Transport Strategies for Net-Zero Systems by Design

Report

8 November 2021

2. Transport strategies for net-zero systems by design: changing priorities

Abstract

This chapter provides a summary of the results obtained from applying the three steps of the Well‑Being Lens process to the surface transport sector. The first step – envision – defines the outcomes that a well-functioning system should achieve. The second step – understand – provides a snapshot of the key dynamics leading to unsustainable-by-design transport and urban systems. The chapter explains how mobility-oriented mental models and policies lead to unsustainable results and limit the scope and effectiveness of climate strategies. It also provides a snapshot of what climate strategies embedded in a system redesing logic will look like for the sector.

Achieving the Paris Agreement goals will require transformational change. The OECD Well-being Lens process aims to help policy makers identify policy packages with the potential to achieve such change. It triggers two mind-set shifts, that this report argues are needed to meet net-zero targets on time: i) from means (e.g. GDP) to ends (well-being); and ii) from parts to systems functioning. The first shift allows envisioning an increase in well-being (health, equity, etc.) through low-demand systems (rather than considering high demand as a condition for high life quality). For policy-making, this means that managing or reducing demand becomes a policy lever. The second shift sheds light on the importance of understanding the systems’ dynamics driving unsustainable results. For policy-making, this means focusing climate action on reversing such dynamics and redesigning systems.

This report applies the three steps of the Well-being Lens process to the passenger surface transport sector,1 with a focus on urban areas and their hinterlands. The first step of the process, envision, is about defining the outcomes that a sustainable system should achieve.

The second step, understand, is about identifying: i) key dynamics in the system’s structure that are leading to unsustainable results (i.e. the vicious cycles); ii) relevant actors in the system; and iii) barriers to systemic change (e.g. mindsets, policies in place, governance, budget allocation, monitoring frameworks, power dynamics). This report focuses on an analysis of the key systems dynamics2 underlying car dependency (sub-step i), and discusses how a mobility-oriented perspective, monitoring frameworks and governance arrangements – and the policies that result from these – lead to such results (elements of sub-step iii). Further analysis of the relevant actors, institutional arrangements and power dynamics (which may explain, for example, why a mobility-oriented perspective has prevailed) are interesting areas for future research.3

The third step, redesign, is about identifying the policies with the potential to reverse the undesired dynamics discussed in Step 2, and the way forward for ensuring their implementation. It is about identifying actions that would accelerate the transition towards urban and transport systems that – by design – produce desirable and sustainable results.

Section 2.1 focuses on the first step of the Well-being Lens process: envision. It defines the outcomes that a well-functioning4 system should achieve. Section 2.2 focuses on the second step: understand. It provides a snapshot of the key dynamics leading to unsustainable-by-design (i.e. car-dependent) transport and urban systems (analysed in more detail in sections 3,4, and 5). It also discusses how mobility-oriented mental models and policies lead to such unsustainable dynamics, and limit the scope and effectiveness of climate strategies.Section 2.3 provides a summary of the type of policies and actions that can help urban and transport systems shift away from unsustainable dynamics, and in this way help accelerate the tansition towards net-zero, while also improving well-being.

2.1. Envision sustainable-by-design transport systems

A first step to transitioning towards sustainable systems is to define the type of results a well‑functioning system should provide, as to then understand how current systems should be (re)organised/designed to achieve those results. By sustainable systems, we refer to systems with the possibility to continue a specific behaviour over long periods of time (e.g. without hitting limits that hinder such functioning). This depends on environmental, social and economic sustainability, which are intrinsically interrelated. The notion of sustainability also embeds the notion of resilience throughout this report, as the ability to cope with crises and shocks is a necessary characteristic of systems that last.

This report defines the sustainable delivery of accessibility as the key desirable outcome of sustainable transport systems.5 This is based on two ideas. First, as discussed in (OECD, 2019[1]), people’s well-being does not ultimately depend on how much and how far they can travel, but on the possibility to easily access opportunities and meet their needs (e.g. consumption, leisure, work, health services, etc.) with ease (accessibility), including by not having to travel long distances, or not having to travel at all. Second, access needs to be created sustainably, i.e. by enabling the conditions for most trips to be done safely and conveniently through active and/or shared modes (including public transport). These modes are less space-intensive than private vehicles,6 allowing for a better balance between proximity and mobility7 (see Section 2.2). They are also less emission- (and pollution-) intensive.

Current transport and urban systems perform poorly in the sustainable delivery of accessibility. Accessibility is limited, in particular for low-income households, and the most space- and emission-intensive transport modes are privileged.

Figure 2.1 shows what the transition from “unhealthy” to “healthy” transport systems could look like. The left panel illustrates the most frequently used transport means in (current) unsustainable transport and urban systems. The right panel illustrates the most frequently used transport means in sustainable systems, as described above. The figure uses the food pyramid analogy. The healthiness of a food diet can be assessed by positioning the foods we eat in a pyramid, according to their frequency and amount. If sugar and fat are the bottom of the pyramid (i.e. eaten often), our diets are unhealthy, and will likely lead to undesirable results such as diabetes or obesity.

Figure 2.1. From unhealthy to healthy transport systems

Applying this analogy, “unhealthy” transport (and urban) systems are those in which people use motorised, and in particular private, vehicles (the sugar and the fat) for the majority of their trips (represented at the bottom of the pyramid, in the left panel). This is the case in most territories today, where distances to places are long, and where private motorised vehicles (cars, motorbikes) are the safest and quickest (and sometimes only) transport means available. Importantly, even when often less convenient and safe than cars, public transport is also used by many, often “captive users”, to cover the bulk of their daily trips, due to average long distances to their places of interest. Thus, also adding emissions that could be avoided if high shares of those trips were shorter and made by active modes; as well as if public transport was invested in and made better and cleaner.

The outcome of such a system is high traffic volumes (mobility), with several negative impacts, such as high emissions, air pollution, poor road safety, and disease (e.g. caused by air pollution as well as a lack of physical activity). Long distances and restricted travel options also result in poor and unequal accessibility. As will be explained in detail in Section 2.2, the choice to drive a car or a motorbike is not solely a result of people’s individual preferences (as is often argued). It is, to a large extent, the result of transport and urban systems shaped by mobility-oriented policies, i.e. policies focused on allowing people to move as fast and as far as possible. Such systems ignore the mismatch between increased travel and access to services and opportunities (Ferreira, Beukers and Brömmelstroet, 2012[2]) and the importance of creating proximity (see Section 2.2).

“Healthy”, or sustainable-by-design, transport and urban systems are those in which people walk, cycle and use micro-mobility for the majority of their trips (represented at the bottom of the pyramid, in the right panel). People use more emitting and space-intensive modes for less frequent trips (towards the top of the right-hand pyramid). This is possible in systems in which distances between people and places are short (there is proximity), and where the public space is organised in such a way that active and shared modes (including public transport) are the fastest and safest modes for most people (including children) to get to places. This implies that, by design, these systems will yield lower mobility and emissions while at the same time result in healthier lifestyles, and higher quality and more equitable access to opportunities.

Section 2.2 explains why current transport and urban systems are “unhealthy”, and what can be done to transition towards “healthy” systems.

2.2. Understand why current transport and urban systems are unsustainable

Transport and urban systems are social systems created and shaped by people through a more or less co-ordinated series of decisions and actions. These decisions and actions are, in turn, the result of what we measure and consider success, which ultimately depends on the mental models that shape what we see.

Mental models can be thought of as the lens through which humans observe reality.8 They are the unquestioned, and often implicit or unconscious, assumptions through which we understand the world. The type of systems in which we operate are shaped, and reinforced, by these implicit assumptions, which are, in turn, shaped by the stories that we have been exposed to (Figure 2.2; see also Box 2.2).

Figure 2.2. Systems, actions and mental models

This section focuses on understanding why current transport and urban systems are “unhealthy”, or unsustainable-by-design. It is an invitation to question some of the implicit assumptions through which transport and urban systems have been shaped in the past.

The first sub-section provides a snapshot of the functioning of most transport and urban systems (“the system we create” in Figure 2.2). This functioning, as will be explained, leads to car-dependency and increased traffic volumes, making systems “unhealthy” by design. The following sub-section analyses how mobility-oriented policy decisions (“what we do” in Figure 2.2) and the mental models and measurement frameworks underlying them (“what we see” and “what we measure” in Figure 2.2) have locked (and continue locking) transport and urban systems into “unhealthy” dynamics. It also explains why mobility‑oriented and analytical (rather than systemic) decision making limits the scope and effectiveness of climate strategies, leaving countries ill equipped to achieve net-zero goals on time.

2.2.1. The system we create

Figure 2.3 illustrates the dynamics often observed in transport and urban systems. Understanding these dynamics (or functioning) can help policy makers identify what drives the behaviours/results they are trying to influence), and what needs to change in the system structure (or design) to achieve different results. This report uses system dynamics: an approach to understanding the cause-effect relationships that lead systems to behave as they do, and thus produce the results that we observe (e.g. unsustainable levels of emissions, increased traffic volumes, etc.).9

One of the key insights policy makers can get from system dynamics analysis is that the results observed in a system (e.g. people using a car for the bulk of their trips) are not entirely a result of people’s independent choices, but that these choices are conditioned by the structure of the system in which these choices are made. If the choices people are making are unsustainable, and if those choices depend on the system’s design, redesigning systems to incentivise different choices is a crucial policy lever to achieve more sustainable results.

Based on Sterman (2000[4]), this report finds that three dynamics lead to car dependency, and are at the heart of why people use cars for the bulk of their trips. These dynamics are induced demand, urban sprawl, and the erosion of shared and active modes of transport.

Induced demand refers to the phenomenon by which investments in road expansion to reduce congestion end up having the opposite effect. Congestion increases because the more roads there are, the more attractive the car becomes and the more people choose to drive (see Section 3.1). Urban sprawl is the phenomenon by which people move further away from cities – which tend to concentrate the places of interest– when they can to them within a reasonable time budget, e.g. 30 minutes by car. The more roads expand, the more this is possible. Daily distances increase (as the new catchment area10 grows), density decreases, and single-use development11 is fostered. Both these dynamics erode active and shared modes (the third dynamic), either because they are not safe and/or because they are less convenient than, for example, driving a car. As distances increase active modes such as walking, cycling or micro-mobility are no longer an option. Also, as density decreases and single-use development expands, public transport is also less of an option, as it is difficult to get good service. Note that active and shared modes are often referred to as “alternative” modes, shedding light on how central cars (and private motorised vehicles more broadly) are in current mental models (see Box 2.2).

Figure 2.3. Key system dynamics leading to unsustainable transport systems

The dynamics illustrated in Figure 2.3 underlie the observed sustained increase in car use, travel distances and traffic volumes, which are the source of high emissions and a number of negative impacts on people’s well‑being. Among these are air and noise pollution, congestion, road injuries and fatalities, and reduced travel options, which lead to unequal access to opportunities. According to the ITF (2021[5]), private vehicle travel12 is responsible for three-quarters of all emissions from urban passenger transport, and this is the result of the continued growth in private vehicle ownership as well as the increasing average size of vehicles. Based on data from the International Energy Agency, the ITF report also highlights that under the current conditions, private vehicle ownership will grow by around 30% over the next ten years.

One of the key messages of this report is that the increased use of cars and related traffic volumes is not a fatality to which transport and climate policies need to adapt to, but the result of unsustainable system dynamics, which can be redesigned. As shown by Litman (2021[6]), people would choose to drive less, use active and shared modes more often if incentives and policy decisions did not favour automobiles over other modes of transport.

Furthermore, decarbonising a system that “encourages” more vehicles is a very difficult, if not impossible, task. Regardless of its feasibility, it is certainly not the most efficient or effective way to reduce emissions at the pace and scale needed (nor solve other key challenges, such as health or equity) (see section 2.2.2).

Reversing the dynamics described above should be at the core of transport and climate strategies. Most transport and climate strategies, however, either leave the dynamics intact or reinforce them. Section 2.2.2 dives deep into why this is the case.

2.2.2. Mobility-oriented transport policies

As illustrated in Figure 2.2, “the systems we create” are a result of “what we do”. What has been done in terms of transport policy, as explained by Chapman (2019[7]), has historically been to support mobility for economic growth, with other outcomes – including health and climate stability – seen as second-order priorities (Chapman, 2019[7]). Most transport policies are mobility-oriented: for decades, the priority of transport policies has been improving mobility via travel speed (Chapman, 2019[7]).

Such policy decisions are guided by analytical tools and measurement frameworks, which determine “what we see” (and what we don’t). Mobility-related metrics, such as vehicle-kilometres, passenger-kilometres (passenger), tonne-kilometres (freight) or number of trips, have historically been the gauges of “success” (bottom of Figure 2.4). Increasing mobility is, in turn, often used as a proxy for increased well-being and a prosperous territory, similar to how gross domestic product (GDP) growth is used as a proxy of progress or higher well-being at the economy level (see OECD (2019[1]); Hickel et al. (2021[8])).

Figure 2.4. Systems, actions and mental models: Application to the transport sector

The use of mobility as a proxy for “well-being” is linked to the deeply engrained mental model that the way to improve people’s well-being is by allowing them to travel as far and as fast as possible (i.e. increased mobility), with as much flexibility as possible. This and other related (also deeply engrained) ideas shape current policy decisions and citizens’ expectations, constituting a crucial barrier to systemic or transformational change. Some of these related ideas include:

The role of policy makers is to adapt to people’s choices, that are exogenous to (or independent from) the system in which they are embedded. In the transport sector, policy makers need to adapt to the inevitable growing use of cars as the city develops (Jones et al., 2018[9]) and income increases.13 This is based on the idea that people should be free to choose what is best for them, and that they tend to consider that driving a car is better than other transport options, unconditioned by the context. This leads to the association that car use is a “right” (ITF, 2021[5]).14
The “free” use of public space and road infrastructure (e.g. streets, parking slots) by cars, and the spread of the cost of such infrastructure across society is considered “normal” to ensure the “right” described above.15
Travel time is seen as the key “disutility” to be minimised. Air pollution, noise and road fatalities are seen as inevitable consequences of living in dense cities (e.g. the idea that if a person wants silence, they should move to the countryside or to lower density suburbs).
Cities and urban design are “fixed” (i.e. cannot be changed) and as cities grow, distances increase, and the only way to facilitate access to places is by allowing more, and faster, mobility. The street and territory redesign needed to make active (e.g. walking, cycling) and shared modes attractive can help in some cases, but it is only possible in already dense inner-city areas.

Lamb et al. (2020[10]) also identify deeply engrained ideas at the source of discourses of climate delay (Figure 2.5), which can be applied to the transport sector. When these ideas are coupled with the mobility-oriented mental models described above and the analytical paradigm described in Box 2.1, they lead to the decoupling focus (see more below) of current climate strategies and are a fundamental barrier to transformational climate action. “Technical optimism” is likely the most widespread discourse when it comes to reducing emissions in the transport sector.16 Technological optimism refers to the idea that technological improvements will allow countries to reduce emissions at the pace and scale needed. It sees technology as a way to increase vehicle performance (in terms of speed, fuel consumption, emissions, etc.), rather than improving the way systems are organised, where technological potential is mostly untapped and could lead to enormous emission reductions (see Chapter 6). The focus on technology applied to improving parts can be traced to a widespread analytical, rather than systemic, mindset (Box 2.1). “Appeal to well-being” is often also used to explain why reducing the number of cars to reduce emissions is not an option (as mobility is conflated with well-being, as explained above), and thus climate strategies are constrained to lowering vehicles’ emissions (i.e. decoupling growing mobility from emissions).

More broadly, Hickle et al. (2021[8]) identify a growth-oriented paradigm as a key barrier to net‑zero systems. The authors argue that “Growth is an unquestioned norm”, and that this is problematic since decarbonisation is more challenging in systems driving increases in energy demand.

Figure 2.5. Mental models underlying discourses of climate delay

Box 2.1. Differences between an analytical and systems thinking, and why this is important for achieving net-zero goals

There are two fundamentally different, and complementary, ways of thinking and understanding the systems1 around us: analytical thinking and systems thinking. Like tools in a toolbox, these ways of thinking are complementary, and using one or the other depends on the task.

Currently, however, there is a tendency to use analytical thinking to solve complex problems such as climate change or growing inequalities, for which systems thinking could be a better tool. This box explains the differences between analytical and systems thinking and why thinking in systems can unlock opportunities for achieving net-zero goals.

The analytical thinker breaks wholes into parts and focuses on optimising or replacing individual parts. The world is like a machine, and thus when trying to “repair the machine”, the analytical thinker tries to find the “piece” that is causing the problem, as to repair or replace it. An implicit assumption of this way of proceeding is that the whole is equal to the sum of its parts. This translates into the idea that the way parts are organised is not important: interactions between the parts do not affect the results or behaviour of the system (i.e. synergies2 do not exist), the properties of the parts do. Isolating, dividing and improving parts (e.g. vehicle emissions) is, thus, the logical way to solve problems.

The assumption that the whole is the sum of its parts does not hold for every system. Complexity science shows that, in complex systems,3 the whole can be more or less than the sum of its parts, depending on the way these parts are arranged (i.e. depending on positive or negative synergies).

“You think that because you understand ‘one’ that you must therefore understand ‘two’ because one and one make two. But you forget that you must also understand ‘and’.” (Meadows, 2008[11])

One of the key insights of complexity science is that the results observed from complex systems emerge from the systems’ structure, from the interactions among the parts rather than from the properties of the parts in themselves. If results depend on the system’s structure or design, there are opportunities for changing the results by redesigning the system’s interactions, which is what systems thinking allows one to do.

To solve problems, the system thinker focuses their attention on systems as wholes, on how parts could be reorganised to achieve better results. This is why this report recommends placing policies such as street redesign at the centre of climate strategies.

Figure 2.6. Analytical and systems thinking

The Well-Being Lens process applied in this report is a guide for applying systems thinking to policy making. It provides a set of tools, such as the causal loop diagrams in Sections 3.1, 4.1 and 5.1, that can help policy makers observe the system’s functioning at the source of emissions, and focus climate strategies on achieving better functioning systems for better lives.

1. A system is a set of elements whose interconnections determine its structure and behaviour. Elements are things, people, factories, bikes. Interconnections are the way the elements are organised: rules, incentives, sanctions, information.

2. A synergy is a particular type of interaction between parts; it is a non-linear interaction where the specific way the parts interact creates an effect greater or less than the simple sum of their effects in isolation.

3. A complex system is a system composed of many interdependent parts or components. The economy, the financial market, cities, transport systems, the food system, etc. are all complex systems.

Sources: Meadows (2008[11]); Systems Innovation (2020[13]).

The ideas and mental models are not independent from the stories that people have been exposed to. In the case of the transport sector, it is important to recognise that the mobility- and automobile-centric mind-set that we have today is a construction, as illustrated in Box 2.2. As such, constructing a “different story”, one of “automobile independence”, is possible; and this could importantly support the implementation of the type of policies put forward in this report (Box 2.3). Incorporating communication efforts as a core element of climate strategies, and linking these actions to well-being outcomes, could also significantly increase policy acceptability. A number of authorities (e.g. Brussels, see below) are taking key steps in this direction.

Box 2.2. Stories matter: shaping car-dependent cities

Stories, and narratives more broadly, shape reality. Narratives are sets of stories, which include and exclude certain things. Reality, and what people find acceptable or unthinkable, greatly depend on which narratives dominate. This box provides an example of communication efforts that have contributed to a dominant car-centric narrative. The significant resources invested in advertisement reinforce this narrative.1 Efforts to counter the car-centric narrative, although less funded, are also numerous. Examples of such efforts are provided in the next box.

A communication campaign for car-centric cities

“A hundred years ago, if you were a pedestrian, crossing the street was simple: You walked across it. Today, if there is traffic in the area and you want to follow the law, you need to find a crosswalk. And if there’s a traffic light, you need to wait for it to change to green… To most people, this seems part of the basic nature of roads. But it’s actually the result of an aggressive, forgotten 1920s campaign led by auto groups and manufacturers that redefined who owned the city streets.” (Stromberg, 2015[14])

Mental models are highly dependent on the stories people have been exposed to (Saltmarshe, 2018[15]), which are, in turn, subject to, to a great extent, political economy factors and power dynamics within systems. The in-depth analysis of these factors (e.g. the influence of the automobile industry in shaping the transport system) is beyond the scope of this report, but is an interesting area for future research.2

The mass introduction of cars to cities was a disruptive change for which advertisement played a significant role (Freund and Martin, 1993[16]; Stromberg, 2015[14]). Cars were, not always widely accepted by the public. Before the mass introduction of cars, streets functioned like parks or malls, in which people could move carelessly (Dukes, 2013[17]). As Norton (2011[18]) explains, the public considered it to be the driver’s responsibility to pay attention, not the pedestrian’s, and the public response to the skyrocketing number of road fatalities after the introduction of cars was outrage. Cars were considered to be violent intruders.

This idea has changed radically, towards the idea that streets are for cars. Pedestrians became the intruders and the ones that need to pay attention (or get blamed if they are hit by a car). This idea persists today. Indeed, if a child is hit by a car, the first thing that likely comes to mind is that the parents are irresponsible. There is also a general perception that pedestrian deaths caused by vehicles, while tragic, are inevitable. For example, in the United States, 17 pedestrians – mainly from low-income, black and Latino neighbourhoods - were killed every day in 2018. That is one person having chosen to walk on a street killed every 90 minutes (Moran, 2021[19]). Unfortunately, these deaths do not receive the same media coverage, or congressional attention, as other tragedies like mass shootings.

Since the 1920s, the automobile industry has been dedicating significant resources to communication campaigns to increase the public’s acceptability and desirability of cars, which has, as Norton (2011[18]) demonstrates, reshaped cities and mainstreamed a number of deeply engrained ideas in society. Through such communication efforts to individuals and governments alike, the auto industry has been able to convey the message that vehicles are essential to improving well-being (Freund and Martin, 1993[16]). The car has become a symbol of freedom, social status and power, and opposition to the car is perceived as a direct threat to basic needs such as freedom and safety (Gössling, 2020[20]).

Norton (2011[18]) identifies the “jaywalking” campaign as a turning point. The campaign managed to redefine “what streets are for” and to normalise the idea that pedestrians did not have the right to walk freely on streets. This campaign is an interesting example of how framing and communication efforts can change people’s perception of reality, to accept – and even fiercely support – what previously was unacceptable or unthinkable. The term “jaywalker” was a pejorative word used to define people not knowing how to conduct themselves in a city (Norton, 2007[21]). The term aimed to ridicule people not crossing on the recently installed pedestrian crossings and helped redefine who the street belonged to, as well as who is to blame in the case of a road fatality (e.g. jaywalkers were pictured as threatening public safety).

“The ridicule of their fellow citizens is far more effective than any other means which might be adopted”. (Norton, 2007[21])

This quote, from one of the heads of the pro-automobile coalition Motordom, highlights the importance given to communication – and in particular to the technique of shaming – to switch the public’s perception on what streets were for, and whether it was the vehicle’s or the pedestrian’s “recklessness” to blame in case of a road fatality. .Before the 1920s, people considered cars to be intruders. By the 1930s, they considered pedestrians (“jaywalkers”) as being in the way of cars (Norton, 2007[21]); and since then, streets have belonged to cars.

Changing mental models and mainstreaming the idea that streets are for cars significantly influenced the shape of transport and urban systems (see first 3 panels in Figure 2.7).

Figure 2.7. A short history of traffic engineering

1. Zenith Media (2019[23]) estimates advertising expenditure by the automotive industry at USD 35.5 billion in 14 key markets in 2018, with the United States accounting for half of such expenditure (USD 18 billion).

2. For an overview of the key political-economic factors underlying car dependence, see Mattioli et al. (2020[24]).

Box 2.3. Stories matter: towards car independency

“Our cities do not need driver-less cars. Instead, they desperately need more car-less drivers!”
Marco Te Brömmelstroet

Communication efforts towards car-independent territories have the potential to change the narrative again, towards one more conducive to delivering sustainable transport systems. Examples of such efforts are multiple, from governments to non-governmental organisations and civil society movements.

Bruxelles Mobilité, for example, launched a communication campaign around walking (Bruxelles Mobilité, 2021[25]). The campaign uses humour and ridicule to convey the practicality of walking by presenting it as a high-tech technology (making reference to the “technological solutionism” discourse explained above). Similarly, Bike is Best conveys the message that bikes are the best tools for short journeys, by making an analogy with overdimensioned tools for other uses (BikeIsBest, 2021[26]). Possible, a UK charity, compiles stories of traffic reduction measures and allow users to “explore a world of Car Free Cities” for change towards people-friendly, clean air cities (Possible, 2021[27]) (Possible, 2021[28]).

The global campaign “Vision Zero” is another example of an effort for changing the narrative, in this case from seeing traffic fatalities as inevitable externalities of transport systems towards the idea that “no one should be killed or seriously injured from using the road network” (Towards Zero Foundation, n.d.[29]). This leads to the idea of “The Safe System”, a design approach viewing human life and health as “the first and foremost consideration when designing a road network”. In 2015, Mexico City committed to Vision Zero and reduced traffic fatalities by 18% in the first two years. The narrative change around traffic fatalities that the campaign fostered was identified as key to its success (Ballesteros, 2018[30]; Vision Zero Network, n.d.[31]). The case of Superblocks (see Section 3.2.2) is another example of how important these communications efforts are for policy acceptability and implementation.

The Journée sans voiture (day without cars) organised once a year in Paris is a way for people to experiment using the space allocated to roads for different uses (Ville de Paris, 2021[32]). Such events, in particular if organised more frequently (e.g. once a month), could increase the acceptability of policies towards car-independent systems. La Rue est à Nous and Parking Day are examples of citizen-led campaigns aiming to build a collective imaginary of cities with less cars. These campaigns shed light on how urban space could be used differently, and, in the case of La Rue est à Nous, on the health benefits arising from improved air quality and physical activity from active modes, in particular for children (La Rue est à Nous, 2021[33]; Parking Day, n.d.[34]). Scholars such as Marco Te Brömmelstroet, from Utretch and Amsterdam Universities, and artists such as Jan Kamensky, are also making active communication efforts on social media (e.g. LinkedIn), via online courses, creative videos, video repositories and talks, to overcome the car-centric story for cities. See, for example, Te Brömmelstroet (2020[35]; 2020[36]) and (Kamensky, 2021[37]).

A mobility-centred mental model, and the mobility-centred policies resulting from it, is problematic for many reasons. First, it disregards the importance of creating proximity for ensuring access (this is referred to as the “proximity blind spot” in the remainder of this report). Many of the decisions leading to the three dynamics behind car dependency would not have been an option if policies were not “proximity blind”. Second, it reduces the scope and effectiveness of climate strategies in the sector. The rest of this section is dedicated to discussing these two consequences in detail.

Proximity-blind policies

As mentioned above, a mindset focused on mobility leads to proximity-blind policies. Mobility is seen as the means to contribute to well-being, disregarding the importance of proximity. Mobility is, however, a bad proxy (or performance indicator) for the contribution of transport systems to well‑being (Silva and Larson, 2018[38]; ITF, 2019[39]) (Box 2.4). As explained in Section 2.1, people’s well-being does not ultimately depend on how much and how far they can travel (i.e. increased mobility). Rather, it depends on the possibility to access places with ease, including by not having to travel long distances (or to travel at all).

Box 2.4. Mobility is a misleading proxy for well-being

Mobility is a misleading proxy for the transport system’s contribution to well‑being. Fist, increasing mobility may be a symptom of deteriorating accessibility (ITF, 2019[39]). Total mobility can grow when people and places of interest (e.g. schools, shops, hospitals, gardens, etc.) are poorly connected, and when connections by active and shared transport modes are limited. For example, mobility increases if children cannot go to school by foot or bike due to safety concerns, and have to be driven. Mobility also increases when proximity to shops decreases (e.g. local shops close) and people need to drive to meet their basic needs. Second, growing mobility may hide a widening accessibility gap between population groups. As motorised private vehicles become the most attractive or only way to get to places (as explained in Chapter 3), access to opportunities may be reduced for less affluent households,* increasing inequality and reducing their well-being.

A number of indicators are used to measure mobility or physical movement, reflecting either the movement of vehicles or of people. As the ITF highlights (2017[40]) “[b]y narrowing down the problem to maximising physical movement, both [types of indicators] fail to provide accurate information about changes in access to goods, services, activities and destinations. Consequently, the importance of non-motorised modes, land-use decisions, mobility substitutes (e.g. home office, delivery services), etc. are overlooked”. For example, when vehicle-kilometres or other indicators focused on traffic are measured, the value of public transport is reduced, as these indicators do not account for public transport’s high load factors (passengers per kilometre travelled), which indicators such as passenger-kilometres could capture. The passenger-kilometres indicator, however, poorly reflects the value of active modes and many shared services (e.g. micro-mobility and e-bikes), as these are not high‑occupancy services. Measuring the number of trips could better reflect, to a certain extent, the value of non-motorised modes; however, measuring the number of trips still falls into the trap that “more [mobility] is better”, hiding, for instance, the fact that people could be better off if they could meet several needs in one single trip.

As explained in Section 2.1, accessibility, or “the opportunity of individuals to participate in activities” (ITF, 2017[40]), is a better proxy for assessing the transport system’s contribution to people’s well‑being. Measuring accessibility directly would therefore better inform decisions. Accessibility is more complex to measure than mobility because it depends on both mobility and proximity, and on various factors such as land use and transport availability. A number of indicators exist though. The most common (and simplest forms) are contour-based accessibility measures. Contour-based indicators measure the number of opportunities/services/facilities (e.g. jobs, green spaces, transport stations) which can be reached within a given travel time, distance or cost; or the time/cost (average) required to gain access to a fixed number of opportunities/services/facilities from different locations (ITF, 2017[40]). Because accessibility needs to be delivered sustainably and equitably, this type of indicator should ideally be calculated for different modes of transport and for different locations and population groups.

For further information on accessibility indicators (contour and others) and their use for improving planning and appraisal, see ITF (2019[39]).

* While less affluent households may travel less due to affordability issues, those who can afford to use a private vehicle drive more often and longer distances. Overall mobility can therefore increase.

Transport systems, thus, contribute to people’s well-being when they enhance accessibility. Accessibility is the interaction of mobility and proximity (Silva and Larson, 2018[38]) (Figure 2.8). Because trade-offs exist between space used for mobility and space used for other purposes (e.g. commercial or leisure areas, or housing), delivering accessibility sustainably requires striking a balance between facilitating mobility and creating proximity.

Figure 2.8. Accessibility, mobility and proximity

Policies focused on mobility rather than accessibility ignore the trade-off between mobility and proximity. This “proximity blind spot” explains, to a great extent, why policies have allocated a high – arguably excessive (Crozet, 2019[41]) – share of public space to fast, yet space-intensive,17 means of transport, such as private cars. This comes at the expense of dedicated space for sustainable, cost18- and space-efficient modes, and for creating proximity. For example, inner space in cities that has been prioritised for roads has often contributed to pushing other uses (e.g. housing) to the fringes, promoting urban sprawl (see Section 4.1 for a detailed description of the dynamic).

Overall, proximity-blind policies lead to systems in which people need to travel further distances to meet their needs. In such systems, the car is often the most convenient or only available option, thus people “choose” to drive for the bulk of their trips (left panel of Figure 2.1).

Proximity-blind policies compensate for the lack of proximity with yet more mobility, locking systems into a vicious cycle of car dependency, high emissions, and low and unequal accessibility.

Decoupling emissions from mobility

Another important consequence of mobility-oriented policy and mind-sets is that climate strategies have focused on decoupling emissions from growing mobility, which is assumed to be independent from the system and unquestionably linked to well-being, prosperity and freedom. In other words, climate action has concentrated on decarbonising the existing high-mobility and car-dependent (but low-proximity and limited accessibility) system.

A focus on decoupling strategies has also been reinforced by approaching policy-making through an analytical, rather than a systemic logic. When taking an analytical approach, the analyst identifies the part in the system causing the undesired result, and looks for a solution to such cause. Since most emissions come from combustion motorised vehicles, these are, from an analytical point of view, identified as the part or element in the system to be optimised or improved (i.e. as the problem); while ignoring the systems’ functioning that leads, in the case of transport, to an increase in the number of vehicles and traffic (see more on the difference between analytic and systemic mind-sets in section 2.2.2).

A focus on decoupling high/growing mobility from emissions has resulted in an overriding emphasis on improving or replacing combustion engine (especially private) vehicles which is considered to be the main challenge for attaining low emissions. Decoupling strategies, thus, improve vehicle energy efficiency and push for the switch to engines powered by lower carbon energy sources (e.g. EVs), leading to pathways highly dependent on technological change to optimise an element in the system. Meanwhile, efforts to reduce the number of vehicles, distances travelled, car use and more generally growing mobility are perceived as going against people’s freedom and well-being. If undertaken, such efforts are kept at the margin of climate action. They are often considered to be something that can help, but only an option for very specific places (e.g. city centres of large metropoles) and/or for very specific people (e.g. those who already like to cycle), rather than as core actions to redesign the system and reverse the dynamics behind car-dependency.

Decoupling strategies are unfit to achieve net-zero targets on time. By focusing on decoupling growing/high mobility from emissions, decoupling strategies miss the opportunity to reduce emissions by avoiding unnecessary trips and long distances, and by enabling the conditions for triggering a significant modal shift from more to less sustainable modes. By keeping car dependency intact, traffic volumes continue to increase, and it is therefore not surprising to see that emissions reductions from decoupling efforts, e.g. from vehicle electrification, have been ineffective in most countries. As Lamb et al. observe, “while the electrification of road transport holds much promise, its impact has been hardly visible in the period up to 2018, and looking forward it is in danger of being offset by growing levels of travel activity and countervailing trends such as increasing vehicle size and weight” (Lamb et al., 2021[42]). This is similar to decoupling efforts at the economy level being offset by economic growth”19 (Lamb et al., 2021[42]). ODYSSEE-MURE (2020[43]) estimates the main drivers of energy consumption (used here as a proxy for emissions) in the European Union (EU) and its member states. They find that the increase of energy consumption in the EU’s transport sector was mainly driven by an increase of activity (+80.3 million tonnes of oil equivalent [Mtoe]). While energy savings simultaneously reduced energy consumption (‑50.4 Mtoe), these reductions could not keep up with the increases driven by the increased activity. Thus, climate strategies focused on a decoupling logic “swim against the current”; and in fact, there are also important rebound effects from improvements in vehicle performance (see Chapter 6) that are hardly ever reflected in appraisal or policy prioritisation exercises. As a result estimated reductions from vehicle technology improvements are often overstated, while the role of policies with the potential to redesign the system (which can limit rebound effects) is underestimated.

Modelling of future scenarios also suggests that the level of emissions reductions that decoupling strategies can achieve is, overall, insufficient to reach net-zero goals at the pace needed (Buckle et al., 2020[44]). For instance, the new NZE2050 case developed by the International Energy Agency20 confirms that triggering behavioural change (including for the transport sector) will be indispensable for meeting stringent mitigation targets. The NZE2050 sets out further measures (in addition to decoupling measures) that would be required to reach carbon neutrality by 2050 instead of 2070 (which the previous Sustainable Development Scenario [SDS] was in line with). It concludes that “behaviour changes are… essential to achieve the pace and scale of emissions reductions in the NZE2050, and they account for around 30% of the difference in emissions between the SDS and NZE2050 in 2030”.

Fulton, Mason and Meroux (2017[45]) and Fulton (2018[46])21 develop world urban transport scenarios and find that emissions can be reduced by about 44% (in 2050, relative to 2015) in a scenario focused on improving vehicle technology (i.e. decoupling strategies). This contrasts with a reduction of 76% in a scenario where technological improvements are embedded in a wider policy package promoting the use of active modes and shared/high-occupancy vehicles, including important changes in urban planning (i.e. systems redesign) (Figure 2.9). Importantly, the scenario focused on technological improvements (2R) is a high mobility scenario since high private vehicle use remains. Private vehicle use and passenger-kilometres even increase by 8% (both) compared to the business-as-usual (BAU) scenario, as the assumed accelerated shift towards automated vehicles exacerbates the overuse of private vehicles. In contrast, the scenario that depicts a shift away from car dependency would yield almost 50% less vehicle kilometres and 8% less passenger kilometres than the BAU scenario by 205022 via the increase in shared vehicle trips and greater public transport and non-motorised travel (as well as changes in land use). This would allow achieving much greater reductions in energy use and emissions, from both petroleum use and electricity; as modelling does not assume a complete decarbonisation of electricity; and despite the increased uptake of electrification assumed in both scenarios, the share of internal combustion engine vehicles continues to be important during the studied period. The latter is important, as even if the decarbonisation of electricity is achieved, lower demand will still do the “heavy lifting” early on (Brand et al., 2020[47]), as the complete electrification of the fleet is unlikely to take place in the first half of this century (even if the pace picks up) (Fulton, Mason and Meroux, 2017[45]). Interestingly, the cost of the scenario that results in the most emissions reductions (3R) is less than the cost of the scenario focused on improvements in vehicle technology (2R). Cost savings emerge mainly after 2030 and arise from reduced costs of vehicle purchase (as fewer vehicles are purchased), energy savings, and reduced road and parking infrastructure costs. Costs are reduced by 40% compared to the BAU scenario, leading to over USD 5 trillion in savings per year. When comparing the costs of the 2R to the BAU scenario, the authors find that induced demand and more costly vehicles (e.g. bigger vehicles) mostly offset the cost savings from lower cost EVs and autonomous vehicles. Both cost savings and emissions reductions (see Lamb et al. (2021[42])) can be offset by dynamics such as induced demand, shedding light on the importance of designing climate strategies with the potential to reverse such dynamics.

Figure 2.9. World urban transport scenario: Results for decoupling and systems redesign policies

The ITF (2021[5]) reaches similar conclusions, showing two scenarios yielding an 87% and a 73% reduction in worldwide urban and non-urban passenger transport emissions by 2050 (relative to 2015 levels). It shows that this could be possible if technological change is embedded into the aim of “reshaping” transport systems23 (bringing -73% reduction). Building on the recovery to accelerate transformational change (Reshape + scenario) could further reduce emissions in the short run (achieving -87% reduction in 2050). The Reshape+ scenario also yields much lower total travel demand (passenger-kilometres) than the BAU scenario, and this is key to drastically cutting down emissions. This reduction of total travel demand, in line with the claims made in this report, is not at the expense of well-being, as accessibility by both car and public transport, and the relative competitiveness of public transport vis‑à‑vis the car are improved in this scenario (ITF, 2021[5]).

Decoupling strategies also leave potential synergies untapped, and create significant (and evitable) trade-offs between climate mitigation, other environmental goals and wider well-being outcomes. This leads to missed opportunities to increase the cost-effectiveness and public acceptability of climate policies.

Synergies between climate action and other challenges that need to be solved within the same time frame (e.g. the Sustainable Development Goals, the 2030 Agenda, etc.) can increase the cost‑efficiency, cost-effectiveness and acceptability of policies. Increasing policy acceptability is fundamental for achieving net-zero goals: while potentially cost-efficient and effective in theory, unimplemented policies – or policies whose ambition needs to be lowered due to public resistance – are ineffective. Examples of untapped synergies are multiple. For instance, the replacement of combustion cars with EVs improves air quality, and thus health. But it fails to unleash the (mental and physical) health benefits that can come from the use of active modes such as walking and cycling (modes which would also improve air quality). Decoupling strategies also fail to align the climate, road safety, equity, gender equality24 and social inclusion agendas. By isolating climate and other problems caused by car-dependent systems, decoupling strategies are part of policy frameworks that lead to sub-optimal solutions and create continuous trade-offs. For instance policies aiming to reduce road fatalities in car-dependent systems often use the promotion of pedestrian overbridges or subways to address what is considered to be an externality of (inevitable) car-dependent systems. Such infrastructure can increase safety to a certain extent, but it importantly reduces the attractiveness of walking and cycling, as going up and down stairs increases the time and effort for people choosing such means. It thus contributes to the erosion of sustainable modes (a dynamic discussed in detail in Chapter 5), reducing the scope for modal shift, while also importantly limiting accessibility for non-car users (Anciaes and Jones, 2018[48]). Furthermore, it has been observed that the increased time and effort for pedestrians to go up and down stairs results in them crossing at other (highly unsafe) places rather than using the overbridges (Bhagat, Manoj Patel and Palak Shah, 2014[49]).

As shown by the examples above, by locking in car-dependent lifestyles, decoupling strategies can also perpetuate inequalities (Powell et al., 2021[50]): car dependency creates a vicious cycle where the gap between the possibility and ease to access opportunities (i.e. accessibility gap) between car and non-car owners increases. As higher shares of the population “opt” for a car, businesses locate in areas with good car access and poor public transport access, and authorities focus their efforts on accommodating new car use (Mattioli, 2013[51]). ITF (2021[5]) shows that policies focused on ensuring access to car use, which climate policies focused on decoupling do, can cause forced car ownership, in particular for lower income households living in areas with fewer alternative transport options.25 In these cases, private vehicles, and their associated costs, become the only way to satisfy people’s needs, locking them into car dependency and transport-related costs.

According to the ITF (2021[5]), equity issues are better served by policies ensuring “[a] right to carry out daily activities without needing a car”. Given the car-dependent nature of current systems, allowing for such a right requires redesigning transport and urban systems, and embedding efforts for improving vehicle technologies into wider, systemic, policy packages (see section 2.3 and chapters 3-5). Focusing climate action on redesigning systems to shift them away from car dependency opens the door to policies (such as street redesign) that can simultaneously reduce emissions, increase safety, encourage the use of active modes (which can improve health via better air quality and physical activity), and address equity and social exclusion (e.g. through the promotion of human interactions).26

Decoupling strategies, which importantly rely on the shift towards EVs also imply the replacement of a big (and growing) private vehicle fleet, and thus increasing the already unsustainable level of materials consumption (OECD, 2019[52]). As highlighted by Xu et al. (2020[53]), “[t]he success of the transition to electric vehicles will depend partly on whether the material supply can keep up with the growth of the sector in a sustainable way and without damaging the reputation of EV”. For example, the IEA estimates that total mineral consumption would need to quadruple over the next 20 years to meet net-zero goals by 2070 (IEA, 2021[54]). EVs and battery storage account for approximately half of such consumption (IEA, 2021[54]), which would need to be further accelerated if net-zero goals are to be met by 2050. In a recent study, Xu et al. (2020[53]) estimate the material demand that would be required to sustain light-duty EVs if their development was aligned with the IEA Stated Policy (STEP) and the SDS scenarios.27 They find that the increase in EVs in line with these scenarios would require a radical expansion of the global production capacity for lithium, cobalt and nickel; and most probably the discovery of new resources.28 Even if new resources were discovered in time, the environmental impacts associated with their extraction would necessarily increase (Swaminathen, 2020[55]; Katwala, 2018[56]). Environmental impacts from mineral extraction include land‑use change, water use and waste generation (IEA, 2021[54]). Land-use change directly affects ecosystems and people and can cause habitat loss for endangered species as well as the displacement of communities (Katwala, 2018[56]). Mining requires large volumes of water, which can cause water contamination from acid mine drainage, the disposal of tailings and wastewater discharge from the mining process (IEA, 2021[54]). Alongside these three major environmental challenges, the mining development process can result in air pollution, gaseous emissions and noise pollution, and may also have a number of social impacts (health and safety, human rights, etc.) (IEA, 2021[54]).

The replacement of increasing private vehicle fleets could also put pressure on the power sector. Global electricity demand from EVs is expected to increase from less than 100 terawatt hours (TWh) in 2019 to almost 1 000 TWh in 2030 (approximately 4% of global electricity consumption in 2019) according to the IEA’s SDS (IEA, 2020[57]). This requires additional power system infrastructure (plants, networks), which can have trade-offs with land-use and biodiversity (Gasparatos et al., 2017[58]). While EVs can be a great source of flexibility that can provide a broad range of services to the power system, facilitating the integration of variable renewable energy sources such as solar and wind, they can also increase total and peak demand (Gschwendtner, 2021[59]) and exacerbate stress on the power grid if charging from multiple users is not well co‑ordinated (e.g. simultaneous charging in the evening after coming home from work). In this respect, having a higher share of shared fleets (which are not incentivised by decoupling strategies) would most likely be conducive for grid integration, because these could support the early deployment of vehicle-to-grid (V2G) technologies29 by enabling more centralised infrastructure to serve many cars and thus installation and maintenance costs (Gschwendtner, 2021[59]). As discussed in chapter 6, even efforts to implement circular batteries will be very limited in a growing fleet scenario, and transitioning towards a system that can deliver better access with a smaller fleet would be needed for efforts to electrify vehicles to be more feasible, effective and truly sustainable.

Finally, by not dealing with car dependency, decoupling strategies fail to enable the conditions for other relevant policies, such as carbon prices, to also be more acceptable and effective. Pricing carbon is fundamental for steering sustainable choices. In car-dependent systems, these options are, however, not always available, or may not be safe or convenient enough to trigger people’s behavioural change. The effectiveness of pricing and other market-based mechanisms depends on the availability and attractiveness of sustainable options. For example, price elasticities are much lower when dense networks of public transport are not available (see Chapter 6). Carbon pricing acceptability will likely be low in a context in which low-income households are car dependent, for whom transport costs are already high and alternative modes of transport may not be available (Mattioli et al., 2020[24]; Handy, 2020[60]; OECD, 2019[61]). The Yellow Vests (Gilets Jaunes) movement in France is a concrete example of low policy acceptability, and thus low policy effectiveness, due (to an important extent) to the absence of enabling conditions.

Climate and transport strategies need to change radically, from a focus on decarbonising the current unsustainable-by-design system (left panel of Figure 2.1) towards enabling the conditions for sustainable-by-design systems (right panel of Figure 2.2). While there is an increasing willingness to reverse car dependency (ITF, 2021[5]), mobility- and decoupling-focused transport and climate strategies stand in the way of the transition towards sustainable transport and urban systems in most countries.

“Cleaner”, but still car-dependent, systems are not enough to achieve net-zero goals and simultaneously improve well-being. As argued by Systems Innovation (2021[62]), electric and autonomous vehicles “are tools, they are not a solution to systems-level dysfunctionalities”.

Achieving net-zero carbon goals will require moving beyond mobility and analytical mind-sets and decoupling-oriented climate strategies. A first step towards this shift is to envision the outcomes that sustainable-by-design systems should achieve, as described at the beginning of this section. The second step is to understand why current systems lead to unsustainable results, and identify what mental models or implicit assumptions shaped such systems, so as to question and revise them as needed. Once assumptions are in line with the observed systems’ functioning, and policy goals are informed by such understanding and set based on the vision defined in the first step, policy packages can be re-designed to accelerate the transition towards better systems for better lives.

The next section dives deep into what such policy packages could look like concretely; chapters 3-6 provide more detail.

2.3. Redesign systems by changing policy priorities

Climate strategies prioritising accessibility via the policies put forward in this report would be radically different from today’s strategies. The difference arises from the way the problem is defined.

As discussed before, by taking an analytical (or linear) approach, the analyst looks for a direct cause of emissions, and for a solution to that cause. In the surface transport sector, most emissions come from combustion motorised vehicles, which increase is seen as exogenous, and its cause, thus, is not analysed (see Section 3.1). From a mobility-centred perspective, the increase of traffic volume is also seen as the inevitable consequence of “progress” (see section 2.2.2). If the increase in the number of vehicles does not depend on the system’s functioning (i.e. is exogenous) and is inevitable (i.e. as a decrease would result in poorer life quality or less “progress”), then the type of vehicles in circulation are the problem, and the solution to reduce emissions is to electrify them or improve their fuel performance.

This is why, an analytical approach, coupled with a mobility-oriented perspective, constrains climate strategies to decoupling emissions from vehicle use. In transport jargon, such an approach and perspective push climate policies to place an overriding focus on “improve” effects.30 Section 2.2.2 explained why this focus is unfit to achieve net-zero targets.

This report takes a systemic approach and moves towards an accessibility-centred perspective. An accessibility-centred perspective sees the sustainable delivery of accessibility – rather than mobility – as the key desirable outcome of well-functioning transport systems. A systemic approach shows that recurrently high levels of emissions and poor, unequal and unsafe accessibility are the result of a system that is not working properly as a whole. The problem is no longer (just) the emissions performance of the vehicles in circulation, but the system’s functioning or dynamics leading to an increase in the number of vehicles and traffic. These dynamics depend, for example, on the way roads (and public space more broadly) are organised. The solution is thus no longer to (just) improve vehicles’ performance, but to improve the system’s functioning (briefly explained in section 2.2). To continue with the analogy, the focus is on changing the direction of the escalator, so that it helps us go faster, rather than slowing us down.

Because the system’s functioning is defined as the main problem to be tackled, and growing mobility is no longer seen as unquestionably linked to progress or well-being, climate strategies are, from a systemic and accessibility-centred perspective, no longer constrained to improving the type of vehicle (i.e. to decoupling emissions from increased vehicle use). Climate strategies can, instead, focus on reversing the dynamics that lead to car dependency and overuse and thus transition towards car independent systems.31

Reversing the dynamics that lead to car dependency and overuse can lead to transformational change (see Box 1.1) via systems redesign so that systems deliver high and quality (including safe) accessibility with low emissions. In other words, reversing these dynamics means changing the way the system functions, and thus its results: from induced demand to disappearing traffic (transformational change #1, see Chapter 3); from sprawl to proximity (transformational change #2, see Chapter 4); and from the erosion of active and shared modes to making these modes the fastest, most comfortable and safest modes, so that they become people’s first choice (transformational change #3, see Chapter 5).

Modelling suggests that climate strategies aimed at redesigning systems to deliver high accessibility and low emissions have a greater potential to reduce emissions than strategies limited to decoupling emissions from vehicle use (i.e. “improve” effects)32(see section 2.2.2). Climate strategies focused on improving the system’s functioning so that it delivers accessibility sustainably prioritise policies that set the conditions for avoiding unnecessary trips, by creating proximity, and for a shift towards sustainable transport modes, by reallocating public space, investment and technology to increase the attractiveness of such modes. Emission reductions via decoupling (i.e. improve effects) are also important in accessibility-oriented climate strategies, but they are part of a wider effort to improve systems, rather than embedded in systems that are unsustainable-by-design.

This report calls for a shift towards accessibility-oriented climate strategies centred on redesigning transport and urban systems so that these can, by design, foster accessibility sustainably. As explained in section 2.2, an accessibility-oriented perspective is fundamental because it sheds lights on the importance of achieving a balance between mobility and proximity. Creating proximity is crucial to reducing emissions, as proximity can “avoid” large distances and trips (e.g. through increasign the scope for trip chaining33) as well as to increase the attractiveness of sustainable modes such as walking and cycling, which are most competitive for short distance trips. As described above, accessibility-oriented climate strategies can also foster synergies and avoid trade-offs that decoupling strategies tend to exacerbate.

This section presents an overview of the policies with the potential to accelerate the transition towards car independency, further described in Chapters 3-7. This section can also be read as a summary of the results of the third step of the Well-being Lens process: redesign.

2.3.1. Transformational transport policies for net-zero systems by design

Policies focused on street redesign and management, spatial planning, and the development of multi-modal networks should be at the core of climate strategies. These policies can help strike a balance between mobility and proximity, and reverse the dynamics leading to car-dependent and high-emission transport and urban systems. Changes at the level of governance and monitoring frameworks are fundamental to facilitate the implementation of such policies, and innovation and technological change – both at the parts and the systems level – have a major role to play to increase the effectiveness of climate strategies.

Street redesign and policies for better managing public space (roads included) can lead to “disappearing traffic”, reversing the dynamic of “induced demand” (Cairns, Atkins and Goodwin, 2002[63]; Goodwin, Hass-Klau and Cairns, 2015[64]). Street redesign and public space management policies are based on the recognition that public space, currently mostly allocated to roads for cars, should accommodate multiple transport modes and uses beyond transport. A fairer allocation of public space (and in particular of roads) across transport modes and other uses is a condition for creating proximity, and for increasing the attractiveness of active and shared transport modes. Chapter 3 describes Superblocks as an example of radical street redesign, and discusses the potential of parking and road-pricing policies to contribute to ensuring that public space is designed and managed with the aim of enhancing accessibility. In a nutshell:

Barcelona’s Superblocks reorganise the city into polygons of approximately 400 m x 400 m. Inner roads are not closed to motorised vehicles, as these can enter the superblock but they cannot cross it (and have to stay within a speed limit of 10 km/h). Superblocks convert streets from a single function (i.e. dedicated to motorised vehicles) to spaces welcoming active modes and with multiple functions (e.g. recreational) (Ajuntament de Barcelona, 2014[65]). Superblocks are “low-cost urbanism” (López, Ortega and Pardo, 2020[66]) with the potential to transform the urban ecosystem and bring health, safety, social and environmental benefits (e.g. better air quality, emissions reductions) in the short run.
Parking policies, as used (or not used) today, incentivise car use by subsidising, underpricing or providing an oversupply of parking space. Parking policies could instead be designed to regulate and discourage car use (Kodransky and Hermann, 2011[67]), by putting a price on space scarcity. Higher parking prices, smart parking meters and zoning are some of the ways in which parking policies could play a regulatory role and help to reduce emissions and air pollution, and enhance well-being.
Road pricing can contribute to shifting away from a “predict and provide” approach towards an emphasis on better managing the use of existing roads. Road-pricing schemes have often been set with the aim of increasing traffic speeds and reducing delays for motorists, often considered to be congestion’s most important disutility (ITF, 2019[68]; van Dender, 2019[69]). Road-pricing schemes will, however, better deliver climate and well-being goals if they are designed with the aim of efficiently using road space.The most efficient road-pricing schemes from international experience are those that are distance-based and with differentiated prices (e.g. peak hours, vehicle’s emissions level, load factors). Road pricing can be a powerful tool if combined with street redesign and re-allocation in favour of sustainable modes.

Urban sprawl can be contained – and reversed – via spatial planning aimed at redesigning territories, supported by improved governance frameworks. Chapter 4 focuses on the changes needed in terms of governance and monitoring for effectively integrating transport and land-use planning,34 which is fundamental for sustainably redesigning territories. In the current situation, decisions on transport and urban planning, land‑use management, or housing (all fundamental from an accessibility lens) are not systematically integrated or co-ordinated across territories with metropolitan areas or regions. In a nutshell:

Metropolitan transport authorities have been found to be excellent institutional configurations for developing strategic planning for metropolitan areas and regions, striking a balance between place‑based local planning and ensuring coherence at the metropolitan level. Especially when embedded in larger metropolitan bodies with land-use planning competencies, metropolitan transport authorities can importantly contribute to integrated planning (see Chapter 4), which can facilitate territory redesign.
Planning, and decision making more broadly, (including by metropolitan transport authorities) needs to be guided by accessibility-oriented monitoring frameworks. Frameworks such as the 15‑minute city (see Chapter 4) can steer decisions towards sustainable urban restructuring (e.g. for urban renewal and new development). For example, the 15-minute framework guides decisions towards the creation of proximity by defining three radii accessible by foot and bike within which authorities need to ensure access to a certain number of services (Duany and Steuteville, 2021[70]).
Parking regulation and transport assessments for new developments, such as residential buildings and offices, have an impact on urban form. Revising regulation to move from minimum towards maximum parking standards and requiring developers to produce multi-modal, rather than traffic-oriented, transport assessments are both key actions to reverse sprawl and encourage compact development. These changes are also key to ensuring shifts towards sustainable modes (e.g. by guiding new developments in areas served by public transport) and facilitate the creation of proximity (e.g. by freeing parking space for other uses).

Redesigning urban space may be perceived as a slow or challenging process, which could only bring benefits in the long term. There are, however, numerous examples of rapid and successful changes (especially in terms of street redesign) that reap benefits in the short term, such as Superblocks and the numerous initiatives implemented during the COVID-19 pandemic (see Chapter 7). Changes in urban and territorial form are deeper and will be longer term changes. Examples in Chapter 4 show, however, that the redesign of large city areas could be achieved within the next 10 years, and that benefits from such redesign would be visible in the short-term (likely earlier than the benefits from widespread vehicle electrification, often perceived as being shorter-term efforts).

Policies fostering the development of multi-modal transport networks are fundamental to reverse the erosion of active and shared modes of transport. There are huge opportunities for enlarging the offer of collective, flexible and sustainable modes of transport by integrating new technologies and business models along policy frameworks that are conducive to making shared and active modes central. Necessary actions to accelerate the creation of multi-modal transport networks that can provide sustainable and quality options (see Chapter 5) include:

Strengthening public transport networks, including by increasing investment and improving the methodologies for determining public transport pricing and planning, e.g. to avoid the public transport low-cost, low-revenue, low-quality trap.
Integrating and mainstreaming on-demand and shared services such as e-bikes, other micro‑mobility options and micro-transit. This can be done via new technologies, “softer regulation” that promotes cooperation between government and service providers, and government subsidies in areas where micro-mobility or on-demand services can bring social and environmental benefits but may not be profitable for the private sector. Support to the development of new vehicles (e.g. innovative micro-mobility) and the expansion of services for multipurpose trips (e.g. cargo e-bikes, shared bikes and e-bikes with baby seats, kids’ bikes) could also contribute to making shared mobility more attractive. Mainstreaming on-demand and shared services can help unleash important mitigation potential and reduce strain and crowding on public transport, further increasing its attractiveness.

Importantly, the policies addressing the different dynamics can reinforce each other. The shift towards public space (Chapter 3) and territorial design (Chapter 4) that prioritise walking, cycling, micro‑mobility and shared modes, can greatly facilitate the development of multi-modal transport networks, making these modes more attractive (e.g. fast, safe, reliable, comfortable) than private individual vehicles. In turn, systems in which active, shared and high occupancy modes are the norm will require less cars, and can further liberate space (e.g. previously devoted to car parking and use), thus increasing the scope for street and whole-of-territories redesign, allowing for the creation of proximity between people and places (e.g. recreational space, markets, etc.) and for expanding the use of sustainable modes (see Chapter 5).

Policies aiming at systems redesign also have the potential to convert vicious circles into virtuous ones. While the dynamics described in section 2.2.1 reinforce each other resulting in higher traffic volumes and emissions, the dynamics that policies in this report can trigger – i.e. those leading to disappearing traffic, proximity, and a greater attractiveness of active and shared modes – reinforce each other, this time in a desired direction: that of sustainable accessibility. TfL (2018[71]) refers to this as the “virtuous circle of road danger reduction”. In Paris, for example, six out of ten people cycling in the city today were not doing so before policies reallocated road space to bike lanes during the COVID-19 pandemic (see Chapter 7). Such reallocation has resulted in an increase in the number of cyclists, which can lead to even more cyclists, since the more cyclists there are, the more people may consider cycling as a safe and convenient option.

Synergies between space reallocation and market-based mechanisms such as carbon pricing, fundamental for the transition towards sustainable systems, are particularly interesting. For example, evidence suggests that the impact of fuel prices on people’s choice is low when alternatives to car driving are not available; and that prices’ impact on people’s choice increases when public transport infrastructure is available (Avner, Rentschler and Hallegatte, 2014[72]), to which space reallocation can contribute to improving. Policies reallocating space away from car use and parking can also contribute to road safety goals, in particular if they build on “safe system” approaches (see Chapter 3). This is very different from a situation in which one problem is solved and another is exacerbated (or its resolution becomes more difficult). For example, as discussed above, pedestrian bridges reduce road fatalities, but they also reduce the attractiveness of active modes, rendering the transition towards low-emission systems more difficult.

2.3.2. The potential of systems innovation

Innovation has a major role to play in climate strategies that aim to reverse the dynamics underlying car dependency. This report calls for climate strategies that foster systems innovation to design sustainable systems.

Systems innovation is innovation aimed at transforming the systems’ functioning. Innovation efforts have, so far, mainly focused on technological change to improve parts, e.g. vehicle emissions. While important, placing an overriding focus on innovation at the vehicle level has been a barrier for innovation (including low-tech innovation) to address car dependency and achieve the transformational change needed to achieve net-zero goals. Innovation can, and given the scale of the challenge should, go beyond technology and parts.

New technologies can open up enormous opportunities for emission reductions if they are embedded in the aim of improving the system’s functioning (Systems Innovation, 2021[62]). For example, until a few decades ago, it was unimaginable to share vehicles (bikes, cars, etc.) and combine transport modes as efficiently as can be done today with GPS technologies and apps. This can significantly change transport systems’ functioning from one based on private car ownership to one where transport is seen as a service. The potential of such a change, in which transport systems become integrated networks of sustainable modes, has not yet been unlocked, partly as these technologies are not embedded in policy packages to transition towards car-independent systems. Furthermore, policy frameworks surrounding these technologies currently foster private and low occupancy rather than active, shared and high occupancy (e.g. translating into more ride-hailing than ride-sharing). In addition, there is limited financial support to expand the offer of vehicles and business models for shared active and micro‑mobility options.

Improving vehicles’ performance (i.e. innovation at the parts’ level) remains fundamental, and the effectiveness of such efforts can significantly be increased if they are embedded in a wider systemic transformation. For example, in systems fostering shared mobility (e.g. transport as a service), EVs can become more competitive via higher vehicle utilisation, turnover of the vehicle stock and cost-effectiveness of technological change (Taiebat and Xu, 2019[73]; IEA, 2020[57]; Goetz, n.d.[74]). Smaller fleets could also reduce resource use and the EVs’ pressure on the power sector in terms of energy demand (Kamiya and Teter, 2019[75]) (see Chapter 6).

While innovation at the parts’ level and systems innovation can be complementary, innovation efforts at the parts’ level currently tend to jeopardise systems innovation. For example, incentives to purchase EVs or more efficient vehicles reinforce car dependency by reducing the attractiveness of active modes or public transport (e.g. EVs allowed to use bus lanes), or simply by further locking-in space for car use (e.g. exceptions from parking fees), space which becomes unavailable for other uses (e.g. wide and safe bike lanes). To avoid these trade-offs, incentives for the purchase of EVs (including charging infrastructure) should be thought of as complementary to street redesign, spatial planning and policies fostering the development of multi-modal networks (see Section 6.2).

To facilitate policy priorisation towards systems innovation, evaluation methods behind policy comparisons and evaluation need to better reflect the limitations of opting for strategies and pathways that place an overriding focus on technological change to improve parts (e.g. adequately reflecting rebound effects and real-world, rather than laboratory, emissions). These also need to better reflect the multiple benefits of transformational policies (discussed in Chapters 1 and 3-5).

Innovating at the systems level can also increase the effectiveness of carbon pricing. Redesigning systems so that they allow people to avoid trips and choose active and shared modes (because these have become the fastest, safest and most convenient modes) can significantly increase the feasibility and effectiveness of ambitious carbon prices, as well as raise fewer distributional issues. Similar to incentives for cleaner vehicles, carbon pricing should be seen as one policy lever, rather than the policy lever, to achieve net-zero transport systems for better lives (IMF / OECD, 2021[76]) (Rosenbloom et al., 2020[77]).

2.3.3. Policies and dynamics in a nutshell

Table 2.1 summarizes the policies discussed in this report. It identifies policies that target each of the dynamics behind car-dependency (described in more detail in section 2.2 and chapters 3 to 5), and illustrates which of these policies are central in climate strategies following a decoupling (second column from the right) or a redesign (last column) logic. The table highlights that policies currently regarded as supporting (or optional) actions become central in strategies focused on reversing unsustainable systems dynamics. From this perspective, policies currently considered as core climate policies are in reality supporting policies, as, on their own, they do not directly target key dynamics at the source of car dependency and high emissions. Overall, policies in Table 2.1 are complementary: policies that redesign systems shift the direction towards sustainable systems, while market-based instruments and incentives and regulations towards vehicle improvements can accelerate the pace of such transition.

In addition to providing an overview of policies discussed in the report, Table 2.1 could be used as a checklist for governments to assess whether (and the extent to which) climate efforts are focused on redesigning systems or mainly on improving parts (potentially in unsustainable-by-design systems); i.e. whether policies target the key dynamics underlying unsustainable results. A key limitation of most policy assessments is that these describe the type of instruments used (e.g. market vs non-market instruments) without making the distinction between policies with the potential to trigger transformational or incremental change. Understanding this is important because ensuring that sufficient efforts go to redesign actions with the potential to trigger transformational change can significantly increase the likelihood of reaching the Paris Agreement goals while improving people’s lives (see Box 1.2).

	Disappearing traffic (reversing induced demand)	Proximity (reversing urban sprawl)	Active and shared modes become the norm (reversing erosion)	Hierarchisation of policies according to their capacity to trigger transformational change	At the centre of current climate strategies (decoupling strategies)	At the centre of climate strategies focused on redesigning systems
Market-based instruments / Incentives and regulations for vehicle improvement
Carbon prices1		X	X	Supporting	Yes	Yes
Taxes and other incentives to increase the uptake of cleaner vehicles (including electric vehicles)2				Supporting	Yes	Yes
Investment and support of charging infrastructure3				Supporting	Yes	Yes
Street redesign and improved management of public space⁴
Street redesign	X			Core	No	Yes
Parking policy	X			Core	No	Yes
Road pricing	X			Core	No	Yes
Spatial planning aimed at increasing proximity⁴
Parking standards for new developments		X		Core	No	Yes
Mainstreaming accessibility-based planning via governance and monitoring changes (e.g. 15‑minute city framework, metropolitan transport authorities)		X		Core	No	Yes
Multi-modal assessments for new developments		X		Core	No	Yes
Minimum (rather than maximum) parking requirements for new developments		X
Policies for developing multi-modal and sustainable networks⁴
Investments in public transport and better pricing methodologies			X	Core	No	Yes
Policies increasing the attractiveness of shared bicycles, micro-mobility (through direct support, regulation fostering cooperation and promoting innovation in these sectors)			X	Core	No	Yes
Policies to integrate micro-transit (e.g. on-demand vans) into public transport networks			X	Core	No	Yes

1. If coupled with other policies addressing systems dynamics.

2. Depending on the design, they could reinforce erosion dynamics (e.g. use of bus lanes by electric vehicles could increase bus congestion and reduce their attractiveness).

3. Depending on planning, can exacerbate induced demand (e.g. charging stations mostly for private car use).

4.The policies identified in this report as part of this broad category are not exhaustive

Note: The list of policies presented in this table is not comprehensive.

References

[65] Ajuntament de Barcelona (2014), Metropolitan Area Urban Mobility Plans (PMU).

[48] Anciaes, P. and P. Jones (2018), “Estimating preferences for different types of pedestrian crossing facilities”, Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 52, pp. 222-237, http://dx.doi.org/10.1016/j.trf.2017.11.025.

[72] Avner, P., J. Rentschler and S. Hallegatte (2014), “Carbon price efficiency: Lock-in and path dependence in urban forms and transport infrastructure”, Policy Research Working Paper, World Bank, Washington, DC, https://doi.org/10.1596/1813-9450-6941 (accessed on 29 March 2021).

[30] Ballesteros, L. (2018), “Changing culture to save lives: Mexico City’s bold commitment to Vision Zero”, press release, Vision Zero Network, https://visionzeronetwork.org/mexico-citys-bold-commitment-to-vision-zero (accessed on 10 August 2021).

[86] Bergerot, A., G. Comolet and T. Salez (2021), “Les usagers de la route paient-ils le juste prix de leurs circulations?”, No. 283, French Ministry of Economy, Finance and the Recovery, Paris, https://www.tresor.economie.gouv.fr/Articles/2021/04/27/les-usagers-de-la-route-paient-ils-le-juste-prix-de-leurs-circulations (accessed on 26 July 2021).

[49] Bhagat, P., E. Manoj Patel and E. Palak Shah (2014), “Pedestrian priority in urban area and usefulness towards community”, IJRET: International Journal of Research in Engineering and Technology, Vol. 3/1, pp. 2321-7308, http://dx.doi.org/10.15623/ijret.2014.0301088.

[26] BikeIsBest (2021), “The best tool for the job”, https://www.youtube.com/watch?v=V6ChTqII-Yk (accessed on 21 July 2021).

[47] Brand, C. et al. (2020), “Road to zero or road to nowhere? Disrupting transport and energy in a zero carbon world”, Energy Policy, Vol. 139, p. 111334, http://dx.doi.org/10.1016/j.enpol.2020.111334.

[25] Bruxelles Mobilité (2021), “Les pieds”, https://www.youtube.com/watch?v=EAkm773d7RQ (accessed on 1 July 2021).

[44] Buckle, S. et al. (2020), “Addressing the COVID-19 and climate crises: Potential economic recovery pathways and their implications for climate change mitigation, NDCs and broader socio-economic goals”, OECD/IEA Climate Change Expert Group Papers, No. 2020/04, OECD Publishing, Paris, https://dx.doi.org/10.1787/50abd39c-en.

[63] Cairns, S., S. Atkins and P. Goodwin (2002), “Disappearing traffic? The story so far”, Municipal Engineer, Vol. 151/1, pp. 13-22, http://dx.doi.org/10.1680/muen.151.1.13.38856.

[7] Chapman, R. (2019), “Managing environmental and energy transitions for regions and cities”, prepared for the Expert Meeting on Managing the Transition to a Climate-Neutral Economy for Regions and Cities", OECD, Paris, https://www.oecd.org/cfe/regionaldevelopment/Chapman-2019-Managing-Transition-Regions-Cities.pdf (accessed on 19 August 2020).

[22] Colville-Andersen, M. (2018), Copenhagenize: The Definitive Guide to Global Bicycle Urbanism, Island Press/Center for Resource Economics, http://dx.doi.org/10.5822/978-1-61091-939-5.

[41] Crozet, Y. (2019), “Cars and space consumption: Rethinking the regulation of urban mobility”, International Transport Forum Discussion Papers, No. 2020/13, OECD Publishing, Paris, https://doi.org/10.1787/8abaa384-en.

[70] Duany, A. and R. Steuteville (2021), “Defining the 15-minute city”, Public Square: A CNU Journal, https://www.cnu.org/publicsquare/2021/02/08/defining-15-minute-city (accessed on 8 March 2021).

[17] Dukes, J. (2013), “The modern Moloch”, 99% Invisible, https://99percentinvisible.org/episode/episode-76-the-modern-moloch (accessed on 30 June 2021).

[2] Ferreira, A., E. Beukers and M. Brömmelstroet (2012), “Accessibility is gold, mobility is not: A proposal for the improvement of Dutch transport-related cost-benefit analysis”, Environment and Planning B: Planning and Design, Vol. 39/4, pp. 683-697, http://dx.doi.org/10.1068/b38073.

[16] Freund, P. and G. Martin (1993), The Ecology of the Automobile, Black Rose Books, London, https://www.researchgate.net/publication/289117639_The_Ecology_of_the_Automobile (accessed on 24 June 2021).

[46] Fulton, L. (2018), “Three revolutions in urban passenger travel”, Joule, Vol. 2/4, pp. 575-578, http://dx.doi.org/10.1016/j.joule.2018.03.005.

[45] Fulton, L., J. Mason and D. Meroux (2017), Three Revolutions in Urban Transportation: How to Achieve the Full Potential of Vehicle Electrification, Automation, and Shared Mobility in Urban Transportation Systems Around the World by 2050, UC Davis and Institute for Transportation & Development Policy, https://merritt.cdlib.org/d/ark%253A%252F13030%252Fm52c3sbx/1/producer%252FSTEPS-2050.pdf.

[58] Gasparatos, A. et al. (2017), “Renewable energy and biodiversity: Implications for transitioning to a green economy”, Renewable and Sustainable Energy Reviews, Vol. 70, pp. 161-184, http://dx.doi.org/10.1016/j.rser.2016.08.030.

[74] Goetz, M. (n.d.), “Electric vehicle charging considerations for shared, automated fleets”, policy brief, UC Davis, Institute of Transportation Studies, https://3rev.ucdavis.edu/sites/g/files/dgvnsk6431/files/files/page/3R.EVSE_.final_UPDATED_Oct17.pdf.

[64] Goodwin, P., C. Hass-Klau and S. Cairns (2015), “Evidence on the effects of road capacity reduction on traffic levels”, Traffic Engineering & Control, Vol. 39/6, pp. 348-354.

[20] Gössling, S. (2020), “Why cities need to take road space from cars – and how this could be done”, Journal of Urban Design, Vol. 25/4, pp. 443-448, http://dx.doi.org/10.1080/13574809.2020.1727318.

[59] Gschwendtner, C. (2021), “Vehicle-to-grid (V2G) and car sharing: Joining forces to decarbonize electricity and transport?”, Energy Blog, ETHzürich, https://blogs.ethz.ch/energy/v2g-and-car-sharing-joining-forces (accessed on 10 August 2021).

[60] Handy, S. (2020), What California Gains from Reducing Car Dependence, National Center for Sustainable Transportation, http://dx.doi.org/10.7922/G25X276H.

[78] Harich, J. (2010), “Change resistance as the crux of the environmental sustainability problem”, System Dynamics Review, Vol. 26/1, pp. 35-72, http://dx.doi.org/10.1002/sdr.431.

[8] Hickel, J. et al. (2021), “Urgent need for post-growth climate mitigation scenarios”, Nature Energy, Vol. 6/8, pp. 766-768, http://dx.doi.org/10.1038/s41560-021-00884-9.

[84] Hinton, J. (2021), Relationship-to-Profit: A Theory of Business, Markets, and Profit for Social Ecological Economics, Thesis for Degree of Doctor of Philosophy in Sustainability Science and Economics, Stockholm University, http://dx.doi.org/10.13140/RG.2.2.31508.73603 (accessed on 5 July 2021).

[54] IEA (2021), The Role of Critical Minerals in Clean Energy Transitions, World Energy Outlook Special Report, International Energy Agency, Paris, https://www.iea.org/reports/the-role-of-critical-minerals-in-clean-energy-transitions.

[57] IEA (2020), Global EV Outlook 2020: Entering the Decade of Electric Drive, OECD Publishing, Paris, https://doi.org/10.1787/d394399e-en.

[82] IEA (2020), World Energy Outlook 2020, OECD Publishing, Paris, https://dx.doi.org/10.1787/557a761b-en.

[76] IMF / OECD (2021), Tax Policy and Climate Change: IMF/OECD Report for the G20 Finance Ministers and Central Bank Governors, April 2021, Italy, http://www.oecd.org/tax/tax-policy/imf-oecd-g20-report-tax-policy-and-climate-change.htm (accessed on 13 September 2021).

[81] IPCC (2014), AR5 Climate Change 2014: Mitigation of Climate Change, Intergovernmental Panel on Climate Change, Geneva, https://www.ipcc.ch/report/ar5/wg3 (accessed on 23 June 2021).

[5] ITF (2021), ITF Transport Outlook 2021, OECD Publishing, Paris, https://dx.doi.org/10.1787/16826a30-en.

[85] ITF (2021), “Reversing car dependency: Summary and conclusions”, ITF Roundtable Reports, No. 181, OECD Publishing, Paris, https://doi.org/10.1787/bebe3b6e-en.

[39] ITF (2019), “Improving transport planning and investment through the use of accessibility indicators”, International Transport Forum Policy Papers, No. 66, OECD Publishing, Paris, https://doi.org/10.1787/46ddbcae-en.

[68] ITF (2019), “The social impacts of road pricing: Summary and conclusions”, ITF Roundtable Reports, No. 170, OECD Publishing, Paris, https://doi.org/10.1787/d6d56d2d-en.

[89] ITF (2019), Transport Connectivity: A Gender Perspective, International Transport Forum, Paris, https://www.itf-oecd.org/transport-connectivity-gender-perspective (accessed on 27 August 2021).

[40] ITF (2017), Income Inequality, Social Inclusion and Mobility, ITF Roundtable Reports, No. 164, OECD Publishing, Paris, https://doi.org/10.1787/g2g7ae77-en.

[80] ITF (2015), ITF Transport Outlook 2015, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789282107782-en.

[9] Jones, P. et al. (2018), Urban Mobility: Preparing for the Future, Learning from the Past, CREATE, https://www.researchgate.net/publication/329168103_Urban_Mobility_Preparing_for_the_Future_Learning_from_the_Past (accessed on 16 March 2021).

[37] Kamensky, J. (2021), Jan Kamensky website, http://www.jan-kamensky.de/ (accessed on 20 September 2021).

[75] Kamiya, G. and J. Teter (2019), “Shared, automated… and electric?”, International Energy Agency, Paris, https://www.iea.org/commentaries/shared-automated-and-electric (accessed on 17 March 2021).

[56] Katwala, A. (2018), “The spiralling environmental cost of our lithium battery addiction”, WIRED, https://www.wired.co.uk/article/lithium-batteries-environment-impact (accessed on 16 March 2021).

[67] Kodransky, M. and G. Hermann (2011), Europe’s Parking U-Turn: From Accommodation to Regulation, Institute for Transportation & Development Policy, New York, NY, https://itdpdotorg.wpengine.com/wp-content/uploads/2014/07/Europes_Parking_U-Turn_ITDP.pdf.

[33] La Rue est à Nous (2021), “La rue est à nous”, website, https://larueestanous.fr (accessed on 1 July 2021).

[10] Lamb, W. et al. (2020), “Discourses of climate delay”, Global Sustainability, Vol. 3, http://dx.doi.org/10.1017/SUS.2020.13.

[42] Lamb, W. et al. (2021), “A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018”, Environmental Research Letters, Vol. 16/7, p. 073005, http://dx.doi.org/10.1088/1748-9326/abee4e.

[6] Litman, T. (2021), Socially Optimal Transport Prices and Markets Principles, Strategies and Impacts, Victoria Transport Policy Institute, Victoria, British Columbia, https://www.vtpi.org/sotpm.pdf.

[66] López, I., J. Ortega and M. Pardo (2020), “Mobility infrastructures in cities and climate change: An analysis through the superblocks in Barcelona”, Atmosphere, Vol. 11/4, p. 410, http://dx.doi.org/10.3390/ATMOS11040410.

[51] Mattioli, G. (2013), “Car dependence, sustainability and the transport policy stalemate: The potential trade-offs between intra- and inter-generational equity”, The International Journal of Sustainability Policy and Practice, Vol. 8/1, pp. 45-57, http://dx.doi.org/10.18848/2325-1166/cgp/v08i01/55416.

[24] Mattioli, G. et al. (2020), “The political economy of car dependence: A systems of provision approach”, Energy Research & Social Science 66, p. 101486, http://dx.doi.org/10.1016/j.erss.2020.101486.

[79] Meadows, D. (1999), Leverage Points: Places to Intervene in a System, The Sustainability Institute, Hartland, VT, https://donellameadows.org/wp-content/userfiles/Leverage_Points.pdf (accessed on 16 June 2021).

[19] Moran, M. (2021), “Right of way: Race, class, and the silent epidemic of pedestrian deaths in America”, Journal of the American Planning Association, Vol. 87/2, pp. 302-303, http://dx.doi.org/10.1080/01944363.2021.1885273.

[83] National Institute on Aging (2019), “Social isolation, loneliness in older people pose health risks”, web page, https://www.nia.nih.gov/news/social-isolation-loneliness-older-people-pose-health-risks (accessed on 6 July 2021).

[18] Norton, P. (2011), Fighting Traffic: The Dawn of the Motor Age in the American City, The MIT Press, https://mitpress.mit.edu/books/fighting-traffic (accessed on 19 March 2021).

[21] Norton, P. (2007), “Street rivals: Jaywalking and the invention of the motor age street”, Technology and Culture, Vol. 48/2, pp. 331-359, http://dx.doi.org/10.1353/tech.2007.0085.

[43] ODYSSEE-MURE (2020), European Union Energy Profile: Energy Efficiency Trends and Policies, European Union, https://www.odyssee-mure.eu/publications/efficiency-trends-policies-profiles/european-union.html (accessed on 17 March 2021).

[61] OECD (2019), Accelerating Climate Action: Refocusing Policies through a Well-being Lens – Highlights, OECD Publishing, Paris, https://www.oecd.org/environment/accelerating-climate-action-2f4c8c9a-en.htm (accessed on 19 April 2020).

[1] OECD (2019), Accelerating Climate Action: Refocusing Policies through a Well-being Lens, OECD Publishing, Paris, https://dx.doi.org/10.1787/2f4c8c9a-en.

[52] OECD (2019), Global Material Resources Outlook to 2060: Economic Drivers and Environmental Consequences, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264307452-en.

[34] Parking Day (n.d.), “Parking Day”, website, http://www.parkingday.fr (accessed on 29 July 2021).

[28] Possible (2021), Car Free Stories: The irresistible rise of people-friendly, clean air cities, http://www.newweather.org (accessed on 22 September 2021).

[27] Possible (2021), Explore a world of Car Free Cities, https://wearepossible.github.io/carfreestories/ (accessed on 22 September 2021).

[50] Powell, S. et al. (2021), Net Zero Transport: The Role of Spatial Planning and Place-based Solutions, Royal Town Planning Institute, https://www.rtpi.org.uk/media/7600/rtpi-net-zero-transport-january-2021.pdf.

[77] Rosenbloom, D. et al. (2020), “Opinion: Why carbon pricing is not sufficient to mitigate climate change – and how “sustainability transition policy” can help”, Proceedings of the National Academy of Sciences, Vol. 117/16, pp. 8664-8668, http://dx.doi.org/10.1073/pnas.2004093117.

[15] Saltmarshe, E. (2018), “Using story to change systems”, Stanford Social Innovation Review, https://ssir.org/articles/entry/using_story_to_change_systems (accessed on 19 March 2021).

[38] Silva, C. and A. Larson (2018), “Challenges for accessibility planning and research in the context of sustainable mobility”, International Transport Forum Discussion Papers, No. 2018/07, OECD Publishing, Paris, https://doi.org/10.1787/8e37f587-en.

[4] Sterman, J. (2000), Business Dynamics: Systems Thinking and Modeling for a Complex World, Irwin/McGraw-Hill, http://jsterman.scripts.mit.edu/Business_Dynamics.html (accessed on 8 March 2021).

[14] Stromberg, J. (2015), “The forgotten history of how automakers invented the crime of “jaywalking””, Vox, https://www.vox.com/2015/1/15/7551873/jaywalking-history (accessed on 10 March 2021).

[55] Swaminathen, A. (2020), “The massive environmental cost of batteries”, ONiO, https://www.onio.com/article/environmental-cost-of-batteries.html (accessed on 16 March 2021).

[62] Systems Innovation (2021), Mobility Systems Innovation, Systems Innovation, https://www.systemsinnovation.io/post/mobility-systems-innovation (accessed on 13 August 2021).

[3] Systems Innovation (2021), Reflexive Thinking Canvas, Systems Innovation, https://www.systemsinnovation.io/post/reflexive-thinking-canvas (accessed on 25 March 2021).

[12] Systems Innovation (2021), Systems Innovation Platform, website, https://www.systemsinnovation.io (accessed on 26 August 2021).

[13] Systems Innovation (2020), Complexity Theory: A Field Guide to Complex Systems, Systems Innovation, https://drive.google.com/file/d/1KV9z_ZrS33dD4gLAAplWrVdzzqBRppPP/view (accessed on 26 August 2021).

[73] Taiebat, M. and M. Xu (2019), “Synergies of four emerging technologies for accelerated adoption of electric vehicles: Shared mobility, wireless charging, vehicle-to-grid, and vehicle automation”, Journal of Cleaner Production, Vol. 230, pp. 794-797, http://dx.doi.org/10.1016/j.jclepro.2019.05.142.

[36] Te Brömmelstroet, M. (2020), “Library of cycling documentaries”, Urban Cycling Institute Blog, https://urbancyclinginstitute.com/library-of-cycling-documentaries (accessed on 3 August 2021).

[35] Te Brömmelstroet, M. (2020), “Library of cycling marketing”, Urban Cycling Institute Blog, https://urbancyclinginstitute.com/library-of-cycling-marketing (accessed on 3 August 2021).

[71] TfL (2018), Vision Zero Action Plan: Taking Forward the Mayor’s Transport Strategy, Transport for London, London, http://content.tfl.gov.uk/vision-zero-action-plan.pdf.

[29] Towards Zero Foundation (n.d.), “The Safe System”, web page, http://www.towardszerofoundation.org/thesafesystem (accessed on 10 August 2021).

[87] UK Department for Transport (2014), Value for Money Assessment for Cycling Grants, Department for Transport, London, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/348943/vfm-assessment-of-cycling-grants.pdf (accessed on 25 August 2021).

[69] van Dender, K. (2019), “Taxing vehicles, fuels, and road use: Opportunities for improving transport tax practice”, OECD Taxation Working Papers, No. 44, OECD Publishing, Paris, https://dx.doi.org/10.1787/e7f1d771-en.

[32] Ville de Paris (2021), Retour en images sur une journée sans voiture, https://www.paris.fr/pages/journee-sans-voiture-10107 (accessed on 22 September 2021).

[31] Vision Zero Network (n.d.), “What is the Vision Zero Network?”, web page, https://visionzeronetwork.org/about/vision-zero-network (accessed on 10 August 2021).

[88] World Economic Forum (2015), Top Ten Urban Innovations, prepared by the Global Agenda Council on the Future of Cities, World Economic Forum, Geneva, http://www3.weforum.org/docs/Top_10_Emerging_Urban_Innovations_report_2010_20.10.pdf.

[11] Wright, D. (ed.) (2008), Thinking in Systems, Chelsea Green Publishing, https://www.chelseagreen.com/product/thinking-in-systems.

[53] Xu, C. et al. (2020), “Future material demand for automotive lithium-based batteries”, Communications Materials, Vol. 1/1, pp. 1-10, http://dx.doi.org/10.1038/s43246-020-00095-x.

[23] Zenith Media (2019), Global Intelligence: Automotive Adspend Forecasts, Zenith Media, https://www.zenithmedia.com/wp-content/uploads/2019/03/Automotive-adspend-forecasts-2019-executive-summary.pdf (accessed on 13 August 2021).

Notes

← 1. Excluding water transport.

← 2. The report uses system dynamics, an approach for understanding the structure and dynamics of the system being analysed, and identifies high leverage points for fostering change. Leverage points are places to intervene in a system’s structure (Meadows, 1999[79]), and are based on the idea that “different types of solutions have different amounts of leverage to change the system” (Hinton, 2021[84]). Low leverage points refer to places where an action generates little change in the system’s behaviour and results. High leverage points are places where an action triggers important changes in the system’s behaviour and results. The closer to the root causes of a problem, the higher the leverage. For more, see Meadows (1999[79]).

← 3. Tools such as the Systems Improvement Process developed by Harich (2010[78]), which combines system dynamics and root cause analysis, could be particularly useful moving forward.

← 4. The terms well-functioning, sustainable and “healthy” systems are used interchangeably throughout this report.

← 5. Even when based on evidence, defining a well-functioning system and its desirable results are, to a great extent, normative choices, as what is “rational” or “right” is socially constructed (Hinton, 2021[84]).

← 6. The terms “private vehicles” and “private motorised vehicles” are used intercheangeably throughout this report. The term “cars” is often used as a shortcut for “private motorised vehicles” (i.e. including motorcycles and sport utility vehicles [SUVs]).

← 7. Accessibility being the interaction between mobility and proximity (see Annex A).

← 8. The “Well-being Lens” process is called as such since a first step towards better results is a decision‑making process based on a well-being – rather than a GDP-focused – lens. For the transport sector, this translates into a decision-making process based on accessibility, rather than mobility (see Section 2.2.2 for a discussion).

← 9. The results that a system produces depend on its cause-effect relationships, and in particular on its feedback loops (i.e. non-linear cause-effect relationships). Cause-effect relationships are often non-linear in complex systems (such as transport and urban systems), pointing to the need for a systemic approach, allowing the analyst to apprehend non-linear dynamics (Sterman, 2000[4]).

← 10. “A catchment area is the area from which a city, service or institution attracts a population that uses its services” (https://en.wikipedia.org/wiki/Catchment_area).

← 11. Single-use development (and logic) refers to a type of urban development in which each area focuses on a specific land use, e.g. suburbs tend to be residential neighbourhoods, places of interest are often concentrated in city centres or in specific areas (e.g. shopping malls), and offices are clustered in working districts.

← 12. In 2015, private vehicles accounted for half of total passenger-kilometres in cities, or 2.6 times more than by public transport (ITF, 2021[5]). Importantly, private vehicles have much lower load factors than public transport and thus passenger-kilometres travelled by private vehicles translate into a great amount of vehicle‑kilometres.

← 13. Evidence from world cities shows that the intensity with which incomes translate into car ownership vary greatly, and that policies and infrastructure play an important role in changing the extent to which these are correlated (Jones et al., 2018[9]; ITF, 2015[80]).

← 14. Which in turn greatly influences what is considered to be acceptable or “fair” in terms of policy decisions. The ITF (2021[85]) argues that how to provide an equal access to car use often dominates the policy-making discourse.

← 15. For example, a report by the French Treasury finds that in very dense urban areas, car drivers pay only 8% of the full cost of driving. If less dense and urban areas are considered, they cover on average one‑third of the costs (Bergerot, Comolet and Salez, 2021[86]).

← 16. Supported by measurement biases when evaluating policy options. See Chapter 6.

← 17. For example, on the space of a typical lane width (9-9.5 feet, 2.7-2.9 metres), an automobile can move approximately 2 000 people per hour, compared to 25 000 for heavy rail transport (Systems Innovation, 2021[62]).

← 18. The UK Department for Transport (2014[87]) finds that small investments encouraging safe environments for cyclists (e.g. separate bike lanes, bike-sharing schemes, etc.) can have payouts as large as 35:1. Improved safety significantly increases cycling adoption, which can lead to better health, air quality and faster commutes (cycling is, on average, 40% faster than private motorised transport during peak hours) (World Economic Forum, 2015[88]).

← 19. Figure 5.7 in IPCC (2014[81]) decomposes the evolution of fossil energy CO₂ between 1970 and 2010 as follows: changes in population (+87%), per capita GDP adjusted with purchasing power parity (PPP) (+103%), energy intensity in GDP (‑35%) and CO₂ intensity of energy (‑15%). The figure shows that emissions have grown in absolute terms, since the emissions reductions achieved through energy efficiency and decarbonisation efforts (decoupling strategies) have largely been offset by the continuous growth of global population and GDP. As highlighted in (OECD, 2019[1]) GDP is also a bad proxy for well-being.

← 20. The World Energy Outlook 2020 models a NZE2050 case that would reach net-zero CO₂ emissions by 2050 (IEA, 2020[82]).

← 21. The studies compare three global urban transport scenarios: 1) a BAU scenario; 2) 2Revolution (assuming automation and electrification), in which the policy focus is on improving technologies, with “shift” and “avoid” efforts being second-order priorities; and 3) 3Revolution (assuming automation, electrification and shared mobility), which puts an emphasis on “avoid” and “shift” effects, through urban planning policies for higher use of active modes and shared/high-occupancy vehicles, in addition to accelerated electrification of the fleet.

← 22. In this scenario, rapid automation of vehicles is also assumed, but these are mainly used as part of shared services.

← 23. The Reshape+ scenario builds on the recovery to accelerate the implementation of an array of “avoid”, “shift” with urban development and street redesign as central elements, while also incentivising technological change.

← 24. Women depend heavily on public transport, and utilise it more than men, often resulting in longer and more numerous trips (ITF, 2019[89]).

← 25. This was reflected in the decoupling-focused scenario discussed above, in which vehicle use and passenger-kilometres increase compared to the BAU scenario (Fulton, Mason and Meroux, 2017[45]).

← 26. Human interactions have been found to have a significant impact on people’s health. They contribute to longer lives, a higher sense of purpose and improved mood, with some research pointing to potentially improved cognitive function. It has been shown, especially among older people (who find themselves alone due to lack of transportation and mobility, retirement, or loss or separation from friends and family), that loneliness is linked to a higher risk of obesity, heart disease, anxiety, depression and Alzheimer’s disease, to name a few (National Institute on Aging, 2019[83]).

← 27. With the higher EV deployment featured in the Sustainable Development Scenario leading to 1.7-2 times higher material demand than in the STEP scenario.

← 28. This holds even without considering the potential demand from heavy duty vehicles and other sectors in the economy (Xu et al., 2020[53]).

← 29. V2G technology enables bidirectional power flows between EVs and the electricity grid (Gschwendtner, 2021[59]).

← 30. Climate policies in the transport sector have often been categorised into policies that: avoid unnecessary trips and long distances; shift trips from less to more sustainable modes; and improve the fuels and technologies of vehicles used for travel.

← 31. Car indepent systems are those in which a bulk of daily activities can be done without a car or a motorcycle. People only move from less emitting and space intensive modes (e.g. active, then micro-mobiliy and public transport/ micro-transit) to the more emitting and space intensive ones (e.g. cars or motorcycles), as they make less frequent trips. Car and motorcycle use is reserved for those those trips that can create more value than the costs they impose to society (i.e. reserved for specific purposes or circumstances); but they are not systematically the most convenient, nor the only, available option in most places.

← 32. The analysis could go further. Analysts may wish to explore what the political economy factors are, or which role the “rules of the game” (i.e. structure) of the economic system in which transport and urban systems are embedded play in defining such dynamics. While it is beyond the scope of this report, this is an area of interesting research for the future. The Systems Improvement Process developed by Harich (2010[78]), combining system dynamics with root cause analysis, is an interesting tool to explore the root causes of the dynamics described in this report. Likely, some of the root causes underlying the transport and urban system dynamics would also apply to other systems, such as electricity, housing or food systems, which would allow emissions to be addressed by multiple sectors simultaneously. The closer the analyst gets to the root cause of the problem, the higher the leverage point, and thus the effectiveness of the policy intervention. The closer the analyst gets to the root cause, however, the more the system’s resistance to change is likely to increase.

← 33. Trip chaining means grouping errands or activities into a single trip instead of returning home (or to a departure point) in between each one.

← 34. In addition to better co-ordination, it is fundamental to consult and co-ordinate with businesses and people living in the areas to be redesigned.

Featured topics

Agriculture and fisheries

Climate change

Development

Digital

Economy

Education and skills

Employment

Environment

Finance and investment

Governance

Health

Industry, business and entrepreneurship

Regional, rural and urban development

Science, technology and innovation

Society

Taxation

Trade

Energy

Nuclear energy

Transport

Featured topics

Agriculture and fisheries

Climate change

Development

Digital

Economy

Education and skills

Employment

Environment

Finance and investment

Governance

Health

Industry, business and entrepreneurship

Regional, rural and urban development

Science, technology and innovation

Society

Taxation

Trade

Energy

Nuclear energy

Transport

Countries A - C

Countries D - I

Countries J - M

Countries N - R

Countries S - T

Countries U - Z

Regional and global engagement

Countries

Countries A - C

Countries D - I

Countries J - M

Countries N - R

Countries S - T

Countries U - Z

Regional and global engagement

Publications

Publications

Featured publications

Data

Data

Featured data

News & Events

News & Events

Featured Events

About OECD

About

Engage with us

Work with us

Featured topics

Agriculture and fisheries

Climate change

Development

Digital

Economy

Education and skills

Employment

Environment

Finance and investment