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At least 523 records · Page 29

Chemistry-mediated Ostwald ripening in carbon-rich C/O systems at extreme conditions

Abstract There is significant interest in establishing a capability for tailored synthesis of next-generation carbon-based nanomaterials due to their broad range of applications and high degree of tunability. High pressure (e.g., shockwave-driven) synthesis holds promise as an effective discovery method, but experimental challenges preclude elucidating the processes governing nanocarbon production from carbon-rich precursors that could otherwise guide efforts through the prohibitively expansive design space. Here we report findings from large scale atomistically-resolved simulations of carbon condensation from C/O mixtures subjected to extreme pressures and temperatures, made possible by machine-learned reactive interatomic potentials. We find that liquid nanocarbon formation follows classical growth kinetics driven by Ostwald ripening (i.e., growth of large clusters at the expense of shrinking small ones) and obeys dynamical scaling in a process mediated by carbon chemistry in the surrounding reactive fluid. The results provide direct insight into carbon condensation in a representative system and pave the way for its exploration in higher complexity organic materials. They also suggest that simulations using machine-learned interatomic potentials could eventually be employed as in-silico design tools for new nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Designing for Zero Energy and Zero Carbon on a Multi-Building Scale Using URBANopt: Preprint

Groundbreaking efforts are necessary to mitigate contributors increasing impacts of climate change. In parallel to inventing pioneering clean energy technologies it is even more fundamental to rethink designing energy systems within a singular facility and collectively to function as a district. Facilities should not be continuously passive by just consuming; there is a need to shift to perform more dynamically. Designing for zero energy and zero carbon on a multi-building scale can uncover opportunities for building energy efficiency, decarbonization, demand flexibility, and resiliency that are not accessible at an individual building scale. This approach can be challenging without innovative tools to evaluate the multitude of possibilities. As an investigated result, we highlight the use of a campus-scale energy modeling platform - URBANopt™ - for the expansion of the National Renewable Energy Laboratory's (NREL's) South Table Mountain campus in Golden, Colorado. Programmatic growth included the design of three new all-electric, zero-energy, and zero-carbon, mixed used buildings (a combination of research laboratories and office space). This investigation is critical to NREL reaching net-zero emissions for its operational footprint, which will occur in phases over the next decade. Leveraging URBANopt's capabilities, we evaluate 1) high-performance building energy efficiency and decarbonization measures, 2) 4th generation district heating and cooling (4th GDHC) systems, 3) optimized onsite generation and energy storage assets that meet zero-energy and zero-carbon targets at minimum life-cycle costs, and 4) cost-optimal distributed energy technology mixes, dispatch strategies, and associated capacities that increase resiliency to grid outages. This work demonstrates the use and capabilities of URBANopt through a real-world case study on a multi-building scale.

community energy model↗

From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world

Soils represent the largest terrestrial reservoir of organic carbon, and the balance between soil organic carbon (SOC) formation and loss will drive powerful carbon-climate feedbacks over the coming century. To date, efforts to predict SOC dynamics have rested on pool-based models, which assume classes of SOC with internally homogenous physicochemical properties. However, emerging evidence suggests that soil carbon turnover is not dominantly controlled by the chemistry of carbon inputs, but rather by restrictions on microbial access to organic matter in the spatially heterogeneous soil environment. The dynamic processes that control the physicochemical protection of carbon translate poorly to pool-based SOC models; as a result, we are challenged to mechanistically predict how environmental change will impact movement of carbon between soils and the atmosphere. In this study, we propose a novel conceptual framework to explore controls on belowground carbon cycling: Probabilistic Representation of Organic Matter Interactions within the Soil Environment (PROMISE). In contrast to traditional model frameworks, PROMISE does not attempt to define carbon pools united by common thermodynamic or functional attributes. Rather, the PROMISE concept considers how SOC cycling rates are governed by the stochastic processes that influence the proximity between microbial decomposers and organic matter, with emphasis on their physical location in the soil matrix. We illustrate the applications of this framework with a new biogeochemical simulation model that traces the fate of individual carbon atoms as they interact with their environment, undergoing biochemical transformations and moving through the soil pore space. We also discuss how the PROMISE framework reshapes dialogue around issues related to SOC management in a changing world. We intend the PROMISE framework to spur the development of new hypotheses, analytical tools, and model structures across disciplines that will illuminate mechanistic controls on the flow of carbon between plant, soil, and atmospheric pools.

54 ENVIRONMENTAL SCIENCES↗

Spectroscopy-based isotopic (δ 13 C) analysis for high spatial resolution of carbon exchange in the rhizosphere

The rhizosphere is a highly dynamic zone bridging plant roots with needed nutrient resources in soil. While the rhizosphere may be small, it has a disproportionally large impact on plant success and biomass production. A suite of rhizosphere-hosted microbial and geochemical interactions facilitate nutrient acquisition by plant roots, and, in turn, the roots stimulate these processes by supplying organic carbon into the rhizosphere. The small physical dimensions of the rhizosphere, however, can constrain efforts to elucidate key carbon exchange processes and their spatial extent and localization. We present a method for spatially resolved δ 13 C analysis of rhizosphere samples by coupling laser ablation (LA) sampling with isotopic analysis using capillary absorption spectroscopy (CAS) which differs from conventional mass spectrometer (MS) approaches. The CAS system has high sensitivity (requires fewer nanomoles of CO 2 per analysis) than comparable MS systems, which enables reduced sample size requirements to thereby improve spatial resolution (from 25 μm to as low as a projected 5 μm spatial resolution). We demonstrate the utility of CAS using rhizosphere samples from switchgrass plants exposed to 13 CO 2 . As a result, this technique will provide a capability for tracking the extent and spatial distribution of root exudate into the rhizosphere at highly detailed spatial scales.

59 BASIC BIOLOGICAL SCIENCES↗

Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)

Plant and microbial nitrogen (N) dynamics and N availability regulate the photosynthetic capacity and capture, allocation, and turnover of carbon (C) in terrestrial ecosystems. Studies have shown that a wide divergence in representations of N dynamics in land surface models leads to large uncertainties in the biogeochemical cycle of terrestrial ecosystems and then in climate simulations as well as the projections of future trajectories. In this study, a plant C–N interface coupling framework is developed and implemented in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0). The main concept and structure of this plant C–N framework and its coupling strategy are presented in this study. This framework takes more plant N-related processes into account. The dynamic ratio (CNR) for each plant functional type (PFT) is introduced to consider plant resistance and adaptation to N availability to better evaluate the plant response to N limitation. Furthermore, when available N is less than plant N demand, plant growth is restricted by a lower maximum carboxylation capacity of RuBisCO (V c,max ), reducing gross primary productivity (GPP). In addition, a module for plant respiration rates is introduced by adjusting the respiration with different rates for different plant components at the same N concentration. Since insufficient N can potentially give rise to lags in plant phenology, the phenological scheme is also adjusted in response to N availability. All these considerations ensure a more comprehensive incorporation of N regulations to plant growth and C cycling. This new approach has been tested systematically to assess the effects of this coupling framework and N limitation on the terrestrial carbon cycle. Long-term measurements from flux tower sites with different PFTs and global satellite-derived products are employed as references to assess these effects. The results show a general improvement with the new plant C–N coupling framework, with more consistent emergent properties, such as GPP and leaf area index (LAI), compared to the observations. The main improvements occur in tropical Africa and boreal regions, accompanied by a decrease in the bias in global GPP and LAI by 16.3 % and 27.1 %, respectively.

54 ENVIRONMENTAL SCIENCES↗

Iron Impurity Impairs the CO 2 Capture Performance of MgO: Insights from Microscopy and Machine Learning Molecular Dynamics

Magnesium oxide (MgO) is a promising sorbent for direct air capture (DAC) of carbon dioxide. Iron (Fe) is a common impurity in naturally occurring MgO and minerals used to produce MgO, yet a molecular-scale understanding of Fe-doping effects on carbonation is lacking. Here, in this study, we observed reduced carbonation performance in Fe-doped MgO experimentally. The energetics of adsorbing a (bi)carbonate ion on pristine and Fe-doped MgO(001) surfaces were further investigated using ab initio and machine learning potential molecular dynamics coupled with metadynamics simulations. Both pristine and Fe-doped surfaces exhibited a basic (OH – ) hydration layer, where the (bi)carbonate ion adsorption is thermodynamically favorable. However, the dissolution of surface Fe had smaller energy barriers and was more favorable than Mg. Leached Fe likely neutralized the near-surface basicity, yielding reduced reactivity on Fe-doped MgO. Our observations offer critical insights for material selection and emphasize the importance of evaluating the geologic origin of earth materials used for DAC.

36 MATERIALS SCIENCE↗

Influence of nuclear quantum effects on the electronic properties of amorphous carbon

We carry out quantum simulations to study the physical properties of diamond-like amorphous carbon by coupling first-principles molecular dynamics with a quantum thermostat, and we analyze multiple samples representative of different defective sites present in the disordered network. We show that quantum vibronic coupling is critical in determining the electronic properties of the system, in particular its electronic and mobility gaps, while it has a moderate influence on the structural properties. We find that despite localized electronic states near the Fermi level, the quantum nature of the nuclear motion leads to a renormalization of the electronic gap surprisingly similar to that found in crystalline diamond. We also discuss the notable influence of nuclear quantum effects on band-like and variable-hopping mechanisms contributing to electrical conduction. Our calculations indicate that methods often used to evaluate electron–phonon coupling in ordered solids are inaccurate to study the electronic and transport properties of amorphous semiconductors composed of light atoms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A distributed temperature profiling system for vertically and laterally dense acquisition of soil and snow temperature

Abstract. Measuring soil and snow temperature with high vertical and lateral resolution is critical for advancing the predictive understanding of thermal and hydro-biogeochemical processes that govern the behavior of environmental systems. Vertically resolved soil temperature measurements enable the estimation of soil thermal regimes, frozen-/thawed-layer thickness, thermal parameters, and heat and/or water fluxes. Similarly, they can be used to capture the snow depth and the snowpack thermal parameters and fluxes. However, these measurements are challenging to acquire using conventional approaches due to their total cost, their limited vertical resolution, and their large installation footprint. This study presents the development and validation of a novel distributed temperature profiling (DTP) system that addresses these challenges. The system leverages digital temperature sensors to provide unprecedented, finely resolved depth profiles of temperature measurements with flexibility in system geometry and vertical resolution. The integrated miniaturized logger enables automated data acquisition, management, and wireless transfer. A novel calibration approach adapted to the DTP system confirms the factory-assured sensor accuracy of ±0.1 ∘C and enables improving it to ±0.015 ∘C. Numerical experiments indicate that, under normal environmental conditions, an additional error of 0.01 % in amplitude and 70 s time delay in amplitude for a diurnal period can be expected, owing to the DTP housing. We demonstrate the DTP systems capability at two field sites, one focused on understanding how snow dynamics influence mountainous water resources and the other focused on understanding how soil properties influence carbon cycling. Results indicate that the DTP system reliably captures the dynamics in snow depth and soil freezing and thawing depth, enabling advances in understanding the intensity and timing in surface processes and their impact on subsurface thermohydrological regimes. Overall, the DTP system fulfills the needs for data accuracy, minimal power consumption, and low total cost, enabling advances in the multiscale understanding of various cryospheric and hydro-biogeochemical processes.

54 ENVIRONMENTAL SCIENCES↗

Comparison of water nanodroplet properties on different graphite-based substrates

The molecular structure and dynamics of water differ considerably at various interfaces. We compare the interfacial water structure–property relationship on three different carbon substrates, namely, amorphous carbon, compressed expanded natural graphite, and pure graphite by utilizing atomistic molecular dynamics simulations. The effect of different substrates on the structural and dynamical properties of water can readily be observed. Here, the density distributions parallel and normal to the substrates show oblate droplet structures. The normal to the substrate water distribution shows a strong hydration layer at the interface that does not vary with substrates. However, the disparity in the structure and dynamics on three different substrates shows that the surface morphologies of the substrates are critical for determining nanoscale water properties. Furthermore, it is observed that the formation of an interfacial water layer or the hydration layer is a direct consequence of both water “confinement” at the nanoscale and “attraction” between water molecules and the carbon substrates.

42 ENGINEERING↗

Cost-effective carbon fiber precursor selections of polyacrylonitrile-derived blend polymers: carbonization chemistry and structural characterizations

Blending polyacrylonitrile (PAN) with plastic wastes and bio-based polymers provides a convenient and inexpensive method to realize cost-effective carbon fiber (CF) precursors. In this work, PAN-based blend precursors are investigated using ReaxFF reactive molecular dynamics simulations with respect to the formation of all-carbon rings, the evolutions of oxygen-containing and nitrogen-containing species, and the migration of carbon atoms to form turbostratic graphene. From these simulations, we identify that PAN/cellulose (CL) blend manifests the highest carbon yield and the most substantial all-carbon ring formation. This ReaxFF-based finding is confirmed by Raman and TEM experiments indicating high crystallinity for PAN/CL-derived blend CFs. We trace the pathway of gasification and carbonization of PAN/CL to elaborate the mechanism of the formation of all-carbon ring networks. We discover that the acetals of CL can catalyze the cyclization of the blend precursor, allowing for the search for CL derivatives or the other kinds of bio-based polymers with similar functionalities as alternative blends. In addition, we examine the structural characteristics using the carbon–carbon (C–C) radial distribution functions, C–C bond length distributions, and sp2 C atom ratios for the four representative precursors, i.e., PAN, oxidized PAN, PAN/nylon 6,6, and PAN/CL. Our simulation results show the most extensive all-carbon ring cluster and graphitic structure growths for PAN/CL. Here, we propose PAN/CL as a cost-effective alternative CF precursor, since (a) CL is naturally abundant and eco-friendly for production, (b) the blend precursor PAN/CL does not require oxidation treatment, (c) PAN/CL has a high carbon yield with substantial all-carbon ring formation, and (d) PAN/CL based CFs potentially provide a mechanical property enhancement.

36 MATERIALS SCIENCE↗

Thermal Neutron Scattering Cross Sections for Graphitic Amorphous Carbon

Carbon materials are commonly found in both nuclear reactors and experimental systems. Various carbon structures occur in nuclear applications ranging from crystalline and nuclear graphite to the amorphous carbon seen in next-generation advanced reactor designs. Amorphous carbon is based on a randomized graphite-like structure and offers the unique ability to disperse impurities throughout the bulk composition. A graphite-like amorphous carbon system was modeled using the classical molecular dynamics (MD) code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator). An improved version of the temperature-dependent Adaptive Intermolecular Reactive Empirical Bond Order (AIREBO) potential was used to model the carbon-carbon atomic interactions for the temperature at 300 K along with densities 1.60, 1.70, 1.85, and 2.23 g/cm 3 . From the normalized velocity autocorrelation function (VACF), the phonon density of state (DOS) was then calculated as the Fourier transform of the normalized VACF. This DOS was then used as the primary input for the evaluation of the thermal scattering law (TSL, i.e. S(α,β)) and associated neutron thermal scattering cross sections. The TSL was analyzed using the Full Law Analysis Scattering System Hub (FLASSH). The amorphous structure results in shifts of the phonon DOS to lower energy modes than typically displayed for ideal crystalline graphite. This impact on the DOS is directly reflected in the TSL. Furthermore, the typical features and the optical graphitic peak at 0.25 eV for the ideal graphite DOS disappear for graphite-like amorphous carbon, which shows good agreement with the expected structure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Integrated flux and pool size analysis in plant central metabolism reveals unique roles of glycine and serine during photorespiration

Photorespiration is an essential process juxtaposed between plant carbon and nitrogen metabolism that responds to dynamic environments. Photorespiration recycles inhibitory intermediates arising from oxygenation reactions catalysed by Rubisco back into the C 3 cycle, but it is unclear what proportions of its nitrogen-containing intermediates (glycine and serine) are exported into other metabolisms in vivo and how these pool sizes affect net CO 2 gas exchange during photorespiratory transients. Here, to address this uncertainty, we measured rates of amino acid export from photorespiration using isotopically non-stationary metabolic flux analysis. This analysis revealed that ~23–41% of the photorespiratory carbon was exported from the pathway as serine under various photorespiratory conditions. Furthermore, we determined that the build-up and relaxation of glycine pools constrained a large portion of photosynthetic acclimation during photorespiratory transients. Furthermore, these results reveal the unique and important roles of glycine and serine in successfully maintaining various photorespiratory fluxes that occur under environmental fluctuations in nature and providing carbon and nitrogen for metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

A synthesis of methane dynamics in thermokarst lake environments

Greenhouse gas emissions from physical permafrost thaw disturbance and subsidence, including the formation and expansion of thermokarst (thaw) lakes, may double the magnitude of the permafrost carbon feedback this century. These processes are not accounted for in current global climate models. Thermokarst lakes, in particular, have been shown to be hotspots for emissions of methane (CH4), a potent greenhouse gas with 32 times more global warming potential than carbon dioxide (CO2) over a 100-year timescale. Here, we synthesize several studies examining CH4 dynamics in a representative first-generation thermokarst lake (Vault Lake, informal name) to show that CH4 production and oxidation potentials vary with depth in thawed sediments beneath the lake. This variation leads to depth-dependent differences in both in situ dissolved CO2:CH4 ratios and net CH4 production responses to additional warming. Comparing CH4 production, oxidation, and flux values from studies at Vault Lake suggests up to 99% of produced CH4 is oxidized and/or periodically entrapped before entering the atmosphere. We summarize these findings in the context of CH4 literature from thermokarst lakes and identify future research directions for incorporating thermokarst lake CH4 dynamics into estimates of the permafrost carbon feedback.

58 GEOSCIENCES↗

Carbon Dioxide Production in Bedrock Beneath Soils Substantially Contributes to Forest Carbon Cycling

Abstract Soils are widely considered the primary terrestrial organic matter pool mediating carbon transactions with the atmosphere and groundwater. Because soils are both a host and a product of rhizosphere activity, they are thought to mark the location where photosynthetic fixation of carbon dioxide (CO 2 ) is balanced by the oxidation of organic matter. However, in many terrestrial environments, the rhizosphere extends below soils and into fractured bedrock, and it is unknown if the resulting biological and hydrologic dynamics in bedrock have a significant impact on carbon cycling. Here we show substantial production of CO 2 in weathered bedrock at 4–8 m below the thin soils (<0.5 m thick) of a Northern California forest using innovative monitoring technology for sampling gases and water in fractured rock. The deep CO 2 production supports a persistent upward flux of CO 2(g) year‐round from bedrock to soil, constituting between 2% and 29% of the average daily CO 2 efflux from the land surface. When water is rapidly transported across the fractured bedrock vadose zone, nearly 50% of the CO 2 produced in the bedrock dissolves into water, promoting water‐rock interaction and export of dissolved inorganic carbon (DIC) from the unsaturated zone to groundwater, constituting as much as 80% of the DIC exiting the hillslope. Such CO 2 production in weathered bedrock is subject to unique moisture, temperature, biological, and mineralogical conditions which are currently missing from terrestrial carbon models.

54 ENVIRONMENTAL SCIENCES↗

Time-Resolved Probing of the Iodobenzene C-Band Using XUV-Induced Electron Transfer Dynamics

Time-resolved extreme ultraviolet spectroscopy was used to investigate photodissociation within the iodobenzene C-band. The carbon–iodine bond of iodobenzene was photolyzed at 200 nm, and the ensuing dynamics were probed at 10.3 nm (120 eV) over a 4 ps range. Two product channels were observed and subsequently isolated by using a global fitting method. Their onset times and energetics were assigned to distinct electron transfer dynamics initiated following site-selective ionization of the iodine photoproducts, enabling the electronic states of the phenyl fragments to be identified using a classical over-the-barrier model for electron transfer. In combination with previous theoretical work, this allowed the corresponding neutral photochemistry to be assigned to (1) dissociation via the 7B2, 8A2, and 8B1 states to give ground-state phenyl, Ph(X), and spin–orbit excited iodine and (2) dissociation through the 7A1 and 8B2 states to give excited-state phenyl, Ph(A), and ground-state iodine. The branching ratio was determined to be 87 ± 4% Ph(X) and 13 ± 4% Ph(A). Similarly, the corresponding amount of energy deposited into the internal phenyl modes in these channels was determined to be 44 ± 10 and 65 ± 21%, respectively, and upper bounds to the channel rise times were found to be 114 ± 6 and 310 ± 60 fs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lithium Deposition-Induced Fracture of Carbon Nanotubes and Its Implication to Solid-State Batteries

The increasing demand for safe and dense energy storage has shifted research focus from liquid electrolyte-based Li-ion batteries toward solid-state batteries (SSBs). However, the application of SSBs is impeded by uncontrollable Li dendrite growth and short circuiting, the mechanism of which remains elusive. Herein, we conceptualize a scheme to visualize Li deposition in the confined space inside carbon nanotubes (CNTs) to mimic Li deposition dynamics inside solid electrolyte (SE) cracks, where the high-strength CNT walls mimic the mechanically strong SEs. We observed that the deposited Li propagates as a creeping solid in the CNTs, presenting an effective pathway for stress relaxation. When the stress-relaxation pathway is blocked, the Li deposition-induced stress reaches the gigapascal level and causes CNT fracture. Mechanics analysis suggests that interfacial lithiophilicity critically governs Li deposition dynamics and stress relaxation. Furthermore, our study offers critical strategies for suppressing Li dendritic growth and constructing high-energy-density, electrochemically and mechanically robust SSBs.

25 ENERGY STORAGE↗

Estimating CO 2 fluxes through integrating spatial and temporal input layers via deep learning algorithms

Background Accurate estimation of net ecosystem exchange of CO 2 fluxes (Fc) is essential for understanding carbon cycle processes and assessing ecosystem carbon budgets. However, conventional modeling approaches often emphasize temporal dynamics while overlooking the pronounced spatial heterogeneity within the footprint of eddy covariance (EC) towers, potentially limiting predictive accuracy and interpretability of Fc estimates. To address this challenge, we developed a spatiotemporal model that integrates high-resolution footprint-weighted spatial information with sequential environmental drivers. Results The integrated model combines a deeper graph convolutional network to characterize fine-scale spatial variability within EC footprints and a gated recurrent unit network to capture temporal dependencies in biophysical conditions. Using multi-year flux tower observations, remote sensing vegetation indices and footprint modeling, we evaluate the proposed method across three land cover types. This spatiotemporal model consistently outperforms temporal-only and spatial-only baselines, achieving the highest overall accuracy (R 2 = 0.9569) and the lowest RMSE (1.8128 μmol m −2 s −1 ) and MAE (1.1939 μmol m −2 s −1 ). Performance gains are particularly evident in ecosystems with strong vegetation heterogeneity, where spatial structure substantially modulates Fc variability. Conclusions This study demonstrates the importance of joint modeling spatial heterogeneity and temporal dynamics for improving Fc estimation and provides a robust method for advancing footprint-based Fc estimates across diverse ecosystems, supporting refined assessments of terrestrial carbon fluxes, and enhancing scientific foundations for carbon studies.

CO2 flux estimate↗

MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive

This Modeling Archive is in support the publication “Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: A Mechanistic Modeling Analysis” (Liang et al., 2021). Here we provide model code, inputs, outputs and evaluation datasets for the Microbial ENzyme Decomposition (MEND) model for the Missouri Ozarks AmeriFlux eddy covariance measurement site (MOFLUX) near Ashland, Missouri USA. The MEND model was developed with explicit representation of microbial and enzyme pools to mechanistically simulate the role of microbial organisms and extracellular enzymes in soil organic carbon (SOC) decomposition. Long-term SOC dynamics under intensified moisture extremes are studied using the MEND model that is parameterized with 11 years of measurements from the MOFLUX forest. The model explicitly represents microbial dormancy and resuscitation, different types of SOC-degrading enzymes, and how they vary with changes in soil moisture (Wang et al. 2015, 2019). A combination of two levels of frequency and severity of soil moisture, as well as a control with normal interannual variability, are used to simulate a range of moisture scenarios over 100 years. The code of Microbial-ENzyme Decomposition (MEND) as well as the input and output data are included in the archive. A user’s manual (MEND_Readme.pdf) is included with instructions for compiling and running the model to simulate soil organic carbon decomposition under various moisture scenarios. This dataset contains the modelling archive contained within a compressed (*.zip) file, a file-level metadata file in comma separate (*.csv) format, and two instructional files in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗