Resource Library Category: Massachusetts (24 items)

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Documents presented here are not the product of nor are they necessarily endorsed by National Wind Watch. This resource library is 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.

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Wind Turbine Health Impact Study Is Junk Science

Source:  Hartman, Raymond

[Wind Turbine Health Impact Study: Report of Independent Expert Panel, January 2012, prepared for: Massachusetts Department of Environmental Protection, Massachusetts Department of Public Health]

Junk Science: What Is It?

“Junk science is faulty scientific data and analysis used to advance special interests and hidden agendas.”

General Examples

“Government regulators may use junk science to expand their regulatory authority, increase their budgets or advance the political agenda of elected officials.”

“Businesses may use junk science to bad-mouth competitors’ products, make bogus claims about their own products, or to promote political or social change that would increase sales and profits.”

“Politicians may use junk science to curry favor with special interest groups, to be politically correct or to advance their own personal political beliefs.”

Specific Real-World Examples

The Tobacco Research Institute

• It was funded by the big tobacco companies.
• It produced “scientific research” for 50 years or more “demonstrating” that smoking was good, or at least not bad, for people.
• Over time, as doctors and patients complained that smoking caused lung cancers and cardiovascular diseases, the Tobacco Research Institute produced more “scientific research” demonstrating that something else caused the disease.

→ The “research” was Junk Science.
→ It was untrue, manipulated and unreliable.
→ The “research” caused disease and death.

Asbestos Manufacturers

• Asbestos was used for decades in shipbuilding, construction and a variety of other trades.
• Those workers installing and working with asbestos were told for decades that research demonstrated that the workers were safe.
• Workers were not safe.
• Asbestos caused innumerable cases of cancer – mesothelioma.
• The asbestos manufacturers put forward research “demonstrating” that the cancers were not caused by the asbestos.

→ The “research” was Junk Science.
→ It was untrue, manipulated and unreliable.

Manufacturers of DDT

• DDT was first used as a pesticide in the 1940s.
• It was claimed to be a successful and safe pesticide.
• The US government began banning DDT for particular uses in the 1960s.
• It was banned outright in 1972.

→ The original “research” was Junk Science.
→ It ignored the health and environmental risks of DDT.

The Wind Turbine Health Impact Study Is Junk Science

Deval Patrick sponsored and defends the study which “found no scientific evidence or medical studies to prove that living near a wind turbine has adverse impacts on people’s health, though it acknowledged further study is needed to look at health impacts stemming from ‘annoyance’ for residents who live near turbines.” [State Capitol Briefs, Afternoon Edition, Thursday, January 19, 2012, State House News Service]

The conclusions reached by the study are utterly and profoundly dishonest.

The study is labeled a “Report of Independent Expert Panel.”

• The panel was not independent.
• Several “experts” have pro-wind industry connections. [For one important example, I understand that Dr. James Manwell’s Wind Energy Center is heavily funded by the Commonwealth. I believe that it is therefore impossible for him to offer a neutral opinion on the health effects of industrial wind turbine installations, given the Commonwealth’s obvious infatuation with wind energy.]
• The Panel is no more qualified or expert than the substantial number of opponents, including Dr. Pierpont and myself.
  [NWW: Perhaps much less so — see this Jan. 28 letter running down the members of the panel.]

The Panel relies primarily on an inexplicably small number (4) of published research papers, out of 100s that are available.

• Two Swedish research papers, one Dutch research paper and one New Zealand Research paper.
• The Panel dismisses for unsupported reasons all the other studies.
• In statistical modeling, this is called “cherry picking” – choosing only those studies that support a desired conclusion.

The sizes of the wind turbines studied are quite small.

• The turbines studied were only 164-213 feet tall.
• These are much smaller than those proposed for Mount Massaemet which are nearly 500 feet tall.
• Noise effects increase with the size of the turbine blades.

The data, models and statistical analyses in these papers are flawed, in ways explicitly noted by the Panel.

• The Panel notes: “The peer-reviewed papers have weaknesses, including the cross sectional designs and sometimes quite low response rates (p. 28).”
• The Panel further notes: “The model from which this conclusion was drawn, however, imposed a linear relation on the association between noise level category and annoyance. But … it appeared that the relation might not be linear (p. 18).”
• In statistical modeling, the imposition of a linear relationship when it is invalid is called specification bias.

→ When present, the model and analysis are wrong.
→ The studies introduce a multiplicity of other possible factors, all of which interfere with properly analyzing and estimating the impact of the primary factor upon health – turbine noise.

The Panel mentions but ignores the findings of the most recent analysis by the authors of two of their chosen studies (the Swedish studies). This most recent study contradicts the Panel’s conclusions as follows [as noted explicitly by the Panel at page 19]:

• “A more intricate statistical model of the association between turbine noise levels and annoyance that used the data from both Swedish studies … suggested a significant association between noise levels and annoyance even after considering other factors.”
• Why didn’t the Panel consider this third study by the same authors, which used better analytic and statistical methods?

→ This exclusion is unprofessional, unscientific and outright dishonest.
→ This is Junk Science.

The Panel identifies the preferred type of study – time-series analyses, looking at families and households before and after the industrial turbines are put into operation → “A Before-and-After Study.”

• The Panel notes “Cross-sectional studies [which the Panel uses] lack the ability to determine the temporality of cause and effect; in the case of these kinds of studies, we cannot know whether the annoyance level was present before the wind turbines were operational from a cross sectional study design.”
• Why didn’t the Panel look at time-series experiences that have occurred in New England – Maine, Vermont, and Massachusetts? [I understand that the ISO-NE seasonal-claimed capability spreadsheet identifies the following industrial wind turbine (IWT) sites which could have been used for “Before-and-After” studies: 19 IWT projects in Massachusetts; 9 IWT projects in Maine, including Mars Hill which is outside the ISO-NE area and so is not listed on the ISO's spreadsheet; 3 IWT projects in Rhode Island; 2 IWT projects in New Hampshire; and 2 IWT projects in Vermont.]
• This is the most natural set of experiments to be done and is easily available.
• Is the reason because they knew what such experiments would find – that Industrial Wind Turbines cause sleep problems and severe annoyance, leading to health problems?

The Panel does admit to finding the following:

• “Wind turbines can produce unwanted sound (referred to as noise) during operation (p. ES-4)”
• “The whooshing that is heard is NOT infrasound … [It] is at higher frequency … It is important to note then that when a complaint is tied to the thumping or whooshing that is being heard, the complaint may not be about ILFN at all even if the complaint mentions low frequency noise. Kamperman et al. (2008) state that, ‘It is not clear to us whether the complaints about ‘low frequency’ noise are about the audible low frequency part of the ‘swoosh-boom’ sound, the once-per-second amplitude modulation … of the ‘swoosh-boom’ sound, or some combination of the two (p. 13).” [Emphasis added. These are precisely the sounds described by Neil Anderson from Falmouth.]
• “Most epidemiologic literature on human response to wind turbines relates to self-reported ‘annoyance’ … (p. ES-5).”
• “A very loud wind turbine could cause disrupted sleep, particularly in vulnerable populations, at a certain distance, while a very quiet wind turbine would not likely disrupt even the lightest of sleepers at that same distance (p. ES-6).”

The Panel however concludes that there is insufficient evidence that industrial wind turbines will have any effects upon residents near the installation. It states:

• “There is limited evidence from epidemiologic studies suggesting an association between noise from wind turbines and sleep disruption. In other words, it is possible that noise from some wind turbines can cause sleep disruption. … But there is not enough evidence to provide particular sound-pressure thresholds at which wind turbines cause sleep disruption (p. ES-5 and ES-6).”
• “Whether annoyance from wind turbines leads to sleep issues or stress has not been sufficiently quantified. While not based on evidence of wind turbines, there is evidence that sleep disruption can adversely affect mood, cognitive functioning, and overall sense of health and well-being (p. ES-6).”
• “There is insufficient evidence that the noise from wind turbines is directly (i.e., independent from an effect on annoyance or sleep) causing health problems or disease (p. ES-6).”

Reflect closely on this language.

• Noise causes annoyance and disrupts sleep.
• Annoyance and sleep disruption causes stress and disease states.
• While the evidence demonstrates that industrial wind turbines cause annoyance and disrupt sleep, the Panel finds it is insufficient or an indirect cause.
• Do you believe that assertion?

The Panel’s report and conclusions are JUNK SCIENCE.

What does this mean for Shelburne?

• There will be wind turbine noise.
• Prepare yourself for the “‘swoosh-boom’ sound, the once-per-second amplitude modulation … of the ‘swoosh-boom’ sound, or some combination of the two.” [See the Impact Study, p. 13, cited above.]
• This noise will disrupt the sleep of an unknown number of Shelburne and Buckland residents.
• This noise will cause low-to-severe cases of “annoyance,” every day, every hour, every minute for an unknown number of residents.
• The non-stop annoyance and sleep disruption will cause stress and disease states for an unknown number of residents.
• This noise will affect many Shelburne residents in precisely the same fashion as has been found in Falmouth, Vinalhaven and across New England.
• Are you ready to be guinea pigs for an experiment in which we suffer the possible consequences while outside developers make hundreds of millions of dollars in subsidies, and then leave town?

Raymond S. Hartman is a Shelburne resident, living in the Patten District: ‘I have a BA from Princeton University and a Masters and PhD from MIT. All of my degrees are in mathematical economics. I have been a member (Associate Professor) of the faculties of MIT, Boston University, and University of California, Berkeley. I have published more than 100 peer-reviewed articles and contract research using statistical and mathematical models, methods, and data. I am currently President and Director of Greylock McKinnon Associates, an economic consulting firm specializing in analysis in support of litigation. Indeed, I regularly have testified as an expert witness on behalf of the Massachusetts Attorney General’s office in a variety of matters, including the 1995-1996 tobacco litigation (the result of which the Commonwealth received billions of dollars in settlement from “Big Tobacco”); litigation against large drug companies for defrauding the Massachusetts Medicaid program (2008-2011); the restructuring of the electric power industry (1990s); and a variety of utility rate cases (2000s). Over the past 40 years, I have reviewed and responded to hundreds of “Expert Reports” like “The Wind Turbine Health Impact Study.”’

Download original document: “The Wind Turbine Health Impact Study Is Junk Science”

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Nina Pierpont interviews Falmouth, Mass., wind turbine syndrome victims — September 2011

Source:  Pierpont, Nina

Mark Cool: his health has been affected since a 1.65-megawatt Vestas wind turbine was activated near his home. He said it took months of headaches and other cognitive changes before he began to realize it wasn’t just him; other neighbors nearby curiously had developed odd symptoms at the same time. Dr. Pierpont asks pointed questions about his health and how his his life has changed post turbine in search of answers about the new environmental malady wind turbine syndrome.

Neil Andersen has been having a strange ailment plague him ever since a Vestas 1.65-megawatt turbine went up in his neighborhood July 2010. The interview takes place in September 2011. Neil feels the turbine is destroying his life. Dr. Pierpont inquires about his symptoms and his ability to carry on a normal life now.

Betsy Andersen has had strange symptoms plaguing her ever since a 1.65 MW Vestas wind turbine was put online near her home. Dr. Pierpont wants to find out if Betsy may be suffering from wind turbine syndrome.

Ed Hobart: his health and life have changed after a 1.65-megawatt Vestas wind turbine was installed behind his house a year ago. Mr. Hobart believes the turbine’s activity is plaguing his house with an inexplicable thump and causing a variety of health symptoms that make him feel like he has developed a disease.

Download these videos: I (Mark Cool), II (Neil Andersen), III (Betsy Andersen), IV (Ed Hobart)

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Adverse health effects of industrial wind turbines: a preliminary report

Source:  Nissenbaum, Michael; Aramini, Jeff; and Hanning, Chris

INTRODUCTION

Guidelines and regulations for the siting of industrial wind turbines (IWT) close to human habitation are generally predicated on the need to protect the sleep of the residents. The recommended setback distances and “safe” external noise levels make the assumptions that IWT noise can be regarded as similar to other forms of environmental noise (traffic, rail and aircraft) and is masked by ambient noise. There has been no in dependent verification that these assumptions are justified and that the safeguards are sufficient to protect sleep.

Anecdotal complaints of annoyance and health effects from IWT noise have grown in number in recent years, not least because turbine size has increased and they have been placed closer to population centers. The predominant symptom of health complaints is sleep disturbance (Frey & Hadden 2007; Pierpont 2009; van den Berg et al. 2008; WindVOICe 2010). The consequences of sleep disturbance and the contribution of environmental noise are well documented (WHO 2009).

Complaints of adverse health effects were made shortly after IWT installations at Mars Hill and Vinalhaven, Maine, USA, began operating. A preliminary survey at Mars Hill, comparing those living within 1,400 m with a control group living 3,000-6,000 m away showed that sleep disturbance was the main health effect (Nissenbaum 2011, submitted for publication). A further study was therefore carried out at both Mars Hill and Vinalhaven using validated questionnaires and comparing those living within 1.5 km of the turbines with a control group living 3,500-6,000 m away.

METHODS

General study design

A questionnaire was offered to all residents meeting inclusion criteria living within 1.5 km of an IWT and to a random sample of residents meeting inclusion criteria living 3 to 7 km from an IWT between March and July of 2010. The protocol was reviewed and approved by IRB Services, Aurora, Ontario, Canada.

Questionnaire

The questionnaire comprised validated instruments relating to mental and physical health (SF-36v2) (QualityMetric Inc.), sleep disturbance (Pittsburgh Sleep Quality Index (PSQI) (Buysse et al. 1989) and the Epworth Sleepiness Scale (ESS) (Johns 1991), in addition to headache functional inquiry questions and a series of attitudinal questions relating specifically to changes with exposure to IWT noise. Only the results from the validated instruments are presented here.

Participant selection

The Mars Hill site is a linear arrangement of 28 General Electric 1.5 megawatt turbines, sited on a ridgeline. The Vinalhaven site is a cluster of three similar turbines, sited on a flat tree covered island. All residents living within 1.5 km of an IWT at each site were identified via tax maps, and approached either door to door or via telephone and asked to participate in the study. Homes were visited up to three times or until contact was made. Those below the age of 18 or with a diagnosed cognitive disorder were excluded. A random sample of households in a similar socioeconomic area 3 to 7 km away from IWTs at each site was chosen to participate in the study as a control group. Households were approached door-to-door until a similar number of participants were enrolled.

Data handling and validation

Questionnaire results were coded and entered into a spreadsheet (Microsoft Excel 2007). The distance from each participant’s residence to the nearest IWT was measured using satellite maps. SF36-V2 responses were processed using QualityMetric Health OutcomesTM Scoring Software 3.0 to generate Mental (MCS) and Physical (PCS) Component Scores. Missing values were verified and outliers were individually assessed. Data quality of the SF36-V2 responses was determined using QualityMetric Health OutcomesTM Scoring Software 3.0. All SF36-V2 data quality indicators (completeness, response range, consistency, estimable scale scores, internal consistency, discriminant validity, and reliable scales) exceeded parameter norms.

Statistical analysis

All analyses were performed using SAS 9.22. Descriptive and multivariate analyses were performed to investigate the effect of the main independent variable of interest (distance to nearest IWT) on the various outcome measures.

Significance of binomial outcomes was assessed using either the GENMOD procedure with binomial distribution and logit link; or when cell frequencies were small (<5), Fisher’s Exact Test. When assessing significance between variables with a simple score as the outcome (eg. 1-5), the exact Wilcoxson Score (Rank Sums) test was employed using the NPAR1WAY procedure. Significance of continuous outcome variables was assessed using the GENMOD procedure with normal distribution. When using the GENMOD procedure, age, gender and site were forced into the model as fixed effects. The potential effect of household clustering on statistical significance was accommodated by using the REPEATED statement.

Independent variables assessed included the following: Site (Mars Hill, Vinalhaven); Distance to IWT (both as a categorical and continuous variable); Age (continuous variable); Gender (categorical variable). Significance of Site as an effect modifier was assessed by fitting an interaction term (Site*distance).

Dependent variables assessed include the following: Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), SF36-v2 Mental Component Score (MCS), SF36-v2 Physical Component Score (PCS).

For the purpose of interpreting statistical significance, the following were used: P-value < 0.05 = Significant; P-value 0.1 – 0.05 = Moderately significant; P-value > 0.1 = Not significant

Effect of Site on outcome parameters

The effect of Site was assessed by fitting Site (Mars Hill vs Vinalhaven) as a fixed effect, and as an interaction term with the main independent variable of interest (distance). Among all outcomes investigated, Site, and Site*Distance were not significant.

RESULTS

Study participants

33 and 32 adults were identified as living within 1,500 m of the nearest IWT at the Mars Hill (mean. 805 m, range 390-1,400) and Vinalhaven sites (mean 771 m range 375-1,000) respectively. 23 and 15 adults at the Mars Hill and Vinalhaven sites respectively completed questionnaires. Recruitment of control group participants continued to approximately the same number as study group participants, 25 and 16 for Mars Hill and Vinalhaven respectively.

There were no significant differences between the groups with respect to household size, age, or gender (Table 1).

Sleep quality and health

The study group had worse sleep as evidenced by significantly higher mean PSQI and ESS scores and a greater number with PSQI >5 (Table 2). More subjects in the study group had ESS scores >10 but the difference did not reach statistical significance (p=0.1313).

The study group had worse mental health as evidenced by significantly higher mean mental component score of the SF36. There was no difference in the physical component scores.

ESS, PSQI and SF36 scores were modeled against distance from the nearest IWT using the equation: Score = ln(distance) + gender + age + site [controlled for household clustering] and are shown in Figures 1-3. In all cases, there was a clear and significant relationship with the effect diminishing with increasing distance from the IWT.

DISCUSSION

This study, which is the first controlled study of the effects of IWT noise on sleep and health, shows that those living within 1.4 km of IWT have suffered sleep disruption which is sufficiently severe as to affect their daytime functioning and mental health. Both the ESS and PSQI are averaged measures, i.e. they ask the subject to assess their daytime sleepiness and sleep quality respectively, over a period of several weeks leading up to the present. For the ESS to increase, sleep must have been shortened or fragmented to a sufficient degree on sufficient nights for normal compensatory mechanisms to have been overcome. The effects of sleep loss and daytime sleepiness on cognitive function, accident rate and mental health are well established (WHO 2009) and it must be concluded that at least some of the residents living near the Vinalhaven and Mars Hill IWT installations have suffered serious harm to their sleep and health.

The significant relationship between the symptoms and distance from the IWTs, the subjects’ report that their symptoms followed the start of IWT operations, the congruence of the symptoms reported here with previous research and reports and the clear mechanism is strong evidence that IWT noise is the cause of the observed effects.

IWT noise has an impulsive character and is several times more annoying than other sources of noise for the same sound pressure level (Pedersen & Persson Waye 2004). It can prevent the onset of sleep and the return to sleep after a spontaneous or induced awakening. Road, rail and aircraft noise causes arousals, brief lightening of sleep which are not recalled. While not proven, it is highly likely that IWT noise will cause arousals which may prove to be the major mechanism for sleep disruption. It is possible that the low frequency and infrasound components of IWT noise might contribute to the sleep disruption and health effects by other mechanisms but this remains to be determined and further research is needed.

Attitudes to IWT and visual impact have been shown to be factors in annoyance to IWT noise (Pedersen et al. 2009) but have not been demonstrated for sleep disturbance. Most respondents in the present study welcomed the IWT installations as offering economic benefits. The visual impact of IWT decreases with distance, as does the noise impact making separation of these factors impossible.

We conclude that IWT noise at these two sites disrupts the sleep and adversely affects the health of those living nearby. The current ordinances determining setback are inadequate to protect the residents and setbacks of less than 1.5 km must be regarded as unsafe. Further research is needed to determine a safe setback distance and to investigate the mechanisms of causation.

• Michael Nissenbaum MD, Northern Maine Medical Center, Fort Kent, Maine, USA, mnissenbaum/att.net
• Jeff Aramini PhD, Intelligent Health Solutions Inc., Fergus, Ontario, Canada, jeff.aramini/gmail.com
• Chris Hanning MD, University Hospitals of Leicester, Leicester, UK, chrisdhanning/tiscali.co.uk

10th International Congress on Noise as a Public Health Problem (ICBEN) 2011, London, UK

REFERENCES

Buysse DJ, Reynolds CF, Monk TH et al. (1989). The Pittsburgh Sleep Quality Index (PSQI): A new instrument for psychiatric research and practice. Psychiatry Res 28: 193-213.

Frey BJ, Hadden PJ (2007). Noise radiation from wind turbines installed near homes: effects on health. www.windnoisehealthhumanrights.com

Johns MW (1991). A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 14: 540–545. Nissenbaum M. (2011). Health effects of industrial wind turbines – a preliminary study. Submitted for publication.

Pedersen E, Persson Waye K (2004). Perception and annoyance due to wind turbine noise—a dose-response relationship. J Acoust Soc Am 116: 3460–3470.

Pedersen E, van den Berg F, Bakker R et al. (2009). Response to noise from modern wind farms in The Netherlands. J Acoust Soc Am 126: 634-643.

Pierpont N (2009). Wind turbine syndrome. A report on a natural experiment. Santa Fe, NM: K-selected books.

van den Berg GP, Pedersen E, Bouma J et al. (2008). Project WINDFARMperception. Visual and acoustic impact of wind turbine farms on residents. FP6-2005-Science-and-Society-20. Specific Support Action Project no. 044628. Final report. http://docs.wind-watch.org/wfp-final-1.pdf

WHO (2009). Night noise guidelines for Europe. Copenhagen: WHO Regional Office for Europe.

WindVOICe (Wind Vigilance for Ontario Communities). 2010. A self-reporting survey: adverse health effects with industrial wind turbine complexes and the need for vigilance. July 2010. http://www.healthywindwisconsin.com/Ontario%20Health%20Survey%20Abstract%20Results%20and%20Responses.pdf

Download original document: “Adverse health effects of industrial wind turbines: a preliminary report”

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Princeton, Mass., wind turbines

Source:  Feinsilver, Sam

Princeton Municipal Light Department spent about $7,300,000 for two 1.5-MW Fuhrlander wind turbines, each of them a total height of 360 feet. They became fully operational on January 12, 2010.

Many more pictures, and captions, are available on Flickr: click here.

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