How North India's pollution levels sound through musical notes
Organisation: India Today (India)
Publication Date: 11/29/2016
Size of team/newsroom:large
DescriptionDelhi is the most toxic city in the world and on November 5th, 2016 (post the week of Diwali, the festival of lights), the PM 2.5 level in Delhi's air climbed up to 999. Let me remind you, 65 is the normal breathing unit and at 165, China declares a nation-wide emergency. Of course, there were plenty of reports circulating on newspapers, TV and digital platforms about Delhi's choking air but the statistics became too adaptive to the readers and they accepted the air as normal. It wasn't normal. It still isn't. I worked on a different method of describing Delhi's deadly air, for that, I used the sound as storytelling method. In this experiment, I took the last ten days' data from three northern cities of India - Delhi, Varanasi and Patna's Air Quality Index (AQI). For example, on October 23, 2016 – one week before Diwali – Varanasi recorded a 24-hour average pm 2.5 level of 96 µg/m³, nearly half the level recorded last year. Similarly, average pollution levels in Agra and Delhi were 38 per cent and 30 per cent lower respectively, than those recorded on the corresponding day in 2015 (November 4, 2015). Lucknow was 11 per cent less polluted this year, while only Patna recorded 38 per cent higher levels, compared to 2015. Later, we tried representing air pollution data of three cities - Delhi, Varanasi and Patna - in sound through data sonification process.
What makes this project innovative? What was its impact?When one thinks of audio as a storytelling method, podcasts and radio comes in mind, but we can also display the data through sound. And it catches your attention. Similarly for this project, we thought why not create the sound for air pollution Delhi created after Diwali? We acquired the data from the Delhi government's Air Quality Index's website and for each high PM 2.5 value, a musical note was placed. High amplitude denotes the record high AQI in each city. And voila, you have a background sound for air pollution levels. The feedback from the readers were full of enthusiasm and people tweeted this story as "This is so cool". The possibilities are endless if one thinks of distributing data through sound. Imagine a real time sports data played through sound. Imagine acquiring twitter sentiments from an API and come up with a sound after Donald Trump was elected as 45th President of the United States ( in fact, I have done this story, you can access it here http://www.dailyo.in/variety/donald-trump-us-presidential-elections-2016-hillary-clinton-twitter-sound/story/1/13960.html). I still believe sound has a long way to go and journalists should definitely use this medium.
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