English

This paper presents a summary of calculations on the total cost effects of the remedial measures to reduce high summer time room temperatures in a hypothetical building. In the base case the room air temperature is too high during the summer, and causes a considerable reduction in the productivity. The following economical items are included in the study: first cost of the remedial measure, the effect of the measure in operating cost, particularly on energy consumption, and the effect on productivity.

The provision of a healthy and satisfactorily clean indoor environment requires that consideration be given to a range of issues, such as the type of indoor environment, indoor and outdoor sources, indoor activity and others. The selection of relevant measures to achieve the required indoor air quality (IAQ) depends on knowledge and understanding of the mechanisms and parameters affecting the concentration levels indoors.

This project covered 16 aircrafts including both smoking and non-smoking flights from June 1996 to August 1997. The parameters concerned were carbon dioxide (C02), humidity, temperature, carbon monoxide (CO), ozone (03), bacteria, fungus, and respirable suspended particulate (RSP). Compared with the Federal Aviation Administration (FAA) standard, C02, CO and ozone levels on all flights were within such standards. Peak levels of C02 and particulate were observed during both boarding and deboarding periods.

This paper summarizes baseline results from the U.S. Environmental Protection Agency's (EPA) school demonstration studies. Indoor pollutants of concern were formaldehyde, sum of targeted volatile organic compounds o:VOC), carbon monoxide (CO), particulate matter less than 2.5 microns (PM2.5), particulate matter less than 10 microns (PM10), and bioaerosols (bacteria, fungi, and thermophiles). The five schools presented here had no significant indoor air quality problems. Locations of these schools were distributed throughout various climate zones in the United States.

The numerical investigation of airflow and chemical transport characteristics for a general class of buildings involves identifying values for model parameters, such as effective leakage areas and temperatures, for which a fair amount of uncertainty exists. A Monte Carlo simulation, with parameter values drawn from likely distributions using Latin Hypercube sampling, helps to account for these uncertainties by generating a corresponding distribution of simulated results.

This paper is based on a dual approach (experimental and numerical) in order to predict the indoor air quality for small ventilated enclosures. The experimental part employs a ventilated test room and a tracer gas technique (constant method as gas injection) to estimate the diffusion of a pollutant. The gas used is the sulphur hexafluoride (F6S). The numerical approach is a CFD simulation, adding a convection - diffusion equation (to determine the local mass fraction of the pollutant) to the equations normally used to solve a turbulent flow.

Measurement campaign was conducted in a controlled office environment during January 1999 to get indoor/outdoor ratio for particles less than 0.5 micrometers in diameter. Aerosol concentrations for diameters between 7-500 nanometers were measured simultaneously indoors and outdoors with two DMPS systems. Other continuously measured quantities included temperature, ventilation rate, relative humidity, air pressure and four inorganic gases (S02, NO, NOx and 03). The measured room was practically airtight and had a mechanical ventilation system.

Gas cooking in the home can release high levels of nitrogen dioxide (N02) and carbon monoxide (CO). This study investigated the effect of various ventilation strategies to reduce personal exposure to these pollutants. It considered the effectiveness of windows, a kitchen extract fan and trickle ventilators for different dwellings, occupant behaviour, environmental conditions etc. Strategy selection was based on the need to minimise both personal exposure and energy loss. These strategies were simulated using BRE's BREEZE multi-zonal computer code.