Roger Caiazza
The New York Draft State Energy Plan prepared by the New York State Energy Research & Development Authority (NYSERDA) is currently out for comments. There is absolutely no indication the New York State is treating the stakeholder comment period as anything but an obligation so I had no plans to invest time and effort developing technical comments that would be ignored. Then I read the Health Impacts Analysis chapter. It is so bad that I had to document this embarrassing scientific travesty for the record.
Alberto Brandolini has stated that: “The amount of energy necessary to refute BS is an order of magnitude bigger than to produce it.” To fully document the problems would require an overly large post so this will reference articles at my blog addressing the different components. Nonetheless I show that the NYSERDA analysis chose its health impact goals and then contrived an analysis to support those claims.
Health Benefits Claims
In a recent article Doreen M. Harris who serves as President and CEO of the New York State Energy Research and Development Authority and Chair of the New York State Energy Planning Board summarized the health benefit message in the Draft Energy Plan. She said: “Additional analysis shows that continued implementation of the State’s energy policies would provide substantial public health benefits throughout the State in all communities, with the greatest benefits realized in disadvantaged community areas.” She made some specific claims: “This includes reduced emissions and cleaner air resulting in avoided hospitalizations, work loss days and emergency room visits due to asthma.”
The relationship between inhalable particulate matter and emergency room visits due to asthma is frequently cited as proof of air quality impacts. In my analysis I only looked at those parameters because of the frequent references and because I found historical data for both parameters.
Before continuing I should note that asthma health impact claims related to air quality is a shaky proposition from the get-go. I used Perplexity AI to generate a summary of the confounding factors affecting asthma related emergency room visits. There are environmental, socio-economic, healthcare access, clinical, comorbidity, behavioral, clinical management and psychosocial confounder factors affecting asthma. Claiming that any one of the factors affecting emergency room visits is agenda-driven science.
Health Impact Relationship
Correlation does not indicate causation. Claiming causation when then is no correlation is tone-deaf agenda driven science. I posted an article that documents there is no relationship.
I compared data from two sources. The New York State Department of Health has developed the New York State Asthma Dashboard that includes asthma emergency department visits data. The New York State Department of Environmental Conservation (DEC) operates an ambient air quality monitoring system across the state and prepares annual reports. The Methodology Appendix in the Health Impact Analysis chapter of the Draft Energy Plan compares the observed inhalable particulate matter (PM2.5) with their model predictions to validate their approach as shown in Table A-3 below. That analysis used data from 19 monitoring sites. I used the same sites except for the near-road monitor because they are not intended to capture average ambient concentrations.
Source: Draft Energy Plan Health Impacts Analysis
In my article on this relationship, I provided plots of the observed data for county-level pollution and emergency room visits. I did not think there would be an obvious relationship, but I was surprised that it was so bad. Only two of the sixteen comparisons suggested that there was a relationship that indicated that inhalable particulate concentrations influenced asthma emergency department visits.
Air Quality Analysis
I have a long and wide-ranging background in air quality modeling. When I read that the health analysis estimated benefits from reduced exposure to inhalable particulate matter concentrations at the community scale, I was taken aback because of the level of effort required. Estimating the impacts of all the sources of air pollution down to the level of 4,911 census tracts in New York State is challenging simply due to numbers. The second challenge is that they considered five pollutants and the Appendix notes that both primary and secondary pollutants were considered. Inhalable particulates (PM2.5) can be emitted directly but most of the observed particles are secondary pollutants formed in chemical reactions from NOx, SO2, VOCs, and NH3. The chemical reactions that create secondary pollutants vary by season, meteorological conditions, and distance/time from the emitting source. When modeling local impacts, it is sufficient to only consider straight line impacts determined by hourly wind directions. However, secondary upwind pollutant reactions occur over multiple hours necessitating more sophisticated transport patterns to track pollution transport.
The solution to this policy impact challenge is to use a simplified average impact analysis. EPA’s CO–Benefits Risk Assessment (COBRA) screening model fits the bill. COBRA uses the well-established and proven Climatological Regional Dispersion Model (CRDM) that categorizes parameters affecting pollutant dispersion and transport. This approach is best suited for local impacts of primary pollutants. When used for secondary pollutants it is less appropriate because there are more factors involved.
The Draft Energy Plan needed an analysis that addressed disadvantaged communities at a finer resolution than COBRA provides. This analysis was conducted using a newly developed air quality and health impacts modeling framework—the NY Community-Scale Health and Air Pollution Policy Analysis (NY-CHAPPA) model. My problem with the NY-CHAPPA model is that it over-simplifies the air quality analysis. The most important air pollution impact parameter is wind direction, because impacts only occur if the wind is blowing from the source to the receptor of concern. CRDM uses 16 wind categories, but NY-CHAPPA only uses four. Given all the sources in the analysis I think using only four wind directions is unacceptable. This gives results that are just too crude to be representative of the actual relationship between sources and receptors.
Given that this is a new modeling approach, I believe it is incumbent upon NYSERDA to verify that their new model is valid. The Appendix to the Health Impact Analysis chapter purports to validate the model for this reason. An air quality model verification analysis uses historical meteorology and emissions input to predict air quality concentrations and compares those results with observed concentrations over the same time period. The process is not complicated. It is necessary to compare model results against observed concentrations. Obviously, the observations need to be for the same time period as the predictions. The NYSERDA analysis does not do that. On page A-13 the draft states: “Because model projections were only available starting with year 2025, these results were compared against multiple years of observational data”.
When I first read that statement, I did a double take and read it again. I could not believe it. It is inconceivable that anyone could claim to evaluate model performance by comparing observed historical concentrations against future predicted concentrations. It is just plain wrong. The verification statistics presented are worthless. The biggest problem describing this situation is finding the right terms to describe the enormity of the error without using profanity.
Context
There is no question that reducing air pollutant emissions will provide health benefits, but the relationship is complex, and in my opinion usually exaggerated. NYSERDA’s claimed public health effects are listed in Table 2 of the Health Impacts Analysis chapter. I addressed whether the avoided emergency room visits due to asthma benefits which range from 1,100 to 3,600 fewer cases per year are meaningful relative to historical rates.
Source: Draft Energy Plan Health Effects Chapter
I compared the emergency room visits due to asthma health effect relative to observed data from the .New York State Asthma Dashboard. Table 1 lists the annual asthma emergency room visits for different age groups. All my analyses used the total asthma emergency department visits. Of particular interest note that the Covid Pandemic changed the identification of asthma. In my opinion, limiting the comparison data from 2009 to 2019 would be more representative of an actual relationship.
Table 1: NYSDOH New York State Asthma Dashboard Asthma Emergency Department Visits
Emergency room asthma reporting changed in 2020 due to Covid. Because this changed the reporting metric, I ran the statistics for the data available from 2009 to 2019. Table 2 lists simple statistics describing the data for that period. The range of emergency room visits over all 10 years of data before Covid is 47,636. The maximum number of avoided emergency room visits is 24% of the standard deviation and 7.6% of the range of observed emergency room visits. The predicted improvement is a small fraction of the observed emergency room visit variation.
Table 2: NYSDOH Asthma Dashboard Asthma Emergency Department Visits Statistics 2009-2019
In my analysis of the context of the predictions I also looked at the inhalable particulate variations. The average predicted concentration reduction for all three modeling scenarios is less than the range of observed annual concentrations. This means that the predicted reductions are within the range of inter-annual variation and that, contrary to the messaging, this suggests that the results will not be observable.
Discussion
My recent posts address shortcomings of the NYSERDA analysis of health benefits of the net-zero transition analyzed in the Draft State Energy Plan. I believe that the air quality analysis used to predict health impacts was overly simplified. NYSERDA used a new procedure to estimate health impacts that needs to be validated but the alleged verification process was fatally flawed. One of the key health concerns is the effect of inhalable particulates on asthma related emergency room visits but there is no observed relationship between annual average PM2.5 and emergency room visits related to asthma for the New York State monitoring stations used in the NYSERDA analysis. I also showed that the predicted impacts on emergency room visits, and inhalable particulate air quality reductions are within the range of observed variations.
Conclusion
My comments should precipitate, at a minimum, a revision to NY-CHAPPA to include 16 wind directions and a valid verification analysis of the modeling. I don’t expect NYSERDA to respond. Instead, I expect that my comments will be ignored like all my previous submittals. It is clear to me that NYSERDA established the public relation slogans for the goals of the program and then perverted the science to get answers to support those claims. When I described this to one of my friends, he remarked that this proof that science and NYSERDA cannot be used in the same sentence.
Roger Caiazza blogs on New York energy and environmental issues at Pragmatic Environmentalist of New York. This represents his opinion and not the opinion of any of his previous employers or any other company with which he has been associated.
One question that should be resolved is the identity of the clown directing the New York energy plan that will work when pigs fly in the post illustration. It could be Governor Cuomo who signed the legislation, Governor Hochul who continues to push it, Doreen Harris who leads the agency implementing it, or even Dr Robert Howarth who claimed to author the Climate Act legislation. Or it could be all four – They are the four clowns of the apocalypse to come.
Thank you for this analysis, and please keep up the good work. It is frustrating to see NY pushing previously useful agencies to make such absurd claims.
That’s an imaginary composite clown (all of them).
THey’re clearly now promoting dumb sh– to protect careers that have become expendable for a few more years. I’d like to give them a pass, but if I say “sure, go hide in an office surfing Instagram for a few more years then retire quietly”, what happens next? A whole new generation of unproductive nonsense, which seems to be the state of US democracy circa 2023.
US democracy circa 2023.
Change that to US governance circa 2000.
Perhaps instead of this article’s title being, ‘New York Draft Energy Plan’, it should be, ‘New York Daft Energy Plan’.
Or to get right to the point, “New York’s plan to ensure a lack of energy.”
A gold standard study is one of the best example of bad attribution analysis.
Premature mortality due to increase in ground level ozone in 96 us cities – Bell McDermott. A textbook example of what proports to be the gold standard yet exemplifies the problems in medical attribution studies. Quite a few flaws.
Similar problems with the 2.5pm studies, As the air gets incrementally cleaner, the health risks increase – go figure.
When researching comments I found that the new story is that it is the number of pariculates not the mass that causes the alleged problems.
Oh brother. They just keep moving the goalposts and singing the same tired tune.
They’ll “save us” from nothing – whether we like it or not and regardless of the cost or consequences.
I believe that my ancestors survived much higher PM2.5 exposure than under discussion.
I also believe that the calculations done using linear no-threshold extrapolation models are dubious at best, and used to support political agendas, not human betterment.
Imaginary asthmatics. Where are the real health effects? Where are the real dead?
I think it can be argued that the real dead are those in third world who are still relying on bio-mass open fires for subsistence because the clowns don’t want them to use fossil fuels.
An issue is that one part of the Feds, the NIH if I recall correctly, states asthma has an unknown cause. The EPA, on the other hand, writes regulations as if particulates are a well established cause.
Rather like being liable for following bad advice one received from an IRS employee.
Tom H – As I noted above, Attribution studies are notoriously weak (flawed possibly), yet are treated as being highly reliable.
I read about a study a number of years back, where the researchers have identical tax scenarios to a dozen IRS tax agents. They got back a dozen different answers regarding the taxes owed.
At one time there used to be a legal principal that if a law was so vague that even the experts couldn’t figure out what it meant, the law was unconstitutional.
What if that principal were to be applied to the US tax code?
Mark – I am a CPA with a specialization in taxation. during the 1980’s Forbes used to run an annual article where they had given the sample return to 10 or so CPA’s. The sample return had numerous unusual facts, that invariably, there would items the experienced CPA’s would miss. It never was a simple return.
I dont recall a sample return given to IRS agents. That being said, very few IRS agents have any in depth understanding of tax law. Its actually quite rare that I dont have to explain very basic tax law to an IRS agent.
Probably 10x worse with the army of additional IRS agents hired under Biden, whose primary “qualifications” likely had nothing to do with being able to do the job.
Virtually all of the health effects studies cited by EPA are exercises in confirmation bias. That’s especially true of the infamous Harvard 6 Cities study that justified particulate regulations. It was apparently so bad that EPA went to great lengths to prevent any outside scrutiny of the raw data and analysis methods. They even tried to cover for the lack of valid studies by conducting their own highly unethical study exposing vulnerable human subjects directly to diesel truck exhaust in closed rooms. These studies apparently didn’t result in triggering bouts of asthma.
One can only hope that the current administration will dig deep and expose the past fraudulent scientific abuse by EPA and other agencies used to justify their persecution of American businesses.
Re – the harvard study – See my comment on the premature mortality with increase in ground level ozone in 96 US cities, by Bell McDermott. Similar issues with any attribution study. Though not nearly as bad as the 12% of asthma cases caused by gas stove study. That one was pure academic fraud.
Re – the harvard study – See my comment on the premature mortality with increase in ground level ozone in 96 US cities, by Bell McDermott. Similar issues with any attribution study. Though not nearly as bad as the 12% of asthma cases caused by gas stove study. That one was pure academic fraud.
It sounds very much like the social justice nonsense peddled by the Mayor of London.
I can’t speak to New York, though I’d be surprised if things were greatly different, but in London the proclaimed benefit of expanding ULEZ is bogus. It does make revenue, but the claims are a distraction from the very real problem the Mayor refuses (ie it costs money) to address.
What’s the point of “cleaning air” (allegedly) at the surface when you are actively encouraging people to use the heavily polluted tube system? And almost five million people use the system every day.
“Tube dust levels treble on London Underground’s Victoria line as worst station revealed
Victoria line replaces Northern line as having the worst dust levels on the Tube” – Standard
Ventilation
The transport network is well ventilated. Tube, train, tram and bus doors opening frequently ensures a regular exchange of air across the public transport network – Transport for London
“Sadiq Khan has insisted London Underground’s air is safe despite acknowledging he has asked Transport for London to find ways to clean it up, while a scientific report shows pollution levels exceed limits set by the World Health Organization (WHO).” – My London
It’s ideological (critical theories) politics and nothing more.
I have not read yet, but I’m pre-bracing for billion-dollar decisions based on survey data taken from 30 college kids living in the same dorm building. Health studies are the worst statistics abuse – I can’t imagine what adding a climatologist would do to one.
I have not read yet, but I’m pre-bracing for billion-dollar decisions based on survey data taken from 30 college kids living in the same dorm building. Health studies are the worst statistics abuse – I can’t imagine what adding a climatologist would do to one.
“Because model projections were only available starting with year 2025, these results were compared against multiple years of observational data”.
Oh silly me – I should have guessed.
I can’t imagine what adding a climatologist would do to one -> A climatologist would add it to a model based on curve fits and hind-casting. There would be no way to verify because -all- available data was used for the curve fits and hind-casting. Duh.
A climatologist would have based all the data based on one tree. 😆🤣
A second post of your comment wastes electrons and computer memory space.
Not sure what happened. Was not intentional. I don’t have delete authority.
No worries, we’ll won’t call the Carbon Police…
Story tip:
Eco-activists rage as Tories pledge to axe ‘failed’ Climate Change Act
A wave of environmentalist organisations have slammed the Tories’ pledge to scrap the legislation.
Friends of the Earth chief executive Asad Rehman branded Ms Badenoch’s move as “desperate”.
[Thursday Funny]
“Climate change is not some theoretical threat – we can see it out of our windows”
…
Wildlife and Countryside Link chief executive Richard Benwell said reversing the Climate Change Act would represent a move of “national self-harm”.
…
Miliband vowed that the Government “will not let the Conservatives or Reform tank our country’s clean energy economy”, which the minister has described as “booming”. – GBN
The consensus is over.
Climate crisis and science should not be used in the same sentence, paragraph, or report.
I just gave you 3 up votes. There is no climate crisis because most of the climate is water, ice, snow, rocks and sand. Activities of humans aren’t going to effect the climate the vast Pacific ocean or the Sahara desert.
Activities of humans can effect local climates due to the UHI effect.
Very nice Roger, thank you for all the work you do. I have a real problem with all the lying and cheating that government agencies are allowed to get away with. Can you imagine the fallout if someone like Exxon submitted a report as shoddy as this one to the government? The CAGW clowns would be using it against them for a hundred years or more and the government would go apoplectic.
I always learn from your posts, Roger.
There is another context in which something similar is done routinely. That context is general rate cases. The utility uses historical data to help model new rates in a future test year to see how the new rate structure will perform — I.e. using a year that has not occurred to show requested rates are just and reasonable. The utility believes this reduces their risk of justified revenue losses accruing during the time period of arguing their case and the PSC granting new rates.
Critics have argued that 1) the potential for revenue loss during the decision period introduces a bit of market discipline that helps keep rates low, and 2) projecting into a future test year involves so many additional assumptions and unknowns that it greatly increases uncertainty of results.
Unquantified, or incompetently quantified uncertainty appears to me a flaw running through quite a lot of this “energy transition.”
My brief foray into rate cases has not run into this yet. I agree that certainty hubris is a common flaw.
Roger, thanks for this report. It is a lot of work, and though it seems doubtful that anyone in NYSERDA or other NY state entities will read it, let alone respond to comments, you should find eager readers here. Your posts are always appreciated.