4.8 Article

Life cycle inherent toxicity: a novel LCA-based algorithm for evaluating chemical synthesis pathways

期刊

GREEN CHEMISTRY
卷 18, 期 11, 页码 3257-3264

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ROYAL SOC CHEMISTRY
DOI: 10.1039/c5gc02768c

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资金

  1. U.S. National Science Foundation [CBET-1454414]
  2. Directorate For Engineering
  3. Div Of Chem, Bioeng, Env, & Transp Sys [1454414] Funding Source: National Science Foundation

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Green chemistry has long called for a life cycle approach in designing and assessing new syntheses. In evaluating hazardous chemical use, most green chemistry metrics only consider those chemicals directly associated with the synthesis and miss upstream hazards that can contribute to or even dominate overall impacts when evaluated using life cycle assessment (LCA). Conversely, LCA metrics are wholly dependent on emissions and do not capture potential risks posed by inherently hazardous chemicals. Life cycle inherent toxicity i* is a proposed novel metric that adapts the computational framework of LCA by attaching measures of inherent hazard to the intermediate chemical flows, rather than considering only emissions. Thus, it captures toxicity associated with the entire cradle-to-gate of a chemical, rather than just direct chemical inputs into a synthesis, and is a function of upstream use of hazardous chemicals, rather than only emissions. Values of i* are calculated for 181 organic chemicals from the ecoinvent LCI database. Statistical testing revealed no significant correlation between life cycle inherent toxicity and conventional toxicity, suggesting that the proposed metric provides novel information that can be used in conjunction with current green chemistry metrics. Outliers are investigated where the target chemical is much more toxic than its upstream building blocks (e.g., phosgene) and, conversely, where upstream chemical toxicity dominates (e.g., aniline). Values of i* are weakly correlated with values of conventional life cycle toxicity from the USEtox LCIA model, again suggesting that the new metric provides additional knowledge. A similar computational approach can be applied to examine other types of chemical hazards, such as corrosivity.

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