Sustainable solutions for co-gasification of sewage sludge and biomass: Insights from Aspen Plus, response surface methodology, and multi-criteria decision-making integration

被引:0
|
作者
Tang, Huanchen [1 ]
Dong, Jingyang [1 ]
Mei, Dan [2 ]
Xu, Di [1 ]
Yuan, Jinhai [1 ]
Dong, Lichun [3 ]
机构
[1] Chongqing Univ Sci & Technol, Sch Chem & Chem Engn, Chongqing 401331, Peoples R China
[2] Chongqing Commun Ind Serv Co Ltd, Chongqing, Peoples R China
[3] Chongqing Univ, Sch Chem & Chem Engn, Chongqing 401331, Peoples R China
关键词
Gasification; Simulation; Optimization; Sustainability assessment; Multi-criteria decision-making; Biomass; Sewage sludge; MULTIOBJECTIVE OPTIMIZATION; ENERGY; SIMULATION;
D O I
10.1016/j.eti.2024.103894
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
This paper presents a novel framework integrating process simulation, optimization, and multicriteria decision-making (MCDM) to identify sustainable co-gasification solutions for sewage sludge (SS) and biomass. Gasifier modeling in Aspen Plus, validated with experimental data, evaluated five feedstock blend routes. Sensitivity analysis was conducted on key gasification parameters, while Response Surface Methodology (RSM) optimized process routes by revealing complex relationships between variables and performance metrics. MCDM was applied to assess alternatives based on eight criteria covering environmental, economic, and social sustainability. The study introduced an integrated objective weighting method, leveraging data variations and correlations, alongside a vector-based ranking approach for prioritizing solutions. Results indicated that a biomass-to-sewage sludge ratio of 3:7, under co-gasification conditions of 649.72 degrees C, 1.13 atm, and a steam to feedstock ratio of 0.5, achieved the highest sustainability score of 0.506. This configuration outperformed other alternatives in terms of sustainability. Validation through three distinct analytic methods confirmed the robustness of the MCDM framework. In general, this work integrates simulation, RSM optimization, and MCDM analysis into a streamlined tool, offering a systematic progression from process simulation to decision-making. It reduces the reliance on costly trial-and-error experimentation while ensuring optimal operating conditions and comprehensive sustainability evaluation. These contributions tackle key challenges in data handling, optimization, and assessment, enabling more sustainable and cost-effective environmental technology innovations.
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页数:15
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