Advertisement

Variations of Selected Criteria Air Pollutants During High Particulate Event

  • Syabiha ShithEmail author
  • Leong Weng Woh
  • Nor Azam Ramli
  • Maisarah Sulaiman
  • Nur Baitul Izati Rasli
  • Nurul Adyani Ghazali
Conference paper
Part of the Lecture Notes in Civil Engineering book series (LNCE, volume 53)

Abstract

Nitrogen Dioxide (NO2), Ground Level Ozone (O3), and Particulate Matter with size less than 10 μ (PM10) are air pollutants measured under the Malaysia Ambient Air Quality Guideline requirements. The focus of this research is the interaction between each criteria pollutant as well as the effects of daytime (DT), nighttime (NT), four monsoon seasons [northeast monsoon (NE), southwest monsoon (SW), 1st intermonsoon (AM) and 2nd intermonsoon (SO)] and high particulate events (HPEs) that occurred in one year towards O3 concentrations. The hourly concentration trends of air pollutants were compared and contrasted using descriptive analysis and graphical analysis. Pearson correlation coefficient was used to analyze the relationship between PM10 with O3 and O3 with NO2. The results show that seasonal variation has the least effect for each pollutant. Even the correlation on each pollutant is less significant, the effect to monthly mean value indicates that HPE has the highest mean value of PM10 concentration at 116.16 µg/m3. April–May inter-monsoon has the lowest level of all three air quality parameters with PM10 (24.09 μg/m3), O3 (5.35 and 8.83 ppb) and NO2 (6.61 and 7.93 ppb), respectively. September–October inter-monsoon has higher mean concentration than April–May (PM10, 53.20 μg/m3; O3, 22.33 ppb and NO2, 8.29 ppb). DT and NT provide the information whereby O3 and NO2 are highly dependent on the daily human activities and sunlight as these two pollutants are significantly differenced between DT and NT. Besides, the study also showed that the mean concentration of PM10 in Taiping monitoring station has a positive correlation coefficient towards O3, which indicate that the increase of PM10 will increase O3. Essentially, during HPE, a high concentration of PM10 induced high formation of O3 compared to during non-HPE.

Keywords

Coefficient correlation Daytime Nighttime Ozone Particulate matter Seasonal monsoon 

Notes

Acknowledgements

This research was part of work supported by RUI USM Grant Scheme, 1001/PAWAM/814278. Thanks to the Department of Environment Malaysia for providing the monitoring records.

References

  1. 1.
    Afroz R, Hassan MN, Ibrahim NA (2003) Review of air pollution and health impacts in Malaysia. Environ Res 92(2):71–77CrossRefGoogle Scholar
  2. 2.
    Akhir MF, Chuen YJ (2011) Seasonal variation of water characteristics during inter-monsoon along the East Coast of Johor. J Sustain Sci Manag 6(2):206–214Google Scholar
  3. 3.
    Akhir M, Fadzil M, Zakaria NZ, Tangang F (2014) Intermonsoon variation of physical characteristics and current circulation along the east coast of Peninsular Malaysia. Int J Oceanogr 2014(Article ID 527587):9Google Scholar
  4. 4.
    Awang NR, Ramli NA, Shith S, Md Yusof NFF, Zainordin NS, Sansuddin N, Ghazali NA (2018) Time effects of high particulate events on the critical conversion point of ground-level ozone. Atmos Environ 187:328–334CrossRefGoogle Scholar
  5. 5.
    Awang NR, Ramli NA, Shith S, Zainordin NS, Manogaran H (2018) Transformational characteristics of ground-level ozone during high particulate events in urban area of Malaysia. Air Qual Atmos Health 11(6):715–727CrossRefGoogle Scholar
  6. 6.
    Awang NR, Ramli NA, Yahaya AS, Elbayoumi M (2015) Multivariate methods to predict ground level ozone during daytime, nighttime, and critical conversion time in urban areas. Atmos Pollut Res 6(5):726–734CrossRefGoogle Scholar
  7. 7.
    Awang NR, Ramli NA, Mohammed NI, Yahaya AS (2013) Time series evaluation of ozone concentrations in Malaysia based on the location of monitoring stations. Int J Eng Technol 3(3)Google Scholar
  8. 8.
    Azmi SZ, Latif MT, Ismail AS, Juneng L, Jemain AA (2010) Trend and status of air quality at three different monitoring stations in the Klang Valley, Malaysia. Air Qual Atmos Health 3(1):53–64CrossRefGoogle Scholar
  9. 9.
    Banan N, Latif MT, Juneng L, Ahamad F (2013) Characteristics of surface ozone concentrations at stations with different backgrounds in the Malaysian Peninsula. Aerosol Air Qual Res 13(3):1090–1106CrossRefGoogle Scholar
  10. 10.
    DOE (2019) Department of Environment Malaysia. Department of Environment’s (DOE) official application for Air Pollutant Index (API) is APIMS. Available on http://apims.doe.gov.my. Accessed on 27 May 2019
  11. 11.
    DOE (2015) Department of Environment Malaysia. Malaysia environmental quality report 2015. In: M. O. S. Department of Environment, Technology and the Environment, Kuala LumpurGoogle Scholar
  12. 12.
    DOE (2000) Department of Environment Malaysia. A guide to air pollutant in Malaysia, (API). Ministry of Science, Technology and Environment, Kuala LumpurGoogle Scholar
  13. 13.
    Ghazali NA, Ramli NA, Yahaya AS, Md Yusof NFF, Sansuddin N, Al Madhoun W (2010) Transformation of nitrogen dioxide into ozone and prediction of ozone concentrations using multiple linear regression techniques. Environ Monit Assess 165(1):475–489CrossRefGoogle Scholar
  14. 14.
    Liu CM, Liu SC (1991) A study of the winter surface ozone in Taipei. J Meteorol Soc Jpn Ser. II, 69(2):161–169CrossRefGoogle Scholar
  15. 15.
    Marković DM, Marković DA, Jovanović A, Lazić L, Mijić Z (2008) Determination of O3, NO2, SO2, CO and PM10 measured in Belgrade urban area. Environ Monit Assess 145(1–3):349–359CrossRefGoogle Scholar
  16. 16.
    Masseran N, Razali AM (2016) Modeling the wind direction behaviors during the monsoon seasons in Peninsular Malaysia. Renew Sustain Energy Rev 56:1419–1430CrossRefGoogle Scholar
  17. 17.
    McNaught AD, Wilkinson A (1997) IUPAC. In: Compendium of chemical terminology, 2nd edn, (the BGold Book). Blackwell Scientific Publications, OxfordGoogle Scholar
  18. 18.
    Ramli NA, Ghazali NA, Yahaya AS (2010) Diurnal fluctuations of ozone concentrations and its precursors and prediction of ozone using multiple linear regressions. Malays J Environ Manag 11(2):57–69Google Scholar
  19. 19.
    Tayeh SM, Ramli NA (2012) High particulate events in Southeast Asia and their impacts. In: The 4th international engineering conference—towards engineering of 21st century, International University of Gaza, pp 1–12Google Scholar
  20. 20.
    Tong L, Zhang H, Yu J, He M, Xu N, Zhang J, Qian F, Feng J, Xiao H (2017) Characteristics of surface ozone and nitrogen oxides at urban, suburban and rural sites in Ningbo, China. Atmos Res 187:57–68CrossRefGoogle Scholar
  21. 21.
    Venkanna R, Nikhil GN, Rao TS, Sinha PR, Swamy YV (2015) Environmental monitoring of surface ozone and other trace gases over different time scales: chemistry, transport and modelling. Int J Environ Sci Technol 12(5):1749–1758CrossRefGoogle Scholar
  22. 22.
    World Bank Group (1998) Pollution prevention and abatement handbook, 1998: toward cleaner production. World Bank Publications. World Bank Group, Washington, D.C. http://documents.worldbank.org/curated/en/758631468314701365/Pollution-prevention-and-abatement-handbook-1998-toward-cleaner-production

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Syabiha Shith
    • 1
    Email author
  • Leong Weng Woh
    • 1
  • Nor Azam Ramli
    • 1
  • Maisarah Sulaiman
    • 1
  • Nur Baitul Izati Rasli
    • 1
  • Nurul Adyani Ghazali
    • 2
  1. 1.Environmental Assessment and Clean Air Research (EACAR), School of Civil EngineeringUniversiti Sains Malaysia (USM)Nibong TebalMalaysia
  2. 2.School of Marine EngineeringUniversiti Malaysia Terenganu (UMT)Kuala TerengganuMalaysia

Personalised recommendations