Site Sampling and Treatability Studies for Demonstration of WasteChem’s Asphalt Encapsulation Technology Under EPA’s SITE Program

ABSTRACT

Exposures from indoor environments are a major issue for evaluating total long-term personal exposures to the fine fraction (<2.5μm in aerodynamic diameter) of particulate matter (PM). It is widely accepted in the indoor air quality (IAQ) research community that biocontamination is one of the important indoor air pollutants. Major indoor air biocontaminants include mold, bacteria, dust mites, and other antigens. Once the biocontaminants or their metabolites become airborne, IAQ could be significantly deteriorated. The airborne biocontaminants or their metabolites can induce irritational, allergic, infectious, and chemical responses in exposed individuals.

Biocontaminants, such as some mold spores or pollen grains, because of their size and mass, settle rapidly within the indoor environment. Over time they may become nonviable and fragmented by the process of desiccation. Desiccated nonviable fragments of organisms are common and can be toxic or allergenic, depending upon the specific organism or organism component. Once these smaller and lighter fragments of biological PM become suspended in air, they have a greater tendency to stay suspended. Although some bioaerosols have been identified, few have been quantitatively studied for their prevalence within the total indoor PM with time, or for their affinity to penetrate indoors.

This paper describes a preliminary research effort to develop a methodology for the measurement of nonvi-able biologically based PM, analyzing for mold and ragweed antigens and endotoxins. The research objectives include the development of a set of analytical methods and the comparison of impactor media and sample size, and the quantification of the relationship between outdoor and indoor levels of bioaerosols. Indoor and outdoor air samples were passed through an Andersen nonviable cascade impactor in which particles from 0.2 to 9.0 um were collected and analyzed. The presence of mold, ragweed, and endotoxin was found in all eight size ranges. The presence of respirable particles of mold and pollen found in the fine particle size range from 0.2 to 5.25 um is evidence of fragmentation of larger source particles that are known allergens.     

IMPACTS OF CLIMATE CHANGE ON MISSOURI RWER BASIN WATER YIELD1

ABSTRACT: Water from the Missouri River Basin is used for multiple purposes. The climatic change of doubling the atmospheric carbon dioxide may produce dramatic water yield changes across the basin. Estimated changes in basin water yield from doubled CO₂ climate were simulated using a Regional Climate Model (RegCM) and a physically based rainfall‐runoff model. RegCM output from a five‐year, equilibrium climate simulation at twice present CO₂ levels was compared to a similar present‐day climate run to extract monthly changes in meteorologic variables needed by the hydrologic model. These changes, simulated on a 50‐km grid, were matched at a commensurate scale to the 310 subbasin in the rainfall‐runoff model climate change impact analysis. The Soil and Water Assessment Tool (SWAT) rainfall‐runoff model was used in this study. The climate changes were applied to the 1965 to 1989 historic period. Overall water yield at the mouth of the Basin decreased by 10 to 20 percent during spring and summer months, but increased during fall and winter. Yields generally decreased in the southern portions of the basin but increased in the northern reaches. Northern subbasin yields increased up to 80 percent: equivalent to 1.3 cm of runoff on an annual basis.     

Female mate choice in the zebra finch — the effect of male beak colour and male song

Studies of female mate preference in zebra finches (Taenopygia guttata) have shown that male beak colour and song rate are important. However, the two characters are correlated. Here the effect of beak colour and song rate on female choice are examined independently. In mate choice tests involving two males, beak colour was manipulated artificially using nail varnish. The results showed that females showed a significant preference for males with a high song rate, but not with a red beak. Females did not prefer males with a red beak if song rate was low and females preferred males with orange beaks who expressed a high song rate. Female preference for males with red beaks was not found when beak and song characters were no longer correlated.     

Patterns and ecological predictors of age-related performance in female North American barn swallows,Hirundo rustica erythrogaster

Life history theory describes the optimization of important trade-offs within an individual’s lifetime and predicts that an individual’s reproductive performance (RP) will improve up until a point of senescence. Despite abundant evidence for this pattern, relatively few studies consider the mechanisms associated with age-related improvements in RP. In this study, we aimed to describe patterns of age-related RP (seasonal fledgling production) in female North American barn swallows (Hirundo rustica erythrogaster) using a longitudinal data set to test multiple hypotheses about the social, morphological, and ecological factors underlying this prominent life history pattern. To address these objectives, we used generalized linear mixed models in a three-step series of analyses in which we assessed (1) patterns of female age-related RP; (2) the influence of age on changes in social, morphological, and ecological factors; and (3) whether the changes in RP were concomitant with changes in these factors. We found that (1) females showed patterns of age-related reproduction, in which performance increased in the first 2 years of breeding and decreased thereafter, (2) female tail streamer length increased and the extent of breast coloration increased then decreased significantly with age, and (3) changes in morphological traits did not covary with changes in reproductive performance over time. Our within-individual results highlight the importance of considering explicit links between morphology and reproductive performance that are not easily captured by population-level analyses.     

Modeling resource selection using polytomous logistic regression and kernel density estimates

Wildlife resource selection studies typically compare used to available resources; selection or avoidance occurs when use is disproportionately greater or less than availability. Comparing used to available resources is problematic because results are often greatly influenced by what is considered available to the animal. Moreover, placing relocation points within resource units is often difficult due to radiotelemetry and mapping errors. Given these problems, we suggest that an animal’s resource use be summarized at the scale of the home range (i.e., the spatial distribution of all point locations of an animal) rather than by individual points that are considered used or available. To account for differences in use-intensity throughout an animal’s home range, we model resource selection using kernel density estimates and polytomous logistic regression. We present a case study of elk (Cervus elaphus) resource selection in South Dakota to illustrate the procedure. There are several advantages of our proposed approach. First, resource availability goes undefined by the investigator, which is a difficult and often arbitrary decision. Instead, the technique compares the intensity of animal use throughout the home range. This technique also avoids problems with classifying locations rigidly as used or unused. Second, location coordinates do not need to be placed within mapped resource units, which is problematic given mapping and telemetry error. Finally, resource use is considered at an appropriate scale for management because most wildlife resource decisions are made at the level of the patch. Despite the advantages of this use-intensity procedure, future research should address spatial autocorrelation and develop spatial models for ordered categorical variables.     

Links among nitrification, nitrifier communities, and edaphic properties in contrasting soils receiving dairy slurry

Soil biotic and abiotic factors strongly influence nitrogen (N) availability and increases in nitrification rates associated with the application of manure. In this study, we examine the effects of edaphic properties and a dairy (Bos taurus) slurry amendment on N availability, nitrification rates and nitrifier communities. Soils of variable texture and clay mineralogy were collected from six USDA-ARS research sites and incubated for 28 d with and without dairy slurry applied at a rate of ~300 kg N ha(-1). Periodically, subsamples were removed for analyses of 2 M KCl extractable N and nitrification potential, as well as gene copy numbers of ammonia-oxidizing bacteria (AOB) and archaea (AOA). Spearman coefficients for nitrification potentials and AOB copy number were positively correlated with total soil C, total soil N, cation exchange capacity, and clay mineralogy in treatments with and without slurry application. Our data show that the quantity and type of clay minerals present in a soil affect nitrifier populations, nitrification rates, and the release of inorganic N. Nitrogen mineralization, nitrification potentials, and edaphic properties were positively correlated with AOB gene copy numbers. On average, AOA gene copy numbers were an order of magnitude lower than those of AOB across the six soils and did not increase with slurry application. Our research suggests that the two nitrifier communities overlap but have different optimum environmental conditions for growth and activity that are partly determined by the interaction of manure-derived ammonium with soil properties.     

A Comparison of Nonlinear Regression and Neural Network Models for Ground-Level Ozone Forecasting

ABSTRACT

A hybrid nonlinear regression (NLR) model and a neural network (NN) model, each designed to forecast next-day maximum 1-hr average ground-level O₃ concentrations in Louisville, KY, were compared for two O₃ seasons—1998 and 1999. The model predictions were compared for the forecast mode, using forecasted meteorological data as input, and for the hindcast mode, using observed meteorological data as input. The two models performed nearly the same in the forecast mode. For the two seasons combined, the mean absolute forecast error was 12.5 ppb for the NLR model and 12.3 ppb for the NN model. The detection rate of 120 ppb threshold exceedances was 42% for each model in the forecast mode. In the hindcast mode, the NLR model performed marginally better than the NN     

Phytoestrogens and mycotoxins in Iowa streams: an examination of underinvestigated compounds in agricultural basins

This study provides the first broad-scale investigation on the spatial and temporal occurrence of phytoestrogens and mycotoxins in streams in the United States. Fifteen stream sites across Iowa were sampled five times throughout the 2008 growing season to capture a range of climatic and crop-growth conditions. Basin size upstream from sampling sites ranged from 7 km2 to > 836,000 km2. Atrazine (herbicide) also was measured in all samples as a frame-of-reference agriculturally derived contaminant. Target compounds were frequently detected in stream samples: atrazine (100%), formononetin (80%), equol (45%), deoxynivalenol (43%), daidzein (32%), biochanin A (23%), zearalenone (13%), and genistein (11%). The nearly ubiquitous detection of formononetin (isoflavone) suggests a widespread agricultural source, as one would expect with the intense row crop and livestock production present across Iowa. Conversely, the less spatially widespread detections of deoxynivalenol (mycotoxin) suggest a more variable source due to the required combination of proper host and proper temperature and moisture conditions necessary to promote Fusarium spp. infections. Although atrazine concentrations commonly exceeded 100 ng L(-1) (42/75 measurements), only deoxynivalenol (6/56 measurements) had concentrations that occasionally exceeded this level. Temporal patterns in concentrations varied substantially between atrazine, formononetin, and deoxynivalenol, as one would expect for contaminants with different source inputs and processes of formation and degradation. The greatest phytoestrogen and mycotoxin concentrations were observed during spring snowmelt conditions. Phytoestrogens and mycotoxins were detected at all sampling sites regardless of basin size. The ecotoxicological effects from long-term, low-level exposures to phytoestrogens and mycotoxins or complex chemicals mixtures including these compounds that commonly rake place in surface water are poorly understood and have yet to be systematically investigated in environmental studies.     

A comparison of nonlinear regression and neural network models for ground-level ozone forecasting

A hybrid nonlinear regression (NLR) model and a neural network (NN) model, each designed to forecast next-day maximum 1-hr average ground-level O3 concentrations in Louisville, KY, were compared for two O3 seasons--1998 and 1999. The model predictions were compared for the forecast mode, using forecasted meteorological data as input, and for the hindcast mode, using observed meteorological data as input. The two models performed nearly the same in the forecast mode. For the two seasons combined, the mean absolute forecast error was 12.5 ppb for the NLR model and 12.3 ppb for the NN model. The detection rate of 120 ppb threshold exceedances was 42% for each model in the forecast mode. In the hindcast mode, the NLR model performed marginally better than the NN model. The mean absolute hindcast error was 11.1 ppb for the NLR model and 12.9 ppb for the NN model. The hindcast detection rate was 92% for the NLR model and 75% for the NN model.     

Nutrient and sediment concentrations and corresponding loads during the historic June 2008 flooding in eastern Iowa

A combination of above-normal precipitation during the winter and spring of 2007-2008 and extensive rainfall during June 2008 led to severe flooding in many parts of the midwestern United States. This resulted in transport of substantial amounts of nutrients and sediment from Iowa basins into the Mississippi River. Water samples were collected from 31 sites on six large Iowa tributaries to the Mississippi River to characterize water quality and to quantify nutrient and sediment loads during this extreme discharge event. Each sample was analyzed for total nitrogen, dissolved nitrate plus nitrite nitrogen, dissolved ammonia as nitrogen, total phosphorus, orthophosphate, and suspended sediment. Concentrations measured near peak flow in June 2008 were compared with the corresponding mean concentrations from June 1979 to 2007 using a paired t test. While there was no consistent pattern in concentrations between historical samples and those from the 2008 flood, increased flow during the flood resulted in near-peak June 2008 flood daily loads that were statistically greater (p < 0.05) than the median June 1979 to 2007 daily loads for all constituents. Estimates of loads for the 16-d period during the flood were calculated for four major tributaries and totaled 4.95 x 10(7) kg of nitrogen (N) and 2.9 x 10(6) kg of phosphorus (P) leaving Iowa, which accounted for about 22 and 46% of the total average annual nutrient yield, respectively. This study demonstrates the importance of large flood events to the total annual nutrient load in both small streams and large rivers.