Effect of ozonization in degradation of trifluralin residues in aqueous and food matrices

Abstract

This study investigates the oxidation of trifluralin residues during ozonation in aqueous and food matrices (tomato). Domestic ozonation equipment with average production of 23.9?mg O₃ L^?1 h^?1 was used in the tests. Modern chromatographic systems (SPME-GC-IT/MS/MS and QuEChERS-GC-IT/MS/MS) were applied for extraction and detection of trifluralin residue in fortified samples of ultrapure water, tap water, superficial water and tomato fruit. The samples were submitted to the ozonation process during 0, 5, 10 and 20?min. Treatment at 5?min was able to degrade 71.5% of herbicide trifluralin in surface water. The removal (%) in ultrapure water reached 83.4% after 20?min of ozonation. The degradation of trifluralin in fortified tomato samples (0.025–0.1?mg kg^?1) were conducted with ozonation at 20?min, and it ranged from 84.4 to 92.7%. After treatment, levels of trifluralin in tomato remained within the established MRLs to EU, USEPA and ANVISA (Brazil). The data provided evidence that ozone is effective for removing trace trifluralin from water and foods.     

Spectral tests of randomness for spatial point patterns

We develop a spectral framework for testing the hypothesis of complete spatial randomness (CSR) for a spatial point pattern. Five formal tests based on the periodogram (sample spectrum) proposed in Mugglestone (1990) are considered. A simulation study is used to evaluate and compare the power of the tests against clustered, regular and inhomogeneous alternatives to CSR. A subset of the tests is shown to be uniformly more powerful than the others against the alternatives considered. The spectral tests are also compared with three widely used space-domain tests that are based on the mean nearest-neighbor distance, the reduced second-order moment function (K-function), and a bivariate Cramér-von Mises statistic. The test based on the scaled cumulative R-spectrum is more powerful than the space-domain tests for detecting clustered alternatives to CSR, especially when the number of events is small.     

Climate dynamics and extreme precipitation and flood events in Central Europe

Past changes and possible future variations in the nature of extreme precipitation and flood events in Central Europe and the Alpine region are examined from a physical standpoint. An overview is given of the following key contributory physical processes: (1) the variability of the large-scale atmospheric flow and the associated changes of the North-Atlantic storm track; (2) the feedback process between climate warming and the water cycle, and in particular the potential for more frequent heavy precipitation events; and (3) the catchment-scale hydrological processes associated with variations in major river flooding events and that are related to land-use changes, river training measures, and shifts in the proportion of rain to snowfall. In this context an account is provided of the possible future forecasting and warning methodologies based upon high-resolution weather prediction and runoff models. Also consideration is given to the detectability of past (future) changes in observed (modeled) extreme events. It is shown that their rarity and natural fluctuation largely impedes a detection of systematic variations. These effects restrict trend analysis of such events to return periods of below a few months. An illustration using daily precipitation from the Swiss Alps does yield evidence for pronounced trends of intense precipitation events (return period 30 days), while trends of stronger event classes are not detectable (but nevertheless can not be excluded). The small detection probability for extreme events limits possible mitigation of future damage costs through an abatement of climate change alone, and points to the desirability of developing improved early forecasting/warning systems as an additional no-regret strategy. This revised version was published online in July 2006 with corrections to the Cover Date.     

Spatial modelling of the probability of obtaining a detectable concentration of ammonia in Moreton Bay, Australia

Ammonia is an important water quality variable, which in excess, can be detrimental to waterways and their ecosystems. In the Ecosystem Health Monitoring Program in South-east Queensland ammonia is monitored monthly, however, often more than 50% of the ammonia observations in Moreton Bay are below detection limit, making it difficult to draw useful inferences. In this paper a clipped Gaussian random field is used to spatially model and map the probability of detectable concentration of ammonia. The methodology is applied to the Moreton Bay samples collected in February 2005. The results suggest that for this month the oceanic impacted areas have higher probability of detectable ammonia concentration than the areas closer to the main sources of anthropogenic inputs.     

SAGEBRUSH RANGELAND HYDROLOGY AND EVALUATION OF THE SPUR HYDROLOGY MODEL1

ABSTRACT: An excellent hydrologic record on sagebrush range-land has been developed at the Reynolds Creek Experimental Watershed in southwestern Idaho. The objectives of this paper were two-fold: (1) to analyze and describe the hydrologic record (8–18 years) from four sagebrush watersheds (1–83 ha); and (2) to evaluate the hydrology component of SPUR, a comprehensive rangeland model. The watersheds represent a gradient in elevation (1180–1658 m) and precipitation (240–350 mm/yr). Runoff was a small fraction (> 2 percent) of the total water budget for all of the watersheds. It occurred very infrequently at the three lower elevation watersheds: Summit, Flats, and Nancy Gulch. At Lower Sheep, the highest elevation watershed, runoff occurred most years for a period of 1 to 17 weeks in the winter. Frozen soil combined with rainfall or snowmelt was associated with most of the runoff from Flats and Nancy Gulch. At Summit summertime thunderstorms produced all of the runoff. The average annual sediment yield from all of the watersheds was low (17–950 kg/ha). It was highest from Summit, which had well developed alluvial channels and very steep slopes. SPUR was able to simulate runoff with reasonable accuracy only at Summit, where frozen soils were not a factor. There was poor correlation between predicted and actual annual 8ediment loss. The model tended to overpredict evapotranspiration early in the growing season and underpredict it in the late summer.     

BAYESIAN MODELS OF FORECASTED TIME SERIES1

Bayesian Processor of Forecasts (BPF) combines a prior distribution, which describes the natural uncertainty about the realization of a hydrologic process, with a likelihood function, which describes the uncertainty in categorical forecasts of that process, and outputs a posterior distribution of the process, conditional upon the forecasts. The posterior distribution provides a means of incorporating uncertain forecasts into optimal decision models. We present fundamentals of building BPF for time series. They include a general formulation, stochastic independence assumptions and their interpretation, computationally tractable models for forecasts of an independent process and a first-order Markov process, and parametric representations for normal-linear processes. An example is shown of an application to the annual time series of seasonal snowmelt runoff volume forecasts.     

PARAMETRIC ESTIMATION OF COVARIANCES OF REGIONALIZED VARIABLES1

ABSTRACT: The usefulness of stochastic models in describing the spatial variability of hydrogeologic quantities, such as permeability, storativity, piezometric head, seepage velocity, and solute concentrations is now widely recognized. In practice, these quantities are represented as the sum of a well-structured component, or drift, and a more erratic fluctuation component which is described statistically through its covariance function. This paper reviews some of the most recent and most promising methods for the estimation of parameters of these covariances from existing data. They are maximum likelihood, restricted maximum likelihood, minimum-variance unbiased quadratic estimation, and minimum-norm (weighted least squares) estimation. The applicability of such methods to conditional and unconditional probability problems is discussed.     

Restoration ecology of riverine wetlands: II. An example in a former channel of the Rhône River

Riverine wetlands, which provide numerous valuable functions, are disappearing in floodplains of a channelized European river. A restoration project has been proposed by scientists to restore a former braided channel of the Rhône River by the removal of fine organic sediments in order to enhance groundwater supply. A precise and intensive prerestoration monitoring program during one year (including comparison with a reference channel) has taken into account several variables and ecological performance indicators measured at various spatial and temporal scales. Three restoration techniques were then suggested, taking into account two characteristics of ecosystem functions for increasing restoration success and self-sustainability: (1) the riparian forest as well as the shores must be preserved or disturbed as little as possible; and (2) the upstream alluvial plug must be preserved to prevent direct supply of nutrientrich water from the Rhône River. Among the three restoration options proposed, it was not possible to carry out the less ecologically disturbing one as it was considered too expensive, time consuming, and difficult to realize. A precise and intensive postrestoration monitoring program, conducted over two years, demonstrated restoration success but also unpredicted problems, such as a locally thick layer of fine organic sediment. As long as a self-sustainable state is not achieved, this monitoring should be continued. Afterwards, a less precise and less intensive long-term monitoring should enable the detection of future events that may influence ecosystem changes.     

Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA

This paper presents an approach to modeling land-cover change as a function of land-use change. We argue that, in order to model the link between socio-economic change and changes in forest cover in a region that is experiencing residential and recreational development and agricultural abandonment, land-use and land-cover change need to be represented as separate processes. Forest-cover change is represented here using two transition probabilities that were calculated from Landsat imagery and that, taken together, describe a Markov transition matrix between forest and non-forest over a 10-year period. Using a three-date land-use data set, compiled and interpreted from digitized parcel boundaries, and scanned aerial photography for 136 sites (c. 2500 ha) sampled from the Upper Midwest, USA, we test functional relationships between forest-cover transition probabilities, standardized to represent changes over a decade, and land-use conditions and changes within sample sites. Regression models indicated that about 60% of the variation in the average forest-cover transition probabilities (i.e. from forest to non-forest and vice versa) can be predicted using three variables: amount of agricultural land use in a site; amount of developed land use; and the amount of area increasing in development. In further analysis, time lags were evaluated, showing that agricultural abandonment had a relatively strong time-lag effect but development did not. We demonstrate an approach to using forest-cover transition probabilities to develop spatially-constrained simulations of forest-cover change. Because the simulations are based on transition probabilities that are indexed to a particular time and place, the simulations are improved over previous applications of Markov transition models. This modeling approach can be used to predict forest-cover changes as a result of socio-economic change, by linking to models that predict land-use change on the basis of exogenous human-induced drivers.     

DESIGN OF DESALTING PLANTS FOR CONJUNCTIVE OPERATION1

ABSTRACT The selection of an evaporator design must reflect the balancing of captial cost (primarily in heat exchanger surface and vessels) against operating cost (primarily steam cost) to achieve minimum cost. In a conjunctive plant the tendency is to select a low-capital cost, high-operating cost plant. In addition, it is advantageous to use a high-capacity plant which needs to be operated much less of the time than a plant which is sized just at the needed rate. For example, in the study of a possible system to satisfy a future increase of 450 MGD in water supply to New York Qty, a plant of 750 MGD capacity was selected as optimum. This plant, of the advanced VTE-MSF process type, would have a performance ratio of 9 lb product/1000 Btu as compared to 10-13 normally used for base-loaded plants. Steam would be supplied by a multi-unit dual-purpose nuclear power plant. The most economical type of energy supply would be “interruptible”; the steam would be used by a low pressure turbine to generate electricity during periods of peak electrical demand but would be available to the desalting plant at other times. The low pressure turbine would be available as spinning reserve during desalting plant operation. It is estimated that the desalting plant would have a load factor of 27 per cent over its life.