SPATIOTEMPORAL OF NITROGEN DIOXIDE (NO2) CONCENTRATION IN THE URBAN ENVIRONMENT OF KLANG VALLEY, MALAYSIA
DOI:
https://doi.org/10.21837/pm.v22i33.1559Keywords:
Air Quality, NO2 Concentration, Spatiotemporal Analysis, Man-Kendall Statistical Analysis, Interpolation Technique GIS, Klang Valley, MalaysiaAbstract
The high concentration of nitrogen dioxide (NO2) directly results in Klang Valley’s air quality deterioration, causing a public health risk. This study was conducted to analyse the daily-averaged and annual concentration of nitrogen dioxide (NO2) on a spatial-temporal scale at five continuous monitoring stations under the Department of Environment (DOE) in Klang Valley, namely, Klang, Shah Alam, Petaling Jaya, Kajang, and Cheras from 2000 to 2009 using Man-Kendall statistical analysis and interpolation technique in Geographic Information System (GIS). The result clearly showed that the Petaling Jaya station was identified as the most polluted compared to other stations, with an average concentration of more than 0.050 ppm every year and reaching the maximum concentration of 0.069 ppm where the mean was 0.030 in 2001. Based on the p-value derived from the Mann-Kendall statistical analysis, the Klang, Petaling Jaya, Shah Alam, and Cheras stations recorded a significant trend with p-values < 0.05 at 0.0001 and 0.020, respectively. The annual concentration of NO2 in all the stations was in the range of 0.015 to 0.04 ppm from 2004 to 2009, compared to 0.005 to 0.01 ppm from 2000 to 2003. The highest annual-averaged NO2 concentration was reported at the Petaling Jaya station between 0.035 and 0.004 ppm for all years except 2007 and 2009 when concentrations were in the 0.03 to 0.035 ppm. Notably, the Petaling Jaya station had the highest annual NO2 concentration, which ranged from 0.025 to 0.04 ppm due to emissions from motor vehicles. The major pressure on road infrastructure was recognised, mainly a lack of space to accommodate the effect of the maximum density of motor vehicles and traffic, resulting in traffic congestion in the city centre.
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