Weight of evidence analysis for attributing monitored sulfur dioxide exceedances to emission source zones

  • Stephen Feinberg
  • , Varun Yadav
  • , Jay Turner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A study was conducted to support efforts by the Southeast Michigan Air Quality Study Group (SEMAQS) to address the air quality standards that are based on good science and good policy. In this case, the Michigan Department of Environmental Quality (MDEQ) compliance monitoring station at Southwest High School (SWHS) in the City of Detroit violates the 1-hour SO2 NAAQS. The drivers for exceedances at that site have been a topic of considerable discussion within SEMAQS and were the focus of this study. A top-down analysis was performed to identify the geographic region likely to include the most important SO2 emission source(s) impacting the SWHS site. Hour-specific and daily 1-hr maximum monitored and modeled concentrations were weakly correlated, whereas quantile-quantile plots of the monitored and modeled hourly SO2 concentrations showed reasonably good agreement given the uncertainties when allocating annual emissions to specific hours. This is an abstract of a paper presented at the 106th AWMA Annual Conference and Exhibition (Chicago, IL 6/25-28/2013).

Original languageEnglish
Title of host publication106th Air and Waste Management Association Annual Conference and Exhibition, ACE 2013
PublisherAir and Waste Management Association
Pages2489-2493
Number of pages5
ISBN (Print)9781629934440
StatePublished - 2013
Event106th Air and Waste Management Association Annual Conference and Exhibition, ACE 2013 - Chicago, IL, United States
Duration: Jun 25 2013Jun 28 2013

Publication series

NameProceedings of the Air and Waste Management Association's Annual Conference and Exhibition, AWMA
Volume4
ISSN (Print)1052-6102

Conference

Conference106th Air and Waste Management Association Annual Conference and Exhibition, ACE 2013
Country/TerritoryUnited States
CityChicago, IL
Period06/25/1306/28/13

Keywords

  • Dispersion modeling
  • Nonparametric wind regression
  • Weight of evidence analysis

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