A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models
Citation:
Dionisio, K., H. Chang, AND L. Baxter. A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models. EPA CLARC Annual Meeting 2016, Ann Arbor, MI, June 06 - 07, 2016.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Description:
A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models
