Gaseous air pollution background estimation in urban, suburban, and rural environments

  • Mufreh S. Al-Rashidi
  • Mohamed F. Yassin
  • Nawaf S. Alhajeri
  • Marium J. Malek
Original Paper


There is a great demand for estimating the ambient air pollutant background concentrations in order to assess the effectiveness of different emission control strategies. In this paper, the background concentrations of four pollutants, namely sulfur dioxide (SO2), nitrogen oxides (NOx), carbon monoxide (CO), and ozone (O3) pollutants in urban, suburban, and rural environments were investigated using Kolmogorov–Zurbenko (KZ) filter technique. Air quality data from monitoring stations over a period of 4 years (2007–2010) was analyzed for three locations in Kuwait, namely urban, suburban, and rural. The spatial and temporal (daily, weekly, and monthly) variations of the four pollutants were analyzed. The results show that the levels of ambient air pollutant background concentrations were high in the urban site compared to suburban and rural area. The diurnal variation of SO2 concentration showed an early morning peak, while the diurnal variation of NOx concentration constituted has two peaks, one was in the early morning hours (5 to 8 a.m.) and the second was in nighttime hours (8 to 11 p.m.). These two peaks were observed at all three locations. The monthly background NOx concentration reached a maximum in winter and minimum in summer. Diurnal variation of CO concentration showed a similar trend to SO2 concentrations in all three locations. Because of the photochemical reactions that occur in the atmosphere, the background concentration of O3 showed an inverse relation with respect to background concentration of NOx.


Air pollution Kolmogorov–Zurbenko (KZ) filter Openair Meteorological conditions Urban, suburban, and rural environment 



The authors would like to thank Dr. Ali Al-Hemoud from Kuwait Institute for Scientific Research for his encouragement, valuable advice, and guidance in the writing of this research.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Arunachalam S., Valencia A., Akita Y., Serre M.L., Omary M., Garcia V., Isakov V. (2014) A method for estimating urban background concentrations in support of hybrid air pollution modeling for environmental health studies. Int. J. Environ. Res Public Health (2014), 11, 10518–10536Google Scholar
  2. Berkowicz R (2000) A simple model for urban background pollution. Environ Monit Assess 65(1/2):259–267. CrossRefGoogle Scholar
  3. Carslaw, D.C. (2012). The open-air manual open-source tools for analyzing air pollution data. Manual for version 0.7-0, King’s College, LondonGoogle Scholar
  4. Carslaw DC, Ropkins K (2012) Openair an R package for air quality data analysis. Environ Model Softw 27:52–61CrossRefGoogle Scholar
  5. Cosemans G, Panis LI, Mensink C (2005) How to determine urban background concentration from traffic flows in neighboring street canyons. In: Proceedings of the 10th int. conf. on harmonisation within atmospheric dispersion modelling for regulatory purposes, 206(210)Google Scholar
  6. Fiore AM, Oberman JT, Lin MY, Zhang L, Clifton OE, Jacob DJ, Naik V, Horowitz LW, Pinto JP, Milly GP (2014) Estimating North American background ozone in U.S. surface air with two independent global models: variability, uncertainties, and recommendations. Atmos Environ 96:284–300. CrossRefGoogle Scholar
  7. Henschel S, Querol X, Atkinson R, Pandolfi M, Zeka A, Tertre AL, Analitis A, Katsouyanni K, Chanel O, Pascal M, Bouland C, Haluza D, Medina S, Goodman PG (2013) Ambient air SO2 patterns in 6 European cities. Atmos Environ 79:236–247. CrossRefGoogle Scholar
  8. Kukkonen J, Partanen L, Karppinen A, Walden J, Kartastenp R, Aarnio P, Koskentalo T, Berkowicz R (2003) Evaluation of the OSPM model combined with an urban background model against the data measured in 1997 in Runeberg street, Helsinki. Atmos Environ 37(8):1101–1112. CrossRefGoogle Scholar
  9. Latif MT, Dominick D, Ahamad F, Khan MF, Juneng L, Hamzah FM, Nadzir MSM (2014) Long-term assessment of air quality from a background station on the Malaysian Peninsula. Sci Total Environ 482–483:336–348CrossRefGoogle Scholar
  10. Lefohn AS, Emery C, Shadwick D, Wernli H, Jung J, Oltmans SJ (2014) Estimates of background surface ozone concentrations in the United States based on model-derived source apportionment. Atmos Environ 84:275–288. CrossRefGoogle Scholar
  11. Lin W, Xu X, Ma Z, Zhao H, Liu X, Wang Y (2012) Characteristics and recent trends of sulfur dioxide at urban, rural, and background sites in North China: effectiveness of control measures. J Environ Sci 24(1):34–49. CrossRefGoogle Scholar
  12. Lindley SJ, Walsh T (2005) Inter-comparison of interpolated background nitrogen dioxide concentrations across Greater Manchester, UK. Atmos Environ 39(15):2709–2724. CrossRefGoogle Scholar
  13. McCarthy MC, Hafner HR, Montzka SA (2006) Background concentrations of 18 air toxics for North America. J. Air Waste Manage. Assoc. 56(1):3–11.
  14. McKendry, I.G., 2006. Background concentrations of PM2. 5 and ozone in British Columbia, Canada. British Columbia Ministry of Environment [Environmental Quality Branch]Google Scholar
  15. Meng Z-Y, Xu X-B, Wang T., Zhang X-Y, Yu X-L, Wang S-F, Lin W-L, Chen Y-Zd, Jiang Y-A, An X-Q (2010) Ambient sulfur dioxide, nitrogen dioxide, and ammonia at ten background and rural sites in China during 2007–2008 Atmospheric Environment44 (2010) 2625–2631Google Scholar
  16. Na C, Dong-Sheng JI, Jia-Shan C, Jin-Yuan X, Bo H, Yue-Si W, Hui W, Ze M (2014) Characteristics of gaseous pollutants at a regional background station in Southern China, Atmos. Oceanic Sci. Lett. 7(4):340–345
  17. Nielsen-Gammon JW, Tobin J, McNeel A, Li G (2005) A conceptual model for eight-hour ozone exceedances in Houston, Texas. Part I: background ozone levels in eastern Texas, Center for Atmospheric Chemistry and the Environment. Texas A&M University, USAGoogle Scholar
  18. Ortiz ST, Friedrich R (2013) A modeling approach for estimating background pollutant concentrations in urban areas. Atmos Pollut Res 4(2):147–156. CrossRefGoogle Scholar
  19. Parrish DD, Aikin KC, Oltmans SJ, Johnson BJ, Ives M, Sweeny C (2010) Impact of transported background ozone inflow on summertime air quality in a California ozone exceedance area. Atmos Chem Phys Discuss 10(6):16231–16276. CrossRefGoogle Scholar
  20. Pournazeri S, Tan S, Schulte N, Jing Q, Venkatram A (2014) A computationally efficient model for estimating background concentrations of NOx, NO2, and O3. Environ Model Softw 52:19–37. CrossRefGoogle Scholar
  21. Rashki A., W Rautenbach C.J. Eriksson P.G., Kaskaoutis D.G., Gupta P. (2013) Temporal changes of particulate concentration in the ambient air over the city of Zahedan, Iran, Air Qual Atmos Health, 6:123–135, 1, DOI:
  22. Rojas ALP, Venegas LE (2013) Upgrade of the DAUMOD atmospheric dispersion model to estimate urban background NO2 concentrations. Atmos Res 120–121:147–154CrossRefGoogle Scholar
  23. Shin HJ, Cho KM, Han JS, Kim JS, Kim YP (2012) The effects of precursor emission and background concentration changes on the surface ozone concentration over Korea. Aerosol Air Qual Res 12:93–103Google Scholar
  24. Stevenson, D. (2001). Global influences on future European tropospheric ozone. Proceedings from the Eighth European Symposium on the Physical–Chemical Behaviour of Atmospheric Pollutants 17–20 September 2001, Torino, ItalyGoogle Scholar
  25. Taiwo AM, Beddows DSC, Shi Z, Harrison RM (2014) Mass and number size distributions of particulate matter components: comparison of an industrial site and an urban background site. Sci Total Environ 475:29–38. CrossRefGoogle Scholar
  26. Tchepel O, Costa AM, Martins H, Ferreira J, Monteiro A, Miranda AI, Borrego C (2010) Determination of background concentrations for air quality models using spectral analysis and filtering of monitoring data. Atmos Environ 44(1):106–114. CrossRefGoogle Scholar
  27. Venegas LE., Mazzeo N.a. (2006) Modelling of urban background pollution in Buenos Aires City (Argentina), Environ Model Softw 21, 577–586, 4, DOI:
  28. Venegas LE, Mazzeo NA (2002) An evaluation of daumod model in estimating urban background concentrations. Water, Air, Soil Pollut: Focus 2(5/6):433–443. CrossRefGoogle Scholar
  29. Vingarzan R (2004) A review of surface ozone background levels and trends. Atmos Environ 38(21):3431–3442. CrossRefGoogle Scholar
  30. Wise EK, Comrie AC (2005) Extending the Kolmogorov–Zurbenko filter: application to ozone, particulate matter, and meteorological trends. J Air Waste Manage Assoc 55(8):1208–1216. CrossRefGoogle Scholar
  31. Zurbenko, I. 1986. The spectral analysis of time series. North-Holland Series in Statistics and ProbabilityGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2018

Authors and Affiliations

  • Mufreh S. Al-Rashidi
    • 1
  • Mohamed F. Yassin
    • 1
  • Nawaf S. Alhajeri
    • 2
  • Marium J. Malek
    • 1
  1. 1.Environment & Life Sciences Research CenterKuwait Institute for Scientific ResearchKuwait CityKuwait
  2. 2.Department of Environmental Technology Management, College for Life ScienceKuwait UniversityKuwait CityKuwait

Personalised recommendations