IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i13p7936-d851541.html
   My bibliography  Save this article

Forecasting Daytime Ground-Level Ozone Concentration in Urbanized Areas of Malaysia Using Predictive Models

Author

Listed:
  • NurIzzah M. Hashim

    (Faculty of Civil Engineering Technology, Universiti Malaysia Perlis, d/a Pejabat Pos Besar, P.O. Box 77, Kangar 01007, Malaysia)

  • Norazian Mohamed Noor

    (Faculty of Civil Engineering Technology, Universiti Malaysia Perlis, d/a Pejabat Pos Besar, P.O. Box 77, Kangar 01007, Malaysia
    Sustainable Environment Research Group (SERG), Centre of Excellence Geopolymer and Green Technology (CEGeoGTech), Universiti Malaysia Perlis, d/a Pejabat Pos Besar, P.O. Box 77, Kangar 01007, Malaysia)

  • Ahmad Zia Ul-Saufie

    (Faculty of Computer and Mathematical Sciences, Universiti Teknologi Mara (UiTM), Shah Alam 40450, Malaysia)

  • Andrei Victor Sandu

    (Faculty of Materials Science and Engineering, Gheorghe Asachi Technical University of Iasi, 61 D. Mangeron Blvd., 700050 Iasi, Romania
    Romanian Inventors Forum, St. P. Movila 3, 700089 Iasi, Romania
    National Institute for Research and Development in Environmental Protection INCDPM, Splaiul Independentei 294, 060031 Bucharest, Romania)

  • Petrica Vizureanu

    (Faculty of Materials Science and Engineering, Gheorghe Asachi Technical University of Iasi, 61 D. Mangeron Blvd., 700050 Iasi, Romania)

  • György Deák

    (National Institute for Research and Development in Environmental Protection INCDPM, Splaiul Independentei 294, 060031 Bucharest, Romania)

  • Marwan Kheimi

    (Department of Civil Engineering, Faculty of Engineering—Rabigh Branch, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

Ground-level ozone (O 3 ) is one of the most significant forms of air pollution around the world due to its ability to cause adverse effects on human health and environment. Understanding the variation and association of O 3 level with its precursors and weather parameters is important for developing precise forecasting models that are needed for mitigation planning and early warning purposes. In this study, hourly air pollution data (O 3 , CO, NO 2 , PM 10 , NmHC, SO 2 ) and weather parameters (relative humidity, temperature, UVB, wind speed and wind direction) covering a ten year period (2003–2012) in the selected urban areas in Malaysia were analyzed. The main aim of this research was to model O 3 level in the band of greatest solar radiation with its precursors and meteorology parameters using the proposed predictive models. Six predictive models were developed which are Multiple Linear Regression (MLR), Feed-Forward Neural Network (FFANN), Radial Basis Function (RBFANN), and the three modified models, namely Principal Component Regression (PCR), PCA-FFANN, and PCA-RBFANN. The performances of the models were evaluated using four performance measures, i.e., Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Index of Agreement (IA), and Coefficient of Determination (R 2 ). Surface O 3 level was best described using linear regression model (MLR) with the smallest calculated error (MAE = 6.06; RMSE = 7.77) and the highest value of IA and R 2 (0.85 and 0.91 respectively). The non-linear models (FFANN and RBFANN) fitted the observed O 3 level well, but were slightly less accurate compared to MLR. Nonetheless, all the unmodified models (MLR, ANN, and RBF) outperformed the modified-version models (PCR, PCA-FFANN, and PCA-RBFANN). Verification of the best model (MLR) was done using air pollutant data in 2018. The MLR model fitted the dataset of 2018 very well in predicting the daily O 3 level in the specified selected areas with the range of R 2 values of 0.85 to 0.95. These indicate that MLR can be used as one of the reliable methods to predict daytime O 3 level in Malaysia. Thus, it can be used as a predictive tool by the authority to forecast high ozone concentration in providing early warning to the population.

Suggested Citation

  • NurIzzah M. Hashim & Norazian Mohamed Noor & Ahmad Zia Ul-Saufie & Andrei Victor Sandu & Petrica Vizureanu & György Deák & Marwan Kheimi, 2022. "Forecasting Daytime Ground-Level Ozone Concentration in Urbanized Areas of Malaysia Using Predictive Models," Sustainability, MDPI, vol. 14(13), pages 1-23, June.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7936-:d:851541
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/13/7936/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/13/7936/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fatemeh Barzegari Banadkooki & Mohammad Ehteram & Ali Najah Ahmed & Chow Ming Fai & Haitham Abdulmohsin Afan & Wani M. Ridwam & Ahmed Sefelnasr & Ahmed El-Shafie, 2019. "Precipitation Forecasting Using Multilayer Neural Network and Support Vector Machine Optimization Based on Flow Regime Algorithm Taking into Account Uncertainties of Soft Computing Models," Sustainability, MDPI, vol. 11(23), pages 1-21, November.
    2. Jeongin Eum & Hyungkyoo Kim, 2021. "Effects of Air Pollution on Assaults: Findings from South Korea," Sustainability, MDPI, vol. 13(20), pages 1-13, October.
    3. Svajone Bekesiene & Ieva Meidute-Kavaliauskiene & Vaida Vasiliauskiene, 2021. "Accurate Prediction of Concentration Changes in Ozone as an Air Pollutant by Multiple Linear Regression and Artificial Neural Networks," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    4. Hassanzadeh, S. & Hosseinibalam, F. & Omidvari, M., 2008. "Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(10), pages 2317-2327.
    5. Nidhi Verma & Sonal Kumari & Anita Lakhani & K Maharaj Kumari, 2019. "24 Hour Advance Forecast of Surface Ozone Using Linear and Non-Linear Models at a Semi-Urban Site of Indo-Gangetic Plain," International Journal of Environmental Sciences & Natural Resources, Juniper Publishers Inc., vol. 18(2), pages 46-55, March.
    6. Henry Kaiser, 1974. "An index of factorial simplicity," Psychometrika, Springer;The Psychometric Society, vol. 39(1), pages 31-36, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chelladurai Aarthi & Varatharaj Jeya Ramya & Przemysław Falkowski-Gilski & Parameshachari Bidare Divakarachari, 2023. "Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction," Sustainability, MDPI, vol. 15(2), pages 1-16, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lillemo, Shuling Chen, 2014. "Measuring the effect of procrastination and environmental awareness on households' energy-saving behaviours: An empirical approach," Energy Policy, Elsevier, vol. 66(C), pages 249-256.
    2. Xiaoxu Dong & Huawei Zhao & Tiancai Li, 2022. "The Role of Live-Streaming E-Commerce on Consumers’ Purchasing Intention regarding Green Agricultural Products," Sustainability, MDPI, vol. 14(7), pages 1-13, April.
    3. Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Governance, capital flight and industrialisation in Africa," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-22, December.
    4. Pamela E. Ofori & Simplice A. Asongu & Vanessa S. Tchamyou, 2021. "The Synergy between Governance and Economic Integration in Promoting Female Economic Inclusion in Sub-Saharan Africa," Working Papers 21/071, European Xtramile Centre of African Studies (EXCAS).
    5. Simplice A. Asongu, 2014. "Knowledge Economy and Financial Sector Competition in African Countries," African Development Review, African Development Bank, vol. 26(2), pages 333-346, June.
    6. Pasura Aungkulanon & Walailak Atthirawong & Pongchanun Luangpaiboon & Wirachchaya Chanpuypetch, 2024. "Navigating Supply Chain Resilience: A Hybrid Approach to Agri-Food Supplier Selection," Mathematics, MDPI, vol. 12(10), pages 1-42, May.
    7. Chimere O. Iheonu, 2019. "Governance and Domestic Investment in Africa," Working Papers 19/001, European Xtramile Centre of African Studies (EXCAS).
    8. Rodríguez-Fuentes, Carlos Javier & Hernández-López, Montserrat, 1997. "Análisis de diferencias estructurales interregionales determinantes en el impacto de la política monetaria," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 7, pages 141-157, Junio.
    9. Asongu, Simplice & Tchamyou, Vanessa & Asongu, Ndemaze & Tchamyou, Nina, 2018. "The Comparative African Economics of Governance in Fighting Terrorism," MPRA Paper 92346, University Library of Munich, Germany.
    10. Leiv Gabrielsen & Pål Ulleberg & Reidulf Watten, 2012. "The Adolescent Life Goal Profile Scale: Development of a New Scale for Measurements of Life Goals Among Young People," Journal of Happiness Studies, Springer, vol. 13(6), pages 1053-1072, December.
    11. Simplice A. Asongu & Rexon T. Nting & Joseph Nnanna, 2020. "Linkages between Globalisation, Carbon Dioxide Emissions and Governance in Sub-Saharan Africa," International Journal of Public Administration, Taylor & Francis Journals, vol. 43(11), pages 949-963, August.
    12. Simplice A Asongu, 2013. "Modeling the future of knowledge economy: evidence from SSA and MENA countries," Economics Bulletin, AccessEcon, vol. 33(1), pages 612-624.
    13. Megha Gupta & Suhasini Verma & Smita Pachare, 2023. "An analysis of Conventional and Alternative financing—Customers' perspective," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2404-2414, July.
    14. Xiangfei Yuan & Haijing Hao & Chenghua Guan & Alex Pentland, 2022. "Which factors affect the performance of technology business incubators in China? An entrepreneurial ecosystem perspective," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-20, January.
    15. Nihat Can Karabulut & Murat Ozen & Oruc Altintasi, 2024. "Understanding the Determinants of Lane Inefficiency at Fully Actuated Intersections: An Empirical Analysis," Sustainability, MDPI, vol. 16(2), pages 1-17, January.
    16. Naznin Sultana & Thao T. P. Nguyen & Ahmed Hossain & Md. Asaduzzaman & Minh H. Nguyen & Ishrat Jahan & Kien T. Nguyen & Tuyen Van Duong, 2022. "Psychometric Properties of the Short-Form Geriatric Depression Scale (GDS-SF) and Its Associated Factors among the Elderly in Bangladesh," IJERPH, MDPI, vol. 19(13), pages 1-14, June.
    17. Orkhan Sariyev & Tim K. Loos & Manfred Zeller & Tulsi Gurung, 2020. "Women in household decision-making and implications for dietary quality in Bhutan," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 8(1), pages 1-20, December.
    18. Chang, Yuan-Chieh & Chen, Min-Nan, 2016. "Service regime and innovation clusters: An empirical study from service firms in Taiwan," Research Policy, Elsevier, vol. 45(9), pages 1845-1857.
    19. Romero, Pascual & Botía, Pablo & del Amor, Francisco M. & Gil-Muñoz, Rocío & Flores, Pilar & Navarro, Josefa María, 2019. "Interactive effects of the rootstock and the deficit irrigation technique on wine composition, nutraceutical potential, aromatic profile, and sensory attributes under semiarid and water limiting condi," Agricultural Water Management, Elsevier, vol. 225(C).
    20. Ivana BLEŠIÆ & Andjelija IVKOV-DŽIGURSKI & Uglješa STANKOV & Igor STAMENKOVIÆ & Milan Bradiæ, 2011. "Research Of Expected And Perceived Service Quality In Hotel Management," Revista de turism - studii si cercetari in turism / Journal of tourism - studies and research in tourism, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 11(11), pages 6-14, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7936-:d:851541. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.