From measuring to managing air quality – Understanding atmospheric conditions and pollutant dispersion with remote sensing

Smog in the city
Sustainability
5 p.m. EEST/ 2 p.m. UTC

Poor air quality is a serious environmental health issue around the world, resulting in hundreds of thousands of premature deaths every year. In the atmosphere, mixing layer and boundary layer height variations affect the concentration of air pollutants. Pollutants don’t just stay in cities, however. Wind can carry them long distances — making them even harder to track, let alone manage.

Cities are now looking to address air quality challenges by implementing ambient air quality monitoring systems. Two technologies that can help: Wind maps and remote sensing.

Join us in this informative webinar to learn how to use both. We'll talk about:

  • What mixing layers and wind maps are, and how they can be used in monitoring and modeling air quality
  • How remote sensing weather instruments can be used in mixing layer height measurement and wind map creation
  • The customer perspective on applying both strategies to address boundary layer meteorology, fire weather, and air quality concerns

Who should attend:
Environmental protection agencies, smart city decision-makers, and others interested in improving air pollution for their city’s residents.
If you can’t attend the live time, register anyway and we’ll send you a link to the recording.

 

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Speakers:

Dr. Kenneth H. Underwood

Senior Scientist, Certified Consulting Meteorologist/ T&B Systems Inc.

Dr. Underwood is a graduate of Penn State University where he received his Ph.D. in meteorology with an emphasis on boundary layer turbulence and remote sensing of the atmospheric boundary layer using ground-based instruments and systems.  During the past 35 years, he has developed several remote sensing systems and instruments that are currently in use worldwide.  He applied his unique combination of skills using his understanding of the atmosphere to the instrument designs based on advanced digital signal processing techniques for the development of cost-effective, operationally adaptive, and power-efficient autonomous field systems tailored for wind energy, air pollution monitoring, airport monitoring, and research applications.