indoor environment

Buildings typically are expected to provide their inhabitants with the opportunity to influence the indoor environment using various control devices. These include, for example, windows, luminaires, radiators, and shading elements. The quality and adequacy of the indoor environment is thus dependent on the availability and effectiveness of such devices. There is arguably a lack of generally agreed-upon evaluation procedures for this aspect of buildings' indoor environment, namely its controllability by building users, or – in the terminology of Human Ecology – its "ecological valency".

The present talk will present some of the initiatives from ASHRAE regarding “smart” in general and then focus on indoor environmental activities related to “smart” ventilation. The ASHRAE society theme for 2018/19 is “Building Our New Energy Future”. In the future, our buildings will be interconnected through a “Smart Grid” in general the electricity grid.

Building automation systems provide potential to optimise the energy consumption of buildings as well as to detect failures in the operation of buildings. Providing the occupants with control over the indoor environment is widely accepted to positively affect the occupant’s satisfaction. The system building-HVAC-automation-user is becoming more complex. So what does the term ‘perceived control’ really mean? Psychological constructs from social learning theory and personality psychology transferred to the field of personal control of the indoor environment will be discussed.

In the preceding companion paper (Part I), a method with one sensor that could identify the indoor contaminant source location and strength in short time was presented. On the basis of further theoretical study, a method with two sensors is presented in this paper to identify contaminant source with higher accuracy. This paper demonstrates how to use the method with two sensors to find the location of contaminant source in a threedimensional room. In addition, the accuracy of two types of methods was compared.

In case contaminants are released in occupied rooms, it is necessary to determine the contaminant source location and strength rapidly so that prompt response measures can be taken to protect indoor occupants. This paper presents a new method with one sensor to identify the contaminant source location and strength. It completes the time-consuming computational fluid dynamics (CFD) simulations before the release event, and finds the source in real time during the event. In addition, an index called “correctness probability” for evaluating the accuracy of this method is proposed.

Efforts to save energy may easily lead to the compromisation of indoor environmental conditions and vice-versa. This study suggests an indicator for indoor environmental quality classification, developed with the purpose of assisting households that are trying to save energy, to maintain optimum levels of indoor environmental quality during this effort. The “Dwelling Environmental Quality Index” (DEQI) is a comprehensive indoor environmental quality indicator, reported to occupants as an easily understood number (percentage).

BR10 requires that all new residential constructions should be built as low energy housing. In order to meet these requirements residential buildings must be equipped with far more complex technology, than conventional housing. This, for example, could be a combination of mechanical balanced ventilation, natural ventilation, heat pumps, solar heating, solar cells or automatic sunscreens.

Today an acceptable indoor air quality is mainly defined by specifying the required level of ventilation in air changes per hour or the outside air supply rate. This would be equivalent to defining the requirements for thermal comfort by specifying the level of heating or cooling in Watts. The increasing societal need for energy efficiency will often result in very tight buildings. This means that the amount of outside air supplied by infiltration is not enough to provide the required ventilation.

The overarching objective of this study was to develop a numerical model based on computational fluid dynamics to predict aerosol concentration distributions in indoor environments. Towards this end, this paper proposes a wall surface deposition model of nano-scale aerosol that can predict unsteady deposition flux of aerosol indoors; it also reports the results of sensitivity analyses for targeting a plug-flow-type chamber.