Abstract
Understanding of regional greenhouse gas emissions into the atmosphere is a prerequisite to mitigate climate change. In this study, we investigated the regional contributions of carbon dioxide (CO2) at the location of the high Alpine observatory Jungfraujoch ("JFJ", Switzerland, 3580 m a.s.l.). To this purpose, we combined receptor-oriented atmospheric transport simulations for CO2 concentration in the period of 2009–2017 with stable carbon isotope (δ13C-CO2) information. We applied two Lagrangian particle dispersion models driven by output from two different numerical weather prediction systems (FLEXPART-COSMO and STILT-ECMWF) in order to simulate CO2 concentration at JFJ based on regional CO2 fluxes, to estimate atmospheric δ13C-CO2, and to obtain model-based estimates of the mixed source signatures (δ13Cm). Anthropogenic fluxes were taken from a fuel type-specific version of the EDGAR v4.3 inventory and ecosystem fluxes were based on the Vegetation Photosynthesis and Respiration Model (VPRM). The simulations of CO2, δ13C-CO2 and δ13Cm were then compared to observations performed by quantum cascade laser absorption spectroscopy. Around 40 % of the regional CO2 variability above or below the large-scale background was captured by the models, and up to 35 % of the regional variability in δ13C-CO2. This is remarkable considering the complex Alpine topography, the low intensity of regional signals at JFJ, and the challenging measurements. Best agreement between simulations and observations in terms of short-term variability and intensity of the signals for CO2 and δ13C-CO2 was found between late autumn and early spring. The agreement was inferior in the early autumn periods and during summer. This may be associated with the atmospheric transport representation in the models. In addition, the net ecosystem exchange fluxes are a possible source of error, either through inaccuracies in their representation in VPRM for the (Alpine) vegetation or through a day (uptake) vs. night (respiration) transport discrimination to JFJ. Furthermore, the simulations suggest that JFJ is subject to relatively small regional anthropogenic contributions, due to its remote location (elevated and far from major anthropogenic sources), and the limited planetary boundary layer-influence during winter. Instead, the station is primarily exposed to summer-time ecosystem CO2 contributions, which are dominated by rather nearby sources (within 100 km). Even during winter, simulated gross ecosystem respiration accounted for approximately 50 % of all contributions to the CO2 concentrations above the largescale background. The model-based monthly mean δ13Cm ranged from −22 ‰ in winter to −28 ‰ in summer and reached the most depleted values of −35 ‰ at higher fractions of natural gas combustion, and the most enriched values of −17 to −12 ‰ when impacted by cement production emissions. Observation-based δ13Cm values derived by a moving Keeling-plot approach were in good agreement with the model-based estimates. They exhibited a larger scatter, while model-based estimates spread in a more narrow range. Overall, observation-based δ13Cm were limited to a smaller number of data points compared to model-based estimates owing to the stringent analysis prerequisites in combination with the low regional signal at JFJ.
Highlights
Reliable regional quantification of greenhouse gas (GHG) emissions into the atmosphere is a prerequisite to determine the effectiveness of mitigation strategies to limit global warming
Additional differences 330 appear related to the smaller domain size and shorter backward integration used for FLEXPART-COSMO, which are directly associated with smaller integrated surface CO2 fluxes
JFJ uniquely allows for evaluating model-based estimates of atmospheric δ13C-CO2 and of mixed source signatures (δ13Cm) through comparison with atmospheric δ13C-CO2 observations and thereof derived 520 ("observation-based") δ13C-CO2 or mixed isotope source signatures (δ13Cm) values using a moving Keeling approach. 3.2.1 Regression analysis of hourly-scale atmospheric δ13C-CO2 estimates vs. observations We evaluated the atmospheric δ13C-CO2 isotope ratio estimates (δ13Ca), which are derived following Eq (2) on a 3hourly basis, through comparison with the quantum cascade laser absorption spectroscopy (QCLAS) observations during the period 2012–2015 (Figure 6, Table 4)
Summary
Reliable regional quantification of greenhouse gas (GHG) emissions into the atmosphere is a prerequisite to determine the effectiveness of mitigation strategies to limit global warming. Its atmospheric concentrations are altered by both anthropogenic and natural (terrestrial ecosystem and oceanic) fluxes (Friedlingstein et al, 2020). Remote sites are ideal to study large-scale and global 45 emissions, but make it more challenging to characterize individual sources and sinks as during transport of air masses to remote sites the signals of individual sources and sinks become diluted and mixed. Remote atmospheric sites typically focus on long-term trends, and, sporadic events are often discarded in the time series analyses. This leads to loss of potentially insightful information
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