Using technology to predict dirty air can reduce its impact on vulnerable populations

Using technology to predict dirty air can reduce its impact on vulnerable populations

Using technology to predict dirty air can reduce its impact on vulnerable populations

The Paris-based Organisation for Economic Co-operation and Development (OECD) released a report earlier this summer that suggests outdoor air pollution caused more than 3 million premature deaths in 2010, with elderly people and children most vulnerable. I've got to believe the untold numbers of homeless youth and adults who live on the streets in urban centers around the world are also incredibly susceptible to ill effects of vehicle exhaust and particulate matter in the air – and the serious heart and lung conditions they can bring on. With the OECD projecting a possible doubling, or even tripling, of premature deaths from dirty air by 2060, public officials should pay close attention to technology solutions like the one described below from Council Associate Partner Siemens. – Philip Bane

 As the World Health Organization has pointed out, there are seven million deaths every year from air pollution, yet there are also local measures cities can implement on short notice to mitigate the effects of dirty air.

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Enter Dr. Ralph Grothmann from Siemens Corporate Technology (CT). He has developed air pollution forecasting models based on neural networks that can predict the degree of pollution in large urban areas several days in advance.

"Neural networks are computer models that operate like the human brain," Grothmann explains in an article in Pictures of the Future, a Siemens magazine on research and innovation. "Through training, they learn to recognize relationships and to make predictions."

Using London as a testbed As he developed his forecasting system, Grothmann used the weather and emissions data the city of London collects from some 150 sensor stations located throughout the metro area.

"This data allowed us to train our system," Grothmann explains. "Specifically, we gathered emission measurements for gases such as carbon monoxide, carbon dioxide and nitrogen oxides.

 



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