Air pollution is becoming a major environmental issue in Malaysia. This study focused on the identification of potential sources of variations in air quality around the study area based on the data obtained from the Malaysian Department of Environment (DOE).  Eight air quality parameters in ten monitoring stations for seven years (2006 – 2012) were gathered.  The Principal Component Analysis (PCA) method from chemometric technique was applied to identify the source identification of pollution around the study area. The PCA method has identified methane (CH4), non-methane hydrocarbon (NmHC), total hydrocarbon (THC), ozone (O3) and particulate matter under 10 microns (PM10) are the most significant parameters around the study area.  From the study, it can be concluded that the application of the PCA method in chemometric techniques can be applied for the source apportionment purpose. Hence, this study indicated that for the future and effective management of the Malaysian air quality, an effort should be placed as a priority in controlling point and non-point pollution sources.

Phytosterols provide important health benefits: in particular, the lowering of cholesterol. From environmental and commercial points of view, the most appropriate technique has been searched for extracting phytosterols from plant matrices. As a green technology, supercritical fluid extraction (SFE) using carbon dioxide (CO2) is widely used to extract bioactive compounds from different plant matrices. Several studies have been performed to extract phytosterols using supercritical CO2 (SC-CO2) and this technology has clearly offered potential advantages over conventional extraction methods. However, the efficiency of SFE technology fully relies on the processing parameters, chemistry of interest compounds, nature of the plant matrices and expertise of handling. This review covers SFE technology with particular reference to phytosterol extraction using SC-CO2. Moreover, the chemistry of phytosterols, properties of supercritical fluids (SFs) and the applied experimental designs have been discussed for better understanding of phytosterol solubility in SC-CO2.

This study intends to show the effectiveness of hierarchical agglomerative cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), factor analysis (FA) and multiple linear regressions (MLR) for assessing the air quality data and air pollution sources pattern recognition. The data sets of air quality for 12 months (January-December) in 2007, consisting of 14 stations around Peninsular Malaysia with 14 parameters (168 datasets) were applied. Three significant clusters -low pollution source (LPS) region, moderate pollution source (MPS) region, and slightly high pollution source (SHPS) region were generated via HACA. Forward stepwise of DA managed to discriminate 8 variables, whereas backward stepwise of DA managed to discriminate 9 out of 14 variables. The method of PCA and FA has identified 8 pollutants in LPS and SHPS respectively, as well as 11 pollutants in MPS region, where most of the pollutants are expected derived from industrial activities, transportation and agriculture systems. Four MLR models show that PM 10 categorize as the primary pollutant in Malaysia. From the study, it can be stipulated that the application of chemometric techniques can disclose meaningful information on the spatial variability of a large and complex air quality data. A clearer review about the air quality and a novel design of air quality monitoring network for better management of air pollution can be achieved.

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/jctb.4603This article is protected by copyright. All rights reserved AbstractRecent technological advances and the development of new methods has provided an opportunity to obtain highly purified natural bioactive compounds extracts with potential for the treatment and prevention of human diseases. The use of hazardous and toxic solvents in extraction and processing of bioactive compounds from plant materials is considered as a big problem in health, safety and environmental pollution. Advanced technology aims to increase the production of the desired compounds and find an alternative to using toxic solvents in the extraction processes of bioactive compounds from plant materials. The ever growing interest in plant bioactive compounds and today's concern on environment issues have led to an increase need for efficient and green extraction method. This review is focused on the extraction of bioactive compounds from plant using advanced and environmental friendly methods such as supercritical fluid extraction method, microwave-assisted extraction method, ultrasound-assisted extraction and similar techniques that can give fast and organic residues free extract. An update overview of the bioactive compounds present in plant of Phaleria macrocarpa and its extraction, fractionation, purification and isolation are provided. The advantages and disadvantages of both conventional and non-conventional extraction methods are also discussed in this review.

Fatty acid constituents of total lipids extracted from the head, the skin and the viscera of three neritic tuna species, namely Thunnus tonggol, Euthynnus affinis and Auxis thazard, using supercritical carbon dioxide (SC-CO2) and Soxhlet extraction method were determined and compared. Saturated fatty acid (39.7-48.5%) was dominant in conjunction with monounsaturated fatty acid (21.9-26.6%) and polyunsaturated fatty acid (PUFA) (24.1-27.9%) in all species, and the difference between methods were nonsignificant. Docosahexaenoic acid was the major PUFA, accounting for 17.0-19.9% in the head, 15.7-17.3% in the skin and 14.3-16.1% in the viscera of total fatty acids. Total oil extracted by SC-CO2 had lower free fatty acid (FFA) and peroxide value (PV) content than that by Soxhlet method. The ranges of FFA and PV were 1.8-5.0 and 1.2-2.4%, respectively. It was concluded that SC-CO2 is an effective method to extract fish oil that is rich in omega-3 fatty acids from tuna by-products.