Tales Of Our Times
By JOHN BARTLIT
New Mexico Citizens
for Clean Air & Water
History Recalls The Wisdom In Clean Air Decisions
A common theme is: “Those who fail to learn from the past are doomed to repeat it.” The history of cleaning polluted air gave us hard-won lessons learned that can spare us from repeating them. As ever, what we don’t know or remember will again cost the continuing effort. So, this column looks back at the early years of clean air rules (the 1970s), when rules were first shaped.
Those pioneer struggles for clean air showed us much more than merely the outcomes of lawsuits. To aid their interests, varied groups rolled out a wealth of worries, a right borne in democracy. A jumbled contest of worries followed, which paid no heed to the passing of precious years. Time passed; new pollutants stayed. The EPA and citizens began to see that air pollutants had different histories — old devils and newer ones. Such differences compelled different ways of treating them.
The first chemicals controlled as air pollutants were a half dozen ugly oldies. For decades, these six had done widespread damage. The occasional extreme cases made news and added clarity. That history left a trove of court-tested data to show the amounts of each that can harm people or crops.
The six –sulfur dioxide, nitrogen dioxide, particulate matter, carbon monoxide, ozone, and lead — were officially termed “criteria” pollutants. “Criteria” hints at the precise details that were known for each one of the six.
As its next huge task, the EPA soon had to begin control of some 180 other air pollutants, termed “hazardous”. Although classed as “carcinogens”, they all lacked the hefty “criteria-level” records of risks. To produce that much new, high quality data for so many chemicals would take how many decades? Who would, or should, fund the long stretch of work — taxpayers, institutions, or industries? Time passed; pollution stayed. With so few timely answers in sight, the EPA sought something more workable, even if less than ideal. The best bet was to adopt a quicker system — a means of regulating all air toxics alike.
Yes, toxic chemicals vary widely in their risks. Yet, a system that treats them alike as a group has advantages. Risk as a whole is reduced by restrictions on the group as a whole. Such a standardized system needs much less time and money to be up, running, and boosting safety.
A similar idea works well for speed limits. Everywhere, roads have speed limits posted that take no account of the relative harm from the differing features of vehicles. Speed limits are the same for an 18-wheeler hauling logs, a horse trailer, or a motorcycle. The standardized system has indeed triggered safer roads. Similar methods for air pollutants have likewise achieved major reductions in hazardous emissions. The rough-cut system may still be the best path forward in a working democracy, where struggles to win funds tend to delay solutions to problems.
Air dispersion modeling is another vital tool in the EPA’s clean air rules. Air dispersion models are equations that apply math and science to predict how air pollutants from a known source will disperse in the atmosphere. They serve many purposes. Air Quality Bureaus use models to help decide whether projected emissions will meet legal limits, thus, whether to issue an air permit.
Modeling battles flared up early among skilled citizens, agencies, and industry. Contests stretched on for years. Time passed; pollution stayed. An efficient list of approved models solved that problem, and also makes for consistency in air permits across all states.
EPA’s approval process for models used detailed reviews and revision by an array of experts in the field. An example is the 288-page report of the American Meteorological Society entitled, “Air Quality Modeling and the Clean Air Act: Recommendations to EPA on Dispersion Modeling for Regulatory Applications (1981)”.
The fairest appraisals today include views through the lens of history. Now, as then, stakeholders of every stripe hope to make clean air rules stronger, or weaker, or different.