Resource Documents — latest additions
Documents presented here are not the product of nor are they necessarily endorsed by National Wind Watch. These resource documents are provided to assist anyone wishing to research the issue of industrial wind power and the impacts of its development. The information should be evaluated by each reader to come to their own conclusions about the many areas of debate.
Author: Alves-Pereira, Marian; Bakker, Huub; Rapley, Bruce; and Summers, Rachel
On the Engineers Ireland website, a search for ‘infrasound’ or ‘low-frequency noise’ yields zero results. A search on ‘noise’, however, yields 44 results. Why is it that infrasound and low frequency noise (ILFN) is still such a taboo subject? While it is improbable that this particular question will be answered here, an exposé of ILFN will be provided with a brief historical account of how and why ILFN was ultimately deemed irrelevant for human health concerns.
Infrasound and low-frequency noise (ILFN) are airborne pressure waves that occur at frequencies ≤ 200 Hz. These may, or may not, be felt or heard by human beings. In order to clarify concepts, in this report the following definitions are used:
- Acoustic phenomena: airborne pressure waves that may or may not be perceived by humans;
- Sound: acoustic phenomena that can be captured and perceived by the human ear;
- Noise: sound that is deemed undesirable;
- Vibration: implies a solid-to-solid transmission of energy.
In the early part of the 20th century, Harvey Fletcher of the Western Electrics Laboratories of AT&T, was tasked with improving the quality of reception in the telephone. To generate the sounds in a telephone earpiece, he used an AC voltage and had some of his colleagues rate the loudness of the sound received compared to the quietest tone heard.
The company was already using a logarithmic scale to describe the power in an electrical cable and it made sense to rate the loudness of the sounds also on a logarithmic scale related to the quietest voltage that could just be heard.
Initially he called this metric a ‘sensation unit’ but later, to commemorate their founder Alexander Graham Bell, they renamed it the ‘Bel’. A tenth of a Bel became known as the deciBel, corrupted to decibel, which has stuck with the scientific community to this day.
Fletcher-Munson curves and the dBA metric
To address the problem of industrial noise in the early 20th century, measurement was essential, as was a metric. At that time, researchers were critically aware that the readings on a sound level meter did not represent how loud or intense the sound was with respect to the subject’s perception of hearing.
From a biomedical perspective, this concept of perception is subjective, and changes between individuals and over timescales from minutes to decades. These serious constraints notwithstanding, it was acknowledged that some average measure of loudness would have some value for medicine and public health.
Harvey continued his research with Wilden Munsen, one of his team, by varying the frequency of the electricity to give pure tones, to which it is understood 23 of his colleagues listened to different levels of loudness, again through a simple telephone earpiece. (It is assumed they all had good hearing). They were then asked to score the sounds for equal loudness to that generated by an alternating current at 1000 cycles per second.
The level of the sound of course depended on the voltage applied, which could be measured. It is important to note two significant constraints here: The sounds were ‘pure’ sine waves, which are not common in nature, and the headphones enclosed the ear of the subject. This is a very unnatural way to listen to a very unnatural sound.
The numerical results of this study are known as the Fletcher-Munsen Curves (Fig 1). The (logarithmic) units of these curves are known as ‘phons’ and the inverse of the 40 phon curve forms the basis of the A-frequency weighting scale used everywhere today (Fig 2).
A-Frequency weighting scale
The minimum pressure required for humans to perceive sound at 1000 Hz is considered to be 20 micropascal, or an intensity of 10−12 watts per square meter. This corresponds to 0 phon on Figure 1, and 0 dBA in Figure 2. For all its shortcomings, the A-weighting has endured for decades and has become the de facto standard for environmental noise measurement. But is the A-weighting sufficient for all circumstances?
The answer is an emphatic ‘No’. It relates to the perception of loudness, which heavily discounts all frequencies below 1000 Hz and ends at 20 Hz. This 20-Hz limit was a consequence of equipment limitations of the 1920s and 30s, but has remained as the lower limit of human hearing to this day. The assumption that harm from excessive noise exposure is directly related to the perception of loudness has also remained to this day.
Observe in Fig 2 that, at 10 Hz, there is a 70-dB difference between what is measured and what is, de facto, present in the environment. In other words, three-and-a-half orders of magnitude of energy are discounted at this frequency.
The implications for public health are considerable, and within this line of reasoning, any event below 20 Hz becomes of no consequence whatsoever – and more so because it is not implicated in the classical effects of excessive noise exposure: hearing loss.
There are also issues of time and frequency resolution. Acoustic phenomena are time-varying events. A 10-minute average of acoustic events can hide more than it reveals. Similarly, segmenting frequencies into octave or 1/3-octave bands for analysis can also hide much that needs to be seen.
Today, affordable and highly portable equipment can record acoustical environments, and allow for post-analysis in sub-second time increments and 1/36-octave resolution. Waveform analysis from the sound file directly can achieve an even better resolution.
Field studies in Ireland
The following results, recently obtained in field-studies conducted in Ireland (July-November 2017), show why such resolution is needed to understand ILFN-rich environments. The classical metric (in dBA, 10-min averages and 1/3-octave bands) will be contrasted with what is needed for human health-related concerns (in dB with no frequency weighting, and resolutions of 0.2s and 1/36-octave bands), and not merely compliance with regulations.
Equipment and methods
Acoustical environments were recorded with a SAM Scribe FS recording system, a 2-channel recorder with sampling rates up to 44.1 kHz at 16-bit resolution and linear response down to almost 0.1 Hz [4-6]. Recordings were saved as uncompressed WAV files including the 1000 Hz/94 dB reference calibration tone prior to and after measurements. Windshields were placed on both microphones during the entire measurement sessions. Microphones were attached to tripods at approximately 1.5 m above the ground.
Five homes located around the same industrial wind turbine (IWT) development have been the object of study. The data presented here refers to Home 1 (Fig 3). Table 1 shows the dates and times of all recordings that have been made to date in this home. The recordings selected for analysis and presentation herein were chosen on their educational value.
Table 1: Dates and times of recordings
|Home No.||Date||Time||Blue Channel||Red Channel|
|1||04 Jul||04:05–06:48||In child’s bedroom, 1||In child’s bedroom, 2|
The information classically obtained with the dBA metric, 1/3-octave bands and 10-min averaging (on 10 October, 2017, at 18:30) is given in Figs 4 and 5. Weather conditions obtained from Met Éireann for the closest weather tower at this time were as follows: air temperature: 14°C, precipitation: 0.1 mm, mean sea-level pressure: 1006.0 hPa, wind speed: 5.1 m/s (10 kt), wind direction: southwest (200° az).
The values obtained for the sound pressure level and 1/3-octave bands are seen in Figs 4 and 5. The overall dBA metric (red bars labelled ‘Tot’) reflects the sound that humans would hear if they were present in this environment.
The sound pressure level in dBLin metric (grey bars labelled ‘Tot’) reflect the amount of acoustic energy to which humans are concomitantly exposed. The growing discrepancy between the two can be seen as the frequency falls below 1000 Hz.
Figure 6 shows the sonogram corresponding to the same 10-min period. This visual representation of time- and frequency-varying acoustic events provides much more information than the classical approach (Figs 4 and 5).
Here, short-term events can be seen in the region of 20-50 Hz (Fig 6). Tonal components can be seen at 10 Hz and 20 Hz that are not steady in amplitude and may be amplitude modulated, i.e., where the amplitude of the pressure is not continuous and varies periodically with time. The 10-minute averages, used in almost all legislation, hide these variations and are representative only of tonal components that are essentially unvarying over the 10-minute period in question.
The periodogram (Fig 7) over the same 10 minutes shows that there are distinct tonal components that form a harmonic series. When IWTs are the source of ILFN, the rotating blades generate repeated pressure waves as each blade replaces the previous one at any position.
A harmonic series is formed with the ‘blade pass frequency’ as the fundamental frequency (0.8 Hz here). These harmonics constitute what is called the wind turbine signature , which is impossible to identify using the classical dBA, 1/3-octave, 10-minute averaging methodology.
Health concerns associated with excessive exposure to ILFN in the workplace have been around since the industrial boom in the 1960s . In recent years, however, residential neighbourhoods have also begun to be flooded with ILFN [9-14]. The family living in Home 1, for example, has abandoned their residence due to severe health deterioration in all family members.
Accredited acousticians cannot ascertain compliance levels for ILFN because there are none – the vast majority of regulations worldwide do not cover this part of the acoustic spectrum. Nevertheless, public health officials and agencies should fulfil their job descriptions by becoming aware of the limitations of current noise guidelines and regulations.
Alternatives exist to gather the acoustic information relevant to the protection of human populations, in both occupational and residential settings. Noise regulations and guidelines need urgent updating in order to appropriately reflect ILFN levels that are dangerous to human health.
School of Economic Sciences and Organizations (ECEO), Lusófona University, Lisbon, Portugal
School of Engineering and Advanced Technology, Massey University, Palmerston North, New Zealand
Atkinson & Rapley Consulting, Palmerston North, New Zealand
School of People, Environment and Planning, Massey University, Palmerston North, New Zealand
 Wikicommons (2017). Fletcher-Munson Curves. https://commons.wikimedia.org/wiki/File:Lindos4.svg
 Dirac (2017). Dirac Delta Science & Engineering Encyclopedia, A-Weighting. http://diracdelta.co.uk/wp/noise-and-vibration/a-weighting/
 Atkinson & Rapley Consulting Ltd (2017). Specification sheet for the SAM Scribe FS Mk 1. www.smart-technologies.co.nz
 Primo Co, Ltd. (Tokyo, Japan) (2017). Specification sheet for the electret condenser microphone, custom-made, model EM246ASS’Y. http://www.primo.com.sg/japan-low-freq-micro
 Bakker HHC, Rapley BI, Summers SR, Alves-Pereira M, Dickinson PJ (2017). An affordable recording instrument for the acoustical characterisation of human environments. ICBEN 2017, Zurich, Switzerland, No. 3654, 12 pages.
 Cooper S (2014). The Results of an Acoustic Testing Program Cape Bridgewater Wind Farm. Prepared for Energy Pacific (Vic) Pty Ltd, Melbourne, Australia.
 Alves-Pereira M (1999). Noise-induced extra aural pathology. A review and commentary. Aviation, Space and Environmental Medicine, 70 (3, Suppl.): A7-A21.
 Torres R, Tirado G, Roman A, Ramirez R, Colon H, Araujo A, Pais F, Lopo Tuna JMC, Castelo Branco MSNAA, Alves-Pereira M, Castelo Branco NAA (2001). Vibroacoustic disease induced by long-term exposure to sonic booms. Internoise2001, The Hague, Holland, 2001: 1095-98. (ISBN: 9080655422)
 Araujo A, Alves-Pereira M, Joanaz de Melo J, Castelo Branco NAA (2004). Vibroacoustic disease in a ten-year-old male. Internoise2004. Prague, Czech Republic, 2004; No. 634, 7 pages. (ISBN: 80-01-03055-5)
 Alves-Pereira M, Castelo Branco, NAA (2007). In-home wind turbine noise is conducive to vibroacoustic disease. Second International Meeting on Wind Turbine Noise, Lyon, France, Sep 20-21, Paper No. 3, 11 pages.
 Castelo Branco NAA, Costa e Curto T, Mendes Jorge L, Cavaco Faísca J, Amaral Dias L, Oliveira P, Martins dos Santos J, Alves-Pereira M (2010). Family with wind turbines in close proximity to home: follow-up of the case presented in 2007. 14th International Meeting on Low Frequency Noise, Vibration and Its Control. Aalborg, Denmark, 9-11 June, 2010, 31-40.
 Lian J, Wang X, Zhang W, Ma B, Liu D (2017). Multi-source generation mechanisms for low frequency noise induced by flood discharge and energy dissipation from a high dam with a ski-jump type spillway. International Journal of Environmental Research and Public Health, 14 (12): 1482.
 Rapley BI, Bakker HHC, Alves-Pereira M, Summers SR (2017). Case Report: Cross-sensitisation to infrasound and low frequency noise. ICBEN 2017, Zurich, Switzerland (Paper No. 3872).
Author: Cooper, Steven; and Chan, Chris
The conduct of stereo measurements for both playback in high-quality headphones and in a hemi-anechoic room has been undertaken for a number of wind farms and other low-frequency noise sources as an expansion of the material previously presented at the Boston ASA meeting. The results of the additional monitoring, evaluation, and subjective analysis of this procedure are discussed and identifies the benefits of monitoring noise complaints and assessments of wind farm noise in stereo. The laboratory mono subjective system was used to reproduce the audio wave file obtained in a dwelling. The test signal, being inaudible, was presented as a pilot double blind provocation case control study to 9 test subjects who have been identified as being sensitized to wind turbine noise and low frequency pulsating industrial noise. All test subject could detect the operation of the inaudible test signal. The use of a stereo manikin to investigate detected inaudible ”hotspots” is discussed.
Steven Edwin Cooper, Chris Chan
The Acoustic Group, Lilyfield, New South Wale, Australia
174th Meeting of the Acoustical Society of America
New Orleans, Louisiana, 4–8 December 2017
Download original document: “Subjective perception of wind turbine noise – The stereo approach”
Subjective perception of wind turbine noise
The evaluation of wind turbine noise impacting upon communities is generally related to external noise environments and has a problem with separating wind turbine noise from ambient noise (which includes the presence of wind) which is not normally the case for general environmental noise. Subjective testing of wind turbine noise to examine amplitude modulation and subjective loudness has tended to use large baffle speaker systems to produce the infrasound/low-frequency noise and one high-frequency speaker – all as a mono source. Comparison of mono and stereo recordings of audible wind turbine noise played back in a test chamber and a smaller hemi-anechoic space provides a distinct different perception of amplitude modulation of turbines. A similar exercise compares use of high-quality full-spectrum headphones with the two different sound files applied to just the ears is discussed.
Steven Edwin Cooper
The Acoustic Group, Lilyfield, New South Wale, Australia
173rd Meeting of the Acoustical Society of America
Boston, Massachusetts, 25–29 June 2017
Download original document: “Subjective perception of wind turbine noise”
Author: Plummer, James; Frank, Charles; and Michaels, Robert
We compare three technologies that produce electricity in the United States: wind, solar, and combined-cycle gas turbines (CCGT). We use the 2016 electric utility database compiled by the U.S. Energy Information Administration (EIA). That database has the advantage of being based on a census of U.S. power plants rather than sampling, as well as excluding any subsidies received by the power plants.
We show the cost savings achieved when there is a shift between coal-fired generation and generation by wind, solar, or CCGTs, where costs include both capital and operating costs. The net cost reduction per tonne of CO₂ reduction is $4,340 for a shift from coal to wind, −$98,826 (a cost increase rather than a cost decrease) for a shift from coal to solar, and a $251,920 decrease for a shift from coal to CCGT.
When the net emissions from switching away from coal are considered, the net cost savings for each tonne of emissions avoided is $1.27 for a switch from coal to wind, −$44.11 (a net cost increase) for a switch from coal to solar, and a savings of $50.72 for a switch from coal to CCGT. The differentials between the savings from a switch to wind or solar and a switch to CCGT is a measure of the “dead weight economic loss involved in switching from coal to either form of “renewables” instead of switching from coal to CCGT.
This research concludes that CCGT is the only “economic” choice from the perspective of benefit-cost analysis.
- Following Joskow, we do separate analyses for peak and off-peak generation.
- This study borrows heavily from a 2014 Brookings Working Paper by Charles R. Frank, “The Net Benefits of Low and No-Carbon Electricity Technologies.” However, we use updated 2016 data.
- The basic data for this study is the annual census of electricity generation conducted by the EIA of the U.S. Department of Energy.
- One advantage of using the EIA data is that it measures the costs of electricity production on a “real resource cost basis.” That is, the data do not incorporate the large U.S. government subsidies paid to the owner/operators of U.S. wind and solar electricity plants.
- The federal subsidy to solar energy is 30% of capital cost. The federal “production tax credit” (PTC) for wind was $.023 per kWh in 2016, but has complex annual yearly inflation adjustments.
OTHER BASIC ASSUMPTIONS
- A new low-carbon (wind, solar, or CCGT) plant replaces a coal plant off-peak and a simple cycle gas turbine on-peak.
- The price of natural gas is the average price paid by electric utilities.
- The cost of capital is 7.5%.
- The emissions from a new CCGT plant are grossed up to account for fugitive from the production and transport of natural gas.
- We include “balancing and cycling costs.” These are the extra cost that electric utilities incur to accommodate the intermittent nature of wind and solar.
THE CONCEPT OF “DECARBONIZATION EFFICIENCY”
Decarbonization cost is the differential cost of producing a MW year of electricity via coal plants and three other technologies – wind, solar, and CCGTs – divided by the differential CO₂ emissions (measured in tonnes per year).
Total net cost savings in 2016 of switching from coal to …
- Wind: $4,340 per MW-year
- Solar: $98,826 per MW-year
- CCGT: $237,684 per MW-year
Tonnes of CO₂ emissions per MW-year avoided by switching from coal to …
- Wind: 3,418
- Solar: 2,241
- CCGT: 4,686
Net cost savings per tonne of emissions avoided
- Wind: $1.27
- Solar: −$44.11
- CCGT: $50.72
DEAD WEIGHT ECONOMIC LOSS …
Of a decision to switch from coal to wind instead of to CCGT:
- $49.45 per tonne of emissions avoided
Of a decision to switch from coal to solar instead of to CCGT:
- $94.83 per tonne of emissions avoided
Conclusion: Switching to either wind or solar instead of to CCGT involves a dead weight economic loss. However, the dead weight economic loss is twice as great for a switch to solar instead of a switch to wind.
A SCENARIO OF DECARBONIZATION
In recent years, U.S. CO₂ emissions have been about 5.8 billion tonnes per year.
Suppose a goal of reducing those emissions by 10% or about 580 million tonnes.
As shown before, substitution of wind for coal results in a cost savings of $1.27 per tonne of CO₂ reduction, or $0.74 billion in this decarbonization scenario.
As shown before, substitution of solar for coal results in extra costs of $44.11 per tonne of CO₂ reduction, or $25.58 billion if all the investment was in solar.
However, if all the investment were done in CCGT, then the total cost savings would be $29.42 billion. So, the cost savings are larger when all the investment is in CCGT. The differences in cost savings are the amount of “dead weight economic loss” from investing in wind or solar instead of CCGTs.
These equations could be turned around to calculate, for a given fixed outlay of costs, what would be the “foregone CO₂ emissions opportunity” from investing in wind or solar instead of CCGT.
OTHER ALLEGED “SIDE BENEFITS OR COSTS” OF RENEWABLES
Job creation. Many of the jobs created by renewables are at the installation or capital goods production stages. The inherent capital intensivity of renewables limit their job creation potential.
Infant industry learning. This was a label invented by Argentine economist Raul Prebisch to argue for tariff protection of industry in less developed countries. However, those tariffs often led to “soft industries” that became dependent on the tariffs and did not focus on increased efficiency. A higher gain results from investing in specialized R&D activity.
Siting issues. Renewables progress over time from more favorable wind and solar sites to sites that involve higher cost per kWh produced, a classic example of “diminishing economic returns.” CCGTs are smaller physical plants, which can be sited close to natural gas supply or end-use electricity customers.
BROADER ISSUES OF RENEWABLES VS. CCGTs
Should CCGT be eligible to receive federal tax credits analogous to the current federal tax subsidies to wind and solar? No. This would be doubling down on a bad federal policy. CCGT does not need subsidies. They can out compete wind and solar on their own.
The states mainly follow a policy of “renewables mandates” placed on regulated utilities. The utilities don’t resist these mandates very hard because the system of a fixed return on “utility rate base” largely eliminates the incentives to lower costs via investment in CCGTs. This pattern is a classic example of political “confusion of ends and means.” If the goal of electricity policy at the state level is reducing CO₂ emissions, then the state should not intervene to put CCGTs at a disadvantage.
James L. Plummer, President, Climate Economics Foundation
Charles R. Frank, Senior Non-resident Fellow, Brookings Institution
Robert R. Michaels, California State University Fullerton
[presented at the 35th United States Association for Energy Economics/International Association for Energy Economics Conference, November 12–15, 2017, Houston]
Author: Hutchins, Michael
Wind energy is known to many as a “green” solution to climate change. But wind energy is really just another form of industrial development, and we can’t ignore its costs and consequences to wildlife and their habitats. As Director of ABC’s Bird-Smart Wind Energy Campaign, I often encounter several common misconceptions about wind development. Read on to learn more about the real impact of unchecked wind energy development on birds and other wildlife.
Myth 1: Wind turbines are “green” energy with little or no impact on the environment.
Any form of energy production, including renewable energy, has environmental impacts. The construction of large-scale, commercial wind energy facilities takes up entire landscapes, which reduces wildlife habitat. And the maintenance roads and other support infrastructure necessary also alter habitats and affect wildlife, often in very deleterious, subtle ways. If not properly sited, operated, and regulated, renewable energy can be very harmful to wildlife and natural habitats.
Myth 2: We shouldn’t be concerned about wind energy because it doesn’t take nearly the same toll on birds as feral cats, building collisions, pesticides, and other threats.
There are two things to remember here. First, wind turbines’ impacts are far from trivial. And the impacts of all human-caused mortality are cumulative, making comparisons irrelevant and misleading.
Wind turbines and their associated infrastructure – primarily power lines and towers – are one of the fastest-growing threats to birds in the United States and Canada. At the end of 2016, there were more than 52,000 commercial-scale wind turbines operating in the United States, and tens of thousands more are currently planned or under construction. Research shows that hundreds of thousands of birds and bats die every year when they accidentally collide with the fast-spinning turbine blades. That number grows with each turbine built.
Myth 3: Power lines and towers are a separate issue.
Power lines and towers are clearly part of the equation, because they’re necessary to carry power to the grid. As a result of large-scale, commercial wind and solar development, hundreds of miles of new power lines and towers are being built to transport energy across the United States, putting birds at risk of collisions and electrocutions. The generation of energy and its transportation go hand in hand – and both present risks to wildlife. Tens of millions of birds are killed every year when they collide with towers with or are electrocuted by electrical lines.
Myth 4: The wind industry is mitigating for bird and bat deaths.
As far as birds are concerned, only two mitigation methods have been proven to be successful: building wind energy facilities away from large concentrations of birds, and slowing or stopping the movement of turbine blades (known in the industry as “curtailment”). Unfortunately, neither of these approaches is working. Turbines are going up virtually everywhere, and curtailment is unpopular with wind companies because it cuts into their profit margins.
Some companies say they use radar to detect birds and bats and then temporarily shut down a turbine’s blades. But these technologies are expensive and appear to be seldom used – and their efficacy in preventing bird and bat deaths has not been thoroughly tested.
Northern Long-eared Bat/U.S. Fish and Wildlife Service
One way to make wind turbines safe for birds and bats, such as this Northern Long-eared Bat, is to build them far from large concentrations of these animals. Photo by U.S. Fish and Wildlife Service
Myth 5: The U.S. Fish & Wildlife Service (FWS) and state wildlife agencies are regulating the wind industry to minimize its impacts on wildlife.
We have at least three federal laws designed to protect our native birds and bats from purposeful or accidental harm: the Endangered Species Act, the Migratory Bird Treaty Act, and the Bald and Golden Eagle Protection Act. Enforcement of these laws has been sporadic at best, especially with regard to the wind industry. To make matters worse, federal guidelines governing wind energy development are voluntary, not mandatory, and few developers at present are obtaining the “take” permits necessary to kill protected species.
Meanwhile, state and local regulation of the wind industry varies widely. Some states, such as Oklahoma, have virtually no regulations at all. Others, like Hawai‘i, have more-stringent policies. Wind energy has developed so rapidly that it has gotten way out ahead of the regulatory framework.
Myth 6: Wind companies conduct scientifically rigorous studies before and after new facilities are built to assess the risks wind turbines pose to birds – and are transparent in what they find.
Federal guidelines currently allow wind companies to hire consultants to prepare reports assessing a proposed facility’s risk for wildlife. It’s important to note that these are not independent, third-party scientists; they are individuals who are being paid by wind companies to do this work. Unsurprisingly, I have yet to encounter any pre-construction study that recommends moving a proposed project because of elevated risks to wildlife.
There is also the problem of hidden data. The wind industry treats information on bird and bat mortality as a proprietary trade secret. Some wind energy developers have even sued to hide these data from the public. Hawai‘i is currently the only state that requires the collection of mortality data by independent, third-party experts, and makes the information available to the public on request.
Myth 7: Offshore wind development is less destructive than onshore wind development.
There’s no indication that turbines placed in the open ocean or in the Great Lakes are any safer for birds than land-based turbines. A whole suite of different organisms could be impacted by offshore wind development and underwater cables, including migrating marine birds, waterfowl, cetaceans, fish, and other ocean-dwelling wildlife. And it’s going to be more difficult to gauge the impact: risk assessments are often based on visual observations, which can be difficult, if not impossible, during rough weather, when birds may be at highest risk. What’s more, birds that collide with the turbine blades will fall into open water and be lost.
Myth 8: We can build wind turbines in and around the Great Lakes with little or no impact on wildlife.
The best way to reduce the impacts of wind energy on birds and bats is to keep turbines away from large concentrations of these animals. Major migratory routes, stopover habitat, and key breeding or foraging areas should all be off-limits for wind development. Yet all of these are found in and around the Great Lakes, which is home to one of the world’s densest concentrations of migratory birds and bats.
Here at ABC, we oppose wind turbine construction in the Great Lakes and within at least five miles of its shorelines. We base our position on recent advanced radar studies conducted by the FWS on all five of the Great Lakes. All of the studies clearly show vast numbers of birds and bats flying over the lakes or along their shorelines, many within the rotor-swept areas of wind turbines. The FWS currently recommends that no turbines be built within three miles of the Great Lakes shorelines, while the Nature Conservancy recommends five miles. However, these are just recommendations, and some wind developers are disregarding them.
Myth 9: When it comes to combating climate change, there are no workable alternatives to industrial-scale wind energy.
There are many other ways we can address climate change besides building these huge structures in ecologically sensitive areas. We can preserve wetlands and forests to sequester carbon dioxide; we can be more energy-efficient; and we can reduce our use of fossil fuels and rely less on domestic animals (a major source of greenhouse gases) as a protein source, for starters. One of the best options is distributed solar in our already built environment – parking lots, buildings, and roads.
Myth 10: Climate change is the top threat to wildlife today; we can ignore all other threats because they pale in comparison.
Birds and other wildlife confront many threats, and they add up. One recent analysis of 8,000 species on the International Union for Conservation of Nature Red List of Threatened Species found that climate change is not the most immediate threat to wildlife today; that distinction went to the traditional threats of over-exploitation (overfishing, hunting, and so on) and habitat loss from agriculture. The authors concluded that “efforts to address climate change do not overshadow more immediate priorities for the survival of the world’s flora and fauna.”
We support wind energy development that’s done in ways that do not threaten our irreplaceable and ecologically important wildlife. To make that happen, wind energy development must be regulated more effectively. We must address climate change, to be sure – but the point is that we could be doing it so much better.
Michael Hutchins, Director of American Bird Conservancy’s Bird-Smart Wind Energy Campaign, earned his Ph.D. in animal behavior at the University of Washington. Prior to ABC, Michael was Director/William Conway Endowed Chair, Department of Conservation and Science, at the Association of Zoos and Aquariums for 15 years, and Executive Director/CEO at The Wildlife Society for seven years. He has authored over 220 articles and books on various topics in wildlife science, management, and conservation, and has traveled to over 30 countries to pursue his passion for conservation.
Originally published December 06, 2017, at abcbirds.org.