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13:15
The World Health Organization (WHO) considers air pollution to be the world's single largest environmental health threat, accounting for approximately 7 million deaths worldwide every year. That's why in this talk we want to speak about how the problem of air pollution can be understood and predicted using HPC pollution modeling and its application based on general concepts and our own research.
We are Dr. Johannes Bieser and Dr. Martin Ramacher, both working at the Helmholtz Zentrum Hereon in the field of numerical pollution modelling. While Dr. Bieser wrote his Dissertation on emission modelling and its application, Dr. Ramacher wrote his Dissertation on pollutant transport and exposure modelling.
In our talk on numerical air quality modelling systems, we want to introduce basic principles and share our personal knowledge in the field of numerical pollution modelling, covering the entire pathway from emissions, transport, transformation and human exposure. Each of these steps relies heavily on large amounts of data from many different sources - satellite data, activity and meta data, measurements and many more - and skills in computer science. By default, environmental scientists are often not trained in computer science and high performance computing which implies a challenge of its own (and allows Nerds like us to excel).
Our talk will be enriched with practical, technical and partially political examples to demonstrate the difficulties scientist face during their quest to improve air quality for everyone: from TB of wasted data due to historically grown data formats to counterproductive policy decisions to „improve“ air quality. We’ve seen it all and after participating in the CCC for many years now, we decided to draw attention to some state-of-the science approaches for solving one of the world’s single largest environmental health threats: „air pollution“.