Fighting tax evasion: a cellular automata approach

Estudio de la dinámica de una población donde los individuos son contribuyentes (pagadores de impuestos) o no mediante un autómata celular 2D

User benefit assessment by a dynamic LUTI model for Madrid

Assessing users’ benefit in a transport policy implementation has been studied by many researchers using theoretical or empirical measures. However, few of them measure users’ benefit in a different way from the consumer surplus. Therefore, this paper aims to assess a new measure of user benefits by weighting consumer surplus in order to include equity assessment for different transport policies simulated in a dynamic middle-term LUTI model adapted to the case study of Madrid. Three different transport policies, including road pricing, parking charge and public transport improvement have been simulated through the Metropolitan Activity Relocation Simulator, MARS, the LUTI calibrated model for Madrid). A social welfare function (WF) is defined using a cost benefit analysis function that includes mainly costs and benefits of users and operators of the transport system. Particularly, the part of welfare function concerning the users, (i.e. consumer surplus), is modified by a compensating weight (CW) which represents the inverse of household income level. Based on the modified social welfare function, the effects on the measure of users benefits are estimated and compared with the old WF ́s results as well. The result of the analysis shows that road pricing leads a negative effect on the users benefits specially on the low income users. Actually, the road pricing and parking charge implementation results like a regressive policy especially at long term. Public transport improvement scenario brings more positive effects on low income user benefits. The integrated (road pricing and increasing public services) policy scenario is the one which receive the most user benefits. The results of this research could be a key issue to understanding the relationship between transport systems policies and user benefits distribution in a metropolitan context.

Localización óptima de una planta de bioetanol a partir de tubérculos de pataca (Helianthus tuberosus l.) en la Cuenca del Duero

El objetivo del presente trabajo es determinar la localización óptima de una planta de producción de 30.000 m3/año de bioetanol a partir de tubérculos de pataca (Helianthus tuberosus L.) cultivada en regadío, en tierras de barbecho de la Cuenca Hidrográfica del Duero (CH Duero). Inicialmente se elaboró, a partir de datos bibliográficos, un modelo de producción de pataca en base a una ecuación de regresión que relaciona datos experimentales de rendimientos de variedades tardías con variables agroclimáticas. Así se obtuvo una función de producción basada en la cantidad de agua disponible (precipitación efectiva + dosis de riego) y en la radiación global acumulada en el periodo brotación‐senescencia del cultivo. A continuación se estima la superficie potencial de cultivo de pataca en la CH Duero a partir de la superficie arable en regadío cartografiada por el Sistema de Ocupación del Suelo (SIOSE), a la cual se le aplican, en base a los requerimientos del cultivo, unas restricciones climáticas, edafológicas, topográficas y logísticas mediante el uso de Sistemas de Información Geográfica (SIG). La proporción de superficie de regadío restringida se cuantifica a escala municipal con el fin de calcular la superficie de barbecho en regadío apta para el cultivo de pataca. A partir de las bases de datos georreferenciadas de precipitación, radiación global, y la dotación de agua para el riego de cultivos no específicos establecida en el Plan Hidrológico de la Cuenca del Duero a escala comarcal, se estimó la producción potencial de tubérculos de pataca sobre la superficie de barbecho de regadío según el modelo de producción elaborado. Así, en las 53.360 ha de barbecho en regadío aptas para el cultivo de pataca se podrían producir 3,8 Mt de tubérculos al año (80 % de humedad) (761.156 t ms/año) de los que se podría obtener 304.462 m3/año de bioetanol, considerando un rendimiento en la transformación de 12,5 kg mf/l de etanol. Se estiman los costes de las labores de cultivo de pataca así como los costes de la logística de suministro a una planta de transformación considerando una distancia media de transporte de 25 km, en base a las hojas de cálculo de utilización de aperos y maquinaria agrícola oficiales del Ministerio de Agricultura, Alimentación y Medio Ambiente (MAGRAMA). Considerando el balance de costes asociados a la producción de bioetanol (costes de transformación, distribución y transporte del producto, costes estructurales de la planta, ahorro de costes por la utilización de las vinazas generadas en el proceso como fertilizante y un beneficio industrial), se ha estimado que el coste de producción de bioetanol a partir de tubérculos de pataca asciende a 61,03 c€/l. Se calculan los beneficios fiscales para el Estado por el cultivo de 5.522 ha de pataca que suministren la materia prima necesaria para una planta de bioetanol de 30.000 m3/año, en concepto de cotizaciones a la Seguridad Social de los trabajadores, impuestos sobre el valor añadido de los productos consumidos, impuesto sobre sociedades y ahorro de las prestaciones por desempleo. Se obtuvieron unos beneficios fiscales de 10,25 c€ por litro de bioetanol producido. El coste de producción de bioetanol depende del rendimiento de tubérculos por hectárea y de la distancia de transporte desde las zonas de producción de la materia prima hasta la planta. Se calculó la distancia máxima de transporte para que el precio de coste del bioetanol producido sea competitivo con el precio de mercado del bioetanol. Como resultado se determinó que el precio del bioetanol (incluido un beneficio industrial del 15%) de la planta sería igual o inferior al precio de venta en el mercado (66,35 c€/l) con una distancia máxima de transporte de 25 km y un rendimiento mínimo del cultivo de 60,1 t mf/ha. Una vez conocido el área de influencia de la planta según la distancia de transporte máxima, se determinó la localización óptima de la planta de producción de bioetanol mediante un proceso de ubicación‐asignación realizado con SIG. Para ello se analizan los puntos candidatos a la ubicación de la planta según el cumplimiento de unos requerimientos técnicos establecidos (distancia a fuentes de suministro eléctrico y de recursos hídricos, distancia a estaciones de ferrocarril, distancia a núcleos urbanos y existencia de Espacios Naturales Protegidos) que minimizan la distancia de transporte maximizando la cantidad de biomasa disponible según la producción potencial estimada anteriormente. Por último, la superficie destinada al cultivo de pataca en el área de influencia de la planta se determina en base a un patrón de distribución del cultivo alrededor de una agroindustria. Dicho patrón se ha obtenido a partir del análisis del grado de ocupación del cultivo de la remolacha en función de la distancia de transporte a la planta azucarera de Miranda de Ebro (Burgos). El patrón resultante muestra que la relación entre el grado de ocupación del suelo por el cultivo y la distancia de transporte a la planta siguen una ecuación logística. La localización óptima que se ha obtenido mediante la metodología descrita se ubica en el municipio leonés de El Burgo Ranero, donde la producción potencial de tubérculos de pataca en la superficie de barbecho situada en un radio de acción de 25 km es de 375.665 t mf/año, superando las 375.000 t mf requeridas anualmente por la planta de bioetanol. ABSTRACT Jerusalem artichoke (Helianthus tuberosus L.) is a harsh crop with a high potential for biomass production. Its main use is related to bioethanol production from the carbohydrates, inulin mainly, accumulated in its tubers at the end of the crop cycle. The aerial biomass could be used as solid biofuel to provide energy to the bioethanol production process. Therefore, Jerusalem artichoke is a promising crop as feedstock for biofuel production in order to achieve the biofuels consumption objectives established by the Government of Spain (PER 2011‐2020 and RDL 4/2013) and the European Union (Directive 2009/28/EC). This work aims at the determination of the optimal location for a 30,000 m3/year bioethanol production plant from Jerusalem artichoke tubers in the Duero river basin. With this purpose, a crop production model was developed by means of a regression equation that relates experimental yield data of late Jerusalem artichoke varieties with pedo‐climatic parameters from a bibliographic data matrix. The resulting crop production model was based on the crop water availability (including effective rainfall and irrigation water supplied) and on global radiation accumulated in the crop emergence‐senescence period. The crop potential cultivation area for Jerusalem artichoke in the Duero basin was estimated using the georeferenced irrigated arable land from the “Sistema de Ocupación del Suelo” (SIOSE) of Spain. Climatic, soil, slope and logistic restrictions were considered by means of Geographic Information Systems (GIS). The limited potential growing area was then applied to a municipality scale in order to calculate the amount of fallow land suitable for Jerusalem artichoke production. Rainfall and global radiation georeferenced layers as well as data of irrigation water supply for crop production (established within the Duero Hydrologic Plan) were use to estimate the potential production of Jerusalem artichoke tubers in the suitable fallow land according to the crop production model. As a result of this estimation, there are 53,360 ha of fallow land suitable for Jerusalem artichoke production in the Duero basin, where 3.8 M t fm/year could be produced. Considering a bioethanol processing yield of 12.5 kg mf per liter of bioethanol, the above mentioned tuber potential production could be processed in 304,462 m3/year of bioethanol. The Jerusalem crop production costs and the logistic supply costs (considering an average transport distance of 25 km) were estimated according to official agricultural machinery cost calculation sheets of the Minister of Agriculture of Spain (MAGRAMA). The bioethanol production cost from Jerusalem artichoke tubers was calculated considering bioethanol processing, transport and structural costs, industrial profits as well as plant cost savings from the use of vinasses as fertilizer. The resulting bioetanol production cost from Jerusalem artichoke tubers was 61.03 c€/l. Additionally, revenues for the state coffers regarding Social Security contributions, added value taxes of consumed raw materials, corporation tax and unemployment benefit savings due to the cultivation of 5,522 ha of Jerusalem artichoke for the 30.000 m3/year bioethanol plant supply were calculated. The calculated revenues amounted to 10.25 c€/l. Bioethanol production cost and consequently the bioethanol plant economic viability are strongly related to the crop yield as well as to road transport distance from feedstock production areas to the processing plant. The previously estimated bioethanol production cost was compared to the bioethanol market price in order to determine the maximum supply transport distance and the minimum crop yield to reach the bioethanol plant economic viability. The results showed that the proposed plant would be economically viable at a maximum transport distance of 25 km and at a crop yield not less than 60.1 t fm/ha. By means of a GIS location‐allocation analysis, the optimal bioethanol plant location was determined. Suitable candidates were detected according to several plant technical requirements (distance to power and water supply sources, distance to freight station, and distance to urban areas and to Natural Protected Areas). The optimal bioethanol plant location must minimize the supply transport distance whereas it maximizes the amount of available biomass according to the previously estimated biomass potential production. Lastly, the agricultural area around the bioethanol plant finally dedicated to Jerusalem artichoke cultivation was planned according to a crop distribution model. The crop distribution model was established from the analysis of the relation between the sugar beet (Beta vulgaris L.) cropping area and the road transport distance from the sugar processing plant of Miranda de Ebro (Burgos, North of Spain). The optimal location was situated in the municipality of ‘El Burgo Ranero’ in the province of León. The potential production of Jerusalem artichoke tubers in the fallow land within 25 km distance from the plant location was 375,665 t fm/year, which exceeds the amount of biomass yearly required by the bioethanol plant.

A Cost-Benefit analysis model for technical debt management considering uncertainty and time

In the last few years, technical debt has been used as a useful means for making the intrinsic cost of the internal software quality weaknesses visible. This visibility is made possible by quantifying this cost. Specifically, technical debt is expressed in terms of two main concepts: principal and interest. The principal is the cost of eliminating or reducing the impact of a, so called, technical debt item in a software system; whereas the interest is the recurring cost, over a time period, of not eliminating a technical debt item. Previous works about technical debt are mainly focused on estimating principal and interest, and on performing a cost-benefit analysis. This cost-benefit analysis allows one to determine if to remove technical debt is profitable and to prioritize which items incurring in technical debt should be fixed first. Nevertheless, for these previous works technical debt is flat along the time. However the introduction of new factors to estimate technical debt may produce non flat models that allow us to produce more accurate predictions. These factors should be used to estimate principal and interest, and to perform cost-benefit analysis related to technical debt. In this paper, we take a step forward introducing the uncertainty about the interest, and the time frame factors so that it becomes possible to depict a number of possible future scenarios. Estimations obtained without considering the possible evolution of the interest over time may be less accurate as they consider simplistic scenarios without changes.

3D simulation of complex shading affecting PV systems taking benefit from the power of graphics cards developed for the video game industry

Shading reduces the power output of a photovoltaic (PV) system. The design engineering of PV systems requires modeling and evaluating shading losses. Some PV systems are affected by complex shading scenes whose resulting PV energy losses are very difficult to evaluate with current modeling tools. Several specialized PV design and simulation software include the possibility to evaluate shading losses. They generally possess a Graphical User Interface (GUI) through which the user can draw a 3D shading scene, and then evaluate its corresponding PV energy losses. The complexity of the objects that these tools can handle is relatively limited. We have created a software solution, 3DPV, which allows evaluating the energy losses induced by complex 3D scenes on PV generators. The 3D objects can be imported from specialized 3D modeling software or from a 3D object library. The shadows cast by this 3D scene on the PV generator are then directly evaluated from the Graphics Processing Unit (GPU). Thanks to the recent development of GPUs for the video game industry, the shadows can be evaluated with a very high spatial resolution that reaches well beyond the PV cell level, in very short calculation times. A PV simulation model then translates the geometrical shading into PV energy output losses. 3DPV has been implemented using WebGL, which allows it to run directly from a Web browser, without requiring any local installation from the user. This also allows taken full benefits from the information already available from Internet, such as the 3D object libraries. This contribution describes, step by step, the method that allows 3DPV to evaluate the PV energy losses caused by complex shading. We then illustrate the results of this methodology to several application cases that are encountered in the world of PV systems design. Keywords: 3D, modeling, simulation, GPU, shading, losses, shadow mapping, solar, photovoltaic, PV, WebGL