Catching the Unseen: AI's Role in Tackling Microplastic Pollution

[00:00:15] Samantha Martin: Welcome everyone to today's edition of Water Data Forum. Water Data Forum is a web series presented in partnership with Cleveland Water Alliance, Midwest Big Data Hub, and WEF, the Water Environment Federation. Today's topic is Catching the Unseen, AI's Role in Tackling Microplastic Pollution. We'll have plenty of time at the end for Q&A, but if you want to ask questions while you think of them, go ahead and use the Q&A function at the bottom.

[00:00:42] Sometimes our panelists can get to them before the end as well, but we will definitely have time at the end for questions. We always have a really interactive group here. So we look forward to welcoming them. So let me introduce our moderator for today's session. This is Alexander Tompkins, CEO of Remedion and Alexander. Go ahead and introduce our panelists for today.

[00:01:06] Alexander Tompkins: Thank you. John McMullen, Samantha Martin, Cleveland Water Alliance, Midwest Big Data Innovation Hub, and WES, Intelligent Water Technology Committee for hosting this webinar. We have an incredible panel of experts with us today to discuss the crucial topics of microplastic pollution and how artificial intelligence can assist us in tackling these pervasive pollutants.

[00:01:24] Let's meet our panelists for today's discussion. Dr. Yongli Wager is an Associate Professor in the Department of Civil and Environmental Engineering at Wayne State University. Her research focuses on water treatment and water quality. Her group's microplastic research includes understanding the fate and transportation of microplastics in natural and engineered water systems.

[00:01:44] Developing high throughput microplastic sensing technologies, developing data tools to identify sources and pathways of waste plastics entering the environment and conducting community outreach campaigns to reduce plastic pollution. Rachel Miller is the founder of Resalia Project for a Clean Ocean, co inventor of the Coroball, CEO of Coroball, a National Geographic Fellow, and Explorers Club Fellow.

[00:02:08] Rachel is focused on protecting the ocean by specifically addressing the problems of marine debris and microplastic pollution through cleanup, prevention based education, embracing innovation and technology, as well as conducting solutions based research in urban and coastal waters from surface to seafloor.

[00:02:24] Dr. Andrés Prada is an accomplished civil engineer with extensive experience in data analytics and environmental research. Currently, he applies his expertise at Frost Defense and ViroTec Inc., developing predictive tools and machine learning models to optimize agricultural products application, significantly reducing uncertainty and enhancing effectiveness.

[00:02:43] Additionally, as an assistant research scientist at the Prairie Research Institute, Dr. Prada leads pioneering initiatives in PFAS and microplastic mitigation. And as you know, I'm Alexander Thompkins, CEO of Remedion, a clean tech company dedicated to providing pollutant free alternative food and water products.

[00:02:59] We utilize proprietary systems to remove physical contaminants like microplastics and chemical contaminants like PFAS from water in order to produce our pollutant free consumables. Currently, Remedion is in the process of launching our microplastic free bottled water line and are working with a Warwick, Rhode Island non profit to construct a pollutant free community garden.

[00:03:19] The first question for our panelists will detail a broad understanding of microplastic pollution. Who is responsible? Where are these contaminants found? When do we become aware of them? How does microplastic pollution affect us? And why is this a major problem? Let's begin by hearing from Rachel Zoemiller.

[00:03:32] Rachel, what is microplastic pollution?

[00:03:35] Rachel Miller: Thank you. Microplastic pollution, we'll just get straight into it, of course, is definition wise when bits of plastic, they can be made that small, which we call primary, or they can have broken off of something bigger, which they call secondary. Five millimeters or less, which is actually a really big range because five mil, you can see it's like half the width of your pinky nail and you get down into where we spend a lot of our time, which is working on microfiber, a subset of microplastic and that you need, some kind of magnification to see, and then nanoplastics are another category below that.

[00:04:15] So broadly speaking, microplastics are Pieces of plastic and synthetic material that are less than five millimeters. But can take on different shapes and forms, including fibers, fragments, films, beads, like little spheres and the like.

[00:04:35] Alexander Tompkins: Thank you for your insights. If I'm correct, you just got back from the Arctic Circle and that would be a great time to talk about where these contaminants are found.

[00:04:43] Rachel Miller: Yes, we've had some amazing research expeditions over the last year that included up as far as 81 degrees north in the Arctic and also in the Southern Ocean and, around the Antarctic Peninsula and South Georgia, and the best way to say it is that microplastics are not found in every single sample people take, but they are found in every region people look.

[00:05:12] And so we can say with confidence that they are ubiquitous. Our work, we are looking for microplastics and anthropogenic or manmade microfiber in the air, sort of in suspension. We're using an air pump and in the surface water. Although we have also sampled the entire Hudson River, looking down in the water column as well, the primary work that we've been doing from pole to pole has been surface water and air atmospheric suspension.

[00:05:41] And again, we're finding microplastic, mostly microfiber for this work that we're doing. Our collection methods are to do what's called a grab sample and then filter. So, other people do things like trawls, where you tend to get the bigger pieces of microplastic. Again, it's a big range. We sort of need more words for this and,  but doing the grab sample, Sampling with the filtering lets us catch the smaller pieces. And, yeah, I can say with some confidence, it's ubiquitous air and water and soil.

[00:06:18] Alexander Tompkins: Thank you for your outstanding response. Dr. Prada, Do you have any insights?

[00:06:25] Andres Prada: Yeah, that was a very good response by Rachel. I would add, or let's say she has been sampling in the Arctic, but most of my work has been in cities. So in the case of a city, we believe that the life of a plastic doesn't end in a landfill because we have detected microplastics in landfill lead shades that are sent to wastewater treatment plants.

[00:06:59] But wastewater treatment plants are not designed to treat microplastics. So microplastics end up going back to the environment, by the wastewater team, but the wastewater effluent and biosolids. So we find them in rivers and then in agricultural soils.

[00:07:20] Alexander Tompkins: Thank you. And Dr. Wager, how does microplastic pollution affect us? And why is this a major problem? 

[00:07:26] Yongli Wager: All right. Hey, I think microplastic can affect us in many, many ways. I mean, they can basically go into our water, surface water. They can go to our water supply. And when they go to our water supply, they can go to our drinking water. So, also, when they are microplastic in the aquatic environment, and as those organisms that are leaving in the water, that will be, they could accumulate those microplastic, in those organisms, and then, so basically, there could be a build up in a foot web, and then we human being consume those food. We could also consume those microplastic in our body. So basically, we human beings, we could consume the microplastic from water supply from food we eat.  

[00:08:19] There is already a number of research and reports, including our research from our group that we found that microplastic did exist in drinking water supply, in food, in fish. So it's definitely that we are taking microplastic into our body. So speaking to what exact impact that if we take in microplastic into our body, right? What is the impact that it could cause?  There are research out there.

[00:08:48] So we actually, our group, did some research in zebrafish, as a model to expose zebrafish to nanoplastics and then we did find that those zebra fish that were exposed to those,  nanoplastics, develop some adverse like the behavior and hypertension, inflammation and also genetics disorder from zebrafish. 

[00:09:16] There's many other research that found that animals who are exposed to the micro plastics have similar adverse impacts. In terms of the human response, it's a much broader topic, but from the, and there’s not many research out there yet in terms of the exact human health impact. But there are a few papers that have come out, indicating that the microplastic may be associated with some non disease asthma, because a researcher did find the microplastic in lung tissue, blood tissue.

[00:09:53] So I'm saying that we still have a lot of work to do to find exactly what microplastic can cause to human health and ecological health, but there is definitely sign evidence that show that. It does cause some impact on ecological and human health. 

[00:10:14] Rachel Miller: Can I add something?

[00:10:15] Alexander Tompkins: Please.

[00:10:16] Rachel Miller: I'm going to put the link in there. Yeah, that was great. Just a month ago, just over a month, 5 weeks ago, there's a paper that came out in the New England journal medicine. I'm sure you guys may have seen it. It's pretty fascinating. I just put the link in there. It's open access, but it's very cleverly done.

[00:10:40] It's obviously hard to test how this affects humans because we can't dose humans like that would be terrible. And so, you know, there has to be creative ways to understand just correlation. So, this was a very creative study, where they took arterial plaque that was removed from like 200 people who went in for that kind of surgery.

[00:11:07] So the stuff was taken out in order. So these are people who were sick. Arterial plaque was then looked at, 60 percent of the people had microplastic in their black and then the study looked at long term and the people that had microplastic had a 4 and a half times higher likelihood to experience stroke, a heart attack or die within 34 months of the surgery and it's a pretty fascinating again.

[00:11:38] It's not a causation situation. It is a potential link. But one that has gone farther than a lot of other studies have gone. And I think people looking into this will find it interesting to add to the pile of growing information about human health implications.

[00:11:59] Yongli Wager: Yeah, that's great that you share the article. Yeah, I have a few articles I can share later. So all those articles did find some correlation about microplastic in human health. That's awesome.

[00:12:12] Alexander Tompkins: Thank you both your answers were both engaging and informative. Let's move on to question two. Our next question for our panelists involves the use of raw data for realized impact. We'll start question two by hearing from Dr. Wager. Dr. Wager, how does the study of microplastic pollution leverage data for impact?

[00:12:31] Yongli Wager: So, that's a very big question. So I will probably talk about some research that our group is doing. I'm pretty sure other panelists will provide some insight information from their experience. So basically, our research group is doing a lot of research on how to identify where those microplastics come from, and then how to reduce the pollution from sources.

[00:12:59] The reason that we focus on this area is because we know that. Microplastic is very small, right? Once they are into the environment, it's basically, it's very hard to clean them up. I mean, we could pick up some debris, large debris, like big bottles, plus big plastic bottles. But when we talk about those small particles in milliliters, micrometers, or even nanometers, it's really hard to remove them.

[00:13:27] So our research group focuses on how to identify where those microplastics come from and then how to identify those and then to reduce the sources. So basically we are collecting data from all sorts of the environment from wastewater, from drinking water, from soil, like green infrastructure soil, urban soil, from surface water, and also from sediment to look at what kind of microplastic are there and then we integrate those data.

[00:13:57] So, basically, what microplastic are there and also together with what does it look like particular for those larger pieces of plastics, what their texture looks like and what the color looks like. And also, where do we collect it? What's the landscape associated with those areas? We collected it. So, with all that information we put in a library, we already have a build microplastic data library, so that library is in our farm version testing right now. So that, including over 2000 of the samples, including all those micro plastic and larger plastic samples, debris from the environment, also environment as well as post consumer plastic products.

[00:14:43] So with those data together, we also develop CN. It is a machine learning algorithm. So with those algorithms, we can track or tell us, all right, what kind of these plastic pieces could come from, what kind of a plastic product. And then that information will give us the oral community, a particular community of scientists to say what is the top contribution for those micro plastics in a certain environment for the particular region there. So that's what we have been doing. Right now we are expanding our work. 

[00:15:23] So we just got a new brand, just came in. So we're going to expand our work with communities with probably 20 communities, we start with 4 or 5 communities, and then we are expanding our sample collections to 200 communities in the Great Lakes area. And then with those communities, enjoy our data collection and use those data as a set. It's metadata. 

[00:15:51] So we're going to use picture image, data collection, sample information, and also we use the Raman spectrum. So the Raman spectrum will tell us whether it's plastic or it's or other synthetic material, or it's non synthetic material. So, with all this data collected together, we're going to refine our tool to track where those pollution sources come from in a particular community, particular regions.

[00:16:17] So that can inform those leaders in those communities to take action to reduce those pollutions. 

[00:16:28] Alexander Tompkins: Your passion on the subject matter is evident. Thank you for such an outstanding response. Should we hear from Dr. Prada now?

[00:16:35] Andres Prada: Sure. So data is the basis for all these studies right now. So the ones that Rachel had shared are based on data collected from all these studies. And that's the route that any contaminant has to go before we can implement any legislation.

[00:17:00] So recently we have seen, as an example, What's going on with PFAS? and now after years and years of research, like the US EPA came up with the regulations in drinking water. So microplastic have to go on the same route after years of data collection and studies, to finally identify what are the implications for human health.

[00:17:33] So, as Rachel was saying, it is very difficult for humans, but one thing that I can add is, the influence that microplastics in agricultural soils can have on bacteria. So, bacteria attached to anything, they are in agricultural soils and there is this new material, the plastic, that contains also chemicals and additives.

[00:18:05] So bacteria add to the plastics and react to those new chemicals, becoming even resistant to antibiotic treatment. And those bacteria go into the food chain, and then that is the bigger problem of having antibiotic resistant bacteria. So that's one of the biggest implications that I see with microplastics besides the direct effect on our bodies.

[00:18:40] But is the effect on bacteria and how that translates to humans.

[00:18:49] Alexander Tompkins: Thank you for your contribution. Rachel, can we hear from you now?

[00:18:53] Rachel Miller: Yeah, so I'll balance it with some work that we're doing on the, again, the microfiber side in a very specific way. So, we figure we do these expeditions and we're filtering water and we're getting some number it could be depending on how many samples we take.

[00:19:12] And if we're doing it in the Hudson River, or we're doing it in the Southern Ocean, tens, dozens to hundreds to thousands of individual particles, and these individual particles, depending on what process one is using to identify them. Could take from 4 to 30 minutes per particle to figure out the source.

[00:19:33] And we can't stop this if we don't know the sources. We have to know what is there in order to prevent it. And so the impact that data science can bring to all this is making it so we can speed up the identification process in one of the ways is to speed up the identification process.

[00:20:01] So, if we can just have at the human side. Or even a machine side, a magnified image of, say, an anthropogenic or manmade fiber, and then an algorithm trained a data set that's been trained can come in and identify that the color, the shape, the width and potentially the material, we can start to zero in on what's really out there.

[00:20:26] And as far as textiles go and microfiber goes, you know, the way we see it, what this will help us learn is on the prevention side is answering the question. Are there point sources for this stuff? where there's like a factory making something that's purple, and that's why there's a lot of purple delta fibers that are 25 microns wide in a place, and we can track it back.

[00:20:53] Or is this multiple diffuse sources of all of our collective clothing falling apart when we wash it, when we dry it, when we wear it? And if that's the case, we need our clothing to be more resilient and we need our clothing, perhaps to be made out of something that is bio derived and bio benign, at least one of those.

[00:21:15] And so it's this power of data to make these identifications to drive understanding to be able to prevent. These problems, significant problems. So, that's what we're trying to do is,  we're working with Staffordshire University in the UK on using AI to come up with an app or to create the app that we can have a global citizen science microplastic mapping and monitoring project.

[00:21:48] And this is for the smallest of the micro plastics and microfibers.  We call it C.S.I. For the ocean and we're sharing. We're taking methods from forensic science as well as marine science to bring it all together. But ultimately, it's success will be because of AI.

[00:22:08] Alexander Tompkins: Thank you. That's just such a great concept and bridges us right into our final question we have for our panelists today.

[00:22:13] It's on AI advancements and observing pervasive pollutants. Dr. Prada, what does the future of AI detecting microplastics look like to you?

[00:22:22] Andres Prada: Yeah, so both Professor Wager and Rachel have mentioned how it will help with detection, but I will add that we are creating a giant database, so every, I don't know, every week or every every month, a lot of newspapers are coming out and coming out, so we need the power of computing to help us, summarize, and identify, those contributions and  compare, between contributions and find topics where they overlap and then demonstrate the same thing or so we can identify the, as I said, the health effects on humans on bacteria and on the ecosystems.

[00:23:21] So, that's when it comes handy, the artificial intelligence to help us navigate through those giant databases and have meaningful outcomes.

[00:23:38] Alexander Tompkins: Thank you, Dr Prada. I know you touched on it before, Rachel, but I'd love to hear more from you. How will AI help in the future with detecting microplastic pollution?

[00:23:48] Rachel Miller: I think what AI will do is shorten the distance, shorten the time, shorten the amount of people and effort that needs to happen to go from, collecting information about this problem to actually doing something about it.

[00:24:09] In terms of making the actual data drive decision making. So, again, whether that's driving funding that supports research on making alternative materials, or something that's made out of waste organics that's happening, but it's happening in small batches and in order for it to make an impact, it needs to be made in big batches.

[00:24:35]  Also in driving something like our project, obviously, you know, it's easy for me to come back to our project because what we see is if we can enlist not just students, but community scientists from all over the world to look and see what's in their, air and water. It'll work with atmospheric deposition, just using a bucket and also a bucket in the water and filtering, which can be done pretty simply.

[00:25:02] Again, we can start to understand if there are any point sources. And those are low hanging fruit for solutions. At least you can talk to one group of people or a smaller group of people, or if this is going to have to be, or continue to have to be a textile wide thing. So, I think,  there's very little that's more valuable in our ability to have an impact, then managing the data that's being collected and using AI for good.

[00:25:37] Alexander Tompkins: Thank you. That's such an incredible insight. Our company, Remedion, we do something similar, where we will actually have artificial intelligence control our water quality and when we must change our water within our community garden. So a lot of what we've been talking about really revolves around the identification processes of artificial. Dr. Wager, do you have any insights to add to this?

[00:26:00] Yongli Wager: I would add, I think you all have a great point. I just would like to add or I think to summarize a little bit of what you're talking, you guys have great talk point. I think AI in terms of microprocessing will have an impact in the future. I think overall it's going to make the detection reduction, all those things is more how to say, higher efficiency of the says, because we can use AI to grab those data more efficiently, analysis data more efficiently. Also accuracy, like, higher accuracy to basically to identify those plastic resources more accurately.  I'll come back to my research again.

[00:26:43] It's an example when we develop those, SC and AI language machine learning algorithms to incorporate with our ramen spectrum to identify microplastic from the environment samples. Right? Our methods really can reach over 99 percent of accuracy. As I say, we have over 2000 data.

[00:27:07]  We train our data and then use 80 percent of our data training, 20 percent of the data prediction and validation. And then we compared our own machine learning tool with a standard library or like the Raman Spectrum library to compare, and we did find our machine learning to have a higher Accuracy of, say overall, 30% to 50% of accuracy.

[00:27:34] This is because micro prosecuted, when they go to the environment, they have degradation after degradation, we all know that  after weathering, it makes the identification become more challenging because their characteristics will change when we use Raman or other testing tools.

[00:27:54] So when we compare the standards. Spectrum in a standard library is going to change, give us certain results there. So I have to say efficiency, accuracy, and also definitely a last point. It is data driven decision and actions. That's what actually what we would like to say is because. There are so many sources, point sources, non point sources, and also all those sources depend on the particular, like the specific regions.

[00:28:24] So, for example, in some regions, they might not have recycled programs. There might be a lot of plastics coming from some debris and also near the highway. Maybe the microplastic comes from the tire driving. So there is a source, So many different sources there. I think that AI will really help us to get the data driven decision actions.

[00:28:51] I have to say geospatial, data driven. Decision and actions for specific regions, if they want to take actions to tackle this problem.

[00:29:02] Andres Prada: Is your Raman system able to estimate concentration? So, or you just detect the type of polymer?

[00:29:14] Yongli Wager: We this, so for concentration, we need to come to them. So we can use, immediately.We count them. Basically, we use

[00:29:23] Andres Prada: Accounting.

[00:29:23] Yongli Wager: Yeah. Yeah. We need automatic accounting. So, basically, we scan the samples and then automatically accounting. So, the Raman is a Raman spectrum. It is just among those particles that we found there. And then we will detect them 1 by 1 to see whether it's around the spectrum. It's identification basically.

[00:29:47] Rachel Miller: We used polarizing light microscopy, which is something taken from forensics as well, particle by particle. With one human and thinking about that as you were talking is that. You know, for all of our papers that we've published with these expeditions that we've done, in particular the Hudson River, where we sampled from the Adirondack mountains to Ambrose light the whole Hudson River.

[00:30:15] It's interesting because you get agricultural suburban, extremely urban industrial Alpine, like all these regions in one relatively small river, 300 miles anyway.  We have had only 1 analyst look at everyone, which is a big ask of 1 person to look at. 4,000 particles, but it's until we have some machine based ability. 

[00:30:45] We can't risk that maybe you see blue a different way, I see blue when an actually important characteristic is color. We have it the same, the same color being seen differently by different people and being called something else. And so, like you said, it's moving towards machines being able to identify the same thing the same way every time, no matter what the circumstances, it's going to be very valuable instead of.

[00:31:19] So, we've dealt with it by asking 1 person to do an extraordinary amount of work. So, at least we know all of the blues. Are in the same blue, because that is how she saw that blue. So, yeah, I think it'll make a big difference.

[00:31:34] Alexander Tompkins: Most definitely. Where Remedion will be applying artificial intelligence to our microplastic free bottled water line is our inline Raman spectroscopy data will be transformed by artificial intelligence to create visual representations of our water quality.

[00:31:46] That water quality graph will then be posted as a live feed to our website to ensure our customers know the quality of our products. So, thank you all for everything. I mean, this has been an incredible panelist we've had today.

[00:32:01] At this point, do we open it up to Q&A's?

[00:32:08] John McMullen: Sounds good. We do have one question in the Q&A so far, and I encourage other attendees to drop those in there as well. But we do have a large number of water utility folks typically on this call. And so this question, I think, is related to that. So,  Andres, you mentioned, EPA regulation around microplastics and drinking water.

[00:32:32]  Can you talk a little bit more about that process? And, and then, you know, water utilities are going to be interested in how they can filter out microplastics. And so any insights that you all have on best practices for that, I think might be appreciated.

[00:32:49] Andres Prada: Yeah, thank you for the question.

[00:32:51] Now, what I tried to say was that the EPA released the regulations for PFAS like a few weeks ago, a week ago. So I was comparing like, the emerging contaminant of PFAS compared to microplastics. So PFAS has been studied for a longer time, and now it gets to a point that we can take measurements and regulate the use.

[00:33:23] But microplastics are still under research, and then the effects on human health are not well understood. So we have to get to that point of like, detect those problems and say, okay, we need to regulate filtrate microplastics for drinking water facilities, for example. So sorry about the confusion. I just tried to give an example to compare. Microplastics with another contaminant as that answers the question.

[00:34:03] Yongli Wager: May I add a comment there?  Alex, so since I have done a lot of work in a drinking water plant, we collaborate with water utilities. So we sample drinking water, like, source water.

[00:34:22] We sample the water after each treatment process, for example, coagulation, flocculation, sedimentation and filtration and treated water. The good news is that from our report, the water treatment plant, it's actually very, I have to say, pretty efficient to remove microplastics.

[00:34:46] At least our data show, like, over 98 percent of removal. So I think what do we need to do is, How to punch that little bit left there.That's basically, there's still, as I said, 98 percent of over removal. It's a very good removal efficiency, but there's still some there.

[00:35:05] Andres Prada: Yeah, that's very, that's very true for.

[00:35:08] So for drinking water facilities, I wouldn't be worried about microplastics. The problem, or there is more exposure with plastic barrel water. Every time that you open your bottle, your plastic bottle, you are adding microplastics. Every time that you leave your bottle under the sun, the plastic is degrading and coming into your water.

[00:35:34] Yongli Wager: That's a good point, yeah.

[00:35:35] Andres Prada: So tap water can be,or we could say, safe in most parts for microplastics, but then again, the main problem is with when we put it in plastic containers.

[00:35:54] Alexander Tompkins: This is where Remedion is, truly championing our microplastic free bottled water line. We'll be producing our water, filtrating it, purifying it, and bottling it in glass with core T tops.

[00:36:06] In order to ensure that our customers do not receive microplastics in their product, one of the effective wastewater treatment options that we have is our hydroelectric water purification system. It co generates purified water and hydroelectricity. While producing that pollutant free product for your consumer,

[00:36:27] We utilize a combination of purification and absorption processes to accomplish this for you. And I also just dropped the link in the chat as well.

[00:36:43] John McMullen: Thanks for that. We do have a couple of other questions in the chat.  Alexander, if you can't see those, let me know, but one is sort of about that evolution of regulation in that space, but then as well, how we can rapidly detect microplastics, maybe using some of those machine learning techniques that were talked about before.

[00:37:13] Rachel Miller: This is a tough one, I think, depending on how small you want to see that there's some organizations that are working on pump based,  FTIR based detection in to do environmental samples, but they're still not quite seeing the sub 100 micron fibers and things like that. So there's a little bit of which, you know, like I said, we need a few more words inside of just microplastics to describe what's really out there.

[00:37:49] I think there needs to be a couple more categories, but. Yeah, it would that's something to work towards for sure. I mean, for us, we foresee right now, we're still going to need humans to do the filtration and then the innovations, the opportunity for innovation is big to do scanning of filter papers or of.

[00:38:14]  Slides with this we use a tape lift with a material called easy lift tape again, came from forensic science to transfer what's left on the filter paper onto a glass slide. So we can use polarizing light microscopes.  So for us, we're still needing humans to get 400 times magnification pictures of each of the particulates of interest, and then it would be identifiable, at least as a 1st, immediate step.

[00:38:40] But my guess is that. My fellow panelists are using something more automated. Is that correct?

[00:38:52] Yongli Wager: There are. As I said, Rachel, you got the right point. It really depends on the size. So the size difference from my experience, it really depends on how efficient or how quickly you can analyze a sample. So, like, micron size, millimeter size, I mean, millimeter size, it's much easier. We can actually say it and the micron size get a little bit harder because we need a microscope or some sort of an appliance to detect it and also when it's nanometer size is going to be even more challenging because the nanometer size, is really small, really tiny. And then whatever, analytical tool we use, for example FTR Raman and then the wavelengths or signals become very weak. And then also there's a non noise background noise there.

[00:39:44] So the nanometer size is. It's very challenging. It really depends on the size. I know there's one company they are doing,they claim that they have a product called OPTR. So I'm not, I'm not in that company. Okay. There is some research there, but if interested, I can put it there, I think it's OPTR.

[00:40:09] You can take a look at that. Yeah, I have not used that machine yet, but I have a colleague who works at that machine. He said it's okay. It can do some automatic scanning and then, can go down to a nanometer or something like that. So that's something very challenging for nanometers.

[00:40:33] So again, I coming back to the AI I think we actually have an idea right now to once we get the newest new project going on, we are actually thinking about it to link the macro plastics and micro plastics. So, basically, when we have those data, right, we have a lot of already published data and other groups data or our own data.

[00:41:00] When we collect the plastics, right? We have some range in macro plastic, larger pieces. We have some in smaller pieces. So there are maybe some creations between those micro and macro. So we have been thinking if we can find some correlation or some sort of underlying mechanism there in one day.

[00:41:23] We hope that we can look at those larger plastic kills can give us this into those smaller particles. 

[00:41:30] Rachel Miller: That would be nice.

[00:41:31] Yongli Wager: Yeah

[00:41:31] Rachel Miller: It simplifies things. That's right.  We did a study outside, within our Hudson River trip, we just did as much as we could expeditions are expensive.

[00:41:45] So, we did as much as we could and we did a wastewater treatment plant study and we haven't published this yet. But we sampled at the outflow, so we called that 0, that's where the marked on the chart, the effluent coming clean effluent from the wastewater treatment plant. And then we sampled half mile, 1 mile, 1 and a half and 2 miles.

[00:42:06] Up current and down current of the 0 point. At the surface, the mid water column and 1 meter above the river floor in the Hudson. At a rural suburban and urban location on the East River. And, you know, sort of very preliminarily, we are finding similar concentrations in the water column with that sort of same thought of, like, let's make things easier that if that holds up, and this is just kind of an initial study.

[00:42:37] And I don't know if you guys did that as well, but if you could just take surface samples, at least in rivers, similar to the Hudson, I'm sure the hydrodynamics are different everywhere,  But that would be nice because not having to take depth samples would simplify monitoring, you know, because that's where we need to turn.

[00:42:55] And I think we're AI and big data has an opportunity to simplify the monitoring. So we are still understanding the problem, but we know enough to take some actions and actions are being taken from policy to innovation. Like, what Alexander's doing, to other types of consumer education, related actions, like people washing differently, or we're using a core ball or something like that.

[00:43:22]  The monitoring is going to be really important and knowing if we find the big stuff, it means there's also little stuff. Or if we find microplastic on the surface, it also means it's in the water column is going to be really helpful.

[00:43:40] Alexander Tompkins: I would just like to add, I believe the balance between prevention and removal, we do need to emphasize the prevention side of things.

[00:43:47] I don't know how many of our jeans, T shirts, sneakers, we're all just wearing plastic products. We're not wearing natural materials that can return back to the environment when they shut off. So I believe that on the regulation side of things for microplastics, prevention is just as important as removal. And I think it's way easier, if not more. Yes, if not more.

[00:44:07] Yongli Wager: Yeah, I agree.

[00:44:10] Alexander Tompkins: The national shift towards cotton based clothes would be way more attainable than putting these crazy limits out and expecting people to meet them on a specific timeline.

[00:44:22] Rachel Miller: It's tough though, because the naturally based clothes, you know, that are derived from something natural like cotton, aren't free of problems.

[00:44:32] We're finding huge percentages of the fibers in natural places are anthropogenic cottons. They have dyes. The dyes are not that natural. In fact, they don't even need to tell us what's in them. They're often not something we want to drink or we don't want creatures drinking them. There's additive things like wrinkle releasers and dye setting agents and things like that.

[00:45:03] So,  yeah, even beyond trying to move, you know, like, there's lots of ways to affect this. In addition to, yeah, I don't know that we can fully vilify synthetic clothing, entirely because it's also unrealistic. You know, we need to stay warm and dry when we do things outside and temperature regulated and that kind of thing.

[00:45:29] And so I think, yeah, it's super complex for sure. As far as the clothing side goes, but not insurmountably. But I think on the clothing side, it really has to be all prevention. Pretty much the wastewater treatment plants are doing a great job. Just like you said, 98 percent is incredible, but it's 98 percent of a lot.

[00:45:55] So that means 2 percent is still a lot. And so prevention ends up and the way I usually explain it is this is like, pick up on this side. Like, cleanup is like billing a big thing, a table salt in a field, and then trying to go pick up the individual pieces. It's. It's just not efficient or effective, or probably even possible at this point with the technology we've got.

[00:46:23] Alexander Tompkins: That was an incredible analogy that I'll definitely borrow.

[00:46:26] Rachel Miller: It's all yours. 

[00:46:34] John McMullen: Right, we do have another question in the Q&A,  that we can throw to the panel.  Rachel, you were talking about different types of plastics earlier and the differences between, fibers and, and others. For example, this questionnaire is asking about petroleum based or hydrocarbon based plastics versus,  maybe some of the newer ones that are more bioplastic or break down more easily. Are there differences in the ways that you guys approach those? Are there differences in the tools that may be able to be used to detect those?

[00:47:15] Rachel Miller: I love this question and what you're thinking about here because we're thinking about this a lot too is like, is this just about plastic clothing or Petra based clothing? Again, we need more words. Plastic as a word is just too broad for now. All the materials that live under it.  Yeah, from our side, I have to say that.

[00:47:37] Using the polarizing light microscope helps us differentiate between, something that was, that is from a sort of flora or fauna base like fauna for us would be wool or Alpaca, something like that.  But in our work and with our partners, I'm not aware of automated opportunities there.

[00:48:04] And I hope that we get to keep working on this, because that means that bio based or alternative materials are making their way into, especially textiles and being able to understand those is really, really important. I mean, I'm talking about this as a potential solution, but we do need to know more about.

[00:48:26] The implications of that as a solution and is it better and that kind of thing. So, how about, how about you guys, have you been working on that, like differentiating? 

[00:48:37] Yongli Wager: We have been working on basically we use a Raman and FTRR spectrum. So basically that does give us what kind of particular material like the specific if we get them PVC or what line or what other material it is sort of for the background.

[00:49:01] I think there are some projects going on out there. But, but I think, as Rachel said, there are so many materials out there. We need more advanced data tools to basically identify all sorts of different materials.

[00:49:23] And I mean, hundreds of thousands of materials. I mean, also Raman and others are commonly used tools, they can also be used to identify other materials, not just the plastics, not just polymers. So I think at this point, there's really a need a lot more work to definitely look at those bioplastic sites.

[00:49:42] We have not gotten into the bioplastic side yet. So, right now we are focused on petroleum based plastics, or our algorithm is also developed based on petroleum based plastics, but that's great question. That's something we can think of in the future.

[00:50:03] Rachel Miller: Yeah. And part of it's going to be that as some new materials are coming out into the world that those libraries, the FTIR, Spectra library.  Even what we know, as far as the ranges for polarizing for birefringence and polarizing, like, microscopy, you know, we need to know what the new stuff is, like, what their numbers and what their spectra look like, so that they can be identified.

[00:50:32] As a new thing, so that'll be interesting coordination really between the scientific community and the textile innovation community as well. That'll be important.

[00:50:43] Yongli Wager: Yeah, exactly. Rachel, I think that's a really good point. I think that's the library out there, build a library, keep adding those spectrum or data into the library.

[00:50:55] That's really important. So, as I said, we are going to expand our project to collect those posts for consumer products. So, as more of those bio based plastic, it goes into play that goes into the market and product. We hope to add in those samples, spectrum samples, like those into the library. So, I think that would be really useful.

[00:51:17] Rachel Miller: It would be good it's like. Ask funders or whoever's doing this, it's sort of like, require that that work gets done as these new materials get developed somehow. I don't know how this gets done on a global way.

[00:51:35] Yongli Wager: I think the national institution of the standard needs. They do have a branch. They do have office programs to collect that, I think they are focused on FTRR. FTR spectrum for like a thousand, thousands of materials. So I think that's, I think also the database is probably open data, open database. I think it's definitely worth checking out. 

[00:52:01] Andres Prada: Another very important industry is food packaging.

[00:52:06] That needs a lot of innovation because we cannot keep putting our chips in a bag that lasts for hundreds of years, so we need to change the whole food packaging and create something either reusable or degradable, biodegradable.

[00:52:30] Alexander Tompkins: Where we come into this is we do not specify on the chemical composition of any contaminants where we are actually a size class oriented company, where we remove that up to 0.1 nanometer contaminants from the source water to produce our food free consumables. So I would like to see a real effort on deciding whether or not we need to move towards these bio based plastics or get rid of plastic entirely. I think petrol based products in our lives are really starting to dampen down on our health.

[00:53:12] John McMullen: Great well, thank you all for the discussion today. I'm going to invite Samantha Martin from our partners at the Cleveland Water Alliance to come back and talk about an upcoming session for this series.

[00:53:27] Samantha Martin: Thanks, John. Let me go ahead and share this slide here. So thanks again to all of our panelists.

[00:53:35] Thank you to our moderator, Alexander, for a great discussion. And this webinar is being recorded and it will be emailed to all registrants, even if they weren't able to attend today.  And stay tuned for information on our next webinar.  The date is still being finalized but the topic will be cyber security in water.

[00:53:55]  So we'll keep everyone posted on when that's scheduled this summer and we'll send out information to everyone to all the registrants and we'll send out the recording as well. Thank you so much everyone for participating today.

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