56 research outputs found
Outdoor, Indoor, and Personal Exposure to VOCs in Children
We measured volatile organic compound (VOC) exposures in multiple locations for a diverse population of children who attended two inner-city schools in Minneapolis, Minnesota. Fifteen common VOCs were measured at four locations: outdoors (O), indoors at school (S), indoors at home (H), and in personal samples (P). Concentrations of most VOCs followed the general pattern O ≈ S < P ≤ H across the measured microenvironments. The S and O environments had the smallest and H the largest influence on personal exposure to most compounds. A time-weighted model of P exposure using all measured microenvironments and time–activity data provided little additional explanatory power beyond that provided by using the H measurement alone. Although H and P concentrations of most VOCs measured in this study were similar to or lower than levels measured in recent personal monitoring studies of adults and children in the United States, p-dichlorobenzene was the notable exception to this pattern, with upper-bound exposures more than 100 times greater than those found in other studies of children. Median and upper-bound H and P exposures were well above health benchmarks for several compounds, so outdoor measurements likely underestimate long-term health risks from children’s exposure to these compounds
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Impact of Outdoor Air Pollution on Indoor Air Quality in Low-Income Homes during Wildfire Seasons
Indoor and outdoor number concentrations of fine particulate matter (PM2.5), black carbon (BC), carbon monoxide (CO), and nitrogen dioxide (NO2) were monitored continuously for two to seven days in 28 low-income homes in Denver, Colorado, during the 2016 and 2017 wildfire seasons. In the absence of indoor sources, all outdoor pollutant concentrations were higher than indoors except for CO. Results showed that long-range wildfire plumes elevated median indoor PM2.5 concentrations by up to 4.6 times higher than outdoors. BC, CO, and NO2 mass concentrations were higher indoors in homes closer to roadways compared to those further away. Four of the homes with mechanical ventilation systems had 18% higher indoor/outdoor (I/O) ratios of PM2.5 and 4% higher I/O ratios of BC compared to other homes. Homes with exhaust stove hoods had PM2.5 I/O ratios 49% less than the homes with recirculating hoods and 55% less than the homes with no stove hoods installed. Homes with windows open for more than 12 hours a day during sampling had indoor BC 2.4 times higher than homes with windows closed. This study provides evidence that long-range wildfire plumes, road proximity, and occupant behavior have a combined effect on indoor air quality in low-income homes.</p
Truck and Multivehicle Truck Accidents with Injuries Near Colorado Oil and Gas Operations
Unconventional and conventional oil and gas (O&G) operations raise public health concerns, such as the potential impacts from trucking activity in communities that host these operations. In this work, we used two approaches to evaluate accidents in relation to O&G activities in the State of Colorado. First, we calculated the rate of truck accidents by computing the ratio of accident count and county population. When comparing counties with increased O&G operations to counties with less activity, we found that counties with more activity have greater rates of truck traffic accidents per capita (Rate Ratio = 1.07, p < 0.05, 95% CI: 1.01–1.13). Second, we laid a grid over the eleven counties of interest and counted, for each cell, the number of truck accidents, the number of multivehicle accidents with injuries, the number of homes, and the number of O&G wells. We then applied hurdle count models, using the accident counts as the outcomes and the number of homes and number of wells as independent variables. We found that both independent variables are significant predictors of truck accidents and multivehicle truck accidents. These accidents are of concern since they can have an impact on the people who live near O&G operations
Interpreting variability in population biomonitoring data: role of elimination kinetics
Biomarker concentrations in spot samples of blood and urine are implicitly interpreted as direct surrogates for long-term exposure magnitude in a variety of contexts including (1) epidemiological studies of potential health outcomes associated with general population chemical exposure, and (2) cross-sectional population biomonitoring studies. However, numerous factors in addition to exposure magnitude influence biomarker concentrations in spot samples, including temporal variation in spot samples because of elimination kinetics. The influence of half-life of elimination relative to exposure interval is examined here using simple first-order pharmacokinetic simulations of urinary concentrations in spot samples collected at random times relative to exposure events. Repeated exposures were modeled for each individual in the simulation with exposure amounts drawn from lognormal distributions with varying geometric standard deviations. Relative variation in predicted spot sample concentrations was greater than the variation in underlying dose distributions when the half-life of elimination was shorter than the interval between exposures, with the degree of relative variation increasing as the ratio of half-life to exposure interval decreased. Results of the modeling agreed well with data from a serial urine collection data set from the Centers for Disease Control. Data from previous studies examining intra-class correlation coefficients for a range of chemicals relying upon repeated sampling support the importance of considering the half-life relative to exposure frequency in design and interpretation of studies using spot samples for exposure classification and exposure estimation. The modeling and data sets presented here provide tools that can assist in interpretation of variability in cross-sectional biomonitoring studies and in design of studies utilizing biomonitoring data as markers for exposure
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