Identification of Neighborhood Hotspots via the Cumulative Hazard Index: Results From a Community-Partnered Low-Cost Sensor Deployment.

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.

The effect of air purifiers and curtains on aerosol dispersion and removal in multi-patient hospital rooms.

Airborne transmission of disease is of concern in many indoor spaces. Here, aerosol dispersion and removal in an unoccupied 4-bed hospital room were characterized using a transient aerosol tracer experiment for 38 experiments covering 4 configurations of air purifiers and 3 configurations of curtains. NaCl particle (mass mean aerodynamic diameter ~3 µm) concentrations were measured around the room following an aerosol release. Particle transport across the room was 1.5-4 min which overlaps with the characteristic times for significant viral deactivation and gravitational settling of larger particles. Concentrations were close to spatially uniform except very near the source. Curtains resulted in a modest increase in delay and decay times, less so when combined with purifiers. The aerosol decay rate was in most cases higher than expected from the clean air delivery rate, but the reduction in steady-state concentrations resulting from air purifiers was less than suggested by the decay rates. Apparently, a substantial (and configuration-dependent) fraction of the aerosol is removed immediately, and this effect is not captured by the decay rate. Overall, the combination of curtains and purifiers is likely to reduce disease transmission in multi-patient hospital rooms.

Cannabis Cultivation Facilities: A Review of Their Air Quality Impacts from the Occupational to Community Scale.

This review addresses knowledge gaps in cannabis cultivation facility (CCF) air emissions by synthesizing the peer-reviewed and gray literature. Focus areas include compounds emitted, air quality indoors and outdoors, odor assessment, and the potential health effects of emitted compounds. Studies suggest that ß-myrcene is a tracer candidate for CCF biogenic volatile organic compounds (BVOCs). Furthermore, ß-myrcene, d-limonene, terpinolene, and α-pinene are often reported in air samples collected in and around CCF facilities. The BVOC emission strength per dry weight of plant is higher than most conventional agriculture crops. Nevertheless, reported total CCF BVOC emissions are lower compared with VOCs from other industries. Common descriptors of odors coming from CCFs include "skunky", "herbal", and "pungent". However, there are few peer-reviewed studies addressing the odor impacts of CCFs outdoors. Atmospheric modeling has been limited to back trajectory models of tracers and ozone impact assessment. Health effects of CCFs are mostly related to odor annoyance or occupational hazards. We identify 16 opportunities for future studies, including an emissions database by strain and stage of life (growing cycle) and odor-related setback guidelines. Exploration and implementation of key suggestions presented in this work may help regulators and the industry reduce the environmental footprint of CCF facilities.

Using Low-Cost Sensors to Assess Fine Particulate Matter Infiltration (PM2.5) during a Wildfire Smoke Episode at a Large Inpatient Healthcare Facility.

Wildfire smoke exposure is associated with a range of acute health outcomes, which can be more severe in individuals with underlying health conditions. Currently, there is limited information on the susceptibility of healthcare facilities to smoke infiltration. As part of a larger study to address this gap, a rehabilitation facility in Vancouver, Canada was outfitted with one outdoor and seven indoor low-cost fine particulate matter (PM2.5) sensors in Air Quality Eggs (EGG) during the summer of 2020. Raw measurements were calibrated using temperature, relative humidity, and dew point derived from the EGG data. The infiltration coefficient was quantified using a distributed lag model. Indoor concentrations during the smoke episode were elevated throughout the building, though non-uniformly. After censoring indoor-only peaks, the average infiltration coefficient (range) during typical days was 0.32 (0.22-0.39), compared with 0.37 (0.31-0.47) during the smoke episode, a 19% increase on average. Indoor PM2.5 concentrations quickly reflected outdoor conditions during and after the smoke episode. It is unclear whether these results will be generalizable to other years due to COVID-related changes to building operations, but some of the safety protocols may offer valuable lessons for future wildfire seasons. For example, points of building entry and exit were reduced from eight to two during the pandemic, which likely helped to protect the building from wildfire smoke infiltration. Overall, these results demonstrate the utility of indoor low-cost sensors in understanding the impacts of extreme smoke events on facilities where highly susceptible individuals are present. Furthermore, they highlight the need to employ interventions that enhance indoor air quality in such facilities during smoke events.

Spatial Modeling of Daily PM2.5, NO2, and CO Concentrations Measured by a Low-Cost Sensor Network: Comparison of Linear, Machine Learning, and Hybrid Land Use Models.

Previous studies have characterized spatial patterns of pollution with land use regression (LUR) models from distributed passive or filter samplers at low temporal resolution. Large-scale deployment of low-cost sensors (LCS), which typically sample in real time, may enable time-resolved or real-time modeling of concentration surfaces. The aim of this study was to develop spatiotemporal models of PM2.5, NO2, and CO using an LCS network in Pittsburgh, Pennsylvania. We modeled daily average concentrations in August 2016-December 2017 across 50 sites. Land use variables included 13 time-independent (e.g., elevation) and time-dependent (e.g., temperature) predictors. We examined two models: LUR and a machine-learning-enabled land use model (land use random forest, LURF). The LURF models outperformed LUR models, with increase in the average externally cross-validated R2 of 0.10-0.19. Using wavelet decomposition to separate short-lived events from the regional background, we also created time-decomposed LUR and LURF models. Compared to the standard model, this resulted in improvement in R2 of up to 0.14. The time-decomposed models were more influenced by spatial parameters. Mapping our models across Allegheny County, we observed that time-decomposed LURF models created robust PM2.5 predictions, suggesting that this approach may improve our ability to map air pollutants at high spatiotemporal resolution.

Quantifying high-resolution spatial variations and local source impacts of urban ultrafine particle concentrations.

To quantify the fine-scale spatial variations and local source impacts of urban ultrafine particle (UFP) concentrations, we conducted 3-6 weeks of continuous measurements of particle number (a proxy for UFP) and other air pollutant (CO, NO2, and PM2.5) concentrations at 32 sites in Pittsburgh, Pennsylvania during the winters of 2017 and 2018. Sites were selected to span a range of urban land use attributes, including urban background, near local and arterial roads, traffic intersections, urban street canyon, near-highway, near large industrial source, and restaurant density. The spatial variations in urban particle number concentrations varied by about a factor of three. Particle number concentrations are 2-3 times more spatially heterogeneous than PM2.5 mass. The observed order of spatial heterogeneity is UFP > NO2 > CO > PM2.5. On average, particle number concentrations near local roads with a cluster of restaurants and near arterial roads are roughly two times higher than the urban background. Particle number concentrations in the urban street canyon, downwind of a major highway, and near large industrial sources are 2-4 times higher than background concentrations. While traffic is known as an important contributor to particle number concentrations, restaurants and industrial emissions also contribute significantly to spatial variations in Pittsburgh. Particle size distribution measurements using a mobile laboratory show that the local spatial variations in particle number concentrations are dictated by concentrations of particles smaller than 50 nm. A large fraction of urban residents (e.g., ~50%) in Pittsburgh live near local sources and are therefore exposed to 50%-300% higher particle number concentrations than urban background location. These locally emitted particles may have greater health effects than background particles.

Carbonaceous aerosol sampling of gasoline direct injection engine exhaust with an integrated organic gas and particle sampler.

Positive and negative artifacts of particle-phase organic carbon (p-OC) and the polycyclic aromatic hydrocarbons (PAHs) in gasoline direct injection (GDI) engine exhaust particulate matter (PM) were assessed using an integrated organic gas and particle sampler (IOGAPS). Three configurations (denuder + sorbent impregnated filters (SIFs), upstream Zefluor filter + denuder + SIFs, and standard filter pack + SIFs) were used to collect GDI exhaust samples at cold start and highway cruise operating conditions with no aftertreatment. Approximately 35% of the measured GDI p-OC was attributed to positive artifacts; negative artifacts were not detectable due to low overall SVOC concentrations. GDI engine exhaust PAH concentrations were approximately 10 times higher during cold start than highway cruise. At highway cruise, pyrene and fluoranthene were the dominant PAHs in the undenuded filter pack; downstream of the denuder benzo(a)anthracene was the dominant PAH. From a comparison of our findings to published PAH emission factors we estimate that three-way catalyst conversion efficiencies of PAHs were approximately 80% for 3 of the 15 PAHs measured during highway cruise operation. These conversion efficiencies may be considerably lower during cold start operation when the three-way catalyst has not reached its operating temperature. Our previous work showed that adverse biological responses to GDI engine exhaust exposure may be dominated by the particle phase when measured downstream of a Teflon filter. Understanding the partitioning characteristics of PAHs may help elucidate specific PAHs contributing to this effect.

Methane Emissions from Natural Gas Production Sites in the United States: Data Synthesis and National Estimate.

We used site-level methane (CH4) emissions data from over 1000 natural gas (NG) production sites in eight basins, including 92 new site-level CH4 measurements in the Uinta, northeastern Marcellus, and Denver-Julesburg basins, to investigate CH4 emissions characteristics and develop a new national CH4 emission estimate for the NG production sector. The distribution of site-level emissions is highly skewed, with the top 5% of sites accounting for 50% of cumulative emissions. High emitting sites are predominantly also high producing (>10 Mcfd). However, low NG production sites emit a larger fraction of their CH4 production. When combined with activity data, we predict that this creates substantial variability in the basin-level CH4 emissions which, as a fraction of basin-level CH4 production, range from 0.90% for the Appalachian and Greater Green River to >4.5% in the San Juan and San Joaquin. This suggests that much of the basin-level differences in production-normalized CH4 emissions reported by aircraft studies can be explained by differences in site size and distribution of site-level production rates. We estimate that NG production sites emit total CH4 emissions of 830 Mg/h (95% CI: 530-1200), 63% of which come from the sites producing <100 Mcfd that account for only 10% of total NG production. Our total CH4 emissions estimate is 2.3 times higher than the U.S. Environmental Protection Agency's estimate and likely attributable to the disproportionate influence of high emitting sites.

Reduced Ultrafine Particle Concentration in Urban Air: Changes in Nucleation and Anthropogenic Emissions.

Nucleation is an important source of ambient ultrafine particles (UFP). We present observational evidence of the changes in the frequency and intensity of nucleation events in urban air by analyzing long-term particle size distribution measurements at an urban background site in Pittsburgh, Pennsylvania during 2001-2002 and 2016-2017. We find that both frequency and intensity of nucleation events have been reduced by 40-50% over the past 15 years, resulting in a 70% reduction in UFP concentrations from nucleation. On average, the particle growth rates are 30% slower than 15 years ago. We attribute these changes to dramatic reductions in SO2 (more than 90%) and other pollutant concentrations. Overall, UFP concentrations in Pittsburgh have been reduced by ∼48% in the past 15 years, with a ∼70% reduction in nucleation, ∼27% in weekday local sources (e.g., weekday traffic), and 49% in the regional background. Our results highlight that a reduction in anthropogenic emissions can considerably reduce nucleation events and UFP concentrations in a polluted urban environment.

Comparison of Airway Responses Induced in a Mouse Model by the Gas and Particulate Fractions of Gasoline Direct Injection Engine Exhaust.

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.

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

A majority of the ultrafine particles observed in real-world conditions are systematically excluded from many measurements that help to guide regulation of vehicle emissions. To investigate the impact of this exclusion, coincident near-road particle number (PN) emission factors were quantified up- and downstream of a thermodenuder during two seasonal month-long campaigns with wide-ranging ambient temperatures (-19 to +30 °C) to determine the volatile fraction of particles. During colder temperatures (<0 °C), the volatile fraction of particles was 94%, but decreased to 85% during warmer periods (>20 °C). Additionally, mean PN emission factors were a factor of 3.8 higher during cold compared to warm periods. On the basis of 130 000 vehicle plumes including three additional campaigns, fleet mean emission factors were calculated for PN (8.5 × 1014 kg-fuel-1), black carbon (37 mg kg-fuel-1), organic aerosol (51 mg kg-fuel-1), and particle-bound polycyclic aromatic hydrocarbons (0.7 mg kg-fuel-1). These findings demonstrate that significant differences exist between particles in thermally treated vehicle exhaust as compared to in real-world vehicle plumes to which populations in near-road environments are actually exposed. Furthermore, the magnitude of these differences are dependent upon season and may be more extreme in colder climates.

Assessing the Climate Trade-Offs of Gasoline Direct Injection Engines.

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.

Murine precision-cut lung slices exhibit acute responses following exposure to gasoline direct injection engine emissions.

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.

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

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