Carbon capture process

Abstract

A computer-implemented method for estimating carbon capture through enhanced weathering. Input data is received, comprising location data 710 and enhanced weathering material data 712. A plan is gener

Description

Field The present invention relates to a method of carbon sequestration. More particularly, the present invention relates to a computer-implemented method for estimating carbon capture through enhanced weathering of areas of land and then determining and optimising an enhanced weathering process for these areas of land and / or selecting areas of land for enhanced weathering within a larger area being considered and / or verifying the carbon capture achieved on the selected areas of land and / or replanning the enhanced weathering process following verification. Background The release of greenhouse gas emissions caused by human activities, for example as a result of burning fossil fuels, has been the main driver of climate change since the 1800s. Climate change refers to the long-term shifts in global temperatures and weather patterns, and greenhouse gas emissions, such as carbon dioxide emissions, act like a blanked wrapped around the earth and trap the suns heat and raise global temperatures. As a result of human activities causing climate change, global temperatures are around 1.1 degrees Celsius higher than in the late 1800s. The consequences of climate change, and of the climate continuing the change in future, will be severe and therefore there is a global effort to reduce adverse climate change. The process of enhanced weathering uses natural weathering effects but at an accelerated rate to capture carbon dioxide from the atmosphere and sequester it in the ground. In natural weathering, atmospheric carbon dioxide dissolves in rainwater to form weak carbonic acid, which in combination with soil carbon dioxide (from microbial respiration and root exudates) dissolves silicate minerals such as olivine, pyroxene and plagioclase. This releases solutes such as bicarbonate (HCO3-) and carbonate (CO3-) anions, as well as cations such as calcium (Ca2+) and magnesium (Mg2+) into soil porewaters (i.e. free water present in a soil, normally under hydrostatic pressure and which affects the shear strength of the soil). These solutes can be precipitated as pedogenic carbonate minerals in soils (which act as a short term carbon sink) or transported via rivers to the oceans (where carbon dioxide is sequestered by the precipitation of carbonates (CaCO3). The contribution of bicarbonate to the ocean can counteract ocean acidification. The physical and chemical breakdown of silicate rocks on the Earth’s surface as part of natural weathering is a fundamental process controlling atmospheric carbon dioxide levels and, in turn, the climate. Over geological time scales, the natural weathering of rocks of basaltic composition sequesters around 180 million tons of carbon dioxide annually. Soil also contains soil organic carbon, but this is vulnerable to reversals due to changes in land management practices whereas the dissolution of the silicate rock is not susceptible to such reversibility. In enhanced weathering, the natural process of weathering is accelerated through the spreading of highly reactive, finely crushed silicate rock such as basalt, or minerals such as olivine or wollastonite across forests and urban or agricultural soils. The process of spreading rock with an increased reactive surface area has the potential to sequester gigatons of atmospheric carbon dioxide and thereby help mitigate climate change. It is therefore desirable to be able to determine how much carbon can be sequestered via enhanced weathering and to optimise the process of enhanced weathering. Summary of Invention Aspects and / or embodiments seek to provide a method and system for determining one or more enhanced weathering configurations for applying enhanced weathering to one or more surfaces. In embodiments, a measurement, reporting and verification process is provided that is built around data integrity and comprehensive empirical in-field measurement to provide confidence in quantifying carbon sequestration and provide a process that can be used for gigatonne-scale removal in future. In embodiments, quantification data can be used with a predictive geochemical weathering model to improve the accuracy of the model. According to a first aspect, there is provided a computer-implemented method comprising: receiving input data, the input data comprising location data of at least one location and enhanced weathering material data of at least one enhanced weathering materials; generating a plan to apply the at least one enhanced weathering materials to the at least one location; generating an estimate of carbon capture over time at the at least one location using the input data when applying the at least one enhanced weathering materials to the at least one location based on the generated plan; generating an estimate of pH over time at the at least one location using the input data when applying the at least one enhanced weathering materials to the at least one location based on the generated plan; outputting the estimate of carbon capture over time at the at least one location, the estimate of pH over time at the at least one location, and the plan. By generating a plan for application of enhanced weathering that also provides an estimate of carbon captured and pH of the land to which enhanced weathering is to be applied, plans can be generated that allow assessment of improvements to the fertility of the land to undergo enhanced weathering as well as an assessment of the amount of carbon captured. Optionally, generating the plan comprises generating an initial plan and then iterating generation of revised plans using the generated estimate of carbon capture over time and the generated estimate of pH over time for the initial plan. By iterating the plan for enhanced weathering using the estimated values for carbon capture and soil pH, plans can be iterated to improve the outcome of an enhanced weathering process. Optionally, the method further comprises optimising the iterating generation of revised plans in order to substantially maximise the estimate of carbon capture and / or stabilise the estimate of pH over time. By optimising an enhanced weathering plan to either maximise carbon capture and / or to stabilise pH overtime, optimised enhanced weathering processes can be implemented that either maximise utility to a farmer or maximise the capture of carbon from the atmosphere or balance these two outcomes. Optionally, the input data comprises any or any combination of: air temperature data; air temperature data over time; pH data; pH data over time; precipitation data; precipitation data over time; electrical conductivity data; electrical conductivity data over time; in-field measurement data; sensor data; meteorological data; live data; soil mesocosm data; time series data. By taking in a variety of input data, improved predictions of soil state and / or carbon capture can be generated by embodiments. Optionally, the location data comprises any or any combination of: grid co-ordinates of each location; satellite data of each location; topographic data of each location; boundary data of each location; dimension data of each location. By having precise location data, the plan for enhanced weathering of a site can be tailored to the specific site. Optionally, the enhanced weathering material data comprises any or any combination of: geochemical composition; pH; particle size distribution; density; average particle surface area; size categories of bulk material; source information. By having precise bulk material data, the plan for enhanced weathering of a site can be tailored to the materials available for enhanced weathering. Optionally, the method further comprises a three-stage model wherein the three-stage model comprises an initial soil solids model, a soil solution model and an evolved soil solids model; wherein generating the estimate of carbon capture over time and / or generating the estimate of pH over time comprises using the three-stage model; optionally wherein the soil solution model interacts with any or any combination of: a basalt application model; an atmosphere model; a plant model; a water model. By providing a three-stage model, the situations before, during and after enhanced weathering can be predicted in order to improve estimates of carbon capture and / or soil state. Optionally, the plan comprises any or any combination of: determining which at least one location to which enhanced weathering processes will be applied; determining one or more portions of the at least one location to which enhanced weathering processes will be applied; determining one or more time periods during which enhanced weathering processes will be applied to each of the at least one locations; one or more selections of enhanced weathering materials to be applied to each at least one location. By determining which portions of land should have enhanced weathering applied, it can be possible to maximise the utility of enhanced weathering processes where constrained by resources to implement enhanced weathering across an entire available area of land. Optionally, generating the plan comprises assessing whether to apply enhanced weathering processes to each of the at least one locations based on one or more predetermined thresholds; optionally wherein the one or more pre-determined thresholds comprise any or any combination of: an amount of carbon predicted to be sequestered; a predicted pH overtime; a minimum pH; a maximum pH. Determining which areas of available land should be subject to enhanced weathering can be performed based on one or more predetermined criteria or thresholds, allowing for a more automated and objective assessment to be made as part of plan generation. Optionally, the method further comprises performing enhanced weathering using the generated plan, optionally wherein performing enhanced weathering comprises periodically applying enhanced weathering materials to each at least one location a plurality of times. Performing the generated plan can be automated or implemented manually, following generation, iteration or optimisation of an enhanced weathering plan. Optionally, the method further comprises performing verification of the generated estimate of carbon capture over time following performing enhanced weathering using the generated plan; optionally wherein verification is performed by taking measurements of geochemical parameters at each at least one location. By verifying the planned carbon capture and soil state, implemented enhanced weathering plans can be assessed. Optionally, the method further comprises generating a revised plan to apply the at least one enhanced weathering materials to the at least one location following performing verification of the generated estimate of carbon capture over time; and performing the revised plan. By revising the plan and / or re-implementing or re-performing enhanced weathering following verification of estimated carbon capture / soil state values, carbon capture and / or soil states can be optimised. Optionally, generating either or both of (i) an estimate of carbon capture over time; and (ii) an estimate of pH over time; is performed using one or more simulations; optionally wherein the one or more simulations comprise Monte Carlo simulations. By performing Monte Carlo simulations, a variety of possible time series values, carbon capture estimates and / or soil state estimate can be generated to allow a better understanding of the possible minimum and maximum effects of an enhanced weathering process being applied. Optionally, the generated plan seeks to optimise at each at least one location a stabilised pH over time within a predetermined range of pH values. By optimising a soil state or pH value in a area of land, enhanced weathering processes can be applied that improve or optimise fertility for a given area of land for a farmer while also providing a mechanism for carbon sequestration. Brief Description of Drawings Embodiments will now be described, by way of example only and with reference to the accompanying drawings having I ike-reference numerals, in which: Figure 1 shows an overview of enhanced weathering using bulk material created from basaltic rocks that are crushed and applied to forests or agricultural land according to an embodiment; Figure 2 shows an example of the particle size distribution in a typical sample of bunk material that can be used for enhanced weathering applications according to an embodiment; Figure 3 shows the measured surface area for each size category of the bulk material shown in Figure 2; Figure 4 shows an overview of an enhanced weathering process for applying bulk material to agricultural land using farm machinery according to an embodiment; Figure 5 shows the enhanced weathering process of Figure 4, where the enhancing weathering process has been partially applied to some of the fields on a farm according to an embodiment; Figure 6 shows an overview of an enhanced weathering model according to an embodiment of the invention; Figure 7 shows an embodiment using the enhanced weathering model of Figure 6 to develop and optimise an enhanced weathering plan; Figure 8 shows an embodiment of a verification process for carbon captured via enhanced weathering; Figure 9 shows an illustration of the use of sensors on farmland that has had an enhanced weathering process applied according to an embodiment; Figure 10 shows an embodiment of a series of steps to optimise an enhanced weathering process; Figure 11 shows an illustration of two graphs showing carbon captured, where Figure 11a shows predicted carbon capture before an enhanced weathering is applied including error bars and Figure 11b shows the same location at a later point in time where real data allows the error bars for the remaining future predicted carbon capture to be constrained, all according to an embodiment; Figure 12 shows example data output to further illustrate the data plotted in Figures 11a and 11b; Figure 13 shows an example extract of data for one month from the plot in Figure 12; and Figure 14 shows an example set of data recording the path of an enhanced weathering spreading operation plotted on a satellite map. Specific Description Referring to Figure 1, an overview of enhanced weathering 100 according to an embodiment will now be described. Basaltic rock 110 is extracted from the ground at a quarry or mine and stored or transported as a variety of sizes of rocks and / or aggregate, as the quarrying or mining process is likely to produce some large rocks but also a variety of sized smaller rocks, stones and aggregate. The basaltic rock 110 is then introduced to a crusher 120, which might require that some of the large sized rocks are manually reduced in size to fit into the crusher 120, and the crusher 120 reduces the size of at least some of the rocks and / or aggregate to a more consistent size of particle / aggregate. This process of crushing may happen in stages, and sometimes involved multiple different crusher 120 machines that iteratively reduce rock / stone / particle size. The output of the crusher 120 (or crushers 120) is crushed basalt 130 of a certain range of particle sizes. This crushed basalt 130 can also be referred to as bulk material. The crushed basalt 130 can then be spread upon the surface of the ground in forests and / or agricultural land 140. Rain 150 falls periodically on the forests and / or agricultural land 140 and the crushed basalt 130 absorbs carbon dioxide in the atmosphere as it reacts with the water in the rain 150 and produces various solutes by chemical reaction. These solutes are then carried away by the rain 150 as it enters the water system first via streams and rivers neighbouring the forests and / or agricultural land 140 and then on to the seas and oceans thereby depositing the solutes as oceans carbonate materials 160. This process allows for the capture and sequestration of carbon dioxide from the atmosphere. The quantification of carbon dioxide removal can be based on the results of the PHREEQC geochemical platform, which is a computer program that is designed to perform a wide variety of aqueous geochemical calculations. The PHREEQC platform implements several types of aqueous models, including two ion-association aqueous models, and has been developed by the US Geological Survey. This programme / model can be used to simulate chemical reactions and transport processes in natural or polluted water, for example in laboratory experiments or in industrial processes. The program is based on equilibrium chemistry of aqueous solutions interacting with mineral, gases, solid solutions, exchangers and sorption surfaces, but the programme has evolved to include the capability to perform further modelling. The model can be used, along with data from tracing the products of weathering (such as calcium and magnesium ions or bicarbonate), to calculate how much carbon dioxide is sequestered in the ocean as bicarbonate stored as calcium or magnesium carbonate. Specifically, how much carbon dioxide is sequestered is modelled using the predicted major ion release based on the dissolution of the minerals present within the basalt used in embodiments as the bulk material during enhanced weathering and the modelling can be corrected or adjusted based on measured major ion concentrations, for example from field studies or mesocosms, based on the geochemical calculations performed using the model using the proportions of minerals in the basalt and kinetic and thermodynamic data. Soil mesocosms aim to replicate climate and soil conditions for a region of interest, e.g. a field to be assessed for enhanced weathering. Soil mesocosms incorporate the complexity of soils in a controlled lab environment, including plants or microbes. This approach allows measurement of an enhanced weathering signal in a closed system. In an embodiment, multiple soil cores are taken from a site of interest or from a representative site (i.e. representative of the climate and soil conditions that apply) and a minimum of ten soil cores (five control and five Basalt-amended) will be sampled down to a 30cm depth. For the Basalt-amended cores, application densities will be used that replicate the planned enhanced weathering activities, using well characterised Basalt. The soil cores are housed in a temperature-controlled laboratory that allows for a controlled ambient atmospheric CO2 composition. Using peristaltic pumps, the soil mesocosms will be irrigated at the top of the column and effluent water will be collected at the bottom. This will enable the replication of the seasonal precipitation variations at the side, based on high-resolution, long-term meteorological data (such as available from the UK Meteorological Office). For both control and Basalt-amended mesocosms, pH, electrical conductivity and alkalinity of the effluent solutions will be measured. Additionally, major ion concentrations will be determined on a subset of samples. By comparing the control cores with the Basalt-amended cores, background weathering can be accounted for and the dissolution rate of the added Basalt can be calculated. Estimation of the cumulative amount of CO2 sequestered by enhanced weathering is calculated by measuring the difference in CO2 sequestered between the start and the end of the mesocosm trials, and this is calculated using the model and proxy measurements such as pH, alkalinity, electrical conductivity (EC) and major ion concentration. Referring now to Figure 2, an overview of the particle size distribution in the bulk material 200 used in enhanced weathering according to an embodiment will now be described. Bulk material produced by the quarrying and crushing process described in relation to Figure 1 above can have a range of particle sizes, either naturally or as a result of the quarrying or crushing processes. A typical example of the distribution 200 of particle sizes 220 (ranging from less than 0.063mm up to more than 4mm in diameter as shown in Figure 2) is shown against the fraction of a given volume of bulk material 210 (ranging from 0% to 40% as shown in Figure 2). In other examples, different distributions might be found, and it might be possible to predict the distribution for a particular quarry and crushing process given enough previous data. Referring now to Figure 3, an overview of the measured surface area of each particle size distribution category 300 as shown in Figure 2 in the bulk material used in enhanced weathering according to an embodiment will now be described. The bulk material produced by the quarrying and crushing process described in relation to Figure 1 above can have a range of particle sizes, either naturally or as a result of the quarrying or crushing processes as shown in Figure 2, but the measured surface area 310 of each size category of bulk material 320 does not vary in an intuitive way across size classes, as shown in the distribution plotted for the sample in Figure 3, where the surface area in m2 / g varies from approximately 15 m2 / g for the largest category of particle size down to approximately 11 m2 / g and then back up to approximately 19 m2 / g for the smallest category of particle size. In some embodiments, detailed data is recorded across the entire supply chain to ensure that the life cycle analysis of carbon expenditure, where possible, relies on primary data (such as GPS or calibrated weight cells) using an operational data management system to track bulk material / feedstock from quarry to enhanced weathering location. The detailed data recorded in the operational data management system can include geochemical, mineralogical and structural detail of the rock, where that rock has been spread, any confirmation data to prove that the operations have been delivered, accurate project emissions from quarry to field (e.g. from transport vehicles used to move the rock and from quarrying and crushing operations). In some embodiments, most of all of this data is collected in real time using embedded sensors and / or software with user input via a user interface where required. By collecting this data, traceability back from the carbon captured to the specific type of rock spread on a specific field can be established and matched up with modelled carbon capture. Referring now to Figure 4, an overview of a process for enhanced weathering techniques being applied to farmland 400 according to an embodiment will now be described. As described more generally earlier in respect of Figure 1, quarry machinery 410 extract quarried rocks 110 such as basalt and these are crushed 120 into crushed rocks or bulk material 130. The crushed rocks 130 are then transported to the location where they will be applied, such as a farm, and loaded into a crushed rock spreader 430 which is typically attached to farm machinery 420 such as a tractor or other vehicle. The crushed rock spreader 430 can be any type of vehicle or vehicle attachment that is able to contain and spread the crushed rocks. The crushed rocks are then spread 440 onto the farmland 140 for which enhanced weathering is to be carried out. As part of the enhanced weathering process, the farmland 140 has its soil enhanced by the chemical process that occurs when the crushed rocks 130 are applied to the farmland 140. Referring now to Figure 5, an overview of a process for enhanced weathering techniques being applied to farmland 500 according to an embodiment will now be described. The land on the example farm is split into the farmland 140 on which enhanced weathering will take place and the non-weathered land 510 that is not to be subject to enhanced weathering. The farm machinery 420 moves the crushed rock spreader across the farmland 140 and spreads the crushed basalt bulk material 430 on the surface of the farmland 140. Data is collected from the spreading operation and the path of the spreading operation and the amount of rock spread is stored in a database. An example path 1400 is shown in Figure 14, with the path taken plotted on a satellite photo 1410 of the site to which enhanced weathering operations are being performed. Referring now to Figure 6, there is shown an enhanced weathering model 600 according to an embodiment, which will now be described in more detail. The enhanced weathering model 600 is made up from three sub-models: (i) an initial soils model 615; (ii) a soil solution model 620; and (iii) a evolved soil solids model 635. The initial soils model 615 aims to model the state of the location to which enhanced weathering processes will be applied prior to the application of these processes, i.e. before the application of the bulk material to the soil. This model 615 works by taking some input data, which in this embodiment is precipitation data, pH data, and temperature data, and determining the current properties of the soil to which enhanced weathering will be applied. Next, the soil solution model 620 aims to model what happens when the enhanced weathering process occurs, i.e. when the bulk material is applied to the soil. To do this it takes input from four models: (a) a basalt application model 610; (b) an atmosphere model 625; (c) a plant model 630; and (d) a water model 640. In this embodiment, the soil solution model 610 is configured based on data generated from measuring the difference in the concentrations of a mobile element in the feedstock after weathering, relative to before weathering. Elements such as titanium and rare earth elements can be used as an immobile tracer to calculated Mg2+ and Ca2+ release rates. Titanium and other rare earth elements are present as insoluble primary minerals, or form stable secondary minerals that are not readily removed from the solid phase. The initial soils model 615 either receives data and / or estimates the original ratio of these immobile tracers to major cations within the bulk material (e.g. the basalt applied during enhanced weathering) which can be used by the soil solution model 620 to calculate the concentration of released weathering products based on the change in the concentration of the immobile tracer in pre- and post- weathering soils. This allows the soil solution model 620 to predict the maximum amount of carbon dioxide removal, as cations may be lost due to weathering by non-carbonic acids, plant uptake, or removed on to soil exchangeable sites. Data on the elemental concentrations can be gathered using inductively coupled plasma mass spectrometry in rock and soil samples, either to use as training data for the model or for verification. Pairing the mass balance approach (i.e. estimating or measuring mobile cation to immobile trace element ratios) with soil pore water analysis of nitrite / nitrate and sulfate concentrations allows for estimation of non-carbonic acid based weathering in order to account for cations adsorbed on to exchangeable sites (for example where samples are leached with ammonium acetate). The basalt application model 610 takes input data pertaining to the properties of the bulk material to be applied to the soil and models the geochemical properties of the bulk material based on this input data. In embodiments, the basalt application model 610 is able to predict, using prior data and / or input data, chemical dissolution of minerals within the rock, saturation information and changes in surface area with weathering shrinking the bulk material. In this embodiment, for each quarry used to obtain bulk material, data is gathered on the bulk material including geochemical (XRF, ICP MS), mineralogical (XRD) and physical properties (PSD, SSA, moisture content). Surface area is also a very important variable for understanding mineral dissolution and is an input to the geochemical weathering model 600 / basalt application model 610 and is typically measured for every feedstock / bulk material sample. An assessment of the heterogeneity of the feedstock geochemistry and mineralogy is also made for samples of the feedstock / bulk material. The bulk material minerology is an input parameter in the geochemical weathering model 600 / basalt application model 610. The mineral composition in addition to published solubility and dissolution rate constants allows for estimation of cation release and hence CO2 sequestration by charge balance. In some embodiments, to provide data for the basalt application model 610 and / or to assess the bulk material, x-ray diffraction is used to determine the mineralogy of sample of bulk material, to assess the suitability of a rock source for enhanced weathering operations. X-ray diffraction also has the capability to identify small quantities of carbonate materials (which, while these weather quickly, remove only 50% of the CO2 from the atmosphere via weathering relative to that of a silicate material) and thus can be used to assess whether there is a significant proportion (i.e. more than 1%) of carbonate present in the rock as this is needed to interpret both model and field results. In some embodiments, the elemental composition of the bulk material is screened using ICP-OES or ICP-MS to assess whether any potentially toxic elements are present and in what quantities. If these quantities are over a pre-determined threshold, bulk material can be prevented from being used in enhanced weathering. In embodiments, mafic rock sources are used (e.g. basalt) and in other embodiments, faster weathering (but with limited supply) rocks are used (e.g. wollastonite skarn). The atmosphere model 625 takes input data pertaining to the expected range of temperature at the location to which enhanced weathering processes will be applied and models the typical atmospheric conditions expected following the application of the bulk material to the soil. The plant model 630 models the effects of the growth of any plant matter present at the location, for example crop growth, forestry growth or other plant matter such as weeds. The plant model 630 aim to estimate cation loss via plant uptake, using data from analysis of cation concentration in crop biomass (roots, shoots and grain) which can be performed on field monitoring sites and in experiments in order to be able to predict this for sites with limited data. The water model 640 models the pore water at the location to which enhanced weathering processes will be applied. During silicate weathering in acidic conditions, protons are “consumed” during the mineral dissolution reactions, and base cations (e.g. Ca2+, Mg2+, Na* and K*) are released from the mineral structure, and carbonic acid is converted to bicarbonate (HCO3). Pore water analysis allows for characterisation of the products of weathering, such as pH, electrical conductivity, major cations and anions and alkalinity, in order to be able to estimate carbon sequestration. The water model 640 receives at least some data and predicts the pore water properties for the site of interest based on previous data gathered in field or in experiments. An increase in power water pH, base cation concentrations and bicarbonate concentrations (which can be inferred from alkalinity) can be observed when bulk material / basalt is amended into soils / used for enhanced weathering. Experimental and in-field measurements gather data on changes in pH, cation concentration and alkalinity in pore water at different soil depths, which can also be used to quantify carbon dioxide removal in combination with the mass balance approach (described elsewhere) as well as being integrated into the weathering model for calibration. The soil solution model 620 determines the impact of the various factors modelled by the basalt application model 610, atmosphere model 625, plant model 630 and water model 640 starting from the output of the initial soil solids model 615 and the input data provided to the model 600. The output of the modelling is an evolved soil solids model 635, which can be used to predict the soil state over time following application of the enhanced weathering processes. For example, this model 635 can be used to determine predictions for the pH of the soil over time and the carbon capture of the soil over time. In embodiments, the model combines the mass balance measurement with pore water analysis to provide a prediction of carbon dioxide removal for a given soil type, taking into account farming practices and crop type. By gathering data over a number of monitoring sites where both pore water data and mass balance data at high sampling rates are acquired, it is possible to determine the delta between total weathering and carbonic acid weathering and therefore carbon dioxide removal. This delta can be used by applying it as a correction factor to mass balance results obtained from the land subject to enhanced weathering, either to existing weathering predictions by way of verification / reduction of error bars on predictions or to use as training data for future predictions. In some embodiments, an assessment is made as to whether or not to apply enhanced weathering processes to an area of land. Due to the difference in solubility of carbonate materials in soils, where weathering takes place, and rivers, where bicarbonate is transported, the precipitation of secondary carbonate (for example, pedogenic or river carbonate) can occur which releases the CO2 consumed during weathering and thereby reduces the efficiency of sequestration through enhanced weathering by 50%. The proportion of CO2 stored as carbonate materials is unknown, and little research has directly assessed the permanence of removal. The formation of pedogenic carbonate occurs when minerals such as calcite are supersaturated in soil pore waters, and can lead to carbonate precipitation. Pedogenic carbonate formation is more likely under specific conditions, for example in regions with low or intermittent precipitation and high evapotranspiration (i.e. arid to semi-arid locations), or in regions with irrigation systems, or in soils with additions of dolomite, gypsum or lime, and high Mg minerals, or where the application or organic and mineral amendments results in higher soil inputs of Ca, Mg and Sodium. To mitigate these risks, in some embodiments the plan output by the method avoids applying bulk material to such soils. Further, the plan output by the method avoids using basalts that contain significant amounts of carbonate as it does not contribute to the carbon dioxide removal (CDR) function of the rock. Where sites have pedogenic carbonate identified as being present, closer monitoring of the sites will need to be performed. Other processes that potentially slow down the weathering process, such as passivation of the surface of the basalt particles by secondary minerals or formation of a silica rich surface layer that inhibits further weathering can be used to threshold planning to prevent incorrect bulk materials being applied and sites that may have a low sequestration efficiency can be removed from the planned enhanced weathering operations. In some embodiments, advanced machine learning techniques (such as deep neural networks and / or supervised auto-encoders) are used / combined with precise hydrological measurements from satellite data and / or global datasets to develop a predictive model that can predict carbon dioxide leakage from rivers / stream transport in areas of interest. In some embodiments, the inputs include information on the crushed Ca- and Mg- rich silicate rock mineralogy, specific surface area and density of the application (of bulk material), site-specific soil chemical composition (starting soil pH, cation exchange capacity) and physical parameters (bulk density and water-filled porosity) and high-resolution, long-term climate (precipitation, soil temperature data). In some embodiments, instead of performing experiments and taking samples, local site-specific soil chemical and physical parameters, as well as climate parameters, are either taken directly or calculated from parameters from globally harmonised datasets such as from the Harmonised World Soil Database or EU Copernicus ERA5-Land climate datasets. In some embodiments, carbon sequestration is modelled using the PREEQC geochemical platform using published experimentally derived kinetic and thermodynamic data. In this embodiment, the model simulates the change in mineral solubility over time as weathering progresses and reactive minerals dissolve. From the chemical weathering reactions, the model shows the evolution of pH in the soil pore waters as well as the element release rates. By predicting the products of weathering, a calculation can be made (that can later be verified by gathering this data) of the carbon dioxide sequestered by balancing the chemical equations with bicarbonate. This allows the generation of a weathering curve that provides an estimate of the cumulative amount of carbon dioxide sequestered per hectare over time. Referring now to Figure 7, there is shown and will be described an enhanced weathering model 700 according to an embodiment. The enhanced weathering model 700 receives some input data, specifically input weathering location data 710 and input basalt application data 712. The input weathering location data 710 includes location data for the one or more areas of land being considered for enhanced weathering processes to be applied, as well as properties of each one or more areas of land including average expected rainfall (or expected rainfall over time), pH data, average expected temperature (or expected temperature over time). In some embodiments, input data can include any or any combination of: quarry information; rock information; haulage information; land management information; spreading data; soil data; soil sample data; soil sample results data; soil type; soil pH; soil carbon content data; rainfall chemistry data; hydrology data; temperature data; precipitation data; ground cover data; irrigation data; rock geochemistry data; soil chemistry data and soil properties data. The Input basalt application data 712 includes property data for the bulk material to be applied during the enhanced weathering process, including particle size distribution for the bulk material, surface area distribution for the bulk material, and geochemical composition data for the bulk material. This input data is provided to both a weathering model 715 and an enhanced weathering optimisation model 725. The weathering model 715 uses the input data to generate an output carbon sequestration estimate 720 which estimates the amount of carbon sequestered by the land for a default spread of weathering materials. The output carbon sequestration estimate 720 is provided to the enhanced weathering optimisation model 725 along with the input data. The enhanced weathering optimisation model 725 models a range of possible variations to the input basalt application data 712 as refined basalt application data 722 and, working with the weathering model 715 by inputting the refined basalt application data 722 into the weathering model 715, uses the weathering model 715 to produce a plurality of output sequestration estimates 720 across a range of basalt application options, thus producing a range of output carbon sequestration estimates across this range of basalt application options. Based on the output sequestration estimates 720, the enhanced weathering optimisation model 725 can select the optimal basalt application option from the refined basalt application data 722 and output an enhanced weathering plan 730 along with an output fertilisation estimate 732. The output enhanced weathering plan 730 is the selected plan based on the refined basalt application data 722 and the corresponding output carbon sequestration estimate 720. For example, the selected plan 730 can be the plan that captures the maximum estimated amount of carbon 720, or the plan that causes the soil pH to reach a certain range of pH values and maintain this overtime, or both. The output fertilisation estimate 732 is a prediction over time of at least the predicted pH over time for the location to undergo enhanced weathering based on the output plan 730. The plan 730 is then executed by spreading the enhanced weathering materials 735, either once or multiple times at predetermined intervals according to the output plan 730. In some embodiments, the plan 730 comprises one or more dose maps, to plan for the specific amounts, spread and composition of the bulk material to be spread on each portion of the area to be subjected to enhanced weathering processes. In some embodiments, the enhanced weathering model 700 allows the provision of a iterated weathering plan for each specific location which allows the generation of actionable outputs from the model, such as a substantially optimised enhanced weathering application plan and a corresponding carbon sequestration estimate for that plan (which can be verified by subsequent data gathering) and which can be used for various other activities such as generation and / or verification of carbon credits as well as fertilisation of land. The output carbon sequestration estimate(s) 720, the output fertilisation estimate 732 and the plan 730 are provided to the verification process 740 which will be described in relation to Figure 8 below. In embodiments, the enhanced weathering model 700 takes as its input some input data, which in this embodiment includes location specific data 710. In some embodiments, the location specific data includes data from mesocosms and in-field measurements. Obtaining data from mesocosms in such embodiments involves sinking multiple boreholes into the specific location to sample the soil and then taking various measurements of the properties of the soil samples. The mesocosms are built and deployed to reflect real-world conditions and thus to provide more realistic input data. In-field measurements in this embodiment include taking, for the specific location, one or more pH measurements of the soil, rainfall measurements overtime, and temperature measurements overtime. In other embodiments a wide variety of in-field measurements, including those mentioned herein, can be used in various combinations to generate input data for the model. In some embodiments, the enhanced weathering model 700 also has access to previous data from other mesocosms and in-field measurements and the resulting output data such as weathering plans, estimates of carbon sequestration and changes in pH over time. Rather than having data from only one location, the model can be tuned to allowed for starting parameters to be used for the specific location of interest and to apply a weathering model that is customised to the specific location. In some embodiments, a one-dimensional geochemical reactive transport soil process basalt weathering model is used to estimate CO2 removal and mineral weathering over multidecade timescales. In the one-dimensional model, the downward migration of rainwater or irrigation water is assumed, through a 30cm soil profile with basalt mixed into the top 5cm. The model inputs are information on the basalt minerology, particle size and surface area, and density of application. These are coupled with local site-specific soil chemical and physical parameters and high-resolution, long-term climate (precipitation, air temperature) data. Carbon sequestration is modelled using known kinetic and thermodynamic data. The model simulates the change in the mineral solubility overtime as weathering progresses and reactive minerals dissolve. From the chemical weathering reactions, the model shows the evolution of pH in the soil pore waters, as well as element release rates (e.g. HCOs', CA2+, Mg2+). By tracing the products of weathering (Ca, Mg, bicarbonate (or alkalinity)), the model can be used to calculate how much CO2 is sequestered by balancing the chemical equations with bicarbonate (HCOs'). From these data, the model generates a “weathering curve” that provides an estimation of the cumulative tonnes of CO2 sequestered per hectare over time. In some embodiments, the model uses Monte Carlo techniques (such as Monte Carlo based sensitivity analysis) to tune each of one or more parameters of the model to generate large numbers of varying modelled scenarios, following a validated input script - for example to generate a variety of values for the refined basalt application data 722 (but in other embodiments, a variety of data can be generated for other input data in order to generate a larger range of output carbon sequestration estimates 729). This allows the model to consider a range of possible scenarios generated using the Monte Carlo techniques, which has the effect of simulating a range of possible inputs and provides a method of generating error bars for each variable (pulling from a distribution of values for each variable). This allows a user to visualise how all of the uncertainties for the specific location flow through the model and generates statistics over time as time series data that can then be compared to future measurements and allows future tuning of parameters based on the actual future data compared to the originally predicted data with error bars. The use of Monte Carlo approaches, like the one described, can allow accounting for the effect on CO2 sequestration arising from the variability of model input parameters such as basalt mineralogy and surface area, soil chemical and physical parameters and climate variables. The Monte Carlo process includes assigning a probability density function, built from a mean value and a standard deviation, for each of the model input parameters. The model of at least some embodiments is then run a plurality of times (for example thousands of times) with the input parameters for each run time being pulled randomly from the respective probability density functions. In this embodiment, the primary objective of the Monte Carlo analysis is to account for variations in carbon dioxide sequestration stemming from fluctuations in model input parameters, which include (but are not limited to) crushed CA- and Mg- silicate rock mineralogy and surface area, soil chemical and physical parameters, and various climate variables. By assigning a probability density function to each model input parameter, each probability density function being constructed using a mean value and standard deviation, the weathering model can be run / executed multiple times where each execution uses input parameters selected at random from the probability density function. By plotting the data generated from each execution on a two-dimensional histogram, such as shown in Figure 12, the plot 1200 illustrates the cumulative amount of carbon dioxide sequestered 1220 as a probability heatmap 1230, 1240 over time 1210. Following generation of the plotted data, subsequent analysis can establish a standard deviation profile by scanning the two-dimensional histogram 1230, 1240 on a monthly basis to create a one dimensional histogram for each month 1330 (allowing the mean and standard deviation for each month to be determined) as shown in Figure 13, where an example per-month data plot is shown 1300 where a count 1310 is plotted against carbon sequestration 1320 to show the data for that month 1330 as well as a plot of the mean data 1340. In some embodiments, to implement the Monte Carlo approach, a controller generates the number of simulations that are required to generate the output data needed and informs a script generator of this number. The script generator causes the number of processes required to model each of the simulations to be spawned and then each of these simulations outputs one set of output data. The combined output data can then be used to generate the range of output values mentioned above. This approach also allow the process to be computed on a cloud computing system as parallel compute operations, per simulation script, allowing the process to be scalable and generate the output data in a tractable computing operation. In embodiments, the computation can be deployed to allow for thousands of jobs to be set up, run and post-processed in an automated, performant and time-efficient way - with this framework, on a single node, hundreds of parallel weathering models can be run and the whole operation can scale up to manage jobs over multiple nodes if needed. The data from each job is then combined and can be used to form a plot displaying the cumulative CO2 sequestered over time for all of the jobs. This can be displayed as a probability heat-map, which allows the mean value and standard deviation for each time bin to be determined. This can be used to account for the variability in the input parameters, for example to take a conservative estimate of CO2 sequestration until verification is performed. In some embodiments, the input parameters are treated as Gaussian in form, centred around the input parameter value with the measurement error as the width of the Gaussian bounds. In some embodiments, the real data gathered in future versus the predictions generated by the model including error bars can then be stored in the model dataset to improve the model simulations of real life weathering conditions in future. One of the benefits for the land users is that the process of enhanced weathering using basalt acts to improve soil conditions by increasing the soil pH, and so in some embodiments the model generates an enhanced weathering plan 730 that substantially optimises both carbon sequestration and soil pH overtime. In embodiments, the model 700 aims to determine an application rate of enhanced weathering materials that maintains a stable pH in the land and dose maps across the surface area of the field or fields can be generated in some embodiments - this is incorporated into the output plan 730. In some embodiments, the in-field measurements made are to gather accurate data on rainfall and temperature data over time as well as the soil pH over time. In some embodiments this is gathered / output as time series data. In some embodiments, gradient descent techniques are used to match in-field measurements against the model predictions, for example during the verification 740 or alternatively for example during re-planning to update the weathering plan 730. In some embodiments, the model calculates / estimates how much carbon dioxide is sequestered by charge balancing the chemical equations with bicarbonate, where CO2 has a residence time in the oceans of 100,000 years. The quantity of carbon dioxide sequestered (as direct carbon dioxide rather than CO2e) is quantified using predicted major ion release based on the dissolution of the minerals present within the basalt, and this modelling can be continually calibrated through the lifecycle of the project by using the measured major ion concentrations (e.g. from field measurements or soil mesocosms). The geochemical calculations are performed by the model using the proportions of minerals in the basalt and using experimentally derived kinetic and thermodynamic data. In some embodiments, data is used that includes dissolution rates for primary rock forming silicate materials, as well as wollastonite. In other embodiments, a thermodynamic and kinetic databased is used that compiles mineral dissolution rates under far-from-equilibrium conditions as a function of pH and temperature for primary rock forming silicate minerals and glasses and secondary silicate minerals such as clays and zeolites (allowing the modelling of 36 primary minerals using kinetic dissolution rates, as well as the thermodynamic constants for 375 solid phases (e.g. silicate, oxides, hydroxides), 15 gases (including CO2, O2 N2, ammonia, N2O etc), 31 independent basis aqueous species (HCO3-, CA2+, Mg+, K+, Na+ etc), 156 dependent aqueous species (CaHCO3+), 40 redox couples (including Fe2+ / Fe3+, oxidised and reduced forms of N, nitrate and ammonia) and 3 types of soil organic matter (including monoprotic carboxylic, monoprotic phenolic and diprotic carboxylic-phenolics). As data is collected, the new data can be incorporated into the existing data to train / re-train the model or improve the output of the existing model by using the improved data. In some embodiments, the model simulates soils in one dimension with a fixed amount of saturation. In other embodiments, a model simulates in two dimensions with variable saturation using variable saturated two dimensional reactive transport modelling in the vadose zone, allowing modelling of the hydraulics of the soil under representative environmental conditions such as periods of intermittent rainfall and irrigated systems. In embodiments, in order to calibrate the model, the input parameters and constants of the weathering model are adjusted to better represent real world data. To achieve this, nongradient based (derivative-free) optimisation techniques are used to refine the models input parameters. Optimisation of the model aims to simulate real-world behaviour in order to predict the dissolution of Ca- and Mg- rich silicate materials and predict carbon dioxide removal across diverse soil, cropping systems and climate conditions. Referring now to Figure 8, according to an embodiment there is shown the verification process 800 which will now be described in more detail. As previously described above in relation to Figure 7, a plan is created 805 for the enhanced weathering application to the land to be weathered. The plan is output 810 and used to apply the rocks by spreading 815 the bulk material on the land to be weathered. Following application 815 of the bulk material to the land to be weathered, in-field measurements can be taken including soil mesocosms 820 and sensor measurements 825. The data gathered 830 from these measurements 820, 825 is then used to determine either a measurement or an estimate of the carbon captured 835 using the weathering model discussed in Figure 7 above. A comparison 840 is made between the original estimate of carbon capture 850 for the outputted plan 810 and the measurement / estimate 835 based on the data 830 as well as between the measured data 830 and the previously estimated time series data 845. If the comparison 840 determines that there is a significant variance (above a predetermined threshold, for example 5% or 10%) between either the carbon capture estimate 850 and measurement 835 or the measured data 830 and the estimated data 845, then the plan can be regenerated 805 and the process 800 repeated. Referring now to Figure 9, according to an embodiment there is shown an example of the use of in-field sensors 900 which will now be described in more detail. Using the same example farm as in Figure 5, where there is an area of farmland 930 that has been subject to enhanced weathering using crushed rock 920 spread over the farmland 930 and where there is also non-weathered land 940 that has not been subject to enhanced weathering, in-field sensors 910 are deployed at various points on the farmland 930 (optionally in other embodiments, in-field sensors 910 are also deployed on the non-weathered land 940). The sensors 910 collect time series data including temperature data, precipitation data and pH data, depending on embodiment. In some embodiments not all of these data points are collected. In other embodiments, there are specific sensors that collect each of these individual data only. In embodiments, high-resolution in-field measurements are performed in selected regions of interest that are representative of the area undergoing enhanced weathering (or site of interest for enhanced weathering in other embodiments). In some embodiments, in-field monitoring consists of a weather station being used to collect local climate variables such as air temperature and precipitation, in combination with automated soil stations consisting of in situ depth- and time- integrated sensors to measure soil temperature, pH, moisture and electrical conductivity (EC). In some embodiments, in addition physical soil and porewater samples will be taken periodically, and these samples will be analysed for pH, electrical conductivity, alkalinity as well as major ions - this will allow calculation of CO2 sequestration using the models described. In some embodiments the infield sensors only measure pH and electrical conductivity, as these can be measured continuously. In some embodiments there are three soil monitoring profiles at 5, 10 and 30cm depth which will acquire hourly data. In some embodiments, for a project area (an area on which enhanced weathering is to be performed, the project area has one or more small plot monitoring sites selected and one or more split field monitoring sites selected. Small plot monitoring sites are tested for mass balance and pore water sampling while split field monitoring sites are tested for mass balance and soil testing. Split field monitoring sites are designed the measure the quantification of carbon sequestration through a mass balance approach in addition to monitoring soil acidity and electrical conductivity following applications of Ca- and Mg- rich silicate rock. Further, by taking samples in neighbouring parallel sampling lines, the side-by-side nature of the sampling also allows the gathering of data that can provide empirical results on changes in the crop configuration. The side-by-side sampling lines allow one line of sampling to be a control and one line of sampling to be on weathered soil. Typically, each sample line allows five samples to be taken, so a total of ten samples per split field monitoring site. Small plot monitoring sites are designed to measure mass balance and pore water in combination across an increasing weathering material application density, increasing the probability of seeing a weathering signal as this density increases. This allows data to be gathered on the agronomic benefits as well as the weathering signal. Typically a site is made up of six replicate strips of four application densities (control, operational application rate, 2x operational application rate, 10x operational application rate). Baseline soil sampling is completed prior to any application of bulk material, and annual measurements are taken thereafter, of mass balance, pH, electrical conductivity, base cations, cation exchange capacity, soil organic and inorganic carbon, soil texture and concentrations of potentially toxic elements - at sampling depths of either 7cm in grassland or 15cm in arable land. Pore water extraction is performed using macro rhizon samplers installed shortly after the time that bulk material is applied, to sample pore water at regular intervals. The rhizon samplers are installed in 5 and 10cm depths to ensure that extracted pore water has been in direct contact with the bulk material / basalt amended horizon. Pore water is analysed for pH, electrical conductivity, cations, anions, and total alkalinity. Crop observations are also made at regular intervals, depending on the crop planted, to determined critical stages in development and to determine emergence, stand establishment, early season vigour, stand counts, relative greenness and biomass. Plant grain samples will be collected and assessed for plant health and nutrient content. Referring now to Figure 10, according to an embodiment there is shown a method of performing enhanced weathering which will now be described in more detail. The first step in the process is to input the location data 1010. This involves providing the size of the field (or area of land to be weathered) and the location thereof (e.g. by providing the co-ordinates of the corner points, or the shape, of the area of land). The second step is to input the field measurements 1020, in other words to provided data on pH, air temperature, precipitation and electrical conductivity. In some embodiments, this data might be one-time data obtained from the field by taking measurements or samples. In other embodiments, time series data may be obtained over a period of time or from third party data sources (for the specific land or for broadly comparable or nearby locations) such as geochemical databases, land databases, or meteorological databases. The third step is to estimate the time series data 1030 for the field, i.e. to predict the relevant time series data required in order to generate a carbon capture estimate. In this embodiment this includes generating a time series estimate into the future for air temperature and precipitation. The time series data generates varies the possible inputs in order to generate a range of output data for each of these sets of time series data, in order to generate a range of values over time for, for example, air temperature and precipitation. The fourth step is to determine the range of carbon capture estimates for the location 1040. Using the generated time series data from the third step 1030, the model generates using the ranges of values for the time series data, a range of possible carbon capture estimates over time - i.e. over time, generating a maximum and minimum predicted carbon capture value and plurality of values in between. The fifth step is to optimise the enhanced weathering parameters 1050, which is done using the carbon capture range of values over time and the other time series data, in order to cause the pH of the field to reach a predetermined optimum range of values and then stay within that range, while maximising the carbon captured. The parameters optimised include, in this embodiment, the amount and density of bulk material spread on the field and the areas on which the bulk material is spread in each spreading event, the number of spreading events and the time in between these, and the particle size distribution and mix of rock types. The sixth and last step is to perform enhanced weathering using the optimised parameters 1060. Referring now to Figures 11a and 11b, according to an embodiment there is shown the maximum and minimum carbon capture estimates over time, both prior to performing verification and post verification where the estimates are adjusted accordingly which will now be described in more detail. In Figure 11a, there is a shown a illustrative graph of carbon captured 1120a versus time 1110a. On this, the estimates of carbon captured are plotted, showing the possible maximum carbon captured estimate 1130a and the minimum carbon captured 1140a that is output by the method according to an embodiment prior to application of the enhanced weathering process to the land being considered for enhanced weathering. In Figure 11b, there is a shown a illustrative graph of carbon captured 1120b versus time 1110b. This diagram shows the situation of Figure 11a where enhanced weathering has been applied to the land and verification has been performed to determine the amount of carbon captured and this data has been plotted 1106. This has resulted in the estimates for maximum and minimum carbon captured to be re-estimated and plotted as a top error bar 113b (revised estimated maximum carbon captured) and a bottom error bar 1140b (minimum revised estimated carbon captured). In at least some embodiments, two separate measurement approaches to quantify carbon removal can be used, either individually or in combination. The first measurement approach is to use a weathering proxy that allows for estimation of how much rock has weathered via ICP-MS (inductively coupled plasma mass spectrometry) measurements to estimate a maximum theoretical carbon dioxide removal (by cation loss due to weathering). This approach uses mobile cation to immobile trace element ratios, measured in soils before and after weathering (and in some embodiments used as input to the respective models / model components) to trace concentration changes of elements that are present in the feedstock material, relative to the concentrations that persist in the soil after weathering. The second measurement approach is to measure the direct products of weathering in pore waters from field trials and mesocosms (e.g. major cation, anion and alkalinity), which allows for estimate of carbon dioxide sequestration by charge balance. In embodiments using both approaches, the pore water analysis helps negate some of the limitations of ICP-MS, specifically the inability of the first approach to distinguish non-carbonic acid based weathering. In some embodiments, these measurements are made in parallel on intensively monitored sites to generate a detailed data set which accounts for the variability in climate, soil conditions and crop type across our project area, allowing us to generate significantly stronger evidence of carbon dioxide removal. In embodiments, a variety of measurement techniques can be used. For example, traditional soil sampling can be used, or advanced sensors designed to measure weathering proxy parameters across a wide range of soil types, crop types and weather conditions. In some embodiments, experimental data is generated from humidity call dissolution experiments on mineralogically complex feedstock materials, which provides data on dissolution rates that can be used in the modelling process. In some embodiments, experimental data is generated using any or any combination of soil mesocosm experiments (in highly controlled laboratory experiments and / or in the field), small plot field experiments and larger split field experiments - the experimental data generated from collecting and analysing soil and pore water samples and determining agronomic impact (e.g. alkalinity, pH, electrical conductivity, major cations and anions, soil exchangeable cation concentrations and potential toxic metal concentrations) can be compared to the output of the model simulating the expected results of weathering in order to verify the model output and / or adjust any error bars in the output of the model under a range of climate, crop type and soil conditions. Any system feature as described herein may also be provided as a method feature, and vice versa. As used herein, means plus function features may be expressed alternatively in terms of their corresponding structure. Any feature in one aspect may be applied to other aspects, in any appropriate combination. In particular, method aspects may be applied to system aspects, and vice versa. Furthermore, any, some and / or all features in one aspect can be applied to any, some and / or all features in any other aspect, in any appropriate combination. It should also be appreciated that particular combinations of the various features described and defined in any aspects can be implemented and / or supplied and / or used independently.

Claims

1. A computer-implemented method comprising:receiving input data, the input data comprising location data of at least one location and enhanced weathering material data of at least one enhanced weathering materials;generating a plan to apply the at least one enhanced weathering materials to the at least one location;generating an estimate of carbon capture over time at the at least one location using the input data when applying the at least one enhanced weathering materials to the at least one location based on the generated plan;generating an estimate of pH over time at the at least one location using the input data when applying the at least one enhanced weathering materials to the at least one location based on the generated plan;outputting the estimate of carbon capture over time at the at least one location, the estimate of pH over time at the at least one location, and the plan.

2. The method of any preceding claim, wherein generating the plan comprises generating an initial plan and then iterating generation of revised plans using the generated estimate of carbon capture over time and the generated estimate of pH over time for the initial plan.

3. The method of claim 2, further comprising optimising the iterating generation of revised plans in order to substantially maximise the estimate of carbon capture and / or stabilise the estimate of pH over time4. The method of any preceding claim, wherein the input data comprises any or any combination of: air temperature data; air temperature data overtime; pH data; pH data over time; precipitation data; precipitation data over time; electrical conductivity data; electrical conductivity data over time; in-field measurement data; sensor data; meteorological data; live data; soil mesocosm data; time series data.

5. The method of any preceding claim, wherein the location data comprises any or any combination of: grid co-ordinates of each location; satellite data of each location; topographic data of each location; boundary data of each location; dimension data of each location.

6. The method of any preceding claim, wherein the enhanced weathering material data comprises any or any combination of: geochemical composition; pH; particle size distribution; density; average particle surface area; size categories of bulk material; source information.

7. The method of any preceding claim, further comprising a three-stage model wherein the three-stage model comprises an initial soil solids model, a soil solution model and an evolved soil solids model; wherein generating the estimate of carbon capture over time and / or generating the estimate of pH over time comprises using the three-stage model; optionally wherein the soil solution model interacts with any or any combination of: a basalt application model; an atmosphere model; a plant model; a water model.

8. The method of any preceding claim, wherein the plan comprises any or any combination of: determining which at least one location to which enhanced weathering processes will be applied; determining one or more portions of the at least one location to which enhanced weathering processes will be applied; determining one or more time periods during which enhanced weathering processes will be applied to each of the at least one locations; one or more selections of enhanced weathering materials to be applied to each at least one location.

9. The method of any preceding claim, wherein generating the plan comprises assessing whether to apply enhanced weathering processes to each of the at least one locations based on one or more pre-determined thresholds; optionally wherein the one or more pre-determined thresholds comprise any or any combination of: an amount of carbon predicted to be sequestered; a predicted pH over time; a minimum pH; a maximum pH.

10. The method of any preceding claim further comprising performing enhanced weathering using the generated plan, optionally wherein performing enhanced weathering comprises periodically applying enhanced weathering materials to each at least one location a plurality of times.

11. The method of claim 10, further comprising performing verification of the generated estimate of carbon capture over time following performing enhanced weathering using the generated plan; optionally wherein verification is performed by taking measurements of geochemical parameters at each at least one location.

12. The method of claim 11, further comprising generating a revised plan to apply the at least one enhanced weathering materials to the at least one location following performing verification of the generated estimate of carbon capture over time; and performing the revised plan.

13. The method of any preceding claim wherein generating either or both of (i) an estimate of carbon capture over time; and (ii) an estimate of pH over time; is performed using one or more simulations; optionally wherein the one or more simulations comprise Monte Carlo simulations.

14. The method of any preceding claim wherein the generated plan seeks to optimise at each at least one location a stabilised pH over time within a predetermined range of pH values.27

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