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Including congestion effects in urban road traffic CO2 emissions modelling: do local government authorities have the right options?

Including congestion effects in urban road traffic CO2 emissions modelling: do local government authorities have the right options?
Including congestion effects in urban road traffic CO2 emissions modelling: do local government authorities have the right options?
Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.

This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.

Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.
road traffic model, emissions model, greenhouse gas, air quality, congestion, local government
1361-9209
95-106
Grote, Matt
f29566f9-42a7-498a-9671-8661a4287754
Williams, Ian
c9d674ac-ee69-4937-ab43-17e716266e22
Preston, John
ef81c42e-c896-4768-92d1-052662037f0b
Kemp, Simon
942b35c0-3584-4ca1-bf9e-5f07790d6e36
Grote, Matt
f29566f9-42a7-498a-9671-8661a4287754
Williams, Ian
c9d674ac-ee69-4937-ab43-17e716266e22
Preston, John
ef81c42e-c896-4768-92d1-052662037f0b
Kemp, Simon
942b35c0-3584-4ca1-bf9e-5f07790d6e36

Grote, Matt, Williams, Ian, Preston, John and Kemp, Simon (2016) Including congestion effects in urban road traffic CO2 emissions modelling: do local government authorities have the right options? Transportation Research Part D: Transport and Environment, 43, 95-106. (doi:10.1016/j.trd.2015.12.010).

Record type: Article

Abstract

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.

This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.

Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.

Text
Grote (2016) Including congestion in urban CO2 models.pdf - Version of Record
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More information

Accepted/In Press date: 22 December 2015
e-pub ahead of print date: 11 January 2016
Published date: March 2016
Keywords: road traffic model, emissions model, greenhouse gas, air quality, congestion, local government
Organisations: Centre for Environmental Science, Transportation Group

Identifiers

Local EPrints ID: 385381
URI: http://eprints.soton.ac.uk/id/eprint/385381
ISSN: 1361-9209
PURE UUID: 38f0d38f-6fb4-420d-8c81-17bcfdf544df
ORCID for Ian Williams: ORCID iD orcid.org/0000-0002-0121-1219
ORCID for John Preston: ORCID iD orcid.org/0000-0002-6866-049X

Catalogue record

Date deposited: 19 Jan 2016 14:11
Last modified: 17 Dec 2019 01:46

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