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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    大気汚染指数の測定方法:

    大気汚染レベルについて

    指数大気質指数の分類(米国)健康影響 / カテゴリ粒子状物質(PM10,PM2.5)
    0 - 50良い - Good通常の活動が可能なし
    51 -100並 - Moderate特に敏感な者は、長時間又は激しい屋外活動の減少を検討非常に敏感な人は、長時間または激しい活動を減らすよう検討する必要がある。
    101-150敏感なグループにとっては健康に良くない - Unhealthy for Sensitive Groups心臓・肺疾患患者、高齢者及び子供は、長時間又は激しい屋外活動を減少心疾患や肺疾患を持つ人、高齢者、子供は、長時間または激しい活動を減らす必要がある。
    151-200健康に良くない - Unhealthy上記の者は、長時間又は激しい屋外活動を中止
    すべての者は、長時間又は激しい屋外活動を減少
    心疾患や肺疾患を持つ人、高齢者、子供は、長時間または激しい活動を中止する必要がある。それ以外の人でも、長時間または激しい活動を減らす必要がある。
    201-300極めて健康に良くない - Very Unhealthy上記の者は、すべての屋外活動を中止
    すべての者は、長時間又は激しい屋外活動を中止
    心疾患や肺疾患を持つ人、高齢者、子供は、全ての屋外活動を中止する必要がある。それ以外の人でも、長時間または激しい活動を中止する必要がある。
    300+危険 - Hazardous上記の者は、屋内に留まり、体力消耗を避ける
    すべての者は、屋外活動を中止
    全ての人が屋外活動を中止する必要がある。特に、心疾患や肺疾患を持つ人、高齢者、子供は、屋内に留まって激しい活動を避け静かに過ごす必要がある。
    (Reference: see wikipedia,and cn.emb-japan.go.jp/)

    大気汚染についての更なる詳細をお知りになりたい方は、WikipediaAirNowを参照してください。

    北京在住の医師Richard Saint Cyr氏による大変役に立つ健康上のアドバイスは、 www.myhealthbeijing.com をご覧ください。


    使用上の注意: すべての大気質データは公開時点では妥当性が担保されていないため、これらのデータは予告なしに修正することがあります。 世界大気質指数プロジェクトは、この情報の内容を編集に最善の注意を尽くしておりますが、いかなる状況においても World Air Quality Index プロジェクトチームまたはそのエージェントは、このデータの供給によって直接的または間接的に生じる損失や損害について責任を負いません。



    設定


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    Temperature unit:
    Celcius