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Discrete Dynamics in Nature and Society
Volume 2018, Article ID 2512350, 18 pages
Research Article

A Dynamic Analysis of a Motor Vehicle Pollutant Emission Reduction Management Model Based on the SD-GM Approach

College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China

Correspondence should be addressed to Shuwei Jia; moc.361@666999aijiewuhs

Received 6 November 2017; Revised 29 June 2018; Accepted 12 July 2018; Published 1 August 2018

Academic Editor: Rodica Luca

Copyright © 2018 Shuwei Jia. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The present study constructed a motor vehicle pollution charging management model by primarily reducing the trip volume of motor vehicles, introducing the charging mechanism, and employing integration of the system dynamics and grey model theory (SD-GM) from the perspective of the environment and society. To optimize the chosen parameters, the dynamic growth rate graphical function of the gross domestic product (GDP) was firstly generated based on the GM(1,1) prediction theory. In addition, verification was conducted in accordance with the degree of grey incidence. Secondly, the net migration rate was estimated based on the attraction degree of the city and the average net migration rate. The degree of PMx and NOx pollution was finally defined and endowed with different weights to define the degree of air pollution in accordance with the actual degree of air pollution in Beijing. In terms of model testing and verification, we conducted extreme condition tests and sensitivity tests and checked the residual error. Finally, this study analyzed and compared different policies, which indicate that the amount of motor vehicle trips (AMVT), the amount of PMx generation (APMG), the amount of NOx generation (ANOG), and the degree of air pollution (DAP) decreased by 31.01%, 26.52%, 21.29%, and 12.50%, respectively.