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1-2-many - how many samples do we need to quantify greenhouse gas emissions in agricultural fields

Main subject area: Greenhouse gas emissions; spatial variation

Short project description

Greenhouse gas emissions vary in space and throughout the growing season. In addition, we typically measure greenhouse gas fluxes in a relatively small area which makes it difficult to infer to large scales. It is often unclear how many samples are needed to accurately represent greenhouse gas emissions of a large area, because of many different influencing factors. In this master project, we aim to quantify the spatial variation of greenhouse gas emissions in an agricultural field with the objective of improving our understanding of large-scale emissions.

Department and supervisor

Christian Dold

Tenure Track assistant professor

Project start


Physical location of project and students work

Blichers Alle 20, Tjele, 8830-DK

Extent and type of project

30 ECTS: Theoretical thesis based on literature studies and/or analysis of issued and edited data sets.

45 ECTS: Experimental theses in which the student is responsible for collection and analysis of his/her own original data

Additional information

This master project can either be based on a thorough literature review combined with new datasets taken from a nearby field (30 ECTS), or on data taken by the MSc student his/herself (45 ECTS). Greenhouse gas emissions will be measured with a novel laser-based analyzer. MSc students with interest in remotely sensed or georeferenced data are very welcome. Christian Dold will be the main supervisor with additional support of PhD student Dhimas Sigit Bimantara. The MSc student will also work together with different researchers and technical staff. This MSc project will be linked to the DISGREE project.

Relevant articles

Parkin, Timothy B., and Rodney T. Venterea. "USDA-ARS GRACEnet project protocols, chapter 3. Chamber-based trace gas flux measurements." Sampling protocols. Beltsville, MD p (2010): 1-39.

Turner, P. A., et al. (2016). "A geostatistical approach to identify and mitigate agricultural nitrous oxide emission hotspots." Science of the Total Environment 572: 442-449.