Compressed Sensing for Climate: A Novel Approach to Localize, Quantify and Characterize Urban Greenhouse Gas Emitters

Introduction

Climate change is a defining issue of our time. Without significant, rapid greenhouse gas (GHG) emission reductions, we will face unpredictable consequences for climate and life. To effectively reduce GHGs, the emissions must be accurately quantified and unknown emitters found.

Challenges in Measurement

However, measuring global GHG emissions is very challenging, and hence current emission inventories rely mostly on bottom-up calculations, which lack accuracy and the ability to detect unknown sources.

Project Overview

In CoSense4Climate, I will use the powerful mathematical theory of compressed sensing (CS) to revolutionize atmospheric inversion. My goal is to develop a method to locate, quantify, and attribute GHG emitters with unmatched spatial resolution and accuracy.

Methodology

CS has been used with great success in signal and image processing by taking advantage of the fact that most signals contain redundancies. Using CS in combination with domain transformations, I will:

• Generate accurate high-resolution emission fields
• Reveal unknown sources
• Require less data than conventional methods

I will develop a CS inversion framework not only for local sensor data but also for satellite data, which, upon success, will lead to a breakthrough in monitoring urban GHG emissions globally.

Personal Qualifications

I am best suited to reach this goal. I have gathered a unique dataset with my fully automated differential column GHG network MUCCnet, the first of its kind.

With my rich experience in applying:

1. Computational fluid dynamics (CFD)
2. Solar-induced fluorescence (SIF)
3. Machine learning (ML)

I will additionally create:

• A high-resolution CFD-based atmospheric transport model
• A satellite SIF-based urban CO2 biogenic flux model
• A ML method for source attribution based on ratios of GHG and air pollutant concentrations

Conclusion

CoSense4Climate will establish a new standard for GHG emission monitoring and provide ground-breaking scientific methods to help solve one of today’s most urgent problems: climate change.