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DOE OSTI2022

Protoplast fusion in Bacillus species produces frequent, unbiased, genome-wide homologous recombination

Abstract In eukaryotes, fine-scale maps of meiotic recombination events have greatly advanced our understanding of the factors that affect genomic variation patterns and evolution of traits. However, in bacteria that lack natural systems for sexual reproduction, unbiased characterization of recombination landscapes has remained challenging due to variable rates of genetic exchange and influence of natural selection. Here, to overcome these limitations and to gain a genome-wide view on recombination, we crossed Bacillus strains with different genetic distances using protoplast fusion. The offspring displayed complex inheritance patterns with one of the parents consistently contributing the major part of the chromosome backbone and multiple unselected fragments originating from the second parent. Our results demonstrate that this bias was in part due to the action of restriction–modification systems, whereas genome features like GC content and local nucleotide identity did not affect distribution of recombination events around the chromosome. Furthermore, we found that recombination occurred uniformly across the genome without concentration into hotspots. Notably, our results show that species-level genetic distance did not affect genome-wide recombination. This study provides a new insight into the dynamics of recombination in bacteria and a platform for studying recombination patterns in diverse bacterial species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Coupling localized Noah-MP-Crop model with the WRF model improved dynamic crop growth simulation across Northeast China

Croplands play a critical role in regulating the energy and moisture exchanges between the land surface and atmosphere. However, the interactions between cropland and climate are usually poorly represented due to a lack of detailed representation in crop types and field management. Here, we coupled the Noah-MP-Crop model with the state-of-the-art Weather Research and Forecasting (WRF) model to explore and evaluate the crop growth dynamics in response to climate variations across Northeast China. The default parameters of the crop model were not exactly suitable for the agricultural ecosystems in Northeast China. The detailed cropland distribution, and crop phenology parameters including growing degree days (GDD) and planting (harvesting) date were first created using multi-source remote sensing products and reanalysis data, and was then successfully used to simulate the growth and yield for corn and soybean and associated energy exchanges. We also optimized and calibrated other crop parameters using the time-series of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface products. The modified crop model substantially improved the simulation of crop growth, plant physiology, and biomass accumulation for both corn and soybean. Coupling the localized dynamic crop model into the WRF led to considerable decreases in the simulated mean-absolute-errors (MAEs) and biases of the leaf area index, evapotranspiration, and gross primary production compared with the MODIS observed values. Compared with the statistical yield from each province, the modified crop model underestimated the corn yield from 11.1% to 48.6%, whereas overestimated the soybean yield from 16.5% to 162.6%.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Neutralization Short-Circuiting with Weak Electrolytes Erodes the Efficiency of Bipolar Membranes

Bipolar membranes (BPMs) are critical components of a variety of electrochemical energy technologies. Many electrochemical applications require the use of buffers to maintain stable, nonextreme pH environments, yet the impact of buffers or weak acids/bases on the electrochemical behavior of BPMs remains poorly understood. Here, our data for a cell containing weak electrolytes is consistent with internal pH gradients within the anion exchange membrane (AEM) or cation exchange membrane (CEM) component of the BPM that form via ionic short-circuiting processes at open-circuit. Short-circuiting results from the coupling of co-ion crossover and parasitic neutralization and leads to buffering of the bipolar interface. This phenomenon, which we term neutralization short-circuiting, serves to erode BPM efficiency by attenuating the open-circuit membrane voltage and introducing parasitic reverse bias currents associated with weak acid/base dissociation at the interface. These findings establish a mechanistic basis for the operation of BPM cells in the presence of weak acid/base electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Status of the Muon Neutrino Charged-Current Mesonless Cross Section Measurement in the NOvA Near Detector

NOvA is a long-baseline accelerator neutrino experiment at Fermilab whose physics goals include precision neutrino oscillation as well as cross-section measurements. We present the status of the measurement of a muon neutrino charged-current cross section with zero mesons in the final state at the NOvA near detector. This measurement is being made with respect to the kinematics of the final state muon. The chosen interaction channel is especially sensitive to quasielastic and meson exchange current interactions and aims to provide experimental constraints for the development of models of neutrino interactions. It will also provide a handle for constraining cross section systematic uncertainties in oscillation analyses in current and future experiments. For particle identification, we use a convolutional neural network (CNN) trained on individual particles simulated in the NOvA near detector that allows us to select the desired signal while reducing the potential bias from neutrino interaction modeling. Charged pion background constraining is further improved via Michel electron tagging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Status of the Muon Neutrino Charged-Current Zero Mesons Cross Section at the NOvA Near Detector

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Dynamic global vegetation models underestimate net CO 2 flux mean and inter-annual variability in dryland ecosystems

Despite their sparse vegetation, dryland regions exert a huge influence over global biogeochemical cycles because they cover more than 40% of the world surface (Schimel 2010 Science 327 418–9). It is thought that drylands dominate the inter-annual variability (IAV) and long-term trend in the global carbon (C) cycle (Poulter et al 2014 Nature 509 600–3, Ahlstrom et al 2015 Science 348 895–9, Zhang et al 2018 Glob. Change Biol. 24 3954–68). Projections of the global land C sink therefore rely on accurate representation of dryland C cycle processes; however, the dynamic global vegetation models (DGVMs) used in future projections have rarely been evaluated against dryland C flux data. Here, we carried out an evaluation of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 dryland flux sites in the southwestern US encompassing a range of ecosystem types (forests, shrub- and grasslands). We find that all the models underestimate both mean annual C uptake/release as well as the magnitude of NEE IAV, suggesting that improvements in representing dryland regions may improve global C cycle projections. Across all models, the sensitivity and timing of ecosystem C uptake to plant available moisture was at fault. Spring biases in gross primary production (GPP) dominate the underestimate of mean annual NEE, whereas models' lack of GPP response to water availability in both spring and summer monsoon are responsible for inability to capture NEE IAV. Errors in GPP moisture sensitivity at high elevation forested sites were more prominent during the spring, while errors at the low elevation shrub and grass-dominated sites were more important during the monsoon. We propose a range of hypotheses for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future dryland DGVM developments. Our analysis suggests that improvements in modeling C cycle processes across more than a quarter of the Earth's land surface could be achieved by addressing the moisture sensitivity of dryland C uptake.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Direct determination of cellulosic glucan content in starch-containing samples

A simple and highly selective analytical procedure is presented for the determination of cellulosic glucan content in samples that contain both cellulose and starch. This method eliminates the unacceptably large compounding errors of current two-measurement methods. If both starch and cellulose are present before analytical hydrolysis, both will be hydrolyzed to glucose causing bias and inaccuracy in the method. To prevent this interference, the removal of starch prior to cellulosic quantification is crucial. The method presented here is a concise in-series procedure with minimal measurements, eliminating large compounding errors. Sample preparation consists of a starch extraction employing enzymatic hydrolysis followed by a simple filtration and wash. The samples are then subjected to a two-stage acid hydrolysis. The concentration of glucose is determined by ion exchange high-performance liquid chromatography with a Pb 2+ column and a refractive index detector. The cellulosic glucan content is calculated based on the initial dry weight of the starting material. Data for the native biomass materials studied show excellent reproducibility, with coefficients of variance of 3.0% or less associated with the method. This selectivity for cellulosic glucan by the procedure was validated with several analytical techniques such as liquid chromatography coupled with mass spectrometry (LC–MS), Raman spectroscopy, and nuclear magnetic resonance.

09 BIOMASS FUELS↗

DOE OSTI2023

Evaluating Northern Hemisphere Growing Season Net Carbon Flux in Climate Models Using Aircraft Observations

Understanding terrestrial ecosystems and their response to anthropogenic climate change requires quantification of land-atmosphere carbon exchange. However, top-down and bottom-up estimates of large-scale land-atmosphere fluxes, including the northern extratropical growing season net flux (GSNF), show significant discrepancies. We developed a data-driven metric for the GSNF using atmospheric carbon dioxide concentration observations collected during the High-Performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations and Atmospheric Tomography Mission flight campaigns. This aircraft-derived metric is bias-corrected using three independent atmospheric inversion systems. We estimate the northern extratropical GSNF to be 5.7 ± 0.3 Pg C and use it to evaluate net biosphere productivity from the Coupled Model Intercomparison Project phase 5 and 6 (CMIP5 and CMIP6) models. While the model-to-model spread in the GSNF has decreased in the CMIP6 models relative to that of the CMIP5 models, there is still disagreement on the magnitude and timing of seasonal carbon uptake with most models underestimating the GSNF and overestimating the length of the growing season relative to the observations. We also use an emergent constraint approach to estimate annual northern extratropical gross primary productivity to be 56 ± 17 Pg C, heterotrophic respiration to be 25 ± 13 Pg C, and net primary productivity to be 28 ± 12 Pg C. The flux inferred from these aircraft observations provides an additional constraint on large-scale gross fluxes in prognostic Earth system models that may ultimately improve our ability to accurately predict carbon-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Effect of Framework Composition and NH 3 on the Diffusion of Cu + in Cu-CHA Catalysts Predicted by Machine-Learning Accelerated Molecular Dynamics

Cu-exchanged zeolites rely on mobile solvated Cu + cations for their catalytic activity, but the role of the framework composition in transport is not fully understood. Ab initio molecular dynamics simulations can provide quantitative atomistic insight but are too computationally expensive to explore large length and time scales or diverse compositions. We report a machine-learning interatomic potential that accurately reproduces ab initio results and effectively generalizes to allow multinanosecond simulations of large supercells and diverse chemical compositions. Biased and unbiased simulations of [Cu(NH 3 ) 2 ] + mobility show that aluminum pairing in eight-membered rings accelerates local hopping and demonstrate that increased NH 3 concentration enhances long-range diffusion. The probability of finding two [Cu(NH 3 ) 2 ] + complexes in the same cage, which is key for SCR-NOx reaction, increases with Cu content and Al content but does not correlate with the long-range mobility of Cu + . Supporting experimental evidence was obtained from reactivity tests of Cu-CHA catalysts with a controlled chemical composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

The Dynamic Assimilation Technique measures photosynthetic CO2 response curves with similar fidelity as steady-state approaches in half the time

The net CO2 assimilation (A) response to intercellular CO2 concentration (Ci) is a fundamental measurement in photosynthesis and plant physiology research. The conventional A/Ci protocols rely on steady-state measurements and take 15-40 minute per measurement, limiting data resolution or biological replication. Additionally, there are several CO2 protocols employed across the literature, without clear consensus as to the optimal protocol or systematic biases in their estimations. We compared the non-steady state Dynamic Assimilation Technique (DAT) protocol and the three most used CO2 protocols in steady-state measurements, and tested whether different CO2 protocols lead to systematic differences in estimations of the biochemical limitations to photosynthesis.

A/Ci response↗

DOE OSTI2023

Controlling swelling in mixed transport polymers through alkyl side-chain physical cross-linking

Semiconducting conjugated polymers bearing glycol side chains can simultaneously transport both electronic and ionic charges with high charge mobilities, making them ideal electrode materials for a range of bioelectronic devices. However, heavily glycolated conjugated polymer films have been observed to swell irreversibly when subjected to an electrochemical bias in an aqueous electrolyte. The excessive swelling can lead to the degradation of their microstructure, and subsequently reduced device performance. An effective strategy to control polymer film swelling is to copolymerize glycolated repeat units with a fraction of monomers bearing alkyl side chains, although the microscopic mechanism that constrains swelling is unknown. Here we investigate, experimentally and computationally, a series of archetypal mixed transporting copolymers with varying ratios of glycolated and alkylated repeat units. Experimentally we observe that exchanging 10% of the glycol side chains for alkyl leads to significantly reduced film swelling and an increase in electrochemical stability. Through molecular dynamics simulation of the amorphous phase of the materials, we observe the formation of polymer networks mediated by alkyl side-chain interactions. When in the presence of water, the network becomes increasingly connected, counteracting the volumetric expansion of the polymer film.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Engineering of Lead Selenide Quantum Dot Based Devices and Core/Shell Heterostructures

Near infrared (NIR) emitting colloidal quantum dots (QDs) such as PbSe are interesting materials for implementation in various optoelectronic devices such as solar cells, photodetectors, and radiation detectors. Material properties like size tunable emission wavelengths, facile solution processability, the possibility of carrier multiplication and Auger assisted up-conversion, and high Z number provide PbSe QDs with unique advantages over many currently available commercial materials used in these devices. In this dissertation, after an introduction to QDs in general, we first focus on synthesis of PbSe-based heterostructured QDs for study via optical spectroscopy. PbSe/CdSe QDs synthesized via cation exchange reaction were used as seeds to study the proper conditions for further CdSe or CdS shell growth. Optical spectroscopy studies show that growth of thicker CdSe shells leads to tunable visible emission, while growth of thick CdS shells can greatly increase the photoluminescence quantum yield (PLQY) observed from the intermediate CdSe shell. NIR PL lifetimes can be greatly enhanced by the growth of CdS shells, due to strong delocalization of the hole wavefunction within the PbSe core, while the electron is delocalized throughout the QD including in the CdS shell, resulting in radiative lifetimes in the tens of microseconds. Two pulse delay measurements show that Auger assisted up conversion is also taking place in these engineered QD dot heterostructures. In the sections that follow, we look at QD devices, first with a focus on novel devices fabricated from PbSe QDs, using an amine synthesis method that allows for facile in-solution ligand exchange. QD film mobilities are measured for PbSe QDs capped with various short ionic ligands. Carrier densities in PbSe QD films are calculated from C-V measurements, showing for the first time that carrier densities can be modulated by simply changing the capping ligand. vii Radiation detectors utilizing PbSe QDs capped with KI and NH4I ligands show tangible response to incident alpha radiation. Current output response to alpha radiation is dependent on strength of radiation source and amount of bias voltage applied. In the final section a critical review of hybrid layered 2D-QD photodetectors is presented. In a typical example, PbSe and PbS QDs act as the absorbing layer in phototransistor devices which utilize layered 2D materials such as graphene and transition metal dichalcogenides as transport layers. Resulting devices display high gains and improved directivities compared to QD only and 2D only devices.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Comparative Density Functional Theory Study of Magnetic Exchange Couplings in Dinuclear Transition-Metal Complexes

Multicenter transition-metal complexes (MCTMs) with magnetically interacting ions have been proposed as components for information-processing devices and storage units. For any practical application of MCTMs as magnetic units, it is crucial to characterize their magnetic behavior, and in particular, the isotropic magnetic exchange coupling, J, between its magnetic centers. Due to the large size of typical MCTMs, density functional theory is the only practical electronic structure method for evaluating the J coupling. Here, we assess the accuracy of different density functional approximations for predicting the magnetic couplings of eight dinuclear transition-metal complexes, including five dimanganese, two dicopper, and one divanadium with known reliable experimental J couplings spanning from ferromagnetic to strong antiferromagnetic. The density functionals considered include global hybrid functionals which mix semilocal density functional approximations and exact exchange with a fixed admixing parameter, six local hybrid functionals where the admixing parameters are extended to be spatially dependent, the SCAN and r 2 SCAN meta-generalized gradient approximations (GGAs), and two widely used GGAs. We found that global hybrids tested in this work have a tendency to over-correct the error in magnetic coupling parameters from the Perdew–Burke–Ernzerhof (PBE) GGA as seen for manganese complexes. The performance of local hybrid density functionals shows no improvement in terms of bias and is scattered without a clear trend, suggesting that more efforts are needed for the extension from global to local hybrid density functionals for this particular property. The SCAN and r 2 SCAN meta-GGAs are found to perform as well as benchmark global hybrids on most tested complexes. We further analyze the charge density redistribution of meta-GGAs as well as global and local hybrid density functionals with respect to that of PBE, in connection to the self-interaction error or delocalization error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Evaluation of the interactive stratospheric ozone (O3v2) module in the E3SM version 1 Earth system model

Stratospheric ozone affects climate directly as the predominant heat source in the stratosphere and indirectly through chemical reactions controlling other greenhouse gases. The U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1) implemented a new ozone chemistry module that improves the simulation of the sharp tropopause gradients, replacing a version based partly on long-term average climatologies that poorly represented heating rates in the lowermost stratosphere. The new O3v2 module extends seamlessly into the troposphere and preserves the naturally sharp cross-tropopause gradient, with 20 %–40 % less ozone in this region. Additionally, O3v2 enables the diagnosis of stratosphere–troposphere exchange flux of ozone, a key budget term lacking in E3SMv1. Here, we evaluate key features in ozone abundance and other closely related quantities in atmosphere-only E3SMv1 simulations driven by observed sea surface temperatures (SSTs, years 1990–2014), comparing them with satellite observations of ozone and also with the University of California, Irvine chemistry transport model (UCI CTM) using the same stratospheric chemistry scheme but driven by European Centre forecast fields for the same period. In terms of stratospheric column ozone, O3v2 shows reduced mean bias and improved northern midlatitude variability, but it is not quite as good as the UCI CTM. As expected, SST-forced E3SMv1 simulations cannot synchronize with observed quasi-biennial oscillations (QBOs), but they do show the typical QBO pattern seen in column ozone. This new O3v2 E3SMv1 model mostly retains the same climate state and climate sensitivity as the previous version, and we recommend its use for other climate models that still use ozone climatologies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

An improved representation of the relationship between photosynthesis and stomatal conductance leads to more stable estimation of conductance parameters and improves the goodness-of-fit across diverse data sets

Stomata play a central role in surface-atmosphere exchange by controlling the flux of water and CO 2 between the leaf and the atmosphere. Representation of stomatal conductance (g sw ) is therefore an essential component of models that seek to simulate water and CO 2 exchange in plants and ecosystems. For given environmental conditions at the leaf surface (CO 2 concentration and vapor pressure deficit or relative humidity), models typically assume a linear relationship between g sw and photosynthetic CO 2 assimilation (A). However, measurement of leaf-level g sw response curves to changes in A are rare, particularly in the tropics, resulting in only limited data to evaluate this key assumption. Here, we measured the response of g sw and A to irradiance in six tropical species at different leaf phenological stages. We showed that the relationship between g sw and A was not linear, challenging the key assumption upon which optimality theory is based-that the marginal cost of water gain is constant. Our data showed that increasing A resulted in a small increase in g sw at low irradiance, but a much larger increase at high irradiance. We reformulated the popular Unified Stomatal Optimization (USO) model to account for this phenomenon and to enable consistent estimation of the key conductance parameters g 0 and g 1 . Our modification of the USO model improved the goodness-of-fit and reduced bias, enabling robust estimation of conductance parameters at any irradiance. In addition, our modification revealed previously undetectable relationships between the stomatal slope parameter g 1 and other leaf traits. We also observed nonlinear behavior between A and g sw in independent datasets that included data collected from attached and detached leaves, and from plants grown at elevated CO 2 concentration. We propose that this empirical modification of the USO model can improve the measurement of g sw parameters and the estimation of plant and ecosystem-scale water and CO 2 fluxes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Ramifications of Ion Migration in 2D Lead Halide Perovskites

Lower dimensional or 2D halide perovskites with their versatile structural and functional properties, are known to improve the performance and room temperature stability of perovskite solar cells. One would expect 2D perovskites to be more resistant to ion migration compared to their 3D counterparts because of the presence of bulky organic cations. However, recent findings show ion migration indeed is prevalent in 2D halide perovskites similar to 3D perovskites. Halide ion migration in 2D perovskites manifests itself as halide ion segregation under photoirradiation as well as in halide exchange between physically paired films of 2D perovskites with different halide ions. Besides halide ion migration, cation migration of spacer cations and A-site cation is also seen when 2D/3D perovskite films are subjected to light and thermal stress. It is important to recognize the importance of ion migration while incorporating 2D perovskites in solar cells and other optoelectronic devices as it can be detrimental for achieving streamlined performance and long-term stability Furthermore, this perspective discusses recent reports on ion migration in 2D and in 2D/3D halide perovskite films under the operational conditions (at elevated temperature and given in-built bias) and presents a few mitigating strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Influence of Lake Ice Biases in Reanalysis Data on Downscaled Climate Simulations over the Great Lakes Region

This data package contains observation-based and model-simulated datasets (all provided in NetCDF format) for evaluating how wintertime lake-ice representation affects regional weather and climate over the Laurentian Great Lakes (freshwater lake ecosystem) during the high–ice-cover winter of 2009. The observational component includes: (1) Stage IV gridded precipitation at 4 km, hourly resolution for January–February 2009 over the Great Lakes region (radar–gauge multisensor precipitation analyses); (2) Great Lakes Surface Environmental Analysis (GLSEA) satellite-derived lake-ice coverage at 1.3 km, daily resolution for the 2009 winter months, providing ice coverage over Lakes Superior, Michigan, Huron, Erie, and Ontario; and (3) in situ measurements at the Standard Rock site on Lake Superior from the Great Lakes Evaporation Network (GLEN) at hourly resolution, including near-surface atmospheric variables and sensible and latent heat fluxes (air–lake exchange) at a fixed point location. The modeling component provides corresponding fields from two simulations, both archived at 4 km, hourly resolution: a standalone Weather Research Forecasting model (WRF) run driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), and a two-way coupled model using WRF and the Finite Volume Community Ocean Model (WRF-FVCOM, a 3-D hydrodynamic lake model). These outputs include variables relevant to air–lake interaction and lake-effect processes (e.g., near-surface temperature, humidity, wind, precipitation, and surface turbulent fluxes), enabling direct comparison with the observational datasets. Users can analyze and visualize these NetCDF files with common tools such as Python (e.g., xarray, netCDF4, numpy, pandas), NCO/CDO, Panoply, or ncview; NetCDF variables can also be converted to other formats (e.g., CSV, GeoTIFF) using these utilities.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗

DOE OSTI2024

A Vertically Resolved Canopy Improves Chemical Transport Model Predictions of Ozone Deposition to North Temperate Forests

Abstract Dry deposition is the second largest tropospheric ozone (O 3 ) sink and occurs through stomatal and nonstomatal pathways. Current O 3 uptake predictions are limited by the simplistic big‐leaf schemes commonly used in chemical transport models (CTMs) to parameterize deposition. Such schemes fail to reproduce observed O 3 fluxes over terrestrial ecosystems, highlighting the need for more realistic treatment of surface‐atmosphere exchange in CTMs. We address this need by linking a resolved canopy model (1D Multi‐Layer Canopy CHemistry and Exchange Model, MLC‐CHEM) to the GEOS‐Chem CTM and use this new framework to simulate O 3 fluxes over three north temperate forests. We compare results with in situ measurements from four field studies and with standalone, observationally constrained MLC‐CHEM runs to test current knowledge of O 3 deposition and its drivers. We show that GEOS‐Chem overpredicts observed O 3 fluxes across all four studies by up to 2×, whereas the resolved‐canopy models capture observed diel profiles of O 3 deposition and in‐canopy concentrations to within 10%. Relative humidity and solar irradiance are strong O 3 flux drivers over these forests, and uncertainties in those fields provide the largest remaining source of model deposition biases. Flux partitioning analysis shows that: (a) nonstomatal loss accounts for 60% of O 3 deposition on average; (b) in‐canopy chemistry makes only a small contribution to total O 3 fluxes; and (c) the CTM big‐leaf treatment overestimates O 3 ‐driven stomatal loss and plant phytotoxicity in these temperate forests by up to 7×. Results motivate the application of fully online vertically explicit canopy schemes in CTMs for improved O 3 predictions.

Vermeuel, Michael P. [Department of Soil, Water, a↗