Biomedical subjects

Will Ollison

Publications and source records attributed to Will Ollison.

3 recordsLinked to original sources

PubMed2004

A pilot study using scripted ventilation conditions to identify key factors affecting indoor pollutant concentration and air exchange rate in a residence.

A pilot study was conducted using an occupied, single-family test house in Columbus, OH, to determine whether a script-based protocol could be used to obtain data useful in identifying the key factors affecting air-exchange rate (AER) and the relationship between indoor and outdoor concentrations of selected traffic-related air pollutants. The test script called for hourly changes to elements of the test house considered likely to influence air flow and AER, including the position (open or closed) of each window and door and the operation (on/off) of the furnace, air conditioner, and ceiling fans. The script was implemented over a 3-day period (January 30-February 1, 2002) during which technicians collected hourly-average data for AER, indoor, and outdoor air concentrations for six pollutants (benzene, formaldehyde (HCHO), polycyclic aromatic hydrocarbons (PAH), carbon monoxide (CO), nitric oxide (NO), and nitrogen oxides (NO(x))), and selected meteorological variables. Consistent with expectations, AER tended to increase with the number of open exterior windows and doors. The 39 AER values measured during the study when all exterior doors and windows were closed varied from 0.36 to 2.29 h(-1) with a geometric mean (GM) of 0.77 h(-1) and a geometric standard deviation (GSD) of 1.435. The 27 AER values measured when at least one exterior door or window was opened varied from 0.50 to 15.8 h(-1) with a GM of 1.98 h(-1) and a GSD of 1.902. AER was also affected by temperature and wind speed, most noticeably when exterior windows and doors were closed. Results of a series of stepwise linear regression analyses suggest that (1) outdoor pollutant concentration and (2) indoor pollutant concentration during the preceding hour were the "variables of choice" for predicting indoor pollutant concentration in the test house under the conditions of this study. Depending on the pollutant and ventilation conditions, one or more of the following variables produced a small, but significant increase in the explained variance (R(2)-value) of the regression equations: AER, number and location of apertures, wind speed, air-conditioning operation, indoor temperature, outdoor temperature, and relative humidity. The indoor concentrations of CO, PAH, NO, and NO(x) were highly correlated with the corresponding outdoor concentrations. The indoor benzene concentrations showed only moderate correlation with outdoor benzene levels, possibly due to a weak indoor source. Indoor formaldehyde concentrations always exceeded outdoor levels, and the correlation between indoor and outdoor concentrations was not statistically significant, indicating the presence of a strong indoor source.

Air Pollution, Indoor↗

PubMed2004

Frequency of open windows in motor vehicles under varying temperature conditions: a videotape survey in Central North Carolina during 2001.

Air pollution exposures in the motor vehicle cabin are significantly affected by air exchange rate, a function of vehicle speed, window position, vent status, fan speed, and air conditioning use. A pilot study conducted in Houston, Texas, during September 2000 demonstrated that useful information concerning the position of windows, sunroofs, and convertible tops as a function of temperature and vehicle speed could be obtained through the use of video recorders. To obtain similar data representing a wide range of temperature and traffic conditions, a follow-up study was conducted in and around Chapel Hill, North Carolina at five sites representing a central business district, an arterial road, a low-income commercial district, an interstate highway, and a rural road. Each site permitted an elevated view of vehicles as they proceeded through a turn, thereby exposing all windows to the stationary camcorder. A total of 32 videotaping sessions were conducted between February and October 2001, in which temperature varied from 41 degrees F to 93 degrees F and average vehicle speed varied from 21 to 77 mph. The resulting video tapes were processed to create a vehicle-specific database that included site location, date, time, vehicle type, vehicle color, vehicle age, window configuration, number of windows in each of three position categories (fully open, partially open, and closed), meteorological factors, and vehicle speed. Of the 4715 vehicles included in the database, 1905 (40.4%) were labeled as "open," indicating a window, sunroof, or convertible top was fully or partially open. Stepwise linear regression analyses indicated that "open" window status was affected by wind speed, relative humidity, vehicle speed, cloud cover, apparent temperature, day of week, time of day, vehicle type, vehicle age, vehicle color, number of windows, sunroofs, location, and air quality season. Open windows tended to occur less frequently when relative humidity was high, apparent temperature (a parameter incorporating wind chill and heat index) was below 50 degrees F, or the vehicle was relatively new. Although the effects of the identified parameters were relatively weak, they are statistically significant and should be considered by researchers attempting to model vehicle air exchange rates.

Air Movements↗

PubMed2002

Determining the frequency of open windows in motor vehicles: a pilot study using a video camera in Houston, Texas during high temperature conditions.

Researchers have developed a variety of computer-based models to estimate population exposure to air pollution. These models typically estimate exposures by simulating the movement of specific population groups through defined microenvironments. Exposures in the motor vehicle microenvironment are significantly affected by air exchange rate, which in turn is affected by vehicle speed, window position, vent status, and air conditioning use. A pilot study was conducted in Houston, Texas, during September 2000 for a specific set of weather, vehicle speed, and road type conditions to determine whether useful information on the position of windows, sunroofs, and convertible tops could be obtained through the use of video cameras. Monitoring was conducted at three sites (two arterial roads and one interstate highway) on the perimeter of Harris County located in or near areas not subject to mandated Inspection and Maintenance programs. Each site permitted an elevated view of vehicles as they proceeded through a turn, thereby exposing all windows to the stationary video camera. Five videotaping sessions were conducted over a two-day period in which the Heat Index (HI)-a function of temperature and humidity-varied from 80 to 101 degrees F and vehicle speed varied from 30 to 74 mph. The resulting videotapes were processed to create a master database listing vehicle-specific data for site location, date, time, vehicle type (e.g., minivan), color, window configuration (e.g., four windows and sunroof), number of windows in each of three position categories (fully open, partially open, and closed), HI, and speed. Of the 758 vehicles included in the database, 140 (18.5 percent) were labeled as "open," indicating a window, sunroof, or convertible top was fully or partially open. The results of a series of stepwise linear regression analyses indicated that the probability of a vehicle in the master database being "open" was weakly affected by time of day, vehicle type, vehicle color, vehicle speed, and HI. In particular, open windows occurred more frequently when vehicle speed was less than 50 mph during periods when HI exceeded 99.9 degrees F and the vehicle was a minivan or passenger van. Overall, the pilot study demonstrated that data on factors affecting vehicle window position could be acquired through a relatively simple experimental protocol using a single video camera. Limitations of the study requiring further research include the inability to determine the status of the vehicle air conditioning system; lack of a wide range of weather, vehicle speed, and road type conditions; and the need to exclude some vehicles from statistical analyses due to ambiguous window positions.

Air Movements↗