A Method of Predicting Point and Path- Averaged Ambient Air VOC Concentrations,Using Meteorological Data

A method of predicting point and path-averaged ambient air VOC concentrations is described. This method was developed for the case of a plume generated from a single point source, and is based on the relationship between wind directional frequency and concentration. One-minute means of wind direction and wind speed were used as inputs to a Gaussian dispersion model to develop this relationship.

Both FTIR spectrometry and a whole-air sampling method were used to monitor VOC plumes during simulated field tests. One test set was also conducted using only whole-air samplers deployed in a closely-spaced network, thus providing an evaluation of the prediction technique free of any bias that might exist between the two analytical methods.

Correlations between observed point concentrations and wind directional frequencies were significant at the 0.05 level in most cases. Predicted path-integrated concentrations, based on observed point concentrations and meteorological data, were strongly correlated with observed values. Predicted point concentrations, based on observed path-integrated concentrations and meteorological data, accurately reflected the location and magnitude of the highest concentrations from each test, as well as the shape of the concentration-versus-crosswind distance curve.     

Environmental Condition Assessment of US Military Installations Using GIS Based Spatial Multi-Criteria Decision Analysis

Environment functions in various aspects including soil and water conservation, biodiversity and habitats, and landscape aesthetics. Comprehensive assessment of environmental condition is thus a great challenge. The issues include how to assess individual environmental components such as landscape aesthetics and integrate them into an indicator that can comprehensively quantify environmental condition. In this study, a geographic information systems based spatial multi-criteria decision analysis was used to integrate environmental variables and create the indicator. This approach was applied to Fort Riley Military installation in which land condition and its dynamics due to military training activities were assessed. The indicator was derived by integrating soil erosion, water quality, landscape fragmentation, landscape aesthetics, and noise based on the weights from the experts by assessing and ranking the environmental variables in terms of their importance. The results showed that landscape level indicator well quantified the overall environmental condition and its dynamics, while the indicator at level of patch that is defined as a homogeneous area that is different from its surroundings detailed the spatiotemporal variability of environmental condition. The environmental condition was mostly determined by soil erosion, then landscape fragmentation, water quality, landscape aesthetics, and noise. Overall, environmental condition at both landscape and patch levels greatly varied depending on the degree of ground and canopy disturbance and their spatial patterns due to military training activities and being related to slope. It was also determined the environment itself could be recovered quickly once military training was halt or reduced. Thus, this study provided an effective tool for the army land managers to monitor environmental dynamics and plan military training activities. Its limitation lies at that the obtained values of the indicator vary and are subjective to the experts' knowledge and experience. Thus, further advancing this approach is needed by developing a scientific method to derive the weights of environmental variables.     

A new method to quantify the impact of soil carbon management on biophysical soil properties: the example of two apple orchard systems in New Zealand

A new method to diagnose the environmental sustainability of specific orchard management practices was derived and tested. As a significant factor for soil quality, the soil carbon (C) management in the topsoil of the tree-row of an integrated and organic apple orchard was selected and compared. Soil C management was defined as land management practices that maintain or increase soil C. We analyzed the impact of the soil C management on biological (microbial biomass C, basal respiration, dehydrogenase activity, respiratory quotient) and physical (aggregate stability, amount of plant-available water, conductive mean pore diameter near water saturation) soil properties. Soil in the alley acted as a reference for the managed soil in the tree row. The total and hot-water-extractable C amounts served as a combined proxy for the soil C management. The soil C management accounted for 0 to 81% of the degradation or enhancement of biophysical soil properties in the integrated and organic system. In the integrated system, soil C management led to a loss of C in the top 0.3 m of the tree row within 12 yr, causing a decrease in microbial activities. In the tree row of the organic orchard, C loss occurred in the top 0.1 m, and the decrease in microbial activities was small or not significant. Regarding physical soil properties, the C loss in the integrated system led to a decrease of the aggregate stability, whereas it increased in the organic system. Generally, the impact of soil C management was better correlated with soil microbial than with the physical properties. With respect to environmental soil functions that are sensitive to the decrease in microbial activity or aggregate stability, soil C management was sustainable in the organic system but not in the integrated system.     

Projecting Cumulative Benefits of Multiple River Restoration Projects: An Example from the Sacramento-San Joaquin River System in California

Despite increasingly large investments, the potential ecological effects of river restoration programs are still small compared to the degree of human alterations to physical and ecological function. Thus, it is rarely possible to “restore” pre-disturbance conditions; rather restoration programs (even large, well-funded ones) will nearly always involve multiple small projects, each of which can make some modest change to selected ecosystem processes and habitats. At present, such projects are typically selected based on their attributes as individual projects (e.g., consistency with programmatic goals of the funders, scientific soundness, and acceptance by local communities), and ease of implementation. Projects are rarely prioritized (at least explicitly) based on how they will cumulatively affect ecosystem function over coming decades. Such projections require an understanding of the form of the restoration response curve, or at least that we assume some plausible relations and estimate cumulative effects based thereon. Drawing on our experience with the CALFED Bay-Delta Ecosystem Restoration Program in California, we consider potential cumulative system-wide benefits of a restoration activity extensively implemented in the region: isolating/filling abandoned floodplain gravel pits captured by rivers to reduce predation of outmigrating juvenile salmon by exotic warmwater species inhabiting the pits. We present a simple spreadsheet model to show how different assumptions about gravel pit bathymetry and predator behavior would affect the cumulative benefits of multiple pit-filling and isolation projects, and how these insights could help managers prioritize which pits to fill.     

Using diatoms as quality indicators for a newly-formed urban lake and its catchment

Periphytic diatoms were studied to evaluate the water quality of a newly created lake, formed by the enclosure of the formerly tidal Cardiff Bay (Wales, UK), and the effects of two inflowing rivers which drain densely populated and industrialised catchments. Seven sites in Cardiff Bay and two locations on the inflowing rivers were monitored for diatoms and water chemistry over 2 years. Water quality was assessed using a revised UK trophic diatom index (TDI) and new methods to determine ecological quality ratios and ecological status classes as required by the EU Water Framework Directive. Diatom assemblages reflected spatiotemporal variations in environmental conditions between the rivers and Cardiff Bay and within the bay. In the bay, diatoms reflected differences in river quality and possibly local pollution in certain areas of the lake. High values of the TDI indicated eutrophic to hypertrophic conditions in both rivers and in the bay and diatoms indicated poor ecological status.     

Decolorization and detoxification of two textile industry effluents by the laccase/1-hydroxybenzotriazole system

The aim of this work was to determine the optimal conditions for the decolorization and the detoxification of two effluents from a textile industry—effluent A (the reactive dye bath Bezactive) and effluent B (the direct dye bath Tubantin)—using a laccase mediator system. Response surface methodology (RSM) was applied to optimize textile effluents decolorization. A Box–Behnken design using RSM with the four variables pH, effluent concentration, 1-hydroxybenzotriazole (HBT) concentration, and enzyme (laccase) concentration was used to determine correlations between the effects of these variables on the decolorization of the two effluents. The optimum conditions for pH and concentrations of HBT, effluent and laccase were 5, 1 mM, 50 % and 0.6 U/ml, respectively, for maximum decolorization of effluent A (68 %). For effluent B, optima were 4, 1 mM, 75 %, and 0.6 U/ml, respectively, for maximum decolorization of approximately 88 %. Both effluents were treated at 30 °C for 20 h. A quadratic model was obtained for each decolorization through this design. The experimental and predicted values were in good agreement and both models were highly significant. In addition, the toxicity of the two effluents was determined before and after laccase treatment using Saccharomyces cerevisiae, Bacillus cereus, and germination of tomato seeds.     

Assessing and testing prediction uncertainty for single tree-based models: A case study applied to northern hardwood stands in southern Québec, Canada

Estimating prediction uncertainty for a single tree-based model is hindered by the complex structure of these models. In this paper, we addressed this issue with a case study applied to northern hardwood stands in Québec, Canada. SaMARE is a stochastic single tree-based model that was designed for these types of stands. Using a Monte Carlo approach, the model can provide a mean predicted value and its confidence limits for some plot-level attributes.The mean predicted values were compared to observed values in terms of bias and accuracy. In addition to these common statistics, we compared nominal coverage of Monte Carlo-simulated confidence intervals with real (observed) coverage to verify the adequacy of the simulated uncertainty. A comparison was made using several plot-level attributes, which exhibited an increasing discriminative complexity. This complexity ranges from coarse attributes, such as all-species basal area, up to more complex ones, such as basal area for stems of a particular species and with sawlog potential.The results showed that in terms of absolute value, biases were small, but could be relatively high with respect to the average observed value when the discriminative complexity of the attribute increased. The comparison between nominal and real coverage of confidence intervals gave satisfactory results for all-species plot-level attributes. However, for some species-specific attributes, the Monte Carlo-simulated confidence intervals overestimated the real coverage.     

A free-enzyme catalyst for the bioremediation of environmental atrazine contamination

Herbicide contamination from agriculture is a major issue worldwide, and has been identified as a threat to freshwater and marine environments in the Great Barrier Reef World Heritage Area in Australia. The triazine herbicides are of particular concern because of potential adverse effects, both on photosynthetic organisms and upon vertebrate development. To date a number of bioremediation strategies have been proposed for triazine herbicides, but are unlikely to be implemented due to their reliance upon the release of genetically modified organisms. We propose an alternative strategy using a free-enzyme bioremediant, which is unconstrained by the issues surrounding the use of live organisms. Here we report an initial field trial with an enzyme-based product, demonstrating that the technology is technically capable of remediating water bodies contaminated with the most common triazine herbicide, atrazine.