Call your legislator and have them try this very simple spreadsheet that illustrates the big actions necessary to cut emissions at the IPCC rate.
State legislators, agencies, and NGOs continue to offer incremental policy measures to decarbonize Oregon and Washington. More often than not, the sum total of these increments falls woefully short of the reductions necessary, thus wasting the precious time available to mitigate the climate emergency.
The spreadsheet simply adds the emissions reductions from consumers and businesses switching their purchases from emitting infrastructure (vehicles, buildings, factories, power plants, etc.) to zero-emission infrastructure options, in each sector. We are buying new emitting infrastructure every day, and those purchases lock in emissions for the lifetime of the hardware. The cheapest route to cleaning up our emissions is to steer those purchases to zero-emission options.
Download the spreadsheet here. To express your plan, just enter the portion of zero-emission sales for each sector every five years, in the green cells.
The long version:
Successful decarbonization strategies must work on all levels—the physical, economic, and policy levels. The physical level is by far the simplest, since the goals are specified by the state’s goals, the 2018 IPCC report, or other targets. Economically, the sectors with the most mature clean technologies can generally respond the fastest and with the most competitive costs. Regardless of the economic or social costs or the types of policies enacted, adding up the physical emissions is very simple and the inventory by sector relates well to the sector-specific options.
The most affordable path to replacing infrastructure is to steer the ongoing new purchases to zero-emission technologies. The policy options include mandates, rebates, fees, or other policies. (For example, Norway uses both carrots and sticks to equalize the purchase prices of EVs with comparable gas/diesel vehicles.)
This simplified emissions planning tool treats each of the emission sectors as an infrastructure replacement process, wherein the sector emissions decrease proportionally with fleet replacements that are zero-carbon (whether vehicles, power plants, furnaces, etc.) The model inputs by year are simply the portion of infrastructure purchases that are zero-carbon (“% of sales” for each sector). That annual addition rate is accumulated as a “% of fleet” for that sector, which reduces the GHG emissions for that sector and is plotted. Because the electricity sector is regulated to meet a Renewable Portfolio Standard (RPS), the electricity inputs are “% of fleet” by year. The “% of fleet” is normalized to 0% clean in 2016; thus describing only the emitting portion of the sector.
Disclaimer: This spreadsheet is the architect’s dull pencil for initial sketches. Any plan is better than no plan, because it can be analyzed and optimized. The inputs and outputs on this spreadsheet are purposely oversimplified, to focus on the large rocks in the box. It ignores conservation and efficiency contributions. It does not calculate any costs, although the infrastructure replacement inputs illustrate how much money is available to be steered (0 to 100% of current purchases), as opposed to additional funding (if “% of sales” is larger than 100%). It does not presume any policy structures. It ignores interactions between sectors, the largest being the increased grid load from electrification of transportation and the indirect electric vehicle emissions from electricity generation.
And those are just the major inaccuracies. But we’re at the dull-pencil phase, and sharp pencils are only distracting in this phase.
The business-as-usual (BAU) numbers in the input cells are also subject to lots of differing forecasts and arguments. EV forecasts are particularly wide-ranging, but it’s increasingly evident that EVs will be a large portion of global fleets by at least 2040, so the BAU should indicate significant GHG reductions from vehicles. (Bloomberg’s 2020 EV forecast is arguably a good business-as-usual forecast.) Similarly, coal power plants are being shuttered because they’re increasingly uneconomic, and gas peaker plants are being replaced by utility-scale batteries. Figure 1 is a screen capture of the spreadsheet with some BAU numbers, illustrating for this case a 25% reduction by 2035 due to existing policy and market forces.
Figure 2 illustrates achieving the target reductions by 2035 through changing the inputs for three sectors: 1) copying what Norway is doing for light-duty vehicles (this is aggressive), 2) assuming the same is possible 5 years later for medium- and heavy-duty vehicles, and 3) adopting the 2035 Report emissions trajectory for cleaning up the grid. This scenario achieves Oregon’s state target; it does not indicate that the work is done, but it can provide guidance on useful directions to pursue.
Figure 1. Screen shot of the Oregon model tab with some business-as-usual assumptions.
Figure 2. Screen shot of the model with aggressive adoptions of clean vehicles and electricity.
A serious modeling tool that links specific policies to emission reductions and economic effects is the Energy Policy Simulator from Energy Innovations. This is open-source and online for the US, California, and other countries; an Oregon adaptation is under development with the Northwest Economic Research Center at PSU.
Webinar on how to decarbonize Oregon’s energy, including sample policies, the real costs of gasoline, and how much money decarbonization can save at the household level.
2015 presentation on how to cut your household footprint by 50%