Harnessing the Power of Data – Real-world Applications of AirScape

• By AirScape
• June 14, 2023

Harnessing the Power of Data – Real-world Applications of AirScape

In our modern era, data is often touted as the new oil, driving not only business decisions but increasingly, environmental improvements. At AirScape, we have leveraged the power of air quality data to spark meaningful changes in urban spaces across the globe, proving that data is indeed a formidable force in our fight against air pollution.

AirScape’s street-level, real-time air quality data has been instrumental in many parts of the world, beyond London, guiding informed decisions and fostering healthier, more sustainable communities.

A Groundbreaking Initiative in Camden

In a landmark collaboration with the Camden Clean Air Initiative and Camden Council, we installed 229 real-time air quality sensors in the borough. This world-first deployment provides residents with hyper-local air quality data every minute, empowering them to make informed decisions for their health and advocate for policy change. The dense network of sensors actively monitors nitrogen dioxide, particulate matter, and ozone, offering an unprecedented level of spatial resolution and frequency of updates.

This initiative underscores the transformative potential of real-time air quality sensors and serves as an exemplary model for communities worldwide. By making data accessible to everyone, on our user-friendly map platform at airscape.ai, we’re empowering the community to fight against air pollution effectively.

The Future of Sustainable Construction

In Denmark, we’re part of the Green Construction Site of the Future project, an initiative aiming to reduce the environmental impact of construction activities. Our real-time monitoring of air quality and noise on and around the construction site provides transparency and documentation of the project’s environmental impact. This initiative also involves converting construction machines to electricity and other alternative fuels, dust control technologies, logistics optimisation, and a digital twin for emission reduction opportunities.

The project, concluding in December 2023, promises to deliver significant insights on the most effective ways to minimise environmental impact in the construction industry.

Paving the Way for Cleaner Streets

In Westminster, we partnered with an estate owner facing the challenge of improving the neighborhood’s air quality. With a goal of pedestrianising a street through the estate, our sensors played a crucial role in gathering evidence of the positive effects of restricting vehicle access. Our real-time air quality data provided tangible evidence of significantly lower levels of NO2 in the pedestrianised street, influencing the local authorities’ decision to consider permanent pedestrianisation.

Data: Our Weapon Against Air Pollution

You can’t manage what you can’t measure. From assisting policymakers in documenting the effects of interventions to enabling researchers to correlate pollution with health impacts, our data-driven approach is making a significant impact. We’re helping businesses show their commitment to the community and aiding individuals to choose healthier routes and make informed decisions about where to live, work, and play. At AirScape, we firmly believe that when it comes to tackling air pollution, knowledge truly is power.

The Future is Clear

The power of air quality data in combating environmental issues is undeniable. As we continue to innovate, we are encouraged by the impact our data has had and the role it plays in driving change. We remain committed to our mission of making air pollution visible and actionable, empowering individuals, communities, and policymakers alike to contribute to a cleaner, healthier future.

For more detailed insights into how our data has been used to drive positive environmental change, check out the case studies on our website.

Change begins with awareness. Together, let’s make the invisible, visible, playing our part in making our air cleaner, one data point at a time.