Examination of the Mathematical Models Used in Atmospheric Source Apportionment Studies

大气源解析研究中使用的数学模型的检验

• 批准号: 9114750
• 负责人: Philip Hopke
• 金额: $ 28.45万
• 依托单位: Clarkson University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-12-01 至 1995-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9114750&HistoricalAwards=false
• 关键词: Examination; Mathematical; Models; Used; Atmospheric

During the past 2 decades, there has been increasing use of multielemental analytical methods to characterize airborne particulate matter and collected precipitation. With the availability of these large multivariate data sets and new multivariate 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. The original objective of this on-going research program was to continue the examination of the statistical problems associated with the source identification and mass apportionment of urban aerosols. During the current grant period, the program has changed its emphasis toward larger scale phenomena and the development and testing of statistical methods to extract information from analyzed samples obtained on a larger spatial and temporal scale. Specifically, the PI proposes to validate the Potential Source Contribution Function (PSCF) analysis and Total Potential Source Contribution Function (TPSCF) analysis Techniques both by applying PSCF to small-scale data sets and applying PSCF to the Across North America Tracer Experiment (ANATEX) data where the location and quantities of source emissions are known, to study and further develop three- way modeling via the application of existing methods to additional data sets and an investigation into alterations that may be necessary to these methods in the presence of constraints, and the further study of empirical orthogonal functions and their use in studying ozone transport.

在过去的二十年中，越来越多地使用多元素分析方法来表征空气中的颗粒物和收集的降水。 随着这些大型多元数据集和新的多元统计方法的出现，这些方法因计算机规模和速度的不断增加而变得实用，从表征收集的颗粒或降水的数据中提取有关大气过程的信息的机会增加了。 这项正在进行的研究计划的最初目标是继续研究与城市气溶胶的来源识别和质量分配相关的统计问题。 在当前的资助期内，该计划已将重点转向更大规模的现象以及统计方法的开发和测试，以从更大的空间和时间尺度上获得的分析样本中提取信息。 具体来说，PI建议验证潜在源贡献函数（PSCF）分析和总潜在源贡献函数（TPSCF）分析技术，将PSCF应用于小规模数据集，并将PSCF应用于已知源排放位置和数量的跨北美示踪实验（ANATEX）数据，通过将现有方法应用于其他数据集和调查来研究和进一步开发三向模型 在存在限制的情况下可能需要对这些方法进行改变，以及进一步研究经验正交函数及其在研究臭氧传输中的用途。