1. Fracking Chemical Influence on Algal Populations
By: Sam Little
Pittsburgh Central Catholic
PJAS 2018
Grade 9

2. Problem
Does a simulation formula of a fracking solution have an effect on algal populations?

3. Fracking Runoff into local watershed?
A process of retrieving natural gas from deep below the Earth’s surface
After the main bore hole is drilled, a mixture is pumped down it
Water – 90%
Sand – 9.5%
Additives - 0.5%
Companies use a “proprietary blend” of chemicals in the additives
The primary concern is the impact of the additives on the environment
Runoff into local watershed?

4. Variable
A formula that has been used in other studies regarding the additives in fracking
It is a simulation because fracking companies’ actual formula is not known
Chemicals
Mg/L
Calcium Chloride
16.650
Magnesium Chloride
0.4750
Barium Chloride
0.1851

5. Algae Good model for showing over-all aquatic heath
Used in this experiment
Euglena
Chlamydomonas
These two species are common and excellent lab models
Primary Producers

6. Euglena gracilis Unicellular, algal-like, Protist
Very common in nature
Live in fresh and brackish water rich in organic matter
Autotroph and heterotroph

7. Chlamydomonas reinhardtii
Unicellular, algal-like protists
Biflagellate
Cup-shaped Chloroplast
Commonly found in soil 
and fresh water ponds

8. Purpose
The purpose of this experiment is to determine if a fracking simulation formula will have an effect on algal populations.

9. Hypothesis
Null Hypothesis- The fracking simulation formula will not have a significant effect on algal populations.
Alternative Hypothesis- The fracking simulation formula will significantly reduce algal growth.

10. Materials Euglena gracilis (Carolina Science)
Chlamydomonas reinhardtii (Carolina Science)
Test Tubes – 100mm x 13mm Borosilicate culture tubes
Pipettes
Micro
Macro
Spectrophotometer
Test Tube Rack
Fracking Simulation Formula
Soil Water
Spring Water
Wax Paper

11. Procedure The test tube rack was filled with 24 tubes in a single row.
The temperature of the testing room was set to 20 degrees Celsius and the rack was placed next to a window
The variable, model, and waters were mixed in the following manner to create the desired concentrations.

12. Test Tube Mixtures Ingredients 0% 0.1% 0.5% 1% Algae 1 ml 1ml
Soil Water
Spring Water
3 ml
2.71 ml
1.53 ml
0.06 ml
Formula
0 ml
0.29 ml
1.47 ml
2.94 ml

13. Procedure
Each tube was mixed by inversion before it was placed into the spectrophotometer.
The spectrophotometer was set to 430nm
The absorbance was recorded for each test tube once a day for 10 days.

14. P-Value
P-Value
P-Value

15. P-Value
P-Value
P-Value

16. Conclusion ANOVA failed to reject the null hypothesis
There was not significant variation among the groups
The fracking simulation formula did not have a significant effect on the growth of algae

17. Limitations and Future Research
Health of Culture- the model was not subjected to optimal growing conditions
The variable – actual fracking additives
Temperature – window?
Optimal Lighting
The Spectrophotometer and tubes- slight drift in readings
Future Research
Optimal lighting
Test different species of algae
Try other ingredients in the fracking simulation formula
Vary simulation fracking formula exposures
Interaction effect with other variables in watershed

18. Works Cited “Algae” Algae Facts, 2017, https://kids.britannica.com
 The Editors of Encyclopædia Britannica. ?Chlamydomonas.? Encyclopædia Britannica, Encyclopædia Britannica, Inc., 2 Mar ,  The Editors of Encyclopædia Britannica. ?Chlamydomonas.? Encyclopædia Britannica, Encyclopædia Britannica, Inc., 2 Mar ,  The Editors of Encyclopædia Britannica. ?Euglena.? Encyclopædia Britannica, Encyclopædia Britannica, Inc., 27 Dec , 
“What Is Fracking?” What Is Fracking?, 2017, 
“What Is Groundwater?” What Is Groundwater?, 2017, 

19. Spectrophotometry
Machine used to measure the amount of light passing through a medium
Useful in chemistry, physics, biochemistry, material and chemical engineering

20. Averages Euglena Chlamy 0% 0.10% 0.50% 1% 0.122 0.111 0.118 0.105
0.122
0.111
0.118
0.105
0.086
0.095
0.097
0.089 1
0.108
0.081
0.096
0.075
0.068
0.09
0.084
0.067 2
0.102
0.077
0.088
0.072
0.091
0.092
0.083 3
0.1
0.076
0.078
0.082
0.099 4
0.07
0.085
0.062
0.044 5
0.028
0.032
0.034
0.074
0.093
0.101 6
0.063
0.061
0.046
0.117 7
0.053
0.039
0.052
0.129
0.106 8
0.065
0.047
0.049
0.103
0.124
0.15
0.12 9
0.079
0.045
0.054
0.05
0.126
0.157
0.176
0.141 10
0.041
0.131
0.162
0.144

21. ANOVA Euglena Day 2 Anova: Single Factor SUMMARY Groups Count Sum
Average
Variance
Column 1 3
0.309
0.103
Column 2
0.23
3.73E-05
Column 3
0.265
5.43E-05
Column 4
0.216
0.072
ANOVA
Source of Variation SS df MS F
P-value
F crit
Between Groups
Within Groups 8
Total 11

22. ANOVA Euglena Day 6 Anova: Single Factor SUMMARY Groups Count Sum
Average
Variance
Column 1 3
0.188
Column 2
0.183
0.061
9.1E-05
Column 3
0.139
9.23E-05
Column 4
0.137
ANOVA
Source of Variation SS df MS F
P-value
F crit
Between Groups
Within Groups 8
Total 11

23. ANOVA Euglena Day 10 Anova: Single Factor SUMMARY Groups Count Sum
Average
Variance
Column 1 3
0.204
0.068
Column 2
0.162
0.054
Column 3
0.225
0.075
Column 4
0.124
6.33E-06
ANOVA
Source of Variation SS df MS F
P-value
F crit
Between Groups
Within Groups 8
Total 11

24. ANOVA Chlamydomonas Day 2
Anova: Single Factor
SUMMARY
Groups
Count
Sum
Average
Variance
Column 1 3
0.269
9.33E-06
Column 2
0.274
Column 3
0.276
0.092
Column 4
0.248
ANOVA
Source of Variation SS df MS F
P-value
F crit
Between Groups
5.5E-05
Within Groups 8
Total 11

25. ANOVA Chlamydomonas Day 6
Anova: Single Factor
SUMMARY
Groups
Count
Sum
Average
Variance
Column 1 3
0.274
2.13E-05
Column 2
0.354
0.118
Column 3
0.346
Column 4
0.3
0.1
ANOVA
Source of Variation SS df MS F
P-value
F crit
Between Groups
Within Groups 8
Total 11

26. ANOVA Chlamydomonas Day 10
Anova: Single Factor
SUMMARY
Groups
Count
Sum
Average
Variance
Column 1 3
0.392
Column 2
0.468
0.156
5.7E-05
Column 3
0.47
Column 4
0.433
ANOVA
Source of Variation SS df MS F
P-value
F crit
Between Groups
Within Groups 8
Total 11