Case Studies on Transport Policy 10 (2022) 2430–2442 Contents lists available at ScienceDirect Case Studies on Transport Policy journal homepage: www.elsevier.com/locate/cstp Exploring traffic evaporation: Findings from tactical urbanism interventions in Barcelona Samuel Nello-Deakin * Department of Geography, Autonomous University of Barcelona, Cerdanyola del Vallès, Spain A R T I C L E I N F O A B S T R A C T Keywords: Traffic evaporation – i.e. the opposite of induced traffic – is acknowledged as a well-established phenomenon Traffic evaporation which presents important implications for local urbanism and mobility policies, but there continue to be few Disappearing traffic academic studies which explore this issue in detail. This paper explores relative levels of traffic evaporation Road space following the implementation of multiple tactical urbanism interventions on 11 streets in Barcelona in the Traffic counts Tactical urbanism context of the COVID-19 pandemic. Based on the analysis of publicly available traffic count data, the findings Superblocks provide empirical support for the existence of significant levels of traffic evaporation following road space reduction. On average, traffic levels on streets with interventions diminished by − 14.8 % relative to streets in the rest of the city. In the wider vicinity of intervention streets, traffic levels also decreased slightly on average (− 0.9 %) compared to the rest of the city, except on immediately adjacent parallel streets to those affected by in­ terventions, which reported a small relative traffic increase (+0.7 %). Overall, these findings provide further support for street redesign policies which entail the reduction of road space for motor vehicles, and suggest that fears of traffic congestion following such schemes may often be unfounded. From a methodological standpoint, this study also offers a transparent method of evaluating traffic evaporation which could be replicated in future studies. 1. Introduction tactical interventions have increasingly been promoted by public au­ thorities themselves as a strategy to implement rapid changes in the In recent years, measures seeking to reallocate road space from public realm. Especially in the context of the COVID-19 pandemic, motorised traffic to active travel modes and other public space uses have tactical urbanism has become a common means of reallocating road gained widespread popularity worldwide. This “reclaiming” of car space space from motorised traffic to active travel, public transport, and public for other uses is increasingly seen as critical in encouraging an urban space use (Glaser and Krizek, 2021; Rojas-Rueda and Morales-Zamora, mobility transition towards low-carbon transportation and more live­ 2021). able cities (Petzer et al., 2021; Tennøy and Hagen, 2021). In particular, Nevertheless, and as the title of Janette Sadik-Khan’s account of her “tactical urbanism” – i.e. the speedy implementation of low-cost infra­ time as transport commissioner in New York suggests – Streetfight (Sadik- structural interventions in the public realm, often with a temporary or Khan and Solomonow, 2016) – tactical street interventions often lead to experimental character – has become a prominent strategy for city ad­ a vocal confrontation between their proponents and opponents, which ministrations to push forward measures which entail a reduction in the relies on partisan argumentation with little empirical support, and is amount of space allocated to motorised traffic (Lydon et al., 2015; Sadik- highly subject to media narratives. Indeed, street interventions which Khan and Solomonow, 2016). In this respect, tactical interventions can reduce the amount of space dedicated to motorised traffic typically face be understood as a form of street experiment which seek to recast streets entrenched resistance from a wide variety of actors, including business as spaces “for people” rather than “for traffic” (Bertolini, 2020). The and motor vehicle lobbies, residents, taxi drivers, and municipal traffic concept of tactical urbanism has its origins in small-scale unsanctioned engineers among others (Hickman and Huaylla Sallo, 2022). While such bottom-up interventions carried out by ordinary residents and neigh­ schemes are resisted on the assumption that they will increase traffic bourhood groups (Finn, 2014; Silva, 2016). In recent years, however, congestion, in reality it appears that they frequently lead to a reduction * Address: Edifici B, 08193 Bellaterra (Cerdanyola del Vallès), Spain. E-mail address: samuel.nello@uab.cat. https://doi.org/10.1016/j.cstp.2022.11.003 Received 4 July 2022; Received in revised form 18 October 2022; Accepted 2 November 2022 Available online 8 November 2022 2213-624X/© 2022 World Conference on Transport Research Society. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 in overall traffic levels, a phenomenon which has been named “dis­ inequalities (Hartman and Prytherch, 2015; Illich, 1974). appearing traffic” or “traffic evaporation” (Cairns et al., 2002; Nello- Despite being written two decades ago, a summary article by Cairns Deakin, 2020). Up to date, however, relatively few empirical studies et al. (2002) continues to provide the best available overview of the have sought to explore the issue of traffic evaporation in detail. As existing state of knowledge on traffic evaporation. Indeed, it is difficult argued by Nello-Deakin (2020), further empirical research on traffic to disagree with Melia and Calvert’s (2021) recent appraisal of the evaporation can play a critical role in helping policymakers justify road existing literature on the topic: “two observations stand out: the breadth space reallocation schemes in the eyes of the public (or justify the of the two original studies (Cairns et al., 1998, Cairns et al., 2002) and concerns of their critics). In this sense, documenting and quantifying the limited advance of knowledge on the subject since then” (p.2). traffic evaporation is critical in order to evaluate the effects of road Building on a previous study which reviewed more than 70 road space space reallocation schemes, and can indirectly contribute to advancing reallocation schemes (Goodwin et al., 1998), Cairns et al. found that 51 urban liveability by providing a solid evidence base for traffic reduction of the 70 schemes reported a decrease in traffic levels, compared to only measures. 11 schemes which reported an increase in traffic. The median observed Following this rationale, the present paper seeks to assess relative reduction in traffic was 11 % across all schemes, but the authors noted levels of traffic evaporation following multiple tactical urbanism in­ that there was wide variability between cases, partly because of the terventions implemented in Barcelona in the context of the COVID-19 different geographical scales and time periods under study. Further­ pandemic, using traffic count data collected by the local municipality. more, they noted that it is difficult to disentangle the effects of road More generally, the paper also offers a methodological contribution to schemes from natural variability in traffic levels. the existing literature on traffic evaporation by proposing a transparent Beyond these two original studies, there exist a handful of more way of assessing relative changes in traffic levels on intervention streets recent academic articles on traffic evaporation following temporary or (and their vicinity) compared to the rest of the city, which could be permanent road closures. Some of these focus on planned road closures fruitfully replicated in future empirical studies. (e.g. Chung et al., 2012; Hunt et al., 2002; Tennøy and Hagen, 2021), The paper begins with a literature review section which examines the while others examine the effects of unplanned disruptions (Zhu et al., existing academic literature on traffic evaporation, linking it to wider 2010). Another notable feature of various of these studies is their focus issues of street space distribution. After this, I present the methodology on bridges (Bucsky and Juhász, 2022; Hunt et al., 2002; Zhu et al., 2010) used to assess changes in traffic levels (and relative levels of traffic or tunnels (Tennøy and Hagen, 2021), which provide good case studies evaporation) following street redesign. The next section focuses on the since they allow to clearly isolate the impact of their closure (or capacity case study and its empirical results, first describing the tactical in­ reduction) on the wider road network. By and large, these studies have terventions implemented in Barcelona, and situating them in the context reported comparable conclusions: namely, that traffic levels tend to of the tactical urbanism interventions which numerous cities worldwide adapt to reductions in road space capacity, and that road congestion carried out during the COVID-19 pandemic. The discussion section impacts tend to be less severe than predicted by conventional traffic considers the implications of the findings, while the final conclusion models. Nevertheless, the widely different focus of each study summarises them and highlights some avenues for future research. (geographical context, timeline, type of intervention) means that establishing comparisons between cases remains difficult. This said, 2. Literature review: The phenomenon of traffic evaporation reported reductions in traffic levels following partial road capacity reduction tend to be on the order of − 5% to − 25 %, (e.g − 4.4 % in Hunt Briefly defined, traffic evaporation or “disappearing traffic” (Cairns et al. (2002); − 23 % in Tennøy and Hagen (2021)), which is consistent et al., 2002) refers to the reduction in traffic flows which is often with the findings of the review article by Cairns et al. (2002). These rates observed following a reduction in road space capacity. The existence of are also similar to those reported by the Municipality of Paris (− 5 to this phenomenon means that the impacts of road space reduction on − 28 %) along alternative traffic routes following the pedestrianisation traffic congestion are less severe than predicted by traffic models which of the right bank of the river Seine (Varoquier and Hasse, 2018). assume traffic levels to be inelastic. Traffic evaporation can be thought Although most studies limit themselves to trying to quantify the of as the opposite of induced traffic, i.e. the observed rise in traffic extent of traffic evaporation following the reduction of road space, some volumes following road capacity expansion. Although induced traffic also seek to explore the underlying mechanisms and behavioural re­ has been more thoroughly studied than traffic evaporation (Bucsky and sponses which may explain this reduction in traffic flows, such as modal Juhász, 2022; Goodwin, 1996; Litman and Colman, 2001), the latter shift or trip suppression. In these cases, analysis of traffic count data is currently seems a more pressing topic of study given the urgent need to supplemented by a survey of travel behaviour changes in vicinity of transition to transportation systems which rely less on private car use. scheme area (Hunt et al., 2002; Melia and Calvert, 2021; Zhu et al., Regarding the mechanisms which may explain traffic evaporation, one 2010), occasionally complemented by an exploration of changes in may consider three broad possible explanations, including 1) trip public transport ridership (e.g. Chung et al., 2012). The emerging rerouting beyond the area of measurement; 2) modal shift; and 3) trip consensus from these studies is that the degree of behavioural change suppression (Cairns et al., 2002; Melia and Calvert, 2021). In the third and modal shift away from motorised travel tends to be proportional to case, these “suppressed trips” are associated with wider changes in in­ the level of disruption to the existing car traffic network. dividual travel practices such as a change of destination, working from While these studies have contributed to generate growing evidence home, or car-sharing. Over the long term, reduced road space capacity of traffic evaporation, the fact remains that “significant knowledge gaps might even lead to changes in residential and activity location. remain as a priority for future research” (Melia and Calvert, 2021, p. 1). More generally, the issue of traffic evaporation also connects with At the most basic, there is a need to further build up a critical mass of wider debates on the distribution of street space and its relationship to empirical evidence documenting traffic evaporation across a variety of issues of urban equity and fairness, which are becoming an area of geographic settings. Likewise, there still exists relatively little research increasing academic attention (e.g. Creutzig et al., 2020; Gössling, 2016; exploring the effects of road space reallocation schemes beyond the local Guzman et al., 2021; Nello-Deakin, 2019). As these accounts stress, intervention area, or the cumulative effect of multiple neighbouring motorised traffic is currently granted a disproportionate share of the interventions. Although road space reallocation schemes have become scarce public space in modern cities, which could be more equitably and more popular than ever in the light of the COVID-19 pandemic, the fact efficiently used if it were dedicated to other functions. Since car use remains that “politics, financial pressures on local authorities and remains restricted to specific population groups in most cities, this pri­ practical challenges often curtail the scope of traffic removal schemes oritisation of the interests of car drivers over the needs and desires of and confound attempts to evaluate their wider impacts” (Melia and other citizens may reproduce and amplify existing urban and transport Calvert, 2021, p. 8). By seeking to evaluate the traffic impacts of 2431 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 multiple tactical urbanism interventions during the COVID-19 pandemic 4. Application to a case study: tactical interventions in in the centre of Barcelona, the present study hopes to provide a signif­ Barcelona icant contribution to this topic. 4.1. Barcelona’s Eixample and superblocks scheme 3. Methodology The regular grid city of Barcelona’s Eixample district is well known The research method presented in this article involves the analysis of among urban planners as one of the most prominent examples of 19th- temporal changes in permanent traffic count data, through a comparison century urbanism. In many ways, the Eixample of Barcelona provides a of pre- and post-intervention traffic counts. At an empirical level, this good case study to explore changes in traffic levels following the real­ analysis relies on the availability of a city-wide historical dataset of location of road space, since most of its streets follow an isotropic grid permanent traffic count data, often publicly available from municipal layout and share similar fundamental characteristics (e.g. width, traffic open data repositories. For each individual traffic counter, this data is speed, number of lanes), thereby facilitating comparisons between usually provided in the form of average daily traffic (ADT), sometimes streets. In addition, this grid layout makes it easy to identify parallel further summarised into weekly or monthly daily average traffic alternative routes, although it potentially also makes it more difficult to (MADT). clearly delimit the boundaries of the study area. Importantly, the presented method does not only examine traffic As a result of Barcelona’s high population density – which is highest changes in streets affected by tactical interventions, but also in streets in in the Eixample (36.267 pop./km2) in 2020) – the city allegedly has the the wider neighbouring area, as well as in the rest of the city. This makes “highest car density in Europe” according to the local municipality.3 it possible to explore relative changes in traffic levels between various Regardless of the accuracy of this claim, it is undeniable that most streets street categories, and identify potential traffic displacement from in the Eixample district support high levels of through traffic, with intervention streets to other street categories. This method is premised traffic-calmed streets being almost non-existent. These high traffic in­ on the classification of traffic counting stations into four distinct cate­ tensities are responsible for serious negative local externalities such as gories, corresponding to four different street typologies (for a map noise and air pollution, as well as a lack of public open space within the showing the distribution of these categories in the specific case study of district (Mehdipanah et al., 2019; Mueller et al., 2020). In recent years, Barcelona, see Fig. 3 in Section 4.3): the Eixample has served as the reference case for developing the “su­ perblock” model of traffic calming, which has received considerable • Intervention street: This category includes traffic counters on streets attention in international media and urban planning circles (e.g. Bau­ which have been directly affected by street redesign or tactical ur­ sells, 2016; O’Sullivan, 2020). Put briefly, the original superblock model banism interventions, resulting in the reduction of at least one traffic (Rueda, 2019) amalgamates nine individual city blocks (3 × 3) and lane. confines through motor traffic to the outer edges of the resulting “su­ • Adjacent street: This category includes traffic counters on parallel perblock”, leading to the near-pedestrianisation of the street segments streets adjacent to intervention streets running in the same direction, within the superblock. In doing so, the superblock model seeks to which provide likely alternative routes for traffic.1 significantly curtail overall traffic levels. • Buffer area: This category includes all remaining traffic counters The first official superblock in Barcelona was implemented in 2017 within a 500 m distance from tactical urbanism interventions,2 in the neighbourhood of Poblenou followed by the more recent in­ excluding traffic counters already included in the two previous cat­ terventions in the Sant Antoni area (in the Eixample district). While the egories. The rationale behind this category is to explore potential original aspiration was to extend this model throughout the rest of the traffic displacement not only on parallel adjacent streets, but also in Eixample, significant opposition to this plan has since led to a less the wider vicinity of tactical urbanism interventions. ambitious, more pragmatic plan in an attempt to increase political and • Control area: This category includes all traffic counters on streets in social consensus. In effect, the current long-term traffic calming strategy rest of the city (excluding urban highways), beyond a 500 m distance for the Eixample moves away from the literal concept of superblocks from streets affected by tactical urbanism interventions. This cate­ towards the idea of “green corridors”, i.e. the pedestrianisation of spe­ gory acts as a control group in relation to the previous three cate­ cific streets along their full length rather than multiple streets in a gories, providing a baseline rate of temporal changes in traffic counts specific area. Nevertheless, the “superblocks” label has been retained to for the rest of the city. refer to the collection of traffic calming interventions and street re­ designs which fall under this long-term strategy. Fig. 1 visually summarises the main steps of the research method, While academic research on Barcelona’s superblocks has recently which involves a combination of GIS mapping, data processing and begun to emerge (e.g. Mehdipanah et al. (2019) and Mueller et al. visualisation (in the present article, a combination of QGIS and R was (2020) on public health impacts; Scudellari et al. (2020) and Zografos used). When comparing the evolution of traffic counts between street et al. (2020) on politics and governance), there still appears to be a lack categories, the results can be presented (Step 4) both in the form of of studies seeking to assess their impacts on local mobility patterns. A aggregate counts across multiple traffic count stations, and single- recently published technical report by the Municipality of Barcelona,4 station averages for each street category. While aggregate counts are however, estimated that average daily traffic (ADT) in the Sant Antoni useful in providing an estimate of absolute changes in traffic levels for superblock diminished by 15 % between 2017 and 2019, and by 21 % each street category, the large difference in the number of traffic stations between 2017 and 2022.5 While traffic decreased most markedly on the in each category means that single-station averages allow for a better main intervention street, traffic counts also decreased slightly on comparison between street categories. 3 Municipality of Barcelona, 2016. https://ajuntament.barcelona.cat/eixa 1 In the case study of Barcelona, adjacent streets which themselves have also mple/ca/noticia/sabies-que-barcelona-es-la-ciutat-deuropa-amb-mes-densitat been subject to tactical urbanism interventions have been excluded from this -de-vehicles_403904. 4 category, since they are already included in the intervention street category. Municipality of Barcelona, 2022. https://ajuntament.barcelona.cat/superill 2 The size of this buffer (500 m) has been designed taking into account the es/sites/default/files/2022–03-28_ESTUDI_IMPACTE_MOBILITAT_2023_TOM_ urban and street density of Barcelona, but alternative buffer sizes might be I_web.pdf. 5 more suitable for more or less dense urban environments (e.g. suburban This rate of change includes both traffic flows on the main intervention neighbourhoods with a sparser street network). street and on the two adjacent parallel streets in the same direction. 2432 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 Fig. 1. Visual summary of the research method, broken down into discrete steps. adjacent parallel streets on either side, suggesting that some degree of declared on 14 March 2020 as a response to the COVID-19 pandemic, traffic evaporation has taken place. during which people were only allowed to go outdoors to travel to work and undertake other essential trips. These measures were gradually relaxed from May 2020 onwards, but successive COVID-19 waves 4.2. Tactical urbanism interventions during COVID-19 pandemic resulted in the reintroduction of new restrictions from October 2020, including variable degrees of travel restrictions between municipalities/ The unexpected onset of the COVID-19 pandemic in early 2020 counties, and night-time curfews. All in all, complete normality was only entailed a major disruption to urban travel patterns worldwide regained on 9 May 2021, when the state of alarm was suspended and all (Abduljabbar et al., 2022). In most cases, travel demand plummeted domestic travel restrictions were lifted. because of lockdowns and mobility restrictions; owing to the fear of At the height of the pandemic (spring 2020), the municipality of contagion, this reduction in trips was particularly severe in the case of Barcelona announced various emergency measures which entailed the public transport, and entailed a relative modal shift towards active and reallocation of road space on multiple streets from motorised traffic to motorised private transport (Coppola and De Fabiis, 2021; Gkiotsalitis active and public transport, primarily in the central Eixample district. and Cats, 2021). Although travel demand has gradually recovered since These measures sought both to respond to the exceptional context of the the end of pandemic restrictions, it is likely that some structural changes pandemic and to advance the underlying urban mobility vision of the in urban mobility patterns will remain. In particular, travel demand for city administration, which aspires to reduce the prominence of motor­ private modes generally appears to have recovered to a greater extent ised traffic in the city centre through the implementation of “super­ than for public transport (Abduljabbar et al., 2022), while increased blocks” and “green corridors”. Largely adhering to tactical urbanism teleworking may contribute to an overall reduction in travel compared principles and elements (e.g. use of paint and cement blocks), most of to pre-pandemic values (Möllers et al., 2022). these interventions were carried out speedily compared to normal street In turn, the COVID-19 pandemic acted as a major stimulus or “win­ redesigns. The bulk of these interventions were carried out in May 2020, dow of opportunity” for the implementation of tactical interventions with a small number of them being announced and implemented later in seeking to prioritise active travel modes in urban space in cities 2020 and early 2021. worldwide (Glaser and Krizek, 2021; King and Krizek, 2021; Rojas- Table 1 lists all streets in the Eixample district which experimented Rueda and Morales-Zamora, 2021). In Europe, cities like Paris, notable tactical urbanism interventions during 2020 and early 2021 in Milano, Berlin or Barcelona rolled out new “pop-up” bike lanes and the context of the COVID-19 pandemic, which provide the empiric focus closed down streets to motor traffic, as prominently reported in inter­ of the present study6 (for a visualisation of these interventions on a map, national media (Laker, 2020; Zafra et al., 2020). Subsequently, many of see Fig. 3 in Section 4.3). In all cases, the reallocation of road space these emergency measures have been made permanent (Fenu, 2021). following these interventions resulted in the reduction of at least one These measures sought to facilitate social distancing by increasing the conventional traffic lane. It should also be noted that in cases where only amount of public space and providing active travel alternatives to public one traffic lane remained after the street redesign, speed limits were transport, as well as to try and curb a potential increase in private automatically reduced from 50 to 30 km/h (even though this limit is motorised vehicle use in the wake of the COVID-19 pandemic. Never­ rarely enforced in practice). While in certain cases the “tactical” nature theless, many cities also used the pandemic as an occasion to accelerate of these interventions is apparent (e.g. new tactical sidewalks), in other various plans which already formed part of their long-term policy vision (Glaser and Krizek, 2021), taking the opportunity to push forward schemes which might have encountered greater resistance during “normal” times. 6 As an exception, two streets for which no traffic count data was available In Spain, a state of alarm which imposed a strict lockdown was (Rocafort and Castillejos) were excluded from the analysis. 2433 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 Table 1 List of street interventions assessed in the present study. Street Traffic lanes pre- Traffic lanes post-intervention Traffic lane Execution period Number of traffic intervention reduction counters Consell de 2 traffic lanes + bike 1 traffic lane + bike lane + tactical sidewalk 1 May 2020 1 Cent lane Girona 2 traffic lanes + bike 1 traffic lane + bike lane + tactical sidewalk 1 May - June 2020 1 lane Roger de 3 traffic lanes + bus 2 traffic lanes + bus lane + bike lane 1 May 2020 2 Llúria lane Pau Claris 3 traffic lanes + bus 2 traffic lanes + new bike lane (+bus lane) 1 May 2020 3 lane Aragó 6 traffic lanes Stage 1: 5 traffic lanes + bus lane; Stage 2: 4 traffic 2 November 2019 (Stage 1); November 6 lanes + bus lane + bike lane -December 2020 (Stage 2) Indústria 2 traffic lanes + bus 2 traffic lanes 1 May 2020 1 lane Gran Via 4 traffic lanes + bus 3 traffic lanes + 2 bus lanes 1 November-December 2020 3 lane València 3 traffic lanes + bus 2 traffic lanes + bus lane + bike lane 1 May 2020 7 lane1 Ronda 4 traffic lanes + 2 bus 2 traffic lanes + 2 bus lanes 2 November 2020-April 2021 1 Universitat lanes Plaça 4 traffic lanes 3 traffic lanes 1 November 2020-April 2021 1 Universitat Pelai 3 traffic lanes + 1 bus 2 traffic lanes + 1 bus lane 1 March 2021 2 lane2 1 Part of València Street has a car parking lane on it, so only had 2 conventional traffic lanes prior to the intervention. 2 Part of Pelai Street only had conventional 2 traffic lanes prior to the intervention. cases (e.g. new bike lane construction) these measures differed little single-station MADT for all traffic count stations in Barcelona for the from similar past schemes, beyond the speediness with which they were years 2019–2021. As can be seen, traffic counts decreased dramatically implemented. Fig. 2 shows the example of Girona Street before and after in early 2020 as a result of COVID-19 lockdown, and remained signifi­ the implementation of a tactical sidewalk, which entailed the elimina­ cantly below 2019 values for the rest of 2020 and early 2021. By the tion of one traffic lane and on-street car parking. second half of 2021 traffic was closer to, but still somewhat below 2019 values. 4.3. Results In Fig. 5, I display the evolution of average single-station MADT from the beginning of 2019 to the end of 2021 according to the four previ­ Following the previously described research method, the traffic im­ ously defined street categories. This figure shows that traffic counts have pacts of the tactical interventions listed in Table 1 were assessed using decreased most markedly for intervention streets; for the three publicly available permanent traffic count data published by the Mu­ remaining categories, the evolution in traffic counts appears to be nicipality of Barcelona for the years 2019–2021.7 For each individual relatively similar, pointing to a slight reduction in traffic levels over the traffic counter, the municipality provides this data in the form of period under consideration. Although the effects of seasonality and monthly average daily traffic (MADT) by type of day (Monday/Week­ COVID-19 restrictions (particularly for the lockdown during April-May day/Friday/Saturday/Sunday), from which a global MADT was calcu­ 2020) are similar for all street categories, the linear trend for each lated for each traffic counter. category (discontinuous line) clearly evidences that traffic counts on Fig. 3 maps all street interventions listed in Table 1, and shows the intervention streets have decreased more pronouncedly than for the classification of traffic counters according to the four street categories other three categories.8 described in the Methodology (the total number of traffic counters in The relative evolution of traffic levels between street categories can each category is displayed in the map legend). All traffic counters with be visualised more clearly by examining how traffic counts have evolved available data for all years were included in the analysis, except for three relative to the 2019 annual average for each category, as displayed in counters which were significantly affected by a temporary traffic Fig. 6. This graph shows that traffic counts have recovered at a similar diversion following roadworks on a section of Avinguda Diagonal in rate after COVID-19 restrictions for all street categories except for 2021. For these three locations, preliminary results showed that traffic intervention streets, for which traffic counts have recovered at a counts deviated largely from usual values because of traffic rerouting significantly slower rate relative to 2019 values. By December 2021 – during much of 2021, leading to their exclusion from the analysis. the last month with available data – average traffic values on inter­ Given the large fluctuations in traffic values during 2020 and early vention streets had recovered to 82 % of the 2019 annual average on 2021 as a result of COVID-19 restrictions, the main analysis has been intervention streets, compared to 92 % on both adjacent and buffer restricted to two distinct time periods, which also largely correspond streets, and 95 % on control streets. with pre-and post-pandemic stages: namely, the 2nd semester of 2019 Critically, the significant reduction in traffic counts on intervention (pre-intervention), and the 2nd semester of 2021 (post-intervention). As streets does not appear to have caused a commensurate increase in part of the exploratory analysis, I also examined differences in results by traffic counts in adjacent and buffer streets compared to streets in the day of the week (weekday vs weekend), but have not included these in control group. As shown in Figs. 5 and 6, the overall evolution of traffic the results, since they did not reveal any noteworthy pattern. levels is very similar for the adjacent, buffer and control categories (in To contextualise the results, Fig. 4 shows the evolution of the average fact, Fig. 6 suggests that traffic levels during the second half of 2021 7 8 Yearly traffic count data sets can be found at the city’s Open Data portal: As a clarification, the reason why average traffic counts are highest on https://opendata-ajuntament.barcelona.cat/data/ca/dataset/aforaments-deta intervention streets is simply that these interventions took place on streets with ll. higher traffic values than the city average. 2434 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 Fig. 2. Girona Street before and after the implementation of a new tactical sidewalk (Source: Google Street View/author). 2435 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 Fig. 3. Street interventions and traffic counters by category. Note: Most traffic counters in the control street category are situated beyond the boundaries of the map (up to the municipal limits of the city). relative to 2019 are even somewhat lower on average for adjacent and small relative increase in traffic relative compared to control streets, buffer streets than for control streets). This can be seen by visually while traffic levels on buffer streets have evolved almost identically to comparing the evolution of traffic counts relative to the control group for streets in the control group. the remaining three street categories (Fig. 7). As illustrated in previous Within-category variability between individual counting stations is graphs, this figure confirms that relative traffic counts have clearly displayed in Fig. 8, which provides a box plot of relative traffic count decreased in intervention streets. However, the most noteworthy finding evolution between 2019 and 2021 by street category. As can be seen, is that the trend line for the parallel and buffer street categories is variability is greatest within the control group given the large number of essentially flat or even slightly negative relative to the control group counting stations it includes, while outliers within the other three cat­ category. If traffic from intervention streets had been largely displaced egories are rarer. At the individual street level, estimates of relative to adjacent streets and the wider neighbouring area, one would expect to traffic change on intervention streets compared to the control category see a positive trend line. Instead, these results show that traffic levels have vary between +22 % and − 36 % (+13 % and − 45 % in absolute terms). declined in intervention streets without causing a corresponding traffic in­ Within the intervention street category, only four traffic count stations crease in their vicinity, thereby suggesting that a significant amount of have experimented a relative increase in traffic counts compared to the traffic evaporation has taken place. control group. Three of these four traffic count stations were these sit­ As a complement to the above graphs, Table 2 provides a numerical uated on the same street (Gran Via), which differs from most other summary of the relative evolution of average traffic counts between the intervention streets because of its uniquely large width and number of second semester of 2019 (pre-intervention) and the second semester of traffic lanes (see Table 1). As already shown in Table 3, the box plot 2021 (post-intervention) for each street category. This table displays highlights that traffic levels on most adjacent streets have increased average and median changes in single-station traffic counts between slightly compared to the streets in the control group, while most streets 2019 and 2021 for each category, as well as the total aggregate change in the buffer category have experimented a small relative decrease. for all streets in each category (i.e. sum of individual traffic stations). Further information on the evolution of traffic counts at an indi­ Table 3 presents the same information for streets in the intervention, vidual station level is presented in the map in Fig. 9, which displays the adjacent and buffer categories relative to streets in the control group. relative change in MADT for traffic stations in the intervention (□), This table shows that traffic levels between 2019 and 2021 have adjacent (△) and buffer (○) street categories compared to control group decreased significantly on intervention streets compared to control streets. While this study does not seek to examine changes in traffic streets, with an average relative reduction of − 14.8 % (− 23.8 % in counts on a street-by-street basis, the map confirms that traffic levels absolute terms), and a total relative reduction of − 13.6 % across all have generally evolved in the same direction for counting stations on the intervention streets. By contrast, traffic levels in adjacent streets show a same street. Considering all three street categories together 2436 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 Fig. 4. Average single-station MADT by year. Fig. 5. Average single-station MADT by type of street. 2437 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 Fig. 6. Average single-station MADT by type of street relative to 2019 annual average. Fig. 7. Evolution of average single-station MADT relative to control stations. 2438 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 Table 2 schemes can potentially lead to the emergence of “loser” streets Absolute traffic count evolution by street category (2nd semester 2019–2nd adversely affected by traffic displacement (Appleyard, 1981), in the semester 2021). present case study adjacent streets only experienced small relative in­ Type of street Average Median Total creases in traffic (+2%). This suggests that rather than causing wide­ Intervention − 23.8 % − 24.8 % − 23.3 % spread traffic displacement, the interventions under study been led to a Adjacent − 8.3 % − 5.5 % − 7.2 % significant “evaporation” of traffic. Buffer − 9.5 % − 10.5 % − 8.7 % Although comparing between studies requires caution given the Control − 9.1 % − 9.4 % − 9.7 % different temporal scale and geographical setting of each study, it is interesting to note that average that the median relative traffic reduction across all intervention streets in the present study (− 15.4 %) is quite Table 3 similar to the median reduction of − 11 % reported in the review of 70 Relative traffic count evolution by street category compared to streets in the cases by Cairns et al. (2002), and within the same order of magnitude control group (2nd semester 2019–2nd semester 2021). than the observed reductions from other studies which entailed the Type of street Average Median Total partial removal of car lanes (e.g. − 4.2 % in Bucsky and Juhász (2022); Intervention − 14.8 % − 15.4 % − 13.6 % − 23 % in Tennøy and Hagen (2021)). This suggests that although it may Adjacent +0.7 % +3.9 % +2.4 % be difficult to accurately model or predict exact levels of traffic reduc­ Buffer − 0.4 % − 1.1 % +1.0 % tion, it is not unreasonable to venture an educated guess about the di­ rection and magnitude of traffic changes to expected following road space reallocation measures. (intervention, adjacent and buffer), relative traffic levels have decreased Admittedly, the findings of the present study cannot be fully sepa­ in 77 of 127 stations within the area of influence in Fig. 9, with the rated from context of the COVID-19 pandemic and the overall reduction remaining 50 stations experimenting a relative increase compared to the in urban travel demand in its aftermath. Given the recent implementa­ control group. Overall, total traffic levels (sum of individual station tion of the tactical urbanism schemes under examination, this study only averages) within the area of influence have decreased by − 4.1 % be­ assessed their implications over a relatively short term (<1 year), in a tween 2019 and 2021 compared to the rest of the city (i.e. control group context where traffic levels have not yet entirely recovered to pre- stations). pandemic values. In this respect, the COVID-19 pandemic paradoxi­ cally provided the conditions which allowed for the implementation of 5. Discussion tactical interventions, but also made it more difficult to evaluate their effect. Since the pandemic entailed a significant disruption of daily Overall, the results of the analysis show that traffic levels have mobility patterns which resulted in a global temporary reduction of diminished significantly on intervention streets (− 23 % in absolute motorised traffic, it is virtually impossible to assess the immediate short- terms, and − 14 % relative to the rest of the city), without causing a term impacts these interventions would have had under “normal” con­ substantial increase in the neighbouring area. While traffic calming ditions. Although daily mobility patterns had largely gone back to usual Fig. 8. Change in mean semestral ADT by street category (Jul-Dec 2019 to Jul-Dec 2021). The red line indicates the average for the control group category. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 2439 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 Fig. 9. % change in MADT for individual traffic counters in intervention (□), adjacent (△) and buffer (○) streets relative to control group stations (Jul-Dec 2019 to Jul-Dec 2021). by the second semester of 20201, traffic levels remained below pre- trips. Indeed, the rise of teleworking has been one of the main legacies of pandemic levels by the end of 2021, making it difficult to assess abso­ the COVID-19 pandemic, both in Barcelona (Andrés et al., 2021) and lute levels of traffic evaporation (since traffic has “evaporated” every­ worldwide (Möllers et al., 2022). The Eixample is a pre-eminently central where, so to speak). For this reason, the paper has focused on assessing mixed use district, characterised by an important concentration of office relative traffic evaporation on intervention streets, compared to control spaces, tertiary services, and predominantly white-collar residents, group streets. While this inevitably limits the scope of the findings, it suggesting that it is one of Barcelona’s neighbourhoods where reduced nevertheless provides a way forward to evaluate changes in traffic travel as a result of telework is likely to be most felt. Likewise, the counts in the light of the COVID-19 pandemic. Given the enduring general reduction in tourism in Barcelona in the aftermath of the prominence and relevance of public debates on this topic, being able to pandemic might account for part of the “evaporated” traffic. The tactical partially evaluate the effects of street space reallocation measures dur­ street interventions under study (and the COVID-19 pandemic more ing the pandemic certainly seems preferable to not doing so at all. broadly) may have also led to some modal shift towards active travel, This focus on relative rather than absolute traffic changes, I suggest, and cycling and e-scooter use in particular, which in the metropolitan is not only valuable in the context of the COVID-19 pandemic, but might area of Barcelona saw a +4.3 % rise in usage between 2019 and 2020 contribute to provide a more suitable way of assessing traffic evapora­ (Andrés et al., 2021). Public transport provision in the Eixample district tion more generally. Traffic levels are rarely static, but fluctuate over (and Barcelona more generally), meanwhile, has not varied significantly time in response to influences such as temporary road closures, new between 2019 and 2021, and public transport demand continued to be at measures which might affect traffic levels (e.g. congestion charges, low approximately 75–80 % of its pre-pandemic level by the end of 2021.9 In emissions zones), and long-term trends (e.g. decreasing car use in urban this respect, there is little evidence which suggests a modal shift from areas, economic cycles). As a way of overcoming this difficulty, I pro­ motorised to public transport. pose that focusing on relative traffic changes on intervention streets Finally, it is important to be aware that numerical traffic counts in compared to control group streets may provide a more rigorous way of the form of ADT these are a useful but nevertheless simplistic indicator assessing traffic evaporation. of changes in traffic. For residents and transport planners alike, alter­ Regarding the possible causes of traffic evaporation, existing studies native measures such as traffic speeds, congestion levels, environmental suggest that it can be attributed to a combination of modal shift, trip suppression and changes in trip destination (Hunt et al., 2002; Melia and Calvert, 2021; Zhu et al., 2010). While the present study is unable to 9 This data on public transport demand is published by the Metropolitan investigate the relative role of various factors in explaining traffic Transport of Barcelona (ATM) as part of a COVID-19 interactive dashboard: evaporation, in the context COVID-19 pandemic and its aftermath it https://datastudio.google.com/u/0/reporting/8134194c-db6d-4d6a-ac8b-fd5e seems plausible to ascribe most of the “evaporated” traffic to suppressed 34dbfc4d/page/oWSOB. 2440 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 and acoustic pollution, or traffic accidents might often provide more their cumulative effect within the whole study area. Nevertheless, this relevant metrics than simple traffic counts to assess traffic changes at a makes it difficult to assess the effect of each individual intervention. In given location. Furthermore, ADT counts usually focus exclusively on future research, it would be interesting to explore the extent to which motorised traffic, ignoring other means of transport such as cyclists, the effect of isolated interventions is comparable to that of multiple pedestrians, electric scooters, or bus users. In the present study, for interventions. Finally, and as pointed out in the discussion, focusing not instance, reductions in conventional traffic lanes were accompanied by only on traffic counts but also on other complementary dimensions (e.g. new cycling and bus lanes on various streets. Although beyond the scope traffic noise, pollution, speed, pedestrian counts) would represent an of the present study, exploring how the use of these other transport important step forward towards a more holistic assessment of the im­ modes has changed as a result of street interventions (e.g. cyclist counts, plications of road space reallocation schemes. bus occupancy rates) would contribute to deliver a fuller picture of their effect on street-level mobility. Author contributions To close, I would like to note two additional limitations of the present study. As mentioned previously, the analysis relies on publicly available Samuel Nello-Deakin: Conception, analysis and writing. traffic count data which was not collected for the specific goals of the present study. Although the spatial coverage of municipal traffic Declaration of Competing Interest counting stations is extensive, there are certain relevant streets for which no data is available. In this respect, a targeted data collection The authors declare that they have no known competing financial scheme for this specific purpose would be able to deliver more precise interests or personal relationships that could have appeared to influence results. Secondly, and given the relatively extensive study area and time the work reported in this paper. period considered, the study does not account for all small temporary road closures and other street-level disruptions which might introduce some level of noise into the data at the level of individual traffic References counting stations. Abduljabbar, R.L., Liyanage, S., Dia, H., 2022. A systematic review of the impacts of the coronavirus crisis on urban transport: Key lessons learned and prospects for future 6. Conclusion cities. Cities 127, 103770. https://doi.org/10.1016/j.cities.2022.103770. Andrés, D., Bach, X., Nel⋅lo, S. Pérez, N., Pérez, M., Solé, G. La pandèmia i la mobilitat metropolitana: canvis efímers o transició permanent? Anuari Metropolità de Barcelona The present study has examined the impact on traffic levels of 2020, 163-183. IERMB. https://iermb.uab.cat/wp-content/uploads/2021 tactical urbanism interventions implemented during COVID-19 /07/ANUARI_IERMB_2020_web.pdf. Appleyard, D., 1981. Livable Streets. Univ of California Press. pandemic on 11 streets in Eixample district in Barcelona, which led to Bausells, M., 2016, May 17. Superblocks to the Rescue: Barcelona’s Plan to Give Streets the reduction of one or more traffic lanes on each street. The findings Back to Residents. The Guardian. https://www.theguardian.com/cities/2016/may/1 show that between 2019 and 2021, total traffic levels on intervention 7/superblocks-rescue-barcelona-spain-plan-give-streets-back-residents. streets decreased by − 23 % in absolute terms, and by − 14 % compared Bertolini, L., 2020. From “streets for traffic” to “streets for people”: Can street experiments transform urban mobility? Transp. Rev. 40 (6), 734–753. https://doi. to control group streets (i.e. streets in the rest of the city). Although total org/10.1080/01441647.2020.1761907. traffic levels relative to streets in the control group increased slightly for Bucsky, P., Juhász, M., 2022. Long-term evidence on induced traffic: A case study on the parallel streets immediately adjacent to intervention streets (+2%), relationship between road traffic and capacity of Budapest bridges. Transp. Res. Part A: Policy Pract. 157, 244–257. https://doi.org/10.1016/j.tra.2022.01.018. traffic in other streets within the wider vicinity of the intervention area Cairns, S., Atkins, S., Goodwin, P., Bayliss, D. 2002. Disappearing traffic? The story so (500 m buffer) did not evolve significantly differently to streets in the far. Proc. Inst. Civil Eng.: Municipal Engineer, 151(1), 13–22. https://doi.org/10.1680/ control group. Overall, these results suggest that significant traffic muen.2002.151.1.13. Chung, J.-H., Yeon Hwang, K., Kyung Bae, Y., 2012. The loss of road capacity and self- evaporation has taken place in streets where tactical urbanism in­ compliance: Lessons from the Cheonggyecheon stream restoration. Transp. Policy terventions were implemented, without leading to a corresponding in­ 21, 165–178. https://doi.org/10.1016/j.tranpol.2012.01.009. crease in traffic within streets in their vicinity. While there is evidence of Coppola, P., De Fabiis, F., 2021. Impacts of interpersonal distancing on-board trains during the COVID-19 emergency. Eur. Transp. Res. Rev. 13, 13. https://doi.org/ some local traffic displacement from intervention to adjacent streets, the 10.1186/s12544-021-00474-6. level of relative traffic increase on adjacent streets is much less than the Creutzig, F., Javaid, A., Soomauroo, Z., Lohrey, S., Milojevic-Dupont, N., corresponding decrease in traffic on intervention streets. Ramakrishnan, A., Sethi, M., Liu, L., Niamir, L., Bren d’Amour, C., 2020. Fair street space allocation: ethical principles and empirical insights. Transp. Rev. 40 (6), At a theoretical and empirical level, this article contributes to the 711–733. growing critical mass of studies which provide empirical evidence of Fenu, N., 2021. Bicycle and urban design. A lesson from Covid-19. TeMA – J. Land Use traffic evaporation. More specifically, the present study represents one Mobil. Environ. 14 (1), 69–92. https://doi.org/10.6092/1970-9870/7716. of the first attempts to evaluate the traffic impacts of tactical urbanism Finn, D., 2014. DIY urbanism: Implications for cities. J. Urban. 7 (4), 381–398. https:// doi.org/10.1080/17549175.2014.891149. measures adopted during the coronavirus pandemic in a rigorous and Gkiotsalitis, K., Cats, O., 2021. Public transport planning adaption under the COVID-19 transparent manner. By providing a detailed explanation of the meth­ pandemic crisis: literature review of research needs and directions. Transp. Rev. 41 odology used, this study presents a step forward towards developing a (3), 374–392. Glaser, M., Krizek, K.J., 2021. Can street-focused emergency response measures trigger a transparent way of evaluating traffic reduction schemes, which might transition to new transport systems? Exploring evidence and lessons from 55 US serve as an example for future studies. In this respect, the increasing cities. Transp. Policy 103, 146–155. https://doi.org/10.1016/j.tranpol.2021.01.015. availability of traffic count data in municipal open data databases offers Goodwin, P., 1996. Empirical evidence on induced traffic. Transportation 23 (1), 35–54. https://doi.org/10.1007/BF00166218. an opportunity for replicating the methodology of the present study in a Goodwin, P., Hass-Klau, C., Cairns, S., 1998. Evidence on the effects of road capacity different setting. reduction on traffic levels. Traff. Eng. Control 39 (6), 348–354. In terms of future research, it would be interesting to carry out a Gössling, S., 2016. Urban transport justice. J. Transp. Geogr. 54, 1–9. https://doi.org/ 10.1016/j.jtrangeo.2016.05.002. follow-up study of the present case study in a few years. By then, various Guzman, L.A., Oviedo, D., Arellana, J., Cantillo-García, V., 2021. Buying a car and the of the current tactical street redesign measures are set to be replaced street: Transport justice and urban space distribution. Transp. Res. Part D: Transp. with permanent street redesigns, and complemented with further traffic Environ. 95, 102860. Hartman, L. M., Prytherch, D. 2015. Streets to live in: justice, space, and sharing the reduction measures as part of the roll-out of proposed superblocks plans road. Environ. Ethics, 37(1), 21–44. in Barcelona. Another important methodological challenge which future Hickman, R., Huaylla Sallo, K., 2022. The political economy of streetspace reallocation research could seek to address is the difficulty of disentangling the ef­ projects: Aldgate Square and Bank Junction, London. J. Urban Design 1–24. https:// fects of multiple neighbouring interventions. Given the relative prox­ doi.org/10.1080/13574809.2022.2033113. Hunt, J.D., Brownlee, A.T., Stefan, K.J., 2002. Responses to centre street bridge closure: imity and temporal simultaneity of all interventions in the present case where the “disappearing” Travelers went. Transp. Res. Rec. 1807 (1), 51–58. https:// study, I opted to consider them largely as a single whole, focusing on doi.org/10.3141/1807-07. 2441 S. Nello-Deakin Case Studies on Transport Policy 10 (2022) 2430–2442 Illich, I., 1974. Energy and Equity. Harper & Row. Rojas-Rueda, D., Morales-Zamora, E., 2021. Built environment, transport, and COVID-19: King, D.A., Krizek, K.J., 2021. Visioning transport futures through windows of A review. Curr. Environ. Health Reports 8 (2), 138–145. https://doi.org/10.1007/ opportunity: Changing streets and human-scaled networks. Town Plann. Rev. 92 (2), s40572-021-00307-7. 157–163. https://doi.org/10.3828/tpr.2020.60. Rueda, S., 2019. Superblocks for the design of new cities and renovation of existing ones: Laker, L., 2020, April 11. World Cities Turn Their Streets Over to Walkers and Cyclists. Barcelona’s case. In: Nieuwenhuijsen, M., Khreis, H. (Eds.), Integrating Human The Guardian. https://www.theguardian.com/world/2020/apr/11/world-cities-tu Health into Urban and Transport Planning: A Framework. Springer International rn-their-streets-over-to-walkers-and-cyclists. Publishing, pp. 135–153. https://doi.org/10.1007/978-3-319-74983-9_8. Litman, T., Colman, S.B., 2001. Generated traffic: Implications for transport planning. Sadik-Khan, J., Solomonow, S., 2016. Streetfight: handbook for an urban revolution. ITE J. 71 (4), 38–46. Viking. Lydon, M., Garcia, A., Duany, A. 2015. Tactical Urbanism: Short-term Action for Long-term Scudellari, J., Staricco, L., Vitale Brovarone, E., 2020. Implementing the Supermanzana Change. Island Press. approach in Barcelona. Critical issues at local and urban level. J. Urban Design 25 Mehdipanah, R., Novoa, A.M., León-Gómez, B.B., López, M.J., Palència, L., Vasquez, H., (6), 675–696. https://doi.org/10.1080/13574809.2019.1625706. Díez, È., Borrell, C., Pérez, K., 2019. Effects of Superblocks on health and health Silva, P., 2016. Tactical urbanism: Towards an evolutionary cities’ approach? Environ. inequities: a proposed evaluation framework. J. Epidemiol. Community Health 73 Plann. B: Plann. Design 43 (6), 1040–1051. https://doi.org/10.1177/ (7), 585–588. https://doi.org/10.1136/jech-2018-211738. 0265813516657340. Melia, S., & Calvert, T. (2021). Does traffic really disappear when roads are closed? Proc. Tennøy, A., Hagen, O.H., 2021. Urban main road capacity reduction: Adaptations, effects Inst. Civil Eng. - Municipal Engineer, 1–9. https://doi.org/10.1680/jmuen.21.00014. and consequences. Transp. Res. Part D: Transp. Environ. 96, 102848 https://doi.org/ Möllers, A., Specht, S., Wessel, J., 2022. The impact of the Covid-19 pandemic and 10.1016/j.trd.2021.102848. government intervention on active mobility. Transp. Res. Part A: Policy Pract. Varoquier, J., Hasse, B., 2018, February 18. Paris : mais si, le trafic autour des voies sur https://doi.org/10.1016/j.tra.2022.09.007. berge s’améliore ! leparisien.fr. https://www.leparisien.fr/info-paris-ile-de-france-ois Mueller, N., Rojas-Rueda, D., Khreis, H., Cirach, M., Andrés, D., Ballester, J., Bartoll, X., e/transports/paris-mais-si-le-trafic-autour-des-voies-sur-berge-s-ameliore-18-02- Daher, C., Deluca, A., Echave, C., 2020. Changing the urban design of cities for 2018-7566675.php. health: The superblock model. Environ. Int. 134, 105132. Zafra, M. Á. M., Clemente Álvarez, Yolanda Clemente, Mariano, 2020, October 27. Nello-Deakin, S., 2019. Is there such a thing as a ‘fair’ distribution of road space? Carriles bici: la respuesta de las ciudades ante la pandemia. El País. https://elpais. J. Urban Design 24 (5). https://doi.org/10.1080/13574809.2019.1592664. com/clima-y-medio-ambiente/2020-10-27/carriles-bici-la-respuesta-de-las-ciudade Nello-Deakin, S., 2020. Environmental determinants of cycling: Not seeing the forest for s-ante-la-pandemia.html. the trees? J. Transp. Geogr. 85, 102704 https://doi.org/10.1016/J. Zhu, S., Levinson, D., Liu, H.X., Harder, K., 2010. The traffic and behavioral effects of the JTRANGEO.2020.102704. I-35W Mississippi River bridge collapse. Transp. Res. Part A: Policy Pract. 44 (10), O’Sullivan, F. 2020, November 11. Barcelona Will Supersize its Car-Free “Superblocks.” 771–784. https://doi.org/10.1016/j.tra.2010.07.001. Bloomberg.com. https://www.bloomberg.com/news/articles/2020-11-11/barcelona Zografos, C., Klause, K.A., Connolly, J.J.T., Anguelovski, I., 2020. The everyday politics -s-new-car-free-superblock-will-be-big. of urban transformational adaptation: Struggles for authority and the Barcelona Petzer, B.J.M., Wieczorek, A.J., Verbong, G.P.J., 2021. The legal street: a scarcity superblock project. Cities 99, 102613. https://doi.org/10.1016/j. approach to urban open space in mobility transitions. Urban Transform. 3 (1), 3. cities.2020.102613. https://doi.org/10.1186/s42854-021-00018-0. 2442