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Nation’s Urban Centers Ranked for Carbon Footprint

Report Released This Thursday, 5/29

For the first time, the nation’s 100 largest metro areas are ranked for the size of their carbon footprints in a new report to be released this Thursday, May 29th by the Brookings Institution’s Metropolitan Policy Program.

An AUDIO NEWS CONFERENCE will take place with the report authors to discuss findings and policy recommendations:

WHEN: Wednesday, May 28, 1:00 PM EDT

DIAL-IN: 877-795-3647

“Shrinking the Carbon Footprint of Metropolitan America” provides extensive analysis and surprising conclusions on

· The dramatic variations in the carbon footprints of our large urban centers

· Regional comparisons - which regions are shrinking their footprints and which are growing theirs

· The per capita size of the carbon footprint of an urban dweller vs. a non-urban dweller

· What factors determine the size of a carbon footprint – residential buildings, cars, development patterns, rail transit, freight traffic, weather, electricity sources, and electricity prices

The report offers recommendations on how the federal government should step up its support of metropolitan efforts to shrink their carbon footprints.

If you would like to receive embargoed materials or interview the authors, please contact Carrie Collins at 301-664-9000 x18 or ccollins@bcc-associates.com or Vanessa Bilanceri at 202-244-0121 or vbilanceri@gmail.com .

Short run vs. long run

A brief anecdote:

Yesterday, I was spending time with a friend who lives in rural Maryland, and he mentioned that he’d just sent his resume out in DC looking for a job so he could move into the city. His reason? High gas prices. Driving around Montgomery County every day has simply become too pricey.

We discussed this as he filled up with $3.81/gal gas. It was fascinating seeing short run price inelasticity juxtaposed so immediately on long run price elasticity.

Mapping affordability

The Center for Neighborhood Technology, in conjunction with the Brookings Urban Markets Initiative, has created an interactive map that displays the spatial distribution of affordable housing in 52 U.S. metropolitan areas. The two basic layers overlay either the traditional measure of affordability (rent 0-30% of area median income) or the project’s Housing + Transportation Index. The HTI (explained in some detail here) incorporates modelled transportation costs into the definition, such that the range of affordability becomes 0-48% of area median income.

Here are two maps centered on Columbia Heights, Petworth, Mt. Pleasant, and Shaw in DC, four neighborhoods that are often described as recently gentrified/gentrifying.

In the first map, blue designates unaffordable areas as defined by the 0-30% housing guideline. When we factor in transportation in the second map, little changes except that a small portion of Mt. Pleasant just left of center becomes affordable by this 0-48% definition (probably due to DC’s relatively comprehensive and cheap public transit system).

There are numerous advanced layers that provide a more finely-discretized representation of the above variables — one can also restrict the data to renters or homeowners. There are also layers for the component variables, such as average neighborhood income, average monthly rent (shown below), transit connectivity index, and so on.

Not only are these great for planners and policy wonks, but also for the DC citizenry. When I was new to DC and looking for a place with only craigslist to guide me, such graphics could have efficiently guided my search.

These maps also provide a valuable snapshot of gentrification and urban development. However, from what I can gather, the area median income is determined at the census block group level. Thus, it does provide an idea of how affordable housing is to the current residents of the neighborhood without allowing wealthy suburbs (e.g. Potomac, MD) to determine the affordability of poorer areas (SE DC). However, since it is only a snapshot, it suffers from massive selection problems. Obviously, people currently living in an area are more likely than not to be able to afford living there, at least to some extent. A big issue that often arises with regard to gentrification and urban development is that people are supposedly priced out of their homes. This static representation does not help determine whether this is happening. Hopefully, the project will continue and be able to trace trends in the future, because I think it’s a fascinating tool with amazing potential.

H/T: Magda.