1 Year of Hazmat Headlines

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Presented at the Division of Chemical Health and Safety technical sessions at the Denver 2011 American Chemical Society Meeting

Presented at the Division of Chemical Health and Safety technical sessions at the Denver 2011 American Chemical Society Meeting

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Transcript

  • 1. Lessons from one years worth of HAZMATheadlinesRalph Stuart, CIH <secretary@dchas.org>August 30, 2011
  • 2. The Project✤ Beginning February 1, 2010, I have been using Google reader to collect newspaper headlines in English from the global press.✤ As of August 20, 2011, I have collected 2696 events that google identified as containing these key words: ✤ “hazmat” ✤ “chemical” and (“fire” or “explosion”) ✤ “laboratory” and (“fire” or “explosion” or “accident” or “injury”)✤ There is a lot of duplication of stories; I use the first one that I find on a particular event.
  • 3. Why?
  • 4. Why?✤ The purpose is to provide context to headline grabbing events such as the UCLA pyrophoric incident, Texas Tech laboratory explosion, and Yale machine shop death
  • 5. Why?✤ The purpose is to provide context to headline grabbing events such as the UCLA pyrophoric incident, Texas Tech laboratory explosion, and Yale machine shop death✤ The core question in my mind is: Can we tell if the safety performance of laboratories is different from other parts of the economy?
  • 6. Why?✤ The purpose is to provide context to headline grabbing events such as the UCLA pyrophoric incident, Texas Tech laboratory explosion, and Yale machine shop death✤ The core question in my mind is: Can we tell if the safety performance of laboratories is different from other parts of the economy?✤ The intent is not statistical (because of the many filters between an event and the press as well as between the press and the readers), but rather to identify stories with learning opportunities, as well as keeping the CH&S community abreast of events and trends of interest.
  • 7. Why?✤ The purpose is to provide context to headline grabbing events such as the UCLA pyrophoric incident, Texas Tech laboratory explosion, and Yale machine shop death✤ The core question in my mind is: Can we tell if the safety performance of laboratories is different from other parts of the economy?✤ The intent is not statistical (because of the many filters between an event and the press as well as between the press and the readers), but rather to identify stories with learning opportunities, as well as keeping the CH&S community abreast of events and trends of interest.✤ However, some numbers provide helpful context for an individual report.
  • 8. How?✤ The Google Newsreader service identifies news stories on the web that contain specific keywords✤ Pinboard is a web site bookmarking service that allows you to tag the a web site of interest with keywords for future review and sorting✤ I review the stories and classify them based on: ✤ Location ✤ Economic sector (industrial, transportation, public, lab, other) ✤ Type of event (explosion, fire, release, discovery) ✤ Extent of damage (response, injury, death, follow-up) ✤ Primary Chemical Involved✤ I exclude “white powder” and fuel releases during normal traffic accidents.
  • 9. A Google Reader Page
  • 10. The News Story Page
  • 11. The Pinboard submission
  • 12. The Electronic Advantage✤ Dr. Rob Toreki, president of ilpi.com, inspired by human-based inconsistencies in the reports, offered to automate the process starting in about June of 2010. The refinement of this intelligence engine is ongoing.✤ This was done with custom javascript programming and organizing the digests for DCHAS-L via a cron job.✤ Consistent data entry is the core advantage - suggested tags are easier to generate and avoid misspelling✤ Much easier identification of location of the event✤ Learning as time goes by gets encoded into the system✤ It takes about 15 minutes per day for someone with both hazmat and computer experience
  • 13. The Results:How often do events occur?Month Events/day2/28/10 3.73/31/10 3.44/30/10 2.35/29/10 4.56/30/10 4.37/31/10 3.78/31/10 4.49/30/10 4.910/31/10 6.311/28/10 4.512/30/10 4.61/31/11 4.92/28/11 5.93/31/11 5.34/30/11 5.2
  • 14. Results: Where are they reported? Country Percent reported United States 76% United Kingdom 6% India 4% Canada 4% Australia 3% China 1% New Zealand 1%
  • 15. Results: Where are they reported? Country Percent reported United States 76% An example of the “headlines” filter: United Kingdom 6% Of 171 Death Events: India 4% US reported 80 (46%) India reported 27 (16%) Canada 4% China reported 15 (9%) Australia 3% China 1% New Zealand 1%
  • 16. Results:What Sector was Involved? Percent of Events Sector Reports Industrial 37% Transportation 19% Home 17% Other 9% Laboratory 9% Illegal 5% Education 4%
  • 17. Results: What Happened? Type of Percent of event total Release 54% Fire 23% Explosion 16% Discovery 7%
  • 18. Results: How Bad Was It? Percent Extent reported Response 71% Injury 30% Death 9%
  • 19. Results: What Chemicals? Chemical Percent other 40% unknown_chemical 13% petroleum 7% meth_lab 6% acid 6% ammonia 4% solvent 3% ag_chemicals 3% wastes 3% chlorine 3% explosives 3% pool_chemicals 2%
  • 20. Some Lessons I Draw
  • 21. Some Lessons I Draw✤ HAZMAT happens - we should learn from it.
  • 22. Some Lessons I Draw✤ HAZMAT happens - we should learn from it.✤ There’s a reason for the regulations.
  • 23. Some Lessons I Draw✤ HAZMAT happens - we should learn from it.✤ There’s a reason for the regulations.✤ A big event can develop from a small risk.
  • 24. Some Lessons I Draw✤ HAZMAT happens - we should learn from it.✤ There’s a reason for the regulations.✤ A big event can develop from a small risk.✤ Information moves in odd ways.
  • 25. Some Lessons I Draw✤ HAZMAT happens - we should learn from it.✤ There’s a reason for the regulations.✤ A big event can develop from a small risk.✤ Information moves in odd ways.✤ People learn from stories; DCHAS-L follow up discussion is unpredictable
  • 26. Some Lessons I Draw✤ HAZMAT happens - we should learn from it.✤ There’s a reason for the regulations.✤ A big event can develop from a small risk.✤ Information moves in odd ways.✤ People learn from stories; DCHAS-L follow up discussion is unpredictable✤ The press isn’t great, but isn’t bad, with chemical names; it’s worse with follow up.
  • 27. Some Lessons I Draw✤ HAZMAT happens - we should learn from it.✤ There’s a reason for the regulations.✤ A big event can develop from a small risk.✤ Information moves in odd ways.✤ People learn from stories; DCHAS-L follow up discussion is unpredictable✤ The press isn’t great, but isn’t bad, with chemical names; it’s worse with follow up.✤ No trends are evident over the year, but copy catting happens (meth labs, bottle bombs or suicides) - whether this is individuals copying each other or the press copying itself is not clear.
  • 28. Moving Forward✤ Managing free-form chemical information electronically presents interesting opportunities in helping laboratory workers conduct risk reviews✤ You can use the data yourself at http://www.pinboard.in/u:dchas✤ Or contact me for an Excel spreadsheet with the information in it.