Climate change-air quality-public health fallacy—does it make sense?

First and foremost…for PM2.5 and ozone, none of the studies we mentioned in both papers were based on the biological plausibility of these factors contributing to illness or death. They are based on the following assumptions: possible Causes of illness or death, such as PM2.5 or ozone.

PM2.5

Our first paper examines what the U.S. Environmental Protection Agency (EPA) claims are two key public health endpoints caused by PM2.5 exposure—nonfatal heart attacks and premature death. For both endpoints, we show that the health effects studies (observational epidemiological studies) cited by the EPA to support their claims do not take appropriate account of hidden bias or the reproducibility of these studies Conduct rigorous testing.

The most obvious biases to us, but hidden to most readers, are the use of questionable (poor) research practices, multiple hypothesis testing, and the irreproducibility (falseness) of research claims. Our paper also points to the large number of null studies in the academic literature showing that PM2.5 does not cause non-fatal heart attacks and premature death.

Answering the PM2.5 non-fatal heart disease/premature death claim depends on interpretation of the scientific method: if the method is flawed, then the evidence is also flawed. Research that engages in poor research practices should be considered untrustworthy unless proven otherwise. In the absence of statistical correction, studies that perform many statistical comparisons tend to produce more false-positive association errors. Finally, the PM2.5−heart attack/premature death association study failed our statistical reproducibility test using p-value plots.

The problems with the PM2.5 health effects studies that the EPA relies on are that they are non-randomized designs without effective researcher controls. They give researchers unlimited flexibility in designing, analyzing, interpreting and reporting results. Their data set is not available for independent reproducibility testing by others. These types of designs and lack of controls do not address issues of bias and confounding. It is easy to appear in these studies spurious risk statistics that resemble real effects, when in fact they are simply the product of hidden biases and confounding factors.

With no reproducible causal effects and ongoing, hidden biases and confounding factors in PM2.5 health research, any purported link between PM2.5 and public health is completely unfounded and should not be taken seriously .

ozone

Our second paper shows that ozone precursor emission data and ozone levels recorded by the EPA at U.S. air monitoring stations over the past few decades show a very different trend (decline) than predicted by climate change models into the future. For example:

• Over the 42 years from 1980 to 2022, average ozone levels at 132 monitoring sites steadily decreased by 7 ppb per decade
• According to the EPA Air Quality Index, from 2000 to 2022, the total number of days in 35 major cities with ozone reaching “sensitive subgroup unhealthy” or above has steadily decreased, with a steady decrease of 600 days per decade.

Therefore, any potential impact of climate change models on air quality and asthma should be viewed with skepticism.

The link between ozone and asthma

The EPA considers respiratory effects, including asthma, to be the primary health impact of ozone exposure. They used results from controlled human exposure studies (i.e., in-house studies) and animal toxicology studies to claim that ozone causes lung function effects. They used results from observational epidemiological studies to claim that ozone levels in outdoor air are associated with asthma attacks. They used results from observational studies and animal toxicology studies to claim that ozone causes asthma attacks. It sounds complicated, but it's not.

First – in-house research. We present a number of compelling arguments demonstrating the absence of adverse effects or differences in effectiveness between non-asthmatic and asthmatic patients exposed to ozone in controlled room studies. These include confounds from awareness bias and measurement variability, as well as a lack of external validity.

Second – observational epidemiological studies. Our findings can be succinctly summarized as follows…Same methodology as PM2.5, same flaws, no evidence.

Third – Experimental Animal Research. The U.S. Environmental Protection Agency (EPA) hypothesizes several mechanisms by which ozone exposure may cause asthma attacks or asthma attacks. Of course, experimental animals are not humans and there are many problems. Best of all, they do not spontaneously develop asthma and cannot be tested in traditional ways of diagnosing asthma or asthma symptoms.

Only through the imaginative use of smoke and mirrors, perhaps with the help of artificial intelligence, can one conclude that the evidence cited by the EPA from indoor, epidemiological, and animal studies supports asthma or asthma symptoms caused by ozone exposure accidental influence.

Questions we ask WUWT readers

We posed an open question to WUWT readers that is an important part of the problem we encounter in assessing the so-called climate change-air quality-public health nexus.

this Scientific Evidence Reference Manual is a document created for U.S. federal judges to help them understand and interpret difficult issues involving scientific testimony. third edition Reference manualis a more than 1,000-page document published in 2011 in partnership with the Federal Justice Center and the National Research Council (NRC) of the National Academies of Sciences, Engineering, and Medicine (NASEM).

NASEM is primarily composed of renowned academics. Authors who contributed to 2011 Reference Manual Among them are many such scholars. 16 chapters in total 2011 Reference Manual14 academics have been identified as lead authors or co-authors. A total of 30 authors or co-authors contributed, 22 of whom are academics.

Over the past few decades, as these “established” academics have built their careers, junk science—false (erroneous) or fraudulent scientific data, studies, or analyses—has proliferated in the peer-reviewed literature . False or fraudulent evidence from junk science has been used to advance special interests and hidden government regulatory agendas on many socially important topics—climate change, environmental pollution, health impacts, and more. Therefore they should not be considered independent.

The U.S. Supreme Court recently struck down a long-standing, controversial doctrine known as the “Chevron Doctrine,” which gave regulators like the EPA an unfair advantage in court. This decision now imposes an obligation on Congress to legislate more clearly and on courts to interpret the law without running counter to agency decisions, which, as we established above, is questionable in the case of the EPA .

Given this result, we believe it is crucial Reference manual Appropriate updates for judges (and attorneys) so they can better understand junk science and how it proliferates in academic research, government policymaking, and regulatory development.

[Our question] How best to accomplish updating the Reference Manual to address junk science, given such substantial input from entrenched academic circles in the past?

The credibility of peer-reviewed literature has changed little since John Ioannidis’s 2005 paper Why most published research results are wrongNASEM published two reports on the non-reproducibility of scientific results (one in 2016 and one in 2019), and the National Association of Scholars released a report on the non-reproducibility of scientific results in 2018.

The last thing that should be allowed when updating Reference manual It's about getting the author's composition overweight, working with renowned academics to figure out what to do with the 800-pound gorilla of junk science they helped create and/or allow to thrive on their watches.

S. Stanley Young is CEO of CGStat in Raleigh, North Carolina, and director of the National Association of Scholars quicksand project. Warren Kindzierski is a retired university professor (public health) in St. Albert, Alberta, and a contributor to Project Quicksand.

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