Regulating “Particulate Matter”: The EPA Doesn’t Even Believe Its Own Bogus Numbers


People who have watched environmental policy debates soon learn that the alarmist interventionists—the ones claiming that the government needs to act quickly in order to prevent catastrophe—are not afraid to throw around terrifying statistics that are absurd on their face. In a different forum, I walked through this phenomenon when it came to proposed regulations of mercury emissions from power plants. Susan Dudley, of George Washington University’s Regulatory Studies Center, recently published a scathing critique of the EPA’s Final Rule on ambient air quality standards for particulate matter. As Dudley points out, the EPA’s numbers are patently absurd, and not even the EPA is following its own logic seriously. This episode is just another example of wildly inflated statistics being used to justify a desired policy move.

A Return That Would Make Warren Buffett Blush

Dudley first provides the context for her analysis:

On January 14th, the Environmental Protection Agency published a final rule in the Federal Register updating the National Ambient Air Quality Standards (NAAQS) for particulate matter (PM).  The rule reduces allowable annual concentrations of fine particles (PM2.5) by 20 percent, from 15.0 μg/m3 (last set in 2006) to 12.0 μg/m3. According to EPA, meeting the standard “will provide health benefits worth an estimated $4 billion to $9.1 billion per year in 2020—a return of $12 to $171 for every dollar invested in pollution reduction.

Let’s be sure to parse these statements. The EPA regulates the acceptable concentration of “PM2.5,” which stands for “particulate matter” (very fine particles floating in the air) that have a diameter of no more than 2.5 micrometers, i.e. 0.25 percent of one millimeter in diameter. (These aren’t softballs we’re talking about here.)  Currently, the EPA standard (in force since 2006) sets a maximum concentration of these particles in the air at 15 micrograms per cubic meter. To get a rough sense of what that means, if we took the particulate matter to be table salt, and the air volume to be Olympic-sized swimming pools, then the current rule imposes a maximum concentration of a “pinch” of table salt dropped in six pools.

Yet the EPA wants to tighten the regulations by 20 percent, from 15 micrograms down to 12 micrograms. In order for certain regions of the country to comply with these tighter standards, costly changes must be made to the way industry operates. Yet don’t worry, because EPA’s analysis suggests that the benefits to human health (from the reduction in concentration of tiny particulate matter in the air) will vastly outweigh the regulatory costs. As Dudley quotes, the EPA states that its tighter rule “will provide health benefits worth an estimated $4 billion to $9.1 billion per year in 2020—a return of $12 to $171 for every dollar invested in pollution reduction.”

Working backwards, EPA is here saying that the compliance costs of the new regulations will range somewhere between $53 million and $333 million. Then, if the estimated health benefits range between $4 billion and $9.1 billion, the health benefits per dollar of compliance costs will be at least $12 ($4 billion divided by $333 million), and at most $171 ($9.1 billion divided by $53 million).

The implied rates of return are astounding. In the worst-case scenario, EPA is claiming the public will take a dollar of anti-pollution spending and get back $12 in health benefits, while in the best-case scenario each dollar spent on reducing particulate matter will yield $171 in benefits. If the actual numbers are anywhere close to this, one wonders why it takes the EPA to force such an outcome on the economy. Why doesn’t the government simply pay the relevant industries (say) $1 million to change their emission practices, in order to save (say) $2 million in Medicare payments? This wouldn’t require any extra tax dollars; indeed it would save the government money, assuming the EPA’s numbers were true.

Indeed, if these wild numbers are even remotely correct, it shouldn’t take the government to do anything except publicize this research, and then private health and life insurance companies would have an incentive to pay industry to revamp their operations. It’s true, there would be all sorts of “leakage” of the benefits from these expenditures, but with a payoff of $12 to $171 in health benefits (sometimes in the form of an “premature death avoided”) to each dollar spent on emission controls, there’s a big margin for error.

Why Stop There?

After documenting the EPA’s incredible estimates for the potency of the proposed rule, Dudley takes their own logic to its full conclusion:

According to EPA’s final Regulatory Impact Analysis, meeting the 12.0 μg/m3 standard will avoid between 460 and 1,000 premature deaths per year.  However, the analysis also indicates that further tightening—going from a standard of 12 μg/m3 to 11 μg/m3—would yield additional life savings of 1,040 to 2,300 mortalities per year. Furthermore, the incremental life-savings EPA estimates from reducing the standard from 12μg/m3 to 11μg/m3 are significantly larger than the life-saving increment it estimates for a reduction from 13μg/m3 to 12μg/m3. Particularly given EPA’s statutory mandate, it is puzzling that the Administrator chose to set a standard that leaves so many lives unprotected.

Dudley goes on to suggest that one explanation for this “puzzle” is that the EPA doesn’t actually believe these numbers, either.

The Fuzziness in the Estimated Dangers of “Particulate Matter”

One of the major problems that vitiates the EPA’s entire analysis is that the estimates of the public health dangers of particulate matter are quite dubious. In her analysis of the impact of a different EPA regulatory rule, Anne Smith explained (pp. 6-7):

[R]eaders unfamiliar with the literature on PM2.5 health risks should be aware that the estimates of PM2.5-attributed deaths…are based entirely on statistical associations between total mortality rates in various locations of the US and their respective monitored, region-wide ambient PM2.5 concentrations…EPA’s estimate of 6,800 to 17,000 PM2.5-related premature deaths avoided in 2016 as a result of the Proposed [Utility MACT] Rule is based on an assumption that 130,000 to 320,000 deaths, respectively, of 2005’s US deaths were hastened by breathing ambient PM2.5. And yet, EPA identifies not a single death during 2005 that was attributed, even in part, to exposure to ambient PM2.5.  If PM2.5 is indeed having this estimated effect on the public health, there is no evidence indicating when or where these events occurred, or who was affected.  Rather, these mortality estimates are merely inferences drawn after making a host of assumptions about how to convert a statistical association into a concentration-response function.  No one really even knows what types of deaths might be implicated.  A common belief among researchers is that the deaths are primarily cardiovascular in nature, but this is far from an established fact:  everything from cardiovascular causes to diabetes to lung cancer has been mentioned as having such an association in one paper or another. There is no clinical evidence to inform these inferences either, despite at least 15 years of efforts by researchers to find a clear physiological mechanism to explain and lend credibility to these estimates based solely on statistical correlations. [Bold added.]

Conclusion

When we delve into the specifics of EPA’s estimates of the cost/benefit ratio of its rules, the results are so absurd that even EPA doesn’t logically act upon them. Indeed, if the policymakers involved actually thought these numbers were defensible, it wouldn’t take government coercion to obtain immediate action. They could simply explain the medical facts to various insurance companies, who would stand to save millions of dollars by subsidizing the necessary compliance measures. Yet I imagine such a suggestion would be laughed out of court, showing that these estimates are quite dubious and wouldn’t stand up in front of people who had a choice in spending the money.

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