Lateral distribution, environmental occurrence, and assessment of organic pollutants in surface sediments of the East Malaysia

One of the molecular chemical markers used to identify anthropogenic inputs is linear alkylbenzenes (LABs) that cause serious impacts in the bays and coastal ecosystems. The surface sediments samples collected from the East Malaysia, including Brunei bay to estimate the LABs concentration and distri...

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Bibliographic Details
Published in:Environmental monitoring and assessment 2023-06, Vol.195 (6), p.720-720, Article 720
Main Authors: Alkhadher, Sadeq Abdullah Abdo, Suratman, Suhaimi, Zakaria, Mohamad Pauzi
Format: Article
Language:English
Subjects:
Alkylbenzenes
Anthropogenic factors
Atmospheric Protection/Air Quality Control/Air Pollution
Bay water
Bays
Carbon isotopes
Chromatography
Coastal ecosystems
Coastal sediments
Congeners
Contamination
Correlation coefficient
Correlation coefficients
Degradation
Distribution
Earth and Environmental Science
Ecology
Ecosystem
Ecotoxicology
Effluents
Environment
Environmental Management
Environmental Monitoring
Environmental Pollutants
Environmental science
Fractionation
Gas chromatography
Homology
Human influences
Hydrocarbons
Malaysia
Mass spectrometry
Mass spectroscopy
Monitoring/Environmental Analysis
Sediment
Sediment pollution
Sediment samplers
Sediment samples
Sediments
Sewage
Sewage treatment
Variance analysis
Wastewater treatment
Water purification
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Summary:One of the molecular chemical markers used to identify anthropogenic inputs is linear alkylbenzenes (LABs) that cause serious impacts in the bays and coastal ecosystems. The surface sediments samples collected from the East Malaysia, including Brunei bay to estimate the LABs concentration and distribution as molecular markers of anthropogenic indicators. Gas chromatography–mass spectrometry (GC–MS) was used after purification, fractionation the hydrocarbons in the sediment samples to identify the sources of LABs. The analysis of variance (ANOVA) and Pearson correlation coefficient were applied to analyze the difference between sampling stations’ significance at p  
ISSN:0167-6369
1573-2959
DOI:10.1007/s10661-023-11310-w