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Adding NASA Earth Science Results to EPHTN via the NM/EPHT System

Most Recent 48-hour PM 2.5 Dust Animation
Most Recent 48-Hour PM 2.5 Dust Animation
Most Recent 48-hour PM 10 Dust Animation
Most Recent 48-Hour PM 10 Dust Animation		     

This project bridges individual health and community health by forecasting atmospheric ozone, dust and other aerosols that trigger asthmatic responses or myocardial infarction; and, by enhancing the New Mexico Environmental Public Health Tracking System's ability to prepare for, and to provide early warning to, populations at risk. The three primary tasks are to:

  1. assimilate products from NASA satellite sensors into EPA's Community Multi-scale Air Quality (CMAQ) model and the Dust Regional Atmospheric Model (DREAM). For human health applications, these include (a) bi-monthly land cover characterizations derived from MODIS data that are available daily from both the TERRA and AQUA observatories; (b) MODIS aerosol optical depth measurements from TERRA and AQUA; and, (c) aerosol profile products from CALIPSO and GLORY;
  2. verify and validate model outputs and assess improvements to ozone, dust, and other aerosol forecasts; and
  3. (3) Enhance EPHTS and EPHTN decision support systems with model outputs and forecasts.

Bi-monthly inputs of land cover that includes a barren land category will help CMAQ and DREAM to simulate desert dust production and biogenically emitted chemicals such as isoprene and monoterpenes. In addition, satellite aerosol measurements will help set more realistic initial and boundary conditions for the models. This project engineers a new course for incorporating satellite measurements of aerosols and land cover change data into forecast models that support health decisions. To test the two tasks and transition outputs to EPHTS and EPHTN, the project is collaborating with New Mexico's Department of Health and CDC's Environmental Public Health Tracking Program.

Benefits are: (1) incorporating Earth science results for health care and decision making in respiratory disease diagnoses and surveillance; (2) improving cost effectiveness of inpatient health care by providing 36-48 hour forecasts that assist decisions for hospital staffing, diagnosis, and treatment; and, (3) expanding the knowledge gained in earlier air quality/health efforts to an atmospheric chemistry model in the PM2.5 and finer size ranges.
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