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.

How Much Has the Regional Greenhouse Gas Initiative Reduced CO2 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 second 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. I will show how this added cost ultimately affects emissions in this post.

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.

RGGI Region CO2 Emission Reductions
For this analysis the RGGI reductions in the first two compliance periods of 2009-2011 and 2012-2014 will be compared to a pre-program baseline of 2006-2008. Note that this is an update to the estimates provided in an earlier post to incorporate RGGI’s latest Investment Summary Report . table-1-rggi-annual-co2-changes lists the changes in CO2 emissions in the RGGI states by fuel type. Note that this analysis uses EPA data and is not completely compatible with the RGGI affected source inventory.

The total and fuel-type specific annual emissions were subtracted from the baseline to get the reductions during the RGGI program. For the facilities in this dataset in the 2012-2104 compliance period there has been a 36 million ton reduction from the 127 million ton baseline or a 28% reduction. Note that coal and residual oil emissions dropped 49 million tons from the baseline of 85 million tons or 57%. Natural gas emissions increased 13 million tons and other solids (mostly wood) increased 0.5 million tons. Over the same time period, gross loads and steam load declined 20% and 55%, respectively.

According to the most recent RGGI Investment Summary Report “The lifetime effects of these RGGI investments are projected to save 76.1 million MMBtu of fossil fuel energy and 20.6 million MWh of electricity, avoiding the release of approximately 15.4 million short tons of carbon pollution.” In the 2012-2014 compliance period RGGI CO2 emissions were 91,421,635 tons of CO2 so based on this RGGI report were it not for RGGI there would have been 15.4 million more tons of CO2 emitted so total emissions would have been 106,821,635 tons. I also calculated the percentage difference with and without the program and that shows emissions would have been 17% higher than without the program.

A paper by Murray and Maniloff (2015) includes an estimate of RGGI program emission reductions. They concluded that “after the introduction of RGGI in 2009 the region’s emissions would have been 24 percent higher without the program, accounting for about half of the region’s emissions reductions during that time”. The April 29 2016 RGGI stakeholder presentation described that paper and further suggested that “The other half is due to recession, complementary environmental programs and lowered natural gas prices.” The results in this paper are based on an econometric modelling analysis.

After the publication of the Murray and Maniloff paper I contacted the authors with my reservations about their approach. After an initial response from Dr. Maniloff to my reservations I never received a follow up to my response. One disagreement was whether CO2 is different than all other air pollutants such that this undermines their explanation of how firms react to carbon constraints. I took exception to their characterization “firms facing a future carbon price regime may have reacted by retooling power plants to lower emitting processes in advance of the regulation taking effect”. I noted that there are no end of pipe abatement technologies for CO2, as there are for other pollutants (e.g. SO2 scrubbers) save for CCS which is not economic. Dr Maniloff responded that “this hardly means there are not actions that can be taken in response to the carbon constraints. Plants can improve efficiency (heat rate) at fossil units as they have, and firms can engage in fuel switching/redispatch from coal and oil to gas and renewables, as they have.” I responded that this is fine in theory but in practice, especially in a de-regulated market, the control strategy is to simply run with the allowances that are purchased. Heat rate improvements run the risk of running afoul of New Source Review requirements. If EPA determines that facility upgrades improve performance above their thresholds, then that the facility must upgrade its pollution control equipment to new source standards. Improvement to heat rate would likely throw the facility into NSR immediately and the costs of that equipment cannot be directly recovered in the bid price and those costs would overwhelm any value to RGGI compliance. The cost of carbon has been so low relative to the fuel cost that a switch to natural gas was the driver only based on fuel costs. Affected de-regulated sources do not re-dispatch to the operator’s renewables, they simply run less. Practically speaking for RGGI affected sources CO2 control was different because the only viable option was to run based on allowances purchased.

I think the biggest problem is that econometric models cannot fully account for site specific regulation impacts. No model can account for all the effects of regulations on company decisions to invest in new control equipment unless each facility is explicitly considered. Because of my particular experience in New York I have explicitly considered the factors affecting particular facilities when analyzing the impact of regulations. Consider, for example, the coal-fired RG&E Russel station in Rochester, NY and the NRG Huntley station outside Buffalo, NY. Before RGGI began the owners were faced with decisions for the future.

Before 2009, Russel station needed to invest in pollution control equipment for particulates, Hg and NOx or the facility would not be able to operate and meet emission compliance requirements already on the books. It operated from 2006-2008 (emitting ~ one million tons of CO2) but retired before 2009. I believe the owners decided that they might not be able to recover the costs for all the pollution control equipment over time so they decided to retire the facility. RGGI compliance is only an issue when the unit runs and simply adding the allowance cost to the bid price insures that cost is recovered. Therefore, I conclude that none of the observed reductions from this facility can be ascribed to RGGI.

At the other end of the spectrum for New York coal facilities is Huntley. This facility retired in early 2016 even though its owners made investments in pollution controls to meet the opacity, Hg and NOx limits. Despite those investments the facility closed like many other coal-fired plants because the operating cost of burning coal was not competitive with gas-fired competition. Presumably the erosion of load due to the recession and loss of manufacturing higher load requirements also played a factor. It can be argued that adding the allowance price to their bids meant the unit ran less. In practice I believe that this factor was small. It is only when the added price is enough to change the order of the bids in a step-wise fashion that there is an effect. My understanding is that the allowance price is so small relative to the fuel price differential that it was inconsequential. Given the range of factors affecting these coal units we can assume that New York coal retirements and operating reductions are more likely due to non-RGGI factors than RGGI itself. Ultimately, look at it this way – in the absence of RGGI the facilities would still have retired so any modeling approach that presumes that RGGI influenced the NYS coal retirements is wrong.

The lower bound for RGGI program CO2 emissions reductions during this period can also be estimated. It can be argued that the coal and residual oil emissions were lower due solely to the changes in cost differences relative to natural gas and additional regulations and compliance pressure for NOx, Hg, and (in New York) opacity. This assumes that RGGI compliance is incorporated into the bid price and so was not a driver in facility pollution control decisions. Making those assumptions then means that the CO2 reductions directly due to RGGI should be the savings of 76.1 million mmBtu of generation from natural gas specifically and the natural gas emission factor for CO2 should be used for CO2 displacement. Table 3 lists this calculated value, 4,452,850 tons. This calculation shows that emissions would have been only 5% higher than without the program.

To summarize, there is a range of CO2 emissions with and without RGGI based on assumptions and methodology. The upper bound 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 then emissions would have been only 5% higher.

Has the Regional Greenhouse Gas Initiative Been Successful?

The Regional Greenhouse Gas Initiative (RGGI) was supposed to be nearing completion of a 2016 Program Review[1] but the election of Donald Trump and the fate of the national Clean Power Plan has delayed that process. This is the first post in a series of posts that will discuss how RGGI has fared so far. This particular post will provide background information so that I don’t have to include it every time. The RGGI stakeholder process is dominated by its adherents and now that I am retired I can offer an alternative view of the program. In this post I will offer my thoughts on whether the program has been successful.

RGGI is a cap and auction program in nine states – Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode Island and Vermont – to reduce greenhouse gas emissions[2]. According to the most recent RGGI Investment Summary Report[3]:

Proceeds from the Regional Greenhouse Gas Initiative (RGGI) have powered an investment of $1.37 billion in the energy future of the New England and Mid-Atlantic states. This report reviews the benefits of programs funded through 2014 by RGGI investments, which have reduced harmful carbon dioxide (CO2) pollution while spurring local economic growth and job creation. The lifetime effects of these RGGI investments are projected to save 76.1 million MMBtu of fossil fuel energy and 20.6 million MWh of electricity, avoiding the release of approximately 15.4 million short tons of carbon pollution.

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. From that background let’s look at the RGGI results quoted above.

The biggest flaw in the adherent’s vision of RGGI success is that RGGI is a driver of affected source decisions. In my opinion based on my experience and discussion with company folks responsible for the economics and operations of affected facilities where I worked and elsewhere, RGGI is simply a tax. Yes it adds 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. I will address how this added cost ultimately affects emissions in a later post.

When RGGI notes that $1.37 billion is being invested in the energy future of the New England and Mid-Atlantic states that number reflects the proceeds from the allowance auctions aka the tax. Because this is a carbon tax there a couple of cautionary tales. The reference notes that the nine participating RGGI states received $1.79 billion in auction proceeds in the period covered by this report. RGGI investments represent $1.37 billion spent to date and another $329.4 million is committed to 2015 and future programs. Note that these numbers do not total up. Despite best intentions by those folks who set up the program $93.1 million has been transferred to state general funds by politicians. In other words any carbon tax should have iron clad specifications on how the money will be used or politicians will get involved and co-opt the stated goal of the tax.

In RGGI the stated goal was to invest the RGGI proceeds in programs that would ultimately reduce carbon emissions and protect the rate-payers. The Investment Summary Report notes the fraction of funding that reduce carbon emissions (overall 80%) for energy efficiency (57%), clean & renewable energy (15%), and GHG abatement (8%) programs. Direct bill assistance (15%) is a more difficult sell as a carbon abatement program but because increased costs to the consumer disproportionately affect those least able to afford those increases I personally can live with those programs. However, 4% of the funds went to “administration” and another 1% to the RGGI organization itself. Clearly when big bucks are involved politicians are not the only ones attracted to the trough. The concept of a carbon tax that offsets that cost and returns all proceeds to offset other taxes is attractive. Based on RGGI, however, be careful what you wish for.

To their credit RGGI analyses have always been careful to not over-sell the actual emission reductions due to RGGI itself. When the Program Review notes that the lifetime effects of these RGGI investments are projected to save 76.1 million MMBtu of fossil fuel energy and 20.6 million MWh of electricity they are basing those numbers on the displacement of energy and emissions due to their energy efficiency, clean and renewable energy and GHG abatement programs. As noted earlier these numbers will be addressed in a later post.

Finally let’s consider the ultimate goal of the program – GHG reductions. The Program Review Summary claims their investments have avoided the release of approximately 15.4 million short tons of carbon pollution. However, note that they spent $1.37 billion to achieve those reductions so the cost per ton is $88.67. Given that the EPA social cost of carbon is $36 per ton these reductions are not cost effective by that measure.

However one thing is missing in all of the analyses and reports to date. The ultimate purpose of the program is to lower global warming but nothing has ever been published quantifying what these reductions will do in that regard. A back of the envelope calculation shows why. A recently published paper[4] estimates that the Federal Clean Power Plan will reduce global temperature rise by 0.013 degrees Centigrade. The Clean Power Plan is supposed to reduce CO2 emissions by 870 million tons. The carbon reductions attributable to RGGI are 15.4 million tons and simply pro-rating the published projection of global temperature rise with the RGGI emissions yields 0.00023 degrees Centigrade. In my opinion because we cannot possibly measure that small a change in temperature the global warming benefit of this program is nil.

I will give RGGI credit for developing the infrastructure to conduct a cap and auction program. They have an auction system that has conducted numerous sales without a hitch, there is a CO2 tracking program and the compliance methodology works. In addition the investments in energy efficiency and direct bill assistance are social benefits with no regrets.  As a result I believe that RGGI is only a qualified limited success and no where near as successful as it its adherents claim.

[1] https://www.rggi.org/design/2016-program-review

[2] https://www.rggi.org/rggi

[3] https://www.rggi.org/rggi_benefits

[4] Bjorn Lombory, 2015: Impact of Current Climate Proposals, Global Policy, Article first published online: 9 NOV 2015, DOI: 10.1111/1758-5899.12295, http://onlinelibrary.wiley.com/doi/10.1111/1758-5899.12295/full

Cuomo Proposes a Lower Regional Greenhouse Gas Initiative Cap

I had intended to make my first post a description of what I hope to do at this website. However, I want to comment on an issue that has come up and have decided that an example of what I hope to do is better than a description.

On January 9, New York Governor Cuomo presented the 14th proposal of his 2017 State of the State: http://www.governor.ny.gov/news/governor-cuomo-presents-14th-proposal-2017-state-state-lower-regional-greenhouse-gas-initiative. He proposed lowering the Regional Greenhouse Gas Initiative (RGGI) Cap by 30% between 2020 and 2030. Let’s look at both sides of this issue.

Issue

The Regional Greenhouse Gas Initiative (https://www.rggi.org/) is a cooperative effort by nine Northeastern and Mid-Atlantic States to cap and reduce CO2 emissions from the power sector. Because emissions dropped much more than expected, the RGGI states revised and lowered the 2014 RGGI cap to 91 million short tons. The RGGI CO2 cap then declines 2.5 percent each year from 2015 to 2020. The current policy is that the cap will remain flat after that. Cuomo proposes to further reduce the cap from 78.2 million tons in 2020 to 75.1 million tons in 2021, declining to 54.6 million tons in 2030.
 

Cuomo’s Side of the Issue

According to the press release

In New York, RGGI has led to a 46 percent reduction in carbon emissions from affected power plants and a 90 percent reduction in coal-fired power generation. To date, New York State has generated close to $1 billion in RGGI proceeds, which help fund clean energy and emission reduction programs. Under the current policy, the RGGI cap remains consistent after 2020 and emissions remain flat region-wide. By reviewing the RGGI program and adjusting the cap to reflect the progress made in just a few short years, New York and neighboring states will continue to reduce emissions annually after 2020 and ensure that power sector emission reductions continue through 2030.

The Governor’s proposal to reduce RGGI’s cap an additional 30 percent between 2020 and 2030, builds upon Governor Cuomo’s landmark clean energy programs, including the Clean Energy Standard, established by the Governor in August 2016 to require 50 percent of New York’s electricity to come from renewable energy sources by 2030. An additional component of this plan includes capturing the carbon benefits of zero-emission nuclear power. 

Pragmatic Environmentalist Side of the Issue

While it is probably not fair to ask for supporting documentation for a press release, the Governor’s landmark clean energy programs have been remarkable for the lack of implementation information so developing a response is difficult. Nonetheless it is possible to show that the press release sound bite is at best, misleading. Consider this quote: “In New York, RGGI has led to a 46 percent reduction in carbon emissions from affected power plants and a 90 percent reduction in coal-fired power generation.” The implication is that were it not for RGGI these reductions would not have occurred.

The Environmental Energy Alliance of New York (EEANY) submitted a relevant white paper to RGGI on June 6, 2106 archived under the April 29 2016 stakeholder meeting section at https://www.rggi.org/design/2016-program-review/stakeholder-comments-2016. The white paper notes that there was a paper on this topic : Murray, Brian C., Maniloff, Peter T., Why Have Greenhouse Emissions in RGGI States Declined? An Econometric Attribution to Economic, Energy Market, and Policy Factors, Energy Economics (2015), doi:10.1016/j.eneco.2015.07.013. This paper concluded that “The analysis shows that after the introduction of RGGI in 2009 the region’s emissions would have been 24 percent higher without the program, accounting for about half of the region’s emissions reductions during that time”. The presentation further suggested that “The other half is due to recession, complementary environmental programs and lowered natural gas prices.”

There also was a relevant Congressional research service report Ramseur, Jonathan L., April 27, 2016: The Regional Greenhouse Gas Initiative: Lessons Learned and Issues for Congress, Congressional Research Service, 7-5700, R41836, The Regional Greenhouse Gas Initiative: Lessons Learned and Issues for Congress. There was no attempt to quantify the specific emissions impact but the author noted that

“Although actual emissions were ultimately well below the original emissions cap, the cap’s existence attached a price to the regulated entities’ CO2 emissions. Because the cap level was above actual emissions, the allowance price acted like an emissions fee or carbon tax. Although the cap likely had limited direct impact on the region’s power plant emissions, the revenues generated from the emission allowance sales likely had some impact on emission levels in the region.”

The White Paper includes an analysis that I prepared to quantify the change in emissions due to RGGI. I used data from EPA’s CAMD Data and Maps website to look at the changes in CO2 emissions in the RGGI states by fuel type. The analysis did not attempt to reconcile differences between RGGI and all the other programs in this database. Annual data were downloaded for the years 2006-2015 for the RGGI states for all programs. Non-RRGI affected units are included and some of the included units report only six months of the year so this is not an exact analysis. Nonetheless, these data can give us an idea of how RGGI emissions were reduced.

For this analysis (Table 1 in the white paper) the 2006-2008 data were averaged to establish a pre-RGGI baseline and the total and fuel-type specific annual emissions were subtracted from the baseline to get the reductions during the RGGI program. For the facilities in this dataset in 2015 there has been a 41 million ton reduction from the 127 million ton baseline or a 32% reduction. Note that coal and residual oil emissions dropped 57 million tons from the baseline of 85 million tons or 67%. Natural gas emissions increased 15 million tons and other solids (mostly wood) increased1.3 million tons. Over the same time period gross loads and steam load declined 23% and 58%, respectively.

The RGGI “Investment of RGGI Proceeds Through 2013” (Published April 2015 by RGGI Investment of RGGI Proceeds: Full Report). report states that “Over their lifetime, these RGGI investments are projected to save more than 48.7 million mmBtu of fossil fuels and 11.5 million MWh of electricity, avoiding the release of approximately 10 million short tons of carbon pollution”. In 2013 RGGI CO2 emissions were 89,115,811 tons of CO2 so based on this RGGI report were it not for RGGI there would have been 10 million more tons of CO2 emitted so total emissions would have been 99,115,811 tons so the difference from the baseline is 28,178,600 tons (Table 2 in the white paper). I calculated the percentage difference with and without the program to compare with results from the Murray and Maniloff paper. That calculation estimates that emissions would have only been 11% higher than without the program according to the RGGI estimate of investment impacts.

The lower bound for RGGI program CO2 emissions reductions during this period can also be estimated. It can be argued that the coal and residual oil emissions were lower due solely to the changes in cost differences relative to natural gas and additional regulations and compliance pressure for NOx, Hg, and (in New York) opacity. This assumes that RGGI compliance is incorporated into the bid price and so was not a driver in facility decisions. Making those assumptions then means that the CO2 reductions directly due to RGGI should be the savings of 48.7 million mmBtu of natural gas specifically and the natural gas emission factor for CO2 should be used for CO2 displacement. Table 3 lists this calculated value, 2,848,950 tons. This calculation shows that emissions would have been only 3% higher than without the program.

Recall the quote: “In New York, RGGI has led to a 46 percent reduction in carbon emissions from affected power plants and a 90 percent reduction in coal-fired power generation”. It is difficult to reproduce the reduction estimates but the values are consistent with the white paper estimates of the total reductions. Three different evaluations of the actual impact of RGGI concluded that the emissions would have ranged between 24% and 3% higher than without the program. I should also note that claiming RGGI has anything to do with the coal-fired power generation reductions is a stretch because of the effect of lower natural gas prices and other New York environmental regulations.

Next post: the feasibility of further CO2 reductions in New York.