The analysis of soil cores polluted with certain metals using the Box-Cox transformation

To define the soil properties for a given area or country including the level of pollution, soil survey and inventory programs are essential tools. Soil data transformations enable the expression of the original data on a new scale, more suitable for data analysis. In the computer-aided interactive analysis of large data files of soil characteristics containing outliers, the diagnostic plots of the exploratory data analysis (EDA) often find that the sample distribution is systematically skewed or reject sample homogeneity. Under such circumstances the original data should be transformed. The Box-Cox transformation improves sample symmetry and stabilizes spread. The logarithmic plot of a profile likelihood function enables the optimum transformation parameter to be found. Here, a proposed procedure for data transformation in univariate data analysis is illustrated on a determination of cadmium content in the plough zone of agricultural soils. A typical soil pollution survey concerns the determination of the elements Be (16 544 values available), Cd (40 317 values), Co (22 176 values), Cr (40 318 values), Hg (32 344 values), Ni (34 989 values), Pb (40 344 values), V (20 373 values) and Zn (36 123 values) in large samples.     

Development of a biotic ligand model (BLM) predicting nickel toxicity to barley (Hordeum vulgare)

A biotic ligand model (BLM) was developed to predict nickel toxicity, affecting root growth of barley (Hordeum vulgare), in nutrient solutions. The extent to which Ca(2+), Mg(2+), Na(+), K(+) ions and pH each influenced nickel toxicity was determined. Higher activities of Mg(2+) linearly increased the 4d EC50 Ni (2+) , while Ca(2+), Na(+), K(+) and H(+) activities did not significantly influence Ni(2+) toxicity. Stability constants for the binding of Ni(2+) and Mg(2+) to the biotic ligand were obtained: logK(NiBL)=5.27 and logK(MgBL)=3.47. Further, it was calculated that on average 57% of the biotic ligand sites needed to be occupied by nickel to induce 50% root growth inhibition. Auto-validation of the BLM indicated that predicted EC50s differed from the observed EC50s by a factor of less than 2, indicating that the BLM concept may also be used to predict metal toxicity to terrestrial plants.     

Quantitative structure-activity relationships for toxicity and genotoxicity of halogenated aliphatic compounds: wing spot test of Drosophila melanogaster

Halogenated aliphatic compounds were evaluated for toxic and genotoxic effects in the somatic mutation and recombination test employing Drosophila melanogaster. The tested chemicals included chlorinated, brominated and iodinated; mono-, di- and tri-substituted; saturated and unsaturated alkanes: 1,2-dibromoethane, 1-bromo-2-chloroethane, 1-iodopropane, 2,3-dichloropropene, 3-bromo-1-propene, epibromohydrin, 2-iodobutane, 3-chloro-2-methylpropene, 1,2,3-trichloropropane, 1,2-dichloroethane, 1,2-dichlorobutane, 1-chloro-2-methylpropane, 1,3-dichloropropane, 1,2-dichloropropane, 2-chloroethymethylether, 1-bromo-2-methylpropane and 1-chloropentane. N-methyl-N-nitrosourea served as the positive and distilled water as the negative control. The set of chemicals for the toxicological testing was selected by the use of statistical experiment design. Group of unsaturated aliphatic hydrocarbons were generally more toxic than saturated analogues. The genotoxic effect was observed with 14 compounds in the wing spot test, while 3 substances did not show any genotoxicity by using the wing spot test at 50% lethal concentration. The highest number of wing spots was observed in genotoxicity assay with 1-bromo-2-chloroethane, 1,2-dichloroethane, 1,2-dibromoethane and 1-iodopropane. Nucleophilic superdelocalizability calculated by quantum mechanics appears to be a good parameter for prediction of both toxicity and genotoxicity effects of halogenated aliphatic compounds.     

Resource management as a key factor for sustainable urban planning

Due to fast urbanization and increasing living standards, the environmental sustainability of our global society becomes more and more questionable. In this historical review we investigate the role of resources management (RM) and urban planning (UP) and propose ways for integration in sustainable development (SD). RM follows the principle of circular causation, and we reflect on to what extent RM has been an element for urban planning. Since the existence of the first settlements, a close relationship between RM, urbanization and technological development has been present. RM followed the demand for urban resources like water, energy, and food. In history, RM has been fostered by innovation and technology developments and has driven population growth and urbanization. Recent massive resource demand, especially in relation to energy and material flows, has altered natural ecosystems and has resulted in environmental degradation. UP has developed separately in response to different questions. UP followed the demand for improved living conditions, often associated to safety, good manufacturing and trading conditions and appropriate sanitation and waste management. In history UP has been a developing research area, especially since the industrial era and the related strong urbanization at the end of the 18th century. UP responded to new emerging problems in urban areas and became increasingly complex. Nowadays, UP has to address many objectives that are often conflicting, including, the urban sustainability. Our current urban un-sustainability is rooted in massive resource consumption and waste production beyond natural limits, and the absence of flows from waste to resources. Therefore, sustainable urban development requires integration of RM into UP. We propose new ways to this integration.     

Introduction-global to local: Ecological Land Classification

Ecological Land Classification (ELC) is a scientific endeavour which attempts to organize, stratify and evaluate ecosystems (and complexes of ecosystems) for the purposes of land resource management. Since ecosystems themselves are not easily defined in practical terms, ELC is likewise not a trivial concept. Nonetheless, ELC is a prerequisite for ecosystem management and the conservation of biological diversity simply because ecosystems must be described, characterized and spatially-located before they can be managed. Regarding the current status and future direction of ELC, mainly in relation to forest management: 1) approaches to ELC construction and utilization have shifted considerably over the past 2 decades; 2) there appears to be a current consensus regarding basic approaches to ELC; 3) spatial scale is a critical variable that must be addressed by ELCs; 4) ELCs must strive to more directly address management objectives; 5) natural ecosystem functions need to be better integrated within ELC frameworks; and, 6) the need for quality, georeferenced ELC-related data will continue to grow.