For the purposes of this blog, I’m going to look at “consumption based” emissions. These are emissions that result directly or indirectly from a person’s activities. Indirect emissions (such as those used to create the clothing you purchase) are harder to model than direct emissions (such as those generated by the furnace that heats your home). But they can add a useful dimension, so some researchers at UC Berkeley spent a few years modeling consumption emissions for neighborhoods across the country (1). What can we learn from their work?
You don’t hear the phrase “average Palo Alto” too often. But Palo Alto is distinctly average when it comes to these emissions. That is pretty surprising, given we have two big things going for us:
Our temperate climate means we need relatively little energy for heating and cooling.
Our electricity is emissions-free, thanks to Palo Alto Utilities. So we get “for free” what accounts for about 15% of household emissions across the States.
What is going on? Why aren’t our emissions well below average, given those advantages?
To start with, Palo Altans have only average emissions in two important areas, travel and food. We generate about one-third of our emissions from travel, with an average of 24% from gas-powered vehicle travel, and 9% from air travel. Our travel emissions are similar to the average US resident, but slightly greater because we fly about twice as much.
Our diet accounts for 17% of our emissions, which is similar to households across the US. Although Bay Area residents in general eat somewhat less than the national average (and as a consequence, obesity rates are lower here), our diet composition is similar to that of the national diet, so our emissions are close to average.
What are we missing? While we aren’t beating the national average on travel and food, we aren’t lagging it by much either. And our home energy and electricity emissions are well below average. Where are we generating many more emissions than typical in the United States?
The two remaining categories of emissions activities reflect our consumption of “goods” and “services”, which account for a whopping 40% of our emissions. And this is where we fall well behind the national average -- it turns out that we buy and do a lot of stuff! The model indicates that our purchases and activities generate nearly twice the emissions of the average US household. Some of the big ticket items in this category are health care, recreation, clothing, and furnishings and appliances.
This analysis has many limitations. Indirect emissions are difficult to measure, and the model is pretty basic. Even for more direct emissions, it doesn’t account for EV usage, and some estimates like air travel and food are largely tied to income and/or household size. Costs for home heating, moderate in the study, are likely greatly understated due to evolving understanding of how leaky our natural gas network is. But nevertheless it is easy to identify our biggest emission sources. The Cliff Notes version of the Palo Alto carbon “diet” is:
- Ditch the fuel pump. This is by far the biggest thing we can do, and there are many options here, from leasing an EV to carpooling to using transit or a bike.
- Think about your air travel. Cut back, or consider buying carbon offsets.
- Eat less beef. This is a surprisingly big one, and we’ll talk about why in a coming blog. For extra credit, go easy on lamb and cheese too, and buy only what you eat.
- Save on gas at home. A smart thermostat is a nice low-cost win here, and there are clean electric options when heaters and appliances need replacing.
- Buy less stuff! Save your money for … carbon offsets?
We end up with a pretty simple list of big-impact items, each of which has a growing range of alternatives. I’ll go into them in more depth in future blogs, as well as some of the science behind them. Interestingly, though, there is one very impactful thing missing from the list, which is something easy and important that we all can do to reduce emissions. Anyone know what it is?
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References and notes:
1. The data used in this blog are available at https://coolclimate.org. Cool Climate is a partnership based at UC Berkeley involving some universities, businesses, governments, and non-profit organizations dedicated to the broad dissemination of climate solutions. The assumptions used in the consumption-based emissions model are simplistic in some respects (as just one example, they do not account for electric vehicle penetration), and the correlation coefficients of their models are not the greatest. But the high-level guidance and regional variations are interesting. One place to start is this paper: https://escholarship.org/uc/item/2sn7m83z. Appendix A covers the modeling assumptions.
2. A local organization called Community Climate Solutions has developed a terrific set of climate action sites customized to our cities. To find ideas that may be right for you, tailored to Palo Alto, take a look at https://paloaltogocarbonfree.org/actions. For Menlo Park, see https://www.menlogreenchallenge.org/actions, and for Los Altos, check out https://www.greentownchallenge.org/actions. You can also set up a profile for personalized recommendations.
3. It can be interesting to examine variations in emissions across the Bay Area, and the country. Take a look at https://coolclimate.org/maps. You will see that the areas that fare best around here wrt emissions are Stanford and San Francisco, where there is much less driving and, in the case of Stanford, much less consumption due to lower incomes. Note that, because the study was done in 2015, it does not account for the new greener energy options provided by Peninsula Clean Energy or Silicon Valley Clean Energy.
4. Consumption metrics are somewhat controversial, because they are difficult to measure (involving many assumptions) and can end up being based largely on income. More generally, they may cast doubt on whether wealthy people can be sufficiently green. We’ll discuss that next week!
