溶剂
甲醇
环境友好型
化学
化学工业
乙腈
生命周期评估
绿色化学
四氢呋喃
氯化溶剂
离子液体
生化工程
有机化学
环境化学
环境科学
生产(经济)
催化作用
工程类
污染
生态学
宏观经济学
经济
生物
作者
Christian Capello,Ulrich Fischer,Konrad Hungerbühler
出处
期刊:Green Chemistry
[The Royal Society of Chemistry]
日期:2007-01-01
卷期号:9 (9): 927-927
被引量:1613
摘要
Solvents define a major part of the environmental performance of processes in chemical industry and also impact on cost, safety and health issues. The idea of “green” solvents expresses the goal to minimize the environmental impact resulting from the use of solvents in chemical production. Here the question is raised of how to measure how “green” a solvent is. We propose a comprehensive framework for the environmental assessment of solvents that covers major aspects of the environmental performance of solvents in chemical production, as well as important health and safety issues. The framework combines the assessment of substance-specific hazards with the quantification of emissions and resource use over the full life-cycle of a solvent. The proposed framework is demonstrated on 26 organic solvents. Results show that simple alcohols (methanol, ethanol) or alkanes (heptane, hexane) are environmentally preferable solvents, whereas the use of dioxane, acetonitrile, acids, formaldehyde, and tetrahydrofuran is not recommendable from an environmental perspective. Additionally, a case study is presented in which the framework is applied for the assessment of various alcohol–water or pure alcohol mixtures used for solvolysis of p-methoxybenzoyl chloride. The results of this case study indicate that methanol–water or ethanol–water mixtures are environmentally favourable compared to pure alcohol or propanol–water mixtures. The two applications demonstrate that the presented framework is a useful instrument to select green solvents or environmentally sound solvent mixtures for processes in chemical industry. The same framework can also be used for a comprehensive assessment of new solvent technologies as soon as the present lack of data can be overcome.
科研通智能强力驱动
Strongly Powered by AbleSci AI