Expert elicitation on agricultural enhanced weathering highlights CO2 removal potential and uncertainties in loss pathways

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The true scale of potential CDR remains difficult to constrain due to its complexity across the entire field-to-ocean pathway and a paucity of system-level empirical data. We used a formal expert elicitation process to quantify the ranges of best CDR estimates, uncertainties, and key data needs for six EW feedstocks. Expert opinion of the CDR potential varied by feedstock, with estimates averaging 0.2-0.7 Gt CO2e/yr, but with a wide range (less than zero to greater than 5 Gt CO2e/yr). The efficiency of CDR, meaning the fraction of potential CDR ultimately realized from a given amount of material applied ranged from 27-39%. Key constraints included feedstock availability at scale (especially for wollastonite), calcite saturation, secondary clay formation, and deep soil/freshwater emission pathways. The results suggest a strong need for additional data collection (given deployments are already occurring), leveraging existing data on liming where appropriate, and continued study as applications occur at scale. Overall, there appears to be significant CDR potential for EW at broad scales, though quantification and underlying data uncertainties are significant and should be resolved. Earth and environmental sciences/Biogeochemistry/Carbon cycle Earth and environmental sciences/Environmental sciences/Environmental chemistry Earth and environmental sciences/Planetary science/Geochemistry Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Slowing the pace of global climate change will require a combination of rapid emissions reductions and carbon dioxide (CO 2 ) removal (CDR) to limit future warming and reduce greenhouse gas (GHG) concentrations already in the atmosphere (IPCC 2023 ). However, few CDR technologies can achieve durable carbon (C) sequestration (i.e., > 100 years) at a sufficient scale and pace needed to meet projected CDR demands (Field and Mach 2017 , Lamb et al. 2024 ). Enhanced weathering (EW) has the potential to be a broadly applicable CDR technology with long-term, durable storage. The EW approach focuses on accelerating the natural process of rock weathering, which is known to be an important control on long-term (ca million year) atmospheric CO 2 levels. However, the ability to accelerate weathering rates at large scales remains an outstanding question, one that requires consideration of feedstock availability and energy inputs (Strefler, 2018), land system response (Goll et al., 2021 ), efficiency of CDR across the land-to-sea continuum (Ilyina et al., 2013 ), and the potential for adverse environmental impacts (Levy et al., 2024 ) Enhanced weathering exposes the feedstock, such as finely ground cation-rich material, to environments conducive to rapid weathering processes, often agricultural soils (Anthony et al. 2025 , Hartmann et al. 2013 , Vakilifard et al. 2021 , Beerling et al. 2020 ). In soil, the finely ground materials undergo chemical dissolution reactions driven by carbonic acids, converting CO 2 in the soil into bicarbonate ions and releasing base cations, such as Ca 2+ and Mg 2+ . The bicarbonate may be precipitated as carbonates in situ or transported to the ocean for long-term storage (e.g., as alkalinity, or incorporated into shells as calcium carbonate). While the process of CDR above is well established through decades of research on natural weathering (Berner and Maasch 1996 ; Gaillardet et al., 1999 ; Caldiera 1995., Caves et al., 2016 ), it remains unclear the extent to which large-scale deployment of EW could contribute meaningfully to the magnitude of carbon removal necessary to achieve climate targets under the Paris Agreement (e.g., well below 2˚C warming). Estimates of global weathering rates are derived from both measurements of riverine fluxes and earth systems models, and are typically divided between silicate weathering and carbonate weathering, with silicate weathering constrained to transfer between 0.33 to 0.51 Gt CO 2 /yr from the atmosphere to the oceans, compared to carbonate weathering rates of 0.48 to 1.39 Gt CO 2 /yr (Hilton and West 2020 ), though there are many poorly constrained processes and high uncertainties remaining (e.g., groundwater fluxes, Zhang and Planavsky 2019 ). For comparison, estimates of EW CDR capacity using silicate rocks ranges from 0.5 to > 4 Gt CO 2 e y − 1 (e.g., Smith et al. 2016 , Fuss et al. 2018 , Strefler et al. 2018 , Beerling et al. 2020 , Fuhrman et al. 2023 ). Integrated assessment models (IAMs) typically assume that enhanced weathering could contribute removals of around 2–4 Gt CO2/yr by 2050 (e.g., Minx et al. 2018 ; Fuss et al. 2018 ; Brack and King 2021 ; Hepburn et al. 2019 ). Projections for 2100 span a much wider range, of 0.5 up to 27 Gt CO 2 e/yr, with an average estimate of approximately 6 Gt CO 2 e/yr due to variation across scenarios and underlying assumptions (e.g., Brack & King 2021 ; Mühlbauer et al. 2025 ). Thus far, however, these estimates are largely derived from models rather than empirical data, often assume maximum adoption and deployment, and do not always consider geochemical limits of EW. Weathering, especially with the aim of long-term CDR, is a complex process that requires a full system perspective to evaluate. Many rock materials are under consideration for EW. Agricultural lime (aglime) is typically dominated by calcium carbonate, though other materials like dolomite can be included, and has been used for millennia to adjust pH in acidic soils. Interest in the C uptake potential of silicates like olivine, basalt, and wollastonite has recently increased (Renforth et al. 2015 , te Pas et al. 2023 ). Recycled materials, especially steel slag and cement waste (Yoshioka et al. 2022 ), are also being explored for this purpose. Each material has unique properties that feed into its overall CDR potential. In particular, feedstocks differ in terms of their CO 2 capture efficiency, potential to form secondary minerals (e.g., secondary clay formation vs carbonates), biological reactions, and side effects such as metal accumulation in vegetation, soils, or waterways (Abdalqadir et al. 2024 ). Multiple factors determine the real-world potential of EW. Feedstock availability is a significant question: to reach the gigatonne CDR scale, the quarrying and mining of EW feedstocks at a similar scale as the production of crushed stone (1.6 Gt), sand and gravel (1 Gt), and construction aggregate (2.5 Gt) in the United States (USGS, 2025 ) would be needed The rate, completeness, and mode (e.g., carbonic acid vs. nitric acid weathering) of the feedstock weathering reaction is a significant driver of overall efficiency (Deng et a. 2023, Baek et al. 2023 , Edwards et al. 2017 ). Once the material is completely weathered (or as completely as conditions/feedstocks allow), there are multiple downstream loss processes that can reduce the efficacy of EW for climate benefit. Precipitation of secondary minerals can reduce CDR efficiency by generating acidity and consuming base cations, resulting in the conversion of bicarbonate back to CO 2 (Bertagni and Porporato 2022 , Vienne et al. 2025 ). Carbon losses during river transport may also impact the net CDR potential of EW. Secondary carbonate formation in rivers, triggered by increased carbonate saturation states, could reduce efficiency (Knapp and Tipper 2022 ). Uncertainty in the significance of these loss pathways is still high. For example, Zhang et al. ( 2022 , 2025 ) suggest that river transport may not significantly limit EW’s CDR potential in most rivers in the US, though these estimates are chemistry-focused and do not always include the full suite of potentially relevant processes (e.g., biological carbon uptake, Neumann et al. 2025 ). There are limited estimates of the fate of weathering products in nearshore environments and the oceans (Kanzaki et al., 2023 ; Beerling et al., 2025 ). Overall, for EW to be a reliable means for quantifiable CDR, the entire system efficiency needs to be reliably evaluated. Although not directly relevant to CDR, aspects of EW increase its viability as a scalable practice, further driving interest. As the weathering reaction progresses in frequently acidified agricultural soils, an EW-induced increase in soil pH may typically raise nutrient availability (at least up a pH of ~ 7; Amann and Hartmann 2019 ), improve crop yields (e.g., Li et al. 2019 , Abdalqadir et al. 2024 ), reduce soil N 2 O production (Chiaravalloti et al. 2023 ), and improves air quality (Beerling et al. 2025 ). Potential challenges also exist, however. For example, there are concerns that some EW feedstocks contain heavy metal elements (e.g., nickel, cadmium), which can accumulate in soils and impact crop health and food safety (Dupla et al. 2023 , Levy et al. 2024 ). In addition, potential interactions with the soil organic carbon (SOC) reservoir have not been well documented for many of the potential feedstocks. Enhanced weathering in any one site may reduce or enhance the land organic C sink, and these effects are both site, feedstock, and time dependent (Buss et al. 2024 , Sokol et al. 2024 ). Biological system interactions with the EW process are also highly variable, both positively and negatively (Wang et al. 2021 , Vicca et al. 2022 , Niron et al. 2024 ). The balance of these tradeoffs will determine both EW’s viability as a CDR pathway and its sustainability if scaled. Tens of millions of tons of agricultural lime (“aglime,” carbonate minerals) are currently added every year to soils (e.g., West and McBride, 2005 ) for agronomic benefits currently. Although substantial uncertainty of system-level CDR efficacy remains, commercial projects spreading cation-rich rocks in agricultural have begun being funded via the voluntary carbon market (carbon crediting). Having confidence in the value of EW-based GHG offsets requires a critical evaluation of the robustness of EW as a real climate solution. Claims that fail to deliver on their system-level CDR promise – for example, if a significant fraction of initially fixed C were lost during aquatic transport stages – will result in unintended and untracked emissions to the atmosphere. Given poorly constrained uncertainties about multiple aspects of the EW process, we pursued a formal expert elicitation ( sensu Morgan 2014 ) to identify the magnitude of potential CDR via EW in agriculture, and to highlight the most critical research gaps surrounding CDR efficiency along the soil to ocean continuum. Expert elicitations are intended to incorporate both the full spectrum of available data, as well as expert opinion on that data. The process addressed multiple questions which are key to the scalability and climate value of EW in agriculture, including: What is the potential global climate impact of EW via inorganic C removal, considering supply chain, feedstock type and availability, and emissions of other GHGs? What is the efficiency of C capture at the field scale, and of transport from the field to long-term ocean storage, both in total and by process stage (Fig. 1 )? What level of uncertainty is expected in quantifying capture and transport efficiency? How do the sources and magnitudes of error influence whether models or empirical data (or a mix) are most appropriate for monitoring? Are there significant health or environmental impact concerns if EW is scaled, and for which feedstocks? Because the responses are feedstock dependent, these questions were addressed independently for each of six feedstocks: lime, basalt, olivine-rich rock, wollastonite-rich rock, steel slag, and concrete waste. Results Overall, global annual CDR rate estimates via agricultural EW – which encompass constraints on feedstock production, land availability, as well as non-target GHG emissions associated with rock grinding, changes in soil biogeochemistry, and other factors – varied by feedstock. Throughout, note that positive values will refer to a CO 2 sink (e.g., removal from the atmosphere) and negative values to emissions to the atmosphere. Individual estimates of the most likely amount of CDR ranged substantially, from a source of -0.1 Gt CO 2 e yr − 1 to a sink of + 4.0 Gt CO 2 e yr − 1 (Fig. 2 A, circles). Estimates of the minimum possible amount of CDR ranged from a source of -2.0 Gt CO 2 e yr − 1 (the lowest option provided in the survey) to a sink of 1.0 Gt CO 2 e yr − 1 , while estimates for the maximum possible amount of CDR ranged from 0 Gt CO 2 e yr − 1 to > 5.0 Gt CO 2 e yr − 1 (For individual responses, see SI1; for the survey instrument see SI2). Mean and median values (presented as “mean/median” below) for group estimates of the maximum and most likely amount of CDR were greatest for basalt and smallest for wollastonite. For basalt, the maximum possible CDR was 2.1 (mean) / 2.0 (median) Gt CO 2 e yr − 1 , while the most likely amount of CDR was 0.7/0.4 Gt CO 2 e yr − 1 . For wollastonite, the maximum possible CDR was 0.9/0.1 Gt CO 2 e yr − 1 , while the most likely amount of CDR was 0.2/0.01 Gt CO 2 e yr − 1 . Means and medians for agricultural lime were close to basalt for the maximum and most likely amount of CDR, while those for the other feedstocks clustered together and fell between that of wollastonite and agricultural lime. For all feedstocks, the mean and median estimate for the minimum amount of CDR intersected zero (i.e., no C removal). Confidence, meaning the likelihood that the true value was within the estimated ranges, was generally low. It was, across the group, lowest for concrete waste (66% / 60%) and highest for basalt (74%/75%), corresponding to roughly 2:1 to 3:1 odds that the real value is within the estimated ranges. For individual ranges with confidence, see Fig. 2 . For individual feedstock global estimates, see SI3 Table 1. We found little relationship between the magnitude of the estimate for the most likely amount of CDR and confidence in the overall range (SI3 Fig. 1 ). Efficiency (transfer potential) The fraction of a hypothetical 10 tons ha − 1 of fixed CO 2 moving from the field to the ocean over 20 years (and with 100 year minimum retention time in the ocean) was broadly similar among feedstocks – approximately 1/3 – but with high variability in individual estimates (Fig. 2 B). On average, estimates for the most likely amount of C removed as durable CDR given a theoretical potential of 10 tons C fixed ha − ranged from 2.7 ton ha − 1 for lime (e.g., 27%) to 3.9 ton ha − 1 for wollastonite (e.g., 39%). Low range estimates were around 1 ton ha − 1 (lowest for lime with 0.6 tons ha − 1 , or a 6% efficiency); high range estimates spanned from 5.6 ton ha − 1 (lime) to 7 ton ha − 1 for wollastonite. Some individual responses were lower and higher, reflecting disagreement across respondents. Confidence in those ranges was approximately 70%, regardless of feedstock (approximately 2:1 odds the true value is actually within those ranges). For responses on all feedstocks, including confidence estimates, see SI3 Table 2. At the stage level, efficiency estimates were lowest (i.e., most fixed C lost) in earlier stages and highest in latter stages regardless of feedstock (Fig. 3 ). The 5th – 95th estimates of C fixed and moving through the field averaged (across all feedstocks) from 21–76%, with a mean of 46%. For all responses on individual stages and feedstocks, including confidence, see SI3 Table S3 . Other Measurement error associated with CDR was consistently estimated as approximately 100% regardless of feedstock or stage (meaning that the uncertainty equals the magnitude of potential carbon removal). This response encompassed both empirical and current modeling uncertainties, though the deep soil and coastal ocean stages were frequently estimated to have > 100% error in measurement. This pattern was independent of feedstock (SI3 Fig. 2 ). The potential for significant health or environmental damage if deployed at scale varied substantially by feedstock, though generally declined when moving downstream from the field. Agricultural lime had the lowest estimated potential for damage regardless of stage (though experts expressed slightly higher concerns for freshwater systems, specifically). In contrast, steel slag and olivine had higher values across the stages, with the highest concerns for both at the field scale (Fig. 4 ). Experts were split on the level of empirical monitoring or modeling needed for monitoring, measurement, reporting, and validation for the voluntary carbon market. At the field scale, nearly half suggested that modeling would be sufficient, though another third thought empirical measurements should be required. Overall, the trend was a preference for more empirical measures at the field and soil stage, moving towards a greater modeling emphasis at later stages. To better constrain the global CDR potential of EW, experts cited the need for a better understanding of soil organic carbon and microbial responses in various geographic settings, more information about feedstock availability, and additional focus on poorly studied loss pathways beyond field application: secondary clay formation, carbonate precipitation rates, biological pathways, and downstream degassing were identified as significant unknowns that would tighten uncertainty bands if they could be resolved. For all qualitative responses on datasets to resolve uncertainties, see the individual responses in SI1. Discussion The expert elicitation estimated that the global potential for CDR from agricultural EW ranged from 0.2 to 0.7 Gt (median 0.01–0.4) CO 2 e yr − 1 depending on feedstock. Basalt and lime had the highest average estimated potential globally. However, experts also identified the potential for lime, basalt and olivine to be a source of C emissions, depending on lifecycle emissions and CDR efficacy. There was marked uncertainty and substantial variation in estimates (Fig. 2 ). In general, however, the preponderance of experts indicated a net positive CDR potential for all feedstocks. This result aligns with the estimates of overall transport efficiency from field to long term storage, which averaged from ~ 27–39%. Estimates were generally lower than the prevailing literature estimates (e.g., 0.5–3.6 Gt yr − 1 , Smith et al. 2016 , Beerling et al. 2020 , Reershemius et al. 2023 ; review in Power et al. 2025). The lower estimates in this study may reflect recent field studies that demonstrate strong constraints on the export of weathering products from soils, as well as potential downstream (post-field) loss processes not yet incorporated (or simplified) into transport models (Laruelle et al. 2017 , Zhang et al. 2025 , Neumann et al. 2025 ). Lower estimates were, in some cases, guided by the low efficiencies implied by the global rate of natural CO 2 consumption by silicate weathering (~ 0.5 CO 2 e yr − 1 ; Gaillardet et al. 1999 ) and by the fraction of total silicate weathering associated with weathering of basaltic rocks on Earth today (0.04 to 0.07 Gt CO 2 /yr, Hartmann et al., 2009 , Dessert et al., 2003 ). Supply constraints, which were considered for the global estimates (Fig. 2 a), are also not always incorporated in global modelling studies. The supplies of lime, basalt, and olivine are effectively unlimited (even if production would need to increase, Hartmann and Moosdorf 2012 , Geerts et al. 2025 ). Concrete waste is substantial, and towards 600 million tons in the US alone (however, estimates include all construction waste so the true number is likely lower; EPA 2025 ). Steel slag is more constrained, though significant; Gao et al. ( 2023 ) estimates an annual production of 120 Mt in China and industry estimates more than 400 Mt per year globally (Worldsteel 2021 ). In contrast, current production of wollastonite is approximately 1 Mt per year, though unsurveyed reserves potentially exploited in the future may exceed 100 Mt (USGS 2024 ). Once applied, the CDR potential of EW is influenced by the weathering rate and subsequent efficiency of carbon transport at each stage from field to ocean. In the Midwestern U.S. context provided, the largest estimated post-weathering losses (lowest efficiency) were expected in the earlier stages of the process, for example by non-carbonic acid weathering during feedstock dissolution, secondary mineral formation, or retarded movement of weathering products through the deeper soils. Estimates of efficiency rose as the inorganic carbon moved into freshwater, coastal ocean, and marine systems. Unsurprisingly, efficiency estimates by feedstock also converged, reflecting the general bicarbonate identity of the fixed carbon (though some noted that cations from feedstocks would also be transported and potentially have secondary effects, thereby altering their estimates). Individual estimates in overall efficiency estimates varied considerably, reflecting differences in interpretation of current data. Studies have estimated an approximately 40% increase in alkalinity export from the Mississippi River, partially attributed to cropland application of limestone since the 1940’s (Raymond and Hamilton, 2018 ). This could suggest that a significant CDR potential of limestone applied to the US has been realized over the past roughly 90 years (Raymond and Hamilton, 2018 ; West and McBride, 2005 ). Some large river systems are characterized by calcite supersaturation (e.g., Ibarra et al., 2016 ). There is debate on the extent to which supersaturation may drive significant burial or export of calcium carbonate that would lead to a substantial inefficiency in the EW process (see Zhang et al., 2022 ). Globally, there are limited quantitative estimates of bicarbonate export by major rivers. More work on the effects of agricultural liming on rivers, in a range of agricultural settings, is an immediate opportunity that could help resolve some of the uncertainties in carbon leakage estimates. Overall, however, the capacity of major river systems to export additional alkalinity from various feedstocks to the ocean is a major uncertainty. Nonetheless, overall estimated transfer efficiency was > 0. This implies that the fundamental EW process itself - once at the field stage - is potentially an effective CDR strategy. However, upstream emissions (e.g., mining, crushing, transport, and spreading) must be balanced against the CDR gains. As those emissions are more straightforward to estimate, reducing uncertainty in the CDR process becomes essential to correctly estimating the net value of EW as a CDR opportunity. However, there was low confidence in the current ability to measure and verify CDR rates and efficiencies. Error estimates clustered around 100%, meaning the magnitude of the measurement error was anticipated to be approximately equivalent to the magnitude of the CDR. This reflects the challenge of measuring weathering processes directly; many respondents indicate the need for either improved and well-validated models or further empirical study, especially in-field trials that encompass deep soils. Validation of models, especially for processes occurring in deep soils and the aquatic system, was considered to be relatively poor. As result, balancing CDR gains in the weathering process against emissions associated with the system process is a challenge for programs that incentivize CDR with carbon credits, for example, as the effect of an individual effort is difficult to anticipate or assess. Spatial aggregation may partially alleviate this challenge, as has been shown in soil organic carbon quantification, where estimates are also highly variable (e.g., Bradford et al., 2023 ). But research needs to be done to confirm and better understand the role of spatial scale in EW effectiveness. Human and ecosystem health concerns were elevated for olivine, steel slag, and concrete waste at the field stage. This corresponds to known concerns about heavy metal accumulation on fields from olivine, and potential concerns related to the relatively little-studied steel and recycled concrete feedstocks. In all cases, health concerns declined with stage progression. We did not evaluate the health risks of mining, processing, or transporting the material, which was considered out of scope. Wollastonite in particular has received attention for potential lung damage due to commonly being found in a small, needle-like form and contaminated with asbestos. However, studies are mixed. Maxim et al. ( 2014 ) found no significant relationship between wollastonite mining and lung damage when controlling for smoking. Overall, there is a dearth of literature on any specific health hazards regarding EW material mining or application, which must be considered, especially if the practice is to scale feedstock usage to globally relevant magnitudes. Strategic research to increase confidence To build confidence in agricultural EW as a CDR strategy, strategic research to target the largest magnitude uncertainties is needed (Calabrese et al., 2022 ). We identified a wide range of reported metrics that would improve confidence in global potential and efficiency estimates (see SI2). In particular, the pH dynamics of deep soils, the potential for pedogenic carbonate formation and secondary material formation, unknown flowpaths, biological feedbacks and interactions, and the possibility of non-carbonic acid weathering were noted as sources of uncertainty. Timing is another significant unknown. Cation sorption and the slow movement of cations from limestone applications through the soil are basic concepts in soil science and agronomy, but timing of this process in a CDR context is poorly constrained. Many recent soil mesocosm studies suggest the majority of cations released by silicate weathering are retained in the soil column (te Pas et al. 2025 ). In the aquatic stages, experts had concerns about the lack of knowledge regarding calcite formation (and redissolution), biological feedbacks, and fine-grained information on water chemistry. The marine system was considered to have the highest estimated pass-through efficiency, meaning from inflow to ultimate long-term storage. Deep ocean characteristics, especially alkalinity and dissolved inorganic carbon (DIC) profiles, were cited as information that would improve those estimates. Parallels with the ocean alkalinity enhancement literature and ongoing research could be used to inform both pathways. Targeted data collection alongside commercial deployments could help close existing knowledge gaps. But, for now, most industry data remains private and measurements are generally limited to the top ~ 30cm of soil, leaving processes occurring in areas such as the deep soil understudied. Leveraging commercial data will be most effective if both sufficient data collection occurs at all stages of carbon dynamics in these systems, and if the data are available for evaluation and analysis. A focus on catchment-scale studies of historically limed (e.g., Raymond and Hamilton, 2018 ) or silicate amended watersheds (e.g., Taylor et al., 2021 ) provides one approach for investigating the efficiency of alkalinity and cation transit through a watershed, though the degree to which lime can inform silicates, and the converse, are not perfectly known. Soil organic carbon (SOC) – a significant complication The net value of EW as a CDR strategy must include all emissions within the system, including from SOC. SOC was incorporated into the broad global estimate of CDR potential reported here. However, SOC losses or gains were not part of the stage-based assessment of efficiency. Weathering influences SOC at broad scales (Slessarev et al. 2022 ), and experimental work suggests that rock applications can reduce SOC accrual rates via pH increases (Sokol et al., 2024 ; Niron et al., 2024 ; Vienne et al., 2024 , Lei et al. 2025 ); this also impacts adjacent freshwater systems (Klemme et al. 2022 ). However, the effect on net carbon uptake is variable (Buss et al. 2024 , Sokol et al. 2024 ). For example, wollastonite additions increased soil pH and dissolved organic carbon concentrations, thereby increasing soil CO₂ efflux by approximately 330% across various land-use types (Yan et al. 2023 ), and basalt amendments raised soil pH and microbial activity, enhancing soil enzyme activities and priming (Xu et al. 2024 ). However, SOC stabilization may also be promoted over longer timescales (Niron et al. 2024 ). In contrast to the paucity of data on the role of silicates in mediating SOC storage, there is a much more robust set of observations on the effects of limestone application to agricultural fields. A recent meta-analysis on the effects of agricultural liming (Wang et al. 2021 ) suggests that the process has a positive impact on SOC stocks. To the extent that lime acts similarly to less-broadly tested silicates with respect to SOC (e.g., by raising pH), it could be reasonable to expect similar directionality over broad spatial and temporal scales. However, feedstock specific chemistry suggests that generalization must be done carefully. Current evidence underscores the context-dependent nature of the impact of EW on SOC dynamics. Diverse outcomes ranging from stimulated to suppressed organic matter decomposition have been observed, and depend heavily on soil characteristics, microbial community structure, and plant interactions. Moreover, the temporal dimension is crucial; short-term effects on decomposition rates may differ significantly from long-term outcomes, as stabilization via mineral-associated mechanisms likely becomes more pronounced with prolonged weathering processes (Vicca et al., 2022 ). Conclusions The expert elicitation here suggests that EW may be a viable CDR strategy, with best estimates generally positive. Confidence in quantification remains a challenge - there are systemic uncertainties that still need to be properly characterized, including field-specific impacts on SOC, the role of secondary mineral formation in the deep soil, and the role of the biological community in freshwater systems (among others). Further, there is no widely agreed upon set of rules for quantifying EW-induced CDR (Nordahl et al., 2024 ), and decisions made to guide estimates are not necessarily normative decisions about how carbon accounting should be done in CDR. For example, we chose to ignore the production emissions for steel slag and concrete waste from our global estimates as we assumed steel and concrete would be produced regardless of EW activity; for the other feedstocks (e.g. wollastonite) we included estimated emissions, assuming they would primarily be mined for EW. In general, any estimate of the EW scale potential hinges on assumptions such as these about the rules underlying carbon removal quantification. Ultimately, the value of EW as a CDR strategy rests on its ability to drive lower atmospheric greenhouse gas concentrations and climate warming, inclusive of upstream emissions and all system-level effects. However, the effects of agricultural production also need to be taken in account given the large greenhouse gas footprint of food production. The results here, while lower than many models or commercial estimates, suggest a real potential for EW to CDR. However, given the complexities of attributing change in atmospheric chemistry to any given process, quantification questions and data uncertainties are significant and should be resolved. A system-level perspective and strategic and focused research is necessary to place EW into the broader toolkit of CDR technologies. Methods Expert elicitation method Expert elicitation is a research strategy designed to obtain informed, quantitative and qualitative judgments and uncertainty ranges from experts, in situations in which there is insufficient data to determine those values directly (Speirs-Bridge et al. 2010 , Morgan 2014 , Morgan 2017 ). The methodology relies on judgments from experts who are qualified to address the fundamental mechanisms under consideration. We followed established protocols, focusing on quantifying best estimates and uncertainty (Hemming et al. 2018 ). Description of process Experts currently working on soil-based enhanced weathering for carbon dioxide removal were identified. Ultimately, we included 19 experts (research suggests that 6–12 experts are sufficient to get stable estimates; Hemming et al. 2018 ). The experts spanned the terrestrial and aquatic domains. For reported expertise, see SI1. The expert elicitation process followed the protocol outlined in Hemming et al. ( 2018 ). Briefly, participants were given a formal survey (described below; a copy at SI 1). Initial results were summarized, and the group was convened to ensure each question was perceived similarly by each participant (e.g., clarifying confusing language) and resolve discrepancies. We did not attempt to reach consensus or agreement on the estimated values or other responses. After the meeting, the survey was modified for clarity and reissued. The second round of survey responses, which could have matched or differed from initial survey responses, comprised the dataset analyzed here. Initial results were discarded. Four respondents were not present for the mid-project meeting. Those participants were contacted to discuss the proceedings of the meeting, and they also re-did the survey. To ensure bias was not introduced by this process, their responses were noted as “remote”. We checked for systematic differences in the overall average global estimates and the overall efficiency estimates (see below for details) with and without the inclusion of the remote participants. As there was no significant difference (p > 0.05, ANOVA), results are presented with the entire pool of participants included. Estimating the net CDR potential of EW First, to assess the global scale potential of EW, participants were asked to provide their best estimate of the global CDR potential of each of six feedstocks independently: lime, basalt, concrete waste, olivine-rich rock (hereafter, olivine), steel slag, and wollastonite-rich rock (hereafter, wollastonite). This estimate included the entire system, including other GHGs (e.g., alterations to N 2 O production), organic carbon, and transport of the material. We also considered the entire production process for all feedstocks except steel slag and concrete waste. For those two feedstocks, which are waste products from ongoing manufacturing, emissions associated with that manufacturing were excluded. Constraints like material supply were considered but not quantitatively pre-determined (in other words, experts individually determined the likely magnitude of the future supply). Experts were then asked for their high-range estimate (95th percentile) and their low-range estimate (5th percentile) of CDR potential (in terms of CO 2 e). Lastly, they were asked how confident they were that their estimated range contained the true value, from 50% (e.g., the real value had an equal probability of falling in or out of their range) to 100% (complete certainty that the 95% range contained the true estimate). For the precise wording and conditions, see the questions (SI2) Second, to estimate where C may be lost to the atmosphere throughout the process, we focused on transfer efficiency through the overall EW system. While there is potential for EW deployment in a wide range of agroecosystems, we constrained the scenario to a hypothetical Midwestern US context to obtain realistic and comparable estimates. Specifically, efficiency estimates were for non-irrigated, non-tile drained loamy soils in the American Midwest with an average pH value of 5.5-6, a base saturation of 65%, and a cation exchange capacity (CEC) of 10 meq/100 mg. Participants assumed a feedstock grind size of < 100 um. The export pathway was through a major waterway (e.g., the Mississippi River) into the ocean. This hypothetical setting was constructed with the goal of selecting a representative setting that lacks characteristics of both ideal settings for EW (e.g., tile drains and very low CEC) and suboptimal settings (e.g., arid regions). The stages of this pathway were 1) the agricultural field, 2) deeper soils and groundwater, 3) freshwater streams, 4) nearshore marine systems, and 5) deep water marine systems. Participants were asked not to consider potential interactions with the organic C cycle (e.g., EW-induced changes in soil organic C cycling) in these transfer efficiency estimates (see Discussion). Each stage was framed individually. The field-stage involved application of raw feedstock to the bottom of the layer actively ploughed/tilled. The relevant questions were framed as “if enough material were applied to potentially fix 10 tons CO 2 ”, such that the expert’s estimates include judgement on the fraction of feedstock dissolved over the considered timeframe (20 yrs). The deep soil stage encompassed the movement of C captured in the field stage from the bottom of the tilling zone to free-flowing freshwater. For this and all other stages, transport efficiency (pass-through fraction, or the proportion of C which enters that stage which then moves through to the next stage) were assessed with a starting condition of 10 tons of fixed C entering that stage. The freshwater stage extended from free-flowing drainage from a field to brackish estuarine systems. The coastal ocean stage encompassed brackish water and the nearshore mixing zone. The marine stage included deeper waters. We allowed that C might be resident within each stage for up to 20 years. Ultimately, storage was considered to be > 100 years in the ocean. The same range and confidence estimates used in the global estimate were collected at each stage (5th, 50th, 95th percentile, and certainty in range estimate). Because stages were evaluated independently, they could not be combined to calculate an overall field-to-marine pass-through fraction. So, a final question evaluated the anticipated fraction of the material that would successfully move through all stages from field application to marine deposition. In addition, for each stage, experts were asked to estimate the current measurement error they would expect if we quantified efficacy by feedstock and stage. For example, a measurement error of 100% suggested the error in measuring EW efficacy at that stage was roughly the same as the magnitude of the CDR process itself, whereas an error of 200% meant the uncertainty was double that of the process itself. Experts were also asked about the potential for each feedstock to cause significant human or environmental harm if deployed at broad scales (for each stage). Lastly, they were asked qualitative questions at each stage and feedstock regarding the three most important variables that influenced their estimate and the three most important unknowns which, if better constrained, would improve the certainty of their estimate. Here, data are primarily presented as the full range of individual responses, to transparently display the range of estimates obtained. Because individuals expressed differential levels of certainty in their range estimates, the ranges were standardized to their 80th percentile credible intervals following Hemming et al. ( 2018 ). Raw range estimates and certainty estimates are available in the source data. Where necessary, summary statistics such as means and ranges are included. All responses (anonymized) are available at SI2. Declarations Conflict of Interest The authors declare no conflict of interest. NP was a co-founder of Lithos Carbon but has no financial ties to the company. CD acts as a scientific advisor to the Rock Flour Company, but does not receive financial compensation for the role. Acknowledgements BB was supported gifts from Christina and Jeffrey Bird and Mary Anne Baker and G. Leonard Baker, Jr. EO and DG were partially supported by King Philanthropies. MA, SZ, JH, NP, and TJS acknowledge funding from the Department of Energy (DOE) Earthshot Initiative (#DE-SC0024709). TJS acknowledges funding from the Swiss National Science Foundation (P500PN_210790). 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River chemistry constraints on the carbon capture potential of surficial enhanced rock weathering. Limnol. Oceanogr. 67, S148–S157. https://doi.org/10.1002/lno.12244 Zhang, S., Reinhard, C. T., Liu, S., Kanzaki, Y., & Planavsky, N. J. (2025). A framework for modeling carbon loss from rivers following terrestrial enhanced weathering. Environmental Research Letters, 20(2), 024014. https://doi.org/10.1088/1748-9326/ada398 Additional Declarations There is NO Competing Interest. Supplementary Files SupportingInformation1IndividualResponses.xlsx Supplemental Information 1 SupportingInformation2ExpertElicitationsurvey.pdf Supplemental Information 2 SupplementalInformation3v9.docx Supplemental Information 3 Cite Share Download PDF Status: Published Journal Publication published 12 Mar, 2026 Read the published version in Communications Earth & Environment → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7040857","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":484522367,"identity":"20f9e33b-7d41-4c37-bbe7-25bae57199d8","order_by":0,"name":"Brian Buma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAp0lEQVRIiWNgGAWjYBACAwkQWcHA2N5AmpYzDIw9B0jSwthGihZz6R7TDT/n2cj2MDAf+/iFGC2Wc86Y3ezdlmbcw8CWPFuGKIfdyDG7wbvtcOJ+Bh5jZglitdz8O+d/Yg9JWm7zNhwAa2H8QIwWyznHym7LHEs27mFmS2YmRgcwxJq33XxTYyfbw958mPEHUXrgAGgFMw9pWoCAVFtGwSgYBaNghAAAc2gyoZXYSbkAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-2402-7737","institution":"Environmental Defense Fund","correspondingAuthor":true,"prefix":"","firstName":"Brian","middleName":"","lastName":"Buma","suffix":""},{"id":484522368,"identity":"f3962b5d-54a0-422e-a478-29859b588a09","order_by":1,"name":"Christiana Dietzen","email":"","orcid":"https://orcid.org/0000-0002-3939-9472","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Christiana","middleName":"","lastName":"Dietzen","suffix":""},{"id":484522369,"identity":"c8c610fc-71b7-4326-8c0b-5cba16c880ca","order_by":2,"name":"Doria Gordon","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Doria","middleName":"","lastName":"Gordon","suffix":""},{"id":484522370,"identity":"ac5a0f2f-6dc6-4a0d-887a-b7caecd9f7fc","order_by":3,"name":"Katharine Maher","email":"","orcid":"https://orcid.org/0000-0002-5982-6064","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Katharine","middleName":"","lastName":"Maher","suffix":""},{"id":484522371,"identity":"bf9fad76-893e-49de-9202-02d3ce54fdb7","order_by":4,"name":"Rebecca Neumann","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Rebecca","middleName":"","lastName":"Neumann","suffix":""},{"id":484522372,"identity":"bfe15425-6818-4c47-badb-ad5413437330","order_by":5,"name":"Noah Planavsky","email":"","orcid":"https://orcid.org/0000-0001-5849-8508","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Noah","middleName":"","lastName":"Planavsky","suffix":""},{"id":484522373,"identity":"3ff8d9f2-a5c8-40ce-92fd-05f2b7c2414e","order_by":6,"name":"Tom Reershemius","email":"","orcid":"https://orcid.org/0000-0003-3512-6693","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Tom","middleName":"","lastName":"Reershemius","suffix":""},{"id":484522374,"identity":"4805b705-6ca8-48c7-85fb-4303be742f42","order_by":7,"name":"Tim Jesper Suhrhoff","email":"","orcid":"https://orcid.org/0000-0002-7934-7159","institution":"Yale University","correspondingAuthor":false,"prefix":"","firstName":"Tim","middleName":"Jesper","lastName":"Suhrhoff","suffix":""},{"id":484522375,"identity":"d1d1c9ec-b51f-45ef-a905-386fb2042b56","order_by":8,"name":"Sara Vicca","email":"","orcid":"https://orcid.org/0000-0001-9812-5837","institution":"University of Antwerp","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Vicca","suffix":""},{"id":484522376,"identity":"da42e314-1cea-4947-bada-798c892675bd","order_by":9,"name":"Bonnie Waring","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Bonnie","middleName":"","lastName":"Waring","suffix":""},{"id":484522377,"identity":"b342d46f-a38c-4d1a-8be6-60814cd586c2","order_by":10,"name":"Maya Almaraz","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Maya","middleName":"","lastName":"Almaraz","suffix":""},{"id":484522378,"identity":"159fbf01-8c26-418f-bdf5-cd930d2414af","order_by":11,"name":"Salvatore Calabrese","email":"","orcid":"https://orcid.org/0000-0002-9997-9778","institution":"Texas A\u0026M University","correspondingAuthor":false,"prefix":"","firstName":"Salvatore","middleName":"","lastName":"Calabrese","suffix":""},{"id":484522379,"identity":"e67b9e39-8ad0-48aa-961b-295a78996a79","order_by":12,"name":"Louis A. Derry","email":"","orcid":"https://orcid.org/0000-0001-7062-7333","institution":"Cornell University","correspondingAuthor":false,"prefix":"","firstName":"Louis","middleName":"A.","lastName":"Derry","suffix":""},{"id":484522380,"identity":"6b97a25f-e1f0-480e-8bc3-e5658fc6e3b7","order_by":13,"name":"M. Granger Morgan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"Granger","lastName":"Morgan","suffix":""},{"id":484522381,"identity":"0d52acc0-77e8-493d-bab3-a957a8ad27f5","order_by":14,"name":"John Andrew Higgins","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"Andrew","lastName":"Higgins","suffix":""},{"id":484522382,"identity":"023cf4e7-65dc-4d7e-ada9-7aa1de397c72","order_by":15,"name":"Benjamin Houlton","email":"","orcid":"https://orcid.org/0000-0002-1414-0261","institution":"Cornell University","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Houlton","suffix":""},{"id":484522383,"identity":"f14a8349-55e2-49dd-945e-4d2e5403f214","order_by":16,"name":"Yoshiki Kanzaki","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yoshiki","middleName":"","lastName":"Kanzaki","suffix":""},{"id":484522384,"identity":"dbce82d5-cc73-440a-b7cc-3861ad60b3b6","order_by":17,"name":"Alexandra Klemme","email":"","orcid":"https://orcid.org/0000-0002-6877-4964","institution":"University of Bremen","correspondingAuthor":false,"prefix":"","firstName":"Alexandra","middleName":"","lastName":"Klemme","suffix":""},{"id":484522385,"identity":"d1ffd6d7-c4cc-4a77-b1e9-c2bfcb5a5528","order_by":18,"name":"Tyler Kukla","email":"","orcid":"https://orcid.org/0000-0002-3413-0925","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Tyler","middleName":"","lastName":"Kukla","suffix":""},{"id":484522386,"identity":"60824bb7-50bb-47e8-9d1e-2d296138d17c","order_by":19,"name":"Emily Oldfield","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Emily","middleName":"","lastName":"Oldfield","suffix":""},{"id":484522387,"identity":"424823a2-55de-4586-a1e7-36f9e76bf3b3","order_by":20,"name":"Ian Power","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ian","middleName":"","lastName":"Power","suffix":""},{"id":484522388,"identity":"e0aa7133-dac8-4c3e-81ef-21f91978801c","order_by":21,"name":"Christopher R. Pearce","email":"","orcid":"","institution":"National Oceanography Centre","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"R.","lastName":"Pearce","suffix":""},{"id":484522389,"identity":"ccb3e2aa-feb2-4e9d-b16c-b9a194081d93","order_by":22,"name":"Whendee Silver","email":"","orcid":"https://orcid.org/0000-0003-0372-8745","institution":"University of California","correspondingAuthor":false,"prefix":"","firstName":"Whendee","middleName":"","lastName":"Silver","suffix":""},{"id":484522390,"identity":"7ef06a5c-31c9-4a03-8d37-209ce9a742d7","order_by":23,"name":"Shuang Zhang","email":"","orcid":"https://orcid.org/0000-0003-1745-4642","institution":"Texas A\u0026M University","correspondingAuthor":false,"prefix":"","firstName":"Shuang","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-07-03 18:45:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7040857/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7040857/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s43247-026-03375-5","type":"published","date":"2026-03-12T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87885271,"identity":"cfa061b8-b2c0-4a0a-8718-96b238b14fdc","added_by":"auto","created_at":"2025-07-30 05:06:32","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":133559,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual flow of carbon fixed via enhanced rock weathering, and the specific stages considered in the study. The CDR value ultimately is a function of the balance between CO\u003csub\u003e2\u003c/sub\u003e fixation as a result of feedstock application and CO\u003csub\u003e2\u003c/sub\u003e flux into the atmosphere. This balance can be shaped by carbon flux and alkalinity export.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7040857/v1/279584d69e81c6bb3dac0987.jpg"},{"id":87884185,"identity":"67dfb019-c867-442a-afc9-cede6e4310de","added_by":"auto","created_at":"2025-07-30 04:58:32","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":213460,"visible":true,"origin":"","legend":"\u003cp\u003eEstimates and certainty in estimated ranges.\u0026nbsp; A: Total global CDR potential by feedstock, including production emissions, impact on N\u003csub\u003e2\u003c/sub\u003eO and other greenhouse gases, supply limitations, and other system-level factors. Estimates are for maximum deployment of each feedstock independently (e.g., individual estimates should be added together). Circles mark the estimate for “most likely amount of system-wide, annual CO\u003csub\u003e2\u003c/sub\u003e removal given widespread adoption” while bars mark “lowest/5th percentile” and “highest/95th percentile” plausible possibility. B: Estimates of total CDR efficiency of the process starting from field application and ending with long term storage, assuming enough material is applied to potentially fix 10 tons of carbon ha\u003csup\u003e-1\u003c/sup\u003e. We allowed a maximum 20-year potential residence time within each stage with the exception of the marine stage, where the time was defined as lasting at least 100 years. Estimates in (B) excluded potential organic C cycle feedbacks (i.e., losses or gains of SOC). Circles and bars same as in (A). In both A and B, the darker the shading the higher the confidence that the defined range contains the true probability.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7040857/v1/39eb64561c691824bd20b1a3.jpg"},{"id":87884187,"identity":"70b2b949-b310-4814-a2c3-8bcff1256d70","added_by":"auto","created_at":"2025-07-30 04:58:32","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":90938,"visible":true,"origin":"","legend":"\u003cp\u003eEfficiency estimates for transfer from stage to stage, and overall. Values are the mean of the best estimates for all responses (parentheses: mean of the 5th and 95th percentile). See methods for definition of stages. For confidence in individual stages, see S3 Table 2.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7040857/v1/cdfc638fbb72d8b2bb8db010.jpg"},{"id":87885272,"identity":"af49be6b-c652-41cf-84b4-f980afdb7824","added_by":"auto","created_at":"2025-07-30 05:06:32","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":105826,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated probability that a feedstock will cause significant ecosystem or human health damage at each stage when applied at commercially and climatically relevant amounts and scales. Each feedstock was considered independently.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7040857/v1/2c0adcfbddcc99249036fb3a.jpg"},{"id":107973458,"identity":"5705f5ce-5ecf-4b9c-8b0b-512c9e77a4ee","added_by":"auto","created_at":"2026-04-28 07:11:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":888954,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7040857/v1/2708e910-12fe-4ed1-a651-c221eb2bb658.pdf"},{"id":87884189,"identity":"0a3d54a5-a1c6-497f-a540-e5f3c76c705b","added_by":"auto","created_at":"2025-07-30 04:58:32","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":72987,"visible":true,"origin":"","legend":"Supplemental Information 1","description":"","filename":"SupportingInformation1IndividualResponses.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7040857/v1/15d446e01a521cf335bc8067.xlsx"},{"id":87884191,"identity":"714ca858-0fe9-46e7-b55e-d32f3a1038e3","added_by":"auto","created_at":"2025-07-30 04:58:33","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":899002,"visible":true,"origin":"","legend":"Supplemental Information 2","description":"","filename":"SupportingInformation2ExpertElicitationsurvey.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7040857/v1/0672f5f26fa610ff7a22aca2.pdf"},{"id":87884192,"identity":"23428f57-5f73-4da7-94e5-bd7da58d1a2b","added_by":"auto","created_at":"2025-07-30 04:58:33","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":207239,"visible":true,"origin":"","legend":"Supplemental Information 3","description":"","filename":"SupplementalInformation3v9.docx","url":"https://assets-eu.researchsquare.com/files/rs-7040857/v1/15ad70adfbb0140fb605ef35.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"\u003cp\u003eExpert elicitation on agricultural enhanced weathering highlights CO\u003csub\u003e2\u003c/sub\u003e removal potential and uncertainties in loss pathways\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSlowing the pace of global climate change will require a combination of rapid emissions reductions and carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) removal (CDR) to limit future warming and reduce greenhouse gas (GHG) concentrations already in the atmosphere (IPCC \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, few CDR technologies can achieve durable carbon (C) sequestration (i.e., \u0026gt;\u0026thinsp;100 years) at a sufficient scale and pace needed to meet projected CDR demands (Field and Mach \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Lamb et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Enhanced weathering (EW) has the potential to be a broadly applicable CDR technology with long-term, durable storage. The EW approach focuses on accelerating the natural process of rock weathering, which is known to be an important control on long-term (ca million year) atmospheric CO\u003csub\u003e2\u003c/sub\u003e levels. However, the ability to accelerate weathering rates at large scales remains an outstanding question, one that requires consideration of feedstock availability and energy inputs (Strefler, 2018), land system response (Goll et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), efficiency of CDR across the land-to-sea continuum (Ilyina et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and the potential for adverse environmental impacts (Levy et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eEnhanced weathering exposes the feedstock, such as finely ground cation-rich material, to environments conducive to rapid weathering processes, often agricultural soils (Anthony et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e, Hartmann et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Vakilifard et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Beerling et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In soil, the finely ground materials undergo chemical dissolution reactions driven by carbonic acids, converting CO\u003csub\u003e2\u003c/sub\u003e in the soil into bicarbonate ions and releasing base cations, such as Ca\u003csup\u003e2+\u003c/sup\u003e and Mg\u003csup\u003e2+\u003c/sup\u003e. The bicarbonate may be precipitated as carbonates \u003cem\u003ein situ\u003c/em\u003e or transported to the ocean for long-term storage (e.g., as alkalinity, or incorporated into shells as calcium carbonate).\u003c/p\u003e\u003cp\u003eWhile the process of CDR above is well established through decades of research on natural weathering (Berner and Maasch \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Gaillardet et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Caldiera 1995., Caves et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), it remains unclear the extent to which large-scale deployment of EW could contribute meaningfully to the magnitude of carbon removal necessary to achieve climate targets under the Paris Agreement (e.g., well below 2˚C warming). Estimates of global weathering rates are derived from both measurements of riverine fluxes and earth systems models, and are typically divided between silicate weathering and carbonate weathering, with silicate weathering constrained to transfer between 0.33 to 0.51 Gt CO\u003csub\u003e2\u003c/sub\u003e/yr from the atmosphere to the oceans, compared to carbonate weathering rates of 0.48 to 1.39 Gt CO\u003csub\u003e2\u003c/sub\u003e/yr (Hilton and West \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), though there are many poorly constrained processes and high uncertainties remaining (e.g., groundwater fluxes, Zhang and Planavsky \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For comparison, estimates of EW CDR capacity using silicate rocks ranges from 0.5 to \u0026gt;\u0026thinsp;4 Gt CO\u003csub\u003e2\u003c/sub\u003ee y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (e.g., Smith et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Fuss et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Strefler et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Beerling et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Fuhrman et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Integrated assessment models (IAMs) typically assume that enhanced weathering could contribute removals of around 2\u0026ndash;4 Gt CO2/yr by 2050 (e.g., Minx et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fuss et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Brack and King \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hepburn et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Projections for 2100 span a much wider range, of 0.5 up to 27 Gt CO\u003csub\u003e2\u003c/sub\u003ee/yr, with an average estimate of approximately 6 Gt CO\u003csub\u003e2\u003c/sub\u003ee/yr due to variation across scenarios and underlying assumptions (e.g., Brack \u0026amp; King \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; M\u0026uuml;hlbauer et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Thus far, however, these estimates are largely derived from models rather than empirical data, often assume maximum adoption and deployment, and do not always consider geochemical limits of EW. Weathering, especially with the aim of long-term CDR, is a complex process that requires a full system perspective to evaluate.\u003c/p\u003e\u003cp\u003eMany rock materials are under consideration for EW. Agricultural lime (aglime) is typically dominated by calcium carbonate, though other materials like dolomite can be included, and has been used for millennia to adjust pH in acidic soils. Interest in the C uptake potential of silicates like olivine, basalt, and wollastonite has recently increased (Renforth et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, te Pas et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Recycled materials, especially steel slag and cement waste (Yoshioka et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), are also being explored for this purpose. Each material has unique properties that feed into its overall CDR potential. In particular, feedstocks differ in terms of their CO\u003csub\u003e2\u003c/sub\u003e capture efficiency, potential to form secondary minerals (e.g., secondary clay formation vs carbonates), biological reactions, and side effects such as metal accumulation in vegetation, soils, or waterways (Abdalqadir et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMultiple factors determine the real-world potential of EW. Feedstock availability is a significant question: to reach the gigatonne CDR scale, the quarrying and mining of EW feedstocks at a similar scale as the production of crushed stone (1.6 Gt), sand and gravel (1 Gt), and construction aggregate (2.5 Gt) in the United States (USGS, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) would be needed The rate, completeness, and mode (e.g., carbonic acid vs. nitric acid weathering) of the feedstock weathering reaction is a significant driver of overall efficiency (Deng et a. 2023, Baek et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Edwards et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Once the material is completely weathered (or as completely as conditions/feedstocks allow), there are multiple downstream loss processes that can reduce the efficacy of EW for climate benefit. Precipitation of secondary minerals can reduce CDR efficiency by generating acidity and consuming base cations, resulting in the conversion of bicarbonate back to CO\u003csub\u003e2\u003c/sub\u003e (Bertagni and Porporato \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Vienne et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Carbon losses during river transport may also impact the net CDR potential of EW. Secondary carbonate formation in rivers, triggered by increased carbonate saturation states, could reduce efficiency (Knapp and Tipper \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Uncertainty in the significance of these loss pathways is still high. For example, Zhang et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) suggest that river transport may not significantly limit EW\u0026rsquo;s CDR potential in most rivers in the US, though these estimates are chemistry-focused and do not always include the full suite of potentially relevant processes (e.g., biological carbon uptake, Neumann et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). There are limited estimates of the fate of weathering products in nearshore environments and the oceans (Kanzaki et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Beerling et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Overall, for EW to be a reliable means for quantifiable CDR, the entire system efficiency needs to be reliably evaluated.\u003c/p\u003e\u003cp\u003eAlthough not directly relevant to CDR, aspects of EW increase its viability as a scalable practice, further driving interest. As the weathering reaction progresses in frequently acidified agricultural soils, an EW-induced increase in soil pH may typically raise nutrient availability (at least up a pH of ~\u0026thinsp;7; Amann and Hartmann \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), improve crop yields (e.g., Li et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Abdalqadir et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), reduce soil N\u003csub\u003e2\u003c/sub\u003eO production (Chiaravalloti et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and improves air quality (Beerling et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Potential challenges also exist, however. For example, there are concerns that some EW feedstocks contain heavy metal elements (e.g., nickel, cadmium), which can accumulate in soils and impact crop health and food safety (Dupla et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Levy et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In addition, potential interactions with the soil organic carbon (SOC) reservoir have not been well documented for many of the potential feedstocks. Enhanced weathering in any one site may reduce or enhance the land organic C sink, and these effects are both site, feedstock, and time dependent (Buss et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Sokol et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Biological system interactions with the EW process are also highly variable, both positively and negatively (Wang et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Vicca et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Niron et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The balance of these tradeoffs will determine both EW\u0026rsquo;s viability as a CDR pathway and its sustainability if scaled.\u003c/p\u003e\u003cp\u003eTens of millions of tons of agricultural lime (\u0026ldquo;aglime,\u0026rdquo; carbonate minerals) are currently added every year to soils (e.g., West and McBride, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) for agronomic benefits currently. Although substantial uncertainty of system-level CDR efficacy remains, commercial projects spreading cation-rich rocks in agricultural have begun being funded via the voluntary carbon market (carbon crediting). Having confidence in the value of EW-based GHG offsets requires a critical evaluation of the robustness of EW as a real climate solution. Claims that fail to deliver on their system-level CDR promise \u0026ndash; for example, if a significant fraction of initially fixed C were lost during aquatic transport stages \u0026ndash; will result in unintended and untracked emissions to the atmosphere.\u003c/p\u003e\u003cp\u003eGiven poorly constrained uncertainties about multiple aspects of the EW process, we pursued a formal expert elicitation (\u003cem\u003esensu\u003c/em\u003e Morgan \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) to identify the magnitude of potential CDR via EW in agriculture, and to highlight the most critical research gaps surrounding CDR efficiency along the soil to ocean continuum. Expert elicitations are intended to incorporate both the full spectrum of available data, as well as expert opinion on that data. The process addressed multiple questions which are key to the scalability and climate value of EW in agriculture, including:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat is the potential global climate impact of EW via inorganic C removal, considering supply chain, feedstock type and availability, and emissions of other GHGs?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat is the efficiency of C capture at the field scale, and of transport from the field to long-term ocean storage, both in total and by process stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat level of uncertainty is expected in quantifying capture and transport efficiency? How do the sources and magnitudes of error influence whether models or empirical data (or a mix) are most appropriate for monitoring?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAre there significant health or environmental impact concerns if EW is scaled, and for which feedstocks?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eBecause the responses are feedstock dependent, these questions were addressed independently for each of six feedstocks: lime, basalt, olivine-rich rock, wollastonite-rich rock, steel slag, and concrete waste.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, global annual CDR rate estimates via agricultural EW \u0026ndash; which encompass constraints on feedstock production, land availability, as well as non-target GHG emissions associated with rock grinding, changes in soil biogeochemistry, and other factors \u0026ndash; varied by feedstock. Throughout, note that positive values will refer to a CO\u003csub\u003e2\u003c/sub\u003e sink (e.g., removal from the atmosphere) and negative values to emissions to the atmosphere. Individual estimates of the most likely amount of CDR ranged substantially, from a source of -0.1 Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to a sink of +\u0026thinsp;4.0 Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, circles). Estimates of the minimum possible amount of CDR ranged from a source of -2.0 Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (the lowest option provided in the survey) to a sink of 1.0 Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, while estimates for the maximum possible amount of CDR ranged from 0 Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to \u0026gt;\u0026thinsp;5.0 Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (For individual responses, see SI1; for the survey instrument see SI2).\u003c/p\u003e\u003cp\u003eMean and median values (presented as \u0026ldquo;mean/median\u0026rdquo; below) for group estimates of the maximum and most likely amount of CDR were greatest for basalt and smallest for wollastonite. For basalt, the maximum possible CDR was 2.1 (mean) / 2.0 (median) Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, while the most likely amount of CDR was 0.7/0.4 Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. For wollastonite, the maximum possible CDR was 0.9/0.1 Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, while the most likely amount of CDR was 0.2/0.01 Gt CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Means and medians for agricultural lime were close to basalt for the maximum and most likely amount of CDR, while those for the other feedstocks clustered together and fell between that of wollastonite and agricultural lime. For all feedstocks, the mean and median estimate for the minimum amount of CDR intersected zero (i.e., no C removal). Confidence, meaning the likelihood that the true value was within the estimated ranges, was generally low. It was, across the group, lowest for concrete waste (66% / 60%) and highest for basalt (74%/75%), corresponding to roughly 2:1 to 3:1 odds that the real value is within the estimated ranges. For individual ranges with confidence, see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. For individual feedstock global estimates, see SI3 Table\u0026nbsp;1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe found little relationship between the magnitude of the estimate for the most likely amount of CDR and confidence in the overall range (SI3 Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eEfficiency (transfer potential)\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe fraction of a hypothetical 10 tons ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of fixed CO\u003csub\u003e2\u003c/sub\u003e moving from the field to the ocean over 20 years (and with 100 year minimum retention time in the ocean) was broadly similar among feedstocks \u0026ndash; approximately 1/3 \u0026ndash; but with high variability in individual estimates (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). On average, estimates for the most likely amount of C removed as durable CDR given a theoretical potential of 10 tons C fixed ha\u003csup\u003e\u0026minus;\u003c/sup\u003e ranged from 2.7 ton ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for lime (e.g., 27%) to 3.9 ton ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for wollastonite (e.g., 39%). Low range estimates were around 1 ton ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (lowest for lime with 0.6 tons ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, or a 6% efficiency); high range estimates spanned from 5.6 ton ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (lime) to 7 ton ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for wollastonite. Some individual responses were lower and higher, reflecting disagreement across respondents. Confidence in those ranges was approximately 70%, regardless of feedstock (approximately 2:1 odds the true value is actually within those ranges). For responses on all feedstocks, including confidence estimates, see SI3 Table\u0026nbsp;2.\u003c/p\u003e\u003cp\u003eAt the stage level, efficiency estimates were lowest (i.e., most fixed C lost) in earlier stages and highest in latter stages regardless of feedstock (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The 5th \u0026ndash; 95th estimates of C fixed and moving through the field averaged (across all feedstocks) from 21\u0026ndash;76%, with a mean of 46%. For all responses on individual stages and feedstocks, including confidence, see SI3 Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\u003cp\u003eMeasurement error associated with CDR was consistently estimated as approximately 100% regardless of feedstock or stage (meaning that the uncertainty equals the magnitude of potential carbon removal). This response encompassed both empirical and current modeling uncertainties, though the deep soil and coastal ocean stages were frequently estimated to have \u0026gt;\u0026thinsp;100% error in measurement. This pattern was independent of feedstock (SI3 Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe potential for significant health or environmental damage if deployed at scale varied substantially by feedstock, though generally declined when moving downstream from the field. Agricultural lime had the lowest estimated potential for damage regardless of stage (though experts expressed slightly higher concerns for freshwater systems, specifically). In contrast, steel slag and olivine had higher values across the stages, with the highest concerns for both at the field scale (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eExperts were split on the level of empirical monitoring or modeling needed for monitoring, measurement, reporting, and validation for the voluntary carbon market. At the field scale, nearly half suggested that modeling would be sufficient, though another third thought empirical measurements should be required. Overall, the trend was a preference for more empirical measures at the field and soil stage, moving towards a greater modeling emphasis at later stages.\u003c/p\u003e\u003cp\u003eTo better constrain the global CDR potential of EW, experts cited the need for a better understanding of soil organic carbon and microbial responses in various geographic settings, more information about feedstock availability, and additional focus on poorly studied loss pathways beyond field application: secondary clay formation, carbonate precipitation rates, biological pathways, and downstream degassing were identified as significant unknowns that would tighten uncertainty bands if they could be resolved. For all qualitative responses on datasets to resolve uncertainties, see the individual responses in SI1.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe expert elicitation estimated that the global potential for CDR from agricultural EW ranged from 0.2 to 0.7 Gt (median 0.01\u0026ndash;0.4) CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e depending on feedstock. Basalt and lime had the highest average estimated potential globally. However, experts also identified the potential for lime, basalt and olivine to be a source of C emissions, depending on lifecycle emissions and CDR efficacy. There was marked uncertainty and substantial variation in estimates (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In general, however, the preponderance of experts indicated a net positive CDR potential for all feedstocks. This result aligns with the estimates of overall transport efficiency from field to long term storage, which averaged from ~\u0026thinsp;27\u0026ndash;39%.\u003c/p\u003e\u003cp\u003eEstimates were generally lower than the prevailing literature estimates (e.g., 0.5\u0026ndash;3.6 Gt yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, Smith et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Beerling et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Reershemius et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; review in Power et al. 2025). The lower estimates in this study may reflect recent field studies that demonstrate strong constraints on the export of weathering products from soils, as well as potential downstream (post-field) loss processes not yet incorporated (or simplified) into transport models (Laruelle et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Zhang et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2025\u003c/span\u003e, Neumann et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Lower estimates were, in some cases, guided by the low efficiencies implied by the global rate of natural CO\u003csub\u003e2\u003c/sub\u003e consumption by silicate weathering (~\u0026thinsp;0.5 CO\u003csub\u003e2\u003c/sub\u003ee yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; Gaillardet et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) and by the fraction of total silicate weathering associated with weathering of basaltic rocks on Earth today (0.04 to 0.07 Gt CO\u003csub\u003e2\u003c/sub\u003e/yr, Hartmann et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Dessert et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Supply constraints, which were considered for the global estimates (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), are also not always incorporated in global modelling studies. The supplies of lime, basalt, and olivine are effectively unlimited (even if production would need to increase, Hartmann and Moosdorf \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Geerts et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Concrete waste is substantial, and towards 600\u0026nbsp;million tons in the US alone (however, estimates include all construction waste so the true number is likely lower; EPA \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Steel slag is more constrained, though significant; Gao et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) estimates an annual production of 120 Mt in China and industry estimates more than 400 Mt per year globally (Worldsteel \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In contrast, current production of wollastonite is approximately 1 Mt per year, though unsurveyed reserves potentially exploited in the future may exceed 100 Mt (USGS \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOnce applied, the CDR potential of EW is influenced by the weathering rate and subsequent efficiency of carbon transport at each stage from field to ocean. In the Midwestern U.S. context provided, the largest estimated post-weathering losses (lowest efficiency) were expected in the earlier stages of the process, for example by non-carbonic acid weathering during feedstock dissolution, secondary mineral formation, or retarded movement of weathering products through the deeper soils. Estimates of efficiency rose as the inorganic carbon moved into freshwater, coastal ocean, and marine systems. Unsurprisingly, efficiency estimates by feedstock also converged, reflecting the general bicarbonate identity of the fixed carbon (though some noted that cations from feedstocks would also be transported and potentially have secondary effects, thereby altering their estimates).\u003c/p\u003e\u003cp\u003eIndividual estimates in overall efficiency estimates varied considerably, reflecting differences in interpretation of current data. Studies have estimated an approximately 40% increase in alkalinity export from the Mississippi River, partially attributed to cropland application of limestone since the 1940\u0026rsquo;s (Raymond and Hamilton, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This could suggest that a significant CDR potential of limestone applied to the US has been realized over the past roughly 90 years (Raymond and Hamilton, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; West and McBride, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Some large river systems are characterized by calcite supersaturation (e.g., Ibarra et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). There is debate on the extent to which supersaturation may drive significant burial or export of calcium carbonate that would lead to a substantial inefficiency in the EW process (see Zhang et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Globally, there are limited quantitative estimates of bicarbonate export by major rivers. More work on the effects of agricultural liming on rivers, in a range of agricultural settings, is an immediate opportunity that could help resolve some of the uncertainties in carbon leakage estimates. Overall, however, the capacity of major river systems to export additional alkalinity from various feedstocks to the ocean is a major uncertainty.\u003c/p\u003e\u003cp\u003eNonetheless, overall estimated transfer efficiency was \u0026gt;\u0026thinsp;0. This implies that the fundamental EW process itself - once at the field stage - is potentially an effective CDR strategy. However, upstream emissions (e.g., mining, crushing, transport, and spreading) must be balanced against the CDR gains. As those emissions are more straightforward to estimate, reducing uncertainty in the CDR process becomes essential to correctly estimating the net value of EW as a CDR opportunity. However, there was low confidence in the current ability to measure and verify CDR rates and efficiencies. Error estimates clustered around 100%, meaning the magnitude of the measurement error was anticipated to be approximately equivalent to the magnitude of the CDR. This reflects the challenge of measuring weathering processes directly; many respondents indicate the need for either improved and well-validated models or further empirical study, especially in-field trials that encompass deep soils. Validation of models, especially for processes occurring in deep soils and the aquatic system, was considered to be relatively poor. As result, balancing CDR gains in the weathering process against emissions associated with the system process is a challenge for programs that incentivize CDR with carbon credits, for example, as the effect of an individual effort is difficult to anticipate or assess. Spatial aggregation may partially alleviate this challenge, as has been shown in soil organic carbon quantification, where estimates are also highly variable (e.g., Bradford et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). But research needs to be done to confirm and better understand the role of spatial scale in EW effectiveness.\u003c/p\u003e\u003cp\u003eHuman and ecosystem health concerns were elevated for olivine, steel slag, and concrete waste at the field stage. This corresponds to known concerns about heavy metal accumulation on fields from olivine, and potential concerns related to the relatively little-studied steel and recycled concrete feedstocks. In all cases, health concerns declined with stage progression. We did not evaluate the health risks of mining, processing, or transporting the material, which was considered out of scope. Wollastonite in particular has received attention for potential lung damage due to commonly being found in a small, needle-like form and contaminated with asbestos. However, studies are mixed. Maxim et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) found no significant relationship between wollastonite mining and lung damage when controlling for smoking. Overall, there is a dearth of literature on any specific health hazards regarding EW material mining or application, which must be considered, especially if the practice is to scale feedstock usage to globally relevant magnitudes.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eStrategic research to increase confidence\u003c/span\u003e\u003c/p\u003e\u003cp\u003eTo build confidence in agricultural EW as a CDR strategy, strategic research to target the largest magnitude uncertainties is needed (Calabrese et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). We identified a wide range of reported metrics that would improve confidence in global potential and efficiency estimates (see SI2). In particular, the pH dynamics of deep soils, the potential for pedogenic carbonate formation and secondary material formation, unknown flowpaths, biological feedbacks and interactions, and the possibility of non-carbonic acid weathering were noted as sources of uncertainty. Timing is another significant unknown. Cation sorption and the slow movement of cations from limestone applications through the soil are basic concepts in soil science and agronomy, but timing of this process in a CDR context is poorly constrained. Many recent soil mesocosm studies suggest the majority of cations released by silicate weathering are retained in the soil column (te Pas et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In the aquatic stages, experts had concerns about the lack of knowledge regarding calcite formation (and redissolution), biological feedbacks, and fine-grained information on water chemistry. The marine system was considered to have the highest estimated pass-through efficiency, meaning from inflow to ultimate long-term storage. Deep ocean characteristics, especially alkalinity and dissolved inorganic carbon (DIC) profiles, were cited as information that would improve those estimates. Parallels with the ocean alkalinity enhancement literature and ongoing research could be used to inform both pathways.\u003c/p\u003e\u003cp\u003eTargeted data collection alongside commercial deployments could help close existing knowledge gaps. But, for now, most industry data remains private and measurements are generally limited to the top\u0026thinsp;~\u0026thinsp;30cm of soil, leaving processes occurring in areas such as the deep soil understudied. Leveraging commercial data will be most effective if both sufficient data collection occurs at all stages of carbon dynamics in these systems, and if the data are available for evaluation and analysis. A focus on catchment-scale studies of historically limed (e.g., Raymond and Hamilton, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) or silicate amended watersheds (e.g., Taylor et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) provides one approach for investigating the efficiency of alkalinity and cation transit through a watershed, though the degree to which lime can inform silicates, and the converse, are not perfectly known.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSoil organic carbon (SOC) \u0026ndash; a significant complication\u003c/span\u003e\u003c/p\u003e\u003cp\u003eThe net value of EW as a CDR strategy must include all emissions within the system, including from SOC. SOC was incorporated into the broad global estimate of CDR potential reported here. However, SOC losses or gains were not part of the stage-based assessment of efficiency. Weathering influences SOC at broad scales (Slessarev et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and experimental work suggests that rock applications can reduce SOC accrual rates via pH increases (Sokol et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Niron et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Vienne et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Lei et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2025\u003c/span\u003e); this also impacts adjacent freshwater systems (Klemme et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the effect on net carbon uptake is variable (Buss et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Sokol et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). For example, wollastonite additions increased soil pH and dissolved organic carbon concentrations, thereby increasing soil CO₂ efflux by approximately 330% across various land-use types (Yan et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and basalt amendments raised soil pH and microbial activity, enhancing soil enzyme activities and priming (Xu et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, SOC stabilization may also be promoted over longer timescales (Niron et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In contrast to the paucity of data on the role of silicates in mediating SOC storage, there is a much more robust set of observations on the effects of limestone application to agricultural fields. A recent meta-analysis on the effects of agricultural liming (Wang et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) suggests that the process has a positive impact on SOC stocks. To the extent that lime acts similarly to less-broadly tested silicates with respect to SOC (e.g., by raising pH), it could be reasonable to expect similar directionality over broad spatial and temporal scales.\u003c/p\u003e\u003cp\u003eHowever, feedstock specific chemistry suggests that generalization must be done carefully. Current evidence underscores the context-dependent nature of the impact of EW on SOC dynamics. Diverse outcomes ranging from stimulated to suppressed organic matter decomposition have been observed, and depend heavily on soil characteristics, microbial community structure, and plant interactions. Moreover, the temporal dimension is crucial; short-term effects on decomposition rates may differ significantly from long-term outcomes, as stabilization via mineral-associated mechanisms likely becomes more pronounced with prolonged weathering processes (Vicca et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe expert elicitation here suggests that EW may be a viable CDR strategy, with best estimates generally positive. Confidence in quantification remains a challenge - there are systemic uncertainties that still need to be properly characterized, including field-specific impacts on SOC, the role of secondary mineral formation in the deep soil, and the role of the biological community in freshwater systems (among others). Further, there is no widely agreed upon set of rules for quantifying EW-induced CDR (Nordahl et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and decisions made to guide estimates are not necessarily normative decisions about how carbon accounting should be done in CDR. For example, we chose to ignore the production emissions for steel slag and concrete waste from our global estimates as we assumed steel and concrete would be produced regardless of EW activity; for the other feedstocks (e.g. wollastonite) we included estimated emissions, assuming they would primarily be mined for EW. In general, any estimate of the EW scale potential hinges on assumptions such as these about the rules underlying carbon removal quantification.\u003c/p\u003e\u003cp\u003eUltimately, the value of EW as a CDR strategy rests on its ability to drive lower atmospheric greenhouse gas concentrations and climate warming, inclusive of upstream emissions and all system-level effects. However, the effects of agricultural production also need to be taken in account given the large greenhouse gas footprint of food production. The results here, while lower than many models or commercial estimates, suggest a real potential for EW to CDR. However, given the complexities of attributing change in atmospheric chemistry to any given process, quantification questions and data uncertainties are significant and should be resolved. A system-level perspective and strategic and focused research is necessary to place EW into the broader toolkit of CDR technologies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eExpert elicitation method\u003c/span\u003e\u003c/p\u003e\u003cp\u003eExpert elicitation is a research strategy designed to obtain informed, quantitative and qualitative judgments and uncertainty ranges from experts, in situations in which there is insufficient data to determine those values directly (Speirs-Bridge et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Morgan \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Morgan \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The methodology relies on judgments from experts who are qualified to address the fundamental mechanisms under consideration. We followed established protocols, focusing on quantifying best estimates and uncertainty (Hemming et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eDescription of process\u003c/span\u003e\u003c/p\u003e\u003cp\u003eExperts currently working on soil-based enhanced weathering for carbon dioxide removal were identified. Ultimately, we included 19 experts (research suggests that 6–12 experts are sufficient to get stable estimates; Hemming et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The experts spanned the terrestrial and aquatic domains. For reported expertise, see SI1.\u003c/p\u003e\u003cp\u003eThe expert elicitation process followed the protocol outlined in Hemming et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Briefly, participants were given a formal survey (described below; a copy at SI 1). Initial results were summarized, and the group was convened to ensure each question was perceived similarly by each participant (e.g., clarifying confusing language) and resolve discrepancies. We did not attempt to reach consensus or agreement on the estimated values or other responses. After the meeting, the survey was modified for clarity and reissued. The second round of survey responses, which could have matched or differed from initial survey responses, comprised the dataset analyzed here. Initial results were discarded.\u003c/p\u003e\u003cp\u003eFour respondents were not present for the mid-project meeting. Those participants were contacted to discuss the proceedings of the meeting, and they also re-did the survey. To ensure bias was not introduced by this process, their responses were noted as “remote”. We checked for systematic differences in the overall average global estimates and the overall efficiency estimates (see below for details) with and without the inclusion of the remote participants. As there was no significant difference (p \u0026gt; 0.05, ANOVA), results are presented with the entire pool of participants included.\u003c/p\u003e\u003cp\u003e\u003cem\u003eEstimating the net CDR potential of EW\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFirst, to assess the global scale potential of EW, participants were asked to provide their best estimate of the global CDR potential of each of six feedstocks independently: lime, basalt, concrete waste, olivine-rich rock (hereafter, olivine), steel slag, and wollastonite-rich rock (hereafter, wollastonite). This estimate included the entire system, including other GHGs (e.g., alterations to N\u003csub\u003e2\u003c/sub\u003eO production), organic carbon, and transport of the material. We also considered the entire production process for all feedstocks except steel slag and concrete waste. For those two feedstocks, which are waste products from ongoing manufacturing, emissions associated with that manufacturing were excluded. Constraints like material supply were considered but not quantitatively pre-determined (in other words, experts individually determined the likely magnitude of the future supply). Experts were then asked for their high-range estimate (95th percentile) and their low-range estimate (5th percentile) of CDR potential (in terms of CO\u003csub\u003e2\u003c/sub\u003ee). Lastly, they were asked how confident they were that their estimated range contained the true value, from 50% (e.g., the real value had an equal probability of falling in or out of their range) to 100% (complete certainty that the 95% range contained the true estimate). For the precise wording and conditions, see the questions (SI2)\u003c/p\u003e\u003cp\u003eSecond, to estimate where C may be lost to the atmosphere throughout the process, we focused on transfer efficiency through the overall EW system. While there is potential for EW deployment in a wide range of agroecosystems, we constrained the scenario to a hypothetical Midwestern US context to obtain realistic and comparable estimates. Specifically, efficiency estimates were for non-irrigated, non-tile drained loamy soils in the American Midwest with an average pH value of 5.5-6, a base saturation of 65%, and a cation exchange capacity (CEC) of 10 meq/100 mg. Participants assumed a feedstock grind size of \u0026lt; 100 um. The export pathway was through a major waterway (e.g., the Mississippi River) into the ocean. This hypothetical setting was constructed with the goal of selecting a representative setting that lacks characteristics of both ideal settings for EW (e.g., tile drains and very low CEC) and suboptimal settings (e.g., arid regions). The stages of this pathway were 1) the agricultural field, 2) deeper soils and groundwater, 3) freshwater streams, 4) nearshore marine systems, and 5) deep water marine systems. Participants were asked not to consider potential interactions with the organic C cycle (e.g., EW-induced changes in soil organic C cycling) in these transfer efficiency estimates (see Discussion).\u003c/p\u003e\u003cp\u003eEach stage was framed individually. The field-stage involved application of raw feedstock to the bottom of the layer actively ploughed/tilled. The relevant questions were framed as “if enough material were applied to potentially fix 10 tons CO\u003csub\u003e2\u003c/sub\u003e”, such that the expert’s estimates include judgement on the fraction of feedstock dissolved over the considered timeframe (20 yrs). The deep soil stage encompassed the movement of C captured in the field stage from the bottom of the tilling zone to free-flowing freshwater. For this and all other stages, transport efficiency (pass-through fraction, or the proportion of C which enters that stage which then moves through to the next stage) were assessed with a starting condition of 10 tons of fixed C entering that stage. The freshwater stage extended from free-flowing drainage from a field to brackish estuarine systems. The coastal ocean stage encompassed brackish water and the nearshore mixing zone. The marine stage included deeper waters. We allowed that C might be resident within each stage for up to 20 years. Ultimately, storage was considered to be \u0026gt; 100 years in the ocean. The same range and confidence estimates used in the global estimate were collected at each stage (5th, 50th, 95th percentile, and certainty in range estimate). Because stages were evaluated independently, they could not be combined to calculate an overall field-to-marine pass-through fraction. So, a final question evaluated the anticipated fraction of the material that would successfully move through all stages from field application to marine deposition.\u003c/p\u003e\u003cp\u003eIn addition, for each stage, experts were asked to estimate the current measurement error they would expect if we quantified efficacy by feedstock and stage. For example, a measurement error of 100% suggested the error in measuring EW efficacy at that stage was roughly the same as the magnitude of the CDR process itself, whereas an error of 200% meant the uncertainty was double that of the process itself.\u003c/p\u003e\u003cp\u003eExperts were also asked about the potential for each feedstock to cause significant human or environmental harm if deployed at broad scales (for each stage). Lastly, they were asked qualitative questions at each stage and feedstock regarding the three most important variables that influenced their estimate and the three most important unknowns which, if better constrained, would improve the certainty of their estimate.\u003c/p\u003e\u003cp\u003eHere, data are primarily presented as the full range of individual responses, to transparently display the range of estimates obtained. Because individuals expressed differential levels of certainty in their range estimates, the ranges were standardized to their 80th percentile credible intervals following Hemming et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Raw range estimates and certainty estimates are available in the source data. Where necessary, summary statistics such as means and ranges are included. All responses (anonymized) are available at SI2.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of Interest\u003c/h2\u003e\u003cp\u003eThe authors declare no conflict of interest. NP was a co-founder of Lithos Carbon but has no financial ties to the company. CD acts as a scientific advisor to the Rock Flour Company, but does not receive financial compensation for the role.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eBB was supported gifts from Christina and Jeffrey Bird and Mary Anne Baker and G. Leonard Baker, Jr. EO and DG were partially supported by King Philanthropies. MA, SZ, JH, NP, and TJS acknowledge funding from the Department of Energy (DOE) Earthshot Initiative (#DE-SC0024709). TJS acknowledges funding from the Swiss National Science Foundation (P500PN_210790).\u003c/p\u003e\u003ch2\u003eData and Code Availability\u003c/h2\u003e\u003cp\u003eAnonymized data and R code to replicate the analyses are available on Zenodo: \u0026ldquo;Expert elicitation on agricultural enhanced weathering suggests potential for significant carbon dioxide removal and highlights uncertainties in loss pathways.\u0026rdquo; Data set. 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Effectiveness and characteristics of atmospheric CO2 removal in croplands via enhanced weathering of industrial Ca-rich silicate byproducts. Frontiers in Environmental Science, 10, p.1068656.\u003c/li\u003e\n\u003cli\u003eZhang, S., Planavsky, N.J., 2019. Revisiting groundwater carbon fluxes to the ocean with implications for the carbon cycle. Geology 48, 67\u0026ndash;71. https://doi.org/10.1130/G46408.1\u003c/li\u003e\n\u003cli\u003eZhang, S., Planavsky, N.J., Katchinoff, J., Raymond, P.A., Kanzaki, Y., Reershemius, T., Reinhard, C.T., 2022. River chemistry constraints on the carbon capture potential of surficial enhanced rock weathering. Limnol. Oceanogr. 67, S148\u0026ndash;S157. https://doi.org/10.1002/lno.12244\u003c/li\u003e\n\u003cli\u003eZhang, S., Reinhard, C. T., Liu, S., Kanzaki, Y., \u0026amp; Planavsky, N. J. (2025). A framework for modeling carbon loss from rivers following terrestrial enhanced weathering. Environmental Research Letters, 20(2), 024014. https://doi.org/10.1088/1748-9326/ada398\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7040857/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7040857/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEnhanced weathering (EW) in agriculture is a potential gigatonne-scale carbon dioxide removal (CDR) pathway. The true scale of potential CDR remains difficult to constrain due to its complexity across the entire field-to-ocean pathway and a paucity of system-level empirical data. We used a formal expert elicitation process to quantify the ranges of best CDR estimates, uncertainties, and key data needs for six EW feedstocks. Expert opinion of the CDR potential varied by feedstock, with estimates averaging 0.2-0.7 Gt CO2e/yr, but with a wide range (less than zero to greater than 5 Gt CO2e/yr). The efficiency of CDR, meaning the fraction of potential CDR ultimately realized from a given amount of material applied ranged from 27-39%. Key constraints included feedstock availability at scale (especially for wollastonite), calcite saturation, secondary clay formation, and deep soil/freshwater emission pathways. The results suggest a strong need for additional data collection (given deployments are already occurring), leveraging existing data on liming where appropriate, and continued study as applications occur at scale. Overall, there appears to be significant CDR potential for EW at broad scales, though quantification and underlying data uncertainties are significant and should be resolved.\u003c/p\u003e","manuscriptTitle":"Expert elicitation on agricultural enhanced weathering highlights CO2 removal potential and uncertainties in loss pathways","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-30 04:58:28","doi":"10.21203/rs.3.rs-7040857/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-earth-and-environment","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsenv","sideBox":"Learn more about [Communications Earth and Environment](https://www.nature.com/commsenv/)","snPcode":"","submissionUrl":"","title":"Communications Earth \u0026 Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1b87046f-5aba-4426-948b-18f631030ded","owner":[],"postedDate":"July 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":52339319,"name":"Earth and environmental sciences/Biogeochemistry/Carbon cycle"},{"id":52339320,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry"},{"id":52339321,"name":"Earth and environmental sciences/Planetary science/Geochemistry"}],"tags":[],"updatedAt":"2026-04-28T07:10:48+00:00","versionOfRecord":{"articleIdentity":"rs-7040857","link":"https://doi.org/10.1038/s43247-026-03375-5","journal":{"identity":"communications-earth-and-environment","isVorOnly":false,"title":"Communications Earth \u0026 Environment"},"publishedOn":"2026-03-12 04:00:00","publishedOnDateReadable":"March 12th, 2026"},"versionCreatedAt":"2025-07-30 04:58:28","video":"","vorDoi":"10.1038/s43247-026-03375-5","vorDoiUrl":"https://doi.org/10.1038/s43247-026-03375-5","workflowStages":[]},"version":"v1","identity":"rs-7040857","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7040857","identity":"rs-7040857","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}