NYS Climate and Community Protection Act

In the 2019-2020 regular sessions the New York State (NYS) legislature is debating the Climate and Community Protection Act (CCPA). This post calculates how much this legislation will reduce global warming.

The legislation definitions include “Greenhouse gas” means carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, sulfur hexafluoride, and any other substance emitted into the air that may be reasonably anticipated to cause or contribute to anthropogenic climate change.

The emission reduction goals are listed below

  • 75-0107. Statewide greenhouse gas emissions limits.
    1. No later than one year after the effective date of this article, the department shall, pursuant to rules and regulations promulgated after at least one public hearing, establish a statewide greenhouse gas emissions limit as a percentage of 1990 emissions, as estimated pursuant to section 75-0105 of this article, as follows:
          1. 2020: 85% of 1990 emissions.
          2. 2025: 65% of 1990 emissions.
          3. 2030: 50% of 1990 emissions.
          4. 2035: 35% of 1990 emissions.
          5. 2040: 20% of 1990 emissions.
          6. 2045: 10% of 1990 emissions.
          7. 2050: 0% of 1990 emissions.

In the absence of any official quantitative estimate of the impact on global warming from CCPA or any other New York State initiative related to climate change I did my own calculation. I simply adapted data for this emission reduction from the calculations in Analysis of US and State-By-State Carbon Dioxide Emissions and Potential “Savings” In Future Global Temperature and Global Sea Level Rise. This analysis of U.S. and state by state carbon dioxide 2010 emissions relative to global emissions quantifies the relative numbers and the potential “savings” in future global temperature and global sea level rise.   These estimates are based on the MAGICC: Model for the Assessment of Greenhouse-gas Induced Climate Change) so they represent projected changes based on the Intergovernmental Panel on Climate Change estimates. All I did in my calculation was to pro-rate the United States impacts by the ratio of New York emissions divided by United States emissions to determine the effects of a complete cessation of all CO2 emissions in New York State in 1990 proposed in the CCPA plan.

The first step is to quantify NY emissions. The New York State Energy Research and Development Authority Greenhouse Gas Inventory 1990-2015 contains an inventory of historical greenhouse gas emission data from 1990-2015 for New York State’s energy and non-energy sectors. In 1990 the NY total was 218.1 million metric tons. The New York impacts were calculated by the ratio of the NY emissions reductions to the US reductions in the report. For example, the NY % of global total emissions equals the % of US global total (17.88%) times the CCPA reduction emissions goal (218.1) divided by the US emissions (5631.3). The CCPA Potential “Savings” in Future Global Temperature Table lists the results.

These calculations show current growth rate in CO2 emissions from other countries of the world will quickly subsume New York total emissions much less any reductions in New York CO2 emissions. According to data from the U.S. Energy Information Administration (EIA) and based on trends in CO2 these emission reductions will be subsumed by global emissions growth in 79 days. Furthermore, using assumptions based on the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports we can estimate the actual impact to global warming for CCPA. The ultimate impact of the CCPA 100% reduction of 218.1 million metric tons on projected global temperature rise would be a reduction, or a “savings,” of approximately 0.0032°C by the year 2050 and 0.0067°C by the year 2100.

These small numbers have to be put in context. First consider temperature measuring guidance. The National Oceanic & Atmospheric Administration’s Requirements and Standards for NWS Climate Observations states that: “The observer will round the entered data to whole units Fahrenheit”. The nearest whole degree Fahrenheit (0.55°C) is over one hundred seventy times greater than the projected change in temperature in 2050.

Although this change is too small to measure I am sure some will argue that there will nonetheless be some effect on the purported impacts. However if these numbers are put into perspective of temperatures we routinely feel then that argument seems hollow. For example, in Syracuse NY the record high temperature is 102°F and the record low temperature is -26°F so the difference is 128 °F which is over 27,000 times greater than the predicted change in temperature in 2050. The annual seasonal difference ranges from the highest daily average of 71.6°F to the lowest daily average of 23.2°F, or a difference of 48.4°F which is over 10,000 times greater than the predicted change in temperature in 2050. The average difference between the average daily high and average daily low temperature is 10.4°F or nearly 4,000 times greater than the predicted change in temperature in 2050. Clearly the projected temperature change is so much less than what we routinely encounter there will be no personal effect.

Another way to give you an idea of how small this temperature change consider changes with elevation and latitude. Generally, temperature decreases three (3) degrees Fahrenheit for every 1,000 foot increase in elevation above sea level. The projected temperature difference is the same as going down 27 inches. The general rule is that temperature changes three (3) degrees Fahrenheit for every 300 mile change in latitude at an elevation of sea level. The projected temperature change is the same as going south two thirds of a mile.


I do not think that there is any question why the State has not provided a quantitative estimate of the impact on global warming from CCPA or any other New York State initiative related to climate change. Clearly we can expect no discernable impact. The calculated values provided in this post are based on the “consensus” estimates of the Intergovernmental Panel on Climate Change which I personally believe over-estimate the impact of temperature changes caused by greenhouse gas emissions but do represent the justification for the CCPA. As shown here claiming any observable impacts for the projected small change in temperature due to these emissions reductions is a stretch at best.

New York Peaking Turbines


On February 28, 2019 the New York State of Department of Environmental Conservation (DEC) proposed regulations to lower allowable nitrogen oxide (NOx) emissions from simple cycle and regenerative combustion turbines during the ozone season. On the face of it this should be a relatively simple air quality issue but it is complicated by Governor Cuomo’s clean energy agenda. I am motivated to write this post on air quality regulation and energy policy because the majority of what has been said so far about this regulation fails to discuss the complexities of the issue and misses the point of the regulations.

This post describes an open regulatory issue and I want to emphasize that the following represents my opinion and not the opinion of any of my previous employers or any other company with which I have been associated. Ozone pollution is currently New York State’s most difficult air quality issue and I have been following the particular aspect of these turbines and their effect on ozone for over 20 years. I will try to show in this post the background of the problem and how this regulation is embroiled in energy policy implications that are complicating the issue considerably.


The proposed regulation covers simple cycle and regenerative combustion turbines but I am going to focus on just simple cycle turbines in New York City which make up the majority of the turbines in question. In the early 70’s Consolidated Edison was an integrated utility and responsible for generating and distributing electricity to New York City. Their generation planners developed a fleet of baseload, intermediate and peaking generating plants to provide power for the expected demand. (If you are unfamiliar with this concept I recommend the Generation Planning 101 section at this link).

Keep in mind that New York City requires massive amounts of power and there are geographical limitations as to how much can be imported in so the whole metropolitan area is a load pocket.   Moreover there were areas in the City that had their own load issues, i.e. they are in load pockets within the City-wide load pocket. In order to provide peaking power for the City and those areas Con Ed developed four combustion turbine facilities that use simple cycle turbines: Astoria (558 MW current nameplate capacity), Gowanus (640 MW), Narrows (352 MW) and Ravenswood (375.3 MW). According to the NYISO “Gold Book” in 2017 the net energy generated from all four facilities was 212.2 GWh with an overall capacity factor of 1.3% as shown in New York City Simple Cycle Peaking Turbines Summary.

New York City Simple Cycle Peaking Turbines Summary
  Number of Name Plate 2017 Net Energy Capacity
Facilities Turbines (MW) GWh Factor
Astoria 12 558.0 103.2 2.1%
Gowanus 32 640.0 31.9 0.6%
Narrows 16 352.0 56.6 1.8%
Ravenswood 10 375.3 20.5 0.6%
Total 70 1,925.3 212.2 1.3%

The units at these facilities are known as peaking turbines for a reason. They only run when power is really needed. For New York City this is primarily during the summer when load peaks due to air conditioning load. When Consolidated Edison was responsible for electric system reliability they had a fuel and generating mix that addressed peak load using these relatively cheap to install and operate turbines. Simple cycle turbines are basically jet engines hooked up to an electrical generator. In order for these sources to be profitable they have to recover all their operating and maintenance costs for the year during those peak periods. Part of the reason costs go up so much when energy demand is high is because of this effect.


While appropriate at the time they are ready for replacement. The turbines at these four facilities are approaching 50 years old, they are inefficient inasmuch as they burn more fuel than a new turbine to produce the same amount as power, and they are dirty, that is to say their emission rates are much higher than a modern turbine.


However, New York State de-regulated the electric sector at the turn of the century. As part of that process, Consolidated Edison sold most of their generating facilities and, in order to encourage competition, the in-city fossil generation assets were sold to three different companies. In the simpler time before de-regulation, DEC would have promulgated a phase-out rule and Consolidated Edison would have proposed replacement power generating facilities and received cost recovery from the NYS Department of Public Service in a rate case because of the obvious need.   Today’s owners have no such assurances. Instead they have to rely on the market to recover their investment costs. As a result energy policy is a major concern.


Ozone Air Quality Issue

As noted previously, ozone is New York State’s most difficult are quality problem. Despite years of progress ozone stubbornly fluctuates around the current National Ambient Air Quality Standard (NAAQS) limit that protects human health. It is important to keep in mind that the limit has changed over time so there has been progress but reaching the current limit has proven difficult. Ground-level ozone is not directly emitted into the atmosphere. Instead it is created in a complex photo-chemical reaction (it needs sunlight) from oxides of nitrogen (NOX) and volatile organic compounds (VOC). It is difficult to control in New York City because there are two pollutants, the reaction that creates ozone takes time so wind transport is an issue and transport in the complicated wind regimes along the Atlantic and Long Island Sound coastlines is difficult to simulate.


Ozone reaches unhealthy levels on hot sunny days and therein lies the rub. On hot sunny days people want air conditioning and as a result those are the days of peak load. That means that the peaking turbines usually run on those days most conducive to ozone formation. On those days reductions at all sources of NOX and VOC have been considered to control ozone. Because NOX is emitted from all combustion sources and VOCs are emitted from most things that have an odor there are all kinds of sources that affect ozone concentrations. Peaking turbines are one of the last large sources and I believe need to be controlled. As a side note however, I don’t think that when they are controlled that ozone compliance will be attained but it is progress and their time has come.

Electric Sector Energy Policy

If this were only an air quality issue the New York State Department of Environmental Conservation (DEC) would have simply promulgated a rule that requires phase out over time a long time ago. Unfortunately, there are energy policy ramifications, because while they are dirty, they also are necessary to provide power during peak periods. DEC wants to keep the lights on so they have not proposed such a rule until this time. During the development of the regulation the primary concern was how to develop a regulation that would give time for replacement power to be developed.

According to de-regulated utility theory the market will respond to needs when the price is right. In this case, that will be when developers believe the market supports permitting and building replacement power plants. I am not an economist or power plant developer but it is my opinion that you asking a lot of the market to provide an incentive to an investor to commit to developing a power plant anywhere, but (as we shall see) in New York that is doubly true. So what is the peaker market situation in New York? As mentioned before three companies currently own the four primary peaker turbine facilities in New York. One has not done anything. As far as I can tell that simply may because their facility has more site constraints than the other two companies. The other two companies have replacement plans.

According to the NYISO Gold Book, NRG Energy first proposed to re-power its Astoria Gas Turbine facility in the 2009 Gold Book and there is a project proposed in the most recent edition. Their plan is to build “fast-response, high efficiency combined cycle” turbines to replace the existing facility. New York has excruciating permitting requirements for power plants which are a major hurdle for development. The fact that NRG has a permitted project is a big plus. Again, I am no economist or power plant developer, but it appears to me that NRG thought they could make money when they were doing the permitting but has not yet decided to commence construction so they are not sure they can make money re-powering its turbines. Only time will tell whether that economic decision will change when this regulation is implemented.

Eastern Power Generation owns the Gowanus and Narrows turbine facilities. They have proposed to re-power Gowanus and retire Narrows at the formal start of their permitting process so they are navigating the process. In addition to emission reductions, their proposal will reduce the peak amount of power that can be generated. Given that their permitting program is proceeding they must believe they can make money once the facility is built.


To recap, DEC has proposed a regulation to phase out older peaking turbines because of their high emissions that affect ozone concentrations. The phase out is complicated by the need to insure peaking power is available but two owners have expressed interest in developing replacement power plants to meet that need. So on the face of it all looks good. If only it were this simple.

New York State Announcement

The only official announcement of this rule was from the New York State Energy Research and Development Authority (NYSERDA).

Governor Andrew M. Cuomo today announced that the New York State Department of Environmental Conservation released proposed regulations to improve air quality and protect public health with new, stringent requirements on peak-use power plants. The proposal will substantially reduce emissions from the “peaking” power plants operating on the hottest days with the most air pollution. These dirty, inefficient plants, are also major sources of carbon pollution. Transitioning away from them is a critical component of achieving Governor Cuomo’s nation-leading Green New Deal. These regulations will help to reduce greenhouse gas emissions 40 percent by 2030 and shift to 100% clean electricity by 2040.

“Climate change is a frightening reality, and while the federal administration buries its head in the sand, New York is taking action to protect our environment and the health of our residents,” Governor Cuomo said. “These proposed regulations are a critical step toward getting older, dirty power plants off the grid in the state’s most vulnerable areas, and demonstrates New York’s leadership in developing a clean energy economy and healthier communities for generations to come.”

There are several odd things about this announcement. Firstly, it did not come from the agency responsible for the rule. I am not sure why DEC would not have made it. The press release correctly notes that it will substantially reduce emissions from peaking power plants. However it states that these units are “also major source of carbon pollution”. Then it goes on to state that this is a critical component for the greenhouse gas emissions goals. The comment about “getting older, dirty power plants off the grid in the state’s most vulnerable areas” is an apparent sop to the environmental justice community. The bottom line is that we have gone from an air quality issue complicated by de-regulation to a “critical” component of Governor Cuomo’s Green New Deal and all the political pandering that entails. I address these points relative to the real world below.

Cuomo’s announcement says that these sources are a major source of carbon pollution. The four peaking turbine facilities I am focusing on in this post emitted 79,385 tons of CO2 in 2017. Other RGGI affected sources in New York emitted 26,064,607 tons of CO2 in 2017. I do not agree that 0.32% of the electric sector emissions is significant. The claim that these turbines are a major source of carbon pollution is absurd.

Cuomo also claims that this is a critical component of the needed reductions for his goals. The NYSERDA Greenhouse Gas Inventory 1990-2015 contains an inventory of historical greenhouse gas emission data from 1990-2015 for New York State’s energy and non-energy sectors. It shows that in 2015 the electric sector was responsible for 16.3% of the state’s emissions. The percentage of these peaking turbines to total electric sector emissions is only 0.043%.   One of the Cuomo goals is to reduce total NYS emissions 80% from 1990 levels. In 1990 CO2 emissions in New York State totaled 185,719,081 tons so the goal will be to get down to 37,143,816 tons. In 2015, CO2 emissions were 164,726,801 tons so the State “only” has to reduce another 127,582,985 tons. If the state is to meet the 2050 goal, then reductions of 3,645,228 tons per year are necessary. In other words the peaking turbines “critical” component (79,385 tons) is 2.2% of the reduction needed for one year which is, again, absurd.

My concern is with the energy policy implications. The announcement also quotes Cuomo as saying “These proposed regulations are a critical step toward getting older, dirty power plants off the grid in the state’s most vulnerable areas”. While these plants are indisputably old and dirty the energy policy question is whether they can be replaced by markedly cleaner fossil. Cuomo was badgered into “committing” to no new natural gas plants in May 2018. In February 2018 the Administration forced the New York Power Authority to do additional studies of the proposed Empire State Plaza Microgrid and Combined Heat and Power Plant project in Albany because the power plant was going to be powered by natural gas in response to local pressure to not use natural gas. I am not sure what the Administration position is on natural gas units for his Green New Deal. Additionally note that the New York City Council Climate Mobilization Act proposed regulation requires the city to complete a study over the next two years on the feasibility of closing all 24 oil- and gas-burning power plants in city limits and replacing them with renewables and batteries. Ultimately the question is whether the environmental agenda for absolutely no more natural gas infrastructure will derail the proposals for new power plants.

 The air quality issue is whether these climate related energy agenda policies will affect the schedule for the replacement of these power plants. One last time, I am no economist or power plant development investor but it seems to me that these are not policies that encourage the proposed re-powering projects. On the other hand I have done enough energy research to determine that replacing dispatchable peaking power with renewables and enough energy storage to guarantee power is available for the peak needs given New York City constraints is a technological reach and a money pit. I fear that the politicians are going to delay what I believe what will ultimately be determined as necessary re-powering projects.


While many stories I have read about the proposed regulation to retire these peaking turbines as a component of Cuomo’s clean energy initiatives that is not the case. The New York City peaking turbines need to be replaced as part of the process of ozone attainment. They are dirty and inefficient but most of all they are approaching 50 years old and may fail when needed most. Proposals have been made to replace existing units with modern, efficient and markedly cleaner units. Unfortunately the energy innumerate claim that they can be replaced with renewables but the reality is that that is a technological stretch. The real story is that Cuomo’s energy initiatives will likely delay replacing these units or putting the City at risk of another black out banking on an untried and technologically challenging renewable and storage plan.

NYS Climate and Community Protection Act Rationale

In the 2019-2020 regular sessions the New York State (NYS) legislature is debating the Climate and Community Protection Act (CCPA). This post addresses the claims of increasing severity and frequency of events attributed to climate change in the CCPA rationale.

The bill states:

Climate change is adversely affecting economic well-being, public health, natural resources, and the environment of New York. The adverse impacts of climate change include:

      • an increase in the severity and frequency of extreme weather events, such as storms, flooding, and heat waves, which can cause direct injury or death, property damage, and ecological damage (e.g., through the release of hazardous substances into the environment);
      • rising sea levels, which exacerbate damage from storm surges and flooding, contribute to coastal erosion and saltwater intrusion, and inundate low-lying areas, leading to the displacement of or damage to coastal habitat, property, and infrastructure;
      • a decline in freshwater and saltwater fish populations;
      • increased average temperatures, which increase the demand for air conditioning and refrigeration among residents and businesses;
      • exacerbation of air pollution; and
      • an increase in the incidences of infectious diseases, asthma attacks, heart attacks, and other negative health outcomes.

This rationale is similar to most calls for action. Invariably there is a listing of weather events, claims of increasing severity and frequency, notes that extreme weather causes damages and, finally, insinuations that the proposed action will reduce damage.

When I first started this blog I developed a list of pragmatic environmentalist principles that describe my beliefs. This post illustrates my first principle that there are two sides to environmental issues and my latest principle that arguments about the issue are usually based on how each side interprets conflicting data. In this case the focus on one interpretation obscures the possibility that direct action would likely be a more effective policy alternative than the indirect policy proposed to control greenhouse gas emissions in hopes that will affect one of the drivers of the rationale examples.

Extreme Weather Events

The CCPA claims that climate change is adversely affecting New York now and cites storms, flooding, heat waves and rising sea-levels. If the CCPA were correct then all the occurrence of all these events should be increasing in frequency and intensity. In fact, the data on these extreme weather events are all easily available, and clearly show that there are no increases in any category other than normal fluctuations, and certainly nothing that can be attributed to human influences. Here is a link to a definitive document prepared by Francis Menton compiling evidence in all these categories and others. Judith Curry recently prepared a Special Report on Hurricanes and Climate Change that assesses the current status of hurricanes and climate.

The NY CCPA rationale for extreme weather events echoes the constant barrage of popular media accounts that attribute any unusual weather to climate change but in every instance there are data that indicate otherwise.

Decline in freshwater and saltwater fish populations

One example of the claim that declining fish populations are due to warming seas is the recent paper Impacts of historical warming on marine fisheries production. It states that “temperature-dependent population models to measure the influence of warming on the productivity of 235 populations of 124 species in 38 ecoregions. Some populations responded significantly positively (n = 9 populations) and others responded significantly negatively (n = 19 populations) to warming, with the direction and magnitude of the response explained by ecoregion, taxonomy, life history, and exploitation history. Hindcasts indicate that the maximum sustainable yield of the evaluated populations decreased by 4.1% from 1930 to 2010, with five ecoregions experiencing losses of 15 to 35%.” This description of the study seemingly supports CCPA rationale. It states that the study “looked at the impact of rising ocean temperatures on 124 marine species representing about one-third of the global catch from 1930 to 2010. It found that the “maximum sustainable yield,” or the amount of fish that could be caught each year without jeopardizing future harvests, dropped by 4.1 percent over this period as a result of climate change.”

Actually the study did not say anything nearly as alarming. It looked at 235 populations and found that warming had a positive influence on 9 populations, no influence on 207 populations and a negative influence on 19. Reality is that the 4.1% decrease in maximum sustainable yield only could be attributed to 19 of 235 populations. There is no question that decreasing fish stocks is a serious environmental problem. However the problem is over-whelmingly due to over-fishing “Increased human demand for fish and subsidies for fishing fleets have resulted in too many boats chasing too few fish”.

The NY CCPA rationale does not address the root cause of the decline in fish populations so it is unlikely that the legislation will have any effect on fish populations.

Increased average temperatures

I agree that average temperatures are increasing but I do want to point out that even this relatively uncontroversial statement is complicated. For example, consider the points made about the United States average temperature trend in this video. It shows that if you calculate the trend using the raw data the trend is cooling but recent adjustments have shifted it to warming.

The primary concern for increased temperature is heat waves and the National Weather Service NYC office determined the trend of decadal heat waves that clearly showed an increase in the length of heat waves since 1880. However, I believe that it can be argued that the urban heat island mentioned in the report is a primary driver of the Central Park trend. Trying to determine how much of the temperature and heat wave trend is caused by the greenhouse gas effect (the target of CCPA) compared to land use change and natural variation is a non-trivial task completely ignored by simply claiming that average temperatures are increasing.

Exacerbation of air pollution

The only air pollutant regulated by the Environmental Protection Agency that can possibly be exacerbated by warmer temperatures is ozone. Ozone is a secondary air pollutant created by a complex photo-chemical reaction from nitrogen oxides and volatile organic compounds and that reaction is temperature dependent. However regarding ozone levels, the relative effect of temperature compared to emission rates is small as shown by the fact that New York State ozone concentrations have been decreasing even though temperatures are increasing.

Increased incidences of diseases

The CCPA rationale claims climate change can increase the incidences of infectious diseases, asthma attacks, heart attacks, and other negative health outcomes. According to the World Health Organization report on climate change and infectious diseases it is well known that climatic conditions affect epidemic diseases. That report goes on to state that “Malaria is of great public health concern, and seems likely to be the vector-borne disease most sensitive to long-term climate change”. However, it also is well known that during the construction of the Erie Canal canal fever was a concern, particularly during construction across the Montezuma Marsh.   In fact there were malaria problems even further north in Ontario when the Rideau Canal was built. This article explains that malaria can be controlled by “reducing the numbers of malaria parasites to a point low enough to break the infection cycle.”

The argument for asthma attacks and climate change is that it increases water and air pollution. One study claims that there is an increase in heat-induced heart attack risk in recent years. But they go on to note that “Individuals with diabetes or hyperlipidaemia were particularly at risk over the latter period. The researchers suspect that this is partly a result of global warming, but that it is also a consequence of an increase in risk factors such as diabetes and hyperlipidaemia, which have made the population more susceptible to heat.”

All these examples are similar and the rationale that reducing greenhouse gases will have an effect is flawed.   For malaria the effect of long-term climate change can be mitigated much better by directly breaking the infection cycle than indirectly reduce mosquitos by trying to control temperatures. Directly mitigating air and water pollution is more effective than trying to reduce it by controlling temperature. Finally, directly reducing other heart attack risk factors is likely more effective than indirectly reducing temperature.


Advocates for this legislation and other similar programs in New York State claim that they are all for the science. So am I. There is no question that global temperatures have been warming since the end of the Little Ice Age in the early 1800’s. There also is no question that increased levels of carbon dioxide and other greenhouse gases reduce out-going long-wave radiation and that warming results. Because human activities have added to those gases there is no question in my mind that at least some of the observed warming is very likely due to mankind. The question is how much of the observed warming is due to greenhouse gases relative to other human factors and the natural causes that have driven all previous climatic change. That makes all the difference.

Despite the constant barrage of popular media accounts that simply state that climate change is real and caused by mankind, reality is much more complex and it is not clear that mitigating greenhouse gases will necessarily affect climate change. We do not understand the natural causes of climate variation responsible for historic climate change. If we did understand them then we would be able to predict the weather for the next season, for example how much snow and how much cold. Clearly we don’t.

More importantly, for societal policy there is a trade-off. I tried to show that if we are concerned about the issues in the CCPA rationale that are ascribed to climate change that directly addressing them will likely be more effective than trying to control the climate. Moreover, the Ridley’s Paradox should also be considered: Economic damage from man-made ‘climate change’ is illusory whereas damage from man-made ‘policies’ to fight the said change is real.

Pragmatic Environmentalist of New York Principle 10: Environmental Issues are Rarely Definitive

This is one of the principles that that describe my pragmatic environmentalist beliefs.

Principle 1 states that almost all environmental issues have two legitimate sides. Because that is a given that means that two people can look at the same data and come up with opposite conclusions. This corollary principle asserts that as a result there are two legitimate arguments based on how each side interprets data. As a result environmental issues are not usually definitive.

For an example of this failure, consider “How to use critical thinking to spot false climate” claims by Peter Ellerton, Lecturer in Critical Thinking, Director of the UQ Critical Thinking Project, The University of Queensland. The author states:

Despite scientists’ best efforts at communicating with the public, not everyone knows enough about the underlying science to make a call one way or the other. Not only is climate science very complex, but it has also been targeted by deliberate obfuscation campaigns.

His post describes a paper that describes a “critical thinking approach to climate change denial”.

He describes six steps to evaluate contrarian climate claims and the post provides an example how it can address the following example:

    • Premise one: The climate has changed in the past through natural processes
    • Premise two: The climate is currently changing
    • Premise three: If something was the cause of an event in the past, it must be the cause of the event now
    • Conclusion: The climate is currently changing through natural processes.

In order to prove that this is incorrect he states that “Current climate change is much more rapid than previous climate change” and concludes that they are not the same phenomenon so the argument that climate is changing due to natural processes is wrong.

This argument fails to note that the historical data record for climate rate change is very limited and ambiguous at best. Ideally in order to evaluate climate change you would want to measure a parameter using the same instruments with the same techniques at a location that has had no nearby changes over as long a period of time as possible. Clearly this limits your available data quite a bit so you have to make compromises to get a long period of record. In order to get really long climate change records you eventually have to substitute instrumentals records with proxies. Even if you can find a proxy that has the same accuracy the problem for rate of change estimates is that the observational time scale differs. For example, if you are using coral growth rates, the temperature signal is measured over years whereas thermometers measure over days. As a result, comparison of different rate of change trends are difficult and may not be appropriate due to the classic apples to oranges comparison issue.

The premise in this paper to prove the contrarian argument wrong is that current climate change is much more rapid than previous climate change. The failure to acknowledge that any data used to estimate the rate of climate change is ambiguous weakens that premise considerably.   Pragmatic environmentalism is all about science based decision making that acknowledges both sides of arguments.

Air Source Heat Pumps In New York

New York’s proposed Community and Climate Protection Act has a goal for “the state of New York to reduce greenhouse gas emissions from all anthropogenic sources 100% over 1990 levels by the year 2050, with an incremental target of at least a 50 percent reduction in climate pollution by the year 2030”. In order to reach that ambitious CO2 reduction goal all sources of CO2 emissions have to be reduced. One energy sector with relatively large emissions is residential home heating and the clean energy alternative for home heating is electric heat pumps. In this post I explain why I think that air source heat pump deployment in New York coupled with the simultaneous goal to eliminate greenhouse gas emissions is fatally flawed based on a case study for conversions near Caledonia, NY.


How Stuff Works explains that “heat pumps use a small amount of energy to move heat from one location to another”. Air conditioners cool our homes by removing heat from the air inside and moving outside. An air-source heat pump acts like an air conditioner in the summer and in the winter works in reverse moving heat from the outside air into the home to warm it. Obviously this kind of heat pump eliminates the need to have two separate systems and advocates tout its energy savings too. According to the Department of Energy (DOE):

An air-source heat pump can provide efficient heating and cooling for your home. When properly installed, an air-source heat pump can deliver one-and-a-half to three times more heat energy to a home than the electrical energy it consumes. This is possible because a heat pump moves heat rather than converting it from a fuel like combustion heating systems do.

Air-source heat pumps have been used for many years in nearly all parts of the United States, but until recently they have not been used in areas that experienced extended periods of subfreezing temperatures. However, in recent years, air-source heat pump technology has advanced so that it now offers a legitimate space heating alternative in colder regions.

For example, when entire units are replaced in the Northeast and Mid-Atlantic regions, the Northeast Energy Efficiency Partnerships (NEEP) found that the annual savings when using an air-source heat pump are around 3,000 kWh (or $459) when compared to electric resistance heaters, and 6,200 kWh (or $948) when compared to oil systems. When displacing oil (i.e., the oil system remains, but operates less frequently), the average annual savings are near 3,000 kWh (or about $300).

Reading this statement gives the impression that this technology is a “no regrets” solution for replacing oil heating CO2 emissions because it saves money for home heating. However, there is a critical caveat for New York State. Air-source heat pumps only work when they move heat and when it is really cold (below zero degrees Fahrenheit) there is no heat in the air to move.

The American Council for an Energy-Efficient Economy published a paper that illustrates this issue with air source heat pumps: Field Assessment of Cold Climate Air Source Heat Pumps (ccASHP) (https://aceee.org/files/proceedings/2016/data/papers/1_700.pdf). The report describes a Center for Energy and Environment field study in Minnesota where cold climate air source heat pumps were directly compared to propane and heating oil furnaces. The report notes that “During periods of very cold temperatures when ccASHPs do not have adequate capacity to meet heating load, a furnace or electric resistant heat can be used as backup.” Figure 2 (ASHP Supplemental Energy Use) from that document graphically shows the problem. In this field study homes were instrumented to measure the heat pump and furnace backup usage. Backup furnace usage was relatively low and the heat pump provided most of the heat until about 20 deg. F. For anything lower, heat pump use went down and the furnace backup went up. Below zero the air source heat pumps did not provide heat and furnace backup provided all the heat.

I believe that there are two problems with the plan to deploy air source heat pumps. I suspect but will not try to evaluate that because a fossil fired furnace or electric resistant heat must be used as backup in a typical New York State winter the cost savings from a more efficient heat pump are offset by the need to maintain a second heating system. The other problem is what might happen to peak electrical loads if electric resistant heat is the preferred backup system. The analyses that I have reviewed point out that converting a natural gas system to an electric heat pump system increases operating costs because natural gas is so low. Propane or fuel oil conversions save money so would be the first to convert because of the higher costs of propane and fuel oil. However, I am not sure that homeowners who convert would want to maintain an oil or propane furnace simply because of the storage system requirement. Consequently, I believe radiant electric heat will be the preferred option for air source heat pump conversions. If residential home heating is electrified significantly electric load will increase and I wonder what could happen to load when the efficient heat pump is replaced with radiant electric heat when the temperatures get really cold.


I hypothesize that the combination of widespread air source heat pump deployment and increased reliance on wind and solar renewable energy will create unacceptable reliability issues during peak winter load periods. I evaluated energy usage for one week before and one week after the 2017-2018 peak winter day (January 5, 2018). I had previously analyzed data near Caledonia, NY and will use that for this analysis.

 I used two sources of data. Electric load data for New York State are available from the New York State Independent System Operator and meteorological data are available from the NYS Mesonet meteorological system. The NYS mesonet is a network of 126 weather observing sites across New York State. The official website of the Mesonet includes a tab for live data that brings up station information for the 125 operating individual sites that shows that available data include wind direction and speed, temperature at two levels, relative humidity, precipitation, pressure, solar radiation, snow depth, and camera images. I obtained hourly and 5-minute archived meteorological data for two sites near Caledonia, NY where a 180 MW solar farm has been proposed.

The Winter 2017-2018 load peak occurred during an intense cold snap. From December 29 to January 8 the temperature did not get above freezing and there were four days with below freezing temperatures as shown in the table of Daily temperature and load statistics. Note that the highest load did not occur on the coldest day. This was because the coldest day was a Saturday when business loads are lower. Also note that the New Year’s holiday occurred during this period which also reduced the load. The graph of load, temperature and wind speed for winter peak 2017-2018 shows how hourly load varies with temperature over the 15 day peak period.

In order to estimate how much renewable energy would be available during these conditions I converted to solar insolation and wind speed into power generated in MW using example utility-scale facilities. For solar power I used the 180 MW Horseshoe Solar Farm estimated output because it is near the NYS mesonet stations. In my analysis of Solar Issues in Upstate New York using that facility I assumed that 180 MW of power would be generated when the solar insolation equaled 600 watts per square meter and power output the rest of the time would be proportional so observed solar insolation. I believe that is a conservative assumption but would welcome comment.

There aren’t any wind farms nearby. So I estimated power output for a 100 MW wind farm. I found a reference that stated “Wind turbines start operating at wind speeds of 4 to 5 metres per second and reach maximum power output at around 15 metres/second”. I assumed that below 9 mi/hr wind output was zero and that power output was proportional to the wind speed difference between 9 mi/hr and 33 mi/hr consistent with that reference. The NYS mesonet measures wind at 10m and I assumed that the wind farm hub height was 90m. I modified observe wind speed using the wind profile power law with a coefficient of 1/7 to account for the relationship between wind speed and height.

I used Field Assessment of Cold Climate Air Source Heat Pumps Figure 2 (ASHP Supplemental Energy Use) to estimate the amount of power needed when an individual home convert to an air source heat pump and uses radiant electric heat when the heat pump becomes ineffective (assumed to be 15 deg F). I crudely digitized the lines in Figure 2 and calculated the best fit lines for ASHP Consumption and Furnace Backup Consumption. I converted the energy use to electrical energy by converting Btu to watts by dividing the Btu energy use by 3.41. The Energy Use for Residential Home Heating Electrification Table Table illustrates my concern that residential home heating conversion to air source heat pumps has the unintended consequence that when it gets below 15 deg F and consumers really need to heat their homes that the rate of energy use increases over six times per five degree drop in temperature.

Case Study

The purpose of this analysis is to determine if there are problems if the 100% renewable solar and wind target is coupled with widespread implementation of residential home heating with air source heat pumps. The Housing Units by Space Heating Fuel Table lists the number of occupied housing units for two counties near Caledonia. The Field Assessment of Cold Climate Air Source Heat Pumps report states that liquefied propane (LP gas) and fuel oil or kerosene space heating are the most likely sectors to convert to heat pumps because of fuel cost savings. There are 18,244 housing units that burn those two fuels. I calculated the electricity required for 10%, 15% and 25% conversions for 18,244 housing units.

The figure entitled Residential Home Heating ASHP Conversion and Renewable Power Case Study shows the relationship between home heat electrical load and meteorological conditions affecting renewable wind and solar power. Colder days in Upstate New York often occur on clear, windless nights. When the sun rises the temperature increases quickly. Although cloudless skies maximize solar power the sun is low in the sky and the days are short so the power output is low. Of course the cold weather increases the need for home heating energy.

The Cumulative Renewable Charging and Discharging Margins graph attempts to estimate energy storage requirements. Clearly the only way that solar and wind can be expected to cover winter peak loads is by incorporating energy storage. During this windless case study energy storage needs to discharge to cover the residential home heating power requirement as shown in blue. During the day solar power recharges the energy storage as shown in red. In this case study the maximum storage needed was 372 MW-hr on hour 82. It turns out that renewable excess power charged to the system before this case study was sufficient to cover that requirement.


This case study illustrates my concern that wide-spread implementation of air source heat pumps coupled with increased use of renewables will be difficult. In this analysis the meteorological conditions on New Year’s Eve 2018 show that the proposed Horseshoe solar facility with a nameplate capacity of 180 MW and a wind farm with a nameplate capacity of 100 MW would have been just able to cover the conversion of 2,737 homes to air source heat pumps. However, energy storage capable of at least 372 MW-hr has to be available somewhere. There already are 47,000 homes using electricity and another 15,000 homes that are supposed to be cost-effective candidates for conversion just in two local counties. Most importantly, this is just one component of residential electricity load which is one component of total load.

The Horseshoe Solar Farm – Public Involvement Program claims that the facility will provide enough electricity to meet the average annual consumption of 33,000 or 50,000 households, based on average annual household electric consumption of 10.8 MWh for the U.S. and 7.2 MWh for New York State, respectively. I bet that these household electric consumption averages do not reflect an electrically heated home in cold regions. If I guess that the average consumption for this 15 day period is a decent number for the heating season and assume a 90 day heating season that more than doubles the electric consumption for a New York State household. In other words there is no way Horseshoe Solar Farm is going to provide enough electricity for 50,000 homes using air source heat pumps.

Even though this is a crude “back of the envelope” analysis, the sobering results suggest that the Legislature should do a complete winter peak analysis correctly before codifying reductions that eliminate fossil fueled power plants and require the conversion of residential home heating to meet some arbitrary CO2 reduction goal. According to Patterns and Trends – New York State Energy Profiles: 2002-2016 there are over a million homes currently using fuel oil or kerosene, 500,000 homes using electricity and another 200,000 using propane in New York State.

Based on my analysis I think that even moderate air source heat pump deployment for the residential home heating sector in New York coupled with the simultaneous goal to eliminate greenhouse gas emissions using extensive deployment of wind and solar power is fatally flawed.  I cannot imagine how much wind power, solar power and energy storage would have to be deployed to cover the winter peak, much less the winter peak adding significant electrification of residential home heating, for the entire state because those renewable resources are very weak during winter peak load periods. It is incumbent upon the advocates for the Climate and Community Protection Act to determine what renewable resources will be required and how much they will cost before their legislation is considered by the Legislature.


Five Reasons Why the Catastrophic Anthropogenic Global Warming Story is Wrong

Scott Adams (of Dilbert comic fame) recently did a video about climate persuasion titled “Scott Adams solves the climate debate and saves the world (really)”, available here on periscope or here on twitter that has sparked folks to distill their arguments for and against climate change. After hearing about this and faced with the constant barrage of media stories about the latest inevitable climate doom story I thought it would be appropriate for me summarize five reasons why I think that the political agenda to transform the energy system of the world is not supported well enough by sufficient scientific evidence to proceed.

The majority of the claims that anthropogenic carbon dioxide emissions are the cause of the observed warming and that we only have a short time to do something or else are based on projections from global climate models (GCM). As noted below I do have relevant experience, education and background to inform my opinion. However, I believe that anyone who does research based on their personal experience, background and education can reach their own informed opinion of these claims if they actively try to get both sides of the story.

First a bit of background of these models. If you want details, Dr. Judith Curry did a detailed overview that includes a summary description. For my purposes all you need to know is that these models are a variation upon the meteorological models that provide predictions that everyone uses when you make decisions based on weather forecasts. There are differences but they use the same physical relationships such as momentum, conservation of heat and conservation of mass.

I have M. S. and a B. S. degrees in meteorology and in my fourth semester of Weather Analysis & Forecasting the laboratory assignment was to break off into teams and write a simple weather forecast model. I have been inside this kind of model but most readers also have some mathematical background that is relevant. In particular you may remember in algebra that if you have three equations you can solve for three unknowns but if you only have two equations you cannot solve them. The problem in meteorological models is that you have more unknowns than you have equations so model developers have to improvise. In particular, instead of using direct relationships for every single factor that affects weather or climate forecasts, meteorologists use parameters to simulate the effects of some atmospheric processes.

The first reason that I am skeptical of any GCM results is the use of parameters which can be thought of as “fudge factors’.   Model developers necessarily have to account for some things that cannot be modeled directly. John von Neumann allegedly summed up the problem stating that “With four parameters I can fit an elephant, and with five I can make him wiggle his trunk”[1]. In other words, he could develop a mathematical model that described an elephant simply by fudging the parameters. Everyone who makes a decision based on a weather forecast has learned that you can trust a forecast for tomorrow better than one several days away. In the 43 years since I graduated the forecasts have become more reliable for dates further in the future because weather forecasters have constant feedback and have been able to adjust the parameters in the meteorological models to improve forecasts based on observations. There is only one global climate system and forecasts made today for 100 years away cannot be checked until 100 years have passed. One insurmountable problem is that the parameters and their use in GCMs cannot be verified as correct in our lifetimes.

Another issue with the parameters is that the focus is on just one of these parameters. Richard Lindzen commented on this:

“Here is the currently popular narrative concerning this system. The climate, a complex multifactor system, can be summarized in just one variable, the globally averaged temperature change, and is primarily controlled by the 1-2% perturbation in the energy budget due to a single variable – carbon dioxide – among many variables of comparable importance.  This is an extraordinary pair of claims based on reasoning that borders on magical thinking.”

My final difficulty with parameters in GCMs is that they are used to model clouds. Dr. Curry explains that in order to solve the physical equations in a global climate the world has to be divided up into a three-dimensional grid. The equations are calculated for each grid cell and repeated to generate a forecast. My particular problem is that the grid cell size needed in order to do these calculations are on the order of 100 km horizontally, the vertical height is often 1 km and they do the calculations every 30 minutes or so. As a result, the models cannot simulate clouds. That single parametrization is a big enough driver of climate that this model component alone could dominate the GCM projections. This uncertainty is well understood in climate science by those who have worked with these models. However, the problems with parameterization is not well understood and its ramifications on the policy decisions is poorly understood by most of those who advocate eliminating fossil fuel use.

My second reason for not trusting these models is related to my experience in air pollution meteorology and work I did as a consultant to EPA evaluating the performance of air quality dispersion models. Complexity-wise those models are orders of magnitude simpler than climate models and they are simple enough to be directly verified. All air quality dispersion models are based on results from field studies that injected tracers into stack effluents, measuring the downwind concentrations in a test array under a wide array of meteorological conditions and then developing coefficients for pollution dispersion. I worked on a project where we compared the known emissions and observed ambient concentrations to model projections at power plants. The results showed that the models in use at the time adequately predicted maximum concentrations so EPA was comfortable that they were working correctly. The frightening result in my mind is that it was not uncommon for the model to predict a maximum concentration close to the maximum observed value but the meteorological conditions for the predicted maximum would be different than the meteorological conditions for the observed maximum.

Consider the differences between the GCMs and air quality models. Air quality models use parameters that are based directly on observations, incorporate known emissions, and have been extensively verified in field studies but those models could get the right answers for the wrong reasons. GCMs use parameters that are based on model developer opinions, have to estimate future emissions, and cannot be tested in the climate system. We are supposed to believe the models are getting the right answers for right reasons. I don’t think that is a reasonable assumption for modeling that is the basis for converting the entire economy away from fossil fuels.

My third reason for not accepting the commonly held belief that catastrophe is inevitable is that the projections that make that claim are only one answer in a wide range of potential outcomes. Consider for example that the Intergovernmental Panel on Climate Change (IPCC) does not give a single value for the sensitivity of atmospheric temperature to carbon dioxide. Instead they give a range of potential warming for a doubling of atmospheric concentrations of carbon dioxide of between 1.5 and 4.5 degrees C. Nic Lewis does a nice job discussion climate sensitivity here.  The GCM projections cover a wide range of potential outcomes from benign to catastrophic. Without going too deep I want to point out that the damage claims for increased carbon dioxide depend on the shape of the distribution of this sensitivity. Damage affects society when costs are greater and those estimates are strongly affected by the probability of extreme damages. The first problematic aspect of this issue is that the projections for high impacts rely on a relatively high probability of extreme impacts. Although recent research has shown that the likelihood of extreme outcomes is lower than previously thought, those results have not been incorporated into the damage estimates. If they were considered, then the costs currently claimed would be reduced.

More problematic to me than the range of possible model outcomes is the use of the worst-case representative concentration pathway as the business as usual scenario. The IPCC developed a set of four pathways to concentrations representing the range of radiative forcing (i.e. greenhouse effect) in the literature for 2100. The range of possible future atmospheric forcing levels runs from relatively low levels of carbon dioxide to the highest forcing they thought possible. The problem is that these concentrations had to be related back to emission scenarios and the worst case representative concentration pathway with a forcing of 8.5 watts per meter squared is so high that the emission scenario necessary to get that level is not credible. Many of the really scary projections that get the headlines and dominate the narrative why we need to reduce carbon dioxide emissions use RCP 8.5 as business as usual. We already know that the likelihood of that future emission scenario is extremely unlikely. When coupled with models that give a range of outcomes from benign to problematic, I can only conclude that while it is not impossible that there could a catastrophic impact the probability is so low that it should not drive policy decisions.

My fourth reason for not trusting the models that claim carbon dioxide is the primary driver of the recently observed warming is that even for the limited results we have from the models that can be compared to climatic system they don’t do well. Dr. Curry has explained that inconsistency well:

Between 1910 and 1940, the planet warmed during a climatic episode that resembles our own, down to the degree. The warming can’t be blamed on industry, she argues, because back then, most of the carbon-dioxide emissions from burning fossil fuels were small. In fact, Curry says, “almost half of the warming observed in the twentieth century came about in the first half of the century, before carbon-dioxide emissions became large.” Natural factors thus had to be the cause. None of the climate models used by scientists now working for the United Nations can explain this older trend. Nor can these models explain why the climate suddenly cooled between 1950 and 1970, giving rise to widespread warnings about the onset of a new ice age.

The final reason that I believe that the political agenda to transform the energy system of the world is not supported by sufficient evidence to be credible is the suggestion that climate change is easy to solve because renewables are a viable solution. As convinced as I am that the climate science does not support this agenda I believe the suggestion that wind and solar can solve our energy problems is even more of an exaggeration. In fact that issue is the primary driver why I blog and have written so much about New York’s climate change plans. However, don’t listen to me, listen to Bill Gates who states “The idea that we have the current tools and it’s just because these utility people are evil people and if we could just beat on them and put (solar panels) on our rooftop—that is more of a block than climate denial,” Gates said. “The ‘climate is easy to solve’ group is our biggest problem.” Another problem is that the renewable “solution” very likely has very significant environmental impacts that are generally ignored. Michael Shellenberger had a Ted talk “Why renewables can’t save the planet” that addresses this issue.

To sum up. The rationale used to justify the need to convert the energy system of the world is that carbon dioxide will cause inevitable catastrophe and we can be saved if only we implement renewable wind and solar which will be easy to do. I don’t believe the science supports inevitable catastrophe because those projections are based on global climate models. Those models use too many fudge factors that can give too many results that can never be tested, much simpler models that are based entirely on observations can give the right answer for the wrong reason and the model results to date do not adequately predict the one climate experiment we can test. Most of the catastrophic outcomes that dominate the political and media narrative depend on an emissions scenario that is not credible. I do not believe that diffuse and intermittent solar and wind can be used to replace reliable and affordable electric power much less generate enough energy to convert transportation, heating, and industrial use of fossil fuel to electricity.

[1] Attributed to von Neumann by Enrico Fermi, as quoted by Freeman Dyson in “A meeting with Enrico Fermi” in Nature 427 (22 January 2004) p. 297


Solar Energy Issues in Upstate New York

Led by Governor Andrew Cuomo, New York’s solar ambitions are a key component in his agenda for to ensure “vital progress on the climate” is continued. This is a post on one aspect of the NY-Sun program. I am a retired meteorologist who worked in the electric generation sector for over 35 years and I know that New York is not a particularly sunny place in the winter so I wanted to check out potential issues with solar variability during the peak summer and winter loads. The opinions expressed in this post reflect my personal opinion.


NY-Sun is supposed to make solar affordable for all New Yorkers. According to the NY Sun section in the NYS website Leading on Climate Change and Protecting our Environment:

  • NY-Sun is developing a sustainable, self-sufficient solar industry in the State by incentivizing New Yorkers, businesses, and communities to invest in solar energy.
  • The Governor’s $1 billion NY-Sun program has grown solar power in New York State by nearly 800% since 2011, and has reduced greenhouse gas emissions by nearly 25%.
  • The program aims to add more than 3 gigawatts of installed solar capacity in the State by 2023, enough solar energy to power 400,000 homes.

(Proof reading this before publication I was struck by these claims so I posted on them at my companion site.)

In order to evaluate the effect of solar variability on the transmission grid I needed an example facility. New York State’s permitting process for power plants of 25 megawatts or higher has extensive requirements for public involvement. Invenergy Solar Project Development LLC has started the permitting process for construction of Horseshoe Solar Farm which I will use as my example. According to the Horseshoe Solar Farm – Public Involvemen Program it will be a 180 MW Solar Electric Generating Facility Located in the Town of Caledonia, Livingston County, New York. Eventually I will address this particular project in detail later but this post only looks at potential performance during peak periods.

It is interesting to note that the New York Independent System Operator had this to say about solar photo voltaic (PV) facilities in their 2018 Load & Capacity Data report:

The actual impact of solar PV varies considerably by hour of day. The hour of the actual NYCA peak varies yearly. The forecast of solar PV-related reductions in summer peak reported in Table I-9 assumes that the NYCA peak occurs from 4 p.m. to 5 p.m. EDT in late July. The forecast of solar PV-related reductions in winter peak is zero because the sun sets before the assumed peak hour of 6 p.m. EST.

Because reliability planning necessarily focuses on peak periods I decided to look at the loads on the 2017 peak summer day (July 19, 2017) and the 2017-2018 peak winter day (January 5, 2018). The load data are available from the NYISO on hourly or 5-minute intervals. I decided to estimate the capacity from this facility during these peak periods (one week before and one week after the peak day) using the hourly data. I also wondered about the short term variations so I used the five minute data for the 72 hours around each peak day.


In order to estimate the solar generation output from this facility I used solar radiation data from two nearby NYS Mesonet meteorological systems (Rush and York). The NYS mesonet is a network of 126 weather observing sites across New York State. The official website of the Mesonet includes a tab for live data that brings up station information for the 125 operating individual sites. You can change the station by clicking on any dot on the state map. Data available include wind direction and speed, temperature at two levels, relative humidity, precipitation, pressure, solar radiation, snow depth, and camera images. I got archived solar insolation data on an hourly and 5-minute interval for two nearby sites that I used to estimate solar generation.

I calculated the electrical generation output from the 180 MW Horseshoe Solar Farm based on my internet research. I think it is a pretty good estimate but if someone reading this could confirm that or tell me what I am doing wrong I would appreciate it. The mesonet stations provide solar insolation measured in watts per meter squared. I assumed that the 180 MW of solar cells produced 180 MW when the solar insolation equals 800 watts per square meter (the PVUSA test condition) and I did not account for any other factors such as the cell temperature or any losses. So my naïve formula was simply the observed input solar insolation times 180 divided by 800.

The first question to address is how much power can we expect from a 180 MW facility in upstate New York during the peak periods? Frankly, I would expect this location to be pretty good relative to other central to western New York sites. Locations closer to Syracuse would be worse and locations due east of Lake Erie or Lake Ontario would be much worse because of lake-effect clouds. The Estimated Solar Generation from Horseshoe Solar Farm table lists the results. In the summer the results are pretty good. According to my methodology peak output could be over 200 MW when insolation is highest and the capacity factor over the entire 15-day peak period is over 23%. However, in the winter the solar generation output would be abysmal. The peak generation hour was only 103 MW and the capacity factor of the 15-day peak period would be no more than 7%.

The second question is what about the shorter term variability in solar generation output. The Genesee Load and Horseshoe Solar figure lists 5-minute load (MW) data for the Genesee Control Area Total Load (pink circles), estimated Horseshoe solar potential output using the Rush NYS Mesonet station solar radiation data (blue box) and the estimated Horseshoe solar potential output using the York NYS Mesonet station solar radiation data (red cross).

There are several issues. Note that the scales are different so for starters this solar farm makes little difference to the energy needs of the Genesee NYISO control area load.  As noted by NYISO the solar potential energy diurnal cycle does not match the load peak well because actual load peaks after solar generation peaks. The estimates of solar generation from both sites shows quite a bit of variation during the day. For example, the peak insolation at 12:55 EDT is 1,046 watts per square meter but ten minutes later it is down to 491. I estimate that will translate into a swing of over 100 MW that some facility somewhere has to cover. Also note that there are numerous periods when the estimated solar generation using Rush data differ from estimates using York data. This suggests that it was a partly cloudy day with significant variations in solar insolation. Because these are 5-minute averages the instantaneous variations are likely larger.


As I suspected these data show that the proposed NY-Sun solar buildout in Upstate New York will not end well. With respect to the abysmal capacity factor of the winter peak keep in mind that Cuomo’s Reforming the Energy Vision includes plans to convert residential home heating to electrical heating and there are activists that not only want to do that on an accelerated schedule but also are insisting that all the electrical power be produced by wind and solar energy only. Theoretically, battery storage could provide all the renewable power. However, only the energy innumerate or energy naïve could possibly think that solar energy coupled with battery storage could provide enough energy to heat all upstate residences during winter peak periods without massive overbuilding of both solar farms and battery storage simply because solar potential in the winter is so poor.

The summer short-term period data illustrate the fallacy that solar is cost-equivalent to coal or gas or whatever the claim is today. Fossil-fired facilities provide near constant energy but these data show that solar has huge variations. When considered alone, if this facility or any other solar facility gets built someone else on the grid has to provide support so that power sent to the grid is near constant. Battery energy storage can provide that service and frankly given the degree of intermittency on a day like the peak summer day would be the only solution that might work. However, any battery solution at least doubles the cost of solar. Not surprisingly it is even worse. If you dedicate a battery array to providing smooth power you cannot use the battery array for storage. The State really needs to explain how they propose to incorporate 3 gigawatts of solar.

On the other hand, if battery storage is a requirement for a solar facility these impacts are addressed. That way their wildly fluctuating output does not impact the grid and the units can be dispatched to match the observed load. Of course if that is required the price of solar at least doubles so it is unlikely that prudent and politically inconvenient approach will be adopted.