RGGI Lessons to Date – November 2019 Edition

I recently had a simple version of this RGGI article published at Whats Up with That .  This article provides more details and considers other issues with the Regional Greenhouse Gas Initiative (RGGI).  The program is ten years old and has been touted as a successful example of a “cap and dividend” pollution control program and now it is being proposed as the model for a similar control program in the Transportation Control Initiative (TCI).  This post looks at the numbers to see if this praise is warranted and whether RGGI is a good model for the proposed TCI.  Ultimately the question is whether any cap and trade program for carbon dioxide (CO2) can be successful.

I have been involved in the RGGI program process since its inception.  I blog about the details of the RGGI program because very few seem to want to provide any criticisms of the program. I have extensive experience with air pollution control theory and implementation having worked every cap and trade program affecting electric generating facilities in New York including the Acid Rain Program, Regional Greenhouse Gas Initiative (RGGI) and several Nitrogen Oxide programs.  Note that my experience is exclusively on the industry side and the difference in perspective between affected sources trying to comply with the rules and economists opining about what they should be doing have important ramifications.  The opinions expressed in this post do not reflect the position of any of my previous employers or any other company I have been associated with, these comments are mine alone.

Background

RGGI is a market-based program to reduce greenhouse gas emissions. It is a cooperative effort among the states of Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode Island, and Vermont to cap and reduce CO2 emissions from the power sector.  According to a RGGI website: “The RGGI states issue CO2 allowances which are distributed almost entirely through regional auctions, resulting in proceeds for reinvestment in strategic energy and consumer programs. Programs funded with RGGI investments have spanned a wide range of consumers, providing benefits and improvements to private homes, local businesses, multi-family housing, industrial facilities, community buildings, retail customers, and more.”

The RGGI states developed a cap during a long stakeholder process that was based on historical operations and emissions.  The cap is the regional budget for CO2 emissions.  The Nine-State RGGI Region Emissions, Original RGGI Cap, and the Adjusted RGGI Cap table lists observed emissions and two caps.  The original cap was developed before the fracking revolution changed the cost of natural gas such that it became significantly cheaper than coal and residual oil.  After natural gas prices dropped so much the original projections for emissions were so out of tune to what was happening the RGGI states developed an adjusted cap to account for that development.

In order to determine if RGGI is successful and a program to emulate let’s define some metrics.  The primary goal of the program is to reduce greenhouse gas emissions (GHG) from the electric generation sector so quantifying the emissions change from before the program to the present is a key metric.  Another appropriate metric is cost efficiency per ton of CO2 reduced compared to the Social Cost of Carbon (SCC).  This parameter is an estimate of the economic damages from emitting a ton of CO2 and is widely used to justify GHG programs.  For a comparison metric I will ignore issues with this parameter even though I agree with the following by Paul Driessen and Roger Bezdek: “The SCC assumes fossil-fuel-driven carbon dioxide emissions are causing dangerous manmade climate change, and blames U.S. emissions for every conceivable climate-related cost worldwide. But it fails even to mention, much less analyze, the tremendous and obvious benefits of using oil, gas and coal to power modern civilization.”

In addition to these metrics we have to look at lessons learned and considerations that are not yet resolved to determine whether RGGI is a good model for future control programs.  I address the following: the theory and reality of historical trading programs, control options for affected sources, allowance management, allowance ownership and allowance costs.  Most of these issues were not discussed in the What’s Up with That post.

Theory and Practice

I agree with the argument that economic incentives or market trading programs reduced emissions more cost-effectively than a command and control program.  However, it is instructive to look at the reasons why emission reductions occurred because the theory does not necessarily drive the observed reductions.  It is necessary to review historical performance of RGGI to determine why CO2 emissions reductions have occurred so we can reasonably expect a similar result in other applications like the TCI..

Let me first point out that there is a fundamental difference between the way affected sources operate in emissions trading markets and the way economic theory predicts they should operate.  I believe that electric generating affected source allowance management is different than theory because the affected sources do not treat allowances as a storable commodity or a financial asset in the usual sense of the term.  Instead allowance management is overwhelmingly driven by regulatory requirements for the current compliance period. i.e., do I have enough allowances to cover expected emissions?  Financially it is simply another cost of operating and not a potential profit center.  The important difference is that the academic economic theory holds that affected sources are looking years into the future, but in reality, there is no such long-term time horizon for affected sources.  Their decision on the quantity of allowances to buy is driven by their expected operations in the period between auctions and, at most, the entire compliance period.  Also note that most companies include a small margin for operational variations and regulatory compliance considerations. Because of the differences between the way affected sources operate and the way economic theory says they should operate, I have little faith in the models that predict future allowance margins.

The Acid Rain Program (ARP) was undoubtedly a successful program because it lowered emissions more than expected at far lower costs than predicted.  This program was open and transparent so all emissions and allowance data are available.  In order to meet the initial emission cap target of a 50% reduction, affected sources were awarded half of their historical emissions.  Although it is common practice to vilify this program for giving away the allowances for free the rationale is still valid today. The concept for the acid rain program was that power plants would install SO2 control equipment and if they over-controlled their emissions, they could sell the excess allowances earned to other facilities that could not install the control equipment as cost-effectively.  This approach incentivizes over-control because affect sources can subsidize control equipment investments they made by selling excess allowances.  This cost reduction efficiency brings down overall costs.   It turned out that fuel switching and technological improvements were so effective that far greater than expected reductions occurred.  Fuel switching occurred because technology to burn lower sulfur coal was developed and railroad de-regulation opened the market to transporting coal cost-effectively over very long distances. Another subtle point is that the ARP allowance bank was earned, that is to say excess allowances in the bank represent over-controlling emissions lower than the cap limits.

The Regional Greenhouse Gas Initiative (RGG) is a cap-and-invest program that has been touted as a model for a TCI cap-and-invest trading program because of its “success”.  Although the RGGI states claim that the program is open and transparent the fact is that there is no allowance ownership information available.  There is no question that CO2 emissions have come down in the RGGI states since the inception of the program but it is important to determine why they have come down.  I will address that point later on.  There is a fundamental difference in the way that affected sources treated RGGI as opposed to ARP, namely ARP was considered a control program and RGGI was considered a tax.  Because there are no cost-effective add-on controls for CO2 at existing power plants there are limited options to meet the cap.  Because allowances all have to be purchased and the incremental cost was low plant control programs to reduce CO2 through efficiency were not implemented.  The allowance bank does not represent earned reductions below the cap limits.  Instead the bank is made up of allowances purchased at auctions and on the market.  The RGGI states in their program reviews were very concerned that the allowance bank was large and have taken steps to adjust the allowances sold at auction to force the bank smaller.  In the naïve belief that RGGI investments significantly reduced emissions the RGGI states have also reduced the cap going forward.  As a result. RGGI going forward is going to be significantly different that RGGI in the past and that has ramification on its value as a model for TCI or any other future emissions trading program.

I noted above the distinction between the ARP “earned” allowance bank and the RGGI allowance bank.  Because the ARP affected sources over-controlled emissions below their cap levels, they earned the allowance bank.  That means the bank represents surplus allowances that are not needed for compliance so it does not matter who owns them.  On the other hand, all RGGI allowances were purchased at one time or another by anyone who offered a high enough price at an auction or on the market.  Because allowance ownership is not transparent, we only know the number of allowances owned in the following three categories:

      • Compliance-oriented entities are compliance entities that appear to acquire and hold allowances primarily to satisfy their compliance obligations.
      • Investors with Compliance Obligations are firms that have compliance obligations but which hold a number of allowances that exceeds their estimated compliance obligations by a margin suggesting they also buy for re-sale or some other investment purpose. These firms often transfer significant quantities of allowances to unaffiliated firms.
      • Investors without Compliance Obligations are firms without any compliance obligations.

To this point in 2019 the affected sources with compliance obligations have been able to get the allowances needed to cover their emissions from auctions and the market.  However, at some point going forward this will change and it will make a difference.  I have addressed the status of RGGI emissions and allowances elsewhere but briefly because the allowance cap is being reduced so much, the affected sources are going to have to go to the investors without compliance obligations.  This is uncharted territory and, at a minimum, I expect that the allowance prices will spike upwards.  Note that this price spike provides no dividends for CO2 reduction investments because the dividends are earned at the initial sale.  But it could be even worse if the entities without compliance obligations withhold allowances and create a shortage such that affected sources do not have enough allowances to run.

RGGI supporters who claim it is successful point to emission reductions of 40 to 50%.  In order to evaluate the RGGI emissions reduction claims I used data from the Environmental Protection Agency Clean Air Markets Division air markets program website.  Emissions data from the electric generating unit (EGU) sector are available from before RGGI started to the present, so I downloaded all the EGU data for the nine states currently in RGGI from 2006 until 2018.  In order to establish a baseline, I calculated the average of three years before the program started.  As shown in the RGGI Nine-State EPA CAMD Annual CO2 Emissions table the total emissions have decreased from over 127 million tons prior to the program to just under 75 million tons in 2018, for over a 40% decrease.  Note that these numbers are slightly different than the previous table because different sets of sources are used.

However, when you evaluate emissions by the primary fuel type burned it is obvious that emissions reductions from coal and oil generating are the primary reason why the emissions decreased.  Note that both coal and oil emissions have dropped over 80% since the baseline.  Natural gas increased but not nearly as much.  I believe that the fuel switch from coal and oil to natural gas occurred because natural gas was the cheaper fuel and had very little to do with RGGI because the CO2 allowance cost adder to the plant’s operating costs was relatively small.   There is no evidence that any affected source in RGGI installed add-on controls to reduce their CO2 emissions.  The only other option at a power plant is to become more efficient and burn less fuel.  However, because fuel costs are the biggest driver for operational costs that means efficiency projects to reduce fuel use means have always been considered by these sources.   Because the cost adder of the RGGI carbon price was relatively small I do not believe that any affected source installed an efficiency project as part of its RGGI compliance strategy.

As a result, the only reductions from RGGI that can be traced to the program are the reductions that result from direct investments of the RGGI auction proceeds. Information necessary to evaluate the performance of the RGGI investments is provided in the RGGI annual Investments of Proceeds update.  In order to determine reduction efficiency, I had to sum the values in the previous reports because the most recent report only reported lifetime benefits.  In order to account for future emission reductions against historical levels the annual reduction parameter must be used.  The Accumulated Annual Regional Greenhouse Gas Initiative Benefits table lists the sum of the annual avoided CO2 emissions generated by the RGGI investments from three previous reports.  The total of the annual reductions is 2,818,775 tons while the difference between the baseline of 2006 to 2008 compared to 2017 emissions is 59,508,436 tons.  The RGGI investments are only directly responsible for less than 5% of the total observed reductions!

In order to argue that RGGI emission reduction programs are a good investment relative to the expected societal cost of CO2 emissions the Social Cost of Carbon (SCC) parameter can be used.  SCC values range widely depending on assumptions, but if you use a discount rate of 3% and consider global benefits like the Obama-era Environmental Protection Agency (EPA) did then the 2020 SCC value is $50.  The Accumulated Annual Regional Greenhouse Gas Initiative Benefits table lists the data needed to calculate the RGGI CO2 reduction cost per ton.  From the start of the program in 2009 through 2017 RGGI has invested $2,527,635,414 and reduced annual CO2 emissions 2,818,775 tons.  The result, $897 per ton reduced, is 18 times than the current EPA SCC value for United States benefits.

There is another key lesson from RGGI that applies to any CO2 emissions marketing control program. There is an important difference between cap and trade programs for SO2 and nitrogen oxides (NOx) emissions and cap and invest programs for GHG emissions.  There are add-on control options for SO2 an NOx whereas there isn’t any cost-effective option for CO2.  In the ARP the affected sources could directly control their compliance.  In RGGI there were limited direct options for the affected sources and, going forward especially, they are going to have to rely on indirect reductions, i.e., someone will build a zero-emitting plant that displaces enough output from a fossil plant that enough allowances are available to cover the affected source requirements.  The ultimate control strategy for a emissions marketing CO2 control program is to run less and hope power is available from somebody else.

Conclusion

I believe that RGGI is not the success that its adherents believe. Based on the numbers there are some important caveats to the simplistic comparison of before and after emissions.  Fuel switching was the most effective driver of emissions reductions since the inception of RGGI.  Emission reductions from direct RGGI investments were only responsible for 5% of the observed reductions.  RGGI investments in emission reductions were not efficient at $897 per ton of CO2 removed.  In my opinion those are not the hallmarks of a successful program.

I want to highlight a related point.  In order to determine emission reduction efficiency from the RGGI investment reports, I had to sum the values in the previous reports because the most recent report only reported lifetime benefits.  The RGGI website only lists the lifetime benefits of RGGI investments in 2017 but those parameters are useless for the most obvious application.  In order to account for future emission reductions against historical levels the annual reduction parameter must be used.  It is hard to not believe that excluding the accumulated annual reductions was deliberate because the numbers are so poor.

As a model for future programs, RGGI successfully proved that a regional entity could implement a cap and auction program.  However, the actual cause of observed reductions and ability of affected sources to make the reductions proposed should be considered before other programs adopt the RGGI model.  I considered the use of the RGGI model in Transportation Climate Initiative Draft Framework Cap and Invest Caiazza Comments  that were submitted as part of their stakeholder process.  I concluded that there are so many differences between a program for mobile sources and electric generating units that simply implementing a tax and investing the proceeds as proposed would be less likely to have serious problems with unintended consequences and unanticipated issues.

As a result of the issues raised in this post, I believe that it is fair to ask whether any cap and trade program for CO2 can be successful if the ultimate goal is a significant reduction in emissions.  Because CO2 from fossil fuels is such an integral part of our lifestyles a large reduction in emissions is going to have to require changes in lifestyles.  Therefore, the question becomes will people accept lifestyle changes such as giving up the gas automobile with all its current advantages over any alternative as a result of indirect CO2 pricing?

Abuse of Air Quality Trends Data

When I first saw a graph from a New York Times article entitled “America’s air quality worsens, ending years of gains, study says” my first thought was that the reporter must have mis-read the analysis report. However, National Bureau of Economic Research working paper 26381 “Recent Increases in Air Pollution: Evidence and Implications for Mortality” by Karen Clay and Nicholas Z. Muller (hereinafter “Clay and Muller”) from Carnegie Mellon University apparently does claim that air quality is getting worse. I am spurred to check this claim out because the last time I checked all the air quality trends were down.

Although the emphasis of my work before retirement was environmental regulatory analysis coupled with emissions reporting I have always been primarily an air quality meteorologist. My experience includes managing an ambient air quality monitoring network, modeling air quality and interpreting the monitoring and modeling results for regulatory applications. Frankly, this claim struck a nerve with me and I felt I had to respond. The opinions expressed in this post do not reflect the position of any of my previous employers or any other company I have been associated with, these comments are mine alone.

Background
The abstract for the Clay and Muller paper states:

After declining by 24.2% from 2009 to 2016, annual average fine particulate matter (PM2.5) in the United States in counties with monitors increased by 5.5% between 2016 and 2018. Increases occurred in multiple census regions and in counties that were in and out of attainment with National Ambient Air Quality Standards (NAAQS). We explore channels through which the increase may have occurred including increases in economic activity, increases in wildfires, and decreases in Clean Air Act enforcement actions. The health implications of this increase in PM2.5 between 2016 and 2018 are significant. The increase was associated with 9,700 additional premature deaths in 2018. At conventional valuations, these deaths represent damages of $89 billion.

The National Trend of PM2.5 graph attributed to the paper in the New York Times article shows an “alarming” reversal of the air quality trend. I am only going to respond to this trend claim and the discussion of possible causes. The discussion of health implications deserves a response too but that will have to wait.

PM2.5

The EPA PM basics page describes this pollutant.  PM2.5 is particulate matter with a diameter 2.5 micrometers and smaller.  It is also called fine inhalable particles and the key point is that these particles are so small that they can be inhaled deeply into the lungs.  Although this can clearly cause health problems there are controversies about threshold effects.  The EPA reference describes the sources of PM:

These particles come in many sizes and shapes and can be made up of hundreds of different chemicals.  Some are emitted directly from a source, such as construction sites, unpaved roads, fields, smokestacks or fires.  Most particles form in the atmosphere as a result of complex reactions of chemicals such as sulfur dioxide and nitrogen oxides, which are pollutants emitted from power plants, industries and automobiles.

Measuring particles this small is difficult and a representative national network for monitoring PM2.5 has only been available since 2000.  However, because most of these fine particles are created from sulfur dioxide and nitrogen oxides, we can use trends from those pollutants as a surrogate for expected levels of PM2.5.

EPA has trend data readily available for all the national ambient air quality standard pollutants.  Also included at the website is an interactive trend report.  Importantly for this post, the EPA website provides links for easy data downloads.

Clay and Muller Analysis

Clay and Muller used daily data from the EPA Air Quality Data System for all observations in the contiguous United States from 2009 to 2018.  They considered not only the total PM2.5 concentration but also the three major species: ammonium nitrate, sulfate and elemental carbon.  The dataset of 1.8 million daily readings was statistically processed to calculate trends not only nation-wide but also in different regions of the country.

Once they found their worrisome trend they examined three possible channels through which the recent increase may have occurred: economic activity, wild fires, and enforcement.  Economic activity was studied by looking at the speciated PM2.5 data to attribute the source of pollution.  Wildfire effects were determined by looking at the West, Midwest, and California regions by omitting June through September data.  To estimate the effect of enforcement they used an EPA database of “actions resulting in a penalty for violations of section 113d of the Act”.

The New York Times article claims that this work shows a reversal of a decades-long trend toward cleaner air and quotes study co-author Nick Muller, a professor of economics, engineering and public policy at Carnegie Mellon as saying “After a decade or so of reductions this increase is a real about-face.”

My Analysis

In order to do this kind of analysis correctly is a big deal.  Ambient air quality refers to the make-up of the air we breathe.  It is affected by air pollution emissions and the meteorological conditions that affect the transport and diffusion of the material between the time it is emitted and the time we breathe it.  For regulatory assessments whether the ambient concentrations comply with the National Ambient Air Quality Standards you need to consider both of those components.  As you can imagine setting up an inventory of all the pollutants that affect PM2.5, developing a meteorological database to model transport and diffusion and finally running a model that not only incorporates those factors but also includes the chemistry that changes the emissions to the chemicals we breathe is a massive undertaking.  Nonetheless, I think we can do something simpler to test the conclusions of the Clay and Muller paper.

Contrary to popular opinion calculating environmental trends is not as simple as you might first imagine.  For example, if the number and location of monitoring stations changes over time then the trends may change because of those changes and not because of some underlying difference in emissions, economic activity or enforcement actions.  As noted previously EPA analyzes and reports on air quality trends.  Importantly their primary consideration is to make sure the data they report represents what is actually happening and does not include data artifacts.  Another point is that because meteorological conditions affect pollution concentrations, we should expect variations in monitored values solely due to weather.  In order to minimize that effect the longer the period of record for the data the better because it averages the weather impacts out.

EPA PM2.5 trend data from a representative network of stations is available from the EPA website starting in 2000 so the obvious first thing to do is to look at all the data available.  The EPA Air Quality Data Summary table lists the annual nation-wide average, the year-to-year differences and the difference over the entire period of record and the difference between 2016 and 2018.  These numbers corroborate the claim that PM2.5 air quality did get worse the last two years.  However, the period of record air quality data in my table show that there has been a marked improvement since 2000:  PM2.5 is down nearly 40%, SO2 is down 82% and NOx is down 33%.  Even though there was a concentration increase the last two years, note that there were three other years when the PM2.5 concentrations failed to go down and two of them had higher increases than the last two years. Similar results are shown in the SO2 and NOx data.

Remember that ambient concentrations are a function of weather and emissions.  Rather than trying to estimate the effect of emissions on concentrations by looking at the observed content it is simpler, and much more likely to be accurate, to simply look at the emissions.  EPA also provides emissions trend data.  The EPA Emissions Data Summary table lists annual PM2.5, SO2 and NOx emissions data in the same format as the air quality data summary table.  These data include emissions from electric utilities, industry, storage, transportation, and a miscellaneous category that includes wildfires.  Estimating emissions from the wide variety of sources means that there is a wide range of data quality but I assume that these values are appropriate for the purpose at hand.  Note that according to these data PM2.5, SO2 and NOx emissions all went down not only over the period of record but also between 2016 and 2018.

Clay and Muller examined three possible channels through which the recent increase may have occurred: economic activity, wild fires, and enforcement.  In their analysis of economic activity, they conclude that “The chemical composition of particulates point to increased use of natural gas and to vehicle miles traveled as likely contributors to the increase in PM2.5”.  Because their analysis did not consider the potential effect of weather on transport and diffusion and because the emissions trend was down even while the ambient concentrations went up, I disagree with that conclusion.  With regards to wildfires, Clay and Muller conclude that wild fires “may account for some of the observed increase in PM2.5 from 2016 to 2018, but not for the general pattern of decline and then reversal.  I think that their methodology is too coarse to pick up a wildfire signal.  Even though the paper doesn’t find a link between enforcement actions and the PM2.5 trend they conclude “The decline in enforcement actions, however, is concerning in light of the increases in air pollution in both attainment and nonattainment counties after 2016.”  In the first place in my experience the majority of enforcement actions have little to do with emissions levels and mostly to do with reporting inconsistencies but I believe it is much more likely that enforcement actions are going down because the regulatory agencies are doing a good job.  That is to be applauded not to be a matter of concern.

Conclusion

I am not impressed with the methodology used in this paper.  Number crunching over a million records to determine a trend has risks that professors of economics apparently did not recognize.  Ambient levels of pollution are affected not only be emissions and the factors that they examined but also by meteorology and monitoring system issues.  The inter-annual changes noted were more likely simply due to meteorology as any change in emissions and precursor emissions that the Clay and Muller paper claimed.

I am trying to give the authors the benefit of the doubt that they did not know any better but I am frustrated that they apparently did not bother to seek the advice of any air quality meteorologist or air pollution monitoring scientist.  I am confident that anyone of those experts would have said the longer the trend the better and don’t expect a perfectly decreasing ambient air quality trend even when the emissions are decreasing over time.  Trying to tease out a rationale for an air quality trend change likely less than the variability of the measurements due to weather is an abuse of air quality trends.  Now that these results have shown up in the New York Times many people have been mislead.

October 28 2019 Buffalo NYS Public Participation Workshop on Regional Approaches to Climate and Transportation

On October 28, 2019 I attended the Buffalo NYS Public Participation Workshop on Regional Approaches to Climate and Transportation.  As I promised previously this post describes the meeting.

My over-whelming impression of this meeting is that the NYS Department of Environmental Conservation (DEC) and Department of Transportation (DOT) staff supporting the effort to develop a low-carbon transportation future believe that their public stakeholder process represents the will of the people.  I disagree with this characterization because my definition of “public” refers to society as a whole.  This stakeholder process has been confined to a limited and biased subset of the people based on my attendance at three meetings.  Please consider submitting a comment asking for costs which I think is the primary concern of the “public”.

Background

According to the Transportation and Climate Initiative webpage:

“The Transportation and Climate Initiative (TCI) is a regional collaboration of 12 Northeast and Mid-Atlantic states and the District of Columbia that seeks to improve transportation, develop the clean energy economy and reduce carbon emissions from the transportation sector. The participating states are: Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Virginia.”

This meeting was part of New York’s response to the TCI and a component of the response to the state’s Climate Leadership and Community Protection Act (CLCPA).  In order to meet the “most aggressive” climate law transportation controls are needed on the sector because as shown in the New York State GHG Emissions 1990–2016 table it is has the most emissions of any sector.  Moreover, because the CLCPA is now the law DEC and DOT have to come up with a plan to make reductions from the sector.

The invitation to the meeting described the purpose and provided links to background information:

“The State Departments of Environmental Conservation (DEC) and Transportation (DOT) and the New York State Energy Research and Development Authority (NYSERDA) are conducting public outreach to inform New York’s participation in a multi-state initiative to reduce greenhouse gas emissions from the transportation sector with the Transportation and Climate Initiative (TCI). DEC, DOT, and NYSERDA are seeking input from the public regarding New York’s potential participation in a regional program designed to reduce emissions, boost the economy, improve public health, and achieve fair and equitable outcomes for underserved communities and transportation-related businesses.”

“The states participating in the Transportation and Climate Initiative have released a framework for a draft regional policy proposal to reduce greenhouse gas emissions from transportation and are seeking public feedback. The framework can be reviewed at https://www.transportationandclimate.org/sites/default/files/TCI-Framework_10-01-2019.pdf. We invite the public to submit input to the TCI portal at https://www.transportationandclimate.org/main-menu/tci-regional-policy-design-stakeholder-input-form. Background materials are available at https://www.transportationandclimate.org/main-menu/tcis-regional-policy-design-process-2019.”

“In addition, DEC, DOT and NYSERDA are conducting public meetings to better understand various perspectives on New York’s potential participation in a regional policy. The agencies will also seek input on alternative or complementary strategies to reduce emissions from transportation.”

“Additional information is available on the DEC website https://www.dec.ny.gov/energy/99223.html.  Questions can be directed to climateandtransportation@dec.ny.gov.”

Meeting

The agenda for the workshop that I attended had two main components.  After opening remarks that introduced speakers and introduced the topics, the first main component was “Key Elements of a Potential Regional Approach to Transportation and Climate”.  After a break the second component was a “Discussion on Investment Opportunities”.  The meeting ended with “suggestions, reflection and next steps”.

The description of the cap-and-invest program described their current thinking.  At this time, they plan to regulate state fuel suppliers of gasoline and on-road diesel.  That means the tank farms where distributors provide gasoline and diesel fuel that is sent to retail outlets will have to participate in the trading program.  They are doing analyses to determine the cap level and, as I understand it, the costs necessary to fund control programs to determine the rate of reductions that will be proposed.  Frankly, the lack of specificity for this aspect of the proposed framework is troubling and this meeting provided no details.

My primary interest in the meeting was the discussion of the multi-state process to develop a potential cap-and-invest program.  I have been involved with emissions marketing pollution control programs since 1990 and the Regional Greenhouse Gas Initiative (RGGI) since its inception over ten years ago so I wanted to see what they are thinking in the first half of the meeting.  In my opinion the proponents of a transportation cap-and-invest program overlook many of the lessons of RGGI.  Because they have to do something I took the opportunity to make the following suggestion for doing what I think will be least destructive and costly:

I think you should just go with a carbon tax rather than trying a cap and dividend program for the following reasons:

      • In the TCI framework the affected sources are state fuel suppliers.  They have no real stake in compliance with the cap and minor options to directly meet the cap. All they will do is sell fuel up to the cap limit and tack the price they paid for allowances onto the price they sell to fuel retailers.
      • RGGI was a cap and dividend program and it did not work out as well as many believe. Per the 2017 proceeds investment report that came out earlier this month, of the observed RGGI emission reductions less than 5% were directly attributed to dividend investments
      • The observed cost per ton of CO2 reduced was $897 – far higher than the social cost of carbon.
      • Logistically there is a cost issue. As reductions are made the amount of fuel sold will go down so the dividend proceeds will also go down.  How can you maintain the funding to keep up the rate of reductions needed?
      • I also worry that there will be cost increases related to the cap and dividend program that will increase cost to customers that will not be passed on as dividends to the public.

The second half of the meeting focused on the question “How could the proceeds from a cap-and-invest program promote cleaner transportation, improve public health, create economic opportunities, and enhance mobility?  While it is nice to come up with a list of possible investment projects such a list does not consider practicality and cost so I see little value in the exercise.  Faced with a two and a half hour ride home I left the meeting at the break.

Impression

As noted in the introduction my overall impression with this process is that the organizers and administrators truly believe that their public stakeholder process is representative of the “public”.  I disagree with this characterization because my definition of “public” refers to society as a whole and I have seen no indication that this topic has not been confined to a limited and biased subset of the public who have vested interests in transportation planning.  I base this impression on the three meetings I attended.

I went to the Georgetown Climate Center listening session in Albany, NY on April 9, 2018.  I don’t believe that there was public notice of the meeting because I got a call from NYS Department of Environmental Conservation Deputy Commissioner Jared Snyder asking why I wanted to attend.  He was clearly surprised that I knew about the meeting.  After assuring him that I would behave, I was allowed to attend.  When I showed up at the meeting, where I expected to be the only member of the public, I was surprised how many members of environmental organizations were present in addition to the regulatory agency people.   Whatever the motivation to check my rationale to participate, this was not an event that the general public knew about.

New York had its own listening sessions  to help advance a cleaner, safer, and more reliable low-carbon transportation future in the summer of 2018.  I attended the Central New York session on August 21, 2018.  The meeting was “designed to engage stakeholders with diverse interests and concerns in discussion of the economic and social considerations for deploying clean transportation options, opportunities to enhance environmental and public health benefits through a modernized transportation system, how innovative, low-carbon transportation can enhance quality of life and boost economic competitiveness, and what policies and programs may help advance a clean transportation future”.  Notice for this meeting was provided in the NYS DEC e-mail distribution system and there was a press release, so the general public as a whole might have had the opportunity to hear about the meeting.  However, attendance at the meeting was limited to members of environmental organizations, staff from transit agencies in the region, other people with a vested interest in a clean transportation future, and me.

Because the Buffalo meeting did not include an opportunity to formally meet people and the attendance list was not published, I don’t know the background of the attendees.  However, the people I did know were mostly agency staff so at least a third were there as part of their job.  The meeting was hosted by PUSH Buffalo whose mission is “to mobilize residents to create strong neighborhoods with quality, affordable housing; to expand local hiring opportunities; and to advance economic and environmental justice in Buffalo”.  As a result, I think that the majority of the rest of the audience were in that demographic or environmental organizations.  I do believe that there were some industry people in attendance but did not hear from any of them while I was at the meeting.

Therefore, I think it is presumptuous to say that these meetings provide engagement from the public, which I define as including anyone outside the wonky world of future transportation policy especially as it pertains to environmental justice.  Moreover, the format of these meetings was more about “what are the things we can do for clean transportation options” than “how can we implement these options and at what cost?”.  None of the meetings I attended addressed implementation issues, feasibility concerns, or potential costs.

Public Involvement

Roger Pielke Jr.’s Iron Law of Climate Policy states that “while people are often willing to pay some price for achieving environmental objectives, that willingness has its limits”.  I find it difficult to believe that the modeling mentioned at this meeting and described on the TCI webpage has not generated an estimated cost per gallon of fuel.  I believe that is an over-riding concern of the public so I suggest that asking for that information is entirely appropriate.

I think it is very important that residents of Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Virginia submit input to the TCI portal at https://www.transportationandclimate.org/main-menu/tci-regional-policy-design-stakeholder-input-form.   All you have to do is go to that link, fill out a few questions and then you can share your input with the Transportation and Climate Initiative.  I think a comment as simple as “I am concerned about the cost of this initiative and would like to know the expected cost increase to a gallon of gasoline.” from members of the public and not just the folks who go to these meetings would be effective.  By all means please consider making more extensive comments but the more people who ask for the costs the better.  New Yorkers could also send an email to climateandtransportation@dec.ny.gov asking for the expected cost.  I am not saying that they won’t ignore the request but at least they will be on notice that the public worries about the cost.

Final Note

By the way I did wear my yellow vest so I may go down as the first such protester at a NY meeting.  I did not go out of my way to get a reaction from the meeting attendees but I did make my point.  Over the years I have made the acquaintance of many people at DEC including Deputy Director Jared Snyder and now retired DEC climate advocate Lois New.  I got to the meeting early and had a chance to make sure they understood I was wearing the vest because I think yellow vest protests are inevitable.  Their reaction was a mixture of amusement (curmudgeon Roger is joking around again) and amazement (I don’t think that either Jared or Lois have contact with very many people who don’t agree with their views on climate change so this kind of confrontation surprised them.)

NYS Public Participation Workshop on Regional Approaches to Climate and Transportation

On October 28, 2019 I attended the Buffalo NYS Public Participation Workshop on Regional Approaches to Climate and Transportation.  I wore a yellow vest to the meeting because I believe that the policy suggested at the workshop will inevitably lead to prices that will be unacceptably high.  I also made up a handout if anyone asked about the yellow vest and that included a link to my posts on the Climate Leadership and Community Protection Act (CLCPA) page where I have posted this expanded version of the Handout DEC Workshop on Regional Approaches to Climate and Transportation.  I will post on the meeting itself later.

There have been multiple instances where expensive climate policies were the initial spark to protests that expanded in scope to cover more issues.  The French “Yellow Vest” movement was triggered in November 2018 when fuel prices were raised.  In October 2019 protests started in Chile when subway fares were increased.  The evidence in this post and my handout suggests that a similar protest could occur in New York as the 2030 requirement to reduce greenhouse gas (GHG) emissions to 60 percent of 1990 emissions levels in 2030 included in the CLCPA legislation is implemented.

The New York State GHG Emissions 1990–2016 table lists historical GHG emissions in New York.  The State has yet to provide a plan to meet the requirements of the CLCPA.  One way to meet the 2030 emission target in ten years would be to require all these sectors to reduce their 2016 emissions 30%.  While the ultimate plan probably will require different amounts from each sector the final strategy’s reduction requirements probably will not vary too much from 30% each.

I only considered the transportation sector in my handout.  The ultimate strategy to meet the CLCPA goals will have to specify options for each component of the transportation sector.   In order to meet a 30% reduction goal from this sector the plan could call for 30% electric vehicle conversions of each of these registration categories in the New York State Dept of Motor Vehicles Registrations in 2016 table.  For the standard registration category that means that we would need 2,844,099 electric vehicles on the road by 2030.  According to the NYS Energy Research & Development Authority (NYSERDA) there are 58,278 electric vehicle registrations in the state as of June 2019 and 35,296 were registered since January 2017.  As a result, we need to have 2,808,803 more electric vehicles to meet the 30% reduction goal and sales would have to average 244,244 electric vehicles per year.  That is over four times per year the total number of electric vehicles in the state in June 2019.

The transportation cap-and-invest program proposed would “cap emissions of carbon dioxide from the combustion of the fossil component of finished motor gasoline and on-road diesel fuel in the region”.  Owners of fuel at terminals would buy permits to sell the equivalent amount of fuel corresponding to the emissions cap and then New York will invest the money received in programs to reduce fuel use.  One investment could be to fund the current $2,000 NYSERDA incentive for the purchase of electric vehicles.  In the previous example that is $488 million per year and would roughly add 9 cents per gallon.  However, the $2,000 per car incentive is not working well enough to get many people to purchase them.  If the incentive is kicked up to $10,000 per vehicle then the cap cost would go up to 43 cents per gallon.  The cost per electric vehicle is just the start of the costs necessary to implement over two million electric vehicles.  What is the plan for charging infrastructure particularly in cities where residents have to park in lots or on the street and how much will that cost?

A recent poll asked the public how much they were willing to pay to combat climate change.  The poll found that “To combat climate change, 57 percent of Americans are willing to pay a $1 monthly fee and 23 percent are willing to pay a monthly fee of $40.”  Dividing the NYS annual gasoline sales of 5.73 million gallons in 2016 by the 9,480,329 standard registrations averages 50 gallons per month so the nine cents per gallon equates to $4.29 per month but would rise to $21 a month for 43 cents per gallon to fund a $10,000 per vehicle incentive.

Advocates for the cap-and-invest program point to the Regional Greenhouse Gas Initiative (RGGI) as model of a program that works.  I believe that RGGI has significant differences that make the approach unlikely to work well if at all.  In RGGI, affected sources did not have viable options to install control equipment but could switch to a lower emitting fuel.  I have calculated that fuel switching was the cause of most of the reductions and that reductions linked directly to investments from the auction dividends provided only 5% of the total reductions.  Another big difference is that affected sources have different stakes.  The TCI proposed cap and dividend approach proposes to regulate state fuel suppliers.  In RGGI affected sources were penalized if they did not comply but the TCI affected sources have no stake in compliance with the cap.  They will only sell whatever amount of fuel is specified by the cap and will not worry about how society meets the cap.  As a result, the TCI price signal has to be high enough to force the public to reduce fuel use and TCI dividend investments have to give citizens viable options that use less fuel.

There is another problem.  The RGGI dividend investment results did not reduce emissions enough to meet the cap.  If the TCI investments don’t reduce emissions sufficiently to meet the cap necessary to meet New York’s CLCPA targets, then the inevitable outcome is that there will be more demand for fuel than the cap allows and the amount of fuel available will be limited.  It is inconceivable to me that government-caused fuel outages would be acceptable to the citizens of New York.

Ultimately a cap-and-dividend program equates to a tax.  Just as taxes are invested by government for services this approach takes in money that supposedly will be invested to promote cleaner transportation, improve public health, create economic opportunities, and enhance mobility.  Before anyone can reasonably be expected to decide to support this program the State needs to provide their plan for specific programs and resulting costs.  What is the expected increase to fuel prices for this new tax and how will it be structured so that the those least able to afford a price increase not be adversely affected in general and particularly the rural poor located beyond the availability of public transit?

Most importantly, this analysis looks only at one sector.  The electric generation, residential, commercial, industrial and other sectors all have to make similar reductions.  Given that the costs of just this sector fall between the amount 57% and 23% of the public are willing to pay I believe it is clear that there will be pushback similar to the French “yellow vest” movement in New York when the costs of the CLCPA become apparent.  Roger Pielke Jr.’s Iron Law of Climate Policy states that “while people are often willing to pay some price for achieving environmental objectives, that willingness has its limits”.  New York will test that law.

Let Experience be your Guide to Climate Science

In this post I explain why I think that your direct experience should guide your opinion on global warming climate science.  You may not be a climate scientist but your personal experiences enable you to judge the certainty of the climate claims popularly heard.

Update November 1, 2019: Added a link at the end to a post about the reliability of extended forecasts

Greenhouse Effect

The reason that we hear that there is an inevitable, imminent climate emergency is because of the greenhouse effect.  But how do we observe it in the atmosphere?  All things being equal, if you know whether it is warmer or colder in the morning after a clear night then you understand the impact of the greenhouse effect.  Of course, the answer is it is colder after a clear night.  Simply put, when something, in this case clouds, reduces the amount of heat loss (long wave radiation) from the surface and atmosphere, then the temperature does not cool as much, so it is colder after a clear night than a cloudy night.

There are a couple of ramifications of what you already know about this greenhouse effect fact.  On clear nights cooling can occur at about 3.4 deg F an hour while on an overcast night cooling is only about 0.5 deg F per hour.  Global average temperature was on the order of 2.5 deg F warmer in 2017 than in 1850.  If all the warming since 1850 was due to greenhouse gases, then that warming is less than one hour of a cloudy night as opposed to a clear night.  Therefore, clouds have a much stronger effect on temperature than greenhouse gases.   The other point is that the greenhouse gas effect is stronger at night than during the day so nights are warming faster than days.  Keep this in mind when you hear that climate change is going to cause much hotter day time temperatures.  The reality is that the average is going up more because the minimum temperature is going up rather than because the maximum temperature is going up.

Forecast Skill

Predictions of a climate emergency are based on climate prediction models.  Remember weather is what we feel over short periods and climate is how the atmosphere acts over longer periods of time, i.e., decades.  Observant weather-wise people understand the uncertainty of forecasts for different time periods.  Obviously, a 24-hour forecast is more reliable than a seven-day forecast.  You know that longer term weather forecasts are not as reliable because you have observed that.  The fact is that the physical relationships for forecasting weather and climate are the same.  There are differences but the inescapable conclusion is that climate forecasts for one hundred years from now are much less reliable than weather forecasts.

Although people like to say that the weather forecasting profession is the only one that lets you be wrong much of the time and still have a job, the reality is that weather forecasts have improved markedly over time.  When I graduated in 1976 with a master of science degree in meteorology, three to five-day forecasts were much less accurate than they are today.  In no small part that is because weather forecasters are constantly verifying their predictions against observations.  If the forecast is radically wrong then the data are re-evaluated and the modeling parameters are reviewed.  Testing a new modeling variation with the data from the period when the old model forecast failed to test improvements and then implementing the revised modeled is a constant process.  Obviously, a 100-year climate forecast cannot be tested the same way.  It is just not possible to improve climate models much because they cannot be tested frequently enough to make a lot of improvements.

Clouds

Another aspect of forecasting that observant folks understand is the effect of clouds on forecast reliability and usefulness.  Consider the uncertainty when the forecast is for scattered showers.  You know that you may get rain or just as likely may not and if your outdoor activity depends on dry weather that means a lot.  For numerous reasons it is not possible under many conditions to predict exactly when and where a shower may pop up.  The primary reason is that cloud formation is a process that takes place over a small spatial-scale – yards instead of miles.  Weather forecast models can incorporate the factors that cause clouds and precipitation into the predictions but not the small-scale factors that cause them at a specific location and time.  Residents of Upstate New York are very familiar with the forecast that lake-effect snow is going to occur “north of the Thruway”.  Even though forecasters run finer-scale models that are limited to areas immediately adjacent to the Great Lakes, they still can only predict that somewhere in that area there will be a snow band but not exactly where.

There are very serious implications of clouds on the climate forecasting models.  Because climate models have to predict over the entire globe, none of the physical processes that create clouds are incorporated into the models.  Instead the models simulate clouds by parameters which, to be kind, is simply the expert opinion of the model developer.  Don’t believe me?  Here is what Nakamura Mototaka says in Confessions of a climate scientist:

“Clouds are represented with parametric methods in climate models. Are those methods reasonably accurate? No. If one seriously studies properties of clouds and processes involved in cloud formation and dissipation, and compare them with the cloud treatment in climate models, one would most likely be flabbergasted by the perfunctory treatment of clouds in the models. The parametric representations of clouds are ad hoc and are tuned to produce the average cloud cover that somewhat resembles that seen in the current climate. Can we, or should we, expect them to simulate the cloud coverage and properties in the “doubled atmospheric carbon dioxide” scenario with reasonable accuracy? No.”

Implications

I have described three aspects of global warming climate science that observant folks basically understand based on their personal experience.  We know that clouds cause great differences in temperatures.  Clearly weather forecast models that can be tested are more reliable than climate prediction models that cannot be tested for the relevant forecast period.  Even though weather forecast models have improved we know that they still don’t do as well as we would like for clouds and precipitation.

This all leads to the implication of the fact that the climate models do not do a credible job with clouds.  We all know that clouds have a big effect on the temperatures we observe.  If the climate models that cannot be tested do not simulate clouds correctly, why should we have much faith in the projections of inevitable, imminent climate emergency from those climate models?

I believe we should consider the results of climate models the same way we treat a forecast for a slight chance of scattered showers.  Based on our experiences we know that there are a range of potential outcomes for that forecast.  Clearly, those who claim that there is an inevitable, imminent climate catastrophe are stretching credibility.  While nothing here can lead to the conclusion that a catastrophic outcome is impossible, the uncertainty surely dictates that our response be carefully crafted. While it might seem prudent to act we must not forget  Ridley’s ParadoxEconomic damage from man-made ‘climate change’ is illusory whereas damage from man-made ‘policies’ to fight the said change is real.  Moreover, there is the potential that the current focus on a climate emergency is diverting attention that might be better spent on higher probability issues such as: global pandemics, antibiotic resistance, Carrington events, or, if you worried about truly existential threats with low probabilities, asteroid impacts.

November 1, 2019 Update  This post by Dr. Cliff Mass provides good background to our experience that extended forecasts are not reliable.

Status of Climate Change Science October 2019

Several recent blog posts have come to my attention that I want to pass on to readers of this blog because all three make good points and, ultimately justify a pragmatic approach in my opinion.  I have summarized them below but recommend that you read them all in their entirety.

Judith Curry argues that the science does not support the claims that climate change in an existential threat.  I believe it is safe to say that Cliff Mass is more worried about the threats of climate change but makes the point that there is an active group in the climate debate, “mainly on the political left, that is highly partisan, anxious and often despairing, self-righteous, big on blame and social justice, and willing to attack those that disagree with them” that he believes may in the end do more harm than good.  Finally, Larry Kummer offers suggestions that could be implemented today with widespread support from most of society.

Judith Curry writing on her Climate Etc blog posted her response to a reporter’s questions about the current state of climate limits and timelines.  The reporter asked about the deadlines (e.g., the 12 years to act) currently in the news. She concluded:

Bottom line is that these timelines are meaningless.  While we have confidence in the sign of the temperature change, we have no idea what its magnitude will turn out to be.  Apart from uncertainties in emissions and the Earth’s carbon cycle, we are still facing a factor of 3 or more uncertainty in the sensitivity of the Earth’s climate to CO2, and we have no idea how natural climate variability (solar, volcanoes, ocean oscillations) will play out in the 21st century.  And even if we did have significant confidence in the amount of global warming, we still don’t have much of a handle on how this will change extreme weather events.  With regards to species and ecosystems, land use and exploitation is a far bigger issue.

Cleaner sources of energy have several different threads of justification, but thinking that sending CO2 emissions to zero by 2050 or whenever is going to improve the weather and the environment by 2100 is a pipe dream.  If such reductions come at the expense of economic development, then vulnerability to extreme weather events will increase.

There is a reason that the so-called climate change problem has been referred to as a ‘wicked mess.’

Cliff Mass has his own blog on weather and climate.  He recently posted on the Real Climate Debate.  The point of his post was that there are two groups of people active in the climate change debate covered by media and politicians.  He defines the two groups as the ACT group (Apolitical/Confident/Technical) and the the ASP group (Anxious, Social-Justice, Partisan).  The ACT group thinks that global warming is a technical problem with technical solutions while the ASP group see that social change is necessary to deal with global warming and that will require re-organizing society.  His bottom line:

Progress on climate change is being undermined by the efforts of the highly vocal, partisan, and ineffective ASP group.  They are standing in the way of bipartisan action on climate change, efforts to fix our forests, and the use of essential technologies.   They are a big part of the problem, not the solution.

In contrast to the ASP folks, the ACT group generally tries to stay out of the public eye, quietly completing the work  needed to develop the technologies and infrastructure that will allow us to mitigate and adapt to climate change.  In the end, they will save us.  That is, if the ASP folks don’t get in their way.

Larry Kummer writing at the Fabius Maximus blog recommended issues that he hopes a presidential candidate can adopt that will address serious threats. One of the issues he included was Climate Change.  The only disagreement I have with his recommendations concerns conversion to non-carbon-based energy. I think this needs to be included but would prefer that the emphasis be on R&D to find alternatives that are cheaper than fossil fuels.  Until that happens I believe that Roger Pielke Jr.’s Iron Law of Climate Policy will make implementation impossible.  His “iron law” simply states that “while people are often willing to pay some price for achieving environmental objectives, that willingness has its limits”.  Larry’s recommendations are:

   “We don’t even plan for the past.”
— Steven Mosher (member of Berkeley Earthbio here), a comment posted at Climate Etc.

We are locked into two camps, with a large confused mass between the climate extremists and those who deny that global warming is a threat. The resulting gridlock leaves us vulnerable to the inevitable repeat of past extreme weather and the effects of the continuation of the two centuries of warming (from a combination of natural and anthropogenic factors). We can continue to do almost nothing, waiting for one side to stampede the American public into acquiescence – or for the weather to decide for us. Or we can immediately take smaller but still effectual steps. I gave these recommendations six years, and they remain sound today. They could command popular support.

        1. Increased government funding for climate sciences. Many key aspects (e.g., global temperature data collection and analysis) are grossly underfunded. But this research should be run with tighter standards (e.g., posting of data and methods, review by unaffiliated experts), just as we do for biomedical research – and for the same reason, to increase its reliability.
        2. Fund a review of the climate forecasting models by a multidisciplinary team of relevant experts who have not been central players in this debate. Include a broader pool than those who have dominated the field, such as geologists, chemists, statisticians and software engineers. This should include a back-test of the climate models used in the first four Assessment Reports of the IPCC (i.e., run them with forcing data through now, and compare their predictions with actual weather). This will tell us much (details here).
        3. We should begin a well-funded conversion in fifty years to mostly non-carbon-based energy sources. We need not wreck the economy or defund defenses against the many other threats we face. This is justified by both environmental and economic reasons (see these posts for details). As we learn more about climate change, this program can be accelerated if necessary.
        4. Begin more aggressive efforts to prepare for extreme climate. We’re not prepared for repeat of past extreme weather(e.g., a major hurricane hitting NYC), let alone predictable climate change (e.g., sea levels climbing, as they have for thousands of years).

Conclusion

My pragmatic take based on these posts.  Climate change is an extraordinarily difficult problem to understand but the extremely bad projections are very unlikely.  Unfortunately those worst-case projections have the attention of a segment of society that is convinced otherwise and their passion may make reasonable and no regrets responses impossible.  Because we don’t understand natural variability well enough to pick out the small signal of human-caused global warming and, more importantly because the current alternatives to will be extremely expensive we need to monitor the climate better, focus our climate research on results and natural variability, develop a research program to develop alternative to fossil fuels that are cheaper than they are, and finally develop resiliency to observed extreme weather.

RGGI Investment Report for 2017

UPDATE: November 15, 2019  – The lifetime totals listed in the originally posted text were wrong due to a copy and paste error.

In October 2019 the Regional Greenhouse Gas Initiative (RGGI) released their annual Investments of Proceeds update.  This post compares the claims about the success of the investments against reality.

I have been involved in the RGGI program process since its inception.  I blog about the details of the RGGI program because very few seem to want to provide any criticisms of the program. The opinions expressed in this post do not reflect the position of any of my previous employers or any other company I have been associated with, these comments are mine alone.

Background

RGGI is a market-based program to reduce greenhouse gas emissions. It is a cooperative effort among the states of Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode Island, and Vermont to cap and reduce CO2 emissions from the power sector.  According to a RGGI website: “The RGGI states issue CO2 allowances which are distributed almost entirely through regional auctions, resulting in proceeds for reinvestment in strategic energy and consumer programs. Programs funded with RGGI investments have spanned a wide range of consumers, providing benefits and improvements to private homes, local businesses, multi-family housing, industrial facilities, community buildings, retail customers, and more.”

Released in October 2019, The Investment of RGGI Proceeds in 2017 report tracks the investment of the RGGI proceeds and the benefits of these investments throughout the region. According to the report, the lifetime benefits of RGGI investments made in 2017 include:

      • 9 million MWh of electricity use avoided
      • 6 million MMBtu of fossil fuel use avoided
      • 3 million short tons of CO2 emissions avoided
      • 13.9 million MWh of electricity use avoided
      • 22.6 million MMBtu of fossil fuel use avoided
      • 8.3 million short tons of CO2 emissions avoided

The report’s press release quotes Ben Grumbles, Secretary of the Maryland Department of the Environment and Chair of the RGGI, Inc. Board of Directors: “The 2017 report shows why RGGI is a climate leader globally and nationally, not only cutting emissions in half but generating revenues to strengthen local economies and communities.” Katie Dykes, Commissioner of the Connecticut Department of Energy and Environmental Protection and Vice Chair of the RGGI, Inc. Board of Directors said “RGGI states’ investments accelerate clean energy, reduce climate risk, and improve lives”.  Bruce Ho at the National Resources Defense Council blogged that the report “confirms that RGGI is a tremendous success story whose benefits continue to grow, and it shows how, in the absence of national leadership, states are forging ahead to protect our health, environment, and economy from the worst impacts of climate change.”

As I will show below, I disagree with these assertions of success.  I believe that the report mis-characterizes some of the numbers relative to the value of the program as an emission reduction approach.  This is because they present “lifetime” benefits of the investments.  Everyone is talking about emissions reductions from some annual value, usually 1990.  In order to determine effectiveness to meet those goals the only benefits that count are annual reductions due to RGGI.  While it may be appropriate to document the lifetime dollar savings for energy efficiency, I am convinced that using lifetime values for any other parameter is bogus.

Emissions Reductions

In the first year of the RGGI program, 2009, the states of Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode Island, and Vermont emitted 123,880,601 tons of CO2.  This report was for 2017 and those states emitted 66,349,058 tons of CO2 so emissions the emission reduction was 46% which is close enough to half to accept the claim.  However, the real question is why did the emissions go down.  I believe that the real measure of RGGI emissions reductions success is the reduction due to the investments made with the auction proceeds.

The report does not provide the annual RGGI investment savings values accumulated since the beginning of the program.  In order to make a comparison to the CO2 reduction goals we have to sum the values in the previous reports to provide that information.  The table Accumulated Annual Regional Greenhouse Gas Initiative Benefits lists the annual avoided CO2 emissions generated by the RGGI investments from three previous reports as well as the lifetime values.  The total of the annual reductions is 2,818,775 tons while the difference between total annual 2009 and 2017 emissions is 57,531,543 tons.  The RGGI investments are only directly responsible for 5% of the total observed reductions!

Cost Efficiency

In order to argue that RGGI emission reduction programs are a good investment relative to the expected societal cost of CO2 emissions the Obama Administration developed a value for the social cost of carbon.  This parameter was developed to estimate the cost of the long-term (that is to say hundreds of years) damage done by a ton of carbon dioxide (CO2) emitted today. This dollar figure also represents the benefit of a CO2 reduction. I have posted on some of the issues with this parameter but for the purposes of this post you need to know that the values range widely depending on assumptions.  For example, if you use a discount rate of 3% and consider global benefits like the Obama-era Environmental Protection Agency (EPA) did then the 2020 SCC value is $50.  On the other hand, the current Administration EPA SCC value for SCC is $7 for a 3% discount rate and $2 for a 5% discount rate that represents only benefits to the United States.  The Institute for Policy Integrity report “Expert Consensus on the Economics of Climate Change” projected a higher 2020 SCC value of ~$140 based on a survey of experts.  A 2015 paper in Nature Climate Change “Temperature impacts on economic growth warrant stringent mitigation policy” suggest that the SCC value should be $220.

The Accumulated Annual Regional Greenhouse Gas Initiative Benefits table lists the data needed to calculate the RGGI CO2 reduction cost per ton.  From the start of the program in 2009 through 2017 RGGI has invested $2,527,635,414 and reduced CO2 2,818775 tons annually.  The result, $897 per ton reduced, is four times greater than the highest SCC value and two orders of magnitude greater than the current EPA SCC value for United States benefits.

Conclusion

The fact is that for policy purposes the annual reductions from RGGI have to be considered because that is the “apples to apples” comparison.  I have to believe the reason why the RGGI investment reports no longer report the accumulated annual benefits and only report the lifetime benefits is because the values appropriate for determining the effectiveness of this program as a control program reflect so poorly on the program.  Reductions of CO2 directly attributable to investments made from the auction proceeds only total %5 of the observed CO2 reductions from 2009 to 2017.  Those poor results combined with $2.5 billion investments costs result in a nearly $900 cost per ton of CO2 reduced.  That value far exceeds the social cost of carbon value contrived to prove the value of CO2 reductions.