Air Quality Forecasting in Northern India

Posted on February 28th 2016
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Himalayan Mountains seen from Space

During the past months, the World Air Quality team has been working on analyzing several new Air Quality forecast models, as well as improving the Air Quality forecast model demonstrator.

This article will present the latest forecast model demonstrator, which is based on the Gridded Population of the World (GPW), and which will be applied to analyze the Air Quality forecast for the Northern India region (including Bangladesh, Pakistan and Nepal).

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The forecast model and computation is still based on the GFS Wind Forecast, as we demontrated in the previous article about the forecast in Beijing region that the wind is an essential component for Air Quality forecasting.

However, unlike in the previous simulation where the pollution sources where arbitrarily located in specific locations in the Hebei region, the model used for this Northern India forecast is based on the Gridded Population of the World (aka GPW 2015) from the University of Columbia CIESIN[1]: The assumption is that the higher the number of person living in a given area, the higher the chance of anthropogenic pollution beeing generated.

It is indeed not a 100% correct assumption since the pollution generated by heavy industries can be much higher than the pollution generated by the population, but that's something we will address in our next article. So, for this article, what is wanted is to verify the impact of wind on the pollution under the assumption of a correlation between population density and pollution concentration.

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The image below is showing the density model (at 0.2° resolution) used for the simulation. Each "pixel", or point on this gridded map, is considered as a pollution source. The green color is used for low density regions, which are generating very small amount of pollution, while darker colors represent zones where both population and generated pollution is higher.

Population Density (persons per square meter)
The animation below is showing the real-time concentration based on actual[2] wind data. Note that the color coding and the associated concentration levels is arbitrary - and can not (and should not) be associated one-to-one to AQI levels without further work. The essential idea is to plot the zones which are more likely to have
high
or
very high
pollutant concentration based on the wind condition forecast.

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Particule Concentration Scale:
Air Quality Forecast Viewer
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Loading ...

Forecast Time:


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Without too much surprise, New Delhi is seeing a high level of pollution concentration, but what is really interesting is to compare the situation in New Delhi compared to Beijing: In Beijing, there is literally almost no anthropogenic pollution in the near north, so, when the wind blows from the north, the air gets immediately cleaned. But for New Delhi the population density in the north in still quite high, so the chance of getting immediate clean air from the North are much lower. In order words, New Delhi requires a much higher amount of ventilation (or cumulated wind power) to get its air cleaned-up.

The second observation is the situation in Bangladesh: From the above simulation, the pollution is getting obviously trapped in Bangladesh by the proximity of mountains in the East and North. That's actually not a surprise to anyone who has been living in Dhaka. Unfortunately, there is actually not any available monitoring stations in Bangladesh / Dhaka at the time of writing, so it is not possible to verify forecast accuracy vs the actual observations. (Note: Few days after this article was written, the US Consultate in Dhaka started to publish their Air Quality Data, which you can find from this link: city/bangladesh/dhaka/us-consulate). For more information about the Air Quality in Bangladesh, you can refer to this page: country/bangladesh.

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As a conclusion, this forecast model is still far from being complete, but at least, it has the advantage of showing the impact of wind the pollution concentration in Northern India, and especially how the Himalayan mountains are trapping the air pollution. In the next version, we will introduce a enhanced version for the pollution sources, taking into account known positive flux which we can be deducted from observations.

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Note: In order to get the real-time forecast viewer to be able to handle such a wide region, our team had to work hard on a quite a few improvements and optimizations. We are now working on an even further optimized version able to handle more than 10K particles, and we are considering making its code open source, so if you are interested, drop us a message via the "discuss" board below (we will will only make it open source only if there is enough demand for it).

[1] Center for International Earth Science Information Network
[2] so, if you check this animation tomorrow, you might see a very animation


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    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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