Shadow Flicker Impact Analysis for the Alabama Ledge Wind Farm in Genesee County, New York

Transcription

1 Shadow Flicker Impact Analysis for the Alabama Ledge Wind Farm in Genesee County, New York Prepared for Alabama Ledge Wind Farm, LLC 2 Borden Avenue, Suite 203 Perry, New York Prepared by 160 Federal Street, 3 rd Floor Boston, Massachusetts April 2010

2 Shadow Flicker Impact Analysis TABLE OF CONTENTS 1.0 INTRODUCTION OVERVIEW OF SHADOW FLICKER WINDPRO SHADOW FLICKER IMPACT ANALYSIS RESULTS CONCLUSION REFERENCES... 8 TABLES Table 1. Table 2. Table 3. Shadow Flicker Impacts for Receptors with Maximum Impacts Greater than 30 Hours/Year... 4 Statistical Summary of Shadow Flicker Impacts at Modeled Receptor Locations... 5 Shadow Flicker Impacts for Receptors with Maximum Impacts Greater than 30 Minutes/Day... 5 FIGURES Figure 1. Sensitive Receptors... 9 Figure 2. Expected Shadow Flicker Impact Areas ATTACHMENT Attachment A Shadow Flicker Analysis Results Summary i

3 Shadow Flicker Impact Analysis 1.0 INTRODUCTION Tetra Tech EC, Inc. (Tetra Tech) performed a revised shadow flicker impact analysis on behalf of Alabama Ledge Wind Farm, LLC (ALWF) for the proposed Alabama Ledge Wind Farm (the Project) located in the Town of Alabama in Genesee County, New York. Tetra Tech conducted an initial shadow flicker impact analysis for the Project in support of the Draft Environmental Impact Statement (DEIS) which was accepted by the Town of Alabama on February 26, 2008 as the Lead Agency in the State Environmental Quality Review (SEQR) process. The initial shadow flicker impact analysis considered three turbine model types which were being considered by ALWF at that time for a 52-turbine layout with a maximum capacity of 104 megawatts (MW), as was presented in the DEIS. Three hundred sixty-five (365) receptors were identified in the surrounding Project area using recent aerial photography considered in the initial shadow flicker impact assessment. The receptors considered represent residences (houses) within 1,500 meters of any proposed wind turbine location. Of those 365 receptors, only 21 had predicted shadow flicker greater than 30+ hours per year of shadow flicker. The initial shadow flicker assessment used conservative assumptions in the modeling in order to demonstrate the expected shadow flicker impacts resulting from operation of the Project. As ALWF continues to develop the Project with the ultimate goal of completing necessary permitting requirements and satisfying the State Environmental Quality Review Act (SEQRA) in order to commence construction, ALWF has begun micrositing Project features in an effort to reduce and avoid environmental and community impacts resulting from the Project wherever possible. Since the DEIS was issued, ALWF has reduced the Project layout to include up to 40 turbines (layout Version 18). As wind turbine technology continues to evolve rapidly, the potential exists for ALWF to select a different wind turbine than the turbine models evaluated previously in earlier iterations of the shadow flicker analysis. Final selection of the wind turbine model to be used for the Project has not been determined at this time. Since larger wind turbines generally result in greater shadow flicker impacts, this revised shadow flicker analysis has evaluated a generic larger wind turbine that represents the largest likely turbine dimensions to be used in this Project (details given in Section 2.0) to ensure that the most conservative predicted shadow flicker impacts are evaluated. Tetra Tech has performed this revised shadow flicker impact analysis in order to provide ALWF with more realistic expected impacts to receptors using the latest Project Version 18 layout and most conservative turbine model scenario. The results of this report will also support the Town of Alabama s Supplemental Draft Environmental Impact Statement (SDEIS) for the Project. 1

4 Shadow Flicker Impact Analysis 2.0 OVERVIEW OF SHADOW FLICKER A wind turbine s rotating blades can cast a moving shadow on locations within a certain distance of a turbine. These moving shadows are called shadow flicker, and can temporarily impact nearby residences or public gathering places. The potential impact area depends on the time of year and day (which determines the sun s azimuth and altitude angles) and the wind turbine s physical characteristics (height, rotor diameter, blade width, and orientation of the rotor blades). Shadow flicker generally occurs during low angle sunlight conditions, typical during sunrise and sunset times of the day. However, when the sun angle is very low (less than 3 degrees), the light has to pass through more atmosphere and becomes too diffuse to form a coherent shadow. Shadow flicker will not occur when the sun is obscured by clouds/fog, the source turbine is not operating, or at night. Further, shadow flicker impacts can be greatly diminished by the presence of trees or other tall structures located closer to the receptor. Shadow flicker intensity is defined as the difference in brightness at a given location in the presence and absence of a shadow. Shadow flicker intensity diminishes with greater receptorto-turbine separation distance. Shadow flicker intensity for receptor-to-turbine distances beyond 1,500 meters is very low and generally considered imperceptible. In general, the largest number of shadow flicker hours, along with greatest shadow flicker intensity, occurs nearest the wind turbines. Since the Town of Alabama requires a minimum turbine siting setback of meters to any residence, receptors are generally not located in the in the area where the potential shadow flicker impacts would be greatest, which ensures that shadow flicker impacts are minimized. The final wind turbine model has not yet been determined for the Project. Since larger turbines generally result in greater shadow flicker impacts, this study has been conservatively based on a generic turbine with the largest potential dimensions that would be reasonably used for the Project. The generic turbine evaluated has a hub height of 100 meters and a rotor diameter of 90 meters. Shadow flicker frequency is related to the wind turbine s rotor blade speed and the number of blades on the rotor. From a health standpoint, such low frequencies generated by wind turbines are harmless. For comparison, strobe lights used in discotheques have frequencies which range from about 3 Hertz (Hz) to 10 Hz (1 Hz = 1 flash per second). As a result, public concerns that flickering light from wind turbines can have negative health effects, such as triggering seizures in people with epilepsy are unfounded. The Epilepsy Action (working name for the British Epilepsy Foundation), states that there is no evidence that wind turbines can cause seizures (Epilepsy Action 2008). However, they recommend that wind turbine flicker frequency be limited to 3 Hz. Since the blade pass frequency for any of the wind turbines that may be selected, will be less than 1.0 Hz (less than 1 alternation per second), no negative health effects to individuals with photosensitive epilepsy are anticipated. 2

5 Shadow Flicker Impact Analysis Shadow flicker impacts are not regulated in applicable state or federal law, and there is no permitting trigger with regard to hours per year of anticipated impacts to a receptor from a wind energy project. Due to the significant growth of the wind energy industry in recent years, some states have published model bylaws for local governments to adopt or modify at their own discretion which sometimes includes guidance and recommendations for shadow flicker levels and mitigation. However, a general precedent has been established in the industry both abroad and in the United States that fewer than 30 hours per year of shadow flicker impacts is acceptable to receptors in terms of nuisance and well below health hazard thresholds. This shadow flicker impact analysis presents the potential shadow flicker exposure in both expected hours per year and worst case minutes per day in order to address the Town of Alabama zoning requirements of fewer than 30 hours per year and 30 minutes per day at a receptor. 3.0 WINDPRO SHADOW FLICKER IMPACT ANALYSIS An analysis of potential shadow flicker impacts from the Project was conducted using the software package. The analysis was conducted to determine shadow flicker impacts under realistic impact conditions (actual annual expected shadow). This analysis calculated the total amount of time (hours and minutes per year) that shadow flicker is expected to occur at receptors out to 1,500 meters. The realistic impact condition scenario is based on the following assumptions: The elevation and position geometries of the wind turbines and surrounding receptors. Elevations were determined using United States Geological Survey (USGS) digital elevation model (DEM) data. Positions geometries were determined using geographical information system (GIS) and referenced to Universal Transverse Mercator (UTM) Zone 18 (NAD83). The position of the sun and the incident sunlight relative to the wind turbine and receptors on a minute by minute basis over the course of a year. Historical sunshine hours availability (percent of total available). Historical sunshine rates for the area (as listed for Alabama, New York; City-Data 2008) used in this analysis are as follows: Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 33% 39% 48% 52% 58% 65% 68% 65% 58% 49% 33% 28% Estimated wind turbine operations and orientation based on 2 years ( ) of onsite measured wind data (wind speed/wind direction frequency distribution). The calculated wind direction frequency distribution for operating hour winds is as follows: N NNE ENE E ESE SSE S SSW WSW W WNW NNW 4.2% 5.2% 5.9% 5.6% 4.2% 4.0% 6.2% 14.5% % 8.1% 4.7% 3

6 Shadow Flicker Impact Analysis Receptor viewpoints (i.e., house windows) are assumed to always be directly facing turbine to sun line of sight ( greenhouse mode ). incorporates terrain elevation contour information and the analysis accounts for terrain elevation differences. The sun s path with respect to each turbine location is calculated by the software to determine the cast shadow paths every minute over a full year. Sun angles less than 3 degrees above the horizon were excluded, for the reasons identified earlier in Section 2.0. A total of 365 receptor locations were identified within 1,500 meters of the proposed Project turbines. These locations correspond to houses in the Project Area. A receptor in the model is defined as a 1 square meter area (approximate size of a typical window), 1 meter aboveground level. Approximate eye level is set at 1.5 meters in the model. Figure 1 shows the receptor locations considered for this analysis. 4.0 RESULTS predicts that shadow flicker impacts will primarily occur near the wind turbines. Figure 2 describes the predicted expected shadow flicker impact areas for the Project and includes the results from the field verification study conducted at the Project site. A detailed shadow flicker analysis results summary, for each of the modeling receptor locations, is provided in Attachment A. Table 1 presents the predicted shadow flicker impacts for the receptors with expected shadow flicker impacts greater than 30 hours per year. Table 1. Shadow Flicker Impacts for Receptors with Maximum Impacts Greater than 30 Hours/Year Shadow Hours per Year (Expected) Receptor ID* [Hours:Minutes/Year] : : : : : : : : : : : : : :03 *Note that all receptors in Table 1 are Project participants except #104 4

7 Shadow Flicker Impact Analysis The maximum predicted shadow flicker impact at any receptor, for the range of potential wind turbine options, is 47 hours, 57 minutes per year, which is only approximately 1.1 percent of the potential available daylight hours. The overwhelming majority of the receptor locations evaluated have less than 30 hours per year of predicted shadow flicker impact. The shadow flicker impact prediction statistics are as summarized in Table 2. Table 2. Statistical Summary of Shadow Flicker Impacts at Modeled Receptor Locations Cumulative Shadow Flicker Time (Expected) Number of Receptors Total 365 = 0 Hours 138 > 0 and < 10 Hours and < 20 Hours and < 30 Hours and < 40 Hours 9 40 Hours 5 As shown in Table 2, only 14 of the 365 receptors modeled had shadow flicker impact predicted for more than 30 hours per year. The software program was used to predict the maximum potential shadow flicker impacts that could possibly result from the Project turbines at surrounding receptors (houses) in minutes per day as well in order to satisfy the Town of Alabama zoning requirement. results indicate that up to 87 receptors had maximum impacts of 30 minutes or greater per day. The results for these worst case receptors are presented in Table 3. Table 3. Shadow Flicker Impacts for Receptors with Maximum Impacts Greater than 30 Minutes/Day Shadow Minutes per Day (Expected) Receptor ID [Hours:Minutes/Day] 78 1: : : : : : : : : : :08 5

8 Shadow Flicker Impact Analysis Shadow Minutes per Day (Expected) Receptor ID [Hours:Minutes/Day] 40 1: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :44 6

9 Shadow Flicker Impact Analysis Shadow Minutes per Day (Expected) Receptor ID [Hours:Minutes/Day] 106 0: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :30 7

10 Shadow Flicker Impact Analysis Note that the maximum daily shadow flicker impacts predicted with are especially conservative since they represent worst case potential impacts, and unlike annual expected impacts do not take credit for any typical mitigating conditions (i.e., cloud cover, turbines not operating or not in direct alignment with incoming sunlight, etc.). However, the worst case minutes per day of shadow flicker have been evaluated in this study as it is required by the Town of Alabama zoning law that shadow flicker impacts fall below 30 minutes per day and 30 hours per year at receptors and ALWF intends to use these findings to help the Project comply with local regulations. 5.0 CONCLUSION The analysis of potential shadow flicker impacts from the Project on nearby receptors shows that shadow flicker impacts on the majority of houses within the area of study are expected to be minor. The analysis conservatively assumes that the houses all have a direct in line view of the incoming shadow flicker sunlight and does not account for trees or other obstructions which may block sunlight, thus limiting potential impacts. In reality, the windows of many houses will not face the sun directly for the key shadow flicker impact times. In addition, potential shadow flicker impacts for wind turbines up to 1,500 meters away were determined in order to perform a conservative assessment of potential shadow flicker resulting from the Project. For these reasons, shadow flicker impacts resulting from the Project are expected to be less than estimated with the conservative analysis presented in the DEIS, and shadow flicker is not expected to be a significant environmental impact. The receptors with the highest number of modeled hours of shadow flicker expected per year who are under lease with ALWF have considered and waived concern for potential nuisance from shadow flicker on their property associated with the Project. Finally, there is no state or federal regulatory threshold for shadow flicker hours per year at a given receptor; therefore, the Project in no way violates state or federal permitting requirements or conditions according to the results of this shadow flicker impact analysis. With regard to the local Town of Alabama zoning ordinance, the Project as proposed could exceed the thresholds of 30 minutes per day of shadow flicker at 87 receptors and 30 hours per year of shadow flicker at 14 receptors on a given day; however, ALWF intends to mitigate these impacts and comply fully with the local law, which allows for applicant mitigation measures where exceedances are anticipated. 6.0 REFERENCES City-Data City.Data.com. Accessed 9/5/08. Epilepsy Action British Epilepsy Association. Accessed 9/5/08. 8

11 ,000 2,000 Project Location 1,200 Meters 3,000 4,000 Feet New York WTG 2 Pennsylvania WTG 1 Legend WTG 5 Wind Turbine (not to scale) Receptor WTG 7 WTG 6 WTG 13 WTG 19 WTG 15 WTG 17 WTG 16 WTG 18 WTG 20 WTG 21 WTG 25 WTG 23 WTG 37 WTG 35 WTG 28 WTG 27 WTG 31 WTG 29 WTG 30 WTG 34 WTG 33 WTG 33A WTG 38 WTG 42 WTG 42A WTG 50 WTG 49 WTG 41 WTG 48 WTG 22 WTG 24 WTG 56 WTG 39 WTG 40 Aerial Image Source: 2005 NAPP Digital Orthophoto Quarter Quadrangles WTG Source: Project Layout Version 18 represents the latest revised Project layout and was provided by Fisher Associates on October 28, WTG 45 WTG 55 WTG 43 ALABAMA LEDGE WIND FARM GENESEE COUNTY, NEW YORK FIGURE 1 SENSITIVE RECEPTORS TODD.GYS(ECIBOSDGYST) P:\Horizon - ALWF\GIS\Spatial\MXD\ShadowFlicker\ALWF_Receptors_11x17.mxd 2/24/2010

12 ,000 Project Location 1,000 Meters 2,000 3,000 4,000 5,000 Feet New York WTG 2 Pennsylvania WTG 1 WTG 5 Legend Wind Turbine (not to scale) WTG 7 Receptor >30 hrs/yr Expected Shadow Flicker WTG 6 Receptor Shadow Flicker Iso Line 15 hrs/yr 30 hrs/yr 50 hrs/yr 100 hrs/yr WTG 15 WTG 19 WTG 25 WTG WTG 27 WTG 31 WTG 50 WTG 49 WTG 41 WTG 48 WTG 28 WTG 38 WTG 42 WTG 42A WTG 22 WTG 24 WTG 34 WTG 33 WTG 33A 155 WTG 20 WTG 29 WTG WTG 35 WTG WTG 37 WTG 17 WTG WTG hrs/yr WTG WTG WTG 56 WTG 39 Aerial Image Source: 2005 NAPP Digital Orthophoto Quarter Quadrangles WTG Source: Project Layout Version 18 represents the latest revised Project layout and was provided by Fisher Associates on October 28, WTG WTG 55 WTG 43 ALABAMA LEDGE WIND FARM GENESEE COUNTY, NEW YORK FIGURE 2 WINDPRO PREDICTED EXPECTED SHADOW FLICKER IMPACT AREAS TODD.GYS(ECIBOSDGYST) P:\Horizon - ALWF\GIS\Spatial\MXD\ShadowFlicker\ALWF_Isolines_11x17.mxd 2/24/2010

13 Shadow Flicker Impact Analysis ATTACHMENT A Shadow Flicker Impact Analysis Results Output

14 Shadow Flicker Analysis Results Summary Receptor ID Worst Case Max shadow (hrs / day) Expected Shadow Flicker (hrs / yr) UTM-E UTM-N ,320 4,771,668 1:09 47:57: ,372 4,771,656 1:15 43:29: ,275 4,772,034 0:59 43:16: ,492 4,771,657 1:03 42:15: ,127 4,770,581 1:10 41:35: ,405 4,771,648 1:08 39:42: ,204 4,770,526 1:02 38:57: ,213 4,772,705 1:36 33:40: ,341 4,771,737 0:53 33:15: ,780 4,771,377 1:38 33:11: ,191 4,772,107 1:09 32:00: ,175 4,770,106 1:04 30:58: ,293 4,771,978 0:48 30:24: ,278 4,771,704 0:51 30:03: ,368 4,774,505 1:13 29:48: ,540 4,774,481 0:50 29:12: ,219 4,770,648 0:42 29:12: ,441 4,774,490 0:41 28:22: ,228 4,771,060 0:56 24:43: ,352 4,771,903 0:32 23:05: ,361 4,772,312 0:44 22:29: ,268 4,770,471 0:45 22:06: ,075 4,771,515 0:42 21:47: ,115 4,771,764 1:11 21:41: ,292 4,772,045 0:34 20:57: ,284 4,771,805 0:51 20:56: ,085 4,771,014 0:52 20:43: ,077 4,771,700 1:17 20:15: ,333 4,774,148 0:49 20:00: ,289 4,771,868 0:40 19:32: ,330 4,774,906 0:54 19:25: ,242 4,771,546 0:47 19:22: ,272 4,774,163 0:55 19:11: ,289 4,771,840 0:46 19:07: ,372 4,772,449 0:53 18:43: ,127 4,771,016 1:01 18:31: ,481 4,770,855 0:52 18:20: ,411 4,774,542 0:38 18:09: ,542 4,775,561 1:06 17:25: ,387 4,772,518 1:00 17:21: ,718 4,770,977 1:20 16:58: ,230 4,770,898 0:54 16:41: ,348 4,771,833 0:42 16:40: ,408 4,772,732 0:56 16:37: ,258 4,771,430 0:51 15:45: ,536 4,770,907 0:48 15:29:00

15 Shadow Flicker Analysis Results Summary Receptor ID Worst Case Max shadow (hrs / day) Expected Shadow Flicker (hrs / yr) UTM-E UTM-N ,634 4,770,996 0:57 15:16: ,336 4,775,003 0:49 15:14: ,107 4,772,059 0:38 15:12: ,018 4,774,494 0:38 15:09: ,182 4,772,477 0:42 14:36: ,148 4,772,134 0:41 14:17: ,559 4,770,991 0:46 14:16: ,240 4,774,492 0:30 13:56: ,317 4,774,563 0:32 13:54: ,157 4,773,877 0:35 13:41: ,042 4,772,025 0:35 13:15: ,451 4,774,141 0:38 12:22: ,038 4,770,370 0:52 11:42: ,065 4,771,096 0:46 11:29: ,391 4,772,494 0:27 11:23: ,646 4,771,007 0:25 11:05: ,434 4,774,186 0:40 11:03: ,477 4,770,962 0:41 10:59: ,108 4,770,970 0:45 10:35: ,614 4,771,473 0:37 10:30: ,324 4,772,651 0:28 10:26: ,587 4,771,014 0:27 10:14: ,386 4,769,895 0:28 10:05: ,027 4,772,125 0:33 9:54: ,037 4,774,575 0:33 9:53: ,266 4,773,778 0:29 9:50: ,334 4,770,988 0:58 9:46: ,185 4,774,483 0:42 9:29: ,671 4,775,569 0:45 9:21: ,219 4,769,943 0:28 9:09: ,383 4,771,287 0:32 8:49: ,233 4,771,023 0:38 8:46: ,223 4,772,863 0:41 8:35: ,334 4,772,928 0:56 8:33: ,381 4,771,043 0:34 8:20: ,527 4,770,608 0:21 8:14: ,087 4,769,909 0:24 7:57: ,540 4,771,534 0:33 7:55: ,271 4,773,840 0:29 7:37: ,178 4,773,790 0:31 7:17: ,618 4,770,962 0:26 6:53: ,464 4,771,038 0:30 6:53: ,143 4,772,616 0:50 6:52: ,567 4,771,448 0:36 6:52: ,458 4,771,527 0:29 6:49: ,657 4,771,012 0:28 6:45:00

16 Shadow Flicker Analysis Results Summary Receptor ID Worst Case Max shadow (hrs / day) Expected Shadow Flicker (hrs / yr) UTM-E UTM-N ,121 4,770,146 0:24 6:38: ,514 4,771,013 0:29 6:38: ,570 4,774,620 0:22 6:28: ,921 4,774,411 0:26 6:28: ,309 4,771,057 0:35 6:18: ,915 4,774,471 0:23 6:17: ,188 4,774,552 0:40 6:12: ,486 4,769,861 0:21 6:04: ,730 4,771,430 0:27 6:01: ,450 4,770,762 0:21 5:49: ,614 4,771,153 0:38 5:33: ,177 4,771,034 0:25 5:30: ,626 4,770,945 0:26 5:26: ,211 4,772,982 0:37 5:17: ,293 4,772,916 0:28 5:12: ,415 4,770,535 0:18 5:11: ,137 4,772,533 0:45 5:06: ,415 4,771,480 0:29 5:03: ,219 4,769,806 0:18 5:02: ,253 4,773,016 0:28 4:59: ,963 4,774,404 0:22 4:56: ,628 4,771,492 0:24 4:55: ,282 4,770,335 0:26 4:55: ,718 4,771,499 0:26 4:51: ,275 4,773,016 0:28 4:46: ,254 4,773,047 0:28 4:46: ,961 4,774,467 0:22 4:46: ,288 4,773,016 0:27 4:40: ,988 4,774,406 0:22 4:37: ,278 4,773,046 0:27 4:33: ,423 4,774,624 0:16 4:33: ,343 4,772,999 0:26 4:22: ,296 4,773,046 0:27 4:21: ,027 4,774,557 0:32 4:19: ,309 4,773,043 0:26 4:16: ,430 4,774,593 0:15 4:05: ,471 4,774,584 0:14 4:01: ,045 4,774,393 0:20 4:00: ,449 4,770,248 0:18 3:52: ,055 4,774,453 0:20 3:52: ,075 4,774,393 0:20 3:42: ,763 4,771,698 0:25 3:37: ,427 4,774,580 0:14 3:36: ,726 4,771,714 0:24 3:35: ,301 4,774,552 0:27 3:31: ,474 4,774,610 0:15 3:31:00

17 Shadow Flicker Analysis Results Summary Receptor ID Worst Case Max shadow (hrs / day) Expected Shadow Flicker (hrs / yr) UTM-E UTM-N ,155 4,772,728 0:26 3:30: ,107 4,774,472 0:19 3:24: ,993 4,769,912 0:15 3:20: ,533 4,775,538 0:30 3:20: ,035 4,775,491 0:25 3:18: ,544 4,775,585 0:29 3:15: ,174 4,772,721 0:45 3:13: ,469 4,774,551 0:13 3:09: ,173 4,769,591 0:13 3:06: ,240 4,771,177 0:16 2:54: ,557 4,769,779 0:19 2:52: ,389 4,774,558 0:14 2:52: ,915 4,774,575 0:28 2:47: ,179 4,769,942 0:16 2:43: ,475 4,774,670 0:15 2:36: ,498 4,774,644 0:14 2:30: ,476 4,774,688 0:15 2:30: ,234 4,771,096 0:16 2:26: ,263 4,774,387 0:16 2:21: ,480 4,774,720 0:15 2:20: ,303 4,774,457 0:15 2:09: ,970 4,775,592 0:23 2:08: ,429 4,774,538 0:14 2:06: ,759 4,774,580 0:24 2:01: ,338 4,774,394 0:15 1:59: ,412 4,770,486 0:18 1:57: ,177 4,769,852 0:16 1:56: ,711 4,775,538 0:22 1:56: ,505 4,774,883 0:15 1:56: ,354 4,774,435 0:14 1:55: ,198 4,771,212 0:15 1:54: ,368 4,774,434 0:14 1:53: ,362 4,774,384 0:14 1:52: ,384 4,774,392 0:14 1:47: ,390 4,774,446 0:14 1:46: ,822 4,769,887 0:18 1:44: ,400 4,774,128 0:13 1:44: ,674 4,775,537 0:21 1:43: ,405 4,774,436 0:14 1:42: ,390 4,774,264 0:13 1:41: ,405 4,774,228 0:13 1:40: ,397 4,774,290 0:13 1:40: ,433 4,773,601 0:16 1:39: ,410 4,774,343 0:13 1:38: ,409 4,774,391 0:13 1:38: ,410 4,774,317 0:13 1:37:00

18 Shadow Flicker Analysis Results Summary Receptor ID Worst Case Max shadow (hrs / day) Expected Shadow Flicker (hrs / yr) UTM-E UTM-N ,588 4,775,503 0:20 1:23: ,433 4,775,312 0:17 1:20: ,553 4,775,485 0:19 1:19: ,080 4,775,594 0:18 1:19: ,404 4,775,595 0:18 1:19: ,265 4,772,171 0:15 1:12: ,448 4,773,651 0:16 1:12: ,458 4,775,467 0:18 1:11: ,510 4,774,925 0:15 1:10: ,504 4,775,269 0:16 1:10: ,746 4,771,806 0:15 1:09: ,839 4,769,779 0:14 1:08: ,524 4,775,128 0:15 1:08: ,520 4,775,162 0:15 1:07: ,515 4,775,421 0:16 1:07: ,195 4,770,903 0:15 1:06: ,839 4,769,833 0:15 1:05: ,400 4,774,613 0:17 1:03: ,523 4,775,492 0:16 1:03: ,563 4,775,376 0:15 1:01: ,440 4,775,599 0:17 1:00: ,363 4,773,543 0:15 0:58: ,407 4,774,105 0:12 0:58: ,408 4,774,157 0:13 0:56: ,329 4,775,437 0:16 0:55: ,367 4,773,493 0:15 0:54: ,409 4,774,202 0:13 0:54: ,054 4,771,424 0:15 0:53: ,428 4,774,470 0:13 0:52: ,417 4,774,437 0:13 0:52: ,411 4,774,246 0:13 0:52: ,373 4,773,434 0:16 0:52: ,651 4,775,445 0:13 0:51: ,335 4,775,599 0:16 0:50: ,431 4,774,435 0:13 0:50: ,248 4,775,538 0:15 0:47: ,465 4,774,307 0:12 0:46: ,468 4,774,344 0:12 0:46: ,218 4,775,538 0:15 0:45: ,465 4,774,283 0:12 0:45: ,156 4,775,522 0:14 0:38: ,229 4,773,194 0:09 0:13: ,097 4,769,818 0:02 0:06: ,939 4,775,219 0:00 0:00: ,084 4,769,917 0:00 0:00: ,671 4,775,881 0:00 0:00:00

19 Shadow Flicker Analysis Results Summary Receptor ID Worst Case Max shadow (hrs / day) Expected Shadow Flicker (hrs / yr) UTM-E UTM-N ,896 4,775,656 0:00 0:00: ,983 4,775,587 0:00 0:00: ,033 4,775,539 0:00 0:00: ,141 4,773,849 0:00 0:00: ,256 4,773,865 0:00 0:00: ,136 4,773,897 0:00 0:00: ,214 4,773,621 0:00 0:00: ,146 4,773,608 0:00 0:00: ,229 4,773,517 0:00 0:00: ,204 4,772,836 0:00 0:00: ,238 4,773,275 0:00 0:00: ,274 4,773,957 0:00 0:00: ,345 4,773,889 0:00 0:00: ,348 4,774,020 0:00 0:00: ,266 4,773,446 0:00 0:00: ,081 4,775,554 0:00 0:00: ,199 4,772,985 0:00 0:00: ,765 4,771,922 0:00 0:00: ,656 4,772,214 0:00 0:00: ,794 4,772,195 0:00 0:00: ,758 4,773,154 0:00 0:00: ,842 4,774,709 0:00 0:00: ,826 4,774,730 0:00 0:00: ,763 4,774,654 0:00 0:00: ,922 4,774,637 0:00 0:00: ,971 4,774,648 0:00 0:00: ,151 4,774,638 0:00 0:00: ,098 4,774,643 0:00 0:00: ,069 4,774,625 0:00 0:00: ,954 4,774,501 0:00 0:00: ,976 4,773,863 0:00 0:00: ,204 4,773,864 0:00 0:00: ,372 4,773,928 0:00 0:00: ,422 4,773,866 0:00 0:00: ,338 4,773,855 0:00 0:00: ,541 4,773,856 0:00 0:00: ,479 4,773,862 0:00 0:00: ,690 4,773,793 0:00 0:00: ,491 4,773,905 0:00 0:00: ,513 4,773,909 0:00 0:00: ,587 4,773,902 0:00 0:00: ,623 4,773,901 0:00 0:00: ,546 4,773,906 0:00 0:00: ,571 4,773,857 0:00 0:00: ,811 4,773,891 0:00 0:00: ,813 4,773,925 0:00 0:00:00

20 Shadow Flicker Analysis Results Summary Receptor ID Worst Case Max shadow (hrs / day) Expected Shadow Flicker (hrs / yr) UTM-E UTM-N ,806 4,773,963 0:00 0:00: ,795 4,773,855 0:00 0:00: ,809 4,773,830 0:00 0:00: ,733 4,773,789 0:00 0:00: ,801 4,773,757 0:00 0:00: ,802 4,773,780 0:00 0:00: ,806 4,773,802 0:00 0:00: ,866 4,773,855 0:00 0:00: ,852 4,773,826 0:00 0:00: ,854 4,773,807 0:00 0:00: ,852 4,773,792 0:00 0:00: ,852 4,773,768 0:00 0:00: ,856 4,773,841 0:00 0:00: ,735 4,773,618 0:00 0:00: ,828 4,773,461 0:00 0:00: ,772 4,773,515 0:00 0:00: ,767 4,773,463 0:00 0:00: ,759 4,773,421 0:00 0:00: ,735 4,773,287 0:00 0:00: ,727 4,773,226 0:00 0:00: ,832 4,773,198 0:00 0:00: ,716 4,773,094 0:00 0:00: ,743 4,773,043 0:00 0:00: ,806 4,772,939 0:00 0:00: ,740 4,772,955 0:00 0:00: ,801 4,772,679 0:00 0:00: ,668 4,772,585 0:00 0:00: ,302 4,772,414 0:00 0:00: ,807 4,772,366 0:00 0:00: ,707 4,772,338 0:00 0:00: ,067 4,773,239 0:00 0:00: ,845 4,771,439 0:00 0:00: ,662 4,769,467 0:00 0:00: ,226 4,769,468 0:00 0:00: ,548 4,769,330 0:00 0:00: ,771 4,769,257 0:00 0:00: ,391 4,769,083 0:00 0:00: ,911 4,768,924 0:00 0:00: ,015 4,768,986 0:00 0:00: ,831 4,769,039 0:00 0:00: ,385 4,768,976 0:00 0:00: ,623 4,768,975 0:00 0:00: ,645 4,769,057 0:00 0:00: ,696 4,769,053 0:00 0:00: ,716 4,768,981 0:00 0:00: ,991 4,768,786 0:00 0:00:00

21 Shadow Flicker Analysis Results Summary Receptor ID Worst Case Max shadow (hrs / day) Expected Shadow Flicker (hrs / yr) UTM-E UTM-N ,150 4,768,921 0:00 0:00: ,137 4,768,993 0:00 0:00: ,007 4,768,992 0:00 0:00: ,947 4,768,991 0:00 0:00: ,886 4,768,993 0:00 0:00: ,837 4,768,994 0:00 0:00: ,765 4,769,056 0:00 0:00: ,781 4,768,987 0:00 0:00: ,260 4,769,068 0:00 0:00: ,171 4,769,061 0:00 0:00: ,354 4,769,296 0:00 0:00: ,206 4,769,377 0:00 0:00: ,177 4,769,226 0:00 0:00: ,169 4,774,340 0:00 0:00: ,373 4,773,926 0:00 0:00: ,378 4,773,980 0:00 0:00: ,390 4,774,042 0:00 0:00: ,460 4,774,015 0:00 0:00: ,455 4,773,975 0:00 0:00: ,459 4,773,904 0:00 0:00: ,488 4,774,051 0:00 0:00: ,454 4,774,087 0:00 0:00: ,454 4,774,124 0:00 0:00: ,453 4,774,139 0:00 0:00: ,454 4,774,156 0:00 0:00: ,456 4,774,171 0:00 0:00: ,458 4,774,190 0:00 0:00: ,457 4,774,205 0:00 0:00: ,464 4,774,251 0:00 0:00: ,536 4,774,373 0:00 0:00: ,586 4,774,375 0:00 0:00: ,710 4,774,371 0:00 0:00: ,949 4,776,188 0:00 0:00: ,988 4,769,300 0:00 0:00: ,101 4,769,268 0:00 0:00: ,028 4,769,114 0:00 0:00: ,296 4,769,030 0:00 0:00: ,625 4,769,299 0:00 0:00: ,627 4,769,231 0:00 0:00: ,898 4,768,899 0:00 0:00: ,164 4,769,450 0:00 0:00: ,251 4,771,236 0:00 0:00: ,443 4,773,713 0:00 0:00:00