Anthropogenic influences significantly modify the hydrochemical properties and material flow in riverine ecosystems across Asia, potentially accounting for 40-50% of global emissions. Despite the pervasive impact on Asian rivers, there is a paucity of studies investigating their correlation with carbon dioxide (CO) emissions. In this study, we computed the partial pressure of CO (pCO) using the carbonate equilibria-based model (pCOSYS) and examined its correlation with hydrochemical parameters from historical records at 91 stations spanning 2013-2021 in the Ganga River. The investigation unveiled substantial spatial heterogeneity in the pCO across the Ganga River. The pCO concentration varied from 1321.76 μatm, 1130.98 μatm, and 1174.33 μatm in the upper, middle, and lower stretch, respectively, with a mean of 1185.29 μatm. Interestingly, the upper stretch exhibited elevated mean pCO and FCO levels (fugacity of CO: 3.63 gmd) compared to the middle and lower stretch, underscoring the intricate interplay between hydrochemistry and CO dynamics. In the context of pCO fluctuations, nitrate concentrations in the upper segment and levels of biological oxygen demand (BOD) and dissolved oxygen (DO) in the middle and lower segments are emerging as crucial explanatory factors. Furthermore, regression tree (RT) and importance analyses pinpointed biochemical oxygen demand (BOD) as the paramount factor influencing pCO variations across the Ganga River (n = 91). A robust negative correlation between BOD and FCO was also observed. The distinct longitudinal patterns of both parameters may induce a negative correlation between BOD and pCO. Therefore, comprehensive studies are necessitated to decipher the underlying mechanisms governing this relationship. The present insights are instrumental in comprehending the potential of CO emissions in the Ganga River and facilitating riverine restoration and management. Our findings underscore the significance of incorporating South Asian rivers in the evaluation of the global carbon budget.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.envres.2024.118902 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!