Mobile Sources Are Still an Important Source of Secondary Organic Aerosol and Fine Particulate Matter in the Los Angeles Region.

Secondary organic aerosol (SOA) is a significant component of atmospheric fine particulate matter. Mobile sources have historically been a major source of SOA precursors in urban environments, but decades of regulations have reduced their emissions. Less regulated sources, such as volatile chemical products (VCPs), are of growing importance. We analyzed ambient and emissions data to assess the contribution of mobile sources to SOA formation in Los Angeles during the period of 2009-2019. During this period, air quality in the Los Angeles region has improved, but organic aerosol (OA) concentrations did not decrease as much as primary pollutants. This appears to be largely due to SOA, whose mass fraction in OA increased over this period. In 2010, about half of the freshly formed SOA measured in Pasadena, CA appears to be formed from hydrocarbon (non-oxygenated) precursors. Chemical mass balance analysis indicates that these hydrocarbon SOA precursors (including intermediate volatility organic compounds) can largely be explained by emissions from mobile sources in 2010. Our analysis indicates that continued reduction in emissions from mobile sources should lead to additional significant decreases in atmospheric SOA and PM2.5 mass in the Los Angeles region.

Evidence of Air Dispersion: HFPO-DA and PFOA in Ohio and West Virginia Surface Water and Soil near a Fluoropolymer Production Facility.

Perfluorooctanoic acid (PFOA) was used as a fluoropolymer manufacturing aid at a fluoropolymer production facility in Parkersburg, WV from 1951 to 2013. The manufacturer introduced a replacement surfactant hexafluoropropylene oxide dimer acid (HFPO-DA) that has been in use at this site since 2013. Historical releases of PFOA and related epidemiological work in this area has been primarily focused on communities downstream. To provide an update on the ongoing impacts from this plant, 94 surface water samples and 13 soil samples were collected mainly upstream and downwind of this facility. PFOA was detected in every surface water sample with concentrations exceeding 1000 ng/L at 13 sample sites within an 8 km radius of the plant. HFPO-DA was also found to be widespread with the highest levels (>100 ng/L) found in surface water up to 6.4 km north of the plant. One sample site, 28 km north of the plant, had PFOA at 143 ng/L and HFPO-DA at 42 ng/L. Sites adjacent to landfills containing fluorochemical waste had PFOA concentrations ranging up to >1000 ng/L. These data indicate that downwind atmospheric transport of both compounds has occurred and that the boundaries of the impact zone have yet to be fully delineated.

Translational data analytics in exposure science and environmental health: a citizen science approach with high school students.

BACKGROUND: Translational data analytics aims to apply data analytics principles and techniques to bring about broader societal or human impact. Translational data analytics for environmental health is an emerging discipline and the objective of this study is to describe a real-world example of this emerging discipline. METHODS: We implemented a citizen-science project at a local high school. Multiple cohorts of citizen scientists, who were students, fabricated and deployed low-cost air quality sensors. A cloud-computing solution provided real-time air quality data for risk screening purposes, data analytics and curricular activities. RESULTS: The citizen-science project engaged with 14 high school students over a four-year period that is continuing to this day. The project led to the development of a website that displayed sensor-based measurements in local neighborhoods and a GitHub-like repository for open source code and instructions. Preliminary results showed a reasonable comparison between sensor-based and EPA land-based federal reference monitor data for CO and NOx. CONCLUSIONS: Initial sensor-based data collection efforts showed reasonable agreement with land-based federal reference monitors but more work needs to be done to validate these results. Lessons learned were: 1) the need for sustained funding because citizen science-based project timelines are a function of community needs/capacity and building interdisciplinary rapport in academic settings and 2) the need for a dedicated staff to manage academic-community relationships.

Ten questions concerning the implications of carpet on indoor chemistry and microbiology.

Carpet and rugs currently represent about half of the United States flooring market and offer many benefits as a flooring type. How carpets influence our exposure to both microorganisms and chemicals in indoor environments has important health implications but is not well understood. The goal of this manuscript is to consolidate what is known about how carpet impacts indoor chemistry and microbiology, as well as to identify the important research gaps that remain. After describing the current use of carpet indoors, questions focus on five specific areas: 1) indoor chemistry, 2) indoor microbiology, 3) resuspension and exposure, 4) current practices and future needs, and 5) sustainability. Overall, it is clear that carpet can influence our exposures to particles and volatile compounds in the indoor environment by acting as a direct source, as a reservoir of environmental contaminants, and as a surface supporting chemical and biological transformations. However, the health implications of these processes are not well known, nor how cleaning practices could be optimized to minimize potential negative impacts. Current standards and recommendations focus largely on carpets as a primary source of chemicals and on limiting moisture that would support microbial growth. Future research should consider enhancing knowledge related to the impact of carpet in the indoor environment and how we might improve the design and maintenance of this common material to reduce our exposure to harmful contaminants while retaining the benefits to consumers.

Comparison of Gasoline Direct-Injection (GDI) and Port Fuel Injection (PFI) Vehicle Emissions: Emission Certification Standards, Cold-Start, Secondary Organic Aerosol Formation Potential, and Potential Climate Impacts.

Recent increases in the Corporate Average Fuel Economy standards have led to widespread adoption of vehicles equipped with gasoline direct-injection (GDI) engines. Changes in engine technologies can alter emissions. To quantify these effects, we measured gas- and particle-phase emissions from 82 light-duty gasoline vehicles recruited from the California in-use fleet tested on a chassis dynamometer using the cold-start unified cycle. The fleet included 15 GDI vehicles, including 8 GDIs certified to the most-stringent emissions standard, superultra-low-emission vehicles (SULEV). We quantified the effects of engine technology, emission certification standards, and cold-start on emissions. For vehicles certified to the same emissions standard, there is no statistical difference of regulated gas-phase pollutant emissions between PFIs and GDIs. However, GDIs had, on average, a factor of 2 higher particulate matter (PM) mass emissions than PFIs due to higher elemental carbon (EC) emissions. SULEV certified GDIs have a factor of 2 lower PM mass emissions than GDIs certified as ultralow-emission vehicles (3.0 ± 1.1 versus 6.3 ± 1.1 mg/mi), suggesting improvements in engine design and calibration. Comprehensive organic speciation revealed no statistically significant differences in the composition of the volatile organic compounds emissions between PFI and GDIs, including benzene, toluene, ethylbenzene, and xylenes (BTEX). Therefore, the secondary organic aerosol and ozone formation potential of the exhaust does not depend on engine technology. Cold-start contributes a larger fraction of the total unified cycle emissions for vehicles meeting more-stringent emission standards. Organic gas emissions were the most sensitive to cold-start compared to the other pollutants tested here. There were no statistically significant differences in the effects of cold-start on GDIs and PFIs. For our test fleet, the measured 14.5% decrease in CO2 emissions from GDIs was much greater than the potential climate forcing associated with higher black carbon emissions. Thus, switching from PFI to GDI vehicles will likely lead to a reduction in net global warming.

Intermediate Volatility Organic Compound Emissions from On-Road Gasoline Vehicles and Small Off-Road Gasoline Engines.

Dynamometer experiments were conducted to characterize the intermediate volatility organic compound (IVOC) emissions from a fleet of on-road gasoline vehicles and small off-road gasoline engines. IVOCs were quantified through gas chromatography/mass spectrometry analysis of adsorbent samples collected from a constant volume sampler. The dominant fraction (>80%, on average) of IVOCs could not be resolved on a molecular level. These unspeciated IVOCs were quantified as two chemical classes (unspeciated branched alkanes and cyclic compounds) in 11 retention-time-based bins. IVOC emission factors (mg kg-fuel(-1)) from on-road vehicles varied widely from vehicle to vehicle, but showed a general trend of lower emissions for newer vehicles that met more stringent emission standards. IVOC emission factors for 2-stroke off-road engines were substantially higher than 4-stroke off-road engines and on-road vehicles. Despite large variations in the magnitude of emissions, the IVOC volatility distribution and chemical characteristics were consistent across all tests and IVOC emissions were strongly correlated with nonmethane hydrocarbons (NMHCs), primary organic aerosol and speciated IVOCs. Although IVOC emissions only correspond to approximately 4% of NMHC emissions from on-road vehicles over the cold-start unified cycle, they are estimated to produce as much or more SOA than single-ring aromatics. Our results clearly demonstrate that IVOCs from gasoline engines are an important class of SOA precursors and provide observational constraints on IVOC emission factors and chemical composition to facilitate their inclusion into atmospheric chemistry models.

Gas-Particle Partitioning of Vehicle Emitted Primary Organic Aerosol Measured in a Traffic Tunnel.

We measured the gas-particle partitioning of vehicle emitted primary organic aerosol (POA) in a traffic tunnel with three independent methods: artifact corrected bare-quartz filters, thermodenuder (TD) measurements, and thermal-desorption gas-chromatography mass-spectrometry (TD-GC-MS). Results from all methods consistently show that vehicle emitted POA measured in the traffic tunnel is semivolatile under a wide range of fleet compositions and ambient conditions. We compared the gas-particle partitioning of POA measured in both tunnel and dynamometer studies and found that volatility distributions measured in the traffic tunnel are similar to volatility distributions measured in the dynamometer studies, and predict similar gas-particle partitioning in the TD. These results suggest that the POA volatility distribution measured in the dynamometer studies can be applied to describe gas-particle partitioning of ambient POA emissions. The POA volatility distribution measured in the tunnel does not have significant diurnal or seasonal variations, which indicate that a single volatility distribution is adequate to describe the gas-particle partitioning of vehicle emitted POA in the urban environment.

Intermediate Volatility Organic Compound Emissions from On-Road Diesel Vehicles: Chemical Composition, Emission Factors, and Estimated Secondary Organic Aerosol Production.

Emissions of intermediate-volatility organic compounds (IVOCs) from five on-road diesel vehicles and one off-road diesel engine were characterized during dynamometer testing. The testing evaluated the effects of driving cycles, fuel composition and exhaust aftertreatment devices. On average, more than 90% of the IVOC emissions were not identified on a molecular basis, instead appearing as an unresolved complex mixture (UCM) during gas-chromatography mass-spectrometry analysis. Fuel-based emissions factors (EFs) of total IVOCs (speciated + unspeciated) depend strongly on aftertreatment technology and driving cycle. Total-IVOC emissions from vehicles equipped with catalyzed diesel particulate filters (DPF) are substantially lower (factor of 7 to 28, depending on driving cycle) than from vehicles without any exhaust aftertreatment. Total-IVOC emissions from creep and idle operations are substantially higher than emissions from high-speed operations. Although the magnitude of the total-IVOC emissions can vary widely, there is little variation in the IVOC composition across the set of tests. The new emissions data are combined with published yield data to investigate secondary organic aerosol (SOA) formation. SOA production from unspeciated IVOCs is estimated using surrogate compounds, which are assigned based on gas-chromatograph retention time and mass spectral signature of the IVOC UCM. IVOCs contribute the vast majority of the SOA formed from exhaust from on-road diesel vehicles. The estimated SOA production is greater than predictions by previous studies and substantially higher than primary organic aerosol. Catalyzed DPFs substantially reduce SOA formation potential of diesel exhaust, except at low speed operations.

Intermediate-volatility organic compounds: a large source of secondary organic aerosol.

Secondary organic aerosol (SOA) is a major component of atmospheric fine particle mass. Intermediate-volatility organic compounds (IVOCs) have been proposed to be an important source of SOA. We present a comprehensive analysis of atmospheric IVOC concentrations and their SOA production using measurements made in Pasadena, California during the California at the Nexus of Air Quality and Climate Change (CalNex) study. The campaign-average concentration of primary IVOCs was 6.3 ± 1.9 µg m(-3) (average ± standard deviation), which is comparable to the concentration of organic aerosol but only 7.4 ± 1.2% of the concentration of speciated volatile organic compounds. Only 8.6 ± 2.2% of the mass of the primary IVOCs was speciated. Almost no weekend/weekday variation in the ambient concentration of both speciated and total primary IVOCs was observed, suggesting that petroleum-related sources other than on-road diesel vehicles contribute substantially to the IVOC emissions. Primary IVOCs are estimated to produce about 30% of newly formed SOA in the afternoon during CalNex, about 5 times that from single-ring aromatics. The importance of IVOCs in SOA formation is expected to be similar in many urban environments.

Gas-particle partitioning of primary organic aerosol emissions: (2) diesel vehicles.

Experiments were performed to investigate the gas-particle partitioning of primary organic aerosol (POA) emissions from two medium-duty (MDDV) and three heavy-duty (HDDV) diesel vehicles. Each test was conducted on a chassis dynamometer with the entire exhaust sampled into a constant volume sampler (CVS). The vehicles were operated over a range of driving cycles (transient, high-speed, creep/idle) on different ultralow sulfur diesel fuels with varying aromatic content. Four independent yet complementary approaches were used to investigate POA gas-particle partitioning: artifact correction of quartz filter samples, dilution from the CVS into a portable environmental chamber, heating in a thermodenuder, and thermal desorption/gas chromatography/mass spectrometry (TD-GC-MS) analysis of quartz filter samples. During tests of vehicles not equipped with diesel particulate filters (DPF), POA concentrations inside the CVS were a factor of 10 greater than ambient levels, which created large and systematic partitioning biases in the emissions data. For low-emitting DPF-equipped vehicles, as much as 90% of the POA collected on a quartz filter from the CVS were adsorbed vapors. Although the POA emission factors varied by more than an order of magnitude across the set of test vehicles, the measured gas-particle partitioning of all emissions can be predicted using a single volatility distribution derived from TD-GC-MS analysis of quartz filters. This distribution is designed to be applied directly to quartz filter data that are the basis for existing emissions inventories and chemical transport models that have implemented the volatility basis set approach.

Reactive organic carbon air emissions from mobile sources in the United States.

Mobile sources are responsible for a substantial controllable portion of the reactive organic carbon (ROC) emitted to the atmosphere, especially in urban environments of the United States. We update existing methods for calculating mobile source organic particle and vapor emissions in the United States with over a decade of laboratory data that parameterize the volatility and organic aerosol (OA) potential of emissions from on-road vehicles, nonroad engines, aircraft, marine vessels, and locomotives. We find that existing emission factor information from Teflon filters combined with quartz filters collapses into simple relationships and can be used to reconstruct the complete volatility distribution of ROC emissions. This new approach consists of source-specific filter artifact corrections and state-of-the-science speciation including explicit intermediate-volatility organic compounds (IVOCs), yielding the first bottom-up volatility-resolved inventory of US mobile source emissions. Using the Community Multiscale Air Quality model, we estimate mobile sources account for 20 %-25 % of the IVOC concentrations and 4.4 %-21.4 % of ambient OA. The updated emissions and air quality model reduce biases in predicting fine-particle organic carbon in winter, spring, and autumn throughout the United States (4.3 %-11.3 % reduction in normalized bias). We identify key uncertain parameters that align with current state-of-the-art research measurement challenges.

Volatility of organic molecular markers used for source apportionment analysis: measurements and implications for atmospheric lifetime.

Molecular markers are organic species used to define fingerprints for source apportionment of ambient fine particulate matter. Traditionally, these markers have been assumed to be stable in the atmosphere. This work investigates the gas-particle partitioning of eight organic species used as molecular markers in receptor models for biomass burning (levoglucosan), motor vehicles (5α-cholestane, n-hexacosane, n-triacontane, 1,2-benz[a]anthracene, coronene), and meat cooking (cholesterol, oleic acid). Experiments were conducted using a thermodenuder to measure the evaporation of single component particles. The data were analyzed using the integrated volume method to determine saturation concentrations and enthalpies of vaporization for each compound. The results indicate that appreciable quantities (>10%) of most of these markers exist in the gas phase under typical atmospheric conditions. Therefore, these species should be considered semivolatile. Predictions from a chemical kinetics model indicate that gas-particle partitioning has important effects on the atmospheric lifetime of these species. The atmospheric decay of semivolatile compounds proceeds much more rapidly than nonvolatile compounds because gas-phase oxidation induces evaporation of particle-phase material. Therefore, both gas-particle partitioning and chemical reactions need to be accounted for when semivolatile molecular markers are used for source apportionment studies.

Predicting the risk of GenX contamination in private well water using a machine-learned Bayesian network model.

Per- and polyfluoroalkyl substances (PFAS) are emerging contaminants that pose significant challenges in mechanistic fate and transport modeling due to their diverse and complex chemical characteristics. Machine learning provides a novel approach for predicting the spatial distribution of PFAS in the environment. We used spatial location information to link PFAS measurements from 1207 private drinking water wells around a fluorochemical manufacturing facility to a mechanistic model of PFAS air deposition and to publicly available data on soil, land use, topography, weather, and proximity to multiple PFAS sources. We used the resulting linked data set to train a Bayesian network model to predict the risk that GenX, a member of the PFAS class, would exceed a state provisional health goal (140 ng/L) in private well water. The model had high accuracy (ROC curve index for five-fold cross-validation of 0.85, 90% CI 0.84-0.87). Among factors significantly associated with GenX risk in private wells, the most important was the historic rate of atmospheric deposition of GenX from the fluorochemical manufacturing facility. The model output was used to generate spatial risk predictions for the study area to aid in risk assessment, environmental investigations, and targeted public health interventions.