A tradable credits scheme for VMT reduction and environmental effects: a simulation case study for Great Britain

Transcription

1 A tradable redits sheme for VMT redution and environmental effets: a simulation ase study for Great Britain Meng Xu Institute for Transport Studies University of Leeds University Road, LS2 9JT Leeds, UK Tel: Tel: +44 (0) m.xu@leeds.a.uk And State Key Laboratory of Rail Traffi Control and Safety Beijing Jiaotong University Beijing, , China mengxu@bjtu.edu.n Susan Grant-Muller Institute for Transport Studies University of Leeds University Road, LS2 9JT Leeds, UK Tel: +44 (0) s.m.grant-muller@ leeds.a.uk Word Count: 6338 (5338 Text+ 3 Tables and 1 Figures) Paper submitted for possible presentation to the 94th Annual Meeting of the Transportation Researh Board and publiation in the Journal of the Transportation Researh Board 1 st August,

2 Abstrat We investigate the influene of a tradable redits sheme (TCS) on travel demand and vehile emissions, based on the vehile miles travelled (VMT). With a miroeonomi quantitative analysis sheme, a onstant elastiity of substitution (CES) funtion is used as an approah to model the annual mileage by different travel purposes. An illustration is given for the effets of a TCS on emission mitigation based on historial data for Great Britain. A senario analysis demonstrates that a tradable redits sheme an ahieve a target for reduing the number of private trips. Besides a movement of trips from the private ar mode to publi modes, there is also some trip restraint, with individuals hoosing not to take some trips. Compared with past researh on road priing in London (Fowkes et al. (1995)), the researh illustrates that a TCS an be designed to have similar effets to a road priing sheme. We also demonstrate that a TCS ould bring emission hanges arising from the hanges with respet to VMT. Keywords: Tradable redits sheme; Emission; Mode hoie; Vehile miles travelled; Climate hange assessment 2

3 1. introdution Urban transport has an overriding role in eonomi ativity and growth and is also of major importane for the quality of life of individuals as well as regional produtivity. However in many ities, traffi ongestion, emissions, traffi noise, and inreasing travel osts have led to a series of problems. Congestion results in travel time delays and unreliability, inreases in fuel onsumption and inreased driver stress. In the European Union (EU), transport generates approximately 25 to 30 perent of total greenhouse gas (GHG) emissions (Ellerman, et al., 2010). In China, statistis have shown that more than three quarters of total air pollution omes from vehile arbon monoxide and hydroarbon emissions in large ities inluding Beijing, Shanghai and Guangzhou (China Business News, 2011). The World Energy Outlook (WEO) 2009 projet pointed out that global demand for transport appears unlikely to derease in the foreseeable future and transport will grow by 45% by From the International Energy Ageny statistis for 2010, the transport setor represented 22% of global CO2 emissions in 2008, whilst CO2 emissions from transport were dominated by road modes. The transport setor is therefore onsidered one of the main soures of greenhouse gas emissions. The Kyoto Protool proposed use of a system of emission permits as an eonomi tool for limate hange mitigation. However, the use of a TCS for transport emissions is a relatively new measure both in theory and in pratie. The lak of pratial appliation of this eonomi measure may be attributable to an undeveloped and inomplete theoretial foundation and partiular pratial issues that are yet to be resolved. However the tradable redits sheme is a promising poliy tool for mobility management and has reeived inreasing attention in reent years. Some reviews of tradable redits sheme in the transport setor inlude: the regulation of road transport externalities (Verhoef et al., 1997), a review and appraisal of roadway apaity alloation (Fan and Jiang, 2013) and road ongestion management (Grant-Muller and Xu, 2014). If a TCS were to be implemented in an urban transport system, the budget for redits will beome an additional resoure onsidered within individuals mode hoie. The use of a private ar will beome subjet to additional monetary osts if there is a wish to use it beyond the limit of the initial redit alloation. There are various options within the sope of the sheme: people may want to fully use their redits, buy additional redits (where their use of the ar exeeds the initial alloation), or save and sell them for finanial gain. As a result, people have to not only deide on the neessity of the trips they take, but also on how they want to manage their budget of alloated redits. Mode hoie for a typial individual in eah geographi area will be affeted by the individuals transport budget, the travel ost aording to different modes and the individuals attitudes. 3

4 Different oneptual forms of TCS have been developed within existing road transport studies and aording to the potential appliation area. These may inlude tradable driving day rights, tradable vehile-miles, tradable fuel permits and tradable parking rights for example. A TCS based on VMT provides an alternative to restriting vehile miles, although there are some potential disadvantages in the politial reality and poliy ramifiation, and also limitations, as pointed by Verhoef et al. (1997). These inlude the diffiulties in applying the system in a spatially differentiated manner and the possibility of providing insuffiient inentives to improve on vehile tehnology. Under this sheme, eah individual ould reeive a ertain number of personal vehile-miles (the unit of redits), whih ould subsequently be traded so as to aomplish an eventual distribution where only the vehile miles with the highest benefits would remain, and some vehile trips will be stopped or resheduled. Furthermore, the poliy target, defined as total vehile mileage, has also a lose onnetion with vehile emissions. Like similar papers, the politial reality and poliy ramifiations are not treated here, however the authors make note of these limitations. To implement a TCS, a fundamental question is how to measure the effets of a TCS quantitatively with respet to the VMT and vehile emissions. In this study, we examine how travelers mode hoie preferenes ould be influened by implementing a TCS. The study supposes that the regional authority is responsible for implementing the tradable redits sheme, the initial redit alloation is free and individuals reeive a number of redits (representing vehile-miles). Now, in order to redue the VMT and vehile emission in the given urban area, individuals (in maximizing their utility), must onsider their travel mode hoie based on the redits distributed. That is, the individual must onsider the permitted number of vehile miles and the redit prie (p e ). To investigate the influene of a given TCS we present a miroeonomi quantitative analysis framework to simulate poliy senarios. Travel patterns are ompared before and after introdution of a tradable redits sheme. This is also extended to onsider how a TCS should be designed so that it has similar impats to a ongestion priing sheme. This is important in order that poliy makers may understand how a TCS would need to look in order to at as a substitute sheme in the future, or in order to bring further improvement from road priing. Furthermore, we disuss the effets of TCS on vehile emissions based on VMT. The simulation studies presented in this paper are based on Fowkes et al. (1998), whih investigated the effets on mileage by publi and private transport in 2006 of various measures that have been proposed to restrain the use of the private ar. That study utilized a series of household survey data, inluding the 1985/6 National Travel Surveys (NTS), and seleted tabulations from the 1991/3 hybrid data set provided by the Statistis Diretorate of the Department of Transport (DOT). The NTS provided a 4

5 national data bank of personal travel information for Great Britain (DOT, 1993). As emphasized by Fowkes et al. (1998), the 2006 projetion is by no means a foreast, as it merely attempts to projet the 1985 to 1993 trends through to The organization of the paper is as follows. In Setion 2, we present an estimation model for individual average trips (based on a neo-lassial miroeonomi model) with and without a tradable redits sheme, inluding the determination of redit equilibrium prie. In Setion 3, the details of the simulation framework are given, involving journey data for Great Britain in 2006 and the London road priing sheme. We also give the fundamental parameters and input settings based on data for Great Britain. In Setion 4, we ompare the effets of TCS arising from the simulation framework presented with those of the ongestion priing sheme in London, disussing differenes in emissions with and without a TCS. The paper onludes in Setion Methodology Before introduing the simulation framework, we present the methodologial approah as follows. Firstly we list the notation used in Setion 2.1, followed by a presentation of the model formulation in Setion 2.2 and determination of the travel pattern with a TCS in Setion 2.3. The theoretial determination of the redit prie is derived in Setion Notation Considering a given area i, i = 1,, N, then we adopt the following notation: P i x i b x i x i,k b x i,k population in area i, i = 1,, N individual trips via private mode in area i, unit: vehile miles travelled (VMT), x N = i=1 P i x i individual trips via publi mode in area i, unit: VMT, x b N b = i=1 P i x i individual trips with travel purpose k via private mode in area i, unit: VMT individual trips with travel purpose k via publi mode in area i, unit: VMT U i (x i, x b i ) (U i,k (x i,k, x b i,k )) utility funtion for a representative individual in area i (for travel purpose k) I i individual transport budget devoted to travel in area i p i,v (p i,k,v ) prie of private mode per mile travelled in area i (for travel purpose k), inluding maintenane osts, fuel and insurane p i,b (p i,k,b ) prie of publi mode per mile travelled in area i (for travel purpose k) Parameters: a i alloation parameter for private mode trips/the proportion of transport inome spent on private mode use 5

6 a i,k alloation parameter for private mode trips for travel purpose k/the proportion of transport inome spent on private mode use ρ i (ρ i,k ) substitution elastiity in area i (for travel purpose k) ε i (ε i,k ) elasti oeffiient in area i (for travel purpose k), ε i = 1 1 ρ i (ε i,k = 1 1 ρ i,k ) Tradable redits sheme p i,e prie of tradable redits in area i x i redits reeived per individual in area i, e.g., eah redit/liense entitles the holder to travel one mile by private mode. x N total number of redits set aording to the total VMT, x = P i x i 2.2 A onstant elastiity of substitution (CES) model Suppose for a partiular area i, the daily travel modes for travelers is split into publi () and private (b). Considering environmental goals or other fators, the authority may wish to restraint the number of private trips for different travel purposes (k) with respet to the number of annual average mileage travelled (i.e. restraint private mileage by VMT) and it is supposed that the authority will approah this target with a tradable redit sheme. Before implementation of the TCS, it is assumed that eah individual in area i, with travel purpose k, maximizes his/her utility by U1: Max U i,k (x i,k, x b i,k ) = [a i,k (x i,k ) ρi,k + (1 a i,k )(x b i,k ) ρi,k ] s. t. K K b 1 ρ i,k i=1 (1a) k=1 p i,k,v x i,k + k=1 p i,k,b x i,k I i, i = 1,, N (2a) x i,k 0, i = 1,, N, k = 1,, M (3a) x b i,k 0, i = 1,, N, k = 1,, M (4a) It is noted that we assume all travel ativities (for all travel purposes) are within the given transport budget I i. Alternative, if we do not onsider the travel purpose k, the utility model an be written as U1 for eah area i, U1 : Max U i (x i, x b i ) = [a i (x i ) ρ i + (1 a i )(x b i ) ρi 1 ρ ] i s. t. (1b) p i,v x i +p i,b x i b I i, i = 1,, N x i 0, i = 1,, N x b i 0, i = 1,, N (2b) (3b) (4b) The target utility funtion in U1, U1, and also the following U2, U2, is alled the onstant elastiity of substitution (CES) utility funtion in miroeonomi analysis. 6

7 The CES form of the utility funtion allows several situations to be onsidered, whih depend on the value of the parameter ρ (Bulteau, 2012). In this study, when the parameter ρ = 0, the utility funtion is, in fat, in the form of a Cob-Douglas utility funtion, whih shows the private mode and publi mode as not being substitutable. When parameter ρ = 1, it indiates the private mode and publi mode to be perfet substitutes; when the parameter ρ =, it indiates that the private mode and publi mode are omplementary. A similar model has been used as an approah to individual utility in related areas suh as: eonomis (Santos et al., 2010), an individual tradable emission permit sheme for urban motorists (Bulteau, 2012) and the influene of urban form on energy onsumption aording to individual onsumption behaviour (Yin et al., 2013). 2.3 A CES model onsidering a TCS Suppose the regulatory authority then implements a tradable redits sheme. The initial redit distribution is free and eah individual in eah area reeives a number of redits that permits private trips: x i. The individual then needs to onsider the amount of miles that are allowed by a private mode e.g., ar and the prie of a redit if they wish to travel further miles by a private mode. Under the TCS, the utility maximization problem for eah representative individual in area i with respet to different travel purposes an then be formulated as the following: U2: K Max U i,k (x i,k, x b i,k ) = [a i,k (x i,k ) ρi,k + (1 a i,k )(x b i,k ) ρi,k ] s. t. K K k=1 p i,k,v x i,k + ( k=1 p i,e x i,k x i )+ k=1 pi,k,b x i,k I i, i = 1,, N (6a) x i,k 0, i = 1,, N, k = 1,, M b 1 ρ i,k (5a) (7a) x b i,k 0, i = 1,, N, k = 1,, M (8a) Similar to U1 above, if we do not onsider the travel purpose k, the utility model (5a-8a) an be written as U2 U2 : Max U i (x i, x b i ) = [a i (x i ) ρ i + (1 a i )(x b i ) ρi 1 ρ ] i s. t. (5b) p i,v x i + p i,e (x i x i )+pi,b x i b I i, i = 1,, N (6b) x i 0, i = 1,, N (7b) x b i 0, i = 1,, N (8b) Comparing Eq. (2a)/(2b) and Eq. (6a)/(6b), we find that there exists a balane with the redits sheme from the perspetive of individuals as follows. Firstly, it brings an inreased ost for private mode use (p e ) and seondly, it brings an inrease in the individuals transport budget (I i + p i,e x i ) for area i. This term pi,e x i ould be treated as a transport saving if an individual hose to sell redits. Aording to the assoiated Lagrangian, we an derive the following solution for U2 when two modes 7

8 are used: x i,k = ( ε a i,k i Ii +p i,j,e x i K j=1,j k pi,j,v x ) i,j ε p i,v +p i,e a i,k(pi,v i +p i,e ) 1 εi,k +(1 a i ) ε i,kp i,b 1 ε i,k, i = 1,, N, k = 1,, M (9a) x i b = ( 1 a i p i,b ) ε i,k Ii +p i,e x i K b j=1,j k pi,j,b x i,j a i ε i,k(pi,k,v +p i,e ) 1 ε i,k +(1 a i ) ε i,kp i,k,b 1 ε i,k, i = 1,, N (10a) where ε i,k is the elasti oeffiient in area i for travel purpose k, ε i,k = 1 1 ρ i,k. The solution of U2 : x i = ( ε a i i I ) i +p i,e x i ε p i,v +p i,e a i i (p i,v +p i,e ) 1 εi +(1 a i ) ε ip i,b I i +p e x i x b i = ( 1 a ε i i ) p i,b a i ε i (p i,v +p i,e ) 1 εi +(1 a i ) ε ip i,b 1 ε i, i = 1,, N 1 ε i, i = 1,, N where ε i is the elasti oeffiient in area i, ε i = 1 1 ρ i. Solutions for models U1 and U1 an inluded in Eqs. (9a-10a) and Eqs. (9b-10b) by setting p i,e = 0, and x i = 0, i = 1,, N, separately. (9b) (10b) 2.4 Determination of the redit prie We an further determine the redit prie in Setion 3.3 and disuss how this will affet the traveler s mode hoie. In order for the market to be balaned and onsistent with the target for private mode use (as set by the regulatory authority), the redit prie, whih is based on the VMT, an be set as x N = K N i=1 k=1 P i x i,k = x = i=1 x i (11) Or, if we do not onsider the travel purpose, x N N = i=1 P i x i = x = i=1 P i x i (12) From Equation (11), Similarly, from Equation (12) N K P i (x i=1 k=1 i,k x i ) = 0 (13) N P i (x i=1 i x i ) = 0 (14) Combining equations (13) and (9a), we have the following p i,e = ε i,k(ii a +p i i,e x i ) K pi,j,v x N K j=1,j k i,j i=1 k=1 ε i,k(pi,k,v a +p i i,e ) 1 ε i,k +(1 ai ) ε 1 ε i,k i,k pi,k,b N i=1 x i 1 ε i,k [ ] Combining equations (14) and (9b), we have the following p i,v, i = 1,, N (15) 8

9 p i,e = [ ε a i(ii +p N i i,e x i ) i=1 ε a i(pi,v +p i i,e ) 1 ε i +(1 ai ) ε i 1 ε pi,b i N i=1 x i ] 1 ε i p i,v, i = 1,, N (16) Eq. (15) or (16) give an impliit solution for the redit prie, whih ould be solved using an iterative approah given the ar osts per kilometer travelled p i,v, the prie of mass transit per kilometer travelled p i,b, the individual transportation budget in zone i, I i, the total number of redits sets by the authority x, and related oeffiients. 3. Case study for Great Britain 3.1 Simulation framework To arry out a senario study based on the available data for Great Britain in 2006, we firstly present here a simulation framework for the analysis of a TCS. This is based on the methodology developed and presented in Setion 2. A ase study for Great Britain is presented in Setion 3.2 and employs a senario based approah, as summarized in Figure 1 below. Determination of inputs of p i,v, p i,k,v p i,b, p i,k,b and I i for eah area i aording to the available data (e.g., See Setion 3.3) Parameters a i (a i,k ) and ρ i (ρ i,k ) estimation based on the annual average miles (VMT) for private and publi modes in Great Britain (Benhmark mileages given in ase I in Table 1) Design of TCS (set values for the tradable redits prie for eah area i (p i,e ), the initial redits distribution, and the total number of redits (x )) Estimated annual mileages of private and publi modes with and without the implementation of a TCS (aording to Eqs. (9a-10a) or (9b-10b)) Senarios Analysis with/without TCS: omparing with road priing; emission measure Figure 1 Simulation framework Aording to the methodology developed and presented in Setion 2, the simulation framework atually provides an impliit assumption that land use remains unhanged, whih is onsistent with the empirial studies of road ongestion given in Fowkes et 9

10 al. (1995). The assumption that land use remains unhanged and therefore firm and residential loation are treated as predetermined is not new, and has been wide used in existing studies, e.g., Keeler and Small(1977). Therefore, the proposed modelling approah is only a partial equilibrium model, and what is analyzed based on this simulation framework is a short-term response to hanges in the ost of travel. As shown in this paper, this modelling ould partially answer the question of how a TCS should be designed so that it has similar impats to a ongestion priing sheme. This might be of interest to poliy makers who may wish to understand how a TCS would need to look in order to at as a substitute sheme but have similar impats. If it were possible to do this in priniple, then from a soial researh perspetive it would be interesting to hear the views of poliy makers as to why they would not wish to implement the redit sheme. It may also indiate whether it is possible to design a sheme that would have advantages over the ongestion priing sheme, either in terms of the size of the impats or the distribution of the impats. By applying a TCS, there are undoubtedly long-term effets on firms and residential loation deisions, whih would need further onsideration of land use hanges. For this kind of approah, a general equilibrium modeling methodology would be neessary. Whilst this goes signifiantly beyond the sope of this paper, it ould however go some way to answering more interesting questions, suh as how far would households move from work if a VMT-based TCS is implemented? How would their long-term travel patterns hange as a onsequene of an inrease in VMT-based TCS,? From the general equilibrium approah, interested readers an refer to related studies on ongestion, land use and management poliies, e.g., Anas and Kim (1996), Anas and Xu (1999), Anas and Rhee (2006, 2007), Safirova et al.(2006), Gupta et al.(2006), and Zhang (2010). 3.2 Annual journey average mileages in Great Britain in 2006 In Fowkes et al. (1995), the daily travel mode disregarded walking and yling and was split into publi and private. The publi mode was defined to be all rail and bus modes plus taxi and domesti air, whilst the private mode inorporated private ars, plus vans, lorries and motoryles. Travel purposes inluded work, business and leisure. Also based on that study, a hierarhy of urbanisation an be used with Great Britain typially divided four-ways: London, the onurbations, urban and rural. London is taken as the first area type. Seondly, all the built up areas of the English Metropolitan Counties and Glasgow are ombined and oded as onurbations. The third ategory, oded urban, is all other built-up areas whih together have a total population of over 25,000. All other loations have been oded rural, inluding any towns of less than 25,000 persons. As shown in Table 1, ase I shows the annual average miles given by a base 2006 projetion for Great Britain with respet to the four ategories. The base 2006 projetion is not a foreast as it attempts to projet the 1985 to 1993 trip trends of 10

11 private and publi modes through to Case II reflets the redution in annual average vehiles miles with an 8 all day harge to travel into entral London. It takes the effets to be a London-wide redution for private mode mileage of 7% for work, 2% for business and 7% for leisure, whih is equal to an overall redution of about 6.5%. As demonstrated in Table 1, annual average vehiles miles in the other areas (inluding onurbations, urban, and rural), remain onstant in ase I and ase II. Table base mileage and road priing in London (Unit: annual average miles) Case Mode Purpose London Conurbations Urban Rural Total I Private Work Business Leisure Subtotal Publi Work Business Leisure Subtotal II Private Work Business Leisure Subtotal Publi Work Business Leisure Subtotal Key: ase I: 2006 Base; ase II: 2006 New London with road priing. 3.3 Input determination Firstly we determine the model inputs used here, whih inlude the prie of the private mode p i,v, the prie of the publi mode p i,b and the individuals transport budget I i for eah area i. The determination of these inputs depends on the data available from Siu et al. (1994), Fowkes et al. (1995) and Fowkes et al. (1998). Prie of private mode p i,v The prie of the private mode is determined by the average running fee with respet to the definition of the private mode in Fowkes et al. (1995), and then transferred to the unit of per mile. Prie of publi mode p i,b The prie of the publi mode is determined by the average fare of different publi modes ( per mile) aording to Fowkes et al. (1995). Individuals transport budget I i It is diffiult to obtain an aurate budget for travel for individuals in eah geographi area. Here we estimate it aording to the inome statistis given by Siu et al. (1994) (See Table 6, page 21), whih presented mean household inomes by person type and area type based on the NTS dataset. Generally, 11

12 we assume that no more than 20% of an individuals inome is used as the transport budget. Aording to the data available, the inputs (p i,v, p i,k,v, p i,b, p i,k,b and I i ) are as shown in Table 2, whih are used in the senario simulation for the TCS. Aording to the 2006 base mileages presented for ase I in Table 1, we an determine the parameters (a i, a i,k, ρ i, ρ i,k ) for eah area and for different travel purposes, also as shown in Table 2. These parameters are used in the analysis in Setion 5. Table 2 Inputs and alibrated parameters aording to 2006 base mileage Parameters Purpose London Conurbations Urban Rural p i,v (p i,k,v ) Work p 1,1,v = p 2,1,v = p 3,v = p 4,v = Business p 1,2,v = p 2,2,v = Leisure p 1,3,v = p 2,3,v = p i,b (p i,k,b ) Work p 1,1,b = p 2,1,b = p 3,b = p 4,b = Business p 1,2,b = p 2,2,b = Leisure p 1,3,b = p 2,3,b = a i (a i,k ) Work a 1,1 =0.61 a 2,1 =0.96 a 3 =0.96 a 4 =0.97 Business a 1,2 =0.81 a 2,2 =0.98 Leisure a 1,3 =0.98 a 2,3 =0.95 ρ i (ρ i,k ) Work ρ 1,1 =0.14 ρ 2,1 =0.41 ρ 3 =0.24 ρ 4 =0.21 Business ρ 1,2 =0.22 ρ 2,2 =0.12 Leisure ρ 1,3 =0.23 ρ 2,3 =0.28 I i Simulation and disussion 4.1 Comparing the effets of a TCS and ongestion priing sheme for London: a modelling approah Although road ongestion priing is regarded as an effiient priing strategy, it also brings some debates regarding, e.g., soial equity (Giuliano, 1994) and eonomi effiieny (Banister, 1994; Viegas, 2001). Some people may also feel that paying for ongestion is inappropriate, beause they may prefer to pay for things they wish to aquire rather than for things they wish to avoid (i.e., traffi ongestion) (Kahneman and Tversky, 1984; Geller, 1989). In fat reent studies have demonstrated that some alternative shemes an be designed to have the same impats as road ongestion priing shemes. For example, Tillema et al. (2013) ompared two ongestion management shemes (road priing and peak avoidane rewarding) and their impat on ommuter behaviour, based on two studies that were onduted in the Netherlands. They onluded that the reward measure appears to be somewhat more effetive in persuading people to travel outside peak hours, whih would suggest that rewarding them may be more effetive than harging (i.e., punishing) them. The behavioural rationale of many demand-based strategies aimed at managing traffi ongestion, is 12

13 often based on negative inentives that assoiate the at of driving with punishment (in the form of tolls or inreased parking osts). With the parameters and inputs given in Table 2, we an estimate the annual mileage for eah area and by different travel purpose. Senario I in Table 3 presents the estimated annual mileage of Great Britain aording to the data available, given in Setion 4.2. Comparing Senario I in Table 3 and Case I in Table 1, we find that the model U1 and U1 an approah the 2006 base mileage given by Fowkes et al. (1998) well. We are naturally interested in further onsidering the question of how should a TCS be designed so that it has similar impats to ongestion priing? This is important in order that poliy makers may understand how it would need to look in order to at as a substitute sheme whilst having similar impats. If it were possible to do this in priniple, then it would be interesting to evaluate the reations of poliy makers and also to bring further views from the soial researh perspetive. Instead of the 8 all day harge to travel into entral London (as mentioned in Setion 3.2), we now investigate the implementation of a TCS in London only. The model with a TCS was presented in Setion 3. Aording to the simulation framework (as shown in Figure 1), we an derive the annual average miles. With the parameter settings as in Table 2, we further onsider the following two senarios: TCS1: p 1,e = 1, x = 16139, redits are distributed equivalently initially; TCS2: p 1,e = 0.5, x = 16139, redits are distributed equivalently initially. For the senarios TCS1 and TCS2 we assume that a TCS will be implemented in the London area, with eah individual in London reeiving the number of redits x = at the beginning, whih entitles the holder to travel miles within one year. As shown in Senario II of Table 3, the annual mileage estimated from the model is similar to ase II of Table 2, whih are the results based on the road ongestion priing sheme given by Fowkes et al. (1995). It is also noted that the annual mileage did not hange in other three areas (onurbations, urban and rural) as we only onsider the TCS for the London area. To identify the effets of the redit prie, we implement a simulation with p 1,e = 0.5, as shown in TCS2, whih halves the redits prie whilst keeping other settings the same as in TCS1. As shown in Senario III of Table 3, the annual mileage for the private mode will derease whilst the annual mileage for the publi mode will inrease in the London area, ompared with Senario I without TCS. The differene between the annual mileage for the two modes demonstrate that the effets of the redit prie. The redit prie given in TCS1, p 1,e = 1, is the equilibrium prie alulated aording to Eqs (15) in Setion 2.4. Furthermore, omparing the annual mileage differenes for the private mode and publi mode in the London area (Comparing Senario II and Senario III in London area), we find that the redution in annual mileage for the private mode, (i.e =801.5miles), is not 13

14 equal to the inrease in annual mileage for the publi mode, (i.e =305.2miles). This demonstrates that in addition to individuals hanging from the use of the private mode to the publi mode, individuals hoose not to take some trips. Table 3 Annual mileages with a TCS in London under different senarios (Unit: annual average miles) Senarios Mode Purpose London Conurbations Urban Rural Total I Private Work Business Leisure Subtotal Publi Work Business Leisure Subtotal II Private Work Business Leisure Subtotal Publi Work Business Leisure Subtotal III Private Work Business Leisure Subtotal Publi Work Business Leisure Subtotal Key: senario I: Estimated annual mileage based on models U1 and U1 (without TCS); senario II: Estimated annual mileage with U2 and U2 (with TCS1) senario III: Estimated annual mileage with U2 and U2 (with TCS2) 4.2 Emissions impat We an further estimate the emissions impats based on the simulations outlined in Table 3. Aording to the statistis (Naei.defra.gov.uk, 2014), the UK emissions data is 133.7gCO2/km (82.89gCO2/mile) for a petrol ar, gco2/km (82.65gCO2/mile) for a diesel ar and gCO2/km (741.25CO2/mile) for a bus. Without loss of generality, we assume all vehiles are petrol ars with the higher emissions fator. From Senarios I-III given in Table 2, we an then roughly estimate 14

15 the emission differenes as given in Table 4. Furthermore, onsidering the inrease in annual mileage for the publi mode is small (fewer than 3 miles per day for Senario II and even less for senario III), we assume that the inrease in miles for the publi mode did not hange the operational aspets of that mode (e.g., bus operations) and therefore does not inrease publi mode emissions. We further assume a load fator for the private mode of 1, i.e, one ar orresponds to one person travelling in the TCS. Based on Senarios I, II and III given in Table 3, we an therefore alulate the annual CO2 emissions for the private mode aording to the emission fators. As shown in Table 4, omparing Senario I without a TCS and Senarios II and III with TCS1 and TCS2, the CO2 emissions for the private mode derease with the redution in VMT. Therefore, we an aim to ahieve both journey mileage and vehile emission redution targets with the implementation of a TCS, and further researh will explore this more. Table 4 Emissions differenes with a TCS in London under different senarios Senarios Mode Mileage (unit:miles) Emission (unit:gco2) Variane (unit:gco2) I Private II Private ( ) III Private ( ) 5. Conlusions The TCS has beome familiar to environmental eonomists as a pollution ontrol measure. This is in ontrast to the ase for many transport eonomists and transport management pratitioners, for whom it is yet a new and unfamiliar approah. Despite that, researhers in transport eonomis an see the potential of a TCS for road traffi mobility management, although it is lear that many theoretial and appliation related issues remain undeveloped. In this paper, we have disussed how a TCS affets travelers mode hoie using a simulation framework and measured the effets with respet to VMT and CO2 emissions. A simulation study in Great Britain has been arried out to illustrate the working of the proposed model. We onlude that a TCS provides a promising poliy option in reduing use of the private mode with respet to VMT. A ap-and-trade measure an ahieve a target for trip redutions by private mode (as refleted by VMT) by hanging travel mode-hoies. The design of a tradable redits sheme (inluding the setting of a redit prie) has been disussed. We emphasize that a TCS an learly affet travelers mode hoie under different redit pries, people an move from private mode to publi mode and even restraint their total trips under a TCS. From another perspetive, the presene of a TCS and a redution in private mode use an 15

16 bring a redution in total emissions. The tradable redit sheme studied in this paper disourages use of the private mode by imposing quantitative restraints and enouraging a swith to PT travel, whih ould result in further emissions redutions. The TCS ould be onsidered as an alternative to road ongestion priing and improve the transport system by restraining the growth of private mode trips and enouraging people to hoose the publi mode. This ould also bring benefits from vehile emission redutions. We assumed the inrease in miles for the publi mode did not hange the operational aspets and therefore does not result in an inrease in publi mode emissions. This ould be realized in pratie with the development of the lean bus with low or zero emissions, whih is an issue for future researh. Some other key issues for further study are: An in-depth disaggregated analysis of the effets of the TCS on mode hoie is neessary in order to explore how this type of sheme an deal with different mode hoies from different perspetives; Further development of the model is needed to integrate route hoie behavior under a marosopi transport network equilibrium analysis; From general equilibrium approah to disuss the relationship of ongestion, land use and management poliies; Poliy pakages are now favoured by many poliy makers as an effetive means to introdue behavioural hange. Pakages an be defined as any ombination of one or more eonomi measures with one or more other types of measures (regulatory, physial, tehnology). Further researh is needed to investigate how a tradable redits sheme ould interat with these other types of measures within suh a pakage. Aknowledgements We are grateful to the five anonymous reviewers for their valuable feedbak. The study is supported by the EU Marie Curie IIF (MOPED, ), and the National Natural Siene Foundation of China ( , ). The ontent is solely the responsibility of the authors and does not neessarily represent the views of the funding soures. Any remaining errors or shortomings are our own. Any views or onlusions expressed in this paper do not represent those of funding soures. Referenes Anas, A., and Kim, I., General equilibrium models of polyentri urban land use with endogenous ongestion and job agglomeration, Journal of Urban Eonomis, 40(2), Anas, A., and Xu.R., Congestion, land use and job dispersion. Journal of Urban Eonomis, 45, Anas, A., and Rhee, H.J., Curbing exess sprawl with ongestion tolls and urban boundaries, Regional Siene and Urban Eonomis, 36, Anas, A., and Rhee, H.J., When are urban growth boundaries not seond-best poliies to ongestion tolls? Journal of Urban Eonomis, 61,

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