Air pollution poses significant risks to human health and the environment, necessitating comprehensive monitoring and analysis to identify and mitigate the presence of harmful pollutants. This study focuses on Hamilton and Sarnia, Ontario, Canada, known for their industrial activities and associated air pollution challenges. Employing gas chromatography coupled with ion mobility spectrometry and high-resolution mass spectrometry (GC-IMS-MS) on samples collected by polyurethane foam passive samplers, we aimed to uncover the presence of halogenated airborne organic pollutants, including those not typically monitored in standard air quality assessments. Our research successfully identified 19 groups of halogenated pollutants in the air samples. These include a range of chlorinated and brominated anisoles, as well as a previously undocumented polyfluoroalkyl substance (PFAS) that was confirmed with a synthesized standard. Polychlorinated biphenyls (PCBs), chlorinated organophosphate esters (OPEs) and various agricultural contaminants were also tentatively identified based on mass spectral interpretation. The study revealed significant differences in the pollutant profiles between the two cities, reflecting their distinct industrial influences. The application of non-target screening techniques also highlighted the complex nature of air pollution and the necessity for broader monitoring strategies to protect public health and the environment.

The Michigan–Ontario Ozone Source Experiment (MOOSE) is an international air quality field study that took place at the US–Canada Border region in the ozone seasons of 2021 and 2022. MOOSE addressed binational air quality issues stemming from lake breeze phenomena and transboundary transport, as well as local emissions in southeast Michigan and southern Ontario. State-of-the-art scientific techniques applied during MOOSE included the use of multiple advanced mobile laboratories equipped with real-time instrumentation; high-resolution meteorological and air quality models at regional, urban, and neighborhood scales; daily real-time meteorological and air quality forecasts; ground-based and airborne remote sensing; instrumented Unmanned Aerial Vehicles (UAVs); isotopic measurements of reactive nitrogen species; chemical fingerprinting; and fine-scale inverse modeling of emission sources. Major results include characterization of southeast Michigan as VOC-limited for local ozone formation; discovery of significant and unaccounted formaldehyde emissions from industrial sources; quantification of methane emissions from landfills and leaking natural gas pipelines; evaluation of solvent emission impacts on local and regional ozone; characterization of the sources of reactive nitrogen and PM2.5; and improvements to modeling practices for meteorological, receptor, and chemical transport models.

Industrial emissions of trace gases and VOCs can be an important contributor to air quality in cities. Disentangling different point sources from each other and characterizing their emissions can be particularly challenging in dense industrial areas, such as Detroit, Dearborn and surrounding areas in Southeast Michigan (SEMI). Here, we leverage mobile measurements of trace gases and speciated volatile organic compounds (VOCs) to identify emitting sites. We characterize their complicated emissions fingerprints based on a core set of chemical ratios. We report chemical ratios for 7 source types including automakers, steel manufacturers, chemical refineries, industrial chemical use (cleaning; coatings; etc.), chemical waste sites, compressor stations, and more. The source dataset includes visits to over 85 distinct point sources. As expected, we find similarities between the different types of facilities, but observe variability between them and even at individual facilities day-to-day. Certain larger sites are better thought of as a collection of individual point sources. These results demonstrate the power of mobile laboratories over stationary sampling in dense industrial areas.

Ambient fine particulate matter (PM2.5) data were collected in the lower City of Hamilton, Ontario to apportion the sources of this pollutant over an 18-month period. Hamilton has complex topographical features that may result in worsened air pollution within the lower city, thus, dispersion-normalized, multi-time resolution factor analysis (DN-MT-FA) was used to identify and quantify contributions of factors in a manner that reduced the influence of local meteorology. These factors were secondary organic aerosols type 1 (SOA_1), particulate nitrate (pNO3), particulate sulphate (pSO4), primary traffic organic matter (PTOM), Steel/metal processing and vehicular road dust emissions (Steel & Mobile) and, secondary organic aerosols type 2 (SOA_2) with origins ranging from mainly regional to mainly local. Factors that were mainly local (PTOM, Steel & Mobile, SOA_2) contributed up to 17% of the average PM2.5 mass while mixed local/regional factors (pNO3, pSO4) made up 43% on average, indicating the potential for further reduction of harmful PM concentrations locally. Of particular interest from a health protection perspective, was the composition of PM2.5 on days when an exceedance of the 24-hr WHO air quality guideline for this pollutant was observed. In general, SOA_1 was found to drive summer exceedances while pNO3 dominated in the winter. During the summer period, SOA_1 was attributable to wildfires in the northern parts of Canada while local traffic sources in winter contributed to the high levels of pNO3. While local, industrial factors only had minor relative mass contributions during exceedances, they are high in highly oxidized organic species (SOA_2) and toxic metals (Steel & Mobile). Thus, they are likely to have more impacts on human health. The methods and results described in this work will be useful in understanding prevalent sources of particulate matter pollution in the ambient air in the presence of complex topography and meteorological effects.

Traffic-related air pollutants (TRAP) including nitric oxide (NO), nitrogen oxide (NOx), carbon monoxide (CO), ultrafine particles (UFP), black carbon (BC), and fine particulate matter (PM2.5) were simultaneously measured at near-road sites located at 10 m (NR10) and 150 m (NR150) from the same side of a busy highway to provide insights into the influence of winter time meteorology on exposure to TRAP near major roads. The spatial variabilities of TRAP were examined for ambient temperatures ranging from -11 °C to +19 °C under downwind, upwind, and stagnant air conditions. The downwind TRAP concentrations at NR10 were higher than the upwind concentrations by a factor of 1.4 for CO to 13 for NO. Despite steep downwind reductions of 38 % to 75 % within 150 m, the downwind concentrations at NR150 were still well above upwind concentrations. Near-road concentrations of NOx and UFP increased as ambient temperatures decreased due to elevated emissions of NOx and UFP from vehicles under colder temperatures. Traffic-related PM2.5 sources were identified using hourly PM2.5 chemical components including organic/inorganic aerosol and trace metals at both sites. The downwind concentrations of primary PM2.5 species related to tailpipe and non-tailpipe emissions at NR10 were substantially higher than the upwind concentrations by a factor of 4 and 32, respectively. Traffic-related PM2.5 sources accounted for almost half of total PM2.5 mass under downwind conditions, leading to a rapid change of PM2.5 chemical composition. Under stagnant air conditions, the concentrations of most TRAP and related PM2.5 including tailpipe emissions, secondary nitrate, and organic aerosol were comparable to, or even greater than, the downwind concentrations under windy conditions, especially at NR150. This study demonstrates that stagnant air conditions further widen the traffic-influenced area and people living near major roadways may experience increased risks from elevated exposure to traffic emissions during cold and stagnant winter conditions.

Industrial emissions of volatile organic compounds (VOCs) directly impact air quality downwind of facilities and contribute to regional ozone and secondary organic aerosol production. Positive matrix factorization (PMF) is often used to apportion VOCs to their respective sources using measurement data collected at fixed sites, for example air quality monitoring stations. Here, we apply PMF analysis to high time-resolution VOC measurement data collected both while stationary and while moving using a mobile monitoring platform. The stationary monitoring periods facilitated the extraction of representative industrial VOC source profiles while the mobile monitoring periods were critical for the spatial identification of VOC hotspots. Data were collected over five days in a heavily industrialized region of southwestern Ontario containing several refineries, petrochemical production facilities and a chemical waste disposal facility. Factors associated with petroleum, chemical waste and rubber production were identified and ambient mixing ratios of selected aromatic, unsaturated and oxygenated VOCs were apportioned to local and background sources. Fugitive emissions of benzene, highly localized and predominantly associated with storage, were found to be the dominant local contributor to ambient benzene mixing ratios measured while mobile. Toluene and substituted aromatics were predominantly associated with refining and traffic, while methyl ethyl ketone was linked to chemical waste handling. The approach described here facilitates the apportionment of VOCs to their respective local industrial sources at high spatial and temporal resolution. This information can be used to identify problematic source locations and to inform VOC emission abatement strategies.

Passive samplers have proven to be effective for continuous monitoring of volatile organic compounds (VOCs) in ambient air in remote, urban and industrial environments. Thermal desorption tubes fitted with endcaps that facilitate passive uptake through diffusion are now routinely used for monitoring fugitive benzene emissions from refineries and petrochemical facilities across North America (EPA Method 325A/B). However, deployment periods of 14 days are typically employed to minimize the risk of poor retention, requiring 26 deployments per year to return an annual average concentration for comparison with chronic exposure health-based standards. Here, we explore extending the deployment duration of these passive samplers to one, two and three months by limiting VOC uptake rates using an alternative diffusive endcap featuring a smaller cross-sectional area. Field testing was performed beside a major highway during two separate three-month campaigns. Uptake rates for benzene, toluene, ethylbenzene and xylenes (BTEX) were observed to remain linear for deployments of up to three months when using the low-uptake endcaps. Application of the low-uptake endcaps and the uptake rates determined here will enable annual average concentrations of BTEX to be calculated using only four tube deployments per year. The cost savings associated with this decreased deployment frequency will facilitate increased spatial resolution during future exposure assessment studies. The stability of selected air toxics within the tubes was also assessed and the results suggest that while aromatic VOCs are stable for storage times of at least 70 days, chloroform and trichloroethylene begin to degrade within two weeks of sampling.

Ambient fine particulate matter (PM2.5) data of similar continuously monitored species at two air monitoring sites with different characteristics within the City of Toronto were used to gauge the intra-city variations in the PM composition over a largely concurrent period spanning two years. One location was <8 m from the side of a major highway while the other was an urban background location. For the first time, multi-time resolution factor analysis was applied to dispersion-normalized concentrations to identify and quantify source contributions while reducing the influence of local meteorology. These factors were particulate sulphate (pSO(4)), particulate nitrate (pNO(3)), secondary organic aerosols (SOA), crustal matter (CrM) that were common to both sites, a hydrocarbon-like organic matter (HOM) exclusive to the urban background site, three black carbon related factors (BC, BC-HOM at the highway site, and a brown carbon rich factor (BC-BrC) at the urban background site), biomass burning organic matter (BBOM) and brake dust (BD) factors exclusive to the highway site. The PM2.5 composition was different between these two locations, over only a 10 km distance. The sum of SOA, pSO(4) and pNO(3) at the urban background site averaged 57% of the PM2.5 mass while the same species represented 43% of the average PM2.5 mass at the highway site. Local or site-specific factors may be of greater interest for control policy design. Thus, regression analyses with potential explanatory, site-specific variables were performed for results from the highway site. Three model approaches were explored: multiple linear regression (MLR), regression with a generalized reduced gradient (GRG) algorithm, and a generalized additive model (GAM). GAM gave the largest fraction of variance for the locally-found factors at the highway site. Heavy-duty vehicles were most important for explaining the black carbon (BC and BC-HOM) factors. Light-duty vehicles were dominant for the brake dust (BD) factor. The auxiliary modelling for the local factors showed that the traffic-related factors likely originated along the main roadways at their respective sites while the more regional factors, - pSO(4), pNO(3), SOA, - had sources that were both regional and local in origin and with contributions that varied seasonally. These results will be useful in understanding ambient particulate matter sources on a city scale that will support air quality management planning Crown Copyright (C) 2020 Published by Elsevier B.V. All rights reserved.

Road traffic emissions are an increasingly important source of particulate matter in urban and non-road environments, where non-tailpipe emissions can contribute substantially to elevated levels of metals associated with adverse health effects. Thus, better characterization and quantification of traffic-emitted metals is warranted. In this study, real-world emission factors for fine particulate metals were determined from hourly x-ray fluorescence measurements over a three-year period (2015–2018) at an urban roadway and busy highway. Inter-site differences and temporal trends in real-world emission factors for metals were explored. The emission factors at both sites were within the range of past studies, and it was found that Ti, Fe, Cu, and Ba emissions were 2.2–3.0 times higher at the highway site, consistent with the higher proportion of heavy-duty vehicles. Weekday emission factors for some metals were also higher by 2.0–3.5 times relative to Sundays for Mn, Zn, Ca, and Fe, illustrating a dependence on fleet composition and roadway activity. Metal emission factors were also inversely related to relative humidity and precipitation, due to reduced road dust resuspension under wetter conditions. Correlation analysis revealed groups of metals that were co-emitted by different traffic activities and sources. Determining emission factors enabled the isolation of traffic-related metal emissions and also revealed that human exposure to metals in ambient air can vary substantially both temporally and spatially depending on fleet composition and traffic volume.

Industrial metalworking facilities emit a variety of air toxics including volatile organic compounds, polycyclic aromatic hydrocarbons (PAHs) and heavy metals. In order to investigate these emissions, a 1-month multi-instrument field campaign was undertaken at an industrial site in Grande-Synthe, Dunkirk (France), in May and June 2012. One of the main objectives of the study was to provide new information on the chemical composition of particulate matter with aerodynamic diameters smaller than 2.5 μm (PM2.5) in the vicinity of metalworking facilities. An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed to provide size-resolved chemical mixing state measurements of ambient single particles at high temporal resolution. This mixing state information was then used to apportion PM2.5 to local metalworking facilities influencing the receptor site. Periods when the site was influenced by metalworking sources were characterised by a pronounced increase in particles containing toxic metals (manganese, iron, lead) and polycyclic aromatic hydrocarbons (PAHs) with a variety of chemical mixing states. The association of specific particle classes with a nearby ferromanganese alloy manufacturing plant was confirmed through comparison with previous analysis of raw materials (ores) and chimney filter particle samples collected at the facility. Particles associated with emissions from a nearby steelworks were also identified. The contribution of local metalworking activities to PM2.5 at the receptor site for the period when the ATOFMS was deployed ranged from 1 to 65% with an average contribution of 17%, while the remaining mass was attributed to other local and regional sources. These findings demonstrate the impact of metalworking facilities on air quality downwind and provide useful single particle signatures for future source apportionment studies in communities impacted by metalworking emissions.

The contribution of traffic-related particulate matter (PM2.5, particles smaller than 2.5 mu m in diameter) sources can vary temporally and spatially, which may disproportionately contribute to health outcomes. Furthermore, non-exhaust emissions are a growing concern due to the high concentrations of redox active metals that can be present. The temporal and spatial variabilities of traffic-related PM2.5 sources were investigated in this study by comparing source contributions between two near-road sites. In order to identify local PM2.5 sources with greater temporal and spatial resolution, receptor modeling was performed for hourly-resolved organics, inorganic ions, trace elements, and black carbon in PM2.5 simultaneously measured at downtown and highway sites located within 15 m of a major roadway and highway, respectively, in Toronto. The source apportionment study revealed that traffic-related PM2.5 sources were mainly from exhaust emissions (9%-19% of PM2.5) and non-exhaust emissions including brake wear (2%-6%) and resuspension of road dust (3%-4%). The traffic-related sources exhibited strong diurnal and spatial variabilities, whereas no spatial and temporal differences were observed for the largest PM2.5 contributors, oxidized organic aerosol and secondary sulphate. During morning rush hours, the overall contribution of traffic exhaust and non-exhaust emissions were elevated up to 35%-48% of total PM2.5 mass, which was found to be the largest PM2.5 source at the highway site and the second largest contributor in the downtown area. Furthermore, the contribution of traffic-related sources at the highway site was higher than at the downtown site by a factor of 2-3, suggesting that exposure to traffic-related emissions varies greatly in space and time. Nearly one-third of the traffic-related source contributions were associated with non-exhaust emissions from brake wear and road dust resuspension in the urban environment. Elevated levels of non-exhaust sources were correlated with the number of heavy-duty vehicles, rather than total traffic volume. Although the contribution of brake wear and road dust sources to total PM2.5 mass was relatively low, non-exhaust emissions contributed a substantial fraction of trace elements, especially for Ba (74-79%), Cu (66-71%), and Mn (53-65%) in the urban atmosphere.

Exposure to wildfire smoke is a public health issue of increasing prominence in North America, particularly in western states and provinces. In this study, Aethalometer data collected at six sites in the Lower Fraser Valley (LFV), British Columbia, from September 2016 through August 2017 were analyzed to investigate the relative importance of fossil fuel and biomass burning contributions to black carbon (BC) in the region. Annual mean BC mass concentrations were in the range 0.3-0.8 mu g m(-3), and BC was apportioned to fossil fuel and biomass burning sources at hourly resolution using the dual-wavelength Aethalometer model, applying a typical a priori assumed biomass burning Absorption Angstrom Exponent (AAE) value close to 2. However, this approach was found to underestimate biomass contributions to BC mass by up to a factor of three during wildfire events that impacted air quality throughout the region in July and August 2017. Hourly resolution PM2.5 concentrations in excess of 100 mu g m(-3) were recorded at multiple sites and mean ambient PM2.5 concentrations for the wildfire smoke periods were up to nine times higher than mean concentrations for the remainder of the summer. A background extraction approach was applied to optimize BC source apportionment during these events and to enable the calculation of wildfire aerosol AAE, with similar values for the latter determined across all six sites (1.35 +/- 0.09). The relatively low AAE values observed suggest that evaporation and/or photo-bleaching of brown carbon occurred during transport of wildfire aerosol to the receptor sites. From an exposure perspective, for the sites investigated, up to 69 +/- 20% (+/- 1 sigma) of ambient BC is attributed to wildfires during these events. On an annual scale, however, fossil fuel combustion and residential/agricultural biomass burning are estimated to be more important contributors to ambient BC mass concentrations at every site.

Accurate, continuous long-term measurements of aromatic volatile organic compounds with known health impacts are needed for comprehensive assessments of air quality in the vicinity of industrial and vehicular emission sources. Historically, evacuated canister sampling and on-line gas chromatography (GC) have been the most popular approaches applied by government institutions in North America to measure benzene, toluene, ethylbenzene and xylenes (BTEX) in ambient air. Canister sampling is labour-intensive and typically does not provide the continuous data needed for epidemiological studies, while on-line GCs are costly and require shelter and power. In this work, the accuracy and suitability of three techniques for generating long-term ambient BTEX datasets are assessed. The first is a passive sampling method involving sorbent-packed thermal desorption tubes, the second is an on-line miniature gas chromatograph (miniGC) coupled with a photoionization detector (PID) and the third is a more traditional on-line gas chromatograph coupled with a flame ionization detector (GC-FID). These three techniques were deployed at an air quality monitoring station located adjacent to a busy highway for six weeks in summer 2018 to compare method performance and accuracy. Ambient mean concentrations of BTEX determined from the three methods for the entire study period were found to agree within 7% for benzene and within 30% for the other species. Interestingly, a temperature dependent positive bias previously identified for 14-day passive tube sampling for ethylbenzene and xylenes under cold wintertime conditions was found to be negligible under summertime conditions.

In a context where a significant fraction of the population lives near industrial areas, the main objectives of this study are to provide (a) new data on PM2.5 chemical compositions, heavy-metal concentrations and trace gases released by metalworking activities and (b) new information on the near-field evolution (up to about a thousand meters) of such industrial plumes in terms of particle chemical composition and size distribution. For that purpose, a one-month field campaign was performed in an industrial area near the city of Dunkirk (Northern France), combining measurements of atmospheric dynamics and physico-chemical characterization of air masses. Comparisons between several elemental ratios (mainly Mn/Fe), particle size distributions and volatile organic compound (VOC) concentrations at the stacks and at a near-field site suggest that plumes of a ferromanganese alloy plant were quickly mixed with pollutants emitted by other sources (mainly other industries, possibly traffic and sea spray), in particular a neighboring steelworks, before reaching the sampling site. This led to the emergence of secondary particles related to condensation and/or aggregation phenomena inside the plumes. Metalworking emissions were also identified as a source of new particle formation, formed through the emission of gaseous precursors and their fast transformation and condensation, over a timescale of minutes before reaching the near-field site 800 m downwind. Ultrafine particles emitted at the stacks also quickly agglomerated to form larger particles before reaching the near-field site. These results show that, even over short distances, the chemical composition and size distribution of metalworking plumes may evolve rapidly and the characteristics of particles at the boundary of an industrial area (especially in contiguous urban areas) may differ from those emitted directly at the stacks.

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.

Six heavy metals - Mn, Fe, Cu, Zn, Se, and Pb among other elemental species were monitored in ambient PM2.5 at three near-road ambient air monitoring locations in the Greater Toronto and Hamilton Area (GTHA) with semi-continuous X-ray fluorescence (XRF) instrumentation over a period spanning January 1st, 2014 to June 30th, 2017. Land use in these air monitoring locations includes residential, institutional and industrial, thus, air monitoring is representative of typical urban areas. Ambient metal concentrations were found below Ontario's ambient air quality criteria. Temporal trends however indicated that high concentrations of Fe and Cu correlated with peak commuting and working hours on weekdays. To further understand the potential sources of these metals, scatterplots of metal concentrations and criteria pollutant gases were made on weekdays and weekends. These scatterplots reveal edges that are due to multiple sources of these metals. When these scatterplots are colour-coded by the hour of day, edges associated with the morning rush hour on weekdays for Fe and Cu (also Mn and Zn to a lesser extent) likely due to traffic-related emissions are more clearly-delineated from other edges arising from industrial or regional sources that were prevalent during other times of the day. Finally, an auxiliary receptor model was used to explore the potential source regions of these metals. It was observed that Mn, Fe and Cu had intense potential source regions within the GTHA on weekdays that diminished on the weekends, and in the case of Fe, the potential source regions in the GTHA were sensitive to the morning rush hour period, indicating that traffic-related emissions are a major source of Fe. Other metals, especially Zn, Se and Pb have source regions that are less sensitive to the morning rush hour period and are usually situated outside the GTHA.

Traffic-related air pollution near roadways: discerning local impacts 1 from background 2 Nathan Hilker, Jonathan M. Wang, Cheol-Heon Jeong, Robert M. Healy, Uwayemi Sofowote, Jerzy 3 Debosz, Yushan Su, Michael Noble, Anthony Munoz, Geoff Doerksen, Luc White, Céline Audette, 4 Dennis Herod, Jeffrey R. Brook, Greg J. Evans 5 Southern Ontario Centre for Atmospheric Aerosol Research, Department of Chemical Engineering and Applied Chemistry, 6 University of Toronto, Toronto, ON, M5S 3E5, Canada 7 Environmental Monitoring and Reporting Branch, Ontario Ministry of the Environment Conservation and Parks, Etobicoke, 8 ON, M3P 3V6, Canada 9 Air Quality Policy and Management Division, Metro Vancouver, Burnaby, BC, V5H 0C6, Canada 10 Air Quality Research Division, Environment and Climate Change Canada, Ottawa, ON, K1A 0H3, Canada 11 Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON, M3H 5T4, Canada 12 Correspondence to: Greg J. Evans (greg.evans@utoronto.ca) 13

Real-time analysis of volatile organic compounds (VOCs) in air is useful both for source identification and emissions compliance applications. In this work, two complementary triple quadrupole mass spectrometers, fitted with an atmospheric pressure chemical ionization (APCI) and a low pressure chemical ionization (LPCI) source, respectively, were deployed simultaneously to investigate emissions of VOCs associated with an Ontario-based chemical waste disposal facility. Mobile measurements performed upwind and downwind of the facility enabled selection of the best locations for stationary sampling. Seven separate field studies were undertaken between 2000 and 2016 to assess how emissions of VOCs have changed at the site as a function of time. Up to twenty-nine VOCs were successfully identified and quantified using MS/MS in each study. Simultaneous deployment of the two mass spectrometers enabled the detection of polar VOCs including alcohols, esters, amines and ketones as well as non-polar aromatic VOCs including benzene and naphthalene in real time. Concentrations of VOCs were found to decrease significantly in the vicinity of the facility over the sixteen year period, in particular since 2007. Concentration values for each year are compared with odour thresholds and provincial guidelines and implications of future expansion of on-site solid waste landfill volumes are also discussed.

Temporal variations of vehicle emissions are affected by various compounding factors in the real world. The focus of this study is to determine the effects of ambient conditions and post-tailpipe changes on traffic emissions measured in the near-road region. Emission factors allowed for the isolation of the traffic signal and accounted for effects of local meteorology and dilution. Five month-long measurement campaigns were conducted at an urban near-road site that exhibited a broad range of ambient conditions with temperatures ranging between -18 and + 30 degrees C. Particle number emission factors were 2.0 x higher in the winter relative to the summer, which was attributed to changes in particles post-tailpipe. Conversely, toluene emissions were 2.5 x higher in the summer relative to the winter, attributed to changes in fuel composition. Diurnal trends of emission factors showed substantial increases in emissions during the morning rush hour for black carbon (1.9 x), particle number (2.4 x), and particle-bound polycyclic aromatic hydrocarbons (3.0 x), affected by fleet make-up. In contrast, particle number emission factors were highest midday with mean values 3.7 x higher than at night. This midday increase was attributed to particle formation or growth from local traffic emissions and showed different wind direction dependence than regional events.

Traffic has a substantial impact on air pollution in many cities. As the introduction of new vehicle technologies reduces emissions of some pollutants, the role of non-tailpipe emissions is increasing in prominence. The impact of non-tailpipe emissions has been investigated using 18 months of data collected at two near road monitoring sites in Toronto, one beside a downtown arterial road and the other beside highway 401 within the busiest stretch of highway in North America. These data indicate that non-tailpipe emissions can have large impacts on the concentrations of selected metals. Hourly and 24-h integrated measurements have revealed diurnal, weekday/weekend, seasonal and meteorology dependent patterns that help to isolate traffic-related metal sources and provide insight into the relative importance of direct emissions and resuspension of road dust. Positive matrix factorization has been applied to isolate traffic-related factors and the contribution of non-tailpipe emissions to ambient PM2.5. The oxidative potential and metal concentrations in dust samples collected at sites across Toronto are being used to evaluate the relative hazard posed by these vehicle emissions. Overall, this talk will summarize what is known about the sources, composition, and size of the different non-tailpipe particulate emission components and highlight markers of these sources that can be used for future source apportionment and modeling efforts.