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How low can we go?
Whether dancing the Limbo or reducing our carbon footprint, low is where it’s at and we’d like you to participate. Yesterday a Carbon Neutral Neighborhoods group, met with SDOT to talk about progress and challenges as we work on making our community more livable and walkable (i.e. Walk Bike Ride becoming the “easiest” way to get around) and they would love your input!! Seattle’s existing Climate Action plan calls for us to be 80% below 1990 levels by 2050 and Seattle City Council’s Carbon Neutral City effort asks how low we can go – what do you say???
Here at SDOT we have been working on making it easier to walk, bike and ride transit and partnering with King County and others to develop better tools to show the benefits of investing in livable communities and transportation choices. This map shows Estimated GHG Emissions by Neighborhoood from Vehicle Travel by household in and outside our urban villages. 
Green areas on the map above have lower Co2 emissions than purple areas (data from 2006). We believe all the neighborhoods on Seattle’s map are turning green as investments in livable walkable neighborhoods continue. Join the discussion, and see how low you can go with your own footprint!
Posted: August 4th, 2010 under SDOT.
@Matt – The reason I asked the question is to see if the conclusion you drew was supported by the data. It could be, but not to a certainty necessary to support the policy change you suggest. Additionally, the model was clearly constructed by the consultant to generate a result that favors density over SF zoning. That’s not surprising. For example, adding in vegetation and permeable surface % per parcel would correctly balance some environmental factors. Making the jobs/population balance sensitive to livable wage jobs data would correct for the fact most jobs in multi-use tend to be retail commuter jobs, balancing some GHG issues there. Adding these changes and a few others would make for a better balanced model.
The big flaw is the transit data don’t show actual ridership. It uses door openings, which in a rational world might be a proxy but here in Seattle misses on two accounts. (1) It doesn’t tell you how many people ride, and (2)Since Metro doesn’t apportion routes by demand (see also 20-40-40), it isn’t a reliable proxy.
I’ll also note that most SF houses taken down for MF uses are smaller in square footage by 2x-3x than the townhomes that replace them. Overall, the energy efficiency per parcel gets worse and the loss of trees and permeable surface makes the equation balance out. If we had better transit service for our willing Seattleites, you’d see much more green on the map.
@SDOT Blog — Thanks so much for the details. I’m crossing fingers that ORCA can generate ridership data at some point for us and that we can get our hands on the weightings/spreadsheet so we can start figuring policy/communication tools to bump ridership in our SF neighborhoods and start turning some of that purple to green.
Models like this one are useful, don’t get me wrong. There is far too much purple area in our urban villages. We need to incentivize development there in alignment with neighborhood planning and above penalize people for underbuilding to allowed zoning (absent a darn good reason why) in our urban core areas.
Above all, we need to break 40-40-20 and get empty routes to nowhere redirected to our comparatively much denser neighborhoods so we can get the horde of willing Seattle residents into buses.
Glad to help with the info. And we’re pleased to see that the post has generated such much interest.
Can you comment, or send by e-mail, what methdology and assumptions you use to create this map?
Thanks,
David
We have asked the author of the blog post to contact you directly. You should expect to hear from her shortly (after the furlough day).
Hi David, I’m happy to explain. It is difficult to do without sounding pretty technical and wonky, but I’ll do my best.
retail floor-area ration, 9) bus door openings per week, 10) jobs/population balance, 11) mean travel time to 13 major traffic analysis zone (TAZ) destinations by single occupancy vehicle, and 12) mean travel time to 13 major TAZ destinations by transit. Often the data that was used had to be limited to data that was available for all of King County, instead of Seattle specific.
The Map depicts estimated greenhouse gas (GHG) emissions from residential travel in Seattle at the level of the census block group. The numbers represent the estimated average yearly CO2 emissions (measured in tons) per household. The black outlines show Seattle’s urban village boundaries, which are areas that have been targeted by the city for higher density development, additional transit service and transit oriented development, and increased pedestrian scale infrastructure. The map illustrates a strong correlation between urban village boundaries with relatively low CO2 emissions, indicating that Seattle’s urban village policy is helping the city meet its Comprehensive Plan and Climate Action Plan goals to reduce GHG emissions.
The data shown are based on estimated from a residential travel GHG emissions model created for King County by Urban Design 4 Health, inc. Twelve variables were incorporated into the model, using data from the 2006 Puget Sound Regional Council (PSRC) Travel Survey and the 2000 U.S. Census. The variables included: 1) average household size, 2) average number of workers per household, 3) average number of vehicles per licensed driver, 4) household income, 5) intersection density, 6) net residential density, 7) mixed used index,
It is important to know the data was derived from 2006 data; and is an estimate of GHG emissions based on the aforementioned model and not actual CO2 measurements. However this new model is one of the most cutting edge methods to measure the benefits of transportation and land use investments in reducing GHG. We are currently partnering with the state DOT to further develop this model.
[...] Well, duh. But it’s nice to see a map that corrolates so well with the theory. From SDOT: [...]
Although the transportation side of the equation helps, the best way to cut our emissions are on the planning side. As your map shows, the more dense the area, the less driving that people do. But also, the less heating that is needed per unit, the less electricity that is used, the fewer miles of sewer pipe, electrical lines, roadways, parking lots, etc.
In the next few decades our region will absorb another million people. If we upzone our urban villages and surrounding areas maybe we can bring a large portion of these people into a sustainable urban lifestyle rather than make them sprawl out in the suburbs.