Erick Guerra and Robert Cervero from UC Berkeley have published a new paper, Transit and the “D” word, examining the relationship between urban density and the cost of constructing and operating rail-based transit.
They looked at 54 light rail and heavy rail projects constructed in 20 US cities between 1970 and 2006. The paper is a summary of a larger one published here (the latter one’s gated though).
Transit projects with low capital costs look attractive but some also have low ridership. Some that cost a lot have correspondingly high patronage. For example:
The first section of the Red Line in Los Angeles cost more to build per route-mile than any other investment but had below average costs per passenger-mile. Because of its low ridership, San Jose light rail had among the highest costs per passenger-mile despite low investment costs per route-mile.
The authors accordingly look at both capital and operating costs and compare them against ridership to arrive at a reasonable measure of cost-effectiveness.
After netting off fare revenue, they find the lowest combined capital and operating subsidy is $0.14/passenger km for the Denver Central Corridor light rail project. So a commuter who travels 20 km each way five days a week relies on an average weekly subsidy of $27.
But the highest subsidy is almost fifty times greater – $6.48/passenger km for the Newark light rail extension to Broad Street. A commuter who travelled the same distance on this system requires an average subsidy of $1,296 per week!
The average subsidy across all 54 projects is $0.84 per passenger kilometre (around $170 per week for my notional commuter). Half the projects require a subsidy of more than $0.50/passenger km and 20% exceed $1.00/passenger km.
The authors emphasise that “a system with few passengers and a high price tag is, by most accounting, a poor investment economically, environmentally, and socially.” In their view, the key to cost-effective rail-based transit is high population density and, especially, high job density (hence their reference to the “D” word).
However they find the density of neighbourhoods around the transit stations they studied is very low. Only 26% of 526 heavy rail stations and 19% of 261 light rail stations meet the influential minimum population density thresholds for successful transit proposed by Boris Pushkarev and Jeffrey Zupan.
As the exhibit shows, Guerra and Cervero modelled jobs and population density against subsidy cost per passenger mile and arrived at their own thresholds.
The results…..suggest that, on average, light rail is more cost-effective than heavy rail in areas of up to approximately 28 residents and jobs per gross acre. With system-area densities near or below 20 residents and jobs per acre, Atlanta, Miami, and Baltimore appear better suited for light than heavy rail, while heavy rail is the appropriate choice in the San Francisco Bay Area and Washington, DC.
They argue many recent transit investments have failed to recognise the importance of urban development patterns. Many of them lack the concentration of activity required for cost-effective transit.
All too often, rail transit investments in the US have been followed by highway-oriented, rather than transit-oriented, growth…..Despite the unease many citizens, planners and politicians have with density, if costly rail and BRT investments are to pay off, larger shares of growth—particularly jobs—must be concentrated around transit stops.
Nevertheless they acknowledge that density is only one factor, albeit an important one. Other aspects of transit design and management matter too. For example:
Despite low surrounding densities, the Franconia-Springfield extension of the Blue Line in Washington DC, is one of the best performing investments. Low capital costs, a plentiful supply of parking at stations, frequent train service, and good access to downtown jobs contribute to low costs per rider. By contrast, the Buffalo light-rail system is one of the least cost-effective, despite above-average job and population densities.
Unfortunately, this paper doesn’t provide a lot of supporting technical information so it’s hard to evaluate the author’s claims. For example, I can’t tell if their recommended density thresholds make sense; I’m not sure adding job and population density into a single figure works; and I suspect they’ve under-estimated construction costs for older projects.
With that caveat, here’re the key things I take away from this paper. Density really does matter for rail-based transit, most especially employment density.
It’s quite possible to provide an acceptable level of rail transit without any high density stations, but it might not be cost-effective. But density isn’t the whole story – there’re other important dimensions to providing and operating cost-effective public transport too e.g. connectivity, frequency, parking.
The size and nature of the “market” being served should determine the type and scale of the public transport “solution” that’s suitable. Guerra and Cervero’s findings on per passenger kilometre costs suggest that’s not always – or perhaps even often – the case.
Cost-effectiveness matters. I don’t know what’s a reasonable level of subsidy per passenger kilometre for the benefits of public transport. But the available financial and political capital is frustratingly finite and great care and attention should accordingly be given to maximising the cost-effectiveness of projects.
I think the key message (the authors are strong transit advocates) is precious financial and political capital shouldn’t be squandered on rail-based projects that don’t deliver, no matter how glamorous they might be. If a project doesn’t stack up, other options need to be considered.
(If someone can e-mail me the more extensive gated version published in the Journal of the American Planning Association I’d appreciate it. Address is in About This Blog. Update: have a copy – thanks Matt).