M.Sc. Topic I: “The Use of Artificial Intelligence in Energy System Modeling"

Supervisor: Dr. Danial Esmaeili Aliabadi & | E-MAIL

1. Convolution Neural Networks for image processing, and
2. Large Language Models for natural language processing.

• Organizing the inputs for the AI model
• Implementing and fine-tuning the AI model
• Preparing the dataset/scenario for the optimization model to use

M.Sc. Topic II: “Spatially-explicit modeling of the bioenergy in Germany”

Supervisor: Dr. Danial Esmaeili Aliabadi | E-MAIL

• Increasing the spatial resolution of the Bioenergy Optimization (BenOpt) model using GIS information.
• Developing new tools to facilitate the interaction between backend (i.e., the GAMS solver) and frontend (i.e., user-interface).
• Analyzing consumers’ behavior using an agent-based model in connection with the produced optimization model.

M.Sc. Topic V: “Wind energy in forests: ownership, structural parameters of forests, regional comparison”

Supervisors: David Manske & Nora Mittelstädt | E-MAIL

• Analyse forest ownership data, forest properties and wind energy site data
• Compare regional tendencies

B.Sc. Topic VI: “Closest to the energy transition: expansion of renewable energies in (former) lignite mining areas.”

Supervisor: Nora Mittelstädt | E-MAIL

• Registration of German lignite areas in GIS software and overlap with renewable energy additions and land cover classes
• Assessment of administrative and political conditions (for example: re-cultivation obligations) for (former) lignite mining areas
• Qualitative analysis, for example by method of causal-process tracing

B.Sc. Topic IX: “Regional analyses: Wind energy in forests: ownership, structural parameters of forests”

Supervisors: David Manske & Nora Mittelstädt | E-MAIL

• Analyse forest ownership data, forest properties and wind energy site data for one selected region

Regional explicit LCA impacts

Supervisor:  Matthias M. Welker  

Most conducted LCA studies to not rely on regionalized characterization factors, even though according methods are available (GLAM, Impact World+). Further multiple tools allow regional impact assessment (OpenLCA, brightway with edges). Additionally novel tools allow database regionalization (regioinvent). The master thesis goal would be to explore those approaches, assess their practicability and conduct a specific case study that compares regional explicit vs. regional independent impact assessment.

Tasks:

• Literature Review of different regionalization approaches
• Comparison of regionalization approach implementations
• Conducting LCA with regional-explicit vs. globally uniform impacts
• Discussing implications

Prerequisites:

• Recommended: Experience in LCA e.g. Successful completion of course "Life Cycle Analyses and Sustainability" or through relevant work experience
• Optional: experience in python programming

Biodiversity, land-use, and positive environmental impacts of green roof systems

Supervisor:  Matthias M. Welker  

Green roof systems are associated with higher greenhouse gas emissions than conventional roofing, however they contribute positively to the environment by providing space and soil for biodiversity rich flora and insects. Anecdotally, this trade-off might be even more severe the more stable the roofing structure. How can this relationship be accounted for in LCA? How high is there negative climate contribution? How could biodiversity impacts in the roofs use phase be modelled? The master thesis, aiming to answer these or related questions, would review existing literature on land-use/biodiversity indicators, published studies on green roof impacts and apply one or several land/use biodiversity indicators to a specific case study of a green roof system.

Tasks:

• Literature review of biodiversity impact categories and LCAs of green roof systems
• Comparison of biodiversity impacvt category values
• Conducting LCA of green roof system under consideration fo different biodiversity impact categories
• Discussing implications

Prerequisites:

• Recommended: Experience in LCA e.g. Successful completion of course "Life Cycle Analyses and Sustainability" or through relevant work experience

Review of Biophysical Limits/Planetary Boundary Indicators for LCA

Supervisor:  Matthias M. Welker  

Absolute Environmental Sustainability Assessment proposes the comparison of biophysical limits against absolute limits (e.g. Planetary Boundaries) with the goal to conclude not if a system is more sustainable than another (comparative LCA) but to conclude if a system is sustainable enough. The method depends heavily on expression of biophysical limits in the same units as LCA (Sala et al. 2020, Ryberg et al. 2018).
This master thesis would review the different conceptualization of biophysical limits for one or multiple impact categories to compare the normative decisions behind it. To do so the practical implementation should include the comparison of an average product basket against multiple of those indicators in a specific case study.

Tasks:

• Literature Analysis of biophysical limits indicators
• Comparison of indicator assumptions, underlying values and final results
• Application of multiple indicators to a simple product system (average product basket)
• Discussion of indicator choices, results from product-basket implementation

Prerequisites:

• Recommended: Experience in LCA e.g. Successful completion of course "Life Cycle Analyses and Sustainability" or through relevant work experience

Integration of Techno-Economic Analysis (TEA) and Life Cycle Assessment (LCA)

Supervisor:  Madeleine Pries  

Life Cycle Assessment (LCA) and Techno-Economic Assessment (TEA) are widely used to evaluate new technologies and processes. While LCA focuses on environmental impacts, TEA assesses economic performance and scalability.

The thesis will investigate how such TEA-based scaling approaches and datasets can support prospective LCA modeling and improve the robustness of environmental assessments of emerging technologies. A particular focus will be on process scaling: TEA often uses engineering-based approaches to estimate industrial-scale performance from laboratory or pilot-scale data. The thesis will explore how these methods and data can support prospective LCA studies and help create more realistic environmental assessments of future large-scale processes.

Possible tasks include a literature review of existing TEA-LCA integration approaches, and application to a practical case study in the bioeconomy.

Prerequisites:

• Experience in either TEA or LCA
• Successful completion of course "Life Cycle Analyses and Sustainability" or relevant work experience in TEA/LCA

Development of a Database Exchange Tool between Brightway and openLCA

Supervisor:  Dr.-Ing. Walther Zeug  

Brightway and openLCA are widely used open-source software environments for Life Cycle Assessment (LCA). However, exchanging life cycle inventory databases between these environments can be challenging because they use different data models, structures, and import/export formats. Reliable interoperability is essential for reproducible research and for enabling practitioners to use datasets across different LCA tools.

The aim of this thesis is to develop and evaluate a data exchange tool for transferring LCA databases between Brightway and openLCA. The work will focus on translating relevant database elements—such as processes, products, flows, exchanges, units, parameters, and metadata—while preserving the consistency and integrity of the original data.

From a data science perspective, the thesis will address challenges related to data transformation, schema mapping, validation, and quality assurance. Existing exchange formats and software interfaces will be assessed, and a transparent and reproducible conversion workflow will be designed. The resulting tool should support automated checks to identify missing information, inconsistent mappings, and potential data losses during conversion.

Tasks:

• reviewing existing tools, data formats, and approaches for exchanging LCA databases
• comparing the data models of Brightway and openLCA
• defining mapping and conversion rules for relevant database elements
• implementing a modular exchange tool, preferably in Python
• developing automated validation and testing procedures
• evaluating the tool using selected LCA databases and specific case studies
• documenting the software and its limitations to support future development and use

The final scope, including whether the tool supports one-way or bidirectional exchange, can be adapted to the student’s interests and the technical feasibility of the project.

Prerequisites:

• good programming skills, preferably in Python
• experience with data processing, database structures, or software development
• interest in Life Cycle Assessment and environmental data
• experience with Brightway, openLCA, or another LCA tool is desirable
• successful completion of the course “Life Cycle Analyses and Sustainability” or relevant experience in LCA, data science, or software engineering

Development of a Serious Game on Democratic Economic Planning for Socio-Ecological Transformation

Supervisor:  Dr.-Ing. Walther Zeug  

The socio-ecological transformation of cities, infrastructures, and essential supply systems requires decisions that consider environmental limits, social needs, available labor, and competing interests. Democratic economic planning offers approaches for collectively negotiating such decisions. However, the interdependencies and conflicts involved often remain abstract and are difficult to communicate through conventional teaching formats.

This thesis will contribute to the development and scientific evaluation of PLANET (“Playing and Planning for Ecological Transformation”), a serious game in which participants design transformation pathways for a fictional urban district. The game covers supply systems such as energy, mobility, housing, and food. Participants must meet societal needs while respecting defined budgets for resource use, emissions, and labor.

A particular focus will be on translating quantitative sustainability assessments and democratic decision making into accessible game mechanics. Life Cycle Assessment data and models developed in openLCA may be used to represent the environmental and social consequences of different technologies and infrastructure choices. Through role-playing, negotiation, and collective decision-making, participants will experience trade-offs, dependencies, and distributional conflicts associated with socio-ecological transformation.

Tasks:

• reviewing existing serious games on sustainability, economic planning, and societal transformation
• developing scenarios, stakeholder roles, decision rules, and transformation option
• translating indicators for resource use, emissions, labor, and social needs into game mechanics
• designing or refining physical and digital game materials
• integrating Life Cycle Assessment results or openLCA models into the game
• conducting and evaluating test sessions with students or other participant groups
• assessing usability, learning outcomes, negotiation processes, and participant engagement
• revising and documenting the game for future teaching and research applications

The final scope may focus on game development, the integration of sustainability data, or the empirical evaluation of the game, depending on the student’s interests and background.

Prerequisites:

• interest in socio-ecological transformation, democratic planning, and sustainability
• strong conceptual and analytical skills
• experience with qualitative or quantitative research methods
• experience in game design, economics, sustainability assessment, or educational research is desirable
• knowledge of Life Cycle Assessment or openLCA is beneficial but not required
• successful completion of the course “Life Cycle Analyses and Sustainability” or relevant experience in sustainability, economics, environmental science, or a related field

Data-Based Evaluation of Tokens for a Multi-Criteria Economy against Life Cycle Assessment Indicators and Planetary Boundaries

Supervisor:  Dr.-Ing. Walther Zeug  

Cybernetic Democratic Economic Planning (CDEP) proposes a three-dimensional token system for coordinating production and consumption within ecological and social limits. The three tokens represent raw material consumption (RMC), climate footprint (CF), and work (W). They are intended to provide an accessible representation of the much larger set of environmental, economic, and social indicators covered by Holistic and Integrated Life Cycle Sustainability Assessment (HILCSA).

An open research question is whether these three tokens adequately represent the broader HILCSA indicator set and the environmental pressures associated with the planetary boundaries. Indicators such as land use, water consumption, biodiversity loss, toxicity, working conditions, and human health may correlate with the tokens in some production systems but not in others. A systematic empirical analysis is therefore required to determine which sustainability dimensions are captured by the tokens and which may remain insufficiently represented.

The thesis will compile and analyze HILCSA results for selected products, technologies, or provisioning systems. Principal component analysis and related multivariate methods will be used to examine correlations, identify underlying dimensions in the data, and assess how much of the variation in the complete indicator set can be explained by RMC, CF, and W. HILCSA indicators will also be mapped to planetary boundaries and, where possible, evaluated against corresponding sustainability thresholds. The analysis should distinguish between statistical correlation and the ability of the token system to indicate compliance with absolute ecological limits.

Tasks:

• reviewing literature on sustainability indicators, proxy indicators, HILCSA, and planetary boundaries
• selecting suitable products, processes, sectors, or transformation scenarios for analysis
• compiling and harmonizing a dataset of HILCSA results and token values
• mapping environmental indicators to planetary-boundary categories and control variables
• conducting exploratory data analysis and correlation analysis
• applying principal component analysis, factor analysis, clustering, or regression methods
• evaluating how well RMC, CF, and W explain or predict the remaining indicators
• identifying indicators, sectors, and technologies that are insufficiently represented by the tokens
• testing the sensitivity of the results to normalization, weighting, system boundaries, and dataset selection
• developing recommendations for additional tokens, safeguards, or complementary satellite indicators

The results will contribute to the empirical validation and further development of the CDEP token system. They may also provide broader insights into the opportunities and limitations of reducing multidimensional sustainability information to a small number of lead indicators.

Prerequisites:

• experience with statistical or multivariate data analysis
• programming skills in Python, R, or a comparable analytical environment
• interest in Life Cycle Assessment, sustainability indicators, or planetary boundaries
• experience with openLCA, HILCSA, or environmental datasets is desirable
• successful completion of the course “Life Cycle Analyses and Sustainability” or relevant experience in LCA, data science, statistics, environmental science, or a related field

LCA-Based Simulation of Cybernetic Democratic Economic Planning for Decent Living Standards

Supervisor:  Dr.-Ing. Walther Zeug  

Decent Living Standards (DLS) describe the material conditions and essential services required to enable a good life for all. These include adequate housing, nutrition, mobility, energy, healthcare, education, communication, and other forms of social provision. A central challenge of socio-ecological transformation is determining whether these needs can be met for an entire population while remaining within planetary and regional ecological and societal boundaries.

Cybernetic Democratic Economic Planning (CDEP) proposes a system for coordinating production and consumption through democratic planning, sustainability assessment, and multidimensional resource budgets. Instead of monetary prices, the approach uses three tokens representing raw material consumption (RMC), climate footprint (CF), and work (W). Life Cycle Assessment (LCA) provides the underlying data needed to calculate the direct and indirect requirements of goods, services, and provisioning systems.

The thesis will develop an LCA-based simulation that connects DLS requirements with the CDEP planning and token framework. A basket of goods and services representing decent living standards will be defined for a selected population or region. Its material requirements, climate impacts, and labor requirements will then be calculated and compared with sustainable per-capita or regional token budgets. The simulation will investigate whether and under which conditions CDEP could coordinate the provision of decent living standards within ecological and social limits.

Tasks:

• reviewing literature on Decent Living Standards, absolute sustainability assessment, LCA, and democratic economic planning
• selecting and operationalizing a DLS framework for a defined population or region
• translating DLS dimensions into demand for specific goods, services, and infrastructures
• developing LCA models for provisioning systems such as housing, food, mobility, energy, healthcare, and education
• calculating the RMC, CF, and W token requirements associated with the selected DLS scenario
• implementing a simulation model in Python, R, openLCA, or a suitable system-dynamics or agent-based modeling environment
• modeling the allocation of token budgets across households, sectors, or forms of provision
• identifying resource, emission, labor, or infrastructure bottlenecks
• conducting sensitivity and uncertainty analyses for key assumptions and parameters
• deriving recommendations for sustainable provisioning and the further development of the CDEP framework

The final scope may focus on a specific provisioning sector, a regional case study, or an integrated DLS scenario. Depending on data availability and the student’s interests, the simulation may examine static feasibility or dynamic transformation pathways toward decent living standards.

Prerequisites:

• experience with Life Cycle Assessment or quantitative sustainability assessment
• programming or modeling skills, preferably in Python or R
• interest in Decent Living Standards, socio-ecological transformation, or democratic economic planning
• experience with openLCA, system dynamics, agent-based modeling, or optimization is desirable
• successful completion of the course “Life Cycle Analyses and Sustainability” or relevant experience in LCA, data science, environmental modeling, economics, or a related field

Updating the Social Life Cycle Assessment Component of HILCSA through a Labour Footprint

Supervisor:  Dr.-Ing. Walther Zeug  

Social Life Cycle Assessment (S-LCA) evaluates the positive and negative social effects associated with products, organizations, and their value chains. The field is developing rapidly. Important recent advances include the publication of ISO 14075:2024, the UNEP S-LCA Guidelines and methodological sheets, and updated social databases such as PSILCA 4.0. At the same time, methodological questions concerning data quality, impact pathways, stakeholder categories, aggregation, and the interpretation of social indicators remain unresolved.

The Holistic and Integrated Life Cycle Sustainability Assessment (HILCSA) framework combines environmental, economic, and social indicators in a consistent life cycle model. To reflect current developments in S-LCA, its social assessment component and underlying indicator set should be reviewed and updated. A particular focus of this thesis will be the development of a labour footprint that quantifies the direct and indirect labour embodied in products and services across their complete supply chains.

The labour footprint should distinguish between the amount of labour required and the conditions under which that labour is performed. Worker hours can provide an activity variable for tracing labour through supply chains, but they do not by themselves represent social impacts such as inadequate wages, occupational accidents, forced or child labour, discrimination, excessive working hours, or restrictions on collective bargaining. The thesis will therefore examine how quantitative labour requirements and qualitative labour conditions can be combined without obscuring their different meanings.

Tasks:

• reviewing current methodological developments, standards, databases, and applications in S-LCA
• comparing the UNEP guidance and ISO 14075:2024 with the current HILCSA methodology
• reviewing and updating HILCSA’s social stakeholder categories, subcategories, and indicators
• examining alternative approaches based on worker hours, risk-weighted worker hours, and directly quantified raw values
• defining the scope and calculation method of a product- or service-level labour footprint
• distinguishing direct from upstream labour and paid from unpaid or reproductive work where data allow
• evaluating recent S-LCA databases, including PSILCA 4.0 and SoCa, regarding coverage, transparency, regional resolution, and data quality
• implementing updated indicators and characterization factors in openLCA
• applying the revised method to a practical case study
• comparing the updated results with those produced by the current HILCSA method
• conducting sensitivity and uncertainty analyses for activity variables, risk levels, aggregation, and weighting
• documenting the revised method and providing recommendations for its future integration into HILCSA

The thesis will contribute to a more transparent and methodologically current representation of labour in life cycle sustainability assessment. It should clarify which aspects can meaningfully be combined into a labour footprint and which working conditions need to remain visible as separate indicators.

Prerequisites:

• experience with Life Cycle Assessment, Social LCA, or quantitative sustainability assessment
• interest in labour, social sustainability, and global supply chains
• skills in data processing and quantitative analysis
• experience with openLCA, Python, R, or S-LCA databases is desirable
• successful completion of the course “Life Cycle Analyses and Sustainability” or relevant experience in LCA, sustainability science, social sciences, economics, or a related field

Hybrid Allocation Principles of Planetary Boundaries in Product-Level Assessments

Supervisor:  Dr. Enrique A. Perdomo E.  

The concept of planetary boundaries defines a global “safe operating space” for humanity. To use this concept in practice (e.g., for climate or land‑use targets), global limits could be downscaled and allocated to countries, sectors or products.
Different allocation rules (e.g., per capita, based on income, or on historical emissions) reflect different ideas of distributive justice and lead to different allowed “budgets”. Hybrid rules that combine several of these aspects (population, capability, historical responsibility, efficiency) could offer more balanced and fair allocations.
This thesis should develop and test 1–2 hybrid allocation principles that mathematically combine, for example, population, income/capability, and historical responsibility, and apply them to the assessment of a generic industrial product (e.g. steel, cement or a common consumer good).

Tasks:

• Literature review on planetary boundary downscaling and distributive justice
• Design of 1–2 hybrid allocation formulas that combine several dimensions (e.g. population + inverse income + historical emissions).
• Simple calculation of national or regional budgets under these hybrid rules.
• Application of these budgets in a product‑level assessment using existing LCA or emission data to derive and compare “absolute sustainability” indicators.

Development and validation of an AI-assisted framework for integrating circularity indicators into ecoinvent background processes in openLCA

Supervisor:  Dr. Enrique A. Perdomo E.  

Applying circularity indicators from a life-cycle perspective requires circularity variables to be traced across both foreground and background processes. However, standard LCI databases such as ecoinvent do not explicitly contain all required variables.

This thesis will develop a reproducible method for integrating a selected circularity indicator into a licensed ecoinvent database in openLCA. It will investigate how AI can support the classification of relevant processes and compare AI-assisted classifications with deterministic rules based on process metadata and exchanges. The method will be implemented for a defined material or process group and tested on a product system.

Tasks:

• Review circularity indicators and their data requirements
• Map selected indicator variables to ecoinvent data
• Develop and compare rule-based and AI-assisted process classification
• Implement the variables in openLCA using a reproducible script
• Test the method on a product system
• Evaluate accuracy, uncertainty and methodological limitations

Prerequisites:

• Recommended: Experience in LCA and openLCA
• Basic Python knowledge or willingness to learn
• Interest in circular economy, data analysis and AI

Climate Substitution Benefits and Biomass-Use Efficiency

Supervisor:  Dr. Enrique A. Perdomo E.  

Bioeconomy monitoring often reports production, value added, employment, or the amount of biomass used. Such metrics do not show whether a bio-based product actually replaces a fossil-based alternative or whether the replacement reduces life-cycle greenhouse-gas (GHG) emissions.

Aim. To develop and pilot-test a transparent LCA-based framework for quantifying the climate substitution benefit and biomass-use efficiency of competing bio-based applications while explicitly identifying non-climate environmental trade-offs.

Tasks:

• Conduct a targeted systematic or scoping review of substitution metrics, displacement factors, biomass-efficiency metrics, and LCA-based trade-off methods.
• Model a Level 1 (bottom-up approach) bio-based pathway and its fossil-based functional equivalent using a common database version and life-cycle impact assessment method.
• Model a Level 2, sector-level monitoring. Relevant question: Has substitution become large enough to change sectoral fossil dependence? (Maybe this is a second thesis)