通过优化藻类生物质的超声波预处理,提高生物氢气和沼气的产量,实现可持续能源生产

IF 8 Q1 ENERGY & FUELS
Asad A. Zaidi , Sohaib Z. Khan , Hamad Almohamadi , Enio Pedone Bandarra Filho , Noreen Sher Akbar , M. Imran Khan , Fahid Riaz , Muhammad Farooq
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引用次数: 0

摘要

藻类是一种有前途的可持续能源生产资源,包括沼气和生物氢。研究了超声波预处理对浒苔藻产气量的影响。利用响应面法(RSM),以累积沼气产量为响应参数,对超声时间、振幅和液固比三个关键参数进行了优化。在最佳条件下(5 min超声,30%振幅,20:1液固比),最大累积沼气产量为373 ml,生物氢产率为32.7% (v/v)。扫描电子显微镜(SEM)显示明显的细胞壁破坏,提高了微生物消化的底物利用率。然而,由于抑制作用,长时间的超声处理降低了产率。采用修正的Gompertz模型和Logistic函数模型建立动力学模型表明,预处理样品的反应速度更快,生产潜力更高。本研究强调了US预处理在提高藻类生物降解性方面的潜力,为生物能源生产提供了一种高效、可持续的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing bio-hydrogen and biogas yields through optimized ultrasonic pretreatment of algal biomass for sustainable energy production
Algae are a promising resource for sustainable energy production, including biogas and bio-hydrogen. This study investigates the effect of ultrasonic (US) pretreatment on Enteromorpha algae to enhance biogas yields. Using response surface methodology (RSM), three key parameters—sonication time, amplitude, and liquid-to-solid ratio—were optimized, with cumulative biogas production as the response. The optimal conditions (5 min sonication, 30 % amplitude, 20:1 liquid-to-solid ratio) resulted in a maximum cumulative biogas production of 373 ml and a bio-hydrogen yield of 32.7 % (v/v). Scanning electron microscopy (SEM) revealed significant cell wall disruption, enhancing substrate availability for microbial digestion. However, prolonged sonication reduced yields due to inhibitory effects. Kinetic modeling with Modified Gompertz and Logistic Function models demonstrated faster reaction rates and higher production potentials for pretreated samples. This study highlights the potential of US pretreatment for improving the biodegradability of algae, offering an efficient and sustainable method for bioenergy production.
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来源期刊
Energy nexus
Energy nexus Energy (General), Ecological Modelling, Renewable Energy, Sustainability and the Environment, Water Science and Technology, Agricultural and Biological Sciences (General)
CiteScore
7.70
自引率
0.00%
发文量
0
审稿时长
109 days
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