When I was the planning director of San Diego five years ago, the city’s now-vaunted Climate Action Plan was being prepared. At the time, my department was under considerable pressure to increase densities to reduce vehicle miles traveled (and greenhouse gas emissions) while at the same time we felt pressure from neighborhoods to limit densities in order to limit congestion.
So it seemed logical to meet, in several meetings with the consultants modeling GHG emissions reductions, to ask them to draw a straight line between the land use policies we were pursuing and the emissions reductions that served as our policy goal. Like, for example, increase emissions X% and reduce emissions Y%.
But they couldn’t do it. The best they could do was say, generally, that if we pursued policies associated with higher density, more transit, and more walkable communities, then broadly speaking that would advance us toward the goal.
It was a sobering moment, and it’s been a problem ever since in San Diego, as the city is still battling with neighborhoods along the new Mid-Coast light-rail line over densities. If a neighborhood is opposed to higher density, how can you defend a policy decision to increase density when you can’t prove the connection between the policy and the ultimate goal?
This story came to mind when I read the California Air Resources Board’s recently issued 10th anniversary progress report on SB 375 -- the Sustainable Communities and Climate Protection Act – which was designed to implement the state’s greenhouse gas emissions reduction goals, especially through regional transportation and housing planning efforts. The progress report is a gloomy assessment, noting that “California is not on track to meet greenhouse gas emissions expected under SB 375” and noting in particular (this is on page 4 of the report) that vehicle miles traveled per capita has actually increased sharply in the last few years – most specifically, since right around the time I was meeting with San Diego’s consultants about the Climate Action Plan.
As I explained in these pages shortly after SB 375 passed, the transportation and land use planning efforts mandated at the regional level by the law are part of a “three-legged stool” that California’s policy wonks have long claimed is necessary to meet greenhouse gas emissions goals in the transportation sector.
The first is reducing the amount of carbon in vehicle fuels, a goal pursued by adoption of the low-carbon fuel standard. The second is reducing the amount of fuel used by increasing gas mileage, a policy now challenged by the Trump Administration. But the third – the subject of most discussion under SB 375 – is reducing the overall amount of driving and in particular the amount of driving per capita. Under ARB guidance, the state’s metropolitan planning organizations are supposed to embed in their Regional Transportation Plans – and, less explicitly, in each region’s local land use plans – a reduction in vehicle miles traveled on the order of 18% to 19% per capita.
And yet VMT keeps going up. The ARB report contains a fair amount of hang-wringing about this and throws out a kitchen-sink list of reasons why it’s not happening: poor alignment of transportation dollars with SCS goals, a lack of housing construction, the conundrum of compliant housing elements while there is little housing construction, the fact that a lot of agricultural land in the San Joaquin Valley is being converted use, the possible need for congestion pricing, and on and on and on. The usual litany.
The report also lays out two-dozen possible SB 375 “progress performance indicators” (page 20), ranging from fuel prices to new homes built by type, to acres developed to percentage of population living near a grocery store.
But ARB is pretty up-front that these are almost all indirect measures. Just as I learned five years ago in San Diego, ARB is conveying that it is almost impossible – with current data – to draw a straight line between transportation and land use policies and a reduction in VMT.
Take just the example of proximity to grocery stores. ARB does a pretty extensive job of reporting how close people live to grocery stories – the figure is 88% proximate statewide, which is pretty good – but acknowledges that the board used this metric because it was available, even if it might not be a very accurate representation of how accessible people’s daily needs are to where they live.
So the most important thing buried in the report is the conclusion that most of the data available doesn’t really answer the question.
It reminds me of the old distinction in metrics between measuring inputs, measuring outputs, and measuring outcomes. In this case, an input would be, say, how much money the state is spending on highways versus transit. An output would be, say, how much greenfield land is being developed. Interesting as these statistics may be, they don’t really help you understand whether you are achieving your desired outcome, which is reducing VMT.
If reducing VMT is a major state policy goal – implemented through the MPOs – then the state and the regions have to work together to figure out how to measure progress toward that outcome.
The ARB report contains some good ideas, including better tracking of non-work trips, better combined statewide tracking of transportation investments, and better collection of data at the neighborhood level for transportation, air quality, and the actual relationship between affordable (or unaffordable) housing and VMT reduction.
The bottom line is you can’t manage what you can’t measure. We measure all kinds of things associated with transportation and land use. But now, no less than five years ago, we’re not measuring how all those policies translate into reduction in VMT – and reduction in greenhouse gas emissions.