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HEEECC

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6 - 9 December 2014, Bad Honnef, Germany

The 577. WE-Heraeus Seminar brings together theoretical physicists and complex systems scientists with distinguished researchers working on health, energy, and climate change to (i) learn about the complex interactions between these global systems, (ii) provide young physicists with an opportunity to explore fields of application of great societal importance, (iii) discuss in an interdisciplinary way the potentials and perspectives of cutting-edge modeling and data analysis methods from theoretical physics for studying both the individual subsystems as well as the whole complex, (iv) show that the language of theoretical physics and complex systems science is a natural and fruitful framework for this transdisciplinary field, and (v) initiate new promising scientific studies and projects in this context.

As the Intergovernmental Panel on Climate Change (IPCC) summarizes in its 4th assessment report, climate change has already increased the spread of diseases and premature deaths on a global scale through changes in (i) weather patterns (temperature, precipitation, sea-level rise and more frequent extreme events), (ii) air, food, and water quality, and (iii) agriculture, ecosystems, settlements, and industry. These currently small effects on human health include increased heatwave-related deaths and alterations in the seasonal distribution of some allergenic pollen species and the distribution of some infectious disease vectors, and are forecast to increase globally over the century. In particular, projections based on the state of the art scientific models indicate an increase in (iv) malnutrition and related disorders due to crop failures, including those relating to child growth and development, (v) people suffering from extreme weather events such as droughts, floods, fires, heatwaves, and storms, (vi) the operating range of infectious disease vectors, (v) diarrhoeal diseases, (vi) cardio-respiratory problems due to ground-level ozone, and (vii) risk of dengue (Confalonieri et al. 2007). The World Health Organisation estimates that the warming and precipitation trends due to anthropogenic climate change of the past 30 years already claim over 150,000 lives annually (Patz et al. 2005).

Some of the mechanisms underlying these findings are not yet sufficiently understood to reliably infer robust policy recommendations that would counteract these health implications, not only in developing countries but also in high-income countries which are, e.g., affected by hurricanes and heatwaves of increased frequency and severity. For example, the mixed effects on malaria, with a contraction of geographical range in some places and an expansion elsewhere and changes in the transmission season, involve complex nonlinear spatio-temporal dynamics that are hard to model and analyse with traditional methods.

Climate change affects health also through changes in infrastructure, especially energy supply and use. The United Nations Development Programme reports that (i) local and regional air pollution (e.g., fine particles, ozone, nitrogen, and sulphur emissions) from solid-fuel (e.g., charcoal and fuelwood) cooking, heating, and vehicles may be responsible for more than five percent of the global burden of disease and damages to forests, soils, and lakes, (ii) large-scale hydropower projects in forests and surface mining affect health via changes in the ecosystem, and (iii) most importantly, energy systems account for two-thirds of human-generated greenhouse gas increases driving climate change, thus forming a feedback loop (Goldemberg 2000).

Even in well-developed industrialized countries and during normal weather conditions, power outages can have severe effects on public health. For example, a major power outage occurred in 2003 in the midwest and northeast United States affecting some 50 million people through loss of refrigeration and multiple municipal infrastructures, in particular municipal environmental systems such as food protection, public water supply, and wastewater treatment, medical services, emergency response, and public health efforts (Kile et al. 2005). Independently from their effects on health, power blackouts can impose huge costs on societies (Newman et al. 2011). Hence reducing the risk of blackouts is crucially important for both adaptation to and mitigation of climate change because power grid stability is threatened both by volatile wind and solar energy production and by extreme events. E.g., outages onshore can often be corrected quickly so that only a small amount of energy is lost, but with offshore wind energy, the window for carrying out repairs or replacing components is often limited (Goldemberg 2000). The larger the share of renewable energy production, and the more frequent and severe weather extremes have to be expected, the more resilient to perturbations one must make the grid. Although, in retrospect, the total costs of a blackout have often exceeded the price tag of additional transmission lines that would likely have prevented this particular blackout in the first place, it is hard to judge in advance which new transmission lines should be built to most effectively improve a power grid’s stability against blackouts in general. A recent study (Menck et al. 2013b) performed at PIK employed a novel node-wise version of basin stability (Menck et al. 2013), a nonlinear stability concept developed at PIK, to investigate how a grid’s global degree of resilience against individual local perturbations is influenced by certain patterns of the wiring topology.

These complex relationships between health, energy, and extreme events in a changing climate form a prime example of a global complex dynamical system containing several network-like structures including infrastructure networks such as the regional and global power grids, functional networks such as the interaction network of climate dynamics, and socio-economic networks such as the contact network involved in the spreading of diseases. Modern theoretical physics and complex systems science have developed a number of cutting-edge modeling and data analysis methods to infer the individual components' interactions and mechanisms of such systems from data and model their emergent effects.

In particular, complex networks theory (Newman 2003, Boccaletti et al. 2006) and the recently developed concept of networks of networks may turn out to be the natural modeling framework for the interaction of health, energy, and climate. Network science has greatly evolved in the past decade and a half, and is currently a leading scientific field in the description of complex systems, which affects every aspect of our daily life. Famous examples include the findings about sexual partners, Internet and WWW, epidemic spreading, immunization strategies, citation networks, structure of financial markets, social percolation and opinion dynamics, structure of mobile communication networks, and many others. Among the phenomena that have been shown to fall in this conceptual framework are: cascading failures, blackouts, crashes, bubbles, crises, viral attacks and defense against them, introduction of new technologies, infrastructure, understanding, measuring and predicting the emergence and evolution of networks and their stylized features, spreading phenomena and immunization strategies, as well as the stability and fragility of airline networks (Havlin et al. 2012).

In addition, major developments of physics-based data analysis method are related to the concept of recurrence. The basic idea is that the temporal pattern of recurrences into the vicinity of previously visited states (in the sense of Poincaré) encodes essential information on the nonlinear dynamical characteristics of the system under study. Quantifying distinct patterns in a recurrence plot thus provides a widely applicable approach for characterizing various aspects related with the dynamical complexity, predictability and transitions of the studied system (Marwan 2007, Donges et al. 2011, Altmann and Kantz 2005).

 

 

The goal of the 577. Wilhelm und Else Heraeus Seminar on Health, Energy & Extreme Events in a Changing Climate (HEEECC) is to bring together theoretical physicists and complex systems scientists with distinguished researchers from the named fields of application to (i) learn about the complex interactions between these global systems, (ii) provide young physicists with an opportunity to explore fields of application of great societal importance, (iii) discuss in an interdisciplinary way the potentials and perspectives of the above-mentioned and other cutting-edge modeling and data analysis methods from theoretical physics for studying both the individual subsystems as well as the whole complex, (iv) show that the language of theoretical physics and complex systems science is a natural and fruitful framework for this transdisciplinary field, and (v) initiate new promising scientific studies and projects in this context. We expect a successful interchange that will lead to many synergies and concrete research opportunities.

 

References

Altmann E, Kantz H (2005) Recurrence time analysis, long-term correlations, and extreme events. Phys. Rev. E 71, 056106.

Boccaletti S, Latora V, Moreno Y et al. (2006) Complex networks: Structure and dynamics. Phys. Rep. 424(45):175–308.

Confalonieri U, Menne B, Akhtar R et al. (2007) Human health. In: Parry ML, Canziani OF, Palutikof JP (eds.) Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, 391–431.

Donges JF, Donner RV, Trauth MH, Marwan N, Schellnhuber HJ, Kurths J (2011) Nonlinear detection of paleoclimate-variability transitions possibly related to human evolution. PNAS, 108(51), 20422–20427.

Donges JF, Heitzig J, Donner RV, Kurths J (2012) Analytical framework for recurrence-network analysis of time series. Phys. Rev. E 85, 046105.

Donner RV, Zou Y, Donges JF, Marwan N, Kurths J (2010) Recurrence networks – a novel paradigm for nonlinear time series analysis. New J. Phys. 12:033025

Goldemberg J et al. (eds., 2000), Energy and the challenge of sustainability, United Nations Development Programme.

Havlin S, Kenett DY, Ben-Jacob E et al. (2012) Challenges in network science: Applications to infrastructures, climate, social systems and economics. EPJST 214(1):273–93.

Kile JC, Skowronski S, Miller MD et al. (2005) Impact of 2003 power outages on public health and emergency response. Prehospital and disaster medicine 20(2):93–7.

Marwan N, Romano MC, Thiel M, Kurths J (2007) Recurrence Plots for the Analysis of Complex Systems, Physics Reports 438(5–6):237–329.

McMichael AJ, Powles JW, Butler CD, Uauy R (2005) Food, livestock production, energy, climate change, and health. Lancet 370(9594):1253–63.

Menck PJ, Heitzig J, Marwan N, Kurths J (2013) How basin stability complements the linear-stability paradigm. Nature Physics 9:89–92.

Menck PJ, Heitzig J, Kurths J, Schellnhuber HJ (2013b) Sustainable power grids need smart wiring. Under review for Nature Communications.

Newman D, Carreras B, Lynch V, Dobson I (2011) Exploring complex systems aspects of blackout risk and mitigation. IEEE Transactions on Reliability 60(1):134–143.

Newman M (2003) The structure and function of complex networks. SIREV: SIAM Review 45.

Patz JA, Campbell-Lendrum D, Holloway T, Foley JA (2005) Impact of regional climate change on human health. Nature 438(7066):310–7.

Sauerborn R, Ebi K (2012) Climate change and natural disasters: integrating science and practice to protect health. Global Health Action 5:1–7; doi:10.3402/gha.v5i0.19295.

Woodward A, Smith K, Campbell-Lendrum D, Chadee D, Honda Y, Liu Q, Olwoch J, Revich B, Sauerborn R, Chafe Z, Haines A (2014) Climate change and health – the latest report from the IPCC. The Lancet
283:1185–1189.

Yamamoto SS, Louis VR, Sie A, Sauerborn R (2014). Biomass smoke in Burkina Faso: what is the relationship between particulate matter, carbon monoxide, and kitchen characteristics? Environ Sci Pollut Res Int. 21(4):2581–91.

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