A.C. Terry

Crucial Role for Outdoor Chemistry in Ultrafine Particle Formation in Modern Office Buildings

In the developed world, we spend most of our time indoors, where we receive the majority of our exposure to air pollution. This paper reports model simulations of PM2.5 and ozone concentrations in identical landscape offices in three European cities: Athens, Helsinki, and Milan. We compare concentrations during an intense heatwave in August 2003 with a meteorologically more typical August in 2009. During the heatwave, average indoor ozone concentrations during office hours were 44, 19, and 41 ppb in Athens, Helsinki, and Milan respectively, enhanced by 7, 4, and 17 ppb respectively relative to 2009. Total predicted PM2.5 concentrations were 13.5, 3.6, and 17.2 μg m(-3) in Athens, Helsinki, and Milan respectively, enhanced by 0.5, 0.4, and 6.7 μg m(-3) respectively relative to 2009: the three cities were affected to differing extents by the heatwave. A significant portion of the indoor PM2.5 derived from gas-phase chemistry outdoors, producing 2.5, 0.8, and 4.8 μg m(-3) of the total concentrations in Athens, Helsinki, and Milan, respectively. Despite filtering office inlet supplies to remove outdoor particles, gas-phase precursors for particles can still enter offices, where conditions are ripe for new particles to form, particularly where biogenic emissions are important outdoors. This result has important implications for indoor air quality, particularly given the current trend for green walls on buildings, which will provide a potential source of biogenic emissions near to air inlet systems.

Development of a probabilistic multi-zone multi-source computational model and demonstration of its applications in predicting PM concentrations indoors

This paper highlights the development and application of the probabilistic model (IAPPEM), which predicts PM10 and PM2.5 concentrations in the indoor environments. A number of features are detailed and justified through simulated comparison, which are shown to be necessary when modelling indoor PM concentrations. A one minute resolution predicts up to 20% higher peak concentrations compared with a 15 min resolution. A modified PM10 deposition method, devised to independently analyse the PM2.5 fraction of PM10, predicts up to 56% higher mean concentrations. The application of the model is demonstrated by a number of simulations. The total PM contribution, from different indoor emission sources, was analysed in terms of both emission strength and duration. In addition, PM concentrations were examined by varying the location of the emission source. A 24-hour sample profile is simulated based on sample data, designed to demonstrate the combined functionality of the model, predicting PM10 and PM2.5 peak concentrations up to 1107±175 and 596±102 μg m(-3) respectively, whilst predicting PM10 and PM2.5 mean concentrations up to 259±21 and 166±11 μg m(-3) respectively.