SUNEX-Integrated Modelling Framework
SUNEX-IMFA is an integrated modelling framework based on sectoral demand-supply analysis of the FEW-systems. It has been developed within SUNEX project to support sustainable FWE-policies and strategies for cities. SUNEX-IMFA has been applied to formulate urban FWE-demand-supply strategies and evaluate key FWE-Nexus indicators.
- quantifies demand and supply of FEW-systems and its interactions at city scale,
- supports policy making by formulating future FWE-development scenarios,
- allows exploring long-term dynamics in human-environment interactions,
- highlights trade-offs across competing policy ambitions of resource supply & demand,
- offers quantitative information about pathways to possible futures through tangible NEXUS indicators,
- provides insights into alternative sustainable pathways of urban FWE-systems.
Thus, SUNEX-IMFA helps in preparing policy guidelines for sustainable urban transformation.
In the beginning sectoral system models for food -, water- and energy- supply and demand have been elaborated. These three comprehensive models build the foundations for the integrated modelling framework representing a simplified flow of FWE-supply-demand:
The starting point is the modelling and calibration of a base year FWE demand-supply. Various data from different sources, the calculation of various input parameters and the adjustment to establish a base year FWE balance was necessary to apply the model to case study cities. For this purpose, several datasets and statistics applied. Due to the persisting lack of data at urban scale several approaches are applied in collecting, consolidating, and preparing the needed input data. If a simplification is not feasible, aggregated data are taken from regionalized national statistics. Following the reconstruction of a real base year future development scenarios are defined for the time range 2020 to 2050 reflecting the expected demographic, socio-economic and technological development of the considered city. Two main development pathways are considered:
- BAU (business as usual) scenario follows the historical trend development
- SDS (sustainable development scenario) reflects a sustainable development path following the expected city’s socio-economic and technological developments. It reflects the conceived transition towards efficient, reliable and low-carbon FWE systems.
Structure of the SUNEX integrated FWE modelling framework
STEPS in applying SUNEX-IMFA:
The modelling framework is implemented within MS Excel, setting up modules for supply- and demand- sub-models through tables, equations and macros which reflect the relations between the sources as well as supply and demand.
input data into of sunex-imfa
The input data required to describe a city case study are prepared in a systematic way to describe the current system state (base year) and the anticipated future development (future development scenarios). Current presented data in the test application refer to Vienna case study. The required data to run SUNEX-IMFA can be classified in 5 main groups:
- Demographic and economic input data framework triggering supply and demand
- Energy supply and demand
- Water supply and demand
- Food supply and demand
- Result tables with NEXUS indicators
The framework data are provided as totals for the case study city. Demand data are provided for the city’s population. Supply data must refer to the different supply regions: local, regional, national, international import. Result tables are again provided for the case study city. The model’s data set consists of 18 tables:
Scenario background framework: Demographic and Socio-Economic data
The socio-economic data cover among others population, family and dwelling size, city GPD and GDP-VA per sector and related growth rate for future development. The data is compiled based on city’s and national statistics, external references and assumptions based on expert judgement. To set up the socio-economic background for the FWE supply and demand a basic set of variables characterising the framework triggering the demand (and the supply) are added for both, the base year and the future reference years till the target year (here 2050)-
- Population numbers and growth rate
- Average size and numbers of households, growth rate
- GDP-VA and growth rate of GDP by sector of agriculture, construction, mining, manufacturing, services, energy).
The following tables shows the data for Vienna case study.
FWE supply and demand data: FOOD, WATER, ENERGY
Input data are entered into several sheets in the predefined Excel table structure. Demand and Supply over time are modelled through scenarios for all the 3 systems simultaneously: Energy, Water, Food.
To run the model, demand-supply data are provided for the base year and the different predefined entities (energy by fuel type and energy form, water by water quality, food by food classes, etc.). Future demand is estimated based on the base year and the expected future socio-economic and technological determinants (e.g., population, GDP by different sectors, efficiency, user behaviour) by entities: energy by energy carrier, water by water quality, food by food classes, etc. Future supply is modelled to cover the projected demand considering the set limits on local resources and import possibilities.
Here only a coarse data structure is defined – detailed data may be extracted and aggregated from national and regional statistics or results from detailed system models (on energy, water and food).
Impact of lifestyle, e.g., changing consumption patterns for food or energy, must be calculated in advance through sectoral models in which the impact of changes (e. g. mobility, car ownership, appliances use, food diets, water consumption by end-use, energy intensity, water intensity, efficiency etc.) is examined in detail. If there are no results available, assumptions must be made based on literature review.
The modelling results cover the FWE-demand and supply of the considered city for the base year and the predefined reference years up to 2050. The results are evaluated and checked by an interactive process to ensure plausibility and consistency among the various drivers and the generated key outputs. Beside the trend development of FWE by commodity and source of supply (local production, regional and external import) a set of key indicators are generated. For example, this covers per capita values, FWE-intensities and elasticities, share of renewable energy supply, energy-related CO2-emission, self-sufficiency, etc.
The diagrams below show energy and water demand per capita for food provision, where figures are growing over time due to increased local to regional production.
key nexus indicators
Furthermore, a set of key nexus indicators (KNIs) are generated based on Nexus-approach established within SUNEX project. Tracing the main intersections along the FWE-supply chains numerous effects have been specified covering 22 dual KNIs (like food delivery, refrigeration, water heating, wastewater treatment/ water desalination, food/water transport, etc..) and 6 triple KNIs comprising urban farming, food and beverage processing, packaging and labelling, cooking, Dishwashing, food catering and hospitality services, Food waste treatment.
The following tables shows the data for Vienna case study.
Finally, dashboards are developed, depicting energy and water demand for local & total food supply (energy and water intensity of food provision).