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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Materials Data on Pm2Mg by Materials Project

MgPm2 crystallizes in the monoclinic C2/m space group. The structure is two-dimensional and consists of two MgPm2 sheets oriented in the (1, 0, 0) direction. Mg is bonded in a body-centered cubic geometry to eight Pm atoms. There are a spread of Mg–Pm bond distances ranging from 3.36–3.40 Å. There are two inequivalent Pm sites. In the first Pm site, Pm is bonded in a 4-coordinate geometry to four equivalent Mg atoms. In the second Pm site, Pm is bonded in a 12-coordinate geometry to four equivalent Mg atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Pm3Sm by Materials Project

SmPm3 is Uranium Silicide structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Sm is bonded to twelve equivalent Pm atoms to form SmPm12 cuboctahedra that share corners with twelve equivalent SmPm12 cuboctahedra, edges with twenty-four equivalent PmPm8Sm4 cuboctahedra, faces with six equivalent SmPm12 cuboctahedra, and faces with twelve equivalent PmPm8Sm4 cuboctahedra. All Sm–Pm bond lengths are 3.65 Å. Pm is bonded to four equivalent Sm and eight equivalent Pm atoms to form PmPm8Sm4 cuboctahedra that share corners with twelve equivalent PmPm8Sm4 cuboctahedra, edges with eight equivalent SmPm12 cuboctahedra, edges with sixteen equivalent PmPm8Sm4 cuboctahedra, faces with four equivalent SmPm12 cuboctahedra, and faces with fourteen equivalent PmPm8Sm4 cuboctahedra. All Pm–Pm bond lengths are 3.65 Å.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Pm3Dy by Materials Project

DyPm3 is Uranium Silicide structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Dy is bonded to twelve equivalent Pm atoms to form DyPm12 cuboctahedra that share corners with twelve equivalent DyPm12 cuboctahedra, edges with twenty-four equivalent PmPm8Dy4 cuboctahedra, faces with six equivalent DyPm12 cuboctahedra, and faces with twelve equivalent PmPm8Dy4 cuboctahedra. All Dy–Pm bond lengths are 3.63 Å. Pm is bonded to four equivalent Dy and eight equivalent Pm atoms to form PmPm8Dy4 cuboctahedra that share corners with twelve equivalent PmPm8Dy4 cuboctahedra, edges with eight equivalent DyPm12 cuboctahedra, edges with sixteen equivalent PmPm8Dy4 cuboctahedra, faces with four equivalent DyPm12 cuboctahedra, and faces with fourteen equivalent PmPm8Dy4 cuboctahedra. All Pm–Pm bond lengths are 3.63 Å.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Pm3Ga by Materials Project

Pm3Ga is Uranium Silicide structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Pm is bonded to eight equivalent Pm and four equivalent Ga atoms to form distorted PmPm8Ga4 cuboctahedra that share corners with twelve equivalent PmPm8Ga4 cuboctahedra, edges with eight equivalent GaPm12 cuboctahedra, edges with sixteen equivalent PmPm8Ga4 cuboctahedra, faces with four equivalent GaPm12 cuboctahedra, and faces with fourteen equivalent PmPm8Ga4 cuboctahedra. All Pm–Pm bond lengths are 3.42 Å. All Pm–Ga bond lengths are 3.42 Å. Ga is bonded to twelve equivalent Pm atoms to form GaPm12 cuboctahedra that share corners with twelve equivalent GaPm12 cuboctahedra, edges with twenty-four equivalent PmPm8Ga4 cuboctahedra, faces with six equivalent GaPm12 cuboctahedra, and faces with twelve equivalent PmPm8Ga4 cuboctahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Pm3Hf by Materials Project

Pm3Hf is Uranium Silicide structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Pm is bonded to eight equivalent Pm and four equivalent Hf atoms to form PmPm8Hf4 cuboctahedra that share corners with twelve equivalent PmPm8Hf4 cuboctahedra, edges with eight equivalent HfPm12 cuboctahedra, edges with sixteen equivalent PmPm8Hf4 cuboctahedra, faces with four equivalent HfPm12 cuboctahedra, and faces with fourteen equivalent PmPm8Hf4 cuboctahedra. All Pm–Pm bond lengths are 3.52 Å. All Pm–Hf bond lengths are 3.52 Å. Hf is bonded to twelve equivalent Pm atoms to form HfPm12 cuboctahedra that share corners with twelve equivalent HfPm12 cuboctahedra, edges with twenty-four equivalent PmPm8Hf4 cuboctahedra, faces with six equivalent HfPm12 cuboctahedra, and faces with twelve equivalent PmPm8Hf4 cuboctahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on PmEr3 by Materials Project

Er3Pm is beta Cu3Ti-like structured and crystallizes in the hexagonal P6_3/mmc space group. The structure is three-dimensional. there are three inequivalent Er sites. In the first Er site, Er is bonded to eight Er and four equivalent Pm atoms to form ErPm4Er8 cuboctahedra that share corners with four equivalent PmEr12 cuboctahedra, corners with fourteen equivalent ErPm4Er8 cuboctahedra, edges with six equivalent PmEr12 cuboctahedra, edges with twelve ErPm4Er8 cuboctahedra, faces with four equivalent PmEr12 cuboctahedra, and faces with sixteen ErPm4Er8 cuboctahedra. There are a spread of Er–Er bond distances ranging from 3.51–3.63 Å. There are two shorter (3.54 Å) and two longer (3.60 Å) Er–Pm bond lengths. In the second Er site, Er is bonded to eight Er and four equivalent Pm atoms to form ErPm4Er8 cuboctahedra that share corners with four equivalent PmEr12 cuboctahedra, corners with fourteen ErPm4Er8 cuboctahedra, edges with six equivalent PmEr12 cuboctahedra, edges with twelve ErPm4Er8 cuboctahedra, faces with four equivalent PmEr12 cuboctahedra, and faces with sixteen ErPm4Er8 cuboctahedra. There are a spread of Er–Er bond distances ranging from 3.51–3.63 Å. There are two shorter (3.54 Å) and two longer (3.60 Å) Er–Pm bond lengths. In the third Er site, Er is bonded to eight Er and four equivalent Pm atoms to form ErPm4Er8 cuboctahedra that share corners with four equivalent PmEr12 cuboctahedra, corners with fourteen ErPm4Er8 cuboctahedra, edges with six equivalent PmEr12 cuboctahedra, edges with twelve ErPm4Er8 cuboctahedra, faces with four equivalent PmEr12 cuboctahedra, and faces with sixteen ErPm4Er8 cuboctahedra. There are two shorter (3.54 Å) and two longer (3.60 Å) Er–Pm bond lengths. Pm is bonded to twelve Er atoms to form PmEr12 cuboctahedra that share corners with six equivalent PmEr12 cuboctahedra, corners with twelve ErPm4Er8 cuboctahedra, edges with eighteen ErPm4Er8 cuboctahedra, faces with eight equivalent PmEr12 cuboctahedra, and faces with twelve ErPm4Er8 cuboctahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Pm3Gd by Materials Project

GdPm3 is Uranium Silicide structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Gd is bonded to twelve equivalent Pm atoms to form GdPm12 cuboctahedra that share corners with twelve equivalent GdPm12 cuboctahedra, edges with twenty-four equivalent PmPm8Gd4 cuboctahedra, faces with six equivalent GdPm12 cuboctahedra, and faces with twelve equivalent PmPm8Gd4 cuboctahedra. All Gd–Pm bond lengths are 3.64 Å. Pm is bonded to four equivalent Gd and eight equivalent Pm atoms to form PmPm8Gd4 cuboctahedra that share corners with twelve equivalent PmPm8Gd4 cuboctahedra, edges with eight equivalent GdPm12 cuboctahedra, edges with sixteen equivalent PmPm8Gd4 cuboctahedra, faces with four equivalent GdPm12 cuboctahedra, and faces with fourteen equivalent PmPm8Gd4 cuboctahedra. All Pm–Pm bond lengths are 3.64 Å.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Pm3Al by Materials Project

Pm3Al is Uranium Silicide structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Pm is bonded to eight equivalent Pm and four equivalent Al atoms to form distorted PmPm8Al4 cuboctahedra that share corners with twelve equivalent PmPm8Al4 cuboctahedra, edges with eight equivalent AlPm12 cuboctahedra, edges with sixteen equivalent PmPm8Al4 cuboctahedra, faces with four equivalent AlPm12 cuboctahedra, and faces with fourteen equivalent PmPm8Al4 cuboctahedra. All Pm–Pm bond lengths are 3.45 Å. All Pm–Al bond lengths are 3.45 Å. Al is bonded to twelve equivalent Pm atoms to form AlPm12 cuboctahedra that share corners with twelve equivalent AlPm12 cuboctahedra, edges with twenty-four equivalent PmPm8Al4 cuboctahedra, faces with six equivalent AlPm12 cuboctahedra, and faces with twelve equivalent PmPm8Al4 cuboctahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on NaPm3 by Materials Project

NaPm3 is Uranium Silicide structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Na is bonded to twelve equivalent Pm atoms to form NaPm12 cuboctahedra that share corners with twelve equivalent NaPm12 cuboctahedra, edges with twenty-four equivalent PmNa4Pm8 cuboctahedra, faces with six equivalent NaPm12 cuboctahedra, and faces with twelve equivalent PmNa4Pm8 cuboctahedra. All Na–Pm bond lengths are 3.64 Å. Pm is bonded to four equivalent Na and eight equivalent Pm atoms to form PmNa4Pm8 cuboctahedra that share corners with twelve equivalent PmNa4Pm8 cuboctahedra, edges with eight equivalent NaPm12 cuboctahedra, edges with sixteen equivalent PmNa4Pm8 cuboctahedra, faces with four equivalent NaPm12 cuboctahedra, and faces with fourteen equivalent PmNa4Pm8 cuboctahedra. All Pm–Pm bond lengths are 3.64 Å.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on PmMg3 by Materials Project

Mg3Pm is beta Cu3Ti-like structured and crystallizes in the hexagonal P6_3/mmc space group. The structure is three-dimensional. there are three inequivalent Mg sites. In the first Mg site, Mg is bonded to eight Mg and four equivalent Pm atoms to form distorted MgPm4Mg8 cuboctahedra that share corners with four equivalent PmMg12 cuboctahedra, corners with fourteen MgPm4Mg8 cuboctahedra, edges with six equivalent PmMg12 cuboctahedra, edges with twelve MgPm4Mg8 cuboctahedra, faces with four equivalent PmMg12 cuboctahedra, and faces with sixteen MgPm4Mg8 cuboctahedra. There are a spread of Mg–Mg bond distances ranging from 3.23–3.48 Å. There are two shorter (3.29 Å) and two longer (3.39 Å) Mg–Pm bond lengths. In the second Mg site, Mg is bonded to eight Mg and four equivalent Pm atoms to form distorted MgPm4Mg8 cuboctahedra that share corners with four equivalent PmMg12 cuboctahedra, corners with fourteen MgPm4Mg8 cuboctahedra, edges with six equivalent PmMg12 cuboctahedra, edges with twelve MgPm4Mg8 cuboctahedra, faces with four equivalent PmMg12 cuboctahedra, and faces with sixteen MgPm4Mg8 cuboctahedra. There are a spread of Mg–Mg bond distances ranging from 3.23–3.48 Å. There are two shorter (3.29 Å) and two longer (3.39 Å) Mg–Pm bond lengths. In the third Mg site, Mg is bonded to eight Mg and four equivalent Pm atoms to form distorted MgPm4Mg8 cuboctahedra that share corners with four equivalent PmMg12 cuboctahedra, corners with fourteen MgPm4Mg8 cuboctahedra, edges with six equivalent PmMg12 cuboctahedra, edges with twelve MgPm4Mg8 cuboctahedra, faces with four equivalent PmMg12 cuboctahedra, and faces with sixteen MgPm4Mg8 cuboctahedra. Both Mg–Mg bond lengths are 3.23 Å. There are two shorter (3.29 Å) and two longer (3.39 Å) Mg–Pm bond lengths. Pm is bonded to twelve Mg atoms to form PmMg12 cuboctahedra that share corners with six equivalent PmMg12 cuboctahedra, corners with twelve MgPm4Mg8 cuboctahedra, edges with eighteen MgPm4Mg8 cuboctahedra, faces with eight equivalent PmMg12 cuboctahedra, and faces with twelve MgPm4Mg8 cuboctahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Pm3Ti by Materials Project

Pm3Ti is Uranium Silicide structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Pm is bonded to eight equivalent Pm and four equivalent Ti atoms to form distorted PmPm8Ti4 cuboctahedra that share corners with twelve equivalent PmPm8Ti4 cuboctahedra, edges with eight equivalent TiPm12 cuboctahedra, edges with sixteen equivalent PmPm8Ti4 cuboctahedra, faces with four equivalent TiPm12 cuboctahedra, and faces with fourteen equivalent PmPm8Ti4 cuboctahedra. All Pm–Pm bond lengths are 3.46 Å. All Pm–Ti bond lengths are 3.46 Å. Ti is bonded to twelve equivalent Pm atoms to form TiPm12 cuboctahedra that share corners with twelve equivalent TiPm12 cuboctahedra, edges with twenty-four equivalent PmPm8Ti4 cuboctahedra, faces with six equivalent TiPm12 cuboctahedra, and faces with twelve equivalent PmPm8Ti4 cuboctahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Elevated-Temperature Cyclic Properties of Alloy 316H Fabricated by Powder Metallurgy Hot Isostatic Pressing (Rev.1)

Powder metallurgy hot isostatic pressing (PM HIP), an advanced manufacturing technique, is viewed by the Department of Energy as a “transformational technology” for heavy section manufacturing of nuclear components. Although PM HIP is a mature technology, it has not been qualified in Section III, Division 5 for elevated-temperature nuclear construction. This work seeks to demonstrate a PM HIP qualification method for elevated-temperature nuclear construction that is based on allowable material characteristics. Specifically, the elevated-temperature cyclic properties of PM HIP 316H are investigated. The creep-fatigue properties of PM HIP 316H are significantly degraded compared to those of wrought. Current PM HIP practices are not able to fabricate elevated-temperature nuclear components with creep-fatigue properties that are equivalent to or better than traditional wrought components. A research and development program is proposed for qualifying PM HIP 316H for elevated-temperature nuclear construction.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Measurement of the top quark pair production cross section in dilepton final states containing one $\tau$ lepton in pp collisions at $\sqrt{s}=$ 13 TeV

The cross section of top quark pair production is measured in the $\mathrm{t\bar{t}}\to (\ell\nu_{\ell})(\tau_\mathrm{h}\nu_{\tau})\mathrm{b\bar{b}}$ final state, where $\tau_\mathrm{h}$ refers to the hadronic decays of the $\tau$ lepton, and $\ell$ is either an electron or a muon. The data sample corresponds to an integrated luminosity of 35.9 fb$^{-1}$ collected in proton-proton collisions at $\sqrt{s}=$ 13 TeV with the CMS detector. The measured cross section is $\sigma_{\mathrm{t\bar{t}}} =$ 781 $\pm$ 7 (stat) $\pm$ 62 (syst) $\pm$ 20 (lum) pb, and the ratio of the partial width $\Gamma($t$\to\tau\nu_{\tau}$b) to the total decay width of the top quark is measured to be 0.1050 $\pm$ 0.0009 (stat) $\pm$ 0.0071 (syst). This is the first measurement of the $\mathrm{t\bar{t}}$ production cross section in proton-proton collisions at $\sqrt{s}=$ 13 TeV that explicitly includes $\tau$ leptons. The ratio of the cross sections in the $\ell\tau_\mathrm{h}$ and $\ell\ell$ final states yields a value $R_{\ell\tau_\mathrm{h}/\ell\ell}=$ 0.973 $\pm$ 0.009 (stat) $\pm$ 0.066 (syst), consistent with lepton universality.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Studies of the decay $$ {\textrm{D}}_{\textrm{s}}^{+}\to {\textrm{K}}^{+}{\textrm{K}}^{-}{\mu}^{+}{\nu}_{\mu } $$

Abstract The$$ {D}_s^{+}\to {K}^{+}{K}^{-}{\mu}^{+}{\nu}_{\mu } $$ D s + → K + K − μ + ν μ decay is studied based on 7.33 fb −1 ofe + e − collision data collected with the BESIII detector at center-of-mass energies in the range from 4.128 to 4.226 GeV. The absolute branching fraction is measured as$$ \mathcal{B}\left({D}_s^{+}\to \phi {\mu}^{+}{\nu}_{\mu}\right)=\left(2.25\pm 0.09\pm 0.07\right)\times {10}^{-2} $$ B D s + → ϕ μ + ν μ = 2.25 ± 0.09 ± 0.07 × 10 − 2 , the most precise measurement to date. Combining with the world average of$$ \mathcal{B}\left({D}_s^{+}\to \phi {e}^{+}{\nu}_e\right) $$ B D s + → ϕ e + ν e , the ratio of the branching fractions obtained is$$ \frac{\mathcal{B}\left({D}_s^{+}\to \phi {\mu}^{+}{\nu}_{\mu}\right)}{\mathcal{B}\left({D}_s^{+}\to \phi {e}^{+}{\nu}_e\right)}=0.94\pm 0.08 $$ B D s + → ϕ μ + ν μ B D s + → ϕ e + ν e = 0.94 ± 0.08 , in agreement with lepton universality. By performing a partial wave analysis, the hadronic form factor ratios atq 2 = 0 are extracted, finding$$ {r}_V=\frac{V(0)}{A_1(0)}=1.58\pm 0.17\pm 0.02 $$ r V = V 0 A 1 0 = 1.58 ± 0.17 ± 0.02 and$$ {r}_2=\frac{A_2(0)}{A_1(0)}=0.71\pm 0.14\pm 0.02 $$ r 2 = A 2 0 A 1 0 = 0.71 ± 0.14 ± 0.02 , where the first uncertainties are statistical and the second are systematic. No significantS-wave contribution fromf 0 (980)→ K + K − is found. The upper limit$$ \mathcal{B}\left({D}_s^{+}\to {f}_0(980){\mu}^{+}{\nu}_{\mu}\right)\cdot \mathcal{B}\left({f}_0(980)\to {K}^{+}{K}^{-}\right)<5.45\times {10}^{-4} $$ B D s + → f 0 980 μ + ν μ ⋅ B f 0 980 → K + K − < 5.45 × 10 − 4 is set at 90% credibility level.

Physics↗
DOE OSTI2025

Estimating evapotranspiration from deciduous broadleaf forests by considering the effect of foliar litter

Forest litter cover significantly alters the ground surface resistance, which influences the water and energy transfer processes between the land surface and atmosphere. Penman-Monteith (PM) model is widely used to estimate land surface evapotranspiration (ET). However, it was shown to overestimate ET during the period when foliar litter covers the ground surface. Therefore, incorporating the effect of foliar litter on ground surface resistance can potentially improve ET estimates. Here, in this study, we proposed a foliar litter surface resistance model to describe the effect of litter cover on water vapor transport, then incorporated the litter surface resistance into the PM model (noted as PM-EL model). The performance of the PM-EL model was evaluated using observations from 18 deciduous broadleaf forest (DBF) flux sites across global FLUXNET2015 datasets. Results showed that: (1) both the PM model and the PM-EL model are most sensitive to ground surface resistance among resistance parameters; (2) the proposed litter resistance model is capable of describing the seasonal dynamic of litter in DBF ; (3) the PM-EL model, has been shown to improve ET estimates with the coefficient of determination increased by 8.5 %, the mean absolute error and relative root mean square error decreased by 22.1 % and 20.9 %, respectively. The study contributes to our understanding of the effect of litter cover on ET estimation and provides insights into forest ecohydrology and land surface mass and energy transfer processes.

Deciduous Broadleaf Forest↗
DOE OSTI2026

A hybrid Penman-Monteith and machine learning model for simulating evapotranspiration and its components

Integrating physical processes with machine learning has advanced evapotranspiration (ET) simulation, yet most hybrid models fail to partition total ET into its components: soil evaporation (E) and vegetation transpiration (T). This study introduces Residual Neural Network–Penman–Monteith (RNN-PM), a novel hybrid dual-source ET model designed to overcome this limitation. The model synergizes the physically-based Penman–Monteith framework with three specialized residual neural networks trained to estimate key conductance parameters (canopy conductance, soil surface conductance, and aerodynamic conductance). Furthermore this explicit parameterization allows for the direct partitioning of total ET. Validation at National Ecological Observatory Network (NEON) flux sites using high-frequency partitioned E and T shows that RNN-PM reliably reproduces ET and the transpiration fraction (T/ET). For ET, the model achieves an average Kling–Gupta efficiency (KGE) of 0.89 and a root-mean-square error (RMSE) of 0.55 mm/day; for T/ET, the KGE is 0.87 with an RMSE of 0.06. Furthermore, RNN-PM demonstrates robust generalization, accurately simulating ET and its components well beyond the initial training dataset, even under extreme climatic conditions. This study extended the analysis by comparing the RNN-PM model with seven established dual-source ET models. The results indicate that RNN-PM outperforms both conventional machine learning models and purely physical process-based models in simulating ET components in most cases. Among the purely physical process-based dual-source models, those based on surface temperature decomposition showed improved performance as the leaf area index (LAI) decreased when evaluated against high-frequency ET component datasets. In contrast, the performance of conductance-based dual-source models declined with decreasing LAI. Although purely machine learning-based models can produce relatively accurate simulations of ET components, they often exhibit limited generalization capability, an issue that the RNN-PM model effectively overcomes. Ultimately, the RNN-PM model represents a significant advance in simulating ET components, offering a novel and scalable approach for improving the representation of land–atmosphere interactions in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
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↗