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Investigating the Links Between GMES & Emission Inventories - An Update

This article provides an update on the investigation of the connections between GMES (Global Monitoring for Environment and Security) services and emission inventories. It discusses the challenges and opportunities in integrating GMES data into emission inventory compilation, and explores themes such as downscaling, now-casting, sectoral estimates, and verification. The article also highlights the importance of improving emissions inventories through the integration of facility reporting data, survey/census data, proxy data indicators, and continuous emissions monitoring networks. Furthermore, it suggests the use of standards such as INSPIRE and annual inventories to improve data consistency and flows.

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Investigating the Links Between GMES & Emission Inventories - An Update

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

  2. GMES services and emission inventories • GMES (Global Monitoring for Environment and Security) European Earth Observation Program for the implementation of information services set up to support EU environmental policy and security. • 1) Workshop 10-11th October 2011 to explore from two perspectives: • 1. Emission inventory as input to GMES services • 2. Using GMES data in emission inventory compilation • 2) Develop ongoing work programmeover a number of years

  3. Workshop Objectives • GMES Emission Estimation. • Successes • future opportunities •  Themes... • Downscaling: Cities/spatial grids using in-situ and satellite data • Now-casting: Real time data collection • Sectoral estimates: e.g. gap filling, shipping, road transport, wildfires • Verification: Consistency between GMES/MACC emission inventory and official inventories (LRTAP, UNFCCC)

  4. Who may be interested? • Earth Observation & GMES community, • Scientific modeling (air quality, climate and ecosystem modeling), • Emission inventory community, • Policy makers and industry with an interest in emission inventory improvement and verification.

  5. Emissions Inventories  GMES

  6. Problems with Inventories for GMES • Annual National Inventories: • national totals only with 50x50km + Large Point Sources for some air pollutants. • Time-lag (~2 years) and by the time modelling enhancements are applied ~ 3-5 years • Limited details of monthly, daily or hourly variations available. • Regulated installation inventories: • Limited detail of source categories, stack height, activity data, temporal (only annual totals: not monthly, daily or hourly) variations. • Thresholds and threshold reporting limits the usability of the data and the comparability with real emissions. • Time-lag (~2 years), No projections • City Inventories: • Irregular update frequency (often out of date) • Time consuming and bespoke, involving lots of data suppliers without long term data flows or strong institutional arrangements. • Lack of standards and consistent/comparable emissions datasets limit quality. • Difficult to integrate/compare with national inventories/statistics. • Time-lag in production (~2 years) and no projections. • Global Inventories: • Time-lag in production (~5 years) • Limit on level of spatial detail achievable globally • Large dataset to maintain with many inconsistencies with other smaller scale data to resolve. • Irregular update frequency (often out of date) • Limited accuracy through use of “generic” global datasets (e.g. population, employment etc)

  7. Improving Emissions Inventories • Integration & Data from facility reporting (energy consumption, stack height and temporal variation) (IPPC/E-PRTR/EUETS). • More survey/census data (e.g. Domestic wood, cities, fuel type) • Methods to use proxy data indicators (e.g. temperature, traffic flows, electricity/gas demand). • Continuous emissions monitoring networks OGC –Sensor Observation Services • Automatic Number Plate Recognition for road traffic. • Aircraft flight data. • Shipping route data. • Real time energy supply data (e.g. http://www.nationalgrid.com/uk/Electricity/Data/Realtime/Demand/). • Temporal variations(e.g. monthly, daily and hourly traffic, energy demand and production, agricultural activity etc). • Speciation of pollutants (e.g. NMVOC, Heavy Metals, and POPs). • PM characteristics EC, OC, BC, PM size distribution and particle number. • City/urban inventory Standards • INSPIRE. • Annual inventories to y-1 • Improve national data consistency and flows.

  8. GMES Emissions Inventories

  9. Problems with GMES for inventories • National Inventory Compilation • Methods and data sources well established and utilise national statistics and other ground based datasets. • Limited “intensity” information unable to “Quantify” national emissions for energy, waste and industrial process emissions. E.g. Fuel use, traffic density, numbers of cars, fuel type. • Cloud cover and/or instrument failure may prohibit a continuous operation and quality may vary between countries depending on climatic conditions. • Limitation on historic datasets. Cannot go back to years before the satellites existed. • Spatial emissions distribution. • Limited intensity information, (better for area based source/removal categories) • Limitation on historic datasets and timeseries mapping. • Inventory verification. • Modelling and data needs for verification. • Some questions about update frequency if EAS GlobCover dataset is becoming available in 2010 showing 2005 data.

  10. Improving GMES services for emission inventories • National Inventory Compilation: • emissions/removals and biomass from forest growth and deforestation (LULUCF) and natural sources (Volcanoes, forest fires). • no other satellite based datasets known that are viable replacements or enhancements to established statistics (energy, waste, agriculture and industrial process) based inventory accounting. • Spatial & temporal emissions distribution: • GPS tracking of vehicle movements & type to estimate traffic intensity. • Inverse near-real-time modelling of atmospheric concentrations and emissions based on high resolution column measurement data. • spatial distribution of forest growth and deforestation • spatial distribution of statistics based agriculture Crop types and areas, fertilizer applications and management practice surveys. • A number of these techniques are quite well advanced and have been tested in a number of EU projects (APMOSPHERE, IMPRESARIO, GEMs, PROMOTE) • Inventory Verification: • Verification of emissions from and location of Large Emission Sources based on their stack plumes. • verifying Landuse, Land Use Change and Forestry (LULUCF) inventories reported under UNFCCC/EUMM by providing detailed maps of forest change. • Verification based on inverse modelling of column measurement. • This is a relatively new solution to independent verification of reported emissions inventory data. Approaches still have high uncertainties and methods need streamlining and developing.

  11. Thank you http://acm.eionet.europa.eu/meetings 1) Scoping Paper 2010 ETC-ACC 2010 (see ETC-ACC) 2) Workshop 10-11th October 2011 Copenhagen register at: 3) Plan for a multi-annual work programme to facilitate engagement between GMES and Emissions communities

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