CarboSense4D

Four-dimensional mapping of carbon dioxide using low-cost sensors, atmospheric transport simulations and machine learning

Started
April 1, 2018
Status
Completed
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Abstract

How to determine real-time CO2 emissions of the city of Zurich and track their year-to-year evolution, enhance the understanding of CO2 exchange between biosphere and atmosphere over Switzerland, and improve the data quality of low-cost sensor networks.

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SDSC Team:
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PI | Partners:

EMPA:

  • Dominik Brunner

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description

Problem:

  • Determine real-time CO2 emissions of the city of Zurich and track their year-to-year evolution
  • Enhance understanding of CO2 exchange between biosphere and atmosphere over Switzerland
  • Improve data quality of low-cost sensor networks

Solution:

Integrate complimentary information from

  • Dense network of CO2 sensors across Switzerland
  • Atmospheric transport simulations * Data analysis and machine learning

Impact:

  • CarboSense4D improves the operation of dense trace gas sensor networks and the understanding of CO2 fluxes at urban and regional scales to support the assessment of CO2 emission reduction measures.

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