'Chemical cybernetics' and the problem of climate change

(Part 3 of 3)

The devastation caused by “Sendong” in Mindanao last month serves as a grim reminder of just how disaster-prone the Philippines really is. The impact was especially bad since the storm came right at the tail end of the typhoon season, just when everyone thought the worst was over, and just before the festivities of the year-end holidays were about to begin. As the year begins, and Cagayan de Oro and Iligan struggle to recover in the aftermath of the storm, the country can at least count on several months of typhoon-free weather during the dry season. Not surprisingly, there is plenty of discussion among local scientists and researchers on how to manage the effects of such disasters that hit the Philippines on such a regular basis. Climate change also adds an element of uncertainty to this problem, as it remains difficult to predict how long-term weather patterns in our part of the world will shift in the coming decades. Furthermore, disasters also have subtle downstream effects which, while not as spectacular, may have significant adverse developmental consequences. For example, one of the speakers at an event organized by the Climate Change Commission which I attended in mid-2011 pointed out that in disaster-hit areas, residents will often sacrifice their children’s schooling as they rebuild their lives. While such decisions are not surprising, it makes me wonder how much long-term socio-economic damage is caused by people foregoing education in many parts of the Philippines.  

The fundamental problem with such downstream effects of such disasters is that they are not as readily captured on camera as floods and landslides, nor as easily measured as the number of casualties or homes destroyed. Thus, researchers need to develop models to be able to quantify and predict this sort of “collateral damage.” These models provide a mathematical foundation for the analysis of the consequences of natural disasters, and when implemented as computer software, can provide valuable decision support for vulnerability assessment and risk management. One particular approach is known as “inoperability input-output modeling,” or IIM, which was first proposed by systems engineer Yacov Haimes and his Ph.D. student at the University of Virginia in 2001. The underlying approach of IIM is based on the use of systems of linear equations to capture interdependencies of the components that make up critical infrastructure systems; as the name implies, it bears considerably similarity to economic input-output analysis for which Leontief won the Nobel Prize in 1973. IIM makes use of a dimensionless quantity called “inoperability,” which ranges from 0 (corresponding to the normal state of a system) to 1 (signifying total collapse). Intermediate values of the inoperability metric will of course indicate various degrees of system failure, which may be in terms of physical or economic terms. The mathematical linkages within an IIM model can then be used to compute how the consequences of disasters propagate through an infrastructure network to manifest eventually as downstream effects. For example, IIM can be used to calculate the economic damage (for example, in the form of lost livelihood from the collapse of major service industries such as tourism) caused by such events as the tsunami of 2004. It can also be used to determine the optimal allocation of resources in the immediate aftermath of events such as last year’s disaster at Fukushima, where an earthquake and tsunami led to a major nuclear crisis. It can even be used for the analysis of man-made calamities — for example, an ex post analysis of the downstream effects of the 9/11 attacks has been done by Haimes’ research team at the University of Virginia.

As a researcher in the field of process systems engineering (widely known as PSE in most countries, but also known as “chemical cybernetics” in Russia and parts of the former Soviet Union), it is quite clear to me that IIM can be used to great effect for disaster vulnerability assessment in the Philippines. My specific research interest is to develop inoperability-based models to provide a rigorous basis for climate change adaptation measures. For example, early last year I developed a model for optimal planning of robust energy supply chains by matching energy sources with demands while taking into account inoperability constraints from multiple risk scenarios; a brief description of the model appeared in this column in August, while a full account was also published in the journal Applied Energy. In 2012, IIM will be ranked prominently in my own research agenda, and in fact one of the key plans we have at De La Salle University is to invite one of Haimes’ former Ph.D. students, and now himself an established authority on IIM at George Washington University (as well as a University of the Philippines alumni), Dr. Joost Santos, for a brief visit in July to begin collaborative work with local systems engineers and economists. 

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Prof. Raymond R. Tan is a university fellow and full professor of chemical engineering at De La Salle University. He is also the current director of that institution’s Center for Engineering and Sustainable Development Research (CESDR). He is the author of more than 70 process systems engineering (PSE) articles that have been published in chemical, environmental and energy engineering journals. He has over 80 articles listed in Scopus with an h-index of 17. He is also member of the editorial boards of the journals Clean Technologies and Environmental Policy, Philippine Science Letters and Sustainable Technologies, Systems & Policies, and is co-editor of the forthcoming book Recent Advances in Sustainable Process Design and Optimization. He is also the recipient of multiple awards from the National Academy of Science and Technology (NAST) and the National Research Council of the Philippines (NRCP). He may be contacted via e-mail ([email protected]).