Using emission estimates as exposure matrix: Respiratory Disease in Relation to Outdoor Air Pollution in Kanpur, UP, India

Background: Air quality in Kanpur, Uttar Pradesh, India, was poor during the first half of 2000’s, often showing daily PM levels in the range of hundreds of micrograms/m3. Air quality monitoring did not cover the whole city and all times, and information about potential health effects was missing. No health impact assessment was previously done. Yet it was clear that evidence for health effects of poor air quality needs to be gathered. Aim: We wanted to evaluate the effect of outdoor air pollution on respiratory disease in Kanpur. Methods: Available data were journal information on respiratory symptoms and hospital visits of patients of a local specialized hospital in 2006, and sporadic air quality monitoring results not covering the whole region. Emission inventory for SO2, NOx and PM10 was developed on a 1x1 km grid, and health information and exposure based on home address emission category were analyzed using logistic regression models. Results: The main sources of air pollution are industries (SO2 and NOx), domestic fuel burning (SO2, PM, NOx) and vehicles (NOx and PM). The emissions of PM per grid are strongly correlated to the emissions of SO2 and NOX. There is a strong correlation between visits to the hospital due to respiratory disease and emission strength in the area of residence. Conclusion: The results clearly indicate that appropriate health and environmental monitoring, actions to reduce emissions to air, and further studies that would allow assessing the development in health status are necessary. We have also shown that other exposure metric than air concentration can be used in the absence of air quality data, to demonstrate the clear effect of pollution on health.