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Wang, M.; Kinyua, J.; Jiang, T.; Sedlak, M.; McKee, L. J. .; Fadness, R.; Sutton, R.; Park, J. - S. 2022. Suspect Screening and Chemical Profile Analysis of Storm-Water Runoff Following 2017 Wildfires in Northern California. Environmental Toxicology and Chemistry . SFEI Contribution No. 1089.

The combustion of structures and household materials as well as firefighting during wildfires lead to releases of potentially hazardous chemicals directly into the landscape. Subsequent storm-water runoff events can transport wildfire-related contaminants to downstream receiving waters, where they may pose water quality concerns. To evaluate the environmental hazards of northern California fires on the types of contaminants in storm water discharging to San Francisco Bay and the coastal marine environment, we analyzed storm water collected after the northern California wildfires (October 2017) using a nontargeted analytical (NTA) approach. Liquid chromatography quadrupole time-of-flight mass spectrometric analysis was completed on storm-water samples (n = 20) collected from Napa County (impacted by the Atlas and Nuns fires), the city of Santa Rosa, and Sonoma County (Nuns and Tubbs fires) during storm events that occurred in November 2017 and January 2018. The NTA approach enabled us to establish profiles of contaminants based on peak intensities and chemical categories found in the storm-water samples and to prioritize significant chemicals within these profiles possibly attributed to the wildfire. The results demonstrated the presence of a wide range of contaminants in the storm water, including surfactants, per- and polyfluoroalkyl substances, and chemicals from consumer and personal care products. Homologs of polyethylene glycol were found to be the major contributor to the contaminants, followed by other widely used surfactants. Nonylphenol ethoxylates, typically used as surfactants, were detected and were much higher in samples collected after Storm Event 1 relative to Storm Event 2. The present study provides a comprehensive approach for examining wildfire-impacted storm-water contamination of related contaminants, of which we found many with potential ecological risk. Environ Toxicol Chem 2022;00:1–14. © 2022 SETAC

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Oram, J. J.; McKee, L. J. .; Davis, J. A.; Sedlak, M.; Yee, D. 2008. Sources, Pathways and Loadings Workgroup: Five-Year Workplan (2008-12). SFEI Contribution No. 567. San Francisco Estuary Institute: Oakland.
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McKee, L. J. . 2005. Sources, Pathways, and Loadings: 5-Year Work Plan (2005-2009). SFEI Contribution No. 406. San Francisco Estuary Institute. p 25.
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Barnard, P. L.; Schoellhamer, D. H.; Jaffe, B. E.; McKee, L. J. . 2013. Sediment transport in the San Francisco Bay Coastal System: An overview. Marine Geology Special Issue: A multi-discipline approach for understanding sediment transport and geomorphic evolution in an estuarine-coastal system.
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Bigelow, P.; Pearce, S.; McKee, L. J. .; Gilbreath, A. N. 2008. A Sediment Budget for Two Reaches of Alameda Creek. SFEI Contribution No. 550. San Francisco Estuary Institute.
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McKee, L. J. .; Feng, A.; Sommers, C.; Looker, R. 2009. RMP Small Tributaries Loading Strategy. San Francisco Estuary Institute: Richmond, CA.
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McKee, L. J. . 2008. Review of sediment gauging studies in Alameda Creek Watershed. SFEI Contribution No. 571. San Francisco Estuary Institute.
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McKee, L. J. .; GeoSyntec,. 2006. Review of methods to reduce urban stormwater loads. SFEI Contribution No. 429. San Francisco Estuary Institute: Oakland. p 150xx.
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Wu, J.; Gilbreath, A.; McKee, L. J. 2017. Regional Watershed Spreadsheet Model (RWSM): Year 6 Progress Report. SFEI Contribution No. 811. San Francisco Estuary Institute: Richmond, CA.
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Trowbridge, P. R.; Davis, J. A.; Mumley, T.; Taberski, K.; Feger, N.; Valiela, L.; Ervin, J.; Arsem, N.; Olivieri, A.; Carroll, P.; et al. 2016. The Regional Monitoring Program for Water Quality in San Francisco Bay, California, USA: Science in support of managing water quality. Regional Studies in Marine Science 4.

The Regional Monitoring Program for Water Quality in San Francisco Bay (RMP) is a novel partnership between regulatory agencies and the regulated community to provide the scientific foundation to manage water quality in the largest Pacific estuary in the Americas. The RMP monitors water quality, sediment quality and bioaccumulation of priority pollutants in fish, bivalves and birds. To improve monitoring measurements or the interpretation of data, the RMP also regularly funds special studies. The success of the RMP stems from collaborative governance, clear objectives, and long-term institutional and monetary commitments. Over the past 22 years, high quality data and special studies from the RMP have guided dozens of important decisions about Bay water quality management. Moreover, the governing structure and the collaborative nature of the RMP have created an environment that allowed it to stay relevant as new issues emerged. With diverse participation, a foundation in scientific principles and a continual commitment to adaptation, the RMP is a model water quality monitoring program. This paper describes the characteristics of the RMP that have allowed it to grow and adapt over two decades and some of the ways in which it has influenced water quality management decisions for this important ecosystem.

Yee, D.; McKee, L. J. .; Oram, J. J. 2010. A Regional Mass Balance of Methylmercury in San Francisco Bay, California, USA. Environmental Toxicology and Chemistry . SFEI Contribution No. 619.
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Oram, J. J.; McKee, L. J. .; Davis, J. A.; Hetzel, F. 2007. Polychlorinated biphenyls (PCBs) in San Francisco Bay. Environmental Research 105, 67-86 . SFEI Contribution No. 526.
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McKee, L. J. .; Pearce, S.; Shonkoff, S. 2006. Pinole Creek Sediment Source Assessment: Pavon Creeks Sub-basin. SFEI Contribution No. 515. San Francisco Estuary Institute. p 67.
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Wu, J.; Kauhanen, P.; Hunt, J. A.; Senn, D.; Hale, T.; McKee, L. J. . 2019. Optimal Selection and Placement of Green Infrastructure in Urban Watersheds for PCB Control. Journal of Sustainable Water in the Built Environment 5 (2) . SFEI Contribution No. 729.

San Francisco Bay and its watersheds are polluted by legacy polychlorinated biphenyls (PCBs), resulting in the establishment of a total maximum daily load (TDML) that requires a 90% PCB load reduction from municipal stormwater. Green infrastructure (GI) is a multibenefit solution for stormwater management, potentially addressing the TMDL objectives, but planning and implementing GI cost-effectively to achieve management goals remains a challenge and requires an integrated watershed approach. This study used the nondominated sorting genetic algorithm (NSGA-II) coupled with the Stormwater Management Model (SWMM) to find near-optimal combinations of GIs that maximize PCB load reduction and minimize total relative cost at a watershed scale. The selection and placement of three locally favored GI types (bioretention, infiltration trench, and permeable pavement) were analyzed based on their cost and effectiveness. The results show that between optimal solutions and nonoptimal solutions, the effectiveness in load reduction could vary as much as 30% and the difference in total relative cost could be well over $100 million. Sensitivity analysis of both GI costs and sizing criteria suggest that the assumptions made regarding these parameters greatly influenced the optimal solutions. 

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DOI: 10.1061/JSWBAY.0000876

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