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首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >A Geostatistical Approach to Assess the Spatial Association between Indoor Radon Concentration Geological Features and Building Characteristics: The Case of Lombardy Northern Italy
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A Geostatistical Approach to Assess the Spatial Association between Indoor Radon Concentration Geological Features and Building Characteristics: The Case of Lombardy Northern Italy

机译：评估室内Rad浓度地质特征与建筑特征之间空间联系的地统计学方法：以意大利北部伦巴第为例

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Radon is a natural gas known to be the main contributor to natural background radiation exposure and second to smoking, a major leading cause of lung cancer. The main source of radon is the soil, but the gas can enter buildings in many different ways and reach high indoor concentrations. Monitoring surveys have been promoted in many countries in order to assess the exposure of people to radon. In this paper, two complementary aspects are investigated. Firstly, we mapped indoor radon concentration in a large and inhomogeneous region using a geostatistical approach which borrows strength from the geologic nature of the soil. Secondly, knowing that geologic and anthropogenic factors, such as building characteristics, can foster the gas to flow into a building or protect against this, we evaluated these effects through a multiple regression model which takes into account the spatial correlation of the data. This allows us to rank different building typologies, identified by architectonic and geological characteristics, according to their proneness to radon. Our results suggest the opportunity to differentiate construction requirements in a large and inhomogeneous area, as the one considered in this paper, according to different places and provide a method to identify those dwellings which should be monitored more carefully.
机译：on是一种天然气，已知是导致自然本底辐射暴露的主要原因，其次是吸烟，而吸烟是肺癌的主要诱因。 of的主要来源是土壤，但气体可以通过许多不同方式进入建筑物并达到室内高浓度。为了评估人们对的暴露程度，许多国家都促进了监测调查。本文研究了两个互补的方面。首先，我们利用地统计学方法从大面积的土壤地质性质中汲取了强度，从而绘制了一个较大且不均匀区域中的室内ra浓度。其次，我们知道地质和人为因素（例如建筑物的特征）会促使气体流入建筑物或对此采取保护措施，因此我们通过考虑数据空间相关性的多元回归模型评估了这些影响。这使我们能够根据don的倾向性，对不同的建筑类型进行分类，这些类型由建筑和地质特征确定。我们的研究结果表明，有机会根据不同的地点，在大面积和不均一的区域中区分建筑要求，并提供一种方法来识别应该更仔细监控的住宅。

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