MSCCES 2017 Abstracts

Full Papers Short Papers
Full Papers
Paper Nr: 1
Title:

A Prospective Fuzzy Approach for the Development of Integral Seismic Risk Scenarios for Barcelona, Spain
Authors:

J. Rubén G. Cárdenas, Francisco Mugica and Àngela Nebot
Abstract: We create a set of synthetic seismic risk scenarios by combining stochastic seismic simulations with social fragility indicators by mean of a fuzzy Mamdani type inference nested-model. The original values of the social economic variables were modified by arbitrary increments to simulate either constrains or improvement in their reported levels, and the Fuzzy Seismic Risk Model was applied again for each of these variations to produce a range of final integral seismic risk levels. Even if this experiment clearly needs to be further tuned, the use of fuzzy inference in the creation of risk scenarios becomes a simpler task once suitable membership functions have been defined, since the non-linear influence of each of the variables involved can be easily quantified. The final product is capable to facilitate the prospective view needed in decision-making planning while avoiding compensability issues, commonly reflected when composite indicators are used to represent social dimensions.
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Short Papers
Paper Nr: 2
Title:

Fuzzy Inference Systems as Geographic Patterns of Climatic Warming Over Mexico
Authors:

Carlos Gay, Bernardo Bastien, Valeria Vidal and Jessica Pelcastre
Abstract: Local and regional temperature response to the global temperature rising is a matter of relevance in terms of climate change impacts assessment. However, in developing countries, the estimation of this response has been hampered, mainly, due to the lack of regional climate models and of higher computational power. This work analyzes the high-resolution warming signal over Mexico as function of the global mean temperature using Adaptive Neuro-Fuzzy Inference Systems. The geographical array of Fuzzy Inference Systems are presented as warming patterns that were used to project the temperature trend, in the 21st century, under the four Representative Concentration Pathways. We based on the assumptions that the global temperature increase is the dominant influence on future climate and that the local response is determined by the local geographic conditions. The resulting scenarios shows that the northwestern and south central regions present the highest warming values, likewise, all maps display a region where the projected warming remains uncertain. The proposed methodology is presented as an alternative pattern scaling technique whose results pretend to serve as an analysis tool of potential impacts of regional warming over Mexico, and lead to the generation and improvement of adaptation and mitigation strategies.
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Paper Nr: 3
Title:

Modeling a Flue-Gas Desulfurization Plant with a Fuzzy Methodology to Optimize the SO2 Absorption Process
Authors:

Antoni Escobet, Àngela Nebot, Francisco Mugica, Xavier Gamisans and Xavier Guimerà
Abstract: Sulfur oxides are some of the major existing pollutants that directly affect the atmosphere. In combination with particles and air humidity, produce the most detrimental effects attributed to air pollution. The treatment of gas streams containing sulfur dioxide and its subsequent recovery is, therefore, a matter of great importance for the elimination of the environmental burden of their emission into the atmosphere. In this research, a fuzzy model of a flue-gas desulfurization plant is developed with the aim of dealing with two optimizations problems. The first one, is centered in finding the amount of liquid that should be injected into the plant in order to optimize the SO2 absorption process. The second one, is the development of a tool to help to size the absorption tower (find the right dimension), given the optimum amount of liquid derived from the previous goal. The results obtained, although preliminary, are reliable and useful for chemical engineering plant design.
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Paper Nr: 4
Title:

A Simple Fuzzy Model to Estimate Carbon Emissions towards 2100 Consistent with Expected Temperature Increases
Authors:

Carlos Gay García and Oscar Casimiro Sánchez-Meneses
Abstract: It is a matter of discussion the magnitude of impacts caused by incremental thresholds of global temperature over the most important socio-economic and natural sectors. The focus is on the 2 °C and 1 °C thresholds. Based on a set of linear emission trajectories of CO2, a simple fuzzy model which estimates CO2 emissions for 2100, starting from the emissions projected for 2030 is shown. An additional fuzzy variable, the year for which the net carbon emissions begin to decrease, is also calculated. For the estimates of future global mean temperature increments, the simple climate model MAGICCv5.3, with moderate climate sensitivity, was used. The uncertainties of values of future emissions are easily included by a convenient selection of fuzzy sets in the input and output variables of the model. The results show that, in order to reach the 2 °C threshold, it will be necessary to require negative net emissions for years as close to 2030 as 2060´s and, even more, for the case of 1 °C. Indeed, 1 °C is, by now, far of the actual mitigation capabilities of the world. This information must be useful for the decision makers. The model developed can be extended for other values of global temperature increments.
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Paper Nr: 5
Title:

An Agent-based Model of Food-borne Diseases Under Climate Change Scenarios in Mexico City - The Risk of Street-food in a Warming City
Authors:

B. Bastien-Olvera, E. Bautista Gonzalez and C. Gay Garcia
Abstract: Food is a conventional vehicle for pathogens to reach and infect new hosts. Distinctively, street food is a major source of food-borne diseases and climate change effects will intensify this by increasing the mean surface temperature and thus, the microorganisms growth rate. Through this research we present a preliminary agent-based model that simulates at various levels the dynamic of street-food consumers and food-borne disease under climate change scenarios, using tunable parameters such as hygiene level, microorganisms growth rate and number of consumers. The results show that the model has the potential to be a useful tool for optimizing decision-making and urban planning strategies related to health and climate change.
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