RGGI as the Electric Sector Compliance Tool to Achieve 2030 State Climate Targets

This is another in a series of posts on the Regional Greenhouse Gas Initiative (RGGI). The program includes periodic reviews to consider program successes, impacts, and design elements. In the current program review process one of the big issues is whether the cap on CO2 emissions should continue to decrease after 2020 when the current program ends. Not surprisingly many environmental organization advocate continued reductions based on reductions made to date and cite a report prepared by Synapse Energy Economics entitled “The RGGI Opportunity 2.0, RGGI as the Electric Sector Compliance Tool to Achieve 2030 State Climate Targets” (hereinafter the “Synapse Study”).  In previous posts I have looked at emission reductions and this post looks at the claims made in the Synapse Study.

I have been involved in the RGGI program process since its inception. In the final years before my retirement I analyzed air quality regulations that could affect electric generating company operations. 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. I am motivated to write these posts on RGGI because the majority of the stakeholder opinions expressed at meetings and in submitted comments are, in my opinion, very naïve relative to the actual burden implanting their preferred alternatives, overly optimistic about the potential value of continued RGGI reductions, and ignore the potential for serious consequences if things don’t work out as planned.

The Synapse Study was commissioned by the Sierra Club, Pace Energy and Climate Center and Chesapeake Climate Action Network. The introduction to the Synapse report states that it “…builds upon Synapse’s prior analysis of emission reductions in the electric and transportation sectors by additionally analyzing emission reductions in the building sector to create a robust least-cost buildout of compliance with RGGI states’ 2030 climate goals.” During the stakeholder process associated with the current RGGI program review a number of organizations have endorsed the implementation of a steeply declining RGGI emissions cap between 2020 and 2030, primarily based on the assertions found in the Synapse Study. Specifically, two comments posted to the Program Review record on June 29, 2016 from a total of 23 environmental and health organizations contained the following statement:

“Throughout the program review, numerous groups have requested that the RGGI states model a scenario with capped emissions declining by 5% of the 2020 baseline each year through the modeling horizon, resulting in a 2030 cap level of 39 million tons. This request is based on the dual justification that A) such a trajectory is consistent with RGGI emissions reductions to date, and B) multisector analysis has demonstrated that this is the most cost-effective pathway to achieving the RGGI states’ 2030 economy-wide GHG commitments”.

In my previous posts I have pointed out that the emissions trajectory to date is not reflective of further reductions because emissions from the primary source of past reductions (coal and residual oil generation) are already close to de minimus levels. This post addresses the “multi-sector analysis” prepared by Synapse for future reductions. I focus on the viability of the measures proposed to reduce CO2 emissions and whether all the necessary costs for implementation have been included for the ultimate cost-effectiveness evaluation.

Based on the following analysis of various statements this study does not make a strong case. I did not try to cover every proposed aspect of the multi-sector analysis. Instead I evaluated four components. The Synapse study text is shown in italics; my comments in regular text.

 Half of Emission Reductions Come from the Electric Sector (p. 7, Synapse Study)

Electric-sector efficiency and renewables are responsible for nearly half of the additional required reductions in 2030. Figure 5 presents emission reductions in the electric sector for the baseline and 40 percent emission reduction policy scenarios. In the 40 percent emission reduction scenario, Northeast states’ electric sector emissions are capped at 39 million short tons in 2030 compared to the currently mandated RGGI cap of 78 million short tons in 2020.

The latest EIA data indicates that 2014 electric sector emissions (Table 1) were 86.1 million tons compared to the 78 million ton current cap. Note that coal and residual oil made up 34.6 million tons of the total sector emissions and that natural gas emissions were 51.5 million tons. Since 1990 most of the electric sector emission reductions have been as the result of coal and residual oil reductions primarily due to retirements and changes in operations driven by economics and not necessarily RGGI. Natural gas use went up as it displaced the other two fuels.

These data suggest that future reductions necessary to meet the current 2020 cap of 78 million tons is close enough to be achievable. However, an additional 39 million ton reduction is necessary to meet the proposed 2030 cap. In a previous post I showed the bounds for CO2 reductions that could be attributed to RGGI investments to date. The upper bound is an econometric model that estimates that emissions would have been 24 percent higher (31.9 million tons) without the program. RGGI estimates that emissions would have been 17% higher (22.6 million tons) than without a program. If you assume that all the savings in fossil fuel use earned by RGGI investments only displaced natural gas rather than historical use as the RGGI estimate did, then emissions would have been only 5% higher (4.2 million tons). My point is that future reductions will have to come as the result of RGGI and state programs not fuel economics and depending on how you calculate the impact of RGGI programs to date this could be relatively easy or not. Given that future reductions will be from displacing natural gas I believe it is more difficult that presumed by this study.

Efficiency, Wind, and Solar Drive Down Electric-Sector Emissions (p. 8, Synapse Study)

Under the 40 percent emission reduction scenario new, lower RGGI caps drive deeper, more wide-spread changes in the RGGI states’ electric system. Figure 6 reports the impact of these measures in terms of generation by resource. Coal, oil, and natural gas-fired generation are replaced by efficiency and renewables. Note that electric sector generation is lower in the 40 percent emission reduction scenario than in the RGGI baseline even though substantial generation is needed to power electric vehicles and heat pumps: savings from energy efficiency outweigh additional electricity sold to owners of electric vehicles and heat pumps.

 Renewables supply one-half of the RGGI region’s electric generation in 2030 (p. iv, Synapse Study). Adding 50,000 gigawatt-hours of new wind and solar in the 40 percent emission reduction scenario results in a future where half of all electricity generation comes from renewable resources in 2030, compared to just 30 percent in the baseline RGGI scenario.

The Synapse study neglects a major aspect of the electric system in their assumptions that renewables can replace coal, oil, and natural gas to the extent proposed. The electric power system is very complex and must operate within narrow parameters while balancing loads and resources and supporting synchronism. In countries like Germany, it has only been possible to develop an aggressive level of renewable generation in their power system because Germany is able to rely on neighboring country’s conventional facilities in the grid for load support. Synapse has presumed that renewables in the RGGI system can provide the necessary ancillary support but has not shown that it can provide all the important parameters provided by central power stations. For example:

Conventional rotating machinery such as coal, nuclear, and gas plants as well as hydro generation provide a lot of support to the system. This includes reactive power (vars), inertia, regulation of the system frequency and the capability to ramping up and down as the load varies. Most renewable resources lack these important capabilities and are only intermittently available (e.g., not dispatchable). Unlike conventional generators that rotate at constant speed, wind turbines must rotate at variable speeds so that their rotational energy offers no support to the system.

Some, but not all of the disadvantages of solar and wind energy can be mitigated at extra costs through electronic and mechanical means. When these resources make up only a small percentage of the generation on the system, overall system stability is not adversely impacted in a significant way. Stated another way, when the overall system is robust enough, utilities can allow a small percentage of solar “lean” on the system and still provide a stable source of electricity. As the penetration of solar and wind energy increases the system robustness will degrade and reliability will be compromised without costly improvements. Such additional costs are not generally applied to the evaluation of renewable resources at this time, and it certainly appears that the Synapse study has failed to take any of these types of costs and issues into account.

As noted above, the German grid relies on its neighbors to provide a wide range of support services. It may not be possible for the RGGI electrical systems to support the Synapse study’s presumed high penetration of renewable power and the provision of those services are not incorporated in their costs projections. In order for the Synapse projections to work in a real-world scenario the RGGI grid operators will also end up relying on neighboring power systems to provide this support, thus promoting  “emissions leakage”.

Energy Efficiency Savings Are One-Third of Total Emission Reductions (p. 9, Synapse Study)

 Efficiency measures will continue to lower consumers’ bills. Applying Massachusetts’ expected electric energy efficiency savings in terms of percent of sales—based on their current three-year plan—to all RGGI states lowers electric sales by 11 percent by 2030. These efficiency savings have been determined to be cost effective in Massachusetts.

This presumption does not account for the current state of energy efficiency in other RGGI states. If a state is presently more efficient than Massachusetts then it is inappropriate to assume that the same rate of efficiency savings is possible simply because easier energy efficiency targets have already been implemented.

Wallet Hub analyzed Energy Efficiency RGGI State Rankings using data from the U.S. Census Bureau, the National Climatic Data Center, the U.S. Energy Information Administration and the Federal Highway Administration. Their conclusions are highlighted below:

“To identify the most energy-efficient states, WalletHub analyzed data for 48 states based on two key dimensions, including “home-energy efficiency” and “car-energy efficiency.” We obtained the former by calculating the ratio between the total residential energy consumption and annual degree days. For the latter, we divided the annual vehicle miles driven by gallons of gasoline consumed. Each dimension was weighted proportionally to reflect national consumption patterns.

In order to obtain the final ranking, we attributed a score between 0 and 100 to correspond with the value of each dimension. We then calculated the weighted sum of the scores and used the overall score to rank the states. Together, the points attributed to the two major categories add up to 100 points.

Home-Energy Efficiency – Total Points: 55

Home-Energy Efficiency = Total Residential Energy Consumption per Capita / Degree-Days

Car-Energy Efficiency – Total Points: 45

Car-Energy Efficiency = Annual Vehicle Miles Driven / Gallons of Gasoline Consumed

The Wallet Hub 2015 Energy Efficiency RGGI State Rankings are listed in Table 2. Four states are more efficient than Massachusetts and New York and Vermont are markedly more efficient than Massachusetts. Therefore, the presumption that New York and Vermont will be able to reduce emissions by 11% or the same as the Massachusetts expected electrical energy efficiency savings level is difficult to justify and appears to be unfounded.

1.3 Million Electric Heat Pumps Replace Oil Heaters (p. 11, Synapse Study)

In 2015, over 4 million families in the RGGI region were still heating their homes with oil. By 2030, this number is expected to shrink to 3 million households in the RGGI baseline scenario as households move to more efficient forms of heating. These oil furnaces and boilers would release 20.4 million short tons of CO2 into the atmosphere in 2030.

The 40 percent emission reduction scenario shifts 1.3 million of the remaining 3 million households from oil to air-source heat pumps by 2030 (see Figure 9). Heat pumps are appliances that use electricity to absorb heat energy in cold areas (i.e., outside) and transfer it to indoor areas. Heat pumps have the advantage of being able to work in reverse—not only can they provide heating in winter months, but they take the place of a central air conditioning systems in the summer months. Heat pump technology has existed for decades, and these units are commonplace in Europe and Asia, but high-performing systems that function well in cold-weather climates as in many of the Northeast states have just recently begun to make inroads in the United States. By shifting heating consumption from inefficient, high-emitting oil boilers and furnaces to highly efficient heat pumps, 9 million short tons of CO2 are avoided.

 Despite the Synapse disclaimer heat pumps are at a disadvantage in cold climates like New York and other RGGI states there are physical issues: “An air-source heat pump works well as long as temperatures are above freezing. Below that temperature, less heat is available, and the pump may have to rely on its supplemental heating coil to warm your home. This coil uses electricity to heat and will increase heating costs.”

Traditionally, heat pumps have not enjoyed a wide level of penetration in housing markets because consumers are primarily interested in cost of ongoing operation. Furthermore, there does not appear to be any in-place incentives that would lead to a wide-scale shift from conventional oil- and gas-fired boilers to heat pumps. Absent some regulatory requirement or financial incentive program, the Synapse study assumption that one million conventional furnaces will be replaced with heat pumps over a fifteen year period has no basis in fact and appears to be a highly unlikely scenario.

Ten Million Electric Vehicles Offset 28 Million Short Tons of CO2 (p. 12, Synapse Study)

The 40 percent emission reduction scenario adds 10 million battery electric vehicles in the nine RGGI states by 2030, above what is currently in place and expected in the baseline forecast (see Figure 10).9 The stock of electric vehicles in the RGGI baseline is based on the Energy Information Administration’s 2015 projections and reaches 46,000 vehicles in the RGGI region in 2030. In contrast, Synapse’s 40 percent emission reduction scenario assumes that one-third of the RGGI region’s light-duty vehicles run on electricity by 2030 based on the Federal Highway Administration’s projection of the potential for electric vehicle adoption. These new electric vehicles reduce total RGGI state emissions by 28 million short tons of CO2 in 2030.

The Energy Information Administration’s Annual Energy Outlook 2016 includes tables with projections of future vehicle stocks. The vehicular data are categorized by region not state so it was not possible to reproduce the Synapse Study numbers. Table 40. Light-Duty Vehicle Stock by Technology Type notes that, nationwide, in the reference case there are 340,481 conventional light duty cars in the 100 mile electric vehicle and 200 mile electric vehicle classes in 2016 and in 2030 predicts there will be 3,534,097 vehicles in the reference case and 3,542,276 vehicles in the reference case without the Clean Power plan.

In New York there are about nine million light duty vehicles registered. The Synapse study claims that it is possible to replace one third of the 8.7 million gas powered vehicles with electric vehicles, which equates to 2.9 million electric vehicles in New York by 2030. That would be 82% of the EIA projected total for 2030.  In order to reach the projected total in the Synapse study presumption, over 190,000 per year would have to be sold. At the current time, there are no regulatory structures and only insufficient financial incentives in place to support this massive level of electric vehicle penetration.

Presuming for a moment that it would be possible to effect such a significant change in the driving habits of New Yorkers, the Synapse study has not taken into consideration that there are significant infrastructure requirements for the 2.9 million electric vehicles projected. One of the greatest impediments to the further development of electric vehicle market is that charging stations in public places have not yet been implemented on a widespread basis nor has a satisfactory cost model been developed on how to finance such a massive infrastructure build-out. Clearly, if one in every third car parked on a New York City street is to be an electric vehicle, significant costly changes to the existing electrical systems must come about. The Synapse study has not taken those costs into account in its presumption that an unprecedented change in the vehicle market will lead to the emission reductions proposed.

Summary

I looked at four components of the Synapse study: electric sector, energy efficiency, home heating and electric vehicles. Synapse claims 103 million ton CO2 emission reductions when these recommendations are implemented. In the following I offer alternative estimates of the tons saved based on the aforementioned evaluation.

In the Synapse electric sector analysis (section 2.4, p. 7) half of the emission reductions or 39 million tons come from the electric sector. The big unknown is how much renewable will displace the natural gas usage and it was argued above that as little as 4.3 million tons of reductions occurred because of RGGI itself. Synapse assumes that the state renewable portfolio standards will be implemented but does not explain how. For example, they note that:

For New York, in addition to modeling the existing RPS (approximately 24 percent of retail electric sales by 2015), we modeled an additional 3,000 MW of utility-scale photovoltaic (PV) solar added by 2023 and an additional 1,600 MW of wind added by 2029, in line with the New York State Energy Research and Development Authority’s (NYSERDA) projections for capacity that will come online as a result of the NY-Sun and Large-Scale Renewables programs

The missing piece is how much generation will that presumed additional capacity generate and how much will it displace natural gas generation. It is not enough to assume that it is a straight ratio because the ancillary services provided by traditional power plants would not be included. Synapse did not account for electric system reliability issues in its projected penetration of renewables into the RGGI states power system. For an upper bound estimate of potential reductions I used the 2014 EIA data and assume that petroleum products are already at their de minimus level, coal goes to zero, and that natural gas stays the same assuming that the replacement of coal by natural gas equals the reduction by renewables. Using those assumptions there are only 22.6 million tons of savings.

The energy efficiency Synapse projection (section 2.6, p. 9) accounts for one third of total emission reductions or 27 million tons. I think that Synapse overestimated the amount of emissions savings that are available from energy efficiency programs absent additional policy and/or regulatory structures.  Their analysis presumes that the Massachusetts rate of energy efficiency improvement can be applied to four states that have better efficiency but that is inappropriate. I assumed that the expected energy improvement of 11% in those four states would only be half of that, scaled the reductions as a function of residential and commercial end use and determined that instead of 17 million tons of electric energy efficiency there would only by 12.1 million tons. The remaining 10 million tons of Synapse energy efficiency comes from gas energy. They simply assumed without much justification that it could be improved by 1% per year but I accept their guess.

For home heating (section 2.7, p. 11) Synapse projects that 1.3 million heat pumps will replace of the 3 million home heating furnaces still on oil saving 9 million tons of CO2. Their analysis does not address the physical constraints of heat pumps in freezing weather. Synapse has not provided a plausible structure that will bring about its projected transition to electrically-powered heat pumps. Rather than their high bound assumption that 43% of the furnaces will be converted to heat pumps I think a realistic lower bound for conversion is 10% so the CO2 savings would be 2.1 million tons.

The Synapse electric vehicle scenario (section 2.8, p. 12) projects that there will be 10 million electric cars in RGGI by 2030 and also notes that EIA projects only 46,000 more electric vehicles by 2030. That equates to some kind of incentive program to get RGGI drivers to buy 9,954,000 electric vehicles and even if the incentive is only $1,000 that is over $9 billion dollars. Synapse failed to appreciate the complexities and costs associated with a massive conversion of driving preferences to electric vehicles. In the real world a more realistic estimate would be RGGI incentivizes an order of magnitude more electric vehicles (460,000) than EIA and the CO2 savings would be 1.3 million tons.

Synapse claims 103 million ton CO2 emission reductions when their recommendations for these four components are implemented. However, based on my evaluation I expect only 51.6 million tons of reductions from these four components.

RGGI Containment Reserves

This is another in a series of posts on the Regional Greenhouse Gas Initiative. Previous posts have looked at how the program has been working from the viewpoint of an outsider. This post is a technical discussion of two components of the system currently being discussed in the 2016 Program Design process: the Cost Containment Reserve (CCR) and the proposed Emissions Containment Reserve (ECR).

I have been involved in the RGGI program process since its inception. Before retirement from a Non-Regulated Generating company, I was actively analyzing air quality regulations that could affect company operations and was responsible for the emissions data used for compliance. 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. I am motivated to write these posts on RGGI because the majority of the stakeholder opinions expressed at meetings and in submitted comments are, in my opinion, overly optimistic about the potential value of continued RGGI reductions and ignore the potential for serious consequences if things don’t work out as planned.

Overview of Containment Reserves

The RGGI website has an overview of the cap and auction system that includes a description of the CCR. One of the original stakeholder concerns was cost. In order to put a limit on the cost of allowances the CCR was established to add allowances to the program when the cost exceeds a threshold. The theory is that adding allowances will reduce the allowance cost. The trigger price for adding 5,000,000 million allowances in 2014 or 10,000,000 allowances thereafter was $4 in 2014, $6 in 2015, $8 in 2016, and $10 in 2017, rising by 2.5 percent each year thereafter. The CCR has been triggered twice, in the first quarter of 2014 and the third quarter of 2015, adding 15,000,000 allowances to the system.

One of the primary stakeholder topics of the RGGI 2016 program review is future reductions in the cap. As it stands now the cap declines by 2.5% per year until 2020 and remains at the level. Proponents of future reductions claim that past performance suggests the cap can continue to decline. The ECR was proposed as a possible solution to the cap adjustments. In particular, the ECR decreases the number of allowances auctioned if the price gets too low. The theory is that if the costs are too low that means there is a surplus of allowances and the cap can be lowered accordingly. It seems to me that it could be used as the mechanism to adjust the cap in the future in addition to its price control aspect.

RGGI Allowance Status

The status of the cap and implications on compliance and cost need to be addressed in the context of these containment reserves. Another stakeholder topic in the 2016 Program Design Review is the appropriate size of the allowance bank. The allowance bank is the surplus allowances over and above the compliance requirements. In the first two compliance periods of RGGI the number of authorized allowances far exceeded actual emissions. As a result the bank of allowances was so large that the RGGI states made interim adjustments to subsequent auctions to lower the number of allowances available.

The appropriate size of the bank is controversial. Advocates for more reductions want a smaller bank so that reductions occur sooner. Proponents of higher allowance prices want to reduce the size of the bank because fewer available allowances should drive the price up. However, there are reasons that the bank should not get too small. Emissions are directly proportional to operating times which are strongly related to weather-related demand. Affected sources want to have sufficient banked allowances in their accounts to be able to supply power in periods of increased demand. In addition, companies prefer to have a margin in order to address monitoring problems. Ultimately, if insufficient allowances are available then affected sources will not be able to operate.

In that context consider the RGGI allowance status today. In the first compliance period (2009-2011), 429,381,635 allowances were auctioned, sold or awarded, the CO2 emissions were 382,075,544 tons so the margin between the available allowances and emissions (the allowance bank) at the end of the compliance period was 47,306,091 allowances. The allowance bank at the end of the second compliance period was 120,175,954 allowances. As it stood at the end of 2016 the allowance bank as defined as the difference between the allowances auctioned, sold, or awarded and the RGGI allowances retired was 173,105,751. Note, however, that there is a difference between the 2015-2016 allowances retired and emissions. RGGI retires 50% of the compliance obligation at the end of the year instead of waiting until the end of the compliance period to retire all the emissions. If all the emissions are withdrawn the allowance bank at the end of 2016 is 90,446,582 allowances. For comparison purposes the 2016 total emissions were 80,624,392 tons.

There is an affected source or compliance entity concern with the allowance bank trends. The RGGI allowance database is not as open and transparent as the EPA allowances databases for their programs. EPA provides ownership information on all allowances but RGGI does not. The RGGI market monitoring reports provide the only breakdown between the allowances held by compliance entities and that is only the percentage of the total bank held by compliance entities. At the end of the first compliance period 97% or 45,886,908 of the allowances were owned by entities that needed the allowances to comply with the requirements of the program. At the end of the second compliance period the compliance entity share was down to 81% or 97,342,522 allowances. At the end of 2016 the compliance entity share was only 54% or 93,477,106 allowances. However, remember that RGGI only considers the retired allowances so the compliance entities have to cover 82,659,170 tons of emissions with their share at the end of 2016. Consequently the true compliance entity share of the allowance bank is only 12% or 10,817,936 allowances and that concerns the compliance entities.

In particular, the trend shows that compliance entities will have to go to the non-compliance entities to obtain enough allowances to operate. This problem will be exacerbated if RGGI cuts the cap and/or makes adjustments to the allowance bank. In my former life I was responsible for trading program compliance tracking and had input into corporate compliance strategy. Environmental staff and all corporations I have dealt with consider compliance the highest priority and the only way to insure that is to only generate emissions less than allowances in hand. Theoretically, you could generate and then go out to the market to cover what you emitted but, especially in the case of a constrained market, there is a compliance risk. RGGI is evolving towards the ultimate constrained market and there are two serious potential consequences. Firstly, affected sources could be forced to purchase allowances from an entity that knows they have a compliance obligation and could require them to pay an exorbitant amount for the allowances. This has two downsides: the windfall of money is not anything that will be invested like the RGGI auction proceeds (i.e., there is no societal benefit to those higher priced allowances) and eventually the price will show up on ratepayer bills[1].

Secondly, a company could choose not to run because they don’t have the allowances and that will affect the power system badly, in the worst case it could even affect reliability. Were it up to me because environmental compliance is number one I would advise option 2.

Emission Containment Reserve

I think the ECR is an elegant solution to the issue of whether or not the cap should continue to decline. Ideally, the RGGI cap should create an allowance market where the price is within the acceptable range determined by the RGGI states. The CCR prevents the cost from getting too high. The ECR works on the lower end of the range to keep the price from getting too low. As an alternative to a declining cap the ECR determines the appropriate cap level by withdrawing allowances from the market to the point that the price rises above the low threshold of the target range. As proposed the withdrawn allowances are put into a reserve but it could be set up so that the allowances displace the allowances in the CCR and when there are more than 10,000,000 allowances displaced then allowances from the cap would be withdrawn. I want to emphasize however, that my support of this approach is in lieu of a specified declining cap.

In my opinion future reductions will not be as easy as the past. The majority of the reductions in the RGGI region to date have occurred because of coal unit retirements and cutbacks in the use of residual oil which were driven by the economics of low natural gas fuel prices. However, most of the coal facilities have retired and residual oil emissions are about as low as they can go so future reductions will have to displace more economic natural gas. Therefore, the ECR approach addresses this uncertainty. If further reductions are easily obtained then the ECR will lower the cap. If not then the RGGI program is not in danger of non-compliance meeting an artificial cap.

Unfortunately RGGI seems to be headed towards a mandated declining cap. The last round of proposed policy cases did not even consider the possibility that further reductions may not be available or even slower than expected primarily because all scenarios assume compliance with proposed state programs. While it is appropriate to include the scenario in which it is assumed that the state programs that propose to increase renewable power come to fruition, the fact is that they will necessarily have to increase costs. In my opinion a scenario which only considers economics of conversion also should be included to address the possibility that the political winds could change. In addition, the timing component should be included. Industry has had to deal with licensing delays for years and there is no reason to expect that the infrastructure necessary for the renewable deployments required will not also be affected.

Finally, the issue of the compliance entity share of allowances relative to a declining cap should be addressed. The unintended consequence of further reductions is to exacerbate the cost implications and increased reliability risks. Ultimately, society will pay those costs and I predict that the blame will fall back on the generating companies and not those who recklessly advocate more and more reductions. The existing program has worked as well. The CCR has limited allowance costs from increasing too much and the ECR seems to be a viable alternative to not only limit costs that go too low but also to be the mechanism that reduces the cap based on what is happening to the generating mix.

[1] There are those folks who would applaud increasing costs to the generating companies. To them I say that electricity is an essential driver to the health and welfare of our society. As with all essentials, electricity should be as reliable, secure and cost-effective as possible. It is no less important than food and water. Somehow, someway those increased costs will impact society, most likely impacting those who can least afford it the most.

Murphy Editorial “EPA Chief is wrong on the greenhouse gas effect”

On April 18, 2017 the Syracuse Post Standard published a featured editorial by Dr. Cornelius Murphy, Jr. “EPA Chief is wrong on the greenhouse gas effect”. I was given the opportunity to submit a rebuttal but was asked to make it the same length. This presents a problem because of the Baloney Asymmetry Principle, the third of my pragmatic environmentalist principles. In particular, the amount of information necessary to refute BS is an order of magnitude bigger than to produce it. This post rebuts his arguments.

Dr. Murphy’s editorial is an example of the straw man fallacy prominent amongst the critics of the current EPA. He describes the science behind the greenhouse effect and claims that Administrator Pruitt disagrees with those facts to support his claim that Pruitt must not be allowed to provide direction and policy for CO2 mitigation. The Catastrophic Anthropogenic Global Warming (CAGW) hypothesis espoused by Dr. Murphy claims that mankind’s emissions of greenhouse gases are responsible for the recent observed warming of the globe and, unless stopped soon, will have catastrophic impacts on the planet. This post addresses the catastrophic component of global warming which, I believe, are not obvious by simply “looking around” as Murphy suggests.

Robust scientific theories and hypotheses rely on a combination of both empirical and correlative evidence. In the case of a theory that cannot be directly tested through a controlled experiment, we have to rely on long term observations and comparison of projections based on the theory against the observations. Empirical observations and correlative evidence for the CAGW hypothesis are not as obvious as Murphy implies.

I have no issues with Dr. Murphy’s description of the greenhouse effect. The basic greenhouse gas theory is not controversial. Carbon dioxide is a greenhouse gas.  It retards radiative cooling.  All other factors held equal, increasing the atmospheric concentration of CO2 will lead to a somewhat higher atmospheric temperature.  It is not controversial that CO2 has risen in the last century or that at least half of the increase was due to mankind. It is also obvious that average temperatures are increasing over that same period. Dr. Murphy said that Administrator Pruitt “doesn’t think that CO2 is responsible for heating our planet”, but I don’t think Mr. Pruitt would dispute any of the aforementioned facts.

However, those facts do not necessarily lead to catastrophe and there is a healthy debate on most policy-relevant aspects of global warming. In the first place, there is a predicted warming due to greenhouse gases when all factors are held equal but all other things are never held equal in meteorology. In that case, doubling the concentration of atmospheric CO2 from its pre-industrial level would reduce outgoing infrared radiation by about 4 watts per meter squared and the temperature of the atmosphere would increase about 1.2 deg. C. Note that about half of this warming has already occurred. So clearly some of the observed warming is caused by this effect.

The most recent warming period started before the recent rise in CO2. There have been other warm periods of the same magnitude of the current period in the last two thousand years when anthropogenic CO2 was not the driver. At a minimum the CAGW theory has to explain why the causes of the warming between 1900 and 1940 which is of the same order of magnitude as the current warming are not playing a role now.

Dr. Murphy says that Administrator Pruitt should look at what is happening around him and cites several examples: “We have wild extremes in temperatures but annual average global temperatures continuing to rise. The temperatures of our Great Lakes are 6 degrees above average, extreme weather events challenge us all too frequently, and we experience mega droughts globally on a regular basis.” I address those points below.

I do not dispute that annual average global temperatures continue to rise. However, to me, if there is a valid concern about rising temperatures, then we should be able to find evidence that heat waves are increasing. The EPA climate change indicators high and low temperatures web page lists several parameters associated with temperature. The heat wave index shows an overwhelming spike in the 1930’s but there is no suggestion of a recent trend. There is a trend in the area of unusually hot temperatures graph but I wonder how they addressed the development of heat islands in that data so I am skeptical. I see nothing happening to warrant alarm.

His only quantitative claim is that “the temperatures of our Great Lakes are six degrees above average” but his claim does not withstand scrutiny.  According to EPA’s Climate Change Indicators web page on Great Lake temperatures: “Since 1995, average surface water temperatures have increased slightly for each of the Great Lakes”, but that is nowhere near six degrees.  The web site Great Lakes Statistics lists the current temperatures relative to their period of record starting in 1992 and all five lakes are currently less than two degrees above the mid-April average.

Dr. Murphy says extreme weather events challenge us all too frequently insinuating that they are getting worse but, again, looking at data indicates no cause for alarm. In recent testimony before the House of Representatives, Dr. Roger A. Pielke, Jr. addressed trends of extreme events in the United States. He noted that global weather-related disaster losses as a percentage of Global GDP are trending down since 1990; that there is no trend in hurricane landfall frequency or intensity; that the IPCC noted no evidence of a trend for floods; that US flood impacts are going down; and that there low confidence in observed trends for hail or tornadoes.

Dr. Murphy says that we experience mega droughts globally on a regular basis but Dr. Pielke quotes the IPCC: “there is low confidence in detection and attribution of changes in drought over global land areas since the mid-20th century”. If the Intergovernmental Panel on Climate Change concludes no trends in droughts then the only way we can interpret the regular basis comment is that this has been the case in the past and it continues today. His statement is not wrong but it also is not cause for alarm upon inspection either.

Because it is impossible to run a controlled experiment on Earth’s climate (there is no control planet), the only way to “test” the CAGW hypothesis is through models.  If the CAGW hypothesis is valid, then the models should demonstrate predictive skill. However the models are not predicting temperatures well enough to meet that standard because they predict a sensitivity to CO2 two to three times greater than that supported by observations. Dr. Curry’s summary of the global climate models makes five points about the use of these models for this purpose:

  1. GCMs have not been subject to the rigorous verification and validation that is the norm for engineering and regulatory science.
  2. There are valid concerns about a fundamental lack of predictability in the complex nonlinear climate system.
  3. There are numerous arguments supporting the conclusion that climate models are not fit for the purpose of identifying with high confidence the proportion of the 20th century warming that was human-caused as opposed to natural.
  4. There is growing evidence that climate models predict too much warming from increased atmospheric carbon dioxide.
  5. The climate model simulation results for the 21st century reported by the Intergovernmental Panel on Climate Change (IPCC) do not include key elements of climate variability, and hence are not useful as projections for how the 21st century climate will actually evolve.

Finally, Dr. Murphy notes that Pruitt is not a scientist but is an attorney. Although Dr. Murphy is a chemist and not a meteorologist like me I don’t believe that a person’s background necessarily means much. Look at the evidence yourself. When you check the numbers and claims like I did then you can determine whether or not to believe whoever is making the claims. In this case I find little support for Dr. Murphy’s claims but readers should decide themselves.

I have not found sufficient evidence to convince me that CO2 mitigation efforts are appropriate at this time. While it is very likely that human activities are the cause of at least some of the warming over the past 150 years the question is how much.  There is no robust statistical correlation to indicate that CO2 is the primary driver.  The failure of the climate models outline above clearly demonstrates the CAGW hypothesis is flawed.

I conclude that our children and grandchildren are not in imminent danger from CAGW and would be better served by investments to make society more resilient to observed extreme weather rather than trying to mitigate CO2 emissions to try to prevent the speculative weather projected by the flawed models. I believe Administrator Pruitt’s agenda to reign in the ill-conceived CO2 mitigation programs of the Obama Administration is appropriate. On the other hand, I do not agree with any plans to cut the climate monitoring and observing programs at EPA and elsewhere. I support research into all the causes of climate change not just anthropogenic causes. Ultimately, until such time that a cheaper alternative to fossil fuels is available society will continue to use them because of their tremendous benefits. If you believe that we society should stop using fossil fuels then research and development for alternatives is appropriate.

Pragmatic Environmentalist of New York Principle 5: Observation on Environmental Issue Stakeholders

This one of a series of background posts for my perception of pragmatic environmentalists.

Pragmatic Environmentalist of New York Principle 5: The more vociferous/louder the claims made by a stakeholder the more likely that the stakeholder is guilty of the same thing. This observation was also described by Gary: “My experience is that the things people complain about loudly are so very frequently the same things of which they also are guilty. The inability to see oneself realistically is a fascinating human trait.”

The poster child for this particular behavior is Dr. Michael Mann, Distinguished Professor of Atmospheric Science, Penn State University and Director, Penn State Earth System Science Center. On March 29, 2017 he gave testimony before the Committee on Science, Space and Technology that illustrates this phenomenon in three ways.

I prepared a table summarizing Michael Mann testimony with general categories for the contents. There were 26 paragraphs. Dr. Mann used 4 paragraphs to describe his background. Thirteen paragraphs described either “anti-science” attacks on him or Dr. Thomas Karl and his rebuttals to those attacks, two paragraphs attacked other scientists and seven of the 26 paragraphs addressed the science of climate change.

The first example of Principle 5 is the matter of personal attacks which are bad if they directed to him but OK if he is doing the attacking. The majority of his testimony addresses what he characterizes as “anti-science” attacks on him. He notes that “Science critics will therefore often select a single scientist to ridicule, hector, and intimidate.” However, his testimony then ridicules three out of the four individuals at the hearing because they “represent that tiny minority that reject this consensus or downplay its significance”. I think it is reprehensible and clear intimidation to label Dr. Judith Curry as a “climate science denier” equating her views of the consensus on climate change as equivalent to those who deny the Holocaust. He notes “I use the term carefully—reserving it for those who deny the most basic findings of the scientific community, which includes the fact that human activity is substantially or entirely responsible for the large-scale warming we have seen over the past century”.

The second example is the scientific debate on climate change. Dr. Mann invokes the 97% consensus argument that “of scientists publishing in the field have all concluded, based on the evidence, that climate change is real, is human-caused, and is already having adverse impacts on us, our economy, and our planet”.  But then goes on to say “there is indeed a robust, healthy, and respectful debate among scientists when it comes to interpreting data and testing hypotheses”. Obviously no debate is possible interpreting any data or hypotheses that climate change is human-caused. I am also troubled by his lack of qualifiers for what the referenced 97% consensus actually referred to.

The third example is the proper channel for scientific debate. Dr. Mann states “True scientists are skeptics—real skeptics, contesting prevailing paradigms and challenging each other, in the peer-reviewed literature, at scientific meetings, and in seminars—the proper channels for good faith scientific debate.” However, he “proves” that James Hansen famous predictions from the 1980’s and 1990’s were successful by referencing the Real Climate blog. In Congressional testimony he mentions “the huge potential costs if the impacts turn out to be even greater than predicted, something that appears to be the case now with the potential rapid collapse of the West Antarctic Ice Sheet and the increased sea level rise that will come with it.” His citation is a newspaper article “Climate Model Predicts West Antarctic Ice Sheet Could Melt Rapidly” by Justin Gillis, New York Times, March 30, 2016. Two examples of precisely the improper channel he was alluding to in his description of good faith scientific debate.

One final point regarding this testimony. Dr. Mann notes that he coined the term “Serengeti strategy” to characterize his attackers. He describes this as when special interests “single out individual scientists to attack in much the same way lions of the Serengeti single out an individual zebra from the herd”. He is blissfully unaware that his moral of the story “In numbers there is strength, but individuals are far more vulnerable” may not be the whole story. My impression is that the lions single out the weakest link in the herd: the old, the sick, the young and, dare I say it, the one with the weakest arguments.

Replacement Power for Indian Point – Renewables and Energy Efficiency

In an earlier post I addressed the potential availability of power to replace Indian Point’s capacity. This is an update to that analysis with a discussion of a new report. In January 2017 New York’s Governor Andrew Cuomo announced the closure of the Indian Point Energy Center located 25 miles north of New York City. Cuomo claims that Indian Point produces 2,000 megawatts of electrical power and that “more than enough replacement power to replace this capacity will be available by 2021”. Since then environmental advocates have claimed that the replacement power “can and must be replaced with a portfolio of energy efficiency and clean energy resources: renewable resources such as wind, hydroelectric and solar.”

The basis of this claim is the Synapse Energy Economics report prepared for the Riverkeeper and Natural Resources Defense Council entitled “Replacement Energy and Capacity Resources for the Indian Point Energy Center Under New York Clean Energy Standard (CES)” that claims that replacing Indian Point can be done with a combination of renewables and energy efficiency. This post addresses that report.

I am generally skeptical of the Synapse report for two fundamental reasons. The report is sponsored by organizations that don’t want Indian Point or central power stations in general and also support development of renewable energy. It would not be presented to the public if it did not support their goals and objectives. Secondly, the analysis uses the National Renewable Energy Laboratory (NREL) ReEDS (Regional Energy Deployment System) modeling system. Clearly this organization has specific goals in mind and I doubt that they would have developed a model that did not support their renewable energy goals. These reasons do not necessarily say that the results should be dismissed out of hand but it does suggest that the results have to show no signs of bias towards a pre-determined result to be valid.

In order to determine whether there is bias it is necessary to dig into the approach. ReEDS is a” long‐term capacity expansion and dispatch model of the electric power system in the lower 48 states”.   The report notes that it has a “high level of renewable energy resource detail with many wind and solar resource regions, each with availability by resource class and unique grid connection costs”. Capacity, dispatch and load planning models are complicated and the characterization of the grid is a particular problem for New York. EPA and RGGI have relied on a similar model called the Integrated Planning Model that is notorious for its mis-characterization of the New York grid with the particular problem being transmission constraints to New York City and Long Island. EPA uses a version that has yet to get it right but New York’s influence in RGGI has led to a version that is acceptable in this regard. In the absence of a thorough review of the model I doubt that ReEDShas been tuned to correctly characterize this problem. If not, the fact that there are transmission constraints can lead to poor estimates of future load and capacity development making it easier to claim that renewables can be integrated easily.

The bigger problem is that the modeling approach assumes too much. In particular, they assumed that the levels of energy efficiency necessary to meet the CES will be met. The report itself describes the weakness of that assumption: “The CES order assumes annual incremental savings through energy efficiency of roughly 1.5 percent of overall electric energy demand, resulting in a reduction from ~160k GWh in 2016 to ~146k GWh in 2030. However, the CES order does not include any mechanism to ensure that these levels of energy efficiency are achieved, in contrast to the binding and enforceable 50 percent by 2030 renewable energy target enacted by the CES order. Nor has the Public Service Commission enacted any other policies outside the scope of the CES order to ensure that the state achieves these levels of energy efficiency. Rather, existing policies (which consist primarily of Energy Efficiency Transition Implementation Plan (ETIP) targets and budgets for each of the state’s investor‐owned utilities) guarantee only a small fraction of this 1.5 percent annual incremental savings.”

In other words, the modeling assumes that energy efficiency gains will occur despite the lack of a mechanism for it to occur. Furthermore, the insinuation that the renewable goal will be met because there is a binding order misses the point that the goal may not be achievable.

I am a fan of energy efficiency because it has no regrets. In other words because there is no completely benign way to make electricity reducing the amount you need is a very good thing. Moreover, you can target the energy efficiency and conservation funding so that those least able to pay for their energy get direct benefits. As a result even if it turns out that we don’t need to reduce CO2 emissions because of its impact on climate we still get benefits from this approach. Unfortunately I have qualms about the capability of energy efficiency to provide a significant amount of replacement power for Indian Point.

First and foremost is simply accounting for energy efficiency. The Clean Energy Ministerial discusses the obstacles to assessing energy efficiency gains and notes “Because savings represent the absence of energy use, it is impossible to directly measure energy efficiency impacts”. In the absence of direct measurements it is therefore necessary to estimate energy use in the absence of the energy efficiency savings project. I would hope that the CES order clearly defines the metrics for these estimates so that they are credible, certain and consistent. Frankly, the lack of documentation thus far in the CES does not give me hope in this regard.

One aspect to the continuing aggressive efficiency goals that I have not seen addressed is market saturation. A significant fraction of New York’s RGGI investments have been allocated to energy efficiency and those investments were preceded by years of subsidies for energy efficiency in other programs. An anecdote is just to consider household conservation. Once all the windows and doors have been replaced by more efficient versions, investing in even better ones will not be as cost effective. After you have spent money to do the obvious things any future investments cost more but yield less relative improvement. My point is that the Synapse projections of further efficiency goals do not include assessments of what is available. Instead they simply assume that the CES goals will be met and that even more reductions are possible if we throw even more money into the programs.

Finally there are concerns about the “rebound effect” that suggest that maintaining the proposed level of annual incremental savings is ambitious. The “rebound effect” is when an improvement in energy efficiency triggers an increase in demand for energy. The impact of this effect is controversial and there is much uncertainty regarding the magnitude of rebound effects associated with energy efficiency improvements.

The renewable goals are similarly based on assuming that the CES requirements will be met. The Synapse report states: “We incorporated New York State CES parameters into our projection of load and resource requirements. These parameters include CES‐assumed increased levels of energy efficiency and meeting the 50 by ’30 renewable energy requirement. We reflect New York’s target of obtaining 2,400 MW of offshore wind energy by 2030 in all scenarios, staged to reflect 600/1200/1800/2400 MW attained by, respectively, 2024/2026/2028/2030.” In 2015 3,398 MW of new offshore capacity was added worldwide, bringing the total to over 12,107 MW according to the Global Wind Energy Council. In theory that should mean that New York can install 2,400 by 2030 but it should be noted that New York’s total on-shore wind capacity in 2015 was 1,891 MW.

The biggest failing in this report is the lack of cost data. The report notes that their cost comparison is “not meant to be definitive in the absolute sense; rather we use a consistent framework across the different scenarios in order to ascertain relative cost patterns”. This modeling purports to show that their preferred alternative is cheaper than other choices using their relative costs. What is missing is the overall cost. The fact that the ReEDS model which “builds” off-shore wind capacity based in part on economics had to be adjusted by Synapse to “hard-wire” the capacity built to match the CES requirement suggests that ReEDS is not as optimistic about that resource. Furthermore, it has been noted that “The average household in Germany contributes an estimated 240 euros a year to renewable energy subsidies.” is not reassuring in this regard.

I will conclude this post with some particular issues with the modeling that may indicate problems with the results. The model “incorporates the addition of previously committed gas‐fired generation in the region in 2018” and cites the “CPV Valley unit, at 650 MW; and a generic combustion turbine unit at 90 MW”. The CPV unit is expected to be online in 2018 but instead of 90 MW of new combustion turbine capacity the Cricket Valley station alone is 1,100 MW   This plant is permitted, under construction and expected to be on line in the first quarter of 2020. That means that renewables will not be displacing old inefficient fossil-fired generation but the latest and most efficient fossil technology. Another assumption used in all the modeling scenarios is that there will be a 2.5% decline in the RGGI cap which has been proposed by Governor Cuomo but is not yet RGGI policy.

When I model something the first thing I check is the results relative to recent observations. I have a couple of problems with projections for 2016 compared to actual values. For example, the model’s estimate of 2016 CO2 emissions is 20% higher than actual emissions. When a model over estimates a key parameter by 20% in the first year I don’t put much weight into their projections in 2030. Another issue is the 2016 wind generation estimate of 5 TWh when the 2015 observed wind generation was only 4 TWh.   It is highly unlikely that the wind generation will increase 20% in one year so that is another likely over-estimate.

I have posted three tables with model projections for all six model runs for 2018, 2022 and 2030. Synapse Synapse Energy Generation and Capacity Appendix A Scenarios describes the model runs. Synapse Energy Generation and Capacity Appendix A Comparison of Generation Estimates describes the generation (TWh) estimates and Synapse Energy Generation and Capacity Appendix A Comparison of Capacity (MW) Estimates describes the  (MW) estimates for fourteen different source-type categories. I have issues with some of those category results. The scenarios address the Indian Point retirements so the nuclear estimates show that. Note that those projections assume no changes in the upstate nuclear units. Cuomo’s war on coal is reflected in shutting down the remaining coal plants. One of the unintended consequences of the renewable and energy efficiency is the effect on the profitability of the remaining fossil stations. For example, in the gas category there is a projected reduction in gas capacity of 21% from 2018 to 2030 in Scenario A6 but the generation drops 74%. My concern is that the drop in the generation from those facilities will mean that they cannot remain viable without a capacity payment. For new gas note that the exclusion of Cricket Valley means that their 2022 estimate of just over 5 Twh of generation is less than half of what I expect if Cricket Valley runs as expected. The wind estimates are all at least three times the observed 2015 NYS generation which confirms my expectation that aggressive wind development is necessary in these projections. It is also not clear why the wind generation projections in all four scenarios are less than either reference case. Even more vexing is that solar in the last scenario does not increase from 2018 to 2030. I am guessing that the solar money goes to aggressive energy efficiency. Note that the modeling assumes several fold increases in DG PV capacity. The last category that I want to address is oil-gas-steam. New York is unique in its reliance on this source category as backup for emergencies. Unless a production cost model is specifically tuned to New York then this is an easy category to turn down. However, reducing the generation, much less the capacity, is not as simple as it appears on first glance because of the role these units cover. I do not think those category estimates are realistic.

Ultimately this modeling exercise is a good example of Pragmatic Environmentalist Principle 4: We can do almost anything we want, but we can’t do everything. In the absence of absolute estimates I can only guess what the ultimate costs will be but the German experience of 20 euros per month for renewables is not comforting. I cannot endorse this approach because I fear the additional costs of renewables will divert too much of the state’s resources relative to other needs. New York State has to invest $40 billion in its water infrastructure just to provide clean water and treat wastewater. In my opinion investing in that immediate need and energy efficiency is a more appropriate social policy than subsidizing renewable energy. If, in fact, Indian Point has to close I suggest that accepting that its replacement power will have to include fossil generation is necessary.

Revisions to Replacement Power for Indian Point

Summary

Since the publication of my original post on this topic I realized that there were two natural gas fired combined cycle electric generating units in development and not just the one I thought. This update to the original post addresses the ramifications of that on replacement power and other emissions. Because the additional facility affects the conclusions I revised the entire post.

New York’s Governor Andrew Cuomo has threatened the closure of the Indian Point Energy Center located 25 miles north of New York City since his election and in January 2017 announced its closure by April 2021. Cuomo claims that Indian Point produces 2,000 megawatts of electrical power and that “more than enough replacement power to replace this capacity will be available by 2021”.

However, the problem is what are the characteristics of the replacement power relative to Indian Point? Indian Point’s nameplate capacity is 2,311 MW not 2,000 as described. Nuclear power is characterized by high capacity factors and because Indian Point provides over 20% of New York City’s power the location of the replacement generation matters. There are three projects that can replace that capacity and are at least located near New York City. Champlain Hudson Power Express transmission line has been permitted to bring 1,000 MW of Hydro Quebec hydropower into New York City but construction has not started. The Cricket Valley Energy Center is a 1,000 megawatt combined-cycle, natural gas fired generating plant that has just started construction and is expected to be on-line the first quarter of 2020. I did not include the CPV Valley Energy Center in the first post. It is a 650 MW combined-cycle, electric generating plant that is scheduled to go on line in February 2018.

In the original post I did not include CPV Valley so the claim of 2,000 MW so I disputed the claim that the replacement power was readily available but with adding it that claim is correct. The remaining and more subtle issue is whether these three facilities can replace Indian Point and not jeopardize other environmental goals.

I have been involved in the RGGI program process since its inception. Before retirement from a Non-Regulated Generating company, I was actively analyzing air quality regulations that could affect company operations and was responsible for the emissions data used for compliance. 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.

Cuomo’s Indian Point Closure Plan

As part of his state of the state proposals, Governor Andrew M. Cuomo announced the closure of the Indian Point Energy Center by April 2021. As described in the press release the Governor’s position is:

  • Replacement Power: Indian Point produces 2,000 megawatts of electrical power. Currently, transmission upgrades and efficiency measures totaling over 700 megawatts are already in-service. Several generation resources are also fully permitted and readily available to come online by 2021, after the plant’s closure, including clean, renewable hydropower able to replace up to 1,000 megawatts of power. Together, these sources will be able to generate more than enough electrical power to replace Indian Point’s capacity by 2021.
  • No Net Increase of Emissions Due to Closure: The Governor’s leadership on energy and climate change will ensure that Indian Point’s closure will not have an adverse impact on carbon emissions at the regional level. Through the Regional Greenhouse Gas Initiative, the state will continue to drive reductions in greenhouse gases across the power sector. Further, the Governor’s Clean Energy Standard to get 50 percent of New York’s electricity from renewables by 2030 is the most comprehensive and ambitious mandate in the state’s history to fight climate change, reduce harmful air pollution, and ensure a diverse and reliable energy supply at affordable prices.
  • Early Close Date: Entergy Corp. has agreed to cease all operations at Indian Point and will shut down the Unit 2 reactor in April of 2020. Unit 3 will be shut down in April of 2021. Unit 1 reactor was permanently shut down in October 1974 because the emergency core cooling system did not meet regulatory requirements. In the event of an emergency situation such as a terrorist attack affecting electricity generation, the State may agree to allow Indian Point to continue operating in 2-year increments but no later than April 2024 and April 2025 for Units 2 and 3 respectively.
  • Negligible Bill Impact: The Public Service Commission’s Indian Point Contingency Plan and other planning efforts have ensured that more than adequate power resources are able to come online by 2021 to ensure reliability of the power grid. Given these planning efforts and likely replacement resources, the plant’s closure in 2021 will have little to no effect on New Yorkers’ electricity bills.

Other Side of the Story – Replacement Power

There are two aspects of power generation that have to be considered when discussing replacements. The potential power output or name plate capacity and the actual generation produced. The New York State Independent Operator annual load and capacity report, the “Gold Book” provides that information. The name plate capacity of Indian Point 2 is 1,299 MW and Indian Point 3 is 1,012 MW. The average net generation from 2011 to 2015 from Indian Point 2 was 8,530 GWh and from Indian Point 3 was 8,422 GWh or 16,953 GWh from the facility. My point is that the net generation is the key parameter for replacement not the capacity.

In order to determine whether the Governor’s plan holds water we have to parse the press release. The first suggested component is “transmission upgrades and efficiency measures totaling over 700 MW that are already in-service”. In the original post I noted that I had trouble understanding how these measures will replace observed generation, but have since found a reference with an explanation. The New York Independent System Operator (NYISO) publishes an annual description of power trends. This is an absolute necessity due to the changes in the New York State electric system driven by the Governor’s Clean Energy Standard and Reforming the Energy Vision. The 2016 Power Trends document provided an explanation of the transmission projects. These projects were designed to increase the transfer capability into Southeastern NY so that excess upstate NY capacity could be transmitted to the region served by Indian Point. According to this document the transfer capacity was raised by 450 megawatts.

New York State has always had constraints on the amount of power that could be transmitted from upstate to downstate. These projects should be able to replace Indian Point generation that is used in the New York City area. However, I don’t think it is a like kind replacement of no-pollutant generation. While it can clearly move the upstate wind and solar power downstate, the upstate renewable facilities are not constrained by system needs. If they can generate then they do. The same argument can be made for the upstate nuclear power. If the nukes can run then they do. In other words, their generation is already being used elsewhere and is not going to provide added generation that can be transmitted downstate by these upgrades. Instead, the upstate replacement generation that can be transferred to downstate to make up the 450 MW will either be existing under-utilized fossil generation or new renewables. If it is fossil generation then there will be an increase in CO2 and other pollutants. If it is renewable then it is not new renewable that is going to be used to increase the amount of no-CO2 generation. Instead it is only going to replace the loss of the no-CO2 nuclear generation. In either case because Governor Cuomo has established goals for more renewables the source of the power from these transfer capacity improvements should be addressed.

The aforementioned NYISO 2015 Gold Book also notes that it also included 125 MW of additional demand response and combined heat and power resources to be implemented by Consolidated Edison, some of which is already in effect. The problem is that the 450 MW transmission upgrades these additional resources do not sum up to 700 MW.

The press release notes that “several generation resources are also fully permitted and readily available to come online by 2021, after the plant’s closure, including clean, renewable hydropower able to replace up to 1,000 megawatts of power.”   I assume that the hydropower replacement refers to Champlain Hudson Power Express. According to the Champlain Hudson Power Express web site the project will bring up to 1,000 megawatts (MW) of clean, renewable power to the New York metro area. This is consistent with the press release.

However the question is whether the three projects that are permitted can replace all 16,953 GWh of the generation from Indian Point. For the purposes of this analysis assume that Champlain Hudson Power Express power can be provided 100% of the time. With that assumption, it provides 8,760 GWh of power so we still have to replace 8,193 GWh of Indian Point Generation. According to the Cricket Valley web site this is a proposed 1,000 megawatt (MW) combined-cycle, natural gas-fired generating plant in Dover, NY that is expected to be on line by the first quarter of 2020. I could not find a proposed capacity factor (actual generation divided by the maximum potential generation) so assumed 80% which would produce 7,008 GWh. CPV Valley Energy Center is a 650 MW combined-cycle, natural gas-fired generating plant near Middletown, NY that is much further along and expected to be online in February 2018. Assuming an 80% capacity factor for this plant gives 4,555 GWh so these three facilities can provide over 3,300 GWh more than Indian point generated.

Other Side of the Story – Net Emissions

This revised post also addressed the claim that the plan is supposed to lead to no net increase of emissions due to closure. The emphasis has always been on carbon “pollution” and the press release is careful to claim no adverse impact on carbon emissions at the regional level skirting the question whether NY emissions will increase. Cricket Valley and CPV Valley both will emit carbon. Cricket Valley has an annual limit of 3,630,484 tons of GHG emissions and CPV Valley has an annual limit of 2,164,438 tons of CO2. To some extent in any scenario both facilities will displace Indian Point rather other fossil-fired facilities and those emissions will increase New York’s total emissions.

Of more concern to me are Nitrogen Oxides. The final Cross State Air Pollution Rule allowance budget and the Governor’s policies on allowance distributions could lead to a problem covering emissions with allowances (a topic for a separate post). If the generation gap from the closure of Indian Point is made up by the three projects described above, CPV Valley and Cricket Valley would increase annual NOx emissions by 289 tons. Emissions in the 2016 ozone season were 6,521 and the future allowance budget is only 5,135 tons so any increase in emissions is a further strain on the budget. New York State has aggressively pursued NOx reduction policies and there are not many opportunities left for additional reductions so any increase is problematic.

Other Sides – Timing and Bill Impact and Emissions

These sections from the original post are included for your information. No changes were made to the following paragraphs.

The schedule is for Entergy Corp. to shut down the Unit 2 reactor in April 2020 and Unit 3 in April 2021. The State may agree to allow Indian Point to continue operating in 2-year increments but no later than April 2024 and April 2025 for Units 2 and 3 respectively. Both the Champlain Express and Cricket Valley projects have been permitted but neither has started construction. The expected construction time for Champlain Express is three and a half years which means that it will not be ready by April 2020. Because natural gas combined cycle plants have relatively short construction times it probably will meet the first closure date if construction begins soon. I strongly believe that no new generation facility greater than 25 MW in New York State can be permitted in less than five years because of the extraordinary policies in place so nothing else could be permitted and constructed by the second closure date. So I expect that the extensions will be needed.

The Governor claims there will be negligible bill impact because of planning efforts and likely replacement resources. I am not an economist but the expected costs of Champlain Express is $2.2 billion and Cricket Valley is $1.5 billion have to be paid for somewhere. Surely the costs to continue operating Indian Point are less than that. Why won’t pre-mature retirement of this resource have a bill impact?

How Much Has the Regional Greenhouse Gas Initiative Reduced Other Pollutant Emissions?

The Regional Greenhouse Gas Initiative (RGGI) was supposed to be nearing completion of a 2016 Program Review but the election of Donald Trump and the fate of the national Clean Power Plan has delayed that process. This is the third post in a series of posts that will discuss how RGGI has fared so far and how that could affect the program review. As noted previously, I believe that RGGI allowance prices add to the cost of doing business but because the cost of allowances can be added into the bid price it is a nuisance and not a driver of decisions. This post addresses the effect RGGI has had on other pollutants as estimated by Abt Associates: Analysis of the Public Health Impacts of the Regional Greenhouse Gas Initiative, 2009 -2014.

According to the Energy Coordinating Agency this report shows that since 2009, RGGI has significantly reduced air pollution from fossil fuel power plants. The report goes on to estimate improvements to the health of people living in the Northeast as a result of those pollution reductions. According to the study the effort to curb carbon emissions has prevented 300-830 adult deaths, avoided 13,000 – 16,000 respiratory illnesses and staved off 39,000 – 47,000 lost work days for workers.

I have been involved in the RGGI program process since its inception. Before retirement from a Non-Regulated Generating company, I was actively analyzing air quality regulations that could affect company operations and was responsible for the emissions data used for compliance. 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.

Approach

I will briefly describe the three steps that Abt Associates used in their analysis. This post will primarily analyze the first step in their process. I compare their predicted generation and emissions reductions relative to the total reductions observed in the measured data. For the last two steps I offer some general comments.

Abt Associates used a three-step analytic process to estimate the impacts on air quality and public health resulting from implementation of the RGGI program from 2009 to 2014. In each of these steps they used specific modeling tools and datasets to estimate the incremental impacts of RGGI on the following variables: generation (in megawatt-hours (MWh)) by power plants, air pollution emissions, air quality, and public health. The approach is sequential. Results steps one and two were input to the final step that projected health impacts. Abt Associates noted that they “reviewed draft results at a highly disaggregated level and performed quality control before using results as an input to the next analytic step. In many cases, draft results were benchmarked to results from similar analyses and studies as another cross-check.”

The three steps are described as follows:

Step 1: Estimate annual changes in electric generation and emissions of air pollutants at power plants as a result of RGGI implementation from 2009 to 2014 using electricity dispatch modeling and EPA emissions data for EGUs.

Step 2: Estimate annual changes in air quality at the county level associated with changes in SO2 and NOx emissions from power plants, by year. EPA Co-Benefits Risk Assessment (COBRA) screening model

Step 3: Assess public health impacts associated with changes in air quality due to RGGI implementation from 2009 to 2014. EPA Benefits Mapping and Analysis Program (BenMAP).

Generation Reductions

Abt Associates calculated changes in electricity generation due to RGGI first on an absolute basis and then expressed them as a percentage relative to generation that would have occurred in the No RGGI scenario. They note that:

In competitive electricity markets, changes in any number of variables, including fuel prices, weather, and plant and system operational changes, can cause variations in the level of electricity dispatched by a given power plant (or group of plants) from year to year. In this analysis, however, our modeling results account for all of these factors and thereby isolate the incremental effect of RGGI on electricity markets and dispatch. Thus, we interpret RGGI-induced changes in generation to be a result of the combination of (1) RGGI states’ investments in energy efficiency and renewable energy and (2) the effect of CO2 allowance prices on electricity dispatch.

Therefore their Table 4 results in Comparison of Abt Associates Generation Changes Due to RGGI relative to Total Generation Changes are the reductions they assume that would not have occurred were it not for RGGI. Let’s try to compare their estimates with the total generation reductions that occurred.

I used measured data for my estimate of the total load reduction and that methodology has differences relative to their approach. I assume that their annual differences in Table 4 are relative to 2008. The EPA Clean Air Markets Division website provides gross load generation data from all electric generating units that participate in RGGI. Modeling electricity generation in their approach uses net load so there is a difference there.   In my analysis I did not include New Jersey and they did for the first compliance period. I did not go to the effort to manually include only those sources that participate in RGGI for the 2008 data. Instead I calculated the load from all programs that report to EPA in 2008. I believe that is a minor error because the difference in the RGGI only and “All Program” data sets in the years 2009-2014 ranged from 0.50% to 0.71%.

In my approach I calculated the total change in generation from 2008. The Abt Associates approach calculated reductions in annual generation ranging from a low of 2.0 percent in 2011 to a high of 7.0 percent in 2013. The difference in gross load between 2008 and the six years in the first two RGGI compliance periods ranged from a low of 3.5% in 2010 to a high of 18.7% in 2014. If we assume the two approaches are compatible, then we can estimate the fraction of the total reduction resulting from the Abt Associates estimates of RGGI investments and CO2 allowance prices on electricity dispatch. In 2010, this comparison suggests that the fraction of reductions induced by RGGI was over 80% of the total reduction. Even in the lowest year, 2011, the fraction of reductions induced by RGGI was 26.4%.

Disappointingly, the Abt Associates analysis does not provide an estimate of CO2 emission reductions determined by their approach so that we can directly compare alternative approaches provided in previous work. Although generation is not directly comparable to CO2 emissions it is relevant to point out the conclusions from my previous post:

The upper bound in CO2 emissions reductions due to RGGI is an econometric model that estimates that emissions would have been 24 percent higher without the program. RGGI estimates that emissions would have been 17% higher than without a program. If you assume that all the savings in fossil fuel use only displaced natural gas use instead of some other aggregation of fuels then emissions would have been only 5% higher.

These numbers are starkly different and need to be addressed before the Abt Associates analysis can be considered credible. To that end I recommend that Abt Associates provide their CO2 emission reduction estimates.

Emissions Reductions

In the first step Abt Associates estimated annual changes in electric generation and emissions of air pollutants at power plants as a result of RGGI implementation from 2009 to 2014 using electricity dispatch modeling and EPA emissions data for Electric Generating Units (EGUs). Essentially they are estimating the emissions that would have occurred were it not for the RGGI investments and CO2 adder cost to the dispatch cost of the plants. Using the same methodology as for the generation estimate I calculated the total emission reductions. Sulfur dioxide cumulative reductions from a 2008 baseline totaled 1,673,601 tons from all nine RGGI states compared to the ABT Associates estimated impact of RGGI reduction of 109,000 tons so the estimated reduction of RGGI is 6.5% of the total.   Nitrogen oxides cumulative reductions from a 2008 baseline totaled 335,440 tons from all nine RGGI states compared to the ABT Associates estimated impact of RGGI reduction of 46,000 tons so the estimated reduction of RGGI is 13.7% of the total.   While I have reservations that RGGI had any impact other than from the load associated with RGGI investments, I can accept them as upper bound estimates of the SO2 and NOx emission reductions due to RGGI.

Second Step

In the second step Abt Associates used EPA’s Co-Benefits Risk Assessment (COBRA) screening model. According to EPA, COBRA works as follows:

  1. COBRA contains detailed emission estimates of PM2.5, S02, NOX, NH3, and VOCs for the year 2017 as developed by the U.S. EPA. Users create their own scenario by specifying increases or decreases to the baseline emission estimates. Emission changes can be entered at the county, state, or national levels, and outcomes can be modeled nationwide or for smaller geographic areas.
  2. COBRA uses a reduced form air quality model, the Source-Receptor (S–R) Matrix, to estimate the effects of emission changes on ambient PM.
  3. Using an approach to estimating avoided health impacts and monetized benefits that is generally consistent with EPA practice, the model translates the ambient PM changes into human health effects and monetizes them.
  4. Users can view the results in tabular or geographic form.

There are multiple problems with this model for this application. EPA notes that it is “inflexible and simple” such that it is limited to the 2017 timeframe and there is no ability to import a different baseline. Abt Associates applied the model to different periods and used a different baseline. The RGGI sources are point sources and this model does not address their specific factors that convert emissions from these plants to particulate matter as opposed to the generic factors used. Finally, note that all the air quality impacts are a function of particulate matter.

Secondly, BenMAp “estimates the number and economic value of heath impacts resulting from changes in air quality – specifically, ground-level ozone and fine particles but note that the COBRA impacts are solely based on particulate matter. The model presumes that the health impacts of both pollutants include premature death and aggravated asthma. Ambient levels of sulfur dioxide, nitrogen oxides and particulate matter have all been reduced in recent years but at the same time asthma rates have been increasing. This inconsistency needs to be addressed before this approach can be accepted.

There also is a deeper issue associated with EPA epidemiological work with PM and health impacts that is the basis of BenMAP. EPA’s epidemiological work is based on data sets that are not available for independent review, were prepared by organizations that were being paid by EPA (and would lose funding if this were not an issue) and the relationship they claim is not present in other similar data sets. Moreover, EPA has yet to determine the specific effect of PM on humans that triggers the claimed impacts of their epidemiological studies. Given those limitations I do not accept these health effects. I encourage you read Steve Milloy’s book “Scare Pollution: Why and How to Fix the EPA” (2016) Bench Press for the complete story of this travesty.

Finally, we can make an order of magnitude estimate of the health outcomes using their methodology by simply scaling their emission reductions relative to the total emission reductions (Abt Associates Cumulative RGGI Health Benefits and Total Cumulative Health Benefits, 2009-2014). This estimate does not account for even the gross site specific implications of the Abt Associates analysis. However, because the air quality estimated concentrations are proportional to the emissions input the general concept is acceptable. There is one other gross assumption. Because fine particulates in the northeast are primarily related to SO2 and BenMAP calculates health impacts of particulates, I only scaled the SO2 emissions to predict the health impact differences. My point of these numbers is that the predicted impacts are large enough that someone should be able to prove this model works by evaluating the observed health effect data. Until that is done I will remain skeptical of this approach.

Whines

Not to be petty but in order for an analysis to be useful in public policy debate the results have to be reproducible. This analysis went out of its way to make replicating their numbers difficult. Frankly when there are obvious obfuscations you start to wonder if it was deliberate. To prevent that perception providing numbers up front is the safest course. Also note that I did ask the corresponding author for data but did not get a response. The following is a list of specific whiny issues I had with the report.

What was the baseline? I could not find this definition anywhere. I assume that because annual numbers were used that the year before the program started was the baseline. In my previous analyses of RGGI data I use the three-year period 2006 to 2008 as the baseline to compare with the three-year RGGI compliance periods.

SO2 and NOX data in metric tons. I do not understand why the emissions are reported in metric tons. In order to compare their results with any EPA report they have to be converted. Moreover, the input to the COBRA model is in short tons.

No tables with numbers. In order to compare their projections with actual emissions I had to manually scale bars on their figures. I think my estimates are good enough but this was an unnecessary hassle.

No CO2 reductions report. This was serious enough to include in the main body but bears repeating. In order for this study to be credible it needs to be compared to previous work. Without CO2 that is impossible.

Emission reductions in Figures 6 and 8 don’t add up to the emission reductions in Figure 7. After manually estimating the bars in the two figures it was very frustrating to find they didn’t match their totals. Double checking my work it is clear that there is a mistake in the Abt numbers.