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Earth observation for monitoring and assessment of the environmental impact of energy use

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IntroductionObjectivesProject logicGEO contextDPSIR framework

in EnerGEOPilotsEnerGEO portalPIAWrap up

Project overview

Seventh Framework Programme Theme 6 - EnvironmentFP7-ENV-2008-1GA No. 216364

• 12 partners from 6 countries• Project duration: 11/2009 – 10/2013• EC contribution: € 6 010 930• Coordinator: Dr. Martijn Schaap, TNO • Website: http://www.energeo-project.eu

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http://www.energeo-project.eu/

Consortium

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No Beneficiary name BeneficiaryShort name

Country Logo and website

1 Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek, Coordinator

TNO Netherlands

2 Association pour la Recherche et le Développement des Méthodes et Processus Industriels

ARMINES France

3 Deutsches Zentrum für Luft- und Raumfahrt DLR Germany

4 ARGOSS ARGOSS Netherlands

5 Research Studies Austria Forschungsgesellschaft mbH

RSA Austria

6 International Institute for Applied Systems Analysis

IIASA Austria

7 Uniresearch B.V. UNR Netherlands

8 Paris-Lodron-Universität Salzburg Centre for Geoinformatics Z_GIS

PLUS Austria

9 AGH University of Science and Technology / Krakow

AGH-UST Poland

10 Pakistan Space and Upper Atmosphere Research Commission

SUPARCO Pakistan

11 Institut für Energie- und Umwelttechnik IUTA e.V.

IUTA Germany

12 Stichting Ruimte Onderzoek Nederland SRON Netherlands



Project background

• Worldwide demand of energy is growing and will continue to do so for the next decades to come.

• The International Energy Agency IEA has estimated that global primary energy demand will increase by 40 – 50 % from 2003 to 2030 (2005 estimates) depending on the fact whether energy policies are directed towards energy-saving and fuel-diversification will be effectuated.

• Since energy production, transportation and consumption place considerable pressures on the environment, there is serious concern regarding the sustainability of the current and future pattern of energy consumption.

EnerGEO develops products and methodologies that provide energy companies, consultants and policy makers (local, regional, global) with the tools to evaluate the environmental impact of changes in energy use in terms of the complete life cycle including exploration, development, exploitation, maintenance and decommissioning.

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Project objectives

EnerGEO develops a strategy for a global assessment of current and future impacts of the exploitation of energy resources on the environment and ecosystems based on the use of the Global Earth Observation System of Systems (GEOSS) capacities. This strategy is demonstrated for a variety of energy resources worldwide (fossil fuels, biomass, solar and wind energy).

EnerGEO combines:1. Existing energy system models and models capable of

assessing and forecasting environmental impacts and costs of energy exploitation

2. Existing global earth observation datasets from which environmental indicators are derived in order to quantify changes to freshwater systems, biosphere, ecosystems, atmosphere and oceans

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Project objectives

4 Pilots were selected for testing and demonstrating the observation system and developed scenarios: Fossil fuels: impact on atmospheric composition and land

degradationBiomass: impact on ecosystems, biodiversity and food

securitySolar energy: select optimum power plant locations and support

electricity grid integrationWind: assess the potential (net) energy, assess

environmental impacts of the substitution of fossil energy by wind power

all pilot outputs will be converted into Environmental Impact Assessments and tentatively integrated through the Platform Integrated Assessment (PIA)

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Project logic



GEO Context

EnerGEO represents a major contribution of the European Commission to GEOSS, in particular to the Societal Benefit Area (SBA) Energy and the GEO-tasks • EN-01 (Energy and Geo-Resources Management) and• SB-05 (Impact Assessment of Human Activities) (or any GEO Workpackage derived from these).

By developing a distributed systembased on the recommendations of the GEO-Architecture and Data Committee (ADC), global collection and dissemination ofdata relating to the impact of energy use on the environmentwill be supported.

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The SBAs of GEOSS

DPSIR framework in EnerGEO

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Fossil Fuels – origin of air pollution

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Particulate matter (PM) has a negative impact on human health. We improve the modeling of PM concentrations over Europe including the development of a source apportionment tool to assess the contribution of fossil fuel combustion. These results were compared to Positive Matrix Factorisation results.

Comparison of carbon concentration ascribed to burning of heavy fuel oil PMF and LOTOS-EUROS

Share of PM2.5 concentration caused by coal burning

Share of EC2.5 concentration caused by diesel burning

Fossil Fuels – Mercury modeling and emissions

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Coal fired power plants are an important source of (reactive) mercury. • A mercury module for air quality model

Polyphemus was developed and tested• Emission databases are lacking detail in

both type of Hg emitted and source sectors and report quite different mercury emissions.

Schematic of Mercury module developed

Emission of Hg divided over source sectors for three different databases % of emissions from the power sector to overall concentration of particulate mercury

Fossil Fuels – Energy Transition

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in EnerGEOPilotsEnerGEO portalPIAWrap up Model used: air quality model LOTOS-EUROS

Large scale energy transitions have a significant impact on air quality.Generally air quality will benefit from less emissions, but there are some issues:• Large-scale production of biomass will

affect ozone concentrations• Because solar and wind energy revenue is

dependent on meteorology, the timing of emissions from the back-up fossil fuel combustion will change as well. This may impact air pollution from fossil fuel use. When change in emission timing is included,

power plant pollution is more persistent

Increased isoprene emissions from biomass production will increase ozone concentrations and damage indicators

Biomass - Energy potentials

G4M is used to produce global energy potentials from forestry

EPIC is used to produce global energy potentials from crops

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Energy potentials from forests as computed with the G4M model. Values in TJ/y/grid cell of 0.5x0.5º. White: no forest. Red: tropical forests and savannahs.

Bioenergy potentials for 2090 derived from barley, grain maize, oats, rapeseed, rye and wheat. Modeled on 10 km2 resolution with the EPIC model

Biomass

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A landcover / landuse database for Pakistan was developed

BETHY/DLR uses remote sensing data to derive biomass maps from which net primary productivity maps can be computed.

A landuse / landcover database for Pakistan was constructed

The use of LIDAR data for the identification of vegetation types was tested but not yet successful.

Solar energy: Siting supportThe aim of this part of the solar energy pilot is to provide a web service with information on the best locations to build a solar park. Inputs used are solar radiation, land use, population density, infrastructure, electricity grid, etc. Output is available as maps and as location-specific raster diagrams.

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Left: examples of input maps (electric grid, population, irradiance) to calculate best sites to locate a solar power plant.Right: example of output of the web service: map with potential for solar power plants and raster diagram for one location.

Solar energy: Grid planning support

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Focus on grid planning support by providing information about the reliability of solar energy specific weather forecasts. This is important because good forecasts are needed to estimate how much solar energy will be produced and how much other electricity is needed at each time.

Error estimate of direct normal irradiation, forecast 12 hours ahead: Root mean square error divided by mean DNI. Left: based on ECMWF forecast; Right: based on 2day persistance method, which assumes yesterday’s weather conditions and electricity generation also for the following day

Wind - Potential wind energy

High-resolution meteorological models are used to analyse potential energy yields, accounting for wind speeds, maintenance schemes and transport

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Wind - Potential wind energy

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Mean wind power potential Correlation between wind speeds at location off the coast of Norwich and the rest of the area. This correlation is important in view of availability of electricity: what is the chance that there is wind in one wind park when the other is not producing because of lack of wind?

Wind - LCA Results:Environmental impacts / kWh produced at the high-voltage onshore grid

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Main assumptions:

- 50 Wind Turbines per farm and per HV transformer

- Load factor: 53%- WT lifetime : 20 years- HV transformer lifetime: 35 years- Submarine cables lifetime: 40 years- Distance to shore: 50km- O&M scheme: inspection 4 times

per year by helicopter + 1 return transport farm/harbor by transoceanic tanker during the life time of the farm

- No additional recycling scheme considered (Ecoinvent already include recycled materials in its inventories)

Environmental impacts per kWh energy produced for all aspects of building and maintenance of wind mills.

Wind - Life Cycle Assessment

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LCA results are also available on maps via http://viewer.webservice-energy.org/energeo_wind_pilot/index.htmExample of result from LCA analysis: primary energy required to build a park of 40 wind mills.

http://viewer.webservice-energy.org/energeo_wind_pilot/index.htm

http://viewer.webservice-energy.org/energeo_wind_pilot/index.htm

EnerGEO portal – link to GEOSS

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EnerGEO Portal Architecture is linked to GEOSS Common Infrastructure (GCI)

EnerGEO portal - example

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http://energeo.researchstudio.at/

Example of web service available through EnerGEO portal: Climate change impact of solar panels

http://energeo.researchstudio.at/

Platform for Integrated Assessment: PIA

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• Following the DPSIR (Drivers, Pressure, State, Impact, Response) concept• Focus on the conversion from STATE indicators into IMPACT indicators

through damage functions• A display of pilot results through graphical Web clients and depository

process

Example of PIA result: web service for health impact due to PM2.5 pollution. Concentrations feed in from GAINS and LOTOS-EUROS model, these are weighted by population (age specific) and damage functions

PIA – Energy Scenarios

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Four energy scenarios for Europe are defined and will be assessed in the PIA

Top: ‘Open Europe’ energy scenario, characterised by a relatively large share of electricity from biomass, calculated with the GAINS model.

Left: Electricity production time profile for a summer week in June in a scenario using 80% renewable electricity. For all scenarios such time profiles are calculated using the REMIX model.

Wrap up

• Linking Energy Use and Environmental Impact by making use of state of the art environmental, energy and scenario models

• Collecting the necessary datasets and deriving indicators from them by connecting to current GEO-contributions and state-of-the-art in-situ global networks

• Enabling the collection of and access to EnerGEO-data by building a portal within the context of GEO and based on GEO-ADC-recommendations

• Testing the EnerGEO approach through dedicated pilots making our approach viable and supportive

• Proposing perspectives from Pilot-scale to Global Scale enabling to run global scenarios on energy use and environmental impact

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Thank you

http://www.energeo-project.eu/

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Documents

energy companies

energy production

wind energy

energy policies

variety of energy resources

global primary energy

costs of energy exploitation2

existing energy system