Browsing by Author "Xu, Yuan-Yuan"
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Item Carbonate chemistry dynamics along the U.S. eastern continental shelf(University of Delaware, 2019) Xu, Yuan-YuanThe uptake of carbon dioxide (CO2) from the atmosphere by seawater has caused ocean acidification globally. In addition to anthropogenic CO2 uptake, the coastal ocean experiences enhanced acidification due to freshwater discharge, eutrophication, upwelling, etc. This coastal acidification affects the health of calcifying species and has a harmful impact on commercial fisheries and the marine ecosystem. It is critical to monitor coastal acidification and determine the spatial and temporal trends of related parameters. This dissertation focuses on the carbonate/bicarbonate buffering system, which is a chemical buffer system that regulates seawater pH. I analyze the carbonate chemistry dynamics and buffer capacities for the east coast using four shipboard datasets, satellite remote sensing data, and model outputs. Results suggest that total dissolved inorganic carbon and the aragonite saturation state along the U.S. eastern continental shelf have patterns that agree with predictions based on carbon dioxide equilibrium with the atmosphere. This indicates a solubility control mechanism that leads to low carbonate ion concentrations and aragonite saturation state in cold northern waters and the opposite in warm southern waters. In terms of short-term variability of aragonite state in the central Mid-Atlantic Bight, quantitative analyses show that physical advection and mixing processes are the dominant forces for a higher aragonite saturation state in slope waters while biological carbon removal and carbon dioxide degassing contribute to higher aragonite state in shelf waters. On decadal and longer time scales, dissolved inorganic carbon has increased while aragonite saturation state and pH have decreased along the U.S. eastern continental shelf. However, dissolved inorganic carbon increase and aragonite saturation state decrease were dampened in the Mid-Atlantic Bight because of seawater temperature increase. The analyses of carbonate chemistry parameters in various spatial and temporal scales help us to better understand the processes that can alter carbonate chemistry in coastal waters. In addition, with specific regional-scale ocean models, the community can extend our ability of quantitative understanding carbonate chemistry dynamics and take necessary efforts to prevent the occurrence of low pH or undersaturation conditions in the future.Item Carbonate Parameter Estimation and Its Application in Revealing Temporal and Spatial Variation in the South and Mid-Atlantic Bight, USA(Journal of Geophysical Research: Oceans, 2022-06-22) Li, Xinyu; Xu, Yuan-Yuan; Kirchman, David L.; Cai, Wei-JunTo overcome the limitations due to sporadic carbonate parameter data, this study developed and evaluated empirical multiple linear regression (MLR) models for dissolved inorganic carbon (DIC), pH in total scale (pHT), and aragonite carbonate saturation state (ΩAr) using hydrographic data (temperature, salinity, and oxygen) measured during 2007–2018 in the South Atlantic Bight (SAB) and Mid-Atlantic Bight (MAB) along the U.S. East Coast. We first reviewed the assumptions and routines of MLR models and then generated MLR models for each cruise for all three carbonate parameters in each region and assessed model performance. Models derived from measured spectrophotometric pH have smaller uncertainties than pHT models based on pH calculated from total alkalinity (TA) and DIC. The regional differences of carbonate parameters between MAB and SAB are reflected in the coefficients of the empirical models. The MLR model temporal consistency indicates that the effect of the atmospheric CO2 increase on seawater carbonate parameters cannot be unequivocally resolved for the period of this study in the regions. Therefore, we combined different cruises to build composite models for each region. The composite models can capture the key features in the SAB and MAB. To further assess the model applicability, we applied our models to Biogeochemical-Argo data to reconstruct carbonate parameters. The algorithm in this study helps to reconstruct seawater carbonate chemistry using proxy data of high spatial and temporal resolution, which will enhance our understanding of physical and biological processes on carbon cycle and the long-term anthropogenic carbon inputs in coastal oceans. Key Points: - pH estimation models based on measured pH have smaller uncertainties than those based on pH calculated from other carbonate parameters - Models differ between the Mid and South Atlantic Bights, and their temporal changes due to atmospheric CO2 are limited over 10 years - Multiple linear regression models provide a promising tool for reconstructing carbonate parameters using data from autonomous platforms Plain Language Summary: Coastal ocean carbon cycling is a complex process that is influenced by various physical and biological processes. Sporadic carbonate data challenges our understanding of carbon cycling in coastal areas. We first reviewed the assumptions and routines in developing coastal empirical models, and then built linear regression models with frequently measured seawater properties, such as temperature, salinity, and O2, to estimate the carbonate variables along the U.S. East Coast. The key features of seawater carbonate parameters are captured by the empirical models. The sub-regional differences are reflected in the coefficients of the empirical models. We also found that the effect of anthropogenic carbon dioxide increase on the DIC is limited over 10 years. This study helps to reconstruct seawater carbonate chemistry where data are limited, predict future changes in coastal carbonate chemistry, and enhance our understanding of long-term anthropogenic carbon inputs in the coastal ocean.