The goal of the airPb package is to easily and reproducibly assess exposure to airborne lead at specific locations in and around Cincinnati, Ohio. The package calculates predictions of air lead exposure from a land use random forest model developed by Dr. Cole Brokamp based on ambient air sampling in Cincinnati, OH between 2001 and
The model predictors include greenspace (NDVI) within 1000 meters, population density within 500 meters, length of bus routes within 900 meters, percent pasure within 800 meters, percent developed open land within 1100 meters, percent developed medium land within 400 meters, percent developed low land within 900 meters, and percent developed high land within 1500 meters.
Additionally, these air lead exposures can be adjusted to account for the temporal variation associated with changing air lead levels in the area over time. Scaling factors are constructed using measurements of airborne lead recorded by the EPA in the Cincinnati area. These scaling factors are the average air lead measured over a time period of interest (e.g., gestation, the month leading up to date of hospitilization, etc) divided by the average air lead recorded over the ambient air sampling period (2001 to 2005). Scaling factors are then applied to air lead estimates from the land use model.
Reference
Cole Brokamp, Roman Jandarov, MB Rao, Grace LeMasters, Patrick Ryan. Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches. Atmospheric Environment. 151. 1-11. 2017. http://dx.doi.org/10.1016/j.atmosenv.2016.11.066
Examples
See our vignette for example usage.