Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS
- Equal contributors
1 Beijing Meteorological Observatory, Beijing 100089, China
2 Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing 100081, China
3 College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
BMC Public Health 2013, 13:891 doi:10.1186/1471-2458-13-891Published: 27 September 2013
Evaluation of the adverse health effects of PM10 pollution (particulate matter less than 10 microns in diameter) is very important for protecting human health and establishing pollution control policy. Population exposure estimation is the first step in formulating exposure data for quantitative assessment of harmful PM10 pollution.
In this paper, we estimate PM10 concentration using a spatial interpolation method on a grid with a spatial resolution 0.01° × 0.01°. PM10 concentration data from monitoring stations are spatially interpolated, based on accurate population data in 2000 using a geographic information system. Then, an interpolated population layer is overlaid with an interpolated PM10 concentration layer, and population exposure levels are calculated. Combined with the exposure-response function between PM10 and health endpoints, economic costs of the adverse health effects of PM10 pollution are analyzed.
The results indicate that the population in Lanzhou urban areas is distributed in a narrow and long belt, and there are relatively large population spatial gradients in the XiGu, ChengGuan and QiLiHe districts. We select threshold concentration C0 at: 0 μg m-3 (no harmful health effects), 20 μg m-3 (recommended by the World Health Organization), and 50 μg m-3 (national first class standard in China) to calculate excess morbidity cases. For these three scenarios, proportions of the economic cost of PM10 pollution-related adverse health effects relative to GDP are 0.206%, 0.194% and 0.175%, respectively. The impact of meteorological factors on PM10 concentrations in 2000 is also analyzed. Sandstorm weather in spring, inversion layers in winter, and precipitation in summer are important factors associated with change in PM10 concentration.
The population distribution by exposure level shows that the majority of people live in polluted areas. With the improvement of evaluation criteria, economic damage of respiratory disease caused by PM10 is much bigger. The health effects of Lanzhou urban residents should not be ignored. The government needs to find a better way to balance the health of residents and economy development. And balance the pros and cons before making a final policy.