Application of the probability-based Maryland Biological Stream Survey to the state’s assessment of water quality standards

The Clean Water Act presents a daunting task for states by requiring them to assess and restore all their waters. Traditional monitoring has led to two beliefs: (1) ad hoc sampling (i.e., non-random) is adequate if enough sites are sampled and (2) more intensive sampling (e.g., collecting more organisms) at each site is always better. We analyzed the 1,500 Maryland Biological Stream Survey (MBSS) random sites sampled in 2000–2004 to describe the variability of Index of Biotic Integrity (IBI) scores at the site, reach, and watershed scales. Average variability for fish and benthic IBI scores increased with increasing spatial scale, demonstrating that single site IBI scores are not representative at watershed scales and therefore at best 25% of a state’s stream length can be representatively sampled with non-random designs. We evaluated the effects on total taxa captured and IBI precision of sampling for twice as many benthic macroinvertebrates at 73 MBSS sites with replicate samples. When sampling costs were fixed, the precision of the IBI decreased as the number of sites had to be reduced by 15%. Only 1% more taxa were found overall when the 73 sites where combined. We concluded that (1) comprehensive assessment of a state’s waters should be done using probability-based sampling that allows the condition across all reaches to be inferred statistically and (2) additional site sampling effort should not be incorporated into state biomonitoring when it will reduce the number of sites sampled to the point where overall assessment precision is lower.     

A New Mathematical Approach in Environmental and Life Sciences: Gene–Environment Networks and Their Dynamics

An important research area in life sciences is devoted to modeling, prediction, and dynamics of gene-expression patterns. As clearly understood in these days, this enterprise cannot become satisfactory without acknowledging the role of the environment. To a representation of past, present, and most likely future states, we also encounter measurement errors and uncertainties. This paper surveys and improves recent advances in understanding the foundations and interdisciplinary implications of the newly introduced gene–environment networks, and it integrates the important theme of carbon dioxide emission reduction into the networks and dynamics. We also introduce some operational and managerial issues of practical working and decision making, expressed in terms of sliding windows, quadrants (modules) of parametric effects, and navigating (controlling) between such effects and directing them. Given data from DNA microarray experiments and environmental records, we extract nonlinear ordinary differential equations that contain parameters that have to be determined. For this, we employ modern (Chebychevian) approximation and (generalized semi-infinite) optimization. After this is provided, time- discretized dynamical systems are studied. A combinatorial algorithm with polyhedra sequences allows to detect the region of parametric stability. Finally, we analyze the topological landscape of gene–environment networks with its structural (in)stability. By embedding as a module and investigating CO₂ emission control and figuring out game theoretical aspects, we conclude. This pioneering work is theoretically elaborated, practically devoted to health care, medicine, education, living conditions, and environmental protection, and it invites the readers to future research.      

Long-term study of palladium in road tunnel dust and sewage sludge ash

The present work summarizes data about palladium contents of road tunnel dust from 1994 to 2007 and sewage sludge ash from 1972 to 2006. Since palladium is emitted from automotive catalytic converters as elemental particles, road dust is quiet useful to study traffic-related Pd emissions. Very high Pd values of up to 516 μg Pd kg⁻¹ were found in the road dust samples collected in 2007. Heavy metals of all urban emissions, also dental practice effluent, are enriched in sewage sludge ash and thus this matrix is useful for the documentation of palladium emission caused by the use of Pd alloys in dental medicine. In sewage sludge ash highest Pd contents of maximum 460 μg Pd kg⁻¹ were found in the years 1986-1997. In both matrices correlations of Pd content to Pd demand of industry are discussed.     

Lagrangian sampling of 3-D air quality model results for regional transport contributions to sulfate aerosol concentrations at Baltimore,MD, in summer 2004

We use ensemble-mean Lagrangian sampling of a 3-D Eulerian air quality model, CMAQ, together with ground-based ambient monitors data from several air monitoring networks and satellite (MODIS) observations to provide source apportionment and regional transport vs. local contributions to sulfate aerosol and PM_2.5 concentrations at Baltimore, MD, for summer 2004. The Lagrangian method provides estimates of the chemical and physical evolution of air arriving in the daytime boundary layer at Baltimore. Study results indicate a dominant role for regional transport contributions on those days when sulfate air pollution is highest in Baltimore, with a principal transport pathway from the Ohio River Valley (ORV) through southern Pennsylvania and Maryland, consistent with earlier studies. Thus, reductions in sulfur emissions from the ORV under the EPA's Clean Air Interstate Rule may be expected to improve particulate air quality in Baltimore during summer. The Lagrangian sampling of CMAQ offers an inexpensive and complimentary approach to traditional methods of source apportionment based on multivariate observational data analysis, and air quality model emissions separation. This study serves as a prototype for the method applied to Baltimore. EPA is establishing a system to allow air quality planners to readily produce and access equivalent results for locations of their choice.     

SOCIOECONOMIC IMPACTS OF CLIMATE CHANGE ON U.S. WATER SUPPLIES1

ABSTRACT: A greenhouse warming would have major effects on water supplies and demands. A framework for examining the socioeconomic impacts associated with changes in the long-term availability of water is developed and applied to the hydrologic implications of the Canadian and British Hadley2 general circulation models (GCMs) for the 18 water resource regions in the conterminous United States. The climate projections of these two GCMs have very different implications for future water supplies and costs. The Canadian model suggests most of the nation would be much drier in the year 2030. Under the least-cost management scenario the drier climate could add nearly $105 billion to the estimated costs of balancing supplies and demands relative to the costs without climate change. Measures to protect instream flows and irrigation could result in significantly higher costs. In contrast, projections based on the Hadley model suggest water supplies would increase throughout much of the nation, reducing the costs of balancing water supplies with demands relative to the no-climate-change case.     

Spatio-temporal covariation of urban particle number concentration and ambient noise

Mobile measurements of ambient noise and particle number concentrations were carried out within an urban residential area in Essen, Germany, during summer 2008. A busy major road with a traffic intensity of about 44,000 vehicles per day was situated within the study area. The spatio-temporal distribution of noise and particles was closely coupled to road traffic on the major road. Total particle number concentrations in proximity to the main road were on average between 25,000 cm^?3 and 35,000 cm^?3 while sound levels reached 70–78 dB(A). These estimates were more than double-fold (factor 2.4) in comparison to the urban residential background. At a 50 m distance off the road particle number concentrations were decaying to about 50% of the initial value. The measurements were characterised by close spatial correlation between total particle number concentration and ambient noise with correlation coefficients of up to r = 0.74. However, during one measurement day coupling between both quantities was weak due to higher turbulent mixing within the canopy layer and a change in ambient wind directions. Enhanced dilution of particle emission from road traffic by turbulent mixing and ‘decoupling’ from the influence of road traffic are believed to be responsible.     

Effect of soil ageing on in vivo arsenic bioavailability in two dissimilar soils

Arsenic (As) bioavailability in spiked soils aged for up to 12 months was assessed using in vitro and in vivo methodologies. Ageing (natural attenuation) of spiked soils resulted in a decline in in vivo As bioavailability (swine assay) of over 75% in soil A (Red Ferrosol) but had no significant effect on in vivo As bioavailability even after 12 months of ageing in soil B (Brown Chromosol). Sequential fractionation, however, indicated that there was repartitioning of As within the soil fractions extracted during the time course investigated. In soil A, the As fraction associated with the more weakly bound soil fractions decreased while the residual fraction increased from 12% to 35%. In contrast, little repartitioning of As was observed in soil B indicating that natural attenuation may be only applicable for As in soils containing specific mineralogical properties.     

Application of an in vivo swine model for the determination of arsenic bioavailability in contaminated vegetables

Considerable information is available in the literature regarding the uptake of arsenic (As) from contaminated soil and irrigation water by vegetables. However, few studies have investigated As speciation in these crops while a dearth of information is available on As bioavailability following their consumption. In this study, the concentration and speciation of As in chard, radish, lettuce and mung beans was determined following hydroponic growth of the vegetables using As-contaminated water. In addition, As bioavailability was assessed using an in vivo swine feeding assay. While As concentrations ranged from 3.0 to 84.2mg As kg(-1) (dry weight), only inorganic As (arsenite and arsenate) was detected in the edible portions of the vegetables. When As bioavailability was assessed through monitoring blood plasma As concentrations following swine consumption of As-contaminated vegetables, between 50% and 100% of the administered As dose was absorbed and entered systemic circulation. Arsenic bioavailability decreased in the order mung beans>radish>lettuce=chard.     

Analysing the influence of different street vegetation on traffic-induced particle dispersion using microscale simulations

Urban vegetation can be viewed as compensation to the environmental drawbacks of urbanisation. However, its ecosystem function is not well-known and, for urban planning, vegetation is mainly considered as an element of urban design. This article argues that planning practice needs to re-examine the impact of vegetation cover in the urban fabric given our evaluation of vegetation's effects on air quality, including the dispersion of traffic-induced particles at street level. Using the three-dimensional microclimate model ENVI-met?, we evaluate these effects regarding the height-to-width ratio of streets flanked by buildings and the vertical and horizontal density of street vegetation. Our results reveal vegetation's effect on particle dispersion through its influence on street ventilation. In general, vegetation was found to reduce wind speed, causing inhibition of canyon ventilation and, consequently, an increase in particle concentrations. Vegetation was also found to reduce wind speed at crown-height and to disrupt the flow field in close vicinity to the canopy. With increasing height-to-width ratio of street canyons, wind speed reduction increases and the disturbance of the flow impacts across a canyon's entire width. We also found that the effect is more pronounced in configurations with poor ventilation, such as the low wind speed, perpendicular inflow direction, and in deep canyons cases.     

Infant Mortality and Air Pollution: A Comprehensive Analysis of U.S. Data for 1990

ABSTRACT

This paper uses U.S. linked birth and death records to explore associations between infant mortality and environmental factors, based on spatial relationships. The analysis considers a range of infant mortality end points, regression models, and environmental and socioeconomic variables. The basic analysis involves logistic regression modeling of individuals; the cohort comprises all infants born in the United States in 1990 for whom the required data are available from the matched birth and death records. These individual data include sex, race, month of birth, and birth weight of the infant, and personal data on the mother, including age, adequacy of prenatal care, and smoking and education in most instances. Ecological variables from Census and other sources are matched on the county of usual residence and include ambient air quality, elevation above sea level, climate, number of physicians per capita, median income, racial and ethnic distribution, unemployment, and population density. The air quality variables considered were 1990 annual averages of PM₁₀, CO, SO₂, SO₄ ^2-, and “non-sulfate PM₁₀” (NSPM₁₀—obtained by subtracting the estimated SO₄ ^2-mass from PM₁₀). Because all variables were not available for all counties (especially maternal smoking), it was necessary to consider various subsets of the total cohort.

We examined all infant deaths and deaths by age (neonatal and postneonatal), by birth weight (normal and low [<2500 g]), and by specific causes within these categories. Special attention was given to sudden infant death syndrome (SIDS). For comparable modeling assumptions, the results for PM₁₀ agreed with previously published estimates; however, the associations with PM₁₀ were not specific to probable exposures or causes of death and were not robust to changes in the model and/or the locations considered. Significant negative mortality associations were found for SO₄ ^2-. There was no indication of a role for outdoor PM_2.5, but possible contributions from indoor air pollution sources cannot be ruled out, given higher SIDS rates in winter, in the north and west, and outside of large cities.