[1] Isoprene, monoterpenes, b-caryophyllene, and toluene are known to be important secondary organic aerosol (SOA) precursors. In this study, characteristic SOA tracers of these precursors were quantified in ambient samples of PM 2.5 taken in Hong Kong and their contributions to SOA were estimated using a tracer-based method. Samples were collected every other day from four sampling sites during a field measurement campaign in the summer of 2006. Fourteen SOA tracers, along with 24 other polar oxygenated compounds, were identified and quantified using gas chromatography/ion trap mass spectrometry with prior trimethylsilylation. Concentrations of the individual tracers ranged from a few tenths to a few hundreds ng m À3 . The tracer concentrations were found to be 1 order of magnitude higher on days under regional transport influences due to elevated oxidant levels than on days under mainly local emissions influences. Using the measured SOA tracer concentrations in the ambient aerosols and laboratory-derived tracer mass fractions reported by Kleindienst et al. (2007), we estimated that the average SOA attributable to isoprene, monoterpenes, b-caryophyllene, and toluene was 8.83 mg m À3 on days under regional transport influences versus 0.99 mg m À3 on days under mainly local emissions influences, accounting for approximately 49% and 21%, respectively, of the ambient OC concentrations. The tracer-based estimates indicate that monoterpenes and b-caryophyllene are significant contributors to ambient PM 2.5 in the summer, which may be due to the high emissions of these biogenic hydrocarbons in Hong Kong.

[1] The major inorganic constituents and organic tracer compounds in PM 2.5 were used in positive matrix factorization (PMF) and chemical mass balance (CMB) models to apportion the primary and secondary source contributions to organic carbon (OC) in Hong Kong during the summer of 2006. Secondary organic aerosol (SOA) tracers of several biogenic and anthropogenic hydrocarbons were included in the PMF analysis. Their inclusion allowed the identification of two components of SOA among seven factors resolved by PMF. One SOA component was mainly associated with secondary sulfate and nitrate. The other SOA component, characterized by biogenic SOA tracers and mixed with biomass burning and vegetative detritus particles, was biomass burning-induced SOA. Secondary OC (SOC) apportioned by PMF (SOC PMF ) was on average 6.84 mgC m −3 (65% of PM 2.5 OC) on high pollution days under influence of significant regional transport (i.e., regional days) and 0.70 mgC m −3 (25% of PM 2.5 OC) on days under the influence of mainly local emissions (i.e., local days). The biomass burning-induced SOA accounted for 20% of the total SOA on the regional days, underlining the importance of biomass burning aerosol source in this region. The average uncertainty for the SOC PMF estimates was ∼20% on the regional days and ∼120% on the local days. SOC PMF was compared with SOC determined by CMB (SOC CMB , i.e., unapportioned OC by CMB analysis) and a tracer-based method (SOC TBM ) that apportioned SOC contributions by four hydrocarbon precursors including isoprene, monoterpenes, b-caryophyllene, and toluene. The three estimates of SOC closely tracked with each other among individual samples. The SOC CMB and SOC PMF estimates on the majority of the regional days differed from each other by less than 25%. Good correlations between contributions of SOC and individual primary OC sources apportioned by PMF and CMB further added to the credence to the PMF-derived estimation of secondary and primary OC source contributions by using secondary and primary aerosol organic tracers as the fitting species.Citation: Hu, D., Q. Bian, A. K. H. Lau, and J. Z. Yu (2010), Source apportioning of primary and secondary organic carbon in summer PM 2.5 in Hong Kong using positive matrix factorization of secondary and primary organic tracer data,

PM 2.5 filter sampling was conducted on a daily basis at the HKUST Air Quality Research Supersite (AQRS) for one year from March 2011 to February 2012. Approximately one fifth of the filter samples were subjected to full chemical analysis including major ions, elements, organic carbon (OC), elemental carbon (EC), and non-polar organic compounds (NPOCs). The major ions (sulfate, nitrate, and ammonium) were compared with those measured online by a MARGA system and the two sets of data were found in agreement within 25% or better. The major PM 2.5 components (crustal materials, organic matter, soot, ammonium sulfate, ammonium nitrate, and non-crustal trace elements) accounted for 90% of the measured mass with sulfate being the most abundant (32.0%), followed by organic matter (23.5%) and ammonium (11.8%). The monthly variation patterns for different components suggested variable regional/super-regional sources, reflecting variation of transport contribution caused by shifts in synoptic weather conditions.Receptor modeling analysis by Positive Matrix Factorization revealed that secondary sulfate formation process (annual average of 31%), biomass burning (23%), and secondary nitrate formation process (13%) were the three dominant contributing sources to the observed PM 2.5 at HKUST AQRS throughout the sampling year. The PM 2.5 mass concentrations of all the individual sampling days were within the recently-proposed AQOs standards by the Hong Kong government (35 µg/m 3 for annual average and 75 µg/m 3 for 24-hr average) while approx. 52% of the sampling days were recorded with PM 2.5 concentrations exceeding the WHO health 24-hr standards of 25 µg/m 3 . Major composition and source analysis showed that the increased mass concentrations on high PM days were mainly caused by air pollutant transport from the outside-Hong Kong regions. Results from this study indicate the importance of regional/super-regional strategies such as reduction in SO 2 , NO 2 (precursors for secondary inorganic aerosols) and restricting biomass burning for lowering PM 2.5 in Hong Kong.

Biomass burning emits particles (black carbon and primary organic aerosol) and precursor vapors to the atmosphere that chemically and physically age in the atmosphere. This theoretical study explores the relationships between fire size (determining the initial plume width and concentration), dilution rate, and entrainment of background aerosol on particle coagulation, organic aerosol (OA) evaporation, and secondary organic aerosol (SOA) condensation in smoke plumes. We examine the impacts of these processes on aged smoke OA mass, geometric mean diameter (Dg), peak lognormal modal width (σg), particle extinction (E), and cloud condensation nuclei (CCN) concentrations. In our simulations, aging OA mass is controlled by competition between OA evaporation and SOA condensation. Large, slowly diluting plumes evaporate little in our base set of simulations, which may allow for net increases in mass, E, CCN , and Dg from SOA condensation. Smaller, quickly diluting fire plumes lead to faster evaporation, which favors decreases in mass, E, CCN, and Dg. However, the SOA fraction of the smoke OA increases more rapidly in smaller fires due to faster primary organic aerosol evaporation leading to more SOA precursors. Net mass changes for smaller fires depend on background OA concentrations; increasing background aerosol concentrations decrease evaporation rates. Although coagulation does not change mass, it can decrease the number of particles in large/slowly diluting plumes, increasing Dg and E, and decreasing σg. While our conclusions are limited by being a theoretical study, we hope they help motivate future smoke‐plume analyses to consider the effects of fire size, meteorology, and background OA concentrations.

Abstract. Secondary organic aerosol (SOA) has been shown to form in biomass-burning emissions in laboratory and field studies. However, there is significant variability among studies in mass enhancement, which could be due to differences in fuels, fire conditions, dilution, and/or limitations of laboratory experiments and observations. This study focuses on understanding processes affecting biomass-burning SOA formation in laboratory smog-chamber experiments and in ambient plumes. Vapor wall losses have been demonstrated to be an important factor that can suppress SOA formation in laboratory studies of traditional SOA precursors; however, impacts of vapor wall losses on biomass-burning SOA have not yet been investigated. We use an aerosol-microphysical model that includes representations of volatility and oxidation chemistry to estimate the influence of vapor wall loss on SOA formation observed in the FLAME III smog-chamber studies. Our simulations with base-case assumptions for chemistry and wall loss predict a mean OA mass enhancement (the ratio of final to initial OA mass, corrected for particle-phase wall losses) of 1.8 across all experiments when vapor wall losses are modeled, roughly matching the mean observed enhancement during FLAME III. The mean OA enhancement increases to over 3 when vapor wall losses are turned off, implying that vapor wall losses reduce the apparent SOA formation. We find that this decrease in the apparent SOA formation due to vapor wall losses is robust across the ranges of uncertainties in the key model assumptions for wall-loss and mass-transfer coefficients and chemical mechanisms.We then apply similar assumptions regarding SOA formation chemistry and physics to smoke emitted into the atmosphere. In ambient plumes, the plume dilution rate impacts the organic partitioning between the gas and particle phases, which may impact the potential for SOA to form as well as the rate of SOA formation. We add Gaussian dispersion to our aerosol-microphysical model to estimate how SOA formation may vary under different ambient-plume conditions (e.g., fire size, emission mass flux, atmospheric stability). Smoke from small fires, such as typical prescribed burns, dilutes rapidly, which drives evaporation of organic vapor from the particle phase, leading to more effective SOA formation. Emissions from large fires, such as intense wildfires, dilute slowly, suppressing OA evaporation and subsequent SOA formation in the near field. We also demonstrate that different approaches to the calculation of OA enhancement in ambient plumes can lead to different conclusions regarding SOA formation. OA mass enhancement ratios of around 1 calculated using an inert tracer, such as black carbon or CO, have traditionally been interpreted as exhibiting little or no SOA formation; however, we show that SOA formation may have greatly contributed to the mass in these plumes.In comparison of laboratory and plume results, the possible inconsistency of OA enhancement between them could be in part attributed to the effect of chamber walls and plume dilution. Our results highlight that laboratory and field experiments that focus on the fuel and fire conditions also need to consider the effects of plume dilution or vapor losses to walls.

Abstract. Smog chambers are extensively used to study processes that drive gas and particle evolution in the atmosphere. A limitation of these experiments is that particles and gas-phase species may be lost to chamber walls on shorter timescales than the timescales of the atmospheric processes being studied in the chamber experiments. These particle and vapor wall losses have been investigated in recent studies of secondary organic aerosol (SOA) formation, but they have not been systematically investigated in experiments of primary emissions from combustion. The semi-volatile nature of combustion emissions (e.g. from wood smoke) may complicate the behavior of particle and vapor wall deposition in the chamber over the course of the experiments due to the competition between gas/particle and gas/wall partitioning. Losses of vapors to the walls may impact particle evaporation in these experiments, and potential precursors for SOA formation from combustion may be lost to the walls, causing underestimations of aerosol yields. Here, we conduct simulations to determine how particle and gas-phase wall losses contributed to the observed evolution of the aerosol during experiments in the third Fire Lab At Missoula Experiment (FLAME III). We use the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithm coupled with the organic volatility basis set (VBS) and wall-loss formulations to examine the predicted extent of particle and vapor wall losses. We limit the scope of our study to the dark periods in the chamber before photo-oxidation to simplify the aerosol system for this initial study. Our model simulations suggest that over one-third of the initial particle-phase organic mass (41 %) was lost during the experiments, and over half of this particle-organic mass loss was from direct particle wall loss (65 % of the loss) with the remainder from evaporation of the particles driven by vapor losses to the walls (35 % of the loss). We perform a series of sensitivity tests to understand uncertainties in our simulations. Uncertainty in the initial wood-smoke volatility distribution contributes 18 % uncertainty to the final particle-organic mass remaining in the chamber (relative to base-assumption simulation). We show that the total mass loss may depend on the effective saturation concentration of vapor with respect to the walls as these values currently vary widely in the literature. The details of smoke dilution during the filling of smog chambers may influence the mass loss to the walls, and a dilution of ~ 25:1 during the experiments increased particle-organic mass loss by 33 % compared to a simulation where we assume the particles and vapors are initially in equilibrium in the chamber. Finally, we discuss how our findings may influence interpretations of emission factors and SOA production in wood-smoke smog-chamber experiments.

<p><strong>Abstract.</strong> Secondary organic aerosol (SOA) has been shown to form in biomass-burning emissions in laboratory and field studies. However, there is significant variability among studies in mass enhancement, which could be due to differences in fuels, fire conditions, dilution, and/or limitations of laboratory experiments and observations. This study focuses on understanding processes affecting biomass-burning SOA formation in laboratory smog-chamber experiments and in ambient plumes. Vapor wall losses have been demonstrated to be an important factor that can suppress SOA formation in laboratory studies of traditional SOA precursors; however, impacts of vapor wall losses on biomass-burning SOA have not yet been investigated. We use an aerosol microphysics model that includes representations of volatility and oxidation chemistry to estimate the influence of vapor wall loss on SOA formation observed in the FLAME-III smog-chamber studies. Our simulations with base-case assumptions for chemistry and wall loss predict a mean OA mass enhancement (the ratio of final to initial OA mass, corrected for particle-phase wall losses) of 1.8 across all experiments when vapor wall losses are modeled, roughly matching the mean observed enhancement during FLAME-III. The mean OA enhancement increases to over 3 when vapor wall losses are turned off, implying that vapor wall losses reduce the apparent SOA formation. We find that this decrease in the apparent SOA formation due to vapor wall losses is robust across the ranges of uncertainties in the key model assumptions for wall-loss and mass-transfer coefficients and chemical mechanisms.<br><br> We then apply similar assumptions regarding SOA formation chemistry and physics to smoke emitted into the atmosphere. In ambient plumes, the plume dilution rate impacts the organic partitioning between the gas and particle phases, which may impact the potential for SOA to form as well as the rate of SOA formation. We add Gaussian dispersion to our aerosol microphysical model to estimate how SOA formation may vary under different ambient-plume conditions (e.g. fire size, emission mass flux, atmospheric stability). Smoke from small fires, such as typical prescribed burns, dilutes rapidly, which drives evaporation of organic vapor from the particle phase, leading to more effective SOA formation. Emissions from large fires, such as intense wildfires, dilute slowly, suppressing OA evaporation and subsequent SOA formation in the near field. We also demonstrate that different approaches to the calculation of OA enhancement in ambient plumes can lead to different conclusions regarding SOA formation. OA mass enhancement ratios of around 1 calculated using an inert tracer, such as BC or CO, have traditionally been interpreted as exhibiting little or no SOA formation; however, we show that SOA formation may have greatly contributed to the mass in these plumes.<br><br> In comparison of laboratory and plume results, the possible inconsistency of OA enhancement between them could be in part attributed to the effect of chamber walls and plume dilution. Our results highlight that laboratory and field experiments that focus on the fuel and fire conditions also need to consider the effects of plume dilution or vapor losses to walls.</p>

Oxalic acid is one of the most abundant dicarboxylic acids in the atmosphere, receiving a great deal of attention due to its potential influence on cloud condensation nucleus activities. In this work, we report 10 months of hourly oxalate measurements in particulate matter of less than 2.5 μm in aerodynamic diameter (PM 2.5 ) by a Monitor for Aerosols and Gases in ambient Air at a suburban coastal site in Hong Kong from April 2012 to February 2013. A total of more than 6000 sets of oxalate and inorganic ion data were obtained. The mean (±SD) oxalate concentration was 0.34 (±0.18) μg m À3 , accounting for 2.8% of the total ion mass and 1.5% of the PM 2.5 mass. Seasonal variation showed higher concentrations in fall and winter (0.54 and 0.36 μg m À3 , respectively) and lower concentrations in spring and summer (~0.26 μg m À3 ). Different from the inorganic ions, a shallow dip in the oxalate concentration consistently occurred in the morning after sunrise (around 9:00 A.M.) throughout all seasons. Our analysis suggests that this was likely due to photolysis of oxalate-Fe (III) complex under sunlight. In summer, a small daytime peak was discernable for oxalate and nitrate. This characteristic, together with a more evident diurnal variation of O 3 , indicates comparatively more active photochemical oxidation in summer than other seasons. High correlations were observed between oxalate and non-sea-salt SO 4 2À (NSS) (R 2 = 0.63) and O x (O 3 + NO 2 ) (R 2 = 0.48), indicating significant commonality in their secondary formation. Positive matrix factorization analysis of oxalate and other real-time gas and particle-phase component data estimates that secondary formation processes, including secondary gas or aqueous oxidation processes (49%), oxidation processes of biomass burning emissions (37%), accounted for the majority of PM 2.5 oxalate. A backward trajectories cluster analysis found that higher oxalate/NSS ratios were associated with low pollution samples under the influence of marine air masses while the ratios were lower in high pollution samples that were typically associated with continental air masses passing through areas of high anthropogenic emissions. Isolating the "low pollution marine" aerosols across the entire data set indicates that oxalate production increased in the summer compared to other seasons, suggesting either more active marine emissions of oxalate precursors or stronger photochemical processes in the summer.