No abstract

Soil and leaf litter are significant global sources of small oxidized volatile organic compounds, VOCs (e.g., methanol and acetaldehyde). They may also be significant sources of larger VOCs that could act as precursors to secondary organic aerosol (SOA) formation. To investigate this, soil and leaf litter samples were collected from the University of Idaho Experimental Forest and transported to the laboratory. There, the VOC emissions were characterized and used to drive SOA formation via dark, ozone-initiated reactions. Monoterpenes dominated the emission profile with emission rates as high as 228 μg-C m–2 h–1. The composition of the SOA produced was similar to biogenic SOA formed from oxidation of ponderosa pine emissions and α-pinene. Measured soil and litter monoterpene emission rates were compared with modeled canopy emissions. Results suggest surface soil and litter monoterpene emissions could range from 12 to 136% of canopy emissions in spring and fall. Thus, emissions from leaf litter may potentially extend the biogenic emissions season, contributing to significant organic aerosol formation in the spring and fall when reduced solar radiation and temperatures reduce emissions from living vegetation.

The Yakima Air Wintertime Nitrate Study (YAWNS) was conducted in January 2013 to investigate the drivers of elevated levels of fine particulate matter (PM 2.5) frequently present in the region during winter stagnation periods. An extended stagnation period occurred during the study. For the first four days of the event, skies were clear and the strong diel variation in air pollution patterns were consistent with the expected effects of strong lowlevel nighttime temperature inversions with moderate mixing during daylight hours. Later in the event a low-level cloud layer formed that persisted over the Yakima Valley for the next seven days while regional conditions remained stagnant. Coincident with the onset of cloud, the levels of all measured primary pollutants, including CO 2 , CO, NO x , particle number concentration, and black carbon, dropped dramatically and remained low with negligible diel variation for as long as the cloud layer was present. The observed patterns for these air pollutants are consistent with decreased stability and enhanced mixing associated with the cloud-topped boundary layer. Interestingly, levels of secondary pollutants, most notably particulate ammonium nitrate, did not exhibit the same decline. This difference may be due to shifts in the chemical production of secondary pollutants during cloudy conditions, or may merely reflect a further influence of mixing. The results imply that the best strategies for managing wintertime air quality during episodes of persistent cloud are likely different from those needed during clear-sky stagnation events.

No abstract

A multiple linear regression (MLR) chemical mass balance model was applied to data collected during an air quality field experiment in Yakima, WA, during January 2013 to determine the relative contribution of residential wood combustion (RWC) and vehicle emissions to ambient pollutant levels. Acetonitrile was used as a chemical tracer for wood burning and nitrogen oxides (NOx) as a chemical tracer for mobile sources. RWC was found to be a substantial source of gas phase air toxics in wintertime. The MLR model found RWC primarily responsible for emissions of formaldehyde (73%), acetaldehyde (69%), and black carbon (55%) and mobile sources primarily responsible for emissions of carbon monoxide (CO; 83%), toluene (81%), C2‐alkylbenzenes (81%), and benzene (64%). When compared with the Environmental Protection Agency's 2011 winter emission inventory, the MLR results suggest that the contribution of RWC to CO emissions was underestimated in the inventory by a factor of 2. Emission ratios to NOx from the MLR model agreed to within 25% with wintertime emission ratios predicted from the Motor Vehicle Emissions Simulator (MOVES) 2010b emission model for Yakima County for all pollutants modeled except for CO, C2‐alkylbenzenes, and black carbon. The MLR model results suggest that MOVES was overpredicting mobile source emissions of CO relative to NOx by a factor of 1.33 and black carbon relative to NOx by about a factor of 3.