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      Impact of Climate on the Global Capacity for Enhanced Rock Weathering on Croplands

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          Abstract

          Enhanced rock weathering (ERW) on croplands has emerged as an economically and ecologically promising negative emissions technology. However, estimated total carbon sequestration potential from ERW on croplands and its potential sensitivity to climate conditions requires further understanding. Here we combine 1‐D reactive transport modeling with climate model experiments to simulate ERW on ∼1,000 agricultural sites globally. Applying a fixed rate of 10 tons of basalt dust per hectare on these sites sequesters 64 gigatons of CO 2 over a 75‐year period; when extrapolated to all agricultural land, ERW sequesters 217 gigatons of CO 2 over the same time interval. However, we find that a significant fraction of applied basalt does not weather even on a multidecadal timescale, indicating the need to optimize application strategies for cost effectiveness. We find that ERW becomes modestly more effective with global warming and predict that the payback period for a given ERW deployment is significantly shorter in hot and humid environments currently coinciding with relatively low per‐capita incomes. These results provide strong impetus for investment in agricultural reform in developing economies and highlight an additional potential co‐benefit of ERW.

          Plain Language Summary

          Enhanced rock weathering (ERW) on croplands is a promising negative emissions concept that accelerates natural weathering by amending soils with crushed rock. Our simulations of ERW with a fixed rate of 10 tons of basalt dust per hectare on all global croplands suggest ERW can sequester >200 gigatons of CO 2 over a 75‐year period. This suggests that cost and logistical concerns, rather than weathering potential, are likely to be the key limiting factors for large‐scale deployment of enhanced weathering. Notably, ERW is resilient to global climate change and becomes more effective with global warming. ERW is moreover far more efficient in hot and humid environments currently coinciding with relatively low per‐capita gross domestic product economies. Our study provides strong support for the assertion that ERW represents a resilient carbon capture strategy that is non‐competitive for arable land and can foster CO 2 removal at the gigaton scale.

          Key Points

          • Enhanced rock weathering (ERW) with fixed annual application rates of 10 tons of basalt dust per hectare on 1,000 global cropland sites sequesters 64 gigatons of CO 2 over 2006–2080

          • Extrapolated to all croplands, ERW with a fixed application rate of 10 tons of basalt dust per hectare sequesters 215 gigatons of CO 2 over 2006–2080

          • ERW is resilient to global climate change but is much more efficient over hot and humid environments

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          Most cited references53

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          A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests

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            SoilGrids250m: Global gridded soil information based on machine learning

            This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods—random forest and gradient boosting and/or multinomial logistic regression—as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10–fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.
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              Temperature sensitivity of soil carbon decomposition and feedbacks to climate change.

              Significantly more carbon is stored in the world's soils--including peatlands, wetlands and permafrost--than is present in the atmosphere. Disagreement exists, however, regarding the effects of climate change on global soil carbon stocks. If carbon stored belowground is transferred to the atmosphere by a warming-induced acceleration of its decomposition, a positive feedback to climate change would occur. Conversely, if increases of plant-derived carbon inputs to soils exceed increases in decomposition, the feedback would be negative. Despite much research, a consensus has not yet emerged on the temperature sensitivity of soil carbon decomposition. Unravelling the feedback effect is particularly difficult, because the diverse soil organic compounds exhibit a wide range of kinetic properties, which determine the intrinsic temperature sensitivity of their decomposition. Moreover, several environmental constraints obscure the intrinsic temperature sensitivity of substrate decomposition, causing lower observed 'apparent' temperature sensitivity, and these constraints may, themselves, be sensitive to climate.
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                Author and article information

                Contributors
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                Journal
                Earth's Future
                Earth's Future
                American Geophysical Union (AGU)
                2328-4277
                2328-4277
                August 2023
                August 14 2023
                August 2023
                : 11
                : 8
                Affiliations
                [1 ] Department of Earth and Planetary Sciences Yale University New Haven CT USA
                [2 ] School of Earth and Atmospheric Sciences Georgia Institute of Technology Atlanta GA USA
                [3 ] Yale Center for Natural Carbon Capture Yale University New Haven CT USA
                [4 ] Department of Oceanography Texas A&M University College Station TX USA
                Article
                10.1029/2023EF003698
                7c4d07be-bbd4-471c-a458-d0d5ed15a170
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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