The same data yields two very different pictures of what's important.
Behold: two very different ways of looking at U.S. climate-warming emissions, thanks to the Oregon Department of Environmental Quality (pdf presentation here). First, the geeky view, with emissions broken out by the specific activities and economic sectors that directly account for emissions:
In this view, electricity and transportation dominate -- suggesting that those are pretty good places to look for emissions reductions.
But here's another, somewhat more personal view -- one that fits our "carbon footprint" into the context of our daily lives.
This chart shows that it is our stuff that carries the biggest carbon footprint. Emissions related to buildings (heating, cooling and lighting) are a close second.
Interestingly, the two charts rely on the exact same underlying numbers. Yet they present completely different perspectives on the best leverage points for reducing GHG emissions. Which view is more helpful to keep in mind, for someone trying to fight climate change? I'm not sure. Perhaps neither -- since the real key to curbing climate change isn't finding where emissions are most abundant, but finding where they are most easily curbed.
That said, as someone who's used to thinking about the first chart -- where electricity and transportation dominate the picture -- the second chart comes as something of an eye-opener. How we get around town is certainly a big deal. Yet as harmful as personal vehicles are to the climate, I probably should be paying a bit more attention to my stuff.
It's not very conflicting at all...merely cutting the contribution by industry vs by function.
A technologist would look at the first chart to identify areas that need the most innovation, e.g., opportunities in alternative fuels and grid energy.
A conservationist would look at the second chart to identify areas where we can cutback, e.g., opportunities in reducing power consumption, or buying goods sourced closer to home.
The second chart looks like a good argument to turn off the A/C and open a window, and to start buying more local goods. Neither of those rely on companies making the next generation of "x" technology available to consumers.
from a policy-setting perspective the second graph is worthless.
e.g. if you are going to tax emitting activities, do you look @ the second graph & tax food, even though food having been transported a short distance & used little energy in production will be penalized along with the food which is more responsible for the problem? of course not, you look at the first graph & tax transport, then the impact falls appropriately upon the most problem-causing food
Unless we all move to southern California or China for our goods, I don't believe there is a realistic way to make much of an impact on this.
Excellent information. Since it's based on the same dataset, this is a great example of how sorting data into information directs how it can be acted upon. Different stakeholders (policymakers, consumers), or different tactics (policy, consumption) require the different info to direct appropriate action.
I really like that this approach encourages us to see many facets of the issue, with no "one way" to interpret a dataset. By presenting data in multiple ways it encourages envisioning (& hopefully implementing) multiple solutions. Kudos.
In addition to "buy local" (an interpretation I absolutely agree with), I see another solution: "buy less":
a) Reducing purchases (doing without or replacing on a longer cycle) can affect the 38%. Viewed this way, the second chart urges us to consume less & to think about the impact of always having the trendiest thingamabob. Changing "always" to "occasionally" or "aah, nevermind" helps.
b) Re-use & freecycling (no favorites, www.freecycle.org is only one example of free-exchange communities) doesn't just reduce landfill. Finding a new local home for still-useful stuff eliminates a new "good or material" from having to be "provided", reducing the 38%.
c) Thoughtfully designed & produced products (the amount & type of energy & raw materials used to produce & transport goods & materials).
d) Yet, all things in moderation, including moderation: This does not necessarily mean we should put off purchasing that high-efficiency appliance to replace a wasteful one. Also, less stuff doesn't mean depriving yourself or vilifying trendy new designs. It can be Really Great "less stuff", i.e. one FANTASTIC purse instead of one for each outfit.
Thank you for sharing this information. Sorry for the lengthy post.
I think that the second graph is very illuminating. I live in NYC and here buildings make up an even larger portion of greenhouse gas emissions. Up until now building policy has focused on new construction, but the real challenge is all of the existing buildings. I'd like to see more people advocating for policies that will encourage and/or require owners and operators of existing buildings to make them more energy efficient, especially since many of the improvements that would have the largest impact will also pay for themselves within 5-10 years.