A Source-Oriented Approach to Coal Combustion PM2.5 Health Effects

• Activity Number: 665 - Spatial Methods for Weather, Climate, and Health
• Type: Contributed
• Date/Time: Thursday, August 3, 2017 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Kevin Cummiskey* and Chanmin Kim and Christine Choirat and Corwin Zigler
• Companies: Department of Biostatistics, Harvard T.H. Chan School of Public Health and Harvard University and Harvard University and Harvard University
• Keywords: air pollution ; PM2.5 ; Coal combustion ; HYSPLIT ; long range transport ; propensity score

Abstract

Several studies have found exposure to fine particulate matter from coal combustion emissions has a stronger association with negative health outcomes than other sources of air pollution. A central challenge to attributing air pollution exposure to pollution sources is long-range transport: air pollution moves, often at great distances, from emitting sources to exposed populations. Existing methods get around this challenge by inferring broad source categories from the chemical composition of the air to determine a population's exposure. This simplification limits the utility of these methods to address very relevant public health issues about the relationship between emissions from specific point sources and health. In this paper, we deploy a novel statistical analysis method to more directly isolate the association between fine particulate matter from coal-fired power plants and health. Specifically, we use Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) simulations to directly estimate the influence of individual power plants on populations residing at over 14,000 US ZIP codes. Propensity score matching is used to adjust for potential confounding.