Rapid cloud removal of dimethyl sulfide oxidation products limits SO2 and cloud condensation nuclei production in the marine atmosphere.

Oceans emit large quantities of dimethyl sulfide (DMS) to the marine atmosphere. The oxidation of DMS leads to the formation and growth of cloud condensation nuclei (CCN) with consequent effects on Earth's radiation balance and climate. The quantitative assessment of the impact of DMS emissions on CCN concentrations necessitates a detailed description of the oxidation of DMS in the presence of existing aerosol particles and clouds. In the unpolluted marine atmosphere, DMS is efficiently oxidized to hydroperoxymethyl thioformate (HPMTF), a stable intermediate in the chemical trajectory toward sulfur dioxide (SO2) and ultimately sulfate aerosol. Using direct airborne flux measurements, we demonstrate that the irreversible loss of HPMTF to clouds in the marine boundary layer determines the HPMTF lifetime (τHPMTF < 2 h) and terminates DMS oxidation to SO2 When accounting for HPMTF cloud loss in a global chemical transport model, we show that SO2 production from DMS is reduced by 35% globally and near-surface (0 to 3 km) SO2 concentrations over the ocean are lowered by 24%. This large, previously unconsidered loss process for volatile sulfur accelerates the timescale for the conversion of DMS to sulfate while limiting new particle formation in the marine atmosphere and changing the dynamics of aerosol growth. This loss process potentially reduces the spatial scale over which DMS emissions contribute to aerosol production and growth and weakens the link between DMS emission and marine CCN production with subsequent implications for cloud formation, radiative forcing, and climate.

Biofuel blending reduces particle emissions from aircraft engines at cruise conditions.

Aviation-related aerosol emissions contribute to the formation of contrail cirrus clouds that can alter upper tropospheric radiation and water budgets, and therefore climate. The magnitude of air-traffic-related aerosol-cloud interactions and the ways in which these interactions might change in the future remain uncertain. Modelling studies of the present and future effects of aviation on climate require detailed information about the number of aerosol particles emitted per kilogram of fuel burned and the microphysical properties of those aerosols that are relevant for cloud formation. However, previous observational data at cruise altitudes are sparse for engines burning conventional fuels, and no data have previously been reported for biofuel use in-flight. Here we report observations from research aircraft that sampled the exhaust of engines onboard a NASA DC-8 aircraft as they burned conventional Jet A fuel and a 50:50 (by volume) blend of Jet A fuel and a biofuel derived from Camelina oil. We show that, compared to using conventional fuels, biofuel blending reduces particle number and mass emissions immediately behind the aircraft by 50 to 70 per cent. Our observations quantify the impact of biofuel blending on aerosol emissions at cruise conditions and provide key microphysical parameters, which will be useful to assess the potential of biofuel use in aviation as a viable strategy to mitigate climate change.

Airborne Emission Rate Measurements Validate Remote Sensing Observations and Emission Inventories of Western U.S. Wildfires.

Carbonaceous emissions from wildfires are a dynamic mixture of gases and particles that have important impacts on air quality and climate. Emissions that feed atmospheric models are estimated using burned area and fire radiative power (FRP) methods that rely on satellite products. These approaches show wide variability and have large uncertainties, and their accuracy is challenging to evaluate due to limited aircraft and ground measurements. Here, we present a novel method to estimate fire plume-integrated total carbon and speciated emission rates using a unique combination of lidar remote sensing aerosol extinction profiles and in situ measured carbon constituents. We show strong agreement between these aircraft-derived emission rates of total carbon and a detailed burned area-based inventory that distributes carbon emissions in time using Geostationary Operational Environmental Satellite FRP observations (Fuel2Fire inventory, slope = 1.33 ± 0.04, r2 = 0.93, and RMSE = 0.27). Other more commonly used inventories strongly correlate with aircraft-derived emissions but have wide-ranging over- and under-predictions. A strong correlation is found between carbon monoxide emissions estimated in situ with those derived from the TROPOspheric Monitoring Instrument (TROPOMI) for five wildfires with coincident sampling windows (slope = 0.99 ± 0.18; bias = 28.5%). Smoke emission coefficients (g MJ-1) enable direct estimations of primary gas and aerosol emissions from satellite FRP observations, and we derive these values for many compounds emitted by temperate forest fuels, including several previously unreported species.

Impact of Alternative Jet Fuels on Engine Exhaust Composition During the 2015 ECLIF Ground-Based Measurements Campaign.

The application of fuels from renewable sources ("alternative fuels") in aviation is important for the reduction of anthropogenic carbon dioxide emissions, but may also attribute to reduced release of particles from jet engines. The present experiment describes ground-based measurements in the framework of the ECLIF (Emission and Climate Impact of Alternative Fuels) campaign using an Airbus A320 (V2527-A5 engines) burning six fuels of chemically different composition. Two reference Jet A-1 with slightly different chemical parameters were applied and further used in combination with a Fischer-Tropsch synthetic paraffinic kerosene (FT-SPK) to prepare three semi synthetic jet fuels (SSJF) of different aromatic content. In addition, one commercially available fully synthetic jet fuel (FSJF) featured the lowest aromatic content of the fuel selection. Neither the release of nitrogen oxide or carbon monoxide was significantly affected by the different fuel composition. The measured particle emission indices showed a reduction up to 50% (number) and 70% (mass) for two alternative jet fuels (FSJF, SSJF2) at low power settings in comparison to the reference fuels. The reduction is less pronounced at higher operating conditions but the release of particle number and particle mass is still significantly lower for the alternative fuels than for both reference fuels. The observed correlation between emitted particle mass and fuel aromatics is not strict. Here, the H/C ratio is a better indicator for soot emission.

Worldwide data sets constrain the water vapor uptake coefficient in cloud formation.

Cloud droplet formation depends on the condensation of water vapor on ambient aerosols, the rate of which is strongly affected by the kinetics of water uptake as expressed by the condensation (or mass accommodation) coefficient, αc. Estimates of αc for droplet growth from activation of ambient particles vary considerably and represent a critical source of uncertainty in estimates of global cloud droplet distributions and the aerosol indirect forcing of climate. We present an analysis of 10 globally relevant data sets of cloud condensation nuclei to constrain the value of αc for ambient aerosol. We find that rapid activation kinetics (αc > 0.1) is uniformly prevalent. This finding resolves a long-standing issue in cloud physics, as the uncertainty in water vapor accommodation on droplets is considerably less than previously thought.

The development and validation of the major life changing decision profile (MLCDP).

BACKGROUND: Chronic diseases may influence patients taking major life changing decisions (MLCDs) concerning for example education, career, relationships, having children and retirement. A validated measure is needed to evaluate the impact of chronic diseases on MLCDs, improving assessment of their life-long burden. The aims of this study were to develop a validated questionnaire, the "Major Life Changing Decision Profile" (MLCDP) and to evaluate its psychometric properties. METHODS: 50 interviews with dermatology patients and 258 questionnaires, completed by cardiology, rheumatology, nephrology, diabetes and respiratory disorder patients, were analysed for qualitative data using Nvivo8 software. Content validation was carried out by a panel of experts. The first version of the MLCDP was completed by 210 patients and an iterative process of multiple Exploratory Factor Analyses and item prevalence was used to guide item reduction. Face validity and practicability was assessed by patients. RESULTS: 48 MLCDs were selected from analysis of the transcripts and questionnaires for the first version of the MLCDP, and reduced to 45 by combination of similar themes. There was a high intraclass correlation coefficient (0.7) between the 13 members of the content validation panel. Four more items were deleted leaving a 41-item MLCDP that was completed by 210 patients. The most frequently recorded MLCDs were decisions to change eating habits (71.4%), to change smoking/drinking alcohol habits (58.5%) and not to travel or go for holidays abroad (50.9%).Factor analysis suggested item number reduction from 41 to 34, to 29, then 23 items. However after taking into account item prevalence data as well as factor analysis results, 32 items were retained. The 32-item MLCDP has five domains education (3 items), job/career (9), family/relationships (5), social (10) and physical (5). The MLCDP score is expressed as the absolute number of decisions that have been affected. CONCLUSIONS: The 32-item (5 domains) MLCDP has been developed as an easy to complete generic tool for use in clinical practice and for quality of life and epidemiological research. Further validation is required.

Virus infection of phytoplankton increases average molar mass and reduces hygroscopicity of aerosolized organic matter.

Viral infection of phytoplankton is a pervasive mechanism of cell death and bloom termination, which leads to the production of dissolved and colloidal organic matter that can be aerosolized into the atmosphere. Earth-observing satellites can track the growth and death of phytoplankton blooms on weekly time scales but the impact of viral infection on the cloud forming potential of associated aerosols is largely unknown. Here, we determine the influence of viral-derived organic matter, purified viruses, and marine hydrogels on the cloud condensation nuclei activity of their aerosolized solutions, compared to organic exudates from healthy phytoplankton. Dissolved organic material derived from exponentially growing and infected cells of well-characterized eukaryotic phytoplankton host-virus systems, including viruses from diatoms, coccolithophores and chlorophytes, was concentrated, desalted, and nebulized to form aerosol particles composed of primarily of organic matter. Aerosols from infected phytoplankton cultures resulted in an increase in critical activation diameter and average molar mass in three out of five combinations evaluated, along with a decrease in organic kappa (hygroscopicity) compared to healthy cultures and seawater controls. The infected samples also displayed evidence of increased surface tension depression at realistic cloud water vapor supersaturations. Amending the samples with xanthan gum to simulate marine hydrogels increased variability in organic kappa and surface tension in aerosols with high organic to salt ratios. Our findings suggest that the pulses of increased dissolved organic matter associated with viral infection in surface waters may increase the molar mass of dissolved organic compounds relative to surface waters occupied by healthy phytoplankton or low phytoplankton biomass.

Multi-campaign ship and aircraft observations of marine cloud condensation nuclei and droplet concentrations.

In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP2EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosol-cloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates.

CCN spectra, hygroscopicity, and droplet activation kinetics of secondary organic aerosol resulting from the 2010 Deepwater Horizon oil spill.

Secondary organic aerosol (SOA) resulting from the oxidation of organic species emitted by the Deepwater Horizon oil spill were sampled during two survey flights conducted by a National Oceanic and Atmospheric Administration WP-3D aircraft in June 2010. A new technique for fast measurements of cloud condensation nuclei (CCN) supersaturation spectra called Scanning Flow CCN Analysis was deployed for the first time on an airborne platform. Retrieved CCN spectra show that most particles act as CCN above (0.3 ± 0.05)% supersaturation, which increased to (0.4 ± 0.1)% supersaturation for the most organic-rich aerosol sampled. The aerosol hygroscopicity parameter, κ, was inferred from both measurements of CCN activity and from humidified-particle light extinction, and varied from 0.05 to 0.10 within the emissions plumes. However, κ values were lower than expected from chemical composition measurements, indicating a degree of external mixing or size-dependent chemistry, which was reconciled assuming bimodal, size-dependent composition. The CCN droplet effective water uptake coefficient, γ(cond), was inferred from the data using a comprehensive instrument model, and no significant delay in droplet activation kinetics from the presence of organics was observed, despite a large fraction of hydrocarbon-like SOA present in the aerosol.

Beyond the Ångström Exponent: Probing Additional Information in Spectral Curvature and Variability of In Situ Aerosol Hyperspectral (0.3-0.7 µm) Optical Properties.

Ångström exponents (α) allow reconstruction of aerosol optical spectra over a broad range of wavelengths from measurements at two or more wavelengths. Hyperspectral measurements of atmospheric aerosols provide opportunities to probe measured spectra for information inaccessible from only a few wavelengths. Four sets of hyperspectral in situ aerosol optical coefficients (aerosol-phase total extinction, σ ext, and absorption, σ abs; liquid-phase soluble absorption from methanol, σ MeOH-abs, and water, σ DI-abs, extracts) were measured from biomass burning aerosols (BBAs). Hyperspectral single scattering albedo (ω), calculated from σ ext and σ abs, provide spectral resolution over a wide spectral range rare for this optical parameter. Observed spectral shifts between σ abs and σ MeOH-abs/σ DI-abs argue in favor of measuring σ abs rather than reconstructing it from liquid extracts. Logarithmically transformed spectra exhibited curvature better fit by second-order polynomials than linear α. Mapping second order fit coefficients (a 1, a 2) revealed samples from a given fire tended to cluster together, that is, aerosol spectra from a given fire were similar to each other and somewhat distinct from others. Separation in (a 1, a 2) space for spectra with the same α suggest additional information in second-order parameterization absent from the linear fit. Spectral features found in the fit residuals indicate more information in the measured spectra than captured by the fits. Above-detection σ MeOH-abs at 0.7 µm suggests assuming all absorption at long visible wavelengths is BC to partition absorption between BC and brown carbon (BrC) overestimates BC and underestimates BrC across the spectral range. Hyperspectral measurements may eventually discriminate BBA among fires in different ecosystems under variable conditions.

Combined optical and X-ray tomosynthesis breast imaging.

PURPOSE: To explore the optical and physiologic properties of normal and lesion-bearing breasts by using a combined optical and digital breast tomosynthesis (DBT) imaging system. MATERIALS AND METHODS: Institutional review board approval and patient informed consent were obtained for this HIPAA-compliant study. Combined optical and tomosynthesis imaging analysis was performed in 189 breasts from 125 subjects (mean age, 56 years ± 13 [standard deviation]), including 138 breasts with negative findings and 51 breasts with lesions. Three-dimensional (3D) maps of total hemoglobin concentration (Hb(T)), oxygen saturation (So(2)), and tissue reduced scattering coefficients were interpreted by using the coregistered DBT images. Paired and unpaired t tests were performed between various tissue types to identify significant differences. RESULTS: The estimated average bulk Hb(T) from 138 normal breasts was 19.2 µmol/L. The corresponding mean So(2) was 0.73, within the range of values in the literature. A linear correlation (R = 0.57, P < .0001) was found between Hb(T) and the fibroglandular volume fraction derived from the 3D DBT scans. Optical reconstructions of normal breasts revealed structures corresponding to chest-wall muscle, fibroglandular, and adipose tissues in the Hb(T), So(2), and scattering images. In 26 malignant tumors of 0.6-2.5 cm in size, Hb(T) was significantly greater than that in the fibroglandular tissue of the same breast (P = .0062). Solid benign lesions (n = 17) and cysts (n = 8) had significantly lower Hb(T) contrast than did the malignant lesions (P = .025 and P = .0033, respectively). CONCLUSION: The optical and DBT images were structurally consistent. The malignant tumors and benign lesions demonstrated different Hb(T) and scattering contrasts, which can potentially be exploited to reduce the false-positive rate of conventional mammography and unnecessary biopsies.

Aerosol responses to precipitation along North American air trajectories arriving at Bermuda.

North American pollution outflow is ubiquitous over the western North Atlantic Ocean, especially in winter, making this location a suitable natural laboratory for investigating the impact of precipitation on aerosol particles along air mass trajectories. We take advantage of observational data collected at Bermuda to seasonally assess the sensitivity of aerosol mass concentrations and volume size distributions to accumulated precipitation along trajectories (APT). The mass concentration of particulate matter with aerodynamic diameter less than 2.5 µm normalized by the enhancement of carbon monoxide above background (PM2.5/ΔCO) at Bermuda was used to estimate the degree of aerosol loss during transport to Bermuda. Results for December-February (DJF) show that most trajectories come from North America and have the highest APTs, resulting in a significant reduction (by 53 %) in PM2.5/ΔCO under high-APT conditions (> 13.5 mm) relative to low-APT conditions (< 0.9 mm). Moreover, PM2.5/ΔCO was most sensitive to increases in APT up to 5 mm (-0.044 µg m-3 ppbv-1 mm-1) and less sensitive to increases in APT over 5 mm. While anthropogenic PM2.5 constituents (e.g., black carbon, sulfate, organic carbon) decrease with high APT, sea salt, in contrast, was comparable between high- and low-APT conditions owing to enhanced local wind and sea salt emissions in high-APT conditions. The greater sensitivity of the fine-mode volume concentrations (versus coarse mode) to wet scavenging is evident from AErosol RObotic NETwork (AERONET) volume size distribution data. A combination of GEOS-Chem model simulations of the 210Pb submicron aerosol tracer and its gaseous precursor 222Rn reveals that (i) surface aerosol particles at Bermuda are most impacted by wet scavenging in winter and spring (due to large-scale precipitation) with a maximum in March, whereas convective scavenging plays a substantial role in summer; and (ii) North American 222Rn tracer emissions contribute most to surface 210Pb concentrations at Bermuda in winter (~75 %-80 %), indicating that air masses arriving at Bermuda experience large-scale precipitation scavenging while traveling from North America. A case study flight from the ACTIVATE field campaign on 22 February 2020 reveals a significant reduction in aerosol number and volume concentrations during air mass transport off the US East Coast associated with increased cloud fraction and precipitation. These results highlight the sensitivity of remote marine boundary layer aerosol characteristics to precipitation along trajectories, especially when the air mass source is continental outflow from polluted regions like the US East Coast.

Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors.

Cloud drop number concentrations (N d) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosol optical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak in spring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing N d on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH), low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-N d days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-N d days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing N d to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to N d for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol-N d relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of N d.

Characterization of masses in digital breast tomosynthesis: comparison of machine learning in projection views and reconstructed slices.

PURPOSE: In digital breast tomosynthesis (DBT), quasi-three-dimensional (3D) structural information is reconstructed from a small number of 2D projection view (PV) mammograms acquired over a limited angular range. The authors developed preliminary computer-aided diagnosis (CADx) methods for classification of malignant and benign masses and compared the effectiveness of analyzing lesion characteristics in the reconstructed DBT slices and in the PVs. METHODS: A data set of MLO view DBT of 99 patients containing 107 masses (56 malignant and 51 benign) was collected at the Massachusetts General Hospital with IRB approval. The DBTs were obtained with a GE prototype system which acquired 11 PVs over a 50 degree arc. The authors reconstructed the DBTs at 1 mm slice interval using a simultaneous algebraic reconstruction technique. The region of interest (ROI) containing the mass was marked by a radiologist in the DBT volume and the corresponding ROIs on the PVs were derived based on the imaging geometry. The subsequent processes were fully automated. For classification of masses using the DBT-slice approach, the mass on each slice was segmented by an active contour model initialized with adaptive k-means clustering. A spiculation likelihood map was generated by analysis of the gradient directions around the mass margin and spiculation features were extracted from the map. The rubber band straightening transform (RBST) was applied to a band of pixels around the segmented mass boundary. The RBST image was enhanced by Sobel filtering in the horizontal and vertical directions, from which run-length statistics texture features were extracted. Morphological features including those from the normalized radial length were designed to describe the mass shape. A feature space composed of the spiculation features, texture features, and morphological features extracted from the central slice alone and seven feature spaces obtained by averaging the corresponding features from three to 19 slices centered at the central slice were compared. For classification of masses using the PV approach, a feature extraction process similar to that described above for the DBT approach was performed on the ROIs from the individual PVs. Six feature spaces obtained from the central PV alone and by averaging the corresponding features from three to 11 PVs were formed. In each feature space for either the DBT-slice or the PV approach, a linear discriminant analysis classifier with stepwise feature selection was trained and tested using a two-loop leave-one-case-out resampling procedure. Simplex optimization was used to guide feature selection automatically within the training set in each leave-one-case-out cycle. The performance of the classifiers was evaluated by the area (Az) under the receiver operating characteristic curve. RESULTS: The test Az values from the DBT-slice approach ranged from 0.87 +/- 0.03 to 0.93 +/- 0.02, while those from the PV approach ranged from 0.78 +/- 0.04 to 0.84 +/- 0.04. The highest test Az of 0.93 +/- 0.02 from the nine-DBT-slice feature space was significantly (p = 0.006) better than the highest test Az of 0.84 +/- 0.04 from the nine-PV feature space. CONCLUSION: The features of breast lesions extracted from the DBT slices consistently provided higher classification accuracy than those extracted from the PV images.

Coupling an online ion conductivity measurement with the particle-into-liquid sampler: Evaluation and modeling using laboratory and field aerosol data.

A particle-into-liquid sampler (PILS) was coupled to a flow-through conductivity cell to provide a continuous, nondestructive, online measurement in support of offline ion chromatography analysis. The conductivity measurement provides a rapid assessment of the total ion concentration augmenting slower batch-sample data from offline analysis and is developed primarily to assist airborne measurements, where fast time-response is essential. A conductivity model was developed for measured ions and excellent closure was derived for laboratory-generated aerosols (97% conductivity explained, R2 > 0.99). The PILS-conductivity measurement was extensively tested throughout the NASA Cloud, Aerosol and Monsoon Processes: Philippines Experiment (CAMP2Ex) during nineteen research flights. A diverse range of ambient aerosol was sampled from biomass burning, fresh and aged urban pollution, and marine sources. Ambient aerosol did not exhibit the same degree of closure as the laboratory aerosol, with measured ions only accountable for 43% of the conductivity. The remaining fraction of the conductivity was examined in combination with ion charge balance and found to provide additional supporting information for diagnosing and modeling particle acidity. An urban plume case study was used to demonstrate the utility of the measurement for supplementing compositional data and augmenting the temporal capability of the PILS.

Investigation of factors controlling PM2.5 variability across the South Korean Peninsula during KORUS-AQ.

The Korea - United States Air Quality Study (May - June 2016) deployed instrumented aircraft and ground-based measurements to elucidate causes of poor air quality related to high ozone and aerosol concentrations in South Korea. This work synthesizes data pertaining to aerosols (specifically, particulate matter with aerodynamic diameters <2.5 micrometers, PM2.5) and conditions leading to violations of South Korean air quality standards (24-hr mean PM2.5 < 35 µg m-3). PM2.5 variability from AirKorea monitors across South Korea is evaluated. Detailed data from the Seoul vicinity are used to interpret factors that contribute to elevated PM2.5. The interplay between meteorology and surface aerosols, contrasting synoptic-scale behavior vs. local influences, is presented. Transboundary transport from upwind sources, vertical mixing and containment of aerosols, and local production of secondary aerosols are discussed. Two meteorological periods are probed for drivers of elevated PM2.5. Clear, dry conditions, with limited transport (Stagnant period), promoted photochemical production of secondary organic aerosol from locally emitted precursors. Cloudy humid conditions fostered rapid heterogeneous secondary inorganic aerosol production from local and transported emissions (Transport/Haze period), likely driven by a positive feedback mechanism where water uptake by aerosols increased gas-to-particle partitioning that increased water uptake. Further, clouds reduced solar insolation, suppressing mixing, exacerbating PM2.5 accumulation in a shallow boundary layer. The combination of factors contributing to enhanced PM2.5 is challenging to model, complicating quantification of contributions to PM2.5 from local versus upwind precursors and production. We recommend co-locating additional continuous measurements at a few AirKorea sites across South Korea to help resolve this and other outstanding questions: carbon monoxide/carbon dioxide (transboundary transport tracer), boundary layer height (surface PM2.5 mixing depth), and aerosol composition with aerosol liquid water (meteorologically-dependent secondary production). These data would aid future research to refine emissions targets to further improve South Korean PM2.5 air quality.

Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms.

PURPOSE: The authors develop a practical, iterative algorithm for image-reconstruction in undersampled tomographic systems, such as digital breast tomosynthesis (DBT). METHODS: The algorithm controls image regularity by minimizing the image total p variation (TpV), a function that reduces to the total variation when p = 1.0 or the image roughness when p = 2.0. Constraints on the image, such as image positivity and estimated projection-data tolerance, are enforced by projection onto convex sets. The fact that the tomographic system is undersampled translates to the mathematical property that many widely varied resultant volumes may correspond to a given data tolerance. Thus the application of image regularity serves two purposes: (1) Reduction in the number of resultant volumes out of those allowed by fixing the data tolerance, finding the minimum image TpV for fixed data tolerance, and (2) traditional regularization, sacrificing data fidelity for higher image regularity. The present algorithm allows for this dual role of image regularity in undersampled tomography. RESULTS: The proposed image-reconstruction algorithm is applied to three clinical DBT data sets. The DBT cases include one with microcalcifications and two with masses. CONCLUSIONS: Results indicate that there may be a substantial advantage in using the present image-reconstruction algorithm for microcalcification imaging.

Detecting nonpalpable recurrent breast cancer: the role of routine mammographic screening of transverse rectus abdominis myocutaneous flap reconstructions.

PURPOSE: To perform a retrospective cohort study to determine the rates of recall and cancer detection and then to develop a decision analytic model to evaluate the effectiveness of routine screening of transverse rectus abdominis myocutaneous (TRAM) flap reconstructions. MATERIALS AND METHODS: This study was approved by the institutional review board, and the methods comply with HIPAA regulations. A retrospective search of the institutional mammographic results database was done to identify bilateral screening mammographic examinations obtained from January 1, 1999, through July 15, 2005. The search included the term TRAM; the recall and cancer detetion rates were then detected. Subsequently, a decision analytic model was constructed to evaluate a hypothetical cohort of women with TRAM flap reconstructions. RESULTS: Of 554 mammograms (265 TRAM flap reconstructions), 546 (98.6%) had negative results (Breast Imaging Reporting and Data System category 1 or 2). Eight (1.4%) had positive test results (Breast Imaging Reporting and Data System category 0, 3, 4, or 5). All suspicious lesions underwent biopsy and had benign pathologic results. No interval breast cancers were identified. The detection rate for nonpalpable recurrent breast cancer was 0% (exact 95% confidence interval: 0.0%, 1.4%). According to decision analysis, screening would help detect an estimated 12 additional recurrent cancers per 1000 women screened, providing an additional 1.6 days of life expectancy for the screened cohort. Under base-case conditions, screening of TRAM flap reconstructions is less effective than screening asymptomatic women in their 40s. Sensitivity analysis revealed that a benefit equivalent to that of screening asymptomatic women in their 40s was achievable under conditions related to estimates of screening effectiveness and cancer detection rate. CONCLUSION: Routine screening mammography of TRAM flap reconstructions has a very low detection rate for nonpalpable recurrent breast cancer. Decision analysis indicates that screening such women is less effective than screening asymptomatic women in their 40s for primary breast cancer.

Computer-aided detection of masses in digital tomosynthesis mammography: comparison of three approaches.

The authors are developing a computer-aided detection (CAD) system for masses on digital breast tomosynthesis mammograms (DBT). Three approaches were evaluated in this study. In the first approach, mass candidate identification and feature analysis are performed in the reconstructed three-dimensional (3D) DBT volume. A mass likelihood score is estimated for each mass candidate using a linear discriminant analysis (LDA) classifier. Mass detection is determined by a decision threshold applied to the mass likelihood score. A free response receiver operating characteristic (FROC) curve that describes the detection sensitivity as a function of the number of false positives (FPs) per breast is generated by varying the decision threshold over a range. In the second approach, prescreening of mass candidate and feature analysis are first performed on the individual two-dimensional (2D) projection view (PV) images. A mass likelihood score is estimated for each mass candidate using an LDA classifier trained for the 2D features. The mass likelihood images derived from the PVs are backprojected to the breast volume to estimate the 3D spatial distribution of the mass likelihood scores. The FROC curve for mass detection can again be generated by varying the decision threshold on the 3D mass likelihood scores merged by backprojection. In the third approach, the mass likelihood scores estimated by the 3D and 2D approaches, described above, at the corresponding 3D location are combined and evaluated using FROC analysis. A data set of 100 DBT cases acquired with a GE prototype system at the Breast Imaging Laboratory in the Massachusetts General Hospital was used for comparison of the three approaches. The LDA classifiers with stepwise feature selection were designed with leave-one-case-out resampling. In FROC analysis, the CAD system for detection in the DBT volume alone achieved test sensitivities of 80% and 90% at average FP rates of 1.94 and 3.40 per breast, respectively. With the 2D detection approach, the FP rates were 2.86 and 4.05 per breast, respectively, at the corresponding sensitivities. In comparison, the average FP rates of the system combining the 3D and 2D information were 1.23 and 2.04 per breast, respectively, at 80% and 90% sensitivities. The difference in the detection performances between the 2D and the 3D approach, and that between the 3D and the combined approach were both statistically significant (p = 0.02 and 0.01, respectively) as estimated by alternative FROC analysis. The combined system is a promising approach to improving automated mass detection on DBTs.

Analysis of the mammographic and sonographic features of pseudoangiomatous stromal hyperplasia.

OBJECTIVE: The purpose of this study was to describe the imaging findings in 149 patients with pseudoangiomatous stromal hyperplasia (PASH) who had undergone at least 4 years of clinical follow-up for detection of subsequent malignancy. CONCLUSION: PASH is a common entity that presents with benign imaging features without evidence of subsequent malignant potential. At our institution, in the absence of suspicious features a diagnosis of PASH at core biopsy is considered sufficient, and surgical excision has been obviated.