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Abstract Since the very beginning of the COVID-19 pandemic, control policies and restrictions have been the hope for containing the rapid spread of the virus. However, the psychological and economic toll they take on society entails the necessity to develop an optimal control strategy. Assessment of the effectiveness of these interventions aided with mathematical modelling remains a non-trivial issue in terms of numerical conditioning due to the high number of parameters to estimate from a highly noisy dataset and significant correlations between policy timings. We propose a solution to the problem of parameter non-estimability utilizing data from a set of European countries. Treating a subset of parameters as common for all countries and the rest as country-specific, we construct a set of individualized models incorporating 13 different pandemic control measures, and estimate their parameters without prior assumptions. We demonstrate high predictive abilities of these models on an independent validation set and rank the policies by their effectiveness in reducing transmission rates. We show that raising awareness through information campaigns, providing income support, closing schools and workplaces, cancelling public events, and maintaining an open testing policy have the highest potential to mitigate the pandemic.

Recent climate change mitigation strategies rely on the reduction of methane (CH4) emissions. Carbon and hydrogen isotope ratio (δ13CCH4 and δ2HCH4) measurements can be used to distinguish sources and thus to understand the CH4 budget better. The CH4 emission estimates by models are sensitive to the isotopic signatures assigned to each source category, so it is important to provide representative estimates of the different CH4 source isotopic signatures worldwide. We present new measurements of isotope signatures of various, mainly anthropogenic, CH4 sources in Europe, which represent a substantial contribution to the global dataset of source isotopic measurements from the literature, especially for δ2HCH4. They improve the definition of δ13CCH4 from waste sources, and demonstrate the use of δ2HCH4 for fossil fuel source attribution. We combined our new measurements with the last published database of CH4 isotopic signatures and with additional literature, and present a new global database. We found that microbial sources are generally well characterised. The large variability in fossil fuel isotopic compositions requires particular care in the choice of weighting criteria for the calculation of a representative global value. The global dataset could be further improved by measurements from African, South American, and Asian countries, and more measurements from pyrogenic sources. We improved the source characterisation of CH4 emissions using stable isotopes and associated uncertainty, to be used in top-down studies. We emphasise that an appropriate use of the database requires the analysis of specific parameters in relation to source type and the region of interest. The final version of the European CH4 isotope database coupled with a global inventory of fossil and non-fossil δ13CCH4 and δ2HCH4 source signature measurements is available at https://doi.org/10.24416/UU01-YP43IN (Menoud et al., 2022a).

The reasons for spatial and temporal variation in methane emission from mire ecosystems are not fully understood. Stable isotope signatures of the emitted methane can offer clues to the causes of these variations. We measured the methane emission (FCH4) and 13C signature (δ13C) of emitted methane by automated chambers at a hemiboreal mire for two growing seasons. In addition, we used ambient methane mixing ratios and δ13C to calculate a mire-scale 13C signature using a nocturnal boundary-layer accumulation approach. Microbial methanogenic and methanotrophic communities were determined by a captured metagenomics analysis. The chamber measurements showed large and systematic spatial variations in δ13C-CH4 of up to 15 ‰ but smaller and less systematic temporal variation. According to the spatial δ13C–FCH4 relations, methanotrophy was unlikely to be the dominating cause for the spatial variation. Instead, these were an indication of the substrate availability of methanogenesis being a major factor in explaining the spatial variation. Genetic analysis indicated that methanogenic communities at all sample locations were able to utilize both hydrogenotrophic and acetoclastic pathways and could thus adapt to changes in the available substrate. The temporal variation in FCH4 and δ13C over the growing seasons showed hysteresis-like behavior at high-emission locations, indicative of time-lagged responses to temperature and substrate availability. The upscaled chamber measurements and nocturnal boundary-layer accumulation measurements showed similar average δ13C values of −81.3 ‰ and −79.3 ‰, respectively, indicative of hydrogenotrophic methanogenesis at the mire. The close correspondence of the δ13C values obtained by the two methods lends confidence to the obtained mire-scale isotopic signature. This and other recently published data on δ13C values of CH4 emitted from northern mires are considerably lower than the values used in atmospheric inversion studies on methane sources, suggesting a need for revision of the model input.

The Arctic is exposed to even faster temperature changes than most other areas on Earth. Constantly increasing temperature will lead to thawing permafrost and changes in the methane (CH4) emissions from wetlands. One of the places exposed to those changes is the Abisko–Stordalen Mire in northern Sweden, where climate and vegetation studies have been conducted since the 1970s. In our study, we analyzed field-scale methane emissions measured by the eddy covariance method at Abisko–Stordalen Mire for 3 years (2014–2016). The site is a subarctic mire mosaic of palsas, thawing palsas, fully thawed fens, and open water bodies. A bimodal wind pattern prevalent at the site provides an ideal opportunity to measure mire patches with different permafrost status with one flux measurement system. The flux footprint for westerly winds was dominated by elevated palsa plateaus, while the footprint was almost equally distributed between palsas and thawing bog-like areas for easterly winds. As these patches are exposed to the same climatic and weather conditions, we analyzed the differences in the responses of their methane emission for environmental parameters. The methane fluxes followed a similar annual cycle over the 3 study years, with a gentle rise during spring and a decrease during autumn, without emission bursts at either end of the ice-free season. The peak emission during the ice-free season differed significantly for the two mire areas with different permafrost status: the palsa mire emitted 19 mg-C m−2 d−1 and the thawing wet sector 40 mg-C m−2 d−1. Factors controlling the methane emission were analyzed using generalized linear models. The main driver for methane fluxes was peat temperature for both wind sectors. Soil water content above the water table emerged as an explanatory variable for the 3 years for western sectors and the year 2016 in the eastern sector. The water table level showed a significant correlation with methane emission for the year 2016 as well. Gross primary production, however, did not show a significant correlation with methane emissions. Annual methane emissions were estimated based on four different gap-filing methods. The different methods generally resulted in very similar annual emissions. The mean annual emission based on all models was 3.1 ± 0.3 g-C m−2 a−1 for the western sector and 5.5 ± 0.5 g-C m−2 a−1 for the eastern sector. The average annual emissions, derived from these data and a footprint climatology, were 2.7 ± 0.5 and 8.2 ± 1.5 g-C m−2 a−1 for the palsa and thawing surfaces, respectively. Winter fluxes were relatively high, contributing 27 %–45 % to the annual emissions.