Abstract:
This thesis report an investigation of the diurnal variation and frequency analysis of a traffic related pollutant, carbon-monoxide (CO).with the aim to understand the underlying physical processes and the influence of emission sources on the variability of its concentrations. The CO concentration was measured with Lascar EL-USB CO portable data logger from 4 – 10, October 2013. The observed CO concentration was analyzed using R programming language (R statistical software package “Sapa”). Descriptive and exploratory analyses were done to examine the distribution of CO concentrations. Spectral analysis was also carried out to check for periodicities and diurnal variations that affect CO concentrations. It was discovered that the CO measurements at the study site is affected by diurnal variations. Cross Spectral analysis was also done to check for factors that significantly contribute to the variations in Carbon Monoxide Measurements. To achieve this coherence plots between CO and traffic count, wind speed and wind speed direction was examined. Traffic count showed the highest coherence with CO followed by wind speed. Correlation analysis was also carried out and it was discovered that traffic count had the highest correlation with Caron Monoxide concentration. A pairs plot made showed that the relationship between Carbon Monoxide and traffic count is positive indicating that as traffic count increases, Carbon Monoxide concentration increases.
The results obtained for CO reveal the important contributions of traffic and wind speed and direction. However, the spectrum signals at low frequencies are significantly different between the Co concentration measured thus stressing that diurnal variations of CO are influenced by different processes. Cross-spectrum analysis of carbon monoxide measured was performed against wind measurements and traffic counts which allowed us to identify the contribution of short-range transport over a period of about 6 days.
Thus, the spectrum and cross-spectrum analysis performed in this study reveal the distinct influence of local traffic emissions on the diurnal variation of CO fluctuations in the polluted urban area. The methodology shows to be a powerful tool for the analysis of the causes of air pollution.
