MSCCEC 2013 Abstracts


Full Papers
Paper Nr: 3
Title:

Quantitative Models Evaluating the Effect Climate Change Effects on Tourism - State of the Art

Authors:

Jaume Rosselló

Abstract: In a context of climate change, many destinations are considering what effects can be predicted on the tourist demand and how they should be tackled. This work analyses the most relevant perspectives presented in the literature evaluating the effect of climate change on tourism. A review is made by showing the results that rise from a triple point of view: the consideration of physical changes, the analysis of the tourist attractiveness through climatic indexes and modeling tourism demand. The review suggests that, although some methodologies are on a primary stage of development, results from the different perspectives agree in presenting a similar map of the main affected areas (positively and negatively) in terms of tourism demand and/or tourism attractiveness.

Paper Nr: 4
Title:

Statistical and Scaling Analyses of Neural Network Soil Property Inputs/Outputs at an Arizona Field Site

Authors:

Alberto Guadagnini, Shlomo P. Neuman, Marcel G. Schaap and Monica Riva

Abstract: Analyses of flow and transport in the shallow subsurface require information about spatial and statistical distributions of soil hydraulic properties (water content and permeability, their dependence on capillary pressure) as functions of scale and direction. Measuring these properties is relatively difficult, time consuming and costly. It is generally much easier, faster and less expensive to collect and describe the makeup of soil samples in terms of textural composition (e.g. per cent sand, silt, clay and organic matter), bulk density and other such pedological attributes. Over the last two decades soil scientists have developed a set of tools, known collectively as pedotransfer functions (PTFs), to help translate information about the spatial distribution of pedological indicators into corresponding information about soil hydraulic properties. One of the most successful PTFs is the nonlinear Rosetta neural network model developed by one of us. Among remaining open questions are the extents to which spatial and statistical distributions of Rosetta hydraulic property outputs, and their scaling behavior, reflect those of Rosetta pedological inputs. We address the last question by applying Rosetta, coupled with a novel statistical scaling analysis recently proposed by three of us, to soil sample data from an experimental site in southern Arizona, USA.

Paper Nr: 7
Title:

A Fuzzy Cognitive Map for México City’s Water Availability System

Authors:

Iván Paz Ortiz and Carlos Gay García

Abstract: .

Paper Nr: 9
Title:

Fuzzy Approaches Improve Predictions of Energy Performance of Buildings

Authors:

Àngela Nebot and Francisco Mugica

Abstract: The energy consumption in Europe is, to a considerable extent, due to heating and cooling used for domestic purposes. This energy is produced mostly by burning fossil fuels with a high negative environmental impact. The characteristics of a building are an important factor to determine the necessities of heating and cooling loads. Therefore, the study of the relevant characteristics of the buildings with respect to the heating and cooling needed to maintain comfortable indoor air conditions, could be very useful in order to design and construct energy efficient buildings. In previous studies, statistical machine learning approaches have been used to predict heating and cooling loads from eight variables describing the main characteristics of residential buildings which obtained good results. In this research, we present two fuzzy modelling approaches that study the same problem from a different perspective. The prediction results obtained while using fuzzy approaches outperform the ones described in the previous studies. Moreover, the feature selection process of one of the fuzzy methodologies provide interesting insights to the principal building variables causally related to heating and cooling loads.

Paper Nr: 10
Title:

Using Andaptive Neuro Fuzzy Inference System to Build Models with Uncertain Data for Rainfed Maize - Study Case in the State of Puebla (Mexico)

Authors:

Anais Vermonden Thibodeau and Carlos Gay Garcia

Abstract: Using the methodology of Adaptive Neuro Fuzzy Inference System (ANFIS) a model to determine the relationship suitability index with the yields per hectare and the percentage of production area lost of rainfed maize for the state of Puebla was built. The data used to build the model presented inconsistencies. The data of the INEGI’s land use map presented more municipalities without rainfed maize agriculture than the database of SAGARPA. Also the SAGARPA data, in terms of the percentage of production area lost, do not show any distinctions between the loss due to climate, pests, or simply that the farmer did not plant the total area that was declared, or had not harvested all the area declared. Even with data inconsistencies ANFIS produced a coherent output reviewed by experts. The model shows that higher the percentage of production area lost and high yields the higher the suitability index is. According to local studies this is due to the high degradation of the soils.

Paper Nr: 11
Title:

Policy Design, Eco-innovation and Industrial Dynamics in an Agent-Based Model - An Illustration with the REACH Regulation

Authors:

Nabila Arfaoui, Eric Brouillat and Maider Saint Jean

Abstract: The paper proposes an agent-based model to study the impact of European regulation REACH on industrial dynamics. This new regulation adopted in 2007 establishes a new philosophy in how to design environmental protection and health. For this reason, REACH appears as a privileged object of study to analyze the impact of regulation on innovation strategies of firms and the market structure. Our model focuses on the interactions between clients and suppliers in order to take into account interdependencies at the heart of vertical relationships that are upset by the new principles introduced by REACH. The main contribution of this paper is to show, through an agent-based model, how different combinations of flexible and stringent instruments designed on REACH regulation (Extended Producer Responsibility, authorization process and restrictions) create the incentives and the constraints to shape market selection and innovation.

Paper Nr: 12
Title:

Carbon Dioxide Capture from Synthesis Gas Containing Steam by Pressure Swing Adsorption at Mid-high Temperature

Authors:

Cheng-tung Chou, Yu-Hau Shih, Yu-Jie Huang and Hong-sung Yang

Abstract: .

Paper Nr: 13
Title:

Natural Handling of Uncertainties in Fuzzy Climate Models

Authors:

Carlos Gay García and Oscar Sánchez Meneses

Abstract: The wide range of the IPCC emission scenarios and the corresponding concentrations, forcings and temperature obtained with the use of the Magicc/Scengen Model are substituted by linearly increasing emissions that preserve the ranges of the values for the concentrations forcings and temperatures. In fact IPCC values are comprised within the values of the linear emissions. These allow the identification of simple relationships that are translated to fuzzy rules that in turn conform the fuzzy model. The sources of uncertainty that the model permits to explore are: the uncertainty due to not knowing what the emissions are going to be in the future, the one related to the climate sensitivity of the models (this has to do with different parameterizations of processes used in the models) and the uncertainties in the temperature maps produced by the models. Here we produce maps corresponding to 1, 2, 3, etc., degrees centigrade of temperature increase and discuss the timing of exceeding them. Therefore the argument instead of talking about the uncertainty in temperature at a certain date becomes about the uncertainty in the date certain temperature will be reached. The timing becomes another uncertainty.