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Climate change, wildfires, and environmental justice concerns have drawn increased attention to the impact of air pollution on children's health and development. Children are especially vulnerable to air pollution exposure, as their brains and bodies are still developing. The objective of this systematic review was to synthesize available empirical evidence on the associations between air pollution exposure and brain outcomes in developmental samples (ages 0-18 years old). Studies were identified by searching the PubMed and Web of Science Core Collection databases and underwent a two-phase screening process before inclusion. 40 studies were included in the review, which included measures of air pollution and brain outcomes at various points in development. Results linked air pollution to varied brain outcomes, including structural volumetric and cortical thickness differences, alterations in white matter microstructure, functional network changes, metabolic and molecular effects, as well as tumor incidence. Few studies included longitudinal changes in brain outcomes. This review also suggests methodologies for incorporating air pollution measures in developmental cognitive neuroscience studies and provides specific policy recommendations to reduce air pollution exposure and promote healthy brain development by improving access to clean air.

Chronic exposure to traffic-related air pollution (TRAP) is known to promote systemic inflammation, which is thought to underlie respiratory, cardiovascular, metabolic and neurological disorders. It is not known whether chronic TRAP exposure dampens inflammation resolution, the homeostatic process for stopping inflammation and repairing damaged cells. In vivo, inflammation resolution is facilitated by bioactive lipid mediators known as oxylipins, which are derived from the oxidation of polyunsaturated fatty acids. To understand the effects of chronic TRAP exposure on lipid-mediated inflammation resolution pathways, we measured total (i.e. free+bound) pro-inflammatory and pro-resolving lipid mediators in serum of female rats exposed to TRAP or filtered air (FA) for 14 months. Compared to rats exposed to FA, TRAP-exposed rats showed a significant 36-48% reduction in fatty acid alcohols, specifically, 9-hydroxyoctadecadienoic acid (9-HODE), 11,12-dihydroxyeicosatetraenoic acid (11,12-DiHETE) and 16,17-dihydroxydocosapentaenoic acid (16, 17-DiHDPA). The decrease in fatty acid diols (11,12-DiHETE and 16, 17-DiHDPA) corresponded to a significant 34-39% reduction in the diol to epoxide ratio, a marker of soluble epoxide hydrolase activity; this enzyme is typically upregulated during inflammation. The findings demonstrate that 14 months exposure to TRAP reduced pro-inflammatory 9-HODE concentration and dampened soluble epoxide hydrolase activation, suggesting adaptive immune changes in lipid mediator pathways involved in inflammation resolution.

Epidemiological and toxicological studies continue to demonstrate correlative and causal relationships between exposure to traffic-related air pollution and various metrics of adverse pulmonary, cardiovascular, and neurological health effects. The key challenge for in vivo studies is replicating real-world, near-roadway exposure dynamics in laboratory animal models that mimic true human exposures. The advantage of animal models is the accelerated time scales to show statistically significant physiological and/or behavioral response. This work describes a novel exposure facility adjacent to a major freeway tunnel system that provides a platform for real-time chronic exposure studies. The primary conclusion is that particulate matter (PM) concentrations at this facility are routinely well below the National Ambient Air Quality Standards (NAAQS), but studies completed to date still demonstrate significant neurological and cardiovascular effects. Internal combustion engines produce large numbers of ultrafine particles that contribute negligible mass to the atmosphere relative to NAAQS regulated PM2.5 but have high surface area and mobility in the body. It is posited here that current federal and state air quality standards are thus insufficient to fully protect human health, most notably the developing and aging brain, due to regulatory gaps for ultrafine particles.

We have recently developed a low-cost spark-induced breakdown spectroscopy (SIBS) instrument for in-situ analysis of toxic metal aerosol particles that we call TARTA (toxic-metal aerosol real time analyzer). In this work, we applied machine learning methods to improve the quantitative analysis of elemental mass concentrations measured by this instrument. Specifically, we applied least absolute shrinkage and selection operator (LASSO), partial least squares (PLS) regression, principal component regression (PCR), and support vector regression (SVR) to develop multivariate calibration models for 13 metals (e.g., Cr, Cu, Mn, Fe, Zn, Co, Al, K, Be, Hg, Cd, Pb, and Ni), some of which are included on the US EPA hazardous air pollutants (HAPS) list. The calibration performance, adjusted coefficient of determination (R2) and normalized root mean square error (RMSE), and limit of detection (LOD) of the proposed models were compared to those of univariate calibration models for each analyte. Our results suggest that machine learning models tend to have better prediction accuracy and lower LODs than conventional univariate calibration, of which the LASSO approach performs the best with R2 > 0.8 and LODs of 40-170 ng m-3 at a sampling time of 30 min and a flow rate of 15 l min -1. We then assessed the applicability of the LASSO model for quantifying elemental concentrations in mixtures of these metals, serving as independent validation datasets. Ultimately, the LASSO model developed in this work is a very promising machine learning approach for quantifying mass concentration of metals in aerosol particles using TARTA.

Traffic-related air pollution (TRAP) is a risk factor for Alzheimer’s disease (AD) where neuroinflammation underlies disease progression and pathogenesis. Unresolved inflammation in AD is known to be exacerbated by brain deficits in unesterified pro-resolving lipid mediators enzymatically synthesized from polyunsaturated fatty acids. Recently, we reported that in the brain, unesterified pro-resolving lipid mediators which are bioactive, can also be supplied from less bioactive esterified lipid pools such as neutral lipids (NLs) and phospholipids (PLs). It is not known whether esterified pro-resolving lipid mediators are affected by AD pathology and exacerbated by TRAP exposure. In the present study we addressed this data gap using TgF344-AD male and female rats that express human AD risk genes and their wildtype littermates exposed to filtered air (FA) or TRAP from 1 to 15 months of age. Esterified lipid mediators within NLs and PLs were quantified by mass-spectrometry. We observed a significant reduction in pro-resolving lipid mediators in both NLs and PLs of female TgF344-AD rats compared to wildtype controls. TRAP exposure also reduced pro-resolving lipids in the female brain, mainly in PL pools, but did not exacerbate changes observed in TgF344-AD rats. Minimal changes were observed in males. Our findings indicate that AD genotype and chronic TRAP exposure result in sex-specific deficits in brain esterified pro-resolving lipid mediators, the pool that supplies free and bioactive lipid mediators. These data provide new information on lipid-mediated mechanisms regulating impaired inflammation resolution in AD, and show for the first time that chronic TRAP exposure targets the same lipid network implicated in AD.

BackgroundTraffic-related air pollution (TRAP) is linked to increased risk for age-related dementia, including Alzheimer's disease (AD). The gut microbiome is posited to influence AD risk, and an increase in microbial-derived secondary bile acids (BAs) is observed in AD patients. We recently reported that chronic exposure to ambient TRAP modified AD risk in a sex-dependent manner in the TgF344 AD (TG) rat.ObjectivesIn this study, we used samples from the same cohort to test our hypothesis that TRAP sex-dependently produces gut dysbiosis and increases secondary BAs to a larger extent in the TG rat relative to wildtype (WT) controls.MethodsMale and female TG and age-matched WT rats were exposed to either filtered air (FA) or TRAP from 28 days up to 15 months of age (n = 5-6). Tissue samples were collected after 9 or 14months of exposure.ResultsAt 10 months of age, TRAP tended to decrease the alpha diversity as well as the beneficial taxa Lactobacillus and Ruminococcus flavefaciens uniquely in male TG rats as determined by 16 S rDNA sequencing. A basal decrease in Firmicutes/Bacteroidetes (F/B) ratio was also noted in TG rats at 10 months. At 15 months of age, TRAP altered inflammation-related bacteria in the gut of female rats from both genotypes. BAs were more affected by chronic TRAP exposure in females, with a general trend of increase in host-produced unconjugated primary and microbiota-produced secondary BAs. Most of the mRNAs of the hepatic BA-processing genes were not altered by TRAP, except for a down-regulation of the BA-uptake transporter Ntcp in males.ConclusionIn conclusion, chronic TRAP exposure produced distinct gut dysbiosis and altered BA homeostasis in a sex and host genotype-specific manner.

Epidemiological studies have demonstrated that air pollution is a significant risk factor for age-related dementia, including Alzheimer's disease (AD). It has been posited that traffic-related air pollution (TRAP) promotes AD neuropathology by exacerbating neuroinflammation. To test this hypothesis, serum and hippocampal cytokines were quantified in male and female TgF344-AD rats and wildtype (WT) Fischer 344 littermates exposed to TRAP or filtered air (FA) from 1 to 15 months of age. Luminex™ rat 23-cytokine panel assays were used to measure the levels of hippocampal and serum cytokines in 3-, 6-, 10-, and 15-month-old rats (corresponding to 2, 5, 9, and 14 months of exposure, respectively). Age had a pronounced effect on both serum and hippocampal cytokines; however, age-related changes in hippocampus were not mirrored in the serum and vice versa. Age-related changes in serum cytokine levels were not influenced by sex, genotype, or TRAP exposure. However, in the hippocampus, in 3-month-old TgF344-AD and WT animals, TRAP increased IL-1ß in females while increasing TNF ɑin males. In 6-month-old animals, TRAP increased hippocampal levels of M-CSF in TgF344-AD and WT females but had no significant effect in males. At 10 and 15 months of age, there were minimal effects of TRAP, genotype or sex on hippocampal cytokines. These observations demonstrate that TRAP triggers an early inflammatory response in the hippocampus that differs with sex and age and is not reflected in the serum cytokine profile. The relationship of TRAP effects on cytokines to disease progression remains to be determined.

To meet the demand for identifying and controlling toxic air contaminants in environmental justice communities, we have recently developed a cost-effective spark-induced breakdown spectroscopy (SIBS) instrument for detecting and quantifying toxic metal air pollutants. We characterized the detection limit and linearity of this SIBS instrument by analyzing nebulized elemental standard solutions. The experimental parameters affecting SIBS performance were optimized, including the time delay to observation, the distance between electrodes, and the ablation voltage. The instrument successfully detected Cr, Cu, Mn, Fe, Zn, Co, and Ni, with limits of detection ranged from 0.05 μg m-3 to 0.81 μg m-3 at a flow rate of 15 l min-1 and a 30 min sampling duration. Similar to other investigations using ion breakdown spectroscopy, we did not observe strong emissions lines for As, Sb, Se, Hg, Pb, and Cd, which were likely due to spectral overlap, matrix effects, and the limited detection range of the optical components. Overall, SIBS is a promising technique for field measurements of toxic metals for environmental justice, industrial and urban applications.

Animal models are often used to assess the airborne transmissibility of various pathogens, which are typically assumed to be carried by expiratory droplets emitted directly from the respiratory tract of the infected animal. We recently established that influenza virus is also transmissible via "aerosolized fomites," micron-scale dust particulates released from virus-contaminated surfaces (Asadi et al. in Nat Commun 11(1):4062, 2020). Here we expand on this observation, by counting and characterizing the particles emitted from guinea pig cages using an Aerodynamic Particle Sizer (APS) and an Interferometric Mie Imaging (IMI) system. Of over 9000 airborne particles emitted from guinea pig cages and directly imaged with IMI, none had an interference pattern indicative of a liquid droplet. Separate measurements of the particle count using the APS indicate that particle concentrations spike upwards immediately following animal motion, then decay exponentially with a time constant commensurate with the air exchange rate in the cage. Taken together, the results presented here raise the possibility that a non-negligible fraction of airborne influenza transmission events between guinea pigs occurs via aerosolized fomites rather than respiratory droplets, though the relative frequencies of these two routes have yet to be definitively determined.

Wearing surgical masks or other similar face coverings can reduce the emission of expiratory particles produced via breathing, talking, coughing, or sneezing. Although it is well established that some fraction of the expiratory airflow leaks around the edges of the mask, it is unclear how these leakage airflows affect the overall efficiency with which masks block emission of expiratory aerosol particles. Here, we show experimentally that the aerosol particle concentrations in the leakage airflows around a surgical mask are reduced compared to no mask wearing, with the magnitude of reduction dependent on the direction of escape (out the top, the sides, or the bottom). Because the actual leakage flowrate in each direction is difficult to measure, we use a Monte Carlo approach to estimate flow-corrected particle emission rates for particles having diameters in the range 0.5-20 μm. in all orientations. From these, we derive a flow-weighted overall number-based particle removal efficiency for the mask. The overall mask efficiency, accounting both for air that passes through the mask and for leakage flows, is reduced compared to the through-mask filtration efficiency, from 93 to 70% for talking, but from only 94-90% for coughing. These results demonstrate that leakage flows due to imperfect sealing do decrease mask efficiencies for reducing emission of expiratory particles, but even with such leakage surgical masks provide substantial control.

BackgroundEpidemiological data link traffic-related air pollution (TRAP) to increased risk of Alzheimer's disease (AD). Preclinical data corroborating this association are largely from studies of male animals exposed acutely or subchronically to high levels of isolated fractions of TRAP. What remains unclear is whether chronic exposure to ambient TRAP modifies AD risk and the influence of sex on this interaction.ObjectivesThis study sought to assess effects of chronic exposure to ambient TRAP on the time to onset and severity of AD phenotypes in a preclinical model and to determine whether sex or genetic susceptibility influences outcomes.MethodsMale and female TgF344-AD rats that express human AD risk genes and wildtype littermates were housed in a vivarium adjacent to a heavily trafficked tunnel in Northern California and exposed for up to 14 months to filtered air (FA) or TRAP drawn from the tunnel and delivered to animals unchanged in real time. Refractive particles in the brain and AD phenotypes were quantified in 3-, 6-, 10-, and 15-month-old animals using hyperspectral imaging, behavioral testing, and neuropathologic measures.ResultsParticulate matter (PM) concentrations in TRAP exposure chambers fluctuated with traffic flow but remained below 24-h PM with aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5) U.S. National Ambient Air Quality Standards limits. Ultrafine PM was a predominant component of TRAP. Nano-sized refractive particles were detected in the hippocampus of TRAP animals. TRAP-exposed animals had more amyloid plaque deposition, higher hyperphosphorylated tau levels, more neuronal cell loss, and greater cognitive deficits in an age-, genotype-, and sex-dependent manner. TRAP-exposed animals also had more microglial cell activation, but not astrogliosis.DiscussionThese data demonstrate that chronic exposure to ambient TRAP promoted AD phenotypes in wildtype and genetically susceptible rats. TRAP effects varied according to age, sex, and genotype, suggesting that AD progression depends on complex interactions between environment and genetics. These findings suggest current PM2.5 regulations are insufficient to protect the aging brain. https://doi.org/10.1289/EHP8905.

BackgroundTraffic-related air pollution (TRAP) is made up of complex mixtures of particulate matter, gases and volatile compounds. However, the effects of TRAP on the cardiopulmonary system in most animal studies have been tested using acute exposure to singular pollutants. The cardiopulmonary effects and molecular mechanisms in animals that are chronically exposed to unmodified air pollution as a whole have yet to be studied. Additionally, sex-dependent toxicity of TRAP exposure has rarely been evaluated.ObjectivesThis study sought to assess the cardiopulmonary effect of chronic exposure to unmodified, real-world TRAP in both female and male rats.MethodsFour-week-old male and female rats were exposed to TRAP or filtered air for 14 months in a novel facility drawing air from a major freeway tunnel system in Northern California. Inflammation and oxidative stress markers were examined in the lung, heart, spleen, and plasma, and TRAP deposits were quantified in the lungs of both male and female rats.ResultsElemental analysis showed higher levels of eight elements in the female lungs and one element in the male lungs. Expression of genes related to fibrosis, aging, oxidative stress, and inflammation were higher in the rat hearts exposed to TRAP, with female rats being more susceptible than males. Enhanced collagen accumulation was found only in the TRAP-exposed female hearts. Plasma cytokine secretion was higher in both female and male rats, but inflammatory macrophages were higher only in TRAP-exposed male spleens.DiscussionOur results in rats suggest pathological consequences from chronic TRAP exposure, including sex differences indicating females may be more susceptible to TRAP-induced cardiac fibrosis. https://doi.org/10.1289/EHP7045.

The COVID-19 pandemic triggered a surge in demand for facemasks to protect against disease transmission. In response to shortages, many public health authorities have recommended homemade masks as acceptable alternatives to surgical masks and N95 respirators. Although mask wearing is intended, in part, to protect others from exhaled, virus-containing particles, few studies have examined particle emission by mask-wearers into the surrounding air. Here, we measured outward emissions of micron-scale aerosol particles by healthy humans performing various expiratory activities while wearing different types of medical-grade or homemade masks. Both surgical masks and unvented KN95 respirators, even without fit-testing, reduce the outward particle emission rates by 90% and 74% on average during speaking and coughing, respectively, compared to wearing no mask, corroborating their effectiveness at reducing outward emission. These masks similarly decreased the outward particle emission of a coughing superemitter, who for unclear reasons emitted up to two orders of magnitude more expiratory particles via coughing than average. In contrast, shedding of non-expiratory micron-scale particulates from friable cellulosic fibers in homemade cotton-fabric masks confounded explicit determination of their efficacy at reducing expiratory particle emission. Audio analysis of the speech and coughing intensity confirmed that people speak more loudly, but do not cough more loudly, when wearing a mask. Further work is needed to establish the efficacy of cloth masks at blocking expiratory particles for speech and coughing at varied intensity and to assess whether virus-contaminated fabrics can generate aerosolized fomites, but the results strongly corroborate the efficacy of medical-grade masks and highlight the importance of regular washing of homemade masks.

Influenza viruses are presumed, but not conclusively known, to spread among humans by several possible routes. We provide evidence of a mode of transmission seldom considered for influenza: airborne virus transport on microscopic particles called "aerosolized fomites." In the guinea pig model of influenza virus transmission, we show that the airborne particulates produced by infected animals are mainly non-respiratory in origin. Surprisingly, we find that an uninfected, virus-immune guinea pig whose body is contaminated with influenza virus can transmit the virus through the air to a susceptible partner in a separate cage. We further demonstrate that aerosolized fomites can be generated from inanimate objects, such as by manually rubbing a paper tissue contaminated with influenza virus. Our data suggest that aerosolized fomites may contribute to influenza virus transmission in animal models of human influenza, if not among humans themselves, with important but understudied implications for public health.

Epidemiological studies link traffic-related air pollution (TRAP) to increased risk for various neurodevelopmental disorders (NDDs); however, there are limited preclinical data demonstrating a causal relationship between TRAP and adverse neurodevelopmental outcomes. Moreover, much of the preclinical literature reports effects of concentrated ambient particles or diesel exhaust that do not recapitulate the complexity of real-world TRAP exposures. To assess the developmental neurotoxicity of more realistic TRAP exposures, we exposed male and female rats during gestation and early postnatal development to TRAP drawn directly from a traffic tunnel in Northern California and delivered to animals in real-time. We compared NDD-relevant neuropathological outcomes at postnatal days 51-55 in TRAP-exposed animals versus control subjects exposed to filtered air. As indicated by immunohistochemical analyses, TRAP significantly increased microglial infiltration in the CA1 hippocampus, but decreased astrogliosis in the dentate gyrus. TRAP exposure had no persistent effect on pro-inflammatory cytokine levels in the male or female brain, but did significantly elevate the anti-inflammatory cytokine IL-10 in females. In male rats, TRAP significantly increased hippocampal neurogenesis, while in females, TRAP increased granule cell layer width. TRAP had no effect on apoptosis in either sex. Magnetic resonance imaging revealed that TRAP-exposed females, but not males, also exhibited decreased lateral ventricular volume, which was correlated with increased granule cell layer width in the hippocampus in females. Collectively, these data indicate that exposure to real-world levels of TRAP during gestation and early postnatal development modulate neurodevelopment, corroborating epidemiological evidence of an association between TRAP exposure and increased risk of NDDs.

In 2019, Wexler showed that, by applying Raoult's law rigorously to aqueous solutions and properly accounting for hydration of solutes, equations can be derived that accurately describe solute and solvent activity over the full range of concentrations from infinitely dilute to pure solutes. One feature of this theory is that it also predicts the amount of water that is free and the amount that is bound to the solute. In 2004 and 2005, Choi and co-workers used an electrodynamic balance to measure (i) the concentration of a range of organic and electrolyte solutes as a function of water activity and (ii) the amount of free and bound water in these solutions using the fluorescence of pyranine as a probe. In the current work, we compare the predictions of Wexler's theory to the measurements of Choi. After the adjustments to the amount of free water obtained by these measurements, the predictions of Wexler's theory match the measurements of Choi. The potential reasons for the adjustments are discussed.

Previously, we demonstrated a strong correlation between the amplitude of human speech and the emission rate of micron-scale expiratory aerosol particles, which are believed to play a role in respiratory disease transmission. To further those findings, here we systematically investigate the effect of different 'phones' (the basic sound units of speech) on the emission of particles from the human respiratory tract during speech. We measured the respiratory particle emission rates of 56 healthy human volunteers voicing specific phones, both in isolation and in the context of a standard spoken text. We found that certain phones are associated with significantly higher particle production; for example, the vowel /i/ ("need," "sea") produces more particles than /ɑ/ ("saw," "hot") or /u/ ("blue," "mood"), while disyllabic words including voiced plosive consonants (e.g., /d/, /b/, /g/) yield more particles than words with voiceless fricatives (e.g., /s/, /h/, /f/). These trends for discrete phones and words were corroborated by the time-resolved particle emission rates as volunteers read aloud from a standard text passage that incorporates a broad range of the phones present in spoken English. Our measurements showed that particle emission rates were positively correlated with the vowel content of a phrase; conversely, particle emission decreased during phrases with a high fraction of voiceless fricatives. Our particle emission data is broadly consistent with prior measurements of the egressive airflow rate associated with the vocalization of various phones that differ in voicing and articulation. These results suggest that airborne transmission of respiratory pathogens via speech aerosol particles could be modulated by specific phonetic characteristics of the language spoken by a given human population, along with other, more frequently considered epidemiological variables.

The United States Environmental Protection Agency (US EPA) list of hazardous air pollutants (HAPs) includes toxic metal suspected or associated with development of cancer. Traditional techniques for detecting and quantifying toxic metals in the atmosphere are either not real time, hindering identification of sources, or limited by instrument costs. Spark emission spectroscopy is a promising and cost-effective technique that can be used for analyzing toxic metals in real time. Here, we have developed a cost-effective spark emission spectroscopy system to quantify the concentration of toxic metals targeted by the US EPA. Specifically, Cr, Cu, Ni, and Pb solutions were diluted and deposited on the ground electrode of the spark emission system. The least absolute shrinkage and selection operator (LASSO) was optimized and employed to detect useful features from the spark-generated plasma emissions. The optimized model was able to detect atomic emission lines along with other features to build a regression model that predicts the concentration of toxic metals from the observed spectra. The limits of detections (LODs) were estimated using the detected features and compared to the traditional single-feature approach. LASSO is capable of detecting highly sensitive features in the input spectrum; however, for some toxic metals the single-feature LOD marginally outperforms LASSO LOD. The combination of low-cost instruments with advanced machine learning techniques for data analysis could pave the path forward for data-driven solutions to costly measurements.

Raoult's law, published in 1887, is taught in chemistry and chemical engineering fields as a first approximation to the vapor pressure and activity of solutes and solvents in mixtures. In ideal solutions, it is exact but many solutions are known to have substantial deviations from Raoult's law as conventionally interpreted. In 1908, Callendar showed that water hydrated to the solute can explain some of the departures from Raoult's law in aqueous solution. Here, we show that by simply assuming equilibria between the free water in solution and its hydrated forms, Raoult's law and Callendar's extension are valid over the full range of concentrations, while also showing how water and solutes interact in solution. This model of solutions has importance in highly concentrated solutions common in atmosphere aerosols relevant to climate change and air quality, and in numerous industrial processes.

Wet cooling towers evaporate water to transfer waste heat to the environment. In the process, they also emit liquid water in the form of spray drift. These emissions dry in the atmosphere to form aerosol particles composed of impurities in the water. Emission factor guidance for cooling towers is provided by EPA AP42. Total emissions are a combination of spray drift and ambient aerosol passing through the tower. Net emissions take into account the scrubbing of ambient particles in the tower. We directly measured tower particulate emissions and ambient concentrations to determine the contribution of spray drift to tower emissions as well as scrubbing effect on ambient particles. Two companion papers describe the instrumentation and the spray drift measurements. Copyright © 2025 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Due to US regulations, concentrations of hygroscopic inorganic sulfate and nitrate have declined in recent years, leading to an increased importance of the hygroscopic nature of organic matter (OM). The hygroscopicity of OM is poorly characterized because only a fraction of the multitude of organic compounds in the atmosphere is readily measured, and there is limited information on their hygroscopic behaviors. Hygroscopicity of aerosol is traditionally measured using a humidified tandem differential mobility analyzer (HTDMA) or electrodynamic balance (EDB). EDB measures water uptake by a single particle. For ambient and chamber studies, HTDMA measurements provide water uptake and particle size information but not chemical composition. To fill this information gap, we developed a novel methodology to assess the water uptake by particles collected on Teflon filters. This method uses the same filter sample for both hygroscopicity measurements and chemical characterization, thereby providing an opportunity to link the measured hygroscopicity with ambient particle composition. To test the method, hygroscopic measurements were conducted in the laboratory for ammonium sulfate, sodium chloride, glucose, and malonic acid, which were collected on 25 mm Teflon filters using an aerosol generator and sampler. Constant-humidity solutions (CHSs), including potassium chloride, barium chloride dihydrate, and potassium sulfate, were employed in a saturated form to maintain the relative humidity (RH) at approximately 84 %, 90 %, and 97 % in small chambers. Our preliminary experiments revealed that, without the pouch, water uptake measurements were not feasible due to rapid water loss during weighing. Additionally, we observed some absorption by the aluminum pouch itself. To account for this, concurrent measurements were conducted for both the loaded and the blank filters at each RH level. Thus, the dry loaded and blank Teflon filters were placed in aluminum pouches with one side open and in RH-controlled chambers for more than 24 h. The wet loaded samples and wet blanks were then weighed using an ultramicrobalance to determine the water uptake by the respective compound and the blank Teflon filter. The net amount of water absorbed by each compound was calculated by subtracting the water uptake of the blank filter from that of the wet loaded filter. Hygroscopic parameters, including the water-to-solute (W / S) ratio, molality, mass fraction solute (mfs), and growth factors (GFs), were calculated from the measurements. The results obtained are consistent with those reported by the Extended Aerosol Inorganics Model (E-AIM) and previous studies utilizing HTDMA and EDB for these compounds, highlighting the accuracy of this new methodology. This new approach enables the hygroscopicity and chemical composition of individual filter samples to be assessed so that in complex mixtures, such as chamber and ambient samples, the total water uptake can be parsed between the inorganic and organic components of the aerosol. [ABSTRACT FROM AUTHOR]

Mechanistic hypotheses about airborne infectious disease transmission have traditionally emphasized the role of coughing and sneezing, which are dramatic expiratory events that yield both easily visible droplets and large quantities of particles too small to see by eye. Nonetheless, it has long been known that normal speech also yields large quantities of particles that are too small to see by eye, but are large enough to carry a variety of communicable respiratory pathogens. Here we show that the rate of particle emission during normal human speech is positively correlated with the loudness (amplitude) of vocalization, ranging from approximately 1 to 50 particles per second (0.06 to 3 particles per cm3) for low to high amplitudes, regardless of the language spoken (English, Spanish, Mandarin, or Arabic). Furthermore, a small fraction of individuals behaves as "speech superemitters," consistently releasing an order of magnitude more particles than their peers. Our data demonstrate that the phenomenon of speech superemission cannot be fully explained either by the phonic structures or the amplitude of the speech. These results suggest that other unknown physiological factors, varying dramatically among individuals, could affect the probability of respiratory infectious disease transmission, and also help explain the existence of superspreaders who are disproportionately responsible for outbreaks of airborne infectious disease.

Fourier transform infrared spectroscopy (FT-IR) has been used to predict elemental carbon (EC) on polytetrafluoroethylene (PTFE) filter samples from the United States Environmental Protection Agency's Chemical Speciation Network (CSN). This study provides a proof-of-principle demonstration of using multilevel modeling to determine thermal/optical reflectance (TOR) equivalent EC (a.k.a., FT-IR EC) on PTFE samples collected in the CSN. Initially, spectra from nine geographically disperse sites were pooled and calibrated directly to collocated TOR EC measurements. The FT-IR EC quantified in test samples was deemed substandard when judged against an earlier study, e.g., R2 = 0.760 and median absolute deviation (MAD) = 26.7%. Upon scrutinizing each sample's absolute prediction error and squared Mahalanobis distance, Elizabeth, NJ predictions were found to exhibit atypical systematic errors, motivating the development of a multilevel classification and calibration procedure. Atypical Elizabeth spectra were distinguished from the (typical) CSN spectra by training a partial least-square discriminant analysis. Predicting EC using calibrations dedicated to either atypical or typical samples produced a satisfactory improvement in overall performance (R2 = 0.886, MAD = 19.8%). Analysis of the atypical FT-IR spectra and select TOR thermal fractions suggested that Elizabeth samples contained elevated levels of diesel particulate matter as evidenced by the use of organic nitrogen functional groups for prediction, very low average OC/EC, and minimal charring during TOR speciation. FT-IR EC from the other eight sites was predominately determined by aliphatic C-H, C = C aromatic, and functional groups associated with oxidation. This study provides preliminary confirmation that FT-IR EC may be accurately determined from source-oriented calibrations under a combined classification and calibration methodology. Copyright © 2018 American Association for Aerosol Research.

The concentration of solute molecules at the surface of a liquid is a factor in heterogeneous reactions, surface tension, and Marangoni-effect-driven surface flows. Increasingly, X-ray photoelectron spectroscopy (XPS) has enabled surface concentrations to be measured. In prior work, we employed statistical mechanics to derive expressions for surface tension as a function of solute activity in a binary solution. Here we use a Gibbs relation to derive concomitant expressions for surface concentration. Surface tension data from the literature for five alcohols are used to identify parameters in the surface tension equation. These parameters are then used in the surface concentration equation to predict surface concentrations. Comparison of these predictions to those measured with XPS shows a factor of three difference between measured and predicted surface concentrations. Potential reasons for the discrepancy are discussed, including lack of surface-bulk equilibrium in the measurements.

Mammalian lungs are comprised of large numbers of tracheobronchial airways that transition from the trachea to alveoli. Studies as wide ranging as pollutant deposition and lung development rely on accurate characterization of these airways. Advancements in CT imaging and the value of computational approaches in eliminating the burden of manual measurement are providing increased efficiency in obtaining this geometric data. In this study, we compare an automated method to a manual one for the first six generations of three Balb/c mouse lungs. We find good agreement between manual and automated methods and that much of the disagreement can be attributed to method precision. Using the automated method, we then provide anatomical data for the entire tracheobronchial airway tree from three Balb/C mice. Anat Rec, 2017. © 2017 Wiley Periodicals, Inc. Anat Rec, 300:2046-2057, 2017. © 2017 Wiley Periodicals, Inc.

Among solid organs, the kidney's vascular network stands out, because each nephron has two distinct capillary structures in series and because tubuloglomerular feedback, one of the mechanisms responsible for blood flow autoregulation, is specific to renal tubules. Tubuloglomerular feedback and the myogenic mechanism, acting jointly, autoregulate single-nephron blood flow. Each generates a self-sustained periodic oscillation and an oscillating electrical signal that propagates upstream along arterioles. Similar electrical signals from other nephrons interact, allowing nephron synchronization. Experimental measurements show synchronization over fields of a few nephrons; simulations based on a simplified network structure that could obscure complex interactions predict more widespread synchronization. To permit more realistic simulations, we made a cast of blood vessels in a rat kidney, performed micro-computed tomography at 2.5-μm resolution, and recorded three-dimensional coordinates of arteries, afferent arterioles, and glomeruli. Nonterminal branches of arcuate arteries form treelike structures requiring two to six bifurcations to reach terminal branches at the tree tops. Terminal arterial structures were either paired branches at the tops of the arterial trees, from which 52.6% of all afferent arterioles originated, or unpaired arteries not at the tree tops, yielding the other 22.9%; the other 24.5% originated directly from nonterminal arteries. Afferent arterioles near the corticomedullary boundary were longer than those farther away, suggesting that juxtamedullary nephrons have longer afferent arterioles. The distance separating origins of pairs of afferent arterioles varied randomly. The results suggest an irregular-network tree structure with vascular nodes, where arteriolar activity and local blood pressure interact.

ObjectivesPositive pressure ventilation exposes the lung to mechanical stresses that can exacerbate injury. The exact mechanism of this pathologic process remains elusive. The goal of this study was to describe recruitment/derecruitment at acinar length scales over short-time frames and test the hypothesis that mechanical interdependence between neighboring lung units determines the spatial and temporal distributions of recruitment/derecruitment, using a computational model.DesignExperimental animal study.SettingInternational synchrotron radiation laboratory.SubjectsFour anesthetized rabbits, ventilated in pressure controlled mode.InterventionsThe lung was consecutively imaged at ~ 1.5-minute intervals using phase-contrast synchrotron imaging, at positive end-expiratory pressures of 12, 9, 6, 3, and 0 cm H2O before and after lavage and mechanical ventilation induced injury. The extent and spatial distribution of recruitment/derecruitment was analyzed by subtracting subsequent images. In a realistic lung structure, we implemented a mechanistic model in which each unit has individual pressures and speeds of opening and closing. Derecruited and recruited lung fractions (Fderecruited, Frecruited) were computed based on the comparison of the aerated volumes at successive time points.Measurements and main resultsAlternative recruitment/derecruitment occurred in neighboring alveoli over short-time scales in all tested positive end-expiratory pressure levels and despite stable pressure controlled mode. The computational model reproduced this behavior only when parenchymal interdependence between neighboring acini was accounted for. Simulations closely mimicked the experimental magnitude of Fderecruited and Frecruited when mechanical interdependence was included, while its exclusion gave Frecruited values of zero at positive end-expiratory pressure greater than or equal to 3 cm H2O.ConclusionsThese findings give further insight into the microscopic behavior of the injured lung and provide a means of testing protective-ventilation strategies to prevent recruitment/derecruitment and subsequent lung damage.

The Rotating Drum Impactor (RDI) is designed to collect samples of airborne particulate matter that are resolved by aerodynamic particle diameter as a function of time. The purpose of this study is to characterize the accuracy and precision of measurements for particulate matter less than 2.5 μm (PM2.5) from the latest generation of the RDI sampler for use in relatively low concentration environments. Nominal RDI size cuts were used to interpret the results; a laboratory calibration of the RDI was not undertaken. Airborne particulate matter was collected on the campus of the University of California at Davis during the winter and summer of 2013. Two RDI samplers operating with 1 h resolution, two IMPROVE samplers operating 21 h per day, and one MOUDI sampler operating 42 h every two days were deployed for both seasons to enable a comparison of co-located measurements. The RDI samples were scanned using synchrotron X-rays from the Advanced Light Source (ALS), Lawrence National Berkeley Laboratory, to obtain X-ray Fluorescence (XRF) spectra. IMPROVE and MOUDI samples were analyzed using Panalytical XRF instruments using the IMPROVE protocol, then analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) using an Agilent 7500i. Repeated measurements from the same samplers and analytical techniques were compared to elucidate precision; inter-comparisons between measurements made with different sampler and analytical technique combinations were used to indirectly evaluate accuracy. The IMPROVE XRF analysis technique gave similar repeated measurements for 78% of the elements present above stated Minimum Detection Limits (MDLs) in winter and 42% of elements above MDL in summer. The MOUDI XRF analysis technique gave similar repeated measurements for 33% and 37% of the elements above stated MDLs in winter and summer, respectively. The MOUDI, ICP-MS analysis technique was the most repeatable method tested, yielding similar repeated measurements for 62% and 91% of elements above stated MDLs in winter and summer, respectively. The RDI, XRF analysis technique was the least repeatable method tested, yielding similar repeated measurements for 35–40% and 5–20% of elements above stated MDLs in winter and summer, respectively. PM2.5 measurements from IMPROVE samplers were in better agreement with integrated size-resolved measurements made by MOUDI samplers than RDI samplers in the summer season, however with higher concentrations in the winter season both instruments performed with similar accuracy when using the XRF analysis method. MOUDI samples analyzed by ICP-MS had the best agreement overall with IMPROVE samples analyzed by ICP-MS. These results suggest that MDLs should be reassessed for all methods and a longer collection time should be considered under low concentration conditions.

Atmospheric particles (total suspended particles, TSPs) mass samples (288) were collected by high volume samplers at nine sampling locations in Faisalabad, Pakistan from May 2012 to April 2013. These TSP mass samples were subjected to gravimetric and quantitative chemical analyses for determining trace elements (Pb, Cd, Ni, Zn, Cu, Fe) using atomic absorption spectroscopy and water-soluble cations (Ca2+, Mg2+, Na+ and K+, NH4+) and anions (Cl−, SO42−, and NO3−) by ion chromatography. The average TSP mass and elemental concentrations at all locations were found to be highest during the dry and lowest during the wet season. The crustal elements Ca, Fe, Mg, and Na were the largest contributors to TSP mass while elements of anthropogenic origin Pb, Cd, Ni, Cu, and Zn had relatively lower concentrations and also showing a high spatial variation. The concentration of TSP and elements exhibited the maxima at the sampling locations characterized by intensive industrial and vehicular activities. The wind rose analysis and the UNMIX model applied to chemical speciation data both identified the same three primary sources of TSP: power plant/refinery, brick kilns, and roadways. The normalized dot product was successfully used to quantify the similarity between different source profiles extracted from UNMIX model. The coupling of UNMIX with wind direction analysis complemented each other and provided a complete assessment of source contributions and locations.

The influence of losses of organic vapors to chamber walls during secondary organic aerosol (SOA) formation experiments has recently been established. Here, the influence of such losses on simulated ambient SOA concentrations and properties is assessed in the University of California at Davis / California Institute of Technology (UCD/CIT) regional air quality model using the statistical oxidation model (SOM) for SOA. The SOM was fit to laboratory chamber data both with and without accounting for vapor wall losses following the approach of Zhang et al. (2014). Two vapor wall-loss scenarios are considered when fitting of SOM to chamber data to determine best-fit SOM parameters, one with "low" and one with "high" vapor wall-loss rates to approximately account for the current range of uncertainty in this process. Simulations were run using these different parameterizations (scenarios) for both the southern California/South Coast Air Basin (SoCAB) and the eastern United States (US). Accounting for vapor wall losses leads to substantial increases in the simulated SOA concentrations from volatile organic compounds (VOCs) in both domains, by factors of ∼2-5 for the low and ∼5-10 for the high scenarios. The magnitude of the increase scales approximately inversely with the absolute SOA concentration of the no loss scenario. In SoCAB, the predicted SOA fraction of total organic aerosol (OA) increases from ∼0.2 (no) to ∼0.5 (low) and to ∼0.7 (high), with the high vapor wall-loss simulations providing best general agreement with observations. In the eastern US, the SOA fraction is large in all cases but increases further when vapor wall losses are accounted for. The total OA/ΔCO ratio captures the influence of dilution on SOA concentrations. The simulated OA/ΔCO in SoCAB (specifically, at Riverside, CA) is found to increase substantially during the day only for the high vapor wall-loss scenario, which is consistent with observations and indicative of photochemical production of SOA. Simulated O:C atomic ratios for both SOA and for total OA increase when vapor wall losses are accounted for, while simulated H:C atomic ratios decrease. The agreement between simulations and observations of both the absolute values and the diurnal profile of the O:C and H:C atomic ratios for total OA was greatly improved when vapor wall-losses were accounted for. These results overall demonstrate that vapor wall losses in chambers have the potential to exert a large influence on simulated ambient SOA concentrations, and further suggest that accounting for such effects in models can explain a number of different observations and model-measurement discrepancies.

Quantum chemical calculations were employed to model the interactions of the [(NH4(+))4(HSO4(-))4] ammonium bisulfate cluster with one or more molecular products of monoterpene oxidation. A strong interaction was found between the bisulfate ion of this cluster and a carboxylic acid, aldehyde, or ketone functionality of the organic molecule. Free energies of adsorption for carboxylic acids were in the -70 to -73 kJ/mol range, while those for aldehydes and ketones were in the -46 to -50 kJ/mol range. These values suggest that a small ambient [(NH4(+))4(SO4(-))4]cluster is able to adsorb an oxygenated organic molecule. While adsorption of the first molecule is highly favorable, adsorption of subsequent molecules is less so, suggesting that sustained uptake of organic molecules does not occur, and thus is not a pathway for continuing growth of the cluster. This result is consistent with ambient measurements showing that particles below ∼1 nm grow slowly, while those above 1 nm grow at an increasing rate presumably due to a lower surface energy barrier enabling the uptake of organic molecules. This work provides insight into the molecular level interactions which affect sustained cluster growth by uptake of organic molecules.

The EPA regulates ambient particulate matter (PM) because substantial associations have been established between PM and health impacts. Presently, regulatory compliance involves broad control of PM emission sources based on mass concentration rather than chemical composition, although PM toxicity is likely to vary depending upon PM physicochemical properties. The overall objective of this study was to help inform source-specific PM emission control regulations. For the first time, source-oriented PM was collected from the atmosphere in Fresno, CA, onto 38 source/size substrates. Mice were exposed via oropharyngeal aspiration to equivalent mass doses [50 μg] of two size fractions: ultrafine (Dp < 0.17μm) and submicron fine (0.17 < Dp < 1 μm) during summer and winter seasons. At 24 hours post-exposure, cellular and biochemical indicators of pulmonary inflammation were evaluated in the bronchoalveolar lavage fluid. Significant inflammatory responses were elicited by vehicle, regional background, and cooking PM sources that were dependent on season and particle size. This is the first study of source-oriented toxicity of atmospheric PM and supports source-specific emissions control strategies.

The activities of solutes and solvents in solutions govern numerous physical phenomena in a wide range of practical applications. In prior work, we used statistical mechanics and multilayer adsorption isotherms to develop a transformative model for capturing thermodynamic properties of multicomponent aqueous solutions over the entire concentration range (Dutcher et al. J. Phys. Chem. 2011, 2012, 2013). That model needed only a few adsorption energy values to represent the solution thermodynamics of each solute. In the current work, we posit that the adsorption energies are due to dipole-dipole electrostatic forces in solute-solvent and solvent-solvent interactions. This hypothesis was tested in aqueous solutions on (a) 37 1:1 electrolytes, over a range of cation sizes, from H(+) to tetrabutylammonium, for common anions including Cl(-), Br(-), I(-), NO3(-), OH(-), ClO4(-), and (b) 20 water-soluble organic molecules including alcohols and polyols. For both electrolytes and organic solutions, the energies of adsorption can be calculated with the dipole moments of the solvent, molecular size of the solvent and solute, and the solvent-solvent and solvent-solute intermolecular bond lengths. Many of these physical properties are available in the literature, with the exception of the solute-solvent intermolecular bond lengths. For those, predictive correlations developed here enable estimation of solute and solvent solution activities for which there are little or no activity data.

Spatial and temporal variations in aerosol particulate matter (PM) were investigated for distribution over the four seasons of chemical constituents and particle size fractions in Faisalabad, Pakistan from June 2012 to April 2013. At nine sampling sites, four PM mass size fractions (total suspended particulates [TSP], PM10, PM4 and PM2.5) were monitored; simultaneously, TSP mass samples were collected on glass fber flters using a high volume air sampler. TSP samples (144) were subjected to quantitative chemical analyses for determining trace elements (Pb, Cd, Ni, Zn, Cu, Fe) using atomic absorption spectroscopy, and water-soluble cations (Ca2+, Mg2+, Na+, K+, NH4+) and anions (Cl–, SO42– and NO3–) by ion chromatography. The highest PM mass concentrations were observed at industrial sites, while they were somewhat lower in major road intersections and lowest in the remote background site. It was also observed that PM mass concentrations were about two to 20 times higher than the standard limits of the World Health Organization and the US Environmental Protection Agency. Coarse particles (TSP, PM10 and PM4) were found to be highest during the summer, while relatively fne particles (PM2.5) were higher during the winter period. Concentrations of all size fractions were lowest during the monsoon sampling period at all sites. Concentrations of different elements and water-soluble ions also followed the similar temporal pattern as PM mass concentrations. The crustal elements Ca, Fe, Mg and Na were the largest contributors to TSP mass while elements of anthropogenic origin (Pb, Cd, Ni, Cu and Zn) had relatively lower concentrations and also showed a high spatial variation. Among the anions, sulfate (SO42–) was the predominant species contributing to 50-60% of the total anion concentration. It was found that rainfall, wind speed and relative humidity were the most important meteorological factors affecting PM concentrations. The evaluation of data presented in this paper will serve as a basis for future regional modeling and source apportionment.

Ambient particulate matter (PM) originates from a range of sources and differs in composition with respect to season, time of day, and particle size. In this study, ambient PM samples in the ultrafine and submicrometer fine range were tested for the potential to exacerbate a murine model of allergic airway inflammation when exposure occurs solely during allergic sensitization, but not during subsequent allergen challenge. Temporally resolved and size-segregated PM samples were used to understand how summer or winter, day or night, and ambient ultrafine and submicrometer fine particle size influence PM's ability to exacerbate allergic inflammation. PM was collected in urban Fresno, CA. BALB/c mice were exposed to PM and house dust mite allergen (HDM) via intranasal aspiration on d 1, 3, and 5. HDM challenge occurred on d 12-14, with inflammation assessed 24 h following final challenge. While season or particle size did not predict allergic inflammation, daytime ultrafine and submicrometer fine particles significantly increased total cellular inflammation, specifically lymphocyte and eosinophil infiltration, compared to allergic controls. Further studies examined PM-mediated changes within the lung during the period where allergen sensitization occurred by measuring direct effects of PM on pulmonary oxidative stress and inflammation. Pulmonary levels of heme oxygenase-1 (HO-1), a biomarker of oxidative stress, but not cellular inflammation, demonstrated a remarkable correlation with the degree of allergic inflammation in animals sensitized to allergen and PM concomitantly, suggesting acute PM-mediated HO-1 levels may serve as a predictive indicator of a particle's ability to exacerbate allergic airway inflammation.

Particulate matter (PM) exposure contributes to respiratory diseases and cardiopulmonary mortality. PM toxicity is related to sources and composition, such as abundance of polycyclic aromatic hydrocarbons (PAHs). We exposed adult male BALB/c mice, via oropharyngeal aspiration, to a range of doses of PM2.5 collected during the winter in downtown Sacramento near a major freeway interchange (SacPM). Two preparation methods (spin-down and multi-solvent extraction) were tested to remove particles from collection filters. Three doses were analyzed 24 h after treatment for (1) leukocytes and total protein in bronchoalveolar lavage fluid (BALF), (2) airway-specific and whole lobe expression of PAH-sensitive genes (CYP1B1 and CYP1A1) and IL-1 b, (3) lung histology, and (4) platelet function. Both extraction methods stimulated biological responses, but the spin-down method was more robust at producing IL-1 b and CYP1B1 gene responses and the multi-solvent extraction induced whole lung CYP1A1. Neutrophils in the BALF were increased 5- to 10-fold at the mid and high dose for both preparations. Histopathology scores indicated dose-dependent responses and increased pathology associated with spin-down-derived PM exposure. In microdissected airways, spin-down PM increased CYP1B1 gene expression significantly, but multi-solvent extracted PM did not. Platelet responses to the physiological agonist thrombin were approximately twice as potent in the spin-down preparation as in the multi-solvent extract. We conclude (1) the method of filter extraction can influence the degree of biological response, (2) for SacPM the minimal effective dose is 27.5-50 µg based on neutrophil recruitment, and (3) P450s are upregulated differently in airways and lung parenchyma in response to PAH-containing PM.