Skip to main content

Spatial Analysis of the Air Pollutant Index in the Southern Region of Peninsular Malaysia Using Environmetric Techniques

  • Conference paper
  • First Online:
From Sources to Solution

Abstract

Air pollution is becoming a major environmental issue in the southern region of Peninsular Malaysia. Environmetric techniques (HACA, DA, and PCA/FA) were used to evaluate the spatial variations in the southern region of Peninsular Malaysia, followed by API prediction comparison using ANN and MLR models. The datasets of air pollutant parameters for 3 years (2005–2007) were applied in this study. HACA clustered three different groups of similarity based on the characteristics of air quality parameters. DA shows all seven parameters (CO, O3, PM10, SO2, NOx, NO, and NO2) gave the most significant variables after stepwise backward mode. PCA/FA identify that the major source of air pollution is due to combustion of fossil fuels in motor vehicles and industrial activities. The ANN model shows a better prediction compared to the MLR model with R2 values equal to 0.819 and 0.773 respectively. This study concluded that the environmetric techniques and modelling become an excellent tool in API assessment, air pollution source identification, apportionment, and interpretation of complex dataset with a view to get better information about the air quality, and can be setbacks in designing an API monitoring network for effective air pollution resources management.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Kamal MM, Jailani R, Shauri RCA (2006) Prediction of ambient air quality based on neural network technique. In: 4th Student Conference on Research and Development, pp 115–119

    Google Scholar 

  • Karatzas KD, Kaltsatos S (2007) Air pollution modelling with the aid of computational intelligence methods in Thessaloniki, Greece. Simul Model Pract Theory 15:1310–1319

    Article  Google Scholar 

  • Levine JS, Augustsson TR, Andersont IC, Hoell JM Jr (1984) Tropospheric sources of NO4: lighting and biology. Atmos Environ 18:1797–1804

    Google Scholar 

  • Mittal ML, Hess PG, Jain SL, Arya BC, Sharma C (2007) Surface ozone in the Indian region. Atmos Environ 41:6572–6584

    Article  CAS  Google Scholar 

  • Motallebi N, Flocchini RG, Myrup LO, Cahill TA (1990) A principal component analysis of visibility and air pollution in six California cities. Atmósfera 3:127–141

    Google Scholar 

  • Mutalib SNSA, Juahir H, Azid A, Sharif SM, Latif MT, Aris AZ, Zain SM, Dominick D (2013) Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia. Environ Sci: Process Impacts 15:1717–1728. doi: 10.1039/C3EM00161J

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hafizan Juahir .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media Singapore

About this paper

Cite this paper

Azid, A. et al. (2014). Spatial Analysis of the Air Pollutant Index in the Southern Region of Peninsular Malaysia Using Environmetric Techniques. In: Aris, A., Tengku Ismail, T., Harun, R., Abdullah, A., Ishak, M. (eds) From Sources to Solution. Springer, Singapore. https://doi.org/10.1007/978-981-4560-70-2_56

Download citation

Publish with us

Policies and ethics