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AN EMPIRICAL AIR QUALITY ANALYSIS UTILIZING COMPUTER-ASSISTED CARTOGRAPHIC MODELING TECHNIQUES.

机译:利用计算机辅助制图技术对空气质量进行经验分析。

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摘要

A general methodology is proposed for analyzing air quality problems as spatial relationships through the use of computer-assisted cartographic modeling techniques. Geographically oriented data are stored, manipulated, and analyzed in the form of computer maps. An empirical air pollutant dispersion model is developed as a spatial relationship in an intrinsically linear form. The cartographic analyses system is interfaced with a statistical data management package (SAS, 1979) and the model is parameterized by a multiple regression optimization technique. The methodology is applied to the analyses of heavy metal particulates surrounding a lead/zinc smelter in a mountain valley location. Emissions dispersed from over one-hundred sources are simultaneously analyzed over two-hundred days of lead, cadmium, and total suspended particulate data. Industrial point sources and fugitive emissions from the metals industry, roads, and dust reentrained by the wind are considered. Non-homogeneity associated with complex terrain and inconstant source behavior is addressed in the model formulation. The effect of reentrained fugitive dusts on the attainment of the National Ambient Air Quality Standard for Lead is quantified and presented graphically. The potential utilization of the methodology in academic and regulatory practice is discussed.
机译:提出了一种通用方法,通过使用计算机辅助制图建模技术来分析空气质量问题作为空间关系。地理数据以计算机地图的形式存储,处理和分析。建立了经验性空气污染物扩散模型,作为固有线性形式的空间关系。制图分析系统与统计数据管理软件包(SAS,1979)相连,并且该模型通过多元回归优化技术进行参数设置。该方法适用于分析山谷位置铅/锌冶炼厂周围的重金属颗粒。在200天的铅,镉和总悬浮颗粒物数据中,同时分析了来自一百多个源的排放物。考虑了来自金属行业,道路和被风夹带的灰尘的工业点源和逃逸排放物。在模型公式中解决了与复杂地形和源行为不稳定相关的不均匀性。量化并以图形方式显示了重新夹带的扬尘对达到《国家环境空气铅标准》的影响。讨论了该方法在学术和监管实践中的潜在利用。

著录项

  • 作者单位

    Yale University.;

  • 授予单位 Yale University.;
  • 学科 Geological Survey.; Environmental Sciences.
  • 学位 Ph.D.
  • 年度 1980
  • 页码 357 p.
  • 总页数 357
  • 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

  • 入库时间 2022-08-17 11:51:40

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