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The air quality forecast rote: Recent changes and future challenges.

William F Ryan1

  • 1a Department of Meteorology , The Pennsylvania State University, University Park , Pennsylvania , USA.

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Air quality forecasting has evolved significantly, with numerical air quality prediction models now crucial for improving accuracy. Continuous calibration is essential due to ongoing emission reductions in urban areas.

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Area of Science:

  • Environmental Science
  • Atmospheric Chemistry
  • Meteorology

Background:

  • Air quality forecasting is a recent field, with most programs established in the last 20 years.
  • Forecast preparation methods have undergone dramatic changes in the past decade.
  • Routine air quality forecasts are now standard for major U.S. metropolitan areas.

Purpose of the Study:

  • To summarize challenges in air quality forecasting.
  • To detail the current forecast preparation process.
  • To analyze prospects for future improvements in air quality prediction.

Main Methods:

  • Utilizing a blend of past, current, and future pollutant observations for initial forecast fields.
  • Employing numerical air quality prediction (NAQP) models for real-time forecast support.
  • Incorporating forecaster expertise to adjust for mesoscale features not resolved by models.

Main Results:

  • Air quality forecasts are inherently more uncertain than weather forecasts due to multiple pollutant predictions.
  • Reductions in precursor emissions have degraded the skill of older statistical forecasting methods.
  • NAQP models and statistical techniques are now central to the current forecast adjustment process.

Conclusions:

  • Advances in NAQP model resolution, chemical data assimilation, and emissions data are expected to enhance mesoscale predictions.
  • Future improvements in air quality forecasting will likely be driven by enhanced NAQP capabilities.
  • Ongoing calibration of all forecasting methods is necessary to adapt to emission reductions.