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Man-made Environmental Disasters

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					Man-made Environmental Disasters

  Can knowledge of Probabilistic methods
            minimize them?




              CEE6430: Environmental
               Disasters (Man-Made)
                  The Relevance

• Bhopal Disaster had its 20th Anniversary
• A lot of Man-made disasters are caused by ‘errors’
• Uncertainty analyses/ Error Analysis/ Probabilistic
  Methods/Risk Management can all help to reduce the
  chance
• We’ll talk about one Man-made Environmental Disasters:
  Bhopal Disaster (India)




                     CEE6430: Environmental
                      Disasters (Man-Made)
                        Bhopal Disaster

• Gas Leak on December 3, 1984 – MIC (Methyl
  Iso Cyanate)
• 8000 people died, 50,000 injured
• Gas leaked from a Union Carbide Plant at night
                     Main effect: Pulmonary Edema, skin
                     and eye damage (total blindness)
                     Secondary effect: Bronchitis, Bronchial
                     pneumonia

People fled from the poison
                                                               A Bhopal Victim
gas in the middle of the
night
                              CEE6430: Environmental
                               Disasters (Man-Made)
                     How it Happened

• In the middle of the night. People fast asleep (many on
  the streets)
• 40 tonnes of MIC leaked from Union Carbide Plant




 The Plant

 Union Carbide still maintains
 ‘Sabotage’ as the cause:
 ‘Someone’ put water in the boiler to
                                                Source: BBC
 trigger a set of reactions
                           CEE6430: Environmental
                            Disasters (Man-Made)
                 Here’s One Story

• Bhopal station was filling with panicking passengers
  fleeing the fumes
• Station Manager Mr. Dastagir was sensing something
  wrong (note: no one yet knew what was going on)
• The next train was scheduled to depart 20 minutes later
• He ordered the train to leave immediately (early)
• Incoming trains were all diverted
• It was Catch 22 situation. Uncontaminated passengers
  incoming to Bhopal could not be put at risk.
• Yet, those in Bhopal wanted to flee the fumes boarding
  as many trains.

                     CEE6430: Environmental
                      Disasters (Man-Made)
                         Cont’d.

• The station had instead become a scene of misery and
  death all around.

• Mr. Dastagir’s action saved many lives. Unfortunately
  he’s a forgotten Hero (died a year spending most of his
  remaining life in hospitals




                      CEE6430: Environmental
                       Disasters (Man-Made)
    Could The Disaster Been Avoided?

• Probably (Bhopal lacked emergency planning – had
  never considered of such a scenario )
• Union Carbide had a sloppy management practice (poor
  safety procedures).
• Such situations could be avoided through Rigorous Risk
  Assessment (Probabilistic)
• All kinds of possible scenarios are considered with their
  probabilities
• Joint probabilities, independence, dependence, mutually
  exclusiveness etc.
• Example: Nuclear Waste Regulatory Practice – Yucca
  Mountains – Groundwater Contamination.
                      CEE6430: Environmental
                       Disasters (Man-Made)
   But How Exactly do We Minimise the
          Impact of Disasters?
• First, before even actual implementation of a
  project/plant, we consider ‘what if’ scenarios.
• We ask then the most plausible effect of the ‘what if’
• Next we ask ‘can we afford to live with it?’
• Next we try to compute the chance, odds (odds ratio),
  probability (using very much the CEE6430 theory we’ve
  learnt) of those ‘what ifs’.
• It’s impossible to consider all ‘what ifs’ scenarios
• But good news – Computers are getting powerful to do
  the job – to consider error in all sources.
• New numerical techniques emerging, Fuzzy concepts,
  Optimization, AI, Error Analysis, Error Propagation
                     CEE6430: Environmental
                      Disasters (Man-Made)
    More Specific Example: Hydrologic

• Imagine this: National Weather Service
• Issuing Flood Forecasts
• Considers only upto 100 years of return period in its
  probabilistic forecast
• What if – storm were a 500 year return period?
• How do we calculate the flood level (probabilistic)?
  Remember, we need to consider uncertainty in both
  rainfall and model – random processes
• Next question – can the city afford the damage expected
  from a 500 year storm?
• If not – what kind of proactive measures can it take
  (emergency measures) to minimise loss of life.
                     CEE6430: Environmental
                      Disasters (Man-Made)

				
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posted:11/29/2011
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