Systems and methods for carbon monitoring and management in water systems

Abstract

A system and method for carbon monitoring in a water system may include: sealing water in a container of the first monitoring system, the container having a fill level of the water leaving a defined gas fraction; collecting sensor data from the water and the defined gas fraction, the data including measuring a carbon concentration of the gas fraction and measuring water conditions including at least water temperature, water conductivity, and water pH; and, after the water reaches equilibrium in the container, determining a dissolved inorganic carbon concentration condition based on the carbon concentration, temperature, water conductivity, and water pH. The system and method may further include adding a supplement to the water system and adjusting the addition of the supplement based on a change in the determined dissolved inorganic carbon concentration condition.

Description

[Technical Field]

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application claims the benefit of U.S. Provisional Application No. 63 / 434,760, filed December 22, 2022, which is incorporated by reference in its entirety.

[0002] [Technical field] The present invention relates generally to the field of carbon monitoring, management, and storage, and more particularly to a novel and useful system and method for integrating carbon management, storage, and monitoring in aqueous solutions. [Background technology]

[0003] With climate change becoming a growing concern every day, controlling carbon emissions has become an important topic for research and development. While most technologies address the reduction of atmospheric carbon, a significant amount of carbon emissions comes from water, which remains relatively ignored. One problem is the lack of a method to accurately quantify and verify carbon reduction processes in water systems. Therefore, there is a need in the field of carbon management to create new and useful systems and methods for carbon monitoring in water systems. The present invention provides such new and useful systems and methods. [Brief explanation of the drawings]

[0004] [Figure 1A] and [Figure 1B] 1A and 1B are schematic diagrams of top and side views of one system variation.

[0005] [Figure 2A] and [Figure 2B] Schematic diagram of another system variation having a removable lid or cover for adding water.

[0006] [Figure 3] 1 is a schematic diagram of an exemplary automated system.

[0007] [Figure 4] Schematic diagram of a second exemplary automated system.

[0008] [Figure 5] 1 is a schematic diagram of an example of an automated system having a carbon handling system.

[0009] [Figure 6] Schematic of a variation using CO2 supplements.

[0010] [Figure 7] 1 is a schematic diagram of a system having multiple monitor systems.

[0011] [Figure 8] Schematic diagram of a variation using a supplemental alkaline source.

[0012] [Figure 9] Schematic of one carbon manipulation system.

[0013] [Figure 10] FIG. 10 is a detailed schematic diagram of the operating components of a variation of the carbon handling system.

[0014] [Figure 11] 1 is a flowchart representation of an exemplary method.

[0015] [Figure 12] 1 is a flowchart representation of a method variation.

[0016] [Figure 13] 1 is a flow chart illustrating a variation of a method used to improve water quality.

[0017] [Figure 14] 1 is a flow chart showing a variation of the method change using convergence analysis of different methods for determining dissolved inorganic carbon compounds.

[0018] [Figure 15] Schematic representation of the method applied within a multi-monitor system implementation.

[0019] [Figure 16] Detailed flow diagram of sensing data and determination of dissolved inorganic carbon concentration status.

[0020] [Figure 17] Chart showing application of convergence analysis of multiple methods for modeling dissolved inorganic carbon compounds.

[0021] [Figure 18] 10A-10C are exemplary sensor data and dissolved inorganic carbon concentration status data resulting from water condition improvements.

[0022] [Figure 19] An exemplary system architecture that may be used in implementing the present system and / or method. DETAILED DESCRIPTION OF THE INVENTION

[0023] The following description of embodiments of the invention is not intended to limit the invention to those embodiments, but rather to enable any person skilled in the art to make and use the invention.

[0024] [1. Overview] A system and method for carbon monitoring in water systems utilizes a monitoring system that uses a closed-water sample equilibrium monitoring approach to measure and model carbon-based compound concentrations in aqueous / water systems. The system and method may use a detection vessel containing a spectroscopic sensor capable of measuring gaseous carbon compounds and a sensor capable of measuring water system properties, and includes partially filling the detection vessel with water, equilibrating unfilled and filled regions of the detection vessel, measuring the carbon concentration in the unfilled region using the spectroscopic sensor, measuring the water properties, such as temperature, pH (and other pH properties such as acidity and alkalinity), conductivity, and salinity of the water, and determining the dissolved inorganic carbon (DIC) concentration using the carbon concentration in the unfilled region and water chemistry to determine the carbon concentration in the filled region based on the carbon equilibrium relationship between air and water. The system and method may be used to output or use DIC concentration status information, alternatively characterized as water carbon concentration. DIC state information can include concentration measurements or other quantifications of one or more different DIC compounds (or DIC species), such as CO, bicarbonate (HCO), and carbonate (CO) compounds / ions in the liquid / water, as well as related carbon chemistry parameters, such as carbonate saturation state.

[0025] In some variations, the systems and methods may be used in combination with carbon manipulation systems that may be used to augment or improve water systems to initiate removal of CO2 through conversion to stable forms within the water system.

[0026] In one particular variation, the system and method may be used to enable a measured-controlled alkalinity addition system ("CDR system") for carbon dioxide (CO) removal and storage in water, converting excess biogenic dissolved CO in atmospherically bound, high-CO waters (e.g., estuaries) to stable dissolved bicarbonate (HCO) and carbonate (CO) ions in the same water. In this way, the system and method can reduce excess CO in water, providing important ecosystem co-benefits by reducing harmful local acidification. This excess CO (e.g., >425 ppm) is detected using a monitoring system, and the carbon manipulation system / CDR system may then add an amount of alkaline solution until CO reduction reaches ambient concentrations (~425 ppm) with associated pH and saturation endpoint controls.

[0027] The system and method may generally be implemented as part of any closed or open water source for water monitoring and management. In closed systems, the system and method may be used to monitor and maintain water quality (e.g., reservoirs). In open systems, the system and method may enable fluid management in conjunction with other activities occurring in the body of water. For example, the system and method may be implemented in areas where waste is released, in areas with variable population use of water (e.g., tourist destinations), near mining operations, and in other industrial operations and waste disposal.

[0028] In one example, the system and method may be used in connection with a waterway, such as a river or stream, to monitor and actively regulate water conditions within the waterway.

[0029] In another example, the system and method may be used in industrial water systems, such as mining operations. In this variation, the system and method may be used to treat water used in mining operations, and in some variations, to store carbon.

[0030] The present system and method can provide several potential benefits. The present system and method are not limited to always providing such benefits and are presented only as an exemplary representation of how the system and method may be used. This list of benefits is not intended to be exhaustive, and other benefits may additionally or alternatively exist.

[0031] One potential benefit is that the systems and methods can provide measurement-based validation for carbon capture in water systems. How alkalinity behaves in ecosystems can vary significantly from theory and laboratory experiments. There may be a variety of carbon removal and / or storage approaches in water, including adding alkalinity to increase CO absorption by the water or convert dissolved CO to HCO and CO. The systems and methods described herein can provide a way to measure the efficacy of carbon dioxide removal attempts and / or manage the operation of such carbon removal and storage processes.

[0032] Another potential benefit is that this system and method can be implemented as a relatively low-cost, robust method for monitoring DIC concentrations. Once CO2 enters water, DIC speciation occurs in the water, which can be difficult to quantify and measure. Conventional approaches rely on time-consuming and expensive laboratory analysis and / or expensive sensing systems that utilize expensive components such as gas-permeable membranes and internal calibration gases. Such approaches are prohibitively expensive. This allows for a practical, distributed, and practically usable monitoring system.

[0033] Another potential benefit is that the system and method can operate substantially autonomously, which can help keep operating costs low and make it a practical solution.

[0034] The system and method may provide the benefit of more accurate carbon information. By using spectroscopic sensors, the system and method may be able to provide measurements of carbon dioxide, carbonate, and bicarbonate.

[0035] Additionally, the system and method can provide the benefit of real-time continuous carbon measurement. By implementing an automated version of this system, continuous measurements of carbon concentration can be collected and used directly.

[0036] As another potential benefit, the systems and methods may provide a solution for proactively managing carbon capture by proactively improving the alkalinity and / or other properties of the water system. In some variations, carbon may be stored in the water and / or carbon present in the water may be modified for enhanced storage. Such modifications may be controlled using the active monitoring of the systems and methods.

[0037] Additionally, the systems and methods may further enable monitoring and management of carbon stocks, which, in conjunction with water quality monitoring and management, would offer the potential benefit of enabling improved water quality (e.g., by reducing water acidity).

[0038] [2. System] As shown in Figures 1A and 1B, 2A, 2B, 3, and 4, a system for carbon monitoring of a fluid includes a measurement reservoir 110 that, once partially filled with liquid, allows liquid to flow into and out of the measurement reservoir in an open state and prevents gas from flowing into or out of the measurement reservoir in a closed or operating state, and an integrated sensor system 120 for detecting the status of the aqueous / water-soluble portion and the gaseous portion. The sensor system preferably includes a pressure sensor 121 and a spectroscopic sensor 122 for monitoring the gaseous portion, a temperature sensor 123 for monitoring the aqueous portion, a conductivity sensor 124, and a pH sensor 125. Such a system may be implemented within a single monitoring system. In some alternative variations, multiple instances of such a monitoring system may be used in combination so that DIC concentration status data can be collected at multiple points and / or across multiple regions.

[0039] When implemented as a single monitor instance 100, the system functions as a monitor device that detects and measures the carbon content of a liquid once it is partially filled with liquid and closed. That is, the system utilizes general properties of the liquid (e.g., salinity, pH, and temperature) in conjunction with gaseous carbon concentration measurements in the unfilled region (i.e., gas portion) of the measurement reservoir to determine the liquid carbon concentration. Accordingly, in many variations, sensor system 120 may further include other sensor components capable of further measuring gas and / or liquid properties within the measurement reservoir.

[0040] This system may be particularly useful for measuring or monitoring carbon compound concentrations in water. This system allows for the measurement and monitoring of carbon dioxide in water, as this is the primary source of carbon in water. Similarly, this system may be implemented to measure carbonate (CO3) and bicarbonate (HCO3) concentrations (or their conjugate acid, carbonic acid (H2CO3)). In general, this system may be implemented to measure fluctuations in these compounds (or other carbon compounds) in any fluid, potentially determining the specific concentration of each of these carbon compounds in the fluid.

[0041] In some variations, the monitoring system may operate fully or partially autonomously, where the monitoring system can be set up for monitoring in a particular area and then continuously or periodically monitor the DIC concentration at that site.

[0042] In some alternative variations, the monitoring system may determine the DIC concentration status of the water in response to a measurement request (e.g., measuring the dissolved carbon content of CO, CO, and / or HCO). For example, a user interface may trigger a measurement request, and the system may collect measurements and output the determined DIC concentration status data.

[0043] In some variations, such as automated variations, the system may further include a communication system 130 that allows system communication with external systems and users and includes the ability to transmit collected data to external sources, and a control system 140 that monitors system components and alters system operating parameters as desired depending on implementation and operational use.

[0044] In some examples, variations of the automated system may also be part of a larger control feedback system. For example, the automated system may operate in conjunction with a carbon manipulation system 150 (which may or may not be part of the system). Thus, in some variations, the system may include or interface with the carbon manipulation system 150. The carbon manipulation system 150 may function to increase or decrease the carbon concentration in a fluid by modifying the water. In some variations to increase the carbon concentration, such as in the example mining use case, CO2 may be added to the water. Relatedly, the automated system may monitor changes in the carbon concentration of the fluid. For some predetermined desired carbon concentration ranges, the automated system may provide control feedback to the carbon manipulation system 150, which in turn may utilize collected carbon concentration data to instruct the carbon manipulation system 150 to increase or decrease the fluid carbon concentration. In many implementations, the automated system may also provide control feedback to the carbon manipulation system 150 to improve the rate of carbon increase or decrease.

[0045] This control feedback system may be an open or closed system. As part of a closed system, the carbon manipulation system 150 may be located on or within the measurement reservoir 110. The measurement reservoir 110 may be filled with a desired volume of fluid (e.g., water). The carbon therein may then be altered based on measurements of the fluid in the reservoir until a desired carbon content is reached. Once the desired concentration is reached, the fluid may be released and altered to allow new fluid to enter, or may be stored in the reservoir.

[0046] Variations on closed systems may use a specially designed measurement vessel 110 (e.g., with a desired fluid volume) or may be incorporated as part of a pre-existing fluid storage system. For example, water silos and other closed water reservoirs (e.g., in water treatment plants) may be converted to closed control feedback systems.

[0047] As shown in FIG. 5, in an automated example of a closed system, carbon manipulation system 150 alters the carbon concentration in measurement reservoir 110 in direct response to sensor measurements of the fluid in the reservoir. In one implementation of this example, carbon manipulation system 150 may contain stored carbon (e.g., carbon dioxide). Carbon manipulation system 150 may release stored carbon dioxide in response to a high pH, ​​high alkalinity measurement in the fluid. Alternatively, carbon manipulation system 150 may introduce CO2-removing minerals or materials (e.g., alkaline hydroxides such as magnesium hydroxide (Mg(OH)2), carbonates such as limestone (CaCO3), alkaline silicates such as wollastonite (CaSiO3), and sorbents such as zeolites) in response to a high CO2, low pH measurement in the fluid. Because the general trend for a particular region is typically constant, carbon manipulation system 150 may typically store either carbon-reducing / pH-increasing compounds or carbon-depositing / pH-decreasing compounds. However, this is merely a desired specific limitation to limit cost and space. In general, the carbon manipulation system 150 can actively store both carbon-enhancing and carbon-decreasing compounds, which may be implemented for use cases with greater fluctuations in water conditions.

[0048] In one implementation of a control feedback example, a carbon manipulation system 150 may be set up along a river (or other body of moving water) to reduce carbon dioxide concentrations in the river, as shown in FIG. 7. An automated monitoring system may be set up downstream (e.g., 100 meters) of the carbon manipulation system 150. In general, the automated monitoring system can be set up anywhere downstream, where its exact location can depend on the desired implementation. For example, in one implementation, the automated monitoring system may be set up adjacent to the carbon manipulation system 150, while in another implementation, the automated monitoring system may be located several miles downstream (e.g., along a narrow waterway) from the carbon manipulation system 150. As the carbon dioxide in the water decreases, the automated monitoring system may provide control feedback to the carbon manipulation system 150 to prevent the carbon dioxide levels in the water from reaching levels that would harm local aquatic plants. This automated monitoring system may also provide feedback in response to concentrations of other forms of carbon (e.g., HCO, CO, etc.). In these variations, the automated monitoring system may release CO into the system, thereby improving the alkalinity or acidity of the water.

[0049] In another implementation of the control feedback example, the system may include at least two automated monitoring systems. In a flow implementation similar to that described above, one automated monitoring system may be located upstream of the carbon manipulation system 150 and another automated monitoring system may be located downstream of the carbon manipulation system 150. In this implementation, the upstream unit may function as a control unit or as a first measurement unit. Measurements from this upstream unit may be used (e.g., by a control system) to determine the amount of carbon to be reduced using the carbon manipulation system 150. The downstream monitoring unit may then function as a final, or second, measurement unit. This second measurement unit can then evaluate the effectiveness of the carbon manipulation and provide (e.g., via the control system) more nuanced improvements to the carbon concentration due to the carbon manipulation system 150.

[0050] In a third implementation of the control feedback example, the system may comprise a network of carbon monitoring systems. In this example, each carbon monitoring system may be automated. Alternatively, any number of systems in the network may be implemented manually. This implementation may be particularly useful in areas where water flow is inconsistent or unknown. In the network example, the network of carbon monitoring systems may be located anywhere along an interconnected waterway (e.g., a bay, lake, channel, etc.) with the carbon manipulation system 150. As the carbon manipulation system 150 alters DIC concentrations, measurements at each carbon monitoring system (or node) may be used to monitor and alter the operation of the carbon manipulation system 150. Depending on the operating conditions (e.g., flow, temperature, aquatic biome, etc.), this can result in many types of different operations. In one example, each monitoring system may control local area carbon concentrations to prevent them from rising above or falling below a certain threshold. In another example, the carbon manipulation system 150 is provided with operational instructions that are the result of a network-wide average. This average may be weighted by node significance as the significance of each node becomes more apparent. In another example, the most proximal node of a carbon manipulation unit may act as a safety control (e.g., preventing extreme carbon conditions), while more distant nodes may provide a measure of operational effectiveness (e.g., providing finer control feedback).

[0051] The measurement reservoir 110 serves as a reservoir for measuring carbon concentration. The measurement reservoir 110 comprises a reservoir that can be filled with water that is functionally divided into two portions: a top portion (also referred to as a gas portion) and a bottom portion (also referred to as a liquid or water portion). As used herein, the terms "top" and "bottom" (or "gas and liquid portions") are generally functional names that indicate the levels to which the measurement reservoir must be partially filled in order to function. That is, the top and bottom do not necessarily indicate different structures between the top and bottom, but rather indicate the approximate levels to which the measurement reservoir must be filled with liquid in order to function.

[0052] The measurement reservoir 110 preferably includes an internally defined cavity that can be partially filled with water during water measurements, and preferably has a geometric profile that results in a continuously connected gas region when filled with water to a target level.

[0053] In some variations, particularly in closed control feedback implementations, the measurement reservoir 110 may comprise a pre-existing fluid storage vessel that has been modified to function as a system component. In general, the measurement reservoir 110 may comprise any fluid-containing vessel. Examples include silos and closed reservoirs.

[0054] The measurement reservoir 110 may be made of (or may be made of) any material that is water and liquid impermeable (e.g., plastic or metal). Depending on the implementation (e.g., the fluid to be tested), the measurement reservoir 110 may also be made of a material that is corrosion resistant to the fluid.

[0055] The measurement reservoir 110 may have at least one opening. Depending on the implementation, the number and type of openings may vary significantly.

[0056] The measurement reservoir 110 preferably includes an integrated sensor system 120 with sensors configured to read appropriate attributes of the environment within the reservoir 110. As shown in FIGS. 1A and 1B, the sensors may be integrated into an upper portion configured to be adjacent to the gas portion when filled (e.g., in the headspace region of the device). The sensors for monitoring the water can extend or otherwise be positioned to contact the water. The sensors for monitoring the gas portion can be oriented to be within the gas portion. As shown in FIGS. 3 and 4, other arrangements and configurations of the different sensors of the sensor system 120 may alternatively be used within the measurement reservoir 110.

[0057] The measurement reservoir 110 may include a cap with an integrated sensor from 120. In one example, as shown in Figures 2A and 2B, the opening may be provided with a removable lid so that the lid can be removed, the measurement reservoir 110 partially filled with water, and then the lid can be reattached for operation. In another variation, the measurement reservoir 110 may include an automatic door that can be opened and closed automatically. The door preferably includes a seal so that, when in a closed state, the contained water can be sealed within the measurement reservoir 110.

[0058] The measurement vessel 110 or the monitoring system more generally may include a controllable air valve that can be opened to allow air flow between the gaseous portion and the ambient atmosphere and closed to stop the air flow. The air valve may be opened to facilitate draining or removing water from the vessel. The air valve may be closed when the vessel is refilled to seal or isolate the gaseous portion when establishing equilibrium.

[0059] In another example, as shown in Figure 3, for automated operation, the measurement reservoir 110 may have an inlet and an outlet to allow liquid to flow through the reservoir. Depending on the implementation, these openings may be permanently open or closable. A pump or other system may be included to control the intake and output of liquid from the reservoir 110. This may be particularly useful for implementations in high flow areas.

[0060] In another automated example, as shown in Figure 4, the measurement reservoir may have a single opening for liquid exchange. Additionally, the measurement reservoir may have an additional "lid-like" opening, which may allow easy access to the internal components of the measurement reservoir for easier cleaning and maintenance.

[0061] In general, the measurement reservoir 110 may have any number of openings in both the liquid and gas portions of the reservoir. Depending on the implementation, these openings may be closable or permanently open. In some variations, during the closed and operating states, doors or openings for water flow into and / or out of the measurement reservoir 110 may be sealed so that there is no gas exchange between the gas portion of the reservoir and the outside of the reservoir. Note that this does not require any openings to actually be closed. For example, as shown in FIG. 3, two openings may be located in the liquid portion of the measurement reservoir 110 such that the liquid itself is sufficient to prevent gas exchange with the outside.

[0062] In some variations, the system may further include a sprayer, mixer, or other perturbation system 112 to perturb the water. Disturbance or mixing of the water can occur at the inlet (e.g., while filling the vessel) or after the water has reached a filled level. This may accelerate the establishment of equilibrium.

[0063] The sensor system 120 functions to collect sensor data for the gas and liquid portions.

[0064] The sensor system may include a pressure sensor 121 and a spectroscopic sensor 122 for monitoring the gas portion, a temperature sensor 123 for monitoring the water portion, a conductivity sensor 124, and a pH sensor 125.

[0065] The sensors of sensor system 120 are preferably positioned to measure properties of appropriate portions of measurement vessel 110 (i.e., gas sensors are positioned in the gas portion and liquid sensors are positioned in the liquid portion). Examples of gas sensors that may be included in sensor system 120 include temperature sensors, pressure sensors, and hygrometers. Examples of liquid sensors that may be included in sensor system 120 include temperature sensors, pressure sensors, pH sensors, alkalinity sensors, flow meters, electrical conductivity sensors, refractive index sensors (e.g., refractometers), specific gravity sensors (e.g., hydrometers), etc. Depending on the liquid and other environmental conditions to be measured, any other sensors may be incorporated as part of the sensor system. The sensors of sensor system 120 may function to measure specific quantities for which they are designed, but may also function in conjunction to determine more complex fluid properties such as viscosity and salinity.

[0066] Pressure sensor 121 functions to measure the pressure of the gas portion. This can be used to control the partial pressure of the unfilled portion through connection with an electronically controlled air valve, ensuring that gas pressure in the unfilled region is maintained during and after active filling of the container with water. This can also provide the precise determination of gas pressure required to calculate water carbon using air carbon sensing.

[0067] The spectroscopic sensor 122 functions to determine the concentration of CO or other carbon compounds in the gas portion. The spectroscopic sensor 122 is preferably tuned and positioned to measure carbon compounds within the gas portion of the measurement vessel 120. More specifically, the spectroscopic sensor 122 is tuned to detect and measure common carbon compounds in gases such as carbon dioxide. In one example, the spectroscopic sensor 122 is a non-dispersive infrared (NDIR) sensor. The sensor may also measure temperature and humidity for self-calibration, or the sensor may be calibrated using external humidity and temperature readings from the rest of the sensor platform. Alternatively, other sensor types may be used.

[0068] In some variations, the system may further include a fan integrated into the measurement reservoir 110 to circulate air, which can serve to improve measurement quality and potentially accelerate the attainment of equilibrium.

[0069] The temperature sensor 123 functions to measure the temperature of the water. In some variations, the temperature sensor 123 can be a separate sensor that measures the temperature of the water to improve the accuracy of the final calculated hydrocarbon conditions. In some variations, the temperature sensor 123 can be part of a CO2 sensor, such as the spectroscopic sensor 122.

[0070] The conductivity sensor 124 functions to measure the conductivity of the water, which can be used to determine a measure of the alkalinity and / or salinity of the water.

[0071] The pH sensor 125 functions to measure the pH level of the water.

[0072] Other additional or alternative sensors may be used, in one variation a depth sensor may be used to determine this water level.

[0073] In some variations, particularly automated variations, the system may include a communication system 130. The communication system 130 functions to enable system communication with any external device. The communication system 130 may be located on, within, or anywhere associated with the system. In some variations, the communication system 130 may have components (e.g., antennas) located on the exterior and / or gas portion of the measurement vessel to better enable signal transfer.

[0074] In some implementations, the communication system 130 may include only simple one-way data transfer (e.g., the system unilaterally transmits collected data to an external device). Alternatively, the communication system 130 may allow signals and / or data to be transmitted between the system and any external device. Examples include smartphones, computers, remote servers, etc. Depending on the range, type of data transfer, and type of external device, the communication system 130 may incorporate any type of wireless technology and protocol. Examples include Wi-Fi or Bluetooth, RF, IR, and any wireless cellular technology (2G, 3G, 4G, etc.).

[0075] The system may include a control system 140. The control system 140 may be particularly suited for automated modification of the system, but may be included in any desired implementation. The control system 140 may function to change the operating parameters of the system. The changes in the operating parameters of the system may be in response to data feedback (e.g., controlled feedback during carbon operations as described above, weather conditions) or in response to received external input (e.g., user input via a communication system).

[0076] The control system may include one or more computer-readable media storing instructions that, when executed by one or more computer processors, cause the computing platform to perform operations including sealing water in a vessel of the first monitoring system, the vessel having a fill level of water that leaves a defined gas fraction in the vessel, collecting sensor data from the water and the defined gas fraction, and determining a DIC concentration condition based on the sensor data of the water and the defined gas fraction after the water reaches equilibrium in the vessel. The instructions may additionally or alternatively be configured to perform any of the method process variations described herein.

[0077] Depending on the implementation, the system may have many operating parameters that can be improved via the control system 140. For example, the control system 140 may allow for the activation (or deactivation) of the system and activate specific operating modes. Possible operating parameters of the system may include turning the system on, turning the system off, changing the liquid flow rate (e.g., by opening and closing the opening of the measurement reservoir 110 to some extent to improve the incubation time for better measurements), changing the release rate of carbon or material, increasing / decreasing the rate of data collection, etc.

[0078] As described above in control feedback implementations, control system 140 may further control carbon manipulation system 150. In these variations, control system 140 may monitor the carbon concentration of the liquid and then adjust the operation of carbon manipulation system 150 to thereby increase or decrease the liquid carbon concentration.

[0079] The carbon manipulation system 150 functions to improve water quality. In particular, the carbon manipulation system 150 functions to improve DIC concentration conditions through the addition of a supplement. In one variation, this supplement may be an alkaline supplement, such as an alkaline solution. In another variation, this supplement may be carbon dioxide gas or a gas containing carbon dioxide (e.g., air, flue gas) that can be permeated or distributed through the water. In some variations, pure (or concentrated CO2 gas) may be provided by direct air capture, and the system may then be used for carbon storage in the water. Another option may be flue gas (low CO2 concentration).

[0080] The carbon manipulation system 150 may be directly integrated with the measurement reservoir 110 such that the supplement is measured directly against the water contained and enclosed by the measurement reservoir 110 .

[0081] In another variation, the carbon handling system 150 may be in communication with the monitoring system and / or the control system 140. In this variation, the carbon handling system 150 may be removed and / or established separately from the monitoring system.

[0082] The carbon handling system 150 may include a supplement deposition mechanism for adding solid or liquid supplemental materials to the water. The carbon handling system 150 may also include a mixer or other system for integrating the supplements into the water.

[0083] In some variations, the carbon manipulation system 150 may include a deposition mechanism that adds the supplement in controlled, quantified amounts. In this manner, the carbon manipulation system 150 can add a specified amount of the supplement. In other variations, the carbon manipulation system 150 may include a deposition mechanism that adds in discrete amounts. This variation can add discrete amounts periodically until a target condition is met.

[0084] In one variation, the carbon manipulation system 150 is integrated between two monitoring systems, as shown in exemplary FIG. 8. The first upstream monitoring system can report a base DIC concentration condition, and the subsequent downstream monitoring system can report the resulting DIC concentration condition for output. The sensors may be capable of determining the pH, dissolved carbon content, and other chemicals of the fluid. In one implementation, the system may be implemented in close proximity to a mining operation. In the mining discharge, the sensors can detect high mineral content and potentially high alkalinity and pH. The carbon manipulation system 150 can be controlled to dispense supplements to modify the system.

[0085] As shown in FIG. 6, the water from the input may have magnesium and calcium content and a high pH. The control system 140 can control the carbon manipulation system 150 to release carbon dioxide into the fluid, thereby increasing the DIC concentration and lowering the pH. As a generalized reaction, magnesium and calcium can combine with CO2 in the water to produce HCO3, CO3, and a lower pH. Ca and Mg will balance the charge of HCO3 and CO3 and become dissolved ions in the water. A downstream sensor may be used for controlled feedback to fine-tune the amount of carbon dioxide released into the fluid. The amount of CO2 emitted may be adjusted based on measurements in the downstream monitoring system.

[0086] 8, water from an input having a high CO2 concentration and low pH can be modified with an alkaline compound such as CaCO3. Control system 140 may control carbon manipulation system 150 to release an alkaline supplement source. The alkaline supplement source can combine with CO2 in the water to form HCO3 and calcium (e.g., in water-soluble dissolved free ions, Ca2+), raising the pH in the process.

[0087] As shown in Figure 9, a carbon manipulation system 150 may be implemented as a supply station (docked on the ground or on a floating or supported system on water) that can facilitate the mixing and addition of supplements. As shown in Figure 10, such a carbon manipulation system 150 may prepare the supplements and then add them into a water stream that is being metered and monitored. This approach may be used in natural water systems, but may also be used in closed water systems, such as treating wastewater from industrial applications.

[0088] [3. Method] As shown in FIG. 11 , a method for carbon monitoring may include, in a first monitor system, sealing S110 water in a container of the first monitor system, the container having a fill level of water that leaves a defined gas fraction, collecting S120 sensor data from the water and the defined gas fraction, and determining S130 a DIC concentration condition based on the sensor data of the water and the defined gas fraction after the water reaches equilibrium in the container.

[0089] This method functions by using a specially configured monitoring system that can establish an isolated, sealed environment to measure and monitor the DIC concentration state of a body of water. That is, the method utilizes specific properties of a body of water and the carbon concentration of a gaseous region in equilibrium with a portion of the body of water to determine the carbon concentration of the body of water. With additional information regarding some general thermodynamic and molecular properties, the method may be implemented to determine the carbon concentration of any fluid. This method, implemented using a specially configured monitoring system, may be implemented using a closed, non-moving body of water (e.g., a lake) or an open, dynamic body of water (e.g., a river). This method may be used with systems such as those described herein, or may be implemented in conjunction with alternative systems.

[0090] In some variations, collecting sensor data from the water and the defined gas fraction S120 preferably collects sensor data related to the condition of the water and the gas fraction to determine the carbon status condition within the water. Block S120 may include measuring the carbon concentration of the gas fraction S122 and measuring the water conditions, including at least the water temperature, conductivity, and water pH S124. Block S130 specifically includes determining the DIC concentration condition S130 based on the carbon concentration, temperature, water conductivity, and water pH, as shown in FIG. 12. This resulting water carbon status preferably includes characterization or measurement, including gravimetric measurements of CO, HCO, and CO.

[0091] As part of managing the carbon status monitor, the method may further include determining S132 a water equilibrium state and / or promoting S134 a water equilibrium state.

[0092] To determine DIC concentration conditions (e.g., measurements of CO2, HCO3, and CO3 in water), this method can rely on determining two constraint variables: pH and alkalinity, pH and CO2, or alkalinity and CO2, which can then be used as inputs to a DIC modeling calculation method to calculate the rest of the system. In this method, pH may be measured directly using a sensor. Alkalinity may not be available as a directly sensed value using an affordable sensor; instead, this method may apply an approach that quantifies alkalinity using conductivity (e.g., using a calibration and modeling approach that can account for the effects of salinity and temperature on conductivity to quantify both salinity and alkalinity). Also, directly measuring CO2 in water can be practically difficult within a practical / affordable device. This method can use an approach that uses air-water equilibration, so that measuring CO2 from the air can be combined with salinity (from conductivity) and temperature data to calculate the dissolved CO2 in water from measurements of CO2 in the unfilled area to calculate the solubility constant of CO2 in water. This approach can result in having three variables to calculate CO, HCO, and CO, while only two are needed to perform the necessary DIC modeling calculations. Thus, this approach allows for three independent methods for DIC modeling calculations (pH and CO, pH and alkalinity, CO and alkalinity), and then triangulates the various results from these three methods to obtain a more refined, more accurate measurement, as shown in exemplary FIG. 17.

[0093] Thus, in some variations, as shown in FIG. 14 , the method may include, in a first monitoring system, sealing S110 water in a container of the first monitoring system, the container having a fill level of water that leaves a defined gas fraction; collecting S120 sensor data from the water and the defined gas fraction; determining S130 DIC concentration states based on the sensor data of the water and the defined gas fraction after the water reaches equilibrium in the container, the determining including determining S1300 a set of variables derived from the sensor data including salinity, a set of solubility constants for CO in water, alkalinity, partial pressure of CO, and CO dissolved in aqueous solution; determining S1310 a set of preliminary DIC concentration states from a set of separate DIC modeling methods based on the derived variables; and determining S1320 DIC concentration values ​​through convergence analysis of the set of preliminary DIC concentration states.

[0094] Some method variations may be further extended for carbon management of a fluid, where the carbon status may be directly influenced and / or enhanced. In these variations, the method may further include improving water quality S140, which may be performed based on and / or in response to DIC concentration, as shown in FIG. 13 . In such water management method variations, the method may function to actively monitor and control water quality. In addition to monitoring and improving DIC concentration, the method may control water quality by improving water pH, water alkalinity, water mineral content, and / or water mineral quality (e.g., by salt formation). This water quality improvement can be controlled and adjusted using control feedback from the determined DIC concentration of the water.

[0095] In some variations, the method may be implemented in connection with a single monitor system, while in other variations, the method may be implemented in connection with multiple monitor systems used in combination to monitor the carbon status of a water system.

[0096] As shown in FIG. 15 , a method for carbon monitoring in a network includes, at a first monitor system, sealing S1110 a first volume of water in a first container of the first monitor system, the first container having a fill level of water leaving a defined gas fraction; collecting S1120 sensor data from the water and the defined gas fraction; and determining S1130 a DIC concentration status of the first monitor system based on carbon concentration, temperature, water conductivity, and water pH after the water reaches equilibrium in the first container; and at a second monitor system, sealing S1130 a second volume of water in a second container of the second monitor system using a second volume of water, the first container having a fill level of water leaving a defined gas fraction. The method may include enclosing S2110 a second container with a fill level of water leaving a second defined gas portion (i.e., a second defined gas portion), the second container being downstream of the first monitoring system in the water system; collecting S2120 sensor data (e.g., a second set of sensor data) from the second volume of water and the defined gas portion in the second container; determining S2130 a DIC concentration state in the second monitoring system based on carbon concentration, temperature, water conductivity, and water pH after the water in the second monitoring system has reached equilibrium in the second container; and comparing S136 the DIC concentration state in the first monitoring system with the second monitoring system to determine a change in the DIC concentration state.

[0097] The two monitoring systems can preferably individually implement the monitoring operations described herein, and then the results can be compared and / or used in combination. For example, collecting sensor data (e.g., a second set of sensor data) from the second volume of water and the defined gas portion in the second container S2120 may include measuring the carbon concentration of the gas portion in the second monitoring system and measuring water conditions in the second monitoring system including at least water temperature, water conductivity, and water pH.

[0098] In one exemplary application, two or more monitoring systems may be used in an industrial wastewater system, where an initial upstream monitoring system is used to monitor initial DIC concentration conditions and a subsequent downstream monitoring system is used to monitor resulting DIC concentration conditions. This may be used to treat water resulting from an industrial process. This may also be used to monitor the impact of the industrial process on a water source.

[0099] In another exemplary application, two or more monitoring systems may be used in a natural water system. For example, an initial upstream monitoring system may be located at an upstream location in the flowing water system, and a subsequent downstream monitoring system may be located at a downstream location in the flowing water system.

[0100] This method may also be used across a large network having several monitoring points and / or several points or areas where water system improvements may be applied.

[0101] Block S110 includes sealing water in a container of the first monitoring system and functions to obtain a sample of the body of water for analysis. Sealing water in the container can include filling the container. The container is preferably partially filled so that a portion of the container (i.e., the filled region or water portion) is filled with water and a portion of the container (i.e., the unfilled region or gas portion) is empty. Thus, the water is sealed at a fill level that leaves a defined gas portion within the container. The monitoring system preferably includes a container equipped or otherwise configured to sense the condition of the water and the gas.

[0102] In some variations, Block S110 is a single operation and a single sample is taken. Alternatively, Block S110 may involve setting up the detection vessel so that water moves continuously through the filled region while the gas portion remains empty (of water / liquid).

[0103] Enclosing water in the first monitoring system container can include receiving water from an external water system through an inlet in the monitoring system / container until the water reaches a fill level. After the water reaches equilibrium and / or after sensing and monitoring is completed, the method can include releasing the water.

[0104] In some variations, the external water system is a natural water system. Natural water systems can include flowing natural water systems such as streams, rivers, tidal estuaries, and coastal waters, but can also include substantially stagnant water systems such as ponds, lakes, and reservoirs. In some variations, the external water system is an industrial water system, such as a wastewater system.

[0105] In some variations, water may be received from a water source and then the monitored water may be discharged back to the same water source. In some variations, water may be received from a water source and then discharged to several water outputs. This may be of particular use in industrial applications where water from several sources is received via inbound conduits (e.g., pipes, channels, etc.) and then discharged to several outbound conduits.

[0106] In one variation, the monitoring system may include a single water opening. This water opening may be dynamically opened and closed to allow water to enter and exit the container. Thus, sealing the water may include opening the container opening, thereby allowing water to fill the container, and closing the container opening once completed, thereby allowing water to exit the container. In some variations, the monitoring system may further include a controllable air valve 126 that can be mechanically opened and closed to allow air to enter to drain the water, and then close when the container is refilled. Thus, sealing the water may include opening the container opening and air valve, thereby allowing water to fill the container, and closing the container opening and air valve once completed, thereby allowing water to exit the container. In some cases, the container is not emptied, but new water can enter to replace the water previously contained therein.

[0107] In another variation, the monitor may include an inlet and an outlet. The inlet may be opened to allow water to enter and may be closed when new water reaches this fill level. The outlet may be opened to allow water to exit and then closed to facilitate sealing in a fixed amount of water.

[0108] In some variations, the method may include detecting water reaching a fill level. In one variation, detecting the water level may include using a float switch that uses a buoyant float to trigger a change in an electrical signal when the water rises to a certain level. Alternatively, detecting the water level may include using a conductive water level sensor on the edge of the container, using an optical / visual depth sensor, and / or other sensing approaches. In some variations, the method may not be contingent on achieving a certain volume of water. The method may include sensing the water level, which can be used to calculate the volume of the water and / or gas fraction. The water and gas volume variables may be factored into the process of determining the DIC concentration state. Other alternative methods may manage the fill level using a non-sensing approach. In one such variation, the amount of water added may be controlled, regulated, or implemented. In one exemplary variation, the fill level may be controlled or managed by controlling the flow of water into the container, such that the fill level may be determined by the amount of time water is added to the container.

[0109] In a continuous flow variation, the rates of water inflow and outflow from the system can be the same so that the volumes of water and air in the vessel remain the same, and changes in water carbon can be quantified in a continuous flow fashion. The volumes of both air and water can be optimized to detect more rapid or larger magnitude fluctuations in water carbon.

[0110] Block S120, which includes collecting sensor data from the water and defined gas portions, functions to detect a set of measurable parameters of the water and gas portions within the vessel. These measurable parameters can be used in assessing the state of various chemical reactions that can be indicative of DIC concentration conditions.

[0111] In particular, collecting sensor data preferably collects sensor data for detecting water temperature, water conductivity, water pH, pressure of the gas fraction, and CO2 concentration of the gas fraction. Thus, collecting sensor data from the water and the defined gas fraction may include measuring and / or sensing at least the carbon concentration of the gas fraction S122 and measuring and / or sensing water conditions including at least water temperature, conductivity, and water pH S124. The collected sensor data is preferably collected from a set of different sensors integrated within the encapsulation. This sensor data may be communicated or otherwise transferred to a computing device.

[0112] Several sensor data measurements are periodically monitored and read as a method for assessing and / or determining the equilibrium state. For example, CO2 and pH may be periodically monitored for a steady-state condition indicative of the water's equilibrium state. In one exemplary implementation, these measurements may be taken periodically (e.g., every 3 seconds), although any suitable period may be used. This period may also be adjusted based on the amount of water in the container. These periodic measurements may be taken during filling and afterward until the equilibrium state is determined. This equilibrium state may be determined when CO2 does not change by more than some threshold (e.g., the accuracy of the sensor used) for a set period of time (e.g., 30 seconds). All measured parameters may then be taken at a final "equilibrium" point to calculate the water's DIC composition state. Other sensor data inputs may be sensed during the equilibrium state so that they can be used in determining the DIC concentration state.

[0113] In some variations, measurements may be taken periodically (e.g., every 10 seconds) to provide a substantially continuous record of both baseline metrics and metrics to assess the impact of carbon dioxide removal (CDR) practices, if implemented. These data, as well as system status and performance metrics, may be automatically uploaded to an online dashboard for remote monitoring by operators, third-party MRV providers, regulators, and any other interested parties.

[0114] Block S122, which includes measuring the carbon concentration of the gas portion, functions to determine the CO2 level within the gas portion. Measuring the carbon concentration preferably measures the concentration of CO2 in the gas portion, although additional or alternative carbon compounds may be detected as well. Sensing CO2 or other carbon-based molecules may use a wide-range spectrometer. Because the primary form of carbon includes carbon dioxide, a spectrometer operating in the infrared spectrum may be sufficient to measure the carbon concentration of the unfilled region. Measuring CO2 may use a spectroscopic sensor, such as an NDIR sensor, in some variations.

[0115] In addition to measuring the carbon concentration of the gas portion, collecting sensor data may include measuring the pressure within the gas portion. Thus, in some variations, an alternative process to block S122 may include measuring the carbon concentration and pressure of the gas portion. In one variation, measuring the pressure may use a gas pressure sensor integrated into the vessel and oriented to sense within the gas portion. Alternative variations may estimate or use alternative techniques for incorporating pressure. In one variation, the pressure may be held stationary by a responsive pressure valve that functions to bring the pressure within the gas portion to a known amount. Knowing the pressure improves the accuracy of the conversion of CO2 in air to CO2 in water by better constraining the solubility constant for CO2.

[0116] Block S124, which includes measuring the water condition, functions to evaluate a set of parameters used to determine the water condition. Measuring the water condition can include measuring at least the water temperature, water conductivity, and / or water pH. Water salinity and / or alkalinity are other important parameters that can be derived using the sensed data. For example, salinity can be based in part on the water temperature and electrical conductivity, while alkalinity can be based in part on electrical conductivity and other parameters, depending on the implementation. Measuring the water properties S134 can be performed in the detection vessel, but, particularly for large bodies of water, block S134 can be performed anywhere within the body of water that is likely to have properties similar to those of the sample taken.

[0117] Block S130 includes determining the DIC concentration state based on the carbon concentration, temperature, water salinity, and water pH, and functions to use measurable properties after the water reaches equilibrium in the vessel to estimate the levels of various carbon compounds using assumed chemical reactions. At steady state, this gaseous carbon concentration may be used in conjunction with the water properties to calculate the DIC concentration.

[0118] Depending on the implementation, Block S130 may further determine the concentration of one or more different molecular forms of carbon. In one variation, the hydrocarbon condition may be characterized by at least measurements (e.g., concentration measurements) of at least CO, HCO, and CO. That is, determining the DIC concentration S130 may further include determining a water carbon dioxide concentration, determining a water carbonate concentration, and / or determining a water bicarbonate concentration.

[0119] Measuring the DIC concentration state preferably uses sensor data from block S120 collected from the gas and water fractions to determine several intermediate parameters and then to determine measurements of the individual DIC components: CO2, HCO3, and CO3. Thus, in one variation, determining the DIC concentration state may include determining a set of variables derived from the sensor data S1300, determining a set of preliminary DIC concentration states from a set of different methods (i.e., DIC modeling methods) based on the derived variables S1310, and determining DIC concentration values ​​by convergence analysis of the set of preliminary DIC concentration values ​​S1320, as shown in FIG. 14. Using multiple methods to derive the DIC concentration state can serve to improve the prediction of the DIC concentration state by triangulating from different methods that have different biases in their modeling. Different methods may rely on different relationships and / or chemical transformations / reactions to model the predicted DIC concentration values. This convergence analysis can combine and evaluate these different predicted DIC concentration values ​​to output a preferably more reliable and accurate prediction of the DIC concentration state. Because the resulting responses can be highly multivariate, using convergence analysis of different independent methods can yield more accurate predictions that are less affected by the assumptions of the individual methods.

[0120] Furthermore, the final DIC concentration state not only characterizes the measurements for a combination of DIC components, but also for multiple DIC components, i.e., CO2, HCO3 - and CO3 2- It is possible to provide individual measurements for

[0121] However, in some variations, the method may be simplified to use a single method in which determining the DIC concentration state includes determining a set of derived variables from the sensor data and then directly determining the DIC concentration state from the set of derived variables. This variation may use a single DIC modeling method, which may be used in certain situations or implementations. For example, in some applications, the initial state of the water may be substantially stable, and a single method may be sufficient to predict the measured DIC concentration state.

[0122] Block S1300 includes determining a set of variables derived from the sensor data and functions to use the sensor data to determine various other intermediate parameters that can be used to assess the DIC concentration condition. The exact derived variables determined may depend on the method used to model the DIC concentration condition.

[0123] 14 and 16, determining the set of variables derived from the sensor data may include first determining salinity from conductivity S1301, determining a set of solubility constants for CO2 in water, including pK1 and pK2, from temperature, salinity, and pressure S1302, determining alkalinity from at least the conductivity S1303, determining the partial pressure of CO2 in the atmosphere (e.g., μatm) from pressure and CO2 ppm measurements S1304, and determining dissolved CO2 in the aqueous solution S1305 from the partial pressure of CO2 and the solubility constant KCO2 for CO2. - and the DIC components (or species) of CO32 can be represented by the following formula:

[0124] DIC = [H2CO3] + [HCO3-] + [CO3 2- ]

[0125] H2CO3=pCO2KCO2

[0126] H2CO3=HCO3+[H]K1

[0127] HCO3=CO32+[H]K2

[0128] Dissolved CO2 can contain two pools: free CO2 and H2CO3. The air-to-water solubility coefficient, K co2 , and the first and second dissociation constants K1 and K2 of carbonic acid (H2CO3), are functions of salinity and temperature. pCO2 is the partial pressure of CO2 gas in the atmosphere in equilibrium with water.

[0129] Determining salinity from conductivity S1301 may use a conductivity measurement of the water in combination with a temperature measurement to predict salinity, which may be measured in parts per trillion.

[0130] Determine a set of solubility constants for CO2 in water from temperature, salinity, and pressure S1302 can determine the solubility constants KCO2, pK1, and pK2.

[0131] Determining alkalinity from conductivity S1303 can use conductivity in combination with other sensor data and / or intermediate derived variables. This alkalinity may be measured in related units, such as micromoles / kg. In one variation, alkalinity may be derived based on a combined analysis of pH, aqueous CO2 concentration, and conductivity, or by conductivity alone when incorporated into a numerical model that can be used to directly quantify alkalinity. Taking into account temperature dependence, electrical conductivity may be interpreted or modeled as a description of the sample's bulk composition—salinity, total dissolved solids (TDS), alkalinity, and ionic strength. In some modeling approaches, alkalinity can be expressed as a linear relationship between conductivity and alkalinity using both empirically derived regression models and / or theoretically derived models that consider the ionic strength and activity of individual ions. Dynamic calibration of this linear modeling can further enhance this approach.

[0132] In some variations, a machine learning model may be trained to predict alkalinity based on pH, conductivity, and CO2 concentration. Thus, determining alkalinity may include processing conductivity, pH, CO2 concentration, and / or other additional sensor data and / or derived variables in a model (e.g., a trained AI / ML model such as a neural network) and outputting the alkalinity measurement as a derived variable. In another variation, the derived CO2 may be used with other sensor data and / or derived variables and one DIC modeling method to determine a preliminary DIC concentration state prediction, and the results may then be applied to back-calculate alkalinity measurements that may be used in one or more other DIC modeling methods in S1310.

[0133] Determine partial pressure of CO2 in atmosphere from pressure and CO2 ppm measurements S1304 functions to use pressure measurements from the gas portion (e.g., headspace pressure measured using a pressure transducer) and CO2 concentration measurements (e.g., using an NDIR sensor measuring CO2 in ppm).

[0134] Determine solubility constants for CO2 and CO2Ko dissolved in aqueous solution from the partial pressure of CO2 S1305 functions to predict the CO2 concentration in water at equilibrium using the solubility constant of CO2 and the partial pressure of CO2 in air above the water. Both the water and air volumes must be known, and equilibrium must be established. In some variations, the water may be dispensed using a sprayer or some other mechanism to agitate the water. Additionally, the sensor data may be monitored to detect when equilibrium is established based on stabilization of the sensor data (e.g., reaching a steady state).

[0135] Block S1310 includes determining a set of preliminary DIC concentration states from a set of distinct methods based on the derived variables, and functions to use different independent DIC modeling methods to determine measurements of DIC components. Each method can generate one preliminary DIC concentration state measurement. In one variation, three different DIC modeling methods can be used. However, some variations may use two or more different DIC modeling methods. In one variation, a first DIC modeling method may include predicting a first preliminary DIC concentration state based on modeling alkalinity and pH, a second DIC modeling method may include predicting a second preliminary DIC concentration state based on modeling CO2 and pH, and a third DIC modeling method may include modeling a third DIC concentration state based on modeling alkalinity and CO2. As in the exemplary variations of the first, second, and third DIC modeling methods described above, these different methods may use different inputs and may be based on different modeling assumptions or calculations.

[0136] A first DIC modeling method may use alkalinity and pH to derive a preliminary DIC concentration state. For example, CO can be calculated independently using = (alkalinity - ((Kb (boron solubility constant) x Bt (boron concentration)) / (Kb + H)) - ((10^-7) / H) + H) / ((K1 / H) + (2 x ((K1 x K2) / (H^2)))), which can then be used as above to calculate DIC and other parameters.

[0137] A second DIC modeling method can use CO2 and pH to derive different DIC component measurements to establish a preliminary DIC concentration state. Once dissolved CO2 is calculated using the above, it can be used to calculate the total concentration of all dissolved inorganic carbon ions (CO2, HCO3, CO3) using the formula: DIC = CO2 × (1 + (K1 / h) + ((K1 × K2) / h2)), where h is the standard hydrogen ion concentration (derived from pH) and CO2 is in uatm. Once the overall DIC is calculated from the above, its known quantities, pH, and CO2 can be used to calculate HCO3 and CO3 and other related parameters (e.g., carbonate saturation). As noted above, sometimes this method based on CO2 and pH may be used to infer or determine alkalinity measurements that can be used in other methods. However, different approaches to determining alkalinity may alternatively be used, including the electrical conductivity approach described above.

[0138] A third DIC modeling method can use alkalinity and CO2 to determine another preliminary DIC concentration state, where alkalinity and CO2 are used in a quartic equation to calculate pH, which is then incorporated into the above method for calculation of the remaining DIC compounds.

[0139] Block S1320 includes determining DIC concentration values ​​through a convergence analysis of the set of preliminary DIC concentration values, which functions to triangulate or otherwise perform a combined analysis of different modeled DIC concentration states to determine several combined outputs. For example, different DIC modeling methods may generate a first set of DIC concentration state measurements for CO2, HCO3, and CO3, a second set of DIC concentration state measurements for CO2, HCO3, and CO3, and a third set of DIC concentration state measurements for CO2, HCO3, and CO3. This convergence analysis can examine the overlap of value predictions of the different measurements to determine the final DIC concentration state, as shown in FIG. 17. In another embodiment, this convergence analysis may use some averaging (e.g., a weighted average) of the different DIC concentration values.

[0140] Determining the DIC concentration state can depend on the water achieving equilibrium within the sealed vessel. Therefore, the method may include a block S132 that determines or detects the water equilibrium state, which serves to identify when the system (e.g., the interaction between the water and the gas) has relaxed to a steady state. That is, the system can be allowed to rest until there is no net molecular exchange between the filled and unfilled regions of the detection vessel. Sealing the unfilled regions (and possibly the filled regions) may be required for the system to reach this steady state.

[0141] In some variations, this determination may be based on a prediction using various factors. In this manner, determining the equilibrium state may include predicting the equilibrium state. For example, this equilibrium state may be predicted to occur after a certain period of time. In this manner, water may be sealed and allowed to settle for a certain period of time, after which the DIC concentration state may be analyzed. This amount of time may be variable based on various conditions, such as initial temperature, pressure, pH, and CO2 levels. Therefore, initial sensor data may be measured when predicting the equilibrium state.

[0142] In other variations, the determination of equilibrium may be actively detected using sensor data. For example, a steady state of CO2 and / or pH may be an indicator of equilibrium. In this manner, determining the equilibrium state of water may include detecting equilibrium by periodically measuring CO2 and pH for an enclosed volume of water. The CO2 and pH measurements may be monitored until a steady state is reached. This steady state condition is generally when the CO2 and pH levels no longer change. The sensitivity and / or error threshold of the sensor, as well as an acceptable level of variation, may be incorporated into the condition. For example, CO2 may be monitored for consistent readings with a variance of less than 5 ppm, which corresponds to the error range of some sensors.

[0143] Due to the continuous flow implementation, the system may be prevented from reaching a steady state, as unfilled regions will be continuously replenished from the external environment.

[0144] Therefore, due to the implementation of continuous flow in the filled region, the method may use a water body for measurements that is large enough to act as a reservoir so that the particle concentration in the water body is not affected by the unfilled region of the detection vessel reaching a steady state.

[0145] The time required to reach steady state may be implementation specific. Depending on external environmental conditions (e.g., temperature, carbon imbalance between air and water, etc.), the time required to equilibrate the filled and unfilled regions S120 may vary. In some new implementations, this time may be optimized by taking an initial sample and monitoring the carbon fluctuations in the unfilled region. This may be done multiple times at different temperatures to potentially determine the time required at different times of day.

[0146] Block S134 includes promoting equilibrium of the water and functions to alter the establishment of equilibrium. In one variation, promoting equilibrium can include spraying, aerating, shaving, mixing, evaporating, or otherwise agitating the water enclosed within the container. In some variations, this may function to ensure equilibrium when taking measurements to determine DIC concentration conditions.

[0147] As discussed, some variations may implement multiple monitoring systems so that DIC concentration status monitoring can be tracked at different locations and / or stages of water changes (e.g., from industry practice, as an improvement via S140).

[0148] Implementations using multiple monitoring systems can have each monitoring system perform the monitoring process described herein. In some variations, there may be two monitoring systems in a flowing water system, with one monitoring system used upstream and a second monitoring system used downstream. In other variations, monitoring systems may be distributed across multiple regions within a region. For example, when monitoring a large body of water, such as a lake, monitoring systems may then be distributed at various points to establish a "map" of DIC concentration conditions.

[0149] When multiple DIC concentration conditions are measured, the method may then include S136 comparing the DIC concentration conditions in the first monitoring system with those in the second monitoring system to determine changes in the DIC concentration conditions. Block S136 functions to evaluate the changed conditions between one monitoring system and another. When used in a flow-through water system, this may be used to see how the water has changed. In some variations, the first monitoring system may be oriented upstream to determine initial conditions, and then some enhancement or change may be introduced into the water between the first and second monitoring systems. Then, after the change, the subsequent downstream monitoring system can determine the measured carbon concentration conditions resulting from the change. Comparing the results from the two monitoring systems may be used to determine the impact of the change.

[0150] In some variations, the introduced change may be natural, such as a stream flowing into a major river system, or from some industrial process or system.

[0151] In one variation, the change introduced may be the introduction of a supplement based on the DIC concentration status as part of S140.

[0152] Block S140 includes improving the water quality and functions to change the composition of the water by changing the pH of the water, the alkalinity of the water, and / or the DIC concentration. Improving the water quality S140 can be responsive to the measured DIC concentration or other water quality, as determined by block S130.

[0153] One variation S140 for improving water quality involves adding a supplement and adjusting the addition of the supplement to meet the target water carbon condition. In some variations where the CO2 concentration in the water is increased, the supplement is alkaline and may be provided and added in various forms. In one variation, an alkaline supplement is provided through a solution and mixed with the water. The target DIC concentration condition can be achieved by adding an alkaline supplement to maintain the pH below 8.5 or even higher for precipitation and management of solid carbon minerals.

[0154] In some other variations, the supplement can be CO2, such as recovered gaseous CO2, flue gas, or ambient air. Improving water quality S140 can include distributing gaseous CO2 through the water. This may further include adjusting the distribution of gaseous CO2 to meet target water carbon requirements. This may be done, for example, in a water system containing a certain amount of magnesium and calcium and a high pH. The introduction of CO2 can result in reactions that convert magnesium, calcium, and CO2 to HCO3, CO3, CaCO3, and MgCO3. These reactions can further lower the pH of the water.

[0155] If multiple monitoring systems are present, they may be used to determine changes in DIC concentration conditions between the two monitoring systems. In this scenario, improving water quality may be based on this change. Therefore, improving water quality, in one variation, includes adding a supplement or additive to the water system and adjusting the addition of the supplement based on the determined change in DIC concentration conditions. The supplement may be a dry powder or concentrate added to the water. In another variation, the supplement may be a diluent. Adding the supplement may further include an integration process to initiate a reaction or integration of the supplement with the water. For example, adding the supplement may include permeating a supplement gas through the water, or in another example, stirring or mixing a solution in the water. Different supplements or actions may be performed for different conditions and / or implementations.

[0156] In one exemplary scenario variation where the local water is highly alkaline and rich in minerals, improving the water quality S140 may serve to reduce the pH (e.g., by adding carbon dioxide). Adding CO can then convert the CO to HCO and CO (e.g., for storage).

[0157] In another scenario variation where the water has a high carbon concentration and / or a low pH, improving the water quality S140 can involve adding alkaline compounds to increase the pH and recover / remove carbon from the water. The alkaline compounds may be introduced into the water's initial carbon chemistry (CO, HCO, CO concentrations, and pH) to reduce excess CO, bring it into equilibrium with the atmosphere (e.g., 425 ppm), and bring the pH below a threshold (e.g., below 8.5). As shown in Figure 18, the addition of alkalinity may be used to reduce CO, increase HCO and CO, and maintain a pH below 8.5. This alkalinity can convert dissolved CO2 to HCO3 and CO3 via the generalized pathway CO2(aq) + H2O + CaCO3 (or other alkalinity) → 2HCO3(aq) + Ca2+(aq).

[0158] Improving water quality by adding supplements can include adding the supplements within the container, but alternatively, adding them externally to the container. In some variations, an external carbon manipulation system is used. This carbon manipulation can be controlled to deposit the supplement. In some variations, it may add discrete amounts at different times. In other variations, varying amounts of supplement may be added. In some variations, the amount of supplement added is based on the current state of the DIC concentration condition. Adding the supplement may further include mixing, dispersing, or otherwise integrating the supplement within the water system. This improvement may be performed until the desired condition is met. In some variations, this may be done through an iterative process of adding the supplement, evaluating the new DIC concentration condition after equilibration of the water sample, and then repeating until the DIC concentration condition matches the target condition.

[0159] [4. System Configuration] Systems and methods of embodiments may be embodied and / or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions may be executed by a computer-executable component integrated with an application, applet, host, server, network, website, communication service, communication interface, hardware / firmware / software element of a user computer or mobile device, wristband, smartphone, or any suitable combination thereof. Other systems and methods of embodiments may be embodied and / or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions may be executed by a computer-executable component integrated with the above-mentioned types of devices and networks. The computer-readable medium may be stored in RAM, ROM, flash memory, EEPROM, optical device (CD or DVD), hard drive, floppy drive, or any other suitable device or medium. The computer-executable component may be a processor, although any suitable dedicated hardware device may (alternatively or additionally) execute the instructions.

[0160] In one variation, a system comprising one or more computer-readable media (e.g., non-transitory computer-readable media) storing instructions that, when executed by one or more computer processors, cause the computing platform to perform operations including operations of the systems or methods described herein, such as sealing water in a container of a first monitoring system, the container having a fill level of water that leaves a defined gas fraction, collecting sensor data from the water and the defined gas fraction, and determining a DIC concentration state based on the sensor data of the water and the defined gas fraction after the water reaches equilibrium in the container.

[0161] 19 is an exemplary computer architecture diagram of one implementation of the system. In some implementations, the system is implemented in multiple devices that communicate over a communication channel and / or network. In some implementations, elements of the system are implemented in separate computing devices. In some implementations, two or more of the system elements are implemented in the same device. The system and portions of the system may be integrated into a computing device or system that can function as or within the system.

[0162] Communications channel 1001 interfaces with processors 1002A-1002N, memory (e.g., random access memory (RAM)) 1003, read-only memory (ROM) 1004, processor-readable storage medium 1005, display device 1006, user input device 1007, and network device 1008. As shown, a computer infrastructure may be used in connecting sensor system 1101, communication system 1102, control system 1103, carbon manipulation system 1104, and / or other suitable computing devices.

[0163] The processors 1002A-1002N can take many forms, such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a microprocessor, an ML / DL (Machine Learning / Deep Learning) processing unit, such as a tensor processing unit, an FPGA (Field Programmable Gate Array), a custom processor, and / or any suitable type of processor.

[0164] The processors 1002A-1002N and main memory 1003 (or some subcombination) may form a processing unit 1010. In some embodiments, the processing unit includes one or more processors communicatively coupled to one or more of RAM, ROM, and machine-readable storage media, where one or more processors of the processing unit receive instructions stored by one or more of RAM, ROM, and machine-readable storage media via a bus, and the one or more processors execute the received instructions. In some embodiments, the processing unit is an ASIC (Application Specific Integrated Circuit). In some embodiments, the processing unit is a SoC (System-on-Chip). In some embodiments, the processing unit includes one or more of the elements of the system.

[0165] The network device 1008 may provide one or more wired or wireless interfaces for exchanging data and commands between the system and / or other devices, such as devices in external systems. Such wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, a Bluetooth interface, a Wi-Fi interface, an Ethernet interface, a Near Field Communication (NFC) interface, etc.

[0166] Computer and / or machine-readable executable instructions comprising software programs (such as operating systems, application programs, and device drivers) may be stored in memory 1003 from a processor-readable storage medium 1005, a ROM 1004, or any other data storage system.

[0167] When executed by one or more computer processors, each machine-executable instruction may be accessed by at least one of processors 1002A-1002N (of processing unit 1010) via communication channel 1001 and then executed by at least one of processors 1001A-1001N. Data, databases, data records, or other storage formations created or used by the software program may also be stored in memory 1003, and such data may be accessed by at least one of processors 1002A-1002N during execution of the machine-executable instructions of the software program.

[0168] The processor-readable storage medium 1005 may be one (or a combination of two or more) of a hard drive, a flash drive, a DVD, a CD, an optical disk, a floppy disk, flash storage, a solid-state drive, a ROM, an EEPROM, an electronic circuit, a semiconductor memory device, etc. The processor-readable storage medium 1005 may include an operating system, software programs, device drivers, and / or other suitable subsystems or software.

[0169] As used herein, terms such as first, second, third, etc. are used to characterize and distinguish various elements, components, regions, layers, and / or sections. These elements, components, regions, layers, and / or sections should not be limited by these terms. The use of numerical terms may be used to distinguish one element, component, region, layer, and / or section from another element, component, region, layer, and / or section. The use of such numerical terms does not imply a sequence or order unless clearly indicated by context. Such numerical references may be used interchangeably without departing from the teachings of the embodiments and variations herein.

[0170] Those skilled in the art will appreciate from the foregoing detailed description, and from the drawings and claims, that modifications and variations can be made to the embodiments of the invention without departing from the scope of the invention, which is defined in the claims that follow.

Claims

1. In the first monitoring system, water is sealed inside the container of the first monitoring system, and the container has a water level that leaves a defined gas portion. The collection of sensor data from the water and the defined gas portion, The carbon concentration of the aforementioned gas portion is measured, At a minimum, the water's condition, including water temperature, water conductivity, and water pH, must be measured. Including collecting, After the water reaches equilibrium in the container, the dissolved inorganic carbon concentration state is determined based on the carbon concentration, temperature, water conductivity, and water pH. Methods that include...

2. The method according to claim 1, wherein sealing the water in the container of the first monitoring system includes receiving water from an external water system through the inlet of the container until the water reaches the filling level, and releasing the water after the water has reached the equilibrium state.

3. The method according to claim 2, wherein the external water system is a natural water system.

4. The method according to claim 2, wherein the external water system is a wastewater system.

5. The hydroxycarbon state is at least CO ２ , HCO ３ , and CO ３ The method according to claim 1, comprising a weight measurement.

6. Determining the dissolved inorganic carbon concentration state is, Determine the set of variables derived from the aforementioned sensor data, Based on the derived variables, a set of pre-dissolved inorganic carbon concentration values ​​is determined from a separate set of modeling methods, The method according to claim 1, comprising determining the dissolution concentration state by convergent analysis of a set of preliminary dissolution concentration values.

7. Based on the derived variables, a set of pre-dissolved inorganic carbon concentration values ​​can be determined from a separate set of modeling methods. Determining the salt concentration from the aforementioned water conductivity, CO2 in water ２ Determining the set of solubility constants, At least from the water conductivity, CO ２ To determine the alkalinity, The pressure and CO in the aforementioned gas portion ２ From the amount of CO in the atmosphere ２ Determining the partial pressures, said CO ２ partial pressure, and the solubility constant for CO in said set of solubility constants ２ based on the solubility constant for CO, determining said CO dissolved in said water ２ and determining Based on the derived variables, a set of pre-dissolved inorganic carbon concentration values ​​can be determined from a separate set of modeling methods, such as a modeling method based on alkalinity and pH, and CO2. ２ and pH-based modeling methods, as well as alkalinity and CO2 ２ This includes using a separate set of modeling methods, including a modeling method based on The method according to claim 6.

8. The method according to claim 1, further comprising detecting the equilibrium state of the water.

9. In the second monitoring system, a second volume of water is sealed in the second container of the second monitoring system, wherein the water in the second container is at a filling level that leaves a defined gas portion, and the second monitoring system is located downstream from the first monitoring system in the water system. The method involves collecting sensor data from the second volume of water in the second container and the defined gas portion, The carbon concentration of the gas portion of the second monitoring system is measured, The collection of data includes measuring the water conditions of the second monitoring system, including at least water temperature, water conductivity, and water pH. After the water in the second monitoring system reaches equilibrium in the second container, the dissolved inorganic carbon concentration state in the second monitoring system is determined based on the carbon concentration, temperature, water conductivity, and water pH. The dissolved inorganic carbon concentration state in the first monitoring system is compared with that of the second monitoring system to determine the change in the dissolved inorganic carbon concentration state, The method according to claim 1, further comprising:

10. The method according to claim 9, further comprising adding a supplement to the water system and adjusting the addition of the supplement based on the determined change in the dissolved inorganic carbon concentration state.

11. The method according to claim 1, further comprising adding an alkaline supplement and adjusting the addition of the supplement to satisfy a target hydroxyl state.

12. The method according to claim 11, wherein the target hydrocarbon state includes a pH of less than 8.

5.

13. The method according to claim 1, further comprising distributing gaseous carbon dioxide through the water and adjusting the distribution of gaseous carbon dioxide to satisfy a target hydrocarbon state.

14. Measuring container and Sensor system and, A control system, when executed by one or more computer processors, The first monitoring system involves sealing water in the measuring container, including the water at a filling level that leaves a defined gas portion within the measuring container. The collection of sensor data from the water and the defined gas portion, The carbon concentration of the aforementioned gas portion is measured, At a minimum, the water's condition, including water temperature, water conductivity, and water pH, must be measured. Including collecting, and After the water reaches equilibrium in the container, the dissolved inorganic carbon concentration state is determined based on the carbon concentration, temperature, water conductivity, and water pH. A control system having a computer-readable medium that stores instructions for causing the control system to perform an operation including the above, A system equipped with these features.

15. The system according to claim 14, wherein the measuring container has at least one opening controlled to seal in the water.

16. The system according to claim 14, wherein the sensor system comprises a pressure sensor 121, a spectroscopic sensor integrated within the gas portion of the measuring container, a temperature sensor integrated within the water, a conductivity sensor, and a pH sensor.

17. The system according to claim 14, further comprising a carbon improvement system, wherein the command causes the control system to perform an operation in the carbon improvement system, which includes adding a supplement to a water system and adjusting the addition of the supplement based on the determined change in the dissolved inorganic carbon concentration state.

18. A non-temporary computer-readable medium that, when executed by one or more computer processors of a computing platform, stores instructions that cause the computing platform to perform an action: In the first monitoring system, water is sealed inside the container of the first monitoring system, and the water is contained in the container at a filling level that leaves a defined gas portion. The collection of sensor data from the water and the defined gas portion, The carbon concentration of the aforementioned gas portion is measured, At a minimum, the water's condition, including water temperature, water conductivity, and water pH, must be measured. Including collecting, After the water reaches equilibrium in the container, the dissolved inorganic carbon concentration state is determined based on the carbon concentration, temperature, water conductivity, and water pH. A non-temporary computer-readable medium for storing instructions that cause the computing platform to perform an operation including the above.

19. A non-temporary computer-readable medium according to claim 18, further comprising adding a supplement to a water system and adjusting the addition of the supplement based on a determined change in the dissolved inorganic carbon concentration state.

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