Page 10 - Case study: Air quality management in Southern California, USA

2. The smart project(s)

2.1. Vision and content

The air quality approach discussed in this case study integrates air quality sensor data with
measured and modelled meteorology and presents the information in a way that facilitates rapid
understanding and response. Sophisticated analytical methods are used but re‑engineered and
presented in a way that non‑subject matter experts can use.

The Southern California districts’ target is very clear: to clean the air and protect the health of all
residents through practical and innovative strategies, adopting policies and regulations, considering
also ideas and comments from the public. A Governing Board comprised of several members
discusses the way to improve the air quality and establish effective clean air programs. It has
concluded that a digital platform that is capable of analyzing a wide‑ranged of real‑time data is an
essential component to improve air quality in the districts.

The key feature is the ability to use proprietary algorithms based on mathematical atmospheric
dispersion models such as WRF (Weather Research and Forecasting) , CALMET (Computer Aided
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Learning in Meteorology) and CALPUFF (California Puff Model) .
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These models are preferred by the US Environmental Protection Agency for assessing long range
transport of pollutants and their impacts on a case‑by‑case basis for certain near‑field applications
involving complex meteorological conditions.

Many cities and regions all around the world have implemented online sites, dashboards and
platforms that show and graph air quality information so citizens can check the air pollution and
make decisions according to that.

Moreover, it is also typical that these Smart City platforms allow to check other vertical applications
data such as water quality, weather data, waste management, car park availability, etc. but it is
relatively rare to see that the intelligence behind these platforms correlate different siloed data.

Envirosuite´s platform combine multiple data sources data such as air quality data, weather data,
emission rates, weather forecasts and altitude to provide a very accurate baseline about air
pollution. Significant innovation in design makes complex data sets simple for non‑subject matter
experts to understand and use in real‑time decision making and response to incidents.

And the solution has been implemented on a very large scale, covering several counties with the
technical challenges this implies.

Information and Communications Technologies are crucial for this project as real‑time data is
needed in order to feed Envirosuite´s proprietary algorithms. Real‑time air quality data from
these Districts’ air quality monitoring network is collected and aggregated as a dataset. It is then
augmented with real‑time actual weather data and sent to Envirosuite´s platform for processing
(Envirosuite platform is running on Amazon Web Services).

4 Air quality management in Southern California| California, USA