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Diesel exhaust has been associated with asthma, but its response to other engine emissions is not clear. The increasing prevalence of vehicles with gasoline direct injection (GDI) engines motivated this study, and the objective was to evaluate pulmonary responses induced by acute exposure to GDI engine exhaust in an allergic asthma murine model. Mice were sensitized with an allergen to induce airway hyperresponsiveness or treated with saline (non-allergic group). Animals were challenged for 2-h to exhaust from a laboratory GDI engine operated at conditions equivalent to a highway cruise. Exhaust was filtered to assess responses induced by the particulate and gas fractions. Short-term exposure to particulate matter from GDI engine exhaust induced upregulation of genes related to polycyclic aromatic hydrocarbon (PAH) metabolism ( Cyp1b1 ) and inflammation ( TNFα ) in the lungs of non-allergic mice. High molecular weight PAHs dominated the particulate fraction of the exhaust, and this response was therefore likely attributable to the presence of these PAHs. The particle fraction of GDI engine exhaust further contributed to enhanced methacholine responsiveness in the central and peripheral tissues in animals with airway hyperresponsiveness. As GDI engines gain prevalence in the vehicle fleet, understanding the health impacts of their emissions becomes increasingly important., Competing Interests: The authors declare no conflict of interest.

Gasoline direct injection (GDI) engines are increasingly prevalent in the global vehicle fleet. Particulate matter emissions from GDI engines are elevated compared to conventional gasoline engines. The pulmonary effects of these higher particulate emissions are unclear. This study investigated the pulmonary responses induced by GDI engine exhaust using an ex vivo model. The physiochemical properties of GDI engine exhaust were assessed. Precision cut lung slices were prepared using Balb/c mice to evaluate the pulmonary response induced by one-hour exposure to engine-out exhaust from a laboratory GDI engine operated at conditions equivalent to vehicle highway cruise conditions. Lung slices were exposed at an air-liquid interface using an electrostatic aerosol in vitro exposure system. Particulate and gaseous exhaust was fractionated to contrast mRNA production related to polycyclic aromatic hydrocarbon (PAH) metabolism and oxidative stress. Exposure to GDI engine exhaust upregulated genes involved in PAH metabolism, including Cyp1a1 (2.71, SE=0.22), and Cyp1b1 (3.24, SE=0.12) compared to HEPA filtered air (p<0.05). GDI engine exhaust further increased Cyp1b1 expression compared to filtered GDI engine exhaust (i.e., gas fraction only), suggesting this response was associated with the particulate fraction. Exhaust particulate was dominated by high molecular weight PAHs. Hmox1, an oxidative stress marker, exhibited increased expression after exposure to GDI (1.63, SE=0.03) and filtered GDI (1.55, SE=0.04) engine exhaust compared to HEPA filtered air (p<0.05), likely attributable to a combination of the gas and particulate fractions. Exposure to GDI engine exhaust contributes to upregulation of genes related to the metabolism of PAHs and oxidative stress., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The Strathcona neighborhood in Vancouver is particularly vulnerable to environmental injustice due to its close proximity to the Port of Vancouver, and a high proportion of Indigenous and low‐income households. Furthermore, local sources of air pollutants (e.g., roadways) can contribute to small‐scale variations within communities. The aim of this study was to assess hyperlocal air quality patterns (intra‐neighborhood variability) and compare them to average Vancouver concentrations (inter‐neighborhood variability) to identify possible disparities in air pollution exposure for the Strathcona community. Between April and August 2022, 11 low‐cost sensors (LCS) were deployed within the neighborhood to measure PM2.5, NO2, and O3 concentrations. The collected 15‐min concentrations were down‐averaged to daily concentrations and compared to greater Vancouver region concentrations to quantify the exposures faced by the community relative to the rest of the region. Concentrations were also estimated at every 25 m grid within the neighborhood to quantify the distribution of air pollution within the community. Using population information from census data, cumulative hazard indices (CHIs) were computed for every dissemination block. We found that although PM2.5 concentrations in the neighborhood were lower than regional Vancouver averages, daily NO2 concentrations and summer O3 concentrations were consistently higher. Additionally, although CHIs varied daily, we found that CHIs were consistently higher in areas with high commercial activity. As such, estimating CHI for dissemination blocks was useful in identifying hotspots and potential areas of concern within the neighborhood. This information can collectively assist the community in their advocacy efforts. Plain Language Summary: Historically marginalized communities can experience environmental injustice due to disproportionately high air pollution relative to other communities. The Strathcona neighborhood in Vancouver is of particular concern due to its proximity to the Port of Vancouver, major roads and railways, and a high proportion of Indigenous and low‐income households. Here, we assess hyperlocal air quality patterns in Strathcona and compare them to average Vancouver concentrations to assess potential air quality inequity. Between April and August 2022, 11 low‐cost sensors (LCS) measuring PM2.5, O3, and NO2 were deployed in community backyards. The daily average concentrations were compared to those in other Vancouver neighborhoods. Concentrations were also estimated at every 25m grid within the neighborhood using ordinary kriging, a relatively simple spatial interpolation technique. Using Census population data, cumulative hazard indices (CHIs, which combine PM2.5, O3, and NO2 in a single metric) were computed for every dissemination block. We found that daily NO2 concentrations and summer O3 concentrations consistently higher than in other Vancouver neighborhoods. Although CHIs varied daily, CHIs were consistently higher in areas with high commercial activity. The kriging model was more easily implemented than traditional land use regression models, and may be useful to communities struggling to interpret LCS network data. Key Points: Mapping the cumulative hazard index (CHI) is a useful way for communities to summarize complex outputs from low‐cost air quality sensorsThe NO2 concentrations in the study area were consistently higher than other Metro Vancouver neighborhoodsThe western and eastern peripheries (high commercial density) of the study domain were the dominant hotspots, depending on wind direction [ABSTRACT FROM AUTHOR]

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 µ g 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. [ABSTRACT FROM AUTHOR]

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 µgm-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. [ABSTRACT FROM AUTHOR]

Low-cost PM 2.5 sensors often suffer from environmental cross-sensitivities, requiring regular calibration across a wide range of concentrations. This is typically achieved by co-locating LCS with regulatory stations and using statistical models. However, this approach becomes challenging in regions with limited regulatory monitoring stations or access. To address this challenge, we explored building separate calibration models for the pseudo-regional component of the total PM 2.5 concentration, which represents background concentration, and the hyper-local component of the total concentration. This is based on the premise that the regional concentration is consistent across a given region and therefore direct co-location is less necessary, and the idea that the local concentration is not influenced by geographic properties and therefore can be calibrated based on co-location elsewhere. In this work, we used publicly-available PurpleAir data for 2022 from five different cities in South Asia and North America, and built city-specific calibration models for the regional concentrations using multiple linear regression. We tested the model performance in the city the model was built in (intra-city models; trained and cross-validated in the same city) and in other cities (inter-city models; trained and cross-validated in different cities). The regional calibration model reduced the normalized root mean square error (nRMSE) of both intra-city models, from 51% to 26%, and inter-city models, from 55% to 25% compared to PurpleAir reported concentrations. Overall, the results of this work demonstrate the potential for improved transferability of calibration models and provides evidence that calibration models built for regional concentration and local concentration separately may be a viable solution when deploying in places with limited regulatory monitoring or access to monitoring stations. • Used data from 15 LCS to create geographically-transferable calibration models. • Models were tested in different countries and for monsoon and non-monsoon. • Methodology involved decomposing total signal into regional and local components. • Inter-city models (trained and tested in different cities) reduced nRMSE by 30%. [ABSTRACT FROM AUTHOR]

Abstract: The TSI Fast Mobility Particle Sizer (FMPS), Engine Exhaust Particle Sizer (EEPS), and Scanning Mobility Particle Sizer (SMPS) provide size distributions for 6–560 nm particles. The aim of this study was to perform comprehensive equivalence testing of these three particle sizing instruments with particles of contrasting chemical and physical characteristics (urban ambient, diesel exhaust, and laboratory-generated particulate). It was observed that the EEPS and FMPS measurements agreed to within 15% thus concluding that data from these instruments may be considered equivalent. Parallel measurements with the SMPS showed that when measuring diesel exhaust particulate during ISO8178 Mode 9 operation there is significant overestimation of particle concentrations by both the EEPS and the FMPS in the 20–120 nm size range (25–38% overestimation). This overestimation also occurred for near-road measurement of heavy emitter vehicle plumes in ambient samples (up to 75% overestimation). Laboratory-generated soot agglomerate particles, whose shape was verified by transmission electron microscopy, were also tested. The agglomerate nature of diesel soot particulate was the dominant cause of the overestimation; parallel measurements with an FMPS and an Ultrafine Condensation Particle Counter of the laboratory-generated soot particulate showed overestimation by up to a factor of three. [Copyright &y& Elsevier]

Over the past decade, there has been exponential growth in low-cost air pollution sensing technology. While low-cost sensors can provide a path towards more accessible air quality measurement, there are several guidelines that should be considered prior to deploying a low-cost sensor network. In this tutorial guide, we focus on low-cost aerosol sensors (in this case, PM 2.5). The tutorial reviews key guidelines for implementing a low-cost PM sensor network. This article is also associated with a companion web-tutorial (https://nzimmerman-ubc.github.io/lcs-PM-demo/) on downloading and assessing sample low-cost PM sensor data from the PurpleAir network using the new U.S. EPA Fine Particle Sensor Base Testing Guidelines. While this tutorial does not cover every single consideration a researcher or citizen scientist might undertake, it covers the key areas of evaluation and calibration, siting, data reporting, and post-processing. The aim of the tutorial is to improve outcomes for researchers using low-cost PM sensor networks and develop a broader community of practice. • A brief review of important considerations for deploying and using a low-cost PM sensor network. • Considerations include not just calibration, but data reporting and access. • This article is accompanied by a web-based tutorial for downloading and assessing data from the PurpleAir network. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]