Examination of the Mathematical Models Used in Atmospheric Source Apportionment Studies

查明造成这一现象的各种来源， 在给定位置的空气中颗粒物的组成是一个 发展有效监管的重要先决条件 空气质量政策。 在过去的十年里， 越来越多地使用元素和化学分析 表征空气中颗粒物的方法， 收集的降水。 随着这些大型 数据集和新的多元统计方法， 由于计算机的不断发展， 规模和速度，有一个增强的机会， 从数据中获取有关大气过程的信息 表征收集的颗粒或沉淀。 以来 有些元素与地球化学密切相关， 元素数据中的冗余限制了 这些参数对识别来源有影响。 另一个数据来源是物理表征（大小， 形状，纹理）的单个颗粒通过计算机控制 扫描电镜 这个项目将研究几个基于特征向量的 统计方法来调查区域尺度的运输 空气中的颗粒物 通过使用主成分 分析，经验正交函数，三模因子 分析，预计空间和 气溶胶组成的时间变化可以更好地 理解和与区域气象学的关系 定义了 此外，还将开发用于提取 颗粒纹理的定量测量， 用扫描电子显微镜获得的单个颗粒 显微镜 分形维数、特征向量与傅立叶变换 将探讨分析方法。 化学物质的影响 通过与气体反应来改变颗粒表面 物种对视觉表面的纹理和图像的效果 将研究分析方法。

Identifying the various sources responsible for the composition of airborne particles at a given location is an important prerequisite to developing effective regulatory policies for air quality. During the past decade, there has been increasing use of elemental and chemical analytical methods to characterized airborne particulate matter and collected precipitation. With the availability of these large data sets and new multivariate of statistical methods that have been made practical by the continuing increases in computer size and speed, there is an enhanced opportunity to extract information about atmospheric processes from data characterizing collected particles or precipitation. Since some elements are strongly geochemically related, there is redundancy in the elemented data that limits the number of parameters that are influential in identifying sources. Another source of data is physical characterization (size, shape, texture) of individual particles by computer-controlled scanning electron microscopy. This project will examine several eigenvector-based statistical methods to investigate regional scale transport of airborne particulate matter. By using principal components analysis, empirical orthogonal functions, and three-mode factor analysis, is it expected that the patterns of spatial and temporal variations in the aerosol compositions can be better understood and relationships with the regional meteorology defined. In addition, methods will be developed for extracting quantitative measures of particle texture from images of individual particles obtained with a Scanning Electron Microscope. Fractal dimension, eigenvector and Fourier analysis methods will be explored. The effects of chemical modification of the particle surface by reaction with gaseous species on the visual surface texture and results of the image analysis methods will be examined.