Predicting polycyclic aromatic hydrocarbons using a mass fraction approach in a geostatistical framework across North Carolina.

ABSTRACT: Currently in the United States there are no regulatory standards for ambient concentrations of polycyclic aromatic hydrocarbons (PAHs), a class of organic compounds with known carcinogenic species. As such, monitoring data are not routinely collected resulting in limited exposure mapping and epidemiologic studies. This work develops the log-mass fraction (LMF) Bayesian maximum entropy (BME) geostatistical prediction method used to predict the concentration of nine particle-bound PAHs across the US state of North Carolina. The LMF method develops a relationship between a relatively small number of collocated PAH and fine Particulate Matter (PM2.5) samples collected in 2005 and applies that relationship to a larger number of locations where PM2.5 is routinely monitored to more broadly estima

SUBMITTER: Reyes JM 

PROVIDER: S-EPMC6013350 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature