APE_F01: Emissions of acidifying substances - outlook from LRTAP

Assessment versions

Published (reviewed and quality assured)

• No published assessments

Rationale

Justification for indicator selection

Emissions of acidifying substances cause damage to human health, ecosystems, buildings and materials (corrosion). The effects associated with each pollutant depend on its potential to acidify and the properties of the ecosystems and materials. The deposition of acidifying substances still often exceeds the critical loads of ecosystems across Europe.

The outlook presents plausible future for how much air pollution is released into the atmosphere due to economic development, increased energy consumption, industrial production, traffic and agricultural activities in 43 European countries. It also explores how pollution from above mentioned sources is transported in the atmosphere, and which regions are affected. The outlook helps to identify to which extend the policy targets set in the UNECE Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone, the EU National Emissions Ceilings Directive  (2001/81/EC) and the EU Thematic Strategy on Air Pollution are achievable and what additional policy measures should be taken.

Scientific references

• No rationale references available

Indicator definition

Definition:

Emissions of acidifying pollutants tracks trends in anthropogenic emissions of acidifying substances such as nitrogen oxides, ammonia, and sulphur dioxide, each weighted by their acidifying potential. Outlook form EMEP LRTAP provides information for nitrogen oxides, sulphur dioxide and ammonia. It is presented in total volumes of pollutants from all sources by sectors: power plants, process industry, domestic, road transport, off-road, and other.

Model used:

GAINS/RAINS, EMEP

Ownership: 

UNECE Convention on Long-range Transboundary Air Pollution (LRTAP)

Temporal coverage:

Emissions' trends: 2000-2007, projections: 2010, 2020

Geographical coverage:

Units

The indicator is measured in Gg of acidifying pollutant per year (EMEP data base) and/or in kilotones per year /acidifying equivalent/ (GAINS/RAINS database)

Policy context and targets

Context description

Pan-European policy context

At the Pan-European level this indicators is related to the implementation of the 1999 Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone. The Protocol sets emission ceilings for 2010 for four pollutants: sulphur, NOx, VOCs and ammonia. These ceilings were negotiated on the basis of scientific assessments of pollution effects and abatement options. Parties whose emissions have a more severe environmental or health impact and whose emissions are relatively cheap to reduce will have to make the biggest cuts.

EU policy context

[1] Directive 2001/81/EC, on national emissions ceilings (NECD) for certain atmospheric pollutants. (consolidated version)

EECCA policy context

Most of the EECCA countries ratified the 1979 Convention on Long-Range Transboundary Air Pollution. These are A list of countries ratified the 1979 Convention: Armenia (1997), Azerbajan (2002), Belarus (1980), Georgia (1999), Kazakhstan (2001), Kyrgyzstan (2000), Republic of Moldova (1995), Russian Federation (1980), the Ukraine (1980).

At the same time only two of them signed in the Gothenburg Protocol to abate acidification, eutrophication and ground-level ozone, notably Armenia (1999), Republic of Moldova (2000).

Targets

Pan-European level
Once the Gothenburg Protocol is fully implemented, European sulphur emissions should be cut by at least 63%, NOx emissions by 41% and its ammonia emissions by 17% compared to 1990.

The Protocol also sets tight limit values for specific emission sources (e.g. combustion plant, electricity production, dry cleaning, cars and lorries) and requires best available techniques to be used to keep emissions down. Guidance documents adopted together with the Protocol provide a wide range of abatement techniques and economic instruments for the reduction of emissions in the relevant sectors, including transport.

EU level

Emissions of NO_x and SO₂ are covered by the EU National Emission Ceilings Directive (NECD) (2001/81/EC) and the Gothenburg protocol under the United Nations Convention on Long-Range Transboundary Air Pollution (LRTAP Convention) (UNECE 1999).

The NECD generally involves slightly stricter emission reduction targets than the Gothenburg Protocol for EU-15 countries for the period 1990-2010.

Table: Percentage reduction required by 2010 from 1990 levels by country, for emissions of acidifying substances: NOx, SOx and NH3 (emission targets weighted by acidifying potential).

EECCA level
No specific targets at the sub-regional level are set.

Related policy documents

• 1999 Protocol to Abate Acidification, Eutrophication and Ground-level Ozone
  Convention on Long-range Transboundary Air Pollution 1999 Protocol to Abate Acidification, Eutrophication and Ground-level Ozone, amended on 4 May 2012.
• UNECE Convention on Long-range Transboundary Air Pollution
  UNECE Convention on Long-range Transboundary Air Pollution.

Methodology

Methodology for indicator calculation

The projections of the acidifying pollutants for this outlook are based on the GAINS (former RAINS) Model. Its European implementation covers 43 countries in Europe including the European part of Russia. GAINS estimates emissions, mitigation potentials and costs for six air pollutants (SO2, NOx, PM, NH3, VOC) and for the six greenhouse gases included in the Kyoto protocol.

The new GAINS model incorporates the latest version of the RAINS-Europe model (Regional Air Pollution Information and Simulation) as it has been prepared and reviewed for the CAFE programme and the 2007 revision of the NEC directive. Emissions of pollutants are calculated as a product of activity level, uncontrolled emission factor, removal efficiency of control technology applied in a given sector, and implementation level of that technology in a given emission scenario.

Overview of the model

The Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS)-Model provides a consistent framework for the analysis of co-benefits reduction strategies from air pollution and greenhouse gas sources.

The model considers emissions of:

• Carbon dioxide (CO2)
• Methane (CH4)
• Nitrogen oxides (NOx)
• Nitrous oxide (N2O)
• Particulate matter (TSP, PM10, PM2.5 and PM1)
• Sulfur dioxide (SO2)
• Volatile organic compounds (VOC)

Certain versions of the GAINS Model also contain:

• Ammonia (NH3)
• Carbon monoxide (CO)
• Fluorinated greenhouse gases (F-Gases)

The GAINS Model consists of several screen options, which display information pertaining to:

• Economic Activity Pathways
  activities causing emissions (energy production & consumption, passenger & freight transport, industrial and agricultural activities, solvent use, etc.)
• Emission Control Strategies
  the evolution of emissions and control over a given time horizon
• Emissions Scenarios
  emissions are computed for a selected emissions scenario (combination of energy pathway and emissions control strategy), emission factors, results displays, and input values are also available under this action
• Emission Control Costs
  displays emission control costs computed for a selected emissions scenario
• Impacts
  presents ecosystem sensitivities and human health impacts of air pollution
• Data Management
  provides an interactive interface where owner-specific data can be modified, updated, exported, and downloaded

The GAINS Model simultaneously addresses health and ecosystem impacts of particulate pollution, acidification, eutrophication and tropospheric ozone. Simultaneously, the GAINS Model considers greenhouse gas emission rates and the associated value per ton of CO2 equivalence. Historic emissions of air pollutants and GHGs are estimated for each country based on information collected by available international emission inventories and on national information supplied by individual countries. The GAINS Model assesses emissions on a medium-term time horizon, emission projections are specified in five year intervals through the year 2030.

Options and costs for controlling emissions are represented by several emission reduction technologies. Atmospheric dispersion processes are often modeled exogenously and integrated into the GAINS Model framework. Critical load data and critical level data are often compiled exogenously and incorporated into the GAINS modeling framework.

The model can be operated in the 'scenario analysis' mode, i.e., following the pathways of the emissions from their sources to their impacts. In this case the model provides estimates of regional costs and environmental benefits of alternative emission control strategies. The Model can also operate in the 'optimization mode' which identifies cost-optimal allocations of emission reductions in order to achieve specified deposition levels, concentration targets, or GHG emissions ceilings. The current version of the model can be used for viewing activity levels and emission control strategies, as well as calculating emissions and control costs for those strategies.

 The The current version (June 2008) allows access to

• the recent set of activity data and projections for all European countries that has been developed for the revision of the NEC directive,
• computations of emissions, emission projections and control costs for the air pollutants (SO2, NOx, PM, NH3, VOC),
• emissions, control measures and emission control costs of the optimized policy scenarios that are analyzed for the NEC review,
• computation and display of concentration and deposition fields of selected air pollutants,
• computation and display of health and environmental impacts of air pollutants,
• emission inventories and projections for CO2,
• estimates for the other greenhouse gases (CH4, N2O, HFC, PFC, SF6).
• Atmospheric dispersion processes over Europe for all pollutants are modelled on the basis of results of the European EMEP model developed at the Norwegian Meteorological Institute (Simpson et al., 2003).Atmospheric dispersion processes over Europe for all pollutants are modelled on the basis of results of the European EMEP model developed at the Norwegian Meteorological Institute (Simpson et al., 2003).

For more information see: http://gains.iiasa.ac.at/gains/docu.EU/index.menu?page=448 (requires regstration)

Overview of the EMEP model

The European Monitoring and Evaluation Program (EMEP) developed a Unified EMEP model in order to provide, on a regular basis, governments and other parties under the Convention on Long Range Transboundary Air Pollution with scientific information that can support the continuing development and evaluation of the protocols under the convention. Unified EMEP model combines several models. For integrated assessment analyses it uses RAINS model developed and maintained at the Center for Integrated Assessment Modeling (CIAM). It also uses MSC-W model for atmospheric dispersion and deposition of acidifying compounds, compounds causing eutrophication, ground level ozone and particulate matter developed by the Meteorological Synthesizing Centre West (MSC-W), one of the centers under the EMEP programme. Additionally it uses EMEP Chemical Transport Models for the regional atmospheric dispersion and deposition of heavy metals (Cd, Pb, Hg) and selected persistent organic compounds (PCB, PAH, HCB, PCDD/Fs, g-HCH). The latest model version has been documented in the EMEP Status report I, Part I (Simpson et. al., 2003) and the EMEP Status report 2004 (Tarrasón et al., 2004) where a few updates are described.

The model domain covers Europe and the Atlantic Ocean. The model grid has a horizontal resolution of 50 km at 60 ⁰N, which is consistent with the resolution of emission data reported to CLRTAP. In the vertical, the model has 20 sigma layers reaching up to 100 hPa. The unified model uses 3-hourly resolution meteorological data from the PARLAM-PS model, a dedicated version of the HIRLAM (high resolution limited area model) numerical weather prediction model.

The emissions consist of girded annual national emissions of sulphur dioxide, nitrogen oxides, ammonia, non-methane volatile organic compounds and carbon monoxide. They are available in each cell of the 50 * 50 km2 model grid and distributed temporally according to monthly and daily factors derived from data provided by the University of Stuttgart (IER). Concentrations of 71 species are computed in the latest version of the Unified EMEP model (56 are advected and 15 are short-lived and not advected). Four secondary and two primary PM compounds are included in the model. The sulphur and nitrogen chemistry is coupled to the photo-chemistry, which allows a more sophisticated description of e.g. the oxidation of sulphur dioxide to sulphate, also including oxidant limitations.

Dry deposition is calculated using the resistance analogy and is a function of the pollutant type, meteorological conditions and surface properties. Parametrisation of wet deposition processes includes both in-cloud and sub-cloud scavenging of gases and particles using scavenging coefficients.

For more information see: http://www.emep.int/

Use of Scenarios

The LRTAP uses GAINS/RAINS and EMEP to calculate global and European emissions for two categories of scenarios: 'current legislation'  and  'maximum technically feasible reduction' (MFR) scenarios.

The 'current legislation' (CLE) scenario reflects the current perspectives of individual countries on economic development and takes into account the anticipated effects of presently decided emission control legislation.

The 'maximum technically feasible reduction' (MFR) scenario outlines the scope for emission reduction offered by a full implementation of the best available emission control technologies. Considering this calculation as a theoretical analysis of the long-term reduction potential, practical limitations on the penetration of most advanced emission control measures imposed by the gradual turnover of existing capital stock especially in the short run are not taken in to account, and the obviously high costs of such a theoretical emission control strategy are not estimated. On the other hand, in this scenario the potential for emission reductions offered by structural changes, such as increased energy efficiency measures, fuel substitution, more efficient production technologies or reduced transport demand is not considered. Earlier studies have shown that the emission reduction potential of such measures is considerable and that some of them could be even cost-effective (e.g., Rentz et al., 1994, Van Vuuren et al., 2005). The latest version of the model allows to build scenarios which accounts for structural changes. Such set of scenarios is developed by the IISAA in order to identify new NEC for the EU.

Methodology for gap filling

The input data for RAINS model comes from different international sources as main data sets. National data were used for verification of the international data sources and for gap filling (see data sets).

For Unified EMEP model, officially reported country data constitutes maximum 60% of the data in the EMEP inventory; the remaining 40% are MSC-W estimates. For several countries, officially reported emissions were not available or not reliable for the years. They were analyzed in the framework of the model, and thus replaced with expert estimates. The largest source of MSC-W estimates is emission data from the regional European RAINS model.

Methodology references

No methodology references available.

Data specifications

EEA data references

• No datasets have been specified here.

External data references

• Input data for RAINS model - Emission factors for NOx, SO2
• Input data for RAINS model - Emission standards for Europe
• Input data for RAINS model - Emission standards other parts of the world
• Input data for RAINS model - energy projections for EU countries from PRIMES model
• Input data for RAINS model - energy projections from national sources
• Input data for RAINS model - livestock projectionist for the EU countries
• Input data for RAINS model - livestock projections for other countries from FAO
• Input data for RAINS model - livestock projections from national projections
• Input data for RAINS model - transport activity from TREMOVE model
• Output data from RAINS model, total and by sector - NOx emissions
• Output data from RAINS model, total and by sector - SO2 emissions
• Output data from RAINS model, total and by sector - NH3 emissions

Data sources in latest figures

Uncertainties

Methodology uncertainty

RAINS model
A methodology has been developed to estimate uncertainties of emission calculations based on uncertainty estimates for the individual parameters of the calculation (Suutari et al., 2001). It was found that uncertainties in modeled national emissions of SO2 and NOx in Europe typically lie in the range between 10 and 30 percent (Outlook from RAINS model). In general, the uncertainties are strongly dependent on the potential for error compensation. This compensation potential is larger (and uncertainties are smaller) if calculated emissions are composed of a larger number of similar-sized source categories, where the errors in input parameters are not correlated with each other. Thus, estimates of national total emissions are generally more certain than estimates of sectoral emissions.

The uncertainty in input parameters showed that the actual uncertainties are critically influenced by the specific situation (pollutant, year, country). Generally, however, the emission factor is an important contributor to the uncertainty in estimates of historical emissions, while uncertainty in the activity data dominates the future estimates.

For more information see http://www.iiasa.ac.at/rains/review/suutari.pdf.

EMEP models
Uncertainties in the model formulation itself give rise to uncertain deposition estimates. It has been shown that the EMEP model performance is rather homogeneous over the years (Fagerli et al. 2003b), but depend on geographical coverage and quality of the measurement data. The EMEP model has also been validated for nitrogen compounds in Simpson et al. (a) and for dry and wet deposition of sulphur, and wet depositions for nitrogen in Simpson et al. (b) with measurements outside the EMEP network.
For more information see http://www.emep.int/publ/reports/2006/status_report_1_2006_ch.pdf.

Data sets uncertainty

National projections reflect national governmental expectations and probably in many cases also merely policy ambitions. Thus there is no guarantee for international consistency, e.g., in the volumes of exports and imports or in the underlying assumptions on the development of oil prices. However, the value of this set of projections is that it reflects bottom-up expectations on economic development as seen today by the individual countries.

For more information see methodology uncertainty.

Rationale uncertainty

N.A.