Assessing the impact of alkali pretreatment of rice husk on its composition and product portfolio: Tradeoff between biogas and valuable materials recovery for sustainability

Aparna Reddy, Sameena Begum, Sudharshan Juntupally and Gangagni Rao Anupoju

Renewable Energy, 2024, vol. 226, issue C

Abstract: The burning of agricultural crop residues has evolved into a significant global issue with far-reaching implications for public health and environmental integrity. Utilizing biochemical methodologies to valorize these residues presents a dual advantage, mitigating disposal challenges while concurrently fostering wealth generation through bioenergy production and the creation of value-added materials. Nevertheless, the biodegradation of residues faces impediments due to the presence of recalcitrant silica and lignin. To assess the efficacy and elucidate the performance of biochemical approaches, this study investigates the impact of NaOH treatment (2%, 4%, 6%, 8%, and 10% w/v) on rice husk (RH) at 90 °C for 2 h initially followed by anaerobic digestion (AD) for biogas generation. This recovers silica, yielding residual pulp devoid of lignin, a raw material for biogas generation. Analytical investigation through FE-SEM reveals mild fissures and surface ruptures in 4% NaOH-treated RH, while XRD shows a crystallinity index increase from 43.3% (untreated RH) to 69.4% (NaOH-treated RH). The optimal NaOH concentration, yielding 0.16 g/g of silica and 0.206 L/g VSadded of biogas is 4%. These results highlight tailored NaOH's potential for enhancing silica recovery and biogas production from RH. Spearman's correlation analysis reveals a strong correlation (0.9–1.0) among the reduction in volatile solids (VS %), total solids (TS %), methane yield (mL/g VSadded), and biogas yield (mL/g VSadded). P values for artificial neural network (ANN) and fuzzy models consistently range from 10−4 to 10−19. Achieving sustainability necessitates balancing the trade-off between maximizing biogas production and optimizing silica recovery for an environmentally sound and efficient system.

Keywords: Artificial neural network; Anaerobic digestion; NaOH; Rice husk; Silica (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:226:y:2024:i:c:s0960148124004580

DOI: 10.1016/j.renene.2024.120393

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