In assuming the contamination concentration near buildings, the time fluctuation to be considered is theoretically analysed, hypothetical volume method is proposed, and experimental results of measurements near buildings are described. There are two kinds of variations of contamination around buildings : time fluctuations and space distributions. Considering the outdoor contamination as one of the main sources of indoor air contamination, the possible effect of time fluctuation of outdoor concentration on those of indoor air is analysed by deriving the frequency transfer functions (2-23), (2-24) and (2-25) from which the amplitude gains are obtained and shown in the Bode diagrams (Figs. 2-2, 2-3). Since average existing time length of contamination within room is, in case of air-conditionned or naturally ventilated buildings, in the range of 1/2-1/6 hours and if the fluctuations of outdoor contamination are of less than 0.3-1.0 cycle/hour the gain will be 20log P. If the fluctuation is more than 3-10 cycle/hour. the attenuation of more than 10 would be added and the influence of fluctuation on indoor concentration would become very small. It can be concluded that average concentration for 20-30 minutes would possibly be used without excessive negligence of possible influence of outdoor concentration fluctuations. In presupposing the outdoor concentration near buildings, a new method using hypothetical volume adjoining buildings is proposed. If the hypothetical air changes to this volume can be predicted in relation with types of the hypothetical volumes and other conditions such as wind speed and direction, and source strength, approximate values of contamination concentration due to sources near buildings can be calculated using equations (3-1) and (3-2). One of main sources of contamination near buildings is traffic exhaust and it is necessary to determine the amount generated within the hypothetical volume to predict the concentration. For this purpose the traffic should be taken into account as source strength instead of simple passing rate as usually done especially when traffic conditions change by time. In determining the source strength, a photographical method to determine the number of existing cars in the block in question or the traffic density was tried and compared with other method using the number of cars passing and driving speed. Traffic density or number of existing cars looks proportional to the number of passing cars to certain extent but, if any traffic congestion occurs for some reason, the relation of these two can become quite different. It was concluded either method can be utilised. Actual measurements of carbon monooxide concentration near buildings are carried out. Samples are taken at 3-4 levels from the ground as shown in Fig. 5-1 and analysed with an infra-red CO gas analyser. Wind speeds are also measured at several points near building using heated wire anemometer with linearzer and analysed by calculating auto-correlation functions and power spectral densities. The results of our mesurements are shown in Table 1 and Figs. 5-3, 5-10. From the CO concentration profiles (Figs. 5-10, 5-11), it seems that rather uniform concentration distribution exists vertically in the hypothetical volume in the leeward and this has the common characterisity with wind speed profiles which also shows rather uniform distribution in vertical direction and random characterisity without significant frequency. Since the wind speed near building is not very significantly influenced by general wind which was indicated by N. Ito et al, the traffic density should have strong influence on the CO concentration. From the results of measurement, as shown in Fig. 5-12, it seems that the concentration is related with traffic density. The hypothetical air changes calculated are also shown in Table 1. The values ranged from 10 to 40 changes/hour. The relation of the air
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