Potential Contribution of Carbon Sequestration in the North Eastern Part of the Bay of Bengal Bangladesh

Abstract

This research delves into the critical study of carbon sequestration dynamics in the northeastern Bay of Bengal (BoB) with a focus on understanding the status, trends and influencing factors. A multifaceted approach encompassing both secondary satellite data and primary field observations was employed. Satellite data, sourced from platforms such as MODIS and others, were meticulously processed using ArcGIS modeling approaches tools. Concurrently, field observation data, encompassing parameters like Chlorophyll-a (Chl a)concentration, Carbon Flux (CF), Total Carbon (TC) and Phytoplankton Sinking Rate (PSR) were collected, processed and analyzed to provide comprehensive insights of Carbon sequestration. The study highlight intriguing seasonal and annual variations in key parameters, notably Chl-a, Particulate Organic Carbon (POC) and Particulate Inorganic Carbon (PIC). Seasonal variations demonstrated distinct trends across different seasons, suggesting variations in carbon sequestration activities. Over a 3-years period (2009-10, 2014-15, 2019-20), the average surface POC concentration was 177.64±144.61 mgm-3 and PIC concentration was 0.05±0.13 mgm-3 in the northern Bay of Bengal (BoB). Specifically, increasing trends in winter and monsoon for POC and PIC imply enhanced carbon sequestration activities during these periods. Depth-wise variations further illuminated the influence of CF and total carbon emphasizing their significance in carbon sequestration dynamics. This pioneering study provides invaluable insights into the seasonal and annual trends of Chlorophyll-a, Total Carbon and Phytoplankton Sinking Rate in the Bay of Bengal region, bridging the gap between real-time data and MODIS satellite observations. The research underscores the substantial carbon sequestration potential of the northeastern BoB, particularly during the monsoon season. However, further research is imperative to refine MODIS data accuracy and explore the vertical and spatial profiles of carbon stock.