Statistical issues in farmworker studies.
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Agriculture↗
Biomedical subjects
Lance A Wallace
Publications and source records attributed to Lance A Wallace.
Source strengths of ultrafine and fine particles due to cooking with a gas stove.
Cooking, particularly frying, is an important source of particles indoors. Few studies have measured a full range of particle sizes, including ultrafine particles, produced during cooking. In this study, semicontinuous instruments with fine size discriminating ability were used to calculate particle counts in 124 size bins from 0.01 to 2.5 microm. Data were collected at 5 min intervals for 18 months in an occupied house. Tracer gas measurements were made every 10 min in each of 10 rooms of the house to establish air change rates. Cooking episodes (N = 44) were selected meeting certain criteria (high concentrations, no concurrent indoor sources, long smooth decay curves), and the number and volume of particles produced were determined for each size category. For each episode, the particle decay rate was determined and used to determine the source strength for each size category. The selected cooking episodes (mostly frying) were capable of producing about 10(14) particles over the length of the cooking period (about 15 min), more than 90% of them in the ultrafine (< 0.1 microm) range, with an estimated whole-house volume concentration of 50 (microm/cm)3. More than 60% of this volume occurred in the 0.1-0.3 microm range. Frying produced peak numbers of particles at about 0.06 microm, with a secondary peak at 0.01 microm. The peak volume occurred at a diameter of about 0.16 microm. Since the cooking episodes selected were biased toward higher concentrations, the particle concentrations measured during about 600 h of morning and evening cooking over a full year were compared to concentrations measured during noncooking periods at the same times. Cooking was capable of producing more than 10 times the ultrafine particle number observed during noncooking periods. Levels of PM2.5 were increased during cooking by a factor of 3. Breakfast cooking (mainly heating water for coffee and using an electric toaster) produced concentrations about half those produced from more complex dinnertime cooking. Although the number and volume concentrations observed depend on air change rates, house volume, and deposition rates due to fans and filters, the source strengths calculated here are independent of these variables and may be used to estimate number and volume concentrations in other types of homes with widely varying volumes, ventilation rates, and heating and air-conditioning practices.
Air Pollution, Indoor↗
Particle concentrations in inner-city homes of children with asthma: the effect of smoking, cooking, and outdoor pollution.
Inner-city children have high rates of asthma. Exposures to particles, including allergens, may cause or exacerbate asthma symptoms. As part of an epidemiologic study of inner-city children with asthma, continuous (10-min average) measurements of particle concentrations were made for 2-week periods in 294 homes drawn from seven cities. Measurements were made using an optical scattering device that is most sensitive to fine particles. The concentrations recorded by these devices were corrected to agree with colocated outdoor gravimetric PM2.5 monitors. Indoor concentrations in the homes averaged 27.7 (standard deviation = 35.9) micro g/m3, compared with concurrent outdoor concentrations of 13.6 (7.5) micro g/m3. A multivariate model indicated that outdoor particles penetrated indoors with an efficiency of 0.48 and were therefore responsible for only 25% of the mean indoor concentration. The major indoor source was smoking, which elevated indoor concentrations by 37 micro g/m3 in the 101 homes with smokers. Other significant sources included frying, smoky cooking events, use of incense, and apartment housing, although the increases due to these events ranged only from 3 to 6 micro g/m3. The 10-min averaging time allowed calculation of an average diurnal variation, showing large increases in the evening due to smoking and smaller increases at meal times due to cooking. Most of the observed variance in indoor concentrations was day to day, with roughly similar contributions to the variance from visit to visit and home to home within a city and only a small contribution made by variance among cities. The small variation among cities and the similarity across cities of the observed indoor air particle distributions suggest that sources of indoor concentrations do not vary considerably from one city to the next, and thus that simple models can predict indoor air concentrations in cities having only outdoor measurements.
Air Pollutants↗
Real-time indoor and outdoor measurements of black carbon in an occupied house: an examination of sources.
Black carbon (BC) was measured every 5 min for two years (May 1998-May 2000) inside and immediately outside a northern Virginia house (suburban Washington, DC) occupied by two nonsmokers. Two aethalometers, which measure BC by optical transmission through a quartz fiber tape, were employed indoors and outdoors. Meteorological parameters were obtained on an hourly basis from nearby Dulles airport. Indoor activities were recorded to identify indoor sources such as combustion activities, which occurred 9% of the time during the first year and 4% of the time during the second year. At times without indoor sources, indoor/outdoor BC ratios averaged 0.53 in the first year and 0.35 in the second year. The main outdoor source of BC was the general regional background, contributing 83-84% of the total during each of the two years. Morning rush hour traffic contributed 8-9% of the total BC. An evening peak in the fall and winter, thought to include contributions from wood burning, was responsible for approximately 8% of the annual average BC concentration. The main indoor sources of BC were cooking and candle burning, contributing 16 and 31%, respectively, of the annual average indoor concentrations in the two years. Relative humidity (RH) affected the outdoor aethalometer in both years. An artifact associated with the tape advance was noted for the aethalometer, but a correction factor was developed that reduced the associated error by a factor of 2.
Air Pollutants↗
The effect of opening windows on air change rates in two homes.
More than 300 air change rate experiments were completed in two occupied residences: a two-story detached house in Redwood City, CA, and a three-story townhouse in Reston, VA. A continuous monitor was used to measure the decay of SF6 tracer gas over periods of 1-18 hr. Each experiment first included a measurement of the air change rate with all exterior doors and windows closed (State 0), then a measurement with the single change from State 0 conditions of opening one or more windows. The overall average State 0 air change rate was 0.37 air changes per hour (hr(-1)) (SD = 0.10 hr(-1); n = 112) for the California house and 0.41 hr(-1) (SD = 0.19 hr(-1); n = 203) for the Virginia house. Indoor/outdoor temperature differences appeared to be responsible for the variation at the Virginia house of 0.15-0.85 hr(-1) when windows were closed. Opening a single window increased the State 0 air change rate by an amount roughly proportional to the width of the opening, reaching increments as high as 0.80 hr(-1) in the California house and 1.3 hr(-1) in the Virginia house. Multiple window openings increased the air change rate by amounts ranging from 0.10 to 2.8 hr(-1) in the California house and from 0.49 to 1.7 hr(-1) in the Virginia house. Compared with temperature differences and wind effects, opening windows produced the greatest increase in the air change rates measured in both homes. Results of this study indicate the importance of occupant window-opening behavior on a home's air change rate and the consequent need to incorporate this factor when estimating human exposure to indoor air pollutants.
Air Pollution, Indoor↗
Volatile organic compounds as breath biomarkers for active and passive smoking.
We used real-time breath measurement technology to investigate the suitability of some volatile organic compounds (VOCs) as breath biomarkers for active and passive smoking and to measure actual exposures and resulting breath concentrations for persons exposed to tobacco smoke. Experiments were conducted with five smoker/nonsmoker pairs. The target VOCs included benzene, 1,3-butadiene, and the cigarette smoke biomarker 2,5-dimethylfuran. This study includes what we believe to be the first measurements of 1,3-butadiene in smokers' and nonsmokers' breath. The 1,3-butadiene and 2,5-dimethylfuran peak levels in the smokers' breath were similar (360 and 376 microg/m(3), respectively); the average benzene peak level was 522 microg/m(3). We found higher peak values of the target chemicals and shorter residence times in the body than previously reported, probably because of the improved time resolution made possible by the continuous breath measurement method. The real-time breath analyzer also showed the presence of the chemicals after exposure in the breath of the nonsmokers, but at greatly reduced levels. Single breath samples collected in evacuated canisters and analyzed independently with gas chromatography/mass spectrometry confirmed the presence of the target compounds in the postexposure breath of the nonsmokers but indicated that there was some contamination of the breath analyzer measurements. This was likely caused by desorption of organics from condensed tar in the analyzer tubing and on the quartz fiber filter used to remove particles. We used the decay data from the smokers to estimate residence times for the target chemicals. A two-compartment exponential model generally gave a better fit to the experimental decay data from the smokers than a single-compartment model. Residence times for benzene, 1,3-butadiene, and 2,5-dimethylfuran ranged from 0.5 (1,3-butadiene) to 0.9 min (benzene) for tau1 and were essentially constant (14 min) for tau2. These findings will be useful in models of environmental tobacco smoke exposure and risk.
Adult↗