacterial concrete using Bacillus megaterium. Similarly manner in the ternary cementitious system, the highest gain in compressive strength is seen when 10% alccofine is substituted with 10% silica fume in the cement mixture. Calcium carbonate precipitation validated the enhanced properties of bacterial concrete. The microorganisms used in the concrete are non-toxic and environmentally being. Results indicate that using Bacillus megaterium alongside AF and SF helps to reduce cement usage, lessens carbon dioxide emissions, and makes concrete more environmentally friendly. Using Scanning Electron Microscopy (SEM), the calcite precipitations in bio-additive mixed ternary admixture blended concrete were confirmed. The proposed regression equations produced minimal errors when compared to the experimental results, thus providing accurate and effective predictions of the flexural, split, and compressive strengths. The strength properties of these blends were validated through SEM studies.

R. Porselvan, T. S. Lakshmi and M. Tholkapiyan

Diversity and Temporal Frequency of Records of the Herpetofauna of the Equatorial Seasonally Dry Tropical Forest in the Rural Community of Lucarqui, Piura, Northwestern Peru

Reptile and amphibian species in the Equatorial BTES face threats such as fragmentation, habitat loss, and climate change. Between 2019 and 2021, the richness and abundance of herpetofauna species was evaluated in the Lucarqui peasant community in Piura, northwest Peru. The objective of this research is to provide a preliminary list of species and understand their temporal frequency patterns. The study area was divided into specific zones: with anthropogenic activity, “crops” and “population centers”, where incidental catches and visual surveys were carried out, and without anthropogenic activity, “forests” and “ravines”, where transects of variable length and fixed width (2 m), the biological data obtained were analyzed with the iNEXT statistical tool, and a standardized methodology was provided for the calculation of the temporal frequency of recordings (FRT). The study identified 26 species: 7 amphibians and 19 reptiles. Amphibians dominated in abundance, while reptiles were rare. 85.71% (6) of amphibians and 47.36% (9) of registered reptiles are restricted to the Equatorial BTES. FRT patterns varied by habitat and time. These, along with wealth and abundance, were altered and reduced in areas influenced by human activity, crops, and population centers. It was found that there were still more species to be reported, especially reptiles. The study highlights the richness and vulnerability of the herpetofauna in the Equatorial BTES, reaffirming the urgent need for conservation strategies and continued research to ensure the protection and deep understanding of this valuable, fragile ecosystem.

Juan Carlos Soto Q., Armando Fortunato Ugaz C., Angel Enrique Llompart N., Irwing Smith Saldaña U., José Manuel Marchena D., Mariana Alexandra Montero S., and Robert Barrionuevo G.

Spatio-Temporal Analysis of Aridity Trends and Shifts in Karnataka Over 63 Years (1958-2020): Insights into Climate Adaptation

Understanding aridity trends is crucial for climate adaptation strategies. This study analyzes the spatial and temporal fluctuations in aridity across Karnataka, India, over 63 years from 1958 to 2020 using the Aridity Index (AI). Monthly, seasonal, and annual AI values were calculated using precipitation and potential evapotranspiration data sourced from TerraClimate. The results indicate that approximately 74% (142,464 sq. km) of Karnataka is classified as dryland, ranging from semi-arid to dry subhumid zones, while 26% (49,416 sq. km) falls under more humid non-dryland areas. The Malnad and coastal regions are more humid compared to the predominantly semi-arid northern inland Karnataka. Temporal analysis between the periods 1958–1990 and 1991–2020 revealed that 6.24% of the land area shifted from semi-arid to dry subhumid, indicating increased moisture availability, whereas 0.43% shifted from dry subhumid to semi-arid, suggesting localized aridification. During the post-monsoon season, 14.12% of dryland areas transitioned to non-dryland, with substantial improvements in moisture availability observed in districts such as Uttara Kannada (59.21%) and Mandya (82.97%). Conversely, 1.5% of non-dryland areas converted to dryland, indicating localized decreases in water resources. Seasonal analysis revealed that 99.92% of the summer aridity status remained constant, while during the monsoon season, only 2.42% of dryland areas changed to non-dryland, reflecting stable monsoonal rainfall patterns. These findings highlight the significant influence of topography, monsoonal patterns, and water management on aridity dynamics in Karnataka. The study provides valuable insights for developing policies on climate adaptation, sustainable agriculture, and regional water resource management. Addressing the increasing trends in aridity is essential to reduce desertification risks and enhance the State’s resilience to climate change.

Sawant Sushant Anil, Dhananjayen and M. Sasi

Enhancing Economic Benefits from Forest Preservation In Papua, Indonesia: A Review

This study aims to demonstrate the importance of the Social Enterprise Model Canvas (SEMC) as an alternative to addressing social and ecological system challenges that describe important aspects of obtaining economic benefits from forest conservation in remote areas such as Papua. The method is carried out through Systematic Reviews and MetaAnalyses (PRISMA) and qualitative content analysis process of social services implemented in Indonesia and formulated into the required SEMC using 216 documents sourced from the Scopus Core Collection database, which consists of three types of documents: articles, reviews, and book reviews. The results are: First, content analysis of environmental service payment business models in Indonesia provides insight for the government and environmental service providers. Second, the benefits scheme as part of SEMC is an important component in determining successful outcomes. Third, in special regions such as Papua which have special autonomy status, where traditional community regulations play an important role, SEMC must cover aspects of government and regional regulations. The implications of this research can be used as recommendations in determining policies related to payment for forest environmental services.

A. A. Awirya, K. E. N. Sianipar, A. Kurniawan and I. A. Sasanti

Enhancing Land Use/Land Cover Analysis with Sentinel-2 Bands: Comparative Evaluation of Classification Algorithms and Dimensionality Reduction for Improved Accuracy Assessment

Accurately classifying land use and land cover (LULC) is crucial for understanding Earth’s dynamics under human influence. This study proposes a novel approach to assess LULC classification accuracy using Sentinel-2 data. Authors have compared traditional and Principal Component Analysis (PCA)-based approaches for Maximum Likelihood Classification, Random Forest, and Support Vector Machine (SVM) classifiers. Four key classes (agricultural land, water bodies, built-up areas, and wastelands) are classified using supervised learning. Accuracy is evaluated using producer, user, overall accuracy, and kappa coefficient. Our findings reveal superior accuracy with PCA-SVM compared to other methods. PCA effectively reduces data redundancy, extracting essential spectral information. This study highlights the value of combining PCA with SVM for LULC classification, empowering policymakers with enhanced decision-making tools and fostering informed policy development.

Akil V. Memon, Nirav V. Shah, Yogesh S. Patel and Tarun Parangi,

Portable Hybrid System for Producing Green Hydrogen by Electrolysis Using Energy Generated Through an Archimedean Screw

At a global level, energy production is predominantly based on the use of conventional resources such as oil, coal, and gasoline; this dependence has led to adverse effects such as climate change and detrimental impacts on human health; consequently, green hydrogen emerges as a renewable energy source. This work develops and analyses the parameters of a portable hybrid system to produce green hydrogen on a small scale in a more efficient way, allowing it to be placed in rural areas to be used as an ecological fuel source. The hybrid system is divided into two stages; for energy production, a microhydraulic system was developed based on an Archimedes screw turbine, which is made up of a mechanical and electrical design, where the electricity produced is stored in a continuous energy source, which supplies the electric current to the electrodes in the alkaline electrolysis process; where a reaction occurs in the water resource to produce green hydrogen and oxygen. It was demonstrated that the turbine, when presenting a greater wetted area and slope of fall, produces a higher electrical potential, while in the electrolysis process to produce green hydrogen and oxygen, it was determined that the appropriate electrolyte to use is potassium hydroxide at 20?cause it has greater electrical conductivity unlike sodium chloride and sodium hydroxide; evidencing the most efficient parameters to implement the hybrid system in rural areas to replace the conventional fuel that is used in cooking food.

E. Aliaga Villanueva, P. D. Inga Canales, M. G. Mori Paccori, J. V. Cornejo Tueros and K. G. Ibarra Hinostroza

Reflective Building Façades: The Effect of Albedo on Outdoor Thermal Comfort – A Case Study of Low-Rise Apartments

In tropical locations, where urban areas experience considerable temperature rises relative to rural areas, the Urban Heat Island (UHI) effect is becoming more and more evident. Reflective building façades, global warming, and hardscape areas are all contributing issues. Because they reflect solar heat, materials like glass, high-pressure laminates, and metallic sheets raise outdoor temperatures, which affects both human comfort and the environment. This study looks into ways to lessen the negative impacts of reflecting façades on urban heat islands (UHIs), with a particular emphasis on how albedo affects microclimates and urban canyons. We examine the impacts of albedo on outdoor thermal comfort by analyzing research from 2003 to 2022. Thermal comfort indices can be calculated with ENVI-met software, which is useful for specialists in urban planning and architecture. To demonstrate these consequences, a case study of a low-rise housing complex located in Greater Noida, India, is provided. With a subtropical climate, this region sees wide changes in temperature, with summer highs frequently reaching 43°C and winter lows of about 7°C. The study uses ENVI-met simulations to evaluate how reflective façades affect thermal comfort in real-world conditions. This highlights the pronounced heat island effect and the localized heat buildup in urban areas during peak daytime h. The simulation revealed significant temperature variations throughout the day, with air temperatures peaking above 43.77°C by mid-afternoon between buildings, demonstrating the pronounced heat island effect. Relative humidity levels were low, around 39% to 40%, contributing to dry air discomfort. Wind velocities exceeded 1.5 meters per second at certain junctions, intensifying discomfort by amplifying the perceived heat. These findings indicate that the use of reflective materials on building façades in Greater Noida exacerbates human thermal discomfort outdoors. The study provides an opportunity to further measure and analyze these effects to develop targeted strategies for mitigating the urban heat island phenomenon and enhancing outdoor comfort in the region.

Gunjan Tyagi, and Md Danish

Utilizing Bacteria for Crude Oil-Contaminated Soil Bioremediation and Monitoring Through Tomato Plant Growth

This paper provides an in-depth analysis of the process of cleaning up crude oil-contaminated soil by using a carefully selected combination of bacteria that are capable of hydrocarbon breakdown. We assessed this bioremediation approach’s efficacy by evaluating tomato plant growth and vigor as indications of soil recovery. According to our research, adding hydrocarbon-degrading bacteria significantly enhanced the crude oil’s ability to break down in contaminated soil. Over time, the amount of petroleum hydrocarbons in the soil decreased significantly as a result of the bacterial consortium’s effective hydrocarbon metabolism. It became out that this bioremediation method was both economically and environmentally viable. Furthermore, we noticed significant improvements in the general health and growth of tomato plants grown in the bioremediated soil. These plants showed signs of excellent soil quality restoration, including higher biomass, enhanced root development, and less stress symptoms. This work highlights the possibility of bacteria-mediated bioremediation as a workable and long-term solution to soil pollution caused by crude oil. Additionally, incorporating plant growth monitoring highlights the ecological benefits of bioremediation as a remediation approach for repairing contaminated ecosystems and provides a useful way to assess the efficacy of bioremediation operations. The findings showed a substantial decrease in petroleum hydrocarbons and enhanced tomato plant growth in treated soils, demonstrating effective ecosystem restoration. By using bioremediation to treat soil contamination caused by crude oil, this research supports the conservation and sustainable use of terrestrial ecosystems, which is in line with Sustainable Development Goal 15: Life on Land.

Vijaya Sundravel K., Abdul Bari J. and Ramesh S.

The Implementation of Contingent Valuation Method for Waste Management at Telaga Ngebel, Ponorogo, Indonesia: A Novel Approach to Ecotourism Waste Processing House

The increase in the number of visitors to the tourism sector has a positive impact on the economy of the surrounding merchants. However, it also creates negative externalities through increased waste generation. The generation of unresolved waste will disrupt the function of the environment. Ecotourism Waste Management is one way to handle waste from sellers and tourists by collecting, processing, and selling processed products. The “Waste Treatment House” manages sales proceeds from and for sellers with a profit-sharing system. This effort requires the willingness to pay (WTP) sellers for waste management. This study aims to determine the amount of waste retribution and the factors that influence it. The data used in this study were primary data of 104 sellers in Telaga Ngebel Area, Ponorogo, Indonesia, and were processed using ordinary least squares (OLS) regression and descriptive analysis. WTP value is influenced by age, monthly expenses, number of dependents, operating hours, and length of business. The products produced through the program are organic waste processed into compost and fish feed, while inorganic waste is processed into handicrafts. Finally, selling processed waste products and the proceeds from these sales are used to increase merchant empowerment through revenue sharing and savings and loan products. This study has limited secondary data, namely information about the sustainability of waste management that has been carried out and the exact number of sellers in the area around Telaga Ngebel.

Evi Gravitiani, Ainina Ratnadewati and Nur Widiastuti

Potential Efficiency of Green Algae Scenedesmus quadricauda in Bioremediation of Polycyclic Aromatic Hydrocarbon, Benzo[a] Pyrene(BaP)

Using algae to break down or detoxify dangerous environmental pollutants, thereby changing them into a non-hazardous condition, is known as bioremediation. Investigating the ability of the green algae Scenedesmus quadricauda (Turpin) Brébisson to break a particular polycyclic aromatic hydrocarbon (PAH) known as Benzo[a]pyrene (BaP), Under regulated laboratory circumstances and on BG11 media, the alga was cultivated and exposed to different BaP dosages (0.5, 1, and 1.5 mM). High-performance liquid chromatography (HPLC) study helped to ascertain the BaP concentration. Involving the growth curve, doubling time, photosynthetic pigments, total protein, carbohydrates, and Lipid peroxidation (Malondialdehyde MDA) levels, the research investigated various physiological and biochemical aspects. Furthermore, measured were the levels of catalase (CAT), superoxide dismutase (SOD), and reactive oxygen species (ROS). Whereas the lowest growth rate was 0.00047 on the 15th day at a concentration of 1.5 mM, the maximum growth rate (k) recorded was 0.391 on the 7th day at a concentration of 0.5 mM. Doubling time also varied from 0.00014 throughout the 15th day with 1.5 mM and from 0.1179 throughout the 7th day with 0.5 mM BaP. The results showed a definite influence of the different quantities of BaP degradation by S. quadricauda; the greatest magnitude was 40.13 throughout the 15th with 0.5 mg.L-1, while the lowest magnitude was 0 throughout the 1st day with 0.5 Mm. While the min magnitude was 0.41µg.mL-1 in 0.5 mM throughout 1st day, the max magnitude of chlorophyll-a was 18.71 (µg.mL-1) in 1.5 mM throughout the 15th day. Whereas the greatest magnitude was 9.19 µg.mL-1 in 1.5 mM throughout the 15th day, the lowest magnitude of chlorophyll b was 0.36 µg.mL-1 in 1.5 mM throughout the 1st day. While the min was 0.013 on 1st day with 1 mM, the max magnitude of ROS was 0.28 until the 15th day with 1.5 mM. With 1 mM over 1st day, the carbohydrate showed a max magnitude of 35.13 µm.mL-1, and with 1.5 mM over the 15th day, the min magnitude was 12.25(µm.mL-1). While the min protein content was 1.83 µg.mL-1 in 1.5 Mm throughout the 8th day, the max protein content was 2.14 µg.mL-1 in 1 mM throughout the 8th day; moreover, SOD fluctuated between 22.22 µg.mL-1 in 0.5 mM throughout 1st day, and 60 µg.mL-1 in as the min magnitude throughout 8th day with 1.5 mM. The results show that magnitudes of CAT fluctuated between 13.33 µg.mL-1 in the 8th and 15th mM throughout the 15th day and 73.33 µg.mL-1 in 1 mM throughout the 15th day. MDA showed the largest magnitude 59.92 µmoL.L-1 in 1.5 mM over the 1st day, while the lowest magnitude, 36.58 µmoL.L in 1 mM over the 15th day.

Hala R. Mohammed, Jasim Mohammed Salman and Adi Jassim Abd Al-Rezzaq

Transforming Type 2 Diabetes Management Through Telemedicine, Data Mining and Environmental Insights

Diabetes mellitus is a prevalent chronic disease with significant implications for public health, including an expanded chance of coronary heart malady, stroke, persistent kidney illness, misery, and useful inability. In India, the predominance of diabetes among grownups matured 20 a long time and more seasoned rose from 5.5% in 1990 to 7.7% in 2016. Traditionally, diabetes management involves costly consultations and diagnostic tests, presenting challenges for timely diagnosis and treatment. Additionally, a comprehensive study was conducted to investigate the relationship between the incidence of type 2 diabetes mellitus (T2DM) and environmental exposure to arsenic in the form of air, water, and food pathways. The majority of the analyzed studies examined the levels of arsenic in water samples, with analyses of urine, blood, serum, and plasma samples coming next. Groundwater supplies may get contaminated by arsenic, especially in regions where arsenic deposits are naturally occurring or as a result of industrial activity. Additionally, various meals contain it, particularly rice, seafood, and poultry. Besides, it might be released into the environment by industrial processes such as coal combustion, smelting, and mining, which could lead to occupational exposure. There may be a genetic component to the association between arsenic exposure and the onset of diabetes. Ultimately, diabetes mellitus is enhanced by arsenic pollution through air, food, and drinking water. Advances in machine learning and telemedicine offer innovative solutions to address these challenges. Data mining, a crucial aspect of machine learning, facilitates the extraction of valuable insights from extensive datasets, enabling more efficient and effective diabetes management. This study explores a telemedicine-based system utilizing five classification techniques Tree, Naive Bayes, Support Vector Machine, and others to predict Type-2 diabetes. By leveraging real-time data analysis, the system aims to enhance early diagnosis and management of Type-2 diabetes, potentially preventing progression to critical conditions. The results evaluate the effectiveness of these models in a telemedicine context, identifying the bestperforming model to assist healthcare professionals in making informed decisions for early intervention and improved patient outcomes.

Sapna S. Basavaraddi and A. S. Raju

Assessment of Bioefficacy of Achromobacter xylosoxidans KUESCCHK-6, Isolated from Textile Contaminated Soil, in Treating Textile Effluent and its Impact on Vigna mungo

Textile effluents are major pollutants with varied contaminants. Traditional treatment methods are costly and produce sludge, necessitating alternative, eco-friendly solutions. Biological treatment methods are receiving attention as it is proven to be cheap, environment-friendly, and highly efficient treatment methods for dye effluent on an industrial scale as compared to the other available treatment methods. The present work evaluates the bioremediation of textile effluent using a pure culture of a bacterium isolated from the soil samples contaminated with textile wastewater. The strain was identified as Achromobacter xylosoxidans KUESCCHK-6 (GenBank Accession Number: OM475749) through 16S rRNA molecular analysis. This bacterial strain was used to treat textile effluent under specific conditions: glucose as the carbon source, urea as the nitrogen source, a C/N ratio of 6:1, a temperature of 35°C, a pH of 8.5, and a static incubation period of 5 days. The results indicated that the strain effectively reduced various physiochemical parameters of the raw textile wastewater: color by 87.94%, BOD by 80.61%, COD by 80.96%, EC by 73.11%, fluoride by 81.15%, phosphate by 79.57%, sodium by 76.88%, and turbidity by 81.02%. Additionally, metal ions, including iron, were removed by 84.83%, while other metals, such as zinc, nickel, manganese, copper, lead, cadmium, total chromium, arsenic, barium, cobalt, and boron, were reduced to belowdetectable limits. Phytotoxicity tests confirmed the non-toxic nature of the treated effluent. Overall, the study concludes that Achromobacter xylosoxidans KUESCCHK-6 is a promising candidate for the bioremediation of textile industrial effluents, with potential for commercial application.

C. Chaithra and Hina Kousar

Assessment of Toxic Metals in an Open Dump Site Near PNG University of Technology, Papua New Guinea

Groundwater contamination near the municipal solid waste dump at the Papua New Guinea University of Technology (PNGUoT) has raised serious health concerns in the local communities. To testify to this, a research study was conducted to quantify the presence of heavy metals. Water sample analyses showed Cd levels ranging from 0.0002 to 0.02 mg.L-1, Pb from 0.00002 to 0.094 mg.L-1, and Hg from 0.0001 to 0.052 mg.L-1, all of which exceed the World Health Organization’s (WHO) safe drinking water limits. These metals are known to cause a range of health problems, including kidney disease, cancer, brain damage, and developmental delays in children. The situation calls for urgent action to safeguard the local community’s health. Immediate improvements in waste management, such as better landfill designs with systems to capture and treat leachate, are needed to prevent further contamination of groundwater. Additionally, water treatment technologies like reverse osmosis should be considered to provide safe drinking water. Regular monitoring of groundwater quality and public health education in the area are also key steps in minimizing risks. These combined efforts will help ensure safer water for the community and more responsible management of the waste disposal site.

John Ape, Srikanth Bathula, Sailesh Samanta and Krishna Kumar Kotra

Evaluation of Air Quality by Particulate Matter in Junin and Huancavelica, Peru

Anthropogenic atmospheric particles with a diameter of less than 2.5µm (PM2.5) and between 2.5 to 10 µm (PM10) are among the main contributors to air pollution and have become a serious pollution threat in the Junin and Huancavelica region of Peru. This increase could be due to the burning of vegetation in the Amazon region of Brazil. Therefore, data obtained with the low-cost PA-II Purpleair sensor were analyzed to measure particulate matter (fine and coarse fashions) in the Junin region (Chanchamayo, station T. Huancayo, station T1 and Chupaca, station T3) and Huancavelica (Pampas, station T2). Likewise, the Hysplit model was used to quantify the transboundary wind trajectories from the Amazon region in Brazil to the Junin region in Peru. Shows that, during the rainy season, the maximum concentrations of PM2.5 and PM10 are 151 µg.m- ³ (station T1) and 178 µg.m- ³ (station T1), respectively. Finally, the results of the air quality index (AQI) for PM2.5 allow for the classification of the Huancayo and Chanchamayo stations with “very bad” and “moderate to bad” air quality, respectively. Also, in Pampas and Chupaca, the AQI is classified as very unhealthy and hazardous on almost 50% and 43% of days, respectively

Julio Angeles Suazo, Roberto Angeles Vasquez, Esmila Yeime Chavarría Márquez, Carmencita Lavado-Meza, Leonel de la Cruz-Cerrón, Nataly Angeles Suazo, Liz Quispe Quincho and Hugo Abi Karam

Land Use/Land Cover (LULC) Change Classification for Change Detection Analysis of Remotely Sensed Data Using Machine Learning-Based Random Forest Classifier

Land Use and Land Cover (LULC) classification is critical for monitoring and managing natural resources and urban development. This study focuses on LULC classification for change detection analysis of remotely sensed data using a machine learning-based Random Forest classifier. The research aims to provide a detailed analysis of LULC changes between 2010 and 2020. The Random Forest classifier is chosen for its robustness and high accuracy in handling complex datasets. The classifier achieved a classification accuracy of 86.56% for the 2010 data and 88.42% for the 2020 data, demonstrating an improvement in classification performance over the decade. The results indicate significant LULC changes, highlighting areas of urban expansion, deforestation, and agricultural transformation. These findings highlight the importance of continuous monitoring and provide valuable insights for policymakers and environmental managers. The study demonstrates the effectiveness of using advanced machine-learning techniques for accurate LULC classification and change detection in remotely sensed data.

H. N. Mahendra, V. Pushpalatha, V. Rekha, N. Sharmila, D. Mahesh Kumar, G. S. Pavithra, N. M. Basavaraj and S. Mallikarjunaswamy

Effect of EPS Concrete: Balancing Construction Efficiency and Environmental Sustainability

Expanded polystyrene (EPS) is a material that may be harmful to human health. This is mainly because it releases specific chemicals during its manufacture, usage, and disposal. It is important to remember that the effects on health can change depending on the particular situation, exposure levels, and personal sensibilities. There are initiatives underway to address these environmental issues. Increasing EPS recycling rates, locating substitute materials, and encouraging appropriate disposal techniques are the main goals of several projects. Furthermore, studies into more environmentally friendly EPS substitutes for a variety of applications are still in progress. Creating a circular economy and lowering the total amount of single-use plastics used are two more aspects of larger plans to lessen the environmental impact of materials like EPS. The introduction of EPS cubes into concrete has reduced the adverse effects of EPS materials in the environment. This study substituted EPS, which is generated from industrial waste products, for aggregate. For an experimental study, a good-strength, sustainable concrete mix of grade M30 has been developed. In increments of 25%, five different mix proportions were evaluated for EPS cubes with size variations of 10 mm, 12 mm, and 20 mm. The range of 0 to 100% was studied. The replacement of EPS cubes by volume of course aggregates in the mixture yields the maximum increase in crushing, rupture, and bending strength, according to the mechanical properties of concrete that have been observed. This replacement ratio of 25% was shown to be efficient. The use of EPS materials in concrete is therefore shown to produce large reductions in environmental pollutants in addition to significant cost and energy savings.

R. Rajeshwaran, J. Logeshwari and R. Abirami

Spatial Model of Fire Vulnerability Distribution Based on Multicriteria in Tropical Forest Areas, Central Sulawesi, Indonesia

The problem of fire always threatens the existence of forests in Indonesia, repeatedly occurring every year, so it becomes one of the national and regional issues, both occurring naturally and caused by human actions. This study aims to develop a spatial analysis model of the multi-criteria-based fire vulnerability distribution in tropical forest areas. Modeling using GIS and spatial correlation analysis. In a tropical forest area of 7,042.29 Ha in the Tepo Asa Aroa KPH area, North Morowali Regency, Central Sulawesi, a spatial model of the distribution of fire vulnerability based on multi-criteria was produced, which could support rapid mapping of fire-prone forest areas. The results of the analysis of variables on land use/vegetation cover, rainfall, slope, distance from roads and settlements, business permits, forest protection, and security simultaneously made it possible to lower the fire vulnerability rating from ‘very high’ and ‘high’ to a ‘medium’ vulnerability rating. ‘ to ‘low’ and ‘very low’. All parameters tested statistically have a spatial correlation with fire vulnerability

Akhbar, Abdul Rosyid, Bau Toknok, Rahmat Kurniadi Akhbar and Rizky Purnama

A Review on Artificial Intelligence for Water Quality Prediction in Amazonian Countries

Water quality prediction plays an important role in environmental monitoring and ecosystem sustainability in the Amazon. Therefore, this review focuses on determining the advances in the scientific production of artificial intelligence in water quality prediction in the Amazon, as well as the limitations and perspectives compared to water quality indexes (WQI). In this sense, Boolean operators were applied, using the following terms: “artificial intelligence”, “machine learning”, “water quality,” and “Amazonia” The databases were Scopus, web of Science, Springer, and IEEE. In this study, 14 scientific articles published during the period 2000-2024 focused on Amazonian countries were evaluated. Although in the Amazon low scientific production was evidenced and is led by Brazil, the highest scientific growth was for 2021, and 93?longs to the Scopus database, with a compound annual rate of 12.16%. The IA is characterized by using data from governmental institutions and is only limited to parameters such as Total Suspended Solids (TSS), Total Organic Carbon, Turbidity, and Chlorophyll, using satellite imaging techniques, and the most commonly used algorithm was the Clustering Algorithms. In this context, AI applications are still very low in Amazonian countries compared to other European countries. Its limitations are in the accuracy and the limited amount of physicochemical and microbiological data used for predictions. However, AI is a tool that will replace the water quality indexes used manually.

J. E. Cruz de La Cruz, W. A. Mamani, F. Pineda, V. Yana-Mamani, R. Santa Cruz, Í. Maldonado-Ramírez, R. Pérez-Astonitas and E. Morales-Rojas

Using Deep Learning for Plant Disease Detection and Classification

In India’s economy, farming is crucial, making early detection of plant diseases an important task. This helps in reducing crop damage and preventing the diseases from spreading further. Numerous plants, such as corn, tomatoes, and potatoes, display evident symptoms of diseases on their leaves. These noticeable patterns can be employed to accurately predict the diseases and facilitate prompt intervention to reduce their impact. The customary method involves farmers or plant pathologists visually inspecting plant leaves and identifying the specific disease. This project involves a deep learning model designed for classifying plant diseases, utilizing CNNs for their proficiency in image classification. The model, which utilizes architectures like MobileNet, InceptionNet, ResNet, and ResNeXt, delivers faster and more accurate predictions than traditional manual methods. Notably, ResNeXt, with its added dimension of cardinality that aids in learning more complex features, achieved the highest accuracy, reaching 98.2%.

G. N. Balaji, G. Parthasarathy, A. K. P. Kovendan and Aakash Jha

Impact of Landfill Proximity on Soil Quality: A Comparative Study of Dumping and Non-Dumping Sites Near Srinagar, Garhwal, Uttarakhand

The present study aims to analyze changes in the physicochemical parameters of the soil in the vicinity of a small municipal solid waste landfill site. The research results were analyzed based on general physicochemical properties, which include pH, electrical conductivity (EC), organic carbon (OC), available nitrogen (N), phosphorus (P), and potassium (K) by using standard methods. The results show that the soil from the dump sites contained higher amounts of soil properties (EC, SOC, N, P, K) than the non-dumping sites. Pearson correlation shows that pH exhibits a robust negative correlation with all other parameters while the remaining other parameters had a positive correlation with each other. Also, PCA analysis shows dumping sites mostly depict positive values in PC1, whereas the non-dumping sites indicate negative values. The final interpretation indicates that the soil in the dump site was found suitable for plant growth. However, due to improper solid waste management, this nutrient-rich soil could be mixed up with several other contaminants, such as soluble salts, plastics, heavy metals, and so on. This could make the soil unhealthy or unsuitable for plant growth. The study also suggests proper segregation, recovery, treatment, and safe disposal of solid waste and formulates an integrated municipal solid waste management plan for this particular dumping site.

Ajay Negi and Ashok Kumar Meena

Determination of the Water Quality Index (ICA-PE) of Lake Chinchaycocha, Junín, Peru

The objective of the research was to determine the water quality index of Lake Chinchaycocha, which has faced pollution problems for several years. To do this, we worked with data from ten water quality monitoring points collected by the National Water Authority (ANA) during the period 2019-2023, after which the water quality index (ICA-PE) was calculated by analyzing a total of 12 parameters, using the Water Quality Standard (ECA) for water category 4 E1 (lagoons and lakes). The results of the physicochemical parameters indicated that the values of total nitrogen exceed the limits established in the ECA in 82% of the data obtained, pH in 13%, and phosphorus in 1%. In the evaluation of inorganic parameters, data from the LChin1S monitoring point showed that lead and zinc levels exceeded the values established in the ECA by 8% and 3%, respectively. Regarding the ICA-PE of the dry and wet seasons, it was determined that both present a good quality according to their averages and with the results obtained from the ICA-PE in a general way, it is concluded that Lake Chinchaycocha has a good water quality having total nitrogen as the main pollutant.

Steve Dann Camargo Hinostroza, Carmen Andrea Taza Rojas, Diana Lizet Poma Limache and Camila Jimena Poma Romero

Evaluation of Landscape Resources and Legal Protection Boundary Setting in Xinchang County, China

Landscapes are vital for ecological protection and cultural heritage, facing challenges from urbanization, agricultural modernization, and climate change. By setting legal boundaries, land use can be regulated to prevent unreasonable development and ensure the sustainable use of landscapes. This paper assesses the forest, geological, aquatic, cultural, and religious relic landscape resources of Xinchang County, Zhejiang Province, using the Analytic Hierarchy Process (AHP) and fuzzy evaluation methods to quantify their protection needs. The study finds that establishing nature reserves, ecological protection red lines, and historical and cultural villages can effectively maintain ecosystem stability and biodiversity, and protect cultural heritage. Legal protection has significantly improved forest coverage and water quality in Tianmu Mountain National Forest Park and Wozhou Lake Scenic Area, while Meizhu Ancient Village and Waipo Keng Village have excelled in cultural landscape protection. However, challenges such as inadequate law enforcement, low public participation, and insufficient funding hinder the execution of legal boundaries. Recommendations include strengthening law enforcement, raising public environmental awareness, and expanding funding sources. This paper provides a scientific basis and practical guidance for the formulation and implementation of landscape protection policies, contributing to the sustainable utilization and long-term protection of landscape resources in Xinchang County and other regions.

Ya Li, and Faridah Sahari

Bioremediation of Manganese by Thermophilic Bacterial Isolates of Tapt Kund, Soldhar, and Gauri Kund Hot Springs of Uttarakhand, India

Manganese (Mn) contamination in groundwater is a global concern due to its harmful effects. The high concentration of Mn2+ in humans creates memory issues, decreased fertility, appetite loss, sleeplessness, sperm abnormalities, and ‘Manganism’. In this study, the isolation of thermophiles was followed by their assessment for MIC (minimum inhibitory concentration) and Mn bioremediation. We have isolated a total of 11 Mn-resistant bacterial strains of thermophiles with the identification of their bioremediation potential from the Tapt Kund, Soldhar, and Gauri Kund hot springs of Uttarakhand, India. Out of 11 strains, three isolates (TA8, SA9, and GA7) were identified with the highest metal resistance properties for toxic Mn2+. The metal tolerance capabilities of the strains were evaluated through MIC and the metal biosorption rate was estimated by the live cells bioremediation through thermophilic bacteria. ICP-MS (inductively coupled plasma mass spectrometry) was used to assess the Mn2+ removal rate of bacterial bioremediation. It turned out that every strain exhibited promising bioremediation potential and proved Mn-resistant. The bacterial strain TA8 exhibits the highest MIC (600 µg.L-1.) with a bioremediation rate of 98.34% for Mn2+. The bacterial strain SA9 has a MIC value of 525 µg.L-1, with a biosorption rate of 77.74% for Mn2+. The bacterial strain GA7 has a MIC of 475 µg.L-1, with an efficiency rate of 61.17% for Mn2+ removal. The most promising strain of thermophilic bacteria for Mn2+ bioremediation is the TA8, which has demonstrated the highest potential (98.34%) out of all the tested strains. The findings may have public health implications, as reducing manganese levels in groundwater can help mitigate health risks associated with Mn exposure. Also, this research enriches our knowledge of microbial bioremediation and its potential applications in environmental management. Ultimately, this research could offer a novel, economical, and environmentally beneficial approach to managing metal toxicity

A. Patil, S. Devi, Y. Sharma, S. Singh, N. K. Prabhakar, S. Agrawal and Mamta Arya

Investigating the Effectiveness of Peanut Hull as Biosorbent of Lead (Pb) from Water

Lead contamination poses a major threat to health and environmental well-being. The remediation of this heavy metal from water sources is essential to safeguard health and ensure access to clean water. In this study, Peanut hull was used as a biosorbent for lead (Pb) removal from water. It focuses on optimizing various parameters important for lead removal. Statistical analysis, such as the Kruskal-Wallis test, was done to assess the significance of these parameters on lead biosorption, and an inverse variance weighting technique was employed to derive the weighted contribution of each variable for fixed Pb removal categories in the range of 80-100% and 80% (below). On analysis, it was found that factors such as pH and biomass dosage played major roles in lead removal. Furthermore, Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray Spectroscopy (EDS), were done to find out changes in the structural and elemental characteristics of peanut hull after lead sequestration. Overall, this study highlights the potential of peanut hull as a promising biosorbent for lead removal from water, thereby offering a sustainable solution to water contamination with heavy metals.

Mehak Verma and Sarita Sachdeva

Sustainability Evaluation of Waste Management Using RAPWASTE Method at the 3R Temporary Waste Disposal Site in Yogyakarta City

The waste problem has become a big problem in Indonesia as the population continues to grow. The daily amount of waste generated in Yogyakarta City is 303.13 tons.day-1, with the composition of the largest waste source, namely household waste, around 63.75%. This data shows that there is a need for improvements related to management; 3R Temporary Waste Disposal Sites is an alternative for reducing waste before it is transported to the final processing place. This research aims to understand performance and waste transportation management and evaluate the level of waste management and sustainability of waste management at 3R Temporary Waste Disposal Sites Nitikan Yogyakarta. This research was conducted on 99 respondents using a purposive sampling method; the data analysis used was the evaluation of waste transportation, analysis of incoming, managed, and unmanaged waste data, categorization of questionnaire data, evaluation of waste management performance and analysis of the sustainability of waste management using RAPFISH software. The research results show that waste volume management at 3R Temporary Waste Disposal Sites Nitikan is 941.15 kg.day-1, and compost production is 190.65 kg.day-1. Transport management is carried out using the Stationary Container System (SCS) and is carried out 2 times. The evaluation of waste management performance is moderate, with a total relative value of 15.4, based on studies on the technical sector, institutional sector, financial sector, and the area of community participation. Based on the attribute index in each sector, it is concluded that the sustainability status of waste sorting and management at 3R Temporary Waste Disposal Sites Nitikan is 79.03, or very sustainable.

Willis Muhammad Iqbal, Hashfi Hawali Abdul Matin and Prabang Setyono

Deep Learning Approach for Evaluating Air Pollution Using the RFM Model

Air pollution is a required environmental and public health issue in India, with multiple municipalities repeatedly ranking among the most polluted in the world. This study leverages large datasets to construct a predictive model for forecasting air quality trends using a novel approach that integrates the Recency Frequency Monetary (RFM) model with deep learning. The research aims to efficiently quantify pollution events frequency and assess the impact of air quality variations on public health, offering a more flexible and adaptive system for air quality monitoring. As a result, a large volume of air quality data provided by RFM (Recency, Frequency, and Monetary) will be flexible and frequently handled and analyzed. In this research, the performance of the integrated RFM technology is examined using Python and Google Colab, and the simulation results are compared to air pollution information from neural networks for structures in additional data using existing air quality monitoring systems in India. Performance examination of both regression and classification techniques in RFM. The execution of RFM can be one of the models and its potential to enhance air quality monitoring and urban sustainability

Jannah Mohammad and Mohammod Abul Kashem

Systematic Review of Phytoremediation: Efficacy of Aquatic Plants in Wastewater Treatment and Pollutant Removal

The swift process of industrialization and urbanization in our society has resulted in a growing issue of wastewater production, which presents a substantial danger to ecosystems and human well-being. This study examines the efficacy of aquatic plants in wastewater treatment by using their innate ability to remove pollutants. Water hyacinth (Eichhornia crassipes), water lettuce (Pistia stratiotes), and duckweeds (Lemnaceae) are types of aquatic plants that have been thoroughly researched due to their capacity to cleanse domestic, industrial, agricultural, and wastewater. This study encompasses a range of studies completed from 2014 to 2024, which investigate the efficacy of different aquatic plants in eliminating contaminants and provide insights into the specific mechanisms employed by these plants. Research has revealed remarkable findings, indicating that specialist plants can eliminate pollutants, including nitrogen, phosphate, and heavy metals, with an efficiency of up to 100%. Furthermore, the incorporation of these plants into wetlands and natural purification systems has been demonstrated to enhance the purification process by stimulating increased biomass production and the absorption of noxious gases. Future research should give priority to genetically modifying plants to enhance their capacity for absorbing contaminants and to develop integrated systems for treating wastewater. In summary, this study showcases the capacity of aquatic plants to serve as a highly effective and eco-friendly substitute for wastewater treatment. Implementing phytoremediation techniques can enhance the sustainability of water management practices and aid in safeguarding our ecosystems and the health of society

Mangesh Jabade and Jasneet Kaur

Geospatial Analysis of the Relationship Between Land Surface Temperature and Land Use/Land Cover Indices: A Study of Raiganj Municipality, West Bengal, India

The present study is focused on the estimation of Land Surface Temperature (LST) and its relationship with three Land Use and Land Cover (LULC) indices--Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI), and Normalised Difference Built-up Index (NDBI) in Raiganj Municipality, India. Landsat-5 TM (2001 & 2011) and Landsat-8 OLI (2021) satellite images were used, processed, and analyzed in the ArcGIS. The study observed that the values of LST and NDBI were increased by +0.9?C and +0.71, and the values of NDVI and NDWI were decreased by -0.20 and -0.34 during 2001- 2021. The highest LST is observed over the built-up spaces and the lowest over vegetation cover and water bodies. The result indicates LST has a significant positive correlation with NDBI and a negative correlation with NDVI and NDWI. LST is increased due to dramatic changes in LULC especially in unplanned infrastructural development and losses in green and blue spaces.

Bapi Sarkar, Sribas Patra and Mallikarjun Mishra

Thermodynamic Modeling Studies on Biosorption of Reactive Amoxicillin Antibiotic by Pithophora Macroalgae in Aqueous Solution

Antibiotic removal poses a serious risk to the environment due to its intricate structure. Consequently, scientists are developing new and efficient techniques to remove antibiotic compounds from wastewater. The goal of this study is to employ green Pithophora macroalgae to remove the antibiotic amoxicillin (AMX) from a water-based solution. With a focus on understanding the process, this study assesses the application of reacting AMX biosorption on the biomass of Pithophora algae in aqueous solutions using thermodynamic modeling. The determined thermodynamic characteristics show that an endothermic process is used in the biosorption of the antibiotic AMX, considering that AMX has a positive electrical charge of ?Hº at 49.796 KJ.moL-1. As ?Gº has a positive charge (2.982 kJ.moL-1, 3.718 kJ.moL-1, and 4.793 kJ.moL-1) for AMX at (298 K, 303 K, and 308 K, respectively. This positive result indicates that the reaction is not feasible or spontaneous. The decrease in chaos at the liquid/solid interface caused by AMX biosorption on Pithophora macro algae is reflected in the negative charge of ?Sº, which was -176.735 kJ.moL-1. The effect of temperature on the biosorption of AMX was investigated for different initial AMX concentrations. At a lower temperature of 298 K, the AMX molecules were more likely to diffuse into the internal pores of the Pithophora algae. This suggests that the diffusion rate of the adsorbate (AMX) across the bulk and pore boundaries of the biosorbent particles may be increased at lower temperatures. The findings of this study indicate that the biomass of the macroalgae Pithophora is a valuable biosorbent for the biosorption of AMX antibiotics, and it may have potential applications in the treatment of wastewater.

Murad M. Khamayseh and Rana Kidak

A Comprehensive Study on the Environmental Features of Green Buildings in Dhaka, Bangladesh: Prospects, Challenges and Mitigation Strategies

The construction industry has played a significant role in causing environmental degradation, primarily due to its substantial energy use. Focusing on green building development projects is gaining momentum as a sustainable solution for mitigating environmental challenges. This study assessed several environmental features of 22 green buildings in Dhaka, the capital of Bangladesh. In addition, the challenges were discussed, and mitigation strategies were recommended. The Leadership in Energy and Environmental Design (LEED) certification technique is widely acknowledged and globally accepted as the leading green building certification standard. Three LEED versions, v3 for new construction and major renovations and v4 and v4.1 for building design and construction, were investigated. Seven environmental features of three versions, including rainwater management, renewable energy, enhanced commissioning, optimized energy performance, construction and demolition waste management, water use reduction, and water efficient landscaping, were considered in this work. A survey questionnaire was prepared to receive information about these LEED-certified (or applied for certification) buildings. The findings of our study suggested that the general trend for seven environmental features of the selected green buildings was positive except for renewable energy, where 72.72% of buildings were in ‘very poor’ condition. Regarding rainwater management, enhanced commissioning, and optimized energy performance, 40.91% of buildings were in ‘very good’ condition. Despite satisfactory responses for several environmental features, the survey found that renewable energy integration remains challenging for all buildings. Solar energy should be extensively employed to enhance energy utilization efficiency, reduce energy demand, and minimize environmental impact. It was suggested that a few challenges, including the government’s lack of action and initiatives, financial incentives, investor hesitation, and knowledge gaps, must be overcome to create a truly green building market in Bangladesh. Bridging this disparity requires policy reforms, public awareness, industry development, and capacity building. This study provides a basic understanding of the green building situation and guides future research and policy initiatives to accelerate Bangladesh’s commitment to sustainable development goals.

Md. Sultanul Islam, Nafis Ibna Oli and Md. Hasibul Hassan

Enabling Environment for Climate-Smart Agriculture: A Critical Review of Climate Smart Practices from South Asia and Sub-Saharan Africa

In South Asian and Sub-Saharan African nations, climate change offers numerous hurdles to growth and development. These regions are susceptible to climate change due to their vast population reliance on agriculture, high demand for natural resources, and comparatively limited strategies for coping. Reduced food grain yields, crop losses, feed scarcity, lack of potable water for livestock during the summer, forceful animal migrations, and severe losses in the poultry and fishery industries have all been documented, posing a threat to the lives of the rural poor. As global food security and agricultural productivity become increasingly vulnerable, the focus has shifted towards adopting climate-smart agricultural practices and techniques. The present study discussed the need to identify and prioritize regionally evolving climate-smart farming practices and the enabling environment required for CSA uptake. The popular CSA practices in South Asia and Sub-Saharan Africa are crop rotation, cultivation of drought/flood-tolerant crops, legume intercropping, changing planting dates, rainwater harvesting, agroforestry, micro-irrigation technologies, minimum tillage, and integrated crop-livestock farming. A solid institutional structure, policy environment, infrastructure, agricultural insurance, climate information services, and gender and social inclusion provide the required enabling environment to alleviate farmer issues, lower CSA adoption obstacles, and improve operational sustainability. Highlights of the study are: This study examines how climate-smart farming practices are evolving in South Asia and SubSaharan Africa. We used a systematic approach to categorize and characterize agricultural adaptation alternatives to climate change. Our specific goals are to gain knowledge of the CSA adoption-enabling environments and the climate-smart agriculture practices employed in South Asia and Sub-Saharan Africa

Arpita Ghosh, Puneet Sharma, Arnab Mondal and Surajit Mondal

Studies on the Effect of the Zinc Oxide Nano Additives along with Rice Bran Biodiesel Diesel Blends into CI Engine to Reduce Pollution

Pollution is a major problem for urban cities and their associated industries. The pollution caused by industries is mainly because of the burning of fossil fuels. Some of the pollutants can be controlled by plantation, but the oxides of nitrogen cannot be controlled only by planting trees. Some extra efforts are required to minimize pollution associated with the normal functioning of the shop floor of the industries concerned but not affecting its performance. The fuel that is best for industrial use is the need of the hour. In this study, zinc oxide nanoparticles are used as an additive to the rice bran blended biodiesel and analyze the combustion, performance, and emission parameters in the single-cylinder four-stroke engine water-cooled powered by diesel normally utilized in industries at a constant speed and compression ratio. The available fuel alternatives for testing consist of multiple combinations of diesel fuel and RB biodiesel, each with varying proportions. Furthermore, many gasoline mixes additionally have Zinc Oxide nanoparticles at a concentration of 30 parts per million (ppm). The findings suggest that the brake-specific fuel consumption of Rice bran biodiesel combined with Zinc oxide nano additive exhibits a consistent enhancement, but the brake thermal efficiency declines in comparison to diesel fuel. The concentrations of hydrocarbon (HC) and oxides of nitrogen (NOX) have been reduced. However, there has been a small rise in carbon dioxide (CO2) and carbon monoxide (CO). When rice bran biodiesel fuel combined with Zinc Oxide nano additive was used, an abnormally high exhaust gas temperature (EGT) was detected. According to this research, the addition of Zinc Oxide nano additive to rice bran biodiesel blends improves performance and decreases the noxious exhaust emissions generated by diesel engines.

Abhijeet Maurya, Bhanu Pratap Singh and Ajay Kumar Sharma

Biomonitoring of Bedog River Water Quality Using Dragonfly Diversity as Bioindicators in Yogyakarta, Indonesia

The quantity of contaminants being released into rivers is rising in direct correlation with the growth of the human population. Bedog River is a tributary located in the vicinity of Mount Merapi. This river flows through agricultural, residential, and cattle sectors, making it easier to detect river contamination. The objective of this study is to evaluate the water quality of the Bedog River. The research employs a methodology that evaluates water quality by considering biological indicators, specifically the existence of dragonfly species, with the analysis of other chemical and physical properties in river water. The water quality research findings indicate that the physical and chemical characteristics remain satisfactory, with the water falling into the moderately polluted category. It also meets the water quality criteria outlined in PPRI No. 82 of 2001, specifically the class 2 threshold. A total of 23 Odonata species were identified. The upstream section, as indicated by the presence of Neurobasis chinensis florida and Heliocypha fenestrata, which are endemic, along with Macrogomphus parallelogramma, which is rare, is considered an optimal habitat capable of supporting sensitive dragonfly species. The dragonfly variety index in the Bedog River is relatively high, with values of 2.08, 2.79, and 1.47 for the upstream, middle, and downstream sections, respectively. The Pearson correlation coefficient indicates a strong positive correlation of 0.961, while the significance level of 0.179 suggests a statistically meaningful association. The findings highlight the potential of using dragonflies as bioindicators for long-term monitoring of river health and pollution levels. This study contributes to the understanding of how water quality impacts biodiversity and provides a basis for future research and river management practices. This research fills a gap by integrating biological indicators with traditional water quality assessments in a specific regional context. It provides new insights into the relationship between water quality and dragonfly diversity, offering valuable information for environmental monitoring and conservation efforts.

Sapta Suhardono, Muhammad Amin Sunarhadi, Iva Yenis Septiariva, Hening Triandika Rachman and I. Wayan Koko Suryawan

From Preservative to Environmental and Health Hazards: A Review on Diverse Applications, Health Impacts and Detection Methods of Paraben(s)

Paraben(s), or p-hydroxybenzoate derivatives, have been extensively used as preservatives in catalogs of products for decades. The chemical(s) of the group are well known for their water solubility, chemical stability, and low production costs. Additionally, these synthetic organics can be used as supplements in cosmetics, packaged foods, pharmaceuticals, and many other products requiring prolonged shelf lives. However, recent reports of parabenmediated endocrine disruptions, allergic responses, cancer, loss of fertility, and respiratory disorders are alarming and are the signs of growing health and environmental hazards. The unregulated disposal of packaged products supplemented with parabens and unintended uses may increase the environmental burden in the time to come. Recent studies exploring the health hazards associated with the use or consumption of compounds have provided insight into the underlying mechanisms of action. The paraben(s) are assimilated through two routes: oral administration and skin permeation. The ability to detect compounds in different environmental habitats with robust and specific techniques is important due to the unintended public health burdens of these compounds. This review presents the recent findings on the health burden of the compounds, fallacies in detection, and chronological advancements in the detection of paraben(s). This review assesses the impact of the increasing use of parabens on different cohorts, health hazards, and the need to develop more robust and accurate tools for detecting parabens in different environments.

Pooja Upadhyay, Pammi Gauba and Ashwani Mathur

Enhanced Microplastics Removal from Paper Recycling Industry Wastewater Using Membrane Bioreactor Technology

Urbanization and industrialization have caused a ubiquity of microplastics in the environmental system. An effective elimination technique is required for microplastics from industrial effluent and other wastewater systems due to its growing threats to the ecosystem and human health. The present study endeavors to evaluate the potential of the membrane bioreactor (MBR) technique in the removal of microplastics from paper recycling industry wastewater effluent. The effectiveness of the MBR system was evaluated relative to the conventional method used in industry for wastewater treatment. The paper recycling industrial effluent consists of 148 pieces/L of microplastics. The conventional treatment plant’s effluent is used as an MBR system influent, and MBR removes 64.9% of the microplastic present after the conventional treatment plant, which is ascribed to the complementary actions of membrane filtration. MBR technology offers a reliable and workable plan to decrease the quantity of microplastics in industrial wastewater. It also offers a scalable solution that is consistent with sustainable environment management.

Savita Kalshan, Rajesh Dhankhar, Shivani Narwal, Amit Chhillar, Manju Desondia, Poonam Yadav and Sashi Yadav

Exploring Institutional Climate Capacity Assessment Indicators of Community-Based Organizations in the Conservation Projects: A Participative Approach

The present comprehensive study seeks to evaluate the institutional climate capacity of Community-based Organizations (CBOs) involved in coastal ecotourism conservation projects along the Maharashtra coastal region in India. The primary objective is to understand the community interactions, organizational structures, and adaptive capacities of CBOs in the face of climate change, utilizing an integrated approach through participative and stakeholder interaction. The research methodology employed through the integrated investigated assessment, which includes- focused group discussions (n=06) and a survey of key informants’ interviews and community participants (n=143), additionally were added to this set of data combined for a total of 204 respondents, to comprehensively evaluate the institutional climate capacity of the CSOs engaged in coastal ecotourism projects. The findings identify key dimensions influencing CBO-led conservation projects, emphasizing the importance of different actors’ interplay and processes reflected through the communities. Notable strengths include effective communication, inclusive planning, and budgetary processes contributing to climate action orientation, emphasizing strengths in communication, inclusive planning, and budgetary processes. Socially excluded groups actively participate, underscoring the significance of their involvement for project success. Integrating socio-cultural factors into climate change planning is highlighted, emphasizing the need for quantitative research in this area. These identified key dimensions influence the CSO’s institutional climate capacities.

Ravi Sharma and Vinayak Patil

Larval Age-Dependent Parasitization Performance of Cotesia flavipes on Sesamia inferens

Cotesia flavipes is an important hymenopteran larval parasitoid that belongs to the family Braconidae. Its usage in pest management strategies is promising due to its parasitic impact on the larval stage of lepidopteran pests. The current investigation aims to determine the optimal host age for the parasitoid’s mass proliferation and augmentative releases. The experiments showed that the female C. flavipes parasitizes all larval age groups of Sesamia inferens. Among all the larval ages, C. flavipes preferred second to third instars for parasitism during the spring (up to 90%) and kharif (up to 80%) seasons. There was no substantial difference in the development period between stinging, cocoon production, and the adult emergence of parasitoids. The age of the host has a substantial impact on adult longevity, with females taking longer than males. Thus, larval instars (second and third) are also recommended for high-quality mass-rearing larval parasitoids, especially C. flavipes, due to their strong parasitism and high net reproductive rate. Therefore, the second and third instars of S. inferens will recommend the mass rearing of C. flavipes and the release of these parasitoids in the field as a successful bio-control program.

V. K. Sonawane, S. K. Gharde, K. S. Ghodekar, A. M. Raut and Amine Assouguem

Sustainable Biomass Conversion: Impact of NaCl Pretreatment on Cabbage Waste

Vegetable waste, particularly cabbage waste (CW), is a valuable raw material for various applications, including bioenergy production, owing to its high lignocellulosic content. However, the potential of lignin in biomass conversion remains largely untapped. This study is significant as it aims to optimize the pretreatment of CW biomass using different chemical reagents and concentrations (sulphuric acid, acetic acid, sodium hydroxide, potassium hydroxide, and sodium chloride) at 12 and 24 h for 50, 75, and 100°C. In this study, a novel pretreatment approach was introduced with 2% NaCl at 50°C for 12 h for CW biomass. At this optimized condition, 2% NaCl led to 28?lignification for CW biomass. The study examined the impact of pretreatment efficacy on biomass characterization using SEM, XRD, and FTIR analytical techniques. Results showed that 2% NaCl pretreatment significantly improved digestibility, increased surface area and porosity, altered the crystallinity index, and confirmed delignification through shifts in peaks and intensity changes. Furthermore, reduced hemicellulose and reduced lignin were noted in comparison to untreated biomass. This reassures us of the effectiveness of the pretreatment method. This promising result underscores the feasibility, economics, sustainability, and environmental friendliness of this pretreatment method. The method not only offers a cost-effective solution but also aligns with the principles of sustainability and environmental protection, thereby reassuring the researchers about its potential for various industrial applications.

Sunder, Sangita Yadav and Jitender Pal

Expository Assessment of Air Quality Scenario with Sentinel-5 Precursor TROPOMI Explorer Sensor

Air pollution is the atmospheric state in which the concentration of specific elements has adverse impacts on human health as well as the environment, including global warming, transportation disruptions, acid rain, and ozone layer depletion. Nowadays, a large portion of the world’s population lives in urban areas, where population growth and the increasing number of vehicles have significantly worsened air quality. Clean air is essential for the health and well-being of any region’s environment and its inhabitants. Henceforth, the primary focus of this research endeavor is to meticulously scrutinize the levels of key air pollutants, notably nitrogen dioxide (NO?) and sulfur dioxide (SO?), leveraging satellite remote sensing data obtained from TROPOMI EXPLORER across a network of monitoring stations dispersed throughout Lucknow City. Additionally, it aims to meticulously dissect groundbased air quality monitoring data to validate and amalgamate the observations derived from satellite technology. Furthermore, it analyzes the distribution of concentrations of primary air pollutants, encompassing NO?, SO?, and PM??, within Lucknow City, juxtaposing them against the stringent benchmarks stipulated by the World Health Organization (WHO) for air quality standards. Moreover, it endeavors to ascertain the deleterious health ramifications of air pollution by correlating air quality metrics with health outcomes among the denizens of Lucknow City through a meticulously crafted questionnaire survey. The scrutiny of satellite imagery unveiled a conspicuous escalation in the concentration of air pollution parameters vis-à-vis the WHO’s prescribed thresholds, portending consequential adverse ramifications for both the environment and human health.

Abhay Yadav, Divya Srivastava and Vivek Mathur

Flood Frequency Analysis of Kadamaian and Wariu Rivers in Kota Belud, Sabah, Malaysia

Flood frequency analysis is crucial for understanding flood risks in specific regions. This study applied the Gumbel Distribution Method to analyze flood frequency using river discharge data from the Kadamaian and Wariu Rivers in Kota Belud, Sabah, Malaysia. The analysis involved data collection, parameter estimation, goodness-of-fit testing, and determination of annual recurrence intervals (ARIs). The study found that the ARIs for the Kadamaian and Wariu Rivers are 50 years and 30 years, respectively, highlighting the need for targeted flood mitigation strategies in these areas. These findings emphasize the higher flood risk in the Kadamaian River basin, necessitating more robust flood control measures compared to the Wariu River basin. The Gumbel distribution provided accurate flood frequency estimations validated by the Kolmogorov-Smirnov test and correlation coefficient (R2). The calculated ARIs offer valuable insights for flood hazard assessment and contingency planning. These findings underscore the importance of accurate flood frequency analysis in enhancing flood mitigation strategies and disaster preparedness. It is recommended that local authorities incorporate these results into flood management and urban planning initiatives.

K. Sharir, A. Saidin and R. Roslee

Spatial Analyses of Reliability of Solar Power in the Western Part of Iraq

This study presents a comprehensive statistical and meteorological investigation of the western part of Iraq, specifically focusing on the Anbar governorate. To facilitate a detailed analysis, the study area was divided into four sections corresponding to the geographical directions: north, south, east, and west. The primary objective was to evaluate the potential for solar power exploitation in this region by analyzing a wide range of physical and meteorological data. The study encompassed various parameters including solar irradiation, air temperature, and other climatic variables that influence solar power generation. The physical and meteorological data demonstrated a strong correlation in most cases, indicating a consistent trend across the study area. However, two variables— diffuse horizontal irradiation and air temperature—showed inverse trends, deviating from the general pattern. These deviations were carefully analyzed to understand their impact on solar power potential. Furthermore, the analysis revealed that regions with elevated terrains, particularly in the western and southern parts of the Anbar governorate, exhibited higher solar power gains. This finding is significant as it highlights the influence of topography on solar energy potential. The combination of statistical and meteorological data provided a robust framework for assessing the feasibility of solar power projects in the region. The results of this study indicate the promising potential for solar power generation in the Anbar governorate. The integration of statistical and meteorological analyses offers valuable insights for policymakers and stakeholders involved in renewable energy planning and development. This investigation paves the way for future research and practical applications aimed at harnessing solar energy in western Iraq.

Raid Khider Salman, Sabah Sultan Farhan, Muneer Naji Al-Falahi and Thaer Eyada Mohammed

Effect of Biochar and Silicon with Different Phosphorus Levels on Maize Yield and Soil Chemical Properties

Silicon fertilizer combined with biochar improved the utilization of phosphorus fertilization applications. The experiment was carried out with eight treatment combinations with varying proportions of rice husk biochar, silicon, and phosphorus in a completely randomized design with 75 days of growth in the greenhouse. To identify the optimum rate of phosphorus combined with rice husk biochar and Si for maximizing maize yield and soil chemical properties. This experiment showed that the application of biochar combined with silicon has the potential to reduce the amount of phosphorus fertilizer requirement. The application of 5 t ha-1 RHB + 100% Si + 25% TSP showed the highest pH compared to other treatments. While application of 2.5 t ha-1 RHB + 100% Si + 100% TSP showed the highest exchangeable K, Ca and Mg. Moreover, the application of 5 t ha-1 RHB + 100% Si + 100% TSP recorded the highest dry biomass compared to other treatments. Lastly, the application of 5 t ha-1 RHB + 100% Si + 50% TSP Showed the highest cob length(cm), cob weight(g), no of grain per cob, and grain yield (t.ha-1) compared to other treatments. The combined application of biochar and silicon, along with 50% phosphorus, is recommended for improving maize yield and soil health in greenhouse conditions.

Muhammad Wasil Bin Abu Bakar, M. K. Uddin, Susilawati Kasim, Syaharudin Zaibon, S. M. Shamsuzzaman and A. N. A. Haque

Management of Grapevine Fungal Diseases by Using Antagonistic Endophytes - An Environment-Friendly Approach

Grapevine (Vitis vinifera L.) is one of the major crops grown commercially throughout the world. In recent years, there have been major losses to grapevine production due to the challenges caused mainly due to fungal diseases like downy mildew, powdery mildew, grey mold, black rot, and anthracnose. In the last few decades, rampant chemical fertilization and bio-magnification of hazardous chemicals have posed a threat to human health and destroyed the health of the soil as well as crops. For effective management of these fungal diseases of grapes, nowadays, many researchers are conducting various studies on endophytes, which are proven to be better bio-control agents to suppress the growth and development of grapevine phytopathogens. Endophytes are eco-friendly, effective, and easy to apply at field levels, making endophyte-based formulations suppress the growth and development of grapevine pathogens without causing any detrimental effects to the beneficial micro-organisms present at the rhizospheric zone of soil and host plants as compared to the traditional fungicides usage. It also competes with these pathogens for nutrition, space, and colonization. It helps in the production of secondary metabolites with antifungal properties for preventing the growth of fungal pathogens that cause damage to the grapevine crop. It also induces a defense mechanism in grapevine crops against diseasecausing fungal phytopathogens. In this review article, biocontrol mechanisms of endophytes and their potential application in the management of grapevine fungal diseases have been discussed.

Akhilesh Chandrapati, Jay Prakash Singh, Yenda Damodhara Rao, Meenakshi Rana, Somnath K. Holkar and Seweta Srivastava

Full Issue

Acceptance Rate and Publication Time

Acceptance rate: 30-40 %
Preliminary Scrutiny: 10-15 days from submission
Initial Acceptance Letter: 7-8 weeks from submission
Prepublished Paper: 4-6 weeks from final acceptance
Final Publication: 7-10 months from final acceptance

Journal Metrics

Scopus CiteScore (2023): 1.2
Scopus SJR Index (2024) = 0.234
SJR H Index (2024) = 20
Index Copernicus International (2023) = 132.21
NAAS Rating (2024) = 5.33

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