Biomedical subjects

Lars Carlsen

Publications and source records attributed to Lars Carlsen.

12 recordsLinked to original sources

PubMed2004

Ranking of chemical substances based on the Japanese Pollutant Release and Transfer Register using partial order theory and random linear extensions.

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.

Data Interpretation, Statistical↗

PubMed2003

Phthalates, nonylphenols and LAS in an alternately operated wastewater treatment plant--fate modelling based on measured concentrations in wastewater and sludge.

The performance of an alternately operated activated sludge wastewater treatment plant (WWTP) has been investigated with respect to six phthalates, nonylphenol (NP) and nonylphenol diethoxylate (NPDE) and linear alkylbenzene sulphonates (LAS). Samples of raw sewage, primary and secondary sludge and treated water were collected during an 8-day period in May 1999 and analysed for dissolved and sorbed substances. To evaluate the system performance with respect to substance removal through biodegradation and sorption to sludge the measured data were applied in a model describing the different bioreactors as one single reactor, corresponding to the concepts of, e.g. SimpleTreat. The most abundant of the investigated phthalates was di-(2-ethylhexyl)-phthalate (DEHP) with a measured mean inlet flow of 240g/day. Two percent of this amount was found in the treated water, 70% was biodegraded and 28% was found in the sludge. For LAS the mean inlet flow was 20,300g/day, of which less than 1% was found in the treated water, 84% was biodegraded and 15% was found in the sludge. The mean inlet flow of NP and NPDE was 44 and 590g/day, of which 4% and 2% was found in the treated water, 80% was biodegraded for both substances, and 16% and 18% was found in the sludge, respectively. The WWTP removal of the investigated substances was thus high compared to other studies of conventional activated sludge WWTPs. The simple model set-up presents a strong tool for predicting substance removal and system sensitivity related to changes in the inlet conditions, such as concentrations and flow. Furthermore, it allows the inclusion of complex alternately operated WWTPs in risk assessment tools such as e.g. SimpleTreat.

Alkanesulfonic Acids↗

PubMed2003

Model description of an alternately operated wastewater treatment plant--evaluation of the applicability of SimpleTreat.

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.

Bioreactors↗

PubMed2003

Analysis of monitoring data of pesticide residues in surface waters using partial order ranking theory.

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.

Data Interpretation, Statistical↗

PubMed2002

Phthalates and nonylphenols in profiles of differently dressed soils.

The concentrations of nonylphenols and phthalates in depth profiles of eight differently dressed, fertilised and cultured fields were investigated. The fields were typical for Danish agriculture and comprised an uncultured location, two manured fields, an artificially fertilised field and three fields amended with different amounts of sewage sludge. In addition, a location receiving run-off from a sewage sludge storage facility were investigated. At each location, two 50 cm vertical soil cores were taken, divided into sections of 10 cm each and analysed for nonylphenols and phthalates by high-resolution mass spectrometry. Di-(2-ethylhexyl)-phthalate (DEHP) was the most abundant phthalate in all samples whereas Di-(n-butyl)-phthalate (DBP) played a minor role. Nonylphenols occurred in significant concentrations only in soil samples exposed to high amounts of sludge and at the run-off location. A close relationship was found between the concentrations of contaminants in the soil samples and the method of dressing. The concentrations were low at comparable levels in the soil samples from the artificially fertilised field and in the fields amended with low amounts of sludge, as well as in the manured fields. Remarkably, these concentrations did not differ significantly from the level in an uncultured recreational preserved area, which was used as a reference. In contrast, much higher levels of contaminants were found in the soil samples from fields exposed to high amounts of sludge. We must conclude that sludge amendment below a certain limit does not lead to elevated levels of nonylphenols and phthalates in the soils, whereas heavy sludge amendment leads to the accumulation of these contaminants. For the vertical distribution of substances in the soils, an influence of soil characteristics on the concentration profile was noted. Thus, in soils with visible clay in the upper layers, a DEHP maximum occurred at a depth of 10-20 cm, whereas in most sandy soils no such maximum was observed. A 2-year time trend study of the highly sludge amended soil showed no measurable reduction in the substances during this period. The time study further suggested a downward movement of the DEHP maximum of approximately 10 cm per year.

Agriculture↗

PubMed2002

Linear alkylbenzene sulfonates (LAS) in the terrestrial environment.

The occurrence of linear alkylbenzene sulfonates (LAS) in a series of soil samples originating from the municipality of Roskilde has been studied. The study includes soil samples from eight different locations with different histories: a preserved natural area that has not been cultured for 50-100 years, a soil that has been ecologically cultured for 40 years, a soil sustainably manured in ecologically culture for 5 years (formerly conventionally cultured) and a soil that has been conventionally cultured using artificial fertilizer. In addition, a soil was studied that had been sludge amended by applying medium amounts of sludge as well as a soil that has been amended with high amounts of sludge for a 25-year period. In the latter case, the sludge amendment was abandoned 6 years before the first sampling, followed by the application of artificial fertilizers. Finally, a meadow in the run-off zone from a sludge storage area was included in the investigations. In addition to the soil samples, selected samples of the applied sludge and other fertilizers were analyzed for their possible content of LAS. Apart from the location where the soil had been heavily sludge-amended and the location situated in the run-off zone of the sludge storage, concentrations of LAS in all soil samples were found to be below approximately 1 mg/kg, which is well below the proposed preliminary soil quality criteria for LAS of 5 mg/kg. On the other hand, the study unambiguously disclosed that in the case of heavy sludge amendment, the proposed soil quality criteria might well be exceeded.

Alkanesulfonic Acids↗

PubMed2002

Characterisation of humic materials of different origin: a multivariate approach for quantifying the latent properties of dissolved organic matter.

The inherent chemical properties of eight different dissolved organic matters (DOMs) originating from soil, surface and groundwater have been analysed. The samples consist of isolated fulvic acids (FA), humic acids (HA), and humic substances (HS), i.e. natural mixtures containing a humic and a fulvic fraction. The humic substances have been characterised by elemental analysis, size exclusion chromatography, E2/E3 and E4/E6 UV absorption ratios, and liquid-state 13C-NMR spectroscopy. The information contents of the different analytical methods have been investigated by pattern recognition, i.e. cluster analysis and principal component analysis (PCA). A comparative study of the information contents of DOM descriptors derived from different analytical methods is presented. Through extraction of information content of the individual analytical methods the inherent properties of DOM are quantified. Pattern recognition revealed significant quantitative differences in the inherent properties of DOM of different origin and type. PCA based on the NMR descriptors showed highest explained variance. However, all models showed low robustness due to the limited number of samples. The supervised pattern recognition, i.e. PCA, indicates a classification of DOMs into groups of similar properties by an increase in the number of samples. Furthermore that the number of groups may be higher and more continuously distributed than the conventional classification into fulvic acids, humic acids or humic substances.

Chromatography, Gel↗

PubMed2002

Comparison of the combined monitoring-based and modelling-based priority setting scheme with partial order theory and random linear extensions for ranking of chemical substances.

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.

Algorithms↗

PubMed2002

Reverse quantitative structure-activity relationship for modelling the sorption of esfenvalerate to dissolved organic matter. A multivariate approach.

The sorption of the pyrethroid, esfenvalerate, to the dissolved and/or dispersed fraction of eight different natural humic compounds has been investigated. The dissolved organic matters (DOMs) included in this study originate from ground water, soil pore water, and surface waters. Sorption was modelled at DOM concentration levels where equilibrium partitioning of esfenvalerate between DOM and the aqueous bulk phase prevails. The inherent characteristics of the eight different humic materials, quantified in the preceding paper by Thomsen et al. (2002, this issue (PII: S0045-6535(02)00335-1)), have been used as explanatory variables for modelling this equilibrium partitioning. Using a reverse QSAR approach based on by projection-into-latent-structure regression (PLS-R) inherent sorbent properties determining for the sorption affinity of esfenvalerate to DOM were analysed. For all humic substances a decrease in the DOM-normalised equilibrium-partitioning coefficient, K(DOM), with increasing concentration of DOM was observed. Significant variations in K(DOM) values, as function of the inherent characteristics of the individual humic substances, were found at DOM concentrations of 75 and 100 ppm, respectively. The latter is a strong indication of variations in sorption mechanisms of esfenvalerate to DOM of varying inherent properties. Groupings in the principal property space quantifying DOMs may indicate that separate models are needed for quantifying the equilibrium partitioning to different classes of DOM.

Adsorption↗

PubMedDate not supplied

A comparison of partial order technique with three methods of multi-criteria analysis for ranking of chemical substances.

An alternative to the often cumbersome and time-consuming risk assessments of chemical substances could be more reliable and advanced priority setting methods. An elaboration of the simple scoring methods is provided by Hasse Diagram Technique (HDT) and/or Multi-Criteria Analysis (MCA). The present study provides an in depth evaluation of HDT relative to three MCA techniques. The new and main methodological step in the comparison is the use of probability concepts based on mathematical tools such as linear extensions of partially ordered sets and Monte Carlo simulations. A data set consisting of 12 High Production Volume Chemicals (HPVCs) is used for illustration. It is a paradigm in this investigation to claim that the need of external input (often subjective weightings of criteria) should be minimized and that the transparency should be maximized in any multicriteria prioritisation. The study illustrates that the Hasse diagram technique (HDT) needs least external input, is most transparent and is least subjective. However, HDT has some weaknesses if there are criteria which exclude each other. Then weighting is needed. Multi-Criteria Analysis (i.e. Utility Function approach, PROMETHEE and concordance analysis) can deal with such mutual exclusions because their formalisms to quantify preferences allow participation e.g. weighting of criteria. Consequently MCA include more subjectivity and loose transparency. The recommendation which arises from this study is that the first step in decision making is to run HDT and as the second step possibly is to run one of the MCA algorithms.

Chemical Industry↗

PubMedDate not supplied

Improving the predicting power of partial order based QSARs through linear extensions.

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.

Computer Simulation↗

PubMedDate not supplied

Estimation of averaged ranks by a local partial order model.

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.

Journal Article↗