Difference Equation Model-Based PM[sub.2.5] Prediction considering the Spatiotemporal Propagation: A Case Study of Bohai Rim Region, China

Accurate reporting and prediction of PM[sub.2.5] concentration are very important for improving public health. In this article, we use a spectral clustering algorithm to cluster 44 cities in the Bohai Rim Region. On this basis, we propose a special difference equation model, especially the use of no...

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Bibliographic Details
Published inDiscrete dynamics in nature and society Vol. 2021
Main Authors Lei, Ceyu, Han, Xiaoling, Gao, Chenghua
Format Journal Article
LanguageEnglish
Published Hindawi Limited 31.03.2021
Subjects
Air pollution
Analysis
Case studies
Forecasts and trends
China
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Summary:Accurate reporting and prediction of PM[sub.2.5] concentration are very important for improving public health. In this article, we use a spectral clustering algorithm to cluster 44 cities in the Bohai Rim Region. On this basis, we propose a special difference equation model, especially the use of nonlinear diffusion equations to characterize the temporal and spatial dynamic characteristics of PM[sub.2.5] propagation between and within clusters for real-time prediction. For example, through the analysis of PM[sub.2.5] concentration data for 92 consecutive days in the Bohai Rim Region, and according to different accuracy definitions, the average prediction accuracy of the difference equation model in all city clusters is 97% or 90%. The mean absolute error (MAE) of the forecast data for each urban agglomeration is within 7 units (μ g/m[sup.3]). The experimental results show that the difference equation model can effectively reduce the prediction time, improve the prediction accuracy, and provide decision support for local air pollution early warning and urban comprehensive management.
ISSN:1026-0226
1607-887X
DOI:10.1155/2021/6614950