Citation:

Braggio, J., E. Hall, S. Weber, AND A. Huff. Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland. ATMOSPHERE. MDPI, Basel, Switzerland, 11(2):209, (2020). https://doi.org/10.3390/atmos11020209

Impact/Purpose:

This is an EPA journal article which used the Hierarchical Bayesian Model (Temporal-Spatial Ambient Concentrator Estimator [T-SpACE]) to assess fine particulate matter impact on respiratory and cardiovascular illness in Baltimore Maryland. This journal article is a follow-up to the journal article that assessed the same issues in New York City, "Assessing the Impact of Fine Particulate Matter (PM2.5) Sources on Respiratory-Cardiovascular Chronic Diseases in the New York City Metropolitan Area using Hierarchical Bayesian Model Estimates".

Description:

The fine particulate matter baseline (PMB), which includes PM2.5 monitor readings fused with Community Multiscale Air Quality (CMAQ) model predictions, using the Hierarchical Bayesian Model (HBM), is less accurate in rural areas without monitors. To address this issue, an upgraded HBM was used to form four experimental aerosol optical depth (AOD)-PM2.5 concentration surfaces. A case-crossover design and conditional logistic regression evaluated the contribution of the AOD-PM2.5 surfaces and PMB to four respiratory-cardiovascular hospital events in all 99 12 km2 CMAQ grids, and in grids with and without ambient air monitors. For all four health outcomes, only two AOD-PM2.5 surfaces, one not kriged (PMC) and the other kriged (PMCK), had significantly higher Odds Ratios (ORs) on lag days 0, 1, and 01 than PMB in all grids, and in grids without monitors. In grids with monitors, emergency department (ED) asthma PMCK on lag days 0, 1 and 01 and inpatient (IP) heart failure (HF) PMCK ORs on lag days 01 were significantly higher than PMB ORs. Warm season ORs were significantly higher than cold season ORs. Independent confirmation of these results should include AOD-PM2.5 concentration surfaces with greater temporal-spatial resolution, now easily available from geostationary satellites, such as GOES-16 and GOES-17.

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