Pith. sign in

REVIEW

Targeted Source Detection for Environmental Data

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1908.11056 v1 pith:RCFYQUEK submitted 2019-08-29 eess.SP cs.LGstat.APstat.ML

classification eess.SPcs.LGstat.APstat.ML
keywords wateractivitiescontaminantscontaminationdetectionenergyenvironmentalhuman
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original 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.

Discussion (0). Continue with ORCID to comment.

Pith tools