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Prather, Kimberly A.

Publications and source records attributed to Prather, Kimberly A..

Bioaerosols are the dominant source of warm-temperature immersion-mode INPs and drive uncertainties in INP predictability

Ice-nucleating particles (INPs) are rare atmospheric aerosols that initiate primary ice formation, but accurately simulating their concentrations and variability in large-scale climate models remains a challenge. Doing so requires both simulating major particle sources and parameterizing their ice nucleation (IN) efficiency. Validating and improving model predictions of INP concentrations requires measuring their concentrations delineated by particle type. We present a method to speciate INP concentrations into contributions from dust, sea spray aerosol (SSA), and bioaerosol. Field campaign data from Bodega Bay, California, showed that bioaerosols were the primary source of INPs between –12° and –20°C, while dust was a minor source and SSA had little impact. We found that recent parameterizations for dust and SSA accurately predicted ambient INP concentrations. However, the model did not skillfully simulate bioaerosol INPs, suggesting a need for further research to identify major factors controlling their emissions and INP efficiency for improved representation in models.

54 ENVIRONMENTAL SCIENCES↗

Grazer-induced changes in molecular signatures of cyanobacteria

Algal biomass production is an emerging renewable source of fuels, nutrients, manufacturing materials, and pharmaceuticals. Industrial-scale production is predominantly performed in open raceway ponds that are inexpensive to build, operate, and maintain compared to closed bioreactors. However, these open pond systems suffer from increased opportunities for biological contamination from predators, pathogens, and competitors, which result in reduced biomass quality and yields and often the complete destruction of the crop over a short period of time. Early detection of contaminants is a necessary step of integrated pest management for triggering and informing interventions to prevent crop losses. To develop a sensitive method of detection utilizing mass spectrometry (MS), we used three methods – imaging mass spectrometry (imaging MS), liquid chromatography MS/MS (LC-MS/MS) combined with molecular networking, and gas chromatography MS/MS (GC–MS/MS) – to observe and identify molecular signatures from a model predator-prey system of the heterolobosean amoeba HGG1 preying on the filamentous cyanobacterium Anabaena sp. PCC 7120. Imaging MS enabled the association of molecules with the crop, the predator, or the activity of protozoan grazing, while LC-MS/MS-based molecular networking identified a subset of the grazing-specific signals as the chlorophyll breakdown products pyropheophytin, pheophorbide A, and pyropheophorbide. Application of MS techniques to other amoebacyanobacterial predator-prey pairs allowed categorization of grazing signatures as universal or specific to the species of prey, predator, or the prey-predator pairing, indicating that MS-based techniques can distinguish crops from competitors and potentially identify predators. Finally, GCMS/MS was shown to be capable of monitoring novel volatile organic compounds (VOCs), including those predicted to be released through chlorophyll breakdown, in the headspace over algal cultures under predation. Furthermore, these results demonstrate that the combination of multiple MS technologies creates a predictive framework to identify and catalog relevant molecular signatures for informing crop protection strategies.

09 BIOMASS FUELS↗

Development of Heterogeneous Ice Nucleation Rate Coefficient Parameterizations From Ambient Measurements

Ice nucleating particles (INPs) are a rare subset of particles that can have an outsized impact relative to their prevalence. To simulate INP variability, models require parameterizations for the most important sources of INPs. Most parameterizations in the literature were developed from laboratory experiments that used proxies for ambient particles. Whether these laboratory models effectively represent ambient aerosol is still not well understood and parameterizations developed from field measurements may be more atmospherically relevant. Expanding on previous work in which we used an ice chamber and a single-particle mass spectrometer (SPMS) to characterize INP composition, we calculate heterogeneous ice nucleation rate coefficients for ambient particles. We find good agreement between our dust and previous measurements of airborne dust. We also use a Monte Carlo approach to assess the relative contribution of each measurement to the uncertainty and find that the biggest source is the sampling efficiency of the SPMS.

54 ENVIRONMENTAL SCIENCES↗

Continuous measurements of volatile gases as detection of algae crop health

Wide adoption of algae cultivation to produce environmentally sustainable biofuels and fine chemicals is currently hampered by large losses (10 to 30%) incurred by grazer infections. We show the usage of real-time chemical ionization mass spectrometry to rapidly identify gaseous indicators of grazer infections in cyanobacteria cultures. Grazing was detected significantly faster (up to 3 d) using real-time mass spectrometry than the current methods of microscopy and qPCR. By employing this technology, cultivators may be empowered to treat grazer infestations sooner, thereby protecting the crop and enhancing profitability.

09 BIOMASS FUELS↗

Ejection of Dust From the Ocean as a Potential Source of Marine Ice Nucleating Particles

Oceans are, generally, relatively weak sources of ice nucleating particles (INPs). Thus, dust transported from terrestrial regions can dominate atmospheric INP concentrations even in remote marine regions. Studies of ocean-emitted INPs have focused upon sea spray aerosols containing biogenic species. Even though large concentrations of dust are transported over marine regions, resuspended dust has never been explicitly considered as another possible source of ocean-emitted INPs. Current models assume that deposited dust is not re-emitted from surface waters. Our laboratory studies of aerosol particles produced from coastal seawater and synthetic seawater doped with dust show that dust can indeed be ejected from water during bubble bursting. INP concentration measurements show these ejected dust particles retain ice nucleating activity. Doping synthetic seawater to simulate a strong dust deposition event produced INPs active at temperatures colder than -13 °C and INP concentrations one to two orders of magnitude greater than either lab sea spray or marine boundary layer measurements. The relevance of these laboratory findings is highlighted by single particle composition measurements along the Californian coast where at least 9% of dust particles were mixed with sea salt. Additionally, global modeling studies show that resuspension of dust from the ocean could exert the most impact over the Southern Ocean, where ocean-emitted INPs are thought to dominate atmospheric INP populations. More work characterizing the factors governing the resuspension of dust particles is required to understand the potential impact upon clouds.

54 ENVIRONMENTAL SCIENCES↗

The Relationships Between Insoluble Precipitation Residues, Clouds, and Precipitation Over California's Southern Sierra Nevada During Winter Storms

Ice formation in orographic mixed-phase clouds can enhance precipitation and depends on the type of aerosols that serve as ice nucleating particles (INP). The resulting precipitation from these clouds is a viable source of water, especially for regions such as the California Sierra Nevada. Thus, a better understanding of the sources of INP that impact orographic clouds is important for assessing water availability in California. This study presents a multi-site, multi-year analysis of single particle insoluble residues in precipitation samples that likely influenced cloud ice and precipitation formation above Yosemite National Park. Dust and biological particles represented the dominant fraction of the residues (64% on average). Cloud glaciation, determined using GOES satellite observations, not only depended on high cloud tops (greater than 6.2 km) and low temperatures (less than -26 C), but also on the composition of the dust and biological residues. The greatest prevalence of ice-phase clouds occurred in conjunction with biologically-rich residues and mineral dust rich in calcium, followed by iron and aluminosilicates. Dust and biological particles are known to be efficient INP, thus these residues are what likely influenced ice formation in clouds above the sites and subsequent precipitation quantities reaching the surface during events with similar meteorology. The goal of this study is to use precipitation chemistry information to gain a better understanding of the potential sources of INP in the south-central Sierra Nevada, where cloud-aerosol-precipitation interactions are under-studied and where mixed-phase orographic clouds represent a key element in the generation of precipitation and thus the water supply in California.

Creamean, Jessie M.↗

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

general circulation models↗

Evaluation of Aerosol Mixing State Classes in the GISS Modele-matrix Climate Model Using Single-particle Mass Spectrometry Measurements

Aerosol particles in the atmosphere are composed of multiple chemical species. The aerosol mixing state, which describes how chemical species are mixed at the single-particle level, provides critical information on microphysical characteristics that determine the interaction of aerosols with the climate system. The evaluation of mixing state has become the next challenge. This study uses aerosol time-of-flight mass spectrometry (ATOFMS) data and compares the results to those of the Goddard Institute for Space Studies modelE-MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) model, a global climate model that includes a detailed aerosol microphysical scheme. We use data from field campaigns that examine a variety of air mass regimens (urban, rural, and maritime). At all locations, polluted areas in California (Riverside, La Jolla, and Long Beach), a remote location in the Sierra Nevada Mountains (Sugar Pine) and observations from Jeju (South Korea), the majority of aerosol species are internally mixed. Coarse aerosol particles, those above 1 micron, are typically aged, such as coated dust or reacted sea-salt particles. Particles below 1 micron contain large fractions of organic material, internally-mixed with sulfate and black carbon, and few external mixtures. We conclude that observations taken over multiple weeks characterize typical air mass types at a given location well; however, due to the instrumentation, we could not evaluate mass budgets. These results represent the first detailed comparison of single-particle mixing states in a global climate model with real-time single-particle mass spectrometry data, an important step in improving the representation of mixing state in global climate models.

climate models↗