Quaternary Science Advances (Jul 2023)

Spatial and temporal variability of the sources and sinks of carbonate system in the southwest bay of Bengal from 2014 to 2020

  • Muthumanickam Naveen,
  • Kandasamy Priyanka,
  • Ramalingam Shanthi,
  • Udayakumar Utthamapandiyan,
  • Ayyappan Saravanakumar,
  • Rajdeep Roy,
  • P.V. Nagamani

Journal volume & issue
Vol. 11
p. 100080

Abstract

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This study presents a synthesis of surface water partial pressure of CO2 (pCO2) and nutrient measurement in the southwest Bay of Bengal (swBoB) from 2014 to 2020 and characterizes the spatial and temporal variability. pCO2 rates found to be high (1191 μatm) during the 2015 monsoon and low (176 μatm) in the summer season during the month of May 2015. The inter-annual CO2 fluxes varied from −4.79 to 9.97 mmol Cm−2d−1. The significant a negative CO2 flux (−4.79 mmol Cm−2d−1) was recorded during the summer season in the year 2019, whereas a positive significant CO2 flux (9.97 mmol Cm−2d−1) was observed during the monsoon in 2014. Major physical parameters are at their highest during summer owing to increased high solar radiation during cloud-free circumstances, reduced or inadequate riverine flux, and a lack of vertical mixing of the water column, which results in the lowest nutrients concentration, Dissolved Oxygen (DO), Dissolved Inorganic Nitrogen (DIN), Dissolved Organic Carbon (DOC), chlorophyll-a, Particulate Organic Carbon (POC), pCO2, that leads to negative CO2 flux to the atmosphere. In contrast during monsoon season colossal discharge of freshwater high DO, DIN, DOC, chlorophyll-a, POC, pCO2 as results source CO2 flux to the atmosphere. Statistical analysis the correlation coefficient depicts Total Alkalinity (TA), DIC, POC, DIN, and DO found a positive correlation with pCO2 and fCO2 during the monsoon season. In the swBoB, pCO2 had a negative relationship with sea surface temperature (SST), sea surface salinity (SSS), and pH because CO2 solubility changes with SST and increases in cold water rather than warm water. In this study, we examine the association between all carbonate variables and the SSS and SST to better understand seasonal fluctuations.

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