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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications

Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring. We have deployed strainmeters and then conducted injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters (30 to 40m depth) was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 n/d over a few days. The signal at two strainmeters at shallow depth were consistent, although the magnitude of the horizontal strains were different reflecting the different radial directions from the well. The signal at a deep strainmeter deployed at reservoir depth was much different, with tensile vertical strains and compressive horizontal strains. These data can be interpreted by inverting poroelastic forward models developed using numerical and analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. This model is fast and can be inverted to estimate reservoir stiffness and geometry. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. The proxy model is periodically updated and refined using the finite element model to ensure accuracy. This approach significantly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. We have shown that the strain tensor in the caprock is sensitive to pressure in the reservoir, boundaries in the reservoir, and pressure in the caprock caused by leaks. These results indicate that coupling strain tensor data with inversion has the potential to help evaluate reservoirs during initial characterization, and to monitor them during the CO2 injection and storage process.

Murdoch, Larry↗
DOE OSTI2022

Proxy-Based Bayesian Inversion Of Poroelastic Simulations To Interpret Strain Tensor Data Measured During Well Testing

The long runtimes of 3D poroelastic numerical simulators makes it impractical to interpret deformation datasets using many inversion schemes. Recent advances in instrumentation have made it possible to measure the strain tensor during well testing, but the lack of robust inversion methods is limiting the ability to interpret these data. We have developed an inversion workflow that reduces the number of computations required to complete a Bayesian inversion using DREAMzs. The workflow trains a KNN model using output from the poroelastic simulator, and then uses the KNN model as a proxy for the simulator during inversion. The workflow also includes a strategy for ensuring the results from the proxy model converge to the results from the simulator, ensuring the accuracy of the final results. An idealized example configured to represent a well test in a deep aquifer is used to verify that the workflow correctly identifies parameters and characterizes noise. Field data measured using strainmeters during an injection test at an oil reservoir in Oklahoma are used to evaluate performance with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), and the results are used to characterize posterior parameter distribution and evaluate the prediction uncertainty. This approach makes it feasible to invert strain data measured during well testing and this has the potential to improve the characterization of aquifers and reservoirs.

Roudini, Soheil↗
DOE OSTI2025

Interpretation of Ion Irradiation and Neutron Irradiation Damage in Additively Manufactured 316 Stainless Steel using Multiscale Modeling

The accelerated adoption of nuclear energy necessitates advanced manufacturing technologies, such as additive manufacturing, to meet heightened supply chain requirements and support innovative reactor technologies. Due to the unique microstructural characteristics of additively manufactured materials under distinct solidification conditions, comprehensive evaluation of their performance in reactor environments is essential. The Advanced Materials and Manufacturing Technologies program under the Department of Energy's Office of Nuclear Energy focuses on understanding the irradiation performance and damage evolution of laser powder bed fusion 316 stainless steel, with an emphasis on integrating ion and neutron irradiation data to accelerate the development and qualification of materials for advanced nuclear reactor applications. While ion irradiation is a cost- and time-effective method, modeling and simulation are required to interpret the data for the broader range of irradiation conditions encountered in advanced reactors. In fiscal year 2025, integrated multiscale modeling and simulations were conducted to assess irradiation damage in additively manufactured 316 stainless steel. Key outcomes include predictions of chromium enrichment at grain boundaries, nickel enrichment at dislocation cell walls and void surfaces, and heterogeneous void evolution under ion and neutron irradiation conditions. Cluster dynamics simulations revealed the coarsening of voids at high irradiation temperatures and the suppression of void growth by high network dislocation density, while also demonstrating significant growth and coarsening of voids and self-interstitial atom loops at low dose rates. Machine learning-accelerated atomistic simulations highlighted the impact of the local environment and chromium concentration on vacancy diffusivity, providing key insights on the influence of composition on void swelling and radiation-induced segregation. Additionally, molecular dynamics simulations demonstrated the presence of defect production bias and a significant effect of carbon content on defect cluster behavior. These combined efforts aim to predict the performance of additively manufactured materials under various reactor conditions, supporting their qualification for nuclear reactor applications by interpreting ion irradiation data. This report underscores the potential of integrated multiscale modeling to analyze ion irradiation data in the effort to accelerate the qualification of additively manufactured materials for nuclear reactor components.

316 stainless steel↗
DOE OSTI2025

Shallow cumulus entrainment: observational retrieval, physical interpretation, and climate impacts (Final grant report)

This document constitutes a final technical report for DE-SC0020083, a research grant awarded by the US Department of Energy Office of Science, to Prof. Daniel Kirshbaum at McGill University. The original research proposal, entitled "Shallow cumulus entrainment: observational retrieval, physical interpretation, and climate impacts", defined four scientific objectives that synthesized ARM observations with turbulence-permitting large-eddy simulations (LES) to quantify and understand the process of cumulus entrainment, whereby a cumulus cloud ingests surrounding air through its lateral edges. These objectives included developing observational climatologies of cumulus bulk entrainment rate at two ARM observatories, physical interpretation of these findings using LES, quantification of the impacts of subcloud circulations on entrainment, and the climate impacts of flow-dependent entrainment variations. In the six years that have elapsed since the grant was awarded (three funded years and three no-cost annual extensions), all four of the objectives were successfully addressed. Four personnel were trained (one B.Sc., one M.Sc. to completion, five years of Ph.D. training, and 2.5 years of postdoctoral training), eight peer-reviewed articles were published in high-impact journals, and 20 presentations were delivered (three invited).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Collaborative Research: Enabling multi-scale studies of magnetic reconnection with interpretable data-driven models

The development of accurate reduced descriptions and improved closures for magnetic reconnection is an important and a long‐standing challenge in plasma physics. The four‐fluid approach, and associated closures, that were investigated have the potential to improve the accuracy of plasma fluid models, capturing physical effects which would otherwise require a kinetic description. If successful, this approach could have an important impact for the modeling of laboratory and space plasmas. The major goals of this project were to develop new machine learning (ML) tools based on sparse and symbolic regression techniques, and to extract interpretable and generalizable reduced models (e.g., in the form of partial differential equations - PDEs) from data generated by first principles plasma simulations. Preserving interpretability of such data‐driven models is key to addressing the long‐standing theoretical and numerical challenges. Prior proof‐of‐principle studies have demonstrated the enormous potential of this approach, by recovering the well‐established hierarchy of plasma equations (from Vlasov to MHD) from data produced by particle‐in‐cell (PIC) simulations. Our goal in this project was to extend and apply these new tools to construct better kinetic closures for magnetic reconnection; to derive better models of particle injection and acceleration by this fundamental plasma process; and to use this understanding to accelerate the development of multi‐scale plasma algorithms. While our immediate focus was on the problem of magnetic reconnection, the tools that were will developed are general and applicable to other areas of plasma physics, and more broadly to many‐body phenomena. We anticipate that the development of these multi‐scale models will have a significant impact across different areas of plasma science, from fusion to space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Avenues for a number density interpretation of dihadron fragmentation functions

In this letter, we reassess the underlying physics of the number sum rule for dihadron fragmentation functions. We will argue that, currently, there are no settled constraints on what constitutes a valid number density interpretation for multihadron fragmentation functions. Imposing overly restrictive criteria might lead to misinterpretating the data. Most importantly, and on the basis of phenomenological analyses, the slightly varying definitions used in previous work are not excluded from possessing legitimate number density interpretations (up to the usual issues with ultraviolet divergences and renormalization), so long as they are paired with appropriate factorization theorems. We advocate for further theoretical analyses to be challenged with experimental data, available at JLab or at the future EIC.

First principle↗
DOE OSTI2019

Attosecond Streaking Time Delays: Finite-Range Interpretation and Applications

We review theoretical studies of the attosecond streaking time delay concept in photoionization via the investigation of the electron dynamics in the streaking field after the transition of the photoelectron into the continuum upon absorption of an extreme ultraviolet photon. Based on the results, a so-called finite range interpretation was introduced, which highlighted that the delay is accumulated until the streaking pulse ends and, hence, over a finite range of the potential of the parent ion. Following a discussion of the analysis leading to this interpretation, we summarize a few applications which provide insights into different aspects of the streaking time delay concept in photoionization. Besides a review of previously presented results, we give an analysis of the relevance of the first half-cycle of the streaking field and an outlook regarding the perspective of using the streaking method to resolve dynamical changes in the potential that the photoelectron explores during its propagation in the continuum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Interpreting Mobile and Handheld Air Sensor Readings in Relation to Air Quality Standards and Health Effect Reference Values: Tackling the Challenges

The US Environmental Protection Agency (EPA) and other federal agencies face a number of challenges in interpreting and reconciling short-duration (seconds to minutes) readings from mobile and handheld air sensors with the longer duration averages (hours to days) associated with the National Ambient Air Quality Standards (NAAQS) for the criteria pollutants-particulate matter (PM), ozone, carbon monoxide, lead, nitrogen oxides, and sulfur oxides. Similar issues are equally relevant to the hazardous air pollutants (HAPs) where chemical-specific health effect reference values are the best indicators of exposure limits; values which are often based on a lifetime of continuous exposure. A multi-agency, staff-level Air Sensors Health Group (ASHG) was convened in 2013. ASHG represents a multi-institutional collaboration of Federal agencies devoted to discovery and discussion of sensor technologies, interpretation of sensor data, defining the state of sensor-related science across each institution, and provides consultation on how sensors might effectively be used to meet a wide range of research and decision support needs. ASHG focuses on several fronts: improving the understanding of what hand-held sensor technologies may be able to deliver; communicating what hand-held sensor readings can provide to a number of audiences; the challenges of how to integrate data generated by multiple entities using new and unproven technologies; and defining best practices in communicating health-related messages to various audiences. This review summarizes the challenges, successes, and promising tools of those initial ASHG efforts and Federal agency progress on crafting similar products for use with other NAAQS pollutants and the HAPs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Caution Is Required in Interpretation of Mutations in the Voltage Sensing Domain of Voltage Gated Channels as Evidence for Gating Mechanisms

The gating mechanism of voltage sensitive ion channels is generally considered to be the motion of the S4 transmembrane segment of the voltage sensing domains (VSD). The primary supporting evidence came from R→C mutations on the S4 transmembrane segment of the VSD, followed by reaction with a methanethiosulfonate (MTS) reagent. The cys side chain is –SH (reactive form –S−); the arginine side chain is much larger, leaving space big enough to accommodate the MTS sulfonate head group. The cavity created by the mutation has space for up to seven more water molecules than were present in wild type, which could be displaced irreversibly by the MTS reagent. Our quantum calculations show there is major reorientation of three aromatic residues that face into the cavity in response to proton displacement within the VSD. Two phenylalanines reorient sufficiently to shield/unshield the cysteine from the intracellular and extracellular ends, depending on the proton positions, and a tyrosine forms a hydrogen bond to the cysteine sulfur with its side chain –OH. These could produce the results of the experiments that have been interpreted as evidence for physical motion of the S4 segment, without physical motion of the S4 backbone. The computations strongly suggest that the interpretation of cysteine substitution reaction experiments be re-examined in the light of these considerations.

Biochemistry & Molecular Biology↗
DOE OSTI2016

Structural Interpretation of the Large Slowdown of Water Dynamics at Stacked Phospholipid Membranes for Decreasing Hydration Level: All-Atom Molecular Dynamics

Hydration water determines the stability and function of phospholipid membranes as well as the interaction of membranes with other molecules. Experiments and simulations have shown that water dynamics slows down dramatically as the hydration decreases, suggesting that the interfacial water that dominates the average dynamics at low hydration is slower than water away from the membrane. Here, based on all-atom molecular dynamics simulations, we provide an interpretation of the slowdown of interfacial water in terms of the structure and dynamics of water–water and water–lipid hydrogen bonds (HBs). We calculate the rotational and translational slowdown of the dynamics of water confined in stacked phospholipid membranes at different levels of hydration, from completely hydrated to poorly hydrated membranes. For all hydrations, we analyze the distribution of HBs and find that water–lipids HBs last longer than water–water HBs and that at low hydration most of the water is in the interior of the membrane. We also show that water–water HBs become more persistent as the hydration is lowered. We attribute this effect (i) to HBs between water molecules that form, in turn, persistent HBs with lipids; (ii) to the hindering of the H-bonding switching between water molecules due to the lower water density at the interface; and (iii) to the higher probability of water–lipid HBs as the hydration decreases. Lastly, our interpretation of the large dynamic slowdown in water under dehydration is potentially relevant in understanding membrane biophysics at different hydration levels.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Prediction of Long-Term Geochemical Change in Bentonite Based on the Interpretative THMC Model of the FEBEX In Situ Test

Since nuclear energy is crucial in the decarbonization of the energy supply, one hurdle to remove is the handling of high-level radioactive waste (HLW). Disposal of HLW in a deep geological repository has long been deemed a viable permanent option. In the design of a deep geological repository, compacted bentonite is the most commonly proposed buffer material. Predicting the long-term chemical evolution in bentonite, which is important for the safety assessment of a repository, has been challenging because of the complex coupled processes. Models for large-scale tests and predictions based on such models have been some of the best practices for such purposes. An 18-year-long in situ test with two dismantling events provided a unique set of chemical data that allowed for studying chemical changes in bentonite. In this paper, we first developed coupled thermal, hydrological, mechanical, and chemical (THMC) models to interpret the geochemical data collected in the in situ test and then extended the THMC model to 200 years to make long-term prediction of the geochemical evolution of bentonite. The interpretive coupled THMC model shows that the geochemical profiles were strongly affected by THM processes such as evaporation/condensation, porosity change caused by swelling, permeability change, and the shape of concentration profiles for major cations were largely controlled by transport processes, but concentration levels were regulated by chemical reactions, and the profiles of some species such as pH, bicarbonate, and sulfate were dominated by these reactions. The long-term THMC model showed that heating prolongs the time that bentonite becomes fully saturated in the area close to the heater/canister; however, once the bentonite becomes fully saturated, high concentrations of ions in bentonite near the heater, which was observed in the field test, will disappear; illitization continues for 50 years but will not proceed further.

Zheng, Liange↗
DOE OSTI2023

The Structural Characterisation and DFT-Aided Interpretation of Vibrational Spectra for Cyclo(l-Cys-d-Cys) Cyclic Dipeptide in a Solid State

Cyclic dipeptides with two intramolecular peptide bonds forming a six-membered 2,5-diketopiperazine ring are gaining significant attention due to their biological and chemical properties. Small changes in the local geometry of such molecules (from cis to trans) can lead to significant structural differences. This work presents the results of a study of cyclo(l-Cys-d-Cys), a dipeptide comprising two cysteine molecules in opposite chiral configurations, with the functional groups situated at both sides of the diketopiperazine ring. X-ray diffraction (XRD) experiment revealed that the molecule crystallises in the $P$-1 space group, which includes the centre of inversion. The IR and Raman vibrational spectra of the molecule were acquired and interpreted in terms of the potential energy distribution (PED) according to the results of density functional theory (DFT) calculations. The DFT-assisted analysis of energy frameworks for the hydrogen bond network within molecular crystals was performed to support the interpretation of X-ray structural data. The optimisation of the computational model based on three-molecule geometry sections from the crystallographic structure, selected to appropriately reflect the intermolecular interactions responsible for the formation of 1D molecular tapes in cyclo(l-Cys-d-Cys) crystal, allowed for better correspondence between theoretical and experimental vibrational spectra. This work can be considered the first complete structural characterisation of cyclo(l-Cys-d-Cys), complemented via vibrational spectroscopy results with full band assignment aided with the use of the DFT method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

3FGL demographics outside the galactic plane using supervised machine learning: pulsar and dark matter subhalo interpretations

Nearly one-third of the sources listed in the Third Fermi Large Area Telescope (LAT) catalog (3FGL) remain unassociated. It is possible that predicted and even unanticipated gamma-ray source classes are present in these data waiting to be discovered. Taking advantage of the excellent spectral capabilities achieved by the Fermi LAT, we use machine-learning classifiers (Random Forest and XGBoost) to pinpoint potentially novel source classes in the unassociated 3FGL sample outside the Galactic plane. Here we report a total of 34 high-confidence Galactic candidates at |b|⩾5{sup ∘}. The currently favored standard astrophysical interpretations for these objects are pulsars or low-luminosity globular clusters hosting millisecond pulsars (MSPs). Yet these objects could also be interpreted as dark matter annihilation taking place in ultra-faint dwarf galaxies or dark matter subhalos. Unfortunately, Fermi LAT spectra are not sufficient to break degeneracies between the different scenarios. Careful visual inspection of archival optical images reveals no obvious evidence for low-luminosity globular clusters or ultra-faint dwarf galaxies inside the 95% error ellipses. If these are pulsars, this would bring the total number of MSPs at |b|⩾5{sup ∘} to 106, down to an energy flux ≈4.0 × 10{sup −12} erg cm{sup −2} s{sup −1} between 100 MeV and 100 GeV. We find this number to be in excellent agreement with predictions from a new population synthesis of MSPs that predicts 100–126 high-latitude 3FGL MSPs depending on the choice of high-energy emission model. If, however, these are dark matter substructures, we can place upper limits on the number of Galactic subhalos surviving today and on dark matter annihilation cross sections. These limits are beginning to approach the canonical thermal relic cross section for dark matter particle masses below ∼100 GeV in the bottom quark (b b-bar ) annihilation channel.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The impact of non-uniform thermal structure on the interpretation of exoplanet emission spectra

The determination of atmospheric structure and molecular abundances of planetary atmospheres via spectroscopy involves direct comparisons between models and data. While varying in sophistication, most model spectra comparisons fundamentally assume one-dimensional (1D) model physics. However, knowledge from general circulation models and of solar system planets suggests that planetary atmospheres are inherently three-dimensional in their structure and composition. We explore the potential biases resulting from standard “1D” assumptions within a Bayesian atmospheric retrieval framework. Specifically, we show how the assumption of a single 1D thermal profile can bias our interpretation of the thermal emission spectrum of a hot Jupiter atmosphere that is composed of two thermal profiles. We retrieve spectra of unresolved model planets as observed with a combination of the Hubble Space Telescope Wide Field Camera 3 (WFC3)+Spitzer Infrared Array Camera (IRAC) as well as the James Webb Space Telescope (JWST) under varying differences in the two thermal profiles. For WFC3+IRAC, there is a significantly biased estimate of CH{sub 4} abundance using a 1D model when the contrast is 80%. For JWST, two thermal profiles are required to adequately interpret the data and estimate the abundances when contrast is greater than 40%. We also apply this preliminary concept to the recent WFC3+IRAC phase curve data of the hot Jupiter WASP-43b. We see similar behavior as present in our simulated data: while the H{sub 2}O abundance determination is robust, CH{sub 4} is artificially well-constrained to incorrect values under the 1D assumption. Our work demonstrates the need to evaluate model assumptions in order to extract meaningful constraints from atmospheric spectra and motivates exploration of optimal observational setups.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Transient Cosmic-ray Events beyond the Heliopause: Interpreting Voyager-1 Observations

In 2013 March and 2014 May, Voyager-1 ( V1 ) experienced small but significant increases in the flux of galactic cosmic rays (GCRs) in the hundred MeV/n range. Additionally, V1 also saw episodic depletion of GCR flux around perpendicular pitch angles. We discuss the pitch-angle distribution and the time profiles of these events. In a previous paper, we interpreted the 2013 “bump” as the GCRs remotely sensing a shock that reached the magnetic field line passing through V1 : particles gained energy as they were reflected on the approaching region of the stronger magnetic field of the disturbance. Here, we point out that energy gain is not restricted to reflected particles—GCRs passing through the disturbance also gain energy. The effect should be present in a broad range of pitch angles with the maximum increase of GCR intensity predicted to occur at the critical reflection angle. In this paper, the shock is not step-like, but a gradual increase of the magnetic field strength, B , taking a few days, in agreement with V1 measurements. This smoothens the profile of the predicted bump in the GCR flux. We also address the linear episodic decreases seen around perpendicular pitch angles. These events are interpreted in terms of adiabatic cooling behind the shock due to the slow weakening of B . We present simple numerical model calculations and find that a gradual shock followed by a slow decrease of B , as observed, may account for both the episodic increases and the anisotropic depletion of GCR fluxes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Effects of Subhalos on Interpreting Highly Magnified Sources Near Lensing Caustics

Large magnification factors near gravitational lensing caustics of galaxy-cluster lenses allow the study of individual stars or compact stellar associations at cosmological distances. We study how the presence of sub-galactic subhalos, an inevitable consequence of cold dark matter, can alter the property of caustics and hence change the interpretation of highly magnified sources that lie atop them. First, we consider a galaxy-cluster halo populated with subhalos sampled from a realistic subhalo mass function calibrated to N-body simulations. Then, we compare a semianalytical approximation and an adaptive ray-shooting method that we employ to quantify the property of the caustics. As a case study, we investigate Earendel, a z = 6.2 candidate of magnified single- or multiple-star system with a lone lensed image atop the critical curve in the Sunrise Arc. We find that the source size constraint (≲0.3 pc) previously derived from macrolens models should be relaxed by a factor of a few to 10 when subhalos are accounted for, therefore allowing the possibility of a compact star cluster. The subhalos could introduce an astrometric perturbation that is ≲0$^{"}_{.}$5, which does not contradict observation. These conclusions are largely robust to changes in the subhalo population. Subhalos therefore should be seriously accounted for when interpreting the astrophysical nature of similar highly magnified sources uncovered in recent high-z observations.

Caustic curve↗
DOE OSTI2016

Interpreting space-based trends in carbon monoxide with multiple models

Here, we use a series of chemical transport model and chemistry climate model simulations to investigate the observed negative trends in MOPITT CO over several regions of the world, and to examine the consistency of time-dependent emission inventories with observations. We also found that simulations driven by the MACCity inventory, used for the Chemistry Climate Modeling Initiative (CCMI), reproduce the negative trends in the CO column observed by MOPITT for 2000–2010 over the eastern United States and Europe. However, the simulations have positive trends over eastern China, in contrast to the negative trends observed by MOPITT. The model bias in CO, after applying MOPITT averaging kernels, contributes to the model–observation discrepancy in the trend over eastern China. This demonstrates that biases in a model's average concentrations can influence the interpretation of the temporal trend compared to satellite observations. The total ozone column plays a role in determining the simulated tropospheric CO trends. A large positive anomaly in the simulated total ozone column in 2010 leads to a negative anomaly in OH and hence a positive anomaly in CO, contributing to the positive trend in simulated CO. Our results demonstrate that accurately simulating variability in the ozone column is important for simulating and interpreting trends in CO.

54 ENVIRONMENTAL SCIENCES↗