Research of Carbon Emissions of Highway Operation Period Based on Grey Relational Analysis

Abstract

The CO2 emissions of highway transportation industry are huge. In order to study factors affecting carbon emissions of highway operation period, selected five primary route design indicators to analyze. The five indicators were Speed, Gradient, Radius of Curvature, IRI, Traffic Volume and Green Belt. Combined the existing Carbon Accounting Model and the Carbon Accounting Software of Highway Operation Period[4], which could calculate the equivalent carbon emissions. By using Gray relational analysis method, calculated the relational degrees between route design indicators and carbon emissions of highway operation period. At last, found that the most important factor affecting carbon emissions of highway operation period was average daily traffic volume. The research will be helpful to discuss the carbon emissions of highway operation period in a targeted manner.

The use of grey-based methods in multi-criteria decision analysis for the evaluation of sustainable energy systems: A review

“…The recent extensive literature on the application of grey relational analysis to energy issues underlines the current importance of the topic [18,20,24,[42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57] because GRA is well suited to the analysis of multi-objective systems [11,58,59]. As other studies have noted, multi-criteria optimization analysis methods have gained in popularity beyond 1990s [9].…”

“…As other studies have noted, multi-criteria optimization analysis methods have gained in popularity beyond 1990s [9]. Selecting fuels [42,45,48,54,58], optimize operation conditions [44,46,47,53,60], environmental impact assessment, in terms of emissions [49,50,55,61] are the main applications identified in the recent literature. Moreover, it is well recognized that the GRA method in several research fields other than energy to deal with project selection, prediction analysis, performance assessment or factor effect evaluation [30].…”