10th International Aerosol Conference
September 2 - September 7, 2018
America's Center Convention Complex
St. Louis, Missouri, USA

Abstract View


A Software to Map the Time-lapse History of Global Air Pollutions (TH-GAPs)

MAOHUA PAN, Zechen Yu, Chang Yu Wu, Myoseon Jang, Paul Gader, University of Florida

     Abstract Number: 1625
     Working Group: Aerosol Education

Abstract
Air pollutions, such as particulate matter (PM), NOx, Ozone, SO2, in heavily polluted areas can pose significant health effects to human beings. Time-lapse history of these air pollutants’ concentration could help student better learn the global air quality patterns, while visualization of these data could also impress the public. Our lab has designed a software (TH-GAPs) to process data downloaded from Goddard Earth Sciences Data and Information Services Center (GES DISC) to generate a series of time-lapse videos for visualizing the dynamic behavior of global air pollutants. MatLab APP Designer is used to create the software. The observation or simulation data (e.g. ground level ozone concentration) are loaded into the software and then averaged according to the selected average time interval (e.g. 2 month) and/or the selected resolution (e.g. 1°x1°). Afterwards, these processed data could be saved and transferred to the second part of TH-GAPs to generate maps of the time-lapse concentration history of different air pollutants. Total ozone and ground level PM2.5 data from 2010-2016 were used to prove the feasibility of this software. Videos of the time-lapse ground level PM2.5 and total ozone concentration over South Pole, North Pole and around the world were successfully generated, and maps generated from this software are identical with maps from the National Aeronautics and Space Administration (NASA). Compared with commercially available software, the TH-GAPs is fast, convenient, open source and easy to share, and there are no strict requirements for the resolutions of the input data. This implies that Matlab App Designer can be used for software design to make air quality data processes faster and convenient, and to make air pollution results more illustrative and acceptable to the public. Our work demonstrates incorporating programming into environmental engineering can create better tools to engage people to care more about environmental problems.