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A method for estimating traffic fuel consumption and vehicle emissions: an application to the Community Energy Plan of Salerno

Authors: Armando Carteni'; Stefano de Luca;

A method for estimating traffic fuel consumption and vehicle emissions: an application to the Community Energy Plan of Salerno

Abstract

One of the main issues within urban planning concerns the reduction of energy consumption and emissions produced by industry, public services, transport system, and the like. Today, transport energy consumption and emissions account for about 20%-40% of the total. In such a context, effective estimation of transport impacts should be envisaged and strategies/policies for their mitigation proposed. Recently the Community Energy Plan (CEP) was introduced as a fundamental step of urban planning activities. The CEP is a strategic plan which aims to reduce energy consumption and pollutant emissions produced by several sectors. Adoption and implementation of CEPs is obligatory in certain EU Member States. Some cities adopt plans on a voluntary basis to improve quality of life or in order to comply with EU standards to protect human health (e.g. air quality). In the literature, estimation of energy consumption and vehicle emissions is usually carried out by the application of mathematical models that allow estimation of average concentrations by means of variables representing the characteristics of the travel demand (e.g. origin-destination matrix, the composition of the vehicle fleet, the average length of trips) as well as variables representing the traffic flow conditions (e.g. average speed, vehicle density). These input variables can be estimated through surveys or through simulation models. In the former case, we can only estimate the impacts compared to a base scenario (current); in the latter case, it is possible to estimate impacts with regard to design scenarios (e.g. changes in the socio-economic system, modal split variation, traffic congestion reduction). The most pursued approaches are often aggregated and use input variables estimated through surveys. Those approaches that implement disaggregated models are based on simulation models, but refer only to small portions of the transport system (e.g. single individual intersections or roads) and do not allow evaluation of the impacts on the entire system. This paper proposes a method to estimate traffic fuel consumption and emissions at urban scale. The aim is threefold: (i) to propose a methodology which, pursuing a disaggregate approach, integrate transportation models with fuel consumption and emission models; (ii) to apply the methodology to the CEP of Salerno (Italy); (iii) to carry out a sensitivity analysis with respect to different input variables (vehicle types, modal split, vehicle flow density) allowing to evaluate the effects of travel demand management strategies. The methodology is based on consolidated methods/models of transportation system analysis, and it pursues the European approach based on Computer Programme to Calculate Emissions from Road Transport (COPERT) for estimating fuel consumptions and emissions.

Country
Italy
Keywords

fuel consumption, Copert, sustainable transport, vehicle emissions, Energy Plan, fuel consumption; vehicle emissions; Energy Plan; Copert; sustainable transport

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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