We present the unprecedented capability to identify and quantify volatile organic compounds (VOCs) by means of proton transfer reaction time-of-flight (PTR-TOF) mass spectrometry on-line with high time resolution. A mass resolving power of 4000 -5000 and a mass accuracy of 2.5 ppm allow for the unambiguous sum-formula identification of hydrocarbons (HCs) and oxygenated VOCs (OVOCs). Test masses measured over an 11-wk period are very precise (SD Ͻ 3.4 ppm) and the mass resolving power shows good stability (SD Ͻ 5%). Based on a 1 min time resolution, we demonstrate a detection limit in the low pptv range featuring a dynamic range of six orders of magnitude. Sub-ppbv VOC concentrations are analyzed within a second; sub-pptv detection limits are achieved within a few tens of minutes. We present a thorough characterization of our recently developed PTR-TOF system and address application fields for the new instrument. (J Am Soc Mass Spectrom 2010, 21, 1037-1044

Wildfires emit significant amounts of pollutants that degrade air quality. Plumes from three wildfires in the western U.S. were measured from aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Biomass Burning Observation Project (BBOP), both in summer 2013. This study reports an extensive set of emission factors (EFs) for over 80 gases and 5 components of submicron particulate matter (PM1) from these temperate wildfires. These include rarely, or never before, measured oxygenated volatile organic compounds and multifunctional organic nitrates. The observed EFs are compared with previous measurements of temperate wildfires, boreal forest fires, and temperate prescribed fires. The wildfires emitted high amounts of PM1 (with organic aerosol (OA) dominating the mass) with an average EF that is more than 2 times the EFs for prescribed fires. The measured EFs were used to estimate the annual wildfire emissions of carbon monoxide, nitrogen oxides, total nonmethane organic compounds, and PM1 from 11 western U.S. states. The estimated gas emissions are generally comparable with the 2011 National Emissions Inventory (NEI). However, our PM1 emission estimate (1530 ± 570 Gg yr−1) is over 3 times that of the NEI PM2.5 estimate and is also higher than the PM2.5 emitted from all other sources in these states in the NEI. This study indicates that the source of OA from biomass burning in the western states is significantly underestimated. In addition, our results indicate that prescribed burning may be an effective method to reduce fine particle emissions.

S1 Solutions from positive matrix factorisa-1 tion 2 For this study, a four factor solution was determined to best represent the 3 measured aerosol. A two factor solution separates the Ship Emissions factor 4 from the ambient background aerosol, while a three factor solution includes 5 the Organic factor. It is only with four factors that the Marine Biogenic 6 factor is separated from the Continental factor. Additional factors either 7 identify instrumental noise, or split the existing factors. Figure S1 shows 8 the decrease in Q/Q exp as additional factors are included, where Q exp is 9 the expected Q. We see that including a 5 th factor decreases Q/Q exp by 10 identifying instrumental noise, while additional factors only serve to capture 11 episodic events, often coinciding with ship emissions. Even though Q/Q exp 12 decreased slightly from 3.36 for four factors down to 3.06 for 10 factors, 13 including more factors did not contribute additional information about the 14 measured aerosol. As such, the four factor solution was deemed to give the 15 most information about the measured ambient aerosol. 16 The robustness of the solution can be explored by either varying the initial 17 seed, which changes the set of pseudorandom values used for the initial point 18 (Paatero, 1997), or by using bootstrapping analysis, in which the rows of X 19 are randomly sampled and PMF is executed on the new dataset (as described 20 by Reff et al., 2007). Both of these methods were used and the four factor 21 solution at fPeak =-0.75 was found to be robust: 100 values for the initial 22 seed parameter in the PMF2 program resulted in 90 of the cases giving the 23 solution presented here, while 100 iterations of the bootstrapping analysis 24 S1