High anthropogenic activities are rapidly increasing phenomenon and it is assumed to have global implications. In Nigeria, high anthropogenic activities rapidly increase above the standard of the threshold values especially the lighting sources. This increase due to the vastly growing of industries, residential and commercial uses and other sources such as street lighting in urban and semiurban areas, which can make the night sky brightness in the area above the threshold set for polluted status. The study measures the night sky brightness at the most densely populated urban centers of Nigeria; to estimate and quantify the level of the night sky brightness from the sites nearby the cities of the planned research study. The research monitored the zenith sky brightness from November 2015 to March 2016 using Sky Quality Meter (SQM). However, typical values ranging from 20.14 to 22.00Mag.sqm /arc sec.2 were measured at different sites of the study area. This data recorded in the field was analyzed using Agglomerative Hierarchical Method via Ward's Methods to cluster our data according to the pollution status of the areas. Result showed three clusters in which class 1 has low pollution; class 2 is moderate while class 3 has the high pollution status. The sites classified in class 3 are more polluted due to the high use of artificial light. However, geographical information system (GIS) software was employed to confirm the results obtained from environ-metric technique and concluded that this result is confirmed to be the same. Hence, it illustrated that sites in cluster 1 have an excellent dark location that can be used to build optical observatory stations and other astronomical observations due to their dark sky.
This research presents marine water quality status in three different mangrove estuaries. The objective of this study is to evaluate the surface water quality of three estuaries in east coast Peninsular Malaysia. The parameters measured were Dissolved Oxygen (DO), pH, Biochemical Oxygen Demand (BOD), total dissolved solid (TDS), ammonium (NH4-N), turbidity (TUR), total suspended solid (TSS) and coliform. Monthly sampling was performed during the dry season, from June 2016 until September 2016. Data were analysed using principal component analysis (PCA). PCA yielded two PCs where VF1 forms strong factor loadings for pH, NH4-N, SAL, and TDS signifying saltwater intrusion in mangrove area. VF2 designed strong factors of BOD, TUR and Coliform and strong negative loading of DO indicating anthropogenic pollutions in the area. This study output will be a baseline setting for future studies in mangrove estuary marine water quality. Mangrove marine water samples of future monitoring studies in mangrove estuary will benefit by enabling understanding of pollution loading and coastal water quality. It is essential to plan a workable water quality modelling as powerful tool to simulate marine water quality and forecast future consequences to facilitate mangrove biodiversity conservation.
The objectives of this study are to identify the significant variables and to verify the best statistical method for determining the effect of indoor air quality (IAQ) at 7 different locations in Universiti Sultan Zainal Abidin, Terengganu, Malaysia. The IAQ data were collected using in-situ measurement. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discrimination analysis (LDA), and agglomerative hierarchical clustering (AHC) were used to classify the significant variables as well as to compare the best method for determining IAQ levels. PCA verifies only 4 out of 9 parameters (PM 10 , PM 2.5 , PM 1.0 , and O 3 ) and is the significant variable in IAQ. The PLS-DA model classifies 89.05% correct of the IAQ variables in each station compared to LDA with only 66.67% correct. AHC identifies three cluster groups, which are highly polluted concentration (HPC), moderately polluted concentration (MPC), and low-polluted concentration (LPC) area. PLS-DA verifies the groups produced by AHC by identifying the variables that affect the quality at each station without being affected by redundancy. In conclusion, PLS-DA is a promising procedure for differentiating the group classes and determining the correct percentage of variables for IAQ.
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