Bibliographic Details
| Title: |
Detection of Methane Emission from a Local Source Using GOSAT Target Observations |
| Authors: |
Akihiko Kuze, Nobuhiro Kikuchi, Fumie Kataoka, Hiroshi Suto, Kei Shiomi, Yutaka Kondo |
| Source: |
Remote Sensing, Vol 12, Iss 2, p 267 (2020) |
| Publisher Information: |
MDPI AG, 2020. |
| Publication Year: |
2020 |
| Collection: |
LCC:Science |
| Subject Terms: |
gosat, methane, partial column density, swir, tir, gas leak, wrf, flux, Science |
| More Details: |
Emissions of atmospheric methane (CH4), which greatly contributes to radiative forcing, have larger uncertainties than those for carbon dioxide (CO2). The Thermal And Near-infrared Sensor for carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observing SATellite (GOSAT) launched in 2009 has demonstrated global grid observations of the total column density of CO2 and CH4 from space, and thus reduced uncertainty in the global flux estimation. In this paper, we present a case study on local CH4 emission detection from a single-point source using an available series of GOSAT data. By modifying the grid observation pattern, the pointing mechanism of TANSO-FTS targets a natural gas leak point at Aliso Canyon in Southern California, where the clear-sky frequency is high. To enhance local emission estimates, we retrieved CO2 and CH4 partial column-averaged dry-air mole fractions of the lower troposphere (XCO2 (LT) and XCH4 (LT)) by simultaneous use of both sunlight reflected from Earth’s surface and thermal emissions from the atmosphere. The time-series data of Aliso Canyon showed a large enhancement that decreased with time after its initial blowout, compared with reference point data and filtered with wind direction simulated by the Weather Research and Forecasting (WRF) model. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2072-4292 |
| Relation: |
https://www.mdpi.com/2072-4292/12/2/267; https://doaj.org/toc/2072-4292 |
| DOI: |
10.3390/rs12020267 |
| Access URL: |
https://doaj.org/article/aa34b7232479443dae75c501418955ef |
| Accession Number: |
edsdoj.34b7232479443dae75c501418955ef |
| Database: |
Directory of Open Access Journals |
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