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Publications (10 of 156) Show all publications
Öberg, T. (2016). Under strecket: Gruvinspektören som uppfann naturen. Svenska Dagbladet, Kulturdelen (18 oktober), pp. 24-24
Open this publication in new window or tab >>Under strecket: Gruvinspektören som uppfann naturen
2016 (Swedish)In: Svenska Dagbladet, Kulturdelen, no 18 oktober, p. 24-24Article in journal, News item (Other (popular science, discussion, etc.)) Published
National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science
Identifiers
urn:nbn:se:lnu:diva-57431 (URN)
Available from: 2016-10-18 Created: 2016-10-18 Last updated: 2016-11-15Bibliographically approved
Sahlin, U., Jeliazkova, N. & Öberg, T. (2014). Applicability domain dependent predictive uncertainty in QSAR regressions. Molecular Informatics, 33(1), 26-35
Open this publication in new window or tab >>Applicability domain dependent predictive uncertainty in QSAR regressions
2014 (English)In: Molecular Informatics, ISSN 1868-1743, Vol. 33, no 1, p. 26-35Article in journal (Refereed) Published
Abstract [en]

Predictive models used in decision making, such as QSARs in chemical regulation or drug discovery, call for evaluated approaches to quantitatively assess associated uncertainty in predictions. Uncertainty in less reliable predictions may be captured by locally varying predictive errors. In the current study, model-based bootstrapping was combined with analogy reasoning to generate predictive distributions varying in magnitude over a model’s domain of applicability. A resampling experiment based on PLS regressions on four QSAR data sets demonstrated that predictive errors assessed by k nearest neighbour or weighted PRedicted Error Sum of Squares (PRESS) on samples of external test data or by internal cross-validation improved the performance of the uncertainty assessment. Analogy using similarity defined by Euclidean distances, or differences in standard deviation in perturbed predictions, resulted in better performances than similarity defined by distance to, or density of, the training data. Locally assessed predictive distributions had on average at least as good coverage as Gaussian distribution with variance assessed from the PRESS. An R-code is provided that evaluates performances of the suggested algorithms to assess predictive error based on log likelihood scores and empirical coverage graphs, and which applies these to derive confidence intervals or samples from the predictive distributions of query compounds.

National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science
Identifiers
urn:nbn:se:lnu:diva-28032 (URN)10.1002/minf.201200131 (DOI)000346768100004 ()2-s2.0-84895165560 (Scopus ID)
Available from: 2013-08-11 Created: 2013-08-11 Last updated: 2019-11-25Bibliographically approved
Tetko, I. V., Schramm, K.-W., Knepper, T., Peijnenburg, W. J. G., Hendriks, A. J., Navas, J. M., . . . Brandmaier, S. (2014). Experimental and theoretical studies in the EU FP7 Marie Curie Initial Training Network Project, Environmental ChemOinformatics (ECO). ATLA (Alternatives to Laboratory Animals), 42(1), 7-11
Open this publication in new window or tab >>Experimental and theoretical studies in the EU FP7 Marie Curie Initial Training Network Project, Environmental ChemOinformatics (ECO)
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2014 (English)In: ATLA (Alternatives to Laboratory Animals), ISSN 0261-1929, Vol. 42, no 1, p. 7-11Article in journal, Editorial material (Other academic) Published
National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science; Environmental Science, Environmental Chemistry; Chemistry, Organic Chemistry
Identifiers
urn:nbn:se:lnu:diva-34142 (URN)000343746700008 ()24773483 (PubMedID)2-s2.0-84900527606 (Scopus ID)
Funder
EU, FP7, Seventh Framework Programme
Available from: 2014-05-11 Created: 2014-05-11 Last updated: 2019-08-27Bibliographically approved
Filipsson, M., Ljunggren, L. & Öberg, T. (2014). Gender differences in risk management of contaminated land at a Swedish authority. Journal of Risk Research, 17(3), 353-365
Open this publication in new window or tab >>Gender differences in risk management of contaminated land at a Swedish authority
2014 (English)In: Journal of Risk Research, ISSN 1366-9877, E-ISSN 1466-4461, Vol. 17, no 3, p. 353-365Article in journal (Refereed) Published
Abstract [en]

Any risk analysis process leading to the remediation of contaminated land will be affected by individual judgements. Many contaminated land risk assessments in Sweden are reviewed by the County Administrative Board (CAB), a regional government authority. The cost for risk assessments and eventually remediation is funded by whichever operator is legally responsible; however, when the responsible party is unknown, the cost can be met by government grants. A questionnaire was sent to all employees working with contaminated land at each of Sweden’s CABs to investigate whether gender, age and work experience, as well as funding source, affect the reviewing of risk assessments, and the employees’ perception of knowledge gained from the Sustainable Remediation (Hållbar Sanering) research programme. It was found that gender was the most significant factor, but also age and experience of the employees influenced the respondent’s answers. The reviews of risk assessments also varied depending on funding source.

National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science
Identifiers
urn:nbn:se:lnu:diva-25605 (URN)10.1080/13669877.2013.808690 (DOI)000328464300005 ()2-s2.0-84890793980 (Scopus ID)
Available from: 2013-05-12 Created: 2013-05-12 Last updated: 2017-12-06Bibliographically approved
Öberg, T. (2014). Skratta aldrig åt dina egna skämt: Under strecket den 1 maj.. Svenska Dagbladet, Kulturdelen (2014-05-01)
Open this publication in new window or tab >>Skratta aldrig åt dina egna skämt: Under strecket den 1 maj.
2014 (Swedish)In: Svenska Dagbladet, Kulturdelen, no 2014-05-01Article in journal, News item (Other (popular science, discussion, etc.)) Published
National Category
Other Humanities
Identifiers
urn:nbn:se:lnu:diva-34137 (URN)
Available from: 2014-05-10 Created: 2014-05-10 Last updated: 2016-11-15Bibliographically approved
Öberg, T. (2014). Socio-economic analysis in the REACH regulation: Impact assessment to support risk management. In: : . Paper presented at Presentation vid Paris Risk Group 2nd International Meeting, London, 18-19 mars, 2014..
Open this publication in new window or tab >>Socio-economic analysis in the REACH regulation: Impact assessment to support risk management
2014 (English)Conference paper, Oral presentation only (Other academic)
National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science
Identifiers
urn:nbn:se:lnu:diva-33633 (URN)
Conference
Presentation vid Paris Risk Group 2nd International Meeting, London, 18-19 mars, 2014.
Available from: 2014-04-06 Created: 2014-04-06 Last updated: 2016-11-15Bibliographically approved
Öberg, T. (2014). Substitution of chemicals based on assessment of hazard, risk and impact [Letter to the editor]. Journal of Risk Research, 17(5), 565-568
Open this publication in new window or tab >>Substitution of chemicals based on assessment of hazard, risk and impact
2014 (English)In: Journal of Risk Research, ISSN 1366-9877, E-ISSN 1466-4461, Vol. 17, no 5, p. 565-568Article in journal, Letter (Other academic) Published
National Category
Chemical Sciences Environmental Sciences
Research subject
Environmental Science, Environmental Chemistry
Identifiers
urn:nbn:se:lnu:diva-31421 (URN)10.1080/13669877.2013.841737 (DOI)
Available from: 2014-01-10 Created: 2014-01-10 Last updated: 2017-12-06Bibliographically approved
Brandmaier, S., Peijnenburg, W., Durjava, M. K., Kolar, B., Gramatica, P., Papa, E., . . . Tetko, I. V. (2014). The QSPR-THESAURUS: The Online Platform of the CADASTER Project. ATLA (Alternatives to Laboratory Animals), 42(1), 13-24
Open this publication in new window or tab >>The QSPR-THESAURUS: The Online Platform of the CADASTER Project
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2014 (English)In: ATLA (Alternatives to Laboratory Animals), ISSN 0261-1929, Vol. 42, no 1, p. 13-24Article in journal (Refereed) Published
Abstract [en]

The aim of the CADASTER project (CAse Studies on the Development and Application of in Silico Techniques for Environmental Hazard and Risk Assessment) was to exemplify REACH-related hazard assessments for four classes of chemical compound, namely, polybrominated diphenylethers, per and polyfluorinated compounds, (benzo)triazoles, and musks and fragrances. The QSPR-THESAURUS website (http: / /qspr-thesaurus.eu) was established as the project's online platform to upload, store, apply, and also create, models within the project. We overview the main features of the website, such as model upload, experimental design and hazard assessment to support risk assessment, and integration with other web tools, all of which are essential parts of the QSPR-THESAURUS.

National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science; Environmental Science, Environmental Chemistry
Identifiers
urn:nbn:se:lnu:diva-34140 (URN)10.1177/026119291404200104 (DOI)000343746700009 ()24773484 (PubMedID)2-s2.0-84900526209 (Scopus ID)
Available from: 2014-05-11 Created: 2014-05-11 Last updated: 2019-05-27Bibliographically approved
Iqbal, M. S. & Öberg, T. (2013). Description and Propagation of Uncertainty in Input Parameters in Environmental Fate Models. Risk Analysis, 33(7), 1353-66
Open this publication in new window or tab >>Description and Propagation of Uncertainty in Input Parameters in Environmental Fate Models
2013 (English)In: Risk Analysis, ISSN 0272-4332, E-ISSN 1539-6924, Vol. 33, no 7, p. 1353-66Article in journal (Refereed) Published
Abstract [en]

Today, chemical risk and safety assessments rely heavily on the estimation of environmental fate by models. The key compound-related properties in such models describe partitioning and reactivity. Uncertainty in determining these properties can be separated into random and systematic (incompleteness) components, requiring different types of representation. Here, we evaluate two approaches that are suitable to treat also systematic errors, fuzzy arithmetic, and probability bounds analysis. When a best estimate (mode) and a range can be computed for an input parameter, then it is possible to characterize the uncertainty with a triangular fuzzy number (possibility distribution) or a corresponding probability box bound by two uniform distributions. We use a five-compartment Level I fugacity model and reported empirical data from the literature for three well-known environmental pollutants (benzene, pyrene, and DDT) as illustrative cases for this evaluation. Propagation of uncertainty by discrete probability calculus or interval arithmetic can be done at a low computational cost and gives maximum flexibility in applying different approaches. Our evaluation suggests that the difference between fuzzy arithmetic and probability bounds analysis is small, at least for this specific case. The fuzzy arithmetic approach can, however, be regarded as less conservative than probability bounds analysis if the assumption of independence is removed. Both approaches are sensitive to repeated parameters that may inflate the uncertainty estimate. Uncertainty described by probability boxes was therefore also propagated through the model by Monte Carlo simulation to show how this problem can be avoided.

National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science; Environmental Science, Environmental Chemistry
Identifiers
urn:nbn:se:lnu:diva-21826 (URN)10.1111/j.1539-6924.2012.01926.x (DOI)000321439500018 ()2-s2.0-84880136416 (Scopus ID)
Available from: 2012-09-27 Created: 2012-09-27 Last updated: 2017-12-07Bibliographically approved
Iqbal, M. S., Golsteijn, L., Öberg, T., Sahlin, U., Papa, E., Kovarich, S. & Huijbregts, M. A. J. (2013). Understanding quantitative structure-property relationships uncertainty in environmental fate modeling. Environmental Toxicology and Chemistry, 32(5), 1069-1076
Open this publication in new window or tab >>Understanding quantitative structure-property relationships uncertainty in environmental fate modeling
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2013 (English)In: Environmental Toxicology and Chemistry, ISSN 0730-7268, E-ISSN 1552-8618, Vol. 32, no 5, p. 1069-1076Article in journal (Refereed) Published
Abstract [en]

In cases in which experimental data on chemical-specific input parameters are lacking, chemical regulations allow the use of alternatives to testing, such as in silico predictions based on quantitative structure–property relationships (QSPRs). Such predictions are often given as point estimates; however, little is known about the extent to which uncertainties associated with QSPR predictions contribute to uncertainty in fate assessments. In the present study, QSPR-induced uncertainty in overall persistence (POV) and long-range transport potential (LRTP) was studied by integrating QSPRs into probabilistic assessments of five polybrominated diphenyl ethers (PBDEs), using the multimedia fate model Simplebox. The uncertainty analysis considered QSPR predictions of the fate input parameters' melting point, water solubility, vapor pressure, organic carbon–water partition coefficient, hydroxyl radical degradation, biodegradation, and photolytic degradation. Uncertainty in POV and LRTP was dominated by the uncertainty in direct photolysis and the biodegradation half-life in water. However, the QSPRs developed specifically for PBDEs had a relatively low contribution to uncertainty. These findings suggest that the reliability of the ranking of PBDEs on the basis of POV and LRTP can be substantially improved by developing better QSPRs to estimate degradation properties. The present study demonstrates the use of uncertainty and sensitivity analyses in nontesting strategies and highlights the need for guidance when compounds fall outside the applicability domain of a QSPR.

National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science
Identifiers
urn:nbn:se:lnu:diva-23272 (URN)10.1002/etc.2167 (DOI)000317852700013 ()2-s2.0-84876412109 (Scopus ID)
Available from: 2013-01-04 Created: 2013-01-04 Last updated: 2017-12-06Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9382-9296

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