The whole-life cycle of a building can be analyzed from the point of view of energy used for each phase of the operation (Life Cycle Energy Analysis — LCEA). An investment process begins when an investor chooses a plot or decides to build a facility, and ends with a handover of the building to the user. This is also the moment when the real life of a building starts, the one with the resident.
On the global scale, what is built-up, and above all operating, is responsible for consumption of 30–40% of energy. The research on the product life cycle cost analysis  shows that the energy needed for construction (transport, construction, demolition etc.) is marginal, about 1% of the energy used in the entire life of the building. Whereas operation in Portugal consumes up to 85%. Operation is closely related to the occupant/resident, which is why this time we need to talk about us — users and our role in energy consumption.
The occupation begins as soon as the keys are handed over and it shows the truth about the building’s performance and its relation with the environment. It shows whether the design team responded to the needs of the resident, and that they understood the climate and its impact on the immediate surroundings. However, even the most sophisticated technologies, materials and tools, such as quadruple window glazing, weather sensors or design optimization will perform poorly as long as we designers don’t understand the necessities of the future residents, and the users* themselves don’t know how the building operates and how much energy is worth. I don’t want to shift responsibility to users or their lifestyle, but it’s worth taking a look at.
Let’s start with an anecdote that shows an extreme situation. Designers from the British firm bere: architects describe their effort  to make their next project the most energy-efficient, a great project that challenges passive and active technologies, preliminary simulations, multiple sensors and many more means. Even so, there was a significant jump in monitoring energy consumption in the spring. Is it spring cleaning? -They were asking themselves. No. The designers’ doubts were only dispelled by satellite photos and interviews with residents. It turned out that the residents decided to put two bouncy castles (!) and a jacuzzi in the garden. It was 32% higher than in a comparable period.
Energy consumption in a building could be organized in three groups: (1) heating and water heating; (2) cooking, electric sockets, mechanical ventilation and cooling; and (3) lighting. Instituto Nacional de Estatística (the Government office for national statistics of Portugal) research on Portugal  shows that the first group consumes about 45% of energy used in the building. More than 67% of heating in households comes from burning wood and another 14% from LPG, while renewable energy is lower than 1%. The report says a lot about the availability of clean energy in Portugal and the GHG emitted while heating a house. This means that if an architect fails to design an energy-efficient house — optimal solar orientation of a building or a functional layout that reflects the life of the inhabitants — the residents will use active methods (smoking in the fireplace or heat fans) to control living comfort. Therefore it is crucial to understand when (occupancy patterns) and how a resident uses a building (occupant behavior).
The occupancy patterns indicate at what times of the year and days a building, and its rooms are used. The model assigns a 0–1 value for each of 8,760 hours of the year, where ‘0’ means there are no occupants and ‘1’ that there are. It is good practice that occupancy is checked separately for working days and holidays. In the survey, the users are asked what room they stay in during the given hours, and for a situation where a room is occupied by more than half of the users, the value is assigned ‘1’, and ‘0’for the remaining situations. This model will decide whether you need to consider heating or lighting apartments in the afternoon during summer, when perhaps most of them are away from home. For example, in Cyprus employers tend to shift working hours during the hot summer so that employees leave in the early afternoon, or in Italy, when factories are taking a break in the hottest month of the year — August.
The occupant behavior can be divided into passive, i.e., thermal gains merely due to the occupant’s metabolic rate, and active ones, i.e. those that change the temperature and humidity, for example cooking, lighting, opening windows, sliding blinds, etc. A passive action, that is, the presence of the user, we can predict and model relatively easily, with the help of BEM (Building Energy Modelling). Active behavior is much more difficult. It depends on many factors: opening and closing windows may depend on the number of people in the room, whether someone smokes cigarettes and ventilates; regulating heating may depend on gender and age, what kind of lighting we use, and whether we practice yoga every morning. There are attempts to take into account active behavior, which are harnessed by appropriate algorithms that analyse a large portion of information, and are able to predict how the resident will behave. However, it will be a few more years until such knowledge will be easily accessible and reliable. Until then it is more important to talk to the future residents in the case of single-family houses or the property manager in the case of larger investments, who can familiarize us with the specifics of the building.
In order to understand the user better, and this mainly applies to office spaces, it is worth conducting a thorough analysis with the facility manager whenever possible. A few years ago, I had a conversation with a client, a large corporation, who said that they always wear three-piece suits to work. This means that even in summer, when it is boiling outside, they cannot adjust their clothing level, it is impossible to ‘take off your jacket’. The clothing level is one of the parameters that are included in the modelling of a building’s energy performance and can improve comfort. Well, in some cases it’s enough to put on a sweater. Other aspects of thermal comfort are related to the biology of the human body, the metabolic rate, age and gender. Numerous studies show that women feel discomfort at higher temperatures than men. Moreover, in office spaces requiring formal attire, men wear more layers.
A significant role is played by sensors and screens that inform the user about energy consumption. It is proven that such a technology can reduce energy consumption by 30% . Such a technology allows occupants to better understand how to responsibly use the building and which activities are the most energy consuming.
The user and their behavior are the most important aspect in a building’s operation. A house designed without considering human thermal comfort and occupancy patterns will have a negative impact on the environment. Finally all create a network of interdependent relations. If one is poorly performing it influences others. I remember in high school my math teacher was opening windows in the break, even in the freezing winter, this helped to exchange air but at the same time caused significant energy losses.
A thorough analysis of the performance of a building improves its future relationship with the environment. Such an approach must include occupancy and behavior of the user. Otherwise it is likely incorrect. Finally, as we wrote in our previous article, now we need to challenge new pandemic and post-pandemic occupancy patterns and understand how our buildings operate.
*Although it is worth to mention a 2000 watt Society, that allows the residents of a community to use only 2000 watts
 Asiedu Y. and Gu P., “Product life cycle cost analysis: State of the art review”, International Journal of Production Research, vol. 36, no. 4, (Apr. 1998), pp. 883–908. https://doi.org/10.1080/002075498193444
 Oliveira S. et al., Energy modelling in architecture: A practice guide, 1sted. RIBA Publishing, 2020. Available: https://www.taylorfrancis.com/books/9781000033830 https://doi.org/10.4324/9781003021483
 Lee J.-W. and Kim Y. I., “Energy Saving of a University Building Using a Motion Detection Sensor and Room Management System”, Sustainability, vol. 12, no. 22, (Nov. 2020), p. 9471. https://doi.org/10.3390/su12229471