Quantifying urban CO2 emissions using satellite-based atmospheric CO2 observations: an assessment of uncertainties

Kai Wu,  The University of Edinburgh,  kwu2@ed.ac.uk (Presenter)
Paul Palmer,  The University of Edinburgh,  pip@ed.ac.uk
Dien Wu,  The California Institute of Technology,  dienwu@caltech.edu
Tomohiro Oda,  Universities Space Research Association,  toda@usra.edu
Liang Feng,  The University of Edinburgh,  liang.feng@ed.ac.uk

Cities account for more than 70% of global CO2 emissions so that efforts to halt the rise in atmospheric CO2, in the context of the Paris Agreement, will require rapid and progressive emission estimates from urban areas. With the exception of a few major cities, our ability to develop robust CO2 data-driven emission estimates is non-existent. Here, we assess the theoretical ability of OCO-3 and the upcoming French-UK MicroCarb, both which have city-scan observing modes, to determine integrated city emissions of CO2. We use the ODIAC inventory and the X-Stochastic Time-Inverted Lagrangian Transport model (X-STILT) at 1 km resolution to build an urban CO2 inversion system. We use this system in a closed-loop experiment configuration to evaluate the impact of XCO2 retrieval errors, prior error correlation length scales, sampling patterns and satellite revisit times, taking into account clear-sky scenes. We compare results with a simpler analytical method of estimating urban emissions.

Poster: Poster_Wu__108_25.pdf 

Presentation Type: Poster

Session: 4.2a Observations to quantify hot spots and local/urban emissions

Session Date: Thursday (6/17) 10:00 AM