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At least 55 records · Page 3

Comparing structure-property evolution for PM-HIP and forged alloy 625 irradiated with neutrons to 1 dpa

The nuclear power industry has growing interest in qualifying powder metallurgy with hot isostatic pressing (PM-HIP) to replace traditional alloy fabrication methods for reactor structural components. But there is little known about the response of PM-HIP alloys to reactor conditions. This study directly compares the response of PM-HIP to forged Ni-base Alloy 625 under neutron irradiation doses ~0.5–1 displacements per atom (dpa) at temperatures ranging ~321–385 °C. Post-irradiation examination involves microstructure characterization, ASTM E8 uniaxial tensile testing, and fractography. Up through 1 dpa, PM-HIP Alloy 625 appears more resistant to irradiation-induced cavity nucleation than its forged counterpart, and consequently experiences significantly less hardening. This observed difference in performance can be explained by the higher initial dislocation density of the forged material, which represents an interstitial-biased sink that leaves a vacancy supersaturation to nucleate cavities. These findings show promise for qualification of PM-HIP Alloy 625 for nuclear applications, although higher dose studies are needed to assess the steady-state irradiated microstructure.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Humidified single-scattering albedometer (H-CAPS-PM SSA ): Design, data analysis, and validation

In this work, we report the development and validation of a new humidified aerosol single-scattering albedometer to quantify the effects of water uptake on submicrometer particle optical properties. The instrument simultaneously measures in situ aerosol light extinction ( σ ep ) and scattering ( σ sp ) using a cavity-attenuated phase shift-single scattering albedo particulate matter (PM) monitor (CAPS-PM SSA , Aerodyne Research, Inc., Billerica, MA, USA). It retrieves by difference aerosol light absorption ( σ ap ) and directly quantifies aerosol single-scattering albedo (SSA), the aerosol “brightness.” We custom built a relative humidity (RH) control system using a water vapor-permeable membrane humidifier and coupled it to the CAPS-PM SSA to enable humidified aerosol observations. Our humidified instrument (H-CAPS-PM SSA ) overcomes problems with noise caused by mirror purge-flow humidification, heating, and characterizing cell RH. Careful angular truncation corrections in scattering, particularly for larger particles, were combined with empirical observations. Results show that the optimal operational size to be D p < 400 nm. The H-CAPS-PM SSA was evaluated with several pure single-component aerosols including ammonium sulfate ((NH 4 ) 2 SO 4 ), absorbing nigrosin, and levoglucosan, an organic biomass smoke tracer. The measured σ ep , σ sp , and the derived optical hygroscopicity parameter ( κ ) for size-selected ammonium sulfate are in good agreement with literature values. For dry size-selected nigrosin in the 100 < D p < 400 nm range, SSA values increased from ~0.3 to 0.65 with increasing D p . The enhancement in nigrosin σ ap at RH = 80% was a factor of 1.05–1.20 relative to dry conditions, with the larger particles showing greater enhancement. SSA increased with RH with the largest fractional enhancement measured for the smallest particles. For polydisperse levoglucosan, we measured an optical κ of 0.26 for both light extinction and scattering and negligible absorption. Our new instrument enables reliable observations of the effects of ambient humidity on mixed aerosol optical properties, particularly for light-absorbing aerosols whose climate forcing is uncertain due to measurement gaps.

54 ENVIRONMENTAL SCIENCES↗

Mortality attributable to PM 2.5 from wildland fires in California from 2008 to 2018

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM 2.5 ), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM 2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM 2.5 estimates. We used a concentration-response function for PM 2.5 , applying ZIP code–level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM 2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $\$432$ to $\$456$ billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

60 APPLIED LIFE SCIENCES↗

$\overline{\Sigma }^{\pm }$ production in $\text {pp}$ and $\text {p}{-}\text{Pb}$ collisions at $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV with ALICE

The transverse momentum spectra and integrated yields of anti-$Σ$ hyperons ($\overline{\Sigma}^{\pm}$) have been measured in and collisions at $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV with the ALICE experiment. Measurements are performed via the newly accessed decay channel $\overline{\Sigma}^{\pm}$ → $\bar{\textrm{n}}π^±$. A new method of antineutron reconstruction with the PHOS electromagnetic spectrometer is developed and applied to this analysis. The p T spectra of $\overline{\Sigma}^{\pm}$ are measured in the range 0.5 < p T < 3 GeV/c and compared to predictions of the PYTHIA 8, DPMJET, PHOJET, EPOS LHC and EPOS4 models. The EPOS LHC and EPOS4 models provide the best descriptions of the measured spectra both in pp and p-Pb collisions, while models which do not account for multiparton interactions provide a considerably worse description at high p T . The total yields of $\overline{\Sigma }^{\pm }$ in both pp and p-Pb collisions are compared to predictions of the Thermal-FIST model and dynamical models PYTHIA 8, DPMJET, PHOJET, EPOS LHC and EPOS4. All models reproduce the total yields in both colliding systems within uncertainties. The nuclear modification factors R pPb for both $\overline{\Sigma}^{+}$ and $\overline{\Sigma}^{-}$ are evaluated and compared to those of protons, $Λ$ and $Ξ$ hyperons, and predictions of EPOS LHC and EPOS4 models. No deviations of R pPb for $\overline{\Sigma}^{\pm}$ from the model predictions or measurements for other hadrons are found within uncertainties.

Abualrob, I. J. [University of Houston] (ORCID:000↗

PM Science Working Group Meeting on Spacecraft Maneuvers

The EOS PM Science Working Group met on May 6, 1997, to examine the issue of spacecraft maneuvers. The meeting was held at NASA Goddard Space Flight Center and was attended by the Team Leaders of all four instrument science teams with instruments on the PM-1 spacecraft, additional representatives from each of the four teams, the PM Project management, and random others. The meeting was chaired by the PM Project Scientist and open to all. The meeting was called in order to untangle some of the concerns raised over the past several months regarding whether or not the PM-1 spacecraft should undergo spacecraft maneuvers to allow the instruments to obtain deep-space views. Two of the Science Teams, those for the Moderate-Resolution Imaging Spectroradiometer (MODIS) and the Clouds and the Earth's Radiant Energy System (CERES), had strongly expressed the need for deep-space views in order to calibrate their instruments properly and conveniently. The other two teams, those for the Advanced Microwave Scanning Radiometer (AMSR-E) and the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the Humidity Sounder for Brazil (HSB), had expressed concerns that the maneuvers involve risks to the instruments and undesired gaps in the data sets.

Parkinson, Claire L.↗

Advancing Methodologies for Applying Machine Learning and Evaluating Spatiotemporal Models of Fine Particulate Matter (PM 2.5 ) Using Satellite Data Over Large Regions

Reconstructing the distribution of fine particulate matter (PM 2.5 ) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM 2.5 health impacts. Flexible statistical methods for prediction have demonstrated the integration of satellite observations with other predictors, yet these algorithms are susceptible to overfitting the spatiotemporal structure of the training datasets. We present a new approach for predicting PM 2.5 using machine-learning methods and evaluating prediction models for the goal of making predictions where they were not previously available. We apply extreme gradient boosting (XGBoost) modeling to predict daily PM 2.5 on a 1 x 1 km 2 resolution for a 13 state region in the Northeastern USA for the years 2000–2015 using satellite-derived aerosol optical depth and implement a recursive feature selection to develop a parsimonious model. We demonstrate excellent predictions of withheld observations but also contrast an RMSE of 3.11 μg/m 3 in our spatial cross-validation withholding nearby sites versus an overfit RMSE of 2.10 μg/m 3 using a more conventional random ten-fold splitting of the dataset. As the field of exposure science moves forward with the use of advanced machine-learning approaches for spatiotemporal modeling of air pollutants, our results show the importance of addressing data leakage in training, overfitting to spatiotemporal structure, and the impact of the predominance of ground monitoring sites in dense urban sub-networks on model evaluation. The strengths of our resultant modeling approach for exposure in epidemiologic studies of PM 2.5 include improved efficiency, parsimony, and interpretability with robust validation while still accommodating complex spatiotemporal relationships.

air pollution↗

MRP: Qualification of Powder Metallurgy Hot Isostatic Pressed (PM HIP) Materials for Elevated-Temperature Nuclear Construction

PM HIP is a mature technology that offers many advantages that are attractive to the microreactor industry. The elevated-temperature creep-fatigue properties of the PM HIP 316H SS bar that has been characterized are reduced compared to the wrought material. Work will be carried out in fiscal year 2022 to identify the mechanisms responsible for the reduced creep-fatigue properties. Confirmatory testing of optimized material will be conducted to demonstrate long-term PM HIP properties comparable to the wrought-product form. The lessons learned for PM HIP 316H SS will be applied to the procurement and confirmatory testing of PM HIP Alloy 800H.

316H stainless steel↗

Experiment design for the neutron irradiation of $\mathrm{PM-HIP}$ alloys for nuclear reactors

Here, this article describes the design of an Advanced Test Reactor (ATR) drop-in neutron irradiation experiment aiming to directly compare the performance of nuclear structural alloys fabricated by powder metallurgy with hot isostatic pressing (PM-HIP) against conventional casting or forging. There is growing interest in PM-HIP alloys for nuclear applications because of their microstructural uniformity, superior mechanical properties, and reduced dependence on welding and machining, compared to cast/forged alloys. Nuclear code-qualification of PM-HIP alloys requires neutron irradiation testing to demonstrate performance under relevant conditions. In this experiment, six nuclear structural alloys were irradiated: Ni-based alloys 625 and 690, Grade 91 ferritic steel, SA508 pressure vessel steel, and 304L and 316L austenitic stainless steels. The experiment is assembled into seven capsules in four test trains and irradiated in three ATR inboard A positions. Both the PM-HIP and cast/forged versions of each alloy were irradiated under nearly identical conditions for comparative purposes, to target doses of 1 ± 0.2 and 3 ± 0.2 dpa at temperatures of 300 ± 50 °C and 400 ± 50 °C. A thorough description of the experiment design and thermal, structural and neutronic analyses performed to ensure the targeted irradiation conditions are met is provided. Specimens were configured as small disks, compact tension specimens and tensile bars to facilitate post-irradiation examination (PIE) that will include mechanical testing, microstructure characterization, and fracture toughness testing. Given the considerations for ASTM standardized mechanical testing, comparative fluence and temperature across specimen pairs, and comprehensive PIE planning herein, this work serves as a template for future nuclear materials qualification experiment designs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Disparities in the air quality monitoring stations and PM₂.₅ in Chicago’s air quality landscape

Fine particulate matter (PM₂.₅) poses significant public and environmental health risks in urban areas. Chicago’s dense industry and traffic create variable air quality, yet monitoring is unevenly distributed, resulting in undersampling of air quality data in some city areas. This study applied a hybrid approach using GIS-based kernel density mapping, interpolation modeling (IDW, Spline, Kriging) of USEPA monitoring data, multi-scale temporal trend analyses (hourly to annual), and ESDA. Accordingly, the density surface showed that monitors are concentrated in the affluent north, northwest, and southwest sides of Chicago (up to ~ 0.07 stations per sq mile), while the south and southeast regions, with predominantly minority communities, have virtually no coverage. Overall, citywide coverage is minimal (~ 4–5 monitors total; ~0.02 per sq mile; ≈1 per 600,000 residents). Temporal analyses showed that the city’s mean annual PM₂.₅ (~ 10.8 µg/m³) exceeds USEPA/WHO standards (9 µg/m³), with summer means (~ 17.1 µg/m³) significantly higher than other seasons. Diurnally, a clear pattern was observed, with PM₂.₅ concentrations peaking overnight (00:00–03:00) and during the morning rush hours, and dipping during midday to late afternoon. Spatial distribution of PM₂.₅ identified hotspots near O’Hare Airport, the downtown Loop area, and south-side neighborhoods, contrasting with lower concentrations on the north side, revealing Chicago’s socioeconomic divides and resulting environmental inequities. The findings underscore the need for expanded monitoring and targeted interventions in under-monitored, high-pollution communities to advance equitable community health.

54 ENVIRONMENTAL SCIENCES↗

Evaluating county-level lung cancer incidence from environmental radiation exposure, PM 2.5 , and other exposures with regression and machine learning models

Characterizing the interplay between exposures shaping the human exposome is vital for uncovering the etiology of complex diseases. For example, cancer risk is modified by a range of multifactorial external environmental exposures. Environmental, socioeconomic, and lifestyle factors all shape lung cancer risk. However, epidemiological studies of radon aimed at identifying populations at high risk for lung cancer often fail to consider multiple exposures simultaneously. For example, moderating factors, such as PM 2.5 , may affect the transport of radon progeny to lung tissue. This ecological analysis leveraged a population-level dataset from the National Cancer Institute’s Surveillance, Epidemiology, and End-Results data (2013–17) to simultaneously investigate the effect of multiple sources of low-dose radiation (gross γ activity and indoor radon) and PM 2.5 on lung cancer incidence rates in the USA. County-level factors (environmental, sociodemographic, lifestyle) were controlled for, and Poisson regression and random forest models were used to assess the association between radon exposure and lung and bronchus cancer incidence rates. Tree-based machine learning (ML) method perform better than traditional regression: Poisson regression: 6.29/7.13 (mean absolute percentage error, MAPE), 12.70/12.77 (root mean square error, RMSE); Poisson random forest regression: 1.22/1.16 (MAPE), 8.01/8.15 (RMSE). The effect of PM 2.5 increased with the concentration of environmental radon, thereby confirming findings from previous studies that investigated the possible synergistic effect of radon and PM 2.5 on health outcomes. In summary, the results demonstrated (1) a need to consider multiple environmental exposures when assessing radon exposure’s association with lung cancer risk, thereby highlighting (1) the importance of an exposomics framework and (2) that employing ML models may capture the complex interplay between environmental exposures and health, as in the case of indoor radon exposure and lung cancer incidence.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Extraction of Pm-147 from savannah river site nuclear material management programs

The Savannah River Site (SRS) processes used-nuclear fuel to recover uranium. There are many interesting fission products lost in the raffinate from this separation including 147 Pm. Here, the goal of this work was to recover 147 Pm from SRS waste solutions. A radiochemical separation method typically used for the determination of 147 Pm and 151 Sm was modified to purify significant quantities of 147 Pm from the H Canyon waste solutions. The developed scheme was tested on a small aliquot of waste solution from the processing of used fuel from the High Flux Isotope Reactor at Oak Ridge National Laboratory.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Impact of wildfires on regional ozone and PM 2.5 : Considering the light absorption of Brown carbon

The influence of wildfire brown carbon (BrC) in moderating the formation of O 3 and fine particulate matter (PM 2.5 ) due to its absorption of ultraviolet (UV) radiation is, for the first time, investigated using a modified community multiscale air quality (CMAQ) model. The wavelength-dependent imaginary refractive index of the organic carbon from wildfires, which are needed by the CMAQ model for its inline photolysis rate calculation, are generated experimentally from wood burning aerosols from a combustion chamber. On high emission days of the Bastrop County Complex fire in Texas in early September 2011, BrC UV absorption reduces the daytime average NO 2 photolysis rate by up to 38% in the core region of the wildfire plume compared to the base scenario that does not consider BrC absorption. Consequently, O 3 production in the smoke plume is suppressed compared to the base scenario due to reduced HO x radical concentrations. Further, in the core region, the predicted O 3 increase due to wildfire reaches as high as 47–123 ppb without considering BrC absorption, the predicted increase of O 3 is 5–15% lower when BrC absorption is considered. Similarly, considering the BrC UV absorption leads to approximately 1% (or ~2–3 µgm -3 ) lower estimation of the wildfire emissions’ impact on total PM 2.5 . This change is small because secondary aerosols, which are the components affected by BrC absorption, only account for a small fraction of the total PM 2.5 in wildfire impacted regions in this study. In addition, our study shows that assumptions about aerosol mixing state (core-shell vs. homogeneous) in the inline photolysis rate calculation would not significantly affect out assessment of the impact of wildfire BrC light absorption on O 3 and PM 2.5 .

54 ENVIRONMENTAL SCIENCES↗

Persistent high PM 2.5 pollution driven by unfavorable meteorological conditions during the COVID-19 lockdown period in the Beijing-Tianjin-Hebei region, China

Lockdown measures to curtail the COVID-19 pandemic in China halted most nonessential activities on January 23, 2020. Despite significant reductions in anthropogenic emissions, the Beijing-Tianjin-Hebei (BTH) region still experienced high air pollution concentrations. In this work, employing two emissions reduction scenarios, the Community Multiscale Air Quality (CMAQ) model was used to investigate the PM 2.5 concentrations change in this region. The model using the scenario (C3) with greater traffic reductions performed better compared to the observed PM 2.5 . Compared with the no reductions base-case (scenario C1), PM 2.5 reductions with scenario C3 were 2.70, 2.53, 2.90, 2.98, 3.30, 2.81, 2.82, 2.98, 2.68, and 2.83 µg/m 3 in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai, respectively. During high-pollution days in scenario C3, the percentage reductions in PM 2.5 concentrations in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai were 3.76, 3.54, 3.28, 3.22, 3.57, 3.56, 3.47, 6.10, 3.61, and 3.67%, respectively. However, significant increases caused by unfavorable meteorological conditions counteracted the emissions reduction effects resulting in high air pollution in BTH region during the lockdown period. This study shows that effective air pollution control strategies incorporating these results are urgently required in BTH to avoid severe pollution.

54 ENVIRONMENTAL SCIENCES↗

Source sector and fuel contributions to ambient PM 2.5 and attributable mortality across multiple spatial scales

Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Reducing the PM 2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM 2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM 2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52–0.95] million deaths; 19.2%), industrial (0.45 [0.32–0.58] million deaths; 11.7%), and energy (0.39 [0.28–0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.

54 ENVIRONMENTAL SCIENCES↗

Future PM 2.5 emissions from metal production to meet renewable energy demand

A shift from fossil fuel to renewable energy is crucial in limiting global temperature increase to 2 °C above preindustrial levels. However, renewable energy technologies, solar photovoltaics, wind turbines, and electric vehicles are metal-intensive, and the mining and smelting processes to obtain the needed metals are emission-intensive. We estimate the future PM 2.5 emissions from mining and smelting to meet the metal demand of renewable energy technologies in two climate pathways to be 0.3–0.6 Tg yr -1 in the 2020–2050 period, which are projected to contribute 10%–30% of total anthropogenic primary PM 2.5 combustion emissions in many countries. The concentration of mineral reserves in a few regions means the impacts are also regionally concentrated. Rapid decarbonization could lead to a faster reduction of overall anthropogenic PM 2.5 emissions but also could create more unevenness in the distributions of emissions relative to where demand occurs. Options to reduce metal-related PM 2.5 emissions by over 90% exist and are well understood; introducing policy requiring their installation could avoid emission hotspots.

54 ENVIRONMENTAL SCIENCES↗

Pathways of China's PM 2.5 air quality 2015–2060 in the context of carbon neutrality

Clean air policies in China have substantially reduced particulate matter (PM 2.5 ) air pollution in recent years, primarily by curbing end-of-pipe emissions. However, reaching the level of the World Health Organization (WHO) guidelines may instead depend upon the air quality co-benefits of ambitious climate action. Here, we assess pathways of Chinese PM 2.5 air quality from 2015 to 2060 under a combination of scenarios that link global and Chinese climate mitigation pathways (i.e. global 2°C- and 1.5°C-pathways, National Determined Contributions (NDC) pledges and carbon neutrality goals) to local clean air policies. We find that China can achieve both its near-term climate goals (peak emissions) and PM 2.5 air quality annual standard (35 μg/m3) by 2030 by fulfilling its NDC pledges and continuing air pollution control policies. However, the benefits of end-of-pipe control reductions are mostly exhausted by 2030, and reducing PM 2.5 exposure of the majority of the Chinese population to below 10 μg/m 3 by 2060 will likely require more ambitious climate mitigation efforts such as China's carbon neutrality goals and global 1.5°C-pathways. Our results thus highlight that China's carbon neutrality goals will play a critical role in reducing air pollution exposure to the level of the WHO guidelines and protecting public health.

54 ENVIRONMENTAL SCIENCES↗

Measurement of particulated matter (PM1, PM2.5, PM10) using a PM sensor during the SAIL campaign in Gothic, CO and Mt. Crested Butte, CO

We deployed another PM sensor (Modulair-PM, QuantAQ) to measure the mass concentration of particulate matter (PM) for three size cuts at both the main site (M1) and supplementary site (S2) of the SAIL from 14 June 2022 to 14 June 2023. The instruments provide the mass concentration of PM1, PM2.5 and PM10. Mass concentrations were calculated based on measurements made with a nephelometer and an OPC. We used Quant-AQ's algorithm [please see their documentation here and the references within] to determine the mass concentrations reported. Here, we present the time series of sample relative humidity, temperature, pressure, and the mass concentration of PM1, PM2.5 and PM10. We also present the size distribution of the aerosol particles within a diameter range of 0.35 - 40 micron, measured by the OPC of the pm-modulair. However, we encourage caution while using the size distribution data, since it is operated only with the factory calibration. Abstract and description of the campaign can be found here : https://www.arm.gov/research/campaigns/amf2022ssb.

54 ENVIRONMENTAL SCIENCES↗

Phase-lock demodulation of a PM signal contaminated with incidental AM

Signals from phase-modulated satellite transmitters usually exhibit some degree of incidental amplitude modulation. The effects of incidental AM are analyzed when this type of signal is demodulated by a phase-lock receiver which does not employ a limiter preceding the loop phase detector. The presence of incidental AM causes a reduction in the receiver output signal-to-noise ratio. The tolerable level of AM decreases in proportion to the phase modulation index Beta. For a square-wave modulating signal, a 1 db reduction results at the receiver PM channel output when Beta = 1 radian and the percentage of AM = 23, Beta = 1.2 radians and the percentage of AM = 16, or Beta = 1.5 radians and the percentage of AM = 4. Although only the PM channel of the receiver is used ordinarily, utilizing both the AM and PM channel by summing offers an improvement in S/N relative to the S/N ratio of the PM channel if the percentage of incidental AM is greater than fifteen.

Robinson, G. B.↗