响应面法优化海藻酸钠碳捕集与封存技术

0 ENERGY & FUELS
Muhammad Arqam Khan , Shaine Mohammadali Lalji , Moiz Ali Khan Sial , Areeba Batool , Mohsin Ayubi , Syed Imran Ali , Muhammad Mustafa , Mei-Chun Li
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引用次数: 0

摘要

对可持续碳捕获技术的需求日益增长,需要探索新的二氧化碳吸收溶剂。碳捕集与封存(CCS)是控制温室气体排放、应对气候变化的关键技术。本研究利用模拟软件Aspen Plus研究了海藻酸钠(Na-Alg)作为生物基溶剂在碳捕集技术中的效率。建立了模拟塔板中CO2吸收的模型,并使用温度、压力、溶剂流速等关键参数对海藻酸钠溶液的性能进行了分析,以最大限度地提高碳捕获效率。并结合已有文献和实验数据对仿真结果进行验证,发现仿真结果具有较好的相关性。采用海藻酸钠溶液对CO2的捕集效率可达97%。采用响应面法评估了工艺参数之间的关系及其对CO2捕集的影响,确定了10 - 20℃、10 bar压力、20-25 kmol/h溶剂流速的最佳条件。这些发现突出了海藻酸钠作为一种有效的、环保的CCS溶剂的潜力,具有环境和操作优势。该研究还证明了仿真和优化技术在提高CCS性能方面的效用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of carbon capture and storage technology using sodium alginate through response surface methodology
The increasing demand for sustainable carbon capture technologies necessitates the exploration of novel solvents for CO2 absorption. Carbon Capture and Storage (CCS) is a critical technology for controlling greenhouse gas emissions and tackling climate change. This study investigated the efficiency of sodium alginate (Na-Alg) as a bio-based solvent in carbon capture technology using the simulation software, Aspen Plus. The model was developed to simulate the absorption of CO2 in a tray column, and the performance of sodium alginate solution was analyzed using various key parameters, including temperature, pressure, and solvent flow rate, to maximize the carbon capture efficiency. The simulation was then validated with the help of existing literature and experimental data and was found to be in good correlation. The carbon capture efficiency of CO2 was observed at 97 % using sodium alginate solution. The relations between process parameters and their influence on CO2 capture were evaluated by applying response surface methodology, identifying optimal conditions at 10–20 °C, 10 bar pressure, and a solvent flow rate of 20–25 kmol/h. These findings highlight the potential of sodium alginate as an effective, eco-friendly solvent for CCS, offering both environmental and operational advantages. The study also demonstrates the utility of simulation and optimization techniques in enhancing CCS performance.
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