Comprehensive diagnosis model of environmental impact caused by expressway vehicle emission

Environ Monit Assess. 2022 Sep 16;194(10):796. doi: 10.1007/s10661-022-10471-4.

Abstract

With the rapid development of the economy, the expressway has been used as a main mode of transportation due to its function to meet traffic demand of people and thus has been given full attention. But, at the same time, it has gradually become the main cause of pollution of traffic environment. To clarify the degree of pollution caused by expressway vehicle and improve the expressway pollution diagnosis system, upon the notion of low-carbon transportation, this paper divides expressway environmental pollution into four types: air pollution, photochemical smog pollution, noise pollution, and vibration pollution, and analyzes each of them, respectively. Then, a comprehensive diagnosis model of environmental pollution caused by running vehicles will be built. This paper monitors the pollution intensity on different spots on the expressway to obtain the single-vehicle factors of various pollutants of the motor vehicles. Combined with the geographic information system, this puts forward the diagnosis methods in terms of the environmental "air pollution," "photochemical smog pollution," "noise pollution" and "vibration pollution" caused by the expressway vehicles, respectively, and further establishes a diagnosis model of vehicle pollution corresponding to the characteristics of the expressway. The result of the case study on the actual monitoring data of six expressways in Jiangsu Province shows that the pollution diagnosis values of six expressways are all between (0.4, 0.6] which symbolizes "slight pollution." The research results can provide technical support for monitoring of environmental pollution caused by expressway more comprehensively and reasonably, and provide data support for formulating effective control strategies.

Keywords: Diagnostic model; Expressway; Pollution; Running vehicles.

MeSH terms

  • Carbon
  • Environmental Monitoring
  • Environmental Pollutants*
  • Humans
  • Noise
  • Smog
  • Vehicle Emissions* / analysis

Substances

  • Environmental Pollutants
  • Smog
  • Vehicle Emissions
  • Carbon