When was the last time you checked a weather forecast? It’s not hard to do: it’s on the home screen of our phones and talked about in almost every news bulletin. Yet behind the intuitive content lies a global system of immense complexity: each forecast is the product of hundreds of billions of daily observations, ingested by the world’s fastest supercomputers and interpreted by a global network of scientists that turn vast quantities of data into information that we can consume without needing to think.
Like weather, outdoor air pollution is ever present and ever changing. Nine in ten of us are breathing air that is so dirty it damages our health, which the World Health Organization links to over 4 million premature deaths globally each year.
Yet, unlike weather, many people and policymakers lack a comprehensive understanding of local air quality. OpenAQ, the global aggregation platform for air quality data, found that only half of the world’s national governments produce ambient air quality data in any capacity, and fewer than 40% share real-time air quality data publicly.
The problem is particularly acute in low- and middle-income regions. For example, only 6% of children in Africa live near a reliable ground-level real-time air quality monitor, compared to 72% of children in Europe and North America.
As well as a lack of ground monitoring, satellite remote sensing and modelling tools are continuously improving, but often provide data that is unsuitable for local contexts or inaccessible to the relevant decision makers.
There are opportunities for change. A growing toolbox of methods is making it easier to fill data gaps, driven by an accelerating pace of innovation. Monitors are becoming cheaper, more accessible and easier to deploy, satellites are generating data products that are increasingly high resolution and usable in local contexts, and there is a large and growing bank of models and emission inventories that can be applied at various scales.
There is therefore an opportunity to transform our understanding of air quality so that a lack of data is no longer an excuse for a lack of action. Ubiquitous, locally relevant and easily accessible data about the sources, concentrations and associated impacts of air pollution is possible, everywhere. This would be transformative in our fight for better air quality: providing a foundation upon which policies and actions to mitigate air pollution can be designed, implemented, assessed and enforced more easily and effectively.
The Clean Air Fund is committed to achieving this. Since launching in 2019, we have supported our partners to roll out large scale pilots of new technologies, build new data aggregation platforms, provide policymakers with new methods to detect pollution hotspots and support cities with targeted technical assistance. Click here to read a case study on our technical assistance with C40.
Our air quality data strategy sets out how and where we will work to build on this foundation and to catalyse change towards our vision:
By 2030, air quality data is globally ubiquitous: citizens understand the quality of the air that they breathe and every policymaker has good enough data on which they make informed decisions.
To deliver this vision, our strategy sets out four priority workstreams and associated goals that we will be working towards:
- Piloting and innovation
Goal: Cost and capacity are no longer barriers to widespread monitoring
- Data for engagement
Goal: Citizens understand the quality of the air that they breathe
- Data into policy
Goal: Policymakers have good enough data on which they can make informed decisions
- Sharing and scaling best practice
Goal: Data, knowledge and experience is widely shared across a connected field
Each workstream identifies a set of enabling actions which will drive our grant making approach over the next three years to build on our successes to date.
The strategy is built on an in-depth review of the current state of play across all elements of the data ecosystem including:
- the generation of data (from wearable sensors to satellites),
- the modelling of data (from Gaussian plumes to chemical weather forecasts),
- the interpretation of data (from APIs to quality control)
- the management of data (the human and legal dimensions, such as operational capacity, political engagement and availability of funding), and
- the actioning of data (the transformation of data to information that is made accessible to the intended user)
Our vision is ambitious, but we know we cannot achieve it alone. We invite funders to work collaboratively with us in achieving our goals, which we know will require a significant scaling of funding towards the issue.
We also invite the ideas and innovative approaches to contribute towards the objectives of this strategy from those working in the air quality data field. Whilst the Clean Air Fund does not accept unsolicited proposals, we may invite proposals from partners where we see a demonstrable alignment in strategic objectives, a clear understanding of the problem being addressed, applicability to our geographies and a planned pathway to scale.
By building coalitions across the field, we hope to support the growth of the global air quality data ecosystem to a level of sophistication comparable to today’s global weather system. The ubiquitous, real-time and free access to accurate weather data is only made possible by decades of deep government and institutional investment in monitoring infrastructure, modelling capabilities, education, visual communications, and international cooperation. As a result, weather information is now deeply rooted in daily life and underpins countless decisions and actions. We believe a similar level of capability is possible – and within reach – for air quality data.
If you can help us deliver our strategy, please get in touch at firstname.lastname@example.org