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Issues in the analysis of air quality modeling data in attainment demonstrations of the 8-hr ozone standard.

机译:在达到8小时臭氧标准的演示中,空气质量建模数据的分析问题。

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摘要

Attainment demonstrations of the ozone standard serve as the basis for regional air quality planning, but do the recommended analytical techniques establish control strategies that will be effective? The relative interpretation of model data was introduced by the Environmental Protection Agency (EPA) to compensate for poor model performance, and use of 8-hr averages was introduced to mirror the standard. The sensitivity of the relative reduction factor (RRF) is tested against model bias, using a Houston, Texas regulatory model. There is an inverse linear correlation with model bias at each site (R2 = 0.47), changing future design values by 0-5 ppb. Ninety percent of cell selections for the RRF calculation in these episodes are 14-19 km from the monitor. The RRF approach is recommended only when modeled ozone response is linear. Model error statistics using 8-hr concentration averages overestimate performance compared to those using 1-hr values (11.7% versus 14.8%, median).
机译:臭氧标准的达到证明是区域空气质量计划的基础,但是推荐的分析技术是否可以建立有效的控制策略?环境保护局(EPA)引入了模型数据的相对解释,以弥补模型性能不佳的问题,并引入了8小时平均值来反映标准。使用得克萨斯州休斯顿的管制模型,针对模型偏差测试了相对降低因子(RRF)的敏感性。每个站点的模型偏差存在反线性相关性(R2 = 0.47),将未来的设计值更改为0-5 ppb。在这些情节中,用于RRF计算的90%的小区选择距离监测仪14-19公里。仅当建模的臭氧响应为线性时才建议使用RRF方法。与使用1小时值的模型误差统计相比,使用8小时浓度的模型误差统计平均值平均高估了性能(中值分别为11.7%和14.8%)。

著录项

  • 作者

    Biton, Leiran.;

  • 作者单位

    The University of North Carolina at Chapel Hill.$bEnvironmental Sciences & Engineering.;

  • 授予单位 The University of North Carolina at Chapel Hill.$bEnvironmental Sciences & Engineering.;
  • 学科 Atmospheric Sciences.; Environmental Sciences.
  • 学位 M.S.
  • 年度 2007
  • 页码 171 p.
  • 总页数 171
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 环境科学基础理论;
  • 关键词

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