This chapter assesses five climate-relevant policies currently being implemented in Catalonia to understand their potential to transform the structure of the transport system and shift it towards a low-emissions model. The policies analysed include incentives for the uptake of electric private vehicles, low emission zones, investments in public transport, fare reductions on public transport and road space redistribution.
Transforming Catalonia’s Mobility System for Net Zero
Abstract
Catalonia has implemented several climate-relevant policies in the passenger transport sector. While information on which policies are being prioritised in the region is limited, analysis of plans and strategies (see Table 2.1 in Chapter 2) and the interviews conducted reveal that a subset of policies are discussed more frequently and granted more importance than others. These include:
incentives for the uptake of electric private vehicles
low-emission zones
investing in public transport
fare reductions on public transport
road space redistribution and street redesign.
For each of these policies, this chapter explores their transformative effect on the system structure described in Chapter 3. Transformative policies are defined as those able to modify the system structure, so that the design of the system can foster patterns of behaviour aligned with desired results. In systems jargon, transformative policies “push” on high leverage points, namely places in which a small intervention may lead to a system transformation capable of triggering large behavioural changes (Meadows, 2008[1]).
In the “understand” step of the OECD’s three-step process presented in Chapter 1, policies are classified according to their intent and transformative potential, given the local context and characteristics of the system (Figure 4.1). A detailed explanation of the methodology to identify policy intent and potential is available in Annex E.
Source: Authors.
The intent of a policy refers to the objective that the policy was designed to achieve. Policies are categorised based on whether they react to a situation (reactive intent), anticipate the impact of a pattern expected to take place (anticipatory intent), or aim at transforming the system structure and/or engrained mental models that lock in the existing system (transformative intent). Policies categorised as reactive and anticipatory tend to aim to reduce the harm of the results or patterns of behaviours the system produces.
A policy’s transformative potential is linked to the actual impact the policy has on the system’s structure and is characterised as low, medium or high. The policy’s transformative potential is assessed in terms of its effect on: (1) the system’s dynamics (see Section 3.3); (2) the system’s physical stocks (infrastructure and space allocated per mode); and (3) the mindsets affecting policy decision making and public acceptability. The sub-sections below analyse the transformative potential of the five selected policies in turn.
Incentives for the uptake of electric private vehicles in Catalonia include price subsidies for purchasing electric and hybrid vehicles,1 with a price ceiling of EUR 45 000, as well as subsidies for installing private or public electric vehicle (EV) charging infrastructure (Generalitat de Catalunya, 2021[2]). Subsidies are channelled via the MOVES III programme since 2021, co-ordinated by the Spanish Institute for diversification and energy savings (IDAE), managed by the Catalan Energy Institute (ICAEN), and financed by the European Union program Next Generation EU. The MOVES III programme includes vehicles classified as M1 (light-duty vehicles and SUVs), N1 (vans and light vans), L7e (heavy quadricycles), L5e (light tricycles), L4e (motorcycles with sidecar), L6e (micro-cars), and L3e (motorcycles without sidecar); and excludes electric bicycles (Gobierno de España, 2024[3]). In the terms of ITF modelling, MOVES III incentives are based on a “like-for-like” approach: the incentives focus on replacing internal combustion engine vehicles (ICEVs) with EVs or hybrid vehicles, without aiming to trigger a switch to another transport mode (ITF, 2023[4]).
Interviews with Catalan stakeholders revealed confidence in the potential of EV incentives to reduce emissions from passenger transport in the region. The allocation of resources in the Integrated National Energy and Climate Plan (PNIEC) also reveal confidence in the policy. At the regional level, since 2021, EUR 65 million have been channelled annually via EV purchase subsidies and charging infrastructure (Table 4.1). Of the vehicles subsidised, 55% were battery EVs and 45% were plug-in hybrid vehicles2 (Internal information from ICAEN, (IDESCAT, 2024[5]), and larger vehicles receive larger subsidies in absolute terms3 (Generalitat de Catalunya, 2021[2]) (see Box 4.1 for an exploration of the environmental and safety implications of large vehicles). At the national level, 114 million euros are allocated to the promotion of electric vehicles (MITECO, 2024[6]).
Note: Funding for 2024 shows the expected amount until 31st July 2024.
Source: Authors, based on internal information from the Catalan Energy Institute (ICAEN).
Vehicle size has increased in most European countries since the 2000s (ICCT, 2023[7]) (Figure 4.2). In Spain, while the average vehicle size is below the European average, average vehicle size has increased by 15% in the last two decades (ICCT, 2023[7]). The upward trend in vehicle size is also observed in electric vehicle sales. Over the past six years, the share of electric SUVs and large EVs from global EV sales more than doubled (120% increase): SUVs and large EVs accounted for 25% of global EV sales in 2018 and for 55% in 2023 (IEA, 2024[8]).
Source: Extracted from (ICCT, 2023[7]), European Vehicle Market Statistics - Pocketbook 2023/24, https://eupocketbook.org/wp-content/uploads/2024/01/Pocketbook_202324_Web.pdf.
The increase in vehicle size is negatively correlated with environmental sustainability and safety. Energy consumption, GHG emissions, raw material consumption and extraction impacts, and use of public space all increase as vehicles get bigger (ICCT, 2023[7]; Oliver, 2020[9]). Road fatalities also rise as vehicle size increases. In car-versus-SUV crashes, car occupants face significantly higher fatality rates than in crashes with vehicles of a similar mass: the likelihood of car occupants dying in the accident doubles in collisions with medium-sized SUVs and triples in collisions with large SUVs (Davis and Truett, 2020[10]). In micromobility-vs-vehicle crashes, drivers of large vehicles were responsible for 4 out of 5 fatalities of micromobility users (Monfort and Mueller, 2020[11]; ITF, 2020[12]). The risk of pedestrian deaths also increases with SUVs and large EVs. The increased height of the vehicle front end means that the point of contact in collisions with pedestrians is more likely to be at chest or head level, which increases the risk of death. Evidence suggests that a 10-cm increase in front-end height is linked to a 22% to 30% increase in fatality risk for pedestrians (Tyndall, 2024[13]; VIAS Institute, 2023[14]).
ITF (2023[4]) finds that electrification subsidies have a higher abatement potential and can contribute to road safety if designed to foster the purchase of small vehicles such as electric microcars and micromobility, such as e-bikes and e-scooters. See Annex F for more information on how refined eligibility criteria for subsidies could lead to more sustainable choices.
Analysis for this report (based on the OECD methodology summarised in Figure 4.1 and explained further in Annex E) finds that incentives for the uptake of EV vehicles have an anticipatory intent and only limited potential to transform car-centric systems and reduce emissions at the pace and scale needed. The intent is anticipatory because the policy anticipates and reduces the negative consequences of growing private car use. The policy’s transformative potential is limited because the incentives do not fundamentally transform the way the system structure fosters car use. Although the incentives help to increase the share of EVs within the car fleet via increased EV sales (1 in Figure 4.3), they leave the system structure intact, and may in fact inadvertently reinforce it in two ways.
First, EV incentives may induce car demand and urban sprawl, and reinforce a car-centric structure. EVs generally cost less to use than ICEVs (2 in Figure 4.3), which can lead to increased distances travelled (3 in Figure 4.3) (Orsi, 2021[15]; Caulfield, Carroll and Ahern, 2020[16]; Kampman, van Essen and Braat, 2011[17]), creating a rebound effect as the share of EVs in the car fleet increases. Orsi (2021[15]) found that, on average in Europe, EVs halve the cost of driving when compared to an ICEV (for 100km before recent oil price increases) and estimated a 6-18% increase in total mileage as a result. Evidence on the rebound effect of electric vehicles is, however, not always consistent with this estimate. For example, a study in Germany found that for a subgroup of households who substituted an ICEV with an EV, annual mileage decreased by 23%, suggesting behaviour aligned with environmentally-friendly choices rather than a rebound effect (Huwe and Gessner, 2020[18]).
Note: To avoid clutter, the diagram does not show that EV incentives may also reduce ICEV sales, or that increasing the attractiveness of driving also directly increases total distances travelled by car. The coloured arrows show the relationship between variables. A pink arrow between variables means that they vary in the same direction: an increase in a variable leads to an increase in the variable it points to; a decrease in a variable leads to a decrease in the variable it points to. A blue arrow means that variables vary in the opposite direction: an increase in a variable leads to a decrease in the variable it points to; a decrease in a variable leads to an increase in the variable it points to. Arrows marked by a “||”- symbol indicate a delayed effect. Each loop label (e.g. B1) denotes a feedback loop. A feedback loop is either reinforcing (R) or balancing (B). See Box 3.2 in Chapter 3 for more information on how to read causal loop diagrams.
Second, EV incentives may reinforce “moto-normativity”4 or car-centric mindsets. EVs are often presented as “zero-emissions” or “carbon-neutral” vehicles, which could potentially lead to an overestimation of their environmental benefits (Box 4.2) and may lead to the perception that using a private EV for the bulk of trips is sustainable. This perception may reduce public support for policies aimed at triggering modal shifts towards active and shared modes, such as public space redistribution. Climate policy packages solely or mostly focused on EV incentives may also reinforce the perception of unfairness in the climate transition. Low-income households may lack savings to buy a new vehicle despite subsidies (Aryanpur et al., 2022[19]), and live in rented accommodation with low access to EV charging infrastructure. For example, in Ireland, EV subsidies mainly benefit high-income households (Caulfield et al., 2022[20]). Data on how EV subsidies in Catalonia have benefited different income groups are so far not available. The coupling of EV subsidies with low-emission zones, which restrict areas of the territory to people able to afford energy-performant or electric vehicles, may further reinforce the perception of injustice.5
When considering lifecycle GHG-emissions,1 emissions from EVs are in the range of 125g CO2/p-km (CO2/passenger-kilometre), only 23% lower than those generated by ICEV equivalents (ITF, 2020[21]). The EV production phase emits 75% more CO2 than ICEV production (42g CO2/p-km and 24g CO2/p-km respectively) (ITF, 2020[21]). As batteries’ production mostly takes place overseas, a transition from ICEVs to EVs shifts part of the avoided tailpipe emissions to battery-producing countries, where manufacturing plants are mostly powered by polluting energy sources2 (ICCT, 2018[22]; Henderson, 2020[23]).
The mining of lithium-ion and cobalt to produce batteries for EVs are associated with pressing environmental damage, health and human rights issues (IEA, 2021[24]). By 2050, the global cumulative demand for cobalt is projected to increase by a factor of between 7 and 17 based on stated EV policies, and would be double this number for a like-for-like uptake pathway (i.e. a swap between ICEVs and EVs) that aligns with the Paris Agreement (Xu et al., 2020[25]). Mining and battery production are unlikely to keep up with rising EV demand in a sustainable way (Banza Lubaba Nkulu et al., 2018[26]). Adding and expanding mining sites may exacerbate unfair labour conditions, cause habitat loss for endangered species and displace communities (Katwala, 2018[27]).
Whether or not EV fleets become an asset or a burden to the energy sector depends on the EV uptake scenario envisioned. There are promising opportunities to create synergies between shared EV fleets and the energy sector through vehicle-to-grid interactions3 (Gschwendtner and Krauss, 2022[28]). However, a like-for-like EV uptake complicates the energy transition as grid infrastructure will need to absorb an already increasing electricity demand (Henderson, 2020[23]).
The adoption of EVs powered by renewable energy would increase land use for solar and wind production, further increasing the space consumption gap between private cars and sustainable modes. The energy sector of EU Member Countries is committed to producing 42.5% of energy from renewable sources by 2030. Orsi (2021[15]) estimates the impact on land use of a 40% electrified European car fleet to be approximately 60 000 km2 (twice the size of Catalonia). The Catalan Energy Institute is currently developing estimates of the land required for producing local renewable energy to supply its transport system (Generalitat de Catalunya, 2023[29]) and the Department of Territory is making efforts to reduce the space footprint of such generation. For example, the initiative Carreteras descarbonizadas (decarbonized roads) aims to transform road infrastructure into energy generation hubs by installing renewable solar energy along existing roads (Generalitat de Catalunya, 2024[30]).
Notes: 1 Total GHG emissions generated during vehicle production, use, and end-of-life. 2 Most current and projected battery production takes place in China and is largely powered by coal (ICCT, 2018[22]). 3 Vehicle-to-grid interactions refer to energy to be pushed from the battery of an electric vehicle to the power grid.
The impact of subsidies on transitioning the vehicle fleet may take longer than expected. Vehicle fleets are “hard-to-change” stocks: it could take several decades longer to replace the entire fleet than assumed. Global scenarios suggest that reaching high EV fleet shares before 2050 seems unlikely (IEA, 2022[31]). Large volumes of ICEVs will continue to enter the fleet until at least 2035 and endure for 10-15 years (OECD, 2022[32]). The case of Norway, the fastest adopter of EVs, illustrates the delay between attaining a high share of vehicle sales and changing the total vehicle stock. By the time EV sales in Norway reached 80% of total sales (perceived as an important milestone), only 20% of the car fleet was electric (OECD, 2022[32]).
In Catalonia, ICAEN estimates that ICEVs will continue to make up the majority share of vehicle sales until 2029 and will represent an important – although declining – share of total sales until 2036 at the earliest. Although total sales of electric and hybrid vehicles in Catalonia have increased yearly since 2017, the number of ICEVs entering the fleet has remained approximately 20 times that of EVs (Figure 4.4). The share of EVs in the total vehicle fleet is estimated at only 1% in 2022.6
The extent to which EV subsidies can reduce emissions also depends on the energy mix underlying electricity supply. In Catalonia, EV subsidies have the potential to reduce emissions, as almost two thirds of the electricity produced in the region came from nuclear and renewable energy (2022 data) (Idescat, 2022[33]).
Evolution of battery-electric (EV), plug-in hybrid vehicle (PHEV) and other vehicle sales (ICEV) in Catalonia
Source: Authors, based on internal information from the Catalan Energy Institute (ICAEN).
Low emission zones (LEZs) aim to reduce emissions and local air pollutants by restricting access to certain areas by emission-intensive vehicles. State Law 7/2021 on Climate Change and the Energy Transition mandated that all Spanish municipalities exceeding 50 000 inhabitants must establish an LEZ by 2023 (BOE, 2021[34]).7 Catalonia lowered the inhabitant threshold to 20 000 for municipalities that regularly exceed air pollution levels (ATM Barcelona, 2023[35]). Additionally, the recently approved Air Quality Plan outlines specific conditions and a timeline for implementing LEZs in selected Catalan municipalities (Generalitat de Catalunya, 2024[36]).
By 2024, 10 municipalities have implemented LEZs (AMB, 2024[37]; ZBE Cat, 2024[38]) and by 2026, 67 municipalities are expected to have established LEZs. In the AMB area, the access restriction includes a temporary exception for low-income households and people of reduced mobility (Sergio, 2024[39]; AMB, 2024[40]).
Analysis for this report finds that LEZs have an anticipatory intent and low transformative potential. LEZs aim to limit and anticipate the negative consequences of private vehicle use (e.g. air pollution) by restricting access to certain zones by polluting vehicles. The transformative potential of LEZs is low because the policy effect on the system structure is mixed and temporary. The effect is mixed because, on the one hand, LEZs (1 in Figure 4.5) reduce the attractiveness of driving for owners of polluting vehicles (2) due to limited access to certain zones, potentially reducing traffic volume. On the other hand, LEZs increase the attractiveness of driving low-emission vehicles due to reduced traffic and travel time (3). The effect of LEZs is temporary because the number of people owning energy-performant or electric vehicles, and thus having access to the restricted area, may increase if the policy is successful, leading to improvements in air quality but a rebound to former traffic volumes.
Note: The coloured arrows show the relationship between variables. A pink arrow between variables means that they vary in the same direction:
an increase in a variable leads to an increase in the variable it points to; a decrease in a variable leads to a decrease in the variable it points to. A blue arrow means that variables vary in the opposite direction: an increase in a variable leads to a decrease in the variable it points to; a
decrease in a variable leads to an increase in the variable it points to. Arrows marked by a “||”- symbol indicate a delayed effect Each loop label (e.g. B1) denotes a feedback loop. A feedback loop is either reinforcing (R) or balancing (B). See Box 3.2 in Chapter 3 for more information on how to read causal loop diagrams.
The impact of LEZs on mindsets is also mixed. On the one hand, the introduction of LEZs in Catalonia has strengthened the link between mobility and public health in public debates, which can foster more holistic action. On the other hand, the policy may reinforce the idea that vehicle improvements may be sufficient to achieve well-being and climate outcomes and reinforce the perception of an unjust green transition if the impact and benefits of LEZs are unequally distributed across income groups. Evidence from London and Brussels suggests, for example, that LEZs have disproportionately affected low-income households who live in areas with poor public transport services and who are likely to own non-compliant vehicles unable to access LEZs (Verbeek and Hincks, 2022[41]).
Investment in public transport aims to improve bus and rail infrastructure and services. Data aggregated at the regional level (since 2015) suggest that investment in public transport is a priority for Catalonia. Investment in the rail network has been more than double the investment in the road network since 2015 (Figure 4.6), whereas the reverse is true for OECD territories on average (especially for maintenance costs) (OECD, 2023[42]). Investment in Catalonia’s rail network led, for example, to a 57% and 44% increase in metro and tram infrastructure coverage (respectively) between 2005 and 2022 (Generalitat de Catalunya, 2023[43]). Additionally, 30 kms of interurban Bus Rapid Transit corridors (BRCat) are currently being built or planned (EUR 78 million, not shown in Figure 4.6).
Recent infrastructure investments and maintenance and operating costs in Catalonia by mode (2015-2021)
Note: These infrastructure investments reflect the interurban network and investments in rail and bus networks reflect mostly investments in the interurban network and investments in metro (rail), tramway (rail), and buses in the AMB area. Notable exceptions are direct investment from municipalities (mainly urban buses outside AMB, public space design and the construction and maintenance of bike lanes in urban areas). When unknown, the ratio between road maintenance and new infrastructure is assumed equal to the average ratio from the investment data for which this information is available.
Source: Authors, based on internal information from the Department of Territory.
The analysis of this report finds that public transport investment has a transformative intent and medium transformative potential. Investment in bus and rail (1 and 2 in Figure 4.6) has a transformative intent as it aims to enable the conditions for modal shifts towards public transport via the provision of better services (3 in Figure 4.6). The transformative potential is rated as only medium, however, due to the skewed distribution of infrastructure and space in the system. While aggregated data on investment before 2015 are not available, the kilometres of infrastructure per mode illustrated in Chapter 3 (section 3.3.1) highlight that the priority given to investment in motorised vehicles in previous decades has locked-in these modes within the system.
Notes: 1 The arrow between rail investment and attractiveness of sustainable modes has a delay mark (“||”). As noted by many stakeholders during interviews, the results of rail investment will tend to take longer to appear Bus investment, for instance by deploying Bus Rapid Transit services, can be more rapid than rail investment. 2 The coloured arrows show the relationship between variables. A pink arrow between variables means that they vary in the same direction: an increase in a variable leads to an increase in the variable it points to; a decrease in a variable leads to a decrease in the variable it points to. A blue arrow means that variables vary in the opposite direction: an increase in a variable leads to a decrease in the variable it points to; a decrease in a variable leads to an increase in the variable it points to. Arrows marked by a “||”- symbol indicate a delayed effect. Each loop label (e.g. B1) denotes a feedback loop. A feedback loop is either reinforcing (R) or balancing (B). See Box 3.2 in Chapter 3 for more information on how to read causal loop diagrams.
Given the extent of the physical lock-in of road infrastructure and the vehicle fleet (see Figure 3.13, and Figure 3.14), increasing the quantity of investment in public transport may not be sufficient for it to become as attractive as (or more attractive to) driving, unless coupled with ambitious efforts to redistribute space (see Section 4.6). To illustrate the limitations of investing in a system already dominated by cars (investment that adds), Figure 4.8 uses the level of water in a bathtub to represent the attractiveness of each mode, proxied by the space and infrastructure allocated to each of them. The left-hand side of the figure represents the current situation, whereby road infrastructure over the second half of the 20th century have received more investments than other modes (ITF, 2023[44]; ITF, 2021[45]; OECD, 2024[46]). This has led in most areas to an attractiveness gap, represented by the uneven water levels in both bathtubs on the left-hand side of the figure.
This analysis suggests that, in addition to public transport investments (opening the public transport tap), efforts to subtract space from private cars may be needed in parallel (right-hand side of Figure 4.8). Policy packages are not limited to opening and closing taps; they can also pull the plug of road infrastructure to liberate space and redistribute it to favour sustainable modes. As is further discussed in Chapter 5, given the physical lock-in of the system, policy packages will need to simultaneously pull the plug and redistribute space across modes to trigger modal shifts towards sustainable modes. This is because space is a key determinant of the attractiveness of transport modes and is also a limited resource: allocating space to one mode means it is unavailable for others.
Source: Authors.
The effect of public transport investment on mindsets is mixed. On the one hand, it can reinforce the idea that a wider use of shared modes is necessary and desirable. On the other hand, when disconnected from policies such as space redistribution, the investment may fail to trigger modal shifts towards shared modes at scale, leading to a sense of impossibility and discouragement among the public and staff. Indeed, as mentioned in Chapter 2, there is little optimism in the region surrounding the public sector’s capacity to improve public transport and foster modal shifts. Interviews also revealed frustration among stakeholders and a feeling of “swimming against the current” when trying to trigger modal shifts towards shared modes. For some stakeholders, the absence of modal shifts towards public transport, despite substantial effort and investment, reinforced the idea that the choice of private vehicles is an individual preference beyond the scope of policy.
Fare reductions for public transport refer to a discount on public transport ticket prices for all citizens. Public funding covers the difference in cost between the regular and the reduced fares. As part of a wide effort to foster the use of public transport, Catalonia has reduced fares and increased integrated ticketing since 2001. In addition, the Spanish government implemented two fare reduction packages across Spain in December 2022 to compensate for the rising cost of living due to energy price increases, and to simultaneously promote sustainable transport (Gobierno de España, 2023[47]).8 This involved halving the price of multi-trip cards. Autonomous communities such as Catalonia could decide whether to opt in to the policy, and if they chose to join, the cost of the fare reduction was shared 60:40 between the state and autonomous communities. Catalonia chose to adhere to the policy; in 2022, the policy cost the region EUR 69.2 million.9 For commuter and regional services operated by Renfe (national rail operator), and state-owned bus lines connecting autonomous communities with other regions, tickets became free on meeting certain conditions.10 The state funded the entire cost of this policy.
The analysis for this report finds that fare reductions on public transport have a reactive intent and a low transformative potential. The policy has a reactive intent because it is designed to compensate or reduce the harm of a cause outside its remit, in this case, increased energy prices.11 Its transformative potential is low because the policy does not rebalance the bias in the system that favours cars, and may in fact reduce the attractiveness of public transport (and perceptions of attractiveness) due to crowding and a lack of budgets to improve services. Via lower prices, fare reductions (1 in Figure 4.9) temporarily increase the attractiveness of sustainable modes (2). However, the resources allocated to cover the price difference are no longer available to improve the capacity, quality and connectivity of public transport (3), thus potentially reducing its attractiveness in the medium to long term.
Note: The coloured arrows show the relationship between variables. A pink arrow between variables means that they vary in the same direction:
an increase in a variable leads to an increase in the variable it points to; a decrease in a variable leads to a decrease in the variable it points to. A blue arrow means that variables vary in the opposite direction: an increase in a variable leads to a decrease in the variable it points to; a
decrease in a variable leads to an increase in the variable it points to. Arrows marked by a “||”- symbol indicate a delayed effect. Each loop label (e.g. B1) denotes a feedback loop. A feedback loop is either reinforcing (R) or balancing (B). See Box 3.2 in Chapter 3 for more information on how to read causal loop diagrams.
Evidence suggests that price is not the main factor determining mode choice and may thus have limited impact in triggering modal shifts towards public transport. In Ireland, Caulfield, Caroll and Ahern (Caulfield, Carroll and Ahern, 2020[16]) suggest that fare reductions and free transport may jeopardise efforts to increase the service attractiveness. Another study, of seven European cities, finds that, in addition to affordable prices, other factors such as built environment, service quality and reliability, access to stations, and access restrictions to private vehicles play a key role in people’s decision to use public transport (Gascon et al., 2020[48]). Two recent travel surveys from Tarragona show that despite the price difference between driving a private car and using public transport, more than half of the population choose to drive12 (ATM Tarragona, 2020[49]). In both surveys, the two most common reasons given for private vehicle use were (1) the lack of an adequate public transport offer (32% and 41% of car users in each survey); and (2) relative comfort (36% and 29% of car users in each survey) (ATM Tarragona, 2020[49]), rather than price. The introduction of Germany's 9-Euro Ticket, a public transport pass offered for a month at a reduced price, primarily resulted in increased travel among existing public transport users, rather than reduced car use (Andor et al., 2023[50]). OECD (2021[51]) analysis suggests that a combination of targeted fare reductions, for example, based on income, and policies to eliminate hidden subsidies to car use (such as free highways or underpriced on-street parking) may allow governments to ensure affordability of public transport to all citizens while continuing to invest in service quality improvements.
Road space redistribution and street redesign (road space redistribution hereafter) refer to the reallocation of space currently dedicated to roads for cars and motorcycles to sustainable transport modes and/or to green or recreational spaces, or markets. Public space affects the relative attractiveness of transport modes (Héran, 2008[52]), and its distribution is thus fundamental for triggering behavioural shifts towards sustainable modes. Rueda (2012[53]) estimates that 60 to 70% of public space is dedicated to roads for private motorised vehicles in Spanish cities. Figure 3.18 in Chapter 3 shows the space allocated to each mode in the city of Barcelona. Data on space allocation was not available for the rest of the region.
The city of Barcelona is the birthplace of the Superblock initiative (Superilles in Catalan), an international reference for road space redistribution and street redesign initiatives around the globe (Figure 4.10).13 Superblocks are polygons of approximately 400 square metres, hosting 5 000 to 6 000 residents, in which pedestrians and cyclists have priority over private vehicles, which can only access the area at a maximum speed of 10km/h (OECD, 2021[51]). The concept of Superblocks originated in the 1990s and aimed to cover the entire Barcelona municipality, increase the space allocated to pedestrians from 16 to 67%, and reduce the space allocated to private motorised vehicles by between 61 and 70% (BCN Ecologia, 2021[54]; Rueda, 2019[55]; Eggimann, 2022[56]). Between 2004 and 2020, Barcelona doubled the surface area of streets with pedestrian priority, from 62 hectares to 133 hectares (Ajuntament de Barcelona, 2020[57]). With the Green Axis project in 2023 transforming an additional 12 hectares, the city now has 145 hectares of pedestrian-priority streets, representing 7.6% of the total street surface in the city (Ajuntament de Barcelona, 2021[58]).
The implementation of interurban Bus Rapid Transit (BRCat) in Catalonia since 2012 provides another example of the reallocation of space towards sustainable modes. The six initial BRCat projects aim to create 30km of bus-prioritised lanes,14 as well as 28km of segregated bike lanes. Some of the lanes were (or will be) created by widening existing roads, others by reallocating existing roads to bus lanes (data on the shares of road widening and reallocation were not available at the time of drafting this report). The Catalan “bus-VAO” – 18 kilometres of interurban exclusive lanes on high-congestion roads for buses, vehicles with 3 or more users, and low-emission vehicles – is another example of space reallocation (Generalitat de Catalunya, 2023[59]). There is currently no aggregated information on space allocation for dedicated bus lanes at the municipality level.
Note: Within superblocks, priority is given to pedestrians and cyclists, while motorized traffic is restricted to residents, delivery vehicles, and emergency services. All streets within a superblock are converted to one-way streets for cars, and to two-way streets for cyclists, with speed limits set between 10 to 20 km/h (except for emergency vehicles). Through traffic and public transport are redirected to the larger streets surrounding the superblocks. See Annex G and (Eggimann, 2022[56]) for further information.
Source: Produced by Prof Dr Sven Eggimann.
The analysis for this report concludes that road space reallocation has transformative intent and high transformative potential if implemented at scale. The policy aims to transform the system structure by affecting a key stock in the system: public space. The policy’s transformative potential lies on the weakening of the dynamic of induced car demand, and the introduction of a new dynamic: the induced demand of sustainable modes (Figure 4.11).
As explained in Chapter 2, policy packages designed through a reactive and mobility-focused mindset have focused on reducing congestion by increasing road capacity for cars. Policy packages designed instead through an accessibility and relative-attractiveness mindset can use road space redistribution (1 in Figure 4.11) to respond to the public pressure to reduce congestion (9), thus weakening the dynamic of induced car demand and “breaking” the link between public pressure to reduce congestion (9) and public investment in roads (2). By reducing the currently over-dimensioned road capacity for cars (3), the redistribution of road space to sustainable modes (2) acts on “both sides of the attractiveness gap”. It liberates space for sustainable modes (4 and 5) and increases their attractiveness (7), while also making driving less attractive (8). Evidence shows that, when implemented at scale,15 road space redistribution has led to significant reductions in traffic volume (Box 4.3). The space redistribution may also help to reduce a city’s catchment area (6) as the liberation of space for local services and activity provides opportunities for creating proximity between people and places. The integration of land-use and transport policies is fundamental to harness this potential.
Note: The coloured arrows show the relationship between variables. A pink arrow between variables means that they vary in the same direction:
an increase in a variable leads to an increase in the variable it points to; a decrease in a variable leads to a decrease in the variable it points to. A blue arrow means that variables vary in the opposite direction: an increase in a variable leads to a decrease in the variable it points to; a
decrease in a variable leads to an increase in the variable it points to. Arrows marked by a “||”- symbol indicate a delayed effect. Each loop label (e.g. B1) denotes a feedback loop. A feedback loop is either reinforcing (R) or balancing (B). See Box 3.2 in Chapter 3 for more information on how to read causal loop diagrams.
Empirical evidence shows that reallocating road space can reduce overall traffic volume, a phenomenon known as "traffic evaporation" (Cairns, Atkins and Goodwin, 2002[60]; Rapid Transition Alliance, 2019[61]). Nello-Deakin (2022[62]) finds that road space redistribution has led to disappearing traffic in territories across the OECD, with an average traffic reduction of 14%. Cairns, Atkils and Goodwin (2002[60]) found an average of 21.9% traffic reduction (based on 70 case studies), due to changes in traffic behaviour such as rerouting, modal shifts, and trip suppression (Cairns, Atkins and Goodwin, 2002[60]; Melia and Calvert, 2023[63]). In Pontevedra, Spain, street redesign and mixed land-use planning cut car traffic by 69% in the town centre and 90% in the downtown core (Concello de Pontevedra, 2019[64]). In Finland, after the permanent closure of Kajaani's High Street, over half of the former traffic did not reappear on nearby streets, effectively "evaporating" (Rapid Transition Alliance, 2019[61]). Similarly, in Barcelona, tactical urbanism interventions in the context of the COVID-19 pandemic resulted in a 14.8% traffic decrease, with minimal traffic increase on adjacent roads (Nello-Deakin, 2022[62]). In Paris, the closure of the banks of the River Seine led to an overall traffic decrease of 5-28% on parallel roads. A 40% reduction in car traffic was observed between 2011 and 2024 across the city as a consequence of space reallocation efforts (Hasse, 2017[65]; Varoquier and Hasse, 2018[66]; Ville de Paris, 2024[67]). Oslo saw a 16-21% reduction in car commuting without severe delays or congestion, and Copenhagen reduced traffic by increasing space for walking, cycling, and public transport (ITF, 2021[45]).
Road space redistribution also impacts mental models by reinforcing the idea that behavioural change is needed to improve system outcomes. The policy aligns the objective of modal shifts towards sustainable modes with concrete action to enable this shift. To increase political support, the policy needs to be accompanied by communication efforts to counteract ingrained ideas about the policy impact (Thigpen et al., 2022[68]). These include the perception that the policy will displace rather than reduce traffic, thus “moving the problem from a place to another”; and the perception that it may harm local businesses. These perceptions can be counteracted by the evidence presented in Box 4.3 and Box 4.4.
Evidence also suggests that public support for the policy may be higher than currently perceived by public officials. For example, data from France revealed that there is often a discrepancy between the perceptions of public officials and the actual opinions of citizens. Already in 1999, 72% of French citizens were in favour of limiting car usage to improve urban traffic, yet mayors underestimated this, believing only 27% supported such measures (Chassignet, Wester and Louvet, 2024[69]). Today, similar findings continue to show public support for such policies. For example, Dublin carried out a consultation in the context of its city centre transport plan (approved in 2024) to ask the population for their views on space reallocation and the limitation of through traffic in the city. To one of the questions in the consultation - "Do you think road space for private vehicles in the city centre should be reduced to facilitate a more efficient public transport system that has increased capacity?" - over 80% of participants expressed support for the proposal (Dublin City Council, 2024[70]). Interestingly, over half of car drivers (54%) also endorsed this measure.
Reallocating street space enhances urban environments, promotes liveability and supports active modes like cycling. However, public acceptance can be challenging due to concerns about disruptions to businesses and daily life (ITF, 2022[71]).
Studies show that car-free or low-traffic zones often increase customer interest and commercial activity. For example, Oslo's Car-free Liveability Program faced business opposition, but eateries in car-free zones saw an increase in consumer interest, as evidenced by Yelp data (Bliss, 2021[72]; European Commission, 2021[73]). A survey conducted in Berlin showed that only 7% of customers on commercial roads used cars, with non-car travellers accounting for 91% of spending (von Schneidemesser and Betzien, 2021[74]). A London study found that non-drivers spent more per month at shopping centres than drivers (Transport for London, 2011[75]).
Shifting kerbside space from car parking to mixed-use purposes, such as bike parking or cafe dining, has economic advantages. A study by Urbis found that bike parking can generate more revenue than car parking within the same space (Urbis, 2021[76]; Lee and March, 2010[77]). Increased pedestrian and cyclist flows from pedestrianising streets and creating biking infrastructure are associated with new business creation and job growth, as seen on Madero Street in Mexico City, where commercial activity increased by 30% and crime decreased by 96% (C40, 2018[78]).
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← 1. Both battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) with an electric range of above 30km are eligible for the subsidy (Generalitat de Catalunya, 2021[2]).
← 2. Evidence suggests a gap between the advertised abatement potential of plug-in-hybrids and their real performance. See (Transport & Environment, 2020[80]; European Commission, 2024[81]) for more.
← 3. Subsidies range from EUR 1 100 for electric motorcycles to EUR 7 000 for vans (Generalitat de Catalunya, 2021[2]).
← 4. ITF (ITF, 2024[79]) defines moto-normativity as “decisions about motorised transport, by individuals and policy makers, that show unconscious biases due to cultural assumptions about the role of private cars and which may systematically distort policy decisions and prevent addressing the role of the car objectively. [Moto-normativity] can result in a built-in acceptance of risks and harms from motor vehicles”.
← 5. The restriction exception in the AMB area based on income (Sergio, 2024[39]; AMB, 2024[40]) may reduce this risk in Barcelona.
← 6. Estimates from the Department of Territory on ICAEN and IDESCAT data, based on the assumption that all EVs purchased since 2017 are still in circulation.
← 7. According to this criterion, 20 Catalan municipalities must establish a LEZ by 2026.
← 8. The package was designed to last for a year, but the policy remains active in 2024, after being extended twice.
← 9. Internal information from the Department of Territory.
← 10. Users paid deposit fees for tickets which could be fully reimbursed once they reached a threshold of 8/16 trips per month (depending on which ticket was purchased).
← 11. The State policy stated objective was to “respond to the economic and social consequences of the war in Ukraine, to contribute to alleviating citizens' pockets in the face of the high price of energy, which particularly affects daily mobility, while at the same time encouraging the use of collective public transport, a safer and more sustainable mode of transport” (Gobierno de España, 2023[47]).
← 12. ICEV drivers spend an average of EUR 119 per month (EUR 100 on fuel, EUR 11 on tolls, and EUR 7-8 on parking), while public transport users pay an average of EUR 25 per month on public transport (ATM Tarragona, 2020[49]). More than half (53%) of people in Tarragona choose to use private vehicles (ATM Tarragona, 2020[49]).
← 13. For more details see Annex G.
← 14. Bus prioritisation includes measures such as exclusive bus lanes, priority at traffic intersections, and traffic redistribution to reduce congestion in bus itineraries.
← 15. Implementation at scale is also fundamental to avoid gentrification effects.