Gasification is one of the most important thermochemical processes to convert a solid fuel to energy carriers of a gaseous product called syngas. This process has been well addressed in the literature for biomass and several valuable researches have been performed on plastic waste gasification. However, it is the first effort for a systematic comprehensive investigation and multi-objective optimization of gasification process for waste polymeric foams using response surface methodology and TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) approach. Air and steam waste rigid polyurethane foam gasifications were modeled using coupled method of Gibbs minimization free energy and Lagrange method of undetermined multipliers, and then, validated. Effects of key features consisting gasification temperature and moisture content in both air and steam gasification types and equivalence ratio in air and steam to waste foam ratio in steam types were thoroughly studied on gas composition and energy and hydrogen efficiencies. Analysis of variance was employed for recognizing the most effective parameters on air and steam gasification performances. The results revealed that hydrogen and energy efficiencies of air gasification at multi-objective optimum conditions were 42.68 % and 89.58 %, respectively, and these values were 64.02 % and 96.52 % for steam gasification type. Air gasification of waste rigid polyurethane foam produced 3.13 g of CO₂ emission at optimum state; however, its value was 10.02 g for steam gasification type. A multi-criteria decision analysis based on TOPSIS method was utilized for selecting the best gasification type in different scenarios and the findings indicated that air gasification had better performance compared to steam type due to its low emissions.

气化是将固体燃料转化为称为合成气的气态产品的能量载体的最重要的热化学过程之一。这个过程在生物质的文献中得到了很好的解决，并且已经对塑料废物气化进行了一些有价值的研究。然而，这是使用响应面方法和 TOPSIS（通过与理想解决方案相似的顺序性能技术）方法对废弃聚合物泡沫的气化过程进行系统全面调查和多目标优化的首次尝试。使用吉布斯最小化自由能和拉格朗日不确定乘数法的耦合方法对空气和蒸汽废物硬质聚氨酯泡沫气化进行建模，然后进行验证。深入研究了包括空气和蒸汽气化类型的气化温度和水分含量以及空气和蒸汽与蒸汽类型的废泡沫比的当量比对气体成分以及能量和氢气效率的关键特征的影响。方差分析用于识别空气和蒸汽气化性能的最有效参数。结果表明，多目标优化条件下空气气化的氢气和能量效率分别为42.68%和89.58%，蒸汽气化类型的这些值分别为64.02%和96.52%。废弃硬质聚氨酯泡沫的空气气化产生 3.13 克 CO 结果表明，多目标优化条件下空气气化的氢气和能量效率分别为42.68%和89.58%，蒸汽气化类型的这些值分别为64.02%和96.52%。废弃硬质聚氨酯泡沫的空气气化产生 3.13 克 CO 结果表明，多目标优化条件下空气气化的氢气和能量效率分别为42.68%和89.58%，蒸汽气化类型的这些值分别为64.02%和96.52%。废弃硬质聚氨酯泡沫的空气气化产生 3.13 克 CO₂最佳状态下的排放；但是，蒸汽气化型的值为 10.02 g。基于 TOPSIS 方法的多准则决策分析用于选择不同场景下的最佳气化类型，结果表明，空气气化由于其排放量低而比蒸汽类型具有更好的性能。