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Urban PM2.5 Diffusion Analysis Based on the Improved Gaussian Smoke Plume Model and Support Vector Machine

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DOI: 10.4209/aaqr.2017.06.0223
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Peng He1, Bohong Zheng1, Jian Zheng 2

  • 1 School of Architecture and Art, Central South University, Changsha 410075, China
  • 2 School of Architecture, South China University of Technology, Guangzhou 510640, China

Highlights

Excessive urbanization in China creates haze, which is a health hazard.
A new Gaussian smoke plume model on diffusion and evolution of PM2.5 was proposed.
The algorithm obtained much precise simulation results with lower error.
The results will help in government’s strategies of reducing air pollution.


Abstract

With the acceleration of urbanization in China, haze is becoming a growing threat to human health. However, comprehensive research on the diffusion and evolution of PM2.5 is still lacking. Therefore, this study proposes an improved Gaussian smoke plume model considering the influence of multiple factors such as rain wash, gravity sedimentation, and surface rebound on PM2.5. Additionally, the evolution of PM2.5 was predicted by selecting 9 factors that had large influences on PM2.5. In the prediction, support vector machine and Radial Basis Function kernel function were adopted to construct classifiers and obtain the maximum distinction degree, respectively. Finally, the diffusion simulation and experimental evolution prediction were verified using data obtained from nine PM2.5 monitoring stations in Wuhan. The experimental results showed that the algorithm could obtain considerably accurate simulation results of PM2.5 diffusion, had low error with measured values, and has significance in government plans for formulating planning strategies of controlling and reducing environment pollution.

Keywords

PM2.5 Diffusion simulation Evolution prediction Gaussian smoke plume model SVM


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