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Spatial Interpolation of Fine Particulate Matter Concentrations Using the Shortest Wind-Field Path Distance

机译：使用最短风场路径距离的细颗粒物浓度的空间插值

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摘要

Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health.
机译：对空气污染暴露的有效评估取决于能否准确预测未监测位置的污染物浓度，这可以通过空间插值来实现。但是，当前使用的大多数插值方法都是基于欧几里得距离的，无法解决风场中空气污染分布所显示的复杂非线性特征。在这项研究中，开发了一种基于最短路径距离的插值方法，以表征复杂的城市风场对颗粒物浓度分布的影响。在这种方法中，首先通过对气象站网络中的观测风场进行插值，然后使用该连续风场基于高斯弥散模型构造成本面并计算最短风场路径，从而合并风场。位置之间的距离，最后用最短的风场路径距离替换通常在逆距离加权（IDW）中使用的欧几里得距离。该拟议方法用于生成2013年5月北京市区颗粒物浓度的每日和每小时估算表面。这项研究表明，可以使用最短的风场路径距离将风场合并到插值框架中，这导致风流效应的预测准确性和视觉再现性都得到了显着提高，这两者对于评估污染物对人体健康的影响都至关重要。

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