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 refine 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 montains 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 particules will get blocked by the montains 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 emmitting one particule every hour. The more the number of particules 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 advantange 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!


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    대기 품질 및 환경 오염 측정에 관하여 :

    대기 품질 지수 단계에 대하여

    AQI지수구분구간의미
    0 - 50좋음대기오염 관련 질환자군에서도 영향이 유발되지 않을 수준
    51 -100보통환자군에게 만성 노출시 경미한 영향이 유발될 수 있는 수준
    101-150민감군영향환자군 및 민감군에게 유해한 영향이 유발될 수 있는 수준
    151-200나쁨환자군 및 민감군(어린이, 노약자 등)에게 유해한 영향 유발, 일반인도 건강상 불쾌감을 경험할 수 있는 수준
    201-300매우나쁨환자군 및 민감군에게 급성 노출시 심각한 영향 유발, 일반인도 약한 영향이 유발될 수 있는 수준
    300+위험환자군 및 민감군에게 응급 조치가 발생되거나, 일반인에게 유해한 영향이 유발될 수 있는 수준
    (Reference: see airkorea.or.kr)

    대기 품질과 오염에 대해 더 많은 것을 알아보려면 위키피디아의 공기품질 문서(영어)을 보거나 공기 품질과 건강에 대한 AirNow 가이드(영어)를 참조해보세요.

    베이징 의사 Richard Saint Cyr MD의 건강 관련 팁을 보려면 www.myhealthbeijing.com 에 블로그를 확인하세요.


    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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    Temperature unit:
    Celcius