ALBERT

Description: Atmospheric nitrous oxide (N2O) levels have been continuously growing since preindustrial times. Mitigation requires information about sources and sinks on the regional and global scales. Isotopic composition of N2O in the atmosphere could contribute valuable constraints. However, isotopic records of N2O in the unpolluted atmosphere remain too scarce for large-scale N2O models. Here, we report the results of discrete air samples collected weekly to biweekly over a 5-year period at the high-altitude research station Jungfraujoch, located in central Switzerland. High-precision N2O isotopic measurements were made using a recently developed preconcentration and laser spectroscopy technique. The measurements of discrete samples were accompanied by in situ continuous measurements of N2O mixing ratios. Our results indicate a pronounced seasonal pattern with minimum N2O mixing ratios in late summer, associated with a maximum in δ15Nbulk and a minimum in intramolecular 15N site preference (δ15NSP). This pattern is most likely due to stratosphere–troposphere exchange (STE), which delivers N2O-depleted but 15N-enriched air from the stratosphere into the troposphere. Variability in δ15NSP induced by changes in STE may be masked by biogeochemical N2O production processes in late summer, which are possibly dominated by a low-δ15NSP pathway of N2O production (denitrification), providing an explanation for the observed seasonality of δ15NSP. Footprint analyses and atmospheric transport simulations of N2O for Jungfraujoch suggest that regional emissions from the planetary boundary layer contribute to seasonal variations of atmospheric N2O isotopic composition at Jungfraujoch, albeit more clearly for δ15NSP and δ18O than for δ15Nbulk. With the time series of 5 years, we obtained a significant interannual trend for δ15Nbulk after deseasonalization (-0.052±0.012 ‰ a−1), indicating that the atmospheric N2O increase is due to isotopically depleted N2O sources. We estimated the average isotopic signature of anthropogenic N2O sources with a two-box model to be -8.6±0.6 ‰ for δ15Nbulk, 34.8±3 ‰ for δ18O and 10.7±4 ‰ for δ15NSP. Our study demonstrates that seasonal variation of N2O isotopic composition in the background atmosphere is important when determining interannual trends. More frequent, high-precision and interlaboratory-compatible measurements of atmospheric N2O isotopocules, especially for δ15NSP, are needed to better constrain anthropogenic N2O sources and thus the contribution of biogeochemical processes to N2O growth on the global scale.

Description: Aerosol particles are essential constituents of the Earth's atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence times, resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in situ near-surface segment of the atmospheric observation system. This paper will provide the widest effort so far to document variability of climate-relevant in situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High-quality data from almost 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single-scattering albedo, and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information, including data provision procedures, quality control and analysis, data policy, and usage of the ground-based aerosol measurement network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.

Description: Abundance-based model evaluations with observations provide critical tests for the simulated mean state in models of intercontinental pollution transport, and under certain conditions may also offer constraints on model responses to emission changes. We compile multiyear measurements of peroxy acetyl nitrate (PAN) available from five mountaintop sites and apply them in a proof-of-concept approach that exploits an ensemble of global chemical transport models (HTAP1) to identify an observational “emergent constraint”. In April, when the signal from anthropogenic emissions on PAN is strongest, simulated PAN at northern midlatitude mountaintops correlates strongly with PAN source–receptor relationships (the response to 20 % reductions in precursor emissions within northern midlatitude continents; hereafter, SRRs). This finding implies that PAN measurements can provide constraints on PAN SRRs by limiting the SRR range to that spanned by the subset of models simulating PAN within the observed range. In some cases, regional anthropogenic volatile organic compound (AVOC) emissions, tracers of transport from different source regions, and SRRs for ozone also correlate with PAN SRRs. Given the large observed interannual variability in the limited available datasets, establishing strong constraints will require matching meteorology in the models to the PAN measurements. Application of this evaluation approach to the chemistry–climate models used to project changes in atmospheric composition will require routine, long-term mountaintop PAN measurements to discern both the climatological SRR signal and its interannual variability.

Description: This work presents the methane (CH4) and nitrous oxide (N2O) products as generated by the IASI (Infrared Atmospheric Sounding Interferometer) processor developed during the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). The processor retrieves CH4 and N2O with different water vapour and water vapour isotopologues (as well as HNO3) and uses a single a priori data set for all the retrievals (no variation in space and time). Firstly, the characteristics and errors of the products are analytically described. Secondly, the products are comprehensively evaluated by comparisons to the following reference data measured by different techniques and from different platforms as follows: (1) aircraft CH4 and N2O profiles from the five HIAPER Pole-to-Pole Observation (HIPPO) missions; (2) continuous in situ CH4 and N2O observations performed between 2007 and 2017 at subtropical and mid-latitude high-mountain observatories (Izaña Atmospheric Observatory and Jungfraujoch, respectively) in the framework of the WMO–GAW (World Meteorological Organization–Global Atmosphere Watch) programme; (3) ground-based FTIR (Fourier-transform infrared spectrometer) measurements made between 2007 and 2017 in the framework of the NDACC (Network for the Detection of Atmospheric Composition Change) at the subtropical Izaña Atmospheric Observatory, the mid-latitude station of Karlsruhe and the Kiruna polar site.The theoretical estimations and the comparison studies suggest a precision for the N2O and CH4 retrieval products of about 1.5–3 % and systematic errors due to spectroscopic parameters of about 2 %. The MUSICA IASI CH4 data offer a better sensitivity than N2O data. While for the latter the sensitivity is mainly limited to the UTLS (upper troposphere–lower stratosphere) region, for CH4 we are able to prove that at low latitudes the MUSICA IASI processor can detect variations that take place in the free troposphere independently from the variations in the UTLS region. We demonstrate that the MUSICA IASI data qualitatively capture the CH4 gradients between low and high latitudes and between the Southern Hemisphere and Northern Hemisphere; however, we also find an inconsistency between low- and high-latitude CH4 data of up to 5 %. The N2O latitudinal gradients are very weak and cannot be detected. We make comparisons over a 10-year time period and analyse the agreement with the reference data on different timescales. The MUSICA IASI data can detect day-to-day signals (only in the UTLS), seasonal cycles and long-term evolution (in the UTLS and for CH4 also in the free troposphere) similar to the reference data; however, there are also inconsistencies in the long-term evolution connected to inconsistencies in the used atmospheric temperature a priori data.Moreover, we present a method for analytically describing the a posteriori-calculated logarithmic-scale difference of the CH4 and N2O retrieval estimates. By correcting errors that are common in the CH4 and N2O retrieval products, the a posteriori-calculated difference can be used for generating an a posteriori-corrected CH4 product with a theoretically better precision than the original CH4 retrieval products. We discuss and evaluate two different approaches for such a posteriori corrections. It is shown that the correction removes the inconsistencies between low and high latitudes and enables the detection of day-to-day signals also in the free troposphere. Furthermore, they reduce the impact of short-term atmospheric dynamics, which is an advantage, because respective signals are presumably hardly comparable to model data. The approach that affects the correction solely on the scales on which the errors dominate is identified as the most efficient, because it reduces the inconsistencies and errors without removing measurable real atmospheric signals. We give a brief outlook on a possible usage of this a posteriori-corrected MUSICA IASI CH4 product in combination with inverse modelling.

Description: The knowledge of surface ozone mole fractions and their global distribution is of utmost importance due to the impact of ozone on human health and ecosystems and the central role of ozone in controlling the oxidation capacity of the troposphere. The availability of long-term ozone records is far better in the Northern than in the Southern Hemisphere, and recent analyses of the seven accessible records in the Southern Hemisphere have shown inconclusive trends. Since late 1995, surface ozone is measured in situ at "El Tololo", a high-altitude (2200 m a.s.l.) and pristine station in Chile (30° S, 71° W). The dataset has been recently fully quality controlled and reprocessed. This study presents the observed ozone trends and annual cycles and identifies key processes driving these patterns. From 1995 to 2010, an overall positive trend of  ∼  0.7 ppb decade−1 is found. Strongest trends per season are observed in March and April. Highest mole fractions are observed in late spring (October) and show a strong correlation with ozone transported from the stratosphere down into the troposphere, as simulated with a model. Over the 20 years of observations, the springtime ozone maximum has shifted to earlier times in the year, which, again, is strongly correlated with a temporal shift in the occurrence of the maximum of simulated stratospheric ozone transport at the site. We conclude that background ozone at El Tololo is mainly driven by stratospheric intrusions rather than photochemical production from anthropogenic and biogenic precursors. The major footprint of the sampled air masses is located over the Pacific Ocean. Therefore, due to the negligible influence of local processes, the ozone record also allows studying the influence of El Niño and La Niña episodes on background ozone levels in South America. In agreement with previous studies, we find that, during La Niña conditions, ozone mole fractions reach higher levels than during El Niño conditions.

Description: Fossil fuel CO2 (CO2ff) is the major contributor of anthropogenic CO2 in the atmosphere, and accurate quantification is essential to better understand the carbon cycle. Since October 2012, we have been continuously measuring the mixing ratios of CO, CO2, CH4, and H2O at five different heights at the Beromünster tall tower, Switzerland. Air samples for radiocarbon (Δ14CO2) analysis have also been collected from the highest sampling inlet (212.5 m) of the tower on a biweekly basis. A correction was applied for 14CO2 emissions from nearby nuclear power plants (NPPs), which have been simulated with the Lagrangian transport model FLEXPART-COSMO. The 14CO2 emissions from NPPs offset the depletion in 14C by fossil fuel emissions, resulting in an underestimation of the fossil fuel component in atmospheric CO2 by about 16 %. An average observed ratio (RCO) of 13.4 ± 1.3 mmol mol−1 was calculated from the enhancements in CO mixing ratios relative to the clean-air reference site Jungfraujoch (ΔCO) and the radiocarbon-based fossil fuel CO2 mole fractions. The wintertime RCO estimate of 12.5 ± 3.3 is about 30 % higher than the wintertime ratio between in situ measured CO and CO2 enhancements at Beromünster over the Jungfraujoch background (8.7 mmol mol−1) corrected for non-fossil contributions due to strong biospheric contribution despite the strong correlation between ΔCO and ΔCO2 in winter. By combining the ratio derived using the radiocarbon measurements and the in situ measured CO mixing ratios, a high-resolution time series of CO2ff was calculated exhibiting a clear seasonality driven by seasonal variability in emissions and vertical mixing. By subtracting the fossil fuel component and the large-scale background, we have determined the regional biospheric CO2 component that is characterized by seasonal variations ranging between −15 and +30 ppm. A pronounced diurnal variation was observed during summer modulated by biospheric exchange and vertical mixing, while no consistent pattern was found during winter.

Description: Critical data selection is essential for determining representative baseline levels of atmospheric trace gases even at remote measurement sites. Different data selection techniques have been used around the world, which could potentially lead to reduced compatibility when comparing data from different stations. This paper presents a novel statistical data selection method named adaptive diurnal minimum variation selection (ADVS) based on CO2 diurnal patterns typically occurring at elevated mountain stations. Its capability and applicability were studied on records of atmospheric CO2 observations at six Global Atmosphere Watch stations in Europe, namely, Zugspitze-Schneefernerhaus (Germany), Sonnblick (Austria), Jungfraujoch (Switzerland), Izaña (Spain), Schauinsland (Germany), and Hohenpeissenberg (Germany). Three other frequently applied statistical data selection methods were included for comparison. Among the studied methods, our ADVS method resulted in a lower fraction of data selected as a baseline with lower maxima during winter and higher minima during summer in the selected data. The measured time series were analyzed for long-term trends and seasonality by a seasonal-trend decomposition technique. In contrast to unselected data, mean annual growth rates of all selected datasets were not significantly different among the sites, except for the data recorded at Schauinsland. However, clear differences were found in the annual amplitudes as well as the seasonal time structure. Based on a pairwise analysis of correlations between stations on the seasonal-trend decomposed components by statistical data selection, we conclude that the baseline identified by the ADVS method is a better representation of lower free tropospheric (LFT) conditions than baselines identified by the other methods.

Description: We present inverse modelling (top down) estimates of European methane (CH4) emissions for 2006–2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions. The inverse models infer total CH4 emissions of 26.8 (20.2–29.7) Tg CH4 yr−1 (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006–2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 Tg CH4 yr−1 (2006) to 18.8 Tg CH4 yr−1 (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3–8.2) Tg CH4 yr−1 from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain. Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between −40 and 20 % at the aircraft profile sites in France, Hungary and Poland.

Description: In this work we describe the Horizontal Ice Nucleation Chamber (HINC) as a new instrument to measure ambient ice-nucleating particle (INP) concentrations for conditions relevant to mixed-phase clouds. Laboratory verification and validation experiments confirm the accuracy of the thermodynamic conditions of temperature (T) and relative humidity (RH) in HINC with uncertainties in T of ±0.4 K and in RH with respect to water (RHw) of ±1.5 %, which translates into an uncertainty in RH with respect to ice (RHi) of ±3.0 % at T 〉 235 K. For further validation of HINC as a field instrument, two measurement campaigns were conducted in winters 2015 and 2016 at the High Altitude Research Station Jungfraujoch (JFJ; Switzerland, 3580 m a. s. l. ) to sample ambient INPs. During winters 2015 and 2016 the site encountered free-tropospheric conditions 92 and 79 % of the time, respectively. We measured INP concentrations at 242 K at water-subsaturated conditions (RHw = 94 %), relevant for the formation of ice clouds, and in the water-supersaturated regime (RHw = 104 %) to represent ice formation occurring under mixed-phase cloud conditions. In winters 2015 and 2016 the median INP concentrations at RHw = 94 % was below the minimum detectable concentration. At RHw = 104 %, INP concentrations were an order of magnitude higher, with median concentrations in winter 2015 of 2.8 per standard liter (std L−1; normalized to standard T of 273 K and pressure, p, of 1013 hPa) and 4.7 std L−1 in winter 2016. The measurements are in agreement with previous winter measurements obtained with the Portable Ice Nucleation Chamber (PINC) of 2.2 std L−1 at the same location. During winter 2015, two events caused the INP concentrations at RHw = 104 % to significantly increase above the campaign average. First, an increase to 72.1 std L−1 was measured during an event influenced by marine air, arriving at the JFJ from the North Sea and the Norwegian Sea. The contribution from anthropogenic or other sources can thereby not be ruled out. Second, INP concentrations up to 146.2 std L−1 were observed during a Saharan dust event. To our knowledge this is the first time that a clear enrichment in ambient INP concentration in remote regions of the atmosphere is observed during a time of marine air mass influence, suggesting the importance of marine particles on ice nucleation in the free troposphere.

Description: A simple statistical model to predict the number of aerosols which activate to form cloud droplets in warm clouds has been established, based on regression analysis of data from four summertime Cloud and Aerosol Characterisation Experiments (CLACE) at the high-altitude site Jungfraujoch (JFJ). It is shown that 79 % of the observed variance in droplet numbers can be represented by a model accounting only for the number of potential cloud condensation nuclei (defined as number of particles larger than 80 nm in diameter), while the mean errors in the model representation may be reduced by the addition of further explanatory variables, such as the mixing ratios of O3, CO, and the height of the measurements above cloud base. The statistical model has a similar ability to represent the observed droplet numbers in each of the individual years, as well as for the two predominant local wind directions at the JFJ (northwest and southeast). Given the central European location of the JFJ, with air masses in summer being representative of the free troposphere with regular boundary layer in-mixing via convection, we expect that this statistical model is generally applicable to warm clouds under conditions where droplet formation is aerosol limited (i.e. at relatively high updraught velocities and/or relatively low aerosol number concentrations). A comparison between the statistical model and an established microphysical parametrization shows good agreement between the two and supports the conclusion that cloud droplet formation at the JFJ is predominantly controlled by the number concentration of aerosol particles.