KxKali v0.1: A Work-in-Progress Tool for Streamlining Thermal Comfort Evaluation in Building Design and Occupancy

Thermal comfort evaluation is crucial in the design of buildings, as it impacts the well-being and productivity of building occupants. Many national regulations and international standards provide guidelines for assessing thermal comfort. In order to simplify this process, we have developed a program called KxKali, which is intended to evaluate thermal comfort based on temperature and relative humidity data input using the adaptative comfort model of EN 16798. The current version of the software, v0.1, is only able to accept data from computer simulation using the official Spanish simulation software HULC and performs graphing and counting automatically, without the need for the user to edit, modify or handle any data manually. By using HULC as the source of input data, the tool can take advantage of the software’s established reputation and acceptance among professionals in the building design industry in Spain, streamlining the comfort evaluation process by eliminating the need to generate input data manually, or using additional software. However, future versions are planned to accept data from other software and also monitored data. In addition, there are plans to implement the evaluation of thermal comfort following other regulations. The ultimate goal of this project is to convert KxKali into a user-friendly and widely accessible web-app that professionals can use in the design phase without performing any additional work apart from what they are already doing for energetic certification, which may improve building design by allowing architects and engineers to quickly evaluate different thermal comfort scenarios and optimize their design for comfort, and also facilitate the process of post-occupancy evaluations (POE). The goal of this presentation is to show the current capabilities of the KxKali tool, and to obtain feedback from other specialists on how to improve it and make it more widely useful. In the paper, the limitations of using simulation data from HULC and the ongoing developments of KxKali such as accepting monitoring data and converting it into a web-app will be discussed. Additionally, the paper will showcase mockups of the future web-app version of the tool, providing a glimpse into its intended user interface, and the expected reporting and output

Characterization of the Thermal Behavior of Semi-Exterior Laundry Spaces in an Overheating Passivhaus Residential Building in Bilbao, Spain

Overheating in buildings is a growing challenge in temperate climates, even in those where the traditional design focus was on protecting from cold and winter energy savings. This paper addresses a collateral problem that arose during the study of overheating in a residential Passivhaus building in Bilbao, northern Spain. Specifically, the local climate of three laundry spaces was investigated, where high daytime and nighttime temperatures were recorded. An extensive monitoring campaign was carried out with different durations up to more than 21,000 h over four years, and the collected data were compared with outdoor climatic conditions. The results allowed for characterizing the thermal behavior of these semi-outdoor spaces and show the magnitude of the problem, quantifying it. Laundry spaces were confirmed to be hotter and dryer than the outdoor climate almost always. The mean average difference between the monitored rooms and the exterior was quantified to be around positive 5 °C during both daytime and nighttime. Extreme heat events were documented, with maximum temperatures above 50 °C and temperature differentials of up to 15.85 °C. In addition, this article comments on the impact of overheating these laundry spaces on the interior of the dwellings, pointing out the differences between the assumptions made during the design phase of the project and the observed or measured reality. Questions were raised about the possible implications of the peculiar performance of these semi-outdoor spaces on the mechanical heat recovery ventilation system (MHRV). The data presented in this article revealed and quantified a design flaw that went unnoticed by all agents involved in the planning, design, and construction of the 361-apartment project. The inability to predict the behavior of the studied spaces has had a negative impact on building performance during the summer months and has prevented the implementation of strategies that could have been beneficial in other periods. A thorough analysis of the thermal behavior of similar spaces becomes essential to prevent performance gaps in future projects and to inform adequate building modeling in the design stagesThis research was funded by the Department of Territorial Planning and Housing of the Basque Government. The same funder covered both the acquisition of the equipment and the APC

Impact of COVID-19 Lockdown on Wildlife-Vehicle Collisions in NW of Spain

ABSTRACT: Wildlife-vehicle collisions (WVCs) in many places have a significant impact on wildlife management and road safety. The COVID-19 lockdown enabled the study of the specific impact that traffic has on these events. WVC variation in the Asturias and Cantabria regions (NW of Spain) because of the COVID-19 lockdown reached a maximum reduction of -64.77% during strictconfinement but it was minimal or nonexistent during "soft" confinement. The global average value was -30.22% compared with the WVCs registered in the same period in 2019, but only -4.69% considering the average throughout the period 2010-2019. There are huge differences between conventional roads, where the traffic reduction was greater, and highways, where the traffic reduction was lesser during the COVID-19 lockdown. The results depend on the season, the day of the week and the time of day, but mainly on the traffic reduction occurring. The results obtained highlight the need to include the traffic factor in WVC reduction strategies.This research was partially funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), the Spanish State Research Agency (AEI) and the European Regional Development Fund of the European Union (ERDF, EU) through the project HOFIDRAIN-MELODRAIN, Re. RTI2018-094217-B-C32, financed y MCIN/AEI/10.13039/501100011033/ERDF “A way to make Europe”

Comparative Analysis of the Effect of the Evolution of Energy Saving Regulations on the Indoor Summer Comfort of Five Homes on the Coast of the Basque Country

In the last decade, several European directives have been established to contribute to the 2020, 2030 and 2050 energy saving targets and impose energy efficiency requirements for new construction, existing buildings and building renovation operations. One of the ways to achieve said objectives is to rely on the most demanding energy efficiency labels existing in Europe, such as Passivhaus, and to implement similar concepts into the national energy regulations of European countries based on a high-performance thermal envelope (high insulation and high-performance windows), high airtightness and high-performance heat-recovery ventilation systems, and solar heat harvesting. This energy conservation concept has shown to be effective for houses with low-density occupation in cold climates, but may cause severe overheating problems in denser collective housing in temperate and hot climates with higher solar radiation. To assess this impact, five flats in three developments from different periods that range from no insulation at all to a nZEB, Passivhaus-certified high-rise are compared in this paper, using data from a monitoring campaign during the summer of 2020. The results show and quantify the strong impact the evolution of the energy saving regulatory trend has had on summer indoor comfort, which may in some cases lead to previously unnecessary air conditioning for cooling and, ultimately, be counterproductive towards the end goals of reducing energy consumption and greenhouse-effect gas emissions and mitigating climate change.This study has been partially funded by the Department of Architecture of the University of The Basque Country (UPV-EHU). In addition, part of the work presented in this paper was funded by the research Project 3SqAir, Sustainable Smart Strategy for Air Quality Assurance in Classrooms (SOE4/P1/E1004), funded by the Interreg Sudo

Comparison of machine learning algorithms for wildland-urban interface fuelbreak planning integrating ALS and UAV-Borne LiDAR data and multispectral images

Producción CientíficaControlling vegetation fuels around human settlements is a crucial strategy for reducing fire severity in forests, buildings and infrastructure, as well as protecting human lives. Each country has its own regulations in this respect, but they all have in common that by reducing fuel load, we in turn reduce the intensity and severity of the fire. The use of Unmanned Aerial Vehicles (UAV)-acquired data combined with other passive and active remote sensing data has the greatest performance to planning Wildland-Urban Interface (WUI) fuelbreak through machine learning algorithms. Nine remote sensing data sources (active and passive) and four supervised classification algorithms (Random Forest, Linear and Radial Support Vector Machine and Artificial Neural Networks) were tested to classify five fuel-area types. We used very high-density Light Detection and Ranging (LiDAR) data acquired by UAV (154 returns·m−2 and ortho-mosaic of 5-cm pixel), multispectral data from the satellites Pleiades-1B and Sentinel-2, and low-density LiDAR data acquired by Airborne Laser Scanning (ALS) (0.5 returns·m−2, ortho-mosaic of 25 cm pixels). Through the Variable Selection Using Random Forest (VSURF) procedure, a pre-selection of final variables was carried out to train the model. The four algorithms were compared, and it was concluded that the differences among them in overall accuracy (OA) on training datasets were negligible. Although the highest accuracy in the training step was obtained in SVML (OA=94.46%) and in testing in ANN (OA=91.91%), Random Forest was considered to be the most reliable algorithm, since it produced more consistent predictions due to the smaller differences between training and testing performance. Using a combination of Sentinel-2 and the two LiDAR data (UAV and ALS), Random Forest obtained an OA of 90.66% in training and of 91.80% in testing datasets. The differences in accuracy between the data sources used are much greater than between algorithms. LiDAR growth metrics calculated using point clouds in different dates and multispectral information from different seasons of the year are the most important variables in the classification. Our results support the essential role of UAVs in fuelbreak planning and management and thus, in the prevention of forest fires.Ministerio de Economía, Industria y Competitividad (DI-16-08446; DI-17-09626; PTQ-16-08411; PTQ- 16-08633)European Commission through the project ‘MySustainableForest’ (H2020-EO-2017; 776045

Fauna silvestre y accidentes de tráfico en Asturias

Los accidentes de tráfico con animales silvestres son un problema creciente en muchas partes del mundo y un importante aspecto de los conflictos entre humanos y vida silvestre con incidencia en la seguridad vial y en las poblaciones animales. En este trabajo se analizan los accidentes (n= 6 377) registrados por las autoridades de carreteras y de caza en Asturias en el periodo 2007-2014. Los resultados muestran las especies implicadas, que atañen principalmente al jabalí (sus scrofa), envuelto en el 60,36 % de los siniestros, y al corzo (Capreolus capreolus), en el 29,95 %, así como la distribución geográfica, los patrones mensuales, diarios y horarios de ocurrencia y la evolución de los siniestros, debatiéndose sus posibles causas y consecuencias. Los aspectos tratados pueden ayudar al diseño de medidas de mitigación y a la gestión de las poblaciones silvestres

Response to the COVID-19 Pandemic in Classrooms at the University of the Basque Country through a User-Informed Natural Ventilation Demonstrator

The COVID-19 pandemic has generated a renewed interest in indoor air quality to limit viral spread. In the case of educational spaces, due to the high concentration of people and the fact that most of the existing buildings do not have any mechanical ventilation system, the different administrations have established natural ventilation protocols to guarantee an air quality that reduces risk of contagion by the SARS-CoV-2 virus after the return to the classrooms. Many of the initial protocols established a ventilation pattern that opted for continuous or intermittent ventilation to varying degrees of intensity. This study, carried out on a university campus in Spain, analyses the performance of natural ventilation activated through the information provided by monitoring and visualisation of real-time data. In order to carry out this analysis, a experiment was set up where a preliminary study of ventilation without providing information to the users was carried out, which was then compared with the result of providing live feedback to the occupants of two classrooms and an administration office in different periods of 2020, 2021 and 2022. In the administration office, a CO2-concentration-based method was applied retrospectively to assess the risk of airborne infection. This experience has served as a basis to establish a route for user-informed improvement of air quality in educational spaces in general through low-cost systems that allow a rational use of natural ventilation while helping maintain an adequate compromise between IAQ, comfort and energy consumption, without having to resort to mechanical ventilation systems.This research was funded under the title “Proyecto Piloto Sobre Calidad del Aire en Espacios Interiores Universitarios” in the CBL program 2020–2021 and 2021–2022, promoted by the Directorate of Sustainability, Vice-Rectorate for Innovation and Social Commitment of the University of the Basque Country (UPV-EHU)

Proyecto BRACC: caracterización de la fiabilidad de las obras de abrigo por efecto del cambio climático

Los autores agradecen el apoyo del Ministerio de Ciencia, Innovación y Universidades por la financiación recibida para llevar a cabo este proyecto (BIA2017-87213-R)

Avances en la resolución conjunta de los procesos costeros y portuarios para la predicción de la agitación en la bahía de Algeciras

Se agradece a la APBA la financiación dentro del proyecto “Algeciras Safeport”

Exfoliation of Alpha-Germanium: A Covalent Diamond-Like Structure

2D materials have opened a new field in materials science with outstanding scientific and technological impact. A largely explored route for the preparation of 2D materials is the exfoliation of layered crystals with weak forces between their layers. However, its application to covalent crystals remains elusive. Herein, a further step is taken by introducing the exfoliation of germanium, a narrow-bandgap semiconductor presenting a 3D diamond-like structure with strong covalent bonds. Pure α-germanium is exfoliated following a simple one-step procedure assisted by wet ball-milling, allowing gram-scale fabrication of high-quality layers with large lateral dimensions and nanometer thicknesses. The generated flakes are thoroughly characterized by different techniques, giving evidence that the new 2D material exhibits bandgaps that depend on both the crystallographic direction and the number of layers. Besides potential technological applications, this work is also of interest for the search of 2D materials with new properties