Near-Road Air Pollutant Measurements: Accounting for Inter-Site Variability Using Emission Factors.

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 x, and particle number EFs (R2:0.50-0.75), with lower model performance for CO and black carbon (BC) EFs (R2:0.28-0.46). NO x 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.

Real-World Emission of Particles from Vehicles: Volatility and the Effects of Ambient Temperature.

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 (<0 °C), the volatile fraction of particles was 94%, but decreased to 85% during warmer periods (>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 findings demonstrate that significant differences exist between particles in thermally treated vehicle exhaust as compared to in real-world vehicle plumes to which populations in near-road environments are actually exposed. Furthermore, the magnitude of these differences are dependent upon season and may be more extreme in colder climates.

Field Measurements of Gasoline Direct Injection Emission Factors: Spatial and Seasonal Variability.

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.

Characterization of winter air pollutant gradients near a major highway.

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.

Elucidating long-term trends, seasonal variability, and local impacts from thirteen years of near-road particle size data (2006-2019).

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.

Quantifying metal emissions from vehicular traffic using real world emission factors.

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.

Comparing emission rates derived from a model with those estimated using a plume-based approach and quantifying the contribution of vehicle classes to on-road emissions and air quality.

This study presents a comparison of fleet average emission factor (s) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to carbon monoxide (CO), nitrogen oxides (NOx), and elemental carbon (EC) along an urban corridor. To this end, a field campaign was conducted over one week in June 2016 on an arterial road in Toronto, Canada. Traffic data were collected using a traffic camera and a radar, whereas air quality was characterized using two monitoring stations: one located at ground level and another at the rooftop of a four-story building. A traffic simulation model was calibrated and validated, and second-by-second speed profiles for all vehicle trajectories were extracted to model emissions. In addition, dispersion modeling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. The results indicate that modeled EFs for CO and NOx are twice as high as plume-based EFs. Besides, modeled results indicate that transit bus emissions accounted for 60% and 70% of the total emissions of NOx and EC, respectively. Transit bus emission rates in g/passenger·km for NOx and EC were up to 8 and 22 times, respectively, the emission rates of passenger cars. In contrast, the Toronto streetcars, which are electrically fueled, were found to improve near-road air quality despite their negative impact on traffic speeds. Finally, we observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background given that the study network is located in a busy downtown area. Implications: This study presents a comparison of fleet average emission factor (s) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to various pollutants. Besides, dispersion modeling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. It was observed that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background, as the study network is located in a busy downtown area.