C Mathematical and Quantitative Methods
Refine
Document Type
- Master's Thesis (2)
Language
- English (2)
Has Fulltext
- yes (2)
Keywords
- Blue Carbon Potential Index (1)
- Blue carbon (1)
- EEG (1)
- Electricity prices (1)
- GIS (1)
- Geoinformationssystem (1)
- Mangrove (1)
- Python (1)
- Renewable energy (1)
- Spatial multicriteria analysis (1)
Faculty
- Fakultät 12 / Institut für Technologie und Ressourcenmanagement in den Tropen und Subtropen (2) (remove)
Mangrove forests have been studied broadly in the recent three decades for their outstanding ability to sequester carbon in the beneath soil and other beneficial ecosystem services. Endeavors to conserve and regenerate mangrove cover are still increasing worldwide as a mechanism to include them in NDCs and carbon markets. Therefore, decision-makers in the private and public sectors require identify possible areas for conservation and restoration prior to blue carbon project investment. Thus, an integral assessment of potential mangrove carbon reservoirs in a landscape scale, considering environmental and socioeconomic factors was performed. This study was aimed to determine areas with the highest blue carbon sequestration potential in the Gulf of Guayaquil through the construction of a Blue Carbon Potential Index (BCPI) based on Spatial Multicriteria Analysis (SMCA). A narrative integrative literature review was employed to select indicators of mangrove carbon sequestration gains and losses. These indicators were pondered following the Analytical Hierarchy Process (AHP) with the judgments of two experts and reclassified in four potential categories based on their thresholds. Since no consensus was achieved in the indicator importance hierarchization, a comparative of equal weighting method and AHP weighting was implemented. The linear combination rule was used to integrate these factors into a unique-scaled index supported by a geographic Information System (GIS). The results showed that 15.82% and 16.21% of the study area belonged to high and moderate potential of blue carbon sequestration respectively. Moreover, no significant differences were found between the two weighting methods applied. The BCPI provides a comprehensive understanding of spatial distribution of blue carbon potential reservoirs and grants a quantification of this potential to prioritize conservation and restoration areas.
This thesis presents the perspective and basis for modeling of retail electricity price components in Germany. Detailed Python models are developed to provide predictions for yearly development of average network charges, EEG, StromNEV-19 and KWK surcharges for the period 2015-2035. For network charges and EEG surcharge, scenario-B (2035) from NEP2015 has been chosen as the model scenario. For KWK surcharge, the 2025 KWK share target, set by KWKG-2016, has been chosen as the model scenario. Individual component model results are validated against available academic literature and institutional reports. Model results for EEG surcharge, indicate an increasing yearly EEG costs till 2024, after which the expiring EEG plants of past will unburden the related high costs and EEG surcharge will drop but still be around 99% of 2015 level in 2035. Model results for network charges indicate a consistently increasing yearly trend owing to high grid investments needed for reaching the target RE share of 57%. KWK model results also indicate a growing KWK surcharge until 2020 which then would remain stagnant at that level onwards. All model results are collected under three consumption categories, namely, households, privileged and nonprivileged industries. The final results indicate that the average German household will face an overall increase of around 3.37 Cents/kWh in retail electricity prices (excluding VAT) till 2028, after which the retail prices will drop a little due to dropping EEG surcharge. The similar but slightly reduced trend can be seen for nonprivileged industrial consumption. The increment effect, however, is only minute for privileged industrial consumption due to high exemptions in EEG & KWK surcharges and reduced individual network charges.