Impact of financial assumptions on the cost optimality towards nearly zero energy buildings - a case study
Abstract
5 result(s) found
Over half of the population of the world live in
urban areas. This means that efforts to meet human
development goals and sustain economic growth
must be concentrated in cities. However, the pursuit
of more prosperous, inclusive and sustainable urban
development is complicated by climate change, which
multiplies existing environmental risks, undermines the
effectiveness of existing infrastructure, and creates new
resource constraints.
In this paper, we conclusively demonstrate that there
There are indications that energy-retrofitted buildings can create risks for indoor environmental quality (IEQ) and therefore for health and comfort of occupants. A review was conducted to identify and verify those risks, within three themes: building envelope, heating, ventilating and air conditioning (HVAC)-systems, and occupants. Publications from the last five years in major peer-reviewed journals from different fields (energy, buildings, indoor air, social sciences) were found by using a variety of keywords (health effects, occupant behaviours, energy-efficient retrofitting, etc.).
This paper presents a comprehensive literature review of what drives the adoption of green building (GB) practices among construction stakeholders. The review is based on literature that have been published in peer-reviewed journals. Through a systematic review of the literature, authors are able to identify generic drivers for stakeholders to pursue GB. A total of 64 drivers were identified from reviewing 42 selected empirical studies. The paper presents a classification framework for the GB drivers.
The reliability, security, and sustainability of energy generation and supply are of global importance and the building sector accounts for up to 32% of total energy consumption, which makes it a key player in the domain. Previous research has identified that the actual energy consumption in buildings could be as much as 2.5 times of the predicted or simulated.