Evaluation of land use regression models for NO2 in El Paso, Texas, USA (original) (raw)

The Science of the total environment, 2012

Abstract

Developing suitable exposure estimates for air pollution health studies is problematic due to spatial and temporal variation in concentrations and often limited monitoring data. Though land use regression models (LURs) are often used for this purpose, their applicability to later periods of time, larger geographic areas, and seasonal variation is largely untested. We evaluate a series of mixed model LURs to describe the spatial-temporal gradients of NO(2) across El Paso County, Texas based on measurements collected during cool and warm seasons in 2006-2007 (2006-7). We also evaluated performance of a general additive model (GAM) developed for central El Paso in 1999 to assess spatial gradients across the County in 2006-7. Five LURs were developed iteratively from the study data and their predictions were averaged to provide robust nitrogen dioxide (NO(2)) concentration gradients across the county. Despite differences in sampling time frame, model covariates and model estimation meth...

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