Ocean Carbon Dioxide Removal Frequency-Based Detection
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Solution Overview
Problem
Current ocean Carbon Dioxide Removal (CDR) systems face challenges in measuring and verifying the effectiveness of atmospheric CO2 removal due to natural variations in ocean chemistry, making it difficult to distinguish human-induced changes from natural fluctuations.
Innovation Solution
A frequency-based detection method is employed, where ocean CDR systems release base substances at specific frequencies that coincide with quiet natural variations, allowing sensors to collect and process time-based data to generate power spectra, thereby isolating and verifying human-induced contributions to atmospheric CO2 removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous monitoring of ocean chemistry is performed to measure atmospheric CO2 removal, then measurement coverage is improved, but natural variations in ocean chemistry make it difficult to distinguish human-induced changes from natural fluctuations
Solution Approach 1:
The patent applies periodic action by releasing base substances at specific frequencies that coincide with quiet natural variations in ocean chemistry. This periodic release creates detectable signals at known frequencies, allowing sensors to distinguish human-induced changes from natural fluctuations through frequency analysis of the collected data.
Solution Approach 2:
The patent changes the temporal parameter of base substance release from continuous or random to periodic at specific frequencies. This parameter change transforms the measurement approach by creating distinct frequency signatures that can be detected and analyzed, enabling reliable distinction between anthropogenic and natural ocean chemistry variations.
2Productivity
If base substances are released continuously to maximize CO2 removal, then productivity is improved, but the ability to detect and measure the contribution becomes difficult due to signal masking by natural variations
Solution Approach 1:
The system maintains high productivity through continuous CO2 removal while improving detectability by implementing periodic release patterns at specific frequencies. The periodic action creates distinct temporal signatures in the ocean chemistry data that can be easily detected and measured, solving the masking problem while preserving overall removal effectiveness.
Solution Approach 2:
The patent introduces dynamics by varying the release timing and frequency of base substances rather than using a static continuous release. This dynamic approach allows the system to adapt the release pattern to maximize both productivity and detectability, creating time-varying signals that stand out against natural background variations.
3Reliability
If frequency-based detection method is used to improve measurement reliability, then signal-to-noise ratio is increased, but device complexity increases due to frequency analysis requirements
Solution Approach 1:
The patent introduces an intermediary layer of frequency analysis between the raw sensor data and the final measurement result. This intermediary processing step transforms the complex signal containing natural variations into a clear frequency-based signature that indicates human-induced changes, thereby improving reliability while managing complexity through systematic signal processing.
Data Source
AI summary
MRV for an ocean CDR system is achieved by varying the release/delivery of base substance into ocean seawater such that the base substance propagates as a series of release batch wavefronts along a dispersion path. A release frequency, which controls a timing of the release batch wavefronts, is selected to coincide with a non-natural frequency (e.g., a frequency exhibiting quiet/weak power spectra in a natural seawater chemistry variation power spectrum). Time-based seawater carbonate chemistry measurement data, which is collected by ocean-based sensors disposed in the base substance's dispersion path during base substance release, records both human-induced contributions caused by the release batch wavefronts and natural seawater chemistry variations. The time-based sensor data is processed using frequency-domain techniques to generate a power spectrum in which human-induced contributions at the non-natural frequency can be distinguished from natural variation contributions, thereby facilitating verification of the system's contribution to atmospheric CO2 reduction.