Publications

Abstract not provided.

The understanding of soot formation in combustion processes and the optimization of practical combustion systems require in situ measurement techniques that can provide important characteristics, such as particle concentrations and sizes, under a variety of conditions. Of equal importance are techniques suitable for characterizing soot particles produced from incomplete combustion and emitted into the environment. Additionally, the production of engineered nanoparticles, such as carbon blacks, may benefit from techniques that allow for online monitoring of these processes. In this paper, we review the fundamentals and applications of laser-induced incandescence (LII) for particulate diagnostics in a variety of fields. The review takes into account two variants of LII, one that is based on pulsed-laser excitation and has been mainly used in combustion diagnostics and emissions measurements, and an alternate approach that relies on continuous-wave lasers and has become increasingly popular for measuring black carbon in environmental applications. We also review the state of the art in the determination of physical parameters central to the processes that contribute to the non-equilibrium nanoscale heat and mass balances of laser-heated particles; these parameters are important for LII-signal analysis and simulation. Awareness of the significance of particle aggregation and coatings has increased recently, and the effects of these characteristics on the LII technique are discussed. Because of the range of experimental constraints in the variety of applications for which laser-induced incandescence is suited, many implementation approaches have been developed. This review discusses considerations for selection of laser and detection characteristics to address application-specific needs. The benefits of using LII for measurements of a range of nanoparticles in the fields mentioned above are demonstrated with some typical examples, covering simple flames, internal-combustion engines, exhaust emissions, the ambient atmosphere, and nanoparticle production. We also remark on less well-known studies employing LII for particles suspended in liquids. An important aspect of the paper is to critically assess the improvement in the understanding of the fundamental physical mechanisms at the nanoscale and the determination of underlying parameters; we also identify further research needs in these contexts. Building on this enhanced capability in describing the underlying complex processes, LII has become a workhorse of particulate measurement in a variety of fields, and its utility continues to be expanding. When coupled with complementary methods, such as light scattering, probe-sampling, molecular-beam techniques, and other nanoparticle instrumentation, new directions for research and applications with LII continue to materialize.

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.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

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.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.