Quantifying Remediation Effectiveness under Variable External Forcing Using Contaminant Rating Curves

• Published in: Environmental science & technology 2011-09, Vol.45 (18), p.7874-7881
• Main Authors: Kirchner, James W, Austin, Carrie M, Myers, Alexandra, Whyte, Dyan C
• Format: Article
• Language: English
• Subjects: Applied sciences; Bioremediation; California; Comparative analysis; Decontamination. Miscellaneous; Earth sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Environmental cleanup; Environmental Monitoring - methods; Environmental Restoration and Remediation; Exact sciences and technology; Geologic Sediments - analysis; Mercury; Mercury - analysis; Mines; Mining; Nephelometry and Turbidimetry; Pollution; Pollution, environment geology; Rain; Remediation and Control Technologies; Soil and sediments pollution; Water Pollutants, Chemical - analysis; Weather
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/es2014874

Remediation efforts are typically assessed through before-and-after comparisons of contaminant concentrations or loads. These comparisons can be misleading when external drivers, such as weather conditions, differ between the pre- and postremediation monitoring periods. Here, we show that remediation effectiveness may be better assessed by comparing pre- and postremediation contaminant rating curves, which permit “all else equal” comparisons of pre- and postremediation contaminant concentrations and loads under at any specified external forcing. We illustrate this approach with a remediation case study at an abandoned mercury mine in Northern California. Measured mercury loads in the stream draining the mine site were a factor of 1000 smaller after the remediation than before, superficially suggesting that the cleanup was 99.9% effective, but rainstorms were weaker and less frequent during the postremediation monitoring period. Our analysis shows that this difference in weather conditions alone reduced mercury loads at our site by a factor of 73–85, with a further factor of 12.6–14.5 being attributable to the remediation itself, implying that the cleanup was 92–93% (rather than 99.9%) effective. Our results illustrate the need to account for external confounding drivers when assessing remediation efforts, particularly in systems with highly episodic forcing.