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Only urban and sub-urban background monitoring stations have been included in the calculations. Data for Cyprus, Denmark, Greece and Malta, are not included due to missing availability of operational urban and sub-urban background monitoring stations in the Urban Audit cities.
The limit value is 125 µg SO2/m3 as a daily average, not to be exceeded more than three days in a year. Over the years 2001-2009 the total population for which exposure estimates are made, increased from 85 to 100 million people due to an increasing number of monitoring stations reporting under the Exchange of Information Decision. Year-to-year variations in exposure classes are partly caused by the changes in spatial coverage. Only urban and sub-urban background monitoring stations have been included in the calculations. Data for Cyprus, Denmark, Greece and Malta, are not included due to missing availability of operational urban and sub-urban background monitoring stations in the Urban Audit cities.
The target value is 120 µg O3/m3 as daily maximum of 8 hour mean, not to be exceeded more than 25 days per calendar year, averaged over three years and to be achieved where possible by 2010. Over the years 2001-2010 the total population for which exposure estimates are made, increased from 88 to 118 million people due to an increasing number of monitoring stations reporting under the Exchange of Information Decision. Year-to-year variations in exposure classes are partly caused by the changes in spatial coverage. Only urban and sub-urban background monitoring stations have been included in the calculations. Data for Cyprus, Greece and Malta is not included due to missing availability of operational urban and sub-urban background monitoring stations in the Urban Audit cities.
The annual mean limit value is 40 µg NO2/m3. Over the years 2001-2010 the total population, for which exposure estimates are made, increased from 93 to 124 million people due to an increasing number of monitoring stations reporting air quality data under the Exchange of Information Decision. Year-to-year variations in exposure classes are partly caused by the changes in spatial coverage. Only urban and sub-urban background monitoring stations have been included in the calculations. Data for Cyprus, Greece and Malta, are not included due to missing availability of operational urban and sub-urban background monitoring stations in the Urban Audit cities.
This figure illustrates the percentage population in Norhern European countries connected to a waste water collection and treatment systems (UWWTPs) over the period 1980 to 2009. In addition, a breakdown by treatment type is portrayed.
The list of projects is drawn from an unpublished report prepared for the EEA by members of the Swedish University of Agricultural Sciences (SLU). Some more examples were added as a result of a questionnaire sent to all partners of the European Topic Centre on Biological Diversity (ETC/BD). An EIONET consultation provided more information that was further enlarged by ETC/BD partner European Centre for Nature Conservation (ECNC).
This data visualisation shows the total of released data envelopes via Reportnet (Eionet's data flow system). The charts are updated automatically by querying Content Registry.
Fluorinated greenhouse gases (f-gases) covered by the UNFCCC’s Kyoto Protocol comprise hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and sulphur hexafluoride (SF6). The graphs present the quantities of f-gases reported under different type of activities for years 2007-2011, based on the information submitted by undertakings under Regulation (EC) No 842/2006 (F-Gas Regulation). In cases where less than three companies have reported for the particular year on the specific type of gases, or where there is a lack of detailed information, the aggregated quantities are provided in the 'Unspecified mix of f-gases' totals.
The graph presents the ‘environmentally compatible’ energy cropping data and scenario developed by the EEA for 2020.
The schema shows how resource efficiency relates to the use of natural capital and ecosystem resilience.
The chema outlines critical factors for the overall environmental performance of bioenergy and how the resource efficiency concept can be applied for environmental assessment.
The schema shows the most common biomass categories derived from agriculture, forests and wastes, and the conversion routes that are expected to become economic by 2020.
The figure shows the differences in terms of the contribution to the overall EU domestic agricultural potential.
The potential estimates refer to the EU’s agricultural bioenergy potential in 2020 for three storylines. These storylines explore plausible bioenergy development paths from a resource efficiency perspective under three specific sets of economic and political assumptions.
The figure provides a first overview of the relative efficiency of different types of bioenergy. Data represent net efficiencies taking into account results of life-cycle analysis.
The graph gives an overview of the absolute contribution of perennials per type to the bioenergy potential of a country in the Resource efficiency storyline.
The graph illustrates that energy systems differ in the extent and complexity of their impacts by presenting the projected life cycle land use of fossil, nuclear and renewable electricity systems in 2030. To understand the implications of increased bioenergy production, it is important to recognise that the land used for energy cropping is a natural resource, comprising soil, minerals, water and biota. Where bioenergy involves energy cropping it often necessitates changes to land use, with significant implications for related systems as well Other renewable technologies do also use some land and so do fossil and nuclear systems but the area is comparatively small. Nevetheless these technologies have other limitations.
The potential estimates refer to the EU’s agricultural bioenergy potential in 2020 for 3 storylines. These storylines explore plausible bioenergy development paths from a resource efficiency perspective under three specific sets of economic and political assumptions.
For references, please go to https://www.eea.europa.eu/data-and-maps/find/global or scan the QR code.
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