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At least 487 records · Page 27

The impact of urban configuration types on urban heat islands, air pollution, CO 2 emissions, and mortality in Europe: a data science approach

The world is becoming increasingly urbanized. As cities around the world continue to grow, it is important for urban planners and policymakers to understand how different urban configuration patterns affect the environment and human health. We aimed at identifying European urban configuration types, based on the Local Climate Zones categories and street design variables from Open Street Map, and evaluating their association with motorized traffic flows, Surface Urban Heat Island (SUHI) intensities, tropospheric nitrogen dioxide (NO 2 ), CO 2 per capita emissions and age-standardized mortality. We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal–Wallis test followed by a post-hoc Dunn's test. We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low-density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low-density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO 2 exposure were significantly higher in compact high density and open low rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low-density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO 2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types. Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Sensitivity of Hyporheic Exchange to Fractal Properties of Riverbeds

Hyporheic exchange in riverbeds is driven by current-bed topography interactions. Because riverbeds exhibit topographic roughness across scales, from individual grains to bedforms and bars, they can exhibit fractal patterns. This study analyzed the influence of fractal properties of riverbed topography on hyporheic exchange. A set of synthetic fractal riverbeds with different scaling statistics was used as inputs to sequentially coupled numerical simulations of turbulent channel flow and hyporheic flow. In the analysis, the maximum power spectrum (dune size) and the fractal dimension (topographic complexity) were considered as independent variables and we then investigated how interfacial fluxes and hyporheic travel times are functionally related to these variables. As the maximum power spectrum increases (i.e., dune height to flow depth ratio), the average interfacial flux increases logarithmically whereas it increases exponentially with an increase in fractal dimension. Hyporheic exchange is more sensitive to additional roughness (larger fractal dimensions) than to bedform size (larger maximum power). Our results imply that fractal properties of riverbeds are crucial to predicting hyporheic exchange. The predictive relationships we propose could be integrated with reduced complexity, large-scale models. Further, they can also be used to design artificial topographies that target hyporheic ecosystem services.

54 ENVIRONMENTAL SCIENCES↗

Modeling and Calibration of Supplier Selection Problem in Freight Agent-Based Simulations

Freight transportation modeling often struggles with data limitations, especially in accurately representing complex supplier selection processes and their impact on network flows. This research addresses this critical gap by developing a large-scale, calibrated agent-based model for supplier selection, complemented by a probabilistic heuristic for international shipments. Our approach integrates trade relationships between industry sectors, transportation costs, and a supplier-rating model adapted from existing literature. The model’s core objective is to minimize the discrepancy between modeled and observed commodity flows while ensuring a close match to regional shipping distance distributions. Implemented and tested across four major U.S. metropolitan areas—Atlanta, Chicago, Dallas–Fort Worth, and Los Angeles—the model demonstrates high fidelity in replicating observed freight patterns. Key findings reveal consistent alignment with national shipping distance trends and highlight significant spatial variations in commodity trade assignments and demand across the study regions. This behaviorally informed and transport-sensitive framework is designed to approximate real-world decision making, providing a robust tool for policymakers and planners to evaluate targeted interventions, assess infrastructure investments, and enhance supply chain resilience in the face of disruptions.

Ismael, Abdelrahman (ORCID:0000000303712110)↗

Data and scripts associated with "Coupled primary production and respiration in a large river contrasts with smaller rivers and streams."

This data package is associated with the publication "Coupled primary production and respiration in a large river contrasts with smaller rivers and streams." in review at Limnology and Oceanography (Roley et al. 2023). This study focuses on understanding ecosystem metabolism for the Hanford Reach of the Columbia River in Washington state, a free-flowing stretch with a substantial discharge. Large rivers have been overlooked compared to small and medium rivers due to the challenges associated with measurements. Our study presents novel ways to address these challenges and highlights that metabolism patterns in large rivers differ from those observed in small-medium rivers and requires the application of knowledge and tools beyond those implemented for smaller rivers.This data package includes the data and R scripts for the analyses described in Roley et al. 2023. It includes dissolved oxygen and temperature data from a dissolved oxygen HOBO sensor, light data collected from the National Solar Radiation Database (https://nsrdb.nrel.gov/) and hydrologic variables estimated from the MASS-1 model (Niehus et al.; 2014). It also includes metabolism estimates (gross primary production, ecosystem respiration, and net ecosystem production) estimated via streamMetabolizer (Appling et al.; 2018). All analyses in the paper can be replicated with these data and scripts.The data package is comprised of one main data folder. The folder includes (1) file-level metadata (flmd); (2) a data dictionary (dd) for each data file; (3) data files; and (4) R scripts for metabolism estimates and data analysis. All files are .R, .csv, or .pdf.

54 ENVIRONMENTAL SCIENCES↗

Proton-rich Production of Lanthanides: The vi Process

The astrophysical origin of the lanthanides is an open question in nuclear astrophysics. Besides the widely studied s, i, and r processes in moderately to strongly neutron-rich environments, an intriguing alternative site for lanthanide production could in fact be robustly proton-rich matter outflows from core-collapse supernovae under specific conditions—in particular, high-entropy winds with enhanced neutrino luminosity and fast dynamical timescales. In this environment, excess protons present after charged-particle reactions have ceased can continue to be converted to neutrons by (anti)neutrino interactions, producing a neutron-capture reaction flow up to A ∼ 200. This scenario, christened the νi process in a recent paper, has previously been discussed as a possibility. Here, we examine the prospects for the νi process through the lenses of stellar abundance patterns, bolometric light curves, and galactic chemical evolution models, with a particular focus on hypernovae as candidate sites. We identify specific lanthanide signatures for which the νi process can provide a credible supplement to the r/i processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Simple Route for Open Fluidic Devices with Particle Walls

Open fluidics, allowing liquid in a flow channel to interact with the external environment, is a revolutionary concept. However, fabricating a highly stable open fluidic device of arbitrary complexity, while maintaining reconfigurability, is still a challenge. This is achieved by the use of a patterned substrate and liquids that are covered with functional, readily available hydrophobic particles, providing great flexibility in the construction and use of open fluidic structures. Decorated with a coating of modified carbon nanotubes (CNTs) to encapsulate the fluids, the study capitalizes on the photothermal characteristics of CNTs to fabricate a device to probe the effects of temperature on tumor chemotherapy. The strategy substantially increases the availability and potential use of open fluidic devices.

Liu, Heng↗

Hyporheic Oxygen Dynamics in the East River, Colorado: Insights From an In–Situ, High Frequency Time Series During Two Distinct Flow Seasons

Dissolved oxygen (DO) is critical for aquatic ecosystems, however, few studies have focused on the long-term DO dynamics in hyporheic zones, which are a function of both transport (hydrologic exchange between river and hyporheic zone) and uptake by biogeochemical reactions or respiration. We explore the dynamics of temperature and DO at 10, 20, and 35 cm depth beneath the East River, Colorado, from July–October 2017 (relatively normal water year) and April to October 2018 (comparatively low flow year), enabled by distinctive, in-situ, high frequency (Δt = 5 min) sensors that provided continuous time-series from the undisturbed study site over 14 months. We expect that hyporheic DO, which has a regular daily fluctuation pattern, is supplied by the surface water (at all times we estimate downwelling) and that diurnal hyporheic DO temporal patterns should be aligned with diurnal hyporheic temperature patterns. However, this was not found to be the case. Hyporheic DO becomes depleted briefly at 20 and 35 cm depths in 2017, and at all three hyporheic depths for extended periods in 2018. Whereas diurnal temperature fluctuations have consistent timings of maxima and minima, hyporheic DO rarely has as regular a pattern, and daily ranges are inconsistent. Rainfall events caused some of these changes to diurnal hyporheic DO patterns without repeatable effects. Antecedent snowpack conditions influence streamflow dynamics and therefore hyporheic DO dynamics in this alpine river. These results also point to the strong and variable influence of hyporheic microbial communities regulating hyporheic DO.

54 ENVIRONMENTAL SCIENCES↗

First experimental confirmation of island SOL geometry effects in a high radiation regime on W7-X

Abstract This work characterizes the detachment behavior and radiation characteristics of the low
iota configuration in the Wendelstein 7-X (W7-X) stellarator. The island scrape-off layer (SOL) of the
low iota has a poloidal mode number of 6 islands surrounding the last closed flux surface (LCFS).
The island geometry of the low iota configuration is significantly different to that of the standard
magnetic field configuration, whose detachment characteristics have already been described in previous
work[2, 3, 4]. Experimental results show that the radiation pattern in the low iota configuration
is starkly different to that of the standard magnetic field configuration, with radiation concentrated
at the island SOL O-points, rather than the X-points. Additionally, this O-point localized radiation
pattern is associated with unstable detachment, with both radiation oscillations in experiments and the
lack of a self-consistent plasma solution at high radiated power fraction in EMC3-Eirene simulations.
EMC3-Eirene simulations are used to understand the radiation distribution. It was found that the O-
point localized radiation arises first from local impurity accumulation near the parallel flow stagnation,
which is located close to the geometrical center of the island (”O-point”). The local cooling in this
region leads to plasma condensation in the islands in closest magnetic connection to the divertor target
plates. The heat source to this region of the island, which is thermally isolated from the upstream heat
source in terms of parallel transport, must arise via perpendicular heat transport. This heat source is
expected to be large for the low iota configuration due to its very small internal island field line pitch.
This work highlights the importance (complementary to previous work, e. g. [5, 6]) of the internal
island field line pitch not only on the radiation pattern, but also the detachment performance of the
island divertor.

Winters, Victoria (ORCID:0000000181087774)↗

Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits

Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes, which could lead to inflammatory diseases including atherosclerosis and metabolic syndrome. Sodium 4-phenylbutyrate is a potential therapeutic compound which can reduce the inflammation caused by SD-LPS. To understand the gene regulatory networks of these processes, we have generated scRNA-seq data from mouse monocytes treated with these compounds and identified 11 novel cell clusters. We have developed a machine learning method to integrate scRNA-seq, ATAC-seq, and binding motifs to characterize gene regulatory networks underlying these cell clusters. Using guided regularized random forest and feature selection, our method achieved high performance and outperformed a traditional enrichment-based method in selecting candidate regulatory genes. Our method is particularly efficient in selecting a few candidate genes to explain observed expression pattern. In particular, among 531 candidate TFs, our method achieves an auROC of 0.961 with only 10 motifs. Finally, we found two novel subpopulations of monocyte cells in response to SD-LPS and we confirmed our analysis using independent flow cytometry experiments. Our results suggest that our new machine learning method can select candidate regulatory genes as potential targets for developing new therapeutics against low grade inflammation.

60 APPLIED LIFE SCIENCES↗

Progress Towards a Predictive Eagle Behavior and Risk Modeling Framework: Overview and Recent Validation Efforts

This presentation summarizes progress to date of the U.S. Department of Energy project, "Development of a computational framework for modeling golden eagles (Aquila chrysaetos) near wind farms," which focuses on stochastic behavioral modeling of soaring raptors across landscape, facility, and turbine spatiotemporal scales. This publicly available, open-source modeling framework includes behavioral models based on three different underlying principles: energy minimization at landscape scale, behavioral heuristics at landscape-facility scale, and data-driven behaviors at the facility-micro-scale. We will briefly overview the key advancements in the behavioral modeling state of the art, which leverages multiple high-resolution telemetry data sources combined with high-fidelity atmospheric flow modeling insights. We then present preliminary results from a validation study in Altamont, California. This new study involves a novel application of the Stochastic Soaring Raptor Simulator (SSRS), in a new geographic locale, to understand facility scale eagle movement patterns over time scales representative of a wind project's lifetime. For this desktop analysis (that does not depend on any high-performance computing resources), SSRS simultaneously considers a variety of wind conditions and eagle approach vectors toward a project site of interest. This work demonstrates the integration of publicly available landscape-scale atmospheric datasets, our recently improved engineering updraft models (see presentation from Thedin et al.), and our energy minimization behavioral models within the SSRS framework. While we only present results from a single behavioral model, the integration of these three modeling components forms the foundation for our more sophisticated behavioral models (see presentations from Brandes et al., Sandhu et al.) that are under active development. Results are presented in the form of presence maps, which may be applied to estimate risk to wildlife, augment ground survey data, inform wind-plant operations, or incorporated into wind-plant designs.

agent-based modeling↗

Insights of Boundary Layer Turbulence Over the Complex Terrain of Central Himalaya from GVAX Field Campaign

Limited observations hinder understanding of turbulent characteristics in mountainous terrain resulting from heating or cooling of slopes, wind, vertical motions, and heat or moisture advection, which disperse aerosols and other pollutants over the region. In this study, the 1290 MHz radar wind profiler data are utilized to compute the boundary layer height (BLH), the refractive index structure constant (C n 2 ), and the energy dissipation rate (ε) over the central Himalayan site for the period of November 2011 to March 2012, from the intense Ganges Valley Aerosol Experiment (GVAX) field measurements. The radar wind profiler (RWP) based estimation of BLH and ε is validated against the radiosonde, representing the effectiveness of the datasets for further investigation. The strong seasonal variation of log C n 2 and log ε, with average values of ≈ -12 m -2/3 and -2 m 2 s -3 , respectively, is associated with the mountain-induced local circulations and stability in the atmospheric boundary layer. The weak stratification during weak flow is found to be responsible for deep mixing, particularly in the nocturnal boundary layer in spring. Furthermore, the level of cloud cover significantly impacts the strength of turbulence, with the highest cloud cover resulting in a substantial increase in log C n 2 (approximately -11 m -2/3 ) due to intense updraft and downdraft motions compared to clear skies. Additionally, the distribution of aerosol loading across the site, coupled with the behavior of BLH, atmospheric stability, and orographic-induced circulations, implies distinctive seasonal mechanisms for transporting aerosols toward the mountains. This study offers valuable insights into the diurnal and seasonal patterns of turbulent mixing and the mechanisms behind the transport of pollutants through boundary layer processes over the region.

54 ENVIRONMENTAL SCIENCES↗

Active microrheology and dynamic phases for pattern-forming systems with competing interactions

We consider the driven dynamics of a probe particle moving through an assembly of particles with competing long-range repulsive and short-range attractive interactions, which form crystal, stripe, labyrinth, and bubble states as the ratio of attraction to repulsion is varied. We show that the probe particle exhibits a depinning-like threshold from an elastic regime, where the probe particle is trapped by interactions with the other particles, to a plastic flow regime, where the probe particle can break bonds in the surrounding medium. For a fixed particle density, the depinning threshold and sliding velocity of the probe particle vary nonmonotonically as the attraction term is increased. A velocity minimum appears near the crystal to stripe crossover, and there is a significant increase in the depinning threshold in the bubble regime when the probe particle is strongly confined inside the bubbles. For fixed attractive interaction but increasing particle density, the behavior is also nonmonotonic, and there are jumps and drops in the velocity and depinning threshold corresponding to points at which the system transitions between different structures. There are also several distinct flow states that can be characterized by the amount of plastic deformation induced by the probe particle in the surrounding medium. Each flow state generates a different amount of effective drag on the probe particle, and there can be jumps in the velocity-force curve at transitions between the states. In conclusion, we also find that when oriented stripes are present, the probe particle can move along the stripe in an edge transport state that has a finite Hall angle.

36 MATERIALS SCIENCE↗

Predicting future well performance for environmental remediation design using deep learning

Here in this study, we developed a deep learning (DL) framework with a multi-channel three-dimensional convolutional neural network (MC3D-CNN) to predict well performance and thereby assist future environmental remediation design. Such prediction of extraction well performance at designated locations is critical for configuring pump-and-treat (P&T) well network design and operation, setting reasonable target closure dates for overall remedying, and estimating remedy costs. The framework is developed with operational and monitoring data routinely collected during P&T remedy operations, including well extraction and injection rates as well as in situ contaminant concentrations. Traditionally, the collected data were rarely used for purposes other than assessing past well performance and the accuracy of the conceptual site model. However, recent advances in data-driven computational approaches enable better use of the large datasets to inform future well performance, enhance site characterization, and improve remediation planning. In this study, we established a DL framework to integrate transient three-dimensional contaminant plumes and multiple aquifer properties (e.g., hydraulic conductivity and hydrostratigraphic maps) to identify characteristic patterns controlling and representing extraction well mass recovery, aiming at providing future mass recovery estimates for existing wells and candidate wells at any proposed locations. We evaluated our framework by using a realistic synthetic dataset generated from a well-calibrated flow and transport model used in the 200 West Area of the U.S. Department of Energy’s Hanford Site in southeastern Washington state. The multi-channel feature in our framework allows integration of various types and temporal densities of training datasets for DL model development. Overall, we found that the trained DL model achieved an accuracy of over 90% in ranking extraction well performance in validation datasets, and over 80% in predicting high-performance-ranking well locations. This data-informed approach provides a flexible tool to support adaptive site management, streamline decision-making, and potentially reduce remediation time and costs. Our DL framework can be used as a filtering tool to improve the current P&T network optimization design by reducing the number of candidate well locations.

54 ENVIRONMENTAL SCIENCES↗

Analysis of the Aeroelastic Dynamics of Lightweight Flexible Variations of the SNL-NRT Turbine

Current trends show that wind turbines are growing in size to meet a rising demand for renewable energy generation, and their upscaled rotors have inherently become more flexible to maintain a proportionally lighter design. This is because larger rotors must be less massive relative to their diameter to minimize the levelized cost of energy (LCOE), which means that blades that are notably less stiff are produced as a result. These structural changes to blades are often reflected in their compromised aeroelastic stability and amplified deformation during operation, which has the potential to decrease the blade’s expected lifetime and the performance of the machine overall. Variations in blade flexibility are also known to influence vortex-wake structures downstream of the turbine, causing patterns of velocity deficit to evolve in ways that affect the performance of other turbines in the farm. This research explores how the increased flexibility of modern utility-scale wind turbine blades influences rotor aeroelastic behavior and interactions with farm flow. High-fidelity simulations of Sandia National Laboratories’ (SNL) National Rotor Testbed (NRT) wind turbine are presented. Flexible variations of the NRT baseline blade are simulated in a variety of realistic operational conditions typically expected at the SNL’s SWiFT facility in Lubbock, Texas. Solutions are then compared to investigate how specific changes to the structural properties of the NRT baseline blade’s design and construction can influence its aeroelastic response at the rotor and the evolution of the turbine’s wake.

Farrell, Alayna (ORCID:000000023555720X)↗

Impact of large-scale effects on mass transfer and concentration polarization in Reverse Osmosis membrane systems

Here, we present well-resolved computational fluid dynamics simulations of a large-scale reverse osmosis membrane-spacer configuration (1 m). Our computational model solves the flow and transport equations with variable solute-dependent properties. We utilize a high resolution computational mesh to resolve all relevant length scales associated with spacer-induced mixing and thin concentration boundary layers. An important contribution of this work is the development of a modified mass-transfer correlation that accounts for the development of the concentration boundary layer along the channel. A set of 2D axisymmetric simulations were performed for a spiral wound module layer with varying cross-flow conditions and spacer diameters which indicate a significant entrance length effect for concentration profile development at lower flow rates while mixing effects dominate at higher flow rates. The mass-transfer correlations at higher flow rates compare well with published correlations while a surrogate model for Sherwood number was obtained that depends on an additional similarity variable that accounted for entrance length effects at lower flow rates. Finally, a large-scale membrane-spacer design relevant to high-pressure reverse osmosis is studied with a non-uniform arrangement of spacers, which indicate a substantial saving in pressure drop (~40%) compared to traditional uniformly spaced pattern with minor variations (~2%) in concentration polarization, product water quality (~1%) and water recovery (~7%) compared to a uniform spacer pattern.

97 MATHEMATICS AND COMPUTING↗

Measurement of pressure gradients near the interface in the viscous fingering instability

The viscous fingering instability, which forms when a less-viscous fluid invades a more-viscous one within a confined geometry, is an iconic system for studying pattern formation. For both miscible and immiscible fluid pairs the growth dynamics change after the initial instability onset and the global structures, typical of late-time growth, are governed by the viscosity ratio. Here we introduce an experimental technique to measure flow throughout the inner and outer fluids. This probes the existence of a new length scale associated with the local pressure gradients around the interface and allows us to compare our results to the predictions of a previously proposed model for late-time finger growth. Published by the American Physical Society 2024

Physics↗

Impact of Primary and Secondary ZDDP and Ionic Liquid as Lubricant Oil Additives on the Performance and Physicochemical Properties of Pd-Based Three-Way Catalysts

In the present study, two industry primary and secondary zinc dialkyldithiophosphate standards, ZDDP1 and ZDDP2, respectively, are evaluated for their impact on the performance of Pd-based three-way catalyst and bench-marked against two mixed lubricant additives formed from either ZDDP1 or ZDDP2 with a second-generation oil-miscible phosphoric-containing ionic liquid (IL). The three-way catalysts (TWCs) are exposed to the lubricant additives in an engine bench under four different scenarios: a base case with no additive (NA), ZDDP1, IL+ZDDP1, ZDDP2, and IL+ZDDP2. The engine-aged TWC samples are characterized through a variety of analytical techniques, including evaluation of catalyst reactivity in a bench-flow reactor. With respect to the water–gas shift reaction and the oxygen storage capacity, the ZDDP2- and IL+ZDDP2-aged TWC samples are more degraded than the ZDDP1- and IL+ZDDP1-aged TWC samples. X-ray diffraction (XRD) patterns indicate that phosphorus in the form of CePO4 was found to be present in the washcoat of all TWC samples, with the highest amount found in the ZDDP2-aged TWC sample. The results obtained from XRD are further confirmed by those from inductively coupled plasma-optical emission spectroscopy (ICP-OES), which show that more phosphorus is detected in the washcoat of ZDDP2- and IL+ZDDP2-aged TWC samples than in the ZDDP1- and IL+ZDDP1-aged TWC samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A minor respiratory process with major global implications: is atmospheric methane oxidation in tree stems driven by stem respiration rather than microbial methanotrophy?

Tree stem surfaces are widely recognized as sites of carbon dioxide (CO₂) efflux and oxygen (O₂) influx, reflecting the dynamics of aerobic respiration of photosynthate substrates, such as sugars, delivered via the phloem. Stems are also largely considered passive conduits for methane (CH₄) produced in anoxic soils via microbial methanogenesis, where CH₄ is thought to be transported upward through the transpiration stream and/or diffusion and emitted through stem surfaces and the canopy. However, recent observations from dynamic stem chambers suggest that stems may also act as active sinks for atmospheric CH₄. Despite these findings, the extent and drivers of stem CH₄ consumption remain poorly characterized across biomes, species, and environmental gradients, and its quantitative relationship to stem respiration has not been established. Moreover, previous studies captured only snapshot fluxes, leaving diurnal patterns of CH₄ exchange uncharacterized. Here, we address these limitations by combining real-time measurements of stem CH₄ and O₂ uptake under ambient conditions in a California cherry tree, using a dynamic stem gas exchange system with three chambers receiving a continuous flow of ambient air and automated chamber and reference air sampling every 10 min. Our results confirm that stems of upland trees can actively consume both atmospheric CH₄ and O₂, but with decreasing temperature sensitivity as daily temperatures increase. Early mornings were marked by rapid influxes of both gases, followed by declining uptake as temperatures rose further. Methane uptake was tightly coupled with O₂ influx and represented a minor (0.012% ± 0.002%) fraction of stem respiratory activity, as determined by concurrent O₂ uptake. These findings suggest that while atmospheric CH₄ oxidation is a minor respiratory process in stems, it is strongly linked with stem physiological activity. This challenges the current assumption that terrestrial CH₄ uptake is driven solely by microbial methanotrophy and raises the possibility that living stem tissues may contribute to CH₄ oxidation through an as-yet-unidentified plant-based mechanism.

Atmospheric greenhouse gases↗