Cooperative Agreement for CESU-affiliated Partner of the Great Rivers Cooperative Ecosystem Studies Unit
At a glance
Cooperative Agreement for CESU-affiliated Partner of the Great Rivers Cooperative Ecosystem Studies Unit is a closed federal cooperative agreement opportunity from the Geological Survey (Department of the Interior). The application deadline was April 10, 2021. Individual awards are listed as $25K – $80K. Applicant types listed as eligible include others (see notice). Cost sharing is not required. It is funded under Assistance Listing 15.808 (U.S. Geological Survey Research and Data Collection).
Summary assembled from the official notice's fields. The official notice governs.
Key facts
- Mar 23, 2021Posted
- Apr 10, 2021Application deadline
- Posted
- Mar 23, 2021
- Close date
- Apr 10, 2021
- Award floor
- $25,000
- Award ceiling
- $80,000
- Est. total funding
- Not specified
- Expected awards
- Not specified
- Cost sharing
- Not required
- Funding instrument
- Cooperative Agreement
- Opportunity category
- Discretionary
Who can apply
- Others (see notice)
Additional information on eligibility (from the notice)
This financial assistance opportunity is being issued under a Cooperative Ecosystem Studies Unit (CESU) Program. CESU’s are partnerships that provide research, technical assistance, and education. Eligible recipients must be a participating partner of the Great Rivers Cooperative Ecosystem Studies Unit (CESU) Program.
A quick check against the listed applicant types — other requirements in the notice still apply.
Based on the published notice. Review the official notice for complete eligibility requirements.
What it funds
Official synopsis as published by the agency, formatted for readability.
The US Geological Survey is offering a funding opportunity to a CESU partner for research in the “Development of a cell phone application for use by oil spill responders for semi-quantitative analysis of hydrocarbons following spills and disasters.”
Research Objectives:
The USGS is currently conducting science to characterize and optimize the fluorescent properties of oil extracts to detect oil using image analysis. The general approach for the project is to: (1) optimize the fluorescent properties of simple oil/solvent systems for characterizing environmental samples, (2) characterize oil concentration based on the image analysis using laboratory derived concentration relationships, (3) develop a machine learning model and related equations to predict oil concentration using fluorescence based optical properties.
The objectives of this funding opportunity is to provide science to enhance the design of a cell phone adaptor/system 1) addresses interference of oil spill sample image collection, 2) approaches to optimize power usage, and 3) evaluate the confounding factors/conditions to optimize control/restriction of the image collection. In this task we will seek input from the oil spill practice community for input on the design and implementation of an image collection approach.
Three key questions should be answered:
What confounding factors or conditions might affect fluorescent image analysis of oil samples?
In an image collection system how can electrical energy be optimized and or managed to ensure efficient and stable image collection?
What approaches can be used to address confounding factors in a fluorescent image analysis system (1) while addressing issues identified in energy optimization identified in (2)?
This study will address USGS Ecosystem Mission Area goals to (1) Identify, prioritize, and detect contaminants; (2) Reduce the impact of stressors on the environment, fish, and wildlife; (3) Discover the complex interactions and combined effects of exposure to contaminants; and (4) Prepare for and respond to environmental impacts and related health threats of anthropogenic disasters.
Products of the research should include prototype systems that integrate approaches addressing the optimized fluorescent image collection and providing multiple prototype systems (up to 50) that can be provided for integration with the machine learning application for field demonstration. Research funded under this agreement will be conducted during FY 2021, initial data summaries and deliverables will be provided to USGS by September 30, 2021 and final reports will be provided to USGS by September 30, 2023.
Full announcement & documents
The full announcement has the complete rules — page limits, required attachments, evaluation criteria and any letter-of-intent dates. Files download directly from Grants.gov.
Assistance Listing
What is an ALN?Reported obligations under ALN 15.808
Historical data · not a predictionAgency contact (as published)
Geological Survey
fgraves@usgs.gov
703-648-7344
Quick answers
Who is eligible to apply for this opportunity?
The official notice names these applicant types as eligible: Others (see notice). Additional restrictions may apply; review the full notice.
How much funding is available through this opportunity?
Per the notice, individual awards are listed as $25k – $80k.
How do I apply for this opportunity?
Applications are submitted through the official source, not through GrantsJunction. Open the official notice on Grants.gov (opportunity G21AS00407), and review the full announcement and application package. Organizations applying through Grants.gov generally need an active SAM.gov registration and a Grants.gov account, which can take several weeks to set up.
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