Allen Ryan W, Gombojav Enkhjargal, Barkhasragchaa Baldorj, Byambaa Tsogtbaatar, Lkhasuren Oyuntogos, Amram Ofer, Takaro Tim K, Janes Craig R
Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6 Canada.
Air Qual Atmos Health. 2013 Mar;6(1):137-150. doi: 10.1007/s11869-011-0154-3. Epub 2011 Aug 9.
Epidemiologic studies have consistently reported associations between outdoor fine particulate matter (PM) air pollution and adverse health effects. Although Asia bears the majority of the public health burden from air pollution, few epidemiologic studies have been conducted outside of North America and Europe due in part to challenges in population exposure assessment. We assessed the feasibility of two current exposure assessment techniques, land use regression (LUR) modeling and mobile monitoring, and estimated the mortality attributable to air pollution in Ulaanbaatar, Mongolia. We developed LUR models for predicting wintertime spatial patterns of NO and SO based on 2-week passive Ogawa measurements at 37 locations and freely available geographic predictors. The models explained 74% and 78% of the variance in NO and SO, respectively. Land cover characteristics derived from satellite images were useful predictors of both pollutants. Mobile PM monitoring with an integrating nephelometer also showed promise, capturing substantial spatial variation in PM concentrations. The spatial patterns in SO and PM, seasonal and diurnal patterns in PM, and high wintertime PM/PM ratios were consistent with a major impact from coal and wood combustion in the city's low-income traditional housing (ger) areas. The annual average concentration of PM measured at a centrally located government monitoring site was 75 μg/m or more than seven times the World Health Organization's PM air quality guideline, driven by a wintertime average concentration of 148 μg/m. PM concentrations measured in a traditional housing area were higher, with a wintertime mean PM concentration of 250 μg/m. We conservatively estimated that 29% (95% CI, 12-43%) of cardiopulmonary deaths and 40% (95% CI, 17-56%) of lung cancer deaths in the city are attributable to outdoor air pollution. These deaths correspond to nearly 10% of the city's total mortality, with estimates ranging to more than 13% of mortality under less conservative model assumptions. LUR models and mobile monitoring can be successfully implemented in developing country cities, thus cost-effectively improving exposure assessment for epidemiology and risk assessment. Air pollution represents a major threat to public health in Ulaanbaatar, Mongolia, and reducing home heating emissions in traditional housing areas should be the primary focus of air pollution control efforts.
流行病学研究一直报告室外细颗粒物（PM）空气污染与不良健康影响之间的关联。尽管亚洲承担了空气污染造成的大部分公共卫生负担，但由于人群暴露评估方面的挑战，北美和欧洲以外地区开展的流行病学研究较少。我们评估了两种当前暴露评估技术——土地利用回归（LUR）建模和移动监测的可行性，并估算了蒙古乌兰巴托空气污染导致的死亡率。我们基于在37个地点进行的为期2周的被动式小川测量以及免费可得的地理预测因子，开发了用于预测冬季NO和SO空间模式的LUR模型。这些模型分别解释了NO和SO中74%和78%的方差。从卫星图像得出的土地覆盖特征是两种污染物的有效预测因子。使用积分浊度计进行的移动PM监测也显示出前景，捕捉到了PM浓度的显著空间变化。SO和PM的空间模式、PM的季节和日模式以及冬季较高的PM/PM比值与该市低收入传统住房（蒙古包）地区煤炭和木材燃烧的重大影响一致。位于市中心的政府监测站点测得的PM年平均浓度为75μg/m，或超过世界卫生组织PM空气质量指南的七倍多，这是由冬季平均浓度148μg/m导致的。在一个传统住房地区测得的PM浓度更高，冬季PM平均浓度为25μg/m。我们保守估计，该市29%（95%CI，12 - 43%）的心肺死亡和40%（95%CI，17 - 56%）的肺癌死亡可归因于室外空气污染。这些死亡人数相当于该市总死亡率的近10%，在不太保守的模型假设下，估计范围高达死亡率的13%以上。LUR模型和移动监测可以在发展中国家城市成功实施，从而以具有成本效益的方式改善流行病学暴露评估和风险评估。空气污染对蒙古乌兰巴托的公众健康构成重大威胁，减少传统住房地区的家庭取暖排放应成为空气污染控制努力的主要重点。
