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Adverse health outcomes related to exposure to air pollution have gained much attention in recent years, with a particular emphasis on traffic-related pollutants near roadways, where concentrations tend to be most severe. As such, many projects around the world are being initiated to routinely monitor pollution near major roads. Understanding the extent to which local on-road traffic directly affects these measurements, however, is a challenging problem, and a more thorough comprehension of it is necessary to properly assess its impact on near-road air quality. In this study, a set of commonly measured air pollutants (black carbon; carbon dioxide; carbon monoxide; fine particulate matter, PM2.5; nitrogen oxides; ozone; and ultrafine particle concentrations) were monitored continuously between 1 June 2015 and 31 March 2017 at six stations in Canada: two near-road and two urban background stations in Toronto, Ontario, and one near-road and one urban background station in Vancouver, British Columbia. Three methods of differentiating between local and background concentrations at near-road locations were tested: (1) differences in average pollutant concentrations between near-road and urban background station pairs, (2) differences in downwind and upwind pollutant averages, and (3) interpolation of rolling minima to infer background concentrations. The last two methods use near-road data only, and were compared with method 1, where an explicit difference was measured, to assess accuracy and robustness. It was found that method 2 produced average local concentrations that were biased high by a factor of between 1.4 and 1.7 when compared with method 1 and was not universally feasible, whereas method 3 produced concentrations that were in good agreement with method 1 for all pollutants except ozone and PM2.5, which are generally secondary and regional in nature. The results of this comparison are intended to aid researchers in the analysis of data procured in future near-road monitoring studies. Lastly, upon determining these local pollutant concentrations as a function of time, their variability with respect to wind speed (WS) and wind direction (WD) was assessed relative to the mean values measured at the specific sites. This normalization allowed generalization across the pollutants and made the values from different sites more comparable. With the exception of ozone and PM2.5, local pollutant concentrations at these near-road locations were enhanced by a factor of 2 relative to their mean in the case of stagnant winds and were shown to be proportional to WS−0.6. Downwind conditions enhanced local concentrations by a factor of ∼2 relative to their mean, while upwind conditions suppressed them by a factor of ∼4. Site-specific factors such as distance from roadway and local meteorology should be taken into consideration when generalizing these factors. The methods used to determine these local concentrations, however, have been shown to be applicable across pollutants and different near-road monitoring environments.

The province of Alberta, Canada, is home to three oil sands regions which, combined, contain the third largest deposit of oil in the world. Of these, the Athabasca oil sands region is the largest. As part of Environment and Climate Change Canada's program in support of the Joint Canada-Alberta Implementation Plan for Oil Sands Monitoring program, concentrations of trace elements in PM2. 5 (particulate matter smaller than 2.5 µm in diameter) were measured through two campaigns that involved different methodologies: a long-term filter campaign and a short-term intensive campaign. In the long-term campaign, 24 h filter samples were collected once every 6 days over a 2-year period (December 2010–November 2012) at three air monitoring stations in the regional municipality of Wood Buffalo. For the intensive campaign (August 2013), hourly measurements were made with an online instrument at one air monitoring station; daily filter samples were also collected. The hourly and 24 h filter data were analyzed individually using positive matrix factorization. Seven emission sources of PM2. 5 trace elements were thereby identified: two types of upgrader emissions, soil, haul road dust, biomass burning, and two sources of mixed origin. The upgrader emissions, soil, and haul road dust sources were identified through both the methodologies and both methodologies identified a mixed source, but these exhibited more differences than similarities. The second upgrader emissions and biomass burning sources were only resolved by the hourly and filter methodologies, respectively. The similarity of the receptor modeling results from the two methodologies provided reassurance as to the identity of the sources. Overall, much of the PM2. 5-related trace elements were found to be anthropogenic, or at least to be aerosolized through anthropogenic activities. These emissions may in part explain the previously reported higher levels of trace elements in snow, water, and biota samples collected near the oil sands operations.

An aerosol time-of-flight mass spectrometer (ATOFMS) was employed to provide real-time single particle mixing state and thereby source information for aerosols impacting the western Mediterranean basin during the ChArMEx-ADRIMED and SAF-MED campaigns in summer 2013. The ATOFMS measurements were made at a ground-based remote site on the northern tip of Corsica. Twenty-seven distinct ATOFMS particle classes were identified and subsequently grouped into eight general categories: EC-rich (elemental carbon), K-rich, Na-rich, amines, OC-rich (organic carbon), V-rich, Fe-rich and Ca-rich particles. Mass concentrations were reconstructed for the ATOFMS particle classes and found to be in good agreement with other co-located quantitative measurements (PM1, black carbon (BC), organic carbon, sulfate mass and ammonium mass). Total ATOFMS reconstructed mass (PM2. 5) accounted for 70–90 % of measured PM10 mass and was comprised of regionally transported fossil fuel (EC-rich) and biomass burning (K-rich) particles. The accumulation of these transported particles was favoured by repeated and extended periods of air mass stagnation over the western Mediterranean during the sampling campaigns. The single particle mass spectra proved to be valuable source markers, allowing the identification of fossil fuel and biomass burning combustion sources, and was therefore highly complementary to quantitative measurements made by Particle into Liquid Sampler ion chromatography (PILS-IC) and an aerosol chemical speciation monitor (ACSM), which have demonstrated that PM1 and PM10 were comprised predominantly of sulfate, ammonium and OC. Good temporal agreement was observed between ATOFMS EC-rich and K-rich particle mass concentrations and combined mass concentrations of BC, sulfate, ammonium and low volatility oxygenated organic aerosol (LV-OOA). This combined information suggests that combustion of fossil fuels and biomass produced primary EC- and OC-containing particles, which then accumulated ammonium, sulfate and alkylamines during regional transport. Three other sources were also identified: local biomass burning, marine and shipping. Local combustion particles (emitted in Corsica) contributed little to PM2. 5 particle number and mass concentrations but were easily distinguished from regional combustion particles. Marine emissions comprised fresh and aged sea salt: the former was detected mostly during a 5-day event during which it accounted for 50–80 % of sea salt aerosol mass, while the latter was detected throughout the sampling period. Dust was not efficiently detected by the ATOFMS, and support measurements showed that it was mainly in the PM2. 5–10 fraction. Shipping particles, identified using markers for heavy fuel oil combustion, were associated with regional emissions and represented only a small fraction of PM2. 5 particle number and mass concentration at the site.

Biomass burning organic aerosol (BBOA) can be emitted from natural forest fires and human activities such as agricultural burning and domestic energy generation. BBOA is strongly associated with atmospheric brown carbon (BrC) that absorbs near-ultraviolet and visible light, resulting in significant impacts on regional visibility degradation and radiative forcing. The mixing state of BBOA can play a critical role in the prediction of aerosol optical properties. In this work, single-particle measurements from a Soot-Particle Aerosol Mass Spectrometer coupled with a light scattering module (LS-SP-AMS) were performed to examine the mixing state of BBOA, refractory black carbon (rBC), and potassium (K, a tracer for biomass burning aerosol) in an air mass influenced by wildfire emissions transported from northern Québec to Toronto, representing aged biomass burning plumes. Cluster analysis of single-particle measurements identified five BBOA-related particle types. rBC accounted for 3–14 wt % of these particle types on average. Only one particle type exhibited a strong ion signal for K+, with mass spectra characterized by low molecular weight organic species. The remaining four particle types were classified based on the apparent molecular weight of the BBOA constituents. Two particle types were associated with low potassium content and significant amounts of high molecular weight (HMW) organic compounds. Our observations indicate non-uniform mixing of particles within a biomass burning plume in terms of molecular weight and illustrate that HMW BBOA can be a key contributor to low-volatility BrC observed in BBOA particles. The average mass absorption efficiency of low-volatility BBOA is about 0.8–1.1 m2 g−1 based on a theoretical closure calculation. Our estimates indicate that low-volatility BBOA contributes ∼ 33–44 % of thermo-processed particle absorption at 405 nm; and almost all of the BBOA absorption was associated with low-volatility organics.

The climatic impacts of black carbon (BC) aerosol, an important absorber of solar radiation in the atmosphere, remain poorly constrained and are intimately related to its particle-scale physical and chemical properties. Using particle-resolved modelling informed by quantitative measurements from a soot-particle aerosol mass spectrometer, we confirm that the mixing state (the distribution of co-emitted aerosol amongst fresh BC-containing particles) at the time of emission significantly affects BC-aerosol optical properties even after a day of atmospheric processing. Both single particle and ensemble aerosol mass spectrometry observations indicate that BC near the point of emission co-exists with hydrocarbon-like organic aerosol (HOA) in two distinct particle types: HOA-rich and BC-rich particles. The average mass fraction of black carbon in HOA-rich and BC-rich particle classes was

An automated identification and integration method has been developed for in-use vehicle emissions under real-world conditions. This technique was applied to high-time-resolution air pollutant measurements of in-use vehicle emissions performed under real-world conditions at a near-road monitoring station in Toronto, Canada, during four seasons, through month-long campaigns in 2013–2014. Based on carbon dioxide measurements, over 100 000 vehicle-related plumes were automatically identified and fuel-based emission factors for nitrogen oxides; carbon monoxide; particle number; black carbon; benzene, toluene, ethylbenzene, and xylenes (BTEX); and methanol were determined for each plume. Thus the automated identification enabled the measurement of an unprecedented number of plumes and pollutants over an extended duration. Emission factors for volatile organic compounds were also measured roadside for the first time using a proton transfer reaction time-of-flight mass spectrometer; this instrument provided the time resolution required for the plume capture technique. Mean emission factors were characteristic of the light-duty gasoline-dominated vehicle fleet present at the measurement site, with mean black carbon and particle number emission factors of 35 mg kg fuel−1 and 7.5 × 1014 # kg fuel−1, respectively. The use of the plume-by-plume analysis enabled isolation of vehicle emissions, and the elucidation of co-emitted pollutants from similar vehicle types, variability of emissions across the fleet, and the relative contribution from heavy emitters. It was found that a small proportion of the fleet (< 25 %) contributed significantly to total fleet emissions: 100, 100, 81, and 77 % for black carbon, carbon monoxide, BTEX, and particle number, respectively. Emission factors of a single pollutant may help classify a vehicle as a high emitter; however, regulatory strategies to more efficiently target multi-pollutant mixtures may be better developed by considering the co-emitted pollutants as well.

Understanding the impact of atmospheric black carbon (BC)-containing particles on human health and radiative forcing requires knowledge of the mixing state of BC, including the characteristics of the materials with which it is internally mixed. In this study, we examine the mixing state of refractory BC (rBC) and other aerosol components in an urban environment (downtown Toronto) utilizing the Aerodyne soot particle aerosol mass spectrometer equipped with a light scattering module (LS-SP-AMS). k-means cluster analysis was used to classify single particle mass spectra into chemically distinct groups. One resultant particle class is dominated by rBC mass spectral signals (C1&plus; to C5&plus;) while the organic signals fall into a few major particle classes identified as hydrocarbon-like organic aerosol (HOA), oxygenated organic aerosol (OOA), and cooking emission organic aerosol (COA). A gradual mixing is observed with small rBC particles only thinly coated by HOA (~ 28% by mass on average), while over 90% of the HOA-rich particles did not contain detectable amounts of rBC. Most of the particles classified into other inorganic and organic particle classes were not significantly associated with rBC. The single particle results also suggest that HOA and COA emitted from anthropogenic sources were likely major contributors to organic-rich particles with vacuum aerodynamic diameter (dva) ranging from ~ 200 to 400 nm. The similar temporal profiles and mass spectral features of the organic classes identified by cluster analysis and the factors from a positive matrix factorization (PMF) analysis of the ensemble aerosol data set validate the interpretation of the PMF results.

Receptor modeling was performed on quadrupole unit mass resolution aerosol mass spectrometer (Q-AMS) sub-micron particulate matter (PM) chemical speciation measurements from Windsor, Ontario, an industrial city situated across the Detroit River from Detroit, Michigan. Aerosol and trace gas measurements were collected on board Environment Canada's Canadian Regional and Urban Investigation System for Environmental Research (CRUISER) mobile laboratory. Positive matrix factorization (PMF) was performed on the AMS full particle-phase mass spectrum (PMFFull MS) encompassing both organic and inorganic components. This approach compared to the more common method of analyzing only the organic mass spectra (PMFOrg MS). PMF of the full mass spectrum revealed that variability in the non-refractory sub-micron aerosol concentration and composition was best explained by six factors: an amine-containing factor (Amine); an ammonium sulfate- and oxygenated organic aerosol-containing factor (Sulfate-OA); an ammonium nitrate- and oxygenated organic aerosol-containing factor (Nitrate-OA); an ammonium chloride-containing factor (Chloride); a hydrocarbon-like organic aerosol (HOA) factor; and a moderately oxygenated organic aerosol factor (OOA). PMF of the organic mass spectrum revealed three factors of similar composition to some of those revealed through PMFFull MS: Amine, HOA and OOA. Including both the inorganic and organic mass proved to be a beneficial approach to analyzing the unit mass resolution AMS data for several reasons. First, it provided a method for potentially calculating more accurate sub-micron PM mass concentrations, particularly when unusual factors are present, in this case the Amine factor. As this method does not rely on a priori knowledge of chemical species, it circumvents the need for any adjustments to the traditional AMS species fragmentation patterns to account for atypical species, and can thus lead to more complete factor profiles. It is expected that this method would be even more useful for HR–ToF–AMS data, due to the ability to understand better the chemical nature of atypical factors from high-resolution mass spectra. Second, utilizing PMF to extract factors containing inorganic species allowed for the determination of the extent of neutralization, which could have implications for aerosol parameterization. Third, subtler differences in organic aerosol components were resolved through the incorporation of inorganic mass into the PMF matrix. The additional temporal features provided by the inorganic aerosol components allowed for the resolution of more types of oxygenated organic aerosol than could be reliably resolved from PMF of organics alone. Comparison of findings from the PMFFull MS and PMFOrg MS methods showed that for the Windsor airshed, the PMFFull MS method enabled additional conclusions to be drawn in terms of aerosol sources and chemical processes. While performing PMFOrg MS can provide important distinctions between types of organic aerosol, it is shown that including inorganic species in the PMF analysis can permit further apportionment of organics for unit mass resolution AMS mass spectra.

A newly developed framework for quantifying aerosol particle diversity and mixing state based on information-theoretic entropy is applied for the first time to single particle mass spectrometry field data. Single particle mass fraction estimates for black carbon, organic aerosol, ammonium, nitrate and sulfate, derived using single particle mass spectrometer, aerosol mass spectrometer and multi-angle absorption photometer measurements are used to calculate single particle species diversity (Di). The average single particle species diversity (Dα) is then related to the species diversity of the bulk population (Dγ) to derive a mixing state index value (χ) at hourly resolution. The mixing state index is a single parameter representation of how internally/externally mixed a particle population is at a given time. The index describes a continuum, with values of 0 and 100% representing fully external and internal mixing, respectively. This framework was applied to data collected as part of the MEGAPOLI winter campaign in Paris, France, 2010. Di values are low (~ 2) for fresh traffic and wood-burning particles that contain high mass fractions of black carbon and organic aerosol but low mass fractions of inorganic ions. Conversely, Di values are higher (~ 4) for aged carbonaceous particles containing similar mass fractions of black carbon, organic aerosol, ammonium, nitrate and sulfate. Aerosol in Paris is estimated to be 59% internally mixed in the size range 150–1067 nm, and mixing state is dependent both upon time of day and air mass origin. Daytime primary emissions associated with vehicular traffic and wood-burning result in low χ values, while enhanced condensation of ammonium nitrate on existing particles at night leads to higher χ values. Advection of particles from continental Europe containing ammonium, nitrate and sulfate leads to increases in Dα, Dγ and χ. The mixing state index represents a useful metric by which to compare and contrast ambient particle mixing state at other locations globally.

Numerous laboratory experiments have been performed in an attempt to mimic atmospheric secondary organic aerosol (SOA) formation. However, it is still unclear how close the aerosol particles generated in laboratory experiments resemble atmospheric SOA with respect to their detailed chemical composition. In this study, we generated SOA in a simulation chamber from the ozonolysis of α-pinene and a biogenic volatile organic compound (BVOC) mixture containing α- and β-pinene, Δ3-carene, and isoprene. The detailed molecular composition of laboratory-generated SOA was compared with that of background ambient aerosol collected at a boreal forest site (Hyytiälä, Finland) and an urban location (Cork, Ireland) using direct infusion nanoelectrospray ultrahigh-resolution mass spectrometry. Kendrick mass defect and van Krevelen approaches were used to identify and compare compound classes and distributions of the detected species. The laboratory-generated SOA contained a distinguishable group of dimers that was not observed in the ambient samples. The presence of dimers was found to be less pronounced in the SOA from the BVOC mixtures when compared to the one component precursor system. The molecular composition of SOA from both the BVOC mixture and α-pinene represented the overall composition of the ambient sample from the boreal forest site reasonably well, with 72.3 ± 2.5% (n = 3) and 69.1 ± 3.0% (n = 3) common ions, respectively. In contrast, large differences were found between the laboratory-generated BVOC samples and the ambient urban sample. To our knowledge this is the first direct comparison of molecular composition of laboratory-generated SOA from BVOC mixtures and ambient samples.

Single-particle mixing state information can be a powerful tool for assessing the relative impact of local and regional sources of ambient particulate matter in urban environments. However, quantitative mixing state data are challenging to obtain using single-particle mass spectrometers. In this study, the quantitative chemical composition of carbonaceous single particles has been determined using an aerosol time-of-flight mass spectrometer (ATOFMS) as part of the MEGAPOLI 2010 winter campaign in Paris, France. Relative peak areas of marker ions for elemental carbon (EC), organic aerosol (OA), ammonium, nitrate, sulfate and potassium were compared with concurrent measurements from an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), a thermal–optical OCEC analyser and a particle into liquid sampler coupled with ion chromatography (PILS-IC). ATOFMS-derived estimated mass concentrations reproduced the variability of these species well (R2 = 0.67–0.78), and 10 discrete mixing states for carbonaceous particles were identified and quantified. The chemical mixing state of HR-ToF-AMS organic aerosol factors, resolved using positive matrix factorisation, was also investigated through comparison with the ATOFMS dataset. The results indicate that hydrocarbon-like OA (HOA) detected in Paris is associated with two EC-rich mixing states which differ in their relative sulfate content, while fresh biomass burning OA (BBOA) is associated with two mixing states which differ significantly in their OA / EC ratios. Aged biomass burning OA (OOA2-BBOA) was found to be significantly internally mixed with nitrate, while secondary, oxidised OA (OOA) was associated with five particle mixing states, each exhibiting different relative secondary inorganic ion content. Externally mixed secondary organic aerosol was not observed. These findings demonstrate the range of primary and secondary organic aerosol mixing states in Paris. Examination of the temporal behaviour and chemical composition of the ATOFMS classes also enabled estimation of the relative contribution of transported emissions of each chemical species and total particle mass in the size range investigated. Only 22% of the total ATOFMS-derived particle mass was apportioned to fresh, local emissions, with 78% apportioned to regional/continental-scale emissions.

Ambient wintertime background urban aerosol in Cork city, Ireland, was characterized using aerosol mass spectrometry. During the three-week measurement study in 2009, 93% of the ca. 1 350 000 single particles characterized by an Aerosol Time-of-Flight Mass Spectrometer (TSI ATOFMS) were classified into five organic-rich particle types, internally mixed to different proportions with elemental carbon (EC), sulphate and nitrate, while the remaining 7% was predominantly inorganic in nature. Non-refractory PM1 aerosol was characterized using a High Resolution Time-of-Flight Aerosol Mass Spectrometer (Aerodyne HR-ToF-AMS) and was also found to comprise organic aerosol as the most abundant species (62%), followed by nitrate (15%), sulphate (9%) and ammonium (9%), and chloride (5%). Positive matrix factorization (PMF) was applied to the HR-ToF-AMS organic matrix, and a five-factor solution was found to describe the variance in the data well. Specifically, "hydrocarbon-like" organic aerosol (HOA) comprised 20% of the mass, "low-volatility" oxygenated organic aerosol (LV-OOA) comprised 18%, "biomass burning" organic aerosol (BBOA) comprised 23%, non-wood solid-fuel combustion "peat and coal" organic aerosol (PCOA) comprised 21%, and finally a species type characterized by primary extit{m/z}~peaks at 41 and 55, similar to previously reported "cooking" organic aerosol (COA), but possessing different diurnal variations to what would be expected for cooking activities, contributed 18%. Correlations between the different particle types obtained by the two aerosol mass spectrometers are also discussed. Despite wood, coal and peat being minor fuel types used for domestic space heating in urban areas, their relatively low combustion efficiencies result in a significant contribution to PM1 aerosol mass (44% and 28% of the total organic aerosol mass and non-refractory total PM1, respectively).

An Aerosol Time-Of-Flight Mass Spectrometer (ATOFMS) was deployed to investigate the size-resolved chemical composition of single particles at an urban background site in Paris, France, as part of the MEGAPOLI winter campaign in January/February 2010. ATOFMS particle counts were scaled to match coincident Twin Differential Mobility Particle Sizer (TDMPS) data in order to generate hourly size-resolved mass concentrations for the single particle classes observed. The total scaled ATOFMS particle mass concentration in the size range 150–1067 nm was found to agree very well with the sum of concurrent High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and Multi-Angle Absorption Photometer (MAAP) mass concentration measurements of organic carbon (OC), inorganic ions and black carbon (BC) (R2 = 0.91). Clustering analysis of the ATOFMS single particle mass spectra allowed the separation of elemental carbon (EC) particles into four classes: (i) EC attributed to biomass burning (ECbiomass), (ii) EC attributed to traffic (ECtraffic), (iii) EC internally mixed with OC and ammonium sulfate (ECOCSOx), and (iv) EC internally mixed with OC and ammonium nitrate (ECOCNOx). Average hourly mass concentrations for EC-containing particles detected by the ATOFMS were found to agree reasonably well with semi-continuous quantitative thermal/optical EC and optical BC measurements (r2 = 0.61 and 0.65–0.68 respectively, n = 552). The EC particle mass assigned to fossil fuel and biomass burning sources also agreed reasonably well with BC mass fractions assigned to the same sources using seven-wavelength aethalometer data (r2 = 0.60 and 0.48, respectively, n = 568). Agreement between the ATOFMS and other instrumentation improved noticeably when a period influenced by significantly aged, internally mixed EC particles was removed from the intercomparison. 88% and 12% of EC particle mass was apportioned to fossil fuel and biomass burning respectively using the ATOFMS data compared with 85% and 15% respectively for BC estimated from the aethalometer model. On average, the mass size distribution for EC particles is bimodal; the smaller mode is attributed to locally emitted, mostly externally mixed EC particles, while the larger mode is dominated by aged, internally mixed ECOCNOx particles associated with continental transport events. Periods of continental influence were identified using the Lagrangian Particle Dispersion Model (LPDM) "FLEXPART". A consistent minimum between the two EC mass size modes was observed at approximately 400 nm for the measurement period. EC particles below this size are attributed to local emissions using chemical mixing state information and contribute 79% of the scaled ATOFMS EC particle mass, while particles above this size are attributed to continental transport events and contribute 21% of the EC particle mass. These results clearly demonstrate the potential benefit of monitoring size-resolved mass concentrations for the separation of local and continental EC emissions. Knowledge of the relative input of these emissions is essential for assessing the effectiveness of local abatement strategies.

An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed for the measurement of the size resolved chemical composition of single particles at a site in Cork Harbour, Ireland for three weeks in August 2008. The ATOFMS was co-located with a suite of semi-continuous instrumentation for the measurement of particle number, elemental carbon (EC), organic carbon (OC), sulfate and particulate matter smaller than 2.5 μm in diameter (PM2.5). The temporality of the ambient ATOFMS particle classes was subsequently used in conjunction with the semi-continuous measurements to apportion PM2.5 mass using positive matrix factorisation. The synergy of the single particle classification procedure and positive matrix factorisation allowed for the identification of six factors, corresponding to vehicular traffic, marine, long-range transport, various combustion, domestic solid fuel combustion and shipping traffic with estimated contributions to the measured PM2.5 mass of 23%, 14%, 13%, 11%, 5% and 1.5% respectively. Shipping traffic was found to contribute 18% of the measured particle number (20–600 nm mobility diameter), and thus may have important implications for human health considering the size and composition of ship exhaust particles. The positive matrix factorisation procedure enabled a more refined interpretation of the single particle results by providing source contributions to PM2.5 mass, while the single particle data enabled the identification of additional factors not possible with typical semi-continuous measurements, including local shipping traffic.

A new denuder-filter sampling technique has been used to investigate the gas/particle partitioning behaviour of the carbonyl products from the photooxidation of isoprene and 1,3,5-trimethylbenzene. A series of experiments was performed in two atmospheric simulation chambers at atmospheric pressure and ambient temperature in the presence of NOx and at a relative humidity of approximately 50%. The denuder and filter were both coated with the derivatizing agent O-(2,3,4,5,6-pentafluorobenzyl)-hydroxylamine (PFBHA) to enable the efficient collection of gas- and particle-phase carbonyls respectively. The tubes and filters were extracted and carbonyls identified as their oxime derivatives by GC-MS. The carbonyl products identified in the experiments accounted for around 5% and 10% of the mass of secondary organic aerosol formed from the photooxidation of isoprene and 1,3,5-trimethylbenzene respectively. Experimental gas/particle partitioning coefficients were determined for a wide range of carbonyl products formed from the photooxidation of isoprene and 1,3,5-trimethylbenzene and compared with the theoretical values based on standard absorptive partitioning theory. Photooxidation products with a single carbonyl moiety were not observed in the particle phase, but dicarbonyls, and in particular, glyoxal and methylglyoxal, exhibited gas/particle partitioning coefficients several orders of magnitude higher than expected theoretically. These findings support the importance of heterogeneous and particle-phase chemical reactions for SOA formation and growth during the atmospheric degradation of anthropogenic and biogenic hydrocarbons.

No abstract available.