Tran Thi Vo-Quyen, IIASA guest research scholar from the Vietnam Academy of Science and Technology (VAST), talks to Professor Dr. Ninh Khac Ban, Director General of the International Cooperation Department at VAST and IIASA council member for Vietnam, about achievements and challenges that Vietnam has faced in the last 5 years, and how IIASA research will help Vietnam and VAST in the future.
Professor Dr. Ninh Khac Ban, Director General of the International Cooperation Department at VAST and IIASA council member for Vietnam
What have been the highlights of Vietnam-IIASA membership until now?
In 2017, IIASA and VAST researchers started working on a joint project to support air pollution management in the Hanoi region which ultimately led to the successful development of the IIASA Greenhouse Gas – Air Pollution Interactions and Synergies (GAINS) model for the Hanoi region. The success of the project will contribute to a system for forecasting the changing trend of air pollution and will help local policy makers develop cost effective policy and management plans for improving air quality, in particular, in Hanoi and more widely in Vietnam.
IIASA capacity building programs have also been successful for Vietnam, with a participant of the 2017 Young Scientists Summer Program (YSSP) becoming a key coordinator of the GAINS project. VAST has also benefited from two members of its International Cooperation Department visiting the IIASA External Relations Department for a period of 3 months in 2018 and 2019, to learn about how IIASA deals with its National Member Organizations (NMOs) and to assist IIASA in developing its activities with Vietnam.
What do you think will be the key scientific challenges to face Vietnam in the next few years? And how do you envision IIASA helping Vietnam to tackle these?
In the global context Vietnam is facing many challenges relating to climate change, energy issues and environmental pollution, which will continue in the coming years. IIASA can help key members of Vietnam’s scientific community to build specific scenarios, access in-depth knowledge and obtain global data that will help them advise Vietnamese government officials on how best they can overcome the negative impact of these issues.
As Director General of the International Cooperation Department, can you explain your role in VAST and as representative to IIASA in a little more detail?
In leading the International Cooperation Department at VAST, I coordinate all collaborative science and technology activities between VAST and more than 50 international partner institutions that collaborate with VAST.
As the IIASA council representative for Vietnam, I participate in the biannual meeting for the IIASA council, I was also a member of the recent task force developed to implement the recommendations of a recent independent review of the institute. I was involved in consulting on the future strategies, organizational structure, NMO value proposition and need to improve the management system of IIASA.
In Vietnam, I advised on the establishment of a Vietnam network for joining IIASA and I implement IIASA-Vietnam activities, coordinating with other IIASA NMOs to ensure Vietnam is well represented in their countries.
You mentioned the development of the Vietnam-IIASA GAINS Model. Can you explain why this was so important to Vietnam and how it is helping to improve air quality and shape Vietnamese policy around air pollution?
Air pollution levels in Vietnam in the last years has had an adverse effect on public health and has caused significant environmental degradation, including greenhouse gas (GHG) emissions, undermining the potential for sustainable socioeconomic development of the country and impacting the poor. It was important for Vietnam to use IIASA researchers’ expertise and models to help them improve the current situation, and to help Vietnam in developing the scientific infrastructure for a long-lasting science-policy interface for air quality management.
The project is helping Vietnamese researchers in a number of ways, including helping us to develop a multi-disciplinary research community in Vietnam on integrated air quality management, and in providing local decision makers with the capacity to develop cost-effective management plans for the Hanoi metropolitan area and surrounding regions and, in the longer-term, the whole of Vietnam.
About VAST and Ninh Khac Ban
VAST was established in 1975 by the Vietnamese government to carry out basic research in natural sciences and to provide objective grounds for science and technology management, for shaping policies, strategies and plans for socio-economic development in Vietnam. Ninh Khac Ban obtained his PhD in Biology from VAST’s Institute of Ecology and Biological Resources in 2001. He has managed several large research projects as a principal advisor, including several multinational joint research projects. His successful academic career has led to the publication of more than 34 international articles with a high ranking, and more than 60 national articles, and 2 registered patents. He has supervised 5 master’s and 9 PhD level students successfully to graduation and has contributed to pedagogical texts for postgraduate training in his field of expertise.
Notes: More information on IIASA and Vietnam collaborations. This article gives the views of the authors, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
By Pallav Purohit, researcher with the IIASA Air Quality and Greenhouse Gases Program
More than 300 million people in Hindu Kush Himalaya-countries still lack basic access to electricity. Pallav Purohit writes about recent research that looked into how the issue of energy poverty in the region can be addressed.
The Hindu Kush Himalayas is one of the largest mountain systems in the world, covering 4.2 million km2 across eight countries: Afghanistan, Bangladesh, Bhutan, China, India, Myanmar, Nepal, and Pakistan. The region is home to the world’s highest peaks, unique cultures, diverse flora and fauna, and a vast reserve of natural resources.
Ensuring access to affordable, reliable, sustainable, and modern energy for all – the UN’s Sustainable Development Goal (SDG) 7 – has however been especially elusive in this region, where energy poverty is shockingly high. About 80% of the population don’t have access to clean energy and depend on biomass – mostly fuelwood – for both cooking and heating. In fact, over 300 million people in Hindu Kush Himalaya-countries still lack basic access to electricity, while vast hydropower potentials remain largely untapped. Although a large percentage of these energy deprived populations live in rural mountain areas that fall far behind the national access rates, mountain-specific energy access data that reflects the realities of mountain energy poverty barely exists.
Source: Wester et al. (2019)
The big challenge in this regard is to simultaneously address the issues of energy poverty, energy security, and climate change while attaining multiple SDGs. The growing sectoral interdependencies in energy, climate, water, and food make it crucial for policymakers to understand cross-sectoral policy linkages and their effects at multiple scales. In our research, we critically examined the diverse aspects of the energy outlook of the Hindu Kush Himalayas, including demand-and-supply patterns; national policies, programmes, and institutions; emerging challenges and opportunities; and possible transformational pathways for sustainable energy.
Our recently published results show that the region can attain energy security by tapping into the full potential of hydropower and other renewables. Success, however, will critically depend on removing policy-, institutional-, financial-, and capacity barriers that now perpetuate energy poverty and vulnerability in mountain communities. Measures to enhance energy supply have had less than satisfactory results because of low prioritization and a failure to address the challenges of remoteness and fragility, while inadequate data and analyses are a major barrier to designing context specific interventions.
In the majority of Hindu Kush Himalaya-countries, existing national policy frameworks currently primarily focus on electrification for household lighting, with limited attention paid to energy for clean cooking and heating. A coherent mountain-specific policy framework therefore needs to be well integrated in national development strategies and translated into action. Quantitative targets and quality specifications of alternative energy options based on an explicit recognition of the full costs and benefits of each option, should be the basis for designing policies and prioritizing actions and investments. In this regard, a high-level, empowered, regional mechanism should be established to strengthen regional energy trade and cooperation, with a focus on prioritizing the use of locally available energy resources.
Some countries in the region have scaled up off-grid initiatives that are globally recognized as successful. We however found that the special challenges faced by mountain communities – especially in terms of economies of scale, inaccessibility, fragility, marginality, access to infrastructure and resources, poverty levels, and capability gaps – thwart the large-scale replication of several best practice innovative business models and off-grid renewable energy solutions that are making inroads into some Hindu Kush Himalayan countries.
This further highlights an urgent need to establish supportive policy, legal, and institutional frameworks as well as innovations in mountain-specific technology and financing. In addition, enhanced multi-stakeholder capacity building at all levels will be needed for the upscaling of successful energy programs in off-grid mountain areas.
Finally, it is important to note that sustainable energy transition is a shared responsibility. To accelerate progress and make it meaningful, all key stakeholders must work together towards a sustainable energy transition. The world needs to engage with the Hindu Kush Himalayas to define an ambitious new energy vision: one that involves building an inclusive green society and economy, with mountain communities enjoying modern, affordable, reliable, and sustainable energy to improve their lives and the environment.
 Dhakal S, Srivastava L, Sharma B, Palit D, Mainali B, Nepal R, Purohit P, Goswami A, et al. (2019). Meeting Future Energy Needs in the Hindu Kush Himalaya. In: The Hindu Kush Himalaya Assessment. pp. 167-207 Cham, Switzerland: Springer. ISBN 978-3-319-92287-4 [pure.iiasa.ac.at/15666]
By Matt Cooper, PhD student at the Department of Geographical Sciences, University of Maryland, and 2018 winner of the IIASA Peccei Award
I never pictured myself working in Europe. I have always been an eager traveler, and I spent many years living, working and doing fieldwork in Africa and Asia before starting my PhD. I was interested in topics like international development, environmental conservation, public health, and smallholder agriculture. These interests led me to my MA research in Mali, working for an NGO in Nairobi, and to helping found a National Park in the Philippines. But Europe seemed like a remote possibility. That was at least until fall 2017, when I was looking for opportunities to get abroad and gain some research experience for the following summer. I was worried that I wouldn’t find many opportunities, because my PhD research was different from what I had previously done. Rather than interviewing farmers or measuring trees in the field myself, I was running global models using data from satellites and other projects. Since most funding for PhD students is for fieldwork, I wasn’t sure what kind of opportunities I would find. However, luckily, I heard about an interesting opportunity called the Young Scientists Summer Program (YSSP) at IIASA, and I decided to apply.
Participating in the YSSP turned out to be a great experience, both personally and professionally. Vienna is a wonderful city to live in, and I quickly made friends with my fellow YSSPers. Every weekend was filled with trips to the Alps or to nearby countries, and IIASA offers all sorts of activities during the week, from cultural festivals to triathlons. I also received very helpful advice and research instruction from my supervisors at IIASA, who brought a wealth of experience to my research topic. It felt very much as if I had found my kind of people among the international PhD students and academics at IIASA. Freed from the distractions of teaching, I was also able to focus 100% on my research and I conducted the largest-ever analysis of drought and child malnutrition.
Now, I am very grateful to have another summer at IIASA coming up, thanks to the Peccei Award. I will again focus on the impact climate shocks like drought have on child health. however, I will build on last year’s research by looking at future scenarios of climate change and economic development. Will greater prosperity offset the impacts of severe droughts and flooding on children in developing countries? Or does climate change pose a hazard that will offset the global health gains of the past few decades? These are the questions that I hope to answer during the coming summer, where my research will benefit from many of the future scenarios already developed at IIASA.
I can’t think of a better research institute to conduct this kind of systemic, global research than IIASA, and I can’t picture a more enjoyable place to live for a summer than Vienna.
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.
Quantitative models are an important part of environmental and economic research and policymaking. For instance, IIASA models such as GLOBIOM and GAINS have long assisted the European Commission in impact assessment and policy analysis2; and the energy policies in the US have long been guided by a national energy systems model (NEMS)3.
Despite such successful modelling applications, model criticisms often make the headlines. Either in scientific literature or in popular media, some critiques highlight that models are used as if they are precise predictors and that they don’t deal with uncertainties adequately4,5,6, whereas others accuse models of not accurately replicating reality7. Still more criticize models for extrapolating historical data as if it is a good estimate of the future8, and for their limited scopes that omit relevant and important processes9,10.
Validation is the modeling step employed to deal with such criticism and to ensure that a model is credible. However, validation means different things in different modelling fields, to different practitioners and to different decision makers. Some consider validity as an accurate representation of reality, based either on the processes included in the model scope or on the match between the model output and empirical data. According to others, an accurate representation is impossible; therefore, a model’s validity depends on how useful it is to understand the complexity and to test different assumptions.
Given this variety of views, we conducted a text-mining analysis on a large body of academic literature to understand the prevalent views and approaches in the model validation practice. We then complemented this analysis with an online survey among modeling practitioners. The purpose of the survey was to investigate the practitioners’ perspectives, and how it depends on background factors.
According to our results, published recently in Eker et al. (2018)1, data and prediction are the most prevalent themes in the model validation literature in all main areas of sustainability science such as energy, hydrology and ecosystems. As Figure 1 below shows, the largest fraction of practitioners (41%) think that a match between the past data and model output is a strong indicator of a model’s predictive power (Question 3). Around one third of the respondents disagree that a model is valid if it replicates the past since multiple models can achieve this, while another one third agree (Question 4). A large majority (69%) disagrees with Question 5, that models cannot provide accurate projects, implying that they support using models for prediction purposes. Overall, there is no strong consensus among the practitioners about the role of historical data in model validation. Still, objections to relying on data-oriented validation have not been widely reflected in practice.
Figure 1: Survey responses to the key issues in model validation. Source: Eker et al. (2018)
According to most practitioners who participated in the survey, decision-makers find a model credible if it replicates the historical data (Question 6), and if the assumptions and uncertainties are communicated clearly (Question 8). Therefore, practitioners think that decision makers demand that models match historical data. They also acknowledge the calls for a clear communication of uncertainties and assumptions, which is increasingly considered as best-practice in modeling.
One intriguing finding is that the acknowledgement of uncertainties and assumptions depends on experience level. The practitioners with a very low experience level (0-2 years) or with very long experience (more than 10 years) tend to agree more with the importance of clarifying uncertainties and assumptions. Could it be because a longer engagement in modeling and a longer interaction with decision makers help to acknowledge the necessity of communicating uncertainties and assumptions? Would inexperienced modelers favor uncertainty communication due to their fresh training on the best-practice and their understanding of the methods to deal with uncertainty? Would the employment conditions of modelers play a role in this finding?
As a modeler by myself, I am surprised by the variety of views on validation and their differences from my prior view. With such findings and questions raised, I think this paper can provide model developers and users with reflections on and insights into their practice. It can also facilitate communication in the interface between modelling and decision-making, so that the two parties can elaborate on what makes their models valid and how it can contribute to decision-making.
Model validation is a heated topic that would inevitably stay discordant. Still, one consensus to reach is that a model is a representation of reality, not the reality itself, just like the disclaimer of René Magritte that his perfectly curved and brightly polished pipe is not a pipe.
Eker S, Rovenskaya E, Obersteiner M, Langan S. Practice and perspectives in the validation of resource management models. Nature Communications 2018, 9(1): 5359. DOI: 10.1038/s41467-018-07811-9 [pure.iiasa.ac.at/id/eprint/15646/]
Nuccitelli D. Climate scientists just debunked deniers’ favorite argument. The Guardian. 2017. https://www.theguardian.com/environment/climate-consensus-97-per-cent/2017/jun/28/climate-scientists-just-debunked-deniers-favorite-argument
By Marcus Thomson, researcher, IIASA Ecosystems Services and Management Program
While living in Cairo in 2010, I witnessed first-hand the human toll of political and environmental disasters that washed over Africa at the end of the last century. Unprecedented numbers of migrants were pressing into North Africa, many pushed out of their homelands by conflict and state-failure, pulled towards safer, richer, less fragile places like Europe. Throughout Sub-Saharan Africa, climate change was driving up competition for scarce land and water, and raising pressure on farmers to maintain the quantity and quality of their crops.
It is a similar story throughout the developing world, where many farmers do without the use of expensive chemical fertilizer and pesticides, complex irrigation, or boutique seed varieties. They rely instead on traditional land management practices that developed over long periods with consistent, predictable conditions. It is difficult to predict how dryland farmers will respond to climate change; so it is challenging to plan for various social, economic, and political problems expected to develop under, or be exacerbated by, climate change. Will it spur innovation or, as has been argued for the Syrian civil war, set up conflict? A major stumbling block is that the dynamics of human social behavior are so difficult to model.
Instead of attempting to predict farmers’ responses to climate change by modelling human behavior, we can look to the responses to environmental changes of farmers from the past as analogues for many subsistence farmers of the future. Methods to fill in historical gaps, and reconstruct the prehistoric record, are valuable because they expand the set of observed cases of societal-scale responses to environmental change. For instance, some 2000 years ago, an expansive maize-growing cultural complex, the Ancestral Puebloans (APs), was well established in the arid American Southwest. By AD 1000, members of this AP complex produced unique and innovative material culture including the famed “Great Houses”, the largest built structures in the United States until the 19th century. However, between AD 1150 and 1350, there was a profound demographic transformation throughout the Southwest linked to climate change. We now know that many APs migrated elsewhere. As a PhD student at the University of California, Los Angeles, I wondered whether a shift to cooler, more variable conditions of the “Little Ice Age” (LIA, roughly AD 1300 to 1850) was linked to the production of their staple crop, maize.
I came to IIASA as a YSSP in 2016 to collaborate with crop modelers on this question, and our work has just been published in the journal Quaternary International. I brought with me high-resolution data from a state-of-the-art climate model to drive the crop simulations, and AP site information collected by archaeologists. Because AP maize was quite different from modern corn, I worked with IIASA soil scientist Juraj Balkovič to modify the crop simulator with parameters derived from heirloom varieties still grown by indigenous peoples in the Southwest. I and IIASA economic geographer Tamás Krisztin developed a statistical technique to analyze the dynamical relationship between AP site occupation and simulated yield outcomes.
We found that for the most climate-stressed high-elevation sites, abandonments were most associated with increased year-to-year yield variability; and for the least stressed low-elevation and well-watered sites, abandonment was more likely due to endogenous stressors, such as soil degradation and population pressure. Crucially, we found that across all regions, populations peaked during periods of the most stable year-to-year crop yields, even though these were also relatively warm and dry periods. In short, we found that AP maize farmers adapted well to gradually rising temperatures and drought, during the MCA, but failed to adapt to increased climate variability after ~AD 1150, during the LIA. Because increased variability is one of the near certainties for dryland farming zones under global warming, the AP experience offers a cautionary example of the limits of low-technology adaptation to climate change, a business-as-usual direction for many sub-Saharan dryland farmers.
This is a lesson from the past that policymakers might take note of.
 Kelley, C. P., Mohtadi, S., Cane, M. A., Seager, R., & Kushnir, Y. (2015). Climate change in the Fertile Crescent and implications of the recent Syrian drought. Proceedings of the National Academy of Sciences, 201421533.
 Thomson, M. J., Balkovič, J., Krisztin, T., MacDonald, G. M. (2018). Simulated crop yield for Zea mays for Fremont Ancestral Puebloan sites in Utah between 850-1499 CE based on temperature dailies from a statistically downscaled climate model. Quaternary International. https://doi.org/10.1016/j.quaint.2018.09.031