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

1. Lessons from one year's worth of HAZMAT
headlines
Ralph 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/day
2/28/10 3.7
3/31/10 3.4
4/30/10 2.3
5/29/10 4.5
6/30/10 4.3
7/31/10 3.7
8/31/10 4.4
9/30/10 4.9
10/31/10 6.3
11/28/10 4.5
12/30/10 4.6
1/31/11 4.9
2/28/11 5.9
3/31/11 5.3
4/30/11 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.