EQA - International Journal of Environmental Quality

[Not quotable] The adsorption of Pb2+ and Ni2+ ions utilizing modified chitosan beads: A response surface methodology and artificial neural network modelling study

2023-11-16T12:52:06+01:00

Editorial Note - 2024-05-31
The article has been temporarily retracted due to ongoing investigations.
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This work investigates the application of artificial neural networks (ANN) and response surface methodology (RSM) in developing a technique for removing Pb²⁺ and Ni²⁺ ions from wastewater using chitosan derivative. The materials including chitosan beads (CS) and grafted chitosan beads (MCS) were evaluated using infrared spectroscopy (FTIR) and a scanning electron microscope (SEM). The process factors were modeled and optimized using the central composite design (CCD) derived from RSM. Removal efficiency was described as the response for the output layer. However, the input layer feed data consists of pH, adsorbent dose, contact duration, temperature, and concentration. Two neurons were used as the ANN algorithm's output layers, which correspond to the adsorption of Pb²⁺ and Ni²⁺ ions. Both models were measured using statistical metrics like average relative errors (ARE), coefficient of determination (R²), Marquart's percentage standard deviation (MPSD), mean squared error (MSE), Pearson's Chi-square (), root means square errors (RMSE), and the sum of squares of errors (SSE). The ideal trained neural network depicts the training, validation, and testing phases, with R² values of 1.0, 0.968, and 0.961, respectively. The findings, however, showed that the ANN technique is superior to the RSM-CCD model approach. At pH 5, starting concentration of 100 mg/L, an adsorbent mass of 6.0 g, a reaction time of 55 min, and a temperature of 40 ^oC, the RSM-CCD model's optimization results for the process variables were achieved. The greatest removal percentages for Pb²⁺ and Ni²⁺ ion was 98.14% and 98.12%, respectively. The findings suggest that ANN can be utilized in forecasting the removal of adsorbates from wastewater.

Harnessing heavy metal-tolerant bacteria and phytotoxicity assessment for ecofriendly treatment of industrial effluents

2024-03-04T02:30:33+01:00

This study treated heavy-metal pollution in industrial wastewater by isolating and characterizing heavy metal-tolerant bacterial strains for bioremediation of industrial wastewater. The effluent samples were sterilized and aseptically inoculated with isolated heavy metal-tolerant bacteria such as Bacillus lichniformis, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia. The samples were subjected to physicochemical analysis, and titrimetric analysis. Further, Atomic Absorption Spectroscopy (AAS) was used for Heavy metal analysis. Phytotoxic assay was carried out by seed germination tests and pot culture study. Over 96-hour period, improvement featuring reduced turbidity, a stabilized neutral pH, and a substantial 72% decrease in total solids was observed. The application of the bioremediation techniques using heavy metal tolerant bacteria resulted in a significant reduction of heavy metal concentrations, surpassing 85%. Moreover, seed germination rates in the treated industrial effluent were higher than the untreated samples. Pot culture tests further revealed diminished toxicity (2.5%) in treated roots compared to untreated ones (36.7%), accompanied by increased root and shoot growth in the treated pots. The noticeable enhancement in germination rates and the improved growth of plants in the treated effluent underscore the promising potential for the sustainable application of these eco-friendly bacteria, making them a cost-effective microbial bioremediation solution for industrial wastewater.

Dynamic relationship among agriculture-renewable energy-forestry and carbon dioxide (CO2) emissions: empirical evidence from GUAM countries

2024-02-12T10:38:39+01:00

Nowadays with the climate change the environmental degradation has became the crucial issue in the World. This study empirically investigates the impact of agriculture value-added, forest area, and renewable energy on CO₂ emissions in GUAM union countries from 1996 to 2019. The independent variables in this study are agriculture value-added, forest, renewable energy and the dependent variable is CO₂ emissions. The statistical methods as the Panel unit root test, Pedroni and Kao panel co-integration test and OLS, FMOLS, and DOLS long-run tests were employed for the empirical part of the paper. The independent variables in this study are agriculture value-added, forest, renewable energy and the dependent variable is CO₂ emissions. The statistical methods as the Panel unit root test, Pedroni and Kao panel co-integration test and OLS, FMOLS, and DOLS long-run tests were employed for the empirical part of the paper. The outputs of the Pedroni and Kao panel co-integration tests confirmed that there is a long-term relationship between the analyzed series. The findings of the OLS, FMOLS, and DOLS tests indicate a negative relationship between the analyzed variables. According to the the results of empirical analyzes it was confirmed that there is a statistically significant and negative relationship between agriculture value-added, forest, renewable energy and CO₂ emissions which means that an increase of agricultural production, forest areas and renewable energy consumption decreased the CO₂ emissions in GUAM countries for the time span 1996-2019.

Influence of groundnut and bean seeds fortification with slaughterhouse and palm oil mill wastewaters on growth performance

2024-03-08T10:44:53+01:00

Recycling of waste water for agriculture can improve environmental sustainability while improving cost of farming. The aim of this work is to study the growth performance of groundnut and bean seeds fortified with slaughter house and palm oil mill waste waters. For each wastewater type, 6 concentrations of 100, 75, 50, 25, 10 and 5% were prepared with tap water as the control. The seeds were soaked in each of these samples for a period of 5 hours, 10 hours and 24 hours. The germination percentage was monitored for four weeks while leaf number, and stalk length were monitored for 14 weeks. The soil used was a gravely sandy soil with a bulk density of 2.39 g/cm³. For palm oil mill wastewater, optimum germination for beans seeds was obtained with 10 hours of fortification as germination occurred in all tested concentrations and the control from week two in equal amounts. Meanwhile germination of groundnut seeds fortified with palm oil mill wastewater for 5 hours started with 5, 25 and 75% in week 2 but germination was observed in all concentrations from week 3 and control in week 4. For slaughter house wastewater, optimum germination for groundnut seeds was obtained with 24 hours of fortification for 5-100% in week 2 in equal amounts and control in third week, with similar results for beans fortified for 10 hours. Longer fortification periods (10 and 24 hrs) are more favourable in case of slaughter house wastewater for both seeds germination irrespective of the slaughterhouse wastewater concentration but shorter fortification period favourable for palm oil wastewater (5 hours for groundnut and 10 hours for beans). This results shows that at low concentrations of wastewaters tested irrespective of the fortification time, inhibitory effects on the germination percentages were low compared to higher concentrations.

Heavy metal profiles and pollution indices of top soil sampled from six metallic material scrapyards located in Benin city, Mid Western Nigeria

2024-01-19T10:28:52+01:00

Heavy metal levels and other parameters which included organic carbon content of topsoil samples collected from six metallic material scrapyards and a control sites all located in Benin city were determined using routine techniques. The locations of the visited municipal scrapyards were; Aduwawa, St Savior street, 1st and 2nd Ibiwe, Waterboard at Iyaro (Idia college), and Uwelu. The control soil samples was collected from the premises of the Botanical Garden located within the premises of the Faculty of Life Sciences, University of Benin, Benin City. Duplicate soil samples were collected from the various study locations once every month during the months of February and March, 2022. The pH and EC values of soils collected in February ranged from 6.71 – 7.47 and 606.5 – 2541µS/cm respectively. Soil borne Fe and Pb readings varied from 763.5-2034.5mg/kg and 548.5-1881.5mg/kg as well as 24.50 – 50.35 and 24.75 – 50.60 for samples obtained in February and March respectively. Findings in this study revealed that soil samples obtained from the various scrapyard dumpsites where contaminated with high levels of heavy metals such as Iron, Lead, Chromium and Cadmium. Furthermore, it was observed that the levels of heavy metals analyzed in soil samples from the various scrapyard dumpsites were generally higher in values compared to control sites. Continuous monitoring and further studies on the prevailing soil borne levels of these trace metals should be conducted at regular intervals to ascertain long-term effects on the surrounding environment.