1
00:00:00,000 --> 00:00:04,000
Yeah, so I'm gonna get the temperature here.

2
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Alright, we have a very humid day today.

3
00:00:46,000 --> 00:00:50,000
So it is 1340.

4
00:00:50,000 --> 00:00:52,000
What was the temperature?

5
00:00:52,000 --> 00:00:54,000
Negative 20 of it.

6
00:00:54,000 --> 00:00:58,000
It is minus 25.4.

7
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Alright.

8
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Oh, yeah.

9
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Time and initial.

10
00:01:24,000 --> 00:01:28,000
Yeah, that is 13.

11
00:01:28,000 --> 00:01:30,000
Alright.

12
00:01:30,000 --> 00:01:33,000
Then, you want me to read them off as I put them in?

13
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Yes.

14
00:01:34,000 --> 00:01:36,000
Let's move this apart.

15
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Alright.

16
00:01:43,000 --> 00:01:44,000
So, Ruth?

17
00:01:44,000 --> 00:01:45,000
Ruth.

18
00:01:45,000 --> 00:01:47,000
It does must be the fresh ones.

19
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Just that one.

20
00:01:57,000 --> 00:01:59,000
Alright.

21
00:01:59,000 --> 00:02:01,000
Big stone.

22
00:02:01,000 --> 00:02:02,000
12.

23
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Yep.

24
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Mom.

25
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12.

26
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Silver.

27
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5, yes.

28
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Alright, that's it.

29
00:02:21,000 --> 00:02:29,000
Alright.

30
00:02:29,000 --> 00:02:33,000
So then, we'll go down the hall if you want to do patience here.

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Is the fan okay?

32
00:02:35,000 --> 00:02:37,000
Is there a lot of interference?

33
00:02:37,000 --> 00:02:39,000
If we could turn it off, that'd be awesome.

34
00:02:39,000 --> 00:02:43,000
Yeah.

35
00:02:43,000 --> 00:02:47,000
Thank you.

36
00:02:47,000 --> 00:02:59,000
Yeah, I don't know what happened today, but the humidity in the building is crazy.

37
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Yeah, I've got the mic so I can talk if that helps.

38
00:03:05,000 --> 00:03:11,000
So, once we receive the fish, we grind them using a KitchenAid mixer.

39
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So, this is our homogenization process, and the reason we do this is to make sure that when we take a small sample of fish to do the mercury analysis, we're getting a uniform portion of the sample.

40
00:03:26,000 --> 00:03:33,000
When we do the actual mercury analysis, it's about .2 grams of tissue that we weigh out for the analysis.

41
00:03:33,000 --> 00:03:43,000
So, it's a very small part of the sample, and so we want to make sure that it's just representative of the entire fillet that we have.

42
00:04:04,000 --> 00:04:08,000
So, we put the fish through the grinder three times.

43
00:04:08,000 --> 00:04:26,000
The first time we catch the first little bit that comes out and throw that away because we want to make sure we do a very good job cleaning everything, but we want to make sure if there was any fish that was hung up in that grinder that we're throwing away that first portion when it comes out.

44
00:04:26,000 --> 00:04:37,000
So, send it through the first time. It comes out of the grinder. It's homogenized in the bowl. Then we send it through two more times.

45
00:04:56,000 --> 00:05:09,000
Where did this sample come from?

46
00:05:09,000 --> 00:05:24,000
This sample is from Lake Superior. We have a mixture of fish that were caught for a fall project that they did.

47
00:05:24,000 --> 00:05:36,000
So, this is actually a Cisco that was caught in Lake Superior near Red Cliff. Many of the fish that we do for walleye, the largest portion of what we do for walleye.

48
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And so, every summer we get between about 400 and 450 walleye that we homogenize each one individually and then analyze those for mercury.

49
00:05:48,000 --> 00:06:03,000
The walleye that we do are from inland lakes in Wisconsin, Michigan and Minnesota. The fall samples that we get are all samples that are from Lake Superior and there are a variety of species that we do.

50
00:06:03,000 --> 00:06:09,000
Does the species difference make a difference in the amount of mercury based on the food chain?

51
00:06:09,000 --> 00:06:18,000
Yes, exactly. So, if we're doing something that's eating organisms that are lower on the food chain, they're going to have less mercury.

52
00:06:18,000 --> 00:06:35,000
So, for example, whitefish have lower mercury levels than a lake trout. Walleye are the ones that have a lot of higher concentrations of mercury overall, I would say.

53
00:06:35,000 --> 00:06:52,000
So, then we take, after the third time it goes through and it's mixed within the bowl, then we fill one of these vials. They hold about 20 grams of fish and we seal it up and we put them all in a container and then they're frozen.

54
00:06:52,000 --> 00:07:01,000
Once we get about 30 to 40 fish, then we're ready to do the analysis. So, how many fish would you say you can process in a day?

55
00:07:01,000 --> 00:07:16,000
About 30 in a day. So, we generally do the, we do a lot of this up front and then later on we kind of come back in and start doing more of the analysis.

56
00:07:16,000 --> 00:07:38,000
So, that are really important part of this, the part that's probably our least favorite. I've grown thousands of fish on this project, but the dishwashing is the very most important part because if you're not getting the dishes clean, then the fish analysis that we do later on could have contamination in it from an earlier fish.

57
00:07:38,000 --> 00:07:46,000
And we, we really rely on the students that we have here at UWS to help us make sure they're doing a good job.

58
00:07:46,000 --> 00:07:57,000
We also do a lot of quality assurance on the project. So, when we're doing grinding the fish, probably every hundred samples, we do a tuna sample.

59
00:07:57,000 --> 00:08:05,000
That's called a procedural blank. So, we take just a portion of the tuna sample out of the container, drain the water out of the container.

60
00:08:05,000 --> 00:08:14,000
Take a portion of the sample and just put it directly into a container and then we would process the tuna just as we have with the walleye.

61
00:08:14,000 --> 00:08:28,000
And once we've done that, we put that into a vial and then we analyze those as a before grinding and after grinding to make sure that we're not adding any mercury or losing any mercury in the process.

62
00:08:28,000 --> 00:08:37,000
So, that's a good check to make sure that we are keeping things clean as we're processing the fish.

63
00:08:37,000 --> 00:08:53,000
So, the washing process is just washing the sample with washing the sample with a laboratory cleaning solution called liquinox.

64
00:08:53,000 --> 00:08:59,000
We rinse things off to make sure we don't get a lot of the tissue going down the drain and clogging things up.

65
00:08:59,000 --> 00:09:07,000
So, yeah, washing the things and then we soak them in a dilute acid solution for a minute.

66
00:09:07,000 --> 00:09:19,000
That also helps to remove any residual metals that we would have that would be in the sample analysis portion.

67
00:09:19,000 --> 00:09:34,000
And then they get rinsed really well with misty distilled water and then that distilled water just gets rid of any extra residual soap, acid, and then we put the thing back together and repeat the process.

68
00:09:34,000 --> 00:09:37,000
Over and over and over.

69
00:09:37,000 --> 00:09:46,000
It's, you know, I kind of miss these days grinding because it's can be mindless, you can listen to a podcast, you can listen to music.

70
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If you're in here with someone you enjoy working with, lots of visiting.

71
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So, it's really not that bad. Some days I miss it.

72
00:09:56,000 --> 00:10:02,000
What if you're with somebody doing a drink? Well, then it's less fun. Then you put on a podcast.

73
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Is that why he can place podcasts in the car? Could be.

74
00:10:07,000 --> 00:10:13,000
He just really likes to learn or have, you know, have fun needs a little comedy in his life.

75
00:10:13,000 --> 00:10:23,000
So this grad student or regular student, we don't have any, we don't have any graduate students here at UWS in science.

76
00:10:23,000 --> 00:10:31,000
We do have, there's education does have some and I think maybe counseling, but not biology.

77
00:10:31,000 --> 00:10:44,000
Yeah, so this is Jayden's first year here with us. She's only actually been doing this for maybe the last month.

78
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But we're very glad. We're always very glad for our students.

79
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It's a great opportunity to get some experience in the sciences.

80
00:10:54,000 --> 00:11:02,000
And ideally, not only is she in here grinding and washing dishes, she'll get to see the entire process.

81
00:11:02,000 --> 00:11:12,000
A lot of students use this as a capstone experience or an undergraduate research project where they can then,

82
00:11:12,000 --> 00:11:22,000
everyone here has to do a senior project presentation. And so a lot of students use the glithwick research that we've done to present.

83
00:11:22,000 --> 00:11:27,000
So it's kind of nice because it gets that information out there as well.

84
00:11:27,000 --> 00:11:37,000
So what are the yellow and blue? We just have, each like gets a color and it's not specific to the lake each year.

85
00:11:37,000 --> 00:11:43,000
It's just so that we can kind of add a glance in the boxes that we have. They hold 72 vials.

86
00:11:43,000 --> 00:11:46,000
I kind of like this.

87
00:11:46,000 --> 00:11:51,000
So we just have the lake identification and then the sample identification for the fish.

88
00:11:51,000 --> 00:11:58,000
And then on the caps we have a code that we have come up with, generally it's a three-letter code.

89
00:11:58,000 --> 00:12:04,000
And because we've done, because the glithwick samples the lakes kind of on a cycle,

90
00:12:04,000 --> 00:12:11,000
we've done many of these lakes many times. And so we have the same sample code year after year.

91
00:12:11,000 --> 00:12:18,000
So that's kind of a nice way for us to just look at all those freezers that we have if we need to find a fish

92
00:12:18,000 --> 00:12:22,000
and be able to pull fish from a particular lake.

93
00:12:22,000 --> 00:12:27,000
Do you have samples from Lake Manor Kagan? Is that one that they pulled from?

94
00:12:27,000 --> 00:12:29,000
I know they do surveys there, but I wasn't sure.

95
00:12:29,000 --> 00:12:35,000
Right. I would have to look and not remember right after time in my head.

96
00:12:35,000 --> 00:12:38,000
Yeah, certainly not a big deal.

97
00:12:38,000 --> 00:12:43,000
Yeah. I don't know. I'm not really sure.

98
00:12:43,000 --> 00:12:46,000
So, um...

99
00:12:46,000 --> 00:12:51,000
Do you know, are they heavy samples from the nether target?

100
00:12:51,000 --> 00:12:54,000
We might.

101
00:12:55,000 --> 00:13:01,000
Yeah, we can check. We have the code breakdown, so it'd be a quick check.

102
00:13:01,000 --> 00:13:08,000
Let me check the numbers.

103
00:13:08,000 --> 00:13:11,000
That was the one we passed on the way here on the left, right?

104
00:13:11,000 --> 00:13:12,000
No, no.

105
00:13:12,000 --> 00:13:14,000
It's by cable.

106
00:13:14,000 --> 00:13:15,000
Yeah.

107
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So, are we back in?

108
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We're going to go into this, um...

109
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Sometimes people do odd things up there.

110
00:13:28,000 --> 00:13:32,000
We probably saw Ethan play football years ago.

111
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He's out proud alone.

112
00:13:34,000 --> 00:13:36,000
Oh, cool. That's awesome.

113
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2017, yeah. All my classes were involved in that.

114
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Oh, yeah.

115
00:13:40,000 --> 00:13:41,000
Never had class in here.

116
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You missed your class.

117
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You missed your dream fish.

118
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But you would have... Yeah, you missed your chance.

119
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How did you get out of having a...

120
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Either heads take like an environmental class.

121
00:13:49,000 --> 00:13:51,000
Yeah, I did, um, I went to community college.

122
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I knew you were very good.

123
00:13:52,000 --> 00:13:53,000
Okay.

124
00:13:53,000 --> 00:13:55,000
I kind of got all the same care that came up here for two years.

125
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Nice.

126
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From my degree.

127
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Yeah.

128
00:13:58,000 --> 00:13:59,000
Good.

129
00:13:59,000 --> 00:14:04,000
All right, so, um, we have a new Mercury Analyzer this year.

130
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We're very excited about it.

131
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It's this DNA 80, so it stands for direct Mercury Analyzer.

132
00:14:10,000 --> 00:14:16,000
Um, the thing we are excited about with this analyzer is that, as it says,

133
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it's a direct Mercury Analyzer.

134
00:14:18,000 --> 00:14:22,000
So in the past, when we were doing Mercury Analysis, we would have to, um,

135
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digest the samples with concentrated hot acids, and that was dangerous.

136
00:14:29,000 --> 00:14:34,000
And not really great for the environment, but in order to get from the fish sample

137
00:14:34,000 --> 00:14:39,000
to having the Mercury released in a form that the instrument was able to measure it,

138
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that's what we had to do previously.

139
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But this new instrument actually does thermal decomposition

140
00:14:46,000 --> 00:14:48,000
of the fish tissue.

141
00:14:48,000 --> 00:14:53,000
So basically what it does is just heat the fish up really hot over a short period of time.

142
00:14:53,000 --> 00:14:58,000
It takes about six minutes to get a Mercury concentration from a fish, um,

143
00:14:58,000 --> 00:14:59,000
using this instrument.

144
00:14:59,000 --> 00:15:03,000
And so, yeah, we put a sample into a sample boat.

145
00:15:03,000 --> 00:15:04,000
I'll demonstrate that.

146
00:15:04,000 --> 00:15:10,000
Uh, we push start and it gives us a concentration after six minutes.

147
00:15:10,000 --> 00:15:15,000
Again, we do have a lot of quality assurance that goes in prior to that.

148
00:15:15,000 --> 00:15:19,000
So we make up standards of known concentrations of Mercury.

149
00:15:19,000 --> 00:15:23,000
Uh, we do duplicate analysis of fish to make sure that we're getting the same

150
00:15:23,000 --> 00:15:25,000
concentration from the same fish.

151
00:15:25,000 --> 00:15:29,000
If we repeat it, we do spike concentrations.

152
00:15:29,000 --> 00:15:32,000
We spike samples with a known amount of Mercury.

153
00:15:32,000 --> 00:15:36,000
So we can subtract that known amount of Mercury and make sure that, again,

154
00:15:36,000 --> 00:15:39,000
we're recovering all of the Mercury through the process.

155
00:15:39,000 --> 00:15:43,000
And then one of the other important things that we do is we have a certified reference standard

156
00:15:43,000 --> 00:15:47,000
that we run multiple times a day with each one of the fish samples,

157
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or each one of the groups of fish samples that we do.

158
00:15:50,000 --> 00:15:55,000
So if we do 30 samples in a day, we would do, um, our certified reference material

159
00:15:55,000 --> 00:15:57,000
probably three times.

160
00:15:57,000 --> 00:16:01,000
And the material that we use is called a dorm sample.

161
00:16:01,000 --> 00:16:03,000
It is from Canada.

162
00:16:03,000 --> 00:16:06,000
And it's actually dogfish liver tissue.

163
00:16:06,000 --> 00:16:11,000
So it is a fish tissue, so it's similar tissue type to what we're analyzing.

164
00:16:11,000 --> 00:16:16,000
Um, so it's important that we're using matrices that are similar in type.

165
00:16:16,000 --> 00:16:21,000
So, um, so I'll go ahead and show you the analysis that we do.

166
00:16:21,000 --> 00:16:25,000
So the first thing that we do is we weigh out a sample.

167
00:16:25,000 --> 00:16:31,000
So in the other lab, we saw the sample being ground and put into these vials.

168
00:16:31,000 --> 00:16:33,000
So I took these out earlier.

169
00:16:33,000 --> 00:16:39,000
Um, again, when we did the acid rinse in the lab across the hall,

170
00:16:39,000 --> 00:16:45,000
we do that here in between samples to make sure that we're not carrying over any mercury.

171
00:16:45,000 --> 00:16:51,000
So we just have a little bit of acid there that I was soaking in.

172
00:16:51,000 --> 00:17:00,000
Um, I already put the boat here and then I need to turn the balance on.

173
00:17:00,000 --> 00:17:08,000
Kind of mix this up to make sure that if there was any moisture in the vial,

174
00:17:08,000 --> 00:17:11,000
it's mixed back in with the fish.

175
00:17:11,000 --> 00:17:18,000
Um, and then we weigh out approximately .2 grams of fish.

176
00:17:18,000 --> 00:17:25,000
Triciest part is getting it into the boat and not everywhere else.

177
00:17:25,000 --> 00:17:33,000
I'm going to stop right there.

178
00:17:33,000 --> 00:17:42,000
It's 1.187 grams.

179
00:17:42,000 --> 00:17:58,000
Now we record the weight.

180
00:17:58,000 --> 00:18:03,000
So over here, there is a previous sample that I did in there.

181
00:18:03,000 --> 00:18:10,000
That's the dorm sample to make sure that we were getting the concentrations that we wanted this morning.

182
00:18:10,000 --> 00:18:12,000
So the sample's in there.

183
00:18:12,000 --> 00:18:18,000
Then I have to enter the mass and the identification here on the screen of the sample.

184
00:18:18,000 --> 00:18:25,000
So I already did the identification code, but the amount that I weighed out, I need to enter here.

185
00:18:25,000 --> 00:18:34,000
So it's .187 grams and then a check mark.

186
00:18:34,000 --> 00:18:43,000
Oh, well, let's try that again.

187
00:18:43,000 --> 00:18:51,000
Okay, so .187 grams, check mark, and then I just go ahead and press this green light.

188
00:18:51,000 --> 00:19:02,000
When I press this arrow, what will happen is this carousel will rotate and there's an arm here that will pick up the sample and it will push it into the furnace.

189
00:19:02,000 --> 00:19:07,000
Then we can't see anything beyond that, but we'll see on the screen as it measures.

190
00:19:07,000 --> 00:19:10,000
So I'm going to push start.

191
00:19:10,000 --> 00:19:14,000
So does that quick turn?

192
00:19:14,000 --> 00:19:18,000
Picks up the sample and puts it into the sample combustion chamber.

193
00:19:18,000 --> 00:19:23,000
The light here changes so that we know that it's in the process of doing an analysis.

194
00:19:23,000 --> 00:19:27,000
And while it's doing the analysis that will be red.

195
00:19:27,000 --> 00:19:32,000
And then what we can do is we can click on here to watch the signal.

196
00:19:32,000 --> 00:19:45,000
So what's happening is there's a spectrophotometer that's built into this instrument and it's able to measure the mercury absorption.

197
00:19:45,000 --> 00:19:50,000
The amount of mercury that is absorbed is relative to how much is there.

198
00:19:50,000 --> 00:19:55,000
So that's when we do a standard curve so we can determine a known amount.

199
00:19:55,000 --> 00:19:58,000
We'll have this absorption so we can make a line out of it.

200
00:19:58,000 --> 00:20:01,000
A calibration curve is what we would call it.

201
00:20:01,000 --> 00:20:09,000
And then when we run a sample and get an absorption, we can just calculate what concentration is in the sample.

202
00:20:09,000 --> 00:20:17,000
So you can see that on the screen it's showing we have an absorption that's coming off from that particular sample.

203
00:20:17,000 --> 00:20:21,000
This instrument has three different cells built into it.

204
00:20:21,000 --> 00:20:27,000
So what it will do is it will analyze the concentration in each one of the cells individually.

205
00:20:27,000 --> 00:20:36,000
And it will give us a result based on where the best fit is for the line within which one of those cells.

206
00:20:36,000 --> 00:20:40,000
So it takes about six minutes to get an analysis here.

207
00:20:40,000 --> 00:20:43,000
But that's what the process is.

208
00:20:43,000 --> 00:20:45,000
So you can see the graph.

209
00:20:45,000 --> 00:20:46,000
Yep, you can see the graph.

210
00:20:46,000 --> 00:20:49,000
It'll be a little bit easier once we're completely done.

211
00:20:49,000 --> 00:20:50,000
I can show you.

212
00:20:50,000 --> 00:20:52,000
So that's the sample coming off.

213
00:20:52,000 --> 00:20:53,000
We can come back to here.

214
00:20:53,000 --> 00:20:55,000
But this is a calibration curve.

215
00:20:55,000 --> 00:21:00,000
So here we had going across the bottom here.

216
00:21:00,000 --> 00:21:02,000
It says mercury nanograms.

217
00:21:02,000 --> 00:21:06,000
So we know how much mercury we had in our standards.

218
00:21:06,000 --> 00:21:09,000
And then this is the absorption here on the y-axis.

219
00:21:09,000 --> 00:21:16,000
And so it's graphing the concentration versus the absorbance.

220
00:21:16,000 --> 00:21:25,000
And it's because we're looking at a broad difference of concentrations here.

221
00:21:25,000 --> 00:21:27,000
It's actually an s-shaped curve.

222
00:21:27,000 --> 00:21:35,000
If you look at a smaller range of concentrations, you have more of a linear curve.

223
00:21:35,000 --> 00:21:41,000
And so what will happen is we'll get an absorption based on our sample there.

224
00:21:41,000 --> 00:21:46,000
And using this curve, we're able to calculate the concentration.

225
00:21:46,000 --> 00:21:48,000
So that's the calibration curve.

226
00:21:48,000 --> 00:21:56,000
But if we go back to measure, this is the sample right now that's being analyzed.

227
00:21:56,000 --> 00:21:58,000
So is it for you?

228
00:21:58,000 --> 00:21:59,000
Can you look at the angle?

229
00:21:59,000 --> 00:22:01,000
Ooh, that's normal.

230
00:22:01,000 --> 00:22:02,000
That's high.

231
00:22:02,000 --> 00:22:03,000
That's low.

232
00:22:03,000 --> 00:22:04,000
Not now.

233
00:22:04,000 --> 00:22:05,000
Not yet.

234
00:22:05,000 --> 00:22:06,000
Not yet.

235
00:22:06,000 --> 00:22:11,000
Because it has the three cells, and it hasn't done all three of them yet.

236
00:22:11,000 --> 00:22:14,000
So it's a little bit hard at this particular point.

237
00:22:14,000 --> 00:22:17,000
But once it's done running, I can say, oh, yeah, that's...

238
00:22:17,000 --> 00:22:19,000
It'll give us the concentration.

239
00:22:19,000 --> 00:22:23,000
Well, if we have a few more minutes, then you can probably just get some close shots.

240
00:22:23,000 --> 00:22:37,000
Just we're lucky we had a process where when we do every sample we analyze, we charge our cells basically for using it.

241
00:22:37,000 --> 00:22:41,000
So it's coming hard to get grant funding for new instruments.

242
00:22:41,000 --> 00:22:49,000
So we have to kind of, because we've been at this for so many years, we know we have to set aside money as we're going ahead.

243
00:22:49,000 --> 00:22:53,000
This is, like I said, I've been here since 1997 working on it.

244
00:22:53,000 --> 00:22:55,000
This is the fourth instrument I've used.

245
00:22:55,000 --> 00:22:59,000
So, yeah, we've had to replace three in the time that I've been having.

246
00:22:59,000 --> 00:23:03,000
That can analyze a variety of different metals.

247
00:23:03,000 --> 00:23:06,000
We've used that on projects with Glyphwitt.

248
00:23:06,000 --> 00:23:13,000
We've done things where they had a project a couple years ago that was because of the Thanksgiving project.

249
00:23:13,000 --> 00:23:18,000
And that one, they were looking at...

250
00:23:18,000 --> 00:23:19,000
So it's done now.

251
00:23:19,000 --> 00:23:20,000
That's quick.

252
00:23:20,000 --> 00:23:21,000
I guess it's quick.

253
00:23:21,000 --> 00:23:22,000
It's so quick.

254
00:23:22,000 --> 00:23:23,000
It's so quick.

255
00:23:23,000 --> 00:23:26,000
And then look, so you saw what the tissue looked like.

256
00:23:26,000 --> 00:23:35,000
Fire to, you know, when I put it into the sample boat, now that you're looking at it, it's just ash that's left in there.

257
00:23:35,000 --> 00:23:39,000
So it's a nice procedure too, because we don't have a lot.

258
00:23:39,000 --> 00:23:41,000
We're not creating hazardous waste.

259
00:23:41,000 --> 00:23:43,000
Where does the mercury go now?

260
00:23:43,000 --> 00:23:49,000
The mercury that was there is, there's a trap that's on the back of this instrument.

261
00:23:49,000 --> 00:23:50,000
It's a carbon trap.

262
00:23:50,000 --> 00:23:53,000
So it just catches the mercury vapor that's in there.

263
00:23:53,000 --> 00:23:58,000
That has to be replaced probably every year based on how often we use the instrument.

264
00:23:58,000 --> 00:24:05,000
But it's just, it's a small, about this quantity of carbon activated charcoal basically.

265
00:24:05,000 --> 00:24:07,000
And so that is a hazardous waste.

266
00:24:08,000 --> 00:24:17,000
But prior, when we had the other instrument, we were creating significantly more than that because we had to add so many chemicals to do the digestion.

267
00:24:17,000 --> 00:24:20,000
So now you can look at the graph.

268
00:24:20,000 --> 00:24:33,000
And you can see what this is, the way that you look at this is, it's looking at the peak height of the curves.

269
00:24:34,000 --> 00:24:40,000
And so this is, because there's the two cells, it's got two different peaks.

270
00:24:40,000 --> 00:24:43,000
And actually there's a third one down here.

271
00:24:43,000 --> 00:24:48,000
And so this was like one of the cells, a second cell and the third cell.

272
00:24:48,000 --> 00:24:54,000
So what it does is it just chooses the one that's the best fit.

273
00:24:55,000 --> 00:25:12,000
So if we go back to the result right here on the screen, it says that that sample was 351 micrograms per kilogram of mercury, which usually we would report it in milligrams per kilogram.

274
00:25:12,000 --> 00:25:18,000
So it would be like 0.351 milligrams per kilogram.

275
00:25:18,000 --> 00:25:20,000
So I would say that's relatively low.

276
00:25:25,000 --> 00:25:27,000
I don't know what the cutoff is now.

277
00:25:27,000 --> 00:25:33,000
It used to be one, but I think they've lowered it for consumption advisories.

278
00:25:33,000 --> 00:25:39,000
So this is a little more than a third of compared to a good enzyme.

279
00:25:39,000 --> 00:25:40,000
Yeah.

280
00:25:40,000 --> 00:25:41,000
Yeah.

281
00:25:41,000 --> 00:25:45,000
So I would say this is a pretty healthy fish to eat.

282
00:25:45,000 --> 00:25:49,000
So are you able to differentiate the types of mercury you're looking at?

283
00:25:49,000 --> 00:25:50,000
No.

284
00:25:51,000 --> 00:25:54,000
So this is a total mercury analyzer.

285
00:25:54,000 --> 00:26:11,000
So when you talk about mercury, certainly the methyl mercury is the part that's the worst mercury because the most bio available and most able to cross the cell membranes and things like that.

286
00:26:11,000 --> 00:26:21,000
So that's the more dangerous form, but most of the mercury that's present in fish is present as methyl mercury.

287
00:26:21,000 --> 00:26:24,000
So, but this is a total mercury.

288
00:26:24,000 --> 00:26:29,000
If there was something there that was not methylated, we would still catch it.

289
00:26:29,000 --> 00:26:30,000
Okay.

290
00:26:30,000 --> 00:26:31,000
Cool.

291
00:26:31,000 --> 00:26:33,000
Can we have you two up another?

292
00:26:33,000 --> 00:26:34,000
Absolutely.

293
00:26:35,000 --> 00:26:37,000
Probably part Ethan right over here.

294
00:26:37,000 --> 00:26:38,000
Does that really want to be?

295
00:26:38,000 --> 00:26:39,000
Does that make sense?

296
00:26:39,000 --> 00:26:40,000
For what?

297
00:26:40,000 --> 00:26:41,000
To see her lower another one.

298
00:26:41,000 --> 00:26:42,000
Yeah.

299
00:26:42,000 --> 00:26:49,000
And then before you put it over here, Ethan will probably reposition just so we can see it going in and it all but the wheel's spinning in.

300
00:27:05,000 --> 00:27:06,000
Okay.

301
00:27:06,000 --> 00:27:07,000
All right.

302
00:27:07,000 --> 00:27:08,000
All right.

303
00:27:08,000 --> 00:27:09,000
All right.

304
00:27:09,000 --> 00:27:10,000
All right.

305
00:27:10,000 --> 00:27:11,000
All right.

306
00:27:11,000 --> 00:27:12,000
All right.

307
00:27:12,000 --> 00:27:13,000
All right.

308
00:27:13,000 --> 00:27:14,000
All right.

309
00:27:14,000 --> 00:27:15,000
All right.

310
00:27:15,000 --> 00:27:16,000
All right.

311
00:27:16,000 --> 00:27:17,000
All right.

312
00:27:17,000 --> 00:27:18,000
All right.

313
00:27:18,000 --> 00:27:19,000
All right.

314
00:27:19,000 --> 00:27:20,000
All right.

315
00:27:20,000 --> 00:27:21,000
All right.

316
00:27:21,000 --> 00:27:22,000
All right.

317
00:27:22,000 --> 00:27:23,000
All right.

318
00:27:23,000 --> 00:27:24,000
All right.

319
00:27:24,000 --> 00:27:25,000
All right.

320
00:27:25,000 --> 00:27:26,000
All right.

321
00:27:26,000 --> 00:27:27,000
All right.

322
00:27:27,000 --> 00:27:28,000
All right.

323
00:27:28,000 --> 00:27:39,000
All right.

324
00:27:39,000 --> 00:27:42,000
So again, we just mix it up to make sure that it's homogenous in there.

325
00:27:42,000 --> 00:27:47,000
And if there's any moisture at the bottom, we're mixing it kind of back in.

326
00:27:47,000 --> 00:28:09,000
All right.

327
00:28:09,000 --> 00:28:10,000
All right.

328
00:28:10,000 --> 00:28:19,000
All right.

329
00:28:19,000 --> 00:28:39,800
All right.

330
00:28:39,800 --> 00:28:46,800
Okay, which slot are you going to get in?

331
00:28:46,800 --> 00:28:47,800
Three.

332
00:28:47,800 --> 00:28:48,800
Yeah.

333
00:28:48,800 --> 00:28:49,800
Perfect.

334
00:28:49,800 --> 00:28:50,800
Yep.

335
00:28:50,800 --> 00:28:51,800
Okay.

336
00:28:51,800 --> 00:28:57,560
So then we put the sample into slot three.

337
00:28:57,560 --> 00:29:02,800
And over here, we need this meal is going to spin and then the little...

338
00:29:02,800 --> 00:29:03,800
Yep.

339
00:29:03,800 --> 00:29:05,800
So I'm going to push this into the front.

340
00:29:05,800 --> 00:29:06,800
Yep.

341
00:29:06,800 --> 00:29:10,800
I already typed in the sample identification here.

342
00:29:10,800 --> 00:29:16,800
Then we have to enter the mass.

343
00:29:16,800 --> 00:29:24,800
Two, six, eight.

344
00:29:24,800 --> 00:29:37,800
Accept it.

345
00:29:37,800 --> 00:29:43,800
So now we have the sample identification and the sample weight.

346
00:29:43,800 --> 00:29:50,800
And we identify that we're doing this as a normal measurement.

347
00:29:50,800 --> 00:29:57,800
And then we press go.

348
00:30:20,800 --> 00:30:49,800
This screen is showing what temperatures that is actually happening in the difference.

349
00:30:49,800 --> 00:30:53,800
So it goes up to...

350
00:30:53,800 --> 00:31:00,800
The last one goes up to 750 degrees Celsius.

351
00:31:00,800 --> 00:31:03,800
So that's how it combusts the sample.

352
00:31:03,800 --> 00:31:12,800
It does that thermal decomposition to get the mercury in the state that we need to measure again.

353
00:31:12,800 --> 00:31:19,800
Why was its flavor that way?

354
00:31:19,800 --> 00:31:26,800
Yeah.

355
00:31:26,800 --> 00:31:44,800
So that's the little bar that shows how much time it's left.

356
00:31:44,800 --> 00:31:45,800
Yes.

357
00:31:45,800 --> 00:31:46,800
Yep.

358
00:31:46,800 --> 00:31:56,800
So this is the total time we ran that to where we're at.

359
00:31:56,800 --> 00:32:15,800
Yep.

360
00:32:15,800 --> 00:32:18,800
So that one was very similar to concentration.

361
00:32:18,800 --> 00:32:24,800
The first one we did was 351 micrograms per kilogram.

362
00:32:24,800 --> 00:32:28,800
The second one we did was 359 micrograms per kilogram.

363
00:32:28,800 --> 00:32:31,800
They're both from the same lake, but the second one, yeah.

364
00:32:31,800 --> 00:32:33,800
They're both from the same lake.

365
00:32:33,800 --> 00:32:39,800
It would be interesting to go and look at the lengths to see how close in size they were.

366
00:32:39,800 --> 00:32:42,800
But oftentimes from the same lake there.

367
00:32:42,800 --> 00:32:46,800
And that's what I was talking about, the water quality, the fish are water quality.

368
00:32:46,800 --> 00:32:52,800
To capture super close-ups of putting the sample in the tray and stuff like that.

369
00:32:52,800 --> 00:32:54,800
I could if you think that's important.

370
00:32:54,800 --> 00:32:56,800
I think it'd be kind of fun sequencing.

371
00:32:56,800 --> 00:32:57,800
Sure.

372
00:32:57,800 --> 00:32:58,800
To be fun with wood shots.

373
00:32:58,800 --> 00:33:01,800
Yeah, like some kind of telephoto.

374
00:33:01,800 --> 00:33:03,800
Yeah, I could try that.

375
00:33:03,800 --> 00:33:05,800
It's just space I'd have to be like...

376
00:33:05,800 --> 00:33:07,800
If you would mind turning towards me?

377
00:33:07,800 --> 00:33:08,800
Sure.

378
00:33:08,800 --> 00:33:10,800
That's all right.

379
00:33:10,800 --> 00:33:13,800
Just to make sure across the board we're getting all.

380
00:33:13,800 --> 00:33:17,800
I do have a tissue course in California this Friday.

381
00:33:17,800 --> 00:33:18,800
Oh, okay.

382
00:33:18,800 --> 00:33:19,800
Must be on site.

383
00:33:19,800 --> 00:33:20,800
Oh, great.

384
00:33:20,800 --> 00:33:21,800
Sometimes.

385
00:33:21,800 --> 00:33:22,800
Yeah.

386
00:33:22,800 --> 00:33:23,800
That might be high too.

387
00:33:23,800 --> 00:33:24,800
That's good.

388
00:33:24,800 --> 00:33:32,800
So for this, I think if you can just kind of point out to Ethan where you're going to go next to allow him to focus.

389
00:33:32,800 --> 00:33:33,800
Yep.

390
00:33:33,800 --> 00:33:34,800
It's harder to get a depth of field on this.

391
00:33:34,800 --> 00:33:35,800
Yeah.

392
00:33:35,800 --> 00:33:36,800
So, okay.

393
00:33:36,800 --> 00:33:38,800
So I'm going to take a boat from here.

394
00:33:38,800 --> 00:33:40,800
Put it on there.

395
00:33:40,800 --> 00:33:41,800
Yep.

396
00:33:41,800 --> 00:33:43,800
And then I'll do the mix.

397
00:33:43,800 --> 00:33:45,800
I'll take that here.

398
00:33:45,800 --> 00:33:47,800
We can move this out of the way.

399
00:33:47,800 --> 00:33:48,800
It's not better.

400
00:33:48,800 --> 00:33:49,800
Sure.

401
00:33:49,800 --> 00:33:52,800
It would like that not there too.

402
00:33:52,800 --> 00:33:53,800
Okay.

403
00:33:53,800 --> 00:33:54,800
Sounds good.

404
00:33:54,800 --> 00:33:55,800
Yeah.

405
00:33:55,800 --> 00:33:56,800
Do your thing.

406
00:33:56,800 --> 00:33:57,800
All right.

407
00:34:02,800 --> 00:34:04,800
Grab it by the tab.

408
00:34:09,800 --> 00:34:10,800
Okay.

409
00:34:10,800 --> 00:34:12,800
Tear it.

410
00:34:12,800 --> 00:34:17,800
So we zeroed out and then I'm going to grab this vial.

411
00:34:17,800 --> 00:34:18,800
Okay.

412
00:34:18,800 --> 00:34:20,800
Whenever you're ready.

413
00:34:20,800 --> 00:34:21,800
Okay.

414
00:34:21,800 --> 00:34:23,800
And I'll grab this.

415
00:34:23,800 --> 00:34:24,800
Okay.

416
00:34:27,800 --> 00:34:31,800
And I need to rinse it over there, but I can move this again.

417
00:34:39,800 --> 00:34:48,800
I'm going to grab a camera, but keep that there.

418
00:34:48,800 --> 00:34:53,800
Then I'm going to mix the sample up with in the vial here.

419
00:34:53,800 --> 00:34:58,800
It's not good there.

420
00:34:58,800 --> 00:35:07,800
And then I'll take a little bit of this and put it in the boat.

421
00:35:07,800 --> 00:35:14,800
Okay.

422
00:35:14,800 --> 00:35:21,800
Okay.

423
00:35:21,800 --> 00:35:26,800
Okay.

424
00:35:26,800 --> 00:35:35,800
Make sure the cord lights.

425
00:35:35,800 --> 00:35:45,800
And then that's it, it'll go back over there then.

426
00:35:45,800 --> 00:35:46,800
That's good.

427
00:35:59,800 --> 00:36:00,800
Okay.

428
00:36:06,800 --> 00:36:08,800
Okay, whatever you're in.

429
00:36:08,800 --> 00:36:09,800
Okay.

430
00:36:12,800 --> 00:36:14,800
What do you think possible to do that again?

431
00:36:14,800 --> 00:36:16,800
Yeah, let's shake it this time.

432
00:36:16,800 --> 00:36:17,800
No, no.

433
00:36:17,800 --> 00:36:20,800
I'm too, I'm too, I'm too, much like telephoto less.

434
00:36:22,800 --> 00:36:24,800
Okay, just look it up a little higher if you don't mind.

435
00:36:24,800 --> 00:36:26,800
And then whenever you're ready, go ahead and go.

436
00:36:26,800 --> 00:36:27,800
Okay.

437
00:36:27,800 --> 00:36:28,800
Okay.

438
00:36:29,800 --> 00:36:30,800
Perfect.

439
00:36:30,800 --> 00:36:31,800
And close the glass thing.

440
00:36:32,800 --> 00:36:33,800
Perfect.

441
00:36:33,800 --> 00:36:34,800
Okay.

442
00:36:35,800 --> 00:36:37,800
I was shaking too.

443
00:36:47,800 --> 00:36:48,800
All right.

444
00:36:48,800 --> 00:36:51,800
And then when I press the green button that will go ahead.

445
00:36:51,800 --> 00:36:52,800
All right.

446
00:36:55,800 --> 00:36:56,800
Okay.

447
00:36:57,800 --> 00:36:58,800
Okay.

448
00:37:03,800 --> 00:37:04,800
Perfect.

449
00:37:04,800 --> 00:37:05,800
Yeah.

450
00:37:05,800 --> 00:37:07,800
Oh, so much of this green.

451
00:37:07,800 --> 00:37:08,800
So I see what you can see.

452
00:37:08,800 --> 00:37:09,800
Yeah.

453
00:37:09,800 --> 00:37:11,800
So then I can, oh, that's exactly what we're looking for.

454
00:37:11,800 --> 00:37:12,800
Perfect.

455
00:37:14,800 --> 00:37:15,800
Okay.

456
00:37:15,800 --> 00:37:16,800
Okay.

457
00:37:16,800 --> 00:37:17,800
Cool.

458
00:37:18,800 --> 00:37:19,800
Ah.

459
00:37:19,800 --> 00:37:29,800
It's really a pretty impressive body of work that we've been able to keep all that.

460
00:37:29,800 --> 00:37:31,800
And I was, we were talking.

461
00:37:31,800 --> 00:37:33,800
Oh, I had to wash my hands.

462
00:37:33,800 --> 00:37:35,800
They just smell like gloves now.

463
00:37:39,800 --> 00:37:40,800
Wow.

464
00:37:40,800 --> 00:37:42,800
You're doing the political stuff here.

465
00:37:42,800 --> 00:37:43,800
They're busy.

466
00:37:43,800 --> 00:37:44,800
Yeah.

467
00:37:44,800 --> 00:37:45,800
Yeah.

468
00:37:45,800 --> 00:37:46,800
Yeah.

469
00:38:07,800 --> 00:38:08,800
Yes.

470
00:38:08,800 --> 00:38:12,800
Except the biggest difference is we can almost, some of those we ended up having just,

471
00:38:12,800 --> 00:38:15,800
we tried analyzing them here, but there was a lot of background noise.

472
00:38:15,800 --> 00:38:22,800
We couldn't, like, I think stuff that was in the organics when we did, you know, because

473
00:38:22,800 --> 00:38:28,800
that's also a digestion with concentrated acids and then you have to break it down with us because

474
00:38:28,800 --> 00:38:32,800
we wanted to give you good results, but we just couldn't get them with that.

475
00:38:32,800 --> 00:38:33,800
Unfortunately.

476
00:38:35,800 --> 00:38:36,800
Okay.

477
00:38:36,800 --> 00:38:37,800
I'll get up your ways.

478
00:38:38,800 --> 00:38:39,800
All right.

479
00:38:39,800 --> 00:38:40,800
Sorry.

480
00:38:40,800 --> 00:38:41,800
Just one second.

481
00:38:41,800 --> 00:38:45,800
I guess you want to show and tell?

482
00:38:45,800 --> 00:38:46,800
Yeah.

483
00:38:46,800 --> 00:38:47,800
Absolutely.

484
00:38:47,800 --> 00:38:49,800
What do we, what do we have in here?

485
00:38:49,800 --> 00:38:50,800
Right.

486
00:38:50,800 --> 00:38:54,800
We have years worth of fish samples in here.

487
00:38:55,800 --> 00:39:01,800
That we've gotten from Glyphwick and you can see, we have some from 2013, 2011.

488
00:39:01,800 --> 00:39:22,800
We have a variety of, both, this one is white fish, lake trout, we have a lot of spring walleye

489
00:39:22,800 --> 00:39:23,800
samples.

490
00:39:23,800 --> 00:39:31,800
By far, the most, what we do is spring walleye, so we get between 350 and 450 spring walleye

491
00:39:31,800 --> 00:39:38,800
samples annually from Glyphwick and we've been analyzing those for Mercury and every year

492
00:39:38,800 --> 00:39:42,800
when we are done analyzing them, we store them in these freezers.

493
00:39:42,800 --> 00:39:49,800
So we archive the samples in case anyone would like to analyze them for something later on

494
00:39:49,800 --> 00:39:53,800
or in case we have to go back and answer other questions about Mercury.

495
00:39:53,800 --> 00:40:02,800
So we have four freezers that are full, this full of Mercury samples dating back to 1996.

496
00:40:02,800 --> 00:40:09,800
So it's been a really good archive so that people can go back and look at potential metals

497
00:40:09,800 --> 00:40:14,800
that become other metals or other chemicals that become of interest, that we didn't know

498
00:40:14,800 --> 00:40:19,800
were a problem and now we're learning are more problematic, such as potentially PFAS.

499
00:40:19,800 --> 00:40:25,800
It seems to be the most obvious one that you, I mean it does seem like that's an open,

500
00:40:25,800 --> 00:40:30,800
an invitation to figure out, okay, when did it first start appearing in fish?

501
00:40:30,800 --> 00:40:31,800
It is.

502
00:40:31,800 --> 00:40:38,800
One thing we have to be a little bit careful about with the archive samples is the processing

503
00:40:38,800 --> 00:40:46,800
that we used from the full laying to the grinding to the sample containers themselves.

504
00:40:46,800 --> 00:40:49,800
Is it compatible with PFAS analysis?

505
00:40:49,800 --> 00:40:55,800
Because we don't want to be a part of the problem in the analysis of that.

506
00:40:55,800 --> 00:40:57,800
But it is a potential source.

507
00:40:57,800 --> 00:41:03,800
We've had people go back and look at PCBs and other different things that are in those samples.

508
00:41:03,800 --> 00:41:10,800
So problem this out for me, obviously your research institute, what is it that it does?

509
00:41:10,800 --> 00:41:14,800
I mean you're part of this relationship with Glyphwyth, but you've given me the broader picture

510
00:41:14,800 --> 00:41:19,800
in the context of wildlife what we're interested in, but a lot of the research that goes into that.

511
00:41:19,800 --> 00:41:24,800
Right, so the Lake Superior Research Institute has been here.

512
00:41:24,800 --> 00:41:32,800
We do grant funded research and we've had a relationship with Glyphwyth since the middle of the 1990s.

513
00:41:32,800 --> 00:41:35,800
So we receive samples from them.

514
00:41:35,800 --> 00:41:45,800
We do the mercury analysis on them and then we give the analysis the concentrations of mercury back to Glyphwyth.

515
00:41:45,800 --> 00:41:59,800
And then they use that information to make maps where they do consumption advisories of lakes that are in the seated territories.

516
00:41:59,800 --> 00:42:03,800
And they do it on a basis of a couple of different things.

517
00:42:03,800 --> 00:42:09,800
They do the women of childbearing age and young children.

518
00:42:09,800 --> 00:42:17,800
And then they have the adults that are beyond childbearing age and males because mercury is a neurotoxin.

519
00:42:17,800 --> 00:42:28,800
And so it's more of a concern in younger children and women of childbearing age than it is in adult males or women beyond childbearing age.

520
00:42:28,800 --> 00:42:31,800
So you're one of the first ones to see the info come out.

521
00:42:31,800 --> 00:42:33,800
Have there been times where you're like, whoa.

522
00:42:33,800 --> 00:42:38,800
There are some times I see a fish that I go, oh well I would not want to eat the fish from that lake.

523
00:42:38,800 --> 00:42:45,800
And there are certain lakes that are certainly higher in concentration in mercury than other lakes.

524
00:42:45,800 --> 00:42:51,800
It has a lot to do with the ecology of just what's around certain lakes.

525
00:42:51,800 --> 00:43:02,800
And certain lakes what kind of if they have a lot of swampy areas around them or if they have a lot of rock more like granite or basalt around them.

526
00:43:02,800 --> 00:43:06,800
That's going to have an impact on how much mercury is present in the fish.

527
00:43:06,800 --> 00:43:11,800
So you said that one was kind of a baseline for when you start to worry.

528
00:43:11,800 --> 00:43:16,800
I guess walk me through because those were like the .35.

529
00:43:16,800 --> 00:43:27,800
Right the fish that we looked at today they were in about the .3 milligrams per kilogram of fish that we were looking at.

530
00:43:27,800 --> 00:43:30,800
Those I would say are not a high concern.

531
00:43:30,800 --> 00:43:38,800
Again it depends on your age and the frequency that you're eating the fish certainly.

532
00:43:39,800 --> 00:43:47,800
My general rule after having done this for many years is that I try not to eat any walleye that are over 20 inches.

533
00:43:47,800 --> 00:43:50,800
That seems to be kind of a good cut off.

534
00:43:50,800 --> 00:43:55,800
It's not safe in every lake to eat fish that are in that size range.

535
00:43:55,800 --> 00:44:00,800
But that's generally I would say a pretty safe area.

536
00:44:01,800 --> 00:44:05,800
So what is the one break threshold?

537
00:44:05,800 --> 00:44:10,800
Where is the point where you said oh that's a lake that no one should be eating this?

538
00:44:10,800 --> 00:44:17,800
I'm not exactly sure right now what the concentration is where we're calling.

539
00:44:17,800 --> 00:44:20,800
Things have changed over the years.

540
00:44:20,800 --> 00:44:29,800
One used to be kind of the mark that we would use as people probably shouldn't be eating any fish that are in that concentration.

541
00:44:30,800 --> 00:44:43,800
So I would say that that certainly would not be eating it but because most people don't know just what they take a fish out of a lake they're not going to know what concentration that is.

542
00:44:43,800 --> 00:44:48,800
Oh I was going to just get a look at the last year we sampled them.

543
00:45:14,800 --> 00:45:33,800
We're going to come in on a Monday and vomit.

544
00:45:33,800 --> 00:45:37,800
And then who gets that job?

545
00:45:37,800 --> 00:45:42,800
So yeah these have alarms we're real excited about them.

546
00:45:48,800 --> 00:45:50,800
Yeah we lost some of that one.

547
00:45:50,800 --> 00:45:55,800
That was last year I think.

548
00:46:07,800 --> 00:46:19,800
We lost some things.

549
00:46:19,800 --> 00:46:24,800
Yeah no problem.

550
00:46:24,800 --> 00:46:29,800
Let's go back in here.

551
00:46:29,800 --> 00:46:33,800
Close it before it starts chirping at us.

552
00:46:33,800 --> 00:46:38,800
Beautiful. It's been updated a lot. It's really nice.

553
00:46:38,800 --> 00:46:43,800
The person that she came, she fixed it, she put her two weeks in.

554
00:46:43,800 --> 00:46:46,800
Okay.

555
00:46:46,800 --> 00:46:59,800
So I guess the story is about the walleye. Why in your estimation? Why is walleye one of the key ones to pay attention to for these kind of issues?

556
00:46:59,800 --> 00:47:08,800
Well I think it's important because especially for the tribes it's such an important food culturally to them.

557
00:47:08,800 --> 00:47:16,800
And it's just a part of many of their ceremonies and their culture and it's important to make sure that we're keeping their population safe.

558
00:47:16,800 --> 00:47:28,800
And looking at how much mercury is present in those and then making these consumption advisories so that people are informed about what is a safe lake to fish in.

559
00:47:28,800 --> 00:47:35,800
How many fish meals they can eat from there a month basically and make sure that they're keeping their families safe.

560
00:47:35,800 --> 00:47:41,800
So when you're doing this work, I mean this is probably just one portion of like the job you're doing.

561
00:47:41,800 --> 00:47:49,800
You talked about you came here the year after this started. What does it mean to you to be part of such a long longitudinal study?

562
00:47:49,800 --> 00:47:58,800
Right. It's amazing to have just the breadth of this and the depth of this study because we've been able to work on this for years.

563
00:47:58,800 --> 00:48:07,800
And I've learned a lot of things as a scientist. I started here just out of graduate school. I ground a lot of fish and now I'm managing the project.

564
00:48:08,800 --> 00:48:25,800
So I was able to see that through. I've been able to work with Glifwick individuals, several different individuals there on writing quality advisories and looking at what's important when we're doing the analysis to make sure that we're answering the questions that are important to them

565
00:48:25,800 --> 00:48:33,800
and doing really good quality work. So we have the quality checks built in like duplicates and standards and reference checks.

566
00:48:33,800 --> 00:48:38,800
So it's important to us. It's great to be able to give that information to people.

567
00:48:38,800 --> 00:48:43,800
And I think we just have a really good relationship with Glifwick and to be able to provide that to them.

568
00:48:43,800 --> 00:48:49,800
And it's an interesting topic too. Like everybody's excited about fishing and everybody loves catching a walleye.

569
00:48:49,800 --> 00:48:53,800
So it's good information to be part of all of that together.

570
00:48:53,800 --> 00:48:58,800
Anything else that you can think of that you want to add or what we've been talking about?

571
00:48:59,800 --> 00:49:02,800
Do you see the trends going?

572
00:49:02,800 --> 00:49:04,800
Yeah, I was worried you were going to ask that.

573
00:49:07,800 --> 00:49:18,800
Part of the problem is that because it's a partnership, one of the things that we do is we analyze the fish and we write the report and we hand it off to Glifwick.

574
00:49:19,800 --> 00:49:28,800
And then you guys make the maps, but I don't have a clear picture of what have been the trends over 30 years.

575
00:49:28,800 --> 00:49:39,800
We should be able to look at that. I think that there were rules enacted to kind of keep mercury emissions lower.

576
00:49:39,800 --> 00:49:43,800
And I think that that did help mercury concentrations in fish.

577
00:49:43,800 --> 00:49:48,800
I think that I'm not sure that we're seeing that as much anymore.

578
00:49:48,800 --> 00:49:56,800
I think that we saw things kind of drop off with mercury concentrations in fish and now they've plateaued and maybe jumped up a little bit.

579
00:49:56,800 --> 00:50:01,800
But I don't know why that is. I think there's a lot of things that can contribute to that.

580
00:50:01,800 --> 00:50:12,800
So that would be it would be really nice to know if we could take a look at the data over those years because we have lakes that we've looked at on five year and three year cycles.

581
00:50:12,800 --> 00:50:25,800
So I think we do have the information that we would be able to look at data and write a really good paper on what are the mercury trends in the seated territories in Wisconsin and Minnesota and Michigan.

582
00:50:25,800 --> 00:50:27,800
So I think that's really important.

583
00:50:27,800 --> 00:50:36,800
Long term over the next 10 to 20 years, is mercury still a bigger concern than PFAS?

584
00:50:37,800 --> 00:50:45,800
That's a good question. I think that we know what the effects of having too much mercury in your body are.

585
00:50:45,800 --> 00:50:49,800
So I think that's not going away at all.

586
00:50:49,800 --> 00:50:55,800
I think right now PFAS is a little bit of an unknown as far as what are the effects on people.

587
00:50:55,800 --> 00:51:00,800
And so I think that research needs to be done to determine the effects.

588
00:51:01,800 --> 00:51:05,800
PFAS analysis is very complicated.

589
00:51:05,800 --> 00:51:11,800
And so I think there needs to be efforts made in that front to make sure we're doing good analysis.

590
00:51:11,800 --> 00:51:22,800
And hopefully 30 years down the road, they've got something like this that they can look back on and say, you know, we've got really good solid results that we're confident in the quality of those results.

591
00:51:23,800 --> 00:51:26,800
Can I get you to say and spell your name and give your title?

592
00:51:26,800 --> 00:51:30,800
Oh, yes, this is going to take a while. My name is really long.

593
00:51:30,800 --> 00:51:40,800
Christine Polkinghorn, C-H-R-I-S-T-I-N-E, the last name is Polkinghorn, P-O-L-K-I-N-G-H-O-R-N-E.

594
00:51:40,800 --> 00:51:45,800
And my title is Research Program Manager at the Lake Superior Research Institute.

595
00:51:45,800 --> 00:51:49,800
Is that technically at UW Superior?

596
00:51:49,800 --> 00:51:50,800
Yes.

597
00:51:51,800 --> 00:51:56,800
Yes, it's at the Lake Superior Research Institute at the University of Wisconsin-Superior.

598
00:51:56,800 --> 00:51:58,800
I'd like to have the...

599
00:51:58,800 --> 00:52:03,800
Yes, and technically, I think it's University of Wisconsin-Superior Lake Superior Research Institute.

600
00:52:03,800 --> 00:52:06,800
I think UW is supposed to come first.

601
00:52:11,800 --> 00:52:12,800
Oh, cool.

602
00:52:12,800 --> 00:52:13,800
1922?

603
00:52:13,800 --> 00:52:14,800
No.

604
00:52:14,800 --> 00:52:16,800
Wow, that's those records.

605
00:52:16,800 --> 00:52:17,800
Yeah.

606
00:52:17,800 --> 00:52:18,800
2022.

607
00:52:18,800 --> 00:52:19,800
Cool.

608
00:52:19,800 --> 00:52:22,800
I realize they're probably going to be fine.

609
00:52:49,800 --> 00:52:50,800
Yeah.

610
00:52:50,800 --> 00:52:51,800
Yeah.

611
00:52:51,800 --> 00:52:52,800
Yeah.

612
00:52:52,800 --> 00:52:53,800
Yeah.

613
00:52:53,800 --> 00:52:54,800
Yeah.

614
00:52:54,800 --> 00:52:55,800
Yeah.

615
00:52:55,800 --> 00:52:56,800
Yeah.

616
00:52:56,800 --> 00:52:57,800
Yeah.

617
00:52:57,800 --> 00:52:58,800
Yeah.

618
00:52:58,800 --> 00:52:59,800
Yeah.

619
00:52:59,800 --> 00:53:00,800
Yeah.

620
00:53:00,800 --> 00:53:01,800
Yeah.

621
00:53:01,800 --> 00:53:02,800
Yeah.

622
00:53:02,800 --> 00:53:03,800
Yeah.

623
00:53:03,800 --> 00:53:04,800
Yeah.

624
00:53:04,800 --> 00:53:05,800
Yeah.

625
00:53:05,800 --> 00:53:06,800
Yeah.

626
00:53:06,800 --> 00:53:07,800
Yeah.

627
00:53:07,800 --> 00:53:08,800
Yeah.

628
00:53:08,800 --> 00:53:09,800
Yeah.

629
00:53:09,800 --> 00:53:10,800
Yeah.

630
00:53:10,800 --> 00:53:11,800
Yeah.

631
00:53:11,800 --> 00:53:12,800
Yeah.

632
00:53:12,800 --> 00:53:13,800
Yeah.

633
00:53:13,800 --> 00:53:14,800
Yeah.

634
00:53:14,800 --> 00:53:15,800
Cool.

635
00:53:15,800 --> 00:53:16,800
Yeah.

636
00:53:16,800 --> 00:53:17,800
All right.

637
00:53:17,800 --> 00:53:18,800
We got here.

638
00:53:18,800 --> 00:53:34,220
We have to turn this over to UW

639
00:53:34,220 --> 00:53:35,800
for five minutes.

640
00:53:35,800 --> 00:53:38,800
So, theyeahsen Summit

641
00:53:38,800 --> 00:53:40,980
is next

642
00:53:40,980 --> 00:53:42,300
background in the screen.

643
00:53:42,300 --> 00:53:56,740
Okay, just holding that there for a second.

644
00:53:56,740 --> 00:54:00,260
Green is now a cog right here, huh?

645
00:54:00,260 --> 00:54:01,260
Mm-hmm.

646
00:54:01,260 --> 00:54:02,260
And KG is the code.

647
00:54:02,260 --> 00:54:04,260
Maybe you can put them back.

648
00:54:04,260 --> 00:54:05,260
Okay.

649
00:54:06,260 --> 00:54:12,260
Okay, you grab another one.

650
00:54:12,260 --> 00:54:17,260
Okay, that back too.

651
00:54:17,260 --> 00:54:20,260
I'll just get a closer shot at it.

652
00:54:20,260 --> 00:54:21,260
Okay.

653
00:54:21,260 --> 00:54:26,260
So that's nine fish from that way down here.

654
00:54:26,260 --> 00:54:28,260
That's okay.

655
00:54:28,260 --> 00:54:29,260
Okay.

656
00:54:29,260 --> 00:54:31,260
Typically we get 12, 38.

657
00:54:31,260 --> 00:54:32,260
12.

658
00:54:32,260 --> 00:54:37,260
And Minnesota just created a new model that might can reduce the cycle size down to six.

659
00:54:37,260 --> 00:54:38,260
Really?

660
00:54:38,260 --> 00:54:40,260
Yeah, since we have so much historical data.

661
00:54:40,260 --> 00:54:41,260
Yeah.

662
00:54:41,260 --> 00:54:43,260
They're able to predict using that historical data.

663
00:54:43,260 --> 00:54:47,260
Remember, we may be able to cut it down to six.

664
00:54:47,260 --> 00:54:48,260
Okay.

665
00:54:48,260 --> 00:54:50,260
Then I can double the price for fish.

666
00:54:50,260 --> 00:54:51,260
Yeah.

667
00:54:51,260 --> 00:54:52,260
Okay.

668
00:54:52,260 --> 00:54:53,260
We found it.

669
00:54:53,260 --> 00:54:54,260
Okay.

670
00:54:54,260 --> 00:54:55,260
Thanks.

671
00:54:55,260 --> 00:54:56,260
All right.

672
00:54:56,260 --> 00:54:57,260
Have a good day.

673
00:54:58,260 --> 00:55:01,260
So that's why we want to go box by box.

674
00:55:01,260 --> 00:55:02,260
I know.

675
00:55:02,260 --> 00:55:03,260
Yeah.

676
00:55:03,260 --> 00:55:05,260
It would have been the absolute end.

677
00:55:05,260 --> 00:55:12,260
Karen's doing something completely different now.

678
00:55:12,260 --> 00:55:15,260
She switched to hydrologists.

679
00:55:15,260 --> 00:55:16,260
Yeah.

680
00:55:16,260 --> 00:55:18,260
Does she jump into?

681
00:55:18,260 --> 00:55:19,260
Yeah.

682
00:55:19,260 --> 00:55:20,260
Did you have training in that too?

683
00:55:20,260 --> 00:55:22,260
I mean, she got a degree in that.

684
00:55:22,260 --> 00:55:23,260
Oh, okay.

685
00:55:23,260 --> 00:55:24,260
Oh, no.

686
00:55:24,260 --> 00:55:25,260
Yeah.

687
00:55:26,260 --> 00:55:27,260
Good.

688
00:55:27,260 --> 00:55:28,260
Sure.

689
00:55:28,260 --> 00:55:32,260
There's the actually labeled the link of the company.

690
00:55:32,260 --> 00:55:33,260
Perfect.

691
00:55:33,260 --> 00:55:38,260
Let's follow about the FAL.

692
00:55:38,260 --> 00:55:46,260
Not on there, but most likely.

693
00:55:46,260 --> 00:56:07,260
Okay.

694
00:56:07,260 --> 00:56:08,260
That's great.

695
00:56:08,260 --> 00:56:09,260
Right.

696
00:56:10,260 --> 00:56:13,260
That's my writing.

697
00:56:13,260 --> 00:56:15,260
I can't blame anybody but myself.

698
00:56:15,260 --> 00:56:18,260
I mean, you should have saw one big writing in the day.

699
00:56:18,260 --> 00:56:20,260
But we recognize the name.

700
00:56:20,260 --> 00:56:21,260
Exactly.

701
00:56:21,260 --> 00:56:23,260
I always keep a gel.

702
00:56:23,260 --> 00:56:24,260
Good enough.

703
00:56:24,260 --> 00:56:26,260
I always challenge.

704
00:56:26,260 --> 00:56:28,260
Oh, I.

705
00:56:28,260 --> 00:56:29,260
Okay.

706
00:56:29,260 --> 00:56:31,260
So I signed that.

707
00:56:31,260 --> 00:56:33,260
Does it already have the car?

708
00:56:33,260 --> 00:56:37,260
Do you want to scan it?

709
00:56:37,260 --> 00:56:38,260
Okay.

710
00:56:38,260 --> 00:56:39,260
So that I have a copy.

711
00:56:39,260 --> 00:56:41,260
We should have a copy of that too.

712
00:56:41,260 --> 00:56:42,260
Sorry.

713
00:56:42,260 --> 00:56:43,260
I forgot.

714
00:56:43,260 --> 00:56:44,260
Yeah.

715
00:56:44,260 --> 00:56:45,260
Great.

716
00:56:45,260 --> 00:56:46,260
And Karen sent the.

717
00:56:46,260 --> 00:56:47,260
Yes.

718
00:56:47,260 --> 00:56:48,260
Yeah.

719
00:56:48,260 --> 00:56:49,260
A test.

720
00:56:49,260 --> 00:56:50,260
Yep.

721
00:56:50,260 --> 00:56:51,260
Yep.

722
00:56:51,260 --> 00:56:52,260
Should be the labeled stuff.

723
00:56:52,260 --> 00:56:53,260
Yep.

724
00:56:53,260 --> 00:56:54,260
Yeah.

725
00:56:54,260 --> 00:56:55,260
Whatever I gave back to her.

726
00:56:55,260 --> 00:56:56,260
I just need to scan.

727
00:56:56,260 --> 00:56:57,260
Email.

728
00:56:57,260 --> 00:56:58,260
All right.

729
00:56:58,260 --> 00:56:59,260
All right.

730
00:56:59,260 --> 00:57:00,260
I've not already got a copy.

731
00:57:00,260 --> 00:57:01,260
That's true.

732
00:57:01,260 --> 00:57:03,260
Cause it's not going to be on the clipboard.

733
00:57:03,260 --> 00:57:04,260
Yep.

734
00:57:04,260 --> 00:57:05,260
It's going to stay on the clipboard.

735
00:57:05,260 --> 00:57:06,260
Okay.

736
00:57:06,260 --> 00:57:10,260
And honestly, like, I don't know if it would be something like, but it's not Friday.

737
00:57:10,260 --> 00:57:12,260
I don't want it to be on the clipboard.

738
00:57:12,260 --> 00:57:13,260
Okay.

739
00:57:13,260 --> 00:57:14,260
Okay.

740
00:57:14,260 --> 00:57:15,260
Cause I got it.

741
00:57:15,260 --> 00:57:16,260
I got like.

742
00:57:16,260 --> 00:57:17,260
A little more.

743
00:57:17,260 --> 00:57:18,260
Okay.

744
00:57:18,260 --> 00:57:19,260
Okay.

745
00:57:19,260 --> 00:57:20,260
Okay.

746
00:57:20,260 --> 00:57:21,260
That was.

747
00:57:21,260 --> 00:57:22,260
That was.

748
00:57:22,260 --> 00:57:23,260
Okay.

749
00:57:23,260 --> 00:57:24,260
Okay.

750
00:57:24,260 --> 00:57:25,260
That's pretty good, right?

751
00:57:25,260 --> 00:57:26,260
Yeah.

752
00:57:26,260 --> 00:57:27,260
That's awesome.

753
00:57:27,260 --> 00:57:28,260
Thank you.

754
00:57:28,260 --> 00:57:29,260
I appreciate that.

755
00:57:29,260 --> 00:57:30,260
Yeah.

756
00:57:30,260 --> 00:57:31,260
I feel bad.

757
00:57:31,260 --> 00:57:32,260
It's not going to get more time with the thing.

758
00:57:32,260 --> 00:57:33,260
That's quite all right.

759
00:57:34,260 --> 00:57:35,260
It's one of those little elements.

760
00:57:35,260 --> 00:57:36,260
One second.

761
00:57:36,260 --> 00:57:37,260
Sorry.

762
00:57:37,260 --> 00:57:38,260
Could you start?

763
00:57:38,260 --> 00:57:39,260
Sorry.

764
00:57:39,260 --> 00:57:40,260
Don't worry.

765
00:57:40,260 --> 00:57:41,260
Yeah.

766
00:57:41,260 --> 00:57:42,260
Okay.

767
00:57:42,260 --> 00:57:43,260
Oh, one second.

768
00:57:43,260 --> 00:57:44,260
Okay.

769
00:57:44,260 --> 00:57:51,260
Whatever you're in.

770
00:57:51,260 --> 00:57:52,260
Perfect.

771
00:57:52,260 --> 00:58:13,260
Thank you.

772
00:58:14,260 --> 00:58:23,260
That was like the elementary school science.

773
00:58:23,260 --> 00:58:24,260
Water cycle.

774
00:58:24,260 --> 00:58:25,260
Yeah.

775
00:58:25,260 --> 00:58:28,260
That was like the elementary school science.

776
00:58:28,260 --> 00:58:29,260
Water cycle.

777
00:58:29,260 --> 00:58:30,260
Yeah.

778
00:58:30,260 --> 00:58:31,260
That was things.

779
00:58:31,260 --> 00:58:32,260
Operation.

780
00:58:32,260 --> 00:58:33,260
Yeah.

781
00:58:33,260 --> 00:58:38,260
When I did my yahara 2070 dock, we had to create a graphic for me that showed like the water cycle.

782
00:58:38,260 --> 00:58:42,260
I was kind of thinking that, you know, we did.

783
00:58:42,260 --> 00:58:43,260
Yeah.

784
00:58:43,260 --> 00:58:44,260
So it's like, ooh.

785
00:58:44,260 --> 00:58:45,260
Yeah.

786
00:58:45,260 --> 00:58:46,260
Doing that so well.

787
00:58:46,260 --> 00:58:47,260
I'm like, hipster.

788
00:58:47,260 --> 00:58:48,260
I'm going to.

789
00:58:48,260 --> 00:59:14,260
It's going to shoot.

790
00:59:14,260 --> 00:59:24,260
Yeah.

791
00:59:24,260 --> 00:59:32,260
That's nuts.

792
00:59:32,260 --> 00:59:58,260
Yeah.

793
00:59:58,260 --> 00:59:59,260
Yeah.

794
01:00:00,260 --> 01:00:01,260
Wow.

795
01:00:01,260 --> 01:00:04,260
You get up to it, you know, above 20 inches and it really spikes.

796
01:00:04,260 --> 01:00:09,260
That's more than what's quadruple what they were saying is.

797
01:00:09,260 --> 01:00:10,260
Right.

798
01:00:10,260 --> 01:00:11,260
What they would feel comfortable.

799
01:00:11,260 --> 01:00:12,260
Oh, I know.

800
01:00:12,260 --> 01:00:13,260
It's the most funny.

801
01:00:13,260 --> 01:00:14,260
Yeah.

802
01:00:14,260 --> 01:00:16,260
It's like the Canada.

803
01:00:16,260 --> 01:00:18,260
That's all it would be.

804
01:00:18,260 --> 01:00:19,260
Yeah.

805
01:00:19,260 --> 01:00:20,260
Wow.

806
01:00:20,260 --> 01:00:21,260
Make it enough.

807
01:00:21,260 --> 01:00:23,260
It barely attached little scenes.

808
01:00:23,260 --> 01:00:24,260
Yeah.

809
01:00:24,260 --> 01:00:25,260
Right.

810
01:00:26,260 --> 01:00:30,260
It's like the lake we are in, it's not.

811
01:00:30,260 --> 01:00:33,260
Everything's 23 and 24 and 24.

812
01:00:33,260 --> 01:00:34,260
It's just fun.

813
01:00:34,260 --> 01:00:35,260
Fun catch.

814
01:00:35,260 --> 01:00:36,260
We are.

815
01:00:36,260 --> 01:00:42,260
But we are frustrated because we don't keep one over 20.

816
01:00:43,260 --> 01:00:44,260
Yeah.

817
01:00:44,260 --> 01:00:45,260
Yeah.

818
01:00:45,260 --> 01:00:46,260
Yeah.

819
01:00:46,260 --> 01:00:47,260
Yeah.

820
01:00:47,260 --> 01:00:48,260
Yeah.

821
01:00:48,260 --> 01:00:49,260
Yeah.

822
01:00:49,260 --> 01:00:50,260
Yeah.

823
01:00:50,260 --> 01:00:51,260
Yeah.

824
01:00:51,260 --> 01:00:52,260
Yeah.

825
01:00:52,260 --> 01:00:53,260
Yeah.

826
01:00:53,260 --> 01:00:54,260
Yeah.

827
01:00:54,260 --> 01:00:55,260
Yeah.

828
01:00:55,260 --> 01:00:56,260
Yeah.

829
01:00:56,260 --> 01:00:57,260
Yeah.

830
01:00:58,260 --> 01:00:59,260
Yeah.

831
01:00:59,260 --> 01:01:06,260
Yeah.

832
01:01:06,260 --> 01:01:14,260
Yeah.

833
01:01:14,260 --> 01:01:15,260
Yeah.

834
01:01:15,260 --> 01:01:16,260
You've been there twice.

835
01:01:16,260 --> 01:01:17,260
It's never happened before.

836
01:01:17,260 --> 01:01:23,260
It said it was at like 35% which is a good amount of time.

837
01:01:23,260 --> 01:01:24,260
And then it just cuts a glass.

838
01:01:24,260 --> 01:01:30,100
The reason I think it does that, maybe the numbers will miss confusing is because this

839
01:01:30,100 --> 01:01:31,100
is powering everything.

840
01:01:31,100 --> 01:01:36,500
It's powering this, firing the camera, so maybe it sucks more energy up.

841
01:01:36,500 --> 01:01:39,660
Apparently that's the nice feature about this one.