Long-term spatial and temporal variability of ambient carbon monoxide in Urmia, Iran

One of the pillars of epidemiologic research on the long-term health effects of air pollution is to estimate the chronic exposures over space and time. In this study, we aimed to measure the intraurban ambient carbon monoxide (CO) concentrations within Urmia city in Iran, and to build a model within the geographic information system (GIS) to estimate the annual and seasonal means anywhere within the city. We collected more than 5,000 measurements from 53 locations during July 2010 to July 2011 in four seasons to calculate the annual and seasonal means in Urmia. The Universal Kriging was used to predict the spatial and seasonal concentrations of CO. The annual mean and annual peak CO concentrations were respectively 2.5 and 4.4 ppm. The results of the spatial analysis showed that the north-eastern parts of the city were more polluted than the other areas. The mean and peak seasonal spatial patterns were consistent over time. This is the first study that monitored and predicted the long-term CO concentrations with a dense measurement network in Urmia, providing a foundation for future epidemiological studies on the health effects of air pollution. The spatial estimates can also be used for a variety of other purposes, such as evidence-based air quality management and urban planning. Overall, the CO levels in Urmia were lower than the values recommended by the World Health Organization. However, further research is required on other important pollutants, such as particulate matter, nitrogen dioxide, air toxics and so forth.

Keywords:

Air pollution , carbon monoxide variability , intra-urban , long-term , spatial