Tag: transport

Measuring Comparative Public Transport Accessibility for GB Cities

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Although Greater London has an extensive transit network, this is not the case for many UK cities where underinvestment and privatisation has seen bus, metro and rail networks stagnate in recent decades, falling well behind European peers. Improving public transport is an important aspect of addressing the UK’s regional inequalities and poor productivity, and is a prominent issue for the 2024 general election.

Accessibility measures are an ideal tool to gauge the comprehensiveness and efficiency of public transport networks – they describe the ease with which populations can reach key services by different travel modes. The leading UK urban thinktank, the Centre for Cities (see their new Cities Outlook report 2024), has been doing some accessibility analysis of English cities compared to continental European cities, and this was recently republished in the Financial Times in an article on productivity challenges-

Centre for Cities report (left); Financial Time article (right).

It’s great to see accessibility analysis feature in the media. The measure used above however has some serious problems leading to nonsensical results (e.g. does Manchester really have half the accessibility of Liverpool and Newcastle?). The Centre for Cities measure uses a single time threshold (30 minutes) when we know that accessibility varies considerably at different time thresholds. It is based on a single destination point, when cities can have multiple employment centres. And it describes accessibility as a percentage of all city jobs, which means that the smaller the urban settlement is, the higher the accessibility result will be using this measure. In reality, larger city-regions have better jobs accessibility.

Creating Robust Public Transport Accessibility Measures – R5R and PTAI-2022
We can create much better and more reliable accessibility measures for UK cities. There have been significant recent advances. The open source R5R software has solved many of the computational challenges for accurately calculating public transport accessibility, allowing the calculation of full travel matrices for all possible trips and handling accessibility variation over time. In the UK, Rafael Verduzco and David McArthur at the Urban Big Data Centre have taken this one step further and pre-calculated accessibility indicators for all of Great Britain at a range of time thresholds in their Public Transport Accessibility Indicators dataset. This dataset is calculated using R5R, and is based on the median travel time across a three hour travel time window, 7am to 10am on a typical weekday (Tuesday 22nd November 2021), and uses the latest public transport service datasets such as the Bus Open Data Service. The results are at LSOA scale for GB only (no Northern Ireland), based on census 2011 zones (so I have used 2020 population data in the below analysis).

Origin and Destination Accessibility Measures
This article focuses on jobs accessibility, and this can be analysed from either the perspective of trip origins (residential-based accessibility to jobs) or from the perspective of trip destinations (workplace-based accessibility by residents). Both perspectives are complementary, and are developed below. For residential measures, if we take the average accessibility for all residents in a city then we get a good overview of how extensive and efficient the public transport network is. This requires city boundaries to define all the residents in each city. The analysis below uses the Primary Urban Area geography.

Public Transport Jobs Accessibility Trip Origin Results
The table and chart below show average accessibility to jobs for residents in all major GB cities by three travel time thresholds- 30 minutes, 45 minutes and 60 minutes. London’s accessibility results are inevitably much higher than any other GB city, being around 3 to 4 times higher at all three travel times, and emphasising just how big the gap is between the capital and all other GB cities. The 30 minute threshold describes shorter trips, and identifies higher density compact cities where residents are on average closer to employment centres. Small compact cities such as Cambridge and Oxford score well at 30mins (though note this is not the case at 45 or 60mins). Edinburgh and Glasgow have the highest residential average accessibility outside of London at both 30 and 45 minutes. This is due to Scottish cities historically following a higher density European urban model, and maintaining better public transport networks by avoiding some of the worst effects of privatisation.

The 60 minute accessibility measure picks up longer distance commuting on regional rail and metro networks. This is where the strengths of larger city regions such as Greater Manchester and the West Midlands are highlighted, with Manchester second and Birmingham forth in the ranking (Glasgow is third and also has a large regional rail network). Given their large populations, Manchester and Birmingham should however be scoring higher in absolute terms and closing the gap on London. Both have poor accessibility for the shorter 30 minute accessibility measure, reflecting the need for further inner-city densification (as the Centre for Cities have argued). For longer commutes, Manchester and Birmingham metro networks should also continue to be extended regionally. Leeds scores relatively well at 30 minutes due to its medium-density urban core, but it lacks a metro and is behind Birmingham, Glasgow and Manchester for the longer commuting times.

Peak Public Transport Accessibility by Trip Destination
We can also analyse accessibility by trip destination, which produces similar results to the trip origin residential measure but is more from the perspective of employment centres. The table below shows the peak accessibility by workplace within each Primary Urban Area, which is a measure of labour market size and agglomeration potential for the UK’s largest city centres. London retains its huge advantage with this measure, at 3 to 4 times higher than the next best cities. City-regions with larger rail and metro networks score better with the peak destination measure, with Birmingham and Manchester ranked second and third respectively, exceeding 2 million people at 60 minutes. Cities with strong rail connections to London, such as Reading and Crawley, also score highly at 60 minutes, but have much lower accessibility at 45 and 30 minutes. Smaller compact cities such as Edinburgh and Cambridge rank much lower by the destination measure compared to the residential analysis.

Both the trip origin residential average accessibility measure and the trip destination peak accessibility measure provide useful perspectives. The residential average measure is a good summary of the coverage and extent of public transport across a city, and how likely residents are to use public transport modes. The trip destination peak accessibility measures employment centre labour market size, and summarises the total number of people that can reach city centres by rail and metro. This is a better measure of agglomeration potential and is more closely correlated with city-region size.

Mapping the Accessibility Results
We can also map the results to view the geography of accessibility to jobs. Firstly the trip origin accessibility to jobs measure. This emphasises how large the area of high accessibility is across Greater London, with parts of Outer London and the South East having higher accessibility to jobs than residents in the city centres of the next largest cities, Manchester and Birmingham. The Primary Urban Area geography is also shown, which is the basis of the residential average accessibility chart and table shown above.

Next we map the trip destination accessibility to population measure. This has a very similar geography, but with more of an emphasis on city centres, as we are measuring average accessibility on a weekday 7am-10am when there will be more commuting services going to, rather than from, central areas. Again London has a huge advantage, peaking at 7 million people. We can also see the centres of Birmingham and Manchester reaching accessibility levels above 2 million people, while Glasgow, Leeds, Newcastle and Liverpool exceed 1 million.

Conclusion- Open Data and Software is Available to Create High Quality Accessibility Measures
With software such as R5R (see this workshop for an intro) and the exemplary and easy to use PTAI-2022 dataset from the UBDC, it is easier than ever to produce accurate public transport accessibility measures. The comparative accessibility analysis of GB cities shown here has highlighted the huge accessibility gap between London and all other UK cities. It has also shown the generally better accessibility performance of Glasgow and Edinburgh, and the high regional accessibility of Birmingham and Manchester which contrasts with their weaker accessibility in these regions for shorter travel times, which supports inner-city densification. There is no single perfect accessibility measure that answers all questions we are interested in – this analysis has confirmed that variation at different travel times reveals contrasting patterns in local and regional accessibility; that average and peak accessibility in cities emphasise different aspects of transit networks; and that trip origin and trip destination measures provide complementary perspectives. We therefore need to test a range of measures to understand accessibility patterns.

Future Improvements
This has been a relatively quick demonstration of the PTAI-2022 data and there are several areas for further improvements-

Including European cities for comparison would be very interesting, as the Centre for Cities explored in their original analysis. A recent major paper in Nature has shown how accurate international accessibility comparisons can be done- https://www.nature.com/articles/s42949-021-00020-2.

The PTAI-2022 dataset is a really good tool that makes GB accessibility analysis much more straightforward for researchers. Currently it uses the 2011 census boundaries, and the next update should use the 2021 boundaries allowing the latest census data to be used. Additionally, the current PTAI-2022 release uses 2021 public transport data, and updating this with the latest rail and bus data would also be a useful update. A related issue is that reliability on UK public transport networks can be poor, and that timetables can overestimate transit accessibility. This topic has been analysed by Tom Forth in this blog post.

This analysis has used the Primary Urban Area geography, which is a useful description of GB city-regions, but there are some issues with PUAs due to the underlying local authority geography. A few PUAs for medium-sized cities have quite large hinterlands (e.g. Sheffield) and this lowers the average accessibility measured in these PUAs due to lower accessibility outside of the urban core. A more thorough analysis of accessibility would need to test multiple urban geographies and gauge the extent of Modifiable Areal Unit Problem variation.

Can the Green Belt be Developed Sustainably to Ease London’s Housing Crisis?

Posted in City Planning, Housing, London, Mapping, Sustainability, transport, UncategorizedTagged , , , , , , 2 Comments

The housing crisis in London has become increasingly severe in the last decade with much higher prices, rents, and largely static incomes, while housing development volumes have remained consistently below targets. Green Belt reform is often cited as a solution to boost development, though this has been off the agenda during the last 13 years of Conservative government. Recent announcements by the Labour leadership, supporting Green Belt reform and setting ambitious targets for housing development, could change this state of affairs with the general election coming in 2024.

This article analyses housing development in the London region from 2011-2022 (full CASA Working Paper here), using the Energy Performance Certificate Data. There is strong evidence that the Green Belt is a major barrier to development and is in need of reform. On the other hand, there are very substantial challenges around the quality and sustainability of new build housing in the South East. The analysis shows that, outside of Greater London, new build housing typically has poor travel sustainability and energy efficiency outcomes. Any release of Green Belt land needs to be dependent on travel sustainability criteria and improved energy efficiency for new housing. Sustainable housing outcomes are much more likely to be achieved through prioritising development in existing towns and cities and in Outer London.

London’s Housing Affordability Crisis
House prices in London doubled between 2009 and 2016, pricing out households on moderate and low incomes from home ownership, and translating into rent increases, longer social housing waiting lists, increased overcrowding and homelessness (see Edwards, 2016; LHDG, 2021). Price rises are linked to on the one hand to the financialization of housing (exacerbated by record low interest rates and Help to Buy loans in the 2010s) and on the other a long period of low housing supply, stretching back to the 1980s and the erosion of public housing.

The impact is record levels of unaffordability, with Inner London average house prices reaching £580k and Outer London £420k in 2016 (see chart below). The median house price to income ratio for Inner London soared from 9.9 in 2008 to 15.1 in 2016; for Outer London the ratio increased from 8.2 in 2008 to 11.8. In addition to high prices, first-time buyers have also been hit with record mortgage deposit requirements, with average deposits reaching £148,000 for Greater London, compared to around £10,000 in the late 1990s (Greater London Authority, 2022). Owner occupation is now effectively impossible in Inner, and much of Outer, London for low and moderate income buyers.

There have also been substantial increases in prices across the London region. The map below shows prices per square metre in the South East showing four radial corridors of high prices extending beyond Greater London into the Green Belt. East London is increasingly mirroring West London with two radial corridors of higher prices extending north-east and south-east from Inner East London. These are the primary areas of gentrification in London in the last decade (discussed in previous blog post), squeezing out what was the largest area of affordable market housing. There is also a distinct spatial alignment between London’s Green Belt boundary and higher prices, which is evidence of regional housing market integration, and that Green Belt restrictions are pushing up prices.

New Build Housing Delivery in the London Region
Greater London has struggled to meet its housing targets in the last decade. The current London Plan target is for 52k annual completions, which, as can be seen in the graph below, London is significantly short of. The 52k annual target has been criticised as being too low, with other estimates of housing need calculating that 66k or even 90k houses per year are needed (LHDG, 2021). Given the extremely high prices, affordable housing tenures are needed more than ever, yet affordable housing delivery has fallen in the 2010s (although note there has been progress in affordable housing starts in the last two years). Finally, the recent impacts of the pandemic and high interest rates have hit market housing activity, meaning that London will very likely continue to miss its overall housing targets for the next 2-3 years.

We can look in more detail at the geography of housing delivery at local authority level in the scatterplot below. There is high development in most of Inner London, and some Outer London boroughs. These boroughs contain Opportunity Areas (major development sites in the London Plan): Canary Wharf in Tower Hamlets; the Olympic Park in Newham; Battersea Power Station in Wandsworth; Hendon-Colindale in Barnet; Wembley in Brent; Old Oak Common-Park Royal in Ealing; and Croydon town centre. Given that there are only a few Opportunity Areas in Outer London, this leads to relatively low delivery in most Outer London boroughs, and points to the need for a wider strategy for Outer London development.

Meanwhile, there is low development activity in nearly all Green Belt local authorities, much lower than London boroughs and also below the average for the rest of the South East. Green Belt restrictions affect both local authorities in the commuter belt and also Outer London boroughs as well (e.g. Enfield, Bromley) with 27% of Outer London consisting of Green Belt land. We can confirm how rigidly Green Belt restrictions are being applied using the official statistics, which calculate that the London region Green Belt land area was 5,160km2 in 2011 and 5,085km2 in 2022 (DLUHC, 2023). Therefore, only 74km2 or 1.4% of Green Belt land was released over the decade (this figure is for all development uses, not only housing), which is strong evidence of minimal change.

One final impact of the Green Belt can be seen by mapping development in the last decade as shown below. In addition to the patterns of high development in Opportunity Area sites, and generally low development in the Green Belt, there is a ring of high development activity just beyond the Green Belt boundary. This ring includes dispersed car-dependent development in semi-rural areas, and the expansion of medium-sized towns and cities such as Milton Keynes and Reading. This pattern looks very much like Green Belt restrictions are pushing development beyond the Green Belt boundary, creating sprawl-type patterns in several authorities. One important caveat is that several South East cities have strong economies in their own right, particularly technology industries in the Oxford-Milton Keynes-Cambridge arc, creating local development demands in addition to London-linked demand.

Potential for Green Belt Reform
With Greater London consistently falling short of housing targets, reform of the Green Belt has been cited as a promising solution (see for example Mace, 2017; Cheshire and Buyuklieva, 2019). The release of Green Belt land could greatly boost development and ease prices. Green Belt reform could also be a substantial source of revenue for austerity-hit local authorities, if authorities are given the powers to purchase Green Belt land at current use value and benefit from the land value uplift (this is part of the Labour proposals).

Traditional objections to Green Belt development focus on rural land preservation. Yet the Green Belt is massive in scale – 12.5% of all the land in England is Green Belt. London’s Green Belt is 5,085km2, or three times bigger than Greater London. Medium density housing development would take up a small proportion of this land. For example, building 100k dwellings at a gross density of 40 dwellings per hectare would add up to 25km2, or less than 0.5% of the London region’s Green Belt. Appropriate Green Belt reform could simultaneously allow for a moderate increase in development and improve environmental aspects of the Green Belt – the current environmental record of the Green Belt is mediocre on key measures such as biodiversity – through green infrastructure funding and principles of Net Biodiversity Gain. The land preservation arguments against Green Belt development do appear to be solvable. There are however further sustainability impacts from housing development to consider, including transportation and housing energy impacts, as discussed below.

Sustainability Impacts- Travel
Transport is the largest source of GHG emissions in the UK – 26% of all emissions in the latest 2021 data (DBEIS, 2023). The route to Net Zero requires both the electrification of transport systems and a significant mode shift from private cars to public transport, walking and cycling (HM Government, 2021). Greater London is a UK leader in sustainable travel, but this is not the case for the wider London region, much of which is car dependent. The analysis here uses car ownership and commuting mode choice data from the 2021 census to create a Travel Sustainability Index, as shown in the table below, which classifies Greater South East residents into 6 travel classes of around 4 million people. The South East covers a very wide range of travel behaviours, from an average of 20% commuting by car and 62% zero car households in the most sustainable class 1; to as high as 87% car commuting and 6% zero car households in the most car-dependent class 6.

Travel Sustainability Classes Average Statistics (2021 Census data)

Travel Sustainability ClassTravel Sustain. IndexCar
Commute %		Public Transport Commute %Walk & Cycle Commute %Car Owning Households %Residential Net Density (pp/km2)Total Pop. in South East
145-8220.348.526.438.351.5k3.56m
230-4541.633.220.961.532.1k4.03m
321-3060.618.117.674.725.0k4.03m
415-2171.610.914.283.320.2k4.16m
510-1580.06.510.989.416.4k4.34m
61-1087.33.66.794.111.1k4.29m

Mapping the travel sustainability classes highlights the stark travel behaviour differences between Greater London and the wider region. The Inner London population-weighted average travel sustainability score is 51.6 (class 1), and Outer London is 32.1 (class 2). The Green Belt is overwhelmingly in car dependent classes 4 and 5, with an overall population-weighted average of 16.4 (class 4). The Rest of the South East has a population-weighted average score nearly identical to the Green Belt at 16.5, emphasising the disappointing levels of car dependence in the Green Belt despite its rail infrastructure and proximity to London.

The patterns shown in the above map clearly present a challenge for Green Belt development, as new housing in the wider region risks extending patterns of car dependence. Car dependent areas include some locations next to rail stations (proximity to rail stations has been advocated as a criteria for prioritising Green Belt land for housing). We can directly measure the travel sustainability of housing development from the last ten years by matching the output areas locations of new housing to the Travel Sustainability Index scores. This is shown in the scatterplot below, where Inner London boroughs score highly with this measure, followed by Outer London. Much of the housing development in the wider region scores poorly in terms of travel sustainability, including in areas with high housing development such as Bedfordshire and Milton Keynes.

Although travel sustainability is generally low in the wider region, there are trends identifiable in the above results that can be used as basis for guiding more sustainable development. Several towns and cities show moderately sustainable travel outcomes, including the Green Belt towns Luton, Watford, Guildford and Southend, and wider South East towns and cities Brighton, Reading, Oxford, Cambridge, Portsmouth, Norwich and Southampton. Generally, development in existing towns and cities is likely to be more sustainable than developing smaller settlements and more dispersed rural areas. There are also noticeably better results in active travel-oriented cities such as Brighton and Cambridge. Overall, if we want Green Belt housing development to minimise travel sustainability impacts, then it would be most realistic to achieve this by extending existing towns and cities, both within the Green Belt and in the wider South East. Promoting development in Outer London boroughs also looks to be an efficient strategy given generally good travel sustainability levels in Outer London, and that Outer London is 27% Green Belt land.

Sustainability Impacts- Energy
Another important sustainability impact of new build is energy use and carbon emissions resulting from space and water heating, which we can estimate from the Energy Performance Certificate data as shown below. CO2 emissions per dwelling are considerably lower in Inner and Outer London, with overall London emissions per dwelling around two thirds of the value for the Green Belt and Rest of the South East. This is only partly due to smaller dwelling sizes, as CO2 emissions per square metre in London are significantly lower as well. The lower emissions in London housing can be explained by the much higher proportion of flats and also the use of community/district heating, with three quarters of all new build in Inner London and 47% of new build in Outer London connected to community heating networks. The community heating approach is only efficient for high density developments. For medium and lower density developments, air and ground source heat pump technologies are a key technology for improving energy efficiency and replacing gas boilers. The statistics from 2011-22 are very disappointing on this front, at 4% of new build with heat pumps in the Green Belt and 6% in the Wider South East.

New Build Annual Average CO2 Emissions and Energy Summary 2011-2022 (Data: EPC 2023)

SubregionCO2 per Dwelling
(tonnes)		CO2 per m2 (kg)Energy Consumption
(kWh/m2)		Community
Heating %		Heat Pump % (air + ground)
Inner London0.9312.972.975.22.7
Outer London1.0415.387.246.92.8
Green Belt1.6018.7106.97.93.5
Rest of South East1.5317.297.75.75.9
All Subregions1.3416.392.527.04.3

The average annual CO2 emissions by dwelling are summarised at the local authority level in Figure 19 (note y axis starts at 0.5). Similar to the travel sustainability results, London boroughs have considerably more sustainable results. Town centres in the South East again are the best performing outside of London, including Cambridge, Southampton, Eastleigh, Reading, Luton, Watford, Woking and Dartford. As the chart shows average CO2 per dwelling, there is a connection between affluence and dwelling size, with higher income boroughs such as Richmond Upon Thames and particularly Kensington and Chelsea, having high emissions. Overall however, energy efficiency is much better in London boroughs and this is a further challenge for the sustainability of Green Belt development. Similar to the travel sustainability analysis, the results point to the extension of existing towns and cities, and Outer London development, as the most sustainable development strategies.

Summary
There is a widespread consensus that London needs to build more housing to meet demand and try to reduce record levels of unaffordability. Yet London has been consistently short of meeting housing targets for the last decade, despite substantial growth in Inner London. Green Belt restrictions do appear to have played a major role in constraining development, with low levels of new build in Green Belt local authorities, and in Outer London boroughs with extensive Green Belt land. There is also a significant price premium in Green Belt areas compared to the wider South East.

This analysis agrees with research advocating Green Belt reform. Travel sustainability conditions are needed to avoid this reform producing highly car dependent housing, such as has been occurring in Central Bedfordshire and Milton Keynes (where the East-West should have been built much earlier). Pedestrian access to rail stations is a sensible starting point for prioritising Green Belt land for housing, but it is not sufficient to produce sustainable travel outcomes in the Green Belt. The aim should be for new housing to have local access to a range of services (e.g. retail, schools), providing sustainable travel options for multiple trip types. Another related issue is the need for more sustainable energy efficiency measures in medium density new build housing. There is little evidence in the EPC data for adoption of key housing technologies such as heat-pumps and solar PV. Widespread adoption of these technologies is needed for sustainable development at scale in the Green Belt. Other studies have also identified poor design and planning in new build housing in the UK (see Carmona et al., 2020), and this needs to change as part of any plan to increase the volume of new housing.

Green Belt reform would have to come from national government, changing the very restrictive current National Planning Policy Framework to allow authorities with housing shortages to develop Green Belt land of low environmental quality near services, and to use land value uplift to fund services and affordable housing. It would be logical to give powers to the GLA (and other combined authorities) for the strategic coordination of this development within their boundaries, given the GLA’s strong track record on sustainable housing delivery. It is difficult however to envisage large scale change happening in the South East without national government also organising improved regional coordination and planning. This analysis identifies better travel sustainability outcomes for new build in larger towns and cities in the South East, and supports the urban extension model for development in the Green Belt. There are many candidate towns in London’s Green Belt for urban extensions, including Luton, Guildford, Watford, Maidenhead, Hemel Hempstead, Chelmsford, Basildon, Reigate and Harlow. This larger scale solution is politically more challenging, and would again require leadership and coordination from national government.

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Read the full CASA Working Paper.

This research is part of the ESRC / JPI Europe SIMETRI Project.

Post-Pandemic Changes in Travel Behaviour: Evidence from the National Travel Survey England 2021

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The pandemic and subsequent lockdowns have seen the largest and most sustained disruptions to travel behaviour in most of our lifetimes. Stay-at-home policies have fuelled a dramatic increase in remote working, and wider online substitution of other activities such as shopping and socialising. In sustainability terms, the pandemic has severely hit public transport and incentivised car travel, but has also likely reduced travel distances overall as well as encouraging new patterns in active travel. The big question is to what extent pandemic related changes are turning into longer term shifts in travel behaviour patterns.

This post looks at timeseries travel data across the last three years, and then summarises results from the recently published National Travel Survey data 2021 for England, with a particular focus on trip purpose and differences between London and England as a whole.

Transport Use Timeseries Data from DfT
The Department for Transport have continually updated a very useful timeseries on how busy different transport modes have been in England throughout the pandemic. This index integrates many different datasets and is intended as a broad summary of trends (see methodology here). The graph below summarises this data, which is indexed to February 2020. The overall picture is of huge disruption in 2020, continued disruption with a transition towards recovery in 2021, and then what looks like settling into a new normal in 2022.

The chart paints a mixed picture in sustainability terms. Car travel has been the fastest transport mode to recover after each of the national lockdowns, and was back to near normal levels as early as summer 2021. While this is a challenge going forward, it could potentially have been worse. The pandemic could have resulted in substantial increases in car travel. Instead, there is a minor reduction to about 96% car use in the DfT data, sustained into 2022 (in per-capita terms this reduction will be more substantial given population increases). Note the motorised vehicle index that includes freight reaches 100% of pre-pandemic levels in 2022, possibly due to more online delivery traffic.

Public transport has been much slower to recover, falling to less than 50% of passenger numbers in 2020, increasing substantially throughout 2021 and then settling around 70-85% of pre-pandemic passenger numbers in 2022. Rail and tube travel were hardest hit in 2020 due to the widespread fall in commuting and these modes have taken longer to recover than bus travel. It is difficult to gauge whether public transport levels have now levelled off around the 75% level, or will continue to recover further in 2023 (the rail and tube strikes in summer 2022 may have curtailed further increases).

A positive sustainability story comes from the cycling data from the DfT. This is a less reliable metric, but nonetheless indicates growth in active travel, albeit from a low base in 2019. The annual variation in cycling in the DfT data between 2020 and 2022 is interesting. The initial 2020 increase in cycling makes sense, as there was a big growth in active travel for households locked down in their local area. This falls to 2019 levels in 2021, and then rebounds in 2022. Perhaps the fall off in new cyclists has given way to more practical longer term adoption of cycling in 2022.

National Travel Survey Data 2021
The results for the National Travel Survey 2021 data were released at the end of August 2022. This long running survey records full travel diaries of thousands of residents in England, allowing analysis of topics such as trip purposes, walking trips and demographic analysis. There have been some data gathering challenges during the pandemic (see data quality report). The overall picture from the DfT chart below is that the 2021 NTS data is very similar to the 2020 data in terms of per person trips and annual distance recorded. This suggests that the NTS 2021 is not picking up much of the 2021 travel recovery that is shown in the DfT timeseries data we discussed above.

We can break down the annual trip distance per person by transport mode. The chart below compares the years 2019, 2020 and 2021. The results backs up the conclusion that, at the national level, the 2021 data is very similar to 2020. There is big reduction in car miles of 30%, while public transport levels are at around half the levels of 2019. There is a small increase in walking and cycling distances, though this falls back to 2019 levels in 2021.

Interestingly, the equivalent chart for London shows a very different picture in terms of travel behaviour responses. Car use increased marginally in 2020 (probably substituting for public transport trips) then falls in 2021, though this reduction is lower than the national picture. Bear in mind London mileages are around a third of the national average, so there may be fewer optional trips to cut. Meanwhile, public transport records a significant recovery in 2021 for rail and underground, much closer to the DfT time series analysis shown above (note the bus recovery is lower than expected). Walking and cycling follows the national picture by increasing in 2020 and then falling in 2021, though note that the 2021 cycling level is substantially up on the 2019 figure.

Overall the broad 2021 National Travel Survey results are fairly close to the 2020 results at the national level. In comparison to the DfT Transport use timeseries, it appears to be closer to the 2020 picture rather than the 2022 trend of a substantial recovery in transportation use. So we may have to wait for the National Travel Survey 2022 to confirm which changes are really sticking in terms of longer term behaviour. The London data is interesting, as it much more clearly shows a recovery in public transport travel in 2021, and a different picture for changes in car mileage, as well as a substantial increase in cycling.

Trip Purpose Analysis
An important question is the type of trips most affected by the pandemic, and whether these changes are becoming longer term trends. The charts below show the trips per person per year and total distance per year between 2019 and 2021. As expected commuting is taking the biggest hit in terms of trips and distance, falling by 36% in distance terms and with only small signs of recovery in the 2021 NTS data. Drops in business travel are even larger, more than halving. Interestingly shopping trips have taken nearly as big a hit as commuting, with distances falling 26%. There has been a widespread trend towards online supermarket deliveries and online shopping more generally post-pandemic and it looks like this behaviour has continued into 2021. The 2021 NTS even shows shopping trips and distances falling again in 2021 from the 2020 level. Alongside commuting changes, shopping travel behaviour looks to be the major trip type that has been cut, possibly for the longer term.

Outside of commuting and shopping, other trip types with big reductions include holidays, business, and entertainment. In contrast day trips increased and walking trips nearly doubled (though both fell back marginally in 2021 from the 2020 peak). Visiting friends at their home also continued during the pandemic, with a more minor reduction in trips and distances.

Finally we repeat the distance trip purpose chart for London. Commuting takes an even bigger hit in London, falling by 48% in 2020, then moderately picking up in 2021. Business trips fell by a huge 67% and there is little sign of recovery. In contrast some trip types that declined in 2020 are nearly back at 2019 levels, such as education and education/other escort trips. The trips with the biggest increases in 2020, visiting friends at private homes and day trips, have also returned to their 2019 levels in the 2021 data. Walking trips have however remained considerably above their 2019 level, indicating that the active travel increase is looking more stable for London.

Summary

The DfT timeseries data shows travel patterns settling into a ‘new normal’ after more than two years of disruption. Car travel is only marginally down on pre-pandemic levels, while public transport is around 70-85% of the passenger numbers from 2019. There are some encouraging signs for active travel after increases in leisure walking and cycling trips, though the situation is dynamic.

The National Travel Survey 2021 data records a similar picture overall to 2020 in terms of major disruption- distances and trips down substantially. Car miles are down 30%, though the DfT timeseries data suggests this will not be the case in the 2022 data. Public transport remains around half of 2019 levels.

The trip types with the biggest reductions are commuting and business as expected, but also shopping (and the related travel type of personal business). Shopping trips fell again in 2021, and this looks, like commuting, to be a case of significant online substitution, possibly long term.

The London NTS data is very interesting, with some significant differences. Car use appears to have marginally increased in London in 2020, before falling in 2021 below 2019 levels. Public transport has staged a major comeback in London in the 2021 data, and there is also a sustained increase in cycling. The NTS data is also disaggregated into urban/rural categories and it would be interesting to test whether these trends are London specific or shared with other major English cities.


A Compact City for the Wealthy? Continuing Inner London Gentrification and Impacts on Accessibility Inequalities

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We have a new paper out in the Journal of Transport Geography- “A compact city for the wealthy? Employment accessibility inequalities between occupational classes in the London metropolitan region 2011“. The paper explores how the increasingly affluent nature of Inner London has improved sustainable travel opportunities for more affluent professional and management classes, while less affluent groups have increasingly been priced out to lower accessibility Outer London locations.

The Continuing Gentrification of Inner London
The gentrification of Inner London was first recorded by Ruth Glass back in the 1960s, with middle class residents moving into largely working class neighbourhoods as London’s economy began its long evolution from manufacturing towards service jobs. This process has continued for decades, ultimately transforming most of Inner London. In the 21st century, some researchers have argued that gentrification has stalled (perhaps because there are few neighbourhoods left to gentrify) or has entered a different phase (e.g. processes such as super-gentrification and new-build gentrification as discussed by Davidson and Lees).

This research uses the Standard Occupational Class data as the basis of measuring social class. This classification was found to correspond to differences in income, as well as to a distinct residential geography. In particular, the three most affluent groups (Management, Professional and Associate Professional) cluster together, resulting in the social geography we can see in the map below using the 2011 Census data. There is a clear clustering of professional classes in Inner-West London, with two prominent radial corridors extending northwards through Camden, Islington and Hampstead; and south-westwards through Kensington, Wandsworth and Richmond. Concentrations of non-professional groups are mainly in Outer London to the east, north-east and west, with only smaller pockets remaining in Inner London. This analysis largely matches the description of Inner London now being dominated by professional classes, with lower income groups increasingly in Outer London (with some exceptions remaining in Inner East and South-East London).

Professional Classes (Manag., Prof. & Assoc. Prof.) Residential Percentage 2011. Data: Census 2011 (Office for National Statistics, 2016).

As well as mapping the 2011 geography of occupational class, we looked at more recent changes to see if gentrification is continuing or has slowed, using the ONS Annual Population Survey. Analysing changes between 2006 and 2016, we found had substantial gentrification had continued in Inner London, as shown in the table below. The Management, Professional and Associate Professional groups all grew as a proportion of the Inner London population, while all other occupational classes fell proportionally (green cells are above the average for the metro region, and orange cells are below the average). Interestingly, the biggest growth was in the Management and Professional classes, rather than the younger Associate Professional class, arguably more in line with super-gentrification processes. In contrast, there are proportional increases in several lower income classes in Outer London.

Sub-Regional Occupational Class Percentage Point Change by Residence 2006–2016 (final 2016 sub-regional percentages in brackets)

We can also explore these changes at the more detailed level of local authorities, and show that even more dramatic changes are occurring at the local level. In the chart below, each Local Authority is shown as a trajectory connecting its position in 2006 to its position in 2016 in relation to the percentage of professional classes and the total working population. Generally, Inner Greater London Authority (GLA) boroughs experience high working population growth combined with large increases in the proportion of professional classes. Boroughs with a long history of gentrification, such as Camden and Islington, are higher up in the chart reaching 70% professional classes, while more recent gentrifiers, such as Lewisham and Southwark, are rapidly gentrifying from a lower base. Outer GLA boroughs also show substantial population growth but with lower levels of change in professional classes, and decline in some cases. The exceptions are mainly in South and South-West London, with Croydon, Sutton and Richmond all gentrifying. Outer Metropolitan Area (OMA) local authorities have a mixed picture, with some increases in professional occupational classes with minimal working population growth; while some lower income towns such as Luton and Harlow are not gentrifying.

Local Authority Trajectories for Combined Percentage of Professional Occupational Classes and Total Working Population for 2006 and 2016. Data Source: Annual Population Survey 2005–2017.

What Impacts Does Inner London Gentrification have on Accessibility to Jobs?
We would expect that the dominance of more affluent classes in Inner London translates into accessibility advantages for these classes, as Inner London has substantially better accessibility opportunities by public transport, walking and cycling. We were particularly interested in accessibility by more affordable travel modes in this research. Bus travel is in general considerably cheaper than other public transport options in London. This is reflected in higher rates of more affordable bus and walking trips by lower income classes in the 2011 Census data. We can see in the table below that the three lowest income classes (6, 7 & 9) have around three times higher rates of bus travel and two times higher rates of walking than the most affluent three classes (1, 2 & 3)-

We used network analysis to analyse accessibility differences (see working paper on accessibility model). The analysis was carried out using the 2011 census data. The box plot below shows the cumulative accessibility to jobs for 60 minutes travel by Car, Public Transport (all modes) and Bus Only for the occupational classes. We can see differences between classes, particularly for public transport and bus trips, though there is also much variation within each class.

GLA 60mins Cumulative Accessibility to Employment by SOC Groups: Absolute Results

The accessibility differences between occupational classes can be more clearly seen by plotting differences between how the average accessibility for each group varies from the average accessibility for the entire working population, as shown below. Note in this chart the accessibility differences are normalised by travel mode, so the differences between travel modes in the chart above are normalised in the chart below. We can see clear consistent accessibility advantages for the top three occupational classes, particularly for more affordable slower modes- walking and cycling. The remaining occupational classes have below average accessibility to jobs, particularly for the more car oriented Skilled Trades and Process groups.

Greater London Authority 60mins Cumulative Accessibility to Employment by SOC Groups: Relative Differences in Occupational Class Mode Means and Mode Means for Total Population

The results for bus and walking modes is a particular accessibility challenge. Accessibility by these more affordable modes is generally low in absolute terms outside of Inner London. For the bus mode, less than half the number of jobs are reachable at typical commute times compared to the full public transport network. Given that lower income groups are the most frequent bus and walking commuters, and that these classes are increasingly being priced out of Inner London, these limitations are a significant accessibility challenge going forward.

What Policies Can Planner follow to Mitigate this?
In terms of transport policy, this research supports efforts to improve the affordability and connectivity of public transport for lower income populations. This is indeed a priority of the current London Mayor Sadiq Khan, who has committed to freezing public transport fares, and has reformed ticketing to allow multiple bus journeys on a single fare. These measures help offset travel costs for lower income residents in Outer London.

The main policy conclusion is the importance of housing policy in influencing accessibility outcomes in the study area. Low and moderate income groups are being priced out of public transport accessible areas. Without a step-change in the delivery of genuinely affordable housing in accessible locations, the increasing dominance of Inner London by professional classes will continue, resulting in greater accessibility inequalities, and likely increased travel costs for lower income classes.

Note on Covid-19 and Travel Inequalities
This research was completed in 2019, before the recent COVID-19 pandemic. The pandemic has in the short term shut down public transport networks, and greatly disadvantaged millions of city residents around the world. Longer term it is possible that the pandemic will reduce the attraction of inner city areas such as Inner London, due to perceived risk of future pandemics as well as the acceleration of telecommuting and home-working trends. The overall effect could be to slow gentrification processes, although this is difficult to predict. The alternative view is that  London will recover and adapt as it has done following many crises in the past. East Asian metropolises offer a good model of how to built resilience following their response to the earlier SARS and MERS outbreaks.

The wider economic impacts are clearly also important. Certainly we are in line for a very large recession, hitting important sectors such as tourism and hospitality. More specifically in London, the recession may hit development viability for affordable housing, and is a real headache for public transport operators. Transport for London was in financial trouble before the crisis, and is currently dependent on government bailouts to keep running. This will likely curtail the ability of the Mayor to maintain lower public transport fares, and so impact the kind of transport accessibility inequalities this paper discusses.

 

 

 

Global Prospects for a Post-Car World

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Earlier this year I worked on some charts and maps for a Greenpeace report authored by sustainable transport academic Robin Hickman, exploring the impacts of automobile dependence and the prospects for a post-car world. The report is online here.

The much debated phenomenon of ‘peak-car’ can be observed in many countries in the global north,  in terms of a levelling off of private car use and increases in public transport, as shown in the graphs below. Many theories have been put forward to explain this trend, from the growth and densification of cities, to economic crises, fuel tax changes, to declining car use by younger demographics, and behavioural changes related to the internet. Given the many negative impacts of automobile dependence, from substantial GHG emissions, to air pollution, millions of road deaths annually, and contributions to the global obesity epidemic, clearly this behavioural trend is a great opportunity to develop more sustainable city forms much more widely across the globe.

This process is also observable at the level of individual cities, using data compiled by Newman and Kenworthy. Unfortunately this data is only available up to the year 2000.

The picture is of course different for newly industrialised countries, many of which are experiencing substantial growth in car ownership. I mapped data on vehicle sales, highlighting rapid growth in China and in Asia more generally, compared to static and declining markets in Europe and North America-

Thus the global sustainability challenge is to accelerate peak-car trends in the global north, and to try to curb the mistakes of automobile dependence being repeated in the developing world. Note that while the chart above suggests that the global south is increasingly responsible for GHG emissions, the picture from per-capita emissions is quite different as shown below, with the highest per-capita emissions in North America, the Middle East and Australia-

What can the next mayor do to tackle London’s hazardous air pollution?

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If news emerged that a virus was killing thousands of vulnerable Londoners every year then there would justifiably be public alarm, followed by swift political action. Yet the impacts of this imaginary scenario are similar to what air pollution has been inflicting on Londoners for many years, while the political response has been slow. According to the most up-to-date and comprehensive research, air pollution reduces Londoners’ life expectancy equivalent to the death of 9,400 people of average age every year (5,900 due to NO2 and 3,500 due to PM2.5) as well as exacerbating respiratory diseases in vulnerable populations. Despite the severity of these impacts, it has become standard practice over the last decade for national government and the London Mayor to gloss-over the problem, downplay continued breaches of European law, and for politicians to delay taking any significant responses.

The current London mayor, Boris Johnson, has been slow to face up to the challenge. His tenure began by removing the western extension to the Congestion Charging Zone, thus increasing vehicle numbers in Inner West London, and opting out of using the Congestion Charge to tax the most polluting vehicles. This would have boosted the adoption of hybrid and electric vehicles (still only a meagre 1% of new cars) and reduced heavy emitters in Central London. Furthermore Johnson has not succeeded in comprehensively upgrading London’s bus and taxi fleet to hybrid and electric vehicles, instead embarking on an expensive new Routemaster project which still produces substantial emissions and currently makes up a minority of the overwhelmingly diesel bus fleet.

NO2 Annual concentration in London 2010, modelled by the London Atmospheric Emissions Inventory. All of Inner London and many major roads in Outer London greatly exceed the EU limit.
NO2 Annual concentration in London 2010, modelled by the London Atmospheric Emissions Inventory. All of Inner London and many major roads in Outer London greatly exceed the EU limit.

As recently as 2014, Johnson was still playing down the air pollution problem, in the face of strong evidence of London’s busiest streets like Oxford Street having amongst the highest concentrations of nitrogen dioxide in the world. For much of his time as mayor, he has assumed that the issue is not a public priority, and that driver and transport demands trump health concerns. This approach looks more questionable by the day. Evidence continues to mount that air quality is comparable in its health impacts to passive smoking and obesity. The consequences of the current Volkswagen scandal are still emerging as the huge gap between the advertised environmental performance of diesel vehicles and what we are really breathing in our cities is revealed. And the full costs of poor air quality are only beginning to be counted (e.g. billions of pounds added to NHS bills).

Looking to the future, London must now tackle the air pollution problem with a new mayor in the upcoming 2016 elections. The scope for change looks positive, as the main candidates on both the left and right have been openly discussing the need for change. What then could a new mayor do to address air quality and improve the health of Londoners?

Pricing Out Polluting Vehicles with the Ultra Low Emission Zone
To be fair to Boris Johnson, he did finally respond to pressure and announce a significant air pollution policy in 2013, dubbed the ‘Ultra-Low Emissions Zone‘. The ULEZ is set to come into effect in 2020 and essentially uses the Congestion Charging infrastructure to tackle the most polluting vehicles (similar to what Livingstone proposed way back in 2006). The question is whether the ULEZ goes far enough. It’s based on Euro emission standards, which measure NO2 and PM10/2.5 as well as CO2 emissions. It correctly targets diesel vehicles, requiring them to meet the Euro 6 standard, which only came into force in September 2015, so almost all current diesels on the road would have to change or pay the charge. This means that the main source of NO2 emissions will be appropriately targeted.

The current Congestion Charge boundary will be the basis of the Ultra Low Emissions Zone (map by TfL).
The current Congestion Charge boundary will be the basis of the Ultra Low Emissions Zone (map by TfL).

There are limitations however. The charge is only going to be £11.50 (except for large buses and HGVs), so it likely many diesel users will continue to drive into Central London and pay the charge. Furthermore the ULEZ will only affect Central London; the rules on diesel taxis and private hire vehicles have not been decided; and ULEZ zone residents get an overly generous exemption until 2023.

The next mayor will have a number of options that could be pursued if they want to be bolder than Johnson’s ULEZ proposal. These include increasing the ULEZ charge and/or Congestion Charge, bringing the ULEZ implementation forward to an earlier date, and potentially reintroducing the Congestion Charge Western Extension. All of these would make significant improvements to air quality, but would be controversial with drivers, many of whom were mis-sold diesel vehicles in the past as a supposedly environmentally benign option. The mayor may also want to re-examine the wider Low Emission Zone (LEZ) that tackles very polluting vehicles entering the whole of Greater London, as this affects the entire city and has not changed since 2012.

Euston Road, one of London's busiest and most polluted routes with NO2 annual concentrations typically twice the EU limit (photo by D Smith).
Euston Road, one of London’s busiest and most polluted routes with NO2 annual concentrations typically twice the EU limit (photo by D Smith).

Banning Diesel?
A more radical approach currently being proposed for Paris is to ban diesel cars all together. This would certainly make a huge improvement to air quality. The problem for London would be that the city’s bus and taxi fleet would fail this restriction, and there would likely be a backlash from thousands of car and van drivers. This would be a very confrontational approach for a new mayor.

The more pragmatic solution for London would be to work with the ULEZ framework, considering stricter measures and higher charges, and implementing the policy earlier. One very important issue for the new mayor is emerging from the current Volkswagen emissions scandal. It looks like the latest Euro 6 diesels produce significantly higher NO2 emissions in real world driving conditions compared to the misleading testing conditions. If this is the case then the proposed ULEZ will be much less effective in improving air quality (as Euro 6 diesels will be exempt from the charge). The ULEZ may have to charge all diesel vehicles, regardless of their Euro rating. This decision would need to made very early, so that there is sufficient time for car users to adjust behaviours accordingly.

Pedestrianising Streets and Upgrading the Bus Fleet
Oxford Street is London’s busiest pedestrian street and has some of the worst NO2 pollution in Europe. A response that is gaining popularity is to pedestrianise the whole street. Certainly this would be an iconic change to both the image of London, and to the experience of the city for thousands of Londoners and tourists. The challenge for this measure is avoiding creating bus jams at either end of Oxford Street, and handling the extra demand levels that would be placed on the already congested Central Line. These challenges are not necessarily permanent however, as the arrival of Crossrail in 2018 (which follows the west to east Central Line route through Inner London) has been described as a ‘game changer’ that makes pedestrianising Oxford Street a realistic option. The new mayor should certainly pursue this possibility.

The wider challenge for the mayor is not to just think about Oxford Street, but to accelerate the upgrading of the entire bus and taxi fleet towards zero emission vehicles and develop wider pedestrianisation policies. This would improve air quality for all of London’s high streets. London is still at the trial stage of pure electric double-decker buses, which represents disappointingly slow progress considering how long we have known about air pollution problems. There’s been better progress on electric/hydrogen single-deckers. Considerable investment will be needed to upgrade the bus fleet, with decision-making based on real evidence and value-for-money. Johnson’s Routemaster project has failed both these criteria, and better leadership is now required.

Heathrow Third Runway
All the main candidates for the London Mayor oppose the expansion of Heathrow, with air pollution alongside noise pollution amongst the most important factors. You can see how Heathrow already dramatically increases emissions in West London in the NO2 annual concentration map at the top of this article using the London Atmospheric Emissions Inventory data. This is due both to emissions for aircraft engines, and the thousands of cars driving to and from Heathrow everyday. The challenge will be how effectively the new mayor can challenge the UK government to reject the Heathrow expansion option.

Overall, the issue of air pollution has gained unprecedented prominence as we approach the 2016 mayoral elections. The main candidates need to respond accordingly in their manifesto commitments, with London having a lot of catching up to do after eight years of little change. It will be interesting to see which candidates are prepared to be bolder.

 

 

 

 

Animating Global Innovation Diffusion- Public Transport

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UndergroundWorldMap

We know that knowledge networks and intensive competition within cities boosts innovation. There are also further scales to this dynamic. The networks and competition between cities at regional and global scales promotes the adoption of new ideas- as cities buy, borrow and adapt ideas from their competitors. It’s this latter global dynamic that we’re exploring in this post, investigating the spread of new ideas in a sector that’s intrinsically urban in nature- public transport. After widespread decline in the second half of the 20th century, transit has recently undergone an impressive renaissance linked to the dramatic growth of urban populations, high density forms and sustainability policies.

The spread of new ideas between cities is clustered in space and in time, as cities are strongly influenced by nearby competitors, as well as economic investment cycles. Therefore a natural way to visualise these spatial and temporal patterns is through animated cartography. This is the technique used here with the help of Processing and the MapThing library by Jon Reades (allows GIS data to be imported into Processing).

So first up we’re going to head back in time to the invention and dispersion of the underground/subway metro (data from metrobits.org; best viewed HD fullscreen)-

London celebrated 150 years of the Underground this year, and it was three decades after 1863 before other cities in Europe and North America had their own high-frequency high-capacity city centre networks. This delay can be linked to varied levels of industrialisation between countries, as well as the time taken to improve the metro concept with electrical power (the original Underground amazingly used steam locomotives). It’s interesting that the youthful American metropolises of Chicago and Boston were quicker off the mark to build metro systems than many European capitals.

Buenos Aires in 1913 and Tokyo in 1927 (now the world’s largest metro) were early exceptions to the European and North American monopoly on metro systems. Yet it took until the 1980’s onwards with the rise of Newly Industrialised Countries like Brazil, Russia, India, Mexico and Turkey for metro systems to become truly global. China is now in a league of its own with gigantic metros in Shanghai, Guangzhou, Beijing and Hong Kong.

Underground metros may seem like the best answer to cities’ transit demands, but they are highly expensive and disruptive to build, and are pricey to maintain also. These difficulties underlie another key innovation in the global rise of public transport- bus rapid transit. The use of segregated roads, specially designed stations and articulated buses enables BRT to have similar capacity and speed advantages of subways at a much lower cost. We can see from the animation that BRT begins as a Brazilian innovation (data from brtdata.org)-

Initially BRT adoption is highly clustered in Brazil’s major cities, with a few early adopters including Santiago de Chile, Quito, Pittsburgh and Essen in Germany. Then in the late 1990’s the dynamic changes with a burst of new systems in Central America, Canada, Australia, and mainly second-tier cities in Europe. Taipei has spearheaded the adoption of BRT into China, with many new large systems emerging. Sizeable BRTs also recently opened in Istanbul, Tehran and interestingly in Lagos where hopefully further investment in African cities will follow.

In our highly connected globalised world, new city innovations are likely to spread more quickly, and that seems to be the case with BRT. Indeed this acceleration effect is even more marked in the last innovation we’re going to investigate- the bike sharing phenomenon. Now bike share schemes are of course small investments compared to city-wide metro systems, yet they are still an interesting recent advance with similar global dispersion dynamics (data from Bike Sharing World Map and O’Brien Bike Share Map)-

The original pioneer of bike sharing is not as clean cut as the BRT and Underground examples as there have been several generations of innovation (see pdf article). In 1995 Copenhagen successfully created a reasonably sized (1,000 bikes) coin operated system with specially designed bicycles that tried to reduce theft. A small number of cities in Germany and France followed suit. The next generation began in Lyon in 2005 with a larger (4,000 bikes) system using smart card technology that greatly reduced theft. Subsequently bike sharing has exploded globally across Europe, North America, China and South Korea.

Paris has by far the largest system in Europe with 20,000 bikes. But even Paris’s Vélib’ is small compared to two huge Chinese systems in Wuhan (90,000 bikes) and Hangzhou (70,000 bikes). China’s strong cycling tradition has recently been in decline with rising car ownership, and hopefully the Bike Share boom will reverse this trend.

So to conclude, we are experiencing an age of truly global transit adoption with innovations spreading more rapidly through global city networks. While innovation has traditionally arisen in Western European and North American contexts, by far the greatest urban growth is in Newly Industrialised Countries, increasing demand for innovations like BRT. The rapid rise of bike share systems shows that relatively modest innovations can have a global impact when the innovation is popular and effectively implemented.

 

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Notes-

The ridership and scheme size data relates to current passenger levels rather than the size of the system at the time of construction. Would be great to do this visualisation with time-series ridership data, but this is not to my knowledge currently available.

The definition of metro and BRT systems used here comes from the database providers, and there is some ambiguity, e.g. in defining when a regional urban rail system can be classed as a metro (see metrobits.org).

 

 

 

 

 

 

Copenhagen and Hong Kong: Mapping Global Leaders in Green Transport

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Cities that achieve social and economic success without high car use generally have three things in common: high densities, good urban design, and successful planning frameworks that integrate land-use with public transport, walking and cycling networks. I’ve been working on an LSE Cities project that investigated two leading global cities in green transport- Copenhagen and Hong Kong- to better understand how their leading positions were reached. You can read the final Going Green report here.

The project required visualising the level of integration between public transport and urban density in these cities. We developed a technique where the rail network is shown as a transect through a 3D population density surface. This shows how the density of jobs and residents in these cities is clustered around major public transport nodes.

CopenhagenMap_small

Copenhagen has a classic radial pattern, based on the famous ‘Finger Plan‘ developed over 60 years ago, where linear urban features are separated by thin green wedges. This is quite distinct to the UK greenbelt approach. Current expansion is focussed to the south of the city centre along the Orestad corridor served by the more recently developed metro links. This area sites the airport and transport links to Sweden, continuing the cross-border integration between Copenhagen and Malmö.

Hong Kong makes a very interesting comparison. It is on average 8 times(!) higher density than Copenhagen, and peak densities are around four times higher at nearly 150,000 jobs & residents per square kilometre. This is due firstly to the natural boundaries and country park designations that prevent suburban development, and secondly to the unique ‘Rail plus Property’ planning model run by the government and MTR, where extremely high development densities are pursued at rail station sites, and land value gains captured to fund public transport. The result is a polycentric pattern of jagged nodal development.

HongKongMap_small

Another way to consider this relationship is to measure typical distances to rail & metro stations for these cities. As can be seen below, Copenhagen and Hong Kong compare favourably to other leading global cities like London and New York.

It would be interesting to pursue this analysis further for London. You can see that London scores relatively lower for the population within 500 metres of stations. Intensification policies at public transport nodes are a recent policy change for London. Accessibility figures are likely to change over time with several major intensification projects under way at rail stations in Inner London.

(Above figure based on metropolitan regions. Defined as Outer Met Area for London and 100 km by 100 km square centred on Manhattan for NYC).

Automobile 2.0: Electrification, Sharing and Self-Drive

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Autonomous car concept by Mike and Maaike.

 

Despite the litany of sins levelled at the automobile- it’s woeful energy efficiency, harmful pollution, congestion, road casualties, damage to public space, contribution to obesity- we are still wedded to the car. In the UK the car accounts for over three quarters of trip miles. The flexibility, security and door-to-door convenience of automobile travel remains a winning combination, particularly when we spent most of the 20th century developing car-based cities with limited alternatives.

Current planning practice restricts car travel to improve sustainability and urban quality of life. Short of an outright ban however, the car is here to stay in some form or other.

For the automobile to be in any way sustainable we need to radically challenge current systems of car design, driving and ownership to effectively create a new mode of transport. This post considers whether such a revolution is possible in light of exciting recent innovations.

Electrification
We now for the first time have competitive alternatives to the internal combustion engine car on the market with electric and hybrid models from the world’s biggest manufacturers. These technologies dramatically reduce or remove tail-pipe emissions. Surely then the eco-car has now arrived and city transport has been saved?

Nissan Leaf plugport

 

Well… as electric cars (and vans/taxis/buses) become more widespread urban air quality should improve dramatically, as should vehicle mileages. But as we generate the majority of electricity using fossil fuels (and will continue to do so for the next 20 years+), CO2 emissions from electric cars remain significant.

Furthermore several other car design issues are not solved by electrification, such as energy used in manufacture, road congestion, safety and damage to public space. There’s a danger that electric cars become merely a green-wash cover for business as usual, rather than as a step towards bigger change.

Sharing
Most cars are driven for a relatively short period each day, and are parked the rest of the time occupying land (around 10% in cities). On-street parking eats up large amounts of valuable public space from pedestrians, public transport and cyclists. It’s a wasteful situation, both for the efficiency of cities and for the environment due to the vast amounts of materials and energy used to manufacture our largely idle cars.

One increasingly popular solution in cities is car-sharing, with the largest company Zipcar now up to 700,000 members. Car-sharing is a convenient and affordable option for many city residents who want regular car access without the hassles of ownership. The popularity of smartphones provides an easy way to manage car-share booking. Comparable sharing trends are also evident for ride-sharing and for urban cycling.

Is sharing the answer then to the sustainable city travel? It’s definitely an important trend. Sharing allows a much better pricing model for driving, paying by the mile and charging more at peak times, thus encouraging more efficient behaviour.

Car-sharing coverage is limited however to denser urban areas, and it is not yet clear to what extent car-sharing can significantly reduce the total number of vehicles and car parking space in cities.

Self-Drive
The last trend is at a much earlier stage than electrification and car-sharing, yet it could have the most far-reaching consequences. Sat-nav and parking-assist technologies were early steps towards greater automation in cars. Now Google as well as several manufactures have working prototypes of autonomous or self-driving vehicles.

Amazing yes, but what’s the point? In its current form, the application of this technology is not immediately clear, beyond providing a luxury car gizmo that lets you read the paper while your car drives you to work. But future developments will likely involve cars built around self-drive from the ground-up.

Potentially you could have a city taxi fleet of fully autonomous electric cars, requested by smartphone, operating 24 hours a day, moving to areas of high demand, charging batteries when not in use. Whilst bad news for taxi-drivers, such a system could be highly efficient and provide a quick and flexible complement to mass transit networks.

A related concept has already been developed in a rail-pod form operating at Heathrow airport. Dubbed Personal Rapid Transit, it is intended to combine the advantages of both private and public transport. Obviously the challenges of converting such a system to operate autonomously in the ‘wild’ of the urban environment are many, yet are increasingly being tackled.

If such a system could safely and legally operate, the implications would be massive. Imagine freight and courier services operating automatically at night to minimise disruption; your car picking up your shopping on its own, or taking a nap and waking up at your destination.

Reality Check
It’s easy to get carried away with the wonders of new technology. Transport challenges require political and economic solutions as much as technological brilliance. Indeed relying on car manufacturers alone to green transport is as unlikely as “Beyond Petroleum” BP and Shell delivering the renewable energy revolution. Yet there is some incredible innovation currently emerging, and the next couple of decades are certain to be very interesting times for urban transport.

 

Visualising Flows: Great Britain Journey-to-Work

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There have been some wonderful flow maps appearing online recently, such as Paul Butler’s global facebook friend’s map, and maps of global trade and flight patterns. Inspired by these, I’ve been mapping travel patterns in Great Britain using a similar “night-lights” visual style.

The above maps use data from the UK census connecting where people live to where they work, showing how transport flows form complex urban networks and extensive metropolitan regions. The data is at ward level, allowing a good level of detail:

EW_commuter_flows

Taking this visualisation further, a key issue for policy makers is how people travel, with private cars having greater energy, pollution and congestion impacts than alternatives. The final map below groups work trips into car, public transport and walking-cycling travel using an RGB colour scheme, creating a galactic effect (click for larger):

The aim of the visualisation is to put travel patterns in the context of the diverse urban scale and geography of Great Britain, and reveal the degree of regional variation.

The map really highlights how different London is in terms of its extensive regional public transport network, with the other major English conurbations like the West Midlands, Manchester and West Yorkshire being highly car dominant in comparison. The variation in public transport levels could be argued to relate to London’s massive size, yet the Scottish cities of Glasgow and Edinburgh perform well in public transport terms, despite being smaller than England’s northern cities.

Active travel modes of walking and cycling are generally minimal. The cities that do relatively well are the “cathedral cities” like Cambridge and York, with a few surprises like Hull.

The maps were created in ArcGIS using the XY to Line tool, then exported to Illustrator. A key aspect of such flow visualisations is that the thousands of overlapping flows add together to form denser links using a cumulative transparency effect. This is much easier to achieve using a vector graphics program such as Illustrator. Would be nice in a future post to add Northern Ireland and the Republic, and will get a data update with the 2011 census next year.

Mapping Intra-metropolitan Journey-to-work Sustainability

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As cities expand with multiple centres spread over massive regional hinterlands, the need to better understand the geographical variation across and within cities has become more pressing. This need applies strongly to issues of travel sustainability, where urban centres differ greatly in the accessibility they facilitate for private, public and active transport.

Spatial indicators are a useful tool to summarise complicated intrametropolitan patterns, as illustrated in my new working paper mapping CO2 emissions from journey-to-work travel across the London Region. The results of this indicator show a massive range of travel emissions by workplace of up to 300%, with particular problems for airports and the specialised employment region of the Western Sector, as can be seen in the map above.

This paper was co-authored with Joan Serras at CASA, who helped with the development of the road and public transport network analysis to model realistic routing behaviour from origin and destination flows from the 2001 census. One interesting aspect to this was the inclusion of GPS data to model average road speeds in London as illustrated below:

Full paper abstract:

“This paper develops a methodology for estimating network distances and CO2 emissions for UK census ward-level journey-to-work interactions. Improvements are made on existing empirical measures by providing comprehensive intra-metropolitan analysis; increasing network routing accuracy with UK public transport timetable and GPS-based average road speed data; allowing multimodal travel; and developing metrics suitable for travel sustainability analysis. The output unit of CO2 emissions has been selected to enable the integration of mode-choice and travel distance data, and to aid compatibility with integrated assessment applications. 

The methodology is applied to the case study of the London Region for the year 2001. A very high degree of intra-metropolitan variation is identified in the results. Employment sub-centres diverge in their per-capita CO2 emissions by up to 300%, with specific problems of carbon intensive commuting to major airports and the specialised employment region of the Western Sector. These findings indicate that subcentre travel variation may be intrinsic to polycentric urban structures. The paper discusses means to improve the methodology, in relation to issues of coefficient disaggregation and modelling more complicated multi-modal trips.”