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Wind Turbines and Property Values in Ontario: Public Perception and Empirical Evidence – November 18th, 2014

[0:00] [Introductory music plays]

[0:04] Brady: Welcome to FARE Talk, where we set out to provide enduring discussions on contemporary topics relevant to our economy, with particular emphasis on food, agriculture and the environment. My name is Brady Deaton Jr. of the Department of Food, Agriculture and Resource Economics at the University of Guelph. I'll be your host.

[0:24] [Introductory music fades out]

[0:26] Brady: Today is November 18th, 2014, and we will be speaking to Dr. Richard Vyn about his research examining the effects of wind turbines on property values in Ontario. Dr. Richard Vyn is assistant professor in the Department of Food, Agriculture and Resource Economics at the University of Guelph at the Ridgetown campus. Rich, welcome to FARE Talk.

Richard: Thanks Brady, happy to be here.

[0:50] Brady: Rich has written an article recently that has appeared in the Canadian Journal of Agriculture Economics examining this issue, and for those of you tuning in, we will be doing this podcast in a different way, in the sense that we are in a classroom at the University of Guelph, looking and talking with students about this issue, and they will be asking the questions to Rich about his research. So let me begin by handing over the microphone to one of the students who will begin asking the first question.

[1:24] Student: Hello Richard. Before we focus on the effects of wind turbines on surrounding property values, can you give us a general background of wind turbines in the province?

Richard: Sure, yea. The wind energy industry in Ontario has been developing at a fairly rapid pace, and that has come about for a couple of reasons. One of the main push, the primary push behind this would be the Ontario government with the Green Energy and Green Economy Act and that sort of spurred the push to get more energy from renewable resources. So we have seen a considerable expansion in the wind energy industry as a result. This has led to a number of issues, and we have seen this most recently, there was a study that was put out just last week by the government that looked at the impacts of the wind turbines on health, and they didn't find anything significant there in terms of some obvious linkages between health issues and the wind turbines. But, there still are some concerns. They raised the issue of the annoyance factor. Either way though, this has certainly led to a lot of controversy in Ontario. There is a lot of local residents that have complained about the impacts, either on health or on property values, on the inability to sell properties. Which, all of the issues are kind of linked. But ultimately, it has led to this escalading controversy about what the impacts of these wind turbines are. Added to the mix is the fact that a lot of places where wind farms are put up, the municipality can't really reject it. They can be called unwilling hosts, but ultimately it is up to the province to decide whether or not a wind farm application is going to go through. So that's sort of a bit of the background that's led to these concerns about the potential impacts on not only health, but also on property values and that's sort of led to my interest in this subject area too. To see, we have all of these concerns that have been raised, and you look at any story in the popular press, there's a lot of concerns that are expressed there, so what is actually happening? That’s kind of what I wanted to take a look at.

[3:41] Student: Can you tell us a bit about why your study focused on the Melancthon township?

Richard: Yea, the Melancthon Township, yea. That's where I started because that is what I had data for. It was data that included farm sales and rural residential sales. The time that I did the study I didn't have data for anything beyond that township, at least in terms of where a wind farm was actually sited. I do now, and so that's kind of what I am looking to do in the coming months, is kind of expand this research. But for the current study that we are looking at, yes, it was just for the Melancthon Township. It was one of the first industrial wind farms that went up in the province of Ontario, and kind of made a good place to start in terms of assessing the potential impacts of the turbines on property values.

[4:29] Brady: Now Rich, correct me if I am wrong, but when you are talking, Melancthon township would be a township in Dufferin County [Richard: Yes] kind of bordering Grey, is that right?

Richard: Yes, Grey country is next and also bordering Wellington County.

Brady: And this is primarily an agricultural, rural township?

Richard: It is primarily rural, yes. There is, the wind farm itself is situated pretty close to a small town but there are no large urban centres anywhere within visibility of the wind farm.

[5:00] Student: Sorry. Your paper reviews previous research on the effects of wind turbine on property value. So our question to you is if you can review any of this previous research to us.

Richard: Sure, yea. There has been a number of studies that have been conducted, looking at the same issue in other jurisdictions and the results of these studies have been largely mixed. We haven't seen any particular trend that has tended to occur amongst these studies. Some studies have found evidence that yes, there are significant impacts of wind turbines on property values, where others have not found any significant evidence. So, we have seen, yea, a fair bit of mixed results in the literature, and because of that, it becomes necessary to conduct research on specific wind farms if you kind of want to have an idea as to what the impacts actually are. You can't just rely on results of other jurisdictions, just because those results, you know, with both positive and no significant impacts, it is hard to tell what exactly the results might be, for in the case, the Melancthon wind farm.

[6:03] Student: The, some of the previous research used willingness to pay as one of the methods of analysis. Before you get into your method, the hedonic method you used, would you be able to shed some light on the willingness to pay method?

Richard: Sure, yea. The willingness to pay is basically more of a survey approach in many cases, where they'll go to local residents, and they will ask "What has been the impact?" or "What do you perceive to be the impact of these turbines on your property value?" or just to the general public, they may ask, you know, "If you were to be sited next to this wind turbine, what do you think the impact would be?" So this approach looks more at, what people think is the impact, rather than looking at any sales data. Now if you go back to the previous question, looking at the results of previous studies, there is a difference in the results when you compare certain types of studies. So, you mention the willingness to pay studies. Those studies are more likely to produce evidence of a significantly negative impact on property values, whereas studies that use sales data tend not to find evidence of impacts on property values. So there is that difference in previous studies.

[7:25] Student: Hi Dr. Vyn, My name is Vanessa Cipriani. My question to you is, can you explain the method that you used in this particular study, in order to find out the effects on property values?

Richard: Sure. I used the hedonic method, which is a regression approach where you basically make the price a function of the set of attributes that the property has. So, you know, if you have a house on the property it would take a whole bunch of the individual attributes of that house, you know, the square footage, number of bathrooms, number of fireplaces, look at the size of the property itself, the value of any other buildings on the property, sheds and so on. Basically, you take as many possible attributes and it basically determines how much value each attribute contributes to the total value of the property. So that is an approach that has been used for a lot of different valuation studies. It tends to be a fairly effective approach in identifying what the value is associated with a specific attribute. So in this case, I am looking at not only the attributes of the house itself, also the location, you know, how close is it to a city, and then also how close is it to a turbine, or trying to find some attribute that accounts for the potential impacts of turbines. So this approach has been used for other types of studies where you are trying to find, for example, the impact of living close to toxic waste sites, if you are living close to high voltage transmission wires. A whole bunch of different amenities, or perceived disamenities, to determine what the impact might be of living close to those types of sites.

[9:15] Student: Were any of the attributes you chose particularly unique to your study, versus other wind turbine studies?

Richard: Well, the method I used to account for the turbines itself was a little different than had been performed in previous studies. Typically the previous studies looked at either the distance to turbines, or distance from the turbine to the property in question, or they looked at the visibility. I kind of came up with a metric that combined those two, because if you think about it, well, the distance to a turbine might affect the impact that it has on the property, but on the other hand, if the landscape is such that you can't actually see the turbine, than conceivably there wouldn't be as much of an impact relative to a property just as close where you can see the entire turbine. And then, similarly, if you can see the full turbine, but you're 3 kilometers away, likely the impact would be greater for a property than can see turbine that is just 1 kilometer away. So I try and account for the relationship between those two factors in this study. I also did use each factor, the proximity and the visibility separately in assessing the effects of turbines.

[10:30] Student: You touched on this township as being one of the few that had the necessary data. So my question is, what data was necessary to run this study, and where and how did you get it?

Richard: The data I used is property sales data, and the reason that this was the one, or at least at the time, the one county where we had sales data, was just based on the data that we received, Brady and myself, from the municipal property assessment corporation. As we have, as part of the University of Guelph, have a data sharing agreement with the municipal property assessment corporation for sharing back and forth of data. So they will send us property sales data, which we can use to run some of our analysis, and we in turn have provided them some additional data that we have created based on their sales data. But ultimately, running this analysis depended on getting that property sales data from MPAC and it included not only in Dufferin county, but some of the neighbouring counties property sales data there as well. So MPAC had provided rural residential sales data as well as farm sales data. And again, this is something that hadn't been done previously, looked at kind of comparing the effects on farms versus properties that are used more for residential purposes. The hypothesis that would be that, you would expect to see more of an effect on residential properties than farms. Farms are purchased, not only to live in but also to generate an income, where you may not expect to see as much of an impact, or as much value derived from the view. I should add that while the municipal property assessment corporation provided the data, the conclusions that came out of the studies are not necessarily the views of MPAC.

[12:14] Student: Hi Rich. Megan Moore speaking. You mentioned some key variables like proximity in your paper, and I was wondering how you measured those key variables.

Richard: Yea, the proximity variables are measured using geographic information system software, which we ourselves didn't generate; we have somebody who takes the location of the property and in some cases, the location of the city, or the location of the turbine, and generates the distance in meters from the property to each of these locations. So, using the or the distance to the nearest city was based on the road distance. So the most likely path you would take from the property to the city, how many kilometers is that, or how many meters is that. And, a lot of studies that have looked at property values will include some type of location variable, where you would expect the closer you are to an urban centre, the higher the value would be. So a similar approach is used for the distance to the turbine, except in this case, we looked at the straight line distance. So, how far was it from the property to the nearest turbine? So this required having the coordinates, the GIS coordinates for each of the turbines, and then for each property in question, and then using those coordinates to generate the distance between them. And this is sort of an approach that is being used more and more in property value studies, the use of GIS. There is, you know, the data availability there is rapidly increasing, and it really adds to the study, makes it a lot more robust, instead of just estimating what a distance might be.

[13:59] Student: Hi Rich. Clarke Stewart. I was wondering if you could review for us some of your key findings from your research, and tell us how they differed from your original hypothesis.

Richard: Sure. Now when I started this study, I mean I had heard some of the stories of what people had said were happening to their property values as a result of the wind turbines, and so reading about some of these accounts made me think, well, if this many people are suggesting that these impacts have occurred, than there must be something that would be picked up by the results of this study. That hypothesis wasn't supported by what I found however, when I looked at both rural residential and farm properties, I found that no significant impacts were observed, you know, either by looking at the proximity, or by visibility, or by combination of those factors. So, that was, in a way, based on what we have heard, a little surprising given the rhetoric that has occurred around this issue in Ontario. We may have expected to see more of a negative impact, especially in close proximity to the turbines, but that didn't take effect in the results of this study. What we found is that there is no significant impacts, you know, if you look at the impacts that are there, positive or negative, there is slight either way, but nothing that's statistically significant, so that was a little surprising. But, and not in line with what we've heard from a lot of the news stories, but also its important information to have I think. I think, and that was another reason why I wanted to conduct this study, was, you know, we have heard a lot about what people are claiming to be the effects, but when we look at the actual sales data, what is it telling us? And in this case, the sales data is suggesting that there are no significant impacts of the wind turbines in this case.

[15:58] Student: You mentioned that there were no significant impacts. How robust were these findings, and were these findings different for residential and agricultural property values?

Richard: Well first of all, they were not different for rural residential or for agricultural property values. In both cases, there were no significant impacts. In terms of the robustness, I did look at a number of different model specifications to try and ensure that the results were robust. So, I looked at different specifications of what the post turbine period would be. So the post turbine period refers to the period of time in which we would expect impacts to arise. And this is one of the trickiest variables to specify, because when exactly would the impacts begin to arise? That depends on what information is out there. I mean, obviously, when the turbines are actually up, you can see them, and you would expect impacts to occur from that point onward. But what about before that? You know, there is, there can be an announcement effect. So I looked at a number of different specifications for the post turbine period. I didn't find any differences across these different specifications, but basically, I looked at, first of all, the impacts starting at, you know, the time that construction began. So, at that point in time, everybody could kind of see where these turbines are going to be located. They may not be up yet, but, if you are buying a house in the area you can definitely see where they are going to be. I also looked at the post construction period, so when all of the turbines are actually up, and you can see them all. So looking to see, or specifying that as the post turbine period. And then also looking at the post approval time period. So as soon as we know this project is going forward, things are starting to move ahead, then people know that there is going to be turbines there. So, it is possible that the impacts will start at that point in time. So for each of these scenarios, I didn't find any evidence of significant impacts. I also looked at a number of other ways to specify the model. I looked at just repeat sales, so basically where property is sold earlier in the time period that the data covers, and then is sold again at a later point in time. The ideal scenario is where we have one of these sales occurring before the turbines went up, and one occurring after. It makes for a great way to determine whether there is going to be significant impacts. And again, the results are the same. Now the number of sales in close proximity is relatively low, not that it is lower than anywhere else, but just when you are looking at a 1 kilometer band around, you know, the turbines, the number of sales is not huge in the post turbine period. And so this may influence the results to some degree. There is other more recent studies that have just come out this year that have included a much larger number of sales in closer proximity, and finding the same results, in fact. But that can be seen as a limitation of the study, the fact that the number of sales is not as high as we would like it to be.

[19:18] Student: What do you think are the future needs to research within this area?

Richard: Future needs of research in this area? I think that we really need to continue to look at it for individual wind farms. It wouldn't surprise me if we do find, at some point in Ontario, we do find evidence of negative impacts of wind farms. The reason for this is just given the increasing attention this issue has drawn, and just how people value properties. I mean, a lot of the value you place on a property is relatively subjective. So why does one property, you know, exact same house, you put it in a different location, why is the value any different? Because of how people perceive the differences in those locations. SO in the past few years there have been a big increase in the amount of concerns that are raised, the public press articles that are expressing these concerns, and more and more people re hearing about these potential impacts. And so I'm wondering if this will eventually translate into observed impacts on property values. I mean in one sense you can only hear about these impacts again and again for so long before you actually start to believe that these impacts do actually exist. And it's not beyond the realm of possibility when you consider the fact that a large turbine has been put up, that maybe there would be impacts. If you look at the amounts of backlash in Melancthon, after that project was approved, at least from what we can tell, looking at the articles in the local newspaper, there wasn't all that much backlash. There was some concern that was expressed, but relative to the attention that current proposed projects are getting, there certainly wasn’t very much backlash at all. So I am wondering if the amount of backlash we see at some of these more recent wind farm, wind developments projects, if that will translate into more of an observed impact on property values, it wouldn't surprise us. I think that is really where I would like to continue my research. Now, I do have some additional data, sales data, to be able to extend this research, so that is kind of what I am trying to do now, is take a look at some of these more recently developed wind farms to see if the effects are consistent with what we observed in Melancthon or if there is going to be some difference there.

[21:45] Student: Okay, so you mentioned that the literature has reached some different conclusions than your study, could you further discuss these differences, and can these differences be overcome with future research?

Richard: Yea, so there are some of those differences, and as I mentioned before some if it is in part due to the, or it appears to be a result of the type of method used. But that's not even consistent across the method. If you look at the hedonic method, which I used, moth hedonic studies have not found evidence on negative impacts, but there is at least one study that I am aware of that has found some evidence. A study that was based in the state of New York. So they didn't find negative evidence consistently across all locations, but there was some evidence, and that was kind of the first one, at least in the peer reviewed literature that had indicated a negative impact. Previous hedonic studies had not found any evidence of negative impacts. And, whereas if you look at some of the willingness to pay studies, there are certainly more likely to find negative impacts. So, we have this variation in the literature, which makes it hard to determine what the impacts are going to be, and I think that's why further research is going to be necessary. Because, each individual location where a wind farm goes up is sort of a different story, you know, how well it's received by the community, how much community buy in there is, you know, the amount of backlash it gets. So even within Ontario, there is a fair bit of variation in terms of what the situation is as the wind farm develops. And I think that could contribute to the impacts, and that may be behind the varied results in previous studies, just how much backlash was against it, how well people perceived these turbines, you know, if they were happy with the wind farm, happy with the revenue it was bringing to their community. I mean, that's the other side of it. There are those types of benefits that go along with wind development as well that may factor in to how people perceive them. So all this variation, I think, leads to the need for continued research. If you really want to know what the impact is going to be in a given area, you kind of need to examine that area itself, distinct from any other area.

[24:08] Brady: Rich I wanted to comment on your title of the paper that you recently published, which by the way, there will be a link up to on the site, that will allow you to go and look at this paper. And the title is The Effects of Wind Turbines on Property Values in Ontario: Does Public Perception Match Empirical Evidence? This is a great question "does public perception match empirical evidence?" So, in summary of kind of what you've just been presenting to myself and the class, what is the answer to that question?

Richard: The answer is well, for the most part no. At least, it doesn't match what is the majority of public perception. I mean there certainly are people that, you can read comments, that come online under stories on wind turbines, the majority of comments seem to be from people that believe that there are negative impacts of turbines. But there are comments from people who like the turbines, they have no problem with how they look, they, you know, may actually live by them and not be bothered by them, or be willing to live by them. So, I would say that the public perception isn’t consistent across all people. There certainly are those that don’t have a problem with wind turbines, but it seems that the majority of people that you hear from do have an issue with it. So, from that perspective, no, the empirical evidence, at least from this study, doesn't match the public perception.

[25:36] Brady: Now for those of you listening to this podcast, the first set of questions were questions that we worked together in a class, in Land Economics, to prepare for your presentation. What I would like to do now, is turn over the questions to students who might have developed questions in listening to this presentation, or having thought from, thought more about this issue from our reading or your paper. Just while they think about that I'll just ask a question. Have you had any, your paper was just recently published, so far as I know it's one of the first if not the first peer reviewed publication on this issue in the economics journal, in Canada, have you had much of a reaction to it?

Richard: You know, I haven't has as much of a reaction as I would have expected, just given the attention that this issue has received in Ontario. I haven’t heard anything from the government, for example, or from Wind Concerns Ontario, or any organizations like that. Haven't had a response, and maybe that will come, and I certainly hope it does, because I want this research to kind of be a stepping stone to further discussion on the issue in Ontario, and I also don’t see these study as sort of the be all and end all of this issue. Well, this study finds no impacts, it means no exist. I don't look at it that way, I think this is just one step in, on the path to determing what are the impacts here, and how exactly are we going to address this issue. So, I hope that this study gets some more response, and I also hope to build on this study and take a closer look at this issue across the province.

[27:15] Student: Hi, Megan Moore again. You mentioned earlier how you measured your proximity variable and I was really interested in how you measured your visibility variable, because you had three different stages. And how did that affect the public perception when they are looking at wind turbines in their area?

Richard: Right, so how I measured the visibility variable is actually going out to Melancthon Township, and driving around and going to each property that I had in the data sets, and assessing what the visibility of the nearest turbine looked like. So, go to the property, or as close as I could get to it, and determine, you know, how much of the wind turbine was visible. So I had a three point scale, four point if you include no visibility. So one point, if you could just kind of see a little bit of it, you know, maybe just the tip of it above the trees. Two points if you could see the hub of the turbine, and three points if you could see most or all of the turbine. And the theory there is that the more of the turbine you can see, likely, the bigger the impact it might have on property values. If you can't see much of it, it's probably not going to affect your view much, so you may not perceive that to have a negative impact on your property.

[28:24] Student: Hi Richard. My name is Gabby Nichols. I was wondering if you were aware of any other studies done in other regions or countries that preceded turbine development in Ontario, and if they had similar responses to Ontario, kind of the backlash that we saw here. Was it the same, in say, Germany or something like that?

Richard: I'm not actually sure about how, or what the response has been like in some of these other jurisdictions. I know here in Canada, you know, Ontario obviously has a fair bit of wind power, but Alberta has had it well before Ontario ever did. And in Alberta they certainly haven't had anywhere near the kind of backlash that we have had here. It almost seemed to happen without anybody really saying a whole lot about it, and even now, I mean, there is a fair bit of wind power generation in southern Alberta, but there doesn’t seem, or at least I haven't heard of any issues that local residents have raised in terms of the impacts on property values, and I don't expect there to be either, because those turbines have been there for quite a while now. In other jurisdictions, I mean, in the US I have heard of, yes similar type of backlash, especially with, it seems more recent wind farm developments have kind of had greater backlash following their, at least their announcement or suggesting that they are going to go ahead with this plan. SO that seems to be more of the trend that I've seen, is that as time goes on, the resistance to the development of wind power is getting stronger, because of factors such as the impact of property values.

[30:04] Student: Just another question. Going back when you were talking about future research needs, you mentioned how since the value of a house is largely subjective as we move into the future and more people hear about these potential impacts, even though they may be from unreliable sources, you said it could become sort of a self-fulfilling prophecy, as we start to see these go down. So, alternatively, if you improve the access to information, this information specifically, instead of sensationalists’ news stories, do you think that the public perception could improve? So if more people, essentially, read this paper, do you see that improving public perception of it?

Richard: I think it could help a little bit. At the very least it would sort of inform public opinion about these issues. But on the other hand, if people believe that there are these impacts, it really doesn't matter what research studies such as this one suggest. We say that even with the Health Canada study on the, linking the wind turbines to health. They didn’t really find any significant linkages there. It was immediately dismissed, as I imagine this study will be as well, by those that believe strongly that there are these impacts. So, I think it furthers the discussion, but I don't know that a study like this will turn things around in terms of public perception. I would hope it has some impact on how it’s discussed, but I think for those that do believe there is a significantly negative impact on property values, this study isn't going to change. There are certainly some limitations of this study, and I think that because there are limitations, as there are with any study, that may be what gets focused on by those that believe there are negative impacts.

[31:59] Student: Hi, my name is Katie Caldecott, and I was wondering how would your results help policy makers or municipal councils decide how to manage wind turbines or whether to install them?

Richard: Well I would hope they at least take a look and consider the results of this study. I think, you know, municipalities, do need to have, you know, to get some sense as to what the potential impacts are going to be, not just on property values but on the economy of the municipality of a whole, when they are considering these. So, I would hope they would at least consider it and, you know, when, I guess they're not really the ones, in essence, deciding whether it's going to happen or not. I think they can decide whether they're going to be a willing host or not, but ultimately, it seems that the municipalities themselves aren't the ones that are going to be able to say yes or no. They may put up some resistance, but at the very least I would hope that this would help in their discussion, whether they think it would be good for the municipality or not.

[33:02] Brady: Would anybody else in the class like to ask a follow up question?

Richard: I have a question. Does anybody here live close to wind turbines? Yes? So how close?

Student: Um so, I live about ten minutes away from wind turbine farms near Port Burwell. But, it's a ten minute drive, so I can't actually see them.

Richard: Right. But have you noticed or heard anything about, sort of, what the perception is in that area?

Student: Um, there's always rumours going around, oh it’s making people sick, mentally. Um, things like that, but overall, when they first came to town everyone was quite excited.

Richard: Right and that was a few years ago, right? That was one of the first wind farms that were put up in Ontario. Yea.

[34:05] Student: Hi. I just have quick question, cause you mentioned that some studies have shown that there were more sales in the post time period of the turbines, and you mentioned that in your study this was a limitation. I was just wondering how much more, like is there a real significant change in the magnitude of the amount of sales? Like, would it be double? Triple?

Richard: Actually it is quite a bit more. For example, the study that came out this year, from Rhode Island, had about 3,000 sales there were in about 1 mile of the turbines. It's a little different setting there, it's not, it's mostly individual turbines in, that are considered in this study, rather than a wind farm where, in the example of Melancthon, there are 132 or 133 turbines. So this is a little different setting, but yes, they had considerably more sales that are within a close proximity of the turbines. And as well, a study that came out of, another study in the US, kind of looking all across the US had, it was over 1,000 sales that were within, again, 1 mile of the turbine. So, yea, so a couple more recent studies that have also, that are not bound by the same limitation I think, and produced similar results. So, and that's the thing, I mean I think it's important to acknowledge the limitations of these studies, and I think that the argument could be made, well, there is not enough there to, or people might suggest, there is not enough sales in close proximity to generate significant impacts. And I’m not quite sure that that's the case, as, you know, the study that was done in New York State had probably similar numbers of sales that were within the same distance changes, and did find some significant impacts. But also, another, you know, another consideration is that there may be an individual property here or there for whatever reason seems to be negatively impacted, and you know, or can't sell, and so the owners of that place might argue with the results of this study, and I think that's fair enough. But I think the results suggest that overall, you know, for properties that are close by, there really isn't much of an impact. But, the hedonic method, sort of estimates an average effect across all affected properties. So that is not to say that one of those properties is not negatively impacted if, you know, even if the rest of the properties are not. So that possibility may exist, and that's almost more, you know, I mean, you can look at it more anecdotally there, but overall I think the results of this study are encouraging, just from the fact that, you know, it gives you an average affect, and that average affect in this case doesn't seem to be anything significant.

[36:57] Student: Hi my name is Katie again, and I live about half an hour away from wind turbines located in Tiverton. And I can still see the lights flickering at night, and I was wondering, how far of the distance did you go in your studies, to see the effects of wind turbines.

Richard: In the Melancthon area, I went about five kilometers away. And I went during the day time, obviously that is a better time to go to be able to observe, to be able to actually see the turbines. But as I was driving around there I found that 5 kilometers, given the landscape there, was about the extent of visibility. You know, at five kilometers, you could, if you could see it, you could barely see it, and it was kind of such that it didn't really impact your view shed. But I wasn’t there at night, so I don't know what it looked like in terms of the lights flashing.

[37:47] Brady: Dr. Richard Vyn, thank you so much for coming and spending time with our class, and doing this podcast, which I am sure will be of great interest to those in Ontario and throughout Canada and throughout the world. Thank you, very much.

Richard: Thanks, my pleasure.


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