Sorption of the veterinary antimicrobials sulfadimethoxine and ormetoprim in soil

Currently, limited research on the fate of antimicrobials in the environment exists, once they are discharged in human and animal wastes. Sorption of two antimicrobials, sulfadimethoxine (SDM) and ormetoprim (OMP), was investigated in two soils and sand using a series of batch experiments. Because OMP and SDM are often administered in combination, their sorption was also investigated in combination as co-solutes. The rate of SDM and OMP sorption was rapid over the first few hours of the experiments, which then slowed considerably after 16 to 68 h. OMP sorption was enhanced at high concentrations when in combination with SDM, with linear sorption coefficients ranging from 1.3 to 58.3 L.kg(-1) in the single solute experiments and 4.96 to 89.7 L.kg(-1) in the co-solute experiments. Sorption of OMP as a single solute seems to provide a better fit with the Freundlich equation, which became more linear (n approached 1) when SDM was present. Overall, SDM sorbed less than OMP in the two soils and sand. SDM linear sorption coefficients ranged from 0.4 to 25.8 L.kg(-1) as a single solute and 2.5 to 22.1 L.kg(-1) as a co-solute. Sorption of SDM becomes more nonlinear (n < 1) when SDM is present in combination with OMP. Overall, sorption of both antimicrobials increased in the selected soils and sand as the organic matter, clay content, and cation exchange capacity increased. These experiments indicate relatively low sorption of SDM and OMP in natural soils, making them a potential threat to surface and ground water.     

Watershed vulnerability predictions for the Ozarks using landscape models

Forty-six broad-scale landscape metrics derived from commonly used landscape metrics were used to develop potential indicators of total phosphorus (TP) concentration, total ammonia (TA) concentration, and Escherichia coli bacteria count among 244 sub-watersheds of the Upper White River (Ozark Mountains, USA). Indicator models were developed by correlating field-based water quality measurements and contemporaneous remote-sensing-based ecological metrics using partial least squares (PLS) analyses. The TP PLS model resulted in one significant factor explaining 91% of the variability in surface water TP concentrations. Among the 18 contributing landscape model variables for the TP PLS model, the proportions of a sub-watershed that are barren and in human use were key indicators of water chemistry in the associated sub-watersheds. The increased presence and reduced fragmentation of forested areas are negatively correlated with TP concentrations in associated sub-watersheds, particularly within close proximity to rivers and streams. The TA PLS model resulted in one significant factor explaining 93% of the variability in surface water TA concentrations. The eight contributing landscape model variables for the TA PLS model were among the same forest and urban metrics for the TP model, with a similar spatial gradient trend in relationship to distance from streams and rivers within a sub-watershed. The E. coli PLS model resulted in two significant factors explaining 99.7% of the variability in E. coli cell count. The 17 contributing landscape model variables for the E. coli PLS model were similar to the TP and TA models. The integration of model results demonstrates that forest, riparian, and urban attributes of sub-watersheds affect all three models. The results provide watershed managers in the Ozark Mountains with a broad-scale vulnerability prediction tool, focusing on TP, TA, and E. coli, and are being used to prioritize and evaluate monitoring and restoration efforts in the vicinity of the White River, a major tributary to the Mississippi River and Gulf of Mexico.     

Analyzing the Impacts of Dams on Riparian Ecosystems: A Review of Research Strategies and Their Relevance to the Snake River Through Hells Canyon

River damming provides a dominant human impact on river environments worldwide, and while local impacts of reservoir flooding are immediate, subsequent ecological impacts downstream can be extensive. In this article, we assess seven research strategies for analyzing the impacts of dams and river flow regulation on riparian ecosystems. These include spatial comparisons of (1) upstream versus downstream reaches, (2) progressive downstream patterns, or (3) the dammed river versus an adjacent free-flowing or differently regulated river(s). Temporal comparisons consider (4) pre- versus post-dam, or (5) sequential post-dam conditions. However, spatial comparisons are complicated by the fact that dams are not randomly located, and temporal comparisons are commonly limited by sparse historic information. As a result, comparative approaches are often correlative and vulnerable to confounding factors. To complement these analyses, (6) flow or sediment modifications can be implemented to test causal associations. Finally, (7) process-based modeling represents a predictive approach incorporating hydrogeomorphic processes and their biological consequences. In a case study of Hells Canyon, the upstream versus downstream comparison is confounded by a dramatic geomorphic transition. Comparison of the multiple reaches below the dams should be useful, and the comparison of Snake River with the adjacent free-flowing Salmon River may provide the strongest spatial comparison. A pre- versus post-dam comparison would provide the most direct study approach, but pre-dam information is limited to historic reports and archival photographs. We conclude that multiple study approaches are essential to provide confident interpretations of ecological impacts downstream from dams, and propose a comprehensive study for Hells Canyon that integrates multiple research strategies.     

Volunteer Macroinvertebrate Monitoring: Tensions Among Group Goals,Data Quality,and Outcomes

Volunteer monitoring of natural resources is promoted for its ability to increase public awareness, to provide valuable knowledge, and to encourage policy change that promotes ecosystem health. We used the case of volunteer macroinvertebrate monitoring (VMM) in streams to investigate whether the quality of data collected is correlated with data use and organizers' perception of whether they have achieved these outcomes. We examined the relation between site and group characteristics, data quality, data use, and perceived outcomes (education, social capital, and policy change). We found that group size and the degree to which citizen groups perform tasks on their own (rather than aided by professionals) positively correlated with the quality of data collected. Group size and number of years monitoring positively influenced whether a group used their data. While one might expect that groups committed to collecting good-quality data would be more likely to use it, there was no relation between data quality and data use, and no relation between data quality and perceived outcomes. More data use was, however, correlated with a group's feeling of connection to a network of engaged citizens and professionals. While VMM may hold promise for bringing citizens and scientists together to work on joint conservation agendas, our data illustrate that data quality does not correlate with a volunteer group's desire to use their data to promote regulatory change. Therefore, we encourage scientists and citizens alike to recognize this potential disconnect and strive to be explicit about the role of data in conservation efforts.     

The Influence of Proximity to a National Forest on Emotions and Fire-Management Decisions

Because American national forests are managed for all citizens, it is important that researchers explore the differences and similarities between citizens living both near and far from publicly managed land. We surveyed residents living at various distances from nationally managed land to collect resident perceptions of different forest fire-management techniques, to determine public preferences for these techniques, and to examine the motivations behind these preferences. Participants both close to and far away from national forests tended to favor a multipronged approach to fire management by preferring the use of a combination of two or more fire-management techniques. There were no significant differences by proximity in participants’ self-rated emotions, types of fire-management techniques preferred, or the reasons and rationales for their preferred fire-management technique(s), indicating that the proximity variable may not be as significant as previously thought.     

Growth performance of planted mangroves in the Philippines: revisiting forest management strategies

The effort toward restoring lost mangroves in the Philippines has been commendably immense, specifically during the past two decades. In light of such, it is important to evaluate outcomes and, where appropriate, apply the lessons learned to the current strategies in mangrove forest management. This article synthesizes the results from several research projects assessing the performance of planted mangroves across the country. Overall, there is a widespread tendency to plant mangroves in areas that are not the natural habitat of mangroves, converting mudflats, sandflats, and seagrass meadows into often monospecific Rhizophora mangrove forests. In these nonmangrove areas, the Rhizophora seedlings experienced high mortality. Of the few that survived (often through persistent and redundant replanting), the young Rhizophora individuals planted in these nonmangrove and often low intertidal zones had dismally stunted growth relative to the corresponding growth performance of individuals thriving at the high intertidal position and natural mangrove sites. From this evidence, this article argues that a more rational focus of the restoration effort should be the replanting of mangroves in the brackish-water aquaculture pond environments, the original habitat of mangroves. For such, a number of management options can be explored, the implementation of which will ultimately depend on the political will of local and national governments.     

Single-source impact analysis using three-dimensional air quality models

Isolating the effects of an individual emissions source on secondary air pollutants such as ozone and some components of particulate matter must incorporate complex nonlinear processes, be sensitive to small emissions perturbations, and account for impacts that may occur hundreds of kilometers away. The ability to evaluate these impacts is becoming increasingly important for efficient air quality management. Here, as part of a recent compliance enforcement action for a violation of the Clean Air Act and as an evaluation of ozone response to single-source emissions plumes, two three-dimensional regional photochemical air quality models are used to assess the impact on ozone from approximately 2000 to 3000 excess t/month of nitrogen oxides emitted from a single power plant in Ohio. Periods in May, July, and August are evaluated. Two sensitivity methods are applied: the "brute-force" (B-F) method and the decoupled direct method (DDM). Using DDM, maximum 1-hr averaged ozone concentrations are found to increase by up to 1.8, 1.3, and 2.2 ppbv during May, July, and August episodes, respectively, and concentration increases greater than 0.5 ppbv occur in Ohio, Pennsylvania, Maryland, New York, West Virginia, Virginia, and North and South Carolina. B-F results for the August episode show a maximum 1-hr averaged ozone concentration increase of 2.3 ppbv. Significant localized decreases are also simulated, with a maximum of 3.6 ppbv in Ohio during the August episode and decreases of 0.50 ppbv and greater in Ohio, Pennsylvania, Maryland, West Virginia, and Virginia. Maximum increases are compared with maximum decreases for the August period using second-order DDM and are found, in aggregate, to be greater in magnitude by 42%. When evaluated during hours when ozone concentrations exceed 0.060 ppm, the maximum increases in ozone are higher than decreases by 82%. The spatial extent of ozone increase in both cases is about triple that of reduction.     

Implementation of a windblown dust parameterization into MODELS-3/CMAQ: Application to episodic PM events in the US/Mexico border

Windblown dust is known to impede visibility, deteriorate air quality and modify the radiation budget. Arid and semiarid areas with unpaved and unvegetated land cover are particularly prone to windblown dust, which is often attributed to high particulate matter (PM) pollution in such areas. Yet, windblown dust is poorly represented in existing regulatory air quality models. In a study by the authors on modeling episodic high PM events along the US/Mexico border using the state-of-the-art CMAQ/MM5/SMOKE air quality modeling system [Choi, Y.-J., Hyde, P., Fernando, H.J.S., 2006. Modeling of episodic particulate matter events using a 3D air quality model with fine grid: applications to a pair of cities in the US/Mexico border. Atmospheric Environment 40, 5181–5201], some of the observed PM₁₀ NAAQS exceedances were inferred as due to windblown dust, but the modeling system was incapable of dealing with time-dependent episodic dust entrainment during high wind periods. In this paper, a time-dependent entrainment parameterization for windblown dust is implemented in the CMAQ/MM5/SMOKE modeling system with the hope of improving PM predictions. An approach for realizing windblown dust emission flux for each grid cell over the study domain on an hourly basis, which accounts for the influence of factors such as soil moisture content, atmospheric stability and wind speed, is presented in detail. Comparison of model predictions with observational data taken at a pair of US/Mexico border towns shows a clear improvement of model performance upon implementation of the dust emission flux parameterization.     

Characterizing effects of uncertainties in MSW composting process through a coupled fuzzy vertex and factorial-analysis approach

A coupled fuzzy vertex and factorial-analysis approach was developed in this study for systematically characterizing effects of uncertainties in a municipal solid waste composting process. A comprehensive composting process model was also embedded into the system framework and used to address substrate decomposition and biomass growth, as well as the interactions between moisture contents, temperatures, and oxygen concentrations. The applicability of the proposed method was verified through a custom-made pilot-scale composting system. Results from fuzzy simulation indicated that the fuzzy vertex method could effectively communicate implicit knowledge into dynamic simulations and thus provide valuable information for enhancing composting process control under uncertainty. The factorial analysis was effective in quantifying the proportion to which the uncertainty of each single or interactive effect of model parameters contributes to the overall uncertainty of the system outcomes. Thus, sensitive parameters that may lead to errors or unreasonable predictions can be determined. The proposed study system could not only be used in characterizing combined effects of uncertainties for composting processes, but was also applicable to many other environmental modelling systems.     

Characterization of food waste generators: a Hawaii case study

Information on food waste disposal and on recycling methods and recycled amounts is reported. Data were obtained from a mail and phone survey of all licensed food establishments in Hawaii conducted in 2004 and 2005. Of 8253 licensed food establishments, 5033 completed surveys. It was found that relationships exist between food establishment size (measured by the number of meals served per day or the number of employees) and the amount of food an establishment recycled; establishment type and recycling behavior; and establishment type and amount recycled. The amount of food waste recycled in the state of Hawaii was estimated to be 264,000 L/day and annual food waste generation was estimated to be 336,000 tonnes.