Temporal and spatial patterns of micropollutants in urban receiving waters

Based on a monitoring program over the course of a year, we characterize the temporal and spatial distribution of selected micropollutants in an urban watershed within the city of Leipzig, Germany. Micropollutants revealed a ubiquitous presence in untreated and treated wastewater, surface water and groundwater. The loads of 4-nonylphenol in the effluents of the municipal wastewater treatment plant followed a seasonal trend, whereas the loads of all other micropollutants were highly variable and not correlated to seasons. In the surface water, load seasonality of caffeine, galaxolide and tonalide resulted from a rapid removal with increased water temperature. The loads of 4-nonylphenol and of caffeine in the colder months increased when rainfall occurred. In the groundwater, complex spatial and temporal patterns were apparent and were related to varying input, retardation and removal processes. As a consequence, an assessment of micropollutants in urban waters should consider different micropollutants' temporal and spatial variability.     

Isolation and characterization of mesotrione-degrading Bacillus sp. from soil

Dissipation kinetics of mesotrione, a new triketone herbicide, sprayed on soil from Limagne (Puy-de-Dôme, France) showed that the soil microflora were able to biotransform it.Bacteria from this soil were cultured in mineral salt solution supplemented with mesotrione as sole source of carbon for the isolation of mesotrione-degrading bacteria. The bacterial community structure of the enrichment cultures was analyzed by temporal temperature gradient gel electrophoresis (TTGE). The TTGE fingerprints revealed that mesotrione had an impact on bacterial community structure only at its highest concentrations and showed mesotrione-sensitive and mesotrione-adapted strains. Two adapted strains, identified as Bacillus sp. and Arthrobacter sp., were isolated by colony hybridization methods.Biodegradation assays showed that only the Bacillus sp. strain was able to completely and rapidly biotransform mesotrione. Among several metabolites formed, 2-amino-4-methylsulfonylbenzoic acid (AMBA) accumulated in the medium. Although sulcotrione has a chemical structure closely resembling that of mesotrione, the isolates were unable to degrade it.     

Detection of DDT and its metabolites in two estuaries of South China using a SPME-based device: First report of p,p′-DDMU in water column

A solid-phase microextration-based sampling method was employed to determine the concentrations of 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane (DDT) and its metabolites, 1,1-dichloro-2,2-bis(p-chlorophenyl)ethane (DDD), 1,1-dichloro-2,2-bis(p-chlorophenyl)ethene (DDE) and 1-chloro-2,2-bis(p-chlorophenyl)ethene (DDMU), in two estuarine bays, Daya Bay and Hailing Bay, of South China. Six DDT components including p,p′-DDT, o,p′-DDD, p,p′-DDD, o,p′-DDE, p,p′-DDE, and p,p′-DDMU were detected in Hailing Bay, while only p,p′-DDD was found in Daya Bay. p,p′-DDD was the most abundant DDT component in both bays, sharply different from the previous finding in the water column of the Palos Verdes Shelf, California, USA that p,p′-DDE was prevalent. In addition, the occurrence of p,p′-DDMU (with a range of 0.047-0.21 ng/L in Hailing Bay) has not been reported around the globe, and its presence in our study region appeared to stem from dehydrochlorination of p,p′-DDD, favored under aerobic conditions, but further investigations are clearly needed to confirm the mechanism for generation of DDMU in estuarine environments.     

Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations

The new method for the forecasting hourly concentrations of air pollutants is presented in the paper. The method was developed for a site in urban residential area in city of Zagreb, Croatia, for four air pollutants (NO₂, O₃, CO and PM₁₀). Meteorological variables and concentrations of the respective pollutant were taken as predictors. A novel approach, based on families of univariate regression models, was employed in selecting the averaging intervals for input variables. For each variable and each averaging period between 1 and 97 h, a separate model was built. By inspecting values of the coefficient of correlation between measured and modelled concentrations, optimal averaging periods for each variable were selected. A new dataset for building the forecasting model was then calculated as temporal moving averages (running means) of former variables. A multi-layer perceptron type of neural networks is used as the forecasting model. Index of agreement, calculated for the entire dataset including the data for model building, ranged from 0.91 to 0.97 for the respective pollutants. As suggested by the analysis of the relative importance of the input variables, different agreements for different pollutants are likely due to different sources and production mechanisms of investigated pollutants. A comparison of the new method with more traditional method, which takes hourly averages of the forecast hour as input variables, showed similar or better performance. The model was developed for the purpose of public-health-oriented air quality forecasting, aiming to use a numerical weather forecast model for the prediction of the part of input data yet unknown at the forecasting time. It is to expect that longer term averages used as inputs in the proposed method will contribute to smaller input errors and the greater accuracy of the model.     

Numerical simulation of an array of fences in Saemangeum reclaimed land

This paper discusses about the quantitative effect of windbreak fences on wind velocity in the reclaimed land at Saemangeum in South Korea. Windbreak fences were constructed in the reclaimed land to reduce the wind velocity to prevent the generation and diffusion of dust. However, up to this time, no in-depth studies were conducted to quantitatively measure the effect of the windbreak fences on wind velocity thus an optimum windbreak structure is not yet determined. Using CFD simulations, the effects of fence porosity, fence height, and the distance between the adjacent fences were investigated. A wind tunnel experiment was initially conducted and data gathered were used to develop the CFD models. From the experiments and CFD simulations, the overall percentage difference of the measured velocities was 7.20% which is generally acceptable to establishing the reliability of the CFD models. The reduction effect on wind velocity was measured in between the adjacent fences up to a height of 0.6 m from the ground surface. In terms of porosity ( = 0, 0.2, 0.4, 0.6), 0.2 was found to be the optimum value. Conversely, the effect of fence height (0.6, 0.8 and 1.0 m) showed no significant difference; therefore, 0.6 m height is recommended. In addition, the reduction effect of distance between the adjacent fences (2, 4 and 6 m) on wind velocity having a 0.2 porosity has decreased to about 75% regardless of the distance. In the case of the reclaimed land in Saemangeum, a decrease of 75% can prevent the generation and diffusion of dusts. However, the source of dusts is very large. Therefore, constructing an array of windbreak with 6 m distance between them is deemed necessary.     

Structure and thermal stability of toxic chromium(VI) species doped onto TiO2 powders through heat treatment

Chromium(VI)-containing sorbents in the form of sludge or solid residue from treatment processes are often landfilled or used as fill materials, therefore the long-term stability of metal binding is important. The reduction of Cr(VI)–Cr(III) through heat treatment may be a useful detoxification method. After heating at 500, 900, 1000, and 1100 °C for 4 h, the transformation of chemical states of chromium on 105 °C-dried, 7.9% Cr(VI)-doped TiO₂ powders was studied on the basis of surface area measurements, scanning electron microscopy (SEM) images, X-ray diffraction (XRD), and extended X-ray absorption fine structure (EXAFS) spectra. It was shown that Cr(VI) was reduced to Cr(III) in the Cr(VI)-doped samples after heating within 500–900 °C. The present results also suggested that the chromium octahedral was bridged to the titanium tetrahedral and was incorporated in TiO₂ minerals formed after 1000 °C treatment.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.     

Changes in negative air ions concentration under different light intensities and development of a model to relate light intensity to directional change

The purpose of this research was to determine changes in negative air ion (NAI) concentrations produced by plants grown under different light intensities. NAI concentrations were observed and analyzed in an outdoor green space with five plant species (Aloe arborescens, Clivia miniata, Chlorophytum comosum, Opuntia brunnescens, Crassula portulacea) and A. arborescens was then grown under controlled-light conditions in an enclosed space for the subsequent light intensity experiment.