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Methane is the second-most important greenhouse gas after carbon dioxide and accounts for around 10 % of total European Union greenhouse gas emissions. Given that the atmospheric methane budget over a region depends on its terrestrial and aquatic methane sources, inverse modelling techniques appear as powerful tools for identifying critical areas that can later be submitted to emission mitigation strategies. In this regard, an inverse modelling system of methane emissions for Europe is being implemented based on the Weather Research and Forecasting (WRF) model: the Aarhus University Methane Inversion Algorithm (AUMIA) v1.0. The forward modelling component of AUMIA consists of the WRF model coupled to a multipurpose global database of methane anthropogenic emissions. To assure transport consistency during the inversion process, the backward modelling component will be based on the WRF model coupled to a Lagrangian particle dispersion module. A description of the modelling tools, input data sets, and 1-year forward modelling evaluation from 1 April 2018 to 31 March 2019 is provided in this paper. The a posteriori methane emission estimates, including a more focused inverse modelling for Denmark, will be provided in a second paper. A good general agreement is found between the modelling results and observations based on the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite. Model–observation discrepancies for the summer peak season are in line with previous studies conducted over urban areas in central Europe, with relative differences between simulated concentrations and observational data in this study ranging from 1 % to 2 %. Domain-wide correlation coefficients and root-mean-square errors for summer months ranged from 0.4 to 0.5 and from 27 to 30 ppb, respectively. On the other hand, model–observation discrepancies for winter months show a significant overestimation of anthropogenic emissions over the study region, with relative differences ranging from 2 % to 3 %. Domain-wide correlation coefficients and root-mean-square errors in this case ranged from 0.1 to 0.4 and from 33 to 50 ppb, respectively, indicating that a more refined inverse analysis assessment will be required for this season. According to modelling results, the methane enhancement above the background concentrations came almost entirely from anthropogenic sources; however, these sources contributed with only up to 2 % to the methane total-column concentration. Contributions from natural sources (wetlands and termites) and biomass burning were not relevant during the study period. The results found in this study contribute with a new model evaluation of methane concentrations over Europe and demonstrate a huge potential for methane inverse modelling using improved TROPOMI products in large-scale applications. [ABSTRACT FROM AUTHOR]

Methane is the second most important greenhouse gas after carbon dioxide, and accounts for around 10 % of total European Union greenhouse gases emissions. Given that the atmospheric methane budget over a region depends on its terrestrial and aquatic methane sources, inverse modeling techniques appear as a powerful tools for identifying critical areas that can later be submitted to emission mitigation strategies. In this regard, an inverse modeling system of methane emissions for Europe is being implemented based on the Weather Research and Forecasting (WRF) model: the Aarhus University Methane Inversion Algorithm (AUMIA) v1.0. The forward modeling component of AUMIA consists of the WRF model coupled to a multipurpose global database of methane anthropogenic emissions. To assure transport consistency during the inversion process, the backward modeling component will be based on the WRF model coupled to a lagrangian particle dispersion module. A description of the modeling tools, input data sets and one-year forward modeling evaluation from April 01, 2018 to March 31, 2019 is provided in this paper. The a posteriori methane emission estimates, including a more focused inverse modeling for Denmark, will be provided in a second paper. A good general agreement is found between the modeling results and observations based on the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite. Model-observation discrepancies for summer peak season are in line with previous studies conducted over urban areas in central Europe, with relative differences between simulated concentrations and observational data in this study ranging from 1 to 2%. Domain-wide correlation coefficients and root-mean-square-errors for summer months ranged from 0.4 to 0.5 and from 27 to 30 ppb, respectively. For winter months, otherwise, model-observation discrepancies show a significant overestimation of anthropogenic emissions over the study region, with relative differences ranging from 2 to 3%. Domain-wide correlation coefficients and root-mean-square-errors in this case ranged from 0.1 to 0.4 and from 33 to 50 ppb, respectively, indicating that a more refined inverse analysis assessment will be required for this season. According to modeling results, the methane enhancement above the background concentrations came almost entirely from anthropogenicsources; however, these sources contributed with only up to 2 % to the methane total column concentration. Contributions from natural sources (wetlands and termites) and biomass burning were not relevant during the study period. The results found in this study contribute with a new model evaluation of methane concentrations over Europe, and demonstrate a huge and under explored potential for methane inverse modeling using improved TROPOMI products in large-scale applications. [ABSTRACT FROM AUTHOR]

Assessing long-term trends in flood losses and attributing them to climatic and socio-economic changes requires comprehensive and systematic collection of historical information. Here, we present flood impact data for Europe that is part of the HANZE (Historical Analysis of Natural HaZards) database. The dataset covers riverine, pluvial, coastal and compound floods that have occurred in 42 European countries between 1870 and 2020. The data was obtained by extensive data-collection from more than 800 sources ranging from news reports through government databases to scientific papers. The dataset includes 2521 events characterized by at least one impact statistic: area inundated, fatalities, persons affected or economic loss. Economic losses are presented both in the original currencies and price levels as well as inflation and exchange-rate adjusted to the 2020 value of the euro. The spatial footprint of affected areas is consistently recorded using more than 1400 subnational units corresponding, with minor exceptions, to the European Union's Nomenclature of Territorial Units for Statistics (NUTS), level 3. Daily start and end dates, information on causes of the event, notes on data quality issues or associated non-flood impacts, and full bibliography of each record supplement the dataset. Apart from the possibility to download the data (https://dx.doi.org/10.5281/zenodo.8410025), the database can be viewed, filtered and visualized online: https://naturalhazards.eu. The dataset is designed to be complementary to HANZE-Exposure, a high-resolution model of historical exposure changes (such as population and asset value), and be easily usable in statistical and spatial analyses, including multi-hazard studies. [ABSTRACT FROM AUTHOR]

Atmospheric inversions have been used for the past two decades to derive large-scale constraints on the sources and sinks of CO2 into the atmosphere. The development of dense in situ surface observation networks, such as ICOS in Europe, enables in theory inversions at a resolution close to the country scale in Europe. This has led to the development of many regional inversion systems capable of assimilating these high-resolution data, in Europe and elsewhere. The EUROCOM (European atmospheric transport inversion comparison) project is a collaboration between seven European research institutes, which aims at producing a collective assessment of the net carbon flux between the terrestrial ecosystems and the atmosphere in Europe for the period 2006–2015. It aims in particular at investigating the capacity of the inversions to deliver consistent flux estimates from the country scale up to the continental scale. The project participants were provided with a common database of in situ-observed CO2 concentrations (including the observation sites that are now part of the ICOS network) and were tasked with providing their best estimate of the net terrestrial carbon flux for that period, and for a large domain covering the entire European Union. The inversion systems differ by the transport model, the inversion approach, and the choice of observation and prior constraints, enabling us to widely explore the space of uncertainties. This paper describes the intercomparison protocol and the participating systems, and it presents the first results from a reference set of inversions, at the continental scale and in four large regions. At the continental scale, the regional inversions support the assumption that European ecosystems are a relatively small sink (-0.21±0.2 Pg C yr -1). We find that the convergence of the regional inversions at this scale is not better than that obtained in state-of-the-art global inversions. However, more robust results are obtained for sub-regions within Europe, and in these areas with dense observational coverage, the objective of delivering robust country-scale flux estimates appears achievable in the near future. [ABSTRACT FROM AUTHOR]

The European PreInstrumental earthquake CAtalogue EPICA (Rovida and Antonucci, 2021; https://doi.org/10.13127/epica.1.1) is the 1000-1899 seismic catalogue compiled for the European Seismic Hazard Model 2020 (ESHM20), an outcome of the project Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe (SERA), in the framework of the European Union's Horizon 2020 research and innovation programme. EPICA is the update of the SHARE European Earthquake Catalogue SHEEC 1000-1899, with which it shares the main principles - mostly transparency, repeatability, and continent wide harmonization of data - as well as the compilation strategies and methods. The version 1.1 of EPICA contains 5703 earthquakes with either maximum intensity ≥5 or Mw ≥4.0, with a spatial coverage from the Atlantic Ocean to the west to 32°E in longitude, and from the Mediterranean Sea to northernmost Europe. EPICA relies upon the updated knowledge of European preinstrumental seismicity provided by the data gathered in the European Archive of Historical Earthquake Data AHEAD. Such data are both macroseismic intensity data supplied by descriptive historical seismological studies and online macroseismic databases, and parameters contained in regional catalogues. As done for the compilation of SHEEC 1000-1899, these datasets were thoroughly analysed in order to select the most representative of the knowledge of each earthquake, independently from national constraints. Selected intensity distributions are processed with three methods to determine location and magnitude based on the attenuation of macroseismic intensity and are combined with parameters harmonised from modern regional catalogues. This paper describes the compilation procedure of EPICA version 1.1, its input data, the assessment of the earthquake parameters and the resulting catalogue, which is finally compared with its previous version. Technical solutions for accessing the catalogue, both as downloadable files and through webservices. [ABSTRACT FROM AUTHOR]

Ammonia (NH 3), a significant precursor of particulate matter, affects not only biodiversity, ecosystems, and soil acidification but also climate and human health. In addition, its concentrations are constantly rising due to increasing feeding needs and the large use of fertilization and animal farming. Despite the significance of ammonia, its emissions are associated with large uncertainties, while its atmospheric abundance is difficult to measure. Nowadays, satellite products can effectively measure ammonia with low uncertainty and a global coverage. Here, we use satellite observations of column ammonia in combination with an inversion algorithm to derive ammonia emissions with a high resolution over Europe for the period 2013–2020. Ammonia emissions peak in northern Europe due to agricultural application and livestock management, in western Europe (industrial activity), and over Spain (pig farming). Emissions have decreased by - 26 % since 2013 (from 5431 Gg in 2013 to 3994 Gg in 2020), showing that the abatement strategies adopted by the European Union have been very efficient. The slight increase (+ 4.4 %) in 2015 is also reproduced here and is attributed to some European countries exceeding annual emission targets. Ammonia emissions are low in winter (286 Gg) and peak in summer (563 Gg) and are dominated by the temperature-dependent volatilization of ammonia from the soil. The largest emission decreases were observed in central and eastern Europe (- 38 %) and in western Europe (- 37 %), while smaller decreases were recorded in northern (- 17 %) and southern Europe (- 7.6 %). When complemented with ground observations, modelled concentrations using the posterior emissions showed improved statistics, also following the observed seasonal trends. The posterior emissions presented here also agree well with respective estimates reported in the literature and inferred from bottom-up and top-down methodologies. These results indicate that satellite measurements combined with inverse algorithms constitute a robust tool for emission estimates and can infer the evolution of ammonia emissions over large timescales. [ABSTRACT FROM AUTHOR]

This study introduces an Earth observation (EO)-based system which is capable of operationally estimating and continuously monitoring the ultraviolet index (UVI) in Europe. UVIOS (i.e., UV-Index Operating System) exploits a synergy of radiative transfer models with high-performance computing and EO data from satellites (Meteosat Second Generation and Meteorological Operational Satellite-B) and retrieval processes (Tropospheric Emission Monitoring Internet Service, Copernicus Atmosphere Monitoring Service and the Global Land Service). It provides a near-real-time nowcasting and short-term forecasting service for UV radiation over Europe. The main atmospheric inputs for the UVI simulations include ozone, clouds and aerosols, while the impacts of ground elevation and surface albedo are also taken into account. The UVIOS output is the UVI at high spatial and temporal resolution (5 km and 15 min, respectively) for Europe (i.e., 1.5 million pixels) in real time. The UVI is empirically related to biologically important UV dose rates, and the reliability of this EO-based solution was verified against ground-based measurements from 17 stations across Europe. Stations are equipped with spectral, broadband or multi-filter instruments and cover a range of topographic and atmospheric conditions. A period of over 1 year of forecasted 15 min retrievals under all-sky conditions was compared with the ground-based measurements. UVIOS forecasts were within ± 0.5 of the measured UVI for at least 70 % of the data compared at all stations. For clear-sky conditions the agreement was better than 0.5 UVI for 80 % of the data. A sensitivity analysis of EO inputs and UVIOS outputs was performed in order to quantify the level of uncertainty in the derived products and to identify the covariance between the accuracy of the output and the spatial and temporal resolution and the quality of the inputs. Overall, UVIOS slightly overestimated the UVI due to observational uncertainties in inputs of cloud and aerosol. This service will hopefully contribute to EO capabilities and will assist the provision of operational early warning systems that will help raise awareness among European Union citizens of the health implications of high UVI doses. [ABSTRACT FROM AUTHOR]

Halogen (Cl , Br, and I) chemistry has been reported to influence the formation of secondary air pollutants. Previous studies mostly focused on the impact of chlorine species on air quality over large spatial scales. Very little attention has been paid to the effect of the combined halogen chemistry on air quality over Europe and its implications for control policy. In the present study, we apply a widely used regional model, the Community Multiscale Air Quality Modeling System (CMAQ), incorporated with the latest halogen sources and chemistry, to simulate the abundance of halogen species over Europe and to examine the role of halogens in the formation of secondary air pollution. The results suggest that the CMAQ model is able to reproduce the level of O3 , NO2 , and halogen species over Europe. Chlorine chemistry slightly increases the levels of OH , HO2 , NO3 , O3 , and NO2 and substantially enhances the level of the Cl radical. Combined halogen chemistry induces complex effects on OH (ranging from -0.023 to 0.030 pptv) and HO2 (in the range of -3.7 to 0.73 pptv), significantly reduces the concentrations of NO3 (as much as 20 pptv) and O3 (as much as 10 ppbv), and decreases NO2 in highly polluted regions (as much as 1.7 ppbv); it increases NO2 (up to 0.20 ppbv) in other areas. The maximum effects of halogen chemistry occur over oceanic and coastal regions, but some noticeable impacts also occur over continental Europe. Halogen chemistry affects the number of days exceeding the European Union target threshold for the protection of human beings and vegetation from ambient O3. In light of the significant impact of halogen chemistry on air quality, we recommend that halogen chemistry be considered for inclusion in air quality policy assessments, particularly in coastal cities. [ABSTRACT FROM AUTHOR]