WEBVTT Kind: captions Language: en 00:00:08.559 --> 00:00:12.469 Barbara Mahler:  The USGS, we're the sole earth science agency for the US Department 00:00:12.469 --> 00:00:14.020 of the Interior. 00:00:14.020 --> 00:00:21.550 The USGS is tasked with providing impartial information on the health of our ecosystems 00:00:21.550 --> 00:00:24.160 and our environment, among other things. 00:00:24.160 --> 00:00:30.820 One of our many goals is to communicate that information to other federal and state agencies. 00:00:30.820 --> 00:00:32.540 We're not a regulatory agency. 00:00:32.540 --> 00:00:36.940 I'm not advocating for any particular public policy. 00:00:36.940 --> 00:00:43.159 My goal today is to share with you what we've learning in our about 10 years of research 00:00:43.159 --> 00:00:45.080 on this subject. 00:00:45.080 --> 00:00:49.640 How did the USCS get involved in PAH and pavement sealants? 00:00:49.640 --> 00:00:54.870 It might seem like a bit of a stretch, but, it was a very natural outgrowth of the work 00:00:54.870 --> 00:01:01.460 that we've been doing with the National Water Quality Assessment program evaluating contaminant 00:01:01.460 --> 00:01:05.390 trends in time using lake sediment cores. 00:01:05.390 --> 00:01:13.729 So, using lake sediment cores to go back in time to look contaminant histories in watersheds. 00:01:13.729 --> 00:01:19.399 One of our principle goals is to identify trends, and then explain why those trends 00:01:19.399 --> 00:01:22.070 are occurring. 00:01:22.070 --> 00:01:27.650 Some of the trends that we've identify are things like downward trends, across the United 00:01:27.650 --> 00:01:36.159 States, in lakes for contaminants like DDT and PCBs that were banned. 00:01:36.159 --> 00:01:39.860 We see a lot of...each one of these symbols is a lake that we've cored, and the downward 00:01:39.860 --> 00:01:44.350 arrows indicate a statistically significant downward trend. 00:01:44.350 --> 00:01:52.869 A surprise to us was the upward trends that we saw in PAHs, polycyclic aromatic hydrocarbons. 00:01:52.869 --> 00:01:58.479 These were primarily in urban lakes across the United States. 00:01:58.479 --> 00:02:11.039 We were very curious to find out why PAHs were increasing in concentration. 00:02:11.039 --> 00:02:17.470 Coincidentally and simultaneously with the research that we were doing on lake sediments 00:02:17.470 --> 00:02:23.670 and PAHs...I'm located at Texas Water Science Center here in Austin. 00:02:23.670 --> 00:02:32.040 The city of Austin was using a grant from EPA to collect and analyze sediments from 00:02:32.040 --> 00:02:35.459 small urban streams and drainages. 00:02:35.459 --> 00:02:39.599 These were not in heavy industrial or innercity areas. 00:02:39.599 --> 00:02:48.319 These were in areas of light commercial, multifamily, and singlefamily residential housing. 00:02:48.319 --> 00:02:54.739 They were analyzing a very suite of contaminants, and they saw something that was very surprising 00:02:54.739 --> 00:02:56.130 when it came to PAHs. 00:02:56.130 --> 00:03:02.549 They were measuring concentrations in the thousands of PPM in some of these areas. 00:03:02.549 --> 00:03:08.769 This was a real eyeopener, because these concentrations are on par with what are typically measured 00:03:08.769 --> 00:03:11.040 in soils at Superfund sites. 00:03:11.040 --> 00:03:16.930 They're not at all what we would expect to be seeing in residential areas. 00:03:16.930 --> 00:03:22.890 To put these into context, the probable expect concentration, in other words the concentration 00:03:22.890 --> 00:03:29.900 at which we would expect to see adverse effects on lentic biota is only 23 parts per million. 00:03:29.900 --> 00:03:34.540 So these were extremely elevated concentrations. 00:03:34.540 --> 00:03:38.870 They shared this data with us because we have a number of collaborate, cooperative programs 00:03:38.870 --> 00:03:40.959 with the city. 00:03:40.959 --> 00:03:46.099 It was a real eyeopener for us, at first we thought that the laboratory had put a decimal 00:03:46.099 --> 00:03:48.260 point in the wrong place. 00:03:48.260 --> 00:03:51.000 It turned out that they weren't. 00:03:51.000 --> 00:03:55.879 A very astute staff member with the City of Austin was walking watersheds and he walked 00:03:55.879 --> 00:04:03.939 upstream and he noticed that the most contaminated sediments were just below parking lot drainages. 00:04:03.939 --> 00:04:11.299 The parking lots were coated with a black substance, and that substance is coaltarbased 00:04:11.299 --> 00:04:12.890 sealcoat. 00:04:12.890 --> 00:04:23.280 Sealcoat is a consumer product that is marketed as enhancing the appearance of asphalt pavement, 00:04:23.280 --> 00:04:29.650 and preserving or extended the longevity of the underlying asphalt. 00:04:29.650 --> 00:04:36.240 There are two brands, excuse me, two formulations of pavement sealer. 00:04:36.240 --> 00:04:42.370 There is one with an asphalt base which is used primarily west of the continental divide, 00:04:42.370 --> 00:04:46.830 and there's one with a coaltar base which is used primarily east of the continental 00:04:46.830 --> 00:04:48.470 divide. 00:04:48.470 --> 00:04:50.680 These products are sprayed or painted on. 00:04:50.680 --> 00:04:56.150 They can be applied by homeowners or property owners, or you can hire someone to do it. 00:04:56.150 --> 00:04:59.280 It is not an intrinsic part of the pavement process. 00:04:59.280 --> 00:05:05.720 It is an optional product that can be used after paving. 00:05:05.720 --> 00:05:11.650 It's not used on roads, it's primarily used on parking lots, on driveways, and even on 00:05:11.650 --> 00:05:15.580 some playgrounds and sidewalks. 00:05:15.580 --> 00:05:24.009 This turns out to be a concern because the coaltarbased pavement sealants contain anywhere 00:05:24.009 --> 00:05:32.479 from 15 to 35 percent coal tar pitch, crude coal tar, one or the other, either coal tar 00:05:32.479 --> 00:05:35.390 pitch or now some of them are starting to use crude coal tar. 00:05:35.390 --> 00:05:40.350 Both crude coal tar and coal tar pitch are known human carcinogens. 00:05:40.350 --> 00:05:49.750 These have the potential to be very potent sources of PAHs to the urban and residential 00:05:49.750 --> 00:05:53.760 environments. 00:05:53.760 --> 00:05:59.930 Coal tar and coal tar pitch are a concern because among other compounds they contain 00:05:59.930 --> 00:06:05.819 very high concentrations of polycyclic aromatic hydrocarbons, or PAHs. 00:06:05.819 --> 00:06:12.150 PAHs are compounds that have the benzene ring as a building block, and as we combine different 00:06:12.150 --> 00:06:19.319 numbers of benzene rings in different geometric configurations each one of this is a PAH. 00:06:19.319 --> 00:06:25.570 These can be modified by adding additional constituents like nitrogen or sulfur to one 00:06:25.570 --> 00:06:31.580 of the carbons and create heterocyclic compounds that also have important environmental and 00:06:31.580 --> 00:06:34.440 health considerations. 00:06:34.440 --> 00:06:44.009 Seven of the PAHs are probable human carcinogens, and that number is growing as the EPA is modifying 00:06:44.009 --> 00:06:49.259 what they have probable cause to believe are human carcinogens. 00:06:49.259 --> 00:06:55.759 There are a very large number of sources of PAHs in the urban environment. 00:06:55.759 --> 00:07:01.259 PAHs are formed whenever we burn or combust organic matter. 00:07:01.259 --> 00:07:08.440 When we burn a cigarette, or we char meat, or we heat up motor oil in our cars, we're 00:07:08.440 --> 00:07:10.250 creating PAHs. 00:07:10.250 --> 00:07:19.300 Similarly, products that involve organic matter combustion like tires also contain PAHs. 00:07:19.300 --> 00:07:24.400 We're going to add to this list of urban PAH sources then, the coaltarbased pavement sealants. 00:07:24.400 --> 00:07:33.979 The fact that there are so many urban sources has been one of the reasons that for a long 00:07:33.979 --> 00:07:39.879 time it's been very difficult to determine which of these sources are the most important 00:07:39.879 --> 00:07:42.199 in the environment. 00:07:42.199 --> 00:07:47.520 One thing that's very helpful is to put the concentrations of PAHs in these sources into 00:07:47.520 --> 00:07:48.740 some context. 00:07:48.740 --> 00:07:54.190 Here we're looking at concentrations of PAHs in urban sources. 00:07:54.190 --> 00:08:01.110 You can see that while asphalt does contain PAHs it has relatively low concentrations. 00:08:01.110 --> 00:08:07.199 That's why when the City of Austin was looking around to determine where these PAH concentrations 00:08:07.199 --> 00:08:13.759 were coming from, we were discarding the possibility that they were coming from either fresh or 00:08:13.759 --> 00:08:20.259 weathered asphalt surfaces because these concentrations are far lower than the 1,500 milligrams per 00:08:20.259 --> 00:08:23.740 kilogram which were measured in the sediment. 00:08:23.740 --> 00:08:31.330 In fact, even used motor oil which is one of the major sources of PAHs in urban environments, 00:08:31.330 --> 00:08:35.430 if you mix used motor oil with some of the sediments in Austin, you'd be cleaning it 00:08:35.430 --> 00:08:37.729 up. 00:08:37.729 --> 00:08:43.430 If we take a look at the two different formulations of sealcoat products, the asphaltbased product, 00:08:43.430 --> 00:08:50.310 like asphalt itself, has relatively low concentrations, but the coaltarbased product has very high 00:08:50.310 --> 00:08:51.380 concentrations. 00:08:51.380 --> 00:08:56.250 These can range anywhere from 50,000 parts per million all the way up into the hundreds 00:08:56.250 --> 00:09:02.490 of parts per million, depending on the manufacturer and the particular brand of sealcoat that's 00:09:02.490 --> 00:09:04.860 in question. 00:09:04.860 --> 00:09:13.560 To put this into context, a bucket of coal tar sealcoat off the shelf contains about 00:09:13.560 --> 00:09:23.990 100 times more PAHs than a similar volume of used motor oil. 00:09:23.990 --> 00:09:30.140 These products are used extensively in primarily in the Eastern United States, I mentioned 00:09:30.140 --> 00:09:33.579 east of the continental divide, so that's the Great Lakes region, the North East, the 00:09:33.579 --> 00:09:37.350 South East, the Mid West, and here in Texas. 00:09:37.350 --> 00:09:42.040 That rule is not hard and fast, there is some use of the coaltarbased products in the West, 00:09:42.040 --> 00:09:47.760 and there is some use of the asphaltbased products in the East. 00:09:47.760 --> 00:09:55.060 We first heard about this geographic difference as anecdotal information from applicators 00:09:55.060 --> 00:10:02.589 and our investigation since then, that information has held up. 00:10:02.589 --> 00:10:08.050 About 85 million gallons of coaltarbased sealcoat are used every year in the United States. 00:10:08.050 --> 00:10:13.340 Enough to cover about 170 square miles. 00:10:13.340 --> 00:10:18.600 Many applicators recommend that sealcoat be reapplied everywhere from two to every five 00:10:18.600 --> 00:10:24.890 years, and many home owners prefer to reapply to their driveways on a yearly basis. 00:10:24.890 --> 00:10:33.480 If you live anywhere in the United States and you look around at parking lots and driveways, 00:10:33.480 --> 00:10:35.570 you will see sealcoat. 00:10:35.570 --> 00:10:41.030 It's used on commercial properties, it's used as schools, it's used at churches, it's used 00:10:41.030 --> 00:10:50.550 in shopping centers, universities, it's a very commonly used product in the United States. 00:10:50.550 --> 00:10:57.839 The issue is that the PAHs and the sealcoats themselves don't stay where they're put. 00:10:57.839 --> 00:11:02.610 After sealcoat is applied it makes a black shiny surface, and it makes the pavement look 00:11:02.610 --> 00:11:05.470 like new. 00:11:05.470 --> 00:11:12.570 After a few months to years of abrasive action from car tires, and in many parts of the country 00:11:12.570 --> 00:11:18.589 snow plows, it doesn't take long to start seeing some of the underlying asphalt showing 00:11:18.589 --> 00:11:22.980 through as the product abrades and is removed. 00:11:22.980 --> 00:11:28.430 Ultimately after a few years, an asphalt parking lot or a private drive will start to look 00:11:28.430 --> 00:11:29.820 something like this. 00:11:29.820 --> 00:11:36.510 If we go out and we sweep up some of the dust that's on these sealed surfaces, you'll see 00:11:36.510 --> 00:11:38.209 all these little black bits. 00:11:38.209 --> 00:11:41.520 These are little bits of sealcoat. 00:11:41.520 --> 00:11:47.529 They are loose, they are mobile, they can be blown by wind and inhaled, they can be 00:11:47.529 --> 00:11:52.519 washed off by storm water runoff, they can stick to our skin, they can stick to our shoes 00:11:52.519 --> 00:11:54.079 and be tracked to other locations. 00:11:54.079 --> 00:11:57.210 There's lots of places that these little particles can go. 00:11:57.210 --> 00:12:04.209 Part of our research has focused on identifying the effects of coal tar sealcoat on all of 00:12:04.209 --> 00:12:10.370 these different environmental compartments to which these particles can be transported. 00:12:10.370 --> 00:12:16.120 Some PAHs also are volatile, meaning they can evaporate into air. 00:12:16.120 --> 00:12:22.459 Some of our work also has focused determining how important coal tar sealcoats is as a contributor 00:12:22.459 --> 00:12:24.079 to PAHs to air. 00:12:24.079 --> 00:12:27.870 We're going to walk through some of these compartments. 00:12:27.870 --> 00:12:31.070 We're going to start with the dust itself. 00:12:31.070 --> 00:12:37.550 As part of our work for the National Water Quality Assessment Program we go around to 00:12:37.550 --> 00:12:41.199 lakes across the United States and we collect sediment cores. 00:12:41.199 --> 00:12:45.540 In the course of that work we also swept parking lots. 00:12:45.540 --> 00:12:52.839 I love my job, we get to get out and sweep up parking lots all over the United States. 00:12:52.839 --> 00:12:57.790 We measured the concentrations of PAHs in that parking lot dust. 00:12:57.790 --> 00:13:04.100 What you're seeing here confirms what we had heard from the industry about the use of the 00:13:04.100 --> 00:13:09.209 low PAH asphalt products used in the West, and the use of the high PAH coal tar products 00:13:09.209 --> 00:13:11.329 used in the East. 00:13:11.329 --> 00:13:16.010 These concentrations are very consistent with what was measured in some of those stream 00:13:16.010 --> 00:13:20.860 beds in Austin, Texas, suggesting that some of those very small stream beds are getting 00:13:20.860 --> 00:13:24.510 almost completely undiluted runoff from some of these parking lots. 00:13:24.510 --> 00:13:27.210 They are similar to what we see at Superfund sites. 00:13:27.210 --> 00:13:32.420 We also swept up dust from unsealed parking lots, and we saw a very different story. 00:13:32.420 --> 00:13:38.230 We saw much lower concentrations in PAHs, even in the East. 00:13:38.230 --> 00:13:45.600 These parking lots that we swept are all in the same watersheds, they're in the same airsheds, 00:13:45.600 --> 00:13:51.139 and so the difference between these numbers are pointing out that these high concentrations 00:13:51.139 --> 00:13:56.800 really are the result of the sealcoat, because these unsealed parking lots are getting all 00:13:56.800 --> 00:14:06.779 the same other urban PAH sources like car tire fragments, and dripping motor oil, and 00:14:06.779 --> 00:14:12.279 even atmospheric emission. 00:14:12.279 --> 00:14:18.839 The mobile particle then can get washed down storm drains and storm drains end up in streams 00:14:18.839 --> 00:14:21.959 which ultimately flow to lakes. 00:14:21.959 --> 00:14:28.519 One of the big questions that we were interested in as part of the NWQA program, is are these 00:14:28.519 --> 00:14:35.610 products contributing to the upward trends that we're seeing in PAHs in urban lakes. 00:14:35.610 --> 00:14:39.860 The approach that we used is called an environment forensic approach. 00:14:39.860 --> 00:14:47.089 In other words, we used the profiles, the PAH profiles or fingerprints, of different 00:14:47.089 --> 00:14:53.380 PAH urban sources and we compared those to the PAH fingerprint in the sediment samples 00:14:53.380 --> 00:14:56.050 that we were collecting. 00:14:56.050 --> 00:14:58.600 What do I mean by PAH fingerprint? 00:14:58.600 --> 00:15:04.810 There's a whole range of different sizes and shapes of PAHs, and different sources contain 00:15:04.810 --> 00:15:08.550 different proportions of those PAHs. 00:15:08.550 --> 00:15:16.410 We used a statistical model that was developed by USEPA that says, "What is the optimal way 00:15:16.410 --> 00:15:23.820 that I can combine different PAH sources and best replicate the PAH profile or the PAH 00:15:23.820 --> 00:15:27.610 fingerprint that we see in the sediments themselves?" 00:15:27.610 --> 00:15:33.600 When we do that, we tested 22 different urban PAH sources and we divided those into five 00:15:33.600 --> 00:15:36.150 large categories. 00:15:36.150 --> 00:15:43.009 Sealcoat products, vehiclerelated PAH sources, coal burning, oil burning, and wood burning. 00:15:43.009 --> 00:15:47.910 What we're looking at here is urban lakes that we sampled across the United States, 00:15:47.910 --> 00:15:54.610 this is the PAH concentration on the Yaxis, the total PAH concentration, and the different 00:15:54.610 --> 00:16:05.200 colors of the bars are telling us a portioning the PAHs to one of these different five PAH 00:16:05.200 --> 00:16:06.200 source groups. 00:16:06.200 --> 00:16:11.820 What it's showing us is that on the basis of the PAH fingerprints, we're estimating 00:16:11.820 --> 00:16:18.040 that overall about 50 percent of the PAHs in the urban lakes that we've sampled are 00:16:18.040 --> 00:16:20.089 coming from coaltarbased sealcoat. 00:16:20.089 --> 00:16:26.509 Furthermore, if we look at the new urban lakes where we see the most pronounced upward trends 00:16:26.509 --> 00:16:33.120 in PAHs, overwhelmingly those PAHs are coming from coaltarbased sealcoats. 00:16:33.120 --> 00:16:38.089 I want to draw your attention here to the probable effect concentration. 00:16:38.089 --> 00:16:43.670 We saw this a little earlier, 23 milligrams per kilogram, this is the concentration at 00:16:43.670 --> 00:16:50.829 which we would expect to see adverse effects on biota, and many of these lakes have concentrations 00:16:50.829 --> 00:16:55.070 of PAHs that exceed that PEC. 00:16:55.070 --> 00:17:00.019 There has been some work since we've first identified this as a source, there has been 00:17:00.019 --> 00:17:07.110 some research looking specifically at effects of PAHs associated with coaltarbased sealcoat 00:17:07.110 --> 00:17:11.470 on different organisms and on ecological communities. 00:17:11.470 --> 00:17:18.750 I'm sure you're aware that there's a vast amount of research out there on PAHs in general, 00:17:18.750 --> 00:17:23.740 or individual PAHs on a wide variety of test organisms. 00:17:23.740 --> 00:17:29.200 These research projects looked specifically at PAHs from coaltarbased sealcoat. 00:17:29.200 --> 00:17:37.520 They saw chronic and sublethal effects on a couple of different amphibians that were 00:17:37.520 --> 00:17:43.160 tested, they also saw measurable effects on ecological communities changing the number 00:17:43.160 --> 00:17:46.460 and variety of species that were present. 00:17:46.460 --> 00:17:51.590 Very recently, a paper has come out looking at DNA damage on Japanese Medaka associated 00:17:51.590 --> 00:17:56.900 with runoff from coal tar sealed parking lots. 00:17:56.900 --> 00:18:01.570 The next question then is, "Well, what about human health exposure"? 00:18:01.570 --> 00:18:07.690 Because there clearly are a lot of ways that humans can come into contact with the dust 00:18:07.690 --> 00:18:14.860 on these surfaces whether they are coming into contact during play activity, or whether 00:18:14.860 --> 00:18:20.720 they're breathing the fumes that are being volatilized from the surfaces, or whether 00:18:20.720 --> 00:18:26.790 they are coming into contact with the PAHs where it contaminates soil or house dust. 00:18:26.790 --> 00:18:33.770 In fact, one of the interests that we had in determining are PAHs from parking lots 00:18:33.770 --> 00:18:40.660 and driveways as they abrade and adhere to the bottoms of our shoes, are they being tracked 00:18:40.660 --> 00:18:46.210 into homes in the same way that the other contaminants are. 00:18:46.210 --> 00:18:52.990 We did a study in 2010, we looked at 23 apartments in Austin, Texas. 00:18:52.990 --> 00:18:59.070 11 of those had coaltarbased sealcoat on the adjacent parking lot, these were all ground 00:18:59.070 --> 00:19:08.500 floor apartments, and 12 of these either had asphaltbased sealcoats or unsealed asphalt. 00:19:08.500 --> 00:19:13.690 We measured the PAHs concentrations both in the dust on the parking lot and in the apartments 00:19:13.690 --> 00:19:15.330 themselves. 00:19:15.330 --> 00:19:20.260 For the parking lots we saw very similar concentrations to what we'd measured previously in other 00:19:20.260 --> 00:19:21.510 parts of the country. 00:19:21.510 --> 00:19:27.580 Concentrations, median concentrations, were in the thousands on the parking lot. 00:19:27.580 --> 00:19:32.250 We also saw higher concentrations in the house dust. 00:19:32.250 --> 00:19:37.380 The concentration of PAHs in this were about 25 times higher. 00:19:37.380 --> 00:19:45.380 This is the sum of the carcinogenic, the B2PAHs, and the sum was about 25 times higher in those 00:19:45.380 --> 00:19:48.280 apartments that had coaltarbased sealcoat. 00:19:48.280 --> 00:19:56.160 Dr. Williams has looked at a couple of studies using this data along with data for PAHs in 00:19:56.160 --> 00:20:00.820 affected soils, and looked at some implications for human health and that's what he'll be 00:20:00.820 --> 00:20:04.820 talking about in just a few minutes. 00:20:04.820 --> 00:20:11.330 Another pathway for human exposure of course is air, it's inhalation. 00:20:11.330 --> 00:20:19.350 We have been investigating also volatilization of PAHs from coal tar sealed parking lots. 00:20:19.350 --> 00:20:25.410 The way that we've done this, we've used an approach that was developed by Environment 00:20:25.410 --> 00:20:31.190 Canada, using something called a "hat sampler," apparently people in Canada think this is 00:20:31.190 --> 00:20:34.960 what a sombrero looks like, so they call this a hat sampler. 00:20:34.960 --> 00:20:42.030 Essentially the approach is to use a puff up here at about 1.25 meters above the surface, 00:20:42.030 --> 00:20:47.400 and compare concentrations between what's in the puff and what is collected in a puff 00:20:47.400 --> 00:20:50.260 that is underneath the hat sampler. 00:20:50.260 --> 00:20:56.840 We use the gradient in concentrations and other environmental factors to estimate a 00:20:56.840 --> 00:20:57.840 flux. 00:20:57.840 --> 00:21:07.510 In other words, a mass of PAHs leaving a given surface area per unit time. 00:21:07.510 --> 00:21:12.330 The first work that we did was looking at parking lots that had been sealed anywhere 00:21:12.330 --> 00:21:14.900 from months to years earlier. 00:21:14.900 --> 00:21:20.810 These are parking lots that have been in use, have been sealed for quite a while, have been 00:21:20.810 --> 00:21:25.640 exposed to sun, and wind, and rain, and all those environmental factors. 00:21:25.640 --> 00:21:30.690 We compared unsealed asphalt to coal tar sealed lots. 00:21:30.690 --> 00:21:37.940 When we compare the flux between the air over the unsealed parking lot and the flux coming 00:21:37.940 --> 00:21:43.940 off the coal tar sealed parking lot, there's about a factor of 60 difference, even years 00:21:43.940 --> 00:21:45.400 after application. 00:21:45.400 --> 00:21:53.790 It appears that coal tar sealed pavement continues to be a source of PAH to the atmosphere years 00:21:53.790 --> 00:21:55.110 after application. 00:21:55.110 --> 00:22:04.920 Once you remember this number, because the next study that we did investigated PAH fluxes 00:22:04.920 --> 00:22:13.030 from sealcoat directly after application and how those fluxes change over time following 00:22:13.030 --> 00:22:14.520 application. 00:22:14.520 --> 00:22:19.810 We had two test plots sealed in Austin, Texas. 00:22:19.810 --> 00:22:29.140 We compared the concentrations of PAHs volatilizing off a coal tar sealed lot, and compared that 00:22:29.140 --> 00:22:32.540 to what was volatilizing off an asphalt sealed lot. 00:22:32.540 --> 00:22:37.980 We measured the concentration starting pretty much as soon as we could get out on the pavement, 00:22:37.980 --> 00:22:39.910 within hours of application. 00:22:39.910 --> 00:22:42.980 The applicator went nuts, we weren't supposed to walk on their nice wet sealcoat. 00:22:42.980 --> 00:22:49.400 We went out there anyway, and we continued to measure for first starting with hours, 00:22:49.400 --> 00:22:53.220 and then days, and weeks following application. 00:22:53.220 --> 00:22:58.850 Remember this 88 number from the coal tar seal coated parking lots that were sealed 00:22:58.850 --> 00:23:03.970 a few years earlier, that concentration is way out here. 00:23:03.970 --> 00:23:09.840 If we take a look at the flux from seal coated parking lots during about the first two weeks 00:23:09.840 --> 00:23:16.150 after application, we have concentrations that are in the tens of thousands of micrograms 00:23:16.150 --> 00:23:20.800 per square meter every hour. 00:23:20.800 --> 00:23:26.700 Looking at that more closely, so here's the first two weeks following application, and 00:23:26.700 --> 00:23:30.820 we have a diurnal cycle it's hotter during the day so we have more volatilization and 00:23:30.820 --> 00:23:32.170 it's a little less hot at night. 00:23:32.170 --> 00:23:38.140 Remember this is Texas in the summer, so it's pretty hot out there. 00:23:38.140 --> 00:23:45.870 We compute the area under the curve and we come up with a total PAH loss over the two 00:23:45.870 --> 00:23:53.980 weeks after application of about 2.5 grams per square meter of sealed lot. 00:23:53.980 --> 00:24:00.250 If we put that into context, we're going to do a little calculation here for national 00:24:00.250 --> 00:24:01.850 PAH emissions. 00:24:01.850 --> 00:24:04.980 Just during the first two weeks after application. 00:24:04.980 --> 00:24:10.610 We have our numbers for annual sealcoat use and area covered, and our emission rates that 00:24:10.610 --> 00:24:17.430 we've measured of 2.5 grams per square meter, and if we multiply that through, we find that 00:24:17.430 --> 00:24:23.580 PAH emissions on an annual basis are about a thousand mega grams, or a thousand metric 00:24:23.580 --> 00:24:31.770 tons, which is on par or exceeding estimated vehicle emissions. 00:24:31.770 --> 00:24:41.060 It turns out that this is a potentially important source of PAHs to urban air. 00:24:41.060 --> 00:24:49.540 I'm going to circle back now before I pass the microphone over to Spencer, and go back 00:24:49.540 --> 00:24:53.300 to our original question, because we've just had some research published this week that 00:24:53.300 --> 00:24:54.880 I want to share with you. 00:24:54.880 --> 00:25:01.560 The question is, "Are the PAHs that are ending up in those storm drains, are they really 00:25:01.560 --> 00:25:07.440 like our models and our forensic evidence says, an important source of PAHs to lake 00:25:07.440 --> 00:25:08.440 sediments?" 00:25:08.440 --> 00:25:13.610 To investigate this, we had the opportunity to do a study in Austin, Texas, which was 00:25:13.610 --> 00:25:16.820 the first jurisdiction to ban use of coaltarbased sealants. 00:25:16.820 --> 00:25:20.590 They banned them back in 2006. 00:25:20.590 --> 00:25:26.580 Prior to the ban, back in 1998, we had collected a sediment core from Town Lake. 00:25:26.580 --> 00:25:31.340 It was one of those urban lakes where we saw upward trends in PAHs. 00:25:31.340 --> 00:25:37.740 We went back to Town Lake which has been changed to be called Lady Bird Lake now, we went back 00:25:37.740 --> 00:25:44.590 to Lady Bird Lake in 2012 and 2014, and we collected more sediment cores from the downstream 00:25:44.590 --> 00:25:47.090 end of the reservoir here. 00:25:47.090 --> 00:25:51.400 We also collected some bed sediment samples which we could compare to bed sediment samples 00:25:51.400 --> 00:25:56.280 that had been collected back in 2000 before the ban. 00:25:56.280 --> 00:26:01.730 Here are the trends from the sediment core we collected in 1988. 00:26:01.730 --> 00:26:07.640 I apologize, this graph is from a publication and it's showing micrograms per kilogram, 00:26:07.640 --> 00:26:10.800 so actually parts per trillion not parts per million. 00:26:10.800 --> 00:26:15.250 Divide by a thousand to get backs to parts per million like we've been talking about. 00:26:15.250 --> 00:26:19.100 They range from two up to about ten ppm. 00:26:19.100 --> 00:26:23.230 Here's the trend in the lake core that we collected in 98. 00:26:23.230 --> 00:26:31.430 We have a very statistically significant upward trend, an increase of about 20 times in the 00:26:31.430 --> 00:26:35.260 40 years of deposition. 00:26:35.260 --> 00:26:40.720 Here are the results from the lake sediment cores that we collected in 2010, excuse me, 00:26:40.720 --> 00:26:49.840 2012 and 2014, following the 2006 ban on coaltarbased sealcoats. 00:26:49.840 --> 00:26:54.170 Here's our bed sediment before and after the ban. 00:26:54.170 --> 00:26:59.490 If we compare the average concentration in the years directly preceding the ban with 00:26:59.490 --> 00:27:09.900 those from 2012 and 2014, we're seeing almost a 60 percent decrease in PAH concentrations 00:27:09.900 --> 00:27:12.710 following the ban. 00:27:12.710 --> 00:27:19.090 That was published this week in ES&T, that's something I wanted to share with you. 00:27:19.090 --> 00:27:24.790 If we use our source apportionment model on those sediments collected just before the 00:27:24.790 --> 00:27:30.230 ban, it was telling us that most of the PAHs were coming from the coaltarbased sealcoat 00:27:30.230 --> 00:27:31.230 dust. 00:27:31.230 --> 00:27:36.040 We did the same thing for the sediments collected recently. 00:27:36.040 --> 00:27:40.970 We see a decrease in concentration but we still see that most of the PAHs are coming 00:27:40.970 --> 00:27:48.040 from sealcoat as those existing stocks on parking lots and in stream bed sediments continue 00:27:48.040 --> 00:27:54.470 to be depleted, we expect to see that PAH concentration in Lady Bird Lake should continue 00:27:54.470 --> 00:27:57.860 to decrease. 00:27:57.860 --> 00:28:02.830 If you'd like more information about the USGS research, you can find it on this Web page 00:28:02.830 --> 00:28:10.050 here, or you are welcome to contact either me or Dr. Van Meter, we've coauthored a lot 00:28:10.050 --> 00:28:11.380 of papers. 00:28:11.380 --> 00:28:19.160 There have been quite a few publications now by researchers with other government agencies, 00:28:19.160 --> 00:28:22.530 and also researchers with academia. 00:28:22.530 --> 00:28:29.710 All of this independent research has come to similar and consistent conclusions about 00:28:29.710 --> 00:28:35.220 the importance of coaltarbased sealcoat as a PAH source to the urban environment. 00:28:35.220 --> 00:28:40.490 There are some publications that have come out recently that are by consultants funded 00:28:40.490 --> 00:28:45.920 by the PCTC which is the lobby group, which lobbies for the coal tar sealcoat industry, 00:28:45.920 --> 00:28:49.140 and they are disagreeing with our results. 00:28:49.140 --> 00:28:53.790 If anyone would like access to any of these documents, please let me know and I would 00:28:53.790 --> 00:28:56.300 be happy to share them with you. 00:28:56.300 --> 00:29:02.870 Spencer Williams:  My name is Spencer Williams, I'm at Baylor University. 00:29:02.870 --> 00:29:08.470 Prior to being at Baylor University I was a consultant, I worked for a small firm called 00:29:08.470 --> 00:29:11.400 ChemRisk, I was located in Houston. 00:29:11.400 --> 00:29:17.060 In the course of my work there I've worked for a long time with PAHs, and dioxins, and 00:29:17.060 --> 00:29:19.170 a number of organic pollutants. 00:29:19.170 --> 00:29:24.510 I happened to come across a publication from Barbara and Peter on sealcoat, 00:29:24.510 --> 00:29:28.730 I thought it was very interesting, and I continued to follow their work. 00:29:28.730 --> 00:29:32.890 Then a few years later I had an opportunity to come here at Baylor and do some scientific 00:29:32.890 --> 00:29:39.380 research, teaching students, and that very fall I just happened to go into a room at 00:29:39.380 --> 00:29:44.160 the Society for Environmental Toxicology and Chemistry annual conference, and who was standing 00:29:44.160 --> 00:29:47.780 up there giving a talk but Barbara. 00:29:47.780 --> 00:29:50.890 After the meeting, I walked right up to her and I said, "I've been following your work, 00:29:50.890 --> 00:29:53.590 I'm very interested, do you guys have time to chat?" 00:29:53.590 --> 00:29:58.050 We started chatting about it, I told them I was a human health risk assessor. 00:29:58.050 --> 00:30:02.150 They said, "How coincidental, we've been looking for someone just like you." 00:30:02.150 --> 00:30:08.310 Since then we've been having what I think is a really interesting and productive conversation, 00:30:08.310 --> 00:30:11.980 and one that I hope is going to carry us further forward. 00:30:11.980 --> 00:30:16.120 In my previous life as a consultant, I became interested in contaminants in house dust, 00:30:16.120 --> 00:30:19.390 I think that's first how I came across the work. 00:30:19.390 --> 00:30:23.290 For those of you that don't know, house dust is a very important medium for environmental 00:30:23.290 --> 00:30:25.210 contact. 00:30:25.210 --> 00:30:29.530 It's approximated that most people in the United States spend about 90 percent of their 00:30:29.530 --> 00:30:30.660 time indoors. 00:30:30.660 --> 00:30:36.000 Anybody who's worked on environmental lead, one of the great success stories for public 00:30:36.000 --> 00:30:44.220 health over the last 40 years is aware that dust is probably the most important way in 00:30:44.220 --> 00:30:46.590 which children come into contact with lead. 00:30:46.590 --> 00:30:48.360 Probably the most, soil is a close second. 00:30:48.360 --> 00:30:54.520 The relationship between these two media is very complicated. 00:30:54.520 --> 00:31:00.530 Barbara and Peter and I started talking about this, and we started talking about it as, 00:31:00.530 --> 00:31:04.110 their interest was primarily environmental chemistry and environmental forensics, mine 00:31:04.110 --> 00:31:07.650 being human health and also ecological health. 00:31:07.650 --> 00:31:14.260 I was very curious, starting off with, what these might look like in terms of how we know 00:31:14.260 --> 00:31:15.840 people are exposed to PAHs. 00:31:15.840 --> 00:31:19.380 Real quick, I'll give a quick primer on that. 00:31:19.380 --> 00:31:21.340 Barbara told you quite a bit about PAHs. 00:31:21.340 --> 00:31:25.760 They are ubiquitous; you guys all had them for breakfast this morning if you had just 00:31:25.760 --> 00:31:27.990 about any version of foodstuff that you can get. 00:31:27.990 --> 00:31:32.480 They would be in your coffee, they would be in about everything you eat. 00:31:32.480 --> 00:31:38.160 If you go and have a hamburger, if you go and have barbecue, you get a dose of PAHs, 00:31:38.160 --> 00:31:40.180 for certain. 00:31:40.180 --> 00:31:44.440 One of the things that we have been studying over a long period of time is how people come 00:31:44.440 --> 00:31:47.131 into contact with these, by and large. 00:31:47.131 --> 00:31:52.950 Most studies have demonstrated over time, it appears that our primary route of exposure 00:31:52.950 --> 00:31:58.100 for the general public to PAHs is through their diet, as I said. 00:31:58.100 --> 00:32:04.740 This has been pretty well characterized through a number of authors; Charlie Menzie, the incoming 00:32:04.740 --> 00:32:07.240 President of SETAC has done some work on this. 00:32:07.240 --> 00:32:12.170 In particular, we became very interested in a couple of very robust studies that were 00:32:12.170 --> 00:32:17.910 done in North Carolina on children. 00:32:17.910 --> 00:32:22.420 How they did the study was, they had the parents prepare duplicate meals. 00:32:22.420 --> 00:32:25.001 The children would eat one meal, and then the other meal would be taken back to the 00:32:25.001 --> 00:32:33.560 lab for analysis, so they were able to approximate a pretty good approximation has to be the 00:32:33.560 --> 00:32:37.890 PAH content of these children's diet. 00:32:37.890 --> 00:32:41.770 We wanted to look at that as a point of comparison. 00:32:41.770 --> 00:32:46.420 We also have some pretty good ideas about how much dust children tend to ingest on a 00:32:46.420 --> 00:32:47.420 daily basis. 00:32:47.420 --> 00:32:53.250 For those of you who have kids, you know that this is how children are learning about their 00:32:53.250 --> 00:32:54.250 environment. 00:32:54.250 --> 00:32:57.360 They move around and they stick their hands on everything, and then they stick their hands 00:32:57.360 --> 00:33:01.240 in their mouth, and they stick their mouth on window sills and everything, trying to 00:33:01.240 --> 00:33:02.310 come to grips with their environment. 00:33:02.310 --> 00:33:04.050 That brings them into contact with dust. 00:33:04.050 --> 00:33:09.960 This is certainly the case for dust that's contaminated with leadbased paint, so that's 00:33:09.960 --> 00:33:11.240 an important one. 00:33:11.240 --> 00:33:18.020 The same sort of exposure would be expected for the dust that Peter and Barbara were seeing 00:33:18.020 --> 00:33:25.070 in people's homes, so we decided to start off with the simplest way of looking at how 00:33:25.070 --> 00:33:31.890 much dust we think children ingest, on average, and then how much the reasonable maximum might 00:33:31.890 --> 00:33:36.420 be the 95th percentile what do we think children are coming into contact with? 00:33:36.420 --> 00:33:39.150 There have been a number of studies done on this. 00:33:39.150 --> 00:33:44.950 It's a very complicated question to answer because if you're trying to divide soil and 00:33:44.950 --> 00:33:46.820 dust, there's a lot of similarity. 00:33:46.820 --> 00:33:51.530 In some settings, most of the dust will essentially be trackedin soil. 00:33:51.530 --> 00:33:55.230 In other settings, that's just not the case. 00:33:55.230 --> 00:34:02.240 Starting with what we knew...there was a recent study done by a group I was going to ask, 00:34:02.240 --> 00:34:07.390 you guys may know these authors using the Consolidated Human Activity Database to generate 00:34:07.390 --> 00:34:12.639 a couple of estimates of dust from handtomouth and objecttomouth behavior. 00:34:12.639 --> 00:34:13.679 Go on ahead, Barbara. 00:34:13.679 --> 00:34:25.750 You can see here, we started on the left by showing what your exposure to B2 PAHs, so 00:34:25.750 --> 00:34:31.610 these are the ones that are listed as B2, or "probable human carcinogens," and what 00:34:31.610 --> 00:34:33.800 that would look like for your dietary ingestion. 00:34:33.800 --> 00:34:35.950 Those come from the studies in North Carolina. 00:34:35.950 --> 00:34:41.600 Then we decided to compare it with what we knew about the concentrations of these chemicals 00:34:41.600 --> 00:34:46.761 in residences with coal tarsealed parking lots, and then asphalt parking lots that were 00:34:46.761 --> 00:34:49.649 not sealed with coal tar. 00:34:49.649 --> 00:34:51.450 We're looking at these two bars in the middle. 00:34:51.450 --> 00:34:56.889 On the left you can see that just having 27 milligrams of dust per day is going to give 00:34:56.889 --> 00:35:06.610 you an incidental ingestion exposure to PAHs that is significantly higher than typical 00:35:06.610 --> 00:35:09.900 dietary ingestion for children of the same age. 00:35:09.900 --> 00:35:11.600 We felt like that was pretty remarkable. 00:35:11.600 --> 00:35:18.220 Most studies of PAH exposure show that it's rare to find a source for the general public 00:35:18.220 --> 00:35:20.660 that will exceed that kind of an ingestion. 00:35:20.660 --> 00:35:26.770 This is for children that are in the average children that eat the average amount of dust. 00:35:26.770 --> 00:35:31.690 Then if you look at the right, it's about 100 milligrams per day. 00:35:31.690 --> 00:35:35.910 I should say that 100 milligrams per day was sort of a default value for dust not that 00:35:35.910 --> 00:35:37.100 long ago. 00:35:37.100 --> 00:35:42.350 There are a lot of different values that people have settled on, but we feel like these are 00:35:42.350 --> 00:35:44.890 the most robust that are available to us right now. 00:35:44.890 --> 00:35:55.010 As you can see, we're getting up towards 240 nanograms per kilogram per day, compared to 00:35:55.010 --> 00:36:01.400 in the range of about 24 or right around 25 for dietary ingestion so we did believe, from 00:36:01.400 --> 00:36:08.680 this initial set of calculations that we could be looking at a significant source of exposure 00:36:08.680 --> 00:36:13.640 for PAHs for children in residential settings. 00:36:13.640 --> 00:36:19.900 As you guys know, PAH exposures, generally you would think that most of your PAH exposures 00:36:19.900 --> 00:36:21.910 for the general public come from dietary. 00:36:21.910 --> 00:36:27.410 But if you're looking at PAH exposures that are relevant and likely to cause significant 00:36:27.410 --> 00:36:29.610 problems, you'd be thinking about smokers. 00:36:29.610 --> 00:36:32.970 Then on the occupational side, you're thinking about people who work at coke ovens, stuff 00:36:32.970 --> 00:36:34.510 like that. 00:36:34.510 --> 00:36:39.880 We decided to take the next step, and go ahead and take the data that we had and start thinking 00:36:39.880 --> 00:36:45.740 about what this might mean for people in terms of their cancer risk. 00:36:45.740 --> 00:36:52.380 We followed the default parameters for Superfund, knowing that coal tar and coal tar pitches, 00:36:52.380 --> 00:36:57.470 there's quite a bit of epidemiological evidence to support the idea that these are human carcinogens. 00:36:57.470 --> 00:37:03.230 Of course as you all know, EPA has had a float factor for BaP and related compounds for quite 00:37:03.230 --> 00:37:04.230 a while. 00:37:04.230 --> 00:37:05.920 This is still undergoing revision. 00:37:05.920 --> 00:37:10.880 There's still an ongoing robust scientific discussion about this topic, but the bottom 00:37:10.880 --> 00:37:18.070 line is, all of the evidence we have seems to center on the idea that these things do 00:37:18.070 --> 00:37:20.960 cause cancer in people. 00:37:20.960 --> 00:37:24.870 Go on ahead, Barbara, we'll go to the next one. 00:37:24.870 --> 00:37:30.340 The next thing we decided to do is this is a simplification of a larger manuscript so 00:37:30.340 --> 00:37:36.960 what we decided to do was set up a hypothetical scenario in which people who lived in these 00:37:36.960 --> 00:37:43.570 residences adjacent to coal tarsealed pavement were compared to the people who were exposed 00:37:43.570 --> 00:37:49.500 to concentrations of PAH consistent with parking lots that weren't sealed with coal tar. 00:37:49.500 --> 00:37:52.800 Here you can see the differences in the risk. 00:37:52.800 --> 00:37:58.470 What you see over here on the left is something we would generally refer to as in the area 00:37:58.470 --> 00:37:59.610 of de minimis. 00:37:59.610 --> 00:38:06.170 It was mostly right around 10^(6), so right around one in a million. 00:38:06.170 --> 00:38:09.590 Right around one in a million, as high as three in a million. 00:38:09.590 --> 00:38:15.450 If you consider upperrange exposures, then you can get something a bit higher. 00:38:15.450 --> 00:38:22.470 It is completely dwarfed by the theoretical lifetime cancer risk you would expect to encounter 00:38:22.470 --> 00:38:28.860 if you lived in an environment that was contaminated with coal tar, or affected by coal tar. 00:38:28.860 --> 00:38:36.070 What we're seeing here, is concentrations in soil tend to be a bit higher. 00:38:36.070 --> 00:38:38.200 Soil adjacent to these spaces tends to be higher. 00:38:38.200 --> 00:38:43.590 That's not a huge surprise; much more clean as you go inside the home. 00:38:43.590 --> 00:38:48.380 You can see that the predominant source of risk here is associated with soil. 00:38:48.380 --> 00:38:55.280 Even with house dust, we're reaching a level that is in excess of 10^(5), and 10^(4) is 00:38:55.280 --> 00:39:00.950 generally the kind of range for a Superfund risk assessment which EPA would say, "We're 00:39:00.950 --> 00:39:04.860 going to have to do something about this and we need to start thinking about it right now." 00:39:04.860 --> 00:39:09.230 10^(5) for a general population is kind of a remarkable number. 00:39:09.230 --> 00:39:13.900 I should also say, the number that you're looking at right now, this is an average. 00:39:13.900 --> 00:39:16.580 This is not the reasonable maximum exposure. 00:39:16.580 --> 00:39:21.850 This is essential tendency exposure, so the average of what we'd expect people to be exposed 00:39:21.850 --> 00:39:23.710 to. 00:39:23.710 --> 00:39:29.820 If you look at the reasonable maximum exposure, which means people are maybe just eating a 00:39:29.820 --> 00:39:34.240 little more dust or coming into contact with a little more soil, it winds up being about 00:39:34.240 --> 00:39:41.690 5x10^(4), which is an eyeopening number, or it would be in a Superfund risk assessment. 00:39:41.690 --> 00:39:48.270 What we're also looking at here is a lifetime exposure. 00:39:48.270 --> 00:39:53.260 Because of the nature of people, some people do live in the same place for their entire 00:39:53.260 --> 00:39:58.980 life, so we wanted to have a look at this with regard to shorter spans of time. 00:39:58.980 --> 00:40:03.590 One of our exposure scenarios, we were looking at children who lived in these kind of settings, 00:40:03.590 --> 00:40:07.650 basically from birth until right before they turned six years old. 00:40:07.650 --> 00:40:14.960 We found at that time that these children, in average, were in the 4x10^(5) range, so 00:40:14.960 --> 00:40:17.150 that's 4 in 100,000. 00:40:17.150 --> 00:40:22.691 If you think about reasonable maximums, then we're talking in the area of 3x10^(4), so 00:40:22.691 --> 00:40:28.630 even just over six years of life in a reasonable maximum exposure, you would expect children 00:40:28.630 --> 00:40:34.490 to be encountering what most regulatory agencies would consider an unacceptable risk. 00:40:34.490 --> 00:40:41.200 We should also note at this time...Barbara mentioned that there's an ongoing scientific 00:40:41.200 --> 00:40:46.550 debate, and certainly there are individuals out there who disagree with some of our conclusions 00:40:46.550 --> 00:40:52.120 along these lines, and that's certainly a conversation we're happy to have. 00:40:52.120 --> 00:40:57.820 The bottom line is, we did try to be very conservative in the way we've looked at these 00:40:57.820 --> 00:41:01.250 potential risks. 00:41:01.250 --> 00:41:06.640 We did a number of things which we felt were consistent with what we felt the actual situation 00:41:06.640 --> 00:41:07.640 was. 00:41:07.640 --> 00:41:15.340 We were encouraged at several points to use exposure parameters and risk assessment parameters 00:41:15.340 --> 00:41:20.470 characterization parameters that would have tended to increase our numbers, but we felt 00:41:20.470 --> 00:41:24.390 like the ones we were using were probably more reflective of the real situation. 00:41:24.390 --> 00:41:30.800 With regard to that, ultimately what the purpose of these two papers in environmental pollution 00:41:30.800 --> 00:41:35.970 and environmental science and technology the entire purpose of them was to point out that 00:41:35.970 --> 00:41:38.990 the exposures associated with these environments. 00:41:38.990 --> 00:41:46.650 These environments that have clearly been affected by coal tar use in adjacent spaces, 00:41:46.650 --> 00:41:51.330 seems to be associated with a strong likelihood of high PAH exposure for general population, 00:41:51.330 --> 00:41:53.230 for children in particular. 00:41:53.230 --> 00:41:59.230 Then we feel like there, under certain circumstances, are significant concerns for additional human 00:41:59.230 --> 00:42:01.800 health risk. 00:42:01.800 --> 00:42:06.200 What we're trying to do here is not to say that many children are going to wind up coming 00:42:06.200 --> 00:42:10.290 down with leukemia or liver cancer or so forth from this, but simply that at this point we've 00:42:10.290 --> 00:42:13.620 got to learn more about what we're looking at here. 00:42:13.620 --> 00:42:15.310 There is truly not enough data. 00:42:15.310 --> 00:42:22.270 This is an area that is in dire need of further research. 00:42:22.270 --> 00:42:25.820 This was a screeninglevel risk assessment based on theoretical exposures, and we would 00:42:25.820 --> 00:42:31.160 very much like to be able to fully characterize the exposure of children. 00:42:31.160 --> 00:42:35.730 That's a difficult question for lots of reasons, but that's something that we feel is going 00:42:35.730 --> 00:42:40.400 to be a critical area of research over the next several years. 00:42:40.400 --> 00:42:43.510 With that, I think I'll stop talking about human health. 00:42:43.510 --> 00:42:48.200 I think at this time Barbara and I will be ready to answer some questions from the audience. 00:42:48.200 --> 00:42:54.020 Barbara:  Spencer, I'd like to add one point here, which is that this human health risk 00:42:54.020 --> 00:43:01.060 analysis did not take into consideration either inhalation of PAHs in the air over the parking 00:43:01.060 --> 00:43:10.940 lots, nor did it take into consideration dermal contact or nondietary ingestion of the sealcoat 00:43:10.940 --> 00:43:13.490 particles on the parking lot itself. 00:43:13.490 --> 00:43:19.080 This doesn't take into consideration children's play activities, for example, on the seal 00:43:19.080 --> 00:43:20.970 coated driveway or parking lot. 00:43:20.970 --> 00:43:22.470 Spencer:  Yeah, that's absolutely right. 00:43:22.470 --> 00:43:25.730 This was purely from oral ingestion. 00:43:25.730 --> 00:43:28.620 The reason for that is that was our strongest dataset. 00:43:28.620 --> 00:43:32.860 It's also the strongest dataset on exposure parameters as well. 00:43:32.860 --> 00:43:34.890 Thank you very much, Barbara.