ACS ES&T Air最新文献

Biogenic volatile organic compounds (BVOCs), a dominant source of secondary organic aerosol (SOA) globally, exhibit emission rates and compositions that are plant species-specific and vary with environmental stressors. A common outcome of plant stress is increased emissions of acyclic terpenes. The paucity of information about acyclic terpene SOA chemistry contributes to uncertainties in predictions of SOA global loadings and impacts on Earth's radiative budget, particularly in a changing climate where acyclic terpene emissions could become more prominent. This study compared properties of SOA derived from hydroxyl radical (OH) oxidation of acyclic and cyclic monoterpenes (β-ocimene, α-pinene) and sesquiterpenes (β-farnesene, β-caryophyllene). Single-particle mass spectrometry was used for assessing shape, density, and evaporation kinetics of size-selected SOA particles, and nanospray desorption electrospray ionization high-resolution mass spectrometry (nano-DESI-HRMS) was used to measure the molecular composition of SOA. Acyclic terpene SOA exhibited higher viscosity and lower volatility compared to cyclic terpene SOA, and had a greater volume fraction remaining (VFR) after ∼24 h of evaporationapproximately 1.3-1.6 times higher VFR than that of cyclic terpene SOA. Additionally, HRMS analysis revealed greater chemical diversity and higher fractions of extremely low-volatility compounds (56-62% ELVOC/LVOC) in acyclic terpene SOA compared to cyclic counterparts (25-37% ELVOC/LVOC). Our findings highlight the potential importance of accounting for acyclic terpene aerosol chemistry under conditions of plant stress to improve predictions of SOA loadings and impacts.

A new calibration approach, the Network Calibration Algorithm (NCA), was developed and applied to low-cost sensors measuring PM_2.5, O₃, NO₂, NO, and CO at 38 New York State Mesonet sites in the New York City Metropolitan Area. A single low-cost sensor package (the "keystone" package) was colocated alongside regulatory-grade (reference) instruments at the New York State Department of Environmental Conservation Queens College monitoring site for 16 months. For each pollutant, hourly data from the keystone package and reference instruments were used to train a single calibration model that was subsequently applied to all packages at field sites across the network. The calibration models included multiple linear regression (MLR) for CO and a hybrid approach that combined MLR with a Random Forest model for PM_2.5, O₃, NO₂, and NO. The performance of the NCA-calibrated low-cost sensors was quantified using multiple evaluation data sets, with a focus on accuracy and long-term stability over the 16-month period. The performance statistics were consistent with or better than previous reports for similar low-cost sensors, and the NCA was able to compensate for sensor degradation and drift. Empirical estimates of the field limit of detection for each of the low-cost sensors are presented.

Wildland-urban interface (WUI) fires pose unique environmental pollution challenges due to the combustion of both natural vegetation and synthetic building materials. Following the 2025 Palisades and Eaton wildfires in Los Angeles, we conducted a field study to characterize indoor air quality and surface contamination in 19 homes before reoccupancy. Indoor PM_2.5 and PM₁₀ concentrations averaged 3.45 and 31.66 μg/m³, respectively, with several homes showing indoor-to-outdoor (I/O) ratios of >1 (particularly for PM₁₀) compared to typical I/O values of 0.45-0.8 in residences, indicating persistent indoor particle reservoirs. Depending on the air-exchange rate, elevated indoor PM levels in noncleaned homes may arise from two contrasting mechanisms: low ventilation that traps resuspended fire residues triggered by movements during sampling and high ventilation that induces turbulence and disturbs heavily contaminated entry zones. Regression analysis suggested that proximity to the fire, absence of air purifiers, use of non-HEPA vacuums, and open windows during the fire significantly increased indoor PM levels, explaining 73% (PM₁₀) and 86% (PM_2.5) of the variation across homes. Airborne metal concentrations were below health-based thresholds; however, surface wipe samples revealed widespread contamination, with potassium, magnesium, aluminum, and iron frequently exceeding 1000 μg/ft², and detectable levels of zinc, copper, and manganese in many homes. Lead concentrations exceeded the EPA's dust clearance levels in multiple homes, especially on window sills and entry floors. Our findings highlight that while airborne risks may subside within weeks after the fire, indoor surfaces can retain fire-related pollutants, presenting ongoing exposure risks even 2 months after the fire.

Fires occurring at the wildland-urban interface (WUI) can produce smoke, that contains unique chemicals from the combustion of urban structures, which can then contaminate nearby buildings and affect indoor air quality. Assessing property loss and possible occupant exposure to persistent contamination from WUI smoke is challenging, in part because of a lack of measurements detailing chemical contamination in real indoor environments after WUI events. Here, we mimic contamination from a WUI fire by repeatedly exposing a test house to smoke from combustion of residential building surrogates and measure the persistence of volatile nonmethane organic gas (NMOG) contamination. Over the 1.5 month experimental period, we observed an increase in emission rates of 31 NMOGs, indicating the formation of surface reservoirs indoors that increase with subsequent burns. We observe off-gassing time scales of less than 10 days for many highly volatile NMOGs like acetonitrile, acrylonitrile, and styrene. Other NMOGs, like naphthalene and C12 aromatics, took longer than 10 days to off-gas and show emissions persistently elevated above background for at least three months after the end of the experiments. The NMOG emissions from contamination in the test house were lower when compared with a house affected by the Marshall Fire in Colorado. However, the NMOG off-gassing times measured in the test house were longer.

Reliable elemental analysis is important for understanding mineral dust mass concentrations, composition, sources, and atmospheric processing. X-ray attenuation of light elements in widely used X-ray fluorescence (XRF) measurements can lead to underestimated dust mass and inaccurate dust composition, yet attenuation corrections are often neglected in ambient particulate matter (PM) analysis. This study experimentally quantifies attenuation for silicon and aluminum by comparing XRF and gravimetric measurements of samples with known compositions. Silica (SiO₂), alumina (Al₂O₃), and Arizona test dust (ATD) were aerosolized and collected on Teflon filters to generate samples with varying mass loadings and particle size ranges. Results validated that attenuation increases with both mass loading and particle size. Greater Si attenuation observed in ATD than in SiO₂ at equivalent mass loading and size range indicates that other crustal elements enhance Si attenuation. Theoretical models considering only mass loading or particle size underestimated the measured attenuation. We developed empirical equations to correct for Si and Al attenuation. Applying these equations, with a size scaling factor for nondust species, to ambient dust-dominated PM samples from the global Surface PARTiculate mAtter Network (SPARTAN) increased dust concentrations by 21% in PM_2.5 and 29% in PM₁₀. This work demonstrates the importance of considering attenuation effects in XRF analysis for accurate dust inference from measured elements.

The mechanisms of secondary organic aerosol (SOA) formation are not yet fully understood. The relative abundance of hydroperoxyl radicals (HO₂) and peroxy radicals (RO₂) affects SOA properties, but chamber experiments often underemphasize the role of HO₂. To clarify their contribution, this study compares the composition and volatility of SOA formed by the hydroxyl radical (OH) oxidation of α-pinene under low and high HO₂/RO₂ regimes with a constant OH concentration. The particle-phase was characterized with a Filter Inlet for Gases and AEROsols coupled to an iodide Chemical Ionization Mass Spectrometer (FIGAERO CIMS), and a CIMS with NO₃ ^- ionization was used for gas-phase measurements. High HO₂/RO₂ conditions weakened the particle-phase monomer (C₁₀), fragment (C_4-9), and accretion product (C_11-20) signals by 34%, 29%, and 78%, respectively, compared to low HO₂/RO₂ conditions. The only species with an increased signal (180%) was C₁₀H₁₈O₇. The gas-phase changes align with those in the particle-phase within a factor of 2. Overall, the organic mass was reduced by 47% and 39% for particle and gas-phases, respectively. Bulk SOA volatility (log C*) increased slightly from -0.22 μg m^-3 to -0.1 μg m^-3, reflecting the suppression of low volatility accretion products but formation of high volatility hydroperoxide monomers. This study highlights the importance of HO₂ for SOA formation and model predictions.

Global aviation has contributed ∼3.5% to the anthropogenic climate forcing in 2018, of which around two-thirds (with substantial uncertainty) were due to non-CO₂ effects dominated by contrail cirrus. To be sustainable, the aviation industry faces a great challenge in reducing its climate footprint. There are ongoing efforts toward contrail avoidance via rerouting flights to avoid ice supersaturated regions, but serious reservations have been voiced against it because of extra fuel burning and resultant increased CO₂ emissions, among other issues. Based on simulations with a state-of-the-art aerosol and contrail microphysics model, we show that the aviation non-CO₂ climate effect associated with contrail cirrus may be significantly reduced via controlled seeding of a small amount of ice-nucleating particles (INPs). The optimized amount of INPs seeded will consume water vapor and minimize the peak relative humidity reached in the plume. In turn, this reduces the number of exhaust particles activating and forming contrail ice particles by up to 1-2 orders of magnitude, resulting in larger contrail ice particles that fall faster and shorter contrail lifetimes, which is expected to diminish the warming effect of contrail cirrus to a very small level. This novel approach may solve some of the issues associated with the proposed navigational contrail avoidance, but further research is needed to assess its feasibility and environmental impacts.

Bioaerosols can affect human and plant health as well as climate. New automatic bioaerosol monitors capable of detecting and classifying pollen and fungal spores in real time have recently been developed, revolutionizing the way how data are collected, analyzed and distributed to the public. However, the technologies, still being very new, have not been adequately characterized and the instruments' performance is poorly understood. Here, we developed a general method for evaluating the performance of both the hardware (particle detector) and software (machine learning algorithm) of automated bioaerosol monitors. For the first time, number concentration measurements were carried out for particle sizes up to 70 μm. To do this, three different reference methods were combined: a custom-made reference optical particle counter, an inkjet aerosol generator (IAG) and particle tracking velocimetry (PTV). The size-dependent counting efficiency and unit-to-unit variability of five different SwisensPoleno Jupiter bioaerosol monitors was thus determined in a traceable manner over almost the entire pollen and fungal spore size range. The classification efficiency of the supervised machine learning (ML) algorithm developed by MeteoSwiss, which is currently being used by various research institutes and monitoring stations in Europe, was determined by delivering well-known pollen taxa to the Poleno monitor under controlled laboratory conditions. The influence of factors, such as environmental conditions and geographic location of the tree, on the classification efficiency was quantified, and recommendations are made for improving ML algorithm training in the future. The methods outlined in this study aim to establish a traceable framework to ensure that real-time bioaerosol measurements, despite the measurement challenges related to large micrometre-sized particles at low concentrations (a few hundred particles per m³), are carried out at the same level of accuracy as legislated air-quality measurements. This is particularly important as a step toward their integration into European legislation.

Sources of desert dust, atmospheric transport, recorded concentrations of atmospheric particulate matter (PM), physical, compositional, and biological characteristics, and likely direct and indirect impacts on air quality impairment are reviewed without a systematic, but with an expert approach. The aim is to offer information necessary to protect the health of exposed populations in the dust-emitting and dust-receptor regions. This review corroborates the complexity of the process by which air quality is impaired during dust episodes, the mixture of components that PM might contain during dust episodes, the differences between dust emission and reception regions, and the interplay of indirect effects (thinning the boundary layer; concentration of local pollution; interactions with anthropogenic pollutants). Based on these dust episode patterns, we recommend the implementation of alert systems to protect the more vulnerable members of the population and highlight a number of recommendations for air quality monitoring during such episodes to provide adequate data sets to rigorously evaluate health outcomes associated with dust exposure in emitting and receptor regions and the possible causes for these effects.

The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) characterized aerosol composition using measurements at two sites within 3 km (Scripps Pier and Mt. Soledad) from 15 February 2023 to 14 February 2024. Comparing the two sites shows the strong influence of upwind sources that results in similar monthly compositions at both sites. The seasonal changes in chemical mass concentrations were largely driven by the upwind source regions, with coastal northwesterly back-trajectories occurring 63-65% of the year and bringing submicrometer mass concentrations that were lower than the EPCAPE average for all trajectories at each site. In contrast, refractory black carbon (rBC) and nonrefractory (NR)-organics and nitrate mass concentrations exceeded EPCAPE average concentrations for back-trajectories from urban areas such as Los Angeles-Long Beach. For hourly measurements, NR-organics and non-sea-salt (NSS)-sulfate mass concentrations at Mt. Soledad were correlated strongly (r = 0.73-0.82) to those measured at Scripps Pier, but NR-nitrate was correlated only moderately (r = 0.63). The explanation for the lower correlation of NR-nitrate is both emissions between the sites and semivolatility, with semivolatility accounting for site-to-site changes in daily averages of +0.01 μg m^-3 per percentage site-to-site difference in relative humidity and -0.07 μg m^-3 per degree Celsius site-to-site difference in temperature. On average, comparing Scripps Pier to Mt. Soledad, NR-nitrate was higher by 29% because of relative humidity and lower by -26% because of temperature. NR-nitrate and rBC mass concentrations at Scripps Pier for nighttime were 13-15% higher than those for daytime because land breezes brought higher inland concentrations. Concentrations of rBC were 52% higher at Mt. Soledad than those measured at Scripps Pier, accompanied by increases in tracers for brake wear because of traffic on the steep roads within 10 m of that site. The implications are that these nearby sites had comparable monthly concentrations of measured components due to their similar back-trajectories, but hourly and daily concentration differences supported quantification of the meteorological effects from relative humidity and temperature on semivolatile NR-nitrate as well as minor differences from land-sea breezes and local emissions.