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Circular material use rate in the EU and breakdown by material group between 2010 and 2022

The black line indicates changes in the total circular material use rate for the EU over time, while the coloured lines show changes in the circular material use rates for the various material groups.

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Municipal waste landfill rates in Europe by country

Cluster columns chart shows development in landfill rate of municipal waste in European countries in 2010 and 2021. Data is presented in descending order according to 2021 data values. Line chart represents EU landfill target for 2035.

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Amounts and share of waste deposited in landfills, by type of waste category, EU-27

The figure combines two charts. The stacked chart shows the amounts and percentage of waste (excluding major mineral waste) deposited in landfills in the EU-27. The line chart shows amounts landfilled for major waste categories (household and similar waste, combustion waste, sorting residues and other waste).

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Landings and proportion of landings of commercial fish and shellfish for which stock assessments were conducted between 2019-2022, per marine region

The figure shows the proportion of commercial European fish landings assessed per regional sea distinguishing between assessed and non-assessed stocks. For the assessed stocks a distinction is made between (i) landings of stocks for which information is available to determine Good Environmental Status (GES) for Fishing mortality (F) and/or Spawning Stock Biomass (SSB) and (ii) landings for stocks for which information is not available to determine GES for F and/or SSB.

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State of European commercial fish and shellfish stocks (for which stock assessments were conducted between 2019-2022), in relation to the Good Environmental Status criteria for fishing mortality and reproductive capacity per marine region

This figure shows the state of the assessed commercially exploited fish and shellfish stocks per European marine region, for which assessments were conducted in 2019-2022. Stocks for which adequate information is available to determine Good Environmental Status (GES) for fishing mortality (F) and/or reproductive capacity (spawning stock biomass (SSB)) are included (i.e. Z, total number of stocks; Y, total number of assessed stocks; and X, number of stocks for which adequate information is available to determine GES on the basis of these two criteria). A distinction is made between stocks: (1) in good status based on both fishing mortality and reproductive capacity; (2) in good status based on only one of the criteria - fishing mortality or reproductive capacity (either because one of the two criteria is not in good status or because there is only one available criteria, and it is in good status); and (3) not in good status based on both fishing mortality and reproductive capacity (may include cases where only one criteria is available and it is not in good status).

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State of assessed commercial fish and shellfish stocks in relation to the good environmental status criteria for fishing mortality and reproductive capacity in marine regions

This figure shows trends in the status of assessed commercially exploited fish and shellfish stocks between 1947 and 2021, expressed in two metrics-fishing mortality (F) and reproductive capacity (i.e. spawning stock biomass (SSB))-relative to their policy thresholds for the Marine Strategy Framework Directive's 'good environmental status' (GES) (i.e. FMSY and MSY Btrigger, respectively).

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Weighted impacts of EU consumption in a single score (million points), divided into consumption domains from 2010 to 2021

The graph shows the aggregated environmental impacts associated with each of the seven consumption domains, that are caused by EU consumption, regardless of where these impacts occur.

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Consumption footprints for EU countries in 2010 and 2021

The graph shows the level of aggregated environmental impacts associated with the consumption of each EU Member State, expressed in points per capita for the years 2010 and 2021, sorted from the country with the highest impacts to the country with the lowest impacts in 2021.

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Timing of occurrence of a 10 times amplification of the 1-in-100 years historical extreme in CMIP6 future projections

The projected probability increase of a certain extreme sea level is often presented as an amplification factor (AF) that indicates the ratio between the future and historical probability of that extreme sea level (commonly the 1-in-100 years extreme event). The use of the historical probability of the 1-in-100 years extreme sea level combined with future projections of sea level rise, available from CMIP6 projections (Coupled Model Intercomparison Project phase 6), allow to provide and estimate of the year of occurrence for a 10 times amplification of the historical event (AF10) under an optimistic future scenario (Shared Socioeconomic Pathways SSP1-2.6) and a future one without significant emissions abatement (SSP5-8.5).

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Requested sea level rise for an amplification factor of 10 and 100 times

The projected probability increase of a certain extreme sea level is often presented as an amplification factor (AF) that indicates the ratio between the future and historical probability of that extreme sea level (Hermans et al., 2023). The use of these estimates allow one to evaluate the changes of the 1-in-100 years extreme events according to sea level rise projections and provide an estimate of the requested SLR increase to determine a more frequent occurrence, e.g. 1-in-10 year (AF10) or every year (AF100).

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Past trend and projected change in relative sea level across Europe

The arrows show the observed trend in sea level relative to land since 1970 for those tide gauges along the Europe coastline with sufficiently long time series (mm/year). Projections: European sea level change for 2081–2100 for SSP5-8.5 in metres. Results use CMIP6 model projections for long term scenario (2081-2100), for SSP5-8.5, and with respect to a baseline of 1995-2014.

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Observed and projected change in global mean sea level

The left chart depicts the rise in global mean sea level from 1900 to 2022 based on two data sources. All values are relative to the average level of the period 1993-2010, during which the two datasets overlap. The grey line (Palmer et al., 2021) shows the ensemble sea-level reconstruction (using five members) of sea level anomalies during 1900-2010 (Palmer et al., 2021; https://iopscience.iop.org/article/10.1088/1748-9326/abdaec#erlabdaecs2). The dark grey line (CMEMS) shows the altimeter measurements corrected from the Topex-A drift at the beginning of the time series (Legeais et al., 2020), corrected for the GIA using the ICE5G-VM2 GIA model (Peltier, 2004), for the time series from 1993 to 2022. The right chart shows global mean sea level projections under different Shared Socioeconomic Pathways (SSP) scenarios. Sea level projections considering only processes for which projections can be made with at least medium confidence are provided, relative to the period 1995-2014, for five SSP. The scenarios are described in sections TS1.3 and 1.6 and Cross-Chapter Box 1.4 of the Working Group 1 contribution. Sea level projections considering only processes for which projections can be made with at least medium confidence are provided, relative to the period 1995-2014, for five SSP. The scenarios are described in sections TS1.3 and 1.6 and Cross-Chapter Box 1.4 of the Working Group 1 contribution.

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Maximum extent of ice cover in the Baltic Sea in the winter and 15 year moving average

Maximum extent of ice cover in the Baltic Sea in the winters 1719/20-2022/23 (green bars) and 15 year moving average (blue line). Source: Jouni Vainio, Finnish Meteorological Institute (updated from Seinä and Palosuo 1996; Seinä et al. 2001).

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Observed and projected decline in Arctic sea ice area

This figure combines two data sources. The left part shows the observed change in Arctic sea ice are (individual observations and trend lines) over the period 1979 to 2023 for March (maximum ice cover) and September (minimum ice cover). The right part shows projections of Arctic sea ice area in March and September from CMIP6 (Coupled Model Intercomparison Project Phase 6) simulations for three emissions scenarios. The thick lines denote the multimodel ensemble mean (24-27 models, depending on the scenario), and the shading shows the likely uncertainty interval (one standard deviation around the multimodel mean). The dashed line indicates a threshold for near ice-free conditions.

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Changes in the share of collective modes in inland passenger transport and of non-road modes in inland freight transport across European countries between 2010 and 2021

The figure shows the percentage point variations in the share of buses, trains, trams and metro (collective modes) and of inland waterways and trains (non-road modes) in total inland passenger and freight transport activities respectively by country.

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Contribution of collective and non-road modes to inland passenger and freight transport, respectively, in the EU-27

The figure shows the share of buses, trains, trams and metro (collective modes) and of inland waterways and trains (non-road modes) in total inland passenger and freight transport activities respectively in the EU-27. For reference, the absolute activities in the EU-27 for passenger and freight transport have been included.

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Emissions of pollutants from transport in EU-27

The figure shows the relative magnitude of emissions of pollutants from transport in EU-27 compared to 1990.

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Variations (1990-2021) in the emissions of pollutants from transport by mode in EU-27

The figure shows EU-27 variations for the 1990-2021 period in the emissions of different categories of pollutants from transport by mode.

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