Want to Learn Industrial Hygiene? Check this out.

By any measure I am in the latter stages of my career.  I have been around a long time and have seen quite a bit of positive change in the Industrial Hygiene profession.   We are evolving from a “pump jockey” mentality into a much more rigorous scientifically based vocation.   The refinement and enhancement of the science of sampling statistics by Jerry Lynch, John Mulhausen and others along with the pioneering efforts to use Bayesian statistics by Paul Hewitt and others are prime examples. 

At the AIHA conference in Minnesota last month I attended a presentation by Dr. Jerome Lavoue on a freely available statistical analysis tool: expostat.  This effort was new to me and it looked like a great tool.   I sent a note to my friend Tom Armstrong about it.  He responded that he was well aware of this tool and sends me a remarkable slide deck on statistical analysis that he is working on.   

Tom starts off with a 10,000 meter view of IH statistics and rapidly zooms into providing useful, spot-on guidance and details on the current state of the science and where to get more info.  Like I said, it is a remarkable set of 30 or so slides which Tom has agreed to allow me to send to you if you request it:  mjayjock@gmail.com.

Another highlight of the conference for me was a visit to Dr. Susan Arnold’s laboratory at the University of Minnesota.   It is a great lab with a lot of salient instruments and a chamber that allows her and her students to conduct some controlled exposure studies.  She also told me something about her IH curriculum which is very heavy in modeling and science.  I am aware of a few other programs along these lines but I was particularly happy to see Susan doing this.  If I were a young person interested in a top-notched program with opportunity for hands-on research I would consider moving to Minnesota weather notwithstanding.

Dr. Thomas Armstrong National Treasure

I have written about Tom previously in this blog but his latest contribution to the realm of exposure modeling is really quite extraordinary.   It is 111 slides in a PDF file that contains the following gifts for anyone willing to view and study them:

•     Worked examples annotated with Tom’s wonderful insight and guidance.
•      Clear explanation of ALL  the basic elements of inhalation exposure modeling.
•      Specific guidance to the importance of using                 thermodynamic activity coefficients (ACs).
•          Where to get the tools for the determination of ACs
•          Worked example of using ACs
•     Use of EASTMAN Chemical's nominal evaporation rate scale to provide estimates of quantitative evaporation rates in mass/time.
•     Numerous excellent referenced tables for Random Air Movement Indoors and the Eddy Diffusion Coefficient (Dt).
•     Numerous references and links to get what you need to actually do exposure modeling.
•     A wonderful annotated primer for IH MOD 2.

It is easily equivalent a multi-day course on the general subject but presented in a way such that it is relatively easy to follow.  This is especially true if you have some background in modeling or you are willing to delve into the AIHA Modeling text:  Methematical Models for Estimating Occupational Exposure to Chemicals, 2nd Ed. as a companion resource.

I will send the PDF file to anyone who requests it:  mjayjock@gmail.com

Tom would also love to hear from you.    He has been hospitalised twice recently with a serious illness.  The good news is that he is on the mend and will be out of the hospital soon.  The bad news is that he will miss this year’s AIHA Conference because he needs to undergo further treatment for his condition.  We have been corresponding while he was in the hospital and I recently wrote to him: 

"Tell your caretakers that you are a National Treasure and to get on with it!"   He wrote back that this brought a smile to his face.   The truth is that in the realm of IH he truly is a treasure. 

He is very regularly on email at:  twa8hr@gmail.com

Are the Exposure Models Used for REACh Wrong?

Dr Joonas Koivisto and 16 others, including this writer, have recently authored what I believe is a very important paper:  Source specific exposure and risk assessment for indoor aerosols.    It sounds a bit like a paper focused on aerosol assessment but it is actually a comprehensive look at inhalation exposure models and the quality of these models to make decisions relative to chemical regulation and risk assessment.   The reality is that aerosols represent the most challenging scenarios for modeling because of their added properties compared to gases.  If one can accurately model aerosols then gases are relatively simple to model.  

The publication outlines the current state of the science and available models.  It also makes a developing case for the use of first principle mathematical mass balance models versus other types of models (knowledge-based models, and statistical models of exposure determinants) especially for regulatory decisions such as those mandated by REACh.

The Europeans are much more advanced than the US in the application of exposure models because they have to be.   The REACh regulation requires a risk assessment for literally thousands of chemicals and a risk assessment requires an exposure assessment.  There is not nearly enough measured exposure data available, so they have turned to models.   It is clearly evident that the inputs to and data bases for the mathematical mass balance models have not been sufficiently developed so the European Regulators have turned to knowledge-based and statistical models of exposure determinants.  These models are more easily applied because the inputs are relatively simple.   The paper implies that these models are not performing up to the task and that there is a real need to develop the input data necessary to feed the more competent first principle mathematical mass balance models.  

The paper points to an earlier paper I did with Tom Armstrong and Mike Taylor in which we challenged the mass balance 2 zone Near-field/Far-field (NF/FF) model to the Daubert legal criteria which is widely used by the Courts to assess whether expert witnesses scientific testimony is methodologically valid.   In that paper we concluded the NF/FF model fulfils the Daubert criteria and when it is used within its stated limitations, it adequately estimates the exposure as applied to legal decisions.  The implication is that the models currently used for making decisions for REACh would, most likely, not pass the Daubert criteria, which requires that these models:

1) Are applicable and have been tested.

2) Have been subjected to peer-review and are generally accepted.

3) The rate of error is known and acceptable.

4) have maintenance of standards and controls concerning their operation.

5) Are generally accepted in the relevant scientific community.

This Daubert paper is:  Jayjock, M.A., Armstrong, T., Taylor, M., 2011. The Daubert Standard as applied to exposure assessment modeling using the two zone (NF/FF) model estimation of indoor air breathing zone concentration as an example. J. Occup. Environ. Hyg. 8, D114–D122.   I will email an electronic copy to anyone requesting it: mjayjock@gmail.com.

What Dr. Koivisto and the other authors are asserting in this paper is somewhat striking; namely, the currently used REACh models need to be explicitly challenged by the Daubert (or similar objective) criteria and, if found wanting, better alternatives should be developed and employed.   This would, most likely, result in something this writer has been advocating for many years; specifically, comprehensive research and compilation of exposure source data bases.

This should be a straightforward objective scientific exercise; that is, a technically competent and empowered group of scientists would set open and objective criteria and test the currently used regulatory sanctioned models to those standards.   The reality, as I see it, is that there are strong vested interests and forces at work in this case that may resist this sort of effort.   Change is never easy but, hopefully, scientific integrity, good judgement and established facts will ultimately work to improve the public health, partisan politics notwithstanding.

The paper was published online this week at https://doi.org/10.1016/j.scitotenv.2019.02.398 as gold open access, which means that the full pdf text is a free download from the publisher Elsevier.  

Simple Techniques for Assessing Airflow in Occupied Spaces

Jeff Burton is a treasure to our profession.  He wrote a piece on ventilation earlier this year and published it in the AIHA Synergist.  I found it to be incredibly valuable.  On the chance that you did not see it, I am reproducing part of it below with his permission.  It is a trove of practical advice born from a lifetime of experience  and a great resource for any practising IH.

One thing the Jeff did not mention but that I think is important is that much of this can be used for exposure modelling input.

I am reproducing the first few paragraph of the article below.  If you are a member of AIHA, you can go to the online version in the Synergist to get it in all its glory at: 

https://www.aiha.org/membercenter/SynergistArchives/2018SynergistArchives/Pages/Six-Ways-to-Approximate-Airflow.aspx

If you are not a member, and you want it for your personal use, you can send me a request (mjayjock@gmail.com) and I will send you the original MS Word document that Jeff sent to me. 

______________________________________________________

Six Ways to Approximate Airflow

Simple Techniques for Assessing Airflow in Occupied Spaces

By D. Jeff Burton

Every occupational health and safety professional must be able to evaluate the air the occupants of a space are experiencing to assess the potential for IAQ problems and their solutions.

Most OHS professionals today are unable to conduct in-depth testing or measurement of HVAC systems and their airflows. Specialized knowledge of testing, measurement, and balancing is often required on the complex systems of today. Industrial hygiene engineers or TAB (testing, adjusting, and balancing) specialists can be employed to make detailed measurements. However, an OHS professional can often gather enough simple information to quickly provide approximate answers to questions about airflow in a space, regardless of the complexity of the system.

This article provides guidelines for simple testing, measurements, and approximations an OHS professional might perform. These include temperature and humidity; air movement and distribution, outdoor air flowrates, and air exchange rates in the occupied space; concentrations of carbon dioxide in the air; and the effects of wind on the airflow through a building.

The following equipment is needed to perform the simple tests and measurements described in this article: tape measure, thermometer, psychrometer, smoke tubes, and carbon dioxide monitor.

...

Are REACH Exposure Models Good Enough?

The political will in the European Union to enact REACh was and is extraordinary.   The body politic in the EU wants this regulation and certainly needs it to be effective. It should be clear that it cannot be effective if the exposure assessment half of the risk equation used for REACh is faulty.  Underestimation of exposure and risk hurts people's health directly, over-estimations hurts people's well-being by unnecessary hurting of the economy.   The use of good modelling tools is critical or REACh, in my opinion, will ultimately be doomed to fail. 

I have always thought that first principle physical chemical models (FPModels) have been superior to models that are not based on first principles (NFPModels).  Now a thoughtful and talented Danish researcher (Dr. Antti Joonas Koivisto) is examining and demonstrating with logic and DATA exactly why first principle models are better and, most likely, even necessary to make good regulatory decisions.

An early question might be:  Why develop NFPModels when FPModels are available for development?   The easy and probably correct answer:  They can be developed relatively quickly and with less effort and expense. FPModels are available but need to be parameterized for critical exposure scenarios and that means research dollars.

NFPModels, for the most part, are based on dimensionless factors to calculate scores, which are then converted to exposure values.  They are conceptual models than do not have to conform to first-principles and are thus (using Joonas' word) somewhat vague.

While there are other NFPModels, the big hitter in the EU for modelling exposure via REACh appears to be Stoffenmanager® v.7.1 which as of last month:

·         is reportedly validated by 15 scientific studies based on more than 6000 measurements. 

·         has more than 33,000 users with 50 new users per week. 

·         used to make over 200,000 regulatory decisions

It is accepted by the Dutch Labour inspectorate as a validated method to evaluate exposure to hazardous substances in the workplace.   More important, the European Commission officially recognises Stoffenmanager as a instrument to comply with the REACh regulation.

Other REACh-recommended NFPModels include:

ECETOC TRA

MEASE

EMK-EXPO-TOOL

ART

Although somewhat varied in their approach, they all share the same feature that they are

all based on dimensionless factors to calculate scores, which are then converted to exposure values.  They are conceptual models than do not have to conform to first-principles (like the conservation of mass).  Thus, they are not scientifically formalized and that leaves them difficult to explain.

Dr. Koivisto asserts, and I agree, that there should be minimum requirements for regulatory exposure models and that those criteria should be no less than the Daubert criteria used in US Courts for valid scientific testimony.  The model criteria: 

•          Is applicable and has been tested.
•          Has been subjected to peer review and is generally accepted.
•          The rate of error is known and acceptable.
•          The existence and maintenance of standards and controls concerning the                     operation.
•          Is generally accepted in the relevant scientific community.

Joonas goes on to advise that FPMmodels are superior to the above NFPModels (what he calls “imaginary” models) because:

•       Mass flows are traceable à Model can be used for environmental, occupational and consumer exposure assessment!!

•       There is No unit conversions!!

•       Error analysis can be made separately for emission source, emission controls, and dispersion.

•       No need for Tier levels;  the Tier level depends on available information.

•       Possible ”calibration” is straight forward (e.g. chamber tests)

•       In the NF/FF model the NF volume and air mixing are adjustable according to the source (free parameterization).

•       Results are easy to interpret

•       TRANSPARENT!

•       Easy to develop for further needs

•       No need to discretize parameters (e.g. room size, ventilation rate,…)

•       Accuracy superior when compared to compared to mechanistic or conceptual modes

I took most of the above from a November 29, 2018 presentation that Joonas gave in Denmark.  I will be happy to send the PowerPoint slide deck of that talk to anyone who asks at mjayjock@gmail.com.

IH Mod 2.0 - A Major Advance in Exposure Modelling Tools

I have not blogged for quite a while primarily because in 125 blogs I pretty much exhausted what I wanted to say on various topics.  Also, new ideas for blogs from the readers also seemed to have dried up.  I am, however, moved to post again by the wonderful work of Daniel Drolet and Tom Armstrong on the tool many of us know as IH Mod.  For years, they have wanted to combine the power of these deterministic models with the new dimension of stochastic uncertainty modelling (e.g., Monte Carlo simulation).  Daniel is a brilliant programmer and he made it happen!  It is now available as IH Mod 2.0 and, as usual, its a free download.  Daniel and Tom and all the folks who worked on this have done so without pay for the benefit of the professional.  Below is Tom's announcement.   I remain open at mjayjock@gmail.com for ideas for future blogs.   I do have another blog that will come out soon with goodies from Jeff Burton and the wonderful tools on ventilation he has recently provided to the profession.

Attention all exposure assessors who use or want to use mathematical modeling to estimate airborne exposure to chemicals!   IH Mod 2.0 and a Support File are now available (on the public access Exposure Assessment Strategies Committee web page.  https://www.aiha.org/get-involved/VolunteerGroups/Pages/Exposure-Assessment-Strategies-Committee.aspx

IH Mod 2.0 includes the same mathematical models as in the still available original IH Mod.   IH Mod 2.0 gives the user the choice between running the models in deterministic (point value parameters) or in Monte Carlo Simulation mode, with choices of distributions of parameter values.  This is right in MS Excel with no other software needed.  It requires a desktop install of MS Excel,  for  Windows or Apple computers.  The currently posted version has English, French, Serbo-Croation and Japanese language options.  Spanish, German and Italian will be available soon.

A Support File for IH Mod 2.0 is also available.  It includes useful information about IH Mod 2.0, and spreadsheet tabs to estimate liquid spill pool generation rates via the Hummel-Fehrenbacher equation, a units of measure conversion tool, examples of generation rate estimation, a "Bootstrap" procedure tool, a summary of approaches to estimate ALPHA for the exponentially decreasing emission rate models, and some links to other resources.  The support file is evolving and will be updated periodically with new information.  Check back at the EASC web page (URL above) for updates.

Modeling Aerosol Exposures

I have gotten very few requests for blog topics since issuing the offer some time ago.  One such request has come from Richard Quenneville who asks how one might model aerosol or airborne particulate exposure.

Aerosols are certainly different from vapors or gases and the differences significantly complicate any attempt to model their exposure.   Even relatively small aerosol particles (microns or tenths of microns) are much larger than the individual molecules that make up a gas or vapor.  This gives them different properties at least in the following areas:

• ·    They are typically more readily electrically charged especially if they are generated by sliding along a surface (e.g., dust from transporting powder in a pneumatic tube).  This charge can affect the size distribution and sampling of the aerosol.   
• ·     With or without electrical charge, aerosol particles are often susceptible to combining with one another in a mechanism known as agglomeration.  This process, of course, changes the size distribution of the aerosol.
• ·     Most important, because they have much more mass than vapor molecules they have a settling velocity which increases with increasing particle size and this, again, constantly changes the airborne size distribution of the aerosol with time.
• ·     Because of their mass, airborne particles do NOT always make it into sampling orifices thus biasing their measurement.

Assuming agglomeration is not happening in a time frame that is relevant to the potential exposure, one can estimate any time-interval concentration of any aerosol particle or size range of particles.   This is done by taking the average settling velocity of the particles in that size range and accounting for their loss from settling.   Typically is this done for particles from 2 meters in height settling to the floor.  If one is sure that the breathing zone remains at say 2 meters high you can calculate the concentration loss from the horizontal volume at 2 meters height to say, 1.8 meters.   If you do this over small enough time intervals you can estimate a time-weighted average of aerosol concentration for any time period dependent on the nature of the aerosol source.

This brings up another complication of dealing with aerosol.  Compared to vapors, predicting the “release” or generation rate of particulate into the air is highly problematic because it depends on many undefined or unmeasured factors such as inter-particle forces.  I have never been able to use first-principle models to predict this rate. Instead, we have had success experimentally determining this rate from simulating the mechanism of generation, measuring the resultant concentrations and back calculating the rate of generation.  I personally think this is what needs to happen for the exposure assessment of nanoparticles released to the air in various scenarios.

Please note, settling is dependent on the particle size distribution of the generated aerosol.  I have seen situations in plants that were literally “particle fountains” with particle size distributions with a significant portion of the particles were greater than 100 microns.  These particles hit the floor in a time frame of seconds which dramatically lowers the total aerosol mass/volume.   Particles on the other end of the spectrum, e.g., nanoparticles, are going to essentially remain airborne and not settle at an appreciable rate in most scenarios.

Finally, aerosol, especially insoluble aerosol, will deposit in the respiratory track based particle size.  At the current time we have some aerosol exposure limits specified in terms of total and respirable particulate.   These are defined mathematically by the ACGIH and these algorithms can be applied to the concentration in the above size intervals above to render the amount of aerosol that might be inhaled (inhalable mass concentration) or be able to reach the deep pulmonary regions of the lungs (respirable mass concentration).

The above analysis sounds daunting mathematically and indeed it is not simple; however, it is nothing that an Excel spreadsheet cannot handle with relative ease given the proper input of scenario specific dimensions, generation rate, initial particle size distribution, particle size interval-specific settling velocity and ACGIH algorithms.   Like all models it is not exact but, I believe it is accurate enough to be useful.