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.

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Abstract. This study evaluates a deployment strategy of a heavily instrumented mobile lab for characterizing multipollutant spatial patterns based upon a limited number of measurement days spread over different seasons. The measurements obtained through this deployment strategy are used to gain insight into average pollutant levels between routine monitoring sites and in relation to emission sources in the region, as well as to assess correlations between pollutant patterns to better understand the nature of urban air pollutant mixtures. A wide range of locations were part of the deployment in order to characterize the distribution of chronic exposures potentially allowing development of exposure models. Comparison of the mobile lab averages to the available adjacent air quality monitoring network stations to evaluate their representativeness showed that they were in reasonable agreement with the annual averages at the monitoring sites, thus providing some evidence that, through the deployment approach, the mobile lab is able to capture the main features of the average spatial patterns. The differences between mobile lab and network averages varied by pollutant with the best agreement for NO 2 with a percentage difference of 20 %. Sharp differences in the average spatial distribution were found to exist between different pollutants on multiple scales, particularly on the sub-urban scale, i.e., the neighborhood to street scales. For example, NO 2 was observed to be 210-265 % higher by the main highway in the study region compared to the nearby urban background monitoring site, while black carbon was higher by 180-200 % and particle number concentration was 300 % higher. The repeated measurements of near-roadway gradients showed that the rate of change differed by pollutant with elevated concentrations detected up to 600-700 m away for some pollutants. These results demonstrate that through systematic deployment mobile laboratory measurements can be used to characterize average or typical concentration patterns, thus providing data to assess monitoring site representativeness, spatial relationships between pollutants, and chronic multipollutant exposure patterns useful for evaluating and developing exposure models for outdoor concentrations in an urban environment.

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.

Four field campaigns were conducted between February 2014 and January 2015 to measure emissions from light-duty gasoline direct injection (GDI) vehicles (2013 Ford Focus) in an urban near-road environment in Toronto, Canada. Measurements of CO2, CO, NOx, black carbon (BC), benzene, toluene, ethylbenzene-xylenes (BTEX), and size-resolved particle number (PN) were recorded 15 m from the roadway and converted to fuel-based emission factors (EFs). Other than for NOx and CO, the GDI engine had elevated emissions compared to the Toronto fleet, with BC EFs in the 73rd percentile, BTEX EFs in the 80-90th percentile, and PN EFs in the 75th percentile during wintertime measurements. Additionally, for three campaigns, a second platform for measuring PN and CO2 was placed 1.5-3 m from the roadway to quantify changes in PN with distance from point of emission. GDI vehicle PN EFs were found to increase by up to 240% with increasing distance from the roadway, predominantly due to an increasing fraction of sub-40 nm particles. PN and BC EFs from the same engine technology were also measured in the laboratory. BC EFs agreed within 20% between the laboratory and real-world measurements; however, laboratory PN EFs were an order of magnitude lower due to exhaust conditioning.

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, NO , and particle number EFs (R:0.50-0.75), with lower model performance for CO and black carbon (BC) EFs (R:0.28-0.46). NO and BC EFs were affected more than CO and particle number EFs by the fraction of larger vehicles, which also resulted in measurable weekday/weekend differences. Pollutant EFs also varied with ambient temperature and because there were little seasonal changes in fleet composition, this was attributed to changes in fuel composition and/or post-tailpipe transformation of pollutants.

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