|Tuesday, September 15th|
Freddy Soria, Universidad CatÃ³lica Boliviana, Centro de InvestigaciÃ³n en Agua, EnergÃa y Sostenibilidad
11:40 AM - 12:00 PM
Climate change impacts the biosphere, for instance it affects global resources. Given the variable landscape, streamflow generation in mountainous catchments is likely to be stricken with changes at faster rates compared to other geographical locations. La Paz and El Alto are two important cities in the Bolivian Andes, where a large amount of energy supply is generated through hydropower plants distributed in a cascade scheme. Such cascade is located in the headwaters of the Amazon basin, in the downstream direction. The mountains are partially glacierized; such characteristic increases its sensitivity to climate change. Thus, all the elements together constitute a heterogeneous landscape worth studying. To address the study, the approach considers the models WEAP and LEAP; for the baseline, inputs are historical field data whereas to define future scenarios are considered model outputs from the Global Circulation Model HAD GEM2 – ES, RCP (Representative Concentration Pathway) 8.5 scenario from the Fifth Assessment Report of the United Nations Intergovernmental Panel on Climate Change. WEAP works on the water balance whereas LEAP is applied to the energy sector. For this study, the interaction between the water and energy is evaluated considering the impacts of climate on the partially glacierized watersheds which feed upstream flow into the hydropower plants. The interpretation of the results by comparing the simulation of electricity generation with the projected energy demand, and climate change impacts on watershed surface runoff generation, indicates a possibility that in average, electricity demand surpassed energy generation by 2013, implying the necessity to import energy from other systems belonging to the SIN, or to improve the capacity of the plants or implement new power plants.
|Thursday, September 17th|
Geraldine Abrami, Inrae, UMR GEAU
10:20 AM - 10:40 AM
The CoOPLAaGE approach is an integrated set of tools to support the needs of participatory decision-making for natural resource management, particularly water management. These tools cover all stages of a participatory decision-making process, from the preparation of the approach to the implementation of the decision, including monitoring and evaluation. What characterize this approach is that : a. it is centred on the paradigm of Participatory Modelling (PM) as an emancipatory process through its functions of revealing, structuring, sharing and operationalizing stakeholder representations. b. it combines several small PM tools that target different elements : the socio-environmental system (WAG), monitoring and evaluation (ENCORE), action strategies (COOPLAN), distributive justice (JustA-Grid) or the decision-making process itself (PrePAR) c. these tools combine methodological and low tech material elements (everything can be done without a computer) and may be used independently or in an integrated approach d. it is based on a unified modelling framework (meta-model and process). The objective of this communication is to demonstrate how the CoOPLAage approach in general, and its unified modelling framework in particular, may provide answers to some common challenges of PM (and raise other ones!). By providing low tech tools and methodological support (training material and online associated courses), it ambitions to be transposed without additional intervention and with reduced specific skills. The approach and its associated modelling framework are currently under consolidation and computerization. The idea is to going as far as accompanying the steering of the participation by its organizers, and to facilitate the action of the participants. It will value, transfer and “autonomize” as an online service, a large set of (non-digital) know-how, methods, tools, pre-validated through years of intervention-research on participation engineering.
Evelina Trutnevyte, University of Geneva, Switzerland
2:20 PM - 2:40 PM
Bioenergy can make an important contribution to the transition towards renewable electricity and heat generation in Switzerland and elsewhere. Spatially explicit estimates of theoretical and sustainable bioenergy potentials are typically quantified in order to inform decisions. However, these estimates provide only partial insights on which regions shall be prioritized for effectively harvesting bioenergy. Using the spatially-explicit data on potentials of ten types of bioenergy in Switzerland (N= 2274 municipalities), we conduct three subsequent analyses. First, a spatial hotspot analysis is applied to identify groups of neighboring Swiss municipalities with high or low overall bioenergy potentials (so-called hotspots and cold spots, respectively). Second, using k-means clustering, five clusters of municipalities are identified in terms of having a similar structure of bioenergy potentials, namely clusters of high shares of forest wood, high shares of manure, high shares of mixed agricultural bioenergy, high shares of anthropogenic bioenergy (wastes), and lower-than-average bioenergy regions. Third, socio-economic characteristics of these bioenergy hotspots and these clusters of municipalities are analyzed in order to shed light on patterns between bioenergy potentials and socio-economic characteristics that can help initiate the bioenergy uptake. The results serve as a basis for municipal, inter-municipal and national energy planning. Furthermore, location of municipalities with promising “bioenergy portfolios” may be identified to prepare further case study analysis.
Karel Keesman, wageningen university
2:40 PM - 3:00 PM
Electricity can be generated by renewable resources, such and wind and solar radiation, but also from biomass. To avoid competition with food and feed, waste biomass can be used. An additional advantage of waste biomass is that it contributes both to the circular and biobased economy, in which biomass is converted to food/feed, biomaterials, biochemicals or bioenergy. Thus, the waste biomass used to generate electricity can also be used to make chemicals, materials or fuels. Amsterdam, the capital city of the Netherlands, has the ambition to become a leader in the circular economy and it has also set targets related to the reuse and recycling of waste. According to previous research, using data from Amsterdam (i.e. waste streams, energy demand, potential wind and solar energy production based on local, hourly weather data from 1994-2014) and a gasification-based energy system model with demand and supply constraints, the electricity demand of Amsterdam households can be met in the next decades. Another study determined the most profitable, in terms of net present value (NPV), combination of chemicals and materials that could be produced from this waste biomass stream. In this research, these studies are combined to determine the most profitable combination of electricity, materials, chemicals and fuels from waste biomass in Amsterdam. In all three scenarios (worst, base and best case), nearly the full capacity of electricity from wind was used and about 20% of the available area was covered with solar panels. Furthermore, it was projected that wood and organic municipal solid waste are gasified from 2020 to 2029 and are processed in biorefineries from 2031 to 2050, while grass is refined from 2020 to 2050, although no grass is refined in 2030 in the worst and base case scenarios. Results from a sensitivity analysis confirmed the robustness of the model.
Anett Großmann, GWS mbH, Germany
3:00 PM - 3:20 PM
This paper reports on the project “Policy advice for climate resilient economic development (CRED)” on behalf of GIZ (German Corporation for International Cooperation) which aims at (i) improving capacities on building economic models in three pilot countries namely Georgia, Kazakhstan and Vietnam with a focus on climate change, (ii) integrating the results of improved models in economic development strategies and policies as well as adaptation policies and (iii) to strengthen international exchange on these issues between e.g. governments and researchers. In the partner countries, a few environmental models exist but these are not linked to economic models and vice versa. Furthermore, many of these models do not sufficiently reveal their structure (“black box”) and thus can hardly be maintained or extended. The major challenge is to provide a state-of-the-art, science-based solution suitable for policy analysis which at the same time is sustainable so that local experts and researchers can cope with maintaining and enhancing the models independently with limited resources. In the project, an easy to learn yet powerful framework based on Visual Basic for Applications in Microsoft Excel is applied and trained in intensive courses. The framework allows for creating a macro-econometric Input-Output model covering economy, energy and environment (so called E3 models) and provides mechanisms for quickly calculating complex climate change and adaptation scenarios which can be developed also by non-model builders and stakeholders. Model builders must get acquainted to only one programming language to populate and enhance the provided model template and can reuse their Excel knowledge. The full data set, framework and model code as well as the scenarios are stored in just one Excel workbook allowing for easy distribution and evaluation.
Zhenxing Zhang, University of Illinois
3:20 PM - 3:40 PM
Water availability to supply cooling water demand has gained increasing attention as thermoelectric power plants need a large amount of cooling water. Thermoelectric power generation is the largest water user in the state of Illinois, USA. Previous studies often examined water-energy nexus risk by using the long-term average cooling water consumption intensity at an annual scale. However, both water availability and water demand by power generation is highly seasonal with peak demand and low supply coincidently occur in the same time of year in Illinois and many other places. The impacts of the water consumption intensity and streamflow seasonality on electricity generation are less well understood. Using the Integrated Environmental Control Model (IECM), we examined the seasonal risk of water-electricity nexus with three indicators, i.e. reliability, maximum time to recovery, and total power generation loss. The IECM can simulate the water consumption intensity over periods in response to daily ambient climate conditions. Furthermore, a water-electricity nexus model is developed to facilitate electricity generation decisions and environmental policy designs involving cooling water consumption and temperature controls. This nexus model consists of three modules, a physically based hydrologic module, an optimization module, and a thermoelectricity generation module. The three modules are integrated at the daily time step. The model is used to quantify trade-offs between environmental impacts and potential electricity supplies at the power plant and watershed levels. The results showed that the risk of the water-electricity nexus is highly seasonal and is greatly impacted by the seasonal variability of streamflow and the nexus model is applicable for a watershed-wide, coordinated water-energy policy design under different combinations of environmental regulations and economic penalties during a drought event.
John Little, Virginia Tech, United States, USA
3:40 PM - 4:00 PM
Rising human populations have created stress on the natural supply of water resources while corresponding economic activities have contributed to deterioration in water quality. Therefore, it is vital to identify pathways for minimizing water use and contamination while also trying to support economic development in order to achieve sustainability goals. To capture the interactions between hydrologic and economic systems necessary for modelling water use and contamination at a sufficient level of spatial detail, we have designed a framework that couples an economic model with a watershed model using a software called URUNME, which was recently developed to support integrated modelling and scenario analysis. To represent the economic system, the Rectangular Choice-of-Technology (RCOT) model is used because it represents both the physical and monetary aspects of economic activities and, unlike the traditional input-output model or partial and general equilibrium models, it is capable of considering choices among operational technologies in addition to the amount and location of production. RCOT also clearly represents the physical availability of water as well as its corresponding costs and price. Thus, there is a direct interdependence between availability of water and its subsequent quantity and cost for economic activities, which can change the choice selection among specific technologies available to different economic sectors and ultimately affect prices of goods. For the first implementation of this modelling framework, the RCOT model is paired with a hydrological model, Hydrological Simulation Program-Fortran (HSPF), which is calibrated to represent a watershed in northern Virginia. The database for the economic model uses county-level input-output data representative of the region in 2016. Linking the RCOT and HSPF models allows scenarios to be analysed to evaluate how changes in economic activities will cause changes in the water use and contamination in the watershed and vice versa.
Leila Niamir, MCC, IIASA
4:00 PM - 4:20 PM
Defining feasible and cost-effective low-emission pathways are crucial in the transition to sustainable societies. In this context, scenario-based model projections play an important role in evaluating different mitigation options. Current macroeconomic models are widely used to develop climate change mitigation scenarios by finding cost-optimal solutions for total societal costs. Yet, decision-making tools to assess the impact of individual behavioral and lifestyle changes on energy consumption and carbon emissions are scarce. This is surprising, given the importance of diversity/heterogeneity in personal and social factors that influence decisions beyond purely economic considerations. The macroeconomic impacts of individual energy behavioral changes on carbon emissions are explored by using agent-based modelling techniques. We further extend the framework to include the impact of air pollutants from fossil fuel-fired electricity generating units (EGUs) and residential combustion on public health. Air pollution-related public health benefits of these strategies can be appreciable, with thousands of lives saved per year and an array of morbidity benefits from CO2 control strategies that include residential energy efficiency. In this (ongoing) research, we present a novel integrated modular framework to capture climate-health benefits of residential energy behavioural change, considering EGUs and residential combustion. This framework consists of several analysis components and two main models: a bottom-up energy behavioral agent-based model (BENCH model); and an air pollution and climate integrated assessment model (GAINS model). These two models are linked systematically. The BENCH model introduces set of end-user behavioral and social scenarios. As a result, the aggregated changes in residential energy updates GAINS residential energy demand, where ambient air pollution and health impact are determined at the macro scale. This framework supports policy-makers’ decision on climate mitigation options by launching bottom-up (behavioral and social) end-user policies into top-down (monetary incentives) climate-energy-economy macro policies.
Evelina Trutnevyte, University of Geneva, Switzerland
4:20 PM - 4:40 PM
After the Fukushima accident, Switzerland has decided to fundamentally transform its electricity sector to phase out nuclear power and rapidly increase renewable generation. So far, the growth of decentralized renewable generation has been very spatially uneven: some regions became hotspots with a high density of new renewable plants and others lagged behind. Using past statistics and prospective spatial modeling to 2035, we investigated the causes and implications of these emerging regional disparities in terms of electricity generation costs, investment needs, and new renewable capacity requirements. In particular, we quantified the trade-offs between cost-efficient (least-cost) and regionally equitable allocation of new renewable generation. A significant trade-off exists in Switzerland by 2035: 50% increase in a regional equity when allocating renewable generation so that various Swiss regions benefit leads to 18% higher total electricity generation costs. Least-cost allocation implies concentrating renewable generation and associated investments to few most productive locations only. The current diffusion of renewable generation deviates both from the least-cost as well as the highest-equity paths. In our analysis, solar PV emerges as the key technology for increasing regional equity at reasonable generation costs. We conclude with policy implications on managing this costs-equity trade-off.