BACK

Healthy Development Inc.

www.healthydevelopment.us

msimmons@healthydevelopment.us

Phone 850.322.4629

In 2005, Florida’s Taylor County Board of Commissioners advocated for an 800 megawatt coal-fired electric plant to be built four miles south of Perry, the County seat. The Taylor County Development Authority (TCDA) commissioned a Health Impact Assessment (HIA) of the proposed plant. The scope was determined by community stakeholder interviews and surveys. The scope includes (1) risks to health from the air pollution, specifically, particulate matter (PM₁₀), ground level ozone, mercury and carbon dioxide emissions, and (2) benefits to health from employment from the plant and the "community contribution."

Methods: Peer-reviewed scientific evidence was collected on the potential impacts from emissions and economic impacts from Taylor Energy Center (TEC). Mortality effects of PM₁₀ were forecast onto local population statistics using a log-linear risk model of population exposure. No point source model for ground level ozone was available however components of ozone were assessed. Mercury emissions will be modeled by Environmental Consulting & Technology Inc. (ECT) during the permitting phase. Carbon dioxide health impacts are an emerging area of health research that will be discussed. The impact of various employment scenarios on health of employees and their families was estimated based on evidence.

Results: Substantial racial disparities in health were identified. During the operational phase of the plant, local air quality will deteriorate slightly with small effects on mortality that would likely be undetectable over time. Carbon dioxide from the plant will contribute to global climate change having overall negative effects on global health. All emissions evaluated, except carbon dioxide, are regulated by state and federal agencies. It is likely that carbon dioxide will be regulated in the near future. The health benefits of the jobs would be greatest if a large proportion of black residents fill the jobs.

Recommendations are:

In the summer of 2005, rural Florida’s Taylor County Board of Commissioners advocated for an 800 megawatt coal-fired electric plant to be built four miles south of the county seat, Perry. The county is economically disadvantaged and has poorer health compared to the state average, a condition shared by many rural counties. The county has a history of polluting industry, a 40–year-old paper plant, and an organized opposition that has rallied against the coal plant. In an effort to raise the level of debate between the two opposing sides on the health issues to the county’s population involved in the operation of a coal fired electric plant within the county, the Taylor County Development Authority commissioned Healthy Development Inc. (HDI) to conduct a Health Impact Assessment (HIA) on the proposed plant. Although the HIA did not analyze the paper plant, existing fear and stress about additional pollution pervaded the coal plant issue. Furthermore, stakeholder surveys and public health data identified that racial tensions and health disparities are a significant aspect of the community.

The HIA focused on evaluating the likelihood of change in community health from the dual impact of the air emissions and economic growth contributed by the coal plant. Key themes from community stakeholder interviews and surveys set the scope of the HIA. The Taylor Energy Center (TEC) will emit tons of carbon dioxide into the air from the plant and, currently, carbon dioxide is not regulated. The potential impact from this green house gas will be addressed. Additionally, TEC will emit mercury, particulate matter and the components of ground level ozone (a component of smog). The facility will meet all state and federal air quality criteria. The HIA will give particular attention to risks to health from the particulate matter and ground level ozone during the operational phase of the coal plant and benefits to health from the jobs created by the plant. Limitations of the HIA follow the jobs and health section.

Some residents are fearful of the high rates of cancer and respiratory diseases presently reported in the county. Alternative explanations for these high rates were suggested during the scoping phase including air pollution emissions from the paper mill or from high smoking rates. Further deterioration in air quality produced by the Taylor Energy Center is a major concern for some residents. A smoking attributable mortality analysis was calculated by the Florida Department of Health’s Bureau of Epidemiology to ascertain the proportion of deaths in the county that is attributable to smoking. The smoking attributable mortality analysis may shed light on the high cancer and other chronic diseases in the county and is presented first.

The Florida Department of Health’s Bureau of Epidemiology conducted a smoking attributable mortality analysis for deaths in the county for 2003, the most recent data available. There were 103 deaths in the county and 23 of those deaths were linked to causes of death associated with tobacco use. Therefore, about 22 percent of the deaths that occurred in 2003 are attributable to tobacco use. Statewide, the percentage of death attributable to tobacco use was 18% in 2001.

Cigarette smoking is the leading cause of preventable and premature death in the United States. Table 1 lists the diseases that are caused by tobacco use. This list of illnesses associated with tobacco use will shed some light on individual experiences of these illnesses in the county.

The CDC estimates that the cost for medical expenditures and productivity losses related to illnesses associated with smoking to be $4,357 per person in 2006 dollars (CDC 2002). Given that 31.2% of Taylor County residents reported tobacco use, the annual economic impact to county residents is likely to be approximately $28.5 million dollars in medical and lost productivity costs.

Implement and fund additional smoking cessation programs and provide health prevention and education programs to improve health.

Exposure to high levels of mercury can cause neurologic and kidney disorders (CDC 2004). Because methylated mercury in the aquatic environment bioaccumulates in animal tissues in the food chain, people can be exposed to it by eating fish, shellfish and other seafood. Exposure of childbearing-aged women to mercury is of particular concern because of its potential adverse neurologic effects of mercury to fetuses. Mercury in local water bodies and fish originate from both US and non-US sources.

The combustion of fossil fuels containing mercury will result in emissions of elemental mercury (Hg⁰), reactive gaseous divalent mercury (Hg²+ or RGM), and/or particle-bound mercury (Hg_p). Hg_p is emitted in particulate form, while both elemental mercury and RGM are released in the gaseous state. The deposition characteristics of each of these three mercury species differ. Elemental mercury has a long residence time in the atmosphere and travels long distances (i.e., greater than 50 km) before it is ultimately deposited on the Earth’s surface. The other two forms of mercury, RGM and Hg_p, will deposit more locally (i.e., within 50 km) and regionally (i.e., from 50 to several thousand km). Since the fossil fuels planned for the Taylor Energy Center will contain trace amounts of mercury, the facility will be a source of mercury emissions during the operational phase of the plant. Some of the mercury deposited locally can be methylated and could potentially bioaccumulate in fish.

In March of 2005, the Environmental Protection Agency (EPA) issued a federal rule to permanently cap and reduce mercury emissions from coal-fired power plants, the largest source of mercury emissions in the US. The Clean Air Mercury Rule (CAMR) will build on EPA’s Clean Air Interstate Rule (CAIR) to significantly reduce emissions from coal-fired power plants. Coal-fired power plants are the largest remaining sources of mercury emissions in the country. When fully implemented, these rules will reduce utility emissions of mercury from 48 tons to 15 tons a year.

___________________________________________

___________________________________________

The Clean Air Mercury Rule establishes "standards of performance" limiting mercury emissions from new and existing coal-fired power plants and creates a market-based cap-and-trade program that will reduce nationwide utility emissions of mercury in two distinct phases. The first phase cap is 38 tons and emissions will be reduced by taking advantage of "co-benefit" reductions – that is, mercury reductions achieved by reducing sulfur dioxide and nitrogen oxides emissions under CAIR. In the second phase, due in 2018, coal-fired power plants will be subject to a second cap, which will reduce emissions to 15 tons upon full implementation. Additionally, new coal-fired power plants ("new" means construction starting on or after Jan. 30, 2004) will have to meet stringent new source performance standards (i.e., stack mercury emission rate limits) in addition to being subject to the caps.

The November 5, 2004 edition of the Morbidity and Mortality Weekly Report published by the Centers for Disease Control and Prevention reported on the risk of mercury toxicity in the US (CDC 2004). An analysis of blood mercury levels was undertaken for young children and childbearing-aged women in the US from 1999 to 2002. The authors of this study used the CDC’s National Health and Nutrition Examination Survey which began measuring blood mercury levels in these populations in 1999. The data are nationally representative and are based on analysis of cross-sectional data (data were collected at one time and is not longitudinal) for the noninstitutionalized, U.S. household population. The survey consisted of interviews conducted in participants’ homes and standardized health examinations conducted in mobile examination centers.

The findings confirmed that blood mercury levels in young children and women of childbearing age usually are below levels of concern. However, approximately six percent of childbearing-aged women had levels at or above a reference dose, an estimated level assumed to be without appreciable harm (>= 5.8μg/L). The percentage of all women aged 16-49 years with mercury levels >= 5.8 μg/L was 5.66% (95% confidence interval 4.04-7.95). The main limitation of this study is that it did not sample an adequate number of women sport anglers who might eat large amounts of fish to characterize the distribution of total blood mercury in this group.

In Taylor County and elsewhere, fish are an important source of food, high in protein and nutrients and low in saturated fatty acids and cholesterol. The short-term strategy to reduce the risk of mercury is to eat fish with low mercury levels and avoid or reduce consumption of fish with high mercury levels. Women who are pregnant or who intend to become pregnant should follow federal and state advisories on consumption of fish.

The Florida (DOH) s of Health and Environmental Protection (DEP) as well as the Florida Fish and Wildlife Conservation Commission collaborate to produce fish consumption advisories for all the water bodies in the state. Table 2 shows the fish consumption advisories for Taylor County by water body, species of fish and for two populations at risk. This is the best source of information about mercury and risk to individuals who eat fish.

The Taylor Energy Center qualifies as a new coal plant and will be subject to the new source performance standards in addition to meeting the requirements of the Clean Air Mercury Rule and the Clean Air Interstate Rule. ECT states "The Taylor Energy Center will include emission control systems that will reduce total mercury emissions to less than 60 pounds per year. Of this total, less than 10 percent will be RGM and only trace amounts of Hg_p. It is anticipated that deposition modeling will demonstrate that Hg deposition due to Taylor Energy Center emissions will be insignificant compared to current Hg deposition rates for North Florida."  This statement by ECT will be subject to scrutiny and verification during the permitting process for the plant.

To see the table mentioned, see Table 3 at www.doh.state.fl.us/environment/community/fishconsumptionadvisories/Freshfishcountyformat.html#Taylor

A proportion of the "community contribution" could be use to establish baseline mercury levels in the county’s population through hair or blood sampling. The level of risk established by sampling should be followed by community education concerning mercury and fish consumption if a problem is observed in the population. Until then, the best source of information about the risk from mercury is the fish consumption advisories released by the Florida Department of Health annually. Residents should know and meet the fish consumption advisories for fish caught locally.

Carbon dioxide is not classified as a pollutant and, as yet, is not a regulated emission. Carbon dioxide is a green house gas that will be emitted from the TEC. Green house gases raise global temperatures and, as a result, sea levels. Epidemiologists are just beginning to study the impact of rising global temperatures on human health. Research has pointed to a number of effects that may have already occurred. For example, evidence of a link between warming and microbial foodborne, waterborne and mosquito-related illnesses has been observed. Increases in illnesses are also connected to more intense weather disturbances that in part are attributed to increased greenhouse emissions (Hall et al. 2002).

The epidemiological research concerning the health effects of climate change is only now emerging. Thus far the studies that have identified a link between climate change and health have addressed single diseases and local populations. The type of epidemiological evidence that is needed should evaluate global scale impacts affecting human populations at large (Hampton 2006).

The World Health Organization is just beginning to develop standardized comparative risk assessment methods for estimating aggregate disease burdens attributable to different risk factors associated with global warming (Campbell-Lendrum and Woodruff 2006). The assessment is part of the Global Burden of Disease project. The risk assessment has been applied to existing and new models for a range of climate-sensitive diseases in order to estimate the effect of global climate change on current disease burdens and likely proportional changes in the future. The comparative risk assessment approach has been used to assess the health consequences of climate change worldwide and to inform decisions on mitigating greenhouse gas emissions. The approach places climate change within the same criteria for epidemiologic assessment as other health risks and accounts for the size of the burden of climate-sensitive diseases rather than just proportional change, which highlights the importance of small proportional changes in diseases that cause a large burden to individuals and societies.

Health risks associated with climate change identified so far include overall cardiovascular disease deaths, foodborne and waterborne diseases that cause diarrhea episodes, vectorborne disease such as malaria and dengue fever, natural disasters and fatal unintentional injuries, population displacement and malnutrition (Campbell-Lendrum and Woodruff 2006). These exercises by the World Health Organization help clarify important knowledge gaps such as a relatively poor understanding of the role of nonclimatic factors (socioeconomic and other) that may modify future climatic influences and a lack of empirical evidence and methods for quantifying more complex climate–health relationships. These exercises highlight the need for risk assessment frameworks that make the best use of traditional epidemiologic methods and that also fully consider the specific characteristics of climate change. These include the long-term and uncertain nature of the exposure and the effects on multiple physical and biological systems that have the potential for diverse and widespread effects, including high-impact events like hurricanes. Ultimately though, it is clear from the perspective of the World Health Organization that the health impact of global warming could affect the health of billions of people.

ECT estimates that about seven million metric tons of carbon dioxide will be emitted per year. This is the most significant negative impact from TEC. It is reasonable to assume that the carbon dioxide emitted from TEC will contribute to global climate change and human health will be impacted. At a minimum, the coastline of Taylor County is likely to experience sea level rise between seven and 23 inches within the next century (Intergovernmental Panel on Climate Change 2007). Beyond sea level rise, the evidence is too sparse to assess the impact of carbon dioxide emissions on the health of residents of Taylor County. Although the health effects from global warming are still an emerging area of health research, this HIA's assessment of most significant negative impact is based on the precautionary principal.

Unlike other areas that have proposed coal fired utilities, Taylor County is in the unique position with respect to carbon dioxide, as it is the Forest Capital of Florida. Much of the county’s land area is currently forested. Plants and soil sequester carbon dioxide and Taylor County’s forests are a source of sequestration, sometimes referred to as "carbon sinks." The forest cover in the county sequesters’ carbon dioxide in ongoing plant growth through needles, bark and soil. What follows is a rough estimation of the possible sequestration ability of the local forest cover.

The assumptions that were made for this rough calculation are the following:

Source: Steve Bohl, Deputy Forest Management Chief, Florida Division of Forestry

Source of table for carbon stocks for loblolly pine stands: Journal of Forestry, July/August 2004

Source of Equation for Carbon Sequestration Calculation: Smith et al, 2006 U.S. Department of Agriculture. Methods for calculating forest ecosystems and harvested carbon with standard estimates for forest types of the United States.

http://www.treesearch.fs.fed.us/pubs/22954

http://www.fs.fed.us/ne/newtown_square/publications/technical_reports/pdfs/2006/ne_gtr343.pdf (full text)

------------------------------------------------------------------------------------------------------

1 hectare = 2.417 acres

1 metric ton = 2,204 lbs

For loblolly pine forest:

Conversion of carbon sequestration for hectares to acres= 153,306 lbs of Carbon/2.471 = 63,428 lbs per acre.

Conversion of carbon dioxide pounds per acre to metric tons per acre= 63,428 lbs per Acre/2204 = 28.8 tons/acre,

Estimated emission of carbon dioxide from TEC: 7,001,799 metric tons annual

Estimated sequestration of carbon dioxide from Taylor County pine stocks: 450,000 acres X 28.8 metric tons per acre = 12,960,000 metric tons per year or about 13 million metric tons. This estimate does not calculate the full carbon footprint of the county that would include automobiles, existing industry and other carbon dioxide emissions and, on the contrary, other sources of sequestration. It is quite likely that the county is currently and will continue to be carbon dioxide negative after TEC begins operation.

TEC will emit about seven million metric tons of carbon dioxide. This is the most significant negative impact from TEC. Although the health effects from global warming are still an emerging area of health research, this HIA's assessment of negative impact is based on the precautionary principal. Preliminary estimates of the global burden of disease from global warming include overall increase in cardiovascular disease deaths, foodborne and waterborne diseases that cause diarrhea episodes, vectorborne disease such as malaria and dengue fever, natural disasters and fatal unintentional injuries, population displacement and malnutrition. The health impact of global warming could affect billions of people.

This HIA recommends a regular assessment of the County's carbon footprint, as well as a policy to remain carbon negative. Sarasota County, Florida may serve as a model for Taylor because of its efforts to undertake a comprehensive ecological footprint. A rough estimate shows Taylor County's existing forest cover sequesters about 13 million metric tons of carbon dioxide. After the carbon footprint is calculated, the county may pursue selling existing carbon credits on established carbon markets. In addition, the county should adhere to EPA’s smart growth principles in future residential and commercial developments that can be tailored to rural communitiies.

In addition to carbon dioxide and mercury, TEC emissions will include criteria pollutants. This section will describe the health effects of criteria pollutants, the EPA National Ambient Air Quality Standards limits and present the estimated emissions from TEC provided by ECT. Healthy Development Inc. uses the estimates provided by ECT for the Health Impact Assessment with confidence, because these estimates will be provided to DEP and/or EPA for permitting TEC. DEP and EPA require appropriate methodology for estimating emissions for permitting.

EPA identifies six criteria pollutants as indicators of air quality, and has established for each of them a maximum concentration above which adverse effects on human health may occur. They include sulfur dioxide, nitrogen dioxide, particulate matter, carbon monoxide, ozone and lead. Five of the six pollutants will be discussed and defined next using the US Environmental Protection Agency’s Green Book on Criteria Pollutants . Threshold concentrations of criteria pollutants are called National Ambient Air Quality Standards (NAAQS).

Sulfur Dioxide

High concentrations of sulfur dioxide (SO₂) affect breathing and may aggravate existing respiratory and cardiovascular disease. Sensitive populations include asthmatics, individuals with bronchitis or emphysema, children and the elderly. Sulfur dioxide is also a primary contributor to acid deposition, or acid rain, which causes acidification of lakes and streams and can damage trees, crops, historic buildings and statues. In addition, sulfur compounds in the air contribute to visibility impairment in large parts of the country.

Ambient sulfur dioxide results largely from stationary sources such as coal and oil combustion, steel mills, refineries, pulp and paper mills and from nonferrous smelters.

Nitrogen dioxide (NO₂) is a brownish, highly reactive gas that is present in all urban atmospheres. Nitrogen dioxide can irritate the lungs, cause bronchitis and pneumonia, and lower resistance to respiratory infections. Oxides of nitrogen are an important precursor both to ground level ozone and acid rain, and may affect both terrestrial and aquatic ecosystems. The major mechanism for the formation of nitrogen dioxide in the atmosphere is the oxidation of the primary air pollutant nitric oxide. Oxides of nitrogen play a major role, together with volatile organic compounds, in the atmospheric reactions that produce ground level ozone. Oxides of nitrogen form when fuel is burned at high temperatures. The two major emissions sources are transportation vehicles and stationary fuel combustion sources such as electric utility and industrial boilers.

Airborne particulate matter (PM) consists of many different substances suspended in air in the form of particles (solids or liquid droplets) that vary widely in size. Particulate matter includes dust, dirt, soot, smoke and liquid droplets directly emitted into the air by sources such as factories, power plants, cars, construction activity, fires and natural windblown dust. Particles formed in the atmosphere by condensation or the transformation of emitted gases such as sulfur dioxide and volatile organic compounds are also considered particulate matter.

Based on studies of human populations exposed to high concentrations of particles (sometimes in the presence of sulfur dioxide) and laboratory studies of animals and humans, there are major effects of concern for human health. These include effects on breathing and respiratory symptoms, aggravation of existing respiratory and cardiovascular disease, alterations in the body's defense systems against foreign materials, damage to lung tissue, carcinogenesis and premature death. The major subgroups of the population that appear to be most sensitive to the effects of particulate matter include individuals with chronic obstructive pulmonary or cardiovascular disease or influenza, asthmatics, the elderly and children. Particulate matter also soils and damages materials, and is a major cause of visibility impairment in the United States.

Particulate matter is more harmful to human health the smaller it is. Particles less than 10 micrometers in diameter include both fine and coarse particles and are referred to as PM₁₀. Fine particulate matter is a component of coarse particulate matter. Fine particles are defined as less than 2.5 micrometers in diameter and are referred to as PM_2.5. Fine particles pose the greatest health concern because they can pass through the nose and throat and get into the lungs. The TEC has provided estimates of ambient coarse particulate matter for this health impact assessment. The proportion of fine particulate matter within coarse particulate matter can range between 50 and 80 percent (Boldo, Vedina, LeTertre, Hurley, Mucke, Ballester, Aguilera and Eilstein 2006)

Carbon monoxide (CO) is a colorless, odorless and poisonous gas produced by incomplete burning of carbon in fuels. When carbon monoxide enters the bloodstream, it reduces the delivery of oxygen to the body's organs and tissues, and can lead to acute or chronic effects. Health threats are most serious for those who suffer from cardiovascular disease, particularly those with angina or peripheral vascular disease. Exposure to elevated carbon monoxide levels can cause impairment of visual perception, manual dexterity, learning ability and performance of complex tasks.

On average, 77% of the nationwide carbon monoxide emissions are from transportation sources. The largest emissions contribution comes from highway motor vehicles. Thus, the focus of carbon monoxide monitoring has been on traffic-oriented sites in urban areas where the main source of carbon monoxide is motor vehicle exhaust. Other major carbon monoxide sources include wood-burning stoves, incinerators and industrial sources.

Ground level ozone (O₃) is a photochemical oxidant and the major component of smog. While ozone in the upper atmosphere is beneficial to life by shielding the earth from harmful ultraviolet radiation from the sun, high concentrations of ozone at ground level are a major health and environmental concern. Ozone is not emitted directly into the air but is formed through complex chemical reactions between precursor emissions of volatile organic compounds and oxides of nitrogen in the presence of sunlight. These reactions are stimulated by sunlight and temperature so that peak ozone levels occur typically during the warmer times of the year. Both volatile organic compounds and oxides of nitrogen are emitted by transportation and industrial sources. Volatile organic compounds are emitted from sources as diverse as autos, chemical manufacturing, dry cleaners, paint shops and other sources using solvents.

The reactivity of ozone causes health problems because it can damage lung tissue, reduce lung function and sensitize the lungs to other irritants. Scientific evidence indicates that ambient levels of ozone not only affect people with impaired respiratory systems, such as asthmatics, but healthy adults and children as well. Exposure to ozone for several hours at relatively low concentrations has been found to significantly reduce lung function and induce respiratory inflammation in normal, healthy people during exercise. This decrease in lung function generally is accompanied by symptoms including chest pain, coughing, sneezing and pulmonary congestion.

The Clean Air Act, which was last amended in 1990, requires EPA to set National Ambient Air Quality Standards for pollutants considered harmful to public health and the environment (see Table 3). The Clean Air Act established two types of national air quality standards. Primary standards set limits to protect public health, including the health of "sensitive" populations such as asthmatics, children, and the elderly. Secondary standards set limits to protect public welfare, including protection against decreased visibility, damage to animals, crops, vegetation, and buildings. Units of measure for the standards are parts per million (ppm) by volume, milligrams per cubic meter of air (mg/m³), and micrograms per cubic meter of air (µg/m³).

The Taylor Energy Center will report emissions for five of the six criteria pollutants to the Florida Department of Environmental Protection and the US Environmental Protection Agency. These include sulfur dioxide, nitrogen dioxide, particulate matter, and carbon monoxide. Appendix One has an overview and discussion of the modeling methodology for estimating the criteria pollutants from TEC. This model estimates the amount of ambient pollutants that are "on the ground, where they are breathed." TEC air quality impacts were estimated using five years of meteorological data. Table 4 shows the TEC air quality impact estimates for sulfur dioxide, oxides of nitrogen, particulate matter and carbon monoxide.

TEC will not report estimates of ambient ground level ozone. Ground level ozone is formed by a complex series of chemical reactions involving primarily oxides of nitrogen and volatile organic compounds during warm ambient air temperatures in the presence of sunlight. Since ground level ozone is a secondary pollutant, assessment of ambient impacts is typically conducted on a regional basis rather than for individual emission sources such as TEC. For individual emission sources, such as the TEC, there are no generally accepted methods readily available to estimate ground level ozone impacts.

(1) Not to be exceeded more than once per year.

(2) Due to a lack of evidence linking health problems to long-term exposure to coarse particle pollution, the agency revoked the annual PM₁₀ standard in 2006 (effective December 17, 2006).

(3) Not to be exceeded more than once per year on average over 3 years.

(4) To attain this standard, the 3-year average of the weighted annual mean PM_2.5 concentrations from single or multiple community-oriented monitors must not exceed 15.0 µg/m³.

(5) To attain this standard, the 3-year average of the 98th percentile of 24-hour concentrations at each population-oriented monitor within an area must not exceed 35 µg/m³ (effective December 17, 2006).

(6) To attain this standard, the 3-year average of the fourth-highest daily maximum 8-hour average ozone concentrations measured at each monitor within an area over each year must not exceed 0.08 ppm.

(7) (a) The standard is attained when the expected number of days per calendar year with maximum hourly average concentrations above 0.12 ppm is < 1, as determined by appendix H. (b) As of June 15, 2005 EPA revoked the 1-hour ozone standard in all areas except the fourteen 8-hour ozone nonattainment Early Action Compact (EAC) Areas.

Ambient (on-the-ground, where it is breathed) air quality in Taylor County is currently not monitored as Taylor County has no air quality monitoring station. DEP conducted some air monitoring in the county in the 1980s and found no nonatttaiment issues for sulfur dioxide and particulates in the county. Currently, air quality estimates for Taylor County are modeled from Leon County monitors combined with local meteorological data. Criteria pollutants from stack emissions in the county are annually reported and monitored.

AAQS = Ambient Air Quality Standards

Source: ECT, 2006.

See Appendix 1 for a description of the table.

It should be remembered that the purpose of the National Ambient Air Quality Standards is to protect public health, including the health of sensitive populations such as asthmatics, children, and the elderly. Notice in Table 4 the column heading called "% of AAQS." ECT estimates that all of the criteria pollutants emitted from TEC will be at less than 3% of the National Ambient Air Quality Standards. Given the purpose of the ambient air quality standards, then the estimated emissions from TEC should not affect public health, including sensitive populations. The health impact assessment analyzed peer-reviewed scientific evidence and calculated and/or estimated impacts to assess the affect TEC will likely have on Taylor County residents.

In this section, the result of a review of scientific evidence is presented. Scientific researchers, especially those of the World Health Organization, are primarily concerned about the harmful health effects of ground level ozone and particulate matter. The review represents the latest peer-reviewed scientific knowledge (Krzyzanowski, Cohen, Anderson, and the WHO Working Group 2006). Before describing the findings, it is important that the terminology is clearly understood by all audiences.

There are numerous scientific journal articles published concerning particulate matter and ground level ozone. Air pollutants are regulated and data are collected in the same way and for the same time periods in countries all over the world, especially in the North America and Europe. Funding has been provided for epidemiologists to use air quality and health outcome data to study the effects of pollutants on human populations. Toxicology and clinical studies with animals have provided convincing support for the mechanisms of many of the epidemiological studies (Krzyzanowski et al. 2006).

Epidemiologists and other scientists study the effects of the pollutants on people in different locations, among different age groups and sometimes during different seasons. There are two types of studies of humans and pollution, short and long term studies. Short-term studies concern daily (24 hour) fluctuations in air pollution and its effects on daily death rates. Long-term studies follow populations over years and determine the impact of air pollution on death rates. Researchers at the World Health Organization and in European countries have specialized in short-term studies whereas researchers in the United States have specialized in the long-term studies (for more information see Krzyzanowski et al. 2006).

For either short or long term studies, these scientists use statistics to compare, for example, the mortality rate of people exposed to pollutants to the mortality rate of people not exposed to the pollutants in natural settings (non-experimental situations). In simple terms, the average outcome of people exposed is compared to the average outcome of people not exposed. But within both the exposed and non-exposed group, there is a great deal of variation in mortality that the statistical methods take into account.

Given the number of studies on the impact of pollution on health, there also is variation in the effects found by the different studies. It is possible, however, to take the "average" impact of a pollutant from the great variety of different scientific studies. This is called a meta-analysis. The short-term pollutant impact studies have been subject to meta-analyses. A meta-analysis takes all available scientific evidence published that meets certain quality criteria and recalculates the effects of the pollutant to compute a summary estimate of health effects. Using meta-analysis provides additional confidence in the impact due to the fact that extreme positive or negative research findings from the variety of scientific evidence are narrowed to average impact. The health impact assessment will use the results of two meta-analyses on short-term effects of particulate matter and ground level ozone from the World Health Organization Task Force (2004) and another from the journal Epidemiology (Anderson, Atkinson, Peacock, Sweeting, and Marston 2005).

Both meta-analyses and individual scientific research efforts use tests of statistical significance to identify effects that are unlikely to have occurred by chance. Statistical significance means that the researchers used methods to determine with 95 percent confidence that the impact found is not due to chance. A statistically significant finding is one that is not considered to be due to random fluctuation. The evidence presented next communicates the effect size as either risk ratios or odds ratios. A "risk ratio" is the ratio of the percentage of an event occurring in one group to the percentage of an event occurring in another group. Another way to say it is that it is the risk of developing a disease relative to exposure. "Odds ratio" is defined as the ratio of the odds of an event occurring in one group to the odds of it occurring in another group. Both risk and odds ratios can be estimated from samples and can be adjusted for other influences. Risk ratios are the easiest to interpret. A risk ratio of 2.0 means the risk, for example, of dying in the year for one group is twice that of another group. A risk ratio of 1.20 would mean that the risk of dying in the year for the one group is 20% higher than the other group.

As mentioned previously, scientific consensus has emerged that the pollutants most harmful to health are ground level ozone and particulate matter. However, both particulate matter and ground level ozone are comprised of many different harmful chemicals. Sulfur dioxide is harmful to humans when it attaches to particulate matter (this is a simplified version of the complex chemistry that occurs in the atmosphere, for more information see Schlesinger and Cassee 2003). Nitrogen oxides are also ingredients in particulate matter and ozone. Epidemiological studies of pollutant exposures investigate the mixtures of pollutants in outdoor air rather than individual pollutants (World Health Organization Task Force 2004). Toxicological research on animals can investigate a single pollutant at a time and this research has further informed epidemiologists.

Next, summary estimates of short-term (or daily) effects of particulate matter (PM₁₀) and ground level ozone are presented. The meta-analyses show that for each increase in PM₁₀ or O₃ there is an increase in the risk of a poor health outcome. The outcomes presented are mortality, hospitalizations, cough and medication use. In order to conclude that there are negative effects of either PM₁₀ or O₃, the findings must be statistically significant.

Table 6 shows the summary estimates for the three short-term mortality outcomes including all-cause, cardiovascular and respiratory mortality for 24-hour PM₁₀ and 8-hour ozone. The increase in daily mortality for each 10 µg/m³ increase in PM₁₀ was 0.6%, 1.0%, and 0.5% for all-cause, respiratory, and cardiovascular mortality respectively. The increase in mortality for each 10 µg/m³ increase in 8-hour ozone was 0.2% and 0.4% for all-cause and cardiovascular mortality respectively. The estimate for respiratory mortality and ozone was not statistically significant. Notice that the increase in risk of death for PM₁₀ and O₃ are a similar magnitude for each 10 µg/m³ increase in either pollutant. The association of the pollutants with early death is statistically significant.

ж The source is “Meta-analyses of time-series studies and panel studies of particulate matter and ozone,” Report of a World Health Organization Task Force. www.euro.who.int/document/e82792.pdf

Hospitalizations

Table 7 shows the summary estimates for two respiratory hospitalization outcomes for a short-term 10 µg/m³ increase in 24-hour PM₁₀ and 8-hour ozone. Neither of the ozone estimates was statistically significant. Three studies were summarized for respiratory hospitalizations for people 65 and older and the short-term summary estimated effect was a 0.7 percent increase in respiratory hospitalizations for a 10 µg/m³ in PM₁₀. Only one study provided evidence for all ages of people with Chronic Obstructive Pulmonary Disease (COPD). Hospitalizations for people with COPD increased by 1.1 percent for each 10 µg/m³ increase in PM₁₀ within a 24 hour period.

ж Unless otherwise noted the source is “Meta-analyses of time-series studies and panel studies of particulate matter and ozone,” Report of a World Health Organization Task Force. www.euro.who.int/document/e82792.pdf

§ Anderson HR, Atkinson RW, Peacock JL, Sweeting MJ, and Marston L. 2006. Ambient particulate matter and health effects - Publication bias in studies of short-term associations. Epidemiology 16 (2): 155-163.

Cough

A variety of findings were summarized for cough for patients with chronic respiratory diseases including asthma. Table 8 shows the short-term summary estimates for cough from 24-hour PM₁₀ and 8-hour ozone on children and people of all ages. The particulate matter analysis findings were not statistically significant. The ozone analysis findings were also not statistically significant.

ж Unless otherwise noted the source is “Meta-analyses of time-series studies and panel studies of particulate matter and ozone,” Report of a World Health Organization Task Force. www.euro.who.int/document/e82792.pdf

§ Anderson HR, Atkinson RW, Peacock JL, Sweeting MJ, and Marston L. 2006. Ambient particulate matter and health effects - Publication bias in studies of short-term associations. Epidemiology 16 (2): 155-163.

* statistically significant

ж The source is “Meta-analyses of time-series studies and panel studies of particulate matter and ozone,” Report of a World Health Organization Task Force. www.euro.who.int/document/e82792.pdf

Medication Use

Table 9 shows the impact on short-term medication use from particles and ozone on children and adults with asthma or chronic respiratory symptoms. PM₁₀ analysis findings for symptomatic children were not statistically significant. Particulate matter findings for symptomatic adults were mixed with one out of four studies finding a statistically significant impact. Only one study was cited for ozone and symptomatic children. It found that there was a 41.0 percent increase in medication use for each 10 µg/m³ increase in an 8 hour ozone measurement. The confidence interval on this single study is large and suggests the need for more research to validate the findings. Mixed results were identified for symptomatic adults and 8-hour ozone increases with one out of two studies with statistically significant findings.

Long-term exposure to combustion related fine-particles of air pollution is an important environmental risk factor for cardiopulmonary and lung cancer mortality (Pope, Burnett, and Thun et all. 2002). Table 10 shows that fine particulate matter (PM_2.5) is associated with all cause, lung cancer, and cardiopulmonary mortality. Each 10 µg/m³ increase in PM_2.5 is associated with approximately a 4%, 6% and 8% increase in risk of all-cause, lung cancer, and cardiopulmonary mortality, respectively. The risk of premature mortality is even higher for former and current smokers (Pope et al. 2004).

Source: Pope, et al. 2002

CI-Confidence Interval

The scientific evidence reviewed shows that particulate matter has both short-term (daily) and long-term (annual) effects on human health. Both short and long term health effects use the same log-linear risk model of population exposure except that the long term studies mathematically reduce the estimate of PM₁₀ to PM_2.5 by multiplying the PM₁₀ estimate by 60% (Cohen, Anderson, Ostro, Dev Pandey, Krzyzanowski, Künzli, Gutschmidt, Pope, Romieu, Samet and Smith 2004 and Pope 2005).

For PM₁₀ the equation is = RR ^X/₁₀ where X= PM₁₀ and RR is the risk ratio for all-cause or a specific cause of death. For PM_2.5 the equation is the same except X is multiplied by 0.6. The result of each equation is then multiplied by the appropriate Taylor County three-year age adjusted mortality rate including all-cause, respiratory, stroke, heart disease, and chronic lower respiratory disease. It was beyond the scope of this analysis to calculate morbidity impacts because hospital discharge data was necessary to calculate impacts on illness and these data were not available for this assessment.

TEC’s maximum 24 hour mean PM₁₀ µg/m³ is 0.87 and constitutes a fraction of the relative risk identified in the meta-analysis which is for a 10 µg/m³ increase in PM₁₀ (see Tables 5 and 6). Table 11 shows the calculated summary estimates for the three short-term mortality estimates for all-cause, respiratory, and cardiovascular with increases in daily mortality for each 10 µg/m³ increase in PM₁₀ was 0.6%, 1.0%, 0.5% and 0.5% for all-cause, respiratory, stroke and cardiovascular respectively. The percentage increase for all-cause, respiratory, and cardiovascular daily mortality as a result of estimated TEC particulate matter is 0.001%, 0.00009% and 0.00007% respectively. In summary, these percentage increases in daily mortality in Taylor County as a result of TEC particulate emissions is estimated to be well below a one percent increase. It would be difficult to detect such a small change in mortality daily and it would likely appear as random fluctuation.

Long-term exposure to combustion related fine-particles of air pollution is an important environmental risk factor for cardiopulmonary and lung cancer mortality (Pope et al 2002). Long-term exposure analysis uses annual PM₁₀ estimate and TEC annual PM₁₀ estimate is 0.133 (Table 5). TEC’s annual PM₁₀ contribution to the county is much less than the relative risk identified in Pope et al. (2002) which is for a 10 µg/m³ increase in PM₁₀ (Table 10). Table 12 shows the calculated summary estimates for the four long-term mortality estimates for all-cause, chronic lower respiratory disease, heart disease and lung cancer. The percentage increase for all-cause, chronic lower respiratory disease, heart disease and lung cancer long-term mortality from the estimated increase in particulate matter from TEC is 0.285%, 0.017%, 0.102% and 0.04% respectively. In summary, the percentage increase in long-term mortality in Taylor County as a result of TEC particulate emissions is also below a one percent increase.

CI=Confidence Interval

Source: Pope CA, Burnett RT, Thun MJ, et al. 2002. Lung cancer, cardiopulmonary mortality and long-term exposure to fine particulate air pollution. JAMA: Journal of the American Medical Association vol. 287, pp. 1132-1141.

In sufficient amounts during a day, particulate matter is linked to premature death and hospitalization. Based on peer-reviewed science and this health impact assessment calculation using local health data, TEC's estimated maximum particulate matter impact will at most increase daily mortality by 0.001%.

In sufficient amounts over years, particulate matter is linked to premature death. Based on peer-reviewed science and this health impact assessment calculation using local health data, the long-term health impact from TEC's estimated particulate matter impact will at most have 0.3% increase in the annual mortality rate. Both the daily and long-term effects on mortality will be undetectable over time.

In sufficient amounts over a day, ground level ozone is linked to increased daily mortality and medication use. The ozone impact could not be calculated because there are no standard point source models. Based on peer-reviewed science, the similarity in the magnitude of risk between ozone exposure and particulate matter exposure, and TEC emissions estimates, this HIA finds that the ground level ozone impact will be a similar magnitude to particulate matter. The impact will likely be minimal and undetectable over time.

Source: Lynch et al. 2004, Subject to copyright

Data from the US Census and Florida Vital Statistics were used to ascertain baseline health and estimate employment impacts on Taylor County employees. The North Central Florida Regional Planning Council conducted an economic impact analysis and estimated that 66 local residents will be employed by the plant out of the 180 total jobs at the TEC. Additionally, the council estimates that 388 indirect jobs will be created in the county that, for example, will come from increases in restaurants and office suppliers. A community contribution payment from the partners in the plant will be given to Taylor County by the plant is currently estimated at $179 million to be paid over 40 years. It is beyond the scope of this analysis to estimate the impact of indirect job creation and the substantial "community contribution" payment to the county, although both should have positive health impacts.

Source: 2000 US Census

The scientific evidence on the relationship between health and economic development is broad and systematic review papers about impacts of income on health were adapted for this HIA. In general, health status improves as income increases (Subramanian, Belli, and Kawachi 2002). Extensive evidence strongly supports the notion that individual health is a concave function of individual income (Lynch, Smith, Harper, Hillemeir, Ross, Kaplan, and Wolfson 2004; and Wagstaff and van Doorslaer 2000; see Figure 2).

Health and income inequality are largely found to be inversely related. Figures 3 and 4 show the inverse relationship between mortality and income by race in Florida and Taylor County. We used the income and corresponding death rate for Taylor County and for Florida as two end points and mathematically constructed a regular arch curved relationship between them (Lynch et al. 2004). This line was then used to estimate the change in death rate for a given change in income. This was done separately for the income and death rates by black and white race. One curve represents the relationship for the members of the black race and another curve represents the relationship for the white race (Figure 5).

Several employment scenarios using TEC minimum and median salaries were calculated using the estimated change in death rates per income change (Tables 13 and 14). All income data was adjusted to 2006 dollars using the consumer price index. Age and income specific death rates were not available for this analysis.

Figures 3 and 4 show substantial racial disparities in income and mortality in Taylor County and Florida. The jobs at TEC can be a mechanism for improving individual income that is linked to their individual risk for death. Reducing income inequality by raising the incomes of more disadvantaged people will improve the health of poor individuals, help reduce health inequalities, and increase average population health (Lynch et al. 2004).

Figure 5 shows the estimated median household income and mortality rate curves by black and white residents in Taylor County and Florida. The orange curve represents the potential improvement in black Taylor County resident mortality rates if household income approached the income for the average black Floridian. The maroon curve represents the potential improvement in the white Taylor County resident mortality rate as incomes approach the white Floridian average. The graph indicates that there is more room for improvement among blacks than white residents. The absolute difference between income and mortality indicators for blacks is larger than the same indicators for whites. Given the potential decrease in mortality by increasing income to the state average, we hypothesize beyond the data with the dashed orange line, that increasing income for black employees may further reduce their risk of death. The bottom of the graph shows the minimum and median salaries for TEC jobs.

Tables 13 and 14 extrapolate from the information in Figure 5 based on several TEC employment scenarios. Median household income is used here as a proxy for the median income of individuals in the county since these data were unavailable from the US Census. As a result, the authors make the assumption that median household income and individual salary have the same influence on mortality risk for employee families. Table 13 assumes that all 66 jobs will be paid the minimum salary of $33,180 in 2006 dollars. If all the 66 jobs went to black residents, we forecast that their individual risk of mortality would decline to about the state average. In roughly five and one half years, one death would be averted among those 66 employees and their families assuming an age distribution similar to the general population. The age distribution of the employees will likely be of working age and healthier than the general population. The deaths averted estimate is considered the potential maximum impact because it overestimates deaths averted since we did not use age-adjusted death rates. Age adjusted death rates for working age people between 18 and 55 were not available by race.

Table 13 shows that if all the minimum salary jobs are given to white residents, there would likely be no impact on individual risk of mortality since the median household income for white residents is already higher than the minimum salary. If half of the 66 jobs went to white and black residents equally, the impact on family risk for mortality would positively impact black employees’ families only.

Table 14 assumes that 10 Taylor County residents are hired for TEC jobs that pay the median salary of $49,700. Again, the greatest positive impact on employee’s family‘s risk of death is to black employees. With 10 black employees receiving the median salary jobs, a death to those employees would be averted in roughly 35 years. We do not forecast beyond the data that black employee family risk of death would be less that the state average, however the TEC median salary is much greater than the black state resident median household income. Possibly the median salary would further reduce the family mortality rate below the state rate. Therefore, it is possible that a black employee family death would be averted even before 35 years. If the 10 median salary jobs were given to white employees,’ these employees individual risk of death would decrease to around the state average as the median household income is close to the median TEC salary. As a result, we forecast that among the 10 white employees a death would be averted in almost 44 years among those 10 employees.

* Race specific age-adjusted death rates were unavailable for these calculations. This is a maximum estimate since employees are working age and healthier than the total population and their individual risk of death is probably less than the total mortality rate by race for the county used here.

Based on peer-reviewed science and this HIA's estimations, the impact from the minimum salary income from TEC could substantially reduce the risk of mortality for black employees and their families. The minimum salary would not likely improve the risk of mortality of white employees and their families. The income from TEC could address the significant racial disparities in income and mortality between black and white residents in the county. Target TEC job recruitment toward a representative or greater proportion of black residents to be trained for technical level jobs at TEC.

Based on peer-reviewed science and this HIAs estimations, the impact from the median salary income from TEC could substantially reduce the risk of mortality for both black and white employees and their families. A diverse population of Taylor County residents should be recruited and trained for professional jobs at TEC.