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Reasons for the Underperformance of Clean Development Mechanism Project Activities in the Animal Waste Management Sector

An Analysis of Swine Manure treating Facilities in Latin America

dc.contributor.advisorWegener, Jens-Karl
dc.contributor.authorDeecke, Imme Dorotheade
dc.titleReasons for the Underperformance of Clean Development Mechanism Project Activities in the Animal Waste Management Sectorde
dc.title.alternativeAn Analysis of Swine Manure treating Facilities in Latin Americade
dc.title.translatedUrsachen des geringen Erfolgs von Abwasserbehandlungsprojekten in der Tierproduktion im Rahmen des Clean Development Mechanismde
dc.contributor.refereeLücke, Wolfgang Prof.
dc.subject.dnb500 Naturwissenschaftende
dc.description.abstractengINTRODUCTION The Clean Development Mechanism (CDM) is one of the flexible, project based mechanisms of the Kyoto protocol, which came into force in 2005. The projects participating in this mechanism estimate the potential emission reductions ex-ante by following specific guidance of the Executive Board (EB) of the United Nations Framework Convention on Climate Change. The amounts of emission reductions estimated and the amounts of emission reductions monitored ex-post differ. In some sectors projects reduce more emissions than forecasted (e.g. industrial gases sector) in other sectors less (e.g. landfill sector). The performance of project activities undertaken in the animal waste management sector is particular low (45 %). These projects aim at avoiding greenhouse gas emissions by capturing and flaring methane emitted from open lagoons in which swine manure is disposed. The reasons for the overestimation of potential emission reductions are subject to this doctoral thesis. In order to investigate whether inaccurate ex-ante assumptions are to be held responsible, it is analyzed if the ex-ante assessment of descriptive statistical parameters (hypothesis I) or if the use of default values issued by the Intergovernmental Panel on Climate Change (IPCC) (hypothesis II) causes the gap between forecasted and measured emission reductions.MATERIAL AND METHODS A sample of projects is identified, showing comparable characteristics. Relevant documentation regarding each project is consulted including project design documents, validation reports, monitoring reports, verification reports and others. As assessment factor the baseline emission forecast success is introduced. It is analyzed for each project of the sample. The hypotheses are further elaborated by assessing each applicable parameter and developing assumptions on its impact. It is investigated, if the suggested assumptions and introduced alternative approaches influence the baseline emission forecast success. Corresponding correction factors are derived. The quality of the monitoring is assessed by reviewing the monitoring reports and related documentation in order to receive information on mistakes and failures occurring during the monitoring of the projects. The results for all parameters applicable to each hypothesis are combined in order to test the hypothesis. Finally, all quantifiable measures are combined and applied to determine the over-all impact of the parameters on the baseline emission forecast success.RESULTS Initially the projects of the sample estimated the baseline emissions with a forecast success of 25 %, meaning that only 25 % of the forecasted baseline emissions were monitored ex-post. Analysing the descriptive statistical parameters (hypothesis I) results in heterogeneous correction factors between 0.95 (population) and 1.14 (start date). The assessment of the influence of default values (hypothesis II) shows that all default values lead to an overestimation and range from 1.16 (volatile solids not weight adjusted) to 1.64 (methane conversion factor). Using the alternative default values introduced in this study for the methane conversion factor and the volatile solids and adjusting the latter by animal weight have the strongest impact on the baseline emission forecast success. If all resulting correction factors of the analysed parameters are combined the baseline emission forecast success is improved by a factor of approximately 3.13. The resulting forecast success is about 79 %. The impact of the monitoring could not be quantified. On the one hand mistakes of the management personnel and monitoring equipment are found on and on the other, monitoring procedures, such as the indirect determination of the methane content of the biogas on a quarterly basis lead to inaccuracies. However, these effects may influence the forecast success both in a positive and in a negative way. Although the introduced corrections increase the baseline emission forecast success significantly, the improved performance of the projects is still heterogeneous. This shows that not all issues are covered by the corrections. The remaining discrepancies between forecasted and measured data could be due to monitoring issues. Another reason could be the fact that nearly no project specific data was available to test the default values. Therefore, default values were replaced by new and adjusted default values developed in this study.CONCLUSION Although the default factors have been proven to be inaccurate, the institutions advising to use them cannot be held solely responsible for the low performance of the projects. The UNFCCC methodology along with the IPCC guidelines inform the project developer about risks and uncertainties related to the default values and suggest more accurate measures. Nevertheless, it has been shown that the IPCC defaults are not substantiated enough and are based on only few references or estimates. Therefore, project developers have to use the default values with caution and obtain data from on-site measurements whenever possible. In addition, it has to be considered that the perspectives of the IPCC and the UNFCCC are different when estimating emissions. Both aim at conservative estimates. However, from the point of view of the IPCC, emissions should be rather overestimated than underestimated in order to assess the greenhouse gas inventories conservatively. The opposite is the case for CDM projects were the overestimation should be prevented through conservative approaches. Therefore, adjusting the IPCC defaults by a well substantiated conservatism factor when obtaining them for CDM projects should be considered. Summing up, it can be concluded that forecasting the biological process of biodigestion is complex and not thoroughly understood yet. More research has to be undertaken, especially on the methane conversion factor, in order to have default values allowing accurate and conservative forecasts.Abstract (GER)Niedersächsische Staats- und Universitätsbibliothek Göttingen 37070 GöttingenUrheberrechtCopyrightde
dc.contributor.coRefereeMärländer, Bernward Prof.
dc.title.alternativeTranslatedEine Analyse von Schweineproduktionsbetrieben in Lateinamerikade
dc.subject.topicAgricultural Sciencesde
dc.subject.gerMechanismus für umweltverträgliche Entwicklungde
dc.subject.gerClean Development Mechanismusde
dc.subject.gerRahmenübereinkommen der Vereinten Nationen über Klimaänderungende
dc.subject.gerAneaerober Abbaude
dc.subject.engClean Development Mechanismde
dc.subject.engAnimal Waste Managementde
dc.subject.engMethane Conversion Factorde
dc.subject.engEmission Reductionde
dc.subject.engSwine Manurede
dc.subject.engIssuance Successde
dc.subject.engBaseline Emission Forecast Successde
dc.subject.engDefault Valuede
dc.subject.engClimate Changede
dc.subject.engIntergovernmental Panel on Climate Changede
dc.subject.engUnited Nations Framework Convention on Climate Changede
dc.subject.engCertified Emission Reductionde
dc.subject.engAnaerobic Lagoonde
dc.affiliation.instituteFakultät für Agrarwissenschaftende
dc.subject.gokfullZWE 600: Abwassertechnikde
dc.subject.gokfullWR 700: Biologischer Abbau {Biologiede

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