Michelsen, Hope A.; Campbell, Matthew F.; Johansson, K.O.; Tran, Ich C.; Schrader, Paul E.; Bambha, Ray B.; Cenker, Emre; Hammons, Joshua A.; Zhu, Chenhui; Schaible, Eric; van Buuren, Anthony
We have characterized soot particles measured in situ in a laminar co-flow ethylene-air diffusion flame using small-angle X-ray scattering (SAXS). The analysis includes temperature measurements made with coherent anti-Stokes Raman spectroscopy (CARS) and complements soot volume-fraction and maturity measurements made with laser-induced incandescence (LII). We compared the results of fits to the SAXS measurements using a unified model and a fractal core-shell model. Power-law parameters yielded by the unified model indicate that aggregates of primary particles are in the mass-fractal regime, whereas the primary particles are in the surface-fractal regime in the middle of the flame. Higher and lower in the flame, the primary-particle power-law parameter approaches 4, suggesting smooth primary particles. These trends are consistent with fits using the fractal core-shell model, which indicate that particles have an established core-shell structure in the middle of the flame and are internally homogeneous at higher and lower heights in the flame. Primary-particle size distributions derived using the fractal core-shell model demonstrate excellent agreement with distributions inferred from transmission electron microscopy (TEM) images in the middle of the flame. Higher in the flame, a second small mode appears in the size distributions, suggesting particle fragmentation during oxidation. Surface oxidation would explain (1) aggregate fragmentation and (2) loss of core-shell structure leading to smoother primary-particle surfaces by removal of carbon overlayers. SAXS measurements are much more sensitive to incipient and young soot particles than LII and demonstrate significant volume fraction from particles low in the flame where the LII signal is negligible.
In 2018 13.7 EJ of fuel were consumed by the global commercial aviation industry. Worldwide, demand will increase into the foreseeable future. Developing Sustainable Aviation Fuels (SAFs), with decreased CO2 and soot emissions, will be pivotal to the on-going mitigation efforts against global warming. Minimizing aromatics in aviation fuel is desirable because of the high propensity of aromatics to produce soot during combustion. Because aromatics cause o-rings to swell, they are important for maintaining engine seals, and must be present in at least 8 vol% under ASTM-D7566. Recently, cycloalkanes have been shown to exhibit some o-ring swelling behavior, possibly making them an attractive substitute to decrease the aromatic content of aviation fuel. Cycloalkanes must meet specifications for a number of other physical properties to be compatible with jet fuel, and these properties can vary greatly with the cycloalkane chemical structure, making their selection difficult. Building a database of structure-property relationships (SPR) for cycloalkanes greatly facilitates their furthered inclusion into aviation fuels. The work presented in this paper develops SPRs by building a data set that includes physical properties important to the aviation industry. The physical properties considered are energy density, specific energy, melting point, density, flashpoint, the Hansen solubility parameter, and the yield sooting index (YSI). Further, our data set includes cycloalkanes drawn from the following structural groups: fused cycloalkanes, n-alkylcycloalkanes, branched cycloalkanes, multiple substituted cycloalkanes, and cycloalkanes with different ring sizes. In addition, a select number of cycloalkanes are blended into Jet-A fuel (POSF-10325) at 10 and 30 wt%. Comparison of neat and blended physical properties are presented. One major finding is that ring expanded systems, those with more than six carbons, have excellent potential for inclusion in SAFs. Our data also indicate that polysubstituted cycloalkanes have higher YSI values.
In this report we describe an enhanced methodology for performing stochastic Bayesian inversions of atmospheric trace gas inversions that allows the time variation of model parameters to be inferred. We use measurements of methane atmospheric mixing ratio made in Livermore, California along with atmospheric transport modeling and published prior estmates of emissions to estimate the regional emissions of methane and the temporal variations in inferred bias parameters. We compute Bayesian model evidence and continuous rank probability score to optimize the model with respect to temporal resolution. Using two different emissions inventories, we perform inversions for a series of models with increasing temporal resolution in the model bias representation. We show that temporal variation in the model bias can improve the model fit and can also increase the likelihood that the parameterization is appropriate, as measured by the Baysian model evidence. .
The Arctic Methane, Carbon Aerosols, and Tracers Study was a measurement campaign at the NOAA Barrow Observatory and DOE ARM North Slope of Alaska sites in Barrow that involved the deployment of instruments to measure CH4, black carbon (BC), and source tracers. The campaign ran from September 1, 2014 to September 1, 2016 and was extended until July 30, 2017.
We have made the first continuous measurements of black carbon in Barrow, Alaska at the ARM aerosol- observing site at the NOAA Barrow Observatory using a Single-Particle Soot Photometer (SP2). These data demonstrate that BC particles are extremely small, and a majority of the particles (by number density) are smaller than 0.5 fg, the lower limit of reliability of the SP2. We developed the first numerical model capable of quantitatively reproducing the laser-induced incandescence (LII) and scattering signals produced by the SP2, the industry-standard BC instrument. Our model reproduces the SP2 signal temporally and spectrally and demonstrates that the current SP2 optical design allows substantial contamination of LII on the scattering signal. We ran CAM5-SE in nudged mode, i.e., by constraining the transport used in the model with meteorological data. The results demonstrate the problem observed previously of under-predicting BC at high latitudes. The cause of the discrepancy is currently unknown, but we suspect that it is associated with scavenging and rainout mechanisms.
Concern over Arctic methane (CH 4 ) emissions has increased following recent discoveries of poorly understood sources and predictions that methane emissions from known sources will grow as Arctic temperatures increase. New efforts are required to detect increases and explain sources without being confounded by the multiple sources. Methods for distinguishing different sources are critical. We conducted measurements of atmospheric methane and source tracers and performed baseline global atmospheric modeling to begin assessing the climate impact of changes in atmospheric methane. The goal of this project was to address uncertainties in Arctic methane sources and their potential impact on climate by (1) deploying newly developed trace-gas analyzers for measurements of methane, methane isotopologues, ethane, and other tracers of methane sources in the Barrow, AK, (2) characterizing methane sources using high-resolution atmospheric chemical transport models and tracer measurements, and (3) modeling Arctic climate using the state-of-the-art high- resolution Spectral Element Community Atmosphere Model (CAM-SE).
We have used a Single-Particle Soot Photometer (SP2) to measure time-resolved laser-induced incandescence (LII) and laser scatter from combustion-generated mature soot with a fractal dimension of 1.88 extracted from a burner. We have also made measurements on restructured mature-soot particles with a fractal dimension of 2.3-2.4. We reproduced the LII and laser-scatter temporal profiles with an energy- and mass-balance model, which accounted for heating of particles passed through a CW-laser beam over laser-particle interaction times of ~10. μs. The results demonstrate a strong influence of aggregate size and morphology on LII and scattering signals. Conductive cooling competes with absorptive heating on these time scales; the effects are reduced with increasing aggregate size and fractal dimension. These effects can lead to a significant delay in the onset of the LII signal and may explain an apparent low bias in the SP2 measurements for small particle sizes, particularly for fresh, mature soot. The results also reveal significant perturbations to the measured scattering signal from LII interference and suggest rapid expansion of the aggregates during sublimation.
In this project we have developed atmospheric measurement capabilities and a suite of atmospheric modeling and analysis tools that are well suited for verifying emissions of green- house gases (GHGs) on an urban-through-regional scale. We have for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate atmospheric CO2 . This will allow for the examination of regional-scale transport and distribution of CO2 along with air pollutants traditionally studied using CMAQ at relatively high spatial and temporal resolution with the goal of leveraging emissions verification efforts for both air quality and climate. We have developed a bias-enhanced Bayesian inference approach that can remedy the well-known problem of transport model errors in atmospheric CO2 inversions. We have tested the approach using data and model outputs from the TransCom3 global CO2 inversion comparison project. We have also performed two prototyping studies on inversion approaches in the generalized convection-diffusion context. One of these studies employed Polynomial Chaos Expansion to accelerate the evaluation of a regional transport model and enable efficient Markov Chain Monte Carlo sampling of the posterior for Bayesian inference. The other approach uses de- terministic inversion of a convection-diffusion-reaction system in the presence of uncertainty. These approaches should, in principle, be applicable to realistic atmospheric problems with moderate adaptation. We outline a regional greenhouse gas source inference system that integrates (1) two ap- proaches of atmospheric dispersion simulation and (2) a class of Bayesian inference and un- certainty quantification algorithms. We use two different and complementary approaches to simulate atmospheric dispersion. Specifically, we use a Eulerian chemical transport model CMAQ and a Lagrangian Particle Dispersion Model - FLEXPART-WRF. These two models share the same WRF assimilated meteorology fields, making it possible to perform a hybrid simulation, in which the Eulerian model (CMAQ) can be used to compute the initial condi- tion needed by the Lagrangian model, while the source-receptor relationships for a large state vector can be efficiently computed using the Lagrangian model in its backward mode. In ad- dition, CMAQ has a complete treatment of atmospheric chemistry of a suite of traditional air pollutants, many of which could help attribute GHGs from different sources. The inference of emissions sources using atmospheric observations is cast as a Bayesian model calibration problem, which is solved using a variety of Bayesian techniques, such as the bias-enhanced Bayesian inference algorithm, which accounts for the intrinsic model deficiency, Polynomial Chaos Expansion to accelerate model evaluation and Markov Chain Monte Carlo sampling, and Karhunen-Lo %60 eve (KL) Expansion to reduce the dimensionality of the state space. We have established an atmospheric measurement site in Livermore, CA and are collect- ing continuous measurements of CO2 , CH4 and other species that are typically co-emitted with these GHGs. Measurements of co-emitted species can assist in attributing the GHGs to different emissions sectors. Automatic calibrations using traceable standards are performed routinely for the gas-phase measurements. We are also collecting standard meteorological data at the Livermore site as well as planetary boundary height measurements using a ceilometer. The location of the measurement site is well suited to sample air transported between the San Francisco Bay area and the California Central Valley.
We have measured time-resolved laser-induced incandescence (LII) from combustion-generated mature soot extracted from a burner and (1) coated with oleic acid or (2) coated with oleic acid and then thermally denuded using a thermodenuder. The soot samples were size selected using a differential mobility analyser and characterized with a scanning mobility particle sizer, centrifugal particle mass analyser, and transmission electron microscope. The results demonstrate a strong influence of coatings particle morphology and on the magnitude and temporal evolution of the LII signal. For coated particles higher laser fluences are required to reach LII signal levels comparable to those of uncoated particles. This effect is predominantly attributable to the additional energy needed to vaporize the coating while heating the particle. LII signals are higher and signal decay rates are significantly slower for thermally denuded particles relative to coated or uncoated particles, particularly at low and intermediate laser fluences.
The ionospheric disturbance dynamo signature in geomagnetic variations is investigated using the National Center for Atmospheric Research Thermosphere-Ionosphere-Electrodynamics General Circulation Model. The model results are tested against reference magnetically quiet time observations on 21 June 1993, and disturbance effects were observed on 11 June 1993. The model qualitatively reproduces the observed diurnal and latitude variations of the geomagnetic horizontal intensity and declination for the reference quiet day in midlatitude and low-latitude regions but underestimates their amplitudes. The patterns of the disturbance dynamo signature and its source 'anti-Sq' current system are well reproduced in the Northern Hemisphere. However, the model significantly underestimates the amplitude of disturbance dynamo effects when compared with observations. Furthermore, the largest simulated disturbances occur at different local times than the observations. The discrepancies suggest that the assumed high-latitude storm time energy inputs in the model were not quantitatively accurate for this storm.
Rapid identification of aerosolized biological agents following an alarm by particle triggering systems is needed to enable response actions that save lives and protect assets. Rapid identifiers must achieve species level specificity, as this is required to distinguish disease-causing organisms (e.g., Bacillus anthracis) from benign neighbors (e.g., Bacillus subtilis). We have developed a rapid (1-5 minute), novel identification methodology that sorts intact organisms from each other and particulates using capillary electrophoresis (CE), and detects using near-infrared (NIR) absorbance and scattering. We have successfully demonstrated CE resolution of Bacillus spores and vegetative bacteria at the species level. To achieve sufficient sensitivity for detection needs ({approx}10{sup 4} cfu/mL for bacteria), we have developed fiber-coupled cavity-enhanced absorbance techniques. Using this method, we have demonstrated {approx}two orders of magnitude greater sensitivity than published results for absorbing dyes, and single particle (spore) detection through primarily scattering effects. Results of the integrated CE-NIR system for spore detection are presented.
Recent EPA regulations targeting mercury (Hg) emissions from utility coal boilers have prompted increased activity in the development of reliable chemical sensors for monitoring Hg emissions with high sensitivity, high specificity, and fast time response. We are developing a portable, laser-based instrument for real-time, stand-off detection of Hg emissions that involves exciting the Hg (6 3P1 ← 6 1S0) transition at 253.7 nm and detecting the resulting resonant emission from Hg (6 3P1). The laser for this approach must be tunable over the Hg absorption line at 253.7 nm, while system performance modeling has indicated a desired output pulse energy ≥0.1 μJ and linewidth ≤5 GHz (full width at half-maximum, FWHM). In addition, the laser must have the requisite physical characteristics for use in coal-fired power plants. To meet these criteria, we are pursing a multistage frequency-conversion scheme involving an optical parametric amplifier (OPA). The OPA is pumped by the frequency-doubled output of a passively Q-switched, monolithic Nd:YAG micro-laser operating at 10-Hz repetition rate and is seeded by a 761-nm, cw distributed-feedback diode laser. The resultant pulse-amplified seed beam is frequency tripled in two nonlinear frequency-conversion steps to generate 253.7-nm light. The laser system is mounted on a 45.7 cm × 30.5 cm breadboard and can be further condensed using custom optical mounts. Based on simulations of the nonlinear frequency-conversion processes and current results, we expect this laser architecture to exceed the desired pulse energy. Moreover, this approach provides a compact, all-solid-state source of tunable, narrow-linewidth visible and ultraviolet radiation, which is required for many chemical sensing applications.
The deployment of optical fibers in adverse radiation environments, such as those encountered in a low-Earth-orbit space setting, makes critical the development of an understanding of the effect of large accumulated ionizing-radiation doses on optical components and systems. In particular, gamma radiation is known to considerably affect the performance of optical components by inducing absorbing centers in the materials. Such radiation is present both as primary background radiation and as secondary radiation induced by proton collisions with space-craft material. This paper examines the effects of gamma radiation on erbium-, ytterbium-, and Yb/Er co-doped optical fibers by exposing a suite of such fibers to radiation from a Co-60 source over long periods of time while monitoring the temporal and spectral decrease in transmittance of a reference signal. For same total doses, results show increased photodarkening in erbium-doped fibers relative to ytterbium-doped fibers, as well as significant radiation resistance of the co-doped fibers over wavelengths of 1.0-1.6 microns. All three types of fibers were seen to exhibit dose-rate dependences.
A discussion on an active gas imager that can potentially improve system performance and reliability in Smart Leak Detection and Repair covers conventional single-wavelength imaging; differential imaging; methane detection; modification for detecting fugitive emissions relevant to refineries and chemical plants; and system description. This is an abstract of a paper presented at the AWMA's 99th Annual Conference and Exhibition (New Orleans, LA 6/20-23/2006).
Because many solid objects, both stationary and mobile, will be present in an indoor environment, the design of an indoor aerosol cloud finding lidar (light detection and ranging) instrument presents a number of challenges. The cloud finder must be able to discriminate between these solid objects and aerosol clouds as small as 1-meter in depth in order to probe suspect clouds. While a near IR ({approx}1.5-{micro}m) laser is desirable for eye-safety, aerosol scattering cross sections are significantly lower in the near-IR than at visible or W wavelengths. The receiver must deal with a large dynamic range since the backscatter from solid object will be orders of magnitude larger than for aerosol clouds. Fast electronics with significant noise contributions will be required to obtain the necessary temporal resolution. We have developed a laboratory instrument to detect aerosol clouds in the presence of solid objects. In parallel, we have developed a lidar performance model for performing trade studies. Careful attention was paid to component details so that results obtained in this study could be applied towards the development of a practical instrument. The amplitude and temporal shape of the signal return are analyzed for discrimination of aerosol clouds in an indoor environment. We have assessed the feasibility and performance of candidate approaches for a fieldable instrument. With the near-IR PMT and a 1.5-{micro}m laser source providing 20-{micro}J pulses, we estimate a bio-aerosol detection limit of 3000 particles/l.