The New York Draft State Energy Plan prepared by the New York State Energy Research & Development Authority (NYSERDA) is currently out for comments. This is one in a series of posts describing my concerns about the Health Benefits chapter that I am planning to consolidate and submit as a written comment. This post describes issues with the air quality modeling analysis used to predict health benefits.
I am convinced that implementation of the New York Climate Leadership & Community Protection Act (Climate Act) net-zero mandates will do more harm than good if the future electric system relies only on wind, solar, and energy storage because of reliability and affordability risks. The primary emphasis of my career was air pollution meteorology and air quality analysis which is the focus of my planned comments. I have followed the Climate Act since it was first proposed, submitted comments on the Climate Act implementation plan, and have written over 575 articles about New York’s net-zero transition. The opinions expressed in this article do not reflect the position of any of my previous employers or any other organization I have been associated with, these comments are mine alone.
Net-Zero Aspirations
The Climate Act established a New York “Net Zero” target (85% reduction in GHG emissions and 15% offset of emissions) by 2050 and has two electric sector targets: 70% of the electricity must come from renewable energy by 2030 and all electricity must be generated by “zero-emissions” resources by 2040.
According to the New York State Energy Plan website: “The State Energy Plan is a comprehensive roadmap to build a clean, resilient, and affordable energy system for all New Yorkers.” This is the first update of the Energy Plan since the Climate Act was passed in 2019, so it is being revised to incorporate the net-zero mandates. I have provided more background information and a list of previous articles on my Energy Plan page.
Health Benefit Chapter Comments
My first post/ draft written comment described my oral comment at the virtual Draft State Energy Plan Public Hearing on September 13, 2025. I noted that NYSERDA is using a new modeling approach to project the air quality impacts associated with Climate Act implementation that are used to determine health benefits. Although they claimed that they had verified the approach, the methodology used was invalid, thus undermining the credibility of all the health benefits claims.
The crux of the NYSERDA health benefit claim is that various health effects are exacerbated by air pollution. If that is true, then observed inhalable particulate matter (PM2.5) should correlate with observed health outcomes. In my second post I compared observations of the same metrics cited in the Health Benefits chapter. I found no observed relationship between annual average PM2.5 and emergency room visits related to asthma for the New York State monitoring stations used.
The third post compared the air quality projections and the health benefit claims in context with observed variability. I showed that the predicted impacts on emergency room visits, and inhalable particulate air quality reductions are within the range of observed variations. Contrary to the messaging, this suggests that the results will not be observable.
Air Quality Modeling Challenges
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 fine particulate matter (PM2.5) concentrations at the community scale I was taken aback because of the level of effort required. The Appendix to the Health Benefits Chapter states the analysis modeled “dispersion of primary PM2.5 and secondary PM2.5 precursor pollutants nitrogen oxides (NOx), sulfur dioxide (SO2), volatile organic compounds (VOCs), and ammonia (NH3)”. All this is needed to determine state-wide impacts on the resolution required to predict impacts to disadvantaged communities.
The first challenge is the large number of sources and receptors. All significant point sources of air pollution have Title V permits and there are 160 permitted facilities. The Appendix states: “On-road emissions from major and secondary road categories (interstates, arterials, and major collectors) were modeled as line sources.” It also notes that the modeling include “the residential, commercial, and non-road sectors, as well as non-point industrial sources.” All those sources were modeled to estimate impacts on 4,911 census tracts in New York State.
The second challenge is that there are 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. In many areas of the state, the observed PM2.5 is mostly secondary from upwind sources. 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 where the pollution transport.
Finally, it is not simple to characterize emissions for all of society as they claimed to do. It is hard enough to characterize existing emissions from power plants, factories, homes, businesses, and vehicles over time and space. In this analysis they also had to project how emissions would change during the transition away from fossil fuels for projections out to 2040.
Health Benefits Modeling Approach
My first hope was that they would try to do the air quality modeling right. I believe that would require a massive analysis simulating all the processes that affect the air quality concentrations. The analysis is even more complicated because the air quality analysis was only the first step. The goal was to predict health impacts and that required additional analysis The Introduction to the Appendix in the Health Benefits chapter explains that there are two more components in the analysis:
The basic framework of the analysis is:
- Estimate changes in air pollutant emission reductions based on changes in fuel consumption as modeled in the Pathways Analysis (see Pathways Analysis chapter).
- Analyze changes in air quality resulting from reductions in air pollutant emissions.
- Analyze changes in health effects resulting from changes in air quality.
- Calculate the monetized value of the change in health effects using standard economic values.
This analysis supports claims of Draft Energy Plan “substantial” health benefits for the transition across New York down to disadvantaged community levels. The first two components in the framework cover the air quality analysis portion that I have personally done in the past. The other two components listed represent policy support issues that are outside of my experience. It is apparent that the methodologies were dictated by the desire to prove substantial health benefits.
A key difference from the approach used for the Scoping Plan is that 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 —rather than using the Environmental Protection Agency’s (EPA’s) CO-Benefits Risk Assessment Health Impacts Screening and Mapping Tool (COBRA) to analyze health outcomes from changes in fine particulate matter (PM2.5) concentrations. In addition,
The need for impact resolution down to the census tracts required the new NY-CHAPPA model.
COBRA was used to evaluate the impact from changes in ozone concentrations at a county level (this is a new capability now available from COBRA but is limited to the county scale). The NY-CHAPPA modeling framework estimates benefits at a sub-county scale, which enables evaluation of potential health benefits by community type, allowing evaluation of health effects within geographic disadvantaged communities (DACs) as defined under the Climate Act.
EPA’s COBRA model was used to provide information not available from NY-CHAPPA.
Issues
As noted, a comprehensive air quality modeling analysis would require an enormous effort. NY-CHAPPA is a screening model like EPA’s COBRA model. Both include many simplifications to improve computational efficiency. Rather than analyze hour by hour data, COBRA’s core air quality modeling relies on the Phase II Source-Receptor (S-R) Matrix, which establishes fixed transfer coefficients representing the relationship between emission sources and air quality impacts at receptor locations. In my opinion, if the transfer coefficients are based on five years or more of historical meteorological data, then the results are generally acceptable for screening analyses like this health benefits analysis.
My problem with the NY-CHAPPA model is that it over-simplifies the air quality analysis. COBRA uses the well-established and proven Climatological Regional Dispersion Model (CRDM) that categorizes atmospheric stability, wind direction and wind speed like NY-CHAPPA.. Both models use the same number of stability and wind speed categories. 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.
My other problem is that the health impact emphasis on inhalable particulate matter and ozone amplifies the importance of secondary pollutants. The source receptor matrix approach is not well suited for this application. This simplification means the results have much uncertainty. Using them to drive the health benefits and monetized value of change components of the analysis prioritizes getting an answer over getting a defensible answer. One of my problems with the Draft Energy Plan process is that there is no provision for technical meetings to address specific topics where stakeholders could ask questions. One of the problems with a climatological approach like the one used here is interannual variation of the meteorological parameters. The Annex explains that the analysis reviewed five years of data from 29 meteorological monitoring stations:
The data from each year was analyzed to determine the interannual variability in the meteorological data, as discussed in the following section, “Meteorological Sensitivities.” Based on the results of this analysis, a single year of meteorological data (2017) was selected for use in NY-CHAPPA.
Discussion
This is the last of my topical health benefit articles. I will use these posts to prepare a written comment on the Draft Energy Plan. I have been critical of the stakeholder process because it appears that NYSERDA is treating the process as an obligation and not as an opportunity to improve the Energy Plan. This example is no different.
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. 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. This includes reduced emissions and cleaner air resulting in avoided hospitalizations, work loss days and emergency room visits due to asthma.
My written comment will show that the claim of “substantial public health benefits” is the result of an analysis that was designed to get that answer. I compared observed inhalable particulate matter emergency room visits related to asthma and found no relationship. When I compared the air quality projections and the health benefit claims relative to observed variability, I showed that the projections are within the range of observed variations suggesting no observable impact should be expected. This post describes issues with the modeling approach that can only be ignored if a validation analysis indicates that the simplifications do not affect the observed predictions. In my first post I showed that the purported verification study did not compare projections using historical inputs to observed air quality. This makes the methodology invalid, thus undermining the credibility of all the health benefits claims.
Conclusion
All the analyses in NYSERDA used in health benefits chapter of the Draft Energy Plan get a failing grade. They were designed to get a particular answer without regard to common sense science. It is incumbent upon NYSERDA to prove that their new methodology is credible. 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.
Pragmatic Environmentalist of New York 