The Pew Climate Center has a roster of international, US federal, and US state & regional climate initiatives. Wikipedia has a list of climate initiatives. The EPA maintains a database of state and regional initiatives, which they’ve summarized on cool maps. The Center for Climate Strategies also has a map of links. All of these give some idea as to what regions are doing, but not always why. I’m more interested in the why, so this post takes a look at the models used in the analyses that back up various proposals.
In a perfect world, the why would start with analysis targeted at identifying options and tradeoffs for society. That analysis would inevitably involve models, due to the complexity of the problem. Then it would fall to politics to determine the what, by choosing among conflicting stakeholder values and benefits, subject to constraints identified by analysis. In practice, the process seems to run backwards: some idea about what to do bubbles up in the political sphere, which then mandates that various agencies implement something, subject to constraints from enabling legislation and other legacies that do not necessarily facilitate the best outcome. As a result, analysis and modeling jumps right to a detailed design phase, without pausing to consider the big picture from the top down. This tendency is somewhat reinforced by the fact that most models available to support analysis are fairly detailed and tactical; that makes them too narrow or too cumbersome to redirect at the broadest questions facing society. There isn’t necessarily anything wrong with the models; they just aren’t suited to the task at hand.
My fear is that the analysis of GHG initiatives will ultimately prove overconstrained and underpowered, and that as a result implementation will ultimately crumble when called upon to make real changes (like California’s ambitious executive order targeting 2050 emissions 80% below 1990 levels). California’s electric power market restructuring debacle jumps to mind. I think underpowered analysis is partly a function of history. Other programs, like emissions markets for SOx, energy efficiency programs, and local regulation of criteria air pollutants have all worked OK in the past. However, these activities have all been marginal, in the sense that they affect only a small fraction of energy costs and a tinier fraction of GDP. Thus they had limited potential to create noticeable unwanted side effects that might lead to damaging economic ripple effects or the undoing of the policy. Given that, it was feasible to proceed by cautious experimentation. Greenhouse gas regulation, if it is to meet ambitious goals, will not be marginal; it will be pervasive and obvious. Analysis budgets of a few million dollars (much less in most regions) seem out of proportion with the multibillion $/year scale of the problem.
One result of the omission of a true top-down design process is that there has been no serious comparison of proposed emissions trading schemes with carbon taxes, though there are many strong substantive arguments in favor of the latter. In California, for example, the CPUC Interim Opinion on Greenhouse Gas Regulatory Strategies states, “We did not seriously consider the carbon tax option in the course of this proceeding, due to the fact that, if such a policy were implemented, it would most likely be imposed on the economy as a whole by ARB.” It’s hard for CARB to consider a tax, because legislation does not authorize it. It’s hard for legislators to enable a tax, because a supermajority is required and it’s generally considered poor form to say the word “tax” out loud. Thus, for better or for worse, a major option is foreclosed at the outset.
With that little rant aside, here’s a survey of some of the modeling activity I’m familiar with:
California has many GHG-related initiatives, centering around AB32 – see the draft scoping plan at CARB and the joint CEC/CPUC recommendation. A particularly notable “early action” is the Low Carbon Fuel Standard (LCFS). No final decisions have been issued, but momentum at the moment is for a combination of approaches. A multi-sector cap & trade system for the electric power sector and probably the industrial sector would serve as an overlay on command and control and programmatic efficiency measures for point sources and end use. The natural gas sector (e.g., commercial and residential space heat) may not fall under the cap & trade initially. Transport fuels would be influenced by vehicle efficiency mandates (AB1493) and the LCFS; both are intensity measures, leaving total emissions uncapped. Future initiatives might address land use and other drivers of transport demand.
Some models that have played, or will play, a role in the California analyses:
- VISION-CA – a spreadsheet accounting tool used to develop LCFS scenarios. It translates assumptions about vehicle sales and efficiency and fuel carbon intensity into energy and emissions outcomes. Except for aging of the vehicle fleet, the model is totally open-loop. Contact me for a detailed analysis of the model and prospects for an improved tool.
- GREET and LEM – lifecycle analysis models used for LCFS alternatives (see the proceedings of the LCA working group).
- Energy2020 – used by CARB for energy-economic analysis. Energy2020 is probably the most interesting of the large-scale models available, because it takes dynamics and behavior seriously. Other common options, like MARKAL and CGE models, assume an unrealistic degree of optimality in consumer behavior and equilibrium in markets. Unfortunately, I’ve recently spoken with several observers and participants in the modeling process, who expressed frustration with slowness and lack of transparency. For what it’s worth, I suspect that most of the alternatives would be even slower and less transparent, and that users would be happiest with something much simpler than any of the commercial off-the-shelf options. Energy2020 is an energy system model, but it can be linked to REMI for macroeconomic feedback, though it’s not clear to me whether it’s being used that way in California.
- EDRAM – a CGE model being used to look at economic impacts. Great for looking at detailed sector impacts, revenue recycling, and allowance allocation issues. Unlike most CGEs, it is my understanding that EDRAM can consider some departures from economically optimal consumer behavior. Not helpful for dynamics, physical representation of the energy system, or induced technological change (the latter is unfortunate as high hopes are pinned on technical solutions to emissions problems).
- E3 GHG Calculator – a spreadsheet model used in the joint CPUC/CEC proceedings to examine emissions from electric power generation.
- (A little off topic, regional climate modeling was used to develop impact scenarios)
Western Climate Initiative (WCI)
WA, CA, OR, AZ, NM, MT, UT, BC, MB, and QC are partners. 6 US states, 6 Mexican states, and 2 Canadian provinces observe. For a general overview, check the presentations linked in the bullets under the May 21 stakeholder meeting. The WCI’s draft design is focused on cap & trade for the power sector, industrial point sources, and fossil fuel production and processing from the start. Residential/commercial emissions are in the system, but with local options to pursue other regulatory modes. Further analysis is proposed before transport emissions are included in trading. Emissions allocations are to target WCI’s goal of 15% below 2005 levels by 2020.
Like California, the WCI is using Energy2020, but output is apparently not yet available.
Regional Greenhouse Gas Initiative (RGGI)
9 Northeast and mid-Atlantic states. The RGGI goal is:
Develop a multi-state cap-and-trade program covering greenhouse gas (GHG) emissions. The program will initially be aimed at developing a program to reduce carbon dioxide emissions from power plants in the participating states, while maintaining energy affordability and reliability and accommodating, to the extent feasible, the diversity in policies and programs in individual states. After the cap-and-trade program for power plants is implemented, the states may consider expanding the program to other kinds of sources.
The action plan also establishes guiding principles for the program design, including: emphasizing uniformity across the participating states; building on existing successful cap-and-trade programs; ensuring that the program is expandable and flexible, allowing other states or jurisdictions to join in the initiative; starting the program simply by focusing on a core cap-and-trade program for power plants; and focusing on reliable offset protocols (i.e., credits for reductions outside of the power sector) in a subsequent design phase.
The goals have been translated into a model rule. Analyses have been conducted using REMI (a regional macroeconomic input-output model) and IPM (a detailed power sector linear programming model, run by ICF). This strikes me as the usual backwards analytical process: decide what you’re going to do by intuition or politics, then analyze it with stovepiped detailed models, neglecting to consider top-level interactions between the stovepipes, and getting bogged down in so much detail that it’s impractical to reexamine fundamental assumptions, dynamics between stovepipes, and alternative actions. Apparently NE-MARKAL has also been used through NESCAUM.
I’m not personally familiar with this initiative, but as with the WCI it looks like cap & trade driven by emissions targets is a foregone conclusion. The accord’s modeling subgroup has done some thoughtful scoping, but doesn’t appear to have launched a project yet.
Oregon has aggressive goals, not too different from California’s: “by 2020 to achieve greenhouse gas levels 10% less than 1990 levels and by 2050 to achieve greenhouse gas levels 75% below 1990 levels.” The technical arm of Oregon’s Carbon Allocation Task Force has evidently performed some topical analyses, but not on the scale of California’s efforts. As elsewhere, efforts focus on cap & trade for the power sector.
The Arizona Climate Action Initiative looks like it’s just getting rolling. Executive Order 2006-13 establishes a statewide goal to reduce Arizona’s future GHG emissions to the 2000 emissions level by the year 2020, and to 50 percent below the 2000 level by 2040. A climate action plan establishes baseline emissions from data, and a reference projection by extrapolation.
Again, I don’t see model-based analytical output at the Department of Ecology’s site, though there are fairly extensive draft recommendations for ways of tackling markets and sectors. Interestingly, Washington’s transport strategy starts with vehicle miles traveled (VMT), unlike California, which starts with intensity (vehicle efficiency and fuel carbon intensity).
There was a flurry of activity two years ago, but I can’t find any recent model-based analysis. The NM Climate Change Advisory Group did generate one output you can sink your teeth into: an economic analysis of cap & trade by Rose & Wei (see Attachment H-10 here). This is a fairly simple model that posits carbon emissions supply curves for each of 11 western states, then finds the market equilibrium under various cap & trade designs. Under one scenario described, the market clears at $20/tonCO2. California is the largest net permit seller ($1.1 billion) and Utah is the largest net buyer ($455 million; a much larger per capita impact). Total transactions exceed $1 trillion, but result in substantial reductions of mitigation costs. It will be interesting to see whether states’ appetites for the WCI stand up under the prospect of being on the losing end of large net financial transfers from trading. My guess is that they won’t (even though economic theory shows that it’s still a good thing) – another argument for carbon taxes (under which regions keep their revenue).
I haven’t had a chance to investigate every state, so look for a Part II, and please comment if you have something to add. Like New Mexico, Montana, Minnesota, and North Carolina appear to have followed a CCS framework, under which an advisory group generates a policy roadmap, aided by technical working groups for agriculture and forestry, energy supply, residential/commercial/industrial, transportation and land use, and crosscutting issues. Generally the process seems to involve a lot of talking and not much formal modeling; it would seem to be a golden opportunity to develop a portfolio of simple models that could be replicated across regions. (Note that I don’t mean to diminish the importance of talking – it’s essential, and I’ve been facilitating conversations among stakeholders in California. However, it’s hard to make conversations internally consistent and to share the learnings with others. Models are a good way to formalize a conversation so that it can be shared, critiqued, and used by others.)