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Indicator Specification
In recent years scientific evidence has been strengthened by many epidemiological studies that indicate there is an association between long and short-term exposure to fine particulate matter and various serious health impacts. Fine particles have adverse effects on human health and can be responsible for and/or contribute to a number of respiratory problems. Fine particles in this context refer to the sum of primary PM10 and the weighted emissions of secondary PM10 precursors. Primary PM10 refers to fine particles (defined as having diameter of 10 mm or less) emitted directly to the atmosphere. Secondary PM10 precursors are pollutants that are partly transformed into particles by photo-chemical reactions in the atmosphere. A large fraction of the urban population is exposed to levels of fine particulate matter in excess of limit values set for the protection of human health. There have been a number of recent policy initiatives that aim to control particulate concentrations and thus protect human health.
This indicator tracks trends in emissions of primary particulate matter less than 10 mm (PM10) and secondary particulate matter precursors (nitrogen oxides (NOx) , ammonia (NH3), and sulphur dioxide (SO2)), each weighted by their respective particulate matter formation potential factor.
The indicator also provides information on the sources of emissions from a number of sectors: energy industries; road and other transport; industry (processes and energy); other (energy); fugitive emissions; waste; agriculture and other (non energy).
ktonnes (particulate formation potential)
There are no specific EU emission targets set for primary PM10, as with respect to particulate emissions, measures are currently focused on controlling emissions of the secondary PM10 precursors. However, there are several Directives that affect the emissions of primary PM, including the 2008 Air Quality Directive and emission standards for specific mobile and stationary sources for primary PM10 and secondary PM10 precursor emissions. For the particulate precursor species, within the European Union the National Emission Ceilings Directive (NEC Directive) imposes emission ceilings (or limits) for emissions of the particulate precursor pollutants nitrogen oxides, sulphur dioxide and ammonia that harm human health and the environment (the NEC Directive also sets emissions ceilings for a fourth pollutant - non-methane volatile organic compounds). The European Commission is expected to propose a revised NEC Directive in 2009. Other key EU legislation is targeted at reducing emissions of the particulate precursor pollutants from specific sources, for example: Internationally, the issue of air pollution emissions is also being addressed by the UNECE Convention on Long-range Transboundary Air Pollution (the LRTAP Convention) and its protocols. The Gothenburg 'multi-pollutant' protocol under the LRTAP Convention also contains national emission ceilings for the three secondary particulate precursor pollutants that are either equal to or slightly less ambitious than those in the EU NEC Directive. References Directive 2001/81/EC, on national emissions ceilings (NECD) for certain atmospheric pollutants.
UNECE (1999). Protocol to the 1979 Convention on Long-Range Transboundary air pollution (LRTAP Convention) to abate acidification, eutrophication and ground-level ozone. http://www.unece.org/env/lrtap/multi_h1.htm
There are no specific EU emission targets for primary PM10. However, emissions of the precursors NOx, SOx and NH3 are covered by the NECD and the Gothenburg Protocol to the UNECE LRTAP Convention. Both instruments contain emission ceilings (limits) that countries must meet by 2010.
Table 1. Percentage reduction required by 2010 compared to 1990 levels by country, for aggregated emissions of the secondary particulate precursors NOx, SOx and NH3 (individual pollutant emission ceilings weighted by particulate formation potential factors prior to aggregation).
Country | NECD Targets 1990 -2010 (particulate precursors) | Gothenburg Target 1990 -2010 (particulate precursors) | |
Austria | -40% | -38% |
|
Belgium | -58% | -57% |
|
Denmark | -55% | -55% |
|
Finland | -47% | -46% |
|
France | -52% | -50% |
|
Germany | -73% | -73% |
|
Greece | 9% | 12% |
|
Ireland | -45% | -45% |
|
Italy | -54% | -53% |
|
Luxembourg | -52% | -52% |
|
Netherlands | -54% | -53% |
|
Portugal | -9% | -2% |
|
Spain | -44% | -44% |
|
Sweden | -43% | -43% |
|
United Kingdom | -67% | -66% |
|
Bulgaria | -34% | -32% |
|
Cyprus | 29% |
|
|
Czech Republic | -75% | -73% |
|
Estonia | -45% |
|
|
Hungary | -40% | -37% |
|
Latvia | -5% | 11% |
|
Lithuania | -21% | -21% |
|
Malta | -24% |
|
|
Poland | -43% | -43% |
|
Romania | 1% | 1% |
|
Slovakia | -62% | -62% |
|
Slovenia | -63% | -63% |
|
EU27 | -53% | -52% |
|
Turkey | - | - |
|
Iceland | - | - |
|
Liechtenstein | - | - |
|
Norway | - | -27% |
|
Switzerland | - | -39% |
|
This indicator factsheet uses emissions data from the EEA dataservice dataset 'EEA aggregated and gap-filled air emission data'. The 2010 projection estimates reported by the EU-27 Member States under the requirements of the NEC Directive are also included in the analysis http://www.eea.europa.eu/themes/air/datasets). The dataset 'EEA aggregated and gap-filled air emission data' is consistent with the annual 'European Community LRTAP Convention emission inventory' compiled by EEA. This inventory is based on the officially reported emissions data from countries submitted to the UNECE LRTAP Convention and supplemented with additional data reported under the NEC Directive and the EU GHG Monitoring Mechanism/UNFCCC. Air pollutant emissions data are reported by countries using the Nomenclature For Reporting (NFR) sectroal classification system developed by UNECE/EMEP. For the purposes of the 'EEA aggregated and gap-filled air emission dataset', the numerous NFR sectors reported by countries are combined into the following EEA aggregated sectors to allow a simpler analysis: The following table shows how the NFR categories used by countries to report their emissions are aggregated into the EEA aggregated sectors listed above:
EEA Code | EEA classification | Non-GHGs (NFR) |
0 | National totals | National Total |
1 | Energy industries | 1A1 |
3 | Industry (Energy) | 1A2 |
2 | Fugitive emissions | 1B |
7 | Road transport | 1A3b |
8 | Other transport (non-road mobile machinery) | 1A3 (excl 1A3b) + sectors mapped to 8 in table below |
9 | Industry (Processes) | 2 |
4 | Agriculture | 4 + 5B |
5 | Waste | 6 |
6 | Other (Energy) | 1A4a, 1A4b, 1A4b(i), 1A4c(i), 1A5a |
10 | Other (non-energy) | 3 + 7 |
14 | Unallocated | Difference between NT and sum of sectors (1-12) |
12 | Energy Industries (Power Production 1A1a) | 1A1a |
The 'unallocated' sector (14) corresponds to the difference between the reported national total and the sum of the reported sectors for a given pollutant/country/year combination. It can be either negative or positive. Inclusion of this additional sector means that the officially-reported national totals do not require adjustment to ensure they are consistent with the sum of the individual sectors reported by countries.
Where reported data from countries is incomplete, simple gap-filling techniques are used in the 'EEA aggregated and gap-filled air emission dataset' in order to obtain a consistent time-series (see following section).
To obtain an aggregated estimate of the total particulate matter emissions, the emission values of the individual pollutants are multiplied by a particulate formation potentials factor (de Leeuw, 2002) prior to aggregation. The factors are primary PM10: 1.0; NOx: 0.88; SO2: 0.54 and NH3: 0.64. Results are expressed in terms of 'PM10 equivalents' (ktonnes).
Where PM10 data was not reported by countries to UNECE/EMEP, emission estimates for 1990, 1995, 2000 and 2005 were obtained from the IIASA GAINS model PM10 module [1].
To allow trend analysis, where countries have not reported data for one or more years, data in the 'EEA aggregated and gap-filled air emission dataset' has been interpolated to derive the emissions for the missing year or years. If the reported data is missing either at the beginning or at the end of the period, the emission value is assumed to equal the first or last reported value. The use of gap-filling may lead to artificial trends, but it is considered necessary if a comprehensive and comparable set of emissions data for European countries is to be obtained. A spreadsheet containing a record of the gap-filled data is available from EEA's European Topic Centre on Air and Climate Change (ETC/ACC) (http://air-climate.eionet.europa.eu/)
[1] http://www.iiasa.ac.at/rains/gains-online.html?sb=9
No methodology references available.
The use of interpolation/extrapolation procedures to gap-fill the underlying emissions dataset and the application of particulate matter formation factors both lead to uncertainties. With respect to the particulate matter formation factors, these are assumed to be representative for Europe as a whole; on the local scale different factors might be estimated. An extensive discussion on the uncertainties in these factors is available in de Leeuw (2002).
The PM10, NOx, SO2 and NH3 emissions data officially submitted by EU Member States and other EEA member countries follow common calculation (EMEP/EEA 2009) and reporting guidelines (UNECE 2003).
Sulphur dioxide emission estimates in Europe are thought to have an uncertainty of about 10% as the sulphur emitted comes from the fuel burnt and therefore can be more accurately estimated. However, because of the need for interpolation to account for missing data the complete dataset used here will have higher uncertainty. EMEP has compared modelled (using emission inventory data) and measured concentrations throughout Europe (EMEP, 1998). From these studies differences in the annual averages have been estimated in the order of 30% consistent with an inventory uncertainty of 10% (there are also uncertainties in the measurements and especially the modelling).
Nitrogen oxide emission estimates in Europe are thought to have an uncertainty of about +/-20% (EMEP, 2009), as the NOx emitted comes both from the fuel burnt and the combustion air and so cannot be estimated accurately from fuel nitrogen alone. However, because of the need for interpolation to account for missing data, the complete dataset used will have higher uncertainty. The trend is likely to be more accurate than the individual absolute annual values - the annual values are not independent of each other.
Ammonia emissions are also relatively uncertain. NH3 emission estimates in Europe are more uncertain than those for NOx or SO2 due largely to the diverse nature of agricultural sources - which account for the vast majority of NH3 emissions. It is estimated that they are around +/-30% (EMEP, 2009). The trend is likely to be more accurate than the individual absolute annual values - the annual values are not independent of each other.
Primary PM10 data is likely to be of high uncertainty.
References
This indicator on emissions of particulate matter is updated annually by EEA and is used regularly in our reports on the state of the environment. It is therefore important to note the uncertainties related to methodology and data sets.
Work specified here requires to be completed within 1 year from now.
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For references, please go to https://www.eea.europa.eu/data-and-maps/indicators/emissions-of-primary-particles-and-1 or scan the QR code.
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