Targeted Source Detection for Environmental Data

TL;DR

This paper introduces a new technique for identifying and predicting environmental contaminant sources, specifically applied to groundwater contamination in shale gas regions, improving upon existing methods.

Contribution

A novel method for simultaneous source detection and prediction in environmental data, demonstrated through a case study on groundwater contamination from shale gas development.

Findings

Outperforms existing approaches in source identification accuracy

Effective in complex natural and human systems

Applicable to various contaminants and environmental scenarios

Abstract

In the face of growing needs for water and energy, a fundamental understanding of the environmental impacts of human activities becomes critical for managing water and energy resources, remedying water pollution, and making regulatory policy wisely. Among activities that impact the environment, oil and gas production, wastewater transport, and urbanization are included. In addition to the occurrence of anthropogenic contamination, the presence of some contaminants (e.g., methane, salt, and sulfate) of natural origin is not uncommon. Therefore, scientists sometimes find it difficult to identify the sources of contaminants in the coupled natural and human systems. In this paper, we propose a technique to simultaneously conduct source detection and prediction, which outperforms other approaches in the interdisciplinary case study of the identification of potential groundwater contamination within a region of high-density shale gas development.