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In this paper the performance of different Machine Learning and Deep Learning approaches is evaluated in problems related to green mobility in big cities. Specifically, the forecasting of bike sharing demand in Madrid and Barcelona (Spain) is approached, for different prediction time-horizons, and also a problem of cable car demand forecasting in Madrid city. An important number of predictive variables are considered, which are grouped into four different sets (categorical/calendrical, persistence-based, meteorological and, as a novelty of the paper, information about analogue past instances), whose relevance is studied for all cases. A feature selection mechanism is also incorporated in order to improve the prediction accuracy of the proposed algorithms. A total of 12 different multivariate regression techniques are implemented, covering from Machine Learning methods to time-series Deep Learning approaches. Excellent results in all the prediction problems approached are reported. Finally, the consequences of obtaining accurate prediction in these three problem of green mobility in big cities are discussed. In addition, it is studied how the results could be exported to other similar cases in more general urban mobility studies. Novelties of the work include: (1) Addressing the forecast problem of passenger flow on a cable car using ML and DL multivariate techniques; (2) using the demand of analogous past instances as an additional feature to solve the demand prediction problems; and (3) the extraction of global conclusions about feature relevance when addressing a demand forecasting problem in green mobility. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the position value as a centrality measure to evaluate the relevance of the edges and players in a network, with the additional advantage that this value integrates the degree measure of each player in it. In fact, in the real world, it is particularly important to consider the natural influence of connections of a player in a network. Its applications were very limited in real-world situations due to the high computational complexity of exactly obtaining this value. With the aim of solving this problem we provide a method, based on sampling theory, to estimate the position value, which is analyzed in terms of the theoretical properties of the resulting estimator. Moreover, we establish specific statistical results for bounding the absolute error in this approximation. It is important to emphasize that this approach allows for obtaining rankings not only of the nodes but also of the edges of the network. To illustrate the advantages and interest of the proposed methodology, as well as the variety of problems that can be analyzed in this framework, we applied it in three very different settings, the suburban train network of Madrid in the year 2000, the Spanish national team in a match against Portugal, and the Zerkani network responsible for the terrorist attacks of Paris (2015) and Brussels (2016). • The position value gives a measure of the relevance of the links and players in a network. • We rank the members of networks using the position value. • Sampling techniques are used to solve the computational drawbacks in these settings. • As an application, we rank the Spanish national team and the Zerkani network. [ABSTRACT FROM AUTHOR]

Improving the management of the urban water cycle can reduce greenhouse gas emissions and contribute to climate change mitigation in cities. Stormwater in urban areas has traditionally been collected and conveyed to sewage treatment plants, a practice that has continued with the need to manage increased superficial flow. This paper presents the Low Impact Development (LID) measures to improve water management in the new urban development of Valdebebas in Madrid, and the associated benefits. Stormwater was considered a sub cycle; by shortening the water cycle the local use of rainwater was achieved while reducing energy costs and greenhouse gas emissions for off-site treatment. The article analyses the urban water cycle from a preventive approach. It considers how urban design features such as topography and pavement selection were used to convey surface water from impermeable areas to permeable ones (vegetated or permeable pavements) and the infiltration of water into engineered soil, reducing the need for off-site conveyance infrastructure, and the amount of water discharged into municipal treatment installations. Moreover, the captured water increases soil water content available for plants and trees which play an important role in absorbing CO 2 . Water exceeding soil capacity is collected in the subsurface Sustainable Drainage system (SuDS), including infiltration boxes where water is temporarily stored before moving through the soil toward ground water reserves. This paper describes the approaches and criteria used to design a large scale SuDS infrastructure in the district of Valdebebas, in northeastern Madrid (Spain), and analyses its performance, followed by a comparison with the predictions under three climate change scenarios, which consider not only the variation in peak flows and runoff, but also the reduction in GHG emissions. Additionally, it presents a sensitivity analysis for the main variables in the design of SuDS, and a multicriteria analysis, to compare the different drainage systems. [ABSTRACT FROM AUTHOR]

The grandstands of La Zarzuela Racecourse in Madrid designed by the engineer E. Torroja and the architects C. Arniches and M. Dominguez are one of the world’s most outstanding concrete constructions of the first half of the 20th century. This paper describes the design competition and the conceptual design process that led to their construction and carries out a critical assessment of the grandstands from the perspective of Structural Art. By doing so, the paper helps to develop the discipline of structural criticism, and points out lessons learned from their design and construction process which should not be forgotten at the present time, such as: (a) the importance of design competitions; (b) the fact that the pursuit of economy and efficiency can actually improve the quality and aesthetics of the design; (c) the importance of combining logical reasoning based on technical criteria with imagination to achieve excellence in structural design; and (d) the importance of estimating structural behavior by simple formulas and of learning from both existing structures and experimental models. [ABSTRACT FROM AUTHOR]

Accessibility is an essential concept widely used to evaluate the impact of transport and land-use strategies in urban planning and policy making. Accessibility is typically evaluated by using separately a transport model or a land-use model. This paper embeds two accessibility indicators (i.e., potential and adaptive accessibility) in a land use and transport interaction (LUTI) model in order to assess transport policies implementation. The first aim is to define the adaptive accessibility, considering the competition factor at territorial level (e.g. workplaces and workers). The second aim is to identify the optimal implementation scenario of policy measures using potential and adaptive accessibility indicators. The analysis of the results in terms of social welfare and accessibility changes closes the paper. Two transport policy measures are applied in Madrid region: a cordon toll and increase bus frequency. They have been simulated through the MARS model (Metropolitan Activity Relocation Simulator, i.e. LUTI model). An optimisation procedure is performed by MARS for maximizing the value of the objective function in order to find the optimal policy implementation (first best). Both policy measures are evaluated in terms of accessibility. Results show that the introduction of the accessibility indicators (potential and adaptive) influence the optimal value of the toll price and bus frequency level, generating different results in terms of social welfare. Mapping the difference between potential and adaptive accessibility indicator shows that the main changes occur in areas where there is a strong competition among different land-use opportunities. [ABSTRACT FROM AUTHOR]

The Basque Y High Speed Rail connection between Madrid and the Basque Autonomous Community is, quite exceptionally, a mixed freight and passengers HSR line, that has been presented as a fundamental step towards a more sustainable mobility. In this paper, a life-cycle assessment (LCA) is conducted to assess the environmental performance of the line throughout its lifetime, based on the latest data available, including both construction and maintenance burdens. Results show that this new corridor is not justified in terms of reducing emissions and energy consumption, mainly due to its low transport density. It also has a negligible impact on Spanish current low rail freight traffic. We conclude, therefore, that Spain needs to reconsider its AVE network expansion if aiming at increasing rail's modal share and meeting the emissions targets set by the EU. From a policy perspective, many information inconsistencies have been found regarding the demand projections of freight transport, which cast serious doubt about the decision-making process behind Trans-European transport projects. [Display omitted] • Life-cycle assessment (LCA) of the Basque Y high-speed rail line under construction in 2023. • It verifies whether this project is justified in terms of environmental impacts reductions. • Net balance of the Basque Y high-speed rail is very modest, when not detrimental. • This project would not be justified in terms of environmental impacts reductions. • Alternatives to high-speed rail in the transport hierarchy provide better environmental balance. [ABSTRACT FROM AUTHOR]

While air transport brings very significant economic and social benefits to the cities and regions served by airports, aircraft noise is the single major cause of community opposition to airport operations, becoming a critical issue that affects the sustainability of future traffic growth. However, planning operations exclusively focusing on noise impact may result in an increase of fuel consumption or delays. This paper develops a suitable bi-objective model for landing aircraft, which finds a schedule that minimises noise impact, total fuel consumption and delays, under wake vortex separation and Constrained Position Shifting restrictions. The results of this model are compared with real operations in a major European airport to assess the potential level of improvements. By comparing with real data from Madrid-Barajas airport, the research shows potential improvements of up to 4.5% reduction of total fuel consumption (without increasing noise levels) only by modifying the sequence of arrivals, and up to 43% (without extra fuel consumption) of reduction in noise impact over the populations under study. • Reduce fuel consumption and delays considering CPS restrictions is possible. • Current schedule can be improved in terms of noise and fuel without changing STAR routes. • A whole Pareto frontier of better solutions in terms of noise and fuel can be easily found. • Experiments using Madrid airport showed significant improvements vs. current operation. • Congestion has a big influence in the possibilities of scheduling improvement. [ABSTRACT FROM AUTHOR]

Abstract Climate change is expected to increase the frequency and duration of hot weather and its associated adverse health effects. In dense urban areas, these phenomena will be exacerbated by the Urban Heat Island (UHI) effect and indoor overheating. This paper assesses population exposure and vulnerability to high summer temperatures by exploring the geospatial connection between the UHI, housing energy efficiency and overheating risk, and social vulnerability indicators, such as income and the elderly population. Focusing on Madrid and London, two European cities with strong UHIs but contrasting drivers of indoor heat risk, the spatial distribution of selected indicators were analysed by means of Geographical Information Systems, and areas with the highest vulnerability towards summer energy poverty were identified. It was found that while 'hot and vulnerable' areas are present in both Madrid and London, there are significant differences in climate, socioeconomic distribution and housing between the two cities. In warmer climates such as Madrid, energy poverty—traditionally defined by wintertime heating—requires its definition to be broadened to include summertime cooling needs; in the context of climate change and urban warming trends, this may soon also be the case in northern cities such as London. [ABSTRACT FROM AUTHOR]

Abstract: This paper analyzes the mass size distribution of some inorganic species present in the atmospheric aerosol from a field campaign carried out in Madrid throughout a complete year (February 2007–February 2008). Samplings were performed by means of a micro-orifice uniform deposit impactor (MOUDI). Ambient air was sampled during consecutive nocturnal and diurnal periods, and diurnal/nocturnal behaviors were compared for the twenty night-day sampling pairs that were gathered. Annual and seasonal averages were obtained, and some case studies under specific atmospheric conditions are discussed in the paper. Results have shown that the sulfate and ammonium mass was concentrated in the accumulation mode, between 0.18 and 0.56μm, so that gas-phase and condensation processes for secondary aerosol formation prevailed during the sampling periods in this area. An exception to this behavior was found during a fog event when distributions for these two species were centered in the 0.56–1 and 1–1.8μm size stages, corresponding to the droplet mode. In most of the samples, the ammonium mass measured in these size ranges was enough or almost enough to neutralize inorganic acidity by formation of ammonium sulfate and nitrate. However, a significant sulfate mass not neutralized by ammonium was found in the impactor backup quartz filter (aerodynamic diameter<0.056μm). The concentration of this sulfate and its contribution to the ultrafine fraction mass was higher under good dispersive conditions, prevailing in summer, when particle growth processes are not so favored due to the higher atmospheric dilution factors. The origin of this ultrafine sulfate has been attributed to direct emissions from traffic, associated to the nucleation mode. Regarding the nitrate concentration, it was found higher in the coarse mode than in the accumulation mode on an annual basis. The highest concentrations were measured in winter episodic situations. The marked seasonal variability shown in the accumulation mode by this species is related to the volatility of ammonium nitrate. Among all the studied ions, nitrate also presented the highest differences between the diurnal and nocturnal concentrations in all size ranges. This is probably related to the short time scale required for its formation from gaseous precursors. [Copyright &y& Elsevier]

To evaluate a specific form of resource management, for example, the maintenance of valuable cultural landscapes, the contributions of many different viewpoints must be considered. In this paper, a model for assessing and integrating the different aspects contributing to landscape evaluation is proposed. Some results of its use in landscape assessment in the Madrid region (central Spain) are discussed.The model takes into account five assessment dimensions which are considered to be independent—the ecological, productive, economic, social and cultural evaluative systems and it recognises and assumes conflicts and trade-offs between these components. The inclusion of the production system as an independent assessment dimension is original and is justified because it is the link that connects the ecological and economic systems. Since this dimension acts most directly on the ecosystem, the production system includes the attribute of ecological or strong (in the sense of [For the Common Good, Beacon Press, Boston, 1994]) sustainability.The evaluation method places special emphasis on defining a conceptual framework, and from this defines scenarios in comparison with which particular development models (landscape planning, resources management) can be evaluated. Seven scenarios, coming from a hypothetical, traditional sustainable scenario of resources management, are defined. One of these, the sound sustainable scenario, is defended as the only one viable in the long term, particularly in developing countries.This method was employed to evaluate the agricultural and natural landscape of the Madrid region municipalities. The multivariate approach adopted was based on the selection of indicator sets for each evaluative dimension. The structure of relationships among indicators was then analysed separately for each dimension and values assigned to the municipalities according to their position on the main axes of the multivariate analyses. Each municipality was assigned to one of the seven development scenarios by means of discriminant analysis. The approach’s greatest assets are its flexibility in the selection of the indicators and the efficacy in its monitoring and comparison of the different analysed cases once a rigorous conceptual framework was established.The paper discusses the conditions for the sustainability of the human activities and provides a method for evaluating and comparing scenarios of resources management. [Copyright &y& Elsevier]

Aircraft icing is one of the most dangerous weather phenomena in aviation security. Therefore, avoiding areas with high probability of icing episodes along arrival and departure routes to airports is strongly recommended. Although such icing is common, forecasting and observation are far from perfect. This paper presents an analysis of an aircraft icing and turbulence event including a commercial flight near the Guadarrama Mountains, during the aircraft approach to the airport. No reference to icing or turbulence was made in the pre-flight meteorological information provided to the pilot, highlighting the need for additional tools to predict such risks. For this reason, the icing episode is simulated by means of the Weather Research and Forecasting (WRF) model and analyzed using images from the Meteosat Second Generation (MSG) satellite, with the aim of providing tools for the detection of icing and turbulence in the airport vicinity. The WRF simulation shows alternating updrafts and downdrafts (> 2 m s − 1 ) on the lee side of the mountain barrier. This is consonant with moderate to strong turbulence experienced by the aircraft on its approach path to the airport and suggests clear air turbulence above the mountain wave cloud top. At the aircraft icing altitude, supercooled liquid water associated with orographic clouds and mountain waves is simulated. Daytime and nighttime MSG images corroborated the simulated mountain waves and associated supercooled liquid water. The results encourage the use of mesoscale models and MSG nowcasting information to minimize aviation risks associated with such meteorological phenomena. [ABSTRACT FROM AUTHOR]

A change of focus from the current production-based Greenhouse Gas (GHG) emissions inventory to an integrated production-consumption carbon accounting system would improve the quality of city-level inventories. London is one of the few cities in the world which has reported its GHG emission inventory using Consumption-Based (CB) methodologies. Although Madrid has adopted the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories (GPC) to report their GHG emissions, the city has never officially reported its GHG inventory using CB methodologies. Thus, the goal of this study is to analyze the challenges that must be faced by the production-based GHG emission inventory of Madrid in order to estimate GHG emissions from their supply chains and final consumers using the London's GHG emissions inventory experience. From the comparison between the 2010 GHG emission inventories of Madrid and London some challenges could emerge that Madrid's decision-makers might need to face regarding urban carbon accounting practices. As results, this paper shows that if GHG emissions from urban supply chains and final consumers are considered, the total GHG emissions reported by the Madrid inventory could double. This increase is similar to what London experienced when comparing production-based and integrated production-consumption GHG inventories. Besides, some difficulties related to lack of information were found when estimating GHG emissions associated with those goods and services consumed in Madrid. It would be useful to develop a full CB inventory using environmentally extended input-output (EEIO) matrices, more city-level primary data, and local cradle-to-grave factors, following the methodology applied by the London inventory. These actions would allow a more accurate calculation of urban supply chains and final consumer GHG emissions in Madrid. Finally, further research is recommended in order to improve the current knowledge about the contributions of the energy, transport and waste sectors to GHG emissions in both, Madrid and London. [ABSTRACT FROM AUTHOR]

The increase of road traffic in large cities during the last years has produced that long and short-term traffic flow forecasting is a critical need for the authorities. The availability of good traffic flow prediction methods is a must to make informed decisions concerning (punctual) traffic congestions. Previous work has shown that the accuracy of these methods decreases if we consider urban traffic and long-term predictions. In this paper we present a hybrid model, combining a Convolutional Neural Network and a Bidirectional Long–Short-Term Memory network, and apply it to long-term traffic flow prediction in urban routes. This model combines the capability of CNN to extract hidden valuable features from the input model and the capability of BiLSTM to understand the temporal context. In order to assess the usefulness of our model, we considered four streets of the city of Madrid with different characteristics and compared the results of our proposed model with the ones obtained by eight widely used baseline models. The results show that our hybrid model outperforms the baseline models with respect to three metrics commonly used in regression: mean absolute error, root mean squared error and accuracy. [ABSTRACT FROM AUTHOR]

This paper presents a new unsupervised change detection methodology for multispectral images applied to specific land covers. The proposed method involves comparing each image against a reference spectrum, where the reference spectrum is obtained from the spectral signature of the type of coverage you want to detect. In this case the method has been tested using multispectral images (SPOT5) of the community of Madrid (Spain), and multispectral images (Quickbird) of an area over Indonesia that was impacted by the December 26, 2004 tsunami; here, the tests have focused on the detection of changes in vegetation. The image comparison is obtained by applying Spectral Angle Mapper between the reference spectrum and each multitemporal image. Then, a threshold to produce a single image of change is applied, which corresponds to the vegetation zones. The results for each multitemporal image are combined through an exclusive or (XOR) operation that selects vegetation zones that have changed over time. Finally, the derived results were compared against a supervised method based on classification with the Support Vector Machine. Furthermore, the NDVI-differencing and the Spectral Angle Mapper techniques were selected as unsupervised methods for comparison purposes. The main novelty of the method consists in the detection of changes in a specific land cover type (vegetation), therefore, for comparison purposes, the best scenario is to compare it with methods that aim to detect changes in a specific land cover type (vegetation). This is the main reason to select NDVI-based method and the post-classification method (SVM implemented in a standard software tool). To evaluate the improvements using a reference spectrum vector, the results are compared with the basic-SAM method. In SPOT5 image, the overall accuracy was 99.36% and the κ index was 90.11%; in Quickbird image, the overall accuracy was 97.5% and the κ index was 82.16%. Finally, the precision results of the method are comparable to those of a supervised method, supported by low detection of false positives and false negatives, along with a high overall accuracy and a high kappa index. On the other hand, the execution times were comparable to those of unsupervised methods of low computational load. [ABSTRACT FROM AUTHOR]

Nowadays, one of the main concerns in the urban agenda of the European Union and Member States is how to adopt an integrated approach to urban challenges and needs of the consolidated city, in particular, to address the complex condition of multi-deprived neighbourhoods. Beyond the strategic integrated approaches based on economic interests perceived within the European Union, the disadvantage condition of multi-deprived areas requires an active and consistent implication of the diversity of urban players, including the affected communities themselves. This paper pursues to contribute to this urban challenge with a reflection about the social implications of massive remodelling or re-development operations of deprived localities in comparison with rehabilitation projects eluding the whole demolition-reconstruction processes. For this purpose, the social housing estates A, B and C of Fuencarral in Madrid are taken as reference case studies that represent an important lesson of the recent history of the City and the Remodelling Operation of neighbourhoods in Madrid. Fuencarral A and B units, built as temporal settlements in the late 60s, have undergone a massive remodelling intervention that has lasted more than expected; in fact, some residents complain that it is not yet concluded after more than two decades. While Fuencarral C, with somewhat higher standards, is a protected area on the General Urban Development Plan 1997 and declared as an Integrated Rehabilitation Zone (ZRI) in 2008. [ABSTRACT FROM AUTHOR]

The control of the pandemic caused by SARS-CoV-2 is a challenge for governments all around the globe. To manage this situation, countries have adopted a bundle of measures, including restrictions to population mobility. As a consequence, drivers face with the problem of obtaining fast routes to reach their destinations. In this context, some recent works combine Intelligent Transportation Systems (ITS) with big data processing technologies taking the traffic information into account. However, there are no proposals able to gather the COVID-19 health information, assist in the decision-making process, and compute fast routes in an all-in-one solution. In this paper, we propose a Pandemic Intelligent Transportation System (PITS) based on Complex Event Processing (CEP), Fuzzy Logic (FL) and Colored Petri Nets (CPN). CEP is used to process the COVID-19 health indicators and FL to provide recommendations about city areas that should not be crossed. CPNs are then used to create map models of health areas with the mobility restriction information and obtain fast routes for drivers to reach their destinations. The application of PITS to Madrid region (Spain) demonstrates that this system provides support for authorities in the decision-making process about mobility restrictions and obtain fast routes for drivers. PITS is a versatile proposal which can easily be adapted to other scenarios in order to tackle different emergency situations. [ABSTRACT FROM AUTHOR]

For the extension of the lines of the Spanish high speed railway system, a new junction has recently been created to the south of Madrid (Spain). The objective of these works was to connect the lines Madrid-Valencia and Madrid-Seville in order to be able to go directly from Seville to Valencia. The work has been undertaken in the zone of Torrejón de Velasco (Madrid province). The ground of this zone is formed by: a) Anthropic fills. b) Very soft quaternary sediments, mainly clayey soils. c) Hard clay (near substratum). The height of the necessary embankments is variable (to from 2 m to 15 m). For this reason (and proximity to the high speed railway in operation) it has been necessary to design a major ground improvement under the embankments. This paper describes: a) The geotechnical properties of the soft soil (by means of field embankment tests and other field tests). b) The design of the ground improvement. c) The instrument field data obtained during the treatment. [ABSTRACT FROM AUTHOR]

Climate change is expected to influence urban living conditions and challenge the ability of cities to adapt and mitigate climate change. This paper describes a new modelling system for climate change impact assessments on urban climate and air quality with feasible computational costs (the expected CPU time is too large for actual supercomputer platforms). The system takes the outputs from a global climate model, which are injected into a dynamical regional climate model (WRF-Chem) with the nested capability activated, with 25 km spatial resolution. In addition, the system uses a diagnostic meteorological model (CALMET) to produce urban detailed information (with 200 m spatial resolution) using this downscaling procedure. At the city level, a simplified chemical-transport model (based on CMAQ and using linear chemistry) is used to map the spatial distribution of the pollutants. The system is applied to five European cities: Madrid, Antwerp, Milan, Helsinki and London (Kensington–Chelsea area). The modelling system was used to simulate the climate and air quality for present year (2011) and future years (2030, 2050 and 2100) using 2011 emissions as control run, because we want to investigate the effects on the global climate on the actual (2011) cities. Effects on temperature, precipitation, and ozone are also considered. We compare the climate and air concentrations in future years 2030, 2050 and 2100 with the control year (2011). Comparison of simulations for present situation (using NNRP reanalysis 2011 data sets) shows acceptable agreement with measurements which give us strong confidence on the results for the RCP IPCC climate future simulations for 4.5 and 8.5 scenarios. [ABSTRACT FROM AUTHOR]

Third party certified food labelling schemes can be used to reduce asymmetric information in anonymous markets. However, in short food supply chains (SFSCs) trust linkages can be also built through direct contact between consumers and producers. This paper analyzes which type of local producers are interested in these officially recognized certifications, inferring the role that third party certified labelling schemes can play for SFSCs in the Region of Madrid (RofM). For this purpose, 71 producers were surveyed in 2018. We studied their interest in third party certifications, what food attributes they offer to consumers and their perceptions about SFSCs. Producers without interest in third party certifications not only offer direct product attributes but also inform about production methods and their characteristics as producers. Furthermore, these producers have more social and environmental ethical concerns for conventional chains, recognizing SFSCs as solutions with social, economic and environmental benefits. The findings of our study suggest that policies that promote or require existing officially recognized certifications in SFSCs may limit the participation of these committed producers. Therefore, third party certifications may not be the best strategy to support these producers in fostering a transition towards a more sustainable local food system in the RofM. • Third party certifications may not be the best strategy to foster some SFSCs. • Producers' interest in certification is not linked with SFSC perceived drawbacks. • Pro-certification producers understand SFSCs firstly as an economic strategy. • Certifications are not worthy for communicating holistically about food products. • Lack of producers' interest in certification is linked to SFSCs with direct contact. [ABSTRACT FROM AUTHOR]

• A new methodology for sensor reallocation in large scale-systems for fault isolation purposes is proposed. • From an initial set consisting of a limited number of sensors already installed in certain locations of the system, the proposed methodology produces a new sensor placement where some of the sensors are strategically reallocated in different but available places of the system. • The procedure is posed as an optimization problem where the performance index is specific of the fault isolation method to be used. • The algorithm that solves the problem is an incremental upgrading approach based in the Sequential Forward Floating Search algorithm and it combines a forward phase (where sensors are added sequentially) with a backward phase (where sensors can be individually removed from the original sensor placement). • The proposed methodology is illustrated by means of its application to the problem of leak localization in two District Metered Areas from the WDN of the metropolitan area of Madrid (Spain), using real measurements and leak scenarios. This paper presents a new methodology for sensor reallocation in large scale-systems considering fault isolation purposes. From an initial set consisting of a limited number of sensors already installed in certain locations of the system, the proposed methodology produces a new sensor placement where some of the sensors are strategically reallocated in different but available places of the system. The procedure is posed as an optimization problem where the performance index is specific of the fault isolation method to be used. The algorithm that solves the problem is an incremental upgrading approach based in the Sequential Forward Floating Search algorithm and it combines a forward phase (where sensors are added sequentially) with a backward phase (where sensors can be individually removed from the original sensor placement). The proposed methodology is illustrated by means of its application to the problem of leak localization in Water Distribution Networks (WDN), where the particular placement of the pressure sensors has a great impact in the ability to isolate the leaky node. Also, since only a limited number of pressure sensors can be installed in some nodes, space interpolation techniques must be used to estimate the pressure in the other network nodes. The performance of the localization process is measured in terms of pipe distance from the estimated leaky node candidate to the real leaky node. The proposed methodology is applied to two District Metered Areas of the WDN of a metropolitan area of Spain, in simulation and using real measurements and leak scenarios. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the analysis of the performance of a solar cooling facility along one summer season using a commercial single-effect water–lithium bromide absorption chiller aiming at domestic applications. The facility works only with solar energy using flat plate collectors and it is located at Universidad Carlos III de Madrid, Spain. The statistical analysis performed with the gathered data shows the influence of five daily operational variables on the system performance. These variables are solar energy received along the day (H) and the average values, along the operating period of the solar cooling facility (from sunrise to the end of the cold-water production), of the ambient temperature (), the wind velocity magnitude (V), the wind direction (θ) and the relative humidity (RH). First order correlation functions are given. The analysis of the data allows concluding that the most influential variables on the daily cooling energy produced and the daily averaged solar COP are H, V and θ. The period length of cold-water production is determined mainly by H and . [ABSTRACT FROM AUTHOR]

Abstract: This paper focuses on how students from China are institutionally constructed through everyday practice in a Madrid middle school, where three years’ fieldwork was conducted as part of a wider research project. Particular attention is paid to the Welcome Programme at this school, a new educational measure intended for students from a migrant background to learn Spanish before they enter mainstream classes. Taking critical sociolinguistic ethnography as a theoretical/methodological/analytical framework, interactional, discursive, and ethnographic data are used to show (a) what social identities are (re)produced and challenged through school practices, in connection with the ideological framework of the modern nation-state; (b) how these practices contribute to legitimizing a particular distribution/valuation of cultural and linguistic resources within the contemporary Spanish educational system; (c) what the institutional consequences are for these Chinese newcomer students. [Copyright &y& Elsevier]

Abstract: Damage caused to objects of cultural heritage is one of the most serious detrimental effects of air pollutants. Within the 6th Framework Programme of the EU, the CULT-STRAT project is an inter-agency, multi-disciplinary project that has integrated research and monitoring information to provide answers to policy and management questions, which relate the effects of air pollutants on heritage and the management options available to mitigate them. The overall aim of the project has been to assess and predict the effects of different pollutants on materials and objects of cultural heritage in a multipollutant scenario and to identify indicators and thresholds levels of pollutants. These have been used for development of management strategies for sustainable maintenance and preventive conservation of European Cultural Heritage and air quality policy from continental to local scale. The present paper reports one of the studies carried out in the CULT-STRAT project at city level and focused on the town of Madrid (Spain). Different maps are shown for the present and possible future scenarios (2010 and 2020): inventory of stock of cultural heritage for each selected material, concentration of selected pollutants (SO2, NO2, O3 and PM10), corrosion (cast bronze) and recession (Portland limestone), exceedance of tolerable degradation thresholds for each material and corrosion-cultural heritage overlapped maps. [Copyright &y& Elsevier]

Abstract: In recent years, ground vibrations have become an important issue due to the growing awareness of the society about environmental living conditions. In this way, vibrations caused by trains running near houses or workplaces are considered disturbing for residents. Within this framework, this paper presents a procedure to estimate the vibration path caused by the passing of a train. In order to achieve this, the equations which describe the physical phenomenon are set in the frequency and wavenumber domain and solved by using the Fourier Transform. The obtained analytical solution is transformed back into the time and space domain by means of the Fourier series. The obtained theoretical results are compared with experimental measurements carried out in the Madrid–Barcelona High Speed Line in order to analyse the performance of this procedure. [ABSTRACT FROM AUTHOR]

Abstract: In recent years, research on ozone variability has mainly focused on the analysis of its trend. Additionally some studies have analyzed the annual, seasonal and day-to-day ozone variations. However, intra-diurnal total ozone variations are notably less explored. Thus, the main objective of this paper is to analyze the diurnal variability of total ozone column (TOC) as recorded by a Brewer spectrophotometer in Madrid (Spain). The results show that about 90% of days present non-negligible diurnal variability, indicating that, in general, it should not be assumed that TOC remains constant throughout a particular day in urban areas. In addition, this variability has a notable seasonal behavior which should be considered (the spring and summer months show higher diurnal TOC variations than autumn and winter months). This pattern is likely caused by the diurnal photochemical processes in the lower troposphere related to the formation of tropospheric ozone near the earth’s surface at populated urban locations. Thus, these diurnal fluctuations in tropospheric ozone could explain part of diurnal TOC variations (between 20% and 70% depending on the mixing layer height). [Copyright &y& Elsevier]

The majority of wildfires in the Mediterranean Basin are caused directly or indirectly by human activity. Many biophysical and socioeconomic factors have been used in quantitative analyses of wildfire risk. However, the importance and effects of socioeconomic factors in spatial modelling have been given inadequate attention. In this paper, we use different approaches to spatially model our data to examine the influence of human activity on wildfire ignition in the south west of the Madrid region, central Spain. We examine the utility of choropleth and dasymetric mapping with both Euclidean and functional distance surfaces for two differently defined wildfire seasons. We use a method from Bayesian statistics, the Weights of Evidence model, and produce ten predictive maps of wildfire risk: (1) five maps for a two-month fire season combining datasets of evidence variables and (2) five maps for the four-month fire season using the same dataset combinations. We find that the models produced from a choropleth mapping approach with spatial variables using Euclidian and functional distance surfaces are the best of the ten models. Results indicate that spatial patterns of wildfire ignition are strongly associated with human access to the natural landscape. We suggest the methods and results presented will be useful to optimize wildfire prevention resources in areas where human activity and the urban–forest interface are important factors for wildfire ignition. [Copyright &y& Elsevier]

Abstract: This paper presents a decision support system for automatic keep-clear signs management. The system consists of several modules. First of all, an acquisition module obtains images using a vehicle equipped with two recording cameras. A recognition module, which is based on Support Vector Machines (SVMs), analyzes each image and decides if there is a keep-clear sign in it. The images with keep-clear signs are included into a Geographical Information System (GIS) database. Finally in the management module, the data in the GIS are compared with the council database in order to decide actions such as repairing or reposition of signs, detection of possible frauds etc. We present the first tests of the system in a Spanish city (Meco, Madrid), where the systems is being tested for its application in the near future. [Copyright &y& Elsevier]

Abstract: The aim of this paper is to carry out a comparative study with regard to energy consumption and greenhouse gas emissions, in respect of two types of engines with three different fuels. The fuels analysed are diesel, biodiesel 30% (B30) and compressed natural gas (CNG). The engines tested were a spark ignition engine (Otto cycle) and two compression ignition engines (Diesel cycle), the first fed with CNG and the last two with B30 and diesel. What is new about this study is its scope of application concerning refuse collection services in the city of Madrid. The tests were carried out on refuse trucks of the FCC Company along actual urban routes in the city of Madrid. Also taken into account were the energy input and the greenhouse gases emitted for each of the paths taken by the fuels analysed, from resource recovery to delivery to the vehicle tank. [Copyright &y& Elsevier]

Abstract: This paper analyzes the potential competition of the high-speed train with the air transport between Madrid and Barcelona. The analysis estimates disaggregated mode choice models using information provided by mixed revealed and stated preferences database. We obtained different willingness-to-pay measures for improving service quality. In general, values for travel time savings are higher for mandatory trips and increases as the level of comfort falls. We also obtained a high willingness-to-pay estimate for reductions in delay time, being higher in the case of high-speed train than for air transport. Demand responses to various policy scenarios that consider the potential competition between high-speed train and air transport are examined. [Copyright &y& Elsevier]

Abstract: Considering the number of dead people, the worst tornado in the last two centuries in Spain is presented. The words used to describe the phenomenon have hidden it to the general public and the specialist The coetaneous press and other printed sources have been revised, and this has let us know the true sense of those words as well as the sequence of the tornadic event. The synoptic situation that was presented by some European Meteorological Offices in 1886 has been revised when all available data and some indirect information have been included. Tornado track and force have been plotted on the actual map of the city following the available information in the newspapers and other documents. Other subjective comments made by the paper writers have allowed us to find out some psychological and sociological aspects used to enhance the tragic perception of their readers. [Copyright &y& Elsevier]

• We applied MFA to quantify the future energy recovery potential of MSW. • Future scenarios for the year 2030 were defined for Madrid, Spain. • The gross energy recovery potential of MSW is likely to decrease in the future. • MSW streams susceptible to energy recovery account for 48 – 60% of the MSW. • Recycling targets do not necessarily compromise energy recovery. Rules on separate collection and recycling of municipal solid waste (MSW) can have a significant impact on the waste-to-energy (WTE) industry. Understanding the future energy recovery potential of MSW is therefore paramount to establish the role of WTE technologies in waste management plans. In this study we applied material flow analysis (MFA) to systematically quantify the energy recovery potential of MSW under plausible scenarios for 2030. These scenarios describe structural changes that are expected to affect the energy recovery potential, such as the increase in the separate collection rates and the implementation of more efficient material recovery facilities (MRFs). The assessment was performed for Madrid, Spain, as a case study. The results reveal that the gross energy recovery potential of MSW, i.e. the maximum amount of energy that could be obtained, is likely to decrease in the future mainly due to a higher diversion of plastic, paper, and cardboard to recycling. The gross energy recovery potential of the MSW generated in Madrid by 2030 ranges from 4,963 to 6,984 TJ year−1 according to the scenarios defined in this study. This means a decrease of 34 – 7% compared with 2017. However, the waste streams susceptible to energy recovery –organic waste streams and MRFs' rejects– account for 48 – 60% of the MSW generated under the 2030 scenarios. Furthermore, the electricity generation potential could increase between 8 and 55% by 2030 with respect to 2017 if more efficient incineration and/or gasification facilities are implemented. All in all, our findings clearly suggest that recycling targets do not necessarily compromise energy recovery. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid automatic calibration method for transition potential based Cellular Automata land-use models by integrating two calibration methods, process-specific and optimisation-based, into a single hybrid approach, combining the advantages of these two methods. The hybrid approach features the detailed exploration of a large population of possible model parameterisations achieved using optimisation with valuable understanding of land-use systems and their dynamics commonly utilised in process-specific methods to better enhance the plausibility of the results obtained. The utility of the proposed hybrid approach is tested through an application to Madrid, Spain, and outperforms the two other methods (conventional multi-objective optimisation and process-specific) in terms of objective performance, quality of simulated output maps based on visual assessment, and parameter estimates that are more consistent with process understanding. • New method for automatic calibration of Cellular Automata land use models. • Software developed to enable proposed method to be implemented easily. • Method and software tested on case study of Madrid, Spain. • Method outperforms alternative approaches; and. • Method generates plausible simulated output and parameter values without over-calibration. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of the interpretability of a machine learning model designed to predict air quality time series. When constructing a forecasting model, in addition to obtaining good accuracy, it is utterly important to understand why each prediction is made. Usually, interpreting the output of machine learning models is considered to be very difficult due to their complex "black box" architecture. However, we show how Shapley additive explanations can be used to interpret the outputs of a deep neural network designed to predict Nitrogen dioxide concentrations in Madrid. This method computes an estimation of the contribution of each feature for a particular prediction. Furthermore, we compare three explanatory methods to determine which one is more suitable for the air quality data and for the chosen machine learning model. A deeper insight into how the model behaves when predicting the pollution time series is obtained. • A deep learning model is used to predict NO2 concentrations in the atmosphere of Madrid. • The resulting model is complex and, thus, hard to interpret. • Using the SHAP framework an explanation is derived for each prediction. • These explanations allow a deeper insight into how the model behaves in each case. • Results support previous intuitions about the relation of the meteorological variables with NO2. [ABSTRACT FROM AUTHOR]

• Methods for monitoring buildings, testing and adjusting energy simulation software are developed. • Factors influencing energy building performance are investigated in two case studies. • Mixed-method approach helps to define building simulation templates and users' patterns. • Adjusted simulation models allow a reliable building energy consumption evaluation. • Weather data and occupancy patterns are the most influential factors in the adjustment of models. This paper focuses on exploring methods for reducing the gap between the expected and actual building energy performance by using simulation tools. The study has two purposes. The first is to quantify the relative effect of the different building parameters measured on the energy heating and cooling consumption compared with standard parameters through the adjustment of simulation models. The second is to develop an approach, based on three methods, for monitoring residential buildings, while also testing and calibrating methodologies for the simulation software. The approach developed is applied and tested in two real case studies (two apartments in two identically constructed buildings, one refurbished and the other not) in the city of Madrid, Spain. The analysis of the case studies shows that there is a four-fold difference in potential savings in energy for heating between models adjusted with standard and actual parameters. Moreover, the results reveal the significant impact of the use of actual weather data and users' behaviour in the adjustment of simulation models and demonstrate the utility of the application of these methods. [ABSTRACT FROM AUTHOR]

• 21 150 × 200 × 11,000 mm3 Salzmann pine rafters from 18th century building were analysed. • Criteria were established to assign the most adequate nominal cross-section dimension. • NDT measurements were used to optimize the nominal size dimensions assignment. • Central area cross-section showed the best MOE estimation with ToF methods. • Global mean cross-section showed the best MOE estimation with vibration analysis. The frequent highly irregular geometry of the elements in existing timber structures complicates the structural verification of members and influences the use of non-destructive testing (NDT), affecting the inspection time, cost and results obtained. This process therefore needs to be improved. The main aim of this paper is to analyse how to obtain a representative nominal cross-section (NCS) of members, and its influence on determination of the static modulus of elasticity (MOE sta). 21 150 × 200 × 11,000 mm3 Salzmann pine (Pinus nigra subsp. salzmannii (Dunal) Franco) timber rafters from the 18th century Royal Coliseum of Charles III theatre (in Aranjuez, Madrid, Spain) were acoustically tested (by ultrasound, stress wave and vibration). The MOE sta was determined by mechanical testing, and different criteria for determining the NCS were analysed. Good correlation was obtained between the MOE sta and NDT parameters, and the best criterion to assign NCS was proposed to improve the accuracy of the models obtained by reducing the number of NCS measurements. [ABSTRACT FROM AUTHOR]

In this paper we approach the problem of predicting air quality in the region of Madrid using long short term memory recurrent artificial neural networks. Air quality, in this study, is represented by the concentrations of a series of air pollutants which are proved as risky for human health such as CO, NO 2 , O 3 , PM10, SO 2 and airborne pollen concentrations of two genus (Plantago and Poaceae). These concentrations are sampled in a set of locations in the city of Madrid. Instead of training an array of models, one per location and pollutant, several comprehensive deep network configurations are compared to identify those which are able to better extract relevant information out of the set of time series in order to predict one day-ahead air quality. The results, supported by statistical evidence, indicate that a single comprehensive model might be a better option than multiple individual models. Such comprehensive models represent a successful tool which can provide useful forecasts that can be thus applied, for example, in managerial environments by clinical institutions to optimize resources in expectation of an increment of the number of patients due to the exposure to low air quality levels. • A method to forecast CO, NO2, O3, PM10, SO2 and pollen concentrations is applied to a case study in different locations in Madrid. • The method presents and compares different topologies of long short term memory in recurrent neural networks. • A non-parametric hypothesis test is used to backup the decision to select the most accurate and robust configuration. • Results show increases in accuracy when compared to two traditional approaches which are used as a benchmark. • A comprehensive deep network configurations comparison to predict one day-ahead air quality. [ABSTRACT FROM AUTHOR]