| Summary: | Thesis (M.S.) University of Alaska Fairbanks, 2018 The air quality monitoring (AQM) network in Alaska is limited to major urban areas and national parks thus leaving a large proportion of the state unmonitored. To evaluate the use of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived aerosol optical depth (AOD) to predict ground-level PM2.5 concentrations and thereby increase the spatial coverage of the AQM network in Alaska, MODIS AOD was first validated against ground-based measurements of AOD in Utqiagvik and Bonanza Creek Alaska. MODIS AOD from 2000 to 2014 was obtained from MODIS collection 6 using the dark target land and ocean algorithms between the months of April and October. Based on validation results, individual Aqua and Terra products are valid for both locations at 10-kilometer and 3-kilometer resolution. In addition, combined Aqua and Terra MODIS AOD products are valid for both locations at 3-kilometer resolution and 10-kilometer resolution for Utqiagvik. The available PM2.5 data was then compared for satellite retrieval and all retrieval days to determine if there was sufficient data and the amount of bias introduced by possible low retrieval rates. Overall, Juneau had the lowest retrieval rates while Fairbanks and North Pole had the highest retrieval rates. In addition, Juneau appeared to have relatively high bias while stations located in Anchorage, Palmer, Fairbanks and North Pole had relatively low bias. Based on these findings, no models were developed for Juneau (southeast Alaska). Multilinear regression models were then developed for southcentral (Anchorage and Palmer) and interior (Fairbanks and North Pole) Alaska where the log-transform of PM2.5 was the response and meteorological data and the log-transform of MODIS AOD were the predictors. MODIS AOD appeared to be most highly correlated with PM2.5 in interior Alaska, while there was little to no correlation between MODIS AOD and PM2.5 in southcentral Alaska. All models underestimate surface PM2.5 concentrations which may be ...
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