EUC warmly welcomes Dr.听Oleksandr Galychyn as a postdoctoral visitor from Ukraine. Dr.听Galychyn鈥檚 research explores how economies depend on energy, materials, water, and ecosystems. His work brings together ecological economics, environmental accounting, life cycle assessment, and systems modelling to better understand how economic activity affects the environment and how these relationships may change over time. He has contributed to research projects across Europe and the Nordic region involving energy, water, sustainable mobility, circular economy, environmental assessment, and resource modelling. His research has contributed to various projects including Italy's National Recovery and Resilience Plan, Horizon Europe, UC-Mobility, and Nordic Life Cycle Assessment harmonization. He has also collaborated on solar forecasting (Ener-Predict), energy market analysis, and circular economy research and is experienced in scenario modeling, data integration, spatial analysis, and behavioral research.
EUC Special Projects Assistant, Kymary Magpuyo, interviewed Dr. Galychyn to learn more about his postdoctoral research at 91亚色.
Q. Can you describe your research interests and why you chose this as your career path?
A: My research focuses on the relationship between economic activity and the physical environment that supports it. I am particularly interested in how economies use energy, materials, and water, how these resources move through production and consumption, and what environmental impacts result. My original background was in civil engineering and urban planning. After completing my master鈥檚 degree, I worked in urban planning. That experience made me increasingly interested in the wider environmental and economic consequences of how cities and infrastructure develop. This eventually led me to ecological economics. During my PhD, I studied how energy and materials move through cities and economies, from resource extraction and production to consumption, recycling, and waste. After my PhD, I worked on research involving energy, water, mobility, material use, and environmental assessment. I also became particularly interested in systems modelling because it allows us to study not only what is happening today, but also how economic and environmental conditions may change over time. Some of my previous work examined water systems and how changes in water availability can interact with economic activity. This experience is relevant to my current research because a similar systems perspective can also be applied to energy and other physical resources.
Figure 1 is an example from my earlier water-related modelling work. It shows how the supply of a physical resource can be represented within a wider model of economic and environmental change. The same general approach can be applied to other essential resources, including energy.
The broader question behind my research is simple: How can we understand the economy not only in financial terms, but also in terms of the energy, materials, water, and ecosystems that support it? That question is also what attracted me to the research being undertaken at 91亚色.
Q. How does your work connect to the research at the International Ecological Footprint Learning Lab (IEFLL) and why were you interested in collaborating with the project?
A:The research at the International Ecological Footprint Learning Lab, or IEFLL, is closely connected with my own interests because it examines the relationship between economic activity, resource use, and ecological limits. In my previous research, I have worked with carbon, energy, and ecological footprint indicators, as well as environmental accounting and systems modelling. These approaches help us understand the physical consequences of economic activity, including the energy, land, materials, and other resources needed to support production and consumption. I was especially interested in the work of Peter Victor and Eric Miller in the because their research connects economic development with environmental limits. One of the questions I find most interesting is how to connect environmental information with economic change. An ecological footprint, for example, can tell us about the pressure that human activities place on ecosystems. A dynamic economic model can help us explore how changes in investment, production, consumption, or technology might increase or reduce that pressure in the future. Bringing these perspectives together allows us to ask practical questions: What happens to resource use when the economy changes? Can environmental pressures decline while employment and well-being are maintained? What trade-offs appear under different pathways?
IEFLL provides a strong environment for exploring these questions and collaborating with postdoctoral researchers and master鈥檚 students working across ecological economics, ecological footprint analysis, and systems modelling.
Q. How do you plan to structurally reconcile the dynamic and macroeconomic nature of low growth with spatial accounting-based metrics that are used in ecological footprint?
A. The challenge is that these approaches describe different parts of the same system. Macroeconomic models help us understand how production, investment, employment, and consumption may change over time. Environmental accounts and ecological footprint indicators show the physical resources and environmental pressures associated with those activities. My research tries to connect these two perspectives. At 91亚色, one of my main areas of work is energy. Energy is used throughout the economy, but total energy consumption alone does not tell us enough. We also need to understand where energy comes from, how it is converted, which parts of the economy use it, and how efficiently it provides the services people need. For example, households need energy for heating, lighting, and appliances. Transport requires energy to move people and goods. Industry needs energy for machinery and heat. Changes in technology, consumption, and economic activity can therefore have very different effects on energy demand. My current work aims to represent these relationships more clearly within the wider economic model. This is particularly important when we look at long-term change. Electrification can reduce direct fossil fuel use, but it can also increase demand for electricity and materials. Improvements in energy efficiency can reduce demand, while changes in population, production, or consumption can increase it. The goal is not simply to make the model more detailed. It is to understand whether different economic pathways are also realistic in terms of energy, resources, and environmental pressures. My earlier work with water shows a similar idea. Resource demand does not exist in isolation. Changes in economic activity can affect both resource use and environmental conditions.
Figure 2 provides another example from my earlier water-related research. It illustrates how changes in resource demand can interact with environmental pressures. The same systems perspective is relevant to my current energy research, where changes in economic activity, technology, and consumption can affect energy demand and related environmental impacts over time.
There is also an important question of complexity. Adding information about energy, water, materials, and ecosystems can make a model more realistic. But if a model becomes too complicated, it can also become difficult to understand, reproduce, and communicate. An important part of my research is therefore finding the right balance. The model needs enough detail to represent important environmental constraints, while remaining transparent and useful.
Ultimately, this can help us compare different futures for Canada using a broader set of measures than economic growth alone.
Q. Beyond immediate modeling goals, what do you see as the biggest policy or communication barrier to getting Canadian decision-makers to accept and use resource-constrained scenario outputs?
A. One of the biggest barriers is communication. Environmental and economic systems are complex. A model may contain many relationships involving the economy, energy, materials, and ecosystems. This level of detail is useful for researchers, but decision makers cannot be expected to examine every equation or technical indicator. The results therefore need to answer clear and practical questions.
Are we reducing energy and resource use? Are environmental pressures declining? Are we staying within ecological limits? What happens to employment and well-being? What trade-offs appear under different policy choices?
These questions communicate the purpose of the modelling much more clearly than a large set of technical outputs. Transparency is also important. Decision makers need to understand which assumptions are behind a scenario, why a model produces a particular result, and how changing those assumptions could change the outcome. I do not see these models as tools for predicting one exact future. Their main value is in helping us compare different possible futures and understand their consequences. This is particularly important in ecological economics. A pathway may appear successful according to one economic indicator, but the picture can change once energy requirements, resource use, and environmental pressures are also considered.
If these relationships are communicated clearly, ecological-economic models can provide a stronger basis for discussing how environmental sustainability, economic stability, and human well-being can be pursued together.
Recent works:
Pauliuk, S. and听Galychyn, O.,听et al. (2026).听Stylized Facts for the Circular Economy - A Knowledge Synthesis (June 30, 2026). Available at SSRN: or 听
Galychyn,听O., Fath,听B., Wiedenhofer,听D., Buonocore,听E., & Franzese,听P. (2024). An urban emergy footprint: Comparing supply- and use-extended input-output models for the case of Vienna, Austria. Cleaner Production Letters, 6, 100058.
Galychyn, O., Fath, B. D., Shah, I. H., Buonocore, E., & Franzese, P. P. (2022). A multi-criteria framework for assessing urban socio-ecological systems: The emergy nexus of the urban economy and environment. Cleaner Environmental Systems, 5, 100080.