The deadline for EGU 2020 abstract submissions is coming closer – today we highlight sessions focused on the application of (stable) isotope tracers to questions in biogeoscience.
The convenors say:
This session is open to all contributions in biogeochemistry and ecology where stable isotope techniques are used as analytical tools, with a focus on stable isotopes of light elements (C, H, O, N, S, …). We welcome studies from both terrestrial and aquatic (including marine) environments as well as methodological and experimental, theoretical and modeling studies that introduce new approaches or techniques (including natural abundance work, labeling studies, multi-isotope approaches, clumped and metal isotopes).
If your work uses the stable isotopes of light elements, but also carbonyl sulfide (COS) and clumped isotopes, then BG2.1 is a great fit for your abstract: Stable isotopes and novel tracers in biogeochemical and atmospheric research. This session is co-organized by AS4 and convened by Jan Kaiser, Alexander Knohl, Thomas Röckmann and Lisa Wingate.
The convenors say:
Stable isotopes and other novel tracers, such as carbonyl sulfide (COS) and clumped isotopes, help to identify and quantify biological, chemical and physical processes that drive Earth’s biogeochemical cycling, atmospheric processes and biosphere-atmosphere exchange. Recent developments in analytical measurement techniques now offer the opportunity to investigate these tracers at unprecedented temporal and spatial resolution and precision.
This session includes contributions from field and laboratory experiments, latest instrument developments as well as theoretical and modelling activities that investigate and use the isotope composition of light elements (C, H, O, N) and their compounds as well as other novel tracers for biogeochemical and atmospheric research.
Topics addressed in this session include:
– Stable isotopes in carbon dioxide (CO2), water (H2O), methane (CH4) and nitrous oxide (N2O)
– Novel tracers and biological analogues, such as COS
– Polyisotopocules (“clumped isotopes”)
– Intramolecular stable isotope distributions (“isotopomer abundances”)
– Analytical, method and modelling developments
– Flux measurements
– Quantification of isotope effects
– Non-mass dependent isotopic fractionation and related isotope anomalies
Stable isotope data, however, is only as good as its quality. The next session we highlight today deals with high quality isotope data: BG2.5 (co-organized by HS1.1) Quality of stable isotope data – Methods and tools for producing high quality data. This session is convened by Sergey Assonov, David Soto, Philip Dunn and Grzegorz Skrzypek.
The convenors say:
This multidisciplinary session invites contributions on the use of methods and tools aimed to obtain reliable stable isotope data in various areas. The number of papers using stable isotopes as a tool has increased enormously in the last years. Though this become a very common technique in many science fields (biogeosciences, atmospheric, environment, ecology, forensics, etc), such datasets are difficult to compare / combine as the data quality is often unknown. Different protocols used in different labs, not optimal use of Reference Materials (RMs), isotope fractionation during sample-preparation and within TCEA peripherals, exchangeable hydrogen and oxygen, different data corrections – these are a few examples of potential pitfalls. Evaluating data quality may be especially difficult for novel methodologies such as atmospheric research (e.g. N2O), applications using matrices with exchangeable Hydrogen, CSIA (e.g. fatty acids, amino acids). The session calls for papers that try to search flaws in analytical methods, in comparison of different datasets produced in different labs/methods, creating protocols and tools for QA/QC, investigation of proper RMs to be used for the fit-for-purpose. This session is a plea for high quality stable isotope data to be applied in many sciences and produce data that can be utilized for the future (this is important considering all efforts in OA journals, datasets, etc) including creating large reference datasets as based on data produced by different labs in areas such as biological species, soils, atmospheric observations, forensics. Often such reference datasets should not be used in any case without a proper QC applied.
Post written by Alexandra Rodler
