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Rationale: Severe acute respiratory syndrome caused by coronavirus 2 (SARS-CoV-2) was declared a pandemic on March 11, 2020. Countries entered lockdown, restricting medical activities to essential services. Pulmonary function tests (PFT) are crucial for management of lung diseases. With limited data regarding aerosol generation and the risk of disease transmission during PFTs, many laboratories closed. Our objective is to quantify aerosol generation during different PFT modalities. Methods: We measured aerosol particles in the 0.3-10.0 µm range with an Optical Particle Sizer (Model 3330;TSI Incorporated) and collected bioaerosols to detect respiratory pathogens during clinically indicated PFTs at a hospital-based laboratory during 2 time points in 2020. Results: We monitored 81 and 41 individual multi-modality PFT sessions in June/July and December, respectively. Slow vital capacity, forced vital capacity and diffusion capacity generated higher aerosol counts compared to pre- and post-test room levels although all modalities were lower than during talking or coughing. The aerosol sizes generated were primarily 2.5-10 µm. Oscillometry generated higher overall concentrations than room sampling, also primarily in the 2.5-10 µm aerosols. The bioaerosol filters revealed no respiratory viruses or bacteria. Conclusions: While PFT can generate aerosols, it is less than normal speech with the exception of PFT-induced coughing. Our findings suggest the risk of SARS-CoV-2 transmission is not increased and support the re-opening of PFT laboratories that adhere to universal masking, use of personal protective equipment and stringent infection control protocols. We strongly endorse adherence to public health guidelines in the operation of PFT laboratories.

This paper presents a methodology for estimating fleet emission rates from measured roadside concentrations. By filtering measurements based on meteorological conditions, including effective wind speeds above 2 m ⋅ s − 1 and periods where the receptor is downwind, we find our simplified approach can compare well with the more sophisticated Research LINE source (RLINE) model. We applied our method to two years of roadside air pollution and traffic measurements at a Toronto, Canada, highway site to estimate minutely emission rates (ER, mass∙m−1∙s−1) and emission factors (EF, mass∙vehicle−1∙ km−1) for carbon dioxide (CO2), nitrogen oxides (NOX), carbon monoxide (CO), black carbon (BC), particulate matter mass less than 2.5 μm in diameter (PM2.5), particle number (PN), and ozone (O3) over a two-year period. Re-entering these emission rates to a multi-lane RLINE model showed favorable agreement between predicted and measured concentrations for all pollutants with 85-87% of predicted concentrations falling within a factor of two of measured. A multiple-input linear regression was used to determine light-duty vehicle (LDV) and medium/heavy-duty vehicle (MDV + HDV)-specific emission factors, which fell in or near ranges previously reported for all pollutants. More generally, the method proposed here can allow researchers to easily measure emission rates and factors from roadways using near-road concentration measurements and simple analysis methods, and can exclude some or all micrometeorological inputs, allowing researchers to perform inverse dispersion modeling in regions where such inputs are unavailable. The results also provide updated data on Canadian vehicle emissions and refine the relationships between emissions and traffic composition and speed.

Traffic-related air pollutants (TRAP) including nitric oxide (NO), nitrogen oxide (NO

The lockdown measures caused by the COVID-19 pandemic substantially affected air quality in many cities through reduced emissions from a variety of sources, including traffic. The change in PM2.5 and its chemical composition in downtown Toronto, Canada, including organic/inorganic composition and trace metals, were examined by comparing with a pre-lockdown period and respective periods in the three previous years. During the COVID-19 lockdown, the average traffic volume reduced by 58%, whereas PM2.5 only decreased by 4% relative to the baselines. Major chemical components of PM2.5, such as organic aerosol and ammonium nitrate, showed significant seasonal changes between pre- and lockdown periods. The changes in local and regional PM2.5 sources were assessed using hourly chemical composition measurements of PM2.5. Major regional and secondary PM2.5 sources exhibited no clear reductions during the lockdown period compared to pre-lockdown and the previous years. However, cooking emissions substantially dropped by approximately 61% due to the restrictions imposed on local businesses (i.e., restaurants) during the lockdown, and then gradually increased throughout the recovery periods. The reduction in non-tailpipe emissions, characterized by road dust and brake/tire dust, ranged from 37% to 61%, consistent with the changes in traffic volume and meteorology across seasons in 2020. Tailpipe emissions dropped by approximately 54% and exhibited even larger reductions during morning rush hours. The reduction of tailpipe emissions was statistically associated with the reduced number of trucks, highlighting that a small fraction of trucks contributes disproportionally to tailpipe emissions. This study provides insight into the potential for local benefits to arise from traffic intervention in traffic-dominated urban areas and supports the development of targeted strategies and regulations to effectively reduce local air pollution., Graphical abstract Image 1

A new method is presented for measuring atmospheric concentrations of trace metals in airborne particulate matter using polyurethane foam (PUF) disk passive air samplers (PUF-PASs) and passive dry ...

Positive and negative artifacts of particle-phase organic carbon (p-OC) and the polycyclic aromatic hydrocarbons (PAHs) in gasoline direct injection (GDI) engine exhaust particulate matter (PM) were assessed using an integrated organic gas and particle sampler (IOGAPS). Three configurations (denuder + sorbent impregnated filters (SIFs), upstream Zefluor filter + denuder + SIFs, and standard filter pack + SIFs) were used to collect GDI exhaust samples at cold start and highway cruise operating conditions with no aftertreatment. Approximately 35% of the measured GDI p-OC was attributed to positive artifacts; negative artifacts were not detectable due to low overall SVOC concentrations. GDI engine exhaust PAH concentrations were approximately 10 times higher during cold start than highway cruise. At highway cruise, pyrene and fluoranthene were the dominant PAHs in the undenuded filter pack; downstream of the denuder benzo(a)anthracene was the dominant PAH. From a comparison of our findings to published PAH emission factors we estimate that three-way catalyst conversion efficiencies of PAHs were approximately 80% for 3 of the 15 PAHs measured during highway cruise operation. These conversion efficiencies may be considerably lower during cold start operation when the three-way catalyst has not reached its operating temperature. Our previous work showed that adverse biological responses to GDI engine exhaust exposure may be dominated by the particle phase when measured downstream of a Teflon filter. Understanding the partitioning characteristics of PAHs may help elucidate specific PAHs contributing to this effect.

The contribution of traffic-related particulate matter (PM2.5, particles smaller than 2.5 μm 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.

Land use regression (LUR) models that predict intra-urban variability of traffic-related air pollution are frequently used to inform exposure assessments in epidemiological studies. Spatially extending models built in city centres to unmeasured surrounding areas could be beneficial as it increases the size of area available for exposure assessment, which can improve the statistical power of health studies. However, past studies have shown poor performance when these models were transferred to unmeasured areas. In this study, ambient concentrations of black carbon (BC), ultrafine particles (UFP), nitric oxide (NO) and nitrogen dioxide (NO2) with response times ranging from 1 s to 20 s were measured in the summer using a mobile laboratory. These ambient concentrations were temporally deconvolved into local, neighbourhood- and regional-background time-series signals. The temporally resolved signals were used to develop resolved LUR models (i.e. local, neighbourhood-background and regional-background models) while unresolved LUR models were developed from total ambient concentrations (i.e., measurements that were not temporally resolved). Both resolved and unresolved LUR models displayed modest R2 values when compared to models developed from fixed sites which may be due to the mobile nature of our data. External validation of the resolved and unresolved models within the models' original geographic domain showed comparable performance for BC (R2 for resolved vs. unresolved: 0.44 vs. 0.47), UFP (0.34 vs. 0.35), NO (0.18 vs. 0.19) and NO2 (0.42 vs.0.40). However, the resolved models were better able to assess exposure than the unresolved models when they were spatially extended to suburban areas bordering the urban area: UFP (R2: 0.42 vs. 0.29), NO2 (0.36 vs 0.26), NO (0.21 vs 0.14) and BC (0.32 vs 0.30). Furthermore, the resolved models were better able to predict the observed variability in suburban areas with both similar and different land uses to the urban area.

The lockdown measures caused by the COVID-19 pandemic substantially affected air quality in many cities through reduced emissions from a variety of sources, including traffic. The change in PM2.5 and its chemical composition in downtown Toronto, Canada, including organic/inorganic composition and trace metals, were examined by comparing with a pre-lockdown period and respective periods in the three previous years. During the COVID-19 lockdown, the average traffic volume reduced by 58%, whereas PM2.5 only decreased by 4% relative to the baselines. Major chemical components of PM2.5, such as organic aerosol and ammonium nitrate, showed significant seasonal changes between pre- and lockdown periods. The changes in local and regional PM2.5 sources were assessed using hourly chemical composition measurements of PM2.5. Major regional and secondary PM2.5 sources exhibited no clear reductions during the lockdown period compared to pre-lockdown and the previous years. However, cooking emissions substantially dropped by approximately 61% due to the restrictions imposed on local businesses (i.e., restaurants) during the lockdown, and then gradually increased throughout the recovery periods. The reduction in non-tailpipe emissions, characterized by road dust and brake/tire dust, ranged from 37% to 61%, consistent with the changes in traffic volume and meteorology across seasons in 2020. Tailpipe emissions dropped by approximately 54% and exhibited even larger reductions during morning rush hours. The reduction of tailpipe emissions was statistically associated with the reduced number of trucks, highlighting that a small fraction of trucks contributes disproportionally to tailpipe emissions. This study provides insight into the potential for local benefits to arise from traffic intervention in traffic-dominated urban areas and supports the development of targeted strategies and regulations to effectively reduce local air pollution.

Secondary organic aerosol (SOA) produced from atmospheric oxidation of organic vapors comprises a large portion of ambient particulate matter. Currently, SOA models typically assume that all organic species form a well-mixed phase as a simplification, which follows that SOA formation is enhanced in the presence of pre-existing organic aerosol (OA) according to Raoult’s Law. In this work, we show through experiments with atmospherically relevant OA that not all organic species are equally miscible, and the thermodynamics of mixing are composition dependent. SOA formation from α-pinene ozonolysis was investigated in the presence of OA that was collected from Toronto ambient air and other sources including biomass burning, meat-cooking emissions, and diesel exhaust. Compared to experiments with ammonium sulfate seed particles, enhanced SOA yields were observed with particles from biomass burning and meat cooking but not with diesel exhaust and concentrated ambient particles. We demonstrate that both kinetic ...

A daily integrated emission factor (EF) method was applied to data from three near-road monitoring sites to identify variables that impact traffic related pollutant concentrations in the near-road environment. The sites were operated for 20 months in 2015–2017, with each site differing in terms of design, local meteorology, and fleet compositions. Measurement distance from the roadway and local meteorology were found to affect pollutant concentrations irrespective of background subtraction. However, using emission factors mostly accounted for the effects of dilution and dispersion, allowing intersite differences in emissions to be resolved. A multiple linear regression model that included predictor variables such as fraction of larger vehicles (>7.6 m in length; i.e., heavy-duty vehicles), vehicle speed, and ambient temperature accounted for intersite variability of the fleet average NO, NOx, and particle number EFs (R2:0.50–0.75), with lower model performance for CO and black carbon (BC) EFs (R2:0.28–0.4...

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 °C. Particle number emission factors were 2.0× higher in the winter relative to the summer, which was attributed to changes in particles post-tailpipe. Conversely, toluene emissions were 2.5× 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×), particle number (2.4×), and particle-bound polycyclic aromatic hydrocarbons (3.0×), affected by fleet make-up. In contrast, particle number emission factors were highest midday with mean values 3.7× 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.

The Pan and Parapan American Games (PA15) are the third largest sporting event in the world and were held in Toronto in the summer of 2015 (10–26 July and 7–15 August). This was used as an opportunity to coordinate and showcase existing innovative research and development activities related to weather, air quality (AQ), and health at Environment and Climate Change Canada. New observational technologies included weather stations based on compact sensors that were augmented with black globe thermometers, two Doppler lidars, two wave buoys, a 3D lightning mapping array, two new AQ stations, and low-cost AQ and ultraviolet sensors. These were supplemented by observations from other agencies, four mobile vehicles, two mobile AQ laboratories, and two supersites with enhanced vertical profiling. High-resolution modeling for weather (250 m and 1 km), AQ (2.5 km), lake circulation (2 km), and wave models (250-m, 1-km, and 2.5-km ensembles) were run. The focus of the science, which guided the design of the observation network, was to characterize and investigate the lake breeze, which affects thunderstorm initiation, air pollutant transport, and heat stress. Experimental forecasts and nowcasts were provided by research support desks. Web portals provided access to the experimental products for other government departments, public health authorities, and PA15 decision-makers. The data have been released through the government of Canada’s Open Data Portal and as a World Meteorological Organization’s Global Atmospheric Watch Urban Research Meteorology and Environment dataset.

Long-range transport of aerosol from lower latitudes to the high Arctic may be a significant contributor to climate forcing in the Arctic. To identify the sources of key contaminants entering the Canadian High Arctic an intensive campaign of snow sampling was completed at Alert, Nunavut, from September 2014 to June 2015. Fresh snow samples collected every few days were analyzed for black carbon, major ions, and metals, and this rich data set provided an opportunity for a temporally refined source apportionment of snow composition via positive matrix factorization (PMF) in conjunction with FLEXPART (FLEXible PARTicle dispersion model) potential emission sensitivity analysis. Seven source factors were identified: sea salt, crustal metals, black carbon, carboxylic acids, nitrate, non-crustal metals, and sulfate. The sea salt and crustal factors showed good agreement with expected composition and primarily northern sources. High loadings of V and Se onto Factor 2, crustal metals, was consistent with expected elemental ratios, implying these metals were not primarily anthropogenic in origin. Factor 3, black carbon, was an acidic factor dominated by black carbon but with some sulfate contribution over the winter-haze season. The lack of K+ associated with this factor, a Eurasian source, and limited known forest fire events coincident with this factor's peak suggested a predominantly anthropogenic combustion source. Factor 4, carboxylic acids, was dominated by formate and acetate with a moderate correlation to available sunlight and an oceanic and North American source. A robust identification of this factor was not possible; however, atmospheric photochemical reactions, ocean microlayer reaction, and biomass burning were explored as potential contributors. Factor 5, nitrate, was an acidic factor dominated by NO3−, with a likely Eurasian source and mid-winter peak. The isolation of NO3− on a separate factor may reflect its complex atmospheric processing, though the associated source region suggests possibly anthropogenic precursors. Factor 6, non-crustal metals, showed heightened loadings of Sb, Pb, and As, and correlation with other metals traditionally associated with industrial activities. Similar to Factor 3 and 5, this factor appeared to be largely Eurasian in origin. Factor 7, sulfate, was dominated by SO42− and MS with a fall peak and high acidity. Coincident volcanic activity and northern source regions may suggest a processed SO2 source of this factor.

The differences in PM2.5 concentrations between two relatively close stations, one situated near a major highway and the other much more distant were used to develop a protocol for determining the impact of highway traffic on particulate matter concentrations at the roadside. The roadside station was ≳ 50%. Of interest was the variation of multi-time factors based on ME2 analyses of the speciation data from the roadside station during these imbalance events. Of the 7 mass-contributing ME2 factors, a black carbon factor was determined to be the major cause of the PM2.5 imbalance and was especially dominant for the case when PM2.5 concentrations at the roadside station were greater than the farther-station PM2.5. The black carbon concentrations observed during these specific events were further regressed against other traffic-related and meteorological parameters with two nonlinear optimization algorithms (generalized reduced gradient and rules ensemble) in our attempts to model any potential relationships. It was observed that the traffic counts of heavy duty vehicles (predominantly diesel-powered) dominated the relationship with black carbon while contributions from light duty vehicles were negligible during these [PM2.5]Roadside > [PM2.5]Farther events at the roadside station. This work details the most critical ways that highway traffic can contribute to local ambient PM2.5 concentrations that commuters are exposed to and will be important in informing policies and strategies for particulate matter pollution reduction.

Significant attention, especially in the last decade, has been focussed on elevated concentrations of ultrafine particulate matter (UFP) in urban areas and the adverse health effects associated with exposure to UFP. Despite this, there is a relative scarcity of long-term ambient UFP measurements. This study examined trends in UFP measurements made continuously near a busy roadway in downtown Toronto, Canada, between the years 2006 and 2019 using a fast mobility particle sizer (FMPS). These long-term trends were associated with other air pollutant concentrations-namely: nitric oxide (NO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and fine particulate matter mass concentrations (PM2.5)-and persistent declining trends were observed for each during the study period. From 2006 to 2019, reductions of 45%, 68%, 39%, 83%, and 41%, for UFP, NO, NO2, SO2, and PM2.5, respectively, were observed. These reductions are in part associated with a total phase-out of coal-fired electricity generation in Ontario, Canada, between 2004 and 2015, and continuous improvements in vehicle emissions control technologies. Additionally, deconvolution of the time-series yielded seasonal fluctuations which were analysed as a function of particle diameter and ambient temperature, the results from which may aid in the comparison of UFP measurements made in climates with different ambient temperature ranges in a meaningful way. Finally, the UFP data were background-subtracted and it was found that local sources (such as vehicle traffic) contributed ~45% to total concentrations and this fraction remained relatively constant throughout the study. A multilinear function regressed on these local and background concentrations better elucidated the sources contributing to UFP variability-background concentrations were largely covariate with SO2 emissions whereas local concentrations were more affected by NO emissions. The data in this study shows clear co-benefits to reducing UFP concentrations by targeting NOx and SOx emissions.

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.

Black carbon (BC) is of significant interest from a human exposure perspective but also due to its impacts as a short-lived climate pollutant. In this study, sources of BC influencing air quality in Ontario, Canada were investigated using nine concurrent Aethalometer datasets collected between June 2015 and May 2016. The sampling sites represent a mix of background and near-road locations. An optical model was used to estimate the relative contributions of fossil fuel combustion and biomass burning to ambient concentrations of BC at every site. The highest annual mean BC concentration was observed at a Toronto highway site, where vehicular traffic was found to be the dominant source. Fossil fuel combustion was the dominant contributor to ambient BC at all sites in every season, while the highest seasonal biomass burning mass contribution (35%) was observed in the winter at a background site with minimal traffic contributions. The mass absorption cross-section of BC was also investigated at two sites, where concurrent thermal/optical elemental carbon data were available, and was found to be similar at both locations. These results are expected to be useful for comparing the optical properties of BC at other near-road environments globally. A strong seasonal dependence was observed for fossil fuel BC at every Ontario site, with mean summer mass concentrations higher than their respective mean winter mass concentrations by up to a factor of two. An increased influence from transboundary fossil fuel BC emissions originating in Michigan, Ohio, Pennsylvania and New York was identified for the summer months. The findings reported here indicate that BC should not be considered as an exclusively local pollutant in future air quality policy decisions. The highest seasonal difference was observed at the highway site, however, suggesting that changes in fuel composition may also play an important role in the seasonality of BC mass concentrations in the near-road environment. This finding has implications for future policies aiming to improve air quality in urban environments where fuel composition changes as a function of season.

Can mitigating only particle mass, as the existing air quality measures do, ultimately lead to reduction in ultrafine particles (UFP)? The aim of this study was to provide a broader urban perspective on the relationship between UFP, measured in terms of particle number concentration (PNC) and PM2.5 (mass concentration of particles with aerodynamic diameter < 2.5 μm) and factors that influence their concentrations. Hourly average PNC and PM2.5 were acquired from 10 cities located in North America, Europe, Asia, and Australia over a 12-month period. A pairwise comparison of the mean difference and the Kolmogorov-Smirnov test with the application of bootstrapping were performed for each city. Diurnal and seasonal trends were obtained using a generalized additive model (GAM). The particle number to mass concentration ratios and the Pearson's correlation coefficient were calculated to elucidate the nature of the relationship between these two metrics. Results show that the annual mean concentrations ranged from 8.0 × 103 to 19.5 × 103 particles·cm−3 and from 7.0 to 65.8 μg·m−3 for PNC and PM2.5, respectively, with the data distributions generally skewed to the right, and with a wider spread for PNC. PNC showed a more distinct diurnal trend compared with PM2.5, attributed to the high contributions of UFP from vehicular emissions to PNC. The variation in both PNC and PM2.5 due to seasonality is linked to the cities' geographical location and features. Clustering the cities based on annual median concentrations of both PNC and PM2.5 demonstrated that a high PNC level does not lead to a high PM2.5, and vice versa. The particle number-to-mass ratio (in units of 109 particles·μg−1) ranged from 0.14 to 2.2, >1 for roadside sites and, “GEMMA Center in the framework of Project MIUR – Dipartimenti di Eccellenza 2018–2022” funding for measurements in Milan site. Appendix A

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

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.

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.

Long-term trends (2004–2017) in the chemical composition and sources of PM2.5 (particulate matter smaller than 2.5 μm in diameter) in a metropolitan area were investigated using daily integrated PM2.5 chemical speciation data and continuous air pollution measurements. Eleven source factors were identified: coal combustion characterized by secondary sulphate, secondary nitrate, summertime organic carbon (OC), regional elemental carbon (EC), biomass burning, oil combustion, primary tailpipe emissions, non-tailpipe emissions related to road dust, non-tailpipe emissions related to brake wear, metal production, and road salt. Overall, coal combustion, secondary nitrate, regional EC, and oil combustion underwent marked decreases in concentrations with large reduction rates ranging from −8% yr−1 to −18% yr−1, contributing to an overall 34% decrease in annual PM2.5 over the past 14 years. Decreases in local tailpipe emissions (−3% yr−1) were consistent with the reduction of traffic-related air pollutants. In contrast, non-tailpipe emissions remained constant until 2010–2011 and then increased with a range of rates of 21% yr−1 to 27% yr−1 from 2011 to 2016. The contribution of summertime OC increased to approximately 27% in the summer of 2013–2016, rising to become the largest PM2.5 source driven by the reduction of regional sources. The chemical composition of PM2.5 in the urban area drastically changed from inorganic-rich to organic- and metal-rich particles during 2013–2016. The depletion of ascorbic acid was measured using filter samples collected over one year to identify PM2.5 components and sources contributing to the oxidative potential (OP) of PM2.5. The OP was clearly associated with trace elements (e.g., Ba, Cu, Fe). Non-tailpipe emissions related to road dust and brake wear presented high redox activity per mass of PM2.5. This work suggests that summertime OC and non-tailpipe emissions in recent years have become increasingly important. As such, policies targeting traffic-related PM2.5 should focus on these sources for maximum impact.

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 increas...

Vehicle emissions represent a major source of air pollution in many urban regions. Local and city-wide traffic, along with regional sources, can influence concentrations. Real-time pollutant measur...

In many cities, traffic combustion emissions are decreasing as a result of more stringent emissions standards and resulting technological improvements. However, non-tailpipe emissions have been neg...

With concern in recent years about adverse health effects for populations living or spending significant amounts of time near large roadways, an investigation of the air quality characteristics and potential sources influencing levels of PM and its chemical composition was undertaken in Toronto and Vancouver. Three near-road monitoring stations were established in the downtown area and beside a large highway in Toronto, and beside a major trucking route in Vancouver. 24-hour integrated samples were concurrently collected at these near-road and nearby urban background sites. This study has provided detailed chemical data for PM2.5 and reactive gases (NH3, HONO and HNO3) for a year in 2015–2016. Differences between pollutant concentrations at the near-road and background urban sites were identified, and compared with observations at other urban locations. The traffic contribution was quantified as the concentration increment between the near-road and background sites. The highest increments due to traffic were observed for elemental carbon, select trace metals (e.g. Fe, Ba, Cu, Sb, Zn) and reactive gases (NH3, HONO). In general, the percent contribution of local traffic-related emissions followed a descending order of Toronto highway > Vancouver truck route > downtown Toronto for most of these pollutants. It appears that the influence of traffic-related emissions on air pollution near roads depends more on the proportion of large trucks in the fleet than the total traffic volume. Application of principal component analysis (PCA) coupled with multi-linear regression (MLR) analysis to the local traffic increment pollutant data, as well as knowledge of chemical markers representative of different sources, helped to identify the possible sources of traffic-related PM2.5. These sources include non-exhaust (brake wear abrasion, resuspended road dust) and vehicular exhaust (mixed gasoline/diesel, diesel and lubricating oil combustion) emissions. The contribution of each of the sources varied between sites. In particular, the contribution of diesel exhaust emissions, presumably from highly polluting heavy-duty vehicles and trucks, was significant at the truck route (Vancouver) and the highway (Toronto) sites. Furthermore, the substantial contribution of non-exhaust emissions (brake wear and resuspension of road dust) to PM2.5, and thus metals, with differences between sites due to traffic characteristics or local meteorology was identified. Emissions related to lube oil combustion were not statistically significant. Overall, this work delivered valuable information that serves as input for further studies involving other roads and cities in order to generate reliable and representative results for air quality management and associated health outcomes.

Exposure to ambient air pollution has been linked to adverse health outcomes ranging from asthma to premature mortality. However, little to no information exists on the exposure of residents and visitors in the Caribbean islands. While a few previous studies have quantified levels of PM10 (particulate matter

The optical properties of ambient black carbon-containing particles and the composition of their associated coatings were investigated at a downtown site in Toronto, Canada, for 2 weeks in June 2013. The objective was to assess the relationship between black carbon (BC) coating composition/thickness and absorption. The site was influenced by emissions from local vehicular traffic, wildfires in Quebec, and transboundary fossil fuel combustion emissions in the United States. Mass concentrations of BC and associated nonrefractory coatings were measured using a soot particle–aerosol mass spectrometer (SP-AMS), while aerosol absorption and scattering were measured using a photoacoustic soot spectrometer (PASS). Absorption enhancement was investigated both by comparing ambient and thermally denuded PASS absorption data and by relating absorption data to BC mass concentrations measured using the SP-AMS. Minimal absorption enhancement attributable to lensing at 781 nm was observed for BC using both approaches. However, brown carbon was detected when the site was influenced by wildfire emissions originating in Quebec. BC coating to core mass ratios were highest during this period (~7), and while direct absorption by brown carbon resulted in an absorption enhancement at 405 nm (>2.0), no enhancement attributable to lensing at 781 nm was observed. The efficiency of BC coating removal in the denuder decreased substantially when wildfire-related organics were present and may represent an obstacle for future similar studies. These findings indicate that BC absorption enhancement due to lensing is minimal for downtown Toronto, and potentially other urban locations, even when impacted by long-range transport events.

The health of a substantial portion of urban populations is potentially being impacted by exposure to traffic–related atmospheric pollutants. To better understand the rapid physical and chemical transformation of these pollutants, the number size distributions of non–volatile traffic–related particles were investigated at different distances from a major highway. Particle volatility measurements were performed upwind and downwind of the highway using a fast mobility particle sizing spectrometer with a thermodenuder on a mobile laboratory. The number concentration of non–denuded ultrafine particles decreased exponentially with distance from the highway, whereas a more gradual gradient was observed for non–volatile particles. The non–volatile number concentration at 27 m was higher than that at 280 m by a factor of approximately 3, and the concentration at 280 m was still higher than that upwind of the highway. The proportion of non–volatile particles increased away from the highway, representing 36% of the total particle number at 27 m, 62% at 280 m, and 81% at the upwind site. A slight decrease in the geometric mean diameter of the non–volatile particle size distributions from approximately 35 nm to 30 nm was found between 27 m and 280 m, in contrast to the growth of non–denuded particles with increasing distance from the highway. Single particle analysis results show that the contribution of elemental carbon (EC)–rich particle types at 27 m was higher than the contribution at 280 m by a factor of approximately 2. The findings suggest that people living or spending time near major roadways could be exposed to elevated number concentrations of nucleation–mode volatile particles ( 100 nm). The impact of the highway emissions on air quality was observable up to 300 m.

This study applies land-use regression (LUR) to characterize the spatial distribution of ultrafine particles (UFP) in a large city. Particle number (PN) concentrations were measured in residential areas around Toronto, Canada, between June and August 2008. A combination of fixed and mobile monitoring was used to assess spatial gradients between and within communities. The fixed monitoring locations included a central site, two downtown sites, and four residential sites located 6–15 km from the downtown core. The mobile data included average PN concentrations collected on 112 road segments from 10 study routes that were repeated on three separate days. The mobile data was used to create the land-use regression model while the fixed sites were used for validation purposes. The predictor variables that best described the spatial variation of PN concentration (R2 = 0.72, validated R2 = 0.68) included population density within 300 m, total resource and industrial area within 1000 m, total residential area within 3000 m, and major roadway and highway length within 3000 m. The LUR model successfully predicted the afternoon peak PN concentration (slope = 0.96, R2 = 0.86) but over-predicted the 24-h average PN concentration (slope = 1.28, R2 = 0.72) measured at seven fixed monitoring sites.

The TSI Fast Mobility Particle Sizer (FMPS) and Engine Exhaust Particle Sizer (EEPS) provide size distributions for 6–560 nm particles with a time resolution suitable for characterizing transient particle sources; however, the accuracy of these instruments can be source dependent, due to influences of particle morphology. The aim of this study was to develop a source-independent correction protocol for the FMPS and EEPS. The correction protocol consists of: (1) broadening the >80 nm size range of the distribution to account for under-sizing by the FMPS and EEPS; (2) applying an existing correction protocol in the 8–93 nm size range; and (3) dividing each size bin by the ratio of total concentration measured by the FMPS or EEPS and a water-based Condensation Particle Counter (CPC) as a surrogate scaling factor to account for particle morphology. Efficacy of the correction protocol was assessed for three sources: urban ambient air, diluted gasoline direct injection engine exhaust, and diluted diesel engine exhaust. Linear regression against a reference instrument, the Scanning Mobility Particle Sizer (SMPS), before and after applying the correction protocol demonstrated that the correction ensured agreement within 20%.

In this paper, we conducted a comparative study of new particle formation (NPF) events occurring between Qingdao and Toronto during spring. The extent of air pollution in Qingdao was much severer than that in Toronto, but the occurrence frequency of NPF events in Qingdao (41%) was almost same as that (42%) in Toronto. The geometric median diameter of new particles (Dpg,1) increased up to >40 nm in 15 days out of the total 16 NPF days in Qingdao, the Dpg,1 at least in eight days increased up to >60 nm and even reached >80 nm in two days. Two-stage growth was generally observed in these eight NPF events. The first-stage growth occurred in daytime and it was likely associated with formation of secondary organic aerosol (SOA) on basis of the modeling results. The second-stage growth was generally observed at nighttime when the modeling results showed increases of NH4+ and NO3− in concentration together with SOA, implying that NH4NO3 possibly played a role in the growth. In Toronto, the maximum Dpg,1 of the observed new particles in all 13 NPF events was less than 50 nm. A slight second-stage growth of new particles was observed only in four days when either the increase of NH4+ and NO3− in concentration or the increase of relative humidity occurred. The NPF events in Toronto less likely had a significant contribution to cloud condensation nuclei due to the small size of the observed new particles.

Long-range transport of aerosol from lower latitudes to the high Arctic may be a significant contributor to climate forcing in the Arctic. To identify the sources of key contaminants entering the Canadian high Arctic an intensive campaign of snow sampling was completed at Alert, Nunavut, from September 2014 to June 2015. Fresh snow samples collected every few days were analysed for black carbon, major ions, and metals, and this rich data provided an opportunity for a temporally-refined source apportionment of snow composition via Positive Matrix Factorization in conjunction with FLEXPART potential emission sensitivity analysis. Seven source factors were identified: sea salt, regional dust, Eurasian fossil fuel combustion, mixed carboxylic acid sources, nitrate processing, Eurasian industrial activities, and regional volcanic and marine biogenic activity. The majority (73 %) of the black carbon in snow, a light-absorbing compound critical to the Arctic radiative balance, was found to be the product of fossil fuel burning with limited biomass burning influence.

A majority of the ultrafine particles observed in real-world conditions are systematically excluded from many measurements that help to guide regulation of vehicle emissions. To investigate the impact of this exclusion, coincident near-road particle number (PN) emission factors were quantified up- and downstream of a thermodenuder during two seasonal month-long campaigns with wide-ranging ambient temperatures (−19 to +30 °C) to determine the volatile fraction of particles. During colder temperatures ( 20 °C). Additionally, mean PN emission factors were a factor of 3.8 higher during cold compared to warm periods. On the basis of 130 000 vehicle plumes including three additional campaigns, fleet mean emission factors were calculated for PN (8.5 × 1014 kg-fuel–1), black carbon (37 mg kg-fuel–1), organic aerosol (51 mg kg-fuel–1), and particle-bound polycyclic aromatic hydrocarbons (0.7 mg kg-fuel–1). These finding...

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 metals in PM2.5 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-hr filter samples were collected one-in-six days over a two-year period (Dec. 2010–Nov. 2012) at three air monitoring stations in the Regional Municipality of Wood Buffalo. For the intensive campaign (Aug. 2013), hourly measurements were made with an on-line instrument at one air monitoring station; daily filter samples were also collected. The hourly and 24-h filter data were analysed individually using positive matrix factorization. Seven emission sources of PM2.5 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 metal was 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 metals in snow, water, and biota samples collected near the oil sands operations.

Ultrafine particle (UFP), black carbon (BC) and lung deposited surface area (LDSA) concentrations measured during 43 trips on diesel-powered commuter trains revealed elevated exposures under some conditions. When the passenger coaches were pulled by a locomotive, the geometric mean concentrations of UFP, LDSA, and BC were 18, 10, and 6 times higher than the exposure levels when the locomotive pushed the coaches, respectively. In addition, UFP, LDSA, and BC concentrations in pull-trains were 5, 3, and 4 times higher than concentrations measured while walking on city sidewalks, respectively. Exposure to these pollutants was most elevated in the coach located closest to the locomotive: geometric means were 126,000 # cm−3 for UFP, 249 μm2 cm−3 for LDSA, and 17,800 ng m−3 of BC; these concentrations are much higher than those previously reported for other modes of public transportation. Markedly high levels of diesel exhaust are present in passenger trains powered by diesel locomotives operated in pull-mode. Thus, it is recommended that immediate steps be taken to evaluate, and where needed, mitigate exposure in diesel-powered passenger trains, both commuter and inter-city.

This study explores the application of wavelet decomposition as a means to distinguish between local and regional sources of ultrafine particles (UFP). Particle number concentrations were measured at a central site, two downtown sites, and four residential sites located across Toronto, Canada. Using a wavelet decomposition algorithm, particle concentration time series were separated into two signals: high frequency local-to-neighbourhood scale sources and low frequency urban-to-regional scale sources and processes. At the field sites, local–neighbourhood sources contributed between 13 and 32% of the total particle concentration. The urban–regional signal at each field site exhibited stronger correlation and greater homogeneity with respect to the central site than the original concentration time series. In contrast, the high frequency local–neighbourhood source signals exhibited limited correlation and high heterogeneity with respect to the central site. Traffic volume within a 2.5 km buffer explained 87% of the variability in the local–neighbourhood level signal observed between field sites while no significant association with traffic was found for the original particle number concentration data. This study has demonstrated that wavelet decomposition can be a useful tool for estimating exposure to UFP from local–neighbourhood and urban–regional scale sources and processes.

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.

Indoor exposure to air pollutants was assessed through 99 visits to 51 homes located in downtown high-rise buildings and detached houses in suburban and rural areas. The ambient concentrations of ultrafine particles (UFP), black carbon (BC), particulate matter smaller than 2.5 μm in diameter (PM2.5), and trace elements were concurrently measured at a central monitoring site in downtown Toronto. Median hourly indoor concentrations for all measurements were 4700 particles/cm3 for UFP, 270 ng/m3 for BC, and 4 μg/m3 for PM2.5, which were lower than ambient outdoor levels by a factor of 2–3. Much higher variability was observed for indoor UFP and BC across the homes compared to ambient levels, mostly due to the influence of indoor cooking emissions. Traffic emissions appeared to have a strong influence on the indoor background (i.e., outdoor-originated) concentrations of BC, UFP, and some trace elements. Specifically, 85% and 34% of the indoor concentrations of BC and UFP were predominantly from outdoor sources, respectively. Moreover, a positive correlation was observed between indoor concentrations of BC and UFP and total road length within a 300 m buffer zone. There was no significant decrease in indoor air pollution with increasing floor level among high-rise residences. In addition to the influence of outdoor sources on indoor air quality, indoor sources contributed to elevated concentrations of K, Ca, Cr, and Cu. A factor analysis was performed on trace elements, UFP, and BC in homes to further resolve possible sources. Local traffic emissions, soil dust, biomass burning, and regional coal combustion were identified as outdoor-originated sources, while cooking emissions was a dominant indoor source. This study highlights how outdoor sources can contribute to chronic exposure in indoor environments and how indoor activities can be associated with acute exposure to temporally varying indoor-originated air pollutants.

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 μg 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 μg 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 photobleaching 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% (±1σ) 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.

This study reports the diurnal, seasonal, and annual variation of ultrafine particle size distributions in downtown Toronto. The k-means clustering algorithm was applied to five years of size-resolved data for particles with diameters less than 100 nm. Continuous particle number concentrations were measured 16 m from a major arterial roadway between March 2006 and May 2011 using a Fast Mobility Particle Sizer. Eight particle size distribution (PSD) types were identified. The PSD types exhibited distinct weekday–weekend and diurnal patterns. The relative frequency that each PSD occurred varied with season and wind direction and was correlated with other pollutants. These temporal patterns and correlation helped in elucidating the sources and processes that each of the eight PSD represent. Finally, similar PSD types were observed in residential areas located 6 and 15 km away from the central monitoring site suggesting that these PSD types may be generalizable to other sites. Identification of PSD types was found to be a valuable tool to support the interpretation of PSD data so as to elucidate the sources and processes contributing to ultrafine particle concentrations.