Global bottom-up emission inventories: methodologies, application in atmospheric chemistry modeling and possible verification through satellite measurements.

Slides:

Advertisements

Similar presentations

1 Emissions of air pollutants and greenhouses by world country on 0.1 x 0.1 degree grid The EDGAR team: John van Aardenne, Ulrike Doering, Greet Maenhout,

Advertisements

CROATIAN NATIONAL SYSTEM FOR ESTIMATING GHG FROM AGRICULTURE

1 The European Environment Agency and emissions from international maritime transport John van Aardenne, Air and Climate Change Programme February 9, 2011.

On the Gridding Emissions Globally Muntean M. , Pagliari V

Air Pollution and Climate

TNO MACC-II European emissions Model-ready emission set for Jeroen Kuenen, Hugo Denier van der Gon, Antoon Visschedijk TNO, Utrecht, The Netherlands.

Air quality in Europe report. Air pollution impacts human health, contributes to climate change and damages ecosystems. Here are some of the pollutants.

National Inventories of Greenhouse Gas Emissions Yamil Bonduki Coordinator National Communications Support Programme.

Assessment of black carbon in the Arctic: new emission inventory of Russia, model evaluation and implications Kan Huang 1, Joshua S. Fu 1,2, Xinyi Dong.

1 Emission data needs for international reporting and assessments Joint UNECE and EIONET workshop on emission inventories and projections 6-8 May 2002,

Science questions How will source-receptor relations change due to expected changes in emissions? How should future emission scenarios be constructed?

SLCP and other air pollutants: an introduction for policy makers Jun-ichi Kurokawa Asia Center for Air Pollution Research (ACAP), Niigata, Japan High Level.

Integrated Assessment Modeling, cost-effectiveness, and agricultural projections in the RAINS model Zbigniew Klimont International Institute for Applied.

Carbon sequestration in China’s ecosystems, Jingyun Fang Department of Ecology Peking University Feb. 14, 2008.

From experience of emission inventory preparation in Belarus JOINT ACCENT/GEIA Workshop on Anthropogenic emissions for non-OECD countries in global inventories.

1 Global Change: Greenhouse Gases Environmental Sustainability Educational Resources prepared by Gregory A. Keoleian Associate Research Scientist, School.

37th meeting of the Task Force on Integrated Assessment Modeling February 2010, UNECE, Geneva Towards widening the application of integrated assessment.

1 Introduction, reporting requirements, workshop objectives Workshop on greenhouse gas and ammonia emission inventories and projections from agriculture.

Workshop QA/QC 2-3 Oct 2004 Copenhagen Comparing National GHG Inventories with Independent Estimates Including Inverse Monitoring Peter Bergamaschi, Frank.

Research Week 2009‐2010 University of Mauritius A Sookun, R Boojhawon, SDDV Rughooputh1.

Joint Intersectoral Task Force on Environmental Indicators Geneva 5 – 7 November 2013 Transport and environment: newly proposed indicators Vladislav Bizek.

NATIONAL ENVIRONMENTAL RESEARCH INSTITUTE AARHUS UNIVERSITY Marlene Plejdrup, MSc. physical geography Stockholm 4/ SPATIAL DISTRIBUTION OF EMISSIONS.

Harmonization process between inventory and Model projections of Air Pollution Emissions in Italy October, TFEIP Workshop on Emission Projections.

Simulation of European emissions impacts on particulate matter concentrations in 2010 using Models-3 Rob Lennard, Steve Griffiths and Paul Sutton (RWE.

1 Co-benefits of options for cleaner energy use in China Wellcome Trust Meeting, London, May 27, 2008 Kristin Aunan, CICERO China – an important country.

Application of IIASA GAINS Model for Integrated Assessment of Air Pollution in Europe Janusz Cofala International Institute for Applied Systems Analysis.

Global Emissions from the Agriculture and Forest Sectors: Status and Trends Indu K Murthy Indian Institute of Science.

IIASA Sources of PM Emissions in Europe. IIASA RAINS Emission and cost calculation scheme Activity data Vintages Other Emission factor Control strategies,

The GAINS model State of play

Investigating the Links Between GMES & Emission Inventories - An Update Justin Goodwin: ETC-ACC Supported by EEA TFEIP Meeting Stockholm 3th May 2011.

1 ESA Noordwijk 20 Jan 2004 Frank Raes, Peter Bergamaschi, Hugh Eva, Alan Belward Institute for Environment and Sustainability Joint Research Centre European.

1 JRC – Ispra DG JRC and EC4MACS IPTS Institute for Prospective Technology Studies - Peter Russ - Antonio Soria - Szabolc Szekeres IES Institute for Environment.

Emission control in Bulgaria The involved institutions at national and local (sub-national) levels in Emissions inventory are Ministry of Environment.

Clean Air The revision of the National Emission Ceilings Directive and agriculture FERTILIZERS FORUM 23 June 2015.

1 EEA Activities Collect, process and disseminate air emission and air quality data Report on trends in air emissions and in air quality Support the development,

New concepts and ideas in air pollution strategies Richard Ballaman Chairman of the Working Group on Strategies and Review.

Igor Trpevski University of St. Cyril and Methodius Skopje,

1 Global Emissions of Air Pollutants and Greenhouse Gases John van Aardenne Climate Change Unit Acknowledgements: Valerio Pagliari (Italy), Suvi Monni.

Compilation of emission inventories The situation in the Netherlands Special Session of the UNCEEA on Climate Change (New York, 25 June afternoon)

Aim and objective of the parallel activity on emissions inventories Aim: each Malé Declaration country to compile (during Phase III) air pollutant emission.

Reported emissions for models Perspectives from MACC & MACC-II projects, and the use of the LOTOS-EUROS AQ model Jeroen Kuenen, Hugo Denier van der Gon,

Stakeholders’ Meeting of the Malé Declaration 14 th October 2005, Delhi Compilation of emissions inventories using the Malé Declaration Emission inventory.

On behalf of the SCIAMACHY Team SCIAMACHY Measures Air Pollution Andreas Richter.

Agriculture Agriculture Sector Inventory Training Workshop, Agriculture Sector 7/72008 Khartoum Higher Council for Environment and Natural Resources.

EU legal background Air pollution. EU legal background: Air pollution Air pollution in Europe is regulated by several policies, which are targeting the.

Air Quality Forecasting in China using a regional model Bas Mijling Ronald van der A Henk Eskes Hennie Kelder.

The links to global problems Presentation at the 25 th anniversary special event of the Convention on Long-range Transboundary Air Pollution “Past successes.

1 Co-benefits of CDM projects in China CDM and Climate Policy: Multidisciplinary Perspectives MILEN Workshop 18 November 2009 Holmenkollen Park Hotell,

Setting the Boundaries Stephen Boyle, Principal Consultant, Climate Change and Policy 11 th March 2009 A world leading energy and climate change consultancy.

11 September 2015 On the role of measurements and modelling in Dutch air quality policies Guus Velders The Netherlands (RIVM)

Joint Intersectoral Task Force on Environmental Indicators Fifth session Geneva, 4 – 6 July 2012 Grenhouse Gas Emissions Introductory Overview Vladislav.

V.Sedyakin A. Nakhutin Institute of Global Climate and Ecology (IGCE) Institute of Global Climate and Ecology (IGCE)

European Environment Agency An EEA / ETC ACM project on emission scenarios John van Aardenne 7th meeting of the TFEIP’s projections expert panel 2nd May.

1 Emission data needs for assessments and international reporting Joint UNECE and EIONET workshop on emission inventories and projections 9-11 May 2001,

Data BaseCompareVerifyDrivers EDGARv4 UNFCCC EMEP GAINS REAS MICS-Asia PKU VULCAN TNO-MACC EPRTR HTAP_V2 Econo- metrics Decom- position Inverse modeling.

Variability in emission parameters of ozone precursors’ emissions in the GAINS model TFIEP/TFMM Workshop on Uncertainties in emission inventories and atmospheric.

HYMN meeting Bremen Current challenges in modeling of CH 4, N 2 O and H 2 based on comparison to surface observations. 2. Suggestion for.

Workshop on the Criteria to establish projections scenarios Sectoral projection guidance: industrial processes Mario Contaldi, TASK-GHG Emanuele Peschi,

Spatial allocation of diffuse emissions sources

Photo credit: Radha Muthiah

The European Environment Agency and emissions from international maritime transport John van Aardenne, Air and Climate Change Programme February.

Overview of existing excretion factors

vkm in transport modelling

Linking global scale and European scale modelling:

The Thematic strategy and the possible measures of action

Services to support the update of the EMEP EEA Emission Inventory Guidebook, in particular on methodologies for black carbon emissions.

Z.Klimont, J.Cofala EMEP Centre for Integrated Assessment Modelling (CIAM) Variability in emission parameters of ozone precursors’ emissions in the GAINS.

Second Stakeholder Expert Group meeting 19-20/01/2012

Report on the EEA workshop dedicated to the use of GMES data for emission inventories John Van Aardenne (EEA), Justin Goodwin (Aether), Peter de Smet.

The European Commission’s science

Presentation transcript:

Global bottom-up emission inventories: methodologies, application in atmospheric chemistry modeling and possible verification through satellite measurements John van Aardenne European Commission DG Joint Research Centre "The views expressed are purely those of the presenters and may not in any circumstances be regarded as stating an official position of the European Commission."

EDGAR project: Ulrike Doering (JRC) Greet Maenhout (JRC) Suvi Monni (JRC) Jos Olivier (PBL) Valerio Pagliari (JRC), Jeroen Peters (PBL), Fulgencio SanMartin (now at OECD) Lorenzo Orlandini (now at DG AGRI), John van Aardenne (JRC, project leader)

Reliability of emission data Cost / human investment Continuous emissions monitoring extrapolation of existing emissions data Source sampling Emissions modeling Implied emission factor calculation Technology based emission factor calculation How do we calculate emission inventories E-PRTR EDGAR, National Reports National Reports Satellite observations

The Emissions Database for Global Atmospheric Research (EDGAR v4) provides global past and present day anthropogenic emissions of greenhouse gases and air pollutants by country and on spatial grid Inventories for policy purposes: - monitoring the progress/compliance in meeting specific emission targets - scenario studies in emissions reduction options ( period) Inventories for scientific purposes: - understanding processes that lead to anthropogenic and natural emissions - understanding change in atmospheric composition due to emissions trends Science for policy: - impact modeling: human health, ecosystems - assessment of transport of air pollutants across countries and continents (e.g HTAP) 1. Introduction: the EDGAR project Years CO 2 CH 4 N 2 O HFCs PFCs SF 6 CFCs HCFCs CO SO 2 NO X NMVOC NH 3 PM 2.5 PM 10 OC BC

2. Methodology: source categories Main groups: - Energy: Fuel Combustion (IPCC 1A) - Fugitive emissions from fuel (IPCC 1B) - Industrial Processes (non-combustion, IPCC 2) - Product Use (IPCC 3) - Agriculture (including Savanna burning), (IPCC 4) - Land Use Change and Forestry (IPCC 5) - Waste (IPCC 6) - Other anthropogenic sources (fossil fuel fires) (IPCC 7)

Technology based emission factor approach (see for example on road transport) x: compound, c: country, s: sector, yr: year, AD: activity data, TECH: technology, EOP: % of technologies that are controlled by end-of-pipe abatement measures, EF: uncontrolled emission factor by sector & technology, RED: reduction % on the uncontrolled EF by the installed abatement measure. Methodology follows state-of-the-art in large scale emission inventory calculations, IPCC 2006 Guidelines and EEA/EMEP Guidelines 2. Methodology: calculation of emissions by country and sector

AD: activity data, consumption of fuels for combustion (TJ diesel in road transport, with data from International Energy Statistics (IEA, DOE, UN) TECH:technology information: share of activity by technology (% of diesel used by passenger cars, trucks, from literature analysis, own studies) EF:uncontrolled emission factor (kg NO2 / TJ diesel, with datafrom IPCC and EEA/EMEP Emission Inventory Guidelines and literature analysis) EOP:share of the specific emission abatement measures (% of diesel passengers equipped with emission regulations (e.g. EURO II, from scientific literature, country reports and own studies) RED EOP :removal efficiency of abatement measure (% of uncontrolled EF removed, with datafrom IPCC and EEA/EMEP Emission Inventory Guidelines and scientific literature) 2. Example: Road transportation Italy (Diesel combustion)

Spatial allocation (x i, y i ) = representing the lower left corner of each 0.1 grid cell, AD: activity data (e.g. natural gas in power plant sector), for some maps technology data is gridded (e.g. underground hard coal mines), C: country, yr: year, Indicator (spatial grid, e.g. road density map). Grid cells share countries and include point source from different countries (no loss of emission information during gridding) Indicator (spatial proxy) is assigned to Activity data and Technologies (note : in most cases no need to adjust data to match EDGAR datasets) 2. Methodology: spatial allocation

line sources point sources area sources - Ship tracking data - Road network density etc. - Power plant location - Production facilities Agricultural fields - Population/ Animal density etc. 2. Methodology: spatial allocation

Greenhouse gas emissions (Tg CO2 eq.)

3. Example: Global emissions from road transportation EDGAR v4.0 Global emissions from road transportation (unit Tg) Road transport NOx emissions in Annex I and non-Annex I countries (Tg NO2) Allocation on grid: proxy data = road density (modified from VMAP, 2007) and population density (modified from CIESIN, 2007) a) Passenger cars, motorcycles, mopeds, light duty, buses = combined road density and population density b) heavy duty vehicles = road density

3. Trends: Road transportation

3. Trends: Global emissions from agriculture (air pollutants) EDGAR v4.0 Global emissions from agriculture (unit Tg) Spatial allocation of agricultural emissions Agricultural soils IRRI rice map soil acidity map soil type thermal climate zones cropland and grassland maps of Hyde Agricultural waste burning Hyde cropland map Enteric fermentation Animal density maps of FAO for cattle, buffaloes, goats, swine and sheep (FAO) Rural population Example NH3 gridding Using grid: gc_01x01_LO (grass_crop) Rows: Using grid: crop_01x01_LO (crop) Rows: Using grid: buffalo_01x01_LO (buffaloes) Rows: Using grid: poultry_01x01_LO (poultry) Rows: Using grid: Rur_pop_perc (Rural_population) Rows: Using grid: cattle_01x01_LO (cattle) Rows: Using grid: goats_01x01_LO (goats) Rows: Using grid: pigs_01x01_LO (pigs) Rows: Using grid: sheeps_01x01_LO (sheeps_0.1x0.1) Rows:

3. Trends: Agriculture (air pollutants) NH 3 from agriculture, 1970 Majority of NH 3 emissions occur in manure management and N application to soils Global emissions have almost doubled between 1970 and 2005, strong growth especially in Asia In 2005, emission intensity similar in Asia and Europe

3. Emissions from Ozone precursors ( )

4. Satellite data and verification of emission inventories Tropospheric NO2 columns for determined from the SCIAMACHY satellite instrument (Figure taken from HTAP 2007 assessment report Emission of NO x (as NO 2 ) on 0.1 degree grid in EDGARv4 (ton per grid cell)

4. Satellite data and verification of emission inventories Jianzhong Ma,, Andreas Richter, John P. Burrows, Hendrik Nüß and John A. van Aardenne, Comparison of model-simulated tropospheric NO2, over China with GOME-satellite data, Atmospheric Environment. Volume 40, Issue 4, Pages , 2006.

4. Satellite data and verification of emission inventories Jianzhong Ma,, Andreas Richter, John P. Burrows, Hendrik Nüß and John A. van Aardenne, Comparison of model-simulated tropospheric NO2, over China with GOME-satellite data, Atmospheric Environment. Volume 40, Issue 4, Pages , 2006.

4. Satellite data and verification of emission inventories Comparing inventories Direct comparison with satellite data Comparing model results with observations (ground or sat.) Annual budgets√-√ Sector detail√?? Time series√√√ Spatial allocation√√√ Discussion: possible verification of inventory data through satellite measurements?