About us

The YourAirTest air quality monitoring ecosystem is a wide range of Software and Hardware products worked on by a team of scientists, ecologists, developers, graduate students and students.

We model pollution emissions from businesses, fires and cars, as well as emissions from nuclear power plant accidents, to further visualize them on a map and calculate the level of negative impact on the environment and people, so that society can see, realize and rethink the importance of clean air and change the situation around them.

Our Mission

is to create an air quality monitoring ecosystem so that society, governments and businesses together find a mutual path to prosperity.

Every day there is hard work on each of the following areas:

YourAirTest website

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.

WRF (Weather Research and Forecasting)

WRF is a calculated weather forecasting model, a system designed for atmospheric research as well as operational forecasting. We have set up our WRF in which we use GFS, and are now working on an ensemble of GFS & iCON.

Modeling system for air pollution CALPUFF

CALPUFF - is a multilayer dispersion model, with an integrated Lagrangian modeling system that simulates the effects of time and space variable meteorological conditions to simulate the dispersion of atmospheric pollutants.

CALPUFF can be applied to a wide range of scenarios, including long-range effects (beyond 50 km of emissions) that cannot be modeled with traditional flare models (e.g., AERMOD).

Its changing meteorological field makes it useful for regions with very complex topography or unsteady conditions.

YourAirTest mobile app

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 app will be expanded with an air pollution forecast and notifications of significant deterioration in advance.

Predicting air pollution from plants

Our scientists and developers managed to combine WRF (multiple weather forecasting model) and CALPUFF (multilayer scattering model with integrated Lagrangian modeling system) to create a two-day weather and pollution forecast for Krivoy Rog. To do this, we modeled pollution in a few years from businesses to identify pollution patterns and their changes to create a forecast.

Because of the war, we eliminated the forecasting, but it is available at the link where you can see the forecast for January 29-31, 2022.

https://bit.ly/KrRihForecast

MonAir

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.

Training sessions on environmental fundamentals and air pollution

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.

Our Mission

is to create an air quality monitoring ecosystem so that society, governments and businesses together find a mutual path to prosperity.

Every day there is hard work on each of the following areas:

YourAirTest website

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.

WRF (Weather Research and Forecasting)

WRF is a calculated weather forecasting model, a system designed for atmospheric research as well as operational forecasting. We have set up our WRF in which we use GFS, and are now working on an ensemble of GFS & iCON.

MonAir

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.

Modeling system for air pollution CALPUFF

CALPUFF - is a multilayer dispersion model, with an integrated Lagrangian modeling system that simulates the effects of time and space variable meteorological conditions to simulate the dispersion of atmospheric pollutants.

CALPUFF can be applied to a wide range of scenarios, including long-range effects (beyond 50 km of emissions) that cannot be modeled with traditional flare models (e.g., AERMOD).

Its changing meteorological field makes it useful for regions with very complex topography or unsteady conditions.

YourAirTest mobile app

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 app will be expanded with an air pollution forecast and notifications of significant deterioration in advance.

Predicting air pollution from plants

Our scientists and developers managed to combine WRF (multiple weather forecasting model) and CALPUFF (multilayer scattering model with integrated Lagrangian modeling system) to create a two-day weather and pollution forecast for Krivoy Rog. To do this, we modeled pollution in a few years from businesses to identify pollution patterns and their changes to create a forecast.

Because of the war, we eliminated the forecasting, but it is available at the link where you can see the forecast for January 29-31, 2022.

https://bit.ly/KrRihForecast

Training sessions on environmental fundamentals and air pollution

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.

Project Team

  • 3 Universities
  • 5 PhDs
  • 5 Ecologists
  • 8 Developers
  • 5 Mentors

Project development plan

2018
Concept Approval. Creating an MVP for web applications and MonAir sensors. Validation of different sensors.
2020
Beta version of the website and mobile app. Validation of our MonAir ground stations with state stations. Setting up WRF & Calpuff
2021
Configuring the air quality pollution model in Krivoy Rog. Sale of MonAir devices. Complementing functions for B2C, B2G, B2B. IndoorSolution. EcoAirSolutions 2021 conferences.
2022
WRF - the development of the GFS & iCON Ensemble. MonAir Certification. Calpuff & Aermod air pollution modeling from industries, radiation, fires and vehicle emissions. Mobile app with air quality and weather notifications. Scaling.

OUR INTRINSIC MOTIVATION is the SUSTAINABLE DEVELOPMENT GOALS

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