Sun Zhaobin, An Xingqin, Tao Yan, Hou Qing
Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing 100081, China.
BMC Public Health. 2013 Sep 27;13:891. doi: 10.1186/1471-2458-13-891.
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.
评估PM10污染（直径小于10微米的颗粒物）对健康的不利影响对于保护人类健康和制定污染控制政策非常重要。人群暴露估计是制定暴露数据以定量评估有害PM10污染的第一步。
在本文中，我们使用空间分辨率为0.01°×0.01°的网格上的空间插值方法来估计PM10浓度。基于2000年准确的人口数据，利用地理信息系统对监测站的PM10浓度数据进行空间插值。然后，将插值后的人口层与插值后的PM10浓度层叠加，并计算人群暴露水平。结合PM10与健康终点之间的暴露-反应函数，分析PM10污染对健康不利影响的经济成本。
结果表明，兰州市区人口分布呈狭长带状，西固、城关和七里河三区存在较大的人口空间梯度。我们选择阈值浓度C0为：0微克/立方米（无有害健康影响）、20微克/立方米（世界卫生组织推荐）和50微克/立方米（中国国家一级标准）来计算超额发病病例。对于这三种情况，PM10污染相关不良健康影响的经济成本相对于GDP的比例分别为0.206%、0.194%和0.175%。还分析了2000年气象因素对PM10浓度的影响。春季沙尘暴天气、冬季逆温层和夏季降水是与PM10浓度变化相关的重要因素。
按暴露水平划分的人口分布表明，大多数人生活在污染地区。随着评估标准的提高，PM10导致的呼吸道疾病的经济损害要大得多。兰州城市居民的健康影响不容忽视。政府需要找到更好的方法来平衡居民健康与经济发展。并在制定最终政策前权衡利弊。
