Today’s webinar will focus on using 3D visualization to create targeted excavation and injection plans. With that, I’d like to introduce our presenters for today.

We are pleased to have with us Jim Depa, principal geologist at Swenson-Marzec and Associates. Jim Depa has more than 18 years of experience in the environmental consulting field and specializes in creating 3D statistically based visualizations from subsurface data. He has created data deliverables on over 400 environmental investigation projects in 44 states and 7 countries from routine 3D visuals to multi-million dollar design remedies. Specifically, he has helped design over half dozen thermal remediation systems, calculated the in-situ contaminant mass in soil from one of the largest petroleum spills in United States history, and provided exhibits for four separate environmental lawsuits.

We’re also pleased to have with us today Juan Rincón, project manager in the research and development department at Regenesis. Juan Rincón leads the FluxTracer program and oversees laboratory services supporting advanced environmental remediation technologies at Regenesis. He previously worked in the remediation services division or RRS as an environmental staff scientist where he conducted in situ remedial applications across the United States. Applying technologies such as in-situ chemical reduction, in-situ chemical oxidation, biological enhancement, and sorption to address a range of contaminants in soil and groundwater, including petroleum hydrocarbons, chlorinated solvents, and PFAS.

That concludes our introduction, so now I will hand things over to Jim Depa to get us started.

Thanks, Dane. And as Dane mentioned, the talk that I’m going to give today is about sort of building targeted remediation strategies using both the 3D visualization and high resolution tools. And this is really focused on just kind of treating source area remediations.

First, what is the trend in source area remediation?

As you can see from this chart from the Superfund Remedy Report from the US EPA, institutional controls are still number one, kind of shown in green there. And that’s not really surprising as sort of institutional controls are the sort of costly option, but it’s certainly not an option for every type of spill and every type of situation.

Treatment, kind of shown in red there, is number three, but it’s been fairly consistent over the last several decades. Treatment options can come in a variety of different types, such as you know biological and injections and soil mixing or chemical mixing with different amendments or thermal.

We’re going to discuss kind of three different strategies, and this first one is going to be using injection.

So first, the problem. A lot of times, injection strategies rely solely on monitoring well information or limited soil sampling data for treatment design.

And this can be a problem because typically you would have minimal data, sort of no verticalities to the data unless you have well nests, sort of a limited definition of geologic impacts, and which can lead to injections occurring at suboptimal locations and sort of a picture of that is shown in the boring log here where we have a well screened across several geologic units in silt, sand and clay.

Some of those units are showing odor so you have some indication of where there’s contamination but really you know not a lot of good data on exactly where to to inject amendments.

Ideally you want to have you know sites where you have monitoring well screens if you’re injecting into the groundwater, as this is shown here, but as most of us probably know, these are kind of few and far between as putting wellness in a lot of locations is quite costly.

So the solution is basically to create targeted injection plans using both high resolution data and 3D statistical modeling.

And sort of a cross section is shown there where we can determine where we have both clay and sandy soils and where the contamination is located and this is basically from using high resolution data and this allows for because it collects tens of thousands of data points really get really good vertical data distribution that you could determine where you have both your storage and transport zones and this really means that injection locations and depths can be optimized.

So what are some of the drilling tools that we can use to basically collect this data to allow for the completion of injection plans.

One is the membrane interface probe or MIP, which is basically for delineating and investigation of volatile contaminants like petroleum or chlorinated solvents, or the ultraviolet optical screening tool by Dakota, usually called UVOST, which is basically for investigating free-phase petroleum impacts.

There’s also a competing tool called the OIP or image profiler by GeoProbe.

They operate on similar principles but they are slightly different.

And then we’ll also show sort of a traditional soil sampling option as the third case study and we’re all probably familiar with collecting soil samples and analyzing for contaminants using a laboratory.

I just like to also point out that both the Member Interface Probe and UVOS tool as well as the OLIP collect hydraulic profiling data simultaneously which basically at the same time injects a small amount of water into the subsurface and measures the amount of pressure required to inject that water.

So you get a really good sense of the permeability of the subsurface and really understand where your storage and transport zones are.

So first the targeted injection plan from some membrane interface probe data.

This was a former gas station where the contaminant of concern was gasoline.

so your B-tex compounds and naphthalene.

The tool we used here was the membrane interface probe, which also had the hydraulic profiling tool.

And the strategy was injection of amendments.

And the deliverables provided on this project were both a 3D model, which we’ll get into, and a targeted injection plan.

So first, the 3D model, we’ve got the locations of the MIP borings here shown in plan view.

And we’ll kind of rotate this and show this in 3D.

And if you were at the last Regenesis presentation several months ago, this animation was shown, but I’m going to go a little bit more into depth during this presentation.

So first we kind of show where we have our highest PID results from the membrane interface probe, showing sort of the source area.

And then we’ll kind of lower it down from 5 million microvolts, which is what the tool measures in, so voltage, down to 2 and 1 half, and then down to a million, which is the extent of soil that is going to be treated.

We can see using the 3D visualization, it’s really sort of illuminates where the impacts are located.

We could also put on a 3D fence of the geologic data from the hydraulic profiling tool, showing the higher injection pressure areas shown in gray and the lower injection pressures in blue, indicating where we likely have more clayey and more sandy soils.

We could put on a simulated injection plan here that mirrors the 1 million PID plume and these are at 10 foot centers and at half a foot vertical intervals.

We could see how that sort of matches up exactly with that 1 million PID plume.

And we could also look at what the HPT pressure is at each of those injection locations as and this really shows how many of these locations are in those higher pressure clay zones and that is really important information to have when when designing an injection plan and of course these 3d visuals are really nice and I think they can present the problem well to an audience but what you really need is the data and that’s what we can also provide first a map of obviously where these injection points are located once again at 10 foot centers and showing that we would need 98 points to sort of target this this 1 million plume, but also all the data behind those injection points.

What the injection point number is, what the coordinate is, the ground surface, the depth, the elevation, and the HBT pressure and PID reading at each of those points.

This is for every every that was shown in that 3D visual so you could see how you know the 3D plan really shows in whole what was going to be remediating but really this is what could be brought out into the field to be used to implement the plan but I also wanted to show that these plans can be malleable and and can be modified to sort of fit the need for your site so this is our 1 million plume and we’ll show sort of five different different scenarios and this first scenario is of what we showed previously a one million target with half a foot vertical spacing across the whole plume but maybe that’s too many injection points and the project budget can’t handle it here’s at one foot vertical spacings so it’s sort of the same number of borings but we’re gonna do one foot vertical spacings now or maybe we want to basically target those higher pressure zones with half a foot vertical interval and the sandy lower pressure zones as at foot. So we could sort of modify it based on the HPT injection pressure.

Or we might want to sort of really just go after those really high source areas that five million plume and really shrink the number of locations and borings and just sort of hit it where it’s the the worst.

Or maybe we’re going to excavate the first top 15 feet and then only target injections below 15 feet and just kind of show what that might look like as well.

And once again, we could kind of show then what the summary is for each of those different scenarios.

The half a foot vertical spacing, the number of borings, and the injection points.

The scenario two, which basically reduces the injection points by half by going from a half a foot to one foot vertical spacing.

Scenario three was basically modifying the plan to have the half a foot vertical spacing where the HPT pressure was high.

So that would be targeting the clay impacts with closer vertical spacing.

Option four was sort of the one that we basically are just targeting the five million plume and really reducing a number of points and number of borings, or just targeting the deeper soils in scenario five.

So I think these injection plans really show that, you know, they can be modified and really customized to really suit the project budget and be optimized to what the site really needs.

Second scenario is offsite disposal or excavation.

And we could see that the trend in the industry is that it’s been slightly increasing for the past sort of 20 years.

And why, I think this is because clients a lot of times like excavation because of the speed at which it occurs and the certainty, the absolute certainty that when you excavate, you remove all the contaminated soil and you have a clean site.

And it’s usually a lot of times faster than injection options or soil mixing options, which take time.

However, a lot of times, the problem with excavations is that they often grow a lot larger than anticipated and then become a lot more costly than was initially planned.

And I’ve seen this countless times at sites.

And this is due to a lot of problems.

Basically you have inadequate delineation at first, which means you have an incomplete understanding of the sloping or benching that might be required, which leads to a big miscalculation of how much overburdened soils you’re going to remove.

And it’s just countless times when an excavation is planned and the final numbers come in about how much soil has been removed, that a lot of times clients are unhappy with, because almost every time the excavation is largely anticipated.

The solution for this is basically building a 3D excavation plan using both high-res data and 3D statistical modeling.

You can see there’s an example of an excavation plan that we kind of put together for a client who was leaning in that direction to remove some contaminated soils, which at a site we’ll show thirdly.

but you can see the huge volume of soil that would have required to excavate.

One truckload of soil is about 15 cubic yards, so this would have been nearly a thousand trucks of soil, just an incomprehensibly large excavation that quickly we were gonna pivot to another option.

But basically, these excavation plans can visualize the sidewalls at any slope desired, which allows for a really good calculation of the amount of overburden or the volume of soil you’re going to move and then an Aerial extent of the excavation and a size of that area.

So we’ll kind of go into one of these Excavation plans using that was was done with you’ve lost data This was actually an existing gas station where we found free net phrase elmap on the subsurface You can kind of see that in the image there and we use the ultraviolet optical screening tool or you’ve lost by Dakota to delineate this spill.

The remediation strategy here was an excavation and we provided both a 3D model volume calculations and CAD and GIS shape files for use to design this plan.

So first the 3D visual.

We’ve got our footprint of where the impacts are located and we’ll We’ll turn this to view it in 3D.

We can see where most of those soil impacts are located, which is approximately 14 to 18 feet in depth.

You could see the feet above mean sea level there.

I really want to say where this site’s located, but it’s obviously in the western United States where it’s quite a bit higher in elevation.

Here’s our soils above 5% response emitter, which is what the tool measures in.

And it’s a fairly small area, 15 cubic yards of soil.

But obviously we’ve got to, if we need to excavate that, we need to calculate a slope.

And this is about a 45 degree slope, 40 degree slope from vertical.

So about a one-to-one ratio stepping down.

Or we can do a 15 degree slope.

So not quite vertical sidewalls.

And we get 409 cubic yards of soil in this.

Or if we do near vertical sidewalls, about five feet from vertical, We’ve got 302 cubic yards of soil that we would need to excavate.

So this tool allows for sort of those calculations of the amount of overburden.

And you could also basically put the ISO lines on there for CAD and kind of shown that here where you can see it from a top-down view and create shape files at that 40-degree slope, 15-degree slope, or 5-degree slope.

then also export those ISO lines into CAD as a DWG for use in the field.

And then kind of here’s a summary of all three of those scenarios.

That first one was a 40 degree angle from vertical which is about a near one-to-one slope one foot down one foot over and the volume and area of what that would be.

at 15 degrees, which is quite steep sidewalls, about 75 degrees from horizontal, and then nearly horizontal sidewalls, five degrees from vertical, and what that volume would be.

And I just kind of wanted to illustrate how different these volumes and areas are with these different angles.

And of course, the angle of your excavation is going to mostly be on the geology of the site.

If you’re in real dense lay modeling type clay soils, you could probably get away with a five degree or even a close to zero degree vertical sidewall and you might have a small excavation like that.

However, if you’re in more sandier soils, it might be closer to a one-to-one slope where you’re gonna have that larger excavation.

So best to know what you’re dealing with before you start an excavation and this tool can really, really assist with that.

it might cause you to pivot to do something else if you start calculating some numbers that are really not suitable for the project.

And finally, we’re going to talk about another source area treatment remedy, and this is going to be soil mixing using chemical amendments.

And once again, that treatment option is in red, and we’re going to use that underline here, we’re going to use chemical soil mixing at this third and final site.

So here we use traditional soil sampling data.

This was a former metal fabricator and the contaminant here was trichloroethene or TCE.

Once again, we use traditional soil sampling direct push tools to collect our data.

In-situ soil mixing was the strategy and we delivered both a 3D model, various maps, volume calculations, mass estimates, and a remedial plan.

And I’d like to note that this project was performed by Jacob and Heffner Associates.

This was a company I worked for last year for several years.

They’re a really great civil company with a small and large mill arm.

And they’ve sort of given me permission to kind of present this data today.

So first, the 3D model.

Here’s our footprint of the TCE impacts.

And those four rectangles are essentially above-ground storage tanks that used to be at the site.

And that red tank was sort of the offending tank that held the metal degreaser, the TCE.

and that is the one that leaked. And there’s our footprint in soil.

That blue is an active water line that we actually had to abandon before we did this soil mixing project.

Those are the soil sample locations with the concentration of TCE shown.

We had some monstrous concentrations here, 49 ,000 milligrams per kilogram, I think was the highest sample.

And that yellow mass is about 15 milligrams per kilogram, and that was the extent of soil that needed to be treated.

And if you could kind of see from this animation here, the contamination extended to about 22 to 23 feet depth at its deepest, but the vast majority of it was between about 15 and 20 feet.

But before we get into the soil mixing plan, which was the strategy that we implemented at this site, I wanted to show some of the other deliverables that can be created when you have actual soil sampling analytical data.

First we created some plan view maps at various depths showing where the TCE impacts in soil were located.

And I wanted to just reiterate that these were created really efficiently using some code in the 3D modeling software.

Basically the press of a button you can you can make these these slices and for easily creation into figures.

We could also calculate the volumes of impacted soil at any concentration.

So we have that both in graphical view on the left side here and in tabular view on the right side where we have a TC concentration from 5 to 30 ,000 and the of volume of soil at each of those concentrations.

Why each of those in red is shown is that 15 milligrams per kilogram, which is our objective at the site, is the industrial commercial remedial objectives.

So if we meet that objective, we don’t need to have any encumbrances on the property, no institutional controls are needed. That is sort of our remedial goal for the site.

But that thousand milligrams per kilogram is the soil saturation limit for this particular site in in this particular state.

So we have to remove those soils.

There’s no sort of ifs, ands, or buts about it.

That soil has to be treated or removed or gotten down below 1 ,000 milligrams per kilogram.

And these illustrations really help the client and the consultant to understand how much contaminated soil we’re dealing with.

At that 1 ,000 milligrams per kilogram, we’re dealing with 1 ,700 cubic yards of soil, And down to 15, we’re almost at 3 ,700 cubic yards.

And this gives you a general sense of, is this gonna be a $100 ,000 project or a $5 million project?

And should we move up to that 15 level to not have any encumbrance of the property?

And that is what the client chose, but this really sort of outlines it in black and white, how much contamination are we dealing with?

Importantly as well, we could calculate the amount of mass of T.C. in the soil.

And at this site we had fill at the very top from about two feet down and then a silty clay from Austrian deposits and then clay till from glacial deposits.

And what we found was there’s about 62 ,000 pounds of T.C.

in the subsurface and the vast majority of that, over 95 percent of it, was in the silty clay and clay till.

So we knew that an injection wasn’t likely to work here because the clays were just so dense.

That’s why we basically went to a soil mixing strategy because of the amount of contamination and that there was so much in the both the silted clay and clay till.

Now back to our 3D model showing where the impacts are located about 15 milligrams per kilogram and we were to use 3D modeling to generate a concise soil mixing plan basically of five by five foot squares of where we were going to be mixing and as you saw down there this was approved by the regulatory agency.

They were actually shown this model and got comfort that we were mixing in the right locations to the soils and it was accepted and implemented a couple years ago and I’m happy to say that concentrations were quite down last time we collected confirmation samples.

But not just a 3D model, obviously a 3D model is nice but using that 3D model can be dissected to create all different types of maps including this one which is basically a 5×5 grid showing the estimated TCE mass each of those five by five cells and the contractor really appreciated this because they were able to sort of you know create a dosing plan that sort of matched our conceptual site model.

Additionally we showed this to the contractor as well and showing each five by five foot square how deep they had to mix at each of those locations and always better to do elevation than depth because the depth can obviously change a little bit over time so this basically This told them exactly the bottom elevation of each treatment area.

The company that did this was Redox Tech, and they did a fantastic job for us.

On the mixer, they actually had a GPS unit, so they weren’t guessing how far the mixing head was down.

They actually could tell to the tenth of a foot how deep that mixing head was down, and when they knew they were completed.

And then here is that soil mixing plan that was completed both by Jacob Hefner and Redox Tech, essentially taking our 5×5 foot block model and creating some larger dimensions, some volumes, estimated mass, and then you can see sort of on the far right there the amount of super sacs of zero van iron required that was mixed into the soil.

There’s this this this was a whole presentation at Patel and two or three years ago and In it in and of itself this this whole project is was was quite interesting 3d modeling programs.

I use earth volumetric studio by ctech I think it’s it’s a really good software and everything you’ve seen today is was done by earth volumetric studio Cost is about seven thousand a year and that’s one single user and the cost really goes up pretty quickly once your company size gets larger and larger.

So that’s kind of how they price it. Rockworks by Rockware is sort of a cheaper option, only about $5 ,000 per license.

I think it’s sort of, I call it the poor man’s EBS.

I think Earth Volumetric Studios is better than Rockworks, but certainly it has its place as well.

And then LeapFrog by LeapFrog Geo by Sequent It’s sort of, I might even call it the industry standard.

It’s being used, I think, by a lot of the bigger companies.

It’s more expensive.

I think even the prices even go considerably up higher once you start getting more licenses in companies and for larger companies.

But still very good software, but I really can’t speak much to it because I am not a user of ReefProGEO.

Some aerial photography resources.

Everyone’s probably aware of Google Earth.

They have great free aerial photos.

Not everybody might be aware of a Nearmap.

This was an Australian company that I think recently went public and is now owned by an American company.

They have really good high resolution aerial photos that they collect all the time.

And when I say high resolution, I mean you can actually see monitoring walls at sites.

And I’ve actually pinpointed where some monitoring walls are for a client one time when I downloaded this aerial photography.

It’s not free, but it’s also not super expensive.

And then if you need a more up-to-date aerial photo of your site, my previous employer, Jacob and Hepburn, does great drone surveys, and they give current georeferenced high-revolution aerial photos.

And of course, as you go from left to right, you have increasing costs.

And then ground surface elevation, a lot of these sites that you’ve seen today had really ground surface elevation data, which can be.

It’s not always essential, but sometimes it is essential for a good 3D model. You can get elevation data off of Google Earth. It’s free.

It’s usually not great. I don’t recommend it, but if that’s all you got, then use it.

Your next best option is the USGS 3D Elevation Program, or 3DEP.

This has free high-resolution LiDAR data that’s collected, I would say generally every five years, some areas of the country, it’s collected more frequently, others less.

This is fantastic data.

The government has spent millions of dollars collecting LiDAR data consistently across the entire United States.

It does take some processing to make it into usable format.

If you need help, I can help with that.

Know that it’s out there.

And then, of course, if you need a survey at your site that’s more up to date, you can do a drone survey.

A lot of companies do it, but my previous employer, Jake Benhefner, does do drone surveys and they do a really good job, and that gets you basically current LiDAR data.

And of course, moving from left to right again, you get increasing resolution, but it’s also obviously increasing price for the drone survey.

And then finally, just wanted to sort of reiterate that this is not something we’ve done once or twice, created 3D deliverables or a real design from field data on now over 440 projects across the United States and there’s my contact information there if you have sort of any questions on how a 3D visual might assist your project.

And with that, I will turn it over to Juan Rincon of Regenesis.

So, thank you very much.

Thank you, Jim. Great presentation.

We’ll jump now into mass flux.

This is field comparison of sites where we have measured CVOC as well as PFAS, and how this has affected the design and implementation of permeable reactive or permeable sorptive barriers.

This is an initial data point on a site where we deployed mass flux measurement, but you can see here is in the y-axis the depth, this is usually below top of the casing, and the top x-axis is the Darcy velocity in centimeters per day.

Let’s all remember that Darcy velocity is actually telling us the amount of water that is moving through instead of the actual velocity.

to convert these to seepage velocity will need effective porosity.

But what I want to highlight here is how these variability in Darcy velocities observed in this specific site for this specific well, where there is values going from 3 up to 6, closer to 7 centimeters per day.

Now, if I were to tell you that in this site there was contamination of chlorinated solvents, the question will be now, where would you expect most of the mass flux to move through?

And you might think maybe through where the highest Darcy velocity is, right?

Where most of the water is moving through.

Well, we measure mass flux for PC, TCE, and CSDC for this specific site.

And this is the data.

This is in the bottom x-axis, units of milligrams per square meter per day.

And there are two significant peaks observed.

And we can look at the peak at the low end in the 60 to 65 feet.

We’ll see, yes, we were right.

There is some mass flux of PC moving through this zone where there is a spike in Darcy, but this is not the highest peak.

The highest peak is located actually between the 45 and 50 feet.

And this peak is even more, it’s even bigger compared to the peak down below.

Now this is telling us where there is a relationship between Darcy velocity and mass flux, but it can be complicated if we don’t have an actual measurement.

and this presentation will discuss three main topics.

First, flux-based conceptual site models and some examples.

Then we’ll move into a mass flux measurement, how it’s measured, how can be estimated, and what are the differences between the two, and then two case studies.

This is a visual, an idealized scenario based on the ITRC guidance of 2010.

What we see here is three different layers, starting from a low, medium, and high DRC layers from bottom to top.

Of course, there is some mass here that was, let’s say, forward-diffused in the low Darcy layer, in what we will call a more impermeable zone.

And then this mass is back-diffused and transported through advection, through the medium and high Darcy zones.

What we see here is one of the most clear examples of what’s causing most of the plumes nowadays to last for decades.

Now, there is this back-diffusing, and this is causing serving as a secondary source zone and therefore providing mass into these layers that then create a dilute plume.

Now, the first part for here, after of course all the site characterization, let’s say active sampling and pump-as-lock test is how do we estimate mass flux?

And for this we’ll provide this data where we are seeing how the mass flux in terms of the top, let’s say X axis from low to high behaves in the different units.

Now, in this case, it seems to correlate, low Darcy seems to correlate with a low mass flux and a high Darcy with a high mass flux.

And this is just to exemplify what is the correlation or a potential correlation from a conceptual side model standpoint.

Now, from these, we’ll first target what is the treatment zone.

And of course, the treatment zone has to be where most of the mass is moving, in this case, medium and high zone.

But even in between these two layers, there are two different high peaks, two different maximum values that we will refer as A and B, as you can see in this figure.

The next part is the modeling.

So how do we implement or how do we transport these values into what is the dosing, what is the longevity, and where to inject?

And for that, we’ll do modeling for this example where we are modeling the invariant behavior.

So how the contaminant incoming mass flux, once it hits the barrier, what is gonna be the dynamics?

What are the byproducts generation?

And of course, over a given period of time, certifying that there is not gonna be breakthrough over this period of time.

And for that, we divided in the two peaks.

So for peak A, this is a barrier thickness.

You see this shaded area where PRB will be in place.

And there is an incoming mass flux.

You can see, for example, in this case, the main contaminant will be the black dashed line, and there will be a decrease in mass flux.

There could be a generation of byproducts.

For example, if this was BCE and we were doing reductive processes, it could be Cs or TCE, and these will also be created in between the barrier, and then no breakthrough will be observed over a given time.

Let’s say this barrier is designed for 10, 20 years.

Once we do the modeling for the peak B, you can see the same shaded area.

the decrease in the mass flux generation of byproducts but not break through over the same period of time.

Something you might notice here is that there is a darker color for the peak, for the barrier in peak B and this implies the higher dosing.

The reason for that of course is that, well, amendment dosing for peak B is higher than peak A and it’s because of course the mass flux, incoming mass flux for peak B is higher than in peak A.

So delineating the mass flux in a vertical as well as transect zone allows to deliver a targeted approach.

The next part will be the emplacement. The emplacement in this case will be a direct push injection from bottom to top.

So we’ll start in the zone that will refer as zone A or medium Darcy.

Then the amendment will be distributed in this specific process.

It’s key to ensure proper distribution and this is usually with temporal piezometers or monitoring wells observing how the distribution of the amendments occur.

After that we’ll move up to the high Darcy layer where higher dosing will be emplaced and ensure that our barrier will have the longevity that we estimated initially with a dosing calculated before. And then how can we measure these mass flux?

So we already look how the mass flux is applies into a remedial design, but how this is calculated, first part we’ll look into the most common estimations which come through active sampling.

So through active sampling, you get a concentration at a given depth.

And then of course this concentration is key to determine if your well is under compliance, as well as delineating your plume.

But with that, you can also calculate mass flux.

And mass flux is calculated by multiplying this concentration times the Darcy velocity.

Now the Darcy velocity in these kind of scenarios or initial estimates is estimated based on slug or pump test, which provides hydraulic conductivity times the hydraulic gradient.

Therefore, all of these measurements provide an average estimation that can be over a screen, as Jim was mentioning, that can be 10 or up to 30 feet long in some cases.

This is an average estimation.

How do we at Regenesis prefer to obtain mass flux data, high resolution mass flux data?

This is through flux meters.

And these flux meters are deployed over the entire screen section.

They are deployed and left over a given period of time.

Therefore it’s a passive measurement.

Over this period of time, there are two processes occurring.

First, the contaminant is sorb.

The incoming mass flux goes through the media and is sorb to the media.

And then there are preloaded tracers.

So these preloaded tracers are desorbed or elute through the media.

And that allows to estimate Darcy velocity from the contaminant sorbent site, we estimate the mass flux.

So this shaded area is representing the mass flux that moved through the device, crossing it over a given deployment time and providing a resolution.

Now the resolution that we usually provide in these kinds of estimates is a one-foot resolution you’ll obtain, in this case, Darcy velocity and mass flux data at one foot or two foot resolution.

And this provides clear guidance into the decisions taken for the design approach.

So this is providing an improvement regarding two main aspects.

First, temporal resolution.

This is providing a deployment time, a passive method that provides increased temporal resolution.

And you can see here in the bluish shaded area.

But the second and most important is the vertical resolution.

Now, we can delineate in a single screen section what is the mass distribution, what is this high maxima flux, and where do we have to target our approach.

We’ll discuss now two case studies.

Now, this first case study, La Mirada site, will focus on the heterogeneity of the site.

This will not focus on the design, per se, of a reactive barrier or an absorptive barrier, but more how the data collected through flux meters helped to increase or improve the conceptual site model.

And this is the site that you can see, there is a storage tank, PC storage tank that leaked over time, creating a plume that was moving towards the Northwest side.

And there are two monitoring wells.

In one of those wells, FluxTracers were deployed.

And this is the deployment, of course, FluxTracers, which is the flux meter that we offer at Regenesis, are sent ready to be deployed.

It’s an easy deployment.

They are canisters that are two foot long.

They are deployed.

Then after two weeks, they were retrieved, sent back to the lab, which allows for an easy installment, retrieval, and short processing.

Then once they are in the lab, we are in charge of the breakdown of the devices, as well as the sampling, analysis, and reporting.

And this is the data that we observed or collected at this site.

So this plot you might already be a bit familiar with it.

This is the one I show in my first slide.

So we have in the bottom x-axis mass flux in mass over area over time.

Top x-axis is Darcy velocity in centimeters per day.

The y-axis is the depth, in this case, below the top of the casing.

We see here Darcy velocity variations.

Average is four, there is one peak at six.

And the PC, as we mentioned in the first slide, the PC has two maximum peaks that we observe in this site.

Now, the difference between why or the reason when we are looking into this, why the Darcy is behaving like that compared to the mass flux, for that we need to look into a deletology is the first standpoint.

But before that, we want to analyze here.

There is a peak one and peak two.

This peak one is creating a mass flux of about 19, while the Darcy is about four centimeters per day, while peak 2 has a mass flux of 8 milligrams per square meter per day with a higher Darcy of 6.

So this is the soil boring log data that was collected from this well.

As you can see, it seems to be a heterogeneous lithology.

What we do here is maybe the yellowish colors represent more sandy, more permeable units, while the darker brownish colors are more impermeable zones, have zones with higher content of fines that silts and clays.

The first analysis is that if we look at the Darcy velocity, the red triangles, the lighter colors or yellowish colors seem to have a correlation with slight increases in Darcy velocity, and that’s something we will expect.

But more importantly, we have to look at the PCE mass flux and the two spikes.

Two spikes seem to also be located in high permeable units, but while they are in high permeable units, they seem to be above and even in between those high fines units.

And for that, we can then look deeper into those by looking at the fines content from this soil boring log data. And this is percentage contents going from 20 up to 90%.

And when we correlate these fines with the peaks that we observe, we can see clearly that yes, both peaks are in permeable zones, but they are above and in between some high-fine zones.

So this is creating several effects first in peak number one.

Their PC might be having difficulties moving through these high-fine zones.

You need therefore, there is a potential storage unit that can either store back diffuse into these higher permeability.

And therefore with a given increase in Darcy velocity, this will create a concentration-dominated flux, still higher flux in that zone.

The second peak down below, it has higher Darcy velocity, but maybe not as much PCE mass flux or mass move through this zone.

So this, we can denominate it more as a Darcy-dominated flux.

The mass flux is being moved because the water is moving.

Now, the second case study is a dry cleaning facility.

In this, we will look into more the design consequences if you were to utilize estimated mass flux versus a measured mass flux.

So this is a dry cleaning facility.

What you see here in the map of the lab is these isoconcentration lines.

We’ll focus on these closer to the source area where there is this well with a PCE concentration of 4 ,510 micrograms per liter.

And there is a proposed barrier there.

The first approach is to look at the active sampling and the estimated Darcy or seepage velocity and calculate an estimated mass flux.

So for this, first is the approach was an in-situ chemical reduction sorption and donor for bio-stimulation.

What we do is to use these active sampling data first to with our plume force modeling to estimate the dosing at a given longevity.

So the input data is the Darcy velocity of 2.8 and a PCE of 4 ,500 that translate into a mass flux of 126 milligrams per square meter per day.

The output of the model was a PRB with a thickness of 13 feet and this is the colloidal activated carbon dosing and the s micro CBI dosing as well.

What we will look now is into the illustration of the in-barrier dynamics and this is what we will have as a model run of six months, Therefore, there is an incoming.

In this plot, you’ll see the y left axis is the mass flux, y right axis is concentration more connected through Darcy velocity.

Therefore, Darcy velocity is the same before, in the barrier, and after the barrier.

And in the bottom x-axis, you’ll see the distance where 0 being the start of the emplacement for this barrier.

And it goes up to 13 feet.

That’s the estimated thickness.

Then what you see here in green is the PCE.

there is a decrease. Therefore, it’s been S-microCVI is the one in charge of the reduction of PCE.

Therefore, there is slow or negligible regeneration of byproducts.

If we run the model to a three-year model, you’ll see here, yes, PCE is decreasing, but now you see increasing concentration of byproducts.

The reason for this is that after those three years, the CBI in the front end of the barrier has already been oxidized.

Therefore, the bioprocesses start occurring and there is a generation of by-products, in this case we see TCE, Sysdce, and some vinyl chloride.

Still, the purpose of the barrier is to hold this and not allow it to break through, which is occurring in this specific model.

But we’ll now look into the FluxTracer data for this specific site, and this is the plot and the data that we collected.

There is a significant peak of PCE that is located about 18 feet, and this peak is telling us that it is occurring in 30% of the screen section, carrying about 70% of the PCE mass flux.

Potentially, the concentration that was measured in this well was caused mostly by this peak at this depth.

This maximum flux is measuring about 1 ,200 milligrams per square meter per day.

What we’ll do now is to compare this with the active sampling estimated value.

And just to come back to the active sampling concentration of 4500 with an RC of 2.8 will obtain a calculated estimated 126 value that of course now we can highlight is about an order of magnitude different from the value that we obtained with our flux meters and the question now you might wondering is how will this affect the the design now we reprocess the design and what was done here was to come back to the design that we showed before with the 126 milligrams per square meter per day, same dosing at RCF 2.8.

How will these dosing behave in this high peak without rerunning the model, just using the same dosing that we had initially calculated?

And of course, the input for here is now a 3 centimeter per day Darcy velocity and a PCE of 1 ,200 milligrams per square meter per day.

What we see here is that, yes, the PCE, there is no breakthrough of PCE, But we are, of course, showing a different magnitude in the y-axis regarding mass flux, in this case, an order of magnitude higher.

Although you might think there is no breakthrough of the byproducts, there is, especially of vinyl chloride, which will cause this barrier to underperform, therefore reduce the longevity.

What we did after this was to readjust the dosing, make sure it was covering the high flux peak that we measure with FluxTracers, and deploy the successful permeable barrier.

So the reallocation of the product is one of the most common scenarios in these specific cases.

And that is, of course, because it brings cost reductions.

If we now know that the mass flux is not moving in an entire 10 feet screen initial injection interval, but it’s moving in 5 feet, we’ll remove the dosing that was going to be injected into those extra 5 feet and we’ll reallocate it in the 5 feet.

or if we knew the barrier was extended for 50 feet but it’s actually only in 25 feet where the mass flux is moving, we’ll reallocate the product and this has generated significant cost savings in previous projects.

And the second approach will be to increase the amendment dosing and in this case that increase will have generated a 30% increase in amendment dosing to cover the high mass flux peaks.

So those are the two potential options, real location being the predominant, the preferred, and the most common.

Now this has not only been measured in these sites that I measured before, but over 80 sites where FluxTracers have been deployed with some cases here for CVOCs.

What I want to highlight here is that, yes, there is changes in Darcy velocity.

Still, the changes in mass flux are way higher, difficult to predict only by knowing the hydrologic properties, the hydrologic properties of the site or the lithology, and even knowing average site concentrations or average estimated hydraulic conductivities.

And this only also occurs for PFAS sites.

We have seen these sites where high maximum peaks have been observed, and this has occurred for PFOS in the case of site four for 6-2 FDS.

So different various peaks where you might think example in site 3 that this is a homogeneous site there is still a significant peak of PFOS that has to be accounted into the design and also ideally initially into building the conceptual site model.

With that I’ll wrap up with final remarks and first the the most important is that high resolution mass flux data improves conceptual site models it’s critical for engineer effective permeable reactive barriers or permeable sorptive barriers as a result of doing that will obtain targeted approaches, as well as ensure the dosing and the longevity of a barrier.