Temporal analysis of air pollution and its relationship with meteorological parameters in Bahrain, 2006–2012

Original Paper


The objective of this paper is to analyze temporal and seasonal trends of air pollution in Bahrain between 2006 and 2012 by utilizing datasets from five air quality monitoring stations. The non-parametric and robust Theil-Sen approach is employed to study quantitatively temporal variations of particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3). The calculated annual concentrations for PM10 and PM2.5 in Bahrain were substantially higher than recommended World Health Organization (WHO) guideline standards. Results showed increasing trends for PM10, PM2.5, and SO2 whereas O3 and its precursor NO2 showed decreasing behavior. The general increase in air pollution trends is in agreement with prediction of air pollution models for Middle East region due to economic growth, industrialization, and urbanization. The significances of long-term trends were examined. Additional to actual (unadjusted) trends, meteorological adjusted (deseasonalized) trends and seasonal trends were quantified. The box-plot analysis visually illustrated monthly variations of key air pollutants. It showed that only PM10 and PM2.5 exhibited seasonal pattern, and their concentrations increased during summer and decreased during winter. The effects of ambient air temperature, relative humidity, wind speed, and rainfall on particulate matter (PM) concentrations were further investigated. The Spearman correlation coefficient results demonstrated significant negative correlation between relative humidity and PM concentrations (− 0.595 for PM10 and − 0.526 for PM2.5) while significant positive correlation was observed between temperature and PM concentrations (0.420 for PM10 and 0.482 for PM2.5).


Air quality monitoring Arabian Peninsula Long-term trend analysis Particulate matter Seasonal variations Theil-Sen approach 



Any opinion, findings, conclusions, or recommendations expressed herein are those of the authors. They are grateful to the Supreme Council for Environment (SCE) for kindly providing ambient air monitoring data. They are grateful to Climate and Observation Section in the Meteorological Directorate of Bahrain for kindly providing meteorological data.


  1. Al-Anzi B, Abusam A, Khan A (2016) Evaluation of temporal variations in ambient air quality at Jahra using multivariate techniques. Environ Technol Innova 5:225–232. CrossRefGoogle Scholar
  2. Alghamdi MA, Khoder M, Harrison RM, Hyvärinen A-P, Hussein T, Al-Jeelani H, Abdelmaksoud AS, Goknil MH, Shabbaj II, Almehmadi FM, Lihavainen H, Hämeri K (2014) Temporal variations of O3 and NOx in the urban background atmosphere of the coastal city Jeddah, Saudi Arabia. Atmos Environ 94:205–214. CrossRefGoogle Scholar
  3. Atkinson R (2000) Atmospheric chemistry of VOCs and NOx. Atmos Environ 34(12-14):2063–2101. CrossRefGoogle Scholar
  4. Bahrain Census, (2010). Central Informatics Organization, Kingdom of Bahrain, downloaded February 2015,
  5. Bhaskar BV, Mehta VM (2010) Atmospheric particulate pollutants and their relationship with meteorology in Ahmedabad. Aerosol Air Qual Res 10:301–315Google Scholar
  6. Boubel RW, Vallero D, Fox DL, Turner B, Stern AC (1994) Fundamentals of air pollution, 3rd edn. Elsevier, San DiegoGoogle Scholar
  7. BSNC, Bahrain’s Second National Communication to UNFCCC (2012) Public Commission for the Protection of Marine Resources. Environment and Wildlife, Kingdom of Bahrain downloaded July 2017, Google Scholar
  8. Cao H, Amiraslani F, Liu J, Zhou N (2015) Identification of dust storm source areas in West Asia using multiple environmental datasets. Sci Total Environ 502:224–235. CrossRefGoogle Scholar
  9. Carslaw D, Ropkins K (2012) openair—an R package for air quality data analysis. Environ Model Softw 27–28:52–61CrossRefGoogle Scholar
  10. Curtis L, Rea W, Smith-Willis P, Fenyves E, Pan Y (2006) Adverse health effects of outdoor air pollutants. Environ Int 32(6):815–830. CrossRefGoogle Scholar
  11. Draxler R, Gillette D, Kirkpatrick J, Heller J (2001) Estimating PM10 air concentrations from dust storms in Iraq, Kuwait and Saudi Arabia. Atmos Environ 35(25):4315–4330. CrossRefGoogle Scholar
  12. Elagib N, Abdu A (1997) Climate variability and aridity in Bahrain. J Arid Environ 36(3):405–419. CrossRefGoogle Scholar
  13. Farahat A, El-Askary H, Adetokunbo P, Fuad AT (2016) Analysis of aerosol absorption properties and transport over North Africa and the Middle East using AERONET data. Ann Geophys 34(11):1031–1044. CrossRefGoogle Scholar
  14. Givehchi R, Arhami M, Tajrishy M (2013) Contribution of the middle eastern dust source areas to PM10 levels in urban receptors: case study of Tehran, Iran. Atmos Environ 75:287–295. CrossRefGoogle Scholar
  15. Goudie AS (2009) Dust storms: recent developments. J Environ Manag 90(1):89–94. CrossRefGoogle Scholar
  16. Goudie AS, Middleton NJ (2006) Desert dust in the global system. Springer, HeidelbergGoogle Scholar
  17. Hamdi H, Sbia R, Shahbaz M (2014) The nexus between electricity consumption and economic growth in Bahrain. Econ Model 38:227–237. CrossRefGoogle Scholar
  18. Hess A, Iyer H, Malm W (2001) Linear trend analysis: a comparison of methods. Atmos Environ 35(30):5211–5222. CrossRefGoogle Scholar
  19. Karar K, Gupta AK (2006) Seasonal variations and chemical characterization of ambient PM10 at residential and industrial sites of an urban region of Kolkata (Calcutta), India. Atmos Res 81(1):36–53. CrossRefGoogle Scholar
  20. Karimi N, Moridnejad A, Golian S, Samani JMV, Karimi D, Javadi S (2012) Comparison of dust source identification techniques over land in the Middle East region using MODIS data. Can J Remote Sens 38(5):586–599. CrossRefGoogle Scholar
  21. Khamdan S, Al Madany I, Buhussain E (2009) Temporal and spatial variations of the quality of ambient air in the Kingdom of Bahrain during 2007. Environ Monit Assess 154(1–4):241–252. CrossRefGoogle Scholar
  22. Klimont Z, Smith S, Cofala J (2013) The last decade of global anthropogenic sulfur dioxide: 2000–2011 emissions. Environ Res Lett 8(1):014003. CrossRefGoogle Scholar
  23. Kobza J, Geremek M (2017) Do the pollution related to high-traffic roads in urbanized areas pose a significant threat to the local population? Environ Monit Assess 189(1):33. CrossRefGoogle Scholar
  24. Lelieveld J, Hoor P, Jöckel P, Pozzer A, Hadjinicolaou P, Cammas JP, Beirle S (2009) Severe ozone air pollution in the Persian Gulf region. Atmos Chem Phys 9(4):1393–1406. CrossRefGoogle Scholar
  25. Madany I, Danish S, Al-Hussaini A (1993) Spatial and temporal patterns in nitrogen dioxide concentrations in a hot desert region. Atmos Environ 27A(15):2385–2391CrossRefGoogle Scholar
  26. McLinden C, Fioletov V, Shephard M, Krotkov N, Li C, Martin RV, Moran M, Joiner J (2016) Space-based detection of missing sulfur dioxide sources of global air pollution. Nat Geosci 9(7):496–500. CrossRefGoogle Scholar
  27. Melkonyan A, Kuttler W (2012) Long-term analysis of NO, NO2 and O3 concentrations in North Rhine-Westphalia, Germany. Atmos Environ 60:316–326. CrossRefGoogle Scholar
  28. Munir S, Habeebullah TM, Seroji AR, Gabr SS, Mohammed AM, Morsy EA (2013) Quantifying temporal trends of atmospheric pollutants in Makkah (1997–2012). Atmos Environ 77:647–655. CrossRefGoogle Scholar
  29. Munir S, Gabr S, Habeebullah TM, Janajrah MA (2016) Spatiotemporal analysis of fine particulate matter (PM2.5) in Saudi Arabia using remote sensing data. Egypt J Remote Sensing Space Sci 19(2):195–205. CrossRefGoogle Scholar
  30. Notaro M, Alkolibi F, Fadda E, Bakhrjy F (2013) Trajectory analysis of Saudi Arabian dust storms. J Geophys Res Atmos 118(12):6028–6043. CrossRefGoogle Scholar
  31. OECD (2016). The economic consequences of outdoor air pollution, OECD Publishing, Paris.
  32. Roy S, Hegde M, Madras G (2009) Catalysis for NOx abatement. Appl Energy 86(11):2283–2297. CrossRefGoogle Scholar
  33. Schlink U, Dorling S, Pelikan E, Nunnari G, Cawley G, Junninen H, Greig A, Foxall R, Eben K, Chatterton T, Vondracek J (2003) A rigorous inter-comparison of ground-level ozone predictions. Atmos Environ 37(23):3237–3253. CrossRefGoogle Scholar
  34. Shao Y (2008) Physics and modelling of wind erosion. Springer, Atmospheric and Oceanographic Sciences LibraryGoogle Scholar
  35. Smirnov A, Holben BN, Dubovik O, O'Neill NT, Eck TF, Westphal DL, Goroch AK, Pietras C, Slutsker I (2002) Atmospheric aerosol optical properties in the Persian Gulf. J Atmos Sci 59(3):620–634.<0620:AAOPIT>2.0.CO;2 CrossRefGoogle Scholar
  36. Tsiouri V, Kakosimos KE, Kumar P (2015) Concentrations, sources and exposure risks associated with particulate matter in the Middle East area—a review. Air Qual Atmos Health 8(1):67–80. CrossRefGoogle Scholar
  37. WHO (World Health Organization) (2005). WHO air quality guidelines for air quality for particulate matter ozone, nitrogen dioxide, and sulfur dioxide. Geneva, Switzerland, Downloaded in January 2015,
  38. WHO (World Health Organization) (2009). Global health risks: mortality and burden of disease attributable to selected major risks. Geneva, Switzerland, Downloaded in July 2017,
  39. Wise E, Comrie A (2005) Meteorologically adjusted urban air quality trends in the southwestern United States. Atmos Environ 39(16):2969–2980. CrossRefGoogle Scholar
  40. World Bank (2016). The cost of air pollution: strengthening the economic case for action. The World Bank & IHME, Washington DC, USA, Downloaded in April 2017,

Copyright information

© Saudi Society for Geosciences 2018

Authors and Affiliations

  • Majeed S. Jassim
    • 1
  • Gulnur Coskuner
    • 2
  • Said Munir
    • 3
  1. 1.Department of Chemical Engineering, College of EngineeringUniversity of BahrainIsa TownKingdom of Bahrain
  2. 2.Civil Engineering Programme, College of EngineeringWest Virginia University, Royal University for WomenRiffaKingdom of Bahrain
  3. 3.Department of Civil and Structural EngineeringThe University of SheffieldSheffieldUK

Personalised recommendations