YourAirTest is an ecosystem for monitoring the impact of fires on air quality.
We model smoke emissions from forest and peat fires, visualize them on a map, and assess the risks to people and the environment.
YourAirTest combines sensor networks, satellite data, and physical-chemical models into a single system for measuring and predicting the impact of fires on air quality.
We specialize in modeling emissions from forest, peat, and landscape fires. For each case, we calculate the amount of solid particles (PM), gases, and toxic compounds emitted.
We visualize the data on interactive maps, calculate concentrations in populated areas, and prepare validated health risk assessments.
Our focus is to make the impact of fires on the air visible.
We help communities, emergency services, medical institutions, and scientists to respond quickly and plan protective measures.
is to provide a full cycle of analysis: from rapid fire detection and forecasting to emissions assessment and public warning about dangerous air pollution, so that society, governments, and businesses can find a common path to prosperity.
Every day there is hard work on each of the following areas:
Nowadays, every visitor of yourairtest.com has the opportunity to see the current state of the air in his location in 100 countries around the world. In addition, air flows are visualized, which will become a forecast of air pollution in the near future.
The site has easy access to visual information, details about the project and answers to the most common questions.
WildFiresUA is a system for detecting forest fires, analyzing their development, and modeling emissions.
WildfiresUA Identification - fire detection
WildfiresUA Evolution - fire development modeling
WildfiresUA Pollution - assessment of emissions and their spread
It is important to understand that large-scale fires pose a great threat to human life and health, even in regions far from the fire zone itself, as smoke can sometimes spread for tens of kilometers or more.
In the realm of weather forecasting and atmospheric research, precision and innovation are paramount. This case study delves into the development and implementation of YAT-Meteo, a groundbreaking weather research and forecasting product.
MonAir Out - is our full-featured ground-based monitoring stations for atmospheric air with electrochemical sensors which send real-time data on humidity, temperature and pressure levels as well as on presence of O3 (ozone), NO2 (nitrogen dioxide), SO₂ (sulfur dioxide) and CO (carbon monoxide) gasses and two types of dust PM2.5; PM10.
MonAir In - is our home and office air quality sensors that send real-time data on moisture level, temperature and pressure, and AQI.
The mobile app is designed to reduce people's health impacts from poor air quality. We provide accurate data on 6 key pollutants: PM2.5 particulate matter, PM10 particulate matter, O3 (ozone), NO2 (nitrogen dioxide), SO₂ (sulfur dioxide) and CO (carbon monoxide) in the required format (U.S.AQI and EAQI ). We also added a weather forecast.
The app also has the ability to add your locations to favorites, quick to share results and available personalization in the form of four characters (male, female, astronaut and alien).
In the future, the iOS and Android app will be enhanced with an air pollution forecast and notifications of significant deterioration in advance.
We've developed a service that forecasts the potential fallout for up to 24 hours. This system provides insights into the likely path of radioactive particles carried by the wind and their concentration levels. This information allows us to assess which areas might be affected and where the radiation's impact would be most severe.
With the support of universities, we are creating trainings to teach citizens, ecologists and students about the basics of ecology and the effects of air pollution on health, as well as what to do, where to look for information and how to interpret it.
For those who want to dive deeper into air pollution modeling, we suggest exploring the Gaussian Plume Model with us.
The Gaussian Plume Model is the most common air pollution model. It is based on a fairly simple formula that describes the three-dimensional pollution concentration field produced by a point source under steady-state meteorological and emission conditions.
This model is used to predict the pathways and concentrations of pollutants in the air during transport and dispersion in the atmosphere after an emission. These models can be used for emergency preparedness as well as response and recovery operations.
5 Universities
The goals of YourAirTest team directly correlate with the The Sustainable Development Goals (SDGs), set in 2015 by the United Nations General Assembly. Anong this 17 sustainable development goals the leading for our project are the following:
Good Health and Well-being
Clean Water and Sanitation
LIFE ON LAND
PARTNERSHIPS
for sustainable development