Earth Observation for monitoring and assessment of the environmental impact of energy use LOSS OF LIFE EXPECTANCY (LLE) Calculated for the European population; time-span: 30 years (starting in 2005); key-pollutant: PM2.5 (from GAINS baseline). Earth Observation for monitoring and assessment of the environmental impact of energy use RATIONALE The Platform of Integrated Assessment (PIA) aims at assessing the environmental and health impacts by computing and gathering key information on human activity using different energy scenarios for the next 50 years. To get a wider view of environmental impacts, the PIA focuses on different environmental and health aspects: - Annual direct assessment of impacts related to key pollutants: Particulate Matter (PM2.5), Ozone and Greenhouse Gases (GHG) - Global impact by Life Cycle Assessment approach (LCA) METHODOLOGY The PIA functions are the following: 1. Hosting the outcomes of EnerGEO pilots (wind and fossil fuels) through a depository action 2. Implementing damage functions relating pollution indicators to impacts 3. Enabling free access to these impact indicators via Web Services and Web GIS Clients 4. Assessing the environmental impacts of each EnerGEO scenario KEY RESULTS The PIA gathers and computes European maps of impact indicators for four EnerGEO energy scenarios: - Baseline: continuation of current European policies with regard to limitation of CO 2 - Maximum Renewable Power: highest feasible renewable energy share - Open Europe: high renewable energy share with large imports of solar energy from North Africa - Island Europe: high renewable energy share with no energy exchange planned outside Europe Web Services and WebGIS Clients, which are major outcomes of the PIA, are enabling free access to this data: http://viewer.webservice-energy.org/energeo_pia/index.htm INNOVATIVE IMPACT The EnerGEO project proposes a new way to assess environmental impacts of energy scenarios through indicators issued from different methodologies: - GAINS and LOTOS EUROS as direct models that provide air pollutants concentrations and produce a series of direct impact indicators - A global systemic approach through life cycle assessment (LCA) The Platform of Integrated Assessment gathers a wide range of sources, and gives a spatial overview of environmental impacts across four possible energy scenarios. Results can be used to anticipate which scenarios could reduce environmental impacts. Platform of Integrated Assessment (PIA)
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LOSS OF LIFE EXPECTANCY (LLE)
Calculated for the European population; time-span: 30 years (starting in 2005); key-pollutant: PM2.5 (from GAINS baseline).
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RATIONALE
The Platform of Integrated Assessment (PIA) aims at assessing the environmental and health impacts by computing and gathering key information on human activity using different energy scenarios for the next 50 years.
To get a wider view of environmental impacts, the PIA focuses on different environmental and health aspects:
- Annual direct assessment of impacts related to key pollutants: Particulate Matter (PM2.5), Ozone and Greenhouse Gases (GHG)
- Global impact by Life Cycle Assessment approach (LCA)
METHODOLOGY
The PIA functions are the following:
1. Hosting the outcomes of EnerGEO pilots (wind and fossil fuels) through a depository action
2. Implementing damage functions relating pollution indicators to impacts
3. Enabling free access to these impact indicators via Web Services and Web GIS Clients
4. Assessing the environmental impacts of each EnerGEO scenario
KEY RESULTS
The PIA gathers and computes European maps of impact indicators for four EnerGEO energy scenarios:
- Baseline: continuation of current European policies with regard to limitation of CO2
- Maximum Renewable Power: highest feasible renewable energy share
- Open Europe: high renewable energy share with large imports of solar energy from North Africa
- Island Europe: high renewable energy share with no energy exchange planned outside Europe
Web Services and WebGIS Clients, which are major outcomes of the PIA, are enabling free access to this data:
The EnerGEO project proposes a new way to assess environmental impacts of energy scenarios through indicators issued from different methodologies:
- GAINS and LOTOS EUROS as direct models that provide air pollutants concentrations and produce a series of direct impact indicators
- A global systemic approach through life cycle assessment (LCA)
The Platform of Integrated Assessment gathers a wide range of sources, and gives a spatial overview of environmental impacts across four possible energy scenarios.
Results can be used to anticipate which scenarios could reduce environmental impacts.
Platform of Integrated Assessment (PIA)
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The research leading to these results has receved funding from European Community’s Seventh Framework Programme (FP7, 2007-2013) under Grant Agreement Number 226364.
MORE INFORMATION AT:
www.energeo-project.eu
Platform of Integrated Assessment (PIA)
LLE CALCULATION (DIRECT ASSESSMENT)
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Loss of Life Expectancy
APPLICATION FIELD AND SCALE
The Platform of Integrated Assessment (PIA) is currently applied to Europe and focuses on climate change and human health.
PIA could be applied worldwide and extended to handle more environmental issues according to emissions and concentrations pollutants availability.
DATA AND MODELS
Annual direct assessment:
Concentration of pollutants from GAINS which integrates renewable energy potentials from REMix and TASES energy models over Europe for different energy pathways (wind power and fossil fuels) are combined with population density (SEDAC) and forecasted cohorts survivability for the next 50 years for European population (UN). Damage function models are applied to compute the Loss of Life Expectancy (LLE).
Global Life Cycle Assessment (LCA):
The LCA approach is applied to the energy pathways corresponding to each scenario for each European country.
REFERENCESDrebszok, K. M., Wyrwa, A. and Blanc, I. (2012) ‚ Estimating the loss of life
expectancy attributable to PM2.5 emissions in Europe with the use of high
special resolution modelling`, 6th SETAC World Congress / SETAC Europe
Web-interface to the EnerGEO Knowledge Geoportal:http://energeo.researchstudio.at/energeo/catalog/main/home.page
EnerGEO Geoportal
METHODOLOGY
The EnerGEO Knowledge Geoportal uses international standards that form the foundation for information exchange based on metadata of spatial and non-spatial resources. Several improvements to facilitate the discovery of huge data amounts were made.
One of the major enhancements is the integration of recommender systems in the EnerGEO Knowledge Geoportal. Recommender systems facilitate the process of discovery, giving users meaningful recommendations on what might interest them. They are based on previous users’ behaviour (items previously viewed, bought or rated) and the search of other users.
RATIONALE
In many applications of the energy sector, the availability of current and comprehensive spatial information is crucial for decision making. This is true for emergency management, monitoring and predictions as well as for analyses.
Recently, Geoportals have been established as main spatial data infrastructure (SDI) gateways for finding, evaluating and using spatial information.
Within EnerGEO a Knowledge Geoportal was created providing information from the energy domain. It promotes technical and semantic interoperability as well as efficient discovery mechanisms connecting expert and casual users across all businesses.
KEY RESULTS
New methods and modules were developed for the EnerGEO Knowledge Geoportal that contribute to an enhanced discovery experience of energy information and usability:
- Enhanced App-based user experience
- Distributed metadata discovery
- Tag cloud-based search
- Integration in the GEOSS portal
- Auto-suggestion lists
- Recommender-enhanced discovery
- Semantic matching of spatial and non-spatial content
INNOVATIVE IMPACT
The concept of the Knowledge Geoportal website is geared to the task-oriented design philosophy based on User Experience (UX) design concepts for smartphones.
The focused presentation approach enhances the clarity of the website content and draws the attention of the users directly to the available functionalities e.g. the project web-apps.
The EnerGEO Knowledge Geoportal is the first Geoportal providing meaningful discovery results in form of recommendations.
Recommendations are based on user interactions with the content of the portal as well as automatically derived information of semantic matching of spatial and non-spatial content.
The research leading to these results has receved funding from European Community’s Seventh Framework Programme (FP7, 2007-2013) under Grant Agreement Number 226364.
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RECOMMENDATION WORKFLOWDATA AND MODELS
The discovery component of the EnerGEO Knowledge Geoportal uses a recommendation engine offering the possibility to show additional resources that might be of interest to a user based on interactions with search results of other users.
View actions within the EnerGEO Knowledge Geoportal can be considered as clicks on a specific search result, whereas a click on the details or preview page or invocation of a web service could be thought of a buy action.
For calculation of recommendations, a shopping cart analyser called “Association Rule Miner (ARM)” based on the Apriori algorithm “R” and “SlopeOne” is used. For creating additional recommendations, semantic text matching methods such as Latent Semantic Analysis (LSA) are applied.
APPLICATION FIELD AND SCALE
The EnerGEO Knowledge Geoportal fulfils the purpose of providing information on existing resources from the energy domain to a broad audience using standards for technical interoperability as well as efficient discovery mechanisms. The portal contributes its content to the Group on Earth Observations (GEO) Portal. Resources being registered comprise world-wide spatial and non-spatial data that are discoverable in form of standards-based and structured metadata.
The EnerGEO Knowledge Geoportal serves the fundamental basis for information exchange between providers and users and interlinks with other catalogues leveraging harvesting principles. It is built for a wide range of users, both expert and casual users of the energy domain. Users can either discover information or register datasets, services or applications.
REFERENCESBlaschke, T., Mittlboeck, M., Biberacher, M., Gadocha, S., Vockner, B.,
Hochwimmer, B., and Lang, S. (2010)‘The GEOSS - ENERGEO portal: towards an interactive platform to calculate, forecast and monitor the environmental impact of energy carriers’, in Greve, K. and Cremers, A.B. (ed.) (2010) EnviroInfo 2010 - Proceedings of the 24th International Conference on Informatics for Environmental Protection, Aachen: Shaker Verlag.
Vockner, B., Belgiu, M. and Mittlboeck, M. (2012) ‘Recommender-based enhancement of discovery in Geoportals, IJSDIR vol. 7, [Electronic]Available: http://ijsdir.jrc.ec.europa.eu/index.php/ijsdir/article/viewFile/292/333 [Feb 2012]
Scholz, J. and Mittlboeck, M. (2012) ‘Spatio-temporal Visualization of Simulation Results using a task-oriented Tile-based Design-Metaphor’. Conference Proceedings, International Symposium on Service Oriented Mapping Vienna.
CONTACTManfred MittelböckResearch Studios Austria Forschungsgesellschaft mbHSchillerstr. 25,A- 5020 [email protected]
EnerGEO Geoportal
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Energy potentials (terra joules per year and 1 km² grid for Europe) computed with G4M. High values are presented in dark green and
low values in grey colour. White areas represent areas which were not considered as forests.
Biomass Pilot
KEY RESULTS
Time series of the biomass energy potentials for wood and agricultural crops are delivered by applying the biomass energy models BETHY/DLR, EPIC or G4M at European scale (1 km ²) and global scale (10 km²).
The agricultural biomass energy models are sensitive to input data (mainly meteorology for both models and land cover map for BETHY/DLR). The annual variability of NPP reaches 36% for BETHY/DLR and 39% for EPIC when changing these major input datasets. This is a consequence of biological sensitivity to factors, such as weather, soil, species and cultivation that determine growth.
Intensive effort was put on validation activities for all three models as well as a model intercomparison. For agricultural and forest areas all models show a significant linear relationship with reference data (R2 up to 0.95).
INNOVATIVE IMPACT
EnerGEO delivered for the first time a continuous 10 years time series of bioenergy potentials for Europe and the globe starting with the year 2000 and ending in 2050 with 10 years step.
The post-processing of NPP (or dry matter) to bioenergy potential for forestry and agricultural areas is a new tool based on literature data that was published during the course of the project.
G4M estimates for Europe seem to be acceptable as they are close to forest inventory observations.
All results will be used finally in the Platform of Integrated Assessment (PIA).
Bioenergy potentials for Europe (1 km2 resolution) and the globe (10 km2 resolution) derived from BETHY/DLR, EPIC and G4M are available via the EnerGEO Portal.
METHODOLOGY
1. The Biosphere Energy Transfer Hydrology Model (BETHY/DLR) delivers Net Primary Productivity (NPP) maps
2. The Environmental Policy Including Climate Model (EPIC) is used to assess and forecast agricultural side products (straw) and the associated bioenergy potential on a European and global scale
3. The Global Forest Model (G4M) is used to calculate and forecast theoretical energy potentials for forests on European and global scale. For Europe the G4M is driven by NPP maps from BETHY/DLR to estimate future biomass potentials of forests.
4. Biomass and bioenergy maps are computed from NNP maps and are used as input layers for energy models as e.g. REMix, TASES and BeWhere
RATIONALE
The EnerGEO Biomass Pilot implements observational and modeling capacity for using biomass as a current and future energy resource. Biomass energy potentials are delivered and validated at global, continental and regional scale.
One focus is to use historical and actual time series of EO-data as input for the biophysical carbon model BETHY/DLR to derive bioenergy maps with a resolution of 1 km².
The second focus is to forecast biomass distribution of forestry and agricultural areas on a global scale using the models EPIC and G4M.
Forest biomass maps from BETHY/DLR are validated using forest inventory data. G4M and EPIC are cross-validated with BETHY/DLR. Energy maps are used as input layers for energy models (REMix, TASES, BeWhere).
The research leading to these results has receved funding from European Community’s Seventh Framework Programme (FP7, 2007-2013) under Grant Agreement Number 226364.
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DATA AND MODELS
The use of data derived from satellite imagery from GEOSS (e.g. fAPAR, LAI, Land Cover) as input for vegetation models with relatively high spatial resolution (1 km2) is very applicable for deriving NPP or dry matter on a continental scale.
In a post-processing step bioenergy potentials can be estimated and used as input for energy models in order to investigate e.g. energy mix scenarios when solar, wind and bioenergy sources are available.
These results are then linked to the global assessment models GAINS and GLOBIOM, which then model the effects on trans-boundary air pollution (GAINS) and global land use (GLOBIOM).
BIOMASS GEO-WIKI
The Biomass Geo-Wiki has collected a comprehensive set of recent biomass data around the globe, and makes it freely available for visu-alization. This allows users an instant gap analysis of global data.
With a critical mass of data it would be possible to produce a global mosaic of terrestrial biomass. Also additional data like in-situ meas-urements could be uploaded.
As these datasets are crucial in the determination of global bioen-ergy supplies, such a portal allowing users to visualize and compare datasets is highly relevant.
REFERENCESTum, M. and Guenther, K.P. (2011) ‘Validating modeled NPP using statistical data’,
Biomass and Bioenergy, vol. 35, pp. 4665-4674.Tum, M., Buchhorn, M., Guenther, K.P. and Haller, B.C. (2011) ‘Validation of modeled
forest biomass in Germany using BETHY/DLR’, Geoscientific Model Development, vol. 4, pp. 1019-1034.
Tum, M., Strauss, F., McCallum, I., Guenther, K.P. and Schmid, E. (2012) ‘How sensitive are estimates of carbon fixation in agricultural models to input data’, Carbon Balance and Management, vol7, pp.1-13.
Wetterlund, E., Leduc, S., Dotzauer, E. and Kindermann, G. (2012) ‘Optimal use of forest residues in Europe under different policies-second generation biofuels versus combined heat and power`, Biomass Conversion Biorefinery, vol.3, pp.1-16.
Leduc, S., Wetterlund, E., Dotzauer, E. and Kindermann, G. (2012) ‘CHP or biofuel production in Europe?’, Energy Procedia, vol. 20, pp. 40-49.
Tiede, D., Hoffmann, C. and Willhauck, G. (2012) ‘Fully integrated workflow for combining object-based image analysis and LiDAR point cloud metrics for feature extraction and classification improvement’, Conference Proceedings, International LiDAR Mapping Forum (ILFM 2012), Denver.
CONTACTKurt P. Günther Ian McCallumDLR-DFD IIASAMünchnerstr. 20 Schlossplatz 1D-82234 Wessling A-2361 Laxenburg [email protected][email protected]
Biomass Pilot
Web-interface to the biomass GEO-WIKIwww.biomass.geo-wiki.org
Vegetation models used in the biomass pilot (green). Output of vegetation models is used as input for energy models
(yellow) and assessment models (blue).
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Relative increase in SOMO35 (ozone indicator) when 5% of the agricultural land is converted into poplar plantations.
Fossil Fuel Pilot
KEY RESULTS
State-of-the-art emission modeling links the pollutant concentrations to its sources, which can be validated by Positive Matrix Factorisation (PMF) modelling.
In some areas up to 90% of the HgII and HgP concentrations are due to coal-fired power plants.
Accounting for intermittent fossil fuel use it is important to assess co-benefits between climate change and air quality mitigation strategies.
A trend in NOx emissions has been estimated for Europe, by combining satellite NO2 observations with air quality modelling.
Coal mining activities can cause ground deformations of a few centimetres per month.
INNOVATIVE IMPACT
A state-of-the-art modeling system, which quantifies the contribution of fossil fuels to air pollution levels has been demonstrated.
The use of fossil-based energy as back-up and the associated change in the timing of emissions implies that the expected concentration reductions due to reductions in fuel combustion are smaller.
Changing land use for biomass plantations may increase biogenic emissions of Volatile Organic Compounds (VOCs) and therefore also increase tropospheric ozone concentrations significantly.
It has been shown that it is possible to estimate trends in NOx emissions based on NO2 observations from satellite and a dedicated modeling system.
METHODOLOGY
Within the EnerGEO Fossil Fuel Pilot a dedicated source apportionment methodology has been developed, which is used to understand the contribution of fossil fuel combustion to atmospheric concentrations and the resulting impacts.
1. A mercury modeling system has been set up to model the impact of mercury on the environment
2. The LOTOS-EUROS model is used to model some of the impacts of the energy transition on the environment
3. Satellite data are used to quantify changes in concentrations, emissions and land degradation/subsidence
RATIONALE
Combustion of fossil fuels is the main driver for major environmental problems such as climate change and air pollution.
To minimize the impact of fossil fuels, a better understanding of the relations between emissions, air quality and the impact on climate, human health and vegetation is needed.
To optimize the choice of which energy sources to apply where and when, in-depth knowledge of the relations between fossil fuel source and impact, as well as the effects of energy transitions is required.
Furthermore, a monitoring system is necessary to oversee the implementation of improvements.
The research leading to these results has receved funding from European Community’s Seventh Framework Programme (FP7, 2007-2013) under Grant Agreement Number 226364.
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DATA AND MODELS
This EnerGEO Fossil Fuel Pilot is about assessing the impact of fossil fuels on the environment. Modeling emissions, from fossil fuel combustion as well as other sources, and air quality dispersion are the key modeling tools in this assessment.
The modeling tools used in EnerGEO are :
- LOTOS-EUROS model (www.lotos-euros.nl) used by TNO
- POLYPHEMUS model used by AGH
In the framework of this study, POLYPHEMUS is mainly used for modeling mercury dispersion.
APPLICATION FIELD AND SCALE
Application
This research has resulted in recommendations for policy makers, regarding the development of new energy policies. Questions that emerged during the project will be addressed in future research studies.
Scale
The pilot results are mainly applicable to the European scale, although also some global issues have been addressed. However, in principle the models could be extended to global scale if the necessary input data is available.
Coal mining and land subsidence have been addressed at local scale for specific pilot study sites.
REFERENCES
Quass, U., Vercauteren, J. Schaap, M., Hendriks, C. Kuhlbusch, T. et al. (in prep.), ‘Multi-site/multi period PM10 source apportionment by Positive Matrix Factorisation for north-west Europe’, in preparation.
Kranenburg, R., Segers, A.J., Hendriks, C., Schaap, M. (2013) ‘Source apportionment using LOTOS-EUROS: module description and evaluation’, Geoscientific Model Development, vol.6, pp.721-733.
Schaap, M., Kranenburg, R., Curier, L., Jozwicka, M., Dammers, E., Timmermans R., (submitted),’ On the sensitivity of OMI-NO2 product to emission changes
across Europe using a chemistry transport model’, Remote Sensing.Hendriks, C., Kranenburg, R., Kuenen, J., van Gijlswijk, R., Wichink Kruit, R.,
Segers, A., Denier van der Gon, H., Schaap, M. (2013) ‘The origin of ambient particulate matter concentrations in the Netherlands’, Atmospheric Environment , vol.69, pp.289-303.
Hendriks, C., Kuenen, J., Kranenburg, R., Scholz, Y., Schaap M., et al. (in prep.), ‘Changing emission time profiles because of energy transitions impact source receptor matrices’.
Beltman, J., Hendriks, C., Tum, M., Schaap, M. (2013), ‘The impact of large scale biomass production on ozone air pollution in Europe’, Atmospheric Environment, vol.71, pp. 352-363.
The percentage rate of emissions from power sector to overall concentration of mercury of Hgp in the surface level [%].
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DIRECT NORMAL IRRADIATION
Annual sum of direct normal irradiation [kWh/m²] for the Mediterranean basin for the year 2002.
Solar Pilot
KEY RESULTS
The Life Cycle Assessment for 3 kWp PV systems as well as the site ranking service for solar power plants are available as Web Services: http://stbgis.dlr.de/geoserver/
The site ranking service is also accessible in a WebGIS client with additional tools for analysis and integration of further data.
Full-load-hour potential curves are available, enabling the spatial variability assessment of regional renewable energy.
Time series of the potential renewable power generation are provided to generate emissions profiles of pollutants of different energy pathways.
INNOVATIVE IMPACT
LCA models for PV systems can be used for worldwide PV installations over a large spectrum of technologies (multi Si, mono Si, CdTe, etc.) and configurations.
The solar site ranking service is a state-of-the-art web-based decision support tool for locating suitable regions for solar power plants. The previously offline analysis is now freely accessible on the internet and allows users to understand the impacts of certain criteria based on their user-defined preferences.
Renewable energies are relatively new resources used in the power supply system at large scale. Their representation in integrated assessment models needs to take into account the varying spatial and temporal availability.
METHODOLOGY
1. Life Cycle Assessment (LCA) of PV systems assesses various environmental impacts of a given PV system over its life cycle, also accounting for the manufacture of the modules and cells.
2. The solar site ranking service is a Spatial Decision Support System (SDSS) that calculates optimal location for solar power plants expressed by a ranking value.
3. Detailed resource quality information is provided by the high resolution models REMix and TASES to better represent the large scale generation of electricity from intermittent renewable energy resources in GAINS and MESSAGE.
RATIONALE
The need to decarbonize the energy system for environ-mental and economic reasons will lead to larger shares of renewable energies in the energy system.
Solar energy is one of the most established renewable energy resources, and is gaining more and more impor-tance.
The following aspects are addressed by the EnerGEO Solar Pilot:
– Life Cycle Assessment (LCA) of Photovoltaic Systems (PV)
– Optimal location for solar power plants
– PV integration into existing electric grids
The research leading to these results has receved funding from European Community’s Seventh Framework Programme (FP7, 2007-2013) under Grant Agreement Number 226364.
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DATA AND MODELS
The solar LCA web service has been developed specifically for the EnerGEO project, taking advantage of the AIP3 scenario created within GEOSS.http://viewer.webservice-energy.org/energeo_aip3/index.htm
The siting support for solar power plants is based on a spatial multi-criteria analysis considering different optimization objectives and exclusion constraints like radiation data, geophysical conditions and anthropogenic infrastructure. To account for a user-specific focus, the analysis allows individual criteria weightings.
The full-load-hour potential curves and the time series of potential power generation from renewable energy resources are based on meteorological, geographical and statistical data, assumptions about the available area types and shares and characteristic power plant models.
APPLICATION FIELD AND SCALE
The Life Cycle Assessment covers 3 kWp PV systems for several environmental impacts and configurations and has a worldwide coverage.
The selection of optimal locations for solar power plants systems is a multi-criteria based approach that heavily depends on the availability of data in equal and good resolution. The site ranking service therefore covers the area of Europe, where those requirements are met. However, the methods applied are generally transferable to other regions or global scale.
Renewable energy resource data are provided for Europe and parts of North Africa. Global data can be provided in the future but might partly have a lower spatial and temporal resolution.
REFERENCESMénard, L., Blanc, I., Beloin-Saint-Pierre, D., Gschwind, B., Wald, L., Blanc, P., Ranchin,
T., Hischier, R., Gianfranceschi, S., Smolder, S., Gilles, M. and Grassin, C. (2012) ‘Benefit of GEOSS Interoperability in Assessment of Environmental Impacts Illustrated by the Case of Photovoltaic Systems’, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, pp. 1722 – 1728.
Scholz, Y. (2012) ‘Renewable energy based electricity supply at low costs – Develop-ment of the REMix model and application for Europe‘ Dissertation,, University of Stuttgart [Online], Available:
http://elib.uni-stuttgart.de/opus/volltexte/2012/7635/ Wanderer, T., Herle, S., (2013) ‘Using a web-baed SDSS for siting solar power
plants’, Proceedings of the 27th International Conference on Informatics for Environmental Protection, Hamburg, Germany.
CONTACTThomas Wanderer Isabelle BlancDLR MINES Paris Tech / ARMINESPfaffenwaldring 38-40 60, Boulevard Saint-MichelD-70569 Stuttgart F-75272 Paris Cedex [email protected][email protected]
Solar Pilot
The Solar Site Ranking WebGIS client with a resulting suitability map and criteria analysis tool.
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Configuration selected: 20 years life time; 40 turbines; high maintenance; high failure rate;
fixed and floating foundations
IMPACT ON CLIMATE CHANGE [G CO2eq/kWh]
Wind Pilot
KEY RESULTS
The main results derived from the wind farm life cycle assessment workflow are:
– LCA environmental performance maps for several scenarios
– Scenarios based on variable failure rates, operation maintenance schemes, turbine lifetime, potential losses, and technical choices
– Maps published into a WebGIS client tool to ease their dissemination
The results can be explored at: http://viewer.webservice-energy.org/energeo_wind_pilot/index.htm
INNOVATIVE IMPACT
The EnerGEO Wind Pilot allows decision makers to compare not only the financial cost of energy production, but also the impact on our environment.
All aspects such as materials, maintenance and efficiency are taken into account to assess the wind farm life cycle environmental impacts:
METHODOLOGY
The EnerGEO Wind Pilot performs a Life Cycle Assessment (LCA) for a wind turbine, based on geo-dependent environmental performance expressed as the ratio of the impacts issued from a geo-localized Life Cycle Assessment algorithm over the life time electricity production.
The generated electricity windspotentials have been assessed from the selected turbine power curve (5 MW) and the wind speed distribution at hub height. Wind Speed distribution is issued from satellite observations and numerical models.
RATIONALE
Wind energy is one of the primary sources of renewable energy which is currently exploited. However, what is the real impact on our environment of a wind farm over its life cycle?
In the EnerGEO Wind Pilot we evaluate the impact of a wind farm throughout its lifetime, including the materials and energy used to build, install and maintain it.
By visualizing the impact and energy production of wind turbines on a map, decision makers can easily compare the benefits and impacts of wind energy with other forms of energy production.
The research leading to these results has receved funding from European Community’s Seventh Framework Programme (FP7, 2007-2013) under Grant Agreement Number 226364.
MORE INFORMATION AT:
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REFERENCESBlanc, I., Guermont, C., Gschwindt, B., Menard, L., Calkoen, C. and Zelle, H. (2012)
‘Web tool for energy policy decision-making through geo-localized LCA models: A focus on offshore wind farms in Northern Europe`, in Arndt, H.K., Knetsch, G. and Pillmann, W. (ed.) EnviroInfo 2012 – Proceedings of the 26th International Conference on Informatics for Environmental Protection: Part 2: Open Data and Industrial Ecological Management Aachen: Shaker Verlag, p. 499-506.
Zelle, H., Mika, A., Calkoen, C., Santbergen, P., Blanc, I., Guermont, C., Me,nard, L., Gschwind, B. (2013) `Environmental data for the planning of off-shore wind parks from the EnerGEO Platform of Integrated Assessment (PIA)´, Proceedings of the 27th International Conference on Informatics for Environmental Protection, Hamburg, Germany.
DATA AND MODELS
Maps of wind speed were generated with the Weather Research and Forecasting (WRF) regional atmosphere model, which is based on a 12 years historical simulation.
Wind energy production was computed based on a standard 5 MW wind turbine power curve.
For the geo-dependent LCA model, site-sensitive components of the farm have been considered: the length of sub-marine cabling, which is influenced by the distance of the farm to the coast, the marine transport scheme, which depends on the distance to the nearest relevant harbor and the foundation choice (floating vs. fixed), which depends on the water depth.
APPLICATION FIELD AND SCALE
ApplicationThe EnerGEO Wind Pilot has potential applications in policy making as well as for the planning and the development of wind farms.
ScaleThe EnerGEO Wind Pilot was demonstrated for North-West Europe, with a focus on offshore wind turbine installations of the North Sea region. The methodology can directly be applied to worldwide locations of offshore installations and could be translated for onshore wind turbine installations.
