Volume 26 - 2024

The purpose of this study is to anticipate and investigate the groundwater quality in the regions of the Cauvery basin. In the post-monsoon season of 2020, 800 samples were collected from 200 different places for this paper. The AlexNet model is used in this book to forecast the water quality. In order to examine the groundwater quality, the anticipated groundwater samples are analyzed using main cations (K+, Mg2+, Ca2+, and Na+), major anions (NO2- +NO3-, CO3-, F-, HCO3-, Cl-, and SO42-), hardness, pH, and Electrical Conductivity (EC). The accuracy, specificity, and sensitivity of the AlexNet model are used in this publication to validate its efficacy. Validating the following metrics determines if water is suitable for drinking and irrigation: sodium percentage, magnesium ratio, Kelly's ratio, sodium adsorption ratio, water quality index (WQI), and residual sodium carbonate (RSC). According to the research, the AlexNet model predicted water quality with 93%, 94.57%, and 91.47% accuracy, specificity, and sensitivity, respectively. According to the experimental results, the WQI value shows that 22% of the collected samples are acceptable for drinking, 63% are suitable for drinking, and the other 15% are only fit for irrigation and should not be consumed.

Groundwater is a vital resource for human consumption. The study aimed to evaluate toxic metal concentrations in groundwater systems and determine pollutant sources using multivariate methods including cluster analysis (CA), principal factor analysis (PCA), and Pearson correlation coefficient (r). The results were compared with World Health Organization (WHO 2017) and Bureau of Indian Standard (BIS 2012) standards, indicating that Al concentration observed within prescribed values and other Cd, As, Zn, Pb, and Cu were less than the acceptable values, as well as the rest of Fe, Mn, and Ni levels in groundwater were mostly within acceptable values. The PCA results showed three factors (F1, F2, and F3) were responsible for the data structure, which was specified as 37.954%, 23.331%, and 16.132%, as well as total variance of dataset associated with 77.416%, respectively. Factor 1 showed strong positive loading (Cu, Pb, Zn), 2 (Al, Mn), and 3 (As, Ni), which demonstrated the contaminants source from natural and agricultural activities. Moreover, CA results revealed three clusters indicating low to high water pollution due to rock weathering and anthropogenic activities. Overall, results showed that 50% of groundwater samples were acceptable for potable and agricultural uses. Therefore, groundwater treatment is necessary before any use.

This study evaluates the contamination levels of heavy metals and petroleum hydrocarbons in Jafari ‎Creek sediments and the effect of these pollutions on Macrobenthos in 2017. Studies to understand ‎the effect of heavy metal Cadmium, Chromium, Nickel, Lead, Selenium, Zinc, Copper, and ‎Vanadium, and 16 hydrocarbon compounds, organic material, and soil texture on the population of ‎Jafari Creek Macrobenthos in five stations along the estuary and analyzed using standard ‎procedures. The 4 identified Macrobenthos included Bivalvia with 9 species, Gastropoda with 8 ‎species, Crustacea with 7 species, and Polychaeta with 6 species totaling Macrobenthos 3645.14 per ‎square meter. The dominant class was Polychaetes (53.9%), followed by Bivalvia (23.2%), ‎Gastropoda (9.93%), and Crustaceans (15.8%), with slightly different (P<0.05), were in the second ‎and third class. Among the studied metals, zinc, chromium, and nickel had the highest ‎concentration. Among the hydrocarbons, Anthracene at station 1, Fluorene at station 2, ‎Phenanthrene and Dibenzo [A, H] Anthracene at station 3, and Fluoranthene at station 4 with a ‎concentration between <0.01- 0.091 ppm had the highest value. The highest and lowest heavy metal ‎concentrations were measured at station 4 (215.54 ± 14.58 ppm) and station 1 (102.39 ± 24.15 ‎ppm), respectively. In return, stations 1 (0.339 ± 0.074 ppm) and 4 (0.196 ± 0.078 ppm) had the ‎highest and lowest concentration of hydrocarbons, respectively. Regarding the number of identified ‎Macrobenthos, stations 3 and 2, with 1738.64 and 333.28 n/m2 had the highest and lowest numbers, ‎respectively. The class of Crustacea had a positive correlation with zinc, copper, and lead metal and ‎a negative correlation with Selenium. Polychaeta was positively correlated with cadmium and ‎vanadium. Gastropoda had a negative correlation with vanadium and chromium, a positive ‎correlation with lead and hydrocarbons, and Bivalvia correlated negatively with lead and zinc and ‎had a correlation with vanadium. Considering that the areas around Jafari Creek are an industrial, ‎petrochemical, and economic region considered one of the important catchments in the province of ‎Khuzestan, the sediments, water, and animal tissues must be periodically the analysis of heavy ‎metals and oil hydrocarbons should be considered.‎

To conduct this experiment, rhizospheric bacteria were isolated from the root nodules of alfalfa ‎plants (Medicago sativa) in the Khuzestan province during the spring season. For the molecular ‎identification of superior isolates, DNA extraction and expression of 16S rDNA were performed. ‎To investigate nitrate (NO3-) and phosphate (PO43-) removal, 120 mL vials were filled with 50 mL of ‎laboratory wastewater containing specified concentrations of nitrate (25, 50, 100, and 200 mgL-1) ‎and phosphate (5, 10, 20, and 30 mgL-1). The removal percentage was examined over 1, 2, and 3 ‎hours. Results revealed that three rhizobial bacteria, including Sinorhizobium meliloti (bacterium 3) ‎‎(Query ID= DQ-145546.1), Sinorhizobium medicae (bacterium 2) (Query ID= CP-000738.1), and ‎Sinorhizobium meliloti (bacterium 1) (Query ID= CP 021215.1), were isolated and identified. The ‎highest removal efficiency was recorded within 3 hours at 44.61%. With an increase in ‎concentration, the removal efficiency decreased, reaching its lowest value (14.82%) at 200 mg L-1 ‎compared to other concentrations (p < 0.05). Besides, the bacterial type or mixture did not ‎significantly affect the nitrate removal percentage (p>0.05). At a concentration of 25 mg L-1, the ‎highest removal percentage (63.08%) was measured in the presence of bacteria at 3 hours. ‎Furthermore, the highest phosphate removal percentage was obtained at 37.4% at 5%, within 3 ‎hours, and a mixture of 3 bacteria. Furthermore, the efficiency of the mixture of 3 bacteria was ‎higher compared to bacterium 2 (p<0.05). Besides bacteria 1 and 3 with a removal percentage of ‎‎16.23% were ranked higher (p > 0.05). At higher concentrations and increased time, the nitrate and ‎phosphate removal percentages exhibited a consistent and fluctuating trend, respectively (p > 0.05). ‎Ribosome bacteria performed better in nitrate removal compared to phosphate (p ‎‏>‏‎ 0.05). ‎Considering that wastewater from agricultural and industrial centers contains a mixture of ‎nitrogenous and phosphorous substances, it appears that the use of a consortium of these bacteria ‎with different characteristics and compatibilities enhances the efficiency of purification and removal ‎of these parameters.‎

Water is an essential elixir for several living organisms to function and survive. But it gets contaminated through several sources such as industrial wastes, oil spills, marine dumping, etc. With a growing population, availability of good quality water is of grave importance. This has become the motivation to probe into analysis of water quality from the outcomes of Statistical and Ensemble methods and to find the best working models from both methods. Research has been done to predict water quality analysis using standalone statistical and ensemble models. So, this research focuses on obtaining the best Statistical and Ensemble model separately among the models tried. The statistical models implemented for comparison are Principal Component Analysis (PCA), Hierarchical Clustering Analysis (HCA), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA). The Ensemble models used are Bagging, Boosting and Stacking. The models are then combined to build a Hybrid model to observe the comparisons between the three. The performance metrics used are Confusion Matrix, Accuracy, Precision, Recall, F1-score and ROC curve. While comparing the models, it is observed that Hybrid model produces the most accurate results, hence proving that the combination of Statistical and Ensemble model is efficient.

The study addresses the critical issue of water scarcity in agriculture, which causes significant losses by disrupting plant-water connections and increasing oxidative damage to biological components. In this study, we evaluated the synergistic potential of pre-isolated and identified exopolysaccharide-producing strains (ZE15 and ZE11) in combination with the drought-alleviating hormone Brassinosteroids (BR) to boost okra development under PEG-6000-induced drought stress. The experiment was carried out in a controlled environment at the Soil Microbiology and Biotechnology Laboratory. It used a completely randomized design with factorial arrangements and three replications. Individual rhizobacterial strains were evaluated and also used in a consortium (ZE15+ZE11) at two different Brassinosteroids (BR) concentrations (10-4 M and 10-8 M). The results showed that the consortium of (ZE15+ZE11) with foliar spray of BR (10-8 M) greatly increased okra production. Under both control and drought stress conditions, shoot length (37 and 34%), root length (41 and 40%), root surface area (32, 34%), and root volume (35 and 33%) improved significantly compared to the control group. Furthermore, this treatment demonstrated the most promising results in alleviating drought-induced oxidative damage by improving antioxidant defense mechanisms. Key enzyme activities, such as MDA (30 and 31%), GR (32 and 30%), SOD (36 and 37%), and CAT (31 and 34%), rose significantly under both control and drought stress conditions when compared to the control. To summarize, the use of drought-tolerant bacteria in concert with plant growth hormone provides a synergistic approach to mitigating the negative impacts of drought, resulting in considerable gains in okra growth and antioxidant defenses. This technique shows promise as a way to increase agricultural productivity in arid and semi-arid areas.

Streamflow of the Murray River (MR) was investigated from 1978 to 2017, using statistical analysis based on Indian Ocean modes of variability. During the cool season, June to August (JJA), observations and reanalysis products have been used to analyse the relation of streamflow of MR with Indian Ocean High (IOH) and Southern Annular Mode (SAM) over South Australia (SA). Recently, the river has suffered from severe drought, whereas drought drivers differ significantly in terms of interannual and decadal timescales. As a defining feature of atmospheric general circulation, the IOH is quantitatively simulated in all global climate models. Variations in the streamflow of MR have been linked to the variability of intensity and positions of Indian Ocean high pressure (IOHP) meridionally and the impact of SAM across the Indian Ocean. It is found that the correlation of streamflow with IOHP is (r = -0.41), SAM (r = -0.52) and shows the strongest correlation with Indian Ocean High Longitude (IOHLN), which is -0.56. Moreover, SAM explains only 27% of streamflow variability, while IOHP and IOHLN indices calculated by the Center of Action (COA) approach explain 39% of the variation. This paper examines the decline of the inflow rate of MR in SA by applying the COA approach, Mann-Kendall (MK) test and Pearson correlation. We further investigate the impact of significant predictors over the flow of MR. Inflow rate of the hydrology of MR is influenced by the period of time, which shows a decreasing trend with -1.976 by applying autocorrelation. Overall, monthly and annual streamflows have also investigated a significant decreasing trend. Cross-correlation is also used to verify the relationship between streamflow and significant predictors of MR.

This study synthesizes selenium nanoparticles (Se NPs) using a green approach, utilizing Tectona grandis leaf extract in a hydrothermal method. The X-ray diffraction (XRD) analysis provided highly crystalline particles with a trigonal crystal structure, indicative of the well-defined nature of the synthesized Se NPs. Particle size analysis (PSA) results demonstrated a average particle size of 45 nm, further supporting the nano-sized characteristics of the particles. Field emission scanning electron microscopy (FESEM) results exhibited a hexagonal close-packed structure, providing valuable insights into the morphology of the Se NPs. Optical band gap calculations using the Tauc plot method yielded a value of 1.85 eV, highlighting the semiconductor nature of the synthesized Se NPs. The photocatalytic application of these nanoparticles was investigated against various cationic and anionic dyes, including Alizarin Red, Crystal Violet, Reactive Black, and Rhodamine B, under sunlight irradiation. Notably, the Se NPs demonstrated enhanced degradation, particularly for cationic dyes, attributed to electrostatic surface charge interactions. Rhodamine B exhibited the highest degradation efficiency among the dyes, reaching 96%. Furthermore, the stability of the Se NPs was evaluated through five consecutive cycles of photocatalytic degradation. Remarkably, the nanoparticles maintained stability, with only a marginal loss in degradation efficiency (after 5 cycles), affirming their potential as a stable and efficient nano photocatalyst for environmental remediation applications. This comprehensive investigation underscores the significance of green-synthesized Se NPs in advancing sustainable and effective photocatalytic processes.

Increased water conductivity levels have been proposed as a key factor to explain the occurrence of teratological forms in freshwater diatom assemblages. The current study aimed to carry out an experiment on a laboratory scale to assess the response of periphytic diatoms to artificially increased salinity levels. The obtained results show that: a) the proportion of aberrant cells increased in high conductivity treatments, b) developed teratologies were preserved in diatom populations even after being translocated to normal conditions, and c) the degree of valve outline deformation in the dominant species was proportional to the induced water conductivity. All these data support previous field observations that linked high electrolyte content and the abundance of aberrant cells among microalgal communities in continental aquatic ecosystems.

In order to analyze the spatiotemporal change characteristics of regional flood disaster, analyze the main change characteristics and hydrological response of precipitation distribution in Guangxi, and improve the comprehensive utilization efficiency of water resources, this paper introduces the k-means clustering algorithm to design an analysis model of spatiotemporal change characteristics of flood disaster. First of all, obtain the flood data in Guangxi and the observation data of the national meteorological station within 5 km, complete the collection of the basic data of mountain flood disasters. Based on the collected data, an analysis was conducted on the spatial and temporal distribution of flash floods in the Guangxi region. Secondly, the Kriging spatial interpolation method was used to analyze the spatial distribution of precipitation data in Guangxi. The Mann-Kendall trend test was then employed to examine the trend of precipitation-related statistical parameters over time. Additionally, wavelet theory was applied to analyze the time series of annual precipitation and precipitation with different durations in Guangxi. Subsequently, the k-means clustering algorithm was introduced to construct a model for analyzing the spatiotemporal characteristics of flood changes, determining the concentration and duration of precipitation in different years in the region. Finally, analyze the spatiotemporal change characteristics of flood events in different seasons under various indicators, and realize the analysis of flood spatiotemporal change characteristics. The research results indicate that the Frank Copula function fits the best correlation between annual precipitation and temperature, and can better characterize the correlation between the two. The Frank Copula function has the best fitting effect on the correlation between precipitation and temperature in autumn in Guilin, summer in Nanning, and summer and winter in Beihai. In Guangxi Zhuang Autonomous Region, the annual precipitation shows a gradually decreasing trend, especially at R and P stations. In summary, the Frank Copula function can effectively characterize the correlation and trend of precipitation and temperature in different seasons and regions of Guangxi.

Formaldehyde is one of the typical indoor pollutants causing theprevalence of acute health issues among those residing in indoor environments. Biofiltrationis a commonly adopted technique to treat indoor air pollutants. In this investigation, a biofilter was fabricated and compactly filled with compost, vermiculite and activated carbon (65:25:10) as a media composition for enhanced formaldehyde degradation. The influence of formaldehyde inlet concentration (0.01 – 1 gm-3g/m3) and EBRT (30 – 180 s) was studied to evaluate the biofilter performance. Their progression was assessed with dynamic operations in five phases with two stages each. The formaldehyde removal was achieved between the range of 32% to 98% with regular intervals of EBRT at 30, 60, 90, 120, 150 and 180 seconds, which depend upon varying their flow rate and inlet loading rate. The biofilter performance lasted for over 202 days with a 98% formaldehyde removal and 23 g/m3h-1biofilter capacity under the maximum EBRT (180 s) and inlet formaldehyde concentration (1 gm-3g/m3). The experimental findings demonstrated the efficacy of biofilter in withstanding substantial formaldehyde loading rate while maintaining an acceptable EBRT. The primary microbe responsible for formaldehyde degradation was identified to be as gram-negative bacteria.

In this paper, based on the factors of treatment process, treatment scale, as well as water quality, the level and distribution of electricity consumption, drug consumption, and indirect carbon emission of five typical wastewater treatment plants (WWTPs) were examined. The distribution of electricity consumption within the WWTPs were analyzed in terms of wastewater treatment units. The results uncovered that the biological treatment unit was the treatment unit with a high percentage of electricity consumption in the WWTPs. Carbon emissions of main units in the WWTPs presented that the aeration blower, sewage lifting pump, submersible pusher, phosphorus remover and return sludge pump of the biological treatment unit were the top 5 emission units of carbon emissions in the WWTPs, and the key influencing factors of the carbon emissions of the main carbon emission units had been analyzed. Combined with the current situation of sewage treatment energy consumption in Chongqing, the analysis put forward a library of energy saving and consumption reduction measures for Chongqing WWTPs, which applied them to the sewage treatment plant A energy saving and consumption reduction renovation project.

The proliferation of environmental pollution, particularly from hazardous industrial dyes, poses a significant threat to ecosystems and aquatic life. This study uses extract from Nerium oleander leaves as a natural capping and reducing agent to produce copper oxide nanoparticles (CuO NPs), an ecologically acceptable way to tackle this problem. The CuO nanoparticles have improved physicochemical characteristics, as shown by their average crystalline size of 15.56 nm and decreased particle size of 31.84 nm. Additional studies such as SEM, EDX, TEM, and zeta potential were accomplished and revealed the spherical structure; an elevated negative zeta potential of -25.6 mV was observed on the surface property. The photodegradation efficacy of these bio-synthesized CuO NPs was assessed against various industrial dyes, including Rhodamine 6G, Malachite Green, Eosin Yellow, and Reactive Black. The results demonstrated exceptional degradation efficiencies, with rates of up to 97.48%, 99.54%, 89.73%, and 89.33% respectively. The decolorization of organic dyes presented a visual cue that the degradation process was progressing. Notably, using Nerium oleander leaves as reducing agents contributed to the nanoparticles' stability, making them suitable for repeated cycles of photocatalysis. This research underscores the potential of green synthesis methods and highlights the vital role of plant-based reducing agents in advancing environmentally friendly nanomaterials for wastewater treatment and environmental remediation. The findings offer a promising pathway toward sustainable and eco-friendly solutions to mitigate the environmental impact of hazardous industrial dyes, fostering responsible industrial practices and preserving aquatic ecosystems.

The biological synthesis of nanomaterials is drawing immense interest because of their non-hazardous nature and enormous antimicrobial application. In the present study, we explored Polygonatum geminiflorum Decne for phytochemical profiling and biosynthesis of silver nanoparticles to control soft rot/blackleg and bacterial wilt pathogens of potato through in vitro experiment. Phytochemical screening indicated the presence of important secondary chemicals including tannins, glycosides, flavonoids and terpenoids, while, gas chromatography-mass spectrophotometry (GC-MS) study of leaf extract showed the presence of 30 phytochemicals, the most prominent among which included ç-Sitosterol and n-Hexadecanoic acid. The GC–MS qualitative analysis also supported the presence of bioactive compounds responsible for metal reduction processes and synthesized nanoparticles stabilization. In vitro study showed that concentration of 100µg/mL of AgNPs and AgNPs-PE efficiently control both Erwinia carotovora and Ralstonia solanacearum. The outcomes have provided an improved protocol to use prepared AgNPs against the tested pathogens without health hazards.

To control the use and disposal of products containing nanoparticles and lessen the risks they pose to soil and aquatic ecosystems, it is essential to understand the fate and transport of Al2O3 NPs. The stability, settling, retention, and transport of Al2O3 NPs in aqueous environments and saturated sand media were investigated in the current work to determine how solution chemistry and water chemistry influenced these processes. There was a notable rise and variety in settling of nanoparticles in different water stream and simulated aqueous solutions under static aqueous circumstances. The impact of solution chemistry in the transport of the nanoparticles was also examined in a column filled with quartz sand and various combinations of ionic strength (10 to 100 mM of NaCl), pH (3 to 7), natural organic matter (0.1 to 10 ppm of Humic acid), and natural water systems. The results demonstrate that the environmental conditions may significantly affect the transport and retention of nanoparticles, with humic acid exhibiting enhanced movement and natural clay, Kaolinite, increasing retention. Additionally, with natural waters the transport profiles were altered. The combination of DLVO and Clean bed filtration theory provided further assistance in the prediction of the aggregation and transport of the Al2O3 NPs.

The effect of temperature on the adsorption of U-232 and Am-241 by PN6 has been investigated in laboratory and environmental water samples (e.g. seawater and waste water) in the picomolar concentration range. Generally, increasing temperature favors radionuclide adsorption, indicating that radionuclide binding by PN6 is an endothermic and entropy-driven process. In environmental waters, Kd values are significantly lower than the corresponding values in de-ionized water solutions, because of the presence of various cations (e.g., Ca2+, Fe2+) that compete the radionuclide adsorption by PN6 and the presence of complexing anions (e.g. CO32-), which complex and stabilize the actinide cations in solution.

This study aimed to evaluate the pollution level of Ni, Pb, Cd, V, and Hg in the sediments of Musa Estuary and its four main tributaries namely Majidieh, Zangi, Semaili, and Merimos (collectively known as Mahshahr estuaries) in summer and winter 2019 using sediment quality indices. In each tributary, 4 stations were chosen to represent the estuary condition. One control point was also considered at the mouth of the estuary (17 stations in total). 51 sediment samples were collected using the Van Wien Hydrobius grab sampler and measurements were performed utilizing the ICP-MASS device. The heavy metals concentration was ordered as Ni> Pb> Cd> V> Hg and tributaries followed the order of Majidiyeh> Samaili> Zangi> Merimos> Musa's mouth (control point) in terms of heavy metal concentration in both seasons. Heavy metal concentrations were positively and significantly correlated with electrical conductivity and pH (P <0.05). The potential ecological risk (Er) was low for Ni, Pb, and V, moderate for Cd (except for Musa's mouth in summer (27.33)). Hg had low risk in Zangi Tributary and Musa's mouth in summer and medium risk in other tributaries in winter. The ecological risk index (RI) showed considerable risk in Zangi Tributary and Musa's mouth in both seasons and high risk in Merimos, Majidieh, and Samaili tributaries. According to the pollution load index (PLI), the sediments of Mahshahr estuaries showed no pollution in summer and moderate pollution in Majidiyeh and Smaili tributaries in winter. The Nemro Integrated Pollution Index ranged from 8.62 to 20.04 in summer and 9.15 to 21.53 in winter Mahshahr estuaries which indicate its high pollution potential. The findings of this research and those of previous studies alarm increasing levels of heavy metals’ content in the sediments of Mahshahr estuaries over the past years.

In this research, we provide a method for synthesizing ZnO nanoparticles using Moringa Oleifera Leaf (M.O Leaf) Extract. UV-VIS Spectroscopy, Scanning Electron Microscopy, EDS, X-ray diffraction and Fourier Transform Infrared Spectroscopy (FTIR) were used to create and characterize ZnO nanoparticles. The spherical size structure of the synthesized nanoparticles with an average grain size of 1 nm was validated by SEM, EXD, and XRD analysis. After the sunlight exposure, the photocatalytic reagent was used to break down the organic dyes in the synthesized ZnO nanoparticles. Nearly 96–97% of the titan yellow and Congo Red dyes were broken down by ZnO nanoparticles.

In this study, coconut shell biosorbent was synthesized through chemical processes and activated using concentrated sulfuric acid to serve as an organic adsorbent for the effective removal of dye molecules, particularly Crystal Violet (CV) and Methylene Blue (MB), from wastewater. The biosorbent's surface characteristics, including morphology and functional groups, were comprehensively analyzed using techniques such as BET, FTIR, SEM, and EDX. The experimental investigations revealed that optimal conditions, including a pH of 10.0, biosorbent dosage of 3 g/L, initial dye concentration of 20 mg/L, and a contact time of 60 minutes, led to the efficient removal of 89.74% of CV and 82.32% of MB dye molecules from synthetic solutions. Several isothermal studies were conducted to assess whether the adsorption process exhibited homogeneity or heterogeneity, aiming to gain a deeper understanding of its characteristics. Alongside the aforementioned tests, kinetic investigations were performed to ascertain whether the dye adsorption on the adsorbent was of a physical or chemical nature. Thermodynamic analyses were also undertaken to determine the outward-releasing or inward-absorbing characteristic of the dye adsorption process and to assess its spontaneity. Based on the outcomes of the desorption studies, the addition of 0.3N hydrochloric acid (HCl) resulted in the highest desorption rate. This effectively enhanced the recovery of dye molecules from the exhausted adsorbent, underscoring the effectiveness of 0.3N HCl in facilitating the desorption of adsorbed dye molecules.