Skip to main content

Advertisement

SpringerLink
Log in

Air quality pollutants and their relationship with meteorological variables in four suburbs of Greater Sydney, Australia

  • Published:
Air Quality, Atmosphere & Health Aims and scope Submit manuscript

Abstract

Meteorological variability plays a pivotal role in ambient air pollution. An in-depth analysis of air pollutants including meteorological variables in four suburbs of greater Sydney, Australia, was carried out for a continuous period of 24 months from January 2016 to 2018. Results revealed significant air quality problems with seasonal trends, for all six pollutants, in all suburbs. Maximum 24-h average PM10 concentrations for the four suburbs were 49.4, 55.3, 74.0 and 102.8 μg/m3 demonstrating severe PM10 air pollution events. NO2 concentrations exceeded national guideline limits and all four suburbs showed higher than recommended concentrations of O3. Generalised additive model analysis displayed varying dependencies between air pollutants and meteorological variables influenced by season and location. Different plots were used to interpret data in terms of meteorological variables. Generally, easterly and southerly winds led to the highest average concentrations of air pollutants for all suburbs. Extremes in air quality pollution concentrations were related to east and west winds and higher wind speeds (4–8 m/s). Wide variations existed in air pollutants between the 10th and 95th percentile values, especially PM10. Minimum and maximum concentration of all analysed pollutants occurred during low temperatures (11.7–18.4 °C) with the exception of ozone favouring higher temperatures (24–38 °C) during hotter months. Results show pollution formation varies in different seasons and suburbs, in relation to meteorological variables. This study can be used to mitigate, improve prediction and forecast accuracy of air pollution. Such studies open the possibilities to explore the effects of air quality and its impact on public health.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • 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):53–64

    Article  CAS  Google Scholar 

  • Begum BA, Biswas SK, Hopke PK, Cohen DD (2006) Multi-element analysis and characterization of atmospheric particulate pollution in Dhaka. Aerosol Air Qual Res 6(4):334–359

    Article  CAS  Google Scholar 

  • Cao C, Zheng S, Singh RP (2014) Characteristics of aerosol optical properties and meteorological parameters during three major dust events (2005–2010) over Beijing, China. Atmos Res 150:129–142

    Article  CAS  Google Scholar 

  • Carslaw DC, Ropkins K (2012) Openair—an R package for air quality data analysis. Environ Model Softw 27:52–61

    Article  Google Scholar 

  • Gong J, Hu Y, Liu M, Bu R, Chang Y, Li C, Wu W (2015) Characterization of Air Pollution Index and Its Affecting Factors in Industrial Urban Areas in Northeastern China. Pol J Environ 24:4

    Google Scholar 

  • Han S, Bian H, Feng Y, Liu A, Li X, Zeng F, Zhang X (2011) Analysis of the relationship between O3, NO and NO2 in Tianjin, China. Aerosol Air Qual Res 11(2):128–139

    Article  Google Scholar 

  • Han L, Zhou W, Li W, Meshesha DT, Li L, Zheng M (2015) Meteorological and urban landscape factors on severe air pollution in Beijing. J Air Waste Manage Assoc 65(7):782–787

    Article  Google Scholar 

  • Islam MM, Afrin S, Ahmed T, Ali MA (2015) Meteorological and seasonal influences in ambient air quality parameters of Dhaka city. J Civ Eng 43(1):67–77

    Google Scholar 

  • Jacob DJ, Winner DA (2009) Effect of climate change on air quality. Atmos Environ 43(1):51–63

    Article  CAS  Google Scholar 

  • Ji H, Wang QG, Yu Y, Lu Y, Qian X (2019) How have the characteristics of air quality in a typical large Chinese city changed between 2011 and 2017? Air Qual Atmos Health 12(4):401–410

    Article  CAS  Google Scholar 

  • Kayes I, Shahriar SA, Hasan K, Akhter M, Kabir MM, Salam MA (2019) The relationships between meteorological parameters and air pollutants in an urban environment. Glob J Environ Sci Manag 5(3):265–278

    CAS  Google Scholar 

  • Li J, Yang W, Wang Z, Chen H, Hu B, Li J, Sun Y, Huang Y (2014) A modeling study of source–receptor relationships in atmospheric particulate matter over Northeast Asia. Atmos Environ 91:40–51

    Article  CAS  Google Scholar 

  • Manju A, Kalaiselvi K, Dhananjayan V, Palanivel M, Banupriya GS, Vidhya MH, Panjakumar K, Ravichandran B (2018) Spatio-seasonal variation in ambient air pollutants and influence of meteorological factors in Coimbatore, Southern India. Air Qual Atmos Health 11(10):1179–1189

    Article  CAS  Google Scholar 

  • Megaritis AG, Fountoukis C, Charalampidis PE, Denier Van Der Gon HAC, Pilinis C, Pandis SN (2014) Linking climate and air quality over Europe: effects of meteorology on PM 2.5 concentrations. Atmos Chem Phys 14(18):10283–10298

    Article  Google Scholar 

  • Miao Y, Guo J, Liu S, Liu H, Zhang G, Yan Y, He J (2017) Relay transport of aerosols to Beijing-Tianjin-Hebei region by multi-scale atmospheric circulations. Atmos Environ 165:35–45

    Article  CAS  Google Scholar 

  • New South Wales Department of Planning, Industry and Environment (NSWDPEI) – Office of Environment and Heritage (OEH), Monitoring air quality (2019) https://www.environment.nsw.gov.au/topics/air/monitoring-air-quality

  • Pearce JL, Beringer J, Nicholls N, Hyndman RJ, Tapper NJ (2011) Quantifying the influence of local meteorology on air quality using generalized additive models. Atmos Environ 45(6):1328–1336

    Article  CAS  Google Scholar 

  • Pirhadi M, Mousavi A, Taghvaee S, Shafer MM, Sioutas C (2020) Semi-volatile components of PM2. 5 in an urban environment: volatility profiles and associated oxidative potential. Atmos Environ 117197:223

    Google Scholar 

  • R Development Core Team R.F.F.S.C (2011) R: a language and environment for statistical computing

  • Ran L, Zhao C, Geng F, Tie X, Tang X, Peng L, Zhou G, Yu Q, Xu J, Guenther A (2009) Ozone photochemical production in urban Shanghai, China: analysis based on ground level observations. J Geophys Res Atmos 114(D15)

  • Rashki A, Rautenbach CD, Eriksson PG, Kaskaoutis DG, Gupta P (2013) Temporal changes of particulate concentration in the ambient air over the city of Zahedan, Iran. Air Qual Atmos Health 6(1):123–135

    Article  CAS  Google Scholar 

  • Ravindra K, Rattan P, Mor S, Aggarwal AN (2019) Generalized additive models: building evidence of air pollution, climate change and human health. Environ Int 132:104987

    Article  CAS  Google Scholar 

  • Thompson ML, Reynolds J, Cox LH, Guttorp P, Sampson PD (2001) A review of statistical methods for the meteorological adjustment of tropospheric ozone. Atmos Environ 35(3):617–630

    Article  Google Scholar 

  • Tian G, Qiao Z, Xu X (2014) Characteristics of particulate matter (PM10) and its relationship with meteorological factors during 2001-2012 in Beijing. Environ Pollut 192:266–274

    Article  CAS  Google Scholar 

  • Tu J, Xia ZG, Wang H, Li W (2007) Temporal variations in surface ozone and its precursors and meteorological effects at an urban site in China. Atmos Res 85(3-4):310–337

    Article  CAS  Google Scholar 

  • Wood SN (2006) Generalized additive models: an introduction with R. Chapman and Hall/CRC Press, London

    Book  Google Scholar 

  • Yuan Q, Yang L, Dong C, Yan C, Meng C, Sui X, Wang W (2014) Particle physical characterization in the Yellow River Delta of Eastern China: number size distribution and new particle formation. https://doi.org/10.1007/s11869-014-0293-4

  • Zhang H, Wang Y, Hu J, Ying Q, Hu XM (2015) Relationships between meteorological parameters and criteria air pollutants in three megacities in China. Environ Res 140:242–254

    Article  CAS  Google Scholar 

  • Zu Y, Huang L, Hu J, Zhao Z, Liu H, Zhang H, Ying Q, Chen M (2017) Investigation of relationships between meteorological conditions and high PM 10 pollution in a megacity in the western Yangtze River Delta, China. Air Qual Atmos Health 10(6):713–724

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors would like to express their thanks to the Editor and two anonymous reviewers whose comments have helped to improve the paper notably.

Author information

Authors and Affiliations

  1. Cumberland Council, 16 Memorial Avenue, P.O. Box 42, Merrylands, NSW, 2160, Australia

    Khaled Haddad

  2. Family First Chiropractic, Sydney, NSW, Australia

    Nicoletta Vizakos

Authors
  1. Khaled Haddad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nicoletta Vizakos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Khaled Haddad.

Ethics declarations

Competing interests

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Highlights

• Assess impacts of meteorological variables on air quality pollutants

• Assessed temporal variations of air pollutants and meteorological variables

• GAMs used to assess dependency of air pollutants on meteorological variables

• Extremes of pollutants were assessed in relation to 10th and 95th percentiles

• Air pollutant min and max were assessed by trend level and percentile rose plots

Electronic supplementary material

ESM 1

(DOCX 3668 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Haddad, K., Vizakos, N. Air quality pollutants and their relationship with meteorological variables in four suburbs of Greater Sydney, Australia. Air Qual Atmos Health 14, 55–67 (2021). https://doi.org/10.1007/s11869-020-00913-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11869-020-00913-8

Keywords

Search

Navigation