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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dark Energy Survey: A 2.1% measurement of the angular baryonic acoustic oscillation scale at redshift z eff = 0.85 from the final dataset

Here, we present the angular diameter distance measurement obtained with the baryonic acoustic oscillation (BAO) feature from galaxy clustering in the completed Dark Energy Survey, consisting of six years (Y6) of observations. We use the Y6 BAO galaxy sample, optimized for BAO science in the redshift range 0.6 < z <1.2, with an effective redshift at z eff = 0.85 and split into six tomographic bins. The sample has nearly 16 million galaxies over 4,273 square degrees. Our consensus measurement constrains the ratio of the angular distance to sound horizon scale to D M ⁡(z eff )/r d = 19.51 ± 0.41 (at 68.3% confidence interval), resulting from comparing the BAO position in our data to that predicted by planck Λ⁢CDM via the BAO shift parameter α =(D M /r d )/(D M /r d ) PLANCK . To achieve this, the BAO shift is measured with three different methods, angular correlation function (ACF), angular power spectrum (APS), and projected correlation function (PCF), obtaining α = 0.952 ± 0.023, 0.962 ± 0.022, and 0.955 ± 0.020, respectively, which we combine to α = 0.957 ± 0.020, including systematic errors. When compared with the Λ⁢CDM model that best fits planck data, this measurement is found to be 4.3% and 2.1⁢σ below the angular BAO scale predicted. To date, it represents the most precise angular BAO measurement at z > 0.75 from any survey and the most precise measurement at any redshift from photometric surveys. The analysis was performed blinded to the BAO position, and it is shown to be robust against analysis choices, data removal, redshift calibrations, and observational systematics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Improvements to the 115g/115m Cd Nuclear Data

Repeated measurements of the isotope 115m Cd by Los Alamos National Laboratory (LANL), Pacific Northwest National Laboratory (PNNL), and Atomic Weapons Establishment (AWE) have revealed a consistent discrepancy between beta and gamma counting. This suggests that a significant disparity exists between the true value of the isotope’s gamma-ray branching ratios and the values reported by the National Nuclear Data Center (NNDC). Enriched 114 Cd was irradiated using thermal neutrons to produce a high-purity 115m/g Cd source for counting and analysis using traditional singles gamma-ray spectroscopy, liquid scintillation counting, gas-proportional counting, and analysis using the new Gamma-Alpha-Beta-Gamma (GABγ) and Gamma-Alpha-Beta Radio-Isotope EvaLuator (GABRIEL) coincidence detection systems. Using the D-T fusion generated neutrons, reduces the wait time required to let the short-lived 115Cd ground state decay away by leveraging the 1:1 production ratio of the ground and metastable state of 115 Cd from the 115 In (n,p) reaction relative to the 10:1 production ratio of the ground and metastable isotopes of 115 Cd by thermal neutron capture on 114 Cd. However, the much higher flux in from the Washington State University TRIGA reactor is a more rapid method of production of 115m/gCd but requires access to enriched 114 Cd. High purity 115m/g Cd samples were analyzed on regular intervals over a period of 140-days. The activity of 115m Cd measured by beta and gamma show a clear discrepancy using the current best known gamma-ray decay branching ratios. Based on these observations and measurements, a set of new branching ratio recommendations have been produced using conventional counting techniques and the advanced GAB? and GABRIEL instruments.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets

This dataset contains turbine- and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in Steady State (FLORIS) model, version 2.3.0. The 252,500 cases include 500 unique wind plants generated randomly by a specialized Plant Layout Generator (PLayGen) that samples randomized realizations of wind plant layouts from one of four canonical configurations: (i) cluster, (ii) single string, (iii) multiple string, (iv) parallel string. Other wind plant layout parameters were also randomly sampled, including the number of turbines (25-200) and the mean turbine spacing (3D-10D, where D denotes the turbine rotor diameter). For each layout, 500 different sets of atmospheric conditions were randomly sampled. These include wind speed in 0-25 m/s, wind direction in 0 deg.-360 deg., and turbulence intensity chosen from low (6%), medium (8%), and high (10%). For each atmospheric inflow scenario, the individual turbine yaw angles were randomly sampled from a one-sided truncated Gaussian on the interval 0 deg.-30 deg. oriented relative to wind inflow direction. This random data is supplemented with a collection of yaw-optimized samples where FLORIS was used to determine turbine yaw angles that maximize power production for the entire plant. To generate this data, a subset of cases were selected (50 atmospheric conditions from 50 layouts each for a total of additional 2,500 cases) for which FLORIS was re-run with wake steering control optimization. The IEA onshore reference turbine, which has a 130 m rotor diameter, a 110 m hub height, and a rated power capacity of 3.4 MW was used as the turbine for all simulations. The simulations were performed using NREL's Eagle high performance computing system in February 2021 as part of the Spatial Analysis for Wind Technology Development project funded by the U.S. Department of Energy Wind Energy Technologies Office. The data was collected, reformatted, and preprocessed for this OEDI submission in May 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub repository under explore_wind_plant_data_h5.ipynb.

AI↗
NASA NTRS1993

Evidence for a fundamental period of the sun and its relation to the 154 day complex of periodicities

We have analyzed the longitude distributions of major flares observed in the 1955-1991 interval, referring them to coordinate systems rotating about axes tilted with respect to the rotation axis of the solar envelope. We find that the longitude distribution exhibits the largest modulation in the coordinate system with the following parameters: rotation period, 25.50 days; tilt angle of the rotation axis, 40 deg; tilt direction, toward the position of the earth on December 4 in its orbit around the sun. We interpret this as being due to an obliquely rotating structure (or a wave pattern rotating about an oblique axis) which has two exciters. We identify the period of 25.50 days as the fundamental period of the hypothetical 'clock' proposed by Bai and Sturrock (1991). The periods of the subharmonics are 51.0, 76.5, 102.0, 127.5, and 153.0 days, in agreement with periodicities found from analysis of flare occurrence times.

Bai, T.↗
NASA NTRS2017

Chandra's Observations of Jupiter's X-Ray Aurora During Juno Upstream and Apojove Intervals

The Chandra space telescope has recently conducted a number of campaigns to observe Jupiter's X-ray aurora. The first set of campaigns took place in summer 2016 while the Juno spacecraft was upstream of the planet sampling the solar wind. The second set of campaigns took place in February, June and August 2017 at times when the Juno spacecraft was at apojove (expected close to the magnetopause). We report on these upstream and apojove campaigns including intensities and periodicities of auroral X-ray emissions. This new era of jovian X-ray astronomy means we have more data than ever before, long observing windows (up to 72 kiloseconds for this Chandra set), and successive observations relatively closely spaced in time. These features combine to allow us to pursue novel methods for examining periodicities in the X-ray emission. Our work will explore significance testing of emerging periodicities, and the search for coherence in X-ray pulsing over weeks and months, seeking to understand the robustness and regularity of previously reported hot spot X-ray emissions. The periods that emerge from our analysis will be compared against those which emerge from radio and UV wavelengths.

Lunar & Planetary Science & Exploratio↗
DOE OSTI2022

A mathematical assessment of the isolation random forest method for anomaly detection in big data

We present the mathematical analysis of the Isolation Random Forest Method (IRF Method) for anomaly detection, proposed by Liu F.T., Ting K.M. and Zhou Z. H. in their seminal work as a heuristic method for anomaly detection in Big Data. We prove that the IRF space can be endowed with a probability induced by the Isolation Tree algorithm (iTree). In this setting, the convergence of the IRF method is proved, using the Law of Large Numbers. Here, a couple of counterexamples are presented to show that the method is inconclusive and no certificate of quality can be given, when using it as a means to detect anomalies. Hence, an alternative version of the method is proposed whose mathematical foundation is fully justified. Furthermore, a criterion for choosing the number of sampled trees needed to guarantee confidence intervals of the numerical results is presented. Finally, numerical experiments are presented to compare the performance of the classic method with the proposed one.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Satellite detection of phytoplankton export from the mid-Atlantic Bight during the 1979 spring bloom

Analysis of Coastal Zone Color Scanner (CZCS) imagery confirms shipboard and in situ moored fluorometer observations of resuspension of near-bottom chlorophyll within surface waters (1 to 10 m) by northwesterly wind events in the mid-Atlantic Bight. As much as 8 to 16 micrograms chl/l are found during these wind events from March to May, with a seasonal increase of algal biomass until onset of stratification of the water column. Rapid sinking or downwelling apparently occurs after subsequent wind events, however, such that the predominant surface chlorophyll pattern is approx. 0.5 to 1.5 micrograms/l over the continental shelf during most of the spring bloom. Perhaps half of the chlorophyll increase observed by satellite during a wind resuspension event represents in-situ production during the 4 to 5 day interval, with the remainder attributed to accumulation of algal biomass previously produced and temporarily stored within near-bottom water. Present calculations suggest that about 10% of the primary production of the spring bloom may be exported as ungrazed phytoplankton carbon from mid-Atlantic shelf waters to those of the continental slope.

Walsh, J. J.↗
NASA NTRS1995

The effect of sensor sheltering and averaging techniques on wind measurements at the Shuttle Landing Facility

This document presents results of a field study of the effect of sheltering of wind sensors by nearby foliage on the validity of wind measurements at the Space Shuttle Landing Facility (SLF). Standard measurements are made at one second intervals from 30-feet (9.1-m) towers located 500 feet (152 m) from the SLF centerline. The centerline winds are not exactly the same as those measured by the towers. A companion study, Merceret (1995), quantifies the differences as a function of statistics of the observed winds and distance between the measurements and points of interest. This work examines the effect of nearby foliage on the accuracy of the measurements made by any one sensor, and the effects of averaging on interpretation of the measurements. The field program used logarithmically spaced portable wind towers to measure wind speed and direction over a range of conditions as a function of distance from the obstructing foliage. Appropriate statistics were computed. The results suggest that accurate measurements require foliage be cut back to OFCM standards. Analysis of averaging techniques showed that there is no significant difference between vector and scalar averages. Longer averaging periods reduce measurement error but do not otherwise change the measurement in reasonably steady flow regimes. In rapidly changing conditions, shorter averaging periods may be required to capture trends.

Merceret, Francis J.↗
NASA NTRS2001

Evidence-Based Approach to the Analysis of Serious Decompression Sickness with Application to EVA Astronauts

It is important to understand the risk of serious hypobaric decompression sickness (DCS) in order to develop procedures and treatment responses to mitigate the risk. Since it is not ethical to conduct prospective tests about serious DCS with humans, the necessary information was gathered from 73 published reports. We hypothesize that a 4-hr 100% oxygen (O2) prebreathe results in a very low risk of serious DCS, and test this through analysis. We evaluated 258 tests containing information from 79,366 exposures in attitude chambers. Serious DCS was documented in 918 men during the tests. Serious DCS are signs and symptoms broadly classified as Type II DCS. A risk function analysis with maximum likelihood optimization was performed to identify significant explanatory variables, and to create a predictive model for the probability of serious DCS [P(serious DCS)]. Useful variables were Tissue Ratio, the planned time spent at altitude (T(sub alt)), and whether or not repetitive exercise was performed at altitude. Tissue Ratio is P1N2/P2, where P1N2 is calculated nitrogen (N2) pressure in a compartment with a 180-min half-time for N2 pressure just before ascent, and P2 is ambient pressure after ascent. A prebreathe and decompression profile Shuttle astronauts use for extravehicular activity (EVA) includes a 4-hr prebreathe with 100% O2, an ascent to P2 = 4.3 lb per sq. in. absolute, and a T(sub alt) = 6 hr. The P(serious DCS) is: 0.0014 (0.00096 - 0.00196, 95% confidence interval) with exercise and 0.00025 (0.00016 - 0.00035) without exercise. Given 100 Shuttle EVAs to date and no report of serious DCS, the true risk is less than 0.03 with 95% confidence (Binomial Theorem). It is problematic to estimate the risk of serious DCS since it appears infrequently, even if the estimate is based on thousands of altitude chamber exposures. The true risk to astronauts may lie between the extremes of the confidence intervals (0.00016 - 0.00196) since the contribution of other factors, particularly exercise, to the risk of serious DCS during EVA is unknown. A simple model that only accounts for four important variables in retrospective data is still helpful to increase our understanding about the risk of serious DCS.

Conkin, Johnny↗
NASA NTRS2002

CIMEL Measurements of Zenith Radiances at the ARM Site

Starting from October 1, 2001, Cimel at the ARM Central Facility in Oklahoma has been switched to a new "cloud mode." This mode allows taking measurements of zenith radiance when the Sun in blocked by clouds. In this case, every 13 min. Cimel points straight up and takes 10 measurements with 9 sec. time interval. The new Cimel's mode has four filters at 440, 670, 870 and 1020 nm. For cloudy conditions, the spectral contrast in surface albedo dominates over Rayleigh and aerosol effects; this makes normalized zenith radiances at 440 and 670 as well as for 870 and 1020 almost indistinguishable. We compare Cimel measurements with other ARM cart site instruments: Multi-Filter Rotating Shadowband Radiometer (MFRSR), Narrow Field of View (NFOV) sensor, and MicroWave Radiometer(MWR). Based on Cimel and MFRSR 670 and 870 nm channels, we build a normalized difference cloud index (NDCI) for radiances and fluxes, respectively. Radiance NDCI from Cimel and flux NDCI from MFRSR are compared between themselves as well as with cloud Liquid Water Path (LWP) retrieved from MWR. Based on our theoretical calculations and preliminary data analysis,there is a good correlation between NDCIs and LWP for cloudy sky above green vegetation. Based on this correlation, an algorithm to retrieve cloud optical depth from NDCI is proposed.

Marshak, Alexander↗
NASA NTRS2000

CHO cell enlargement oscillates with a temperature-compensated period of 24 min

The rate of increase in cell area of CHO cells when measured at intervals of 1 min using a light microscope equipped with a video measurement system, oscillated with a minimum period of about 24 min. The pattern of oscillations paralleled those of the 24 min period observed with the oxidation of NADH by an external cell surface or plasma membrane NADH oxidase. The increase in cell area was non-linear. Intervals of rapid increase in area alternated with intervals of rapid decrease in area. The length of the 24 min period was temperature-compensated (approximately the same when measured at 14 degrees C, 24 degrees C or 34 degrees C) while the rate of cell enlargement increased with temperature over this same range of temperatures.

Non-NASA Center↗
NASA NTRS1984

Design Spectrum Analysis in NASTRAN

The utility of Design Spectrum Analysis is to give a mode by mode characterization of the behavior of a design under a given loading. The theory of design spectrum is discussed after operations are explained. User instructions are taken up here in three parts: Transient Preface, Maximum Envelope Spectrum, and RMS Average Spectrum followed by a Summary Table. A single DMAP ALTER packet will provide for all parts of the design spectrum operations. The starting point for getting a modal break-down of the response to acceleration loading is the Modal Transient rigid format. After eigenvalue extraction, modal vectors need to be isolated in the full set of physical coordinates (P-sized as opposed to the D-sized vectors in RF 12). After integration for transient response the results are scanned over the solution time interval for the peak values and for the times that they occur. A module called SCAN was written to do this job, that organizes these maxima into a diagonal output matrix. The maximum amplifier in each mode is applied to the eigenvector of each mode which then reveals the maximum displacements, stresses, forces and boundary reactions that the structure will experience for a load history, mode by mode. The standard NASTRAN output processors have been modified for this task. It is required that modes be normalized to mass.

Butler, T. G.↗
NASA NTRS2010

Role of the Russell-McPherron Effect in the Acceleration of Relativistic Electrons

While it is well known that high fluxes of relativistic electrons in the Earth's radiation belts are associated with high-speed solar wind and its heightened geoeffectiveness,less known is the fact that the Russell McPherron(R M) effect strongly controls whether or not a given high-speed stream is geoffective. To test whether it then follows that the R M effect also strongly controls fluxes of relativistic electrons, we perform a superposed epoch analysis across corotating interaction regions (CIR) keyed on the interfaces between slow and fast wind. A total of 394 stream interfaces were identified in the years 1994-2006. Equinoctial interfaces were separated into four classes based on the R-M effect,that is, whether the solar wind on either side of the interface was either(geo)effective (E) or ineffective (I) depending on season and the polarity of the interplanetary magnetic field (IMF). Four classes of interface identified as II, IE, EI,and EE are possible. The classes IE and EI correspond to CIRs with polarity changes indicating passage through the heliospheric current sheet. To characterize the behavior of solar wind and magnetospheric variables, we produced maps of dynamic cumulative probability distribution functions (cdfs) as a function of time over 10-day intervals centered on the interfaces. These reveal that effective high-speed streams have geomagnetic activity nearly twice as strong as ineffective streams and electron fluxes a factor of 12 higher. In addition they show that an effective low-speed stream increases the flux of relativistic electrons before the interface so that an effective to ineffective transition results in lower fluxes after the interface.We conclude that the R-M effect plays a major role in organizing and sustaining a sequence of physical processes responsible for the acceleration of relativistic electrons.

McPherron, R. L.↗
NASA NTRS2012

Eclipse-Free-Time Assessment Tool for IRIS

IRIS_EFT is a scientific simulation that can be used to perform an Eclipse-Free- Time (EFT) assessment of IRIS (Infrared Imaging Surveyor) mission orbits. EFT is defined to be those time intervals longer than one day during which the IRIS spacecraft is not in the Earth s shadow. Program IRIS_EFT implements a special perturbation of orbital motion to numerically integrate Cowell's form of the system of differential equations. Shadow conditions are predicted by embedding this integrator within Brent s method for finding the root of a nonlinear equation. The IRIS_EFT software models the effects of the following types of orbit perturbations on the long-term evolution and shadow characteristics of IRIS mission orbits. (1) Non-spherical Earth gravity, (2) Atmospheric drag, (3) Point-mass gravity of the Sun, and (4) Point-mass gravity of the Moon. The objective of this effort was to create an in-house computer program that would perform eclipse-free-time analysis. of candidate IRIS spacecraft mission orbits in an accurate and timely fashion. The software is a suite of Fortran subroutines and data files organized as a "computational" engine that is used to accurately predict the long-term orbit evolution of IRIS mission orbits while searching for Earth shadow conditions.

Eagle, David↗
NASA NTRS1973

Urban and regional land use analysis: CARETS and Census Cities experiment package

The author has identified the following significant results. The arrival of the so-called energy crisis makes the portion of this experiment dealing with land use climatology of more immediate significance than before, since in addition to helping to understand the processes of climatic change associated with urbanization, the knowledge obtained may be useful in assigning an energy balance impact factor to proposed changes in land use in and around cities. Thermal maps derived from S-192 data are to be used as a measure of the energy being radiated into space from the mosaic of different surfaces in and around the city. While presenting excellent spatial sampling potential for a metropolitan area tests site, the Skylab data permit a very poor temporal sampling opportunity, owing to the large number of factors beyond the investigator's control that determine when data will be taken over a given test site. The strategy is to augment the thermal maps derived from S-192 with a modeling technique which enables the simulation of a number of components of the surface energy balance, calculated at regular time intervals throughout the day or year. Preliminary tests on the performance of the model are still underway, using airborne MSS data from NASA aircraft flights. Results look extremely promising.

Alexander, R. H.↗
DOE OSTI2022

Image analysis reveals differences in tumor multinucleations in Black and White patients with human papillomavirus‐associated oropharyngeal squamous cell carcinoma

Background Understanding biological differences between different racial groups of human papillomavirus (HPV)‐associated oropharyngeal squamous cell carcinoma (OPSCC) patients, who have differences in terms of incidence, survival, and tumor morphology, can facilitate accurate prognostic biomarkers, which can help develop personalized treatment strategies. Methods This study evaluated whether there were morphologic differences between HPV‐associated tumors from Black and White patients in terms of multinucleation index (MuNI), an image analysis‐derived metric that measures density of multinucleated tumor cells within epithelial regions on hematoxylin–eosin images and previously has been prognostic in HPV‐associated OPSCC patients. In this study, the authors specifically evaluated whether the same MuNI cutoff that was prognostic of overall survival (OS) and disease‐free survival in their previous study, T TR , is valid for Black and White patients, separately. We also evaluated population‐specific cutoffs, T B for Blacks and T W for Whites, for risk stratification. Results MuNI was statistically significantly different between Black (mean, 3.88e–4; median, 3.67e–04) and White patients (mean, 3.36e–04; median, 2.99e–04), with p = .0078. Using T TR , MuNI was prognostic of OS in the entire population with hazard ratio (HR) of 1.71 ( p = .002; 95% confidence interval [CI], 1.21–2.43) and in White patients with HR of 1.72 ( p = .005; 95% CI, 1.18–2.51). Population‐specific cutoff, T W , yielded improved HR of 1.77 ( p = .003; 95% CI, 1.21–2.58) for White patients, whereas T B did not improve risk‐stratification in Black patients with HR of 0.6 ( p = .3; HR, 0.6; 95% CI, 0.2–1.80). Conclusions Histological difference between White and Black patient tumors in terms of multinucleated tumor cells suggests the need for considering population‐specific prognostic biomarkers for personalized risk stratification strategies for HPV‐associated OPSCC patients.

Koyuncu, Can F.↗
DOE OSTI2020

Machine-Learning Enabled Evaluation of Probability of Piping Degradation In Secondary Systems of Nuclear Power Plants

The transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, technologies used to perform online monitoring of piping and other secondary system structural components in commercial nuclear power plants (NPPs) are under evaluation. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval thus reducing the maintenance cost. This paper describes distributed high-temperature stable fiber sensors fabricated in optical fibers through a roll-to-roll laser direct writing process using femtosecond lasers. Using phase-sensitive optical time domain reflectometry, distributed acoustic and vibration sensors can be developed and deployed to critical components and systems in NPPs to perform active measurements with spatial resolution down to 0.5-meter throughout the piping systems. Complex acoustic and vibration signatures harnessed by distributed sensors are registered and analyzed by artificial intelligence algorithms for degradation detection and flaw identification. Piping elbows with machined-in flaws were instrumented with fiber sensors. High-spatial-resolution data were used to develop and validate machine learning algorithms, including both linear and nonlinear regression, and classification. Additionally, classification and sensor analysis were also performed for data analysis. The paper concludes with recommendations and future work on applications of machine learning enabled high-resolution fiber sensors for piping degradation monitoring in current or future NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2022

Global Premature Mortality By Dust and Pollution PM 2.5 Estimated From Aerosol Reanalysis of the Modern-Era Retrospective Analysis for Research and Applications, Version 2

This study quantifies global premature deaths attributable to long-term exposure of ambient PM 2.5 , or PM 2.5 -attributable mortality, by dust and pollution sources. We used NASA’s Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) aerosol reanalysis product for PM 2.5 and the cause-specific relative risk (RR) from the integrated exposure-response (IER) model to estimate global PM2.5-attributable mortality for five causes of deaths, namely ischaemic heart disease (IHD), cerebrovascular disease (CEV) or stroke, lung cancer (LC), chronic obstructive pulmonary disease (COPD), and acute lower respiratory infection (ALRI). The estimated yearly global PM 2.5 -attributable mortality in 2019 amounts to 2.89 (1.38–4.48) millions, which is composed of 1.19 (0.73–1.84) million from IHD, 1.01 (0.35–1.55) million from CEV, 0.29 (0.11–0.48) million from COPD, 0.23 (0.14–0.33) million from ALRI, and 0.17 (0.04–0.28) million from LC (the numbers in parentheses represent the estimated mortality range due corresponding to RR spread at the 95% confidence interval). The mortality counts vary with geopolitical regions substantially, with the highest number of deaths occurring in Asia. China and India account for 40% and 23% of the global PM 2.5 -attributable deaths, respectively. In terms of sources of PM 2.5 , about 22% of the global all-cause PM 2.5 -attributable deaths are caused by desert dust. The largest dust attribution is 37% for ALRI. The relative contributions of dust and pollution sources vary with the causes of deaths and geographical regions. Enforcing air pollution regulations to transfer areas from PM 2.5 nonattainment to PM2.5 attainment can have great health benefits. Being attainable with the United States air quality standard (AQS) of 15 μg/m 3 globally would have avoided nearly 40% or 1.2 million premature deaths. The most recent update of PM 2.5 guideline from 10 to 5 μg/m 3 by the World Health Organization (WHO) would potentially save additional one million lives. Our study highlights the importance of distinguishing aerodynamic size from geometric size in accurately assessing the global health burden of PM 2.5 and particularly for dust. A use of geometric size in diagnosing dust PM 2.5 from the model simulation, a common approach in current health burden assessment, could overestimate the PM 2.5 level in the dust belt by 40–170%, leading to an overestimate of global all-cause mortality by 1 million or 32%.

PM2.5↗