Identifying hotspots of greenhouse gas emissions from drained peatlands in the European Union

Identifying hotspots of greenhouse gas emissions from drained peatlands in the European Union | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Identifying hotspots of greenhouse gas emissions from drained peatlands in the European Union Quint Giersbergen, Alexandra Barthelmes, john Couwenberg, Christian Fritz, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4629642/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Dec, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Greenhouse gas (GHG) emissions from drained peatlands in the European Union (EU) significantly contribute to the total EU anthropogenic GHG emissions (6%). The lack of high-resolution spatial data in national monitoring systems hampers effective mitigation planning. We present detailed maps of land use, GHG emissions, and emission hotspots for EU peatlands. Results indicate that undrained peatlands and forest lands are prevalent at high latitudes, while grasslands and croplands dominate around latitudes 50°-55°. Three main emission hotspots are identified, all in the North Sea region: South-western England, Western Netherlands, and North-western Germany, accounting for 20% of EU peatland emissions on just 4% of the peatland area. This study highlights the necessity of targeted curbing of emissions from drained peatlands to meet EU climate goals and reveals substantial underreporting of emissions in current National Inventory Submissions to the UNFCCC, amounting to 59-113 Mt CO2-e annually. Our findings provide a crucial basis for policymakers to prioritize peatland rewetting to reduce GHG emissions. Earth and environmental sciences/Climate sciences/Climate change/Climate-change mitigation Earth and environmental sciences/Climate sciences/Climate change/Climate-change impacts/Governance Organic soil mitigation emission factors land use spatial mapping Figures Figure 1 Figure 2 Introduction In its Sixth Assessment Report the Intergovernmental Panel on Climate Change (IPCC) states that limiting warming to around 1.5°C requires anthropogenic greenhouse gas (GHG) emissions to peak before 2025 and that steps towards systemwide transformations to secure a net-zero, climate-resilient future are immediately taken (Lee et al., 2023). GHG emissions from drained peatlands are an important source of anthropogenic GHG emissions (UNEP, 2022 ). An amount equivalent to 50% of the total (current) atmospheric carbon (C) is stored in peatlands (Dolman et al., 2008 ; Yu et al., 2021 ). While anaerobic conditions of water-saturated peatlands enable net sequestration of C in the peat, in drained peatlands the release of carbon dioxide (CO 2 ) through peat oxidation outweighs C input and turns these ecosystems into huge sources of GHGs (Dolman et al., 2008 ; Tanneberger, et al., 2021a ). If GHG emissions from drained peatlands globally continue at the current rate, this will consume 12–41% of the GHG emission budget for keeping global warming below + 1.5 to + 2°C (Leifeld et al., 2019). In the European Union (EU), peatlands make up for almost 6% of the total land area and are present in every country except Malta (Tanneberger et al., 2017 ). Most of them are concentrated in the northern (boreal and temperate) lowlands. Half of the peatlands in the EU are degraded due to various human activities, most often linked to artificial drainage (Tanneberger, et al., 2021b ). Drainage was mostly done for agricultural activities, forestry, and peat extraction. Instead of acting as a C sink, these drained peatlands currently emit up to 230 Mt CO 2 -eq per year in the EU and 580 Mt CO 2 -eq per year in entire Europe (Global Peatland Database / Greifswald Mire Centre, 2022; UNEP, 2022 ) and are estimated to contribute some 5% to the total EU anthropogenic GHG emissions (Tanneberger et al., 2021a ). Accurate GHG emissions reporting is essential for the development of policy measures to reduce these emissions (Mooney et al., 2021 ). It enables policies and projects to focus appropriately on areas with high GHG emissions, including drained peatlands. Therefore, all parties included in Annex 1 to the United Nations’ Framework Convention on Climate Change (UNFCCC), including the EU member states separately and the EU as one party, are obliged to report their GHG emissions in annual inventories. National Inventory Submissions (NIS) must be based on IPCC emissions reporting guidelines (e.g. IPCC, 2014 for peatlands) and contain two parts, namely the Common Reporting Format (CRF) tables and the annual National Inventory Report (NIR). Reporting the Land Use, Land Use Change and Forestry (LULUCF) emissions was voluntary until 2021. By Decision 529/2013/EU the LULUCF sector has been included in the EU climate and energy framework to phase out the voluntary approach from 2021 onwards. Nevertheless, there are two main limitations regarding this way of reporting with respect to peatlands. Firstly, the reporting of the GHG emissions is done via a bottom-up approach. Each country reports by itself, which makes the process prone to underestimates (Mooney et al., 2021 ), e.g. by underreporting the drained peatland area (‘activity data’), using old emission factors (from earlier IPCC guidelines), not including all relevant GHGs emitted from drained peatlands (CO 2 , CH 4 , N 2 O), and not reporting emissions from ditches. A comparison between the peatland area reported by the EU member states in 2017 and the data of the Global Peatland Database (GPD, https://greifswaldmoor.de/global-peatland-database-en.html ) revealed that many EU member states underreported their drained peatland area at that time and for those reasons (Barthelmes, 2018 ). As a result, in 2021 only 92 Mt CO 2 eq. per year were reported to the UNFCCC for the agriculturally used peatlands in the EU (Cropland and Grassland), compared to 167 Mt from an improved assessment based on more comprehensive and accurate area data and the IPCC (2014) emission factors (Martin & Couwenberg, 2021 ). Secondly, the reporting under the UNFCCC does not require detailed spatial information showing where the peatlands are located (‘wall-to-wall’ approach) and where exactly in the EU peatland emissions are the highest. However, this information is crucial for policymakers to develop climate-smart land use policies for GHG mitigation and to adapt to the changing climate (Carter et al., 2018 ; Schulte et al., 2016 ), as well as to implement cost-efficient rewetting and restoration measures. Already 21 years ago, McClain et al. ( 2003 ) suggested to achieve easy wins by first reducing GHG emissions through policy interventions in peatland GHG emissions hotspot areas. Unfortunately, such reduction could not be observed over the past years (Enviromental European Agency, 2021), despite the increasing accuracy in the reporting (Martin & Couwenberg, 2021 ) and increased awareness for climate protection by rewetting drained peatlands. This suggests the need for more efforts to make both, policymakers and society, aware of GHG emissions from drained peatlands. A promising step forward is to disclose peatland emissions across the EU based on improved spatial maps from scientific and regional to national mapping. The aims of this work were 1) to increase the accuracy in EU GHG reporting from peatlands by providing the first detailed peatland GHG emissions map, and 2) to inform targeted policy measures for GHG mitigation by introducing an EU wide peatland GHG hotspot map. Moreover, the resulting data can stimulate the exchange between EU and IPCC bodies and their member states on the quality of national reporting to the UNFCCC. Methods Land use map for peatlands Spatial peat (and peaty) soil data for EU + countries (EU member states plus Albania, Andorra, Bosnia and Herzegovina, Iceland, Liechtenstein, Montenegro, North Macedonia, Norway, Serbia, Switzerland, United Kingdom) were taken from the European peatland map (Tanneberger et al., 2017 ), which has been updated within the Global Peatland Database for the Global Peatlands Assessment (UNEP, 2022 ). In the updated dataset, 7 datasets from 7 different countries, mainly from peatland and soil research or governmental agencies and ministries, are included. These data come from different time periods between 1958 and 2020, mostly being compiled or updated between 2012 and 2016 (Supplementary data I). Their definition of peatlands is in line with the 2006 (Eggleston et al., 2006 ) and 2014 (Hiraishi et al., 2014) IPCC definition of ‘organic soils’. The EU crop map developed by the Joint Research Centre (JRC) based on satellite images of 2018 with a spatial resolution of 10 meters (d’Andrimont et al., 2021 ) was used to stratify the peatland map according to the 2018 land cover distribution. This map delineates the most common (19) crops grown on agricultural parcels in the EU with an overall accuracy of 76% (d’Andrimont et al., 2021 ). However, it does not include non-agricultural areas and countries outside the EU. Therefore, the land use map of Witjes et al. ( 2022 ) was used as a base layer to distinguish additional land use classes beside Cropland and Grassland. This land use map has a lower resolution of 30 meters and even though it has 40 different classes for agricultural crops, it distinguishes only three types of agricultural land (non-irrigated, irrigated, and grassland). Therefore, it was only used to fill the gaps in the JRC map. We assume that the land cover over the years has not changed much, as the difference between the 2020 and 2021 World cover map developed by Zanaga et al. ( 2022 ) and long-term land use changes in the EU (Kuemmerle et al., 2016 ) are small. The area was calculated in hectares per grid cell. For our analysis, the 63 land uses are aggregated into main classes, namely: Grassland, Cropland, Forest Land, Wetlands and Build-up (Supplementary Table S.1). Emission factors for GHG emissions from peatlands Drainage influences the three most important GHGs in peatlands, CO 2 , CH 4 , and N 2 O, generally so that less intensive drainage results in less GHG emissions. Drained peatlands under higher temperatures (e.g. in temperate zones) emit more GHGs than peatlands under lower temperatures (e.g. in boreal zones) and nutrient-rich peatlands emit more GHGs than nutrient-poor ones (cf. Hiraishi et al., 2014). Depending on the climate zone, there are different default IPCC emission factors (EFs) per land use class. Only one EF per GHG is available for temperate drained Forest Land, whereas nutrient-rich and nutrient-poor drained Forest Lands are distinguished in the boreal region. Three emission factors are available for Grassland in the temperate region: one for drained nutrient-poor Grassland, another for deep-drained nutrient-rich Grassland (NR, DD in Table 1 ), and a third for shallow-drained nutrient-rich Grassland (NR-SD in Table 1 ). For boreal drained Grassland only one general EF is available. These IPCC (2014) EFs have been updated by (Wilson et al. 2016 ; cf. Table 1 ). Due to the lack of EU-wide geo-data on ditch location, only the CH 4 emissions from land were considered and ditch emissions in drained peatlands thus underestimated. Furthermore, peat extraction sites were excluded as the applied land use data did not distinguish them as separate classes. Table 1 Emission factors used in this study (t CO 2 eq. ha -1 year -1 ). Source: Wilson et al., ( 2016 ).Where NP = nutrient poor, NR = nutrient rich, DD = deep drainage, SD = shallow drainage, GWP = 100 year global warming potential. Land use class CO 2 CH 4 N 2 O DOC GWP Boreal Forest Land NP 0.92 0.33 0.09 0.44 1.76 Forest Land NR 3.41 0.20 1.37 0.44 5.42 Cropland 28.97 1.57 5.58 0.44 36.56 Grassland 20.90 1.61 4.08 0.44 27.03 Drained (rewetted) Wetland -1.52 1.4 0.03 0.29 0.28 Temperate Forest Land 9.53 0.21 1.20 1.14 12.08 Cropland 28.97 1.57 5.58 1.14 37.26 Grassland NR, DD 22.37 1.99 3.52 1.14 29.02 Grassland NR, SD 13.20 1.72 0.69 1.14 16.75 Drained (rewetted) Wetland -0.84 4.60 0.03 0.88 4.67 Allocation of nutrient and drainage levels To apply suitable emission factors (Hiraishi, 2014 ; Wilson et al., 2016 , Chap. 2.2) to the land use map of peatlands, the parameters nutrient level and drainage level have to be allocated. As there is currently no suitable European-wide map of nutrient and drainage levels in peatlands available, the biomass productivity map of Tóth et al., ( 2013 ; R 2 of 0.85) was used as a proxy. We assumed that more productivity means a higher probability of drainage and fertilizer application. Also rewetted peatlands with paludiculture can be highly productive, but their area in the EU is currently far less than 1% of the agricultural peatland area (Geurts et al. 2019 ). As a result, we classified a Grassland area ‘deep drained’ if it has 'high biomass production' or ‘shallow drained’ if it has ‘low biomass production' using Tóth et al. ( 2013 ). The same was done for Forest Land: it has been classified ‘nutrient rich’ with ‘high biomass production' or ‘nutrient poor’ with ‘low biomass production' in Tóth et al. ( 2013 ). Furthermore, it was assumed that the biomass productivity has not changed significantly between 2013 and 2018–2020. For applying the biomass productivity map, two tipping point values had to be found for the biomass production level distinguishing, 1) if a Grassland has a high or low agricultural activity; and 2) if a Forest Land is nutrient-rich or nutrient-poor (see Supplementary table S.2). It was assumed that the tipping point biomass production value in Grassland is equal to that of Forest Land. To identify the tipping point value, we applied the mean value and the minus one standard deviation of the mean value as two potential tipping point values per country and per land use and checked whether the ratio between ‘deep drained’ and ‘shallow drained’ follows the given values in the (updated) 2020 UNFCCC National Inventory Submission (cf. Martin & Couwenberg, 2021 ). This has been achieved by overlaying the peat land use maps per country with the biomass productivity map using ArcGIS Pro 2.9. When applying the mean Grassland Productivity Index (PI) of 6.32 across EU to distinguish if a peatland Grassland is shallow drained (below 6.32 PI) or deep drained (above 6.32 PI), 8 out of 13 countries were estimated to agree well (within a ± 5% range) with a previous estimate of the distribution of deep/shallow drained Grassland (Martin & Couwenberg, 2021 & Supplementary Table S.2). As there was no European wide information available about the deviation of nutrient-rich and nutrient-poor Forest Land and wetlands on peatland the mean PI of 6.08 as the tipping point value was used for Forest Land. Peatland GHG emission map and GHG emission hotspot map The spatial 0.000083 degrees (± 10 meters) resolution peatland emissions were estimated using the emission factors of Wilson et al. ( 2016 ; Table 1 ), the land use map of this study, the climatic region map of Sayre et al. ( 2020 ) and the productivity map of Tóth et al. ( 2013 ) with corresponding best fit tipping points to access the nutrient level of Forest Land and the drainage level of Grassland. The emissions (t CO 2 eq .) were calculated for each grid cell by using R-4.3.1 (R Core Team, 2024). For assessing whether a peatland is a hotspot or not, we used the ‘biscale’ package in R (Branson Fox, 2022). This method is based on thematic choropleth mapping with two variables, in this case peatland density (amount of peatland per area) and cumulative peatland emissions per area. The peatland density and the summed GHG emissions within a certain area were calculated on a 0.41667 degrees (± 35 km) resolution. This resolution was chosen because it gives the best visual representation of where the peatland emission hotspots are located and highlights the highest emitting and the densest peatland areas. The ‘equal style’ option has been used within the ‘biscale’ packages to keep a linear gradual changing color pattern, as the emissions are not normally distributed, due to prefixed emission factors. Validation After developing the GHG emission (hotspot) maps, an overview table for the national level has been developed for validation. Here, two emission estimates, the 2023 National Inventory Submissions (UNFCCC 2023) and the corrected 2020 National Inventory Submissions (Martin & Couwenberg, 2021 ) are compared to the outcomes of our study. The peatland area and emission values were aggregated from the coarse CRF categories 3D, 4A-D, 4II and the NIR-files of the 2023 NIS. This evaluation was furthermore used to develop an improved version of the hotspot map by rescaling current (spatial) GHG emission outcomes to the most likely numbers based on all available data and evaluation by expert judgment (cf. UNEP., 2022, Annex III.4), as for some countries the NIS 2023 estimates are based on Tier 2–3 (national) EFs compiled from regional GHG measurements and regionalized land use categories, which can considerably differ from Tier 1 IPCC values (e.g. Evans et al. 2017 , Aitova et al. 2023 ). Results Land use distribution Grasslands dominate around 50-55° N latitude while Forest Land is most prevalent at higher latitudes (Figure 1). In Albania, North Macedonia, Greece, Poland, Bosnia and Herzegovina, Hungary, Spain, Croatia, Liechtenstein, Romania, Portugal, Italy, Serbia, Denmark, and Germany, a relatively high proportion (>20%, descending ordered) of the peatlands is used as Cropland (Table 2). The highest proportion (>40%) of peatlands covered by Grassland is found in the Netherlands, Germany, Luxembourg, Denmark, Liechtenstein, and Ireland. In contrast, Cyprus, Slovenia, Czech Republic, Bulgaria, and Estonia have a relatively high coverage (>60%) of Forest Land on peatland. However, most extensive drained forests occur in Scandinavia and the Baltic states. The highest proportion (>35%) of undisturbed peatland is also found in Scandinavian countries, together with Andorra, the United Kingdom, and Ireland (Supplementary Table S.1). For most countries, this study results in a higher total peatland extent compared to the NIS 2023. More than half of the countries have a higher spatial extent of Cropland and Grassland on peat compared to the reported area (UNFCCC 2023), resulting in totally 12% more Grassland and Cropland on peat in the study area. In addition, most countries indicate in the NIS 2023 lower drained Forest Land area than in this study, while this study significantly underestimates the Forest Land area in Finland and Sweden (Table 2). In this research, the area coverage for agriculture and forestry often deviates (>20%) from the reported values in the 2023 NIS of the EU countries. The estimates for Cropland & Grassland and Forest Land areas largely align only for Latvia (Table 2). In general, the data for agriculture are more consistent than those for Forest Land, as eight countries have similar coverage (±20% in NIS 2023 and this study) of Cropland & Grassland, which together account for 74.5% of the total EU+ Cropland and Grassland sector (Supplementary Table S.3). Only two countries showed similar (±20%) area coverage for Forest Land in the compared sources, adding up to 7% of the total EU+ peat Forest Land (Table 2). Peatland emissions The highest GHG emissions from drained peatlands are observed between latitudes 50° and 55° N (Figure 1 A&B). The largest areas of low-emitting peatlands are concentrated in Finland, Sweden, and Scotland, due to a substantial proportion of undrained peatlands, forested peatlands, and shallow-drained grasslands (Supplementary Table S.1). Additionally, in Estonia, Latvia, Lithuania, and Ireland, there are sizable areas of relatively low-emitting peatlands, largely attributed to a large proportion of shallow-drained grasslands. Summing up our emission estimates, we found the total emission from peatlands to be 236 Mt CO2-e for the EU, which is twice the 121 Mt reported by the EU countries to the UNFCCC (Table 2). GHG emissions from drained peatlands in EU and EU+ contribute substantially (6.2 % and 6.1%, respectively) to the total EU and EU+ anthropogenic GHG emissions (European Environment Agency, 2021). Our spatial emission analysis reveals that for the majority of countries (27 out of 37), higher agricultural emissions were observed (Table 2) than reported (UNFCCC 2023). These differences primarily originate from deviations in area estimates reported for Cropland and Grassland compared to the estimates from our spatial data. When considering average emissions per area (hectare), 16 out of 37 countries exhibit similar agricultural emissions (Cropland + Grassland; indicated in green and orange in Table 2). Countries that deviate by more than 20% in either agricultural area or agricultural emissions in this study compared to the NIS 2023 are typically those with low peatland coverage. Specifically, 7 out of the 16 countries with agricultural peatland coverage lower than 25 kha fall into this category, mainly on the Balkan Peninsula and in the Mediterranean region. Peatland-rich countries with the largest emission deviations between NIS and our analysis are Romania, UK, Poland, Lithuania, Ireland, Iceland, Hungary, and Estonia. Based on this study, Forest Land emissions from drained peatland (Table 2; 70.3 Mt CO 2-e ) are substantially higher than those reported in NIS 2023 (26.5 Mt CO 2 eq.). We see two main reasons (playing out individually for countries): underestimates in area in the first place, and/or inappropriate choice of emission factors or incomplete coverage of gases (CO 2 , CH 4 , N 2 O), DOC and POC in NIS. In our GHG hotspot map, we decided to use the NIS 2023 emission estimates rather than the data from this study for Finland, Ireland, Iceland, and UK because they are using more advanced Tier 2 and 3 reporting and the area emissions ratio seems plausible. Moreover, we adopted the area estimates for Forest Land from NIS 2023 for Denmark, Germany, Poland, Estonia, Norway, and Lithuania. Their NIS area estimates were used to re-calculate emissions using the EFs from this study (Table 1) to complete biased emission reporting in NIS, which has been mainly caused by using outdated EFs from IPCC 2006 or from not reporting CH 4 and N 2 O. These recalculations and considerations lower the emissions of drained peatland under Forest Land in this study to 52.5 Mt CO 2 eq., which is still twice as high as reported to the UNFCCC. Table 2 Comparison of the area and emissions of the EU and EU+ Grassland, Cropland, and Forest Land on peatlands between the NIS 2023 and this study. The colors indicate the alignment of the two sources. The asterisks indicate that the emission value of this study was not used for the hotspot map, see the footnote. Peatland hotspot map Peatland area and GHG emission hotspots (Figure 2, indicated in purplish color = top-right four grids of top legend matrix in A) contribute 15% of the total peatland GHG emissions. Despite covering only 12% (top-right four grids of bottom legend matrix in A) of the total peatland area, their significant impact underscores the need for precise area data and assessment methodologies to facilitate climate change mitigation measures. Notably, the region with the highest relative emissions is situated in North-western Germany and North-eastern Netherlands, contributing to 14.3% of the total EU+ peatland emissions. Additionally, the western part of the Netherlands (3.4% of EU+ total) and South-eastern England (2.1%) also emerge as significant GHG hotspots, while collectively covering just 3.7% of the total EU+ peatland area (Figure 2). Hotspots with lower relevance exist e.g. in Northern England (UK), North-western Ireland, the Danube Delta (Romania), and in the Baltic states. Regions with high GHG emissions from peatlands (without being a peatland area hotspot) have been identified in the Central European Plain, the Alpine foreland in Germany, as well as in Hungary and Romania. Blue colored hotspots indicate a high density of peatlands (peatland area hotspots in Figure 2) which occur especially in North and central Finland and Northern-eastern Sweden, covering 11.3%, 5.2% and 4.6% of the EU+ peatland area, but emitting only 1.5%, 1.8% and 0.6% of the EU+ peatland GHG emissions, respectively. Discussion Area and emission estimates This study raises serious concerns about the overall underreporting of peatland GHG emissions in the NIS of EU + countries, which amounts to 59–113 Mt CO 2 -e annually (based on either Tier 1 partly rescaled using national Tier 2–3 data or sole Tier 1 method). This amount is almost equivalent to the annual emissions from EU + air traffic or from livestock farming and fertilization in the EU (EEA, 2023; Barthelmes, 2018 ). Main reasons for the underreporting in NIS 2023 are 1) the neglect of having drained peatlands in specific land use categories at all, 2) the underestimation of the area under drained land use on peatlands, and 3) the choice of outdated emission factors. National reporting of drained peatlands is lacking for many southern and south-eastern EU countries. Several of them may not have a significant area of drained organic soils, but Hungary and Romania are an exception as they seem to collectively not report ca. 23 Mt CO 2 -e annually. Others seem to underestimate their Cropland on drained organic soil, like the UK not reporting emissions from 186 kha of ‘wasted’ peat, i.e. “former deep peat that has been partly lost through agricultural activity” (NIS UK, 2023 ). Adding these emissions would make a substantial contribution to the UK’s peatland GHG emissions (Rhymes et al., 2023 ). Although Ireland states that there is only grassland on agriculturally used peatland (Environment Protection Agency, 2023 ), this research suggest, however, that 2.3% of the peatlands in Ireland are used for the production of cereals (9.9 kha) and maize (6.7 kha; Supplementary Table S.1), which causes additional emissions of 270–680 kt CO 2 -eq, depending on the drainage class of the grassland. Our findings also point at underreporting of the overall agricultural peatland area for Lithuania (having higher national thresholds for SOC in peat and peat depths ), for France (having a fragmentary peatland map despite recent efforts, cf. Pinault et al. 2023 ), and Estonia (Table 2 , cf. Barthelmes, 2018 ; Martin & Couwenberg, 2021 ). Moreover, the inclusion of all relevant gases (CO 2 , N 2 O, CH 4 ) has not been accomplished in all countries. For example, the CH 4 (Poland, Estonia, Hungary) and N 2 O (Poland, Hungary) emissions from peatlands are not reported, or very low, outdated Tier 1 EFs from the IPCC (2006) for Grassland are used (Poland, Estonia, Lithuania). Finally, land use maps can be blind for the differentiating land use intensity of Grasslands even though we used the biomass productivity map (see Methods). For instance, UK includes 1,278 kha of non-intensive Grasslands in its NIS having very low EFs between − 1.04 and 3.32 t CO 2 -eq ha − 1 y − 1 , resulting in a low average EF for agricultural used peatlands in the NIS - and way higher emissions in this study applying Tier 1 default EFs of IPCC. On the other hand, Finland and Sweden report higher emissions than we have derived in this research, which is probably related to differences both in EFs and in determining drained and undrained forested peatlands. Our remote sensing data may result in underestimation of the drained forest area as compared to the NIS 2023 that rely on national forest inventories since the drained forest area was marked as undrained on the drainage maps if the productivity was classified low or marked as undrained by the drainage map of both countries. This can be substantiated by the difference in Forest Land between the NIS and our research which has the same order of magnitude as the difference in undrained peatland from NIS and our results (Table 2 ; Supplementary Table S.3 & S.4). However, there are large areas of unsuccessful drainages that yield to low wood productivity despite of drainage; in Finland this area is estimated as 10–20% (Schneider & Päivinen, 2020 ). Successful mitigation of GHG emissions from drained peatlands is crucial for achieving GHG neutrality in the EU by 2050 (EU 2021) and strengthening the sink of the LULUCF sector in the EU by 310 Mt by 2050 (EU 2023). Mitigation measures on drained peatlands (like rewetting) provide permanent and high emission reductions even if CH 4 emissions increase temporarily (Günther et al., 2020 ). Underreported emissions at European scale blur the need and potential to reduce these emissions and countries may be overly optimistic at achieving GHG neutrality if these emissions are not fully accounted for in the national GHG inventories for the Agriculture and LULUCF sector. This study credibly highlights both GHG emission hotspots in Europe and shortcomings in national GHG reporting, which hopefully will encourage inventory authorities to improve reporting. This may be more easily achieved in the case of Cropland which is well monitored in the EU. However, for Forest Land on drained peatland, recognizing drained forest areas in the first place, mapping their extent and having appropriate emission factors seem to be still a challenge especially in countries where agriculture is the dominating land use and/or awareness of the role of peatlands in land systems may be low. This paper could encourage them to find a way to include drained peatlands under Forest Land in their GHG inventories. Mitigation hotspots This study provides the first map of GHG emission hotspots from peatlands on a 0.4167x 0.4167 degrees scale (± 1,250 km 2 ) for EU+. Hotspots emit a proportionally higher amount of GHG emissions in relation to the area they cover, which is intricately linked to density and intensity. However, it is crucial to note that the highest cumulative emissions per area do not necessarily imply the highest emission intensity. Our method takes into account also the peat density which increases the total sum of emissions within a grid cell of the hotspot map. An area where the emissions per hectare are only slightly above average, but the peatland area is very large, may still be a hotspot. A notable example is the northern region of Ireland, which is characterized by high peat density and a substantial extent of peatland covered mainly by a mix of drained Grasslands with some drained Forest Land. This leads to emissions that are way above average but not as high in relation to the area as is the case e.g., in the North-western part of Germany. It is therefore recommended that the hotspot map is used in conjunction with the emissions and land use map to develop effective policies and measures to reduce GHG emissions from land use on drained peatlands. Our research emphasizes that emissions from peatlands are not evenly distributed and identifies regional hotspots of GHG emissions. Based on this map, it is possible to design political regulations and subsidies that contribute to reducing these emissions more effectively and efficiently. This EU + hotspot map will be accompanied by detailed national versions in future (emerging from running projects funded under the Horizon Europe program), which can be instrumental for the national (or trans-boundary) spatial planning of climate mitigation action in peatland areas (Tanneberger et al., 2022 ). Based on the hotspot analysis of this study, EU + priority regions for peatland GHG emission reduction could be identified in Ireland, UK, the Netherlands, N-Germany, E-Poland, the Baltic States and E-Romania. Finland (and Sweden) may consider an emission mitigation strategy on landscape level to reduce GHGs from widespread low to mid emitting peatlands in addition to the high emitting peatlands. In future, the accuracy of our hotspot map would benefit from additional ground-truthing, e.g., in the Scottish uplands, Central Finland and Estonia to prove them being emission hotspots. Nevertheless, all these regions are likely suitable for targeted mitigation measures. In addition, 20% of all peatland-related emissions come from regions with low peatland cover, which can be advantageous in finding landowners to reduce emission through rewetting, because their farms may not be highly dependent on peatlands for their income (Kekkonen et al., 2019). Several European policy initiatives encourage to rewet peatlands (e.g. the Nature Restoration Law, EC., 2021 ), but instruments are lacking for developing EU-wide and national policies to target restoration efforts (Nordbeck & Hogl, 2024 ), notably data on extent, condition and related GHG emissions of peatlands (Minasny et al., 2023 ). Our findings emphasize the scale of climate mitigation benefits achievable through targeted raise of water levels in (agricultural) emissions hotspot peatlands. Since agriculturally used peatland cover only 3% of the agricultural land in the EU and the EU is a net food exporter , this would not be much relevant for food security (GMC & Wetlands International, 2023). Our land use and GHG hotspot maps are intended to close knowledge gaps and support the development and implementation of peatland restoration policies and action across the EU+. Furthermore, the hotspot map can be used on a (sub-)national level, and across national borders to tackle emissions hotspots on a transboundary level just like Mason et al. ( 2020 ) do in their research for biodiversity purposes. Limitations and uncertainty Even though we are convinced that this study produced reliable results, all currently available EU or European input data has its specific biases, limitations, and uncertainties. Despite of high accuracies (± 80%) of the land use maps, it is questionable how well they reflect the reality on ground (d’Andrimont et al., 2021 ; Witjes et al. 2022 ). We see four main sources of uncertainty in our input data that may have affected our products: 1) misclassification of specific land use types, 2) neglect of grassland within crop rotation, 3) misclassification of drainage status, and 4) some under or over-representation of spatial peatland area. Classification errors may arise as e.g. used grassland/rangeland and wetland vegetation can look quite similar (Mahdavi et al., 2018 ). Therefore, in areas where wetlands and grasslands are adjacent, such as in the north-western part of Sweden and the far north of Finland, some precaution is required since those areas are most likely undrained wetlands (Turunen & Valpola, 2020; Vasander et al., 2003 ). This might also play a partial role in the GHG emission hotspot in Ireland. In addition, undrained land is classified as wetlands in this study, which includes undrained Forest Land. This would explain the difference between our Forest Land area and the reported NIR 2023 areas especially for Finland and Sweden (Table 2 ). It seems particularly plausible as the total Forest Land and Wetland areas of this study combined are roughly equal to their combined total area in NIR 2023 for both countries. Another major uncertainty factor is that short-term Grassland is sometimes included in the crop rotation and should therefore be assigned to the emission factor of Cropland instead of Grassland, to reflect the real emissions in the higher EF (Upcott et al., 2023 ). This could be tackled by analyzing land use within a 4–6 years period and classify Grasslands as Cropland if the Grassland has been a Cropland during this time (cf. Upcott et al., 2023 ). Furthermore, the assumption that all drained Grassland is nutrient-rich probably leads to an overestimation of emissions, however in the IPCC wetland supplement and in Wilson et al., ( 2016 ), there is no EF for shallow drained nutrient poor Grassland. This has probably to do with the fact that shallow drained nutrient poor Grassland is not very common on agricultural land (Estel et al., 2018 ). However, first regional assessments deliver insights in this respect (Evans et al., 2017 , Aitova et al., 2023 ). The classification of drainage level of Grassland using the tipping point method (see Methods section), seems to be a quite accurate approximator (Supplementary Table S1 ). However, the validation of the Forest Land nutrient status based on the productivity map of Tóth et al. ( 2013 ) has not been evaluated in this research. The lack of validation points for the nutrient levels of forested peatland in in the LUCAS soil survey, where only a small part sampling points (49 of 21.850 samples) originate from forested peatlands, makes it impossible to use them for validation of EU Forest Land on peatland (d’Andrimont et al., 2020 ). New methods to map ditches and estimate drainage impact using remote sensing and machine learning are promising and may yield higher accuracy of drainage extent in European Grassland and Forest Land (cf. Koski et al., 2023 , Lidberg et al., 2022 ). They may tackle the GHG underestimations resulting from not including the CH 4 emissions from ditches which has led to considerably underestimation of emissions (cf. Schrier-Uijl et al., 2011 ; Peacock et el., 2021), and also problems with inaccurate drainage maps e.g. in Finland potentially overestimating drained peatlands. Moreover, the spatial (map) peatland area of the GPD is under- or overestimating the peatland area within some countries, when comparing the country specific estimation of peatland cover to Joosten et al., 2017 , Barthelmes, 2018 and Martin & Couwenberg, 2021 their research. An example of the influence of input data is provided by the Netherlands, where the NIS 2023 includes ‘peat’ and ‘peaty’ soils under agriculture (341 kha), whereas we only included the 'peat' soils (268 kha) in this study. At the other hand, we used for Lithuania a data set that includes larger areas of the ‘peat in soil’ mosaic, while the NIS sets decently high thresholds for C content and peat depth. We mitigated this in the final choice of GHG results for the hotspot map (Supplementary Table S.3 and S.4). Additionally, drained peatland areas are also shrinking due to loss of the peat by oxidation under long-term drainage and use. This is expected to accelerate as result of rising temperatures due to climate change (Fluet-Chouinard et al., 2023 ). Declarations Author contributions QvG, KL, and FT conceptualized and designed the research. QvG, AB, FT, and JC developed the methodology. QvG, AB, FT, and CF validated the findings. QvG was responsible for the visualizations. Formal analysis was performed by QvG and partly by AB. Data curation was conducted by both QvG and AB. The original draft was prepared by QvG, FT, KL, AB, CF, and NM. All authors contributed to the review and editing of the manuscript. Competing interests The authors declare no competing interests. Acknowledgements This research was funded through the 2019-2020 BiodivERsA joint call for research proposals, under the BiodivClim ERA-Net COFUND programme, and with the funding organisations Research Council of Finland and the Federal Ministry of Education and Research (BMBF) through VDI-VDE (Germany). 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COM(2021) 800 final. accessible via https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:52021DC0800 European Commission (2022), Safeguarding food security and reinforcing the resilience of food systems, COM(2022) 133 final, accessible via https://agriculture.ec.europa.eu/system/files/2022-03/safeguarding-food-security-reinforcing-resilience-food-systems_0.pdf Table Table 2 is available in the Supplementary Files section Additional Declarations There is NO Competing Interest. Supplementary Files TableS1.xlsx Table S1 TableS2.docx Table S2 TableS3.xlsx Table S3 TableS4.xlsx Table S4 Supplement.docx Table2.docx Cite Share Download PDF Status: Published Journal Publication published 02 Dec, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4629642","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":318431510,"identity":"7c74b35a-3044-403b-a3d8-9277d4e06f44","order_by":0,"name":"Quint Giersbergen","email":"data:image/png;base64,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","orcid":"","institution":"Radboud university","correspondingAuthor":true,"prefix":"","firstName":"Quint","middleName":"","lastName":"Giersbergen","suffix":""},{"id":318431511,"identity":"ea8b334f-8564-46b7-95cd-55bf4a8f8a31","order_by":1,"name":"Alexandra Barthelmes","email":"","orcid":"","institution":"Greifswald Mire Centre","correspondingAuthor":false,"prefix":"","firstName":"Alexandra","middleName":"","lastName":"Barthelmes","suffix":""},{"id":318431512,"identity":"bb820d9b-fa47-4290-8395-63a9af4b8995","order_by":2,"name":"john Couwenberg","email":"","orcid":"","institution":"Greifswald University","correspondingAuthor":false,"prefix":"","firstName":"john","middleName":"","lastName":"Couwenberg","suffix":""},{"id":318431513,"identity":"1d54d1bc-6cd8-4a25-acc6-40ecb8cb9b83","order_by":3,"name":"Christian Fritz","email":"","orcid":"","institution":"Radboud University","correspondingAuthor":false,"prefix":"","firstName":"Christian","middleName":"","lastName":"Fritz","suffix":""},{"id":318431514,"identity":"ef92b57c-8471-4320-88ce-1daf4cfe03ed","order_by":4,"name":"Kristiina Lång","email":"","orcid":"","institution":"LUKE","correspondingAuthor":false,"prefix":"","firstName":"Kristiina","middleName":"","lastName":"Lång","suffix":""},{"id":318431515,"identity":"ee191937-8c37-471b-b28b-064082a92c43","order_by":5,"name":"Nina Martin","email":"","orcid":"","institution":"Greifswald University","correspondingAuthor":false,"prefix":"","firstName":"Nina","middleName":"","lastName":"Martin","suffix":""},{"id":318431516,"identity":"4e7703c1-30e1-4426-9cc2-ca1ea0f4a1f3","order_by":6,"name":"Franziska Tanneberger","email":"","orcid":"","institution":"University of Greifswald, partner in the GMC","correspondingAuthor":false,"prefix":"","firstName":"Franziska","middleName":"","lastName":"Tanneberger","suffix":""}],"badges":[],"createdAt":"2024-06-24 10:56:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4629642/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4629642/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-65841-6","type":"published","date":"2025-12-02T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59632081,"identity":"7ecdfd2b-acc2-4ab3-b20c-9881c5f2dfde","added_by":"auto","created_at":"2024-07-04 05:41:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1001211,"visible":true,"origin":"","legend":"\u003cp\u003eLand use (A) and greenhouse gas (GHG) emissions (B) in EU+ peatlands. To enhance visibility, certain land uses are aggregated as shown in supplementary Table S.1, and the resolution is downscaled to 1 km² using nearest neighboring resampling.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4629642/v1/dfb39f092949f2a8a830daa0.png"},{"id":59631665,"identity":"683ab5a6-0702-4fab-b5ba-a3573a7cbbb5","added_by":"auto","created_at":"2024-07-04 05:33:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":185011,"visible":true,"origin":"","legend":"\u003cp\u003ePeatland area and GHG emission density hotspot maps of (drained) peatlands in the EU+, in a 30x30 km\u003csup\u003e2\u003c/sup\u003e grid. Increased peat density is depicted in blue colors, increased emissions intensity in red. The simultaneous presence of an increased peatland area and increased emission is denoted in purple.\u0026nbsp; The results were re-scaled for some countries see supplementary Table S.3 and S.4.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4629642/v1/8aef6df972166da4eccb648f.png"},{"id":97321937,"identity":"daddb79b-7ba1-4377-a076-3d863e8b0d62","added_by":"auto","created_at":"2025-12-03 08:07:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1937284,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4629642/v1/3c4b7d4a-f327-4d0e-8eb3-c8285a7e5e18.pdf"},{"id":59632079,"identity":"dfa594cf-b69f-43fe-977d-7006ddad35b1","added_by":"auto","created_at":"2024-07-04 05:41:13","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":42581,"visible":true,"origin":"","legend":"Table S1","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4629642/v1/ac8d539f03f59e73f59583af.xlsx"},{"id":59631669,"identity":"8d92cb07-7dd3-4da1-9de7-171a3cfb585c","added_by":"auto","created_at":"2024-07-04 05:33:13","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":14889,"visible":true,"origin":"","legend":"Table S2","description":"","filename":"TableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4629642/v1/5d8199ec9887508d9d038299.docx"},{"id":59631673,"identity":"601dbe17-1b25-499d-a226-68ecbb40cbfc","added_by":"auto","created_at":"2024-07-04 05:33:13","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":35392,"visible":true,"origin":"","legend":"Table S3","description":"","filename":"TableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4629642/v1/749400448587be72fa1e7a19.xlsx"},{"id":59632080,"identity":"0414607d-5fc0-4522-8636-492a24cc53f5","added_by":"auto","created_at":"2024-07-04 05:41:13","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":27420,"visible":true,"origin":"","legend":"\u003cp\u003eTable S4\u003c/p\u003e","description":"","filename":"TableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4629642/v1/70f355483919e5588222283b.xlsx"},{"id":59631672,"identity":"97e89372-edf5-471d-bbd9-cc56d6f94992","added_by":"auto","created_at":"2024-07-04 05:33:13","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1419910,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-4629642/v1/2f9d39da44c2bc66e52ed3f9.docx"},{"id":59631670,"identity":"cb058cb1-bf7b-48e3-83ad-24fba824b842","added_by":"auto","created_at":"2024-07-04 05:33:13","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":360662,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4629642/v1/abe1ce1ddcf2014cb24afcfc.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Identifying hotspots of greenhouse gas emissions from drained peatlands in the European Union","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn its Sixth Assessment Report the Intergovernmental Panel on Climate Change (IPCC) states that limiting warming to around 1.5°C requires anthropogenic greenhouse gas (GHG) emissions to peak before 2025 and that steps towards systemwide transformations to secure a net-zero, climate-resilient future are immediately taken (Lee et al., 2023). GHG emissions from drained peatlands are an important source of anthropogenic GHG emissions (UNEP, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). An amount equivalent to 50% of the total (current) atmospheric carbon (C) is stored in peatlands (Dolman et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While anaerobic conditions of water-saturated peatlands enable net sequestration of C in the peat, in drained peatlands the release of carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) through peat oxidation outweighs C input and turns these ecosystems into huge sources of GHGs (Dolman et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Tanneberger, et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). If GHG emissions from drained peatlands globally continue at the current rate, this will consume 12–41% of the GHG emission budget for keeping global warming below + 1.5 to + 2°C (Leifeld et al., 2019).\u003c/p\u003e \u003cp\u003eIn the European Union (EU), peatlands make up for almost 6% of the total land area and are present in every country except Malta (Tanneberger et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Most of them are concentrated in the northern (boreal and temperate) lowlands. Half of the peatlands in the EU are degraded due to various human activities, most often linked to artificial drainage (Tanneberger, et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e). Drainage was mostly done for agricultural activities, forestry, and peat extraction. Instead of acting as a C sink, these drained peatlands currently emit up to 230 Mt CO\u003csub\u003e2\u003c/sub\u003e-eq per year in the EU and 580 Mt CO\u003csub\u003e2\u003c/sub\u003e-eq per year in entire Europe (Global Peatland Database / Greifswald Mire Centre, 2022; UNEP, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and are estimated to contribute some 5% to the total EU anthropogenic GHG emissions (Tanneberger et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccurate GHG emissions reporting is essential for the development of policy measures to reduce these emissions (Mooney et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It enables policies and projects to focus appropriately on areas with high GHG emissions, including drained peatlands. Therefore, all parties included in Annex 1 to the United Nations’ Framework Convention on Climate Change (UNFCCC), including the EU member states separately and the EU as one party, are obliged to report their GHG emissions in annual inventories. National Inventory Submissions (NIS) must be based on IPCC emissions reporting guidelines (e.g. IPCC, 2014 for peatlands) and contain two parts, namely the Common Reporting Format (CRF) tables and the annual National Inventory Report (NIR). Reporting the Land Use, Land Use Change and Forestry (LULUCF) emissions was voluntary until 2021. By Decision 529/2013/EU the LULUCF sector has been included in the EU climate and energy framework to phase out the voluntary approach from 2021 onwards. Nevertheless, there are two main limitations regarding this way of reporting with respect to peatlands.\u003c/p\u003e \u003cp\u003eFirstly, the reporting of the GHG emissions is done via a bottom-up approach. Each country reports by itself, which makes the process prone to underestimates (Mooney et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), e.g. by underreporting the drained peatland area (‘activity data’), using old emission factors (from earlier IPCC guidelines), not including all relevant GHGs emitted from drained peatlands (CO\u003csub\u003e2\u003c/sub\u003e, CH\u003csub\u003e4\u003c/sub\u003e, N\u003csub\u003e2\u003c/sub\u003eO), and not reporting emissions from ditches. A comparison between the peatland area reported by the EU member states in 2017 and the data of the Global Peatland Database (GPD, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://greifswaldmoor.de/global-peatland-database-en.html\u003c/span\u003e\u003cspan address=\"https://greifswaldmoor.de/global-peatland-database-en.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) revealed that many EU member states underreported their drained peatland area at that time and for those reasons (Barthelmes, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). As a result, in 2021 only 92 Mt CO\u003csub\u003e2\u003c/sub\u003e eq.\u0026nbsp;per year were reported to the UNFCCC for the agriculturally used peatlands in the EU (Cropland and Grassland), compared to 167 Mt from an improved assessment based on more comprehensive and accurate area data and the IPCC (2014) emission factors (Martin \u0026amp; Couwenberg, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Secondly, the reporting under the UNFCCC does not require detailed spatial information showing where the peatlands are located (‘wall-to-wall’ approach) and where exactly in the EU peatland emissions are the highest. However, this information is crucial for policymakers to develop climate-smart land use policies for GHG mitigation and to adapt to the changing climate (Carter et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Schulte et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), as well as to implement cost-efficient rewetting and restoration measures.\u003c/p\u003e \u003cp\u003eAlready 21 years ago, McClain et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) suggested to achieve easy wins by first reducing GHG emissions through policy interventions in peatland GHG emissions hotspot areas. Unfortunately, such reduction could not be observed over the past years (Enviromental European Agency, 2021), despite the increasing accuracy in the reporting (Martin \u0026amp; Couwenberg, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and increased awareness for climate protection by rewetting drained peatlands. This suggests the need for more efforts to make both, policymakers and society, aware of GHG emissions from drained peatlands. A promising step forward is to disclose peatland emissions across the EU based on improved spatial maps from scientific and regional to national mapping. The aims of this work were 1) to increase the accuracy in EU GHG reporting from peatlands by providing the first detailed peatland GHG emissions map, and 2) to inform targeted policy measures for GHG mitigation by introducing an EU wide peatland GHG hotspot map. Moreover, the resulting data can stimulate the exchange between EU and IPCC bodies and their member states on the quality of national reporting to the UNFCCC.\u003c/p\u003e \n\n \n\n \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e \n\n "},{"header":"Methods","content":"\u003ch3\u003eLand use map for peatlands\u003c/h3\u003e\u003cp\u003eSpatial peat (and peaty) soil data for EU + countries (EU member states plus Albania, Andorra, Bosnia and Herzegovina, Iceland, Liechtenstein, Montenegro, North Macedonia, Norway, Serbia, Switzerland, United Kingdom) were taken from the European peatland map (Tanneberger et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), which has been updated within the Global Peatland Database\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e for the Global Peatlands Assessment (UNEP, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the updated dataset, 7 datasets from 7 different countries, mainly from peatland and soil research or governmental agencies and ministries, are included. These data come from different time periods between 1958 and 2020, mostly being compiled or updated between 2012 and 2016 (Supplementary data I). Their definition of peatlands is in line with the 2006 (Eggleston et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) and 2014 (Hiraishi et al., 2014) IPCC definition of ‘organic soils’.\u003c/p\u003e\u003cp\u003eThe EU crop map developed by the Joint Research Centre (JRC) based on satellite images of 2018 with a spatial resolution of 10 meters (d’Andrimont et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) was used to stratify the peatland map according to the 2018 land cover distribution. This map delineates the most common (19) crops grown on agricultural parcels in the EU with an overall accuracy of 76% (d’Andrimont et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, it does not include non-agricultural areas and countries outside the EU. Therefore, the land use map of Witjes et al. (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) was used as a base layer to distinguish additional land use classes beside Cropland and Grassland. This land use map has a lower resolution of 30 meters and even though it has 40 different classes for agricultural crops, it distinguishes only three types of agricultural land (non-irrigated, irrigated, and grassland). Therefore, it was only used to fill the gaps in the JRC map. We assume that the land cover over the years has not changed much, as the difference between the 2020 and 2021 \u003cem\u003eWorld cover\u003c/em\u003e map developed by Zanaga et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and long-term land use changes in the EU (Kuemmerle et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) are small. The area was calculated in hectares per grid cell. For our analysis, the 63 land uses are aggregated into main classes, namely: Grassland, Cropland, Forest Land, Wetlands and Build-up (Supplementary Table S.1).\u003c/p\u003e\u003ch3\u003eEmission factors for GHG emissions from peatlands\u003c/h3\u003e\u003cp\u003eDrainage influences the three most important GHGs in peatlands, CO\u003csub\u003e2\u003c/sub\u003e, CH\u003csub\u003e4\u003c/sub\u003e, and N\u003csub\u003e2\u003c/sub\u003eO, generally so that less intensive drainage results in less GHG emissions. Drained peatlands under higher temperatures (e.g. in temperate zones) emit more GHGs than peatlands under lower temperatures (e.g. in boreal zones) and nutrient-rich peatlands emit more GHGs than nutrient-poor ones (cf. Hiraishi et al., 2014).\u003c/p\u003e\u003cp\u003eDepending on the climate zone, there are different default IPCC emission factors (EFs) per land use class. Only one EF per GHG is available for temperate drained Forest Land, whereas nutrient-rich and nutrient-poor drained Forest Lands are distinguished in the boreal region. Three emission factors are available for Grassland in the temperate region: one for drained nutrient-poor Grassland, another for deep-drained nutrient-rich Grassland (NR, DD in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), and a third for shallow-drained nutrient-rich Grassland (NR-SD in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For boreal drained Grassland only one general EF is available. These IPCC (2014) EFs have been updated by (Wilson et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; cf. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Due to the lack of EU-wide geo-data on ditch location, only the CH\u003csub\u003e4\u003c/sub\u003e emissions from land were considered and ditch emissions in drained peatlands thus underestimated. Furthermore, peat extraction sites were excluded as the applied land use data did not distinguish them as separate classes.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEmission factors used in this study (t CO\u003csub\u003e2\u003c/sub\u003e eq.\u0026nbsp;ha\u003csup\u003e-1\u003c/sup\u003e year\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e \u003cdiv class=\"Credit\"\u003e\u003cp\u003eSource: Wilson et al., (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).Where NP = nutrient poor, NR = nutrient rich, DD = deep drainage, SD = shallow drainage, GWP = 100 year global warming potential.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLand use class\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCH\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDOC\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGWP\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eBoreal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForest Land NP\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForest Land NR\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.41\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.42\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCropland\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.97\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.58\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36.56\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrassland\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.90\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e27.03\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrained (rewetted) Wetland\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eTemperate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForest Land\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e12.08\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCropland\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.97\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.58\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e37.26\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrassland NR, DD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.37\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e29.02\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrassland NR, SD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.75\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrained (rewetted) Wetland\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.84\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.60\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.67\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eAllocation of nutrient and drainage levels\u003c/h2\u003e\u003cp\u003eTo apply suitable emission factors (Hiraishi, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Wilson et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Chap.\u0026nbsp;2.2) to the land use map of peatlands, the parameters nutrient level and drainage level have to be allocated. As there is currently no suitable European-wide map of nutrient and drainage levels in peatlands available, the biomass productivity map of Tóth et al., (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; R\u003csup\u003e2\u003c/sup\u003e of 0.85) was used as a proxy. We assumed that more productivity means a higher probability of drainage and fertilizer application. Also rewetted peatlands with paludiculture can be highly productive, but their area in the EU is currently far less than 1% of the agricultural peatland area (Geurts et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As a result, we classified a Grassland area ‘deep drained’ if it has 'high biomass production' or ‘shallow drained’ if it has ‘low biomass production' using Tóth et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The same was done for Forest Land: it has been classified ‘nutrient rich’ with ‘high biomass production' or ‘nutrient poor’ with ‘low biomass production' in Tóth et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Furthermore, it was assumed that the biomass productivity has not changed significantly between 2013 and 2018–2020.\u003c/p\u003e\u003cp\u003eFor applying the biomass productivity map, two tipping point values had to be found for the biomass production level distinguishing, 1) if a Grassland has a high or low agricultural activity; and 2) if a Forest Land is nutrient-rich or nutrient-poor (see Supplementary table S.2). It was assumed that the tipping point biomass production value in Grassland is equal to that of Forest Land. To identify the tipping point value, we applied the mean value and the minus one standard deviation of the mean value as two potential tipping point values per country and per land use and checked whether the ratio between ‘deep drained’ and ‘shallow drained’ follows the given values in the (updated) 2020 UNFCCC National Inventory Submission (cf. Martin \u0026amp; Couwenberg, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This has been achieved by overlaying the peat land use maps per country with the biomass productivity map using ArcGIS Pro 2.9. When applying the mean Grassland Productivity Index (PI) of 6.32 across EU to distinguish if a peatland Grassland is shallow drained (below 6.32 PI) or deep drained (above 6.32 PI), 8 out of 13 countries were estimated to agree well (within a ± 5% range) with a previous estimate of the distribution of deep/shallow drained Grassland (Martin \u0026amp; Couwenberg, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e \u0026amp; Supplementary Table S.2). As there was no European wide information available about the deviation of nutrient-rich and nutrient-poor Forest Land and wetlands on peatland the mean PI of 6.08 as the tipping point value was used for Forest Land.\u003c/p\u003e\u003ch3\u003ePeatland GHG emission map and GHG emission hotspot map\u003c/h3\u003e\u003cp\u003eThe spatial 0.000083 degrees (± 10 meters) resolution peatland emissions were estimated using the emission factors of Wilson et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), the land use map of this study, the climatic region map of Sayre et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and the productivity map of Tóth et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) with corresponding best fit tipping points to access the nutrient level of Forest Land and the drainage level of Grassland. The emissions (t CO\u003csub\u003e2 eq\u003c/sub\u003e.) were calculated for each grid cell by using R-4.3.1 (R Core Team, 2024). For assessing whether a peatland is a hotspot or not, we used the ‘biscale’ package in R (Branson Fox, 2022). This method is based on thematic choropleth mapping with two variables, in this case peatland density (amount of peatland per area) and cumulative peatland emissions per area. The peatland density and the summed GHG emissions within a certain area were calculated on a 0.41667 degrees (± 35 km) resolution. This resolution was chosen because it gives the best visual representation of where the peatland emission hotspots are located and highlights the highest emitting and the densest peatland areas. The ‘equal style’ option has been used within the ‘biscale’ packages to keep a linear gradual changing color pattern, as the emissions are not normally distributed, due to prefixed emission factors.\u003c/p\u003e\u003ch2\u003eValidation\u003c/h2\u003e\u003cp\u003eAfter developing the GHG emission (hotspot) maps, an overview table for the national level has been developed for validation. Here, two emission estimates, the 2023 National Inventory Submissions (UNFCCC 2023) and the corrected 2020 National Inventory Submissions (Martin \u0026amp; Couwenberg, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) are compared to the outcomes of our study. The peatland area and emission values were aggregated from the coarse CRF categories 3D, 4A-D, 4II and the NIR-files of the 2023 NIS. This evaluation was furthermore used to develop an improved version of the hotspot map by rescaling current (spatial) GHG emission outcomes to the most likely numbers based on all available data and evaluation by expert judgment (cf. UNEP., 2022, Annex III.4), as for some countries the NIS 2023 estimates are based on Tier 2–3 (national) EFs compiled from regional GHG measurements and regionalized land use categories, which can considerably differ from Tier 1 IPCC values (e.g. Evans et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Aitova et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eLand use\u0026nbsp;distribution\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eGrasslands dominate around 50-55\u0026deg; N latitude while Forest Land is most prevalent at higher latitudes (Figure 1). In Albania, North Macedonia, Greece, Poland, Bosnia and Herzegovina, Hungary, Spain, Croatia, Liechtenstein, Romania, Portugal, Italy, Serbia, Denmark, and Germany, a relatively high proportion (\u0026gt;20%, descending ordered) of the peatlands is used as Cropland (Table 2). The highest proportion (\u0026gt;40%) of peatlands covered by Grassland is found in the Netherlands, Germany, Luxembourg, Denmark, Liechtenstein, and Ireland. In contrast, Cyprus, Slovenia, Czech Republic, Bulgaria, and Estonia have a relatively high coverage (\u0026gt;60%) of Forest Land on peatland. However, most extensive drained forests occur in Scandinavia and the Baltic states. The highest proportion (\u0026gt;35%) of undisturbed peatland is also found in Scandinavian countries, together with Andorra, the United Kingdom, and Ireland (Supplementary Table S.1).\u003c/p\u003e\n\u003cp\u003eFor most countries, this study results in a higher total peatland extent compared to the NIS 2023. More than half of the countries have a higher spatial extent of Cropland and Grassland on peat compared to the reported area (UNFCCC 2023), resulting in totally 12% more Grassland and Cropland on peat in the study area. In addition, most countries indicate in the NIS 2023 lower drained Forest Land area than in this study, while this study significantly underestimates the Forest Land area in Finland and Sweden (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this research, the area coverage for agriculture and forestry often deviates (\u0026gt;20%) from the reported values in the 2023 NIS of the EU countries. The estimates for Cropland \u0026amp; Grassland and Forest Land areas largely align only for Latvia (Table 2). In general, the data for agriculture are more consistent than those for Forest Land, as eight countries have similar coverage (\u0026plusmn;20% in NIS 2023 and this study) of Cropland \u0026amp; Grassland, which together account for 74.5% of the total EU+ Cropland and Grassland sector (Supplementary Table S.3). Only two countries showed similar (\u0026plusmn;20%) area coverage for Forest Land in the compared sources, adding up to 7% of the total EU+ peat Forest Land (Table 2).\u003c/p\u003e\n\u003ch2\u003ePeatland emissions\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe highest GHG emissions from drained peatlands are observed between latitudes 50\u0026deg; and 55\u0026deg; N (Figure 1 A\u0026amp;B). The largest areas of low-emitting peatlands are concentrated in Finland, Sweden, and Scotland, due to a substantial proportion of undrained peatlands, forested peatlands, and shallow-drained grasslands (Supplementary Table S.1). Additionally, in Estonia, Latvia, Lithuania, and Ireland, there are sizable areas of relatively low-emitting peatlands, largely attributed to a large proportion of shallow-drained grasslands. Summing up our emission estimates, we found the total emission from peatlands to be 236 Mt CO2-e for the EU, which is twice the 121 Mt reported by the EU countries to the UNFCCC (Table 2). GHG emissions from drained peatlands in EU and EU+ contribute substantially (6.2 % and 6.1%, respectively) to the total EU and EU+ anthropogenic GHG emissions (European Environment Agency, 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur spatial emission analysis reveals that for the majority of countries (27 out of 37), higher agricultural emissions were observed (Table 2) than reported (UNFCCC 2023). These differences primarily originate from deviations in area estimates reported for Cropland and Grassland compared to the estimates from our spatial data. When considering average emissions per area (hectare), 16 out of 37 countries exhibit similar agricultural emissions (Cropland + Grassland; indicated in green and orange in Table 2). Countries that deviate by more than 20% in either agricultural area or agricultural emissions in this study compared to the NIS 2023 are typically those with low peatland coverage. Specifically, 7 out of the 16 countries with agricultural peatland coverage lower than 25 kha fall into this category, mainly on the Balkan Peninsula and in the Mediterranean region. Peatland-rich countries with the largest emission deviations between NIS and our analysis are Romania, UK, Poland, Lithuania, Ireland, Iceland, Hungary, and Estonia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on this study, Forest Land emissions from drained peatland (Table 2; 70.3 Mt CO\u003csub\u003e2-e\u003c/sub\u003e) are substantially higher than those reported in NIS 2023 (26.5 Mt CO\u003csub\u003e2\u003c/sub\u003e eq.). We see two main reasons (playing out individually for countries): underestimates in area in the first place, and/or inappropriate choice of emission factors or incomplete coverage of gases (CO\u003csub\u003e2\u003c/sub\u003e, CH\u003csub\u003e4\u003c/sub\u003e, N\u003csub\u003e2\u003c/sub\u003eO), DOC and POC in NIS. In our GHG hotspot map, we decided to use the NIS 2023 emission estimates rather than the data from this study for Finland, Ireland, Iceland, and UK because they are using more advanced Tier 2 and 3 reporting and the area emissions ratio seems plausible. Moreover, we adopted the area estimates for Forest Land from NIS 2023 for Denmark, Germany, Poland, Estonia, Norway, and Lithuania. Their NIS area estimates were used to re-calculate emissions using the EFs from this study (Table 1) to complete biased emission reporting in NIS, which has been mainly caused by using outdated EFs from IPCC 2006 or from not reporting CH\u003csub\u003e4\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO. These recalculations and considerations lower the emissions of drained peatland under Forest Land in this study to 52.5 Mt CO\u003csub\u003e2\u003c/sub\u003e eq., which is still twice as high as reported to the UNFCCC.\u003c/p\u003e\n\u003cp\u003eTable 2 Comparison of the area and emissions of the EU and EU+ Grassland, Cropland, and Forest Land on peatlands between the NIS 2023 and this study. The colors indicate the alignment of the two sources. The asterisks indicate that the emission value of this study was not used for the hotspot map, see the footnote.\u003c/p\u003e\n\u003ch2\u003ePeatland hotspot map\u003c/h2\u003e\n\u003cp\u003ePeatland area and GHG emission hotspots (Figure 2, indicated in purplish color = top-right four grids of top legend matrix in A) contribute 15% of the total peatland GHG emissions. Despite covering only 12% (top-right four grids of bottom legend matrix in A) of the total peatland area, their significant impact underscores the need for precise area data and assessment methodologies to facilitate climate change mitigation measures. Notably, the region with the highest relative emissions is situated in North-western Germany and North-eastern Netherlands, contributing to 14.3% of the total EU+ peatland emissions. Additionally, the western part of the Netherlands (3.4% of EU+ total) and South-eastern England (2.1%) also emerge as significant GHG hotspots, while collectively covering just 3.7% of the total EU+ peatland area (Figure 2). Hotspots with lower relevance exist e.g. in Northern England (UK), North-western Ireland, the Danube Delta (Romania), and in the Baltic states.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegions with high GHG emissions from peatlands (without being a peatland area hotspot) have been identified in the Central European Plain, the Alpine foreland in Germany, as well as in Hungary and Romania. Blue colored hotspots indicate a high density of peatlands (peatland area hotspots in Figure 2) which occur especially in North and central Finland and Northern-eastern Sweden, covering 11.3%, 5.2% and 4.6% of the EU+ peatland area, but emitting only 1.5%, 1.8% and 0.6% of the EU+ peatland GHG emissions, respectively.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eArea and emission estimates\u003c/h2\u003e \u003cp\u003eThis study raises serious concerns about the overall underreporting of peatland GHG emissions in the NIS of EU\u0026thinsp;+\u0026thinsp;countries, which amounts to 59\u0026ndash;113 Mt CO\u003csub\u003e2\u003c/sub\u003e-e annually (based on either Tier 1 partly rescaled using national Tier 2\u0026ndash;3 data or sole Tier 1 method). This amount is almost equivalent to the annual emissions from EU\u0026thinsp;+\u0026thinsp;air traffic or from livestock farming and fertilization in the EU (EEA, 2023; Barthelmes, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Main reasons for the underreporting in NIS 2023 are 1) the neglect of having drained peatlands in specific land use categories at all, 2) the underestimation of the area under drained land use on peatlands, and 3) the choice of outdated emission factors.\u003c/p\u003e \u003cp\u003eNational reporting of drained peatlands is lacking for many southern and south-eastern EU countries. Several of them may not have a significant area of drained organic soils, but Hungary and Romania are an exception as they seem to collectively not report ca. 23 Mt CO\u003csub\u003e2\u003c/sub\u003e-e annually. Others seem to underestimate their Cropland on drained organic soil, like the UK not reporting emissions from 186 kha of \u0026lsquo;wasted\u0026rsquo; peat, i.e. \u0026ldquo;former deep peat that has been partly lost through agricultural activity\u0026rdquo; (NIS UK, 2023\u003ca class=\"FNLink\" href=\"#Fn2\" id=\"#FNLinkFn2\"\u003e\u003c/a\u003e). Adding these emissions would make a substantial contribution to the UK\u0026rsquo;s peatland GHG emissions (Rhymes et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Although Ireland states that there is only grassland on agriculturally used peatland (Environment Protection Agency, 2023\u003ca class=\"FNLink\" href=\"#Fn3\" id=\"#FNLinkFn3\"\u003e\u003c/a\u003e), this research suggest, however, that 2.3% of the peatlands in Ireland are used for the production of cereals (9.9 kha) and maize (6.7 kha; Supplementary Table S.1), which causes additional emissions of 270\u0026ndash;680 kt CO\u003csub\u003e2\u003c/sub\u003e-eq, depending on the drainage class of the grassland.\u003c/p\u003e \u003cp\u003eOur findings also point at underreporting of the overall agricultural peatland area for Lithuania (having higher national thresholds for SOC in peat and peat depths\u003ca class=\"FNLink\" href=\"#Fn4\" id=\"#FNLinkFn4\"\u003e\u003c/a\u003e), for France (having a fragmentary peatland map despite recent efforts, cf. Pinault et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and Estonia (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, cf. Barthelmes, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Martin \u0026amp; Couwenberg, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover, the inclusion of all relevant gases (CO\u003csub\u003e2\u003c/sub\u003e, N\u003csub\u003e2\u003c/sub\u003eO, CH\u003csub\u003e4\u003c/sub\u003e) has not been accomplished in all countries. For example, the CH\u003csub\u003e4\u003c/sub\u003e (Poland, Estonia, Hungary) and N\u003csub\u003e2\u003c/sub\u003eO (Poland, Hungary) emissions from peatlands are not reported, or very low, outdated Tier 1 EFs from the IPCC (2006) for Grassland are used (Poland, Estonia, Lithuania). Finally, land use maps can be blind for the differentiating land use intensity of Grasslands even though we used the biomass productivity map (see Methods). For instance, UK includes 1,278 kha of non-intensive Grasslands in its NIS having very low EFs between \u0026minus;\u0026thinsp;1.04 and 3.32 t CO\u003csub\u003e2\u003c/sub\u003e-eq ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, resulting in a low average EF for agricultural used peatlands in the NIS - and way higher emissions in this study applying Tier 1 default EFs of IPCC.\u003c/p\u003e \u003cp\u003eOn the other hand, Finland and Sweden report higher emissions than we have derived in this research, which is probably related to differences both in EFs and in determining drained and undrained forested peatlands. Our remote sensing data may result in underestimation of the drained forest area as compared to the NIS 2023 that rely on national forest inventories since the drained forest area was marked as undrained on the drainage maps if the productivity was classified low or marked as undrained by the drainage map of both countries. This can be substantiated by the difference in Forest Land between the NIS and our research which has the same order of magnitude as the difference in undrained peatland from NIS and our results (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Supplementary Table S.3 \u0026amp; S.4). However, there are large areas of unsuccessful drainages that yield to low wood productivity despite of drainage; in Finland this area is estimated as 10\u0026ndash;20% (Schneider \u0026amp; P\u0026auml;ivinen, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSuccessful mitigation of GHG emissions from drained peatlands is crucial for achieving GHG neutrality in the EU by 2050 (EU 2021) and strengthening the sink of the LULUCF sector in the EU by 310 Mt by 2050 (EU 2023). Mitigation measures on drained peatlands (like rewetting) provide permanent and high emission reductions even if CH\u003csub\u003e4\u003c/sub\u003e emissions increase temporarily (G\u0026uuml;nther et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Underreported emissions at European scale blur the need and potential to reduce these emissions and countries may be overly optimistic at achieving GHG neutrality if these emissions are not fully accounted for in the national GHG inventories for the Agriculture and LULUCF sector. This study credibly highlights both GHG emission hotspots in Europe and shortcomings in national GHG reporting, which hopefully will encourage inventory authorities to improve reporting. This may be more easily achieved in the case of Cropland which is well monitored in the EU. However, for Forest Land on drained peatland, recognizing drained forest areas in the first place, mapping their extent and having appropriate emission factors seem to be still a challenge especially in countries where agriculture is the dominating land use and/or awareness of the role of peatlands in land systems may be low. This paper could encourage them to find a way to include drained peatlands under Forest Land in their GHG inventories.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMitigation hotspots\u003c/h2\u003e \u003cp\u003eThis study provides the first map of GHG emission hotspots from peatlands on a 0.4167x 0.4167 degrees scale (\u0026plusmn;\u0026thinsp;1,250 km\u003csup\u003e2\u003c/sup\u003e) for EU+. Hotspots emit a proportionally higher amount of GHG emissions in relation to the area they cover, which is intricately linked to density and intensity. However, it is crucial to note that the highest cumulative emissions per area do not necessarily imply the highest emission intensity. Our method takes into account also the peat density which increases the total sum of emissions within a grid cell of the hotspot map. An area where the emissions per hectare are only slightly above average, but the peatland area is very large, may still be a hotspot. A notable example is the northern region of Ireland, which is characterized by high peat density and a substantial extent of peatland covered mainly by a mix of drained Grasslands with some drained Forest Land. This leads to emissions that are way above average but not as high in relation to the area as is the case e.g., in the North-western part of Germany. It is therefore recommended that the hotspot map is used in conjunction with the emissions and land use map to develop effective policies and measures to reduce GHG emissions from land use on drained peatlands.\u003c/p\u003e \u003cp\u003eOur research emphasizes that emissions from peatlands are not evenly distributed and identifies regional hotspots of GHG emissions. Based on this map, it is possible to design political regulations and subsidies that contribute to reducing these emissions more effectively and efficiently. This EU\u0026thinsp;+\u0026thinsp;hotspot map will be accompanied by detailed national versions in future (emerging from running projects funded under the Horizon Europe program), which can be instrumental for the national (or trans-boundary) spatial planning of climate mitigation action in peatland areas (Tanneberger et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Based on the hotspot analysis of this study, EU\u0026thinsp;+\u0026thinsp;priority regions for peatland GHG emission reduction could be identified in Ireland, UK, the Netherlands, N-Germany, E-Poland, the Baltic States and E-Romania. Finland (and Sweden) may consider an emission mitigation strategy on landscape level to reduce GHGs from widespread low to mid emitting peatlands in addition to the high emitting peatlands. In future, the accuracy of our hotspot map would benefit from additional ground-truthing, e.g., in the Scottish uplands, Central Finland and Estonia to prove them being emission hotspots. Nevertheless, all these regions are likely suitable for targeted mitigation measures.\u003c/p\u003e \u003cp\u003eIn addition, 20% of all peatland-related emissions come from regions with low peatland cover, which can be advantageous in finding landowners to reduce emission through rewetting, because their farms may not be highly dependent on peatlands for their income (Kekkonen et al., 2019).\u003c/p\u003e \u003cp\u003eSeveral European policy initiatives encourage to rewet peatlands (e.g. the Nature Restoration Law, EC., 2021\u003ca class=\"FNLink\" href=\"#Fn5\" id=\"#FNLinkFn5\"\u003e\u003c/a\u003e), but instruments are lacking for developing EU-wide and national policies to target restoration efforts (Nordbeck \u0026amp; Hogl, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), notably data on extent, condition and related GHG emissions of peatlands (Minasny et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Our findings emphasize the scale of climate mitigation benefits achievable through targeted raise of water levels in (agricultural) emissions hotspot peatlands. Since agriculturally used peatland cover only 3% of the agricultural land in the EU and the EU is a net food exporter\u003ca class=\"FNLink\" href=\"#Fn6\" id=\"#FNLinkFn6\"\u003e\u003c/a\u003e, this would not be much relevant for food security (GMC \u0026amp; Wetlands International, 2023). Our land use and GHG hotspot maps are intended to close knowledge gaps and support the development and implementation of peatland restoration policies and action across the EU+. Furthermore, the hotspot map can be used on a (sub-)national level, and across national borders to tackle emissions hotspots on a transboundary level just like Mason et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) do in their research for biodiversity purposes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and uncertainty\u003c/h2\u003e \u003cp\u003eEven though we are convinced that this study produced reliable results, all currently available EU or European input data has its specific biases, limitations, and uncertainties. Despite of high accuracies (\u0026plusmn;\u0026thinsp;80%) of the land use maps, it is questionable how well they reflect the reality on ground (d\u0026rsquo;Andrimont et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Witjes et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). We see four main sources of uncertainty in our input data that may have affected our products: 1) misclassification of specific land use types, 2) neglect of grassland within crop rotation, 3) misclassification of drainage status, and 4) some under or over-representation of spatial peatland area.\u003c/p\u003e \u003cp\u003eClassification errors may arise as e.g. used grassland/rangeland and wetland vegetation can look quite similar (Mahdavi et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, in areas where wetlands and grasslands are adjacent, such as in the north-western part of Sweden and the far north of Finland, some precaution is required since those areas are most likely undrained wetlands (Turunen \u0026amp; Valpola, 2020; Vasander et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). This might also play a partial role in the GHG emission hotspot in Ireland. In addition, undrained land is classified as wetlands in this study, which includes undrained Forest Land. This would explain the difference between our Forest Land area and the reported NIR 2023 areas especially for Finland and Sweden (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). It seems particularly plausible as the total Forest Land and Wetland areas of this study combined are roughly equal to their combined total area in NIR 2023 for both countries.\u003c/p\u003e \u003cp\u003eAnother major uncertainty factor is that short-term Grassland is sometimes included in the crop rotation and should therefore be assigned to the emission factor of Cropland instead of Grassland, to reflect the real emissions in the higher EF (Upcott et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This could be tackled by analyzing land use within a 4\u0026ndash;6 years period and classify Grasslands as Cropland if the Grassland has been a Cropland during this time (cf. Upcott et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, the assumption that all drained Grassland is nutrient-rich probably leads to an overestimation of emissions, however in the IPCC wetland supplement and in Wilson et al., (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), there is no EF for shallow drained nutrient poor Grassland. This has probably to do with the fact that shallow drained nutrient poor Grassland is not very common on agricultural land (Estel et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, first regional assessments deliver insights in this respect (Evans et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Aitova et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe classification of drainage level of Grassland using the tipping point method (see Methods section), seems to be a quite accurate approximator (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). However, the validation of the Forest Land nutrient status based on the productivity map of T\u0026oacute;th et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) has not been evaluated in this research. The lack of validation points for the nutrient levels of forested peatland in in the LUCAS soil survey, where only a small part sampling points (49 of 21.850 samples) originate from forested peatlands, makes it impossible to use them for validation of EU Forest Land on peatland (d\u0026rsquo;Andrimont et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). New methods to map ditches and estimate drainage impact using remote sensing and machine learning are promising and may yield higher accuracy of drainage extent in European Grassland and Forest Land (cf. Koski et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Lidberg et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). They may tackle the GHG underestimations resulting from not including the CH\u003csub\u003e4\u003c/sub\u003e emissions from ditches which has led to considerably underestimation of emissions (cf. Schrier-Uijl et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Peacock et el., 2021), and also problems with inaccurate drainage maps e.g. in Finland potentially overestimating drained peatlands.\u003c/p\u003e \u003cp\u003eMoreover, the spatial (map) peatland area of the GPD is under- or overestimating the peatland area within some countries, when comparing the country specific estimation of peatland cover to Joosten et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Barthelmes, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e and Martin \u0026amp; Couwenberg, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e their research. An example of the influence of input data is provided by the Netherlands, where the NIS 2023 includes \u0026lsquo;peat\u0026rsquo; and \u0026lsquo;peaty\u0026rsquo; soils under agriculture (341 kha), whereas we only included the 'peat' soils (268 kha) in this study. At the other hand, we used for Lithuania a data set that includes larger areas of the \u0026lsquo;peat in soil\u0026rsquo; mosaic, while the NIS sets decently high thresholds for C content and peat depth. We mitigated this in the final choice of GHG results for the hotspot map (Supplementary Table S.3 and S.4). Additionally, drained peatland areas are also shrinking due to loss of the peat by oxidation under long-term drainage and use. This is expected to accelerate as result of rising temperatures due to climate change (Fluet-Chouinard et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eQvG, KL, and FT conceptualized and designed the research. QvG, AB, FT, and JC developed the methodology. QvG, AB, FT, and CF validated the findings. QvG was responsible for the visualizations. Formal analysis was performed by QvG and partly by AB. Data curation was conducted by both QvG and AB. The original draft was prepared by QvG, FT, KL, AB, CF, and NM. All authors contributed to the review and editing of the manuscript.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThis research was funded through the 2019-2020 BiodivERsA joint call for research proposals, under the BiodivClim ERA-Net COFUND programme, and with the funding organisations Research Council of Finland and the Federal Ministry of Education and Research (BMBF) through VDI-VDE (Germany).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAitova, E., Morley, T., Wilson, D. \u0026amp; Renou-Wilson, F. (2023). A review of greenhouse gas emissions and removals from Irish peatlands. Mires and Peat, Volume 29 (2023), Article 04, 17 pp.,\u003c/li\u003e\n\u003cli\u003eBarthelmes, A. (2018). Reporting greenhouse gas emissions from organic soils in the European Union: challenges and opportunities. 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Bonn, Germany: United Nations Framework Convention on Climate Change (UNFCCC), accessible via National Inventory Submissions 2023 | UNFCCC\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Environment Protection Agency: Ireland, 1990\u0026ndash;2023. Bonn, Germany: United Nations Framework Convention on Climate Change (UNFCCC), accessible via National Inventory Submissions 2023 | UNFCCC\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Which also is evident for Scotland (UK).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e EC 2021. Communication from the commission to the European parliament and the council: Sustainable Carbon Cycles. COM(2021) 800 final. accessible via \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:52021DC0800\u003c/span\u003e\u003cspan address=\"https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:52021DC0800\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e European Commission (2022), Safeguarding food security and reinforcing the resilience of food systems, COM(2022) 133 final, accessible via \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://agriculture.ec.europa.eu/system/files/2022-03/safeguarding-food-security-reinforcing-resilience-food-systems_0.pdf\u003c/span\u003e\u003cspan address=\"https://agriculture.ec.europa.eu/system/files/2022-03/safeguarding-food-security-reinforcing-resilience-food-systems_0.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 2 is available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Organic soil, mitigation, emission factors, land use, spatial mapping","lastPublishedDoi":"10.21203/rs.3.rs-4629642/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4629642/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGreenhouse gas (GHG) emissions from drained peatlands in the European Union (EU) significantly contribute to the total EU anthropogenic GHG emissions (6%). The lack of high-resolution spatial data in national monitoring systems hampers effective mitigation planning. We present detailed maps of land use, GHG emissions, and emission hotspots for EU peatlands. Results indicate that undrained peatlands and forest lands are prevalent at high latitudes, while grasslands and croplands dominate around latitudes 50°-55°. Three main emission hotspots are identified, all in the North Sea region: South-western England, Western Netherlands, and North-western Germany, accounting for 20% of EU peatland emissions on just 4% of the peatland area. This study highlights the necessity of targeted curbing of emissions from drained peatlands to meet EU climate goals and reveals substantial underreporting of emissions in current National Inventory Submissions to the UNFCCC, amounting to 59-113 Mt CO2-e annually. Our findings provide a crucial basis for policymakers to prioritize peatland rewetting to reduce GHG emissions.\u003c/p\u003e","manuscriptTitle":"Identifying hotspots of greenhouse gas emissions from drained peatlands in the European Union","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-04 05:33:08","doi":"10.21203/rs.3.rs-4629642/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4ea75d7b-e4f0-464f-97b9-45c8e5799ff6","owner":[],"postedDate":"July 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33670108,"name":"Earth and environmental sciences/Climate sciences/Climate change/Climate-change mitigation"},{"id":33670109,"name":"Earth and environmental sciences/Climate sciences/Climate change/Climate-change impacts/Governance"}],"tags":[],"updatedAt":"2025-12-03T08:07:01+00:00","versionOfRecord":{"articleIdentity":"rs-4629642","link":"https://doi.org/10.1038/s41467-025-65841-6","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-12-02 05:00:00","publishedOnDateReadable":"December 2nd, 2025"},"versionCreatedAt":"2024-07-04 05:33:08","video":"","vorDoi":"10.1038/s41467-025-65841-6","vorDoiUrl":"https://doi.org/10.1038/s41467-025-65841-6","workflowStages":[]},"version":"v1","identity":"rs-4629642","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4629642","identity":"rs-4629642","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}