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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Integration and Quantitative Comparison of Up-Scaled Molecular Observation Network Data with Existing Soil Databases

MONet provides novel soil molecular data to the research community for understanding biogeochemical processes and complementing other soil datasets. This study assesses MONet's ability to replicate known soil patterns via a comparative analysis of soil respiration (Rs), pH, and clay content against benchmark datasets. Results show moderate agreement for pH and clay content, highlighting MONet's strengths in capturing soil biogeochemical variation in underrepresented regions like urban areas. Rs data are marked by the appropriate trends relative to other datasets, but direct comparison is impractical due to methodological differences in underlying data. Strategic sampling is recommended to improve MONet's coverage and eventual utility in bridging molecular observations with global datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ranking Biological Features in Soil-Based Microbial Multi-Omics Data with Integration Modeling

Distinguishing the most important features (e.g. proteins, metabolites, etc.) per group (e.g. control and treatment) is a critical challenge in feature-rich multi-omics experiments, especially in soil data. Traditional feature identification and ranking approaches, such as differential expression, are based on single omics and thus not directly translatable to multi-omics experiments. Here, 5 multi-omics integration models (DIABLO, JACA, MOFA, MultiMLP, and SLIDE) that were not explicitly built for soil data applications were tested using a soil-based multi-omics experiment. The data were obtained from an experimental setup of an autoclaved soil system inoculated with 8 bacteria and using chitin as the carbon source and including samples collected at 0- (control), 4-, 8-, and 12-weeks post-inoculation. The omics data included metaproteomics, 16S rRNA sequencing, and LC-MS/MS metabolomics (in positive and negative mode). Each multi-omics integration model was implemented, and top features were compared to differential univariate statistics per omic type, demonstrating that integration approaches cut the potential number of top features from 2957 identified by differential statistics to 13-224 (a 99.6% to 92.4% reduction). Interestingly, most top features across integration models were not shared; though, scaling and averaging ranks across models shared similar patterns. This work highlights the usefulness of multi-omics integration models in soil-based microbial studies and the power of using multiple integration models together to interpret results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of Multi-Fidelity Soil Moisture Products Across the Continental United States

We have aggregated the most recent soil moisture datasets from a diverse range of sources, encompassing the Continental United States (CONUS). These sources encompass gridded data from remote sensing products, reanalysis products, machine learning-based projects, and land surface modeling products. Additionally, we have obtained and processed in-situ soil moisture observations from the International Soil Moisture Network. The collected datasets exhibit variations in both temporal and spatial resolutions. Among the 20 datasets, six are available at a spatial resolution of 0.25 degrees, while three are at a coarser spatial resolution of 25 km. To minimize spatial interpolation, we conducted data uncertainty evaluations at the 0.25-degree spatial resolution. For our data evaluations, we maintained a monthly temporal resolution, which effectively captures soil moisture seasonality and interannual variability. Our data processing strategy preserves the raw data and interpolated data at their original temporal resolutions. Datasets with higher temporal resolutions, including daily, three-hourly, and hourly datasets, are set aside for subsequent analyses. These analyses will delve into topics such as soil moisture changes and recovery during extreme weather events. Furthermore, we have processed auxiliary data to enhance our evaluation, leveraging tools such as Google Earth Engine. This includes incorporating topography data, land use land cover data, Köppen-Geiger climate classification, and more to provide a comprehensive assessment from multiple sources.

Li, Lingcheng↗
DOE OSTI2020

Niche Differentiation of Bacterial Versus Archaeal Soil Nitrifiers Induced by Ammonium Inhibition Along a Management Gradient

Soil nitrification, mediated mainly by ammonia oxidizing archaea (AOA) and bacteria (AOB), converts ammonium (NH 4 + ) to nitrite (NO 2 – ) and thence nitrate (NO 3 – ). To better understand ecological differences between AOA and AOB, we investigated the nitrification kinetics of AOA and AOB under eight replicated cropped and unmanaged ecosystems (including two fertilized natural systems) along a long-term management intensity gradient in the upper U.S. Midwest. For five of eight ecosystems, AOB but not AOA exhibited Haldane kinetics (inhibited by high NH 4 + additions), especially in perennial and successional systems. In contrast, AOA predominantly exhibited Michaelis-Menten kinetics, suggesting greater resistance to high nitrogen inputs than AOB. These responses suggest the potential for NH 4 + -induced niche differentiation between AOA and AOB. Additionally, long-term fertilization significantly enhanced maximum nitrification rates (V max ) in the early successional systems for both AOA and AOB, but not in the deciduous forest systems. This was likely due to pH suppression of nitrification in the acidic forest soils, corroborated by a positive correlation of V max with soil pH but not with amoA gene abundance. Results also demonstrated that soil nitrification potentials were relatively stable, as there were no seasonal differences. Overall, results suggest that (1) NH 4 + inhibition of AOB but not AOA could be another factor contributing to niche differentiation between AOA and AOB in soil, and (2) nitrification by both AOA and AOB can be significantly promoted by long-term nitrogen inputs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Microbial Communities Influence Soil Dissolved Organic Carbon Concentration by Altering Metabolite Composition

Rapid microbial growth in the early phase of plant litter decomposition is viewed as an important component of soil organic matter (SOM) formation. However, the microbial taxa and chemical substrates that correlate with carbon storage are not well resolved. The complexity of microbial communities and diverse substrate chemistries that occur in natural soils make it difficult to identify links between community membership and decomposition processes in the soil environment. To identify potential relationships between microbes, soil organic matter, and their impact on carbon storage, we used sand microcosms to control for external environmental factors such as changes in temperature and moisture as well as the variability in available carbon that exist in soil cores. Using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) on microcosm samples from early phase litter decomposition, we found that protein- and tannin-like compounds exhibited the strongest correlation to dissolved organic carbon (DOC) concentration. Proteins correlated positively with DOC concentration, while tannins correlated negatively with DOC. Through random forest, neural network, and indicator species analyses, we identified 42 bacterial and 9 fungal taxa associated with DOC concentration. The majority of bacterial taxa (26 out of 42 taxa) belonged to the phylum Proteobacteria while all fungal taxa belonged to the phylum Ascomycota. Additionally, we identified significant connections between microorganisms and protein-like compounds and found that most taxa (12/14) correlated negatively with proteins indicating that microbial consumption of proteins is likely a significant driver of DOC concentration. This research links DOC concentration with microbial production and/or decomposition of specific metabolites to improve our understanding of microbial metabolism and carbon persistence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Substrate Utilization and Competitive Interactions Among Soil Bacteria Vary With Life-History Strategies

Microorganisms have evolved various life-history strategies to survive fluctuating resource conditions in soils. However, it remains elusive how the life-history strategies of microorganisms influence their processing of organic carbon, which may affect microbial interactions and carbon cycling in soils. Here, we characterized the genomic traits, exometabolite profiles, and interactions of soil bacteria representing copiotrophic and oligotrophic strategists. Isolates were selected based on differences in ribosomal RNA operon ( rrn ) copy number, as a proxy for life-history strategies, with pairs of “high” and “low” rrn copy number isolates represented within the Micrococcales, Corynebacteriales, and Bacillales. We found that high rrn isolates consumed a greater diversity and amount of substrates than low rrn isolates in a defined growth medium containing common soil metabolites. We estimated overlap in substrate utilization profiles to predict the potential for resource competition and found that high rrn isolates tended to have a greater potential for competitive interactions. The predicted interactions positively correlated with the measured interactions that were dominated by negative interactions as determined through sequential growth experiments. This suggests that resource competition was a major force governing interactions among isolates, while cross-feeding of metabolic secretion likely contributed to the relatively rare positive interactions observed. By connecting bacterial life-history strategies, genomic features, and metabolism, our study advances the understanding of the links between bacterial community composition and the transformation of carbon in soils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Model and remote-sensing-guided experimental design and hypothesis generation for monitoring snow-soil–plant interactions

In this study, we develop a machine-learning (ML)-enabled strategy for selecting hillslope-scale ecohydrological monitoring sites within snow-dominated mountainous watersheds, with a particular focus on snow-soil–plant interactions. Data layers rely on spatial data layers from both remote sensing and hydrological model simulations. Specifically, a Landsat-based foresummer drought sensitivity index is used to define the dependency of the annual peak plant productivity on the Palmer drought severity index in the early growing season. Hydrological simulations provide the spatiotemporal dynamics of near-surface soil moisture and snow depth. In this framework, a regression analysis identifies the key hydrological variables relevant to the spatial heterogeneity of drought sensitivity. We then apply unsupervised clustering to these key variables, using the Gaussian mixture model, to group hillslopes into several zones that have divergent relationships regarding soil moisture, snow dynamics, and drought sensitivity. Using the datasets collected in the East River Watershed (Crested Butte, Colorado, United States), results show that drought sensitivity is significantly correlated with model-derived soil moisture and snow-free timing over space and time. The relationship is, however, non-linear, such that the correlation decreases above a threshold elevation and in a heavy snow year due to large snowpacks, lateral flow, and soil storage limitations. Clustering is then able to define the zones that have high or low sensitivity to drought, as well as the mid-elevation regions where sensitivity is associated with the topographic aspect and net potential radiation. In addition, the algorithm identifies the most representative hillslopes with road/trail access within each zone for installing monitoring sites. Our method also aims to significantly increase the use of ML and model-simulation results to guide critical zone and watershed monitoring activities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Effect of Rapid Development on Soil CO2 Efflux in a Cellulosic Biofuel Stand

As awareness of climate change increases, the need for carbon neutral fuel sources is growing. Lignocellulosic biofuel derived from pine trees has been suggested as one potential energy source; however, it requires more research before its efficacy for climate change mitigation can be determined. Due to the large share of forest carbon held in soils and the extensive area of pine plantations in the southeast U.S., a better understanding of plantation soil carbon dynamics is critical for biofuel carbon accounting. This study evaluated the effects of canopy development and productivity on soil CO2 efflux, a proxy for soil respiration (Rs), in an intensively managed loblolly pine (Pinus taeda) stand over a period from May 2015 to December 2019. We found that leaf area index (LAI) and gross ecosystem production (GEP), as well as meteorological variables, had significant effects on Rs, but that both overall Rs and soil carbon pools did not increase over the course of the study. We thus hypothesize that GEP and LAI had intra-annual effects on Rs, and that the lack of change in Rs is the result of an increase in autotrophic respiration (Ra) that offset a decrease in decomposition of the previous stand’s organic matter.

09 BIOMASS FUELS↗
DOE OSTI2020

Coming-of-Age Characterization of Soil Viruses: A User’s Guide to Virus Isolation, Detection within Metagenomes, and Viromics

The study of soil viruses, though not new, has languished relative to the study of marine viruses. This is particularly due to challenges associated with separating virions from harboring soils. Generally, three approaches to analyzing soil viruses have been employed: (1) Isolation, to characterize virus genotypes and phenotypes, the primary method used prior to the start of the 21st century. (2) Metagenomics, which has revealed a vast diversity of viruses while also allowing insights into viral community ecology, although with limitations due to DNA from cellular organisms obscuring viral DNA. (3) Viromics (targeted metagenomics of virus-like-particles), which has provided a more focused development of ‘virus-sequence-to-ecology’ pipelines, a result of separation of presumptive virions from cellular organisms prior to DNA extraction. This separation permits greater sequencing emphasis on virus DNA and thereby more targeted molecular and ecological characterization of viruses. Employing viromics to characterize soil systems presents new challenges, however. Ones that only recently are being addressed. Here we provide a guide to implementing these three approaches to studying environmental viruses, highlighting benefits, difficulties, and potential contamination, all toward fostering greater focus on viruses in the study of soil ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Data from: Niche differentiation of bacterial versus archaeal soil nitrifiers induced by ammonium inhibition along a management gradient

Soil nitrification, mediated mainly by ammonia oxidizing archaea (AOA) and bacteria (AOB), converts ammonium (NH4+) to nitrite (NO2−) and thence nitrate (NO3−). To better understand ecological differences between AOA and AOB, we investigated the nitrification kinetics of AOA and AOB under eight replicated cropped and unmanaged ecosystems (including two fertilized natural systems) along a long-term management intensity gradient in the upper U.S. Midwest. For five of eight ecosystems, AOB but not AOA exhibited Haldane kinetics (inhibited by high NH4+ additions), especially in perennial and successional systems. In contrast, AOA predominantly exhibited Michaelis-Menten kinetics, suggesting greater resistance to high nitrogen inputs than AOB. These responses suggest the potential for NH4+-induced niche differentiation between AOA and AOB. Additionally, long-term fertilization significantly enhanced maximum nitrification rates (Vmax) in the early successional systems for both AOA and AOB, but not in the deciduous forest systems. This was likely due to pH suppression of nitrification in the acidic forest soils, corroborated by a positive correlation of Vmax with soil pH but not with amoA gene abundance. Results also demonstrated that soil nitrification potentials were relatively stable, as there were no seasonal differences. Overall, results suggest that (1) NH4+ inhibition of AOB but not AOA could be another factor contributing to niche differentiation between AOA and AOB in soil, and (2) nitrification by both AOA and AOB can be significantly promoted by long-term nitrogen inputs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A 1 km soil moisture dataset over eastern CONUS generated by assimilating SMAP data into the Noah-MP land surface model

An improved fine-scale soil moisture (SM) dataset at 1 km grid spacing, covering much of the eastern continental US, was generated by assimilating 9 km Soil Moisture Active Passive (SMAP) SM data into the v4.0.1 Noah-MP land surface model. With 12 ensemble members, the assimilation was carried out using the ensemble Kalman filter algorithm within NASA's Land Information System. The SM analysis for 2016 was fully validated against in situ observations from four different networks and compared with four other existing datasets. Results indicate that this SM analysis surpasses other datasets in top-layer SM distribution, including a machine-learning-based product, despite all SM estimates being less heterogeneous than observed. The analysis of anomalous errors suggests that large similarity in intrinsic errors is likely due to overlapping data sources among the selected SM datasets. More detailed evaluations were performed over two geographic areas. The observations collected by the Atmospheric Radiation Measurement facility in Oklahoma suggest that soil temperature and surface heat fluxes are concurrently simulated with good accuracy. Investigation into the 2016 southeastern US drought response further indicates drier conditions and higher evapotranspiration estimates compared to GLEAMv4.1. Notably, large errors are associated with grids having clay soil textures, underscoring the need for refined model treatments for specific soil types to further improve SM estimates. The dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.14370563 (Tai et al., 2024).

Tai, Sheng-Lun [Pacific Northwest National Laborat↗
DOE OSTI2025

Soil oxygen dynamics: a key mediator of tile drainage impacts on coupled hydrological, biogeochemical, and crop systems

Tile drainage removes excess water and is an essential, widely adopted management practice to enhance crop productivity in the US Midwest and throughout the world. Tile drainage has been shown to significantly change hydrological and biogeochemical cycles by lowering the water table and reducing the residence time of soil water, although examining the complex interactions and feedbacks in an integrated hydrology–biogeochemistry–crop system remains elusive. Oxygen dynamics are critical to unraveling these interactions and have been ignored or oversimplified in existing models. Understanding these impacts is essential, particularly so because tile drainage has been highlighted as an adaptation under projected wetter springs and drier summers in the changing climate in the US Midwest. We used the ecosys model that uniquely incorporates first-principle soil oxygen dynamics and crop oxygen uptake mechanisms to quantify the impacts of tile drainage on hydrological and biogeochemical cycles and crop growth in corn–soybean rotation fields. The model was validated with data from a multi-treatment, multi-year experiment in Washington, IA. The relative root mean square error (rRMSE) for the corn and soybean yield in validation is 5.66 % and 12.57 %, respectively. The Pearson coefficient (r) of the monthly tile flow during the growing season is 0.78. Plant oxygen stress turns out as an emergent property of the equilibrium between the soil oxygen supply and biological demand. The impact of tile drainage on the system is achieved through a series of coupled feedback mechanisms. The model results show that tile drainage reduces the soil water content and enhances soil oxygenation. It additionally increases the subsurface discharge and elevates inorganic nitrogen leaching, with seasonal variations influenced by climate and crop phenology. The improved aerobic condition alleviates crop oxygen stress during wet springs, thereby promoting crop root growth during the early growth stage. The development of greater root density, in turn, mitigates water stress during dry summers, leading to an overall increase in the crop yield by ∼6 %. These functions indicate the potential of tile drainage in bolstering crop resilience to climate change and the use of this modeling tool for large-scale assessments of tile drainage. The model reveals the underlying causal mechanisms that drive the agroecosystem response to drainage on the coupled hydrology, biogeochemistry, and crop system dynamics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Calcium is associated with specific soil organic carbon decomposition products

Abstract. Calcium (Ca) may contribute to the preservation of soil organic carbon (SOC) in more ecosystems than previously thought. Here, we provide evidence that Ca is co-located with SOC compounds that are enriched in aromatic and phenolic groups, across different acidic soil types and locations with different ecosystem properties, differing in terms of climate, parent material, soil type, and vegetation. In turn, this co-localised fraction of Ca–SOC is removed through cation exchange, and the association is then only re-established during decomposition in the presence of Ca (Ca addition incubation). Thus, this highlights a causative link between decomposition and the co-location of Ca with a characteristic fraction of SOC. Decomposition increases the relative proportion of negatively charged functional groups, which can increase the propensity for the association between SOC and Ca; in turn, this association can inhibit dissolved organic carbon export or further decomposition. We propose that this mechanism could be driven by Ca hotspots at the microscale shifting local decomposition processes and thereby explaining the co-location of Ca with SOC of a specific composition across different acidic soil environments. Incorporating this biogeochemical process into Earth system models could improve our understanding, predictions, and management of carbon dynamics in soils, as well as accounting for their response to Ca-rich amendments.

Rowley, Mike C. (ORCID:0000000224407855)↗
DOE OSTI2022

Lower functional redundancy in “narrow” than “broad” functions in global soil metagenomics

Understanding the relationship between soil microbial taxonomic compositions and functional profiles is essential for predicting ecosystem functions under various environmental disturbances. However, even though microbial communities are sensitive to disturbance, ecosystem functions remain relatively stable, as soil microbes are likely to be functionally redundant. Microbial functional redundancy may be more associated with “broad” functions carried out by a wide range of microbes than with “narrow” functions in which specific microorganisms specialize. Thus, a comprehensive study to evaluate how microbial taxonomic compositions correlate with broad and narrow functional profiles is necessary. Here, we evaluated soil metagenomes worldwide to assess whether functional and taxonomic diversities differ significantly between the five broad and the five narrow functions that we chose. Our results revealed that, compared with the five broad functions, soil microbes capable of performing the five narrow functions were more taxonomically diverse, and thus their functional diversity was more dependent on taxonomic diversity, implying lower levels of functional redundancy in narrow functions. Co-occurrence networks indicated that microorganisms conducting broad functions were positively related, but microbes specializing in narrow functions were interacting mostly negatively. Our study provides strong evidence to support our hypothesis that functional redundancy is significantly different between broad and narrow functions in soil microbes, as the association of functional diversity with taxonomy was greater in the five narrow than in the five broad functions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

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↗
DOE OSTI2023

Mycorrhiza Better Predict Soil Fungal Community Composition and Function than Aboveground Traits in Temperate Forest Ecosystems

Forests in the northeastern US are experiencing shifts in community composition due to the northward migration of warm-adapted tree species and certain species’ declines (for example, white ash and eastern hemlock) due to invasive insects. Changes in belowground fungal communities and associated functions will inevitably follow. Therefore, we sought to investigate the relative importance of two important tree characteristics—mycorrhizal type [ectomycorrhizal (EcM) or arbuscular mycorrhizal (AM)] and leaf habit (deciduous or evergreen) on soil fungal community composition and organic matter cycling. We sampled soil in the organic and mineral horizons beneath two AM-associated (Fraxinus americana and Thuja occidentalis) and two ECM-associated tree species (Betula alleghaniensis and Tsuga canadensis), with an evergreen and deciduous species in each mycorrhizal group. To characterize fungal communities and organic matter decomposition beneath each tree species, we sequenced the ITS1 region of fungal DNA and measured the potential activity of carbon- and nitrogen-targeting extracellular enzymes. Each tree species harbored distinct fungal communities, supporting the need to consider both mycorrhizal type and leaf habit. However, between tree characteristics, mycorrhizal type better predicted fungal communities. Across fungal guilds, saprotrophic fungi were the most important group in shaping fungal community differences in soils beneath all tree species. The effect of leaf habit on carbon- and nitrogen-targeting hydrolytic enzymes depended on tree mycorrhizal association in the organic horizon, while oxidative enzyme activities were higher beneath EcM-associated trees across both soil horizons and leaf habits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Quantifying spatial and vertical variations in soil C:N relationships in permafrost-affected landscapes

Permafrost regions are experiencing rapid changes that affect carbon (C) and nitrogen (N) cycles, with implications for vegetation dynamics and gas exchanges with the atmosphere. Soil C:N ratio is a key indicator of organic matter quality, yet spatial estimates of N stocks and C:N ratios lag behind those for C. We used quantile regression forests to compare direct and indirect digital soil mapping approaches for predicting soil C:N ratios at 0–30, 30–60, and 60–100 cm depths across a latitudinal transect in Alaska. The indirect approach – deriving C:N from separately predicted C and N stocks – outperformed direct mapping for the surface layer (0–30 cm), while direct mapping was marginally better at greater depths. However, prediction accuracy decreased with depth for both methods. Temperature and topography were the most important predictors. Both approaches overestimated low and underestimated high C:N ratios, with direct mapping showing greater bias. Our results underscore the challenges of modeling C:N ratios in heterogeneous, data-sparse permafrost soils, but also suggest that indirect mapping holds promise if supported by more extensive datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Carbon sequestration into lime-stabilized soils: Engineering and mineralogical characterization

Stabilizing weak clayey soils with lime is an effective method for improving the mechanical properties of soil. However, lime production is an energy-intensive process producing significant CO 2 emissions in lime-stabilized soils, which can be counteracted through accelerated carbonation that enhances its engineering performance. The present study evaluates accelerated carbonation of lime-treated soils by adding gaseous (CO 2 -rich gas), liquid (water-CO 2 mixture), and solid (sodium bicarbonate) CO 2 sources. Results indicated that samples carbonated with gaseous CO 2 exhibited 100% lime carbonation, while samples treated with solid and aqueous sources of CO 2 had a mean lime carbonation of 60% and 40%, respectively. Further, all lime-treated-carbonated samples exhibited a mean 50% increase in unconfined compressive strength compared to the untreated samples after a 7-day curing period. Durability evaluation through cyclic wetting and drying indicated that the carbonated samples had higher durability than the untreated samples. X-ray computed tomography showed that adding solid and liquid sources of CO 2 facilitated the flocculation of montmorillonite, reducing the porosity. However, a higher dosage of solid CO 2 induced clay dispersion, increasing the porosity. X-ray diffraction and thermogravimetric analysis verified CO 2 sequestration through the formation of calcite, a thermodynamically stable polymorph of calcium carbonate.

58 GEOSCIENCES↗