CH4, CO, and H2O spectroscopy for the Sentinel-5 Precursor mission: an assessment with the Total Carbon Column Observing Network measurements

The TROPOspheric Monitoring Instrument (TROPOMI) will be part of ESA's Sentinel-5 Precursor (S5P) satellite platform scheduled for launch in 2015. TROPOMI will monitor methane and carbon monoxide concentrations in the Earth's atmosphere by measuring spectra of back-scattered sunlight in the short-wave infrared (SWIR). S5P will be the first satellite mission to rely uniquely on the spectral window at 4190–4340 cm−1 (2.3 μm) to retrieve CH4 and CO. In this study, we investigated if the absorption features of the three relevant molecules CH4, CO, and H2O are adequately known. To this end, we retrieved total columns of CH4, CO, and H2O from absorption spectra measured by two ground-based Fourier transform spectrometers that are part of the Total Carbon Column Observing Network (TCCON). The retrieval results from the 4190–4340 cm−1 range at the TROPOMI resolution (0.45 cm−1) were then compared to the CH4 results obtained from the 6000 cm−1 region, and the CO results obtained from the 4190–4340 cm−1 region at the higher TCCON resolution (0.02 cm−1). For TROPOMI-like settings, we were able to reproduce the CH4 columns to an accuracy of 0.3% apart from a constant bias of 1%. The CO retrieval accuracy was, through interference, systematically influenced by the shortcomings of the CH4 and H2O spectroscopy. In contrast to CH4, the CO column error also varied significantly with atmospheric H2O content. Unaddressed, this would introduce seasonal and latitudinal biases to the CO columns retrieved from TROPOMI measurements. We therefore recommend further effort from the spectroscopic community to be directed at the H2O and CH4 spectroscopy in the 4190–4340 cm−1 region.

Real-time analysis of δ13C- and δD-CH4 in ambient air with laser spectroscopy: method development and first intercomparison results

In situ and simultaneous measurement of the three most abundant isotopologues of methane using mid-infrared laser absorption spectroscopy is demonstrated. A field-deployable, autonomous platform is realized by coupling a compact quantum cascade laser absorption spectrometer (QCLAS) to a preconcentration unit, called trace gas extractor (TREX). This unit enhances CH4 mole fractions by a factor of up to 500 above ambient levels and quantitatively separates interfering trace gases such as N2O and CO2. The analytical precision of the QCLAS isotope measurement on the preconcentrated (750 ppm, parts-per-million, µmole mole−1) methane is 0.1 and 0.5 ‰ for δ13C- and δD-CH4 at 10 min averaging time. Based on repeated measurements of compressed air during a 2-week intercomparison campaign, the repeatability of the TREX–QCLAS was determined to be 0.19 and 1.9 ‰ for δ13C and δD-CH4, respectively. In this intercomparison campaign the new in situ technique is compared to isotope-ratio mass spectrometry (IRMS) based on glass flask and bag sampling and real time CH4 isotope analysis by two commercially available laser spectrometers. Both laser-based analyzers were limited to methane mole fraction and δ13C-CH4 analysis, and only one of them, a cavity ring down spectrometer, was capable to deliver meaningful data for the isotopic composition. After correcting for scale offsets, the average difference between TREX–QCLAS data and bag/flask sampling–IRMS values are within the extended WMO compatibility goals of 0.2 and 5 ‰ for δ13C- and δD-CH4, respectively. This also displays the potential to improve the interlaboratory compatibility based on the analysis of a reference air sample with accurately determined isotopic composition.

Continuous CO2/CH4/CO measurements (2012–2014) at Beromünster tall tower station in Switzerland

The understanding of the continental carbon budget is essential to predict future climate change. In order to quantify CO₂ and CH₄ fluxes at the regional scale, a measurement system was installed at the former radio tower in Beromünster as part of the Swiss greenhouse gas monitoring network (CarboCount CH). We have been measuring the mixing ratios of CO₂, CH₄ and CO on this tower with sample inlets at 12.5, 44.6, 71.5, 131.6 and 212.5 m above ground level using a cavity ring down spectroscopy (CRDS) analyzer. The first 2-year (December 2012–December 2014) continuous atmospheric record was analyzed for seasonal and diurnal variations and interspecies correlations. In addition, storage fluxes were calculated from the hourly profiles along the tower. The atmospheric growth rates from 2013 to 2014 determined from this 2-year data set were 1.78 ppm yr⁻¹, 9.66 ppb yr⁻¹ and and -1.27 ppb yr⁻¹ for CO₂, CH₄ and CO, respectively. After detrending, clear seasonal cycles were detected for CO₂ and CO, whereas CH₄ showed a stable baseline suggesting a net balance between sources and sinks over the course of the year. CO and CO₂ were strongly correlated (r² > 0.75) in winter (DJF), but almost uncorrelated in summer. In winter, anthropogenic emissions dominate the biospheric CO₂ fluxes and the variations in mixing ratios are large due to reduced vertical mixing. The diurnal variations of all species showed distinct cycles in spring and summer, with the lowest sampling level showing the most pronounced diurnal amplitudes. The storage flux estimates exhibited reasonable diurnal shapes for CO₂, but underestimated the strength of the surface sinks during daytime. This seems plausible, keeping in mind that we were only able to calculate the storage fluxes along the profile of the tower but not the flux into or out of this profile, since no Eddy covariance flux measurements were taken at the top of the tower.

Simultaneous stable isotope analysis of methane and nitrous oxide on ice core samples

Methane and nitrous oxide are important greenhouse gases which show a strong increase in atmospheric mixing ratios since pre-industrial time as well as large variations during past climate changes. The understanding of their biogeochemical cycles can be improved using stable isotope analysis. However, high-precision isotope measurements on air trapped in ice cores are challenging because of the high susceptibility to contamination and fractionation. Here, we present a dry extraction system for combined CH4 and N2O stable isotope analysis from ice core air, using an ice grating device. The system allows simultaneous analysis of δD(CH4) or δ13C(CH4), together with δ15N(N2O), δ18O(N2O) and δ15N(NO+ fragment) on a single ice core sample, using two isotope mass spectrometry systems. The optimum quantity of ice for analysis is about 600 g with typical "Holocene" mixing ratios for CH4 and N2O. In this case, the reproducibility (1σ ) is 2.1‰ for δD(CH4), 0.18‰ for δ13C(CH4), 0.51‰ for δ15N(N2O), 0.69‰ for δ18O(N2O) and 1.12‰ for δ15N(NO+ fragment). For smaller amounts of ice the standard deviation increases, particularly for N2O isotopologues. For both gases, small-scale intercalibrations using air and/or ice samples have been carried out in collaboration with other institutes that are currently involved in isotope measurements of ice core air. Significant differences are shown between the calibration scales, but those offsets are consistent and can therefore be corrected for.

Constraining global methane emissions and uptake by ecosystems

Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a~significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.

Duration of Greenland Stadial 22 and ice-gas Δage from counting of annual layers in Greenland NGRIP ice core

High-resolution measurements of chemical impurities and methane concentrations in Greenland ice core samples from the early glacial period allow the extension of annual-layer counted chronologies and the improvement of gas age-ice age difference (Δage) essential to the synchronization of ice core records. We report high-resolution measurements of a 50 m section of the NorthGRIP ice core and corresponding annual layer thicknesses in order to constrain the duration of the Greenland Stadial 22 (GS-22) between Greenland Interstadials (GIs) 21 and 22, for which inconsistent durations and ages have been reported from Greenland and Antarctic ice core records as well as European speleothems. Depending on the chronology used, GS-22 occurred between approximately 89 (end of GI-22) and 83 kyr b2k (onset of GI-21). From annual layer counting, we find that GS-22 lasted between 2696 and 3092 years and was followed by a GI-21 pre-cursor event lasting between 331 and 369 yr. Our layer-based counting agrees with the duration of stadial 22 as determined from the NALPS speleothem record (3250 ± 526 yr) but not with that of the GICC05modelext chronology (2620 yr) or an alternative chronology based on gas-marker synchronization to EPICA Dronning Maud Land ice core. These results show that GICC05modelext overestimates accumulation and/or underestimates thinning in this early part of the last glacial period. We also revise the possible ranges of NorthGRIP Δdepth (5.49 to 5.85 m) and Δage (498 to 601 yr) at the warming onset of GI-21 as well as the Δage range at the onset of the GI-21 precursor warming (523 to 654 yr), observing that temperature (represented by the δ15N proxy) increases before CH4 concentration by no more than a few decades.

Spatial heterogeneity and lake morphology affect diffusive greenhouse gas emission estimates of lakes

Most estimates of diffusive flux (F) of methane (CH4) and carbon dioxide (CO2) from lakes are based on single-point flux chamber measurements or on piston velocity (k) modeled from wind speed and single-point measurements of surface water gas concentrations (C-aq). We analyzed spatial variability of F of CH4 and CO2, as well as C-aq and k in 22 European lakes during late summer. F and k were higher in the lake centers, leading to considerable bias when extrapolating single-point chamber measurements to whole-lake estimates. The ratio of our empirical k estimates to wind speed-modeled k was related to lake size and shape, suggesting a lake morphology effect on the relationship between wind speed and k. This indicates that the error inherent to established wind speed models can be reduced by determining k and C-aq at multiple sites on lakes to calibrate wind speed-modeled k to the local system.

Psychophysiology of prospective memory

Prospective memory involves the self-initiated retrieval of an intention upon an appropriate retrieval cue. Cue identification can be considered as an orienting reaction and may thus trigger a psychophysiological response. Here we present two experiments in which skin conductance responses (SCRs) elicited by prospective memory cues were compared to SCRs elicited by aversive stimuli to test whether a single prospective memory cue triggers a similar SCR as an aversive stimulus. In Experiment 2 we also assessed whether cue specificity had a differential influence on prospective memory performance and on SCRs. We found that detecting a single prospective memory cue is as likely to elicit a SCR as an aversive stimulus. Missed prospective memory cues also elicited SCRs. On a behavioural level, specific intentions led to better prospective memory performance. However, on a psychophysiological level specificity had no influence. More generally, the results indicate reliable SCRs for prospective memory cues and point to psychophysiological measures as valuable approach, which offers a new way to study one-off prospective memory tasks. Moreover, the findings are consistent with a theory that posits multiple prospective memory retrieval stages.

Optimizing the size of the area surveyed for monitoring a Eurasian lynx (Lynx lynx) population in the Swiss Alps by means of photographic capture-recapture

We studied the influence of surveyed area size on density estimates by means of camera-trapping in a low-density felid population (1-2 individuals/100 km(2) ). We applied non-spatial capture-recapture (CR) and spatial CR (SCR) models for Eurasian lynx during winter 2005/2006 in the northwestern Swiss Alps by sampling an area divided into 5 nested plots ranging from 65 to 760 km(2) . CR model density estimates (95% CI) for models M0 and Mh decreased from 2.61 (1.55-3.68) and 3.6 (1.62-5.57) independent lynx/100 km(2) , respectively, in the smallest to 1.20 (1.04-1.35) and 1.26 (0.89-1.63) independent lynx/100 km(2) , respectively, in the largest area surveyed. SCR model density estimates also decreased with increasing sampling area but not significantly. High individual range overlaps in relatively small areas (the edge effect) is the most plausible reason for this positive bias in the CR models. Our results confirm that SCR models are much more robust to changes in trap array size than CR models, thus avoiding overestimation of density in smaller areas. However, when a study is concerned with monitoring population changes, large spatial efforts (area surveyed ≥760 km(2) ) are required to obtain reliable and precise density estimates with these population densities and recapture rates.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.