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 (CO2) emissions. In this study, we computed the partial pressure of CO2 (pCO2) using the carbonate equilibria-based model (pCO2SYS) 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 pCO2 across the Ganga River. The pCO2 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 pCO2 and FCO2 levels (fugacity of CO2: 3.63 gm2d-1) compared to the middle and lower stretch, underscoring the intricate interplay between hydrochemistry and CO2 dynamics. In the context of pCO2 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 pCO2 variations across the Ganga River (n = 91). A robust negative correlation between BOD and FCO2 was also observed. The distinct longitudinal patterns of both parameters may induce a negative correlation between BOD and pCO2. Therefore, comprehensive studies are necessitated to decipher the underlying mechanisms governing this relationship. The present insights are instrumental in comprehending the potential of CO2 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.

Sewage treatment plants (STPs) are considered as a prominent source for releasing microplastics (MPs) into the riverine systems. Though MPs abundance and removal efficacy in different secondary treatment technique-based STPs have been extensively studied worldwide, such studies are scarce in Indian conditions. Herein, this study comprehensively assesses MPs abundance, characterization, and their removal in the selected secondary treatment technique-based STPs discharging into the middle stretch of the Ganga River in India. MPs concentration (n/L) in influent and effluent of the STPs varied between 42 ± 10 to 150 ± 19 and 3 ± 1 to 22 ± 5, respectively. Overall, the primary treatment stage was observed to remove MPs by 23-42 %, while the secondary treatment stage removed MPs by 67-90 %. Selected technique-based STPs exhibited varying MPs removal efficacies as follows: SBR (94 %), TF (90 %), AL (88 %), UASB (87 %), ASP (85 %), FAB (84 %), and Bio-tower (77 %). MPs ranging from 50 to 250 μm were the dominant sizes, with PP, PE, and PS being the prevalent polymers. The Ganga River receives about 3 × 108 MPs/day from STP effluents, and an estimated 4.5 × 107 MPs/day are released via the sludge. This comprehensive assessment of MPs abundance and removal from different technology-based Indian STPs will allow the comparison of the generated dataset with similar studies worldwide.

A comparative analysis between water and sediment can provide better information to understand the dynamics of the inhabitant microbiome and their respective antibiotic resistance genes of a river. Therefore, the present investigation was carried to explore the limited information available on bacterial microbiome and their predictive antibiotic resistance genes (ARGs) from water and sediment of the Ganga River. The study utilized the NGS-based sequences previously submitted under the accession number (PRJNA847424 and PRJNA892876). Overall analysis revealed that twenty phyla and fifty-four genera were shared between the water and sediment of the Ganga River. Of them, nine phyla and nineteen genera were observed as significantly different (p-value < 0.05). Where the majority of the genera were associated with the sediment samples over the water that identify the sediment samples as more diverse for species richness. Similarly, seventy-six ARGs were shared between water and sediment samples. Of the ten abundant antibiotic resistance pathways, seven were relatively abundant in sediment samples as compared to the water. Vancomycin resistance genes were significantly more abundant among sediment samples, whereas β-lactam resistance genes were equally distributed in water and sediment samples. The network analysis further revealed that five genera (Flavobacterium, Pseudomonas, Acinetobacter, Candidatus_divison CL5003, and Candidatus_division SWB02) showed a significantly positive correlation with six antibiotic resistance pathways (β-lactam, vancomycin, multidrug resistance, tetracycline, aminoglycoside, and macrolide resistance pathways). The study comes out with several findings where sediment may be considered as a more atrocious habitat for evolving the resistance mechanisms against threatful antibiotics over the water samples of the Ganga River.

The present investigation assesses the bacterial microbiome and antibiotic resistance genes (ARGs) of the river Ganga from Uttarakhand (upstream region; US group) and Uttar Pradesh (downstream region; DS group) regions using a 16S rRNA amplicon-based metagenomic approach. Gram-negative, aerobic, and chemo-organotrophic bacteria made up the majority of the bacterial genera during the overall analysis. Physicochemical analysis revealed a higher concentration of nitrate and phosphate in the downstream sites of the Ganga River. The prevalence of Gemmatimonas, Flavobacterium, Arenimonas, and Verrucomicrobia in the water of the DS region indicates a high organic load. Pseudomonas and Flavobacterium emerged as the most prevalent genera among the 35 significantly different shared genera (p-value < 0.05) in the US and DS regions, respectively. Overall antibiotic resistance analysis of the samples showed the dominance of β-lactam resistance (33.92%) followed by CAMP (cationic antimicrobial peptide) resistance (27.75%), and multidrug resistance (19.17%), vancomycin resistance (17.84%), and tetracycline resistance (0.77%). While comparing, the DS group exhibited a higher abundance of ARGs over the US group, where the CAMP resistance and β-lactam ARGs were dominant in the respective regions. The correlation (p-value < 0.05) analysis showed that most bacteria exhibit a significant correlation with tetracycline resistance followed by the phenicol antibiotic. The present findings draw attention to the need for regulated disposal of multiform human-derived wastes into the Ganga River to reduce the irrepressible ARGs dissemination.