Introducing the Airwareness Support App
Table of Contents
Introducing the Airwareness Support App: A New Era in Indoor Air Quality Simulation
At Air Support Project, we’re dedicated to empowering individuals, businesses, and communities with the knowledge and tools they need to create healthier, safer indoor environments. Today, we’re thrilled to announce the beta release of our new web-based application—the Airwareness Support App—now available for free in-browser here.
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What Key Indoor Air Quality Problems Does This App Help Address?
The Airwareness Support App tackles several critical challenges related to indoor air quality, including:
- Understanding how airborne pathogens spread in enclosed spaces.
- Identifying the risk of airborne infection based on factors like room size, ventilation, and occupancy.
- Testing the effectiveness of interventions such as improved ventilation and changes in room configuration.
This app empowers users to make informed decisions to reduce the risk of airborne transmission and improve overall air quality in indoor environments.
How Accurate Are the Simulations, and What Data Do They Rely On?
Accuracy depends on the quality of user-provided inputs, such as room dimensions, ventilation details, and pathogen characteristics. While the app provides detailed insights, it is important to treat the results as approximations that inform decision-making rather than absolute predictions.
The model may not fully address certain edge cases, such as situations where close-range, near-field transmission is more critical. Instead, it excels at providing an overall, long-term average risk assessment for a given space.
Additionally, both the number of infectious doses produced by an infected person and the susceptibility of those exposed can vary significantly between individuals. This variability may help explain why some people remain uninfected despite prolonged or frequent exposure, while others fall ill after only brief contact even in relatively favorable conditions.
What is the Wells-Riley Model?
The Wells-Riley model is a mathematical framework used to estimate the risk of airborne disease transmission in indoor environments. Developed primarily in the mid-20th century, it built upon early work by William F. Wells and was later refined and popularized by Richard L. Riley. Wells, a pioneer in the study of airborne infection, introduced the concept of “quanta”—an infectious dose of airborne particles sufficient to infect approximately 63% of susceptible individuals who inhale it under well-mixed conditions. Riley, working in the 1950s and 1960s, applied and advanced Wells’s ideas to practical scenarios, including tuberculosis transmission in indoor spaces.
The model’s core equation relates four main factors: the concentration of infectious quanta in the air, the ventilation rate of the room (which dilutes the pathogen), the duration of exposure, and the breathing rate of the occupants. By integrating these elements, the Wells-Riley model provides a probability estimate of infection risk. Although simplified and built on assumptions—such as perfectly mixed air and uniform susceptibility—the model remains a widely referenced tool for understanding the influence of ventilation, occupancy, and exposure duration on the spread of airborne diseases. Over time, it has helped inform public health guidelines and shaped strategies for preventing airborne transmission, particularly in clinical, educational, and workplace settings.
This section presents a three-dimensional simulation of airborne infection risk based on the Wells-Riley model. Within this dynamic environment, each red particle represents one infectious quanta—capable of infecting roughly 63% of susceptible individuals in well-mixed air conditions.
By adjusting ventilation rates, room size, and other parameters, you can observe how particles dilute in real-time. High ventilation rates increase the speed and dilution of these particles, effectively lowering the potential for disease spread.
The ability to reset the scenario and modify the simulation speed allows you to explore both short-term dynamics and long-term exposure patterns, providing an interactive and informative view of how different interventions influence overall transmission risks.
The model’s core equation relates four main factors: the concentration of infectious quanta in the air, the ventilation rate of the room (which dilutes the pathogen), the duration of exposure, and the breathing rate of the occupants. By integrating these elements, the Wells-Riley model provides a probability estimate of infection risk. Although simplified and built on assumptions—such as perfectly mixed air and uniform susceptibility—the model remains a widely referenced tool for understanding the influence of ventilation, occupancy, and exposure duration on the spread of airborne diseases. Over time, it has helped inform public health guidelines and shaped strategies for preventing airborne transmission, particularly in clinical, educational, and workplace settings.
3D VISUALIZATION
This section presents a three-dimensional simulation of airborne infection risk based on the Wells-Riley model. Within this dynamic environment, each red particle represents one infectious quanta—capable of infecting roughly 63% of susceptible individuals in well-mixed air conditions.
By adjusting ventilation rates, room size, and other parameters, you can observe how particles dilute in real-time. High ventilation rates increase the speed and dilution of these particles, effectively lowering the potential for disease spread.
The ability to reset the scenario and modify the simulation speed allows you to explore both short-term dynamics and long-term exposure patterns, providing an interactive and informative view of how different interventions influence overall transmission risks.
Transmission Assessment Views
This tool provides two complementary views of transmission risk:
- Expanded View: Displays a standardized 1-hour baseline assessment to provide a clear and consistent risk overview.
- Collapsed View: Offers real-time dynamic risk calculations based on the elapsed exposure time.
Through the pathogen editor, you can adjust parameters to reflect different pathogens, making these assessments adaptable to a wide range of real-world scenarios.
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Occupant Management System
This interface allows you to configure detailed information about room occupants, organizing them into distinct groups with specific characteristics. Each group can be customized with a name and count. By acknowledging demographic variations and potential differences in generation rates, this tool helps refine the Wells-Riley assessments. The result is a more nuanced understanding of risk and how changes in occupant composition influence overall infection probabilities.
Ventilation Controls
This tool monitors and controls the room’s ventilation rate, measured in Air Changes per Hour (ACH) and Cubic Feet per Minute (CFM) per person. ACH represents the airflow rate relative to the room’s volume, indicating how much fresh air flows through the space each hour. This flow creates a dilution effect, mixing fresh air with existing room air.
CFM per person shows the fresh air delivery rate for each occupant. Higher ACH rates indicate better air dilution, which can help reduce airborne transmission risks. With the ability to fine-tune ventilation parameters, you can simulate scenarios ranging from poorly ventilated rooms to those with robust fresh air exchange. This granular control clarifies the critical role ventilation plays in mitigating airborne risks and provides actionable insights for optimizing indoor air quality strategies.
What Types of Indoor Spaces Can Users Simulate?
The Airwareness Support App is designed with broad versatility, enabling users to simulate virtually any indoor environment. Whether it’s a small classroom, an open-plan office, a restaurant or cafeteria, a conference hall or event space, or even a healthcare facility, the app can accommodate a wide range of scenarios.
While different default 3D room models—such as the provided classroom—offer a visual context, they serve a purely aesthetic role and do not influence the simulation’s underlying calculations. This ensures that the tool can adapt to the specific requirements of various industries and use cases.
Extensive Parameter Control
We know that every indoor space is unique, and a one-size-fits-all approach simply doesn’t cut it. That’s why our Beta release (currently in active development) will give you control over a wide range of parameters, including:
- Room Size: Adjust ceiling heights, floor area to mimic real-world conditions.
- Ventilation Systems: Simulate centralized HVAC systems.
- Occupancy & Activity Levels: Explore how different group sizes, occupant and activities affect transmission risk.
- Pathogen Characteristics: Fine-tune infection rates, half-lives of airborne particles, and infectious doses, to examine how any airborne pathogens behave in your space.
Can the Tool Support Decision-Making for Improving Indoor Air Quality?
Absolutely. The Airwareness Support App is designed to help users:
- Quantify risks associated with specific pathogens like SARS-CoV-2.
- Experiment with different ventilation strategies.
- Optimize room layouts and occupancy levels to reduce transmission risks.
- Communicate risks and mitigation strategies effectively to stakeholders.
An Ongoing Journey of Innovation
This beta release is only the beginning. We are continuously refining the user interface, enhancing simulation accuracy, and expanding the repertoire of features.
How Will User Feedback Be Integrated Into Improving the App?
Accuracy depends on the quality of user-provided inputs, such as room dimensions, ventilation details, and pathogen characteristics. While the app provides detailed insights, it is important to treat the results as approximations that inform decision-making rather than absolute predictions.
The model may not fully address certain edge cases, such as situations where close-range, near-field transmission is more critical. Instead, it excels at providing an overall, long-term average risk assessment for a given space.
Additionally, both the number of infectious doses produced by an infected person and the susceptibility of those exposed can vary significantly between individuals. This variability may help explain why some people remain uninfected despite prolonged or frequent exposure, while others fall ill after only brief contact even in relatively favorable conditions.
Contribute to cleaner air and safer spaces
If you’re a software developer yourself, you can contribute to this open-source project’s code base Github
Or, if you’re in a position to contribute financially to Air Support Project, please make your tax-deductible donation here!
Get Started Today
Ready to take control of your indoor air quality? Head over to airsupportproject.com to try the Airwareness Support App for yourself. It’s completely free, requires no download, and is accessible right from your browser.
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Join us on this journey to a world of healthier indoor spaces. With knowledge, visualization, and collaboration, we can build safer environments—together.
"We shape our tools, and thereafter our tools shape us."
Epi-Yeti
Fueling a revolution for cleaner air, I'm the creative powerhouse behind the Air Support Project's groundbreaking open-source technology. With a fiery passion and a rich background in non-profits, I'm on a mission to clear the skies and transform lives worldwide.
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