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Soil bulk density (BD) serves as a fundamental indicator of soil health and quality, exerting a significant influence on critical factors such as plant growth, nutrient availability, and water retention. Due to its limited availability in soil databases, the application of pedotransfer functions (PTFs) has emerged as a potent tool for predicting BD using other easily measurable soil properties, while the impact of these PTFs' performance on soil organic carbon (SOC) stock calculation has been rarely explored. In this study, we proposed an innovative local modeling approach for predicting BD of fine earth (BDfine) across Europe using the recently released BDfine data from the LUCAS Soil (Land Use and Coverage Area Frame Survey Soil) 2018 (0–20 cm) and relevant predictors. Our approach involved a combination of neighbor sample search, forward recursive feature selection (FRFS), and random forest (RF) models (local- RFFRFS). The results showed that local- RFFRFS had a good performance in predicting BDfine (R2 of 0.58, root mean square error (RMSE) of 0.19 gcm-3 , relative error (RE) of 16.27 %), surpassing the earlier-published PTFs (R2 of 0.40–0.45, RMSE of 0.22 gcm-3 , RE of 19.11 %–21.18 %) and global PTFs using RF models with and without FRFS (R2 of 0.56–0.57, RMSE of 0.19 gcm-3 , RE of 16.47 %–16.74 %). Interestingly, we found that the best earlier-published PTF (R2 = 0.84, RMSE = 1.39 kgm-2 , RE of 17.57 %) performed close to the local- RFFRFS (R2 = 0.85, RMSE = 1.32 kgm-2 , RE of 15.01 %) in SOC stock calculation using BDfine predictions. However, the local- RFFRFS still performed better (ΔR2 > 0.2) for soil samples with low SOC stocks (< 3 kgm-2). Therefore, we suggest that the local- RFFRFS is a promising method for BDfine prediction, while earlier-published PTFs would be more efficient when BDfine is subsequently utilized for calculating SOC stock. Finally, we produced two topsoil BDfine and SOC stock datasets (18 945 and 15 389 soil samples) at 0–20 cm for LUCAS Soil 2018 using the best earlier-published PTF and local- RFFRFS , respectively. This dataset is archived on the Zenodo platform at https://doi.org/10.5281/zenodo.10211884 (S. Chen et al., 2023). The outcomes of this study present a meaningful advancement in enhancing the predictive accuracy of BDfine , and the resultant BDfine and SOC stock datasets for topsoil across the Europe enable more precise soil hydrological and biological modeling. [ABSTRACT FROM AUTHOR]

Large hail (greater than 2 cm in diameter) can cause devastating damage to crops and property and can even cause loss of life. Because hail reports are often collected by individual countries, constructing a Europe-wide large-hail climatology has been challenging to date. However, the European Severe Storm Laboratory's European Severe Weather Database provides the only pan-European dataset for severe convective-storm reports. The database is comprised of 62 053 large-hail reports from 40 CE to September 2020, yet its characteristics have not been evaluated. Thus, the purpose of this study is to evaluate hail reports from this database for constructing a climatology of large hail. For the period 2000–2020, large-hail reports are most prominent in June, whereas large-hail days are most common in July. Large hail is mostly reported between 13:00–19:00 local time, a consistent pattern since 2010. The intensity, as measured by maximum hail size, shows decreasing frequency with increasing hailstone diameter and little change over the 20-year period. The quality of reports by country varies, with the most complete reporting being from central European countries. Thus, results suggest that despite its short record, many indications point to the dataset representing some reliable aspects of the European large-hail climatology, albeit with some limitations. [ABSTRACT FROM AUTHOR]

Soil bulk density (BD) serves as a fundamental indicator of soil health and quality, exerting a significant influence on critical factors such as plant growth, nutrient availability, and water retention. Due to its limited availability in soil databases, the application of pedotransfer functions (PTFs) has emerged as a potent tool for predicting BD using other easily measurable soil properties, while the impact of these PTFs' accuracy on soil organic carbon (SOC) stock calculation has been rarely explored. In this study, we proposed an innovative local modelling approach for predicting BD across Europe using the recently released BD data from the LUCAS Soil 2018 (0-20 cm). Our approach involved a combination of neighbour sample search, Forward Recursive Feature Selection (FRFS) and Random Forest (RF) model (local-RFFRFS). The results showed that local-RFFRFS had a good performance in predicting BD (R² of 0.58, RMSE of 0.19 g cm-3), surpassing the traditional PTFs (R² of 0.40-0.45, RMSE of 0.22 g cm-3) and global PTFs using RF with and without FRFS (R² of 0.56-0.57, RMSE of 0.19 g cm-3). Interestingly, we found the best traditional PTF (R²=0.84, RMSE=1.39 kg m-2) performed close to the local-RFFRFS (R²=0.85, RMSE=1.32 kg m-2) in SOC stock calculation using BD predictions. However, the local-RFFRFS still performed better (ΔR²>0.2 and ΔRMSE>0.1 g cm-3) for soil samples with low SOC stock (<3 kg m-2). Therefore, we suggest that the local-RFFRFS is a promising method for BD prediction while traditional PTFs would be more efficient when BD is subsequently utilized for calculating SOC stock. Finally, we produced two BD and SOC stocks datasets (18,945 and 15,389 soil samples) for LUCAS Soil 2018 using the best traditional PTF and local-RFFRFS, respectively. This dataset is archived from the Zenodo platform at https://zenodo.org/records/10211884 (Chen et al., 2023). The outcomes of this study present a meaningful advancement in enhancing the predictive accuracy of BD, and the resultant BD and SOC stock datasets across the Europe enable more precise soil hydrological and biological modelling. [ABSTRACT FROM AUTHOR]

Coastal flooding is recognized as one of the most devastating natural disasters, resulting in significant economic losses. Therefore, hazard assessment is crucial to support preparedness and response to such disasters. Toward this, flood map databases and catalogues are essential for the analysis of flood scenarios, and furthermore they can be integrated into disaster risk reduction studies. In this study and in the context of the European Coastal Flood Awareness System (ECFAS) project (GA 101004211), which aimed to propose the European Copernicus Coastal Flood Awareness System, a catalogue of flood maps was produced. The flood maps were generated from flood models developed with LISFLOOD-FP for defined coastal sectors along the entire European coastline. For each coastal sector, 15 synthetic scenarios were defined focusing on high-frequency events specific to the local area. These scenarios were constructed based on three distinct storm durations and five different total-water-level (TWL) peaks incorporating tide, mean sea level, surge and wave setup components. The flood model method was extensively validated against 12 test cases for which observed data were collated using satellite-derived flood maps and in situ flood markers. Half of the test cases represented well the flooding with hit scores higher than 80 %. The synthetic-scenario approach was assessed by comparing flood maps from real events and their closest identified scenarios, producing a good agreement and global skill scores higher than 70 %. Using the catalogue, flood scenarios across Europe were assessed, and the biggest flooding occurred in well-known low-lying areas. In addition, different sensitivities to the increase in the duration and TWL peak were noted. The storm duration impacts a few limited flood-prone areas such as the Dutch coast, for which the flooded area increases more than twice between 12 and 36 h storm scenarios. The influence of the TWL peak is more global, especially along the Mediterranean coast, for which the relative difference between a 2- and 20-year return period storm is around 80 %. Finally, at a European scale, the expansion of flood areas in relation to increases in TWL peaks demonstrated both positive and negative correlations with the presence of urban and wetland areas, respectively. This observation supports the concept of storm flood mitigation by wetlands. [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]

During the Last Glacial Period, the climate shift to cold conditions associated with changes in atmospheric circulation and vegetation cover resulted in the development of large aeolian systems in Europe. On a regional scale, many factors may have influenced dust dynamics, such as the latitudinal difference between the various aeolian systems and the variability of the sources of wind-transported particles. Therefore, the assumption that the timing of aeolian deposition is strictly synchronous in Europe does not seem to be the most plausible hypothesis and needs to be evaluated. To test this assumption, the chronology of loess deposition in different European regions was investigated by studying 93 luminescence-dated loess–palaeosol sequences with their data recalculated and compiled in a single comma separated values (*.csv) file: the ChronoLoess database. Our study shows that the two major aeolian systems, the Northern European Loess Belt (NELB) on the one hand and the systems associated with the rivers draining the Alpine Ice Sheet on the other hand, developed asynchronously. The significant deposition started at about 32 kyr b2k for the NELB vs. 42 kyr b2k for the perialpine loess and peaked about 2 millennia later for the former (21.8 vs. 23.9 kyr b2k, respectively). This shift resulted mainly from the time lag between the maxima of the Alpine and Fennoscandian ice sheets, which acted as the primary sources of fine-grained particles through glacial abrasion. The major geomorphic changes that resulted from the development and decay of the Fennoscandian and British–Irish ice sheets also played an important role. Particularly, ice sheet coalescence during the Last Glacial Maximum (LGM) diverted meltwater fluxes through the Channel River and provided vast amounts of glacial particles available for deflation in the western NELB. The period during which the maximum mass accumulation rate was reached for each loess–palaeosol sequence is relatively homogeneous in the NELB and ranges from 30 to 19 kyr b2k, whereas it is more scattered in the perialpine systems (>60 to 14 kyr b2k). This probably resulted from a combination of factors, including the asynchrony of maximum valley glacier advances and local geomorphic factors. The ChronoLoess database is available at 10.5281/zenodo.7728616 (Bosq et al., 2023). [ABSTRACT FROM AUTHOR]

Coastal flooding is recognized as one of the most devastating natural disasters, resulting in significant economic losses. Therefore, hazard assessment is crucial to support preparedness and response to such disasters. Toward this, flood map databases and catalogues are essential for the analysis of flood scenarios, and furthermore can be integrated into disaster risk reduction studies. In this study and in the context of the ECFAS project (GA 101004211), which aimed to propose a European Copernicus Coastal Flood Awareness System, a catalogue of flood maps was produced. The flood maps were generated from flood models developed with LISFLOOD-FP for defined coastal sectors along the entire European coastline. For each coastal sector, fifteen synthetic scenarios were defined focusing on high-frequency events specific to the local area. These scenarios were constructed based on three distinct storm durations and five different Total Water Level (TWL) peaks incorporating tide, mean sea level, surge and wave set-up components. The flood model method was extensively validated against twelve test cases for which observed data were collated using satellite-derived flood maps and in situ flood markers. Half of the test-cases well represented the flooding with hit scores higher than 80 %. The synthetic scenario approach was assessed by comparing flood maps from real events and their closest identified scenarios, producing a good agreement and global skill scores higher than 70 %. Using the catalogue, flood scenarios across Europe were assessed, and the biggest flooding occurred in well-known low-lying areas. In addition, different sensitivities to the increase of the duration and TWL peak were noted. The storm duration impacts a few limited flood prone areas such as the Dutch coast for which the flooded area increases more than twice between a 12 h and 36 h storm scenarios. The influence of the TWL peak is more global, especially along the Mediterranean coast for which the relative difference between a 2- and 20-year return period storm is around 80 %. Finally, at a European scale, the expansion of flood areas in relation to increases in TWL (Total Water Level) peaks demonstrated both positive and negative correlations with the presence of urban and wetland areas, respectively. This observation supports the concept of storm flood mitigation by wetlands. [ABSTRACT FROM AUTHOR]

Large hail (greater than 2 cm in diameter) can cause devastating damage to crops and property, and can even cause loss of life. Because hail reports are often collected by individual countries, constructing a European-wide large-hail climatology has been challenging to date. However, the European Severe Storm Laboratory's European Severe Weather Database provides the only pan-European dataset for severe convective storms. The database is comprised of 62,053 large-hail reports from 40 C.E. to September 2020, yet its characteristics have not been evaluated. Thus, the purpose of this study is to evaluate this database for the purposes of constructing a climatology of large hail. For the period 2000–2020, large-hail reports are most prominent in June, whereas large-hail days are most common in July. Large hail is mostly reported between 1300–1900 local time, a consistent pattern since 2010. The intensity, as measured by maximum hail size, shows decreasing frequency with increasing hailstone diameter, and no change over the 20-year period. The quality of reports by country varies, with the most complete reporting being from central European countries. These results suggest that despite its short record, many indications are that the dataset represents some reliable aspects of European large-hail climatology, albeit with some limitations. [ABSTRACT FROM AUTHOR]

Strong winds may uproot and break trees and represent one of the major natural disturbances for European forests. Wind disturbances have intensified over the last decades globally and are expected to further rise in view of the climate change effects. Despite the importance of such natural disturbances, there are currently no spatially-explicit databases of wind-related impact at Pan-European scale. Here, we present a new database of wind disturbances in European forests (FORWIND). FORWIND comprises more than 80,000 spatially delineated areas in Europe that were disturbed by wind in the period 2000–2018, and describes them in a harmonized and consistent geographical vector format. Correlation analyses performed between the areas in FORWIND and land cover changes retrieved from the Landsat-based Global Forest Change dataset and the MODIS Global Disturbance Index corroborate the robustness of FORWIND. Spearman rank coefficients range between 0.27 and 0.48 (p-value<0.05). When recorded forest areas are rescaled based on their damage degree, correlation increases to 0.54. Wind-damaged growing stock volumes reported in national inventories (FORESTORM dataset) are generally higher than analogous metrics provided by FORWIND in combination with satellite-based biomass and country-scale statistics of growing stock volume. Overall, FORWIND represents a valuable and open-access spatial source to improve our understanding of the vulnerability of forests to winds and develop large-scale monitoring/modelling of natural disturbances. Data sharing is encouraged in order to continuously update and improve FORWIND. [ABSTRACT FROM AUTHOR]

The Radioactivity Environmental Monitoring data bank (REMdb) was created in the aftermath of the Chernobyl accident (1986) by the European Commission (EC) – Directorate-General Joint Research Centre (DG JRC), sited in Ispra (Italy). Since then it has been maintained there with the aim to keep a historical record of the Chernobyl accident and to store the radioactivity monitoring data gathered through the national environmental monitoring programs of the member states (MSs). The legal basis is the Euratom Treaty, Chapter III Health and Safety, Articles 35 and 36, which clarify that MSs shall periodically communicate to the EC information on environmental radioactivity levels. By collecting and validating this information in REMdb, JRC supports the DG for Energy in its responsibilities in returning qualified information to the MSs (competent authorities and general public) on the levels of radioactive contamination of the various compartments of the environment (air, water, soil) on the European Union scale. REMdb accepts data on radionuclide concentrations from EU MSs in both environmental samples and foodstuffs from 1984 onwards. To date, the total number of data records stored in REMdb exceeds 5 million, in this way providing the scientific community with a valuable archive of environmental radioactivity topics in Europe. Records stored in REMdb are publicly accessible until 2011 through an unrestricted repository “REM data bank – Years 1984–2006” https://doi.org/10.2905/jrc-10117-10024 (De Cort et al., 2007) and “REM data bank – Years 2007–2011” https://doi.org/10.2905/de42f259-fafe-4329-9798-9d8fabb98de5 (De Cort et al., 2012). Access to data from 2012 onwards is granted only after explicit request, until the corresponding monitoring report is published. Each data record contains information describing the sampling circumstances (sampling type, begin and end time), measurement conditions (value, nuclide, apparatus, etc.), location and date of sampling, and original data reference. In this paper the scope, features and extension of REMdb are described in detail. [ABSTRACT FROM AUTHOR]

Drought is a natural hazard that can cause a wide range of impacts affecting the environment, society, and the economy. Assessing and reducing vulnerability to these impacts for regions beyond the local scale, spanning political and sectoral boundaries, requires systematic and detailed data regarding impacts. This study presents an assessment of the diversity of drought impacts across Europe based on the European Drought Impact report Inventory (EDII), a unique research database that has collected close to 5000 impact reports from 33 European countries. The reported drought impacts were classified into major impact categories, each of which had a number of subtypes. The distribution of these categories and types was then analyzed over time, by country, across Europe and for particular drought events. The results show that impacts on agriculture and public water supply dominate the collection of drought impact reports for most countries and for all major drought events since the 1970s, while the number and relative fractions of reported impacts in other sectors can vary regionally and from event to event. The data also shows that reported impacts have increased over time as more media and website information has become available and environmental awareness has increased. Even though the distribution of impact categories is relatively consistent across Europe, the details of the reports show some differences. They confirm severe impacts in southern regions (particularly on agriculture and pub20 lic water supply) and sector-specific impacts in central and northern regions (e.g. on forestry or energy production). As a text-based database, the EDII presents a new challenge for quantitative analysis; however, the EDII provides a new and more comprehensive view on drought impacts. Related studies have already developed statistical techniques to evaluate the link between drought indices and impacts using the EDII. The EDII is a living database and is a promising source for further research on drought impacts, vulnerabilities, and risks across Europe. A key result is the extensive variety of impacts found across Europe and its documentation. This data coverage may help drought policy planning at national to international levels. [ABSTRACT FROM AUTHOR]

This work is an extended evaluation of near surface ozone as part of the global reanalysis of atmospheric composition, produced within the European Funded project MACC (Monitoring Atmospheric Composition and Climate). It includes an evaluation over the period 2003-2012 and provides an overall assessment of the modelling system performance with respect to near surface ozone for specific European subregions. Measurements at rural locations from the European Monitoring and Evaluation Program (EMEP) and the European Air Quality Database (AirBase) were used for the evaluation assessment. The annual overall error of near surface ozone reanalysis is on average 24% over Europe, the highest found over Scandinavia (27%) and the lowest over the Mediterranean marine stations (21 %). Near surface ozone shows mostly a negative bias in winter and a positive bias during warm months. Assimilation reduces the bias in near surface ozone and its impact is mostly notable in winter. With respect to the seasonal cycle, the MACC reanalysis reproduces the photochemically driven broad spring-summer maximum of surface ozone of central and south Europe. However, it does not capture adequately the early spring peak and the shape of the seasonality at northern and north-eastern Europe. The diurnal range of surface ozone, which is an indication of the local photochemical production processes, is reproduced fairly well, with a tendency for a small overestimation during the warm months for most subregions (especially in central and southern Europe). Possible reasons leading to discrepancies between the MACC reanalysis and observations are discussed. [ABSTRACT FROM AUTHOR]

Air quality over Europe using Models-3 (i.e., CMAQ, MM5, SMOKE) modelling system is performed for winter (i.e., January 2006) and summer (i.e., July 2006) months with the 2006 TNO gridded anthropogenic emissions database. Higher ozone mixing ratios are predicted in southern Europe while higher NO2 levels are simulated over western Europe. Elevated SO2 values are simulated over eastern Europe and higher PM2.5 concentrations over eastern and western Europe. Regional average results suggest that NO2 and PM2.5 are underpredicted, SO2 is overpredicted, while Max8hrO3 is overpredicted for low mixing ratios and is underpredicted for the higher mixing ratios. However, in a number of countries observed and predicted values are in good agreement for the pollutants examined here. Speciated PM2.5 components suggest that NO3 is dominant during winter over western Europe and in a few eastern countries due to the high NO2 mixing ratios. During summer NO3 is dominant only in regions with elevated NH3 emissions. For the rest of the domain SO3 is dominant. Low OC concentrations are simulated mainly due to the uncertain representation of SOA formation. [ABSTRACT FROM AUTHOR]

The article discusses a study conducted to update ECOCLIMAP-I in Europe. It is evident that ECOCLIMAP-I is a database designed to cater needs of meteorological community to examine natural and managed ecosystems in association with weather forecasting and climate change modelling. It discusses methods, datasets and characteristics of producing ECOCLIMAPII/Europe.

We focus here on a mainland Continental Portuguese Rural Fire Database (PRFD) that includes 450 000 fires, the largest such database in Europe in terms of total number of recorded fires in the 1980-2005 period. In this work, we (a) list the most important factors for triggering and controlling the fire regime in mainland Continental Portugal, (b) describe the dataset's production, (c) discuss procedures adopted to identify and correct different fire data inconsistencies, creating a modified PRFD which we use here and make available as Supplement, (d) explore some basic temporal and completeness properties of the data. We find that the dataset's minimum measured burnt areas have changed with time between AF = 0.1 ha (1980-1990), AF = 0.01 ha (1991-1992), and AF = 0.001 ha (1992-2005), with varying degrees of completeness down to these values. These changes in minimum area measured are responsible for greater numbers of fires being recorded. A relatively small number of large fires in the PRFD are responsible for the majority of the burnt area. For example, fires with AF > 100 ha represent about 1 % of all fire records but 75 % of total burnt area. Finally, we consider for each Continental Portugal district and for the 26-yr period, the total number of rural fires and area burnt in forests and shrublands, each normalized by district areas. We find that the highest numbers of fires per unit area are in highly populated districts, and that the largest fraction of burnt area is in forested areas, coinciding with large parcels of continuous forests (predominantly rural and moderately urban areas). [ABSTRACT FROM AUTHOR]

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data. [ABSTRACT FROM AUTHOR]

Water abstractions for irrigation purposes are higher than for any other pan-European water use sector and have a large influence on river runoff regimes. This modelling experiment assesses historic and current irrigation water demands for different crops in five arc minute spatial resolution for pan-Europe. Two different modelling frameworks have been applied in this study. First, soft-coupling the dynamic vegetation model LPJmL with the land use model LandSHIFT leads to overestimations of national irrigation water demands, which are rather high in the southern Mediterranean countries. This can be explained by unlimited water supply in the model structure and illegal or not gauged water abstractions in the reported data sets. The second modelling framework is WaterGAP3, which has an integrated conceptual crop specific irrigation module. Irrigation water requirements as modelled with WaterGAP3 feature a more realistic representation of pan-European water withdrawals. However, in colder humid regions, irrigation water demands are often underestimated. Additionally, a national database on crop-specific irrigated area and water withdrawal for all 42 countries within pan-Europe has been set up and integrated in both model frameworks. [ABSTRACT FROM AUTHOR]

Comments on the paper "Inventories of N2 O and NO Emissions From European Forest Soils," by M. Kesik and colleagues. Databases used to perform the spatial and temporal extrapolation of the NO and N2 O fluxes; Climatic scenarios used to examine the uncertainties of such inventories; Opinion on the comparison between the most sensitive factor and Monte Carlo approaches.

With the recent development of the European Integrated Data Archive (EIDA, http://www.orfeus-eu.org/data/eida/), an open-access infrastructure where data from different networks operating in Europe are archived and disseminated following common standards, we have the opportunity to compile harmonized ground-motion data sets for seismic hazard assessment studies. Here, we present a new and harmonized parametric catalogue for ground shaking studies in Europe obtained using stream2segment, a highly customizable Python package helping the user in the whole workflow of downloading, inspecting and processing event-based seismic data by means of a relational database management system as archiving storage. We used stream2segment to extract segments from EIDA containing recordings of earthquakes with magnitude above 2.5 in continental Europe and above 3 in the Mediterranean area. Through stream2segment, a customized processing pipeline is applied to discard noisy data and to extract parametric information for compiling a parametric table (aka flat file). The flat file (12500 earthquakes, 2200 stations and 205000 records) includes peak parameters (e.g., peak ground velocity and acceleration), spectral acceleration, and Fourier amplitude spectra. As first application of the flat file, here we present the calibration of a harmonized local magnitude scale for Europe. We first calibrate simultaneously a set of non-parametric attenuation functions regionalized over six different regions covering Europe, and anchoring the models to the Richter's scale at 17 km. Uncertainties on the attenuation coefficients, station corrections and magnitude values are evaluated through bootstrap analysis. A second calibration step is performed to derive a parametric attenuation model considering a piece-wise linear function to describe the attenuation with the logarithm of distance, and introducing two hinge-distances at 10 and 60 km. For distances above 10km, we also consider the anelastic attenuation term. We apply a mixed effect regression with network-dependent random effects on the anelastic coefficients. The obtained non-parametric attenuation functions show significant differences among the regions, up to 0.4 m.u. at 400 km, being the attenuation stronger for regions in the Mediterranean area. The non-parametric analysis also highlights the region-dependent changes in the rate of attenuation with distance due to the effects of later arrivals generated by crustal heterogeneity. The parametric analysis confirms the stronger attenuation for networks operating in the Mediterranean area, such as the Italian and Greek networks, with respect to networks located in continental Europe. The network-dependent random effects allow to quantify the between-network variability for different networks operating in the same region or country. The observed between-network variability is within ±0.2 m.u., smaller than the variability among the six regions. [ABSTRACT FROM AUTHOR]