木质纤维素生物质的预处理和厌氧共消化:最新进展

Q1 Environmental Science
Shiva Lall Sunar , Madhu Kumar Kumara , Raj Kumar Oruganti , Kishan Kumar Khadka , Tarun K. Panda , Debraj Bhattacharyya
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引用次数: 0

摘要

本文综述了木质纤维素生物质(LCB)预处理和厌氧共消化的最新进展,以提高沼气产量。尽管LCB是最丰富的有机材料,具有巨大的可再生能源发电潜力,但LCB的木质素、纤维素和半纤维素的复杂结构对有效的生物降解提出了挑战。综述探讨了各种预处理方法-物理(研磨,微波,挤压),化学(碱性,酸性,深共晶溶剂),生物(真菌,酶)和物理化学方法,通过分解其顽固性结构来提高LCB消化率。此外,它还研究了LCB与肥料、食物垃圾、藻类和废水污泥等营养丰富的基质的厌氧共消化,以优化碳氮比并提高甲烷产量。本文重点介绍了如何结合不同的预处理技术和采用共消化方法提高沼气生产效率。这项全面的分析为开发更有效和可持续的方法将LCB转化为沼气,支持从化石燃料向可再生能源的过渡提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Pretreatment and anaerobic co-digestion of lignocellulosic biomass: Recent developments

Pretreatment and anaerobic co-digestion of lignocellulosic biomass: Recent developments
This review examines recent developments in pretreatment and anaerobic co-digestion of lignocellulosic biomass (LCB) for enhanced biogas production. Despite being the most abundant organic material with significant potential for renewable energy generation, LCB's complex structure of lignin, cellulose, and hemicellulose presents challenges for effective biodegradation. The review explores various pretreatment methods - physical (milling, microwave, extrusion), chemical (alkaline, acid, deep eutectic solvents), biological (fungi, enzymes), and physicochemical approaches that enhance LCB digestibility by breaking down its recalcitrant structure. Additionally, it examines the anaerobic co-digestion of LCB with nutrient-rich substrates like manure, food waste, algae, and wastewater sludge to optimize the carbon-to‑nitrogen ratio and improve methane yields. The paper highlights how combining different pretreatment techniques and employing co-digestion approaches enhances biogas production efficiency. This comprehensive analysis provides valuable insights into developing more effective and sustainable methods for converting LCB into biogas, supporting the transition from fossil fuels to renewable energy sources.
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来源期刊
Bioresource Technology Reports
Bioresource Technology Reports Environmental Science-Environmental Engineering
CiteScore
7.20
自引率
0.00%
发文量
390
审稿时长
28 days
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