PPT-Plume Rise Purpose of Air Quality Modeling

Policy Analysis Regional Planning Supplementary Control Systems Air Quality Prediction System Emergency Preparedness Accidental Releases Long Range Transport Acid Rain State Implementation Plan Revisions New Source Review . . Introduction . to Environmental . Engineering and Science. Readings for This Class:. 5.5-5.6. O. hio . N. orthern . U. niversity. Introduction. Chemistry, Microbiology & Material Balance. Water & Air Pollution. Marti Blad PhD PE. EPA Definitions. Dispersion Models. : Estimate pollutants at ground level receptors. Photochemical Models. : Estimate regional air quality, predicts chemical reactions. Receptor Models. Ph.D. Director of Strategic Programming; Co-Director of . The Center for Research on Girls, Laurel School. Licia. Kovach. Science Department Chair, Laurel School. Shaping STEM Education for Girls:. New Research on How to . A New Visualization of . Multi-Model Ensemble Forecasts . Developed to Advance Climate Prediction Research and Communication. Jennifer M. Adams. Center for Ocean-Land-Atmosphere Studies. George Mason University. Environmental Models. Chapter 3: Air Quality Modeling. 3.7: The Basic Plume Model. Puffs vs. Plumes. Consider two distinct types of smoke stack releases shown to the right (Figure 3.15 from . Hadlock. of wild-land fires . to atmospheric composition. M.Prank. 1. , . J. Hakkarainen. 1. , T. Ermakova. 2. ,. . J.Soares. 1. , . R.Vankevich. 2. , M.Sofiev. 1. 1 . Finnish Meteorological Institute. 2. Russian State Hydrometeorological University . . A . Brief . Introduction. Image from Univ. of Waterloo Environmental Sciences. Marti Blad. 2. Transport of Air Pollution. Plumes tell story. Ambient . vs. DALR. Models predict air pollution concentrations . EPA Definitions. Dispersion Models. : Estimate pollutants at ground level receptors. Photochemical Models. : Estimate regional air quality, predicts chemical reactions. Receptor Models. : Estimate contribution of multiple sources to receptor location based on multiple measurements at receptor. Talat Odman. Fernando Garcia-Menendez . Aika. . Yano. Yongtao. . Hu. . CMAS Annual Conference. Chapel Hill, North Carolina. October 16, 2012. Contributors. Scott . Goodrick. , . Yongqiang. Liu, Gary . Seng. K. . Yeoh. , Todd A. Chapman. A. dvisors: David B. Goldstein, . Philip . L. Varghese, Laurence M. . Trafton. Support is provided by . the NASA CDAP and TACC.. 02/23/2012. Enceladus: . A Mysterious Moon of Saturn. ?. The improved spatial, temporal and spectral attributes of the ABI allow for monitors plumes associated with rockets and other hotspots. . Instead of needing to show 3 or 4-panels with separate spectral bands, these RGBs combine information on the plumes from several key spectral bands: 3.9 micrometer or the “fire band”, the upper-level water vapor band (8), and a visible or “near-visible” band. ABI band 2 is used during the day, while the 7.3 micrometer (water vapor) band at night. . William . McDoniel. D. . B. Goldstein, P. L. Varghese, L. M. . Trafton. University of Texas at Austin. Department of Aerospace Engineering. DSMC . Workshop . September . 28. th. , . 2011. Supported by the NASA Planetary . to atmospheric composition. M.Prank. 1. , . J. Hakkarainen. 1. , T. Ermakova. 2. ,. . J.Soares. 1. , . R.Vankevich. 2. , M.Sofiev. 1. 1 . Finnish Meteorological Institute. 2. Russian State Hydrometeorological University . March . 10, 2020. 2. Using Air Dispersion Modeling. Models estimate impacts of pollution emitted by industry. Compare the estimated impacts to air quality standards. Air quality standards limit emissions from industry.