Chapter I

INTRODUCTION

Cougar Lake is an impoundment that is located on the campus of Southern Illinois

University Edwardsville, Madison County, Illinois. The dam was closed in 1965, and the

lake’s main purpose is to provide cooling water for the SIUE cooling plant, which has an

effluent stream located on the western shore of the lake. The approximate dimensions of

Cougar Lake are as follows: surface area of 31.4 ha, maximum depth of 11 m, mean depth of

3.9 m, total lake volume of 1.22 x 106 m3, and an epilimnetic volume of 1.16 x 106 m3. The

watershed encompasses an area of 242.9 ha, which is primarily composed of grassland,

although the shoreline of the lake is heavily wooded. There are 2 main sources of water to

the lake. Surface runoff comprises the largest influx of water, and the other source is tertiary

treated sewage effluent (recently upgraded from secondary treatment).

Cougar Lake is eutrophic due to nitrogen from the tertiary treated sewage input, and

phosphate input from the time when the plant only performed secondary treatment of

wastewater. The lake has previously been treated annually with copper sulfate for algal

control, but that practice ceased in 2002.

Cougar Lake is also dimictic. During early spring, the lake is fully mixed, with

mixing driven by wind. In summer, the lake is stratified, with 3 distinct layers: the

epilimnion (0-5 m), thermocline (5-7 m), and the hypolimnion (7-11 m). The epilimnion is

the only mixed layer, and since this is where biological activity occurs in the summer

months, most of the focus on biota shifts to this layer. In fall the lake begins to turn over

again, which leads to full mixing during the winter unless the lake becomes covered with ice.

With an ice cover, the lake becomes reverse stratified, with the coldest water located on the

2

surface of the lake. In 2002, Cougar Lake was stocked with fish, most notably largemouth

bass, to improve lake quality and recreational fishing.

Cougar Lake was created by damming off the site of a seasonal stream. That stream

was considered to be waters of the state, and thus is regulated by the Illinois Environmental

Protection Agency. The IEPA has separate sets of rules for artificial cooling ponds, and lake

systems, so when the campus air conditioning plant began to use the lake for cooling, it was

still considered under the jurisdiction of the IEPA. The difference in artificial cooling ponds

and lake systems is the biota. Usually, artificial cooling ponds do not have complex biotic

systems contained in them, and herein lays the problem. When a lake is used for cooling of

mechanical systems, the ecology of the lake, as well as the status of the biota must be

considered. The IEPA’s interest in Cougar Lake stemmed from the impact of heated effluent

on the organisms contained within this system (Robert Washburn, personal communication).

SIUE Cooling Plant:

The SIUE cooling plant is located on the campus of SIU Edwardsville, and works

similarly to a window air conditioning unit. The cooling system of central campus (campus

dormitories and Cougar Village are not cooled by the SIUE cooling plant) is a closed circuit.

There is a large reservoir, put on line in 2002, which keeps cold water in circulation

throughout pipes in the buildings that draws heat from the air (Robert Washburn, personal

communication). The heated water is brought back to the SIUE cooling plant, and lake water

is used to draw the excess heat from the water in the campus circuit.

Water from Cougar Lake is drawn from a depth of 4 meters and pumped into the

SIUE cooling plant. Within the SIUE cooling plant, indirect heat exchange occurs between

the water in the campus circuit and the lake water. The heat exchange machinery, or chillers,

operate based on temperature. At a lower temperature, there isn’t as much water needed to

3

drive the air conditioning system, so, the chillers operate under various speeds that quicken

and slow as needed (Dennis Duncan, personal communication). Running at 100% efficiency

24 hours a day, the SIUE cooling plant could cycle the epilimnion of Cougar Lake through

its system in 311 days. Water used to cool the central campus, not including the residence

halls, is pumped back into the reservoir, and the effluent from the SIUE cooling plant is lake

water plus additional heat (1° C above the surface temperature of the lake). Heated effluent

flows into the lake through an artificial stream, and enters the lake at its surface. The process

of heat exchange mostly occurs at night due to decreased energy costs at that time. With

most of the heated effluent entering the lake during the night, it is possible that as the

temperature rises, the lake may show a higher heat content at night than during the day. The

additional heat added to the solar warming during the day could lead to temporal rises in the

lake’s heat content.

Literature Review:

Over the last 30 years, engineers have been researching means of economically

cooling machinery. One of the solutions to this problem is the cooling reservoir. Cooling

reservoirs are generally defined either as ponds dug specifically for that purpose, or stream

beds dammed off to form an impoundment. Advantages of the cooling reservoir to dispose

of waste heat are: lower capital costs, low consumptive use of water, lower consumption of

energy, dissipation of waste heat over a large area to the atmosphere, and greater thermal

inertia (Majewski and Miller, 1979). A cooling reservoir gives the largest cooling capacity,

but is constrained by the large area needed for construction.

Although there is a large area demand for the construction of these reservoirs, they

are becoming more common. Some of the newest power plants that utilize lakes for cooling

are not building their own lakes, but instead are utilizing larger lakes for their cooling needs.

4

One such example is Cornell University’s cooling plant, which is located on the shore of

Lake Cayuga (Figure 1). The Cornell cooling plant operates similarly to the SIUE cooling

plant, but on a much larger scale. Differences occur in the depth at which water is drawn

from and the temperature difference at which water is put back into the lake. SIUE’s cooling

plant draws its water from 4 meters (in the epilimnion) and puts water back 1° C above the

surface lake temperature, while Cornell’s cooling plant removes its water from 250 ft

(bottom of the lake) and replaces the water at about 8° C above surface lake temperature.

Engineers calculate the design of cooling reservoirs by careful modeling, and rules of

thumb. Some of these rules of thumb are 1-2 acres of lake per megawatt of installed

capacity, or 75-150 btu of heat loss per hour per square foot. Engineers cannot always

strictly follow these rules because meteorological differences in different areas may have

large effects on the rate of heat transfer. Thus, all cases must be considered on an individual

basis (IEPA, 1971).

In addition to rules of thumb, engineering research has shown that certain design

aspects of cooling lakes provide more efficient heat dissipation than others. Research has

determined that lakes with similar surface areas can show great differences in cooling

performance. Heat transfer that occurs within the impoundment governs the amount of

surface cooling that can be attained. The most effective configuration is a deep, well-

stratified impoundment. This configuration type exhibits good steady state performance, is

density current dominated, and has excellent thermal inertia (Jirka et al., 1981). Deep,

stratified impoundments are usually wind mixed in the summer, with most of the heat being

contained in the epilimnion. Here, the wind is the agent of mixing, which allows the heat to

be homogenized within the mixed layer (Harleman, 1982). In this case, the ideal cooling

5

Figure 1: Cornell University Plant Function. (The Cornell plant utilizes the same technique as SIUE, but draws colder water from deeper water in a much deeper lake. From http://www.utilities.cornell.edu/LSC/News/WhyLSC/default.htm.)

6

lake will have a high length: width ratio as well as a large fetch (Jirka et al., 1981). The fetch

is an uninterrupted length of lake surface that will allow more powerful wind mixing

(Edmunson and Mazumder, 2002).

In some areas, construction of a deep, stratified impoundment may not be feasible. In

such instances, shallow depth cooling ponds are the only alternative. These ponds are not as

effective and tend to have problems with internal recirculation. Recirculation will lead to a

breakdown of the cooling mechanism by not allowing the pond to mix as well, which also

won’t allow for efficient surface cooling. Shallow ponds need an internal arrangement of

baffles, or below water barriers, to prevent internal recirculation zones. If only a shallow

pond design is feasible, the design of the pond should arrange the baffles to decrease the

number of directional flow changes, which will also prevent recirculation, or create a U-

shaped pond to offset the large costs of baffle design (Jirka et al., 1981).

Other criteria have been applied to cooling lakes to increase their cooling capacity.

One such method is spray cooling. Placing a fountain into a cooling lake will greatly

increase the amount of evaporative loss that can be gained from a cooling lake (up to a 20

fold increase) (Ryan, 1975). Another possible mechanism of cooling is the addition of

vegetation to the cooling pond. Miller (1974) found that costal mangrove forests may

provide increased cooling by the shade provided to the surface of the lake. The shade from

the trees could increase the turbulent transfer of heat and water vapor from the surface of the

water body. Although this study occurred in a tropical area, the advantages could be seen

throughout the temperate region with additional study.

Heat Budget:

The heat budget of a lake is the total amount of heat that is contained in a body of

water at any given time. The heat budget is calculated based on the premise that 1 calorie of

7

energy will raise 1 cm3 of water 1° C. The heat budget is expressed as the amount of heat

contained in the lake over the lake’s surface area. Studies that contain such data refer to it as

the Birgean Heat budget, named after E.A. Birge, the scientist who first calculated it. Birge

and Juday did the first such studies in 1915 at the Finger Lakes in New York (Stewart, 1974).

Juday (1940) later quantified the amount of energy contained in Lake Mendota in Madison,

Wisconsin. From his data, he contended that energy budgets of lakes at different latitudes

are different due to the amount of solar radiation that they receive. For instance, heat content

of temperate lakes will have a peak heat budget in the warm summer months, with most of

the heat being contained in the mixed epilimnion. There will be a constant amount of heat in

the non-mixed hypolimnion until periods of turnover in fall and spring when the lake is

entirely mixed. A decrease in solar radiation over the summer months should result in a

lower heat budget in a temperate lake. Conversely, a tropical lake will receive direct solar

radiation for a longer period of time. Tropical lakes are continually mixed, thus the heat is

allowed to dissipate throughout the entire lake volume, resulting in a larger heat budget.

Heat budget studies are of importance because the amount of solar radiation received

by a lake over the course of a year is the major determining factor of the changes in the

physical, chemical, and biological cycles that occur in the water column (Juday, 1940).

Changes in this heating pattern could alter these cycles greatly. Therefore, by calculating the

amount of energy gained from solar radiation and calculating the loss of surface energy due

to evaporation, it is possible to measure and quantify extraneous sources of heat such as

thermal pollution from industrial plants that use water bodies as a depository for waste heat.

A study done by Stewart (1974) utilized Birgean heat budget data to assess variation

in the heat content in lakes in Madison, Wisconsin. He assessed the impact of a power plant

thermal discharge into a dimictic lake, Lake Monona. Jets discharge heated effluent into the

8

lake at a temperature 10° C above the lake surface temperature. The power plant operated at

a capacity that would cycle the entire volume of the lake over the span of one year, but

Stewart found that the heated effluent did not cause an increase in the heat content of Lake

Monona when compared to 2 lakes without a thermal discharge. Stewart also determined

that the major influence of the heat content of Lake Monona is the local climate. Average

rise in the temperature in Lake Monona was 0.03° C per day, which is small compared with

the day-to-day variation in mean temperature (Hoopes el al., 1968). Although there is a

heated effluent released into Lake Monona, the quick dissipation of heat throughout the

volume of the lake would suggest that the impact of the power plant discharge only affects

the local discharge area (Stewart, 1974). Stewart also contends that since the climatological

variation controls the heat content of the lake, concerns about the overall impact of thermal

discharge (except at the point source discharge) in Lake Monona may be over estimated.

Thermal Pollution:

Thermal pollution is a well-documented phenomenon. Usually it is associated with

large-scale power plant cooling systems, but it can also be associated with small-scale

systems such as SIUE’s cooling plant. Addition of large quantities of waste heat into a lake

could have a very noticeable impact on the biota of that lake through physical change of the

lake shape around the discharge due to erosion from cooling plant effluent, entrapment of

organisms at the area of water intake, stress on organisms due to temperature rise, and in

some cases cooling systems may have an effect on the local climate.

If the thermal discharge is at a great enough force, such as thermal jets, the discharge

area may be structurally altered. Changes in substrate and altered currents have been

noteworthy near the discharge area in some cooling lake systems (Majewski and Miller,

1979). If these systems require a powerful intake system, any organism, most notably (but

9

not limited to) fish, will be affected within a close proximity to the intake pipe. Intake pipes

are usually fitted with screens to prevent larger organisms from entering the system, but this

does not mean that they cannot be harmed in the process. If the intake is powerful enough,

fish could be trapped onto the screens, which could cause them to be killed if they cannot

sufficiently fight the current. Impacts could be costly to the ecosystem and to fisheries if the

lake is used in this manner (Majewski and Miller, 1979; Sill and Gnilka, 1975; Voigtlander,

1980).

There are many ways that aquatic organisms could be negatively affected by thermal

discharges. Phytoplankton, zooplankton, invertebrates, and juvenile fish will be able to pass

through the entire system, which can cause death, and lessen recruitment of these organisms

(Majewski and Miller, 1979). Thermal tolerance of organisms can be exceeded.

Developmental stages of fish eggs may be especially vulnerable. If fish eggs encounter a

large increase in temperature early enough in development, the result could be abnormal

development or death. The ranges of thermal tolerance of fish eggs vary with species, and

need to be evaluated on a species by species basis (Frank, 1974). Organisms are also not

always directly harmed by heated effluent. Thermal discharges have been shown to increase

the number and abundance of pathogens in water systems. Examples of this are increases in

pathonogenic amoeba (Coutant, 1980), alteration of parasite host relationships (Bourque and

Esch, 1974), and even increased human pathogens in waters directly associated with cooling

systems (Lewis, 1980). The greatest effect, though, would be as a result of a combination of

the above factors.

Climate change could also be an expected effect of a cooling lake. Evaporative

surface cooling is an important mechanism for removal of heat from a cooling lake

(Hoffmann, 1980). Large lake systems, such as Lake Michigan, have a direct effect on the

10

climate of the surrounding environment. Large amounts of heated effluent added to larger

lakes could increase effects such as: ground level fog and ice, clouds and precipitation, and

severe weather effects (Majewski and Miller, 1979). These atmospheric effects are more

likely on a large scale, and most likely will not be seen at Cougar Lake due to the small-scale

operation of the SIUE cooling plant.

Despite many negative effects associated with thermal inputs to water systems, there

are also benefits. Fisheries could be positively impacted by an increase in water temperature.

In Cougar Lake, the best fishing is found in one of the warmest, shallowest areas of the lake

(Robert Washburn, personal communication). Thermal discharge areas have also been found

to create preferential habitat for fishes. Cooke et al. (2004) found that smallmouth bass spent

their time in the warmest areas of the water in the summer, and resided within the thermal

effluent in the winter. This example provides support that increased water temperature could

positively impact the productivity of fisheries.

Hypothesis:

I believe that the epilimnion of Cougar Lake is the major determinant of the overall

heat budget of the lake. Because Cougar Lake is dimictic, the major impact of the SIUE

cooling plant will be seen in the upper 5 meters. There is no cooling demand over the winter

months when the lake is fully mixed, whereas the bulk of the demand for cooling will be in

the summer months when the lake is stratified. Since the hypolimnion will not be affected

during the peak-cooling season, the epilimnion is where the interaction between organisms

and waste heat will take place. An addition of large amounts of heat could potentially have

an adverse impact on the top 5 meters of Cougar Lake. My hypothesis is that during the

summer months, the heat put into Cougar Lake by the SIUE cooling plant will raise the

overall heat budget of the lake.

11

Chapter II

METHODS:

Data on the heat budget of Cougar Lake were collected over a period of two years

(2003-2004). In 2003, measurements were taken during the period from March 12 –

December 15, and in 2004 from March 31 – December 16. HOBO© data loggers, 6 x 4

centimeter microprocessors, were used to take water temperature measurements every two

hours during the study period. To prevent water damage, data loggers were placed in water

tight containers with drying packs after being enclosed in whirl pack bags.

Data loggers were placed in a string of pearls configuration using buoys as a float and

marker, a 2.5 kg circular plate as an anchor, rock-climbing clips to attach containers to the

rope, and fishing weights to prevent the sensors from floating outside the desired depth

(Figure 2). In 2003 the measured depths were: 0, 1, 3, 5, 6, 7, 9, and 11 meters. In 2004 the

measured depths were from 0 – 11 meters with a sensor present at each meter interval.

Measurements of air temperature were also obtained by placing a data logger in a whirl pack

bag and a plastic container, which was then attached to the shaded side of a tree on the lake

shore. This sensor was placed in the shade to prevent excess heating from direct sunlight.

My primary sampling site was located near the outflow spillway in the northernmost

arm of Cougar Lake (Figure 3). The array was placed in the deepest part of the lake (12

meters), located northeast of the SIUE cooling plant discharge stream. The array was

stationary except during periods of inclement weather (high winds), where it tended to move

in the range of ~ 5 – 10 meters. The area of each lamina, 1-meter deep increment, of the lake

was calculated by first taking 40 – 50 depth samples throughout the lake. Depth samples

12

Figure 2: Sensor Array. (Sensors were attached to rope using rock climbing clips at 1 m intervals from 0-11 m. The array was anchored using a 2.5 kg circular weight, and floated using a buoy.)

13

Figure 3: Sampling Site Location. (Sample site, indicated by a star, and depth contours for 2, 5, 8, and 11 meters. My sampling site was located in the deepest part of Cougar Lake.)

0 0.2 0.4

kilometers

11

85

2

14

were completed by R. Brugam and C. Guo and are reported in Guo (2001). Each sampling

point was marked with GPS coordinates. The measured coordinates were placed on a map of

Cougar Lake in the MapInfo© computer program, and contour lines were drawn around

coordinates with similar depth measurements. Areas of each lamina were then calculated

using the MapInfo© GIS System (Richard Brugam, personal communication).

My sampling site was reached using a boat equipped with a 6 horsepower motor.

Once in place, the boat was anchored in position and the sensor array was removed from the

water for downloading. Care was taken not to remove the array from its position during

times when measurements were being taken. Data from the sensors were downloaded using

an Onset Computer Corporation HOBO Shuttle© data transporter. After sensors were

downloaded, point measurements of light, dissolved oxygen, temperature, and secchi disc

transparency were taken before returning to the lab to download data onto the computer.

Data from the HOBO shuttle© was downloaded to the Onset Boxcar© computer

program, and then exported to a Microsoft excel spreadsheet as a text file. Data from 3/12 –

8/15/2003 were obtained from a previous study by Micah Miranda to complete the

temperature profile for that year. Temperature profiles for both 2003 and 2004 were graphed

in degrees Celsius as a line graph and an isopleth diagram. For some particular days,

temperature was plotted as a line graph to show anomalies in data.

Temperatures in degrees Celsius were first converted to energy for all measured

laminae in cal/cm3 using the formula:

(1) Thickness of lamina (m)* Area of lamina (m)* temperature (Celsius) * 106 (cm)

The thickness of the lamina for equation 1 would be 1 for both 1 and 6 meters deep because

they were only one m thick. The thickness of the lamina 3, 5, 7, 9, and 11 meters deep would

be 2 because these sensors were used to calculate heat for laminae without sensors.

15

Summation of the energy for the laminae was then used to generate the heat budget for 2003

and 2004. Heat budgets were then calculated in Kcal/ cm2 for the entire lake using the

equation:

∑ energy of laminas (Kcal*cm-3) (2) (surface area of lake (m2)* (1 * 106 cm)

In 2004, all laminas were measured, so equation I from above was used to generate the

energy for each lamina because there were no unmeasured laminas to account for. A heat

budget for the epilimnion (0 – 5 meters) was calculated for 2003 and 2004 using equation 2

from above.

I then obtained temperature data from two previous studies done by Rosen (1978) and

Brugam (personal communication). Data from these previous studies were used to calculate

a heat budget for both the entire lake and the epilimnion for 1975 and 1990. Equation 1 was

used to generate energies for each lamina because all were measured, and equation 2 was

used to generate heat budgets. After all heat budgets were calculated, scatter graphs were

made showing heat budgets for the entire lake and the epilimnion. Next separate heat budget

compilation graphs were made for the Cougar Lake, which contained data from 1975, 1990,

2003, and 2004.

When the final temperature data were calculated, I obtained data from the SIUE

cooling plant. Lee Hoffmeier, manager of the SIUE cooling plant, was contacted and

reported that at 100% efficiency, 12000 btu of heat per hour would be produced for each of

the 3 chillers. The amount of heat produced by the SIUE cooling plant in Kcal/ cm2 for both

2003, and 2004 was calculated using the equation:

(3) Total hours running * operating efficiency * 18.3 million btu * 252 (calories/ btu) * 0.001

(Kcal/cal) (Surface area of the lake (m2)* 1 * 106 cm)

16

After the amount of heat contributed per day from the SIUE cooling plant was calculated, it

was totaled to determine the amount of heat contributed by the SIUE cooling plant over the

course of the year.

Total heat input from the SIUE cooling plant for 2003 and 2004 was then compared

to heat loss from the lake. Pan evaporation data from Belleville, IL were obtained from Jim

Angel, Illinois State Climatologist, and the total evaporative loss from the pan was then used

to calculate the amount of heat lost from the lake per month (Kcal/cm2) using following

equation:

(4) Water evaporated from pan (cm) * pan evaporation coefficient * latent heat of

vaporization of water (cal/cm3) * 0.001 Kcal/ cal

Heat rise per day of Cougar Lake was calculated for 2003 and 2004 by subtracting the

maximum heat budget of a given day from the maximum heat budget of the previous day.

A multiple regression analysis was done to determine the effect of both mean daily

temperature and SIUE cooling plant output on the heat rise in Cougar Lake from one day to

the next. The multiple regression analysis was done on a day by day basis within the year for

both 2003 and 2004. Daily mean temperature and SIUE cooling plant output were lagged by

two days for each year to ensure that there were no effects of either variable on the heat rise

of Cougar Lake for following days. In addition to the time lag analysis, scatter graphs were

made for both years comparing the epilimnetic heat budget to the daily heat input from the

SIUE cooling plant to further assess any effect from the SIUE cooling plant.

Finally, data loggers were placed horizontally from the SIUE cooling plant effluent

stream for one week starting on 3/31/2005 and ending on 4/14/2005. Data loggers were

placed in an arc and their locations were marked using GPS positioning (Figure 4). I wanted

to determine if a temperature input from the plant could be detected. Detection of a plume of

17

Figure 4: Sensor placement for Horizontal Temperature Profile. (Sensors radiated outward from the effluent stream marked by stars.)

18

heated effluent would be determined by increased temperature of the water near the SIUE

cooling plant effluent stream, and lower temperatures away from the effluent stream. Timing

of placement of data loggers was picked so that there would be a period of SIUE cooling

plant inactivity followed by a period of activity. This particular timing was chosen because it

would mark the initial activation of the SIUE cooling plant for the year 2005. If there was a

plume of heated effluent, I would expect to see increased water temperatures closest to the

effluent stream between 4/1 and 4/3/2005. Data were then collected, downloaded, and

plotted in a line graph.

19

Chapter III

RESULTS

2003: The vertical temperature profile for 2003 shows a maximum temperature of 32.76° C

at 1 m on 7/8, and a minimum temperature of 4.57° C at 11 m on 12/14. The upper

temperature limit was taken from 1 m because the sensor located at 0 m was partially

exposed at the water surface, and was influenced by direct solar radiation (Figure 5). The

heat budget showed a maximum heat content of 13.85 kcal/cm2 on 8/26, and a minimum heat

content of 2.439 kcal/cm2 on 3/13 (Figure 6). Most of the heat in Cougar Lake is contained

within the epilimnion (first 5 meters). Figure 6 shows that the heat budget of the epilimnion

closely follows the contours of the heat budget for the entire lake, and the hypolimnion heat

budget does not. Thus, the majority of the heat in the lake is contained in the epilimnion,

which drives the warming and cooling of the lake. The hypolimnion (6-11 m) little effect on

the heat budget of Cougar Lake in the summer because it remains constant. It becomes

increasingly important during fall turnover, because its heat budget rises as Cougar Lake

turns over, allowing a greater range of habitat for biota.

The heat input from the SIUE cooling plant shows a maximum of 0.071 Kcal/cm2 on

8/20, which coincides with the return of students to campus after summer break. The

minimum heat input from the SIUE cooling plant, on days when it was running, was 0.0044

Kcal/cm2 on 11/26. Minimal cooling is needed in the cooler months of the year. The total

amount of heat that was added to Cougar Lake from the SIUE cooling plant in 2003 was 6.6

Kcal/cm2 (Figure 7).

20

5

5

10

10

10

10

15

15

15

15

1515

15

15

15

10

10

10

10

10

1010

10

1515

20

20

20

20

20

2020

20

20

25

25

25

25

2530 30

30303030

30

3030

302020

20

20202020

10

10

10

10

10

10

5

5

55

5

5

5

5

5

DayApr May Jun Jul Aug Sep Oct Nov Dec

Dep

th (m

)

2

4

6

8

10

Figure 5: 2003 Vertical Temperature Profile. (Data for 0 meters was omitted in the diagram (isopleth) because the sensors were exposed to direct solar radiation.)

21

Day

Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2003

Hea

t Bud

get (

Kca

l/cm

2 )

0

2

4

6

8

10

12

14

16Total LakeEpilimnionHypolimnion

Figure 6: 2003 Heat Budget. (The epilimnion curve closely follows the curve for the entire lake, suggesting the driving force in heat content for 2003 is the epilimnion (0-5 m). Data points were calculated using equation 2.)

22

Day

Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Run

ning

tota

l of P

lant

Hea

t Inp

ut p

er d

ay (K

cal/

cm2

0

1

2

3

4

5

6

7

Figure 7: 2003 Air Conditioning Plant Output. (The total amount of heat that could have been added by the air conditioning plant in 2003 was 6.6 Kcal/cm2. Heat addition data were calculated by taking a running sum of the values from equation 3.)

23

Multiple regression analysis showed that the heat rise in the lake per day is not

correlated with the heat input From the SIUE cooling plant for that day (p = 0.671). The

mean daily temperature, though, is correlated with the rise in lake temperature for that day (p

= 0.00005). The multiple regression when daily mean temperature and SIUE cooling plant

heat were lagged for 1 and 2 days shows that the heat added from the SIUE cooling plant

does not affect the temperature in the lake for the days following the heated effluent release

into Cougar Lake( p = 0.459, 0.770) (Figure 8). Mean daily temperature correlated with the

mean daily air temperature for the following day (p = 0.026), but loses its correlation with the

heat rise of the lake after 2 days (p = 0.324) (Figure 8). The r-values for the multiple

regressions were as follows: 0.12 for the same day, 0.02 lagged one day, and 0.006 lagged 2

days. These r-values show that for the same day, only 12% of the variation is explained on

the same day, 2% is explained lagged one day, and < 1% is explained by the regression when

lagged 2 days. The overall heat budget of Cougar Lake shows a similar pattern to the heat

input of the SIUE cooling plant per day, because warmer days will increase cooling demand

(Figure 9).

Table 1: SIUE Cooling Plant Output. (Maximum and minimum output values from the SIUE cooling plant in 2003 and 2004 which were calculated using equation III.)

2003

Heat

(Kcal/cm2) Date Maximum Plant

Input 0.071 8/20/2003 Minimum Plant

Input 0.004 11/26/20032004

Heat

(Kcal/cm2) Date Maximum Plant

Input 0.082 6/18/2004 Minimum Plant

Input 0.004 3/29/2004

24

SIUE Cooling Plant Output (cal * 106)

0 50 100 150 200 250

Res

idua

l Hea

t Ris

e

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0a.)

Daily Mean Temperature (Deg C)

-5 0 5 10 15 20 25 30 35

Lake

Hea

t Ris

e (K

cal/c

m2 )

-3

-2

-1

0

1

2d.)

SIUE Cooling Plant Operation (cal * 106)

0 50 100 150 200 250

Res

idua

l Hea

t Ris

e +

1

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0b.)

Daily Mean Temperature (Deg C)

-5 0 5 10 15 20 25 30 35

Lake

Hea

t Ris

e +

1 (K

cal/c

m2 )

-3

-2

-1

0

1

2e.)

SIUE Cooling Plant Operation (cal * 106)

0 50 100 150 200 250

Res

idua

l Hea

t Ris

e +

2

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0c.)

Daily Mean Temperature (Deg C)

-5 0 5 10 15 20 25 30 35

Lake

Hea

t Ris

e +

2 (K

cal/c

m2 )

-3

-2

-1

0

1

2f.)

Figure 8: 2003 Multiple Regression Analysis. (Letters a-c show residual heat rise of Cougar Lake vs. SIUE cooling plant operation. The SIUE cooling plant has no effect on the heat rise in the lake for any day (p = 0.671, 0.459, 0.770). Letters d-f show lake heat rise vs. daily mean temperature. Daily mean temperature has an effect on the heat rise of Cougar Lake for 1 day (p = 0.00005, 0.026), but loses its correlation at 2 days (p = 0.324).)

25

Julian Day

Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2003

Epi

limni

on H

eat B

udge

t (K

cal/c

m2 )

0

2

4

6

8

10

12

14

day vs epilimnion heat budget

Dai

ly P

lant

Hea

t Out

put (

Kca

l)

0

1e+8

2e+8

3e+8

4e+8

5e+8

plant day vs plant heat

Figure 9: 2003 Epilimnion Heat Budget and Daily Plant Heat Output. (On warmer days, there is an increased demand for cooling, so there will be more plant activity, thus more heat output from the plant.)

26

Evaporative heat loss from Cougar Lake showed a maximum of 8.99 Kcal/cm2 for the

month of July, and a minimum of 5.571 Kcal/cm2 for the month of September. Total

evaporative heat loss for Cougar Lake in 2003 was 36.54 Kcal/cm2 (Figure 10). Evaporative

heat loss from the lake surface far exceeds the heat input from the SIUE cooling plant when

comparing the total amount of heat that could have been contributed to the lake from the

SIUE cooling plant (6.6 Kcal/cm2) to that of the evaporative loss of the lake (36.54

Kcal/cm2). On 7/18, the maximum heat budget of Cougar Lake was reached at 12 am

(Figure 11). Thus the SIUE cooling plant may have a small warming effect on Cougar Lake

on particular nights.

2004: The vertical temperature profile for 2004 shows a maximum temperature of 34.43º C

at 1 m on 7/22, and a minimum temperature of 5.4º C at 11 m on 12/16. Again, the upper

temperature limit was taken from 1 m because the sensor located at 0 m was partially

exposed at the water surface, and was easily influenced by solar radiation (Figure 12). The

heat budget showed a maximum heat content of 14.39 Kcal/cm2 on 7/22 and a minimum heat

content of 2.94 Kcal/cm2 on 12/16 (Figure 13). Again most of the heat in the lake is

contained in the epilimnion, and there is little to no contribution to the heat budget by the

hypolimnion (Figure 13). The same patterns were seen as 2003, where the hypolimnion heat

content continued to rise as the Cougar Lake’s heat budget decreased, which signals that the

hypolimnion is warming due to fall turnover.

Heat input from the SIUE cooling conditioning plant shows a maximum of 0.082

Kcal/cm2 on 6/18, and a minimum for days it was running was 0.0044 Kcal/cm2 on 3/29.

The total amount of heat that could have been added to Cougar Lake in 2004 from the SIUE

cooling plant was 5.806 Kcal/cm2 (Figure 14).

27

Month

MAY JUN JUL AUG SEP total

Lak

e Su

rfac

e E

vapo

rativ

e L

oss (

Kca

l/ cm

2 )

0

10

20

30

40

2003 2004

Figure 10: Evaporative Loss from Lake Surface. (The total surface area evaporation in Cougar Lake was 36.54 Kcal/cm2 for 2003, and 35.65 Kcal/cm2 for 2004. Monthly surface evaporative loss was calculated using equation 4, and the total evaporative loss was calculated by summing the monthly totals.)

28

Day in July 2003

16 17 18 19 20 21

Hea

t Bud

get (

Kca

l/ cm

2 )

12.3

12.4

12.5

12.6

12.7

12.8

Figure 11: Heat Budget from 7/ 16 – 7/ 21/ 2003. (The maximum heat content of Cougar Lake on 7/18 was attained at 12am, suggesting that the campus air conditioning plant may raise the heat of Cougar Lake on some nights. Heat budget calculated using equation 2.)

29

5

10

10

10

10

10

10

10

15

15

15

15

15

1515

15

15

2020

2020

2525

25

25

252525

10

1010

30

30

30

30

25252525

252525

20

2525

10

1515

151510

Day

May Jun Jul Aug Sep Oct Nov Dec

Dep

th0

2

4

6

8

10

Figure 12: 2004 Vertical Temperature Profile. (Data for 0 meters was omitted in the diagram (isopleth) because the sensors were exposed to direct solar radiation.)

30

Day

Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2004

Hea

t Bud

get (

Kca

l/cm

2 )

0

2

4

6

8

10

12

14

16

Total LakeEpilimnionHypolimnion

Figure 13: 2004 Heat Budget. (The epilimnion curve closely follows the curve for the entire lake, suggesting the driving force of the heat content of the lake in 2004 is the epilimnion. Heat Budgets calculated using equation 2.)

31

Day

Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Hea

t Add

ed F

rom

Pla

nt P

er D

ay (K

cal/c

m2 )

0

1

2

3

4

5

6

7

Figure 14: 2004 Air Conditioning Plant Output. (The total amount of heat that could have been added to Cougar Lake by the plant in 2004 was 5.964 Kcal/cm2. Heat addition data were calculated by taking a running sum of the values from equation 3. )

32

Multiple regression analysis showed that the heat rise in the lake per day is not

correlated with the heat input from the SIUE cooling plant for that day (p = 0.852), but the

mean daily temperature was correlated with the rise in lake temperature for that day (p =

0.0068). The multiple regression when daily mean temperature and SIUE cooling plant heat

were lagged for 1 and 2 days showed similar results to 2003. The heat added from the SIUE

cooling plant does not affect the temperature in the lake for the days following the heated

effluent release into Cougar Lake (p = 0.254, 0.150) (Figure 15). Mean daily temperature

loses its correlation with heat rise of the lake on the following day, a shorter time period than

in 2003 (p = 0.704) (Figure 15). The r-values for the multiple regressions were as follows:

0.04 for the same day, 0.009 lagged one day, and 0.01 lagged 2 days. These r-values show

that for the same day, only 4% of the variation is explained on the same day, < 1% is

explained lagged one day, and 1% is explained by the regression when lagged 2 days.

Similarly to 2003, heat input from the SIUE cooling plant showed a similar increase to the

overall heat budget of the lake, because warmer days would require a larger cooling demand

(Figure 16).

Sensors were placed horizontally outward from the SIUE cooling plant effluent

stream (Figure 4) to attempt to detect a plume of warm water entering Cougar Lake (Figure

17). Sensors 1 and 3 were omitted due to a mechanical malfunction. There is a daily

temperature cycle in Cougar Lake, with the maximum temperature peaking between 11am –

2pm, which can be attributed to the natural daily warming rather than SIUE cooling plant

effluent.

Evaporative loss from Cougar Lake in 2004 showed a maximum of 8.39 Kcal/cm2 for

July, and a minimum of 5.964 Kcal/cm2 for September. Total evaporative loss from the lake

in 2004 was 35.65 Kcal/cm2 (Figure 10). These numbers were slightly lower than

33

SIUE Cooling Plant Operation (Cal * 106)

0 50 100 150 200 250 300

Res

idua

l Hea

t Ris

e

-2

-1

0

1

2

3

a.)

Daily Mean Temperature (Deg C)

-5 0 5 10 15 20 25 30 35

Lake

Hea

t Ris

e +

2 (K

cal/c

m2 )

-3

-2

-1

0

1

2c.)

SIUE Cooling Plant Operation (cal * 106)

0 50 100 150 200 250 300

Res

idua

l Hea

t Ris

e +

1

-2

-1

0

1

2

3b.)

Daily Mean Temperature (Deg C)

5 10 15 20 25 30 35

Lake

Hea

t Ris

e +

1 (D

eg C

)

-2

-1

0

1

2

3

d.)

Figure 15: 2004 Multiple Regression Analysis. (Letters a and b mark the residual heat rise of Cougar Lake vs. SIUE cooling plant operation. The SIUE cooling plant has no effect on the heat rise in the lake for either day (p = 0.852, 0.254). Letters c and d show lake heat rise vs. daily mean temperature. Daily mean temperature has an effect on the heat rise of Cougar Lake for the day the measurement was taken (p = 0.0068), but loses its correlation the following day (p = 0.704).)

34

Dai

ly P

lant

Hea

t Inp

ut (K

cal)

0

1e+8

2e+8

3e+8

4e+8

5e+8Daily Plant Heat Input

Day

Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2004

Epi

limni

on H

eat B

udge

t (K

cal/c

m2 )

0

2

4

6

8

10

12

14Epilimnion Heat Budget

Figure 16: 2004 Epilimnion Heat Budget and Daily Plant Heat Output. (On warmer days, there is an increased demand for cooling, so there will be more plant activity, thus more heat output from the plant.)

35

Day

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Tem

pera

ture

(Deg

C)

10

12

14

16

18

sensor 2 sensor 4 sensor 5

sensor 6sensor 7

Figure 17: Horizontal Temperature Profile from 3/ 31 – 4/ 14 2004. (Each peak appears between 11am and 2pm indicating that the variation temperature in Cougar Lake is a factor of the local climate.)

36

evaporative loss in 2003. Total evaporative loss of Cougar Lake far exceeded the input from

the SIUE cooling plant when comparing the total amount of heat that could have been added

by the SIUE cooling plant (5.806 Kcal/cm2) and the total evaporative loss of Cougar Lake

(35.65 Kcal/cm2).

1975, 1990, 2003, and 2004 Comparison:

Figure 18 compares heat budgets from 1975, 1990, 2003, and 2004. Data for 1975

and 1990 were collected using temperature probe data taken approximately once monthly.

For each year, heat budgets follow a similar pattern of warming and cooling. The major

differences between the years are the rapidity of the increase in lake heat content and the time

of peak heat content.

In 1975, the lake showed a similar warming and cooling pattern as 2003. The

rapidity of the increase and decrease in heat content was similar, although 1975 shows lower

values at most points sampled. Data points for 1975 also show similar peaks to 2003, with

data points following similar patterns of variation throughout the year. There were not as

many data points sampled in 1975, so we cannot determine the maximum heat content.

Very few data points were available for 1990, but heat content values for this year are

consistently lower for this year than all other years. The increase and decrease of heat

content shows similar patterns to each other year, and maximum heat content seems to peak

around the same time as 2003.

The heat budget for 2004 was the least similar to the other 3 years. Each year the

maximum heat content was shown at around day 250, but in 2004 the peak was seen 50 days

earlier. The lake seemed to accumulate heat more quickly in 2004 than the other 3 years, and

also showed a sharper peak during the period of maximum heat content. Each other year

showed a more gradual incline to the maximum heat content. In 2004, the heat content of the

37

Julian Day

50 100 150 200 250 300 350 400

Hea

t Bud

get (

Kca

l/ cm

2 )

0

2

4

6

8

10

12

14

16

19901975

2003 2004

Figure 18: Heat Budget Comparison: 1975, 1990, 2003, and 2004. (Data for the years 1975, 1990, and 2003 follow similar patterns of increase, decrease, and peak heat budgets The year 2004 shows a similar pattern of decrease as the other years, but a quicker increase in total heat budget and an earlier peak heat budget. Heat budgets were calculated using equation 2.)

38

lake sharply decreased after the maximum heat occurs. The heat content then stayed

relatively constant during the period where maximum heat is attained in 2003, 1990, and

1975. The decrease in heat content for 2004 then closely follows that of 2003.

39

Chapter IV

DISCUSSION

If the heat budget of Cougar Lake is to be measured accurately, all factors regarding

heat flux into and out of the lake must be taken into account. These factors are defined in the

following equation:

(5) ∆ Heat in Cougar Lake (Kcal/cm2) = Solar Radiation (Kcal/cm2) + Heat from plant

(Kcal/cm2) – atmospheric heat loss (Kcal/cm2)

There are other processes that also can account for thermal energy in a lake, but were

neglected in Cougar Lake due to their minimal impact. These processes are: conduction of

heat from the earth’s crust, transformation of kinetic energy into heat, heating due to

chemical processes, and heating due to biological activity (Saur and Anderson, 1955). We

have also ignored possible heat input from sewage effluent. The above equation was

modified from Saur and Anderson’s by the removal of the gain of heat by advection. Cougar

Lake does not have a constant input from a tributary, so this term does not apply. If my

results are calculated according to equation 5, solar radiation entering the lake can be

determined (Table 2). For both study years, loss of heat to the atmosphere exceeds the

amount of heat added by the SIUE cooling plant by a factor of six. The large discrepancy

between heat added by solar radiation and from the SIUE cooling plant indicates that a

majority of the heat budget of Cougar Lake is a result of solar radiation, which agrees with

Dutton and Bryson’s (1962) findings that the flux of heat through the interface with the

atmosphere is the major source of the heat involved in internal thermal processes of a lake.

40

Although there seems to be no effect on the lake’s heat budget for 2003 and 2004, the

heat budget data suggest that the SIUE cooling plant may have had an impact on the lake

from 1975-2004. From 1975-2004, 205188.6 m3 of building space was added to SIUE

(Washburn, Personal Communication). Thus, the large amount of additional cooling load

may have increased the heat budget of the lake because of the additional SIUE cooling plant

effluent. Although this may seem to be intuitive, the maximum heat budget for 1990 (11.44

Kcal/cm2) is lower than that of 1975, but with 132903.4 m3 of additional building space

requiring cooling. The discrepancy in heat budget from 1975 (12.47 Kcal/cm2) and 1990 to

2004 (14.39 Kcal/cm2) seems to be large, but most likely is a result of insufficient data from

1975 and 1990. For the years 2003 and 2004, I was able to obtain heat measurements from

the lake every 2 hours. In 1975 and 1990, the technology wasn’t available to do such

detailed temperature sampling, so the data for those years were taken once weekly, or even

once monthly. The large gaps of data in 1975 and 1990 may have missed the peak heat

budget for those years, and if the same amount of data was obtained, there might not have

been such a large discrepancy in heat budget values.

Table 2: Calculated Solar Radiation Values. (Show that a majority of the heat flux in Cougar Lake stems from the interaction of the lake surface and the atmosphere. Both evaporative loss and solar input greatly exceed the amount of heat generated by the campus air conditioning plant. Solar radiation was calculated using equation 5.)

Year

Heat Contained in Cougar

Lake (Kcal/cm2)

Solar Radiation

(Calculated) (Kcal/cm2)

Heat From Plant

(Kcal/cm2)

Heat Lost to atmosphere (Kcal/cm2)

2004 13.85 43.79 6.6 36.54

2003 14.39 44.234 5.806 35.65

1990 11.44 N/A N/A N/A

1975 12.47 N/A N/A N/A

41

Although solar radiation is one of the major determinants of the heat budget of a lake

(Benson et al., 2000), morphometry is also important when looking at the lake’s heat budget

(Timms, 1975; Mazumder and Taylor, 1994; Gorham, 1964). The most important aspects of

the morphometry of a lake are surface area, fetch, and mean depth. The surface area of a

lake determines the amount of solar radiation that enters that lake. A lake with a larger

surface area, in general, should have a higher heat budget due to an increased amount of solar

penetration. Also, a larger surface area will, in most cases, create a larger fetch.

In a lake, wind induced mixing determines the depth of the epilimnion and

thermocline and along with evaporative loss, determines the amount of heat retained in the

water column (Ambrosetti and Barbanti, 2001). Therefore, if the fetch is larger, more heat

can be retained in the lake because powerful wind mixing will allow heat to be dissipated

over a larger volume of water.

Mean depth is cited as one of the most important morphometric characteristics of a

lake in many studies (Timms, 1975; Mazumder and Taylor, 1994; Gorham, 1964). Deeper

water columns provide larger capacity to store heat, so a deeper lake with a cold hypolimnion

potentially stores more heat than a shallow lake. Although a deeper lake may have a greater

potential to store heat, it also has to have a large surface area and fetch for there to be a

marked increase in heat content. Without a long fetch, the wind mixing will be less

powerful, decreasing both the depth of the epilimnion and the heat content of the lake. A

large surface area will also allow for larger amounts of heat penetration (through solar

radiation), and a large amount of surface evaporation, which potentially could increase the

heat content of the lake. Both Cougar Lake, and on a larger scale, Cayuga Lake fit this

model.

42

Due to financial constraints, we were not able to obtain heat data from a similarly

sized lake without a thermal input. Although we do not have a full data set, Cougar Lake’s

maximum heat budget can be compared to the maximum heat budget of Lake Waubesa,

Madison, Wisconsin (Stewart, 1973). My reason to compare the heat budgets of these 2

lakes is because of the similarity of their mean depths (Cougar Lake 3.9 m, Lake Waubesa

4.6m). Maximum heat budget of Cougar Lake (13.85 Kcal/cm2 in 2003, 14.39 Kcal/cm2 in

2004) was larger than the mean heat budget of Lake Waubesa over a 3-year period, even

though Lake Waubesa has a larger mean depth. Mean depth is usually directly correlated

with heat content; with a higher mean depth being associated with increased heat content. In

this case, the larger mean depth of Lake Waubesa does not signify larger heat content.

The difference in the heat content of Cougar Lake and Lake Waubesa can result from

many variables. The first is solar radiation. Solar radiation becomes less intense the farther

north of the equator a site is. Thus, less direct solar radiation will mean less heat input to the

lake (Benson et al., 2000). Similarly, at higher latitudes, the temperature could be lower,

potentially lessening the influence of atmospheric heat exchange with the lake surface.

Stewart’s (1973) data also shows variation in the heat budget between years in Lake

Waubesa similar to the heat budget variation in Cougar Lake from 2003 to 2004. From

1962-1963, Lake Waubesa had an increase in the maximum heat budget from 10.95

Kcal/cm2 to 11.74 Kcal/cm2, an increase of 0.8 Kcal/cm2. From 2003-2004, Cougar Lake

showed an increase in the heat budget from 13.85 Kcal/cm2 to 14.39, an increase of 0.54

Kcal/cm2. The increase in the heat budget of Lake Waubesa, a lake without thermal input, in

that 2 year period exceeded the heat budget increase for Cougar Lake over the period from

2003-2004, which suggests that the heat content of both lakes is driven by local climatic

conditions. Even though there is a varying amount of thermal discharge (5.964-6.6

43

Kcal/cm2) in Cougar Lake between years, the change in the heat budget is less than the

change in the heat budget of Lake Waubesa, which would suggest that there is no large-scale

impact of the SIUE cooling plant on the heat budget of Cougar Lake.

Multiple regression analysis showed that for both years, the heat input from the SIUE

cooling plant did not correlate with the heat rise in Cougar Lake. The mean daily

temperature and heat input from the SIUE cooling plant were lagged to assess the impact of

the heated effluent and daily temperature for 2 days. There was no correlation with the input

from the SIUE cooling plant for any of the days following discharge, which shows that there

must be another factor that influences the rise in heat content of Cougar Lake. One factor

that could play a role in influencing lake heat content is the mean daily temperature. In 2003,

the mean daily temperature positively correlated with the temperature of the day the

measurement was taken, as well as the next day. In 2004, the mean daily temperature

positively correlated with the temperature of the day the measurement was taken, but lost its

correlation the following day.

The multiple regression results show that daily mean temperature is a major

determinant of the heat content of Cougar Lake, but it isn’t the only factor. The r-values that

were generated from the multiple regression showed a maximum of .12 and a minimum of

< 0.001. This means that only 12% of the variation in the heat rise in Cougar Lake is

explained by the regression of daily mean temperature and SIUE cooling plant heat against

the heat rise in Cougar Lake. Therefore there are other factors that I have not measured that

have an impact on the change in heat content of Cougar Lake. Examples of such factors are,

but not limited to: rain input, differing amounts of solar radiation input, and humidity in the

air. Any of these factors could contribute to the amount of heat contained in Cougar Lake, or

44

lost to the atmosphere. So, to have an accurate assessment of the driving force of the heat

content of Cougar Lake, these other factors must be taken into account.

The amount of heat cycled through Cougar Lake is much larger than both the amount

of heat contained in the lake and produced by the SIUE cooling plant. Table 1 shows that the

amount of solar radiation exceeds the amount of heat put into the lake by the SIUE cooling

plant by a factor of 7-8 for both years. The amount of evaporative loss for both years

exceeds the amount of heat from the SIUE cooling plant by a factor of ~ 6. Evaporative loss

from the surface of Cougar Lake in a single month is almost equal to, or exceeds, the amount

of heat generated by the SIUE cooling plant over the entire growing season. The large

surface area of Cougar Lake allows for a large amount of evaporation, which leads to a high

amount of heat loss from the evaporated water. The loss of heat through evaporation is the

major reason that allows the heat budget of Cougar Lake to resist changes in heat content that

would be associated with the input of heat from the SIUE cooling plant.

To further assess any impact from the SIUE cooling plant, we determined the

horizontal temperature profile stretching outward from the SIUE cooling plant’s effluent

stream. The SIUE cooling plant, if operating at 100%, would be able to cycle the epilimnion

of Cougar Lake within 311 days. The hypolimnion would not be considered here because the

SIUE cooling plant operates from late spring to fall when the lake is stratified. Therefore, the

mixed layer will not affect water in the hypolimnion, with most heat being contained in the

epilimnion. Water entering the lake from the SIUE cooling plant is only 1° C above the

surface temperature of the lake. The large amount of time it would take to cycle the entire

epilimnion, as well as the small difference in temperature between the surface of the lake and

the effluent, would suggest there should be little to no difference in the temperature readings

of the sensors as the water radiates outward from the SIUE cooling plant effluent stream.

45

Figure 17 shows that there is a temporal cycle for temperature, with peaks occurring each day

between 11am – 2 pm. These peaks are consistent with the maximum temperature and solar

radiation over the course of the day. If an effect of the SIUE cooling plant were to be seen,

peaks would likely occur between 11 pm – 2 am coinciding with the hours of the most

intense SIUE cooling plant operation. There is no plume of heat that is detected from the

effluent stream, the heat from the SIUE cooling plant is most likely dissipated quickly

throughout the epilimnion and lost to evaporation.

Although we did not detect a heat plume outward from the SIUE cooling plant

effluent stream, there may still be a detectible plume present. Sensors 1 and 3, which were

two of the closest sensors to the SIUE cooling plant effluent, malfunctioned and we were

unable to gather data from them. Sensor 1, being closest to the effluent stream, was the most

likely sensor to detect a plume of heat from the effluent stream. Because I could not obtain

these data, it still may be possible that there is a slight temperature plume present. Sensor 7

shows a slightly higher temperature than the rest of the array, which may suggest for some

days when the wind is blowing to the north, the heated effluent reaches sensor 7. Another

possible explanation for the higher temperature reading at sensor 7 may be lake

morphometry. Sensor 7 is in a shallower basin than the other sensors, and if the solar

radiation could penetrate deep enough to warm the substrate of the lake, the temperature at

that spot in the lake would be warmer than in deeper areas.

When Cougar Lake is assessed using the criteria outlined by Jirka et al (1981), it

seems that it is a well-engineered cooling lake. The first such criterion is that the best

cooling lake would be a deep, well-stratified impoundment. Cougar Lake is deep enough to

become stratified, and most of the heat contained in the lake in the summer months is in the

epilimnion, which makes the heat available for evaporation from the surface. Other criteria

46

included a large fetch, which allows for wind mixing allowing the heat to be homogenized

throughout the epilimnion to create a deeper epilimnion (Strub et al., 1985). Cougar Lake

has a long fetch, which allows for a deeper epilimnion, and a continuous cycling of the water

throughout the epilimnion in the summer months (depending on weather patterns). Research

had shown that lakes with similar surface areas showed differences in their ability to

dissipate heat to the atmosphere. Cougar Lake has a large surface area, and when combined

with the long fetch and deep epilimnion, will allow it to dissipate a larger amount of heat

than a shallower lake with a shorter fetch and a similar surface area.

Because a majority of Cougar Lake’s heat comes from solar radiation, it is highly

unlikely that the SIUE cooling plant has a large-scale effect on the heat content of the lake.

Although there may not be any large changes in the heat content of Cougar Lake, there still is

a possibility that there is a small effect of the SIUE cooling plant. Linear regressions for both

2003 and 2004 show a slight upward slope, which indicates that there may be a slight effect

from the SIUE cooling plant, even though the overall data wouldn’t lead to that conclusion.

In 2004, heat input of the SIUE cooling plant was less than 2003, but the heat budget in 2004

was higher. Those heat budget data suggest that the SIUE cooling plant isn’t having an

effect because by that logic, an increased heat load from the SIUE cooling plant would also

show an increased heat content in the lake. Although the heat maximum data for the year

may be inconsistent with the idea that the SIUE cooling plant is affecting the lake, the heat

content for some days may suggest otherwise.

For some nights, the heat content of Cougar Lake reaches the maximum between 10

pm and 2 am. The maximum heat peaking at midnight opposes the view that the maximum

heat content should occur at the time of the maximum air temperature and solar radiation

(between 12-2 pm). Maximum heat content occurring at midnight is consistentnt with the

47

operation of the SIUE cooling plant. The SIUE cooling plant mainly operates at night, due to

lower energy costs. If the SIUE cooling plant operates heavily at night, there should be a

visible effect during the nighttime hours. So, even though a large scale effect is not seen as a

result of the heat input from the SIUE cooling plant, it is still possible that there may be a

small scale effect on the heat content of Cougar Lake at some times of the day and year.

From our data, it seems that concerns over the effect of the SIUE cooling plant on Cougar

Lake may be overestimated.

48

Chapter V

CONCLUSION

Various techniques were utilized to assess the impact, if any; the SIUE cooling plant

has on Cougar Lake. Although there was an increase in the heat content in the lake from

2003 to 2004, it is unlikely that the variation in heat is a result of the SIUE cooling plant’s

activities. Multiple regression analyses determined that the SIUE cooling plant effluent does

not correlate with the rise in the heat content of the lake following discharge for either year

(p = 0.671, 0.459 lagged one day in 2003, 0.852, 0.254 lagged one day in 2004). There also

was not a detectable plume radiating outward from the SIUE cooling plant’s effluent stream.

Climatic variation (temperature and solar radiation) is the major determining factor of

the heat content of Cougar Lake. Multiple regression analysis showed that the mean daily air

temperature correlated with the heat rise in the lake for the day the measurement was

recorded, and for the following day in 2003 (p = 0.00005, 0.026 lagged one day and 0.324

lagged 2 days). The mean daily air temperature correlated with the heat rise in for the day

the measurement was taken, but lost its correlation the following day (0.0068, 0.704 lagged

one day).

The amount of solar radiation that enters the lake, as well as the amount of heat that

evaporated from the surface is considerably larger than the heat discharged from the SIUE

cooling plant. The heat that the SIUE cooling plant discharges is most likely quickly

dissipated throughout the epilimnion, and then lost through evaporation.

Although I did not detect a large-scale effect from the SIUE cooling plant, there may

be a small-scale effect. Such an effect may be detected in the shallow area nearest the SIUE

49

cooling plant’s effluent stream. Overall, the concerns of the impact of the SIUE cooling

plant may be overestimated.

I reject my hypothesis that during the summer months, the heat put into Cougar Lake

by the SIUE cooling plant will raise the overall heat budget of the lake. Climatological

variation, such as solar radiation and daily temperature, is the major determinant of the heat

content of Cougar Lake.

50

LITERATURE CITED

Ambrosetti, W., and Barbanti, L. 2001. Temperature, Heat Content, Mixing, and Stability in Lake Orta: A Pluriannual Investigation. J. Limnol. 60 (1): 60-68. Benson, B. J., Lenters, J. D., Magnuson, J. J., Stubbs, M., Kratz, T. K., Dillon, P. J., Hecky, R. E., and Lathrop, R. C. 2000. Regional Coherence of Climatic and Lake Thermal Variables of Four Lake Districts in the Upper Great Lakes Region of North America. Freshwater Biology. 43: 517-527. Coutant, C. 1980. Pathogenetic Amoebae. In: Internal Atomic Energy Agency Environment effects of Cooling Systems. IAEA, Austria. P 121-124. Cooke, S. J., Bunt, C. M., and Schreer, J. F. 2004. Understanding Fish Behavior, Distribution, and Survival in Thermal Effluents Using Fixed Telemetry Arrays: A Case Study of Smallmouth Bass in a Discharge Canal During Winter. Environmental Management, 33 (1): 140-150. Dutton, J. A., and Bryson, R. A. 1962. Heat Flux in Lake Mendota. Limnol. Oceanogr. 7: 80-97. Edmunson, J. A., and Mazumder, A. 2002. Regional and Hierarchical Perspectives of Thermal Regimes in Subarctic, Alaskan Lakes. Freshwater Biology, 47: 1-17. Harleman, D. R. F. 1982. Hydrothermal Analysis of Lakes and Rivers. Proceedings of the ASCE. 108: 302-323. Frank, M. L. 1974. Relative Sensitivity of Different Developmetnal Stages of Carp Eggs to Thermal Shock. In: Thermal Ecology. Editor: Gibbons, J. W., and Sharitz, R. R. Technical Information Center US Atomic Energy Commission, Virginia. P 171-176. Gorham, E. 1964. Morphometric Control of Annual Heat Budgets in Temperate Lakes. Limnol. Ocanogr. 26: 525-529. Guo, C. 2002. Accumulation of Copper Algaecide in the Sediment of Cougar Lake, a Small Illinois Reservoir. M.S. Thesis, Southern Illinois University Edwardsville. P 1–75. Hoopes, J. A., Zeller, R. W., and Rohlich, G. A. 1968. Heat Dissipation and Induced Circulations From Condensor Cooling Water Discharges into Lake Monona. Univ. Wis. Agr. Exp. Sta. Res. Rep. 35. 204. IEPA. 1971. Effect of Geographic Location on Cooling Pond Requirements and Performance. US Government Printing Office, Washington DC.

51

Jirka, G. H., Cerco, C. F., and Harleman, D. R. F. 1981. Efficient Cooling Ponds: Design. Proceedings of the ASCE. 107: 1547-1563. Juday, C. 1940. The Annual Energy Budget of and Inland Lake. Ecology. 21(4): 138-150. Lewis, B. G. 1980. Human Disease Organisms in Aerosols From Cooling Towers and Cooling Sprays. In: Internal Atomic Energy Agency Environment effects of Cooling Systems. IAEA, Austria. P 124-129. Majewski, W., and Miller, D. C. 1979. Predicting Effects of Power Plant Once-Through Cooling on Aquatic Systems. United Nations Educational, Scientific, and Cultural Organization, Paris. Mazumder, A., and Taylor, W. D. 1994. Thermal Structure of Lakes Varying in Size and Water Calrity. Limnol. Oceanogr. 39 (4), 968-976. Miller, P. C. 1974. Potential Use of Vegetation to Enhance Cooling in holding Ponds In: Thermal Ecology. Editor: Gibbons, J. W., and Sharitz, R. R. Technical Information Center US Atomic Energy Commission, Virginia. P 610-627. Rosen, M. G. 1978. A Limnological Survey of Tower Lake, Madison County, Illinois, with Special Reference to Artificial Aeration. M.S. Thesis, Southern Illinois University Edwardsville. P 1-166. Ryan, P. J. 1975. Heat Dissipation by Spray Cooling. In: Thermal Pollution Analysis. Editor: Schetz, J. A. MIT Press. Cambridge. P 139-152. Saur, J. F. T., and Anderson, E. R. 1956. The Heat Budget of a body of Water of Varying Volume. Limnol. Oceanogr. 1: 247-521. Sill, B. L., and Gnitka, A. 1975. Optimal Discharge of Power Plant Cooling Waters. In: Thermal Pollution Analysis. Editor: Schetz, J. A. MIT Press. Cambridge. P 281- 293. Stewart, K. M. 1974. Detailed Time Variations in Mean Temperature and heart Content of Some Madison Lakes. Limnol. and Ocean. 18(2): 218-226. Strub, P. T., Powell, T., and Goldman, C. R. 1985. Climatic Forcing: Effects of El Nino on a Small, Temperate Lake. Science. 227: 55-57. Timms, B. V. 1975. Morphometric Control of Variation in Annual Heat Budgets. Limnol. Oceanogr. 20: 110-112. Voigtlander, C. 1980. Effects of Cooling Water Intakes on Fish Populations: Entrainment and Impingement. . In: Internal Atomic Energy Agency Environment effects of Cooling Systems. IAEA, Austria. P 60-78.

52

APPENDIX

2003 2004

Day Heat

Content

Heat From SIUE

Cooling Plant

Daily Mean Air

Temperature Day Heat

Content

Heat From SIUE

Cooling Plant

Daily Mean Air

Temperature 12-

Mar 3.0017 0 14.492 1-Apr 5.1930 13834800 4.5913-

Mar 2.4971 0 11.27 2-Apr 5.3711 85314600 6.5814-

Mar 2.9651 0 5.603 3-Apr 5.4526 101455200 7.8115-

Mar 3.1948 0 11.4675 4-Apr 5.5970 36892800 9.4816-

Mar 3.7821 0 13.2295 5-Apr 5.8019 46116000 6.4417-

Mar 3.4678 9223200 14.127 6-Apr 5.9192 73785600 8.8818-

Mar 3.4849 59950800 15.665 7-Apr 6.0662 0 14.9019-

Mar 3.7189 59950800 14.595 8-Apr 6.1579 92232000 16.9620-

Mar 3.7189 59950800 11.932 9-Apr 6.3126 0 12.4721-

Mar 3.5337 59950800 9.066510-Apr 6.1991 78397200 11.31

22-Mar 3.7013 41504400 9.8035

11-Apr 6.1348 0 10.01

23-Mar 3.9276 55339200 14.7625

12-Apr 5.8432 64562400 8.21

24-Mar 4.3836 59950800 16.894

13-Apr 5.8452 36892800 7.88

25-Mar 3.9127 59950800 9.812

14-Apr 6.1411 55339200 7.48

26-Mar 4.2603 41504400 9.9645

15-Apr 6.4678 92232000 10.57

27-Mar 5.1282 23058000 14.5265

16-Apr 6.5971 110678400 15.36

28-Mar 4.8054 18446400 10.2015

17-Apr 7.0606 94076640 21.96

29-Mar 4.1201 55339200 2.3855

18-Apr 9.6535 64562400 23.40

30-Mar 4.2004 9223200 2.6125

19-Apr 50727600 24.60

31-Mar 4.5346 32281200 8.7715

20-Apr 103299840 22.17

1-Apr 6.2168 73785600 19.88521-Apr 50727600 20.63

2-Apr 6.4266 76091400 20.05522-Apr 72402120 18.69

53

3-Apr

7.0862

101455200

23.2223-Apr 64562400 13.31

4-Apr 6.6564 92232000 15.525524-Apr 55339200 12.11

5-Apr 6.1949 92232000 5.97325-Apr 0 14.14

6-Apr

6.3694 32281200 2.5145

26-Apr 59950800 11.27

7-Apr 6.2186 11529000 8.469527-Apr 122207400 12.97

8-Apr 5.9959 34587000 3.148528-Apr 64562400 10.94

9-Apr 5.8539 0 5.379529-Apr 0 19.04

10-Apr 6.0945 9223200 7.3385

30-Apr 46116000 18.73

11-Apr 6.1686 55339200 11.4315

1-May 80703000 17.93

12-Apr 27669600 14.7275

2-May 23058000 11.41

13-Apr 80703000 15.3285

3-May 46116000 9.61

14-Apr 9223200 19.42

4-May 7.8681 53033400 8.88

15-Apr 73785600 20.99

5-May 8.1109 110678400 13.91

16-Apr 101455200 17.86

6-May 8.6505 0 18.50

17-Apr 64562400 10.84

7-May 8.7480 110678400 23.32

18-Apr 0 14.33

8-May 9.2464 209827800 23.40

19-Apr 46116000 17

9-May 9.3914 41504400 23.03

20-Apr 50727600 14.93

10-May 9.4864 0 23.30

21-Apr 53033400 11.045

11-May 9.6845 0 22.03

22-Apr 36892800 10.7415

12-May 9.7046 0 22.83

23-Apr 36892800 11.2

13-May 9.6339 0 20.34

24-Apr 46116000 12.295

14-May 9.2980 69174000 19.64

25-Apr 23058000 10.81

15-May 9.0917 36892800 13.88

26-Apr 36892800 11.901

16-May 9.3107 87620400 14.54

27-Apr 83008800 14.6935

17-May 9.4989 71479800 15.20

28-Apr 73785600 18.26

18-May 9.7026 46116000 21.80

29-Apr 106066800 19.69

19-May 9.5722 73785600 22.70

54

30-Apr 115290000 21.625

20-May 9.8932 0 22.77

1-May 103761000 18.795

21-May 10.3038 0 25.66

2-May 94537800 12.835

22-May 10.4510 138348000 25.52

3-May 64562400 13.3645

23-May 10.3077 27669600 24.03

4-May 66868200 13.175

24-May 10.4631 0 22.46

5-May 25363800 20.855

25-May 10.5099 119901600 22.46

6-May 106066800 19.09

26-May 10.3188 0 20.67

7-May 106066800 18.655

27-May 10.3235 78397200 15.77

8-May 99149400 16.24

28-May 10.1392 0 22.76

9-May 110678400 25.28

29-May 10.4839 110678400 22.20

10-May 115290000 21.485

30-May 10.5979 83008800 20.37

11-May 64562400 14.435

31-May 10.5421 73785600 23.13

12-May 39198600 15.5 1-Jun 10.4079 0 18.1413-

May 48421800 16.7 2-Jun 10.4651 117595800 18.6014-

May 10.0865 99149400 18.225 3-Jun 10.4738 110678400 18.1715-

May 10.2461 73785600 18.29 4-Jun 10.3558 0 18.2716-

May 10.1787 73785600 16.1 5-Jun 10.5209 0 18.5117-

May 10.1946 64562400 17.235 6-Jun 10.5517 0 19.8418-

May 10.3770 92232000 20.585 7-Jun 10.7442 0 21.6619-

May 10.3784 73785600 21.795 8-Jun 11.0587 119901600 24.0320-

May 10.2648 110678400 14.34 9-Jun 10.9326 83008800 26.4621-

May 10.5328 83008800 13.1710-Jun 11.0612 145265400 22.10

22-May 10.7015 57645000 13.4665

11-Jun 11.2089 124513200 24.92

23-May 10.7348 69174000 14.1365

12-Jun 11.2893 175240800 26.56

24-May 10.6401 59950800 14.505

13-Jun 11.3871 18446400 23.14

25-May 10.4277 18446400 15.7

14-Jun 11.4635 78397200 23.86

26-May 10.6137 59950800 15.395

15-Jun 11.5525 119901600 25.43

27-May 10.6850 73785600 17.73

16-Jun 11.5145 166017600 24.76

55

28-May 8.7789 0 19.16

17-Jun 11.6454 156794400 25.26

29-May 8.7977 101455200 18.36

18-Jun 11.7299 258249600 25.56

30-May 9.2009 96843600 19.595

19-Jun 11.5406 175240800 23.57

31-May 8.8627 73785600 17.605

20-Jun 11.4873 46116000 18.21

1-Jun 8.8185 83008800 13.99521-Jun 11.3711 92232000 18.00

2-Jun 8.7931 11529000 11.6822-Jun 11.2808 92232000 20.90

3-Jun 8.5767 39198600 12.83523-Jun 11.0880 119901600 17.24

4-Jun 8.5119 11529000 16.03524-Jun 11.1986 129124800 18.87

5-Jun 8.7533 73785600 16.92525-Jun 11.0524 87620400 22.80

6-Jun 8.7139 64562400 14.83526-Jun 10.9668 87620400 16.88

7-Jun 8.8766 55339200 20.4627-Jun 11.0539 87620400 17.87

8-Jun 9.0818 0 19.0928-Jun 11.1147 46116000 18.81

9-Jun 9.0221 46116000 19.6629-Jun 11.1627 147571200 20.50

10-Jun 9.1972 87620400 21.66

30-Jun 11.2862 0 20.20

11-Jun 9.4143 103761000 21.355 1-Jul 11.4346 179852400 21.5412-Jun 9.3663 89926200 23.115 2-Jul 11.5696 0 23.7313-Jun 9.6475 96843600 22.32 3-Jul 11.5108 89926200 25.2314-Jun 9.5279 106066800 22.025 4-Jul 11.6176 221356800 23.4015-Jun 9.8031 73785600 22.625 5-Jul 11.6270 106066800 25.9616-Jun 9.8442 69174000 22.76 6-Jul 11.6806 119901600 24.6617-Jun 10.0887 69174000 23.155 7-Jul 11.6116 119901600 24.3318-Jun 10.1539 119901600 23.59 8-Jul 11.6626 119901600 21.9019-Jun 10.1108 110678400 20.225 9-Jul 11.8394 119901600 23.5320-Jun 10.4244 64562400 16.895

10-Jul 12.0088 156794400 26.83

21-Jun 10.4585 110678400 18.93

11-Jul 13.3213 64562400 26.26

22-Jun 10.4917 64562400 20.16

12-Jul 13.3692 124513200 27.56

23-Jun 10.5250 108372600 22.36

13-Jul 13.5484 166017600 26.66

24-Jun 10.6564 119901600 24.185

14-Jul 13.7059 161406000 29.09

56

25-Jun 10.9779 110678400 25.06

15-Jul 13.7824 110678400 23.64

26-Jun 10.7539 115290000 18.755

16-Jul 13.7010 0 23.17

27-Jun 10.9886 76091400 19.765

17-Jul 13.5109 202910400 24.27

28-Jun 11.0737 101455200 22.525

18-Jul 13.4372 119901600 22.00

29-Jun 10.9836 59950800 23.925

19-Jul 13.5318 92232000 22.03

30-Jun 11.2414 92232000 23.755

20-Jul 13.5365 92232000 22.66

1-Jul 11.3345 115290000 24.08521-Jul 13.9708 89926200 26.87

2-Jul 11.3469 112984200 25.34522-Jul 14.0362 92232000 29.19

3-Jul 11.6576 115290000 26.81523-Jul 13.8423 0 28.03

4-Jul 11.8535 110678400 28.4524-Jul 13.4666 32281200 24.13

5-Jul 11.8471 55339200 27.9525-Jul 12.5579 0 18.60

6-Jul 12.0766 124513200 27.88526-Jul 12.5743 142959600 16.28

7-Jul 12.1720 101455200 27.7827-Jul 12.7294 119901600 19.47

8-Jul 12.4500 140653800 28.1228-Jul 11.7658 119901600 19.54

9-Jul 12.3120 140653800 27.8229-Jul 11.8324 0 20.07

10-Jul 12.2236 133736400 23.825

30-Jul 11.6310 0 21.34

11-Jul 12.3733 135581040 23.565

31-Jul 11.5811 110678400 19.17

12-Jul 12.2594 124513200 23.33

1-Aug 11.7382 101455200 24.20

13-Jul 12.3419 87620400 22.525

2-Aug 11.8719 92232000 24.60

14-Jul 12.4364 101455200 23.69

3-Aug 11.9685 0 25.37

15-Jul 12.4040 110678400 25.79

4-Aug 12.2204 0 28.16

16-Jul 12.5665 129124800 24.125

5-Aug 11.9735 101455200 25.14

17-Jul 12.6347 119901600 27.015

6-Aug 11.8113 0 19.28

18-Jul 12.5757 221356800 22.665

7-Aug 11.8476 83008800 17.67

19-Jul 12.6958 110678400 24.59

8-Aug 11.9041 83008800 18.64

20-Jul 12.8917 101455200 25.925

9-Aug 11.8903 41504400 20.24

21-Jul 12.9350 159100200 24.965

10-Aug 11.9689 110678400 22.27

22-Jul 12.7416 168784560 21.895

11-Aug 11.8840 83008800 21.17

57

23-Jul 12.6975 110678400 20.36

12-Aug 11.5784 73785600 16.21

24-Jul 12.7765 166939920 20.36

13-Aug 11.2958 69174000 14.22

25-Jul 12.7979 154488600 21.86

14-Aug 11.1666 69174000 15.65

26-Jul 12.7701 101455200 24.195

15-Aug 11.1053 36892800 16.84

27-Jul 12.7768 115290000 28.98

16-Aug 11.1211 46116000 17.57

28-Jul 12.8390 147110040 23.49

17-Aug 11.2550 83008800 18.51

29-Jul 12.8415 140653800 22.525

18-Aug 11.4516 133736400 22.73

30-Jul 12.7289 85314600 22.195

19-Aug 11.5209 142959600 26.07

31-Jul 12.9410 138348000 24.56

20-Aug 11.4986 92232000 24.73

1-Aug 12.8187 103761000 25.355

21-Aug 11.4009 124513200 17.48

2-Aug 12.8252 59950800 24.125

22-Aug 11.5504 110678400 20.57

3-Aug 12.9013 94076640 23.765

23-Aug 11.7124 124513200 20.74

4-Aug 12.7656 93615480 24.795

24-Aug 11.6314 161406000 23.20

5-Aug 12.8658 178930080 24.16

25-Aug 11.4863 119901600 23.37

6-Aug 12.8817 134197560 23.56

26-Aug 11.6245 244414800 23.97

7-Aug 12.8619 126819000 24.265

27-Aug 11.8033 149877000 27.03

8-Aug 12.9243 107911440 23.495

28-Aug 11.7841 124513200 26.90

9-Aug 12.9802 140192640 22.525

29-Aug 11.5439 96843600 24.17

10-Aug 12.9780 83008800 22.59

30-Aug 11.4024 101455200 16.62

11-Aug 12.9643 64562400 22.625

31-Aug 11.5076 96843600 18.97

12-Aug 12.9243 64562400 21.895

1-Sep 11.5355 119901600 21.84

13-Aug 12.9597 138348000 22.595

2-Sep 11.6806 221356800 21.77

14-Aug 12.9150 111600720 26.085

3-Sep 11.6730 126819000 21.38

15-Aug 13.0193 101455200 26.945

4-Sep 11.7890 142959600 21.87

16-Aug 13.1460 149877000 28.05

5-Sep 11.9395 87620400 24.43

17-Aug 13.1922 101455200 29.315

6-Sep 11.8302 32281200 23.87

18-Aug 13.4637 119901600 27.58

7-Sep 11.5712 83008800 20.31

19-Aug 13.4065 159100200 26.75

8-Sep 11.4032 96843600 18.28

58

20-Aug 13.5925 224123760 28.515

9-Sep 11.2928 80703000 17.81

21-Aug 13.6039 142037280 31.785

10-Sep 11.3323 27669600 17.81

22-Aug 13.6516 132814080 26.395

11-Sep 11.4058 136042200 19.91

23-Aug 13.5934 82086480 24.025

12-Sep 11.3734 64562400 20.57

24-Aug 13.6203 62717760 24.925

13-Sep 11.4528 110678400 20.87

25-Aug 13.7552 135119880 27.86

14-Sep 11.5383 136042200 22.57

26-Aug 13.6135 207522000 29.85

15-Sep 11.6888 103761000 22.97

27-Aug 13.7490 147571200 25.985

16-Sep 11.6381 92232000 23.60

28-Aug 13.6729 157255560 27.785

17-Sep 11.4887 110678400 20.87

29-Aug 13.6555 84392280 24.565

18-Sep 11.4505 0 18.77

30-Aug 13.5870 48998250 23.69

19-Sep 11.3337 0 18.87

31-Aug 13.3529 110678400 25.45

20-Sep 11.2431 36892800 20.41

1-Sep 13.2904 64562400 20.27

21-Sep 11.1181 110678400 18.21

2-Sep 12.9574 128202480 18.505

22-Sep 11.0297 96843600 17.94

3-Sep 12.8909 110678400 22.125

23-Sep 11.0863 66868200 19.13

4-Sep 12.7020 107450280 18.805

24-Sep 11.0274 193687200 20.34

5-Sep 12.6158 87620400 18.265

25-Sep 11.0147 83008800 20.70

6-Sep 12.4676 124513200 18.265

26-Sep 10.9956 78397200 21.10

7-Sep 12.4204 64562400 19.435

27-Sep 10.8296 55339200 18.37

8-Sep 12.5454 46577160 20.035

28-Sep 10.6943 221356800 16.44

9-Sep 12.5454 104222160 20.5

29-Sep 10.5105 96843600 16.11

10-Sep 12.6107 133275240 21.665

30-Sep 10.4163 50727600 13.28

11-Sep 12.7162 149877000 22.86 1-Oct 10.3531 69174000 15.3712-

Sep 12.6060 140653800 22.165 2-Oct 10.0978 55339200 16.4713-

Sep 12.5336 110678400 21.47 3-Oct 9.8791 23058000 10.3714-

Sep 12.3417 59950800 17.91 4-Oct 9.6618 103761000 13.2415-

Sep 12.1326 71940960 18.47 5-Oct 9.4584 59950800 11.6116-

Sep 12.1905 146187720 19.37 6-Oct 9.3874 50727600 9.78

59

17-Sep 12.2569 123936750 18.77 7-Oct 9.2681 69174000 13.2118-

Sep 12.1901 138348000 20.8 8-Oct 9.3892 138348000 18.0419-

Sep 12.0269 92232000 13.775 9-Oct 9.2638 129124800 18.3020-

Sep 11.8442 64562400 13.90810-Oct 9.1717 32281200 16.11

21-Sep 12.3085 73785600 16.54

11-Oct 9.0210 69174000 14.90

22-Sep 12.0951 78397200 19.04

12-Oct 8.8763 112984200 13.91

23-Sep 12.0321 119901600 16.67

13-Oct 8.8469 80703000 12.48

24-Sep 12.1459 78397200 22.86

14-Oct 8.5022 0 14.20

25-Sep 11.9454 112984200 14.305

15-Oct 8.4891 0 9.59

26-Sep 11.8981 83008800 18.035

16-Oct 8.1597 0 10.08

27-Sep 11.5865 18446400 14.905

17-Oct 8.0509 46116000 8.48

28-Sep 11.2165 13834800 10.913

18-Oct 7.6287 55339200 11.07

29-Sep 10.8747 55339200 10.407

19-Oct 7.5701 55339200 14.04

30-Sep 10.5280 32281200 7.387

20-Oct 7.5749 0 11.35

1-Oct 10.1010 50727600 10.47221-Oct 7.5289 83008800 11.81

2-Oct 9.9420 43810200 6.87422-Oct 7.6461 92232000 13.91

3-Oct 9.4350 46116000 7.420523-Oct 8.1158 64562400 19.47

4-Oct 9.3139 59950800 14.9324-Oct 8.2619 101455200 19.17

5-Oct 9.4547 64562400 15.67525-Oct 8.2166 80703000 15.54

6-Oct 9.4148 69174000 18.4326-Oct 8.1207 115290000 17.31

7-Oct 9.5697 69174000 18.127-Oct 8.1159 145265400 16.75

8-Oct 9.6705 84853440 18.2328-Oct 8.2164 85314600 17.05

9-Oct 9.6213 110678400 16.07529-Oct 8.6526 48421800 20.44

10-Oct 9.7241 106066800 19.96

30-Oct 8.7411 41504400 24.00

11-Oct 10.1346 115290000 17.91

31-Oct 8.5284 27669600 15.11

12-Oct 9.9548 55339200 14.735

1-Nov 8.4185 55339200 14.28

13-Oct 10.0318 53033400 14.4345

2-Nov 8.2148 110678400 16.55

14-Oct 9.7997 77936040 12.841

3-Nov 7.8641 0 12.38

60

15-Oct 9.5596 115290000 13.2055

4-Nov 7.6811 0 7.15

16-Oct 9.4836 101455200 14.77

5-Nov 7.5266 0 8.19

17-Oct 9.2866 59950800 9.8055

6-Nov 7.3304 0 7.22

18-Oct 9.2652 66868200 13.4375

7-Nov 7.3548 0 14.61

19-Oct 9.3032 62256600 18.43

8-Nov 7.2117 0 12.28

20-Oct 9.5356 71479800 21.87

9-Nov 7.0080 0 7.55

21-Oct 9.3300 106066800 18.035

10-Nov 6.9645 0 8.48

22-Oct 9.2920 101455200 14.375

11-Nov 6.8489 0 12.55

23-Oct 9.2815 87620400 14.008

12-Nov 6.6244 0 10.18

24-Oct 9.3862 96843600 14.9695

13-Nov 6.3276 0 4.36

25-Oct 9.1512 108372600 13.815

14-Nov 6.0742 0 3.59

26-Oct 8.7952 9223200 5.4505

15-Nov 6.0374 0 6.45

27-Oct 8.6630 32281200 7.8815

16-Nov 6.1139 27669600 11.11

28-Oct 8.4012 29975400 9.939

17-Nov 6.3985 87620400 12.31

29-Oct 8.2604 29975400 9.9065

18-Nov 6.4300 0 16.37

30-Oct 8.2984 55339200 15.0355

19-Nov 6.3833 0 12.28

31-Oct 8.1644 110678400 18.4

20-Nov 6.4863 0 12.55

1-Nov 8.1237 62256600 9.94

21-Nov 6.2854 0 11.45

2-Nov 8.2452 83008800 17.935

22-Nov 6.1864 0 8.15

3-Nov 8.3992 64562400 20.325

23-Nov 6.1280 0 8.15

4-Nov 8.3992 124513200 17.9

24-Nov 5.9904 0 11.08

5-Nov 8.2092 73785600 5.8825

25-Nov 5.6641 0 4.25

6-Nov 7.8686 36892800 1.456

26-Nov 5.3446 0 0.19

7-Nov 7.5126 0 2.751

27-Nov 5.2333 0 8.72

8-Nov 7.1207 0 0.855

28-Nov 5.2274 0 7.49

9-Nov 6.8805 0 3.3175

29-Nov 4.9405 0 2.95

10-Nov 6.8304 0 7.148

30-Nov 4.8921 0 4.89

11-Nov 6.7727 27669600 15.705

1-Dec 4.7741 0 3.16

61

12-Nov 6.8284 103761000 12.739

2-Dec 4.5823 0 3.42

13-Nov 6.5644 46116000 3.283

3-Dec 4.5225 0 3.65

14-Nov 6.2602 0 2.75

4-Dec 4.3791 0 3.58

15-Nov 6.1064 18446400 6.652

5-Dec 4.2991 0 7.12

16-Nov 6.0876 9223200 11.1735

6-Dec 4.3508 0 4.12

17-Nov 6.1454 39198600 10.3475

7-Dec 4.4575 0 10.65

18-Nov 6.1454 73785600 13.715

8-Dec 4.3735 0 6.29

19-Nov 6.3065 46116000 10.775

9-Dec 4.3791 0 2.52

20-Nov 6.3563 80703000 14.5375

10-Dec 4.2610 0 8.25

21-Nov 6.4608 78397200 13.141

11-Dec 4.1573 0 3.92

22-Nov 6.5646 46116000 14.905

12-Dec 4.0029 0 0.66

23-Nov 6.3065 59950800 9.248

13-Dec 3.8427 0 4.23

24-Nov 5.9358 0 -0.5465

14-Dec 3.5288 0 -0.91

25-Nov 5.5168 0 1.518

15-Dec 3.2101 0 -4.35

26-Nov 5.5168 13834800 5.3835

16-Dec 3.0188 0 -1.25

27-Nov 5.3146 53033400 8.07728-

Nov 4.9567 0 -0.20929-

Nov 4.6613 94537800 2.0530-

Nov 4.4939 0 10.7731-

Dec 4.4139 0 4.7762-

Dec 4.3147 0 4.51553-

Dec 4.1419 0 3.0534-

Dec 4.0241 0 3.78755-

Dec 3.8090 0 1.1226-

Dec 3.5900 0 -0.5777-

Dec 3.5975 0 2.68658-

Dec 3.5900 0 4.85459-

Dec 3.8090 0 11.145

62

10-Dec 3.6674 0 4.27811-

Dec 3.3739 0 -3.64412-

Dec 3.1546 0 -4.445513-

Dec 2.9420 0 -2.445514-

Dec 2.7139 0 -4.4735