Displaying all 7 publications

  1. Juahir H, Ismail A, Mohamed SB, Toriman ME, Kassim AM, Zain SM, et al.
    Mar Pollut Bull, 2017 Jul 15;120(1-2):322-332.
    PMID: 28535957 DOI: 10.1016/j.marpolbul.2017.04.032
    This study involves the use of quality engineering in oil spill classification based on oil spill fingerprinting from GC-FID and GC-MS employing the six-sigma approach. The oil spills are recovered from various water areas of Peninsular Malaysia and Sabah (East Malaysia). The study approach used six sigma methodologies that effectively serve as the problem solving in oil classification extracted from the complex mixtures of oil spilled dataset. The analysis of six sigma link with the quality engineering improved the organizational performance to achieve its objectivity of the environmental forensics. The study reveals that oil spills are discriminated into four groups' viz. diesel, hydrocarbon fuel oil (HFO), mixture oil lubricant and fuel oil (MOLFO) and waste oil (WO) according to the similarity of the intrinsic chemical properties. Through the validation, it confirmed that four discriminant component, diesel, hydrocarbon fuel oil (HFO), mixture oil lubricant and fuel oil (MOLFO) and waste oil (WO) dominate the oil types with a total variance of 99.51% with ANOVA giving Fstat>Fcritical at 95% confidence level and a Chi Square goodness test of 74.87. Results obtained from this study reveals that by employing six-sigma approach in a data-driven problem such as in the case of oil spill classification, good decision making can be expedited.
    Matched MeSH terms: Petroleum Pollution/analysis*
  2. Vaezzadeh V, Zakaria MP, Bong CW
    Mar Pollut Bull, 2017 Nov 15;124(1):33-42.
    PMID: 28693809 DOI: 10.1016/j.marpolbul.2017.07.008
    The Straits of Malacca is one of the world's busiest shipping routes where frequent oil spills occur. Rapid development in the west coast of Peninsular Malaysia is the other major source of petroleum pollution in this narrow waterway. In order to identify occurrence and origin of hydrocarbons in the Straits, mangrove oysters (Crassostrea belcheri) were collected from five sampling locations and analysed for n-alkanes and biomarkers. Soxhlet apparatus and two step column chromatography were used for extraction, purification and fractionation of the oysters. Petroleum origin n-alkanes were detected in majority of the sampling locations which is indicative of anthropogenic activities in this region. Using source and maturity diagnostic ratios for hopanes revealed used crankcase oil as the main source of petroleum hydrocarbons in oysters from all sampling locations except for the Pulau Merambong where signature of South East Asia crude oil (SEACO) was detected.
    Matched MeSH terms: Petroleum Pollution/analysis*
  3. Marghany M
    Mar Pollut Bull, 2014 Dec 15;89(1-2):20-29.
    PMID: 25455367 DOI: 10.1016/j.marpolbul.2014.10.041
    In this work, a genetic algorithm is applied for the automatic detection of oil spills. The procedure is implemented using sequences from RADARSAT-2 SAR ScanSAR Narrow single-beam data acquired in the Gulf of Mexico. The study demonstrates that the implementation of crossover allows for the generation of an accurate oil spill pattern. This conclusion is confirmed by the receiver-operating characteristic (ROC) curve. The ROC curve indicates that the existence of oil slick footprints can be identified using the area between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills, and the ScanSAR Narrow single-beam mode serves as an excellent sensor for oil spill detection and survey.
    Matched MeSH terms: Petroleum Pollution/analysis*
  4. Abdullah MZ, Saat AB, Hamzah ZB
    Environ Monit Assess, 2012 Jun;184(6):3959-69.
    PMID: 21822578 DOI: 10.1007/s10661-011-2236-y
    Biomonitoring of multi-element atmospheric deposition using terrestrial moss is a well-established technique in Europe. Although the technique is widely known, there were very limited records of using this technique to study atmospheric air pollution in Malaysia. In this present study, the deposition of 11 trace metals surrounding the main petroleum refinery plant in Kerteh Terengganu (eastern part of peninsular Malaysia) has been evaluated using two local moss species, namely Hypnum plumaeforme and Taxithelium instratum as bioindicators. The study was also done by means of observing whether these metals are attributed to work related to oil exploration in this area. The moss samples have been collected at 30 sampling stations in the vicinity of the petrochemical industrial area covering up to 15 km to the south, north, and west in radius. The contents of heavy metal in moss samples were analyzed by energy dispersive x-ray fluorescence technique. Distribution of heavy metal content in all mosses is portrayed using Surfer software. Areas of the highest level of contaminations are highlighted. The results obtained using the principal components analysis revealed that the elements can be grouped into three different components that indirectly reflected three different sources namely anthropogenic factor, vegetation factor, and natural sources (soil dust or substrate) factor. Heavy metals deposited mostly in the distance after 9 km onward to the western part (the average direction of wind blow). V, Cr, Cu, and Hg are believed to have originated from local petrochemical-based industries operated around petroleum industrial area.
    Matched MeSH terms: Petroleum Pollution/analysis*
  5. Ismail A, Toriman ME, Juahir H, Kassim AM, Zain SM, Ahmad WKW, et al.
    Mar Pollut Bull, 2016 Oct 15;111(1-2):339-346.
    PMID: 27397593 DOI: 10.1016/j.marpolbul.2016.06.089
    Extended use of GC-FID and GC-MS in oil spill fingerprinting and matching is significantly important for oil classification from the oil spill sources collected from various areas of Peninsular Malaysia and Sabah (East Malaysia). Oil spill fingerprinting from GC-FID and GC-MS coupled with chemometric techniques (discriminant analysis and principal component analysis) is used as a diagnostic tool to classify the types of oil polluting the water. Clustering and discrimination of oil spill compounds in the water from the actual site of oil spill events are divided into four groups viz. diesel, Heavy Fuel Oil (HFO), Mixture Oil containing Light Fuel Oil (MOLFO) and Waste Oil (WO) according to the similarity of their intrinsic chemical properties. Principal component analysis (PCA) demonstrates that diesel, HFO, MOLFO and WO are types of oil or oil products from complex oil mixtures with a total variance of 85.34% and are identified with various anthropogenic activities related to either intentional releasing of oil or accidental discharge of oil into the environment. Our results show that the use of chemometric techniques is significant in providing independent validation for classifying the types of spilled oil in the investigation of oil spill pollution in Malaysia. This, in consequence would result in cost and time saving in identification of the oil spill sources.
    Matched MeSH terms: Petroleum Pollution/analysis*
  6. Masood N, Halimoon N, Aris AZ, Zakaria MP, Vaezzadeh V, Magam SM, et al.
    Environ Geochem Health, 2018 Dec;40(6):2551-2572.
    PMID: 29802607 DOI: 10.1007/s10653-018-0122-z
    Rapid increase in industrialization and urbanization in the west coast of Peninsular Malaysia has led to the intense release of petroleum and products of petroleum into the environment. Surface sediment samples were collected from the Selangor River in the west coast of Peninsular Malaysia during four climatic seasons and analyzed for PAHs and biomarkers (hopanes). Sediments were soxhlet extracted and further purified and fractionated through first and second step column chromatography. A gas chromatography-mass spectrometry (GC-MS) was used for analysis of PAHs and hopanes fractions. The average concentrations of total PAHs ranged from 219.7 to 672.3 ng g-1 dw. The highest concentrations of PAHs were detected at 964.7 ng g-1 dw in station S5 in the mouth of the Selangor River during the wet inter-monsoonal season. Both pyrogenic and petrogenic PAHs were detected in the sediments with a predominance of the former. The composition of hopanes was homogeneous showing that petroleum hydrocarbons share an identical source in the study area. Diagnostic ratios of hopanes indicated that some of the sediment samples carry the crankcase oil signature.
    Matched MeSH terms: Petroleum Pollution/analysis*
  7. Baharuddin SH, Mustahil NA, Reddy AVB, Abdullah AA, Mutalib MIA, Moniruzzaman M
    Chemosphere, 2020 Jun;249:126125.
    PMID: 32058133 DOI: 10.1016/j.chemosphere.2020.126125
    The application of chemical dispersants in marine oil spill remediation is comprehensively reported across the globe. But, the augmented toxicity and poor biodegradability of reported chemical dispersants have created necessity for their replacement with the bio-based green dispersants. Therefore, in the present study, we have synthesized five ionic liquids (ILs) namely 1-butyl-3-methylimidazolium lauroylsarcosinate, 1,1'-(1,4-butanediyl)bis(1-H-pyrrolidinium) dodecylbenzenesulfonate, tetrabutylammonium citrate, tetrabutylammonium polyphosphate and tetrabutylammonium ethoxylate oleyl ether glycolate, and formulated a water based ILs dispersant combining the synthesized ILs at specified compositions. The effectiveness of formulated ILs dispersant was found between 70.75% and 94.71% for the dispersion of various crude oils ranging from light to heavy. Further, the acute toxicity tests against zebra fish and grouper fish have revealed the practically non-toxic behaviour of formulated ILs dispersant with LC50 value greater than 100 ppm after 96 h. In addition, the formulated ILs dispersant has provided excellent biodegradability throughout the test period. Overall, the formulated new ILs dispersant is deemed to facilitate environmentally benign oil spill remediation and could effectively substitute the use of hazardous chemical dispersants in immediate future.
    Matched MeSH terms: Petroleum Pollution/analysis*
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