Feed-Forward Artificial Neural Network Model for Air Pollutant Index Prediction in the Southern Region of Peninsular Malaysia

This paper describes the application of principal component analysis (PCA) and artificial neural network (ANN) to predict the air pollutant index (API) within the seven selected Malaysian air monitoring stations in the southern region of Peninsular Malaysia based on seven years database (2005-2011). Feed-forward ANN was used as a prediction method. The feed-forward ANN analysis demonstrated that the rotated principal component scores (RPCs) were the best input parameters to predict API. From the 4 RPCs, only 10 (CO, O3, PM10, NO2, CH4, NmHC, THC, wind direction, humidity and ambient temp) out of 12 prediction variables were the most significant parameters to predict API. The results proved that the ANN method can be applied successfully as tools for decision making and problem solving for better atmospheric management.

Observed Trends in Extreme Temperature over the Klang Valley, Malaysia

This study investigates the recent extreme temperature trends across 19 stations in the Klang Valley, Malaysia, over the period 2006^-16. Fourteen extreme index trends were analyzed using the Mann-Kendall non-parametric test, with Sen’s slope as a magnitude estimator. Generally, the annual daily mean temperature, daily mean maximum temperature, and daily mean minimum temperature in the Klang Valley increased significantly, by 0.07°C yr^-1, 0.07°C yr^-1 and 0.08°C yr^-1, respectively. For the warm temperature indices, the results indicated a significant upward trend for the annual maximum of maximum temperature, by 0.09°C yr^-1, and the annual maximum of minimum temperature, by 0.11°C yr^-1. The results for the total number of warm days and warm nights showed significant increasing trends of 5.02 d yr^-1 and 6.92 d yr^-1, respectively. For the cold temperature indices, there were upward trends for the annual minimum of maximum temperature, by 0.09°C yr^-1, and the annual minimum of minimum temperature, by 0.03°C yr^-1, concurrent with the decreases in the total number cold days (TX10P), with -3.80 d yr^-1, and cold nights (TN10P), with -4.33 d yr^-1. The 34°C and 37°C summer days results showed significant upward trends of 4.10 d yr^-1 and 0.25 d yr^-1, respectively. Overall, these findings showed upward warming trends in the Klang Valley, with the minimum temperature rate increasing more than that of the maximum temperature, especially in urban areas.

Composition and source apportionment of dust fall around a natural lake

The aim of this study was to determine the source apportionment of dust fall around Lake Chini, Malaysia. Samples were collected monthly between December 2012 and March2013 at seven sampling stations located around Lake Chini. The samples were filtered to separate the dissolved and undissolved solids. The ionic compositions（NO-3, SO2-4, Cl-and NH＋4） were determined using ion chromatography（IC） while major elements（K, Na, Ca and Mg） and trace metals（Zn, Fe, Al, Ni, Mn, Cr, Pb and Cd） were determined using inductively coupled plasma mass spectrometry（ICP-MS）. The results showed that the average concentration of total solids around Lake Chini was 93.49 ± 16.16 mg/（m2·day）. SO2-4, Na and Zn dominated the dissolved portion of the dust fall. The enrichment factors（EF） revealed that the source of the trace metals and major elements in the rain water was anthropogenic, except for Fe. Hierarchical agglomerative cluster analysis（HACA） classified the seven monitoring stations and 16 variables into five groups and three groups respectively. A coupled receptor model, principal component analysis multiple linear regression（PCA-MLR）, revealed that the sources of dust fall in Lake Chini were dominated by agricultural and biomass burning（42%）,followed by the earth＇s crust（28%）, sea spray（16%） and a mixture of soil dust and vehicle emissions（14%）.

Composition of carbohydrates, surfactants, major elements and anions in PM2.5 during the 2013 Southeast Asia high pollution episode in Malaysia

Haze episodes have become a major concern in Malaysia over the past few decades and have an increasingly important impact on the country each and every year. During haze episodes from biomass burning in Southeast Asia, particularly from Sumatra, Indonesia, particulate matter PM2.5 is found to be one of the dangerous sources of airborne pollution and is known to seriously affect human health. This study determines the composition of carbohydrates （as levoglucosan）, surfactants, major elements, and anions in PM2.5 during a 2013 haze episode. PM2.5 samples were collected from Universiti Kebangsaan Malaysia, Bangi, using a high volume sampler during a seven-day monitoring campaign during the peak of that year＇s haze episode. PM2.5 concentrations ranged between 14.52 and 160.93 μg/m3, exceeding the 2005 WHO air quality guidelines for PM2.5 （25 μg/m3 for 24-h mean）. The patterns for levoglucosan, surfactants, major elements, and anionic compositions were proportional to the PM2.5 concentrations. Changes in PM2.5 observed on days 3 and 4 were influenced by a combination of meteorological factors, which substantiate the theory that such factors play a pivotal role in haze episodes.

Lichens reveal the quality of indoor air in Selangor, Malaysia

Background:Indoor air quality(IAQ)is a concern in kindergartens as children spend much of their time there.Yet,there is a shortage of biological indicators needed for assessing IAQ.Thus,this study evaluated IAQ using transplanted lichen Usnea misaminensis as a biological indicator.Methods:Lichen samples,collected from Bukit Larut,Perak,Malaysia,were exposed to indoor and outdoor environments in an urban area(Ummi Aiman Kindergarten)and a rural area(Ummi Qaseh Pelangi Kindergarten)for 2 months during August 15 to October 14,2019.The concentrations of 12 selected elements and the vitality of the lichens were then evaluated.Results:Increased concentrations of eleven of the twelve elements deposited in the lichen samples in both urban and rural areas were observed.For both areas,the element concentrations in the samples from the indoor environment was lower than those from the outdoor environment,and those in the rural area were lower than those from in the urban area,suggesting the impacts of traffic emissions.The vitality of the lichens showed no significant change in indoor environment,compared to that in outdoor environment,indicating that even exposed to indoor environment,the lichens remained effective biological indicators as same as they were in the outdoor environment.Conclusions:Lichens are effective biological indicators for both outdoor and indoor environments.Furthermore,outdoor emissions could influence IAQ,which could be problematic in densely populated areas such as kindergartens.Mitigation measures should be taken.