David T. Mage

Urban air pollution in megacities of the world

Abstract Urban air pollution is a major environmental problem in the developing countries of the world. WHO and UNEP created an air pollution monitoring network as part of the Global Environment Monitoring System. This network now covers over 50 cities in 35 developing and developed countries throughout the world. The analyses of the data reported by the network over the past 15–20 yr indicate that the lessons of the prior experiences in the developed countries (U.S.A., U.K.) have not been learned. A study of air pollution in 20 of the 24 megacities of the world (over 10 million people by year 2000) shows that ambient air pollution concentrations are at levels where serious health effects are reported. The expected rise of population in the next century, mainly in the developing countries with a lack of capital for air pollution control, means that there is a great potential that conditions will worsen in many more cities that will reach megacity status. This paper maps the potential for air pollution that cities will experience in the future unless control strategies are developed and implemented during the next several decades.

Estimating pesticide dose from urinary pesticide concentration data by creatinine correction in the Third National Health and Nutrition Examination Survey (NHANES-III)

The Third National Health and Nutrition Examination Survey (NHANES-III) of the Centers for Disease Control and Prevention (CDC) recorded data on the urinary concentrations of 12 chemicals (analytes), which were either pesticides or their metabolites, that represent exposure to certain pesticides, in urine samples collected from 1988 to 1994 from a cohort of 978 volunteer subjects, aged 20–59 years. We have used each subjects urinary creatinine concentration and their individual daily creatinine excretion rate (g/day) computed from their age, gender, height and weight, to estimate their daily excretion rate in μg analyte/kg/day. We discuss the mechanisms of excretion of the analytes and certain assumptions needed to compute the equivalent daily dietary intake (μg/kg/day) of the most likely parent pesticide compounds for each excreted analyte. We used literature data on the average amount of parent compound ingested per unit amount of the analyte excreted in the urine, and compared these estimated daily intakes to the US EPAs reference dose (RfD) values for each of those parent pesticides. A Johnson SB distribution (four-parameter lognormal) was fit to these data to estimate the national distribution of exclusive exposures to these 12 parent compounds. Only three such pesticides had a few predicted values above their RfD (lindane 1.6%; 2,4-dichlorophenol 1.3%; chlorpyrifos 0.02%). Given the possibility of a subjects dietary intake of a pesticides metabolites incorporated into treated food, our results show that few, if any, individuals in the general US population aged 20–59 years and not employed in pesticide application were likely to have exceeded the USEPA RfD for these parent compounds during the years studied.

VALIDATION OF THE SIMULATION OF HUMAN ACTIVITY AND POLLUTANT EXPOSURE (SHAPE) MODEL USING PAIRED DAYS FROM THE DENVER, CO, CARBON MONOXIDE FIELD STUDY

Abstract The U.S. Environmental Protection Agency (EPA) developed the Simulation of Human Activity and Pollutant Exposure (SHAPE) model to estimate the frequency distribution of population exposures to carbon monoxide (CO) by computer simulation of microenvironmental concentrations and human activity patterns. To validate the SHAPE model, measured personal CO exposures from an EPA study in Denver, CO, in the winter of 1982–83 were compared with estimates generated by the model. Microenvironmental CO concentrations for the model were generated by Monte Carlo simulation based on the Denver, microenvironmental data, but the activity simulation portions of the model were modified to accommodate real activity patterns from Denver. Observed and predicted population exposure frequency distributions then were compared. A total of 899 24-h responses from Denver yielded 772 usable profiles after invalid responses were eliminated, giving 336 paired days of observations (CO exposure profiles from two successive days for the same respondent). From these data, 22 microenvironments were identified with at least 10 measurements on each of the two days. Microenvironmental CO concentrations were calculated by subtracting hourly ambient background CO concentrations. Ambient background CO concentrations were estimated by three different approaches. All three yielded similar results, with the average value from all fixed monitoring sites performing slightly better than the nearest fixed monitoring site. For nearly every microenvironment, the study found negligible differences between the microenvironmental CO frequency distributions on the 2 days. The microenvironmental CO frequency distributions for Day 1 provided the basis for SHAPE model estimates of Day 2 exposure profiles, and the activity patterns were based on the Denver diaries for Day 2 (the observed times at which people entered and left each microenvironment). CO exposure profiles were calculated using Monte Carlo sampling from the Day 1 microenvironmental CO concentration distributions and adding the estimated ambient background components. The predicted frequency distributions of the 1- and 8-h maximum average CO concentrations agreed reasonably well with the observed frequency distributions. Mean values were quite similar, but the variability in the observed values exceeded the variability in the predicted values, which may be attributable to serial dependencies in a persons activities during a 24-h period and autocorrelation of microenvironmental concentrations and the finite nature of the distributions from which microenvironmental concentrations were sampled.

Predicting Particulate (PM10) Personal Exposure Distributions Using a Random Component Superposition Statistical Model

ABSTRACT This paper presents a new statistical model designed to extend our understanding from prior personal exposure field measurements of urban populations to other cities where ambient monitoring data, but no personal exposure measurements, exist. The model partitions personal exposure into two distinct components: ambient concentration and nonambient concentration. It is assumed the ambient and nonambient concentration components are uncorrelated and add together; therefore, the model is called a random component superposition (RCS) model. The 24-hr ambient outdoor concentration is multiplied by a dimensionless “attenuation factor” between 0 and 1 to account for deposition of particles as the ambient air infiltrates indoors. The RCS model is applied to field PM10 measurement data from three large-scale personal exposure field studies: THEES (Total Human Environmental Exposure Study) in Phillipsburg, NJ; PTEAM (Particle Total Exposure Assessment Methodology) in Riverside, CA; and the Ethyl Corporation study in Toronto, Canada. Because indoor sources and activities (smoking, cooking, cleaning, the personal cloud, etc.) may be similar in similar populations, it was hypothesized that the statistical distribution of nonambient personal exposure is invariant across cities.

Creatinine corrections for estimating children's and adult's pesticide intake doses in equilibrium with urinary pesticide and creatinine concentrations

A urine contaminant concentration per se has uncertain meaning for human health because of dilution by hydration. However, the estimation of the health-related daily intake dose of pollutant (mg/kg/day) that equilibrates with a spot urinary concentration of a pesticide residue or metabolite, or other analyte, can be made using creatinine-corrected toxicant levels (mg analyte/mg creatinine) multiplied by an estimate of the subjects’ expected creatinine excretion rates (mg creatinine/kg/day). The objective was to develop a set of equations predicting a persons expected daily creatinine excretion (mg/kg) as a function of age, gender, race and morphometry, from birth to old age. We review the creatinine excretion literature where infants, children and adults provided 24 h total urine samples for creatinine analysis. Equations are developed for infants (≤3 years), children (3–18 years) and adults (≥18 years) that match at 3 and 18 years. A series of equations that estimate daily creatinine excretion (mg/day) are developed that are piecewise continuous from birth through infancy through adolescence and through adulthood for males and females, and Black and White races. Complicating factors such as diet, health status and obesity are discussed. We propose that these equations, with caveat, can now be used with measured urine concentrations to consistently estimate the corresponding equilibrium intake doses of toxicants at ages from birth to 92 years for the healthy non-obese. We recommend that this system of equations be considered for future development and reporting of applied doses in mg/kg/day of pollutants and toxicants that are measured in urine samples, as in the National Health and Nutrition Examination Survey.

Indoor and outdoor PM2.5 and CO in high- and low-density Guatemalan villages.

Continuous particles less than 2.5 μm in diameter (PM2.5) and carbon monoxide (CO) were monitored during breakfast, lunch, and dinner in three high-density and four low-density villages near Quetzaltenango, Guatemala to help assess the viability of this region for a proposed respiratory health and stove intervention study. Approximately 15 homes were visited during each mealtime in each of the seven villages; in all, 98 homes were visited, with a sampling duration of 2–3 min per home per meal. For each village, a line (transect) was drawn on a village map along existing roads from one end of the village to the other; homes and between-home outside locations along the transect were monitored. Although the predominant stove type was the open fire, several other stoves, in various levels of disrepair, were observed frequently. The highest indoor concentrations of PM2.5 were observed in homes using the open fire (avg.=5.31 mg/m3; SD=4.75 mg/m3) or equivalent, although homes using the plancha — indigenous wood-burning stove with chimney — also had measurements >13.8 mg/m3, PM2.5 limit of detection. The highest indoor concentrations of CO were also observed in homes using the open fire (avg.=22.9 ppm; SD=28.1 ppm), with a maximum measurement of >250 ppm. For both PM2.5 and CO, levels measured in homes with plancha, lorena, or open fire were significantly higher than levels taken in the street or in homes using a gas stove. The Spearman correlation coefficient between PM2.5 and CO for all data combined was 0.81, and ranged from 0.30 for the lorena to 0.68 for the plancha in homes using wood-fueled stoves. Although indoor PM2.5 and CO levels were not significantly different between high- and low-density villages, street-level PM2.5 (p=0.002) and CO (p=0.002), were significantly higher in the high-density villages. These data provide a useful picture of the pollution levels coming from a range of cooking stoves in various levels of disrepair, as well as a representation of how outdoor particle mass and CO levels vary from high- versus low -density villages.

Estimating perchlorate exposure from food and tap water based on US biomonitoring and occurrence data

Human biomonitoring data show that exposure to perchlorate is widespread in the United States. The predominant source of intake is food, whereas drinking water is a less frequent and far smaller contributor. We used spot urine samples for over 2700 subjects and estimated 24 h intake using new creatinine adjustment equations. Merging data from surveys of national health (NHANES) with drinking water monitoring (UCMR), we categorized survey participants according to their potential exposure through drinking water or food. By subtracting daily food doses of perchlorate from the oral reference dose (RfD), we derive an allowances for perchlorate in tap water for several populations. The calculated mean food perchlorate dose in the United States was 0.081 μg/kg/day compared to 0.101 μg/kg/day for those who also had a potential drinking water component. The calculated 95th percentile doses, typically falling between 0.2 and 0.4 μg/kg/day, were well below the RfD (0.7 μg/kg/day) in all populations analyzed. Children aged 6–11 years had the highest mean perchlorate doses in food (0.147 μg/kg/day), with an additional water contribution of only 0.003 μg/kg/day representing just 2% of exposure. Pregnant women had a mean food dose of 0.093 vs 0.071 μg/kg/day for all women of reproductive age. At the 95th percentile intake for both the total population and women of child-bearing age (15–44), the perchlorate contribution from food was 86% and from drinking water 14% (respectively, 30% and 5% of the RfD). At the mean for the same groups, the food to water contribution ratio is approximately 80:20. We calculate that an average 66 kg pregnant woman consuming a 90th percentile food dose (0.198 μg/kg/day) could also drink the 90th percentile of community water for pregnant women (0.033 l/kg/day) containing 15 μg/l perchlorate without exceeding the 0.7 μg/kg/day reference dose.

The fifty percent male excess of infant respiratory mortality

Aim: To test whether infant mortality from clearly respiratory causes has a consistent male excess that is different from the male excess in most cardiac conditions. Methods: Analysis of male excess in infant mortality data from the United States and from north European countries. Data are analyzed for the period 1979–2002 in autopsied and unautopsied cohorts. Results: Several modes of respiratory death in infancy are characterized by an approximate 50% male excess. This common excess is demonstrated in vital statistics for infant respiratory distress syndrome, sudden infant death syndrome, inhalation of food and other objects causing obstruction of respiratory tract or suffocation, congenital pneumonia, viral pneumonia, bronchiolitis and bronchitis, and accidental drowning. Results are presented for these and other respiratory causes of mortality in all United States infant deaths from 1979–1998 and for sudden infant death syndrome from the United Kingdom and Scandinavia. In sudden infant death syndrome, the common male excess appears to exist only for the autopsied post‐neonatal cases. Comparisons are made to the male excess mortality from congenital cardiac anomalies showing a similarly large male excess for those conditions resulting in severe hypoxic and ischemic hypoxia.

An Explicit Solution for SB Parameters Using Four Percentile Points

The S B distributions were defined by Johnson (1949). Tables for fitting the four S B parameters by the method of moments have been provided by Johnson and Kitchen (1971a, b). Bukac (1972) showed that a choice of four symmetrical and equidistant standard normal deviates simplified the solution to allow a direct solution of a quartic equation for the S B parameters. This paper presents a method of reducing Bukacs quartic equations to a quadratic equation which leads to an explicit solution for the S B parameters.

An evaluation of the methods of fractiles, moments and maximum likelihood for estimating parameters when sampling air quality data from a stationary lognormal distribution

Abstract Air pollution control officials often make the simplifying assumption that air pollutant concentrations are independent samples from a stationary probability distribution. If the parent distribution really is stationary and correctly chosen, maximum likelihood estimation almost always will provide the best possible estimate of its parameters. However, the air pollution literature makes little if any mention of this fact and often suggests using the method of moments or the method of fractiles to estimate the parameters of an assumed distribution, and using the results for computing design values to determine the control level required to meet an air quality standard. No estimate is made in the air pollution literature of the magnitude of the difference produced by these different methods. This paper investigates the effectiveness of three different approaches for estimating parameters using a lognormal distribution as an example: (a) method of fractiles; (b) method of moments and (c) method of maximum likelihood. The error associated with each approach for computing emission controls is determined by sampling from a true stationary lognormal distribution using computer simulation. These results then are compared with a fourth approach, direct empirical linear rollback, in which no model is used and design values are calculated using raw observations. The latter approach often is used in practical situations by air pollution control personnel. In 100 simulated years at a site experiencing the same lognormally distributed air pollution in the precontrol state, the correct control level was 50%. The following control levels were calculated: Empirical rollback, 22–82%; Method of fractiles, 32–64%; Method of moments, 41–59% and Method of maximum likelihood, 46–54%, with most years very close to the true value of 50%. Thus, the maximum likelihood approach effectively reduces the variance by ‘filtering out’ the effect of random phenomena occurring during the year and would be the method of choice if the observations are indeed distributed as they are assumed.