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MappAir®: Real Time Pollution Modelling Suite

What is MappAir®?


Our innovative technology, MappAir® ­, ­is an air quality model that uses various cloud-based data inputs to produce a dispersion model for ambient air pollution. The model provides insight into near-real time (NRT), predictive and historical ambient air quality. The combination of data sources and advanced modelling techniques delivers air quality modelling in three resolutions, global, national and city, which can be integrated with third-party systems via an API.


The option to use our MappAir ® model alongside virtual Zephyrs through our web application MyAir ® is also available, making the complete service available in one platform through a single purchase. The combination of models provides usable data and detailed insight into sources where harmful gases and particulates are arising, and how they are dispersing around areas of interest and affecting human health.


MappAir® allows the likes of local authorities, transport planners, integrators, and environmental professionals to visualise and understand how air pollution flows around urban areas as well as providing an indication of the sources of air pollution contributing to our ambient


MappAir®: Global Air Quality Model

global air quality model

The MappAir® Global API models concentrations of nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2) and particulate matter (PM10) using the Copernicus satellite service. Global resolution model provides hourly, and 72-hour forecast data for various air pollutants for identifying pollution events as they occur or in advance of them taking place, allowing effective mitigations to be planned to protect the most vulnerable.


With the Global model, governments and businesses receive insight into worldwide pollution events and how ambient air pollution across whole countries is impacting regional pollution exposure. Using this information, users can learn how economic, cultural, and environmental factors are affecting air quality for driving future legislation.


Global modelling data can be used by governments to alert communities who are likely to be affected by unsafe conditions about forecasted pollution episodes. This can be used to provide guidance about how to keep exposure safe, to encourage members of the public to avoid pollution-heavy areas, and to choose more sustainable methods of travel.


MappAir®: National Air Quality Model

national air quality model

The MappAir® National model uses third party data sources, including real-time traffic data from Highways England and national weather models from the Met Office, to provide 100 x 100msq resolution modelling for fine particulate matter (PM2.5) and nitrogen dioxide (NO2­)­­­ concentrations across the whole of the UK. These data are updated hourly and also include a 3 day forecast to enable future pollution events to be flagged and potential mitigations put in place before they occur.


The National model is presented via MyAir® with a number of tools to enable analytics to be carried out on the data, or delivered via our very own API data service to provide detail about how cities and towns are living and breathing. Also available via our National model is our own virtual Zephyrs capability, our newly developed technology that delivers near real time measurements for areas where our own Zephyr® monitors or any other 3rd party monitoring is not available.


Used alongside source apportionment data, local authorities and environmental planners can highlight areas in need of informed action and identify pollution sources contributing to elevated levels. Data can be used for trialling and testing various mitigation strategies for reducing the implications of exposure to high pollution levels, sources, and hotspots.


National modelling data can also be integrated with existing systems, like traffic management systems, via API. With integrated traffic and pollution data, local authorities and transport professionals can set alerts at hotspot locations so they are notified when high levels are met. With this information, users can make timely responses to pollution episodes and minimise the impact of high levels on those nearby.


In addition, an analysis of the EarthSense Nitrogen Dioxide (NO2) and Particulate Matter 2.5 (PM2.5) air quality dispersion model has shown that the data accuracy is within the limits outlined within The Air Quality Directive (2008/50/EC) guidelines. This is huge leap forwards for ambient air quality modelling and means user can now access industry leading air pollution data for a range of applications via easy access web apps and APIs.


MappAir®: City & Reactive Air Quality Model

city air quality model

The MappAir® City model provides high resolution pollution modelling up to 2 x 2msq for NO2 and PM2.5. Using a range of data sources, land use regression statistics and Computational Fluid Dynamics (CFD), City modelling provides granular information for ambient air quality and illustrates how pollution species disperse and flow around buildings and urban canyons. The city model is available with 72-hour forecasts for identifying concentrations before they happen.


The reactive, City model can be used by transport businesses for dynamic traffic management and reducing the impact of congestion on air quality. Modelled data can be integrated with Urban Traffic controls and switches for real time decision making when traffic build up occurs and hotspot locations arise. Transport professionals can use City modelling data to make informed decisions, such as changing traffic light sequencing during peak hours to reduce vehicle accelerations and enable traffic to flow better. They can also utilise Variable Messaging Signs (VMS) to display air quality concentrations and future levels to motorists, helping to advise them of high pollution levels in advance or as they occur.


The MappAir® City model can also be used by central and local governments for identifying cleaner routes to travel for the public to help reduce their exposure to ambient air pollutants. With NRT and historic data, the model provides localised insight into current and future levels throughout specified routes and users can use the data to identify cleaner routes for the likes of school children and cyclists to safely travel through towns and cities. Further action can be taken at problem areas, such as timed road closures or implementing a Low Traffic Network (LTN) for additional improvements in air quality.


City data can also be utilised by transport companies and authorities for simulating outputs to understand how air pollution would change following the introduction of initiatives such as Clean Air Zones or an electric vehicle fleet. Such data guides future decisions about decarbonisation strategies for working towards net zero by 2050. City modelling can also be used to compare levels post intervention with baseline levels for evidencing how well such strategies work to improve air pollution.


Furthermore, an analysis of the EarthSense MappAir® City modelling capability has shown that the data accuracy is within the limits outlined within The Air Quality Directive (2008/50/EC) guidelines. This means users and integrators of these data can be confident they are utilising outputs that are compliant with current legislative requirements.


Key Model Features


Use Cases


Transport/Traffic


As part of the Network Emissions/Vehicle Flow Management Adjustment (NEVFMA) project, we worked with Aimsun, Oxfordshire County Council and Yunex Traffic (formerly Siemens Mobility) to reduce congestion and subsequently emissions across Oxfordshire with integrated traffic and pollution dispersion data. Aimsun integrated MappAir® City modelling with their traffic model, Aimsun Live to simulate activity within road networks and response plans for reducing traffic build up. By implementing the most effective response plan, it resulted in a 5% improvement in air quality. You can learn more by reading our blog.


Local Authorities


Leicester County Council made use of a Zephyr® network, City modelling with a wood burning smoke estimate and CFD to identify fine particulate matter (PM2.5) concentrations coming from domestic burning within the city. Using modelling and forecast data, the council were able to issue informed guidance to the public about avoiding wood burning on days with high PM2.5 levels, reducing the impact of pollution exposure. Download the Leicester City Council case study for more information.


Smart City & Internet of Things (IoT)


MappAir® modelling data can be integrated into existing IoT systems, making air quality data available as part of online dashboards, applications and more for working towards cleaner, connected and smarter cities. Modelling data can be used to produce a digital twin of cities and towns complete with air pollution data with seamless integration.


Public Health & Postcode Data


Our Annual Average dataset was utilised by Global Action Plan to investigate the number of children across the UK attending schools in areas with air quality levels above World Health Organisation (WHO) guidelines. As a result of the research, they found that 27% of UK schools are located in areas with unsafe air pollution concentrations. Learn more by reading our GAP blog.


Do you want to learn more about using MappAir® to model and mitigate air pollution?


You can request a FREE demo of MappAir® by visiting our website and filling out the form here.

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