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Emerging Technologies for Environmental Remediation: Integrating Data and Judgment

机译:新兴的环境修复技术:集成数据和判断

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摘要

Emerging technologies present significant challenges to researchers, decision-makers, industry professionals, and other stakeholder groups due to the lack of quantitative risk, benefit, and cost data associated with their use. Multi-criteria decision analysis (MCDA) can support early decisions for emerging technologies when data is too sparse or uncertain for traditional risk assessment It does this by integrating expert judgment with available quantitative and qualitative inputs across multiple criteria to provide relative technology scores. Here, an MCDA framework provides preliminary insights on the suitability of emerging technologies for environmental remediation by comparing nanotechnology and synthetic biology to conventional remediation methods. Subject matter experts provided judgments regarding the importance of criteria used in the evaluations and scored the technologies with respect to those criteria. The results indicate that synthetic biology may be preferred over nanotechnology and conventional methods for high expected benefits and low deployment costs but that conventional technology may be preferred over emerging technologies for reduced risks and development costs. In the absence of field data regarding the risks, benefits, and costs of emerging technologies, structuring evidence-based expert judgment through a weighted hierarchy of topical questions may be helpful to inform preliminary risk governance and guide emerging technology development and policy.
机译:由于缺乏与使用它们相关的定量风险,收益和成本数据,新兴技术对研究人员,决策者,行业专家和其他利益相关者群体提出了严峻挑战。当数据过于稀疏或不确定以至于传统风险评估时,多标准决策分析(MCDA)可以支持新兴技术的早期决策。它通过将专家判断与跨多个标准的可用定量和定性输入相集成,以提供相对的技术得分来做到这一点。在这里,MCDA框架通过将纳米技术和合成生物学与常规修复方法进行比较,提供了有关新兴技术对环境修复的适用性的初步见解。主题专家对评估中使用的标准的重要性提供了判断,并根据这些标准对技术进行了评分。结果表明,合成生物学可能比纳米技术和常规方法更受青睐,因为它们具有较高的预期收益和较低的部署成本,但是对于降低风险和开发成本,常规技术可能比新兴技术更受青睐。在缺乏有关新兴技术的风险,收益和成本的现场数据的情况下,通过对主题问题进行加权层次结构来构建基于证据的专家判断,可能有助于初步风险管理,并指导新兴技术的发展和政策。

著录项

  • 来源
    《Environmental Science & Technology》 |2016年第1期|349-358|共10页
  • 作者单位

    Environmental Laboratory, Engineer Research and Development Center, U.S. Army Corps of Engineers, 696 Virginia Road, Concord, Massachusetts 01742, United States;

    RTI International, 3040 East Cornwallis Road, Research Triangle Park, North Carolina 27709, United States;

    School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, Michigan 48109, United States;

    College of Management, University of Massachusetts Boston, 100 Morrissey Boulevard, Boston, Massachusetts 02125, United States;

    Contractor to U.S. Army Corps of Engineers, SOL Engineering Services, 696 Virginia Road, Concord, Massachusetts 01742, United States;

    Environmental Laboratory, Engineer Research and Development Center, U.S. Army Corps of Engineers, 696 Virginia Road, Concord, Massachusetts 01742, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
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