Application of Statistical Methods to Assess Carbon Monoxide Pollution Variations within an Urban Area


In recent years there have been considerable new legislation and efforts by vehicle manufactures aimed at reducing pollutant emission to improve air quality in urban areas. Carbon monoxide is a major pollutant in urban areas, and in this study we analyze monthly carbon monoxide (CO) data from Valencia City, a representative Mediterranean city in terms of its structure and climatology. Temporal and spatial trends in pollution were recorded from a monitoring net- work that consisted of five monitoring sites. A multiple linear model, incorporating meteorological parameters, annual cycles, and random error due to serial correlation, was used to estimate the temporal changes in pollution. An analysis performed on the meteorologically adjusted data reveals a significant decreasing trend in CO concentrations and an annual seasonal cycle. The model parameters are estimated by applying the least-squares method. The standard error of the parameters is determined while taking into account the serial correlation in the residuals. The decreasing trend im- plies to a certain extent an improvement in the air quality of the study area. The seasonal cycle shows variations that are mainly associated with traffic and meteorological patterns. Analysis of the stochastic spatial component shows that most of the intersite covariances can be analyzed using an exponential variogram model.

Share and Cite:

C. Capilla, "Application of Statistical Methods to Assess Carbon Monoxide Pollution Variations within an Urban Area," International Journal of Geosciences, Vol. 3 No. 5A, 2012, pp. 885-890. doi: 10.4236/ijg.2012.325090.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] E. P. Smith, S. Rheem and G.I. Holtzman, “Multivariate Assessment of Trend in Environmental Variables,” In: G. P. Patil and C. R. Rao, Eds., Multivariate Environmental Statistics, Elsevier Science Publishers, North-Holland, 1993, pp. 489-507.
[2] P. Brimblecombe, “Air Composition and Chemistry,” 2nd Edition, Cambridge University Press, Cambridge, 1995.
[3] M. Shahgedanova, T. P. Burt and T. D. Davies, “Carbon Monoxide and Nitrogen Oxides Pollution in Moscow,” Water Air and Soil Pollution, Vol. 112, No. 1-2, 1999, pp. 107-131. doi:10.1023/A:1005043916123
[4] M. T. Fernandez-Jiménez, A. Climent-Font, and J. L. Sánchez-Antón, “Long Term Atmospheric Pollution Study at Madrid City (Spain),” Water, Air and Soil Pollution, Vol. 142, No. 1-4, 2003, pp. 243-260. doi:10.1023/A:1022011909134
[5] V. Kimmel and M. Kaasik, “Assessment of Urban Air Quality in South Estonia by Simple Measures,” Environmental Modelling and Assessment, Vol. 8, No. 1, 2003, pp. 47-53. doi:10.1023/A:1022449831456
[6] A. Chaloulakou, P. Kassomenos, G. Grivas and N. Spyrellis, “Particulate Matter and Black Smoke Levels in Central Athens, Greece,” Environment International, Vol. 31, No. 5, 2005, pp. 651-659. doi:10.1016/j.envint.2004.11.001
[7] L. Zhao, X. Wang, Q. He, H. Wang, G. Sheng, L. Y. Chan, J. Fu, and D. R. Blake, “Exposure to Hazardous Volatile Organic Compounds, PM10 and CO While Walking Along the Streets in Urban Guangzou, China,” Atmospheric Environment, Vol. 38, No. 25, 2004, pp. 6177-6184. doi:10.1016/j.atmosenv.2004.07.025
[8] J. Beauchamp, A. Wisthaler, W. Grabmer, C. Neuner, A. Weber and A. Hansel, “Short Term Measurements of CO, NO, NO2, Organic Compounds and PM10 at a Motorway Location in an Austrian Valley,” Atmospheric Environment, Vol. 38, No. 16, 2004, pp. 2511-2522. doi:10.1016/j.atmosenv.2004.01.032
[9] Development Core Team, “A Language and Environment for Statistical Computing,” Foundation for Statistical Computing, Vienna, 2011.
[10] W. R. Ott, “A Physical Explanation of the Lognormality of Pollutant Concentrations,” Journal of the Air and Waste Management Association, Vol. 40, No. 10, 1990, pp. 1378-1383. doi:10.1080/10473289.1990.10466789
[11] C. K. Lee, “Multifractal Characteristics in Air Pollutant Concentration Time Series,” Water, Air and Soil Pollution, Vol. 135, No. 1-4, 2002, pp. 389-409.doi:10.1023/A:1014768632318
[12] R. Virgarzan, and B. Taylor, “Trend Analysis of Ground Level Ozone in the Greater Vancouver/Fraser Valley Area of British Columbia,” Atmospheric Environment, Vol. 37, No.16, 2003, pp. 2159-2171. doi:10.1016/S1352-2310(03)00158-4
[13] T.A., Rao, and I.G. Zurbenko, “Detecting and Tracking Changes in Ozone Air Quality,” Journal of the Air and Waste Management Association, Vol. 44, No. 9, 1994, pp. 1089-1092. doi:10.1080/10473289.1994.10467303
[14] N. R. Draper, and H. Smith, “Applied Regression Analysis,” 3rd Edition, Wiley, New York, 1998.
[15] A. Sirois, “WMO/EMEP Workshop on Advanced Statistical Methods and Their Application to Air Quality Data Sets,” Report No. 133, Word Meteorological Organization, Geneve, 1998.
[16] N. A. C. Cressie, “Statistics for Spatial Data,” Revised Edition, Wiley, New York, 1993.
[17] O. Berke, “Estimation and Prediction in the Spatial Linear Model,” Water, Air and Soil Pollution, Vol. 110, No. 3-4, 1999, pp. 215-237. doi:10.1023/A:1005035509922
[18] N. A. C. Cressie, “Fitting Variogram Models by Weighted Least Squares,” Mathematical Geology, Vol. 17. No. 5, 1985, pp. 563-586. doi:10.1007/BF01032109

Copyright © 2021 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.