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.
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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