Decision-making under uncertainty refers to a dilemma when a decision-maker is aware of a variety of potential natural states but lacks adequate information to assign any probabilities of occurrence to them. The uncertainty related to the input parameters is one of the main issues in the majority of decision-making situations. Uncertainty may produce some irrational results, which could make the decision-making process even more challenging. To overcome this challenge, a fuzzy extension of Best-Worst Method (BWM) has been proposed, using trapezoidal fuzzy sets, to combine the advantages of a reduced number of pair-wise comparisons and easy handling of ambiguity. The criteria and alternatives have been evaluated by the proposed Trapezoidal Fuzzy Best-Worst Method (TrFBWM), where the weight of each element is represented by a Trapezoidal Fuzzy Number (TrFN). To verify the coherence of judgment, the consistency ratio is evaluated for TrFBWM. The proposed method is then applied to the location selection of a water treatment plant along the bank of the Brahmaputra river in Assam. The obtained results are compared to one previous work and found that the outcomes of the proposed method indicate a good agreement with that. The outcomes of the study provide useful insights for selecting a suitable location for a surface water treatment plant which can also be extended to other service facilities.

Urban morphology impacts micro-climates, solar energy absorption, air flow, wind patterns, energy consumption, and air pollution concentration. Temperature control in public spaces reduces heat island formation, while ventilation corridors potentially improve air quality. However, despite the literature on airflow and urban tall buildings providing valuable insights, further research is needed to understand the complex relationship between airflow patterns and urban high-rise buildings. This research should consider factors such as landscape types, building height, density, and orientation. This research aims to examine airflow patterns in high-rise buildings that are influenced by nearby land use, which can impact ventilation and climate comfort. To investigate these objectives, we utilized the Universal Thermal Climate Index (UTCI) and Predicted Mean Vote Index (PMV) by conducting simulations using ENVI-met software. The results revealed that buildings with narrower widths have better wind warded front conditions, while those with an unfavorable wind angle or a narrow facade are less comfortable. Public spaces that face the wind benefit from improved ventilation. It is essential to consider the optimal arrangement, ventilation, and height of buildings to ensure the favorable airflow. Factors such as the placement of trees, the use of porous walls, water features such as fountains and sprinklers, and the local climate all contribute to creating better wind conditions. Investigating the reciprocal interaction between the landscape, high-rise buildings, and climate comfort could be considered in future research.

Monitoring and managing environmental problems, particularly those impacting human health such as noise and air pollution, are essential. However, the current implementation has certain limitations that need improvement. In the case of noise pollution, accurately computing noise levels requires considering traffic noise propagating in all directions, necessitating the involvement of a 3D building model. Existing methods using raster cells and noise contours are insufficient in achieving high accuracy. To overcome this, we propose integrating a voxelisation approach and 3D kriging, enabling the depiction of traffic noise values for each voxel. In the context of air pollution, wind movement plays a significant role in the dispersion of contaminants. The current practice involves a random selection procedure for wind simulation within the model discretisation. However, we suggest replacing this randomness with a voxel-based model, which not only improves accuracy but also reduces computing time. Thus, the voxel-based model represents the building model in a wind computation environment, facilitating more realistic wind simulation results. This study demonstrates the applicability of the voxelisation technique in two different environmental modeling contexts using the building model of the city building modeling standard. The level of detail (LoD) in the represented building model differs between these approaches. For traffic noise, a low LoD (LoD1) is sufficient to depict exterior buildings accurately. However, for wind simulation, a higher LoD (LoD2) is necessary to accommodate the complexity of buildings and determine appropriate voxel sizes. In conclusion, the proposed improvements in the form of voxel-based modeling techniques offer enhanced accuracy and efficiency in environmental monitoring. The findings of this study have implications for improving the management and reduction of environmental problems, ultimately benefiting human health and well-being.

Paringin District is one of the coal mining areas in South Kalimantan with the exploitation method of open pit mining. This activity opens rock layers containing sulfur, reacting with water and oxygen, spreading sulfide acid into the environment. Analysis of the water quality of the Post-mining Lake in Paringin District is needed based on the biological parameters. The objective aims to analyze the water quality of the Post-mining Lake, Paringin District, based on plankton’s abundance, diversity, and dominance. This research was located in Post-mining Lake, PT. Adaro Indonesia. Data were taken at three sampling points in the pit pond and three depths. Data was taken from 2019 to 2021 using plankton net and analyzed using the enumeration method. The data was processed using the diversity index, dominance index, and saprobic index. Phytoplankton and Zooplankton abundance were dependent on three different depths (p-value>0.05). The most abundant phytoplankton species in all stations was Oscillatoria sp. (>90%) while Nauplius sp. (>30%) for zooplankton. Rainfall in the study area affected the number of individual species very weakly. The highest dominance value of phytoplankton and zooplankton was recorded around the end of 2019 to early 2020 as well as a saprobic index and diversity. Crustacea class considerably exists in all sites, which is Nauplius sp. and Daphnia sp. This situation proved there was a recovery of the plankton population in the lake, no algae blooming and a balance between nutrients and plankton population. In fact, the aquatic habitats are ready to accommodate large ecosystems.

This work explores the potential toxicity of agricultural waste materials, specifically date palm seeds and palm fronds, on plant growth and health. These waste materials have shown promise as bioadsorbents for water purification, but their impact on plants needs to be understood. Toxicity assessments are crucial to ensure safe utilization and prevent negative effects on agricultural systems and ecosystems. Date palm seeds and palm fronds contain chemical compounds that can have allelopathic properties and influence neighboring plant growth. Experimental methods were employed to evaluate the phytotoxic effects of these materials, including germination assays and root growth inhibition tests. The results indicate that upon adsorption of PO4, palm leaves exhibited a significant enhancement in germination, leading to a remarkable increase of up to 371%. This outcome strongly emphasizes the effectiveness of palm leaves as vegetable fertilizers, highlighting their potential in agricultural applications. These findings contribute to understanding the phytotoxic potential of agricultural waste materials and developing sustainable utilization strategies.

The article aims to assess radon concentration in various water samples, revealing levels ranging from 0.53 Bq/L to 4.68 Bq/L. Radon, specifically the isotope 222Rn, is a naturally occurring radioactive gas formed during the decay of the 238U decay series, originating from the breakdown of 226Ra. This gas is commonly found in rocks, soil, natural gas, and groundwater. Exposure to airborne and waterborne radon can increase the risk of certain cancers due to human radiation exposure. The primary Aim of this study was to assess the concentration of radon in water samples collected from diverse regions of Morocco, particularly the Midelt province and the Draa-Tafilalt region located at coordinates 32° 40' 48″ North, 4° 44' 24″ West. For this purpose, Solid State Nuclear Track Detectors of the LR-115 variety were used. The evaluations of annual effective dose equivalents exhibited a range spanning from 11.51 to 1.30 μSv/y, showcasing a consistent pattern of decline. Correspondingly, projections of excess lifetime cancer risk encompassed a spectrum from 4.00 to 1.98. Significantly higher risks were associated with samples S1 and S2, while notably lower risks were tied to S14 and S15. It is worth noting that all the water samples subjected to analysis registered annual effective doses that fell within the global average level recommended for ingestion exposure dose values (0.23 mSv/y) by the United Nations Scientific Committee on the Effects of Atomic Radiation. Given these results, there seem to be no radiation risks from radon gas in the study area.

Several studies have explored the utilization of soil microorganisms, to address the environmental issues associated with glyphosate use and enhance crop yields. In our investigation, screening on Agar plate and broth medium  Luria Bertani was carried out after isolating bacterial strains from rhizospheric agricultural soil in Mascara,  Algeria, to biodegrade glyphosate, following that by testing the Plant Growth-Promoting Rhizobacteria and evaluate the effects of glyphosate on these proprieties. Our findings indicate that five bacterial strains exhibited growth in the presence of glyphosate concentrations up to 25 mg/ml, beyond this concentration the strains have developed tolerance. Following a partial examination of the 16S rRNA sequences, the bacterial strains were identified as belonging to the genus of Enterobacter. After 10 days of incubation with the glyphosate, Phosphate solubilization decreased in broth and agar Pikovskaya medium and the bacterial strains synthetized less of indole-3-acetic acid compared to the control, indicating the impact of glyphosate on these outcomes, high concentration of glyphosate inhibited nitrogen fixation, and various doses of glyphosate were found to restrict the growth of biofilms in these strains. The results of HPLC examination of secondary metabolites revealed that the primary degradation products of glyphosate in all strains were Sarcosine and Glycine. So, it seemed that the strain could both biodegrade glyphosate and use it for growth ,while also possessing rhizobacteria properties that promote plant development, enabling the use of the strains in the bioremediation of glyphosate-contaminated soils.

Phenols have attracted global interest in the sphere of environmental management due to their potential toxicity on human health. This study determined concentrations of three priority phenolic compounds in effluent and water of a local textile industry in Abeokuta, Nigeria.  During tie-dye production, triplicates of effluent, well water, stream and control water were collected three times from five points to give a total of forty-five samples. Physicochemical parameters of samples including temperature, pH, electrical conductivity (EC), total suspended solids (TSS) and total dissolved solids (TDS) were determined according to standard methods while the concentrations of the priority phenolic compounds (4-nitrophenol, 4-chloro-3-methylphenol and 2, 4-dinitrophenol) were determined using High Performance Liquid Chromatography equipped with Ultra-Violet detector (HPLC/UV). Data obtained were subjected to descriptive (mean and standard deviation) and inferential (ANOVA) statistics. pH, EC and TSS of effluent and water samples were higher than the permissible limits of World Health Organization (WHO) and Federal Environmental Protection Agency (FEPA) while temperature of the effluent samples and TDS of the well water samples were within standard values. Higher concentrations of the priority phenolic compounds occurred in effluent than water samples but 4-nitrophenol was below detection limit (DL) in water samples. Concentrations of 4-nitrophenol, 4-chloro-3-methylphenol and 2,4-dinitrophenol in effluent exceeded stipulated standard of WHO (0.01 mg/L) and water samples. High concentrations of phenols in water bodies at the local textile industry suggest uncontrolled discharge of effluent from the industry which could eventually reach surface and ground water with potential significant health implications to the populace.

Artificial neural networks (ANNs) simulate an anaerobic co-digestion process of Organic Fraction of Municipal Solid Waste (OFMSW) and bio-flocculated sludge for a mesophilic lab-scale semi-continuous feed reactor. The operational, substrate quality and process control parameters such as Organic Loading Rate, Hydraulic Retention Time, pH, VFA/Alkalinity ratio and Total Solids are input variables and methane yield and Volatile Solids removal are outputs for ANN modelling. The lab-scale experimental results are used to develop a prediction model using fitting application for ANN. The network architecture was optimized to achieve accurate predictions, resulting in a 5-19-2 architecture for methane yield and a 5-17-2 architecture for %VSremoval. The training was performed using the Bayesian Regularization (trainbr) algorithm, leading to high coefficients of determination (R2) of 0.953 and 0.978 for methane yield and %VSremoval, respectively. The results demonstrate the effectiveness of neural network-based modelling in capturing complex relationships within the methane yield process, facilitating accurate prediction of crucial output parameters.

This study was undertaken to evaluate concentration of Uranium (U) in the drinking water of the Tonk district of Rajasthan (India). The main objective of the study is to determine the distribution of Uranium concentration and the geochemical behavior of Uranium in pre-monsoon (PRM) and post-monsoon (POM) drinking water samples. Uranium was measured by LED fluorimeter. Total 318 drinking water samples were collected for both seasons. It is observed that the water quality of all the samples is within the limits prescribed by WHO (30 µg/L) except a few, and can be used for domestic purposes. The Uranium concentration was found to be in the range 0.21 to 173.72 µg/L with a mean value of 8.58 µg/L in pre-monsoon and 0.21 to 162.34 µg/L with a mean value of 11.22 µg/L in post-monsoon samples. The geochemistry of the study area shows rock-water interaction. The order of average anionic concentration is found to be HCO3 – > Cl – > SO4 2– > NO3 –. Although no definite trend of seasonal variation in the concentration of U was observed, large samples have higher Uranium concentrations in post-monsoon than pre-monsoon.