Scare Pollution: A Review

Steve Milloy is one persistent gentleman. Combining his legal and statistical education, he has spent most of his years ferreting out the false use of statistical techniques in the field of epidemiology. He continues the same quest in his latest book Scare Pollution: Why and How to Fix the EPA (2016) Bench Press. This is his sixth such book since Science-Based Risk Assessment: A Piece of the Superfund Puzzle (1995). Just what is epidemiology? One definition: “the science concerned with the study of the factors determining and influencing the frequency and distribution of disease, injury, and other health-related events and their causes in a defined human population for the purpose of establishing programs to prevent and control their development and spread.” Milloy notes that “The key to the value of epidemiology as an investigative tool is that a researcher must be looking for a relatively high rate of a relatively rare event in a human population… Epidemiologic results are essentially correlations and, as we all learn in Statistics 101, correlations do not equate to causation.” The “devil is in the details” aphorism comes to life as Milloy exposes the EPA’s use of any minute level of correlation as evidence of statistically significant correlation to justify its definition of Clean Air standards.

Milloy’s latest book documents his multiple attempts in multiple formats to hold the EPA to basic standards of ethical epidemiologic theory and practice. His book details the quixotic nature of that quest. An executive order by President Richard Nixon in 1970 unified federal environmental activities into a single new organization, the U.S. Environmental Protection Agency. Though the EPA was never officially organized by Congress as a presidential cabinet-level department, Nixon’s new federal bureaucracy undertook the writing and implementation of Clean Air Act (1970) laws. This unique status of the EPA as an all-powerful federal agency lacking cabinet-level status continues to the present. It has developed itself into a self-perpetuating rogue agency which defies congressional oversight attempts, as Milloy documents. From its $1 billion annual budget and 4,000 employees in 1970, the EPA expanded into a $6 billion annual budget with 16,000 employees by 1991. Milloy began working on a variety of environmental issues involving the EPA in 1990. However, his quest for truth in statistics in identifying such impacts on human health has identified one issue at the top of the pile of EPA “malfeasance” actions. That is the matter of air quality standards. Milloy: "When EPA began regulating PM in 1971, it regulated relatively large pieces of dust and soot that were anywhere from 25 to 45 millionths of a meter (one to two thousandths of an inch) in diameter. In 1987, EPA revised its rules to focus on smaller bits of dust and soot that were 10 millionths of a meter in diameter (about half the width of a human hair) -- so-called PM10 (pronounced P-M-ten). In November 1996 under Administrator Browner, EPA proposed to regulate even smaller bits of dust and soot, particles that were 2.5 millionths of a meter in width -- so-called PM2.5 (pronounced P-M-two-point-five). The EPA’s PM2.5 proposal wasn’t particularly interesting except that the agency claimed its regulation of PM2.5 would save 20,000 lives per year, or in EPA parlance, prevent 20,000 premature deaths. Who knew that outdoor air in America was killing anyone, let alone due to something called PM2.5, which is both a naturally occurring and manmade substance?” Thus, while a major effort has been undertaken by skeptical scientists (i.e. traditional fact-verifying scientists) to disprove EPA claims that fossil fuel usage and CO2 production are driving catastrophic global warming and global climate change, the agency has been toiling away in the background using air quality standard-making as the more effective destructive tool in its regulatory zeal to control our energy production and usage at all levels. What EPA claim is at the center of power for its regulatory onslaught? It is linked to September 22, 2011 when EPA administrator Lisa Jackson testified before a subcommittee of the House Energy and Commerce Committee. Administrator Jackson stated: “Particulate matter causes premature death. It doesn’t make you sick. It’s directly causal to dying sooner than you should… f we could reduce particulate matter to levels that are healthy, we would have an identical impact to finding a cure for cancer.” At the time that would have been almost one in four deaths in America. Yet there were no standardized criteria to identify such a “cause of death” at autopsy, nor a way to separate out other contributing factors. The Clean Air Act bars the EPA from considering costs when setting air quality standards. The Supreme Court has held that the EPA can only set air quality standards based on scientific determinations that provide an adequate margin of safety so as to protect the public health. With no limits on the economic costs of its air pollution remedies, the EPA had the potential to ratchet down PM standards to levels below natural background levels. A succession of presidential regimes attempted to put some rational cost limits in place. The last one standing is from September 1993, when then-president Clinton cancelled Executive Order 12291 of President Reagan and replaced it with his own Executive Order 12866, which only required that “the benefits of the intended regulation justify its costs.” Merely a passing challenge to the EPA was this issue of cost benefits of their air quality standards. As Milloy explains: “Economists have a methodology called ‘contingent valuation’ that fabricates values virtually out of the imaginations of randomly selected and surveyed people. The EPA then estimated that by reducing PM2.5, albeit indirectly, as many as 11,000 lives would be saved every year -- with every life worth $9 million or so, the EPA estimated the benefits of the rule to be worth as much as $90 billion per year. And since $90 billion in benefits is a lot more than $11 billion in costs, EPA had solved its cost-benefit problem. Never mind that the $90 billion in costs were imaginary in nature while the $11 billion costs were actual in nature.” Problem solved. Criticism by Milloy and others of the EPA’s refusal to provide the original data used to make such claims, lead to independent studies by Milloy and by James Enstrom (UCLA) of actual hospital admissions in California. When patient admissions were cross-checked with particulate matter levels, no statistical correlation was found. Smoggier air was not killing the elderly or young. The Clean Air Act only mandated healthy air; it did not mandate esthetically pleasing pristine air. Faced with mounting criticism of its air pollution claims based solely on epidemiological studies, which were merely statistical computer trolling of data of dubious quality, the EPA ventured into human subject testing. Milloy documents the use of human subjects, both young and old, in gas chamber experiments funded by the EPA at the University of North Carolina, the University of Michigan, the University of Washington, the University of Rochester, the University of Southern California, and Rutgers University. Aiming to prove its claim of “death by any level of particulate matter” in ambient air, Milloy documents that such experiments were unethical and in defiance of the Nurnberg Code. In spite of numerous articles in the press, Congressional hearings, and appeals to state boards of medicine by Milloy, none of the perpetrators have been punished. I encourage readers to read Milloy’s book and share the dismay attendant to such overt manipulation of science and the political system by an essentially rogue agency. It is a fond hope that the Trump administration will restore science to its rightful place in federal policy making, and restore our trust in the regulations imposed on us. Charles G. Battig, M.S., M.D., Heartland Institute policy expert on environment; VA-Scientists and Engineers for Energy and Environment (VA-SEEE). His website is www.climateis.com