EarthSense is dedicated to delivering innovative air quality solutions through cutting-edge monitoring, data analysis, and modelling, empowering businesses and communities to make informed decisions for a cleaner, healthier environment.
An exciting new development, users can now access detailed visualisations of pollution trends, identify key emission sources within specific areas, and integrate this data seamlessly into applications such as smart city platforms, traffic management systems, and public health initiatives. The model's data accuracy aligns with the standards outlined in The Air Quality Directive (2008/50/EC), ensuring reliable and actionable insights for businesses, communities, and policymakers.
What is Air Quality Modelling?
Definition:
Air quality modelling uses mathematical methods to simulate and predict the dispersion and concentration of air pollutants in the atmosphere 👨🔬. Powered by EarthSense’s MappAir®, MyAir® offers hourly high-resolution air quality data that delivers clear, actionable insights. By combining data sources such as weather conditions, traffic data, atmospheric physics, and pollution sources 🌦️, MappAir® predicts pollution concentrations across cities, regions, and even globally.
Why It Matters: Air quality modelling is crucial for understanding pollution patterns, predicting future air quality, and informing effective mitigation strategies such as potential health impacts. It enables governments, businesses, and communities to make data-driven decisions that protect public health and the environment.
Whether you're a city planner, transport authority, or a business aiming to meet sustainability goals, MappAir® provides high-quality data that can help fill data gaps. offering reliable information where physical monitoring is unavailable, estimate hypothetical scenarios, and identify pollution sources. ☁️🔍
How MappAir Fits In: MappAir® combines advanced dispersion algorithms and detailed emissions inventories to create high-resolution air quality models. By integrating satellite data, traffic emissions, and weather patterns, it provides dynamic pollution mapping, enabling informed decision-making for urban planning, public health, and environmental management.
New Features in the Latest Version of MappAir
Improved Accuracy & Coverage: The latest release of MappAir® enhances data accuracy and expands coverage across global, UK, and city-scale models. By refining data assimilation techniques, incorporating higher-resolution inputs, and improving machine learning algorithms, it delivers more precise air quality insights
Advanced Visualisation Tools: Now users can interrogate the model to display information relating to local pollution sources. Virtual Zephyrs have also been enhanced to include more granular data regarding weather conditions and pollution sources, taking visualisations to the next level. Learn more about virtual Zephyrs below.
The Power of Virtual Zephyrs
What Are Virtual Zephyrs? Virtual Zephyrs are modelled sensor points driven by MappAir® that generate air quality data for locations without the need for physical sensors. By leveraging advanced algorithms, real-time data assimilation, and historical pollution trends, these virtual sensors provide highly accurate estimations of air pollution levels.
Benefits: Virtual Zephyrs offer significant flexibility by filling data gaps, estimating pollution levels in areas without direct measurements, and predicting future air quality scenarios. By leveraging real-time data assimilation and sophisticated modelling, they provide continuous, high-resolution insights, ensuring comprehensive coverage even in remote or underserved locations.
Real-Life Application: City planners can use Virtual Zephyrs to assess air pollution levels in areas without physical monitoring, enabling data-driven interventions. For example, when designing a low-emission zone, planners can analyse pollution estimates from Virtual Zephyrs to identify high-exposure areas near schools or residential zones. This allows them to implement targeted traffic restrictions, optimise green infrastructure, or adjust urban layouts to reduce pollution impact, ensuring cleaner air for residents even in previously unmonitored locations.
The Impact of Source Apportionment on Air Quality Plans
What is Source Apportionment? Source apportionment is a technique used to identify and quantify the sources of air pollution and their contributions to overall air quality levels. By analysing emissions data, weather patterns, and chemical compositions, it helps determine whether pollution originates from traffic, industry, agriculture, or other sources. This insight enables policymakers and businesses to implement targeted strategies for reducing emissions and improving air quality.
How MappAir Uses This Data: MappAir® utilises source apportionment data to help users pinpoint pollution sources and design targeted air quality interventions. By identifying whether emissions come from traffic, industry, agriculture, or other contributors, MappAir enables policymakers, businesses, and urban planners to develop more effective mitigation strategies. This data supports the creation of low-emission zones, optimised traffic management plans, and cleaner industrial practices, ultimately leading to improved public health and environmental sustainability.
Conclusion
Call to Action: Discover how MappAir® can transform your approach to air quality management with accurate data, advanced modelling, and actionable insights. Sign up for a free trial of MyAir today to explore source apportionment and Virtual Zephyrs, helping you tackle air pollution challenges with precision. Get started now and make informed decisions for a cleaner, healthier environment!
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