Ambient Observations of Sub-1.0 Hygroscopic Growth Factor and F(RH) Values: Case Studies from Surface and Airborne Measurements

This study reports on the first set of ambient observations of sub-1.0 hygroscopicity values (i.e., growth factor, ratio of humidified-to-dry diameter, GF=Dp,wet/Dp,dry and f(RH), ratio of humidified-to-dry scattering coefficients, less than 1) with consistency across different instruments, regions, and platforms. We utilized data from a shipboard humidified tandem differential mobility analyzer (HTDMA) during Eastern Pacific Emitted Aerosol Cloud Experiment (E-PEACE) in 2011, multiple instruments on the DC-8 aircraft during Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) in 2013, as well as the Differential Aerosol Sizing and Hygroscopicity Spectrometer Probe (DASH-SP) during measurement intensives during Summer 2014 and Winter 2015 in Tucson, Arizona. Sub-1.0 GFs were observed across the range of relative humidity (RH) investigated (75-95%), and did not show a RH-dependent trend in value below 1.0 or frequency of occurrence. A commonality between suppressed hygroscopicity in these experiments, including sub-1.0 GF, was the presence of smoke. Evidence of externally mixed aerosol, and thus multiple GFs, was observed during smoke periods resulting in at least one mode with GF < 1. Time periods during which the DASH-SP detected externally mixed aerosol coincide with sub-1.0 f(RH) observations. Mechanisms responsible for sub-1.0 hygroscopicity are discussed and include refractive index (RI) modifications due to aqueous processing, particle restructuring, and volatilization effects. To further investigate ambient observations of sub-1.0 GFs, f(RH), and particle restructuring, modifying hygroscopicity instruments with pre-humidification modules is recommended

Advances in the Projective Dynamics Method: A Procedure of Discretizing the Space applied to Markovian Processes

AbstractThe projection of a continuous space process to a discrete space process via the transition rates between neighboring bins allows us to relate a master equation to a solution of a stochastic differential equation. The presented method is formulated in its general form for the first time and tested with the Brownian Diffusion process of noninteracting particles with white noise in simple one-dimensional potentials. The comparison of the first passage time obtained with Projective Dynamics, Brownian motion simulations and analytical solutions show the accuracy of this method as well as a wide independence of the particular choice of the binning process

Is there an aerosol signature of chemical cloud processing?

The formation of sulfate and secondary organic aerosol mass in the aqueous phase (aqSOA) of cloud and fog droplets can significantly contribute to ambient aerosol mass. While tracer compounds give evidence that aqueous-phase processing occurred, they do not reveal the extent to which particle properties have been modified in terms of mass, chemical composition, hygroscopicity, and oxidation state. We analyze data from several field experiments and model studies for six air mass types (urban, biogenic, marine, wild fire biomass burning, agricultural biomass burning, and background air) using aerosol size and composition measurements for particles 13&ndash;850&thinsp;nm in diameter. We focus on the trends of changes in mass, hygroscopicity parameter &kappa;, and oxygen-to-carbon (O&thinsp;∕&thinsp;C) ratio due to chemical cloud processing. We find that the modification of these parameters upon cloud processing is most evident in urban, marine, and biogenic air masses, i.e., air masses that are more polluted than very clean air (background air) but cleaner than heavily polluted plumes as encountered during biomass burning. Based on these trends, we suggest that the mass ratio (Rtot) of the potential aerosol sulfate and aqSOA mass to the initial aerosol mass can be used to predict whether chemical cloud processing will be detectable. Scenarios in which this ratio exceeds Rtot&sim;0.5 are the most likely ones in which clouds can significantly change aerosol parameters. It should be noted that the absolute value of Rtot depends on the considered size range of particles. Rtot is dominated by the addition of sulfate (Rsulf) in all scenarios due to the more efficient conversion of SO2 to sulfate compared to aqSOA formation from organic gases. As the formation processes of aqSOA are still poorly understood, the estimate of RaqSOA is likely associated with large uncertainties. Comparison to Rtot values as calculated for ambient data at different locations validates the applicability of the concept to predict a chemical cloud-processing signature in selected air masses.</p

In situ measurements of water uptake by black carbon-containing aerosol in wildfire plumes

Water uptake by black carbon (BC)-containing aerosol was quantified in North American wildfire plumes of varying age (1 to ~40 h old) sampled during the SEAC4RS mission (2013). A Humidified Dual SP2 (HD-SP2) is used to optically size BC-containing particles under dry and humid conditions from which we extract the hygroscopicity parameter, κ, of materials internally mixed with BC. Instrumental variability and the uncertainty of the technique are briefly discussed. An ensemble average κ of 0.04 is found for the set of plumes sampled, consistent with previous estimates of bulk aerosol hygroscopicity from biomass burning sources. The temporal evolution of κ in the Yosemite Rim Fire plume is explored to constrain the rate of conversion of BC-containing aerosol from hydrophobic to more hydrophilic modes in these emissions. A BC-specific κ increase of ~0.06 over 40 h is found, fit well with an exponential curve corresponding to a transition from a κ of 0 to a κ of ~0.09 with an e-folding time of 29 h. Although only a few percent of wildfire particles contain BC, a similar κ increase is estimated for bulk aerosol and the measured aerosol composition is used to infer that the observed κ change is driven by a combination of incorporation of ammonium sulfate and oxidation of existing organic materials. Finally, a substantial fraction of wildfire-generated BC-containing aerosol is calculated to be active as cloud condensation nuclei shortly after emission likely indicating efficient wet removal. These results can constrain model treatment of BC from wildfire sources

Eastern Pacific Emitted Aerosol Cloud Experiment

Aerosol–cloud–radiation interactions are widely held to be the largest single source of uncertainty in climate model projections of future radiative forcing due to increasing anthropogenic emissions. The underlying causes of this uncertainty among modeled predictions of climate are the gaps in our fundamental understanding of cloud processes. There has been significant progress with both observations and models in addressing these important questions but quantifying them correctly is nontrivial, thus limiting our ability to represent them in global climate models. The Eastern Pacific Emitted Aerosol Cloud Experiment (E-PEACE) 2011 was a targeted aircraft campaign with embedded modeling studies, using the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft and the research vessel Point Sur in July and August 2011 off the central coast of California, with a full payload of instruments to measure particle and cloud number, mass, composition, and water uptake distributions. EPEACE used three emitted particle sources to separate particle-induced feedbacks from dynamical variability, namely 1) shipboard smoke-generated particles with 0.05–1-μm diameters (which produced tracks measured by satellite and had drop composition characteristic of organic smoke), 2) combustion particles from container ships with 0.05–0.2-μm diameters (which were measured in a variety of conditions with droplets containing both organic and sulfate components), and 3) aircraft-based milled salt particles with 3–5-μm diameters (which showed enhanced drizzle rates in some clouds). The aircraft observations were consistent with past large-eddy simulations of deeper clouds in ship tracks and aerosol– cloud parcel modeling of cloud drop number and composition, providing quantitative constraints on aerosol effects on warm-cloud microphysics

Identifying chemical aerosol signatures using optical suborbital observations: how much can optical properties tell us about aerosol composition

Improvements in air quality and Earth\u27s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine aerosol composition measurements from ground-based networks are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, an airborne field campaign carried out over the US during the summer of 2013). We find distinct optical signatures for AMTs such as biomass burning (from agricultural or wildfires), biogenic and polluted dust. We find that all four AMTs, studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from a few combinations of airborne in situ aerosol optical properties (e.g., extinction Ångström exponent, absorption Ångström exponent and real refractive index). However, we find that the optically based classifications for biomass burning from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results related to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol dataset to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosols, Cloud, Convection and Precipitation (ACCP) designated observables)

A cloud detection neural network for above-aircraft clouds using airborne cameras

For aerosol, cloud, land, and ocean remote sensing, the development of accurate cloud detection methods, or cloud masks, is extremely important. For airborne passive remotesensing, it is also important to identify when clouds are above the aircraft since their presence contaminates the measurements of nadir-viewing passive sensors. We describe the development of a camera-based approach to detecting clouds above the aircraft via a convolutional neural network called the cloud detection neural network (CDNN). We quantify the performance of this CDNN using human-labeled validation data where we report 96% accuracy in detecting clouds in testing datasets for both zenith viewing and forward-viewing models. We present results from the CDNN based on airborne imagery from the NASA Aerosol Cloud meteorology Interactions oVer the western Atlantic Experiment (ACTIVATE) and the Clouds, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex). We quantify the ability of the CDNN to identify the presence of clouds above the aircraft using a forward-looking camera mounted inside the aircraft cockpit compared to the use of an all-sky upward-looking camera that is mounted outside the fuselage on top of the aircraft. We assess our performance by comparing the flight-averaged cloud fraction of zenith and forward CDNN retrievals with that of the prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S) instrument’s cloud optical depth data. A comparison of the CDNN with the SPN-S on time-specific intervals resulted in 93% accuracy for the zenith viewing CDNN and 84% for the forward-viewing CDNN. The comparison of the CDNNs with the SPN-S on flight-averaged cloud fraction resulted in an agreement of .15 for the forward CDNN and .07 for the zenith CDNN. For CAMP2Ex, 53% of flight dates had above-aircraft cloud fraction above 50%, while for ACTIVATE, 52% and 54% of flight dates observed above-aircraft cloud fraction above 50% for 2020 and 2021, respectively. The CDNN enables cost-effective detection of clouds above the aircraft using an inexpensive camera installed in the cockpit for airborne science research flights where there are no dedicated upward-looking instruments for cloud detection, the installation of which requires time-consuming and expensive aircraft modifications, in addition to added mission cost and complexity of operating additional instruments

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty