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Mark C. Green, Jin Xu, and Narendra Adhikari

Abstract

Typical diurnal wind patterns and their relationship to transport of atmospheric aerosol in the Columbia River gorge of Oregon and Washington are addressed in this paper. The measurement program included measurements of light scattering by particles (b sp) with nephelometers, and wind speed and direction, temperature, and relative humidity at seven locations in the gorge. Winds are shown to respond to along-gorge pressure gradients, and five common patterns were identified: strong, moderate, and light westerly (west to east), light easterly, and winter easterly. The strong westerly and winter easterly patterns were the most common summer and winter patterns, respectively, and represented strong gap flow. The light westerly and light easterly patterns occurred most frequently in spring and autumn transition periods. Winter easterly had the highest light scattering and indicated sources east of the gorge mainly responsible for haze. During summer, as westerly winds increased diurnally, a pulse of hazy air from the Portland, Oregon, metropolitan area is transported eastward into the gorge, arriving later with distance into the gorge. During light easterly flow impacts to haze from the city of The Dalles, Oregon, are noted as the wind shifts direction diurnally.

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Mark C. Green, Robert G. Flocchini, and Leonard O. Myrup

Abstract

Temporal principal components analysis was applied separately to monthly long-term wind, temperature, and precipitation data for Southern California. Physical explanations of the significant eigenvectors are presented. Cluster analysis of the component loadings was then used to form groups of months (seasons) having similar spatial patterns. The resulting groupings of months differed from the conventional definition of seasons. The wind and temperature analyses grouped the same months, with long summers, moderately long winters, short springs, and very short autumns. The precipitation analysis formed a long season, including the winter months, representing synoptic systems occasionally passing through the area, a summer thunderstorm season associated with influx of moisture from the south, and dry transitional periods separating these seasons. The purpose of the analysis was to pregroup two years of hourly wind data to remove most of the annual signal before applying spatial eigenvector analysis for a mesoscale climatological classification study. The approach is expected to be most useful when applied to mesoscale areas with significant seasonal variation in spatial patterns of climatic variables.

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Mark C. Green, Judith C. Chow, John G. Watson, Kevin Dick, and Daniel Inouye

Abstract

Many populated valleys in the western United States experience increased concentrations of particulate matter with diameter of less than 2.5 μm (PM2.5) during winter stagnation conditions. Further study into the chemical components composing wintertime PM2.5 and how the composition and level of wintertime PM2.5 are related to meteorological conditions can lead to a better understanding of the causes of high PM2.5 and aid in development and application of emission controls. The results can also aid in short-term air-pollution forecasting and implementation of periodic emission controls such as burning bans. This study examines relationships between PM2.5 concentrations and wintertime atmospheric stability (defined by heat deficit) during snow-covered and snow-free conditions from 2000 to 2013 for five western U.S. urbanizations: Salt Lake City, Utah; Reno, Nevada; Boise, Idaho; Missoula, Montana; and Spokane, Washington. Radiosonde data were used where available to calculate daily heat deficit, which was compared with PM2.5 concentration for days with snow cover and days with no snow cover. Chemically speciated PM2.5 data were compared for snow-cover and snow-free days to see whether the chemical abundances varied by day category. Wintertime PM2.5 levels were highly correlated with heat deficit for all cities except Spokane, where the airport sounding does not represent the urban valley. For a given static stability, snow-cover days experienced higher PM2.5 levels than did snow-free days, mainly because of enhanced ammonium nitrate concentrations. Normalizing average PM2.5 to the heat deficit reduced year-to-year PM2.5 variability, resulting in stronger downward trends, mostly because of reduced carbonaceous aerosol concentrations. The study was limited to western U.S. cities, but similar results are expected for other urban areas in mountainous terrain with cold, snowy winters.

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