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Abstract Background Normalization of target gene expression, measured by real-time quantitative PCR (qPCR), is a requirement for reducing experimental bias and thereby improving data quality. The currently used normalization approach is based on using one or more reference genes. Yet, this approach extends the experimental work load and suffers from assumptions that may be difficult to meet and to validate. Results We developed a data driven normalization algorithm (NORMA-Gene). An analysis of the performance of NORMA-Gene compared to reference gene normalization on artificially generated data-sets showed that the NORMA-Gene normalization yielded more precise results under a large range of parameters tested. Furthermore, when tested on three very different real qPCR data-sets NORMA-Gene was shown to be best at reducing variance due to experimental bias in all three data-sets compared to normalization based on the use of reference gene(s). Conclusions Here we present the NORMA-Gene algorithm that is applicable to all biological and biomedical qPCR studies, especially those that are based on a limited number of assayed genes. The method is based on a data-driven normalization and is useful for as little as five target genes comprising the data-set. NORMA-Gene does not require the identification and validation of reference genes allowing researchers to focus their efforts on studying target genes of biological relevance.

The DDT-induced effects, eggshell thinning and breeding failure in Peregrine Falcon (Falco peregrinus) populations were reverted with restrictions on the use of the compound from the 1970s, and in most studied populations, the eggshell thickness is back to normal. In Greenland, a previous study of eggshell thinning in Peregrines found that shells had not yet reached pre-DDT levels. In this study, we extend the time series and reinterpret shell thinning data for 196 clutches covering a 45-year time span (1972–2017). There was a significant (P<0.001) increase in the eggshell thickness of 0.23% per year. This corresponds to a change in eggshell thinning from 14.5% to 5.4% in 2017 compared to the pre-DDT mean. With the current rate of change, pre-DDT shell thickness is predicted to be reached around the year 2034. However, a few clutches are still below the critical limit. The relatively slower recovery of the shell thickness in the Greenland population is likely indicative of the slower phasing out of DDT in the Greenlandic Peregrines' wintering grounds in Latin America. The shell thinning in the Greenlandic population probably never crossed the 17% threshold associated with population declines, contrary to the populations in many other parts of the world. [ABSTRACT FROM AUTHOR]

The mutualistic relationship that the garden ant Lasius niger (L.) establishes with trophobiotic homopterans makes this ant an unwelcome host in commercial crops, as ants improve the survival of homopteran pests from which they collect honeydew as a source of carbohydrates. Because the offering of alternative sugar sources can be used to disrupt this relationship, the present study explored L. niger ’s preference towards sugar and amino acid components that may be used in sugar solutions to increase their attractiveness. We tested the ant’s preference between basic sugars (mono- and disaccharides) used as main ingredients and attractants (trisaccharides and amino acid (AA) sources) added to basic sugar in small amounts. Results showed that ants preferred disaccharides over monosaccharides, and that trisaccharides increased the attractiveness of sucrose solutions, albeit not when a protein source was added to the mix. In the case of AA sources, ants preferred components with a more diverse composition. In conclusion, trisaccharides and AA sources can be used to increase the attractiveness of sugar solutions, leading to the development of solutions that when supplied in artificial feeders can out-compete honeydew and disrupt harmful ant-homopteran mutualisms in agriculture. [ABSTRACT FROM AUTHOR]

In this paper, we develop a method, termed the Interaction Distribution (ID) method, for analysis of quantitative ecological network data. In many cases, quantitative network data sets are under-sampled, i.e. many interactions are poorly sampled or remain unobserved. Hence, the output of statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. The ID method can support assessment and inference of under-sampled ecological network data. In the current paper, we illustrate and discuss the ID method based on the properties of plant-animal pollination data sets of flower visitation frequencies. However, the ID method may be applied to other types of ecological networks. The method can supplement existing network analyses based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1), pi,j: the probability for a visit made by the ith pollinator species to take place on the jth plant species; (2), qi,j: the probability for a visit received by the jth plant species to be made by the ith pollinator. The method applies the Dirichlet distribution to estimate these two probabilities, based on a given empirical data set. The estimated mean values for pi,j and qi,j reflect the relative differences between recorded numbers of visits for different pollinator and plant species, and the estimated uncertainty of pi,j and qi,j decreases with higher numbers of recorded visits. [ABSTRACT FROM AUTHOR]

Background: Normalization of target gene expression, measured by real-time quantitative PCR (qPCR), is a requirement for reducing experimental bias and thereby improving data quality. The currently used normalization approach is based on using one or more reference genes. Yet, this approach extends the experimental work load and suffers from assumptions that may be difficult to meet and to validate. Results: We developed a data driven normalization algorithm (NORMA-Gene). An analysis of the performance of NORMA-Gene compared to reference gene normalization on artificially generated data-sets showed that the NORMA-Gene normalization yielded more precise results under a large range of parameters tested. Furthermore, when tested on three very different real qPCR data-sets NORMA-Gene was shown to be best at reducing variance due to experimental bias in all three data-sets compared to normalization based on the use of reference gene(s). Conclusions: Here we present the NORMA-Gene algorithm that is applicable to all biological and biomedical qPCR studies, especially those that are based on a limited number of assayed genes. The method is based on a datadriven normalization and is useful for as little as five target genes comprising the data-set. NORMA-Gene does not require the identification and validation of reference genes allowing researchers to focus their efforts on studying target genes of biological relevance. [ABSTRACT FROM AUTHOR]

Abstract: This paper illustrates, by a case study, how to apply the conceptual Worst-Case Definition (WCD) model, developed in the methodological paper in the current journal, by Sørensen et al. (2010-this issue). The case is about eco-toxicological risk assessment of pesticides under Danish conditions. Cumulative aspects are included on a conceptual basis as elements of the worst-case conditions. This defines factors that govern the risk assessment, including location in time and space of risk “hotspots”. Two pillars of concern drive the conceptual modelling: (1) What to protect (denoted Protected Units (PUs)) and (2) the reason for increased risk level (denoted Causes of Risks (CRs)). Both PUs and CRs are analysed using hierarchical procedures that facilitate a complete listing of concrete factors governing increased risk for adverse effect due to agricultural usage of pesticide. The factors governing pesticide risk are combined in a context that combines the protection of relevant groupings of organisms with the factors for increased risk level for each of these. Identification of the most important relations between defined types of PUs and CRs is illustrated using expert knowledge. Existing databases are used to form spatial distributed risk indicators as estimators for a selection of important relations between PUs and CRs. This paper illustrates how the WCD model can break down the complex issue of uncertainty into fractions that are more open for evaluations. Finally, it shows application of risk indicators in a multi-criterion analysis using respectively self organizing mapping and partial order technique in a comparative analysis that highlights critical aspects of uncertainty, due to the ambiguity between single risk indicator rankings. [Copyright &y& Elsevier]

Abstract: This paper helps bridge the gap between scientists and other stakeholders in the areas of human and environmental risk management of chemicals and engineered nanomaterials. This connection is needed due to the evolution of stakeholder awareness and scientific progress related to human and environmental health which involves complex methodological demands on risk management. At the same time, the available scientific knowledge is also becoming more scattered across multiple scientific disciplines. Hence, the understanding of potentially risky situations is increasingly multifaceted, which again challenges risk assessors in terms of giving the ‘right’ relative priority to the multitude of contributing risk factors. A critical issue is therefore to develop procedures that can identify and evaluate worst case risk conditions which may be input to risk level predictions. Therefore, this paper suggests a conceptual modelling procedure that is able to define appropriate worst case conditions in complex risk management. The result of the analysis is an assembly of system models, denoted the Worst Case Definition (WCD) model, to set up and evaluate the conditions of multi-dimensional risk identification and risk quantification. The model can help optimize risk assessment planning by initial screening level analyses and guiding quantitative assessment in relation to knowledge needs for better decision support concerning environmental and human health protection or risk reduction. The WCD model facilitates the evaluation of fundamental uncertainty using knowledge mapping principles and techniques in a way that can improve a complete uncertainty analysis. Ultimately, the WCD is applicable for describing risk contributing factors in relation to many different types of risk management problems since it transparently and effectively handles assumptions and definitions and allows the integration of different forms of knowledge, thereby supporting the inclusion of multifaceted risk components in cumulative risk management. [Copyright &y& Elsevier]

Partial order theory and Hasse diagrams appears to be a promising tool for decision-making in environmental issues. Alternatives or objects are said to be partial ordered when it is impossible to find a mutual relationship (< or >) for all criteria. This is often the case in complicated real life situations. However, sometimes it is attractive to apply a total order, i.e. linear rank, and not just the partial order. Based on ranking probabilities and linear extensions it is possible to derive a total order. A linear extension is a projection of the partial order into a total order that comply with all the relations in the partial order. When all linear extensions are known the ranking probabilities can be found as the probability for an object to occupy a specific rank. However, the total number of linear extensions is proportional with the faculty of the number of objects in the partial order. Therefore it is practically impossible to identify all possible linear extensions for partial orders with more than around 20 objects.This study reviews and evaluates a method which estimates the ranking probability based on sampling of a minor random fraction of the linear extensions.Using standard statistics the necessary number of random linear extensions is described as a function of the ranking probability estimate and the restrictions on the confidence interval around the ranking probability. The analysis reveals a smaller systematic uncertainty, which occurs due to the random selection of ranking between two incomparable objects. The discrepancy appears to be dependent on the structure of the partial order.The method using random linear extensions thus appears as a valuable tool for analysing larger partially ordered sets, which are practically impossible to handle using the total set of linear extensions. [Copyright &y& Elsevier]

In this project, we apply the method of partial ordering on the ranking of 74 contaminated sites located in the county of West Zealand (Denmark). The method is based on the concept that the parameters are kept separated through the ranking analysis, and thus no weighing of the different parameter values is necessary. The ranking is displayed in a graphical form by the Hasse diagram technique to ease the interpretation. A critical comparison is made of the ranking of contaminated sites by the partial ordering method and an index function used by the county of West Zealand. Comparing the ranking by the partial ordering method to the index function shows that the choice of score points and index function highly influences the ranking result, as only four sites are equally ranked. The importance of the parameters used to identify the environmental hazard of the contaminated sites is analyzed in order to evaluate the influence of each parameter on the ranking. From among a total of six different parameters, two have high influence, two medium, and two low because of both the construction of the scoring system and the characteristics of the data. [ABSTRACT FROM AUTHOR]

In this investigation, a new and simple way to analyze, interpret, and generalize monitoring data of occurrence of pesticide active ingredients in surface waters was developed. The occurrence is quantified using the variables frequency of detection and the concentration level. These two parameters are associated with basically different ecotoxicological effects; for example, a high frequency of detection may be related to bioaccumulation problems, while the level of concentration also controls the acute toxicological effects. The active ingredients were ranked on the basis of the monitoring data in relation to both the frequency of finding and concentration level using the concept of partial ordered sets. The resulting rankings was correlated with other rankings based on descriptors such as sprayed area, applied dose, adsorption to soil organic carbon, vapor pressure, and soil dissipation half-life. A similarity index was applied in order to compare the ranking of the monitoring data with the ranking of the descriptors. It is shown how partial order theory can be used to evaluate the relevance of every single descriptor. The dosage is found to be the most important descriptor, followed by the sprayed area and the adsorption to organic carbon ending up a very close similarity between, respectively, the rankings using monitoring data and rankings using these three descriptors. [ABSTRACT FROM AUTHOR]

The risk of five different pyrogenic polycyclic aromatic hydrocarbons (PAHs) toward two soil-dwelling organisms (i.e., springtail [Folsomia fimetaria] and earthworm [Eisenia veneta]) has been investigated with respect to lethality and reproduction at two soil depths in a typical Danish soil. Predicted environmental concentrations (PECs) are calculated with a model describing diffusion, bulk flow, and microbial degradation. Predicted no-effect concentrations (PNECs) are derived from laboratory experiments performed with nominal soil concentrations in the range from 0 to 300 µg PAH/g dry weight. Risk is estimated through a stochastic approach as well as with the conventional point estimate. The point estimate predicts a potential risk for pyrene, log PEC/PNEC = -0.01, with respect to springtail reproduction at 5 cm soil depth. In all other scenarios, the point-estimate log-ratios are significantly lower than 0. For the stochastic approach risk is defined when the probability for risk (i.e., the probability for log PEC/PNEC > 0), is larger than 5%. The results show that risk is present only for springtail and in the following five scenarios: For anthracene, the probability for risk with respect to lethality is 12% at 5 cm soil depth, and 17 and 5% with respect to reproduction at 5 and 50 cm soil depth, respectively; for pyrene the probability for risk with respect to reproduction is 49 and 14% at 5 and 50 cm, respectively. The results show that risk cannot be defined unambiguously with the two approaches. The probabilistic approach is less restrictive, and even small probabilities may be used as early-warning indications that risk may be posed under unfavorable circumstances. [ABSTRACT FROM AUTHOR]

Abstract: Conducting environmental risk assessment of engineered nanomaterials has been an extremely challenging endeavor thus far. Moreover, recent findings from the nano-risk scientific community indicate that it is unlikely that many of these challenges will be easily resolved in the near future, especially given the vast variety and complexity of nanomaterials and their applications. As an approach to help optimize environmental risk assessments of nanomaterials, we apply the Worst-Case Definition (WCD) model to identify best estimates for worst-case conditions of environmental risks of two case studies which use engineered nanoparticles, namely nZVI in soil and groundwater remediation and C60 in an engine oil lubricant. Results generated from this analysis may ultimately help prioritize research areas for environmental risk assessments of nZVI and C60 in these applications as well as demonstrate the use of worst-case conditions to optimize future research efforts for other nanomaterials. Through the application of the WCD model, we find that the most probable worst-case conditions for both case studies include i) active uptake mechanisms, ii) accumulation in organisms, iii) ecotoxicological response mechanisms such as reactive oxygen species (ROS) production and cell membrane damage or disruption, iv) surface properties of nZVI and C60, and v) acute exposure tolerance of organisms. Additional estimates of worst-case conditions for C60 also include the physical location of C60 in the environment from surface run-off, cellular exposure routes for heterotrophic organisms, and the presence of light to amplify adverse effects. Based on results of this analysis, we recommend the prioritization of research for the selected applications within the following areas: organism active uptake ability of nZVI and C60 and ecotoxicological response end-points and response mechanisms including ROS production and cell membrane damage, full nanomaterial characterization taking into account detailed information on nanomaterial surface properties, and investigations of dose–response relationships for a variety of organisms. [Copyright &y& Elsevier]

In 1997 a Pollutant Release and Transfer Register (PRTR) pilot project was initiated in Japan. In 1998 the project was expanded and in 1999 a law concerning the establishment of a national PRTR was adopted. Data on the emissions of chemical substances are therefore now being reported on a continuous base. In relation to the PRTR project data on toxicity have been collected. In order to make efficient use of the collected information on emission and toxicity it is useful to group or rank the chemical substances according to the impact on human health and the environment.It has recently been argued that partial order theory (POT) in combination with the use of linear extensions (LE) may be the most objective way to create a linear rank. The methodology has been further expanded to handle larger data sets by the use of random linear extensions (RLE). In this paper the Japanese PRTR data are ranked using the POT/RLE methodology.An average rank is established for chemical substances in the 1998 and 1999 PRTR in Japan. The top 10 chemical substances in the 1998 PRTR are: dichlorvos, inorganic arsenic compounds, cobalt compounds, beryllium compounds, fenitrothion, disulfoton, parathion, diazinon, 4,4′-diamino-3,3′-dichlorodiphenylmethane and antimony compounds. The top 10 chemical substances from the 1999 PRTR are PCBs, lead compounds, fenitrothion, dichlorvos, disulfoton, inorganic arsenic compounds, chlorothalonil, thiobencarb, chromium and HCFC-141b.The descriptor having the highest influence on the ranking of the 1998 PRTR data is the production volume, which, however, is not given in the 1999 PRTR. Further, the disagreement between the ranking with the lack of toxicity data substituted with mean and maximum values, respectively, strongly indicates a general need for further toxicological investigations. [Copyright &y& Elsevier]

Abstract A suite of perfluoroalkyl substances (PFASs) and polychlorinated naphthalenes (PCNs) were determined in 41 peregrine falcon eggs collected in South Greenland between 1986 and 2014. Median concentrations of perfluorinated sulfonic acids (ΣPFSA) and perfluorinated carboxylic acids (ΣPFCA) were 303 ng/g dry weight (dw) (58 ng/g wet weight, ww) and 100 ng/g dw (19 ng/g ww), respectively, which was comparable to other studies. Perfluorooctane sulfonate (PFOS) accounted for 94% on average of all PFSAs, but did not show a significant time trend. Perfluorohexane sulfonate (PFHxS), perfluoroheptane sulfonate (PFHpS) and perfluorodecane sulfonate (PFDS) showed non-linear decreases over the study period, while some long-chain PFCAs increased significantly. The PCN profile was dominated by the penta-, hexa- and tetrachlorinated congeners CN-52/60, CN-66/67 and CN-42. CN-54, an indicator of combustion, accounted for 2.4% of ΣPCN on average. All PCN congeners showed a decreasing tendency, which was significant for lipid-normalized concentrations of CN-53, CN-54 and CN-63. The ΣPCN median concentration was 21 ng/g lipid weight, which is in the high end of concentrations reported for bird eggs. The PCN and PFAS concentrations add to an already high contaminant burden and a complex chemical cocktail in the peregrine falcon population in Greenland, mainly reflecting contaminant exposure during migration and winter stays in Central and South America. Graphical abstract Unlabelled Image Highlights • Peregrine falcons accumulate persistent pollutants through the terrestrial food web. • PFASs and PCNs were found in 41 eggs collected in South Greenland from 1986 to 2014. • Long-chain perfluoroalkyl carboxylic acids increased, while other PFASs decreased. • Perfluorooctane sulfonate (PFOS) accounted for 94% of perfluorinated sulfonic acids. • PCNs decreased, but their concentration was still high compared with other studies. [ABSTRACT FROM AUTHOR]

Abstract: Peregrine falcon eggs were collected in South Greenland between 1986 and 2003 and analysed for 6 congeners of toxaphene and 5 chlordane-related pesticides (cis-chlordane, trans-chlordane, cis-nonachlor, trans-nonachlor and oxychlordane). Oxychlordane had the highest median concentration of 1448ng/g lipid weight (lw) or 79ng/g wet weight (ww) of all compounds. Of the toxaphene congeners, CHB-50 was the predominant congener, with a median concentration of 215ng/g lw (15.5ng/g ww). Chlordane-related concentrations were comparable with results from the USA, but lower than those from Canada and Norway. Toxaphene was considerably higher than in eggs of Norwegian peregrine falcon eggs, possibly reflecting different toxaphene usage in the areas of peregrine falcon migration. Toxaphene information in birds of prey is limited and comparisons with other species indicate differences in concentrations and organochlorine pattern. Temporal trends showed significant log-linear decreases for cis-chlordane and trans-chlordane, but no significant trends for other chlordanes or the toxaphene congeners, probably affected by the large variation between eggs, also of the same bird. Correlations between chlordanes and toxaphene in the Greenland peregrine falcon eggs might suggest similar sources of exposure. [Copyright &y& Elsevier]

Abstract: Chemical warfare agents (CWAs) have been disposed of in various fashions over the past decades. Significant amounts of CWA, roughly 11,000ton, have been dumped in the Baltic Sea east of the island Bornholm following the disarmament of Germany after World War II. This has caused concerns over potential human and environmental health risks, and resulted in restrictions on fishing in the dumpsite area. The purpose of this paper is to assess the potential indirect human health risks due to consumption of CWA-contaminated fish from the dumpsite area east of Bornholm. Earlier studies suggest that the fish community may be at risk from CWA exposure in the Bornholm basin. Moreover, elevated frequencies of lesions on fish caught in a CWA dumpsite in the Mediterranean Sea have been observed. The fish at the Mediterranean dumpsite had elevated total arsenic (As) concentrations in their tissue, and elevated total As levels were also observed in the sediment. Elevated total sediment As concentrations have also been recorded in CWA dumpsites in the Skagerrak and the Baltic Sea. Triphenylarsine and sulfur mustard gas (Yperite) are the CWAs with the greatest indirect human health risk potential. There are recognized uncertainties concerning Yperite''s and CWA-derived arsenical''s fate and speciation in the environment, as well as their inherent toxicity, warranting caution and further site-specific environmental and human health risk assessments of CWAs dumped in the Bornholm basin. [Copyright &y& Elsevier]

Thirty-seven addled peregrine falcon eggs collected in South Greenland between 1986 and 2003 were analysed for their content of the organochlorine compounds polychlorinated biphenyls (PCBs), dichlorodiphenyl tricloroethane (DDT) and its degradation products, hexachlorocyclohexane (HCH) isomers and hexachlorobenzene (HCB). PCBs and DDT (including metabolites) were by far the most abundant OC groups, with median concentrations of 55 and 40 μg/g lw, respectively. The concentrations were high in an Arctic context, but similar to previously reported levels from Alaska and Norway and slightly lower than concentrations measured in eggs from industrialised regions. Geographical differences may be of importance, considering the migration of peregrine falcons and their prey. ΣHCH and HCB had median concentrations of 0.39 and 0.17 μg/g lw, respectively. On average, DDE accounted for 97% of ΣDDT, but was below critical levels for eggshell thinning. All compound groups showed a weak decreasing trend over the study period, which was statistically significant for HCB and close to being significant for ΣHCH. The weak decrease of ΣPCB and ΣDDT is different from other time trend studies from Greenland, usually showing a more pronounced decrease in the beginning of the study period, followed by a certain stabilisation in recent years. [Copyright &y& Elsevier]

Abstract: Chemical warfare agents (CWAs) have been disposed of in various fashions over the past decades. Significant amounts (∼11,000tonnes) have been dumped in the Baltic Sea east of the island Bornholm following the disarmament of Germany after World War II, causing concerns over potential environmental risks. Absence of risk based on assumptions of extremely low solubility of CWAs cannot alone dismiss these concerns. Existing and modelled fate and effects data were used in the analysis to assess the fish community risk level. The most realistic and also conservative assessment result is the scenario describing 70m water depth for the most realistic dump-site area with a focus on chronic toxicity, at 0–20cm above the sediment, yielding a total mixture toxic unit (TU) of 0.62. Triphenylarsine is the CWA with the highest realistic risk profile at 0.2TU for the fish community followed by Adamsite (0.17), Clark I (0.086) and Yperite (0.083) TU. Adamsite is more persistent and constitutes a potential risk for a longer period than triphenylarsine. The seawater volume potentially at risk is <4m above sediment and <58km down current of dump sites. Further risk assessment of dumped CWAs in the Baltic Sea is warranted. [Copyright &y& Elsevier]

Chemical warfare agents (CWAs) have been used and disposed of in various fashions over the past decades. Significant amounts have been dumped in the Baltic Sea following the disarmament of Germany after World War II causing environmental concerns. There is a data gap pertaining to chemical warfare agents, environmental properties not the least their aquatic toxicities. Given this gap and the security limitations relating to working with these agents we applied Quantitative Structure–Activity Relationship ((Q)SAR) models in accordance with the European Technical Guidance Document (2003) to 22 parent CWA compounds and 27 known hydrolysis products. It was concluded that conservative use of EPI Suite (Q)SAR models can generate reliable and conservative estimations of chemical warfare agents acute aquatic toxicity. From an environmental screening point of view the organoarsenic chemical warfare agents Clark I and Adamsite comprise the most problematic of the screened CWA compounds warranting further investigation in relation to a site specific environmental risk assessment. The mustard gas agents (sulphur and nitrogen) and the organophosphorous CWAs (in particular Sarin and Soman) are a secondary category of concern based upon their toxicity alone. The undertaken approach generates reliable and conservative estimations for most of the studied chemicals but with some exceptions (e.g. the organophosphates). [Copyright &y& Elsevier]

Median levels of regulated flame retardants, i.e., polybrominated diphenyl ethers (PBDEs), brominated biphenyl (BB)-153, and hexabromocyclododecane (HBCD), in 33-48 eggs of peregrine falcons (Falco peregrinus) from Greenland were 1909, 359, and 5.98 ng/g lipid weight (lw), respectively, and generally intermediate to levels in North America and Europe. Unregulated flame retardants had lower median concentrations of 1.06 (2-ethylhexyl-2,3,4,5-tetrabromobenzoate, EH-TBB), 2.42 (1,2-bis(2,4,6-tribromophenoxy)-ethane, BTBPE), 0.52 (2,4,6-tribromophenyl 2,3-dibromopropyl ether, DPTE), and 4.78 (dechlorane plus) ng/g lw. Although these compounds are often described as recent replacements for PBDEs, they were also present in eggs from the 1980s. BDE-209 was the only compound with a significant increase (+7.2% annual change) between 1986 and 2014, while BB-153 and DPTE decreased significantly (-8.0% and -2.8% annual change, respectively). Dechlorane plus showed a nonsignificant increase. Individual birds, equipped with light-logging geolocators, confirmed the contaminant exposure over a large geographical area as the birds spent nearly equal time periods in their breeding and wintering grounds in Greenland and Central/South America, respectively, interrupted by 5-6 weeks of migration through North America.

Conducting environmental risk assessment of engineered nanomaterials has been an extremely challenging endeavor thus far. Moreover, recent findings from the nano-risk scientific community indicate that it is unlikely that many of these challenges will be easily resolved in the near future, especially given the vast variety and complexity of nanomaterials and their applications. As an approach to help optimize environmental risk assessments of nanomaterials, we apply the Worst-Case Definition (WCD) model to identify best estimates for worst-case conditions of environmental risks of two case studies which use engineered nanoparticles, namely nZVI in soil and groundwater remediation and C(60) in an engine oil lubricant. Results generated from this analysis may ultimately help prioritize research areas for environmental risk assessments of nZVI and C(60) in these applications as well as demonstrate the use of worst-case conditions to optimize future research efforts for other nanomaterials. Through the application of the WCD model, we find that the most probable worst-case conditions for both case studies include i) active uptake mechanisms, ii) accumulation in organisms, iii) ecotoxicological response mechanisms such as reactive oxygen species (ROS) production and cell membrane damage or disruption, iv) surface properties of nZVI and C(60), and v) acute exposure tolerance of organisms. Additional estimates of worst-case conditions for C(60) also include the physical location of C(60) in the environment from surface run-off, cellular exposure routes for heterotrophic organisms, and the presence of light to amplify adverse effects. Based on results of this analysis, we recommend the prioritization of research for the selected applications within the following areas: organism active uptake ability of nZVI and C(60) and ecotoxicological response end-points and response mechanisms including ROS production and cell membrane damage, full nanomaterial characterization taking into account detailed information on nanomaterial surface properties, and investigations of dose-response relationships for a variety of organisms., (Copyright © 2011 Elsevier B.V. All rights reserved.)

This paper continues the series of publications about applications of partial ordering. The focus of this publication is the derivation of approximate analytical expressions for the averaged rank and the ranking probabilities. To derive such combinatorial formulas a local partial order is suggested as an approximation. The performance of the approximation is rather high; we therefore conclude that three very simple descriptors of the local partial order seem to be sufficient to get a rough impression of the linear order, induced by the averaged ranks and the ranking probabilities of empirical partially ordered sets. Linear order derived from the partial order, ranking probabilities, and other characteristics are considered as parts of a so-called "General Ranking Model" (GRM). Following the local partial order, the averaged rank of an object x can be estimated applying the following simple formula: Rk(av) = (S+1)*(N+1)/(N+1-U). S is the number of successors of the object x, N is the total number of objects (of the quotient set), and U is the number of objects incomparable with x. More complex formulas for the ranking probabilities are given in the text. A list of abbreviations and symbols can be found in Tables 3 and 4.

The application of partial order theory and Hasse diagram technique in environmental science is getting increasing attention. One of the latest developments in the field of Hasse diagram technique is the use of random linear extensions to estimate ranking probabilities. In the original algorithm for estimating the ranking probability it is assumed that the order between two incomparable pair of objects can be chosen randomly. However, if the total set of linear extensions is considered there is a specific probability that one object will be larger than another, which can be far from 50%. In this study it is investigated if an approximation of the mutual ranking probability can improve the algorithm. Applying an approximation of the mutual ranking probability the estimation of the ranking probabilities are significantly improved. Using a test set of 39 partial orders with randomly chosen values the relative mean root square difference (MRSD) decrease in average from 7.9% to 2.2% and a maximum relative improvement of 90% can be found. In the most successful case the relative MRSD goes as low as 0.77%.

Alternately operated wastewater treatment plants (WWTPs) are fundamentally different compared to conventional activated sludge WWTPs with respect to flow patterns and aeration in the biological reactors. Several model applications exist for conventional WWTPs, e.g. SimpleTreat, and in this study the effect of substituting a complex discontinuous operation, involving alternating degradation and flow conditions between two reactors, with one single bioreactor with continuos flow (SimpleTreat) has been investigated by setting up two models representing the respective operation schemes. The discontinuous operation induces fluctuations in the outlet concentrations that are not modelled with the single bioreactor model, however, the fluctuations and the associated uncertainties were found to be insignificant compared to the influence of the input parameter uncertainties on the model results. An empirical relationship between an aggregate pseudo-1st order degradation rate for the single bioreactor model and realistic aerobic and anoxic 1st order degradation rates, respectively, has been established. When using this aggregate degradation rate in the single bioreactor model an outlet concentration can be calculated that deviates no more than 2% from the mean outlet concentration from the alternating operation model. For substances with aerobic half-lives longer than approximately 2 h, which is valid for many chemical substances, the aggregate 1st order degradation rate can be set equal to the aerobic 1st order degradation rate.

The combined monitoring-based and modelling-based priority setting scheme (COMMPS) used to establish a priority setting list within the EU Water Framework Directive plays a major role in the European environmental policy on chemical substances. The COMMPS procedure can be classified as a so-called scoring method. The applied functional relationship and weight factors are established based on expert judgement, which unfortunately appears to be vulnerable to subjective inputs. In this study an alternative priority setting methods based on partial order theory (POT) and random linear extensions (RLE) is suggested and compared to the COMMPS procedure. The POT/RLE is characterised as being based on fewer assumptions concerning functional relationships and does not apply weighting factors. Using the POT/RLE methodology a different ranking result occur than when using the COMMPS procedure. Eight of the top 20 substances from the COMMPS procedure are not ranked within the top 20 when using POT/RLE. From the viewpoint of environmental protection, especially the substances that have been given low priority in the COMMPS procedure, but a high rank in POT/RLE, are of interest in a regulatory context. These substances are naphthalene, trichloromethane, isoproturon, metolachlor, endosulfan, acenaphthene, alachlor and dichloromethane. An analysis of the ability of the descriptors to separate the single substance discloses that the most significant descriptor is the concentrations detected in the environment. Further, the frequency of detection is not applied as a descriptor in the COMMPS procedure. However, if this descriptor was to be applied the analysis revealed that it would have been the third most significant descriptor.

Partial order theory (POT) is an attractive and operationally simple method that allows ordering of compounds, based on selected structural and/or electronic descriptors (modeled order), or based on their end points, e.g., solubility (experimental order). If the modeled order resembles the experimental order, compounds that are not experimentally investigated can be assigned a position in the model that eventually might lead to a prediction of an end-point value. However, in the application of POT in quantitative structure-activity relationship modeling, only the compounds directly comparable to the noninvestigated compounds are applied. To explore the possibilities of improving the methodology, the theory is extended by application of the so-called linear extensions of the model order. The study show that partial ordering combined with linear extensions appears as a promising tool providing probability distribution curves in the range of possible end-point values for compounds not being experimentally investigated.