Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area

Identifying Patterns and Sources of Fine and Ultrafine Particulate Matter in London Using Mobile Measurements of Lung-Deposited Surface Area

We performed more than a year of mobile, 1 Hz measurements of lung-deposited surface area (LDSA, the surface area of 20-400 nm diameter particles, deposited in alveolar regions of lungs) and optically assessed fine particulate matter (PM_2.5), black carbon (BC), and nitrogen dioxide (NO₂) in central London. We spatially correlated these pollutants to two urban emission sources: major roadways and restaurants. We show that optical PM_2.5 is an ineffective indicator of tailpipe emissions on major roadways, where we do observe statistically higher LDSA, BC, and NO₂. Additionally, we find pollutant hot spots in commercial neighborhoods with more restaurants. A low LDSA (15 μm² cm^-3) occurs in areas with fewer major roadways and restaurants, while the highest LDSA (25 μm² cm^-3) occurs in areas with more of both sources. By isolating areas that are higher in one source than the other, we demonstrate the comparable impacts of traffic and restaurants on LDSA. Ratios of hyperlocal enhancements (ΔLDSA:ΔBC and ΔLDSA:ΔNO₂) are higher in commercial neighborhoods than on major roadways, further demonstrating the influence of restaurant emissions on LDSA. We demonstrate the added value of using particle surface in identifying hyperlocal patterns of health-relevant PM components, especially in areas with strong vehicular emissions where the high LDSA does not translate to high PM_2.5.

Phase State and Relative Humidity Regulate the Heterogeneous Oxidation Kinetics and Pathways of Organic-Inorganic Mixed Aerosols

Inorganic species always coexist with organic materials in atmospheric particles and may influence the heterogeneous oxidation of organic aerosols. However, very limited studies have explored the role of the inorganics in the chemical evolution of organic species in mixed aerosols. This study examines the heterogeneous oxidation of glutaric acid-ammonium sulfate and 1,2,6-hexanetriol-ammonium sulfate aerosols by hydroxyl radicals (OH) under varied organic mass fractions (f_org) and relative humidity in a flow tube reactor. Coupling the oxidation kinetics and product measurements with kinetic model simulations, we found that under both low relative humidity (RH, 30-35%) and high RH conditions (85%), the decreased f_org from 0.7 to 0.2 accelerates the oxidation of the organic materials by a factor of up to 11. We suggest that the faster oxidation kinetics under low-RH conditions is due to full or partial phase separation, with the organics greatly enriched at the particle outer region, while enhanced "salting-out" of the organics and OH adsorption caused by higher inorganics could explain the observations under high-RH conditions. Analysis of the oxidation products reveals that the dilution of organics by the inorganic salts and corresponding water uptake under high-RH conditions will favor alkoxy radical fragmentation by a factor of 3-4 and inhibit its secondary chain propagation chemistry. Our results suggest that atmospheric organic aerosol oxidation lifetime and composition are strongly impacted by the coexistent inorganic salts.

Prediction of Short-Term Ultrafine Particle Exposures Using Real-Time Street-Level Images Paired with Air Quality Measurements

Within-city ultrafine particle (UFP) concentrations vary sharply since they are influenced by various factors. We developed prediction models for short-term UFP exposures using street-level images collected by a camera installed on a vehicle rooftop, paired with air quality measurements conducted during a large-scale mobile monitoring campaign in Toronto, Canada. Convolutional neural network models were trained to extract traffic and built environment features from images. These features, along with regional air quality and meteorology data were used to predict short-term UFP concentration as a continuous and categorical variable. A gradient boost model for UFP as a continuous variable achieved R² = 0.66 and RMSE = 9391.8#/cm³ (mean values for 10-fold cross-validation). The model predicting categorical UFP achieved accuracies for "Low" and "High" UFP of 77 and 70%, respectively. The presence of trucks and other traffic parameters were associated with higher UFPs, and the spatial distribution of elevated short-term UFP followed the distribution of single-unit trucks. This study demonstrates that pictures captured on urban streets, associated with regional air quality and meteorology, can adequately predict short-term UFP exposure. Capturing the spatial distribution of high-frequency short-term UFP spikes in urban areas provides crucial information for the management of near-road air pollution hot spots.

High-spatial-resolution distributions of aerosol chemical characteristics in urban Lanzhou, western China, during wintertime: Insights from an on-road mobile aerosol mass spectrometry measurement experiment

The high-spatial-resolution distributions of the mass concentration and chemical composition of submicron particulate matter (PM₁) across four different functional districts in Lanzhou, a typical northwestern city in China, were studied during the winter haze pollution period using an on-road real-time mobile monitoring system. The purpose of this study is to characterize the spatial variation in the sources and chemical formation of aerosols at the intra-urban scale. A higher PM₁ mass concentration (63.0 μg m^-3) was observed in an industrially influenced district (XG) with major contributions (70.4%) from three secondary inorganic species (sulfate, nitrate, and ammonium) and two oxygenated organic aerosol (OOA) components with different oxygenation levels. Compared with the densely populated district (CG), sulfate and more-oxidized OOA were the two most distinct contributors to the elevated PM₁ mass in XG during the daytime (30.9% in XG vs. 17.5% in CG), whereas nitrate and less-oxidized OOA dominated (41.4% in XG vs. 30.6% in CG) during the nighttime. A lower PM₁ mass (44.3 μg m^-3) was observed in CG and was contributed predominantly by primary organic aerosols emitted from traffic, cooking, and heating activities. The chemical formation mechanisms of secondary PM₁ species in the two different districts during the daytime and nighttime are further examined, which indicated the important photochemical formations of nitrate in CG but sulfate in XG during the daytime, whereas favorable aqueous-phase formations of nitrate and LO-OOA in both districts during the nighttime. The stronger atmospheric oxidation capability might be a key factor leading to the more significant formations of secondary species in XG than CG. These results illustrate city-scale aerosol loading and chemical processes and are useful for local policy makers to develop differentiated and efficient mitigation strategies for the improvement of air quality in Lanzhou.

Phase Behavior of Internal Mixtures of Hydrocarbon-like Primary Organic Aerosol and Secondary Aerosol Based on Their Differences in Oxygen-to-Carbon Ratios

The phase behavior, the number and type of phases, in atmospheric particles containing mixtures of hydrocarbon-like organic aerosol (HOA) and secondary organic aerosol (SOA) is important for predicting their impacts on air pollution, human health, and climate. Using a solvatochromic dye and fluorescence microscopy, we determined the phase behavior of 11 HOA proxies (O/C = 0-0.29) each mixed with 7 different SOA materials generated in environmental chambers (O/C 0.4-1.08), where O/C represents the average oxygen-to-carbon atomic ratio. Out of the 77 different HOA + SOA mixtures studied, we observed two phases in 88% of the cases. The phase behavior was independent of relative humidity over the range between 90% and <5%. A clear trend was observed between the number of phases and the difference between the average O/C ratios of the HOA and SOA components (ΔO/C). Using a threshold ΔO/C of 0.265, we were able to predict the phase behavior of 92% of the HOA + SOA mixtures studied here, with one-phase particles predicted for ΔO/C < 0.265 and two-phase particles predicted for ΔO/C ≥ 0.265. The threshold ΔO/C value provides a relatively simple and computationally inexpensive framework for predicting the number of phases in internal SOA and HOA mixtures in atmospheric models.

Phase Behavior of Hydrocarbon-like Primary Organic Aerosol and Secondary Organic Aerosol Proxies Based on Their Elemental Oxygen-to-Carbon Ratio

A large fraction of atmospheric aerosols can be characterized as primary organic aerosol (POA) and secondary organic aerosol (SOA). Knowledge of the phase behavior, that is, the number and type of phases within internal POA + SOA mixtures, is crucial to predict their effect on climate and air quality. For example, if POA and SOA form a single phase, POA will enhance the formation of SOA by providing organic mass to absorb SOA precursors. Using microscopy, we studied the phase behavior of mixtures of SOA proxies and hydrocarbon-like POA proxies at relative humidity (RH) values of 90%, 45%, and below 5%. Internal mixtures of POA and SOA almost always formed two phases if the elemental oxygen-to-carbon ratio (O/C) of the POA was less than 0.11, which encompasses a large fraction of atmospheric hydrocarbon-like POA from fossil fuel combustion. SOA proxies mixed with POA proxies having 0.11 ≤ O/C ≤ 0.29 mostly resulted in particles with one liquid phase. However, two liquid phases were also observed, depending on the type of SOA and POA surrogates, and an increase in phase-separated particles was observed when increasing the RH in this O/C range. The results have implications for predicting atmospheric SOA formation and policy strategies to reduce SOA in urban environments.

Coexistence of three liquid phases in individual atmospheric aerosol particles

Aerosol particles are ubiquitous in the atmosphere and play an important role in air quality and the climate system. These particles can contain mixtures of primary organic aerosol, secondary organic aerosol, and secondary inorganic aerosol. We show that such internally mixed particles can contain three liquid phases. We also demonstrate that the presence of three liquid phases impacts the time needed for the particles to reach equilibrium with the surrounding gas phase and likely impacts the ability of the particles to activate into cloud droplets. A framework is presented for predicting conditions needed for the formation of three liquid phases in the atmosphere. These results will lead to improved representations of aerosols in models for air quality and climate predictions.

Individual atmospheric particles can contain mixtures of primary organic aerosol (POA), secondary organic aerosol (SOA), and secondary inorganic aerosol (SIA). To predict the role of such complex multicomponent particles in air quality and climate, information on the number and types of phases present in the particles is needed. However, the phase behavior of such particles has not been studied in the laboratory, and as a result, remains poorly constrained. Here, we show that POA+SOA+SIA particles can contain three distinct liquid phases: a low-polarity organic-rich phase, a higher-polarity organic-rich phase, and an aqueous inorganic-rich phase. Based on our results, when the elemental oxygen-to-carbon (O:C) ratio of the SOA is less than 0.8, three liquid phases can coexist within the same particle over a wide relative humidity range. In contrast, when the O:C ratio of the SOA is greater than 0.8, three phases will not form. We also demonstrate, using thermodynamic and kinetic modeling, that the presence of three liquid phases in such particles impacts their equilibration timescale with the surrounding gas phase. Three phases will likely also impact their ability to act as nuclei for liquid cloud droplets, the reactivity of these particles, and the mechanism of SOA formation and growth in the atmosphere. These observations provide fundamental information necessary for improved predictions of air quality and aerosol indirect effects on climate.

Constraining natural gas pipeline emissions in San Juan Basin using mobile sampling

Quantifying methane (CH₄) leaks of pipeline systems is critical to ensure accurate emission factors in regional and global atmospheric models. The previous emission factors in the United States Environmental Protection Agency (EPA) Greenhouse Gas Inventory (GHGI) are from 1996 and do not reflect the modern gathering pipeline system. Additional data from different basins across the United States are urgently needed to improve the emission factors. The National Energy Technology Laboratory conducted a ground-based vehicle survey at Carson National Forest in the San Juan Basin, New Mexico, in September 2019. 187 km of natural gas gathering pipeline systems were surveyed. The mobile CH₄ survey system was efficient in identifying CH₄ plumes and pinpointing the leak sources. Gaussian dispersion modeling suggested our survey system had a minimum detection limit of 1.5 LPM. No leaks were found from the pipelines while a leak of 7.1 +/- 0.2 LPM was on a pig launcher door and another leak of 0.7 +/- 0.1 LPM on a block valve. Limited access to the gathering pipeline system prevented us from quantifying all potential leaks detected by the CH₄ sensors. The low leak frequency phenomenon was also observed in the sole existing study of natural gas gathering pipelines in the Fayetteville Shale.

Quantifying source contributions of volatile organic compounds under hydraulic fracking moratorium

Volatile organic compounds (VOCs) are precursors for ozone (O₃) and secondary particulate matter, which contribute to asthma and cardiovascular diseases. With the technology development of hydraulic fracking, the United States experienced a shale gas boom in the last decade while the public raised concerns about the potential health impacts of co-emitted VOCs and other airborne pollutants. National Energy Technology Laboratory conducted stationary trailer-based ambient monitoring to study the sources of VOCs in Maryland, where the state enacted a moratorium on unconventional natural gas extraction. The campaign had two periods, May to August 2014 (summer) and November 2014 to February 2015 (winter). Ethane was the most abundant VOC, averaging 12.3 ppb (SD = 15.7 ppb) in summer and 21.7 ppb (SD = 21.6 ppb) in winter. The seasonal variation of VOCs indicated different source strengths. The sampling region was in the nitrogen oxides (NO_x) limited regime for O₃ production, and the O₃ concentrations were sensitive to VOC/NO_x ratios in the early mornings. We derived a six-factor profile using positive matrix factorization: motor vehicles, industrial, biogenics, coal burning, fugitive and evaporative, and ozone secondary. The fugitive and evaporative factor explained 44.5% of total VOCs, and the motor vehicles factor followed second with 15.5%. Oil and gas activities had a considerable impact on the abundance of VOCs in this region.

Gathering Pipeline Methane Emissions in Utica Shale Using an Unmanned Aerial Vehicle and Ground-Based Mobile Sampling

The United States Environmental Protection Agency Greenhouse Gas Inventory only recently updated the emission factors of natural gas gathering pipelines in April 2019 from the previous estimates based on a 1990s study of distribution pipelines. Additional measurements are needed from different basins for more accurate assessments of methane emissions from natural gas midstream industries and hence the overall climate implications of natural gas as the interim major energy source for the next decade. We conducted an unmanned aerial vehicle (UAV) survey and a ground-based vehicle sampling campaign targeting gathering pipeline systems in the Utica Shale from March to April in 2019. Out of 73 km of pipeline systems surveyed, we found no leaks on pipelines and two leaks on an accessory block valve with leak rates of 3.8 ± 0.4 and 7.6 ± 0.8 mg/s. The low leak frequency phenomenon was also observed in the only existing gathering pipeline study in Fayetteville Shale. The UAV sampling system facilitated ease of access, broadened the availability of pipelines for leak detection, and was estimated to detect methane leaks down to 0.07 g/s using Gaussian dispersion modeling. For future UAV surveys adopting similar instrument setup and dispersion models, we recommend arranging controlled release experiments first to understand the system’s detection limit and choosing sampling days with steady and low wind speeds (2 m/s).

Moving beyond Fine Particle Mass: High-Spatial Resolution Exposure to Source-Resolved Atmospheric Particle Number and Chemical Mixing State

BACKGROUND

Most epidemiological studies address health effects of atmospheric particulate matter (PM) using mass-based measurements as exposure surrogates. However, this approach ignores many critical physiochemical properties of individual atmospheric particles. These properties control the deposition of particles in the human lung and likely their toxicity; in addition, they likely have larger spatial variability than PM mass.

OBJECTIVES

This study was designed to quantify the spatial variability in number, size, source, and chemical mixing state of individual particles in a populous urban area. We quantified the population exposure to these detailed particle properties and compared them to mass-based exposures.

METHODS

We performed mobile sampling using an advanced single-particle mass spectrometer to measure the spatial variability of number concentration of source-resolved 50-1,000 nm particles and particle mixing state in Pittsburgh, Pennsylvania. We built land-use regression (LUR) models to estimate their spatial patterns and coupled them with demographic data to estimate population exposure.

RESULTS

Particle number concentration had a much larger spatial variability than mass concentration within the city. Freshly emitted particles from traffic and cooking drive the variability in particle number, but mass concentrations are dominated by aged background particles composed of secondary materials. In addition, people exposed to elevated number concentrations of atmospheric particles are also exposed to more externally mixed particles.

CONCLUSIONS

Our advanced measurement technique provides a new exposure picture that resolves the large intra-city spatial heterogeneity in traffic and cooking particle number concentrations in the populous urban area. Our results provide a complementary and more detailed perspective compared with bulk measurements of composition. In addition, given the influence of particle mixing state on properties such as particle deposition in the lung, the large spatial gradients of chemical mixing state may significantly influence the health effects of fine PM. https://doi.org/10.1289/EHP5311.

Influences of Primary Emission and Secondary Coating Formation on the Particle Diversity and Mixing State of Black Carbon Particles

The mixing state of black carbon (BC) affects its environmental fate and impacts. This work investigates particle diversity and mixing state for refractory BC (rBC) containing particles in an urban environment. The chemical compositions of individual rBC-containing particles were measured, from which a mixing state index and particle diversity were determined. The mixing state index (χ) varied between 26% and 69% with the average of 48% in this study and was slightly enhanced with the photochemical age of air masses, indicating that most of the rBC-containing particles cannot be simply explained by fully externally and internally mixed model. Clustering of single particle measurements was used to investigate the potential effects of different primary emissions and atmospheric processes on rBC-containing particle diversity and mixing state. The average particle species diversity and the bulk population species diversity both increased with primary traffic emissions and elevated nitrate concentrations in the morning but gradually decreased with secondary organic aerosol (SOA) formation in the afternoon. The single particle clustering results illustrate that primary traffic emissions and entrainment of nitrate-containing rBC particles from the residual layer to the surface could lead to more heterogeneous aerosol compositions, whereas substantial fresh SOA formation near vehicular emissions made the rBC-containing particles more homogeneous. This work highlights the importance of considering particle diversity and mixing state for investigating the chemical evolution of rBC-containing particles and the potential effects of coating on BC absorption enhancement.

Quantifying Urban Spatial Variations of Anthropogenic VOC Concentrations and Source Contributions with a Mobile Sampling Platform

Volatile organic compounds (VOCs) are important atmospheric constituents because they contribute to formation of ozone and secondary aerosols, and because some VOCs are toxic air pollutants. We measured concentrations of a suite of anthropogenic VOCs during summer and winter at 70 locations representing different microenvironments around Pittsburgh, PA. The sampling sites were classified both by land use (e.g., high versus low traffic) and grouped based on geographic similarity and proximity. There was roughly a factor of two variation in both total VOC and single-ring aromatic VOC concentrations across the site groups. Concentrations were roughly 25% higher in winter than summer. Source apportionment with positive matrix factorization reveals that the major VOC sources are gasoline vehicles, solvent evaporation, diesel vehicles, and two factors attributed to industrial emissions. While we expected to observe significant spatial variability in the source impacts across the sampling domain, we instead found that source impacts were relatively homogeneous.

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 PM_2.5) 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 PM_2.5 mass. The observed order of spatial heterogeneity is UFP > NO₂ > CO > PM_2.5. 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.

Restaurant Impacts on Outdoor Air Quality: Elevated Organic Aerosol Mass from Restaurant Cooking with Neighborhood-Scale Plume Extents

Organic aerosol (OA) is a major component of fine particulate matter (PM_2.5) in urban environments. We performed in-motion ambient sampling from a mobile platform with an aerosol mass spectrometer (AMS) to investigate the spatial variability and sources of OA concentrations in Pittsburgh, Pennsylvania, a midsize, largely postindustrial American city. To characterize the relative importance of cooking and traffic sources, we sampled in some of the most populated areas (∼18 km²) in and around Pittsburgh during afternoon rush hour and evening mealtime, including congested highways, major local roads, areas with high densities of restaurants, and urban background locations. We found greatly elevated OA concentrations (10s of μg m^-3) in the vicinity of numerous individual restaurants and commercial districts containing multiple restaurants. The AMS mass spectral information indicates that majority of the high concentration plumes (71%) were from cooking sources. Areas containing both busy roads and restaurants had systematically higher OA concentrations than areas with only busy roads and urban background locations. Elevated OA concentrations were measured hundreds of meters downwind of some restaurants, indicating that these sources can influence air quality on neighborhood scales. Approximately 20% of the population (∼250 000 people) in the Pittsburgh area lives within 200 m of a restaurant; therefore, restaurant emissions are potentially an important source of outdoor PM exposures for this large population.