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Identifying trend reversals in atmospheric ethane from a multi-site analysis

  • Marina Friedrich*
  • , Siem Jan Koopman
  • , Yicong Lin
  • , Emmanuel Mahieu
  • , Stephan Smeekes
  • , Martine De Maziere
  • , Victoria Flood
  • , Matthias Max Frey
  • , Michel Grutter
  • , James W. Hannigan
  • , Frank Hase
  • , Nicholas Jones
  • , Rigel Kivi
  • , Maria Makarova
  • , Isamu Morino
  • , Isao Murata
  • , Tomoo Nagahama
  • , Justus Notholt
  • , Ivan Ortega
  • , Maxime Prignon
  • Amelie Ninja Rohling, Dan Smale, Kimberly Strong, Yao Te, Minqiang Zhou
*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Ethane is the most abundant non-methane hydrocarbon in Earth's atmosphere and acts as an indirect greenhouse gas, influencing the atmospheric lifetime of methane. Therefore, understanding the development of trends and identifying trend reversals in atmospheric ethane is crucial. Ethane abundance is measured at different ground-based stations worldwide using Fourier transform infrared remote sensing techniques. We compile a new dataset comprising 26 ethane time series from the Northern and Southern Hemispheres. We analyze their long-term trends using different econometric techniques capable of handling missing data and strong seasonal components present in the data. The resulting trend patterns are consistent across the different methods, with similar estimated trends at the various stations. In the Northern Hemisphere, the common trend across stations declined from the 1990s to 2005, gradually increased over the next decade, and then resumed a similar downward trajectory from 2015 onward. The estimated trends reveal a pronounced peak around 2014/2015, marking a reversal from an upward to a downward trend.
Original languageEnglish
Article number66
Number of pages33
JournalClimatic Change
Volume179
Issue number4
DOIs
Publication statusPublished - 25 Mar 2026

Keywords

  • Atmospheric ethane
  • FTIR remote sensing
  • Kalman filter
  • Nonparametric trend analysis

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