Project title: Measurements of Atmospheric Trace Gases Using an Ultraviolet Differential Optical Absorption Spectroscopy (UV-DOAS)
Completed in: 2009
The main purpose of this study was to determine gaseous air pollutants, specifically for NO, NO2, and SO2, at two sites in Seattle via optical absorption using differential optical absorption spectroscopy (UV-DOAS). Ambient concentrations for the first site were measured at the Beacon Hill on March 9-23, 2005, using the UV-DOAS compared with point measurements as a benchmark analysis. Ambient concentrations for the second site were measured at the Olive Way near Interstate-5 (I-5) on September 22- October 2, 2006 using the UV-DOAS.
A secondary data analysis that employed the UV Sentry software program with Savitsky golay drifting filters was used for re-processing absorbance spectra. The new program can quantify the target gases with high linear correlation between NO point and UV DOAS measurements (r = 0.84), intermediate to low for NO2(r = 0.45), and relative low for SO2 (r = 0.15).
The average NO concentrations at the Beacon Hill site (15 ppb) were significant lower than the Olive Way site (192 ppb) (p < 0.001). The Beacon Hill site is not as industrial and urban a site as the Olive Way site. There were 100,000 traffic vehicles at the Olive Way site per day, and approximately 4% of these vehicles were trucks and heavy vehicles. The average temperature was 62.78 F and relative humidity was 67.28 %. The average wind speed was 2.2 mph and wind direction was 265 degrees (from the North) on average.
The primary determinant factors of increasing NO concentrations and PM2.5 levels were associated with traffic volumes, weather conditions---temperature, humidity, wind speed, but not wind direction. The most significant effect on variations of NO concentrations was associated with different days of the week (p < 0.001). The second most significant factor influencing on NO concentrations was temperature, with 1° F decrease contributing to an approximate 18% increase in NO concentrations. Each increase in the number of cars was significantly correlated with a 0.05% increase in NO concentrations (p < 0.001).