Assessment of microplastic pollutants in riverine sediments and their correlation with industrial activity in Southeast Asia

Thesis Abstract

This study addresses the growing concern of microplastic pollution in riverine systems and its linkage to industrial activity in Southeast Asia, a region characterized by rapid urbanization, expanding manufacturing sectors, and variable regulatory enforcement. The problem centers on limited comparative data across transboundary river basins, inconsistencies in microplastic typology and quantification, and the need to elucidate the spatial relationship between industrial emissions and sediment-bound microplastics to inform mitigation strategies. The aim is to quantify microplastic abundance, characterize polymer composition and morphology in riverine sediments, and assess their correlations with industrial activity indicators across representative Southeast Asian basins. Specific objectives include (1) determining microplastic concentration, size distribution, and polymer types in sediment samples from five river systems (Chao Phraya, Mekong, Irrawaddy, Red River, and Kaladan) and their floodplains; (2) evaluating seasonal and hydrological influences on microplastic transport using paired sampling during dry and wet seasons; (3) linking microplastic metrics to industrial activity proxies such as manufacturing density, plastic-related waste streams, and wastewater treatment efficiency; (4) identifying predominant polymer classes and potential bioavailable fractions through spectroscopic and microscopic analyses; and (5) formulating evidence-based recommendations for policymakers and industrial stakeholders. The methodology adopts an explanatory sequential mixed-methods design. The population comprises riverine sediments within 50–100 km of major industrial corridors across the five basins. A stratified random sampling approach yields 200 sediment cores (40 per basin) collected from standardized depths (0–5 cm and 5–20 cm) to capture recent deposition. Data collection employs(a) lab-based microplastic extraction via density separation with zinc chloride solution and filtration, (b) polymer identification and morphometrics using Fourier-transform infrared spectroscopy (FTIR) and micro-Raman spectroscopy, (c) scanning electron microscopy (SEM) for surface characterization, and (d) contamination control through procedural blanks and field rinsing protocols. Industrial activity proxies are compiled from satellite-derived night-time lights data, local manufacturing census, and municipal wastewater treatment plant (WWTP) performance records, supplemented by field surveys of waste handling practices. For data analysis, descriptive statistics summarize microplastic abundance (items per kilogram of dry sediment), size distribution, and polymer classes. Inferential statistics employ multivariate linear regression to test associations between microplastic concentration and industrial proxies, with variance inflation factor checks for collinearity. ANOVA assesses temporal (seasonal) differences, while redundancy analysis (RDA) explores relationships between polymer composition and industrial activity gradients. A generalized additive model (GAM) examines non-linear responses to hydrological variables (discharge, sediment grain size) and sampling position. Quality assurance includes method blanks, recovery tests with spiked sediments, and inter-laboratory calibration for FTIR spectra. Anticipated findings indicate higher microplastic loads in basins with dense manufacturing, greater prevalence of polyethylene terephthalate (PET) and polypropylene (PP) fibers, and a notable seasonal amplification during the monsoon phase due to enhanced runoff and sediment resuspension. The study expects to reveal significant positive correlations between microplastic concentration and indicators of industrial activity, particularly in river downstream of dense industrial estates, with finer sediments hosting greater microplastic retention. The contribution to knowledge lies in (i) providing a harmonized, cross-basin dataset of sediment-associated microplastics for Southeast Asia, (ii) validating a robust linkage between industrial activity indicators and microplastic pollution in riverine sediments, and (iii) offering a framework integrating hydrological, spatial, and industrial metrics for targeted policy interventions. The main conclusion posits that industrial activity substantially drives microplastic contamination in Southeast Asian rivers, mediated by hydrological regime and sediment characteristics. Recommendations include strengthening source control at industrial facilities, improving WWTP effluent management for microplastic removal, implementing riverine sediment management practices in high-risk zones, and developing regional monitoring protocols combining FTIR/MIR microplastic fingerprinting with industrial activity indices. Further research should explore ecological impacts on benthic communities and transport dynamics under climate-change scenarios.