Mountain Scholar :: Browsing by Author "Volckens, John, committee member"

Browsing by Author "Volckens, John, committee member"

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Open Access
A direct-reading particle sizer (DRPS) with elemental composition analysis
(Colorado State University. Libraries, 2023) Sipich, James Robert, author; Yalin, Azer P., advisor; Volckens, John, committee member; L'Orange, Christian, committee member; Carter, Ellison, committee member
There is a lack of aerosol measurement technology capable of quantifying, in real-time, the size, concentration, and composition of large inhalable particles with an aerodynamic diameter larger than 20 µm. Aerosols of this size penetrate the upper respiratory system upon inhalation and present surface contamination hazards upon settling. The ability to obtain information on the composition of airborne particles is necessary to identify and control risks from exposure to potentially toxic materials, especially in the workplace. The objective of this work was to validate the performance of a prototype Direct-Reading Particle Sizer (DRPS) that counts and sizes particles via time-of-flight light scattering and determines single-particle elemental composition via Laser-Induced Breakdown Spectroscopy (LIBS). Counting, sizing, and spectral measurement efficiency were evaluated using test aerosols of multiple materials with diameters between 25 and 125 µm. Particle sizing results showed good agreement with optical microscopy images. The relationship between the median aerodynamic diameters measured by the DRPS time-of-flight and optical microscopy was linear (Deming regression slope of 0.998) and strongly correlated (r2 > 0.999). The mean absolute difference between the median aerodynamic diameters measured by the instrument by time-of-flight and microscopy over all 8 test aerosol types was 0.9 µm with a mean difference in interquartile range of 1.9 µm. The prototype sensor uses an optical triggering system and pulsed Nd:YAG laser to generate a microplasma and ablate falling particles. Particle composition is determined based on collected emission spectra using a real-time material classification algorithm. The accuracy of the composition determinations was validated with a set of 1480 experimental spectra from four different aerosol test materials. We have studied the effects of varying detection thresholds and find operating conditions with good agreement to truth values (F1 score ≥ 0.9). Details of the analysis method, including subtracting the spectral contribution from the air plasma, are discussed. The time-of-flight aerodynamic diameter measurement and LIBS elemental analysis capabilities demonstrated by the DRPS provide a system capable of both counting, sizing, and identifying the composition of large inhalable particles.
Open Access
A fine resolution CDF simulation approach for biomass cook stove development
(Colorado State University. Libraries, 2011) Miller-Lionberg, Daniel David, author; Willson, Bryan, advisor; DeFoort, Morgan, committee member; Sakurai, Hiroshi, committee member; Volckens, John, committee member
More than half of the world's population meets cooking and heating needs through small-scale biomass combustion. Emissions from these combustion processes are a major health hazard and air pollution concern. Simple improvements over traditional cooking fires have been shown to increase combustion and heat transfer efficiency while reducing physically harmful gaseous and particulate matter (PM) emissions. Over approximately 30 years of modern stove development history, designs have largely been based on empirical guidelines, and attempts at improvements have been made through an iterative, trial-and-error approach. Feedback in this design process is typically attained through bulk measurements made during experimental testing of prototypes. While important for assessing the performance of a stove, such testing offers no information on the fine spatial or temporal scales of phenomena within the stove, leaving it a "black box" in the view of the designer. Without higher resolution information, the rate and ultimate level of design improvement may be limited. In response, a computational fluid dynamic (CFD) simulation of a common, production cook stove is conducted using ANSYS FLUENT 13.0 software. Aspects critical to achieving high spatial and temporal resolution flow and temperature field results are included, enabled by necessary simplifications to less important elements. A model for the steady, time-averaged drying and pyrolysis of wood stick fuel is used in conjunction with a consideration for the simultaneous oxidation of the resulting char, to generate gas-phase fuel boundary conditions for the simulation. Fine spatial and temporal resolution are simultaneously possible in an unsteady formulation with the use of the simplified fuel condition, reduced-mass solid boundaries, and abbreviated runtimes. Employment of a large eddy simulation (LES) turbulence model is proposed as necessary to realistically consider the larger scales of gas mixing. Combustion heat release is approximated by reactions dictated by a mixture fraction formulation, assuming equilibrium conditions in a non-adiabatic system, affected by turbulent fluctuations through a probability density function (PDF). Sensitivity studies are conducted on grid parameters, boundary condition assumptions, and the duration of simulation runtime necessary to achieve result significance. A model for particulate emission formation is secondarily explored. A thermocouple-instrumented stove is used in an experiment to generate internal gas temperature profiles for the validation of the CFD simulation through comparable results. Likewise, a heat-exchanger integrated into a cooking pot is employed with the instrumented stove to measure short time-scale heat transfer values that are compared to the CFD simulation results, as well as to benchmark test data from the production stove. Recommendations for future efforts in stove simulation are made.
Open Access
An observational and theoretical investigation of the evolution of biomass burning aerosol size distributions
(Colorado State University. Libraries, 2015) Sakamoto, Kimiko M., author; Pierce, Jeffrey, advisor; Kreidenweis, Sonia, committee member; Volckens, John, committee member
Biomass-burning aerosols contribute to aerosol radiative forcing on the climate system. The magnitude of this effect is partially determined by aerosol size distributions, which are functions of source fire characteristics (e.g. fuel type, MCE) and in-plume microphysical processing (occurring on a GCM sub-grid scale). The uncertainties in biomass-burning emission number size-distributions in climate model inventories lead to uncertainties in the CCN concentrations and forcing estimates derived from these models. This emphasizes the need for observational and modelling studies to better represent effective biomass-burning size-distributions in larger-gridbox models. The BORTAS-B measurement campaign was designed to sample boreal biomass-burning outflow over Eastern Canada in the summer of 2011. Using these BORTAS-B data, we implement plume criteria to isolate the characteristic size-distribution of aged biomass-burning emissions (aged ~ 1 - 2 days) from boreal wildfires in Northwestern Ontario. The composite median size-distribution yields a single dominant accumulation mode with Dpm = 230 nm (number-median diameter), σ = 1.5, which are comparable to literature values of other aged plumes of a similar type. The organic aerosol enhancement ratios (ΔOA/ΔCO) along the path of Flight b622 show values of 0.05-0.18 μg m⁻³ ppbv⁻¹ with no significant trend with distance from the source. This lack of enhancement ratio increase/decrease with distance suggests no detectable net OA production/evaporation within the aged plume over the sampling period. A Lagrangian microphysical model was used to determine an estimate of the freshly emitted size distribution and flux corresponding to the BORTAS-B aged size-distributions. The model was restricted to coagulation and dilution processes only based on the insignificant net OA production/evaporation derived from the ΔOA/ΔCO enhancement ratios. We estimate that the fresh-plume median diameter was in the range of 59-94 nm with modal widths in the range of 1.7-2.8 (the ranges are due to uncertainty in the entrainment rate). Thus, the size of the freshly emitted particles is relatively unconstrained due to the uncertainties in the plume dilution rates. Expanding on the fresh-plume coagulational modelling of the BORTAS-B plumes, a coagulation-only parameterization for effective biomass-burning size-distributions was developed using the SAM-TOMAS plume model and a gaussian emulator. Under a range of biomass-burning conditions, the SAM-TOMAS simulations showed increasing Dpm and decreasing σ (converging to 1.2) with distance from the emission source. Final Dpm also shows a strong dependence on dM/dx (Mass flux x Fire area/vg), with larger values resulting in more rapid coagulation and faster dDpm/dt. The SAM-TOMAS simulations were used to train the Gaussian Emulation Machine for Sensitivity Analysis (GEM-SA) to build a Dpm and σ parameterization based on seven inputs. The seven inputs are: emission Dpm0, emission σ0, mass flux, fire area, mean boundary layer wind (vg), time, and plume mixing depth (dmixing). These inputs are estimated to account for 81% of the total variance in the final size distribution Dpm, and 87% of the total variance in the final σ. The parameterization performs very well against non-training modelled SAM-TOMAS size-di stributions in both final Dpm (slope = 0.92, R² = 0.83, NMBE=-0.06) and final σ (slope = 0.91, R² = 0.93, NMBE = 0.01). These final size distribution parameters are meant to be inserted as effective biomass-burning aerosol size-distributions (single lognormal mode) into larger-scale atmospheric models.
Open Access
Associations between air pollution emitted from cookstoves and central hemodynamics, arterial stiffness, and blood lipids in laboratory and field settings
(Colorado State University. Libraries, 2019) Walker, Ethan Sheppard, author; Peel, Jennifer, advisor; Clark, Maggie, advisor; Dinenno, Frank, committee member; Volckens, John, committee member; Wilson, Ander, committee member
To view the abstract, please see the full text of the document.
Open Access
Autonomous low-cost ozone sensors: development, calibration, and application to study exposure and spatial gradients
(Colorado State University. Libraries, 2022) Giardina, Dylan M., author; Jathar, Shantanu, advisor; Magzamen, Sheryl, committee member; Volckens, John, committee member; Bechara, Samuel, committee member
Ozone (O3), a criteria pollutant and atmospheric oxidant, is not routinely measured in rural and remote environments and hence exposure to ozone pollution in these regions remains poorly understood. In this work, we built, calibrated, and deployed five low-cost, autonomous ozone sensor systems (called MOOS) in Northern Colorado, a region that is non-compliant for O3 during the summertime. Each MOOS included the following components: (i) an Aeroqual SM50, a heated metal oxide ozone sensor, mounted inside a custom radiation shield, (ii) a power system that consisted of a 30 W solar panel, 108 Wh lithium-ion battery, and charge controller, (iii) a Particle Boron to acquire, process, and transmit data to the Cloud, and (iv) an environmental sensor to measure temperature, relative humidity, and pressure. In a three-week long collocated study, we found that all MOOS, calibrated using 48 hours of reference data, compared well against reference monitors with a measurement error between 4-6 parts per billion by volume (ppbv). Manufacturer- and laboratory-based calibrations over- and under-estimated ozone levels at higher and lower ozone mixing ratios, respectively. When deployed in Northern Colorado for an additional three weeks to measure O3 exposure and study O3 trends across an urban-rural gradient, we found that the MOOS, calibrated using data from the collocated study and calibrated using 48 hours of reference data in the field, demonstrated good sensor performance (RMSE of 3.98 - 8.80 ppbv and MBE of 0.22 - 3.82 ppbv). Compared to the collocated study, the field study resulted in larger measurement errors for all five MOOS (RMSE of 3.66 - 4.00 versus RMSE of 3.98 - 8.80). Furthermore, there was modest variability in the field performance across the different MOOS (RMSE < 5 ppbv) that could not be explained by environmental differences between the different sites (e.g., proximity of the MOOS to the reference monitor, land use type, temperature). We found that MOOS were able to capture 100% of non-compliant O3 days during the collocated study and between 25-87% of non-compliant O3 days during the field study depending on the calibration approach used. Furthermore, both reference monitors and MOOS deployed along the east-west corridor in Northern Colorado were able to capture the negative, west-east O3 gradients observed in previous aircraft and modeling studies. Overall, our study indicates that the MOOS shows promise as a low-cost O3 sensor that could be used to supplement routine ambient monitoring and characterize regional ozone pollution.
Open Access
Characteristics of atmospheric ice nucleating particles associated with biomass burning in the US: prescribed burns and wildfires
(Colorado State University. Libraries, 2013) McCluskey, Christina S., author; Kreidenweis, Sonia, advisor; DeMott, Paul, advisor; Pierce, Jeffrey, committee member; Volckens, John, committee member
Insufficient knowledge regarding the sources and number concentrations of atmospheric ice nucleating particles (INP) leads to large uncertainties in understanding the interaction of aerosols with cloud processes, such as cloud life time and precipitation rates. An increasingly important source of aerosol in the United States is biomass burning, particularly in the form of prescribed burns and wildfires in the southeastern and western U.S., respectively. Prior field and laboratory observations have suggested that biomass burning can be a source of INP. However, emissions from biomass burning are complex, varying with combustion efficiency, fuel type, plume age and dilution. Thus, this potentially important source of INP is poorly characterized. This study utilizes measurements of INP from a diverse set of biomass burning events to better understand INP associated with biomass burning in the U.S. Prescribed burns in Georgia and Colorado, two Colorado wildfires and two laboratory burns were monitored for INP number concentrations (nINP) using the Colorado State University continuous-flow diffusion chamber (CFDC) to activate INP in the condensation/immersion freezing nucleation mode. Additional measurements included total particle number concentrations, number concentrations of particles with diameters larger than 500 nm, aerosol mass concentrations, carbon monoxide concentrations and chemically-speciated bulk aerosol filter samples. Additionally, activated INP were collected onto TEM grids downstream of the CFDC, isolating INP for single particle chemical and morphological analyses. These fires varied by fuel type, including wiregrass, longleaf pine and ponderosa pine, and also varied by combustion efficiency, ranging from highly flaming to a mixture of flaming and smoldering. Additionally, plume histories were different between the fires including aged plumes from the wildfires and freshly emitted smoke from the prescribed and laboratory burns. The relationship between nINP and total particle number concentrations, evident within prescribed burning plumes, was degraded within aged smoke plumes from the wildfires, limiting the utility of this relationship for comparing laboratory and field data. Larger particles, represented by n500nm, are less vulnerable to plume processing and have previously been evaluated for their relation to nINP. Our measurements indicated that for a given n500nm, nINP associated with the wildfires were nearly an order of magnitude higher than nINP found in prescribed fire emissions. That is, nINP represented a much larger fraction of n500nm in wildfires as compared with prescribed fires. Further, an existing parameterization for "global" nINP that relates INP abundance to n500nm largely under-predicted and over-predicted nINP emitted from wildfires and prescribed burns, respectively. Reasons for the differences between INP characteristics in these emissions were explored, including variations in combustion efficiency, fuel type, transport time and environmental conditions. Combustion efficiency and fuel type were eliminated as controlling factors by comparing samples with contrasting combustion efficiencies and fuel types. Transport time was eliminated because the expected impact would be to reduce n500nm, thus resulting in the opposite effect from the observed change. Bulk aerosol chemical composition analyses support the potential role of elevated soil dust particle concentrations during the fires, contributing to the population of INP, but the bulk analyses do not target INP composition directly. Predictions from the Naval Aerosol Analysis and Prediction System model further indicate elevated dust mass concentrations during the wildfire periods, suggesting impact of mineral dust from long-range transport (LRT). It is hypothesized that both hardwood burning and soil lofting are responsible for the elevated production of INP in the Colorado wildfires in addition to LRT of mineral dust. The chemical compositions of INP were probed directly via TEM imaging. Single particle analyses of residual INP showed that they comprised various C-containing particle types, but with a higher abundance of mineral and metal oxide containing INP in emissions from flaming phase combustion. Fractal soot was found as an INP type comprising up to 60% of collected INP in young smoke emissions from the Georgia prescribed burns. In a series of laboratory combustion experiments, the use of a new instrumental set up, pairing the CFDC with a single particle soot photometer, revealed up to a 60% decrease in active INP after the removal of refractory black carbon from smoke aerosol emitted from a highly flaming burn of wiregrass, supporting that soot particles serve as INP in fire emissions. The presence of soil minerals was clearly evident in TEM images of samples taken during the wildfires in addition to tarballs, carbon balls most commonly associated with aged smoke plumes. These results demonstrate that the ice nucleating particles observed in the wildfires were influenced by other factors not represented in the smoke emitted from the laboratory or prescribed burns. Finally, an INP parameterization was developed based on the temperature dependent relationship between nINP and n500nm, following methods used by previous studies. This parameterization is likely only representative of the Hewlett and High Park wildfires due to the apparent impact of non-biomass-burning aerosol. However, all wildfires are typically associated with vigorous localized convection and arid soils, required for the lofting of the soils and dusts similar to these wildfires. It will be useful to compare future wildfires in various regions to the proposed parameterization.
Open Access
Characterization and modification of carbon composite electrodes towards more affordable biosensing applications and integration into fluidic devices
(Colorado State University. Libraries, 2022) Clark, Kaylee M., author; Henry, Charles S., advisor; Van Orden, Alan, committee member; Prieto, Amy L., committee member; Volckens, John, committee member
Fast, accurate, and low-cost medical tests and platforms for biomolecule monitoring are essential to the diagnosis, management, and treatment of many diseases. Electrochemical detection allows for highly sensitive measurements with fast response times. Carbon composite electrodes are an attractive option for electrochemical detection due to their low cost, resistance to biological fouling, large electrochemical solvent windows, and ability to be patterned. However, they often suffer from poor electrocatalytic activity, inability to be molded, and need for complex modifications to effectively detect certain analytes. Combining electrochemistry with fluidics is attractive for a wide array of applications including multiplexing, automation, and high-throughput screening. However, fabrication of electrochemical fluidic devices with integrated carbon electrodes remains a challenge. Thermoplastic electrodes (TPEs) are a new class of composite electrodes discussed in this dissertation that exhibit superior electrochemical properties to typical carbon composite electrodes and can be easily molded into intricate structures. Overall, this dissertation aims to improve carbon composite materials for biosensing applications and integration of electrochemical sensors into fluidic devices. Chapter 2 introduces polycaprolactone (PCL) as a new binder material for TPEs and focuses on the electrochemical characterization of the new material. The PCL-based TPEs have excellent electrochemical activity towards a wide range of analytes as well as high electrical conductivity. Chapter 2 also introduces a simple technique for integrating PCL and carbon composite electrodes into microfluidics. The presented electrode-integrated microfluidic devices are quickly fabricated with a laser cutter using PCL as a bonding layer. As a proof-of-concept application, water-in-oil droplets are electrochemically analyzed. Chapter 3 focuses on use of PCL-based TPEs for enzymatic sensors. The simple fabrication of TPEs also allows catalysts and enzymes to be mixed directly into the material to enhance detection. In Chapter 3, the TPE material is bulk-modified with cobalt phthalocyanine, an electrocatalyst, and glucose oxidase, resulting in a robust glucose sensor that demonstrates long-term current response stability. These sensors can be molded into intricate shapes and sanded for surface renewal (without requiring additional steps to maintain the modification), allowing the sensors to be continuously reused even if damaged or fouled. Chapter 4 investigates the properties of TPEs using two different binders – polycaprolactone (PCL) and polystyrene (PS) – with sanded and heat-pressed surface treatment. XPS and SEM analysis suggested that sanded TPEs have a higher density of graphitic edge planes and improved electrochemistry as a result. Electrochemical detection of O2 and H2O2, which are typically difficult to detect on carbon composites without complex modification, was demonstrated on sanded PS-based TPEs. Additionally, Chapter 4 introduces a new 3D-printed TPE sensor module that is reversibly sealed with magnets. A proof-of-concept sensor for detecting H2O2 in flow with the sensor module is presented. Chapter 5 presents a low-cost flow device, made of inexpensive polyethylene terephthalate (PET) and adhesive films, developed to detect SARS-CoV-2 nucleocapsid (N) protein. Upon addition of a sample in the device, reagents and washes are sequentially delivered to an integrated screen-printed carbon electrode for detection thus automating a full sandwich immunoassay with a single end-user step. The modified electrodes are sensitive and selective for COVID-19 N protein and stable for over seven weeks. The flow device was also successfully applied to detect nine different SARS-CoV-2 variants, including Omicron. In summary, this dissertation presents work to improve carbon composite electrodes, their modification, and integration into fluidic devices for applications as biosensors and beyond. The TPEs presented show improved electrochemical and physical properties, that allow for simple modifications. This work also demonstrates simple electrode integration strategies in several types of fluidic devices for easier and more sensitive detection of biologically relevant analytes. Moreover, the platforms established in this dissertation can be easily adapted for a wide variety of analytes and applications. This work provides materials, methods, and platforms to create more affordable biosensors for medical and other biological sensing.
Open Access
Characterization of gaseous and particulate emissions from combustion of algae based methyl ester biodiesel
(Colorado State University. Libraries, 2009) Fisher, Bethany, author; Marchese, Anthony John, 1967-, advisor; Olsen, Daniel B., committee member; Volckens, John, committee member
The advantages to using biodiesel in place of petroleum diesel are also accompanied by disadvantages. Biodiesel is usually made from crops that are also used to produce food. The land and water use impacts would be profound if current biodiesel feedstocks were used to displace a significant portion of current global petroleum diesel consumption. Oil-producing algae is a favorable alternative to the more common biodiesel feedstocks (soy, canola, etc.) because it does not compete with food sources, does not require arable land to grow and has the potential to produce significantly more oil per area per year than any other oil crops. However, the fatty acid composition of the oil produced by algal species currently under consideration for fuel production differs from that of the more common vegetable oils in that it often includes high quantities of long chain and highly unsaturated fatty acids. When transesterified into fatty acid methyl esters (FAME) biodiesel, the unique fatty acid composition could have a substantial impact on emissions such as Nitrogen Oxides (NOx) and particulate matter (PM). Accordingly, the goal of this study was to examine the effect of the chemical structure of algal methyl esters on pollutant emissions from a diesel engine operating on algae-based FAME biodiesel. Tests were performed on a 2.4 L, 39 kW John Deere 4024T, off-road diesel engine meeting USEPA Tier 2 emissions regulations. The engine was fitted with a unique, low-volume fuel system that enabled emissions tests to be conducted with small specialty fuel samples. Tests were performed on 9 different fuel blends at 2 different engine loading conditions. Exhaust gas measurements were made using a 5-gas emissions analysis system that includes chemiluminescence measurement of NOx, flame ionization detection of total hydrocarbons, paramagnetic detection of oxygen and non-dispersive infrared detection of CO and CO2. Particulate matter was characterized using an Aerosol Mass Spectrometer (AMS), which is capable of direct measurement of particle composition. The PM size distributions (between 10 to 1000 nm) were measured using a Sequential Mobility Particle Sizer. Total PM mass emissions were measured using gravimetric analysis of Teflon filters and the ratio of elemental carbon to organic was measured using thermo-optical analysis of quartz filters. Experiments were performed with ultra-low sulfur diesel, soy biodiesel (both pure biodiesel, B100, and a blend of 20% biodiesel and 80% diesel, B20), canola biodiesel (B20 and B100), and two synthetic algal methyl ester formulations (B20 and B100 for each). Combustion of algal methyl esters resulted in decreased NOx relative to both canola and soy biodiesel and ULSD, in contrast to previous research that examined the effect of fatty acid saturation and chain length on NOx emissions. A correlation was found between NOx emissions and premixed burn fraction, which provides an explanation for these results. Emissions of formaldehyde and organic PM were found to be slightly elevated with the two algal fuels in comparison with the traditional feedstocks. Particle size distribution, total PM mass, total hydrocarbons, CO and acetaldehyde emissions were similar between the different types of biodiesel.
Open Access
Climate and health impacts of particulate matter from residential combustion sources in developing countries
(Colorado State University. Libraries, 2018) Kodros, John K., author; Pierce, Jeffrey R., advisor; Volckens, John, committee member; Kreidenweis, Sonia, committee member; Ravishankara, A. R., committee member
Globally, close to 2.8 billion people lack access to clean cooking technology, while 1.8 billion people lack access to electricity altogether. As a means to generate energy for residential tasks, it is common in many developing countries to rely on combustion of solid fuels (wood, dung, charcoal, trash, etc.). Solid fuel use (SFU) can emit substantial amounts of fine particulate matter (PM2.5), often in or in close proximity to residences, creating concerns for human health and climate; however, large uncertainties exist in indoor and outdoor concentrations and properties, limiting our ability to estimate these climate and health impacts. This work explores the uncertainty space in estimates of premature mortality attributed to exposure to PM2.5 from residential SFU (e.g., cooking, heating, lighting) and makes the first estimates of health and radiative effects from combustion of domestic waste (i.e., trash burning). Next, we investigate key uncertain parameters (emission size distribution, black carbon mixing state, and size-resolved respiratory deposition) that drive uncertainties in health and radiative impacts from SFU, in order to improve model estimates of aerosol impacts from all sources. In many developing regions, combustion of solid fuels for cooking and heating is not the only aerosol source impacting air quality and climate. While uncontrolled combustion of domestic waste has been observed in many countries, this aerosol source is not generally included in many global emissions inventories. Using a global chemical-transport model, we estimate exposure to ambient PM2.5 from domestic-waste combustion to cause 270,000 (5th-95th percentile: 213,000 to 328,000) adult mortalities per year, most of which occur in developing countries. Regarding aerosol radiative effects, we estimate the globally averaged direct radiative effect (DRE) to range from -40 mW m-2 to +4 mW m-2 and the aerosol indirect effect (AIE) to range from -4 mW m-2 to -49 mW m-2. In some regions with significant waste combustion, such as India and China, the aerosol radiative effects exceed −0.4 W m−2.The sign and magnitude of the global-mean DRE is strongly sensitive to assumptions on how black carbon (BC) is mixed with scattering particles, while the AIE is strongly sensitive to the emission size distribution. To determine what factors dominate the uncertainty space in mortality estimates from SFU, we perform a variance-based sensitivity analysis on premature mortality attributed to the combined exposure to ambient and household PM2.5 from SFU. We find that uncertainty in the percent of the population using solid fuels for energy contributes the most to the uncertainty in mortality (53-56% of uncertainty across Asia and South America) with the concentration-response function the next largest contributor (40-50%). In the second half of this dissertation, we explore several key uncertainties in climate and health estimates of aerosol from residential sources in order to reduce overall model uncertainty of aerosol impacts from any source. To test the sensitivity of the AIE to treatment of aerosol size distributions in global models, we estimate the AIE due to anthropogenic emissions with prognostic sectional aerosol microphysics and compare this to the AIE calculated when the simulated aerosol mass of each species is remapped onto a prescribed size distribution. Simulations using the prognostic scheme yield a global mean anthropogenic AIE of −0.87 W m−2, while the simulations with the prescribed scheme predict −0.66 W m−2. These differences suggest that simulations with prescribed size‐distribution mapping are unable to capture regional and temporal variability in size‐resolved aerosol number and thus may lead to biases in estimates of the AIE.
Open Access
Comparative analysis of bacterial and fungal communities in two dairy parlors through the use of pyrosequencing, riboprinting, culture techniques, and microscopic analysis
(Colorado State University. Libraries, 2013) VanDyke-Gonnerman, Amanda L., author; Reynolds, Stephen J., advisor; Volckens, John, committee member; Ellis, Robert, committee member
The purpose of this study was to compare three different analysis techniques used to characterize and identify bacteria and fungi. Pyrosequencing, culture techniques, and riboprinting were compared for all of the bacterial samples and pyrosequencing; culture techniques; and microscopic analysis was used to compare the fungal samples. SKC BioSamplers were used to take area samples inside two modern dairy parlors from May 2012-January 2013. Four sampling sessions were completed at each dairy parlor. Four biosamplers ran side-by-side (two at a time) for 60 minutes at 12.5 l/min in addition to a lab and a field blank. A novel resuscitation buffer was used to collect and aid recovery of stressed bacteria and fungi. Three types of media were used to select for bacteria and fungi: tryptic soy agar (TSA) with a 5% sodium chloride addition for Gram-positive bacteria; Eosin methylene blue (EMB) for Gram-negative bacteria, and malt extract agar (MEA) with a chloramphenicol addition for fungi. Based on colony morphology, the five most commonly encountered bacteria from both TSA and EMB agar were subcultured and identified through riboprinting. Pyrosequencing was performed directly on the biosampler collection media. The culturable bacterial concentrations and the pyrosequencing bacterial concentrations were within the same order of magnitude, which was unexpected. The culturable bacterial concentrations, with averages of 7500 CFU/m3 and 500 CFU/m3 for TSA and EMB plates respectively, were higher than the concentrations found in previous studies which could be a result of the novel resuscitation buffer that was used as a collection media. Greater microbiome diversity was found through pyrosequencing analysis than the riboprinting analysis. The pyrosequencing data found many genera that include species that are pathogenic, but more work must be done to confirm if pathogenic species were found during sampling at these two dairy parlors. The riboprinting samples were identified on the species and strain level and found Escherichia coli O157:H7 a known pathogen as well as Pseudomonas aeruginosa, an opportunistic pathogen. The culturable fungi concentrations and the pyrosequencing concentrations were within the same order of magnitude, which was also unexpected. The pyrosequencing data had greater diversity than the microscopic analysis for the first two sets of samples that were sent for pyrosequencing. The second set of fungal samples that were sent for pyrosequencing came back as non-detect samples despite the growth of fungi on the agar. From the pyrosequencing data, there were many genera found that have pathogenic species, but more research needs to be conducted to determine the presence of the pathogenic species. There were no pathogenic fungal species found through the microscopic analysis.
Open Access
Contribution of biomass burning to carbonaceous aerosols in Mexico City during May 2013
(Colorado State University. Libraries, 2014) Tzompa Sosa, Zitely Asafay, author; Kreidenweis, Sonia M., advisor; Fischer, Emily, committee member; Sullivan, Amy, committee member; Volckens, John, committee member
The Mexico City Metropolitan Area (MCMA) is one of the largest megacities in the world with a population of 20 million people. Anthropogenic emissions have been controlled in past decades; however, emissions transported from outside the basin, such as wildfires and agricultural burning, represent a potentially large contribution to air quality degradation. This study analyzed PM10 filter samples from six different stations located across the MCMA from May, 2013, which represented the month with the most reported fire counts in the region over the last 11 years (2002-2013). Two meteorological regimes were established considering the number of satellite derived fire counts, changes in predominant wind direction, ambient concentrations of CO, PM10 and PM2.5, and precipitation patterns inside MCMA. The filter samples were analyzed for biomass burning tracers including levoglucosan (LEV), water-soluble potassium (WSK+); and water-soluble organic carbon (WSOC). Results of these analyses show that LEV concentrations correlated positively with ambient concentrations of PM2.5 and PM10 (R2=0.61 and R2=0.46, respectively). Strong correlations were also found between WSOC and LEV (R2=0.94) and between WSK+ and LEV (R2=0.75). An average LEV/WSOC ratio of 0.0147 was estimated for Regime 1 and 0.0062 for Regime 2. Our LEV concentrations and LEV/WSOC ratios are consistent with results found during the MILAGRO campaign (March, 2006). To the best of our knowledge, only total potassium concentrations have been measured in aerosol samples from MCMA. Therefore, this is the first study in MCMA to measure ambient concentrations of WSK+. Analysis of gravimetric mass concentrations showed that PM2.5 accounted for 60% of the PM10 mass concentration with an estimated PM10/PM2.5 ratio of 1.68. Estimates from our laboratory filter sample characterization indicated that we measured 37% of the total PM10 mass concentration. The missing mass is most likely crustal material (soil or dust) and carbonaceous aerosols that were not segregated into WSOC fraction. Assuming that LEV is inert in the atmosphere, the estimated biomass burning contributions to WSOC ranged from 7-23%. When assuming a LEV lifetime of 1.1 to 5 days, the estimated contributions increased on average 80%. Thus, we conclude that biomass burning sources had a large impact on WSOC and PM2.5 during May 2013, potentially explaining up to half of the measured WSOC. Our results indicate that primary emissions from biomass burning sources represent significant contributions to ambient PM. Future studies are needed to improve the emission inventories that are commonly used by decision makers in the MCMA to design air quality policies and emission source controls.
Open Access
Contribution of ²³⁸U and ²³²TH to radiation dose and risk from fly ash effluent of coal-fired power plants
(Colorado State University. Libraries, 2010) Beckfield, Felicity Cunningham, author; Johnson, Thomas, advisor; Woody, Robert, committee member; Volckens, John, committee member
The goal of this project was to determine the activity concentrations of 238U and 232Th emitted from a coal-fired power plant that could potentially impact human health and the environment. The activity concentration of 238U and 232Th in fly ash was used to estimate effluent uranium and thorium. The estimate of effluent activity was then used to model radiation dose and evaluate any associated increase in cancer risk to employees working in the plant and individuals living near the plant. Grab samples of fly ash were obtained and manually fractionated using the soil sizing techniques of sieving and pipetting. The respective samples were counted using alpha spectroscopy to determine the activity concentrations of 238U and 232Th. Whole body dose was calculated using 10 CFR 20 Appendix B annual limits on intake (ALI). The alpha emissions from 238U and 232Th are of particular interest as they are significant contributors to dose in the lungs and other tissues due to their high relative biologic effectiveness and short range. The results of this study indicate that fly ash contains both 238U and 232Th but is not a radioactive substance as defined by the IAEA transportation safety standards and Title 49 of the Code of Federal Regulations. Although the relative concentration of radionuclides in the fly ash of this study is quite low, it is still possible for individuals to receive a measurable dose. Exceeding occupational and public dose limits would require inhalation of approximately 1-1000 kg of fly ash for 232U and approximately 50 g to 20 kg for 232Th. The highest CEDE (ICRP 30) per unit mass incurred by inhalation of fly ash was class W 232Th (1.81 mrem g-1), while class W 238U had the lowest CEDE per unit mass (3.32 prem g-1). The general relationship between activity concentration of 238U and 232Th found using data from radiochemical analysis and particle size suggest that activity concentration increases with increasing particle size. However the relationship between activity concentration and particle size found in the literature suggests that activity concentration increases with decreasing particle size. The accompanying health risk from 238U and 232Th in fly ash is predicted to be less than 10-5 percent.
Open Access
Decontamination of bioaerosols within engineering tolerances of aircraft materials
(Colorado State University. Libraries, 2012) Frazey, John S., author; Reynolds, Stephen, advisor; Volckens, John, committee member; Keefe, Thomas J., committee member; Ellis, Robert P., committee member; Roy, Chad J., committee member
To view the abstract, please see the full text of the document.
Open Access
Developing a method to sample potential resuspension of radioactive contaminants near the former Rocky Flats Technical Plant
(Colorado State University. Libraries, 2024) Alcantar, Richard V., author; Sudowe, Ralf, advisor; Johnson, Tom, committee member; Volckens, John, committee member
From 1952 until 1989, the Rocky Flats Technical Plant processed plutonium for use as triggers in nuclear weapons. Throughout the facility's nearly 37 years in operation, several events led to radioactive contamination in areas within and surrounding the site. Since then, multiple cleanup projects have occurred, remediating contamination to acceptable levels. However, an increase in the number, size, and severity of Colorado wildfires in recent years has raised public concern for the potential resuspension of radioactive surface contamination to the now-populous areas surrounding Rocky Flats. Air sampling during specific conditions such as high winds, naturally occurring wildfires, and controlled burns would provide valuable data to determine if resuspension of radioactive contamination may be of concern. Sampling under such circumstances, however, is restricted by situation, permission, and weather. Whereas traditional aerosol sampling collects "total dust" samples to amass particles in the air with equal efficiency, without regard to particle size fraction, the use of a cascade impactor to separate aerosols by size can be utilized to relate how deep varied-sized particles might penetrate the human respiratory tract after inhalation. This would not only indicate the presence of radionuclides but also the deposition location within the human body, an important factor in determining the best dose estimate for the person. This study will compare the efficacy of a 3D-printed cascade impactor in separating particle size fractions to the capability of a commercial Andersen cascade impactor. Methods used in this thesis included radiological analysis with a Mirion LB4200 gas proportional counter. Significant imperfections of a printed prototype indicate that a stage-to-stage comparison between a commercial and a 3D-printed cascade impactor cannot be justified. Additionally, it is unlikely that current technology is capable of printing the exact same impactor with each subsequent print. The determination of a similar decay curve between stages of both impactors in some instances as well as similar trends in activity fraction by filter, however, indicate that a functional 3D-printed cascade impactor is feasible. Individually, each printed cascade impactor would require proper characterization to determine the particle size fraction that each stage captures. The evidence outlined in this study suggests that a functional cascade impactor can be fabricated by 3D printing. Still, additional studies would be necessary to characterize particle size distribution properly.
Open Access
Development and application of electrochemical dithiothreitol (DTT) assay for analysis of particulate matter
(Colorado State University. Libraries, 2017) Turner, Laurelle Rose, author; Henry, Charles, advisor; Kipper, Matt, committee member; Volckens, John, committee member
Particulate matter (PM) in air pollution, known to have a negative impact on biological systems, is regulated in many countries across the globe. The generation of PM from energy and mining industries is monitored in an effort to minimize its contributions to diminished human health. And although quantifying total PM generation (mass and number) and exposure can help track health risks, ultimately there exists a need to develop rapid, efficient, accurate methods for analyzing PM composition and health effects. Leading hypotheses over the last decade have theorized that PM, once absorbed into bodily tissues, generate reactive oxygen species (ROS), leading to oxidative stress, thus catalyzing cellular damage. A recently developed analytical electrochemical protocol has shown great potential for investigating the potential for PM to cause oxidative stress. The work discussed within this thesis focuses on the development of the electrochemical assay and its application to real world PM samples. Herein, the development of an electrochemical version of the well-studied dithiothreitol (DTT) absorbance spectroscopy assay is presented as a platform for the analysis of PM in air samples. Flow injection amperometry was used as the primary electrochemical method. Amperometry was performed using a CH Instruments potentiostat and commercially available DropSens modified carbon screen printed electrodes (SPE's) with a DropSens impinging jet flow cell, granting the assay flexibility to be performed in any lab with commercially available components. Previous examples used homemade components restricting accessibility to the field. The ability to use inexpensive, purchasable components eases trouble shooting, training, and allows for the potential to make the assay more mobile. The use of a flow cell also allows for the possibility for linking the assay to other analytical methods to further analyze PM which may not be reactive in the assay. Assay development focused on optimizing the assay temporally, as well as investigating its precision, detection limits, fluid dynamics, reproducibility, and relative accuracy. The electrochemical assay uses shorter reaction times and avoids the need for additional chemical quenching agents used in the absorbance assay, allowing for batch processing. Assay performance was compared to literature with a model oxidant quinone, 1,4-naphthoquinone, and trace metal, Cu(II). The assay was then applied to real exposure samples collected in Fresno, California and Honduras. Data from these samples were correlated against data obtained by the traditional DTT assay to investigate accuracy. Analyses of the Honduras samples will be correlated against health data as part of the Honduras Cookstove Project, moving one step closer to directly connecting PM reactivity to health effects. Although the traditional absorbance DTT assay is the standard in assessing PM reactivity in air samples, and has been used for the last 15 years, the electrochemical assay is a robust, quick, and precise alternative method that can be readily performed using readily available components.
Open Access
Evaluation of seasonal ventilation changes and their effect on ambient dust, endotoxin and bioaerosol concentrations in a dairy parlor
(Colorado State University. Libraries, 2011) Funk, Sara, author; Reynolds, Stephen J., advisor; Roman-Muniz, Noa, committee member; Volckens, John, committee member
This pilot study measured the impact of seasonal ventilation changes on concentrations of organic dust, endotoxin and bacteria in one modern dairy milking parlor. Pyrosequencing, a new non-target specific molecular methodology was used to characterize airborne bioaerosols. Area samples for inhalable dust, respirable dust, endotoxin, and bacteria were collected in one modern dairy parlor during both summer and winter seasons. Five sampling sessions were performed at approximately weekly intervals during each season. The summer season included an open facility with fresh mechanical air ventilation. The winter season consisted of a closed facility with no fresh air ventilation and forced heat. Aerosol size distributions, air velocity inside the parlor, humidity, temperature, and CO2 were also sampled on each trip. Two-way ANOVA was performed to test statistically significant differences between variables. No significant differences between mean concentrations of inhalable dust, respirable dust, or bacteria were seen by season. Endotoxin showed a near significant difference (p=0.06). CO2 concentration doubled during the winter season as compared to the summer (p<0.001) due to reduced ventilation. The aerosol size distribution did not vary between seasons (MMOD=12µm) indicating that seasonal ventilation changes do not affect the particle size distribution. The most common bacterial genera in both seasons were Clostridium (anaerobic), Oscillibacter and Staphylococcus - all Gram positive bacteria. Gram-positive bacterial genera occurred more frequently during the summer than winter seasons. Gram-negative bacteria cell counts increased in the winter season. Average concentrations of total bacteria in the facility during summer and winter were 2839 and 7008 counts/m3, respectively. This study was the first to apply Pyrosequencing to measure bioaerosols in a dairy environment. The diversity of bacteria and predominance of Gram-positive bacteria is consistent with studies in swine and poultry facilities. Concentrations of dust, endotoxin, and bacteria were low during both seasons in this milking parlor, most likely due to the new construction of the facility. These study results will inform the design of future comprehensive studies of aerosol exposure interventions in dairy operations. Understanding these aerosol exposures and potential interventions is important for reducing respiratory disease among workers in the dairy industry.
Open Access
Formation and evolution of secondary organic aerosol in laboratory experiments: precursors, processes, and properties
(Colorado State University. Libraries, 2022) He, Yicong, author; Jathar, Shantanu H., advisor; Pierce, Jeffrey R., committee member; Bond, Tami C., committee member; Volckens, John, committee member
Secondary organic aerosol (SOA) is an important fraction of atmospheric PM2.5 which is defined as fine-mode aerosols with diameters less than 2.5 μm. SOA is ubiquitous in the atmosphere and can have considerable impacts on the climate, air quality and human health. We are limited in our ability to predict the spatial and temporal distribution of SOA and assess its environmental impacts, because current three-dimensional chemical transport models (CTM) still have large biases and relatively weak correlations with observations of SOA. One reason for the model-observation discrepancy could be that we still lack a full understanding of the precursors, chemical/physical processes, and properties of SOA that govern its formation and evolution. Therefore, there is a need to further study the precursors, processes, and properties of SOA in laboratory experiments, and to develop more accurate SOA parameterizations that can be used to update the current CTMs. In Chapter 2, I studied SOA formation from several novel precursors which were vapors from biofuels that were under development at the National Renewable Energy Laboratory (NREL) to be used as future blendstocks to gasoline, and I developed SOA parameterizations for these biofuel precursors that corrected for the influence of vapor wall loss, using a kinetic SOA model called SOM-TOMAS (Statistical Oxidation Model coupled with TwO-Moment Aerosol Sectional Model). Although vapor wall loss has been shown to significantly impact SOA formation in environmental chamber experiments, it has rarely been corrected for in the development of SOA parameters used in atmospheric models. Our parameterizations predicted that under atmospherically relevant conditions, some of the biofuels may produce similar or even more SOA than gasoline, possibly offsetting the environmental benefits they offered. In addition, the parameterizations predicted that correcting for vapor wall loss in chambers always resulted in similar or increased atmospheric SOA mass yields compared to chamber yields, highlighting the potential for vapor wall loss correction to increase SOA predictions from CTMs and to bridge the gap with observations. In Chapter 3, I demonstrated a novel technique to constrain the SOA particle bulk diffusivity (Db) in chamber experiments, using a kinetic model (i.e., SOM-TOMAS) and measurements of the particle size distribution. Db is a property that controls the gas/particle partitioning timescale of SOA, where a higher Db (i.e., liquid aerosol) means faster partitioning and a lower Db (i.e., semi-solid aerosol) means slower partitioning. Here, I showed that the measured particle size distribution in SOA formation experiments contained sufficient information to constrain Db without direct measurement of the particle phase state or viscosity. In Chapter 4, I investigated the differences in the SOA mass yields measured in environmental chambers and oxidation flow reactors. Both chambers and flow reactors can simulate the photooxidation of Volatile Organic Compounds (VOCs), but flow reactors can achieve higher aging time (>2 weeks) than chambers (<1 day) by using very high oxidant concentrations. Their photooxidation chemistry pathways have been thought to be similar, but they produce different SOA mass yields at similar photochemical ages, which remains an unsolved problem. Here, I integrally simulated vapor and particle wall loss, semi-solid phase state, heterogeneous oxidation, particle-phase oligomerization, and new particle formation in chambers and flow reactors with experimentally constrained parameters for these processes. I showed that the SOA mass yield difference could be explained by the different contribution of these processes to SOA formation and evolution in chambers and flow reactors. Furthermore, with a single set of SOA parameterizations for photooxidation, the model was able to simultaneously predict the SOA mass concentration, bulk chemical composition (O:C ratio), and size distribution in chambers and flow reactors. The results highlight that flow reactor data can be modeled consistently with chamber data, and they should be used in synergy with chamber data to develop SOA parameterizations applicable to long photochemical aging times. In Chapter 5, in collaboration with Dr. Kelsey Bilsback, we investigated a widely employed assumption for particle wall loss correction in chamber experiments, regarding the interaction between wall-deposited particles and suspended vapors. Furthermore, as a continuation of the work from Chapter 2, we developed SOA parameterizations that corrected for both vapor and particle wall loss, and integrated these updated parameterizations into a CTM to assess the impacts on atmospheric SOA predictions. Specifically, we first showed that the interaction between vapors and wall-deposited particles was negligible through kinetic modeling, and accurate particle wall loss correction should assume no interaction between the two. We then found that the wall-loss-corrected SOA parameterizations greatly enhanced SOA formation in the CTM, reducing the gap with the observations. We argue that vapor and particle wall loss should be routinely accounted for in developing SOA parameterization.
Open Access
Household air pollution among women using biomass stoves in Honduras: exposure characterization and associations with exhaled nitric oxide and markers of systemic inflammation
(Colorado State University. Libraries, 2018) Benka-Coker, Megan Leigh, author; Clark, Maggie, advisor; Peel, Jennifer, committee member; Volckens, John, committee member; Wilson, Ander, committee member
To view the abstract, please see the full text of the document.
Open Access
Inhalational antibiotic therapy for treatment of chronic pulmonary Mycobacterium abscessus disease in mice
(Colorado State University. Libraries, 2019) Pearce, Camron, author; Gonzalez-Juarrero, Mercedes, advisor; Jackson, Mary, committee member; Volckens, John, committee member
Mycobacterium abscessus (M. abscessus) is a nontuberculous mycobacterium that causes chronic pulmonary infections. Due to M. abscessus's intrinsic antibiotic resistance, treatment is often complex with low cure rates. Tigecycline, a glycylcycline class antibiotic, demonstrates bactericidal effects against M. abscessus without eliciting bacterial resistance mechanisms, however, this antibiotic requires intravenous administration and causes significant side effects that limit its use. Here, we tested the hypothesis that tigecycline administered via inhalation has the potential to maximize the bactericidal effect while reducing side effects. GM-CSF knockout mice with pulmonary M. abscessus infection were treated by intrapulmonary tigecycline aerosols in 0.25 mg, 1.25 mg, and 2.50 mg doses for 28 days. Assessment of pulmonary bacterial burden after full treatment duration shows that inhaled tigecycline is highly effective, dose-dependent, and well tolerated. We concluded that inhaled tigecycline represents a viable treatment option for M. abscessus pulmonary disease. Future studies should address the pharmacokinetics, and ultimately, translation into clinical trials.
Open Access
Investigating the enhancement of air pollutant predictions and understanding air quality disparities across racial, ethnic, and economic lines at US public schools
(Colorado State University. Libraries, 2022) Cheeseman, Michael J., author; Pierce, Jeffrey R., advisor; Barnes, Elizabeth, committee member; Fischer, Emily, committee member; Ford, Bonne, committee member; Volckens, John, committee member
Ambient air pollution has significant health and economic impacts worldwide. Even in the most developed countries, monitoring networks often lack the spatiotemporal density to resolve air pollution gradients. Though air pollution affects the entire population, it can disproportionately affect the disadvantaged and vulnerable communities in society. Pollutants such as fine particulate matter (PM2.5), nitrogen oxides (NO and NO2), and ozone, which have a variety of anthropogenic and natural sources, have garnered substantial research attention over the last few decades. Over half the world and over 80% of Americans live in urban areas, and yet many cities only have one or several air quality monitors, which limits our ability to capture differences in exposure within cities and estimate the resulting health impacts. Improving sub-city air pollution estimates could improve epidemiological and health-impact studies in cities with heterogeneous distributions of PM2.5, providing a better understanding of communities at-risk to urban air pollution. Biomass burning is a source of PM2.5 air pollution that can impact both urban and rural areas, but quantifying the health impacts of PM2.5 from biomass burning can be even more difficult than from urban sources. Monitoring networks generally lack the spatial density needed to capture the heterogeneity of biomass burning smoke, especially near the source fires. Due to limitations of both urban and rural monitoring networks several techniques have been developed to supplement and enhance air pollution estimates. For example, satellite aerosol optical depth (AOD) can be used to fill spatial gaps in PM monitoring networks, but AOD can be disconnected from time-resolved surface-level PM in a multitude of ways, including the limited overpass times of most satellites, daytime-only measurements, cloud cover, surface reflectivity, and lack of vertical-profile information. Observations of smoke plume height (PH) may provide constraints on the vertical distribution of smoke and its impact on surface concentrations. Low-cost sensor networks have been rapidly expanding to provide higher density air pollution monitoring. Finally, both geophysical modeling, statistical techniques such as machine learning and data mining, and combinations of all of the aforementioned datasets have been increasingly used to enhance surface observations. In this dissertation, we explore several of these different data sources and techniques for estimating air pollution and determining community exposure concentrations. In the first chapter of this dissertation, we assess PH characteristics from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) and evaluate its correlation with co-located PM2.5 and AOD measurements. PH is generally highest over the western US. The ratio PM2.5:AOD generally decreases with increasing PH:PBLH (planetary boundary layer height), showing that PH has the potential to refine surface PM2.5 estimates for collections of smoke events. Next, to estimate spatiotemporal variability in PM2.5, we use machine learning (Random Forests; RFs) and concurrent PM2.5 and AOD measurements from the Citizen Enabled Aerosol Measurements for Satellites (CEAMS) low-cost sensor network as well as PM2.5 measurements from the Environmental Protection Agency's (EPA) reference monitors during wintertime in Denver, CO, USA. The RFs predicted PM2.5 in a 5-fold cross validation (CV) with relatively high skill (95% confidence interval R2=0.74-0.84 for CEAMS; R2=0.68-0.75 for EPA) though the models were aided by the spatiotemporal autocorrelation of the PM22.5 measurements. We find that the most important predictors of PM2.5 are factors associated with pooling of pollution in wintertime, such as low planetary boundary layer heights (PBLH), stagnant wind conditions, and, to a lesser degree, elevation. In general, spatial predictors are less important than spatiotemporal predictors because temporal variability exceeds spatial variability in our dataset. Finally, although concurrent AOD is an important predictor in our RF model for hourly PM2.5, it does not improve model performance during our campaign period in Denver. Regardless, we find that low-cost PM2.5 measurements incorporated into an RF model were useful in interpreting meteorological and geographic drivers of PM2.5 over wintertime Denver. We also explore how the RF model performance and interpretation changes based on different model configurations and data processing. Finally, we use high resolution PM2.5 and nitrogen dioxide (NO2) estimates to investigate socioeconomic disparities in air quality at public schools in the contiguous US. We find that Black and African American, Hispanic, and Asian or Pacific Islander students are more likely to attend schools in locations where the ambient concentrations of NO2 and PM2.5 are above the World Health Organization's (WHO) guidelines for annual-average air quality. Specifically, we find that ~95% of students that identified as Asian or Pacific Islander, 94% of students that identified as Hispanic, and 89% of students that identified as Black or African American, attended schools in locations where the 2019 ambient concentrations were above the WHO guideline for NO2 (10 μg m-3 or ~5.2 ppbv). Conversely, only 83% of students that identified as white and 82% of those that identified as Native American attended schools in 2019 where the ambient NO2 concentrations were above the WHO guideline. Similar disparities are found in annually averaged ambient PM2.5 across racial and ethnic groups, where students that identified as white (95%) and Native American (83%) had a smallest percentage of students above the WHO guideline (5 μg m-3), compared to students that identified with minoritized groups (98-99%). Furthermore, the disparity between white students and other minoritized groups, other than Native Americans, is larger at higher PM2.5 concentrations. Students that attend schools where a higher percentage of students are eligible for free or reduced meals, which we use as a proxy for poverty, are also more likely to attend schools where the ambient air pollutant concentrations exceed WHO guidelines. These disparities also tend to increase in magnitude at higher concentrations of NO2 and PM2.5. We investigate the intersectionality of disparities across racial/ethnic and poverty lines by quantifying the mean difference between the lowest and highest poverty schools, and the most and least white schools in each state, finding that most states have disparities above 1 ppbv of NO2 and 0.5 μg m-3 of PM2.5 across both. We also identify distinct regional patterns of disparities, highlighting differences between California, New York, and Florida. Finally, we also highlight that disparities do not only exist across an urban and non-urban divide, but also within urban areas.