Because human activities impact the timing, location, and degree of pollutant exposure, they play a key role in explaining exposure variation. This fact has motivated the collection of activity pattern data for their specific use in exposure assessments. The largest of these recent efforts is the National Human Activity Pattern Survey ( NHAPS ), a 2 -year probability -based telephone survey ( n = 9386 ) of exposure -related human activities in the United States ( U.S. ) sponsored by the U.S. Environmental Protection Agency ( EPA ). The primary purpose of NHAPS was to provide comprehensive and current exposure information over broad geographical and temporal scales, particularly for use in probabilistic population exposure models. NHAPS was conducted on a virtually daily basis from late September 1992 through September 1994 by the University of Maryland's Survey Research Center using a computer -assisted telephone interview instrument ( CATI ) to collect 24 -h retrospective diaries and answers to a number of personal and exposure -related questions from each respondent. The resulting diary records contain beginning and ending times for each distinct combination of location and activity occurring on the diary day ( i.e., each microenvironment ). Between 340 and 1713 respondents of all ages were interviewed in each of the 10 EPA regions across the 48 contiguous states. Interviews were completed in 63% of the households contacted. NHAPS respondents reported spending an average of 87% of their time in enclosed buildings and about 6% of their time in enclosed vehicles. These proportions are fairly constant across the various regions of the U.S. and Canada and for the California population between the late 1980s, when the California Air Resources Board ( CARB ) sponsored a state -wide activity pattern study, and the mid -1990s, when NHAPS was conducted. However, the number of people exposed to environmental tobacco smoke ( ETS ) in California seems to have decreased over the same time period, where exposure is determined by the reported time spent with a smoker. In both California and the entire nation, the most time spent exposed to ETS was reported to take place in residential locations.

Although principal components transformations on remotely sensed multispectral data often produce components that show decreasing image quality with increasing component number, there are numerous examples, especially among aircraft scanner data, where this is not the case. This has led us to define a new trans€ormation, known as the maximum noise fraction (MNF) transformation, which always produces new components ordered by image quality. It can be shown that this transforniation is equivalent to principal components when the noise variance is the same in all bands and that it reduces to a multiple linear regression when noise is in one band only. Noise can be effectively removed from multispettral data by transforming to the MNF space, smoothing or rejecting the most noisy components, and then retransforming to the original space. In this way much more intense smoothing can be applied to the MNF components with high noise and low signal content than could be applied to each band of the original data. The MNF transformation requires knowledge of both the signal and noise covariance mhtrices. Except whbn the noise is in one band only, the noise covariance matrix needs to be estimated. One procedure for doing this is discussed and examples of cleaned images are presented.

No abstract

The air change rates of motor vehicles are relevant to the sheltering effect from air pollutants entering from outside a vehicle and also to the interior concentrations from any sources inside its passenger compartment. We made more than 100 air change rate measurements on four motor vehicles under moving and stationary conditions; we also measured the carbon monoxide (CO) and fine particle (PM 2.5 ) decay rates from 14 cigarettes smoked inside the vehicle. With the vehicle stationary and the fan off, the ventilation rate in air changes per hour (ACH) was less than 1 h À1 with the windows closed and increased to 6.5 h À1 with one window fully opened. The vehicle speed, window position, ventilation system, and air conditioner setting was found to affect the ACH. For closed windows and passive ventilation (fan off and no recirculation), the ACH was linearly related to the vehicle speed over the range from 15 to 72 mph (25 to 116 km h À1 ). With a vehicle moving, windows closed, and the ventilation system off (or the air conditioner set to AC Max), the ACH was less than 6.6 h À1 for speeds ranging from 20 to 72 mph (32 to 116 km h À1 ). Opening a single window by 3 00 (7.6 cm) increased the ACH by 8-16 times. For the 14 cigarettes smoked in vehicles, the deposition rate k and the air change rate a were correlated, following the equation k ¼ 1.3a (R 2 ¼ 82%; n ¼ 14). With recirculation on (or AC Max) and closed windows, the interior PM 2.5 concentration exceeded 2000 mg mÀ3 momentarily for all cigarettes tested, regardless of speed. The concentration time series measured inside the vehicle followed the mathematical solutions of the indoor mass balance model, and the 24-h average personal exposure to PM 2.5 could exceed 35 mg m À3 for just two cigarettes smoked inside the vehicle.

No abstract