Ocean acidification in Massachusetts bay and Boston harbor: Insights from a 1-D modeling approach

Massachusetts Bay (MB)/Boston Harbor (BH) in the northeastern United States has reduced buffering capability, making it highly vulnerable to ocean acidification (OA). We applied the U.S. Northeast Biogeochemistry and Ecosystem Model (NeBEM), integrating the unstructured grid, Finite Volume Community Ocean Model with a modified European Regional Seas Ecosystem Model (ERSEM), to investigate seasonal and interannual OA variability through one-dimensional (1-D) experiments. Objectives were to (a) evaluate model skill in reproducing observed seasonal cycles of OA-related variables, particularly pCO2 and pH, in shallow and deep regions, and (b) assess sensitivity to parameterizations and algorithms for calculating dissolved inorganic carbon (DIC), total alkalinity (TA), pCO2, and pH. The 1-D NeBEM reproduced variability of nutrients, dissolved oxygen, chlorophyll-a, pCO2, and pH at the deep outer bay site, where air-sea interactions dominate, but failed at the shallow inner bay site due to the absence of river discharge-driven advection. Of TA algorithms tested, the semi-diagnostic method best captured observed seasonal pCO2 variation, achieving the highest correlation and lowest root mean square error, although all methods performed similarly for pH. Comparisons with multi-linear regression methods showed that empirical models are highly sensitive to calibration set. Mechanistic analysis indicated that TA variability is mainly regulated by nitrification and net community production (NCP), while DIC variability is driven primarily by NCP. Atmospheric CO₂ loading was the first-order contributor to DIC change in magnitude. However, it has decreased in MB over the past two decades, in contrast to regional and global trends. Therefore, it is not a major driver of OA progression in this system.