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The London LEZ - An Economic Evaluation
1. The London Low Emission Zone
An Economic Evaluation
Isobel Daley
Dissertation submitted in part-fulfillment of the MSc in Economics,
University College London
September 2015
1
2. Abstract
The objective of this study is to economically evaluate the impact of the
London Low Emission Zone (LEZ). Introduced in 2008, the LEZ aims to
improve air quality by levying a charge on vehicles in violation of a specified
set of emissions standards. The LEZ offers vehicle owners the opportunity to
comply with the scheme in four main ways: by replacing the vehicle, modifying
the vehicle, paying the charge or avoiding the zone. The response chosen by
affected drivers underpins the overall performance of the scheme.
To quantify the costs and benefits relating to the LEZ, two blocks of em-
pirical work are presented. The first quantifies the benefits by identifying
changes in air quality that have arisen as a result of the scheme. The second
empirical section estimates the overall costs of the scheme by evaluating the
magnitude of each of the four behavioural responses.
Overall, the findings indicate that the scheme failed to generate sufficient
air quality improvements to justify the high costs of compliance.
2
3. Contents
1 Introduction 6
2 Background 7
3 Literature Review: Low Emission Initiatives Worldwide 10
4 A Model of Decision-Making 13
5 Benefits of the LEZ 16
6 Costs of the LEZ 27
7 Cost Benefit Analysis 50
8 Discussion 52
9 Conclusion 53
References 55
A List of Acronyms 56
B Impact of LEZ on Air Quality: Complete Results 57
C Categorisation of Postcode Areas 62
D Vehicle Cost Price 64
E Discounted Net Costs of LEZ 2005-7 65
3
6. 1 Introduction
Having frequently struggled to meet European Union (EU) and UK standards for Partic-
ulate Matter (PM10) and Nitrogen Dioxide (NO2)1
, London is often considered to have
one of the worst air quality records in Europe. It was in this context that the introduc-
tion of a Low Emission Zone (LEZ) was proposed as a measure to improve air quality. In
February 2008, the first phase of this scheme came into operation. By levying a charge
on all heavy vehicles that do not conform to specified emissions standards, the LEZ aims
to reduce environmental pollution by encouraging the adoption of green technology.
The purpose of this report is to quantify the costs and benefits of the LEZ across the
period 2008-14. This will provide an insight into the scheme’s overall performance, as
well as allowing lessons to be taken and applied to the design of similar schemes in the
future.
Underpinning the performance of the scheme (i.e. scale of environmental benefits versus
compliance costs) is the behavioural response chosen by those affected. They can respond
in one of four ways:
• Replacement: A vehicle can be replaced with an alternative that meets the pre-
scribed standards.
• Modification: A vehicle-owner can choose to modify their vehicle in one of three
ways to become compliant:
– The engine can be changed to meet the required specification
– A filter can be fitted to the vehicle to reduce emissions of particulates
– The vehicle can be converted to run on gas
• Pay the Charge: A vehicle owner can pay the charge on each day it drives within
the LEZ boundaries
• Drive Around the LEZ: The LEZ can be avoided entirely. This may mean taking
longer routes to reach destinations or turning down business within the LEZ.
To evaluate the success of this scheme, two blocks of empirical work are presented. The
first aims to quantify the benefits by identifying changes in air quality, both inside and
near the LEZ, that have arisen as a result of the scheme. Using panel data on atmospheric
concentrations of PM10 and NO2 from a large number of locations across the UK, a fixed
effects approach is used to isolate changes in ambient concentrations attributable to the
1EU and UK standards for PM10 concentrations require that the daily mean does not exceed 50g/m3
on more than 35 days a year and the annual mean must be less than 40g/m3. NO2 concentrations
must not exceed 200g/m3 on more than 18 days a year and the annual mean must be less than 40g/m3.
These standards are set out in directive 2008/50/EC (European Commission, 2008) and The Air Quality
Strategy for England, Scotland, Wales and Northern Ireland (Volume 1) (Department for Environment,
Food and Rural Affairs, 2007).
6
7. policy. The health impact of the LEZ is then quantified through the application of existing
epidemiological estimates linking pollutant concentrations to health outcomes.
The second block of empirical work evaluates the overall costs of the LEZ by estimating
the magnitude of each of the four behavioural responses. The vehicle replacement response
is estimated using data, provided by the Driver and Vehicle Licensing Agency (DVLA),
on UK vehicle registrations by postcode area. Modifications are assessed using Transport
for London (TfL) records on registered low emission vehicle adaptations. The cost to
those who choose to pay the charge is identified through inspection of TfL financial data.
Finally, traffic count data, published by the Department for Transport (DfT), is used to
understand whether the LEZ triggered an exodus of commercial vehicles from London to
its surrounding areas.
Combining these estimated costs and benefits, this study finds that the London LEZ failed
to generate a sufficient improvement in air quality to justify the high costs of compliance.
Moreover, the evidence indicates that the scheme only temporarily accelerated the adop-
tion of green technology. As a result, it is likely that any air quality improvements would
have been realised, even in the absence of the scheme, a few years later.
Existing studies of the London LEZ have primarily made use of descriptive statistics
to assess the performance of the scheme across its first two phases only (implemented
February and July 2008). This study therefore contributes to the literature in two main
ways. First, through the application of econometric techniques this study is better placed
to isolate the causal effects of the scheme. Second, by using data that spans the period
2004-14 the impact of all three phases can be assessed.
This article proceeds in the following way. Section 2 outlines the key features of the LEZ,
placing it in the context of London road pricing as a whole. Section 3 considers existing
research into the impact of low emission initiatives around the world. Section 4 proposes a
conceptual framework of decision-making. This formally sets out the factors influencing
the behavioural response chosen by affected drivers. Section 5 presents the empirical
strategy employed to identify and quantify the benefits of the LEZ. Section 6 computes
the cost of the scheme by estimating the magnitude of each behavioural response. The
costs and benefits are brought together in section 7 to evaluate the overall success of the
scheme. Discussion and conclusions follow in sections 8 and 9.
2 Background
2.1 Externalities and the LEZ
An externality is said to occur when one party (a person, firm etc.) engages in an activity
that affects a third party. Introduced in 2008, the London LEZ aims to tackle one
7
8. externality associated with road usage - poor air quality - by encouraging the adoption
of low emission vehicles. Poor air quality negatively affects populations by causing and
exacerbating respiratory, cardiovascular and other health conditions. These conditions
can significantly impair quality of life and lead to a reduction in life expectancy.
The London LEZ works by levying a charge on non-compliant vehicles entering an area
that covers most of London (see Figure 1). It has two key objectives:
1. To improve the health and quality of life of those living and working within the LEZ
2. To meet air quality objectives set at a national and European level
Figure 1: Map of London LEZ
Implemented in three phases, this scheme mainly targets heavy vehicles. As such it is
predominantly businesses that are affected. Table 1 below details the characteristics of
all vehicles affected by the scheme and the daily charge due upon entering the zone.
8
9. Table 1: LEZ Vehicle Restrictions
Vehicle Type
LEZ
Phase
GVW
(tonnes)
Reg.
before
Daily
Charge
Lorries, Breakdown and Recovery
Vehicles, Concrete Mixers, Fire Engines,
Gritters, Motor Caravans, Motorised
Horseboxes, Refuse Vehicles, Road
Sweepers, Snow Ploughs, Tippers
Phase 1:
Feb 2008
> 12 Oct
2001
£200Phase 2:
Jul 2008
>3.5
Phase 3:
Jan 2012
>3.5 Oct
2006Buses, Coaches (more than 8 passenger
seats)
>5
Large vans, 4X4 Light Utility Vehicles,
Motorised Horseboxes, Pickups
1.205-
3.5
Jan
2002
£100
Ambulances, Motor caravans 2.5-3.5
Notes: GVW is Gross Vehicle Weight
2.2 Road Pricing in London
The London LEZ is one of three main road pricing instruments currently used, or proposed
for use, within London to tackle externalities associated with vehicle usage. To place the
LEZ within the wider context of London road pricing schemes, and to understand possible
interactions or overlaps between policies, the Congestion Charge and Ultra Low Emission
Zone are outlined below.
Congestion Charge (CC)
Introduced in 2003, the CC aims to combat the issue of traffic in Central London. All
vehicles entering or leaving a specified zone of 21km2
between the hours of 07:00 and 18:30
Monday to Friday are required to pay a daily charge of £11.50. Compliance is ensured
by means of Automatic Number Plate Recognition (ANPR) software. This operates at
all entry/exit points along the perimeter of the CC zone. This infrastructure is now also
shared by the LEZ, an arrangement which has reduced the implementation costs of the
scheme.
The LEZ and the CC both aim to address the social costs of vehicle use. However,
there are a number of important differences. Whilst the LEZ operates continuously, the
CC is enforced only during standard weekday working hours. Further, the CC affects all
vehicles, whilst the impact of the LEZ is limited to heavier, generally commercial vehicles.
Finally, the LEZ covers a much larger area and therefore its geographical effects are more
widespread.
Whilst the clearly stated objective of the CC has always been to reduce congestion, it is
interesting to note that alternative-fuel vehicles are exempt from paying the charge. In
9
10. this way, the CC scheme does appear to conflate the objectives of traffic management and
environmental improvement.
Ultra Low Emission Zone (ULEZ)
In early 2015 the Mayor of London, Boris Johnson, confirmed the introduction of an
ULEZ by 2020. Spanning the same area as the CC, this scheme will require all vehicles
entering the zone to comply with a set of emission standards. Crucially this scheme,
which will operate continuously, will affect both domestic and commercial vehicles. In
this sense, the ULEZ is a design hybrid, encompassing features of both the CC and LEZ.
Whilst the parties affected by the ULEZ differ from those affected by the LEZ, the
economic principles underlying the scheme are similar. Owners of non-compliant vehicles
will have the option to respond in a number of ways. The chosen behavioural response
will fundamentally determine the scheme’s impact on air quality. With this in mind,
lessons may be taken from the LEZ and applied to the design of the ULEZ to help ensure
that the policy’s air quality objectives are met.
3 Literature Review: Low Emission Initiatives World-
wide
Whilst LEZs are becoming an increasingly popular method of pollution control, empirical
studies evaluating their impact are few in number. This section draws lessons from related
papers on the impact of low emission initiatives around the world. Aspects that are
particularly relevant to the methodology employed in this study are highlighted.
3.1 Germany
Germany, with 47 separate schemes in place, has become the most prolific adopter of
LEZs. This contrasts sharply with the UK, where London constitutes the only significant
LEZ.2
The nature of the restrictions placed on vehicles is also different. Whilst London
places restrictions on larger, almost exclusively commercial, vehicles, all 46 million Ger-
man vehicles are affected. Each is required to display a coloured sticker that indicates its
PM10 class. Any vehicle that does not meet the required pollution standard, given by its
coloured sticker, is banned from entering the LEZ. Violation of this rule results in a fine
of 40 Euros as well as a one penalty point on the driver’s license.
The multiplicity of German cities with and without an LEZ provides a strong foundation
on which to assess their impact. Wolff (2013) makes use of a panel data set consisting
2Brighton, Norwich, Nottingham and Oxford have minor LEZ schemes in place. Each of these schemes,
spanning a limited geographical area, affects public buses only.
10
11. of daily pollution and meteorological measurements, obtained from a treatment group
(cities with LEZ) and a control group (cities without LEZ), to estimate the effects of the
schemes. Using a difference-in-differences approach, he finds that PM10 levels drop by a
statistically significant 9% in LEZ areas with high volumes of traffic. However, air quality
effects of the LEZ are not evident in areas away from major roads.
Wolff’s investigation highlights an important point: air quality within the LEZ cannot
be considered in isolation. Spatial-substitution effects, in which dirty vehicles are substi-
tuted for clean vehicles in areas near the LEZ, must also be considered. Wolff considers
this spatial-substitution effect by assessing vehicle fleet composition. He finds that the
adoption of low emission vehicles increases with proximity to an LEZ. Based on the as-
sumption that those living closer to the scheme will require more frequent access to the
LEZ, he concludes that there is evidence of spatial substitution.
This investigation into the London experience applies a similar econometric based on
the difference-in-differences approach. Air quality monitoring stations are assigned to
either one of two treatment groups (inside or near the LEZ) or a control group (far from
the LEZ) based on location. In this way, by considering changes in areas surrounding
the LEZ, geographical spillover effects are explicitly considered. In the case of London,
spillover effects could be either positive or negative. If drivers choose to avoid the zone by
driving around the outside, one may expect a deterioration in air quality in surrounding
areas. Alternatively, as illustrated by the German experience, adoption of green vehicles
may also accelerate in nearby areas, thus leading to a reduction in ambient pollutant
concentrations.
3.2 Mexico
An example of a low emission scheme that failed to meet its objectives, as a result of unan-
ticipated behavioural response, can be found in Latin America. In 1989, the authorities in
Mexico City introduced a scheme known as Hoy No Circula (HNC). Translated literally as
“today you can’t drive”, the scheme aims to improve air quality in the area by prohibiting
drivers from using their vehicles on one weekday each week between 5am-10pm. The day
on which a vehicle is banned from the road depends on the last digit of its number plate.
Davis (2008) employs a two-pronged empirical strategy to investigate the effect of this
programme on air quality, across the period 1986-2005. First, he runs a time-series
regression of hourly air pollution on a dummy variable which assumes a value of one for
dates following the scheme’s implementation and includes a number of controls. Second,
he uses a regression discontinuity design to remove the issue of omitted variables, which
may bias the time series estimate. Under both specifications, he finds little evidence of any
improvement in air quality following the introduction of HNC. An important drawback
of this study’s empirical approach is that no monitoring stations outside of Mexico City
are used. This prevents the robust construction of counterfactual emissions through the
use of a control group.
11
12. A key point that can be taken from this study is that the success or failure of any scheme
depends crucially on the behavioural response of drivers. Therefore, to better understand
why air quality in Mexico City appears unaffected, Davis investigates how drivers reacted
to the scheme. Many vehicle owners responded to restrictions by purchasing an additional,
often second-hand, vehicle. Assuming that the last digit of the number plate differed from
that of their existing car, drivers could drive on any day of the week thus sidestepping
HNC controls. This issue, which seems to have been the major factor that prevented
HNC from meeting its objectives, is exacerbated by the fact that older (i.e. second-hand)
vehicles generally have higher emissions.
An important lesson drawn from this example is that the behavioural response to a policy
fundamentally determines its success. The London LEZ allows affected vehicle owners
flexibility in the way that they behave. Ultimately, the action vehicle owners choose
to ensure compliance with the LEZ will determine the total cost and benefits of such
a scheme. For this reason, this evaluation of the London LEZ explicitly models the
magnitude of each behavioural response.
3.3 London
A paper by Ellison, Greaves & Hensher (2013) is one of the few examples that considers the
effects of the London LEZ. In common with this study, the authors use vehicle registration
data from the DVLA (2006-11) and information from the London Air Quality Network
(LAQN) managed by Kings College London (KCL) to understand the impact of the
scheme on vehicle composition and air quality during its first four years.
Through analysis of the high-level trends of fleet composition, they find that the share of
non-compliant vehicles registered in London, as a proportion of all rigid vehicles, drops
more quickly than the national average.
Changes in air quality are assessed by considering PM10 readings at three locations inside
the LEZ (Sutton, Enfield, Hackney) and one near the LEZ (Sawbridgeworth). Inside
the LEZ, they find an average annual reduction in emissions of 2.46-3.07% over the past
decade. Outside of the LEZ, annual emissions decreased by an average of just over 1%.
Following the introduction of the LEZ, those monitoring stations inside the zone have
shown stable or declining PM10 concentrations, whilst there has been an increase in
emissions at Sawbridgeworth. Ellison et al notes that the volume of Heavy Goods Vehicle
(HGV) traffic entering the LEZ has increased. This would lead one to expect an increase
in PM10 concentrations. Since this increase has not been observed, he concludes that the
LEZ has had a small impact on air quality.
As an evaluation of the LEZ, the Ellison et al (2013) paper is subject to a number of
limitations. First, through the use of simple trend analysis, there is no way of separating
the impact of the LEZ from other factors that may affect pollutant concentrations. It
is not possible to draw the robust conclusions that the scheme is the cause of all (or
12
13. part) of the reduction in emissions and change in fleet composition. Second, the air
quality analysis performed in this study relies on very small sample sizes. There is no
information to advise the reader how these have been selected. This sample may not be
representative of the scheme as a whole. Third, by using data that spans 2006-11, it is
not possible to draw inference about the impact of the third and largest phase of the LEZ,
which was implemented in 2012.
This investigation aims to address these limitations by employing a dataset that spans
the introduction of all three phases of the LEZ and encompasses a larger sample size.
Econometric techniques will be used to isolate the causal effect of the LEZ.
4 A Model of Decision-Making
The model below, loosely based on a paper by Alberini, Harrington & McConnell (1995),
provides a conceptual framework with which to understand the factors that influence the
particular behavioural response chosen by vehicle owners affected by the LEZ.
Given that the LEZ predominantly affects commercial vehicles, it is assumed that busi-
nesses comprise the relevant decision-making unit and that they act to maximise profit.
Each decision-maker i will therefore select their behavioural response j in order to max-
imise the present value of profit ⇡⇤
ijt in each period of time t. However, the underlying
profit function ⇡ijt for each business is private information. Therefore, only the selected
response is observed.
⇡⇤
ijt = max(⇡i1t, ⇡i2t, ..., ⇡int)
In each period (t = t
0
), a business can choose to meet its obligations under the LEZ in
one of the four ways previously outlined. Each response is associated with a different
underlying profit function (detailed below). It is assumed that this underlying profit
function will determine the selected response.
• Replacement: Should a business choose to replace its non-compliant vehicle with
one that meets LEZ requirements, the present value of profit is comprised of the
present value of driving services
P1
t=t0 Vit minus the cost of running a compliant
vehicle
P1
t=t0 AC
it, the profit (or more likely loss) from selling the non-compliant
vehicle which consists of the selling price SNC
it minus the original purchase price
KNC
, and the potential profit that could be expected should the new vehicle be
sold SC
it KC
it :
⇡i1t =
" 1X
t=t0
Vit AC
it
#
+ SC
it KC
it + SNC
it KNC
it
13
14. • Modification: A vehicle can be modified to meet the required standards. The
cost of the modification Mi is subtracted from the net present value of driving a
non-compliant vehicle (modification is assumed to leave running costs unaffected)
plus the net resale value of a modified vehicle where SM
it is the resale value:
⇡i2t =
" 1X
t=t0
Vit ANC
it
#
+ SM
it KNC
it Mi
• Pay the Charge: By paying the charge the present value of the profits is given by
the net present value of driving services plus the net resale value of a non-compliant
vehicle minus the cost of the charge Ci multiplied by the number of periods in which
the vehicle intends to drive inside the LEZ today and in the future Lit:
⇡i3t =
" 1X
t=t0
Vit ANC
it
#
+ SNC
it KNC
it CiLit
• Drive around the LEZ: A non-compliant vehicle can choose not to drive inside
the LEZ. In this case, it is assumed that the net present value of driving services is
given by V R
i AR
it. Therefore, the present value of profits is given by:
⇡i4t =
" 1X
t=t0
V R
it AR
it
#
+ SNC
it KNC
it
To complete the model, a number of assumptions are made. First, the running costs of
non-compliant vehicles are greater than the costs of running a compliant vehicle. Compli-
ant vehicles will invariably be newer and are therefore expected to run using more efficient
technology. The cost of restricting a non-compliant vehicle to drive outside of the LEZ
also increases running costs above their normal level as drivers may take indirect routes
to reach customers. This yields the following relationship:
AR
it > ANC
it > AC
it
Second, the purchase cost of a compliant vehicle is greater than the purchase cost of a
non-compliant vehicle. This assumption is justified on the grounds that non-compliant
vehicles are both older than compliant vehicles and violate LEZ regulations. Similarly,
the resale value of a compliant vehicle is greater than that of a non-compliant vehicle.
The resale value of a modified vehicle is greater than that of a non-compliant vehicle as
it has the advantage of LEZ compliance:
KC
i > KNC
i
14
15. SC
it > SM
it > SNC
it
Third, the resale price of each vehicle tends towards zero. This assumption captures the
fact that the resale value of a vehicle falls with its age whilst maintenance costs increase:
lim
t!1
Sit ! 0
Fourth, business owners that choose to avoid the LEZ entirely are faced with a lower
value of driving services, as they are forced to reject business inside London:
Vit > V R
it
The dynamics of this model can be illustrated best with some examples.
Scenario A: Pay the Charge v. Modify Vehicle
A business owner will prefer to pay the charge in any period in which the following
relationship holds:
SNC
it CiLit > SM
it Mi
That is, the resale value of the non-compliant vehicle minus the cost of paying the LEZ
charge is greater than the resale value of the modified vehicle minus the cost of modifi-
cation. For businesses that rarely drive inside the LEZ, Lit will be small. As such, one
would expect to observe drivers in this position paying the charge.
This relationship may change over time. Suppose that the resale value of a non-compliant
vehicle falls more quickly than the resale value of a modified vehicle. This is a realistic
assumption given that a non-compliant vehicle is subject to LEZ restrictions. At some
point, a driver who once chose to pay the charge may prefer to modify his vehicle.
Scenario B: Modify the Vehicle v. Purchase New Vehicle
If the difference between the running costs of a modified vehicle and a compliant vehicle
is smaller than the difference between value of a modified vehicle net of modification cost
and the value of a compliant vehicle net of purchase costs, the business owner will choose
to modify his vehicle:
(SM
it Mi) (SC
it KC
+ SNC
it ) >
1X
t=t0
ANC
it AC
it
15
16. Scenario C: Drive around the LEZ v. Pay the Charge
A vehicle owner may choose to avoid the LEZ completely if the net present value of
driving around the zone exceeds the net present value of accepting business within the
zone but having to pay the charge.
" 1X
t=t0
V R
it AR
it
#
>
" 1X
t=t0
Vit ANC
it
#
CiLit
This framework can be used as a tool to interpret the observed behavioural response
estimate in Section 6.
5 Benefits of the LEZ
The stated goal of the LEZ is to improve air quality in London through a reduction in
tailpipe emissions. The key benefits of enhanced air quality are improvements in human
health and a reduction in the mortality rate.
London has struggled to meet the national and European objectives of two pollutants in
particular: NO2 and PM10. Road transport is responsible for a significant proportion of
both pollutants. Each adversely affects human health by causing and exacerbating respi-
ratory and cardiovascular conditions. Therefore, assessment of the change in atmospheric
concentrations of PM10 and NO2 arising as a result of the LEZ is a crucial component of
the cost-benefit calculations.
This section provides information on the procedures used to estimate this change in air
quality and thus quantify the benefits of the LEZ
5.1 Data
The Environmental Research Group at KCL manage the LAQN. This comprises a network
of sites that operate to monitor air quality and meteorological conditions in and around
London. In addition to the LAQN, KCL also manage a number of more limited networks
located further outside London. All data collected by these networks is uploaded daily to
a central repository. This repository can be freely accessed through an R package, known
as the openair project, which has been written specifically to enable air quality analysis.
To facilitate assessment of the impact of the LEZ on air quality, the hourly mean value of
the two key pollutants (PM10 and NO2), alongside associated meteorological readings for
wind-speed, temperature and rainfall, were downloaded for each site for 2004-14. These
hourly readings were used to calculate the daily mean values of each variable.
Each monitoring site was then assigned to one of three categories according to its location:
16
17. • Inside the LEZ: Located within the LEZ
• Near to the LEZ: Located outside of the LEZ but within 50 miles of Central
London
• Far from the LEZ: Located outside of the LEZ and more than 50 miles from
Central London
The distribution of monitoring sites across the three location categories is shown in Table
2. Notably, the number of monitoring sites located inside the scheme’s boundaries is
larger than the number near to or far from the LEZ. This is in spite of the fact that the
geographical area covered by the LEZ is significantly smaller than the area outside of the
LEZ. This unbalanced sample, perhaps a consequence of London-centric investment in air
quality monitoring, is a limitation of this study. A larger sample of monitoring stations
outside of the LEZ would provide a clearer picture of overall air quality trends in the UK.
Year
Location Category 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Far from LEZ 50 50 47 47 65 74 59 56 50 41 36
In LEZ 119 123 128 127 135 135 132 125 111 95 91
Near to LEZ 49 52 55 59 60 62 49 43 27 31 19
Total 218 225 230 233 260 271 240 224 188 167 146
Table 2: Number of Monitoring Sites by Location Category
Annual mean daily values for each pollutant and meteorological parameter by location
category are provided in Table 3. Meteorological statistics are similar across location
categories.
As would be expected, the mean value of both pollutants is highest inside the LEZ. The
mean value of NO2 increases with time inside the LEZ whilst there is a slight decline in
areas outside of the LEZ boundary. Conversely, the mean concentration of PM10 has,
overall, fallen in each location category. This highlights the importance of viewing air
quality changes within London in the context of national trends. Viewing trends inside
the LEZ in isolation, one might draw the conclusion that the policy has been successful
in cutting PM10. However, if areas outside of London are experiencing a similar decline,
the LEZ is less likely to be a significant causal factor.
5.2 Econometric Strategy
To estimate the impact of the LEZ on air quality, a difference-in-differences approach was
used. This methodology is similar to that employed by Wolff (2013) in his study on the
effects of the German LEZs on air quality.
17
19. Those stations located far from the LEZ were assigned to a control group. This is based
on the assumption that spillover effects from the LEZ decline with distance. Therefore,
the policy impact should be negligible on these distant stations. Stations located inside
or near the LEZ were assigned a separate treatment status. This distinction was made
in order to identify the effects of the LEZ on air quality in neighbouring districts, as well
as those located inside the scheme’s borders.
The difference-in-diffences technique compares air quality change inside (or near the LEZ)
to the change in the control group over the same time period. This econometric approach
relies on the assumption of common trends; in the absence of the treatment (i.e. the LEZ),
the outcome in the treatment and control groups would follow the same time trend.
To assess the validity of this assumption, the logarithmic time trend for air quality by
location category was plotted (see Figures 2 and 3). For NO2, the common trends assump-
tion seems reasonable. Until treatment is applied, in 2008, the time trend of NO2 appears
to be approximately similar across location categories. After 2008 the NO2 time trends
diverge; there is a slight increase in NO2 concentrations within the LEZ accompanied by
a slight decrease outside of the LEZ.
For PM10, given greater volatility, it is more difficult to validate the common trends
assumption. However, across all location categories, there is a downward trend in PM10
concentrations until 2010. Thereafter, there is an upward spike in the pollutant followed
by further reductions. Visual inspection of this data gives little indication of any LEZ
impact.
To investigate further, the following difference-in-differences econometric specification,
given by Equation 1, is used. ln pi,t refers to the natural logarithm of the mean pollutant
concentration (NO2 and PM10) at monitoring site i on day t.
ln pi,t = + TimeDummiest + ⇧interactionInsideLEZ(2008 14)it +
⇤interactionNearLEZ(2008 14)it + Xi,t + ui,t
(1)
The variables interactionInsideLEZ(2008 14)it = InsideLEZi⇤PostLEZt⇤Y earDummyt
and interactionNearLEZ(2008 14)it = NearLEZi⇤PostLEZt⇤Y earDummyt are each
a sequence of 7 interaction variables for the years 2008-14. These assume a value of one if
an air quality observation is taken from inside/near the LEZ, post-LEZ implementation
during the named year. The set of 14 coefficients relating to these two variables, ⇧ and
⇤, are of most interest. Since the natural logarithm of NO2 and PM10 is used as the de-
pendent variable, ⇧ and ⇤ can be interpreted as the very approximate percentage change
in pollutant concentration attributable to the LEZ in or near the zone, cumulatively, by
the specified year.
19
22. TimeDummiest are a set of dummy variables indicating day, month and year. Xi,t com-
prise a set of station, location and time-specific control variables including meteorological
parameters (wind speed, temperature and rain), road traffic and indicators for day of
week. Meteorological conditions are a particularly important determinant of pollutant
concentrations. Higher wind speeds and increased rainfall reduce the ambient pollutant
concentrations.
To control for unobserved heterogeneity across sites, and to avoid the issue of omitted
variable bias, the regression was run under the assumption of Fixed Effects (FE). By
demeaning each variable, this method applies a within transformation to remove time-
invariant heterogeneity (e.g. Xit
¯Xi where ¯Xi =
PT
t=1 Xi,t). Whilst being less efficient
than estimation under the assumption of Random Effects (RE), this method yields consis-
tent estimates without placing assumptions upon the relationship between the unobserved
heterogeneity and included regressors.
5.3 Results
Coefficient estimates for ⇧ and ⇤ are given in Table 4. Complete regression results
are provided in Appendix B. Heteroscedasticity-robust standard errors were calculated,
clustered by monitoring site to account for correlation within each group of observations.
In line with econometric convention, only results significant at the 5% confidence level
will be regarded as a measurable impact of the LEZ.
Considering regression (1), whilst the negative sign on each coefficient is in line with
expectations, it is notable that the scheme appears to have had no significant impact on
PM10 concentrations inside the LEZ during any year. Given that reduction in atmospheric
concentrations of PM10 was a key aim of the LEZ, these results are disappointing.
Results for NO2, given by regression (2), are more encouraging. In 2008 NO2 concentra-
tions fell by approximately 6% inside the LEZ as a result of the scheme. Given that 2008
was a key LEZ implementation date, and air quality is expected to respond quickly to
changes in the environment, these results are consistent with expectations.
In areas near the LEZ there were also statistically significant reductions in NO2 during
2012. However, in the same year there was a statistically insignificant increase in PM10
near the LEZ. Given that a reduction in NO2 arising as a result of the LEZ implies a
reduction in the number of non-compliant vehicles driving near the LEZ, it is difficult to
explain why there was not a corresponding fall in PM10. Returning to consider Table 2,
which shows the distribution of monitoring sites by location category, it is notable that
there is particularly small number of monitoring stations situated near to the LEZ in 2012.
It is possible that the unbalanced nature of the sample used has affected these results.
As a consequence, this result, showing a reduction in NO2 near the LEZ, is treated with
caution.
22
23. The signs on the coefficient estimates for control variables (see Appendix B) are consistent
with expectations. Increased wind speed and rainfall reduces PM10 and NO2 concentra-
tions. The day of week dummy variables provide the impact on concentration levels
relative to Sunday. The sign on each of these dummy variables is positive. This is in line
with expectations given that traffic volumes, and therefore pollutant concentrations, are
generally lower on a Sunday.
23
25. 5.4 Quantifying the Benefits
Results significant at the 5% level will be included in calculations to quantify the benefits
of the LEZ. Therefore, reductions in NO2 in 2008 inside the LEZ and 2012 near the LEZ
only will be included in benefit calculations.
Since the dependent variable is ln NO2 , whilst estimates of ⇤ and ⇧ relate to a dummy
variable, the associated coefficient can only roughly be interpreted as the percentage
change in NO2. This is because the usual percentage approximation, relating logged de-
pendent variables to changes in regressors, is accurate only for small changes in continuous
variables. The independent variables under consideration here are discrete. To calculate
more precisely the percentage impact on NO2 concentrations the following transforma-
tion should be applied to the coefficient estimates for interactionInsideLEZ2008 and
interactionNearLEZ2012:
% NO2Concentrations = 100 ⇤ (e⇤
1) (2)
This yields results that show that during 2008 there was a reduction of 5.9% in NO2
concentrations inside the LEZ as a result of the scheme. Near the LEZ, there was a
cumulative drop of 22.2% as a result of the scheme by 2012.
To map this change in NO2 concentrations into monetised health benefits, methodology
set out by the Department for Environment, Food & Rural Affairs (DEFRA) in their
publication An Economic Analysis to inform the Air Quality Strategy was employed.
Based on the outcome of a range of epidemiological studies DEFRA provide a number
of estimated Concentration Response Coefficients (CRC) by pollutant and health impact
(loss of life expectancy, mortality, respiratory and cardiovascular hospital admissions).
This coefficient can be used, alongside the absolute change in pollutant concentration
and affected population size, to calculate the associated health impacts.
Whilst the evidence quantifying the relationship between PM10 and related health im-
pacts is strong, DEFRA do not currently consider the evidence used to calculate the CRC
for NO2 robust. Therefore DEFRA provide a CRC of 0.5% for respiratory hospital ad-
missions, for use in sensitivity analysis only. To reflect the uncertain relationship between
NO2 and health outcomes, the impact estimates given below use a lower bound CRC of
0.0% and an upper bound of 0.5%. No CRC for the impact of changes in NO2 concen-
trations on life expectancy, mortality or cardiovascular hospital admissions is provided
by DEFRA. It is likely that NO2 concentrations do affect each of these health outcomes
and therefore monetary results presented may underestimate the true value air quality
improvements. Epidemiological research into this area is ongoing. In the near future it is
hoped that it will be possible to revise these estimates based on updated CRCs.
Table 5 provides the inputs to the calculation to derive total benefits. Population sizes for
inside and near the LEZ are taken from the 2011 Census statistics which are published by
25
26. the Office of National Statistics (ONS). A breakdown by postcode is given in Appendix
C. NO2 concentrations in 2007 were selected as the baseline level since this was the
year directly preceding the introduction of the LEZ. Applying upper and lower bound
estimates of the CRC, an assessment of the percentage change in hospital admissions
was derived. Applying this percentage impact to the respective population sizes gave an
estimated reduction in hospital admissions inside the LEZ of 14,127 in 2008 and 35,051
near the LEZ in 2012. DEFRA publish a recommended health value of £1,900-£9,600 (in
2004 prices) per hospital admission for respiratory problems. Using rates published by
the Bank of England, these values were adjusted to reflect inflation and are given below
in 2014 prices.
Table 5: Monetised Benefits of LEZ
Inside LEZ
2008
Near LEZ
2012
Population 9,236,935 10,499,151
Impact of LEZ on NO2
Baseline NO2 51.845 34.186
% Change in NO2 -5.90% -22.20%
Change in NO2 -3.1 -7.6
Concentration Response
Coefficient (per 10g/m3)
LB 0.00% 0.00%
UB 0.50% 0.50%
% Change in Respiratory
Admissions in Population
LB 0.00% 0.00%
UB -0.15% -0.38%
Absolute Change in Respiratory
Admissions in Population
LB 0 0
UB 14,127 35,051
Cost per Respiratory Hospital
Admission
LB £2,606 £2,606
UB £13,165 £13,165
Total Benefits of LEZ
LB £- £-
UB £185,984,883 £461,445,078
Notes: LB - Lower Bound, UB - Upper Bound, CRC - Concentration Response Coefficient
Overall, the estimated benefits of air quality improvements are estimated to be £0-186
million inside the LEZ during 2008, and £0-461 million near the LEZ during 2012. The
wide range stated reflects the uncertainty surrounding (a) the relationship between NO2
and health outcomes3
, and (b) the cost of respiratory hospital admissions.
3The link between NO2 and associated health impacts is a subject of current research. The
government-appointed Committee on the Medical Effects of Air Pollutants (COMEAP) is expected to
report on this during 2015. This may allow application of the updated epidemiological estimates on the
effects of NO2to refine the estimated health benefits.
26
27. 6 Costs of the LEZ
To estimate the costs of the LEZ implementation, it was first necessary to estimate the
magnitude of each of the four key behavioural responses: vehicle replacement, vehicle
modification, payment of the charge or drive around the LEZ. This information was then
used to quantify the costs arising as a result of the LEZ.
6.1 Cost of Vehicle Replacement
6.1.1 Data
To estimate the cost of the vehicle replacement response, data on all vehicle registrations
from 2004-14 was provided by the DVLA. This data was broken down into the number of
vehicles registered each year by postcode area, body-type (HGV, LGV, Cars, Motorcycles,
Buses & Coaches), gross weight and year of first registration.
In each case, the data was categorised according to the following criteria:
• Location: Whether located inside, near to or far from the boundaries of the LEZ.
The following rules were applied to develop this classification:
– All postcode areas located fully or partially within the boundaries of the LEZ
were categorised as being inside the LEZ
– All postcode areas near to the LEZ boundaries were categorised as being near
the LEZ
– All remaining postcode areas were placed in the group of observations far from
the LEZ
A list of postcodes classified as in or near to the LEZ can be found in Appendix C.
• Compliance Status: Whether a vehicle met the standards specified by each phase
of the LEZ. This was determined according to the TfL guidelines given in Table 1
by body-type, year of registration and GVW.
This classification facilitated calculation of the total number of non-compliant vehicles for
each LEZ Phase and area by postcode and year. Thus, a panel data set was created with
which to identify the impact of each LEZ phase on vehicle replacements. A summary
of this data set is provided in Table 6. It is notable that, across the period 2004-14,
there was a large reduction in the number of non-compliant vehicles across all location
categories. This observation serves to highlight that the LEZ’s impact is naturally time-
limited. The policy may accelerate the adoption of green vehicles within the LEZ but,
given a natural vehicle replacement rate, areas outside of the LEZ will eventually also
adopt green technology and therefore similar outcomes will be achieved.
27
29. 6.1.2 Econometric Strategy
As with air quality, a similar difference-in-differences econometric approach was employed
to identify the vehicle replacement response. Vehicles registered far from the LEZ were
used as a control group whilst vehicles registered inside and near the LEZ made up two
treatment groups.
To validate the common trends assumption, the logarithmic number of non-compliant
vehicle in each of the treatment and control groups was analysed (see Figure 4, 5 & 6).
Annual changes in the logarithmic variable are approximately equivalent to the percentage
change in the number of non-compliant vehicles. This percentage change is therefore
indicated by the slope of the line. As each chart shows, before the introduction of the
LEZ, the treatment and control groups follow similar trends. This provides assurance
that the control group provides a reasonable benchmark of the anticipated time trend in
the absence of a policy intervention.
In the years directly preceding the introduction of the LEZ, the number of vehicles affected
by Phase 1 shows a slightly accelerated decline inside the LEZ compared to areas outside
the LEZ. However, the vehicle replacement response to Phase 2 and 3 appears more
marked. This response starts in 2007 for Phase 2 vehicles and 2011 for Phase 3 vehicles.
With these observations in mind, one would expect the econometric results to show a
more marked vehicle replacement response for Phase 2 and 3 than Phase 1.
The econometric model used to assess impact of each phase of the LEZ on vehicle replace-
ment both in and near the LEZ is given below by equation 3, where lnNCLEZPhasei,t
denotes the log of the total number of non-compliant vehicles (by LEZ phase) located in
a given postcode i at time t.
ln NCLEZPhasei,t = + TimeDummiest + ⇧interactionInsideLEZ(2008 14)i,t
(3)
+ ⇤interactionNearLEZ(2008 14)i,t + ui,t
As before, this regression was estimated under the assumption of FE. This controlled
for unobserved heterogeneity across postcode area. Heteroscedasticity-robust clustered
standard errors are calculated to account for correlation across observations from the
same postcode.
6.1.3 Results
The coefficient estimates for ⇧ and ⇤ are reported in Table 7. Each of the coefficient
estimates can be interpreted as a rough approximation to the percentage change in non-
29
33. compliant vehicles registered inside or near the LEZ as a result of the LEZ by the stated
year.
The results show that the impact on the registration of vehicles that are not compliant
with Phase 1 standards is negative and significant at the 1% level inside the LEZ (with
the exception of 2010, which are significant at the 5% level). A similar result is shown for
Phase 2. The effect of the LEZ on vehicles registered inside the LEZ affected by Phase
3 is not significant at the 5% level until 2011. This is consistent with expectations given
that the third phase was not implemented until 2012.
Considering the coefficient estimates relating to vehicle registrations near the LEZ, one
can see that the impact of both Phase 2 and 3 on vehicle registrations is negligible. This
suggests that it is likely vehicle owners located close to the LEZ boundary do not drive
inside the zone often enough to warrant replacing their vehicle. This explanation is also
consistent with the decision-making model presented in Section 4, which demonstrated
that vehicle replacement is a rational response only when the LEZ is entered frequently.
Conversely, Phase 1 has reduced the number of non-compliant vehicles registered near to
the scheme’s boundaries. Phase 1 affected large HGVs only. These vehicles are frequently
used for long distance distribution. They are likely to travel further from their registered
address than lighter vehicles, and are therefore likely to enter the zone. This could explain
why vehicles located outside of the zone were affected by Phase 1 only.
33
35. 6.1.4 Quantifying the Cost of Vehicle Replacement
As with air quality, these coefficient estimates were used to derive, more precisely, the
annual impact of each LEZ phase on vehicle owners by applying the transformation given
by equation 2. This yields the cumulative response inside the LEZ (given in Table 8)
and near the LEZ (given in Table 9). The cumulative response was used to calculate the
impact by year.
Table 8: Impact of LEZ on Non-Compliant Vehicles registered Inside the LEZ
Phase 1 Phase 2 Phase 3
Year Cumulative Annual Cumulative Annual Cumulative Annual
2008 -15% -15% -36% -36% 0% 0%
2009 -19% -5% -40% -4% -4% -4%
2010 -12% 7% -44% -3% -5% -1%
2011 -22% -10% -49% -5% -34% -28%
2012 -26% -4% -56% -7% -45% -12%
2013 -26% 0% -56% 0% -45% 0%
2014 -25% 1% -57% -2% -45% 0%
Notes: The “Annual” results given for 2008 should be interpreted as the impact of the LEZ up
to and including 2008. Thereafter, annual results refer to change as a result of the scheme in
the given year only.
Table 9: Impact of LEZ on Non-Compliant Vehicles Registered Near the LEZ
Phase 1
Year Cumulative Annual
2008 -12% -12%
2009 -12% 0%
2010 N/A 0%
2011 -11% 1%
2012 -13% -2%
2013 N/A 0%
2014 N/A 0%
Notes: The “Annual” results given for 2008 should be interpreted as the impact of the LEZ up
to and including 2008. Thereafter, annual results refer to change as a result of the scheme in
the given year only.
To quantify the vehicle replacement response, the approximate cost of replacing an af-
fected vehicle was required. Data for this purpose was gathered from www.autotrader.co.uk,
an online platform through which vehicles are traded. This information, provided in Ap-
pendix D, was used to derive a lower and upper bound replacement cost by LEZ phase.
Given the heterogeneity of vehicle characteristics and prices, it was impossible to assign
35
36. a narrow range of values. Therefore, as the information given in Table 10 shows, the es-
timated range of vehicle costs is large. Future investigations into this area could work to
narrow this range by estimating the replacement response by vehicle type and conducting
a more detailed survey of vehicle costs. This additional investigation could also include a
price adjustment to account for income derived from the resale of non-compliant vehicles,
as this is not taken into account below.
Table 10: Approximate Cost of Non-Compliant Vehicles by Phase
Baseline No. of
Non-Compliant
Vehicles Inside LEZ
Baseline No. of
Non-Compliant
Vehicles Near LEZ
Approximate Cost of Vehicle
Lower Bound Upper Bound
Phase 1 7,259 15,508 £15,000.00 £105,000.00
Phase 2 9,381 22,290 £10,000.00 £30,000.00
Phase 3 49,735 96,300 £5,000.00 £30,000.00
The information in Table 10 was applied to the estimated behavioural response to derive
a cost for vehicle replacement arising as a result of the LEZ. The results are shown in
Table 11.
A summary of vehicle replacement costs across all three phases is given in Table 12. As
would be expected, the cost of vehicle replacement is greatest in both 2008, the time in
which Phase 1 and 2 were implemented, and 2011, which just preceded the January 2012
implementation of Phase 3.
Table 12: Summary of Vehicle Replacement Costs
Total Cost of Vehicle Replacement
LB UB
2008 £78,869,908 £417,002,954
2009 £19,143,650 £109,048,950
2010 £5,301,050 £23,363,400
2011 £77,586,050 £454,711,350
2012 £44,852,507 £257,859,746
2013 £0 £0
2014 £1,876,200 £5,628,600
36
38. 6.2 Cost of Vehicle Modification
6.2.1 Data & Estimation
Once a vehicle has been modified, it must undergo annual testing with the DVSA to
demonstrate compliance. If the test is passed, the vehicle is issued with a Reduced Pollu-
tion Certificate (RPC) or a Low Emissions Certificate (LEC). Possession of a certificate
enables the vehicle to drive inside the LEZ without charge
Following a Freedom of Information request, TfL supplied monthly data on the number
of RPCs and LECs registered during 2008-2014, broken down by type of modification.
As Figure 7 below illustrates, the total number of modifications peaks in January 2012.
This coincides with the introduction of the third and largest phase of the LEZ. Smaller
peaks coincide with the implementation dates of the first and second phases of the LEZ.
Initially engine replacement appeared to be the most common form of modification. How-
ever, around the time of the introduction of LEZ Phase 3, the installation of abatement
equipment appears more popular. Very few vehicles chose to undergo a fuel conversion
in order to run on gas.
Whilst a modification will only take place once during the lifetime of each vehicle, each
certificate must be renewed annually. Unfortunately, the data provided by TfL does not
separate certificate renewals from new modifications. This prevents perfect identification
of the number of modifications taking place and therefore hinders accurate estimation of
the costs.
To handle this issue, it is necessary to make an assumption about the pattern of new
modifications versus renewals: If a vehicle owner is to respond to the LEZ by modifying
their vehicle, they can be expected to carry out this modification soon after the imple-
mentation date. This will maximise the benefit to the vehicle owner since there is little
point in paying the LEZ charge and then paying for a modification.
This assumption gives rise to the following rule:
• All certificates registered in the 12 months following the LEZ Phase 1 start date
relate to new modifications (February 2008 – January 2009)
• Thereafter, it is assumed that each certificate is renewed after 12 months. Therefore:
– If the number of certificates registered in a particular month is greater than the
number of certificates registered in that month 12-months previously, the dif-
ference between the two are assumed to be new modifications. The remainder
are considered to be renewals
– If the number of certificates registered in a particular month is less than the
number of certificates registered in that month one year previously, all certifi-
cate registrations are assumed to be renewals.
38
40. This rule is applied to the data to provide an estimated breakdown of certificate registra-
tions into renewals and new modifications. The estimated breakdown into modifications
and renewals is shown below in Figure 8.
Visual inspection of the estimated split provides assurance that the assumptions made
are reasonable. The number of engine upgrades peaks with the introduction of the LEZ
in February 2008 and then drops sharply. This is consistent with the suggestion that
owners are most likely to modify their vehicles soon after the date on which they become
affected. Engine upgrades then resurge during 2009/10 before dropping towards zero.
The data suggests that replacing an engine was the most popular response to the first
two phases of the LEZ. Conversely, the installation of abatement equipment was the most
popular response to the third phase of the LEZ, which affected mainly lighter vehicles.
Very few vehicles undergo fuel conversion across the period. This is likely due to the
costly nature of modification, which can be in excess of £20,000.
Renewals increase with the number of modifications until late 2011. After the introduction
of the final phase of the LEZ, renewals start to fall, tracing a 12-month cyclical pattern.
This cyclical pattern is consistent with the assumption that certificates are renewed during
the same month each year. The decline can be attributed to the retirement of non-
compliant vehicles that reach the end of their useful life.
Once broken down, the RPC and LEC data is combined with upper and lower bound
estimates of the cost of each modification (see Table 13 for the source of this cost infor-
mation). This is used to provide an overall estimate of modification costs. Results are
given in 14.
Table 13: Cost of Vehicle Modification
Modification Source LB UB
Abatement Equipment https://tfl.gov.uk/modes/driv-
ing/low-emission-zone/ways-to-
meet-the-standards/fit-a-filter
(Last Accessed 26th August 2015)
£1,800 £7,000
Fuel Conversion Transport Engineer Magazine-
July 2010, p10-13
£10,000 £25,000
Engine Upgrade Range of quotations from:
http://www.euroasiatrucks.com/
(Last Accessed 26th August 2015)
£3,000 £11,000
Certificate Renewal https://www.gov.uk/specialist-
tests-for-coaches-and-
buses/booking-and-fees-for-rpc-
and-lec-tests (Last Accessed 26th
August 2015)
£32 £32
Notes: LB - Lower Bound, UB - Upper Bound
40
43. 6.3 Cost of Paying the Charge & Running Costs
As shown by the conceptual framework presented in Section 4, those driving inside the
LEZ infrequently may find it optimal to pay the charge. Given that this charge is collected
by TfL, therefore adding to funds available for other public projects, it should not be
considered purely as a cost to vehicle-owners. Instead, running/implementation costs
relating to the scheme should be subtracted from charge payments to derive net income.
This net income represents a transfer of resources from vehicle-owners to TfL. However,
there are distortionary costs incurred as a result of this transfer. Estimates of these
distortionary costs vary significantly. A reasonable approximation is considered to be
£0.30 for each £1 of public funds raised.4
As a result, the social benefit (or cost) of this
net income should be valued at 30% of its monetary value. Applying a factor of 0.3 to net
income to financial data provided by TfL generates net benefits/costs given in the final
row of Table 15. Note that negative numbers constitute a cost and positive numbers are
a benefit.5
6.4 Cost of Driving Around the LEZ
To avoid the issue of LEZ compliance, some vehicle-owners may choose to avoid the LEZ
entirely. This may be achieved by turning down business within the zone and/or selecting
alternative driving routes to avoid entry. In order to understand whether this comprised
an important behavioural response to the scheme, trends in traffic volumes in, near and
far from the LEZ were scrutinised.
The DfT conducts around 8,000 manual traffic counts around the UK each year. Data
collected during these exercises are used to determine annual traffic volume. This is
calculated by multiplying the annual average daily flow by the length of the road and
the number of days in the year. The DfT publishes this information by local authority.
An important limitation of this data is that traffic volumes do not differentiate between
LEZ compliant and non-compliant vehicles. Consequently, it is likely that adjustments
in driving behaviour made by affected drivers will be masked by trends in overall traffic
volumes for each vehicle type. For this reason, the analysis provided below is not used
in the overall cost-benefit calculations given in Section 7. Instead, it aims to provide
groundwork for further research into this complex behavioural adjustment.
To facilitate analysis, each local authority was categorised according to its location. An
index was created to show changes in the annual traffic volume for HGVs and LGVs
4This is approximation of the marginal excess burden is taken from p51 of Taxation: A Very Short
Introduction by Stephen Smith (2015) published by Oxford University Press.
5TfL have provided financial information split by their financial year ending 30th March. Since
the other costs/benefits presented in this study are presented by calendar year (i.e. year ending 31st
December), it has been necessary to present costs/income relating to the TfL financial year to the calendar
year in which the majority of the financial year fell. For example, 2005/6 is presented as 2005. Since the
magnitude of TfL operating costs/income is small relative to the other costs and benefits presented here,
this is not expected to distort conclusions in any significant way.
43
45. individually. These vehicle types were selected because, unlike other motor-vehicles such
as cars, they are affected by the LEZ. HGVs were affected from the first phase of the
LEZ, whilst LGVs were affected from the third phase implemented in 2012. Plotted in
Figures 9 to 10 is the annual traffic volume index for HGVs and LGVs.
Figure 9 clearly shows a decline in HGV traffic volumes both near to and far from the
LEZ. In contrast, HGV traffic volumes have remained relatively constant inside the LEZ.
At first sight, this may suggest that few of those HGVs affected by the scheme responded
by avoiding the LEZ. However, it may also be the case that HGV traffic volumes would
have increased without the tempering influence of the LEZ. In this sense, the scheme
could have been effective.
Figure 10 provides an insight into the situation for LGVs. In contrast to HGVs, there
appears to be a similar increase in LGV traffic volumes in areas near to and far from the
LEZ. Meanwhile, from 2008 until 2010 LGV traffic volumes inside the LEZ fell. Between
2010-12, LGV traffic volumes remained fairly constant before beginning to rise again in
2013.
To further investigate the impact of the LEZ on traffic, the fixed effect regression shown
by equation 4 was run for both HGVs and LGVs. As well as annual time dummies, this
regression included a number of additional control variables: (a) lnAllMotorV ehiclesi,t
to control for general traffic trends, (b) The log of Gross Value Added (lnGV Ak,t), a
measure of output, to account for changes in traffic arising from different trends in regional
economic activity (economic recovery in London relative to the rest of the UK may be an
important reason for HGV trends) , (c) lnOtherV ehicleTypei,t, where OtherV ehicleType
refers to the number of LGVs in the HGV regression and the number of HGVs in the
LGV regression, to control for substitution between vehicle types. Since LGVs were not
affected by the scheme until 2012, only the policy interaction variable for 2012 onwards
were included in these regressions.
lnV ehicleType = + TimeDummiest + ⇧interactionInsideLEZ(2008 14)i,t
+⇤interactionNearLEZ(2008 14)i,t + lnAllMotorV ehiclesi,t(4)
lnOtherV ehicleTypei,t + lnGV Ak,t + ui,t
Results are given in Table 16. Analysis of the econometric results show that there is
no statistically significant effect of the LEZ on HGV traffic volumes until 2012. This
suggests that HGV owners did not respond to Phase 1 and 2 of the LEZ by avoiding the
area altogether. However, by 2012 the LEZ appears to have had a statistically significant
effect on HGV and LGV traffic volumes both inside and near the LEZ. In line with
expectations, LGV traffic inside the zone fell during 2012 whilst increasing in surrounding
areas. This is consistent with a behavioural response in which drivers choose to avoid
45
48. the LEZ completely, driving around the outside where possible. In contrast, HGV traffic
from 2012 increases inside the LEZ but falls near the LEZ.
A possible explanation for these results may be found by considering the magnitude of
the LEZ charge relative to the benefits enjoyed by a vehicle-owner entering the zone. Due
to their size, HGVs have greater earning potential than smaller vehicles. Consequently,
the costs of entering the LEZ are likely to make up a smaller proportion of costs for HGV
owners than LGV owners. This may be why the first two phases of the LEZ have not
had a significant impact on HGV traffic volumes whilst the third phase has led to a fall
in LGV traffic volumes inside the city. Further, it can also be suggested that this change
in relative HGV/LGV costs inside the LEZ has led to a substitution towards the use of
HGVs inside the city and a substitution away from the use of HGVs in surrounding areas.
Further investigation would be required to confirm or refute this assertion.
On the other hand, the explanatory power of model (1), the variation in the dependent
variable across time explained by the model (indicated by R2
), is low in comparison to
the explanatory power of model (2). It may also be that the results given by regression
(1) are driven by a time variant omitted variable whilst LGV traffic volumes are well
explained in the context of the LEZ.
48
49. Table 16: Impact of LEZ on Traffic
(1) (2)
lnHGV lnLGV
interactionInsideLEZ2008
-0.011
(0.02)
interactionInsideLEZ2009
0.014
(0.02)
interactionInsideLEZ2010
0.001
(0.03)
interactionInsideLEZ2011
0.023
(0.03)
interactionInsideLEZ2012
0.115*** -0.037***
(0.03) (0.01)
interactionInsideLEZ2013
0.105*** -0.014
(0.03) (0.01)
interactionNearLEZ2008
-0.017
(0.01)
interactionNearLEZ2009
0.004
(0.01)
interactionNearLEZ2010
0.007
(0.02)
interactionNearLEZ2011
-0.022
(0.02)
interactionNearLEZ2012
-0.048** 0.021**
(0.02) (0.01)
interactionNearLEZ2013
-0.038** 0.022*
(0.02) (0.01)
lnAMV
1.088*** 1.063***
(0.10) (0.06)
lnLGV
-0.215***
(0.06)
lnHGV
-0.105***
(0.03)
lnGV A
0.704*** -0.267***
(0.14) (0.08)
R2
0.419 0.842
N 2673 2673
Notes: Heteroscedasticity-Robust standard errors clustered by monitoring station are in
parenthesis, significance levels denoted by *p<0.1, **p<0.05, ***p<0.01
49
50. 7 Cost Benefit Analysis
A summary of the results from the Cost-Benefit Analysis (CBA) is given in Table 17.
This table brings together the monetary estimates of the costs and benefits assessed in
Sections 5 and 6.6
Given that costs and benefits occur in different time periods, it is necessary to use an
appropriate discount rate. This allows comparison of net value across time. In line with
UK government recommendations, an annual discount rate of 3.5% has been chosen.
7
The year in which the LEZ was implemented, 2008, was selected as the base year.
To apply the discount rate the annual compound discount factor was calculated using
equation 5, where t is the year under consideration. .
DFt = 1/(1 + 0.035)t 2008
(5)
This relevant compound discount factor was then applied to the annual net value of
the scheme to compute the discounted net value8
. Notably, the scheme leads to a net
discounted loss in every year, except 2012, where the upper bound estimates suggest net
benefits of £346 million.
Adding the discounted net value of the scheme across 2008-14 yields a Net Present Value
(NPV) of the LEZ between -£2.021 billion and £151 million (see Table 18). The wide
spread of these estimates reflects the uncertain epidemiological estimates of the impact of
NO2 concentrations on health and wide ranging of cost estimates for vehicle modifications
and replacement. However, given that the NPV range falls almost entirely in the negative
domain, it is considered very likely that the net value of the LEZ is negative.
6For the reasons outlined in Section 6.4, the costs of driving around the LEZ is not included in this
CBA.
7See http://data.gov.uk/sib_knowledge_box/discount-rates-and-net-present-value for full details of
the UK government’s discounting recommendations.
8Net financial costs relating to the LEZ implementation 2005-7 are given cumulatively as £12.2 million
in 2008 Net Costs of LEZ. These costs have been discounted appropriately and details can be found in
Appendix E.
50
52. Table 18: London LEZ - Net Present Value
NPV (£’millions)
LB UB
2008 -£802.7 -£4.0
2009 -£190.5 -£40.7
2010 -£186.9 -£49.6
2011 -£491.1 -£91.2
2012 -£299.5 £346.1
2013 -£25.9 -£4.1
2014 -£25.2 -£4.7
Total -£2,021.9 £151.7
Notes: LB - Lower Bound Estimate, UB - Upper Bound Estimate
8 Discussion
If the scheme’s performance is measured in terms of Net Present Value (NPV), the LEZ
has failed to deliver. Across the period 2008-14, it is likely that the scheme generated net
discounted loss. This loss is largely a consequence of the high cost to affected vehicle own-
ers of complying with the policy through vehicle modification/replacement accompanied
by minimal improvements in air quality.
The data on vehicle replacement may provide some indication as to why it has not been
possible to identify a significant LEZ impact on London’s air quality: the number of ve-
hicles in violation of LEZ standards is declining across the country. This is a consequence
of a natural replacement life-cycle in which owners upgrade their vehicles after a certain
time period, regardless of policy initiatives. The LEZ may have temporarily accelerated
the adoption of green vehicles/technology, but the end-result has been the same and the
rate of vehicle replacement appears to have returned to trend.
This observation highlights that, in its current form, the LEZ is a policy tool with time-
limited effects. Within a relatively short period, most vehicles will comply with standards
anyway. To improve the effectiveness of the LEZ, and ensure enduring impacts, TfL
could introduce incremental tightening of the required vehicle standards. This could
work to permanently shorten the lifespan of a heavy vehicle in London, thus leading to
a lasting increase in the rate of adoption of green vehicles. However, apart from being
politically controversial, this would also lead to increased costs of compliance. A much
bigger improvement in air quality would be required to justify these costs. Given that
it has not been possible to demonstrate a large improvement in air quality following the
introduction of the LEZ, even in the short term, a more fundamental policy re-design
may be required.
52
53. Many of these issues are relevant to the proposed ULEZ, which is due to be introduced
in 2020. Although the ULEZ will cover a smaller geographical area and a larger number
of vehicle categories, this scheme will also require vehicle-owners in violation of specified
emissions standards to replace/modify their vehicle or face a daily charge. Without
further analysis it is not possible to infer how air quality will be affected, as this will
depend upon the response of drivers to this charge and the severity of the emission
standards imposed. However, given its suggested design any effects are also likely to be
time-limited. There may be an initially accelerated vehicle replacement response, but
this is likely to return to trend. At best, air quality improvements may be achieved a few
years earlier than would otherwise have been the case. It is likely the costs to drivers will
be large.
The investigation leading to these conclusions has been exploratory in nature. There
is much opportunity for further research to deepen understanding of the behavioural
response and narrow the range of monetary estimates of costs and benefits. In particular,
it is recommended that the following areas are considered for development to allow better
assessment of the LEZ and related policies:
• Investment in additional sensors outside of London would provide a clearer picture of
any ongoing spillover effects of the LEZ to nearby areas and a greater understanding
of wider air quality trends in the UK. This study was limited by the small number
of air quality monitoring stations located outside of London.
• Consideration of the distribution of air quality impacts across areas within Lon-
don could allow a more accurate quantification of the environmental effects of the
scheme. For example, given that densely populated inner London is considered to
have some of the worst air quality in the country, an improvement in this area may
generate greater health benefits than a similar improvement in the suburbs.
• Research into the vehicle replacement and modification response by vehicle type
(e.g. HGV by gross weight) would provide a more detailed picture of the behavioural
response across different categories of driver. This would also allow a narrower range
of cost estimates to be generated as the cost of vehicle replacement/modification
can be tailored to type.
9 Conclusion
This exploratory study sets out to evaluate the performance of the London LEZ. The
empirical evidence presented indicates that the scheme was largely unsuccessful. This
negative assessment of the scheme’s impact is a consequence of limited air quality im-
provements alongside high compliance costs. Given a natural rate of vehicle replacement,
the LEZ has served to accelerate the adoption of green technology only temporarily. It is
53
54. likely that any air quality improvements would still have been achieved in the absence of
the scheme, albeit a few years later.
The LEZ experience has demonstrated the importance of careful policy design. There is
now an opportunity for policymakers to apply these lessons to the design of the ULEZ
and similar schemes worldwide.
54
55. References
Alberini, A., Harrington, W. and McConnell, V. (1995) Determinants of participation in
accelerated vehicle-retirement programs, RAND Journal of Economics, 26, 93–112.
Angrist, J. D. and Pischke, J.-S. (2009) Mostly Hamless Econometrics, Chapter 5, Prince-
ton University Press.
AutoTrader (2015) www.autotrader.co.uk.
Carslaw, D. C. (2015) The openair manual — open-source tools for analysing air pollution
data. manual for version 1.1-4, King’s College London.
Carslaw, D. C. and Ropkins, K. (2012) openair — an r package for air quality data
analysis, Environmental Modelling and Software, 27-28, 52–61.
Davis, L. W. (2008) The effect of driving restrictions on air quality in mexico city, Journal
of Political Economy, 116, 38–81.
DEFRA (2007) The air quality strategy for england, scotland, wales and northern ireland,
Tech. rep.
DEFRA (2013) An Economic Analysis to inform the Air Quality Strategy, Updated Third
Report of the Interdepartmental Group on Costs and Benefits, vol. 3.
DFT (2015) http://www.dft.gov.uk/traffic-counts/.
Eillson, R. B., Greaves, S. P. and Hensher, D. A. (2013) Five years of london’s low emission
zone: Effects on vehicle fleet composition and air quality, Transportation Research Part
D, 23, 25–33.
Santos, G. and Fraser, G. (2006) Road pricing: Lessons from london, Economic Policy,
pp. 263–310.
Santos, G. and Shaffer, B. (2004) Preliminary results of the london congestion charging
scheme, Public Works Management and Policy, 9, 164–181.
Smith, S. (2015) Taxation: A Very Short Introduction, Oxford University Press.
TfL (2002) Cleaning london’s air: Mayor’s air quality strategy, Tech. rep.
Wolff, H. (2013) Keep you clunker in the suburb: Low emission zones and the adoption
of green vehicles, The Economic Journal, 124, F481–F512.
55
56. A List of Acronyms
Acronyms
CC Congestion Charge
DEFRA Department for Environment, Food and Rural Affairs
DFT Department for Transport
DVLA Driver and Vehicle Licensing Agency
DVSA Driver and Vehicle Standards Agency
FE Fixed Effects
HGV Heavy Goods Vehicle
KCL King’s College London
LAQN London Air Quality Network
LEC Low Emission Certificate
LEZ Low Emission Zone
LGV Light Goods Vehicle
NO2 Nitrogen Dioxide
ONS Office for National Statistics
PM10 Particulate Matter measuring less than 10m
RE Random Effects
RPC Reduced Pollution Certificate
TfL Transport for London
ULEZ Ultra Low Emission Zone
56
62. C Categorisation of Postcode Areas
C.1 Postcodes Inside the LEZ
Postcode Area Location Population
BR Bromley 299,293
CR Croydon 405,982
DA Dartford 430,560
E London, East 977,607
EC London, East Central 33,205
EN Enfield 344,434
HA Harrow 480,953
IG Ilford Chigwell 335,694
KT Kingston on Thames 531,664
N London, North 848,197
NW London, North West 551,407
RM Romford 516,824
SE London, South East 988,702
SM Sutton 217,048
SW London, South West 874,844
TW Twickenham 490,472
UB Uxbridge 371,969
W London, West 502,085
WC London, West Central 35,995
TOTAL 9,236,935
62
63. C.2 Postcodes Near the LEZ
Postcode Area Location Population
AL St. Albans 250,427
BN Brighton 802,831
CM Chelmsford 653,492
CT Canterbury 482,504
GU Guildford 725,368
HP Hemel Hempstead 488,351
LU Luton 335,950
ME Medway 607,143
MK Milton Keynes 507,978
OX Oxford 612,827
PO Portsmouth 822,331
RG Reading 778,677
RH Redhill 532,536
SG Stevenage 402,911
SL Slough 373,607
SO Southampton 665,193
SS Southend on Sea 518,677
TN Tonbridge 680,816
WD Watford 257,532
TOTAL 10,499,151
63
65. E Discounted Net Costs of LEZ 2005-7
The table below provides the net discounted costs of the scheme implementation 2005-7.
These are included in 2008 of the CBA in Section 7.
2005 2006 2007
£’million
Net Financial Costs adjusted for Distortionary Costs £1.4 £3.2 £7.0
Discount Factor(Discount Rate - 3.5%, Base Year - 2008) 1.11 1.07 1.04
Discounted Net Financial Costs £1.5 £3.4 £7.2
Cumulative Discounted Net Financial Costs 2005-7 for inclusion in CBA £12.2
65
