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TFIAM meeting 27 May 2005 Berlin. EEA scenario 2005 project : Low greenhouse gas emission pathways Presentation by Hans Eerens EEA Topic Centre Air and Climate Change Netherlands Environmental Assessment Agency (MNP). It is not most important to predict the future,
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TFIAM meeting27 May 2005 Berlin EEA scenario 2005 project : Low greenhouse gas emission pathways Presentation by Hans Eerens EEA Topic Centre Air and Climate Change Netherlands Environmental Assessment Agency (MNP) It is not most important to predict the future, but to be prepared for it Perikles (about 500-429 b. Chr.)
Introduction, methodology • Energy and GHG projections • Regional air quality, emission trend and costs 2030 • Urban background trend (PM10, NO2, SOMO-35) • Street increment (PM10, NO2)
ETC/ACC partners and others involved: • RIVM: IMAGE/TIMER/FAIR/EUROMOVE models, global scenarios, climate effects, coordination • NTUA: PRIMES/GEM-E3/PROMETHEUS models, European energy system • IIASA: RAINS model, European air quality • DNMI: EMEP model • AEAT: non-CO2 GHGs and non-energy CO2 emissions • IPTS: POLES model, technology variants • AUTH: OFIS, OSPM model, transport & urban Air Quality • NILU: Air Pollution State & policies • CCE: Air pollution effects on ecosystems/critical loads • EEA: project guidance, links with issues other than air and climate change
ETC/ACC SoEOR2005 subreport 6Introduction Objectives: • Explore air pollution and climate change trends and projections using 3 scenarios: • Long-Range Energy Modelling (LREM) • Low greenhouse gas Emission Pathways (LGEP) • Plus variants • Target assessment on possible use for EU’s post-2012 debate
SoEOR2005: flow chart of models used M Economy GEM-E3, PROMETHEUS Transport Agriculture PRIMES COPERT III, TREMOVE, TREND AEA-T model RAINS Emissions CO2 CH4, N2O, (Europe) MERLIN HFC, PFC, SF6 (Europe) EMEP CO2 Permit OFIS Price OPSM POLES TIMER FAIR Regional concen-tration:SO2, NO, NH3, PM, O3 Urban conc. PM, NO2, O3 Sinks Street increments CO2, CH4, N2O, HFC, PFC, SF6 IMAGE Energy Price WaterGap CC impacts AQ impacts
Focus air pollution assessment: • Emission/effects/costs change between 2020 and 2030 assuming: • No climate change policies • Increased climate change policies • Different economic growth path • High renewable/biomass ambition • Increase/decrease use of nuclear energy Emission/activity due to various agricultural scenario’s: • CAP reform • Animlib (reduced border protection for pig & poultry, dairy liberalization) • Best environmental practice
Data availability and dissemination • SoEOR2005 report • SoEOR2005 sub reports • SoEOR2005 technical papers • Articles • SoEOR2005 Scenario information platform (web-based application, indicator based country specific information) including maps • presentations
Global development in energy use 1980-2100:hydropower, non-thermal electricity, traditional biofuels, modern biofuels, natural gas, oil and coal. Left baseline (1170 EJ by 2100), right LGEP (730 EJ by 2100)
Projected global energy investment 2000-2050Investments in respectively energy savings, electricity, modern biofuels and fossil fuel. Left baseline (4400 thousand million €/year by 2100), right LGEP (4600 thousand million €/year by 2100
Past and projected prices of fossil fuels and electricity 1970-2050
Changes in the fuel mix of EU-25 gross inland energy consumption compared to the baseline in 2030
Further CO2 reductions are possible through enhanced renewable deployment (meeting targets), while phasing out nuclear risks increasing emissions if these plants are replaced by fossil fuels
Change in air pollutants emissions in developed and developing regions under the baseline and LGEP scenarios relative to year 2000
Change in emissions of air pollutants in the EU 25 region relative to 2000
Identified anthropogenic contribution to modelled grid-average PM2.5 concentrations (annual mean, µg/m3) , 2000, 2020-CAFÉ, 2030-CC, 2030-CC-MFR
Percentage of total ecosystems area receiving nitrogen deposition above the critical loads for the emissions of the year 2000 (top left panel), the current legislation for 2020 (top right), the LGEP in 2030 and the maximum feasible reduction case for 2030 (LGEP-B-MFR – bottom right panel).
Percentage of forest area receiving acid deposition above the critical loads for the emissions of the year 2000 (top left panel), CAFE 2020 (top right), LGEP (bottom left) and LGEP-MFR (bottom right panel).
Regional air quality and impacts Loss in statistical life expectancy that can be attributed to the identified anthropogenic contributions to PM2.5 (in months) for the emissions of the year 2000 (top left panel), ‘CAFE 2020’ (top right), the “LGEP” (bottom left) and the LGEP-MFR (bottom right) panel).
Regional air quality and impacts Grid-average ozone concentrations in ppb.days expressed as SOMO35 for the emissions of the year 2000 (top left panel), CAFE 2020 (top right), LGEP (bottom left) and LGEP-MFR (bottom right panel).
Provisional estimates of premature mortality attributable to ozone (cases of premature deaths per million inhabitants per year)
Percentage of total ecosystems area receiving nitrogen deposition above the critical loads for eutrophication by country group and scenario
Percentage of freshwater ecosystems area receiving acid deposition above the critical loads for by scenario and country. Calculation results for the meteorological conditions of 1997, using grid-average deposition. Critical loads data base of 2004.
Climate change benefit Emission control costs EU-25 billion Euro/year
The trend engine:What is included? • About 50 crop and animal products/activities, covering agriculture according to the definition of Economic Accounts • Plus some major derived products (dairy, oils and cakes) • Areas/herd sizes, yields, market balances, producer and consumer prices, feed requirements … • Time series from 1985 onwards, projected till 2030 • EU25 (minus Cyprus und Malta)
80% organic farming, full covered storage facilities, improved manure handling in the stable. Better application techniques as injections are assumed to reduce ammonia losses during application to 5%No changes are assumed regarding the grazing practice
Urban background: • 20 Cities (MERLIN project), 53 million inhabitants • EMEP regional background (1997) • OFIS model urban background • City specific fleet composition data
two hypothetical street canyon configurations: street 1:narrow canyon with a traffic volume of 20,000 vehicles per day street 2:wide canyon with a traffic volume of 60,000 vehicles per day Orientation: East to West , centrally located, specific fleet composition, average vehicle speed of 26 km/h
Mean annual NO2 street increments (μg/m3) in 20 European cities: OSPM model results compared with observations
Mean annual PM10 street increments (μg/m3) in 20 European cities: OSPM model results compared with observations.
PM10: range modelled street increment 5-16 μg/m3,(average10.3μg/m3). • PM10: Average measured street increment 11.1 μg/m3, (not including exceptionally large street increment for Lisbon). • PM10, 16 station background-street pairs (< 1km distance) from airbase: 6.9 μg/m3 • HDV% and average vehicle speed per day most sensitive assumptions for street emission calculations
basis reduction: discussions on Euro V and Euro VI held at EU level (European Commission, 2004)
COPERT III,TRENDS and input traffic activity data originating from TREMOVE (version 2.23 ).
While a transition such as LGEP can bring enormous benefits, it also presents substantial challenges • Benefits • Decoupling of CO2 emissions from economic growth and reduced European contribution to global climate change • Reduced emissions of air pollutants • Reduced energy import dependency (-20%) • Employment in industrial and agricultural sectors selling biofuels and clean and low energy technologies to Europe and the world • Challenges • Large changes required in the energy sector • Difficult choices over controversial technologies such as nuclear power and carbon capture and storage • Potential for energy efficiency is well-known, but achieving energy reductions in practice will require new policy approaches • Costs may be small in relation to GDP, but are nevertheless large in real terms