摘要
文章基于生命周期评价(life cycle assessment,LCA)法对以N-甲基吡咯烷酮(N-Methylpyrrolidone,NMP)为溶剂精制再生废矿物油工艺的环境影响进行分析,并与传统的减压蒸馏再生废矿物油工艺进行比较;对NMP精制工艺清单数据在正态分布范围内的LCA结果进行Monte Carlo不确定性分析。结果表明:NMP精制工艺主要的中点环境影响类别为呼吸系统无机物、全球变暖潜势和不可再生资源,端点影响类别为人类健康,总环境影响相比于传统的减压蒸馏工艺降低18.74%,说明NMP精制工艺对环境更加友好;NMP精制工艺不确定性分析结果中,多个影响类别的变异系数超过15%,说明参数的不确定性对LCA结果具有不可忽视的影响。LCA法可以准确识别废矿物油再生工艺的环境影响与贡献水平,并根据不确定性与敏感性分析结果为后续工艺的改进与研究提供环境影响方面的思路与方法。
This paper is based on the life cycle assessment(LCA)method to analyze the environmental impact of the process of waste mineral oil regeneration by solvent refining with N-Methylpyrrolidone(NMP)and to compare this process with the conventional process of waste mineral oil regeneration by reduced-pressure distillation.The results of the LCA are also analyzed for uncertainty in the range of normal distribution for the NMP refining process inventory data.The results indicate that the main midpoint environmental impact categories of the NMP refining process include respiratory inorganic substances,global warming potential and nonrenewable resources,and the endpoint impact category is human health.The total environmental impact of the NMP refining process is 18.74%lower than that of traditional reduced-pressure distillation process,indicating that the NMP refining process is more environmentally friendly.The results of Monte Carlo uncertainty analysis of NMP refining process show that the coefficient of variation of several impact categories exceeds 15%,indicating that the uncertainty of parameters has a non-negligible effect on the LCA evaluation results.The LCA evaluation method can accurately identify the environmental impact and contribution level of the waste mineral oil regeneration process,and provide ideas and methods for subsequent process improvement and research based on the results of the uncertainty and sensitivity analysis.
作者
熊鸿斌
丁涛
XIONG Hongbin;DING Tao(School of Resources and Environmental Engineering,Hefei University of Technology,Hefei 230009,China)
出处
《合肥工业大学学报（自然科学版）》
CAS
北大核心
2023年第8期1009-1017,共9页
Journal of Hefei University of Technology：Natural Science
基金
安徽省科技攻关计划重大科技专项资助项目(08010302114)。
