Adaptación del sector turístico al cambio climático en España. La importancia de las acciones a escala local y en empresas turísticas

El 5º Informe del IPCC (Panel Intergubernamental de Cambio Climático, 2014) señala que el turismo será una de las actividades económicas que mayores efectos negativos experimentará en las próximas décadas debido al calentamiento térmico del planeta. En España, el turismo es una fuente principal de ingresos y de creación de puestos de trabajo en su economía. De ahí que sea necesaria la puesta en marcha de medidas de adaptación a la nueva realidad climática que, en nuestro país, va a suponer cambios en el confort climático de los destinos e incremento de extremos atmosféricos. Frente a los planes de adaptación al cambio climático en la actividad turística, elaborados por los gobiernos estatal y regional, que apenas se han desarrollado en España, la escala local muestra interesantes ejemplos de acciones de adaptación al cambio climático, desarrolladas tanto por los municipios (energía, transporte, vivienda, planificación urbanística) como por la propia empresa turística (hoteles, campings, apartamentos). Medidas de ahorro de agua y luz, fomento del transporte público y de las energías limpias, creación de zonas verdes urbanas y adaptación a los extremos atmosféricos destacan como acciones de mitigación del cambio climático en los destinos turísticos principales de nuestro país.

Disentangling trade-offs and synergies around ecosystem services with the influence network framework: illustration from a consultative process over the French Alps

An important aspect of sustainability is to maintain biodiversity and ecosystem functioning while improving human well-being. For this, the ecosystem service (ES) approach has the potential to bridge the still existing gap between ecological management and social development, especially by focusing on trade-offs and synergies between ES and between their beneficiaries. Several frameworks have been proposed to account for trade-offs and synergies between ES, and between ES and other components of social-ecological systems. However, to date, insufficient explicit attention has been paid to the three facets encompassed in the ES concept, namely potential supply, demand, and use, leading to incomplete descriptions of ES interactions. We expand on previous frameworks by proposing a new influence network framework (INF) based on an explicit consideration of influence relationships between these three ES facets, biodiversity, and external driving variables. We tested its ability to provide a comprehensive view of complex social-ecological interactions around ES through a consultative process focused on environmental management in the French Alps. We synthetized the interactions mentioned during this consultative process and grouped variables according to their overall propensity to influence or be influenced by the system. The resulting directed sequence of influences distinguished between: (1) mostly influential variables (dynamic social variables and ecological state variables), (2) target variables (provisioning and cultural services), and (3) mostly impacted variables (regulating services and biodiversity parameters). We discussed possible reasons for the discrepancies between actual and perceived influences and proposed options to overcome them. We demonstrated that the INF holds the potential to deliver collective assessments of ES relations by: (1) including ecological as well as social aspects, (2) providing opportunities for colearning processes between stakeholder groups, and (3) supporting communication about complex social-ecological systems and consequences for environmental management.

Real-time load-side control of electric power systems

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems.

(1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control.

(2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

EVALUATION OF POTENTIAL TRANSLOAD FACILITY LOCATIONS IN THE UPPER PENINSULA (UP) OF MICHIGAN

Shippers want to improve their transportation efficiency and rail transportation has the potential to provide an economical alternative to trucking, but it also has potential drawbacks. The pressure to optimize transportation supply chain logistics has resulted in growing interest in multimodal alternatives, such as a combination of truck and rail transportation, but the comparison of multimodal and modal alternatives can be complicated. Shippers in Michigan’s Upper Peninsula (UP) face similar challenges. Adding to the challenge is the distance from major markets and the absence of available facilities for transloading activities. This study reviewed three potential locations for a transload facility (Nestoria, Ishpeming, and Amasa) where truck shipments could be transferred to rail and vice versa. These locations were evaluated on the basis of transportation costs for shippers when compared to the use of single mode transportation by truck to Wisconsin, Chicago, Minneapolis, and Sault Ste. Marie. In addition to shipping costs, the study also evaluated the potential impact of future carbon emission penalties on the shipping cost and the effects of changing fuel prices on shipping cost. The study used data obtained from TRANSEARCH database (2009) and found that although there were slight differences between percent savings for the three locations, any of them could provide potential benefits for movements to Chicago and Minneapolis, as long as final destination could be accessed by rail for delivery. Short haul movements of less than 200 miles (Wisconsin and Sault Ste. Marie) were not cost effective for multimodal transport. The study also found that for every dollar increase in fuel price, cost savings from multimodal option increased by three to five percent, but the inclusion of emission costs would only add one to two percent additional savings. Under a specific case study that addressed shipments by Northern Hardwoods, the most distant locations in Wisconsin would also provide cost savings, partially due to the possibility of using Michigan trucks with higher carrying capacity for the initial movement from the facility to transload location. In addition, Minneapolis movements were found to provide savings for Northern Hardwoods, even without final rail access.

A dynamic pricing reverse auction-based resource allocation mechanism in cloud workflow systems

Market-oriented reverse auction is an efficient and cost-effective method for resource allocation in cloud workflow systems since it can dynamically allocate resources depending on the supply-demand relationship of the cloud market. However, during the auction the price of cloud resource is usually fixed, and the current resource allocation mechanisms cannot adapt to the changeable market properly which results in the low efficiency of resource utilization. To address such a problem, a dynamic pricing reverse auction-based resource allocation mechanism is proposed. During the auction, resource providers can change prices according to the trading situation so that our novel mechanism can increase the chances of making a deal and improve efficiency of resource utilization. In addition, resource providers can improve their competitiveness in the market by lowering prices, and thus users can obtain cheaper resources in shorter time which would decrease monetary cost and completion time for workflow execution. Experiments with different situations and problem sizes are conducted for dynamic pricing-based allocation mechanism (DPAM) on resource utilization and the measurement of Time∗Cost (TC). The results show that our DPAM can outperform its representative in resource utilization, monetary cost, and completion time and also obtain the optimal price reduction rates.

Análisis del potencial exportador colombiano de carne bovina y porcina a la Federación Rusa

El estudio del potencial exportador colombiano de carne bovina y porcina a la Federación Rusa en función de su oferta y demanda es un proyecto que pertenece a la línea de realidad dentro del área de investigación de la Universidad del Rosario. Es una investigación tipo exploratoria con un enfoque cualitativo que buscará dar respuesta a si Colombia cuenta con el potencial exportador de carne bovina y porcina al mercado de la Federación Rusa. El marco teórico que justifica el proyecto de investigación se compone de la investigación de mercados, el estudio del potencial de la demanda y las restricciones de acceso a otros mercados. A su vez los resultados esperados del proyecto de investigación serán diagnosticar el potencial exportador que tiene Colombia en relación a la carne bovina y porcina, así como examinar la oferta y demanda de estos productos en el mercado de la Federación Rusa y por último detallar las medidas sanitarias y zoosanitarias exigidas por el mercado de la Federación Rusa. Finalmente se utilizarán herramientas de tipo cualitativo que soportarán el desarrollo del proyecto de investigación, para conseguir alinear el objetivo del proyecto con el de la línea de realidad de la universidad y al objetivo del profesor, que buscan la producción de materiales académicos de uso permanente en la Universidad.

Aspectos da produção e mercado de madeira e celulose no Brasil e na Região Norte.

O objetivo deste trabalho foi avaliar o comportamento do mercado de madeira e celulose no Brasil e na Região Norte. O modelo de análise proposto inclui as variáveis relevantes que determinam a oferta e a demanda de madeira e celulose, assim como as expectativas sobre a formação de preços. Os resultados mostram que tanto a oferta quanto a demanda de celulose são inelásticas a preço. Isto significa que tanto o produtor quanto o consumidor fazem ajuste nas quantidades ofertada e demandada em proporção inferior às variações de preço. Outro fato relevante é que a demanda de celulose na Região Norte é perfeitamente inelástica à renda, indicando que o consumo não reage às mudanças na renda do consumidor. A conclusão que se tira dos resultados é que o setor torna-se muito vulnerável às mudanças de política tributária e cambial que incidem diretamente sobre a circulação do produto para mercados interno e internacional.

An heuristic approach for optimal location of gas supply units in transportation system

The best places to locate the Gas Supply Units (GSUs) on a natural gas systems and their optimal allocation to loads are the key factors to organize an efficient upstream gas infrastructure. The number of GSUs and their optimal location in a gas network is a decision problem that can be formulated as a linear programming problem. Our emphasis is on the formulation and use of a suitable location model, reflecting real-world operations and constraints of a natural gas system. This paper presents a heuristic model, based on lagrangean approach, developed for finding the optimal GSUs location on a natural gas network, minimizing expenses and maximizing throughput and security of supply.The location model is applied to the Iberian high pressure natural gas network, a system modelised with 65 demand nodes. These nodes are linked by physical and virtual pipelines – road trucks with gas in liquefied form. The location model result shows the best places to locate, with the optimal demand allocation and the most economical gas transport mode: by pipeline or by road truck.

Towards a demand model for maritime passenger transportation in the Caribbean: a regional study of passenger ferry services

In this paper, the main factors that influence the demand for maritime passenger transportation in the Caribbean were studied. While maritime studies in the Caribbean have focused on infrastructural and operational systems for intensifying trade and movement of goods, there is little information on the movement of persons within the region and its potential to encourage further integration and sustainable development. Data to inform studies and policies in this area are particularly difficult to source. For this study, an unbalanced data set for the 2000-2014 period in 15 destinations with a focus on departing ferry passengers was compiled. Further a demand equation for maritime passenger transportation in the Caribbean using panel data methods was estimated. The results showed that this demand is related to the real fare of the service, international economic activity and the number of passengers arriving in the country by air.

Modeling of hydraulic and energy efficiency indicators for water supply systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

An integrated modeling approach to assess the impact on road freight transport demand of allowing longer and heavier vehicles (LHVs) in Spain

The assessment on introducing Longer and Heavier Vehicles (LHVs) on the road freight transport demand is performed in this paper by applying an integrated modeling approach composed of a Random Utility-Based Multiregional Input-Output model (RUBMRIO) and a road transport network model. The approach strongly supports the concept that changes in transport costs derived from the LHVs allowance as well as the economic structure of regions have both direct and indirect effects on the road freight transport system. In addition, we estimate the magnitude and extent of demand changes in the road freight transportation system by using the commodity-based structure of the approach to identify the effect on traffic flows and on pollutant emissions over the whole network of Spain by considering a sensitivity analysis of the main parameters which determine the share of Heavy-Goods Vehicles (HGVs) and LHVs. The results show that the introduction of LHVs will strengthen the competitiveness of the road haulage sector by reducing costs, emissions, and the total freight vehicles required.

A diagnostic framework for demand amplification problems in supply chains

This dissertation delivers a framework to diagnose the Bull-Whip Effect (BWE) in supply chains and then identify methods to minimize it. Such a framework is needed because in spite of the significant amount of literature discussing the bull-whip effect, many companies continue to experience the wide variations in demand that are indicative of the bull-whip effect. While the theory and knowledge of the bull-whip effect is well established, there still is the lack of an engineering framework and method to systematically identify the problem, diagnose its causes, and identify remedies. ^ The present work seeks to fill this gap by providing a holistic, systems perspective to bull-whip identification and diagnosis. The framework employs the SCOR reference model to examine the supply chain processes with a baseline measure of demand amplification. Then, research of the supply chain structural and behavioral features is conducted by means of the system dynamics modeling method. ^ The contribution of the diagnostic framework, is called Demand Amplification Protocol (DAMP), relies not only on the improvement of existent methods but also contributes with original developments introduced to accomplish successful diagnosis. DAMP contributes a comprehensive methodology that captures the dynamic complexities of supply chain processes. The method also contributes a BWE measurement method that is suitable for actual supply chains because of its low data requirements, and introduces a BWE scorecard for relating established causes to a central BWE metric. In addition, the dissertation makes a methodological contribution to the analysis of system dynamic models with a technique for statistical screening called SS-Opt, which determines the inputs with the greatest impact on the bull-whip effect by means of perturbation analysis and subsequent multivariate optimization. The dissertation describes the implementation of the DAMP framework in an actual case study that exposes the approach, analysis, results and conclusions. The case study suggests a balanced solution between costs and demand amplification can better serve both firms and supply chain interests. Insights pinpoint to supplier network redesign, postponement in manufacturing operations and collaborative forecasting agreements with main distributors.^

Novel Formulation and Efficient Solution Strategy for Strategic Optimization of an Industrial Chemical Supply Chain Under Demand Uncertainty

This paper is concerned with strategic optimization of a typical industrial chemical supply chain, which involves a material purchase and transportation network, several manufacturing plants with on-site material and product inventories, a product transportation network and several regional markets. In order to address large uncertainties in customer demands at the different regional markets, a novel robust scenario formulation, which has been developed by the authors recently, is tailored and applied for the strategic optimization. Case study results show that the robust scenario formulation works well for this real industrial supply chain system, and it outperforms the deterministic formulation and the classical scenario-based stochastic programming formulation by generating better expected economic performance and solutions that are guaranteed to be feasible for all uncertainty realizations. The robust scenario problem exhibits a decomposable structure that can be taken advantage of by Benders decomposition for efficient solution, so the application of Benders decomposition to the solution of the strategic optimization is also discussed. The case study results show that Benders decomposition can reduce the solution time by almost an order of magnitude when the number of scenarios in the problem is large.