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USE OF GIS AND ANCILLARY VARIABLES TO PREDICT VOLATILE ORGANIC COMPOUND AND NITROGEN DIOXIDE LEVELS AT UNMONITORED LOCATIONS
Citation:
SMITH, L., S. MUKERJEE, M. GONZALES, C. STALLINGS, L. M. NEAS, G. A. NORRIS, AND H. A. OZKAYNAK. USE OF GIS AND ANCILLARY VARIABLES TO PREDICT VOLATILE ORGANIC COMPOUND AND NITROGEN DIOXIDE LEVELS AT UNMONITORED LOCATIONS. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 40(20):3773-3787, (2006).
Impact/Purpose:
Overall Goal: To develop spatial analyses using limited network-based air quality and GIS and other ancillary spatial information to estimate exposures for epidemiologic studies.
Goal of NERL Contribution: To develop regression-based spatial models using said measures and ancillary information to predict such exposures at unmonitored locations.
Specific Objectives:
1. To determine whether ultrafine (<0.1 um), accumulation (0.1-0.7), and/or coarse (1-10 um) mode particle counts correlate with CO, NO2 and VOCs emitted from mobile and/or other urban sources using source apportionment modeling techniques.
2. To determine spatial associations among measured levels of NO2, VOCs, and (possibly) ultrafine/accumulation/coarse mode particle counts from mobile and other urban sources in El Paso. Spatial variability in ultrafine/accumulation/coarse mode particle concentrations will be determined using available PM, NO2, VOC and available surrogates of motor vehicle emissions. These measured or predicted spatial associations will then be used by NHEERL to ultimately assess impact of these particle counts and gaseous species on children's exposures in schools.
3. To evaluate accuracy of NO2 and VOC measurements using the passive badges to be deployed by EPA versus collocated FRM devices established by the State of Texas. In addition, to evaluate precision of collocated NO2 and VOC passive badge measurements.
4. To use spatial analysis concepts to evaluate their possible application in an EPA Region 6 study entitled "Air Toxics Data and Analysis and Development of a Predictive Model of Estimation of Ambient Vocs in Selected Census Tracts in Houston-Galveston, TX."
Description:
This paper presents a GIS-based regression spatial method, known as land-use regression (LUR) modeling, to estimate ambient air pollution exposures used in the EPA El Paso Children's Health Study. Passive measurements of select volatile organic compounds (VOC) and nitrogen dioxide (NO2) were conducted at elementary schools in El Paso, Texas. Predictive equations were developed by regressing passive monitor measurements at the schools with land use variables derived from GIS databases. Rather than using an arbitrary linear LUR model, a multi-step approach was used to develop the predictive equations to provide pollutant predictions at other locations in the city where no pollutant monitoring was done to ultimately assess pollutant impact on children's exposures in schools. The VOC/NO2 predictions provided by this LUR modeling method were linked with the epidemiologic models to assess respiratory health effects from traffic and other urban emissions (not discussed). The LUR model approach used in this study is also being applied in the EPA Detroit Children's Health Study.