Our library features many hundreds of entries.

To search among them, click "Search" below to pull down options, including filtering by document type, author, year, and keyword.
Find these options under "Show only items where." Or you can also sort by author, title, type, and year clicking the headings below.

Export 18 results:
Filters: First Letter Of Title is S and Author is Alicia N. Gilbreath  [Clear All Filters]
Report
 (770.95 KB) (882.14 KB)
 (718.98 KB) (1.02 MB)
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.
 (26.45 MB)
 (61.71 MB)
 (1.48 MB)
 (2.31 MB)
Mckee, L.; Gilbreath, A.; Sabin, L. 2022. Small Tributaries Pollutants of Concern Reconnaissance Monitoring: Application of Storm-event Loads and Yields-Based and Congener-Based PCB Site Prioritization Methodologies. SFEI Contribution No. 1067.

Stormwater agencies in the San Francisco Bay Area are identifying watershed areas that are polluted with PCBs in order to prioritize management efforts to reduce impairment in the Bay caused by PCBs carried in stormwater. Water sampling during storms has been used to characterize PCB concentrations but management prioritization based on the comparison of concentrations between watersheds is made difficult due to variations in flow and sediment erosion between storms and in relation to varying land use. In addition, identifying PCB source areas within priority watersheds has proven complex and costly. To address these challenges, the San Francisco Bay Regional Monitoring Program (RMP) has developed two new interpretive methods based on storm-event PCB yields (PCBs mass per unit area per unit time) and fingerprints of Aroclors (commercial PCB mixtures) that make existing data more useful for decision-making. 

The objectives of this study were to: 

  • Apply the yield method to the regional stormwater dataset and provide new rankings, 
  • Estimate the presence of Aroclors in samples where congener data are available
  • Evaluate data weaknesses and recommend watersheds to resample, and
  • Classify watersheds into high, medium, and low categories for potential management.
 (4.33 MB) (1.24 MB) (989.4 KB) (1.83 MB)
 (3.93 MB)
 (16.66 MB)
 (1.76 MB)
 (29.72 MB)
 (38.4 MB) (22.9 MB)
Gilbreath, A. N.; Stark, K.; Pearce, S.; Mckee, L. 2023. Suspended Sediment Loads Analysis of Four Creeks in the San Francisco Bay Area. SFEI Contribution No. 1134. San Francisco Estuary Institute: Richmond, CA.
 (4.92 MB) (7.33 MB) (5.1 MB) (7.5 MB) (7.67 MB)
Moran, K.; Miller, E.; Mendez, M.; Moore, S.; Gilbreath, A.; Sutton, R.; Lin, D. 2021. A Synthesis of Microplastic Sources and Pathways to Urban Runoff. SFEI Contribution No. 1049. San Francisco Estuary Institute: Richmond, CA.

California Senate Bill 1263 (2018) tasks the Ocean Protection Council (OPC) with leading statewide efforts to address microplastic pollution, and requires the OPC to adopt and implement a Statewide Microplastics Strategy related to microplastic materials that pose an emerging concern for ocean health. Key questions remain about the sources and pathways of microplastics, particularly to urban runoff, to inform an effective statewide microplastics management strategy. The OPC funded this work to inform these microplastics efforts. The purpose of this project was to build conceptual models that synthesize and integrate our current understanding of microplastic sources and pathways to urban runoff in order to provide future research priorities that will inform how best to mitigate microplastic pollution. Specifically, we developed conceptual models for cigarette butts and associated cellulose acetate fibers (Section 2), fibers other than cellulose acetate (Section 3), single-use plastic foodware and related microplastics (Section 4), and tire particles (Section 5), which were prioritized based on findings from the recent urban stormwater monitoring of microplastics in the San Francisco Bay region. Conceptual models specific to each of these particle types are valuable tools to refine source identification and elucidate potential source-specific data gaps and management options.

 (9.17 MB)