Intelligent cooperation

By Valeria Javalera Rincón, IIASA CONACYT Postdoctoral Fellow in the Ecosystems Services and Management and Advanced Systems Analysis programs.

What is more important: water, energy, or food?

If you work in the water, energy or agriculture sector we can guess what your answer might be! But if you are a policy or decision maker trying to balance all three, then you know that it is getting more and more difficult to meet the growing demand for water, energy, and food with the natural resources available. The need for this balance was confirmed by the 17 Sustainable Development Goals, agreed by 193 countries, and the Paris climate agreement. But how to achieve it? Intelligent cooperation is the key.

The thing is that water, energy, and food are all related in such a way that are reliant on each other for production or distribution. This is the so-called Water-Energy-Food nexus. In many cases, you need water to produce energy, you need energy to pump water, and you need water and energy to produce, distribute, and conserve food.

Many scientists have tried to relate or to link models for water, agriculture, land, and energy to study these synergic relationships. In general, so far, there are two ways that this has been solved: One is integrating models with “hard linkages” like this:

© Daniel Javalera

In the picture there are six models (let’s say water, land use, hydro energy, gas, coal, food production models) that are then integrated into just one. The resulting integrated model then preserves the relationships but is complex, and in order to make it work with our current computer power you often have to sacrifice details.

Another way is to link them is using so-called “soft linkages” where the output of one model is the input of the next one, like this:

© Daniel Javalera

In the picture, each person is a model and the input is the amount of water left. These models all refer to a common resource (the water) and are connected using “soft linkages.” These linkages are based on sequential interaction, so there is no feedback, and no real synergy.

The intelligent linker agent

But what if we could have the relations and synergies between the models? It would mean much more accurate findings and helpful policy advice. Well, now we can. The secret is to link through an intelligent linker agent.

I developed a methodology in which an intelligent linker agent is used as a “negotiator” between models that can communicate with each other. This negotiator applies a machine-learning algorithm that gives it the capability to learn from the interactions with the models. Through these interactions, the intelligent linker can advise on globally optimal actions.

The knowledge of the intelligent linker is based on past experience and also on hypothetical future actions that are evaluated in a training process.  This methodology has been used to link drinking water networks, such as Barcelona’s drinking water network.

When I came to IIASA, I was asked to apply this approach to optimize trading between cities in the Shanxi region of China. I used a set of previously development models which aimed to distribute water and land available for each city in order to produce food (eight types of crops) and coal for energy. The intelligent linker agent optimizes trading between cities in order to satisfy demand at the lowest cost for each city.

The purpose of this exercise was to compare the solutions with those from “hard linkages” – like those in the first picture. We found that the intelligent linker is flexible enough to find the optimal solution to questions such as: How much of each of these products should each city export/import to satisfy global demand at a global lower economic and ecological cost? What actions are optimal when the total production is insufficient to meet the total demand? Under what conditions is it preferable to stop imports/exports when production is insufficient to supply the demand of each city?

The answers to these questions can be calculated by the interaction with the models of each city just by the interfacing with the intelligent linker agent, this means that no major changes in the models of each city were needed. We also found that, under the same conditions, the solutions using the intelligent linker agent were in agreement with those found when hard linking was used.

My next challenge is to build a prototype of a “distributed computer platform,” which will allow us to link models on different computers in different parts of the world—so that we in Austria could link to a model built by colleagues in Brazil, for example.  I also want to link models of different sectors and regions of the globe, in order to prove that intelligent cooperation is the key to improving global welfare.

References

Xu X, Gao J, Cao G-YErmoliev YErmolieva TKryazhimskiy AV, & Rovenskaya E (2015). Modeling water-energy-food nexus for planning energy and agriculture developments: case study of coal mining industry in Shanxi province, China. IIASA Interim Report. IIASA, Laxenburg, Austria: IR-15-020

Javalera V, Morcego B, & Puig V, Negotiation and Learning in distributed MPC of Large Scale Systems, Proceedings of the 2010 American Control Conference, Baltimore, MD, 2010, pp. 3168-3173. doi: 10.1109/ACC.2010.5530986

Valeria J, Morcego B, & Puig V, Distributed MPC for Large Scale Systems using Agent-based Reinforcement Learning, In IFAC Proceedings Volumes, Volume 43, Issue 8, 2010, Pages 597-602, ISSN 1474-6670, ISBN 9783902661913, https://doi.org/10.3182/20100712-3-FR-2020.00097.

Morcego B, Javalera V, Puig V, & Vito R (2014). Distributed MPC Using Reinforcement Learning Based Negotiation: Application to Large Scale Systems. In: Maestre J., Negenborn R. (eds) Distributed Model Predictive Control Made Easy. Intelligent Systems, Control and automation: Science and Engineering, vol 69. Springer, Dordrecht

Javalera Rincón V, Distributed large scale systems: a multi-agent RL-MPC architecture, Universitat Politècnica de Catalunya. Institut d’Organització i Control de Sistemes Industrials,Doctoral thesis. 2016. http://upcommons.upc.edu/handle/2117/96332

Note: This article gives the views of the author and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Not a heron: the Eurasian Economic Union should ‘stand on two legs’

By Evgeny Vinokurov, Director of the Centre for Integration Studies at the Eurasian Development Bank, member of the IIASA-led project, Challenges and Opportunities of Economic Integration within a Wider European and Eurasian Space

An Italian nursery riddle goes: “Why does the heron stand on one leg? Because if it takes away the second leg, it will fall down!” An ornithologist will tell you that herons have incredibly strong legs. The EAEU, consisting of Armenia, Belarus, Kazakhstan, Kyrgyzstan, and Russia is not a heron – it does need to stand firmly on two legs. In this case, one leg is the European Union, and the other leg is the People’s Republic of China. An economist will tell you that the strength of “economic legs” underpinning the countries which make up the Eurasian Economic Union (EAEU) can be described, at best, as fair to middling: the heavy reliance on oil and gas is not particularly wholesome. That is why Russia and its EAEU partners need to establish close economic ties with both the EU and China.

© Galushko Sergey | Shutterstock

Both partners are critically important for the EAEU. The EU remains its largest trade partner: in 2016 it accounted for 50% of total exports from, and 41% of total imports to the Eurasian Union. EAEU member states are interested in expanding the inflow of European investment capital, transfer of EU technologies, and stable EU demand for energy. The EAEU, in turn, is the third largest EU trade partner (after the US and China); accordingly, the EU may be interested in liberalization of trade with the EAEU (establishment of a free trade agreement), reduction of non-tariff barriers in EAEU member states (with a view to increase EU exports), and stability of EAEU power supplies.

At the same time, the EAEU’s “turn to the East” is slowly gaining momentum: Asia-Pacific Economic Cooperation (APEC) countries,first and foremost, China and Association of Southeast Asian Nations  (ASEAN) countries, are beginning to overtake the EU. By the end of 2016, the Eurasian Union had imported 1.5% more goods from APEC countries (42.3% of total imports, mostly from China, Korea, and ASEAN countries) than it did from EU countries. It is also important for EU investors to understand that they are exposed to an ever-increasing risk of losing EAEU markets due to the inflow of capital from the leading Asian economies.

These matters have been subjected to rigorous applied analysis in Challenges and Opportunities of Economic Integration within a Wider European and Eurasian Space, a project initiated by IIASA in 2014. It advanced an independent dialogue platform to facilitate interaction between representatives of supranational bodies, expert and business communities of the two unions. The project is designed to help its European and Eurasian participants find common ground with respect to a possible inter-union trade and economic agreement.

According to project publications , it is advisable to reach a comprehensive agreement covering a much broader range of partnership domains than that associated with a standard free trade area. According to the latest calculations by European and Russian experts, an EU-EAEU free trade agreement would produce a positive impact. However, experts from the Information and Forschung (IFO) institute in Munich point out that EAEU agriculture and automotive industry may suffer heavy losses. This demonstrates that it is necessary to work out a quite structurally complex solution offering asymmetric advantages to the two sides.

Relations with China display completely different patterns. Two following “tracks” are especially important.

The first relates to the ongoing negotiations on a non-preferential agreement on trade and economic cooperation between the EAEU and China, envisaging reciprocal minimization of barriers in customs regulations and the financial sector, and intensification of investment cooperation. Talks have already been underway for one year, and are expected to continue for another year or two.

The second track deals with realization of the One Belt One Road  initiative. It involves implementation of large-scale joint infrastructure projects, primarily in transportation.  EAEU’s participation in the One Belt One Road initiative is very promising for its member states, especially for Russia and Kazakhstan, which need to remove infrastructural limitations inhibiting railroad carriage of containerized cargoes.  The EAEU continues to face the issue of insufficient investment capital allocation to container logistical hubs. Kazakhstan will also need to eliminate bottlenecks in its transportation and logistics infrastructure, primarily by building modern container terminals. These are but several of the numerous problems facing the EAEU.

We are looking at One Belt One Road in the broad Greater Eurasia context. Higher efficiency of Greater Eurasian land transportation corridors could enhance trade and generate numerous industrial opportunities. This is particularly relevant for landlocked countries and regions (all Central Asian countries, Russian Urals and Western Siberia).

Russia and its EAEU partners need to establish close economic cooperation ties with both the European Union and China. The EAEU will have to learn to balance between those two poles, making ample use of economic vistas presented by the tripartite cooperation setup, and “capitalize on contradictions.” If the EAEU manages to reach this overarching goal, its foreign economic policy would be successful.

This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

The roads to 2050

By Owen Gaffney, Stockholm Resilience Center (excerpted from a post on Rethink.earth)

What will the world be like in 2050?

Of course, it is difficult to make predictions, especially about the future, as the Danish proverb goes.

Part of the difficulty is that we – individuals and the institutions that allow us to act collectively and in the long term – routinely assume the future looks very much like the past. Just as routinely, though, this assumption is flipped on its head. Think of the global financial crisis, the Arab Spring, Brexit, or the recent US election.

But what if we already know what we want the world to look like in 2050. How do we get there?

By Andrew Hitchcock - Flickr, CC BY 2.0, https://commons.wikimedia.org/w/index.php?curid=1708457

Dusk on Chang Jiang (Yangtze) Credit: Andrew Hitchcock | Flickr, CC BY 2.0,

I was reminded of the Danish proverb as I arrived at the International Institute for Applied Systems Analysis (IIASA) outside Vienna earlier this month for a three-day meeting of The World in 2050 (TWI2050) initiative. This was the third such scientific meeting hosted here at the home of some of the leading economic, demographic and energy modellers.

TWI2050 is arguably the most ambitious research being undertaken in the world today. At its heart is an ambition to map out the pathways for a sustainable planet. As with the previous meetings, it attracted about 130 complex-systems thinkers and computer-modelling experts.

Unlike other international modelling initiatives, TWI2050 was not created to explore a range of possible utopian to dystopian scenarios focusing on energy prices or climate change. The baseline assumption is a single scenario: successful completion of the Sustainable Development Goals (SDGs), agreed by all nations in 2015, and arriving in 2050 with a global economy operating within planetary boundaries – the limits of natural systems that keep Earth in a relatively stable state, relating to climate, biodiversity, deforestation, and fertilizer use, among others.

#winwin
The 17 SDGs and their 169 targets are extremely ambitious. Buried in the detail are many trade-offs but also potential win-wins. Meeting the climate goal means reducing greenhouse-gas emissions to zero, and this could affect the energy, biodiversity, or consumption goals either positively or negatively. The goals and their inherent trade-offs are already catalyzing research and the results show how challenging this will be.

This month, scientists publishing in the journal Nature explored Australia’s land-use trade-offs to reach the goals. The team, who were not at the TWI2050 meeting, used a massive computer simulation called Land Use and Trade Offs (LUTO) to see how factors such as climate policies or crop prices could shape Australia’s landscape by 2050. Exploring 648 scenarios, researchers Brett Bryan and Lei Gao found just 1% of scenarios achieved five goals simultaneously. However, some goals seemed to go better together than others. Achieving targets related to food, water, and biofuel production was possible in 6.5% of scenarios, for example. The authors, whose work contributes to Future Earth’s Global Land Programme, conclude that national policymakers need more of this type of analysis to elucidate trade-offs and avoid conflicting policies. Moreover, they argued for more scientific coordination internationally for a global perspective on implementing the SDGs.

Other research groups have also begun exploring the world in 2050. Recently Karl Heinz Erb from the Institute of Social Ecology, Vienna, who attended the TWI2050 workshop, and colleagues explored 500 scenarios to assess options for feeding 9 billion people in 2050 without further deforestation .

Their work, which also supports the Global Land Programme, concluded that it was possible, but would likely mean low meat, vegetarian, or vegan diets globally. Meanwhile, Marco Springmann from the Oxford Martin Programme on the Future of Food, also attending, and colleagues showed that by 2050 a global vegetarian diet would reduce diet-related global mortality by 6-10% and food-related greenhouse gas emissions by 29-70% – contributing to several goals. This type of research is essential to understand potential win-wins but these examples do not provide the pathways to arrive at these scenarios.

So, are computer models powerful enough to capture essential elements of incremental and disruptive change across complex issues relating to poverty, equality, education, technology, policy, energy, food, water, and climate? Read more on the Rethink.earth website

This article is excerpted from an article on the Rethink.earth website. It gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

*The Stockholm Resilience Centre is one of the founding partners of The World in 2050 alongside the Sustainable Development Solutions Network and IIASA. Contributing organisations include the European Commission, Future Earth, Netherlands Environmental Assessment Agency, Potsdam Institute for Climate Impact Research, Future Earth. Check out the website for details.

References

1. Nilsson M, Griggs D, Visbeck M (2016). Policy: Map the interactions between Sustainable Development Goals. Nature 534:7607 PDF for download
2. Nilsson M, Griggs D, Visbeck M, Ringler C (2016). A draft framework for understanding SDG interactions. ICSU – International Council for Science. PDF for download
3. Stafford Smith M, et. al. (2016). Integration: the key to implementing the Sustainable Development Goals. Sustainability Science DOI:10.1007/s11625-016-0383-3
4. Gao L, Bryan BA (2017). Finding pathways to national-scale land-sector sustainability. Nature 544:217–222 DOI:10.1038/nature21694
5. Bryan BA et al. (2016). Land-use and sustainability under intersecting global change and domestic policy scenarios: Trajectories for Australia to 2050. Global Environmental Change 38:130–152 DOI:10.1016/j.gloenvcha.2016.03.002
6. Erb K-H, Lauk C, Kastner T, Mayer A, Theurl MC, Haberl H (2016). Exploring the biophysical option space for feeding the world without deforestation. Nature Communications 7 DOI:10.1038/ncomms11382
7. Springmann M, Godfray HCJ, Rayner M, Scarborough P (2016). Analysis and valuation of the health and climate change cobenefits of dietary change. PNAS 113:15(4146–4151)DOI:10.1073/pnas.1523119113

How clean is green gas?

By Piera Patrizio, IIASA Ecosystems Services and Management Program

Biogas–renewable fuel that can be produced from a variety of natural materials including manure, food waste, plant matter, and other organic matter–has the potential to solve a number of environmental challenges simultaneously: It can reduce the emissions of greenhouse gases  such as methane (for example, from manure storage) and is the only mature type of renewable energy that can be directly used in electric power generation, heat generation, and transport sectors, and it leads to reduced impacts of pollution from waste disposal.

Biogas can be produced from crops like maize as well as waste and ohter organic materials © Giuliano Del Moretto | Shutterstock

However, biogas is not without impacts of its own. The environmental benefit of using agricultural biogas in particular may be smaller than previously thought, because of the farming activities required for the production of suitable biogas feedstock (such as maize, wheat and triticale), which in turn generates local airborne pollution. Such factors are not adequately reflected in current energy measures.

In other words, existing policy instruments that have been adopted so far in Europe do not reflect the environmental impact associated with the production of certain biofuels because they do not account for other relevant environmental burdens generated along the supply chain.

This is especially the case for biogas, whose production contributes to several environmental burdens such as land use, traffic, and local emissions from the intensive use of fertilizers.

To overcome this issue, my colleagues and I have proposed the adoption of a monetization procedure through which the so-called external costs are incorporated in energy wholesale prices. This method, allows to allocate a cost to the environmental damage associated with emissions of a wide range of pollutants, which can be consequently incorporated in any economic optimization model.

 

Biogas production plant, Italy © Roberto Lo Savio | Shutterstock

In a new study, which I conducted with Sylvain Leduc and Florian Kraxner, we took a look at the biogas situation in my home country, Italy. We incorporated the total internal and external costs of different biogas utilization pathways in the BeWhere model—a model used for optimizing renewable energy systems–and compared with the performance of the current Italian energy mix.

We found out that, although each type of biogas leads to reduced CO2 emissions compared to fossil fuels, such environmental benefits are sharply reduced when we take other pollutant emissions into account. .

In particular, farming activities generate high non-carbon emissions such as nitrogen oxides (NOx), sulfur dioxide, and particles. Most of this pollution comes from chemical fertilizers and diesel combustion in farming activities–and these emissions corresponding to almost 6% of the energy content of the raw biogas produced.

The second cause of external costs is transportation of the biomass, which mainly produces local emissions of NOx.  Local concerns about this issue, are a main source of opposition to new plants, and based on our study, these concerns appear reasonable.

Our results suggest that carbon emission mitigation alone is not always a satisfactory measure to evaluate the sustainability of biogas technologies in order to define energy policies. Other environmental burdens need to be considered when we discuss the environmental sustainability of energy production processes.

Reference

Patrizio PLeduc S, Chinese D, & Kraxner F (2017). Internalizing the external costs of biogas supply chains in the Italian energy sector. Energy 125: 85–96

This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

How the Middle East and North Africa see energy: Conflicts and compromise

By Nadejda Komendantova, IIASA Risk and Resilience Program

A transition to new energy sources—whether renewable, nuclear, or shale—does not just depend on technical availability and economic feasibility. In order for new projects to succeed, human factors, such as public and social acceptance, and willingness to use technology or to pay for it, are essential but often overlooked. It is important to understand these factors, because differences in views and perceptions of technology risks, benefits, and costs might lead to conflicts that could threaten the success of new projects.

Conflicts often appear between two or more parties with incompatible goals, different interests, or different risk perceptions, which can develop into either cooperation or conflict. For example, public opposition can lead to cancellation or delay of a planned project, and differences in views and risk perceptions can result in conflicts among different stakeholder groups. At the same time, if policymakers take into account this heterogeneity of views, the knowledge on the ground can lead to a better implementation of energy projects with more benefits for society and a smaller impact on the environment and hosting communities.

Row of high voltage pylons in the desert of Wadi Rum, Jordan, Middle East ©Pierre Brumder | Adobe Stock Photo

Row of high voltage pylons in the desert of Wadi Rum, Jordan ©Pierre Brumder | Adobe Stock Photo

An energy transition is currently taking place in the Middle East and North Africa. The region faces a number of challenges such as rising energy demand, unstable energy imports, increasing pressure on environmental resources, expectations of socioeconomic development, and political transformation. Morocco, Jordan, Tunisia, and other countries in the region are discussing new electricity infrastructure. Although large-scale deployment of renewable energy sources receives political support in this discussion, fossil fuels, and new emerging technologies such as shale oil and nuclear power are two prominent alternatives in the countries’ national development plans.

For this energy transition to succeed, policymakers in the region must adopt an adaptive and inclusive governance approach, which addresses possible risks, benefits, challenges, and socio-ecological shifts. In order to find compromise solutions, this approach should be based on an understanding of the positions of each stakeholder group involved in the project planning and affected by its implementation.

To understand these potential conflicts, a group of IIASA Risk and Resilience Program researchers, including myself, Jenan Irshaid, Love Ekenberg and Joanne Bayer, are conducting a series of six stakeholder workshops in Jordan. Each of the workshops targets different stakeholder groups such as local communities, NGOs, financial institutions, project developers, private companies, academia, young leaders, and national policymakers, including ministries of public works, of water and irrigation, energy and mineral resources, and municipal affairs. The goal of these workshops is to understand how different groups of stakeholders see risks and benefits of different electricity generation technologies, including renewables, fossil fuels, and nuclear, as well as views and visions of different stakeholders of Jordan in 2040 in terms of the social, environmental, and economic situation.

In our research we go beyond the existing discussion on social acceptance as a proxy of a Not-in-My-Back-Yard (NIMBY) attitude. NIMBY is often a misleading concept to understand local objections, because it is frequently understood as some kind of “social gap” between the need of policy intervention, settled at the national level, and the hostility towards its deployment at the local level. The NIMBY concept often includes skepticism of different stakeholder groups towards positions of the others. Also the term “acceptance” towards technology or infrastructure innovation often means a passive position towards something that cannot be changed. In contrary, willingness to use technology or to participate financially means a more active position.

In recent research, we discuss the usefulness of a model that we call “decide-announce-defend” (DAD), and try to understand how integration of various views and risk perceptions can lead to enhanced legitimacy of decision-making processes and trust. To understand the trade-offs between benefits of national energy goals and conflict sensitivity, we evaluated each electricity generation technology that could be relevant for Jordan against a set of criteria, including domestic value chain integration, use of domestic resources, technology and knowledge transfer, global warming potential, electricity system costs, job creation processes, pressure on land and water resources as well as safety, air pollution and non-emission waste.

Participants in the workshop. ©Nadejda Komendantova

Participants in the workshop. ©Nadejda Komendantova | IIASA

The workshops are organized in collaboration with the University of Jordan as part of the Middle East North African Sustainable Electricity Trajectories (MENA Select) project, which is supported by the German Federal Ministry for Economic Cooperation and Development (BMZ) and involves following partners: Bonn International Center for Conversion (BICC), University of Flensburg, Germanwatch, Wuppertal Institute and IIASA as well as a number of partners in the MENA region, such as MENARES, University of Jordan, and DUN.

Further information
Ekenberg, L., Hansson, K., Danielson, M., Cars, G., (2017) Deliberation, Representation and Equity: Research Approaches, Tools and Algorithms for Participatory Processes, Open Book Publishers, 2017.

Komendantova, N., and Battaglini, A., (2016). Beyond Decide-Announce-Defend (DAD) and Not-in-My-Backyard (NIMBY) models? Addressing the social and public acceptance of electric transmission lines in Germany. Energy Research and Social Science, 22. Pp.224-231.

Linnerooth-Bayer, J., Scolobig, A., Ferlisi, S., Cascini, L. and Thompson, M. (2016) Expert engagement in participatory processes: translating stakeholder discourses into policy options. Natural Hazards, 81 (S1). pp. 69-88. http://pure.iiasa.ac.at/view/iiasa/182.html

Yazdanpanah, M., Komendantova, N., Linnerooth-Bayer, J., Shirazi, Z., (2015). “Green or In Between? Examining Young Adults’ Perceptions of Renewable Energy in Iran”. Energy Research and Social Science 8 (2015), 78-85

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.