CCI
CALSCIENCE RESEARCH, INC.
Environmental Engineers and Scientists
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REVIEW AND CRITICAL EVALUATION OF THE SCIENTIFIC
LITERATURE TO DETERMINE IMPORTANT
ENVIRONMENTAL VARIABLES CAPABLE
OF INFLUENCING BIODEGRADATION
RATES OF CHEMICALS
by
James C. S. Lu
Robert J. Stearns
Bert Eichenberger
Calscience Research, Inc.
Huntington Beach, California 92647
Contract No. 68-01-6365
Project Officer
Robert S. Boethling
Office of Pesticides and Toxic Substances
Environmental Protection Agency
401 M Street, S. W.
Washington, D. C. 20460
OFFICE OF PESTICIDES AND TOXIC SUBSTANCES
U.S. ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D. C. 20460
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DISCLAIMER
This report has been reviewed by the U.S. Environmental
Protection Agency, and approved for publication. Approval
does not signify that the contents necessarily reflect the
views and policies of the U.S. Environmental Protection
Agency, nor does mention of trade names or commercial
products constitutes endorsement or recommendation for use.
ii
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ABS TRACT
This report reviews and evaluates the scientific literature
that describes environmental variables that influence the bio-
degradation rates of chemicals. Information sources for this
review and evaluation include relevant papers, books, review
articles, abstracting services, computer searches, and the cur-
rent investigators files of the Smithsonian Science Information
Exchange.
There are numerous variables that can affect biodegradation
rates of chemicals in the environment. These may include physi-
cal variables (such as temperature, dilution, mixing, diffusion,
sorption, hydrostatic pressure, and light), chemical variables
(such as pH, redox potential, nutrients, toxins, and water
availability), arid biological variables (such as microbial inter-
actions and adaptation).
An extensive body of literature is available that identifies
relationships between a single environmental variable and the
biodegradation rate of a particular chemical or class of chemicals
for a specific set of environmental conditions. In some cases,
mathematical expressions have been developed which characterize
these relationships. However, such mathematical expressions
generally cannot be used to accurately predict biodegradation
rates behavior in natural settings. Clearly, much remains to
be learned concerning the influence of environmental variables
on biodegradation.
This report was submitted in fulfillment of Contract No.
68-01—6365 by Calscience Research, Inc. under the sponsorship
of the U.S. Environmental Protection Agency.
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CONTENTS
Abstract
Figures V
Tables V] .]1.
1. Introduction 1
2. Conclusions and Recommendations 3
Conclusions 3
Recommendations 7
3. Physical Environmental Variables 9
Overview 9
Temperature 10
Concentration 31
Sorption 36
Hydrostatic pressure 43
Light 48
4. Chemical Environmental Variables 51
Overview 51
pH 54
Redox potential 58
Nutrients 68
Toxins/inhibitors 84
Water availability 92
5. Biological En’ iironmenta1 Variables 100
Overview 100
Microbial interactions 100
Adaptation 108
Conclusions 110
6. Biodegradation Algorithms 111
Overview 111
Existing algorithms 112
Algorithm modification 137
Summary and discussion 138
References 141
iv
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F IGURES
Number
Page
1 Arrhenius plots for biodegradation of 2-AB 19
2 Arrhenius plots for biodegradation of NTA and LAS 20
3 Mineralization at various temperatures of 1% (v/v)
fresh Sweden crude coil in seawater collected in
late summer 26
4 Effect of temperature on (A) oxyg uptake during
mineral oil oxidation, and (B) CO 2 production
during hexadecane oxidation by Lake Mendota surface
water samples 27
5 Arrhenius plot of the specific growth rate of P.
fluorescensonglucose. 29
6 The effect of temperature on the lag period for bio-
degradation 30
7 The relationship between substrate concentration
and substrate utilization rate 32
8 Biodegradation of phenol as a function of time and
concentration 33
9 Malathion breakdown in sedimented and centrifuged
soil fractions, all four a itoclaved; clay; silt;
sand; organo-mineral complex 38
10 Effect of cation exchange capacity on respiration of
Agrobacterium radiobacter and Achromobacter sp 40
11 Degradation of bentonite-n-alkylaiaines and n-alkyiamines
free in an inorganic salts solution 41
12 (A) Uptake rate of [ U- 14 C1 glutamic acid by the
antarctic psychrophile ant-300 at various
temperatures and pressures 14
(B) Constant uptake rate isopleth for [ U- Clglutamic
acid by ant—300 prepared from the above figure (A).... 45
V
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Number Page
13 pH ranges for growth of (a) E. coil., (b) S.
marinorubra , (c) B. Thalassokoites , (d) marine
coccus Yl, (e) S. aureus , and f) A. laidlawli .
Incubation times and temperatures were: 24 hr
at 24°C for E. coli and S. marinorubra , 24 hr at
30°C for B. thalassokoites , 48hr at 24°C for marine
coccus Yl, 49 hr at 30°C for S. aureus , and 48
hr at 30°C for A. laidawii . A 700 is
absorbance at 700 nm 47
14 Disappearance of dimethylamine from soils of
varying pH 56
15 Total percentage of 14 C recovered as 14 C0 summed
per day for the mineralization of napht alene
in 12 sediment-water suspensions incubated at four
redox potentials and three pH levels 57
16 Total percentage of 14 C recovered as ‘ 4 C0 2 summed
pe day for the mineralization of octadecane in
12 sediment-water suspensions incubated at four
redox potentials and three pH levels 59
17 Effect of anaerobic conditions on dimethylamine
disappearance from a Williamson silt loam 62
18 Biodegradation of 14 C-carboxyl-EDTA (4.4 ppm)
under aerobic and anaerobic and anaerobic-to-
aerobic condtions in sediments 63
19 Disappearance of PCB in cyclone fermentors 66
20 Mineralization of Carex 14 C-cellulose-labeled
lignocellulose in response to different
concentrations of added nutrients 69
21 Mineralization of Carex ‘ 4 C-lignin-labeled ligno—
cellulose in response to different concentrations
of added nutrients 71
22 Rates oxygen uptake during mineral oil oxidation
and CO 2 production during hexadecane oxidation.... 73
23 Correlation between the indigenous rates of oxygen
uptake during mineral oil oxidation and the
indigenous dissolved inorganic phosphate con-
centrations less than 2.5 pg of P per liter 74
vi
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Number Page
24 Effect of nitrogen concentration (NH 4 NO. ) on
the disappearance of hexadecane brougFit about
by Nocardia sp. at 15°C 76
25 Effect of sodium lignirisulfonate on the growth
of Pseudomonas sp 80
26 Dependence of decay rate on N0 3 —N concentration 83
27 Effect of salinity on the degradation rate of
NTA by Pseudomonas sp
28 Biodegradation of (A) bacterial cell wall, and
(B) fungal cell wall in a semi-arid grassland
soil 98
29 Simulated effect of predation on C-limited bacteria
in a chemostat at a dilution rate of 0.45. The
predator returns no nutrients to the bacteria 106
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TABLES
Number Page
1 Temperature Coefficients of Biodegradation 13
2 Activation Energies For Biodegradation 21
3 Bi 1 egradation of 14 C-di-n-butyl Phthalate and
C—di-2-ethylhexyl Phthalate in Freshwater
Hydrosoil 60
4 co., and CO.) Production of Soil Containing Radio-
Labeled DCA-Soil Organic Matter Complex Under
Various Environmental Conditions 70
5 Effect of Carbon-Nitrogen Ratio on Dimethylamine
Accumulation by Micrococcus sp 72
6 Effect of Phosphorous Concentration on the Generation
Time (G) and Maximal Population of Nocardia sp.
(Per ml) Grown at 15°C for 14 days on 1%
Hexadecane 75
7 Effect of Calcium Chloride and Copper Sulfate on the
Accumulation of Ether-Soluble Acids During
Naphthalene Oxidation 77
8 Carbon and Nitrogen Contents of Organic Sources
Used in Experiment 78
9 Stimulatory Effect of Organic Sources on the Degrad-
ation of Parathion Via Nitro-Group Reduction in
Flooded Alluvial Soil 78
10 Degradation of PCB in Fermentors 81
11 Threshold Concentrations of Inorganic Pollutants
That Are Inhibitory to Biological Treatment
Processes 85
12 Threshold Concentration of Organic Pollutants
That Are Inhibitory to Biological Treatment
Processes 86
viii
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Number
13 Mineralization of TCBs in Biologically Active
Versus Poisoned Soil 90
14 Matrix of Interaction of Two Microbial Populations
A and B 101
15 Examples of Basic Biodegradation Algorithms
Used in Various Studies 113
16 Common Biodegradation Algorithms Based on
Enzymatic Reaction Kinetics 129
Ix
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SECTION 1
INTRODUCTION
Chemicals that are considered to be persistent in most
environments are of two types. First, there are natural organic
compounds including paleobiochemicals such as lignin, tannin,
melanin, and complexes such as lignified wood, melanized fungal
walls, and tanned proteins. Secondly, there is the enormous
variety of synthetic organic chemicals (xenobiotics) that enter
the environment either deliberately, via agricultural practice
for example, or inadvertantly as a consequence of industrial-
ization. While not all xenobiotics are of a persistent nature,
those that have caused most concern due to their recalcitrance
include pesticides, detergents, coolants, polymers, resins and
solvents. The number of such chemicals is ever expanding as are
also the purposes for which they are being used (Bull, 1980).
The latter group of chemicals will be the major concern of this
investigation.
Biodegradation of chemicals, as discussed in this report,
refers to the microbiological transformation of chemicals. This
process can result in complete mineralization of the chemical or
it can lead to the loss of some or all of the chemical’s charac-
teristic properties. Biodegradation may be accompanied by
utilization of the chemical as a source of energy or nutrients;
likewise it may result in detoxification with reference to either
the transforming population, a specific target organism or organ-
isms in general.
There are numerous variables that can affect biodegradation
rates of chemicals in the environment. These may include physi-
cal variables (such as temperature, dilution, mixing, diffusion,
sorption, hydrostatic pressure, and light) , chemical variables
(such as pH, redox potential, nutrients, toxins, and water avail-
ability) , and biological variables (such as microbial interac-
tions and adaptation). The objective of this study was to
identify significant environmental variables that influence
biodegradation rates of chemicals, and to evaluate algorithms
for correlation biodegradation rates and environmental variables.
An extensive body of literature is available that identifies
relationships between a single environmental variable and the
biodegradation rates of a particular chemical or class of chemi-
cals for a specific set of environmental conditions. In some
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cases, mathematical expressions have been developed which char-
acterize these relationships. However, such mathematical
expressions generally cannot be used to accurately predict bio-
degradation rate behavior in natural settings. Unlike the
controlled laboratory, the real world is highly dynamic, and
biodegradation rates are influenced by interactions between a
number of everchanging environmental factors, microbial systems,
and organic substrates. Moreover, the interpretation of data
concerning the effects of even a single environmental variable
is complicated by differences in experimental approaches and
techniques, such as pure versus mixed culture, single versus
multiple substrates, batch versus continuous systems, in vitro
(laboratory) versus in situ (field) , and so on. Clearly, much
remains to be learned concerning the influence of environmental
variables on biodegradation.
In this report, the results of the literature review and
evaluation are organized into four topics:
• Physical environmental variables;
o Chemical environmental variabl s;
• Biological environmental variables; and
o Biodegradation algorithms.
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SECTION 2
CONCLUSIONS AND RECONMENDATIONS
CONCLUSIONS
The preparation of this report involved a scientific review
of pertinent literature for identification and evaluation of the
effects of environmental variables on biodegradation rates.
Specific environmental variables are classified as physical,
chemical, or biological, and are summarized in the following
discussion.
Physical Environmental Variables
Temperature—-f
• Within the physiologically tolerated range of
temperature, biodegradation rates increase as
the temperature increases. The “Van’t Hoff Rule”
and “Arrhenius Equation”-are frequently used
to express such relationships.
Concentration--
• In general, there is a positive correlation be-
tween the concentration of a chemical and its
rate of biodegradation. However, little or no
biodegradation may occur for certain substrates
at very low concentrations, and a threshold may
exist below which no significant biodegradation
occurs. Biodegradation rates can also be great-
ly reduced when substrate concentrations are
higher then certain inhibitory levels. -
• Concentrations of chemicals may be affected
greatly in natural environments by a variety
of physical mechanisms, such as dilution, mix-
ing, diffusion, etc. Such effects may either
enhance or reduce biodegradation rates depend-
ing upon whether concentrations increase or
decrease.
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Sorption--
• Sorption of organic compounds to organic and mineral
components of the soil can act to enhance or inhibit
biodegradation. Most studies have found that clay
minerals with high cation exchange capacities can
enhance biodegradation rates.
Hydrostatic Pressure--
• In general, biodegradation rates are inversely
proportional to hydrostatic pressure. However,
biodegradation rates can be enhanced or reduced
by high pressure depending on the co—effects of
temperature and pressure. High pressure can
also result in an extended lag period.
Light--
• Light can enhance or inhibit the biodegradation
of chemicals depending on the specific conditions
and microorganisms involved. Ultraviolet light
acts to inhibit biodegradation because of its
lethal and mutagenic effects. Visible light can
also be lethal or mutagenic to those species which
are without protective carotenoid pigment.
• Light can be used by photosynthetic bacteria to
degrade low molecular weight organic compounds.
Evidence suggests that certain light intensities
may inhibit substrate utilization by bacteria;
though few data are available on this subject.
Chemical Environmental Variables
• Biodegradation generally occurs within a pH range
of 5 to 8, pHs which are commonly encountered in
natural systems. For some chemicals, variation
within this range will influence biodegradation
rates. For others, variations within this range
have a negligible effect on biodegradation rates.
Redox Potential--
• The rate and extent of biodegradation is profound-
ly affeted by redox potential. Though biodegradation
rates are generally found to increase with increasing
redox potentials, certain chemicals are degraded,
and some reactions (e.g., dechlorination) are en-
hanced, at lower redox potentials.
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Nutrients-
• Nutrients may or may not be limiting depending
on the availability of readily available carbon-
aceous substrates. Nitrogen and/or phosphorous
are often implicated in inhibiting biodegradation
by being in limited amounts. When either nitrogen
or phosphorous is provided in excess, biodegradation
may be limited by the amount of the other nutrient.
• Increased microbial activities associated with
nutrient rich soils may lead to misleading inter-
pretations of the effects of nitrogen and phos-
phorous on biodegradation.
• Organic cosubstrate enrichment may inhibit or stimu-
late the biodegradation of xenobiotics.
Toxins /Inhibitors--
• Very little systematic work has been conducted on
the effects of inorganic and organic toxins on bio-
degradation rates. Contradictory evidence indicates
that certain concentrations of a given substance
may be inhibitory to biodegradative processes,
though higher concentrations are reported to be
harmless to such activities.
• Considerable literature is available which describes
the inhibitory, synergistic, and antagonistic effects
of heavy metals, inorganic ions, and organics on
microbial activities in biological treatment processes.
Such data may be of limited value in the prediction
of general trends in biodegradation rates.
Water Availability--
• Water availability in the aqueous environment is
usually measured in terms of water activity, osmotic
pressure, ionic strength, or salinity. Water activity
has been used in most studies to evaluate the effects
of water availability on microbial growth. Quantitative
relationships indicating the effects of water avail-
ability on biodegradation rates have not been found
in the literature.
• In non-aqueous environments, water availability
is usually measured in terms of percent moisture
content or field capacity. Most studies have shown
that when the water content was within a certain
range, biodegradation rates increased with increasing
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water content. However, when the water content was
too high, biodegradation rates either decreased or
remained unchanged.
Biological Environmental Variables
Microbial Interactions--
• Interactions among microbiological populations
can have significant impact on chemical biodegrada-
tion. Basic types of interactions include mutualism,
commensalism, amensalism, predator-prey relationships,
and competition. Mutual and commensal interactions
may provide complete degradation of a subject chemical
and its metabolic products.
Adaptation--
• The phenomenon of adaptation, whereby organisms
acquire new physiological or morphological traits
which enable them to operate under a new set of
environmental conditions, has considerable ecologi-
cal significance. Recent studies show that the
ability of organisms to adapt to a new substrate
or environmental condition depends on the presence
of specific microorganisms.
Biodegradation Algorithms
• A complete generic algorithm(s) which includes the
relationships between biodegradation rates and
various environmental variables is still lacking.
• Basic biodegradation algorithms (i.e., algorithms
only addressing the rate of disappearance of a
growth substrate as a function of substrate concen-
tration) are usually based on one of two basic
approaches: decay or enzymatic reactions. The
latter is believed to be superior to the former
for the quantitative expression of biodegradation
rates.
• Very few. algorithms have been derived for express-
ing the effects of environmental variables on bio-
degradation rates. Variables that have been most
extensively studied for algorithm development in-
clude temperature, substrate inhibition and moisture
content. Algorithms for other variables are either
impractical or do not exist at the present time. Due
to the complexity of environmental factors affecting
biodegradation rates, it is unlikely that useful
mathematical expressions relating dynamic
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interactions in these factors to biodegradation rates
will become available in the near future.
RECOMMENDATIONS
Review of the literature revealed that little systematic
work has been performed in many areas relevant to the effects of
environmental variables on biodegradation rates. Subject areas
which warrant further study are summarized in the following
discussion.
• The literature describing attempts to establish
relationships between certain environmental factors
and biodegradation rates often neglect to report
the state of other significant environmental factors
during experimentation. Future efforts to develop
relationships and algorithms in this area would be
aided greatly by adequate description of all the
significant variables in the experiments.
• Most ‘studies on the relationships between environ-
mental variables and biodegradation rates emphasized
the descriptions of results’rather than causes.
In order to have fruitful understanding in this
area, studies attempting to determine the causes
of the effects of variables should also be conducted.
• The co-effects of environmental variables were
usually neglected in the biodegradation studies
reviewed. For example, the effects of pH on bio-
degradation may be significantly influenced by Eh.
Soils of different organic matter contents may
affect the biodegradation rate differently at
similar pH levels. The mobility of chemicals that
may be toxic to microorganisms is affected by pH
and Eh. Pressure effects may be greatly influenced
by temperature, D.O., and metabolic products. The
effects of sorption may be affected by pH, Eh, the
type and distribution of adsorbent (medium) , etc.
Such co-effects should be considered in any bio—
deqradation studies.
• The literature search revealed that quantitative
data on the effects of the following variables
on biodegradation rates are greatly lacking and
require future research: diffusion of xenobiotics
in the natural environment; light intensity; aerboic/
anaerobic conditions in terms of different redox
(or D.O./dissolved sulfide) levels; inhibitors!
toxins; water availability in the aqueous environ-
ment; and biological variables.
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• If generic algorithms describing effects of environ-
mental variables on biodegradation rates are to be
derived, controlled environmental conditions and
more experiments to cover wide varieties of chemicals
and environmental variables are urgently needed.
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SECTION 3
PHYSICAL ENVIRONMENTAL VARIABLES
OVERVIEW
The biodegradation of chemicals by microorganisms in terres-
trial and aquatic environments may be affected by a multitude of
physical environmental variables. The purpose of this section is
to identify and characterize those physcial environmental vari-
ables that significantly affect biodegradation rates and processes.
The significant factors to be discussed include: (1) temperature;
(2) concentration; (3) sorption; (4) hydrostatic pressure; and (5)
light.
Biodegradation of chemicals involves complicated enzyme—
catalyzed reactions which need heat or thermal energy to proceed
(Farrell et al., 1967; Rose, 1976; and Welker, 1976). Within the
physiologically tolerated range of temperature, biodegradation
rates increase as the temperature increases. The “Van’t Hoff Rule”
or “Arrhenius Equation” are frequently used to express such rela-
tionships. However, when temperatures are higher or lower than
the optimum temperatures for growth, biodegradation rates are
reduced. The literature review also revealed that temperature
can indirectly affect biodegradation rates through changes in
the lag period and in biodegradation pathways.
Several physical variables, such as dilution, mixing, and
diffusion, are found to affect the concentration or opportunity
for contact between organisms and substrates, and, therefore,
influence biodegradation rates of chemicals. In general, a posi-
tive correlation between the concentration of substrates and their
biodegradation rates is found. However, little or no biodegrad-
ation may occur for certain substrates at very low concentrations,
and a threshold may exist below which no significant biodegrad-
ation occurs. On the other hand, when substrate concentrations
are higher than certain inhibitory levels, biodegradation rates
can be greatly reduced.
Sorption also plays an important role in controlling rates
of biodegradation. Sorption of organic compounds to organic
and mineral components of the soil can act to enhance or inhibit
biodegradation, depending on site-specific factors and the com-
pound of interest. Most studies, as shown in the following
pages, have found that clay minerals with high cation exchange
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capacities can enhance biodegradation rates. Chemicals may be
protected from biodegradation once bound to the inner lattice
of clay minerals (e.g., montmorillonite), or when strongly bound
to humic substances. In aqueous environments, enhanced bio-
degradation through adsorption effects have been reported.
Large numbers of microorganisms live below the surface of
water masses, where hydrostatic pressure may be much higher than
one atmosphere. Evidence shows that pressure affects biodegrada-
tion in many ways. Biodegradation rates can be increased or
reduced by high pressure, depending on the co-effects of tempera-
ture and pressure. High pressure can also result in an extended
lag period, enzyme denaturation, biosynthetic pathway changes,
reduction in the pH range for growth, and loss of potassium from
the cells.
Light can enhance or inhibit the biodegradation of chemicals
depending on the specific conditions and microorganisms involved.
Ultraviolet light acts to inhibit biodegradation because of its
lethal and mutagenic effects. Visible light can also be lethal
or mutagenic to those species which are without protective carot—
enoid pigments. Light can be used by photosynthetic bacteria to
degrade low molecular weight organic compounds. Evidence suggests
that certain light intensities may inhibit substrate utilization
by bacteria; though few data are available on this subject.
TEMPERATURE
Biodegradation of chemicals involves complicated enzyme-
catalyzed biochemical reactions, and in order for these reactions
to proceed at a satisfactory rate, the organism needs to be
supplied with heat or thermal energy (Farrell etal., 1967; Rose,
1976; and Welker, 1976). A small fraction of the heat require-
ment of living organisms comes from the organism itself. However,
the main source of heat is the environment (Farrell et al., 1967).
Because of this environmental heat dependency, temperature is
one of the most important environmental variables affecting
the biodegradation of chemicals.
Review of the scientific literature on biodegradation studies
revealed that temperature can affect biodegradation in the follow-
ing ways: -
• Within the physiologically tolerated ranqe of
temperature, biodegradatjonrates increase as
the temperature increases;
• When temperatures are higher than or lower than
the optimum temperatures for growth, biodegradation
rates are reduced as the temperature is raised or
lowered.
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• Temperature can affect the lag time prior to biode-
gradative activity, and therefore, change the overall
time requirement for biodegradation; and
• Temperature can affect biodegradation pathways, and
therefore, change the rates and products of parent
chemical degradation.
Effect of Temperature Within The Physiologically Tolerated Range
Forward (1960) stated that as early as 1864 an empirical
quantification had been attempted by De Fauconpret to correlate
biochemical reactions with temperature within the temperature lim-
its of growth. The correlation revealed that biochemical reactions
were similar to chemical reactions; that is, reaction rate in-
creases as temperature increases. Later, a quantitative relation-
ship was established by Van’t Hoff as the well-known “Van’t Hoff
Rule”. Van’t Hoff suggested that rates of bioactivity increase by
a factor of 2 to 3 when temperature increases by 10°C. This ratio
is called the “temperature coefficient”, or “Q 10 value”, as ex-
pressed by the following equation:
010 = kt+ 10 = 2 to 3 (1)
where k is the reaction rate constant and t is the temperature in
°C. Based on this relationship, the Q 10 value can be calculated
for any temperature interval (t 2 -t 1 ):
log 10 = _ t log (2)
A generalized, and more complicated, expression quantifying
the effects of temperature on biological systems within the tem-
perature limits of growth was suggested by Arrhenius:
k = Ae ’RT (3)
where k is the reaction rate, E is activation energy, R is the
gas constant, and T is absolute temperature. Biologists frequent-
ly substitute the symbol p for E, and call p the “temperature
characteristic” (Forward, 1960).
Although the concepts of Van’t Hoff’s Rule and the Arrhenius’
equation have been used extensively to exptess the temperature
dependence of microbiological activities, especially the growth
of microorganisms, only a few studies have applied such concepts
to biodegradation of chemicals. In the following, examples of
such studies are presented.
In a study concerning the biodegradation of glucose, acetate,
and formate in agar, Ingraham et al. (1959) ound that the
values range from 2.4 to 3.6 for mesophiles, and from 1.5 to
*
t4esophiles: Microorganisms that grow at temperatures between
20 and 50°C, with optimal growth between 35 and 42°C (Welker, 1976).
11
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2.2 for psychrophiles. Tiedje (1977) reported that the Q 10 value
for the biodegradation of EDTA was approximately 2. Howard et al.
(1979) , in their study of the biodegradation of tree and shrub
litter in soil, found that the mean 10 values ranged from 2.3
to 2.6. Heiweg (1981) showed that for the biodegradation of
maleic hydrazide in soils at from 1 to 30°C, the average Q 1 value
was about 3.1. Toerien et al. (1982) found that for glucose in
lake sediments at 10 to 36°C, the Q 10 values ranged from 1.5 to
1.6 and 2.4 to 2.5 for two types of sediment.
Most biodegradation studies have not derived Q 1 values.
Table 1 was prepared from various reports for which values
could be calculated. In some cases Q 1 values had to e estimated
because the essential experimental congitions were unknown or in-
completely described. The calculated results (Table 1) show that
010 values for biodegradation of chemicals mostly fell in the
range of 1.0 to 5.0. By examination of the Q values, several
trends in the temperature effects can be iden fied:
• Higher 0 values were found for mesophiles than psychro-
philes, ich suggests that the former microorganisms
may be more strongly affected by temperature changes
(data ’of Ingraham et al. , 1959);
• Biodegradation of chemicals in relatively dry soils
may be more drastically affected by temperature changes
in comparison to that of wet soils (results of Yaron
et al. (1974); and
• Higher temperatures (especially higher than room
temperature) usually showed lower Q 10 values when
compared to that of lower temperatures (Rose, 1976;
Ward et al., 1976; Cserhatj et al., 1977; and Helweg,
1979)
Attempts were made in some biodegradation studies to identify
the applicability of the Arrhenius equation for quantitating tem-
perature effects. A plot of log k against l/T was generally used
to study the suitability of the equation or the applicable tem-
perature range of the equation. A straight line relationship
of the log k against l/T indicates an applicable situation, and
the slope is equal to —E/2.303R (calculated from Equation (3)).
Walker (1974), in his study of napropamide biodegradation in soil,
found that in both laboratory and field conditions, biodegradation
followed the Arrhenius equation, with activation energies (or
temperature characteristics) of 7.80 and 7.85 kcal/mole for 7.5
and 10% soil moisture content, respectively. A linear plot was
also observed for the biodegradation of linuron in soil in the
temperature range of 10 to 26°C, with an activation energy of
13. 3 kcal/mole (Cserhati et al., 1977). Helweg (1979) found
*
Psychrophiles: Microorganisms that grow optimally at tempera-
tures below 20°C (Welker, 1976; Morita, 1976).
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*
TABLE 1. TEMPERATURE COEFFICIENTS OF BIODEGRADATION
cultured for 60 days
U) fresh Sweden crude oil;
1% concentration;
summer seawater
(ii) fresh Sweden crude oil;
1% concentration:
winter seawater.
iii) weathered Sweden crude
oil; 0.7% concentration
winter seawater.
(J -)
Chonitcals
Medium
Temperature
Range
Studied (*C
Other
Environmental
Conditions
Temperatura Coefficient (0
t i i t
0 lb 20 30 40 SOC
Reference
Glucose
Nutrient agar
and trypticase
aoy agar
10 to 30
(i) Meaophiles:
Escherichia coil
Pseudomonas aeruginosa
(ii) Psychrophiies:
Pseudomonas perolens
Pseudomonas
+
—3.0 to 3.4—
—2.4 to 3.6—
—1.5 to 1.9—.-
—1.7 to 2.2—
Ingraham
et al.
fl959)
Acetate
Nutrient agar
and trypticase
soy egar
10 to 30
(1) Mesophile:
Eacherichia coil
(Ii) Paychrophile:
Pseudomonas
—2.8
—1.9
Ingrah em
et el.
(1959)
Formate
Nutrient agar
and trypticase
soy agar
10 to 30
Ii) Mesophile:
Pseudomonas aeruainosa
(ii) Psychrophile:
Pseudomonas perolens
—3.2
—2.0
Ingraham
et al.
U19 9)
Petroleum Seawater 5 to 20
- 2.2—
• 1. ] — . -
- 1.3 - . -
At] as
et a!.
(l972 )
(Continued)
-------
TABLE 1. (Contiiued)
Chemicals
Medium
Temperature
Range
Studied (°C
Other
Environmental
Conditions
Temperature Coefficient (Q )
flefca-encc
, , , -i
0 10 20 30 40
Bunker C oil
Inorganic
liquid medium
5 to 28
Mixed microbial cultures;
0.125% concentration
3.5 - (Pange: 1.6 to
e.o
Medium: 3.5)
Mulkins—
Philips
et al.
(1 9 -;I)
Azinphosmethyl
(oeaticide)
Soil
6 to 40
Ci) Dry soil (3% moisture
content)
ii) Wet soil (50% moisture
content)
— 2.8—.-
—1.2
Yaron
et al.
fl974)
Napropamjde
(herbicide)
Soil
14 to 28
(i) 10% moisture content
ii) 7.5% moisture content
—1.5---—
.____l.A__
Walker
(1914)
Glucose
Glucose—basal
salts broth
5 to 30
15 to-45
OrganismS
Pseudomonas fluorescens
Organism:
—1.7 ———2.1----
Lynch
et a),
1197 )
Rooc
E. eoli
—4.2—--- —1.04-—
(1976)
Mineral oil Lake 4 to 37 U) Summer water sample —2 1.—-.— 1.1— Ward
water (ii) Fall water sample —2.9-——— 1.5—
iii) Winter water sample —2.8- - - .— 1.6— (1976)
(Continued)
-------
TASLE 1. (Continued)
U i
Chemicals
Medium
Temperature
Range
Studied (°C
Other
Environmental
Conditions
Temperature Coefficient
Reference
(Ofl )
p I
0 10 20 30 40 50C
Hexadecane
Lake
water
4 to 37
(i) Swnmer water sample
(ii) Fall water sample
iii) Winter water sample
-—i.9—— —-- -1.6-—
-1.5—-—3.7 - —
—2.8—. .—--l.l- —
Ward
et al
(l97 )
Lii,uron
Soil
10 to 37
— ———
2.1 --.-0.9--...
Caerhatj
et ci. (1977)
Tree and
Shrub litters
Soil
---
Field testing
Oak. 2.50
Ash= 2.56
Hazel— 2.29
Hawthorn 2.31
(toward
et ci.
11979)
2-amino-
benzimjdazoie
1.2 ,3—tn-
chlorobenzene
Soil
1 to 40
Initial concentration
4 ppm.
-.---——5.0 - —1.0—0.2 . -
Ilelweg
(1979)
Soil
12 to 28
Initial concentration
50 ppm.
1.0—2.0.-
Marinucci
(1979)
N-ch loro-
alanine
queoua
19 to 35
Initial con entration
7.1 x 10 DM to
7.1 x l0 2 M alanine
—4.6-——--—
Stanbro
et al.
11979)
0-chioro-
phenol
Sediment
0 to 20
pH 6.9
HoiFture content 95.5%
Oroanic matter = 24%
(dry wt.)
Initial concentration
100 ug/ml (slurry)
—1.75
Raker
et al.
Tt9 8
(Continued)
-------
Baker
et 81.
11980 a)
TABLE 1. (Continued)
I -a
0 i
Chemicals
Medium
Temperature
Range
Studied (C
Other
Environmental
Conditions
Temperature Coefficient (010)
i u i i i i u i
Reference
0 10 20 30 40 50C
m-ch loro-
phenol
Sediment
0 to 20
pH 6.9
Moisture content 95.5%
Organic matter 24%
(dry wt.)
Initial concentration
= 100 pg/mi (slurry)
—2.0 -
Baker
ai
- •
a
p-chlorooheno
Sediment
0 to 20
Same as above
.—l.5 -
Baker
et al.
T1980e)
2 4-dichloro—
phenol
Sediment
0 to 20
Same as above
- .-- -----1.5 -
Baker
(1980 a)
Pentachioro-
phenol
Sediment
0 to 20
Same as above
—i.o
Baker
et al
T198ö a)
P—chloropheno
Stream water
0 to 20
pH = 7.1
Initial concentration
100 pg/mi
—1.0 -
Baker
et al.
119 a)
2 • 4—dichioro—
phenol
Stream water 0 to 20
Seine as above
1
—2.4 -
(ConUnued)
-------
TABLE 1. (Concluded)
Values estimated from the results of cited references
+ Applicable temperature range for the indicated 010 value
-J
0
Chemicals
Medium
Temperature
Range
Studied ( 6 C
Other
Environmental
Conditions
Temperature Coefficient (Q )
Reference
V I ‘ i i , i i
0 10 20 30 40 50C
Maleic
hydrazide
Soils (3 types)
1 to 30
Moisture content air dry
to 2x field capacity.
• 3.1
Ilelweq
(1981)
Glucose
Lake sediment
10 to 36
(i) Sediment Il
(ii) Sediment 12
—1.5. ---—1.6- -
—2.5—--—2.4—
Toerien
et al.
11982)
-r—
-------
that the degradation of 2—aminobenzimidazole (2-AB) in soil was
in accordance with the Arrhenius equation within the temperature
interval of 1 to 20°C (Figure 1). Maximum biodegradation of 2-AB
was at 22°C, while between 25 and 35°C, the biodegradation re-
mained almost constant, and at 40°C it was almost nil (Figure 1)
Larson (1979) showed that the biodegradation of NTA and alkyl—
benzene sulfonate (LAS) could also be described by the Arrhenius
equation (Figure 2), with calculated activation energies of 14.5
and 9.1 kcal/mole for NTA and LAS, respectively. Maleic hydra-
zide biodegradation in soil also displayed a linear curve within
the range of 1 to 30°C, with an activation energy of about 18.6
kcal/mole (Heiweg, 1981). A recent study conducted by Toerien
et al. (1982) showed glucose biodegradation in sediments with
activation energies in the range of 7.6 to 15.3 kcal/mole. The
calculated results of activation energies from other biodegrad-
ation studies are shown in Table 2.
As illustrated in Table 2, the activation energies for bio-
degradation of chemicals are in the range of 3 to 40 kcal/mole,
with the majority in the range of 10 to 20 kcal/mole. It is
indicated that temperature effects on biodegradation are more
pronounced for chemicals having higher activation energies.
Effects of Temperature Outside t1 ie Physiologically Tolerated
Range
Reduction in biodegradation rates can be found when the
growth temperatures are higher than, or lower than, the optimum
temperature range for growth (Forward, 1960; Farrell et al., 1967;
Welker, 1976; Rose, 1976). In petroleum biodegradation tests,
Ludzack et al. (1956) found that biodegradation of medium grade
motor oil was not measurable at 4°C, but that 20 to 30%, 30
to 50%, and 50 to 80% per week was biodegraded at 10, 20, and
25°C, respectively. ZoBell (1969) reported that the maximum
rates of crude oil biodegradation occurred between 25 and 37°C,
and below 10°C the biodegradation rate was markedly reduced.
Atlas et al. (l972a) also found that at low temperatures bio
degradation rates were significantly lower. Figure 3 shows
that when the temperature was reduced to 5°C, the biodegradation
rate of fresh crude oil in seawater collected in late summer was
negligible. Mulkins-Phillips et al. (1974) also reported that
low temperature resulted in a reduced biodegradation rate for
Bunker C fuel oil. At 15°C, 41 to 85% of Bunker C disappeared
after 7 days, but at 5°C, only about 21 to 52% disappeared after
14 days of incubation. Similar trends of low temperature effects
were also observed by Ward et al. (1976) for hexadecane and min-
eral oil biodegradation. Figure 4 shows that when temperatures
were lower than the optimum range (20 to 25°C) biodegradation
rates were greatly reduced.
At high temperatures (higher than the optimum temperature),
18
-------
TEMPERATURE (°C)
C.)
.-1
0
U
C l )
U
0
z
0
I -I
0
111
0
0.0036 0.0035 0.0034 0.0033
0.0032 1/°K
16
5.4
10.5
19.6
4
22
29.7
0
V
1
V
0
V
0
—p
V
0
I
V
0
—
TOTAL
INCUBATION
TIME (days )
8
15
22
30
36
I
V
I
0
V
I
II
0.2
0.
V
V
V
V
-V
V
U
0
V
V
Figure 1.
Arrhenius plots for biodegradation of 2-AB (Helweg, 1979)
-------
.40
.30
.10
-.10
-.30
-.50
-
0
-J
-1.10
-1.30
-1.50
Figure 2.
3 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4
1/(T + 273) x 10
Arrhenius plots for biodeqradation of NTA and LAS
(Larson, 1979).
20
-------
TABLE 2. ACTIVATION ENERGIES FOR BIODEGRJWATION
F.J
H
Chemicals
Medium
Environmental Conditions/
Microorganisms
Lin ar
ture
Tempera-
Range (°C)
Activation Energy
(Kcal/mole) Reference
Malate
Nutrient
agar and
trypticase
soy agar
(i)
(ii)
Psychrophile:
Pseudomonas p.
(Temperature tested:
5 to 35°C)
Mesophile:
Escherichia culi
(Temperature tested
5 to 35°C)
< S
< 5
to
to
25
25
11.2
11.4
Ingraham
(1959)
(i)
Psychrophile:
< 3
to
> 35
11.4
Ingraharn
Isocitric
Nu1rjent
Acid
agar and
trypticase
soy agar
(ii)
Pseudomonas sp.
(Temperature tested:
3 to 35°C)
Mesophile:
Escherichia coli
(Temperature tested:
3 to 35°C)
< 3
to
> 35
10.5
et
(1959)
(Continued)
-------
TABLE 2. (Continued)
Chemicals
Medi um
Environmental Conditions/
Microorganisms
Linear Tempera-
ture Range (°C)
Act .vatjon Energy
(Kcal/mole)
Reference
Glucose—
6—phos-
phate
Nutrient U)
agar and
trypticase
soy agar
(ii)
Psychrophile
Pseudomonas sp.
(Temperature tested:
5 to 40°C)
Mesophile:
Escherichia Coli
(Temperature tested:
5 to 40°C)
< 5 to
15 to
> 40
> 40
11.4
10.3
Ingraham
(1959)
Glucose
Glucose-
basal
salts broth
Pseudoiflonas
fluorescens
(Temperature tested:
3 to 33°C)
< 3 to
20
4,5
Pali irnbo
et al.
T1969)
Azinphos-
methyl
Soil
3% moisture content
(Temperature tested:
6 to 40°C)
--—
14.4
Yaron
et al.
(1974)
(Continued)
-------
TABLE 2 (Continued)
Chemicals
Medium
Environmental Conditions/
Microorganisms
Linear Tempera-
ture Range (°C)
Activation Energy
(Kcal/mo le)
Rpference
Napropamide
Soil
(1) 10% moisture content
(Temperature tested:
14 to 28°C)
(ii) 7.5% moist-ure content
(Temperature tested:
14 to 28°C)
-——
--—
7.85
7.80
Glucose
Glucose-
basal
salts
broth
Pseudomonas fluorescens
(Temperature tested:
5 to 30°C)
5 — 70
2.9
Lynch
et al.
975)
Mineral
Winter
Temperature tested:
10 — > 37
14.0
Ward
Oil
lake
water
4 to 37°C
et al.
(1976)
Nitrite
——-
(i) pH = 6.5
(ii) pH = 7.3 (optimum)
(iii) pH = 8.5
———
(i) 14.0
(ii) 6.6
(iii) 39.6
Alexander
(1977)
Ammonium
-—-
(i) H = 6
(ii) pH = 7.5 (optimum)
(iii) pH = 8.5
—--
(i) 19.8
(ii) 16.0
(iii) 20.0
Alexander
(1977)
Linuron
Soil
Temperature tested:
10 to 37°C
10 — 26
13.3
Cserhati
et al.
fl9 fl)
EDTA
Soil
EDTA = 2.8 ppm
(Temperature tested:
10 — 50°C
10 30
15.5
Tiedje
(1977)
(Continued)
-------
TABLE 2 (Continued)
Chemicals Medium
Environmental Conditional
Microorganisms
Linear Tempera-
ture Range (°C)
Activation Energy
(Kcal/moie)
Reference
Benefin (i)
Ascalon
Temperature tested:
——-
(1)
11.0
Zimdah l
(ii)
soil
Weld
soil
15 — 30°C
(ii)
13.1
et al.
(1977)
Trifluralin (1)
Ascalon
soil
Temperature tested:
15 — 30°C
——-
(1)
16.5
Zimdahl
et al.
(ii)
Weld
soil
(ii)
14.9
(1977)
2,6-dinitro— (1)
Ascalon
Temperature tested:
---
(i)
11.9
Zlmdah l
N-(3—pentyl)
—c ,a,ci— (ii)
soil
Weld
15 — 30°C
(ii)
10.9
!.. i•
(1977)
trif luoro—p—
soil
toluidine
2-amino-
Soil
Initial concentration
1 -
20
19.7
Heiweg
benzimidazo le
4 ppm
Temperature tested:
1 to 40°C
(1979)
NTA
Surface
water
Temperature tested:
3 to 36°C
0 -
>
36
14.5
Larson
(1979)
LAS
Surface
water
Temperature tested:
3 to 36°C
0 —
>
36
9.1
Larson
(1979)
(Continued)
-------
TABLE 2 (Con luded)
I ’ ,
‘.1’
*
Estimated from the results of cited references
“<“ or “> indicates the linear temperature range may exceed the range as shown.
Chemicals
Medium
Environmental Conditions/
Microorganisms
Linear Tempera-
ture Range (°C)
Activation Energy
(Xcal/mole)
R fcrence
2,4—D
River
water
Temperature tested:
6 to 25°C
40.4
Nesbitt
et al.
TIgiTh
Maleic
hydrazide
Soils
Temperature tested:
1 to 30°C
18.6
Ileiweg
(1981)
Glucose
Lake
sediments
(i) Sediment l
(Temperature tested:
10 to 36 °C)
(ii) Sediment U
(Temperature tested:
10 to 36°C)
———
(i)
(ii)
7.6
15.3
Toerien
et al.
(1982)
H Data not provided or not tested by the cited references.
-------
80
(N
>< 60
U)
0
i 40
U
C .’
(N
0
20
0
53 60
TThIE (days)
Figure 3. Mineralization at various temperatures of 1% (v/v) fresh Sweden crude
oil in seawater collected in late summer (Atlas et al. , 1972a).
3 7 11 18 25 32 39 46
-------
8
6
S..-
0
2
4
4x] 0
4
z 2x10
H
U)
E-’
z
0
0
0
Figure 4 . Effect of temperature on (A) oxygen uptake during
mineral oil oxidation and (B) 14 C0, production
during hexadecane oxidation by Lake Mendota
surface water samples (Ward et al. , 1976).
0 100 200 300 400 500
HOURS
27
-------
reduction in biodegradation rates was also reported by many re-
searchers. Data as shown in Figure 4 indicate that at 37°C
rates of mineral oil and hexadecane biodegradation were greatly
depressed as compared to the optimum temperature range (20 to 25°C)
(Ward et al., 1976). Cserhati et a].. (1977) in their linuron bio-
degradation tests also observed a decline in biodegradation rates
when temperature increased from 26 to 37°C. In another typical
example, shown in Figure 1, biodegradation rates for 2-AB were
reduced when temperatures were higher than about 20°C (Heiweg, 1979).
The reduction of biodegradation rates as observed in the low
and high temperature regions can also be seen from the Arrhenius
plots. Figure 5 shows a typical Arrhenius plot for growth of P.
flourescens on glucose. In the high (higher than 30°C) and low
(lower than 5°C) temperature regions, the reduction of biodegrada-
tion rates can easily be observed. This effect is usually explained
by the denaturation of cell proteins in the high temperature region
and inhibition of enzyme activity in the low temperature region
(Forward, 1960; Rose, 1967; Farrell, 1967; Rose, 1976; Welker, 1976;
and Stanier et al., 1976).
Other Temperature Effects
Temperature also may indirectly affect biodegradation rates
through its effect on lag time and pathways of biodegradation.
Lag time is usually considered to be a reflection of the need for
acclimation of a degrading population, including enzymatic adapta-
tion to degrade the chemical. In recent studies, lag time was
found to be correlated with temperature. For example, Atlas et al.
(1972a) reported that low temperature could cause lag periods to
increase (see Figure 3 as shown previously). The lower the tempera-
ture, the longer the lag period. Such phenomena have also been
observed by other researchers, such as Mulkins-Phillips et al. (1974)
Yaron et a].. (1974), and Ward et al. (1976). Atlas et al. (1972a)
and Yaron et a].. (1974) further reported that such lag periods were
found to be directly proportional to temperature, as can be seen in
Figure 6.
Temperature effects on biodegradation pathways were reported
by Palurnbo et al. (1969) and Lynch et al. (1975). Such effects
were believed to indirectly affect the biodegradation rates of the
parent chemical. Lynch et al. (1975) reported that at low growth
temperatures (0 to 5°C), 2-ketogluconate (2—KG) was the major
biodegradation product from glucose (up to 70%). When the growth
temperature raised to 20°C, only 25% of glucose was recovered as
2-KG. At the optimum temperature (30°C) or above, no 2-KG was
detected at any time during the tests. Lynch et al. (1975)
suggested that at low temperature, the major route for biodegrada-
tion of glucose was the direct oxidative non-phosphorylated pathway.
Other indirect temperature effects on biodegradation rates,
such as effects on limiting biodegradation concentration, effects
28
-------
0
(9
C-)
H
H
C -)
oc
40 30 20 10
0
064
032
016
008
004
002
Figure 5. Arrhenius plot oE the specific growth rate of P.
fluorescenS on glucose (Lynch et al. , 1975) . —
1/°K x
29
-------
U I
REFERENCE: ATLAS
et al. (1972a)
CHEMICAL: SWEDEN
CRUDE OIL
MEDIUM: SEAWATER
1 I
20 25
LAG PERIOD (days)
Fiqure 6.
The effects of temperature on the “lag period”
for biodeqradation.
20
15 -
10 -
5
40
.
0
0
z
o 30
0
0 5 10 15
LAG PERIOD (days)
z
20
10
0
0
10 20 30 40 50
30
-------
on acclimation of organisms in different media, effects on other
essential environmental factors such as pH, chemical speciation,
etc. were also suggested in the literature. But quantitative
evaluations are still lacking. Temperature is one of the difficult
factors to evaluate as a determinant of biodegradation rates of
chemicals because of its association with the kinetics of all
physical and chemical reactions. There are possible a myriad of
indirect effects of temperature on biodegradation. It does not
seem to be fruitful with the present state of knowledge to attempt
precise correlation of temperature with biodegradation under a
multitude of environmental conditions.
CONCENTRATION
Effects of chemical concentration on biodegradation rates
have long been known to microbiologists. The first work describ-
ing such relationships in a mathematic model was performed by
Michaelis and Menten, as early as 1913, in their enzyme reaction
study (Michaelis et al. , 1913). The concentration factor can be
affected by physical mechanisms such as mixing, diffusion, dilu—
tion, and other physical-chemical factors affecting the mobility
of the chemical (e.g., sorption, complexation, solubilization,
etc.). In this subsection, only those factors deemed physical
in nature will be discussed. Since concentration is the direct
factor affecting biodegradation, the concentration effects will
be discussed before the description of the physical variables
influencing concentration.
Effects of Concentration
It is generally true that the biodegradation rate (K) increases
as substrate concentration (S) increases. Such a relationship
holds until a certain maximum biodegradation rate (1< ) is reached,
as shown in Figure 7 (Sawyer et al., 1978; Sundstrom et al., 1979).
As illustrated in Figure 7, when S ‘> Km (where Km = the substrate
concentration at which the reaction rate is one—half of maximum)
the reaction rate is a maximum and independent of the substrate
concentration--the reaction is zero-order. When S << K , the
reaction rate becomes first—order with regard to concen ration.
In recent years, results of research have emphasized the
importance of chemical concentration, especially trace concen-
trations of xenobiotic chemicals, on biodegradation. DiGeronimo
et al. (1979) , in studying the effect of concentration of p-
chlorobenzoate, climethylarnine and 2,4—D on their biodegradation,
found that 2,4-D may be more persistent at very low than at higher
concentrations. They further pointed out that many organic
pollutants could persist in aquatic ecosystems owing in part to
their low prevailing concentration. In a study of the biodegrada-
tion of phenol in river water, Borighem et al. (1978) were able to
distinguish three different phases in the degradation curve (Figure
8): an induction period, a linear decrease in the phenol concen-
tration as a function of time, followed by a slow decrease to zero
31
-------
MAXIMUM RATE
WHERE K =
m
BIIThCOI IIOI
WHICH THE REACTION RATE IS
ONE-HALF OF MAXIMUM.
SUBSTRATE CONCENTRATION (S)
Figure 7.
The re1ation hip between substrate concentration
and substrate utilization rate.
K
0
K 0
2
z
0
H
H
H
F- i
F- i
U)
U,
32
-------
20
E
z 15
0
‘ -I
z
10
z
0
U
0
z
5
0
BIODEGRADATION TIME (hrs)
FIGURE 8. Biodegradation of phenol as a function of time and
concentration (Borighem et al., 1978).
0 150 300
33
-------
concentration. With increasing phenol concentration, the induc-
tion period and the time for complete degradation also increased.
Mason et al. (1979) found a positive correlation between the
concentrations of chemicals and their biodegradation rates. They
showed that the initial rate of demethylation of methylmercury
followed a first order relationship at each pH to a methylmercury
concentration of at least 2 mg/i.
The positive correlation between a chemical’s concentration
and its biodegradation rate is further verified by Boethling and
Alexander (1979a and 1979b). In their studies on biodegradation
rates of glucose, dimethylainine, diethylamine, diethariolainine,
p-chlorobenzoate, chioroacetate, 2,4-D, and l-naphthyl N-methyl-
carbamate at various concentrations, two important findings were
obtained for some of the chemicals studied:
(1) The biodegradation rate may be directly proportional
to chemical concentration at the trace level. A
decrease of approximately one order of magnitude in
biodegradation rate was observed for each successive
decrease in one order of magnitude in the initial
chemical concentration.
(2) Little or no biodegradation may occur at low chemical
concentrations, and a threshold would exist below which
no significant biodegradation occurs. The existence
of a threshold is not predicted by Michaelis-Menten
kinetics.
When the concentration of chemicals increases, according to the
Michaelis-Menten model (illustrated in Figure 7) , the biological
reaction rate approaches a maximum and thereafter exhibits no
correlation with concentration. However, many biological reactions
are susceptible to inhibitors which can affect biochemical activity
within the cell (Sundstrom et al., 1979). Sundstrom et al., (1979)
showed that whenever inhibition is present, the biodegradation rate
decreases. More discussion on substrate inhibition is provided in
Section 6, “Biodegradation Algorithms”.
From the above discussion, it can be concluded that:
• Biodegradation rates are positively correlated with
the substrate concentration when the concentration is
within a certain range;
• Little or no biodegradation may occur for certain sub-
strates at very low concentrations, and a threshold
may exist below which no significant biodegradation
occurs.
• When substrate concentrations are higher than the
range mentioned above, substrate inhibition effects
may cause a lowering of biodegradation rates.
34
-------
Physical Effects On Concentration
Physical effects can influence concentrations of chemicals
in many ways. Dilution (e.g., discharge of xenobiotics into a
strewn) could result in a reduction of chemical concentration and,
therefore, influence the biodegradation rate of that chemical.
Diffusion and dispersion may increase or decrease chemical con-
centration and, as a result, accelerate or hinder the biodegradation
process (Kozak et al., 1979; Gersti et al., 1979; and Parker, 1979).
Mixing may increase the opportunity for contact between micro-
organisms and chemicals (Lo et al., 1978), especially for the
biodegradation of chemicals having very low concentrations.
Dilution is especially important in the biodegradation of
chemicals in surface waters. Diffusion and dispersion effects on
biodegradation may occur in both soil and aqueous environments.
In marine environments, for example, diffusion of oil will greatly
enhance its biodegradation rate (Gerstie et al., 1979). Diffusion
of a substance in soil may also accelerate or hinder the bio-
degradation process. Kozak et al. (1979) reported that a material
may diffuse from one soil setting to another (such as clay), pro-
viding a more susceptible setting for degradation. Movement of the
substance into an air-water, air-soil, or water-soil interface,
where the-material is usually concentrated, desorbed or adsorbed
can also affect transformation rates (Parker, 1979).
Mixing usually improves the rate of biodegradation. Swilley
et al. (1964) investigated the influence of mixing on substrate
biodegradation and obtained a higher reaction rate under stirred
conditions. Theoretical studies on the effects of micromixing
and macromixing on microbial growth have been conducted by several
workers (e.g., Tsai et al., 1969; Fan et al., 1970 and 1971; Dohan
et al., 1973; and Lo et al., 1978). Their results can be summarized
as follows:
In the case of pure cultures of non-aggregatable micro-
organisms, good mixing can prevent individual cells from
settling and increase the frequency of contact of limit-
ing substrate with active sites of cells. In the case
of a pure culture consisting of dispersed and flocculated
microorganisms, the overall limiting substrate removal
rate would depend upon the distribution of dispersed and
flocculated microorganisms in the culture; thus, it should
be a function of degree of mixing because the flocculation—
deflocculation process was found experimentally to vary
with agitation rate when other environmental factors were
kept constant. The specific surface of a particle has
been defined as its surface area divided by its mass.
Thus, specific surface is larger for dispersed micro-
organisms, giving more active sites per unit of biomass.
As a rule, the larger the number of active sites per
unit of biomass, the greater will be the amount of
35
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limiting substrate removed. In the case of mixed culture
systems, where aggregatable and non-aggregatable micro-
organisms of different species exist, good or strong
mixing prevents both kinds of microorganisms from set-
tling and provides more contact between limiting substrate
and cells and flocs per unit time per unit of biomass.
Each species has its own particular shape and average
size and weight. Species of aggregatable microorganisms
flocculate or deflocculate under the influence of mixing
and other environmental factors. Consequently, the limit-
ing substrate removal rate for a given biomass concen-
tration in a mixed culture system should depend not only
on the degree of mixing but also on the aggregation
state and particle (cell and floc) size of different
species. When other controlling or limiting factors are
assumed to be constant, it can be reasoned from the above
discussions that the common factor to control removal
rate in the above mentioned three cases is the frequency
of contact of microorganisms with limiting substrate per
unit of biomass.
Literature search also revealed that in certain cases mixing
showed no effects on biodegradation rates. For example, Ward et
al. (1976) found that incubation of samples on a rotary shaker to
promote mixing did not influence the kinetics of hydrocarbon
biodegradation.
SORPT ION
Considerable research has been conducted regarding the effects
of bacterial and substrate sorption in influencing rates of bio-
degradation in various soils. Beyond terrestrial ecosystems,
however, biodegradation studies have generally not considered
the effects of sorption on biodegradation.
Sorption can be defined as both the taking up of one substance
at the surface of another (adsorption) and the penetration of one
substance into the body of another (absorption). Because it is
often difficult to distinguish between adsorption and absorption
processes, they are commonly grouped under a single heading—-
sorption..
Sorption can be viewed as both a physical and chemical phenom-
enon, involving both weak attractive forces (van der Waal’s forces)
and stronger ionic or molecular attraction. The availability of
organic substrates to soil microorganisms may be enhanced or re-
duced through sorption by particulate matter (Marshall, 1976). For
substrates that are sorbed, the availability will depend on the sub-
strate location relative to that of the degrading microorganisms, or
whether extracellular enzymes are involved and whether these are
sorbed, and on the configuration and arrangement of the substrates
and enzymes in the sorbed state. Some contradictory results have
36
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been reported on the metabolism of specific organic substrates in
different soils, but these probably reflect the complexity of
soils as microbial systems. Several significant studies are
mentioned in the following discussion.
The sorption of maleic hydrazide by clay and organic material
and its influence on substrate biodegradation was studied by Helweg
(1981). It was found that the rate pf decomposition of maleic
hydrazide, at varying temperatures and moisture content, was low-
est in soil with the highest content of organic matter and the
lowest clay content. Heiweg suggested that adsorption of maleic
hydrazide by organic matter reduced the biodegradation rate, but
that the clay content of soil may play an important role (i.e.,
the degradation rate may be higher in soil with a higher clay con-
tent). Evidence suggests that the metabolic products of the
biodegradation of certain pesticides can bind to soil huinic sub-
stances and increase the chances of their persistence (Katan et al.,
1976; Hsu et al., 1976). An assessment of the influence of sorption
by soil organic matter on herbicide stability was made by Hance
(1974). In contrast to the results of the above-mentioned studies,
it was found that the breakdown rates of atrazine and linuron were
not related to their extent of organic adsorption, rather that herb-
icide degradation occurred incidentally to the general metabolism of
organic material in the soil. Gibson and Burns (1977) also demon-
strated that colloidal organic matter itself, or the fraction
associated with it, is the most important single factor concerned
with the rapid breakdown of malathion in the soil studied. The
persistence of malathion in soil and soil fractions is illustrated
in Figure 9. The breakdown of malathion in nonsterile soil com-
ponents is contrasted with autoclaved fractions in which no break-
down occurred.
Soil clays appear to play an important role in influencing
biodegradation. Researchers including Stotzky (1966a and b) and
Stotzky and Rem (1966, 1967) reported that some clays (e.g.,
kaolinite) exerted little influence on bacterial respiration with
glucose as substrate, whereas other clays (e.g., montmorillonite)
stimulated respiration. Montmorillonite also stimulated microbial
degradation of aldehydes, but kaolinite did not (Kunc and Stotzky,
1970). Conversely, 4 C-diquat sorbed by kaolinite was readily
degraded by the soil microflora, while decomposition of the same
herbicide sorbed by montinorillonite was almost completely inhibited
(Weber and Coble, 1968). Specific sorption mechanisms influencing
bacterial respiration and substrate biodegradation, and mechanisms
controlling the degradation of sorbed chemicals, are described
below.
Evidence suggests that one mechanism by which clay minerals
stimulate bacterial respiration is by maintaining a pH suitable
for growth (Stotzky and Rem, 1966; Stotzky, l966a). This mechanism
is dependent on the initial pH of the system and the buffering
capacity of the particles. When the initial pH was sufficiently
high the bacterium was able to initiate and maintain growth until
the accumulation of acidic metabolites reduced the pH to an
37
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1
(A)
z
0
H
Figure 9.
1 2 3 4 5 6 7 9 10 12 14 16 18
TIME (days)
Malathion breakdc, .in in sedimented and centrifugeu soil fractions. • , all tour
autcclaved;•, clay; ,, silt;O, sand; A, or ano-rninera1 ca piex (Gibson anci k urns,i977).
-------
inhibitory level (Stotzky, 1966a). When the particle was also cap-
able of neutralizing these metabolites, thereby maintaining a pH
adequate for growth, the bacterium continued to metabolize until
the buffering capacity was exhausted.
The cation exchange capacity (CEC) of soil is also found to
be correlated with substrate decomposition rates. Novakova (1972a
and b) reported that montmorillonitic clays with saturating cations
Na and Ca stimulated glucose decomposition by a mixed soil micro-
organism culture, but that these forms of kaolinite were somewhat
inhibitory. Using samples of montmorillonite made homOionic to
a range of cations, Stotzky (1966a) reported rates of bacterial
respiration with saturating cations to be in the order Na>Ca>Mg>K>H.
This order reflects the relative basicity of the cations (except
for potassium) , ratl r than their ease of replacement from the
exchange complex, or the ability to displace other cations from
the complex.. The correlation of bacterial respiration and cation
exchange is illustrated in Figure 10. The establishment of cation
exchange capacity as a dominant factor in bacterial respiration is
consistent with aforementioned pH effects, presumably because clay
minerals w th high cation exchange capacity are capable of exchang-
ing more H ions produced during metabolism than those with a lower
cation exchange capacity, thus maintaining the requisite pH of the
ambient solution for a longer time (Stotzky, l966b). Although no
biodegradation rates were mentioned in the above discussion, due
to the close relationship between bacterial respiration and bio-
degradation, the similar effects of CEC on biodegradation also can
be expected.
Protection of a substrate from decomposition is often associa-
ted with sorption within the inner lattice of expanding lattice
clays. Weber and Coble (1968) demonstrated that the decomposition
rate of the cationic herbicide diquat was significantly reduced
when associated with montmorillonite clay, presumably because
sorption of the diquat in interlayer spaces rendered it inaccessible
to microorganisms. xaolinite clay, however, did not inhibit de-
gradation. Burns and Audus (1970) observed similar degradation
rate inhibition from montmorillonite for the herbicide paraquat.
Wszolek and Alexander (1979) found that an increased resistance
to microbial attack was provided to n-alkylainines sorbed to
montmorillonjte, and that higher resistance was found for amines
with higher molecular weights (Figure 11). The researchers also
concluded that t the rate of substrate desorption does not limit the
rate of biodegradation, and that microrganisms may facilitate re-
moval of substrate from clay surfaces by production of extracellular
enzymes.
The biodegradation of herbicides in soil has been described
using first order kinetics (Hamaker, 1972). Zimdahl and Gwynn
(1977) , in their degradation studies of herbicides, found that all
herbicides studied degraded more rapidly in loamy soil than in sandy
soil. They speculated that it may have been due to greater microbial
activity in the loamy soil. Loamy soil contains higher clay and
39
-------
200
160
120
B0
0
60
40
0.01 0.1 1
CATION EXCHANGE CAPACITY
10
(meg x 10 3 /3m1)
Figure 10. Effect of cation exchange capacity on respiration of Agrobacterium radiobacter
and Achrc*n bacter sp. (Stcz.ky, 1966b)
0
0.001
100
-------
72
48
H
‘24
80
40
Figure 11 . iJeçradation of bentonite-n-alkylamines and n-alkylarranes free in
an inorganic salts solution ( 1szolek and Alexander, 1979)
2 4
160
120
6 8
10
0
B
16
8
HOURS
16
41
-------
organic contents than sandy soil. Degradation that is catalyzed
by adsorption on clay or organic matter may be expressed by
(Zimdahl and Gwynn, 1977):
— d [ H ] = k [ H] [ clay] [ OM] (4)
where ‘ [ HJ and [ OM] represent the concentration of herbicide and
organic matter, respectively. Such a reaction would be third
order, but for a given medium the concentration of clay and organ-
ic matter remain constant and only the herbicide concentration is
time-dependent, the reaction appears to be first order.
Enzymes may play an important role in the biodegradation of
sorbed organic chemicals. Early work by McLaren (1963) showed
that proteolytic enzymes may be adsorbed on clay and hydrolyze
adsorbed proteins. Studies have shown that not only protein
adsorbed on the outside surfaces of clay particles but also
protein present in the interlayer space is utilized by micro-
organisms, suggesting that extracellular proteolytic enzymes have
access to the interlayer space (Estermann et al., 1959). Studies
have also shown that the types of clay involved in sorption can
have a drastic influence on enzyme activity: kaolinite clays
inhibited protease activity to a much greater extent than mont-
morillonite clays (Aomine et al., 1964). Interestingly, the
adsorption of enzymes has been reported to be as much as 100 times
greater (per unit weight) on montmorillonite than on kaolinite
(Haska, 1975), suggesting that the activity of sorbed enzymes may
be enhanced or inhibited as a result of selective adsorption.
Immobilized enzymes have, however, been observed to obey Michaelis-
Menten kinetics (Makboul et al., 1979). Attachment of such enzymes
to solid interfaces may affect their affinity towards the substrate.
Makboul et al. (1979) observed that at each substrate (p-nitrophenyl
phosphate, PNP) level tested, the addition of increasing amounts of
clay decreased the activity and increased the k values (the higher
the kmi the lower the affinity for a given subs rate, according to
Michaelis-Menten kinetics). The authors found that the affinity of
sorbed acid phosphatases for PNP was significantly lower with
montmorjllonite than with kaoljnite or illite.
It should be noted that a major limitation in evaluating the
results of the above-mentioned studies is that only one chemical
was applied to a soil at a time. Combinations or mixtures of
chemicals might be a common situation in nature. The behavior
of a chemical mixture may or may not be independent or additive,
but rather based upon the influence of one chemical and/or the
formulation associated with a given chemical.
In review, the availability of organic substrates to soil
microorganisms may be either enhanced or reduced when sorbed to
soil organics and minerals. Clay minerals with high cation ex-
change capacities can enhance biodegradation by maintaining the
suitable pH for growth. Evidence has indicated that chemicals
42
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may be protected from biodegradation once bound to the inner
lattice of clay soils (e.g., montn orillonite) or when strongly
bound to humic substances. Enzymes also play a significant role
in governing the biodegradation rates of sorbed chemicals. Be-
cause of conflicting evidence regarding effects of sorption on
biodegradation of organic substrates, and because of the hetero-
geneous and complex nature of soil systems, much more data are
needed to develop empirical relationships between the effects of
sorption and biodegradation.
HYDROSTATIC PRESSURE
Many microorganisms thrive and multiply in environments, such
as soils, that are at atmospheric pressure. But there are large
numbers of microorganisms living below the surface of a water mass
that are subjected to hydrostatic pressures greater than one atmo-
sphere. In the aqueous environments, pressure increases at a rate
of about one atm for every 10 m depth. Over half of the earth’s
surface is covered with water at depths of 3800 m or more, which
create 380 atm or more of hydrostatic pressure. The greatest
hydrostatic pressures known for the ocean floor and freshwater
lakes are about 1160 and 164 atm, respectively.
There is abundant evidence that biodegradation of chemicals
can occur on the ocean floor, in deep oil well brines, and in
other habitats characterized by high pressure (ZoBell et al. ,
1949; Rose, 1976; and Morita, 1976). No clear understanding,
however, has been reached concerning the effects of pressure on
biodegradation rates of chemicals.
In studies of the effects of pressure on terrestrial and
marine bacteria, ZoBell et al. (1949) concluded that at tempera-
tures below the normal optimum, a pressure of 500 atm greatly
retarded the biochemical reactions. This is because biodegradation
reactions proceed with a volume increase, but high pressure tends
to reduce the overall volume of the reactants and products, and,
therefore, results in a retardation of the reactions. At higher
temperatures, and most noticeably above the optimum, the critical
enzyme undergoes a reversible denaturation that proceeds with an
even larger increase in volume of reaction. At these temperatures,
the net effect of pressure is to increase the rate of the reaction
by reversing the denaturation of the enzyme to a greater extent
than the opposing catalytic reaction. Therefore, ZoBell et al.
(1949) suggested that the effects of pressure are likely, in all
cases, to depend upon temperature, and a complete picture is
obtainable only after exhaustive studies of the reciprocal relation-
ships of both factors. The above-mentioned temperature-pressure
relationship was also reported by Brown et al. (1942) , Strehier
et al. (1954) , and ZoBell (1970).
These authors suggested that increased hydrostatic pressure
may exert an effect on the cells, raising the minimal growth
temperature. They hypothesized that in an environment of low
temperature, an increasing pressure will eliminate growth
43
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and biochemical activity of bacteria, as their minimal growth
temperature are shifted toward, and ultimately surpass, the
environmental temperature.
A more complete description of the co-effects of temperature
and pressure on biodegradation was reported by Morita (1976).
When the temperature was kept constant for psychrophiles, the
pressure increase could result in a decrease in the biodegradation
rate. However, when the pressure was kept constant, a temperature
increase could enhance the biodegradation rate. These relation-
ships are shown in Figure 12. As shown by this figure, in order
to maintain the same rate of substrate uptake, an increase in
hydrostatic pressure should be accompanied by an increase in
temperature.
Morita (1957), in a study of the inactivation of various
dehydrogenases of the tricarboxylic acid (TCA) cycle, reported
that increased hydrostatic pressures had a marked effect on the
biodegradation of formate, malate, and succinate as compared to
one atmosphere as follows:
Percent Degraded (%)
Pressure (atm) Formate Malate Succinate
1 100 100 100
200 97 98 88
600 81 74 52
1,000 21 13 9
However, he indicated that, although the dehydrogenase systems
were inactivated by hydrostatic pressure, such pressure effects
appear to have little or no effect on the absolute biochemical
reaction rates.
Jannasch et al. (1971) reported that the rates of organic
matter (e.g., acetate, mannitol, sodium glutamate, casamino
acids, starch, galactose, peptone, and albumin) degradation were
10 to 100 times slower in the deep sea (1540 m) when compared to
controls at comparable temperatures but atmospheric pressure.
In another study, Jannasch et al. (1973) reported that the in
situ (in the deep sea at depth 1830 m) biodegradation rates of
various organic substrates (e.g., starch, agar, gelatine, bond
paper, paper towels, balsa wood, beech wood) were between one
to three orders of magnitude lower than in the controls (4°C,
performed in the laboratory). These authors reported that the
response of deep-sea microbial populations was similar to that
of surface-water populations incubated in the deep sea or in the
laboratory. They further indicated that successive compression
and decompression of marine bacteria during testing had little
or no effect on the viability of the bacteria. The low rate of
microbial activity also can not be explained by too small an
inoculum or possible effects of oxygen tension. They suggested
that the slow biodegradation rates of organics in the deep-sea
44
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-l
x
I -c
“-I
‘ c i
F ’
F’
C.)
0
[ -4
F’
30
25
20
15
10
5
15
10
5
0
0 100
Fiqure 12.
200 300 400 2 500 600 700
PRESSURE (atm) x 10
(A) Uptake rate of [ U C] qiutamic acid by
psychrophile Ant-300 at various temperatures
(B) Constant uptake isopleth for [ U 4 C] alutamic acid
by Ant-300 prepared from the above Figure (A) (Morita, 1976).
the antarctic
and pressures.
PRESSURE (atm)
F J I I I I I
B
— —
— -
I I I p
I
45
-------
environment could be the result of a relative retardation of
certain critical metabolic processes.
It has been suggested in the literature that some of the
organisms may increase their activities at elevated pressure
compared to that of one atm pressure (ZoBell et al., 1949; Morita,
1976). Wirsen et al. (1976), in their studies of the degradation
of various solid organic materials (e.g., seaweed, wood, paper,
chitin, fish meta, foodstuffs) in the deep sea at depths of 1830-
5300 m for up to 15 months, did not observe a “barophilic” response.
In a comprehensive literature review, ZoBell (1970) also concluded
that the growth of virtually all microbial species examined has
been found to be retarded or completely inhibited by pressures
50 to 500 atm higher than those normally encountered. This
generalization applies to barophilic as well as to barophobic
species, both marine and terrestrial organisms (ZoBell, 1970)
Besides the pressure inhibition effects discussed above,
hydrostatic pressure was also reported to affect biodegradation
lag periods (Rose, 1976). These lag periods may indirectly
affect biodegradation rates because of the overall time require-
ment for biodegradation. Schwarz et al. (1975) demonstrated in
laboratory experiments that Pseudomonas bathycetes , an organism
isolated from the Challenger Deep, had an extremely long lag
period for growth of approximately four months at 1000 atm and 3°C.
Hydrostatic pressure was also found to cause a marked
narrowing of pH ranges for growth and a reduction in growth
yield for a variety of bacteria. Although the direct relation-
ships between pressure and biodegradation were not measured, as
discussed in Section 7 “Biodegradation Algorithms”, a positive
relationship between biodegradation rate and growth has been
found. Examples of the pressure effect on pH ranges for growth
are shown in Figure 13 (Matsumura et al., 1974). As can be seen
from the figure, for each bacterium, p 1-1 ranges for growth were
progressively narrowed with increasing pressure, and growth yields
were also progressively reduced. The authors suggested that the
reduced yields under pressure could be directly related to in-
creased sensitivities to metabolic acids that accumulated in the
system. The increased sensitivity to low pH of bacterial growth
under pressure could be partially reversed with magnesium and
calcium ions.
Other pressure effects that could indirectly influence bio-
degradation include changes in the biodegradation pathways (Rose,
1976), an increase in the loss of potassium from the cells under
high hydrostatic pressure (Matsuxnura et al., 1974), and denatura-
tion of enzymes by moderate (100 to 500 atm) to high hydrostatic
pressures (Rose, 1976; and Morita, 1976). However, as mentioned
by Rose (1976), there is little likelihood of a clearer under-
standing of the effects of hydrostatic pressure on microbes emerg-
ing in the near future, mainly because of a wide variety of factors
46
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10
0 o
o08 o
r . .
0.6
0.4
0.2
003
Acholoplasma
!aidlawui JA1
0.15 (0
0.12
0
g 0.09
0.06
003
0.006
Figure 13. pH ranges for growth of (a) E. coli , (b) S. marinorubra ,
(c) B. thalassokoites , (d) marine coccus Yl, (e) S.
aureus , and (f) A. laidlawjj . Incubation times and
temperatures were: 24 hr at 24°C for E. coli and S.
marinorubra , 24 hr at 30°C for B. thalassokoites ,
48 hr at 24°C for marine coccus Yl, 49 hr at 30°C for
S.aureus , and 48 hr at 30°C for A. laidawii . A is
absorbance at 700 pj (MatsUBlUraet al., 1974) ;70D
E he! I! 111 ! coli B
(,))
1 ATM
‘/ T \
‘ 0 TM
:4 5 6 7 99
Initial pH
10 Ii
Initial pH
OlE
Initial pH
1 ATM
136 ATM
47
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associated with pressure (e.g., temperature, biochemcial reaction
rates, solubilities of substrate and gases, etc.) and the diffi-
culties encountered in carrying out experiments on these effects.
LIGHT
Unlike many environmental factors, light can directly affect
organic substrates: certain recalcitrant xenobiotics can be
chemically transformed by light into forms more usable by micro-
organisms. Some organisms are receptive to light and its effects;
e.g., by using light as an energy source, through damage to cellu-
lar structures caused by light, by movements in response to light,
etc. Before exploring light and its potential effects on biode-
grading microorganisms, a short review of the forms of light, or
radiation, is in order.
Radiation is generally classified according to its wavelength.
Most radiation reaching the earth is in the near ultraviolet (UV),
visible, or infrared (IR) regions of the spectrum illustrated
below.
Wavelength (nm)
______________________A_____________________
I
Visible
Radiation
Ultraviolet radiation (10-300 run) is important in biodegrada-
tive processes largely because of its potential lethal or mutagenic
effects Lupon organisms. Vegetative microbes are varied in their
response to ultraviolet radiation. Rose (1976) reports that the
dose of DV radiation needed to 2 inactivate 90% of a population of
E. coli is less than l0 Jmm (i.e., 1 erg mm 2 ), whereas a
dose of 7 x lO Jmnr 2 , is needed to achieve the same effect with
M. radiodurans . Ultraviolet radiation below 280 nut can damage
cellular DNA and RNA. Visible radiation (300-1000 nut) can also
be lethal or mutagenic to some microbes, but the most important
effects of visible light are in photosynthesis and light-induced
changes in growth rates. Little is known about the effects of
infrared radiation on microorganisms since the energy of this
radiation is immediately converted into heat or thermal energy
on contact with absorbing materials.
10
10
10
rays
G amnia
rays
X-Rays
violet
radiation
Infrared
radiation
48
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A particularly important aspect of light is its effect on
photosynthetic organisms, and in our case, photosynthetic bac-
teria capable of biodegrading organic chemicals. Certain
bacterial genera, e.g. Rhodospirillurn , are capable of using.
reduced organic compounds as electron donors. The photosynthetic
bacteria are found in oxygen-deficient environments where light
is not a limiting factor. These bacteria are found in sediments
of ponds, in estuarine sediments, and in a narrow band at a depth
of approximately 80 to 150 feet in deep lakes and in the open
ocean where oxygen has been depleted and there is still a low
light intensity (Clayton and Sistrom, 1978). Photosynthetic
bacteria are able to photoassiinilate a wide variety of low mole-
cular weight organic compounds, including acetate, pyruvate,
fatty acids, methanol and ethanol, and some are able to degrade
simple sugars and sugar alcohol. The bacteria generally lack
the capacity to break down organic macromolecules such as starch,
cellulose, pectin, lipids and proteins. In natural habitats,
they therefore depend on the activity of chemoorganotrophic
bacteria capable of degrading such macromolecules.
The effects of light intensity on bacterial growth rates
and substrate utilization have’ been the subject of limited in-
vestigation. Nakamura (1937) observed that the rate of oxygen
uptake by Rhodopseudomonas palustris was decreased by illumina-
tion. Partial suppression of oxygen uptake has been observed in
Rp. sphaeroides and Rp. capsulata (Clayton, 1955). The diminish-
ed utilization of oxygen in light is not, however accompanied
by an inhibition of growth, and growth continues essentially at
the same rate in air as under anaerobjosis (Cohen-Bazire et al.,
1957). The utilization of substrates can even remain unchanged
(van Niel, 1941; Morita, 1955), for van Niel demonstrated that
acetate utilization was the same whether suspensions were illum-
inated in air or nitrogen, while oxygen uptake was completely
suppressed in the latter instance. This is not necessarily so,
however, for Clayton (1955) found a different rate of succinate
Utilization in light and dark. Furthermore, Clayton demonstrated
that the relative amount of substrate utilized via either respira-
tion or photosynthesis depended on both light intensity and oxy-
gen tension. The preferential mode of substrate utilization was
through photosynthesis. Johnson and Brown (1954) demonstrated
that light, rather than oxyqen tensiçrn, was inhibiting respira-
tion, by demonstrating that the 18 o ’/ 6 ratios did not change
during illumination of Rhodospirillum rubrum . Later studies
by Thore et al. (1969) determined that light inhibited NADH -2
oxidation in Rs rubrum at an intensity of 1.2 x l0 ergs cm
sec
In review, light can enhance or inhibit the biodegradation
of chemicals depending on the specific conditions and micro-
organisms involved. Ultraviolet light can inactivate microbial
population and, therefore, inhibit biodegradation. Visible light
49
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can also be lethal or mutagenic to those species which are with-
out protective carotenoid pigment. Photosynthetic bacteria are
able to photoassimilate a wide variety of mostly non-xenobiotic
low molecular weight organics. However, the effects of light
intensity on biodegradation rates are largely undocumented. The
capability of photosynthetic bacteria and/or algae to photo-
assimilate xenobiotic organics are also greatly unknown.
50
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SECTION 4
CHEMICAL ENVIRONMENTAL VARIABLES
OVERVIEW
The chemical environment can influence the biodegradation
rate of chemicals in two ways: (1) by direct transformation of
a chemical to a form that is more or less biodegradable or avail-
able than the parent chemical, or (2) promoting or inhibiting the
activity of biodegrading microorganisms. Conversely, the chemical
environment may have no effect in influencing chemical biodegrada-
tion. Chemical environmental variables discussed in this section
are: (1) pH; (2) redox potential; (3) nutrients; (4) toxins!
inhibitors; and (5) water availability.
The optimum pH required for growth of microorganisms varies
considerably, though the physiological limits of pH range from
about pH 4.0 to 9.0. For most organisms, there is a fairly narrow
range within these limits that is most favorable for growth. A
review of the literature revealed many investigations on the effect
of pH on growth rates in pure culture; however, very little is
known about these effects and mechanisms in natural habitats.
The pH of the environment affects microbial activity and thus
biodegradation as a result of the interaction between hydrogen ions
and enzymes (and presumably transport proteins) in the plasma
membrane. Certain pH values will be optimal for activities of
specific enzymes. Optimal pH values may depend on other factors
such as salt concentration (Cockrane, 1958; Doetsch and Cook,
1973; and Dickinson and Pugh, 1974).
In addition to affecting microorganisms and microbial enzymes
directly, pH influences the dissociation of many molecules which
directly influence microorganisms. Of particular importance are
the effects of pH on the availability of required nutrients, e.g.,
ammonium and phosphate, which limit microbial growth rates in
many ecosystems; and on the mobility of heavy metals which may be
toxic to microorganisms.
Many enzymatic reactions are oxidation—reduction, or redox,
reactions. The ability to carry out redox reactions by an organ-
ism depends on the oxidation reduction potential (Eh) of the
environment. It is found that many compounds are resistant to
biodegradation under anaerobic conditions but can be readily
51
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biodegraded in oxidizing conditions. Alternatively, some chemical
transformations, such as dechlorination, can proceed at a faster
rate under anaerobic conditions. It should be noted, however,
that the Eh of an environment may be quite different than that
of a cell, and thus intracellular enzymatic reactions can occur
in spite of environmental redox conditions.
Gradients in Eh are widely evident in nature, and the location
of many populations is quite obviously’ correlated with the potential
that allows for their development. For example, populations capable
of reducing inorganic or organic substances may be activated by a
reduction in Eh as 0 is consumed. Linked with anaerobiosis and
low redox potential s the appearance of other toxicants, H 2 S
and organic acids in particular, and hence an array of forces make
anaerobiosis an effective means whereby one portion of the cornniun—
ity does material harm to a second (Mitchell and Alexander, 1962).
Among the microbial activities directly affected by Eh in
soil are mineral transformations, alterations in organic products,
and changes in pH. Little is known, however, about the effects
of Eh on various physiological processes of microbes in soil (e.g.,
enzyme activity, release of reducing metabolites by drying c lls,
toxin production, nutrient uptake) although some of these effects
have been studied in pure culture (Dolin, 1961).
Rose (1976) defined nutrients as compounds which must be taken
by microorganisms from the environment in order to satisfy their
requirements for biosynthetic raw materials and for energy. Rose
categorized nutrients as: (1) water, (2) energy sources, (3)
bio’ ynthetic raw materials (4) growth factors, and (5) inorganic
minerals. The effects of water on microbial growth and biodegrada-
tion are discussed under water availability.
Biosynthetic raw materials include carbon, hydrogen, oxygen,
nitrogen, phosphorous and sulfur. Carbon, hydrogen and oxygen
account for the bulk of the dry weight of microorganisms. If
growth is to take place, utilizable compounds containing these
elements must be available in the environment in relatively high
concentrations.
Concentrations and sources of available nitrogen and phosphorus
often limit biodegradation in aquatic and soil habitats. ‘The
limiting effects of inorganic nutrients in soil are usually only
apparent when substantial amounts of readily oxidizable carbonaceous
substrates are introduced (Stotzky and Norman, 1961; Stotzky and
Norman, 1964). The concentration of the limiting nutrients then
determines the rate of substrate oxidation.
Growth factors are organic compounds such as amino acids,
vitamins, purines, pyrimidines, and nucleotides, which are either
essential or stimulatory to the growth of microorganisms. The
requirements of a microorganism for growth factors are not fixed
52
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but may vary with the conditions under which the organisms a-re grown.
The requirement for growth factors by different species is dependent
upon environmental conditions, such as pH, Eh, temperature, ionic
composition and the concentration of nutrients. Species not requir-
ing such factors, or able to make use of those present, probably
develop more rapidly after the introduction of readily utilizable
substrates than those species dependent on growth factors. These
“secondary populations” may be dependent upon growth factors that
are synthesized by the primary populations (Laskin and Lechevalier,
1974).
Small amounts of many inorganic cations and anions are required
for growth of all microorganisms. These inorganic nutrients fall
into two classes. Macronutrient elements that+are require 2+
relatively high concentrations include Mg 2 +, K , Fe 3 , Mn 2 , Zn
Na+, Ca 2 +, and Cl -, and the metabolic functions of most of these
ions are reasonably well understood. Micronutrient elements (e.g.,
Co, Ni, Se, V) are required in very much lower concentrations. It
is usually very difficult to establish a requirement for a micro-
nutrient because of contamination in the purest of medium constit—
uents (Rose, 1976)
Mineral elements function in microbial metabolism mainly as
activators of various enzymes. Little is known, however, about
which mineral nutrients are absolutely required for microbial
life in soil or aquatic environments. Deficiencies of some miner-
als can affect the synthesis of enzymes and other biopolymers, the
stabilization of cell walls and tertiary structures of DNA and
RNA, cell division, mobility, and a variety of other physiological
and biochemical processes (Weinberg, 1962).
The presence of other chemicals can have an impact on the fate
of a specific chemical in soil. For example, the presence of
detergents was found to result in an increased persistence of para-
thion and diazinon residues in water (Lichtenstein, 1966). Studies
by Kaufman et al. (1970, 1971, 1977) have shown that the presence
of methylcarbamate and pesticide combinations have increased the
persistence of certain pesticides and herbicides in soils. Like-
wise, Kecskes and Cserhati (1977) observed decreased biodegradation
of linuron in the presence of other pesticides in soil. Conversely,
Liu (1980) reported that the rate of biodegradation of Arochor 1221
was enhanced by enrichment with sodium ligninsulfonate.
Microorganisms possess a range of tolerance mechanisms, most
featuring some kind of detoxification. Many of these detoxifi-
cation mechanisms occur widely in the microbial world. A feature
of heavy metal physiology is that even though many metals are
essential for growth, they are also reported to have toxic effects
on cells, mainly as a result of their ability to denature protein
molecules. There are, however, many reports in the literature of
microbial resistance to heavy metals. The phenomenon of microbial
resistance is particularly relevant to biodegradation, especially
53
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in connection with the roles of microbes in polluted ecosystems
and in the reclamation of metal-contaminated natural habitats. It
is also important to understand the mechanisms of microbial toler—
ance because of the extensive use of some metals and metal compounds
as fungicides and disinfectants (Rose, 1976).
Water accounts for between 80 and 90% of the weight of a
microorganisms. Chemical reactions that take place in living
organisms generally require an aqueous environment, and water
must therefore be in the environment if the organism is to grow
and reproduce. It must be, moreover, in the liquid phase, and
this confines biological activity and biodegradation to tempera-
tures ranging from around -2°C (or lower in solutions of high
osmotic pressure) to approximately 100°C (Rose, 1976).
In order to adequately describe the environment in which a
microorganism exists, some measure is required which indicates
the amount and form of water in that environment. This measure
must give some indication of the suitability of the solvent en-
vironment for the reaction sequences necessary for normal metabo-
lism (Reid, 1980). A measure popular with early workers was
osmotic pressure. This has been disc ssed by Brown (1976) , who
commented on the difficulty of accurately measuring the osmotic
pressure in many systems. Scott (1977) suggested that a suitable
measure of water availability was the thermodynamic water activ-
ity, a , of the equilibrium system.
Microorganisms can grow in media with a values between 0.63
and about 0.99. For any one organism, the important values with-
in this range are the optimum and minimum a values. These have
been determined for a number of microorganisms, and they seem to
be remarkably constant for a particular species and to be inde-
pendent of the nature of the dissolved solutes (Rose, 1976). Brown
(1976) and Troller and Christian (1978) have discussed in detail
the advantages and disadvantages of the use of water activity as
a measure of water availability.
In soil,water availability is usually measured in terms of
percent moisture content and percent of field capacity. It is
generally found that rates of microbial activity increase with
increasing water content of the medium to certain critical values.
When the water content exceeds the ç ritical value, biodegradation
rates will be constant or reduced.
pH
On a gross level, the pH of natural soil/aquatic systems has
been shown to affect biodegradation, which appears to be due to
the influence of pH on the predominance of one group of organisms
over another. Gradients in pH are widely evident in nature. A
review of the literature revealed that most studies on the effect
of pH on biodegradation were concerned with a pH range of 5 to 8,
which are the limits favorable for the growth of most microorganisms.
54
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The effects of pH on the extent and rate of biodegradation are
discussed under individual headings for specific organic compounds.
Dimethylamine
Tate and Alexander (1976) assessed the rate of dimethylamine
(DMA) biodegradation in soils with different pH values. The four
soils tested were Hudson Collamer silt loam (pH 4.5) , Langford
channery silt loam (pH 5.2), Williamson silt loam (pH 6.8) , and
Lima loam (pH 7.0). Their organic matter levels were 1.8, 4.1,
1.6, and 3.6%, respectively. DMA was metabolized in samples of
all of the soils tested. Figure 14 shows that in Williamson silt
loam adjusted to different pH values, the rate and extent of DMA
disappearance decreased as the acidity increased. Figure 14 shows
the disappearance of DMA in three other soils of different pH.
The disappearance was slowest in Hudson Collamer silt loam (pH 4.5)
and was more rapid in Lima loam (pH 7.0) and Langford channery
silt loam (pH 5.2). The differences could have been due to differ-
ing percentages of organic matter in the tested soils. The bio-
degradation rate of dimethylamine was more rapid in Lima loam (3.6%)
and Langford channery silt loam (4.1%) than in Hudson Collamer silt
loam (1.8%). This apparent correlation is also supported by the
rate of biodegradation in two soils of different percentage organic
content having similar pH values (i.e., Lima loam, pH 7.0, 3.6%
organic content; Williamson silt loam, pH 6.8, 1.6% organic content).
The data show that the biodegradation rate was significantly greater
at the higher organic soil content. The results suggest that the
effect of pH on biodegradation rates may be difficult to interpret
in soils having a wide range of organic content.
Naphthalene
Hambrick, DeLuane, and Patrick (1980) studied the biodegrada-
tion of naphthalene in estuarine sediments at varying pH and redox
potentials. Results indicated that naphthalene biodegradation was
significantly greater at pH 6.5 or 8.0 than at 5.0. Figure 15
shows that naphthalerie was biodegraded to a greater extent at all
pH levels under oxidizing conditions than under more reducing
conditions. These results are significant in that they indicate
that the determination of pH effects on biodegradation in other
studies under conditions of unknown redox potential may at best
indicate only a qualitative trend. Strawinski and Stone (1955)
also studied the effect of pH on the biodegradation of naphthalene
though utilizying a pure culture of Pseudornonas sp. The yield of
non-naphthalen±c extract calculated on a basis of 1% naphthalene in
the medium increased from 2 to 29% by adjusting the initial PH
to 8.0 and aerating during aeration. This pure culture study,
while not representative of conditions existing in nature, serves
to substantiate the results of Hambrick et al. (1980). It is
apparent from both studies that pH-Eh reT tT nships should be de-
veloped in order to obtain a better quantitative evaluation and
comparison of pH effects on biodegradation.
55
-------
60
Figure 14.
Disapearance of dimethylarnine from soils of varying
pH. The Williamson soil was adjusted to the PH
values shown (Tate and Alexander, 1976).
40
20
0
60
a,
C,
20
0
4 8 12
DAYS
56
-------
C-)
•— 020
Ez1
dPç
>10
E L)
60
a
50
0
0
030
dP
20
I-
l0
0
70
60
a
50
>
0
U
U
‘ 30
o’P
20
E-
0
E- 10
0
Fiqure 15
DAYS
Total Dercentace of recovered as sumnied per
day for the mineralization of [ 1(4,5,8)-
14 C] naphthalene in 12 sediment-water suspensions
incubated at four redox ootentials and three pH levels
(Hambrjck et al. , 1980).
57
0 5 10 15 20 25 30 35
-------
Oct ad e cane
Hambrick et al. (1980) determined the biodegradation rate
of octadecane in estuarine sediments as affected by different pH
levels under oxidizing and reducing conditions. Highest biodeg-
radation rates occurred at pH 8.0 and the lowest at pH 5.0.
Figure 16 shows that octadecane was biodegraded to a greater
extent at all pH levels under oxidizing conditions than under
more reducing conditions. Generally, biodegradation rates for
octadecane were greater than those for naphthalene (Figure 15).
The results of this study are similar to those obtained for
naphthalene with respect to the importance of pH-Eh diagrams in
the evaluation of pH effects on biodegradation of hydrocarbons.
Chloroani line
Studies by Hsu and Bartha (1973), who measured 14 C0., pro-
duction from soil containing radio-labeled chloroaniline7sOil
organic matter complex under various environmental conditions,
indicate that the biodegradation of chioroaniline in anaerobic,
sterilized soils is not significantly affected by variations in
pH from 5.0 to 8.0.
S umrnary
The extent and rate of biodegradation are generally enhanced
with increasing pH from a level of pH 5 to an approximate limit-
ing value of pH 7 to 8. Exceptions have been reported in which
variations of pH in natural systems have a negligible effect On
the biodegradation rate. Significant variation in soil organic
content may limit the interpretation of pH effects on biodegrada-
tion. Several studies have also shown that pH-Eh diagrams should
be developed in order to make more valid comparisons of pH effects
on biodegradation in different natural soil/water systems.
REDOX POTENTIAL
The effect of redox potential in influencing biodegradation
has been extensively documented in the literature. The ability
of an organism to carry-out oxidation-reduction reactions depends
on the redox potential of the environment. Many enzymatic
reactions are oxidation-reduction reactions. Variations in bio-
degradation rates of ersistent compounds in natural systems may
be attributed, in part, to the effect of redox potential on the
enzymatic action of indigenous microorganisms.
Gradients in Eh are widely evident in nature. For example,
the redox potential of submerged sediments may range from +700
my (highly oxidized) to -400 my (highly reduced). Below the
aerobic sediment surface, facultative bacteria decrease the redox
potential resulting in development of a two-layer system con-
sisting of an oxidized surface layer and an underlying reduced
layer.
58
-------
40
0
>
0
C.-)
C i )
C.)
30
20
10
0
50
40
30
20
10
o’P 0
0
70
60
50
40
30
20
10
0
Figure 6.
5 10 15 20 25 30 35
DAYS
Total percentage of recovered as summed
per day for the mineralization of octadecane in 12
sediment water suspensions incubated at four redox
potentials and three pti levels (Hambrick et al. , (1980).
59
-------
Although Eh apparently has a gross effect on microbial growth,
and therefore, may have some predictive value for biodegradation,
the definition of its effect will depend on the ability to measure
this environmental factor at levels which approximate the micro-
habitat.
The influence of redox potential on the extent and rate of bio-
degradation is discussed under individual headings for specific
organic compounds. The effect of redox potential is presented for
several studies; however, this information is greatly lacking in
the literature.
Di-2-Ethylhexyl Phthalate (DEHP) and Di-n-Butyl Phthalate (DBP )
Johnson and Lulves (1975) reported on the biodegradation of
two widely used plasticizers, di—2—ethylhexyl phthalate (DEHP) and
di-n-buty]. phthalate (DBP) by unidentified aerobic and anaerobic
microorganisms found in hydrosoil of freshwater ponds. The results
of this study show that the biodegradation of DEHP and DBP is much
more rapid under aerobic conditions than under anaerobic conditions
as shown in Table 3. For example, under aerobiosis, 53% of the DBP
was biodegraded within 25 hrs, and 98% within 5 days. Under the
same conditions, nearly 14 days were required for the biodegradation
of approximately 50% of the DEHP. Anaerobosis slowed biodegr adation
of both DBP and DEHP. Although nearly 98% of the DBP was biodegraded
after 30 days in the hydrosoil, the retarding influence of anaerobio-
sis was evident. Approximately 30% of the DBP was biodegraded after
5 days under anaerobic conditions, whereas 98% of the DBP was bio—
degraded after 5 days under aerobic conditions. After 30 days, no
significant biodegradation of DEHP was observed under anaerobic
conditions. The results of this study are in general agreement with
TABLE 3. BIODEGRADATION OF ‘ 4 C-DI-N-BUTYL PHTHALATE AND 4 C-DI-2-
ETJ-IYLHEXYL PHTHALATE IN FRESHWATER HYDROSOIL (Johnson and
Lulves, 1975).
Percent recovery of radioactivity from hydrosoil
Incubation (days) Aerobic Anaerobic
14 C-di-n-butyl phthalate
1 47 100
5 2 69
7 5 59
14 8 39
30 3 2
14 C-di-2—ethylhexyl phthalate
7 100 100
14 50 100
30 41 100
60
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other investigations which indicate that the biodegradation of
organic materials is often enhanced under aerobic condtions and
significantly reduced or prevented under anaerobic conditions.
Unfortunately, this study like many others, did not quriatify the
effects of aerobic and anaerobic environments on biodegradation
rates in terms of a measured redox potential of the studied soil!
water systems.
Dimethylamine (DMA )
Studies by Tate and Alexander (1976) indicate that anaero-
biosis had a significant effect on the stability of dimethylamine
(DMA) in soil. Although DM A was metabolized in Williamson silt
loam under anaerobic as well as aerobic conditions, the extend
and rate of biodegradation was markedly retarded under anaero-
biosis. Figure 17 clearly demonstrates the persistence/bio-
degradability of DMA under the studied conditions.
Ethylenedimethyltriacetate (EDTA )
EDTA had been thought tobe resistantto microbial degradation
(Alexander, 1973) , but studies by Tiedje (1975) and Be1 1y et al.
(1975) concluded that EDTA can be degraded by natural microbial
populations. Tiedje (1977) studied the rate of EDTA biodegrada-
tion in three different sediments. Figure 18 shows that significant
biodegradation occurred under aerobic conditions, although the rate
and extent of biodegradation varied for different sediments. These
variations are probably due, in part, to different soil constituents
which may be significant in governing the extent and rate of bio-
degradation.
Figure 18 shows that EDT 4 biodegradation under anaerobic
conditions did not result in CO 2 production. This finding, in
itself does not confirm the absence of anaerobi 4 biodegradation,
since fermentation would not necessarily yield C0 2 , but rather
could produce organic end products. Such produ s, however,
would be expected to be rapidly metabolized to CO 2 under aerobic
conditions. After periods of anaerobic incubat n, subsequent
aerobic metabolism did not result in a rate of CO production in
excess of that found for continuous aerobic metabo1 sm (Figure 18).
Thus, EDTA does not appear to be subject to significant anaerobic
biodegradation.
When the rate of degradation was determined from the linear
portion of the biodegradation curves, the rate of aerobic biodegra-
dation appeared to be first order for concentrations ranging from
0.4 to 90 ppm. These findings by Tiedje (1977) indicate that EDTA
should be biodegradable in most aerobic soils and sediments, pro-
vided sufficient organic matter is available to support a general
microbial population over a prolonged period of time.
61
-------
60
40
:1-
20
0
10 20 30
Days
Fiqure 17. Effect of anaerobic conditions on dimethylamine
disaopearance from a Williamson silt loam
(Tate and Alexander, 1976).
Anaerobic
Aerobic
62
-------
18
0
U
(n
0
0
U
0
)
12
6
0
Figure 18.
DAYS -
Biodegradation of 14 C-carboxyl-EDTA (4.4 ppm) under
aerobic and anaerobic-to—aerobic conditions in sediments
(Tiedje, 1977).
0 20 40 60 80
63
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Lignin
Hackett et al. (1977) studied lignin biodegradation under
aerobic and anaerobic conditions in a variety of natural materials.
The observed biodegradation of lignin in aerobically incubated
lake sediment implies that lignin degradation in such sediment
could occur when oxygen is provided during and after seasonal
turnover of lake waters. Biodegradation under anaerobic condi-
tions was observed to be extremely slow, in agreement with other
studies (Harken, 1973).
Octadecane and Naphthalene
The ecological significance of the biodegradability of crude
oil hydrocarbons is related to the persistence in the environment
of those hydrocarbons that are more slowly degraded and, that are
often also the more toxic components of petroleuii . Several re-
searchers have reported that the extent of hydrocarbon degradation
quickly decreases with sediment depth because of the development
of a two-layer system consisting of an oxidized or aerobic surface
layer and an underlying reduced or anaerobic layer (Blumer and
Sass, 1972; Hughes and McKenzie, 1975; Ward and Brock, 1978). The
oxygen required for more rapid hydrocarbon biodegradation is not
available in deeper sediments. Submerged sediments display a
range of redox potential from 700 my, which indicates highly
oxidized sediments, to -400 mV, which indicates highly reduced
sediments (DeLaune et al. , 1976).
Hambrick et al. (1980) determined the biodegradation rates
in estuarine sediments of naphthalene and octadecane as affected
by different redox potentials at three PH levels. Hydrocar n
mineralization rates were inferred from the total respired CO 2 .
Figures 15 and 16 show that, in general, the biodegradation rates
for both naphthalene and octadecane increased rapidly with
increasing redox potential (i.e., increasing sediment aerobiosis)
at all pH levels. Biodegradation rates for octadecane were
generally greater than those for naphthalene. The presence of a
lag phase suggests the transformation is microbial in nature.
Ward and Brock (1978) reported similar results in that the bio-
degradation of hexadecane in freshwater lake sediments was very
rapid under aerobic condiitions but very slow under anaerobic
conditions.
One of the major fates of released petroleum hydrocarbons in
the coastal environment is their incorporation into bottom sedi-
ments. The studies of Hambrick et al. (1980) are of considerable
ecological significance in that they show that hydrocarbons de-
posited in reduced sediments, where facultative and anerobic
bacteria predominate, will persist for much greater lengths of
time than hydrocarbons remaining in the sediment surface layer,
64
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where aerobic bacteria predominate. This study also shows the
value of using redox potential as a possible indicator of bio-
degradation rates of petroleum hydrocarbon or other compounds.
Pentachiorophenol (PCP )
Pentachiorophenol (PCP) and its salt, sodium pentachioro-
phenate, (NaPCP) are two of the most versatile pesticides now in
use in the United States. PCP has a wide distribution in the
total environment; therefore, knowledge of its environmental
behavior and fate is essential for effective management of its
use. Microorganisms including bacteria (Watanabe, 1973; Suzuki,
1971; and Reiner et al. , 1978) and fungi (Cserjesi and Johnson,
1972) have demonstrated their ability to degrade PCP and other
chiorophenols.
Liu et al. (1981) determined the rate of NaPCP degradation
under aerobic/anaerobic conditions in laboratory fermentors.
Among the factors studied, oxygenation was found to have a sig-
nificant effect on the rate of PCP degradation (Figure 19). By
measuring the disappearance of PCP from the fermentor broth
(primary degradation) , the researchers found that the con-
centration of PCP in the aerobic fermentor had decreased to a
negligible amount after 3 days, while’ 100% of the added PCP
remained unchanged in the anaerobic fermentor. Further incubation
up to 28 days resulted in only 5% biodegradation, indicating the
inherent persistence of PCP under anaerobic conditions. The half-
lives of PCP in aerobic and anaerobic fermentors were calculated
to be 0.36 and 192 days, respectively. PCP biodegradation rates
determined by Boyle et al. (1980) indicated that PCP had a shorter
half-life (tk = 19 days) under aerobic conditions than under
anaerobic cor ditions (t = 80 days). In consideration of the
complexity involved in he determination of a biocide’s bio-
degradability, the results obtained by Liu et al. (1981) could be
considered in agreement qualitatively with those of Boyle et al.
(1980). The difference observed in these two studies may be
due, in part, to the fact that Liu et al. (1981) used an acclima-
tized culture, while natural pond water was employed in the study
by Boyle et al. (1980). Regardless, the role of redox potential
in determining the persistence/biodegradability of PCP is clearly
demonstrated in both studies.
Phenol and Chlorophenols
The ecological significance of phenol and chiorophenols is
in part related to the fact that they have been shown to be
intermediates in the degradation pathways of some pesticides.
They have also been found in pesticide preparations and industrial
wastes.
The aerobic and anaerobic degradation of phenol and selected
chlorophenols in a clay loam soil containing no added nutrients
65
-------
100
z
0
0
50
z
U
0
100
z
0
0
50
z
U
0
0
Figure 19.
200 400 600
TIME (hours)
Disapearance of PCP in cyclone fermentors (Liu et al., 1981).
66
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was examined by Baker and Mayfield (1980). Results of this study
showed that phenol, o—chlorophenol, p-chlorophenol, 2,4-dichioro-
phenol, 2-6-dichiorophenol and 2,4,6-trichiorophenol were rapidly
degraded by aerobic soil microorganisms. Pentachiorophenol, 2,4,
5-trichlorophenol, 3,4-dichlorophenol and m-chlorophenol were
degraded at much slower rates, while 3,4,5-trichiorophenol and
2,3,4,5-tetrachlorophenol persisted in aerobically incubated
soils for over 160 days. None of the compounds examined were
degraded by microrganisms in anaerobically-incubated soil at 23°C.
Redox potentials were not reported.
The times required for the biodegradation of these compounds
were, in some cases, much shorter than those determined by Alexander
and Aleem (1961) . It is speculated that the different biodegrada-
tion rates observed in these two studies may be due to the smaller
amounts of soil used in the study by Alexander and Aleem (1961)
or perhaps to differences between incubation in soil vs soil
suspension systems. Nevertheless, the persistence of phenol and
chlorophenols under anaerobic conditions is substantiated by both
of these studies.
Dinitroanilines
Contrary to the above-mentioned evidence linking higher
biodegradation rates of selected chemicals to higher redox
potential or more oxygenated environments, the biodegradation of
dinitroanilines (e.g. , trifluralin, benefin) appears to be more
rapid in anaerobic soils than soils of higher redox potential.
For example, Probst et al. (1967) reported a more rapid rate of
degradation of dinitroanilines at 200% of soil field capacity
(anaerobic conditions) than at moisture levels of 0, 50, and 100%
of field capacity. However, the experiment lasted only 40 days.
Other Chlorinated Hydrocarbons
Generally, organochiorine insecticides degrade slowly and
are strongly adsorbed to sediments, but selected compounds have
been observed to decompose readily under anaerobic conditions.
For example, the rapid degradation of lindane has been observed
in flooded rice soils (Raghucet al., 1966; Yashida and Castro,
1970) , lake muds (Lichtenstein et al. , 1966) and in simulated
impoundments under anaerobic conditions (Newland et al., 1969).
The degradation rate under laboratory conditions for lake mud
and rice soils was rapid and normally complete within 8 days to
50 days, but was effectively impeded by soil sterilization
(Lichtenstein et al., 1966). Moreover, the rate of degradation
for aidrin and lindane was significantly greater in lake muds
than in soils (Lichtenstein et al., 1966) , and more rapid for
lindan-e in flooded compared to nonflooded rice soils (MacRae
et al., 1967; Yashida and Castro, 1970). The evidence here
suggests that the rate of biologically mediated dechlorination
may be more rapid under anaerobic conditions (or at lower redox
potential) then under aerobic conditions.
67
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Summary
A review of the literature showed that the extent and rate of
biodegradation is profoundly affected by redox potential. Many
of the chemicals studied were biodegraded much more rapidly under
aerobic conditions than under anaerobic conditions. Limited data
show that biodegradation rates increase rapidly with increasing
redox potential (i.e., increasing aerobiosis). However, results
of selected biodegradation studies involving dinitroanilines and
certain pesticides suggests the opposite. These studies point out
that the persistence of toxic compounds deposited in reduced
sediments is compound specific. Mathematical expressions for
predicting the effect of redox potential on biodegradation are
generally lacking. In most cases, quantitative comparisons of
biodegradation rates cannot be made because the redox potential
of the studied systems was not measured.
NUTRIENTS
Biodegradation of xenobiotic chemicals in aquatic and soil
habitats is often limited by the concentrations and sources of
available nutrients. The limiting effects of inorganic nutrients
in soil are usually only apparent when substantial amounts of
biodegradable carbonaceous substrates are available. Mineral
nutrition can limit the development of indigeneous microorganisms.
This limitation is usually not the result of a scarcity of a
specific nutrient, but rather its biological availability.
Phosphorous and sulfur, though required in smaller quantities
than nitrogen, may also be present in forms not readily assimilable
by the microbial community. The availability of other nutrients
in natural environments is usually adequate to sustain high levels
of microbial growth. Most studies on the effect of nutrients on
biodegradation have been concerned with the concentration levels
and sources of nitrogen and phosphorous.
Cellulose and Lignin
14 14
Biodegradation of specifically labeled C-cellulose and C-
lignin-labeled lignocelluloses was examined in an organic-rich
sediment in response to manipulation of various environmental
factors (Federle and Vestal, 1980). Mineralization was determined
by measuring the amount of radio-labeled CO 2 L released from the
labeled substrates.
Nitrogen (as NHANO. ) and phosphorus (as PD 4 3 ) added alone had
only a slight stimu1 to y effect on the biodegradation of Carex
aquatilis cellulose. Especially noteworthy was the effect of
nitrogen and phosphorous added togeth (Figure 20). At a nutrient
concentration of 10pM, the amount of C-cellulose recovered as
CO 2 was nearly twice that of the control treatment. The data suggest
also that phosphorous may be limiting. The degree to which phos-
phorous limitation severely affects cellulose biodegradation is
68
-------
0
U
rj
0
cz-
0
U
C 1 1
z
0
0
‘ O U
z
r:L
C i
cz
30
20
10
0
Figure 20.
NUTRIENT CONCENTRATI-ON CnN)
Mineralization of Carex 14 C-cellulose labeled lignocellulose in response to
different concentrations of added NH 4 NO 3 (N) , Na 2 HPO 4 (P) , and NH 4 NO 3
plus Na 2 HPOA(N&P) by Toolik Lake sediment áftér 16 day duf in the summer of
1979 (Federle and Vestal, 1980).
control
.0001 0.001 0.01 0.1 1 10
-------
supported by the observation that phosphorous enrichment of oxygen-
depleted treatments resulted in reversal of the inhibition caused
by the lack of oxygen. These results indicate that nutrient
availability is a significant factor in controlling cellulose
biodegradation.
Addition of nitrogen had no effect on the amount of Carex
lignin mineralized. However, addition of phosphorous resulted
in mineralization which was significantly lower than the control
(Figure 21). Phosphorous concentrations as low as O.lpM caused
this inhibition with the greatest inhibition observed at the high-
est phosphorous concentration (10pM). The antagonistic role of
phosphorous in lignin mineralization may be of significance in
understanding the increased proportion of lignin relative to
cellulose in decomposing litter.
Dichloroanjline (DCA )
Hsu and Bartha (1973) investigated the effects of glucose and
NH NO 3 on the mineralization of chioroaniline residues. Table 4
sh ws that addition of a nitrogen source alone 0 mg NH NO /50g
soil) had little effect on either total CO 2 or CO 2 evoIut1 on
from radio-labeled DCA, but a massive amount of glucose (250 mg/50g
soil) with’ source of nitrogen (50 mg NH N0 3 /50g soil) severely
inhibited CO production, though total O production increased
greatly. it i not known whether this phen menon reflects the
decreased availability of °2 in the soil due to the rapid oxidation
of glucose.
TABLE 4. 14 C0 AND CO PRODUCTION IN SOIL CONTAINING RADIO LABELED
DCA- OIL ORGKNIC MATTER COMPLEX UNDER VARIOUS NUTRIENT
CONDITIONS IN 21 DAYS (Hsu and Bartha, 1973)
Conditions
14 C0:
(mmol)
Total CO 2 (mmol)
Nutrients added
30 mg glucose
250 mg glucose
50 mg NH 4 NO 3
3
2.68 x lO_3
5.25 x lO_3
2.36 x 10
3.82
7.02
3.29
250 mg glucose + 50
NH 4 NO 3
mg
3
3.74 x 10
8.13
Dimethylamine (DMA )
Tate and Alexander (1976) conducted a study to determine the
effect of the C/N ratios on the accumulation of DMA during the
biodegradation of trimethylamine (TMA), as shown in Table 5. This
70
-------
1.5
0
U
cn
a
0
C-)
zI
- 1
0
‘ -I
0
el 5
z
0
04
0
Figure 21.
14 .
Mineralization of Carex C—lignin—labeled lignocellulose in responsetO
different concentrations of added NH 4 NO 3 (N) , Na 2 1-1P0 4 (P) , and
NH NO plus Na HPO (N&P) by toolik Lake sediments afte 16 clays during t!ie
su ime of 197 (Fe er1e and Vestal, 1980).
N
p
N &P
I-
contol 0.0001 0.001 0.01
-j
L
0.1
1
-------
study was performed using a laboratory culture and, although not
necessarily directly applicable to natural ecosystems, suggest that
the prevailing C/N ratio may not affect the accumulation of DMA
resulting from the biodegradation of TMA. These results are sur-
prising in view of the fact that the accumulation of DMA in
cultures of Micrococcus sp. provided with TMA depended on the
nitrogen sources available to the bacterium. It is speculated
that nitrogen levels were not limiting in this study.
TABLE 5. EFFECT OF CARBON-NITROGEN RATIO ON DIMETHYLAMINE
ACCUMULATION BY MICROCOCCUS SP. (Tate and Alexander, 1976).
C-N ratio
Dimethylamine (pg/mi)
60:1
831
24:1
882
12:1
726
6:1
814
3:1
955
1:1
838
Hexadecane and Mineral Oil
In studies designed to identify critical environmental para-
meters affecting hydrocarbon biodegradation in freshwater, Ward and
Brock (1976) investigated nutrient limitation on mineral oil and
hexadecane oxidation rates. Indigenous rates of hydrocarbon oxida-
tion were found to be lower in lake water samples without addition
of 300 pg of N per liter as KNO and 100 pg of P per liter as KH 2 PO 4 .
In fact, enrichment of lake wat r samples with nitrogen and
phosphorus resulted in an increase in the rate of mineral oil and
hexadecane oxidation of 2.7 and 27.7 times the indigenous rates,
respectively. When either nitrogen or phosphorous was provided in
excess, biodegradation rates were limited by the amount of the
other nutrients, as indicated in Figure 22.
Figure 23 shows the correlation between mineral oil oxidation
rates and dissolved inorganic phosphate levels. The data resemble
a saturation relationship of the Michaelis-Menten type, and the
line drawing inFigure 22 is a “statistical fit of the linear
regression of a double-reciprocal plot of the same data.” The
authors suggest that, although quite high amounts of nitrogen
and phosphorus may be necessary to balance the carbon used when
substantial hydrocarbon degradation occurs, the rate of degradation
by natural communities only becomes limited at quite low nutrient
levels. In fact, substantial decreases in hydrocarbon oxidation
rates did not occur until the indigenous nutrient levels decreased
to levels near the limits of detection.
Atlas and Bartha (1972b) and Soli and Dens (1972) suggested
that nitrogen and phosphorous would limit biodegradation of
72
-------
0.10
800
0.05
0
pg P/i
0.10
0.05
0
400
0
800
400
0
pg N/i
Figure 22. tes of oxygen uptake during mineral oil oxidation (0) and
CO 2 production during hexadecane oxidation ( ) by Lake
Nenclota surface water sanpleE (Ward and Brock, 1976).
0 50 100
Nitrate with phosphorus provid at 100 iJg/
liter as phosphate.
0 100 200
73
-------
20
.15
01
-1
0
05
0
0
Figure 23.
Correlation between the indigenous rates of oxyoen
uptake during mineral oil oxidation and the indigenous
dissolved inorganic phosphate concentrations less
than 2.5 pa of P per liter (Ward and Brock, 1976).
50 100 150
pg P/i
74
-------
hydrocarbons in a marine area. However, in a study by Mulkins-
Phillips and Stewart (1974) , the concentration of nitrogen
occurring naturally in the marine environment did not signifi-
cantly affect the rate of degradation of hexadecane. From the
straight line portion of the curve in Figure 24, representing
hexadecane disappearance, it was deduced that approximately
0.05 mg of elemental nitrogen was required to bring about the
disappearance of 1 mg of hexadecane in the presence of adequate
supplies of phosphorous. Growth of the organism followed a
course similar to the hexadecane disappearance.
In contrast to the effect of nitrogen on the growth rate,
Mulkins-Philljps and Stewart (1974) found that decreased phos-
phorous concentrations increased the generation time of Nocardia
sp. (Table 6). The log of phosphorous concentration versus gener-
ation time yields a straight—line relationship (exponential)
which indicates a more complex situation than that shown for
nitrogen. The maximal population size was also affected by the
concentration of phosphorous, indicative of a depletion of the
available nutrient. The results indicate that the rate of
natural biodegradation of oil in marine environments is limited
by pho5phorous concentration, but suggest that the concentration
of nitrogen occurring in sea water (approximately 0.875 mg/i) is
probably not rate-limiting.
TABLE 6. EFFECT OF PHOSPHOROUS CONCENTRATION ON THE GENERATION
TIME (C) AND MAXIMAL POPULATION OF NOCARDIA SP. (PER mL)
GROWN AT 15C FOR 14 DAYS ON 1% HEXADECANE (Mulkins-
Phillips and Stewart, 1974)
*
Mg of P/liter
G (h)
Maximal
Population
970.0
97.0
9.7
0.97
0
10.1
11.3
13.5
15.0
no growth
8.8
4.8
7.6
6.4
4.0
x
x
x
x
l0
l0
l0
104
* Phosphorus was added as K 2 HPO 4 and KH 2 PO 4
Malathion
Nerkel and Perry (1977) studied the effect of cosubstrate
enrichment on the biodegradation of malathion. Their results
showed that the addition of 0.1% n-hep decane as cosubstrate
increased the malathion production of CO 2 from radio—labeled
to nearly three times that produced in the “control” culture.
Glucose, glycerol, glycerophosphate, and a mixture of amino acids
and peptides did not have an appreciable effect on the rate of
75
-------
250
9
200
150
100
50
0
Figure 24. Effect of nitrogen concentration (source Nh 4 NO ) on the disappearance of
hexadecane brought about by Nocafdia sp. at 15 C. Trials n triplicate
(Mulkins—Phillios and Stewart, 1974).
8
7 )
Q)
.0
0
z
c’j
- ‘-4
U
1)
0
0
my NITROGEN /L
4
-------
evolved from malathion. These results indicate that the
rate at which recalcitrant compounds are biodegraded may
depend also on the presence of selected organic compounds.
Naphthalene
Strawinski and Stone (1955) conducted studies on the effects
of the presence of copper sulfate and calcium chloride on the
biodegradation of napthalene in a basal medium by a pure culture
of the Pseudomonas group. It was found that the omission of ei-
ther calcium chloride or copper sulfate, or both, tested after
three subcultures in the deficient medium, resulted in a signi-
ficant loss in yield (Table 7) , demonstrating that both are
necessary under these conditions for increasing the biodegradation
of naphthalene
Aranha and Brown (1981) studied the effects of nitrogen
sources (i.e., NH Cl and KNO ) on the biodegradation of naphtha ..
lene in soil cult 1res. The esults obtained indicate that
additions of NH Cl had a greater stimulatory effect on the
biodegradation f naphthalene than was observed for KNO 3 . This
study suggests that the mineral ‘nitrogen source may have a major
influence on naphthalene degradation. However, the relevance
of these findings to the biodegradation of other aroma€ic hydro-
carbons remains to be determined. Confirmation of these results
would be an important factor in obtaining a better understanding
of hydrocarbon biodegradation as affected by the nitrogen source.
TABLE 7. EFFECT OF CALCIUM CHLORIDE AND COPPER SULFATE ON THE
ACCUMULATION 9F ETHER-SOLUBLE ACIDS DURING NAPHTHALENE
OXIDATION (Strawinski and Stone, 1955)
Medium
Final pH
Yield
g
%
No CaC1 2
5.8
0.
35
14.0
No CuSO 4
6.2
0.
40
16.0
No CaC1 2
or
CuSO 4
5.9
0.
03
1.2
Control
6.2
0.
69
27.0
*
2.5 g. naphthalene in 1-liter flasks aerated.
Parathion
Organic matter, either native or applied, is known to influ-
ence the persistence of pesticides applied to soil. By stimulating
microbial activity in soil, the effect of organic carbon sources on
77
-------
the degradation of parathion via nitrogroup reduction and hydrol-
ysis in flooded alluvial soil was investigated by Rajararn and
Sethunathan (1975). The total carbon and nitrogen contents of
organic sources used in this study are given in Table 8.
TABLE 8. CARBON AND NITROGEN CONTENTS OF ORGANIC SOURCES USED IN
THE EXPERIMENT (Rajaram and Sethunathan, 1975).
Organic Matter
Carbon (%) Nitrogen (%) C/N ratio
Glucose
40.
0
--
Rice Straw
34.
0
0.59
58
Farmyard manure
24.
1
1.51
16
Algal crust
12.
8
1.37
9
The degradation of parathion via nitrogroup reduction was
enhanced when the soil containing parathion was incubated with
0.5% glucose, rice straw, algal crust, and farmyard manure under
flooded conditions. The degradation followed the order glucose >
rice straw > algal crust > farmyard manure > unamended. The
greatest degradation occurred with glucose, with 99 percent of
the insecticide being lost in 3 days (Table 9). During the
same period, only 56 percent of the added insecticide was decom-
posed in unamended soil. At 18 days, the insecticide was not
detected in all the amended soils, whereas 9 percent of applied
insecticide still persisted in the unamended soil. It is suggested
that organic amendments to the flooded soil apparently lowered the
Eh of the soil and, thereby, permitted the rapid biodegradation of
parathion.
TABLE 9. STIMULATORY EFFECT OF ORGANIC SOURCES ON THE DEGRADATION
OF PARATHION VIA NITRO-GROUP REDUCTION IN FLOODED ALLUVIAL
SOIL (Rajaram and Sethunathan, 1975)
Incubation
(days)
pg Parathion/20g soil
recovered
Unamended
Farmyard’
Algal
Rice
Glucose
manure
crust
Straw
0
628
625
594
630
630
3
276
189
155
89
7
6
240
163
83
30
0
12
99
39
10
0
0
18
57
0
0
0
0
78
-------
Polychiorinated Biphenyl
Polychlorinated biphenyls (PCBs) are among the most per-
sistent toxic substances found in the enviroruiient and are of
great concern because of their widespread occurrence (Peakall,
1975). Extensive scientific literature addresses the metabolism
of PCBs in living organisms and several excellent works concern-
ing microbial degradation of PCB5 have been published. Ahmed and
Focht (1973) described the degradation of PCBs by two species of
Achromobacter and the kinetics of PCB degradation by some fresh
water bacteria have been investigated by Wong and Kaiser (1975).
Tucker et al. (1975) and Baxter et al. (1975) reported that with
certain multi—component commercial products, some PCB isomer
mixtures were biodegraded more rapidly than if present as a
single compound.
Liu (1980) investigated the stimulation of PCB biodegradation
by sodium ligninsulfonate. It was reported that the rate of bio-
degradation of monochlorinated Aroclor 1221 could be greatly
enhanced by growing Pseudomonas sp. 7509 in a stable PCB-
ligninsulfonate emulsion. The importance of using lignin-
sulfonate to stabilize the PCB emulsion was reflected by its
ability to stimulate the growth of Pseudomonas sp. 7509 growth
rate as shown in Figure 25. It can be seen that Pseudomonas sP.
7509 rapidly used the stable Arochior 1221-sodium ligninsulfonate
emulsion as the sole carbon and energy sourCe for growth. With-
out ligninsulfonate, the emulsion tended to break down with
consequent decline in both the growth rate and the rate of PCB
biodegradation. However, sodium ligninsulfonate, itself, did not
appear to be utilized in the earlier stage of biodegradation
and it supported little microbial growth by itself. Liu (1980)
concluded that the stimulation of PCB degradation by sodium
ligninsulfonate was due to its inherent resistance to microbial
attack, which enables a stable PCB emulsion to be maintained.
This helped the cells to overcome the substrate-surface area
limitation which might otherwise have been a major limiting
factor governing the rate of subsequent PCB degradation.
Liu and Strachan (1981) investigated the effect of nitrogen
enrichment in the growth medium on anaerobic PCB biodegradation
(Table 10). The data show that yeast extract stimulated PCB
degradation, in agreement with other studies (Watanabe, 1973;
Suzuki, 1977). Peptone, however, tended to have some inhibitory
effect on PCB biodegradability. Arnmonium sulfate, ammoniuin
nitrate and urea did not exhibit any significant stimulation
or inhibition when compared with sodium nitrate, which was the
nitrogen source in the basal medium. These results are not in
general agreement with those obtained by A.ranha and Brown (1981)
in which hydrocarbon biodegradation was observed to be affected
by the nitrogen source.
79
-------
0.4
4J 03—
w
>1
0.2 —
0.1 —
0_
0 10 20 30 40 50 60
Figure 25. Effect of sodium ligninsulfonate on the growth of
Pseudomonas sp. 7509 (Liu, 1980).
I I I I I
—A
/— -
£ Aroclor 1221
A Aroclor 1221 + sodium
ligninsulfonate
Sodium ligninsulfonate
U
A
/ U U
_ • • I L •
80
-------
TABLE 10. DEGRADATION OF PCB IN FERMENTORS (Liu and Strachan, 1981)
Reaction Conditions
Induction
Period
(days)
Degradation
t½ (day)
k
(h
—1
) x 10
2
Aerobic metabolism PCB
2.1
0.36
7.4
Aerobic co-metabolism PCB
2.5
0.52
5.1
Anaerobic metabolism PCB
13.0
190
0.014
Anaerobic co-metabolism PCB
20.0
>200
—-
*
Nitrogen source
NaNO 3
1.2
0.63
4.2
(NH 4 ) 2 S0 4
1.2
0.75
3.5
NH 4 NO 3
1.2
0.85
3.1
Urea
1.2
0.61
1.9
Peptone
1.9
1.2
2.3
Yeast extract
1.2
0.36
7.3
*
Experiments were carried out under anerobic metabolism conditions.
Trichlorobenzene (TCB )
Early studies (Chamber et al., 1963; Malaney and McKinney,
1966) concluded that trichlorobenzene (TCB) biodegradation is
negligible. Garrison (1969) suggested volatilization as the
major mechanism of TCB removal from water, but Gaffney (1976)
found di- and trichlorobenzenes in river sediments, indicating
that TCBs can persist in such environments. Simnions et al. (1976)
reported mineralization of l,2,4-TCB in activated s1u e, with
reduction in TCB volatility in the high-organic sludge environment.
The biodegradation rates of the individual TCB isomers, and the
influence of nutrient additions on TCB degradation were investigated
by Marinucci and Bartha (1979).
Glucose and benzene caused a 20 to 50% increase in the bio-
degradation rate compared with a control. Dichlorohexane and
dichlorophenol, used primarily to enrich for dechlorinase activity,
did not appreciably effect the biodegradation rate. The biodegrada-
tion rates in the dichlorobenzene and forest litter treatments were
slightly lower than the control rate.
Soil organic matter (compost) had little direct influence on
TCB mineralization, but a significant abiotic effect of high organic
matter content was the reduction in volatility of both TCBs. In a
field disposal situation, this would reduce volatility losses and
allow the relatively slow microbial degradation processes a longer
time period to act.
-------
The kinetics of TCB biodegradation suggest rate-limiting
reactions of the cometabolic type. However, in these experiments
none of the substrates added to soil increased TCB biodegradation
to a significant extent.
Hydrilla sp. Weed
Due to the lack of sound quantitative information on plant
decay rates, a study was performed to derive a rate function for
plant degradation by bacteria (Waite and Kurucz, 1977). Bacteria
capable of degrading plant material were isolated and introduced
to samples of the rooted hydrophyte Hydrilla sp. Figure 26 shows
the dependency of the degradation rate constant on nitrate
concentration. It can be seen that the rate appears to be inverse-
ly proportional to nitrate concentration, at least in the concen-
tration range utilized in these experiments. It is not clear why
this occurred, as one should expect an increase in biodegradation
activity with increasing nitrate. It is speculated that nitrate
levels were high enough to adversely affect the degradation process.
The model proposed shows good agreement with observed data, but is
limited to nitrate-nitrogen levels lower than 1 mg l1.
Summary
The concentration of available nutrients is an important
environmental factor affecting the extent and rate of biodegrada-
tion. Nutrients may or may not be limiting depending on the
availability of readily biodegradable carbonacous substrates.
Nutrients may also exhibit inhibitory effects on biodegradation.
Several studies suggested that nitrogen and phosphorus
may limit biodegradation of hydrocarbons in marine and fresh
water environments. However, one study demonstrated that the
concentration of nitrogen occurring naturally in sea water would
not affect the rate of biodegradation of a petroleum hydrocarbon.
In general, the available data indicate that low concentrations
of phosphate in marine environments are the principal factors
limiting petroleum biodegradation, providing adequate aeration
and favorable temperatures are provided.
Several studies have shown that PCB isomers are biodegraded
more rapidly in a mixture than by themselves. It has also been
observed that the addition of biphenyl enhances the biodegradation
of some PCB’s. The stimulation of PCB biodegradation in the
presence of ligninsulfonate has been demonstrated, and it was in-
dicated that this enhancement is due to the PCB-ligninsulfonate
emulsion’s increased susceptibility to microbial attack and its
support of microbial growth. It has also been shown that nitrogen
enrichment stimulates the biodegradation of PCBs.
A study on the effect of cosubstrate enrichment for malathion
degradation by addition of n-heptadecane indicated a significant
increase in the biodegradation rate. This study lends support to
82
-------
N0 3 -N (mg/L)
Figure 26,
Dependence of decay rate on N0 3 -N concentration
(Waite and Eurucz, 1977).
0.08
0. Ob
0.04
0.02
0
0.02
1 2 3 4 5
6
83
-------
the supposition that the biodegradation of recalcitrant compounds
may be influenced by the addition of selected organic compounds.
It has also been shown that cosubstrate enrichment for biodegrada-
tion of other pesticides may either inhibit or stimulate biodegrada-
tion. Several studies indicate that nitrogen sources may have a
significant effect on the biodegradation of certain hydrocarbons.
TOXINS/INHIBITORS
The toxic and inhibitory effects of heavy metals and organic
toxins on specific microorganisms have been described in the
literature. However, definitive information on the effect of
inorganic and organic toxins on biodegradation is greatly lacking.
Even though many heavy metals are essential for growth, they
are also reported to have toxic effects on cells, mainly as a
result of their ability to denature protein molecules. As a
result of the chemical and biological factors that affect the
toxicity of a heavy metal, a given concentration of that metal
may be inhibitory under a given set of conditions and non-
inhibitory under other conditions. It is not surprising, there-
fore, that a significant amount of data in the literature is
apparently contradictory, in that certain concentrations are
reported to be harmless. In many cases, these differing effects
of concentration are due to specific environmental conditions of
the microbial community.
A substantial body of literature exists that describes toxic,
antagonistic, and synergistic effects of heavy metals, inorganic
anions, and organic chemicals on conventional biological treatment
processes. Biological treatment can be accomplished in a number
of ways, but the basic characteristic of the system is the use of
a mixed (heterogeneous) bacterial culture for the biodegradation
of organic materials. By defining the effects of inorganic and
organic toxins on the efficiency of common biological treatment
processes (or biodegradation processes) , one can better speculate
on the effects of such toxins on microbial communities and
biodegradation processes in other natural systems. A summary of
the major inhibitory effects of specific inorganic and organic
elements and compounds is given in Tables 11 and 12. The follow-
ing summarizes the currently available data on the inhibitory
effects of specific elements and compounds on biological treat-
ment.
Summary of Inhibitory Properties of Inorganic Substances
Ammonia--
At excessively high levels (480 mg/i) , ammonia exhibits in-
hibitory effects on the activated sludge process (EPA, 1973) . At
concentration levels of 1500 to 3000 mg/i, ammonia is inhibitory
to anaerobic digestion (Pohiand and Kang, 1971).
84
-------
TABLE 11. THRESHOLD CONCENTRATIONS OF INORGANIC POLLUTANTS
THAT ARE INHIBITORY TO BIOLOGICAL TREATMENT PROCESSES.
(U.S. EPA, 1977)
POLLUTANT
CONCENTRATION (mg/i)
ACTIVATED SLUDGE
ANAEROBIC
NITRIFICATION
PROCESSES
DIGESTION
PROCESS
PROCESSES
Ammonia 480 1500
Arsenic 0.1 1.6
Borate (Boron) 0.05—100 2
Cadmium 10—100 0.02
Calcium 2500
Chromium 1—10 5—50 0.25
(Hexavaient)
Chromium 50 50—500
(Trivalent)
Copper 1.0 J.0—10 0.005—0.5
Cyanide 0.1—5 4 0.34
Iron 1000 5
Lead 0.1 0.5
Manganese 10
Magnesium 1000 50
Mercury 0.1—5.0 1365
Nickel 1.0—2.5 0.25
Silver 5
Sodium 3500
Sulfate 500
Sulfide 50
Zinc 0.08—10 5—20 0.08—0.5
Note: Concentrations shown represent influent to the unit processes
in dissolved form.
85
-------
TABLE 12. THRESHOLD CONCENTRATIONS OF ORGANIC POLLUTANTS THAT
ARE INHIBITORY TO BIOLOGICAL TREATMENT PROCESSES
(U.S. EPA, 1977) ______________________
CONCENTRATION (mg/i )
ACTIVATED ANAEROBIC NITRIFI-
SLUDGE DIGESTION CATION
POLLUTANT PROCESSES PROCESSES PROCESSES
A 1 c oh 01 S
Allyl 100 19.5
Crotonyl 500
Heptyl 500
Hexyl 1000
Octyl 200
propargyl 500
phenols
Phenol 200 4-10
Creosol 4-16
2—4 Dinitrophenol 150
Chlorinated Hydro-
carbons
Chloroform 10-16
Carbon Tetrachloride 10-20
Methylene Chloride 100-500
1-2 Dichioroethane 1
Dichiorophen 1
Hex achiorocyc lohexane 48
Pentachiorophenol 0.4
Tetrachloroethylene 20
1, 1, 1, —Trichioroethane 1
Trichioroethylene 20
Trichiorofluoromethane 0.7
Trich lorotri f louroethane
(Freon) 5
Allyl Chloride 180
Dichiorophen 50
Organic Nitrogen Compounds
Acrylonitrile 5
(Continued)
86
-------
TABLE 12. (Continued)
CONCENTRATION (mg/i )
ACTIVATED ANAEROBIC NITRIFI-
SLUDGE DIGESTION CATION
POLLUTANT PROCESSES PRiCESSES PROCESSES
Organic Nitrogen Compounds
(Continued)
Thiourea 0.075
Thioacetamid 0.14
Analine 0.65
Trinitrotoluene (TNT) 20-25
EDTA 25 300
Pyridine 100
Surf act ants
Nacconol 200
Ceepryn 100
Miscellaneous Organic
Compounds
Benzidine 500 5
Thiosemicarbazide 0. 18
Methyl isothiocyanate 0.8
Allyl isothiocyanate 1.9
Dithio-oxamide 1. 1
Potassium thiocyanate 300
Sodium methyl
dithiocarbamate 0.9
Sodium c3imethyl
dithiocarbamate 13. 6
Dimethyl arnrnonium
dimethyi
dithiocarbamate 19. 3
Sodium cyclopentamethylene
dithiocarbamate 23
Piperidinium
cyc lopentamethy lene
dithiocarbamate 57
Methyl thiuroniurn
sulphate 6.5
Benzyl thiuronium
chloride 49
(Continued)
87
-------
TABLE 12. (Concluded)
CONCENTRATION (mg/i )
ACTIVATED ANAEROBIC NITRIFI-
SLUDGE DIGESTION CATION
POLLUTANT PROCESSES PROCESSES PROCESSES
Miscellaneous Organic
Compounds (Contd.)
Tetramethyl thiuram
mornosulphide 50
Tetramethyl thiuram
disuiphide 30
Diallyl Ether 100
Dimethyl-
paranitrosoaniline 7.7
Guanidine carbonate 19
Skatole 16.5
7.0
Strychnine
hydrochloride 175
2 chloro—6 trichioro-
methyl-pyridine 100
Ethyl urethane 250
Hydrazine 58
Methylene blue 100
Carbon disuiphide 35
Acetone 840
8—hydroxyquinoline 73
Streptomycin 400
88
-------
Arsenic--
A level of 0.1 mg/i sodium arsenate (arsenic concentration
0.04 mg/i) showed no effect on oxygen uptake, while levels of
1.0 mg/i sodium arsenate and 0.1 mg/i arsenic trichioride
depressed oxygen uptake about 50% (Goss, 1969).
Cadmium--
Cadmium had no adverse effect on the activated sludge pro-
cess up to a concentration of about 1 mg/i. In the range of
10 to 100 mg/i, a decrease in BOD removal efficiency and re-
duction in oxygen uptake was observed (Goss, 1969) . Synergestic
effects have been reported for cadmium and zinc, as well as
cadmium and manganese. other heavy metals may also show syn-
ergistic effects with cadmium.
Chromium--
Chromium has a stimulatory effect on growth at a concen-
tration level of 0.005 to 0.05 mg/i (Rudolphs et al., 1950).
Interference with biological processes is reported at a concen-
tration level of 1 mg/i (Rudolphs, et al. , 1979) to 10 mg/i
(Reid, 1968). The published literature is contradictory with
respect to the toxicity of chromium in the concentration range
of 1 to 50 mg/i, ranging from serious interference to insignifi-
cant effects (U.S. Dept. of HEW, 1-965). In the range of 50 to
500 mg/i, synergistic effects of chromium with acidity, iron,
and copper have been reported (Rudolphs et al., 1950; Goss, 1969;
U.S. Dept. of HEW, 1965).
Copper--
Synergism of copper with cyanide, acidity, and other heavy
metals has been reported. Antagonism of copper with sulfide,
high pH, and certain chelating agents such as EDTA have been
identified (Loveless and Painter, 1968). Over the range of
copper concentration of 0.1 to 10 mg/i, digestor problems
attributed to the presence of copper were reported that may
have been due to antagonistic or synergestic effects (RudolphS
et al., 1950).
Cyanide--
Cyanide concentrations of 5 mg/i have been found to inter-
fere with the activated sludge process (Rudolphs et al., 1950).
It has been reported that the toxicity of copper and nickel
are enhanced by the presence of cyanide (U.S. Dept. of HEW, 1965).
Iron——
Iron is a necessary element for microbiological growth and
its absence causes a reduction in metabolic activity (Pfeifer
and White, 1964). It is reported that 1000 mg/i stops oxygen
uptake (Goss, 1969). A specific effect of iron synergism with
chromium has been reported (EPA, 1976). Antagonistic effects
may be anticipated with sulfide and hydroxyl ions.
89
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Lead--
Moderate toxicity of lead to microorganisms has been reported
for concentrations ranging from 0.1 to 1 mg/i. A significant
effect on oxygen uptake in the presence of lead is noted at a
concentration level of 10 to 29 mg/i (Rudolphs et al. , 1950).
Manganese--
Synergestic effects of manganese with zinc and cadiurn have
been reported. Oxygen uptake was completely inhibited at 50 mg/i
of manganese (Goss, 1969).
Mercury- -
Mercury at a concentration of 0.1 mg/i was reported to re-
duce the oxygen uptake by 10% in the activated sludge process
(Brinsko, 1974). For concentrations ranging from 1 to 200 mg/i,
there are numerous reports of different degrees of inhibitory
effects on the activated sludge process (Zugger and Ghosh, 1972;
Goss, 1969). In experiments performed by Marinucci and Bartha
(1979) involving the biodegradation of t çhlorobenzene (TCB)
in a soil environment, consistently more CO 2 was evolved from
radio-labeled TCBs when incubated in normal as compared with
HgCl or NaN poisoned soil (Table 13). A comparison of 1,2,3-
and l,2,4-TdB biodegradation rates show that 1,2,4-TCB was degrad-
ed two to three times as fast as l,2,3—TCB in active soil.
TABLE 13. MINERALIZATION OF TCBs IN BIOLOGICALLY ACTIVE VEPSUS
POISONED SOIL
TCB Study
Mineralization
rate (nmol/day per
20 g of
soil)
Active
soil
Poisoned soil
Poison
(1%)
1,2,3—
1,2,4—
A
B
A
B
C
033 -i-
0.38 ±
1.09 -F
0.93 +
1.37 ±
0.13
0.35
0.12
0.35
0.13
0.09 -F 0.12
0.16 ± 0.35
0.05 -f 0.12
0.20 + 0.35
0.04 + 0.13
HgC1 2
NaN 3
HgCl 2
NaN 3
NaN 3
Nickel——
Various adverse effects on oxygen uptake for the activated
sludge process have been reported for nickel concentrations of
2.5 to 200 mg/i (Rudolphs and Ainberg, 1952; Barth et al. , 1965;
Goss, 1969).
90
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Silver--
Silver is extremely toxic to microorganisms. A concentra-
tion of 5 mg/i causes a 84% inhibition of the activated sludge
process. At the 25 mg/i level, inhibition is complete (Goss,
1969)
Sulfide--
Excessive levels of sulfide (25 to 50 mg/i) interfere with
the activated sludge process by depleting the oxygen supply
(EPA, 1973).
Zinc--
Adverse inhibitory effects have been reported for zinc for
0.08 to 0.5 mg/i range (EPA, 1973). Synergistic effects have
been observed for zinc and cadmium, and zinc and manganese (Goss,
1969)
Summary of Inhibitory Properties of Organic Substances
Phenols--
Phenol slug doses of 200 mg/i can deactivate activated slug
and other aerobic treatment plants by killing the biomass
(Beychok, 1967).
Chloroform--
Continuous doses of chloroform at 16 mg/i or more in raw
sludge feed are reported to cause inhibition of anaerobic di-
gestion. Doses at concentrations of between 10 and 15 mg/i
produced a noticeable drop in gas yield during anaerobic di-
gestion (Stickiey, 1970; Ghosh, 1972). Another investigation
(Swanwich and Foulkes, 1971) found a 50% gas reduction due to
0.96 mg/i of chloroform.
Carbon tetrachioride--
Carbon tetrachioride can inhibit anaerobic digestion at
levels of 10 mg/i (Jackson and Brown, 1970). In fact, a 50
percent reduction in methane production was reported at 2.2
mg/i (Swanwick and Foulkes, 1971).
Methylene Chloride--
Methane production in anaerobic digestion was reduced by 50
percent in the presence of 100 mg/i of methylene chloride
(Swanwick and Fouikes, 1971)
Pesticides-—
One laboratory test revealed that two pesticides, aidrin
and simazine, were not inhibitory to the growth of nitrifying
bacteria, Nitrobacter , whereas five other pesticides including
chlordane, heptachlor, lindane, CIPC, and DDD prevented growth.
Heptachior was the most deleterious compound (Winely and Clemente,
1970).
91
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The inhibition of linuron degradation by diazinon was report-
ed by Keckes and Cserhati (1977). A concentration of 30 ppm
applied to carbonaceous soil containing 30 ppm linuron decreased
the decomposition rate by 90% compared to a control sample.
Acrylonitrile--
Inhibitory effects of acrylonitrile on anaerobic digestion
are reported at 5 mg/i (Jackson and Brown, 1970). Another
investigation (Lank and Wallace, 1970) reports that more than
20 mg/i of acrylonitrile in sludge is not harmful to anaerobic
digestion.
Surfactants---
Laboratory tests with the anionic surfactant Nacconol (at
100 mg/i) showed a stimulatory effect on the activated sludge
process. At concentration levels greater than 200 mg/i, in-
hibitory effects were noted. These effects were worse at low PH
(about 5) and low sludge loadings (Manganelli, 1948).
In another laboratory test with the cationic surfactant
Ceepryn, 100 mg/l of this material suppressed oxygen uptake.
The effect was more deleterious at high pH (About 9) (Manganelil,
1948)
Summary
The inhibitory, antagonistic and synergistic effects of
inorganic and organic substances on biological treatment
processes have been described. Inhibitory concentrations Of
specific elements and compounds reported in the literature are
often contradictory. However, in consideration of the many
chemical and biological factors that may affect inhibition,
it is not surprising that certain concentrations of a given
substance have been reported as being inhibitory, while higher
concentrations have been reported as harmless.
WATER AVAILABILITY
The effects of water availability on biodegradation in
aqueous and non-aqueous environments are discussed in this
section.
Aqueous Environment
Water availability in the aqueous environment is usually
expressed in terms of water activity, osmotic pressure, ionic
strength or salinity. In early work, the water content of the
environment was the widely used measure of water availability.
As Mossell (1975) and Corry (1978) have pointed out, this is not
very satisfactory, as the properties of, for example, food
systems, can vary significantly though being of similar water
content. Another measure popular with early workers was osmotic
92
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pressure. This has been discussed by Brown (1976) , who commented
on the difficulty of accurately measuring the osmotic pressure in
many systems. Scott (1977) suggested that a suitable measure of
water availability was the water activity, a , of the equilibrium
system. The effect of ionic strength and sa inity on water avail-
ability is usually measured in terms of their influence on a
values.
The water requirements of microorganisms can be expressed
quantitatively in the form of the water activity (au) . Water has
an aw value of 1.000; this value decreases when solutes are dis-
solved in water. Microorganisms can grow in media with a values
between 0.99 and about 0.63. Bacteria generally require edia
of higher a value (0.99-0.93) than either yeast or molds (Rose,
1976). The range of a from just below 1.00 to 0.96 covers the
normal fresh water, brackish water, and sea water environments
in which most microorganisms exist.
A variety of microorganisms exist that have their growth
optima at an a close of 0.99, but are capable of growth at a
low a , i.e., L60. These are classified as xenotolerant organ-
isms ‘ Brown, 1976).
-‘An organism’s response to a low a can depend on whether the
reduction in a in the external environment is due to high salt
levels or high”non—electrolyte levels. This is not surprising
as the ionic strength of the external medium would be expected to
affect the charge distribution on the cell surface (Reid, 1980)
For any one organism, the important values are the optimum
and minimum a values. These have been determined for a number
of microorgan sms, and they seem to be remarkably constant for a
particular species. As other environmental factors (e.g.,
temperature, pH, p0 2 , ionic and nutritional composition) deviate
from their optimum, the range of tolerance of organisms decreases.
The general effect of lowering the a value of the medium below
the optimum is to increase the length of the lag phase and to
decrease the growth rate. Water activity exerts its most obvious
effects on biodegradation when it falls below a critical a
value. Water activity a values may be applied as a predictive
tool to indicate if biodegradation by specific microorganisms is
possible or unlikely. A large volume of literature exists on the
effects of water activity (a ) on the growth of microorganisms;
however, data are lacking on the effect of this environmental
factor on biodegradation.
The cell-water interface is essentially an ionic one, and
small changes in the ionic composition induce large changes in
microbial physiology. Ionic strength affects osmotic pressure,
or differences in ionic or solute concentrations on opposite
sides of the microbial cell membrane.
93
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In addition to affecting osmotic pressure, high salt con-
ceritrations tend to denature proteins, i.e., disrupt the terti-
ary structure which is essential for enzymatic activity.
Changes in ionic composition are directly influenced by other
physiochemical factors (e.g., pH, Eh, temperature, atmospheric
composition) as well as the metabolic activity of the microbes
themselves. In addition to the overall ionic strength of the
environment, the type, charge, valence, and size of the pre-
dominant ions probably influence microbial events and thus
biodegradation. Data on the affects of ionic strength on bio-
degradation were not found in the literature reviewed.
There is also a scarcity of information available on the
effect of salinity on biodegradation. A pertinent study by
Bourquin and Przybyszewski (1977) reported on the effect of
salinity on the biodegradation of nitrilotriacetate (NTA) by
a estuarine bacteria. A known NTA-degrading bacterium, isolated
from freshwater streams, Pseudomonas sp., was grown on 0.1%
NTA as a sole carbon source in the presence of various NaC1
concentrations. Figure 27 shows that NTA degradation was in-
versely related to salinity under these conditions. Biodegrad-
ation of NTA by the organisms was completely inhibited at 20%
salinity. The organism grew readily during the first 24 hours
of incubation in freshwater medium, but a 48-hr and 72-hr lag
occurred in 10 and 15% salinity media, respectively. It is im-
possible to speculate on the effect of salinity on the biodegrad-
ation of other compounds because of lack of pertinent data.
Non-Aqueous Environment
Water availability may be more critical in non-aqueous
environments than in aqueous environments. In addition to the
water quality (e.g., ionic strength, salinity, etc.) concern
for aqueous environments, water availability in non-aqueous
environments (such as soils) can also be affected by secondary
factors such as medium structure (especially porosity and parti-
cle size), weather conditions (e.g., temperature, humidity,
precipitation, etc.), and composition of the medium (Gray et
al. , 1968)
The pore space in a non-aqueous medium is either filled
with air, as in dried soils, or filled with water, as in Water—
logged soils. In the first case all life processes practically
cease, in the latter case anaerobic processes predominate. The
air-water ratio in the pore space is of utmost importance for
determining the type of biological processes occurring in non-
aqueous environments.
Water in the soil environment can be classified as gravita-
tional, capillary, osmotic, and hygroscopic. Not-all of
these fractions of water are available for microbial activities.
In order to utilize water, a growing organism must expend the
94
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100
75
-I
‘ .0 i
U i j
a)
El
Ficiure 27.
50
25
0
INCUBATION (days)
Effect of salinity on the rate of NTA äd tionby Pseudomonas sp. All
cu1tui es were inbubated in BS rñedium plus 0.1% NTA with CaC1 added to the
desired salinity (Bourquin and Przybyszewski, 1977)
20% Salinity
15% salinity
fresh water
0
10% salinity
1 2 3 4 5 6 7 8
-------
energy or pressure required to remove water from soil. Much
depends on the types and sizes of the soil particles, the char-
acteristics of the aggregates, and on the concentration of the
ions in the water phase. Gray et al. (1968) showed that the
pressure required for removing gravitational water is relatively
low, in the range of 0 to 0.3 atm. But for capillary, osmotic,
and hydroscopic waters, the pressures required are as high as
0.3 to 15, 15 to 150, and above 150 atm, respectively.
A review of the literature revealed that no information is
available on the availability of the above-mentioned water
fractions for microorganisms. In soil environments, water
availability is usually measured in one of o ways: total
moisture content or percent field capacity. Gravitational
water, as mentioned previously, is equivalent to water content
that exceeds the field capacity.
In general, biodegradation rates increase with increasing mois-
ture content up to a certain moisture level. Walker (1974)
in his biodegradation study of napropamide, found that the bio-
degradation rate increased exponentially with soil moisture
content, as can be expressed by the following equation:
k =
where k is the biodegradation rate in terms of day ; M is the
percent moisture content by weight; and m and n are constants.
For napropamide, the m and n values are 0.0037 and 0.550, respect-
ively. A soil moisture effect study was conducted by Lay et al.
(1975) for the biodegradation of propanil. The authors found
that when the soil moisture content was about 1.5% (by weight),
the residual propanil was 27 to 30% of that originally present.
But when the soil moisture content increased to 5.5 and 12.6%
(by weight), residual propanil was reduced to 18 and 9.6%,
respectively. Similar trends in the effects of soil moisture
content on the biodegradation of parathion were also found by
Gerstle et al. (1979). The authors found that with three soil
moisture contents (14, 24, and 34%, by volume), tite rate of
parathion biodegradation rose with increasing water content.
Moisture exerts its most obvious effect when it falls below
some critical value. Howard et al. (1979) reported that for
the biodegradation of litter such a critical value may be as
high as 27 to 100% moisture content (by weight). Above the
critical value, the effects of moisture on biodegradation are
*
Field Capacity: The maximum moisture content that a soil or
a solid material can retain in a gravitational field without
producing continuous downward percolation.
Percent moisture content or field capacity can be expressed
based on either weight or volume.
96
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insignificant. A formula similar to the Michaelis-Mentefl
Equation was suggested as a means of expressing the effects of
moisture on biodegradation rates (Flanagan et al. , 1976; Bunnell
et al. , 1977; and Howard et al. , 1979)
M
a 1 + M a 2 + M
where c is the correction factor for the biodegradation rate; N
is the moisture content; a 1 is the moisture content at which
biodegradation is half its “optimal’ value; and a is the mois-
ture content at which gas exchange is half its “o timal” value.
In contrast to the above-mentioned trend in the effect of
moisture content on biodegradation, Nakas et al. (1979) found
that in field testing, the decomposition of bacterial and fungal
cell walls demonstrated an inverse relationship with soil water
content (Figure 28). However, because several other critical
environmental factors associated with the tests were undisclosed,
the correct interpretation of such data is indeed difficult.
It is speculated that other factors (such as temperature, pH,
etc.) might have had a more pronounced influence on biodegrad-
ation than that of moisture content. Thus, the results of Nakas
et al. (1979) may not reflect the effects of water content as
indicated.
Other researchers have selected field capacity (or water-
holding capacity) as an indicator of water availability in soil
environments. Gray et a!. (1968) found that microbial activity
increased with increasing water content to the critical values
of about 60 to 80% field capacity.* Zimdahl et al. (1977) re-
ported that at zero percent field capacity, trifluralin did not
appear to degrade. However, the extent of biodegradation was
positively correlated with soil water content. After three
weeks, biodegradation of trifluralin was more extensive at 100%
of field capacity than at lower levels. After 3 months, the
ranking of the effects of water content on biodegradation was
100% > 50% > 20% = 0% of field capacity. At 6 months, the
ranking was 100% > 50% > 25% > 0% of field capacity. Helweg
(1979) reported that the biodegradation of 2-aminobenzimidazole
increased exponentially from 28% to 94% of field capacity. He
also found that when the water content was too high, bioclegrad-
ation rates decreased. Marinucci et al. (1979) found that a
lowering of the soil moisture level from 66% to 40% of field
capacity did not affect significantly l,2,3-TCB biodegradation,
but decreased the biodegradation rate of l,2,4-TCB from 1.09 to
*
Unless otherwise indicated, percent of field capacity mentioned
in this report is on a weight basis.
97
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100 1 1 1
80 (A) . fraqariae
- C. lividiurn
—
60
(B) - Trichodexrua sp.
80 Aspergillas sp.
—— Penicilliurn sp.
z60
MOISTURE CONTENT (%)
Figure 28. Biodegradation of (A) bacterial cell wall, and
(B) fungal cell wall in a semi-arid grassland
soil (Nakas et al. , 1979)
9
-------
0.31 nmol/day. Heiweg (1981), in a study of rnaleic hydrazide
biodegradation, reported that at soil moisture contents between
the wilting point and 80 to 90% of field capacity, the degrada-
tion rate doubled with an increase in moisture content of 50% of
field capacity. Above field capacity, the degradation rate was
either unchanged or decreased. Below the wilting point of the
soil, the degradation rate was extremely low.
Although water availability in the non-aqueous environment
is an essential factor for biodegradation, researchers have yet
to derive a theoretically based model. Detailed knowledge of
the influence of important secondary factors, such as soil
structure, particle size, or reduction of the water availability
through osmotic and adsorption processes, is greatly lacking.
Another concern is the choice of indicators of water availabil-
ity. Measurements of the moisture content of soils do not
relate to the ability of organisms to absorb and utilize soil
water (Gray et al. , 1968). An energy or pressure indicator,
such as vapor pressure, or terms representing other character-
istics of the medium, water composition, and organism types may
have to be incorporated into the quantitative evaluation of the
effects of water availability on biodegradation of chemicals.
99
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SECTION 5
BIOLOGICAL ENVIRONMENTAL VARIABLES
OVERVIEW
In addition to the constraints imposed upon biodegrading
populations by the physical and chemical environment, the activ-
ity of neighboring populations acts as an additional external
factor affecting the dynamics of growth and physiological be-
havior (Gause, 1934) . In theory (Slater and Bull, 1978) , for
microbial populations in a continuous culture acting upon a growth-
limiting substrate, one organism can competetively displace all
others since the chance of two organisms having identical maximum
specific growth rates, substrate affinities, energy requirements,
and growth yields is exceedingly small. However, the real world
does not ordinarily behave as a chemostat with a single, growth
limiting substrate. According to Slater and Bull (1978) it is
common, especially where xenobiotics are being studied, to find
communities of microorganisms with two types of populations:
primary and secondary. Primary species are those which metabo-
lize the primary substrate, whereas secondary species cannot
grow on the primary substrate but rely on metabolit.es of the
primary species and/or lytic products to sustain their growth.
The importance of microbial interactions in affecting
chemical biodegradation is obvious, e.g., xenobiotics which can
be metabolized by a single microbial species will persist if the
species is eliminated by another organism. Yet despite the
wealth of literature on microbial interactions, relatively little
is known about interactions between microbes in situ. Most of
the information has been derived from laboratory studies on
simple mixed populations, which precludes an evaluation of higher
order interactions between multiple microbial species and also
between the microbiota and the various physicochemical environ-
mental factors. However, because of the apparent importance of
interactions between microbes to their ecology and population
dynamics, a brief discussion of various types of interactions
is presented.
In some instances, mathematical relationships have been
developed in attempts to model basic microbial interactions.
The models are, as yet, useful only for specific sets of circum-
stances (e.g., specific microbial populations, substrates, and
environmental conditions), and describe only population dynamics.
100
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Because of the complexity of microbial interactions, it is
difficult to be certain that simple interactions have not been
obscured by other interactions. For these reasons, mathematical
expressions describing microbial interactions which can be used
in explaining biodegradation phenomena are generally unavailable.
MICROBIAL INTERACTIONS
Basic Types of Interactions
The association of two or more microbes is usually defined
in terms of their nutritional needs. These associations can be
described by a few basic types of interactions between hypothet-
ical populations A and B, coexisting in a natural environment.
There are, in fact, only three possible responses a growing
population, e.g., A, can make in the presence of population B.
These are (Slater and Bull, 1978)
1. The growth of population B may have a beneficial
or positive effect on the growth of population A;
2. The presence of organism B could have a detrimental
or negative effect on organism A; and
3. The growth of population B may have no effect on
the growth of population A. A neutral response
of this kind would be shown by similar growth
patterns for population A whether or not popula-
tion B was present.
These basic responses by A concerning B are, of course,
reciprocal, inasmuch as the presence of organism A can evoke a
similar or different response from organism B. The various
combinations between the two populations may be summarized in the
simple matrix indicated below (Table 14)
TABLE 14. MATRIX OF INTERACTION OF TWO MICROBIAL POPULATIONS A
AND B (Slater and Bull, 1978)
The effect on the growth of A
by the activity of organism B
+ 0 -
(positive) (neutral) (neqative)
The
effect on the growth
+
++
+0
of
organism B by
(positive)
0
0+
00
0—
the
activity
of
(neutral)
-
—+
-0
--
org
anism A
(negative)
101
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For two membered mixtures, Table 14 illustrates nine differ-
ent interactions between the organisms, and indicates a maximum
of six basic types of interactions, defined as follows:
1. Neutralism (oo)
2. Mutualism (++)
3. Cornmensalism (+0 or 0+)
4. Aniensalism (—0 or 0-)
5. Prey-predator relationships N-- or -+)
6. Competition (--)
In reviewing the above list, it is initially apparent that
neutralism or non-interaction between component species can be
excluded from the list because of its insignificance with regard
to microbial interaction. Though a limited number of studies
(e.g. , Lewis, 1967) have indicated that neutralism does occur,
the growth of any microbial population will induce changes in
that environment which will likely affect the growth of the
second population. The remaining interactions listed above will
be described in this section.
Mutualism (++)--
In this type of interaction, each member in a mixture de-
rives some benefit from the other’s presence, either in the form
of increased growth rate or increased population size. The
types of relationships from which both species benefit are
particularly varied. Interactions can range from a loose coopera-
tion which is not essential for the survival of the interacting
species, to an obligate association on which both species depend
for their continued survival (symbiosis) . Alternatively, two
organisms may interact to degrade a compound or produce a product
that either was incapable of degrading or producing independently.
Such a relationship is termed synergism. Observed interactions
often do not fall nearly into these categories and usually show
the characteristics of more than one type of interrelationship.
Reviewed literature indicated that few studies have positive-
ly identified a symbiotic or synergistic microbial degradation of
xenobiotic compounds. Gunner and Zuckermann (1968) demonstrated
the synergistic microbial degradation of diazinon, but the
utilization of diazinon for growth was not demonstrated.
Daughton and Hsieh (1977) maintained growth of a multispecies
community for more than 2 years in a continuous culture with
parathion as the sole substrate. Since competition, if the
only interaction between species, would necessarily lead to mu-
tual exclusion of all but one species (Jannasch and Mateles,
1974) , the authors assumed a symbiotic interaction existed.
This assumption proved correct when it was shown that parathion
102
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was hydrolyzed by a strain of Pseudomonas stutzeri and the
resultant p-Nitrophenol was utilized by a strain of P. aeruginosa .
Neither of the species could perform each other’s role, but they
could grow symbiotically on parathion in batch and continuous
culture. Therefore, P. stutzeri probably grew on metabolic pro-
ducts from P. aeruginosa .
A mutualistic relationship demonstrated by Yeoh et al. (1968)
involved a two-membered mixed culture of Bacillus polymyxa and
Proteus vulgaris grown in a carbon-limited chemostat in a simple
growth medium which could not sustain either population alone.
That the populations were able to exist together under these
conditions indicated a dependence of one population on the other
to complement its minimum growth requirements. But instead of
organisms existin in steady-state in the continuous culture,
regular oscillations in the populations were observed, which were
attributed to a third interaction between the two populations.
Evidently P. vulgaris produced a proteinaceous compound which
inhibited the growth of B. polymyxa and caused a decrease in
its population size. This in turn reduced the rate of biotin
addition to the environment and, as its concentration declined,
it could not maintain the original Proteus population size which
also went into decline. At a later state the concentration of
the inhibiting protein was lowered sufficiently to cause a re-
surgence of the B. polymyxa population, completing the cyclical
changes of the two populations, which were then repeated. This
example illustrates one of the major difficulties in population
interaction studies; i.e., it is difficult to be certain that
all the contributing interactions have been recognized or that
the postulated simple interactions have not been obscured by
other interactions. These difficulties become particularly acute
in attempting to construct quantitative models with mathematical
formulations of the interactive forces between different popula-
tions.
Cominensalisrn (+0 or 0+)--
Many bacteria produce substances that promote the growth of
other species. Such a phenomenon is probably the most widespread
form of commensalism. In these situations, the microorganism
producing the substances that others use as food may or may not
have received benefit (generally means growth) from the sub-
stance it degraded o transformed. If no benefit was received
by the degrading species, the species is said to have cometaboliz
ed the degraded substance.
A number of studies have appeared to demonstrate cometabolic
degradation mechanisms that ultimately lead to complete degrada-
tion of the subject chemical. In such cases, one or more micro-
organism carries out an initial transformation of the chemical,
with the product of this reaction serving as a growth substrate
for the other population(s) . Thus a microorganism unable to use
a given substrate may live commensally because it obtains
103
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assimilable products that the heterotrophic associate(s) generate
during the degradation of the substrate in question. Extensive
research on the microbial degradation of DDT exemplifies the
cometabolic degradation of xenobiotics. Barker et al. (1965),
Johnson et al. (1967) , and Ledford and Chen (1969) have demon-
strated that microorganisms can catalyze modest changes in the
DDT molecule, converting it to 1, l-dichloro-2, 2-bis (p-chloro-
phenyl) ethene (DDD) and bis (p-chlorophenyl) methane (DDM)
Research by Focht and Alexander (1970) disclosed that DDM could
be further degraded by a strain of Hydrogenornoflas. Pfaender
and Alexander (1972) further demonstrated that the action of two
different bacteria resulted in the extensive biodegradation of
DDT, the enzymes of Hydrogenomonas sp. converting DDT to PCPA,
and those of Arthrobacter sp. degrading PCPA.
There are other ways by which the growth of one population
may stimulate the growth of a cohabitant species. For example,
one section of the population may remove a substance which is
toxic to another or one species may convert an otherwise unavail-
able substrate into a form which is useful to its commensalistic
partner. Alteration in the physicochemical properties of the
microhabitat (e.g., changes in pH, Eh, osmotic pressure, ionic
strength) during growth of one or more unrelated species can
enhance development of the other species. The’ transfer of plas-
mids and genetic recorrthination in bacteria can be considered a
type of coinmensalism, as the recipient may derive an ecological
advantage, such as resistance to inhibitors and greater nutri-
tional capabilities. Although such transfers have not been
demonstrated unequivocably in soil, this form of comrnensalism
would require close proximity between the commensal and the donor.
In many other forms of comrnensalism (e.g., nutritional, detoxifi-
cation, changes in environment) , the actions of the independent
species probably influence commensals in relatively distant micro-
habitats, espEcially if the chemical factors involved are vola-
tile. Although mathematic expressions of the population dynamics
of commensal relationships have been developed, the expressions
are highly specific and merely serve to explain experimental
results.
Amensalism (-0 or 0-)--
An amensal relationship occurs when one population is re-
stricted by the presence of a second, which is unaffected by the
metabolism of the inhibited populations. This kind of harmful
interrelationship may be caused either by the removal of essen-
tial nutrients or by the formation of toxic products, or through
non-specific effects, such as the lowering of the dissolved
oxygen tension or changes in the hydrogen ion concentration
(Slater and Bull, 1978). Although there may be no direct effect
on the inhibiting population, there may well be an indirect
advantage because, by limiting the assimilation of growth re-
sources by the affected populations, a greater proportion
104
-------
of these materials can be made available for growth of the in-
hibiting population.
Predator-Prey Relationships (+— or -+)--
These relationships cause one member of a mixed culture
(predator) to benefit at the expense of a second member (prey)
the latter representing nutrition for the predator. In open-
growth systems or continuous culture experiments, oscillations
of the two populations are typically established, wherein the
growth of the predator population lags behind increases in the
prey population. A number of mathematical models have been con-
structed to describe population fluctuations. However, other
laboratory studies have demonstrated that steady-state conditions
can be achieved in prey-predator interactions, which acts to
discredit the modelling efforts or limit their applicability.
Dent et al. (1976) have concluded that oscillations in predator-
prey populations, as predicted by the Lotka-Volterva model, are
apparently not observed because the prey-predator mixed culture
is “a rather more complex microbial ecosystem composed of a
variety of physiological and ecological interrelationships.”
More recently, Yaron (1981) demonstrated that the interaction of
Bdellovibrio with its prey can be affected by the presence of
other microorganisms regardless of whether they serve as prey
for Bdellovibrio . Different bacteria affected the predator—prey
interaction in different ways: some “competed” with the original
prey for the predator; others enhanced the activity of the preda-
tor toward the original prey, and still others inhibited it.
This case again illustrates the major difficulties in modelling
population interactions: it is difficult to know whether all
contributing interactions have been recognized or that simple
interactions have not been obscured by other interactions.
The effects of predation, as well as other microbial inter-
actions, extend beyond the population dynamics of the microbes
involved. Predation, despite the effect of depression of micro-
bial populations, apparently stimulates mineralization (Barsdate
et al. , 1974) , and can accelerate decomposition by releasing nu-
trients tied up on microbial biomass (Stout, 1974) . Hunt et al.
(1977) developed a model which simulated the effect of predation
on bacteria in a continuous culture. The mcdel was fitted to
data from chemostats on the chemical composition of bacteria
growing in C-, N-, and P-limiting media. The model’s performance
was reasonably successful, and suggested (Figure 29) that preda-
tion effects major changes in the C/N/P (carbon/nitrogen!
phosphorus) ratios of media, thus influencing the availability
of the nutrients for microbial activity and biodegradation.
Notice in Figure 29, however, that the glucose substrate level
increased substantially as the predation rate increased and bio-
mass decreased.
More recent attempts have been made to examine the effects
of bacterial predation in ecosystems without distinguishing the
105
-------
3
120
100
8 - 80
6 - 6O
U)
U)
0
I-1
U
U)
82 20
(-9
0
PREDATION RATE (i g/nti/hr)
Figure 29. Simulated effect of predation on d-lirnited bacteria in a cherTostat
at a dilution rate of 0.45. The predator returns no nutrients
to the bacteria (Hunt et al., 1977)
0 10 20
C’)
0< -
HZ
E- 0
-------
specific activities of individual microbes. In developing mathe-
maticalmodels of biodegradation, practical approaches examining
the bulk impact of the total microfauna can eliminate complex
microbial interactions. DeLeval and Menacle (1979) estimated
the extent of microfaunal predation by batch culture and con-
tinuous culture techniques, without distinguishing the specific
activities of microorganisms. Bottles of river water were pre-
pared with and without predators. In the bottles without pred-
ators, productivity was estimated by:
P = B - B
t 0
Where:
P = bacterial productivity (mg C l 1)
B = bacterial biomass (mg C 1) of the water filtered
through a 8 pm filter
B = bacterial biomass where T = 0
0
Bt= bacterial biomass where T = t(h)
While in bottles with predators
P = N - N + G (6)
t 0
N = bacterial biomass (rag C c 1 ) of the river water
N = bacterial biomass when T = 0
0
N.= bacterial biomass where T = t(h)
1
—1 —1
G = predation (mg C Q t
Thus, combining results from bottles with and without predators,
i.e. , equations (5) and (6):
G=B -B - N + N
t 0 t 0
Results indicated that the bacterial population is not
greatly influenced by predation but should be limited by other
environmental factors.
Competition (- -)--
Competition may be defined as a situation in which the popu-
lations of two species are mutually limiting because of a joint
dependence on a common factor or factors external to them. The
effects of competition on microbial population dynamics have been
demonstrated in a number of studies (Powell, 1958; Tempest et al.,
1967; Brunner et al. , 1968) , the majority of which suggest that a
107
-------
rapid growth rate can give one species the competitive advantage
over another.
Carbon substrates, mineral nutrients, growth factors, O ,
water, light and possibly space can become limiting factors tor
which species within the same microhabitat compete (Alexander,
1971). The extent of competition probably varies between micro-
habitats, depending on their structure, available nutrients, and
other physical and chemical properties. Many environmental
factors (e.g. , pH, Eh, temperature) probably alter the competi—
tive ability of species, primarily by influencing their metabolic
rates and pathways. For example, van Gemerden (1974) found that
the relative abundance of large photosynthetic bacterium ( Chroma
tium weissei ) in natural habitats, normally unable to compete
with a smaller species ( Chromatium vinosum ) , was attributable to
variations in light: in continuous light, with sulfide as the
growth rate-limiting substrate, the specific growth rate of c.
vinosum exceeds that of C. weissei , and the latter is unable
to compete successfully and is washed out in continuous cultures.
With intermittent light-dark illumination, the organisms showed
balanced coexjstencewhen grown in continuous cultures. The
“steady-state” abundance of C. vinosum’was found to be positively
related to the length of the light period, and that of C. weissel
to the length of the dark period.
A number of kinetic models have been developed which describe
competitive interactions between microbes in an open or continuous
culture environment (growing populations are continuously supplied
with a restricted quantity of a required nutrient). In such a
system, the organism with the lower growth rate is eventually
eliminated from the culture. The growth rates of the component
species are influenced, of course, by the affinity of an organism
for the limiting substrate. In most cases the kinetic models
can have a general application to any competitive situation
occurring between two or more organisms under nutrient—limited
conditions in an open (continuous culture) environment.
Although there is little doubt that competition is a major
phenomenon in soil and aquatic ecosystems, conclusive evidence
for most of the mechanisms, in situ, is not available. Many of
the data have been derived from simple laboratory experiments in
which most environmental factors have been kept constant. In
such studies, it is often difficult to distinguish between com-
petition and amensalism.
ADAPTATI ON
An important characteristic of heterotrophs and autotrophs is
their ability to acquire new physiological and/or morphological
traits which enable them to operate under a new set of environ-
mental conditions or metabolize a previously unmetabolizable
substrate. This process of adaptation permits the microorganims
108
-------
to survive in a habitat which has been significantly altered and
in which it could not have survived if its physiological or
morphological needs had not changed. Adaptation may be expressed
subtly, such as in the synthesis of a new enzyme or set of en-
zyrreS,Or may be linked to the formation of additional morphologi-
cal features. Adaptive capacity is of considerable ecological
significance. For in the event that populations are eliminated
or relegated to a minor position when environmental conditions
are altered, adaptable organisms can acclimate to the prevailing
temperature, salinity, light intensity, or newly available or-
ganic substrate.
The occurrence of adaptation in nature and in laboratory—
scale experiments involving xenobiotics cannot be disputed.
Massive oil pollution of the sea has resulted in extensive re-
search on hydrocarbon biodegradation, particularly bacterial
adaptation to oily substrates. These studies have shown not only
that bacteria can degrade oils (Miget et al., 1969; ZoBell,
1969; and Soli and Bens, 1972) , but that biodegradation can pro-
ceed rapidly when microbial cultures have been previously exposed
to oils (ZoBell, 1969; Soli and Bens, 1972; Mulkins-Ph1111PS and
Steward, 1974) . This effect has led some investigators to sug-
gest seeding oil spills with enriched (or adapted) bacteria as
a means of cleaning up accidental spills (Liu and Dutka, 1972)
Spain et al. (1980) devised experiments to determine whether ex-
posure to xenobiotics would cause microbial populations to de-
grade the compounds more rapidly during subsequent exposures.
Water/sediment systems were tested for adaptation to the com-
pounds methyl parathion and p-nitrophenol. River populations
preexposed to methyl parathion and p-nitrophenol degraded the
nitrophenol much faster than did control populations. However,
salt marsh populations did not adapt to degrade the xenobiotiCS.
The results thus indicated that the ability of organisms to adapt
depends on the presence of specific microorganisms.
The role of adaptation in chemical biodegradation 5 also
suggested in literally hundreds of studies showing lag periods
prior to the onset of biodegradatofl. For example, Tiedje (1977)
showed that initial degradation of EDTA was limited, but after
9 weeks incubation the rate accelerated, indicating the adapta-
tion of thermo-tolerant EDTA-degradiflg populations. Ward and
Broch (1976) note a lag phase preceding mineral oil oxidation,
the length of which depended on population density or on fac orS
influencing growth rate. Tucker et al. (1975) found that the
degradation rates of PCB mixtures in activated sludge units
were most rapid after the sludge units had been acclimated for
about 5 months to the appropriate PCB.
The question of whether a culture highly adapted to degrade
a given compound possesses an enzyme system capable of degrading
related compounds has been explored by various researchers. For
example, Chambers et al. (1963) examined the degradation of 104
109
-------
chemical compounds in laboratory flasks containing a mineral salt
medium by a phenol-adapted culture. Results showed that 65.5
percent of the compounds were degraded at rates 1.5 to over 12
times the endogenous rate (rate in flasks seeded, but without a
phenol-adapted culture). In another study, Mulkins-PhillipS
and Steward (1974) found that a Nocardia sp. , isolated from a
culture enriched on Bunker C oil, grew on Venezulan crude oil,
hexadecane, and other hydrocarbon mixtures. These studies
suggest that enzyme systems capable of degrading a given compound
can, in fact, degrade related compounds.
Evidence indicates that the role of adaptation in chemical
biodegradation is clearly significant. However, few natural
systems are analogous to batch or continuous culture laboratory
systems because of their spatial and temporal heterogeneity. In
light of this, one is forced to ask the following highly relevant
question: does the adaptation commonly observed in laboratory
studies really occur in nature? Laboratory studies have tended
to use concentrations of chemicals in the ppm range, though
environmental levels are often in the ppb range or less than 1
ppb. Because biodegradation is substantially reduced or pre-
vented at concentrations below some critical levels (Section 3,
Physical Evnrjonmental Variables, “Concentration”) , adaptation
may not occur at such concentrations. It seems logical to think
that compounds at ppm levels would result in higher numbers of
degraders, and hence greater ability to degrade the chemical upon
subsequent exposure.
CONCLUS IONS
Because of the complexity of microbial systems, interactions
between microorganisms and their influence on biodegradation are
difficult to define. Attempts have been made to develop math-
ematical models, based on the biological factors involved, which
describe and predict the behavior of one or more populations in
their natural environment. The use of such models is limited by
the problems involved in determining the biological parameters,
and by environmental stresses which alter these relationships.
Although interactions may be well-defined for two species under
specific and controlled conditions, changes in temperature,
salinity, nutrient concentrations, etc. can effect major changes
in species interactions. Though the effects of microbial inter-
actions on biodegradation cannot be neglected, the effects in
most cases can only be defined qualitatively.
The ability of microbial populations to acquire new physio-
logical and/or morphological characteristics has profound
ecological significance. The adaptive potential appears to be
influenced by the microbial system or medium.
110
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SECTION 6
BIODEGRADATION ALGORITHMS
OVERVIEW
An extensive body of literature dealing with biodegradation
rates of chemicals is available; however, there are relatively few
studies treating biodegradation algorithms. A complete generic
algorithm(s) which include the relationships between biodegradation
rates and various environmental factors (e.g., chemical concen-
tration, temperature, pH, moisture, pressure, adsorption, diffusion,
mbcing, etc..) is still lacking. It seems unlikely that significant
progress can be made in modelling biodegradation until more is
known about the response of microbial populations to the control-
ling factors, whatever they may be (Shamat, 1978; Howard et al.
1979; Lo et al. , 1978; and Smith, l979a and b). At present, such
information is sparse, and the modeller is forced to invent re-
lationships. This approach would be acceptable if the assumptions
were then checked experimentally.
In this literature review, the following criteria were used
to evaluate the biodegradation algorithms:
• Algorithms of a generic nature that can be used to
represent various environmental conditions;
• Algorithms that have been proven by experimental
data to have reasonable accuracy;
• Algorithms that are not chemical specific and can
indicate the common type of reaction constants.
The biodegradation rates of various chemicals or
chemical groups can thereby be compared; and
• Algorithms including important variables, especially
environmental factors, as discussed in Sections 3 to
5.
In this section, the advantages and limitations of the existing
algorithms are also assessed. Research needs and problem areas
are noted.
111
-------
EXISTING ALGORITHMS
Studies of biodegradation rates are usually conducted under
one of two conditions: batch and continuous. Both conditions
have been used in laboratory and field environments. The major-
ity of the biodegradation algorithms surveyed were employed under
laboratory environments. Few field applications of batch bio-
degradation algorithms were found, probably because of the
complexity of the natural environment, which precludes the use
of the batch models. Many field studies, however, were per-
formed for continuous flow conditions, especially in the area of
wastewater treatment (such as the activated sludge process).
The derivation of biodegradation algorithms, whether batch
or continuous, or laboratory or field studies, is usually based
on one of two basic approaches: decay or enzymatic reactions.
Algorithms may also be derived by strict data fitting to poly-
nomial power functions. Table 15 shows some examples of the
basic biodegradation algorithms (i.e., expressions of the rate
of disappearance of a growth substrate as a function of the
substrate concentration) used in various studies. These algorithms
can then be used as the basis for the incorporation of other
environmental variables, as will be discussed later in this
section.
Decay Algorithms
The use of decay equations (details will be discussed later
in this section) for biodegradation was applied as early as 1925.
Streeter and Phelphs (1925) used a first—order decay equation to
express the bio-oxidation of organic matter in river water. Since
then, the same concept has been used by many researchers either
for specific or non-specific organics. For examples, zero-order
decay kinetics have been used for 2,4-D (Hemmett and Faust, 1969).
First—order kinetics have been observed for urea herbicides
(Hill et al. , 1955) , 2-4-D (Burschel and Freed, 1960) , triazine
and simazine (Z mhahl et al., 1970) , dichlobenil (Montgomery et a]-.
1972) , SAN 6706 and s N 789 (Rahn and Zimdahl, 1973) , napropamide
(Walker, 1974) , azinphosrnethyl (Yaron et al. , 1974) , nietribuzin
(Hyzak and Zimdahl, 1974) , picloram (Miekle et al. , 1974), aquatic
weed (Waite and Kurucz, 1977), and 2,4-D (Parker, 1979). Results
of these studies all showed that the decay algorithms could
satisfactorily approximate the observed patterns of degradation.
*
SAN 6706 = 4-ch loro-5-(dimethylamino)—2-(a,a,a-trifluoro-m-tolyl)-
3 (2H) -pyridazinone.
SAN 9789 = 4-chloro-5-(methy lamino)-2-(a,a,a-trif luoro—m-to lyl)-
3 (2H) -pyridazinone.
112
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TABLE 1 5 EXAMPLES OF BASIC BIODEGRADATION ALCORITIIMS USED IN VARIOUS STUDI’S
N/A Decay
reactions
(1)
ac
-KC
where C = concentration
t time
K = rate constant
(2) Half—life (t½)
t 0.6932
½ K
(3) Effect of moisture
content:
t½ = aMb
where a & b constants
M = moisture
content
(4) Effect of temperature:
hal f—life at
soil molat’irr’
content (I )
10.0 7.5 3.5
C
kg/ha—
5cm
28
4 50
54
63
90
14
4 50
102
117
——
28
2 25
56
——
——
(4) Use of the models gave good
approAlmations to the ob-
served patterns of bio-
degradation of napropamide
Walker (1974)
Herbicide Soil
(naproparnide)
REFERENCE COMPOUND MEDIUM MICRO—
TYPE
OF MODEL RESULTS/COMMENTS
ORGANISM
MODEL
1st—order rate equation (1) t½ for napropamLdr•
Temper- herbicide
ature concen-
tration
(2) a & b for nnprcpsmlde at 78’C-
a = lR9 3
b ——0 550
(3) AK for napropamide.
Moisture (%) AC (Kcahf 0 [ )
10 7 85
7.5 7.80
log t½ - - __ (
t½ 2.3O3R T T
where T & T’ — absolute
tempera-
tur e
(Continued)
-------
TABLE 1 5. (CONTINUED)
Az inphos—
methyl
(pesticides)
(1st—order
kinetics)
(2) Half—life (T½)
T½ = to + t½
where to lag period
(1) Degradation follows two steps.
firstly, the initiol concen-
tration remains constant;
secondly, the concentration
decreases following the first—
order kinetics.
(2) Degradation affected by temper-
ature and moisture. Half-
lifes (Ti ,) are shown as
f 011 ow a:
Temp.
C
Moisture
Sterile
3%
Soil
50%
Natural
3%
Soil
50%
6
484
*
88
484
64
25
135
29
88
13
40
36
6
32
5
a
Yaron,
Heuer,
and Birk
(1974)
Soil
REFERENCE COMPOUND MEDIUM MICRO-
TYPE
OF MODEL RESULTS/COMMENTS
ORGANISM
MODEL
N/A Decay
reactions
(1) Rate:
C
= half—life
of the 1st—
order reactions.
C initial con—
0 centration
Half—life in days.
(Continued)
-------
TABLE 1 5. (CONTINUED)
Waite and Aquatic
Kurucz weed
(1977) Jjj rilla
sp
TYPE OF MODEL
MODEL
Aqueous Gram— Decay
solutio: negative reactions
non—
motile
rod
shaped
bacterium
(1) The first order decay model was
found to fit the degradation
data. (Thp second order model
was not as good as the first
order model)
(2) Biodegradation rate constont
were affected by nitrate leve1 .
Ic varied between 0.0239/day and
0 0907/day for N0 3 -N within the
range of 0.5 to 6 maIl.
(1) Biodegradation:
dS kS
dt
(2) Temperature effectS
(Arrhenius eq
-E
log (kxlO 2 3O3RT 4A
where: S 2,4-0 conc.
Ic rate constant
(day— 1 )
EA= activation
energy
(Kcal/mo le)
A = Con8tant
(l0 ’/day)
B Gas Constant
T = Absolute
Tempera ture
(°K)
(1) Two first order reactions wore ob—
served—slow ph s and fast phase
(2) ReSults of Ic:
2,4-0
Conc.
k for
Ic
(mq/g
soil)
slow
for
fast
1
0 062
0.10)
5
0.031
0.094
10
0.020
0.069
25
0.010
0 089
Moisture
(%, volume
basis)
temp.<
EA
27°C
A
temp .2
EA
7°C
A
22
22.54
17 66
—38 03
2.8
13.9
20.14
18 19
10.7
19.28
14 69
— 4.60
0.12
6.8
25.40
19.01
—53.40
0.50
3 65
REFERENCE COMPOUND MEDIUM MICRO-
RESULTS /CO?*IENTS
y = y e k
where
y = dry weight
initial y
k rate constant
t = time (day)
C c 0 e t
Parker 2.4—0
I- . ,
(1979)
form reactions
group
(3) Results of temperature and moisture
effects.
(Continued)
-------
TABLE 15 . (CONTINUED)
Grady and COD
Williams (multi—
(1975) component
substrate,
containing
glucose,
galactose,
fructose,
sorbitol.
and lysine)
Enzymatic
reactions
(Effects of
substrate
concentration
in a continuous
biological
reactor)
u m x specific
m grnwth rate
constant
K = substrote
saturation
constant
u= LJ 0 S
K +
S
(Monod
eq
urn
K
S
(where S
is low)
The effects of influent
Bubstrate concentration
can be modelcd by an
extension of the Lin.’ar
approximation of the Monod
model In which the propor-
tionality constant is a
function of the jnfluent
concentration.
Substrate Culture K’
glucose A
Ae I. 0-
cjeneo 0 0633 0 0030
glucose mixed
culture 0.2 l 0.0135
mixed
substrate mixed
culture 0.174 0.0014
(2) Effect of S 0 and 0
on flow reactor
effluent S
S= K’S D + K S
0 0
where
D= dilution rate
K’ & K ’ Constants
Aqueous
solution
(mineral
salts
medium)
REFERENCE COMPOUND MEDIUM MICRO-
ORGANISM
TYPE OF MODEL RESULTS/COMMENTS
MODEL
(heterogeneous
microorganisms
from sewage
treatment
plant)
(1)
(I)
Effect of S 0 on K
K’S
where:
K K
5
I—’
I—i
(2) Resu1ts
(Continued)
-------
TABLE 15. (CONTINUED)
Borighem
and
Vereecken
(1978)
L ,o,
Marchildon,
Lakshmanan,
I—i and
Garceau
(1978)
River
water,
distilled
water,
and tap
water
Enzymatic
reactions
(Continuous
f low,
stirred)
Haidane model:
k
K= 0
1+ Km + S
S K 1
(2) Hill and Robinson
K = exp (-s
54K
m
(both equations
based on substrate
inhibition)
(1) Substrate removal:
dC
5 =-k C C
1 a x
(2) C=R
x F
(3) i/C =
C = concentration of
substrate. mg/i.
rate consPant for
ub tra te
util ization
C, — concentration of
microorganisms.
mg/i
C = C /C
x x so
C= initial conc. of
substrate
REFERENCE COMPOUND MEDIUM MICRO-
ORGANISM
TYPE OF
MObEL
MODEL RESULTS/COMMENTS
Phenol
N/A
Enzymatic
reactions
(1)
Model
N/A Solution N/A
(From
actjva ted
sludge
reactor)
organism
Pc ,
)h )
5 m 5 i
(mg.1) (mg/I)
(1)
Bacterium
NCIB 8?50
U.29
—
1T 0
(1)
Trichosporan
utaneunl
0.464
1.66
380
(1)
I’8eU i
0.567
2.38
106
(1)
Pseudomonas
put Ida
0.534
<1
470
(2)
Pieudomonaa
A
0.481
—
840
The overall effect of mixing, In terms
of B, can greatly affect the bIo-
degradation The larger the P. the
hiqher the biodegradation rate.
+ (y/B) (eBK— )/(K+ )
{ RF/d+A/d+
K+LRF/d4Afdm KJ 2
_4AKId]0.5} /2
where:
(Co 1 1 tinned)
-------
TABLE 15. (CONTINUFDP
F I I I II ( ..MI IIIJNU MFI)IIIM MICRo- TYPE OF MOflEL RESULTS/COM14ZP TS
,IIGANISM MODEL
p c c
F xo/ so
C 0 initial ronc of
micrnr,rq.inisms on
feed
I’
-c/c
9 8 80
B — average frequency of
contact between micro-
organisms and limiting
substrate per unit of
biomass
c i — yield coefficIent, grams
of microorganisms produced
per gram of substrate
removal
K kIC k
2 so I
forward rate constant
for decompositio? of
intermediate, h
h - 0/C k
80 1
0 — dilution rate,
— C k 1k
S si 2
d - 0/k 2
P. ( I/B) (uB-dJ
I Fd
(Continued)
-------
TABLE .15. (CONTINUED)
Shamat Chlorinated
(1978) organics
(eight
compounds
were
studied:
2 ,4-dichloro-
phenoxyac et ic
acid; m—, p—,
and 0-
chioro-
benzoic acids;
and 2,4—,
2,5—, 3,5—.
and
2 • 6—
djch loro—
benzoic
acids)
(1) Batch System:
x
K S(—o)
S —
Y
- S+X in
V 0 S—s-xI
— 0 0 (o
I YJ =Umt
I —x I
I 0
(2) Chemostat:
dx
UX—DX
where Steady state:
x
0
Y
U
Urn
D =
t =
saturation Constant
aubstrate conc.
initial X
microbial yield coeff.
specific growth rate
max. u
dilution rate
time
REFERENCE COMPOUND MEDIUM MICRO-
TYPE
OF MODEL RESULTS/COMMENTS
ORGANISM
MODEL
Aqueous From Enzymatic
solution activated reactions
sludge (Monod
kinetics)
I .-’
(1) Batch System:
Urn K
Substrate ( d ) ( mg/i ) Y
2, 4-D
H-CS
P-CB
0-CR
2 • S-DCB
3 • 5-DCB
0.57
2.03
1.22
1.12
0.14
1.02
0.98
0.65
1.52
0 16
(2) Continous flow:
Substrate Um(dl) Ks(mg/i )
2, 4-D
0-CR
P-CS
2.18
1.13
1.12
2.68
1.53
0.99
1 _U 1 1
S D K
K 5 a
where:
K =
5
S =
S 0 initial S
X microbial conc.
(Continued)
-------
ii in.c 1 . ((_uUI INULU )
REFERENCE COMPOUND MEDIUM MICRO-
TYPE OF MODEL RESULTS/COMMENTS
ORGANISM
MODEL
Edeline Organic River H/A Two phases (1) External (Exogenous) substrate Two—phase model account. for up to
dnd pollutants enzymatic degradation: 95% of the total oxygen consumption
Lamber (COD) reactions (a) Organism growth-- in the river. The two phase. are
(1979) — characterized by a logistic model.
u. ’ _ j The first correspond. to a destruction
5 +5 K of about 2/3 of the substrate, and is
accompanied by the formation of cell-
(b) Substrate degradation-— ular reserves. The second I, the
ds -p consumption of the stored substance..
dS _________
ifE (l+ye_it)2
Isignioidal curve)
(C) Oxygen uptake--
dy dS
— (l—Y)
(2) Endogenous substrate
utilization:
dS CjSe(C _So)
or
i 5 e 5 exo
where -l
ii — growth constant (h
11-max U
S — substrate concentration
5— half-saturation constant
B — bacterial biomass (mg/i)
Y — bacterial cell yield
y — dissolved oxygen (mg/i)
B - (S !9)
K 5 Y
S
V Y
B 0
U endogenous substrate
utilization rate
5 e endogenous substrate
conc.
5 exo exogenous substrate
conc
C . C ,K 1 , K 2 constants
(Continued)
-------
TABLE 15 . (CONTINUED)
Gergtl,
Nye and
Ya ron
(1979)
where:
C—parathion conc.
(pg/ni)
C =C +M
o o 0
C 0 =initlal C
N initial
microbial
activity
(pg/mi)
k rate constant
0 = diffusion
cc ’eff.
R = rate of
xt microbial
decomposition
(i e =kCM)
(1)
Biodegradation of parathion showed two
distinct stages as nhown by equation
listed. In the first stage parathion
degraded at an increasing rate. The
initial rate was roughly proportional
to the initial concentration except at
very low concentrations. The second
stage was characterized by a declining rate
(2) Biodegradation is affected by time, moist-
ure content and initial concentration.
Results as follows:
C
0
0—0.3
a
0
4
k
0=0.24
a
0
I c
0—0.1
a
0
4
Ic
ug/m I
0.0363
0 724
0.0229
1.066
.0 0164
20
0.910
0.0264
14
0.214
0.0629
0.386
0.577
0.0421
7
0.290
0.090
0.372
0.402
0.0471
4 4
0.150
0.203
t Q=moisture content
(3) Combine biodegradation and diffusion models,
and rate of parathion decomposition at any
distance, time, and local concentration
can be calculated The proposed model
satisfactorily fits the experimental
results.
Parathion Soil N/A
REFERENCE COMPOUND MEDIUM MICRO-
TYPE
OF MODEL RESULTS/COMMENTS
ORGANISM
‘ MODEL
(1) Enzymatic
reactions
(2) Diffusion
(1) Biodegradation:
C•-C C
In 0 0 + in
*
——C It.
0
(2) Diffusion:
6C
sx - R
xt
(Continued)
-------
TABLE 15 . (CONTINUED)
(1)
k 0.140 lir
0
Km 245 mg/i
(2) Kinettc data collected from a batch reactor are of
limited value for the design of a continuous
biodegradation process.
(1) Degradation is affected by pH and the initial
concentration
(2) Results of K tin mg/i) and V(in ugIl/d) are as
follows
For Enterobacter aeroQeI :
2 ! . I !
Km 4.09 4.2 3.9
V 192 143 92
For Serratia magcesç ns:
ll I !
K 8.4 8.5 38.3
m
V 122 139 661
Beitrame, phenol
Beltrame,
Carniti,
and
Pitea
(1979)
REFERENCE COMPOUND MEDIUM
MICRO-
ORGANISM
TYPE OF MODEL RESULTS/COMMENTS
MODEL
Activated
N/A
Enzyme
Sludge
reactions
Monod equation:
)co
k i_Km
S
(batch reactor)
H
‘-
Mason,
Anderson,
and
Shari at
(1979)
Methyl— Solution (1)
mercuric EnterO-
chloride bacter
Enzymatic
reactions
Michaeiis-Menten
Kinetics:
1 1 Km
v v
m m
(2)
Serratia
mar-
B tS fl a
(Continued)
-------
TABLE j5 . (CONTINUED)
Chlorinated
Organic
Compounids
(Benzoic acid,
0-chlorobenzoate,
m-chlorobenzoate,
p—chlorobenzoate,
2, 4-dichloro—
benzoate,
2, 5-dichloro—
benzoate,
2, 6—dichloro-
benzoate,
3, 5-dichioro—
ben zoa to
Phenoxyacetic
acid.
2, 4-dich loro-
phenoxyacetic
acid)
(Both continuous—
flow reactors and
batch reactors
were tested)
Shame t
and
Maler
(1980)
Liquid N/A
REFERENCE COMPOUND MEDIUM MICRO-
TYPE OF MODEL
RESULTS/CO *4ENTS
ORGANISM
MODEL
(1)
For
batch
reactori
Enzymatic k k 0 S —
reactions
K +S
m
I- ’
k
Compound (day )
m
(mg/i)
Y
(mg/mg)
2,4-Dichioro-
phenoxyacetate 2.3
5.4
0.14
m—Chlorobenzoate 0.6
2.0
0.14
p-Chlorobenzoate 1.2
1.1
0.25
o—Chlorobenzoate 1.0
2.4
0.22
2, 5—Dichioro—
benzoate 0.6
‘ 1.5
0.16
3, 5-Dichioro-
benzoate 0.05
25.3
——
(2) For continuous-flow
reactori
Compound
(day 1 )
(mg ?)
2, 4-Dichlorophenoxy—
acetate
2.2
2.7
o-Ch lorobenzoate
1.1
1.5
p—Ch lorobenzoate
1.1
1.0
(Continued)
-------
TABLE 1 5. (CONCLUDED)
N/ A power C
function
(Luedeking
and Piret
Hypothesis)
P=ctY(S 0 —S)+B Y(S —$ )
where a and B
are constants.
(1) where COD is the growth-limiting factor,
the Monod equation is not applicable
to long activated sludge ages.
(2) The tuedeking and Piret hypothbsis can
be used to estimate the amount of the
product end undegraded substrate present
at any sludge age.
(1) The carbon loss data could not be describ.’d
by the first order kinetics. Neither did
they conform well to Michaelis—Menten
kinetics.
(2) The carbon loss can be expressed by a power
function as shown. k and vs were affected
by loading rate of rice straw.
Explanation of symbols are shown below, unless otherwise explained in the table:
k kinetic rate constant K = solubility product K = substrate saturation constant X — biomass concentration
S vs
maximum growth rate constant K = inhibition constant s substrate concentration
K = equilibrium constant in terms of
concentration
Baskir
and
Spearing
(1990)
REFERENCE COMPOUND MEDIUM MICRO-
TYPE OF
MODEL RESULrS/COM IIENTS
ORGANISM
MODEL
N/A
Enzymatic
reactions
(1)
I.-J
For Substrate:
(Monod kinetics)
k= k S
Km +S
Carbo- Liquid
hydrates (sugar,
sodium
alginate,
and
nutrients)
Clay
soil
(Steady—state
ccntinuous-
culture)
12) For ProducL
Pal and Rice
Broadbent Straw
(1975)
where:
C=carbon loss
k&m=constants
t=t me
-------
The general form of the decay algorithm can be written as
follows:
= —k 4 (S) (7)
where S represents, directly or indirectly (e.g., organic carbon
disappearance or oxygen demand), the concentration of the sub-
stance at time t; k is a rate factor or specific reaction-rate
constant, and 4(S) is a function of the concentration of the
substance remaining. In many cases, 4(S) for biodegradation
can be expressed in terms of Sn, where n is a dimensionless
factor representing the order of the reaction. Therefore,
Equation (7) becomes:
= -kS (8)
As discussed above, many of the biodegradation studies showed a
first-order reaction (i.e., n=l). In this case, Equation (8)
is simplified as:
= -kS (9)
or s = Se t (10)
where S = original concentration of the test substance. The
biodegr dation rate constant, k, can then be calculated:
k = in (ii)
In a complex system, the reaction order may be a fractional order
or higher than first order (Parker, 1979). The following table
shows biodegradation rate constants at several selected reaction
orders:
Reaction Order (n) Biodegradation Rate Constant (k )
0 (S—s)
t 0
•1 1 S
± in - 2
t S
2 1 So-s
t —i .——-
0
3 1 ( S 0 + S) (S—S )
2S 0 2 s 2
125 I
-------
Basically, the decay algorithm is a direct expression of
the changes of concentration versus time, in which no other
factors are incorporated. Such factors or variables are in-
corporated into the k value, that is;
k = f (other environmental factors) (12)
The factors affecting k values will be discussed later in this
section.
Enzymatic Algorithms
Decay algorithms often fail to express the complicated
microbial interactions and population dynamics. Many biodegrad-
ation kinetic studies introduce a biological factor, B
(i.e., concentration of organism(s)), to modify the model.
Because the enzyme(s) is the source or mediator for the uptake
of organic substances by microorganism(s) , B can be replaced
by the enzyme concentration, E. The simplified enzymatic
algorithm can be developed as follows:
k k
E + S - +1 ES +2 E + i ( 13)
- k 1 k 2
Where:
S = substrate;
E enzyme;
k+ 11 k 1 , k÷ 2 , and k 2 = rate constants;
ES = substrate-enzyme complex; and
P = product.
The rate of substrate biodegradation can then be expressed as:
= - k 1 S.E + k_ 1 ES (14)
The rate of ES changes can be expressed as:
dES = k 1 S .E- (k_ 1 +k 2 ) ES + k_ 2 EP (15)
dt
126
-------
The mass balance relationships:
E 0 = E + ES (16)
S 0 = S + P + ES (17)
Where E and S represent the initial concentration of E and S ,
respectively. °EquationS (14) through (17) contain four vari-
ables, S, E, ES and P , and can be solved by the simultaneous
solution of four equations. If it is assumed S >> ES, k 2 = 0,
and equilibrium condition exists for Equation (?3) (i.e.,
dES = 0), then the biodegradation rate of a substance can be
sim lified to the following form:
VS
dS_ m 18
dt 1< +S
m
Equation (18) is the well known Michaelis-Mentefl kinetics
model, where Km is the Michaelis-Menten or substrate saturation
constant and equal to (k_ 1 + k 2 )/k 1 ; V depends on the initial
concentration of microorganism, B: m
V = k B (19)
m 0
where 1 k = maximum specific growth rate constant (unit in
time
k BS
Therefore: dS o
dt - K+S
When: Km >> S , Equation (20) becomes
— ( o ) BS (21)
By comparing Equation (21) to decay equation (Equation 9), it
can be seen that the enzyme model incorporates the biological
factor, B, into the decay kinetic model. Equation (21) be-
comes first order for substrate and biomass concentrations,
or alternatively, second order overall.
When S >> K , the reaction kinetics (Equation 20)) are
first order for he biomass concentration and independent of
the the substrate concentration. When S = Kml Equation (20)
shows that the reaction rate is one-half of its maximum value.
If S 0 and ES are assumed to be constant, Equation (17)
becomes:
127
-------
=_ - (22)
dt dt
If P is assumed to be equal to B, Equation (22; becomes:
k BS
_____ (23)
dt K+S
If P # B and the growth yield, y, is a constant ratio between cell
yield and substrate utilized, Equation (23) becomes:
k BS
dS — dB — 0 (2A)
dt — - Y .dt — - Y(R + S)
m
Equations (23) or (24) are usually referred to as the Monod
equation. The specific growth rate constant or the biodegradation
rate constant can be solved from eauation (23) or (24):
k = /B = :s+ (25)
The Michaelis—Menten and Monod equations or their derivatives
have been used extensively to model the biodegradation of various
organic substances in either aqueous or soil environments. Exam-
ples of such applications are shown in Table 15. As for the decay
reaction algorithms, enzymatic reaction algorithms were also used
for both specific or nonspecific organics under field or labora-
tory conditions. Results as discussed in Table 15 indicate that
enzymatic reaction algorithms can model the biodegradation rates
with satisfactory accuracy. However, if kinetic expressions are
derived from the Monod equation, they should be applied with
caution under unsteady-state conditions, since they were usually
derived assuming steady-state concentration of metabolic inter-
mediates.
Many enzymatic reaction algorithms considered the effects of
inhibition caused by complex formation between substrate and
enzyme (called substrate inhibition), enzyme and other chemicals
(competitive inhibition), or substrate and other chemicals (non-
competitive inhibition). Whenever inhibition is present, the
rate of biodegradation is decreased. Table 16 gives examples of
some coninion biodegradation algorithms based on enzymatic reaction
kinetics.
Power Rate Algorithms
The power rate algorithms were derived mainly from curve
fitting. Theoretically, a curve (or equation) can be derived
for a set of data involving two variables. Examples of such
equations are presented by Hamaker (1972), Pal et al. (1975)
and Parker (1979):
128
-------
k
0
— 1 + K/S
—S
k=k 0 (1-e
k — + (K X/S)
k= k 0 —
1 + (K S
k
k + (K/S)+ (S/K 1 )
k = 1 + (K/S)+ 1K/K
k + (XIS)] [ 1 + (1/K 1 )]
k
0
- K 2
m
• S ‘K
kS 1.
k = +K exp (-S/K 1 )
k S(1 + S/K)
k= °
1 + K IS +S/K.
m 1
k
k 1 + K/S + (S/K 1 ) (1 + S/K)
*
References: Sundstrom et al. (1979)
Der Yang et al. (1975)
k = kinetic rate constant K = Teissier constant
k = maximtm growth rate constant r
0
Kc = equilibrium constant in terms of concentration
K 5 = solubility product
K. = inhibition constant
1
AL 1 = Moser constant S —
Algorithm
TABLE 16. COMMON BIODEGRADATION ALGORITHMS
BASED ON ENZYMATIC REACTION KINETICS
Name
Monod
Teissier
Conto3. S
Moser
Haldane
I = concentration o inhibitive chemicals
K = substrate saturation
constant
substrate concentration
bioma s concentration
129
-------
= a + bt + Ct 2 + ... . 26)
and:
S 0 n = Sn + nkt (27)
where S = substrate concentration;
a,b,c,i,rn,n = constants; and
k = rate constant.
However, the power rate algorithms have very limited value be-
cause of their non—generic nature and in some cases no bio-
degradation rate is expressed. Very few researchers have used
the power rate expressions for biodegradation studies. Hainaker
(1972) suggested that fractional order reaction rates might be
beneficial in predicting pesticide degradation. His model is
as follows:
(1—n) = (1—n) + (1—n) kt (28)
Pal et al. (1975) stated that, in their study, the organic carbon
degradation data could not be described by first-order kinetics.
Also, their data did not conform well to Michaelis-Menten kinet-
ics. However, a good fit was obtained by using the power rate
algorithm shown below:
S = k (29)
where S = substrate concentration in terms of carbon;
k and m = constants; and
t = time.
Effects of Environmental Variables
Biodegradation algorithms as discussed above describe, main-
ly, the relationships be tween two factors: concentration of
organic substances (S) , and time (t). Many of the environmental
variables have been neglected in the biodegradation rate algo-
rithms. Existing literature, however, does show some algorithms
for the quantitative expression of the environmental variables.
Such algorithms can be incorporated into the basic a1górithms as
discussed previously.
Temperature Variable--
Unlike physical or chemical reactions, the temperature range
130
-------
in which biological reactions occur is small. The range for
survival usually extends from -5 to close to 100°C. When growth
rate is plotted as a function of temperature, the optimum tem-
peratures (which give higher biodegradation rates) usually lie
within the range for survival but toward the higher end of the
range. Biodegradation rates approach zero towards the lower and
higher ends of the survival range (Stanier et al., 1976).
Three mathematical algorithms have been used by biologists
to describe relationships between biodegradation rates and
temperature:
• Simple linear regression of biodegradation vs.
temperature;
• model; and
• Arrhenius equation.
The first approach (i.e., linear regression) assumes that
in a certain temerature range, the biodegradation rate, k, is
directly proportional to the temperature, T (°C), (Howard et al.,
1979). That is,
k = ktT (30)
where: kt = constant
or: k 1 = k 2 . (31)
where: k 1 , k 2 = biodegradation rates at temperature T 1
and T 2 respectively.
The second approach 0 mdoel) is based on the Van’t Hoff’s
empirical rule that the ratio of reaction rates at an interval of
10°C is of the order of 2 to 3. This ration is the 0 value.
The relationships between biodegradation rates and tei perature
can then be expressed as:
/ lnQ 10 ’ \
in k = C ÷ T 10 ) 32)
or: ( T 1 -T 2 \
10 ) (33)
where: C = constant; and
T = temperature, °C.
131
-------
This Q model assumes that the logarithm of the biodegradation
rate, , is a linear function of T. The Q 1 approach has been
used by Howard et al. (1979) and Flanagan e al. (1976) for non-
specific organics.
Most biological constants fit an Arrhenius type of tempera-
ture relationship (the third approach):
k = AeE/RT
where: k = biodegradation rate constant at temperature T°K;
E = activation energy;
A = constant; and
P = gas constant in cal/g-mol- 0 K.
or: k 1 = k 2 .exp [ (T2T1)] (35)
The Arrhenius equation has been used extensively to describe the
effect of temperature on biodegradation (e.g., Zimdahl et al.,
1970; Hamaker, 1972; Walker, 1974; Stanier et al. , 1976; Parker,
1979; Howard et a].., 1979; and Sandstrom et al., 1979).
When biodegradation rates as a function of temperature are
plotted, no matter which approach is used, the results are usu-
ally satisfactory only over a certain part of the temperature
range. The deviation near the maximum temperature is interpreted
as due to the thermal denaturation of cell proteins (Stanier et
al., 1976). At the minimum temperature, the deviation may be
caused by the regulatory machinery of the cell (Stanier et
1976). Howard et a ] .. (1979) stated that information on the fac-
tors affecting the temperatures permitted for growth is meagre,
and a precise temperature-biodegradation model can not be derived
using existing limited knowledge.
Contact Opportunity--
As discussed previously, biodegradation rates may be affected
by contact opportunity, in terms of several physical (e.g.,
mixing, diffusion, etc.) and physical-chemical (e.g., sorption,
etc.) mechanisms. Few algorithms correlating such mechanisms
with biodegradation rates were found.
Lo et a].. (1978) suggested complicated algorithms to corre-
late the overall effect of mixing, in terms of , and the bio-
degradation rate for a continuous biological reactor:
132
-------
dC
= -k 1 C c (36)
= RF + (aBK-D ) - ( 37)
K +D
and = + + K + + + K) 2_ 4AK 1 O• 5 1 ( 38)
where:
Cs = concentration of substrate, mg/i;
k = biodegradation rate constant for substrate utiliza-
1 t].on;
C = concentration of microorganisms, mg/i;
C C/C
x x SO
C = initial conce ntratiOn of substrate;
R =C /C
F xo so
C 0 = initial concentration of microorganisms in feed;
y 1 -
= C/C ;
= average frequency of contact between microorganism
and limiting substrate per unit of biomass;
ci. = yield coefficient, grains of microorganisms produced
per grain of substrate removal;
K = k 2 /C 50 k 1 ;
k 2 = forward rate constant for decomposition of intermedi-
ate, h’;
D = D/C 0 k 1 ;
D = dilution rate, h’;
C’ - C k ‘k
s — s 1’ 2’
d = D/k 2 ; and
A — ( l/ ) (a —d )
- 1+d
133
-------
As shown by the above equations, the larger the B values, the
higher the biodegradation rates.
Diffusion was also found to have a profound influence on
the rate of biodegradation. This is because diffusion tends to
move the substrate away from or toward the microorganisms, and
so influences the availability (or concentration levels) of the
substrate. In order to correlate such an effect to the biodeg-
radation rate, the diffusion coefficient (D) of a substrate in
a specific medium should be quantified. The following algorithm
can then be used to calculate the diffusion effect (Gersti et
al. , 1979)
=D C — R t (39)
st
where
C = substrate concentration at time t;
R = biodegradation rate; and
x = the x direction.
Zirndahl et al. (1977) suggested an algorithm to express the
effects of sorption on biodegradation rates of herbicides in the
soil environment. The authors found that the clay and organic
contents are the most important sorbents influencing the biodeg-
radation rate:
— Lc1 = k [ c] [ clay] [ OM] (40)
where [ c] = substrate concentration;
[ clay] = clay content;
[ OM] = organic content; and
k = biodegradation rate constant.
Nutrients/Inhibitors/Toxins--
Microorganisms cannot degrade a chemical substance without
a balanced supply of other essential chemical substances (“nu-
trients”, as defined previously). Most studies, however, have
failed to evaluate the effects of these nutrients on the bio—
degradation of the substrate of interest. Misleading conclusions
may be reached if such effects are not taken into consideration.
For example, in the biodegradation of carbohydrates in a low
134
-------
nitrogen environment, the specific biodegradation rate may be-
come (assuming Monod equation applies)
kS
k = a N (41)
K+ SN
instead of:
kS
k = o c C 42)
K+S
m c
where: SN = nitrogen concentration;
S = carbon concentration.
In the above example, the biodegradation rate obtained will be
limited by the concentration of utilizable nitrogen compounds
instead of the carbon compound of interest (Sundstrom et al.,
1979) . It is quite possible that, in a natural environment (or
even in a laboratory controlled environment), the observed
biodegradation rate(s) are influenced by certain unknown nu-
trient(s) (such as certain unknown growth factors or inorganic
ions and do not accurately portray the biodegradation rate of
the compound of interest. Measured biodegradation rates for the
chemical compound of interest are only representative of true
rates when the studied chemical becomes the limiting growth
factor.
The biodegradation rate is also affected by inhibitors.
Inhibitors may be the substrate of interest (e.g., when the
substrate itself is present at very high levels) or other chemi-
cals. Such effects have been discussed previously under the
heading of “Enzymatic Algorithms”. Whenever an inhibitor is
present, the biodegradation rate is decreased (Sundstrom et al.,
1979). Mathematically, this lower rate is caused by the addition
of more terms to the denominator of the biodegradation rate
algorithms. Examples of such algorithms are presented in Table
16.
Quantitative expressions of the effects of toxins on bio-
degradation rates are still lacking. Due to the wide variety
of toxins and complex relationships between different toxin con-
centration levels and types of microorganisms, derivation of a
generic model appears to be beyond the present knowledge.
-------
Water Availability
In an aqueous environment, the water requirements of micro-
organisms can be expressed quantitatively in the form of the
water activity (as,,) of the environment (Rose, 1976):
(43)
w p 0
- ‘n
or a = ____ (44)
where p = vapor pressure of the solution;
p 0 = vapor pressure of pure water;
v = number of ions formed by each solute molecule;
m = molar concentration of solute; and
= molar osmotic coefficient.
Qualitative effects of a on biodegradation rates have been re-
ported (as discussed in ‘ ection 4) . No quantitative correlatiions
are available, however, for the a and the biodegradation rates.
In a non-aqueous environment, water availability will exert
its effect on biodegradation when moisture content falls below
some critical value (Howard et al., 1979). Three types of
algorithms have been suggested for the quantitative expression
of the effect of moisture content on biodegradation rate:
= + (45)
k = (46)
and: = aiM+ M X a 2 + M
where: S = concentration of organic substances;
degradation rate at M = 0;
M = moisture content;
m and n = constants (for Equation (45) , n <1);
a 1 = moisture content at which activity is half its
“optimal value”;
a 2 = moisture content at which gas exchange is half its
“optimal value”;
136
-------
c = correction constant; and
k = degradation rate constant.
Equation (45) was devised by Hamaker (1972) based on the Freund-
lich equation. The constant, rn, in Equation (45) is dependent
on chemical, soil, and temperature factors. Equation (46) was
modified from the half-life equation used by Walker (1974).
Equation (47) was suggested by Flanagan et al. (1976) and Bunnell
et al. (1977) based on the Michaelis-Menten equation. To date,
no theoretical model has been derived. The first two algorithms
have been checked by experimental results. However, the third
algorithm was not tested experimentally. It is suggested that
additional studies are needed for the confirmation of the above
algorithms or for the derivation of a more generic algorithm.
Other Variables—-
Algorithms for other variables, such as hydrostatic pressure,
pH, Eh, and microbial interactions, are still lacking. Only very
limited data have been reported in the literature for general
trends of the effects o the above variables. Apparently, math-
ematical expressions of the effects of these variables on bio-
degradation rates cannot be derived using the iimited experimental
results available.
ALGORITHMS MODIFICATION
Evaluation of the literature reveals that most algorithms
reported in biodegradation studies were used to explain experi-
mental results involving specific environmental conditions.
Generic models that can be used universally to describe the
effects of various environmental variables are not available.
If biodegradation is to be evaluated on a common basis, the
effects of all significant environmental variables should be
included. Algorithms should be modified by incorporating various
environmental factors.
One of the schemes that can be used to modify biodegradation
algorithms is to incorporate correction factors for all important
environmental variables into the basic biodegradation algorithms,
i.e. , substitute Equation (49) into Equation (48):
= — k 4 (S) (48)
k = f (other environmental variables)
1
= k 0 fl F ( )
1=1
137
-------
where
S = substrate concentration;
k = biodegradation rate;
k 0 = biodegradation rate obtained under certain given
environmental conditions;
F. = correction factor for environmental variable i; and
1
= function of substrate concentration.
As discussed in Sections 3 to 5, a wide variety of environmental
variables can affect biodegradation rates. Practically, it is
impossible to include all the correction factors (F.) for environ-
mental variables. However, it is generally known t 1at, in any
given situation, only one or some limited number variables are of
significance. For example, in applying herbicides to a given soil
environment, the important variables would be temperature and
soil moisture content, inasmuch as other variables (e.g. , clay
content, soil organ,ics, pH, nutrients, etc.) would be relatively
constant, and only temperature and moisture content would show
significant variation during a specified time interval. Under
such a situation, and if the Haldane equation (Table 16) , the
Arrhenius equation (Equation (35)), and the equation suggested
by Flanagan et al. (1976) (i.e., Equation 47)) apply, then the
degradation could be estimated by:
dS r (E T-To\l [ M a 2
=-k [ exP . TT0 )JLai÷M a 2 +M
[ 1 50
+ (Km/S + (S/K )
(refer to the mentioned equations for meaning of symbols)
It should be noted that the derivation of such modified algorithms
relies on the availability of algorithms for each important indi-
vidual variable.
SUMMARY AND DISC SSION
Basic biodegradation algorithms are usually based on one of
two basic approaches: decay or enzymatic reactions. These algo-
rithms only address the rate of disappearance of a growth sub-
strate as a function of the substrate concentration; no environ-
mental variables are included in the models. Among the decay
algorithms, the first order decay algorithm is used more widely
for expressing the biodegradation of chemicals. However, decay
algorithms often fail to express the complicated microbial
interactions and population dynamics. Many enzymatic algorithms
have thus been developed. Numerous studies have modified the
138
-------
enzymatic algorithms by including inhibition effects. Such modi-
fied algorithms are believed to be superior to the decay algo-
rithms.
Three algorithms, i.e., simple linear regression, the Q 10
model, and the Arrhenius equation, are used to describe tempera-
ture effects on biodegradation rates. Among them, the Arrhenius
equation is more extensively used, and in most cases fits the
data satisfactorily. The Q 10 model also found to fit the data
quite well for some organic species. Comparing between the
and the Arrhenius equations, Q 10 provides a readily comprehensible
term descriptive of the overall effect of temperature, and has
the advantage over E (activation energy) in that it offers less
temptation to enter into an oversimplified interpretation. The
main disadvantage in using Q 10 is that 0 drifts more with
temperature than does E. The disadvanta e of the ArrheniuS
equation is that several types of reactions are known which do
not give a straight line when log k is plotted against lIT.
These deviations from the Arrhenius equation have been reviewed
by Hulett (1964). Biological processes, including microbial
growth and enzyme reactions studied in vivo or in vitro, character-
istically give non-linear plots (Farrell and Rose, 1967) and
several attemps have been made to explain this non-linearity for
enzyme activity (Ingraham and Bailey, 1959; I-lulett, 1964; Farrell
and Rose, 1967; Hamaker, 1972; Howard et al. , 1979). Three fac-
tors likely to be important are: (a) susceptibility of enzyme
proteins to certain temperatures; (b) the complexity of reaction
mechanisms of enzyme catalysis and the biochemical organization
of the organisms; and (c) changes in population size, distribution
or metabolic processes influencing the activity of the population
and, therefore, biodegradation rates.
Diffusion effects on biodegradation rates may be quantifiable
if diffusion coefficients in complicated (usually nonhomog noUs)
systems are available. It is suggested that many of the models
used in geohydrology or for pollutant migration in environmental
media can be applied.
Determination of the effects of nutrients on biodegradation
rates may use the same algorithms as that of substrate biodegrad-
ation (i.e., decay or enzymatic algorithms). Apparently, these
models are applicable when nutrients become the limiting f actor
for the growth of microorganisms.
There are numerous algorithms available describing inhibition
effects on biodegradation rates (Table 16). Many of the algo-
rithms are so complicated that their practicality may be limited.
Unlike inhibition effects, quantitative expressions of the effects
of toxins are greatly lacking. It is believed that such effects
may be beyond the enzyme-substrate complexation algorithms as
derived for most of the inhibition effects.
139
-------
No algorithms are available for quantifying the effect of
water availability on biodegradation rates in aqueous environ-
ments. For non-aqueous environments, algorithms based on the
exponential relationships (e.g., Equations (45) and (46) have
been derived based on experimental results. Algorithms similar
to the Michaelis-Menten equation (e.g., Equation (47) have
also been derived for describing the effects of moisture on
biodegradation. However, these types of models need to be vali-
dated experimentally.
Algorithms for other environmental variables (e.g., pH, Eh,
hydrostatic pressure, microbial interactions, etc.) have not been
reported in the literature. Due to the complexity of environ-
mental factors affecting biodegradation rates, it is unlikely
that useful mathematical expressions relating changes in those
factors to effects on biodegradation rates will become available
in the near future.
The literautre review also revealed that biodegradation
studies have encompassed a wide variety of environmental condi-
tions. Some studies were conducted without the control or
measurement, of environmental variables. It is virtually impos-
sible to derive generic algorithms based on experimental results
in which environmental conditions were not controlled or were
unknown. If generic algorithms describing effects of environ-
mental variables on biodegradation rates are to be derived, con-
trolled environmental conditions and more experiments to cover
wide varieties of chemicals and environmental variables are
urgently needed.
140
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