Ozone and Other Air Quality-Related Variables Affecting Visibility in the Southeast United States

Abstract

An analysis of ozone (O₃) concentrations and several other air quality-related variables was performed to elucidate their relationship with visibility at five urban and semi-urban locations in the southeast United States during the summer seasons of 1980-1996. The role and impact of O₃ on aerosols was investigated to ascertain a relationship with visibility. Regional trend analysis over the 1980s reveals an increase in maximum O₃ concentration coupled with a decrease in visibility. However, a similar analysis for the 1990s shows a leveling-off of both O₃ and visibility; in both cases, the results were not statistically significant at the 5% level. A case study of site-specific trends at Nashville, TN, followed similar trends. To better understand the relationships between O₃ concentration and visibility, the analysis was varied from yearly through daily to hourly averaged values. This increased temporal resolution showed a statistically significant inverse relationship between visibility and O₃. Site-specific hourly r² values ranged from 0.02 to 0.43. Additionally, by performing back-trajectory analysis, it was found that the visibility degraded by air mass migration over polluted areas.     

Pollutants and the health of green sea turtles resident to an urbanized estuary in San Diego, CA

Rapid expansion of coastal anthropogenic development means that critical foraging and developmental habitats often occur near highly polluted and urbanized environments. Although coastal contamination is widespread, the impact this has on long-lived vertebrates like the green turtle (Chelonia mydas) is unclear because traditional experimental methods cannot be applied. We coupled minimally invasive sampling techniques with health assessments to quantify contaminant patterns in a population of green turtles resident to San Diego Bay, CA, a highly urbanized and contaminated estuary. Several chemicals were correlated with turtle size, suggesting possible differences in physiological processes or habitat utilization between life stages. With the exception of mercury, higher concentrations of carapace metals as well as 4,4′-dichlorodiphenyldichloroethylene (DDE) and γ chlordane in blood plasma relative to other sea turtle studies raises important questions about the chemical risks to turtles resident to San Diego Bay. Mercury concentrations exceeded immune function no-effects thresholds and increased carapace metal loads were correlated with higher levels of multiple health markers. These results indicate immunological and physiological effects studies are needed in this population. Our results give insight into the potential conservation risk contaminants pose to sea turtles inhabiting this contaminated coastal habitat, and highlight the need to better manage and mitigate contaminant exposure in San Diego Bay.     

Implications of Conceptual Channel Representation on SWAT Streamflow and Sediment Modeling

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool (SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case‐dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

How to Constrain Multi‐Objective Calibrations of the SWAT Model Using Water Balance Components

Accurate discharge simulation is one of the most common objectives of hydrological modeling studies. However, a good simulation of discharge is not necessarily the result of a realistic simulation of hydrological processes within the catchment. We propose an evaluation framework that considers both discharge and water balance components as evaluation criteria for calibration of the Soil and Water Assessment Tool (SWAT). In this study, we integrated average annual values of surface runoff, groundwater flow, and evapotranspiration in the model evaluation procedure to constrain the selection of good model runs for the Little River Experimental Watershed in Georgia, United States. For evaluating water balance and discharge dynamics, the Nash‐Sutcliffe efficiency (NSE) and percent bias (PBIAS) were used. In addition, the ratio of root mean square error and standard deviation of measured data (RSR) was calculated for individual segments of the flow duration curve to identify the best model runs in terms of discharge magnitude. Our results indicate that good statistics for discharge do not guarantee realistic simulations of individual water balance components. Therefore, we recommend constraining the ranges of water balance components to achieve a more realistic simulation of the entire hydrological system, even if tradeoffs between good statistics for discharge simulations and reasonable amounts of the water balance components are unavoidable. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Demonstrating Contaminant Degradation at an MGP Site With Metabolic Gas Flux and Radio Carbon Dating

Obtaining lines of evidence indicating that contamination in sediment environments is degrading and being transformed to less toxic forms is an important component of building support for a monitored natural recovery remedy for contaminated sediments. This project was a field demonstration of manufactured gas plant contaminant degradation in river sediments using metabolic gas flux and was performed in an urban area section of a river in northeastern Indiana. CO₂ sorbent traps were deployed to measure CO₂ flux from the river sediments. Sediment samples were collected and analyzed for polycyclic aromatic hydrocarbon (PAH) concentrations and for microbial community composition using molecular techniques. The results showed that the deployment was successful, measuring CO₂ flux at all sediment locations and demonstrating that microbial contaminant degrading activity was occurring in the sediments. Radio carbon dating showed a significant portion of the CO₂ being generated (approximately 19–27 percent) was the result of fossil fuel degradation. Molecular results showed that the microbial community consisted of phylotypes known to be associated with monocyclic aromatic and PAH degradation. ©2017 Wiley Periodicals, Inc.     

Measurement of gas-phase total peroxides at the summit of Mount Tai in China

Measurement of ambient gas-phase total peroxides was performed at the summit of Mount Tai (Mt. Tai, 1534 m above sea level) in central-eastern China during March 22–April 24 and June 16–July 20, 2007. The hourly averaged concentration of peroxides was 0.17 ppbv (± 0.16 ppbv, maximum: 1.28 ppbv) and 0.55 ppbv (± 0.67 ppbv, maximum: 3.55 ppbv) in the spring and summer campaigns, respectively. The average concentration of peroxides at Mt. Tai, which is in a heavily polluted region, was much lower than hydrogen peroxide measurements made at some rural mountain sites, suggesting that significant removal processes took place in this region. An examination of diurnal variation and a correlation analysis suggest that these removal processes could include chemical suppression of peroxide production due to the scavenging of peroxy and hydroxy radicals by high NO_x, wet removal by clouds/fogs rich in dissolved sulfur dioxide which reacts quickly with peroxides, and photolysis. These sinks competed with photochemical sources of peroxides, resulting in different mean concentrations and diurnal pattern of peroxides in the spring and summer. A principal component analysis was conducted to quantify the major processes that influenced the variation of peroxide concentrations. This analysis shows that in the spring photochemical production was an important source of peroxides, and the major sink was scavenging during upslope transport of polluted and humid air from the lower part of the planetary boundary layer (PBL) and wet removal by synoptic scale clouds. During the summer, highly polluted PBL air (with high NO_x) was often associated with very low peroxides due to the chemical suppression of HO₂ by high NO_x and wet-removal by clouds/fogs in this sulfur-rich atmosphere, especially during the daytime. Higher concentrations of peroxides, which often appeared at mid-nighttime, were mainly associated with subsidence of air masses containing relatively lower concentrations of NO_y.     

Optimal temporal scale for the correlation of AOD and ground measurements of PM2.5 in a real-time air quality estimation system

Aerosol optical depth (AOD), an indirect estimate of particulate matter using satellite observations, has shown great promise in improving estimates of PM_2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 μm) surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM_2.5 in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) an approach that integrates satellite measurements with ground measurements in the estimates of pollutants and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect, identifying the optimal temporal scale to correlate AOD with PM_2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale: within the last 30 days, displays the best model performance in a southern multi-state area centered in Mississippi using 2004 and 2005 data sets.     

Vegetation and outdoor recess time at elementary schools: What are the connections?

Empirical and anecdotal evidence suggests that landscapes with more vegetation have a positive impact on children's focus, attention, and cognitive development. In school, children are able to regain focus, suppress impulses, and pay attention in class longer after exposure to natural settings. Because children spend much of their time in school, the amount and types of vegetation on school grounds may influence their development. Public elementary schools in the Commonwealth of Virginia (N = 988) were surveyed to examine correlations between school ground vegetation and outside recess. The number of trees on school grounds, the size of the school grounds, and the presence of sports fields were modestly correlated with greater outside recess time. These correlations support common sense because sports fields facilitate supervised play and larger school grounds provide space for sports fields and playgrounds and additional opportunities for free play. More trees on school grounds provide a welcoming environment for students and teachers, and encourage outside play. These results may help school personnel design and maintain school grounds that increase outdoor recess time.     

Balancing environmental and industry sustainability: A case study of the US gold mining industry

Mandatory insurance requirements and/or mitigation fees (royalties) for mining companies may help reduce environmental risk exposure for the federal government. Mining is examined since the Environmental Protection Agency (EPA) Toxic Release Inventory reveals that this sector produces more hazardous waste than any other industrial sector. Although uncommon, environmental expense can exceed hundreds of millions of dollars per development. Of particular concern is the potential for mines to become unfunded Superfund sites. Monte Carlo simulation of risk exposure is used to establish a plausible range of unfunded federal liabilities associated with cyanide-leach gold mining. A model is developed to assess these costs and their impact on both the federal budget and corporate profitability (i.e., industry sustainability), particularly if such costs are borne by offending firms.