Mobility Energy Emissions Diagnosis (MEED): A Standardized Approach to Assess the Environmental Impacts of Urban Mobility in France
Damien VERRY, CEREMA, Fabrice Hasiak, CEREMA
A new methodology based on local household travel surveys to assess environmental impact of daily mobility is described. The results on 18 French cities in France are discussed.
Damien VERRY, Fabrice Hasiak, Arnaud Lannoy (Cerema)
The Mobility Energy Emissions Diagnosis (MEED) is a methodology developed conjointly by Cerema (National Centre For Studies and Expertise on Risks, Environment, Mobility, and Urban and Country planning), Ademe (The French Environment and Energy Management Agency) and IFSTTAR (The French Institute of Science and Technology for Transport, Development and Networks). It aims to to estimate the energy consumption, the emissions of Air Regulated Pollutants (NOx, PM, VOC, CO) and Greenhouse Gases directly related to transportation and traffics in urban area. It combines two approaches: a territorial one, all the trips included in an area are considered and an individual one, all the trips made by dwellers are taken into account. This papers is only focused on the dweller approach.
In a first part, we review the literature of environmental assessment based on disaggregated data. On the contrary with more traditional inventory approach, the main goal of the MEED is not to only determine the overall pollutant emissions generated by dwellers mobility. Its purpose is rather to refer the environmental impacts of the mobility to the population behaviors within a given urban area and to simulate the variations of these impacts as a result of changing individual behavior depending on socio-economic and demographic determinants.
In a second part, we describe the methodology used. Each local household travel survey in France are conducted according to the national methodology defined by the CERTU. For each trips inquired an estimation of energy consumption and pollutants emissions are given. GIS input (Transcad) for speed and distance, emission factors (Copert IV) and local data for public transport and air travel are added to make the assessment. Cold start, evaporation loss and abrasion emission are taken into account. Since 2013, all transport local surveys made in France have been used to perform MEED (i.e 18 cities). In the third part a detailed analysis on 13 French cities is presented. The fact to have standardized methodology for mobility measurement and emissions assessment allows comparisons. We try to show how the level of mobility, the proximity and the urban transport environmental effectiveness explains the revealed differences. The first results seems to show that socio-economic factors (activity rate) and job locations are the keys elements to explain the different level of GHG emissions. Cities with high level of density and good public transport offer are, in our sample, dynamic cities with wide peri-uban area and with quite high individual level of emissions.
Association for European Transport