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Citizen air quality monitoring?

What’s the next step in citizen-empowerment about air quality and noise, now that governments release more of their environmental data on the Internet? Cheap, networked amateur/ citizen data collection?

We’re fascinated watching initiatives like AirQualityEgg and Pachube, and the noise meters available for the iPhone. Cheap environmental data collection devices for amateurs may not (yet) be very accurate, but the practical effect of many data points could be substantial. AirQualityEgg puts it this way:

“The Air Quality Egg is a sensor system designed to allow anyone to collect very high resolution readings of NO2 and CO concentrations outside of their home.  These two gases are the most indicative elements related to urban air pollution that are sense-able by inexpensive, DIY sensors….The sensors will not be calibrated and their precision and sensitivity is mediocre.  However, we believe that generating data, even poor data, will not only contribute in a significant manner given the scale and density we can achieve, but we are also giving a community of people who previously had no voice a way to participate.”

Pachube provides a free platform to publish and aggregate citizen data. They note that large amounts of low quality data can produce meaningful results: “The beauty about crowdsourcing is that the dataset draws strength from its heterogeneity.  The outliers are easily spotted and discarded while the data that is consistent across completely unrelated sources is reinforced. There is a network effect here as each additional source to some degree “validates” the rest.” See also  “Making Sense” video: http://vimeo.com/39775046“.

Accuracy seems bound to improve as these devices become more popular. If nothing else, rapid, real-time, crowd-sourced data could identify problems overlooked by government bodies, that warrant full scale professional measurement. Such data could also provide real time evidence of which air quality interventions work to improve local conditions. How can we manage what we don’t measure?

 

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