Preprocessing Methods for Mobile Measurements of Roadside Air Pollution
Journal Title: 河南科技大学学报（自然科学版） - Year 2017, Vol 38, Issue 4
Abstract
When roadside air pollution was measured by a mobile platform, the measurement was prone to be interfered by abnormal samples of high values, pollution background and spatiotemporal scale. Therefore, data preprocessing methods for removing abnormal samples of high values, correcting the pollution background and screening the spatiotemporal scale were reviewed. Then, several selected methods were verified based on mobile measurements of fine particles ( PM2. 5) , ultrafine particles ( PM1. 0) , black carbon ( BC) and carbon monoxide ( CO) in the roadside environment in Shanghai. The results show that the running coefficient of variation method can reasonably remove abnormal samples of high values, and the thin-plate spline regression smoothing method can effectively characterize the time-based pollution background. The comparability of spatiotemporal variations of pollutant concentrations is largely improved via previous two preprocessing steps.The correlation coefficient method further shows that 10 s and 20 m are an ideal combination of temporal and spatial scales for mobile measurement analysis, which can more effectively filter data noise and more objectively present the spatial pattern of pollutant concentrations.
Authors and Affiliations
Zhanyong WANG, Ran YU, Ming CAI, Zhongren PENG
Keywords
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