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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Ubiquity and functional uniformity in CO2 concentrating mechanisms in multiple phyla of Bacteria is suggested by a diversity and prevalence of genes encoding candidate dissolved inorganic carbon transporters

ABSTRACT Autotrophic microorganisms catalyze the entry of dissolved inorganic carbon (DIC; = CO2 + HCO3− + CO32−) into the biological component of the global carbon cycle, despite dramatic differences in DIC abundance and composition in their sometimes extreme environments. “Cyanobacteria” are known to have CO2 concentrating mechanisms (CCMs) to facilitate growth under low CO2 conditions. These CCMs consist of carboxysomes, containing enzymes ribulose 1,5-bisphosphate oxygenase and carbonic anhydrase, partnered to DIC transporters. CCMs and their DIC transporters have been studied in a handful of other prokaryotes, but it was not known how common CCMs were beyond “Cyanobacteria”. Since it had previously been noted that genes encoding potential transporters were found neighboring carboxysome loci, α-carboxysome loci were gathered from bacterial genomes, and potential transporter genes neighboring these loci are described here. Members of transporter families whose members all transport DIC (CHC, MDT and Sbt) were common in these neighborhoods, as were members of the SulP transporter family, many of which transport DIC. 109 of 115 taxa with carboxysome loci have some form of DIC transporter encoded in their genomes, suggesting that CCMs consisting of carboxysomes and DIC transporters are widespread not only among “Cyanobacteria”, but also among members of “Proteobacteria” and “Actinobacteria”.

Scott, Kathleen M.↗
NASA NTRS2016

Comparing GOSAT Observations of Localized CO2 Enhancements by Large Emitters with Inventory-Based Estimates

We employed an atmospheric transport model to attribute column-averaged CO2 mixing ratios (XCO2) observed by Greenhouse gases Observing SATellite (GOSAT) to emissions due to large sources such as megacities and power plants. XCO2 enhancements estimated from observations were compared to model simulations implemented at the spatial resolution of the satellite observation footprint (0.1deg × 0.1deg). We found that the simulated XCO2 enhancements agree with the observed over several continental regions across the globe, for example, for North America with an observation to simulation ratio of 1.05 +/- 0.38 (p<0.1), but with a larger ratio over East Asia (1.22 +/- 0.32; p<0.05). The obtained observation-model discrepancy (22%) for East Asia is comparable to the uncertainties in Chinese emission inventories (approx.15%) suggested by recent reports. Our results suggest that by increasing the number of observations around emission sources, satellite instruments like GOSAT can provide a tool for detecting biases in reported emission inventories.

CO2↗
NASA NTRS2019

Investigating Sources of Variability and Error in Simulations of Carbon Dioxide in an Urban Region

Greenhouse gas (GHG) emissions estimation methods that use atmospheric trace gas observations, including inverse modeling techniques, perform better when carbon dioxide (CO2) fluxes are more accurately transported and dispersed in the atmosphere by a numerical model. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric CO2 from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations).

CO2↗
DOE OSTI2024

Application of Modified Meshgraphnets for Subsurface Prediction during CO2 Sequestration

In the face of the increasingly dire consequences of anthropogenic climate change, capturing and storing carbon dioxide is paramount. However, several impediments exist to the safe and effective subsurface storage of CO2, such as cost of transport, identification of suitable sites for subsurface storage, and assessment of long-term risk from storage in subsurface aquifers. Accurate subsurface modeling is necessary to ensure that CO2 storage is both safe and effective. Still, such modeling has traditionally required either substantial time and computational power (numerical simulation) or a substantial amount of pre-existing data for training (machine learning models). Additionally, these models lack flexibility in dealing with both changes in discretization of the input data and generalizability beyond the data on which they are trained. In order to address these issues, this research applies graph neural networks (GNNs) to predict subsurface saturation and pressure during CO₂ injection in a model of the Illinois Basin-Decatur Project (IBDP). GNNs provide a flexible, intuitive method for representing and manipulating complex unstructured data, which is often found in many practical domain problems such as fluid flow and subsurface characterization. These unstructured grids are easily represented in GNNs by representing spatially-localized features such as permeability, porosity, saturation, and pressure as nodes in a graph and relationships between these properties as edges connecting these nodes. This research applies a specific GNN model called MeshGraphNets (MGN) to model the change in CO2 saturation and pressure over a 50-month time period (36 months of injection, 14 months post-injection). The MGN model leverages a message passing process that allows the network to learn both the spatial and temporal dynamics of this system simultaneously. Additionally, training on a limited dataset (64 realizations, 20 time points each) resulted in a high degree of accuracy in saturation prediction both within the same timeframe as the training (20 months, 0.039 average RMSE) and when projecting out to the end of injection (36 months, 0.053 average RMSE). Temporal predictions such as those generated by MGNs and other similar models are prone to accumulated error over time; in order to address this, a multi-step rollout (MSR) training process was applied to calculate training loss. This method mimics the forward prediction during inference by “rolling out” multiple time points in a single training step using the previous prediction as input to the MGN model. By calculating the loss several time steps forward from the current prediction, the model is forced to find a more stable state over time. Application of MSR to the MGN model resulted in an average 15% reduction in inference error over time during forward prediction. This study showcases the immense potential of GNNs as a game-changing methodology for predicting pressure and saturation evolution in CCS projects, ultimately paving the way for more sustainable and effective carbon storage solutions. Presentation prepared for the 2024 AiChE Annual Meeting, October 27 to November 1 2024, San Diego, CA.

Holcomb, Paul↗
NASA NTRS2019

Is There an Optimal CO2 Partial Column for Flux Inversions?

The fidelity of flux estimates from an atmospheric inversion depends on the ability of atmospheric transport models to simulate the measured quantity. For species such as CO2, with surface fluxes and a large network of surface measurements, this means correctly simulating the dynamics of the planetary boundary layer (PBL), which is one of the most uncertain aspects of atmospheric transport modeling. In contrast, the simulated total column average mole fraction of CO2 (XCO2) is largely insensitive to simulated PBL dynamics. Therefore, measurements of XCO2 provided by current and future short wave infrared (SWIR) greenhouse gas (GHG) satellites such as GOSAT and the OCO family would seem to be more appropriate to flux inversions, as far as minimizing transport model errors (the "noise") is concerned. Unfortunately, the flux-induced variation of CO2 (the "signal") is the largest within the PBL and smallest in XCO2. Therefore, assimilating XCO2 as opposed to PBL CO2 need not give us the strongest "signal to noise" in flux inversions. Recent work on GOSAT and OCO2 retrievals suggest that SWIR satellite spectra may be used to estimate a lower partial column CO2, which could be assimilated in a flux inversion, instead of XCO2.Here we report on a study to assess whether there is an optimal partial column average CO2, intermediate between PBL CO2 and XCO2, whose assimilation might yield the best signal to noise in flux inversions, where (as before) "signal" is the flux-induced variation and "noise" is the error in transport modeling. We simulate atmospheric CO2 with five different global transport models and a common surface CO2 flux over ten years. We consider the spread across the five models to be a proxy for transport model error (the "noise"), and the common variation of CO2 in all five models to be a proxy for the "signal". We compare these signals and noises at different spatiotemporal scales for different partial column specifications to investigate whether there exists an optimal partial column that has large surface flux-driven variations and yet is relatively insensitive to errors in transport models. Finally, we comment on the feasibility of estimating such a partial column from current and future SWIR GHG satellites in the light of recent work on vertically resolved CO2 from current SWIR GHG satellites.

Basu, Sourish↗
NASA NTRS1982

Heat transport in porous cometary nuclei

Heat transport in cometary nuclei is important because it leads to the formation of larger tails and comae after perihelia than before, to early outbursts caused by phase transitions, and to fragmentation. The role of gases in pores in icy (H2O and H2O + CO2) nuclei in the heat transport has been investigated in the viscous and Knudsen diffusion regions. It appears that in pure H2O-ices the heat flow is affected by the presence of pores but is affected only very close to the perihelion by water vapor contained in them. On the other hand, the presence of CO2 vapor in the pores significantly increases the heat flow in mixed nuclei at temperatures above 140 - 150 K. Thus for heliocentric distances between 3 and 5 AU, the above mentioned phenomena should be considerably enhanced in proportion to the admixture of CO2 ices. The overlap and channel formation by pores in nuclei with high porosities is discussed.

Smoluchowski, R.↗
NASA NTRS2019

Prior biosphere model impact on global terrestrial CO2 fluxes estimated from OCO-2 retrievals

This study assesses the impact of different state of the art global biospheric CO2 flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC/yr). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.

Sajeev Philip↗
NASA NTRS2000

Land Use Effects on Atmospheric C-13 Imply a Sizable Terrestrial CO2 Sink in Tropical Latitudes

Records of atmospheric CO2 and 13-CO2, can be used to distinguish terrestrial vs. oceanic exchanges of CO2 with the atmosphere. However, this approach has proven difficult in the tropics, partly due to extensive land conversion from C-3 to C-4 vegetation. We estimated the effects of such conversion on biosphere-atmosphere C-13 exchange for 1991 through 1999, and then explored how this 'land-use disequilibrium' altered the partitioning of net atmospheric CO2 exchanges between ocean and land using NOAA-CMDL data and a 2D, zonally averaged atmospheric transport model. Our results show sizable CO2 uptake in C-3-dominated tropical regions in seven of the nine years; 1997 and 1998, which included a strong ENSO event, are near neutral. Since these fluxes include any deforestation source, our findings imply either that such sources are smaller than previously estimated, and/or the existence of a large terrestrial CO2 sink in equatorial latitudes.

Townsend, Alan R.↗
DOE OSTI2025

MRCI Task 4: Evaluating Regional Infrastructure Technical Summary Report

The infrastructure required to enable carbon capture and sequestration (CCS) goes beyond the equipment and materials needed to capture, transport, and store carbon dioxide (CO2) but includes people and policy that make CCS feasible. The Infrastructure Assessment task of the Midwest Regional Carbon Initiative (MRCI) seeks to determine the infrastructure requirements for the MRCI study area through four activities: • Infrastructure Readiness: Strategizing the buildout of capture, transport, and storage infrastructure in the Midwest, Northeast, and Mid-Atlantic Offshore. • Site Readiness: Determining the CCS readiness of each state in the MRCI region in the categories of subsurface readiness; infrastructure readiness; regulations, permitting, and incentives; and social dynamics. • Jobs, Economics, and Social Characteristics: Quantifying the economic potential, job opportunities, and training opportunities for CCS as well as the social characteristics of the region with a focus on energy and environmental justice (EJ) issues. • Policy and Regulations: Providing an updated accounting of the CCS-relevant policy and regulations in the MRCI region.

CCUS,Carbon storage,Midwest,Midwest Regional Carbo↗
DOE OSTI2025

Modeling commercial-scale CO 2 storage in the gas hydrate stability zone with PFLOTRAN v6.0

Abstract. Safe and secure carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most dangerous effects of climate change. In the last decade, there has been a significant increase in activity associated with reservoir characterization and site selection for large-scale CO2 storage projects across the globe. These prospective storage sites tend to be selected for their optimal structural, petrophysical, and geochemical trapping potential. However, it has also been suggested that storing CO2 in reservoirs within the CO2 hydrate stability zone (GHSZ), characterized by high pressures and low temperatures (e.g., Arctic or marine environments), could provide a natural thermodynamic barrier to gas leakage. Evaluating the prospect of commercial-scale, long-term storage of CO2 in the GHSZ requires reservoir-scale modeling capabilities designed to account for the unique physics and thermodynamics associated with these systems. We have developed the HYDRATE flow mode and the accompanying fully implicit parallel well model in the massively parallel subsurface flow and reactive transport simulator PFLOTRAN to model CO2 injection into the marine GHSZ. We have applied these capabilities to a set of CO2 injection scenarios designed to reveal the challenges and opportunities for commercial-scale CO2 storage in the GHSZ.

carbon storage↗
NASA NTRS2004

Carbon Dioxide Dispersion in the Combustion Integrated Rack Simulated Numerically

When discharged into an International Space Station (ISS) payload rack, a carbon dioxide (CO2) portable fire extinguisher (PFE) must extinguish a fire by decreasing the oxygen in the rack by 50 percent within 60 sec. The length of time needed for this oxygen reduction throughout the rack and the length of time that the CO2 concentration remains high enough to prevent the fire from reigniting is important when determining the effectiveness of the response and postfire procedures. Furthermore, in the absence of gravity, the local flow velocity can make the difference between a fire that spreads rapidly and one that self-extinguishes after ignition. A numerical simulation of the discharge of CO2 from PFE into the Combustion Integrated Rack (CIR) in microgravity was performed to obtain the local velocity and CO2 concentration. The complicated flow field around the PFE nozzle exits was modeled by sources of equivalent mass and momentum flux at a location downstream of the nozzle. The time for the concentration of CO2 to reach a level that would extinguish a fire anywhere in the rack was determined using the Fire Dynamics Simulator (FDS), a computational fluid dynamics code developed by the National Institute of Standards and Technology specifically to evaluate the development of a fire and smoke transport. The simulation shows that CO2, as well as any smoke and combustion gases produced by a fire, would be discharged into the ISS cabin through the resource utility panel at the bottom of the rack. These simulations will be validated by comparing the results with velocity and CO2 concentration measurements obtained during the fire suppression system verification tests conducted on the CIR in March 2003. Once these numerical simulations are validated, portions of the ISS labs and living areas will be modeled to determine the local flow conditions before, during, and after a fire event. These simulations can yield specific information about how long it takes for smoke and combustion gases produced by a fire to reach a detector location, how large the fire would be when the detector alarms, and the behavior of the fire until it has been extinguished. This new capability could then be used to optimize the location of fire detectors and fire-suppression ports as well as to evaluate the effectiveness of fire suppressants and response strategies. Numerical data collected from these simulations could also be used to develop a virtual reality fire event for crew training and fire safety awareness. This work is funded by NASA's Bioastronautics Initiative, which has the objective of ensuring and enhancing the health, safety, and performance of humans in space. As part of this initiative, the Microgravity Combustion Science Branch at the NASA Glenn Research Center is conducting spacecraft fire safety research to significantly improve fire safety on inhabited spacecraft.

Wu, Ming-Shin↗
NASA NTRS2012

Global CO2 Distributions over Land from the Greenhouse Gases Observing Satellite (GOSAT)

January 2009 saw the successful launch of the first space-based mission specifically designed for measuring greenhouse gases, the Japanese Greenhouse gases Observing SATellite (GOSAT). We present global land maps (Level 3 data) of column-averaged CO2 concentrations (X(sub CO2)) derived using observations from the GOSAT ACOS retrieval algorithm, for July through December 2009. The applied geostatistical mapping approach makes it possible to generate maps at high spatial and temporal resolutions that include uncertainty measures and that are derived directly from the Level 2 observations, without invoking an atmospheric transport model or estimates of CO2 uptake and emissions. As such, they are particularly well suited for comparison studies. Results show that the Level 3 maps for July to December 2009 on a lO x 1.250 grid, at six-day resolution capture much of the synoptic scale and regional variability of X(sub CO2), in addition to its overall seasonality. The uncertainty estimates, which reflect local data coverage, X(sub CO2) variability, and retrieval errors, indicate that the Southern latitudes are relatively well-constrained, while the Sahara Desert and the high Northern latitudes are weakly-constrained. A probabilistic comparison to the PCTM/GEOS-5/CASA-GFED model reveals that the most statistically significant discrepancies occur in South America in July and August, and central Asia in September to December. While still preliminary, these results illustrate the usefulness of a high spatiotemporal resolution, data-driven Level 3 data product for direct interpretation and comparison of satellite observations of highly dynamic parameters such as atmospheric CO2.

Hammerling, Dorit M.↗
DOE OSTI2020

Foot-scale Evaluation of CO2-Responsive Polymer and CO2 Binary Fluid as an Alternative Fracturing Fluid for Enhanced Geothermal Systems

A foot-scale high-temperature true-triaxial fracturing apparatus was used to conduct hydraulic fracture tests on rock samples. The fracturing tests used different fluids including water, CO2, CO2 with water, and CO2 with a 1% polyallylamine (PAA)/water solution. The tests were conducted with both constant pressure injection and constant flow rate injection modes. CO2-based fracturing fluids were found to produce higher breakdown pressures, high transient flow rates, and produce higher-conductivity fractures as compared to water-based fracturing fluids. Additionally, faster pressurization rates with CO2-based fracturing fluids (obtained when fracturing at constant flow rate mode) are found to be associated with higher fracture conductivities. When fracturing with CO2-based fluids in the presence of a PAA aqueous solution, for example if the rock is saturated with 1wt% PAA in water, the volume expansion caused by CO2-induced crosslinking of PAA leads to a faster pressure increase due to the associated volume expansion and increase in viscosity. It was also found that CO2 as a fracturing fluid injected in hot dry rock (HDR) attain the highest fracture conductivity only when injected at very high flow rates, followed very closely by the CO2/PAA fracturing fluid system that generates fractures with, on average, similarly high conductivity values though independently of injection flow rate and using 1/6 of the mass of CO2 as compared to CO2 in HDR. Breakdown pressures were also similar for CO2 stimulation in HDR and CO2/PAA fluid system under identical injection flow rates. Finally, the well-known low viscosity of CO2 phase prevents the efficient transport of proppants while the reacted CO2/PAA fluid system is known to form a high viscosity binary fracturing fluid system with the potential to carry proppant in addition of being a fine fracturing fluid.

Enhanced Geothermal Systems, polyallylamine, Co2-r↗
DOE OSTI2020

W.A. Parish Post-Combustion CO 2 Capture and Sequestration Demonstration Project (Final Technical Report)

The Petra Nova Project (Project) is a commercial scale post-combustion carbon capture project developed by a joint venture between NRG Energy, Inc. (NRG) and JX Nippon Oil Exploration (EOR) Limited (JX). The Project is designed to separate and capture carbon dioxide (CO2) from an existing coal-fired unit’s flue gas slipstream at NRG’s W.A. Parish Electric Generating Station (WAP) located southwest of Houston, Texas. The captured CO2 is dried, compressed, and transported via an 81-mile pipeline to the West Ranch oilfield (West Ranch) in Jackson County, Texas, where it is injected to boost oil production. The Project, which is partially funded by a grant (Grant) from the United States (U.S.) Department of Energy (DOE) under the Clean Coal Power Initiative (CCPI) Round 3, uses the Kansai Mitsubishi Carbon Dioxide Recovery advanced amine-based CO 2 absorption technology (KM-CDR Process®), which was jointly developed by Mitsubishi Heavy Industries, Ltd. (MHI) and the Kansai Electric Power Co. Inc., to treat and capture at least ninety percent (90%) of the CO 2 from a 240-megawatt equivalent (MWe) flue gas slipstream off of Unit 8 at WAP. When operating at full capacity, the Project captures approximately 5,200 short tons of CO 2 per day, which would otherwise be emitted into the atmosphere, representing the largest commercial scale deployment of post-combustion CO2 capture technology at a coal power plant to date. Under the Grant, the Project was managed in 3 phases: (1) Phase 1: Project Definition / Front End Engineering Design (FEED) (2) Phase 2: Detailed Engineering, Procurement & Construction (3) Phase 3: Demonstration and Monitoring. On December 29, 2016, commercial operation of the Project was achieved, ending Phase 2 and starting Phase 3, a 3-year demonstration period running from January 1, 2017 through December 31, 2019. The key objectives of Phase 3 were to (a) demonstrate the specific advanced technologies constructed during Phase 2 and (b) monitor the injected CO 2 at West Ranch to demonstrate technologies and protocols for monitoring, verification, and accounting (MVA). As of the end of Phase 3, Petra Nova captured 3,904,978 short tons of CO 2 (3,542,537 metric tons) that was transported to West Ranch. To support the DOE obligation to monitor, verify, and account for the sequestered CO 2 at West Ranch, Petra Nova contracted with the Bureau of Economic Geology (in the Jackson School of Geosciences at The University of Texas at Austin) to (a) design a monitoring program, (b) draft an MVA Plan for DOE review and approval, and (c) working with Petra Nova and the operator of West Ranch to manage and report on the MVA activity. This report discussed the technical aspects of the project during each of the 3 phases of the project as identified above.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2003

Cost Effective Measures to Reduce CO2 Emissions in the Air Freight Sector

This paper presents cost effective measures to reduce CO2 emissions in the air freight sector. One door-to-door transport chain is studied in detail from a Scandinavian city to a city in southern Europe. The transport chain was selected by a group of representatives from the air freight sector in order to encompass general characteristics within the sector. Three different ways of shipping air cargo are studied, i.e., by air freighter, as belly freight (in passenger aircrafts) and trucking. CO2 emissions are calculated for each part of the transport chain and its relative importance towards the total amount CO2 emitted during the whole transport chain is shown. It is confirmed that the most CO2 emitting part of the transport chain is the actual flight and that it is in the take-off and climbing phases that most fuel are burned. It is also known that the technical development of aircraft implies a reduction in fuel consumption for each new generation of aircraft. Thus, the aircraft manufacturers have an important role in this development. Having confirmed these observations, this paper focuses on other factors that significantly affects the fuel consumption. Analyzed factors are, e.g., optimization of speed and altitude, traffic management, congestion on and around the airfields, tankering, "latest acceptance time" for goods and improving the load factor. The different factors relative contribution to the total emission levels for the transport chain has been estimated.

Blinge, Magnus↗
DOE OSTI2025

Real-Time Partitioning of Diurnal Stem CO 2 Efflux into Local Stem Respiration and Xylem Transport Processes

The apparent respiratory quotient (ARQ) of tree stems, defined as the ratio of net stem CO 2 efflux (E S_CO2 ) to net stem O 2 influx (E S_O2 ), offers insights into the balance between local respiratory CO 2 production and CO 2 transported via the xylem. Traditional static chamber methods for measuring ARQ can introduce artifacts and obscure natural diurnal variations. Here, we employed an open flow-through stem chamber with ambient air coupled with cavity ring-down spectrometry, which uses the molecular properties of CO 2 and O 2 molecules to continuously measure E S_CO2 , E S_O2 , and ARQ, at the base of a California cherry tree (Prunus ilicifolia) during the 2024 growing season. Measurements across three stem chambers over 3–11-day periods revealed strong correlations between E S_CO2 and E S_O2 and mean ARQ values ranging from 1.3 to 2.9, far exceeding previous reports. Two distinct diurnal ARQ patterns were observed: daytime suppression with nighttime recovery, and a morning peak followed by gradual decline. Partitioning E S_CO2 into local respiration and xylem-transported CO 2 indicated that the latter can dominate when ARQ exceeds 2.0. Furthermore, transported CO 2 exhibited a higher temperature sensitivity than local respiration, with both processes showing declining temperature sensitivity above 20 °C. These findings underscore the need to differentiate stem CO 2 flux components to improve our understanding of whole-tree carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Three dimensional global modeling of atmospheric CO2

The initial attempts to model the atmospheric CO2 distribution, including couplings to the ocean and biosphere as sources and sinks of atmospheric CO2, encourage the notion that this approach will lead to useful quantitative constraints on CO2 fluxes. Realization of this objective will require: (1) continued improvement in the realism of the global transport modeling; (2) extended timeline of atmospheric CO2 monitoring, which improved precision and improved definition of the uncertainties in the measured CO2 amounts; and (3) given an accurate knowledge of model capabilities and limitations and given a good understanding of CO2 observations and their limitations, there is a need for good ideas concerning what quantitative information on the carbon cycle can be inferred from global modeling.

Hanse, J.↗