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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Simulation Comparisons of Particulate Emissions from Fires under Marginal and Critical Conditions

Using a particulate emissions model developed for FIRETEC, we explore differences in particle emission profiles between high-intensity fires under critical conditions and low-intensity fires under marginal conditions. Simulations were performed in a chaparral shrubland and a coniferous pine forest representative of the southeast United States. In each case, simulations were carried out under marginal and critical fire conditions. Marginal fire conditions include high moisture levels and low winds, often desired for prescribed fires as these conditions produce a low-intensity burn with slower spread rates. Critical fire conditions include low moisture levels and high winds, which easily lead to uncontrollable wildfires which produce a high-intensity burn with faster spread rates. These simulations’ resultant particle emission profiles show critical fire conditions generate larger particle emission factors, higher total mass emissions, and a higher lofting potential of particles into the atmosphere when compared against marginal fire conditions but similar particle size distrubtions. In addition, a sensitivity analysis of the emissions model was performed to evaluate key parameters which govern particle emission factor and particle size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Activated Carbons Derived from High-Temperature Pyrolysis of Lignocellulosic Biomass

Biomass pyrolysis to produce biofuel and hydrogen yields large amounts of charred byproducts with low commercial value. A study was conducted to evaluate their potential for being converted into higher value activated carbons by a low-cost process. Six chars derived from various lignocellulosic precursors were activated in CO 2 at 800 °C to 30–35% weight loss, and their surface area and porosity were characterized by nitrogen adsorption at 77 K. It was found that, in similar activation conditions, the surface area of the activated carbons correlates with the activation energy of the oxidation reaction by CO 2 , which in turn varies inversely with the carbon yield after thermolysis in nitrogen at 1000 °C. Since lignin is the most thermally-stable component of lignocellulosic biomass, these results demonstrate, indirectly, that robust, lignin-rich vegetal precursors are to be preferred to produce higher quality activated carbons. The chars derived from white pine (pinus strobus) and chestnut oak (quercus prinus) were converted to activated carbons with the highest surface area (900–1100 m 2 /g) and largest mesopores volume (0.85–1.06 cm 3 /g). These activated carbons have properties similar to those of commercially-available activated carbons used successfully for removal of pollutants from aqueous solutions.

09 BIOMASS FUELS↗
DOE OSTI2019

From Farms to Forests: Landscape Carbon Balance after 50 Years of Afforestation, Harvesting, and Prescribed Fire

Establishing reliable carbon baselines for landowners desiring to sustain carbon sequestration and identify opportunities to mitigate land management impacts on carbon balance is important; however, national and regional assessments are not designed to support individual landowners. Such baselines become increasingly valuable when landowners convert land use, change management, or when disturbance occurs. We used forest inventories to quantify carbon stocks, estimate annual carbon fluxes, and determine net biome production (NBP) over a 50-year period coinciding with a massive afforestation effort across ~80,000 ha of land in the South Carolina Coastal Plain. Forested land increased from 48,714 ha to 73,824 ha between 1951 and 2001. Total forest biomass increased from 1.73–3.03 Gg to 17.8–18.3 Gg, corresponding to biomass density increases from 35.6–62.2 Mg ha−1 to 231.4–240.0 Mg ha−1. Harvesting removed 1340.3 Gg C between 1955 and 2001, but annual removals were variable. Fire consumed 527.1 Gg C between 1952 and 2001. Carbon exported by streams was <0.5% of total export. Carbon from roots and other harvested material that remained in-use or in landfills comprised 49.3% of total harvested carbon. Mineral soil carbon accounted for 41.6 to 50% of 2001 carbon stocks when considering depths of 1.0 or 1.5 m, respectively, and was disproportionately concentrated in wetlands. Moreover, we identified a soil carbon deficit of 19–20 Mg C ha−1, suggesting opportunities for future soil carbon sequestration in post-agricultural soils. Our results provide a robust baseline for this site that can be used to understand how land conversion, forest management, and disturbance impacts carbon balance of this landscape and highlight the value of these baseline data for other sites. Our work also identifies the need to manage forests for multiple purposes, especially promotion of soil carbon accumulation in low-density pine savannas that are managed for red-cockaded woodpeckers and therefore demand low aboveground carbon stocks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Stand Age and Climate Change Effects on Carbon Increments and Stock Dynamics

Carbon assimilation and wood production are influenced by environmental conditions and endogenous factors, such as species auto-ecology, age, and hierarchical position within the forest structure. Disentangling the intricate relationships between those factors is more pressing than ever due to climate change’s pressure. We employed the 3D-CMCC-FEM model to simulate undisturbed forests of different ages under four climate change (plus one no climate change) Representative Concentration Pathways (RCP) scenarios from five Earth system models. In this context, carbon stocks and increment were simulated via total carbon woody stocks and mean annual increment, which depends mainly on climate trends. We find greater differences among different age cohorts under the same scenario than among different climate scenarios under the same age class. Increasing temperature and changes in precipitation patterns led to a decline in above-ground biomass in spruce stands, especially in the older age classes. On the contrary, the results show that beech forests will maintain and even increase C-storage rates under most RCP scenarios. Scots pine forests show an intermediate behavior with a stable stock capacity over time and in different scenarios but with decreasing mean volume annual increment. These results confirm current observations worldwide that indicate a stronger climate-related decline in conifers forests than in broadleaves.

Forestry↗
DOE OSTI2023

Transcriptomics of Temporal- versus Substrate-Specific Wood Decay in the Brown-Rot Fungus Fibroporia radiculosa

Brown-rot fungi lack many enzymes associated with complete wood degradation, such as lignin-attacking peroxidases, and have developed alternative mechanisms for rapid wood breakdown. To identify the effects of culture conditions and wood substrates on gene expression, we grew Fibroporia radiculosa in submerged cultures containing Wiley milled wood (5 days) and solid wood wafers (30 days), using aspen, pine, and spruce as a substrate. The comparative analysis revealed that wood species had a limited effect on the transcriptome: <3% of genes were differentially expressed between different wood species substrates. The comparison between gene expression during growth on milled wood and wood wafer conditions, however, indicated that the genes encoding plant cell wall-degrading enzymes, such as glycoside hydrolases and peptidases, were activated during growth on wood wafers, confirming previous reports. On the other hand, it was shown for the first time that the genes encoding Fenton chemistry enzymes, such as hydroquinone biosynthesis enzymes and oxidoreductases, were activated during submerged growth on ground wood. This illustrates the diversity of wood-decay reactions encoded in fungi and activated at different stages of this process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Utilization of Synthetic Near-Infrared Spectra via Generative Adversarial Network to Improve Wood Stiffness Prediction

Near-infrared (NIR) spectroscopy is widely used as a nondestructive evaluation (NDE) tool for predicting wood properties. When deploying NIR models, one faces challenges in ensuring representative training data, which large datasets can mitigate but often at a significant cost. Machine learning and deep learning NIR models are at an even greater disadvantage because they typically require higher sample sizes for training. In this study, NIR spectra were collected to predict the modulus of elasticity (MOE) of southern pine lumber (training set = 573 samples, testing set = 145 samples). To account for the limited size of the training data, this study employed a generative adversarial network (GAN) to generate synthetic NIR spectra. The training dataset was fed into a GAN to generate 313, 573, and 1000 synthetic spectra. The original and enhanced datasets were used to train artificial neural networks (ANNs), convolutional neural networks (CNNs), and light gradient boosting machines (LGBMs) for MOE prediction. Overall, results showed that data augmentation using GAN improved the coefficient of determination (R 2 ) by up to 7.02% and reduced the error of predictions by up to 4.29%. ANNs and CNNs benefited more from synthetic spectra than LGBMs, which only yielded slight improvement. All models showed optimal performance when 313 synthetic spectra were added to the original training data; further additions did not improve model performance because the quality of the datapoints generated by GAN beyond a certain threshold is poor, and one of the main reasons for this can be the size of the initial training data fed into the GAN. LGBMs showed superior performances than ANNs and CNNs on both the original and enhanced training datasets, which highlights the significance of selecting an appropriate machine learning or deep learning model for NIR spectral-data analysis. The results highlighted the positive impact of GAN on the predictive performance of models utilizing NIR spectroscopy as an NDE technique and monitoring tool for wood mechanical-property evaluation. Further studies should investigate the impact of the initial size of training data, the optimal number of generated synthetic spectra, and machine learning or deep learning models that could benefit more from data augmentation using GANs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Experience Economy in a Wine Destination—Analysing Visitor Reviews

Wine tourism in rural territories, sometimes organised along wine routes, increasingly attracts visitors, tourism agents, wine producers and those responsible for developing rural territories. Wine tourism is located at the intersection of two distinct business sectors: the agribusiness-oriented wine production and the hedonic service/experience-oriented tourism activity. From the tourism perspective, the visitor experience is paramount and requires an understanding of its nature, conditioning factors and possible outcomes. This study analyses tourist experiences of the Bairrada wine route/Portugal, as reported by regional visitors on TripAdvisor. Results reveal not only the overall quite positive evaluation of these experiences, but also the importance of the aesthetic and educational experience dimensions, when applying Pine and Gilmore’s consumer experience framework. Diverse experience contexts contribute to a rich terroir experiencescape, where contents are far from limited to wine, wine cellars or wineries. These contexts seem to be connected distinctly to diverse experience dimensions, whose analysis should help regional developers understand the role of core resources and conditions for attracting, satisfying and delighting visitors. Additional understanding of the relationship between experience dimensions and outcomes, namely satisfaction and destination loyalty, should further help develop wine destinations more successfully.

Kastenholz, Elisabeth↗
DOE OSTI2015

Avian community composition in response to high explosive testing operations at Los Alamos National Laboratory in Northern New Mexico

Breeding bird abundance, species richness, evenness, diversity, composition, productivity, and survivorship were determined near a high-explosive detonation site at Los Alamos National Laboratory, New Mexico, USA, during pre-operation (1997-1999) and operation (2000-2014) periods. The operation periods consisted of detonations (<23 kg in yield and <3 per breeding season) in open air (2000-2002), within foam containment (2003-2006) and within steel vessel containment (2007-2014) systems; the latter two were employed to reduce noise and dispersal of high-explosives residues. A total of 2952 bird captures, representing 80 species, was recorded during 18 years of mist net operations using the Monitoring Avian Productivity and Survivorship protocol. Individuals captured were identified to species, aged, sexed, and banded during May through August of each year. There were no significant differences (p > 0.05) in mean avian abundance and species evenness in any of the operation periods as compared with the pre-operation period. Species richness and diversity were significantly higher (p < 0.05) during the vessel containment period (2007-2014) than the pre-operation period. The time period of this study coincided with a wildfire (2000), a bark beetle infestation (2002), and two periods of drought (Nov 1999-Mar 2004 and Dec 2005-Dec 2014) that affected the study area. Furthermore, analysis of aerial photos determined that the average percent canopy cover of mature ponderosa pines (Pinus ponderosa) within 100 feet of mist net sites declined from 12% to 3% between 1991 and 2014 and the percent cover of shrubs slightly increased.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Co-Processing Catalytic Fast Pyrolysis Oil in an FCC Reactor

Studies of co-processing catalytic fast pyrolysis (CFP) oil with vacuum gas oil (VGO) are conducted in a Davison Circulating Riser (DCR). The CFP oil (CFPO) for this study was produced by upgrading fast-pyrolysis vapors from pine in an ex-situ fixed-bed reactor. CFPOs were co-processed at up to 5 vol% with VGO at 521°C and 2.57 bar. The yields of oil, aqueous phase, tail gas, and coke were measured. The amount of coke was determined from the carbon containing components in the regenerator flue gas. A compositional analysis was conducted with gas chromatography and elemental analyzers. The organic liquids were distilled into gasoline, jet-fuel, diesel, and resid fractions. A biocarbon analysis was conducted on the organic phase and its individual boiling-point fractions. The results show a small decrease in liquid yield and a generally increased gas yield when co-processing CFPO with VGO. For experiments with E-Cat as catalyst, approximately 70% of biocarbon is incorporated into liquid fuels relative to fossil carbon, while more of the biocarbon is contained in tail gas (as carbon dioxide or olefins) and/or coke. The measurements indicate that cracked CFPO components are predominantly included in the jet-fuel and diesel fractions. A techno-economic analysis (TEA) estimated the minimum fuel selling price (MSFP) for fuel-range products derived from FCC co-processing of CFPO at $3 to $4 per gasoline-gallon equivalent (GGE) at a yield of 51 GGE per ton of biomass.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Overview of the Manitou Experimental Forest Observatory: site description and selected science results from 2008 to 2013

The Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen (BEACHON) project seeks to understand the feedbacks and interrelationships between hydrology, biogenic emissions, carbon assimilation, aerosol properties, clouds and associated feedbacks within water-limited ecosystems. The Manitou Experimental Forest Observatory (MEFO) was established in 2008 by the National Center for Atmospheric Research to address many of the BEACHON research objectives, and it now provides a fixed field site with significant infrastructure. MEFO is a mountainous, semi-arid ponderosa pine-dominated forest site that is normally dominated by clean continental air but is periodically influenced by anthropogenic sources from Colorado Front Range cities. This article summarizes the past and ongoing research activities at the site, and highlights some of the significant findings that have resulted from these measurements. These activities include – soil property measurements; – hydrological studies; – measurements of high-frequency turbulence parameters; – eddy covariance flux measurements of water, energy, aerosols and carbon dioxide through the canopy; – determination of biogenic and anthropogenic volatile organic compound emissions and their influence on regional atmospheric chemistry; – aerosol number and mass distributions; – chemical speciation of aerosol particles; – characterization of ice and cloud condensation nuclei; – trace gas measurements; and – model simulations using coupled chemistry and meteorology. In addition to various long-term continuous measurements, three focused measurement campaigns with state-of-the-art instrumentation have taken place since the site was established, and two of these studies are the subjects of this special issue: BEACHON-ROCS (Rocky Mountain Organic Carbon Study, 2010) and BEACHON-RoMBAS (Rocky Mountain Biogenic Aerosol Study, 2011).

Ortega, John↗
DOE OSTI2017

Secondary organic aerosol formation from in situ OH, O 3 , and NO 3 oxidation of ambient forest air in an oxidation flow reactor

Ambient pine forest air was oxidized by OH, O 3 , or NO 3 radicals using an oxidation flow reactor (OFR) during the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H 2 O, Organics and Nitrogen – Rocky Mountain Biogenic Aerosol Study) campaign to study biogenic secondary organic aerosol (SOA) formation and organic aerosol (OA) aging. A wide range of equivalent atmospheric photochemical ages was sampled, from hours up to days (for O 3 and NO 3 ) or weeks (for OH). Ambient air processed by the OFR was typically sampled every 20–30 min, in order to determine how the availability of SOA precursor gases in ambient air changed with diurnal and synoptic conditions, for each of the three oxidants. More SOA was formed during nighttime than daytime for all three oxidants, indicating that SOA precursor concentrations were higher at night. At all times of day, OH oxidation led to approximately 4 times more SOA formation than either O 3 or NO 3 oxidation. This is likely because O 3 and NO 3 will only react with gases containing C = C bonds (e.g., terpenes) to form SOA but will not react appreciably with many of their oxidation products or any species in the gas phase that lacks a C = C bond (e.g., pinonic acid, alkanes). In contrast, OH can continue to react with compounds that lack C = C bonds to produce SOA. Closure was achieved between the amount of SOA formed from O 3 and NO 3 oxidation in the OFR and the SOA predicted to form from measured concentrations of ambient monoterpenes and sesquiterpenes using published chamber yields. This is in contrast to previous work at this site (Palm et al., 2016), which has shown that a source of SOA from semi- and intermediate-volatility organic compounds (S/IVOCs) 3.4 times larger than the source from measured VOCs is needed to explain the measured SOA formation from OH oxidation. This work suggests that those S/IVOCs typically do not contain C = C bonds. O 3 and NO 3 oxidation produced SOA with elemental O : C and H : C similar to the least-oxidized OA observed in local ambient air, and neither oxidant led to net mass loss at the highest exposures, in contrast to OH oxidation. An OH exposure in the OFR equivalent to several hours of atmospheric aging also produced SOA with O : C and H : C values similar to ambient OA, while higher aging (days–weeks) led to formation of SOA with progressively higher O : C and lower H : C (and net mass loss at the highest exposures). NO 3 oxidation led to the production of particulate organic nitrates (pRONO 2 ), while OH and O 3 oxidation (under low NO) did not, as expected. These measurements of SOA formation provide the first direct comparison of SOA formation potential and chemical evolution from OH, O 3 , and NO 3 oxidation in the real atmosphere and help to clarify the oxidation processes that lead to SOA formation from biogenic hydrocarbons.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Identification of gas-phase pyrolysis products in a prescribed fire: first detections using infrared spectroscopy for naphthalene, methyl nitrite, allene, acrolein and acetaldehyde

Volatile organic compounds (VOCs) are emitted from many sources, includingwildland fire. VOCs have received heightened emphasis due to such gases'influential role in the atmosphere, as well as possible health effects. Wehave used extractive infrared (IR) spectroscopy on recent prescribed burnsin longleaf pine stands and herein report the first detection of fivecompounds using this technique. The newly reported IR detections includenaphthalene, methyl nitrite, allene, acrolein and acetaldehyde. We discussthe approaches used for detection, particularly the software methods neededto fit the analyte and multiple (interfering) spectral components within theselected spectral micro-window(s). We also discuss the method's detectionlimits and related parameters such as spectral resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Impacts of simulated herbivory on volatile organic compound emission profiles from coniferous plants

The largest global source of volatile organic compounds (VOCs) in the atmosphere is from biogenic emissions. Plant stressors associated with a changing environment can alter both the quantity and composition of the compounds that are emitted. This study investigated the effects of one global change stressor, increased herbivory, on plant emissions from five different coniferous species: bristlecone pine ( Pinus aristata ), blue spruce ( Picea pungens ), western redcedar ( Thuja plicata ), grand fir ( Abies grandis ), and Douglas-fir ( Pseudotsuga menziesii ). Herbivory was simulated in the laboratory via exogenous application of methyl jasmonate (MeJA), a herbivory proxy. Gas-phase species were measured continuously with a gas chromatograph coupled to a mass spectrometer and flame ionization detector (GC–MS–FID). Stress responses varied between the different plant types and even between experiments using the same set of saplings. The compounds most frequently impacted by the stress treatment were alpha-pinene, beta-pinene, 1,8-cineol, beta-myrcene, terpinolene, limonene, and the cymene isomers. Individual compounds within a single experiment often exhibited a different response to the treatment from one another.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Experimental design for three interrelated marine ice sheet and ocean model intercomparison projects: MISMIP v. 3 (MISMIP +), ISOMIP v. 2 (ISOMIP +) and MISOMIP v. 1 (MISOMIP1)

Coupled ice sheet-ocean models capable of simulating moving grounding lines are just becoming available. Such models have a broad range of potential applications in studying the dynamics of marine ice sheets and tidewater glaciers, from process studies to future projections of ice mass loss and sea level rise. The Marine Ice Sheet-Ocean Model Intercomparison Project (MISOMIP) is a community effort aimed at designing and coordinating a series of model intercomparison projects (MIPs) for model evaluation in idealized setups, model verification based on observations, and future projections for key regions of the West Antarctic Ice Sheet (WAIS). Here we describe computational experiments constituting three interrelated MIPs for marine ice sheet models and regional ocean circulation models incorporating ice shelf cavities. These consist of ice sheet experiments under the Marine Ice Sheet MIP third phase (MISMIP+), ocean experiments under the Ice Shelf-Ocean MIP second phase (ISOMIP+) and coupled ice sheet-ocean experiments under the MISOMIP first phase (MISOMIP1). All three MIPs use a shared domain with idealized bedrock topography and forcing, allowing the coupled simulations (MISOMIP1) to be compared directly to the individual component simulations (MISMIP+ and ISOMIP+). The experiments, which have qualitative similarities to Pine Island Glacier Ice Shelf and the adjacent region of the Amundsen Sea, are designed to explore the effects of changes in ocean conditions, specifically the temperature at depth, on basal melting and ice dynamics. In future work, differences between model results will form the basis for the evaluation of the participating models.

58 GEOSCIENCES↗
DOE OSTI2023

CORPSE model with litter decomposition parameters derived from the LIDET dataset

This is a version of the CORPSE model (Carbon, Organisms, Rhizosphere and Protection in the Soil Environment, Sulman et al. 2014) that uses litter decomposition parameters derived from a modified Monte Carlo simulation using the LIDET litter decomposition dataset (Long-term Intersite Decomposition Experiment Team, Harmon 2013). The code also includes the Baseline parameters, and the eight other best parameter sets identified in a modified Monte Carlo simulation. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of files:The folder "Input Files" contains one folder for each LIDET site with data necessary to run the model. Note that "(site)" in the filenames below indicates where the LIDET site code appears (see Table 1 for site codes). Data streams include: CORPSE_full_spinup_litter.csv, CORPSE_full_spinup_rhizo.csv, CORPSE_full_spinup_bulk.csv, litterbag_init_100g_6spp.csv: initial C and N (kg C or N/m2) pool values for each soil layer, the litterbag_init_100_6spp.csv file is for the litterbag layer and is the same file for all sites. All initial C and N files have the same columns (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 soilT (site) DOY274start.csv: Average daily soil temperature (oC) interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). soilT (site) DOY274start.csv: Average daily soil volumetric water content (VWC) scalar interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). litter production.csv: Average daily litter production values for each site, data sources listed in Table S3 of related publication. litter (site) CN.csv: C:N ratio for each species from LIDET dataset (Table 2, Harmon 2013). (site).csv: Table indicating number of observations for each species decomposed at each site. Instructions: Save the model code ("CORPSE_LIDET.R") and "Input Files" folder in the same folder. Also make a folder for the model output (e.g., "results_Baseline") in the same folder. Set the working directory (setwd) in the model code to the folder with the files saved in step #1. Select the parameter set to use for the litter and litterbag compartments, comment out all other parameter sets. Run code. Output will be saved in the folder made in step 1. Output destination can be changed as necessary in code section called "Running the model." Table 1 LIDET sites and site codes used in model files. Site Code - Site AND - H.J. Andrews Experimental Forest BNZ - Bonanza Creek Experimental Forest BSF - Blodgett Research Forest CDR - Cedar Creek Natural History Area CPR - Central Plains Experimental Range HBR - Hubbard Brook Experimental Forest HFR - Harvard Forest JUN - Juneau KBS - Kellogg Biological Station KNZ - Konza Prairie Research Natural Area NWT - Niwot Ridge/Green Lakes Valley OLY - Olympic National Park OLY Conifer forest SEV - Sevilleta National Wildlife Refuge SMR - Santa Margarita Ecological Reserve UFL - University of Florida VCR - Virginia Coast Reserve Table 2 LIDET species and species codes used in model files (6 common species). Species - Species Code Sugar maple (Acer saccharum) - ACSA Drypetes (Drypetes glauca) - DRGL Red pine (Pinus resinosa) - PIRE Chestnut oak (Quercus prinus) - QUPR Western redcedar (Thuja plicata) - THPL Wheat (Triticum aestivum) - TRAE References:Bonan, G. B., Hartman, M. D., Parton, W. J., & Wieder, W. R. (2013). Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4). Global Change Biology, 19(3), 957-974. https://doi.org/https://doi.org/10.1111/gcb.12031 Harmon, M. (2013). LTER Intersite Fine Litter Decomposition Experiment (LIDET), 1990 to 2002. Long-Term Ecological Research. Forest Science Data Bank, Corvallis, OR. [Data set]. Accessed http://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023. https://doi.org/10.6073/pasta/f35f56bea52d78b6a1ecf1952b4889c5. Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E., & Pacala, S. W. (2014). Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2. Nature Climate Change, 4, 1099 - 1102. https://doi.org/10.1038/nclimate2436

Juice, Stephanie↗
DOE OSTI2020

ExINP-ENA Ice-Nucleating Particle Concentrations - CRAFT

This data set comprises cumulative ambient ice-nucleating particle (INP) concentrations measured at the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) observatory on Graciosa Island, Azores (39.0916&deg; N, 28.0257&deg; W). Our INP data were generated using a combination of online instruments, the Portable Ice Nucleation Experiment chamber (PINE), and an offline assay instrument, the West Texas Cryogenic Refrigerator Applied to Freezing Test system (WT-CRAFT), for aerosol particle samples collected on polycarbonate filters (with 0.2-micron diameter pores).

47-mm Nuclepore filter sampler, West Texas Cryogen↗
DOE OSTI2023

Productivity and Cost of Post-Tornado Salvage Logging in Upper Coastal Plain of South Carolina, USA

Salvage harvesting is common in the US South following natural disasters such as tornadoes and hurricanes; nevertheless, few studies have evaluated the productivity and costs of these harvests because of their geographic dispersion and the short interval between natural disasters and salvage harvesting. An Enhanced Fujita Scale 3 (EF3) tornado with winds in excess of 250 km per hour struck Aiken County, South Carolina in April of 2020, uprooting trees and severing other stems above breast height. The goal of this study was to estimate the productivity and cost of salvage harvesting in loblolly pine (Pinus taeda L.) stands following severe tornado damage. Salvage harvests were conducted with a rubber-tired drive-to-tree feller-buncher, grapple skidder, tracked loader, and chipper. All stems were chipped and used to produce energy; no roundwood was produced from the harvests. Elemental time-and-motion studies were conducted in three pulpwood-sized stands (<30 cm large-end diameter) and three sawtimber-sized stands (≥30 cm large-end diameter). Hourly harvesting costs were estimated using the machine rate method and per-ton costs were estimated using a modified version of the Auburn Harvesting Analyzer. Skidding productivity was low in each harvest unit, but especially so in the three pulpwood-sized stands because of stem breakage and low weight per stem. Harvesting costs averaged $\$$29.78 and $\$$19.97 (USD) per tonne (onboard truck) in the pulpwood- and sawtimber-sized stands, respectively. High salvage harvesting costs mean that landowners can expect significantly reduced stumpage prices from these harvests; nonetheless, landowners do benefit from reduced reforestation costs. Harvesting promptly after a tornado can reduce harvesting costs and increase timber value recovery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Logging Crew Attributes by Region in the Southeast USA

Urbanization, shrinking markets, and reduced forestry investment may affect harvesting efficiency in regions of the US South. To monitor these conditions, logging businesses have been tracked by surveys conducted by universities and trade associations. This project used a sampling approach coordinated with FIA utilization studies to sample logging crews based on a harvesting location. The approach was used to develop relationships among firm attributes and site attributes in six southeastern states (AL, GA, FL, NC, SC, and VA) from 2011 to 2018. The data included harvest attributes (location, harvest size and stand type) and logging firm attributes (production, crew labor, crew number, the number of machines by type, and machine age). For crew capital value, an equation was developed for this study using machine number and average machine age. The data from logging crews on 419 harvests were analyzed by region, harvest size, and stand type. Mean values for crew labor ranged from 3.1 to 7.1 workers. The average capital value per crew ranged from $\$220,000$ to $\$524,000$ per crew in the Coastal Plain with a narrower range in the Piedmont. In the Coastal Plain, higher productivity was detected for larger harvests and pine versus hardwood and mixed stands; however, in the Piedmont those trends were less obvious. Ratio of feller-bunchers, skidders and loaders were mostly 1:1:1 or 1:2:1 with 41% and 24% of samples, respectively. There were notable trends among Coastal Plain loggers regarding capital value and productivity with evidence supported by a production function. The differences in Piedmont (e.g., ownership size, market access, terrain, population density, etc.) may combine to limit daily production and labor productivity.

54 ENVIRONMENTAL SCIENCES↗