@phdthesis{Hoffmann2019,
  author    = {Hoffmann, Mathias},
  title     = {Improving measurement and modelling approaches of the closed chamber method to better assess dynamics and drivers of carbon based greenhouse gas emissions},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-421302},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xx, 204, xxix},
  year      = {2019},
  abstract  = {The trace gases CO2 and CH4 pertain to the most relevant greenhouse gases and are important exchange fluxes of the global carbon (C) cycle. Their atmospheric quantity increased significantly as a result of the intensification of anthropogenic activities, such as especially land-use and land-use change, since the mid of the 18th century. To mitigate global climate change and ensure food security, land-use systems need to be developed, which favor reduced trace gas emissions and a sustainable soil carbon management. This requires the accurate and precise quantification of the influence of land-use and land-use change on CO2 and CH4 emissions. A common method to determine the trace gas dynamics and C sink or source function of a particular ecosystem is the closed chamber method. This method is often used assuming that accuracy and precision are high enough to determine differences in C gas emissions for e.g., treatment comparisons or different ecosystem components. However, the broad range of different chamber designs, related operational procedures and data-processing strategies which are described in the scientific literature contribute to the overall uncertainty of closed chamber-based emission estimates. Hence, the outcomes of meta-analyses are limited, since these methodical differences hamper the comparability between studies. Thus, a standardization of closed chamber data acquisition and processing is much-needed. Within this thesis, a set of case studies were performed to: (I) develop standardized routines for an unbiased data acquisition and processing, with the aim of providing traceable, reproducible and comparable closed chamber based C emission estimates; (II) validate those routines by comparing C emissions derived using closed chambers with independent C emission estimates; and (III) reveal processes driving the spatio-temporal dynamics of C emissions by developing (data processing based) flux separation approaches. The case studies showed: (I) the importance to test chamber designs under field conditions for an appropriate sealing integrity and to ensure an unbiased flux measurement. Compared to the sealing integrity, the use of a pressure vent and fan was of minor importance, affecting mainly measurement precision; (II) that the developed standardized data processing routines proved to be a powerful and flexible tool to estimate C gas emissions and that this tool can be successfully applied on a broad range of flux data sets from very different ecosystem; (III) that automatic chamber measurements display temporal dynamics of CO2 and CH4 fluxes very well and most importantly, that they accurately detect small-scale spatial differences in the development of soil C when validated against repeated soil inventories; and (IV) that a simple algorithm to separate CH4 fluxes into ebullition and diffusion improves the identification of environmental drivers, which allows for an accurate gap-filling of measured CH4 fluxes. Overall, the proposed standardized data acquisition and processing routines strongly improved the detection accuracy and precision of source/sink patterns of gaseous C emissions. Hence, future studies, which consider the recommended improvements, will deliver valuable new data and insights to broaden our understanding of spatio-temporal C gas dynamics, their particular environmental drivers and underlying processes.},
  language  = {en}
}