Identifying likely PM 2.5 sources on days of elevated concentration: A simple statistical approach

Nanjun Chu, Joseph B. Kadane, Cliff I. Davidson

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

A simple statistical method is described for identifying the likely importance of local sources of PM 2.5 in a region on days when the National Ambient Air Quality Standard is exceeded. The method requires only PM 2.5 mass concentration and wind direction data, and makes use of the EPA database on PM 2.5 emissions in the local region of interest. The method has been illustrated using data from the Pittsburgh Air Quality Study, and suggests that local sources can be very important in affecting PM 2.5 exceedances. The results have implications for many of the urban areas in the eastern United States downwind of large sources in the Midwest, and shows that simple statistical tests can be of value in identifying regions where further testing with sophisticated air quality dispersion models and source-receptor models is warranted.

Original languageEnglish (US)
Pages (from-to)2407-2411
Number of pages5
JournalEnvironmental Science and Technology
Volume43
Issue number7
DOIs
StatePublished - Apr 1 2009
Externally publishedYes

ASJC Scopus subject areas

  • General Chemistry
  • Environmental Chemistry

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