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Near-Road Air Pollutant Measurements: Accounting for Inter-Site Variability Using Emission Factors
Abstract
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 twenty 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 inter-site 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 inter-site 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 (R²:0.28-0.46). NOx 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 was little seasonal changes in fleet composition, this was attributed to changes in fuel composition and/or post-tailpipe transformation of pollutants.
... The SOCAAR facility (43.6589, −79.3954) was located about 15 m from College Street and 3 m above the ground. College Street has a traffic volume of ∼17,200 vehicles per day, 96% of which are lightduty gasoline vehicles (Hilker et al., 2021;Wang et al., 2018 ...
... Thus, the background signal is often associated with regional concentrations, while the local signal is associated with nearby emissions. Other studies have previously applied this concept to separate local and background UFP levels (Klems et al., 2010;Sabaliauskas et al., 2014;Hilker et al., 2019;Wang et al., 2018). ...
... The local and background 1-min time resolution UFP, BC, NO , and 2.5 concentrations were calculated using the rolling minima method, originally developed by Wang et al. (2018) and further validated by Hilker et al. (2019). In this algorithm, a background signal is calculated by averaging the spline of minima. ...
... • The pseudo-wavelet method devised by Wang et al. (2018). ...
... 4. For applications where both upwind measurements and a suitable urban background station are both 670 unavailable or too costly, we suggest applying one of the frequency methods described here, particularly the pseudo-wavelet method developed by Wang et al. (2018) or the rolling ball algorithm. For these frequency methods, in roadway applications we suggest using hyperparameters like those identified here in Table K.1. ...
... While the context of our tests here were up-and down-wind differences targeting a single roadway emissions source, the theoretical basis of frequency methodsthat background concentrations 680 vary on a longer time-scale than local emissionsextends these methods to pollution concentrations regardless of proximity to one particular source. The pseudo-wavelet method applied in this context is also touched upon by Wang et al. (2018) and Hilker et al. (2019). ...
To accurately study the characteristics of an air pollution emitter, it is necessary to isolate the contribution of that emitter to total measured pollution concentrations. A variety of published methods exist to complete this task, like placing measurements upwind the emitter, employing a distant background measurement station, or algorithmic methods that extract a background from the time-series of measured concentrations (e.g., wavelet decomposition). In this study, we measured nitrogen oxides (NOx), carbon monoxide (CO), carbon dioxide (CO2), and fine particulate matter (PM2.5) at four sites spanning Toronto, Ontario, Canada. We first characterized the spatial variability of background concentrations across the city, and then tested the accuracy of seven different algorithmic methods of estimating true measured upwind-of-emitter backgrounds near Toronto’s Highway 401 by using the data collected at a downwind site. These methods included time-series and regression methods, including machine learning (XGBoost). We observed background concentrations had notable spatial variability, except for PM2.5. When predicting backgrounds upwind the highway, we found a distant measurement station provided an accurate background only during some times of day and was least accurate during rush hours. When testing algorithmic predictions of upwind-of-highway backgrounds, we found that regression models outperformed time-series methods, with best predictions having R2 exceeding 0.75 for all four pollutants. Despite the better performance of regression models, time-series methods still provided reasonable estimates; we also found that emitter-specific covariates (e.g. traffic counts, onsite dispersion modelling) did not play an important role in regressions, suggesting backgrounds can be well-characterized by time of day, meteorology, and distant measurement stations. Based on our results, we provide ranked recommendations for choosing background estimation methods. We suggest future air pollution research characterizing individual emitters include careful consideration of how background concentrations are estimated.
... Further studies examining the European vehicle fleet found declining mobile NO x emissions with rising ambient temperatures in light-duty diesel vehicles (Grange et al., 2019;Weber et al., 2019). Some publications suggest that mobile BC emissions peak at the highest ambient temperatures in diesel-fueled vehicles (Book et al., 2015;Chen et al., 2001;Kondo et al., 2006) and in "measureable emitters" (Wang et al., 2018). Other studies found little seasonal difference in the contribution of total PM 2.5 mass concentration from diesel vehicles (Kim and Hopke, 2012); gasoline-powered vehicles may even emit higher BC emissions at colder temperatures, such as during cold-starts (Schauer et al., 2008). ...
... The ΔCO/ΔCO 2 analysis presented in Table 3 shows no significant effect considering all hours; however, we observe higher ratios on weekends and during the afternoon rush hour in April 2020 than in previous years. A plausible explanation for this observation is that vehicles emit more CO at high speeds (Hickman et al., 1999;OECD & ECMT, 2006;Wang et al., 2018;Fig. S7). ...
... Previous studies reported a seasonal cycle in observed ΔBC/ΔCO at suburban and urban sites, with higher ΔBC/ΔCO emission ratios in the summer than in the winter (Chen et al., 2001;Kondo et al., 2006). Additionally, Wang et al. (2018) found higher BC fuel-based emission factors (mg BC kg − 1 fuel ) in the spring-summer than in the fall-winter using observations collected adjacent to a four-lane highway in Toronto, Canada. A similar seasonal pattern is evident at the I-95 NR site. ...
Vehicles are a major source of anthropogenic emissions of carbon monoxide (CO), nitrogen oxides (NOx), and black carbon (BC). CO and NOx are known to be harmful to human health and contribute to ozone formation, while BC absorbs solar radiation that contributes to global warming and also has negative impacts on human health and visibility. Travel restrictions implemented during the COVID-19 pandemic provide researchers the opportunity to study the impact of large, on-road traffic reductions on local air quality. Traffic counts collected along Interstate-95, a major eight-lane highway in Maryland (US), reveal a 60% decrease in passenger car totals and an 8.6% (combination-unit) and 21% (single-unit) decrease in truck traffic counts in April 2020 relative to prior Aprils. The decrease in total on-road vehicles led to the near-elimination in stop-and-go traffic and a 14% increase in the mean vehicle speed during April 2020. Ambient near-road (NR) BC, CO, NOx, and carbon dioxide (CO2) measurements were used to determine vehicular emission ratios (ΔBC/ΔCO, ΔBC/ΔCO2, ΔNOx/ΔCO, ΔNOx/ΔCO2, and ΔCO/ΔCO2), with each ratio defined as the slope value of a linear regression performed on the concentrations of two pollutants within an hour. A decrease of up to a factor of two in ΔBC/ΔCO, ΔBC/ΔCO2, ΔNOx/ΔCO2, and in the fraction of on-road diesel vehicles from weekdays to weekends shows diesel vehicles to be the dominant source of BC and NOx emissions at this NR site. We estimate up to a 70% reduction in BC emissions in April 2020 compared to earlier years, and attribute much of this to lower diesel BC emissions resulting from improvements in traffic flow and fewer instances of acceleration and braking. Future efforts to reduce vehicular BC emissions should focus on improving traffic flow or turbocharger lag within diesel engines. Inferred BC emissions from the NR site also depend on ambient temperature, with an increase of 54% in ΔBC/ΔCO from -5 to 20 °C during the cold season, similar to previous studies that reported increasing BC emissions with rising temperature. The default setting of MOVES3, the current version of the mobile emission model used by the US EPA, does not adjust hot-running BC emissions for ambient temperature. Future work will focus on improving the accuracy of mobile emissions in air quality modeling by incorporating the effects of temperature and traffic flow in the system used to generate mobile emissions input for commonly used air quality models.
... Emission factors (EF) were calculated to investigate the influence of ambient temperature ranges on the amount of NO x and UFP emitted per kilogram of fuel used by vehicles. The fuel-based EF is also useful in accounting for dilution that occurs between the tailpipe and sampling location (Wang et al., 2018a), and how this might be influenced by wintertime meteorology. ...
... where EF (g kg-fuel −1 or # kg-fuel −1 ) is the mass (g) or particle number (#) of pollutant P emitted per kilogram of fuel burned assuming almost all of the carbon in the fuel is oxidized to CO 2 and CO, Δ[P] is the background subtracted concentration of pollutant P (in g m −3 or # m −3 ), Δ[CO] and Δ[CO 2 ] are background-subtracted amount of carbon combustion products (in kg-carbon m −3 , kg m 3 Â molar mass carbon molar mass CO2 or CO ð Þ ) at NR10, and w c = 0.86 (kg-carbon kg-fuel −1 ) the carbon mass fraction of a mixed-fuel fleet (Ban-Weiss et al., 2010). The mean EFs for NO x , CO, BC, and UFP were 3.1 g kg-fuel −1 , 8.6 g kg-fuel −1 , 56 mg kg-fuel −1 , 2.4 × 10 15 # kgfuel −1 , respectively, which compared well with a previous EF study at the same site (Wang et al., 2018a). The EFs for NO x and UFP increased from 2.0 to 4.1 g kg-fuel −1 and 1.0 × 10 15 to 3.9 × 10 15 # kg-fuel −1 , respectively, as the average temperature decreased from 9 to −9°C (Fig. 4b). ...
... The EFs for NO x and UFP increased from 2.0 to 4.1 g kg-fuel −1 and 1.0 × 10 15 to 3.9 × 10 15 # kg-fuel −1 , respectively, as the average temperature decreased from 9 to −9°C (Fig. 4b). The enhanced NO x and UFP emissions under colder temperatures are consistent with past studies that found higher concentrations and emission factor of UFP during colder months (Wang et al., 2018a;Wang et al., 2018b). This distinct temperature dependency of UFP can be explained by the dynamic post-tailpipe processes of vehicle emissions. ...
Traffic-related air pollutants (TRAP) including nitric oxides (NO), nitrogen oxides (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.
(Here is a share link to download the paper by Sep 30, 2022, https://authors.elsevier.com/a/1fZRyB8ccupAQ)
... Emission factors (EF) were calculated to investigate the influence of ambient temperature ranges on the amount of NO x and UFP emitted per kilogram of fuel used by vehicles. The fuel-based EF is also useful in accounting for dilution that occurs between the tailpipe and sampling location (Wang et al., 2018a), and how this might be influenced by wintertime meteorology. ...
... where EF (g kg-fuel −1 or # kg-fuel −1 ) is the mass (g) or particle number (#) of pollutant P emitted per kilogram of fuel burned assuming almost all of the carbon in the fuel is oxidized to CO 2 and CO, Δ[P] is the background subtracted concentration of pollutant P (in g m −3 or # m −3 ), Δ[CO] and Δ[CO 2 ] are background-subtracted amount of carbon combustion products (in kg-carbon m −3 , kg m 3 Â molar mass carbon molar mass CO2 or CO ð Þ ) at NR10, and w c = 0.86 (kg-carbon kg-fuel −1 ) the carbon mass fraction of a mixed-fuel fleet (Ban-Weiss et al., 2010). The mean EFs for NO x , CO, BC, and UFP were 3.1 g kg-fuel −1 , 8.6 g kg-fuel −1 , 56 mg kg-fuel −1 , 2.4 × 10 15 # kgfuel −1 , respectively, which compared well with a previous EF study at the same site (Wang et al., 2018a). The EFs for NO x and UFP increased from 2.0 to 4.1 g kg-fuel −1 and 1.0 × 10 15 to 3.9 × 10 15 # kg-fuel −1 , respectively, as the average temperature decreased from 9 to −9°C (Fig. 4b). ...
... The EFs for NO x and UFP increased from 2.0 to 4.1 g kg-fuel −1 and 1.0 × 10 15 to 3.9 × 10 15 # kg-fuel −1 , respectively, as the average temperature decreased from 9 to −9°C (Fig. 4b). The enhanced NO x and UFP emissions under colder temperatures are consistent with past studies that found higher concentrations and emission factor of UFP during colder months (Wang et al., 2018a;Wang et al., 2018b). This distinct temperature dependency of UFP can be explained by the dynamic post-tailpipe processes of vehicle emissions. ...
... Basic site information and the sampling periods are summarized in Table 1. Detailed descriptions of the NR-TOR and NR-VAN sites is provided in previous publications [40,42,47]. Samples were also collected at nearby background sites in Toronto (BG-TOR) and in Vancouver (BG-VAN), located away from roads. ...
... For the near-road sites, the wind frequently came from the direction of the roadway, with higher wind speeds observed at NR-VAN. The mean (range) ambient temperature and relative humidity during this period were +10 ± 11 • C (−25 to +35 • C) and 63 ± 16% for Toronto, respectively, and +12 ± 7 • C (−8 to +33 • C) and 72 ± 16% for Vancouver, respectively [47]. ...
... Basic site information and pling periods are summarized in Table 1. Detailed descriptions of the NR-TOR VAN sites is provided in previous publications [40,42,47]. Samples were also col nearby background sites in Toronto (BG-TOR) and in Vancouver (BG-VAN), locat from roads. ...
Traffic is a significant pollution source in cities and has caused various health and environmental concerns worldwide. Therefore, an improved understanding of traffic impacts on particle concentrations and their components could help mitigate air pollution. In this study, the characteristics and sources of trace elements in PM2.5 (fine), and PM10-2.5 (coarse), were investigated in dense traffic areas in Toronto and Vancouver, Canada, from 2015–2017. At nearby urban background sites, 24-h integrated PM samples were also concurrently collected. The PM2.5 and PM10-2.5 masses, and a number of elements (i.e., Fe, Ba, Cu, Sb, Zn, Cr), showed clear increases at each near-road site, related to the traffic emissions resulting from resuspension and/or abrasion sources. The trace elements showed a clear partitioning trend between PM2.5 and PM10-2.5, thus reflecting the origin of some of these elements. The application of positive matrix factorization (PMF) to the combined fine and coarse metal data (86 total), with 24 observations at each site, was used to determine the contribution of different sources to the total metal concentrations in fine and coarse PM. Four major sources were identified by the PMF model, including two traffic non-exhaust (crustal/road dust, brake/tire wear) sources, along with regional and local industrial sources. Source apportionment indicated that the resuspended crustal/road dust factor was the dominant contributor to the total coarse-bound trace element (i.e., Fe, Ti, Ba, Cu, Zn, Sb, Cr) concentrations produced by vehicular exhaust and non-exhaust traffic-related processes that have been deposited onto the surface. The second non-exhaust factor related to brake/tire wear abrasion accounted for a considerable portion of the fine and coarse elemental (i.e., Ba, Fe, Cu, Zn, Sb) mass at both near-road sites. Regional and local industry contributed mostly to the fine elemental (i.e., S, As, Se, Cd, Pb) concentrations. Overall, the results show that non-exhaust traffic-related processes were major contributors to the various redox-active metal species (i.e., Fe, Cu) in both PM fractions. In addition, a substantial proportion of these metals in PM2.5 was water-soluble, which is an important contributor to the formation of reactive oxygen species and, thus, may lead to oxidative damage to cells in the human body. It appears that controlling traffic non-exhaust-related metals emissions, in the absence of significant point sources in the area, could have a pronounced effect on the redox activity of PM, with broad implications for the protection of public health.
... Ambient air pollution in urban areas has been known to cause adverse health effects (Krecl et al., 2018), visibility degradation, and global climate change (Singh et al., 2020;Zhang et al., 2017). Road transport emissions, in particular, are the major contributor in urban areas leading to poor air quality (Martinet et al., 2019;Yazdi et al., 2015;Wang et al., 2018aWang et al., , 2018b. Exposure to elevated concentrations of traffic-related air pollutants (TRAP) could cause respiratory and cardiovascular disease (Ning et al., 2008;Wang et al., 2018b), increased risk of asthma, and lung cancer (Yazdi et al., 2015). ...
... Those residing near the roadways (Yazdi et al., 2015), daily commuters, traffic police personnel, and pedestrians are more prone to traffic-related health effects . In the USA and Canada, 19% and 54% of the population live within 500 m of a major roadway (Wang et al., 2018a(Wang et al., , 2018b and it is likely more in countries with higher urban densities, such as India. ...
... But it is quite difficult to capture the emissions from the targeted vehicle/s due to a lot of heterogeneity and congestion in the traffic in most of the low-and middle-income countries. Other real-world methods are fixed-site measurements inside road-tunnels (Abdallah et al., 2020;Gaga et al., 2018;Lawrence et al., 2016;Mancilla et al., 2012;Smit et al., 2017) and road-side locations (Charron et al., 2019;Krecl et al., 2018;Martinet et al., 2019;Ning et al., 2008;Wang et al., 2018aWang et al., , 2018b. Roadway tunnel measurements capture the emissions in the confined environment from the entire fleet including an exhaust and non-exhaust sources. ...
This study develops real-world vehicular fleet emissions factors (EFs) through twin-site measurements for the first time in India. Real-time PM2.5, black carbon (BC), CO, and CO2, and gravimetric PM2.5 and PM10 were simultaneously measured at the kerbside and a background location in Mumbai. Particulate matter was further characterized for metals, carbonaceous constituents and morphology. The measured fleet average (±SD) EFs of PM2.5,
PM2.5–10, and PM10 were 435 (±312), 774 (±259), and 1028 (±403), while for BC and CO it was 184 (±48) and 15,000 (±2000) mg (kg of fuel)⁻¹, respectively. The EFOC and EFEC were 182 (±116) and 137 (±54) mg (kg of fuel)⁻¹, while the EFmetals in PM2.5 and PM10, were 57 and 96 mg (kg of fuel)⁻¹, respectively. The EFcoarse PM was ~1.8 times higher than EFPM2.5, suggesting the dominance of non-exhaust vehicular sources. The estimated uncertainties for the measured vehicular EF of CO, PM, and its chemical constituents ranged 44–128%. Traffic composition, temperature and humidity significantly affect the measured EFs which likely contributed to the uncertainty. These EFs would be useful for building a more accurate vehicular emission inventory and thus helping in urban air quality management, and also as inputs to climate models and policymaking.
... Upon obtaining a split between these local and urban background concentrations, a multilinear regression (MLR) model was applied to each time-series using the aforementioned air pollutants and meteorological parameters. Wang et al. (2018a). This receptor location is within a shallow urban canyon (building heights of 20 m and a street width of 40 m; aspect ratio of 0.5); as such, vehicle emissions often become entrained and recirculate within the canyon, occasionally leading to enhanced concentrations and pollutant residence times (Oke, 1988). ...
... Particle concentrations were background-subtracted using an algorithm originally described in Wang et al. (2018a). For each bin diameter, D p , a baseline-determining function, ψ, was applied to a vector of particle concentrations, n Dp , yielding a baseline vector, b Dp : ...
... Since the SOCAAR facility is near a major arterial roadway, much of the NO x that is measured is attributable to on-road traffic (Wang et al., 2018a;Hilker et al., 2019). Hence, the observed reduction in NO x concentrations over the past years is likely attributable to improvements in NO x emissions control technologies and the gradual removal of highly-emitting vehicles from the fleet. ...
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.
... A secondary advantage of EFs is the normalization of a pollutant with CO 2 emitted by vehicles, thereby accounting for variation in dilution, dispersion, and wind direction. In terms of near-road air quality monitoring networks, EFs represent a useful tool in quantifying vehicle fleet emissions for a variety of site types and conditions (Wang et al., 2018). ...
... CO 2 , local meteorological, and traffic data were averaged to hourly resolution to match the Xact metals data at each site. The background calculation algorithm used is described in detail in Wang et al. (2018) and was previously evaluated for CO 2 , NO, NO x , particle number (PN), and BC using coincident urban and background measurements. Measurements from periods where the background site was upwind of the nearroad site with minimal influence from emissions in the city were chosen: 1) for NR-Tor vs. Bkg-TorS (80e150 ) and 2) for NR-H401 vs. Bkg-TorN (0e60 and 300e360 ). ...
... The real world fuel-based EF calculation method through daily integration has been described in more detail in Wang et al. (2018). Briefly, a linear spline interpolation of minima for each 8-h segment was used to determine the background signal of each pollutant. ...
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.
... The SOA yield of China V vehicle exhaust is the highest among the emission standards, while the China VI vehicle is the lowest. This trend is different from that reported by Zhao et al., which [10,20), [20,30), [30,40), [40,50), [60,70) showed that the SOA yield varied less across the different emission standards 31 . Such discrepancy may be caused by the experimental conditions, e.g., seed aerosol control. ...
... MW CO2 , MW CO , and MW C are the molecular weights of CO 2 , CO, and carbon, respectively. C f denotes the carbon mass fraction of fuel, adopted to be 0.86 10,60 . ...
Vehicle emission is a major source of atmospheric secondary organic aerosols (SOA). Driving condition is a critical influencing factor for vehicular SOA production, but few studies have revealed the dependence on rapid-changing real-world driving conditions. Here, a fast-response oxidation flow reactor system is developed and deployed to quantify the SOA formation potential under transient driving conditions. Results show that the SOA production factor varies by orders of magnitude, e.g., 20–1500 mg kg-fuel ⁻¹ and 12–155 mg kg-fuel ⁻¹ for China V and China VI vehicles, respectively. High speed, acceleration, and deceleration are found to considerably promote SOA production due to higher organic gaseous emissions caused by unburned fuel emission or incomplete combustion. In addition, China VI vehicles significantly reduce SOA formation potential, yield, and acceleration and deceleration peaks. Our study provides experimental insight and parameterization into vehicular SOA formation under transient driving conditions, which would benefit high time-resolved SOA simulations in the urban atmosphere.
... Kozawa et al (2014) reported smaller BC EFs in September (15 ± 11 mg kg fuel −1 ) than in May (21 ± 15 mg kg fuel −1 ) at a freeway in California in 2010, however, the difference between the years was even larger as in 2011 BC EF was larger in June (67 ± 31 mg kg fuel −1 ) than in September (54 ± 6 mg kg fuel −1 ). Wang et al (2018) have studied the temperature dependency in more detail and found that BC EF increased with increasing ambient temperature that was opposite trend to CO, NO x and particle number EFs. In contrast, Li et al (2020) measured slightly larger EC EFs in winter than in spring both for HD (winter 197 ± 41 mg kg fuel −1 , spring159 ± 34 mg kg fuel −1 ) and light duty vehicles (winter 24 ± 5.5 mg kg fuel −1 , spring 16 ± 4.5 mg kg fuel −1 ) in a tunnel in Pittsburgh. ...
... BC EFs have been measured also separately at weekdays and weekends and at different diurnal hours but in those cases the driving force for the differences has typically been different contributions of heavy and light duty vehicles (e.g. Krecl et al 2018, Wang et al 2018. BC EFs have also been noticed to depend on the operating modes of the vehicles which are affected e.g. by the slope of the road; Mancilla and Mendoza (2012) determined EC EF for the traffic in uphill and downhill bores of a tunnel in Mexico, the EC EF being larger for the traffic in uphill bore (8.9 ± 2.1 mg km −1 ) than for the traffic in downhill bore (2.5 ± 2.1 mg km −1 ) for total vehicle fleet. ...
Particulate black carbon (BC) affects global warming by absorbing the solar radiation, by affecting cloud formation, and by decreasing ground albedo when deposited to snow or ice. BC has also a wide variety of adverse effects on human population health. In this article we reviewed the BC emission factors (EF) of major anthropogenic sources, i.e., traffic (incl. marine and aviation), residential combustion, and energy production. We included BC EFs measured directly from individual sources and EFs derived from ambient measurements. Each source category was divided into sub-categories to find and demonstrate systematical trends, such as the potential influence of fuel, combustion technologies, and exhaust / flue gas cleaning systems on BC EFs. Our review highlights the importance of society level emission regulation in BC emission mitigation; a clear BC emission reduction was observed in ambient studies for road traffic as well as in direct emission measurements of diesel-powered individual vehicles. However, the BC emissions of gasoline vehicles were observed to be higher for vehicles with direct fuel injection techniques (GDI) than for vehicles with port-fueled injection (PFI), indicating potentially negative trend in gasoline vehicle fleet BC EFs. In the case of shipping, a relatively clear correlation was seen between the engine size and BC EFs so that the fuel specific BC EFs of the largest engines were the lowest. Regarding the BC EFs from residential combustion, we observed large variation in EFs, indicating that fuel type and quality as well as combustion appliances significantly influence BC EFs. The largest data gaps were in EFs of large-scale energy production which can be seen crucial for estimating global radiative forcing potential of anthropogenic BC emissions. In addition, much more research is needed to improve global coverage of BC EFs. Furthermore, the use of existing data is complicated by different emission factor calculation methods, different units used in reporting and by variation of results due to different experimental setups and BC measurement methods. In general, the conducted review of BC emission factors is seen to significantly improve the accuracy of future emission inventories and the evaluations of the climate, air quality, and health impacts of anthropogenic BC emissions.
... The baseline algorithm (adapted from Wang et al. (2018)) works by finding the local minimum value and performing interpolation in a user-defined time window. We also developed a few extra features to optimize the baseline estimation. ...
... Fig. 4. Flowchart demonstrating operation of baseline function. This is an implementation of the algorithm presented in Wang et al. (2018). each pollutant individually in the ''user_defined_settings.ini'' file. ...
The deployment of a mobile air quality monitoring laboratory requires advanced real-time instrument monitoring and data management software, which can be prohibitively expensive. In this work we present the PLUME Dashboard: a software package built in Python designed specifically for mobile air quality monitoring purposes. It aims to provide a free and open-source alternative to comparable commercial packages, thus reducing the barrier to entry of conducting such research. This paper outlines the development of the PLUME Dashboard and justifies the design choices that were made while also providing thorough documentation and explanation for how the software works. Functionality includes real-time data display, real-time peak identification, baseline subtraction, real-time air quality and self-sampling alerts (based on wind direction and vehicle speed), and post-processing tools such as peak identification and map merging with GPS data. The functionality of PLUME Dashboard is tested using real-world data collected in Toronto and Vancouver Canada.
... where y i is the ith observed value of the response variable in the dataset, y is the mean value of the response variable in the dataset, and n is the total number of data points. In practical applications, the GAM can not only analyze individual influencing factors but also reveal potential interactions among these factors [40][41][42]. By calculating APD and R 2 , the relationships between CO, CO 2 , and VOC concentrations in aircraft exhaust emissions and aircraft type and number can be quantitatively analyzed. ...
The taxiing stage of an aircraft is characterized by its long duration, low operating thrust, and low combustion efficiency, resulting in substantial emissions of CO, CO2, and VOCs, which adversely affect air quality near airports. This study has developed an open-path Fourier transform infrared spectroscopy (OP-FTIR) monitor with second-level time resolution to enable the optical remote monitoring of pollutants during taxiing. Measurements of CO, CO2, and VOCs were conducted over one month at Hefei Xinqiao International Airport (HXIA). The generalized additive model (GAM) is used for data analysis to reveal complex nonlinear relationships between aircraft emission concentrations and meteorological factors, aircraft models, and their corresponding registration numbers. The GAM analysis shows that among meteorological factors, humidity, and atmospheric pressure have the most significant impact on aircraft exhaust monitoring, with a relative average contribution value as high as approximately six. The explanatory power of aircraft models for emissions is low (R² < 0.18), whereas that of registration numbers is high (R² > 0.6), suggesting that individual differences between aircrafts play a crucial role in emission concentration variations. Furthermore, a noticeable correlation was found between the CO/CO2 ratio and volatile organic compound (VOC) concentrations (R² > 0.63), indicating that combustion efficiency significantly affects VOC emissions. This study not only advances the real-time remote sensing monitoring of pollutants during aircraft taxiing but also underscores the crucial role of the GAM in identifying the key drivers of emissions, providing a scientific basis for precise environmental protection management and policy-making.
... At the macroeconomic level, carbon emission intensity is expressed by dividing the carbon emissions of every province by GDP. Among them, the carbon emission accounting method adopts the emission factor method [46,47], which is specifically the sum of energy consumption at the provincial level, which is weighted with the corresponding standard coal conversion coefficient and carbon emission coefficient. ...
New quality productivity (NQP) has the possibility to enhance carbon emission performance which will fortify the groundwork for long-term economic expansion even further. The research examines the panel data of 30 provinces spanning the years 2012 to 2022 for an evaluation framework for NQP and carbon emission performance at the provincial level. Employing fixed effect models, mediation effect analysis, and spatial econometrics, the study explores the effect of NQP on carbon emission performance, its mediating mechanisms, and the spatial spillover effects. The findings indicate that (1) NQP significantly lowers carbon emissions for every unit of GDP and enhances carbon emission performance, and the result holds up when the instrumental variable methods are used. (2) The NQP had a significant contribution to improving carbon emission performance via advancements in green innovation. (3) The NQP does more than directly enhance the regional carbon emission performance; in contrast, it additionally positively influences the carbon emission performance level of the adjacent regions by the spatial spillover effect. (4) The impact of NQP on carbon emission performance is particularly pronounced in eastern and innovative regions. On this basis, we should vigorously develop the NQP, strengthen cross-regional policy coordination, and promote green and sustainable development.
... Air pollution still remains a big problem in urbanized territories across the world. Many research studies reveal diesel heavy-duty vehicles (HDVs, including trucks and buses) to be the major contributors to harmful PM 2.5 , NO X , CO and other pollutants and greenhouse gas emissions [1][2][3][4][5]. ...
... Since the major source of NO 2 emissions is transportation, NO 2 reductions could be explained by reduced vehicular flows and industrial activities during the lockdown (Sathe et al. 2021). Wang et al. showed that about 75% (major highway) and 69% (urban street canyon) of NO X pollution was due to local transportation emissions (Wang et al. 2018). In addition, the O 3 concentrations during March-April and November-December in 2020 and April-May and July-August 2021 were comparatively lower than the same periods in previous years (2016-2019). ...
The severe lockdown imposed to prevent the spread of COVID-19 decreased the emissions of air pollutants in large cities. A comparative approach was adopted to analyze the effect of the COVID-19 lockdown on ambient air pollution concentrations and the impacts of meteorological parameters on them using data from air quality monitoring stations (AQMS) in Tabriz, Iran. Air quality improvement was significant for all pollutants, except for O3, in the first phase of the lockdown compared to other phases. The lockdown (restricted social contact, closing of shops, schools, universities, restaurants, and many administrative centers and companies, etc.) temporarily reduced air pollutants. Comparing meteorological parameters between lockdown periods and the same period in previous years showed no statistically significant variations (P-value < 0.05). Therefore, the meteorological parameters did not intervene in reducing air pollutants during the lockdown. The effects of lockdown on the concentration of air pollutants could provide a special way to understand the extent of quarantine compliance by citizens, evaluate additional air quality policies, and assess the impacts of reducing various emission sources.
... The thermal baseline was computed based on an algorithm presented in ref. 85. An example of a thermal baseline is presented in Supplementary Fig. 13. ...
Haze in Beijing is linked to atmospherically formed secondary organic aerosol, which has been shown to be particularly harmful to human health. However, the sources and formation pathways of these secondary aerosols remain largely unknown, hindering effective pollution mitigation. Here we have quantified the sources of organic aerosol via direct near-molecular observations in central Beijing. In winter, organic aerosol pollution arises mainly from fresh solid-fuel emissions and secondary organic aerosols originating from both solid-fuel combustion and aqueous processes, probably involving multiphase chemistry with aromatic compounds. The most severe haze is linked to secondary organic aerosols originating from solid-fuel combustion, transported from the Beijing–Tianjing–Hebei Plain and rural mountainous areas west of Beijing. In summer, the increased fraction of secondary organic aerosol is dominated by aromatic emissions from the Xi’an–Shanghai–Beijing region, while the contribution of biogenic emissions remains relatively small. Overall, we identify the main sources of secondary organic aerosol affecting Beijing, which clearly extend beyond the local emissions in Beijing. Our results suggest that targeting key organic precursor emission sectors regionally may be needed to effectively mitigate organic aerosol pollution.
... Pemerintah Indonesia mengakui bahwa pertumbuhan ekonomi juga menyebabkan peningkatan emisi polutan udara dari sektor transportasi. [8], [9], [10], [11]. ...
Transportasi dapat mempercepat pertumbuhan ekonomi, memudahkan pergerakan barang dan manusia, memperlancar perdagangan, dan menghubungkan pasar. Namun, sektor transportasi dianggap sebagai penyumbang polusi udara yang signifikan. Transportasi jalan raya biasanya menggunakan bahan bakar fosil seperti bensin dan solar. Transportasi jalan raya didominasi oleh kendaraan bermesin pembakaran internal berbahan bakar bensin dan solar, sehingga menimbulkan tantangan bagi dekarbonisasi. Emisi transportasi berkontribusi terhadap perubahan iklim dan dikaitkan dengan dampak buruk terhadap kesehatan. Penelitian ini bertujuan untuk menganalisis besaran emisi kendaraan terhadap karakteristik pengoperasian kendaraan yang berbeda. Penelitian ini dilakukan dengan survei di lapangan untuk mengetahui karakteristik operasional kendaraan. Kajian faktor emisi dilakukan pada kendaraan berbahan bakar bensin dan solar. Pengumpulan data dilakukan dengan mengukur langsung jumlah emisi CO, HC dan opacity serta karakteristik kendaraan. Hasilnya menunjukkan jumlah emisi CO dan HC dari bahan bakar bensin meningkat seiring bertambahnya jarak tempuh dan usia kendaraan. Selain itu, kapasitas silinder pada suatu kendaraan juga mempengaruhi besarnya emisi gas buang. Karakteristik kendaraan termasuk jarak tempuh dan umur kendaraan mempunyai pengaruh yang signifikan terhadap jumlah emisi gas buang pada kendaraan.Karakteristik kendaraan yang meliputi jarak tempuh dan usia kendaraan berpengaruh signifikan terhadap besaran emisi gas buang pada kendaraan.
... Clark Drive is a major truck route for goods movement and connects to a major regional port. This air quality station is < 20 m from the roadway and is equipped with several reference-grade instruments, including the AE33, to monitor near-road pollutant concentrations (Healy et al., 2019;Wang et al., 2018). The MA300s were co-located at the Clark Drive station for 14 weeks (15 August to 30 November 2020). ...
Black carbon (BC) is a component of particulate matter, emitted from the incomplete combustion of carbonaceous fuels. The presence of BC in the atmosphere can disrupt the atmospheric radiation budget, and exposure to BC can adversely affect human health. Multi-wavelength light-absorption-based dual-spot aethalometers can be used to quantify the source and characteristics of BC from traffic or biomass-burning-based sources. However, aethalometer measurements are affected by artifacts such as aerosol loading and light scattering; hence, they often need correction to reduce measurement uncertainty. This work assesses the performance of the recently developed portable aethalometer (MA300, AethLabs). Due to their portability and ease of usage, MA300s can be suitable for mobile and personal exposure monitoring. Here, we evaluate BC concentration and source apportionment accuracy of three MA300 units relative to a widely used aethalometer, the AE33 (Magee Scientific). Synchronous field measurements were performed at a major traffic intersection during regular and wildfire-smoke-affected days in Vancouver, Canada. We find that MA300-reported BC mass concentrations were strongly correlated (Slope range between 0.73 and 1.01, with R2 = 0.9) compared to the reference instrument, yet there is visible instrumental variability in the normalized concentrations (5 %) across three units. The mean absolute error of MA300-reported BC concentrations ranged between 0.44–0.98 µg m-3, with the highest deviations observed in wildfire-smoke-affected polluted days. From the aerosol light absorption measurement perspective, MA300s tend to underestimate the absorption coefficients (babs) across the five wavelengths. UV channel light absorption results were subjected to the highest amount of noise and were found to be consistently underestimating in all the MA300 units, leading to systematic bias in source apportionment analysis. Absorption Ångström exponent values from the MA300 units were able to capture the variability of aerosol sources within a day, with a mean value of 1.15 during clean days and 1.46 during wildfire-smoke-affected days. We investigated the application of the latest non-linear aethalometer correction protocols in the MA300 and found that flow fluctuations enhanced noise across all channels, compared to onboard instrument correction. We also identify that the UV (λ = 370 nm) channel absorption measurements are most sensitive to instrumental artifacts during the wildfire-smoke-affected period. Hence, as an alternative to traditional UV and IR (λ = 880 nm)-based BC source apportionment methods, in this work, we tested the blue (λ = 470 nm) and IR wavelengths for BC source apportionment calculation. When the blue–IR-based source apportionment technique is adopted instead of the UV–IR, there is a 10 % (on average) decrease in the percentage difference of the apportioned components from the reference monitor.
... Trucks account for 26% of the U.S. transportation sector GHG emissions (EPA, 2020), constituting the second largest vehicle source for GHGs after light-duty vehicles. It has also been found that large trucks are the largest contributor to particular matter pollution in areas near roadways in the U.S. (Wang et al., 2018). Moreover, electric trucks have the potential to provide increased economic value since they are more efficient than their internal combustion engine counterparts and may have lower costs during their long trips due to the simplicity of their electric powertrains (Boloor-Alum et al., 2019). ...
... EPFRs are highly stable because they do not easily decompose after formation, and they are highly persistent, lasting from few minutes to several months (Vejerano et al. 2018). The sources of EPFRs are mainly released from various anthropogenic activities (metallurgical processes, soil contaminants, waste incineration, biomass burning, engine exhaust, and industrial processes of organic materials that interact with metal-containing particles to form a free radical-particle pollutant) and precursors of secondary pollutants such as PAHs and reactive oxygen species (ROS): hydroxyl radicals, hydrogen peroxide (H 2 O 2 ), and superoxide anion radicals (Wang et al. 2018;Li et al. 2020;Chen et al. 2019). Particles emitted from such sources undergo photo-oxidation and uptake another gas phase, such as VOCs (Wang et al. 2009). ...
Environmental pollution, especially indoor air pollution, has become a global issue and affects nearly all domains of life. Being both natural and anthropogenic substances, indoor air pollutants lead to the deterioration of the ecosystem and have a negative impact on human health. Cost-effective plant-based approaches can help to improve indoor air quality (IAQ), regulate temperature, and protect humans from potential health risks. Thus, in this review, we have highlighted the common indoor air pollutants and their mitigation through plant-based approaches. Potted plants, green walls, and their combination with bio-filtration are such emerging approaches that can efficiently purify the indoor air. Moreover, we have discussed the pathways or mechanisms of phytoremediation, which involve the aerial parts of the plants (phyllosphere), growth media, and roots along with their associated microorganisms (rhizosphere). In conclusion, plants and their associated microbial communities can be key solutions for reducing indoor air pollution. However, there is a dire need to explore advanced omics technologies to get in-depth knowledge of the molecular mechanisms associated with plant-based reduction of indoor air pollutants.
... In this method, we determined, for every thermogram of each compound, a background thermogram termed the thermal baseline (Is thbsl ). The thermal baseline was computed using a spline algorithm initially developed by Wang et al. (2018) to determine the background concentration of a pollutant using its concentration time series (by determining the spline of background from varying time intervals). Thermogram data were preaveraged to 1.8 min (corresponding to four data points of the original time resolution of 27 s) to reduce noise for the thermal baseline computation. ...
Measurements of the molecular composition of organic aerosol (OA) constituents improve our understanding of sources, formation processes, and physicochemical properties of OA. One instrument providing such data at a time resolution of minutes to hours is the chemical ionization time-of-flight mass spectrometer with filter inlet for gases and aerosols (FIGAERO-CIMS). The technique collects particles on a filter, which are subsequently desorbed, and the evaporated molecules are ionized and analyzed in the mass spectrometer. However, long-term measurements using this technique and/or field deployments at several sites simultaneously require substantial human and financial resources. The analysis of filter samples collected outside the instrument (offline) may provide a more cost-efficient alternative and makes this technology available for the large number of particle filter samples collected routinely at many different sites globally. Filter-based offline use of the FIGAERO-CIMS limits this method, albeit to particle-phase analyses, which is likely at a reduced time resolution compared to online deployments. Here we present the application and assessment of offline FIGAERO-CIMS, using Teflon and quartz fiber filter samples that were collected in autumn 2018 in urban Beijing. We demonstrate the feasibility of the offline application with a “sandwich” sample preparation for the over 900 identified organic compounds with (1) high signal-to-noise ratios, (2) high repeatability, and (3) linear signal response to the filter loadings. Comparable overall signals were observed between the quartz fiber and Teflon filters for 12 and 24 h samples but with larger signals for semi-volatile compounds for the quartz fiber filters, likely due to adsorption artifacts. We also compare desorption profile (thermogram) shapes for the two filter materials. Thermograms are used to derive volatility qualitatively based on the desorption temperature at which the maximum signal intensity of a compound is observed (Tmax). While we find that Tmax can be determined with high repeatability (±5.7 ∘C) from the duplicate tests for one filter type, we observe considerable differences in Tmax between the quartz and Teflon filters, warranting further investigation into the thermal desorption characteristics of different filter types. Overall, this study provides a basis for expanding OA molecular characterization by FIGAERO-CIMS to situations where and when deployment of the instrument itself is not possible.
... 50 standards under different driving conditions. The speed (km h -1 ) is divided into [0, 10), [10,20), 287 [20,30), [30,40), [40,50), [60,70) High speed, acceleration, and deceleration are found to considerably promote SOA production 303 from gasoline exhaust due to higher organic gaseous emissions caused by unburned fuel emission 304 or incomplete combustion. Moreover, with emission standards updating, such impacts on SOA 305 production tend to weaken. ...
Vehicle emission is a major source of atmospheric secondary organic aerosols (SOA). Driving condition is a critical influencing factor for vehicular SOA production, but few studies have revealed SOA production dependence on the rapidly-changing real-world driving conditions. Here, a fast-response oxidation flow reactor system is developed and deployed to quantify the SOA formation potential under transient driving conditions. Results show that the SOA potential varies by orders of magnitude, e.g., 20-1500 mg kg-fuel ⁻¹ and 12–155 mg kg-fuel ⁻¹ for China V and China VI vehicles, respectively. High speed, acceleration, and deceleration are found to considerably promote SOA production due to higher organic gaseous emissions caused by unburned fuel emission or incomplete combustion. In addition, China VI vehicles significantly reduce SOA potential, yield, and acceleration and deceleration peaks. Our study provides experimental insight into vehicular SOA formation under transient driving conditions, which would benefit high-time-resolved SOA simulations in the urban atmosphere.
... 32,33 This carbon balance method assumes the equal dilution of all emitted pollutants and all carbon in the fuel is converted to CO 2 (complete combustion). 33,34 When calculating NO x EFs from PEMS using eq 9, the baseline concentrations were not subtracted since the measurements were directly conducted at the tailpipe. For each plume-chasing event, the average pollutant concentration increments (either ...
... Like in many other countries, HGV traffic has not decreased at a similar magnitude as private traffic. As the GHG emissions of HGV transportation are significantly higher than those of private traffic (Wang et al., 2018), the reduction of GHG emissions from traffic may not have been linearly associated with the reduction in the pure number of vehicles, but rather strongly related to the types of vehicles on the road. ...
Traffic and transportation are a major source of CO2 emissions. As the volume of heavy goods vehicle (HGV) transportation is difficult to reduce, many governments target private traffic. Next to the direct effect of fewer private vehicles on the roads, an indirect effect may be very important: The less congestion, the more fuel-efficient the remaining drivers may be able to drive because there would be less need to speed up, brake, and maneuver, for example while overtaking. On the other hand, clear roads may be tempting for drivers to speed and thus result in a negative impact of less private traffic. The direction and size of this indirect effect is difficult to measure for two reasons: First, we usually have no real-time driving data from heavy trucks. Second, traffic density usually does not vary to a large extent. We set out to assess the margins of this indirect effect using a unique data set from a large German logistics fleet. We measured truck drivers’ driving behavior as well as emissions from their trucks between January and May 2020. During that time, the COVID-19-related policy measures led to a significant decline in private traffic on highways. We find that less private traffic volume results in improved fuel-efficient driving behavior, resulting in reduced overall CO2 emissions. The effect is u-shaped; too little private traffic density leads to less fuel-efficient driving by the remaining heavy goods vehicle drivers. Moreover, removing the worst drivers from the roads has the same effect in terms of magnitude as reducing private traffic congestion to the medium-density optimum.
... When converting the slope of BC HOA to the BC emission factor (EF BC ) by using a carbon mass fraction (CMF) ratio of CMF CO 2 /CMF fuel of 3141 g kg −1 of fuel (Enroth et al., 2016), a value equal to 0.03 g kg −1 of fuel was obtained. That was roughly one-fifth of EF BC measured in 2012 in Helsinki at the roadside (Enroth et al., 2016), but it was at the same level as EF BC measured near the road in Toronto, Canada, in 2016 (Wang et al., 2018). For BC BBOA , EF BC was not calculated as emitted BC, and CO 2 depends largely on biomass material burned as well as the combustion conditions and devices (Savolahti et al., 2016). ...
This study investigated the sources of black carbon (BC) at two contrasting urban environments in Helsinki, Finland: residential area and street canyon. The measurement campaign in the residential area was conducted in winter–spring 2019, whereas in the street canyon the measurements were carried out in autumn 2015. The sources of BC were explored by using positive matrix factorization (PMF) for the organic and refractory black carbon (rBC) mass spectra collected with a soot particle aerosol mass spectrometer (SP-AMS). Based on the PMF analysis, two sites had different local BC sources; the largest fraction of BC originated from biomass burning at the residential site (38 %) and from the vehicular emissions in the street canyon (57 %). Also, the mass size distribution of BC diverged at the sites as BC from traffic was found at the particle size of ∼100–150 nm whereas BC from biomass combustion was detected at ∼300 nm. At both sites, a large fraction of BC was associated with urban background or long-range-transported BC indicated by the high oxidation state of organics related to those PMF factors.
The results from the PMF analysis were compared with the source apportionment from the Aethalometer model calculated with two pairs of absorption Ångström values. It was found that several PMF factors can be attributed to wood combustion and fossil fuel fraction of BC provided by the Aethalometer model. In general, the Aethalometer model showed less variation between the sources within a day than PMF, indicating that it was less responsive to the fast changes in the BC sources at the site, or it could not distinguish between as many sources as PMF due to the similar optical properties of the BC sources. The results of this study increase understanding of the limitations and validity of the BC source apportionment methods in different environments. Moreover, this study advances the current knowledge of BC sources and especially the contribution of residential combustion in urban areas.
... All field deployments took place at a near-road air quality monitoring station operated by the Ontario Ministry of the Environment, Conservation and Parks (MECP) beside a major highway (HWY401) in Toronto, Canada (43.71112, − 79.54336). The station is equipped with a suite of instrumentation for continuous monitoring of gas and particle phase traffic-related pollutants as described in detail elsewhere Wang et al., 2018). The persistent traffic source, over 400 000 vehicles per day (MTO, 2017), is useful for testing methods that target traffic-related pollutants, for example benzene, toluene, ethylbenzene and xylenes (BTEX). ...
Passive samplers have proven to be effective for continuous monitoring of volatile organic compounds (VOCs) in ambient air in remote, urban and industrial environments. Thermal desorption tubes fitted with endcaps that facilitate passive uptake through diffusion are now routinely used for monitoring fugitive benzene emissions from refineries and petrochemical facilities across North America (EPA Method 325A/B). However, deployment periods of 14 days are typically employed to minimize the risk of poor retention, requiring 26 deployments per year to return an annual average concentration for comparison with chronic exposure health-based standards. Here, we explore extending the deployment duration of these passive samplers to one, two and three months by limiting VOC uptake rates using an alternative diffusive endcap featuring a smaller cross-sectional area. Field testing was performed beside a major highway during two separate three-month campaigns. Uptake rates for benzene, toluene, ethylbenzene and xylenes (BTEX) were observed to remain linear for deployments of up to three months when using the low-uptake endcaps. Application of the low-uptake endcaps and the uptake rates determined here will enable annual average concentrations of BTEX to be calculated using only four tube deployments per year. The cost savings associated with this decreased deployment frequency will facilitate increased spatial resolution during future exposure assessment studies. The stability of selected air toxics within the tubes was also assessed and the results suggest that while aromatic VOCs are stable for storage times of at least 70 days, chloroform and trichloroethylene begin to degrade within two weeks of sampling.
... When converting the slope of BCHOA to the BC emission factor (EFBC) by using a carbon mass fraction (CMF) ratio of CMFCO2/CMFfuel of 3141 g (kg fuel) −1 (Enroth at al., 2016), a value equal to 0.03 g kgfuel -1 was obtained. That was roughly one fifth of EFBC measured in 2012 in Helsinki at the roadside (Enroth et al., 2016) but it was at the same level with EFBC measured near road 435 in Toronto, Canada in 2016 (Wang et al., 2018). For BCBBOA, EFBC was not calculated as emitted BC and CO2 depend largely on biomass material burnt as well as the combustion conditions and devices (Savolahti et al., 2016). ...
This study investigated the sources of black carbon (BC) at two contrasting urban environments in Helsinki, Finland; residential area and street canyon. The sources of BC were explored by using positive matrix factorization (PMF) for the organic and refractory black carbon (rBC) mass spectra collected with a soot particle aerosol mass spectrometer (SP-AMS). Two sites had different local BC sources; the largest fraction of BC originated from biomass burning at the residential site (38 %) and from the vehicular emissions at the street canyon (57 %). Also, the mass size distribution of BC diverged at the sites as BC from traffic was found at the particle size of ~100–150 nm whereas BC from biomass combustion was detected at ~300 nm. At both sites, a large fraction of BC was associated with urban background or long-range transported BC indicated by the high oxidation state of organics related to those PMF factors. The results from the PMF analysis were compared with the source apportionment from the aethalometer model calculated with two pair of absorption Ångström values. It was found that several PMF factors can be attributed to wood combustion and fossil fuel fraction of BC provided by the aethalometer model. In general, the aethalometer model showed less variation between the sources within a day than PMF being less responsive to the fast changes in the BC sources at the site. The results of this study increase understanding of the limitations and validity of the BC source apportionment methods in different environments. Moreover, this study advances the current knowledge of BC sources and especially the contribution of residential combustion in urban areas.
... Many studies used ecological time-series method to determine the effect of air pollutants on COPD (7) and low spatiotemporal resolution of measurements of ambient air pollution obtained from fixed monitoring stations as a surrogate for individual exposure, and ecological fallacy is a concern. A study found traffic-related pollution was affected by many factors including dynamic emissions, measurement distance and height from the roadway, street canyon, obstructions along the way, and meteorological conditions such as wind direction and speed (8). When the exposure concentration was highly spatially and geographically heterogeneous, mis-estimation of exposures would be introduced into analysis (9). ...
Background: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in China. Although numerous studies have been conducted to determine the risk factors for COPD mortality such as ambient air pollution, the results are not fully consistent.
Methods: This study included mortality analysis and a case-control design by using the data extracted from the Mortality Registration System in Jiading District, Shanghai. Traditional logistic regression, geographically weighted logistic regression (GWLR), and spatial scan statistical analysis were performed to explore the geographic variation of COPD mortality and the possible influencing factors.
Results: Traditional logistic regression showed that extreme lower temperature in the month prior to death, shorter distance to highway, lower GDP level were associated with increased COPD mortality. GWRL model further demonstrated obvious geographical discrepancies for the above associations. We additionally identified a significant cluster of low COPD mortality (OR = 0.36, P = 0.002) in the southwest region of Jiading District with a radius of 3.55 km by using the Bernoulli model. The geographical variation in age-standardized mortality rate for COPD in Jiading District was explained to a certain degree by these factors.
Conclusion: The risk of COPD mortality in Jiading District showed obvious geographical variation, which were partially explained by the geographical variations in effects of the extreme low temperature in the month prior to death, residential proximity to highway, and GDP level.
... It can be found that the general trend of the concentration of the detection site of the Olympic Sports Center is very close to that of the road monitoring site, and the value is about one-third of the concentration of road pollutants. We suspect that the diffusion of PM pollutants decreases with increasing distance, and similar conclusions can be obtained from the literature of other researchers [41]. We will discuss this in future research. ...
This research aims to calculate PM2.5 concentration on the road network by considering the network-wide traffic status, which can be used to support research about the impact of urban road network pollution concentration on health. The increase in the use and number of vehicles has brought about a large amount of vehicle exhaust emissions and increased urban air pollutants. This is also one of the important reasons why this issue is worth studying. In this research, traffic emission was an estimate based on network-wide traffic status which was calculated from vehicle trajectories and spatial variance-covariance matrix. An identification method of external input pollutants is proposed to determine the occurrence of external pollutants imported into the urban area. To calculate the impact of multiple influencing factors on the pollution concentration of the entire road network, a multivariate linear model was adopted to calculate a variety of influencing factors and calibrate the model parameters by collecting real data. The results show that traffic emissions, external input pollution, and wind impact are the main factors affecting the PM2.5 concentration on urban road networks. Combined with real-time traffic data, we can obtain the temporal and spatial characteristics of the pollutant concentration of the road network. For policymakers, our research can provide a method for calculating the PM2.5 concentration on the road network, which is useful for establishing a health assessment framework in the future.
... Nitrogen dioxide and NO X both demonstrated many monitors at their lowest concentrations during the SOE period, compared to the previous five years. Wang et al. (2018) using the same monitoring locations as Dabek-zlotorzynska et al. (2019) identified that local contributions from vehicle emissions were much greater for NO X , where 69% (urban street canyon) and 75% (major highway) of NO X pollution was attributable to local transportation sources. Ontario emissions from the transportation sector for NO X are estimated at 69% of total emissions. ...
In March of 2020, the province of Ontario declared a State of Emergency (SOE) to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease (COVID-19). This disruption to the economy provided an opportunity to measure change in air pollution when the population spends more time at home with fewer trips. Hourly air pollution observations were obtained for fine particulate matter, nitrogen dioxide, nitrogen oxides and ozone from the Ontario air monitoring network for 2020 and the previous five years. The analysis is focused on a five-week period during the SOE with a previous five-week period used as a control. Fine particulate matter did not show any significant reductions during the SOE. Ozone concentrations at 12 of the 32 monitors were lower than any of the previous five-years; however, four locations were above average. Average ozone concentrations were 1 ppb lower during the SOE, but this ranged at individual monitors from 1.5 ppb above to 4.2 ppb below long-term conditions. Nitrogen dioxide and nitrogen oxides demonstrated a reduction across Ontario, and both pollutants displayed their lowest concentrations for 22 of 29 monitors. Individual monitors ranged from 1 ppb (nitrogen dioxide) and 5 ppb (nitrogen oxides) above average to 4.5 (nitrogen dioxide) and 7.1 ppb (nitrogen oxides) below average. Overall, both nitrogen dioxide and nitrogen oxides demonstrated a reduction across Ontario in response to the COVID-19 SOE, ozone concentrations suggested a possible reduction, and fine particulate matter has not varied from historic concentrations.
... These impacts are not limited to respiratory problems but also include cardiovascular problems, cancer, premature birth and dementia (American Lung Association, 2019;Public Health Ontario, 2015). In Canada, 30% of the population lives within 500 metres of a major road axis and according to a recent study conducted by a University of Toronto researcher, the type of vehicle would be more important than the traffic volume as a contributor to air pollution and its harmful effects on health: old heavy trucks running on diesel would be the main culprits (Wang et al., 2018). ...
The City of Baltimore, MD has a history of problems with environmental justice (EJ), air pollution, and the urban heat island (UHI) effect. Current chemical transport models lack the resolution to simulate concentrations on the scale needed, about 100 m, to identify the neighborhoods with anomalously high air pollution levels. In this paper we introduce the capabilities of a mobile laboratory and an initial survey of several pollutants in Baltimore to identify which communities are exposed to disproportionate concentrations of air pollution and to which species. High concentrations of black carbon (BC) stood out at some locations - near major highways, downtown, and in the Curtis Bay neighborhood of Baltimore. Results from the mobile lab are confirmed with longer-term, low-cost monitoring. In Curtis Bay, higher concentrations of BC were measured along Pennington Ave. (mean [5th to 95th percentiles] = 2.08 [2.0-10.9] μg m-3) than along Curtis Ave. just ~ 150 m away (0.67[0.1 - 1.8] μg m-3). Other species, including criteria pollutants ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5), showed little gradient. Observations with high spatial and temporal resolution help isolate the mechanisms leading to locally high pollutant concentrations. The difference in BC appears to result not from heavier truck traffic or slower dispersion but from the interruptions in traffic flow. Pennington Ave. has three stoplights while Curtis Ave. has none. As heavy-duty diesel-powered vehicles accelerate, they experience turbo-lag and the resulting rich air-fuel mixture exacerbates BC emissions. Immediate mediation might be achieved through smoother traffic flow, and the long-term solution through replacing heavy-duty trucks with electric vehicles.Implications: We present results documenting the locations within Baltimore of high concentrations of Black Carbon pollution and identify the likely source - diesel exhaust emissions exacerbated by stop-and-go traffic and associated turbo-lag. This suggests solutions (smoother traffic, retrofit particulate filters, replacement of diesel with electric vehicles) that would enhance Environmental Justice (EJ) and could be applied to other cities with EJ problems.Synopsis: This paper presents observations of atmospheric black carbon aerosol showing impacts on environmental justice, then identifies causes and suggests solutions.
Using detailed Global Navigation Satellite System tracing data emitted by all trucks having a gross vehicle weight of over 3.5 tons in Belgium, this paper assesses the efficiency of the current Belgian distance tax system by analyzing its spatial coverage and the matching of the distance taxes with the external costs, globally and locally. Specifically, three research questions are addressed. First, how well do the present charge rates match with external costs? Second, the operationalization of the system requires a good spatial coverage of truck movements. Does the present system guarantee an almost universal coverage? Third, do the distance charges match the external costs? We find that if the distance tax scheme differentiates regionally, it still misses large variations in noise costs. The current tracing infrastructure also captures only part of the truck operations on the territory. If distance tolls for trucks remain the backbone of the taxation of truck operations, it then needs further refinement in time and space if one wants it to be the major tool to correct for the external costs.
Black Carbon (BC) is a component of particulate matter, emitted from the incomplete combustion of carbonaceous fuels. The presence of BC in the atmosphere can disrupt the atmospheric radiation budget, and exposure to BC can adversely affect human health. Multi-wavelength light absorption-based dual-spot aethalometers can be used to quantify the source and characteristics of BC from traffic or biomass burning-based sources. However, aethalometer measurements are affected by artifacts such as aerosol loading and light scattering; hence, they often need correction to reduce measurement uncertainty. This work assesses the performance of the recently developed portable aethalometer (MA300, AethLabs). Due to their portability and ease of usage, MA300s can be suitable for mobile and personal exposure monitoring. Here, we evaluate BC concentration and source apportionment accuracy of three MA300 units relative to a widely used aethalometer, the AE33 (Magee Scientific). Synchronous field measurements were performed at a major traffic intersection during regular and wildfire smoke-affected days in Vancouver, Canada. We find that MA300 reported BC mass concentrations were strongly correlated (Slope range between 0.73 and 1.01, with R2 = 0.9) compared to the reference instrument, yet there is visible instrumental variability (15 %) across three units. The mean absolute error of MA300 reported BC concentrations ranged between 0.44–0.98 ug m-3 with the highest deviations observed in wildfire smoke-affected polluted days. From the aerosol light absorption measurement perspective, MA300s tend to underestimate the absorption coefficients (babs) across the five wavelengths. UV channel light absorption results were subjected to the highest amount of noise, leading to systematic bias in source apportionment analysis. We investigated the application of the latest non-linear aethalometer correction protocols in the MA300 and found that flow fluctuations enhanced noise across all channels, compared to onboard instrument correction. We also identify that the UV (λ = 370 nm) channel absorption measurements are most sensitive to instrumental artifacts during the wildfire smoke-affected period. Hence, as an alternative to traditional UV and IR (λ = 880 nm)-based BC source apportionment methods, in this work, we tested the Blue (λ = 470 nm) and IR wavelengths for BC source apportionment calculation. By adopting Blue-IR based source apportionment technique in MA300, the apportioned BC components improves on average in the order of 10 % when compared against the reference monitor's results.
Measurements of the molecular composition of organic aerosol (OA) constituents improve our understanding of sources, formation processes, and physicochemical properties of OA. One instrument providing such data at a time resolution of minutes to hours is the Chemical Ionization time-of-flight Mass Spectrometer with Filter Inlet for Gases and AEROsols (FIGAERO-CIMS). The technique collects particles on a filter, which are subsequently desorbed, and the evaporated molecules are ionized and analyzed in the mass spectrometer. However, long-term measurements using this technique and/or field deployments at several sites simultaneously, require substantial human and financial resources. The analysis of filter samples collected outside the instrument (offline) may provide a more cost-efficient alternative and makes this technology available for the large number of particle filter samples collected routinely at many different sites globally. Filter-based offline use of the FIGAERO-CIMS limits this method albeit to particle-phase analyses, likely at reduced time resolution compared to online deployments. Here we present the application and assessment of offline FIGAERO-CIMS, using Teflon and Quartz fiber filter samples that were collected in autumn 2018 in urban Beijing. We demonstrate the feasibility of the offline application with “sandwich” sample preparation for the identified over 900 organic compounds with (1) high signal-to-noise ratios, (2) high repeatability, and (3) linear signal response to the filter loadings. Comparable overall signals were observed between the Quartz fiber and Teflon filters for 12-h and 24-h samples, but with larger signals for semi-volatile compounds for the Quartz fiber filters, likely due to adsorption artifacts. We also compare desorption profile (thermogram) shapes for the two filter materials. Thermograms are used to derive volatility qualitatively based on the desorption temperature at which the maximum signal intensity of a compound is observed (Tmax). While we find that Tmax can be determined with high repeatability for one filter type, we observe considerable differences in Tmax between the Quartz and Teflon filters, warranting further investigation into the thermal desorption characteristics of different filter types. Overall, this study provides a basis for expanding OA molecular characterization by FIGAERO-CIMS to situations where and when deployment of the instrument itself is not possible.
Understanding the emission characteristics in the evolution of private vehicle fleet composition has become a key issue to be addressed to develop appropriate emission mitigation strategies in transportation sector. In this study, the influence of such evolution on on-road emissions was investigated based on a comprehensive dataset encompassing vehicle fleet composition, demographic, economic, and energy features from a representative small-medium automotive city in North America. The decoupling analysis was carried out to assess the dynamic linkage between environmental pressure exerted by the transportation sector and economic growth at both city level and national level in North America. We also developed an approach that supports the long-term traffic-related air pollutant prediction and investigated the potential influence on urban air quality. A sharp upward trajectory was observed in the quantity of SUVs from 2001 to 2018, gradually replacing the dominance of the quantity of four-door cars. There was a significant shift in the GHG emissions emitted from vehicle types used for passenger transport: emissions from SUVs and trucks rose by 374.0% and 69.3%, respectively, whereas emissions from four-door cars, two-door cars, station wagons, and vans all decreased. The changes in vehicle composition, along with the steady trend in GHG emissions from private fleet and decrease in on-road air pollutant concentrations found in Regina, were a response to the establishment of federal fuel economy standards and improved fuel economy. Relative decoupling was observed in aggregate for Regina and Canada in most of the years while both experienced economic downturns and increases in environmental pressure in the form of emissions from 2014 to 2015. The predicted results also demonstrate the high capability of XGboost machine learning algorithm in predicting on-road air pollutant concentrations of CO, PM2.5, and NOX.
This study aimed to investigate the possible association between exposure to particulate matter (PM) and bioaerosols with health symptoms and levels of inflammatory blood biomarkers in workers at a Materials Recycling Facility (MRF) in Brazil, compared to a control population of the Federal University of Technology – Parana (UTFPR). A total of 64 volunteers freely agreed to participate in this study, 40 MRF workers (exposed group) and 24 UTFPR staff and students (control group). We applied questionnaires and collected blood samples in November 2018, while PM and bioaerosol (bacteria and fungi) samplings occurred in February 2019 at four different sampling sites: at the MRF, in a waste processing shed (P1), and outdoors (P2); at UTFPR, in a classroom (P3) and the outdoor environment (P4). P1 is the most contaminated site with the highest mean values for PM1.0, PM2.5, PM10 (respectively, 5.7, 27.4, and 562.4 μg m⁻³), and bacteria (1830.7 colony-forming units per cubic meter – CFU. m⁻³). For fungi, P4 presented the highest mean concentration (3218.1 CFU m⁻³). The main microorganisms observed in indoor samples (P1 and P3) were Gram-positive bacteria and fungi Aspergillus spp. Exposure to PM2.5, PM10, bacteria, and fungi may increase the possibility of some respiratory, circulatory, and allergy symptoms among MRF workers. The blood samples showed mixed results; IFN-γ was statistically significant between the two groups and lower for the exposed group. Overall, the study presents a reasonably accurate assessment of air quality and health problems for MRF workers.
Vehicular emissions contribute to roadside pollutants in cities, yet on-road emission estimates remain relatively uncommon. Nevertheless, they make an important contribution to exposure along Hong Kong's congested roads and street canyons. This study used kerbside microsensor-based monitors on Hennessy Road, one of the busiest roads in the north part of Hong Kong Island, to determine both concentrations and emission factors (EFs) of NOx and CO. Kerbside NOx and CO concentrations are skewed, with high concentrations representing plume segments from larger vehicles. The average EFs for each minute of traffic was determined from the pollutant concentration ratio with ΔCO2. These related to bus frequency for NOx, and EURO 4 or lower-emission standard vehicles for CO. The 1-min mean EFNOx 7.55 g kg⁻¹ and EFCO 12.6 g kg⁻¹ are typical for flows for the fleet dominated by buses, but highly skewed (Weibull shape parameter ∼0.44). Individual vehicle EFs were determined from peaks in NOx, CO and CO2, and number plates. Leading and trailing parts of the plume segments gave similar EFs (R² > 0.95), suggesting this method was reasonably robust across the vehicle passage. Nevertheless, these EFs were also skewed, but the shape parameter was again ∼0.44. EFNOX for vehicle classes was: buses > goods vehicles > private cars > vans > taxis and diesel > petrol > LPG, with larger engine sizes also dominant. Differences were more difficult to assess with CO, but LPG vehicles had the highest EFs. Our EF estimates lay in the range found in previous studies but differ from fleet emissions calculated for regulatory purposes in Hong Kong (EMFAC). However, some high EMFAC emitters were also high in our estimates for individual vehicles. Vehicles may not perform on-road as inventory calculations suggest. The high EF variability found in our study implies that a large sample is required to assess the likely emissions from a vehicle fleet.
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 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.
An "event-based" approach to characterize complex air pollutant mixtures was applied in the Oil Sands region of northern Alberta, Canada. This approach was developed to better-inform source characterization and attribution of the air pollution in the Indigenous community of Fort McKay, within the context of the lived experience of residents. Principal component analysis was used to identify the characteristics of primary pollutant mixtures, which were related to hydrocarbon emissions, fossil fuel combustion, dust, and oxidized and reduced sulfur compounds. Concentration distributions of indicator compounds were used to isolate sustained air pollution "events". Diesel-powered vehicles operating in the mines were found to be an important source during NOx events. Industry-specific volatile organic compound (VOC) profiles were used in a chemical mass balance model for source apportionment, which revealed that nearby oil sands operations contribute to 86% of the total mass of nine VOC species (2-methylpentane, hexane, heptane, octane, benzene, toluene, m,p-xylene, o-xylene, and ethylbenzene) during VOC events. Analyses of the frequency distribution of air pollution events indicate that Fort McKay is regularly impacted by multiple mixtures simultaneously, underscoring the limitations of an exceedance-based approach relying on a small number of air quality standards as the only tool to assess risk.
Traditionally, vehicle emissions measurements rely on reference-grade instruments whose high cost and complexity have limited their deployment in real-world environments. New simple-to-operate, low-cost sensing technologies are a potential solution to this problem. To assess their suitability, we deployed six Sensit Real-time, Affordable, Multi-Pollutant (RAMP) monitors measuring PM2.5, NO, NO2, CO2, O3 and CO in three parking garages on the UBC Vancouver campus from April–August 2019. UBC Parking Services provided real-time vehicle counts to help validate our method. After sensor calibration, integrated pollutant and CO2 signals were converted to fuel-based emission factors (EFs). Our calculated EFs fell within the range of previous studies. Evening EFs when vehicles were cold were 10–50% higher than in the morning. We also observed a disproportional contribution of high emitters; the top 25% of plumes contributed 45–65% of total emissions. Our findings indicate that low-cost sensors are a promising technology for real-world vehicle emissions measurement.
Ambient fine particulate matter (PM2.5) data of similar continuously monitored species at two air monitoring sites with different characteristics within the City of Toronto were used to gauge the intra-city variations in the PM composition over a largely concurrent period spanning two years. One location was <8 m from the side of a major highway while the other was an urban background location. For the first time, multi-time resolution factor analysis was applied to dispersion-normalized concentrations to identify and quantify source contributions while reducing the influence of local meteorology. These factors were particulate sulphate (pSO4), particulate nitrate (pNO3), secondary organic aerosols (SOA), crustal matter (CrM) that were common to both sites, a hydrocarbon-like organic matter (HOM) exclusive to the urban background site, three black carbon related factors (BC, BC-HOM at the highway site, and a brown carbon rich factor (BC-BrC) at the urban background site), biomass burning organic matter (BBOM) and brake dust (BD) factors exclusive to the highway site. The PM2.5 composition was different between these two locations, over only a 10 km distance. The sum of SOA, pSO4 and pNO3 at the urban background site averaged 57% of the PM2.5 mass while the same species represented 43% of the average PM2.5 mass at the highway site. Local or site-specific factors may be of greater interest for control policy design. Thus, regression analyses with potential explanatory, site-specific variables were performed for results from the highway site. Three model approaches were explored: multiple linear regression (MLR), regression with a generalized reduced gradient (GRG) algorithm, and a generalized additive model (GAM). GAM gave the largest fraction of variance for the locally-found factors at the highway site. Heavy-duty vehicles were most important for explaining the black carbon (BC and BC-HOM) factors. Light-duty vehicles were dominant for the brake dust (BD) factor. The auxiliary modelling for the local factors showed that the traffic-related factors likely originated along the main roadways at their respective sites while the more regional factors, − pSO4, pNO3, SOA, − had sources that were both regional and local in origin and with contributions that varied seasonally. These results will be useful in understanding ambient particulate matter sources on a city scale that will support air quality management planning.
This study investigates the influence of meteorology, land use, built environment, and traffic characteristics on near-road ultrafine particle (UFP) concentrations. To achieve this objective, minute-level UFP concentrations were measured at various locations along a major arterial road in the Greater Toronto Area (GTA) between February and May 2019. Each location was visited five times, at least once in the morning, mid-day, and afternoon. Each visit lasted for 30 min, resulting in 2.5 h of minute-level data collected at each location. Local traffic information, including vehicle class and turning movements, were processed using computer vision techniques and organized in minute intervals. The number of fast-food restaurants, cafes, trees, traffic signals, and building footprint, were found to have positive impacts on the mean UFP, while the distance to the closest major road was negatively associated with UFP. We employed the Extreme Gradient Boosting (XGBoost) method to develop prediction models for UFP concentrations. The Shapley additive explanation (SHAP) measures were used to capture the influence of each feature on model output. The model results demonstrated that minute-level counts of local traffic from different directions had significant impacts on near-road UFP concentrations. Besides, model performance was robust under random cross-validation as coefficients of determination (R²) ranged from 0.63 to 0.69, but it revealed weaknesses when data at specific locations were eliminated from the training dataset. This result indicates that proper cross-validation techniques should be developed to better evaluate machine learning models for air quality predictions.
Gasoline vehicles (GVs) emissions generally dominate ambient volatile organic compounds (VOCs) in urban areas, while VOC emissions from liquefied natural gas (LNG)-fueled vehicles play an increasingly important role in urban air quality, due to fuel transition from gasoline/diesel to alternative fuels. Here, an extensive dataset of VOC samples collected in three urban tunnels in China was used to explore real-world emission characteristics of ninety-nine VOC species from both GVs and LNG-fueled vehicles. The fleets in the Beijing and Tianjin tunnels comprised >94% GVs whereas the fleet in the Nanjing tunnel comprised both GVs (∼87%) and LNG-buses (∼13%). The VOC emission factors (EFs) in the Beijing tunnel and Tianjin tunnel were highly correlated, implying that they can be applied as existing emission datasets from GVs with aim of distinguishing emissions from LNG-fueled vehicles and GVs in the Nanjing tunnel. For fleet emissions, the average VOC EFs have declined substantially over the last decade; the relative compositions of benzene, toluene, and ethylbenzene were relatively stable despite differences in fleet composition. Ethylene, isopentane, ethane, and toluene; and ethane and propane were enriched in VOC emissions (v∕v) from GVs and LNG-fueled vehicles, respectively. Methyl tert-butyl ether, 2,2,4-trimethylpentane, 2,3,4-trimethylpentane, 3-methylpentane, and methylcyclopentane were potential VOC tracers for GVs. Ethane, propane, and 2,3-dimethylbutane were key tracers that distinguished LNG-fueled vehicles from GVs. Propane, isobutane, and n-butane were key VOC tracers that distinguished liquefied petroleum gas-fueled vehicles from GVs. Alkanes dominated fleet emissions both by mass and by volume. However, aromatics and alkenes (mainly ethylene and propylene) dominated VOC reactivity from gasoline- and LNG-fueled vehicles, respectively. Our study highlights that the wide discrepancy in fleet VOC emissions could be attributed to fleet compositions.
Diesel-powered vehicles are intensively used in urban areas for transporting goods and people but can substantially contribute to high emissions of black carbon (BC), organic carbon (OC), and other gaseous pollutants. Strategies aimed at controlling mobile emissions sources thus have the potential to improve air quality and help mitigate the impacts of air pollutants on climate, ecosystems, and human health. However, in developing countries there are limited data on the BC and OC emission characteristics of diesel-powered vehicles, and thus there are large uncertainties in the estimation of the emission contributions from these sources. We measured BC, OC, and other inorganic components of fine particulate matter (PM), as well as carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), ethane, acetylene, benzene, toluene, and C2-benzenes under real-world driving conditions for 20 diesel-powered vehicles encompassing multiple emission level technologies in Mexico City with the chasing technique using the Aerodyne mobile laboratory. Average BC emission factors ranged from 0.41–2.48 g kg-1 of fuel depending on vehicle type. The vehicles were also simultaneously measured using the cross-road remote sensing technique to obtain the emission factors of nitrogen oxide (NO), CO, total hydrocarbons, and fine PM, thus allowing for the intercomparison of the results from the two techniques. There is overall good agreement between the two techniques and both can identify high and low emitters, but substantial differences were found in some of the vehicles, probably due to the ability of the chasing technique to capture a larger diversity of driving conditions in comparison to the remote sensing technique. A comparison of the results with the US EPA MOVES2014b model showed that the model underestimates CO, OC, and selected VOC species, whereas there is better agreement for NOx and BC. Larger OC / BC ratios were found in comparison to ratios measured in California using the same technique, further demonstrating the need for using locally obtained diesel-powered vehicle emission factor database in developing countries in order to reduce the uncertainty in the emissions estimates and to improve the evaluation of the effectiveness of emissions reduction measures.
Three-way catalyst (TWC) converter is one of the most important after-treatment device for modern light-duty gasoline vehicles (LDGVs), which can efficiently control exhaust emissions of carbon monoxide (CO), total hydrocarbons (THC) and nitrogen oxides (NOX). Nevertheless, a considerable part of in-use taxis in Beijing would operate with TWC purposely removed, which have been indicated by vehicular on-board diagnostic (OBD) systems. In light of high vehicle-use intensity for taxis, we recruited three China 4 non-TWC taxis and three China 4 normal taxis in a comparative experimental test by using a portable emissions measurement system (PEMS). The results indicated that non-TWC taxis emitted significantly higher emissions of air pollutants than normal taxis with TWC functioning. For example, average emission factors of non-TWC vehicles were comparable to emission levels of China 1 LDGVs measured in previous studies. By contrast, emissions from normal China 4 taxis were all below China 4 emission limits. Furthermore, an operating mode binning method and a micro-trip approach have been employed to link vehicle emissions with driving conditions. For non-TWC taxis, we identified strong correlations of all pollutant categories between emission factors and average speed. However, such correlations for normal taxis were less strong, in particular for CO and THC emissions that were hardly sensitive to speed changes. This phenomenon indicates that the role of traffic conditions in affecting real-world emissions would become weaker when TWC can effectively mitigate emissions. This paper highlights the importance of in-use emission inspection to avoid any "high emitters" that have violated regulation enforcement. © 2017 Turkish National Committee for Air Pollution Research and Control.
Kerbside concentrations of NOx, black carbon (BC), total number of particles (diameter > 4 nm) and number size distribution (28–410 nm) were measured at a busy street canyon in Stockholm in 2006 and 2013. Over this period, there was an important change in the vehicle fleet due to a strong dieselisation process of light-duty vehicles and technological improvement of vehicle engines. This study assesses the impact of these changes on ambient concentrations and particle emission factors (EF). EF were calculated by using a novel approach which combines the NOx tracer method with positive matrix factorisation (PMF) applied to particle number size distributions. NOx concentrations remained rather constant between these two years, whereas a large decrease in particle concentrations was observed, being on average 60% for BC, 50% for total particle number, and 53% for particles in the range 28–100 nm. The PMF analysis yielded three factors that were identified as contributions from gasoline vehicles, diesel fleet, and urban background. This separation allowed the calculation of the average vehicle EF for each particle metric per fuel type. In general, gasoline EF were lower than diesel EF, and EF for 2013 were lower than the ones derived for 2006. The EFBC decreased 77% for both gasoline and diesel fleets, whereas the particle number EF reduction was higher for the gasoline (79%) than for the diesel (37%) fleet. Our EF are consistent with results from other on-road studies, which reinforces that the proposed methodology is suitable for EF determination and to assess the effectiveness of policies implemented to reduce vehicle exhaust emissions. However, our EF are much higher than EF simulated with traffic emission models (HBEFA and COPERT) that are based on dynamometer measurements, except for EFBC for diesel vehicles. This finding suggests that the EF from the two leading models in Europe should be revised for BC (gasoline vehicles) and particle number (all vehicles), since they are used to compile national inventories for the road transportation sector and also to assess their associated health effects. Using the calculated kerbside EF, we estimated that the traffic emissions were lower in 2013 compared to 2006 with a 61% reduction for BC (due to decreases in both gasoline and diesel emissions), and 34–45% for particle number (reduction only in gasoline emissions). Limitations of the application of these EF to other studies are also discussed.
To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the 2015 China Victory Day Parade (Victory Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. Atmospheric particulate matter of aerodynamic diameter ≤2.5 µm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions. However, there were few days with stable meteorological conditions during the Victory Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, a generalized linear regression model (GLM) based only on meteorological parameters was built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution and, hence, the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 and 28 % to the reduction of the PM2.5 concentration during APEC and 38 and 25 % during the Victory Parade, respectively, based on the assumption that the concentrations of air pollutants are only determined by meteorological conditions and emission intensities. We also estimated the contribution of meteorological conditions and control strategies in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.
Atmospheric particle number size distributions of airborne particles (diameter range 10–500 nm) were measured over ten weeks at three sites in the vicinity of the A100 urban motorway in Berlin, Germany. The A100 carries about 180 000 vehicles on a weekday, and roadside particle size distributions showed a number maximum between 20 and 60 nm clearly related to the motorway emissions. The average total number concentration at roadside was 28 000 cm−3 with a total range between 1200 and 168 000 cm−3. At distances of 80 and 400 m from the motorway the concentrations decreased to mean levels of 11 000 and 9 000 cm−3, respectively. An obstacle-resolving dispersion model was applied to simulate the 3-D flow field and traffic tracer transport in the urban environment around the motorway. By inverse modelling, vehicle emission factors were derived, representative of a relative share of 6% lorry-like vehicles, and a driving speed of about 80 km h−1. Three different calculation approaches were compared, which differ in the choice of the experimental winds driving the flow simulation. The average emission factor per vehicle was 2.1(±0.2) · 1014 km−1 for particle number and 0.077(±0.01) · 1014 cm3 km−1 for particle volume. Regression analysis suggested that lorry-like vehicles emit 116 (± 21) times more particulate number than passenger car-like vehicles, and that lorry-like vehicles account for about 91% of particulate number emissions on weekdays. Our work highlights the increasing applicability of 3-D flow models in urban microscale environments and their usefulness in determining traffic emission factors.
The chasing method was used in an on-road measurement campaign, and emission
factors (EF) of black carbon (BC), particle number (PN) and nitrogen oxides
(NOx) were determined for 139 individual vehicles of different types
encountered on the roads. The aggregated results provide EFs for BC,
NOx and PN for three vehicle categories: goods vehicles, gasoline and
diesel passenger cars. This is the first on-road measurement study where BC
EFs of numerous individual diesel cars were determined in real-world driving
conditions. We found good agreement between EFs of goods vehicles determined
in this campaign and the results of previous studies that used either
chasing or remote-sensing measurement techniques. The composition of the
sampled car fleet determined from the national vehicle registry information
is reflective of Eurostat statistical data on the Slovenian and European
vehicle fleet. The median BC EF of diesel and gasoline cars that were in use
for less than 5 years decreased by 60 and 47 % from those in use for
5–10 years, respectively; the median NOx and PN EFs of goods
vehicles that were in use for less than 5 years decreased from those in
use for 5–10 years by 52 and 67 %, respectively. Surprisingly, we
found an increase of BC EFs in the newer goods vehicle fleet compared to the 5–10-year old one. The influence of engine maximum power of the measured EFs
showed an increase in NOx EF from least to more powerful vehicles with
diesel engines. Finally, a disproportionate contribution of high emitters to
the total emissions of the measured fleet was found; the top 25 % of
emitting diesel cars contributed 63, 47 and 61 % of BC, NOx
and PN emissions respectively. With the combination of relatively simple
on-road measurements and sophisticated post processing, individual vehicle
EF can be determined and useful information about the fleet emissions can be
obtained by exactly representing vehicles which contribute disproportionally
to vehicle fleet emissions; and monitor how the numerous emission reduction
approaches are reflected in on-road driving conditions.
An automated identification and integration method has
been developed for in-use vehicle emissions under real-world conditions.
This technique was applied to high-time-resolution air pollutant
measurements of in-use vehicle emissions performed under real-world
conditions at a near-road monitoring station in Toronto, Canada, during four
seasons, through month-long campaigns in 2013–2014. Based on carbon dioxide
measurements, over 100 000 vehicle-related plumes were automatically
identified and fuel-based emission factors for nitrogen oxides; carbon
monoxide; particle number;
black carbon; benzene, toluene, ethylbenzene, and
xylenes (BTEX); and methanol were determined for each plume. Thus the
automated identification enabled the measurement of an unprecedented number
of plumes and pollutants over an extended duration. Emission factors for
volatile organic compounds were also measured roadside for the first time
using a proton transfer reaction time-of-flight mass spectrometer; this
instrument provided the time resolution required for the plume capture
technique. Mean emission factors were characteristic of the light-duty
gasoline-dominated vehicle fleet present at the measurement site, with mean
black carbon and particle number emission factors of 35 mg kg fuel−1
and 7.5 × 1014 # kg fuel−1, respectively. The use of the
plume-by-plume analysis enabled isolation of vehicle emissions, and the
elucidation of co-emitted pollutants from similar vehicle types, variability
of emissions across the fleet, and the relative contribution from heavy
emitters. It was found that a small proportion of the fleet (< 25 %) contributed significantly to total fleet emissions: 100,
100, 81, and 77 % for black carbon, carbon monoxide, BTEX, and
particle number, respectively. Emission factors of a single pollutant may
help classify a vehicle as a high emitter; however, regulatory strategies to
more efficiently target multi-pollutant mixtures may be better developed by
considering the co-emitted pollutants as well.
Unlabelled:
Emissions tests were conducted on two medium heavy-duty diesel trucks equipped with a particulate filter (DPF), with one vehicle using a NOx absorber and the other a selective catalytic reduction (SCR) system for control of nitrogen oxides (NOx). Both vehicles were tested with two different fuels (ultra-low-sulfur diesel [ULSD] and biodiesel [B20]) and ambient temperatures (70ºF and 20ºF), while the truck with the NOx absorber was also operated at two loads (a heavy weight and a light weight). The test procedure included three driving cycles, a cold start with low transients (CSLT), the federal heavy-duty urban dynamometer driving schedule (UDDS), and a warm start with low transients (WSLT). Particulate matter (PM) emissions were measured second-by-second using an Aethalometer for black carbon (BC) concentrations and an engine exhaust particle sizer (EEPS) for particle count measurements between 5.6 and 560 nm. The DPF/NOx absorber vehicle experienced increased BC and particle number concentrations during cold starts under cold ambient conditions, with concentrations two to three times higher than under warm starts at higher ambient temperatures. The average particle count for the UDDS showed an opposite trend, with an approximately 27% decrease when ambient temperatures decreased from 70ºF to 20ºF. This vehicle experienced decreased emissions when going from ULSD to B20. The DPF/SCR vehicle tested had much lower emissions, with many of the BC and particle number measurements below detectable limits. However, both vehicles did experience elevated emissions caused by DPF regeneration. All regeneration events occurred during the UDDS cycle. Slight increases in emissions were measured during the WSLT cycles after the regeneration. However, the day after a regeneration occurred, both vehicles showed significant increases in particle number and BC for the CSLT drive cycle, with increases from 93 to 1380% for PM number emissions compared with tests following a day with no regeneration.
Implications:
The use of diesel particulate filters (DPFs) on trucks is becoming more common throughout the world. Understanding how DPFs affect air pollution emissions under varying operating conditions will be critical in implementing effective air quality standards. This study evaluated particulate matter (PM) and black carbon (BC) emissions with two DPF-equipped heavy-duty diesel trucks operating on conventional fuel and a biodiesel fuel blend at varying ambient temperatures, loads, and drive cycles.
Exposure to traffic-related air pollutants is an important public health issue. Here, we present a systematic review and meta-analysis of research examining the relationship of measures of nitrogen oxides and of various measures of traffic related air pollution exposure with lung cancer.
We conducted random effects meta-analyses of studies examining exposure to NO2 and NOx exposure and lung cancer. We identified 20 studies that met inclusion criteria and provided information necessary to estimate the change in lung cancer per 10 μg/m(3) increase in exposure to measured NO2. Further, we qualitatively assess the evidence of association between distance to roadways and traffic volume associated with lung cancer.
The meta-estimate for the change in lung cancer associated with a 10 μg/m(3) increase in exposure to NO2 was 4% (95% CI: 1%, 8%). The meta-estimate for change in lung cancer associated with a 10 μg/m(3) increase in NOx was similar and slightly more precise, 3% (95% CI: 1%, 5%). The NO2 meta-estimate was robust to different confounding adjustment sets as well as the exposure assessment techniques utilized. Trim-and-fill analyses suggest that if publication bias exists the overall meta-estimate is biased away from the null. Forest plots for measures of traffic volume and distance to roadways largely suggest a modest increase in lung cancer risk.
We found consistent evidence of a relationship between NO2 and NOx, as proxies for traffic sourced air pollution exposure, with lung cancer. Studies of lung cancer related to residential proximity to roadways also suggest increased risk, which may be due in part to air pollution exposure. The International Agency for Research on Cancer recently classified outdoor air pollution and particulate matter as carcinogenic (Group 1). These meta-analyses support this conclusion, drawing particular attention to traffic sourced air pollution.
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 (<30 nm), Aitken–mode non–volatile particles (30–100 nm), and EC–rich fine–mode particles (>100 nm). The impact of the highway emissions on air quality was observable up to 300 m.
While several cohort studies report associations between chronic exposure to fine particles (PM2.5) and mortality, few have studied the effects of chronic exposure to ultrafine (UF) particles. In addition, few studies have estimated the effects of the constituents of either PM2.5 or UF particles.
We used a statewide cohort of over 100,000 women from the California Teachers Study who were followed from 2001 through 2007. Exposure data at the residential level were provided by a chemical transport model that computed pollutant concentrations from over 900 sources in California. Besides particle mass, monthly concentrations of 11 species and 8 sources or primary particles were generated at 4 km grids. We used a Cox proportional hazards model to estimate the association between the pollutants and all-cause, cardiovascular, ischemic heart disease (IHD) and respiratory mortality.
We observed statistically significant (p < 0.05) associations of IHD with PM2.5 mass, nitrate elemental carbon (EC), copper (Cu), and secondary organics and the sources gas- and diesel-fueled vehicles, meat cooking, and high sulfur fuel combustion. The hazard ratio estimate of 1.19 (95% CI: 1.08, 1.31) for IHD in association with a 10-µg/m(3) increase in PM2.5 is consistent with findings from the American Cancer Society cohort. We also observed significant positive associations between IHD and several UF components including EC, Cu, metals, and mobile sources.
Using an emissions-based model with a 4 km spatial scale, we observed significant positive associations between IHD mortality and both fine and ultrafine particle species and sources. Our results suggest that the exposure model effectively measured local exposures and facilitated the examination of the relative toxicity of particle species.
Official motor vehicle emission inventories estimate that excess emissions during cold-start operation contribute a significant fraction of all hydrocarbon, CO, NOx emissions from California vehicles. To verify these estimates under real-world conditions, vehicle emissions were measured in an underground parking garage in Oakland, CA, during March 1997. When measured cold-start emission (CSE) factors were scaled to represent a full 200-sec cold-start period, they are lower than the used by California's motor vehicle emission inventory model. Overall, the composition of volatile organic compound emissions measured during cold start was similar to that of hot stabilized emissions. However, the weight fractions of unburned fuel and acetylene were higher.
In this paper we report the first direct measurements of nitrogen
dioxide (NO2) in the UK using a vehicle emission remote
sensing technique. Measurements of NO, NO2 and ammonia
(NH3) from almost 70,000 vehicles were made spanning vehicle
model years from 1985 to 2012. These measurements were carefully matched
with detailed vehicle information data to understand the emission
characteristics of a wide range of vehicles in a detailed way. Overall
it is found that only petrol fuelled vehicles have shown an appreciable
reduction in total NOx emissions over the past 15-20
years. Emissions of NOx from diesel vehicles, including those
with after-treatment systems designed to reduce emissions of
NOx, have not reduced over the same period of time. It is
also evident that the vehicle manufacturer has a strong influence on
emissions of NO2 for Euro 4/5 diesel cars and urban buses.
Smaller-engined Euro 4/5 diesel cars are also shown to emit less
NO2 than larger-engined vehicles. It is shown that
NOx emissions from urban buses fitted with Selective
Catalytic Reduction (SCR) are comparable to those using Exhaust Gas
Recirculation for Euro V vehicles, while reductions in NOx of
about 30% are observed for Euro IV and EEV vehicles. However, the
emissions of NO2 vary widely dependent on the bus technology
used. Almost all the NOx emission from Euro IV buses with SCR
is in the form of NO, whereas EEV vehicles (Enhanced Environmentally
friendly Vehicle) emit about 30% of the NOx as
NO2. We find similarly low amounts of NO2 from
trucks (3.5-12t and >12t). Finally, we show that NH3
emissions are most important for older generation catalyst-equipped
petrol vehicles and SCR-equipped buses. The NH3 emissions
from petrol cars have decreased by over a factor of three from the
vehicles manufactured in the late 1990s compared with those manufactured
in 2012. Tables of emission factors are presented for
NOx, NO2 and NH3 together with
uncertainties to assist the development of new emission inventories.
Canadian cities generally have good air quality; however, exposure to outdoor air pollution continues to elicit considerable negative health effects. Estimates suggest that there are 21 000 premature deaths attributable to air pollution in Canada each year,1 nearly 9 times higher than the number of deaths due to motor vehicle collisions.
The literature on traffic-related air pollution and childhood cancers is inconclusive, and little is known on rarer cancer types.
To examine associations between childhood cancers and traffic-related pollution exposure.
The present study included children younger than age 6 identified in the California cancer registry (born 1998-2007) who could be linked to a California birth certificate (N=3590). Controls were selected at random from California birthrolls (N=80,224). CAlifornia LINE Source Dispersion Modeling, version 4 (CALINE4) was used to generate estimates of local traffic exposures for each trimester of pregnancy and in the first year of life at the address indicated on the birth certificate. We checked our findings by additionally examining associations with particulate matter (PM2.5) pollution measured by community-based air pollution monitors, and with a simple measure of traffic density.
Using unconditional logistic regression, a per interquartile range increase in exposure to traffic-related pollution during the first trimester (0.0538 ppm CO, estimated using CALINE4) was associated with acute lymphoblastic leukemia (ALL; 1st trimester OR=1.05; 95% CI: 1.01, 1.10); germ cell tumors (OR=1.16; 95% CI: 1.04, 1.29), particularly teratomas (OR=1.26; 95% CI: 1.12, 1.41); and retinoblastoma (OR=1.11; 95% CI: 1.01, 1.21), particularly bilateral retinoblastoma (OR=1.16; 95%CI: 1.02, 1.33). Retinoblastoma was also associated with average PM2.5 concentrations during pregnancy, and ALL and teratomas were associated with traffic density near the child's residence at birth.
We estimated weak associations between early exposure to traffic pollution and several childhood cancers. As this is the first study to report upon traffic pollution in relation to retinoblastoma or germ cell tumors, and both cancers are rare, these findings require replication in other studies.
Exposure to traffic-related air pollution has been linked to increased risks of cardiopulmonary disease, asthma, and reduced lung function. Ultrafine particles (UFP; aerodynamic diameter < 100 nm), one component of traffic exhaust, may contribute to these risks. This paper describes the development of UFP emission factors, an important input parameter for dispersion models used for exposure assessment. Measurements of particle number concentration (PNC), a proxy for UFP, were performed in the Central Artery Tunnel on Interstate-93 in Boston (MA, USA). The tunnel system consists of two, unidirectional bores, which each carry ∼9 × 104 vehicles per day (diesel vehicles comprise 2–5% of the fleet in the southbound tunnel and 1–3% in the northbound tunnel). A tunnel was chosen for study because it provided an enclosed environment where the effects of lateral and vertical dispersion by ambient air and photochemical reactions would be minimized. Data were collected using a mobile platform equipped with rapid-response instruments for measuring PNC (4–3000 nm) as well as NOx. Because Boston is located in a temperate region (latitude 42° N), we were interested in studying seasonal and diurnal differences in emission factors. To characterize seasonal differences, mobile monitoring was performed on 36 days spaced at 7–14 day intervals over one year (Sept. 2010–Sept. 2011); to characterize diurnal differences intensive mobile monitoring (n = 90 total trips through the tunnels) was performed over the course of two consecutive days in January 2012. All data collected during congested traffic conditions (∼7% of total data set) were removed from the analysis. The median PNC inside the two tunnels for all trips during the 12-month campaign was 3–4-fold higher than on I-93 immediately outside the tunnel and 7–10-fold higher than on I-93 4 km from the tunnel. The median particle number emission factors (EFPN) (±median absolute deviation) for the southbound and northbound tunnels were 5.1 × 1014 (2.3 × 1014) and 1.4 × 1014 (4.2 × 1013) particles vehicle−1 km−1, respectively. EFPN values were ∼2-fold higher in winter and spring (average ambient temperature at the time of monitoring = 6.9 °C) compared to summer and fall (12.9 °C), and ∼2-fold higher in the morning (−7.9 °C) compared to the afternoon/evening (−0.9 °C) on two consecutive winter days. Our results suggest that seasonal and diurnal variations in particulate emissions from highway vehicles may be important to consider in developing EFPN values.
A fuel-based methodology for calculating motor vehicle emission inventories is presented. In the fuel-based method, emission factors are normalized to fuel consumption and expressed as grams of pollutant emitted per gallon of gasoline burned. Fleet-average emission factors are calculated from the measured on-road emissions of a large, random sample of vehicles. Gasoline use is known at the state level from sales tax data, and may be disaggregated to individual air basins. A fuel-based motor vehicle CO inventory was calculated for the South Coast Air Basin in California for summer 1991. Emission factors were calculated from remote sensing measurements of more than 70,000 in-use vehicles. Stabilized exhaust emissions of CO were estimated to be 4400 tons/day for cars and 1500 tons/day for light-duty and medium- duty trucks, with an estimated uncertainty of ±20% for cars and ±30% for trucks. Total motor vehicle CO emissions, including incremental start emissions and emissions from heavy-duty vehicles were estimated to be 7900 tons/day. Fuelbased inventory estimates were greater than those of California's MVEI 7F model by factors of 2.2 for cars and 2.6 for trucks. A draft version of California's MVEI 7G model, which includes increased contributions from high-emitting vehicles and off-cycle emissions, predicted CO emissions which closely matched the fuel-based inventory. An analysis of CO mass emissions as a function of vehicle age revealed that cars and trucks which were ten or more years old were responsible for 58% of stabilized exhaust CO emissions from all cars and trucks.
This paper presents measurements of traffic-generated gas and particle pollution at two sites, one near a major highway and one near a busy urban street in Copenhagen, Denmark. Both sites were equipped for a 4-week period with a set of two measurement stations, one close to the kerbside and one background station. Measurements were carried out from March to April∼2008, investigating NOx concentrations, submicrometer particle number size distribution (size range 10ĝ€"700 nm), particle mass (PM2.5, PM10), and meteorological parameters. In this study we also estimate the emission factors for NOx, particle number and particle mass using measured traffic volume and dilution rate calculated by the Operational Street Pollution Model (WinOSPM).
The mean concentrations of most of the measured pollutants are similar for the highway and the urban kerbside stations due to similar traffic density. The average concentrations of NOx are 142 μg m−3 and 136 μg m−3 for the highway and the urban kerbside stations, respectively. These values are about 5 times higher compared to the corresponding background values. The average particle number concentration is 24 900 particles cm−3 and 27 100 particles cm−3 for the highway and the urban kerbside stations, respectively, and these values exceed those measured at the background stations by a factor of 3 to 5.
The temporal variation of the traffic contribution (difference of kerbside and background concentrations) is analysed for NOx, particle number and mass, and it follows the traffic pattern at the urban and the highway sites. Emission factors for particle number are found to be quite similar at both sites, (215±5) 1012 particles veh−1 km−1 for the highway and (187±3) 1012 particles veh−1 km−1 for the urban site. Heavy duty vehicles (HDVs) are found to emit about 20 times more particles than light duty vehicles (LDVs), which is in good agreement with other published studies. Emission factors are also determined for individual particle modes identified in the size spectra. Average fleet emission factors for PM2.5 at the highway and the urban site are 29 mg veh−1 km−1 and 46 mg veh−1 km−1, respectively. The estimated particle number and size spectra emission factors will provide valuable input for air quality and particle dispersion modelling near highways and in urban areas.
It is well accepted that airborne particles can induce adverse health effects dependent on the source, composition, morphology and size. Studies indicate that ultrafine particles (diameter < 100 nm) are of specific importance. Therefore, upwind and downwind field measurements of particle number size distributions (14–750 nm), nitrogen oxides, PM10 and PM1 mass concentrations were performed to derive information on sources of those types of particles from motorways. The measurement stations were located at a motorway in a rural area with flat terrain and unhindered air flow situation. The mean particle number concentration was 20,900 #/cm3 downwind and 3,400 #/cm3 upwind of the motorway. The highest total particle number concentration at the downwind station was 141,000 #/cm3. About 90% of these particles were < 100 nm. The measured data were used to derive size-dependent emission factors (EF) using the NOx tracer method. This method is based on listed NOx EF (HBEFA, 2010). The average total particle number EF per vehicle was determined to be 3.5 × 1014 particles/km. The average particle EF was 2.1 × 1014 particles/km and 11.8 × 1014 particles/km for light duty vehicles (LDV) and heavy duty vehicles (HDV). The higher EF for HDV is mainly caused by particles with diameters below 50 nm. The comparison of EF from the literature show the importance of the particle size range investigated. Especially particles at the lower size detection limit contribute to total particle number concentrations and hence determine the EF significantly. In the EURO V directive, particle number emission limits of 6 × 1011 particles/km were set for diesel passenger cars. This value is defined for non-volatile particles > 23 nm. The EF for the given size range (> 23 nm)determined in this study were significantly higher with 1.0 × 1014 for LDV.
To evaluate the success of vehicle emissions regulations, trends in both fleet-wide average emissions as well as high-emitter emissions are needed, but it is challenging to capture the full spread of vehicle emission factors (EFs) with chassis dynamometer or tunnel studies, and remote sensing studies cannot evaluate particulate compounds. We developed an alternative method that links real-time on-road pollutant measurements from a mobile platform with real-time traffic data, and allows efficient calculation of both the average and the spread of EFs for light-duty gasoline-powered vehicles (LDG) and heavy-duty diesel-powered vehicles (HDD). This is the first study in California to report EFs under a full range of real-world driving conditions on multiple freeways. Fleet average LDG EFs were in agreement with most recent studies and an order of magnitude lower than observed HDD EFs. HDD EFs reflected the relatively rapid decreases in diesel emissions that have recently occurred in Los Angeles/California, and on I-710, a primary route used for goods movement and a focus of additional truck fleet turnover incentives, HDD EFs were often lower than on other freeways. When freeway emission rates (ER) were quantified as the product of EF and vehicle miles traveled (VMT) per time per mile of freeway, despite a twoto three-fold difference in HDD fractions between freeways, ERs were found to be generally similar in magnitude. Higher LDG VMT on low HDD fraction freeways largely offset the difference. Therefore, the conventional assumption that free ways with the highest HDD fractions are significantly worse sources of total emissions in Los Angeles may no longer be true.
The growing number of health studies identifying adverse health effects for populations spending significant amounts of time
near large roadways has increased the interest in monitoring air quality in this microenvironment. Designing near-road air
monitoring networks or interpreting previously collected near-road monitoring data is essential for transportation system
planning, environmental impact assessments, and exposure assessments in health studies. For these applications, care must
be taken in determining the pollutants of interest for both air quality and health assessments. In addition, planners and
data analysts need to evaluate and understand the potential influence of the roadway type, design, and presence of roadside
structures on the potential transport and dispersion of traffic-emitted pollutants on these air quality and health evaluations.
This paper summarizes key factors related to the collection and interpretation of near-road air quality data from the perspective
of the pollutants of interest and the location of the monitoring sites.
Gas- and particle-phase pollutants were measured separately for (a) light-duty (LD) vehicles and (b) medium-duty (MD) and heavy-duty (HD) diesel trucks. Measurements were made during summer 2006 at the Caldecott Tunnel in the San Francisco Bay area as part of a continuing campaign to track changes in vehicle emissions over time. When normalized to fuel consumption, NOx emission factors were found to be 3.0±0.2 and 40±3 g kg−1 for LD vehicles and MD/HD diesel trucks, respectively. Corresponding particulate matter (PM2.5) emission factors were 0.07±0.02 and 1.4±0.3 g kg−1. The ratio of particulate black carbon to organic mass (BC/OM) for LD vehicles was 0.71±0.15. For diesel trucks, BC/OM was 2±1, indicating that PM2.5 was dominated by BC. Results from 2006 are compared to similar measurements made at the same site in 1997. For LD vehicles, NOx and PM2.5 emission factors decreased by 67±3% and 36±17%, respectively. Corresponding decreases for diesel trucks were 30±9% for NOx and 48±12% for PM2.5. The ratio of HD to LD emission factor for NOx increased from 6±1 to 13±1 between 1997 and 2006, which indicates an increase in the relative importance of diesel trucks as a source of NOx emissions. The absorption, scattering, and extinction cross-section emission factors parameters relevant to climate change and atmospheric visibility, were an order of magnitude higher for diesel trucks than LD vehicles. Single-scattering albedo, measured at λ=675 nm, was 0.31±0.06 and 0.20±0.05 for LD vehicle and diesel truck PM emissions, respectively.
The road transportation sector contributes largely to air pollution in urban areas, why the knowledge of accurate vehicle emission factors (EF) is crucial to prepare reliable emission inventories, which, in turn, are strategic tools for air quality management. Curbside and rooftop concentrations of several traffic-related species were measured within a busy street canyon in Londrina (Brazil). EF for NOx, black carbon (BC), fine particles (PM2.5) and particle number (PN) were calculated based on these measurements and on inverse modeling using the Operational Street Pollution Model (OSPM). We highlight the importance of this work in quantifying BC, PM2.5, NOx and PN emissions from vehicles driven in an urban area under real conditions in a continent-sized country where there is a lack of EF studies. In the case of EFPN, we report the first value in the entire South America. Our EF were consistent with results from other on-road studies, but much higher than laboratory measurements conducted in Brazil and Europe, especially for particles (quantified as mass and number). This finding suggests that the EF derived from laboratory tests should be revised for all vehicle categories, since inaccurate values can have major implications on the compilation of official national inventories for the road transportation sector and on the assessment of their health and climate (in the case of BC) impacts. Incorporating certification procedures that more closely resemble real driving conditions is highly recommended. Limitations of the EF determined in this research for application in other studies are also discussed.
Temporal variations of vehicle emissions are affected by various compounding factors in the real world. The focus of this study is to determine the effects of ambient conditions and post-tailpipe changes on traffic emissions measured in the near-road region. Emission factors allowed for the isolation of the traffic signal and accounted for effects of local meteorology and dilution. Five month-long measurement campaigns were conducted at an urban near-road site that exhibited a broad range of ambient conditions with temperatures ranging between −18 and +30 °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.
In 2010, the U.S. Environmental Protection Agency (EPA) revised the National Ambient Air Quality Standards (NAAQS) for NO2 to include a primary health-based standard for hourly NO2, and required air quality monitoring next to major roadways in urban areas in the U.S. Requirements for near-road measurements also include carbon monoxide (CO) and particulate matter smaller than 2.5 μm in diameter (PM2.5). We performed a national-scale assessment of air pollutants measured at 81 sites in the near-road environment during the first two years (2014 and 2015) of the new measurement program. We evaluated how concentrations at these locations compared to the NAAQS, to concentrations measured at other sites within the same urban areas, and when considering their site characteristics (distance of monitor to road, traffic volume, and meteorology). We also estimated the contribution of emissions from adjacent roadways at each near-road site to the PM2.5 concentrations above the local urban background concentrations, i.e., the near-road “increment.” Hourly values of CO reached a maximum of 4.8 ppm across 31 sites in 2014 and 9.6 ppm across 47 sites in 2015, and were well below the NAAQS levels for both the 1-hr (35 ppm) and 8-hr (9 ppm) standards. Hourly concentrations of near-road NO2 reached 258 ppb across 40 sites in 2014; however, there were only two occurrences of a daily 1-hr maximum NO2 concentration above 100 ppb (the level of the hourly NO2 standard). In 2015, hourly concentrations of near-road NO2, monitored at 61 sites in 55 urban areas, reached 154 ppb. Only 0.0015% (n = 5) of hourly NO2 observations in 2015 exceeded 100 ppb. The highest annual NO2 average recorded in 2015 (29.9 ppb) occurred at the Ontario site located along I-10 in the Los Angeles, California, area and was below the level of the NO2 annual standard (53 ppb); in 2014, the highest annual mean NO2 was also observed in Los Angeles at the Anaheim site (27.1 ppb). In 2014, sites in Cincinnati, Indianapolis, and Louisville recorded annual average PM2.5 concentrations at or above 12 μg/m³ (the level of the annual standard). There were 15 occurrences in 2014 of 24-hr PM2.5 concentrations above the NAAQS level of 35 μg/m³. Annual average PM2.5 exceeded 12 μg/m³ at near-road sites in five urban areas in 2015, and there were 33 days across 12 near-road locations with 24-hr PM2.5 concentrations above 35 μg/m³. Across the near-road monitoring network, annual average PM2.5 concentrations did not have a significant relationship with traffic volume or distance between the monitor and the adjacent roadway; rather, variations in PM2.5 were mostly driven by urban-scale PM2.5, with a typically small “increment” above urban-scale concentrations due to a site's proximity to the roadway. We estimated this increment, i.e., the difference between near-road PM2.5 concentrations and the concentrations at sites in the urban area of each near-road monitor, to be on average 1.2 μg/m³ (σ = 0.3 μg/m³), with a range of −1.2 μg/m³ to 3.1 μg/m³ across the 26 sites (four of which had a negative increment). The near-road increment is on average 13% of the near-road PM2.5, and 15% of the near-road PM2.5 for sites within 20 m of the roadway.
Significance
We report the significant presence of traffic-originated nanocluster aerosol (NCA) particles in a particle diameter range of 1.3–3.0 nm of urban air, determine the emission factors for the NCA, and evaluate its global importance. Our findings are important because they significantly update the current understanding of atmospheric aerosol in urban areas. They demonstrate that in urban air, extremely small particles form a significant fraction of the total particle number and are a direct result of anthropogenic emissions, that is, the emissions from road traffic. Thus, our findings also imply that in urban areas, an atmospheric nucleation process is not necessary for the formation of a large number of particles that affect population health and climate.
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.
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. In order 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. Based on 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.
Compared to port fuel injection (PFI) engine exhaust, gasoline direct injection (GDI) engine exhaust has higher emissions of black carbon (BC), a climate-warming pollutant. However, the relative increase in BC emissions and climate trade-offs of replacing PFI vehicles with more fuel efficient GDI vehicles remain uncertain. In this study, BC emissions from GDI and PFI vehicles were compiled and BC emissions scenarios were developed to evaluate the climate impact of GDI vehicles using global warming potential (GWP) and global temperature potential (GTP) metrics. From a 20 year time horizon GWP analysis, average fuel economy improvements ranging from 0.14 to 14% with GDI vehicles are required to offset BC-induced warming. For all but the lowest BC scenario, installing a gasoline particulate filter with an 80% BC removal efficiency and <1% fuel penalty is climate beneficial. From the GTP-based analysis, it was also determined that GDI vehicles are climate beneficial within <1-20 years; longer time horizons were associated with higher BC scenarios. The GDI BC emissions spanned 2 orders of magnitude and varied by ambient temperature, engine operation, and fuel composition. More work is needed to understand BC formation mechanisms in GDI engines to ensure that the climate impacts of this engine technology are minimal.
Assessment of the global burden of disease is based on epidemiological cohort studies that connect premature mortality to a wide range of causes, including the long-term health impacts of ozone and fine particulate matter with a diameter smaller than 2.5 micrometres (PM2.5). It has proved difficult to quantify premature mortality related to air pollution, notably in regions where air quality is not monitored, and also because the toxicity of particles from various sources may vary. Here we use a global atmospheric chemistry model to investigate the link between premature mortality and seven emission source categories in urban and rural environments. In accord with the global burden of disease for 2010 (ref. 5), we calculate that outdoor air pollution, mostly by PM2.5, leads to 3.3 (95 per cent confidence interval 1.61-4.81) million premature deaths per year worldwide, predominantly in Asia. We primarily assume that all particles are equally toxic, but also include a sensitivity study that accounts for differential toxicity. We find that emissions from residential energy use such as heating and cooking, prevalent in India and China, have the largest impact on premature mortality globally, being even more dominant if carbonaceous particles are assumed to be most toxic. Whereas in much of the USA and in a few other countries emissions from traffic and power generation are important, in eastern USA, Europe, Russia and East Asia agricultural emissions make the largest relative contribution to PM2.5, with the estimate of overall health impact depending on assumptions regarding particle toxicity. Model projections based on a business-as-usual emission scenario indicate that the contribution of outdoor air pollution to premature mortality could double by 2050.
Tailpipe emissions from sixty-four unique light-duty gasoline vehicles (LDGVs) spanning model years 1987-2012, two medium-duty diesel vehicles and three heavy-duty diesel vehicles with varying levels of aftertreatment were characterized at the California Air Resources Board Haagen-Smit and Heavy-Duty Engine Testing Laboratories. Each vehicle was tested on a chassis dynamometer using a constant volume sampler, commercial fuels and standard duty cycles. Measurements included regulated pollutants such as carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NOx), and particulate matter (PM). Off-line analyses were performed to speciate gas- and particle-phase emissions. The data were used to investigate trends in emissions with vehicle age and to quantify the effects of different aftertreatment technologies on diesel vehicle emissions (e.g., with and without a diesel particulate filter). On average, newer LDGVs that met the most recent emissions standards had substantially lower emissions of regulated gaseous pollutants (CO, THC and NOx) than older vehicles. For example, THC emissions from the median LDGV that met the LEV2 standard was roughly a factor of 10 lower than the median pre-LEV vehicle; there were also substantial reductions in NOx (factor of similar to 100) and CO (factor of similar to 10) emissions
We assessed the emissions response of a fleet of seven light-duty gasoline vehicles to gasoline fuel aromatic content while operating over the LA92 driving cycle. The test fleet consisted of model year 2012 vehicles equipped with either port fuel injection (PFI) or direct injection (DI) technology. Three gasoline fuels were blended to meet a range in total aromatics targets (15%, 25%, and 35% by volume) while holding other fuel properties relatively constant within specified ranges, and a fourth fuel was formulated to meet a 35% by volume total aromatics target, but with a higher octane number. Our results showed statistically significant increases in carbon monoxide (CO), non-methane hydrocarbon (NMHC), particulate matter (PM) mass, particle number, and black carbon emissions with increasing aromatics content for all seven vehicles tested. Only one vehicle showed a statistically significant increase in total hydrocarbon (THC) emissions. The monoaromatic hydrocarbon species that were evaluated showed increases with increasing aromatic content in the fuel. Changes in fuel composition had no statistically significant effect on emissions of nitrogen oxides (NOx), formaldehyde, and acetaldehyde. A good correlation was also found between the PM index and PM mass and number emissions for all vehicle/fuel combinations, with the total aromatics group being a significant contributor to the total PM index followed by naphthalenes and indenes.
A few recent studies have reported positive associations between long-term exposure to traffic-related air pollution and the incidence of breast cancer. We capitalized on an existing Canadian multi-site population-based case–control study to further investigate this association.
We used the National Enhanced Cancer Surveillance System, a population-based case–control study conducted in eight of 10 Canadian provinces from 1994 to 1997. A total of 1569 breast cancer cases and 1872 population controls who reported at least 90% complete self-reported addresses over the 1975–1994 exposure period were examined. Mean exposure levels to nitrogen dioxide (NO2) (an indicator of traffic-related air pollution) were estimated for this period using three different measures: (1) satellite-derived observations; (2) satellite-derived observations scaled with historical fixed-site measurements of NO2; and (3) a national land-use regression (LUR) model. Proximity to major roads was also examined. Using unconditional logistic regression, stratified by menopausal status, we estimated odds ratios (ORs) adjusted for many individual-level and contextual breast cancer risk factors.
We observed positive associations between incident breast cancer and all three measures of NO2 exposure from 1975 to 1994. In fully adjusted models for premenopausal breast cancer, a 10 ppb increase in NO2 exposure estimated from the satellite-derived observations, the scaled satellite-derived observations, and the national LUR model produced ORs of 1.26 (95% confidence intervals (CIs): 0.92–1.74), 1.32 (95% CI: 1.05–1.67) and 1.28 (95% CI: 0.92–1.79). For postmenopausal breast cancer, we found corresponding ORs of 1.10 (95% CI: 0.88–1.36), 1.10 (95% CI: 0.94–1.28) and 1.07 (95% CI: 0.86–1.32). Substantial heterogeneity in the ORs was observed across the eight Canadian provinces and reduced ORs were observed when models were restricted to women who had received routine mammography examinations. No associations were found for road proximity measures.
This study provides some support for the hypothesis that traffic-related air pollution may be associated with the development of breast cancer, especially in premenopausal women. With the few studies available, further research is clearly needed.
Traffic and power generation are the main sources of urban air pollution. The idea that outdoor air pollution can cause exacerbations of pre-existing asthma is supported by an evidence base that has been accumulating for several decades, with several studies suggesting a contribution to new-onset asthma as well. In this Series paper, we discuss the effects of particulate matter (PM), gaseous pollutants (ozone, nitrogen dioxide, and sulphur dioxide), and mixed traffic-related air pollution. We focus on clinical studies, both epidemiological and experimental, published in the previous 5 years. From a mechanistic perspective, air pollutants probably cause oxidative injury to the airways, leading to inflammation, remodelling, and increased risk of sensitisation. Although several pollutants have been linked to new-onset asthma, the strength of the evidence is variable. We also discuss clinical implications, policy issues, and research gaps relevant to air pollution and asthma.
Black carbon (BC) mass and solid particle number emissions were obtained from two pairs of gasoline direct injection (GDI) vehicles and port fuel injection (PFI) vehicles over the U.S. Federal Test Procedure 75 (FTP-75) and US06 Supplemental Federal Test Procedure (US06) drive cycles on gasoline and 10% by volume blended ethanol (E10). BC solid particles were emitted mostly during cold-start from all GDI and PFI vehicles. The reduction in ambient temperature had significant impacts on BC mass and solid particle number emissions but larger impacts were observed on the PFI vehicles than the GDI vehicles. Over the FTP-75 phase 1 (cold-start) drive cycle, the BC mass emissions from the two GDI vehicles at 0°F (-18°C) varied from 57-143 mg/mile, which was higher than the emissions at 72°F (22°C; 12-29 mg/mile) by a factor of 5. For the two PFI vehicles, the BC mass emissions over the FTP-75 phase 1 drive cycle at 0°F varied from 111-162 mg/mile, higher by a factor of 44-72 when compared to the BC emissions of 2-4 mg/mi at 72°F. The use of a gasoline particulate filter (GPF) reduced BC emissions from the selected GDI vehicle by 73-88% at various ambient temperatures over the FTP-75 phase 1 drive cycle. The ambient temperature had less of an impact on particle emissions for a warmed-up engine. Over the US06 drive cycle, the GPF reduced BC mass emissions from the GDI vehicle by 59-80% at various temperatures. E10 had limited impact on BC emissions from the selected GDI and PFI vehicles during hot-starts. E10 was found to reduce BC emissions from the GDI vehicle by 15% at standard temperature and by 75% at 19°F (-7°C).
Vehicle emissions of nitrogen oxides (NOx), carbon monoxide (CO), fine particulate matter (PM2.5), organic aerosol (OA) and black carbon (BC) were measured at the Caldecott tunnel in the San Francisco Bay Area. Measurements were made in the middle bore of the tunnel where light-duty (LD) vehicles accounted for >99% of total traffic, and where heavy-duty trucks were not allowed. Prior emission studies conducted in North America have often assumed that route- or weekend-specific prohibitions on heavy-duty truck traffic imply that diesel contributions to pollutant concentrations measured in on-road settings can be neglected. However, as light-duty vehicle emissions have declined, this assumption can lead to biased results, especially for pollutants such as NOx, OA, and BC, for which diesel engine emission rates are high compared to corresponding values for gasoline engines. In this study, diesel vehicles (mostly medium duty delivery trucks with 2 axles and 6 tires) accounted for <1% of all vehicles observed in the tunnel, but were nevertheless responsible for 18 ± 3, 22 ± 6, 45 ± 8% of measured NOx, OA, and BC concentrations. Fleet-average OA and BC emission factors for light-duty vehicles are respectively 10 and 50 times lower than for heavy-duty diesel trucks. Using measured emission factors from this study and publicly available data on taxable fuel sales, as of 2010, LD gasoline vehicles were estimated to be responsible for 85, 18, 18 and 6% of emissions of CO, NOx, OA, and BC from on-road motor vehicles in the United States.
This study estimates the size and distribution of the population living near high volume roads in the US, investigates race and income disparities in these near roadway populations, and considers the coverage of the national ambient air quality monitoring network. Every US census block is classified by traffic density and proximity to roads falling within several traffic volume ranges using year 2008 traffic data and the 2010 and 2000 US Census. The results indicate that 19% of the population lives near high volume roads. Nationally, greater traffic volume and density are associated with larger shares of non-white residents and lower median household incomes. Analysis at the county level finds wide variation in the size of near roadway populations and the severity of environmental justice concerns. Every state, however, has some population living near a high volume road and 84% of counties show some level of disparity. The results also suggest that most counties with residents living near high volume roads do not have a co-located regulatory air quality monitor.
Pollutant concentrations in the exhaust plumes of individual diesel trucks were measured at high time resolution in a highway tunnel in Oakland, CA, during July 2010. Emission factors for individual trucks were calculated using a carbon balance method, in which pollutants measured in each exhaust plume were normalized to measured concentrations of carbon dioxide. Pollutants considered here include nitric oxide, nitrogen dioxide (NO(2)), carbon monoxide, formaldehyde, ethene, and black carbon (BC), as well as optical properties of emitted particles. Fleet-average emission factors for oxides of nitrogen (NO(x)) and BC respectively decreased 30 ± 6 and 37 ± 10% relative to levels measured at the same location in 2006, whereas a 34 ± 18% increase in the average NO(2) emission factor was observed. Emissions distributions for all species were skewed with a small fraction of trucks contributing disproportionately to total emissions. For example, the dirtiest 10% of trucks emitted half of total NO(2) and BC emissions. Emission rates for NO(2) were found to be anticorrelated with all other species considered here, likely due to the use of catalyzed diesel particle filters to help control exhaust emissions. Absorption and scattering cross-section emission factors were used to calculate the aerosol single scattering albedo (SSA, at 532 nm) for individual truck exhaust plumes, which averaged 0.14 ± 0.03.
Emission factors for particle number in three size ranges (11–30; 30–100 and >100 nm) as well as for PM2.5, PM2.5−10 and PM10 mass have been estimated separately for heavy and light-duty vehicles in a heavily trafficked street canyon in London where traffic speeds vary considerably over short distances. Emissions of NOx were estimated from published emission factors, and emissions of other pollutants estimated from their ratio to NOx in the roadside concentration after subtraction of the simultaneously measured urban background. The estimated emission factors are compared with other published data. Despite many differences in the design and implementation of the various studies, the results for particulate matter are broadly similar. Estimates of particle number emissions in this study for light-duty vehicles are very close to other published data, whilst those for heavy-duty vehicles are lower than in the more comparable studies. It is suggested that a contributory factor may be the introduction of diesel particle oxidation traps on some of the bus fleet in London. Estimates of emission factors for particle mass (PM2.5 and PM2.5−10) are within the range of other published data, and total mass emissions estimated from the ratio of concentration to NOx are tolerably close to those estimated using emission factors from the National Atmospheric Emissions Inventory (NAEI). However, the method leads to an estimate of carbon monoxide emissions 3–6 times larger than that derived using the NAEI factors.
Studies have suggested that aerosol number concentrations may be better correlated to health effects than mass concentrations so that the high particle number concentrations in the vicinity of freeways raise concerns regarding adverse health effects on people living there. Thus, it is important to understand how particles transport and transform near roadways for regulatory purposes. Driven by different mixing forces, exhaust dilution near roadways usually experiences two distinct dilution stages after being emitted—‘tailpipe-to-road’ and ‘road-to-ambient’. The first stage dilution is induced by traffic-generated turbulence and the dilution ratio usually reaches up to about 1000:1 in around 1–3 s; the second stage dilution is mainly dependent on atmospheric turbulence, the additional dilution ratio is usually about 10:1, and the process usually lasts around 3–10 min. The aerosol dynamical processes, such as nucleation, condensation and coagulation were qualitatively investigated in the first stage. For the second stage, condensation and dilution were the major mechanisms in altering aerosol size distribution, while coagulation and deposition play minor roles. Based on the analysis, a modeling structure for a mechanistic roadway air quality model is proposed. Our study also indicates that in order to simulate the first stage, ‘in-tailpipe’ measurement of aerosol size distribution and condensable material concentrations in their original phase states is necessary. The implications for dilution tunnel design are discussed.
Decoupling cetane number from the other compositions and properties of diesel fuel, the individual effect of cetane number on the exhaust emissions from an engine may be researched. This paper has presented a back-propagation neural network model predicting the exhaust emissions from an engine with the inputs of total cetane number, base cetane number and cetane improver, total cetane number and nitrogen content in the diesel fuel; as well as the output of the exhaust emissions of hydrocarbon (HC), carbon oxide (CO), particulate matter (PM) and nitrogen oxide (NOx). An optimal design has been completed for the number of hidden layers, the number of hidden neurons, the activation function, and the goal errors, along with the initial weights and biases in the back-propagation neural network model. HC, CO, PM and NOx have been predicted with the model, the effects of cetane improver and nitrogen content on them have also been analyzed, and better results have been achieved.
In-use, fuel-based motor vehicle emission factors were determined using measurements made in a highway tunnel in Pittsburgh, Pennsylvania. Concentrations of PM2.5 mass, CO, CO2, and NOx were measured continuously. Filter-based measurements included PM2.5 mass, organic and elemental carbon (OC and EC), inorganic ions and metals. Fuel-based emission factors for each pollutant were calculated using a fuel-carbon balance. The weekday traffic volume and fleet composition varied in a consistent diurnal pattern with the estimated fraction of fuel consumed by heavy-duty diesel vehicle (HDDV) traffic ranging from 11% to 36%. The emission rate of most species showed a significant dependence on sample period. NOx, PM2.5, EC and OC emission factors were significantly larger during the early morning, truck-dominated period. Emissions of particulate metals associated with brake wear (Cu, Sb, Ba and potentially Ga) were emitted at higher rates during the rush-hour period, which is characterized by slower, stop-and-go traffic. Emission rates of crustal elements (Fe, Ca, Mg, Li), Zn and Mn were highest during the early-morning period when there was more heavy-truck traffic. A seasonal shift in average OC/EC ratio for the rush-hour period was observed; fall and summer OC/EC ratios are 1.0±0.6 and 0.26±0.06, respectively. Potential causes for this shift are increased partitioning of semi-volatile organic compounds into the gas phase during the summer months and/or effects of seasonal changes in fuel formulation. Emission factors for HDDV and light-duty vehicles (LDV) classes were estimated using a linear regression of emission factor as a function of fleet composition. The extrapolated emission factors generally agree with previously published measurements, though a substantial range in published values is noted.
The objective of this project was to characterize on-road aerosol on highways surrounding the Minneapolis area. Data were collected under varying on-road traffic conditions and in residential areas to determine the impact of highway traffic on air quality. The study was focused on determining on-road nanoparticle concentrations, and estimating fuel-specific and particle emissions km−1.On-road aerosol number concentrations ranged from 104 to 106 particles cm−3. The highest nanoparticle concentrations were associated with high-speed traffic. At high vehicular speeds engine load, exhaust temperature, and exhaust flow all increase resulting in higher emissions. Less variation was observed in particle volume, a surrogate measure of particle mass. Most of the particles added by the on-road fleet were below 50 nm in diameter. Particles in this size range may dominate particle number, but contribute little to particle volume or mass. Furthermore, particle number is strongly influenced by nucleation and coagulation, which have little or no effect on particle volume. Measurements made in heavy traffic, speeds<32 km h−1, produced lower number concentrations and larger particles.Number concentrations measured in residential areas, 10–20 m from the highway, were considerably lower than on-road concentrations, but the size distributions were similar to on-road aerosol with high concentrations of very small (<20 nm) particles. Much lower number concentrations and larger particles were observed in residential areas located 500–700 m from the highway.Estimated emissions of total particle number larger than 3 nm ranged from 1.9 to 9.9×1014 particles km−1 and 2.2–11×1015 particles (kg fuel)−1 for a gasoline-dominated vehicle fleet.
Context Abstract: Nitrous oxide (NO2) is a potent greenhouse gas whose atmospheric budget is poorly constrained. One known atmospheric source is the formation of N2O on three-way motor vehicle catalytic converters followed by emission with the exhaust. Previous estimates of the magnitude of this N2O source have varied widely. Two methods employing tunable infrared lasers to measure N2O/CO2 ratios from a large number of on-road motor vehicles have been developed. Both methods add support to lower estimates of N2O emissions from the US motor vehicle fleet, although significant uncertainty remains.Main Abstract: Two tunable infrared laser differential absorption spectroscopy (TILDAS) techniques have been used to measure the N2O emission levels of on-road motor vehicle exhausts. Cross road, open path laser measurements were used to assess N2O emissions from 1361 California catalyst equipped vehicles in November, 1996 yielding an emission ratio of (8.8±2.8)×10−5 N2O/CO2. A van mounted TILDAS sampling system making on-road N2O measurements in mixed traffic in June, 1998 in Manchester, New Hampshire yielded a mean N2O/CO2 ratio of (12.8±0.3)×10−5, based on correlated N2O and CO2 concentration peaks attributed to motor vehicle exhaust plumes. The correlation of N2O emissions with vehicle type, model year and NO emissions are presented for the California data set. It is found that the N2O emission distribution is highly skewed, with more than 50% of the emissions being contributed by 10% of the vehicles. Comparison of our results with those from four European tunnel studies reveals a wide range of derived N2O emission indices, with the most recent studies (including this study) finding lower values.
Measurements of black carbon (BC) with a high-sensitivity laser-induced incandescence (HS-LII) instrument and a single particle soot photometer (SP2) were conducted upwind, downwind, and while driving on a highway dominated by gasoline vehicles. The results are used with concurrent CO(2) measurements to derive fuel-based BC emission factors for real-world average fleet and heavy-duty diesel vehicles separately. The derived emission factors from both instruments are compared, and a low SP2 bias (relative to the HS-LII) is found to be caused by a BC mass mode diameter less than 75 nm, that is most prominent with the gasoline fleet but is not present in the heavy-duty diesel vehicle exhaust on the highway. Results from both the LII and the SP2 demonstrate that the BC emission factors from gasoline vehicles are at least a factor of 2 higher than previous North American measurements, and a factor of 9 higher than currently used emission inventories in Canada, derived with the MOBILE 6.2C model. Conversely, the measured BC emission factor for heavy-duty diesel vehicles is in reasonable agreement with previous measurements. The results suggest that greater attention must be paid to black carbon from gasoline engines to obtain a full understanding of the impact of black carbon on air quality and climate and to devise appropriate mitigation strategies.