Aim 3: PM Analysis for California Imperial Valley

Determine PM patterns and source area contributors across the California Imperial Valley using fine-scale dispersion models, routine and IVAN low-cost air quality monitors and MAIAC Aerosol Optical Depth.

The California Imperial Valley, located in southeastern California, is one of the most polluted areas of the country with respect to air particulate – consistently exceeding national and state PM2.5 and PM10 ambient air standards. The county also has among the highest rates of childhood asthma hospitalizations and emergency department visits in the state[1]. Recently, the Imperial Valley Air Network (IVAN) – a dense network of modified Dylos DC1700 Low-Cost PM Sensors across the valley – has been completed to supplement the existing regulatory network in the area. IVAN was a collaborative effort under an NIH-funded grant headed by California Department of Public Health and local Imperial Valley community organization Comite Civico del Valle[2],[3].

Using MAIAC satellite AOD fields [4],[5], fine-scale dispersion modeling, ground monitor PM data from the IVAN and regulatory networks and other observations, we aim to better understand and characterize Imperial Valley particulate air pollution at fine spatial scale. Specific topics are:

  • Determination of source-area contributions to PM patterns measured by the IVAN network measurements across the Imperial Valley during 2016 and 2017. Dispersion models are being run for normal and high-wind situations to determine source area contributors to PM in both cases. MAIAC AOD patterns for high-wind springtime PM events are being analyzed to assess the products ability to detect and identify possible source areas for windblown dust in these situations, and to corroborrate the dispersion model analysis. (HAQAST leads: Dr. Akula Venkatram and Dr. Frank Freedman)
  • Fine-scale AOD to PM2.5 statistical modeling utilizing MAIAC and IVAN measurements. We will develop a regional machine learning model to estimate PM2.5 mass concentration in the California Imperial Valley using MAIAC AOD, gridded meteorology, and land use information in 2016-2017. In addition to IVAN measurements, PM2.5 measurements from regulatory EPA monitors will also be integrated into the model. The goal is to characterize the spatial pattern of PM2.5 in and around the Imperial Valley, and try to assess the impact of regional transport on local air quality. (HAQAST lead: Dr. Yang Liu)

[1] http://www.cehtp.org/page/main
[2] https://www.ncbi.nlm.nih.gov/pubmed/28886604
[3] https://www.ncbi.nlm.nih.gov/pubmed/28829718
[4] https://modis-land.gsfc.nasa.gov/MAIAC.html
[5] https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/maiac/

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