持续性
生命周期评估
赤铁矿
零价铁
环境修复
针铁矿
环境科学
环境可持续性指数
能值
废物管理
材料科学
生产(经济)
污染
工程类
化学
吸附
冶金
经济
有机化学
宏观经济学
生物
生态学
作者
Caroline Visentin,Adan William da Silva Trentin,Adéli Beatriz Braun,Antônio Thomé
标识
DOI:10.1016/j.envpol.2020.115915
摘要
Nanoscale zero-valent iron (nZVI) is the main nanomaterial used in environmental remediation processes. The present study aims to evaluate the life cycle sustainability of nZVI production methods applied in environmental remediation. Three production methods of nZVI were selected for analysis: milling, liquid reduction with sodium borohydride, and chemical reduction with hydrogen gas (in two approaches: considering the goethite and hematite synthesis and after using in nZVI production and, using goethite and hematite particles already synthesized for nZVI production). The life cycle sustainability assessment was carried out based on a multi-criteria and multi-attribute analysis. The multi-criteria analysis was used to determine impact category preferences of different specialists in sustainability and remediation, and calculate the sustainability score through a linear additive model. Finally, a Monte Carlo simulation was used to quantify the results uncertainty. The functional unit considered was 1.00 kg of nZVI produced. The milling method and the hydrogen gas method in approach considering the use goethite and hematite particles already synthesized were the most sustainable. Moreover, the sustainability index was found to be influenced by the considered location scenarios as well as the perspectives of the different specialists, which was essential in producing a more accurate and comprehensive evaluation of the aforementioned sustainability methods. Overall, this study significantly contributed to applications of the state-of-the-art life cycle sustainability assessment in studies regarding nanomaterials, employing a simple methodology that included an analysis of different specialists. In addition, this is the first article that uses life cycle sustainability assessment in nanomaterials.
科研通智能强力驱动
Strongly Powered by AbleSci AI