SEARCH · Engineering Papers

Results for “Pm”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM 2.5 ) is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM 2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM 2.5 , and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM 2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM 2.5 -attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM 2.5 (>95 µg/m 3 ). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM 2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sources in South Asia.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2023

Evidence for multi-decadal fuel buildup in a large California wildfire from smoke radiocarbon measurements

In recent decades, there has been a significant increase in annual area burned in California's Sierra Nevada mountains. This rise in fire activity has prompted the need to understand how historical forest management practices affect fuel composition and emissions. Here we examined the total carbon (TC) concentration and radiocarbon abundance (Δ 14 C) of particulate matter (PM) emitted by the KNP Complex Fire, which occurred during California's 2021 wildfire season and affected several groves of giant sequoia trees in the southern Sierra Nevada. During a 26 h sampling period, we measured concentrations of fine airborne PM (PM 2.5 ), as well as dry air mole fractions of carbon monoxide (CO) and methane (CH 4 ), using a ground-based mobile laboratory. We also collected filter samples of PM 2.5 for analysis of TC concentration and Δ 14 C. High correlation among PM 2.5 , CO, and CH 4 time series confirmed that our PM 2.5 measurements captured variability in wildfire emissions. Using a Keeling plot approach, we determined that the mean Δ 14 C of PM 2.5 was 111.6 ± 7.7‰ (n = 12), which was considerably enriched relative to atmospheric carbon dioxide in the northern hemisphere in 2021 (-3.2 ± 1.4‰). Combining these Δ 14 C data with a steady-state one-box ecosystem model, we estimated that the mean age of fuels combusted in the KNP Complex Fire was 40 years, with a range of 29–57 years. These results provide evidence for emissions originating from woody biomass, larger-diameter fine fuels, and coarse woody debris that have accumulated over multiple decades. This is consistent with independent field observations that indicate high fire intensity contributed to widespread giant sequoia mortality. With the expanded use of prescribed fires planned over the next decade in California to mitigate wildfire impacts, our measurement approach has the potential to provide regionally-integrated estimates of the effectiveness of fuel treatment programs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

SMBH binary candidate PKS J2134−0153: possible multi-band periodic variability and inter-band time lags

ABSTRACT Studying the periodic flux-variation behaviour of blazars is vital for probing supermassive black hole binaries and the kinematics of relativistic jets. In this work, we report the detection of multi-band possible periodic variations of the blazar PKS J2134−0153, including infrared ($1.6(\pm 0.4)\times 10^3$ day) and optical ($1.8(\pm 1)\times 10^3$ day) wavelengths. The periods in the infrared and optical bands are statistically consistent with the period in the radio band ($P_{\mathrm{Radio}} = 1760\pm 33$ days, obtained from our previous work). Moreover, flux variations in different bands are correlated with evident inter-band time delays, and the time lags of infrared and optical emission with respect to radio emission are $(3.3\pm 2.3)\times 10^{2}$ days and $(3.0\pm 2.3)\times 10^{2}$ days, respectively. The cross-correlations indicate a common origin of radio, infrared, and optical emission. The relative positions between emission regions of infrared and optical emission and radio emission are estimated according to the time lags, i.e. $0.37\pm 0.26$ and $0.33\pm 0.26$ pc. The relative distances seem to be quantitatively consistent with the theoretical prediction.

Ren, Guo-Wei (ORCID:0000000214978371)↗

DOE OSTI2022

Precision Determination of the Neutral Weak Form Factor of Ca 48

In this work, we report a precise measurement of the parity-violating asymmetry $A_{\rm PV}$ in the elastic scattering of longitudinally polarized electrons from $^{48}{\rm Ca}$. We measure $A_{\rm PV} =2668\pm 106\ {\rm (stat)}\pm 40\ {\rm (syst)}$ parts per billion, leading to an extraction of the neutral weak form factor $F_{\rm W} (q=0.8733$ fm$^{-1}) = 0.1304 \pm 0.0052 \ {\rm (stat)}\pm 0.0020\ {\rm (syst)}$ and the charge minus the weak form factor $F_{\rm ch} - F_{\rm W} = 0.0277\pm 0.0055$. The resulting neutron skin thickness $R_n-R_p=0.121 \pm 0.026\ {\rm (exp)} \pm 0.024\ {\rm (model)}$~fm is relatively thin yet consistent with many model calculations. The combined CREX and PREX results will have implications for future energy density functional calculations and on the density dependence of the symmetry energy of nuclear matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Observation of Same-Sign W W Production from Double Parton Scattering in Proton-Proton Collisions at s = 13 TeV

The first observation of the production of W$^\pm$W$^\pm$ bosons from double parton scattering processes using same-sign electron-muon and dimuon events in proton-proton collisions is reported. The data sample corresponds to an integrated luminosity of 138 fb$^{-1}$ recorded at a center-of-mass energy of 13 TeV using the CMS detector at the CERN LHC. Multivariate discriminants are used to distinguish the signal process from the main backgrounds. A binned maximum likelihood fit is performed to extract the signal cross section. The measured cross section for production of same-sign W bosons decaying leptonically is 80.7 $\pm$ 11.2 (stat) $^{+9.5}_{-8.6}$ (syst) $\pm$ 12.1 (model) fb, whereas the measured fiducial cross section is 6.28 $\pm$ 0.81 (stat) $\pm$ 0.69 (syst) $\pm$ 0.37 (model) fb. The observed significance of the signal is 6.2 standard deviations above the background-only hypothesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Picometer sensitivity metrology for EUV absorber phase

With growing interest in EUV attenuated phase-shift masks due to their superior image quality for applications such as dense contact and pillar arrays, it is becoming critical to model, measure, and monitor the intensity and relative phase of multilayer and absorber reflections. We present a solution based on physical modeling of reflectometry data, which can achieve single picometer phase precision and sensitivity to changes in average film thickness below one atomic monolayer. We measure absorber and multilayer reflectivity to determine thin-film parameters with a multidimensional optimization and then acquire a new measurement of either multilayer or absorber to determine perturbations in surface contamination thickness. While it is difficult to assess the accuracy of the first step, the simplicity of the second step allows us to characterize our sensitivity to changes in contamination thickness. Thus, we apply this analysis using an initial set of measurements and repeated measurements after a period of storage. For the multilayer, the total contamination growth was 1068 pm, which occurred almost exclusively during storage (1085 pm) and decreased very slightly during repeated measurements (-17 pm). For the absorber, the behavior was quite different, with a total growth of 126 pm, which occurred much less during storage (28 pm) and primarily during repeated measurements (98 pm). Ultimately, the change in relative phase (absorber minus multilayer) was -0.86 deg for the multilayer and -1.12 deg for the absorber. We estimate the precision of the surface contamination measurement to be 3σ < 6 pm for measuring thickness and 3σ < 0.2 deg for measuring phase.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Effects of Intrusive Confining Units on Groundwater Flow at Pahute Mesa, Nevada National Security Site

Geological, geophysical, hydrogeological, and hydrological evidence indicates that feeder dikes to rhyolitic lava flows may play a role as confining units in the groundwater flow system underlying the Pahute Mesa (PM) area of underground nuclear testing at the Nevada National Security Site (NNSS) (Figure 1). Of geological significance, the PM testing area is largely situated within the Silent Canyon caldera complex (SCCC), which includes both tuffs and lavas that were fed by (and are connected to) intrusive rock units such as feeder dikes prior to and during volcanic eruptions (Orkild et al., 1968; Byers et al., 1976a). Groundwater modeling results presented in this report support extension of “pool-dam” and “breach scenario” concepts presented in Jackson and Fenelon (2018) and Jackson et al. (2021) to low-permeability intrusive confining units (ICUs) such as feeder dikes that are expected to dissect and ring silicic calderas. As laterally extensive, steeply-dipping, and sub-parallel planar structures, ICUs may further compartmentalize groundwater flow in some areas of the volcanic aquifer system at PM. ICUs may explain unusually high horizontal hydraulic gradient southwest of Cheshire. Breaching of an ICU within which the Cheshire test was emplaced may explain changes in water levels before and after the Cheshire test was detonated in the U-20n emplacement hole on 2/14/76 (USDOE, 2015b). This analysis of the effects of ICUs on groundwater flow at PM addresses a need to evaluate uncertainty in the conceptual model or structural aspects of hydrologic source term (HST) or corrective action unit (CAU) models for groundwater flow and contaminant transport (FFACO, 1996, as amended). At Cheshire and possibly other test locations at PM, downgradient extent of radionuclide contamination may be overpredicted by not including the confining effects of ICUs. On the other hand, contaminant extent may be underpredicted by not considering transient flow effects and/or the re-equilibrated flow field caused by breaching of an ICU by an underground nuclear test. Near Cheshire, the effects of ICUs may be most apparent and impactful to the groundwater flow system at PM because of an unusual combination of thickness, extent, and frequency of dikes transecting the saturated CHLFA4 aquifer and feeding into the overlying unsaturated rhyolite lava of Windy Wash. Chapters 2, 3, and 4 present geological, geophysical, hydrogeological, and hydrological evidence for ICUs at PM. Chapters 5 and 6 examine effects of ICUs on groundwater flow including analysis by groundwater modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Influence of Powder Characteristics and Processing Methods on Creep Performance of Powder Metallurgy Hot Isostatic Pressed SS316

The U.S. nuclear energy expansion goals are driving the demand for manufacturing routes that can rapidly produce large, complex, near net shape components. Powder metallurgy hot isostatic pressing (PM HIP) is an advanced manufacturing technique that can be economically scaled-up, while alleviating the supply chain challenges that forging and casting face in terms of cost and lead time constraints. This makes PM-HIP a viable technology to aid and accelerate large-scale part manufacturing for nuclear applications. However, large-scale qualification and deployment of this technology require a thorough understanding of the influence of powder feedstock quality, powder handling history, hot isostatic pressing (HIP) parameters, and subsequent heat treatment on microstructural evolution and elevated temperature mechanical performance. The present work focusses on 316 austenitic stainless steel (SS316) which is most commonly used in high temperature environments for nuclear applications Results from this study show that PM HIPed SS316 meets ASME tensile requirements at room temperature and at elevated temperature. However, creep performance of PM-HIPed SS316 remains inferior to its wrought counterpart, demonstrating that tensile performance alone is not a reliable metric for long duration high temperature integrity. Further, this report delineates powder derived microstructural features that govern creep damage, with key evidences pointing to “microstructural inheritance” from gas atomized powder feedstocks. Commercial SS316 powders of varying chemical compositions and recycling histories were studies, and the results showed large differences in elemental segregation, oxide surface layers and secondary phase distributions. Multi-scale characterization revealed segregation of chromium, molybdenum, manganese and silicon at the boundaries and the precipitation of manganese-, silicon-, and molybdenum-oxides. During HIP consolidation, these surface oxides transform into decorated prior particle boundaries (PPBs) and grain boundary inclusions that persist through conventional post-HIP solution annealing treatment. The retained oxides in post-HIP microstructures were found to influence grain growth, precipitation behavior, and ultimately creep cavitation and fracture. Such post-HIP heat treatments are therefore limited by a complex trade-off between grain growth, and oxide coarsening which aggravate creep damage by acting as nucleation sites for cavities. The objective of this work is to establish an integrated processing–structure–property framework for PM-HIP 316 stainless steel by investigating the influence of powder feedstock characteristics in pre- and post-HIP processing as well as to understand the significance of post-HIP heat treatment on microstructural evolution and creep properties. The results from this report emphasize the significance of powder feedstock integrity in improving creep performance of PM-HIPed SS316, by highlight the effect of rapid solidification, elemental segregation, oxide formation and powder recycling on microstructural defect inheritance following HIP consolidation. Rather than considering HIP processing, solution annealing, and mechanical performance independently, this report treats powder production, HIP consolidation, post-HIP thermal processing, and creep deformation as interconnected stages within a continuous metallurgical process. The resulting framework will provide a scientific basis for developing feedstock engineering strategies capable of improving long-term reliability of PM-HIP stainless steels and accelerating their qualification for advanced nuclear applications.

Ajjarapu, Pavan [Oak Ridge National Laboratory (OR↗

DOE OSTI2020

Air quality impact of the Northern California Camp Fire of November 2018

The Northern California Camp Fire that took place in November 2018 was one of the most damaging environmental events in California history. Here, we analyze ground-based station observations of airborne particulate matter that has a diameter <2.5 µm (PM 2.5 ) across Northern California and conduct numerical simulations of the Camp Fire using the Weather Research and Forecasting model online coupled with chemistry (WRF-Chem). Simulations are evaluated against ground-based observations of PM 2.5 , black carbon, and meteorology, as well as satellite measurements, such as Tropospheric Monitoring Instrument (TROPOMI) aerosol layer height and aerosol index. The Camp Fire led to an increase in Bay Area PM 2.5 to over 50 µg m –3 for nearly 2 weeks, with localized peaks exceeding 300 µg m –3 . Using the Visible Infrared Imaging Radiometer Suite (VIIRS) high-resolution fire detection products, the simulations reproduce the magnitude and evolution of surface PM 2.5 concentrations, especially downwind of the wildfire. The overall spatial patterns of simulated aerosol plumes and their heights are comparable with the latest satellite products from TROPOMI. WRF-Chem sensitivity simulations are carried out to analyze uncertainties that arise from fire emissions, meteorological conditions, feedback of aerosol radiative effects on meteorology, and various physical parameterizations, including the planetary boundary layer model and the plume rise model. Downwind PM 2.5 concentrations are sensitive to both flaming and smoldering emissions over the fire, so the uncertainty in the satellite-derived fire emission products can directly affect the air pollution simulations downwind. Our analysis also shows the importance of land surface and boundary layer parameterization in the fire simulation, which can result in large variations in magnitude and trend of surface PM 2.5 . Inclusion of aerosol radiative feedback moderately improves PM 2.5 simulations, especially over the most polluted days. Results of this study can assist in the development of data assimilation systems as well as air quality forecasting of health exposures and economic impact studies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Global source apportionment of aerosols into major emission regions and sectors over 1850–2017

Anthropogenic emissions of aerosols and precursor gases have changed significantly in the past few decades around the world. In this study, the Explicit Aerosol Source Tagging (EAST) system is merged into the Energy Exascale Earth System Model version 1 (E3SMv1) to quantify the variations in anthropogenic aerosol concentrations, source contributions, and their subsequent radiative impact in four major emission regions across the globe during 1850–1980, 1980–2010, and 2010–2017. In North America and Europe, changes in anthropogenic PM 2.5 were mainly caused by changes in emissions from local energy and industrial sectors. The local industrial sector caused the largest increase in PM 2.5 in East Asia during 1980–2010 and decrease during 2010–2017. In South Asia, the increase in energy-related emissions dominated the rise in PM 2.5 levels during 1980–2017. During 1850–1980, the increases in emissions from North America contributed to the increase in the European PM 2.5 burden by 1.7 mg m -2 and the sources from the Europe were also responsible for the PM 2.5 burden increase in East Asia and South Asia by about 1.0 mg m -2 . During 1980–2010, East Asia contributed to an increase of 0.4–0.6 mg m -2 in the PM 2.5 burden in North America and Europe, while South Asia contributed about 0.3 mg m -2 . During 2010–2017, the contributions from East Asia to the PM 2.5 burdens in the North America, Europe, and South Asia declined by 0.3–0.6 mg m -2 due to the clean air actions in China, while the contributions from South Asia still increased due to the continuous increase in emissions in South Asia. The historical changes in aerosols had an impact on effective radiative forcing through aerosol–radiation interactions (ERF ari ). During 1980–2010, a decline in North American aerosols resulted in a positive ERF ari change (warming effect) in Europe and a decline in aerosols in Europe caused a warming effect in Russia and northern China. The changes in ERF ari from the increase and decrease in aerosols in China during 1980–2010 and 2010–2017, respectively, are comparable in magnitude. The continuous aerosol increases in South Asia from 1980 to 2017 resulted in negative ERF ari (cooling) changes in South Asia, Southeast Asia, and southern China.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

Electrostatic Beneficiation of Lunar Simulant

Electrostatic beneficiation of lunar regolith is a method allowing refinement of specific minerals in the material for processing on the moon. The use of tribocharging the regolith prior to separation was investigated on the lunar simulant MLS-I by passing the dust through static mixers constructed from different materials; aluminum, copper, stainless steel, and polytetrafluoroethylene (PTFE). The amount of charge acquired by the simulant was dependent upon the difference in the work function of the dust and the charging material. XPS and SEM were used to characterize the simulant after it was sieved into five size fractions (> 100 pm, 75-100 pm, 50- 75 pm, 50-25 pm, and < 25 pm), where very little difference in surface composition was observed between the sizes. Samples of the smallest (< 25 pm) and largest (> 100 pm) size fractions were beneficiated through a charge separator using the aluminum (charged the simulant negatively) and PTFE (charged positively) mixers. The mass fractions of the separated simulant revealed that for the larger particle size, significant unipolar charging was observed for both mixers, whereas for the smaller particle sizes, more bipolar charging was observed, probably due to the finer simulant adhering to the inside of the mixers shielding the dust from the charging material. Subsequent XPS analysis of the beneficiated fractions showed the larger particle size fraction having some species differentiation, but very little difference for the smaller.size. Although MLS-1 was made to have similar chemistry to actual lunar dust, its mineralogy is quite different. On-going experiments are using NASA JSC-1 lunar simulant. A vacuum chamber has been constructed, and future experiments are planned in a simulated lunar environment.

Trigwell, Steve↗

NASA NTRS2016

Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors

We estimated global fine particulate matter (PM(sub 2.5)) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically-based satellite-derived PM(sub 2.5) estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998−2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM(sub 2.5) estimates were highly consistent (R(sup 2) equals 0.81) with out-of-sample cross-validated PM(sub 2.5) concentrations from monitors. The global population-weighted annual average PM(sub 2.5) concentrations were 3-fold higher than the 10 micrograms per cubic meter WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM(sub 2.5) data sources can yield valuable improvements to PM(sub 2.5) characterization on a global scale.

aerosols↗

NASA NTRS2016

The Effect of Future Ambient Air Pollution on Human Premature Mortality to 2100 Using Output from the ACCMIP Model Ensemble

Ambient air pollution from ground-level ozone and fine particulate matter (PM(sub 2.5)) is associated with premature mortality. Future concentrations of these air pollutants will be driven by natural and anthropogenic emissions and by climate change. Using anthropogenic and biomass burning emissions projected in the four Representative Concentration Pathway scenarios (RCPs), the ACCMIP ensemble of chemistry climate models simulated future concentrations of ozone and PM(sub 2.5) at selected decades between 2000 and 2100. We use output from the ACCMIP ensemble, together with projections of future population and baseline mortality rates, to quantify the human premature mortality impacts of future ambient air pollution. Future air-pollution-related premature mortality in 2030, 2050 and 2100 is estimated for each scenario and for each model using a health impact function based on changes in concentrations of ozone and PM(sub 2.5) relative to 2000 and projected future population and baseline mortality rates. Additionally, the global mortality burden of ozone and PM(sub 2.5) in 2000 and each future period is estimated relative to 1850 concentrations, using present-day and future population and baseline mortality rates. The change in future ozone concentrations relative to 2000 is associated with excess global premature mortality in some scenarios/periods, particularly in RCP8.5 in 2100 (316 thousand deaths per year), likely driven by the large increase in methane emissions and by the net effect of climate change projected in this scenario, but it leads to considerable avoided premature mortality for the three other RCPs. However, the global mortality burden of ozone markedly increases from 382000 (121000 to 728000) deaths per year in 2000 to between 1.09 and 2.36 million deaths per year in 2100, across RCPs, mostly due to the effect of increases in population and baseline mortality rates. PM(sub 2.5) concentrations decrease relative to 2000 in all scenarios, due to projected reductions in emissions, and are associated with avoided premature mortality, particularly in 2100: between 2.39 and 1.31 million deaths per year for the four RCPs. The global mortality burden of PM(sub 2.5) is estimated to decrease from 1.70 (1.30 to 2.10) million deaths per year in 2000 to between 0.95 and 1.55 million deaths per year in 2100 for the four RCPs due to the combined effect of decreases in PM(sub 2.5) concentrations and changes in population and baseline mortality rates. Trends in future air-pollution-related mortality vary regionally across scenarios, reflecting assumptions for economic growth and air pollution control specific to each RCP and region. Mortality estimates differ among chemistry climate models due to differences in simulated pollutant concentrations, which is the greatest contributor to overall mortality uncertainty for most cases assessed here, supporting the use of model ensembles to characterize uncertainty. Increases in exposed population and baseline mortality rates of respiratory diseases magnify the impact on premature mortality of changes in future air pollutant concentrations and explain why the future global mortality burden of air pollution can exceed the current burden, even where air pollutant concentrations decrease.

Silva, Raquel A.↗

NASA NTRS2016

Characterization of Particulate Matter Profiling and Alveolar Deposition from Biomass Burning in Northern Thailand: The 7-SEAS Study

Biomass burning (BB) frequently occurs in SouthEast Asia (SEA), which significantly affects the air quality and could consequently lead to adverse health effects. The aim of this study was to characterize particulate matter (PM) and black carbon (BC) emitted from BB source regions in SEA and their potential of deposition in the alveolar region of human lungs. A 31-day characterization of PM profiling was conducted at the Doi Ang Khang (DAK) meteorology station in northern Thailand in March 2013. Substantial numbers of PM (10147 +/- 5800 # per cubic centimeter) with a geometric mean diameter (GMD) of 114.4 +/- 9.2 nm were found at the study site. The PM of less than 2.5 micron in aerodynamic diameter (PM sub 2.5) hourly-average mass concentration was 78.0 +/- 34.5 per cubic microgram whereas the black carbon (BC) mass concentration was 4.4 +/- 2.6 micrograms per cubic meter. Notably, high concentrations of nanoparticle surface area (100.5 +/- 54.6 square micrometers per cubic centimeter) emitted from biomass burning can be inhaled into the human alveolar region. Significant correlations with fire counts within different ranges around DAK were found for particle number, the surface area concentration of alveolar deposition, and BC. In conclusion, biomass burning is an important PM source in SEA, particularly nanoparticles, which has high potency to be inhaled into the lung environment and interact with alveolar cells, leading to adverse respiratory effects. The fire counts within 100 to 150 km shows the highest Pearson's r for particle number and surface area concentration. It suggests 12 to 24 hr could be a fair time scale for initial aging process of BB aerosols. Importantly, the people lives in this region could have higher risk for PM exposure.

biomass burning↗

NASA NTRS2022

Secondary Inorganic Aerosol Chemistry and Its Impact on Atmospheric Visibility Over an Ammonia-Rich Urban Area in Central Taiwan

This study investigated the hourly inorganic aerosol chemistry and its impact on atmospheric visibility over an urban area in Central Taiwan, by relying on measurements of aerosol light extinction, inorganic gases, and PM 2.5 water-soluble ions (WSIs), and simulations from a thermodynamic equilibrium model. On average, the sulfate (SO 4 2− ), nitrate (NO 3 − ), and ammonium (NH 4 + ) components (SNA) contributed ∼90% of WSI concentrations, which in turn made up about 50% of the PM 2.5 mass. During the entire observation period, PM 2.5 and SNA concentrations, aerosol pH, aerosol liquid water content (ALWC), and sulfur and nitrogen conversion ratios all increased with decreasing visibility. In particular, the NO 3 − contribution to PM 2.5 increased, whereas the SO 4 2− contribution decreased, with decreasing visibility. The diurnal variations of the above parameters indicate that the interaction and likely mutual promotion between NO 3 − and ALWC enhanced the hygroscopicity and aqueous-phase reactions conducive for NO 3 − formation, thus led to severely impaired visibility. The high relative humidity (RH) at the study area (average 70.7%) was a necessary but not sole factor leading to enhanced NO 3 − formation, which was more directly associated with elevated ALWC and aerosol pH. Simulations from the thermodynamic model depict that the inorganic aerosol system in the study area was characterized by fully neutralized SO 4 2− (i.e. a saturated factor in visibility reduction) and excess NH 4 + amidst a NH 3 -rich environment. As a result, PM 2.5 composition was most sensitive to gas-phase HNO 3 , and hence NOx, and relatively insensitive to NH 3 . Consequently, a reduction of NOx would result in instantaneous cuts of NO 3 − , PM 2.5 , and ALWC, and hence improved visibility. On the other hand, a substantial amount of NH 3 reduction (>70%) would be required to lower the aerosol pH, driving more than 50% of the particulate phase NO 3 − to the gas phase, thereby making NH 3 a limiting factor in shifting PM 2.5 composition.

aerosol chemistry↗

NASA NTRS2023

Automated Machine Learning to Evaluate the Information Content of Tropospheric Trace Gas Columns for Fine Particle Estimates Over India: A Modeling Testbed

India is largely devoid of high-quality and reliable on-the-ground measurements of fine particulate matter (PM 2.5 ). Ground-level PM 2.5 concentrations are estimated from publicly available satellite Aerosol Optical Depth (AOD) products combined with other information. Prior research has largely overlooked the possibility of gaining additional accuracy and insights into the sources of PM using satellite retrievals of tropospheric trace gas columns. We evaluate the information content of tropospheric trace gas columns for PM 2.5 estimates over India within a modeling testbed using an Automated Machine Learning (AutoML) approach, which selects from a menu of different machine learning tools based on the data set. We then quantify the relative information content of tropospheric trace gas columns, AOD, meteorological fields, and emissions for estimating PM 2.5 over four Indian sub-regions on daily and monthly time scales. Our findings suggest that, regardless of the specific machine learning model assumptions, incorporating trace gas modeled columns improves PM 2.5 estimates. We use the ranking scores produced from the AutoML algorithm and Spearman’s rank correlation to infer or link the possible relative importance of primary versus secondary sources of PM 2.5 as a first step toward estimating particle composition. Our comparison of AutoML-derived models to selected baseline machine learning models demonstrates that AutoML is at least as good as user-chosen models. The idealized pseudo-observations (chemical-transport model simulations) used in this work lay the groundwork for applying satellite retrievals of tropospheric trace gases to estimate fine particle concentrations in India and serve to illustrate the promise of AutoML applications in atmospheric and environmental research.

Machine learning↗

DOE OSTI2023

Integration of Nuclear Material Accounting Data and Process Monitoring Data for Improvement on Detection Probability in Safeguarding Electrochemical Processing Facilities (Final Technical Report)

The KAERI advanced spent fuel conditioning process (ACP) process is a critical component of the US- South Korean nuclear cooperation and the following “123 Agreement.” Its development has received considerable attention in both countries. The ACP is an electrochemical processing (pyroprocessing) that recycles over 96% of the used nuclear fuel (UNF). It is also intrinsically proliferation-resistant in theory. In normal operation, the U/TRU product is very hot radiologically. In addition, the Cm provides a high level of spontaneous neutrons, making the product unsuitable for weapon use. However, as pointed in some study, “the need for safeguards to protect against the diversion and misuse of separated plutonium applies essentially equally to all grades of plutonium.” As pointed by many studies, the well-established traditional Nuclear Material Accounting (NMA) approach cannot be directly applied to electrochemical processing because of the lack of an input accountability tank, the non-continuous material flow, and the unsatisfactory level of confidence in sampling methods. Therefore, nuclear safeguards remain a grand challenge in the developing of commercial electrochemical separations facilities, especially around the heart of such facilities, the electrorefiner (ER) systems. In contrast to NMA data, process monitoring (PM) data is normally an indirect measurement of the SNM and is acquired much more frequently. In a broad sense, PM includes monitoring by various types of equipment, e.g. radiation detectors, cameras, voltage, current sensors. Because it is already being collected by the operator, the additional cost to safeguards is low. It has long been believed that PM data can supplement NMA data and help improve safeguards, although the benefits are hard to quantify. The U.S. DOE’s Material Protection, Accounting, and Control Technology (MPACT) campaign has made substantial investments into innovative PM sensor technology and predictive model development for real- or near real-time measurement and prediction of molten salt density and level, salt composition and actinide concentration especially Pu, the cell voltage, and the cell current to supplement traditional NMA. For aqueous-based reprocessing facilities, it is reported that PM, integrated with traditional NMA, have a high detection probability for specific diversions. For electrochemical reprocessing, preliminary studies have shown that PM data can support traditional NMA in various ways by providing a basis to estimate some of the in-processing nuclear material inventories. Despite early success, further studies on fusion of PM data and NMA data are still needed, which is the goal of this proposed work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Particulate matter sensor

Microfabricated PM sensors measure concentrations of particulate matter (PM) in air. Some sensors improve the accuracy of measurements by accounting for the effect of ambient conditions (e.g., temperature or humidity) on mass-sensitive elements employed to determine a mass of the PM in a stream of air. Some sensors improve the accuracy of measurements by controlling humidity in the stream of air measured by mass-sensitive elements. Some sensors employ a plurality of mass-sensitive elements to extend the useful life of the PM sensor. Some sensors employ one or more mass-sensitive elements and heating elements to cause deposition and allow measurement of different sizes of PM. Some sensors can measure mass concentration of coarse PM in addition to fine PM in a stream of air. Some sensors control the flow rate of a stream of air measured by mass-sensitive elements. Some sensors include features to mitigate electromagnetic interference or electromagnetic signal loss.

Paprotny, Igor↗