Kinetics

1. Respiration Pathways & Wastewater Treatment
Rose Degner and Ty Williams
Mentors: Dr. Caye Drapcho and Libby Flanagan
BE 4101, EEES, Clemson University, Clemson, SC, 29634
Abstract
The purpose of this experiment was to design and monitor three
batch reactor environments for wastewater treatment: aerobic, anoxic
and anaerobic. Waste cooking oil was inoculated with a septic bacteria
and nutrients to encourage biomass growth. While monitoring the
reactors, values of OD, pH, TSS and COD were obtained and graphed
for analysis and comparison. Trends such as decreasing pH during
fermentation, and decreasing TSS values combined with increasing OD
values during hydrolysis were predicted and observed.
Introduction
Aerobic, anoxic and anaerobic conditions have a place in the
wastewater treatment industry with different purposes and set-backs
(Drapcho, 2019). Aerobic treatment consumes organic material rapidly
but at high aeration costs. Anoxic respiration carries out denitrification
in very specific and delicate environments catering to the correct
community of bacteria. Anaerobic conditions digest organic material at
a slower rate resulting in different products. This experiment sought to
analyze the effectiveness of organic material removal and biomass
growth in each of these three respiration conditions.
Materials and Methods
Materials:
Three 1,000 mL beakers with caps, three stir plates, 600 mL
aqueous wastewater from oil processing, sodium hydroxide tablets, 0.30
g nutrient inoculant, 3.75 g yeast extract, 3.75 g active yeast, 26.6 g
potassium nitrate, 30 COD tubes, 0.45*10^-6 m. filter paper, pH probe,
spectrophotometer.
Methods:
Three 1,000 mL beakers, designated Reactors 1-3, were filled with
mock wastewater at a 1:5 dilution. The pH of the wastewater was raised
from 4.62 to 8.01 before dilution. Septic tank nutrient inoculant, yeast
extract, and active yeast were added to each reactor. Potassium nitrate
was added to Reactor 2. Reactors 2 and 3 were loosely capped while
Reactor 1 remained open. All three reactors were placed on stir plates.
Samples of each reactor were collected and analyzed twice a day for
five days. A pH probe identified the pH of each sample. The OD of each
sample was taken before and after filtration. 1.5 and 15 g/L COD tubes
were used to estimate the COD of each sample, diluted accordingly.
Each sample was filtered to collect an estimation of the TSS within as
well. Dr. Caye Drapcho’s laboratory notes were referenced in finding
and calculating the TSS and COD of each sample (Drapcho, 2019).
Results
Figure 1 shows the rise and fall in total suspended solids (TSS) of each
reactor over time, around five days. Each reactor produced more
suspended solids initially and decreased as complex organic material was
being hydrolyzed. Figure 2 illustrates this data. The filter of reactor 3
(right) appears lighter in color than 1 and 2 (left and middle respectively).
The anaerobic reactor appeared to hydrolyze the most organic material
followed by the aerobic reactor. Each reactor slightly increased in TSS
toward the end of the experiment indicating a build-up of biomass.
Figures 3 and 4 below display the optical density (OD) of each reactor
before and after suspended solids were filtered out of the fluid. These
graphs are roughly inversely related.
The “raw” OD of the reactors decreased as organic material was
hydrolyzed and increased as biomass formed. Likewise, as material is
hydrolyzed it slips through filtration and impacts the post-filtration OD.
The anaerobic reactor underwent the most dramatic change in OD before
and after filtration.
Figure 5 shows the change in pH each
reactor underwent throughout the course
of the experiment. Hydrogen was
consumed in each scenario. The anaerobic
reactor ended with the lowest pH implying
a production of acids.
The final results of Figure 5 mimic those
of Figure 1 and 3 proving the consistency
of each reactors’ performance.
Conclusions
The anoxic reactor saw the least activity due to conditions being too harsh
for particular nitrogen reducing bacteria to grow. The anaerobic reactor
underwent fermentation by both yeast and bacteria so therefore saw the
greatest biological activity, confirmed by the harsh odor this reactor produced.
The aerobic reactor reduced the organic material consistently with minimal
unpredicted trends. These conclusions are summarized well by the results of
TSS determination. The lower the TSS, the more organic material was
converted to carbon dioxide gas by the reactor.
References
Drapcho, C. 2019. Unpublished Laboratory Notes, BE 4101, Clemson
University, Clemson SC.
Drapcho, C. 2019. Unpublished Class Notes, BE 4100, Clemson University,
Clemson SC.
Van Hoek, Pim, et al. Effect of Specific Growth Rate on Fermentative
Capacity of Baker’s Yeast. 16 Sept. 1997,
aem.asm.org/content/aem/64/11/4226.full.pdf.
Acknowledgements
We would like to thank Dr. Caye Drapcho, Libby Flanagan, and the Environmental Engineering and
Earth Sciences department for the mentorship and materials necessary for us to carry out this experiment.
Variable Value
Maximum Specific Growth Rate (𝛍max) [1/hr] 0.020
Soluble Substrate Concentration (S) [mg/L] 200
Half-Saturation Constant (KS) [mg/L] 200
Biomass Yield (YB) [mg/mg] 0.535
Biomass Concentration (XB) [mg/L] 100
Figure 1. TSS vs. Time Figure 2. Filtered Reactor Fluid
Figure 4. Filtered OD vs. TimeFigure 3. Unfiltered OD vs. Time
Figure 5. Reactor pH vs. Time
Table 1. Variables and Values used in Reactor Modeling
Figure 6. STELLA Reactor Model Graph Figure 7. STELLA Reactor Model Figure 8. COD vs. Time
Model Development and
Reactor Design
The values in Table 1 were acquired from
both literature sources and class notes.
Figure 6 below represents the model for
the biomass formation and substrate utilization
in our experiment and Figure 7 is a visualization
of the reactor model.
The COD values in Figure 8 were obtained by the absorbance values
measured and the linear regression equations from two different
standard curves constructed.