Assessment of energy efficiency and sustainability scenarios in the transport system

Background Energy Policy is one of the main drivers of Transport Policy. A number of strategies to reduce current energy consumption trends in the transport sector have been designed over the last decades. They include fuel taxes, more efficient technologies and changing travel behavior through demand regulation. But energy market has a high degree of uncertainty and the effectiveness of those policy options should be assessed. Methods A scenario based assessment methodology has been developed in the frame of the EU project STEPS. It provides an integrated view of Energy efficiency, environment, social and competitiveness impacts of the different strategies. It has been applied at European level and to five specific Regions. Concluding remarks The results are quite site specific dependent. However they show that regulation measures appear to be more effective than new technology investments. Higher energy prices could produce on their turn a deterioration of competitiveness and a threat for social goals.

An Experimental Platform for large-scale research facing FI-IoT scenarios

Providing experimental facilities for the Internet of Things (IoT) world is of paramount importance to materialise the Future Internet (FI) vision. The level of maturity achieved at the networking level in Sensor and Actuator networks (SAN) justifies the increasing demand on the research community to shift IoT testbed facilities from the network to the service and information management areas. In this paper we present an Experimental Platform fulfilling these needs by: integrating heterogeneous SAN infrastructures in a homogeneous way; providing mechanisms to handle information, and facilitating the development of experimental services. It has already been used to deploy applications in three different field trials: smart metering, smart places and environmental monitoring and it will be one of the components over which the SmartSantander project, that targets a large-scale IoT experimental facility, will rely on

Robust rolling stock under uncertain demand in rapid transit networks

This paper focuses on the railway rolling stock circulation problem in rapid transit networks where the known demand and train schedule must be met by a given fleet. In rapid transit networks the frequencies are high and distances are relatively short. Although the distances are not very large, service times are high due to the large number of intermediate stops required to allow proper passenger flow. The previous circumstances and the reduced capacity of the depot stations and that the rolling stock is shared between the different lines, force the introduction of empty trains and a careful control on shunting operation. In practice the future demand is generally unknown and the decisions must be based on uncertain forecast. We have developed a stochastic rolling stock formulation of the problem. The computational experiments were developed using a commercial line of the Madrid suburban rail network operated by RENFE (The main Spanish operator of suburban trains of passengers). Comparing the results obtained by deterministic scenarios and stochastic approach some useful conclusions may be obtained.

Analysis of advanced European nuclear fuel cycle scenarios including transmutation and economic estimates

Four European fuel cycle scenarios involving transmutation options (in coherence with PATEROS and CPESFR EU projects) have been addressed from a point of view of resources utilization and economic estimates. Scenarios include: (i) the current fleet using Light Water Reactor (LWR) technology and open fuel cycle, (ii) full replacement of the initial fleet with Fast Reactors (FR) burning U?Pu MOX fuel, (iii) closed fuel cycle with Minor Actinide (MA) transmutation in a fraction of the FR fleet, and (iv) closed fuel cycle with MA transmutation in dedicated Accelerator Driven Systems (ADS). All scenarios consider an intermediate period of GEN-III+ LWR deployment and they extend for 200 years, looking for long term equilibrium mass flow achievement. The simulations were made using the TR_EVOL code, capable to assess the management of the nuclear mass streams in the scenario as well as economics for the estimation of the levelized cost of electricity (LCOE) and other costs. Results reveal that all scenarios are feasible according to nuclear resources demand (natural and depleted U, and Pu). Additionally, we have found as expected that the FR scenario reduces considerably the Pu inventory in repositories compared to the reference scenario. The elimination of the LWR MA legacy requires a maximum of 55% fraction (i.e., a peak value of 44 FR units) of the FR fleet dedicated to transmutation (MA in MOX fuel, homogeneous transmutation) or an average of 28 units of ADS plants (i.e., a peak value of 51 ADS units). Regarding the economic analysis, the main usefulness of the provided economic results is for relative comparison of scenarios and breakdown of LCOE contributors rather than provision of absolute values, as technological readiness levels are low for most of the advanced fuel cycle stages. The obtained estimations show an increase of LCOE ? averaged over the whole period ? with respect to the reference open cycle scenario of 20% for Pu management scenario and around 35% for both transmutation scenarios. The main contribution to LCOE is the capital costs of new facilities, quantified between 60% and 69% depending on the scenario. An uncertainty analysis is provided around assumed low and high values of processes and technologies.

Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty

In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.

Simulation of Land Use and Investment Behaviour under Different Policy Scenarios: Results of the extended farm/household model. Factor Markets Working Paper No. 27, July 2012

Factor markets are a central issue in analyses of farm development and of agricultural sector vitality. Among the different production factors, land is one of the most studied. Several studies seek to estimate the effect of government policy payments on land value or land rental prices. The studies mostly agree that government payments and other types of policy support are significant in explaining land prices and account for a large share of them. In October 2011, the European Commission published a new policy proposal for the common agricultural policy (CAP) up to 2020. The proposed regulation includes a shift from historical to regional payments. The objective of this paper is to provide an ex ante analysis of the impact of the new CAP policy instruments on the land market. In particular, the effect of the regionalisation of payments in Italy is examined. The analysis is based on the use of a mathematical programming model to simulate the changes in land demand for a farm in Emilia Romagna. The results highlight the relevance of the new policy mechanism in determining a change in land demand. Yet the effect is highly dependent on initial ownership of entitlements under the historical payment scheme.

Farm/Household-Level Simulation: Results of Testing Policy and Other Scenarios. Factor Markets Working Document No. 54, June 2013

Among the different production factors, land is the one that most often limits farm development and one of the most studied. The connection between policy and other context variables and land markets is at the core of the policy debate, including the present reform of the Common Agricultural Policy. The proposal of the latter has been published in October 2011 and in Italy it will include the switch of the payment regime from an historical to a regional basis. The authors’ objective is to simulate the impact of the proposed policy reform on the land market, particularly on land values and propensity to transaction. They combine insights and data from a farm household investment model revised and extended in order to simulate the demand curve for land in different policy scenarios and a survey of farmers stated intention carried out in the province of Bologna (Italy) in 2012. Based on these results, the authors calibrate a mathematical programming model of land market exchanges for the province of Bologna and use this model form simulation. The results of the model largely corroborate the results from the survey and both hint at a relevant reaction of the land demand and supply to the shift from the historical to the regionalised payments. As effect, the regionalisation would result in increased rental prices and in a tendency to the re-allocation of land.

Alternative scenarios for federal transportation policy. Volume I - first year final report.

Transportation Department, Office of University Research, Washington, D.C.

Hydro-Meteorology and Water Budget of the Mara River Basin Under Land Use Change Scenarios

Mara is a transboundary river located in Kenya and Tanzania and considered to be an important life line to the inhabitants of the Mara-Serengeti ecosystem. It is also a source of water for domestic water supply, irrigation, livestock and wildlife. The alarming increase of water demand as well as the decline in the river flow in recent years has been a major challenge for water resource managers and stakeholders. This has necessitated the knowledge of the available water resources in the basin at different times of the year. Historical rainfall, minimum and maximum stream flows were analyzed. Inter and intra-annual variability of trends in streamflow are discussed. Landsat imagery was utilized in order to analyze the land use land cover in the upper Mara River basin. The semi-distributed hydrological model, Soil and Water Assessment Tool (SWAT) was used to model the basin water balance and understand the hydrologic effect of the recent land use changes from forest-to-agriculture. The results of this study provided the potential hydrological impacts of three land use change scenarios in the upper Mara River basin. It also adds to the existing literature and knowledge base with a view of promoting better land use management practices in the basin.

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.

From local scenarios to national maps: a participatory framework for envisioning the future of Tanzania

Tackling societal and environmental challenges requires new approaches that connect top-down global oversight with bottom-up subnational knowledge. We present a novel framework for participatory development of spatially explicit scenarios at national scale that model socioeconomic and environmental dynamics by reconciling local stakeholder perspectives and national spatial data. We illustrate results generated by this approach and evaluate its potential to contribute to a greater understanding of the relationship between development pathways and sustainability. Using the lens of land use and land cover changes, and engaging 240 stakeholders representing subnational (seven forest management zones) and the national level, we applied the framework to assess alternative development strategies in the Tanzania mainland to the year 2025, under either a business as usual or a green development scenario. In the business as usual scenario, no productivity gain is expected, cultivated land expands by ~ 2% per year (up to 88,808 km²), with large impacts on woodlands and wetlands. Despite legal protection, encroachment of natural forest occurs along reserve borders. Additional wood demand leads to degradation, i.e., loss of tree cover and biomass, up to 80,426 km² of wooded land. The alternative green economy scenario envisages decreasing degradation and deforestation with increasing productivity (+10%) and implementation of payment for ecosystem service schemes. In this scenario, cropland expands by 44,132 km² and the additional degradation is limited to 35,778 km². This scenario development framework captures perspectives and knowledge across a diverse range of stakeholders and regions. Although further effort is required to extend its applicability, improve users’ equity, and reduce costs the resulting spatial outputs can be used to inform national level planning and policy implementation associated with sustainable development, especially the REDD+ climate mitigation strategy.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers' consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed. (C) 2016 Elsevier Ltd. All rights reserved.

Renewable energy scenarios for South Karelia – non-industrial energy demands

Tässä diplomityössä tarkastellaan täysin uusiutuvaa energiajärjestelmää Etelä-Karjalan maakunnan alueella, mikä onkin jo tällä hetkellä Suomen uusiutuvin maakunta. Diplomityössä tarkastellaan julkisen sektorin, liikenteen ja rakennusten energian kulutusta mutta teollisuuden energiankäyttö jätetään tarkastelun ulkopuolelle. Työssä tutustutaan tämän hetken Etelä-Karjalan energiajärjestelmään ja sen perusteella tehdään referenssi-skenaario. Tulevaisuuden skenaariot tehdään vuosille 2030 ja 2050. Tulevaisuuden skenaarioissa muutos keskittyy järjestelmän sähköistymiseen ja uusiutuvien tuotantomuotojen integroimiseen järjestelmään. Sähköistyminen kasvattaa sähkönkulutusta, joka pyritään kattamaan uusiutuvilla tuotantomuodoilla, lähinnä tuuli- ja aurinkovoimalla. Liikennesektori rajataan kumipyöräliikenteeseen ja sen muutos tulee olemaan haastavin ja aikaa vievin. Muutokseen pyritään liikennepolttoaineiden tuotannolla maakunnassa sekä sähköautoilulla. Uusiutuva energiajärjestelmä tarvitsee tuotannon ja kysynnän joustoa sekä älyä järjestelmältä. Työssä tarkastellaan myös järjestelmän kustannuksia sekä työllisyysvaikutuksia.

The impact of Portuguese demographic changes on the demand and supply of blood in the region of Algarve

Dissertação de Mastrado, Gestão de Unidades de Saúde, Faculdade de Economia, Universidade do Algarve, 2016

Water Demand and Allocation in the Mara River Basin, Kenya/Tanzania in the Face of Land Use Dynamics and Climate Variability

The Mara River Basin (MRB) is endowed with pristine biodiversity, socio-cultural heritage and natural resources. The purpose of my study is to develop and apply an integrated water resource allocation framework for the MRB based on the hydrological processes, water demand and economic factors. The basin was partitioned into twelve sub-basins and the rainfall runoff processes was modeled using the Soil and Water Assessment Tool (SWAT) after satisfactory Nash-Sutcliff efficiency of 0.68 for calibration and 0.43 for validation at Mara Mines station. The impact and uncertainty of climate change on the hydrology of the MRB was assessed using SWAT and three scenarios of statistically downscaled outputs from twenty Global Circulation Models. Results predicted the wet season getting more wet and the dry season getting drier, with a general increasing trend of annual rainfall through 2050. Three blocks of water demand (environmental, normal and flood) were estimated from consumptive water use by human, wildlife, livestock, tourism, irrigation and industry. Water demand projections suggest human consumption is expected to surpass irrigation as the highest water demand sector by 2030. Monthly volume of water was estimated in three blocks of current minimum reliability, reserve (>95%), normal (80–95%) and flood (40%) for more than 5 months in a year. The assessment of water price and marginal productivity showed that current water use hardly responds to a change in price or productivity of water. Finally, a water allocation model was developed and applied to investigate the optimum monthly allocation among sectors and sub-basins by maximizing the use value and hydrological reliability of water. Model results demonstrated that the status on reserve and normal volumes can be improved to ‘low’ or ‘moderate’ by updating the existing reliability to meet prevailing demand. Flow volumes and rates for four scenarios of reliability were presented. Results showed that the water allocation framework can be used as comprehensive tool in the management of MRB, and possibly be extended similar watersheds.