Heavy Metals, Chemical Pollution, and Hidden Clues: Decoding Lake Maurepas

重金属、化学污染和隐藏的线索:解读莫雷帕斯湖

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Abstract

This study provides the first comprehensive assessment of toxic chemicals and heavy metals (HMs) in Lake Maurepas, introducing an innovative approach that integrates the Bayesian spatiotemporal multivariate receptor model (BSMRM) with event response and causality analysis (ERCA). This framework quantitatively evaluates pollutant sources and drivers while identifying high-risk zones across water sampling sites. Using ERCA, we investigated the influence of environmental and anthropogenic factors on the spatiotemporal distribution of sources in the water column. Temporal clustering revealed four distinct source behaviors aligning with anomaly detection, linked to events near river mouths and Pass Manchac. Among the sources, transportation-recreational-accidental release (TRAR) was the most sensitive and death and decay of biological species (DDBS) appears to be the most tolerable source. Sensitivity analysis of ERCA showed that salinity, atmospheric pressure, and wind speed play a dominant role in shaping pollutant variability. Conversely, seismic-drilling predominantly caused negative sensitivities by altering hydrodynamics to reduce transport, but also had a slight positive effect on geological contaminant mobilization. ERCA's causality analysis identified local waterways and Pass Manchac as key pollutant origins, with hydrodynamic circulation and site interactions shaping the broader distributions. These findings offer insights into pollutant resilience and thresholds, providing a framework for targeted mitigation strategies in lakes and similar ecosystems.

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