A Stochastic Approach to Estimate Uncertainty in Pollutant Concentrations in an Archetypal Chilean House

As policy makers strive to reduce the energy demands of houses by reducing infiltration rates, an unintended consequence could be a fall in the quality of indoor air with corresponding negative health effects at a population scale. Measuring pollutant concentrations in-situ is difficult, expensive, invasive, and time consuming and so the simulation of indoor conditions, using representative models of a housing stock, is a more common method of investigation.

A Method to Measure Emission Rates of PM2.5s from Cooking

Exposures to airborne fine particulate matter with a diameter of <2.5μm (PM2.5) are linked to multiple negative health effects, including cardiovascular and respiratory disease. Existing investigations of PM2.5 primarily focus on external sources and exposures, because outdoor air is easier to observe, and therefore, more widely monitored. However, as people spend up to 70% of their time in their own homes, exposures to indoor pollutants could have a greater impact on health. One method of investigating indoor exposures in a stock of houses is by modelling them.


The aim of the study is to quantify the traffic generated particle number concentration levels (PM2.5; PMwith diameter ? 2.5?m) at various heights of a typical high-rise building in close proximity to a majorexpressway in Singapore. A 22-storey naturally-ventilated high-rise residential building located about15m away from a major expressway was selected for the study.