Biogeochemistry of the dissolved organic matter (DOM) in the estuarine rivers of Bangladesh-Sundarbans under different anthropogenic influences

The deciphering of microplastics-derived fluorescent dissolved organic matter in urban lakes, canals, and rivers using parallel factor analysis modeling and mimic experiment

The aim of the study is to investigate the leaching of fluorescent dissolved organic matter (fDOM) from microplastics. In addition, this study identifies the connection between fDOM and microplastics in the aquatic environment. Three-dimensional excitation-emission matrix identified five fluorophores, that is, peak A, M, T, Tuv, and Wuv, and the parallel factor analysis modeling identified five components, that is, tryptophan-like, p-hydroxy acetophenone, humic acid (C-like), detergent-like, and fulvic acid (M-like) in the urban surface water. Mimic experiments using commonly used synthetic plastic (like microplastics) in Mili-Q water under solar radiation and dark environments demonstrate the release of fDOM from plastic. Two fluorophore peaks were observed at Ex/Em = 250/302 nm and Ex/Em = 260/333 nm for the expanded polystyrene plastic polymer and one fluorophore peak at Ex/Em = 260/333 nm for the low-density polyethylene. Fluorophore and component intensity exhibited notable associations with microplastics in the aquatic environment. These findings indicated that the characteristics and dynamics of fDOM in urban surface water are influenced by microplastics. PRACTITIONER POINTS: Fluorescent dissolved organic matters were identified in urban surface waters. Expanded polystyrene (EPS) had shown two fluorophores at Em/Ex = 250/302 and Em/Ex = 260/333. Low-density polyethylene (LDPE) had one fluorophore at Em/Ex = 260/333. Fluorophore and component intensity in the aquatic settings exhibited associations with microplastics.

Using unsupervised machine learning models to drive groundwater chemistry and associated health risks in Indo-Bangla Sundarban region

Groundwater is an essential resource in the Sundarban regions of India and Bangladesh, but its quality is deteriorating due to anthropogenic impacts. However, the integrated factors affecting groundwater chemistry, source distribution, and health risk are poorly understood along the Indo-Bangla coastal border. The goal of this study is to assess groundwater chemistry, associated driving factors, source contributions, and potential non-carcinogenic health risks (PN-CHR) using unsupervised machine learning models such as a self-organizing map (SOM), positive matrix factorization (PMF), ion ratios, and Monte Carlo simulation. For the Sundarban part of Bangladesh, the SOM clustering approach yielded six clusters, while it yielded five for the Indian Sundarbans. The SOM results showed high correlations among Ca2+, Mg2+, and K+, indicating a common origin. In the Bangladesh Sundarbans, mixed water predominated in all clusters except for cluster 3, whereas in the Indian Sundarbans, Cl--Na+ and mixed water dominated in clusters 1 and 2, and both water types dominated the remaining clusters. Coupling of SOM, PMF, and ionic ratios identified rock weathering as a driving factor for groundwater chemistry. Clusters 1 and 3 were found to be influenced by mineral dissolution and geogenic inputs (overall contribution of 47.7%), while agricultural and industrial effluents dominated clusters 4 and 5 (contribution of 52.7%) in the Bangladesh Sundarbans. Industrial effluents and agricultural activities were associated with clusters 3, 4, and 5 (contributions of 29.5% and 25.4%, respectively) and geogenic sources (contributions of 23 and 22.1% in clusters 1 and 2) in Indian Sundarbans. The probabilistic health risk assessment showed that NO3- poses a higher PN-CHR risk to human health than F- and As, and that potential risk to children is more evident in the Bangladesh Sundarban area than in the Indian Sundarbans. Local authorities must take urgent action to control NO3- emissions in the Indo-Bangla Sundarbans region.

Distribution, characteristics and fate of fluorescent dissolved organic matter (FDOM) in the Bay of Bengal

The Bay of Bengal (BoB) is the largest sink to retain discharges from major rivers and the Sundarbans Mangrove Forest in Bangladesh and upholds significant ecological and resource diversity. This study aims to characterize, and identify sources, spatial dynamics, and the fate of the principal ecological web driver that is fluorescent dissolved organic matter (FDOM) in the BoB using advanced techniques of excitation-emission matrix (EEM) fluorescence spectroscopy and multivariate parallel factor (PARAFAC) analyses. The identified four protein-, two humic- and one detergent-like FDOM components mostly showed higher abundance in the shallow water than deep unlike a protein-like component. Such exceptional protein-like component was identified to form colloidal structure under elevated salinity in deep water. Autochthonous humic-like FDOM originated from primary production and water temperature counteracted microbial polymerization in shallow and deep water, respectively. The annual mass deposition indicated the influx of anthropogenic pollutants from both terrestrial and internal marine systems.