THESIS
2018
v, 68 pages : illustrations (some color), maps ; 30 cm
Abstract
Air quality prediction based on regional models is now providing forecasts to the public such
that those who are vulnerable to air pollution can be alerted and advised to avoid outdoor
activities in the heavily polluted days. However, with the current spatial resolution of
regional models, the pollution level in individual street is not resolved and exposure
management for the vulnerable may not be effective.
In this research, simulations by coupling results from CMAQ and ADMS is done to provide a
fine spatial resolution pollution level prediction for Hong Kong so that pollutant
concentration in each street can be shown in a forecast map. The forecast by coupling two
models can provide better forecast skill, especially near road sources and the computational
efficiency is also...[
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Air quality prediction based on regional models is now providing forecasts to the public such
that those who are vulnerable to air pollution can be alerted and advised to avoid outdoor
activities in the heavily polluted days. However, with the current spatial resolution of
regional models, the pollution level in individual street is not resolved and exposure
management for the vulnerable may not be effective.
In this research, simulations by coupling results from CMAQ and ADMS is done to provide a
fine spatial resolution pollution level prediction for Hong Kong so that pollutant
concentration in each street can be shown in a forecast map. The forecast by coupling two
models can provide better forecast skill, especially near road sources and the computational
efficiency is also improved to provide greater lead time.
The CMAQ-ADMS air quality forecast is now set up for daily operational air quality forecast
in the HKUST’s forecasting system. It is expected that the forecast will be made available to
the public later this year. It is also expected that the higher spatial resolution air quality
forecast map can bring new possibilities and ideas on exposure management.
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