My spatial problem deals mainly with determining what scale best fits both birth registry point data in Texas (4.7 million births from 1996-2002) and available spatial resolution of MODIS aerosol optical thickness data. A smaller cell size will more accurately determine ambient particulate matter exposure levels, but may leave too many cells with 0 births at different spatial scales. Increases in the cell size will allow a better coverage of the state, but may limit the spatial statistical relationships of low birth weight rates and accuracy of ambient air pollution exposures. A model will need to be created to combine ground-based air monitor exposure levels and satellite data to accurately determine rural particulate matter exposures.

A temporal problem deals with creating a model that will determine ambient air pollution exposure levels in each cell during different known susceptibility windows during all 4.7 million pregnancies. An analysis will need to be done to determine the variability of particulate matter levels on multiple time scales and incorporate the best fit with pregnancy susceptibility windows.

A combination of the spatial analysis and temporal analysis will incorporate both time lags and spatial clustering. This aspect of the project should be relatively straightforward. The goal of this section will aim to determine whether 1) LBW are clustered in space and time, or 2) whether individual emitters (using EPA TRI data set) are spatially and temporally correlated with LBW.

Below are some examples of different cell size and temporal scales.

1. 2008-2009 LBW hot spot analysis based on Texas census tracts

2. A hot spot analysis using .1x.1 degree (roughly 10km x 10km) grids of 2008-2009 of LBW rates

3. A hot spot analysis using 1×1 degree (roughly 100km x 100km) grids of 1996-2009 LBW rates.