Statistical analysis of a large set of semi-quantitative GC-MS screening data to evaluate and prioritize organic contaminants in surface and drinking water of the Netherlands.

Due to anthropogenic activities in the catchments, surface waters are contaminated with a large variety of chemical compounds. Drinking water companies in the Netherlands use surface water from the rivers Rhine, and Meuse, Lake IJssel and water from a reclaimed land area as sources for the production of drinking water. Samples from the abstraction points and the produced drinking waters were investigated using chemical screening with gas chromatography coupled to mass spectrometry to detect an as wide as possible range of organic contaminants, generating enormous data sets. This study aimed to evaluate and interpret five and a half years of screening data to get insight in the variety of known and new less polar compounds in surface and drinking waters, and to investigate if there were spatial patterns in the detection of compounds. Compounds from a wide variety of applications were detected. The vast majority of detected compounds was found only in a few samples. Certain compounds, however, e.g. organophosphate flame retardants, were detected with prevalences up to 100% per location. Most compounds were detected in samples from the rivers Rhine and Meuse, less in those from Lake IJssel and the reclaimed land area and only few in drinking water. Principal component and Hierarchical Cluster Analyses helped to detect patterns in the presence of contaminants on particular locations and to prioritize compounds for further investigation of their emission sources, and -in case of unknown compounds - their identification.

Probability of detecting and quantifying faecal contaminations of drinking water by periodically sampling for E. coli: a simulation model study.

Drinking water supply companies monitor the presence of Escherichia coli in drinking water to verify the effectiveness of measures that prevent faecal contamination of drinking water. Data are lacking, however, on the sensitivity of the monitoring programmes, as designed under the EU Drinking Water Directive. In this study, the sensitivity of such a monitoring programme was evaluated by hydraulic model simulations of contamination events and calculations of the detection probability of the actual sampling programme of 2002. In the hydraulic model simulations of 16-h periods of 1l h(-1) ingress of untreated domestic sewage, the spread of the contamination through the network and the E. coli concentration dynamics were calculated. The results show that when large parts of the sewage reach reservoirs, e.g. when they originate from the treatment plant or a trunk main, mean detection probabilities are 55-65%. When the contamination does not reach any of the reservoirs, however, the detection probability varies from 0% (when no sampling site is reached) to 13% (when multiple sites are reached). Mean detection probabilities of nine simulated ingress incidents in mains are 5.5% with an SD of 6.5%. In reality, these detection probabilities are probably lower as the study assumed no inactivation or clustering of E. coli, 100% recovery efficiency of the E. coli detection methods and immediate mixing of contaminations in mains and reservoirs. The described method provides a starting point for automated evaluations and optimisations of sampling programmes.

OSPAR standard method and software for statistical analysis of beach litter data.

The aim of this study is to develop standard statistical methods and software for the analysis of beach litter data. The optimal ensemble of statistical methods comprises the Mann-Kendall trend test, the Theil-Sen slope estimation, the Wilcoxon step trend test and basic descriptive statistics. The application of Litter Analyst, a tailor-made software for analysing the results of beach litter surveys, to OSPAR beach litter data from seven beaches bordering on the south-eastern North Sea, revealed 23 significant trends in the abundances of beach litter types for the period 2009-2014. Litter Analyst revealed a large variation in the abundance of litter types between beaches. To reduce the effects of spatial variation, trend analysis of beach litter data can most effectively be performed at the beach or national level. Spatial aggregation of beach litter data within a region is possible, but resulted in a considerable reduction in the number of significant trends.

Development of a 4-NQO toxic equivalency factor (TEF) approach to enable a preliminary risk assessment of unknown genotoxic compounds detected by the Ames II test in UV/H2O2 water treatment samples.

An approach to enable a preliminary risk assessment of unknown genotoxic compounds formed by MP UV/H2O2 treatment of nitrate rich water, is described. Since the identity and concentration of specific genotoxic compounds is not established yet, a compound specific risk assessment cannot be performed. This limitation is circumvented by introducing a toxic equivalency factor, converting the concentration of unknown genotoxic compounds expressed by an Ames II test response into equivalent concentrations of 4-nitroquinoline oxide (4-NQO), to enable a preliminary risk assessment. Based on the obtained 4-NQO equivalent concentrations for the tested water samples and 4-NQO carcinogenicity data, an indication of the associated risk of the by MP UV/H2O2 treatment produced nitrated genotoxic compounds is obtained via the margin of exposure (MOE) approach. Based on a carcinogen study by Tang et al. (2004), a body weight of 70 kg and a drinking water consumption of 2 L per day, the 4-NQO equivalent concentration should not exceed 80 ng/L associated with a negligible risk. Application of this approach on samples from MP UV/H2O2 treated water of a full scale drinking water production facility, a 4-NQO equivalent concentration of 107 ng/L was established. These results indicate a safety concern in case this water would be distributed as drinking water without further post treatment.