Want to Schedule Your Electricity Use to Reduce Pollution? Here’s How

Some of us occasionally feel the urge to turn off the kitchen/porch/office light as our small step towards addressing global climate change. A Berkeley PhD student – Gavin McCormick – has started a nonprofit to provide information on exactly how our actions impact pollution.

Gavin’s organization, WattTime, is analyzing data from around the US to provide information like the map below. You can hover over an area to get almost live information on CO2 emissions.


It turns out that it’s not straightforward to generate the information behind maps like this – far from it.

Consider two different scenarios. In both, I’m assuming that you’re doing something that you don’t usually do – turning off the porch light earlier, for instance – and that other consumers do not change what they do.

To understand what Gavin is doing, we first need a basic understanding of electricity grid operations. Many readers no doubt understand this better than I do, and this is a highly stylized description, but it works for these purposes.

Wherever you live, there’s a grid operator charged with balancing the electricity system and ensuring that there’s enough power generated at any given time to meet demand. The operator also needs to ensure that the plants are not generating too much as that could damage equipment.


The grid operator communicates with power plant operators in the region about how much they’re producing and with the grid operators in adjacent areas about imports and exports. Much of the communication is automated and, for instance, the grid operator’s “request” for less electricity when you turn off your light would likely be communicated through something called Automatic Generation Control (AGC).

Go back to turning off the porch light. If you live in Ohio and it’s a regular night, it’s possible that the AGC system will instruct a coal plant to reduce production. That’s great if you’re trying to reduce GHGs or other pollutants, as coal plants are as dirty as they come.

Turning off your light in West Texas may not be as helpful for reducing greenhouse gas emissions, especially if it’s windy. In this case, you well might be asking the grid operator to back off on the output from wind plants.

In fact, many wind producers receive subsidies from the federal government that increase in the amount of electricity they produce. This is called the production tax credit, and it was recently $23/MWh. So, wind producers actually want you to keep your lights on in the middle of a windy night. In fact, prices can be negative (though rarely below -$23/MWh), meaning that the wind turbine producers are willing to pay consumers to take their power at that point in time.

West Texas Market Clearing Prices for 2010

One thing that’s great about Gavin’s site is that he’s striving to use a better methodology than what’s out there now. There are other sites that simply report the average emissions in a given hour. So, for the Ohioan turning off the light, the other sites are averaging across zero-GHG-emissions nuclear power plants and the coal plants.

This calculation will provide a misleadingly low estimate of the impact of your actions, though, since the nuclear power plants won’t change their output when you turn off your light. They are not marginal, in the language of economists. So, it doesn’t make sense to account for their emissions, as your actions don’t affect them. While average GHG emissions vary by a small amount throughout the day, the marginal plant can vary a lot – from particularly dirty coal to emissions-free wind. The map above still reflects averages, but WattTime maps reflecting marginal emissions are coming very soon.

My example about a single porch light is actually below WattTime’s aim, as a 100W porch light is 1/5,000,000th of the output of a typical 500 MW plant. They’re really targeting the larger decisions by, for example, designing smart plugs for electric cars and industrial load controllers.

If Gavin’s company takes off, which we’re all cheering for, the calculations get a lot more complicated. If his company accounts for a large and predictable share of electricity demand, grid operators might anticipate that fewer people will turn on their porch lights when polluting plants are marginal, and adjust their decisions about which plants to turn on for the day. Ultimately, planners might anticipate this reaction and adjust the type of power plants they build. Gavin and crew are working on incorporating longer run decisions, so stay tuned for Version 2.0 of their site.

Information will help us make better decisions, and I’m delighted that there are innovators like Gavin out there who are perfecting the information that consumers get, and designing cool websites and apps to put the information in front of us.

Posted in Uncategorized | Tagged , , , | 19 Comments

Renewable integration challenges create demand response opportunities

The power grid is getting greener. The graph below summarizes EIA projections of U.S. non-hydro electricity generation under different assumptions about greenhouse gas regulations, fuel prices, and technology costs:


Source: http://www.eia.gov/todayinenergy/detail.cfm?id=16051

Although there is some debate over whether these EIA projections are too conservative, it seems we can all  agree that the penetration of non-hydro renewables will continue to increase in the coming years.

The power grid is also getting smarter.  The Smart Grid Investment program invested close to $8 billion in accelerating the deployment of smart grid infrastructure and technology. It is estimated that smart meters will have been deployed to over 50 percent of U.S. end users by 2015.

Some recent studies highlight some important complementarities between a greener grid and a smarter grid. Before connecting these dots, let’s first review the key operational challenges associated with increasing integration of renewables.

Why lose sleep over increasing grid-penetration of renewables?

Here in California, the “duck chart” has become emblematic of the challenges that increased renewable generation (and solar in particular) could present. The duck helps to illustrate some key issues (not just in California, but any place the sun rises in the morning and sets in the evening).


The colored lines trace out actual (2012-2013) and forecast (through 2020) electricity demand less generation from variable renewables, including wind and solar (“net load”).  As solar PV accounts for a larger share of generation, the change in the net load profile takes on a duck-like shape. Note three key take-aways:

  • Ramping demands: Increased solar puts stress on the system when the sun rises and sets. Conventional generation must ramp down and up to compensate.
  • Over-generation can be a problem when solar output peaks in the early afternoon if demand levels are modest and  inflexible base load generation bumps up against minimum output constraints.
  • Declining marginal value: As the level of renewables penetration (solar in particular) increases, renewable energy output becomes less coincident with peak net load. This drives down the marginal value of the electricity generated, in part by reducing the capacity value of solar on the build margin and in part by driving up the marginal cost of managing variable energy output.

This duck is only an illustrative tool.  For one thing, the chart is based on a somewhat non-representative day in which solar output is high but temperatures are cool and demand for air conditioning low. Perhaps more importantly, the graph makes no attempt to account for adjustments in energy infrastructure and energy markets that can be deployed to mitigate stresses on the system. Fortunately, we have many options available when we think about re-optimizing the electricity sector to accommodate higher levels of renewable energy generation.

Meeting the renewables integration challenge

Over a year ago, Catherine wrote a great post raising key questions about the relative merits of storage versus demand response to renewable resource integration challenges. A year later, we have in hand some studies that systematically consider how different power system investments and operational changes can mitigate ramping and over-generation problems associated with increased renewables penetration.

One study in particular – recently released by Andrew Mills and Ryan Wiser of LBNL- caught my attention last week.   The paper considers alternative approaches to meeting the renewables integration challenge including: energy storage, demand response (assuming a demand elasticity of -0.1), investment in more flexible gas generation, and diversification in renewables deployment (to reduce variance of aggregate renewables output).

The study assesses the economic value of these response options, where “value” is defined in terms of the change in the marginal economic value of wind or solar relative to a base case where no measures are deployed.  That’s a mouthful. The basic idea is the following.  The authors simulate long-run investment decisions, generation dispatch, and wholesale market clearing in California’s electricity sector under a baseline scenario and calculate the marginal economic value of renewables (in terms of energy and capacity cost avoided). They then repeat the entire simulation exercise assuming one of the mitigating alternatives has been deployed.[1]

The following table summarizes some key results from the study:


Qualitatively, the results are quite intuitive. At very high solar penetration rates, bulk storage is particularly valuable. Diversification is more effective in the high wind penetration scenarios. Demand response (RTP)  increases the marginal value of both wind and solar at low and high penetration rates.

Importantly, the study stops short of estimating costs.  Dedicated bulk storage is likely to be costly. In contrast, we have already made a significant investment in the smart grid infrastructure we would need to operationalize widespread demand response.

Smart renewables integration should leverage the smart grid

Increased penetration of variable renewable resources increases the potential value added by demand response. In this sense, renewables integration creates opportunity for demand response. In order to tap this potential,  we’ll need to enable broad based and highly flexible demand response.  This represents a significant departure from today’s standard DR programs.  There is much more we can do- both in terms of automation and pricing- to leverage investments in smart-grid infrastructure. With renewable energy penetration rates on the rise, the cost of overlooking these opportunities gets harder to justify.


[1] Consider, for example, the high solar penetration scenario.  The simulated marginal value of solar  is $25.32/MWh at a 30% PV penetration rate in the baseline scenario.  When demand response to real time pricing incentives is incorporated into the simulations, the marginal value of solar increases to $32.76/MWh. This implies a value of $7.44/MWh.




Posted in Uncategorized | Tagged , , , | 3 Comments

What’s the goal and point of national biofuel regulation?

While preparing a lecture for the 4th Berkeley Summer School in Environmental and Energy Economics, I returned to contemplating the regulation of biofuels as part of a federal strategy to combat climate change and increase energy security. If we review policy approaches for increasing the share of biofuels in the transportation fuels supply across this great land, there are three main approaches. We have subsidies for the production of ethanol and biodiesel, renewable fuels standards (RFS) and low carbon fuels standards (LCFS).

The two main tools employed at the federal level are subsidies, which essentially provide a per gallon payment for producing a gallon of a certain type of biofuel, and renewable fuels standards, which require the production of different classes and quantities of biofuels over a prescribed time path. California has employed a low carbon fuel standard, whose goal it is to decrease the average carbon content of California’s gasoline by prescribed percentages over time. It relies on life cycle calculations for the carbon content of different fuels and allows producers to choose a mix of different fuels, which decrease the average carbon content, thus providing more flexibility in terms of fuels compared to the RFS.

If I were elected the social planner, I would recognize that I am most likely not smarter than the market, but also would not trust the market to make the right decisions when it comes to carbon reductions (see the demonstrated record of markets since 1850). The standard way an economist would approach the problem, assuming that we know what the right amount of carbon abatement is, is to set a cap on emissions and issue tradable rights to pollute (a cap and trade). This would in theory lead to the desired level of emissions reductions at least cost. While preparing for my lecture, I was thinking I should set up a simple model where profit-maximizing producers of fuels face different policy constraints (e.g., subsidies, RFS, LCFS or a cap and trade), a reasonable demand curve and my giant computer. As so often happens to many of us environmental and energy economists, EI@Haas’ all-star team captain Chris Knittel (MIT) and coauthors had already written the paper, which is titled “Unintended Consequences of Transportation Carbon Policies: Land-Use, Emission, and Innovation”.

[Skip this paragraph if you are not a fan of wonk]. The paper, which is a great and relatively quick read, simulates the consequences of the 2022 US RFS, current ethanol subsidies and constructs a fictional national LCFS and cap-and-trade (CAT) system, which are calibrated to achieve the same savings as the RFS. The paper assumes profit-maximizing firms which either face no policy, the RFS, subsidies, LCFS or CAT. Using an impressive county level dataset on agricultural production and waste, the authors set out to construct supply curves for corn ethanol and six different types of cellulosic ethanol. Chris’ daisy chained Mac Pros then maximize profits of the individual firms by choosing plant location, production technology, and output conditional on fuel price, biomass resources, conversion and transportation costs. Changing fuel prices and re-optimizing gets them county level supply curves. Assuming a perfectly elastic supply of gasoline and a constant elasticity demand curve for transportation fuels, they solve for market equilibria numerically.

They use the results to compare the consequences of each policy type for a variety of measures we might care about. Here is what happens:

The CAT leads to the greatest increase in gas prices and largest decrease in fuel consumption. It leads to no additional corn ethanol production and slight increases in second-generation biofuels. The RFS and LCFS both lead to less than half the price increase and fuel reduction compared to the CAT. Both policies see a four to nine fold increase in corn ethanol production relative to no policy and a massive ramp up in second generation biofuels production. All three measures lead to the same reductions in carbon emissions. The subsidies leave fuel costs constant, do not change fuel consumption and lead to a massive increase in first and second generation biofuels, but only achieve two thirds of the carbon reductions compared to the other policies (which is due to the authors using current subsidy rates rather than artificially higher ones which would lead to the same carbon savings).

Biofuels lead to lower gas prices and equivalent carbon savings! This is the point, where biofuels cheerleaders scream “everything is awesome!” But this ain’t a Lego movie. Especially since Legos are not made from corn. The paper evaluates the policies along a number of dimensions. First, compare the abatement cost curves for the CAT and the LCFS. When it comes to marginal abatement cost curves, the flatter, the better. What we see in the paper is a radically steeper marginal abatement cost curve from the LCFS compared to the CAT. In equilibrium the marginal abatement cost for the LCFS is almost five times higher that of the CAT. What about those emissions reductions? What happens in practice is that the CAT leads to higher emissions reductions from reduced fuel consumption (by driving less or more efficient cars) and a little bit of fuel switching. For the LCFS there is much more fuel switching and not much less driving.

What about land use? Well, since the non CAT policies incentivize ethanol production, significant amounts of crop and marginal lands will be pulled into production.

figure 3

The paper shows that total land use for energy crops goes up about ten fold under the biofuels policies and only by about 30% under the CAT. The paper calculates that damages from erosion and habitat loss from these policies can reach up to 20% of the social cost of carbon compared to essentially 0% for the CAT.

Further, ethanol policies create the wrong incentives for innovation, where in some settings the incentives are too strong and in others they are too weak. A further aspect of the paper, which is incredibly clever, is that they show the cost of being wrong in terms of the carbon intensity (e.g., you get the indirect land use effect wrong, which is almost certainly the case) of different fuels can lead to massive amounts of uncontrolled emissions. The carbon damage consequences of being wrong by 10% in terms of the emissions intensity of corn ethanol are an order of magnitude (read 10 times!) the number for the cap and trade. Before I wonk you to death, I will close with some more general thoughts, but staffers of carbon regulators should read this paper. Now.

What this work shows is that in the case of biofuels setting a simple universal policy, which lets market participants choose the least cost ways of finding emissions reductions, is vastly preferred to complex renewable fuels or low carbon fuels standards. While I understand that producers of ethanol enjoy their subsidies (much like I enjoy my home interest mortgage deduction), this paper argues that they are a bad deal for society. And so is the RFS, as would be a national LCFS. As we go ahead and design a national carbon policy, I would hope that we take the lessons from this paper and the decades of environmental economics insight it builds upon to heart. This does not say that first or second generation biofuels are a bad idea, but if they want to compete for emissions reductions, they need to be fully cost competitive with other and currently lower cost emissions reductions alternatives.

Posted in Uncategorized | Tagged , | 1 Comment

Raising Gas Prices to Grow An Economy

Two weeks ago, Yemen increased gasoline prices from $2.20 to $3.50 per gallon, while increasing diesel prices from $1.70 to $3.40.

And last month, Egypt increased gasoline prices from $.47 to $.83 (premium gasoline went from $1.00 to $1.40), while increasing diesel prices from $.61 to $1.00.

These are significant increases.  The reforms in Yemen bring the price of both fuels up to market levels.  And although prices in Egypt remain well below market levels, this is an important step toward rolling back subsidies in a country that has some of the largest energy subsidies in the world.

Economists, including myself, always complain about energy subsidies and celebrate in cases like this when subsidies get rolled back. But what is the big deal?  What’s wrong with subsidizing gasoline?


As I discuss in the video, the economic cost of fuel subsidies can be summarized by this figure, straight out of Econ 101.

PowerPoint Presentation

If you are like most people, you tune out whenever anyone says, “deadweight loss”.  But this is just economist-speak for waste.  When prices are subsidized, gasoline and diesel end up being used in a whole host of low-value ways.  People buy fuel-inefficient vehicles and drive them too much. They produce goods and services using inefficient, fuel-intensive technologies.  And they consume too many fuel-intensive products.

Subsidizing energy shrinks the economy. The deadweight loss triangle means that it costs the economy more to supply this fuel than the value these consumers get out of consuming. So, with every transaction, economic value is destroyed.  This is the opposite of gains from trade.  This is losses from inefficient trade.

By my calculations, prior to the reform the deadweight loss from fuel subsidies in Yemen was $40 million per year.  Total fuels expenditures in Yemen is $1.2 billion annually, so this is small compared to the size of the market. Worldwide, there are many countries with larger subsidies than Yemen.  In fact, Yemen is not even in the top 20.

Egypt, incidentally, with much more generous subsidies and a larger population, was #5 in 2012 in terms of total welfare loss from fuel subsidies, behind only Saudi Arabia, Venezuela, Iran, and Indonesia. When I next redo these calculations, I expect to see Egypt slip back a couple of notches.

The price increases in Yemen and Egypt will also decrease the burden of pollution, traffic congestion, and vehicle accidents. A new IMF report finds that the total cost of externalities from driving exceeds $1.00 per gallon in most countries.  By my calculations, removing subsidies in Yemen will decrease fuels consumption by 90 million gallons per year (a 15% decrease).  So if external costs are $1.00 per gallon, this is $90 million annually in additional benefits.

Sana'a Traffic 2

Traffic jam near Sana’a, the capital of Yemen.

By the way, you might have noticed that there is a smaller purple triangle to the left of the externalities rectangle. To maximize welfare you really want to increase prices all the way to social cost. This would further decrease consumption, yielding this additional welfare gain. You can think of this as another deadweight loss triangle or, alternatively, think of the entire larger triangle as deadweight loss relative to the full social cost of fuels consumption.

(Yes, this is exactly the same as the discussion in California about including transportation fuels in the cap-and-trade program for carbon dioxide. See here and here. The whole point is to move California fuel prices closer to full social cost.)

There is more work to do in both countries. In Yemen, it will be important to once-and-for-all allow gasoline prices to float at market levels. These reforms have brought prices up to market levels, but if there continues to be price controls, these gains will erode over time with inflation. In Egypt, there is still a long way to go before market prices are reached.  The price increases last month went through with relatively little public protest (here), but it remains to be seen whether President Abdel Fattah el-Sisi will be able to push through deeper reforms.

I’m not claiming that subsidy reform is easy. The IMF has some interesting work aimed at trying to better understand the political challenges and potential approaches for facilitating reform (here).  But the economic analysis makes it clear that much is at stake. Pricing energy below cost imposes real inefficiencies, and these are enormous markets so the magnitude of the inefficiencies can be very large.

Posted in Uncategorized | Tagged , , | 18 Comments

Californians Can Handle the Truth About Gas Prices

A few weeks ago, Jim blogged about the concerns that cap-and-trade will drive up gas prices in California.   In late June, those concerns resulted in a letter from Assemblymember Perea and 15 other Democrats asking the California Air Resources Board to delay this expansion of the cap-and-trade program to include transportation fuels from January 1, 2015 to January 1, 2018.  And a couple weeks ago, the ARB Chair, Mary Nichols, sent a reply explaining why ARB was not going to do that.

Meanwhile, the oil industry and some other groups opposed to fuels in the cap-and-trade program have been making inaccurate statements that the change will cause huge increases in gasoline prices.  The ARB and some other supporters of fuels under the cap have responded with their own inaccuracies, saying that including fuels in the program needn’t raise gas prices at all and suggesting that any increase is the fault of oil companies.


There is a real policy debate here about how and when California should reduce its greenhouse gas emissions, 38% of which come from transportation.  I share Jim’s view that this is a moment of truth in which California needs to show it will really step up to reduce GHGs.  Unfortunately, that debate is being obscured by the battling spin over how much gas prices will go up when we expand cap-and-trade on January 1, 2015.

So here’s my attempt at de-spinning (I’m going to focus on gasoline, but the calculations are similar for diesel):

California’s gasoline blend sold at the pump is 90% gasoline and 10% ethanol, a ratio that is unlikely to change anytime soon.  Ethanol counts as zero carbon under cap-and-trade (long story, but not as silly as it sounds).  Pure gasoline emits about 0.009 tons of CO2e (the units of the cap-and-trade allowances) per gallon, so the gasoline blend you put in your car will make the seller responsible for about 0.008 (90% of 0.009) allowances per gallon.

The current price of an allowance is slightly less than $12/ton and the futures market predicts it will be about the same on January 1, 2015.  Our own analysis that I discussed a month ago also finds that the price of allowances will most likely remain in the $12-$15 range out to 2020.[1]  There is a small, but real, risk that allowance prices could go much higher a few years out, which we discuss in detail in our report. But if you want to know what gasoline price “shock” will hit consumers in January when gasoline comes under the cap and trade program, the relevant allowance price is about $12/ton.  That will increase the marginal cost of selling a gallon of gasoline by about 9-10 cents per gallon on January 1.

A large literature in economics has examined what happens to gasoline prices when the marginal cost of selling gas increases, looking at changes in the price of crude oil and changes in gas taxes.  The answer: those increases are passed through one-for-one to consumers, generally in a matter of days or maybe a week or two.

That’s why the almost certain outcome is that within a few days after January 1, 2015, the cap-and-trade program will cause the price of gasoline in California to increase by 9-10 cents, less than the drop in gas prices over the last few weeks.

GasPriceNonsenseSource: Energy Information Administration

 Average California gas price so far this year

(What’s that you say? You didn’t notice the drop? I’m not surprised.  With oil price fluctuations regularly pushing gasoline up or down 25 cents or more, an extra 10 cents one way or the other doesn’t catch the attention of most consumers.)

Before I move on to confront some of the spin, let’s consider that price increase in context.  A 10 cent increase will be about 2.5%.  Here are some things you could do to fully offset that additional cost:

  • Drive 70 mph instead of 72 mph on the freeway. That difference would improve your fuel economy by about 2.5%.  The savings are much larger if you actually drive the speed limit.
  • Buy a car that gets 31 MPG instead of 30 MPG. That will get you more than a 3% savings in fuel cost, more than offsetting the price increase.
  • Keep your tires properly inflated. The Department of Energy estimates that underinflated tires waste about 0.3% of gasoline for every 1 psi drop in pressure.

Instead of this simple reality, we are hearing misinformation coming from both sides:



What The Oil Industry is Claiming (and many others opposed to the program expansion are repeating):  The Western States Petroleum Association (WSPA) says at every opportunity that cap-and-trade will raise the price of gasoline by 16-76 (or 14-69) cents per gallon. Huh?  These ranges don’t even include the most likely effect of 10 cents.  The industry got to these much-scarier ranges in two ways, both of which are – to be charitable – not based on the current information.

First, they took a 2010 ARB study – from before the final details of the program were even set – that predicted a 4%-19% price increase back when gas prices were in the $3 range and just slapped it on the current price of $4.  That doesn’t make any sense because the cost of allowances doesn’t scale up and down with the price of gasoline.  But, in any case, the range was based on a range of possible allowance prices from 2010 analysis.  We know a lot more now than we knew in 2010.  For instance, we now know the current market price of allowances and the market’s prediction for the January price.  Those allowance prices imply gasoline prices will rise by 9-10 cents, below the bottom of the very wide range the oil industry asserts is possible.

Second, WSPA took a prediction from their own consultants’ 2012 report, which argued that allowances would cost $14-$70 and (doing the calculation slightly incorrectly) concluded that this would cause the emissions costs from gasoline to be 14-69 cents per gallon.[2]  More recent information suggests the best forecast for January is below this range, so the oil industry is just choosing to ignore more recent information.

On August 1, the oil industry doubled down on their assertions in a letter to ARB.  While making some valid points about ARB’s misguided claims (which I’ll discuss below), WSPA states that ARB’s 2010 numbers must be the best estimates out there because ARB hasn’t put out a new estimate. That seems less than genuine given that the oil industry is as familiar as anyone with the market price of allowances.  They can certainly do the calculation I’ve done above.[3]

The oil industry might respond that the high end of this range could conceivably happen years from now if no further changes to the program are made.  That’s true — as our report explains — but these figures are being used to argue for a 3-year delay in fuels under the cap, often using the WSPA range to discuss the price shock that might otherwise occur in January 2015.  The “shock’’ on January 1 will be about 10 cents.

The oil industry’s numbers are eye-catching — much more than the boringly realistic 10 cents a gallon impact — and they are getting traction. Media reports of expected increases include 15-40 cents, 17 cents or higher, 40 cents, 15 cents or more and 15 cents (surprisingly moderate for Fox News).  A few stories repeat claims that cap-and-trade could cause gas prices to spike by more than a dollar, though I haven’t seen that claim attributed or justified.  Even the letter from the Assemblymembers to ARB says of the immediate price jump at the pump on January 1, 2015: “an increase of about 15 cents is likely and a much larger jump is possible.”  Not true.



What the Air Resources Board is Claiming:  ARB officials and (others supporting the policy) seem to have decided that counterspin is a better strategy than straight talk.  They have repeatedly suggested that if gas prices rise in January, ARB policy would not be the cause:  Cap-and-trade just requires sellers to turn in allowances; whether they choose to pass along that cost to consumers is their decision, not ARB’s fault.  Really? Every economic analysis of cap and trade I have ever seen –left, right or center politically (and ARB’s own analysis) – recognizes that it will raise the cost of selling gasoline and that this increase will be passed along to consumers.  That isn’t due to some conspiracy.  It’s how markets work; when the marginal cost of selling a good goes up, firms raise their price.  The cap-and-trade program will cause gas prices to go up in January 2015 by about 10 cents per gallon.

An ARB spokesperson has also suggested that these costs somehow won’t or shouldn’t be passed along because oil companies have been buying allowances since 2012 and already have a lot of them.  What?!? That’s like saying you paid for your house long ago so now you should give it away for free when you move.  In reality, every allowance a fuel dealer uses to cover its compliance obligation from selling gasoline will be an allowance it can’t sell in the marketplace.  That’s a real cost.

In the letter to Assemblymember Perea and his colleagues and in other statements ARB argues that any impact from cap-and-trade should occur gradually, not a sudden jump on January 1.  But the cost effect of fuels under cap-and-trade will go from zero on December 31, 2014 to 10 cents on January 1, 2015.  Just like an increase in crude oil prices or raising a gas tax, the empirical evidence is that this will show up at the pump within days.

Bottom Line: Like Jim, I strongly support bringing fuels under cap-and-trade on January 1, 2015.  That’s been the plan for many years and the current arguments for delay contain no new information.  Robust debate is valuable, but that debate is undermined when the public is told either that this change won’t (or shouldn’t) cost them anything or that the cost will be many times higher than the most reasonable estimates.

One Final Note About Public Opinion: Many of the newspaper articles on the price increase and many of the advocates for delay are citing a poll by the Public Policy Institute of California.  They quote the PPIC report saying “A large majority of Californians (76%) favor this requirement [including transportation fuels in cap and trade], but support declines to 39 percent if the result is higher prices at the pump.”  Is that informative? When you look at the actual survey question (page 31, question 30), I’d say it’s pretty useless.  The question asks if you favor requiring oil companies to “produce transportation fuels with lower emissions?” and then “Do you still favor this state law if it means an increase in gasoline prices at the pump?”.  There is no specific increase mentioned; that’s left up to the imagination of the person answering.  I bet if they asked about a one cent increase, there would have been almost no change, and if it asked about a one dollar increase, support would plummet.  Too bad they didn’t ask about a 10 cent increase.  That would have been interesting.  But I have no idea how to interpret the results of the question that was actually asked.



[1] The California Legislative Analyst’s Office sent a letter to Assemblymember Perea last week that called our study the most credible of the studies they reviewed.  They used our estimates to say that gas prices would likely go up 13-20 cents by 2020.  They did not mention that the same reasoning implies the impact in 2015 will be about 9-10 cents per gallon, but that is what their analysis also implies.

[2] Actually, the report states this range for the year 2020, which is three years after the proposed delay of implementing fuels under the cap.

[3] Some in the oil industry continue to argue that transportation fuels under cap-and-trade will hurt sellers – it won’t because the cost will be fully passed through – and that sellers should receive some free allowances to cover this additional burden.  Free allowance allocation would just be equivalent to a cash gift to gasoline distributors; for the marginal cost reasons explained they would still raise gas prices. (In fact EU policy makers tried this and were “shocked’’ to see that the companies getting free EU-ETS allowances still raised their prices).

I tweet interesting energy news articles most days @EnergyClippings

Posted in Uncategorized | Tagged , | 25 Comments

Identifying the Best Ways to Increase Energy Access

NPR ran a story a couple months ago about a seemingly clever device. It’s called the Soccket. The name – and the device – combines soccer with electricity.

SoccketThe Soccket – created by a US-based NGO and distributed around the developing world – allows kids to play soccer during the day and then use the kinetic energy from their balls to power a reading lamp at night. Seems great – helps kids study even if they don’t have electricity in their homes.

To the Soccket entrepreneur’s dismay, NPR’s story pointed out that the devices weren’t robust. The reporter also interviewed a woman whose grandson had been given a Socket, noting that, “for the $60 it cost a charity to provide her family with one Soccket ball, she said she could have had her home hooked up to the electric grid, and that could have provided light for her whole family for years to come.” While her home didn’t have electricity, the grid had already come to her village.

The debates about the Soccket are representative of broader discussions about the best ways to bring electricity to the more than one billion people in the world who live without it: Lots of good intentions, but very little data that could help inform decisions about how to best increase energy access.

The current discussions about energy access tend to focus on two mechanisms: grid extensions and off-grid solutions, like solar home systems, village-level microgrids or even the Soccket. Sometimes these approaches are pitted against one another.

For example, debates between the Breakthrough Institute and Sierra Club have gotten heated. The Sierra Club sees huge potential for growth in off-grid solutions, like solar home systems. They recently put out a report containing the graph below, which depicts the amount of money for grid extensions dwindling while spending on minigrids and solar home systems (SHS) expands.

sierra club chartThe Breakthrough Institute is critical of the report, and notes that solar home systems and similar devices are, “a vision of, at best, charity for the world’s poor, not the kind of economic development that results in longer lives, higher standards of living, and stronger and more inclusive socioeconomic institutions.

Recent data that several colleagues and I have collected in Western Kenya suggest that the distinction between on-grid and off-grid may be too stark. As part of a larger project, we geo-coded over 20,000 structures and noted whether or not they were electrified. Very few of them were: only 5% of the homes and 22% of the businesses.

Here’s the surprising thing, though. All of these structures were within 600 meters of existing transformers. A full half of the unconnected homes were within 200 meters of an existing connection. We are calling these homes and businesses “under-grid” as they’re not on the grid but “off grid” just doesn’t capture their proximity to the existing grid infrastructure.

Many unelectrified households (in green) surround a transformer (T). White circle demarcates 600 meter radius.

Many unelectrified households (in green) surround a transformer (T). White circle demarcates 600 meter radius.

How can this happen? We have several hypotheses that we’re testing rigorously in on-going work. One notable fact is that households must pay over $400 for a connection, a very high sum in a country where average per capita incomes are around $1700. Kenya Power and Light Company claims that its average cost of establishing a new connection is even higher and appears uninterested in lowering the connection charge.

We suspect that there’s a virtuous cycle to take advantage of, though. If KPLC lowered the charge or even offered households a way to finance the charge, paying back the fixed costs over time, more households would likely connect. In turn, with a greater density of new connections, the average cost per connection is likely to be lower.

Building out the grid in Western Kenya

Building out the grid in Western Kenya

How representative is the situation in Western Kenya? To really answer that, we need to collect more hard data about electricity demand and supply around the developing world. The Soccket is clever, but donors interested in helping kids study at night should know that there may be cheaper ways to achieve that goal.

While we are collecting more data, though, I would like to see the term “under-grid” introduced into the debate. Rhetoric can matter, especially in the absence of hard facts. Often, people on both sides of the solar-versus-grid-extensions debate talk about waiting for the grid to “reach” households. Even the term “extensions” suggests a technological challenge, but our results in Kenya suggest that economics – getting the connection charges right – may be the crucial barrier.

There is one aspect of the Kenyan experience that is likely to have general resonance. The country embarked on a massive grid extension program in 2006 focused on electrifying all the schools in the country. Similar ambitions in other countries will bring the grid close to most people. And, after all, while having electricity in your home is one important measure of development, electrified schools and health centers, which are usually close to where people live, are also important.

The cover of the Sierra Club report is pictured below. The man seems proud of his solar home system, which I suspect is why the Sierra Club chose the picture. Note that in the background of the picture, and presumably close to the solar owners’ home, there are grid electricity lines. In many parts of the developing world, those lines could carry electricity from large- scale renewable resources, so the grid does not have to be synonymous with dirty fossil-fuel power.

Sierra Club CoverAchieving energy access for the billion-plus people without pillaging the climate will be one of the toughest challenges of our time. As we do that, it’s important to make decisions with the best possible information.

Posted in Uncategorized | Tagged , , | 12 Comments

Will coal exports abroad offset hard-won carbon reductions at home?

When President Barack Obama took office in 2009, he set a goal of cutting U.S. greenhouse gas emissions by 17 percent of 2005 levels by 2020.  The graph below shows that we appear to be making progress towards meeting this target.  The solid black line tracks domestic GHG emissions in recent years. U.S. emissions have now fallen to their lowest point in two decades!

coablogfigDomestic greenhouse gas emissions (left axis) and electricity generation shares by fuel (right axis)

Sources:  US EPA GHG emissions inventory (emissions) and EIA monthly energy review (fuel shares)

Researchers have been busy digging into the data to explain this decline in domestic emissions– most of which has occurred in the power sector (a great example of recent work can be found here). Part of the explanation clearly lies with the shale gas boom – and limited opportunities to export natural gas.  The resulting fall in domestic natural gas prices over the 2008-2012 has led to a re-allocation of electricity production from coal to gas-fired generating plants. The broken blue line in the graph shows the increasing share of US electricity generated using natural gas; the broken brown line shows the decline of coal. Increased penetration of renewables has also played a role in reducing coal’s share of electricity production over this period.

The graph also shows that we have a ways to go before we hit President Obama’s 2020 emissions reduction target (denoted by the red line).[1]  Recently announced standards to limit carbon pollution from existing power plants, in conjunction with other environmental regulations such as the mercury rule, are expected to further reduce the share of electricity generated using coal in the years ahead.

In sum, a reduced reliance on coal in the domestic power sector has been – and will continue to be – an important driver of reductions in domestic greenhouse gas emissions. But what is happening to the coal that we’re no longer burning here at home?

Domestic coal consumption down, exports on the rise

Over the period 2000-2012, domestic coal consumption declined by 18 percent whereas domestic coal production declined by just over 5 percent. The graph below helps to illustrate how the rise in net exports makes up the difference.

coalfig2U.S. coal imports and exports

Source : Energy Information Administration

This upward trend in net exports is expected to continue apace, particularly if coal companies succeed in building new coal-export ports in the Northwest. It is estimated that ports under consideration in Oregon and Washington could eventually ship over 100 million tons of coal per year to Asia. These developments have environmentalists urgently questioning the extent to which increased energy exports will undermine carbon emissions reductions achieved within the U.S.

What effect do U.S. coal exports have on global GHG emissions?

To answer this question, we need to make assumptions about what patterns of global energy consumption would look like in a world with and without US coal exports. Not surprisingly, different assumptions can generate very different answers.

Consider, for example, a provocative report released earlier this year by the CO2 Scorecard Group.  This report – which attracted considerable attention in the energy/environment blogosphere- looks to estimate the extent to which increased coal exports have eroded domestic emissions reductions from the shale gas boom.  The authors begin by estimating the impact of the shale gas boom on domestic steam coal exports. They then multiply each exported ton by the EPA-reported average emissions rate of 1.8 metric tons of CO2 per short ton of steam coal consumed in the electric power sector. They conclude that, between 2007-2012, CO2 emissions from coal-to-gas fuel switching were more than offset by increased emissions associated with coal exports.[2]

Importantly, this approach assumes that domestic coal exports act to increase global energy consumption, versus displace coal or other energy sources. In other words, each ton of coal exported is assumed to be additional to – versus substituting for- energy that would otherwise be consumed. In fact, it seems much more likely that some fraction of the coal exported will crowd out other coal supplies. Particularly when you consider that China – with its seemingly insatiable appetite for coal- was the third largest destination for US coal exports in recent years. Only the Netherlands and the UK imported more U.S. coal in 2012.

With this in mind, Stanford economist and Energy Institute affiliate Frank Wolak puts forward a different view. Frank and co-authors have been analyzing the likely emissions impacts of expanding U.S. coal exports to Asia using an economic model of global coal markets. This research is finding that increasing domestic coal exports to China could reduce GHG emissions. The basic argument is as follows. Because China has very little natural gas-fired generation and highly inelastic demand for coal, U.S. exports of coal to China will substitute for other coal.  Selling U.S. coal to China could raise coal prices in the U.S. and Europe (a major importer of U.S. coal). In both of these regions there is flexible natural gas fired capacity capable of substituting for coal in the production of electricity. This fuel switching would reduce greenhouse gas emissions. Keep an eye on this site for a full report coming soon.

The bottom-line

Many are hoping that the current U.S. commitment to reducing domestic emissions will provide the moral authority needed to negotiate international commitments to reducing global greenhouse gas emissions next year in Paris.  If we really want to lead by example, it is important to understand and account for the emissions implications of both our energy consumption and production. The extent to which U.S. increased coal exports offset reductions in domestic GHG emissions will depend on parameters that are difficult to estimate, including the elasticity of supply for coal at home and abroad, the elasticity of supply of other energy sources (e.g. natural gas), and the own-price elasticity of demand for coal in China and elsewhere.  That said, economics research can and should shed some much needed light on the most likely emissions implications of US energy exports.


[1] This graph may misrepresent the true target. It is not clear if the official pledge refers to all GHG emissions. The pledge is to reduce emissions: “In the range of 17%, in conformity with anticipated U.S. energy and climate legislation..” The “legislation”  was Waxman-Markey which targeted energy-related emissions primarily.

[2] These numbers would look even worse if we account for the emissions generated in transporting the coal abroad. Based on Joe Shapiro’s excellent work on the emissions implications of trade, this could amount to roughly 0.16 tons CO2 per ton of coal exported. On the flip side, these numbers would look a little better if we account for the fact that coal plants in some importing countries out-perform the average US coal-fired power plant in terms of fuel efficiency and emissions intensity.

Author Comment

Many thank to Andrew Revkin for mentioning this post in his New York Times blog and drawing more attention to these issues.

The intended points of my post are: the impacts of domestic coal exports on global greenhouse gas emissions are difficult to tease apart but important to understand; different underlying assumptions can lead to different conclusions; and, new research in this area will help to shed more light on this controversial question.

This prompted a detailed response from CO2 Scorecard: http://co2scorecard.org/home/researchitem/30

Back-and-forth discussion of the strengths and limitations of different modeling approaches/assumptions can help us understand the true emissions impacts of US energy exports on global emissions. An important – and continuing – conversation to be having on this blog and elsewhere. Thanks for reading.


Posted in Uncategorized | Tagged , , , , , | 6 Comments