A.M.J. Ragas

Priority assessment of toxic substances in life cycle assessment. Part I: Calculation of toxicity potentials for 181 substances with the nested multi-media fate, exposure and effects model USES-LCA

Toxicity potentials are standard values used in life cycle assessment (LCA) to enable a comparison of toxic impacts between substances. In most cases, toxicity potentials are calculated with multi-media fate models. Until now, unrealistic system settings were used for these calculations. The present paper outlines an improved model to calculate toxicity potentials: the global nested multi-media fate, exposure and effects model USES-LCA. It is based on the Uniform System for the Evaluation of Substances 2.0 (USES 2.0). USES-LCA was used to calculate for 181 substances toxicity potentials for the six impact categories freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, freshwater sediment ecotoxicity, marine sediment ecotoxicity, terrestrial ecotoxicity and human toxicity, after initial emission to the compartments air, freshwater, seawater, industrial soil and agricultural soil, respectively. Differences of several orders of magnitude were found between the new toxicity potentials and those calculated previously.

Aquatic ecotoxicity tests of some nanomaterials

Nanoparticles of TiO2, ZrO2, AL2O3, CeO2, fullerene (C60), single-walled carbon nanotubes, and polymethylmethacrylate were tested for ecotoxic effects using one or more ecotoxicity endpoints: Microtox (bacteria), pulse-amplitude modulation (algae), Chydotox (crustaceans), and Biolog (soil enzymes). No appreciable effects were observed at nominal concentrations of up to 100 mg/L. Dilution of nanoparticle suspensions, either in ultrapure (Milli-Q) water or in natural (pond) water, led to formation of larger particles, which settled easily. (Nano)particles in water were characterized by means of atomic force microscopy, energy-dispersive x-ray analysis, inductively coupled plasma-mass spectrometry, flow cytometry, and spectrophotometry. It is concluded that the absence of ecotoxicity is the result of low concentrations of free nanoparticles in the tests, and it is suggested that colloid (in)stability is of primary importance in explaining ecotoxic effects of nanoparticles in the natural environment.

Human-Toxicological Effect and Damage Factors of Carcinogenic and Noncarcinogenic Chemicals for Life Cycle Impact Assessment

Abstract Chemical fate, effect, and damage should be accounted for in the analysis of human health impacts by toxic chemicals in life-cycle assessment (LCA). The goal of this article is to present a new method to derive human damage and effect factors of toxic pollutants, starting from a lognormal dose–response function. Human damage factors are expressed as disability-adjusted life years (DALYs). Human effect factors contain a disease-specific and a substance-specific component. The disease-specific component depends on the probability of disease occurrence and the distribution of sensitivities in the human population. The substance-specific component, equal to the inverse of the ED50, represents the toxic potency of a substance. The new method has been applied to calculate combined human damage and effect factors for 1,192 substances. The total range of 7 to 9 orders of magnitude between the substances is dominated by the range in toxic potencies. For the combined factors, the typical uncertainty, represented by the square root of the ratio of the 97.5th and 2.5th percentile, is a factor of 25 for carcinogenic effects and a factor of 125 for noncarcinogenic effects. The interspecies conversion factor, the (non)cancer effect conversion factor, and the average noncancer damage factor dominate the overall uncertainty.

Classification of floodplain vegetation by data fusion of spectral (CASI) and LiDAR data

To safeguard the goals of flood protection and nature development, a river manager requires detailed and up‐to‐date information on vegetation structures in floodplains. In this study, remote‐sensing data on the vegetation of a semi‐natural floodplain along the river Waal in the Netherlands were gathered by means of a Compact Airborne Spectrographic Imager (CASI; spectral information) and LiDAR (structural information). These data were used to classify the floodplain vegetation into eight and five different vegetation classes, respectively. The main objective was to fuse the CASI and LiDAR‐derived datasets on a pixel level and to compare the classification results of the fused dataset with those of the non‐fused datasets. The performance of the classification results was evaluated against vegetation data recorded in the field. The LiDAR data alone provided insufficient information for accurate classification. The overall accuracy amounted to 41% in the five‐class set. Using CASI data only, the overall accuracy was 74% (five‐class set). The combination produced the best results, raising the overall accuracy to 81% (five‐class set). It is concluded that fusion of CASI and LiDAR data can improve the classification of floodplain vegetation, especially for those vegetation classes which are important to predict hydraulic roughness, i.e. bush and forest. A novel measure, the balance index, is introduced to assess the accuracy of error matrices describing an ordered sequence of classes such as vegetation structure classes that range from bare soil to forest.

Priority assessment of toxic substances in life cycle assessment. Part II: assessing parameter uncertainty and human variability in the calculation of toxicity potentials.

Toxicity potentials are standard values used in life cycle assessment (LCA) to enable a comparison of toxic impacts between substances. This paper presents the results of an uncertainty assessment of toxicity potentials that were calculated with the global nested multi-media fate, exposure and effects model USES-LCA. The variance in toxicity potentials resulting from input parameter uncertainties and human variability was quantified by means of Monte Carlo analysis with Latin Hypercube sampling (LHS). For Atrazine, 2,3,7,8-TCDD and Lead, variation, expressed by the ratio of the 97.5%-ile and the 2.5%-ile, ranges from about 1.5 to 6 orders of magnitude. The major part of this variation originates from a limited set of substance-specific input parameters, i.e. parameters that describe transport mechanisms, substance degradation, indirect exposure routes and no-effect concentrations. Considerable correlations were found between the toxicity potentials of one substance, in particular within one impact category. The uncertainties and correlations reported in the present study may have a significant impact on the outcome of LCA case studies.

Cumulative risk assessment of chemical exposures in urban environments

We performed a cumulative risk assessment for people living in a hypothetical urban environment, called Urbania. The main aims of the study were to demonstrate how a cumulative risk assessment for a middle-sized European city can be performed and to identify the bottlenecks in terms of data availability and knowledge gaps. The assessment focused on five air pollutants (i.e., PM₁₀, benzene, toluene, nonane and naphthalene) and six food pesticides (i.e., acetamiprid, carbendazim, chlorpyrifos, diazinon, imidacloprid and permethrin). Exposure predictions showed that PM₁₀, benzene and naphthalene exposure frequently exceeded the standards, and that the indoor environment contributed more than the outdoor environment. Effect predictions showed that mixture and interaction effects were generally limited. However, model calculations indicated potential synergistic effects between naphthalene and benzene and between chlorpyrifos, diazinon and toluene. PM₁₀ dominated the health impact expressed in Disability Adjusted Life Years (DALYs). We conclude that measures to reduce the health impact of environmental pollution should focus on the improvement of indoor air quality and the reduction of PM₁₀ emissions. Cumulative risk assessment can be improved by (1) the development of person-oriented exposure models that can simulate the cumulative exposure history of individuals, (2) a better mechanistic understanding of the effects of cumulative stressors, and (3) the development of instruments to prioritize stressors for inclusion in cumulative risk assessments.

Tools and perspectives for assessing chemical mixtures and multiple stressors

The present paper summarizes the most important insights and findings of the EU NoMiracle project with a focus on (1) risk assessment of chemical mixtures, (2) combinations of chemical and natural stressors, and (3) the receptor-oriented approach in cumulative risk assessment. The project aimed at integration of methods for human and ecological risk assessment. A mechanistically based model, considering uptake and toxicity as a processes in time, has demonstrated considerable potential for predicting mixture effects in ecotoxicology, but requires the measurement of toxicity endpoints at different moments in time. Within a novel framework for risk assessment of chemical mixtures, the importance of environmental factors on toxicokinetic processes is highlighted. A new paradigm for applying personal characteristics that determine individual exposure and sensitivity in human risk assessment is suggested. The results are discussed in the light of recent developments in risk assessment of mixtures and multiple stressors.

Substance or space? The relative importance of substance properties and environmental characteristics in modeling the fate of chemicals in Europe

The relative influence of substance properties and of environmental characteristics on the variation in the environmental fate of chemicals was studied systematically and comprehensively. This was done by modeling environmental concentrations for 200 sets of substance properties, representative of organic chemicals used, and 137 sets of environmental characteristics, representative of regions in Europe of 250 x 250 km. Since it was expected that the model scale has an influence on the predicted concentration variations, the calculations were repeated for regions with a 100 x 100 km and 50 x 50 km area. Stepwise multiple regression analysis was performed to determine the contribution of each of the individual input parameters on the total concentration variation. Depending on the scenario, the range in predicted environmental concentrations spreads from two up to nine orders of magnitude. In accord with earlier studies, variation in the fate of chemicals in the environment appeared to depend mainly on substance-specific partition coefficients and degradation rates. For the estimation of soil and water concentrations with direct emissions to these compartments, however, the influence of spatial variation in environmental characteristics can mount up to two orders of magnitude, a range that can be significant to account for in certain model applications. Concentration differences in water and soil are predicted to be larger if a smaller region is applied in the model calculations, and the relative influence of environmental characteristics on the total variation increases on a more detailed spatial scale. It is argued that the influence of environmental characteristics as predictors of exposure concentrations of chemicals deserves better attention in comparative risk assessment with conventional nonspatial multimedia box models.

Model and input uncertainty in multi-media fate modeling: Benzo[a]pyrene concentrations in Europe

This paper evaluates the contribution of (i) uncertainty in substance properties, (ii) lack of spatial variability, (iii) intermodel differences and (iv) neglecting sorption to black carbon (BC) to the uncertainty of Benzo[a]pyrene (BaP) concentrations in European air, soil and fresh water predicted by the multi-media fate model Simplebox. Uncertainty in substance properties was quantified using probabilistic modeling. The influence of spatial variability was quantified by estimating variation in predicted concentrations with three spatially explicit fate models (Impact 2002, EVn BETR and BETR Global). Intermodel differences were quantified by comparing concentration estimates of Simplebox, Impact 2002, EVn BETR and the European part of BETR Global. Finally, predictions of a BC-inclusive version of Simplebox were compared with predictions of a BC-exclusive version. For air concentrations of BaP, the lack of spatial variability in emissions was most influential. For freshwater concentrations of BaP, intermodel differences and lack of spatial variability in dimensions of fresh water bodies were the dominant sources of uncertainty. For soil, all sources of uncertainty were of comparable magnitude. Our results indicate that uncertainty in Simplebox can be as large as three orders of magnitude for BaP concentrations in the environment and would be substantially underestimated by focusing on one source of uncertainty only.

Spatially explicit prioritization of human antibiotics and antineoplastics in Europe

This paper presents a screening tool for the location-specific prioritization of human pharmaceutical emissions in Europe, based on risk quotients for the aquatic environment and human health. The tool provides direction towards either monitoring activities or additional research. Its application is illustrated for a set of 11 human antibiotics and 7 antineoplastics. Risk quotients for the aquatic environment were highest for levofloxacin, doxycycline and ciprofloxacin, located in Northern Italy (Milan region; particularly levofloxacin) and other densely populated areas in Europe (e.g. London, Krakow and the Ruhr area). Risk quotients for human health not only depend on pharmaceutical and location, but also on behavioral characteristics, such as consumption patterns. Infants in eastern Spain that consume locally produced food and conventionally treated drinking water were predicted to run the highest risks. A limited comparison with measured concentrations in surface water showed that predicted and measured concentrations are approximately within one order of magnitude.