Prediction of air quality in sydney, australia as a function of forest fire load and weather using bayesian statistics

HIGHLIGHTS

SUMMARY

Weather also determines smoke dispersal patterns: e_g wind speeds, directions, boundary layer heights and broader synoptic patterns influence vertical and lateral smoke movement. Producing highly accurate empirically based predictions from individual fires may not be realistic due to difficulties in collecting enough smoke-pollution observations and relating them to a particular fire: e_g sparse monitoring networks (mostly clustered in cities) making detection from any particular fire unlikely and complex weather circulation patterns between a fire and a monitor. The model could help identify conditions where conducting HRBs requires further consideration of smoke effects before . . .

 



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