The Paris agreement temperature target was a political success and a desired step towards directly targeting a measurable climate change. A basis of this agreement is capacity of each country to accurately quantify its influences on temperature. This means that all greenhouse gas (GHG) fluxes need to be considered in national inventories, and capacity to verify that local mitigation efforts actually work in reality is needed. Unfortunately, such capacity is largely missing despite abundant GHG models, because there is a lack of methods to produce the GHG data at the resolution needed to validate the models. Moreover, a serious limitation arises because landcover information is much less precise than commonly believed, so a large uncertainty in GHG models are the relative areas of the different environments considered.
We need methods for GHG and area measurements that have a higher resolution and are cost-efficient and suitable for use at different scales. The GHG flux methods also need to be mobile and easy to use outside academia in all sectors, activity and landscape types. Recent and ongoing research yielded groundbreaking early progress with such methods based on (1) hyperspectral GHG imaging, (2) GHG sensor networks, and (3) accurate high-resolution land-cover modelling. This project will take on the development from academic prototypes towards applications adapted for use in society and research to make more reliable GHG models and assessments possible.
This project is a collaboration between Linköping University (host institution; Prof. David Bastviken lead applicant), Gothenburg University, Umeå University and University of York.
Funding
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