GEM-MACH (Global Environment Multiscale Modelling Air quality and CHemistry) is an online chemical transport model driven by meteorological fields produced by the GEM numerical weather prediction model . The model was recently adapted to include the emission, advection and diffusion, deposition, and chemical degradation of benzene (BENZ) and seven PAHs: phenanthrene (PHEN), anthracene (ANTH), fluoranthene (FLRT), pyrene (PYR), benz[a]anthracene (BaA), chrysene (CHRY), and benzo[a]pyrene (BaP) . While BENZ in ambient air is gaseous, PAHs are semi-volatile species that are found in both the gas and particle phases. Their particle–gas partitioning in GEM-MACH-PAH is determined via the Dachs–Eisenreich scheme . Section I of the Supplement provides further information on PAH process representations within the model.

GEM-MACH-PAH was run at 2.5 km horizontal grid spacing on a domain that includes large North American urban areas such as Toronto, New York City, Chicago, Washington DC, Philadelphia, Boston, and Detroit (Fig. ).

Two time periods in 2009 were chosen (spring–summer, 13 May to 13 August, and fall–winter, 23 October to 5 January 2010) to balance the computational demands required for this model (IBM Power7 supercomputer) against the ability to examine seasonal differences and include evaluation data from a temporally coincident high-density campaign conducted in 2009 west of Toronto . Additional details about the model setup and run strategy are provided in the Supplement (Sect. I).

Hourly, gridded, and speciated input emission fields were prepared using the Sparse Matrix Operator Kernel Emissions system (SMOKE; https://www.cmascenter.org/smoke, last access: 6 March 2020, ), making use of criteria air pollutant emissions from Canada's 2010 APEI reported by province and US EPA 2011 NEI emissions reported at the county or tribal level. BENZ and PAHs were speciated relative to aggregate VOC emissions using VOC speciation profiles from the Canadian Emissions Processing System for BENZ and special speciation profiles developed by , and for PAHs. PAH emissions from on-road mobile sources were calculated from VOC emissions generated using MOBILE 6.2C and MOVES 2010b (https://www.epa.gov/moves/moves2014-and-moves2010b-versions-limited-current-use, last access: 6 March 2020) for Canada and the US, respectively. PAH species emissions were estimated using PAH-to-VOC and PAH-to-organic carbon emission ratios from MOVES2014 converted to a total organic gas (TOG) basis. Note that reported emission factors (EFs) for PAHs in the literature are highly variable. Different EFs were tested in the model but those from MOVES2014 achieved the best results compared to observations .

SMOKE uses spatial surrogate fields to distribute vehicle emissions reported for each jurisdiction (e.g., provinces in Canada, counties in the US) among model grid cells. Unlike the MOBILE 6.2C-based inventory for Canada, the MOVES2010b-based inventory for the US explicitly includes an “off-network” road type that accounts for emissions when vehicles are stationary (e.g., idle, parked, starting, or refuelling), and this road type contributes ∼60 % of on-road emissions (NEI2011). The effect of this spatial-allocation difference between the MOBILE and MOVES inventories on the modelled on-road vehicle contributions of BENZ and PAH is presented later in this work.

To construct the emissions fields for the no mobile case, emissions from all area sources, off-road mobile sources (e.g., trains, boats, snowmobiles, aircraft, etc.), and minor point sources present in the base case were retained, but all on-road vehicle emissions (of all species) were removed.

Detailed model descriptions and evaluations of GEM-MACH have been published for pollutants other than benzene and PAHs . The GEM-MACH-PAH base simulation used for the current study was previously evaluated in the most rigorous comparison to measurements yet published for such a model at fine spatial resolution . That evaluation compared GEM-MACH-PAH output to benzene and PAH measurements from 121 and 35 network sites, respectively, from Canada's National Air Pollution Surveillance program (NAPS), the US National Air Toxics Trends Stations (NATTS), and the Canada–US Integrated Atmospheric Deposition Network (IADN), which all record 24 h integrated air concentrations every one in six consecutive days, at locations associated with a variety of population densities and land uses (e.g., urban, suburban, industrial, and rural locations). Additional 2-week integrated PAH measurements from 46 sites in a high-spatial-density campaign conducted in Hamilton, Ontario, Canada, in spring–summer and fall–winter 2009 were also used to assess concentration variability within a city as well as within model grid squares (the Supplement, Sect. I).

Ratios of modelled-to-measured concentrations were generally within an order of magnitude of unity, with median values in spring–summer being lower for BENZ and PAHs with molecular weights of 178–202 g mol-1 (0.31–0.86) compared to PAHs with molecular weights of 228–252 g mol-1 (1.8–8.4). Fall–winter values were modestly higher (1.5–9.9) though still within an order of magnitude of unity. Further details can be found in . Modelled concentrations were found to be statistically unbiased relative to measurements (paired t test with t<1, p>0.01) for all compounds and seasons except for BaP in fall–winter , which was biased high. Model output for the latter compound and season combination was therefore excluded from this study. Fall–winter BENZ was also excluded from this study because of an important missing sector discovered in the fall–wintertime BENZ emissions. Please refer to the Supplement, Sect. I, for more information.

GEM-MACH-PAH's particle–gas partitioning parametrization was evaluated at six IADN stations, and the results showed a substantial improvement over the previous AURAMS-PAH partitioning due to an empirically based update in partitioning parameters .

The sensitivity of model results for partitioning and other parameters (e.g., oxidant concentrations) is examined in Sect.  and in the Supplement. Good overall performance of GEM-MACH-PAH has been demonstrated by comparison to measurements as discussed above, with more details in , and our sensitivity analyses further support the model's validity for calculating ambient concentrations and for assessing source contributions at its evaluated resolution (2.5 km grid size and seasonal timescale).

Modelled base case (all emissions activated) average airborne concentrations of BENZ, PHEN, PYR, and BaP are shown in Fig.  for the spring–summer and Fig. S2a in the Supplement for the fall–winter. The three PAH compounds exhibit a range of volatilities. PHEN and BaP are found predominantly in the gas and particle phases, respectively, whereas PYR, with a mid-range volatility, is typically found in both. The spatial distribution of concentrations is similar to the distribution of human population shown in Fig.  as expected from the prevalence of anthropogenic sources in the study area.

Modelled concentrations for BENZ and PAHs are higher in fall–winter than in spring–summer due to lower fall–winter temperatures and solar radiation. These factors lead to reduced photochemical degradation and increased vertical stability, which in turn induce less vertical mixing and dilution and lower boundary layer heights. Thus, ambient concentrations are higher per unit emission in fall–winter than in spring–summer. Additionally, total emissions for PAHs are higher in fall–winter than in spring–summer (Fig. S3a) due to increased on-road vehicle emissions (e.g., cold starts) and combined area and off-road mobile sources (e.g., heating, snowmobiling). Note that different rates of PAH oxidation in the different seasons are expected to lead to different rates of production of secondary products such as oxy- and nitro-PAHs. These secondary products are not yet included in GEM-MACH-PAH due to uncertainties in their sources and properties, but they are under consideration for future addition to the modelling package given that some of these compounds are more toxic than their parent PAHs.

Figures  and S2b (in the Supplement) show the contribution of on-road vehicles to ambient concentrations in the spring–summer and fall–winter, respectively, as represented by the absolute differences in concentrations between the base and no mobile cases. Concentrations in the no mobile case are significantly lower than those for the base case as expected from the lack of on-road vehicle emissions.

Major cities are prominent in Fig.  for all species as expected given the high urban traffic volumes. In the Greater Toronto Area (GTA), BENZ concentrations due to on-road vehicles in spring–summer are on the order of 0.1–0.3 µg m-3 (Fig. S4) and these values are similar to those of other urban centres in Ontario such as Hamilton. Spring–summer contributions up to 0.5–0.9 µg m-3 of BENZ are seen in the large urban centres of the US such as New York City, Chicago, and Washington DC (Fig. S4) as well as in several smaller US cities (Fig. ).

Spatial distributions of absolute on-road mobile source contributions for the PAHs are similar to those for BENZ. Spring–summer contributions in the GTA for PHEN, PYR, and BaP are approximately 2.0, 0.35, and 0.3 ng m-3, respectively, and slightly higher in fall–winter for the species reported in Fig. S2b. Absolute contributions from on-road vehicles are higher in the major US urban areas than they are in the Canadian cities (examples for BENZ and PYR shown in Fig. S4). These cross-border differences arise in part because of differences in the spatial surrogates mentioned above and the different emissions inventories (see Sect.  and the Supplement, Sect. IV). Furthermore, the cities in the US portion of the study region have populations that are larger on average than the cities in the Canadian portion, and concentrations of PAHs have been shown to increase in direct proportion to human population .

However, there are some geographically limited exceptions where the removal of on-road vehicle emissions causes PAH concentrations to increase slightly (areas with negative values in Fig. ): in the spring–summer there are small concentration increases in the northeastern portion of New York State and along the border between Virginia and West Virginia. These apparent anomalies are located where base PAH concentrations are already relatively low, and are consistent with the impacts on oxidant chemistry discussed below and in the Supplement (Sect. V). In fall–winter, PAH increases in the no mobile case are confined to two small regions near the domain borders (Fig. S2b), where factors other than the emission change may be responsible (e.g., boundary effects, numerical issues, etc.).

Nevertheless, measurements show that Ontario's annual ambient air quality criteria for BENZ (0.45 µg m-3) and BaP (0.01 ng m-3), the latter of which is used by the province as a surrogate for PAHs, are exceeded in Toronto, Hamilton, and Windsor . The absolute contributions of on-road vehicles in those areas (Fig. ) suggest that reducing their emissions could assist in reducing those exceedances. Policies and programs seek to achieve air quality benefits with minimal socioeconomic cost, thus knowledge of the relative (e.g., percent) contributions of different sources is an important criterion for prioritizing possible management actions. The reduction in on-road vehicle emissions will only be effective in achieving meaningful reductions in ambient concentrations if their local contributions are significant relative to the total.

The relative contributions (expressed as the percentage of the base case concentrations) of on-road vehicles to BENZ, PHEN, PYR, and BaP concentrations are shown as maps and frequency distributions of domain-wide ranges in Figs.  and , respectively, with maps for the remaining PAH species shown in Figs. S2c and S8. Domain-wide average and maximum values are also listed in Table  and shown in Fig. . Relative on-road vehicle contributions to PAH concentrations in individual model grid squares had maxima as high as 64 %–91 % in spring–summer. Maxima were slightly lower in fall–winter (49 %–72 %) for the subset of PAHs reported for that period (Figs.  and S2c, and Table ). Domain means, however, were higher in the fall–winter than in the spring–summer (Fig. , and Table ). The highest relative on-road vehicle contributions were observed in or near small cities such as North Bay, Ontario; Columbus and Toledo, Ohio; and Grand Rapids, Michigan, where major highways are found in areas of otherwise low ambient concentrations.

In the spring–summertime, domain-mean on-road vehicle contributions to ambient BENZ in the GTA were on the order of 14 %–37 %, consistent with, though slightly lower than, previously reported values due to the latter study including off-road mobile sources in their “mobile” category. PAH contributions in the GTA ranged from 5 % to 50 %, depending on species, season, and proximity to major highways. Even greater contributions were seen in other Canadian cities; thus, our results suggest that fewer and/or less extreme exceedances of provincial BENZ and PAH guidelines could be achieved by reductions in on-road vehicle emissions in cities within the model domain.

This finding is significant in the Canadian policy-making context and demonstrates the value of examining pollutant emissions and concentrations on fine geographic scales. The APEI and other Canadian efforts have estimated that PAH contributions from on-road mobile sources amount to 7 %–8 % of total anthropogenic PAH emissions at the national scale. (Provincial-scale estimates for BENZ and PAHs are not included in the APEI.) Such minor relative contributions at the national scale could lead to the neglect of the on-road mobile source category in emissions reduction strategies, yet we have shown that this category is important at the local scale in terms of impacts of potential BENZ or PAH management actions.

In the US, NEI emissions are reported at the county or tribal level. On-road vehicle contributions in those reported emissions are closer to this study's high-resolution results in ambient air than are the contributions in emissions reported at the national scale. Nonetheless, on-road vehicle contributions of BENZ and PAHs differ between emissions and ambient air due to physico-chemical processing that occurs in the atmosphere. Such processing varies with time of year and levels of vehicle co-pollutants as described below.

Though PAH emissions from on-road vehicles are higher in fall–winter than in spring–summer (Fig. S3a), the relative contribution of on-road vehicles to total emissions is stable among seasons (viz., domain-average differences between fall–winter and spring–summer emission contributions from on-road vehicles are -0.6% and range from -1.8% to +2.7% for species reported for both time periods; see Fig. S3b).

In contrast, relative on-road vehicle contributions to ambient concentrations differ more between seasons than do their emissions, with differences of +3% to +10%, respectively, between fall–winter and spring–summer (Fig. ). This suggests that a given relative reduction in on-road vehicle emissions may lead to greater concentration reductions in fall–winter than in spring–summer, and this highlights the importance of conducting analyses that represent conditions at different times of year. The following analysis expands on factors that are potentially responsible for this temporal variability.

GEM-MACH-PAH includes reactions of BENZ and PAHs with two oxidants: hydroxyl radical (OH, which reacts with BENZ and gaseous PAHs) and ozone (O3, which reacts only with particulate BaP) . As noted earlier, the no mobile case zeroed on-road vehicle emissions for all emitted chemical species, including precursors to tropospheric OH and O3, such as NOx, CO, and VOCs. Thus, the removal of vehicle emissions impacts not only the concentrations of the pollutants of BENZ and PAH directly, but also modifies the concentrations of the oxidants responsible for their chemical degradation.

In the spring–summer, the removal of on-road vehicle emissions of criteria air pollutants leads to OH reductions in most parts of the study region (Fig.  and red areas in Fig. S9a). Oxidative removal rates of BENZ and gaseous PAH are thus reduced in those parts of the domain as a result. This contributes to the finding that reductions in BENZ and PAH emissions of 10 %–27 % associated with the removal of the on-road mobile emissions (Fig. S3b) result in a domain-average concentration reduction to a lesser degree (4 %–21 %) (Table ). The removal of all mobile on-road emissions decreases oxidant concentrations; hence, BENZ and PAH from other sources are oxidized to a lesser degree, offsetting the reductions in BENZ and PAH associated with the mobile emissions removal itself. Conversely, OH increases by 10 %–50 % in some urban cores (e.g., Toronto, Detroit, New York City; blue areas in Fig. S9a) in the spring–summer when on-road vehicle emissions are removed, in response to higher O3 levels via reduced NOx titration, with a similar result over large portions of the study area in fall–winter (blue in Fig. S9b). At these times and locations, a positive feedback is produced, whereby the degradation of BENZ and gaseous PAHs from other sources is accelerated in areas where their emissions from vehicles have been removed.

Similarly, on-road vehicle emissions in spring–summer contribute to a domain-wide median of ∼10% (∼3.5 ppbv) to surface O3 volume mixing ratios (Fig. ). Thus, when vehicle emissions are removed, airborne BaP is reduced less than expected from the emissions reduction because of reduced oxidation of BaP from O3. However, in and around major cities, the changes in O3 due to on-road vehicles are smaller than 10 %, and they are often negative (see blue in Fig. S9c), viz., O3 increases in response to the removal of NOx from on-road vehicles in this hydrocarbon-limited regime , thus increasing oxidation of BaP from non-mobile sources. The no mobile case degradation of BaP is thus enhanced in urban areas. This leads to net urban BaP reductions that are greater than might be expected from the removal of urban BaP on-road vehicle emissions alone.

PAHs are semi-volatile and their mass is therefore partitioned between the gas and particle phases in ambient air. Particulate fraction (PF) , the ratio of the particulate concentration to the total (gaseous + particulate) concentration, is a common descriptor of particle–gas partitioning. Smaller, lighter PAHs have small PFs of about 0 (e.g., for PHEN), whereas larger, heavier PAHs have PFs around 1 (e.g., for BaP), and semi-volatile PAHs like FLRT and BaA fall somewhere in the middle (Fig. a, c). The extent of PAH partitioning varies with temperature and with the availability and composition of particulate matter (PM), where the latter is affected by the zeroing of on-road vehicle emissions as discussed below.

On-road mobile source contributions to domain-averaged PM were 7 % in spring–summer and 10 % in fall–winter (Figs.  and S9e and f), lower than those for total (gaseous + particulate) PAHs. This suggests that PAH PFs might rise; that is, a greater relative amount of the PAH might partition to the particulate phase if on-road mobile source emissions were reduced, because relatively more PM would be available per unit mass of remaining PAH. However, decreases in PAH PFs were observed in the no mobile case (Fig. b, d–f). This was due to the nature of partitioning, which is specific to PM speciation. Elemental carbon (EC) is the prime sorbent for PAHs in the particle–gas partitioning parameterization in the model . The on-road vehicle contributions of EC averaged 27 % of total EC mass in both seasons (Figs.  and S9g and h). Relative to the base case, EC in the no mobile case was thus reduced to a greater extent than PAH due to the high EC fraction of PM emissions from motor vehicles. This in turn, resulted in the particle–gas partitioning equilibrium being shifted toward the gas phase since less EC mass was available to sorb the remaining PAH. Shifts in particle–gas equilibrium in turn affect removal processes such as deposition and degradation, whose mechanisms differ for gaseous and particulate compounds . Further analysis of the differences in PAH lifetimes that arise from a shift in particle–gas partitioning is beyond the scope of this paper, but it should be kept in mind for future analyses, particularly those that incorporate considerations of transboundary or long-range transport.

The results described thus far have shown that on-road vehicle emissions contribute substantially to benzene and PAHs in ambient air at a variety of locations in our study area. Differences between seasonal vehicle contributions have been examined with respect to the atmospheric processing that transforms toxic pollutants after they have been emitted to the air. Potential sensitivities of our model results to the uncertainties in emissions and atmospheric chemistry are explored in this section, and they are described in more detail in the Supplement (Sect. V).

We expect that the largest contribution to uncertainty in our results to be associated with the PAH mobile emissions. The on-road vehicle EFs for PAHs that underlay this study's inventory were taken from MOVES2014b . These factors were determined from two US reports that examined gasoline and diesel emissions separately . We carried out four sensitivity simulations with GEM-MACH-PAH with the BENZ and PAH emissions from on-road vehicles scaled by factors of 0.5 and 2 in both seasons. This range corresponds approximately to the 25th and 75th percentiles of the range of EFs reported in the recent peer-reviewed literature . The model responded consistently to on-road vehicle emission scaling with average changes to the vehicle contribution amount of -5 % to -10 % and +20 % to +30 %, depending on species, for halved and doubled vehicle emissions, respectively (compare Tables  and ). This finding suggests that the relative importance of vehicle contributions when different EFs are used remains consistent with our current results across a broad range of emissions levels. This topic is described in more detail in the Supplement (Sect. V).

Whereas the effects of emissions perturbations are straightforward to evaluate, uncertainties that arise from atmospheric chemistry are complex to assess, because they result from secondary formation processes for atmospheric oxidants. A reduction in precursor emissions yields a non-linear change in oxidant concentrations that depends on chemistry and the physical state of the atmosphere at each location. The removal of on-road vehicle emissions induces a large range of changes in oxidant concentrations (Figs.  and S9). The resulting changes in BENZ and PAH concentrations as a function of changes in oxidant concentration are highly variable (e.g., Figs. S5 and S6), and some geographic areas see a net increase in PAH concentrations because reduced atmospheric oxidation of PAHs overwhelms the effect of removing vehicle emissions. However, such results were uncommon throughout the study area. For a reactive PAH such as pyrene, for example, 88.3 % and 99.9 % of model grid squares in spring–summer and fall–winter, respectively, responded to the removal of vehicle emissions with reductions in ambient PAH concentrations. Relatively unreactive benzene, on the other hand, responded to emissions reductions with ambient concentration reductions in all model grid squares.

The removal of on-road vehicle emissions would lead not only to reductions in ambient benzene and PAH concentrations (as well as in other pollutants), as demonstrated by our model results, but also to reductions in human exposure. Proximity to roadways and traffic has been linked to elevated exposure outdoors, and this has led to particular concerns for commuters . Further inhalation exposure to traffic pollutants occurs in indoor environments, where infiltration of outdoor air can contribute a substantial proportion of benzene and PAH exposure , adding to concerns about residences, schools, and workplaces that are situated near roadways.

PAH species vary in toxicity, and their mixture is often represented as a toxic equivalent concentration (TEQ), which is the sum of contributing compound concentrations that have been normalized by their carcinogenic potencies relative to BaP . The percent reduction in TEQ when on-road vehicle emissions were removed (Fig. ) averaged 19 % across the domain. The magnitudes and geographic distribution of these TEQ reductions closely follow the reductions in simulated PAH concentrations, implying a direct toxicity benefit of mobile emissions reductions. For large urban areas and their suburbs, where both ambient concentrations and human population density are high, results herein suggest that TEQs could be reduced by values of 20 %–60 % if vehicle emissions were removed. Maximum TEQ reductions of up to ∼80 % were predicted for some rural and suburban locations near highways (e.g., North Bay, ON; Sudbury, ON; Grand Rapids, MI; and Maumee, OH).

Benzene has not been assigned a BaP toxic equivalency factor in the available literature. However, the combination of its modelled concentration and its human toxicity potential , which are approximately 1000 times larger and smaller than those of BaP, respectively, suggests that reductions in traffic emissions would lead to similar reductions in risk for benzene as for PAHs.

Further connection of the results of this study to potential human health benefits will require careful attention to the interplay between air toxics and criteria air contaminants, since these are not often considered together in air quality research. The development, evaluation, and first application of GEM-MACH-PAH makes such work possible. Another priority for future research is the improvement of emissions inventories and model process representations.