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National-scale exposure prediction for long-term concentrations of particulate matter and nitrogen dioxide in South Korea

机译：全国范围内对韩国颗粒物和二氧化氮的长期浓度的预测

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The limited spatial coverage of the air pollution data available from regulatory air quality monitoring networks hampers national-scale epidemiological studies of air pollution. The present study aimed to develop a national-scale exposure prediction model for estimating annual average concentrations of PM10 and NO2 at residences in South Korea using regulatory monitoring data for 2010. Using hourly measurements of PM10 and NO2 at 277 regulatory monitoring sites, we calculated the annual average concentrations at each site. We also computed 322 geographic variables in order to represent plausible local and regional pollution sources. Using these data, we developed universal kriging models, including three summary predictors estimated by partial least squares (PLS). The model performance was evaluated with fivefold cross-validation. In sensitivity analyses, we compared our approach with two alternative approaches, which added regional interactions and replaced the PLS predictors with up to ten selected variables. Finally, we predicted the annual average concentrations of PM2 and NO2 at 83,463 centroids of residential census output areas in South Korea to investigate the population exposure to these pollutants and to compare the exposure levels between monitored and unmonitored areas. The means of the annual average concentrations of PM10 and NO2 for 2010, across regulatory monitoring sites in South Korea, were 51.63 mu g/m(3) (SD = 8.58) and 25.64 ppb (11.05), respectively. The universal kriging exposure prediction models yielded cross-validated R(2)s of 0.45 and 0.82 for PM10 and NO2, respectively. Compared to our model, the two alternative approaches gave consistent or worse performances. Population exposure levels in unmonitored areas were lower than in monitored areas. This is the first study that focused on developing a national-scale point wise exposure prediction approach in South Korea, which will allow national exposure assessments and epidemiological research to answer policy-related questions and to draw comparisons among different countries. (C) 2017 Elsevier Ltd. All rights reserved.
机译：可从监管空气质量监测网络获得的空气污染数据的空间覆盖范围有限，妨碍了全国范围的空气污染流行病学研究。本研究旨在建立一个全国规模的暴露预测模型，以使用2010年的监管监测数据估算韩国居民住宅中PM10和NO2的年平均浓度。使用每小时测量的277个监管监测点的PM10和NO2，我们计算了每个站点的年平均浓度。我们还计算了322个地理变量，以表示合理的本地和区域污染源。利用这些数据，我们开发了通用克里金模型，包括通过偏最小二乘（PLS）估算的三个汇总预测变量。通过五重交叉验证评估模型性能。在敏感性分析中，我们将我们的方法与两种替代方法进行了比较，这两种方法增加了区域相互作用，并用最多十个选定变量替代了PLS预测因子。最后，我们预测了韩国住宅人口普查输出区域中83,463个质心的PM2和NO2的年平均浓度，以调查人口对这些污染物的暴露程度，并比较监测和未监测区域之间的暴露水平。在韩国各个监管监测点，2010年PM10和NO2的年平均浓度分别为51.63μg / m（3）（SD = 8.58）和25.64 ppb（11.05）。通用克里金法暴露预测模型得出的PM10和NO2的交叉验证R（2）分别为0.45和0.82。与我们的模型相比，这两种替代方法的效果一致或较差。未监测地区的人口暴露水平低于监测地区。这是第一项专注于在韩国开发一种全国规模的逐点接触预测方法的研究，该方法将使全国接触评估和流行病学研究能够回答与政策有关的问题并进行不同国家之间的比较。 （C）2017 Elsevier Ltd.保留所有权利。

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