Environmental pollution caused by used engine oil has been on the increase as a result of accidental or deliberate discharge of the oil. Used engine oil is relatively recalcitrant to biodegradation due to the high concentrations of metals from the wear and tear of engine parts. Several physical and chemical methods were employed for the remediation of used engine oil-contaminated soil, but bioremediation remains the most economical especially in remediating polluted soils. Therefore, this work aimed to isolate and screen efficient used engine oil-degrading bacteria from serval automobile workshops located at Gadau town, Itas Gadau, Bauchi state, Nigeria. Soil samples were collected from three different locations and were used to isolate, and screen used engine oil-degrading bacteria. The best degrader was Pseudomonas sp. with 82% degradation of 1% (v/v) of used engine oil after 5 days of aerobic incubation. The result further indicated that degradation occurs best at 1% (v/v) and no degradation was recorded at 3% (v/v) of used engine oil. Pseudomonas sp. can be employed in the field remediation of used engine oil-contaminated soil.

Adults who are exposed to high levels of lead may develop hypertension and kidney damage. Lead exposure is dangerous for everyone, but it can have devastating effects on pregnant women and their babies. Methods such as membrane separation, ion exchange, precipitation, and biosorption are currently in use for the removal of lead pollution. Biosorption has the fewest negative aspects of these technologies due to its low operating costs, high efficiency at detoxifying low concentrations of toxicants, and small volume of disposal materials. The biosorption of the biosorption of lead (II) onto the activated carbon from Tridax procumbens is remodeled using nonlinear regression and the optimal mode was determined by a series of error function assessments. The best kinetic model for adsorption of lead (II) was Pseudo-1st order with a reasonable difference in terms of corrected Akaike Information Criterion to the next best model, which was pseudo-2nd order, and followed by the Elovich. However, the error function analyses especially the AICc was not conclusive in ranking the pseudo-1st order model as the best model due to the low (less than 5) absolute values of differences between the model. The pseudo-1st order kinetic constants obtained were qe (mg/g) of 6.181 (95% confidence interval from 5.009 to 7.352) and k1 (per min) of 0.007 (95% confidence interval from 0.004 to 0.009). Nonlinear modeling enables the determination of a 95 percent confidence interval for the uncertainty range, which can be used in model comparison and discriminant analysis.

Acrylamide is a suspected carcinogen and a global pollutant. The presence of acrylamide in the soil is a major source of this chemical. Microbe-mediated acrylamide breakdown as a bioremediation technique is gaining popularity across the world. Several bacteria capable of digesting acrylamide have been identified in paddy field soils. The best isolate was a bacterium identified tentatively as E. cloacae strain UPM2021a based on cultural, colony morphology and biochemical tests. According to early studies, ideal growth parameters included a pH range of 6.5 and 7.5 and a temperature range of 25 to 35 degrees Celsius. Acrylamide dosages of up to 2500 mg/L were explored as a single nitrogen supply. The greatest growth occurs between 300 and 1000 mg/L of acrylamide, resulting in an approximate nett growth of 3 log CFU/mL when compared to the control. Growth was practically tolerated at 1700 mg/L, and growth stopped entirely at concentrations above 2000 mg/L. Toxic heavy metals such as mercury, copper, chromium, and cadmium hampered acrylamide development with mercury being the strongest inhibitor whilst other metal ions such as copper, cadmium, and chromium show from 30 to 50% inhibition whilst lead was the least inhibiting. The relatively high tolerant of acrylamide makes this bacterium suitable for remediation of soil contaminated with acrylamide whilst its sensitivity to heavy metals chiefly mercury means metal-chelating or sequestering compounds must be added to soil contaminated with both acrylamide and heavy metals.

Tannery effluent has remained one of the major sources of chromium pollution in the environment. Although conventional methods have been widely used, they are inefficient and costly. Bacterial remediation is one of the best alternatives being proposed. Therefore, the aim of this research was to isolate bacteria from tannery effluents and screen them for chromium-reduction potentials. Three different tannery effluents were collected and used for the isolation of chromium-reducing bacteria. The organisms were identified using morphological and biochemical characteristics and screened on 1% (v/v) Cr (VI). The results revealed the presence of three bacterial species, namely: Bacillus subtilis, Escherichia coli and Pseudomonas sp. The screening results revealed that out of the three bacterial isolates, Bacillus subtilis had the highest reduction potential (86.23%), while equal reduction capacity was recorded in both E. coli and Pseudomonas sp. (84.03%). Therefore, these three isolates can be used as a consortium to improve biological remediation of Cr (VI) effluents.

While Cd production, consumption, and environmental release have all skyrocketed in recent decades, there is currently no practical way to recycle Cd compounds. This suggests that Cd compounds may be very dangerous to human health. Due to this cadmium remediation from polluted environment is urgently needed. Several viable technologies include biosorption, which has several positive aspects which include low operating expenses, very efficient detoxification of toxicants at low concentrations and low amount of disposal materials. The biosorption of the biosorption of cadmium onto the activated carbon from Tridax procumbens is remodeled using nonlinear regression and the optimal mode was determined by a series of error function assessments. Statistical analysis showed that the best kinetic model for adsorption was pseudo-1st order. All error function analyses supported the pseudo-1st order model. The pseudo-1st order kinetic constants obtained were qe (mg/g) of 5.808 (95% confidence interval from 5.043 to 6.573) and k1 (per min) of 0.009 (95% confidence interval from 0.0064 to 0.0117). Nonlinear modeling enables the determination of a 95 percent confidence interval for the uncertainty range, which can be used in model comparison and discriminant analysis.