The use of multiple tracers for tracking wastewater discharges in freshwater systems

The assessment of potential impacts of wastewater effluent discharges in freshwater systems requires an understanding of the likely degrees of dilution and potential zones of influence. In this study, four tracers commonly present in wastewater effluents were monitored to compare their relative effectiveness in determining areas in freshwater systems that are likely to be impacted by effluent discharges. The four tracers selected were the human pharmaceutical carbamazepine, anthropogenic gadolinium, fluorescent-dissolved organic matter (fDOM), and electrical conductivity (EC). The four tracers were monitored longitudinally in two distinct freshwater systems receiving wastewater effluents, where one site had a high level of effluent dilution (effluent <1 % of total flow) and the other site had a low level of effluent dilution (effluent ～50 % of total flow). At both sites, the selected tracers exhibited a similar pattern of response intensity downstream of discharge points relative to undiluted wastewater effluent, although a number of anomalies were noted between the tracers. Both EC and fDOM are non-specific to human influences, and both had a high background response, relative to the highly sensitive carbamazepine and anthropogenic gadolinium responses, although the ease of measuring EC and fDOM would make them more adaptable in highly variable systems. However, the greater sensitivity and selectivity of carbamazepine and gadolinium would make their combination with EC and fDOM as tracers of wastewater effluent discharges highly desirable to overcome potential limitations of individual tracers.     

Impacts of groundwater metal loads from bedrock fractures on water quality of a mountain stream

Acid mine drainage and metal loads from hardrock mines to surface waters is a significant problem in the western USA and many parts of the world. Mines often occur in mountain environments with fractured bedrock aquifers that serve as pathways for metals transport to streams. This study evaluates impacts from current and potential future groundwater metal (Cd, Cu, and Zn) loads from fractures underlying the Gilt Edge Mine, South Dakota, on concentrations in Strawberry Creek using existing flow and water quality data and simple mixing/dilution mass balance models. Results showed that metal loads from bedrock fractures to the creek currently contribute <1% of total loads. Even if background water quality is achieved upstream in Strawberry Creek, fracture metal loads would be <5%. Fracture loads could increase substantially and cause stream water quality standards exceedances once groundwater with elevated metals concentrations in the aquifer matrix migrates to the fractures and discharges to the stream. Potential future metal loads from an upstream fracture would contribute a small proportion of the total load relative to current loads in the stream. Cd has the highest stream concentrations relative to standards. Even if all stream water was treated to remove 90% of the Cd, the standard would still not be achieved. At a fracture farther downstream, the Cd standard can only be met if the upstream water is treated achieving a 90% reduction in Cd concentrations and the median stream flow is maintained.     

The problem of estimating recent genetic connectivity in a changing world

Accurate understanding of population connectivity is important to conservation because dispersal can play an important role in population dynamics, microevolution, and assessments of extirpation risk and population rescue. Genetic methods are increasingly used to infer population connectivity because advances in technology have made them more advantageous (e.g., cost effective) relative to ecological methods. Given the reductions in wildlife population connectivity since the Industrial Revolution and more recent drastic reductions from habitat loss, it is important to know the accuracy of and biases in genetic connectivity estimators when connectivity has declined recently. Using simulated data, we investigated the accuracy and bias of 2 common estimators of migration (movement of individuals among populations) rate. We focused on the timing of the connectivity change and the magnitude of that change on the estimates of migration by using a coalescent‐based method (Migrate‐n) and a disequilibrium‐based method (BayesAss). Contrary to expectations, when historically high connectivity had declined recently: (i) both methods over‐estimated recent migration rates; (ii) the coalescent‐based method (Migrate‐n) provided better estimates of recent migration rate than the disequilibrium‐based method (BayesAss); (iii) the coalescent‐based method did not accurately reflect long‐term genetic connectivity. Overall, our results highlight the problems with comparing coalescent and disequilibrium estimates to make inferences about the effects of recent landscape change on genetic connectivity among populations. We found that contrasting these 2 estimates to make inferences about genetic‐connectivity changes over time could lead to inaccurate conclusions.     

Adaptive Management: From More Talk to Real Action

The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.     

Aldehyde and Monocyclic Aromatic Hydrocarbon Mixing Ratios at an Urban Site in Las Vegas,Nevada

ABSTRACT

Linhong Jing completed a master's degree in chemistry at UNLV and is currently enrolled in the Ph.D. program at Purdue University. Her address is Department of Chemistry, Purdue University, West Lafayette, IN 47907. Dr. Spencer Steinberg is an associate professor of chemistry at UNLV. His address is UNLV Department of Chemistry, P.O. Box 454003, Las Vegas, NV 89154-4003. Dr. Brian Johnson is an associate professor of chemistry at UNLV. His address is UNLV Department of Chemistry, P.O. Box 454003, Las Vegas, NV 89154-4003.

Oxidation of benzene, toluene, ethylbenzene, and xylenes (BTEX) in air, of significance due to, for example, the potential for O₃ formation, is believed to be initiated by OH attack on the ring (addition) or on the alkyl side chain (H abstraction). A series of ring-breaking reactions follows, with major products predicted to be a-dicarbonyls, simple aldehydes, and organic acids. To test this prediction, ambient air mixing ratios of aldehydes (formaldehyde, ac-etaldehyde, benzaldehyde, glyoxal, and pyruvaldehyde), along with some supporting BTEX data, were measured at an urban site in Las Vegas, NV. Samples were collected on sorbents and determined by chromatographic methods; mixing ratios were compared to ambient levels of CO, O₃, and NO_x. A meteorological analysis (temperature, wind speed, and wind direction) was also included. Statistically significant relationships were noted among the BTEX hydrocarbons (HCs) and among the photochemi-cally derived species (e.g., O₃, NO₂, and some of the aldehydes), although there was seasonal variation. The observations are consistent with a common primary source (i.e., vehicular exhaust or fuel evaporation) for the BTEX compounds and a common secondary source (e.g., OH attack) for glyoxal and pyruvaldehyde.     

The drivers of risk to water security in Shanghai

Big cities are often said to have big water problems, and Shanghai is no exception. In this paper, we examine and compare the influence of the major factors that give rise to the risk of water insecurity in Shanghai. There is an extensive and diverse literature on these issues, dealt with in isolation, and here, we provide a synthesis of the literature, together with our own assessments and calculations, to assess what are the risks to Shanghai’s water supply and what is our degree of confidence in this assessment. We describe the systems that supply water to the city, and past and future changes in the systems, including changes in the glaciers that supply some water to the river, changes in climate, changes in land use, the construction of dams, and water diversions. We show how, at the same time as Shanghai is increasing its dependence on the Yangtze river, water diversions and sea level rise are increasing the risk that this water will be too saline to consume at certain times of the year. This analysis suggests that most of the major drivers of the risk to water security in Shanghai are within the power of environmental managers to control.     

A performance evaluation of the National Air Quality Forecast Capability for the summer of 2007

This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC) that supported, in part, its transition into operational status. This evaluation focuses primarily on discrete forecasts for the maximum 8-h O₃ concentrations covering the 4-month period, June through September, 2007, using measurements obtained from EPA's AIRNow network. Results indicate that the 2007 NAQFC performed as well or better than previous configurations, despite the expansion of the forecast domain into the western half of the nation that is dominated by complex terrain. The mean, domain-wide, season-long correlation was 0.70. When examined over time, the domain-wide correlations exhibit a fairly consistent nature, with values exceeding 0.60 (0.70) over 90% (55%) of the days. The NAQFC systematically over-predicted the 8-h O₃ concentrations, continuing a trend established by earlier NAQFC configurations, though to a lesser degree. The summer-long mean forecast value of 53.2 ppb was 4.2 ppb higher than the observed value, resulting in a domain-wide Normalized Mean Bias (NMB) of 8.7%. Most of the over-prediction is associated with observed concentrations less than 50 ppb. In fact the model tends to under-predict when concentrations exceed 70 ppb. As with the bias, the error associated with the latest configuration was also lower. The summer-long Root Mean Square Error of 13.0 ppb (Normalized Mean Error (NME) = 20.4%) represented marked improvements over earlier forecasts. Examination of the spatial distribution of both the NMB and NME reveals that the NAQFC was generally within 25% for the NME and 25% for the NMB over a majority of the domain. Several areas of poorer performance, where the NMB and NME often exceed 25% and in some cases 50%, were noted. These areas include southern California, where the NAQFC tended to under-predict concentrations (especially on weekends) and the southeast Atlantic and Gulf coasts regions, where the model over-predicted. Subsequent analysis revealed that the incorrect temporal allocation of precursor emissions was likely the source of the under-prediction in southern California, while inaccurate simulation of PBL heights likely contributed to the over-prediction in the coastal regions.     

Implications of simultaneity in a physical damage function

A modeler must often rely on highly simplified representations of complex physical systems when analyzing associated economic issues. Herein, we consider a management problem in which a bioeconomic system exhibits simultaneity in processes governing productivity and damage. In this case, it may benefit the producer to sacrifice productivity to reduce the costs associated with increased damage. We specify empirically a structural damage relationship that explains the biological process by which an invasive species damages a host and estimate the structural model and its reduced form with an exceptional dataset on infestation of olives by the olive fruit fly. We contrast the results of these models with the approach typically taken in the economic literature, which expresses damage as a function of pest density. The population-based approach introduces significantly greater bias into the individual grower's choice of damage-control inputs than estimates based on the structural model.