Air pollution in China is a serious issue: according to a recent study, it causes 4,400 deaths every day.
While denying it in public until recently, the authorities have been aware of the problem for a long time: when Beijing was chosen to host the 2008 Olympic Games, they took major steps to reduce pollutions levels in the city, halting constructions works, shutting down factories and power plants, imposing alternate-day driving rules.
Those measures sure had a positive effect on the situation, leading the International Olympic Committee chief to praise the efforts, saying China had done "everything humanly possible" to reduce PM2.5 levels (which measure particulate emissions of carbon, nitrogen, sulfur, and heavy metals).
But such high-impact provisions are not easy to implement and come with a huge economic cost.
Despite claims to the contrary, they ended up being more one-shot measures than a real solution, and the 'blue skies' didn't last: just a few years later, things seemed to be just as bad as before, forcing the local government, in December 2015, to issue its first ever 'red alert'.
While the problem is still far from be solved, then, a glimmer of hope for residents might come from a ten-year collaboration between the Beijing's Environmental Protection Bureau (EPB) and
The project, which started in 2014, is focused on using IoT and cognitive computing to improve air quality management and forecasting.
"Using the machine learning technology developed for Watson, we take huge amounts of data from weather stations, satellites social media, in Beijing, and we can not only identify exact pollutants and their sources, but also create amazing correlations in the data," IBM's general manager of the Watson project, Harriet Green tells me.
Those correlations, in turn, are used to build forecasting models and create possible future scenarios. "We combine thousands of parameters and tune them for different seasons and different locations," IBM's researcher Meng Zhang says, "and therefore we have been able to dramatically increase the accuracy of pollution predictions."
The forecasting window, with this new technology, has been extended from 2 to 10 days and the accuracy of the estimations jumped from 60% to 80%; this improvement was obtained, partly, combining traditional ground sensors information with data gathered from social media.
"Ground sensors actually are not enough to capture the whole picture of the pollution event, where does it come from, and where will it impact in the next few days. We use also data coming from the Chinese version of Twitter and Instagram to do some cross checking, and get a better understanding of the situation," Zhang explains. A post on Sina Weibo or Tencent, a picture, a camera feed: everything is processed and analyzed.
Besides accuracy, the advantage of this cognitive, machine learning approach is that gives authorities some leverage to plan in advance which measures to take to reduce pollution and allows more targeted, tailored interventions than just shutting down more than 100 factories for weeks, like it happened in 2008.
Thanks to the Watson-based analysis and to other actions, the EPB claims Beijing was able to achieve a 20% reduction in ultra-fine Particulate Matter in the first three quarters of 2015, a significant step which makes the goal of reducing PM 2.5 by 25% by 2017 look feasible.
But while it's true the China has made massive investments in recent years to tackle pollution, and the air quality has been indeed showing meaningful signs of improvement, some caution is advised before celebrating.
"On the large-scale I strongly expect to see continued gains into the future. However, on the scale of individual cities and individual years, one should be careful about over interpreting limited data," Robert Rohde, lead scientist of the California-based independent climate science think-tank Berkeley Earth tells me by email.
The reason of this carefulness is that air quality in cities like Beijing is heavily influenced by the weather.
"Wind patterns determines whether air pollutants are blown out of the city or accumulate near their sources. Rain and snow influence how quickly pollution is removed from the air, temperatures influence how much coal is burnt for heating, and how high pollutants rise in the atmosphere," says Rohde, who is also the co-author of the study "Air Pollution in China: Mapping of Concentrations and Sources".
Given this large impact on pollutant concentrations, it generally requires several years of data to establish if a local trend is robust, the scientist says.
