Harrie Hendriks

Cumulative energy demand as predictor for the environmental burden of commodity production.

Cumulative energy demand has been used as a methodology to assess life cycle environmental impacts of commodity production since the early seventies, but has also been criticized because it focuses on energy only. During the past 30 years there has been much research into the development of more complex single-score life cycle impact assessment methodologies. However, a comprehensive analysis of potential similarities and differences between these methodologies and cumulative energy demand has not been carried out so far. Here we compare the cumulative energy demand of 498 commodities with the results of six frequently applied environmental life cycle impact assessment methodologies. Commodity groups included are metals, glass, paper and cardboard, organic and inorganic chemicals, agricultural products, construction materials, and plastics. We show that all impact assessment methods investigated often provide converging results, in spite of the different philosophies behind these methodologies. Fossil energy use is identified by all methodologies as the most important driver of environmental burden of the majority of the commodities included,with the main exception of agricultural products. We conclude that a wide range of life cycle environmental assessment methodologies point into the same environmental direction for the production of many commodities.

Age at onset variance analysis in spinocerebellar ataxias: a study in a Dutch-French cohort

In dominant spinocerebellar ataxias (SCAs), the issue of whether non‐CAG dependent factors contribute to onset age remains unsettled. Data on SCA genotype, onset age, normal/expanded CAG repeat length, sex of the patient and transmitting parent, and family details were available from 802 patients. Based on the model [log10 (age at onset) = k − b CAGexp + ϵ], we examined changes in adjusted R2 and residual standard error following incorporation of the other factors in this model. The expanded repeat explained 44.3 to 74.9% of onset age variance, although this was less than 50% in SCA3 and SCA6, implicating a large effect of non‐CAG factors. The relation between onset age and CAG repeat was similar for SCA1, 3, 6, and 7, but different for SCA2, pointing to different polyglutamine effects in SCA2. For SCA2 and SCA3, 17.1 and 45.5% of onset age variance, respectively, were explained by currently (unidentified) familial factors. We found a significant contribution of the nonexpanded allele in SCA1 and SCA6. Besides polyglutamine motif (determined by the expanded CAG repeat length), we identified the following age at onset modifiers: protein context in SCA2; familial factors in SCA2 and SCA3; and the nonexpanded CAG repeat in SCA1 and SCA6. Ann Neurol 2005

Environmental and morphological factors influencing predatory behaviour by invasive non-indigenous gammaridean species

Predatory behaviour seems to be more frequent in invasive gammaridean species than in native ones. This results in the exclusion of other, mostly native gammaridean species and a change in benthic communities. The present study analysed the influence of environmental factors (water temperature) and morphological factors (sex, body parts involved in catching and holding prey) on the predatory behaviour of Dikerogammarus villosus. A diet study of invasive relatives of D. villosus showed that predation intensity is especially high in spring and summer, that is, at increasing and high temperatures. Experiments with D. villosus in climate rooms at various temperatures, using the native Gammarus fossarum as prey, showed that the average predation rate by both sexes gradually increased over the temperature range from 5 to 30°C. Natural mortality during the experiments was negligible compared to losses due to predation. At each temperature, the predation rate by females was lower than that by males. Males showed a steep allometric growth of body parts involved in the process of catching and holding prey, compared to females at increasing body size in a number of measurements. This may explain the difference in predatory behaviour between males and females, which plays a role in intraguild predation a supposed mechanism for species displacement.

A Crame´r-Rao–type lower bound for estimators with values in a manifold

A Cramer-Rao type lower bound for minimum loss unbiased estimators with values in a manifold is derived, and the corresponding notion of efficiency is investigated. A by-product is a generalisation of the concept of covariance of a multivariate statistic to one of a statistic with values in a manifold.

Separation of uncertainty and interindividual variability in human exposure modeling

The NORMTOX model predicts the lifetime-averaged exposure to contaminants through multiple environmental media, that is, food, air, soil, drinking and surface water. The model was developed to test the coherence of Dutch environmental quality objectives (EQOs). A set of EQOs is called coherent if simultaneous exposure to different environmental media that are all polluted up to their respective EQOs does not result in exceeding the acceptable or tolerable daily intake (ADI or TDI). Aim of the present study is to separate the impact of uncertainty and interindividual variability in coherence predictions with the NORMTOX model. The method is illustrated in a case study for chlorfenvinphos, mercury and nitrate. First, ANOVA was used to calculate interindividual variability in input parameters. Second, nested Monte Carlo simulation was used to propagate uncertainty and interindividual variability separately. Lifetime-averaged exposure to chlorfenvinphos, mercury and nitrate was modeled for the Dutch population. Output distributions specified the population fraction at risk, due to a particular exposure, and the reliability of this risk. From the case study, it was obtained that at lifelong exposure to all media polluted up to their standard, 100% of the Dutch population exceeds the ADI for chlorfenvinphos, 15% for mercury and 0% for nitrate. Variance in exposure to chlorfenvinphos, mercury and nitrate is mostly caused by interindividual variability instead of true uncertainty. It is concluded that the likelihood that ADIs of chlorfenvinphos and mercury will be exceeded should be further explored. If exceeding is likely, decision makers should focus on identification of high-risk subpopulations, rather than on additional research to obtain more accurate estimates for particular parameters.

Asymptotic behavior of sample mean location for manifolds

We investigate some asymptotic properties of empirical mean location on compact smooth submanifolds of Euclidean space. Thus our results provide the framework for asymptotic least-squares statistics inference regarding mean location in a rather general situation.

PARAMETER UNCERTAINTY IN MODELING BIOACCUMULATION FACTORS OF FISH

We quantified the uncertainty due to biota-related parameters in estimated bioaccumulation factors (BAFs) of persistent organic pollutants for fish through Monte Carlo simulations. For this purpose, the bioaccumulation model OMEGA (Optimal Modeling for EcotoxicoloGical Applications) was parameterized based on data from the existing literature, analysis of allometric data, and maximum likelihood estimation. Lipid contents, fractions of food assimilated, the allometric rate exponent, normalized food intakes, respiration and growth dilution rates, and partial mass transfer resistances in water and lipid layers were included as uncertain parameters. The uncertainty in partial resistances was particularly important in the estimation of the rate constants for chemical intake from water by fish. Uncertainties in the fractions of food assimilated and partial water layer resistances from and to food were particularly important in the estimation of the rate constants of chemical intake from food. The uncertainty in the model outcomes for the bioaccumulation factors for fish was a factor of 10 (ratio of 95th and fifth percentile estimates), which was mainly caused by the uncertainty in the lipid fraction. For chemicals with a K(OW) of 10(3) to 10(6), the uncertainty in the lipid contents of fish accounted for more than 50% of the uncertainty in the estimated bioaccumulation factor. For chemicals with a high K(OW) (10(7) and higher), the fractions of food assimilated and partial resistances also contributed to uncertainty in the estimated bioaccumulation factor (up to 60%). A case study showed that uncertainty in estimated BAF for nonpersistent substances can be dominated by uncertainty in the rate constants for metabolic transformation.

The impact of an additional ecotoxicity test on ecological quality standards

The present study aims to support decisions on whether or not to perform an extra toxicity test in order to improve environmental quality standards (EQSs). The impact of an additional ecotoxicity test was analyzed by predicting new ecotoxicity values with three different estimation methods and adding them to existing species sensitivity distributions (SSDs) on which the EQSs are based. The results show that EQSs are likely to increase due to increasing sample size, but the change also depends on the number of toxicity values available, the estimation method used and the representativeness of the species tested. The management consequences are illustrated in a case study on contaminated freshwater sediment in the Netherlands. It is shown that a slight increase of the EQS can result in a large reduction of sediment remediation costs without impairing regulatory protection levels. The paper identifies indicators that can be used to evaluate the potential impact of an extra ecotoxicity test.

Application of fast spherical Fourier transform to density estimation

This paper is on density estimation on the 2-sphere, S2, using the orthogonal series estimator corresponding to spherical harmonics. In the standard approach of truncating the Fourier series of the empirical density, the Fourier transform is replaced with a version of the discrete fast spherical Fourier transform, as developed by Driscoll and Healy. The fast transform only applies to quantitative data on a regular grid. We will apply a kernel operator to the empirical density, to produce a function whose values at the vertices of such a grid will be the basis for the density estimation. The proposed estimation procedure also contains a deconvolution step, in order to reduce the bias introduced by the initial kernel operator. The main issue is to find necessary conditions on the involved discretization and the bandwidth of the kernel operator, to preserve the rate of convergence that can be achieved by the usual computationally intensive Fourier transform. Density estimation is considered in L2(S2) and more generally in Sobolev spaces Hυ(S2), any υ ≥ 0, with the regularity assumption that the probability density to be estimated belongs to Hs(S2) for some s > υ. The proposed technique to estimate the Fourier transform of an unknown density keeps computing cost down to order O(n), where n denotes the sample size.

Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures

Species in the aquatic environment differ in their toxicological sensitivity to the various chemicals they encounter. In aquatic risk assessment, this interspecies variation is often quantified via species sensitivity distributions. Because the information available for the characterization of these distributions is typically limited, optimal use of information is essential to reduce uncertainty involved in the assessment. In the present study, we show that the credibility intervals on the estimated potentially affected fraction of species after exposure to a mixture of chemicals at environmentally relevant surface water concentrations can be extremely wide if a classical approach is followed, in which each chemical in the mixture is considered in isolation. As an alternative, we propose a hierarchical Bayesian approach, in which knowledge on the toxicity of chemicals other than those assessed is incorporated. A case study with a mixture of 13 pharmaceuticals demonstrates that this hierarchical approach results in more realistic estimations of the potentially affected fraction, as a result of reduced uncertainty in species sensitivity distributions for data-poor chemicals.