Sunday, April 19, 2015

Models and Monitoring are NOT Enemy Camps

A recent blog here asserting that modeling can be more accurate than monitoring may have, as a result of its title, unfortunately enhanced the old notion that modeling and monitoring are at odds with one another.   The blog was written because many consider that monitoring is the “gold standard” and that monitoring will never be accepted as a reasonable substitute for this “proper” characterization of exposure. The truth is that modeling alone, absent field or experimental work to monitor exposure scenarios, to implement, evaluate and refine the models, is a relatively anemic activity.

It is true than one can use “first principles” related to known physical properties of the materials along with accounting procedures that keep track of how much substance might be going into and out of any volume of air but these are all dependent on what I call sub-models.  We need to understand such critical "monitored" realities as:

  •   How the air is moving relative to its velocity and volumetric  rate
  •   The characteristics of the emitting source:
    •  how big is it?
    • is it a point or an area?
    •  the rate of emission as a function of time
    • competing sources within the scenario

All of these require at least some level of experimentation, data gathering (i.e., monitoring) to properly implement the model.  After this phase, the model output needs to be evaluated with the MONITORING of the exposure potential.  If the model got it essentially right, the monitoring will show this.  If not, then the model builders should gain some insight from the monitoring results as to how to improve the model.   It is clearly an iterative process where the monitoring continually shows the model builders where the model needs improving.

Once the model is developed, however, it should really help to inform the monitoring practitioner as to where he or she needs to monitor and, more important, where they do NOT need to monitor. The typical Industrial Hygienist (IH) in an industrial facility is often faced with perhaps hundreds or at least scores of “monitoring opportunities”.   These are scenarios that might result in significant exposure to workers.    Given the practical limitations of available resources, he or she will simply not be able to monitor everything everywhere.  Normally, the IH in this situation applies “expert judgement” to eliminate and exempt the majority of scenarios of undergoing monitoring.   Indeed, John Mulhausen has made the critical point that the typical number of exposure samples taken relative to exposure scenarios is ZERO.
So how does an IH, who only does monitoring, decide where to monitor?   Well, some scenarios are obvious when at least one of the following factors are present:

  • The workers are showing symptoms of overexposure
  • The chemical is highly toxic (low OEL)
  • The process
    •  Is fast (producing relatively high levels of product and  airborne contaminant)
    •  Consists of a considerable amount of volatile or dusty  material
    •  Is relatively open or “leaky”
    •  occurs at elevated temperature
Whether they realize it or not, I believe that many, if not most, IH practitioners in this situation are applying their own personal "experience model" to estimate whether the ratio of potential exposure to the exposure limit for the chemical is significant. If this subliminal model tells them that the ratio can be close to or greater than one then they typically move forward to monitor the scenario. 

What my colleagues and I have been asking for quite a few years now is: Why run a subliminal model when they can use explicit mathematical models with all of their advantages to inform these decisions? 

The bottom line is that modeling and monitoring are not separate camps but really are inextricably connected and feed each other within the process.


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