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DOI | 10.1016/j.jclepro.2019.118499 |
Production of syngas via gasification using optimum blends of biomass | |
AlNouss A.; McKay G.; Al-Ansari T. | |
发表日期 | 2020 |
ISSN | 9596526 |
卷号 | 242 |
英文摘要 | Considering changes in the global climate, there is an impetus to diversify away from fossil fuels as part of efforts to reduce greenhouse gas emissions. Biomass, as a source of energy, has the potential to generate sustainable power and fuels and contribute towards a cleaner future. In fact, the utilisation of biomass as a carbon dioxide neutral organic source in an integrated system generates valuable products, and reduces waste and the consumption of non-renewable resources. Gasification, the preferred option for converting biomass to combustible gas, provides higher electrical efficiencies than combustion, whereby the syngas generated from the gasification process can be utilised to generate clean energy. In addition, syngas can be utilised for the production of ammonia and methanol thus reducing their respective dependencies on natural gas. This study will detail an optimised biomass gasification process considering multiple parameters, including the thermodynamic operating conditions, the type of gasifier (gasifying agent) and feedstock. Fundamentally, this study considers the process pathways for the recycling of multiple sources of biomass to generate high energy syngas from the available biomass options when used in combination as blends or individually. To achieve this aim, an Aspen Plus simulation model is developed for four different biomass agent-based gasification techniques using the biomass characteristics of certain Qatar biomass materials, which include date pits, manure and sewage sludge. Outcomes of the study included an optimisation of the gasification processes to yield different blending options of the biomass feedstock satisfying the downstream operations of power and fuels production. The results demonstrate the domination of date pits for two of the considered configurations with over 99% w/w date pit feed composition. Moreover, the sensitivity analysis conducted on the different configurations highlighted specific optimum operation points in terms of temperature, pressure, and oxygen and steam feed ratios. The hydrogen content in the generated syngas, considered important for the downstream production, yields a peak at approximately 850 °C and 1 bar with a modified equivalence ratio of approximately 2.5, and a ratio of oxygen supplied by an air-steam combination of approximately 0.6. The process can be further optimised by considering trade-offs between product purity or yield, profit, operating efficiency, quality of raw materials blends, and carbon footprint. Elsevier Ltd |
英文关键词 | Biomass blending; Biomass gasification; Gasification performance; Optimisation; Sensitivity analysis; Simulation |
scopus关键词 | Ammonia; Blending; Carbon dioxide; Carbon footprint; Computer software; Economic and social effects; Feedstocks; Fertilizers; Fossil fuels; Gas emissions; Gasification; Greenhouse gases; Organic carbon; Sensitivity analysis; Sewage sludge; Synthesis gas; Synthesis gas manufacture; Waste incineration; Biomass Gasification; Downstream operation; Electrical efficiency; Gasification process; Non-renewable resource; Operating efficiency; Optimisations; Simulation; Biomass |
来源期刊 | Journal of Cleaner Production
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文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/177027 |
作者单位 | Department of Chemical Engineering, College of Engineering, Qatar UniversityDoha, Qatar; Division of Sustainable Development, College of Science and Engineering, Hamad Bin Khalifa University, Qatar FoundationDoha, Qatar |
推荐引用方式 GB/T 7714 | AlNouss A.,McKay G.,Al-Ansari T.. Production of syngas via gasification using optimum blends of biomass[J],2020,242. |
APA | AlNouss A.,McKay G.,&Al-Ansari T..(2020).Production of syngas via gasification using optimum blends of biomass.Journal of Cleaner Production,242. |
MLA | AlNouss A.,et al."Production of syngas via gasification using optimum blends of biomass".Journal of Cleaner Production 242(2020). |
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