Pollution
Volume:11 Issue: 1, Winter 2025

Sustainability of irrigated agriculture is based on the efficient management of quantity and quality of water resources. Water Quality Indices used to assess the suitability of irrigation water, however, often consist of uncertainties arise near the class boundaries. Hence, the objective of the present study is to classify the groundwater for irrigation purpose in Tumkur district, Karnataka, India, using Fuzzy comprehensive evaluation approach for crisp classification. The methodology of this study includes collection of 104 groundwater samples, assessment of hydrogeochemistry, and classification of groundwater by conventional and Fuzzy-logic techniques. Hydrogeochemistry by Piper plot indicates mixed Na-Ca-HCO3 type and Gibbs plot indicates the influence of rock-water interactions. The water classification by conventional irrigation indices such as Electrical Conductivity, Sodium Absorption Ratio, Kelly Index, Percentage Sodium, Residual Sodium Carbonate and Magnesium Hazard showed that 2%, 0%, 86.5%, 40%, 25% (post monsoon) and 4%, 2%, 81%, 38.5%, 4% and 19.2% (pre-monsoon) of groundwater samples were not suitable, respectively. As various indices indicated dissimilar results, an integrated conventional index was evaluated by Fuzzy synthetic evaluation technique based on the Maximum Principle Membership and Fuzzy Class Ratio (FCR) and it showed 3.8 % and 0.98% of samples were classified as Not suitable (N), respectively. However, FCR method was found to be effective in dealing variation in fuzzy boundary conditions and it showed 0.98%, 1.96%, 1.96%, 1.96% samples as not suitable at 5%, 10%, 15% and 20% of degree of variation near class boundaries, respectively.

Glyphosate was a non-specific organophosphate pesticide, which finds widespread application in shielding crops against the weeds. The degradation of glyphosate in soil usually carried out by microbial activity. Soil Pesticide bioremediation is the most economical,  environmentally friendly and successful method available. In this research, four types of bacteria as Bacillus megaterium, Bacillus subtilis, Rhizobium sp., and Azotobacter sp.. The four plant growth promoting Bacteria (4PGPB) were found abundantly in soil. To study the decomposition of the glyphosate pesticide under laboratory conditions and at different concentrations starting  from 5ppm, 10ppm, 15ppm, to 20ppm. These bacteria were grown on mineral salt media in 60 days incubation for the experimental condition in the presence of different concentrations of glyphosate. The removal efficiency of the Glyphosate  depending on the starting concentration were obtained about (0, 60, 80.5 and 99.98%) for 5ppm, (0, 60.98, 79.80, and 96.80%) for 10 ppm, (0, 51.80, 71.80, and 88.95%) for 15 ppm , and (0, 47.94, 63.94, 87.28%), for 20 ppm respectively, via using the Bacillus megaterium bacterial, while the removal efficiency  with values of (0, 59.70, 83.99 and 99.00%) for 5 ppm, (0, 49.87, 82.87, and 93.19%) for 10 ppm, (0, 52.45, 77.45, and 84.99%) 15ppm, and (0, 51.48, 71.48, 75.12%) for 20 ppm, respectively, for the Bacillus subtilisat bacterial. Besides, the removal efficiency for the Glyphosate with values of (0, 96, 86 and 92%) for 5ppm, (0, 57, 80, and 86 %) for 10ppm , (0, 47, 74, and 85 %)for 15ppm , (0, 47, 72, and 84 %), and (0, 45, 67, 80 %) for 20 ppm via using the Azotobacter sp.bactira, respectively. The biodegradation using Rhizobium sp. at 60 day incubation with   the same experimental conditions which was (0, 96, 86 and 92%) for 5 ppm , (0, 57, 80, and 86%) 10 ppm, (0, 47, 74, and 85%), (0, 47, 72, and 84%) for 15 ppm , and (0, 45, 67, 80%) for 20ppm from the Glyphosate concentration.  The removal efficiency increased with increasing incubation time and with the decreasing of Glyphosate concentrations when used it as a source of phosphorus and carbon for the three plant growth promoting Bacteria (4PGPB). The biodegradation of Glyphosate in soil may be effectively utilized for bioremediation or biodegradation for duration of 30 to 60 days.

Thermal pollution refers to the alteration of water properties caused by the use of water as a cooling fluid. This occurs when water is pulled from a water source, condensed to release heat, and then recirculated back into the water source as thermal discharge. The characteristics of thermal discharge dilution are influenced by factors such as jet momentum, buoyancy, turbulence-induced distribution, density stratification of the surrounding environment, configuration of water currents, presence of solid boundaries, and heat exchange at the surface. A single-port diffuser is used for the discharge of hot water. This study employed experimental methods to investigate the impact of fixed vanes on the thermal effluent dilution of a single-port submerged diffuser. The use of fixed vanes increases the dilution of a single-port submerged diffuser. Using fixed vans for H= 1, ΔTm was reduced by 3.13%, 10.26%, and 2.74%, and ΔTe was reduced by 15.66%, 17.86%, and 22.86%, respectively, for each flow ratio. For H= 2, ΔTm decreased by 2.38%, 3.41%, and 4.48%, and ΔTe decreased by 8.33%, 15%, and 16.67%, respectively, for each flow ratio. For H= 3, ΔTm decreased by 2.86%, 2.22%, and 3.45%, and ΔTe decreased by 5%, 29.41%, and 22.73%, respectively, for each flow ratio. In addition, increasing the Reynolds number ratio reduces the mixing zone and increases the dilution temperature.

Predicting the future development of the city has an essential role in achieving sustainable development. There is a direct relationship between land use changes and emission of pollutants. The present study used satellite images, remote sensing models, and geographic information systems to predict land use changes in Qazvin City. In the first step, the Principle Component Analysis was used to summarize the data and highlight the similarities and differences between the different bands. Then, the land use map for each of the studied years (1990, 2000, 2010, and 2020) was drawn using the Land Change Modeler analysis, and the land use changes between 1990 and 2020 were calculated. The findings show a severe decline in agricultural land and green space as a result of their conversion into constructed land. 735.66 hectares of these lands were destroyed during the study period and turned into constructed lands. If this trend continues until 2025, another 69 hectares will be destroyed. Converting agricultural lands and green spaces to residential, commercial, and industrial greatly increases the potential for pollutant emissions. These changes are associated with an increase in greenhouse gases in urban areas. This development should be based on green infrastructure especially the use of renewable energies and the management of freshwater.

The use of abiotic ecological indicators in environmental monitoring does not always reliably reflect the level of anthropogenic impact on aquatic ecosystem. Our study aims to estimate possible differences in abiotic and biotic index-based assessments of the impact of industrial pollution on water quality in the small boreal river located at the eastern edge of Europe (Perm Krai, Russia). We analyzed the contamination of an 13-km long river by major organic and inorganic ions, trace elements, and thermal pollution. To evaluate the toxicity of bottom sediments, threshold effect concentration (TEC), probable effect concentration (PEC), and potential effect concentration quotient (mPECQ) were calculated from the concentration of heavy metals. Also, benthic macroinvertebrates were sampled from headwaters to the mouth of the river. We found the presence of the members of the EPT taxa at the sites with a high concentration of heavy metals, which can be explained by the tolerance of local invertebrates to specific pollutants. Apart from that, our results show that in the middle reach of the river, toxic effect of a nitrite-ion high concentration contradicts the presence of gill breathing crustaceans sensitive to this type of pollution. This can be explained by the high concentration of chlorides at this site, which leads to reduction of nitrite toxicity. Further work should be focused on developing abiotic indices that account for the sensitivity of local invertebrates to specific pollutants, while comprehensive pollution assessment should include antagonistic or synergistic interactions of various pollutants.

Antibiotics are among the most consumed drugs worldwide. These compounds enter the environment from different sources, adversely affecting human and animal health given their high persistence and stability in the environment. Conventional water and wastewater treatment processes have not been designed for removal of such materials. Thus, a suitable method should be devised for removal of these compounds. Among antibiotics, Amoxicillin (AMX) has the minimum metabolism. The aim of this research is the removal of AMX using electro-Fenton (EF) method from aqueous solutions. One of the most important disadvantages of the electro-Fenton method is its high efficiency at acidic pH, causing secondary contamination. As such, for resolving this issue, chelating agents can be used. In this study, the effects of important parameters have been examined on AMX removal efficiency including initial concentration AMX (20-120) mg/L, initial pH (3-7), current intensity (10-130) mA, and EDTA concentration (0-1) mM as chelating agent via design of experiment method. This paper introduces a simplified version of quadratic polynomial Response Surface Methodology (RSM). After analysis of variance, it was found that all examined variables were significant and the model had sufficient validity. The results showed that EDTA in addition to pH has also been influential in enhancing removal efficiency. Regarding the optimal conditions for the examined parameters, the initial concentration of AMX 24 mg/L, the current intensity 85 mA, initial pH 5.6, and EDTA dose 0.6 mM, showed 95.71% AMX removal, eventually. Also, a graphite cathode made of pencil was used for constant production of hydrogen peroxide during the process. The extent of electric energy consumption at the optimal point was obtained 0.86 KWh/m3.

Cigarette smoking is a potential route for radiation exposure because tobacco leaves used in cigarette production contain radioactive elements. From a health perspective, Understanding the radioactivity levels in tobacco leaves and products is crucial for evaluating the radiological effects of smoking tobacco for positive and negative smokers. The study utilized a gamma-ray spectrometer (HPGe) to measure naturally occurring radionuclides, while X-ray fluorescence spectroscopy was used to analyze the levels of Cr, Ni, Zn, and Pb. The results indicate that the mean levels of 238U, 232Th, and 40K activity levels in tobacco samples from all examined locations were below the global data. The mean values of the Raeq, Hin, and Hex indices in tobacco plant samples from all the studied sites were lower than the permissible global limit. The average values of the representative gamma index (Iγ) in the Samilan, Galala, and Qaerawan sites were lower than the permissible global limit. However, the average magnitudes of the Iγ index at the Qasre, Amadiya, Sarsang, Sheladeze, Sidakan, and Penjwin sites were higher than the permissible global limit. The levels of toxic substances in tobacco plants decrease in the following sequence: Cr > Ni > Zn > Pb. Furthermore, descriptive analyses assessing the relationship between radionuclides and heavy metals indicated a strong positive correlation between 238U and 232Th. Additionally, they demonstrate positive correlations between 238U and heavy metals. A tenuous association was detected between 232Th and heavy metals, as well as between 40K and toxic substances.

Technological innovations have the potential to significantly mitigate the global challenge of food waste and its associated carbon emissions. This study aims to explore the key role of technological innovation as a strategy in reducing carbon emissions from food wastage. Time series annual data from 2000 to 2022, collected from World Developed Indicators (WDI) and Badan Pusat Statistik Indonesia (BPS), was utilized. We applied the Johansen Co-integration test and Autoregressive Distributed Lag (ARDL) model for long-run impact assessment. The findings show that food wastage generation and technological innovation have a statistically positive impact on carbon emissions. In the second model, we predict that food wastage, technological innovations, food production, economic growth, and population density have a positive impact on food waste generation in Indonesia. These findings underscore the significance of incentivizing the adoption of technological innovations in the food supply chain to reduce food waste and carbon emissions. Additionally, sustainable practices through the supply chain, such as food packaging and optimal logistics, should be the trademark of food industries in Indonesia.

This study focused deeply on sustainable solid waste management practices, specifically focusing on the co-composting of various organic materials such as sugarcane leaves/ trash, sugarcane bagasse, food waste, cow dung, and press mud (generated from the sugarcane industry). Five trapezoidal shape agitated piles (heap) were prepared with various combinations (Trials 1 to 5). This study investigates the dynamic changes in critical parameters while composting and their implications for compost quality and maturity. The results showed that the percentage increase in total nitrogen (1.76-2.24%, 1.93-2.23%), phosphorus (1.35-3.52%, 1.18-2.62%), and potassium content (4.5-8.7%, 4.7-8.9%) in trial 3 and 5, which underscore their roles in enhancing soil fertility and crop productivity. The decline in carbon-to-nitrogen ratios in trial 3 (45.5-26.3) and trial 5 (46.6-24.3) correlates with the growth of lignocellulose-degrading bacteria, facilitating humic substance formation critical for compost stability. Lignocellulosic degradation, evidenced by cellulose, hemicellulose, and lignin content changes, further emphasises its importance in compost maturation. Additionally, reductions in CO2 evolution rate (20.9-3.8%, 22.1-3.9%) and volatile solids (81.9-43.8%, 83.8-43.8%) content in trials 3 and 5, reflect microbial activity and compost stabilisation. Trial 3 and 5 were the suitable combinations for the sugarcane agro-industrial waste composting. These findings highlight that effective waste management enhances agricultural productivity and reduces environmental impact by improving soil health using of composted sugarcane waste.

In recent years, the problem of air pollution has become increasingly important in the field of the environment. That is why our research focuses on the air quality of this coastal city. It seems essential to carry out a diagnosis for this city. We have rigorously chosen eight sites based on their diverse conditions. The selected and targeted parameters are the following: Total suspended particulate (TSP), lead (Pb), cadmium (Cd), nitrogen dioxide (NO2), sulfur dioxide (SO2), and traffic intensity, which represent the explanatory variables and the explained variable respectively. In addition to the evaluation of the concentration of each pollutant in the study area, we analyzed the correlations between the exogenous variables and the endogenous variable. The results obtained suggest that, according to the coefficient table, the TSP and heavy metals such as Pb and Cd do not seem to play a decisive role in explaining the intensity of traffic because their significant values exceed 5%. On the other hand, nitrogen dioxide and sulfur dioxide showed values significantly below the significance level of 5%, i.e., 0.005 and 0.018, respectively. These factors could provide an explanation for the intensity of traffic. However, the standard error results of these two variables have changed the meaning of their correlation, indicating that only nitrogen dioxide is positively evolving in the same direction as traffic intensity. Nitrogen dioxide exhibits a strong correlation with traffic intensity. NO2 could therefore be considered an indicator of traffic-related urban air pollution. The advantage of this analysis and interpretation methodology lies in its ability to provide a predictive and preventive tool to identify specific measures to reduce air pollution.

Traditional gold mining may cause mercury pollution in rice fields, resulting in a significant decrease in rice grain yields, as well as socio-economic and health issues. Bioremediation using indigenous microbes is a promising method to alleviate mercury contamination. Thus, it is necessary to explore the diversity and ability of microbes to remediate the contamination. This study investigated the indigenous microbes in mercury-contaminated soils collected from paddy fields around a gold mining area in Sukabumi Regency, Indonesia. Six soil samples were collected from three locations at the dry season; two paddy fields and a tailing pond located next to gold amalgamation machinery. Physicochemical analysis and total mercury concentration measurement of the soil samples were performed immediately after sampling. Bacteria in soil samples were cultured on Nutrient Agar and its colonies were counted after 24 hours of cultivation. Morphological characterization of the colonies was observed under a light microscope. Bacterial community composition was investigated using 16S rRNA amplicon sequencing. The resistance of bacteria to the mercury was tested by inoculating the mixed cultures in Mueller-Hinton agar supplemented with HgCl2 in concentrations of 10, 30, and 50 ppm. Bacterial colonies appeared higher in the soil sample with the lowest total mercury concentration. However, microbial community compositions were more diverse in the soil with medium mercury contamination. Furthermore, the microbial community cultured from tailing soil, despite lower bacterial diversity, performed mercury resistance up to 50 ppm. Upcoming studies should be conducted to investigate further potential indigenous microbial communities for reducing mercury contamination in soils.

A field experiment was conducted to study migration of the toxic elements from the flotation tailings of copper smelter slags after sulphuric acid leaching into high-moor peat and lawn grasses. Leaching wastes were studied by X-ray fluorescence, spectral analysis, X-ray powder diffraction and scanning electron microscopy. It has been established that they contain diopside, gypsum, spinel group minerals, jarosite, barite, sphalerite and amorphous silica. 5% of wastes was introduced into lime-neutralized peat. A mixture of lawn grasses was grown on artificial soils in test plots (1 m2). Average samples of soils, shoots and roots were analyzed by inductively coupled plasma mass spectrometry. It was found that, the concentration of most elements is higher in the soil with leaching wastes than in the soil with the flotation tailings, the exceptions are Mn, Co, Ni, Cu, Zn, Cd. The greatest differences in concentration coefficients were noted for Sn (38 times) and S (5.1 times). V, Cr, Co, Ni, Se, Mn, Cu accumulated more strongly in roots on soil with leaching waste compared to both peat and soil with tailings. However, S, Mo, Cd, Sn, Sb, Ba, and Pb accumulate significantly less. The shoots grown on peat with leaching wastes have lower accumulation coefficients for most of the elements compared to both the peat and soil with flotation tailings. The research contributes to the study of the impact of copper smelter slag processing wastes on the environment and is of interest for the development of environmentally friendly and effective methods for their disposal.

The present study introduces a novel soft sensor based on State Dependent Parameter (SDP) models utilizing the Local Instrumental Variables (LIV) method for monitoring a crude oil Desalting and Dehydration Plant (DDP) system. A key advantage of the LIV modeling method is its ability to interpolate directly without necessitating extensive model parameterization. Additionally, the inherent complexity and non-linearity of the process are effectively addressed by LIV-based soft sensors, which require fewer process variables, thereby reducing training time and computational complexity. Two distinct soft sensors were developed to assess the salinity efficiency and water cut efficiency of the DDP system. The efficacy of these soft sensors was evaluated using a dedicated testing dataset, revealing a robust correlation between salinity efficiency, water cut efficiency, and five secondary parameters. Comparisons between SDP-LIV model predictions and real observations of the DDP process show strong agreement. By leveraging these developed soft sensors, continuous evaluation of product properties is possible with minimal delay compared to traditional laboratory analyses. This capability is crucial for pollution control and environmental monitoring, as it allows for real-time detection and mitigation of contaminants in crude oil processing. Lastly, the performance of the proposed soft sensor is benchmarked against other models, such as Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN), demonstrating superior predictive capabilities. This study underscores the potential of SDP-LIV-based soft sensors in enhancing environmental protection and operational efficiency in crude oil processing.

In this study, chemical toxicity prediction was conducted using in silico approaches due to their importance for human health and environmental concerns. Analysis of Tigris River samples near a power station outlet revealed ten compounds, with three identified as toxic by in silico tools. TOXTREE software classified three compounds as high hazards, including heavy aromatic naphtha, light aromatic naphtha, and naphthalene, which was corroborated by QSAR database analysis. QSAR data indicated positive Ames tests for eight naphtha derivatives, suggesting their mutagenic potential. Molecular docking demonstrated strong binding affinity (-6.6 kcal/mol) between naphtha and cytochrome p450, crucial for xenobiotic metabolism, indicating potential interference with detoxification processes. This study highlights the utility of in silico methods in identifying and assessing environmental chemical hazards, emphasizing the importance of monitoring and mitigating toxic pollutants. Further investigation into the long-term environmental impact and bioaccumulation potential of these identified toxic compounds is warranted to ensure comprehensive risk assessment and management.

Methylotrophic bacteria have been identified as using carbon one (C1) compounds such as methane. In recent decades, the priority has been on determining new genera of bacteria that have the capability to consume methane and mitigate the effects of global warming. In order to isolate methane-oxidizing bacteria, oil polluted soil samples were collected from Mushrif gas station in Basrah Governorate/southern Iraq. The analysis of 16srRNA genes identified Paenibacillus sp. and Paenibacillus lautus, which were able to consume methane as its sole carbon source in NMS medium, also detect the pMMO gene (encoded methane monooxygenase enzyme) by real-time PCR. AS far as we know, P. lautus was found for the first time to consume methane as a sole carbon and energy source. These bacteria were able to exploite crude oil as their sole source of carbon and energy, recorded the highest growth for Paenibacillus sp and P. lautus at 1.9 and 0.5 (OD600) after 5 days of incubation successively. The results of gas chromatography analysis revealed high degradation of these bacteria for aliphatic compounds, reaching 92.8% and 89.41% for Paenibacillus sp. and P. lautus, respectively. Additionally, they exhibited high rates of degradation of aromatic compounds at 98.8% and 97.28%, respectively.