Gerrit Schüürmann

External Validation and Prediction Employing the Predictive Squared Correlation Coefficient — Test Set Activity Mean vs Training Set Activity Mean

The external prediction capability of quantitative structure-activity relationship (QSAR) models is often quantified using the predictive squared correlation coefficient, q (2). This index relates the predictive residual sum of squares, PRESS, to the activity sum of squares, SS, without postprocessing of the model output, the latter of which is automatically done when calculating the conventional squared correlation coefficient, r (2). According to the current OECD guidelines, q (2) for external validation should be calculated with SS referring to the training set activity mean. Our present findings including a mathematical proof demonstrate that this approach yields a systematic overestimation of the prediction capability that is triggered by the difference between the training and test set activity means. Example calculations with three regression models and data sets taken from literature show further that for external test sets, q (2) based on the training set activity mean may become even larger than r (2). As a consequence, we suggest to always use the test set activity mean when quantifying the external prediction capability through q (2) and to revise the respective OECD guidance document accordingly. The discussion includes a comparison between r (2) and q (2) value ranges and the q (2) statistics for cross-validation.

Mixture toxicity and its modeling by quantitative structure-activity relationships

Environmental contaminants are frequently encountered as mixtures, and the behavior of chemicals in a mixture may not correspond to that predicted from data on the pure compounds. This paper reviews current quantitative structure-activity relationship (QSAR) methodology for the analysis of mixture toxicity. Interactions of components in a mixture can cause complex and substantial changes in the apparent properties of its constituents, resulting in synergistic or antagonistic effects as opposed to the ideal reference case of additive behavior: concentration addition (CA) and independent action (IA) are two prominent reference models for the evaluation of joint activity, and both have mechanistic support from pharmacology. After discussing graphical tools for analyzing binary mixtures and joint effect indices suitable also for multicomponent mixtures, water solubility and hydrophobicity of mixtures are analyzed with respect to the property contributions of the individual components. With the former, small but significant deviations from ideal behavior are observed even for simple organics, whereas in the case of low concentrations, mixture hydrophobicity was found to agree approximately with the fractional contributions of the components. A variety of studies suggest that mixtures of compounds exerting only one (narcotic or specific) mode of action can be modeled satisfactorily by assuming CA, whereas the interaction of differently acting compounds tends to yield a less than CA joint activity. The QSARs have been used to predict concentrations of components in mixtures from joint effects and defined mixture ratios and have been developed to predict narcotic-type mixture toxicity from molecular descriptors that are calculated as composite properties according to the fractional concentrations of the mixture components. In the case of ionogenic compounds, initial results suggest that CA may serve as a first-order approximation for the joint effect of un-ionized and ionized compound portions.

Persistent organic pollutants in agricultural soils of central Germany

Concentrations of persistent organic pollutants (HCHs, DDX, PCBs and HCB) were measured in topsoils from 11 agricultural fields in the lee of large disused industrial plants in the Leipzig-Halle region at varying distances from emitters. The investigations clearly indicate the deposition of anthropogenic pollutant inputs, not only in the past, but also today. The pollution potential was assessed on the basis of current guide values and limits, as well as in relation to values found in agricultural soils elsewhere in Germany, in Europe and in the USA. The reference values were mainly exceeded for DDX and gamma-HCH (lindane). The PCB pattern was determined and the degradation ratios between the parent substances and their metabolites (DDX and HCH isomers) were calculated in order to distinguish between the previous and current pollutant input of pesticides by means of principal component analysis.

A new risk assessment approach for the prioritization of 500 classical and emerging organic microcontaminants as potential river basin specific pollutants under the European Water Framework Directive

Given the huge number of chemicals released into the environment and existing time and budget constraints, there is a need to prioritize chemicals for risk assessment and monitoring in the context of the European Union Water Framework Directive (EU WFD). This study is the first to assess the risk of 500 organic substances based on observations in the four European river basins of the Elbe, Scheldt, Danube and Llobregat. A decision tree is introduced that first classifies chemicals into six categories depending on the information available, which allows water managers to focus on the next steps (e.g. derivation of Environmental Quality Standards (EQS), improvement of analytical methods, etc.). The priority within each category is then evaluated based on two indicators, the Frequency of Exceedance and the Extent of Exceedance of Predicted No-Effect Concentrations (PNECs). These two indictors are based on maximum environmental concentrations (MEC), rather than the commonly used statistically based averages (Predicted Effect Concentration, PEC), and compared to the lowest acute-based (PNEC(acute)) or chronic-based thresholds (PNEC(chronic)). For 56% of the compounds, PNECs were available from existing risk assessments, and the majority of these PNECs were derived from chronic toxicity data or simulated ecosystem studies (mesocosm) with rather low assessment factors. The limitations of this concept for risk assessment purposes are discussed. For the remainder, provisional PNECs (P-PNECs) were established from read-across models for acute toxicity to the standard test organisms Daphnia magna, Pimephales promelas and Selenastrum capricornutum. On the one hand, the prioritization revealed that about three-quarter of the 44 substances with MEC/PNEC ratios above ten were pesticides. On the other hand, based on the monitoring data used in this study, no risk with regard to the water phase could be found for eight of the 41 priority substances, indicating a first success of the implementation of the WFD in the investigated river basins.

Group contribution methods to estimate water solubility of organic chemicals

Group contribution methods to estimate water solubility have been studied on the basis of a test set of 694 organic nonelectrolytes, consisting of 351 liquids and 343 solids with experimental data taken from literature after critical evaluation. Derivation of a new fragmentation scheme leads to a squared correlation coefficient of 0.95 and an average absolute calculation error of 0.38 log units, which is superior to other group contribution methods currently available. Differences in performance for individual classes of compounds are discussed in detail. Solubility prediction for liquids is generally better than for solids, and the results support the inclusion of a melting point term to account for the entropy of fusion of solids.

Biomonitoring of airborne inorganic and organic pollutants by means of pine tree barks. I. Temporal and spatial variations.

Scots pine (Pinus sylvestris L.) bark samples were collected at two field sites (Neuglobsow, Rösa) and in different years between 1987 and 1996 in the east of Germany. The barks were analyzed with respect to the following inorganic and organic substances: Al, As, B, Ca, Cd, Ce, Cr, Cu, Fe, Hg, Mo, NH4+, Ni, NO3-, PO4(3)-, Pb, Sr, SO4(2)-, Ti, V, W, Zr, Zn, benzo[a]pyrene, fluoranthene, pyrene, alpha-hexachlorocyclohexane (alpha-HCH) and dichlorodiphenyltrichloroethane (DDT). In addition to bark samples from the site Rösa, 53 test sites were investigated in the Nature Park Dübener Heide. Here, the analysis of the barks aimed at discovering spatial patterns of the above-mentioned substances. Since 1991, most of the determined substances (e.g. sulfate, nitrate, calcium, lead, benzo[a]pyrene, alpha-HCH) show decreased concentration values in bark samples from both sites. Temporal variations reflect substantial infra-structural changes in eastern Germany, especially at Rösa and in the industrial region around the cities Leipzig, Halle, and Bitterfeld. Moreover, nitrate concentrations in barks are increasing since 1995. The trend can be explained with increased nitrogen emissions from motor traffic and livestock farms. Spatial patterns of sulphate and ammonia reflect inputs from power plants and agriculture in pine stands of the Nature Park Dübener Heide. The results show that barks of pine trees can be used as biomonitoring tools to indicate and characterize depositions of airborne organic and inorganic pollutants.

Multivariate Discrimination between Modes of Toxic Action of Phenols

A set of 221 phenols, for which toxicity data to the ciliate Tetrahymena pyriformis were available, was subjected to stepwise linear discriminant analysis (LDA) in order to classify their toxic mechanisms of action. The compounds were a priori grouped into the following four mechanisms according to structural rules: polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Hydrophobicity with and without correction for ionisation (log K o w , log D o w u), acidity constant (pK a ), frontier orbital energies (E L U M O , E H O M O ) and hydrogenbond donor and acceptor counts were used as molecular descriptors. LDA models employing 3-6 variables achieved 86-89% overall correct classification of the four mechanisms, with more varied performance for respiratory uncouplers and pro-electrophiles. For the latter, a separate model was developed that discriminated compounds undergoing metabolic activation from compounds with different mechanisms very accurately. Model validation was performed by evaluating the simulated external prediction through LDA models built from complementary subsets.

Evaluation of regional heavy metal deposition by multivariate analysis of element contents in pine tree barks

The airborne immission of heavy metals in the conservation area “Dübener Heide” nearby Bitterfeld was evaluated by biomonitoring studies with bark samples of 60-years-old scots pine (Pinus sylvestris L.). Nitric acid digestion and hydrochloric acid extraction of bark was followed by ICP-AES and ICP-MS analysis of the elements Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb and Zn. Fe and especially Cr were only partly soluble in hydrochloric acid. These elements deposited mostly as insoluble oxides, and their contents in the bark correlate significantly with Ca and S as elements of alkaline and acid deposition. Factor and cluster analysis of all element contents are used for the characterization and evaluation of heavy metal deposition types, which is shown to be a useful tool in forest monitoring control.

The SOLUTIONS project: Challenges and responses for present and future emerging pollutants in land and water resources management

SOLUTIONS (2013 to 2018) is a European Union Seventh Framework Programme Project (EU-FP7). The project aims to deliver a conceptual framework to support the evidence-based development of environmental policies with regard to water quality. SOLUTIONS will develop the tools for the identification, prioritisation and assessment of those water contaminants that may pose a risk to ecosystems and human health. To this end, a new generation of chemical and effect-based monitoring tools is developed and integrated with a full set of exposure, effect and risk assessment models. SOLUTIONS attempts to address legacy, present and future contamination by integrating monitoring and modelling based approaches with scenarios on future developments in society, economy and technology and thus in contamination. The project follows a solutions-oriented approach by addressing major problems of water and chemicals management and by assessing abatement options. SOLUTIONS takes advantage of the access to the infrastructure necessary to investigate the large basins of the Danube and Rhine as well as relevant Mediterranean basins as case studies, and puts major efforts on stakeholder dialogue and support. Particularly, the EU Water Framework Directive (WFD) Common Implementation Strategy (CIS) working groups, International River Commissions, and water works associations are directly supported with consistent guidance for the early detection, identification, prioritisation, and abatement of chemicals in the water cycle. SOLUTIONS will give a specific emphasis on concepts and tools for the impact and risk assessment of complex mixtures of emerging pollutants, their metabolites and transformation products. Analytical and effect-based screening tools will be applied together with ecological assessment tools for the identification of toxicants and their impacts. The SOLUTIONS approach is expected to provide transparent and evidence-based candidates or River Basin Specific Pollutants in the case study basins and to assist future review of priority pollutants under the WFD as well as potential abatement options.

Acute to chronic ratios in aquatic toxicity--variation across trophic levels and relationship with chemical structure.

For fish, daphnids, and algae, acute to chronic ratios (ACRs) have been determined from experimental data regarding new and existing chemicals. Only test results in accord with the European Union Technical Guidance Document (TGD) and validated by authorities were considered. Whereas the median ACRs of 10.5 (fish), 7.0 (daphnids), and 5.4 (algae) are well below the ACR safety factor of 100 as implied by the TGD, individual ACRs vary considerably and go up to 4400. The results suggest that a safety factor of 100 is not protective for all chemicals and trophic levels. Neither a correlation between ACR and baseline toxicity as modeled through the logarithmic octanol-water partition coefficient nor an ACR correlation across trophic levels exists. Narcosis is associated with a preference for a low ACR; nevertheless, low ACRs are frequently obtained for nonnarcotics. Analysis of chemical structures led to the derivation of structural alerts to identify compounds with a significantly increased potential for a high ACR, which may prove to be useful in setting test priorities. At present, however, life-cycle tests are the only way to conservatively predict long-term toxicity.