There is considerable interest in, and support for diesel scrappage schemes. The challenge is to target polluting vehicles making the biggest contribution to poor air quality. In my recent blog on air quality, I said that it would be hard to devise a scrappage scheme for the more polluting diesel vehicles. On reflection, I can see a way forward.

The Mayor of London has advocated a national diesel scrappage fund. Transport for London has developed detailed proposals that involve targeting small businesses, charities, schools, low-income households and the oldest taxis, at a total cost for London of some £500m. The recent Defra/DfT Technical Report on reducing NO2 levels considers a national diesel scrappage scheme aimed at all pre-Euro 6 diesel cars and vans, and also a scheme to replace non-compliant vehicles with battery electric vehicles. The former is extremely expensive, while the latter makes very limited impact.

I propose that a scrappage scheme could be integral to the  Ultra Low Emission Zone (ULEZ) proposed for London, which would naturally target the vehicles making the greatest contribution to poor air quality.

The ULEZ will generate net revenue that could be used to fund a scrappage scheme. The targeted vehicles would be those that pay the largest cumulative charges for entry into the zone, since these make the greatest impact on air quality. The formula might be a contribution of £X00 to scrappage for every £1000 of cumulative charges – a cash-back offer. The value of X could be adjusted in the light of experience of uptake.

Owners scrapping a car or van under the scheme would need to provide evidence that the vehicle had been scrapped. To discourage replacement by a further polluting vehicle, it might be a condition of the scrappage scheme that the owner would not be allowed in future to pay the standard charge for entry of a non-compliant vehicle into the ULEZ, and would therefore incur the penalty charge should this be done.

Over time, as non-compliant vehicles are scrapped, revenue from the ULEZ would fall, as would NO2 levels. Depending on how far the latter was from the statutory limit, the scope of the zone could be extended, whether to more recent vehicles or to a wider geographic area.

I suggest that TfL considers in detail how a scrappage scheme might work as part of a the ULEZ, and what incentives might be sought from the Government to adopt such arrangements.

The Government recently published its latest draft Air Quality Plan for reducing nitrogen dioxide (NO2) in towns and cities. This followed loss of a court case in which the previous Plan was found wanting, particularly by not fully recognising the poor on-the-road emission performance of diesel cars, despite their seeming compliance with regulatory requirements in laboratory tests. This latest Plan has been criticised as inadequate by many protagonists and press commentators.

Nevertheless, the new draft Plan and accompanying Technical Report represent a significant advance analytically, being based on systematic review of options, assessed using multi-criteria analysis and cost-benefit analysis. Impacts include health benefits, social and government costs, time savings from improved traffic flow, and change in greenhouse gas emissions.

The starting point is that road transport is by far the largest contributor to NO2 pollution in the 40 local authorities in England where the statutory limit values are exceeded. London has much the highest level – mean annual concentration in excess of 100 μg/m3, compared with the statutory limit of 40 μg/m3.

The most cost-effective – indeed the only worthwhile – approach to mitigation is through establishing Clean Air Zones (CAZs) where targeted action is taken. The 2015 Plan proposed CAZs in London and 5 other cities. This 2017 Plan extends coverage to 27 in all, reflecting updated assumptions about diesel emissions.

A key issue is whether a CAZ should require that the more polluting vehicles be charged for entry. For locations where NO2 levels are only modestly in excess of the legal limit, measures other than charging may suffice. Nevertheless, the Technical Report models the impact of charging in all 27 cities, which would involve set-up costs of £270m. For 12 of these, charging could be limited to public service and goods vehicles, but for 15 it would need to extend to cars not compliant with the latest Euro 6 diesel standard. The main impact of charging is assumed to be a two-thirds reduction of trips by non-compliant cars. A charging CAZ is projected to result in an 18% reduction in NO2 levels in the first year of impact.

A variety of other measures to reduce NO2 levels are considered in the Report. One approach that has attracted much support is for a scheme to offer payments to owners to scrap older polluting vehicles. The Report states that a national scheme to scrap all pre-Euro 6 diesel cars and vans could cost £60 billion. A scheme limited to replacement by battery electric vehicles assumes that only 15,000 vehicles would be scrapped.

The Report does not consider targeting by area, for which London would have a strong case for funding given the high NO2 levels, although this would be politically contentious. High mileage polluting vehicles would be the target. However, the difficulty is that the oldest vehicles tend to be both most polluting per distance travelled but least used, and owned by low-income households for whom the cash incentive would need to be high. So a well-targeted scrappage scheme seems hard to devise.

Transport for London is consulting on an Ultra Low Emission Zone (ULEZ) – effectively a charging CAZ – to cover the same area as the Congestion Charge. Non-compliant cars and vans will be charged £12.50 a day, which will apply 24/7 from April 2019. This is in addition to an emissions surcharge on top of the congestion charge for pre-Euro 4 cars and vans of £10 from October 2017. There is also a London-wide Low Emissions Zone in operation since 2008 that charges polluting heavy diesel vehicles.

On introduction, the ULEZ is projected to reduce the proportion of road kilometres exceeding limit NO2 values in Central London from 82% to 70% – a moderate air quality benefit but far from sufficient. This suggests that the charge and/or scope may need to be increased in future.

Introducing the ULEZ is relatively easy in London, given the existing of the Congestion Charge arrangements for payment and enforcement. Other cities needing to adopt a charging CAZ could adopt the technology used by London, in which case it would be natural to use it for congestion charging, both to manage peak demand and to raise revenue for investment in local transport. If 27 cities have such arrangements, this constitutes the nucleus of a national road user charging framework, which could be used to raise revenue for the road system as electric vehicles gradually take over, given that these do not pay fuel duty. The Government’s ambition is for all new cars and vans to be zero emission by 2040, and for nearly every car and van to be zero emission by 2050.

Seeing charging CAZs as a precursor to general road pricing would be contentious. This may be why the Government wished to delay publishing its draft Air Quality Plan until after the election, and why in the published consultation document the Government has been coy about charging, stating: ‘The Government believes that charging zones should only be used where local authorities fail to identify equally effective alternatives.’ The analysis presented suggests that the alternatives are unlikely to be sufficient.

The present objective is to reduce NO2 emissions to below the statutory limits specified in the EU air quality directive. However, Britain is to leave the EU, which may open other possible approaches, for instance setting policy targets expected to be achievable with available technologies and resources, balancing benefits against costs. In the long run, the problem of transport NO2 emissions will be solved by switching to electric vehicles – which arguably should be the policy priority.

This blog is the basis for a Viewpoint article in Local Transport Today of 26 May 2017.










Most air travel forecasts predict a long-term rise in demand, with limited consideration of any limits to growth. However for any given population there will be those who have not flown recently, as well as those who never have flown. For the UK, about half the population respond to travel surveys that they did not fly in the previous 12 months. We call these the ‘infrequent flyers’.

Little is known about this group, including  whether they are likely to fly in the future. Anne Graham, of the University of Westminster, and I recently published findings of an analysis of the characteristics of this group and the reasons for their travel habits, using a survey commissioned by the UK Civil Aviation Authority. We found that infrequent flyers make up a heterogeneous consumer group whose non-flying is influenced more by budget constraints and personal circumstances than specific aviation factors such as fear of flying.

The proportion of infrequent flyers in the UK population has remained stable over time. Our findings do not suggest that this is likely to change in the future, so the infrequent flyers are unlikely to be a source of future demand for air travel on account of their increased propensity to fly.

Our paper: Graham&Metz JATM Infreq flyers published

I have for some time taken issue with the way the UK Department for Transport (DfT) plays down the economic benefits of land and property development that result when new transport investment makes land more accessible. While DfT recognises that housing developments may be dependent on provision of new transport services, the associated economic benefit is not included in the estimation of the benefit:cost ratio that determines the value for money of the transport investment.

The Department for Communities and Local Government (DCLG) recently published its Appraisal Guide.  This states (para 3.9):

‘….changes in land values as a result of a change in land-use for a development reflect the economic efficiency benefits of converting land into a more productive use. Land value data should be the primary means of assessing the benefits of a development. Land value data is a rich source of information because it is actual market data on individuals’/firms’ willingness to pay for a piece of land. Assuming individuals and firms are rational in their decision-making, market prices should reveal the ‘true’ private benefit of a development. This information can be used to undertake cost benefit analysis to quantify the potential welfare implications of a development.’
So there is a marked difference in the way two government departments treat land value uplift in economic appraisal, which is pretty odd. My view is that DCLG has the right idea. DfT is wedded to a theoretical framework that focuses on benefits to users of the transport system, and assumes that land use is unchanged. But this flies in the face of extensive evidence that transport investment that makes land more accessible can trigger development – London’s Docklands is a prime example of rail investment making land accessible for development. DfT should adopt an evidence-based approach, using evidence of outcomes from completed investments to inform the case for prospective investments.

The current main method of adding capacity to UK motorways is known as Smart Motorway All Lane Running. This involves allowing traffic to use the hard shoulder (previously reserved for breakdowns), with speed controls to respond to accidents and congested conditions. This approach has been applied to a section of the M25, London’s orbital motorway, increasing running lanes from 3 to 4. A monitoring report after two years of operation has been published. The main findings, compared with before the scheme was introduced: traffic flows up by as much as 17%, well above the regional trend (5%); some journey times increased by up to 8%; and only a slight improvement in reliability. Significantly, the biggest increases in traffic occurred at weekends (as much as 26%).


The intention of investment to increase the capacity of the Strategic Road Network, of which the M25 forms an important part, is to improve connectivity between cities and reduce congestion. However, roads like the M25, that are located in densely populated areas, are also used by local users for their daily travel. Any increase in capacity offers opportunities for more or longer local trips.The resulting extra traffic restore congestion to that it had been prior the the investment in capacity. The findings of the present study are consistent with this general experience. Regrettably, there is no data on the composition of the traffic, by journey purpose or distance travelled. However, the finding of a big increase in weekend traffic is consistent with leisure users taking advantage of initially faster travel to reach more distant destinations.

The findings of this report confirm the phenomenon of ‘induced traffic’ – the traffic that results from additional road capacity – as I discussed recently in connection with the CPRE study. Such traffic adds to congestion and so reduces the time savings expected from such investment, time savings that constitute the main economic benefits presumed to justify the investment.


Bruce Schaller, an expert on urban transportation, has published an informative and insightful report on the impact in New York City of what he calls ‘Transportation Network Companies’ (TNCs) such as Uber and Lyft. Use of these providers of app-based ride services has grown rapidly, more than doubling in each of the past four years. This reflects the popularity of the services offered, which reduce anxiety, uncertainty and stress, not least by providing assurance of a vehicle in situations where hailing the traditional yellow cab may be problematic.

The contribution of the TNCs to congestion has been a matter of controversy. The present report confirms a previous study carried out by the NYC authorities which found that worsening congestion was driven primarily by increased freight movement, construction activity, pedestrian volumes and record levels of tourism, all of which put growing demands on the streets’ limited capacity. However, use of TNCs continue to grow, raising the question of their future impact on congestion.

A key question is whether TNC growth is making more efficient use of scarce street space by putting more passengers in each vehicle, as with UberPool which offers low fares for trips shared with others? Or does it add to traffic by diverting people from high capacity services such as rail and bus, for which evidence of a recent decline in ridership is suggestive? The available evidence as a whole is insufficient for a definitive answer, but the report suggests that diversion is likely to be more important, implying  that TNC’s add to congestion.

The report is concerned that TNCs are fundamentally undoing the cost incentives to use public transport. NYC taxi fares were traditionally set at about 4.5 times the subway fare to encourage the use of transit (public transport). However, as they cut fares, the TNCs are beginning the erase these disincentives to road vehicle use. These fares do not reflect the costs of time delays arising from congestion, hence there would be a case for some kind of congestion charging.


Congestion is self-limiting in that as traffic builds up, for instance from more TNC vehicles, speeds drop, trips take longer, and some road users make alternative decisions, for instance to travel at a less busy time, or to go to a different destination, or to use the subway. So it is not to be expected that growth of TNCs would worsen congestion in already congested parts of NYC. The switch of people from the subway to TNC services would be limited for the same reason.


An excellent report on the impact of road investments has been commissioned by the Campaign to Protect Rural England from Lynn Sloman and colleagues. This report re-examines the outcomes of a number of Highways England road schemes, finding average increased traffic above control levels in the short run (3-7 years) of 7% and in the longer run (8-20 years) of 47%. This is clear evidence for substantial ‘induced traffic’ generated by new capacity. The CPRE study also find very limited evidence for benefits to the local economy from road investments.

These findings pose problems for the  Department for Transport’s WebTAG approach to the economic appraisal of road schemes, in which time savings to users is the dominant benefit. However, induced traffic tends to restore congestion to what it had been, lessening time savings. If induced traffic were properly taken into account, the apparent value of the investment would be substantially less. Moreover, the orthodox approach assumes unchanged land use, yet the CPRE report documents extensive land use change in four detailed case studies. Such changes have implications for local economies, not necessarily wholly advantageous if these take the form of low-wage employment in warehouses or car-dependent residential development.


The main policy objective of the current UK national road investment programme is to boost economic growth by improving inter-urban connectivity and reducing congestion. Each scheme of the programme must offer acceptable value for money on the orthodox approach to appraisal, yet this approach overstates benefits by underestimating induced traffic and disregards changes in land use made possible by improved access. We need an evidence-based approach to investment appraisal, in which careful evaluation of completed schemes of the kind commissioned by the CPRE informs appraisal of prospective investments.

The National Infrastructure Commission (NIC) has been issuing Discussion Papers for comment. I have previously blogged about the paper on technology.

Two further NIC papers are of interest: one concerns the relation between economic growth and the demand for infrastructure, where it is assumed that these are closely correlated. In my response (Metz NIC Econ growth 28-3-17 ) I argued that, for transport, this is far from the case, with demand saturation an important phenomenon.

The other discussion paper concerned the impact of population change and demography  My response (Metz NIC population 23-1-17 ) drew attention to the importance for transport infrastructure investment of where a growing population is housed : greenfield housing leads to road investment, urban densification requires investment in public transport.

My new book, Travel Fast or Smart?, is one in a series of short books on policy and economics topics described as ‘essays on big ideas by leading writers’. My contribution is a critique of the inconsistencies of transport policy in recent decades, which I attribute to the shortcomings of conventional transport economic appraisal in identifying the benefits that arise from investment.  This book is available both in print and as an ebook from Amazon Books

Transport for London (TfL) has published an illuminating report on the topic of Land Value Capture (LVC) – the way in which transport investments could be funded from a share of the increased value of land and property that follows when access is improved as a result of the investment. This study was carried out in response to a request from the Government for detailed proposals.

The range of possible approaches to LVC is wide, and overseas experience is relevant. A conclusion is that of past projects, the Jubilee Line Extension to Docklands resulted in land value uplifts of 52% relative to controls, and the Docklands Light Railway extension to Woolwich, 23%. For eight prospective TfL projects costing around £36bn, land value uplifts could be £87bn. So plenty of value that could help fund these new investments.

The Annexes to the main report are interesting, particularly Annex 7, the literature review of the theory and practice of the relationship between transport and land value, a relationship which does not form part of the orthodox approach to cost:benefit analysis of transport investment. The orthodox approach is concerned with benefits to users, particularly time saved through faster travel. The orthodox view is that to include the uplift of the value of land made more accessible by the investment would double count benefits that accrue to users. However, the user benefits are notional, based on the outputs of transport models, whereas the land value uplifts are real and observable.


The TfL report is important, both to identify possible ways of using LVC to fund new projects, and also to assert the relevance of land value uplift as a measure of the economic impact of transport investments. Chris Grayling, Secretary of State for Transport, in a speech on 6 December 2016, recognised the case for LVC:

I want to look at innovative ways of funding infrastructure development. Often the opening of a new road or a new railway line or station can transform the value of development land. It is right and proper that the government gets back some of the value it has created to invest in infrastructure. We have seen this happen for Crossrail through the mayoral community infrastructure levy.

My new book, Travel Fast or Smart?, is one in a series of short books on policy and economics topics described as ‘essays on big ideas by leading writers’. My contribution is a critique of the inconsistencies of transport policy in recent decades, which I attribute to the shortcomings of conventional transport economic appraisal in identifying the benefits that arise from investment.  This book is available both in print and as an ebook from Amazon Books

There is much current interest worldwide in the concept of Mobility-as-a-Service (MaaS), the aim of which is to provide seamless journeys using the most appropriate travel modes, routed and ticketed by means of a smart phone app. The MaaS provider ‘aggregates’ the services provided by transport operators (in the way that Amazon acts for retail product providers). MaaS is intended to be an attractive alternative to private car ownership. The Transport Catapult has recently published a report on the opportunities for MaaS in the UK. And the New Cities Foundation has addressed the role of public transport operators in its development.

There are many recognised technical and policy issues that need to be tackled, including managing the large amounts of data, and coordinating ticketing and payments on behalf of a multiplicity of operarors. However, there are two aspects that deserve particular consideration. The first is the ability of MaaS to cope with peak travel demand.

Peak demand

Daily travel demand is characterised by morning and evening peaks, and there are also seasonal variations. Peaks result in road congestion and crowding on railways. One approach would be to charge higher prices at times of greatest demand, with the aim of spreading the peak. This model has been adopted in the aviation sector, led by the low-cost carriers, and by Uber for urban taxis (and also in other sectors such as hotels). The railways offer off-peak discounted fares, but do not flex fares upwards to reflect actual peak demand.

However, unless peak pricing is part of the public transport provision (which at present it is not), the scope for coping with peak demand for multi-modal journeys is quite limited. This means that unreliability of travel time for each stage of a journey would present a scheduling problem.

While MaaS comprises a minority of all trips, congestion would be a given, and scheduling would need to allow for expected journey stage times plus a margin for uncertainty, with rerouting in the event of unexpected congestion. On railways, consideration would need to be given to offering alternatives to overcrowded trains. Such dynamic scheduling could be technologically challenging.

Were MaaS to grow to encompass a substantial part of travel demand, there may be scope for routing travellers to spread demand across the network in a way that optimises overall efficiency, simplest for routes that involve stages with assured reliability – rail, bus rapid transit, walking and cycling. There would also be scope to consolidate car trips by means of shared taxis, as with UberPOOL. However, such sharing, incentivised by lower fares, could attract passenger from buses, which could add to congestion.

If MaaS were to be a major intermediary in meeting travel demand, a significant operational issue would be whether to respond to peak demand for door-to-door travel by mobilising more taxis through surge pricing, as does Uber. Surge pricing to deter demand and increase supply is sensible in the absence of congestion, but may not be optimal under congested conditions. In the absence of surge pricing, demand would exceed supply and would be rationed by waiting in a virtual queue until a taxi becomes available. With surge pricing, there is a greater supply of taxis and so less waiting time, but journey times might be slower on account of increased congestion. Which approach would be optimal would require modelling.

Surge pricing works well for aviation, a closed system where an aircraft can only fly if it has airport slots allocated at trip origin and destination. But roads are an open system and hence prone to congestion at peak times in populated areas. MaaS would be more straightforward to implement in lower density areas, less so in urban centres, unless private cars were entirely replaced by a fleet of shared use self-driving vehicles, as has been suggested.

Who owns the platform?

The question of how MaaS can best cope with peak demand is linked to the second problem – the nature of the platform by means of which demand and supply are matched, prices set and revenues allocated. The central issue is familiar: benefits of competitive supply versus benefits of an integrated network. Experience is varied. In the case of buses, Mrs Thatcher’s government opened the bus services outside London to competition with minimal regulation, hoping to benefit users by on-the-road competition between private sector operators. This largely failed to materialise since such competition resulted in unattractive profit margins. In consequence, the present Government has introduced legislation that would allow other cities to adopt the successful London model, whereby an integrated public transport network is operated by a politically controlled public body, Transport for London.

For MaaS, the question is whether an open source public platform would naturally evolve on account of the superior benefits, as envisaged by the TravelSpirit collaboration. Or whether competition in the market between competing platforms would be the main driver, with perhaps a dominant platform emerging through economies of scale and scope.

A dominant private sector platform might need to be regulated to avoid market failure that allowed economic rents to be extracted at the expense of users. The MaaS provider would have access to all the data arising from use of the system. Fair sharing of this data with transport providers would help meet the needs of users. On the other hand, discriminatory sharing could increase returns to the provider.


Traffic congestion is the main problem of the road system. A key question is whether MaaS has the potential to lessen traffic congestion. If it does, then promoting MaaS could be a sensible transport policy, in which case a view would need to be taken of the relative attractions of competing platforms versus a single public platform.

In the longer run, developments in shared use driverless urban vehicles might achieve substantial mitigation of urban traffic congestion. Sharing of taxis would increase vehicle occupancy and hence efficiency of the road system; demand management could limit use of single occupancy vehicles under congested conditions; and the development of vehicle-to-infrastructure communications could permit flow management, analogous to air traffic control. In such circumstances, MaaS would be likely to be an integral part of an urban transport management system. However, development of such a system would be challenging in respect of technology, business models, institutions and public acceptability – hence the feasibility and timing is uncertain. In the meantime, development of MaaS in urban areas would need to cope with traffic congestion.