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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data

This paper presents an independent component analysis (ICA) based unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC) load disaggregation using row-resolution (i.e., 15 minutes) smart meter data. We first demonstrate that the electricity consumption profiles on mild-temperature days can be used to approximate the base load on hot days. A residual load profile can then be calculated by subtracting the mild-day load profile from the hot-day load profile. The residual load profiles are processed using ICA for HVAC load extraction. An optimization-based algorithm is proposed for post-adjustment of the ICA results, considering two bounding factors for enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC energy bounds computed from the relationship between HVAC load and temperature to remove unrealistic HVAC load spikes. Second, we exploit the dependency between the daily nocturnal and diurnal loads extracted from historical meter data to smooth the base load profile. Pecan Street data with sub-metered HVAC data were used to test and verify the proposed methods. Simulation results demonstrated that the proposed method is computationally efficient and robust across multiple customers.

Kim, Hyeonjin↗
DOE OSTI2025

Using Temporal Information from Human Mobility Data to Detect Anchor Points

Spatiotemporal mobility data are available in massive quantities, but large quantities of data typically include fewer variables or data fields. Often, the only available fields are User ID, Longitude, Latitude, Timestamp (ULLT). This raises an important question: how much can we infer about human mobility patterns using only these four fields? With ULLT data, we do not know individuals' socioeconomic status information or when they are visiting their anchor points (AP) or locations (such as homes, places of employment, or schools), and it is a modern challenge to use this data to infer these characteristics. When detecting anchor locations with limited input information, verification and validation (VV) are significant challenges. This paper addresses the problem of identifying individuals' anchor locations using only temporal information from spatiotemporal datasets with limited attributes. Our approach does not explicitly use latitude and longitude during analysis. Locationbased information is only employed in the preprocessing stage to identify periods of movement (trips) and stops (dwelling). Beyond this step, all analysis is based on temporal patterns. In theory, if stops and dwell times could be detected through alternative means, our method could function entirely without location-based input. We demonstrate this methodology on the 2017 National Household Travel Survey (NHTS) data, because it includes a carefully designed and collected time use survey with representative sampling and labeled ground truth. The high-quality survey data allows us to test the accuracy of our methods because NHTS contains intended place labels and agent/user characteristics. We have also applied our validated AP identification algorithm on very large-scale GPS based trajectory data for Patterns-of-Life (PoL) assessment and other applications, but due to space limit that could not be presented here.

McBride, Liz [ORNL] (ORCID:0000000286925869)↗
DOE OSTI2019

Parametric Optimization Problem Formulation for Connected Hybrid Electric Vehicles using Neural Network based Equivalent Model

The dynamics of powertrain control systems are complicated and involve both nonlinear plant model and control functionalities, albeit they are well defined and formulated using first principle approaches. This constitutes difficulties in exploring implementable optimal tuning rules for some selected control parameters using vehicle-to-vehicle (V2V) communications. This paper presents a way to use neural networks (NN) to represent the problem of parameter tuning for optimizing fuel consumption. For this purpose, physical modelling and validation have been firstly performed for the closed loop powertrain system of the concerned vehicle for some given driving cycles. This is then followed by the sensitivity analysis that selects most influential control parameters to optimize. Using the data generated from the obtained physical models, an equivalent NN formulation has finally been obtained that gives simple yet unified objectives and constraints ready to be used to solve the optimization problem that produces optimal tuning rules for the selected control parameters to minimize fuel consumption.

Parameter optimization, V2X, Powertrain modeling↗
DOE OSTI2024

Uncertainty-informed selection of CMIP6 Earth System Model subsets for use in multisectoral and impact models

Earth system models (ESMs) and general circulation models (GCMs) are heavily used to provide inputs to sectoral impact and multisector dynamic models, which include representations of energy, water, land, economics, and their interactions. Therefore, representing the full range of model uncertainty, scenario uncertainty, and interannual variability that ensembles of these models capture is critical to the exploration of the future co-evolution of the integrated human–Earth system. The pre-eminent source of these ensembles has been the Coupled Model Intercomparison Project (CMIP). With more modeling centers participating in each new CMIP phase, the size of the model archive is rapidly increasing, which can be intractable for impact modelers to effectively utilize due to computational constraints and the challenges of analyzing large datasets. In this work, we present a method to select a subset of the latest phase, CMIP6, featuring models for use as inputs to a sectoral impact or multisector dynamics models, while prioritizing preservation of the range of model uncertainty, scenario uncertainty, and interannual variability in the full CMIP6 ensemble results. This method is intended to help impact modelers select climate information from the CMIP archive efficiently for use in downstream models that require global coverage of climate information. This is particularly critical for large-ensemble experiments of multisector dynamic models that may be varying additional features beyond climate inputs in a factorial design, thus putting constraints on the number of climate simulations that can be used. We focus on temperature and precipitation outputs of CMIP6 models, as these are two of the most used variables among impact models, and many other key input variables for impacts are at least correlated with one or both of temperature and precipitation (e.g., relative humidity). Besides preserving the multi-model ensemble variance characteristics, we prioritize selecting CMIP6 models in the subset that preserve the very likely distribution of equilibrium climate sensitivity values as assessed by the latest Intergovernmental Panel on Climate Change (IPCC) report. This approach could be applied to other output variables of climate models and, possibly when combined with emulators, offers a flexible framework for designing more efficient experiments on human-relevant climate impacts. It can also provide greater insight into the properties of existing CMIP6 models.

Snyder, Abigail C.↗
DOE OSTI2017

Impact of Active Climate Control Seats on Energy Use, Fuel Use, and CO2 Emissions

A project was developed through collaboration between Gentherm and NREL to determine the impact of climate control seats for light-duty vehicles in the United States. The project used a combination of experimentation and analysis, with experimental results providing critical input to the analysis process. First, outdoor stationary vehicle testing was performed at NREL's facility in Golden, CO using multiple occupants. Two pre-production Ford Focus electric vehicles were used for testing; one containing a standard inactive seat and the second vehicle containing a Gentherm climate control seat. Multiple maximum cool-down and steady-state cooling tests were performed in late summer conditions. The two vehicles were used to determine the increase in cabin temperature when using the climate control seat in comparison to the baseline vehicle cabin temperature with a standard seat at the equivalent occupant whole-body sensation. The experiments estimated that on average, the climate control seats allowed for a 2.61 degrees Celsius increase in vehicle cabin temperature at equivalent occupant body sensation compared to the baseline vehicle. The increased cabin air temperature along with their measured energy usage were then used as inputs to the national analysis process. The national analysis process was constructed from full vehicle cabin, HVAC, and propulsion models previously developed by NREL. In addition, three representative vehicle platforms, vehicle usage patterns, and vehicle registration weighted environmental data were integrated into the analysis process. Both the baseline vehicle and the vehicle with climate control seats were simulated, using the experimentally determined cabin temperature offset of 2.61degrees Celsius and added seat energy as inputs to the climate control seat vehicle model. The U.S. composite annual fuel use savings for the climate control seats over the baseline A/C system was determined to be 5.1 gallons of gasoline per year per vehicle, corresponding to 4.0 grams of CO2/mile savings. Finally, the potential impact of 100 percent adoption of climate control seats on U.S. light-duty fleet A/C fuel use was calculated to be 1.3 billion gallons of gasoline annually with a corresponding CO2 emissions reduction of 12.7 million tons. Direct comparison of the impact of the CCS to the ventilated seat off-cycle credit was not possible because the NREL analysis calculated a combined car/truck savings and the baseline A/C CO2 emissions were higher than EPA. To enable comparison, the CCS national A/C CO2 emissions were split into car/truck components and the ventilated seat credit was scaled up. The split CO2 emissions savings due to the CCS were 3.5 g/mi for a car and 4.4 g/mi for a truck. The CCS saved an additional 2.0 g/mi and 2.5 g/mi over the adjusted ventilated seat credit for a car and truck, respectively.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Performance and characterization of the SPT-3G digital frequency-domain multiplexed readout system using an improved noise and crosstalk model

The third-generation South Pole Telescope camera (SPT-3G) improves upon its predecessor (SPTpol) by an order of magnitude increase in detectors on the focal plane. The technology used to read out and control these detectors, digital frequency-domain multiplexing (DfMUX), is conceptually the same as used for SPTpol, but extended to accommodate more detectors. A nearly 5× expansion in the readout operating bandwidth has enabled the use of this large focal plane, and SPT-3G performance meets the forecasting targets relevant to its science objectives. However, the electrical dynamics of the higher-bandwidth readout differ from predictions based on models of the SPTpol system due to the higher frequencies used and parasitic impedances associated with new cryogenic electronic architecture. To address this, we present an updated derivation for electrical crosstalk in higher-bandwidth DfMUX systems and identify two previously uncharacterized contributions to readout noise, which become dominant at high bias frequency. The updated crosstalk and noise models successfully describe the measured crosstalk and readout noise performance of SPT-3G. These results also suggest specific changes to warm electronics component values, wire-harness properties, and SQUID parameters, to improve the readout system for future experiments using DfMUX, such as the LiteBIRD space telescope.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Opportunities for Using the Industrial Assessment Center Database for Industrial Water Use Analysis

The manufacturing sector accounted for approximately 5–6% of total U.S. water use in 2015. Of that amount, 75–80% is self supplied withdrawal from surface-water and groundwater sources and the remainder is from public water supplies. Although manufacturing facilities commonly locate in water-scarce areas, water scarcity still poses a great risk to the manufacturing sector. Reliable water is necessary for any facility that relies on it for process and comfort cooling, cleaning, employee use, and steam generation. One of these barriers to water efficiency is the lack of reliable data on overall U.S. industrial water use—how it is used and the quantities required for each sector. If a facility cannot be easily compared with a facility of similar size and sector, knowing if it is effectively using water conservation best practices is difficult. One potential source of industrial water use data is the U.S. Department of Energy (DOE)–sponsored Industrial Assessment Centers (IACs). IACs are university-based organizations that provide free audits to small- and medium-sized manufacturing facilities to identify productivity improvement and waste and energy reduction opportunities. The IACs also maintain a database of all the audits conducted, which currently holds more than 19,267 assessments and 145,000 recommendations (as of July 24, 2020). This database also contains energy utility (electricity, natural gas, and other fuels) and water utility data, making it a potential data source for industrial water use. This report attempts to create regression models to predict a small- or medium-sized industrial facility’s annual water use or cost based on its industrial subsector and several possible relevant variables. Using data collected by IAC assessments, models for several industrial subsectors were generated via stepwise regression techniques to determine which variables (annual sales, number of employees, facility/plant area, annual production hours, and a water stress metric) are relevant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Module 5: End Use Assessment - Lesson 5.1: Introduction to End Use Assessment [Slides]

End use assessment is the process of performing a technical evaluation of the stated end use in relation to the requested commodity and the activities of the end user. An end use assessment requires sufficiently detailed information on the procurement request, commodity technical specifications, end use conditions, end user business activities, industry norms and trends, and WMD or delivery system applications of stated end use. Reviewers should be aware of red flags related to end use assessment. Use best practices when writing an end use assessment. Be familiar with technical resources for end use assessments.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Modeling land use and land cover change: using a hindcast to estimate economic parameters in gcamland v2.0

Abstract. Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. Estimates of future land use and land cover differ significantly across economic models as a result of differences in drivers, model structure, and model parameters; however, these models often rely on heuristics to determine model parameters. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. Specifically, we generate a large set of model parameter perturbations for the selected parameters and run gcamland simulations with these parameter sets over the historical period in the United States to quantify land use and land cover, determine how well the model reproduces observations, and identify parameter combinations that best replicate observations, assuming other model parameters are fixed. We also test alternate methods for forming expectations about uncertain crop yields and prices, including adaptive, perfect, linear, and hybrid approaches. In particular, we estimate parameters for six parameters used in the formation of expectations and three of seven logit exponents for the USA only. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops, landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We examine the change in model parameters as the metric of model error changes, finding that the measure of model fitness affects the choice of parameter sets. Finally, we discuss how the methodology and results used in this study could be used for other regions or economic models to improve projections of future land use and land cover change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Life-cycle impact and exergy based resource use assessment of torrefied and non-torrefied briquette use for heat and electricity generation

Forest residue biomass can be used as bioenergy feedstock, however, issues associated with its properties including low density and high moisture content constrains its valorization. Using mobile conversion technologies that can operate in remote areas and are capable of converting forest residues into high quality energy products can address the issues associated with its valorization for renewable energy production. This study evaluated environmental sustainability of using an integrated novel system of semi-mobile biomass conversion technologies (BCTs) to utilize low-value forest residue biomass as high value bioenergy products. A cradle-to-grave life cycle assessment (LCA) and resource use assessment on a unit-process level was conducted for two bio-products: nontorrefied briquettes (NTB) and torrefied briquettes (TOB). Their use for production of useful thermal energy in wood stoves for domestic heating and electricity at power plants were investigated along with their alternatives. The analyses were performed with SimaPro 8.5 using the DATASMART database. The impact assessment results showed a notable decrease in global warming (GW) impact when substituting fossil fuels with these two bio-products. Specifically, for domestic heating on an equivalent energy basis, a 50% substitution of propane with NTB and TOB showed GHG emission reductions of 46% and 41%, respectively. For electricity generation, 10% cofiring at coal power plant with NTB and TOB showed GHG emission reductions of 6% and 8%, respectively. For the TOB supply chain, a large portion of the GW impact of the came from the torrefaction process and followed by the drying process. This was due to the propane use in these processes. Comparative analysis showed that near-woods biomass conversion for TOB production instead of processing feedstock at an in-town facility with access to grid electricity found 48%–55% lower GW impact for both electricity and heat generation scenarios, respectively. Resourced footprint analysis showed that most exergy extraction from the natural environment came from the drying process for NTB supply chain. In the TOB product system, torrefaction was the major contributor.

09 BIOMASS FUELS↗
DOE OSTI2023

Integrated Sustainable Product Design With Warranty and End-of-Use Considerations

The concept of integrated sustainable product design has recently emerged, aiming to incorporate downstream life cycle performance into the initial product design to enhance sustainability. Various sustainable product design tools based on life cycle assessment or quality function deployment have been established while the impact of reliability on circular practices has received limited attention. Recognizing the critical role of product reliability in post-design performance, this paper develops a product design optimization model that considers the warranty performance and the effect of end-of-use options. The model takes into account the effect of uncertain operating conditions on product reliability. Two optimization goals including the minimization of expected unit life cycle cost and environmental impact are achieved by the model. To demonstrate the benefits of the integrated approach, the model is applied to an electric motor design problem. The results highlight that integrating end-of-use options in the early design phase leads to adjustments in component selection and reliability design. Moreover, the circular utilization of used products enables cost savings throughout the product’s life cycle and contributes to environmental impact reduction. Finally, the study analyzes the effects of operating conditions, warranty policies, and take-back prices for used products on design decisions, providing valuable insights for product designers.

Integrated design↗
DOE OSTI2024

Biofuels Induced Land Use Change Emissions: The Role of Implemented Land Use Emission Factors

Biofuels’ induced land-use change (ILUC) emissions have been widely studied over the past 15 years. Many studies have addressed uncertainties associated with these estimates. These studies have broadly examined uncertainties associated with the choice of economic models, their assumptions and parameters, and a few bio-physical variables. However, uncertainties in land-use emission factors that represent the soil and vegetation carbon contents of various land types across the world and are used to estimate carbon fluxes due to land conversions are mostly overlooked. This paper calls attention to this important omission. It highlights some important sources of uncertainty in land-use emissions factors, explores the range in these factors from established data sources, and compares the influence of their variability on ILUC emissions for several sustainable aviation fuel (SAF) pathways. The estimated land-use changes for each pathway are taken from a well-known computable general equilibrium model, GTAP-BIO. Two well-known carbon calculator models (CCLUB and AEZ-EF) that represent two different sets of emissions factors are used to convert the GTAP-BIO estimated land-use changes to ILUC emissions. The results show that the calculated ILUC emissions obtained from these carbon calculators for each examined SAF pathway are largely different, even for the same amortization time horizon. For example, the ILUC emissions values obtained from the AEZ-EF and CCLUB models for producing jet fuel from corn ethanol for a 25-year amortization period are 24.9 gCO 2 e/MJ and 15.96 gCO 2 e/MJ, respectively. This represents a 60% difference between the results of these two carbon calculators for the same set of land-use changes. The results show larger differences for other pathways as well.

09 BIOMASS FUELS↗
DOE OSTI2018

Quantitative Mapping of Nanoscale Chemical Dynamics in Sub-sampled Operando (S)TEM Images Using Spatio-Temporal Analytics

One of the main limitations in the use of operando scanning transmission electron microscopes to study dynamic chemical processes is the effect of the electron beam on the kinetics of the reaction being observed. Here we demonstrate that a flexible Gaussian mixture model can be used to extract quantitative information directly from sub-sampled images, i.e.~images where not all the pixels in the image are illuminated with the beam. The use of this method is demonstrated for the charge/discharge cycle of a Li-battery, where the deposition and dissolution of Li at the anode can be accurately quantified for sub-sampling levels down to 1%. Performing operando imaging using a small fraction of the pixels means that the observations can significantly reduce the effect of the beam, automatically increase the imaging speed and decrease the total data transfer rate required. Such new software capabilities offer the potential to significantly widen the application of operando hardware approaches to study nanoscale dynamics in materials.

Stanfill, Bryan A.↗
DOE OSTI2018

Modeling and simulation of CO 2 capture using semipermeable elastic microcapsules

Very high rates of CO2 absorption have been demonstrated using semipermeable microcapsules filled with environmentally benign sodium carbonate solutions (Vericella et al., Nature communications 6, 2015). However, such capsules have also exhibited several traits, including water loss/uptake, elastic swelling and buckling, and precipitation of solids, which make them more complicated to engineer as a carbon capture material. To address this, a mechanistic model for mass transfer and chemical reaction has been developed, which accounts for these behaviors, and can be used as a predictive tool to explore capsule performance under different CO2 capture scenarios. The model uses a modified film theory to describe CO2 and H2O mass transfer rates, a concentration based description of vapor-liquid-solid equilibrium inside the capsule, and an elastic description of the capsule shell. Model predictions compare favorably to literature data for precipitating carbonates, as well as recent data for microcapsule CO2 absorption. The model was used to assess practical issues of capsule water transfer during a temperature swing CO2 absorption/desorption cycle. Model predictions indicate that capsules filled with high weight percent, precipitating sodium carbonate solution could be significantly or completely dehydrated during CO2 absorption. Subsequent rehydration of lean capsules at elevated temperature showed strong sensitivity to both gas humidity, and capsule shell elasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Evaluation of microstructure stability at the interfaces of Al-6061 welds fabricated using ultrasonic additive manufacturing

Ultrasonic additive manufacturing (UAM) is a solid-state additive manufacturing process that uses fundamental principles of ultrasonic welding and sequential layering of tapes to fabricate complex three-dimensional (3-D) components. One of the factors limiting the use of this technology is the poor tensile strength along the z-axis. Recent work has demonstrated the improvement of the z-axis properties after post-processing treatments. The abnormally high stability of the grains at the interface during post-weld heat treatments is, however, not yet well understood. In this work we use multiscale characterization to understand the stability of the grains during post-weld heat treatments. Aluminum alloy (6061) builds, fabricated using ultrasonic additive manufacturing, were post-weld heat treated at 180, 330 and 580 °C. The grains close to the tape interfaces are stable during post-weld heat treatments at high temperatures (i.e., 580 °C). This is in contrast to rapid grain growth that takes place in the bulk. Transmission electron microscopy and atom-probe tomography display a significant enrichment of oxygen and magnesium near the stable interfaces. Based on the detailed characterization, two mechanisms are proposed and evaluated: nonequilibrium nano-dispersed oxides impeding the grain growth due to grain boundary pinning, or grain boundary segregation of magnesium and oxygen reducing the grain boundary energy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hong-Ou-Mandel interference with a coexisting clock using transceivers for synchronization over deployed fiber

Interference between independently generated photons is a key step towards distributing entanglement over long distances, but it requires synchronization between the distantly-located photon sources. Synchronizing the clocks of such photon sources using coexisting two-way classical optical communications over the same fiber that transports the quantum photonic signals is a promising approach for achieving photon-photon interference over long distances, enabling entanglement distribution for quantum networking using the deployed fiber infrastructure. Here, we demonstrate photon-photon interference by observing the Hong-Ou-Mandel dip between two distantly-located sources: a weak coherent-state source obtained by attenuating the output of a laser and a heralded single-photon source. We achieve a maximum dip visibility of 0.58 +/- 0.04 when the two sources are connected via 4.3 km of deployed fiber. Dip visibilities > 0.5 are nonclassical and a first step towards achieving teleportation over the deployed fiber infrastructure. In our experiment, the classical optical communication is achieved with - 21 dBm of optical signal launch power, which is used to synchronize the clocks in the two independent, distantly-located photon sources. The impact of spontaneous Raman scattering from the classical optical signals is mitigated by appropriate choice of the quantum- and classical-channel wavelengths. All equipment used in our experiment (the photon sources and the synchronization setup) is commercially available. Finally, our experiment represents a scalable approach to enabling practical quantum networking with commercial equipment and coexistence with classical communications in optical fiber.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Low-Temperature Electrochemical Upgrading of Bio-oils Using Polymer Electrolyte Membranes

While bio-oil-derived fuels hold much promise as a replacement for petroleum, transformation of the highly oxygenated mixture has proven challenging. In particular, bio-oils are reactive and difficult to upgrade through catalytic pyrolysis. To reach a stabilized product capable of deep deoxygenation at elevated pressure and temperature, conversion or separation of reactive groups is required. This paper describes an electrochemical process for stabilization and upgrading of bio-oils prior to hydrotreating at high pressure and temperature. This electrolytic process uses a three-compartment cell designed to hydrogenate reactive carbonyl components while separating small acid molecules, such as acetic and formic acids, which act as catalysts for condensation reactions and consume hydrogen gas to produce low-value gases in hydrotreating. To avoid conductivity issues, electrodes are appended to anion- and cation-exchange membranes. The cell was tested using a mixed acetic acid and formic acid surrogate fed to the cathode compartment, where the decrease in the concentration followed the applied charge to the cell. Experiments performed using pine pyrolysis oil demonstrated a significant reduction in the total acid number (TAN), an increase in pH from 2.6 to over 4, and a modest reduction of the carbonyl concentration. Analysis showed the reduction in TAN was primarily due to removal of carboxylic compounds. Experiments observed a decrease in the reactive carbonyl (aldehydes and ketones) concentration that followed applied charge. The results with the newly devised reactor show promise for the electrochemical route for upgrading bio-oils, but significant improvements in TAN removal and carbonyl conversion are needed. Given the distributed nature of biomass, an electrochemical process paired with pyrolysis could be used to densify and stabilize an oil product near the source. The densified liquid could then be shipped to centralized refineries for final upgrading to fuel and/or chemical products.

Lister, Tedd↗
DOE OSTI2017

Volume changes upon heating of aerosol particles from biomass burning using transmission electron microscopy

The responses of aerosol particles to heating are important for measurements of their chemical, physical, and optical properties, classification, and determination of origin. However, the thermal behavior of organic aerosol particles is largely unknown. We provide a method to analyze such thermal behavior through heating from room temperature to >600°C by using a heating holder within a transmission electron microscope (TEM). Here we describe in-situ shape and size changes and variations in the compositions of individual particles before and after heating. We use ambient samples from wildland and agricultural biomass fires in North America collected during the 2013 Biomass Burn Observation Project (BBOP). The results indicate that individual tar balls (TB; spherical organic material) from biomass burning retained, on average, up to 30% of their volume when heated to 600°C. Chemical analysis reveals that K and Na remain in the residues, whereas S and O were lost. In contrast to bulk sample measurements of carbonaceous particles using thermal/optical carbon analyzers, our single-particle results imply that many individual organic particles consist of multiple types of organic matter having different thermal stabilities. Beyond TBs, our results suggest that because of their thermal stability some organic particles may not be detectable by using aerosol mass spectrometry or thermal/optical carbon analyzers. This result can lead to an underestimate of the abundance of TBs and other organic particles, and therefore biomass burning may have more influence than currently recognized in regional and global climate models.

Adachi, Kouji↗