Airly for Local Governments

Situation: Krakow had issues with air pollution, but was uncertain on the principal cause and therefore the best strategy to address the issue.

Action enabled by Airly: Analysis of data from the Airly network clearly showed that the main pollutant was particulate matter, and pollution was worst on colder days. This analysis implicated burning of wood and coal for domestic heating as the largest single contributor to poor air quality - allowing the government to move to ban solid fuels.

Situation: In order to improve air quality, many cities in the Silesia region have introduced a ban on low-quality coal (which emits more toxins like SO2 and particulate matter).

Action enabled by Airly: Using the Airly network, these cities are able to track the positive impact of their policy vs. baselines collected before the ban. This allows them to prove the efficacy of the ban and win public support and investment.

Situation: As part of their clean air strategy, Birmingham city council wanted to explore options to improve air quality in the city centre to make it more attractive to visitors and businesses.

Action enabled by Airly: Birmingham installed a 70 sensor Airly network to inform policy development. Specifically, the analysis of data from the sensors allows Birmingham to forecast the benefit from the introduction of an Ultra Low Emission Zone (ULEZ) and design the perimeter of the scheme to maximise air pollution benefits with minimal traffic disruption. Then track the benefit of the scheme to justify prolongation or extension to a larger area.

Situation: As part of their clean air strategies, Bedford and Lambeth wanted to explore options to improve air quality around local schools to protect children.

Action enabled by Airly: The Airly network at local schools identified NO2 and PM from vehicular traffic as the main cause of pollution. This analysis allowed the local authorities to design the introduction of “green school streets” (banning vehicle access at drop-off and pick-up) as well as forecast and track the benefits for the children. In addition, schools can make informed decisions on when the air is safest to allow children to play outside.

Situation: Krakow had issues with air pollution, but was uncertain on the principal cause and therefore the best strategy to address the issue.

Action enabled by Airly: Analysis of data from the Airly network clearly showed that the main pollutant was particulate matter, and pollution was worst on colder days. This analysis implicated burning of wood and coal for domestic heating as the largest single contributor to poor air quality - allowing the government to move to ban solid fuels.

Situation: In order to improve air quality, many cities in the Silesia region have introduced a ban on low-quality coal (which emits more toxins like SO2 and particulate matter).

Action enabled by Airly: Using the Airly network, these cities are able to track the positive impact of their policy vs. baselines collected before the ban. This allows them to prove the efficacy of the ban and win public support and investment.