A visual study of Wind impact on PM2.5 Concentration

Posted on November 5th 2015
Share: aqicn.org/faq/2015-11-05/a-visual-study-of-wind-impact-on-pm25-concentration/

A perfect dust storm (attribution)

We have been writing quite a few times about the influence of wind on air pollution, and how strong winds (or, to be more precise, strong ventilation) can help to clean the air in a very short time. But we never had the opportunity to create on a dynamic visualization of this phenomenon, so this is what this article will be writing about.


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When it comes to Air Quality forecasting, the key to a better accuracy is refined the forecasting model, and create a specific modelisation for each country, and, even better, for each city. For instance, in Beijing, it is the proximity of the mountains in the North and Hebei in the south which defines the model:

  • South wind tend to increase the pollution in Beijing: If the wind is not strong enough (i.e. not ventilating enough), then the particles will get blocked by the mountains and will not be able to move further to the north, thus creating a dense particule concentration in Beijing.
  • North wind tend to clear the pollution: When the wind blows sufficiently from the North, the air gets almost immediately cleared since there is no "pollution source" in the north (or, at least, much less than in the south).

This is what one can see in the animation below, in which the pollution sources are arbitrarilly located where the monitoring stations are located in hebei. Each pollution source in emitting one particle every hour. The more the number of particles in a zone, the higher the pollution (blue corresponds to low concentration, red ~ brown to high concentrations). The wind model is based on the Global Forecast System (aka GFS).


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Air Quality Forecast Viewer
version 1.2 (2016/2/18)
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This is of course a very light model compared to the complex models which do require super computer processing power to be able to compute the whole world air quality forecast. But it has the advantage of visually explaining the basic concept behind air quality forecasting.

To be more precise, the model should include vertical wind profile, as well as the forecasting for several heights (layers) - currently, the model is only using the forecast at 10 meters, 100 meters and 5KM. Moreover, the pollution sources should be more complete and include the overall world sources - currently, only sources from Hebei are included.


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Last, many research reports have investigated Machine Learning or Artificial Intelligence based Air Quality forecast systems. The concept behind is to "learn" by comparing the observed data with the forecasted data and identify repetitive patterns (as shown on the diagram on the right).

On the paper, Machine Learning based forecasting system look good, but in actual fact, are they any better than the tradtional deterministic models (which we do prefer at the World Air Quality Index project)? Refering to the excellent TED talk from Talithia Williams on 'Own your body's data', our answer to this question is "show us the data!", and that's something we will be writing about in our next article on forecasting!

Click here to see all the FAQ entries
  • AQI Scale: What do the colors and numbers mean?
  • Using Statistical Distances for Real-time Sensor Networks Validation
  • Nitrogen Dioxyde (NO2) in our atmosphere
  • About the Air Quality and Pollution Measurement:

    About the Air Quality Levels

    AQIAir Pollution LevelHealth ImplicationsCautionary Statement (for PM2.5)
    0 - 50GoodAir quality is considered satisfactory, and air pollution poses little or no riskNone
    51 -100ModerateAir quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution.Active children and adults, and people with respiratory disease, such as asthma, should limit prolonged outdoor exertion.
    101-150Unhealthy for Sensitive GroupsMembers of sensitive groups may experience health effects. The general public is not likely to be affected.Active children and adults, and people with respiratory disease, such as asthma, should limit prolonged outdoor exertion.
    151-200UnhealthyEveryone may begin to experience health effects; members of sensitive groups may experience more serious health effectsActive children and adults, and people with respiratory disease, such as asthma, should avoid prolonged outdoor exertion; everyone else, especially children, should limit prolonged outdoor exertion
    201-300Very UnhealthyHealth warnings of emergency conditions. The entire population is more likely to be affected.Active children and adults, and people with respiratory disease, such as asthma, should avoid all outdoor exertion; everyone else, especially children, should limit outdoor exertion.
    300+HazardousHealth alert: everyone may experience more serious health effectsEveryone should avoid all outdoor exertion

    To know more about Air Quality and Pollution, check the wikipedia Air Quality topic or the airnow guide to Air Quality and Your Health.

    For very useful health advices of Beijing Doctor Richard Saint Cyr MD, check www.myhealthbeijing.com blog.


    Usage Notice: All the Air Quality data are unvalidated at the time of publication, and due to quality assurance these data may be amended, without notice, at any time. The World Air Quality Index project has exercised all reasonable skill and care in compiling the contents of this information and under no circumstances will the World Air Quality Index project team or its agents be liable in contract, tort or otherwise for any loss, injury or damage arising directly or indirectly from the supply of this data.



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