Forest understory plant communities in the eastern United States are often diverse and are potentially sensitive to changes in climate and atmospheric inputs of nitrogen caused by air pollution. In recent years, empirical and processed-based mathematical models have been developed to investigate such changes in plant communities. In the study reported here, a robust set of understory vegetation response functions (expressed as version 2 of the Probability of Occurrence of Plant Species model for the United States [US-PROPS v2]) was developed based on observations of forest understory and grassland plant species presence/absence and associated abiotic characteristics derived from spatial datasets. Improvements to the US-PROPS model, relative to version 1, were mostly focused on inclusion of additional input data, development of custom species-level input datasets, and implementation of methods to address uncertainty. We investigated the application of US-PROPS v2 to evaluate the potential impacts of atmospheric nitrogen (N) and sulfur (S) deposition, and climate change on forest ecosystems at three forested sites located in New Hampshire, Virginia, and Tennessee in the eastern United States. Species-level N and S critical loads (CLs) were determined under ambient deposition at all three modeled sites. The lowest species-level CLs of N deposition at each site were between 2 and 11 kg N/ha/yr. Similarly, the lowest CLs of S deposition, based on the predicted soil pH response, were less than 2 kg S/ha/yr among the three sites. Critical load exceedance was found at all three model sites. The New Hampshire site included the largest percentage of species in exceedance. Simulated warming air temperature typically resulted in lower maximum occurrence probability, which contributed to lower CLs of N and S deposition. The US-PROPS v2 model, together with the PROPS-CLF model to derive CL functions, can be used to develop site-specific CLs for understory plants within broad regions of the United States. This study demonstrates that species-level CLs of N and S deposition are spatially variable according to the climate, light availability, and soil characteristics at a given location. Although the species niche models generally performed well in predicting occurrence probability, there remains uncertainty with respect to the accuracy of reported CLs. As such, the specific CLs reported here should be considered as preliminary estimates.

Respiratory diseases, exacerbated through point source pollution, are currently among the leading causes of hospitalization of children in the United States. This paper investigates the relationship between the proximity of hazardous air pollutants (HAPs) emitted from Toxic Release Inventory (TRI) facilities and the number of children diagnosed in hospitals with a respiratory disease in Tennessee. The importance of controlling for toxicity of those HAPs is of particular interest. Hospital discharge, socioeconomic, TRI emission, and HAP toxicity data are used to estimate, via Generalized Linear Methods, a logistic regression model describing the relationship between the percent of children living in a zip code area treated for respiratory illness and the average annual emissions over the previous 10 years of HAPs from TRI sites in that area. Controlling for area socioeconomic characteristics, we find that accounting for toxicity is important in uncovering the relationship between HAP emissions and respiratory health of children. A one standard deviation increase in toxicity-weighted emissions per 100 square miles is associated with an increase in the number of children diagnosed with asthma (chronic bronchitis) by about 1205 (260). The evidence suggests that, with a goal to improving children’s respiratory health, monitoring the toxicity of chemicals being emitted is at least as important as simply monitoring total emission levels. This suggests that the EPA should consider making efforts toward establishing toxicity adjusted emission guidelines.

Ecological effects of atmospheric nitrogen (N) and sulfur (S) deposition on two hardwood forest sites in the eastern United States were simulated in the context of a changing climate using the dynamic coupled biogeochemical/ecological model chain ForSAFE-Veg. The sites are a mixed oak forest in Shenandoah National Park, Virginia (Piney River) and a mixed oak-sugar maple forest in Great Smoky Mountains National Park, Tennessee (Cosby Creek). The sites have received relatively high levels of both S and N deposition and the climate has warmed over the past half century or longer. The model was used to evaluate the composition of the understory plant communities, the alignment between plant species niche preferences and ambient conditions, and estimate changes in relative species abundances as reflected by plant cover under various scenarios of future atmospheric N and S deposition and climate change. The main driver of ecological effects was soil solution N concentration. Results of this research suggested that future climate change might compromise the capacity for the forests to sustain habitat suitability. However, vegetation results should be considered preliminary until further model validation can be performed. With expected future climate change, preliminary estimates suggest that sustained future N deposition above 7.4 and 5.0 kg N/ha/yr is expected to decrease contemporary habitat suitability for indicator plant species located at Piney River and Cosby Creek, respectively.

An estimated 229 000 m3 of coal fly ash remains in the river system after dredging to clean-up the 2008 Tennessee Valley Authority (TVA) spill in Kingston, Tennessee. The ash is heterogeneous with clear, orange and black spheres and non-spherical amorphous particles. Combustion produces iron oxides that allow low field magnetic susceptibility (χLF) and percent frequency dependent susceptibility (χFD%) to be used to discriminate between coal fly ash and sediments native to the watershed. Riverbed samples with χLF greater than 3.0 × 10−6 m3/kg, have greater than 15% ash measured by optical point counting. χLF is positively correlated with total ash, allowing ash detection in riverbed sediments and at depth in cores. The ratio of ash sphere composition is altered by river transport introducing variability in χLF. Measurement of χLF is inexpensive, non-destructive, and a reliable analytical tool for monitoring the fate of coal ash in this fluvial environment.

The Oak Ridge Reservation, established in 1942, was the designated site for the construction of the atomic bomb. During a 20-year period from 1944 to 1963 radioactive and toxic chemical pollutants, especially mercury compounds were released into the surrounding waterways. Tree diversity and mycorrhizal presence and abundance were analyzed in the mercury-contaminated floodplains of East Fork Poplar Creek Oak Ridge (EFPC) (Tennessee). A subsequent greenhouse study was conducted to assess the phytotoxic effects of different mercuric solutions on Platanus occidentalis (American Sycamore), inoculated with soils from EFPC. Total soil mercury in the field had no effect on tree diversity. Organic species of mercury proved to be more toxic than inorganic species of mercury and soil inoculants from EFPC had no protective effects against Hg toxicity in our greenhouse study. Comparison of the effects of mercury contamination in our field and greenhouse studies was difficult due to uncontrolled factors.

A biological source treatment (BST) technique using remote sensing and biogeochemistry has been developed to address acid mine drainage (AMD) at its source. The BST technique utilizes down-hole injections of microbial inoculum and substrate amendments to establish a biofilm on the surface of metal sulfides (AMD source material). The treatment results in an elevated groundwater pH (from acidic to circum-neutral levels) and prevents further oxidation of AMD source material. The first 2 years of an ongoing field study of the BST technique at a reclaimed coal mine in central Tennessee (USA) has produced successful results. For instance, the water chemistry in a monitoring well down-gradient from injection wells has improved substantially as follows: the pH increased 1.3 units from 5.7 to 7.3, the dissolved (0.45 μm-filtered) iron concentration decreased by 84% from 93 to 15 mg/l, the conductivity decreased by 379 μS/cm, and sulfate decreased by 78 mg/l. Electromagnetic induction surveys were conducted to identify AMD source material and monitor BST performance by measuring changes in subsurface resistivity throughout the site. These surveys revealed a treatment zone created between injection wells where the resistance of contaminated groundwater from up-gradient AMD sources increased as it flowed past injection wells, thus, suggesting this technique could be used to treat AMD sources directly or to intercept and neutralize sub-surface AMD.

Bacteria belonging to the Order Bacteroidales predominate the intestines of warm-blooded animals, and monitoring of these bacteria can indicate fecal pollution impacts to a waterbody. Differences in seasonal concentrations and loadings for Bacteroidales and their relationship with physicochemical water parameters were investigated in temperate, inland streams. Seasonal samples (n = 321) were collected during baseflow in three central Tennessee, USA, watersheds. To estimate total fecal bacteria in receiving streams, general Bacteroidales 16S rRNA gene targets were analyzed by quantitative PCR and reported as concentration and loadings for individual and combined watersheds. In most cases, Bacteroidales marker concentrations were highest during spring/summer and loading values were highest in the spring. Bacteroidales concentrations were positively correlated with temperature and total suspended solids and negatively with dissolved oxygen, while no consistent correlations were found between loadings and abiotic factors. Temperature, total suspended solids, and dissolved oxygen are likely drivers influencing seasonal patterns for Bacteroidales concentrations. Researchers and water quality stakeholders should carefully consider measurement type (concentration versus loading), season, and water quality parameters as elements that could impact results when developing fecal monitoring projects.