Assessment on air quality pattern: a case study in Putrajaya, Malaysia

Kamaruzzaman, A.; Saudi, Ahmad Shakir Mohd; Azid, Azman; Balakrishnan, Avinash; Abu, Izuddin Fahmy; Amin, Nur Azma; Rizman, Zairi Ismael

doi:10.4314/jfas.v9i4s.44

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…(2015b)9.Identification of the spatial variation of air pollutants and its pattern at seven air monitoring stations in the northern part of Peninsular Malaysia for 4 years (2008–2011).HACA, DA and ANNThe predictive ability of chemometrics is at least as good as the standard model.The feed-forward ANN model could predict API values from all existing input with slight precision and could save time and cost of monitoring purposes.Amran et al. (2015)10.Determination of air quality pattern at Putrajaya monitoring station based on three years observation (2011–2013).PCA, FA and SPCPCA and FA model identified five pollutants that affected air quality.SPC analysis verified that SO 2 was the main pollutant.Kamaruzzaman et al. (2017)11.Assessment of ambient air pollution pattern in Shah Alam, Malaysia for 5 years (2009–2013).PCA and SPCThe level of air quality was manipulated by the climate condition, gas, non-gas and secondary air pollutants.Zakaria et al.…”

Section: Resultsmentioning

confidence: 99%

Application of chemometrics techniques to solve environmental issues in Malaysia

Shafii

Saudi

Chyang

et al. 2019

Heliyon

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There has been a growing concern on the rising of environmental issues in Malaysia over the last decade. Many environmental studies conducted in this country began to utilise the chemometrics techniques to overcome the limitation in the environmental monitoring studies. Chemometrics becomes an important tool in environmental fields to evaluate the relationship of various environmental variables particularly in a large and complex database. The review aimed to analyse and summarize the current evidences and limitations on the application of chemometrics techniques in the environmental studies in Malaysia. The study performed a comprehensive review of relevant scientific journals concerning on the major environmental issues in the country, published between 2013 and 2017. A total of 29 papers which focused on the environmental issues were reviewed. Available evidences suggested that chemometrics techniques have a greater accuracy, flexibility and efficiency to be applied in environmental modelling. It also reported that chemometrics techniques are more practical for cost effective and time management in sampling and monitoring purposes. However, chemometrics is relatively new in environmental field in Malaysia and various scopes need to be considered in the future as the current studies focused on very limited number of major environmental issues. Overall, chemometrics techniques have a lot of advantages in solving environmental problems. The development of chemometrics in environmental studies in the country is necessary to advance understanding, thus able to produce more significant impacts towards the effective environmental management.

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Section: Resultsmentioning

confidence: 99%

Application of chemometrics techniques to solve environmental issues in Malaysia

Shafii

Saudi

Chyang

et al. 2019

Heliyon

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“…Statistical methods, shallow machine learning models, regression techniques, least absolute shrinkage and selection operator (LASSO), elastic net, regression tree and regression forest are the most used to solve air-quality prediction problems [15][16][17][18][19]. Many scientists have tried to use the neural network to predict future air quality [20][21][22]. Deep learning methods have become an active research field in recent years for prediction of air quality, with Convolutional Neural Network (CNN) [23], Recurrent Neural Networks (RNN) and their variants have been widely used [24,25].…”

Section: Related Workmentioning

confidence: 99%

A Novel One-Dimensional CNN with Exponential Adaptive Gradients for Air Pollution Index Prediction

et al. 2020

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Air pollution is one of the world’s most significant challenges. Predicting air pollution is critical for air quality research, as it affects public health. The Air Pollution Index (API) is a convenient tool to describe air quality. Air pollution predictions can provide accurate information on the future pollution situation, effectively controlling air pollution. Governments have expressed growing concern about air pollution due to its global effect on human health and sustainable growth. This paper proposes a novel forecasting model using One-Dimensional Deep Convolutional Neural Network (1D-CNN) and Exponential Adaptive Gradients (EAG) optimization to predict API for a selected location, Klang, a city in Malaysia. The proposed 1D-CNN–EAG exponentially accumulates past model gradients to adaptively tune the learning rate and converge in both convex and non-convex areas. We use hourly air pollution data over three years (January 2012 to December 2014) for training. Parameter optimization and model evaluation was accomplished by a grid-search with k-folds cross-validation. Results have confirmed that the proposed approach achieves better prediction accuracy than the benchmark models in terms of Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and the Correlation Coefficient (R-Squared) with values of 2.036, 2.354, 4.214 and 0.966, respectively, and time complexity.

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“…The Air Quality [17][18][19][20][21][22][23][24][25] Guidelines set for the first time a guideline value for particulate matter and the aim of the guidelines is to achieve the lowest concentrations of pollutant in atmosphere as possible [11].…”

Section: Review Of Literaturesmentioning

confidence: 99%

A study on air pollution concentration at Desa parkcity construction site

Saudi

Nurulshyha

Mahmud

et al. 2018

J. Fundam and Appl Sci.

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This study assesses the effect of construction workers exposure towards the air pollution the correlation between meteorological factor with the particulate matter and other gases concentration at a construction site in DesaParkcity. The concentration of PM was collected by using low volume sampler meanwhile CO, CO with the particulate matter concentration. There is a significant association between factor with the concentration orCO, CO 2 , SO 2 and NO 2 at DesaParkcity air pollution; construction worker; meteorological factor.

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Assessment on air quality pattern: a case study in Putrajaya, Malaysia

Cited by 6 publications

References 9 publications

Application of chemometrics techniques to solve environmental issues in Malaysia

Application of chemometrics techniques to solve environmental issues in Malaysia

A Novel One-Dimensional CNN with Exponential Adaptive Gradients for Air Pollution Index Prediction

A study on air pollution concentration at Desa parkcity construction site

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