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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Equilibrium and Sudden Events in Chemical Evolution

We present new analytic solutions for one-zone (fully mixed) chemical evolution models that incorporate a realistic delay time distribution for Type Ia supernovae (SNe Ia) and can therefore track the separate evolution of αelements produced by core collapse supernovae (CCSNe) and iron peak elements synthesized in both CCSNe and SNe Ia. Our solutions allow constant, exponential, or linear–exponential (te{sup -t/τsfh}) star formation histories, or combinations thereof. In generic cases, α and iron abundances evolve to an equilibrium at which element production is balanced by metal consumption and gas dilution, instead of continuing to increase over time. The equilibrium absolute abundances depend principally on supernova yields and the outflow mass loading parameter η, while the equilibrium abundance ratio [α/Fe] depends mainly on yields and secondarily on star formation history. A stellar population can be metal-poor either because it has not yet evolved to equilibrium or because high outflow efficiency makes the equilibrium abundance itself low. Systems with ongoing gas accretion develop metallicity distribution functions (MDFs) that are sharply peaked, while “gas starved” systems with rapidly declining star formation, such as the conventional “closed box” model, have broadly peaked MDFs. A burst of star formation that consumes a significant fraction of a system’s available gas and retains its metals can temporarily boost [α/Fe] by 0.1–0.3 dex, a possible origin for rare, α-enhanced stars with intermediate age and/or high metallicity. Other sudden transitions in system properties can produce surprising behavior, including backward evolution of a stellar population from high to low metallicity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Observations and Modeling of the Green Ocean Amazon 2014/15: Hydroxyl Radical (OH) Chemical Ionization Mass Spectrometer (CIMS) Field Campaign Report

The University of California, Irvine, science team (Dr. Saewung Kim, Dr. Roger Seco, Dr. Alex Guenther, and Dr. Jim Smith) deployed a chemical ionization mass spectrometer system for hydroxyl radical (OH) and sulfuric acid quantifications. As part of the GoAmazon 2014/15 field campaign. Hydroxyl radical determines tropospheric oxidation capacity and had been expected to be very low in the pristine rain forest region such as the Brazilian Amazon because of the presence of significant levels of highly reactive biogenic volatile organic compounds and very low levels of NO, which is an OH recycling agent. However, several recent in situ OH observations provided by a laser-induced fluorescence system reported unaccountably high OH concentrations. To address this discrepancy, a series of laboratory and theoretical studies has postulated chemical reaction mechanisms of isoprene that may regenerate OH in photo-oxidation processes. Along with these efforts, potential artifacts on the laser induced fluorescence system from isoprene and its oxidation products also have been explored. Therefore, the first chemical ionization mass spectrometer observations at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s T3 site in Manacapuru, Brazil, are expected to provide a critical experimental constraint to address uncertainty in constraining oxidation capacity over pristine rain forest environments. In addition, we deployed a National Center for Atmospheric Research (NCAR) proton transfer reaction time-of-flight mass spectrometer to characterize atmospheric volatile organic compound levels, especially isoprene and its oxidation products, which are critical input parameters for box modeling to simulate OH with different isoprene photo-oxidation schemes. As there has been no report on noticeable new particle formation events, our first in situ sulfuric acid observations in the Amazon rain forest were expected to constrain the reasons behind such observations. The planned field observations during Intensive Observational Periods I and II, post-field campaign calibrations, and preliminary data reports have been completed. We presented preliminary data analysis results at the 2014 American Geophysical Union Fall meeting and the GOAmazon Science Meeting in Boston (May 2015). We are in the process of submitting two more abstracts to the 2015 American Geophysical Union fall meeting while we are preparing two manuscripts to be submitted to (tentatively) the GOAmazon special issue of Atmospheric Chemistry and Physics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

A Data Driven Pre-cooling Framework for Energy Cost Optimization in Commercial Buildings

Commercial buildings consume significant amount of energy. Facility managers are increasingly grappling with the problem of reducing their buildings’ peak power, overall energy consumption and energy bills. In this paper, we first develop an optimization framework – based on a gray box model for zone thermal dynamics – to determine a pre-cooling strategy that simultaneously shifts the peak power to low energy tariff regimes, and reduces both the peak power and overall energy consumption by exploiting the flexibility in a building’s thermal comfort range. We then evaluate the efficacy of the pre-cooling optimization framework by applying it to building management system data, spanning several days, obtained from a large commercial building located in a tropical region of the world. The results from simulations show that optimal pre-cooling reduces peak power by over 50%, energy consumption by up to 30% and energy bills by up to 37%. Next, to enable ease of use of our framework, we also propose a shortest path based heuristic algorithmfor solving the optimization problemand show that it has comparable erformance with the optimal solution. Finally, we describe an application of the proposed optimization framework for developing countries to reduce the dependency on expensive fossil fuels, which are often used as a source for energy backup.We conclude by highlighting our real world deployment of the optimal pre-cooling framework via a software service on the cloud platform of a major provider. Our pre-cooling methodology, based on the gray box optimization framework, incurs no capital expense and relies on data readily available from a building management system, thus enabling facility managers to take informed decisions for improving the energy and cost footprints of their buildings

Vishwanath, Arun↗
DOE OSTI2020

Modeling Functional Organic Chemistry in Arctic Rivers: An Idealized Siberian System

Rivers of the Arctic will become ever more important for the global climate, since they carry a majority of continental dissolved organic carbon flux into the rapidly changing polar ocean. Aqueous organics comprise a wide array of functional groups, several of which are likely to impact coastal and open water biophysical properties. Light attenuation, interfacial films, aerosol formation, gas release and momentum exchange can all be cited. We performed Lagrangian kinetic modeling for the evolution of riverine organic chemistry as the molecules in question make their way from the highlands to Arctic outlets. Classes as diverse as the proteins, sugars, lipids, re-condensates, humics, bio-tracers and small volatiles are all included. Our reduced framework constitutes an idealized northward flow driving a major hydrological discharge rate and primarily representing the Russian Lena. Mountainous, high solute and tundra sources are all simulated, and they meet up at several points between soil and delta process reactors. Turnover rates are parameterized beginning with extrapolated coastal values imposed along a limited tributary network, with connections between different terrestrial sub-ecologies. Temporal variation of our total dissolved matter most closely resembles the observations when we focus on the restricted removal and low initial carbon loads, suggesting relatively slow transformation along the water course. Thus, channel combinations and mixing must play a dominant role. Nevertheless, microbial and photochemical losses help determine the final concentrations for most species. Chemical evolution is distinct for the various functionalities, with special contributions from pre- and post-reactivity in soil and delta waters. Several functions are combined linearly to represent the collective chromophoric dissolved matter, characterized here by its absorption. Tributaries carry the signature of lignin phenols to segregate tundra versus taiga sources, and special attention is paid to the early then marine behaviors of low molecular weight volatiles. Heteropolycondensates comprise the largest percentage of reactive carbon in our simulations due to recombination/accumulation, and they tend to be preeminent at the mouth. Outlet concentrations of individual structures such as amino acids and absorbers lie above threshold values for biophysical influence, on the monolayer and light attenuation. The extent of coastal spreading is examined through targeted regional box modeling, relying on salinity and color for calibration. In some cases, plumes reach the scale of peripheral arctic seas, and amplification is expected during upcoming decades. Conclusions are mapped from the Lena to other boreal discharges, and future research questions are outlined regarding the bonding type versus mass release as permafrost degrades. Dynamic aqueous organic coupling is recommended for polar system models, from headwaters to coastal diluent.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Exploring data-driven modeling of boundary layer transition

Prediction of laminar-turbulent transition in boundary layer flows is an important component of predicting the aerodynamic performance of a number of aerospace configurations. According to the CFD Vision 2030 [1], transition modeling represents acriticalarea in CFD simulation capability that will remain a pacing item for the foreseeable future. The fact thattransition can take placevia either one of a myriad possible paths adds to the challenges inreliable transition predictions, despite a limited knowledge of the relevant input parameters. In the low disturbance environments typical of flight applications, transition is often initiated by small amplitude disturbances in the form of linear instability waves of the laminar boundary layer. These disturbances amplify linearly at first and eventually undergo a sequence of nonlinear interactions that result in transition to turbulence. Because the nonlinear phase is rather rapid, the amplification of boundary layer instabilities is governed by the linearstability theory over a majority of the distance leading up to the onset of transition. Semi-empirical transition correlations based on the linear stability theory have been successful in explaining the observed trends in transition location within a broad class of flows. However, the application of stability theory is highly non-robust and often requires a significant domain expertise. Recent work at the NASA Langley Research Center has beenaimed at bridging the gap between physics based transition analyses such as those based on linear stability theory and practical applications that require transition prediction by users that may not be well versed in transition physics. The applications of deep learning have been at the center of these efforts. This presentation will focus on the progress achieved thus far, highlighting the applications of neural networks to selectedtransition scenarios across a range of Mach numbers and flow configuration, as well as the lessons learnedand remaining challengeswithrespect to the selection of training data and neural networks architectures, hyperparameter tuning, and the physical insights distilled from the otherwise black-box models.

M. R. Malik↗
DOE OSTI2016

Determining the flux of methane into Hudson Canyon at the edge of methane clathrate hydrate stability: METHANE FLUX INTO HUDSON CANYON

Methane seeps were investigated in Hudson Canyon, the largest shelf-break canyon on the northern U.S. Atlantic Margin. The seeps investigated are located at or updip of the nominal limit of methane clathrate hydrate stability. The acoustic identification of bubble streams was used to guide water column sampling in a 32 km 2 region within the canyon's thalweg. By incorporating measurements of dissolved methane concentration with methane oxidation rates and current velocity into a steady state box model, the total emission of methane to the water column in this region was estimated to be 12 kmol methane per day (range: 6–24 kmol methane per day). These analyses suggest that the emitted methane is largely retained inside the canyon walls below 300 m water depth, and that it is aerobically oxidized to near completion within the larger extent of Hudson Canyon. Based on estimated methane emissions and measured oxidation rates, the oxidation of this methane to dissolved CO 2 is expected to have minimal influences on seawater pH.

58 GEOSCIENCES↗
DOE OSTI2020

Local order of orthorhombic weberite-type Y 3 TaO 7 as determined by neutron total scattering and density functional theory calculations

Weberite-type oxides are a family of oxides with A 3 BO 7 stoichiometry that can adopt different space groups depending on chemical composition. There is a discrepancy in previous studies as to whether Y 3 TaO 7 is the orthorhombic C222 1 or the Ccmm space group. Here, we describe the short- and long-range structural properties of weberite-type Y 3 TaO 7 using neutron total scattering data, which has a high sensitivity to the oxygen sublattice. Simultaneous analysis of both short- and long-range structural data via conventional Rietveld and small box modelling demonstrates that Y 3 TaO 7 is best modeled as C222 1 . While the Ccmm describes equally well the long-range structure, pair distribution function analysis revealed that the local atomic configuration can be best modelled as C222 1 . This is corroborated by first-principles calculations that confirm the energetic preference of the C222 1 over Ccmm. Further, neutron total scattering data are reported for the first time for the Y 3 TaO 7 weberite-type ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Performance study of a novel dew point evaporative cooler in the climate of central Europe using building simulation tools

This paper presents the performance research of a hybrid air conditioning system (System II) equipped with novel dew point evaporative cooler (DPIEC) for a retail building located in temperate climatic conditions. The new cooler has a dedicated, adaptable structure that maximizes its performance in the climate conditions of central Europe. The unit can operate as a typical regenerative air cooler when outdoor air is drier than indoor air, it can operate as a counter-flow heat recovery unit when indoor conditions are more dry than outdoor and it can operate as a combination of both arrangements. The year-round, hourly-stepped building energy simulations were carried-out using a prognostic tool of energy consumption. The novel dew point evaporative cooler application potential was established using the black-box model based on regression equations was established based on experimental tests on a prototype of novel DPIEC. The hybrid system operation was compared to the typical air handling unit equipped with a standard energy wheel for heat recovery (System I). Presented research shows that DPIEC can cover about 95% of total cooling loads while the energy wheel covers only 9% of total cooling load. System II allows us to save 65% of seasonal electricity consumption comparing to System I. It comes from the fact that during most of the cooling season DPIEC is in operation and it covers most of the cooling loads without the need to switch the chilled water system.

Air conditioning↗
DOE OSTI2020

Sequence-to-sequence neural networks for short-term electrical load forecasting in commercial office buildings

The U.S. power grid is transforming to become smarter, cleaner, and more effi- cient. This is leading to the addition of significant distributed variable renew- able generation. Due to the variable nature of renewable generation, the short- and long-term supply-demand imbalances are less predictable, and conventional approaches to mitigating the imbalance will not be efficient or cost-effective. To address this challenge, transactive control technologies have been proposed which balance energy generation and consumption with market activity and in- frastructural limitations. Transactive control requires the ability of individual end-use loads to express flexibility as a function of a transactive signal (e.g., price). Empirical gray- and black-box models have been widely used to express flexibility, and although these approaches are generally easy to construct and simple to use, they do not capture the non-linear behavior that some end-use loads represent . Machine learning approaches have been proposed to address this limitation. Although deep learning approaches for forecasting end-use loads have been explored, certain aspects of the application of deep models to load forecasting are not well understood. These aspects include how much training data is required, and how models should be structured and trained. To that end, this work explores how to approach applying deep recurrent neural networks to short-term electrical load forecasting with a case study of four commercial office buildings. We identify data requirements for training accurate models of whole building electricity use conditioned on outdoor temperature, provide insight into model hyperparameter sensitivity, and demonstrate how readily models can be generalized to unseen buildings.

Skomski, Elliott↗
DOE OSTI2019

A Bayesian statistical approach to inferring particle dynamics from in-situ pump POC and chloropigment data from the Mediterranean Sea

Concentrations of chloropigments and particulate organic carbon (POC) in large-volume in-situ pump samples from the Mediterranean Sea were used to estimate rate constants of processes that control the fate of particles, and specifically chloropigments, in the water column. In this paper we introduce a Bayesian statistical inversion method that combines the data with a new box model and has the capacity to infer rate constants for POC respiration/dissolution, chlorophyll and pheopigment degradation, and particle aggregation and disaggregation. We use first-order kinetics to model disaggregation, and use both first-order and second-order kinetics to model aggregation. Using these methods, the estimated small-particle (1–70 μm) POC respiration rate constant was 2.44 -1.00 +1.69 yr -1 (0.41 yr). The estimated disaggregation and second-order aggregation rate constants were 85.6 -36.4 +63.4 yr -1 (1.17×10 -2 yr) and 2.78 -1.17 +2.01 μM -1 yr -1 , respectively. Using the optimal rate constants and the corresponding particle concentrations, disaggregation is ~4.2 times faster than the small-size POC dissolution rate, which indicates that disaggregation is a dominant processes at the time of sampling. More importantly, by comparing our results with those of previous studies, we conclude that sampling methods have less influence than tracers themselves on inferring particle dynamic rate constants. We previously introduced a somewhat similar approach to modeling SV sediment trap data, but large volume pumps are a much more common sample collection method in oceanographic surveys than SV sediment traps, and thus our new model should have a wider applicability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Lattice Disorder and Oxygen Migration Pathways in Pyrochlore and Defect-Fluorite Oxides

Atomic-scale disorder plays an important role in the chemical and physical properties of oxide materials. The structural flexibility of pyrochlore-type oxides allows for crystal-chemical engineering of these properties. Compositional modification can push pyrochlore oxides toward a disordered defect-fluorite structure with anion Frenkel pair defects that facilitate oxygen migration. The local structure of the long-range average cubic defect-fluorite was recently claimed to consist of randomly arranged orthorhombic weberite-type domains. Here, we show, using low-temperature neutron total-scattering experiments, that this is not the case for Zr-rich defect-fluorites. By analyzing data from the pyrochlore/defect-fluorite Y 2 Sn 2–x Zr x O 7 series using a combination of neutron pair distribution function and big-box modelling, we have differentiated and quantified the relationship between anion sub-lattice disorder and Frenkel defects. These details directly influence the energy landscape for oxygen migration and are crucial for simulations and design of new materials with improved properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

The reaction between CH 3 O 2 and OH radicals: Product yields and atmospheric implications

The reaction between CH 3 O 2 and OH radicals has been shown to be fast and to play an appreciable role for the removal of CH 3 O 2 radials in remote environments such as the marine boundary layer. Two different experimental techniques have been used here to determine the products of this reaction. The HO 2 yield has been obtained from simultaneous time-resolved measurements of the absolute concentration of CH 3 O 2 , OH, and HO 2 radicals by cw-CRDS. The possible formation of a Criegee intermediate has been measured by broadband cavity enhanced UV absorption. A yield of Φ HO 2 = (0.8 ± 0.2) and an upper limit for Φ Criegee = 0.05 has been determined for this reaction, suggesting a minor yield of methanol or stabilized trioxide as a product. The impact of this reaction on the composition of the remote marine boundary layer has been determined by implementing these findings into a box model utilizing the Master Chemical Mechanism v3.2, and constraining the model for conditions found at the Cape Verde Atmospheric Observatory in the remote tropical Atlantic Ocean. Inclusion of the CH 3 O 2 +OH reaction into the model results in up to 30% decrease in the CH 3 O 2 radical concentration while the HO 2 concentration increased by up to 20%. Finally, production and destruction of O 3 are also influenced by these changes, and the model indicates that taking into account the reaction between CH 3 O 2 and OH leads to a 6% decrease of O 3 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Isomerization of Second-Generation Isoprene Peroxy Radicals: Epoxide Formation and Implications for Secondary Organic Aerosol Yields

We report chamber measurements of secondary organic aerosol (SOA) formation from isoprene photochemical oxidation, where radical concentrations were systematically varied and the molecular composition of semi to low volatility gases and SOA were measured online. Using a detailed chemical mechanism, we find that to explain the behavior of low volatility products and SOA mass yields relative to input H2O2 concentrations, the second generation dihydroxy hydroperoxy peroxy radical (C5H11O6•) must undergo an intra-molecular H-shift with a net forward rate constant of order 0.1 s-1 or higher, consistent with quantum chemical calculations which suggest a net forward rate constant of 0.3-0.9 s-1. Furthermore, these calculations suggest the dominant product of this isomerization is a dihydroxy hydroperoxy epoxide (C5H10O5) which is expected to have a saturation vapor pressure ~2 orders of magnitude higher than the dihydroxy dihydroperoxide, ISOP(OOH)2 (C5H12O6), a major product of the peroxy radical reacting with HO2. These results provide strong constraints on the likely volatility distribution of isoprene oxidation products under atmospheric conditions and thus on the importance of non-reactive gas-particle partitioning of isoprene oxidation products as an SOA source.

D’Ambro, Emma L. (ORCID:0000000230419027)↗
DOE OSTI2022

Ligand Coverage and Exciton Delocalization Control Chiral Imprinting in Perovskite Nanoplatelets

Chiral perovskites have generated significant recent interest, yet little is known about how their chiro-optical properties arise. In this study, chiral methylammonium lead halide perovskite nanoplatelets (NPLs) with varied halide and ligand compositions are prepared using direct synthetic methods. Circular dichroism (CD) and 1 H NMR studies find a non-linear relationship between the chiroptical properties and the ratio of chiral phenylethylammonium (PEA) to achiral octylamine (OA) ligands on the NPL surface. We use density functional theory (DFT) computations and a chiral imprinted particle-in-a-box model to rationalize the experimentally observed CD spectra and find that the saturation point of the induced chirality depends on the size of the perovskite exciton relative to the size of the ligands. Temperature-dependent CD and 1 H NMR studies, combined with DFT analysis, show that both the CD intensity and sign depend strongly on the structure and orientation of the ligands. Furthermore, this work reveals the complex nature of chiral imprinting in perovskite nanostructures and establishes a simple physical model for ligand-induced chiral imprinting to guide the further development of chiral materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Potassium and Calcium Isotopic Fractionation by Plants (Soybean [Glycine max], Rice [Oryza sativa], and Wheat [Triticum aestivum])

Here, we conducted hydroponic experiments growing soybean (Glycine max), rice (Oryza sativa), and wheat (Triticum aestivum) under K and Ca replete conditions to establish the degree of K isotopic fractionation by plants, and compare the isotopic fractionation of Ca and K. Each of the test plants displays fractionation relative to the growth solution favoring the light isotopes of K and Ca. The average δ 41 K values of the roots from the three plant species were similar, and have an overall average of -0.55 ± 0.24‰ 2s, while the overall average δ 44 Ca for roots is -0.67 ± 0.44. For leaves, the overall average of δ 41 K is -0.97 ± 0.4‰, compared to an overall average leaf δ 44 Ca of -0.83 ± 0.09‰. In the case of the soybean plants, the lightest K and Ca occurs in the stems with average δ 41 K of -1.31 ± 0.40‰ 2s and average δ 44 Ca of -1.20 ± 0.19 ‰ 2s. We present a simple box model involving the relative fluxes of K and its isotopic fractionation that reproduces our K isotopic observations and suggests a fractionation of ~0.8‰ with K uptake from solution by roots. Finally, directly comparing the per amu fractionation of K and Ca reveals an average factor of 2.05 ± 0.50 2s greater fractionation of K isotopes which may reflect their different roles and behaviors in plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Contribution of Speciated Monoterpenes to Secondary Aerosol in the Eastern North Atlantic

Extension of laboratory results suggests that monoterpenes, a subset of marine biogenic volatile organic compounds, might play a competitive role in secondary aerosol formation in the remote marine atmosphere, where the oxidation of dimethyl sulfide has traditionally been thought to dominate. However, the current assessment of the role of monoterpenes in secondary aerosol formation in the remote marine atmosphere is limited by the scarcity of speciated monoterpene measurements and the complete absence of collocated measurements of particle chemical composition and monoterpene speciation. Here, in this paper, we present measurements of gas-phase volatile organic compounds, with particular focus on speciated monoterpenes, and commensurate measurements of aerosol chemical composition in the Eastern North Atlantic. The average monoterpene concentration in periods of marine air was 14 ± 10 ppt, and the dominant isomer was β-pinene (46 ± 10%), with other contributions from α-pinene, limonene, and β-ocimene. The total monoterpene concentration in marine air was greater than that of isoprene by a factor of 3.9 on average, in contrast to prior research and potentially due to the large β-pinene contribution. Monoterpenes were significantly smaller in concentration than dimethyl sulfide, which was also highlighted by the substantial contribution of sulfate to non-refractory submicron aerosol. The mean and interquartile range of the sulfate to organic aerosol mass ratio in clean marine air were 2.7 (0.7–3.4). Finally, a simple box model analysis showed that the BVOC precursors, dimethyl sulfide, methanethiol, monoterpenes, and isoprene, could sustain the measured sulfate to organic aerosol ratio in clean marine air.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Reconciling Observed and Predicted Tropical Rainforest OH Concentrations

We present OH observations made in Amazonas, Brazil during the Green Ocean Amazon campaign (GoAmazon2014/5) from February to March of 2014. The average diurnal variation of OH peaked with a midday (10:00–15:00) average of 1.0 × 10 6 (±0.6 × 10 6 ) molecules cm -3 . This was substantially lower than previously reported in other tropical forest photochemical environments (2–5 × 10 6 molecules cm -3 ) while the simulated OH reactivity was lower. The observational data set was used to constrain a box model to examine how well current photochemical reaction mechanisms can simulate observed OH. We used one near-explicit mechanism (MCM v3.3.1) and four condensed mechanisms (i.e., RACM2, MOZART-T1, CB05, CB6r2) to simulate OH. A total of 14 days of analysis shows that all five chemical mechanisms were able to explain the measured OH within instrumental uncertainty of 40% during the campaign in the Amazonian rainforest environment. Future studies are required using more reliable NO x and VOC measurements to further investigate discrepancies in our understanding of the radical chemistry in the tropical rainforest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

New Particle Formation Events Over the Southeast Atlantic Coincide With the African Biomass Burning Season

Abstract We investigated the occurrence and evolution of new particle formation (NPF) events over the southeast Atlantic. The studied region is under the influence of the long‐range transport of aerosols and gases during the southern African biomass burning season, from June to October every year. Interestingly, NPF was observed to coincide with the African biomass burning season, although wet removal of pre‐existing aerosols is needed during these NPF events. Surface and airborne measurements show that these NPF events likely occurred in the upper region of the marine boundary layer, and the newly formed aerosols were further transported to the surface via vertical air motions. Using a box model, we predicted that a large fraction of these particles could grow to sizes related to cloud condensation nuclei. Our study shows that NPF can occur over the southeast Atlantic, and the African biomass‐burning plume likely contributed to the NPF occurrence.

54 ENVIRONMENTAL SCIENCES↗