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Quantification of variability and uncertainty in emission estimation: General methodology and software implementation.

机译：排放估算中可变性和不确定性的量化：通用方法和软件实施。

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摘要

The use of probabilistic analysis methods for dealing with variability and uncertainty is being more widely recognized and recommended in the development of emission factor and emission inventory. Probabilistic analysis provides decision-makers with quantitative information about the confidence with which an emission factor may be used. Variability refers to the heterogeneity of a quantity with respect to time, space, or different members of a population. Uncertainty refers to the lack of knowledge regarding the true value of an empirical quantity. Ignorance of the distinction between variability and uncertainty may lead to erroneous conclusions regarding emission factor and emission inventory. This dissertation extensively and systematically discusses methodologies associated with quantification of variability and uncertainty in the development of emission factors and emission inventory, including the method based upon use of mixture distribution and the method for accounting for the effect of measurement error on variability and uncertainty analysis. A general approach for developing a probabilistic emission inventory is presented. A few example case studies were conducted to demonstrate the methodologies. The case studies range from utility power plant emission source to highway vehicle emission sources. A prototype software tool, AUVEE, was developed to demonstrate the general approach in developing a probabilistic emission inventory based upon an example utility power plant emission source. A general software tool, AuvTool, was developed to implement all methodologies and algorithms presented in this dissertation for variability and uncertainty analysis. The tool can be used in any quantitative analysis fields where variability and uncertainty analysis are needed in model inputs.
机译：在开发排放因子和排放清单时，使用概率分析方法来处理变异性和不确定性已得到广泛认可和推荐。概率分析为决策者提供了有关可以使用排放因子的置信度的定量信息。变异性是指数量相对于时间，空间或总体不同成员的异质性。不确定性是指缺乏关于经验量的真实价值的知识。忽略可变性和不确定性之间的区别可能会导致有关排放因子和排放清单的错误结论。本文广泛而系统地讨论了与排放因子和排放清单的发展中的可变性和不确定性量化相关的方法，包括基于混合分布的方法和考虑测量误差对可变性和不确定性分析的影响的方法。介绍了开发概率排放清单的一般方法。进行了一些示例案例研究，以证明该方法。案例研究的范围从公用电厂的排放源到公路车辆的排放源。开发了原型软件工具AUVEE，以演示基于示例公用电厂排放源的概率排放清单开发的一般方法。开发了通用软件工具AuvTool来实现本文中介绍的用于可变性和不确定性分析的所有方法和算法。该工具可用于模型输入中需要变异性和不确定性分析的任何定量分析领域。

著录项

  • 作者

    Zheng, Junyu.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Engineering Environmental.; Chemistry Analytical.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 304 p.
  • 总页数 304
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 环境污染及其防治;化学;
  • 关键词

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