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The Yurok Tribe partnered with the University of California Davis (UC Davis) Superfund Research Program to identify and address contaminants in the Klamath watershed that may be impairing human and ecosystem health. We draw on a community-based participatory research approach that begins with community concerns, includes shared duties across the research process, and collaborative interpretation of results. A primary challenge facing University and Tribal researchers on this project is the complexity of the relationship(s) between the identity and concentrations of contaminants and the diversity of illnesses plaguing community members. The framework of bi-directional learning includes Yurok-led river sampling, Yurok traditional ecological knowledge, University lab analysis, and collaborative interpretation of results. Yurok staff and community members share their unique exposure pathways, their knowledge of the landscape, their past scientific studies, and the history of landscape management, and University researchers use both specific and broad scope chemical screening techniques to attempt to identify contaminants and their sources. Both university and tribal knowledge are crucial to understanding the relationship between human and environmental health. This paper examines University and Tribal researchers’ shared learning, progress, and challenges at the end of the second year of a five-year Superfund Research Program (SRP) grant to identify and remediate toxins in the lower Klamath River watershed. Our water quality research is framed within a larger question of how to best build university–Tribal collaboration to address contamination and associated human health impacts.

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Exposure to semivolatile organic compounds (SVOCs) in indoor environments and its potential impact on human health have been receiving increased public attention, because people in developed countries spend over 80% of their time indoors 1 and SVOC levels are several orders of magnitude higher indoors than outdoors. [2][3][4] SVOCs are introduced into indoor residential settings in the form of consumer products, building materials, furnishings, pesticides, and combustion by-products. 5,6 When indoor SVOCs are released from their original sources, they are redistributed over time among the gas phase, airborne particles, settled dust, and other indoor surfaces. 6,7 Consequently, residents can be exposed to indoor SVOCs via inhalation, dermal uptake, and dust ingestion. 8 Of interest, for young children who crawl and play on the floor and have frequent hand-to-mouth activity, dust ingestion has been determined to be a major non-dietary exposure route for several classes of SVOCs including phthalates, 9,10 polybrominated diphenyl ethers (PBDEs), 10,11

Urban wildfires may generate numerous unidentified chemicals of toxicity concern. Ash samples were collected from burned residences and from an undeveloped upwind reference site, following the Tubbs fire in Sonoma County, California. The solvent extracts of ash samples were analyzed using GC– and LC–high-resolution mass spectrometry (HRMS) and using a suite of in vitro bioassays for their bioactivity toward nuclear receptors [aryl hydrocarbon receptor (AhR), estrogen receptor (ER), and androgen receptor (AR)], their influence on the expression of genetic markers of stress and inflammation [interleukin-8 (IL-8) and cyclooxygenase-2 (COX-2)], and xenobiotic metabolism [cytochrome P4501A1 (CYP1A1)]. Genetic markers (CYP1A1, IL-8, and COX-2) and AhR activity were significantly higher with wildfire samples than in solvent controls, whereas AR and ER activities generally were unaffected or reduced. The bioassay responses of samples from residential areas were not significantly different from the samples from the reference site despite differing chemical compositions. Suspect and nontarget screening was conducted to identify the chemicals responsible for elevated bioactivity using the multiple streams of HRMS data and open-source data analysis workflows. For the bioassay endpoint with the largest available database of pure compound results (AhR), nontarget features statistically related to whole sample bioassay response using Spearman’s rank-order correlation coefficients or elastic net regression were significantly more likely (by 10 and 15 times, respectively) to be known AhR agonists than the overall population of compounds tentatively identified by nontarget analysis. The findings suggest that a combination of nontarget analysis, in vitro bioassays, and statistical analysis can identify bioactive compounds in complex mixtures.