ACS ES&T Air最新文献

Personal care products can release decamethylcyclopentasiloxane (D₅) to the atmosphere, where it oxidizes to form 1-hydroxynonamethylcyclopentasiloxane (D₄TOH). This oxidation product subsequently can partition to the particle-phase to form secondary organic aerosol (SOA). The gas-particle distribution of D₄TOH has been studied in the laboratory but has yet to be established in ambient air. This study examines the gas-particle distribution of D₄TOH and related oxidation products in New York City during the summertime of 2022 using medium volume air samplers, solvent extraction, and gas and liquid chromatography mass spectrometry methods. Positive sampling artifacts constituted the majority of D₄TOH observed on quartz fiber filters (54-100%, averaging 86%, n = 12), indicating the high potential for particle-phase D₄TOH to be overestimated. After artifact correction, D₄TOH was observed in fine particles in 5 of the 12 sampling periods, with its particle-phase fraction averaging 13%. Because D₄TOH is predominantly in the gas phase, it makes a minor contribution to D₅-derived SOA during summertime. Further oxidation products of D₅, including di, and tetrasiloxanols are predominantly in the particle-phase (>77%, n = 4) during summertime and have relatively small positive artifacts. These polysiloxanols provide evidence of D₅-derived SOA in the urban aerosols and are more suitable tracers for D₅-derived SOA than D₄TOH in summertime because of their higher particle-phase fractions.

Volatility and viscosity are important parameters affecting the formation, reaction, and fate of atmospheric organic aerosols. In this study, a Vaporization Inlet for Aerosol (VIA) coupled with a Vocus chemical ionization mass spectrometer (Vocus-CIMS) using NH₄ ⁺ adduct ionization is employed to simultaneously detect and quantify the molecular composition and volatility of organic aerosols through a program-controlled temperature ramp, thereby providing viscosity information. Volatility calibration was conducted with a series of reference aerosol particles with different chemical compositions, covering a vapor pressure range from 10^-1 to 10^-8 Pa. Secondary organic aerosols (SOA) produced from the potential aerosol mass reactor were analyzed by the VIA-CIMS. Chemical species ranging from semivolatile to low-volatility, including highly oxygenated dimers, were identified. Individual ions from the collected mass spectra were fitted and grouped by volatility basis sets to yield the volatility distribution of the SOA, allowing for the quantification of the glass transition temperatures and viscosities. Results show that β-caryophyllene ozonolysis SOA has lower volatility and is more viscous than the α-pinene SOA. This approach enables the online quantification of SOA particle chemical composition and volatility distribution, while simultaneously characterizing particle phase state, such as viscosity and water diffusion time, providing crucial insights into their chemical processes and climate impacts.

At the wildland-urban interface (WUI) structural fires can generate nonmethane organic gases (NMOGs) from burning urban fuels like structural lumber, plastics, and carpet. These NMOGs can contaminate nearby homes and affect indoor air quality. NMOGs have been quantified extensively from biomass burning, but few measurements exist of yields from structure fires. We calculated yields of 201 NMOGs generated from burning small-scale residential building surrogates. We also constructed surrogates of different sizes and stick packing densities to modulate air ventilation and simulate how reduced oxygen conditions in enclosed fires might affect NMOG yields. We find that reduced aromatics (e.g., benzene, naphthalene) show notably higher yields from combustion of the surrogates compared to biomass, whereas oxygenated NMOG (e.g., formaldehyde, acetaldehyde) yields are lower. Using factor analysis of NMOG time series, we observe chemical signatures from the combustion of synthetic polymers, wood, and mixed fuel char. Though we do not identify unique tracers we identify NMOGs that, if present in enhanced concentrations, may indicate WUI fire contamination in homes.

Photolysis of gaseous organic nitrates is crucial for understanding the formation and fate of air pollutants such as nitrogen oxides (NO _x ) and ozone (O₃). Monoterpenes are prevalent biogenic volatile organic compounds (VOCs), greatly contributing to the formation of organic nitrates; however, there is currently a lack of experimental constraints on the photolysis chemistry of monoterpene organic nitrates. Here, we investigated the photolysis of monoterpene organic nitrates via novel dual chamber experiments, in which a large suite of organic nitrates was formed from hydroxyl and nitrate radical oxidation of α-pinene and β-pinene in one chamber and were introduced into another chamber to study photolysis. We directly measured their photolysis rates with chemical ionization mass spectrometry by minimizing the interferences of other types of chemical and/or physical reactions. The chamber photolysis rate constants vary depending not only on the molecular formulas of organic nitrates but also on the VOC type and oxidation condition. While the photolysis rate constants of 53.1% of the C₁₀ organic nitrates for which the rate constants were estimated are on the order of 1 × 10^-5 s^-1 or larger, the other C₁₀ organic nitrates exhibit little to no decrease in their measured signals. This highlights how differences in chemical structures can affect the photolability of organic nitrates. The most photolabile organic nitrate is C₁₀H₁₇NO₅ (either hydroxy carbonyl nitrate or hydroperoxy nitrate) formed from nitrate radical oxidation of α-pinene and β-pinene, with the chamber photolysis rate constant of 1.1 (±0.1) and 1.3 (±0.3) × 10^-4 s^-1, respectively. When extrapolated to ambient conditions (solar zenith angle of 28.14° in summer), the photolysis rate constant is as large as 6.4 (±3.0) × 10^-4 s^-1 (corresponding to a photolysis lifetime of 0.43 ± 0.20 h). Compared to other loss processes (i.e., OH oxidation and dry deposition) of gaseous organic nitrates formed from nitrate radical oxidation of β-pinene, photolysis serves as either a comparable or dominant sink depending on the molecular formulas of organic nitrates. These findings have important atmospheric implications regarding the role of monoterpene organic nitrates in the spatial distribution of NO _x and O₃ formation.

We investigated the effects of the fuel moisture content and photochemical aging on the toxicity of smoke particulate matter (PM) emissions in simulated wildland fires. We burned fuel beds consisting of surface fuels and duff under moderate and low moisture contents, representative of prescribed fires (Rx) and drought-induced wildfires (Wild), respectively. The Wild emissions were photochemically aged in an oxidation flow reactor (Wild-Aged). We exposed human bronchial epithelial cells to PM extracts from each permutation. PM extracts from all experimental permutations (Rx, Wild, Wild-Aged) induced oxidative stress, evidenced by a significant increase in 8-isoprostane concentration in the cell media compared to control. However, the increase of 8-isoprostane was significantly less in Wild-Aged compared to that in Wild and Rx, indicating loss of oxidative potential due to photochemical aging. Based on the release of lactate dehydrogenase in the cell media, the level of lipid peroxidation, and the magnitude of gene fold-changes, Rx PM extracts were more toxic than Wild. Chemical composition analysis suggests that toxicity was driven by levels of aromatic species in the PM, which were highest in Rx, followed by Wild and Wild-Aged. Overall, these results highlight the complex dependence of the toxicity of wildland-fire smoke on combustion conditions and atmospheric processing.

Isoprene oxygenated organic molecules (IP-OOM) can nucleate new particles in the upper troposphere. These particles may grow into cloud condensation nuclei and influence the clouds and climate. However, little is known about the individual species driving growth and whether they undergo condensed-phase reactions. We conducted isoprene oxidation experiments at 223 and 243 K in the CLOUD chamber at CERN. Gas-phase concentrations were measured with chemical ionization mass spectrometers (NO₃ ^--CIMS, Br^--MION2-CIMS, and NH₄ ⁺-CIMS). Growth rates from 8 to 20 nm were measured by a Neutral Cluster and Air Ion Spectrometer. Particle-phase composition was measured by a filter sampling chemical ionization mass spectrometer. We use the diagonal volatility basis set (dVBS) analysis framework to compare gas- and particle-phase measurements and assess species and processes influencing growth. We find that kinetically limited condensation of a few species dominates particle composition and growth. Particle-phase processes, including oligomerization and organonitrate hydrolysis, do not influence the early growth. dVBS growth rate predictions can explain 90% of the measured growth, dominated by kinetic condensation of low-volatility species. Our findings indicate that initial growth of IP-OOM particles under cold, low-acid conditions may be controlled and modeled by the kinetically limited condensation of low-volatility compounds.

Wildfires can inject smoke at high altitudes into the atmosphere. The resulting free tropospheric aerosols may affect inference of ground-level fine particulate matter (PM_2.5) from satellite aerosol optical depth (AOD), yet the effects of accounting for plume height in this inference are poorly understood. Here, we include in the GEOS-Chem chemical transport model a fire plume height parametrization (GFAS, Global Fire Assimilation System) to examine its effect on PM_2.5 inferred from satellite AOD during wildfires over the United States and Canada. Comparison with six years satellite observations of plume height reveals a low bias of a factor 1.7 in the GFAS plume height over evergreen needleleaf forests. We scale the GFAS plume height over evergreen needleleaf forests in GEOS-Chem to better represent the satellite observations, focusing on 2018 and 2020 when large wildfires yield prominent signals. Replacing the default ground-level wildfire emissions in GEOS-Chem with the scaled GFAS vertically distributed emissions reduces the bias between measured PM_2.5 and PM_2.5 inferred from satellite AOD, and significantly improves the consistency of simulated AOD with sun photometer measurements. Overall, this study signifies the importance of vertically distributing wildfire emissions for the inference of PM_2.5 from satellite AOD.

We investigated the influence of combustion conditions on emissions of elemental carbon (EC) and organic carbon (OC) and the formation of secondary organic carbon (SOC) in wildland fires. We performed combustion experiments using fuel beds representative of three ecoregions in the Southeastern U.S. and varied the fuel-bed moisture content to simulate either prescribed fires (Rx) or drought-induced wildfires (Wild). We used fire radiative energy normalized by fuel-bed mass (FRE_norm) as a proxy for combustion conditions. For fuel beds that contained surface fuels only, the higher moisture content in Rx led to lower FRE_norm compared to Wild and consequently led to lower EC emissions, but higher OC emissions and SOC formation. For fuel beds that contained duff in addition to surface fuels, duff did not ignite in Rx because of the high moisture content. However, duff ignited in Wild, leading to prolonged smoldering and substantially lower FRE_norm in Wild compared to Rx. Consequently, OC emissions and SOC formation were an order of magnitude higher in Wild compared to Rx for the duff-containing fuel beds. These findings indicate that characterizing fuel availability and variability in combustion conditions, which emerges from variability in fuel-bed composition and environmental conditions, is crucial for determining carbonaceous aerosol formation in wildland fires.

China’s air quality has improved significantly since 2013 due to the implementation of strict clean air policies prioritizing highly polluted regions. However, the effectiveness of those actions on reducing environmental inequality is not clear. Here, we analyzed the air pollution disparity changes in China from 2013 to 2018 using a combination of air quality, population and urbanization data. For PM_2.5, PM₁₀, NO₂, SO₂ and CO, we found a general decline in both rural-urban disparity and geographic disparity, with SO₂ and CO showing the most substantial reductions. For O₃, we found mixed changes in rural-urban disparity and an increase in geographic disparity. Our findings suggest that China’s air pollution control strategies have been effective in improving overall air quality and reducing exposure inequalities. We underscore the importance of strategies to reduce NO₂ emissions, given its significant rural-urban and geographic disparities, and its role as a precursor to both PM_2.5 and O₃. This study highlights the effectiveness of China’s clean air actions from a different perspective and emphasizes the need to further improve air quality and alleviate remaining disparities.

Most indoor air pollution studies focusing on modeling and material balance assume well-mixed conditions, which is usually not true in larger and multizonal spaces. Spatially nonhomogenous concentrations can lead to considerably different personal exposure of occupants within the same indoor space. Studying the interzonal transport of pollutants and their governing factors provides critical insights into the fate and transport of pollutants. The current work focuses on predicting PM_2.5 and CO₂ concentrations in different zones of a residential apartment using measured concentrations in one zone using conventional and physics-informed long short-term memory (PI-LSTM) models for different internal door configurations. Model predictions were validated using experimentally obtained spatiotemporal data sets using the exposure and maximum concentration (relative to measured) as key performance metrics. The PI-LSTM model performed better in most cases for PM_2.5, while the LSTM model exhibited better predictive accuracy for CO₂ concentrations. As more internal doors were opened and the number of zones increased, PI-LSTM’s predictive accuracy declined. PM_2.5 predictions were more accurate for zones near the emission source than those farther away.