Analysis of model and observation data for the development of a public PM2.5 air-quality advisories tool (AQuAT)

An air-quality advisory tool (AQuAT) that combines mobile measurements of particulate matter less than or equal to 2.5μm in diameter (PM2.5) with air-quality simulations performed with the Alaska adapted version of the Community Multiscale Air Quality (CMAQ) model was developed to interpolate PM2.5-measurements into unmonitored neighborhoods in Fairbanks, Alaska. AQuAT was developed as traditional interpolation methods of interpolating the mobile measurements were unsuccessful. Such a spatially differentiated air-quality advisory is highly desired in Fairbanks due to health concerns of PM2.5, and the need to improve the quality of life.;The accuracy of AQuAT depends on the accuracy of the air-quality simulations used for its database. Evaluation of these simulations showed that they captured the observed relationships between PM2.5-concentrations and major meteorological fields (e.g., wind-speed, temperature, and surface-inversions) well. Skill scores for simulated PM2.5-concentrations fell in the range of modern models.;The AQuAT database can include information on the nonlinear impacts of various emission sources on PM2.5-concentrations. This benefit was illustrated by investigating the impacts of emissions from point sources, uncertified wood-burning devices, and traffic on the distribution of PM 2.5-concentrations in the neighborhoods. Sensitivity studies on the effects of wood-burning device changeouts on the PM2.5-concentrations suggested that the emission inventory should be updated as soon as possible to capture recent changes in the emission situation in response to the changeout program.;The performance of AQuAT was evaluated with PM2.5-measurements from mobile and stationary sites, and with simulated PM2.5-concentrations of winter 2010/2011 which were assumed to be "grand-truth" data. These evaluations showed that AQuAT captured the magnitudes and temporal evolutions of the PM 2.5-measurements and the "grand-truth" data well. The inclusion of wind-speed, wind-direction, and temperature in AQuAT did not improve its accuracy. This result may be explained by the fact that the relationships between meteorology and PM2.5-concentrations were already captured by the database.;AQuAT allows quick spatial interpolation after the mobile measurements were made and provides error bars. It also allows for any route within the area for which a database of simulated concentrations exists. It was shown that AQuAT can be easily transferred for applications in other regions.