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DETECTION AND QUANTIFICATION OF ASYMMETRIC PEAKS
Citation:
CROGHAN, C. W. AND R. W. WILLIAMS. DETECTION AND QUANTIFICATION OF ASYMMETRIC PEAKS. Presented at SouthEast SAS User Group , Atlanta, GA, October 08 - 10, 2006.
Impact/Purpose:
Six objectives have been defined for this study.
(1) To determine the associations between concentrations measured at central site monitors and outdoor residential, indoor residential and personal exposures for selected air toxics, PM constituents, and PM from specific sources.
(2) To describe the physical and chemical factors that affect the relationship between central site monitors and outdoor residential and indoor residential concentrations, including those that affect ambient source impacts.
(3) To identify the human activity factors that influence personal exposures to selected PM constituents and air toxics.
(4) To improve and evaluate models used to characterize and estimate residential concentrations of and human exposures to selected air toxics, PM constituents, and PM from specific sources.
(5) To investigate and apply source apportionment models to evaluate the relationships for PM from specific sources and to determine the contribution of specific ambient sources to residential concentrations and personal exposures to PM constituents and air toxics.
(6) To determine the associations between ambient concentrations of criteria gases (O3, NO2, and SO2) and personal exposures for these gases as well as personal exposures to air toxics, PM constituents, and PM from specific sources.
Description:
One of the goals of a recent U.S. Environmental Protection Agency air pollution study was to relate the participants' activities to their exposures to particulate matter (PM) during their routine activities. PM concentration data were collected continuously with a real-time monitor, downloaded daily in CSV format and concatenated using AWK. Human activity diary information was collected via pen and paper and recovered using scannable decoding software (TeleForm). All data were converted into SAS. The asymmetric response peaks of the particulate matter concentrations made systematic detection and analysis of the area under their respective curves problematic. To overcome this problem, a program was written to locate each peak and generate an integrated value for its response area. Data were smoothed using a running average, inflection points were identified relative to the start and stoppage of each peak, and a moving baseline calculated. Incorporation of human activity descriptors allowed for the quantification of human activity pattern influence upon potential exposures to particulate matter under real-world conditions.We will be discussing two elements in this paper. The first discussion point is the conversion of the data from multiple sources into SAS. The data were collected in various methods including paper questionnaires, computer assisted technician interview, and electronic transfer from the monitoring instrument. The second element is the program that was written to locate the peaks in the data.