Air pollution forecasting

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Air pollution forecasting is the application of science and technology to predict the composition of the air pollution in the atmosphere for a given location and time. Mainstream pollution prediction algorithms tend to utilize air quality index or PM2.5 concentration to indicate pollution level.

The forecast may give the pollutant's concentration or the air quality index.

Countries and cities are given forecasts by state and local government organizations, as well as private companies like Airly, AirVisual, Aerostate, BreezoMeter, PlumeLabs, and DRAXIS that provide air pollution forecasts.

Techniques[]

• Air pollution forecasting can be done by coupling weather forecasting systems with chemical transport model and atmospheric dispersion modeling.
• Recent studies have incorporated machine learning techniques such as neural networks, regressions, and random forests to achieve high accuracy.^[1]

The forecast takes into account local emission sources (like nearby traffic or industry) and remote sources (e.g. dust that is carried by air parcels and follows the wind direction).

The forecast temporally resolution is usually daily or hourly and the spatial resolution can change from block resolution to dozens of km resolution.

Most forecasts of air quality cover two to five days.^[2]

To reduce the risks related to air pollution, it becomes extremely important to forecast the pollution levels ahead of time. Using the data from the past and combining it with AI and ML technologies, it becomes possible to understand the patterns of air pollution.

Advanced approaches in air quality forecasting combine historical data with data generated via on-ground sensors and satellite observations to provide insights, analysis, and forecasts from global to street-level air pollution. It also takes into consideration local factors like traffic, regional weather patterns, or emissions in the atmosphere.

Motivation[]

• By knowing the air quality forecast one can decide how to act, e.g. due to air pollution health effects, one can prepare ahead of time and choose the best time to do an outdoor activity.
• Deciding whether to put on a skin care ointment.^[3]
• Find the cleanest route for driving, walking or cycling.^[4]
• Deciding whether to leave the windows open or closed.^[5]
• Governments can utilize air quality forecasts to implement effective pollution control measures.^[6]

• Air pollution is one of the world’s biggest problems, and it causes respiratory problems, lung diseases, and cardiovascular issues and can contribute to mental health issues and aggravate existing health conditions. It can cause depletion to planetary health equally. Therefore, reducing and making people aware of these problems caused by air pollution becomes essential.
• With the accurate method of forecasting air pollution, it becomes easier to manage and mitigate the risks of air pollution and ensure a safe level of pollutant concentration in the region. It also helps assess risks to the environment and the climate caused by poor air quality standards. Accurate forecasting can also lead to ease in planning day-to-day activities, avoiding locations with high alert areas, and implementing effective pollution control measures.

References[]

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