Exploring the risk information gap. Research into information supply and information demand of different parties concerned

The Dutch National Institute for Public Health and the Environment (RIVM), a governmental research institute, provides information on environmental and health risks. The primary contractors’ information demands are served well. But the risk information available from the RIVM does not always correspond to the desires and requirements of other parties concerned. It became apparent that – to a certain extent – an information gap exists, arising from a difference between the institute’s information supply and the information demand of the different parties concerned.This explorative study focuses on the information demand and supply with regard to three different risks: flooding by rivers, air pollution and food related risks.For each risk, the information supply was determined by listing the available risk information in RIVM reports. In a second step, the information demand of the five different parties, as well as different channels of communication, were examined. The parties’ perceptions and requirements concerning risk information were identified in interviews and focus group discussions.The public, which in general appeared to be quite unfamiliar with the institute and its information sources, preferred risk information tailored to its personal circumstances. Policy makers mainly appreciated personal contacts in order to keep up to date on risk topics, whereas NGOs and fellow researchers judged the institute’s website and reports to be more relevant. Press releases appeared to add little to satisfying the information demand of the media.     

Land Cover Changes as a Result of Environmental Restrictions on Nitrate Leaching in Dairy Farming

Nitrate leaching forms an important environmental problem because it causes pollution of groundwater and surface water, and adds to already problematic eutrophication. This study analyses the impact of reductions in nitrate leaching on land cover decisions of dairy farms, of which the activities make an important contribution to nitrate leaching. As the level of nitrate leaching depends on groundwater depth as well as on the supply of nitrogen, spatial variation in groundwater levels will cause a spatial variation in land cover under restrictions on nitrate leaching. A non-linear partial optimisation model for the economic and ecological aspects of the problem were used to show how land cover and dairy farms' financial balances change when nitrate losses are reduced. The model is spatially explicit, and describes nitrate leakage and yields of maize and grass as a function of groundwater depth, including the effects of various grazing systems. The model analyses the decisions of a risk neutral agent who minimises costs under the following constraints: (i) production, feed requirements and mass balances for fodder; (ii) constraints for nitrate leaching. Economic costs are attributed to increased costs of fodder and processing of manure when nitrate restrictions are tightened. An important result of the study is the variation in compliance costs and land cover for maize and grass production brought about by spatial variation in groundwater depth. While the effects are negligible for some shallow groundwater classes, it is extremely difficult in other classes – if not impossible – to obtain the EU standard of maximum admissible losses of 34 kg N ha^–1 at low costs. The study shows an important reduction in land cover by maize.     

Principal response curves technique for the analysis of multivariate biomonitoring time series

Although chemical and biological monitoring is often used to evaluate the quality of surface waters for regulatory purposes and/or to evaluate environmental status and trends, the resulting biological and chemical data sets are large and difficult to evaluate. Multivariate techniques have long been used to analyse complex data sets. This paper discusses the methods currently in use and introduces the principal response curves method, which overcomes the problem of cluttered graphical results representation that is a great drawback of most conventional methods. To illustrate this, two example data sets are analysed using two ordination techniques, principal component analysis and principal response curves. Whereas PCA results in a difficult-to-interpret diagram, principal response curves related methods are able to show changes in community composition in a diagram that is easy to read. The principal response curves method is used to show trends over time with an internal reference (overall mean or reference year) or external reference (e.g. preferred water quality or reference site). Advantages and disadvantages of both methods are discussed and illustrated.     

Dielectric properties of MSWI bottom ash for non-invasive monitoring of moisture

The dielectric procperties of MSWI bottom ash as a function of volumetric water content (VWC) are reported in this paper. The objective was to aid the development of microwave based non-invasive emission monitoring and control system for various bottom ash applications. The dielectric measurements were made, on a 1.5-year-old bottom ash, with an electrical network analyzer in microwave range (300 MHz–1.5 GHz). The VWC of the samples ranged between 0.05 and 0.40 m³?m^?3. The relationship between the dielectric permittivity and the VWC was modeled with an empirical model and a physically based Birchak model (BM). The results showed that a linear relationship existed between the permittivity and the VWC at higher water contents (>0.25 m³?m^?3). However, at lower water contents (<0.25 m³?m^?3), the relationship between the permittivity and the WVC was affected by the composition of the bottom ash. The permittivity measurement, with the current method, was not affected by high salt concentrations (10 and 20 dS/m). The empirical model, as compared to BM, provided the best fit between the actual and the predicted water content. The root mean square error (RMSE) values were 0.008–0.010 and 0.06–0.09 m³?m^?3 for the empirical and the Birchak model, respectively.     

Green Toxicology: a strategy for sustainable chemical and material development

Green Toxicology refers to the application of predictive toxicology in the sustainable development and production of new less harmful materials and chemicals, subsequently reducing waste and exposure. Built upon the foundation of “Green Chemistry” and “Green Engineering”, “Green Toxicology” aims to shape future manufacturing processes and safe synthesis of chemicals in terms of environmental and human health impacts. Being an integral part of Green Chemistry, the principles of Green Toxicology amplify the role of health-related aspects for the benefit of consumers and the environment, in addition to being economical for manufacturing companies. Due to the costly development and preparation of new materials and chemicals for market entry, it is no longer practical to ignore the safety and environmental status of new products during product development stages. However, this is only possible if toxicologists and chemists work together early on in the development of materials and chemicals to utilize safe design strategies and innovative in vitro and in silico tools. This paper discusses some of the most relevant aspects, advances and limitations of the emergence of Green Toxicology from the perspective of different industry and research groups. The integration of new testing methods and strategies in product development, testing and regulation stages are presented with examples of the application of in silico, omics and in vitro methods. Other tools for Green Toxicology, including the reduction of animal testing, alternative test methods, and read-across approaches are also discussed.     

The Cost Estimation of Thermal and Catalytic Incinerators for the Control of VOCs

In an earlier paper, major commercially available incinerator technologies designed to treat dilute waste gas streams containing volatile organic compounds (VOCs) were described in a qualitative comparison. In addition, a simplified procedure was outlined through which important sizing parameters could be calculated given certain information about the waste gas. This paper describes the use of these parameters in developing a study (±30percent) cost estimate for the total capital investment and the total annual costs incurred in treating a waste stream of volatile organic compounds (VOCs). An illustrative problem used in the former paper is completed here in order to contrast some of the economic differences between thermal and catalytic incinerator systems.     

Investigation of an Escherichia coli environmental benchmark for waterborne pathogens in agricultural watersheds in Canada

Canada's National Agri-Environmental Standards Initiative sought to develop an environmental benchmark for low-level waterborne pathogen occurrence in agricultural watersheds. A field study collected 902 water samples from 27 sites in four intensive agricultural watersheds across Canada from 2005 to 2007. Four of the sites were selected as reference sites away from livestock and human fecal pollution sources in each watershed. Water samples were analyzed for Campylobacter spp., Salmonella spp., Escherichia coli O157:H7, Cryptosporidium spp., Giardia spp., and the water quality indicator E. coli. The annual mean number of pathogen species was higher at agricultural sites (1.54 ± 0.07 species per water sample) than at reference sites (0.75 ± 0.14 species per water sample). The annual mean concentration of E. coli was also higher at agricultural sites (491 ± 96 colony-forming units [cfu] 100 mL(-1)) than at reference sites (53 ± 18 cfu 100 mL(-1)). The feasibility of adopting existing E. coli water quality guideline values as an environmental benchmark was assessed, but waterborne pathogens were detected at agricultural sites in 80% of water samples with low E. coli concentrations (<100 cfu 100 mL(-1)). Instead, an approach was developed based on using the natural background occurrence of pathogens at reference sites in agricultural watersheds to derive provisional environmental benchmarks for pathogens at agricultural sites. The environmental benchmarks that were derived were found to represent E. coli values lower than geometric mean values typically found in recreational water quality guidelines. Additional research is needed to investigate environmental benchmarks for waterborne pathogens within the context of the "One World, One Health" perspective for protecting human, domestic animal, and wildlife health.     

Copper kinetics and internal distribution in the marbled crayfish (Procambarus sp.)

Metal pollution e.g. copper, in water bodies occurs worldwide. Although copper is an essential trace metal, at certain levels it is still considered as pollutant. The aim of this study was to investigate the effect of exposure concentration on copper bioaccumulation in marbled crayfish (Procambarus sp.) by determining uptake and elimination kinetics. Crayfish were exposed to sub-lethal copper concentrations (average measured concentrations of 0.031 and 0.38 mg Cu L⁻¹) for 14 d and transferred to copper-free water for another 14 d. At different time points during the uptake and elimination phases copper concentrations were measured in five organs (exoskeleton, gills, muscle, ovaries and hepatopancreas). At 0.031 mg Cu L⁻¹, copper levels in the crayfish organs were not significantly increased compared to the control animals, suggesting effective regulation. Exposure to 0.38 mg Cu L⁻¹ did lead to not significantly increased copper levels in muscles and ovaries, while the gills and exoskeleton, which are in direct contact with the water, showed significantly higher copper concentrations. In these four organs, copper showed fast uptake kinetics with equilibrium reached within 10 d of exposure. Copper accumulation was highest in the hepatopancreas; uptake in this storage organ steadily increased with time and did not reach equilibrium within the 14-d exposure period. Copper accumulation levels in the marbled crayfish found in this study were hepatopancreas > gills > exoskeleton > muscle.