Abstract
Spatial distribution modeling of CO in Tehran can lead to better air pollution management and control, and it is also suitable for exposure assessment and epidemiological studies. In this study MARS (Multi–variate Adaptive Regression Splines) is compared with typical interpolation techniques for spatial distribution modeling of hourly and daily CO concentrations in Tehran, Iran. The measured CO data in 2008 by 16 monitoring stations were used in this study. The Generalized Cross Validation (GCV) and Cross Validation techniques were utilized for the parameter optimization in the MARS and other techniques, respectively. Then the optimized techniques were compared based on the mean absolute of percentage error (MAPE). Although the Cokriging technique presented less MAPE than the Inverse Distance Weighting, Thin Plate Smooth Splines and Kriging techniques, MARS exhibited the least MAPE. In addition, the MARS modeling procedure is easy. Therefore, MARS has merit to be introduced as an appropriate method for spatial distribution modeling. The number of air pollution monitoring stations is very low (16 stations for 22 zones) and the distribution of stations is not suitable for spatial estimation, hence the level of errors was relatively high (more than 60%). Consequently, hourly and daily mapping of CO provides a limited picture of spatial patterns of CO in Tehran, but it is suitable for estimation of relative CO levels in different zones of Tehran. Hence, the map of mean annual CO concentration was generated by averaging daily CO distributions in 2008. It showed that the most polluted regions in Tehran are the central, eastern and southeastern parts, and mean annual CO concentration in these parts (zones 6, 12, 13,14 and 15) is between 4.2 and 4.6 ppm.
Highlights
In the last decades, the energy consumption, emission of air pollutants and number of poor air quality days has increased in cities because of increases in population in urban areas (Chan and Yao, 2008)
CO, one of the major air pollutants in Tehran, is mainly formed by primary combustion, in vehicle engines (Givehchi et al, 2013), and there is a direct relationship between CO emission and traffic flow and speed in Tehran (Rashidi and Massoudi, 1980)
The results showed that the Cokriging technique has better performance than the other studied typical interpolation techniques
Summary
The energy consumption, emission of air pollutants and number of poor air quality days has increased in cities because of increases in population in urban areas (Chan and Yao, 2008). Low quality fuels and the large number of old and poorly maintained vehicles are responsible for much of the pollutant emissions in Tehran (Abbaspour and Soltaninejad, 2004; Atash, 2007). The studies in Tehran showed that increased CO concentration can increase the allergenicity of pollen grains (Majd et al, 2004), daily admission in Tehran’s hospitals due to cardiovascular diseases (Hosseinpoor et al, 2005) and the total number of deaths due to respiratory and cardiovascular diseases and cancer (Abbaspour and Soltaninejad, 2004). It has been found that exposure to increased levels of CO during pregnancy may increase the risk of fetal abnormality (Ziaei et al, 2005)
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