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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties

Abstract The regional variability in tundra and boreal carbon dioxide (CO 2 ) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO 2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO 2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO 2 fluxes and test the accuracy and uncertainty of different statistical models. CO 2 fluxes were upscaled at relatively high spatial resolution (1 km 2 ) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO 2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m −2 yr −1 , respectively) compared to tundra (average annual NEE +10 and −2 g C m −2 yr −1 ). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO 2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO 2 sink during 1990–2015, although uncertainty remains high.

Virkkala, Anna‐Maria↗

DOE OSTI2021

Warming and elevated CO 2 promote rapid incorporation and degradation of plant‐derived organic matter in an ombrotrophic peatland

Abstract Rising temperatures have the potential to directly affect carbon cycling in peatlands by enhancing organic matter (OM) decomposition, contributing to the release of CO 2 and CH 4 to the atmosphere. In turn, increasing atmospheric CO 2 concentration may stimulate photosynthesis, potentially increasing plant litter inputs belowground and transferring carbon from the atmosphere into terrestrial ecosystems. Key questions remain about the magnitude and rate of these interacting and opposing environmental change drivers. Here, we assess the incorporation and degradation of plant‐ and microbe‐derived OM in an ombrotrophic peatland after 4 years of whole‐ecosystem warming (+0, +2.25, +4.5, +6.75 and +9°C) and two years of elevated CO 2 manipulation (500 ppm above ambient). We show that OM molecular composition was substantially altered in the aerobic acrotelm, highlighting the sensitivity of acrotelm carbon to rising temperatures and atmospheric CO 2 concentration. While warming accelerated OM decomposition under ambient CO 2 , new carbon incorporation into peat increased in warming × elevated CO 2 treatments for both plant‐ and microbe‐derived OM. Using the isotopic signature of the applied CO 2 enrichment as a label for recently photosynthesized OM, our data demonstrate that new plant inputs have been rapidly incorporated into peat carbon. Our results suggest that under current hydrological conditions, rising temperatures and atmospheric CO 2 levels will likely offset each other in boreal peatlands.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Trading water for carbon in the future: Effects of elevated CO 2 and warming on leaf hydraulic traits in a semiarid grassland

Abstract The effects of climate change on plants and ecosystems are mediated by plant hydraulic traits, including interspecific and intraspecific variability of trait phenotypes. Yet, integrative and realistic studies of hydraulic traits and climate change are rare. In a semiarid grassland, we assessed the response of several plant hydraulic traits to elevated CO 2 (+200 ppm) and warming (+1.5 to 3°C; day to night). For leaves of five dominant species (three graminoids and two forbs), and in replicated plots exposed to 7 years of elevated CO 2 , warming, or ambient climate, we measured: stomatal density and size, xylem vessel size, turgor loss point, and water potential (pre‐dawn). Interspecific differences in hydraulic traits were larger than intraspecific shifts induced by elevated CO 2 and/or warming. Effects of elevated CO 2 were greater than effects of warming, and interactions between treatments were weak or not detected. The forbs showed little phenotypic plasticity. The graminoids had leaf water potentials and turgor loss points that were 10% to 50% less negative under elevated CO 2 ; thus, climate change might cause these species to adjust their drought resistance strategy away from tolerance and toward avoidance. The C4 grass also reduced allocation of leaf area to stomata under elevated CO 2 , which helps explain observations of higher soil moisture. The shifts in hydraulic traits under elevated CO 2 were not, however, simply due to higher soil moisture. Integration of our results with others' indicates that common species in this grassland are more likely to adjust stomatal aperture in response to near‐term climate change, rather than anatomical traits; this contrasts with apparent effects of changing CO 2 on plant anatomy over evolutionary time. Future studies should assess how plant responses to drought may be constrained by the apparent shift from tolerance (via low turgor loss point) to avoidance (via stomatal regulation and/or access to deeper soil moisture).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Photosynthetic responses of switchgrass to light and CO 2 under different precipitation treatments

Switchgrass ( Panicum virgatum L .) is a prominent bioenergy crop with robust resilience to environmental stresses. However, our knowledge regarding how precipitation changes affect switchgrass photosynthesis and its responses to light and CO 2 remains limited. To address this knowledge gap, we conducted a field precipitation experiment with five different treatments, including −50%, −33%, 0%, +33%, and +50% of ambient precipitation. To determine the responses of leaf photosynthesis to CO 2 concentration and light, we measured leaf net photosynthesis of switchgrass under different CO 2 concentrations and light levels in 2020 and 2021 for each of the five precipitation treatments. We first evaluated four light and CO 2 response models (i.e., rectangular hyperbola model, nonrectangular hyperbola model, exponential model, and the modified rectangular hyperbola model) using the measurements in the ambient precipitation treatment. Based on the fitting criteria, we selected the nonrectangular hyperbola model as the optimal model and applied it to all precipitation treatments, and estimated model parameters. Overall, the model fit field measurements well for the light and CO 2 response curves. Precipitation change did not influence the maximum net photosynthetic rate ( P max ) but influenced other model parameters including quantum yield ( α ), convexity ( θ ), dark respiration ( Rd ), light compensation point ( LCP ), and saturated light point ( LSP ). Specifically, the mean P max of five precipitation treatments was 17.6 μmol CO 2 m −2 s −1 , and the ambient treatment tended to have a higher P max . The +33% treatment had the highest α , and the ambient treatment had lower θ and LCP , higher Rd , and relatively lower LSP . Furthermore, precipitation significantly influenced all model parameters of CO 2 response. The ambient treatment had the highest P max , largest α , and lowest θ , R d , and CO 2 compensation point LCP . Overall, this study improved our understanding of how switchgrass leaf photosynthesis responds to diverse environmental factors, providing valuable insights for accurately modeling switchgrass ecophysiology and productivity.

09 BIOMASS FUELS↗

DOE OSTI2022

Accelerated sea-level rise is suppressing CO 2 stimulation of tidal marsh productivity: A 33-year study

Accelerating relative sea-level rise (RSLR) is threatening coastal wetlands. However, rising CO 2 concentrations may also stimulate carbon sequestration and vertical accretion, counterbalancing RSLR. A coastal wetland dominated by a C 3 plant species was exposed to ambient and elevated levels of CO 2 in situ from 1987 to 2019 during which time ambient CO 2 concentration increased 18% and sea level rose 23 cm. Plant production did not increase in response to gradually rising ambient CO 2 concentration during this period. Elevated CO 2 increased shoot production relative to ambient CO 2 for the first two decades, but from 2005 to 2019, elevated CO 2 stimulation of production was diminished. The decline coincided with increases in relative sea level above a threshold that hindered root productivity. While elevated CO 2 stimulation of elevation gain has the potential to moderate the negative impacts of RSLR on tidal wetland productivity, benefits for coastal wetland resilience will diminish in the long term as rates of RSLR accelerate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Skin CO 2 sniffing for wearable metabolic monitoring

CO 2 is a key physiological parameter used to assess hypoventilation and to estimate metabolic rates. However, current CO 2 monitoring relies on bulky breath-analysis systems that are impractical for continuous use in daily life. Here, we present a wearable on-skin gas-sniffing system that quantifies skin-emitted CO 2 and establishes its physiological relevance through direct correlation with exhaled CO 2 and metabolic rate. Participant studies demonstrate strong correlations between CO 2 flow rates from the skin and breath during both rest and exercise, with skin-emitted CO 2 approximately four orders of magnitude lower than exhaled CO 2 . Skin-emitted CO 2 also correlates with metabolic rate, suggesting its potential as a surrogate for breath-based indirect calorimetry. With its wearable form factor and physiological relevance, this skin gas sniffing system enables continuous, noninvasive metabolic monitoring and opens opportunities for studying skin gas exchange.

Kim, Seung-Rok [University of California, Berkeley↗

DOE OSTI2025

The Impact of Membrane Inactive Area on the Durability of Pt-Co Catalyst

Platinum (Pt) is the most active catalyst for oxygen reduction reaction; however, its activity still requires a significant increase to meet the demands of practical applications. To enhance the catalytic activity, alloy catalysts like platinum-cobalt (Pt-Co), are being extensively investigated. However, Co leaching from the Pt-Co alloy remains a significant concern. Evaluating the durability of Pt-Co alloy catalyst is further complicated by variations in Co leaching, which affects both the observed performance and durability. This variability often arises from an overlooked factor: choice of the inactive area of the membrane electrode assembly (MEA) used during the evaluation. This study examines the critical role of membrane inactive area on the performance loss observed during durability testing of Pt-Co alloys. Our findings indicate that a large membrane inactive area reduces the impact of Co leaching on performance and durability, up to 200 mA cm −2 difference in performance is observed between large and small inactive area MEA at 0.7 V for dry conditions, and more Co is retained in the active area of MEA for smaller inactive areas which is responsible for larger performance losses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Deep Learning–Assisted Multiobjective Optimization of Geological CO 2 Storage Performance under Geomechanical Risks

In geological CO 2 storage, designing the optimal well control strategy for CO 2 injection to maximize CO 2 storage while minimizing the associated geomechanical risks is not trivial. This challenge arises due to pressure buildup, CO 2 plume migration, the highly nonlinear nature of geomechanical responses to rock-fluid interaction, and the high computational cost associated with coupled flow and geomechanics simulations. In this paper, we introduce a novel optimization framework to address these challenges. The optimization problem is formulated as follows: maximize total CO 2 storage while minimizing geomechanical risks by adjusting the injection schedules within bounded constraints. The geomechanical risks are primarily driven by injection-induced pressure build-up, which is characterized by ground displacement and the induced microseismicity. We used the Fourier neural operator (FNO)-based deep learning model to construct surrogate models, replacing the time-consuming coupled flow and geomechanics simulations for evaluating the aforementioned objective functions. The developed surrogate models have been incorporated into a multiobjective optimization framework through a genetic algorithm to reduce the computational burden. The proposed optimization framework reduces the computational cost from approximately 2,400 hours, when using objective function evaluations based on physics-based simulations, to around 20 minutes. A set of Pareto-optimal solutions of the proposed workflow yields nontrivial optimal decisions, reducing the microseismicity potential and the vertical displacement. This Pareto front highlights the optimal trade-offs between CO 2 storage amount, safety, and ground displacement, emphasizing the need for careful optimization and management of injection strategies to achieve a balanced outcome. The novelty of this work is twofold. First, we demonstrate the importance of incorporating the minimization of the geomechanical risks as objective functions into the CO 2 storage optimization workflow to mitigate the potential risk of induced microseismicity and ground displacement. Second, we leverage the FNO-based surrogate models to optimize a real-field CO 2 storage operation.

42 ENGINEERING↗

DOE OSTI2020

User’s Manual for StrmtbFlow, the Stream Tube Multiphase Flow Part of the FE/NETL CO 2 Prophet Model, Version 2

The United States (U.S.) Department of Energy (DOE) Office of Fossil Energy (FE) at the National Energy Technology Laboratory (NETL) has developed the FE/NETL CO 2 Prophet Model, which is an updated version of the CO 2 Prophet. This document is a user’s manual for StrmtbFlow, which is one part of the FE/NETL CO 2 Prophet Model. CO 2 Prophet was originally developed in the 1990s by Texaco Exploration and Production Technology Department for DOE. The FE/NETL CO 2 Prophet Model is an oil reservoir simulator that is suitable for simulating water floods and supercritical carbon dioxide (CO 2 ) enhanced oil recovery (EOR). The FE/NETL CO 2 Prophet Model uses a number of assumptions to simplify the equations describing the flow of oil, water (or brine), and CO 2 in the oil reservoir.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

User’s Manual for StrmtbGen, the Stream Tube Generating Part of the FE/NETL CO 2 Prophet Model, Version 2

The United States (U.S.) Department of Energy (DOE) Office of Fossil Energy (FE) at the National Energy Technology Laboratory (NETL) has developed the FE/NETL CO 2 Prophet Model, which is Version 2 of CO 2 Prophet. This document is a User’s Manual for StrmtbGen, which is one part of the FE/NETL CO 2 Prophet Model. CO 2 Prophet was originally developed in the 1990s by Texaco Exploration and Production Technology Department for DOE. The FE/NETL CO 2 Prophet Model is an oil reservoir simulator that is suitable for simulating water floods and supercritical carbon dioxide (CO 2 ) enhanced oil recovery (EOR). The FE/NETL CO 2 Prophet Model uses a number of assumptions to simplify the equations describing the flow of oil, water (or brine), and CO 2 in the oil reservoir.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Fundamental Understanding of Methane-Carbon Dioxide-Water (CH 4 -CO 2 - H 2 O) Interactions in Shale Nanopores under Reservoir Conditions (Quarterly Report)

Shale is characterized by the predominant presence of nanometer-scale (1-100 nm) pores. The behavior of fluids in those pores directly controls shale gas storage and release in shale matrix and ultimately the wellbore production in unconventional reservoirs. Recently, it has been recognized that a fluid confined in nanopores can behave dramatically differently from the corresponding bulk phase due to nanopore confinement. CO 2 and H 2 O, either preexisting or introduced, are two major components that coexist with shale gas (predominately CH 4 ) during hydrofracturing and gas extraction. Note that liquid or supercritical CO 2 has been suggested as an alternative fluid for subsurface fracturing such that CO 2 enhanced gas recovery can also serve as a CO 2 sequestration process. Limited data indicate that CO 2 may preferentially adsorb in nanopores (particularly those in kerogen) and therefore displace CH 4 in shale. Similarly, the presence of water moisture seems able to displace or trap CH 4 in shale matrix. Therefore, fundamental understanding of CH 4 -CO 2 -H 2 O behavior and their interactions in shale nanopores is of great importance for gas production and the related CO 2 sequestration. This project focuses on the systematic study of CH 4 -CO 2 -H 2 O interactions in shale nanopores under high-pressure and high temperature reservoir conditions. The proposed work will help develop new stimulation strategies to enable efficient resource recovery from fewer and less environmentally impactful wells.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2020

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids With Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. Demand-side participation cannot be leveraged effectively without explicitly including the distribution system dynamics in the optimization-based wholesale market operations. This project grew from a vision for co-optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the lower voltage system (distribution or microgrid) can also sell (buy) excess (necessary) energy from the transmission system. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. An ideal microgrid is defined as an electric entity capable of operating in both interconnected (with the high-voltage grid) and islanded mode. As such, the microgrid should incorporate generating units (traditional units and intermittent) and if needed, exchange power with the high-voltage grid. The interplay between the microgrid and high-voltage grid motivated the development of the co-optimization approach to ensure efficient performance of the interconnected network. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Carbonate Management to Enable Energy- and Carbon-Efficient CO 2 Electrolysis (Final Technical Report)

The rapid growth and plummeting cost of solar energy have created great interest in using CO 2 electrolysis to produce chemical feedstocks and fuels such as carbon monoxide, ethylene, ethanol, and propanol. While research in CO 2 electrolysis has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices, the energy efficiency (electrical energy to-product) and carbon efficiency (CO 2 -to-product) of CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal reason for these low efficiencies is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH–) to form carbonate , which forces CO 2 electrolysis cells to operate under conditions that result in large voltage and CO 2 losses. This “CO 3 2 – problem” presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Comparison of Approaches for CO 2 Sequestration as Solid Carbon Products

The growing global climate crisis linked to the rising atmospheric CO 2 levels calls for urgent and innovative solutions. Fixing CO 2 as valuable solid carbon products, such as carbon nanofibers or nanotubes (CNFs or CNTs), offers a promising way to potentially achieve net-negative CO 2 emissions. However, direct CO 2 -to-solid carbon faces significant thermodynamic and kinetic constraints, especially under mild reaction conditions. This mini-review compares three emerging approaches for CO 2 conversion into solid carbon: 1) using molten salt at high temperatures to produce CNFs or CNTs, 2) converting CO 2 to amorphous carbon with pyrophoric liquid metals at near room temperature, and 3) employing an electrocatalytic-thermocatalytic tandem process to produce CNFs at relatively mild temperatures. We examine the underlying principles, thermodynamic driving forces, and recent advances of each approach, and discuss the challenges and opportunities in catalyst development, reactor design, and energy management. We aim to highlight CO 2 fixation, facilitate net-negative CO 2 emissions, and stimulate more innovations for both environmental and economic benefits.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Methanol Steam Reforming on Ru/m-ZrO 2 : Sodium Promotion of the CO 2 -Forming Pathway

Sodium (Na) promotion of Ru/m-ZrO 2 was investigated to elucidate how an alkali modification tunes selectivity in methanol steam reforming (MSR). H 2 -TPR/XANES/EXAFS show that Na increases surface basicity and strengthens Ru–O interactions, shifting RuO x reduction and H 2 spillover to a higher temperature. DRIFTS reveals Na-induced red shifts of the formate ν(CH) band and changes in OCO vibrational splitting, consistent with weakening of the formate C–H bond and an altered binding geometry. CO 2 -TPD confirms a monotonic shift toward stronger basic sites with increasing Na concentrations. Under MSR conditions, Na selectively increases CO2 concentration at the expense of CO. At ~80% conversion and 325 °C, CO 2 selectivity increases from 12.0% (unpromoted) to 16.2, 21.0, and 26.5% for 0.5, 1.0, and 1.8% Na, respectively; at ~300 °C and ~66–69% conversion, CO 2 selectivity increases from 8.6% to 23.7% at 1.8% Na. Transient MSR experiments further show earlier and larger H 2 evolution upon Na addition, corroborating the promotion of the dehydrogenation/decarbonylation route to CO 2 + H 2 . We propose that Na increases basicity and modifies the Ru–support interface to favor formate dehydrogenation/decarboxylation, thereby increasing the H 2 yield and lowering CO formation. Ru’s higher-energy, less occupied d-band stabilizes CO and oxygenated intermediates more strongly in the reforming environment, making the CO-forming pathway more resistant to suppression than on Pt.

CO2 selectivity↗

DOE OSTI2020

Atomic Layer Deposition for Preparing Isolated Co Sites on SiO 2 for Ethane Dehydrogenation Catalysis

Unlike Co clusters, isolated Co atoms have been shown to be selective for catalytic dehydrogenation of ethane to ethylene; however, preparation of isolated Co sites requires special preparation procedures. Here, we demonstrate that Atomic Layer Deposition (ALD) of tris(2,2,6,6-tetramethyl-3,5-heptanedionato)cobalt(III) (Co(TMHD) 3 ) on silica and other supports is effective in producing these isolated species. Silica-supported catalysts prepared with one ALD cycle showed ethylene selectivities greater than 96% at 923 K and were stable when CO 2 was co-fed with the ethane. Co catalysts prepared by impregnation formed clusters that were significantly less active, selective, and stable. Rates and selectivities also decreased for catalysts with multiple ALD cycles. Isolated Co catalysts prepared on Al 2 O 3 and MgAl 2 O 4 showed reasonable selectivity for ethane dehydrogenation but were not as effective as their silica counterpart.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Machine learning deciphers CO 2 sequestration and subsurface flowpaths from stream chemistry

Endmember mixing analysis (EMMA) is often used by hydrogeochemists to interpret the sources of stream solutes, but variations in stream concentrations and discharges remain difficult to explain. We discovered that machine learning can be used to highlight patterns in stream chemistry that reveal information about sources of solutes and subsurface groundwater flowpaths. The investigation has implications, in turn, for the balance of CO 2 in the atmosphere. For example, CO 2 -driven weathering of silicate minerals removes carbon from the atmosphere over ~106-year timescales. Weathering of another common mineral, pyrite, releases sulfuric acid that in turn causes dissolution of carbonates. In that process, however, CO 2 is released instead of sequestered from the atmosphere. Thus, understanding long-term global CO 2 sequestration by weathering requires quantification of CO 2 - versus H 2 SO 4 -driven reactions. Most researchers estimate such weathering fluxes from stream chemistry, but interpreting the reactant minerals and acids dissolved in streams has been fraught with difficulty. We apply a machine-learning technique to EMMA in three watersheds to determine the extent of mineral dissolution by each acid, without pre-defining the endmembers. The results show that the watersheds continuously or intermittently sequester CO 2 , but the extent of CO 2 drawdown is diminished in areas heavily affected by acid rain. Prior to applying the new algorithm, CO 2 drawdown was overestimated. The new technique, which elucidates the importance of different subsurface flowpaths and long-timescale changes in the watersheds, should have utility as a new EMMA for investigating water resources worldwide.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1974

Electronic-to-vibrational energy transfer efficiency in the O/1 D/-N2 and O/1 D/-CO systems

With the aid of a molecular resonance fluorescence technique, which utilizes optical pumping from the v = 1 level of the ground state of CO by A 1 Pi-X 1 Sigma radiation, a study is made of the efficiency of E-V transfer from O(1 D) to CO. O(1 D) is generated at a known rate by O2 photodissociation at 1470 A in an intermittent mode, and the small modulation of the fluorescent signal associated with CO (v = 1) above the normal thermal background is interpreted in terms of E-V transfer efficiency. The CO (v = 1) lifetime in this system is determined mainly by resonance trapping of the IR fundamental band, and is found to be up to ten times longer than the natural radiative lifetime. For CO, (40 plus or minus 8)% of the O(1 D) energy is converted into vibrational energy. By observing the effect of N2 on the CO (v = 1) fluorescent intensity and lifetime, it is possible to obtain the E-V transfer efficiency for the system O(1 D)-N2 relative to that for O(1 D)-CO. The results indicate that the efficiency for N2 is (83 plus or minus 10)% of that for CO.

Slanger, T. G.↗