Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8855004 | Environment International | 2018 | 10 Pages |
Abstract
A Bayesian modeling approach was used to generate unique HAP-PM2.5 kitchen concentrations and personal exposure estimates for all countries, including those with little to no available quantitative HAP-PM2.5 exposure data. The global exposure model incorporating type of fuel-stove combinations can add specificity and reduce exposure misclassification to enable an improved global HAP risk assessment.
Keywords
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Environmental Chemistry
Authors
Matthew Shupler, William Godwin, Joseph Frostad, Paul Gustafson, Raphael E. Arku, Michael Brauer,