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Air liquid interface (ALI) exposure systems are gaining interest, and studies suggest enhanced response of lung cells exposed to particles at ALI as compared to submerged exposure, although the results have been somewhat inconsistent. Previous studies have used monocultures and measured particle deposition using assumptions including consistent particle deposition, particle density, and shape. This study exposed co-cultures of A549 and differentiated THP-1 cells to flame-generated particles using three exposure methods: ALI, pseudo-ALI, and submerged. The dose at ALI was measured directly, reducing the need for assumptions about particle properties and deposition. For all exposure methods an enhanced pro-inflammatory response (TNFα) and Cytochrome P450 (CYP1A1) gene expression, compared to their corresponding negative controls, was observed. ALI exposure induced a significantly greater TNFα response compared to submerged exposure. The submerged exposures exhibited greater induction of CYP1A1 than other exposure methods, although not statistically significant. Some of the factors behind the observed difference in responses for the three exposure methods include differences in physicochemical properties of particles in suspending media, delivered dose, and potential contribution of gas-phase species to cellular response in ALI exposure. However, given the difficulty and expense of ALI exposures, submerged exposure may still provide relevant information for particulate exposures.

As the changing climate expands the extent of arid and semi-arid lands, the number of, severity of, and health effects associated with dust events are likely to increase. However, regulatory measurements capable of capturing dust (PM10, particulate matter smaller than 10 µm in diameter) are sparse, sparser than measurements of PM2.5 (PM smaller than 2.5 µm in diameter). Although low-cost sensors could supplement regulatory monitors, as numerous studies have shown for PM2.5 concentrations, most of these sensors are not effective at measuring PM10 despite claims by sensor manufacturers. This study focuses on the Salt Lake Valley, adjacent to the Great Salt Lake, which recently reached historic lows exposing 1865 km2 of dry lake bed. It evaluated the field performance of the Plantower PMS5003, a common low-cost PM sensor, and the Alphasense OPC-N3, a promising candidate for low-cost measurement of PM10, against a federal equivalent method (FEM, beta attenuation) and research measurements (GRIMM aerosol spectrometer model 1.109) at three different locations. During a month-long field study that included five dust events in the Salt Lake Valley with PM10 concentrations reaching 311 µg m−3, the OPC-N3 exhibited strong correlation with FEM PM10 measurements (R2 = 0.865, RMSE = 12.4 µg m−3) and GRIMM (R2 = 0.937, RMSE = 17.7 µg m−3). The PMS exhibited poor to moderate correlations (R2 < 0.49, RMSE = 33–45 µg m−3) with reference or research monitors and severely underestimated the PM10 concentrations (slope < 0.099) for PM10. We also evaluated a PM-ratio-based correction method to improve the estimated PM10 concentration from PMSs. After applying this method, PMS PM10 concentrations correlated reasonably well with FEM measurements (R2 > 0.63) and GRIMM measurements (R2 > 0.76), and the RMSE decreased to 15–25 µg m−3. Our results suggest that it may be possible to obtain better resolved spatial estimates of PM10 concentration using a combination of PMSs (often publicly available in communities) and measurements of PM2.5 and PM10, such as those provided by FEMs, research-grade instrumentation, or the OPC-N3.

Aerosolization of SARS-CoV-2 by COVID-19 patients can put healthcare workers and susceptible individuals at risk of infection. Air sampling for SARS-CoV-2 has been conducted in healthcare settings, but methods vary widely and there is need for improvement. The objective of this study was to evaluate the feasibility of using a high-volume filter sampler, BioCapture z720, to detect SARS-CoV-2 in COVID-19 patient rooms in a medical intensive care unit, a dedicated COVID-19 ward, and at nurses’ stations. In some locations, the BioSpot-VIVAS, known for high efficiency in the collection of virus-containing bioaerosols, was also operated. The samples were processed for SARS-CoV-2 RNA with multi-plex nested polymerase chain reaction. One of 28 samples collected with the high-volume filter sampler was positive for SARS-CoV-2; all 6 samples collected with BioSpot-VIVAS were negative for SARS-CoV-2. The high-volume filter sampler was more portable and less intrusive in patient rooms than the BioSpot-VIVAS, but limits of detection remain unknown for this device. This study will inform future work to evaluate the reliability of these types of instruments and inform best practices for their use in healthcare environments for SARS-CoV-2 air sampling.

Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical–meteorological interactions that drive high-pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in western U.S. basins. Approximately 120 people participated, representing 50 institutions and five countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological–chemical linkages outlined here, nor to validate complex processes within coupled atmosphere–chemistry models.

Background The coronavirus disease 2019 (COVID‐19) pandemic has highlighted safety concerns surrounding possible aerosol‐generating procedures, but comparative data on the smallest particles capable of transmitting this virus remain limited. We evaluated the effect of nasal endoscopy on aerosol concentration and the role of a high‐efficiency particulate air (HEPA) filter in reducing aerosol concentration. Methods Otolaryngology patients were prospectively enrolled in an outpatient, cross‐sectional study. Demographic information and clinic room characteristics were recorded. A scanning mobility particle sizer and GRIMM aerosol monitor measured aerosols 14.3 nm to 34 μm in diameter (i.e., particles smaller than those currently examined in the literature) during (1) nasal endoscopy (± debridement) and (2) no nasal endoscopy encounters. One‐way analysis of variance (ANOVA) and Student's t test were performed to compare aerosol concentrations and impact of HEPA filtration. Results Sixty‐two patients met inclusion criteria (25 nasal endoscopy without debridement; 18 nasal endoscopy with debridement; 19 no nasal endoscopy). There was no significant difference in age or gender across cohorts. Aerosol concentration in the nasal endoscopy cohort (± debridement) was not greater than the no nasal endoscopy cohort (p = 0.36; confidence interval [95% CI], −1.76 to 0.17 μg/m3; and p = 0.12; 95% CI, −0.11 to 2.14 μg/m3, respectively). Aerosol concentrations returned to baseline after 8.76 min without a HEPA filter versus 4.75 min with a HEPA filter (p = 0.001; 95% CI, 1.73–6.3 min). Conclusion Using advanced instrumentation and a comparative study design, aerosol concentration was shown to be no greater during nasal endoscopy versus no endoscopy encounters. HEPA filter utilization reduced aerosol concentrations significantly faster than no HEPA filter.

Cost-effectively detecting benzene, a human carcinogen, at occupationally and atmospherically relevant concentrations would benefit individuals at risk of exposure. This paper presents the development of a titania (TiO2) nanotube-based sensor array that has a high surface area, is highly sensitive, and operates at room temperature using simple, portable instrumentation. An n-type TiO2 nanotube was synthesized through electrochemical anodization in an electrolytic solution of ammonium fluoride-ethylene glycol and oxygen annealed at 500 °C for up to 8 hours. The nanotube sensor had a bandgap (Eg) of ~2.6 eV, and it was operated at a bias voltage of +1.5 V. The response of the sensor to benzene vapor was measured using an amperometric technique at room temperature, and when exposed to benzene, the sensor exhibited a decrease in current, as expected for an n-type metal oxide semiconductor. The sensor response was proportional to benzene concentration over a range of 100–400 ppb. A sensing mechanism based on Fermi level changes caused by band bending has been explained for this benzene sensor.

Atmospheric aging of combustion particles alters their chemical composition and morphology. Previous studies have reported differences in toxicological responses after exposure to fresh versus aged particles, with chemical composition being the prime suspect behind the differences. However, less is known about the contribution of morphological differences in atmospherically aged particles to toxicological responses, possibly due to the difficulty in resolving the two properties (composition and morphology) that change simultaneously. This study altered the shape of lab-generated combustion particles, without affecting the chemical composition, from fractal-like to a more compact spherical shape, using a water condensation-evaporation method. The two shapes were exposed to a co-culture of human airway epithelial (A549) and differentiated human monocyte (THP-1) cells at air-liquid interface (ALI) conditions. The particles with different shapes were deposited using an electrostatic field-based ALI chamber. For the same mass dose, both shapes were internalized by cells, induced a pro-inflammatory response (IL-8 and TNFα), and enhanced CYP1A1 gene expression compared to air controls. The more compact spherical particles (representative of atmospherically aged particles) induced more early apoptosis and release of TNFα compared to the more fractal-like particles. These results suggest a contribution of morphology to the increased toxicity of aged combustion-derived particles.

Airborne aerosol transmission, an established mechanism of SARS-CoV-2 spread, has been successfully mitigated in the health care setting through the adoption of universal masking. Upper airway endoscopy, however, requires direct access to the face, thereby potentially exposing the clinic environment to infectious particles. This study quantifies aerosol production during rigid nasal endoscopy (RNE) and RNE with debridement (RNED) as compared with intubation, a posited gold standard aerosol-generating procedure.Prospective cross-sectional study.Subspecialty single-center clinic and surgical study.Three aerosol detectors (NANOSCAN-3910, OPS-3330, and APS-3321) with a particle size sensitivity of 10 to 20,000 nm were utilized to detect particulate production during the clinical care of 209 patients undergoing RNE/RNED and 25 patients undergoing intubation.RNE and RNED produced statistically significant particles over baseline in 29.3% and 51.0% of subjects (Instrumentation of nasal airway produces airborne aerosols to a similar degree of those seen during intubation, independent of reactive patient behaviors such as cough or sneeze. These data suggest that an improved understanding is necessary of both the definition of an aerosol-generating procedure and the functional consequences of procedural aerosol generation in clinical settings.

The World Health Organization estimates that 4.3 million deaths globally in 2012 were attributable to household air pollution, of which particulate matter (PM) with a diameter of 2.5 µm or less (PM2.5) is a significant contributor. When integrated with a wireless network, low-cost PM measurements potentially provide personalized information on indoor concentrations in real time so that individuals can take action. The objectives of this study were to (1) deploy a network of research-grade instruments and low-cost sensors in a home environment and evaluate the performance, (2) characterize activities and conditions that increase PM concentrations, and (3) identify how these activities affect the PM levels in different rooms of a home. The wireless sensor network included low-cost PM sensors, a gateway, and a database for storing data. Based on the commercially available Dylos DC1100 Pro (Utah Modified Dylos Sensor) and Plantower PMS sensor (AirU), the low-cost sensors were compared to three research-grade instruments—the GRIMM, DustTrak, and MiniVol—in two households in Salt Lake City during summer and winter, with the results suggesting that the low-cost sensors agreed well with the DustTrak. Of the activities, frying food and spraying aerosol products generated the largest increase in PM, both in the room of the activity (the kitchen and bedroom, respectively) and the adjacent rooms. High outdoor PM concentrations during a cold air pool episode also caused indoor levels to rise. In addition, different PM sources triggered different sensor responses. Consequently, obtaining accurate estimates of the mass concentration in an indoor environment, with its wide variety of PM sources, is challenging. However, low-cost PM sensors can be incorporated into an indoor air-quality measurement network to help individuals manage their personal exposure.

Personal exposure to heightened levels of fine airborne particulate matter (PM) has been linked to numerous adverse health effects in sensitive groups. However, researchers investigating these correlations are struggling to find the spatio-temporal datasets that are sufficient for study. Current airborne PM monitoring solutions are highly accurate, but expensive. Therefore, they are not feasible candidates for spatially dense deployments, and cannot be used to analyze the effects of exposure to pollution microclimates. In this article, we present a low-cost pollution monitoring station that operates as a single node in a wireless network. Each node periodically collects airborne pollution and supporting meteorological data and uploads measurements to a central, open-source database. A total of 50 nodes were deployed across a large metropolitan area (roughly 100 km2) over a six-month campaign. The experimental results show good correlation ( $R^{2}=0.88$ ) between devices co-located with the federal equivalent methods, which have an accuracy traceable to the National Institute of Standards and Technology. By applying linear corrections derived from in situ field measurements to each PM sensor, we were able to demonstrate a $1.8\times $ decrease in root-mean-squared error over the raw measurements.

Short-term exposure to fine particulate matter (PM2.5) pollution is linked to numerous adverse health effects. Pollution episodes, such as wildfires, can lead to substantial increases in PM2.5 leve...

Air pollution causes more damage to health and economy than previously understood, contributing to approximately one in six deaths globally. However, pollution reduction policies remain controversial even when proven effective and cost negative, partially because of misunderstanding and growing mistrust in science. We used an expert assessment to bridge these research&ndash, policy divides in the State of Utah, USA, combining quantitative estimates from 23 local researchers and specialists on the human health and economic costs of air pollution. Experts estimated that air pollution in Utah causes 2480 to 8000 premature deaths annually (90% confidence interval) and decreases the median life expectancy by 1.1 to 3.6 years. Economic costs of air pollution in Utah totaled $0.75 to $3.3 billion annually, up to 1.7% of the state&rsquo, s gross domestic product. Though these results were generally in line with available estimates from downscaled national studies, they were met with surprise in the state legislature, where there had been an almost complete absence of quantitative health and economic cost estimates. We discuss the legislative and personal responses of Utah policy makers to these results and present a framework for increasing the assimilation of data into decision making via regional expert assessment. In conclusion, combining quantitative assessments from local experts is a responsive and cost-effective tool to increase trust and information uptake during time-sensitive policy windows.

In vitro studies are the first step toward understanding the biological effects of particulate matter. As a more realistic exposure strategy than submerged culture approaches, air-liquid interface (ALI) in vitro exposure systems are gaining interest. One challenge with ALI systems is determining accurate particle mass deposition. Although a few commercially available ALI systems are equipped with online mass deposition monitoring, most studies use indirect methods to estimate mass doses. These different indirect methods may contribute to inconsistencies in the results from in vitro studies of aerosolized nanoparticles. This study explored the effectiveness of using a commercially available Quartz Crystal Microbalance (QCM) to estimate the real-time, particle-mass deposition inside an electrostatic, parallel-flow, ALI system. The QCM system required minor modifications, including custom-designed and fabricated headers. Three QCM systems were simultaneously placed in three of the six wells in the ALI exposure chamber to evaluate the uniformity of particle deposition. The measurements from fluorescein dosimetry and QCM revealed an uneven deposition between these six wells. The performance of the QCM system was also evaluated using two different methods. First, using fluorescein deposition in one well, depositions in three other wells were estimated, which was then compared to the actual QCM readings. Second, using the QCM measured deposition in one well, the deposition in three other wells was estimated and compared to deposition measured by fluorescein dosimetry. For both methods, the expected and actual deposition yields a linear fit with the slope ~1. This good fit suggests that QCM systems can be used to measure real-time mass deposition in an electrostatic ALI system.

Objectives To determine whether common otolaryngology procedures generate viable aerosolized virus through a murine cytomegalovirus (mCMV) model for infection. Study Design mCMV model of infection. Setting University of Utah laboratory. Methods Three-day-old BALB/c mice were inoculated with mCMV or saline. Five days later, each mouse underwent drilling, microdebrider, coblation, and electrocautery procedures. Particle size distribution and PM2.5 (particulate matter 100-fold increases in aerosol concentrations over background; only coblation and drilling produce aerosolized viral DNA. The high concentration of aerosols from coblation and electrocautery suggests the need for appropriate safeguards against particle exposure to health care workers. The presence of viral DNA from drilling and coblation procedures warrants the need for appropriate protection against droplet and aerosol exposure.

Ozone (O3) is a potent oxidant associated with adverse health effects. Low-cost O3 sensors, such as metal oxide (MO) sensors, can complement regulatory O3 measurements and enhance the spatiotemporal resolution of measurements. However, the quality of MO sensor data remains a challenge. The University of Utah has a network of low-cost air quality sensors (called AirU) that primarily measures PM2.5 concentrations around the Salt Lake City valley (Utah, U.S.). The AirU package also contains a low-cost MO sensor ($8) that measures oxidizing/reducing species. These MO sensors exhibited excellent laboratory response to O3 although they exhibited some intra-sensor variability. Field performance was evaluated by placing eight AirUs at two Division of Air Quality (DAQ) monitoring stations with O3 federal equivalence methods for one year to develop long-term multiple linear regression (MLR) and artificial neural network (ANN) calibration models to predict O3 concentrations. Six sensors served as train/test sets. The remaining two sensors served as a holdout set to evaluate the applicability of the new calibration models in predicting O3 concentrations for other sensors of the same type. A rigorous variable selection method was also performed by least absolute shrinkage and selection operator (LASSO), MLR and ANN models. The variable selection indicated that the AirU’s MO oxidizing species and temperature measurements and DAQ’s solar radiation measurements were the most important variables. The MLR calibration model exhibited moderate performance (R2 = 0.491), and the ANN exhibited good performance (R2 = 0.767) for the holdout set. We also evaluated the performance of the MLR and ANN models in predicting O3 for five months after the calibration period and the results showed moderate correlations (R2s of 0.427 and 0.567, respectively). These low-cost MO sensors combined with a long-term ANN calibration model can complement reference measurements to understand geospatial and temporal differences in O3 levels.

Particulate matter coming from the combustion of renewable diesel (RD), ultra-low sulfur diesel (ULSD) and a volumetric blend of 30% of RD with ULSD (RD30) were collected and physico-chemically characterized. Soot samples were generated in two flame burner types (non-premixed flame, NPF, and partially premixed flame, PPF) trying to simulate the diffusion and premix regimes found in diesel engines. The impact of both fuel nature and burner type was assessed on soot mass, particle size and morphology, particle nanostructure and surface functional groups. In general, although the results of HRTEM and SMPS suggested that the addition of RD reduced the average particle size and increased the concentration of ultra-fine particles, the mass emission of soot was drastically mitigated regardless of the burner used. The results also suggest that the changes in the chemical characteristics of the soot were slightly more sensitive than the changes in the internal nanostructure of the particles, since the graphitic character (as showed by Raman and infrared analysis) increased as the RD content increased, being stronger for the PPF system. Comparisons between engine soot and flame soot confirmed that the addition of RD into ULSD produced smaller and more carbonized particles. In fact, some engine results were located in between those obtained in PPF and NPF burners, suggesting that both combustion regimes are contributing to soot characteristics in engines. This consistency suggests that a first assessment of the impact of alternative fuels on the characteristics of particulate matter can be conducted through the basic approach offered by laboratory flames, thereby avoiding the costs associated with generating large quantities of fuel and the complexities of in-cylinder physical interactions and engine parameters.

Background Sarcoidosis is believed to represent a genetically primed, abnormal immune response to an antigen exposure or inflammatory trigger, with both genetic and environmental factors playing a role in disease onset and phenotypic expression. In a population of firefighters with post-World Trade Center (WTC) 9/11/2001 (9/11) sarcoidosis, we have a unique opportunity to describe the clinical course of incident sarcoidosis during the 15 years postexposure and, on average, 8 years following diagnosis. Methods Among the WTC-exposed cohort, 74 firefighters with post-9/11 sarcoidosis were identified through medical records review. A total of 59 were enrolled in follow-up studies. For each participant, the World Association of Sarcoidosis and Other Granulomatous Diseases organ assessment tool was used to categorize the sarcoidosis involvement of each organ system at time of diagnosis and at follow-up. Results The incidence of sarcoidosis post-9/11 was 25 per 100,000. Radiographic resolution of intrathoracic involvement occurred in 24 (45%) subjects. Lung function for nearly all subjects was within normal limits. Extrathoracic involvement increased, most prominently joints (15%) and cardiac (16%) involvement. There was no evidence of calcium dysmetabolism. Few subjects had ocular (5%) or skin (2%) involvement, and none had beryllium sensitization. Most (76%) subjects did not receive any treatment. Conclusions Extrathoracic disease was more prevalent in WTC-related sarcoidosis than reported for patients with sarcoidosis without WTC exposure or for other exposure-related granulomatous diseases (beryllium disease and hypersensitivity pneumonitis). Cardiac involvement would have been missed if evaluation stopped after ECG, 48-h recordings, and echocardiogram. Our results also support the need for advanced cardiac screening in asymptomatic patients with strenuous, stressful, public safety occupations, given the potential fatality of a missed diagnosis.

Underground coal thermal treatment (UCTT) is a promising concept that was recently proposed for extracting high-value hydrocarbon fuels from deep coal seams, which are economically unattractive for mining. UCTT is essentially an in situ pyrolysis process that converts underground coals into synthetic liquid and gaseous fuels, while leaving most of the carbon underground as a char matrix. The produced synthetic fuels have higher H/C ratios than coals. The remaining char matrix is an ideal reservoir for CO2 sequestration because pyrolysis significantly increases the surface area of the char. The UCTT concept is relatively new, and there is little research in this area. However, underground oil shale retorting, which is also an in-situ hydrocarbon fuels conversion process, shares key features with UCTT and has gained momentum in demonstration and commercial development. As such, there is a large body of literature available in this area. A review of the studies on underground oil shale retorting that are closely related to UCTT will shed light on the UCTT process. This paper presents a review of the recent literature on underground oil shale retorting that are most relevant to UCTT process. The review provides a background to the reader by comparing the properties of coal with oil shale, with an emphasis on the feasibility of applying oil shale retorting techniques to UCTT process. The review further discusses the coal and oil shale conversion issues and uses the knowledge of the latter as guidance for the development of UCTT. Published data on pyrolysis of large coal blocks at conditions relevant to UCTT process is scarce. Therefore, literature on conventional coal pyrolysis is reviewed for optimization of the UCTT process. Despite the abundant studies on pulverized coal pyrolysis, there are still many open questions on whether they can be directly applied to UCTT. A comparison of the unique environment of UCTT with conditions of conventional pulverized coal pyrolysis clearly shows there are knowledge gaps. Future research needs are then proposed to close these gaps.

The Salt Lake Valley experiences severe fine particulate matter pollution episodes in winter during persistent cold-air pools (PCAPs). We employ measurements throughout an entire winter from different elevations to examine the chemical and dynamical processes driving these episodes. Whereas primary pollutants such as NOx and CO were enhanced twofold during PCAPs, O3 concentrations were approximately threefold lower. Atmospheric composition varies strongly with altitude within a PCAP at night with lower NOx and higher oxidants (O3) and oxidized reactive nitrogen (N2O5) aloft. We present observations of N2O5 during PCAPs that provide evidence for its role in cold-pool nitrate formation. Our observations suggest that nighttime and early morning chemistry in the upper levels of a PCAP plays an important role in aerosol nitrate formation. Subsequent daytime mixing enhances surface PM2.5 by dispersing the aerosol throughout the PCAP. As pollutants accumulate and deplete oxidants, nitrate chemistry becomes less ...

Low-cost, light-scattering-based particulate matter (PM) sensors are becoming more widely available and are being increasingly deployed in ambient and indoor environments because of their low cost and ability to provide high spatial and temporal resolution PM information. Researchers have begun to evaluate some of these sensors under laboratory and environmental conditions. In this study, a low-cost, particulate matter sensor (Plantower PMS 1003/3003) used by a community air-quality network is evaluated in a controlled wind-tunnel environment and in the ambient environment during several winter-time, cold-pool events that are associated with high ambient levels of PM. In the wind-tunnel, the PMS sensor performance is compared to two research-grade, light-scattering instruments, and in the ambient tests, the sensor performance is compared to two federal equivalent (one tapered element oscillating microbalance and one beta attenuation monitor) and gravimetric federal reference methods (FEMs/FRMs) as well as one research-grade instrument (GRIMM). The PMS sensor response correlates well with research-grade instruments in the wind-tunnel tests, and its response is linear over the concentration range tested (200–850 μg/m3). In the ambient tests, this PM sensor correlates better with gravimetric methods than previous studies with correlation coefficients of 0.88. However additional measurements under a variety of ambient conditions are needed. Although the PMS sensor correlated as well as the research-grade instrument to the FRM/FEMs in ambient conditions, its response varies with particle properties to a much greater degree than the research-grade instrument. In addition, the PMS sensors overestimate ambient PM concentrations and begin to exhibit a non-linear response when PM2.5 concentrations exceed 40 μg/m3. These results have important implications for communicating results from low-cost sensor networks, and they highlight the importance of using an appropriate correction factor for the target environmental conditions if the user wants to compare the results to FEM/FRMs.

In vitro studies are a first step toward understanding the biological effects of combustion-derived particulate matter (cdPM). A vast majority of studies expose cells to cdPM suspensions, which requires a method to collect cdPM and suspend it in an aqueous media. The consequences of different particle collection methods on particle physiochemical properties and resulting biological responses are not fully understood. This study investigated the effect of two common approaches (collection on a filter and a cold plate) and one relatively new (direct bubbling in DI water) approach to particle collection. The three approaches yielded cdPM with differences in particle size distribution, surface area, composition, and oxidative potential. The directly bubbled sample retained the smallest sized particles and the bimodal distribution observed in the gas-phase. The bubbled sample contained ∼50% of its mass as dissolved species and lower molecular weight compounds, not found in the other two samples. These differences in the cdPM properties affected the biological responses in THP-1 cells. The bubbled sample showed greater oxidative potential and cellular reactive oxygen species. The scraped sample induced the greatest TNFα secretion. These findings have implications for in vitro studies of air pollution and for efforts to better understand the underlying mechanisms.

Distributed, low-cost sensor networks have become a widely used tool to aid in the interpolation of atmospheric measurements between regulatory grade monitoring stations, referred to as Golden Standards (GS). However, the quality of the data from these sensor networks can be questioned, especially in poorly correlated environments. Sensors can be individually calibrated in a laboratory environment before deployment of the network, but this approach is unfeasible for large networks. To overcome these shortcomings, we propose a novel online, autonomous approach to sensor calibration, by leveraging the ground truth measurements of the GS to calibrate neighboring nodes of the sensor network using a Recursive Least-Squares technique. Our algorithm percolates this calibration through the network such that every connected node will converge towards its ideal linear calibration. The algorithm outperforms a pre-deployment laboratory calibration and provides good tracking of quickly-changing environmental stimulus, which is known to change the inherent sensor calibration. Experimental results show a 45% improvement in estimated measurement error when compared to measurements corrected using a laboratory calibration.

The U.S Environmental Protection Agency’s National Air Toxics Trends Stations Network has been measuring the concentration of hazardous air pollutants (HAPs) including formaldehyde (HCHO) since 2003. Bountiful, Utah (USA) has served as one of the urban monitoring sites since the network was established. Starting in 2013, the mean concentration of HCHO measured in Bountiful, Utah exceeded the non-cancer risk threshold and the 1 in 1 million cancer risk threshold. In addition, the measured concentrations were more than double those found at surrounding locations in Utah. A Positive Matrix Factorization (PMF) analysis using PMF-EPA v5 was performed using historical data (2004–2017) to better understand the sources of formaldehyde in the region. The historical data set included samples that were collected every sixth day on a 24 h basis. Beginning in February 2019 an eight-week air sampling campaign was initiated to measure formaldehyde on a two-hour averaged basis. In addition, the measurements of O3, NO, NO2, benzene, toluene, ethylbenzene, and xylenes (BTEX) were also collected. Corresponding back-trajectory wind calculations for selected time periods were calculated to aid in the understanding of the effects of BTEX emission sources and formaldehyde formation. The results indicate that the principal formaldehyde sources are associated with biomass burning and the conversion of biogenic emissions into HCHO. Back-trajectory wind analysis of low (≤3 ppbv) and high (23.8–32.5 ppbv) HCHO cases show a clear dominance of high HCHO originating in trajectories that come from the southwest and pass over the area of the oil refineries and industrial sources in the north Salt Lake City area.

The use of low-cost air pollution sensors mounted on drones is an exciting new approach to conduct affordable and highly resolved air quality measurements. However, the air flow around a drone consists of complex, unsteady turbulent structures which interact directly with ambient particulate matter and gases. These interactions influence the transport of fine particulate matter (e.g. PM2.5) and, subsequently, its measurement using on-board PM sensors. In this work, we aim to quantify this effect by conducting wind tunnel and open-air experiments using a quadrotor drone and an array of low-cost sensors and research grade instruments. Sensors and instruments were placed around the drone to assess the effect of mixing, dilution, and particle segregation in the wake generated by the drone. Our results indicate little impact on the shape of the particle size distribution but significant differences (p 0.05) in PM2.5 concentration ranging from -70% to greater than 400% when comparing measurements before and after the drone is turned on. These effects varied greatly with sensor location and across experiments. In the wind tunnel, the sensor least affected was located far upstream from the drone with concentration differences less than 7%. The sensor far downstream from the drone as well as one of the sensors to the side of the drone also showed relatively small concentration differences (

The 2020 coronavirus pandemic and the following quarantine measures have led to significant changes in daily life worldwide. Preliminary research indicates that air quality has improved in many urban areas as a result of these measures. This study takes a neighborhood-scale approach to quantifying this change in pollution. Using data from a network of citizen-hosted, low-cost particulate matter (PM) sensors, called Air Quality & yoU (AQ&U), we obtained high-spatial resolution measurements compared to the relatively sparse state monitoring stations. We compared monthly average estimated PM2.5 concentrations from February 11 to May 11, 2019 at 71 unique locations in Salt Lake County, UT, USA with the same (71) sensors’ measurements during the same timeframe in 2020. A paired t-test showed significant reductions (71.1% and 21.3%) in estimated monthly PM2.5 concentrations from 2019 to 2020 for the periods from March 11-April 10 and April 11-May 10, respectively. The March time period corresponded to the most stringent COVID-19 related restrictions in this region. Significant decreases in PM2.5 were also reported by state monitoring sites during March (p

In this study, emissions of ozone precursors from oil and gas operations in Utah's Uinta Basin are predicted (with uncertainty estimates) from 2015-2019 using a Monte-Carlo model of (a) drilling and production activity, and (b) emission factors. Cross-validation tests against actual drilling and production data from 2010-2014 show that the model can accurately predict both types of activities, returning median results that are within 5% of actual values for drilling, 0.1% for oil production, and 4% for gas production. A variety of one-time (drilling) and ongoing (oil and gas production) emission factors for greenhouse gases, methane, and volatile organic compounds (VOCs) are applied to the predicted oil and gas operations. Based on the range of emission factor values reported in the literature, emissions from well completions are the most significant source of emissions, followed by gas transmission and production. We estimate that the annual average VOC emissions rate for the oil and gas industry over the 2010-2015 time period was 44.2E+06 (mean) ± 12.8E+06 (standard deviation) kg VOCs per year (with all applicable emissions reductions). On the same basis, over the 2015-2019 period annual average VOC emissions from oil and gas operations are expected to drop 45% to 24.2E+06 ± 3.43E+06 kg VOCs per year, due to decreases in drilling activity and tighter emission standards.This study improves upon previous methods for estimating emissions of ozone precursors from oil and gas operations in Utah's Uinta Basin by tracking one-time and ongoing emission events on a well-by-well basis. The proposed method has proven highly accurate at predicting drilling and production activity and includes uncertainty estimates to describe the range of potential emissions inventory outcomes. If similar input data are available in other oil and gas producing regions, then the method developed here could be applied to those regions as well.

We evaluate a novel energy strategy, underground coal thermal treatment (UCTT); it involves slowly pyrolyzing coal in-situ, transforming it to a synthetic gas stream containing hydrogen and low molecular-weight hydrocarbons, liquid fuel and char. This evaluation assesses the life-cycle energy and greenhouse gas (GHG) impacts of UCTT for all process stages. It is based on experimental results at two scales, a simple heat-transfer model and literature results. The results show that UCTT can produce a high-quality liquid product and a gas mixture. UCTT's GHG emissions are in the range of those reported for in situ processing of oil shale. Net energy returns (NERs) of 0.48–4.7 are in the range reported oil sands (2.8) and oil shale (0.48–2.6). Product yield at low temperatures, heater temperature, the number of heaters and the moisture content of the coal are key factors in determining the feasibility of the UCTT process.

An effective approach to the model VUQ process by means of direct collaboration between computationalist and experimental data analyst is proposed. An analysis of data from a laminar helium plume experiment provides a demonstration of the proposed collaboration process. Consistency analysis serves a central role in the collaboration. It takes the data and uncertainties from both analyst and computationalist and provides an objective and quantifiable measure of agreement between the two. Despite the simplicity of the laminar helium system and the computational model, certain phenomena brought to light in the collaboration process make it difficult to find quantitative agreement in the data. These phenomena include the unsteady behavior of air flow in an open room, and the presence of helium permeation to the region near the plume. Important sources of error in the simulation include uncertainty in the room temperature (295.15 to 305.15 K), uncertainty in the helium inlet velocity (0.1215 \(\frac {m}{s}\) to 0.1415 \(\frac {m}{s}\)), and uncertainty in local helium permeation (0 % to 3 % by mass.) The collaboration process allows for a better understanding of the phenomena affecting the plume and the relative sensitivies of the system to these phenomena.

We design and build EpiFi, a novel architecture for in-home sensor networks which allows epidemiologists to easily design and deploy exposure sensing systems in homes. We work collaboratively with pediatric asthma researchers to design multiple studies and deploy EpiFi in homes. Here, we report on experiences from two years of deployments in 15 homes, of two different types of studies, including many deployments continuously monitored over the past year. Based on lessons learned from these deployments and researchers, we develop a new mechanism for sensors to bootstrap their connectivity to a subject's home WiFi router and implement data reliability mechanisms to minimize loss in the network through a long-term deplovment.

Low-cost particulate matter (PM) air quality sensors are becoming widely available and are being increasingly deployed in ambient and home/workplace environments due to their low cost, compactness, and ability to provide more highly resolved spatiotemporal PM concentrations. However, the PM data from these sensors are often of questionable quality, and the sensors need to be characterized individually for the environmental conditions under which they will be making measurements. In this study, we designed and assessed a cost-effective (~$700) calibration chamber capable of continuously providing a uniform PM concentration simultaneously to multiple low-cost PM sensors and robust calibration relationships that are independent of sensor position. The chamber was designed and evaluated with a Computational Fluid Dynamics (CFD) model and a rigorous experimental protocol. We then used this new chamber to calibrate 242 Plantower PMS 3003 sensors from two production lots (Batches I and II) with two aerosol types: ammonium nitrate (for Batches I and II) and alumina oxide (for Batch I). Our CFD models and experiments demonstrated that the chamber is capable of providing uniform PM concentration to 8 PM sensors at once within 6% error and with excellent reliability (intraclass correlation coefficient > 0.771). The study identified two malfunctioning sensors and showed that the remaining sensors had high linear correlations with a DustTrak monitor that was calibrated for each aerosol type (R(2) >0.978). Finally, the results revealed statistically significant differences between the responses of Batches I and II sensors to the same aerosol (P-value

The low-cost and compact size of light-scattering-based particulate matter (PM) sensors provide an opportunity for improved spatiotemporally resolved PM measurements. However, these inexpensive sensors have limitations and need to be characterized under realistic conditions. This study evaluated two Plantower PMS (particulate matter sensor) 1003s and two PMS 5003s outdoors in Salt Lake City, Utah over 320 days (1/2016–2/2016 and 12/2016–10/2017) through multiple seasons and a variety of elevated PM2.5 events including wintertime cold-air pools (CAPs), fireworks, and wildfires. The PMS 1003/5003 sensors generally tracked PM2.5 concentrations compared to co-located reference air monitors (one tapered element oscillating microbalance, TEOM, and one gravimetric federal reference method, FRM). The different PMS sensor models and sets of the same sensor model exhibited some intra-sensor variability. During winter 2017, the two PMS 1003s consistently overestimated PM2.5 by a factor of 1.89 (TEOM PM2.5 0.87) and 24-h FRM measurements (R2 > 0.88) while in spring (March–June) and wildfire season (June–October) 2017, the correlations were poorer (R2 of 0.18–0.32 and 0.48–0.72, respectively). The PMS 1003s maintained high intra-sensor agreement after one year of deployment during the winter seasons, however, one PMS 1003 sensor exhibited a significant drift beginning in March 2017 and continued to deteriorate through the end of the study. Overall, this study demonstrated good correlations between the PMS sensors and reference monitors in the winter season, seasonal differences in sensor performance, some intra-sensor variability, and drift in one sensor. These types of factors should be considered when using measurements from a network of low-cost PM sensors.

The physicochemical properties of combustion particles that promote lung toxicity are not fully understood, hindered by the fact that combustion particles vary based on the fuel and combustion conditions. Real-world combustion-particle properties also continually change as new fuels are implemented, engines age, and engine technologies evolve. This work used laboratory-generated particles produced under controlled combustion conditions in an effort to understand the relationship between different particle properties and the activation of established toxicological outcomes in human lung cells (H441 and THP-1). Particles were generated from controlled combustion of two simple biofuel/diesel surrogates (methyl decanoate and dodecane/biofuel-blended diesel (BD), and butanol and dodecane/alcohol-blended diesel (AD)) and compared to a widely studied reference diesel (RD) particle (NIST SRM2975/RD). BD, AD, and RD particles exhibited differences in size, surface area, extractable chemical mass, and the content of individual polycyclic aromatic hydrocarbons (PAHs). Some of these differences were directly associated with different effects on biological responses. BD particles had the greatest surface area, amount of extractable material, and oxidizing potential. These particles and extracts induced cytochrome P450 1A1 and 1B1 enzyme mRNA in lung cells. AD particles and extracts had the greatest total PAH content and also caused CYP1A1 and 1B1 mRNA induction. The RD extract contained the highest relative concentration of 2-ring PAHs and stimulated the greatest level of interleukin-8 (IL-8) and tumor necrosis factor-alpha (TNFα) cytokine secretion. Finally, AD and RD were more potent activators of TRPA1 than BD, and while neither the TRPA1 antagonist HC-030031 nor the antioxidant N-acetylcysteine (NAC) affected CYP1A1 or 1B1 mRNA induction, both inhibitors reduced IL-8 secretion and mRNA induction. These results highlight that differences in fuel and combustion conditions affect the physicochemical properties of particles, and these differences, in turn, affect commonly studied biological/toxicological responses.

The transportation fuel sector is under pressure to reduce its greenhouse gas (GHG) emissions as a result of low-carbon fuel standards (LCFSs), which have been passed by the State of California and the European Union. These standards will be particularly challenging for producers of oil sands, heavy oil, and other unconventional resources. Oxyfiring with CO 2 capture is a promising technology for reducing CO 2 emissions from the transportation fuel sector, but it requires a significant amount of energy to generate oxygen. This study examines the potential for oxyfiring to reduce life-cycle GHG emissions from transportation fuels derived from in situ and ex situ oil shale and ex situ oil sands in the Uinta Basin of Utah. It also examines the effect of oxyfiring with CO 2 capture on the net energy return (NER). The evaluation focuses on the fuel's life-cycle GHG emissions, and it includes resource extraction, upgrading, transportation and refining. The results suggest that oxyfiring could help some unconventional sources of crude oil, such as ex situ production of oil sands and oil shale, meet a LCFS. However, oxyfiring with CO 2 capture reduces NER.

Researchers studying the biological effects of combustion particles typically rely on suspending particles in de-ionized (DI) water, buffer, and/or media prior to in vitro or in vivo experiments. However, the hydrophobic nature of combustion particles makes it difficult to obtain well-suspended, evenly dispersed mixtures, which also makes it difficult to obtain equivalent dosing and endpoint comparisons. This study explored the use of a quartz crystal microbalance (QCM) to measure the mass concentration of combustion particle suspensions. It compared the QCM mass concentration to that estimated by placing a known mass of combustion particles in DI water. It also evaluated the effect of drop volume and combustion particle type on QCM measurements. The results showed that QCM is a promising direct method for measuring suspended combustion particle mass concentrations, and it is particularly effective for quantifying concentrations of difficult-to-suspend particles and for combustion particles placed in polystyrene containers, which can lead to substantial particle losses.

A workshop on Combustion Related to Sustainable Energy was held in Hangzhou, China on March 10–12, 2014. The workshop was jointly sponsored by the U.S. National Science Foundation (NSF) and by the ...

The purpose of the research reported here is to explore how minor coal composition changes can affect oxy-coal flame ignition. Whereas previous work focused on the stability of coaxial turbulent diffusion flames for a single coal, we explore here how two coals of similar rank, fired under aerodynamically identical input conditions, may show very different flame stability characteristics. Since oxy-coal combustion allows oxygen contents in primary and secondary oxidant streams to be varied, flame stability characteristics were determined here by effects of partial pressure of oxygen (PO2) in the primary stream (with differing preheat temperatures in the secondary stream) and effects of PO2 in the secondary stream (with zero O2 in the primary stream), on the flame stand-off distance. The two coals investigated were a Utah Skyline bituminous coal and an Illinois #6 bituminous coal. Flame stability was quantified by probability density functions (PDF) of the flame stand-off distance, which were determined usi...