Carbonate system dynamics are highly variable in coastal and shelf regions, and poor spatiotemporal measurement resolution leads to inadequate constraints for global carbon sequestration estimates. Additionally, conventional pCO2 measurement-based flux calculations require an assumption of homogeneity in near-surface waters and an isometric temperature correction that excludes effects such as biological drivers and air-sea disequilibrium. To quantify the effect of these drivers, by capturing high resolution measurements during short-term events, we present the deployment of a Liquid Robotics Wave Glider equipped with mirrored gas sensor suites at surface and subsurface during the 2022 spring bloom on the Scotian Shelf in eastern Canada. The temporal variability in the data reveals biologically driven diurnal pCO2 behavior that conventional, low-resolution methods may overlook. Additionally, through direct measurement of surface and sub-surface pCO2 levels we demonstrate that conventional underway measurement methods systematically underestimate surface pCO2 values in this region by 1 – 10 µatm, leading to flux estimation errors of up to 7%. These findings emphasize the value of high-resolution data for determining drivers of spatial variability and question the capacity of underway lines to measure true surface pCO2 values. By employing vehicle-based measurement techniques we can improve our understanding of carbon dynamics in coastal environments and refine flux estimates for accurate climate modeling and management strategies.

Ocean alkalinity enhancement (OAE) can potentially remove gigatons of CO2 from the atmosphere for durable storage in the ocean. Before implementing OAE at climate-relevant scales, questions about its safety and verifiability must be addressed. Operational deployment poses a dilemma between pursuing large detectability, essential for effective monitoring, reporting, and verification (MRV), and ensuring environmental safety and satisfying regulatory requirements. In this study, we present a computationally efficient approach, based on a high-resolution, coupled circulation-dissolution model of Halifax Harbour, to simulating the addition, transportation, dissolution, and sinking of various theoretical alkaline feedstocks for different dosages, seasons, and addition sites. Detectability and exposure risk of OAE are quantified and an approach for optimizing OAE deployment is demonstrated. Mean residence times (MRT) are calculated for different subregions and seasons. Results show that for a given amount of feedstock, summer is more favourable from the perspective of detectability but also creates higher exposure risks than other seasons because of a longer MRT. The exposure risk can be mitigated while maintaining large detectability by choosing optimal feedstocks with different characteristics for different seasons. The exposure risk can also be reduced by spreading alkalinity over multiple addition sites. The optimum allocation, where the largest detectability is sought without violating regulatory requirements, is specific to each season, dosage, and choice of feedstock. OAE deployments should be tailored taking into account local hydrography, season, dosage, and feedstock characteristics. Our approach provides a practical avenue for optimizing deployments.