Enhance your knowledge with our pre-conference courses on Monday, October 4, 2021.
Aerosol Data from the Next Generation of Satellites for Air Quality & Climate Research
Monday, October 4, 2021 • 8:00 am - 5:00 pm
Instructors: Dr. Pawan Gupta, Senior Scientist, USRA/NASA Marshall Flight Center; Dr. Robert Levy, Research Physical Scientist, NASA Goddard Space Flight Center
The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard NASA’s Earth Observing Satellites (EOS) have been observing the earth-atmosphere system for nearly two decades. Atmospheric aerosols (particulate matter) play an important role in earth radiation budget and contribute to air pollution. Since its launch, the “dark-target” (DT) aerosol retrieval algorithm has been applied to MODIS to retrieve aerosol optical depth (AOD) and other aerosol properties on a global scale. The AOD data product has been extensively used for both climate and air quality applications. More recently, the DT algorithm is being applied to the next generation of sensors such as Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi-NPP, and the Advanced Himawari and Baseline Imagers (AHI and ABI) on Himawari-8 and GOES-R. The application of consistent algorithm on multiple Low Earth Orbiting (LEO) and GEO stationary (GEO) sensors is key for observing aerosols with high temporal and spatial resolution.
This course will provide lectures and hands-on exercises. Lectures will be about fundamentals of satellite remote sensing of atmospheric aerosols, the dark target aerosol retrieval method, and best research practices. Hands-on exercises will be geared towards accessing data, reading and mapping the aerosol fields, and validating against ground measurements. All activities will use free or open-source software tools.
Back Trajectory Analysis
Monday, October 4, 2021 • 8:00 am - 12:00 pm
Instructor: Kristi Gebhart, Research Physical Scientist, Cooperative Institute for Research in the Atmosphere
Back trajectories are often used for insight into source-receptor relationships and have a long history of use in visibility studies. Bring your laptop to get some hands-on practice automating tasks such as downloading gridded input meteorological data, running the Hysplit back trajectory model in batch mode, and plotting and analyzing the output. The course will include a booklet with practical instructions, tips and tricks learned the hard way, equations and code for some common back trajectory analyses, and where to find resources for additional support. It is helpful, but not necessary, if participants already have Python and R installed on their laptops and have some familiarity with these packages. All software can run on Windows, Linux, or Apple computers.
Low Cost Sensors
Monday, October 4, 2021 • 8:00 am - 12:00 pm
Instructor: Dr. Jay Turner, Vice Dean for Education and Professor of Energy, Environmental and Chemical Engineering, Washington University in St. Louis
Air pollution monitoring devices based on low-cost sensors (LCS) are now widely used to interrogate previously unmonitored environments and to increase monitoring density in areas where high spatiotemporal variability is anticipated. This course will highlight the opportunities and challenges when deploying such devices. The governing physical principles behind LCS will be used to clarify appropriate applications. Use cases will be presented to demonstrate strengths and limitations. Efforts to define performance targets and testing protocols will be summarized, and key considerations for the effective deployment of LCS will be discussed.
The Relationship of Visibility to Particle Composition and Sources
Monday, October 4, 2021 • 1:00 pm - 5:00 pm
Instructors: Dr. Philip K. Hopke, Bayard D. Clarkson Distinguished Professor Emeritus at Clarkson University and Adjunct Professor, Department of Public Health Sciences of the University of Rochester School of Medicine and Dentistry
This course will present the underlying basis for differences in the interaction of light with particles of differing composition and the relationships that have been developed for prediction of visible range based on particle composition. Visibility can also be related to sources. The conceptual framework of receptor models, a mass balance approach, will be described. The resulting mathematical approaches can be then implemented depending on what a priori information is available. Applications of several types of models to various particle composition problems will be described with an emphasis on the practical use of Positive Matrix Factorization for both elemental and organic species data.