Ahmad Shukri Yahaya

Transformation of nitrogen dioxide into ozone and prediction of ozone concentrations using multiple linear regression techniques

Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. This study examines transformation of nitrogen dioxide (NO2) into ozone (O3) at urban environment using time series plot. Data on the concentration of environmental pollutants and meteorological variables were employed to predict the concentration of O3 in the atmosphere. Possibility of employing multiple linear regression models as a tool for prediction of O3 concentration was tested. Results indicated that the presence of NO2 and sunshine influence the concentration of O3 in Malaysia. The influence of the previous hour ozone on the next hour concentrations was also demonstrated.

Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: Case studies from Malaysian Federal Roads

Head-on crashes are among the most severe collision types and of great concern to road safety authorities. Therefore, it justifies more efforts to reduce both the frequency and severity of this collision type. To this end, it is necessary to first identify factors associating with the crash occurrence. This can be done by developing crash prediction models that relate crash outcomes to a set of contributing factors. This study intends to identify the factors affecting both the frequency and severity of head-on crashes that occurred on 448 segments of five federal roads in Malaysia. Data on road characteristics and crash history were collected on the study segments during a 4-year period between 2007 and 2010. The frequency of head-on crashes were fitted by developing and comparing seven count-data models including Poisson, standard negative binomial (NB), random-effect negative binomial, hurdle Poisson, hurdle negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models. To model crash severity, a random-effect generalized ordered probit model (REGOPM) was used given a head-on crash had occurred. With respect to the crash frequency, the random-effect negative binomial (RENB) model was found to outperform the other models according to goodness of fit measures. Based on the results of the model, the variables horizontal curvature, terrain type, heavy-vehicle traffic, and access points were found to be positively related to the frequency of head-on crashes, while posted speed limit and shoulder width decreased the crash frequency. With regard to the crash severity, the results of REGOPM showed that horizontal curvature, paved shoulder width, terrain type, and side friction were associated with more severe crashes, whereas land use, access points, and presence of median reduced the probability of severe crashes. Based on the results of this study, some potential countermeasures were proposed to minimize the risk of head-on crashes.

Monsoonal differences and probability distribution of PM10 concentration

There are many factors that influence PM10 concentration in the atmosphere. This paper will look at the PM10 concentration in relation with the wet season (north east monsoon) and dry season (south west monsoon) in Seberang Perai, Malaysia from the year 2000 to 2004. It is expected that PM10 will reach the peak during south west monsoon as the weather during this season becomes dry and this study has proved that the highest PM10 concentrations in 2000 to 2004 were recorded in this monsoon. Two probability distributions using Weibull and lognormal were used to model the PM10 concentration. The best model used for prediction was selected based on performance indicators. Lognormal distribution represents the data better than Weibull distribution model for 2000, 2001, and 2002. However, for 2003 and 2004, Weibull distribution represents better than the lognormal distribution. The proposed distributions were successfully used for estimation of exceedences and predicting the return periods of the sequence year.

Multivariate methods to predict ground level ozone during daytime, nighttime, and critical conversion time in urban areas

Ground–level ozone (O3) is known to exhibit strong daily variations that lead to complexity of the pollutants’ analysis and predictions. This study aimed to introduce and explore the variations in O3 concentrations during daytime (DT), nighttime (NT), and critical conversion time (CCT) using multiple linear regression (MLR) and principal component regression (PCR) analyses. The original variables and principal component analysis (PCA) results were used as the input for MLR analysis. Hourly averages of six air pollutants and four meteorological parameters at Shah Alam during 1999–2009 were selected for this study. The monitoring records in 2010 were used to assess the developed models using several performance indicators. Results showed that the MLR model during DT exhibited optimal performance in terms of normalized absolute error, index of agreement, prediction accuracy, and coefficient of determination (R2) with values of 0.2762, 0.9211, 0.8581, and 0.7354, respectively. PCR during CCT also showed significantly higher performance than that during DT and NT. This result was evidenced by higher percentage of total variances, which could be explained by the selected variables in PCA during CCT.

Statistical evaluation of pre-selection criteria for industrialized building system (IBS)

AbstractThe Malaysian government has endorsed the use of an industrialized building system (IBS) in domestic projects. These have shifted the focus of the nations construction industry towards mass production and modular products. A proper study on site selection criteria for new IBS precast manufacturing sites has now become essential. The preliminary study in this research determines the IBS precast manufacturing site selection criteria from literature reviews. Questionnaires pertaining to IBS acceptance and preference criteria were send to manufacturers, policymakers, academicians and contractors. The outcome analyses the respondents’ view towards 15 site selection criteria. The result from the ANOVA statistical test indicates that most respondents agreed with the selected criteria except political and regulation criteria, urban requirement criteria, and personal criteria. However, there is a significant difference within the opinions of the contractors and manufacturers sector. Likewise, the mean ran...

A Comparative Study of Count Models: Application to Pedestrian-Vehicle Crashes Along Malaysia Federal Roads

Objectives: The objective of this study was to examine the effects of various roadway characteristics on the incidence of pedestrian–vehicle crashes by developing a set of crash prediction models on 543 km of Malaysia federal roads over a 4-year time span between 2007 and 2010. Methods: Four count models including the Poisson, negative binomial (NB), hurdle Poisson (HP), and hurdle negative binomial (HNB) models were developed and compared to model the number of pedestrian crashes. Results and Conclusions: The results indicated the presence of overdispersion in the pedestrian crashes (PCs) and showed that it is due to excess zero rather than variability in the crash data. To handle the issue, the hurdle Poisson model was found to be the best model among the considered models in terms of comparative measures. Moreover, the variables average daily traffic, heavy vehicle traffic, speed limit, land use, and area type were significantly associated with PCs.

Comparison of Linear Interpolation Method and Mean Method to Replace the Missing Values in Environmental Data Set

Data collected in air pollution monitoring such as PM10, sulphur dioxide, ozone and carbon monoxide are obtained from automated monitoring stations. These data usually contained missing values due to machine failure, routine maintenance, changes in the siting of monitors and human error. Incomplete datasets can cause bias due to systematic differences between observed and unobserved data. Therefore, it is important to find the best way to estimate these missing values to ensure the quality of data analysed are of high quality. Incomplete data matrices are problematic: incomplete datasets may lead to results that are different from those that would have been obtained from a complete dataset (Hawthorne and Elliott, 2004). There are three major problems that may arise when dealing with incomplete data. First, there is a loss of information and, as a consequence, a loss of efficiency. Second, there are several complications related to data handling, computation and analysis, due to the irregulaties in data structure and the impossibility of using standard software. Third, and more important, there maybe bias due to systematic differences between observed and unobserved data. One approach to solve incomplete data problems is the adoption of imputation techniques (Junninen et al., 2004). Thus, this study compared the performance between linear interpolation method (imputation technique) and substitution of mean value for replacement of missing values in environmental data set.

Characterization and Hazard Study of Two Areas of Penang Island, Malaysia

ABSTRACT Penang Island of Malaysia is vulnerable to various natural hazards due to its hilly terrain and weather. Due to recent rapid population and economic growth, the probability of disaster associated with natural hazards has increased. This article characterizes geological and geotechnical parameters collected from field data that relate to natural hazard susceptibility. The areas of investigation were chosen so that each area lay on different geological formations. The variations in selected parameters with depth were obtained. The correlation within parameters was established and was found to be in agreement with that from other researchers. The investigation identifies parameters that can be used to evaluate the degree of hazard susceptibility.

Application of Thermoplastics in Protection of Natural Fibres

Nowadays thermoplastics are widely used in industries; many products used different specifications of the thermoplastics that are adapted to their requirement. The importance of consideration to the environmental protection leads the mankind to thinking about producing environment-friendly material, and also controlling the waste material by recycling or reducing them. In the meantime the natural materials such as cellulose based material are one of the major resources that can be used to replace with many manufactured materials. However, cellulosed based material such as natural fibres, because of their degradability, need protection from any circumferential agents. The protection may require a special condition in order to utilise in soil, due to water absorption, soil organisms, and minerals. Natural fibres are amenable to modifications as they bear hydroxyl groups from cellulose and lignin. In addition coating the fibres with any chemical materials reduce their water absorptions and protect them from any bacteria and fungi attack. The hydroxyl groups may be involved in the hydrogen bonding within the cellulose molecules. This weakness of the natural material and good characteristics of natural fibres is the basis of biocomposites invention.

Evaluation of Environmental Risk Assessment Parameters Due to Hillslope Developments in Penang Island, Malaysia

ABSTRACT Slope failure and soil erosion due to increased development activity in hilly areas can be catastrophic and affect the environment and humans’ well-being. This article investigates the parameters that contribute to environmental risk. Nine contributing parameters were identified. Rating the risk was proposed based on the prediction of occurrences of environmental issues and were categorized from very high (5) to very low (1) with high, medium, and low in between. The assessments were reviewed and evaluated based on rating for the chosen parameters. Maps quantifying risks were developed identifying areas of environmental risk. The overall result shows that development areas PD3 of Tanjung Bungah, and PD3, PD8, and PD9 of Paya Terubong have high rating of environmental risk. No development area is classified as very high risk or very low risk. The rating can be used to develop zones of potential high risk, and from this zoning guideline the viability can be measured for any proposed development.