Do Small Releases Warn of Serious Chemical Accidents? Testing Emission Events as a Leading Indicator at Texas Plants

Process safety standards treat small releases as leading indicators of serious accidents, but the link has rarely been tested with records kept outside the companies themselves. Texas publishes every report of an emission event, an unauthorized release of air pollution above a reportable quantity that a plant must report within 24 hours, and the U.S. Environmental Protection Agency's Risk Management Program (RMP) records serious chemical accidents at covered plants. We collected all 103,614 Texas event reports filed from 2003 to 2026, linked those from RMP plants to the same plants' accident records, and asked, in a preregistered test, whether a plant's unplanned emission events become more frequent in the three months before a serious accident, stopping one week before it. We found no sign that they do. Across 545 accidents at 216 plants from 2003 to 2021, comparing each accident day with the same plant's other days in the same year, the registered estimate was 0.88 times the accident risk per doubling of recent events (95% confidence interval 0.75 to 1.02). After seeing the registered result, we found that it is biased downward. An accident generates its own event reports, 22 times the plant's usual daily rate on the accident day, and those reports fall into the look-back counts of the comparison days that follow. Removing each plant's reports from the accident day and the two days after gives 1.05 (0.85 to 1.29). Rises larger than about 30% per doubling are therefore unlikely, though smaller ones cannot be excluded. In a simulation, the bias hid a real 30% rise and the correction recovered it. Serious incidents reported to the National Response Center, OSHA injury records, events that release the plant's own regulated chemicals, and satellite heat detections at the plant also show no clear rise. Over longer spans there are hints of a link. Across a plant's whole history, periods with more events have modestly more accidents (1.24 per doubling, an exploratory estimate), and between plants, more events in one year go with slightly more accidents the next (1.12, 0.99 to 1.26), although events add little to prediction beyond a plant's size and its past accidents. One exploratory lead, found after the main results were seen, is that accidents were about 1.6 times as likely in the week after a plant reported planned work, mainly startups and shutdowns. A first further test was inconclusive. The registered plan, the code and the derived data are public.