Tech giants spot opportunity in forecasting Country's smog

chika ebuzor

December 29, 2015 5:26 AM

Forecasts can help governments plan when to close schools and airports, restrict vehicles or postpone sporting events, and also decide which polluting factories to shut down temporarily.

Chinese President Xi Jinping delivers a speech during the opening session of the World Climate Change Conference 2015 (COP21) at Le Bourget, near Paris, France, November 30, 2015. REUTERS/Stephane Mahe

Air pollution in China could be big business. Two of the world's largest technology firms, IBM and Microsoft, are vying to tap the nascent, fast-growing market for forecasting air quality in the world's top carbon emitters.

Bouts of acrid smog enveloping Beijing prompted authorities in the Chinese capital to declare two unprecedented "red alerts" this month - a warning to the city's 22 million inhabitants that heavy pollution is expected for more than three days.

Such alerts rely on advances in pollution forecasting, increasingly important for Communist Party leaders as they seek improvements in monitoring and managing the country's notorious smog in response to growing public awareness.

Official interest has also been boosted by China's preparations to host the Winter Olympics - Beijing's smog is worse in the colder months - in 2022.

"There is increasing attention to the air quality forecast service," said Yu Zheng, a researcher at Microsoft. "More and more people care about this information technology."

A rudimentary forecast was pioneered by Dustin Grzesik, a U.S. geochemist and former Beijing resident who created Banshirne.com, a free website and smartphone app, in 2013 to predict clean air days using publicly available weather data on wind patterns.

"If you can predict the weather, it only takes a few more variables to predict air quality," said Robert Rohde of Berkeley Earth, a U.S.-based non-profit that maps China's real-time air pollution. "Most of the time pollutant emissions don't vary very rapidly."

Now, advances in "cognitive computing" - machines programmed to improve modelling on their own - allow more sophisticated forecasting software to provide predictions for the air quality index up to 10 days in advance using data on weather, traffic and land use, as well as real-time pollution levels from government monitoring stations and even social media posts.

chika ebuzor