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The Pennsylvania State University
The Graduate School
College of Engineering
BIOREMEDIATION OF DIESEL CONTAMINATED SOIL USING
SPENT MUSHROOM COMPOST
A Thesis in
Environmental Engineering
by
Alessia Eramo
2009 Alessia Eramo
Submitted in Partial Fulfillment
of the Requirements
for the Degree of
Master of Science
August 2009
The thesis of Alessia Eramo was reviewed and approved* by the following:
Rachel A. Brennan
Assistant Professor of Environmental Engineering
Thesis Advisor
William D. Burgos
Associate Professor of Environmental Engineering
John M. Regan
Associate Professor of Environmental Engineering
Peggy A. Johnson
Professor of Civil Engineering
Head of the Department of Civil and Environmental Engineering
*Signatures are on file in the Graduate School
iii
ABSTRACT
Composting has been shown to be an effective bioremediation technique for the
treatment of hydrocarbon-contaminated soil. In this research, spent mushroom compost
(SMC), a sustainable, inexpensive, and abundant byproduct of the mushroom industry,
was analyzed for its ability to support the remediation of soil contaminated by a diesel
fuel spill. Chitin, a nitrogen-rich polymer derived from crab shell material, was also
investigated as a nutrient amendment to counteract the nitrogen loss commonly observed
in petroleum-contaminated soils. The approach was tested on contaminated soil and SMC
obtained from the California Mushroom Farm, Inc. The results of this study will be used
to guide the implementation of aerobic composting for remediation of diesel-
contaminated soil at the site.
Sacrificial batch microcosm tests were used to evaluate the effect of
substrate/nutrient addition and elevated temperatures on the rate of diesel total petroleum
hydrocarbon (TPH) remediation in a series of two experimental phases. In Phase I, the
conditions evaluated were soil + SMC, soil + SMC with crab-shell chitin, and soil only
(control). In Phase II, TPH removal was monitored at three temperatures typically
encountered during composting: 22 oC, 30
oC, and 50
oC.
In Phase I, all substrate-amended microcosms were successful at diesel removal.
Microcosms amended with SMC and chitin showed an advantage at various points
throughout treatment but did not enhance overall TPH remediation when compared to
microcosms amended with SMC only. In Phase II, microcosms showed different TPH
removal trends at early times depending on temperature, but overall, it was determined
iv
that none of the various temperature conditions provided an advantage for remediation.
After 160 days, TPH concentrations in microcosms were reduced from approximately
1600 to 210 ppm at 22 oC, 180 ppm at 30
oC, and 270 at 50
oC for removals of 87%,
89%, and 83%, respectively.
Denaturing Gradient Gel Electrophoresis (DGGE) was conducted using universal
bacterial 16S rRNA gene primers to characterize the microbial community at different
points during treatment. A diverse community was shown to be present in all conditions
and time points analyzed. Preferential enrichment of specific community members or
hydrocarbon degraders was not found. Functional overlap by various species breaking
down the organic material in the system may be responsible for hydrocarbon degradation
as well.
Composting treatment of diesel contaminated soil using SMC from The California
Mushroom Farm was compared to similar treatments using other locally available low
cost waste substrates. SMC from The Pennsylvania State University Mushroom Testing
Demonstration Facility and sewage sludge-based compost from The University Area
Joint Authority (UAJA) Wastewater Treatment Plant promoted the highest TPH removal,
CO2 production, and O2 usage as compared to The California Mushroom Farm SMC. The
highest TPH removal (43%) was observed in microcosms containing Penn State SMC.
This enhanced performance is probably linked to the higher carbon and nitrogen contents
available in UAJA compost and Penn State SMC per dry mass as compared to The
California Mushroom Farm SMC.
v
The results of this study demonstrate that SMC can serve as an effective compost
amendment to treat weathered, diesel-contaminated soil. Additionally, several other
readily available waste substrates can be utilized in this type of low cost, low energy
remediation system. Optimal conditions for microbial growth and activity, particularly
sufficient O2 and moisture, should be provided at the onset of treatment and monitored
actively throughout the course of remediation to ensure maximum hydrocarbon
degradation.
vi
TABLE OF CONTENTS
LIST OF FIGURES ..................................................................................................... ix
LIST OF TABLES.......................................................................................................xii
ACKNOWLEDGEMENTS.........................................................................................xiv
Chapter 1 Introduction ................................................................................................1
1.1 Characterization, Occurance, and Hazards of Diesel Contaminated Soil ......1
1.2 Biological Treatment of Petroleum Contaminated Soil..................................2
1.3 Composting of Petroleum Contaminated Soil ................................................5
1.4 Optimization of Biological Treatment Conditions .........................................6
1.5 Production and Characterization of Spent Mushroom Compost ....................8
1.6 Chitin’s Role in Bioremediation.....................................................................9
1.7 Abiotic Factors Affecting the Fate of Hydrocarbon Contaminants in Soils...10
1.8 Microbial Community Changes and Detection by DGGE .............................12
1.9 Hypothesis and Objectives .............................................................................13
Chapter 2 Materials and Methods ...............................................................................15
2.1 Phase I and II Microcosm Tests......................................................................15
2.1.1 Chemicals................................................................................................15
2.1.2 Substrate Handling and Characterization................................................15
2.1.3 Experimental Setup ................................................................................17
2.1.3.1 Phase I – Substrate Evaluation ..........................................................17
2.1.3.2 Phase II – Temperature Evaluation ...................................................18
2.1.4 Analysis ..................................................................................................19
2.1.4.1 Headspace Gas Quantification ..........................................................19
2.1.4.2 Total Petroleum Hydrocarbon Analysis ............................................19
2.1.4.3 Statistical Analysis ............................................................................20
2.2 Phase I and II Molecular Analysis..................................................................20
2.2.1 DNA Extraction and Amplification......................................................20
2.2.2 DGGE Solutions...................................................................................22
2.2.3 DGGE Community Profiling................................................................22
2.3 Substrate Screening and Respirometry Tests .................................................24
2.3.1 Chemicals and Substrates .....................................................................24
2.3.2 Screening Test Setup ............................................................................25
2.3.3 Respirometry Test Setup ......................................................................27
2.3.4 Analysis ................................................................................................30
Chapter 3 Results ........................................................................................................32
3.1 Phase I and II Microcosm Tests......................................................................32
3.1.1 Composting Conditions ..........................................................................32
3.1.1.1 Substrate Characterization ................................................................32
3.1.1.2 Moisture Content ...............................................................................33
3.1.2 Oxygen and Carbon Dioxide Headspace Concentrations .......................35
3.1.3 Total Petroleum Hydrocarbon Concentrations ......................................40
3.1.3.1 Phase I Results ..................................................................................40
vii
3.1.3.2 Phase II Results ................................................................................43
3.1.4 Comparison of Phase I and II Removal Rates ........................................45
3.1.5 Degradation Patterns in Diesel Chromatograms ....................................48
3.2 Phase I and II Molecular Analysis..................................................................51
3.3 Substrate Comparison Microcosm and Respirometry Tests...........................58
3.3.1 Substrates Characterization.....................................................................58
3.3.2 Moisture Content ...................................................................................61
3.3.3 Carbon Dioxide and Oxygen Utilization ...............................................63
3.3.4 Total Petroleum Hydrocarbon Concentrations .......................................67
Chapter 4 Discussion ..................................................................................................71
4.1 The Effect of Substrate and Nutrient Additions on Remediation of Diesel
Contaminated Soil .........................................................................................71
4.1.1 Evaluation of Various Substrates............................................................71
4.1.2 Influence of C:N Ratio............................................................................72
4.1.3 The Effect of Nutrient Addition Through Chitin....................................74
4.1.4 Carbon Dioxide Production Under Various Treatments.........................74
4.2 Rates and Descriptions of Removal................................................................75
4.3 Additional Considerations for Full-Scale Implementation of Composting
System ...........................................................................................................76
4.3.1 Moisture Profiles and Control.................................................................76
4.3.2 The Importance of Oxygen .....................................................................77
4.3.3 The Effects of Temperature ....................................................................78
4.3.4 Addressing Potential Residual Concentration Concerns .......................79
4.3.5 Addition of Organic Material..................................................................80
4.4 DGGE as a Tool to Investigate Microbial Communities................................81
4.4.1 Qualitative and Statistical Analysis ........................................................81
4.4.2 Difficulties in Sequence Analysis of Complex Soil Communities.........82 4.4.3 DGGE Optimization ..........................................................................................83
Chapter 5 Conclusions, Engineering Significance, and Future Work ........................85
5.1 Conclusions.....................................................................................................85
5.2 Engineering Significance................................................................................86
5.3 Future Work....................................................................................................87
References....................................................................................................................89
Appendix A Soil Textural Class According to the United States Department of
Agriculture............................................................................................................97
Appendix B Extraction Method Development ............................................................98
B.1.1 Preliminary Considerations.........................................................................98
B.1.2 Extractions in the Phase I and II Microcosm Tests.....................................99
B.1.3 Extractions in the Screening and Respirometry Tests ................................101
B.1.4 Suggested Modifications to the Extraction Procedure................................102
Appendix C pH in Phase II Microcosms on day 34.....................................................104
Appendix D Supplemental Molecular Analysis ..........................................................105
viii
D.1 DGGE Band Confirmation ...........................................................................105
D.2 Comparative Band Movement in DGGE Gels ..............................................106
D.3 Sequencing Results ........................................................................................109
D.4 Cloning...........................................................................................................116
D.4.1 Procedure ....................................................................................................116
D.4.2 Results and Discussion ...............................................................................116
D.5 Fungal Community Analysis .........................................................................119
D.5.1 DNA Extraction and Amplification............................................................119
D.5.2 Recommendations for Future Research......................................................120
Appendix E Respirometry Test Cumulative Oxygen Uptake......................................122
Appendix F Sorption Isotherm Development ..............................................................123
F.1 Purpose and Approach....................................................................................123
F.2 Preliminary Tests............................................................................................123
F.3 Preliminary Test Conclusions.........................................................................126
F.4 Desorption Tests.............................................................................................126
ix
LIST OF FIGURES
Figure 1-1: Chemical structures of polycyclic aromatic hydrocarbons .......................2
Figure 1-2: Diagram of solid phase biological treatment using a composting pile .....6
Figure 1-3: Chemical structure of fully N-acetylated chitin........................................10
Figure 1-4: Main processes affecting the fate of an organic chemical in soil .............12
Figure 2-1: Respirometer Test bioreactor configuration .............................................30
Figure 3-1: Moisture content at two time points during the course of treatment in
closed Phase I microcosms ..................................................................................34
Figure 3-2: Moisture content in closed Phase II microcosms at different
temperatures over time .........................................................................................35
Figure 3-3 Headspace gas concentration ratio in Phase I active microcosms during
mid-points in composting treatment .....................................................................36
Figure 3-4: Carbon dioxide production rates during later time points of Phase I
treatment ...............................................................................................................36
Figure 3-5: Carbon dioxide production rates at various time intervals under three
temperature conditions in closed Phase II microcosms amended with SMC +
chitin .....................................................................................................................38
Figure 3-6: Cumulative carbon dioxide production integrated over time intervals
under three substrate amended temperature conditions in closed Phase II
microcosms ...........................................................................................................39
Figure 3-7: Cumulative oxygen utilization integrated over various time intervals
under three temperature conditions in closed Phase II microcosms amended
with SMC + chitin ................................................................................................39
Figure 3-8: Decrease in Total Petroleum Hydrocarbons (diesel range) during the
Phase I microcosm testing with different substrates at 22 oC ..............................42
Figure 3-9: Decrease in Total Petroleum Hydrocarbons (diesel range) during
Phase II microcosm testing with SMC + chitin under different temperature
conditions..............................................................................................................46
Figure 3-10: Comparison of TPH removal rates for Phase I and II active
microcosms ...........................................................................................................47
x
Figure 3-11: Example chromatograms of fresh diesel (a) and weathered diesel (b)
extracted from a contaminated soil sample at t =0 ...............................................49
Figure 3-12: Comparison of TPH chromatograms in Phase I microcosms
containing SMC and soil only over time ..............................................................50
Figure 3-13: Overlay of TPH chromatograms observed for the active microcosms
containing SMC + chitin at different temperatures on day 26 of Phase II ...........51
Figure 3-14: Phase I DGGE Gel and lane image profiles generated by image
analysis .................................................................................................................54
Figure 3-15: Phase II DGGE Gel and lane image profiles generated by image
analysis .................................................................................................................55
Figure 3-16: DGGE Gel for contaminated soil at different depths below ground
and lane image profiles generated by image analysis...........................................56
Figure 3-17: Moisture content over the course of treatment in Substrate
Comparison Test microcosms (22 oC)..................................................................63
Figure 3-18: Carbon dioxide production in 1 mL of headspace in Screening Test
microcosm bottles at the end of 21 day incubation at 22oC on a platform
shaker ...................................................................................................................64
Figure 3-19: Carbon dioxide production in 1 mL of headspace in Substrate
Comparison Test microcosm bottles prior to hydrocarbon extraction at 3 time
points.....................................................................................................................65
Figure 3-20: Cumulative oxygen usage for 34 days of treatment in bottles
connected to respirometer system after corrections for unlikely jumps in
uptake....................................................................................................................66
Figure 3-21: Initial and final TPH concentrations and overall percent decrease in
compost amended microcosms in the Screening Test over 21 days of
treatment ...............................................................................................................68
Figure 3-22: Diesel TPH removal trends in active microcosms of the Substrate
Screening Test. Substrates and diesel contaminated soil were mixed at a 1:1
ratio by dry mass...................................................................................................70
Figure A-1: Chart showing the percentages of clay, silt, and sand in the basic
textural classes ......................................................................................................97
xi
Figure B-1: Superimposed chromatograms of TPH extracts obtained by identical
procedures from the same contaminated soil sample using the solvents
hexane and acetone ...............................................................................................100
Figure B-2: Effect of sonication time on recovery of diesel range TPH from
weathered soil samples extracted in acetone ........................................................101
Figure D-1: Second run of DGGE gels used to confirm bands excised from the
Phase I and II DGGE gels.....................................................................................105
Figure D-1: Cumulative oxygen usage for 30 days of treatment in bottles
connected to respirometer system.........................................................................122
Figure F-1: Equilibrium test to determine the minimum time necessary to reach
maximum sorption of diesel to soil and SMC ......................................................124
Figure F-2: Results of equilibrium test to determine the minimum amount of time
necessary for sorption of diesel to SMC...............................................................125
xii
LIST OF TABLES
(USEPA Office of Underground Storage Tanks). .......................................................1
Table 2-1: Recipe for 30 and 60% denaturant polyacrilamide DGGE gels................22
Table 2-2: Contents of Screening Test Microcosms prepared at a 1:1
volume:volume ratio (9 mL of each) and adjusted to 50 % moisture..........................27
Table 2-3: Contents of Respirometry Test microcosms prepared at a 1:1 dry
mass:dry mass ratio (5 grams dry weight of each) and adjusted to 50 % moisture.....29
Table 3-1: Classification of The California Mushroom Farm soil based on USDA
guidelines .....................................................................................................................33
Table 3-2: Chemical properties of three substrates used in Phase I and II
microcosm tests............................................................................................................33
Table 3-3: Comparison of Phase I TPH removal rates and TPH concentrations in
active microcosms containing different substrates at 22oC .........................................41
Table 3-4: Changes in average TPH removal rates for active Phase II microcosms
over time ......................................................................................................................44
Table 3-5: Approximate TPH removal in Phase II microcosms under all tested
conditions over 160 days of treatment .........................................................................44
Table 3-6: Sorenson’s indices for Phase I microcosms over time ...............................57
Table 3-7: Sorenson’s indices for Phase II microcosms over time..............................58
Table 3-8: Sorenson’s indices for different depths of diesel contamination in a soil
core obtained from the California Mushroom Farm....................................................58
Table 3-9: Chemical properties of substrates and uncontaminated soil used in the
Screening Test and Substrate Comparison microcosms ..............................................59
Table 3-10: C:N ratios for Screening Test microcosms. Substrates and soil were
mixed at a 1:1 (volume) ratio.......................................................................................59
Table 3-11: C:N ratios for Substrate Comparison Test microcosms. Substrates and
soil were mixed at a 1:1 (dry mass) ratio .....................................................................60
Table 1-1: Pennsylvania UST Corrective Measures as of September 30, 2008
xiii
Table 3-12: Sieve analysis for substrates and soil after grinding with a coffee
grinder. The fraction between 850 um and 2.0 mm was used in Screening Test and
Substrate Comparison Tests.........................................................................................60
Table 3-13: Composition of substrates used to treat diesel contaminated soil in
Substrate Comparison microcosm test ........................................................................61
Table 3-14: Moisture in Screening Test microcosms. Substrates and soil were
mixed at a 1:1 (dry mass) ratio ....................................................................................62
Table 3-15: Comparison of diesel TPH removal in active Substrate Comparison
microcosms over 62 days of treatment ........................................................................70
Table C-1: Comparison of pH in Phase II microcosm on day 34...............................104
Table D-1: Numerical comparison of relative mobilities and percent of total
sample areas for DGGE banding patterns obtained for Phase I microcosm testing ....106
Table D-2: Numerical comparison of relative mobilities and percent of total
sample areas for DGGE banding patterns obtained for Phase II microcosm testing...107
Table D-3: Numerical comparison of relative mobilities and percent of total
sample areas for DGGE banding patterns obtained for contaminated soil from
different depths below ground .....................................................................................108
Table D-4: Sequencing results for bands excised from DGGE gels run with PCR
products from Phase I and II microcosm experiments.................................................109
Table D-5: Sequence analysis of cloning DNA eluted from two DGGE bands..........118
xiv
ACKNOWLEDGEMENTS
I would like to thank my advisor, Dr. Rachel Brennan, for her advice, assistance,
and guidance throughout the course of my research. Thanks also for securing funding for
me throughout my Masters Degree. I would like to thank Bill Burgos and Jay Regan, for
serving on my committee and assisting in the review and discussion of my research.
I would like to thank my mom, dad, and sister, who have always been great
sources of love and support, and Reed for his patience and optimism during my past two
years at Penn State.
Thanks also to The California Mushroom Farm, Inc. for funding and for providing
the idea for this research. Specifically, I would like to acknowledge the General Manager
of the farm, Alan Marlowe. Thanks to The Penn State Institutes for Energy and the
Environment (PSIEE) and the Department of Civil and Environmental Engineering for
additional funding.
Finally, I would like to thank numerous students, faculty members, and staff at
Penn State, who have been so generous with their time and knowledge, especially Dav
Jones for help with using the GC and other instruments, and the students in the basement
of Sackett for their help and encouragement.
Chapter 1
Introduction
1.1 Characterization, Occurance, and Hazards of Diesel Contaminants in Soil
Diesel is the second most frequently treated contaminant after benzene at United
States Environmental Protection Agency (USEPA) Superfund sites (Zytner et al., 2001).
Diesel is a medium-weight petroleum fuel with a boiling point range of 175 oC to 355
oC
(Brady, 2001). It is composed of over 200 petroleum hydrocarbon compounds
corresponding to the molecular weight range of C10-C28 alkanes (Riffaldi et al., 2006).
The composition of diesel is approximately 30% alkanes, 45% cyclic alkanes, and 24%
aromatics (Zytner et al., 2001).
The extensive use of diesel and other petroleum products has caused their
intrusion into soil environments by various routes, including leakage from underground
storage tanks (UST) and pipelines, accidental spills, improper waste disposal practices,
and leaching landfills. Leaking USTs, some of the most common sources of such
contamination, compromise the soil environment and threaten adjacent groundwater
supplies (Yadav and Reddy, 1993). In 1984, legislation was passed by the United States
Congress to address the hazards increasingly caused by leaking USTs. This Subtitle I
amendment to the Resource Conservation and Recovery Act (RCRA) required the EPA
to develop a complete regulatory program regarding USTs storing petroleum or certain
hazardous substances. As of September 2006, the EPA had confirmed over 460,000 UST
releases, and it is estimated that there are still 113,000 that remain to be remediated (EPA
Office of Solid Waste and Emergency Response). Pennsylvania’s cleanup backlog
exceeded 3,000 USTs in late 2008 (Table 1-1).
2
However, many USTs are not under the authority of the government, indicating
that the actual incidence of releases is probably greater than the numbers given by the
EPA. Those USTs that are excluded from federal jurisdiction are:
• Farm and residential tanks of 1,100 gallons or less capacity holding motor fuel
used for noncommercial purposes;
• Tanks storing heating oil used on the premises where it is stored;
• Tanks on or above the floor of underground areas, such as basements or
tunnels;
• Septic tanks and systems for collecting storm water and wastewater;
• Flow-through process tanks;
• Tanks of 110 gallons or less capacity; and
• Emergency spill and overfill tanks.
In these cases, property owners are responsible for the monitoring, maintenance, and
cleanup associated with their tanks (USEPA, 2007). It is important to note that releases
may not always be known, and that the cost of conventional cleanup methods is so high
that even known releases may not be treated due to financial limitations.
Contamination by petroleum products threatens human and ecological health.
Various fuel constituents may enter the human and animal system by inhalation,
ingestion, or dermal contact and may pose hepatic, renal, neurological, and/or respiratory
risks (ATSDR, 1999). Polycyclic aromatic hydrocarbons (PAHs) are the most toxic and
recalcitrant diesel compounds. Many PAHs are highly toxic, carcinogenic, and/or
mutagenic. They consist of carbon and hydrogen formed into two or more fused benzene
rings in linear, angular, or cluster arrangements (Figure 1-1). The USEPA lists 16 PAH
congeners as primary pollutants (Lau et al., 2003). PAHs also enter the environment as a
result of the incomplete combustion of coal, oil, gasoline, and wood or of petrochemical
industries (Andreoni et al., 2007).
Table 1-1: Pennsylvania UST Corrective Measures as of September 30, 2008 (USEPA
Office of Underground Storage Tanks)
Active
Tanks
Total Confirmed
Releases
Total Cleanups
Completed
Cleanups
Backlog
24,235 14,679 11,311 3,368
3
1.2 Biological Treatment of Petroleum Contaminated Soil
While traditional methods of treating petroleum-contaminated soil and
groundwater contamination have relied on removal and containment (Riser-Roberts,
1998), on-site biological treatment, or bioremediation, is becoming an increasingly used
alternative due to its low cost and capacity for complete destruction of contaminants.
Bioremediation is an especially economical and effective treatment for diesel and other
medium distillate fuels because a large portion of these contaminants are easily
degradable (Riffaldi et al., 2006) and, through assimilative biodegradation, can serve as
carbon and energy sources for degrading organisms (Andreoni et al., 2007). Biological
treatment may be implemented by biostimulation or bioaugmentation. Biostimulation
utilizes the degradative potential of the intrinsic microbial communities by stimulating
them with carbon sources or nutrients (Andreoni and Gianfreda, 2007), whereas
Figure 1-1: Chemical structures of polycyclic aromatic hydrocarbons (Cerniglia 1997).
4
bioaugmentation introduces an inoculum capable of contaminant degradation into the
contaminated zone (Andreoni et al., 2004).
The complete mineralization of petroleum hydrocarbons (CyHx) based on
respiration rates is represented by the following equation (Baker et al., 2000; Van de
Steene and Verplancke, 2007):
CyHx + (y + 0.25x) O2 � yCO2 + 0.5x H2O (Equation 1-1)
where y is the number of carbon atoms and x is the number of hydrogen atoms in the
hydrocarbon compound. This equation indicates the molar ratio of oxygen:carbon dioxide
that is necessary for complete aerobic biodegradation. This ratio is derived by
substituting the variables associated with each hydrocarbon into Equation 1-1 and then
dividing the calculated coefficient of O2 by that of CO2. This ratio varies from 1.52 to
1.55 for all diesel range alkanes (C10H22 - C28H58). Equation 1-1 dictates that more moles
of oxygen are necessary per mole of carbon dioxide produced.
The lighter fraction of fuels, such as straight-chained alkanes, are easily degraded
by many organisms, while the heavier and more complex fraction such as PAHs and
cyclo-alkanes are more chemically stable and recalcitrant. They often require degradation
by cometabolic processes (Richard and Vogel, 1999). Cometabolic degradation is not
induced by the presence of the contaminant and occurs without apparent nutritional
benefit to the microorganisms. It is a result of other microbial activities or metabolic
processes (Topp et al., 1997). Furthermore, PAH bioavailability may be limited by low
water solubility and slow mass transfer rates from soil particles. Despite these inherent
disadvantages, several microorganisms are known to be capable of mineralizing a large
variety of PAHs or breaking them down to their less toxic metabolites (Andreoni at al.,
2004). Some fungal community members also contribute to the biodegradation of
hydrocarbons in soil (Leahy and Colwell, 1990) and are able to break down PAHs
(Mancera-Lopez et al., 2008).
There are a number of biological remediation techniques commonly implemented
at the field-scale for the treatment of petroleum contaminated soils. They typically have
5
lower operating costs than physical and chemical processes (Arce-Ortega et al., 2004)
and include: monitored natural attenuation, landfarming, bioventing, biosparging,
bioreactors, and composting. Monitored natural attenuation relies on naturally occurring
biodegradation processes that decrease contaminant concentrations in the environment
over time (Bjorklof et al., 2008). The term “natural attenuation” includes all chemical,
physical, and biological processes that may be responsible for contaminant removal such
as biodegradation, chemical transformation, volatilization, dispersion, dissolution,
dilution, and stabilization by binding to organic material (Andreoni and Gianfreda, 2007).
Landfarming is a treatment option that involves spreading contaminated soil over clean
soil and allowing natural processes to detoxify, degrade, and immobilize contaminants. It
has been used for treating various hazardous wastes, but is especially effective for
petroleum wastes because they have a high concentration of degradable organic
compounds. Landfarming provides good opportunities to accelerate their breakdown by
increasing oxygen levels through soil tilling and adding nutrients. However, degradation
of PAHs by this treatment may take as long as 1 to 2 years (Riser-Roberts, 1998).
Bioventing and biosparging are two in situ bioremediation approaches where oxygen is
introduced into the soil vapor phase and saturated zone, respectively, in order to abolish
oxygen limitations and initiate and support aerobic microbial activity (Doelman and
Breedveld, 1999). This is accomplished through air injection, extraction, or a
combination of the two at low rates through vertical wells. Prior to implementing
bioventing or biosparging, the extent and type of contamination as well as soil
characteristics must be determined to assess the applicability of these processes and
proper placement of air injection wells (Baker, 1999). Various reactor configurations may
also be considered for biological treatment. They include bioslurry reactors, fermenters,
prepared bed reactors, and a number of enclosed systems, which should be utilized if the
potential hazards from discharges and emissions are very serious (Riser-Roberts, 1998).
6
1.3 Composting of Petroleum Contaminated Soil
Another currently used full scale bioremediation technique for petroleum
contaminated soils is composting. Generally, composting is characterized by the addition
of organic matter to soil. Typical amendments include manure, sewage sludge, bark
chips, yard waste, and food processing wastes (Singh et al., 2005). Composting has
emerged as a favorable technology for the bioremediation of hydrocarbon-contaminated
soils because it has relatively low capital and operating costs, simple operation and
design, and relatively high treatment efficiencies (Namkoong et al., 2002). It is able to
achieve higher hydrocarbon degradation rates and lower detectable contaminant levels
than other bioremediation technologies (Hesnawi and McCartney, 2006) and promotes
soil sustainability and reuse, in contrast to non-biological approaches (Antizar-Ladislao et
al., 2004). Composting counteracts the available nutrient deficiency that often limits
degrading microbial communities in heavily contaminated environments (Tiquia et al.,
2002; Waybrant et al., 2002) by supplementing the soil with additional carbon and
nitrogen sources.
A complex carbon source like compost is ideal for providing a suite of substrates
to support the complex microbial community required for diesel degradation (Marin et
al., 2006). The complexity of petroleum fuels requires a microbial consortium, rather than
a single organism (Adebusoye et al., 2007). During the composting process, bacteria and
fungi decompose organic matter while also degrading contaminants. Substrates that have
been shown to be effective in the treatment of hydrocarbon contaminated soil are varied
and include wood shavings and pig slurry (Marin et al., 2006); compost feedstock
consisting of municipal biosolids, leaves, and woodshavings (Heswani and McCarthy,
2006); biowaste composed of vegetable, fruit, and garden waste (van Gestel et al., 2003);
and sewage sludge (Hwang et al., 2006). These amendments stimulate biodegradation by
acting as a source of substrates, nutrients, and microorganisms, while improving the
structure and water-retaining capacity of the soil (Van Gestel et al., 2003).
Full-scale composting systems may be structured as turned or static windrow
systems (Figure 1-2), where the organic material is mixed with contaminated soil and
7
shaped into long rows called windrows or biopiles. Aeration is delivered by turning with
farm machinery in turned windrow systems, or by perforated pipes that run through the
pile in static compost systems (Riser-Roberts, 1998). These compost piles may reach a
height of 2 to 4 meters (Jorgensen et al., 2000).
1.4 Optimization of Biological Treatment Conditions
Successful biological treatments achieve maximized rates and extents of
remediation by the implementation of optimal conditions for microbial growth and
metabolism of hydrocarbons, the bacteria’s electron donors. Some factors affecting
microbial activity are nutrient availability, carbon to nitrogen ratio (C:N), oxygen
concentration, amount and composition of compost amendments, and moisture content.
The amount and composition of compost amendments plays the biggest role in supplying
additional organic carbon (Berry, 1999). Optimum carbon to nitrogen ratios (C:N) for
composting systems have been reported, ranging from 10:1 to 100:1 (Singh et al., 2005),
and can vary based on type of soil and contaminant.
Figure 1-2: Diagram of solid phase biological treatment using a composting pile (EPA,
1997)
8
Water is necessary for microbial growth and for diffusion of nutrients and
byproducts across the cell wall during the biodegradation process (Riser-Roberts, 1998).
It is important to maintain a moisture content that is sufficient for the microbial growth,
but does not water-log the system. Low moisture conditions can restrict the movement of
bacteria. However, excess moisture may fill the smaller pores between particles and limit
oxygen transport (Richard et al., 2002). Optimal moisture contents for composting
systems range from 25 to 80%, but are most common from 50 to 70% (Richard et al.,
2002). Since in many full-scale composting systems, the greatest opportunity to adjust
moisture content occurs during initial mixing, setting the moisture content then is
extremely important (Richard et al., 2002).
Optimization of composting conditions also requires understanding the most
favorable operating temperature for microbial degradation. The ultimate composting
temperature may be affected by compost and hydrocarbon type, incubation time, and
temperature changes caused by reactions within the compost heap (Heswani and
McCartney, 2006). Most composting systems, however, exhibit similar temperature
patterns consisting of an early thermophilic phase (50 oC to 70
oC) followed by a
decrease to ambient temperatures (Hsu and Lo, 1999; Tiquia et al., 1997). Singh et al.
(2005) observed optimal hydrocarbon degradation between 25 and 35oC. Beaudin et al.
(1999) compared composting at two temperatures (23 oC and 47
oC) and found that
removal efficiencies were initially greater at the lower temperature but increased at the
elevated temperature once an acclimation period had passed. PAH degraders have been
shown to favor mesophilic temperature ranges (Peramaki and Blomker, 1997), but
thermophilic temperatures (45 to 65 oC) may be favorable for treating petroleum-
contaminated soil because of increased desorption kinetics at higher temperatures
(Heswani and McCartney, 2006).
Before implementing any remediation strategy, it is important to assess whether it
will be safe and effective in a given contaminated site. Various criteria must be met.
Microorganisms with the catabolic ability to degrade the contaminants at a reasonable
rate and to a certain regulatory level must be present in the system. Toxic byproducts
must not be produced, inhibitory chemicals must be absent, contaminants must be
9
bioavailable, and conditions must be optimized and maintained to support microbial
growth and activity (Andreoni and Gianfreda, 2007). To satisfy these requirements and
determine whether full-scale implementation is a viable option, it is important to test
composting treatments for specific contaminant mixtures at the laboratory level.
1.5 Production and Characterization of Spent Mushroom Compost
Spent mushroom compost (SMC) is an abundantly produced byproduct of the
mushroom industry. The mushroom industry is the biggest solid-state-fermentation
industry in the world, with 5 kg of SMC generated from the production of 1 kg of
mushrooms (Lau et al., 2003). Its uses have generally been limited to soil conditioning
and fertilizing, while the majority of the product is landfilled (Chiu et al, 1998).
However, its bulkiness makes it expensive to transport to disposal facilities, and
additional costs of disposal may be created by disposal charges or landfill taxes (Chiu et
al., 2000). The over-abundance of SMC makes the development of sustainable
management practices and new uses for SMC of prime importance in the mushroom
industry (Ntougias et al., 2004).
SMC contains high levels of residual nutrients and enzymes, which may be
beneficial for stimulating microbial degradation of organopollutants like hydrocarbons
(Chiu et al, 1998; Khammuang and Sarnthima, 2007; Lau et al, 2003). It also contains a
consortium of mushroom mycelia and lignocellulosic biomass which may act as sorbents
for various metals and organopollutants (Chiu et a., 2000). Only one other study was
found that investigated the use of SMC to promote degradation of fuel contamination
(Harmsen et al., 1999). In this case, sediment that had been contaminated with mineral oil
and landfarmed for two years was combined with SMC derived from the production of
two mushroom types. The addition of SMC helped degrade total PAHs 20.6 to 41.7 %
and mineral oil 1.8 to 4.0 %. The authors also investigated the role of active fungi from
the SMC in hydrocarbon degradation and found it to be negligible.
SMC from different producers and different mushrooms can have varied
compositions. Generally, it is composed of two layers: a compost layer made from straw,
10
manure, and gypsum, and a casing layer made from peat and chalk (Stewart et al., 1998).
The first layer undergoes high temperature composting followed by pasteurization and
conditioning, while the second layer actually serves as the base for mushroom growth.
After three to four weeks of mushroom cultivation, the resulting substrate is considered
spent (Ntougias et al., 2004). During mushroom production, other chemicals may be
added to the compost, such as formaldehyde to sterilize the compost following cropping,
and benomyl, a nitrogen rich fungicide, to eliminate competing fungi (Stewart et al.,
1998).
During the development of the composting substrate for mushroom production, a
microbial succession is selected that promotes the growth of mushroom mycelia. The
different phases in composting select for specific organisms that predominate the
compost for only a short period of time. This results in a diverse microbial population
following harvest and a range of extracellular enzymes (Ball and Jackson, 1995). These
characteristics may help promote microbial degradation of hydrocarbons in contaminated
soil environments.
1.6 Chitin’s Role in Bioremediation
Chitin is the second most abundant polysaccharide on earth after cellulose. It is
the main component of the shells and exoskeletons of crustaceans, insects, and mollusks
and is a constituent of fungal cell walls (Gentili et al., 2006). Chitin has various
remediation applications including heavy metal removal (Chiu et al., 2000). It facilitates
the immobilization of trace metals (such as lead from old gasoline spills) through
precipitation and sorption processes (Varma et al, 2004). Mushroom-derived chitin has
shown similar performance to crustacean chitin in metal removal (Chiu et al., 2000).
In addition to chitin, crab-shell material contains calcium carbonate and residual
protein, and may be especially beneficial for microbial activity for several reasons. The
ammonium released from protein and chitin in the shells is in the preferred form of
nitrogen for microbial synthesis (Rittman and McCarty, 2001) and the calcium carbonate
11
in the crab-shell provides excellent buffering capacity (Daubert and Brennan, 2007),
potentially preventing an inhibitory decrease in pH, which has been observed in some
composting systems due to the formation of organic acids (Gardner et al., 1994; Nakasaki
et al., 1993; Tiquia et al., 1998).
Chitin is composed of N-acetylglucosamine units (Figure 1-3), which when
broken down release nitrogen, an essential nutrient for microbial growth (Brennan et al.,
2006). Nitrogen typically needs to be supplemented to bioremediation systems because of
the considerable amount of carbon added to the soils from petroleum waste (Riser-
Roberts, 1998). Degrading microbial communities are often limited by a lack of available
nutrients (Tiquia et al., 2002; Waybrant et al., 2002). Also, soils contaminated with
petroleum fuels tend to undergo increased denitrification and thus lose nitrogen at faster
rates than uncontaminated soils (Brook et al., 2001). For these reasons, crab-shell chitin’s
nutrient composition may make it a beneficial amendment for hydrocarbon
bioremediation applications.
1.7 Abiotic Factors Affecting the Fate of Hydrocarbon Contaminants in Soils
Bioremediation is not the sole removal mechanism for hydrocarbon contaminants
in soils, even when biological treatment is the course of action implemented. In addition
to their degradation into other products, organic chemicals may partition into the various
phases and retain their chemical structure. Their fate and transformations in the soil are
Figure 1-3: Chemical structure of fully N-acetylated chitin (Kasaai, 2009).
12
governed by numerous processes (Figure 1-4). Sorption and desorption affect the
movement of chemicals and their availability for microbial uptake and transformation
into other products. PAHs’ hydrophobicity favors their sorption to organic matter (Lau et
al., 2003) by electrical attractions, van der Waal forces, covalent bonds, and/or hydrogen
bonds. Over large concentration ranges, sorption of these nonionic organic compounds
does not typically follow the same linear pattern that is observed over small ranges and
low concentration levels. Rather, they are typically described by nonlinear isotherm
models (Grathwohl, 1990) that result from heterogeneities of the sorption sites depending
on the concentration level. Several reasons why sorption may not follow a linear model
are: sorption may follow second-order kinetics, hydrocarbons may have absorbed into
suspended particles of organic matter, yielding less apparent sorption than predicted, and
competition for limited sorption sites may have occurred due to the presence of many
organic chemicals (LaGrega et al., 2001).
Aging is a factor in the extent of such abiotic processes. Over time, the chemicals
become sequestered into the soil matrix or more strongly sorbed onto the soil particles,
making them unavailable for microbial degradation (Andreoni and Gianfreda, 2007).
Additionally, numerous studies (Namkoong et al, 2002, Van de Steene and Verplancke,
2007, Van Gestel et al, 2003) attribute some hydrocarbon removal to absorption,
volatilization, and incorporation into microbial biomass. The effect of aging and
weathering processes are apparent in the characteristic “hump” seen in diesel
chromatograms (USEPA 1997). This hump represents diesel’s large unresolved complex
mixture (UCM), whose composition is generally considered to be many structurally
complex isomers and homologues of branched and cyclic hydrocarbons that cannot be
resolved by capillary GC columns. It is more pronounced in degraded or weathered diesel
(Readman et al., 2002). While alkane peaks are distinct in fresh diesel chromatograms,
they become too small to be differentiated from the UCM in weathered samples, and may
co-elute with byproducts of the weathering process (Powell et al, 2007). The prominence
of this recalcitrant and hydrophobic portion in weathered diesel fuel reflects its increased
resistance to biodegradation as compared to fresh fuel.
13
1.8 Microbial Community Changes and Detection by DGGE
Microorganisms rapidly respond to soil disturbances and are sensitive to low
concentrations of contaminants, so changes in community structure are good indicators of
soil pollution (Andreoni et al., 2004). Hydrocarbon contamination selects for a less
diverse but catabolically versatile microbial community able to break down the
contaminants (Maila et al., 2006). Consequently, PAH degrading organisms are
frequently isolated from environments with a history of PAH contamination (Richard and
Vogel, 1999).
Denaturing Gradient Gel Electrophoresis (DGGE) is a molecular technique that
separates DNA strands by their sequence composition. DNA fragments of similar lengths
Figure 1-4: Main processes affecting the fate of an organic chemical in soil. OC: Organic
chemical, M: microorganisms (Andreoni and Gianfreda, 2007).
14
are produced by polymerase chain reaction (PCR) amplification of a target gene and
separated according to their guanine-cytosine (G-C) bond content by applying a voltage
to a gel with a denaturant gradient (Nakatsu 2007). DGGE has been used extensively to
monitor bacterial communities in space and time or to evaluate the impact of
environmental disturbances. The generated banding pattern is considered to be an image
of the bacterial community. Its statistical interpretation reveals information about shifts in
the microbial community structure or the identification of key population which may be
affected by changing conditions (Fromin et al., 2002). DGGE can be used to investigate
the diversity of soil microbial communities from different locations or subjected to
various stresses. In describing DGGE gels, the term diversity refers to the abundance of
bands in lanes. Visual and statistical approaches for evaluating the effects of
environmental changes can be applied to DGGE banding patterns (Muller et al., 2001)
and prominent bands can be excised and sequenced to determine the identity of specific
members under various treatments. Sequence analysis of bands has been shown to
provide similar results to clone library analysis of PCR products (Ogino et al., 2001).
However, DGGE avoids the time and resources necessary for the classical ‘cloning-
sequencing’ technique while helping to assess the diversity of microbial communities
(Fromin et al., 2002).
1.9 Hypothesis and Objectives
The following research primarily served as a lab-scale feasibility study for the
treatment of weathered petroleum contamination at the California Mushroom Farm, Inc.
in Ventura, California. The goals of this study were to assess the practicality of using
SMC produced by the California Mushroom Farm to stimulate bioremediation of
contaminated soil at that site and to further optimize treatment conditions by nutrient
addition and temperature variations. The clean-up goal at the site, established by
California’s Ventura County Environmental Health Division, was 100 ppm (mg/kg). It
was important to use the soil and SMC that would be used in the field-scale application to
15
take into consideration soil, substrate, and contaminant factors specific to that site and to
more accurately estimate the extent of potential remediation.
In this study, the organic material in SMC was used as the primary source of
carbon, and also provided a trace amount of nitrogen. Chitin in the form of crushed crab-
shells, a sustainable byproduct of the shellfish industry, served as an additional source of
nitrogen in some tests to counteract the nitrogen lack typically encountered in petroleum
contaminated soils. Three temperatures commonly encountered during composting
phases (22oC, 30
oC, and 50
oC) were evaluated for optimal treatment conditions. PCR-
DGGE analysis was conducted on microcosm samples preserved from critical time points
and conditions in order to observe microbial community dynamics in samples affected by
different variables. Finally, the treatment efficiency of using The California Mushroom
Farm SMC as a composting amendment was compared to that of other carbon rich waste
products that are readily available and locally produced in The Pennsylvania State
University area. Recommendations were developed for full-scale implementation of the
composting remediation strategy based on the overall results of the study.
The hypothesis of this research is that bioremediation of diesel contamination at
The California Mushroom Farm, Inc. would be stimulated by the addition of SMC and
enhanced by addition of chitin and treatment at elevated temperatures. Since mushrooms
can accumulate heavy metals from growing on contaminated soil (Demirbas, 2000) even
at levels consistent with those at the site, the use of chitin for lead immobilization could
be particularly important at this mushroom farm. It was assumed that the microbial
community would be strongly affected by the influx of substrate into the system and
would select for hydrocarbon degrading organisms. This is thought to be the first study
that investigates the effects of an SMC amendment as the initial course of remedial action
for weathered petroleum contamination.
16
Chapter 2
Materials and Methods
2.1 Phase I and II Microcosm Tests
2.1.1 Chemicals
Stock solutions of individual C10 to C28 alkanes (Grace Davison Discovery
Science Corporation, Deerfield, IL) were prepared in 95+% n-hexane (Alfa Aesar, Ward
Hill, MA) to calibrate the gas chromatograph (GC) and establish retention times for
individual hydrocarbons. Diesel fuel (ULSD #2 15 Motor Vehicle, Sunoco) was used for
spiking soil and to create diesel standard curves. Hexane or chromatography grade
acetone (EMD Chemicals, Inc., Gibbstown, NJ) and anhydrous sodium sulfate (Fisher
Scientific, Fair Lawn, NJ) were used in the TPH extraction procedures. Carbon dioxide
and oxygen standard curves were generated using bone dry carbon dioxide from a gas
cylinder (GTS, Inc.) and laboratory air, respectively.
2.1.2 Substrate Handling and Characterization
The crab-shell chitin used in the microcosms was derived from stabilized
Dungeness crab under the name ChitoRem®
SC-20 (JRW Bioremediation, LLC, Lenexa,
KS). The typical composition of SC-20, according to the provider, is: 20 – 25% chitin, 35
– 50% protein, 25 – 35% mineral matter (CaCO3), and <10% moisture. Spent mushroom
compost and a core of hydrocarbon-contaminated sediment were received from the
California Mushroom Farm. Direct push methods were used to collect the intact core
from two to eight feet below ground surface into a plastic liner. The core was left in the
liner, cut into six sections, capped with parafilm and plastic end caps, and the sections
from four to eight feet were shipped on dry ice to The Pennsylvania State University. The
17
contaminated soil froze during transport, so upon arrival it was allowed to thaw slightly
at room temperature for a few hours. The separate sections were then aliquoted into
separate screw-cap glass jars and stored at 4 oC in the dark until the soil was handled for
microcosm establishment. The SMC was also stored at 4 oC until needed for microcosms.
Uncontaminated soil from the site was shipped to Penn State in glass screw cap jars at
ambient temperature and stored at 4 oC once received. This soil was utilized for various
soil characterization analyses and for spiking to create standards for GC calibration
curves. Portions of contaminated sediment and compost that were to be used for the study
were separately homogenized by sieving. The soil was sieved to eliminate rocks and
pebbles > 2 mm and the SMC was ground and sieved to eliminate or break down
fractions > 4.75 mm. Crab-shell chitin was used as received from the manufacturer in
Phase I microcosms, while fractions between 850 µm and 2 mm were utilized in Phase II
in order to create more uniform substrate conditions.
The pH, moisture content, and carbon and nitrogen content were determined for
the SMC, chitin, and site soil. The pH, moisture content, and bulk density were
determined according to standard lab methods (EPA Method 9045D; Chang and Evett,
2003; Tan, 2005). Soil was classified according to the bottle field test (Food and
Agriculture Organization of the United Nations) in which water is added to a beaker with
5 cm of soil, agitated, and allowed to settle for one hour. The percentage of silt, clay, and
sand in the separated fractions was compared to the published values for various soil
classes (United States Department of Agriculture). Carbon and nitrogen content were
determined by combustion method (Fisons NA1500 Elemental Analyzer) by The
Pennsylvania State University’s Agricultural Analytical Services Laboratory. Lead
analysis was performed on contaminated soil according to EPA Method 3015 and 6010
by the Agricultural Analytical Services Laboratory at The Pennsylvania State University.
18
2.1.3 Experimental Setup
2.1.3.1 Phase I – Substrate Evaluation
Sacrificial microcosms were established in 160 ml glass serum bottles with Teflon
stoppers and aluminum crimp caps. The conditions tested with twenty replicates each
were: 1) contaminated soil + SMC; 2) contaminated soil + SMC + chitin (nutrient
amendment); and 3) contaminated soil only (negative control). Each SMC and SMC +
chitin microcosm contained 3.33 g soil and 1.67 g SMC (5 g total wet weight) to give a
1:1 volume:volume ratio of SMC and contaminated soil. A fractional mass of chitin (0.16
g or ~10% of the wet weight of SMC utilized) was added to each SMC + chitin
microcosm. Controls contained an equivalent mass of soil as the actives, but without any
SMC or chitin. The compost/soil mixture in the microcosms was adjusted to a final
moisture content of 50% by adding 2.5 ml distilled deionized (DDI) water. The moisture
content of sediment-only controls was not adjusted so that hydrocarbon degradation
under natural soil conditions could be reported. The headspace in all microcosms was
laboratory air. The total headspace in the empty serum bottles (measured in triplicate)
was 164 mL. Based on bulk density measurements of the materials, the approximate
initial headspace in substrate amended microcosms was 157 mL and in control
microcosms was 162 mL. Microcosms were periodically sacrificed in duplicate over ten
time points based on the observed rate of remediation. Solid samples (1 g for controls or
1.5 g for actives) from each microcosm were directly extracted with hexane in a 2 mL
centrifuge tubes with 0.4 g NaSO4 followed by vortexing for 15-20 seconds to mix,
sonicating in a sonicator bath for 30 minutes, and centrifuging for 10 minutes at 10,000
rpm. At each sampling point, a small portion of solids was preserved by transferring it to
a sterile 2 mL centrifuge tube and freezing at -20 oC for future microbial analysis.
19
2.1.3.2 Phase II – Temperature Evaluation
At the time the Phase II experiments were initiated, the Phase I microcosms
containing SMC + chitin exhibited slightly higher TPH removal than the microcosms
containing SMC only. Since chitin appeared to offer an advantage for TPH remediation,
and it was believed that the use of chitin could help immobilize residual lead in the soil, it
was decided to include it in the Phase II microcosms as well.
Phase II microcosms were established as described in Phase I. All active
microcosms in Phase II contained contaminated soil, SMC, and chitin, and were tested at
the following temperatures (twenty replicates each): 1) 22 oC (room temperature); 2) 30
oC; and 3) 50
oC. Each active microcosm contained 4.44 g soil, 2.22 g SMC, and 0.16 g
chitin (wet weights, 5 g total dry weight) to give a 1:1 volume:volume ratio of
SMC:contaminated soil (the fractional amount of chitin added did not contribute
significantly to the volume of the microcosms). Microcosms were adjusted to a final
moisture content of 50% by adding 3.34 mL DDI water. Three sets of soil-only controls
were also established at each temperature. They contained 4.44 g soil and the moisture
content was not adjusted. The approximate initial headspace in substrate amended
microcosms was 155 mL and in control microcosms was 160 mL.
Microcosms were periodically sacrificed in duplicate over ten time points based
on the observed rate of remediation. However, after the fifth sampling point, soil controls
were adjusted to 20% moisture content by injecting 1 mL of distilled deionized water
through the septa using a sterile syringe and were later sacrificed in singlet to determine
the effect that the addition of water would have on intrinsic bioremediation over more
time points. Microcosm headspace was tested prior to sacrificing and periodically
between sacrificing points to ensure oxygen levels did not become limiting. The
headspace of the bottles was flushed periodically with laboratory air as needed to
replenish the oxygen supply. A few modifications to the hydrocarbon extraction
procedure were made to enhance the efficiency of the recovery process in this phase:
samples from each microcosm were directly extracted with acetone in a 2 mL centrifuge
tube with 0.4 g NaSO4 followed by vortexing for 1 minute, sonicating for 5 minutes, and
20
centrifuging for 10 minutes at 10,000 rpm. At each sampling point, a small portion of
solids was preserved as in Phase I for future microbial analysis. Moisture content and pH
were also monitored at critical points during this phase of experimentation.
2.1.4 Analysis
2.1.4.1 Headspace Gas Quantification
Oxygen concentrations were quantified using a SRI 8610B gas chromatograph
(GC) equipped with a thermal conductivity detector (TCD) and a Molesieve 5A
molecular sieve column (Alltech). Argon was used as the carrier gas with a pressure of 95
psi and the oven was held at 50 oC for 0.5 minutes, and then ramped at 5
oC/min to 70
oC.
Over the course of experimentation, the temperature program was modified due to
instrument response changes. The carrier gas pressure was changed to 80 psi and the
oven was held isothermally at 40 oC. Late in experimentation, the column was baked at
300 oC for 40 minutes to induce better peak separation. After this the carrier gas pressure
remained at 80 psi and the oven was held isothermally at 50 oC. Carbon dioxide
concentrations were quantified using a SRI 310 gas chromatograph (GC) equipped with a
thermal conductivity detector (TCD) and a Porapak Q column. Helium was used as the
carrier gas with a pressure of 85 psi and the oven was held isothermally at 70 oC.
2.1.4.2 Total Petroleum Hydrocarbon Quantification
Total petroleum hydrocarbon concentrations were determined by injecting 2 uL of
hydrocarbon extract onto an Agilent model 6890 N gas chromatograph (GC) with a flame
ionization detector (FID) and an HP-5 capillary column (J&W Scientific 25 m x 0.32 mm
x 0.52 µm). The GC program used helium as the carrier gas set at a flow rate of 6.5
mL/min with an injector temperature of 225 oC. The initial oven temperature was 45
oC
which was held for 3 minutes followed by a ramp at 12 oC/min to 225
oC where it was
21
held for 7 minutes. The total run time was 25 minutes. Pure alkane standards were used to
identify individual petroleum hydrocarbons and to calibrate the response of the GC at
each sampling point: if a standard exceeded 20% of the previously generated standard
curve, a new standard curve was generated. Standard curves for TPH were generated
from extractions performed on soils spiked with known concentrations of diesel, and the
equivalent extraction efficiency assumed for the samples. Additional information about
the extraction method development used throughout this research is provided in
Appendix B and should be consulted for future studies. Specifically, the extraction
method used in Phase I and II microcosm tests is addressed in Section B.1.2. In this
study, no hydrocarbons were detected past the elution time of the C24 alkane found in the
original samples collected from the site. Hence, total petroleum hydrocarbons were
quantified between 0.1 s before the elution time of C10 and 0.1 s after the elution time of
C24.
2.1.4.3 Statistical Analysis
Analysis of variance (ANOVA) was used to determine if the relationships
between treatment conditions were statistically significant (p > 0.05) at various time
points during the experiments. Tukey 99.0% (� = .01) simultaneous confidence intervals
were used for this analysis and results were generated using the Minitab Statistical
Software ® Program.
2.2 Phase I and II Molecular Analysis
2.2.1 DNA Extraction and Amplification
PCR-DGGE analysis was used to analyze a number of microcosm samples
preserved from Phases I and II. Amplified DNA from various treatments and time points
22
was separated by DGGE in order to visualize community shifts under these variables.
DNA was extracted from microcosm samples by a bead-beating method (MO BIO
Laboratories, Inc., Carlsbad, CA) according to the manufacturer’s instructions. PCR
amplification of the 16S rDNA was performed on the extracted DNA, by using
eubacterial universal primers I-341f-GC (5’ CGCCCGCCGCGCGCGGCGGGCGGG
GCGGGGGCACGGGGGG CCTACGGGIGGCIGCA 3’) and I-533r (5’ TIACCGIIICTI
CTGGCAC 3’) (Watanabe et al., 2001) ordered from Biosearch Technologies (Novato,
CA). PCR amplifications were performed in a 50 µL reaction volume using the Go Taq
PCR Core System (Promega Corporation, Madison, WI). Each reaction volume consisted
of 1 µL of DNA diluted 10X in nuclease free water, 0.25 µM of each primer, 1.25 U
GoTaq® DNA Polymerase, 10 µL 5X colorless buffer, 3.0 mM MgCl, 200 µM PCR
nucleotide mix, and 0.4 mg/mL bovine serum albumin (BSA) (Promega Corporation).
DNA from soil only samples was not diluted. A negative control consisting of 1 µL
nuclease free water instead of DNA was included for each master PCR reaction mixture.
Amplifications were performed in a Flexigene Thermal Cycler (Model FFG02HSD) with
the following temperature program: 10-min activation of the polymerase at 94 oC;
followed by 2 cycles consisting of 1 min melting at 94 oC, 1 min annealing at 52
oC and 2
min extending at 72 oC. The annealing temperature was subsequently decreased by 1
oC
for every second cycle until it reached 47 oC, at which point 30 additional cycles were
carried out, followed by a final 10-min extension at 72 oC. PCR products were confirmed
by electrophoresis through a 0.8% agarose gel, followed by staining with ethidium
bromide for 20 minutes and destaining in DDI water for 20 minutes. Resulting bands
were visualized by ultraviolet illumination and compared to a 50-2000 base pair PCR
markers (USB Corporation, Cleveland, OH). Fungal DNA amplification was also
attempted but was unsuccessful. Information about this procedure and recommendations
for future research are presented in Appendix D.5.
23
2.2.2 DGGE Solutions
Polyacrylamide gels (8% w/v) with a denaturing gradient from 30% to 60% were
used for denaturing gradient gel electrophoresis (DGGE) analysis. The two gel solutions
were prepared by dissolving the components in Table 2-1 in DDI water for a final volume
of 50 mL of each solution. The Tris-acetate-EDTA (TAE) buffer consisted of 50 g tris,
27.5 g boric acid, and 20 mL 0.5 M ethylenediaminetetraacetic acid (EDTA) per liter of
solution. A 10% ammonium persulfate (APS) solution (0.1 g APS/mL) was prepared and
stored at -20 oC for up to 1 month when not in use. Tetramethylethylenediamine
(TEMED) (EMD Chemical, Inc.) was used to catalyze the polymerization of acrylamide
for gel casting. Dye for the gels was made by mixing approximately 8 mL glycerol and 2
mL 0.4% bromophenol blue.
2.2.3 DGGE Community Profiling
DGGE was performed using a D-Code Universal Mutation Detection System
(Bio-Rad) on a gel with a linear chemical gradient ranging from 30% to 60% as described
in Section 2.2.2. Denaturant solutions were prepared in separate sterile plastic centrifuge
tubes by combining 15 mL of the two denaturant stock solutions with 14.5 µL TEMED
and 135 µL 10% APS. Additionally, 135 µL of dye was added to the 60% solutions in
order to visualize the gradient. Each lane was loaded with 7 µL of PCR product mixed
with 7 µL of dye. The outside lanes were not used. Gels were run at 75 V for 14 hours at
Table 2-1: Recipe for 30 and 60% denaturant polyacrilamide DGGE gels.
Component 30% Denaturant Solution* 60% Denaturant Solution
*
40 % acrylamide (mL) 10 10
50 X TAE buffer (mL) 1 1
Formamide (mL) 6 12
Urea (g) 6.3 12.6 * Solutions were stored at 4
oC for up to one month when not in use.
24
60 oC in 1X TAE. The TAE buffer was allowed to heat to 60
oC prior to loading the
samples and starting the run.
After electrophoresis, gels were fixed in 0.5 L 10% (100 mL/L) acetic acid for 30
minutes, rinsed in water three times for 5 minutes each time, stained in 0.5 L 1% (1 g/L)
silver nitrate (AgNO3) with 0.75 mL formaldehyde for 30 minutes with intermittent
gentle shaking, and developed in 0.5 L 3% (30 g/L) cold sodium carbonate (Na2CO3)
solution amended with 113 µL of 10 mg/mL sodium thiosulfate (Na2S2O3·5H2O) at the
last minute. After bands appeared, 0.5 L 10% acetic acid was added to the mixture to fix
the image. The gel was washed in clean water for approximately 5 minutes, scanned with
a UMAX PowerLook 2100 XL digital scanner, and visualized with Adobe Photoshop
Elements 2.0 software. Bands of interest were excised using a sterile razor, placed in 40
uL nuclease free water in a sterile 0.2 mL PCR tube, and the DNA was allowed to elute
overnight at 4 oC. PCR was performed as previously stated using 1 µL eluted DNA.
DGGE was performed a second time with these PCR products to confirm the presence of
the band (Appendix D.1). The singular bands in the lanes were excised and PCR was
performed on eluted DNA from these bands using the forward primer without the GC
clamp. These PCR products were sent for sequencing to The Pennsylvania State
University’s Nucleic Acid Facility and the discernable sequences were searched in the
GenBank database of the National Center for Biotechnology Information using the
BLAST algorithm (http://www.ncbi.nlm.nih.gov/BLAST).
The gel images were straightened, aligned, and analyzed using Quantity One
image analysis software (Bio-Rad). Bands were automatically detected using the
following detection settings: 14.641 sensitivity, 6.604 lane width, 0% min density, 4.00
noise filter, 1.00 shoulder sensitivity, and 5 size scale. Lane-based background
subtraction was applied to each lane using a rolling disk radius of 51. These settings were
chosen to detect all major bands in the lane without falsely identifying background
disturbances as bands. The lanes were converted into x/y plots by importing lane
information into Excel (Microsoft, Inc.). Relative front and relative quantity information
was collected from the Quantity One software. Relative front describes the distance of
each band from the top of the gel and relative quantity describes each band’s percentage
25
of the total intensity of all the bands in the lane. This information is provided in
Appendix D.2. DGGE profiles were also compared using Sorenson’s index, a pairwise
similarity coefficient Cs, which was determined by
Cs = [2j/(a+b)] x 100 (Equation 2-1)
where a is the number of DGGE bands in lane 1, b is the number of DGGE bands in lane
2, and j is the number of common DGGE bands (Murray et al., 1996; Simpson et al.,
1999).
2.3 Substrate Screening and Respirometry Tests
After composting of diesel-contaminated soil with SMC was shown to promote
significant TPH removal, additional microcosm tests were executed to analyze the
bioremediation potential of several different compost substrates. Their performance was
compared to the performance of other sustainable composting amendments against the
California Mushroom Farm’s SMC. An initial screening test was used to select the best
two performing substrates and evaluate them in a subsequent, more sampling intensive
Respirometry Test against the California Mushroom Farm SMC. The purpose of these
tests was to determine whether other locally available inexpensive substrates could be
utilized as in the previous two microcosm tests and provide additional information about
optimal composting conditions for this type of treatment.
2.3.1 Chemicals and Substrates
In the Screening Test, the performance of the previously tested California
Mushroom Farm SMC was compared to the following five readily available inexpensive
compost amendments: SMC from the Mushroom Testing Demonstration Facility at the
Pennsylvania State University; sewage sludge-based compost produced by the University
26
Area Joint Authority (UAJA) Wastewater Treatment Plant in State College, PA; and
SMC, wood chips, and peat moss from Nature’s Cover landscaping supply store in
Bellefonte, PA. Uncontaminated soil that was free of anthropogenic fertilizers or nutrient
amendments was obtained from a wooded location and sieved to < 2 mm. Substrates
were ground using a coffee grinder and sieved. The portion between 850 um and 2 mm
was utilized for microcosms. Bulk density and moisture, carbon, and nitrogen contents of
substrates and soil were determined as stated in Section 2.1.2. The composition of some
of the composts was obtained from the suppliers. Sodium azide (NaN3) (Fisher Scientific)
was used as a biocide in some tests to create abiotic controls.
2.3.2 Screening Test Setup
Soil for the Screening Test microcosms was contaminated with diesel using an
acetone spiking procedure. Sieved soil was mixed with diesel-spiked acetone at an equal
wet mass:volume ratio in a 2 L Pyrex bottle and mixed thoroughly. The bottle opening
was covered with Teflon tape and sealed with a plastic screw cap. The volume of diesel
added to the acetone prior to mixing with soil yielded a theoretical diesel concentration in
the soil of 4630 mg/kg on a dry weight basis. Acetone was added to soil at an equal
volume:wet mass ratio. (In this case, the measured density of diesel was 0.847 g/mL, so
300 mL of acetone were spiked with 1.771 mL (1000 mg) diesel and combined with 300
g wet soil (216 g dry weight)). The bottle was placed upright on an orbital shaker at
approximately 1200 rpm in the dark for 24 hours. After 24 hours, it was spread into a
glass pan under the hood and the acetone was allowed to evaporate for ~2 hours. This
solvent spiking and evaporation procedure is consistent with that found in the scientific
literature (Gunther et al., 1996; Kastner and Mahro, 1996; Lau et al., 2003). The spiked
soil was stored in the capped glass bottle at 4 oC for less than 72 hours until microcosm
establishment.
Microcosms containing spiked soil and one of each of the six substrates described
in Section 2.3.1 were prepared in quadruplicate in 160 mL glass serum bottles with
Teflon stoppers and aluminum crimp caps. Substrate microcosms contained an equal
27
volume:volume ratio of substrate and soil. Moisture content was adjusted to 50% and a
20 gauge needle was inserted into each microcosm septum to allow for continuous
passive oxygen replenishment. Three control conditions were established in a similar
manner as follows: 1) soil only condition to measure contaminant removal without the
addition of substrate (control soil only), 2) soil only condition treated with 0.5% or 0.07 g
of the biocide sodium azide (NaN3) to measure abiotic contaminant removal (abiotic
control), 3) a soil only condition without a needle inserted into the septum to limit
volatilization and measure removal attributable to sorption (sealed abiotic control). The
contents of the microcosms under each condition are listed in Table 2-2. The microcosms
were incubated in the dark at 22 oC on a rotating platform shaker for 21 days. Additional
water was supplied to the substrate-amended conditions 6 days after set-up due to the
appearance of visibly drier conditions. Assuming that moisture reduction was
proportional in all substrate conditions, an equivalent volume of water was added as was
originally supplied at the time of microcosm set-up for each condition. TPH
concentrations were obtained by sacrificing microcosms in duplicate directly following
preparation on day 0 and again on day 21. The length of this experiment was based on the
duration of active hydrocarbon remediation observed in Phase I and II, after which
hydrocarbon removal plateaued. It was thought that the TPH concentration differences
between 0 and 21 days in this test would provide insight into the influence of the various
substrates on bioremediation.
28
2.3.3 Respirometry Test Setup
The two best performers from the Screening Test were chosen for a more
sampling-intensive Substrate Comparison Test against the California Mushroom Farm
SMC using a respirometer. These were Penn State SMC and UAJA Compost. This test
used killed controls that were prepared identically to actives (with compost) rather than
soil-only controls because Phase I and II had already demonstrated that soil only controls
would exhibit much lower removal levels than substrate amended conditions. The
objective of this preparation was to determine the extractable fraction of contaminant that
was diminished by abiotic processes, such as sorption to organic matter. The killed-
controls were amended with 1 g of NaN3, since 0.07 g had been shown to be insufficient
at stopping all microbial activity in the Screening Test. On day 15, the production of CO2
Table 2-2: Contents of Screening Test Microcosms prepared at a 1:1 volume:volume ratio
(9 mL of each) and adjusted to 50 % moisture.
Substrate Amendment
(Prepared in
quadruplicate for two
sampling points)
Mass of
substrate
(g)*
Mass of
soil
(g)*
Volume of
Water (mL)
Approximate
Headspace
(mL)***
CA Mushroom Farm
SMC
6.75 (3.14) 9 (6.48) 3.57 142
Penn State SMC 3.89 (2.52) 9 (6.48) 5.07 141
Nature’s Cover SMC 4.90 (2.91) 9 (6.48) 4.85 141
UAJA Compost 3.02 (2.37) 9 (6.48) 5.70 140
Wood Chips 2.04 (1.88) 9 (6.48) 5.70 140
Peat Moss 1.39 (1.27) 9 (6.48) 6.35 140
None – Soil Only
Control
0 9 (6.48) 3.96 151
None – Abiotic Control 0 9 (6.48) +
0.07
NaN3**
3.96 151
None – Sealed Abiotic
Control
0 9 (6.48) +
0.07
NaN3**
3.96 151
*
wet mass (dry mass) **
NaN3 was dissolved in water prior to moisture adjustment. ***
Based on average total bottle headspace and bulk density measurements.
29
indicated that the microbial community may not have been fully suppressed and an
additional 2 g of NaN3 was added to each killed control.
For the Respirometry Tests, fresh compost was obtained from the California
Mushroom Farm, Inc. to ensure that its performance in the Screening Test was not
compromised by the length of storage. All other composts had been collected and stored
at 4 oC for no more than one week prior to the start of the Screening Test. Also, the
spiking procedure was altered to reflect the concern that the large quantity of solvent used
in the previous procedure could have been toxic to the microbial community and
decreased the number of viable microorganisms (Brinch et al., 2002, Reid et al., 1998). A
less solvent intensive procedure, which minimized potential alterations to the soil’s
natural microbial populations, was used as follows. A quarter of the clean soil was
combined with a 1:1 (mass to volume) ratio of acetone spiked with enough diesel to bring
the total soil mass to 5000 mg/kg level of contamination (dry weight basis). Then the
other 75% of the soil was added to the mix in a 2 L glass bottle and thoroughly mixed
with a glass rod. (In this case, a total of 900 g wet (625.5 g dry) soil was used. A solution
of 3.69 mL (3.13 g) diesel in 22.5 mL acetone was added to 225 g wet soil and mixed.
The other 675 g of soil was added to this mixture and stirred periodically.) The bottle
was capped and agitated by hand shaking to promote homogeneity and was placed
vertically on a rotating shaker in the dark at 22 oC for 24 hours.
Substrates and soil were pretreated as in the Screening Test. An equal dry mass:
dry mass ratio of soil to substrate was used in the preparation of each condition to better
compare relative amount of substrate necessary for treatment (Table 2-3). The design of
these experiment was altered from the equal volume:volume ratio used in Phase I and II
because the different densities of the substrates meant that very different amounts would
be used in the different bottles. In this new preparation, each microcosm contained the
same dry masses of soil and substrate, and equal volumes of water. The moisture content
of the resulting mixture was adjusted to 50% (Table 2-3). Two 20 gauge needles were
inserted into the septum of each bottle to allow for passive replenishment of oxygen.
Microcosms were stored in a lab drawer at room temperature and sampled on days 0, 15,
30
30, and 62. After sampling on days 0 and 15, distilled deionized water was added to bring
the moisture content back up to 50%.
Six additional microcosm bottles were prepared, each one like a different compost
condition as listed in Table 2-3. These were run identically and in parallel to the other
microcosms but connected to a respirometer system from day 0 to day 30 to continuously
record the oxygen utilization profiles and compare them to hydrocarbon remediation rates
under each of the different substrate conditions. The Challenge ANR -100 Respirometer
(Challenge Environmental Systems, Inc. Fayetteville, AK) consists of reaction vessels
(microcosm bottles), oxygen flow measuring cells, an oxygen generation unit, and a
computer for data collection at 10 minute intervals. A 30% KOH solution (2.5 mL) was
placed in each bottle prior to capping, to absorb the CO2 produced. This created a
vacuum within each reaction vessel that drew oxygen into the bottle and across the
respirometer’s measuring cell (Figure 2-1). The number of oxygen bubbles (of a
predetermined calibrated volume) passing through the cell were recorded by the
computer and converted to a cumulative oxygen mass value.
Table 2-3: Contents of Respirometry Test microcosms prepared at a 1:1 dry mass:dry mass ratio
(5 grams dry weight of each) and adjusted to 50 % moisture .
Substrate
Amendment
Mass of
substrate (g)*
Mass of soil
(g)
Volume of
Water (mL)
Approximate
Headspace (mL) ***
CA Mushroom
Farm SMC
11.16 (5) 6.68 (5) 2.16 140
Abiotic CA
Mushroom Farm
SMC
11.16 (5) 6.68 (5) 2.16**
140
Penn State SMC 8.14 (5) 6.68 (5) 5.18 133
Abiotic Penn
State SMC
8.14 (5) 6.68 (5) 5.18**
133
UAJA Compost 6.35 (5) 6.68 (5) 5.98 140
Abiotic UAJA
Compost
6.35 (5) 6.68 (5) 5.98**
140
* wet mass (dry mass)
** 1 g NaN3 was dissolved in water prior to moisture adjustment.
*** Based on average total bottle headspace and bulk density measurements.
31
2.3.4 Analysis
Headspace carbon dioxide concentrations were measured prior to sampling as
stated in Section 2.1.4.1. TPH concentrations in both substrate comparison tests were
quantified by a mechanical shaking extraction procedure modified from Schwab et al.
(1999) with elements from Jorgensen et al. (2005) (Appendix B.1.3). The extraction
procedure was optimized to obtain acceptable extraction efficiencies and correlate
extraction concentrations to soil concentration using the diesel standard curve. In
conjunction with this method, each microcosm’s moisture content was determined
following sacrificing. For each extraction, solids (5 g) were weighed into 20 mL
scintillation vials with 0.5 g NaSO4, and 10 mL of solvent was added to each vial. The
vials were sealed with a foil-lined cap and shaken vigorously by hand for 1 minute,
followed by shaking on a reciprocating platform shaker for 30 minutes. The extracts were
centrifuged for 10 minutes at 180 g and removed carefully from the centrifuge. Samples
(a) (b)
Figure 2-1: Bioreactor schematic with similar configuration to Respirometer Test microcosm bottles that
were connected to a Data Logger to measure oxygen usage (Zytner et al., 2006) (a) and actual
Respirometer Test bioreactor configuration. Microcosm bottles were connected to a computer data
logger to measure oxygen usage. The red arrows indicate the flow of oxygen.
32
were analyzed using a GC-FID as described in Section 2.1.4.2 immediately after
centrifuging or were stored at 4 oC for no more than 30 minutes and then analyzed.
Moisture contents of each microcosm were measured after sacrificing. The equation to
determine the sample concentration is as follows:
CHC = Cgc x 10/ m x ds (Equation 2-1)
where CHC equals the concentration of hydrocarbons in the diesel range in the sample
(µg/mL or ppm), Cgc equals the concentration of extract from the standard curve
(µg/mL), 10 equals the extraction solvent volume (mL), m equals the mass of sample on
which extraction was performed (g), ds equals the dry material in moist sample (g/g)
(modified from Jorgensen et al., 2005).
33
Chapter 3
Results
3.1 Phase I and II Microcosm Tests
3.1.1 Composting Conditions
3.1.1.1 Substrate Characterization
Some analyses could not be performed on contaminated soil from the site for
safety reasons, so uncontaminated sediment from very near the contaminated area was
used as a surrogate. The uncontaminated sediment was classified as a sandy soil (Table
3-1) based on United States Department of Agriculture (USDA) guidelines. The
uncontaminated sediment had a fairly low carbon and nitrogen content and slightly basic
pH (Table 3-2). pH was measured during the course of Phase II experimentation and
remained circumneutral (7.8 ± 0.06; Appendix C). Contaminated core was used to
determine moisture content (6.76 %) and lead content (6.92 ppm) of the contaminated
area. The EPA soil standard for lead in play areas is 400 ppm and 1200 ppm for bare soils
in residential areas. However, 15 µg/L is the action level concentration for drinking water
(USEPA 2001) and most of the contamination lies at or below the groundwater table as
reported by Rincon Consultants, Inc. who performed the initial site characterization. It’s
unknown whether groundwater at the site is used for drinking water. The basic properties
of chitin and SMC were also determined (Table 3-2).
34
3.1.1.2 Moisture Content
Moisture content in the closed microcosms decreased considerably over the
course of the experiments. Figure 3-1 shows the decrease in moisture content in Phase I
microcosms measured at two time points during the course of treatment. The initial
theoretical moisture content was 50% for the two substrate amended conditions based on
moisture contents of SMC and soil and additional water delivered to microcosms at set-
up. The measured moisture content in controls was ~7%. Substrate conditions did not
have an appreciable effect on water loss: the chitin-containing microcosms lost slightly
more moisture (~60%) than the microcosms which only contained SMC (~58%) over the
course of over seven months from the initial theoretical value. However, over this
Table 3-1: Classification of The California Mushroom Farm soil based on USDA
guidelines.
Classification Clay
(%)
Silt
(%)
Sand
(%) Common Name Textural
Class
USDA Guidelines
(See Appendix A)
0-10 0-14
86-100
Sandy soils
(course texture)
Sand
Uncontaminated soil from
The CA Mushroom Farm
2.63
10.53
86.84
Sandy Soil
Sand
Table 3-2: Chemical properties of three substrates used in Phase I and II microcosm tests.
Soil SMC Chitin
pH* 8.2 8.0 8.2
Carbon Content (%)* 0.14 8.96 20.24
Nitrogen Content (%)* 0.01 0.64 3.92
Moisture Content (%) 6.76 61.2 6.8
Sieve Analysis 5.6% > 2 mm
2 mm > 8.1% >
850 µm
86.3% < 850 µm
3.0% > 2 mm
2 mm > 12.6 % >
850 µm
84.5% < 850 µm
6.3% > 2 mm
2 mm > 37.5% >
850 µm
56.3% < 850 µm * Analyses performed on The California Mushroom Farm uncontaminated soil.
35
extended time period, moisture content in the controls decreased ~95%. Until day 86,
moisture content loss was comparable at 51%, 56%, and 54% loss for the soil + SMC,
soil + SMC + chitin, and soil only, respectively. The final moisture content of the active
microcosms at t = 215 days approached 20%, which is sufficient for microbial activity,
but slightly lower than the optimal for composting (25 – 80%; Richard et al., 2002).
More frequent monitoring of moisture content was performed during Phase II. The
theoretical moisture content adjusted on day 0 was 50% in active microcosms. Measured
values stabilized between 20% and 30% between days 8 and 160 (Figures 3-2 and 3-3).
The low moisture content measured in soil only controls on day 26 prompted moisture
content adjustment in these microcosms to 20% on day 27 (within 24 hours of sampling
on day 26), to ensure that lack of moisture was not suppressing remediation. The average
final moisture contents measured on day 160 in actives at 22 oC, 30
oC, and 50
oC were
29.44%, 22.90%, and 25.34%, respectively.
20.769
0.3393.194
21.80024.628
19.858
0
5
10
15
20
25
30
35
soil + SMC soil + SMC + chitin soil only
Mo
istu
re C
on
ten
t (%
))
t = 86 d
t = 215 d
Figure 3-1: Moisture content at two time points during the course of treatment in closed
Phase I microcosms (22 oC). Values are measured duplicate averages; error bars represent
one standard deviation.
36
3.1.2 Oxygen and Carbon Dioxide Headspace Concentrations
At the beginning of the Phase I substrate evaluation test, microcosms were
periodically injected with lab air to supply oxygen. On day 62, headspace was purged due
to the presence of limiting oxygen conditions, and a subsequent decrease in TPH
concentration was detected (Figure 3-8). Sharp decreases in the molar ratio of oxygen to
carbon dioxide in active microcosms between days 78 and 85 and a high rate of carbon
dioxide production as compared to later time points (Figures 3-3 and 3-4) indicate a
revival in respiration and therefore an increase in microbial activity. Molar ratios of
O2:CO2 above 1.5 are sufficient to support aerobic degradation of diesel range
hydrocarbons. Its slower depletion while still above this lower limit indicated a slowing
of microbial activity rather than oxygen limitation. It is clear from Figures 3-3 and 3-4
0
10
20
30
40
50
60
70
80
0 20 40 60 80 100 120 140 160
Time Elapsed (d)
Mois
ture
Conte
nt (%
))Active 22 C
Active 30 C
Active 50 C
Control 22 C
Control 30 C
Control 50 C
Theoretical based on initial moisture
content adjustment.
Natural moisture content
of contaminated soil.
Moisture content
adjusted on day 27.
Figure 3-2: Moisture content in closed Phase II microcosms at different temperatures over
time. Values are duplicate averages for actives, singlet measurements for controls. Error
bars represent one standard deviation.
37
that the chitin-containing condition depleted the headspace gas concentration ratio faster
than did the condition without chitin. Additionally, the chitin-containing bottles
demonstrated much greater carbon dioxide production after headspace purging.
0
2
4
6
8
10
12
75 85 95
Time (d)
O2
: C
O2
(Mola
r B
asis
)
soil + SMC
soil + SMC + chitin
Figure 3-3: Headspace gas concentration ratio in Phase I active microcosms during mid-
points in composting treatment. The sharp decrease in ratios between days 78 and 85 is
attributed to a revival of microbial activity due to headspace purging with air.
0
5
10
15
20
25
30
78-85 153-182 184-208
Time Period of Treatment (d)
Car
bo
n D
iox
ide
Pro
du
ctio
n (
um
ol/
d))
soil + SMC
soil + SMC + chitin
soil only
Figure 3-4: Carbon dioxide production rates during later time points of Phase I treatment.
Carbon dioxide production rates were calculated by dividing the difference between the
moles of carbon dioxide in 1 mL of headspace at each sampling by the number of days
elapsed between sampling and multiplying by 157 mL approximate headspace volume in
active microcosms and 162 mL approximate headspace volume in control microcosms.
38
In the second half of Phase I, and throughout Phase II, oxygen and carbon dioxide
concentrations were closely monitored to ensure that the molar ratio in the microcosms
did not fall below 1.5 (Baker et al., 2000; Van de Steene and Verplancke, 2007). If this
was detected for any of the conditions at any time, all remaining bottles were flushed
with lab air for 15-20 minutes to fully purge the microcosm headspace and replenish
oxygen levels.
Carbon dioxide production rates were calculated for the Phase II temperature
evaluation test. These rates (Figure 3-5) could only be determined between sampling or
headspace purging events, since purging the bottles reset the carbon dioxide levels. Thus,
continuous carbon dioxide production rates could not be calculated for the entire course
of the experiment, but were whenever possible. The molar rate of carbon dioxide
produced per day was highest during the first days of experimentation, dropped
dramatically, and decreased unsteadily until it plateaued later in the experiment. Rates
were lowest in the 22 oC microcosms for the majority of the experiment. Carbon dioxide
production was higher in the 50 oC microcosms at first but was surpassed by the 30
oC
microcosms before day 26. For most of the experiment, carbon dioxide production
remained close in the 30 and 50 oC microcosms. In the controls, carbon dioxide
production remained minor and oxygen utilization was much lower than actives, as
would be expected in the absence of substrate.
39
A similar rate analysis was attempted for oxygen utilization profiles, but results
were much more variable and clear trends could not be detected in the different
temperature conditions. However, it is interesting to note that cumulative carbon dioxide
production and oxygen utilization profiles were very similar under the three temperature
conditions over time (Figures 3-6 and 3-7). These were not truly cumulative gas
measurements since the microcosm system was not set up for continuous analysis but
within the time intervals that could be measured, carbon dioxide production and oxygen
utilization was highest in the 50 oC microcosms, followed by the 30
oC microcosms and
22 o
C microcosms, respectively. Both gas profiles for all conditions show a gradual
increase followed by stabilization and finally a slight increase at the end of the
experiment. Also, it is seen from Figures 3-6 and 3-7 that a greater number of moles of
oxygen were consumed per mole of carbon dioxide produced, as would be expected from
the stoichiometry of hydrocarbon mineralization (Equation 1-1).
Figure 3-5: Carbon dioxide production rates at various time intervals under three temperature
conditions in closed Phase II microcosms amended with SMC + chitin. Carbon dioxide
production rates were calculated by dividing the difference between the moles of carbon
dioxide in 1 mL of headspace at each sampling by the number of days elapsed between
sampling and multiplying by 155 mL approximate headspace volume in active microcosms.
40
Figure 3-6: Cumulative carbon dioxide production integrated over time intervals under
three substrate amended temperature conditions in closed Phase II microcosms. Values
were calculated by summing the moles in each time interval presented in Figure 3-6 with
the moles of previous intervals and multiplying the total number of days in each interval.
Figure 3-7: Cumulative oxygen utilization integrated over various time intervals under
three substrate amended temperature conditions in closed Phase II microcosms. Values
were calculated by summing the moles in each time interval presented in Figure 3-7 with
the moles of previous intervals and multiplying the total number of days in each interval.
41
3.1.3 Total Petroleum Hydrocarbon Concentrations
3.1.3.1 Phase I Results
In Phase I, both substrate mixtures were effective at supporting the degradation of
hydrocarbons, while the soil-only control was not. The SMC + chitin microcosms
followed the same overall trend as the SMC only microcosms, but were able to achieve a
lower concentration at the beginning of the experiment (Figure 3-8). Despite this
advantage at early times, microcosms amended with SMC + chitin did not significantly
enhance overall TPH remediation when compared to microcosms amended with SMC
only (p = 0.855 at the 95% confidence interval). SMC microcosms displayed an apparent
increase in TPH concentration during the first 20 days of sampling. This occurrence has
been shown in other studies (Heswani and McCartney, 2006; Nocentini et al., 2000;
Zytner et al., 2006) and may be caused by uneven mixing of the soil or distribution of the
contaminant, or GC detection of some intermediate or metabolite whose formation was
inhibited in the SMC + chitin microcosms (Zytner et al., 2006). Only a slight apparent
increase in TPH concentration was detected in microcosms containing chitin.
An apparent lag in hydrocarbon degradation was observed between days 49 and
62 during Phase I (Figure 3-8). This may be a result of oxygen limitation, as previously
discussed, or the occurrence of an acclimation period in which microbial communities
were selected according to the remaining contaminant. After the decrease observed after
day 62, the gas concentrations in the headspace of the final set of Phase I microcosms
were closely monitored and the bottles were held from sampling for an extended period
of time to ensure that the lowest achievable hydrocarbon concentration would be reached.
Frequent aeration until day 215 was not able to stimulate a significant decrease in the
hydrocarbon concentrations in active microcosms below the concentrations observed on
day 86 (p = 0.916 at the 95 % confidence interval). However, the TPH concentration in
the controls did exhibit an average decrease (Table 3-3). The additional aeration may
have stimulated volatilization of contaminants, but when considering the range of
42
concentrations in duplicates shown by error bars, the concentration decrease may not
have actually been as sharp.
Although TPH concentrations in microcosms containing SMC only were further
reduced with continued incubation, the rate of removal decreased greatly after day 86
(Table 3-3). Microcosms containing SMC + chitin did not show further reduction in TPH
with extended incubation. In 216 days of treatment, microcosms containing SMC had a
final TPH concentration of 265 mg/kg of soil (84% removal), while those containing
SMC + chitin reached a final TPH concentration of 373 mg/kg of soil (78% removal).
Compared to the initial concentrations in the substrate amended microcosms, TPH
removal in the controls was 36%.
Table 3-3: Comparison of Phase I TPH removal rates and TPH concentrations in active
microcosms containing different substrates at 22 oC. The concentration units ppm refer to
mg TPH/kg soil.
Amendment Rate of removal
between t = 0
and t = 86 d
(ppm/day)
Rate of removal
between t = 86
and t = 215 d
(ppm/day)
Average TPH
Concentration
at t = 86 d
(ppm)
Average TPH
Concentration
at t = 215 d
(ppm)
SMC 16 0.27 300 265
SMC + chitin 15 0.00 363 373
Soil (control) 8.0* 5.8 1990 1241
NOTE: The rate of removal was calculated by dividing the difference in concentrations between the two
sampling times by the number of days elapsed. * Accurate data was not obtained for t = 0 so the rate was calculated from t=1.
0
1000
2000
3000
4000
5000
6000
7000
8000
0 20 40 60 80 100 120 140 160 180 200 220
Time Elapsed (d)
Die
sel
Ran
ge
TP
H (
mg/k
g s
oil)
)com
eon!
SMC + chitin
SMC
Soil (Control)
Figure 3-8: Decrease in Total Petroleum Hydrocarbons (diesel range) during the Phase I microcosm testing with
different substrates at 22 oC. Data points are duplicate averages; error bars represent one standard deviation.
3.1.3.2 Phase II Results
In Phase II, microcosms showed different TPH removal trends at early times
depending on temperature, but final concentrations in microcosms at the various
temperatures were not significantly different (p = 0.175 at the 95% confidence interval).
The microbial community’s performance was apparently not greatly affected by the
different temperature conditions of 22 oC, 30
oC, and 50
oC (Figure 3-10).
First-order TPH degradation rates for various time periods in Phase II are listed in
Table 3-4, and the TPH concentrations and total removal observed for the different
treatments measured are provided in Table 3-5. Like in Phase I microcosms, a decrease
in hydrocarbon removal rates was observed in Phase II after the first 20 days of sampling
(Figure 3-9 and Table 3-4). Microcosms at 50 oC exhibited the highest TPH removal rates
initially, while microcosms at 30 oC exhibited the highest removal rate for a longer period
of time, during the final 140 days of experimentation. Ultimately, the rate of remediation
was lowest in the 50 oC microcosms after the first 20 days of experimentation. Similar to
Phase I, sampling of the final point in Phase II was prolonged in order to more accurately
determine the extent of remediation that could be achieved. It is interesting to note that
the removal trends in Phase II (Figure 3-9) resemble the carbon dioxide production rate
trends (Figure 3-5). Both began high and tapered towards the end of the experiment.
Removal was greatest in 30 oC active microcosms and lowest in 30
oC control
microcosms. Nonetheless, Phase II results indicate that temperature does not play a very
important role in enhancing hydrocarbon removal from the site soil (Table 3-5 and Figure
3-9).
45
In this research, although none of the active conditions in either phase reached the
California requirement of 100 ppm, or 100 mg TPH/kg of soil, once the compost and soil
are mixed on the full-scale, they will no longer be able to be separated and will not be
quantified on a soil mass basis. The dilution factor of adding substrates to the soil can be
taken into account to predict what the actual concentration (mg TPH/mg solids) measured
in the field would be. A dilution factor of 1.24 is obtained by realizing that in each active
microcosm, there are 5.15 g dry solids (4.14 g soil, 0.86 g SMC, and ~0.15 g chitin) for
each 4.14 g dry soil. Thus, 5.15/4.14 yields 1.24. By dividing the concentration per mass
of soil measured in Phase II (Table 3-5) by the dilution factor, concentrations of 169, 146,
and 218 mg TPH/kg solids are obtained for actives at 22 oC, 30
oC, and 50
oC,
respectively.
Table 3-4: Changes in average TPH removal rates* for active Phase II microcosms over
time. The concentration units ppm refer to mg TPH/kg of soil.
22 oC Actives 30
oC Actives 50
oC Actives
Days 0 – 20 57 ppm/day 53 ppm/day 58 ppm/day
Days 20 – 160 1.8 ppm/day 2.6 ppm/day 1.3 ppm/day
Overall: Days 0 – 160 10 ppm/day 10 ppm/day 8.4 ppm/day * Removal rates were calculated by dividing the difference in TPH concentration by the listed time points.
Table 3-5: Approximate TPH removal in Phase II microcosms under all tested conditions
over 160 days of treatment. The concentration units ppm refer to mg TPH/kg of soil.
Condition Initial TPH
concentration
(ppm)
TPH concentration
after 160 days
(ppm)
Overall Removal
(Initial –
Final)/Initial
Active 22 oC 1610 210 87 %
Active 30 oC 1610 181 89 %
Active 50 oC 1610 270 83 %
Control 22 oC 1530 530 65 %
Control 30 oC 1530 960 37 %
Control 50 oC 1530 390 74 %
46
3.1.4 Comparison of Phase I and II Removal Rates
Faster TPH degradation rates were observed in Phase II as compared to Phase I
(Figure 3-10), supporting the conclusion that the Phase I microcosms were probably
oxygen limited. In only 20 days of Phase II experimentation, hydrocarbon concentrations
decreased to lower levels than those that had been achieved after 62 days of Phase I. By
close to day 86, removal rates were comparable between Phases I and II, but Phase II
microcosms ultimately achieved higher removals. Initial monitoring could have an
important effect on the final outcome of treatment. Final TPH concentrations for Phase I
SMC treated microcosms (without chitin) were comparable to those attained in Phase II
at 50 oC (Tables 3-3 and 3-5).
Observed TPH concentrations throughout the course of Phase II support the
previously reported conclusion that the majority of remediation occurs within the first
few weeks of treatment. In Phase II, the greatest rate of removal was observed during the
first 20 days when TPH concentrations decreased by over 1000 ppm in all active
microcosms. This was followed by an extended period of very slow removal where
concentrations only decreased by 257 ppm in 22 oC actives, 371 ppm in 30
oC actives,
and 181 ppm in 50 oC actives over the next 140 days (Figure 3-10).
0
500
1000
1500
2000
2500
3000
3500
4000
0 20 40 60 80 100 120 140 160
Time Elapsed (d)
Die
sel R
ange
TP
H (
mg/k
g s
oil)
))
Active 22 C Control 22 C
Active 30 C Control 30 C
Active 50 C Control 50 C
Figure 3-9: Decrease in Total Petroleum Hydrocarbons (diesel range) during Phase II microcosm testing with SMC + chitin
under different temperature conditions. Data points for the active microcosms are duplicate averages; error bars represent one
standard deviation.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 15 30 45 60 75 90 105 120 135 150 165 180 195 210
Time Elapsed (d)
TP
H F
ract
ion R
emai
nin
g (
C/C
o))))
SMC, 22 C
SMC+ chitin, 22 C
SMC + chitin, 22 C
SMC + chitin, 30 C
SMC + chitin, 50 C
Phase I
Phase II
Figure 3-10: Comparison of TPH removal rates for Phase I and II active microcosms.
3.1.5 Degradation Patterns in Diesel Chromatograms
As expected, chromatograms of weathered (naturally degraded) samples appear
quite different from chromatograms of fresh contaminants (Figure 3-11). The
chromatogram of fresh diesel contamination (Figure 3-11a) clearly illustrates
distinguishable peaks for each readily degradable alkane, whereas the unsymmetrical and
jagged diesel hump with shorter peaks in the weathered soil obtained from the California
Mushroom Farm indicates a sample with degraded components and a smaller percentage
of straight chained alkanes (Figure 3-11b). This indicates that some of the more easily
degradable compounds were already absent from the initial sample, and that the
remaining unresolved complex mixture (UCM) may be difficult to degrade.
The chromatogram in Figure 3-12 (a) illustrates the decrease in TPH area over
time for Phase I microcosms containing SMC as the substrate. The individual alkane
peaks were preferentially degraded, and by day 86 the remaining portion consisted
mainly of the UCM. This chromatographic pattern was consistently detected among all
microcosms for the duration of the experiment. Figure 3-12 (b) shows the preferential
degradation of lower molecular weight compounds which elute earlier in the GC run (on
the left side of the chromatogram) in control microcosms containing only contaminated
soil.
Degradation patterns in Phase II active microcosms containing contaminated soil,
SMC, and chitin at the same sampling time are presented in Figure 3-13. It is evident that
the shape of the chromatograms and area of remaining contaminants are almost identical,
which is reflective of the very similar TPH concentrations at this and subsequent
sampling points.
50
(a)
(b)
Figure 3-11: Example chromatograms of fresh diesel (a) and weathered diesel (b)
extracted from a contaminated soil sample at t = 0.
51
(a)
(b)
Figure 3-12: Comparison of TPH chromatograms in Phase I microcosms containing SMC (a) and
soil only (b) over time. The blue chromatograms were observed on day 4, and the red observed
on day 86. The preferential degradation of lower-molecular weight compounds is apparent by the
decrease in faster-eluting peaks on the left side of the chromatograms.
Soil + SMC
Soil (Control)
52
3.2 Phase I and II Molecular Analysis
The PCR-DGGE analyses revealed that bacterial communities from both soil and
compost undergoing various hydrocarbon treatment conditions were quite diverse. Both
actives and controls in Phases I and II exhibited a great number of DGGE bands. A few
bands were quite pronounced and common to either active or control conditions, but all
lanes showed that the majority of bands were faint and in close proximity to each other.
Chromatograms generated for each DGGE lane helped compare band intensities and
locations (Figures 3-14, 3-15, and 3-16). Band detection with Quantity One selected the
most prominent bands and the intensity fraction that they represented in each lane. These
are listed in tabular format against their relative movement from the top of the lane
(Appendix D) to better exhibit bands that were common to various conditions. Gel lanes
Figure 3-13: Overlay of TPH chromatograms observed for the active microcosms
containing SMC + chitin at different temperatures on day 26 of Phase II. The blue, red,
and green chromatograms represent active microcosms extracts at 22 oC, 30
oC, and 50
oC, respectively.
53
in the Phase II gel were rearranged in this plot for better comparisons between conditions.
The percentages given represent each band’s fraction of the total sample.
Phase I PCR products from days 4, 9, 19, and 86 for the three substrate conditions
were run on a DGGE gel. However, PCR products were not successfully produced for the
SMC + soil + chitin condition on day 19 so the lane appeared blank. PCR products from
the soil only samples display fewer but darker bands, and PCR products from chitin-
containing microcosms display the greatest overall number of bands (i.e., the most
diversity), presumably due to the additional microbial community component in these
microcosms (Figure 3-14). Most treatment conditions show a pronounced band that is
darkest in active microcosms, which decreases in intensity in soil only controls from day
4 until it is not detectable on day 86. It also decreases in intensity in actives but not as
strongly and is still detectable on day 86.
Phase II PCR products from actives on day 0, day 1 at 50 oC, day 4 at 22
oC, and
days 4, 8, 20, and 56 at 30 oC were run along with controls on day 0, 8, 20, and 56 at 30
oC, as well as amplified DNA from chitin and SMC. The early active time points were
selected for microbial analysis because they encompassed the times during treatment
when apparent jumps in TPH concentration were seen. In the Phase II gel, generally, the
abundance of bands in the lanes increase from early time points (t = 0 to t = 8) to later
time points (t = 20 to t = 56). Phase II lanes exhibit many more bands than Phase I. Most
prominent bands are common either to actives or controls (Figure 3-15). Some bands
present at t = 0 remained strong within each treatment, while others appeared later in
active samples to create more complex banding patterns. In addition to those indicated in
Figure 3-15, observations can be made about the banding patterns from the tables in
Appendix D.2. One band at Rf value 0.53 was present in most actives and in DNA
extracted from an SC-20 chitin sample. Another band at Rf value 0.43 was present in all
actives after t = 0 but only in the control at t = 0. Also, actives show a greater abundance
and a number of common bands that are not present in controls. The banding pattern
shows no obvious relation to the duration and type of treatment.
A gel was also run with DNA extracted from samples taken from different
portions of the diesel-contaminated soil core that was shipped from the California
54
Mushroom Farm (Figure 3-16). The lanes in this gel represent contaminated soil from
different depths below ground and exhibit much less diversity than the other two gels but
do have several darker bands which are common to multiple lanes/depths.
PCR products amplified from bands of interest were sent for sequencing analysis.
For some samples, no discernable sequences were obtained. For most samples, indistinct
sequences were obtained, presumably due to interference by other sequences or
fragments. Results of the sequence analysis for the 11 bands that were sequenced can be
found in Appendix D.3 and additional sequencing results from cloning the DNA of two
bands can be found in Appendix D.4. From the characterizations of the results, several
genera and species have been isolated from hydrocarbon-rich environments but no
community members with documented hydrocarbon degrading capability were found in
the microcosms. Many sequences also represented various bacteria with the same %
similarity. However, no real commonality was found between different conditions and
time points investigated through sequencing.
55
Figure 3-14: Phase I DGGE Gel and lane image profiles generated by image analysis. The y-axis is the lane
intensity and the x-axis is the reference front or distance from the top of the gel. Some observed banding patterns
are indicated by black arrows and matching colored circles.
Figure 3-15: Phase II DGGE Gel and lane image profiles generated by image analysis. The y-axis is the
lane intensity and the x-axis is the reference front or distance from the top of the gel. Some band
commonalities are indicated by black arrows and matching colored circles.
57
Sorensen’s indices are presented in Tables 3-6, 3-7, and 3-8 for the three gels.
Values could range between 0 and 100, where if the banding patterns from two samples
were identical the index would be 100% and if the banding patterns from two samples
were completely different, it would be 0%. Values ranged from 11 to 67% with an
average of 31% for the Phase I gel, 0 to 56% with an average of 21% for the Phase II gel,
and 0 to 86% with an average of 33% for contaminated soil from various depths below
ground.
The greatest correlations (67%) for Phase I were found between samples from day
19 and 86 for both substrate-amended conditions. Generally, higher correlations (> 40%)
Figure 3-16: DGGE Gel for contaminated soil at different depths below ground and lane
image profiles generated by image analysis. The y-axis is the lane intensity and the x-axis
is the reference front or distance from the top of the gel.
58
were found between the soil only condition on day 86 and the two substrate-amended
conditions, and between the chitin-amended condition on day 86 and all control samples.
The greatest correlation (56%) was found between controls at 30 oC on days 20 and 56.
The second highest correlation (55%) was found between actives on day 4 at 30 oC and
22 oC. All actives showed some relationship to each other, while some active samples
were completely unrelated to controls. The relationships between active and controls
were generally low with most between 0 and 22%, while the relationship between actives
at different times and under different conditions was generally higher with all between 25
and 55% except for two samples. For the gel with soil core DNA, relationships were
extremely varied. These relationships give more of a related versus unrelated observation
of the different samples with some not being related at all and most with 40% similarity.
The highest correlation (86%) was seen in samples at 5 and 6 feet depth. This was also
the portion of the cores that was used in the microcosms because it had the highest level
of diesel contamination according to the environmental report from The California
Mushroom Farms and preliminary extractions done on the soil from different core
sections.
Table 3-6: Sorenson’s indices for Phase I microcosms over time.
Soil Only (Control) SMC + contaminated soil
SMC +
contaminated
soil + chitin
t=4 t=9 t=19 t=86 t=4 t=9 t=19 t=86 t=4 t=9
t=9 53
t=19 48 57
Soil Only (Control) t=86 19 43 38
t=4 25 44 36 18
t=9 19 29 25 13 36
t=19 29 43 25 13 36 63 SMC +
contaminated soil t=86 20 31 27 13 40 53 67
t=4 11 17 29 14 22 14 14 15
t=9 30 31 40 27 40 40 27 29 62 SMC +
contaminated soil +
chitin t=86 17 25 11 11 11 33 67 47 25 24
59
3.3 Substrate Comparison Microcosm and Respirometry Tests
3.3.1 Substrate Characterization
The basic properties of the substrates and soil contents of the Screening Test and
Substrate Comparison Test were determined (Table 3-9) and yielded subsequent C:N
ratios as listed in Tables 3-10 and 3-11. The California Mushroom Farm SMC was the
densest and had the highest water retention as compared to the other substrates. The C:N
ratio spanned a wide range in active Screening Test microcosms, from 12.8 to 47.3. It
was between 10 and 20 for the four different types of finished compost and much higher
Table 3-7: Sorenson’s indices for Phase II microcosms over time.
Actives Controls
t =
0
t=1
50 o
t=4
22 o
t=8
30 o
t=20
30 o
t=56
30 o t=0
t=8
30 o
t=20
30 o
t=56
30 o
Actives t=1 50 oC 29
t=4 22 oC 43 36
t=4 30 oC 27 37 55
t=8 30 oC 43 36 47
t=20 30 oC 11 25 31 38
t=56 30 oC 35 18 42 33 10
Controls t=0 12 27 17 17 40 11
t=8 30 oC 10 24 22 22 43 29 29
t=20 30 oC 0 0 26 17 21 12 12 30
t=56 30 oC 0 0 24 16 19 11 11 27 56
Table 3-8: Sorenson’s indices for different depths of diesel contamination in a soil core
obtained from the California Mushroom Farm.
4' 4.5' 5' 5.5' 6'
4.5' 40
5' 0 40
5.5' 0 0 29
6' 18 40 86 40
8' 67 40 25 40 36
60
for wood chips and peat moss due to their largely carbonaceous content and lack of
residual nutrients from the composting process. The range of C:N ratios for the three
conditions in the Substrate Comparison Test was much narrower, only between about 15
and 21. Particle size data is reported for substrates and soil after grinding with a coffee
grinder (Table 3-12). As previously stated, the fraction between 850 µm and 2 mm were
used in microcosms. The California Mushroom Farm SMC was so moist that it could
only be realistically sieved below 2 mm. Details about the composition of the three
substrates that were selected for the Respirometry Test are presented in Table 3-13.
Table 3-9: Chemical properties of substrates and uncontaminated soil used in the
Screening Test and Substrate Comparison microcosms.
Substrate Carbon
content (%)
Nitrogen
content (%)
Moisture
Content (%)
Wet Bulk
Density (g/mL)
CA Mushroom
Farm SMC
8.96 0.64 53 0.75
Penn State SMC 14.56 0.94 36 0.43
Nature’s Cover
SMC
15.25 1.44 41 0.54
UAJA Compost 32.78 1.51 21 0.55
Wood Chips 43.46 0.17 7 0.23
Peat Moss 43.34 0.55 9.5 0.15
Soil 5.79 0.34 2.5 1.0
Table 3-10: C:N ratios for Screening Test microcosms. Substrates and soil were mixed at
a 1:1 (volume) ratio.
Condition C:N Ratio
CA Mushroom Farm SMC + contaminated soil 15.6
Penn State SMC + contaminated soil 16.2
Nature’s Cover SMC + contaminated soil 12.8
UAJA Compost + contaminated soil 19.9
Wood Chips + contaminated soil 47.3
Peat Moss + contaminated soil 31.9
Contaminated soil only 17.0
Contaminated soil + NaN3 5.6
61
Table 3-11: C:N ratios for Substrate Comparison Test microcosms. Substrates and soil
were mixed at a 1:1 (dry mass) ratio.
Condition
CA Mushroom Farm SMC + contaminated soil 15.1
Penn State SMC + contaminated soil 15.9
UAJA Compost + contaminated soil 20.8
Table 3-12: Sieve analysis for ground substrates and soil. The fraction between 850 um
and 2.0 mm was used in Screening Test and Substrate Comparison Tests.*
Penn State SMC Wood Chips
2.5 % > 2 mm
850 µm < 40.9 % < 2 mm
56.7 % < 850 µm
40.5 % > 2 mm
850 µm < 35.4 % < 2 mm
24.2 % < 850 µm
Nature’s Cover SMC Peat Moss
18.8 % > 2 mm
850 µm < 64.7 % < 2 mm
16.5 % < 850 µm
10.6 % > 2 mm
850 µm < 20.0 % < 2 mm
69.4 % < 850 µm
UAJA Compost Soil
20.9 % > 2 mm
850 µm < 52.7 % < 2 mm
26.4 % < 850 µm
29.5 % > 2 mm
850 µm < 70.0 % < 2 mm
0.005 % < 850 µm * CA Mushroom Farm SMC was ground and sieved to < 2 mm.
62
3.3.2 Moisture Content
Visible daily monitoring of the moisture content in Screening Test microcosms
indicated that it had to be adjusted in the first six days of the experiment in substrate
amended bottles. Controls still contained some free-standing water so moisture in
controls was assumed to still be at a sufficient level for microbial activity. For the
Table 3-13: Composition of substrates used to treat diesel contaminated soil in Substrate
Comparison microcosm test.
Substrate Ingredients
CA
Mushroom
Farm SMC
Substrate Material:
Wheat based race track bedding straw, Dehydrated Chicken Manure,
Urea, Cottonseed Meal, Grape Pumice, Almond Hulls, Gypsum
Casing Material:
100 % Canadian Sphagnum Peat Moss, Sugar Beet Spent Lime
(Calcium Carbonate)
Additional:
Azadirachtin (Flies)
Chlorine (Bacterial Blotch)
Mertect (Fungal Pathogens)
Source: The California Mushroom Farm, Inc.
Penn State
SMC
Substrate Material:
Straw-bedded horse manure, Switchgrass straw, Poultry litter, Distiller’s
grain (dried), Gypsum
Casing Material:
Sphagnum peat moss buffered with crushed limestone and a casing
inoculum added (mycelium on a vermiculite carrier)
Source: Mushroom Testing Demonstration Facility, The Pennsylvania
State University
UAJA
Compost
High quality municipal biosolids and hardwood sawdust
Source: University Area Joint Authority, State College, PA
63
remaining 19 days, the microcosms retained a small amount of free-standing water and so
did not have to be re-adjusted. Measured final moisture contents ranged between 48 and
59% for substrate-amended conditions and between 36 and 37% for control microcosms
(Table 3-14). This elevated moisture loss in early days of experimentation is comparable
to that observed in Phase II temperature controlled microcosms.
Substrate Comparison Test microcosms maintained moisture contents between 35
and 55% throughout the course of treatment (Figure 3-17). Controls maintained similar
moisture contents as actives with the same compost amendment. Moisture contents in
respirometer bottles were adjusted identically to microcosm bottles on days 6 and 15.
Moisture contents measured when they were sacrificed on day 34 were comparable to
moisture contents in microcosm test bottles on day 30. Visual and physical monitoring of
moisture and measured high water contents in microcosms ensured that moisture was not
a limiting factor in active Substrate Comparison Test bottles.
Table 3-14: Moisture in Screening Test microcosms. Substrates and soil were mixed at a
1:1 (dry mass) ratio. All microcosms were continuously vented to the atmosphere except
where noted.
Substrate/Condition Volume of Water Added at
t = 0 and t = 6 days (mL)
Final Moisture Content
at t = 21 days (%)
CA Mushroom Farm SMC 3.57 47.3
Penn State SMC 5.01 52.9
Nature’s Cover SMC 4.85 49.9
UAJA Compost 5.70 56.6
Wood Chips 5.70 56.2
Peat Moss 6.35 61.5
Soil Only Control 3.96* 38.2
Abiotic Control 3.96* 37.1
Sealed Abiotic Control 3.96* 38.8
* Control microcosms were only moisture adjusted at t = 0.
64
3.3.3 Carbon Dioxide Production and Oxygen Utilization
Carbon dioxide concentrations were measured at the end of 21 days of the
Screening Test. Carbon dioxide concentrations were highest in duplicates containing
Penn State SMC, which were almost double the amount of CO2 in bottles containing
California Mushroom Farm SMC (Figure 3-8). Microcosms containing wood chips
showed the lowest CO2 production, producing only 25% of that produced in Penn State
bottles. UAJA compost bottles showed the second highest production and California
Mushroom Farm SMC, Nature’s Cover SMC, and Peat Moss bottles showed comparable
production all falling within 10 µg CO2 of each other. Control bottles also demonstrated
the presence of carbon dioxide and therefore indicate that microbial activity may not have
0
10
20
30
40
50
60
CMF SMC
Abiotic
CMF SMC
PSU SMC
Abiotic
PSU SMC
UAJA
Compost
Abiotic
UAJA
Compost
Mois
ture
Conte
nt (%
) t=0 t=15 t=30 t=62
Figure 3-17: Moisture content over the course of treatment in Substrate Comparison Test
microcosms (22 oC). These bottles were connected to a respirometer. Data points are
duplicate averages; error bars represent one standard deviation.
65
been fully suppressed by the biocide addition. From this information, it might be
expected that some hydrocarbon removal would be observed in controls.
Carbon dioxide concentrations were also measured in Substrate Comparison Test
microcosms prior to microcosm sacrificing (Figure 3-18). Carbon dioxide was lower in
biocide treated controls as compared to actives, but was still noteworthy: CO2 production
in the control bottles were 48, 55, and 61% that produced in the actives for California
Mushroom Farm SMC, Penn State SMC, and UAJA Compost bottles, respectively. The
production of carbon dioxide suggests that microbial activity was not totally eliminated
despite high (1 g) additions of NaN3. Although an additional 2 g of NaN3 were supplied
and mixed with the contents of the microcosms, subsequent sampling show that it was
not successful in totally suppressing microbial activity. The total mass of NaN3 (3 g)
added to was over 30% of the dry mass in microcosm bottles. However, the complex
162.22184.72
225.97
75.94
167.02
36.3820.79
38.89
302.42
0
50
100
150
200
250
300
350
CM
FSMC
PSUSM
C
NC's
SMC
UAJA
Woo
d Chi
ps
Peat M
oss
Con
trol
Abi
otic
Con
trol
Seale
d Abi
otic
Con
trol
Hea
dsp
ace
CO
2 (
um
ol)
Figure 3-18: Carbon dioxide production in headspace in Screening Test microcosm
bottles at the end of 21 day incubation at 22oC on a platform shaker. All microcosms were
vented continuously to the atmosphere, except where noted. Values are measured
duplicate averages of CO2 in 1 mL of headspace multiplied by the calculated headspace in
bottles under the various conditions; error bars represent one standard deviation.
66
structure of the composting material may have made it difficult for the biocide to
permeate all pores and fully inhibit microbial degradation.
UAJA active microcosms sustained the highest average CO2 production as
compared to other actives for the duration of treatment and it peaked in the middle of
treatment (t = 30 days). It was greatest at this time point; however, in California
Mushroom Farm and Penn State SMC actives, carbon dioxide production was lowest on
day 30. This trend is reflective of hydrocarbon removal and is discussed in the following
section. The California Mushroom Farm SMC microcosm bottles sustained the lowest
CO2 production as compared to other active microcosms (Figure 3-19).
Cumulative oxygen utilization was recorded in bottles connected to respirometer
cells for the first 30 days of the Substrate Comparison Test. The O2 consumption
measurement assumed that all the CO2 produced was absorbed by the KOH and gaseous
0
150
300
450
600
750
900
1050
1200
1350
CM
F SM
C
Abi
otic
CM
F
PSU S
MC
Abi
otic
PSU
SM
C
UAJA
Com
post
Abi
otic
UAJA
Com
post
Hea
dsp
ace
CO
2 (
um
ol)
T=15 T=30 t=62
Figure 3-19: Carbon dioxide production in 1 mL of headspace in Substrate Comparison
Test microcosm bottles prior to hydrocarbon extraction at 3 time points. These bottles
were connected to a respirometer. Values are measured duplicate averages of CO2 in 1
mL of headspace multiplied by the calculated headspace in bottles under the various
conditions; error bars represent one standard deviation.
67
nitrogen species could be neglected. Thus, the O2 consumption was assumed to be solely
due to microbial consumption. Due to erratic and implausible jumps in O2 consumption
(Appendix E) caused by a problem with the respirometer system, data was adjusted to
exclude all measurements that increased more than 1 mg than the previous 10 minute
saved interval. Justification for this correction came from the observation of similar
jumps when water was added to the microcosms and contents were stirred. This shows
that such jumps in oxygen consumption were likely caused by abiotic factors.
Additionally, maximum oxygen utilization rates in Phases I and II did not exceed 1
mg/10 min. Results of the adjustments are presented in Figure 3-20. This made it possible
to visualize some trends and differences in utilization between the different conditions.
0
10
20
30
40
50
60
70
0 5 10 15 20 25 30
Time Elapsed (d)
Cu
mu
lativ
e O
xy
gen
Up
tak
e (m
g))
)
CMF SMC Active CMF SMC Abiotic
PSU SMC Active PSU SMC Abiotic
UAJA Compost Active UAJA Compost Abiotic
Figure 3-20: Cumulative oxygen usage for 30 days of treatment in bottles connected to respirometer
system after corrections for unlikely jumps in uptake. Data was collected every 10 minutes.
68
All three substrate conditions showed an initial elevated rate of O2 uptake
followed by stabilization, similar to previously demonstrated Phase II carbon dioxide
production, oxygen utilization, and hydrocarbon removal profiles. The active UAJA
compost bottle sustained a greater rate of O2 utilization for the duration of the experiment,
followed by the Active Penn State SMC bottle. The Active California Mushroom Farm
SMC lagged behind the other two active conditions and took a longer period of time to
reach maximum O2 uptake. Oxygen utilization was low or nonexistent throughout the
course of treatment for the various controls.
3.3.4 Total Petroleum Hydrocarbon Concentrations
All conditions, including controls, exhibited TPH diesel removal in the Screening
Test microcosms. Penn State SMC, Nature’s Cover SMC, and UAJA Compost amended
microcosms demonstrated the highest removal, all averaging the same value of 27%
removal in 21 days of treatment (Figure 3-21). These were also the three conditions that
demonstrated the highest carbon dioxide production. The California Mushroom Farm
SMC only showed the second to least removal and it is unknown whether its performance
was inhibited by age and storage since Phase I and II experiments. All other substrates
were collected fresh for this test.
Although the environmental set-up was thought to give insight into biotic as well
as abiotic removal factors through the use of various types of controls, TPH removal in
controls reached up to 28%. Enhanced volatilization of contaminants in control
microcosms as compared to compost amended conditions may have occurred without the
complex organic material present to hold the contaminants in the composting matrix.
This is also supported by the fact that sodium azide amended controls demonstrated
relatively high TPH removal, but lower levels of carbon dioxide production, suggesting
that the removal was probably not fully biological.
For use in the Substrate Comparison Test, fresh SMC was delivered from The
California Mushroom Farm. Active microcosms containing UAJA compost still
69
demonstrated the greatest TPH removal, at a total reduction of 986 ppm (mg TPH/kg
mixture) over 62 days of treatment, accounting for 59% of the initial contaminant
concentration (Table 3-15). Diesel TPH removal was much less in California Mushroom
Farm and Penn State SMC bottles, accounting for only 34 and 43% removal,
respectively. Variability in initial diesel concentrations was caused by different
contaminant dilutions with the different composts; therefore, overall contaminant
decrease is a better measure of compost performance rather than the final concentration
achieved.
13.5
20.1
27.226.7
17.3
27.0
0
500
1000
1500
2000
2500
3000
3500
4000
CM
FSMC
PSUSM
C
NC's
SMC
UAJA
Com
post
Woo
d Chi
ps
Peat M
oss
TP
H (
mg
/kg
))))
0
10
20
30
40
50
60
70
80
90
100
Over
all R
emoval
(%
))
t=0 t=21 % Removal
Figure 3-21: Initial and final TPH concentrations and overall percent decrease in compost
amended microcosms in the Screening Test over 21 days of treatment.
70
The hydrocarbon concentration results compare well to respirometry data since
Penn State SMC and UAJA Compost amended conditions demonstrated the greatest TPH
removal, CO2 production, and O2 uptake. However, the removal was slightly greater for
the Penn State SMC condition. Between days 15 and 30, a steeper downward slope is
observed in hydrocarbon removal (Figure 3-22), which also compares well to the
elevated CO2 production level measured on day 30 (Figure 3-19). In contrast, the
California Mushroom Farm SMC and Penn State SMC display an almost level slope
between these sampling days and a greater subsequent slope, reflective of higher carbon
dioxide measurements on day 62.
It is interesting to note the differences in TPH removal trends between the three
substrates over the course of treatment. The CMF active microcosms displayed almost no
removal between the first two sampling points and then showed a constant and elevated
decrease in hydrocarbon concentrations. The CMF active microcosm also displayed a
great lag time in O2 utilization as compared to the other two substrates. The PSU SMC,
however, displayed a sharp initial decrease in TPH, similar to that of the UAJA compost,
a stable intermediate period, and a subsequent additional decrease. PSU SMC and UAJA
compost also displayed similar trends in O2 uptake (Figure 3-20). The UAJA Compost
active microcosms displayed a steady and almost constant rate of TPH removal, and a
decreased removal rate between sampling on days 30 and 62. Unlike Phase I and II
microcosms, decreases in hydrocarbon concentrations occurred consistently throughout
this 62 day experiment. Concentrations did not plateau after about 20 days of treatment as
in Phase I and II, but final TPH concentrations were still high, and therefore a great deal
of contaminant could have still been available for microbial degradation when the
experiment was stopped.
The composition of the substrates had a great affect on the performance. When
removal under each of the substrate conditions was compared the fractions of carbon and
nitrogen in the composts, very strong correlations were found (Figure 3-23). A slightly
less linear but still direct correlation is also evident between removal and C:N ratios in
the microcosms.
71
Table 3-15: Comparison of diesel TPH removal, oxygen uptake, and carbon dioxide production
in active Respirometry Test microcosms over 62 days of treatment. All data was collected from
sacrifical microcosms, except O2, which was collected from serum bottles connected to the
respirometer system. The units ppm refer to mg TPH/kg mixture.
Initial
TPH
(ppm)
Final
TPH
(ppm)
Total TPH
Decrease
(ppm)
Total
TPH
Decrease
(%)
Cumulative
O2 Uptake
(mg) *
Final Total
CO2 in Reactor
(mg)**
California
Mushroom
Farm SMC
1415 934 481 34 43.48 25.54
Penn State
SMC
1596 906 690 43 47.67 29.12
UAJA
Compost
1660 974 686 41 51.26 36.06
* Refers to 30 d of treatment
** CO2 measured in 1 mL of headspace prior to final sampling on day 62 was multiplied by headspace volume (140
mL in California SMC bottles, 133 mL in PSU SMC bottles, and 140 mL in UAJA Compost bottles mL)
750
900
1050
1200
1350
1500
1650
1800
-5 0 5 10 15 20 25 30 35 40 45 50 55 60 65
Time Elapsed (d)
TP
H (
mg
/kg
)
Active CMF SMC
Active PSU SMC
Active UAJA Compost
Figure 3-22: Diesel TPH removal trends in active microcosms of the Substrate Screening Test.
Substrates and diesel contaminated soil were mixed at a 1:1 ratio by dry mass. Data points are
duplicate averages; error bars represent one standard deviation.
72
Chapter 4
Discussion
4.1 The Effect of Substrate and Nutrient Additions on Remediation of Diesel
Contaminated Soil
4.1.1. Evaluation of Various Substrates
The treatability studies performed in this work validate the use of spent
mushroom compost from the California Mushroom Farm, Inc. to remediate diesel-
contaminated soil at the site. In sacrificial microcosms containing contaminated soil,
SMC, and chitin, a maximum TPH reduction of 89% (1610 to 181 ppm) was obtained. It
is very likely that hydrocarbon removal rates in these tests would have been significantly
higher if this study were performed on a freshly contaminated sample. Nonetheless, these
tests showed that the use of SMC in a full-scale composting treatment would create a
beneficial use of the farm’s largely produced waste product and may resolve a long-
standing environmental problem at the farm. However, other carbon rich substrates,
particularly compost from the University Area Joint Authority Wastewater Treatment
Plant in State College and SMC from the Mushroom Testing Demonstration Facility at
Penn State, were shown to provide even greater removal of diesel contamination when
compared to SMC from The California Mushroom Farm. From the results of this
research, wood chips and peat moss would not be recommended as substrates to support
bioremediation of diesel-contaminated soil without the supplementation of some
additional nutrient sources. Through this research, composting of diesel-contaminated
soil has been shown to promote sustainable reuse of a number of readily available,
inexpensive, and locally produced waste products.
The ratio of substrate to soil used in composting systems for treating
contaminated soil may affect the resulting removal. The masses of soil and SMC used in
Phase II microcosms (4.44 g soil, 2.22 g SMC, wet weights) were designed to give an
73
equal volume:volume ratio based on wet bulk densities and constituted 5 g total (dry
weight) per microcosm. This soil:substrate ratio of 1:0.5 was intentionally designed to
correspond with ratios recommended in the literature. When compared with 1:0.1, 1:0.3,
and 1:1 soil:organic matter on a wet weight basis, compost reactors containing 1:0.5 ratio
(as in Phase II) have previously been shown to provide the greatest degradation rates of
n-alkanes and TPH (Namkoong et al. 2002). In the Substrate Comparison Test, the wet
weight ratios of soil to California Mushroom Farm SMC, PSU SMC, and UAJA Compost
were 1 to 1.7, 1.2, and 0.95, respectively. Although the purpose of this test was to
compare the performance of different substrates based on the dry mass of organic
material that was added, the ratio of soil to compost might play an important role as well
and so can be investigated for the chosen compost amendment. This indicates that the
performance results presented in this research may not be absolute and the outcome may
be affected if the parameters are altered. Thus, results may be affected as much by
various elements of composting conditions as by the composition of the substrate itself.
4.1.2. Influence of Amendments on C:N Ratio
The C:N ratio is a function of the carbon material added and any nutrient
additions, as well as soil composition and hydrocarbon concentration, to a minor extent.
A wide range of C:N ratios have been reported as effective in stimulating microbial
degradation during composting. Van Gestel et al. (2006) and Zytner et al. (2006)
conducted composting studies utilizing C:N ratios of 19:1 and 20:1, respectively.
Similarly, Beaudin et al. (1999) cited a study where maximum organic degradation rates
occurred at a C:N ratio of 22:1 and found that degradation was hindered as the C:N ratio
approached 30:1. Other sources show that a reduction of the C:N ratio to less than 20:1 is
useful (Hupe et al., 2001). Since optimal C:N ratios depend on the hydrocarbon
concentration, the nutrient assimilation efficiency of the microorganisms, the bioactivity
and distribution of microbial species affected by different nutrient conditions, and the
class of hydrocarbons being degraded (Walecka-Hutchison and Walworth, 2006), it is
difficult to assume a general C:N ratio.
74
Throughout the course of this research, C:N ratios ranged between 9:1 and 47:1 in
different substrate amended reactor bottles. The highest ratios, which fell in the range
between 30:1 and 50:1, were found in wood chip and peat moss amended microcosm
bottles. Judging from the poor hydrocarbon removal observed in these microcosms, this
C:N ratio is too high for such a system. In Phase I microcosms evaluating the use of
California Mushroom Farm SMC and chitin, the C:N ratio was 14:1 in SMC amended
microcosms and fell to 9:1 in microcosms amended with SMC and chitin due to chitin’s
high nitrogen content. If this is below the range for optimal microbial activity, it could
help explain the limited performance in microcosms containing chitin. The C:N ratio in
Phase II temperature evaluation microcosms was only 9.5:1, due to the presence of chitin.
From the removal percentages of the Substrate Comparison Test, where C:N ratios in
California Mushroom Farm SMC, Penn State SMC, and UAJA Compost microcosms
were 15:1, 16:1, and 21:1, respectively, it may be deduced that the best C:N ratio for this
type of composting system may be higher, or between 16:1 and 21:1.
High contaminant removal (43% over 62 days) in Penn State SMC microcosms
could either be a function of the compost composition or the C:N ratio. UAJA compost
with a very different composition showed comparable removal (41% over 62 days).
Additional experiments could be designed to test whether simply adding more carbon
using any of the substrates would suffice to enhance removal. The relationship between
carbon content and % removal was not linear. UAJA compost had double the carbon
content of Penn State SMC, but did not demonstrate much higher removal. However, due
to this high carbon content, there is a greater risk that removal is a result of sorption
rather than biodegradation. Removal is not enhanced above Penn State SMC’s carbon
content of ~15%. The benefit of UAJA compost in this respect, however, is that high
removal is promoted by a smaller wet mass of sample. The 5 dry grams of each substrate
that were used in the different microcosms actually equated to only about 6 grams of
UAJA Compost, 8 grams of Penn State SMC, and 11 grams of California Mushroom
Farm SMC on a wet weight basis. Hence, although additional substrate could be
supplemented to a hydrocarbon composting system and possibly then achieve comparable
results, the use of UAJA compost would avoid the expense of transporting and storing
75
heavier and more voluminous load. Since treatment at The California Mushroom Farm
will be executed with its own SMC, a slightly higher substrate:soil ratio (and therefore a
higher C:N ratio) than that used in Phase I and II is advisable.
4.1.3. The Effect of Nutrient Addition through Chitin
Through Phase I and II microcosm tests, it was determined that a fractional chitin
amendment did not enhance bioremediation of diesel-contaminated soil. The nitrogen in
SMC and other composts may actually be sufficient to support microbial activity.
Another explanation for chitin’s apparent negative effect could be the osmotic stress
caused by partitioning of surface salts into the pore water of the compost. This has been
observed in other systems amended with nitrogen-rich fertilizer salts (Walecka-Hutchison
and Walworth, 2006). In the case of chitin, the release of sea salt from the surface of the
crab shells may have created localized high concentrations of sodium that inhibited
microbial activity. Pretreating the shell material with a simple tap water rinse to remove
surface-associated salts may be necessary prior to composting to realize the benefits of
this nutrient amendment. Future work is needed, however, to confirm this speculation.
The use of chitin in composting systems cannot be fully discredited as it may provide
nitrogen in beneficial form from a sustainable waste product to compost systems that are
nitrogen deficient, such as those observed in this study utilizing wood chips and peat
moss.
4.1.4. Carbon Dioxide Production under Various Treatments
CO2 production was observed and compared for treatments using various
composting amendments. Under all substrate-amended conditions, enhanced carbon
dioxide production indicated increased microbial activity, which in most cases correlated
well to hydrocarbon removal rates. Carbon dioxide production rates were highest at the
beginning of treatment and then plateaued, as did hydrocarbon removal. However, CO2
76
production is not always expected to be directly reflective of hydrocarbon degradation
rates in aerobic composting systems, since there are a variety of other processes which
can produce CO2. The degradation of other organic matter (for example, compost) and
anaerobic degradation (Salimen et al., 2004) also contribute to CO2 production. Indeed, it
has been noted previously that carbon dioxide production and oxygen utilization rates do
not directly reflect hydrocarbon degradation rates (Baker et al., 2000, Van de Steene and
Verplancke, 2007). This was also observed in chitin containing Phase I microcosms in
this study, which actually produced high carbon dioxide levels and yet exhibited lower
TPH removal. Also, UAJA compost containing microcosms demonstrated the highest
carbon dioxide production but not the highest removal in the Repirometry Test. However,
in the Screening Test, the microcosms containing wood chips demonstrated the lowest
CO2 production as compared to the other active microcosms, but actually promoted
higher removal than the California Mushroom Farm SMC containing microcosms or the
Peat Moss microcosms. In this case, it is not clear whether this elevated removal was
promoted by sorption to wood chips’ high carbon content. Nonetheless, gaseous CO2 and
O2 measurements are good indicators of microbial activity and can be used to help ensure
that the aerobic bacteria have sufficient oxygen availability in closed systems. It is
imperative that carbon dioxide evolved in the system be replaced with oxygen for
microbial consumption.
4.2 Rates and Descriptions of Removal
Phase I and II exhibited elevated hydrocarbon removals followed by a stagnant
period, beyond which little change occurred even during extended treatment. This is not
unusual for diesel bioremediation systems in which microbial breakdown of hydrocarbon
contaminants usually follows a first-order degradation rate during the first few days of
composting followed by slower rate (Huesemann et al., 2004; Namkoong et al, 2002;
Nocentini et al, 2000; Van Gestel et el, 2003; Zytner et al., 2006). At the beginning of
treatment the less complex and bioavailable compounds are removed, and then the rate
decreases to one that is about an order of magnitude lower than earlier time points. The
77
remaining hydrocarbon concentration typically stabilizes on a “residual” value (Nocentini
et al., 2000). This recalcitrance is caused by cometabolic limitations, where additional
contaminants cannot be degraded if not in the presence of others that have already been
depleted, or mass transfer limitations (Zytner et al., 2006). It is also possible that nutrients
added at the beginning of the experiment may become exhausted (Riffaldi et al. 2006).
Nutrient replenishment at later points during treatment may be helpful in counteracting
this observation.
In aged contamination, such as that treated in Phases I and II, the increased soil-
contaminant contact time allows a larger fraction of diesel to diffuse into non-available
sites (De Jonge et al. 1997, Cavalca et al., 2008). As diesel concentrations decrease, the
rate of degradation also decreases because of the low biodegradability of the remaining
contaminants and their binding to organic and inorganic soil fractions (Cavalca et al.,
2008). At higher concentrations, bioavailability is regulated by solubilization from a non-
aqueous phase liquid (NAPL), which exists as a film layer on soil particles or as
dispersed droplets, while at lower concentrations, it is regulated by desorption and
diffusion, because the hydrophobic molecules are adsorbed to the soil at this point. They
must be desorbed prior to microbial degradation (De Jonge et al., 1997).
Volatilization and leaching are two other abiotic loss mechanisms in field
bioremediation applications (Zytner et al., 2001), but in this research, leaching was not an
applicable removal mechanism and volatilization of diesel compounds was assumed to be
negligible as supported by GC-FID analysis of microcosm headspace, which
demonstrated few small peaks eluting prior to diesel range compounds.
4.3 Additional Considerations for Full-Scale Implementation of Composting System
4.3.1. Moisture Profiles and Control
From this research, the greatest moisture loss seems to occur at the beginning of
the composting process. With regular monitoring and adjustment, moisture loss should be
78
an easily avoidable limitation during full-scale treatment. Regular moisture monitoring of
Phase II microcosms showed an initial rapid decrease followed by stabilization between
20 and 30 %. Similarly, additional moisture was necessary for the Screening Test and
Respirometry Tests at the beginning of each experiment. This was necessary to prevent
premature drying and incomplete mineralization of the system (Richard et al., 2002).
After the first two weeks of treatment, moisture levels remained consistent and did not
have to be adjusted again. The mechanism for moisture loss is suspected to be
evaporation, especially during periods of frequent aeration at the beginning of Phase I
and II treatment. Moisture loss may have been greater at the beginning of treatment due
to higher temperature during the thermophilic phase that is typically observed at the
beginning of composting treatments (Hsu and Lo, 1999; Tiquia et al., 1997). As
compared to soil only controls, the addition of organic material greatly improves the
water retention capacity of the soil, helping to facilitate movement of contaminants and
microbial uptake for longer periods of time.
4.3.2. The Importance of Oxygen
As evidenced by numerous studies (Nocentini et al., 2000, Van de Steene and
Verplancke, 2007, Van Gestel et al., 2003), oxygen utilization rates are highest at the
onset of composting and then taper off quite drastically. Van Gestel et al. (2006) reported
that oxygen levels in compost bins decreased dramatically to 8% on day 8 but reached the
ambient concentration of 21% by day 23 by reaching equilibrium between oxygen
utilization and ambient oxygen conditions in an open system. Similarly, carbon dioxide
and oxygen levels in this study had to be closely monitored at the beginning of treatment
in all tests. In Phase II, headspace oxygen levels were depleted in as little as two days.
Over time, however, headspace flushing of the microcosm bottles became a less frequent
requirement, as the molar ratio between oxygen and carbon dioxide remained high
enough to support microbial degradation of organic contaminants.
Degradation may have stalled mid-way through Phase I due to lack of available
oxygen. It is likely that degradation rates would actually have been greater than those
79
presented for Phase I if proper aeration had been consistently maintained. The
enhancement in respiration at later times was consistent with the observed decrease in
hydrocarbon concentrations, indicating that respiration was affiliated with continued
biodegradation. The Phase II 22 oC Actives reached a lower hydrocarbon concentration in
less time than did Phase I microcosms although they were kept under the same
conditions. Oxygen deficiency was likely a limiting factor early in the Phase I
experiment, and if this had been avoided, Phase I removal rates may have been
comparable to Phase II rates. It is imperative that high oxygen levels be maintained at the
onset of aerobic composting treatment to ensure maximum TPH degradation.
4.3.3 The Effects of Temperature
In the Phase II microcosms, there was an apparent increase in TPH concentration
in active microcosms at early times depending on their incubation temperature. The
highest increase was observed at 50 oC on day 1, followed by a moderate increase at 30
oC and only a small increase at 22
oC on day 4 (Figure 3-9). Since the Phase II
concentration increases occurred first at higher and then at lower temperatures to a lesser
extent, it may be attributed to enhanced mobilization and desorption of contaminants at
elevated temperatures (Andreoni et al., 2004). However, at these time points and
temperatures, GC detection of metabolites may also be responsible for the apparent
increase (Zytner et al., 2006).
The decrease in TPH concentrations in the Phase II Controls may be due to
volatilization at high temperatures. Although GC-FID analysis of headspace extracted
from higher temperature microcosms revealed very low concentrations of only lower
molecular weight compounds in the headspace, any evaporated hydrocarbons likely
escaped from the microcosm bottle while the headspace was being flushed with air.
Despite minor variations in TPH degradation observed at different temperatures
during the course of the Phase II experiment, the final results were not statistically
different. Therefore, the conclusion of this research is that temperature does not need to
be closely monitored during the course of full-scale composting treatment of
80
hydrocarbons at the site. The slight advantage of the 30 oC microcosms could likely be
easily maintained at the field scale due to temperature increases that occur naturally
during composting. The results of this study compare to studies where a range of
temperatures, such as 35 and 50 oC (Hogan et al., 1989) resulted in similar removals of
aliphatic and PAHs. Since temperature was determined to be insignificant during the
Phase II tests, all subsequent microcosms were maintained at room temperature (22 oC).
The ability to conduct hydrocarbon composting at ambient temperatures provides an
additional cost benefit for full-scale implementation.
4.3.4 Addressing Potential Residual Concentration Concerns
Phase I and II microcosms were held for an extended period of time to determine
whether the TPH concentration had reached a recalcitrant endpoint beyond which
remediation could not occur. The phenomenon known as the “residual concentration
problem” describes the characteristic of diesel in which a residual fraction remains
undegraded even when optimal conditions have been provided. After a period of marked
degradation, the hydrocarbon concentration seems to stabilize on a value called the
residual concentration, which is dependant on the soil characteristics and age of
contamination (Nocentini et al, 2000). After lighter and less complex molecules have
been removed, the PAH components of the fuel remain strongly absorbed to the soil
particles (Arce-Ortega et al., 2004). In this study, a sharply decreased rate of hydrocarbon
removal was seen after day 50 in Phase I and after day 20 in Phase II. However, in
Substrate Comparison Test microcosms, where the soil had been freshly spiked prior to
treatment, hydrocarbon concentrations seemed to decline up to the final sampling on day
62. It was not yet apparent whether a stable concentration had been reached.
It is unclear whether a residual concentration will occur in contaminated soil at
The California Mushroom Farm based on microcosm sampling in this study. If this is the
case and bioavailability is mostly controlled by desorption and diffusion processes, tillage
will no longer be effective because microstructures responsible for diffusion limitations
are not affected by tillage (De Jonge et al., 1997). If a residual concentration has been
81
reached beyond which degradation can no longer occur naturally, efforts should be
directed towards increasing bioavailability of remaining contaminants. Detergents may be
useful for this purpose, but it is important to note that the degradation of detergents
requires oxygen, leaving less available for contaminant breakdown (Riser-Roberts, 1998).
Although the residual concentration in aged soil has typically been attributed to
lack of bioavailability (Huesemann, 2004), it has also been reported that the main
constraint to degradation is the absence of catabolic features such as the inability to
degrade complex hydrophobic molecules like PAHs (Cavalca et al., 2008). Thus,
enhanced stimulation of the microbial community later in treatment could be enough to
attain the California target concentration of 100 ppm. Although California’s goal had not
been met, the minimum TPH concentration achieved (181 ppm) meets the regulations of
several other states such as Colorado (500 ppm), Delaware (500 ppm), Missouri (50-1000
ppm), Florida (340 ppm), Tennessee (500-1000 ppm), and Rhode Island (500 or 1000
ppm) (Kostecki et al., 2001).
4.3.5 Addition of Organic Material
In assessing the amount of organic material to add to the system and the goal C:N
ratio to be achieved, it is important take into account elevated sorption capacities to this
porous matrix. Increasing the amount of carbon input to some of the treatments may
improve the performance, but the increase in sorption potential could actually limit the
amount of contaminant that can be degraded. The sorption of hydrophobic organic
pollutants in particular tends to be strong and closely related to the fraction of organic
carbon in the system (LaGrega et al., 2001). These compounds would preferentially
partition into the porous compost matrix than into the aqueous phase. Hence, lower
compost additions are favored when possible.
82
4.4 DGGE as a Tool to Investigate Microbial Communities
4.4.1. Qualitative and Statistical Analyses
DGGE gels developed to study the microbial community dynamics of diesel
treatment over time and under various substrate and temperature conditions reflected the
complex patterns of community variability resulting from exposure to a complex array of
environmental factors (Powell et al., 2003). Though it isn’t clear whether DGGE bands
represent the most active species, the most abundant species, the most extractable
species, or a combination of these groups, DGGE remains an effective technique for
detecting differences in community diversity (Muyer et al., 2002). Generally, the picture
of bands in the various samples provides a qualitative analysis of community variations
and commonalities to help assess environmental conditions’ effect on microbial ecology
in the system. As expected, in these analyses on sample relationships based on banding
patterns and commonalities, more correlations were found between substrate amended
condition and between non-substrate amended conditions.
In addition to sequencing of bands, a qualitative DGGE analysis should provide
some information on how microbial communities change in response to environmental
factors. Microbial diversity in soil typically decreases as a result of contamination
(Muller et al., 2002), since hydrocarbon contamination selects for a less diverse but
catabolically versatile bacterial community (Maila et al., 2006). In this study, gels run
with samples from contaminated soil core from different depths below ground
demonstrated very little diversity, while samples from established microcosms exhibited
many more bands. The higher diversity in soil only controls as compared to soil core was
probably due to microbial stimulation from higher oxygen and moisture levels in the
microcosms. Increased diversity in substrate-amended conditions was likely due to the
additional input carbon and nutrients as well as additional microbial communities
naturally present in compost and crab shells.
83
4.4.2. Difficulties in Sequence Analysis of Complex Soil Communities
Despite the value of DGGE as a tool to separate and visualize various members of
an environmental community, its ability to represent all the different sequences is
sometimes compromised. This difficulty arises from various DNA sequences having the
same denaturing point and therefore co-migrating, and also from some organisms
producing multiple bands (Muyer et al., 2002, Powell et al., 2003). Unrelated sequences
may co-migrate to the same position especially when analyzing complex communities
(Fromin et al., 2002). This helps to explain in this study why clear sequences were not
always obtained from the band DNA sent for sequencing, and why in some cases
sequences were completely indiscernible or returned no BLAST results. Another reason
is that microbial diversity in various environments is greater than the bacteria that have
been isolated (Wanatabe 1998). If unclear sequences actually did represent bacterial
species, they may not be present in the BLAST database.
For the sequences that were deciphered, it was difficult to make conclusions about
the exact communities responsible for hydrocarbon degradation because they either
described genuses rather than species, had a short length or ambiguity, or they described
species that were not well documented hydrocarbon degraders in contaminated soil
environments. On the other hand, only the main populations, or those that represent 0.1-
1% of the target organisms, are displayed in DGGE profiles, limiting analysis of the full
diversity of the community (Fromin et al., 2002). Hence, this method is incapable of
detecting minor community components that may be essential in the degradation of
specific hydrocarbon classes (MacNaughton at al., 1999). The hydrocarbon-degrading
community in the soil may have been dwarfed by the large community added by chitin
and SMC. DGGE bands representing hydrocarbon degraders may have been too faint or
crowded to be extracted. In addition, non-documented hydrocarbon degraders may still
have played some role in the soil, even potentially contributing to biodegradation.
Bacterial cultures in contaminated environments also consist of species that do not
directly degrade the contaminant but participate in degradation processes or utilize
metabolites produced (Cavalca et al., 2008). A number of species may possess the same
84
function and species possessing the same function may also respond to environmental
disturbances differently (Muller et al., 2002). It is likely that a single species is not
responsible for all degradation in the system since the natural microbial diversity in soil is
enormous and amplified by the addition of composts. In the case of SMC, which alone
has been found to mineralize benzene (Semple et al., 1998), the degradative potential
may come from various enzymes and metabolic capabilities remaining from the
composting and mushroom growing process. Hence, the soil environment at the
California Mushroom Farm that has been subjected to many years of contamination may
have selected for a community with hydrocarbon degrading capabilities but the specific
members possessing these capabilities cannot be easily isolated by DGGE alone when
targeting a universal gene such as the 16S rRNA gene.
4.4.3. DGGE Optimization
DGGE banding patterns may be affected by many factors. Maximum resolution of
PCR product banding and picture clarity may be achieved by experimenting with
different denaturant gradients, using pre-mixed acrylamide solutions rather than
preparing them in the lab, and limiting gel fixation time (Simpson et al., 1999). Optimal
separation of PCR fragments could also be achieved by varying the running voltage and
gradient (Boon et al., 2001). Additionally, since diverse communities such as those found
in soil produce so many bands for each PCR product, a comparison of duplicate or
triplicate lanes for various samples could more accurately highlight differences and
ensure a more conclusive qualitative analysis. The Sorensen index could then be used to
determine the reproducibility of the banding pattern and the validity of gel casting and
imaging methods. The gel picture is not absolute. Identical PCR products run on different
gels may vary in similarity to each other (Powell et al., 2003). This phenomenon was not
investigated in Phase I and II gels and is probably irrelevant since lanes in the gel were
only compared relative to samples in the same gel rather than lanes in another gel, but it
should be considered for more intensive DGGE investigation. In addition, for more
85
exhaustive molecular analysis, various details about the DGGE method used should be
modified and optimized to ensure that clear, reproducible gels are created.
Modifications can also be made to the size and specificity of PCR products. The
universal 16S primer used in this study amplified bacterial DNA from all community
members in the treatment system, including non-hydrocarbon degraders. The purpose of
this approach was to any identify community changes that may be key to optimizing
treatment. DGGE’s sensitivity can be refined by PCR primers that target precise groups,
such as hydrocarbon degraders or hydrocarbon degrading functional groups. In a system
as diverse as that observed in this research, multiple organisms possessing similar
capabilities may have been responsible for degradation and so functional gene targeting
may have provided more information regarding changes in soil composition over time
and under various treatments. Wanatabe et al. (1998) extracted DNA and amplified
partial fragments of the 16S rRNA gene and the largest subunit of multicomponent
functional gene “phenol hydroxylase” by PCR from phenol-degrading activated sludge.
Targeting functional genes could also provide more insight into the mechanisms and
physiology responsible for hydrocarbon degradation at the site. Nested PCR is also useful
to facilitate analysis of the 16S rRNA gene fragments of different bacterial subgroups by
DGGE. A smaller section of the 16S gene can be targeted after a larger portion is
amplified. This increases sensitivity and makes it possible to visualize species present in
smaller numbers (Boon et al., 2001).
Another option for analyzing DGGE profiles and relating them to the abundance
of species is through cloning and sequencing of PCR products that are run simultaneously
on DGGE gels (van Elsas et al., 2000). In this way, prominent bands may be correlated to
prominent isolated species in samples. Statistical correlations of lanes and statistical
cloning analysis could be performed in parallel. Additionally, cloning of DNA eluted
from bands can help separate multiple sequences that may have migrated to the same
location (Feris et al, 2003; Wang et al., 2008).
Chapter 5
Conclusions, Engineering Significance, and Future Work
5.1 Conclusions
The conclusions that can be made from the research investigating the use of SMC to
bioremediate diesel contaminated soil are:
1. Spent mushroom compost is a viable substrate for the treatment of diesel
contaminated soil.
• Under the best performing condition in the study, microcosms containing
contaminated soil, SMC from The California Mushroom Farm, Inc., and a
fractional amendment of crab-shell chitin were able to decrease the total diesel
concentration by a total of 89% (1489 mg TPH/kg of soil) after 160 days of
treatment. This is within 5% of Ventura County’s Environmental Health Division
target goal of 100 ppm (mg/kg).
2. The inclusion of a fractional amount of crab-shell chitin as a nitrogen source did
not ultimately enhance hydrocarbon removal.
• Crab-shell chitin may still provide other benefits such as pH buffering and metal
immobilization. Its use in such systems should be evaluated depending on specific
nutrient demand of the soil and compost mixture.
3. Temperature does not markedly affect remediation efficiency.
• The ambient operating temperature at The California Mushroom Farm should
therefore be adequate for full-scale treatment unless it takes place during seasons
when the average temperature within the compost pile drops below 22 oC.
• Linked with comparable final TPH concentrations under the three temperature
conditions tested, no apparent preferential community enrichment was found over
time in microcosms at 30 oC, or in microcosms at different temperatures (22
oC
and 50 oC) at early times.
87
4. A residual diesel concentration may have been reached in The California
Mushroom Farm soil beyond which biodegradation can no longer occur.
• However, sufficient aeration, tilling, moisture, and the addition of SMC should
bring the contaminant concentration down to a level that is close to the regulatory
limit.
5. The final concentration reached in this treatability study (181 mg TPH/kg of
soil) exceeded Ventura County’s goal of 100 ppm, but it fell within the
acceptable range of many states in the U.S.A.
• These states include Colorado (500 ppm), Delaware (500 ppm), Missouri (50-
1000 ppm), Florida (340 ppm), Tennessee (500-1000 ppm), and Rhode Island
(500 ppm).
6. Penn State SMC and UAJA Compost, two readily available waste products,
performed better per dry mass than The California Mushroom Farm SMC in
composting diesel contaminated soil.
• Composting of diesel contaminated soils is a versatile strategy that has high
potential to provide a low cost, low energy demand solution for a multitude of
petroleum contaminated sites across the country.
7. Sodium azide is not a satisfactory bioremediation suppressant in compost
amended controls when used in moderate quantities (< 0.3 g/g on a dry weight
basis, or < 0.15 g/g organic material and water).
5.2 Engineering Significance
The findings of this study demonstrate that spent mushroom compost can be used
as a bulking agent and carbon source to support hydrocarbon remediation processes.
SMC has only been shown in one paper to stimulate bioremediation of petroleum
contaminated soil, but only after landfarming and not as an initial treatment option. Since
SMC is an abundantly produced byproduct which continues to be produced in larger
quantities with increased mushroom cultivation, its use as a bioremediation substrate
88
provides a benefit both for the mushroom industry and for environments that are greatly
compromised by petroleum leaks and spills.
The abundance and low cost of SMC makes it an attractive substrate for
remediating contamination in large-scale sites as well as in small, privately owned
locations. Especially in areas of high mushroom production, such as Pennsylvania, SMC
does not have to be transported long distances and is readily available. The use of SMC
overcomes the cost barrier presented to private land owners who are responsible for the
clean-up of their own properties. It is also composed of enough residual nutrients and
enzymes to not require additional nutrient supplementation. Finally, the robustness of the
indigenous microbial community in soil and compost allows the composting system to
perform well under various temperature conditions and therefore avoid this additional
operational energy input.
In addition to SMC from The California Mushroom Farm, various compost
amendments and SMC from numerous sources may be utilized for treatment of diesel
contaminated soil. The cost appeal and environmental benefit of composting diesel
contaminated soil is enhanced by the success that was shown using a number of
sustainable substrates. This research provides further support for biological treatment of
petroleum contaminated soil with a less intensive process than is required by many
conventional treatment techniques.
5.3 Future Work
1. Close monitoring of full-scale implementation of this treatment at the California
Mushroom Farm will provide insight into the performance of the upscaled
bioremediation system.
• Adherence to optimal composting conditions as recommended by this research
should help bring the diesel concentration to the target value.
89
• A record of operational parameters and regular monitoring will help compare the
performance of the laboratory studies to the field system and give better time-
frame estimations for future clean-ups.
• The nature of contaminant end products obtained in the field should be evaluated
to ensure that they do not pose toxic hazards for future activity that will take place
on the site.
2. Gas chromatography – mass spectrometry (GC-MS) analysis could be applied in
future treatability studies of diesel composting to help characterize the
remaining hydrocarbon fraction after maximum biodegradation has occurred.
• Such analytical methods would help assess the proper method for their final
treatment, by identifying the removal of specific contaminants during the course
of treatment and any residual contaminants.
3. Microbial characterization of SMC, as well as more specific bacterial and fungal
targeting, could give more insight into the remediation dynamics and SMC’s role
as an inoculum or simply a biostimulant of the soil microbial community.
• Specific targeting of hydrocarbon degrading genes and species in the various
composting treatments, combined with DGGE optimization and successful
sequencing, could help to isolate pertinent members of the community and
provide insight into enrichment methods for treatment of residual hydrocarbon
concentration.
4. A complete characterization of the compost amendments could be done.
• This analysis would be interesting to determine which biological and chemical
properties provide an advantage over others, and to identify metabolites and end
products formed during the course of treatment.
5. The value of a chitin amendment in systems with a much higher C:N ratio, such
as that with wood chips or peat moss, could be investigated.
6. The sorption implications of adding large quantities of various organic materials
should be assessed.
• It must be ensured that high sorption capacities do not outweigh the benefits of
this sustainable treatment.
90
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Appendix A
Soil Textural Class According to the United States Department of Agriculture
Figure A-1: Chart showing the percentages of clay, silt, and sand in the basic textural
classes (United State Department of Agriculture <http://www.usda.gov>).
Appendix B
Extraction Method Development
B.1.1 Preliminary Considerations
A multitude of extraction methods have been reported in the literature for GC
analysis of TPH concentrations in soil samples. These are developed in house or modeled
after published procedures. Development and use of such procedures are dependent on
the needs and resources of the authors, as well as the target petroleum analytes. For
example, sonication in hexane has been found by several authors to be an effective low-
cost method to extract hydrocarbons from soils and organic material (Guerin, 1999, Punin
Crespo et al., 2006). Guerin (1999) found sonication to be more effective than the
Soxhlet extraction method and recommended a time course study to determine the time
necessary to extract aged hydrocarbons. The appropriate extraction method for this
research was researched extensively and was developed and modified to address specific
details of the experimental design and nature of the samples. Unfortunately, the most
commonly used extraction procedures require either a greater sample mass than was
contained in the Phase I and II microcosms or equipment that was not available in the
Environmental Engineering Kappe labs. GC-FID analysis with a capillary column is
recommended for analysis of petroleum hydrocarbons according to EPA Method 8015D.
Headspace analysis by GC-FID is not possible with heavier fuels such as diesel but this
was not clear at the beginning of research so much effort went into developing a method
that could be used with the headspace autosampler. For these reasons, a new extraction
procedure and analytical protocol was developed for this work.
100
B.1.2 Extractions in the Phase I and II Microcosm Tests
Due to California’s maximum contaminant goal of 100 ppm TPH in soil, it was
necessary to quantify the TPH concentration of the soil fraction rather than that of the
soil-compost mixture that existed in the microcosm bottles. Thus, if the TPH of the
microcosm contents was quantified and compared to conditions not amended with
compost, contaminant dilution caused by the addition of compost material had to be
considered. For this reason, determinations of TPH concentrations in substrate amended
conditions were made by comparing GC-FID areas to a standard curve developed by
extracting diesel from soil spiked with known TPH concentrations (Shin and Kwon,
2000) that was also mixed with a 1:1 (v/v) ratio of uncontaminated SMC, thereby
mimicking the contents of the microcosm bottles. This extraction procedure accounted
for the extraction efficiency of the method as well as the dilution factor and any matrix
effects caused by SMC addition. In order to make the proper quantification and compare
removal in both active and control microcosms, two standard curves were developed
based on extractions from soil of known concentrations with and without the compost
addition. In Phase I, direct extraction with hexane was utilized as described in Section
2.1.3.2.
In order to ensure that the extraction efficiency would not be affected by the
material composition of the extraction vessel, a small test was performed. Soil samples
spiked with five different hydrocarbon concentrations were stored overnight in glass vials
and a replicate set of similarly spiked samples were stored overnight in the same 2.2 mL
plastic tubes that were used in the experimental procedure. Comparable GC areas were
obtained upon extraction from both sets. Another small test was also conducted to
determine whether storage of the sample following extraction prior to GC analysis would
affect the reported hydrocarbon concentration. After overnight storage at 4 oC, the
hydrocarbon concentration in one tested extract decreased by only 6%, so it was assumed
that the maximum 30 min that the extract was stored during day-to-day sampling would
not cause a significant loss of mass.
101
Between Phases I and II, several modifications were made to optimize the
extraction procedure further. First, a solvent optimization test was conducted by
performing the previously developed extraction procedure on contaminated California
Mushroom Farm soil with either hexane or acetone. Superimposed chromatograms
demonstrated identical response curves but a larger area in the extract using acetone,
indicating that a greater contaminant mass was pulled off the same soil sample using
acetone (Figure B-1). Second, the recovery of the extraction procedure was tested with
different sonication times ranging from 5 to 30 minutes. It was determined that recovery
was the most reproducible and did not increase in mass after 5 minutes of sonication
(Figure B-2).
Figure B-1: Superimposed chromatograms of TPH extracts obtained by identical
procedures from the same contaminated soil sample using the solvents hexane (lower red
line) and acetone (upper blue line). The images indicate greater mass recovery using
acetone.
102
B.1.3 Extractions in the Screening and Respirometry Tests
In the Screening and Repirometry Tests, the extraction method was replaced with
a shaking method that correlated extracts directly to diesel standards in acetone. The
shaking procedure was modeled after one performed by Schwab et al (1999), where 1-5 g
of soil were added to a 20 mL scintillation vial with 10 mL of solvent, shaken on a
reciprocating platform shaker from 30-60 min, and centrifuged for 10 minutes at 1000
rpm. These authors compared various extraction procedures and solvents. Acetone was
found to be the best solvent for extracting from differently treated soils when compared
to hexane, dichloromethane, methanol, and methanol + water. Extraction efficiencies
comparable to Soxhlet extraction were found with shaking and a shaking time greater
than 30 minutes was not found to be beneficial. The equation for hydrocarbon
0
5000
10000
15000
20000
25000
-5 5 15 25 35 45 55 65 75 85 95 105 115 125 135
Sonication Time (min)
Are
a (p
A)
Figure B-2: Effect of sonication time on recovery of diesel range TPH from weathered
soil samples extracted in acetone. Data points represent duplicate averages; error bars
represent one standard deviation.
103
concentration based on the standard curve equation was the same as that found in
Jorgensen et al., 2005.
The shaking extraction was simpler because it made it possible to correlate
sample concentrations to a calibration curve generated directly from standards rather than
extractions from soil spiked with standards. It eliminated the need to perform ten
extractions every time a standard curve had to be generated and avoided the assumption
that microcosm contents were homogeneously mixed at a 1:1 volume ratio, although they
were stirred vigorously prior to removing from the serum bottles. However, this method
and other published methods do not take into account the matrix effects of the various
composts. Additional tests would be necessary in any procedure to develop correlations
between the extraction efficiencies and standards at different concentrations.
B.1.4 Suggested Modifications to the Extraction Procedure
Considering the different methods that were used for Phase I and II extractions, a
correlation to extraction from spiked soil standards is impractical, time-consuming, and
incorporates various assumptions. The main reason for choosing such a method was to
ensure that the soil concentration was being monitored rather than the concentration of
the soil-compost mix for regulatory purposes. However, once the soil and compost are
combined, two separate matrices no longer truly exist, especially as the contact time
between them increases, so it is essentially impossible to accurately determine only the
soil concentration. Another approach would be to target a certain fractional TPH removal
and ensure that the TPH concentration in the soil-compost mix decreases by the same
fraction necessary to bring the controls from their starting concentrations to 100 ppm. For
example, if the soil’s starting TPH concentration was 2000 ppm and the goal was 100
ppm, a 95% decline in TPH would be necessary under all substrate amended conditions
as well. It would then not be necessary to correlate the mixture to the soil concentration
because the goal would be removal of a certain percentage. In this way, another extensive
extraction procedure could be applied and compared to pure standards. This overall
104
decrease approach was taken into consideration for the development of the shaking
extraction method.
Various details about extract handling and quantification must be evaluated and
defined prior to selecting and finalizing an extraction procedure. These steps minimize
quantification interferences and contaminant loss during the extraction process. All
extracts were analyzed immediately in all experiments to avoid time effects on the
extracts. However, the proper extraction procedure should include a drying step or
purification step. Drying can be accomplished by using a roto-evaporator or nitrogen
stream, which eliminates most of the solvent and concentrates the sample. Purification
can be accomplished by adding an absorbent such as Florisil©, which removes molecules
that may interfere with accurate quantification of petroleum hydrocarbons (EPA Method
3620C). Neither drying nor purification was used in these analyses because initially the
extract was to be analyzed by direct sample analysis by volatilization into a headspace
vial. After it was discovered that this method could not be used and the samples had to be
individually extracted and direct injected into the GC, the time was not available to
include these steps and then also perform direct injections at 30 minute intervals. The
importance of these steps was also not realized so a solvent volume was used (especially
in Phases I and II) that was too small to be decanted and concentrated.
Additionally, an internal standard is essential for ensuring that the analyte
recovery falls within an acceptable range and is not lost through handling and the steps of
the extraction procedure. In these tests, an internal standard of nonane was initially
attempted, but without a drying step, it became too dilute and the peak was too small to
visualize in the chromatogram. The internal standard should be distinguishable from the
sample area and so should elute before or after the sample retention time. In the case of
the California Mushroom Farm soil, the internal standard would have been a much longer
alkane (i.e. C28 –C40) because it would have eluted clearly past the time frame than
contamination from the California Mushroom Farm samples eluted. A shorter-chain
alkane would not have been effective because smaller contaminant peaks that
consistently eluted before the diesel range in farm’s samples would have interfered with
internal standard quantification.
105
Appendix C
pH in Phase II Microcosms on day 34
The pH of the Phase II microcosms was monitored on day 34 to check the
progress of experimental conditions (Table 4.4). The pH of active microcosms remained
circumneutral (7.8 ± 0.06) though they demonstrated a small drop from the original pH of
SMC and soil (Tables 4.2 and 4.3). Decreases in pH at the onset of composting have
been noted by others. Moretto et al. (2005) detected a decrease in pH during composting
that corresponded with enhanced microbial activity and degradation of PAHs. Tiquia et
al. (1997) found a pH decrease in the first 35 days of composting that correlated closely
to a decrease in ammonium, presumably by utilization by degrading microbes. In this
experiment, the slight drop in pH may be caused by the production of fatty acids from
fermentation of SMC and chitin during biodegradation (Brennan et al., 2006). However,
since chitin also possesses strong buffering capacity, the pH in the microcosms remained
near neutral and within the optimum pH range of 6 – 8 for hydrocarbon bioremediation in
soil (Singh et al., 2005).
Table C-1: Comparison of pH in Phase II microcosm on day 34. Values represent
duplicate averages of the Actives, and singlet points of the Controls.
Temperature Actives (SMC + chitin) Controls (soil only)
22 oC 7.8 7.4
30 oC 7.7 7.7
50 oC 7.8 7.4
Appendix D
Supplemental Molecular Analyses
D.1 DGGE BAND CONFIMATION
Figure D-1: Second run of DGGE gels used to confirm bands excised from the Phase I and II DGGE gels.
(Section 3.2.1). The most distinct bands in these lanes were excised and the DNA was reamplified for
sequencing after eluting overnight. Indicated bands are represented by relative positioning in Phase I and II
gels in Section D.1 and sequencing results are presented in Section D.2.
D.2 COMPARATIVE BAND MOVEMENT IN DGGE GELS
Table D-1: Numerical comparison of relative mobilities and percent of total sample areas for
DGGE banding patterns obtained for Phase I microcosm testing. The bands that could be
deciphered and sequenced are indicated in the margins. Bands that were sequenced are in bold,
and other bands that migrated to the same position are surrounded by a black border.
Soil Only (Control) SMC + contaminated soil SMC + contaminated soil + chitin
t=4 t=9 t=19 t=86 t=4 t=9 t=19 t=86 t=4 t=9 t=19 t=86
0.06 9.47 12.9 8.13
0.12 4.74
0.15 5.03
0.32 18.7 7.79 4.47
0.37 7.77 3.31
0.38 3.12 5.70
0.39 1.18 2.91 8.85
0.41 3.14
0.42 4.97 6.42 5.20 26.87 5.27 3.91 7.17 30.12 21.46 4.21 I - SMC1
0.43 9.24 9.10 2.93
5.53
0.44 2.84 4.95
3.08
0.45 4.39 5.46 6.02
0.47 13.50 4.21 3.76 11.05 I-Control
2.18
0.5 9.05 4.23
0.51 5.13
0.52 3.85 1.98
0.53 24.19 19.34 28.51 10.11
0.58 16.63
0.59 5.95
0.62 11.66 3.21 I-SMC2
0.64 2.74 10.81 1.84
0.65 2.18 2.10
0.66 4.11
0.68 10.34 11.81
0.69 3.78
0.73 6.20
0.76 4.49
0.85 23.74
0.86 27.09 56.60 44.31 26.37 65.36 44.44 32.88 33.53 43.46
0.88 1.79 18.37 16.79 26.32 23.19
0.95
0.96 17.48 26.02 26.94 30.08
108
Table D-2 : Numerical comparison of relative mobilities and percent of total sample areas for DGGE banding patterns obtained
for Phase II microcosm testing. The bands that could be deciphered and sequenced are indicated in the margins. Bands that
were sequenced are in bold, and other bands that migrated to the same position are surrounded by a black border.
Actives Controls
t=0
t=1 50 oC
t=4
22 oC
t=4 30 oC
t=8 30 oC
t=20
30 oC
t=56
30 oC t=0
t=8 30 oC
t=20
30 oC
t=56
30 oC SMC Chitin
0.01 5.962 6.555 11.2 2777
0.02 2.554 2.26
0.03 3.307
0.04 5.12
0.05 4.653 2.206
0.06 2.929 4.813
0.07 4.827 4.602
0.09 7.763
0.1 10.54 4.737 5.668
0.12 10.21 4.068 4.882
0.13 5.734 2.251
0.14 11.14
0.15 10.63 2.334 1.166
0.16 1.606
0.2 2.751
0.22 7.043
0.27 4.249 4.079 9.988
0.28 15.25 1.513
0.29 9.387
0.3 0.935
0.31 4.297
0.35 7.465
0.36 9.057
0.37 13.27 3.60 5.89
0.38 1.07 3.80
0.39 1.76 32.40
0.4 22.80 29.12 24.69
0.41 1.57 3.79 11.29 9.004
0.42 21.00 4.59 16.06 11.39 11.21 8.86 1.86 8.408 II -1
0.43 2.37 3.03 4.90 1.94 4.29 3.85
0.44 8.19 57.36 17.67 15.81 14.93 II - 2
0.45 3.03 4.16 8.45 6.63 7.96 4.871
0.46 1.48 4.07 1.99 14.69 2.47 7.63
0.47 8.83 6.27
0.48 7.20
0.49 4.33 22.76
0.5 2.21
0.51 1.84
0.52 5.16 6.24 5.87 5.48 3.30 II - 3
0.53 7.18 5.43 4.23 2.71 4.257 II - 4
0.54 2.30
0.55 8.97 16.87 11.11 1.44 3.66 II - 5
0.6 6.05 5.68 4.74
0.61 2.74
0.63 5.71 5.81
0.65 11.92
0.66 8.32 8.82 II - 6
0.68 15.85
0.69 14.34
0.8 14.98 II - 7
0.89 9.62 9.39 II - 8
0.94 17.27 36.19 30.96 17.87 23.04 35.25 29.38
0.95 3.40 56.08 37.57
0.97 14.75 10.49 10.26 20.63 6.20 3.54
109
Table D-3 Numerical comparison of relative mobilities and percent of total sample areas for
DGGE banding patterns obtained for contaminated soil from different depths below ground. The
bands that could be deciphered and sequenced are indicated in the margins. Bands that were
sequenced are in bold, and other bands that migrated to the same position are surrounded by a
black border.
Depth
4' 4.5' 5' 5.5' 6' 8'
0.05 9.384
0.06 7.949
0.53 3.084
0.57 45.1 36.85 36.85 39.43 III-1
0.6
0.61 35.41 68.85 5.90 41.98
0.65 25.25 18.59 III-2
0.7 31.15 10.07 6.35 III-3
0.72 12.48 III-4
0.76 9.55
0.77 68.03 5.98
0.98 22.75 24.50
0.99 39.34
D.3 SEQUENCING RESULTS
Table D-4: Sequencing results for bands excised from DGGE gels run with PCR products from Phase I and II microcosm experiments. Gels presented
in Section D.2 demonstrate band identifications and conditions under which each was found. Uncultured strains are not reported, so % similarities
refer to cultured species with the highest % similarities. All are 16S ribosomal, partial sequences.
Band GenBank Closest Matches
%
Similarity Article Title Authors and References
Phase I Bands
I -
Control
Alcanivorax sp. ZXM228,
ZXM018, ZXM221 98
Phylogenetic diversity of cultural bacteria from the coastal water
of Qingdao, China during the massive green algae blooms Zhang,X. and Zhang,X.-H. (unpublished)
Alcanivorax sp. DG1698,
DG1690 98
Isolation of oil-degrading marine bacteria from oil-amended
microcosms Green,D.H. and Hart,M.C. (unpublished)
Alcanivorax sp. 14E 98
Isolation and characterization of oil degrading bacteria from oil
field Ping,H. and Li,Z. (unplublished)
Alcanivorax dieselolei
strain PR56-2 98
PAH-Degrading Bacteria in the Southwest Indian Ocean Deep
Sea Water Column Yuan,J., Lai,Q., Zheng,T. and Shao,Z. (unpublished)
Alcanivorax dieselolei
strain As-I2-8 98
Diversity of Arsenite-resistant Bacteria from Deep-Sea
Sediments of the Southwest Indian Ocean Ridge Chen,S.X. and Shao,Z.Z. (unpublished)
Alcanivorax sp. HU1 98
Effects of surfactant and augmentation on crude-oil
biodegradation by Brevundimonas sp. HU2 isolated from
petroleum-contaminated marine sand
Sawarngnavin,N., Ammuay,G., Thaniyavarn,J. and
Thaniyavarn,S. (unplublished)
Alcanivorax sp. EZ46 98
Facilitation of robust growth of Prochlorococcus colonies and
dilute liquid cultures by 'helper' heterotrophic bacteria
Zinser,E.R., Morris,J.J., Johnson,Z.I., Kirkengaard,R.
and Szul,M.J. 2008. Applied and Environmental
Microbiology, 74 (14): 4530-4534.
Alcanivorax sp. NIOB 441,
NIOB 406 98
Molecular identification of bacteria from marine environments
by 16S rDNA gene sequencing Krishna,K., Ammini,P. and Nair,S. (unpublished)
111
Alcanivorax sp. YDC2-H,
YD13-A 98 Diversity analysis of bacteria isolated from the Indian Ocean Liu,Y., He,P. and Huang,X. (unpublished)
Alcanivorax sp. S71-4, S68-
4 98
Benzene, toluene and xylene degrading bacteria in the surface
water of Straits of Malacca and Singapore Wang,L., Sun,F.Q. and Qiao,N. (unpublished)
Alcanivorax dieselolei
strain PTG4-3 98
Isolation, Characterization and Polycyclic Aromatic
Hydrocarbon Degradation of a Deep Sea Bacterium,
Pseudoruegeria sp. P73
Yuan,J., Lai,Q., Sun,F., Zheng,T. and Shao,Z.
(unpublished)
Alcanivorax dieselolei
isolate P40 98
Genetic analysis of housekeeping genes reveals a deep-sea
ecotype of Alcanivorax dieselolei in the Indian Ocean Lai,Q., Yuan,J. and Shao,Z. (unpublished)
Alcanivorax sp. DJCJ39 98 Phylogenetic analysis of bacteria in the China Sea Qu,L., Sun,X. and Zhang,J. (unpublished)
Alcanivorax sp. 5-2A 98
Diversity of PAHs Degrading Bacteria from Middle Atlantic
Ridge Sediment and Structural Analysis and Dynamics of
Bacterial Communities Cui,Z. and Shao,Z. (unpublished)
Alcanivorax dieselolei
isolate MARMC3H,
MARMC3C, MARMC2N,
MARMC2M, MARMC2L,
MARC4A14, MARC2C-S 98
Diversity of PAHs Degrading Bacteria from Middle Atlantic
Ridge Sediment and Structural Analysis and Dynamics of
Bacterial Communities Cui,Z. and Shao,Z. (unpublished)
Alcanivorax sp.
WINTA111da gene for 98
Microbiota variation in Senegal sole (Solea senegalensis) under
different diets Manchado,M. (unpublished)
Alcanivorax sp. EPR 6 98
Culture-dependent and independent analyses of microbial
assemblages along a temperature gradient at a deep-sea
hydrothermal vent
Vetriani,C., Reed,A.J., Crespo-Medina,M.,
Voordeckers,J. and Lutz,R.A. (unpublished)
Alcanivorax sp. OK2 98 Petroleum degrading marine bacterium Koren,O. and Rosenberg,E. (unpublished)
Alcanivorax sp. MN59 98
Diversity of heavy metal resistant bacteria from deep-sea
sediments Tian,M. and Shao,Z. (unpublished)
Alcanivorax dieselolei
strain B-5 clone 1 16S
ribosomal RNA gene,
partial sequence 98
Alcanivorax dieselolei sp. nov., a novel alkane-degrading
bacterium isolated from sea water and deep-sea sediment
Liu,C. and Shao,Z. 2005. International Journal
Systemic and Evolutionary Microbiology, 55 (PT 3):
1181-1186.
112
Alcanivorax sp. TE-9 gene 98
Development of specific oligonucleotide probes for the
identification and in situ detection of hydrocarbon-degrading
Alcanivorax strains
Shutsubo,K. and Harayama,S. 2001. Environmental
Microbiology, 3 (6): 371-379.
Fundibacter sp. U20 98
Microbial communities in the chemocline of a hypersaline deep-
sea basin (Urania basin, Mediterranean Sea)
Sass,A.M., Sass,H., Coolen,M.J.L., Cypionka,H. and
Overmann,J. 2001. Applied Environmental
Microbiology, 67 (12): 5392-5402.
Alcanivorax sp. PDA15b 98
Multiple approach study of bacterial communities associated to
shoreline environments from Costa da Morte (NW-Spain)
affected by the Prestige oil-spill
Alonso-Gutierrez,J., Figueras,A. and Novoa,B.
(unpublished)
I -
SMC1 H.obtusa 16S rRNA gene 100
In situ detection/identification and phylogeny of uncultured
bacterial endosymbionts Ludwig, W. ( Nature In press)
I -
SMC2
Hydrogenophaga
carboriundus strain
KRH_YZ 98
Hydrogenophaga carboriundus sp. nov., a tertiary butyl alcohol-
oxidizing, psychrotolerant aerobe derived from granular
activated carbon (GAC)
Zhang,Y., Reinauer,K.M. and Finneran,K.T.
(unpublished)
Hydrogenophaga sp. 1130-
64-12, 1130-64-11 98
Microbial Sulfur Cycling and Iron Reduction in Subpermafrost
Saline Fracture Water at the Lupin Gold Mine, Nunavut, Canada Vishnivetskaya,T.A. (unpublished)
Hydrogenophaga bisanensis
strain K102 98
Hydrogenophaga bisanensis sp. nov., isolated from wastewater
of a textile dye works
Yoon,J.H. 2008. International Journal of Systemic
and Evolutionary Microbiology, 58 (PT 2): 393-397.
Hydrogenophaga sp. D11-
24b2, D3-13_1 98
Diversity of Nitrate-reducing and Denitrifying Bacteria in a
Marine Aquaculture Biofilter Krieger,B.U. (unpublished)
Hydrogenophaga sp.
GPTSA100-30,
GPTSA100-10 98
Study of culturable bacterial diversity of an aquatic sample
collected from a warm spring of Assam, India Saha,P. and Chakrabarti,T.
Hydrogenophaga sp. YED1-
18 98
Community and cultivation analysis of arsenite oxidizing
biofilms at Hot Creek
Salmassi,T.M., Walker,J.J., Newman,D.K.,
Leadbetter,J.R., Pace,N.R. and Hering,J.G. 2006.
Environmental Microbiology, 8 (1): 50-59.
Phase II Bands
113
II - 1 Psychrobacter sp. XH6 94
Identification of microorganisms isolated from Great Wall Bay
in the Antarctic Wang,N., Chen,Z., Lin,X. and Shen,J. (unpublished)
Psychrobacter pulmonis
strain S16-5-1, 13 94
Molecular identification of microorganisms isolated from polar
area Lin,X. and Xu,G. (unpublished)
Psychrobacter sp. S11-10-3-
1, S11-6-3, P11-8-2, 17-1 94
Molecular identification of microorganisms isolated from polar
area Lin,X. and Xu,G. (unpublished)
Psychrobacter sp. SH6 94
Phylogenetic analysis of bacteria isolated from Antarctic sea-
water Wang,N., Chen,Z., Lin,X. and Shen,J. (unpublished)
Psychrobacter sp. OTUC8 94
The comparative analysis of microorganism diversity in chilled
beef on sale by two methods Li,Z., Li,B. and Ou,J. (unpublished)
Psychrobacter sp. AP6F1 94
Molecular analysis of bacterial community associated with
different compartments of the digestive tract of Aplodactylus
punctatus Romero,J., Navarrete,P. and Opazo,R. (unpublished)
Psychrobacter sp. 3ps 94
Psychrobacter sp., a novel psychrotolerant isolate from water
brine in Arctic permafrost
Suetin,S.V., Shcherbakova,V.A. and
Chuvilskaya,N.A. (unpublished)
Psychrobacter sp. S06 94
Screening and identification of the bacterium from the chilled
beef on sale Li,Z., Li,B., Ou,J. and Zhao,Y. (unpublished)
Psychrobacter sp. SRA2,
SRA1 94
Improvement of plant growth and nickel uptake by nickel
resistant-plant growth promoting bacteria Ma,Y., Rajkumar,M. and Freitas,H. (unpublished)
Psychrobacter sp. NJ-48 94 Microorganism isolated from Antarctica Xiao,X. (unpublished)
Psychrobacter maritimus
strain KOPRI_22337 94 Isolation and identification of Arctic marine bacteria
Lee,Y.K., Jung,H.J., Cho,H.H., Cho,K.H., Hong,S.G.
and Lee,H.K. (unpublished)
Marine bacterium MSC109,
MSC108, MSC107, MSC33 94
Short peptide induces an 'uncultivable' microorganism to grow in
vitro
Nichols,D., Lewis,K., Orjala,J., Mo,S., Ortenberg,R.,
O'Connor,P., Zhao,C., Vouros,P., Kaeberlein,T. and
Epstein,S.S. 2008. Applied and Environmental
Microbiology, 74 (15): 4889-4897.
Psychrobacter sp. MOLA
38 94
Structure and functions of bacterial communities in a coastal
NW Mediterranean ecosystem Intertaglia,L. (unpublished)
Psychrobacter pulmonis
strain b105, a43, a40, a72 94
Composition and Characterization of Bacterial Communities in
Antibiotic Production Wastewater and the Receiving River
Using Culture-dependent and -independent Techniques Li,D., Zhang,J. and Yang,M. (unpublished)
114
II-2 Sporosarcina sp. JZDN49 98 Phylogenetic analysis of bacteria in mud of Jiaozhou Gulf Qu,L., Zhang,J. and Sun,X. (unpublished)
II-3 Arthrobacter sp. A-21p 93
Phylogenetic diversity and cold-adaptive enzymes of culturable
psychrophilic and psychrotolerant bacteria from King George
Island, Antarctic
Morozova,O.V., Andreeva,I.S. and Zhirakovskiy,V.
(unpublished)
II-4
Firmicutes bacterium
VNs59 98
Characterization by culture and molecular analysis of the
microbial diversity of a deep subsurface gas storage aquifer
Basso,O., Lascourreges,J.F., Le Borgne,F., Le
Goff,C. and Magot,M. 2009. Research in
Microbiology 160 (2), 107-116.
Clostridiaceae bacterium
CAa338 98
Biofilm-producing, alkaliphilic bacteria from ikaite tufa columns
from Greenland Stougaard,P., Aarup,C. and Prieme,A. (unpublished)
Clostridiales bacterium
UXO5-23, UXO5-25,
UXO5-19, UXO5-13 98
Abundance and diversity of octahydro-1,3,5,7-tetranitro-1,3,5,7-
tetrazocine (HMX)-metabolizing bacteria in UXO-contaminated
marine sediments
Zhao,J.-S., Manno,D. and Hawari,J. 2007. FEMS
Microbiology and Ecology, 59 (3), 706-717.
II-5 Ureibacillus sp. A3.03 97
Thermophilic bacteria in cool temperate soil environments: are
they metabolically active or continually added by global
atmospheric transport?
Marchant,R., Franzetti,A., Pavlostathis,S., Okutman
Tas,D., Erdbrugger,I., Unyayar,A. and Banat,I.
(unpublished)
Bacillus sp. 60LAy-1,
50LAy-3 gene 97
Investigation of Heat Generating Bacteria in Thermophilic
Contact Oxidation Process Toilet Daibo,A., Hanaki,K. and Kurisu,K. (unpublished)
Ureibacillus sp. R-31864 97
Comparative analysis of the diversity of aerobic spore-forming
bacteria in raw milk from organic and conventional dairy farms
Coorevits,A., De Jonghe,V., Vandroemme,J.,
Reekmans,R., Heyrman,J., Messens,W., De Vos,P.
and Heyndrickx,M. 2008. Systemic and Applied
Microbiology, 31 (2), 126-140.
Ureibacillus
thermosphaericus 97
A RAPD-based survey of thermophilic bacilli in milk powders
from different countries
Rueckert,A., Ronimus,R.S. and Morgan,H.W. 2004
International Journal of Food Microbiology, 96 (3):
263-272.
Ureibacillus
thermosphaericus strain A3 97 Bacillus thermosphaericus strain A3: a new isolate
Dulger,S., Demirbag,Z. and Belduz,A.O.
(unpublished)
115
Ureibacillus
thermosphaericus strain
S11, S10, S7, S6, T6, D2a,
D2 97
Phenotypic and genotypic characterization of esterase-producing
Ureibacillus thermosphaericus isolated from an aerobic digestor
of swine waste
Gagne,A., Chicoine,M., Morin,A. and Houde,A.
2001. Canada Journal of Microbiology, 47 (10): 908-
915.
Ureibacillus sp. MM196S
gene 97
Distribution of Symbiobacterium thermophilum and related
bacteria in the marine environment
Sugihara,T., Watsuji,T., Kubota,S., Yamada,K.,
Oka,K., Watanabe,K., Meguro,M., Sawada,E.,
Yoshihara,K., Ueda,K. and Beppu,T. 2008.
Bioscience, Biotechnology, and Biochemistry 72 (1):
204-211.
II-6
Geobacillus sp. D623,
D621, D504, D494, D504,
D494, C226, A413, A404,
A392b, A335 95
A polyphasic taxonomic study of thermophilic Bacilli revealed
by 16S rDNA sequence and amplified ribosomal DNA-
restriction analysis (ARDRA) from a wide geothermal region in
Turkey
Coleri Cihan,A., Ozcan,B. and Cokmus,C.
(unpublished)
Anoxybacillus tunisiense 95
Anoxybacillus tunisiense sp.nov, a new thermophilic facultative
aerobic bacterium isolated from a geothermal hot spring in
Tunisia
Sayeh, Roussel, Gannoun, Birrien, Hamdi and
Prieur,R.L. (unpublished)
Brevibacillus laterosporus
strain S62-9 95 High yield bacitracin strains, screening and culture conditions Ju,J.-G., Yu,H.-W. and Jia,Y.-M. (unpublished)
Geobacillus sp. Lp12 95
Evaluation of the biodiversity of a cellulase-producing
thermorphilic microogansism isolated from LaPhu-Phutho hot
spring Man,T.D. and Viet,N.Q. (unpublished)
Geobacillus sp. JAM-
FM0901 gene 95
Phylogenetic and enzymatic diversity of deep subseafloor
aerobic microorganisms in organics- and methane-rich sediments
off Shimokita Peninsula
Kobayashi,T., Koide,O., Mori,K., Shimamura,S.,
Matsuura,T., Miura,T., Takaki,Y., Morono,Y.,
Nunoura,T., Imachi,H., Inagaki,F., Takai,K. and
Horikoshi,K. 2008. Extremophiles, 12 (4): 519-527.
Thermal soil bacterium
YNP 10 95 Prokaryote diversity in an extreme thermal soil
Botero,L.M., Burr,M.D., Willits,D., Elkins,J.G.,
Inskeep,W.P. and McDermott,T.R. (unpublished)
116
Geobacillus sp. SF03 95
Thermoactive extracellular proteases of Geobacillus
caldoproteolyticus, sp. nov., from sewage sludge
Chen,X.G., Stabnikova,O., Tay,J.H., Wang,J.Y. and
Tay,S.T. 2004. Extremophiles, 8 (6): 489-498.
Anoxybacillus flavithermus 95
Isolation, characterization and identification of bacterial
contaminants in semi-final gelatine extracts
De Clerck,E., Vanhoutte,T., Hebb,T., Geerinck,J.,
Devos,J. and De Vos,P. (unpublished)
Bacillus sp. 95
Association of bacteria of the genus Lactobacter with the
dinoflagellate Peridinium from the Sea of Galilee
Prokic,I., Wynnne,D. and Mueller,W.E.G.
(unpublished)
Bacillus sp. OS-ac-18 95
Cultivation of Proteobacteria and Gram Positive Bacteria from a
Hot Spring Microbial Mat
Nold,S.C., Kopczynski,E.D. and Ward,D.M.
(unpublished)
Bacillus sp. NR-1001 95
A thermophilic Bacillus isolate from predigester of Nisarg Runa
Biogas plant
Mehetre,S.T., Kale,S.P., Das,A.D., Venu-Babu,P.,
Mukhopadhyaya,R. and Rao,A.S. (unpublished)
II-7 All uncultured species
II-8
Flavobacteracae bacterium
KKE2-09, KE2-02 96
Egg-associated microflora of Pacific threadfin, Polydactylus
sexfilisand amberjack, Seriola rivoliana, eggs. Characterisation
and properties
Verner-Jeffreys,D.W., Nakamura,I. and Shields,R.J.
2006. Aquaculture, 253 (1-4): 184-196.
D.4 CLONING
D.4.1 Procedure
To confirm PCR-DGGE results, PCR products from two bands (I-SMC2 and II-1)
were purified using the QIAquick PCR purification kit (QIAGEN, Germantown, MD)
and cloned using the TOPO TA Cloning Kit (Invitrogen, Carlsbad, Ca). Prior to ligation,
PCR products were amended with 1 µL PCR nucleotide mix and 1 µL Taq Polymerase
and incubated at 70 oC for 10 minutes. Products (4 µL) were ligated into PCR 2.1 vector
and transformed into One-shot TOP10® E. coli competent cells (Invitrogen) following
the manufacturer’s instructions. The cells were incubated for one hour at 42 oC and plated
on Luria Bertani (LB) with 50 ug/mL ampicillin and 20 mg/mL X-Gal for blue-white
colony screening. Plates were incubated overnight at 30 oC. White colonies were selected
from the plates and were further grown in LB medium with 50 µg/mL ampicillin
overnight at 30 oC. Plasmids were extracted from the cultures using the Axyprep Plasmid
Miniprep Kit (Axygen Scientific, Inc., Union City, CA).
D.4.2 Results and Discussion
The results of the sequence analyses of the clones are shown in Table D-5. I-
SMC2 matched with the sequence analysis from the bands, while II-1 did not. This could
be explained by the % similarity being relatively lower for both of the II-1 samples (94%
from the band and 97% from the clone) and highlights the importance of a much greater
similarity to make any determinations about community members. However, it also
demonstrates that various sequences might have migrated to the same position on the gel.
Since very few clones were produced, the one that was selected and sequenced may not
have contained the prominent sequence in the band. Further DGGE optimization as stated
118
in Section 4.4.3 is necessary to assess conclusively the microbial composition of the
treatment system.
Table D-5 : Sequence analysis of cloning DNA eluted from two DGGE bands. Gels presented in Section D.2 demonstrate band identifications and
conditions under which each was found. Uncultured strains are not reported, so % similarities refer to cultured species with the highest % similarities. All
are 16S ribosomal, partial sequences
Band GenBank Closest Matches
%
Similarity Article Title Authors and References
I -
SMC2
Hydrogenophaga
carboriundus strain
KRH_YZ 100
Hydrogenophaga carboriundus sp. nov., a tertiary butyl alcohol-
oxidizing, psychrotolerant aerobe derived from granular activated
carbon (GAC)
Zhang,Y., Reinauer,K.M. and Finneran,K.T.
(unpublished)
Hydrogenophaga sp. 1130-
64-12, 1130-64-11 100
Microbial Sulfur Cycling and Iron Reduction in Subpermafrost Saline
Fracture Water at the Lupin Gold Mine, Nunavut, Canada
McGown,D.J., Bakermans,C., Ruskeeniemi,T.,
Ahonen,L., Telling,J., Boettiger,C., Ho,R.,
Soffientino,B., Pfiffner,S.M., Sherwood Lollar,B.,
Frape,S., Stotler,R., Pratt,L.M., Vishnivetskaya,T.A. and
Onstott,T.C. (unpublished)
Hydrogenophaga sp. D11-
24b2 100
Diversity of Nitrate-reducing and Denitrifying Bacteria in a Marine
Aquaculture Biofilter
Krieger,B.U., Rezakhani,N., Drake,H.L. and
Schramm,A. (unpublished)
Hydrogenophaga sp.
GPTSA100-30 100
Study of culturable bacterial diversity of an aquatic sample collected
from a warm spring of Assam, India Saha,P. and Chakrabarti,T. (unpublished)
II - 1 Bacillus sp. L244 97
Biologically active bacteria associated with the brown algae
Laminaria saccharina from the Baltic Sea
Wiese,J., Thiel,V., Nagel,K., Staufenberger,T. and
Imhoff,J.F. (unpublished)
Bacillus sp. EK-11, EK -2 97 Impact of nitrate reducers in elecrokinetics system
Choi,J.-H., Maruthamuthu,S., Lee,H.-G., Ha,T.-H. and
Bae,J.-H. (unpublished)
Bacillus sp. K36T, K16T 97
Bacterial community evolution and plant establishment during
rehabilitation of Mediterranean anthropogenic soils using symbiotic
wild legume shrubs
Cardinale,M., Brusetti,L., Lanza,A., Orlando,S.,
Daffonchio,D., Puglia,A.M. and Quatrini,P.
(unpublished)
Bacillus sp. 6M56 97 Novel Bacillus species isolated from cotton waste Kim,B.Y. and Kwon,S.W. (unpublished)
Bacillus sp. PE4 97
Isolation and characterization of a diverse group of phenylacetic acid
degrading microorganisms from pristine soil
O'Connor,K.E., O'Leary,N.P., Marchesi,J.R.,
Dobson,A.D. and Duetz,W. 2005. Chemosphere 61 (7):
965-973.
D.5 FUNGAL COMMUNITY ANALYSIS
Attempts were made in this research to more fully characterize the microbial
communities responsible for degradation by detecting and isolating members of fungal
populations present in Phase I and II microcosms. Two PCR methods were utilized
unsuccessfully with a fungal primer set described in the literature. The methodology and
suggestions are presented below as a reference for future work in analyzing these species.
D.5.1 DNA Extraction and Amplification
PCR amplification of the 18S rDNA was performed on DNA extracted from
various samples as described in Section 2.2.1, by using fungal primer pairs FR1-GC (5’
CCC CCG CCG CGC GCG GCG GGC GGG GCG GGG GCA CGG GCC GAI CCA
TTC AAT CGG TAI T AIC CAT TCA ATC GGT AIT 3’) and FF390 (5’ CGA TAA
CGA ACG AGA CCT 3’) (Vainio and Hantula, 2000) ordered from Biosearch
Technologies (Novato, CA). These primers were utilized in over 20 studies to amplify
fungal DNA extracted from soil samples. PCR amplifications were performed in a 50 µL
reaction volume using the Go Taq PCR Core System (Promega Corporation, Madison,
WI). Each reaction volume consisted of 1 µL of DNA diluted either 5X or 10X in
nuclease free water, 0.5 µM of each primer, 1.25 U GoTaq® DNA Polymerase, 10 µL
5X colorless buffer, 3.0 mM MgCl, 200 µM PCR nucleotide mix, and 0.1 mg/mL bovine
serum albumin (BSA) (Promega Corporation). A negative control consisting of 1 µL
nuclease free water in place of 1 µL DNA was included for each master PCR reaction
mixture. Amplifications were performed in a Bio-Rad iCycler with the following
temperature program:8-min activation of the polymerase at 95 oC; followed by 30 cycles
consisting of 30s min melting at 95 oC, 45 min annealing at 50
oC, and 2 min extending at
72 oC, followed by a final 10-min extension at 72
oC. This was the method detailed in the
original Vainio and Hantula paper and was also used by several other authors, but PCR
amplification was unsuccessful as determined by running the products on an agarose gel.
121
The program was modified to a touch-down method and the concentrations of primers
and MgCl2 were changed to 0.6 µM amd 2.5 mM, respectively (van der Wal et al., 2006).
Undiluted DNA and 10X diluted DNA were tested. The modified thermal cycler program
consisted of 4-min activation of the polymerase at 94 oC, followed by 8 cycles of 92
oC
for 30s, 55 oC for 1 min (decreased by 2
oC every second cycle), and 68
oC for 2 min, and
then 27 cycles of 92 oC for 30s, 47
oC for 60s, 68
oC for 45s + 1s/cycle, and a 10-min
extension at 68 oC. Again, PCR products were not successfully produced.
To test that each of the above methods would amplify DNA from known fungi,
PCR was performed on samples that clearly should have contained fungal spores. The
first method was performed on DNA extracted from moldy perchlorate-contaminated soil
left in the lab from previous unrelated experimentation, and the second method was
performed on DNA extracted from common button mushrooms purchased at a local
grocery store. At least one microcosm sample, known to contain bacterial DNA, was run
with each method to represent a sample on which DNA extraction had been performed
successfully as per the manufacturer’s instructions. Successful PCR amplification could
not be confirmed with an agarose gel for neither the fungal samples nor the microcosm
samples.
D.5.2 Recommendations for Future Research
It is more likely that the difficulties encountered in these procedures arose from
the inability to successfully extract fungal DNA using the bead beating method than from
the PCR recipe or thermal cycler program. The cell lysing technique of typical methods
used to extract bacterial DNA may not be sufficient to lyse fungal spores or mycelium.
Grinding with liquid nitrogen (van Elsas et al., 2000 and Hagn et al., 2003), cell
disruption in extraction buffer (Vainio and Hantula, 2000), and harsher methods of
sonication, crushing, and freeze-thawing in liquid nitrogen and boiling water (Kowalchuk
et al., 2002) have been reported in the literature to accomplish this purpose. It is
suggested that a fungal-specific DNA extraction technique be adopted for future
molecular research in this field. If DNA amplification is still unsuccessful, a PCR
122
optimization test, which analyzes the effect of different MgCl2 concentrations, DNA
dilutions, sample types, and use of BSA can be undertaken.
Appendix E
Respirometry Test Cumulative Oxygen Uptake
0
50
100
150
200
250
300
350
400
0 5 10 15 20 25 30
Time (days)
Cumulative Oxygen
Uptake (m
g)
CMF SMC Active CMF SMC Abiotic PSU SMC Active
PSU SMC Abiotic UAJA Compost Active UAJA Compost Abiotic
Corresponds to
water addition
and mixing
Figure D-1 : Cumulative oxygen usage for 30 days of treatment in bottles connected to respirometer
system. Apparent jumps in uptake were likely caused by instrument error and were corrected and
addressed in Section 3.3.3
Appendix F
Sorption Isotherm Development
F.1 PURPOSE AND APPROACH
Initially, traditional sorption and desorption Freundlich constants were desired to
investigate the sorptive behavior of diesel fuel to SMC and soil from the California
Mushroom Farm, including the maximum sorption capacity over time and the maximum
desorption level after equilibrium had been reached. Sorption and desorption tests would
provide information about the behavior of the contaminant in the presence of the organic
matrix and help determine the fraction of contaminant removal observed in microcosm
tests that could be attributable to irreversible sorption to the organic matrix. The
methodology followed can be found in the OECD Guideline 106, which has been used in
a number of sorption studies with hydrophobic compounds (Walter et al., 2000; von
Oepen et al., 1991).
F.2 PRELIMINARY TESTS
The sorption isotherm guidelines suggest collecting sorption values over several
concentrations, by spiking 0.01 M calcium chloride (CaCl2) aqueous solutions with 1.0,
2.0, 3.0, 4.0, and 5.0 g/L of contaminant and adding the solution to centrifuge tubes with
an uncontaminated soil sample. The volume:mass ratio of solution to soil should be 10:1.
Prior to sampling, equilibrium must be reached. Determination of the minimum time
necessary to reach maximum sorption was attempted by using 35 mL of 0.01 M CaCl2
with the upper concentration of this range (5.0 g/ml) and 3.5 g of soil and SMC. The
solution was amended with 200 mg/L sodium azide (NaN3) to prevent contaminant loss
125
by microbial degradation. Duplicate samples in centrifuge tubes capped with Mininert
valves were placed horizontally on a reciprocating platform shaker and the solution was
sampled periodically by inserting a needle in the septa of the Mininert valve and injecting
1 uL in the GC. Equilibrium could not be observed because consistent values could not
be measured between duplicates (Figure E-1). A downward and stabilizing trend was not
demonstrated after 14-24 hours. In sorption studies of PAHs on soils, complete
adsorption equilibrium were obtained in 2-8 h (Water et al., 2000) and less than 20 hours
(Means et al., 1980). When involving other sorbents, such as charcoal, the equilibrium
time was less than 20 days (Sun and Zhou, 2008).
0
10000
20000
30000
40000
50000
60000
70000
80000
0 5 10 15 20
Time (h)
Are
a (p
A)
Duplicate 1
Duplicate 2
Average
a
(a)
0
10000
20000
30000
40000
50000
60000
70000
80000
0 2 4 6 8 10 12 14
Time (h)
Are
a (p
A)
Duplicate1
Duplicate2
Average
(b)
Figure F-1 : Equilibrium test to determine the minimum time necessary to reach
126
Since the solubility of diesel is so low and it was determined that the
concentrations described in the OECD guideline could not be used if sampling for the
aqueous solution, the CaCl2 solution was spiked with a much lower concentration of 0.29
mg/mL diesel and 35 mL were added to the glass centrifuge tube with 3.5 g SMC. If all
the contaminant in this solution sorbed, it would create a 2900 ppm concentration on the
substrate, comparable to the contaminant concentration observed at the California
Mushroom Farm site. Large error bars encompassing previously and subsequently
obtained data points show that there were no significant differences between any of the
points and again a clear stabilization in concentration could not be achieved (Figure E-2).
maximum sorption of diesel to soil (a) and SMC (b). Duplicates were prepared in 35 mL
centrifuge tubes and placed on a reciprocating shaker between sampling. An equilibrium
trend was not detected after 14 and 24 hours.
Figure F-2 : Results of equilibrium test to determine the minimum amount of time necessary for sorption
of diesel to SMC. Large error bars at t = 0 and between t = 2.5 and t = 20.5 indicate irreproducibility of
duplicates.
127
This is attributable to the inhomogeneity caused by the formation of hydrophobic NAPLs
in the aqueous solution. This would also result in the potential for a disproportionate
amount of contaminant to be extracted during sampling.
F.3 PRELIMINARY TEST CONCLUSIONS
These attempts indicated that aqueous sampling is impossible for sorption
experiments for petroleum fuels. Without an extraction applied to the reaction liquid or
the soil, sorption isotherms of highly hydrophobic compounds are difficult to develop.
Diesel isotherm tests require a minimum of duplicate batch sampling of identically
prepared reaction vessels rather than sampling from the aqueous solution. Extreme care
must be taken in extracting and transferring the sample to ensure contaminant mass is not
lost in the process.
F.4. DESORPTION TESTS
Short term desorption tests at various concentrations of soil and SMC spiked with
diesel were conducted using the method described above of extracting from the solids in
the left in the tubes after ten days of equilibrating on a reciprocating platform shaker.
Briefly, soil and SMC were spiked with 1000, 2000, 3000, 4000, and 5000 ppm diesel as
described in Section 2.3.2. A 3.5 g portion was added to duplicate centrifuge tubes and
allowed to equilibrate in 35 mL 0.01 M CaCl2 solution for 10 days. Initial concentrations
were measured by extraction from duplicate 3.5 g portions from each of the five spiked
samples. During this time the solution was not replaced with a clean aliquot so the
maximum desorption of the diesel could not actually be reached. In the ten days of
shaking, 50-60 % of the contaminant had desorbed from the SMC and 10-40 % of the
contaminant had desorbed from the soil. The extraction from solids proved effective in
quantifying initial and final concentrations, but without multiple “washings” of the soil or
128
substrate by replacing the CaCl2 solution, equilibrium may have been reached between
the sorbed and aqueous phases of the contaminant so that the actual amount that could
desorb would be greater. In contrast to application in a field-scale system, replacement of
the water or contaminant degradation would induce more of the contaminant to partition
into the aqueous phase and become bioavailable.