Changes in quality of life and perceptions of general health before and after operation of wind turbines.

Ontario is Canada's provincial leader in wind energy, with over 4000 MW of installed capacity supplying approximately five percent of the province's electricity demand. Wind energy is now one of the fastest-growing sources of renewable power in Canada and many other countries. However, its possible negative impact on population health, as a new source of environmental noise, has raised concerns for people living in proximity to wind turbines (WTs). The aims of this study were to assess the effect of individual differences and annoyance on the self-reported general health and health-related quality of life (QOL) of nearby residents, using a pre- and post-exposure design. Prospective cohort data were collected before and after WT operations, from the individuals (n = 43) in Ontario, Canada. General health and QOL metrics were measured using standard scales, such as SF12, life satisfaction scales developed by Diener (SWLS) and the Canadian Community Health Survey (CCHS-SWL). The mean values for the Mental Component Score of SF12 (p = 0.002), SWLS (p < 0.001), and CCHS-SWL (p = 0.044) significantly worsened after WT operation for those participants who had a negative attitude to WTs, who voiced concerns about property devaluation, and/or who reported being visually or noise annoyed.

The impact of psychological factors on self-reported sleep disturbance among people living in the vicinity of wind turbines.

Canada's wind energy capacity has grown from approximately 137MW (MW) in 2000 to over 9700MW in 2014, and this progressive development has made Canada the fifth-largest market in the world for the installation of new wind turbines (WTs). Although wind energy is now one of the fastest growing sources of power in Canada and many other countries, the growth in both number and size of WTs has raised questions regarding potential health impacts on individuals who live close to such turbines. This study is the first published research using a prospective cohort design, with noise and sleep measurements obtained before and after installation of WTs to investigate effect of such turbines on self-reported sleep disturbances of nearby residents. Subjective assessment of sleep disturbance was conducted in Ontario, Canada through standard sleep and sleepiness scales, including the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Epworth daytime Sleepiness Scale (ESS). Both audible and infra-sound noises were also measured inside the bedroom. Descriptive and comparison analyses were performed to investigate the effect of WT exposure on sleep data. Results of the analysis show that participants reported poorer sleep quality if they had a negative attitude to WTs, if they had concerns related to property devaluation, and if they could see turbines from their properties. This study provides evidence for the role of individual differences and psychological factors in reports of sleep disturbance by people living in the vicinity of WTs.

Development of a health effects-based priority ranking system for air emissions reductions from oil refineries in Canada.

In Canada, the Canadian Council of Ministers for the Environment (CCME) is currently engaged in a process to determine how best to reduce air emissions from oil refineries. The National Framework for Petroleum Refineries Emissions Reduction (NFPRER) is being developed with the input of stakeholders, including nongovernment organizations (NGOs), industry, and regulatory jurisdictions. One component of this framework is the development of a tool to prioritize emissions for reduction based on estimated health impacts. HEIDI II (Health Effects Indicators Decision Index II) is a spreadsheet-based model that prioritizes a series of carcinogenic and noncarcinogenic air toxicicants and criteria air contaminants commonly emitted from Canadian oil refineries. A generic meteorological dispersion model was applied to reported annual emissions data for each of Canada's 20 refineries. Photodegradation rates and ambient levels of each substance were accounted for, and air concentrations were calculated for 20 geographic zones around each refinery. These were coupled to toxicity data derived mainly from Health Canada and the U.S. Environmental Protection Agency (EPA), and applied to target populations of children, adults and seniors. HEIDI II predicts incidence of relevant disease endpoints from each substance emitted, except for benzene, toluene, ethylbenzene, and xylene (BTEX) and polycyclic aromatic hydrocarbons (PAH), which were treated as chemical mixtures. Rankings were based on predicted case incidence or the application of a common health impact metric, disability-adjusted life years (DALYs), to the predicted incidence. Using the DALY approach, priority rankings can be made within each of the chemical classes, or across all three classes together. HEIDI II incorporates several switches that allow the user to investigate alternate scenarios based on stack height, average daily sunlight hours (for calculating photodegradation), and the possibility of emissions below regulatory reporting thresholds.

Development of the PEARLS model (Particulate Exposure from Ambient to Regional Lung by Subgroup) and use of Monte Carlo simulation to predict internal exposure to 2.5 in Toronto.

Air pollution is a current and growing concern for Canadians, and there is evidence that ambient levels that meet current exposure standards may be associated with mortality and morbidity in Toronto, Canada. Evaluating exposure is an important step in understanding the relationship between particulate matter (PM) exposure and health outcomes. This report describes the PEARLS model (Particulate Exposure from Ambient to Regional Lung by Subgroup), which predicts exposure distributions for 11 age-gender population subgroups in Toronto to PM2.5 (PM with a median aerodynamic diameter of 2.5 microm or less) using Monte Carlo simulation techniques. The model uses physiological and activity pattern characteristics of each subgroup to determine region-specific lung exposure to PM2.5, which is defined as the mass of PM2.5 deposited per unit time to each of five lung regions (two extrathoracic, bronchial, bronchiolar, and alveolar). The modeling results predict that children, toddlers, and infants have the broadest distributions of exposure, and the greatest chance of experiencing extreme exposures in the alveolar region of the lung. Importance analysis indicates that the most influential model variables are air exchange rate into indoor environments, time spent outdoors, and time spent at high activity levels. Additionally, a "critical point" was defined and introduced to the PEARLS to investigate the effects of possible threshold-pathogenic phenomena on subgroup exposure patterns. The analysis indicates that the subgroups initially predicted to be most highly exposed were likely to have the highest proportion of their population exposed above the critical point. Substantial exposures above the critical point were predicted in all subgroups for ambient concentrations of PM2.5 commonly observed in Toronto after continuous exposure of 24 hours or more.

Risk management frameworks for human health and environmental risks.

A comprehensive analytical review of the risk assessment, risk management, and risk communication approaches currently being undertaken by key national, provincial/state, territorial, and international agencies was conducted. The information acquired for review was used to identify the differences, commonalities, strengths, and weaknesses among the various approaches, and to identify elements that should be included in an effective, current, and comprehensive approach applicable to environmental, human health and occupational health risks. More than 80 agencies, organizations, and advisory councils, encompassing more than 100 risk documents, were examined during the period from February 2000 until November 2002. An overview was made of the most important general frameworks for risk assessment, risk management, and risk communication for human health and ecological risk, and for occupational health risk. In addition, frameworks for specific applications were reviewed and summarized, including those for (1)contaminated sites; (2) northern contaminants; (3) priority substances; (4) standards development; (5) food safety; (6) medical devices; (7) prescription drug use; (8) emergency response; (9) transportation; (10) risk communication. Twelve frameworks were selected for more extensive review on the basis of representation of the areas of human health, ecological, and occupational health risk; relevance to Canadian risk management needs; representation of comprehensive and well-defined approaches; generalizability with their risk areas; representation of "state of the art" in Canada, the United States, and/or internationally; and extent of usage of potential usage within Canada. These 12 frameworks were: 1. Framework for Environmental Health Risk Management (US Presidential/Congressional Commission on Risk Assessment and Risk Management, 1997). 2. Health Risk Determination: The Challenge of Health Protection (Health and Welfare Canada, 1990). 3. Health Canada Decision-Making Framework for Identifying, Assessing and Managing Health Risks (Health Canada, 2000). 4. Canadian Environmental Protection Act: Human Health Risk Assessment of Priority Substances(Health Canada, 1994). 5. CSA-Q8550 Risk Management: Guidelines for Decision-Makers (Canada Standards Association, 1997). 6. Risk Assessment in the Federal Government: Managing the Process (US National Research Council, 1983). 7. Understanding Risk: Informing Decisions in a Democratic Society (US National Research Council, 1996). 8. Environmental Health Risk Assessment (enHealth Council of Australia, 2002). 9. A Framework for Ecological Risk Assessment (CCME, 1996). 10. Ecological Risk Assessments of Priority Substances Under the Canadian Environmental Protection Act (Environment Canada, 1996).11. Guidelines for Ecological Risk Assessment (US EPA, 1998b). 12. Proposed Model for Occupational Health Risk Assessment and Management (Rampal & Sadhra, 1999). Based on the extensive review of these frameworks, seven key elements that should be included in a comprehensive framework for human health, ecological, and occupational risk assessment and management were identified: 1. Problem formulation stage. 2. Stakeholder involvement. 3. Communication. 4. Quantitative risk assessment components. 5. Iteration and evaluation. 6. Informed decision making. 7. Flexibility. On the basis of this overarching approach to risk management, the following "checklist" to ensure a good risk management decision is proposed: - Make sure you're solving the right problem. - Consider the problem and the risk within the full context of the situation, using a broad perspective. - Acknowledge, incorporate, and balance the multiple dimensions of risk. - Ensure the highest degree of reliability for all components of the risk management process. - Involve interested and effected parties from the outset of the process. - Commit to honest and open communication between all parties. - Employ continuous evaluation throughout the process (formative, process, and outcome evaluation), and be prepared to change the decision if new information becomes available. Comprehensive and sound principles are critical to providing structure and integrity to risk management frameworks. Guiding principles are intended to provide an ethical grounding for considering the many factors involved in risk management decision making. Ten principles are proposed to guide risk management decision making. The first four principles were adapted and modified from Hattis (1996) along with the addition of two more principles by Hrudey (2000). These have been supplemented by another four principles to make the 10 presented. The principles are based in fundamental ethical principles and values. These principles are intended to be aspirational rather than prescriptive--their application requires flexibility and practical judgement. Risk management is inherently a process in search of balance among competing interests and concerns. Each risk management decision will be "balancing act" of competing priorities, and trade-offs may sometimes have to be made between seemingly conflicting principles. The 10 decision-making principles, with the corresponding ethical principle in italics are: 1. Do more good than harm (beneficence, nonmalificence).- The ultimate goal of good risk management is to prevent or minimize risk, or to "do good" as much as possible. 2. Fair process of decision making (fairness, natural justice). - Risk management must be just, equitable, impartial, unbiased, dispassionate, and objective as far as possible given the circumstances of each situation. 3. Ensure an equitable distribution of risk (equity). - An equitable process of risk management would ensure fair outcomes and equal treatment of all concerned through an equal distribution of benefits and burdens (includes the concept of distributive justice, i.e., equal opportunities for all individuals). 4. Seek optimal use of limited risk management resources (utility). - Optimal risk management demands using limited resources where they will achieve the most risk reduction of overall benefit. 5. Promise no more risk management that can be delivered (honesty).- Unrealistic expectations of risk management can be avoided with honest and candid public accounting of what we know and don't know, and what we can and can't do using risk assessment and risk management. 6. Impose no more risk that you would tolerate yourself (the Golden Rule). - The Golden Rule is important in risk management because it forces decision makers to abandon complete detachment from their decisions so they may understand the perspectives of those affected. 7. Be cautious in the face of uncertainty ("better safe than sorry"). - Risk management must adopt a cautious approach when faced with a potentially serous risk, even if the evidence is uncertain. 8. Foster informed risk decision making for all stakeholders (autonomy). - Fostering autonomous decision making involves both providing people with the opportunity to participate, and full and honest disclosure of all the information required for informed decisions. 9. Risk management processes must be flexible and evolutionary to be open to new knowledge and understanding (evolution, evaluation, iterative process). - The incorporation of new evidence requires that risk management be a flexible, evolutionary, and iterative process, and that evaluation is employed at the beginning and througthout the process. 10. the complete elimination fo risk is not possible (life is not risk free).- Risk is pervasive in our society, and cannot be totally eliminated despite an oft-expressed public desire for "zero risk". However, the level of risk that may ve tolerable by any individual is dependent on values of beliefs, as well as scientific information. Each agency must continue to employ a process that meets the needs of their specific application of risk management. A single approach cannot satisfy the diverse areas to which risk decisions are being applied. However, with increasing experience in the application of the approaches, we are evolving to a common understanding of the essential elements and principles required for successful risk assessment, risk management, and risk communication. Risk management will continue to be a balancing act of competing priorities and needs. Flexibility and good judgement are ultimately the key to successfully making appropriate risk decisions.