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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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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People

Collaborators

PI | Partners:

EMPA:

Dominik Brunner

More info

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.

Presentation

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Additional resources

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Bibliography

Publications

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Mueller, M.; Jaehn, M.; Pentina, A.; Brunner, D.; Perez-Cruz, F.; Hueglin, C.; Emmenegger, L. "Carbosense - CO2 sensor network and simulations" 1st Swiss Workshop on Machine Learning for Environmental and Geosciences (MLEG) 2019 View publication 

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Brunner, D.; Mueller, M.; Jaehn, M.; Graf, P.; Meyer, J.; Hueglin, C.; Pentina, A.; Perez Cruz, F.; Emmenegger, L. "A low-cost sensor network to monitor the CO2 emissions of the city of Zurich" The 3rd ICOS Science Conference on Greenhouse Gases and Biogeochemical Cycles 2018 View publication 