Abstract
Since children are far more vulnerable than adults to the effects of air pollution and spend about a third of their day in school, strict control of indoor environments in educational buildings is paramount to prop-erly identify, manage and mitigate putative environmental risks for children. In this context, this work aimed to provide a holistic view on the outcomes obtained from the national ARIA project, which was focused on broadening the knowledge on the effects on children's health of the exposure to schools' indoor air. In particular, this work performed a comprehensive investigation of the indoor air quality (IAQ) in 20 public primary schools located in Porto (Northern Region, Portugal). This paper presents the results of the investigation along with the recently published main outcomes of ARIA on (1) the char-acteristics of the environment surrounding the surveyed buildings, and (2) the school's environment-related health effects in school-age children from the studied classrooms. The investigation consisted in an extensive assessment plan conducted in 71 classrooms to assess temperature, relative humidity, carbon monoxide and dioxide, particulate matter (PM2.5, PM10, and ultrafine particles), nitrogen dioxide, ozone, volatile organic compounds, formaldehyde, acetaldehyde, airborne fungi, bacteria and endotoxins, and investigate their respective sources, during the cold seasons of 2014-2015. A series of studies was also launched to investigate school environment-related health detriments in 916 children. The results showed that comfort and ventilation issues and/or indoor pollutant levels that exceeded recommended limits were found in a substantial number of the classrooms surveyed. The high density of occupants, deficient ventilation, soil characteristics, presence of indoor pollution sources (e.g. classroom materials and consumer products) and outdoor pollution were some of the factors that seemed to explain the high air stuffiness and/or indoor pollution load identified in classrooms. In fact, some of indoor pollutants detected, even at low exposure levels, were associated with the development of respiratory symptoms in school-age children. Moreover, results from this work have also shown that the characteristics of the environment surrounding the schools, namely the presence of green spaces and species richness, can be major determinants of respiratory health among school-age children. Overall, the body of evidence generated from the ARIA project can support new evidence-based perspectives for promotion of health in educational buildings.

Abstract

Abstract

Abstract
The increasing levels of energy consumption worldwide is raising issues with respect to surpassing supply limits, causing severe effects on the environment, and the exhaustion of energy resources. Buildings are one of the most relevant sectors in terms of energy consumption; as such, efficient Home or Building Management Systems are an important topic of research. This study discusses the use of ensemble techniques in order to improve the performance of artificial neural networks models used for energy forecasting in residential houses. The case study is a residential house, located in Portugal, that is equipped with PV generation and battery storage and controlled by a Home Energy Management System (HEMS). It has been shown that the ensemble forecasting results are superior to single selected models, which were already excellent. A simple procedure was proposed for selecting the models to be used in the ensemble, together with a heuristic to determine the number of models.

Abstract
At a global level, buildings constitute one of the most significant energy-consuming sectors. Current energy policies in the EU and the U.S. emphasize that buildings, particularly those in the residential sector, should employ renewable energy and storage and efficiently control the total energy system. In this work, we propose a Home Energy Management System (HEMS) by employing a Model-Based Predictive Control (MBPC) framework, implemented using a Branch-and-Bound (BAB) algorithm. We discuss the selection of different parameters, such as time-step, to employ prediction and control horizons and the effect of the weather in the system performance. We compare the economic performance of the proposed approach against a real PV-battery system existing in a household equipped with several IoT devices, concluding that savings larger than 30% can be obtained, whether on sunny or cloudy days. To the best of our knowledge, these are excellent values compared with existing solutions available in the literature.

Abstract
The experimental investigation of building-integrated photovoltaic thermal (BIPVT) solar systems is essential to characterise the operation of these elements under real conditions of use according to the climate and building type they pertain. BIPVT systems can increase and ensure energy performance and readiness without jeopardising the occupant comfort if correctly operated. The present work presents a case study's experimental analysis composed of a BIPVT system for heat recovery located in a controlled test room. This work contribution focuses on the presentation of the obtained measured value results that correspond to the BIPVT main boundary conditions (weather and room characteristics) and the thermal behaviour and performance of the BIPVT system, located in the Solar XXI Building, a nZEB exposed to the mild Mediterranean climate conditions of Portugal.