Worldwide air quality forecasts at city-block resolution. Distributed through API


Aerostate is a data platform that helps you add air quality information to your products.
We provide air quality analysis and 4 days forecast at the resolution of a city block.
Our analytical tools transform the raw forecast data into actionable insights for users
of mobile apps and IoT platforms. Our solution is distributed via API and as SaaS.
AeroState delivers sustainable value to industry leaders and increases
engagement of the end users.
Air quality is distributed very irregularly in cities. The reason
is traffic, chaotic wind patterns
and local singularity of urban landscape. This animation transforms Aerostate air quality data into self-explanatory
heat map.

Please select a city from the list
to see Aerostate air qualty forecast.
0 - 50
50 - 100
101 - 150
Lightly Polluted
151 - 200
Moderately Polluted
201 - 300
Heavily Polluted
AQI and Health Implications


Mobile apps

Integrate air quality API into your mobile products - weather, healthcare, fitness and many more. Increase user engagement and retention, as well as DAU of your service. Ads revenue share model is available.

Smart City

Get advantage of Aerostate technology in city planning and decision making. Aerostate and IoT inform citizens about pollution levels, and help reduce their pollution exposure.

Smart Home

Integrate outside air quality into your app to prove the use of air purifier. Notify users when it is safe to open windows or have a walk outside.


Emission database

Our satellite sources include Landsat, MODIS, IASI and others. Emission databases include data from CARMA, MACC, GFAS and others. Traffic emissions are derived using Nokia HERE API, 3d city models, and proprietary vehicle emission models.
Satellite Weather Traffic
Monitoring stations GPS AEROSTATE

Atmosphere models

We run open source and proprietary atmospheric transport, microphysics and chemistry models. We do it at global and local scales. We use a cluster of dedicated machines with redundant environment and automatic scalability.

Supervised by AI

Deep learning neural network with the long-term memory layers is applied over the results of atmosphere models. It helps our solution achieve accuracy of 90%.

Delivered through API

Aerostate data can be received via web API. In addition to the values of air quality our API response contains behaviour suggestions - sensitive groups, health effects, health advisory.




Author of more than 30
publications in atmospheric
science. Reviewer at the Journal
of Geophysical Research and
other high-impact scientific
editions and conferences.
Lead developer and author
of Yandex Meteum - the most
accurate weather forecasting
algorithm over European
and Asian countries.



Author of atmospheric
tracer transport model GELCA.
More than 40 publications
in top peer-reviewed
journals including Nature
Co-designed Yandex
Meteum - the most accurate
weather forecasting algorithm
over European and Asian


Head of Research

10 years of experience in
atmospheric science. Principle
Investigator in GOSAT satellite
project. Took part in
reconstruction of Fukushima
disaster estimating radioactive
emissions. Over 30 publications
in peer-reviewed journals
with high impact-factor
including Nature


Partner Relations

Before joining Aerostate
Evgeny co-founded a travel
agency. He combines
business skills with a science
background. Expert in
atmosphere boundary layer -
took part in more than 10
expeditions as a consultant.
15 publications, over
20 presentations for
international conferences.