Genetic amniocentesis in multiple gestations

Thirty-one genetic amniocenteses involving multiple gestations were performed in the genetics unit between 1976 and 1982. Three sets of triplets were included. Precise locations of the sacs were determined using real-time ultrasonography and successful sampling of all sacs was accomplished. Spontaneous abortions occurred in two normal twins and one normal triplet gestation. Two therapeutic abortions were performed for fetal abnormalities. Two cases of discordance for trisomy 21 (one twin and one triplet) were allowed to continue; the twin case terminated at 25 weeks' gestation with neonatal deaths and the triplets are alive and well.     

Vegetation dynamics in abandoned crop fields on a Mediterranean island: Development of succession model and estimation of disturbance thresholds

This case study on the Sifnos island, Greece, assesses the main factors controlling vegetation succession following crop abandonment and describes the vegetation dynamics of maquis and phrygana formations in relation to alternative theories of secondary succession. Field survey data were collected and analysed at community as well as species level. The results show that vegetation succession on abandoned crop fields is determined by the combined effects of grazing intensity, soil and geological characteristics and time. The analysis determines the quantitative grazing thresholds that modify the successional pathway. Light grazing leads to dominance by maquis vegetation while overgrazing leads to phryganic vegetation. The proposed model shows that vegetation succession following crop abandonment is a complex multi-factor process where the final or the stable stage of the process is not predefined but depends on the factors affecting succession. An example of the use of succession models and disturbance thresholds as a policy assessment tool is presented by evaluating the likely vegetation impacts of the recent reform of the Common Agricultural Policy on Sifnos island over a 20–30-year time horizon.     

Labor market estimates of the senior discount for the value of statistical life

This article develops the first measures of age–industry job risks to examine the age variations in the value of statistical life. Because of the greater risk vulnerability of older workers, they face flatter wage-risk gradients than younger workers, which we show to be the case empirically. Accounting for this heterogeneity in hedonic market equilibria leads to estimates of the value of statistical life–age relationship that follows an inverted U shape. The estimates of the value of statistical life range from $6.4 million for younger workers to a peak of $9.0 million for those aged 35–44, and then a decline to $3.8 million for those aged 55–62. The decline of the estimated value of statistical life with age is consistent with there being some senior discount in the Clear Skies Initiative analysis.     

Axi-symmetric simulation of soil vapor extraction influenced by soil fracturing

Fracturing, either pneumatic or hydraulic, is a method to improve the performance of soil vapor extraction (SVE) in relatively low permeability soils (< 10(-5) cm/s). A two-dimensional model is presented to simulate trichloroethylene (TCE) soil vapor extraction modified by fracturing. Flow and transport is modeled using mobile macropore and micropore networks, which also have been identified in the literature as dual porosity, dual permeability, or heterogeneous flow models. In this model, fluids can flow in both the macropore and micropore networks. This represents a more general model compared to immobile micropore, mobile macropore models presented thus far in the literature for vapor flow and transport in two dimensions. The model considers pressure- and concentration-driven exchange between the macropore and micropore networks, concentration-driven exchange between the gas and sorbed phases within each network, and equilibrium exchange between the gas and water and a sorbed phase within each network. The parameters employed in an example simulation are based on field measurements made at a fractured site. Considered in the simulations were the influence of the volume percentage of fractures, the length of fractures, the relative location of the water table, and the influence of pulsed pumping. For these simulations, internetwork concentration-driven exchange most significantly affected mass removal. The volume percentage of fractures more significantly influence flow and mass removal than the length of fractures. The depth of the water table below the contamination plume only significantly influenced flow and mass removal when the water table was within 60 cm of the bottom of the contaminated soil in the vadose zone for the parameters considered in this study. Pulsed pumping was not found to increase the amount of mass removed in this study.     

Stormwater quality benefits of a porous friction course and its effect on pollutant removal by roadside shoulders.

This project has two main objectives; the first is to documents the effect of a porous friction course overlay on the quality of highway stormwater runoff, and the second is to assess pollutant removal of a vegetated area along the side of a road from both conventional and porous pavements. The quantity and quality of stormwater runoff from a four-lane divided highway in the Austin, Texas, area was monitored before and after the installation of a porous friction course (PFC). Observed concentrations of suspended solids and pollutants associated with particulate material were much lower in the runoff from the PFC compared with runoff from the conventional asphalt surface. The vegetated highway shoulder reduced the concentrations of many stormwater constituents from the conventional asphalt surface; however, the concentrations of these constituents in runoff produced by the PFC were so low that the vegetated area produced no further reduction in concentration.     

Spatial variability of PM2.5 in urban areas in the United States

Data from the U.S. Environmental Protection Agency's Aerometric Information Retrieval System (now known as the Air Quality System) database for 1999 and 2000 have been used to characterize the spatial variability of concentrations of particulate matter with aerodynamic diameter < or = 2.5 microg (PM2.5) in 27 urban areas across the United States. Different measures were used to quantify the degree of uniformity of PM2.5 concentrations in the urban areas characterized. It was observed that PM2.5 concentrations varied to differing degrees in the urban areas examined. Analyses of several urban areas in the Southeast indicated high correlations between site pairs and spatial uniformity in concentration fields. Considerable spatial variation was found in other regions, especially in the West. Even within urban areas in which all site pairs were highly correlated, a variable degree of heterogeneity in PM2.5 concentrations was found. Thus, even though concentrations at pairs of sites were highly correlated, their concentrations were not necessarily the same. These findings indicate that the potential for exposure misclassification errors in time-series epidemiologic studies exists.     

Real-time ozone mapping using a regression-interpolation hybrid approach, applied to Tucson, Arizona

Real-time ozone (O3) maps, intended for public access and mass media, are generated from spatially interpolating (i.e., kriging) sparse monitoring data and are typically characterized by over-smoothed surfaces that inadequately represent local-scale spatial patterns (e.g., averaged over 1 km2). In this paper, a hybrid regression-interpolation methodology is developed to enhance the representation of local-scale spatiotemporal patterns with an application to Tucson, Arizona. The mapping of local patterns is enhanced with pre-interpolation regression modeling of local-scale deviation-from-mean variability, preserving variation in the monitor data that is ubiquitous across the modeling domain (i.e., the areal mean). The model is trained on several years of deviation-from-mean hourly O3 data, and predictor variables are developed using theoretically and empirically derived proxy regression variables. The regression model explains a significant proportion of the variation in the data (r2 = 0.54), with an average error of 7.1 ppb. When augmented with the areal mean, the r2 of the pre-interpolation model increases to 0.847. Model residuals are then spatially interpolated to the extents of the modeling domain. Final concentration estimate maps are the summation of areal mean, regression, and spatially interpolated surfaces, preserving absolute values at monitor locations.