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Estimation of methane emissions from the U.S. ammonia fertilizer industry using a mobile sensing approach
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Estimation of methane emissions from the U.S. ammonia fertilizer industry using a mobile sensing approach
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Estimation of methane emissions from the U.S. ammonia fertilizer industry using a mobile sensing approach
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Journal Article
Estimation of methane emissions from the U.S. ammonia fertilizer industry using a mobile sensing approach
2019
Overview
To date, estimation of greenhouse gas (GHG) emissions from the natural gas (NG) value chain have focused on upstream (production) and midstream (gathering, transmission, and storage) operations. In this study, we estimate methane emissions from an important downstream consumer of NG, the ammonia fertilizer industry, which commonly uses NG as a feedstock and a fuel for the production of ammonia and other upgraded products. Using a Google Street View (GSV) car equipped with a high-precision methane analyzer, we adopted a mobile sensing approach to measure methane mixing ratios along public roads that are downwind of the ammonia fertilizer plants. Useful data were collected from six plants, which represent >25% of the total number of U.S NG-based ammonia fertilizer plants, and use >20% of the total NG consumption by this industry. Based on the measured data, a source characterization model was applied to estimate the methane emission rates from the upwind plants. Assuming that the estimates are representative of emissions during normal operations of a plant, we calculated the NG loss rate (i.e. the ratio between NG emission rate and NG throughput). If the sampled plants are representative of the U.S. ammonia fertilizer industry, the industrial-averaged NG loss rate (± standard deviation) is estimated to be 0.34% (±0.20%), and the total methane emissions (± standard deviation) from this industry are estimated to be 29 (±18) Gigagram per year (Gg CH4/yr) in 2015–2016. This is significantly higher than the reported methane emissions of 0.2 Gg CH4/yr from the U.S. EPA’s Facility Level Information on Greenhouse Gas Tools (FLIGHT). This study begins to fill an important knowledge gap in quantifying methane emissions along the NG value chain, and demonstrates the capability of mobile sensing for characterizing airborne emissions.
