Articles | Volume 11, issue 12
Development and technical paper
04 Dec 2018
Development and technical paper |  | 04 Dec 2018

A Lagrangian approach towards extracting signals of urban CO2 emissions from satellite observations of atmospheric column CO2 (XCO2): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”)

Dien Wu, John C. Lin, Benjamin Fasoli, Tomohiro Oda, Xinxin Ye, Thomas Lauvaux, Emily G. Yang, and Eric A. Kort


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Dien Wu on behalf of the Authors (22 Sep 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (25 Sep 2018) by Christoph Knote
RR by Anonymous Referee #2 (16 Oct 2018)
ED: Publish as is (22 Oct 2018) by Christoph Knote
AR by Dien Wu on behalf of the Authors (01 Nov 2018)  Author's response    Manuscript
Short summary
Urban CO2 enhancement signals can be derived using satellite column CO2 concentrations and atmospheric transport models. However, uncertainties due to model configurations, atmospheric transport, and defined background values can potentially impact the derived urban signals. In this paper, we present a modified Lagrangian model framework that extracts urban CO2 signals from satellite observations and determines potential error impacts.