Human Health Risk Assessment to Chemicals

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.

Tuesday, April 14, 2015

ERATA Regarding the last post: Drs. Crump and Berman were Contractors for the EPA

Below in an email from Dr. Frank Mirer correcting my mistaken impression that Drs. Crump and Berman were contractors for clients with commercial interests in asbestos when, in fact, they were hired as contractors by the EPA. My apology for the misinformation.

Regarding the asbestos piece. First, thanks for noticing it and your thoughtful comments.

Second, more important, when I wrote that Kenny Crump was a “contractor,” I had intended to convey that he was an EPA contractor, not writing a study for management. Can you correct this? This support is disclosed in one of the papers (although the authors do disclose support from a management group as well). In recent years, EPA has commissioned scientific documents of this type which were subsequently published in peer reviewed journals. Kenny Crump co-authored a commentary on formaldehyde for EPA which was helpful to the precautionary side, and which was (in my opinion) validated by recent new knowledge. In the asbestos case, increased risk estimates for amphiboles would support lower tolerances for Libby asbestos, which would be precautionary for Libby and which was EPA’s main concern.

[Can you include the above in your next post, and, if you have an email, forward it to Kenny. Thanks.]

Sunday, April 12, 2015

OELs and Politics

I often stated that I believe that the setting of Occupational Exposure Limits is a political process; however, just as important as the politics, it is a process that needs to be informed by science. This fact came into sharp focus for me when I read a recent article in this month’s (April 2015) issue of The Synergist (a publication of the American Industrial Hygiene Association). The articles is entitled “ABCs and Asbestos Risk Assessment” by Dr. Frank Mirer. Frank walks us through the available science and provides his conclusions concerning the potential for less risk from chrysotile asbestos than for other forms of this mineral. Within this article Frank reviews a controversial analysis and conclusion presented to the EPA’s Science Advisory Board by Drs. Crump and Berman. Dr. Mirer referred to them as contractors who presumably were supported by the asbestos industry.

Drs. Crump and Berman concluded that:

“The best estimates of the potency of chrysotile (for mesothelioma) ranged from zero only up to 1/200^th of the potency of amphibole asbestos… Furthermore, the hypothesis that chrysotile does not cause mesothelioma could not be rejected in any analysis that allowed at least some amphibole contamination in the locations where exposures were principally to chrysotile…(F)or lung cancer … the best estimates of the potency of chrysotile were at least six-fold smaller than the corresponding estimates for amphibole asbestos.”

I strongly recommend that you obtain and read the article by Frank where he outlines and presents the reasons for his primary conclusion; namely, that even if chrysotile is somewhat less potent than amphibole, a significant risk of cancer remains at the current OSHA PEL. He also concludes that the link between chrysotile and mesothelioma has not been broken. Reportedly, most SAB members agree with him.

For me this discussion really brings home the fact that the exposure limit setting process is, at its heart, political. We cannot ban everything that is toxic. However, there may be a reasonable argument for banning asbestos given our current state of control and assessment technology.

I think it is very healthy for the process that accomplished and capable technologists like Drs. Crump and Berman present these arguments in the service of economic interests just as long as their intellectual treatments and suppositions are completely open properly vetted. My sense is that this happened in this case.

It may be entirely possible that chrysotile does not cause mesothelioma in humans. From what I can determine, it simply has not been satisfactorily proven in the context of a reasonably precautionary approach. Perhaps one day we will have tools that allow it to be proven to a reasonable scientific and political certainty, until then we default to considering it to be a cause of this dreaded and invariably fatal disease.

Although many of our politicians have not acquitted themselves well of late, politics per se is not a dirty word. It should be a noble endeavor that is ideally how democracies are supposed to settle questions of the general public good. Indeed, given the uncertainty that we are constantly facing in the realm of human risk assessment, there are many issues that cannot be answered with certainty but that must be decided. We cannot force all exposures and risks from chemicals to zero; however, we can attempt to estimate, limit and equitably balance allowable exposure (i.e., exposure limits) with the benefits derived from these exposures. I believe that to ensure the integrity of the process, we need to do this while also admitting the limits of our scientific knowledge and the inevitable fact that our knowledge will get better with time

Sunday, April 5, 2015

Modeling Breathing Zone Exposure is More Accurate than Monitoring!

Modeling has a bad reputation. Indeed, the conventional wisdom is that monitoring is the Gold Standard for exposure assessment. That is, the estimation of human exposure via the modeling of breathing zone concentrations has generally been considered to be inferior to the direct measurement of the breathing zone air. On the face of it, this attitude and conclusion seems to make perfect sense. After all, models are simply more or less general constructs of reality, while measurement actually samples the reality of interest. What could be clearer?

Well it turns out to be not so clear. The practical reality (spell that C-O-S-T) of monitoring means that not many samples will be taken to provide the estimated exposure. Thus, when one does a rational statistical analysis of what one gets from typical monitoring data versus what one gets from modeling, modeling comes out on top.

All of this has been laid out in strong mathematical and logical detail in an analysis performed by Dr. Mark Nicas. It was presented in a 2002 paper (Uncertainty in Exposure Estimates Made by Modeling Versus Monitoring, AIHA Journal 63:275–283 (2002)). I will be happy to send at pdf copy of this paper to whoever asks me for it at mjayjock@gmail.com. Mark is a brilliant statistician and modeler. Indeed, he has developed and tirelessly promoted the 2-zone model of indoor airborne concentration while providing a very strong technical rationale for the relative strength and superiority of modeling versus standard monitoring data for typical exposure scenarios. I was the second author on the paper but Mark preformed all the “heavy lifting” relative to the development of the mathematical rationale.

I am, of course, biased but I think the paper should have gotten a lot more interest that it did; however, given the complexity of the analysis I can perhaps understand why it did not get more attention. What is nice about this blog is that I can dust off this work and present it in a summary form to a new audience and in a new light.

Mark showed, very logically, that for a sample size of three or fewer workdays, mathematical modeling rather than air monitoring should provide a more accurate estimate of the long-term mean inhalation exposure level if the anticipated geometric standard deviation (GSD) for the distribution of airborne concentrations exceeds 2.3. When the number of samples is n=1 this was true for GSD > 1.7. Paul Hewitt in his publication: Interpretation and Use of Occupational Exposure Limits for Chronic Disease Agents. in Occupational Medicine: State of the Art Reviews, 11(3) July-Sept (1996) online version:

http://www.oesh.com/downloads/TR%2007-01%20OELs%20for%20Chronic%20Disease%20Agents.pdf

tells us that “The range of GSDs - 1.5 to 3.0 - covers the range of most ‘within-worker’ GSDs commonly observed in practice.” My experience has been that the majority of these are on the upper end of this range.

Certainly modeling will do a better job than monitoring when the typical number of monitoring samples taken in most scenarios is n=0 as effectively and convincingly presented by John Mulhausen a number of years ago.

The concluding paragraphs from the 2002 paper is reproduced below:

A framework has been described for comparing uncertainty in estimates of the long-term mean exposure level made by modeling versus monitoring. Although not developed here, a related approach can be used to compare estimates of other exposure parameters such as the 95th percentile of the C distribution. The NF exposure model was used to illustrate the framework, but the authors recognize that different models are more realistic for other scenarios, and that the time-activity pattern of the exposed employee must always be considered. Central to the utility of the modeling approach is that the model be an appropriate physical descriptor of the contaminant emission rate function, the pattern of contaminant dispersion in room air, and the manner of removal from room air. Because the traditional focus of industrial hygiene has been monitoring rather than modeling, the available mechanistic (physical-chemical) indoor air exposure models have not been systematically investigated and validated. In turn, this lack of research leaves much present-day uncertainty regarding source emission rates, dispersion patterns in air, and sink effects.
Based on preliminary analysis, the authors argue that directing research funds to developing and validating mechanistic exposure models will ultimately provide cost-effective exposure assessment tools. Their availability would encourage more assessments of compliance with OSHA permissible exposure limits in small- and medium-sized workplaces that lack the dedicated services of an industrial hygienist. Further, validated models would have benefits beyond OSHA-related compliance determinations. Employers could proactively use such models to devise appropriate exposure controls in planning new processes and operations. Consumer product and environmental regulatory agencies could use models to assess the safety of products that release airborne toxicants. Mathematical models could be applied to epidemiological studies for retrospective exposure estimation when past monitoring data are poor in quality or nonexistent, as is often the case. At a minimum, validated models could be used to rank average exposure levels by task/job, and if sufficient information were available, could provide quantitative estimates for exploring dose-response relationships. (emphasis added)

Sunday, March 29, 2015

Hope and Change in Human Health Risk Assessment

Sarah Palin once mocked our President by asking him, “How’s that Hopey Changey think working out for you?” It struck me that hope and change or, more specifically, the hope for positive change is, or should be, an important and positive human attribute. Indeed, I see the opposite sentiment as resignation, stagnation and despair which really does not serve anyone well.

In the interest of full disclosure, I have to admit that I am a hard core Pollyanna, whose Cambridge Online Dictionary definition is: a person who believes that good things are more likely to happen than bad things, even when this is very unlikely. Indeed, I have been predicting that the general widespread acceptance and application of quantitative human health risk assessment will happen within the next two years for more than 25 years! It has been argued that this has not happened to date as the vast majority of chemical exposures and risk are not well characterized. See previous posts:

We do not estimate Quantitative Risk for Most Chemicals (May 24, 2013)
Why Isn’t Risk Assessment Done on All Chemicals? (October 28, 2013)
Exposure Modeling Data Base Needs (August 8, 2014)
We do NOT spend enough on Risk Assessment (November 24, 2014)

I do want to point out some of the remarkable advances that have occurred over the last 25 years within the science and practical tools of human health exposure/ risk assessment. From my perspective, most of them have come from volunteers within the committees of the American Industrial Hygiene Association. The Exposure Strategies and Modeling Books and the associated modeling software have been great advances on the exposure assessment side. I think most of my colleagues, however, will agree that we could do a lot more given more resources.

On the toxicity side of things the situation is much worse. Except for a few promising exemptions (like EPA ToxCAST), it has remained stagnant for years as we do not have nearly enough exposure limits and necessary improvement in their documentation do not even appear to be on the horizon.

All of this is not to say that some companies and organization do not recognize the importance of doing the exposure or toxicity work to provide good assessment of chemical risk in order to do a rational and responsible job of managing the risk. They have what I call “enlightened self-interest”; they understand the importance and proper place of doing this as the “right thing to do” and in the long run “good business”. Most of my clients fall into this category; however, I must tell you that I do not have many clients. If you want some more insight into one aspect of this reality from someone with a lot more field experience than I do, check out the following post on this blog:

IH’s Dirty Little Secret (January 26, 2014)

Indeed, some companies and their organizations see their relationship with regulators as essentially adversarial, indeed, as covertly but un-apologetically war-like. As a Risk Assessment Scientist working for a large chemical company in the 1970s through 2003, I participated in industry group meetings where I saw this attitude first-hand.

Below is a small and edited excerpt from a letter I wrote to a staffer for such a group many years ago asking their advice:

“I believe that it is not accurate or useful to accuse or think of the regulators as not using science. It implies that we own the scientific truth and I tell you that we do not. We may have some more or less sophisticated scientific information that supports a less conservative regulation but our interpretation may not be compelling to the regulators who obviously have a different perspective. More important, they own the risk management call. It’s not that they do not use science but the reality is that they use “their” science and not “ours”. We need to work on understanding their perspective and their standard of proof while gaining some common ground and building consensus.
Our science policy should be one of cooperation, understanding and bridging and not confrontation. If the science that we developed is particularly well done then historically the difference between “their” science and “ours” should narrow. There are a few examples of this but they all involved considerable expense to do the work that needed doing.”

The letter went on to seek advice from the staffer as to whether I should ever openly voice such an opinion and advocacy for change in policy and approach. The response was that it would not be appreciated and I was advised to not give it voice.

That was almost 15 years ago and general opposition to practical and meaningful reform of the chemical regulatory process including the need for risk assessment in this country continues to receive serious opposition from groups speaking for the industry.

I believe that the industry in general would do so much better to broadly embrace enlightened self-interest and work for rational regulation and significant development of the science. That remains my fervent hope but I am an admitted Pollyanna. Indeed, it is entirely possible that the cold hand of regulation may be the only force that will ultimately catalyzes and provides real change and advancement in the science.

Sunday, March 22, 2015

100 Posts on Human Health and Safety

The post this week is about blogging in general and this blog in particular. When I started it almost two years ago, I did not think it would last for 100 blogs but it definitely has with at least a few more to go. What I would like to do with the remainder of this post is point up some of the things I have learned and some of the very positive aspects of writing a blog.

I did not think that the blog was going to last this long because I did not think I had more than a few dozen topics that I could discuss in a blog. I was wrong, however, the biggest factor in being wrong is that I did not count on the encouragement and inspiration I would get from you, the readers of this blog. I started with a list of topics but that list just kept getting longer as I got more feedback. Indeed, the interaction and networking with you, the readers of this blog, has turned out to be single most positive aspect of writing it. Thanks to all that are helping to keep this going.

This blog has been a remarkable instrument in reaching folks, especially the professional folk I wish to interact with. According to the statistics kept by blogger.com, readers have visited this blog almost 47,023 times in the 48 week since it started for an average of about 980 views per week. I rarely lecture to more than 50 folks in class or perhaps 10 times that amount at a professional conference session. Plus, I hear from blog readers from all over the World whom I would have had a very small chance of ever meeting.

I am sure the other blogging services do this as well, but one of the aspects that I really like about Google Blogger (blogspot.com) is that it provides a complete archive of all the previous blogs such that one can page back through them and find topics that might be of interest. As a further convenience I have cut and pasted all of the post titles to date below.

I remain very interested in hearing your comments about any particular blog and on what topics might be of interest to you in the realm of human exposure and risk assessment to chemicals.

99 Blogs from April 2013 to March 2015

The Air Pollution We Breathe: Where does it come from?

Estimating Airborne Particulate Exposure from Overspray

Short Term or Bolus Exposure Limits

Inhalation Exposure from Spills Modeling – Part II

Evaporation Rate of Small Spills

Introduction to Monte Carlo Simulations for Exposure Assessment

Dr. Zhishi Guo and the Programs IAQX, PARAMS v1.1 and More

i-SVOC (2014): A Modern and Remarkable Advancement over AMEM

AMEM: A Tool to Estimate Human Exposure from Fire Retardants and Plasticizers in Plastics

Inhalation Model Research Needs

Acceptable Risk: Personal Gut Check