Got Methane?

EarthzineDevelop Summer 2017, DEVELOP Virtual Poster Session

This article is a part of the NASA DEVELOP’s Summer 2017 Virtual Poster Session. For more articles like these, click here

Project Team: California Health & Air Quality

Team Location:åÊNASA Jet Propulsion Laboratory ‰ÛÒ Pasadena, California

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Authors:

Jacob Arndt

Kelsey Foster

Erika Higa

Mentors/Advisors:

Kristal Verhulst (NASA Jet Propulsion Laboratory, California Institute of Technology)

Charles Miller (NASA Jet Propulsion Laboratory, California Institute of Technology)

Linear Spectral Unmixing was used to identify endmembers. (Left) Bright features represent feedlots. (Center) Bright features represent lagoons. (Right) Methane and ammonia plumes. Image Credit: California Health & Air Quality Team

Abstract:

Methane (CH4) is a potent greenhouse gas (GHG) with a lifetime of less than 10 years and a global warming potential that is 25 times greater than carbon dioxide (CO2) over a 100-year time period. Between the energy, industrial processes and product use, agriculture, and waste sectors, the majority of CH4 emissions in the United States come from the agriculture sector. Within this sector, enteric fermentation by domestic livestock and manure management are the largest sources of emissions. California is the leading dairy producer in the United States and thus, enteric fermentation and manure management make substantial contributions to the state’s CH4 budget. Furthermore, a number of studies suggest that Environmental Protection Agency bottom-up methodologies are underestimating CH4 emissions in many regions across California. Total number, location, size, and manure management infrastructure of dairy farms throughout the state are also uncertain. Given these uncertainties, in addition to dairy production’s large contribution to CH4 emissions, its industrialization, and the need to more accurately account for and understand CH4 emissions, we located and inventoried dairy farms across California’s Central Valley using RapidEye imagery and image classification techniques. We used the resulting classifications to create a spatial dataset of dairy farms that were used to help interpret Airborne Visible / Infrared Imaging Spectrometer ‰ÛÒ Next Generation (AVIRIS-NG) and Hyperspectral Thermal Emission Spectrometer (HyTES) CH4 plume data collected over the dairy farms. This will ultimately provide insight into an important source of CH4 and help policymakers, dairy farmers, and management officials make more informed decisions on how best to mitigate CH4 emissions within the state of California.

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