Modelling regional maize markets for biogas production in Germany [Elektronische Ressource] : the impact of different policy options on environment and transport emissions / von Ruth Delzeit

rheinische_friedrich-wilhelms-universitat_bonn - Ruth Delzeit

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Publié par	rheinische_friedrich-wilhelms-universitat_bonn
Publié le	01 janvier 2010
Nombre de lectures	14
Langue	English
Poids de l'ouvrage	3 Mo

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Institut für Lebensmittel- und Ressourcenökonomik der
Rheinischen Friedrich-Wilhelms-Universität zu Bonn
_____________________________________________________________________________

Modelling Regional Maize Markets for Biogas Production in
Germany:
The Impact of Different Policy Options on Environment and
Transport Emissions

I n a u g u r a l - D i s s e r t a t i o n
zur
Erlangung des Grades

Doktor der Agrarwissenschaften
(Dr.agr.)

der
Hohen Landwirtschaftlichen Fakultät
der
Rheinischen Friedrich-Wilhelms-Universität
zu Bonn

vorgelegt am 21. Juli 2010

von

Ruth Delzeit

aus Adenau

Referent: Prof. Dr. Karin Holm-Müller
Korreferent: Prof. Dr. Thomas Heckelei
Tag der mündlichen Prüfung: 10. Dezember 2010
Erscheinungsjahr 2011
Diese Dissertation ist auf dem Hochschulschriftenserver der ULB Bonn
elektronisch publiziert (http://hss.ulb.uni-bonn.de/diss_online).

Acknowledgements
I would like to thank everyone who supported me in one way or another
during the course of the dissertation.
This dissertation has been conducted at the Institute for Food and Resource
Economics, Department of Resource and Environmental Economics, at the
University of Bonn. I would like to thank institute for providing me an
excellent working environment and great support.
Many thanks to go my supervisor Prof. Dr. Karin Holm-Müller. She
provided the encouragement and advice necessary for me to complete my
dissertation. I also greatly acknowledge Prof. Dr. Thomas Heckelei for
accepting to take over to co-reference of this thesis.
I gratefully acknowledge the financial support of the NaRoLa project
which is sponsored by the German Federal Ministry of Education and
Research (BMBF). I also thank my project partners from the vTI and IfW
for their help, exchange of data and ideas.
Furthermore, many thanks go to my colleagues from the Institute for Food
and Resource Economics for the warm working atmosphere, fruitful
discussions, and individual help. I would take too long to list them all, but
in particular I would like to thank Wolfgang Britz, as well as Sabine
Täuber and Nina Lange for many discussions in our small working group,
and Simon Schlüter for his practical advices on biogas gas plants. I would
also like to thank Adrian Boos, Hans Josef Greuel, Gisela Julius, Sonja
Macke, Alheide von Wehrs, and Andrea Zimmermann, as wells as Frauke
Bathe, Ulla Kellner, and Christian Westerschulte for their help as student
assistants.
During a research trip to the ISEG in Lisbon I received precious advice
from José Pedro Veloso de Sousa Pontes, whom I would like to thank.
Last but not least, many thanks go to my family and friends for their
constant motivation and assistance.

Abstract
The production of biogas is considered to be a promising candidate for a
sustainable energy mix. Accordingly, Germany’s Renewable Energy Act
(EEG) promotes electricity production from biogas along with other renewable
energies. While overall benefits are seen in terms of climate protection and
increased employment in rural areas, for example, biogas production (mainly
from maize in Germany) also has the potential to create negative
environmental effects on a regional scale. This can be caused by the
production of monocultures and increasing transport volumes, to cite two
prominent examples. To assess environmental effects arising from bioenergy
policies, different types of agricultural models have been applied to determine
the effects on competition for primary factors. Generally, these models do not
however capture the demand side for crops with high transportation costs such
as maize.
Based on location theory combined with an analysis of existing location
models, a new tool to determine optimal locations and sizes for biogas plants
is developed in the course of the thesis, and therewith maize demand curves
are derived. The location model ReSI-M (Regionalised Location Information
System – Maize, or Regionalisiertes Standortinformationssystem – Mais)
allows for the determination of regional demand functions of silage maize as a
function of silage maize prices as well as further explanatory factors such as
transport costs and economic profitability of different biogas plant types. It
simulates demand functions for three different policy scenarios: the EEG
2004, the EEG 2008 including the respective feed-in tariffs, and finally a
counterfactual scenario where feed-in tariffs are paid independent of plant size
and technology. The later is applied to compare the EEG scenarios with a
situation in which the resulting plant structure is theoretically a cost-minimal
solution.
Coupling ReSI-M with RAUMIS, a partial supply model which depicts
German agriculture based on regionally differentiated processes, adds regional
market clearing for a robust impact assessment of biogas production. As a
result, policy implications on land use of different policy settings are analysed
in this thesis. Furthermore, ReSI-M simulates regionally differing CO 2
emissions from transports per kWh (kilowatt hour electric), as well as the el
efficiency of subsidies for the policy scenarios.
i The results show that adding maize demand to an assessment of land use
changes improves the representation of regional maize markets since regional
demand characteristics such as transport costs and availability of inputs are
taken into account. Simulation results indicate that under a scenario adopting
feed-in tariffs according to the EEG 2004, less land for maize cultivation per
kWh is used and also less transport emissions are caused compared to the el
EEG 2008 and the counterfactual scenario. Furthermore, results point out
differences in regional maize markets under the applied scenarios: under the
EEG 2008 scenario, maize production increases in regions with high livestock
densities, which therewith further intensifies maize production in regions
where the production level is already high. Applying the counterfactual
scenario shows that production increases in regions with low transport costs.
However, under the EEG 2008 the greatest amount of energy from biogas is
produced and most subsidies per produced kWh are paid. The efficiency of el
subsidies is best in the counterfactual scenario, in which feed-in tariffs are paid
independent of plant size and technology. Against these results, the thesis
concludes with policy recommendations and suggestions for further research.
The work provides a tool for policymakers to evaluate distinct regional
demand levels for maize and its environmental impacts while the work also
contributes to an ongoing political debate of the benefits and drawbacks of
bioenergy production.

ii Zusammenfassung
Die Produktion von Biogas wird als vielversprechende Option innerhalb eines
nachhaltigen Energiemixes angesehen, und dementsprechend wird in
Deutschland die Produktion von Biogas zusammen mit anderen erneuerbaren
Energien durch das Erneuerbare-Energien-Gesetz (EEG) gefördert. Während
Vorteile für den Klimaschutz und ländliche Entwicklung gesehen werden,
birgt die Produktion von Biogas (in Deutschland hauptsächlich auf der Basis
von Silomais) die Gefahr, negative Umwelteffekte wie beispielsweise den
Anbau von Mais in Monokulturen und steigende Transportaufkommen auf
regionaler Ebene zu verursachen. Zur Bewertung von Umwelteffekten, die
durch unterschiedliche Bioenergiepolitiken entstehen, wurden verschiedene
agrarökonomische Modelle angewandt, um Auswirkungen auf den
Wettbewerb von Einsatzfaktoren zu erfassen. Diese Modelle bilden die
Nachfrageseite von Pflanzen mit hohen Transportkosten, wie beispielsweise
Silomais, jedoch nicht ab.
Basierend auf der Standorttheorie und vor dem Hintergrund bestehender
Standortmodelle, wird im Laufe der Dissertation ein neues Modell entwickelt,
um Standorte und Größen von Biogasanlagen zu bestimmen und somit deren
Maisnachfrage abzuleiten. Das Standortmodell ReSI-M (Regionalsiertes
Standortinformationsmodell – Mais) ermöglicht es regionale Nachfrage-
funktionen für Silomais als eine Funktion von Silomaispreisen und weiteren
Erklärungsvariablen wie Transportkosten und wirtschaftliche Profitabilität von
verschieden Biogasanlagentypen abzuleiten. Es simuliert Nachfragefunktionen
für drei Politikszenarien: das EEG 2004, das EEG 2008 mit entsprechenden
Einspeisevergütungen, und außerdem ein fiktives Szenario („counterfactual
scenario―), in dem Einspeisevergütungen unabhängig von Anlagengröße und –
technologie gezahlt werden. Das letzere Szenario wird angewandt, um die
EEG Szenarien mit einer Situation zu vergleichen, in welcher die resultierende
Anlagenstruktur theoretisch einer kostenminimalen Lösung entspricht.
Durch das Koppeln von ReSI-M mit R