Map Malaysia 2009
Particulate Matter Air Quality Mapping Using
Interpolation Technique
N Othman
Lecturer
Universiti Sains Malaysia, Malaysia
M R Mustapha
Student
Universiti Sains Malaysia, Malaysia
[email protected]
H S Lim
Lecturer
Universiti Sains Malaysia, Malaysia
[email protected]
M Z Mat Jafri
Lecturer
Universiti Sains Malaysia, Malaysia
[email protected]
ABSTRACT
Air pollution is a major concern in many large cities in developed or developing countries around the world. Presently practitioners generate maps of concentration in pollutants by mean of interpolating and extrapolation methods, such as thin plate or Kriging methods. Those methods are familiar and their quality depends on the number of input parameters. Others tools by modeling pollutant dispersion exist but turn to be insufficient and are not validated yet. This paper presents a methodology for the mapping of pollutant concentrations over Makkah, Mina and Arafah using three interpolation techniques namely, Kriging Interpolation, Thin Plate Spline Interpolation and Natural Neighbour Interpolation for particulate matters of size less than 10 micron (PM10). The PM10 data were collected using a handheld DustTrak Meter 8520 and the locations of each point were determined using a handheld Global Positioning System (GPS). This study indicated that Kriging Interpolation method gave highest accuracy based on the highest R2 and lowest RMSE values value for mapping air pollution levels. Kriging Interpolation technique can be used accurately and precisely mapped PM10 concentration in Makkah, Mina and Arafah.
Introduction
In these recent years, urban air quality monitoring and forecasting has become an important issue for many environmental protection agency’s (EPA) around the world. Particulate matter (PM) is an important component of air pollution, having both long-term as well as short-term effects on human health such as cardiovascular, lung and skin diseases, which sometimes leads to premature death (Krewski et al., 2000; Pope et al., 2000; HEI, 2004; Pope and Dockery, 2006). Particulate matter consists of carbon and mineral bodies of different sizes, ranging in diameter from 0.001 to 100 ?m. The smaller the particles, the more the surface were they offer for other pollutants to be absorbed. Therefore smaller particles generally contain a higher amount of harmful compounds. Besides that, the fine particles enter deeper into the respiratory system where they are retained for a long time as well as their higher amount of toxic components makes that fine particles are of primary concern regarding health impacts. Air pollution cause by the PM is one of the major air quality issues in Saudi Arabia due to the desert area surrounding this country. Some meteorological conditions such as temperature inversions can slow down the removal of PM from the atmosphere thereby quickly degrading air quality. Anthropogenic and natural aerosols are recognized as significant atmospheric substances for the present and future climate changes.
This study will presents a methodology for the mapping of pollutant concentrations over Makkah, Mina and Arafah using three interpolation techniques namely, Kriging Interpolation, Thin Plate Spline Interpolation and Natural Neighbour Interpolation for particulate matters of size less than 10 micron (PM10). In this study, Kriging interpolation method gave better result for mapping air pollution levels in the present case based on the highest R2 and lowest RMSE value in Makkah, Mina and Arafah.
Study Area and data acquisition
The selected study area was an urban-desert area of Makkah, Mina and Arafah over Saudi Arabia. Figure 1 shows the study area of the Makkah, Saudi Arabia. Particulate matter (PM10) data over Makkah, Mina and Arafah were collected at the several selected locations around Makkah, Mina and Arafah as in Figure 1 between 9.00 a.m. to 11.00 a.m. on 19th January 2009 using dusttrak meter 8520 and their locations of each point were determined using a handheld GPS. This period of time can be described as off peak season which is not in Hajj season.
Approach and Methodology
Interpolation can be described as procedure of predicting the value of attribute at unsampled site from measurements made at location within the same area or region. Interpolation is necessary when the ground truth data do not cover the domain of interest completely.
In this study, interpolation model of PM10 generated using PCI Geomatica version 10.1.3 digital image processing software in all image-processing analysis. Therefore Kriging Interpolation, Thin Plate Spline Interpolation and Natural Neighbor interpolation were used for interpolation modeling between the sampling points in the table 1.
Burrough and McDonnell (1998) concluded that most interpolation techniques give similar results when data are; most interpolation techniques give similar results. When data are sparse, however, the assumption made about the underlying variation that has been sampled and the choice of method and its parameters can be critical if one is to avoid misleading results.
Table 1: shows the comparison of interpolation techniques.
Source: Based on Burrough and McDonnell 1998
Data analysis and results
A total of 25 sampling measurements were collected around Makkah, Mina and Arafah. Three interpolation techniques namely, Kriging Interpolation, Thin Plate Spline Interpolation and Natural Neighbour Interpolation were used for PM10 mapping over Makkah, Mina and Arafah area. The best of PM10 map concentration were generated using Kriging interpolation technique (Figure 2) which gave the highest R2 value =0.983 and the lowest RMSE values =7.5719 μg/m3. Ung, et al., (2001) and Patil, et al., (2003) also applied the interpolation technique in their studies for air quality mapping. Kriging uses a semivariogram, a measure of spatial correlation between two points, so the weights change according to the spatial arrangement of the samples. Unlike other estimation procedures investigated, Kriging provides a measure of the error or uncertainty of the estimated surface. In addition, Kriging will not produce edge-effects resulting from trying to force a polynomial to fit the data as with trend surface analysis.
In this study, high air pollution concentrations were recorded at several locations such as, (1) the construction site near the Masjid-Al-Haram and Jamrah-Al-Aqabah, as expected that the PM10 level to be high for the construction areas, (2) the open land at several areas around Arafah and (3) near the roadsides that recorded high PM10 levels due to emissions from vehicles.
For the accuracy analysis, ground truth data were divided into two groups; half of the number of PM10 samples were randomly selected for interpolation analysis to generate the air quality maps and the other half for accuracy analysis using the three different interpolation techniques, Kriging Interpolation, Thin Plate Spline Interpolation and Natural Neighbour Interpolation. The air quality values created by the interpolation techniques were then compared to the ground truth data and their accuracies (R2 and RMSE values) were noted. Kriging interpolation technique produced the highest accuracy based on the highest R2 and lowest RMSE values. The results of accuracy analysis produced by this study are shown in Table 2.
Table 2: R2 and RMSE values of the three different interpolation techniques
Conclusion
In this study, the Kriging Interpolation method gave better result for mapping air pollution levels in the present case based on the R2=0.983 and RMSE = 7.5719 value μg/m3. As conclusion, the Kriging Interpolation technique accurately and precisely mapped PM10 concentration in Makkah, Mina and Arafah.
Acknowledgements
This project was carried out using the Hajj Research Cluster USM grants. We would like to thank the technical staff that participated in this project. Thanks are extended to USM for support and encouragement.
References
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