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A Satellite-based Decision Support Tool for Surface PM2.5 Estimates in California
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  • Minghui Diao,
  • Frank Freedman,
  • Mohammad Al-Hamdan,
  • Jason Vargo
Minghui Diao
San Jose State University

Corresponding Author:minghui.diao@sjsu.edu

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Frank Freedman
San Jose State University
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Mohammad Al-Hamdan
Universities Space Research Association at NASA/MSFC
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Jason Vargo
California Department of Public Health
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Fine particulate matter smaller than 2.5 micrometers (PM2.5) at the surface presents large health risks to the public. Providing long-term, spatially continuous data set of PM2.5 surface concentrations can support decision making by health departments, air agencies, as well as other stakeholders interested in public health. In this work, a website-based decision support tool will be shown. The tool includes two main parts. The first part is a multi-year, daily, 3-km database for PM2.5 concentrations in California from 2006 to present in both map and tabulate formats. The second part is a daily, 3-km, near real-time update of PM2.5 surface concentrations in California in the last seven days. The near real-time data are generated within 24 hours after the NASA A-train satellite swath. For both products, PM2.5 surface estimates are generated based on a fusion of EPA ground-based monitored data and satellite-derived PM2.5 data from the NASA Aqua/MODIS satellite sensor. This decision support tool can be used to provide quick and easy visualization of certain episodic events (such as California wildfires) on a daily basis. It can also be used to conduct multi-year statistical analysis, such as identifying the higher PM2.5 concentration days above 95th percentile as the days being impacted by wildfires. These datasets and the decision support tool is publicly available and can be accessed via the SJSU HAQAST website: http://www.met.sjsu.edu/weather/HAQAST/home.html