Engineering topics
Publications and source records attributed to Imre, D..
Activated cloud droplet fraction versus the below-cloud aerosol hygroscopicity for spring and summer campaigns.
Secondary organic aerosol (SOA) is known to impact both climate and air quality, yet molecular-level composition measurements remain challenging, hampering our understanding of SOA formation and evolution. Here, we reveal the importance of underestimated reaction pathways for the (trans)formation of SOA from monoterpenes, one of the largest SOA precursors globally. Utilizing mass spectrometric techniques to achieve a comprehensive characterization of molecular-level changes in the SOA, we were able to link the appearance of high-molecular weight (HMW) organic molecules to the concentration and level of neutralization of particulate sulfate. Interestingly, this oligomerization coincided with a decrease of highly oxygenated molecules (HOMs). Our findings highlight the role of particle-phase processing, and the underestimated importance of sulfate aerosol for monoterpene-SOA formation. The observations of these processes directly in the atmosphere reveal the need to account for the formation of HMW oligomers to fully understand the physicochemical properties of organic aerosol.
Understanding and modeling the behavior of quartz dust particles, commonly found in the atmosphere, requires knowledge of many relevant particles properties, including particle shape. This study uses a single particle mass spectrometer, a differential mobility analyzer, and an aerosol particle mass analyzer to measure quartz aerosol particles mobility, aerodynamic, and volume equivalent diameters, mass, composition, effective density, and dynamic shape factor as a function of particle size, in both the free molecular and transition flow regimes. The results clearly demonstrate that dynamic shape factors can vary significantly as a function of particle size. For the quartz samples studied here, the dynamic shape factors increase with size, indicating that larger particles are significantly more aspherical than smaller particles. In addition, dynamic shape factors measured in the free-molecular (χv) and transition (χt) flow regimes can be significantly different, and these differences vary with the size of the quartz particles. For quartz, χv of small (d < 200 nm) particles is 1.25, while χv of larger particles (d ~ 440 nm) is 1.6, with a continuously increasing trend with particle size. In contrast χt, of small particles starts at 1.1 increasing slowly to 1.34 for 550 nm diameter particles. The multidimensional particle characterization approach used here goes beyond determination of average properties for each size, to provide additional information about how the particle dynamic shape factor may vary even for particles with the same mass and volume equivalent diameter.
Understanding the effect of aerosols on climate requires knowledge of the size and chemical composition of individual aerosol particles - two fundamental properties that determine an aerosol’s optical properties and ability to serve as cloud condensation or ice nuclei. Here we present miniSPLAT, our new aircraft compatible single particle mass spectrometer, that measures in-situ and in real-time size and chemical composition of individual aerosol particles with extremely high sensitivity, temporal resolution, and sizing precision on the order of a monolayer. miniSPLAT operates in dual data acquisition mode to measure, in addition to single particle size and composition, particle number concentrations, size distributions, density, and asphericity with high temporal resolution. When compared to our previous instrument, SPLAT II, miniSPLAT has been significantly reduced in size, weight, and power consumption without loss in performance. We also present ND-Scope, our newly developed interactive visual analytics software package. ND-Scope is designed to explore and visualize the vast amount of complex, multidimensional data acquired by our single particle mass spectrometers, along with other aerosol and cloud characterization instruments on-board aircraft. We demonstrate that ND-Scope makes it possible to visualize the relationships between different observables and to view the data in a geo-spatial context, using the interactive and fully coupled Google Earth and Parallel Coordinates displays. Here we illustrate the utility of ND-Scope to visualize the spatial distribution of atmospheric particles of different compositions, and explore the relationship between individual particle composition and their activity as cloud condensation nuclei.
Secondary organic aerosols (SOA) dominate atmospheric organic aerosols that affect climate, air quality, and health. Recent studies indicate that, contrary to previously held assumptions, at low relative humidity (RH) these particles are semi-solid and evaporate orders of magnitude slower than expected. Elevated relative humidity has the potential to affect significantly formation, properties, and atmospheric evolution of SOA particles. Here we present a study of the effect of RH on the room-temperature evaporation kinetics of SOA particles formed by ozonolysis of α-pinene and limonene. Experiments were carried out on SOA particles generated, evaporated, and aged at 0%, 50% and 90% RH. We find that in all cases evaporation begins with a relatively fast phase, during which 30% to 70% of the particle mass evaporates in 2 hours, followed by a much slower evaporation rate. Evaporation kinetics at 0% and 50% RH are nearly the same, while at 90% RH a slightly larger fraction evaporates. In all cases, aging the particles prior to inducing evaporation reduces the evaporative losses, with aging at elevated RH leading to more significant effect. In all cases, SOA evaporation is nearly size-independent, providing direct evidence that oligomers play a crucial role in determining the evaporation kinetics.
Gasoline Compression Ignition (GCI) engines have the potential to achieve high fuel efficiency and to significantly reduce both NOx and particulate matter (PM) emissions by operating under dilute partially-premixed conditions. This low temperature combustion strategy is dependent upon direct-injection of gasoline during the compression stroke and potentially near top dead center (TDC). The timing and duration of the in-cylinder injections can be tailored based on speed and load to create optimized conditions that result in a stable combustion. We present the results of advanced aerosol analysis methods that have been used for detailed real-time characterization of PM emitted from a single-cylinder GCI engine operated at different speed, load, timing, and number and duration of near-TDC fuel injections. PM characterization included 28 measurements of size and composition of individual particles sampled directly from the exhaust and after mass and/or mobility classification. We use these data to calculate particle effective density, fractal dimension, dynamic shape factors in free-molecular and transition flow regimes, average diameter of primary spherules, number of spherules, and void fraction of soot agglomerates.
Although the Euclidean distance does well in measuring data distances within high-dimensional clusters, it does poorly when it comes to gauging inter-cluster distances. This significantly impacts the quality of global, low-dimensional space embedding procedures such as the popular multi-dimensional scaling (MDS) where one can often observe non-intuitive layouts. We were inspired by the perceptual processes evoked in the method of parallel coordinates which enables users to visually aggregate the data by the patterns the polylines exhibit across the dimension axes. We call the path of such a polyline its structure and suggest a metric that captures this structure directly in high-dimensional space. This allows us to better gauge the distances of spatially distant data constellations and so achieve data aggregations in MDS plots that are more cognizant of existing high-dimensional structure similarities. Our MDS plots also exhibit similar visual relationships as the method of parallel coordinates which is often used alongside to visualize the high-dimensional data in raw form. We then cast our metric into a bi-scale framework which distinguishes far-distances from near-distances. The coarser scale uses the structural similarity metric to separate data aggregates obtained by prior classification or clustering, while the finer scale employs the appropriate Euclidean distance.
Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a multi field visualization problem, where the geospace provides the expanse of the field. However, there is a limit on the amount of multivariate information that can be fit within a certain spatial location, and the use of linked multivari ate information displays has previously been devised to bridge this gap. In this paper we focus on the interactions in the geographical display, present an implementation that uses Google Earth, and demonstrate it within a tightly linked parallel coordinates display. Several other visual representations, such as pie and bar charts are integrated into the Google Earth display and can be interactively manipulated. Further, we also demonstrate new brushing and visualization techniques for parallel coordinates, such as fixedwindow brushing and correlationenhanced display. We conceived our system with a team of climate researchers, who already made a few important discov eries using it. This demonstrates our system’s great potential to enable scientific discoveries, possibly also in oth er domains where data have a geospatial reference.