Modelling and Optimizing the Effect of pH on Remediation of Crude Oil Polluted Soil with Biochar Blend: RSM Approach

Abstract

This research modelled the effect of pH on the remediation of crude oil-polluted soil using biochar blend. The biochar blends, PL-500, pW-500, and RS-400, were made by pyrolyzing poultry litter, pine wood, and rice straw at varied temperatures and times. The pH of the crude oil polluted soil was 4.72. Response surface experimental design mixed biochar to remediate total petroleum hydrocarbons (TPH). Following 30 days of bioremediation, 15g PL-500, 3g PW-500 and 6g RS-400, removed a maximum of 46% TPH. The experimental data were statistically modelled and optimized using design expert software and response surface methods. Analysis of variance (ANOVA) was used to determine the significance of each regression coefficient. Biochar blend improved soil pH to 6.9 following remediation. ANOVA indicated that PL-500 was significant for predicting TPH % degradation at p =0.0290, suggesting that its high pH, nutrient, and soil water conservation values made it more effective in remediating TPH. The quadratic model predicts with R2 =0.8567. A model fit statistics were used to examine soil pH influence on TPH remediation. RSM study indicated a good positive association between statistical model and experiment with R2 = 0.7612. The model fits experimental data and predicts that . Remediation requires soil pH and biochar's alkalinity raised soil pH to 6.9, which promoted hydrocarbon-utilizing bacteria.

Biodegradation Potential of Neptunomonas naphthovoran - NAG-2N-126 for Crude Oil Pollution Mitigation: Experimental and Modelling Insights

“…The contamination of marine ecosystems by crude oil remains a pressing environmental concern, necessitating urgent action to mitigate its far-reaching ecological 2 and socioeconomic impacts [1]. Oil spills, whether resulting from industrial accidents, transportation mishaps, or natural disasters, pose immediate threats to marine life, coastal habitats, and human health [2]. In response to these challenges, bioremediation has emerged as a promising and environmentally sustainable approach for mitigating the impacts of oil pollution [3,4].…”

“…In addressing the pervasive challenges posed by crude oil pollution, mathematical modelling has emerged as a crucial tool for understanding and predicting the dynamics of oil biodegradation and remediation processes [10]. With the increasing frequency of oil spills and their detrimental impacts on the environment, there is a growing imperative to develop effective strategies for mitigating oil pollution [2]. Modelling approaches offer valuable insights into the complex interactions between environmental factors, microbial activity, and oil degradation kinetics, thereby facilitating the design and optimization of bioremediation techniques [11].…”