Air Quality in the Barnett Shale - Part 30: The End... finally!

It all started...so long ago...29 posts ago to be exact, not including this one.

There I was trying to get a bit of information on the air requirements for oil & gas fracing operations in Texas, when I stumbled across the final report Alisa Rich of Wolf Eagle Environmental prepared for the Town of Dish, Texas.  That started Post 1.

Now I promised myself I was not going to write a rant or indignation type of blog; that this blog was going to be nothing more than trying to explain complex environmental laws and regulations and how they impact day-to-day operations. I also wanted to talk about public health issues involving chemical exposure - a new-found interest for me after obtaining my MSPH last May.  Basically though, this blog is nothing more than my attempt to consolidate the information out there so that I understand the topic better.  If it helps someone else understand it better too, well than win-win!

Now what I found interesting in all this research (and after 29 posts I have looked at a lot of stuff on this topic) was this graph from the TCEQ:

As a scientist and as a guy who has spent his career looking at numbers to decide what is "dirty" and what is "clean," any time I see a downward trend (my paycheck excluded) I think "good!"  So "bad" ozone levels - which is basically VOCs - is on the downward slide.  And benzene, the most problematic of the VOCs in terms of health issues, is also on the decrease as well.  And at the same time, oil & gas production is on the rise.  Go figure.

Now you can explain this away anyway you want, economic downturn, manufacturing going to China, pollution control, increase enforcement, but the fact is, with an increase in oil & gas production in the Barnett Shale area, the air has not become more contaminated with these two dominant pollutants of concern.  Which means that the foot print of a well maintained oil & gas production site poses a minimal impact on air quality in this area based on the data we have....and we have a lot of data to bolster this.

I have read all of the reports referenced by all the parties involved.  I have looked up the procedures and read them.  I have looked up the citations and the references.  I have checked and double checked the calculations.  All of this has been done in an effort to either support or dismiss the scientific work presented.

I know - because I have been there and I work with hundreds of different people from different disciplines and organizations - that we humans make mistakes.  Sometimes through sheer incompetence (example), others because the issue was illusive, subtle, or extremely nuanced (i.e. Tedlar bag artifacts).

The whole point of this blog is to look at complex topics, tear them apart, and try to understand all the different things that impact it and give it substance and weight.  What you read here is not my expertise but my journey towards an understanding while I try to comprehend it better.  Because it interests me, it may be of interest to someone else as well, or, it may be helpful to someone trying to better understand an issue.

It may seem after 29 posts that I am being hypercritical of the work performed by Alisa Rich and Dr. Sattler.  I am not.  My critique is about the method and data they used, the assumptions they made, and the inferences drawn by these two professionals for their clients including the town of Dish, Texas and the FWLN.

Alisa Rich holds a Master in Public Health (MPH) and is working on a Ph.D.  For me to consider the possibility that she is not aware of the fundamental difference between an ESL and an AMCV is to say UNT's MPH program is derelict in it's course work.  And if that's not the case then what is it?  The reports she wrote for her clients ignore the basic principle of assigning and describing risk - something she should have learned while obtaining her MPH as well as during her time perusing her Ph.D.

And what about Dr. Sattler?  She is an engineer.  But not just an engineer, but a PE!  That's the top of the heap in terms of the ability to show competence and good engineering principles.  And to top it off she is a professor at a major Texas university.  To build a model around one single sample, to estimate an exposure concentration two miles away that is three times higher than the PEL, to ignore non-Gaussian dispersion in the other samples collected at the same time, and to continue using an ESL - derived for odor no less - for ambient air samples because you don't know if  "the technically competent people [at TCEQ] were involved in this [AMCV] decision."  How can a person with this standing and education and credential allow such questionable work to pass as valid?

And because of the work of these two environmental professionals, the FWLN presented their report to the FWISD recommending set-backs of one mile based on the potential for receptors - children - in this area to be exposed to carbon disulfide and carbonyl sulfide at levels way above those deemed harmful for an adult worker.

And to bolster this report as valid, two additional Ph.Ds signed on as part of the "team of scientists and experts – Dr. Ramon Alvarez, Dr. Melanie Sattler, Dr. David Sterling, and Carl Weimer – who donated their expertise and time to the League to produce this report."  These two Ph.Ds aren't slacks either.  Dr. Sterling is the "Chair of Environmental and Occupational Health, University of North Texas Health Science Center, Fort Worth."

So why should Deborah Rogers - the FWLN "liaison between the League and the team" - question what this team produced?  Why should anyone who reads the FWLN report question its validity with these experts on board?

And therein lies the problem.

If I have not made my case after 29 posts, well I don't know what more I can offer.  I can defend my critique of their work, its all there in cyber black and white.  If I am wrong, then show me so that I may correct it.  That's the intellectuality honest thing to do.  Right now the ball is in Dr. Sattler's court for her to defend her work as valid.

Which is why I took her up on that challenge she made in the Deposition:

I think my work stands up to anybody that has expertise in dispersion modeling.  If anybody was criticizing it, they probably didn't have --well, it wouldn't surprise me to see somebody without a scientific background criticize it, because they probably wouldn't understand it.

Well I don't have expertise in air dispersion modeling, but my white lab coat has allowed me to look at it objectively and question the premise of backing in an ambient air concentration to derive an emission rate.  Oh, and I do have the scientific background to criticize it because after 29 posts, you should see that I do understand it.

So here it is, once more:

In the Town of Dish, Texas report prepared for by Alisa Rich, the six samples collected and used to calculate the emission rate which was then used to develop the plumes, do not show Gaussian dispersion in the ratio of contaminates analyzed.  Explain?

In the FWLN you produced a model - Plot 1 - for carbon disulfide that is based on one sample collected on one day.  Please explain how Plot 1 can be determined to be representative of all the oil & gas production sites in the Barnett Shale area?

In the Town of Dish, Texas report, the model you produced is based on identification and quantification of carbon disulfide identified by the lab as a TIC.  In the FWLN report, Plot 1 utilizes a carbon disulfide identification and quantification that is identified by the lab as a TIC.  In the FWLN report, Plot 2 is based on a carbonyl sulfide identification and quantification from a sample collected in a Tedlar bag which is known to produce artifacts of carbonyl sulfide.  How confident are you in these concentrations you used to "back in" to your model to determine the emission rate?  What is the basis you use to support their validity?

In order for the Gaussian dispersion model to work for a year's worth of plumes, the emission rate must stay constant.  Please explain how in Plot 1 of the FWLN report, at two miles from the source the air concentration for carbon disulfide could be at three times the OSHA PEL without causing illness, death, or a significant odor problem in and around the source if that is, indeed, the correct emission rate?

You assume in all your models, including FWLN, that all of the contaminant found in the ambient air is coming from the O&G source.  When looking at other scientific papers where an ambient air sample is "backed in" there is an upwind sample collected so that background contamination - not from the source - is not included (subtracted out).  On what scientific basis does including background levels of contaminants in your emission rate calculation fall under?

That's all Dr. Sattler needs to respond to.  Five appropriate and scientifically-based questions dealing with her work.

If these are non-issues, well you got me on that.  But I think they are real issues that need to be addressed in order to conclude that the need for a one-mile set-back is valid.  Even Dr. Sattler acknowledged this in her Deposition:

I just think with this [FWLN] study imminently going to provide results of lots of data, that it's prudent to -- to get the results of that study, so that if it recommends a setback distance of 400 feet, say, from a well, we could try to locate the well 400 feet from wherever it is.

"Prudent" to base the recommendation on the results, which I assume means results that can be held up to scrutiny and critique.

And in case you have no idea why this matters to me, read my post on "why bother writing about this."

And to bolster what I wrote back then, read this story on chronic fatigue syndrome that appeared in the Chicago Tribune (I read it today in Sunday's local paper The Eagle.)

And to further support the reason: (4/3/11) "Health officials struggling to contain a measles outbreak that's hit hard in Minneapolis' large Somali community are running into resistance from parents who fear the vaccine could give their children autism." (1)

So lets put an end to bad science, dubious science, misleading science, incompetent science, and just plain ol' science to bolster an agenda.

Regarding the impact of oil & gas on the air in Barnett Shale....me thinks this dead horse done been whipped enough!


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Air Quality in the Barnett Shale - Part 26: That's a lot of n's!

In my last post I looked at the quality of the data presented in the ERG report and the TCEQ report for air quality in the Barnett Shale.

Looking at how the data was obtained is important to understanding how valid it is.  Along with this is the number of individual data points - or n's - were collected.

Since we are making an assumption, such as the air "does not pose a health hazard" or the air is "2 times above a threshold where irreversible effects can occur" the quality of the data and the representation of the data to what is actually found becomes critical.

Alisa Rich in her report to the Town of Dish, Texas, modeled the air using only six samples - collected on one day - and analyzed with the wrong method, concluding

Dr. Sattler, using one sample - collected on one day - and analyzed with the wrong method, concluded in the FWLN report:

And with these two assumptions, FWLN had enough information to support their contention that the air quality in the Barnett Shale in the Fort Worth Area is significantly impacted:

I contend that because of the lack of representative sampling (too few n's) and the incorrect laboratory analysis (TO-14 instead of TO-15) the data Rich and Sattler generated is invalid and, therefore, their model's predictions are invalid, which makes these types of statements regarding carbon disulfide in the Barnett Shale area false.

So what do we know about the air in the Barnett Shale and the emissions from oil & gas production sites?

Quite a lot, actually.  Both the Barnett Shale Energy Education Council (BSEEC) TITAN Engineering report and the ERG report - referenced in the FWLN report - provide a considerable amount of data (lots of n's). And that data can be supported as valid because the reports can show precision and accuracy (which Alisa Rich and Dr. Sattler cannot).

Now you can choose to ignore the BSEEC and ERG's data, but the only grounds to do so is because you suspect some kind of conspiricy between O&G and them.  Possible, but not very plausible.  A conspiracy to distort, fake, or hide sample data implies both a lot of conspirators who will presumably attempt to conceal what they have done, and a lot of readers who can be successfully persuaded that the data in these two reports have been purposely distorted.

If you think there is a conspiracy by BSEEC and/or ERG to fake this information then you can stop reading now and go back to your land of implausibility.  Like I said earlier in my posts on the air in the Barnett Shale area, I assume that the data provided by Alisa Rich and Dr. Sattler has not been purposely manipulated.  It may be invalid, but I don't think it has been faked, tainted, or manipulated.  The same is true for BSEEC and ERG's data.  I assume it to be truthful and honest.

The BSEEC tested the air over four time periods in June, at nine (9) different locations.  EPA Method TO-15 found the following results for 93 samples (n's) of carbon disulfide:

The BSEEC report identified the following concentrations for carbon disulfide and carbonyl sulfide tested using ASTM Method D 5504-08 for sulfur compounds .  Please note that the number "4" by the quantity indicates:

Which means that it may have come from the bag itself and not from the air sampled:

A significant factor in the selection of filter media used for air sampling is the formation of artifacts due to the sorption of sulfur and nitrogen oxides on the filter. These artifacts can erroneously increase measured particulate concentrations. (1)

Here is what the BSEEC reported:

Thats over 21 samples (n's) for carbon disulfide, and of these samples, nine (9) were non-detectable.  Assuming that the concentration reported for this method were not artifacts, the highest concentration of  carbon disulfide was 11 ppbv.  

It should also be noted that only Tables 10, 14, 20, 23, and 26 showed a higher concentration of either contaminant downwind as compared to upwind ("D" = downwind in sample number)  The highest carbon disulfide concentration, 11 ppbv, was found in the upwind sample!

So the BSEEC report brings us a total of 114 n's for carbon disulfide.

Now lets look at the ERG Report, also referenced in the FWLN report.  ERG sampled nine (9) unique O&G sites plus one site designated as background:

At these sites a total of 92 detections for carbon disulfide were found with an average concentration of 0.243 ppbv and the highest concentration detected as 1.64 ppbv for a 24-hour sampling period:

So what do we know about the concentration of carbon disulfide in the air around oil & gas production facilities in the Barnett Shale?

Out of 206 samples (n's) the maximum concentration of carbon disulfide found in the air in the Barnett Shale area was no higher than 11 ppbv.

If Dr. Sattler's contention is true that from her one sample used in the FWLN was found to produce an emission rate that could produce up to 78 ppm (that's 78,000 ppb).  At the backed in calculated emission rate that she believes is emitting carbon disulfide, don't you think we would have seen concentrations above 11 ppbv in at least one of the 206 samples?

And the reason we are not seeing anything higher than 11 ppbv (or 10.8 if we assume the TIC she reported is accurate) is for one simple reason;  you cannot back in an ambient concentration into a Gaussian air dispersion model without placing directly downwind from the site and subtracting the upwind concentration from the result: (2)

The presence of carbon disulfide in the Barnett Shale area, regardless of source, is consistently way below the permitting ESL and the health based AMCV.

206 n's tell us this...and that's a lot of n's!

Next post: Air Quality in the Barnett Shale - Part 27:  Plot 2; Artifact or the Real Deal

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Air Quality in the Barnett Shale - Part 25: What a statistically valid report looks like

So here we are with a bunch of reports...looking at a bunch of numbers...and making a bunch of different observations and conclusions.  Should we trust the TCEQ's findings?  Should we discount what the FWLN's report claims in terms of possible exposure to carbon disulfide?  What about ERG's report and all the work Alisa Rich did for the Town of Dish Texas?

It seems daunting, but it is not if you follow a certain - well recognized - set of basic scientific principles when collecting samples and analyzing them. So lets compare and contrast these reports.

One of my main complaints centers on the identification and quantification of the carbon disulfide concentration Dr. Sattler bases the setback on as well as an indication of potential health concerns.  And one of my main issues with the work performed by Dr. Sattler is the "backed in" data she uses to calculate her emission rate for the air dispersion modeling.  I believe I have laid out a fairly well substantiated reasoning for why her model's predictions are invalid.

Dr. Sattler assumes that with one air sample taken at a distance from the source you can back in to the air dispersion model and calculate the emission rate of the contaminant detected from that source.  With this emission rate, you can then plug it into the air dispersion model along with historical wind and weather information and predict the upper most concentration and distance from the source that could exceed a health based limit.

In my last post I attempted to show how that assumption - based on one single sample - assumes that one single sample accurately represents the air in and around the source.  n = 1 makes the model's predictions invalid, let alone the assumption that you can back in data to obtain the emission rate.  How confident is Dr. Sattler and her team on the representativeness of that one sample used to calculate carbon disulfide in Plot 1 and, most importantly, what do they base that confidence on?

In the ERG interim Report an emission rate was also calculated.  So why should ERGs stand and Dr. Sattler's be discounted?  Lets look at the assumption and the methodology used by ERG:

At 66 sites, preliminary quantitative emission estimates have been generated. Estimated annual emission rates were calculated from the short-term test data, assuming the measured emissions on the day of testing are representative of the emissions that occur over the year.

This is an assumption - it states it as such.  Scientist make assumptions all the time.  Then we test, test again, test some more, and research other similar published work.  Then when we look at all the data collected and we make a reasonable conclusion that our assumption is sound.

Even though ERG's emission rates were calculated from one SUMMA canister's results, there were 66 similar tests performed at 66 different locations.  This gives a representative snapshot as to what is most likely - reasonably - taking place.

A researcher can never know the true value of the population being sampled.  This is why we use statistics to calculate a mean, standard deviation, and variance.  It is with those numbers that we look at our assumptions and make a judgement to its soundness.

With 66 different samples of the population (air within oil & gas sites) collected by ERG, we can look at the report's tables to get a pretty good idea of what is being emitted - provided some additional methodologies were also performed.

Because bias is always present, the sampling team and laboratory need to follow a strict protocol on how they will collect the sample, transport the sample, prepare the sample, test the sample, and report the results.  This is all part of what is referred to as QA/QC.  If you look at the ERG report you will see a section QA/QC and if you look at the TCEQ report you will see the same.  If you look at the FWLN report and the reports by Alisa Rich for the Town of Dish, Texas, you will not see a QA/QC section. (The Dish Final Report does describe the sampling procedures and the analysis method performed.)

So the assumption is this; If the researchers follow their QA/QC plan, the impact of any bias will be reduced and the results can be considered representative and valid.  Additionally, the laboratory follows a similar QA/QC plan and also may choose to follow a strict methodology and become NELAC accredited.  (To be valid in Texas the laboratory must be NELAC accredited.)

For the laboratory that performs the analysis, it must be able to show that they are able to "accurately determine a compound and that they can acquire the same concentrations from different instruments or samples while they are sampling the same gas stream, with an acceptable level of uncertainty."  This is known as measurement precision.  ERG calculated analytical precision by collecting two sets of duplicate samples at two different sites and analyzed them in replicate (page 64). (1)

As well as precision, the laboratory is required to show that it has the "ability to acquire the correct concentration data from an instrument or sample analysis with an acceptable level of uncertainty while measuring a reference gas stream of a known concentration."  This is known as accuracy. (1)

All of this data to show precision and accuracy is identified and report by both ERG and the TCEQ in their two separate reports on air quality in the Barnett Shale.  This data is needed to support their assumption that the results they have put forth are representative and valid.  Since we can never know the actual - or true - value, we need this information to support what we can reasonably ascertain.

This information is missing from Alisa Rich's reports as well as the FWNL report.  With one exception...sort of...GD Air Testing, the laboratory used by FWLN and Alisa Rich - is NELAC  Accredited.

However, when they perform analysis to identify carbon disulfide - a TIC - that analytical method is "not included in the Scope of NELAC Accreditation" (see note 'N' on the Lab report).  Without the FWLN report's laboratory performing the analysis as per their NELAC Accreditation, the results for carbon disulfide is invalid.  That's not the fault of GD Air Testing, its just the way we have to look at data that has not been generated under a strict protocol and methodology designed to minimize the impact of bias and substantiate validity.

To meet this, the samples had to be prepared and analyzed using a method that is designed specifically for the contaminant of concern.

So how did ERG and the TCEQ analyze for carbon disulfide?  They used the correct method, TO-15.

ERG Report

TCEQ Report

And what did Alisa Rich (2) and Dr. Sattler (3) use for their reports?

Dish, Texas Report

FWLN Report

So the wrong method - TO-14 - was used by Alisa Rich and Dr. Sattler to identify the carbon disulfide.  This creates uncertainty on the validity of all the assumptions that were based off the carbon disulfide quantification.

On the other hand, the use of the correct method - TO-15 - reduces the uncertainty and adds to the validity of the results and assumptions made by the TCEQ and ERG in their reports.

Because we cannot know the true value, assumptions are made.  It then becomes necessary for the report writer to show how sound those assumptions are.  Without representative sampling, without QA/QC, and without using the correct analytical method whereby precision and accuracy could be shown, the assumption presented by the FWLN are invalid.

Our assumptions are only as good as our data is sound.

Air Quality in the Barnett Shale - Part 26: That's a lot of n's!


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Air Quality in the Barnett Shale - Part 24: How confident in that 10.8 ppbv are you?

It has taken me a bit of time to get through the ERG "Interim Ambient Air Monitoring" Report as well as to re-read the Ft. Worth League of Neighborhoods (FWLN) "Recommendations for policy Changes for Gas Drilling Near Schools" report.

There is a lot of data to take in as well as looking at the methodology and conclusions.  I also try not to take things at face value and check the sources of the information (which is why I cite and link my sources).

So here is the issue;  Holy lots-o-dots Batman!  There's a bat-boat load of oil & gas related activity in the Ft. Worth area! (1)

So it is only natural that the public in and around these sites would question if their health and safety is being impacted.  And, when it comes to their children, as in "ensuring the safety of the 80,000 children who attend FWISD schools (2)" the need to be assured becomes elevated.  So what to do...what to do.

I am critical of bad science because it can cause people to do things that are more detrimental to their health then the thing they they were trying to avoid.  The issue in all of this should not be carbon disulfide.  Carbon disulfide is a non-issue and it is dominating the discussion and taking away from a real dialog which should be; What can we do to make oil & gas activity in and around homes and schools safer and reduce its impact on the environment?

The discussion should be; You want to extract here, then you need to adopt an "Environmentally Systems Drilling Friendly Program" I spoke about in a previous post.  Instead we have a "team of scientists and experts – Dr. Ramon Alvarez, Dr. Melanie Sattler, Dr. DavidSterling, and Carl Weimer – who donated their expertise and time to the League to produce this report (2)" describing a situation of concern that does not exist.

Whether a setback is a prudent idea is not what I am being critical of.  The FWLN report is basing this "one mile setback" on an air dispersion model's finding that carbon disulfide could be found at concentrations over three times the OSHA permissible exposure level (PEL) one mile from an O&G facility. (241 mg/m3 = 78 ppm)

Now reading this, and knowing that a "team of scientists and experts" - two of them Texas University professors - signed off on the findings, one might reasonably conclude; Holy exposure Batman!  The children!

But a closer look at how that number was derived would lead you to a different conclusion; Holy poor science Batman!  That data for carbon disulfide is invalid!

I have tried to present as objective and scientifically based argument as to why this is so in over 24 posts on this topic.  If I have not made my case then either you don't believe me, don't want to believe me, don't want to consider it, or have some other reason to ignore my conclusion as to why the methodology and findings in the Town of Dish Texas and the FWLN reports are wrong.

These blogs are open to anyone who wants to show where my premise, conclusion, or understanding of the science is incorrect, faulty, or wrong.  If I can dish it out (no pun intended) then I sure as better be able to take it.

So it comes down to this.  The FWLN report includes laboratory analysis for carbon disulfide for one single sample:

With the carbon disulfide concentration as:

So the air dispersion model generating Plot 1:

...was based on the analytical report shown above:

And if for no other reason than that - the results of the model and the conclusion for Plot 1 is invalid.  One sample cannot be used to test the null hypothesis that there is a relationship between the ambient air concentration at one location (SUMMA canister for 300 McNaughton Ln.)  and the expected ambient air concentration at another point (one mile out in Plot 1).

One sample is not representative of the air at that location.  Here is what EPA has to say about samples:

Representative: “a sample of a universe or whole (e.g., waste pile, lagoon, ground water) which can be expected to exhibit the average properties of the universe or whole."

Inferences about the population are made from samples selected from the population. For example, the sample mean (or average) is a consistent estimator of the population mean. In general, estimates made from samples tend to more closely approximate the true population parameter as the number of samples increases. The precision of these inferences depends on the theoretical sampling distribution of the statistic that would occur if the sampling process were repeated over and over using the same sampling design and number of samples.

This then leads to:

[a]fter a sample of a certain size, shape, and orientation is obtained in the field (as the primary sample), it is handled, transported, and prepared for analysis. At each stage, changes can occur in the sample (such as the gain or loss of constituents, changes in the particle size distribution, etc.). These changes accumulate as errors throughout the sampling process such that measurements made on relatively small analytical samples (often less than 1 gram) may no longer “represent” the population of interest.  Because sampling and analysis results may be relied upon to make decisions about a waste or media, it is important to understand the sources of the errors introduced at each stage of sampling samples and take steps to minimize or control those errors. In doing so, samples will be sufficiently “representative” of the population from which they are obtained.

When scientists make statements regrading their observations, the concept of precision and bias come into play:

• Precision is a measurement of the closeness of agreement between repeated measurements. 
• Bias is the systematic or consistent over- or underestimation of the true value

Precision is the ability to get the same - or very close - result each and every time you collect or analyze the sample.  Bias, on the other hand, results from a number of problems inherent in sampling and analysis. 

Sampling Bias: 

• Bias can be introduced in the field and the laboratory through the improper selection and use of devices for sampling and subsampling. Bias related to sampling tools can be minimized by ensuring all of the material of interest for the study is accessible by the sampling tool.

• Bias can be introduced through improper design of the sampling plan. Improper sampling design can cause parts of the population of interest to be over- or under-sampled, thereby causing the estimated values to be systematically shifted away from the true values. Bias related to sampling design can be minimized by ensuring the sampling protocol is impartial so there is an equal chance for each part of the waste to be included in the sample over both the spatial and temporal boundaries defined for the study. 

• Bias can be introduced in sampling due to the loss or addition of contaminants during sampling and sample handling. This bias can be controlled using sampling devices made of materials that do not sorb or leach constituents of concern, and by use of careful decontamination and sample handling procedures. For example, agitation or homogenization of samples can cause a loss of volatile constituents, thereby indicating a concentration of volatiles lower than the true value. Proper decontamination of sampling equipment between sample locations or the use of disposable devices, and the use of appropriate sample containers and 

Analytical Bias:

• Analytical (or measurement) bias is a systematic error caused by instrument contamination, calibration drift, or by numerous other causes, such as extraction inefficiency by the solvent, matrix effect, and losses during shipping and handling.

Statistical Bias:

• When the assumptions made about the sampling distribution are not consistent with the underlying population distribution, or
• When the statistical estimator itself is biased.

Because bias is always in play, the number of samples collected (replicates) and the dates/areas (representative) is increased to minimize the impact of these issues.

So how confident in the number 10.8 ppbv is the report's "team of scientists and experts?" How sure are they that 10.8 ppbv represents the true value of the air at that sample point?  I mean. look at all the potential errors that could have impacted it.  Shouldn't at least a duplicate sample have also been collected and analyzed?

It was that one single value that was used to determine the concentration of 78 ppm determined by the model to be in the plume:

Plume extends 1 mile from the source in this graphic. Full extent of plume was in excess of 2 miles. Plot 1 multiples were up to 1000 times the short term health benchmark for carbon disulfide.

How confident would (could) any reputable scientist be if one - and only one - sample - was used in their published research?

For that reason alone, Plot 1 is not valid.

Now, couple that with this:

 Notice that "N" in the very last column?  That's a note from the laboratory:

What the lab is saying is that all the statistical stuff they do - precision & accuracy - was not performed on this sample.  How confident are they in the number 10.8 ppbv?

So there you have it.  Plot 1 was developed using one sample and analyzed on an instrument that was not calibrated for carbon disulfide.

Holy bias Batman!  Plot 1 values are not statistically valid!


Yes Robin, that's what I have been trying to say all along.  The whole enchilada is an example of bad methodology, sampling, and analysis - and the results and conclusion are invalid.


Next post: Air Quality in the Barnett Shale - Part 25: What a statistically valid report looks like.


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Air Quality in the Barnett Shale - Part 23: Fort Worth League of Neighborhoods Report to FWISD

I received a PDF of a photocopy of a report, dated February 2011, dealing with "Recommendations for Policy Changes for Gas Drilling Near Schools."

As you can see, it brings forth a concern regarding carbon disulfide and uses language that completely disregards the concept of dose, which if you have been reading all 20-something of these posts, was the original issue that started me on this topic.

Okay...so again with the carbon disulfide!  What does this report have to say about that chemical?  Reading... reading.... oh...you have got to be kidding me.  Well no wonder! Seems the same sampling method, the same analytical method, the same premise, the same model assumptions, the same poor science was involved in putting this report together.

It's Dr. Sattler's modeling work!  The same methodology and the same premise was used to produce these setback findings as was performed previously for Alisa Rich.  The same faulty logic that she was raked over the coals for in her December Deposition.  The same methodology I have been writing about in this blog as a way to explain why it is not just wrong, but demonstrably wrong.

I have whipped that dispersion model horse enough, as well as TICs, dose, sample size, and everything else that factors into why her premise and its resulting data are wrong, so I will focus on another factor that really needs to be considered when looking at her work and the conclusion she allows to be made.

What really aggravates me about this is that she knows her work does not meet intellectually honest or scientifically sound practices.  She was told this by the lawyer in the Deposition.  Even if she disagreed, the prudent thing to have done was double checked his concerns.  That obviously did not take place.
And now she not only puts her stamp of approval on it, she brings in another academic, Dr. David Sterling, Chair of Environmental and Occupational Health at the University of North Texas, Health Science Center.  And with him on board, her work, her model's predictions, this report's conclusion, is given the seal of scientifically soundness and approval:

These professionals agreed to assess the information available and make recommendations to the FWISD which could be incorporated into future leases.

This means that all three of them looked at her work and saw nothing wrong with it.  How can this be?

Okay, so lets look at it strictly from a logical point of view.  Let's assume that her model is correct - that every reason I have wrote about is immaterial or does not apply.  So logically if the following is true:

And the model predicted:

This would mean that the emission rate from the source - an emission rate that remains constant for 8760 hours - must be producing way in excess of 241 mg/m3 if that amount was found at up to one mile from the source.

Now according to the model, under calm conditions - perfect so to speak - the concentration at 1000 meters from the stack right smack dab down the center, is 0.001 g/m3 at 1 g/s.  So using that same ratio of dilution, the stack would be putting out at least 241000 mg/s or 241 grams/s of carbon disulfide.

That's a heck of a lot of carbon disulfide in and around the stack.  In fact, to get that much carbon disulfide at one mile from the stack, the amount of carbon disulfide in the immediate area would be at a lethal concentration.

Here is what ATSDR has to say about carbon disulfide (241 mg/m3 = 78 ppm):

• OSHA PEL (permissible exposure limit) = 20 ppm (averaged over an8-hour work shift); 30 ppm (acceptable ceiling concentration; 100 ppm (30-minute maximum peak)
• NIOSH IDLH (immediately dangerous to life or health) = 500 ppm
• AIHA ERPG-2 (maximum airborne concentration below which it is believed that nearly all persons could be exposed for up to 1 hour without experiencing or developing irreversible or other serious health effects or symptoms that could impair their abilities to take protective action) = 50 ppm
• Inhalation is the major route of exposure to carbon disulfide. The vapors are readily absorbed by the lungs. The odor threshold is approximately 200 to 1,000 times lower than the OSHA PEL-TWA (20 ppm). Odors of pure or commercial grades of carbon disulfide usually provide adequate warning of hazardous concentrations

So what this is saying - and here is where the logic comes in - If the one mile concentration could get up to as high as 78 ppm, the emission rate "E" necessary to produce that potential concentration at that distance must be considerably above 78 ppm.  If the model she predicted 241 mg/m3 is true, then the consistent output at the stack must be far greater than 78 ppm.  Which means that whenever the source is in operation, more than 78 ppm of carbon disulfide is being put into the air.

So if the model she predicts 241 mg/m3 is true, the output - "E" - must be producing carbon disulfide in abundance in order to push that much carbon disulfide down the plume to a distance of one mile.

And if that were true, people living in and around these sites at less than1000 meters would be constantly smelling an odor, and - most significantly - these oil & gas production sites would have a lot of very sick or dead workers.

And that is just not happening.  Do people complain about odors?  Yes, but at Dr. Sattler's calculated emission rate, the smell would be constant and never ending since the odor threshold is between  0.1 and 0.2 ppm. And if the level at one mile is 3 times the PEL, the workers at the source would be experiencing consistent health related problems.

This is not happening because there IS NO carbon disulfide being produced at these sites above an amount that will exceed an ESL, cause long or short term harm, or produce an odor.  Not at one mile nor next to the site.  None...at any distance around the facility.

So once again, to show why:

• Dr. Sattler's premise that you can "back in" a concentration to obtain the emission rate "E" is wrong.
• Dr. Sattler's positive identification of carbon disulfide - using EPA Method TO14 - is wrong.
• Dr. Sattler's quantification of carbon disulfide - identified by the lab as a TIC - is wrong.

And because these three things are wrong, her model's predictions are wrong - not off by a little - but wrong.

And because her model's predictions are wrong, the conclusion of the report - based on carbon disulfide concentrations - is wrong.

Next post: Air Quality in the Barnett Shale - Part 24: How confident in that 33.6 ug/m3 are you?

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Air Quality in the Barnett Shale - Part 22: Gaussian for one, Gaussian for all

I was driving home from San Antonio so I had a lot of "me" time in the car.  Instead of thinking about non-work related stuff, my brain got busy thinking about the air dispersion model used for the Town of Dish, Texas, and for the "Fort Worth League of Neighborhoods" in their report to the Fort Worth Independent School District.

All of the modeling - modeling based on the science and math behind a Gaussian dispersion - is predicated on assumptions.  Not that there is anything wrong with that, it's just that if the assumption holds true in one part it must also hold true for the rest.

So my mind is mulling this over and over.  The math behind it is daunting, especially for a guy like me, but the premise, now that is something I think I do understand.

So in the Gaussian model, which is what Dr. Sattler uses, the premise is this:

If you know the wind direction, wind speed, stack height, atmospheric conditions, and emission rate, you can estimate the plume shape and concentration of the contaminant exiting the stack at any point within the plume.

It assumes that under fixed conditions for that run - fixed air speed, fixed emission rate, fixed atmospheric conditions, fixed exhaust stack height - the plume will behave in a Gaussian manner, that is, along a fixed center line (wind direction) the plume will behave the same on each side of that line.  What these models are used for is to say, that under the most ideal conditions it would be possible for a receptor so many meters away to be potentially exposed to this much of the contaminant at that stack height and that emission rate.

Since there is nothing we can do about the wind and weather, we can adjust the stack height or adjust the emission rate to decrease the intensity of the plume for that receptor.  The emission rate is often tweaked by adding pollution control devices on the stack or limiting the production the entity can produce.  No business likes to do less production so its mostly pollution control devices that are used - or sometimes - raising the height of the stack.

In order for Dr. Sattler to generate her models, she had to assume a fixed condition as well to plug into the computer model, a model that she says uses the Gaussian formula:

She had wind and atmospheric conditions for the day of sampling, so those could be plugged in.  She could reasonably estimate the stack hight for the compressors.  What she didn't have was the actual emission rate.  So it was her reasoning, that if she had the concentration from some point in the plume, she could back in that data and calculate the emission rate that must have been in place to generate that particular concentration under these known conditions (wind speed, direction, atmospheric, stack height, plume location "y").

Now this is completely reasonable in approach.  However it is only reasonable if you assume Gaussian dispersion was taking place.  The model is for Gaussian dispersion, so to calculate an emission rate "E", Gaussian dispersion must be in place for the sample "C" used to back in to the formula.

Again, there is nothing wrong with this premise, as long as a Gaussian dispersion was in operation when the sample was collected.  In order to back in the concentration "C" to get the emission rate "E", Dr. Sattler had to have assumed Gaussian dispersion was in place, since she used a Gaussian formula to calculate the emission rate "E."

So if Gaussian dispersion was in place, and a Gaussian formula was used to calculate the emission rate "E", then the other premise of the Gaussian model is also in place as well:

That at a given emission rate "E" and a wind speed "U", and atmospheric conditions "S" and a stack height "H", somewhere on either side of that center line at location "y" you will find the contaminant to be at concentration "C."

That's when it hit me.

Nothing else is in play here in these Gaussian models.  The chemical's properties, the impact of other agents, pooling, condensing, degradation, vortexes.. they do not exist for purposes of generating these plume models.  It looks at ideal conditions to generate the modeled plume.  The model predicts maximum distance where a particular concentration of the chemical might reasonably be found.

So to "back in" the actual concentration found in a canister, the assumption must be that nothing but a Gaussian plume was being produced when the contaminant was sampled.

If that were the case, the amount of contaminants found in each canisters would be proportional, since the emission rate was steady as was everything else.  Each canister was exposed to the same wind speed "U", the same wind direction "Center Line", the same atmospheric conditions "S", and the same stack height "H".  So taking the location of the canister "y" and the concentration of the contaminant "C" and backing it in to the formula would give you "E".  That's what Dr. Sattler did because that's what she said she did in her deposition.

And with that calculated emission rate "E" she was then able to model the air for 8760 individual plumes - the number of hours in a year for which she had historical data for "U" and "S."  With that data, the emission rate "E", and the estimated stack height "H" - she was able to plug all of that into the model, and using the Gaussian plume formula, calculate both the maximum distance where the dispersion model's plume would show a concentration above a threshold (she used the ESL) as well as calculate the highest possible concentration the source could theoretically produce to which a receptor (citizen in the Town of Dish) might be exposed to.

And that's just what she did for the report, producing Table 2:

Brilliant!  Except for one little bit of a problem.  If the calculated emission rate "E" was determined by backing in the concentration "C" in to the formula, it would produce a theoretical concentration (which she averaged in columns 2 and 5).  If that holds true, then that same emission rate "E" would also be able to produce the actual concentrations in canisters 1 - 6 shown in Table 1.

If it can produce a theoretical, it should also be able to reproduce the actual - since the emission rate "E" was derived from that particular actual data.

This means that canister with the highest amount of benzene - canister 4 - must have been located in the Gaussian plume at a location "y" where the benzene would theoretically be the highest (closer to the center line) when compared to all the other canisters.  Because canister 4 has the highest benzene - because of location "y" - the model holds that at a constant emission rate "E" for the other contaminants was in play as well.

For canister 4 to produce the highest benzene concentration its location in the plume would also produce the highest concentrations for all the other contaminants. Regardless of what "E" is calculated for each contaminant, that "E" was in effect for each canister at exactly the same rate for the six contaminants being discharged on that sample day.  If any of the parameters fluctuated at any time, that impact was felt by all.  The same with wind speed, wind direction, and atmospheric conditions.  The same with stack height.  Each canister was placed and collected under the exact same conditions.  Each canister had to be in the same plume when Dr. Sattler backed in data to generate that emission rate "E."  The conditions producing the actual amount of contaminants in the six canisters must be the same if Gaussian dispersion was in play.

Unless it wasn't.

And if you look at Table 2, you will clearly see it was not.  So if Gaussian dispersion was not taking place that day, then how can you back in the data to calculate an emission rate from a formula that is based on showing a Gaussian dispersion?  If the emission rate "E" that Dr. Sattler calculated cannot be used to calculate the actual concentrations seen, then how can it be used to calculate a theoretical maximum?

And if you ignore that by explaining it away saying the actual concentrations in the six canisters were impacted by other conditions, then you are admitting that Gaussian dispersion was not in play, therefore an emission rate "E" cannot be calculated since no other variables are considered in the formula.

And if you say the sample was collected over 24 hours and was diluted, well that doesn't affect Gaussian dispersion since all the samples were collected for that same period and would have been similarly diluted.

And if you say the wind conditions changed for each of the canisters throughout the day impacting the concentrations of some of the contaminants getting to the canisters, well then, you are really grasping at straws.  And besides, if that's the case, how do you know what concentration to back in to the model?

There are two equally valid reasons why Dr. Sattler's modeling and the subsequent "averaged concentrations" are incorrect:

1. It is impossible to calculate the exact concentration attached to a particular "y" to back into the model because - in real life - the plume is consistently changing over time.  Gaussian modeling assumes perfect and steady conditions in order to produce a plume.  So "E" can never accurately be calculated by backing in the concentration.
2. The concentrations captured in the six canisters came from multiple sources and not from one source as modeled.  In this case, backing those concentrations into the model will always generate an emission rate "E" that is higher than what it is.  This incorrect "E" will then generate plumes and concentrations that are also too high.

Bottom line is this:

If you assume Gaussian dispersion modeling can reasonably model possible concentrations within a plume....

....and you assume that the formula for ground level concentrations is correct:

....and you agree that the canisters were all under the same wind speed, wind direction, and atmospheric conditions...

....and the emission rate "E" was exactly the same for each of the contaminants detected in each of the six canisters...

....and you accept that the emission rate, along with all the other parameters, plugged into that formula will produce a plume that is Gaussian (see graphic at the beginning)....

....then the plume produced from that calculated emission rate "E" must accurately match the actual concentrations found in the six canisters in and around that modeled plume....

...and if the modeled plume - using to emission rate obtained by backing in the actual concentration - does not reproduce the actual concentration that were used to derive it....

....then either the model is wrong....

...or the samples have been impacted by conditions not considered in a Gaussian model....

...which means that the actual concentration found in the six canisters cannot be used to calculate the emission rate of the source....

....which means the data presented in Table 2 of the report, as well as any other report produced using backed in data to find an emission rate, is incorrect.

Bottom-bottom line.

As it stands now, Dr. Sattler's methodology of "backed in" data cannot be used to calculate an emission rate in order to generate plume data to show modeled average concentration levels and/or determine the proper setback for a source.

Bottom-bottom-bottom line:

You cannot use non-Gaussian data to determine the value needed in a formula that produces a Gaussian model.


Next post: The Fort Worth League of Neighborhoods Report to FWISD - Different place, same drummer


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Air Quality in the Barnett Shale - Part 21: If you assume E to be...

So in my last post I attempted to explain how the Gaussian model works based on my limited knowledge of the math - or math in general for that matter!

I am pretty sure that to "back in" to the model, the concentration "C" to obtain the emission rate "E," you have to know the values for all the other parameters in the formula:

So Dr. Sattler knows "C", she knows the distance from the stack where the sample was collected - "x".  She has the wind speed "U" and the meteorological data for the two S parameters.  She can estimate the height of the stack "H" and she knows, pi.  The only variable she does not know is "y" which needs to be calculated from the center line - required if the Gaussian principle is to be true - and the distance from the source "x."

The only way to get "y" is to fix the center line in one direction - which would be the wind direction - in order for the Gaussian model to hold true and a dispersion plume to be generated:

At a fixed wind direction, the stack at time = 0 will have the x,y coordinates of 0,0.  "y" is some distance from the stack - one side or the other (does not matter in a Gaussian model - both sides assumed equal in concentration) on the y-coordinate of the graph.

So in the Town of Dish example, here is what we are looking at.  Lets assume the wind is blowing in a Northwest direction.  That would be the center line.

Now I am going to orientate the map so it is in the same direction as the "Top View" plume graphic above:

If we know where the center line from the source is to be placed (wind direction), we can get the x,y coordinates.  With that data, the emission rate "E" can be calculated according to Dr. Sattler.

But that creates a problem....If we assume the Gaussian model to be true, and we assume the "backed in" data can calculate an emission rate "E", and the Gaussian model predicts a concentration at an x,y coordinate based on a wind speed "U" of meters per second and an emission rate "E" of grams per second, then logic would hold that the highest level of benzene would also show the highest levels of the other constituents in that sample point.

Look at Table 1:

In order to claim all of the contaminants in the six canisters came from one source at x,y = 0,0...then the model would predict similar ratios in every sample.  If you were to argue that the wind direction changed - thereby changing the center line - the same principle would hold true under the Gaussian model, that is, if you had low benzene you would also have low carbon disulfide, or if you had high carbon disulfide and low benzene in one sample you would have a similar ratio in the rest.  That's if you consider the Gaussian model to be true.

So either the Gaussian model is wrong in its "heart of the calculation" or the samples contain concentrations of chemicals from more than one source - which - if that the case, the emission rate "E" that was calculated is way too high thereby making all the dispersion model maps and concentrations calculated from it too high as well.

Or maybe wind direction moves all over the place changing the concentrations in the x,y coordinates where the samples were collected over a 24 hour period making it impossible to accurately "back in" to the model to get an emission rate since you would never know where the center line was.

I wonder which one it could be...

As ignorant as I most likely am on dispersion modeling, Dr. Sattler's premise and her emission calculations and dispersion modeling based on that value is wrong.  And that's not even bringing into the overall equation the use of TICs and the fact that all of this is based on a one time sampling event (n=1).

Somethin' aint right about all this.


Next Post: Air Quality in the Barnett Shale - Part 22: Gaussian for one, Gaussian for all.
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