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Simple Summary The DNA damage repair (DDR) gene profile is largely unexplored in head and neck squamous cell cancer (HNSCC), leaving little known about the treatment of HNSCC with PARP inhibitors. In this retrospective study, the prevalence of mutated DDR genes was studied in the tissue and/or blood samples (tDNA and ctDNA samples, respectively) of 170 patients with HNSCC. These findings were correlated with demographic and outcome data. DDR gene mutations were significantly increased in older patients, patients with primary tumors located in the larynx, patients with more advanced cancers at diagnosis and patients previously treated with chemotherapy and/or radiotherapy. Patients with primary tumors in the oropharynx were less likely to have DDR gene mutations. Patients with DDR gene mutations identified in blood samples were found to have worse survival. The combined mutational analysis in blood and tumor demonstrated a high prevalence and an important prognostic role of DDR gene mutations in HNSCC, supporting further clinical research of PARP inhibitors in the genomic guided treatment of HNSCC. Abstract PARP inhibitors are currently approved for a limited number of cancers and targetable mutations in DNA damage repair (DDR) genes. In this single-institution retrospective study, the profiles of 170 patients with head and neck squamous cell cancer (HNSCC) and available tumor tissue DNA (tDNA) and circulating tumor DNA (ctDNA) results were analyzed for mutations in a set of 18 DDR genes as well as in gene subsets defined by technical and clinical significance. Mutations were correlated with demographic and outcome data. The addition of ctDNA to the standard tDNA analysis contributed to identification of a significantly increased incidence of patients with mutations in one or more genes in each of the study subsets of DDR genes in groups of patients older than 60 years, patients with laryngeal primaries, patients with advanced stage at diagnosis and patients previously treated with chemotherapy and/or radiotherapy. Patients with DDR gene mutations were found to be significantly less likely to have primary tumors within the in oropharynx or HPV-positive disease. Patients with ctDNA mutations in all subsets of DDR genes analyzed had significantly worse overall survival in univariate and adjusted multivariate analysis. This study underscores the utility of ctDNA analysis, alone, and in combination with tDNA, for defining the prevalence and the role of DDR gene mutations in HNSCC. Furthermore, this study fosters research promoting the utilization of PARP inhibitors in HNSCC precision oncology treatments.

Background Optimal diagnostic algorithm to differentiate checkpoint inhibitor pneumonitis (CIP) from mimics is uncertain; patients with respiratory comorbidities often receive prolonged corticosteroids until diagnostic clarification. Drawbacks to empiric use of corticosteroids include decreased immunotherapy (IO) efficacy and increased infectious risk. This retrospective study systematically collected data on patients treated for lung cancer who were suspected to have severe CIP. Methods This single-center retrospective cohort study collected data on all lung cancer patients who received > 1 dose of an immune checkpoint inhibitor between 6/1/18 and 2/1/20 (n=210), were subsequently hospitalized and received > 1 dose of systemic corticosteroids for any indication (n=97). Data were collected on clinical factors including comorbidities, cancer stage, IO cycles, biomarkers, diagnostic work-up, antibiotics, steroids, progression, and survival. A blinded radiologist reviewed all imaging of suspected CIP cases and categorized their radiographic patterns. Results In our high-risk cohort of 97 patients, median follow-up was 23 months with progression in 54 patients (56%) at median 11 months and death in 67 patients (69%) at median 14mo. Twelve patients (12%) were suspected to have severe CIP after IO treatment for lung cancer; CIP was confirmed in 5/12 and ruled-out (mimics) in 7/12 after 30 and 3 median IO cycles, respectively. Most suspected patients underwent CXR, CTA chest, blood cultures, and received empiric antibiotics. Common radiographic patterns were ground-glass opacities, organizing pneumonia, hypersensitivity pneumonitis, and acute interstitial pneumonia/acute respiratory distress syndrome (AIP/ARDS) among confirmed cases (4/5) and ground-glass opacities, organizing pneumonias, bronchiolitis, AIP/ARDS among mimics (4/7). The median time to confirm CIP or rule out a mimic was 5 ± 4 days. Median time to onset of symptoms differed substantially for confirmed and mimic cases: 17 months and 1 month, respectively. Conclusions CIP mimics were more common than confirmed cases in routine clinical practice, particularly among patients hospitalized for respiratory symptoms Ethics Approval The study was approved by Wake Forest Baptist Medical Center‘s Ethics Board, IRB approval number 00044126

Simple Summary Immunotherapy has prompted a dramatic change in the management of head and neck squamous cell carcinoma (HNSCC), but the percentage of patients benefiting from treatment is limited to 20% or less. The application of precision oncology to HNSCC introduces the potential for the emergence of biomarkers that may predict a response to immunotherapy and assist with the selection of patients that may benefit from treatment with an immune checkpoint inhibitors. In this retrospective study, the results of tumor mutational burden and programmed death ligand-1 measurements from HNSCC tumors were evaluated independently for their associations with demographics, risk factors, disease characteristics, survival, and response to ICI. Results of this study are expected to assist in laying the groundwork for creating a framework in which PD-L1 and TMB coexist with other variables to predict response to ICI on an individual level. Abstract Failure to predict response to immunotherapy (IO) limited its benefit in the treatment of head and neck squamous cell cancer (HNSCC) to 20% of patients or less. Biomarkers including tumor mutational burden (TMB) and programmed death ligand-1 (PD-L1) were evaluated as predictors of response to IO, but the results are inconsistent and with a lack of standardization of their methods. In this retrospective study, TMB and PD-L1 were measured by commercially available methodologies and were correlated to demographics, outcome, and response to PD-1 inhibitors. No correlation was found between TMB and PD-L1 levels. High TMB was associated with smoking and laryngeal primaries. PD-L1 was significantly higher in African Americans, patients with earlier stage tumors, nonsmokers, and nonethanol drinkers. Patients with high TMB fared better in univariate and multivariate survival analysis. No correlation was found between PD-L1 expression and prognosis. There was a statistically significant association between PFS and response to IO and TMB. There was no association between response to ICI and PD-L1 in this study, possibly affected by variations in the reporting method. Further studies are needed to characterize the biomarkers for IO in HNSCC, and this study supports further research into the advancement of TMB in prospective studies.

The Desert Southwest Coarse Particulate Matter Study was undertaken to further our understanding of the spatial and temporal variability and sources of fine and coarse particulate matter (PM) in rural, arid, desert environments. Sampling was conducted between February 2009 and February 2010 in Pinal County, AZ near the town of Casa Grande where PM concentrations routinely exceed the U.S. National Ambient Air Quality Standards (NAAQS) for both PM 10 and PM 2.5 . In this desert region, exceedances of the PM 10 NAAQS are dominated by high coarse particle concentrations, a common occurrence in this region of the United States. This work expands on previously published measurements of PM mass and chemistry by examining the sources of fine and coarse particles and the relative contribution of each to ambient PM mass concentrations using the Positive Matrix Factorization receptor model (Clements et al., 2014). Coarse particles within the region were apportioned to nine sources including primary biological aerosol particles (PBAPs - 25%), crustal material (20%), re-entrained road dust (11%), feedlot (11% at the site closest to a cattle feedlot), secondary particles (10%), boron-rich crustal material (9%), and transported soil (6%), with minor contributions from ammonium nitrate, and salt (considered to be NaCl). Fine particles within the region were apportioned to six sources including motor vehicles (37%), road dust (29%), lead-rich (10%), with minor contributions from brake wear, crustal material, and salt. These results can help guide local air pollution improvement strategies designed to reduce levels of PM to below the NAAQS.

e21151 Background: Although predictive of chemotherapy toxicity, geriatric assessment measures are not systematically collected in clinical practice and may or may not be predictive for immune-related adverse events. Furthermore, hospitalization during immune checkpoint inhibitor (ICI) treatment for advanced lung cancer has variable prognostic significance. This study aimed to evaluate whether age and documented patient characteristics mapped to geriatric assessment domains (frailty markers, FM) predict survival in this setting. Methods: A single-center retrospective cohort of advanced stage lung cancer patients who received >1 dose of an ICI from 6/1/18 to 2/1/20, were later hospitalized, and received ≥ 1 dose of systemic corticosteroids (n=97) was analyzed. Chart review ascertained documentation of any of the following FMs prior to ICI initiation: inability to walk one block, unintentional weight loss, decreased social activities, recent falls, need for assistance with medications, visual or hearing impairments, living alone, and concern regarding social support. Patients were stratified according to age and three FM categories (0 FM [low risk], ≥1 FMs [at risk], and ≥2 FMs [high risk]). Overall survival (OS) analysis was calculated from first dose of ICI to date of death or last follow-up. Cox’s proportional hazards models were used to assess the relationship between FMs and age on OS; hazard ratios (HR) and 95% confidence intervals (CI) were calculated. Results: Analysis of < 75 and ≥ 75 yo revealed a median OS of 15.1 and 5.4 months respectively (HR 2.76, CI 1.62-4.72). Controlled for performance status (PS), older age (≥75 yo) was associated with a higher risk of death (HR 2.39, CI 1.32-4.31). FMs were associated with higher mortality, adjusted for PS and age (at risk patients HR 1.81, CI 1.03-3.16; high risk patients HR 2.02, CI 1.07-3.78). PS prior to starting ICI was not associated with OS. Conclusions: Age ≥ 75 yo is associated with short survival among lung cancer patients hospitalized while receiving ICI. Pre-treatment FMs documented as part of usual care were associated with worse OS, even after controlling for PS and age. This study shows promise for use of machine learning algorithms to stratify risk in hospitalized patients undergoing treatment for lung cancer with ICIs. These data would allow providers to better target serious illness conversations and end-of-life resources.[Table: see text]

e18016 Background: Next generation sequencing (NGS) has introduced the opportunity for targeted therapies and guidance regarding disease course and prognosis. The mutational landscape of squamous cell cancers of the head and neck (HNSCC) remains incompletely described. DNA repair gene (DRG) mutations are targeted by PARP inhibitors. This study presents the prevalence of DRG mutations in tumor and blood samples of patients with HNSCC and their outcome data. Methods: In this retrospective study, demographic and outcome data were collected and analyzed with regard to the presence or absence of mutated DRG (BRCA1, BRCA2, ATM, BRIP1, BARD1, CDK12, CHEK1, CHEK2, FANCL, PALB2, PPP2R2A, RAD51B, RAD51C, RAD51D, RAD51L, APC, ARID1A and MLL3). Mutated DRG were detected in tumor tissue (tDNA) by Foundation Medicine and/or in blood (ctDNA) by Guardant 360. All 18 genes were analyzed by FM, but only six are included in the G360 panel (BRCA1, BRCA2, ATM, APC, ARID1A and CDK12). Results: Our analysis included 170 HNSCC patients. Of these, 138 underwent NGS via ctDNA, 146 via tDNA and 114 via both methods. Sixty-five patients (47%) had at least one tDNA DRG mutation, 54 patients (37%) had at least one ctDNA DRG mutation and 96 patients (56%) had at least one DRG mutation detected by either method. No significant association was found between DRG mutations and age, gender, race, HPV status, tobacco/alcohol use or stage at diagnosis. Subsite analyses revealed that laryngeal primaries were associated with higher prevalence of DRG mutations detected via tDNA (p = 0.05), ctDNA (p = 0.03) or either method (p = 0.01). Oropharyngeal primaries correlated with a lower prevalence of DRG mutations detected via tDNA (p = 0.03) or via either method (p = 0.02) but were less significant when mutations were detected via ctDNA alone (p = 0.08). Mutated DRG detected via ctDNA correlated significantly with stage at time of ctDNA collection (p = 0.03), presence/absence of cancer at last visit (p = 0.05) and with stage at last visit (p = 0.05). Two-year survival and overall survival (OS) measured from the time of ctDNA collection correlated significantly with mutated ctDNA DRG. The relationship between ctDNA DRG mutations and OS remained statistically significant in a Cox proportional hazards regression model when adjusted for age, tobacco use, tumor site, nodal stage at diagnosis, and previous treatment with chemotherapy, radiation or combined chemoradiation therapy in a multivariate analysis model (p = 0.05). No similar correlation was found between tDNA mutations in DRG and prognosis. Conclusions: A significant proportion of patients with HNSCC were found to have mutations in DRG. Patients with laryngeal disease were most likely to have DRG mutations, whereas those with oropharyngeal disease were less likely. Patients with DRG mutations in ctDNA, but not tDNA, had significantly worse prognoses with a lower likelihood of overall survival and higher disease burden at last visit.

Dust storms are significant contributors to ambient levels of particulate matter (PM) in many areas of the world. Central Asia, an area that is relatively understudied in this regard, is anticipated to be affected by dust storms due to its proximity to several major deserts that are in and generally surround Central Asia (e.g., the Aral Sea region, the Taklimakan desert in Western China). To investigate the relative importance of mineral dust (dust specifically composed of soil related minerals and oxides) in Central Asia, PM10 and PM2.5, and by difference, coarse particles (particles with diameters between 2.5 and 10 μm) were measured at two sites, Bishkek and Lidar Station Teplokluchenka (Lidar), in the Kyrgyz Republic. Samples were collected every other day from July 2008 to July 2009. Daily samples were analyzed for mass and organic and elemental carbon. Samples were also composited on a bi-weekly basis and analyzed for elemental constituents and ionic components. In addition, samples collected on days with relatively high and low PM concentrations were analyzed before, and separately, from the biweekly composites to investigate the chemical differences between the episodic events. Data from the episodic samples were averaged into the composited averages. Using the elemental component data, several observational models were examined to estimate the contribution of mineral dust to ambient PM levels. A mass balance was also conducted. Results indicate that at both sites, mineral dust (as approximated by the “dust oxide” model) and organic matter (OM) were the dominant contributors to PM10 and PM2.5. Mineral dust was a more significant contributor to the coarse PM (PM10-2.5) during high event samples at both sites, although the relative contribution is greater at the Lidar site (average ± standard deviation = 42 ± 29%) as compared with the Bishkek site (26 ± 16%). Principal Components Analysis (PCA) was performed using data from both sites, and PCA indicated that mineral dust explained the majority of the variance in PM concentrations, and that the major apportioned factors of PM10 and PM2.5 were chemically similar between sites.

Particulate matter (PM) mass concentrations, seasonal cycles, source sector, and source region contributions in Central Asia (CA) are analyzed for the period April 2008–July 2009 using the Sulfur Transport and dEposition Model (STEM) chemical transport model and modeled meteorology from the Weather Research and Forecasting (WRF) model. Predicted aerosol optical depth (AOD) values (annual mean value ~0.2) in CA vary seasonally, with lowest values in the winter. Surface PM2.5 concentrations (annual mean value ~10 μg m−3) also exhibit a seasonal cycle, with peak values and largest variability in the spring/summer, and lowest values and variability in the winter (hourly values from 2 to 90 μg m−3). Surface concentrations of black carbon (BC) (mean value ~0.1 μg m−3) show peak values in the winter. The simulated values are compared to surface measurements of AOD as well as PM2.5, PM10, BC, and organic carbon (OC) mass concentrations at two regional sites in Kyrgyzstan (Lidar Station Teplokluchenka (LST) and Bishkek). The predicted values of AOD and PM mass concentrations and their seasonal cycles are fairly well captured. The carbonaceous aerosols are underpredicted in winter, and analysis suggests that the winter heating emissions are underestimated in the current inventory. Dust, from sources within and outside CA, is a significant component of the PM mass and drives the seasonal cycles of PM and AOD. On an annual basis, the power and industrial sectors are found to be the most important contributors to the anthropogenic portion of PM2.5. Residential combustion and transportation are shown to be the most important sectors for BC. Biomass burning within and outside the region also contributes to elevated PM and BC concentrations. The analysis of the transport pathways and the variations in particulate matter mass and composition in CA demonstrates that this region is strategically located to characterize regional and intercontinental transport of pollutants. Aerosols at these sites are shown to reflect dust, biomass burning, and anthropogenic sources from Europe; South, East, and Central Asia; and Russia depending on the time period. Simulations for a reference 2030 emission scenario based on pollution abatement measures already committed to in current legislation show that PM2.5 and BC concentrations in the region increase, with BC growing more than PM2.5 on a relative basis. This suggests that both the health impacts and the climate warming associated with these particles may increase over the next decades unless additional control measures are taken. The importance of observations in CA to help characterize the changes that are rapidly taking place in the region are discussed.

The Desert Southwest Coarse Particulate Matter Study was undertaken to further our understanding of ambient concentrations and the composition of fine and coarse particles in rural, arid environments. Sampling was conducted in Pinal County, Arizona between February 2009 and February 2010. The goals of this study were to: (1) chemically characterize the coarse and fine fraction of the ambient particulate matter in terms of mass, ions, elements, bulk organic and elemental carbon; (2) examine the temporal and spatial variability of particles within the area using a series of three sampling locations and use this information to determine the contribution of local vs. regional sources; (3) collect, re–suspend, and chemically characterize various crustal sources within the area to identify differences which may isolate them (crustal sources) as independent sources, and; (4) use a receptor based modeling approach to identify particle sources and the relative impact of each on ambient PM concentrations. This work reviews the study objectives, design, site descriptions, and measurement techniques relevant to this research effort and presents the general characteristics of PM during the study period. This unique dataset will support efforts to reduce PM10 and PM2.5 concentrations in the area to below the National Ambient Air Quality Standards (NAAQS) for these pollutants.Coarse particle concentrations are, on average, approximately 5 times fine particle mass concentrations within the region. Coarse particle concentrations in Pinal County are highest during spring and fall seasons, consistent with the tilling and harvesting seasons while fine particles concentrations are highest during fall. Crustal material is the dominant component of coarse particle composition, representing 50% of the mass on average followed closely by organic matter representing 15%. Fine particles still contain a significant crustal fraction (30%) but organic matter dominates at 37% of the particle mass.

The vertical structure of aerosol optical and physical properties was measured by Lidar in Eastern Kyrgyzstan, Central Asia, from June 2008 to May 2009. Lidar measurements were supplemented with surface-based measurements of PM2.5 and PM10 mass and chemical composition in both size fractions. Dust transported into the region is common, being detected 33% of the time. The maximum frequency occurred in the spring of 2009. Dust transported to Central Asia comes from regional sources, for example, Taklimakan desert and Aral Sea basin, and from long-range transport, for example, deserts of Arabia, Northeast Africa, Iran, and Pakistan. Regional sources are characterized by pollution transport with maximum values of coarse particles within the planetary boundary layer, aerosol optical thickness, extinction coefficient, integral coefficient of aerosol backscatter, and minimum values of the Ångström exponent. Pollution associated with air masses transported over long distances has different characteristics during autumn, winter, and spring. During winter, dust emissions were low resulting in high values of the Ångström exponent (about 0.51) and the fine particle mass fraction (64%). Dust storms were more frequent during spring with an increase in coarse dust particles in comparison to winter. The aerosol vertical profiles can be used to lower uncertainty in estimating radiative forcing.

The variability of total column ozone (TCO) and tropospheric column ozone (TrCO) was examined in Central Asia. Measurements were conducted at the Lidar Station Teplokluchenka in eastern Kyrgyzstan for one year, July 2008–July 2009. TCO was obtained using a handheld Microtops II Ozonometer (TCO-MII) and from the Aura OMI (TCO-OMI) satellite. Nitrogen dioxide (NO2) and formaldehyde concentrations also were obtained from the OMI satellite. Formaldehyde was used as a surrogate for volatile organic compounds. TrCO was estimated by the difference between TCO-OMI and stratospheric column ozone retrieved from the MLS satellite. Comparison of the ground-based TCO-MII with TCO-OMI showed good agreement (r 2 = 0.93), and linear regression between these was used to estimate missing values in the TCO-MII dataset. The contribution of TrCO to TCO varied from 15% in summertime to 5% in winter. High values of TrCO were observed during summer (July: 45 DU) and low values during winter (December: 15 DU), as is typically observed. The average values of TrCO for summer, autumn, winter, and spring were equal to 42, 27, 20, and 30 DU, respectively. Seasonal variability of TrCO corresponded to solar intensity, indicating that TrCO is likely to form through photochemical means rather than stratospheric intrusion. The spatial distribution of NO2 and VOC were examined to better understand the regional sources of these ozone precursors. Transport from highly populated areas of the Ferghana Valley and Tashkent in Uzbekistan contributed to the TrCO concentrations observed in this work. The HCHO/NO2 ratio, an indicator of the ozone production rate, suggested that reducing NO2 would be more effective in reducing TrCO during most of the year, except summer, when reductions of both would likely be needed.

Measurements were obtained at two sites in northern Tien-Shan in Central Asia during a 1-year period beginning July 2008 to examine the statistical relationship between aerosol optical depth (AOD) and of fine [PM2.5, particles less than 2.5 μm aerodynamic diameter (AD)] and coarse (PMCoarse, particles between 2.5 and 10 μm AD) mass concentrations and composition. The measurements represent the first extended particulate matter measurements in the northern Tien-Shan region of Central Asia. A sun photometer (Microtops II) was used to measure AOD from the surface, which is a widely used aerosol monitoring technique that is used in the AERONET network. In parallel, less routine measurements of continuous hourly PM2.5 data were obtained with the TEOM/FDMS whereas daily average PM2.5 and PM10 were obtained using URG-3000ABC samplers. Daily samples were collected on an every-other-day basis throughout the year. Since clouds interfere with the AOD measurement, a cloud screening procedure based on LIDAR measurements was applied to the AOD data and cloud impacted days were removed from the AOD data set. Depending on the season, the correlation coefficient (r) varied from 0.56 up to 0.87. Higher correlation coefficients between PM2.5 mass and AOD were observed during the spring and autumn periods and appeared to result from the transport of Asian dust (desert crustal material) particles from outside the area. One of the main source areas was the Taklimakan desert located in northwestern China. Linear regression results between AOD and PM2.5 are presented that allow for an estimate of PM2.5 mass concentrations at the surface based on the AOD data, which can be used to help interpret AOD measurements made in Central Asia and potentially other regions of the world.

Central Asia is a relatively understudied region of the world in terms of characterizing ambient particulate matter (PM) and quantifying source impacts of PM at receptor locations, although it is speculated to have an important role as a source region for long-range transport of PM to Eastern Asia, the Pacific Ocean, and the Western United States. PM is of significant interest not only because of its adverse effect on public health but also due to its more recently realized role in climate change. To investigate the sources and characteristics of PM in the region, a series of PM2.5 and PM10 samples were collected on an every-other-day basis at two sites (termed “Bishkek” and “Teploklyuchenka”) in the Central Asian nation of the Kyrgyz Republic (also known as Kyrgyzstan) for a full year from July 2008 to July 2009. These samples were analyzed using standard methods for mass, organic carbon (OC), elemental carbon (EC), water-soluble organic carbon (WSOC), water-insoluble organic carbon by difference (OC minus WSOC) and a variety of molecular marker chemical species to be used in a chemical mass balance (CMB) model to apportion the sources of OC. These analyses indicate that approximately 19 ± 6.4% of the PM2.5 mass at both sites throughout the year consists of OC. The carbonaceous component of PM2.5 is dominated by OC, with OC/Total Carbon (TC) ratios being around 0.8 in the winter to almost 0.95 in the summer months. The CMB analysis indicated that mobile sources, i.e., gasoline and diesel engine exhaust, biomass combustion, and biogenic secondary organic aerosol (SOA) formation from isoprene and α-pinene precursors in the summer months were the dominant sources of OC. A strong positive correlation was observed between non-biomass burning WSOC and the un-apportioned OC from the CMB analysis, indicating that some of this un-apportioned OC is WSOC and likely the result of SOA-forming atmospheric processes that were not estimated by the CMB analysis performed. In addition, a comparison of the predominant contributors to OC between the two sites indicates that biomass combustion is a stronger relative source of OC at the Teploklyuchenka site, particularly in the winter, while contributions of isoprene- and α-pinene-derived SOA to the measured OC was relatively similar between the sites.

A year-long study was conducted in Pinal County, AZ, to characterize coarse (2.5 - 10 microm aerodynamic diameter, AD) and fine (2.5 microm AD) particulate matter (PMc and PMf, respectively) to further understand spatial and temporal variations in ambient PM concentrations and composition in rural, arid environments. Measurements of PMc and PMf mass, ions, elements, and carbon concentrations at one-in-six day resolution were obtained at three sites within the region. Results from the summer of 2009 and specifically the local monsoon period are presented. The summer monsoon season (July - September) and associated rain and/or high wind events, has historically had the largest number of PM10 NAAQS exceedances within a year. Rain events served to clean the atmosphere, decreasing PMc concentrations resulting in a more uniform spatial gradient among the sites. The monsoon period also is characterized by high wind events, increasing PMc mass concentrations, possibly due to increased local wind-driven soil erosion or transport. Two PM10 NAAQS exceedances at the urban monitoring site were explained by high wind events and can likely be excluded from PM10 compliance calculations as exceptional events. At the more rural Cowtown site, PM10 NAAQS exceedances were more frequent, likely due to the impact from local dust sources. PM mass concentrations at the Cowtown site were typically higher than at the Pinal County Housing and Casa Grande sites. Crustal material was equal to 52-63% of the PMc mass concentration on average. High concentrations of phosphate and organic carbon found at the rural Cowtown were associated with local cattle feeding operations. A relatively high correlation between PMc and PMf (R2 = 0.63) indicated that the lower tail of the coarse particle fraction often impacts the fine particle fraction, increasing the PMf concentrations. Therefore, reductions in PMc sources will likely also reduce PMf concentrations, which also are near the value of the 24-hr PM2.5 NAAQS.In the desert southwest, summer monsoons are often associated with above average PM10 (10 microm AD) mass concentrations. Competing influences of monsoon rain and wind events showed that rain suppresses ambient concentrations while high wind increase them. In this region, the PMc fraction dominates PM10 and crustal sources contribute 52-63% to local PMc mass concentrations on average. Cattle feedlot emissions are also an important source and a unique chemical signature was identified for this source. Observations suggest monsoon wind events alone cannot explain PM10 NAAQS exceedances, thus requiring these values to remain in compliance calculations rather than being removed as exceptional wind events.