PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 15212267

Integrated methodology for forensic oil spill identification.

Jan H Christensen·Asger B Hansen·Giorgio Tomasi·John Mortensen·Ole Andersen
View original source ↗Export metadata ↓

Abstract

A new integrated methodology for forensic oil spill identification is presented. It consists of GC-MS analysis, chromatographic data processing, variable-outlier detection, multivariate data analysis, estimation of uncertainties, and statistical evaluation. The methodology was tested on four groups of diagnostic ratios composed of petroleum biomarkers and ratios within homologous PAH categories. Principal component analysis (PCA) was employed and enabled the simultaneous analysis of many diagnostic ratios. Weathering was taken into account by considering the sampling uncertainties estimated from replicate spill samples. Statistical evaluation ensured an objective matching of oil spill samples with suspected source oils as well as classification into positive match, probable match, and nonmatch. The data analysis is further refined if two or more source oils are classified as probable match by using weighted least squares fitting of the principal components, local PCA models, and additional information relevant to the spill case. The methodology correctly identified the source of two spill samples (i.e., crude oils from Oseberg East and Oseberg Field Centre) and distinguished them from closely related source oils.

Explore related subjects

DenmarkForensic SciencesFresh WaterGas Chromatography-Mass SpectrometryMultivariate AnalysisPetroleumPrincipal Component AnalysisSeawaterSoftware DesignWater Pollutants, ChemicalJournal ArticleResearch Support, Non-U.S. Gov't

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jan H Christensen, Asger B Hansen, Giorgio Tomasi, John Mortensen, Ole Andersen. 2004-05-15. Integrated methodology for forensic oil spill identification.. https://doi.org/10.1021/es035261y

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

Emerging trends in invasive Streptococcus dysgalactiae subsp. equisimilis infections in Denmark, 2014 to 2024: a nationwide genomic and registry-based study.

BACKGROUNDIncreasing incidence rates of invasive Streptococcus dysgalactiae subspecies equisimilis (iSDSE) have been detected worldwide.AIMWe aimed to investigate iSDSE infection incidence rates in Denmark during 2014-2024, and characterise the genomic population structure of a subset of iSDSE isolates and their antimicrobial resistance (AMR).METHODSUsing national register data, we estimated overall and sex-/age-stratified iSDSE incidences during 2014-2024, by retrospectively identifying cases of invasive infections with group C and G streptococci or S. dysgalactiae (including specified as subspecies equisimilis). From the voluntary national beta-haemolytic streptococci laboratory surveillance system, whole-genome-sequenced isolates from August 2020-September 2022 were used to investigate the iSDSE genomic population structure. Susceptibility to penicillin, erythromycin and clindamycin was determined and AMR genes identified.RESULTSDuring 2014-2024, iSDSE incidence rates increased significantly (linear trend analysis p&#x2009;<&#x2009;0.001) with mean annual incidence ranging between 10.3 and 16.4 per 100,000, peaking in 2023. Incidence was higher in males, increasing with older age. Nearly 75% of the&#x2009;1,223 iSDSE isolates belonged to four of 14 genetic clusters. Sequence types (STs) ST20 and ST17 were most prevalent, while emm-type stG62647, a variant associated internationally with higher virulence, dominated. All isolates were phenotypically susceptible to penicillin but approximately 10% were respectively erythromycin and clindamycin resistant. High erythromycin resistance prevalence (57%;&#x2009;39/68), coinciding with gene ermA, occurred in one genetic cluster.CONCLUSIONThe findings illustrate the need for national registry-based surveillance to detect epidemiological changes and potential outbreaks. Further, continuous genomic surveillance can monitor the occurrence and expansion of genetic clades and AMR genes.

Denmark↗
PubMed2007

[Primary ovarian cancer. A comparison of registrations in the Danish Cancer Registry and the Pathology Data Bank].

INTRODUCTION: Ovarian cancer (OC) registrations in the Danish Cancer Registry (CR) and the Danish Pathology Data Bank (PDB) 1978-99 were compared in order to assess the possibility of identifying OC cases from another data source than the CR. MATERIAL AND METHODS: A total of 13,320 OC were identified in the CR/PDB and comparisons of the registrations were performed. RESULTS: The frequency of cases registered in both registries increased during 1978-99. Agreement in registration of histological subtypes in the two registries was found in 82% of the cases. Diagnosis among the rest was most often consistent; however, a more specific diagnosis was often found in one or the other registry. The frequency of women only registered with OC in the CR decreased from 81% to 35%, as the number of women with no diagnoses at all in the PDB declined from 1978 to 1997, whereafter it stabilised, primarily because all pathology departments now reported data to the PDB. In 1997-99, 29% of OC registered in the CR with a histologically verified OC diagnosis was still not registered with cancer in the ovaries in the PDB. Most of these, however, could be identified in the PDB with diagnoses consistent with metastases from OC. In total, 749 OC were not registered in the CR, though explanations for their missing registrations could be found in most cases. CONCLUSION: Data from the PDB may not be useful in complete identification of ovarian cancer cases for research purposes. However, it is a good supplement to data from the CR.

Denmark↗