During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO ₂ ) exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we characterize the resulting perturbation of the atmospheric CO ₂ seasonal cycles. 2018 has a good coverage of European regions affected by drought, allowing the investigation of how ecosystem flux anomalies impacted spatial CO ₂ gradients between stations. This density of stations is unprecedented compared to previous drought events in 2003 and 2015, particularly thanks to the deployment of the Integrated Carbon Observation System (ICOS) network of atmospheric greenhouse gas monitoring stations in recent years. Seasonal CO ₂ cycles from 48 European stations were available for 2017 and 2018. Earlier data were retrieved for comparison from international databases or national networks. Here, we show that the usual summer minimum in CO ₂ due to the surface carbon uptake was reduced by 1.4 ppm in 2018 for the 10 stations located in the area most affected by the temperature anomaly, mostly in Northern Europe. Notwithstanding, the CO ₂ transition phases before and after July were slower in 2018 compared to 2017, suggesting an extension of the growing season, with either continued CO ₂ uptake by photosynthesis and/or a reduction in respiration driven by the depletion of substrate for respiration inherited from the previous months due to the drought. For stations with sufficiently long time series, the CO ₂ anomaly observed in 2018 was compared to previous European droughts in 2003 and 2015. Considering the areas most affected by the temperature anomalies, we found a higher CO ₂ anomaly in 2003 (+3 ppm averaged over 4 sites), and a smaller anomaly in 2015 (+1 ppm averaged over 11 sites) compared to 2018. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

We present a novel high-resolution inverse modelling system (“FLEXVAR”) based on FLEXPART-COSMO back trajectories driven by COSMO meteorological fields at 7 km×7 km resolution over the European COSMO-7 domain and the four-dimensional variational (4DVAR) data assimilation technique. FLEXVAR is coupled offline with the global inverse modelling system TM5-4DVAR to provide background mole fractions (“baselines”) consistent with the global observations assimilated in TM5-4DVAR. We have applied the FLEXVAR system for the inverse modelling of European CH₄ emissions in 2018 using 24 stations with in situ measurements, complemented with data from five stations with discrete air sampling (and additional stations outside the European COSMO-7 domain used for the global TM5-4DVAR inversions). The sensitivity of the FLEXVAR inversions to different approaches to calculate the baselines, different parameterizations of the model representation error, different settings of the prior error covariance parameters, different prior inventories, and different observation data sets are investigated in detail. Furthermore, the FLEXVAR inversions are compared to inversions with the FLEXPART extended Kalman filter (“FLExKF”) system and with TM5-4DVAR inversions at $\mathrm{1}{}^{\circ }\times \mathrm{1}{}^{\circ }$ resolution over Europe. The three inverse modelling systems show overall good consistency of the major spatial patterns of the derived inversion increments and in general only relatively small differences in the derived annual total emissions of larger country regions. At the same time, the FLEXVAR inversions at 7 km×7 km resolution allow the observations to be better reproduced than the TM5-4DVAR simulations at $\mathrm{1}{}^{\circ }\times \mathrm{1}{}^{\circ }$ . The three inverse models derive higher annual total CH₄ emissions in 2018 for Germany, France, and BENELUX compared to the sum of anthropogenic emissions reported to UNFCCC and natural emissions estimated from the Global Carbon Project CH₄ inventory, but the uncertainty ranges of top-down and bottom-up total emission estimates overlap for all three country regions. In contrast, the top-down estimates for the sum of emissions from the UK and Ireland agree relatively well with the total of anthropogenic and natural bottom-up inventories.

We describe and implement a data selection algorithm aimed at identifying background atmospheric CO₂ observations from in situ continuous measurements. Several selection criteria for detecting the background data have been developed and are currently used: the main objective of this work was to define a common methodology to extract the atmospheric background signal minimizing heterogeneities due to the use of different selection algorithms. The algorithm used in this study, (BaDS, Background Data Selection) was tested and optimized using data (from 2014 to 2018) from four Italian stations characterized by markedly different environmental conditions (i.e., mountain, coastal and marine): Plateau Rosa (PRS), Mt. Cimone (CMN), Capo Granitola (CGR) and Lampedusa (LMP). Their locations extend from the Alps to the central Mediterranean. The adopted algorithm proved to be effective in separating the local/regional from the background signal in the CO₂ time series. About 6% of the data at LMP, 11% at PRS, 20–38% at CMN and 65% at CGR were identified as non-background. LMP and PRS can be used as reference sites for the central Mediterranean, while CMN and CGR were more impacted by regional sources and sinks. Finally, we discuss a possible application of BaDS screened data.

Several studies investigated the possible impacts of the restriction measures related to the containment of the spread of the COrona VIrus Disease (COVID-19) to atmospheric ozone (O₃) at global, regional, and local scales during 2020. O₃ is a secondary pollutant with adverse effects on population health and ecosystems and with negative impacts on climate, acting as greenhouse gas. Most of these studies focused on spring 2020 (i.e. March–May) and on observations in the planetary boundary layer (PBL), mostly in the vicinity of urban agglomerates. Here, we analyzed the variability of O₃ above the PBL of northern Italy in 2020 by using continuous observations carried out at a high mountain WMO/GAW global station in Italy (Mt. Cimone–CMN; 44°12′ N, 10°42′ E, 2165 m a.s.l.). Low O₃ monthly anomalies were observed during spring (MAM) and summer (JJA), when periods of low O₃ intertwined with periods with higher O₃, within climatological ranges. A similar variability was observed for O₃ precursors like NO₂ and 15 anthropogenic non-methane volatile organic carbons, but the systematic O₃ anomalies were not reflected in these variables. The analysis of meteorological variables and diel O₃ cycles did not suggest major changes in the vertical transport related to the thermal circulation system in the mountain area. The analysis of five days back-trajectories suggested that the observed O₃ anomalies cannot be explained by differences in the synoptic-scale circulation with respect to the previous years alone. On the other hand, the characterization of two transport patterns (i.e. air masses from the regional PBL or from the free troposphere) and the analysis of back-trajectories suggested an important contribution of transport from the continental PBL during the periods with the lowest O₃ at CMN. When proxies of air mass transport from the regional PBL are considered, a lower NO _x content was pointed out with respect to the previous years, suggesting a lower O₃ production in a NO _x -limited atmosphere. Our study suggested for the first time that, during MAM and JJA 2020, the reduced anthropogenic emissions related to the COVID-19 restrictions lowered the amount of this short-lived climate forcer/pollutant at remote locations above the PBL over northern Italy. This work suggests the importance of limiting anthropogenic precursor emissions for decreasing the O₃ amount at remote locations and in upper atmospheric layers.