Abstract. A method for the retrieval of aerosol optical and microphysical properties from in situ light-scattering measurements is presented and the results are compared with existing measurement techniques. The Generalized Retrieval of Aerosol and Surface Properties (GRASP) is applied to airborne and laboratory measurements made by a novel polar nephelometer. This instrument, the Polarized Imaging Nephelometer (PI-Neph), is capable of making high-accuracy field measurements of phase function and degree of linear polarization, at three visible wavelengths, over a wide angular range of 3 to 177• . The resulting retrieval produces particle size distributions (PSDs) that agree, within experimental error, with measurements made by commercial optical particle counters (OPCs). Additionally, the retrieved real part of the refractive index is generally found to be within the predicted error of 0.02 from the expected values for three species of humidified salt particles, with a refractive index that is well established. The airborne measurements used in this work were made aboard the NASA DC-8 aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC 4 RS) field campaign, and the inversion of this data represents the first aerosol retrievals of airborne polar nephelometer data. The results provide confidence in the real refractive index product, as well as in the retrieval's ability to accurately determine PSD, without assumptions about refractive index that are required by the majority of OPCs.

Aerosol models, composed of size distribution, complex refractive index, and spherical fraction, are derived from a new synergistic retrieval of airborne in situ angular scattering measurements made by the Polarized Imaging Nephelometer and absorption measurements from the Particle Soot Absorption Photometer. The data utilized include phase function (F11), degree of polarization (−F12/F11), and absorption coefficient (βabs) measured at low relative humidities during the Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convection Clouds and Chemistry (DC3) field campaigns. The Generalized Retrieval of Aerosol and Surface Properties (GRASP) is applied to these measurements to obtain summaries of particle properties that are optically consistent with the original measurements. A classification scheme is then used to categorize the corresponding retrieval results. Inversions performed on the DC3 measurements indicate the presence of a significant amount of dust‐like aerosol in the inflow of storms sampled during this campaign, with the quantity of dust present depending strongly on the underlying surface features. In the SEAC4RS data, the retrieved size distributions were found to be remarkably similar among a range of aerosol types, including urban and industrial, biogenic, and biomass burning (BB) emissions. These aerosol types were found to have average fine mode volume median radii 0.155 ≤ rvf ≤ 0.163μm and lognormal standard deviations 0.32 ≤ σf ≤ 0.36. There were, however, consistent differences between the angular scattering patterns of the BB samples and the other particle types. The GRASP retrieval predominantly attributed these differences to elevated real and imaginary refractive indices in the BB samples (m532nm≈1.55+0.007i) relative to the two other categories (m532nm≈1.51+0.004i).

Abstract. This work provides a synopsis of aerosol phase function (F11) and polarized phase function (F12) measurements made by the Polarized Imaging Nephelometer (PI-Neph) during the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Deep Convection Clouds and Chemistry (DC3) field campaigns. In order to more easily explore this extensive dataset, an aerosol classification scheme is developed that identifies the different aerosol types measured during the deployments. This scheme makes use of ancillary data that include trace gases, chemical composition, aerodynamic particle size and geographic location, all independent of PI-Neph measurements. The PI-Neph measurements are then grouped according to their ancillary data classifications and the resulting scattering patterns are examined in detail. These results represent the first published airborne measurements of F11 and -F12/F11 for many common aerosol types. We then explore whether PI-Neph light-scattering measurements alone are sufficient to reconstruct the results of this ancillary data classification algorithm. Principal component analysis (PCA) is used to reduce the dimensionality of the multi-angle PI-Neph scattering data and the individual measurements are examined as a function of ancillary data classification. Clear clustering is observed in the PCA score space, corresponding to the ancillary classification results, suggesting that, indeed, a strong link exists between the angular-scattering measurements and the aerosol type or composition. Two techniques are used to quantify the degree of clustering and it is found that in most cases the results of the ancillary data classification can be predicted from PI-Neph measurements alone with better than 85 % recall. This result both emphasizes the validity of the ancillary data classification as well as the PI-Neph's ability to distinguish common aerosol types without additional information.

Clinical diagnosis of THS could be supported by radiological findings. According to the International Classification of Headache Disorders (ICHD)-3 beta diagnostic criteria, the diagnosis must be confirmed with an abnormal MRI and/or pathological sample. We add to the previous findings of THS with a normal MRI. Although MRI plays a crucial role in differential diagnosis, it should not, nor should the biopsy, be a must for the diagnosis. Limitations of using MRI in some patients are another problem.

Abstract. This work provides a synopsis of aerosol phase function (F 11 ) and polarized phase function (−F 12 /F 11 ) measurements made by the Polarized Imaging Nephelometer (PI-Neph) during the Studies of Emissions and Atmospheric Composition, campaigns. In order to more easily explore this extensive dataset, an aerosol classification scheme is developed that identifies the different aerosol types measured during the deployments. This scheme makes use of ancillary data that includes trace gases, 5 chemical composition, aerodynamic particle size and geographic location, all independent of PI-Neph measurements. The PINeph measurements are then grouped according to their ancillary data classifications and the resulting scattering patterns are examined in detail. These results represent the first published airborne measurements of F 11 and −F 12 /F 11 for many common aerosol types. We then explore whether PI-Neph light-scattering measurements alone are sufficient to reconstruct the results of this ancillary data classification algorithm. Principal component analysis (PCA) is used to reduce the dimensionality of the 10 multi-angle PI-Neph scattering data and the individual measurements are examined as a function of ancillary data classification.Clear clustering is observed in the PCA score space, corresponding to the ancillary classification results, suggesting that indeed a strong link exists between the angular scattering measurements and the aerosol type or composition. Two techniques are used to quantify the degree of clustering and it is found that in most case the results of the ancillary data classification can be predicted from PI-Neph measurements alone with better than 85% recall. This result both emphasizes the validity of the ancillary 15 data classification as well as the PI-Neph's ability to distinguish common aerosol types without additional information.

Measurements of particulate matter (PM2.5) chemical composition were carried out in Golden, CO, during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER‐AQ) field study. Chemical composition was dominated by organic compounds, which comprised an average of 75% of the PM2.5 mass throughout the study. Most of the organic matter was secondary (i.e., secondary organic aerosol) and appears to derive predominantly from regional sources, rather than the Denver metropolitan area. The concentration and composition of PM2.5 in Golden were strongly influenced by highly regular wind patterns and the site's close proximity to the mountains (~5 km). This second factor may be the cause of distinct differences between observations in Golden and those in downtown Denver, despite a distance between the sites of only ~15 km. Concentrations of aerosol nitrate, ammonium, and elemental carbon increased significantly during the daytime when the winds were from the northeast, indicating a strong local source for these compounds. Local sources of dust appeared to minimally impact the Golden site, although this was not likely representative of other conditions in the Colorado Front Range. Conversely, dust that had undergone long‐range transport from the southwestern U.S. likely impacted the entire Colorado Front Range, including Golden. During this event, water‐soluble Ca2+ concentrations exceeded 1 µg m−3, and the PM2.5/PM10 ratio reached its lowest level throughout the study. The long‐range transport of wildfire emissions also impacted the Colorado Front Range for 1–2 days during DISCOVER‐AQ. The smoke event was characterized by high concentrations of organics and water‐soluble K+. The results show a complex array of sources, and atmospheric processes influence summertime PM in the Colorado Front Range.

This paper presents the first long-term aerosol speciation analysis in a Mid-Atlantic United States metropolitan area, which is essential for the air quality management agencies in order to revise regulations and reduce human exposure to adverse air quality conditions. The results suggest that although a declining trend in the overall PM2.5 was observed, no significant tendency was observed in the identified sources besides exceptional events such as the impact of wildfires on local air quality and downward contribution from industrial fraction of PM(2.5) after the Steel Mill at Sparrows Point closure in 2012.

The central detector in the MuSun experiment is a pad-plane time projection ionization chamber that operates without gas amplification in deuterium at 31 K; it is used to measure the rate of the muon capture process µ − + d → n + n + ν µ . A new charge-sensitive preamplifier, operated at 140 K, has been developed for this detector. It achieved a resolution of 4.5 keV(D 2 ) or 120 e − RMS with zero detector capacitance at 1.1 µs integration time in laboratory tests. In the experimental environment, the electronic resolution is 10 keV(D 2 ) or 250 e − RMS at a 0.5 µs integration time. The excellent energy resolution of this amplifier has enabled discrimination between signals from muon-catalyzed fusion and muon capture on chemical impurities, which will precisely determine systematic corrections due to these processes. It is also expected to improve the muon tracking and determination of the stopping location.