Total alkalinity minus dissolved inorganic carbon as a proxy for deciphering ocean acidification mechanisms

Ocean acidification (OA) defined as the decline of ocean pH and calcium carbonate saturation state (Omega) as a result of ocean uptake of CO2 from the atmosphere may have considerable negative impacts on global marine organisms and may substantially modify ocean biogeochemistry. However, as changes of pH and Omega are not conservative or linear with respect to ocean physical processes (e.g., mixing, temperature and pressure changes), the influences of anthropogenic CO2 uptake and ocean biogeochemical processes on OA rates cannot be easily identified. Here, we examine whether a composite property [TA-DIG] or the difference between total alkalinity (TA) and dissolved inorganic carbon (DIC), which is conservative to ocean mixing and is not sensitive to temperature and pressure changes, can be used for measuring OA rates and deciphering the underlying OA mechanisms in the global ocean as it in surface waters of several regional oceans. Based on Global Ocean Data Analysis Project Version 2 (GLODAPv2), we demonstrate using this property for measuring OA rates can be applied on a global ocean scale, except at low salinity e.g., < 20 and when [TA-DIG] is < -50 mu mol kg(-1), where the relationships of [TA-DIG] with pH and/or Omega are nonlinear. However, there are almost no limitations when using this property for deciphering the underlying OA mechanisms since the change of [TA-DIG] with time is relatively small on OA timescales of decades or more. Using [TA-DIG], we can readily quantify the influences from freshwater inputs and upwelling on OA rates based on a two end-member mixing model. More importantly, through the Redfield ratio and apparent oxygen utilization, we can directly link biological influences to OA rates and conveniently quantify the biological modulation on OA rates. Therefore, we argue that using [TA-DIG] as a proxy for OA would provide a simple but powerful way of deciphering acidification mechanisms and predicting future development of acidification.