1

Removal of Total Petroleum Hydrocarbons (TPHs) and Polycyclic 1

Aromatic Hydrocarbons (PAHs) in Spent Synthetic-Based Drilling 2

Mud 3

Using Organic Fertilizer 4

5

6

Abstract 7

Treatment and disposal of spent(used)drilling mud have become animportant environmental 8

challenge in the oil and gas industry. Total Petroleum Hydrocarbons (TPHs) and Polycyclic 9

Aromatic Hydrocarbons (PAHs) constitute the major contaminants in spent drilling mud. In this 10

study, five spentsynthetic-based drilling mud samples were collected from five oil fields in the 11

Niger Delta. Samples collected on day 0 were analyzed for TPHs and PAHs. Concentrations 12

higher than thepermissible regulatorylimits were recorded. The efficacy of urea fertilizer in the 13

remediation of TPH-and PAH-impacted mud was investigated. Six sub-samples and six control 14

sub-samples were tested bi-weekly for 12 weeks with 20g, 25g, and 30g doses of urea fertilizer per 15

20L of spent mud for each of the five samplesrepresenting each individual oil field (marked A 16

through E). Removal of TPHs and PAHs with urea fertilizer treatment proved to be fast and 17

efficient. In 6 weeks, with a dose of 1.5g/L, over 98% removal of TPHswas recorded, and more 18

than 94% of PAHs, and in 12 weeks, more than 99.5% removal was recorded for both. The 19

residual levels of TPHs and PAHs met Department of Petroleum Resources(DPR: Nigeria) and US 20

EPA limits for land disposal. Mathematical models with agoodness of fit(R2) of 0.999, were 21

developed to predict the rate of thedegradation processes. 22

Keywords: Spent Drilling Mud, Niger Delta, Total Petroleum Hydrocarbons, and Polycyclic 23

Aromatic Hydrocarbons, Biodegradation, Urea Fertilizer, Mathematical Model. 24

25

1. INTRODUCTION 26

Drilling is one of the major chemical intensive operations in oilfields that generates wastes, which 27

can impact the environment. (Coussotet al., 2004; Ebrahimi et al., 2012; Zhang et al.,2011; Ball et 28

al., 2012; Hu et al., 2014). In drilling operations, two main types of wastes are generated, drill 29

cuttings and spent drilling mud(Mkpaoroetal.,2015;Bakke et al.,2013;Bamberger and 30

Oswald,2012;Bansal and Sugiarto,1999).Drilling fluids, including synthetic base fluids (SBFs), play 31

important roles in drilling operations by providing relatively better shale inhibition, lubricity, and 32

thermal stablity characteristics(Fomasieretal.,2017;Nahmad and Lepe, 2014;Ball et al., 2012). Other 33

SBF functions include lifting of drill cuttings from the well and controlling hydraulic pressure(Anon, 34

2011;Dankwaetal., 2018). 35

2

Total Petroleum Hydrocarbons(TPHs) and Polycyclic AromaticHydrocarbons(PAHs) are some of 36

the major contaminants of the spent drilling mud and they impact adversely on the environment if 37

carelessly disposedof(Fijałet al.,2015; Fontenot et al.,2013). Studies have shown that plant growth 38

is affected when petroleum hydrocarbon-impacted spent drillingmud is released on 39

land(Osisanya,2011). Levels of spent drilling mudabove a few percentages in soil (by weight) have 40

beenshown to degrade plant growth(Clements et al., 2010;Czekajet al.,2005). Improper disposal of 41

spent drilling mud into water bodiesendanger marine life (Anozie and Onwurah,2001).Safe 42

disposal of spentdrillng mud after drilling is a major problem in the oil and gas industry(Gross et 43

al.,2013; Hou et al.,2012;Onwukwe and Nwakaudu,2012). Most of the existing methods of 44

treatment like fixation,andthermal methods,have disadvantages ranging from high risk to personnel 45

to huge costs because of thehigh energy demands due to high temperature requirements(Liu et al., 46

2016;Kerri et al., 2013).Some of these existing methods of treatment require expensive and 47

sophisticated equipment with high capital and operating costs (Hu et al., 2014;Kerri et al.,2013; 48

Xieet al.,2015). 49

Bioremediation is the biological breakdown or biodegradation of contaminants(Bewley et al., 50

2001). It involves the microbial breakdown of organic compounds into less complex compounds, 51

mostly water, and carbon dioxide and sometimes methane(Patel et al., 2012). The rate and extent 52

of biodegradation depends on the population and type of microorganisms, the environment, and the 53

chemical structure of the contaminant(Semple et al., 2003). Most organic compounds are 54

biodegraded under aerobic conditions(Kauppi et al., 2011). Biodegradation of some organic 55

compounds has also occurred under anaerobic conditions, although at rates not as rapid as under 56

aerobic conditions(Akindeet al., 2012). Intrinsic bioremediation or natural attenuation is the 57

biodegradation of a target contaminant without intervention under an appropriate environmental 58

condition, available nutrients (mostly phosphate, nitrogen and sulfur), and 59

microorganisms(Ibieneet al., 2011). However, from regulatory point of view, the rate of intrinsic 60

bioremediation is slow because of time limits(Chikere et al., 2012b). As a result, enhanced 61

(engineered) bioremediation is required most of the time(Abdusalamet al.,2011;Kadaliet al., 62

2012). In engineered bioremediation, the rate of bioremediation is increased in two ways: 63

biostimulation and bioaugmentation(Abdusalamet al,2011;Bourceretet al., 2015). Biostimulation 64

3

was deployed in this study by use of urea fertilizer,as a source of nutrient to the indigenous 65

microorganisms, to biodegrade TPHs and PAHs in impacted, spent synthetic based mud. 66

Urea is one concentrated source of available nitrogen. It is widely used in agriculture as a fertilizer 67

and animal feed additive. Urea fertilizer is the most important nitrogenous fertilizer.It is called the 68

King of Fertilizers because of its high nitrogen content (about 46 percent). 69

It is a white crystalline organic chemical compound. It is neutral and can adapt to almost all the 70

land. It is a waste product formed naturally by metabolizing protein in humans as well as other 71

mammals, amphibians and some fish. The main function of urea fertilizer is to provide the plants 72

with nitrogen to promote green leafy growth. It can make the plants look lush, and it is necessary 73

for the photosynthesis of plants. Nitrogen is an important nutrient required for microbial growth. 74

Urea fertilizer is widely used in biostimulation because of its high nitrogen content. 75

Advantages of urea fertilizer include: highest nitrogen content (this percentage is much higher than 76

in other available nitrogenous fertilizers), low cost of production, no storage risk (not subject to 77

fire or explosion hazards), and wide application-urea fertilizer can be used for all types of crops 78

and soils and does not harm the soil. However, it is very soluble in water and hygroscopic, and 79

requires better packaging quality. 80

81 Mathematical models help to predict the expected outcome of experiments.This saves time and cost for 82

future jobs.More often the field and laboratory data are used to calibrate mulit- purpose regression models 83

of linear and/or higher order equivalence.The statistical approach was adopted in this study for model 84

development. 85

2. METHODOLOGY 86

2.1Area of Case Study 87

4

This study was carried out with spent, synthetic based mud (SBM) from five oilfields in the Niger 88

Delta. TheNiger Delta is located at an elevation of 96m above mean sea level. It lies between East 89 Longitude 5° and 8° and North Latitude 3° and 6°.Samples A, B, C, D and E were taken at 90 Longitude 5°9'40.58"East and Latitude5°19'17.71"North, Longitude 6°47'4.912"East and Latitude 91

3°11'37.644"North, Longitude 6°16'41.972"East and Latitude 4°11'42.948"North, Longitude 92 6°21'20.38"East and Latitude 4°54'28.648"North, Longitude 6°42'12.077"East and Latitude 93

4°59'30.057"North, respectively.( Figure 1.)The region has a population of 30 million people 94

(NBS,2006). Over 90% of Nigeria’s proven oil and gas reserves are located in the region ((Adati, 95 2012). The NigerDelta covers a coastline of 560km

2, and it is formed primarily by sediment 96

deposition(Osinowoet al,2018). It’s a rich mangrove swamp covering over 20,000km2 within 97

wetlands of 70,000km2 (Ekubo and Abowei,2011). Oil was first discovered in the delta by Royal 98

Dutch Shell (Shell Nigeria), formerly Shell-BP, in 1957 at Oloibiri, and production began in 1958. 99

The oil and gas industry play significant role in Nigeria’s economy, accounting for about 90% of 100

its gross income(Abubakar,2014). Figure 1 shows the map of Niger Delta and drilling mud sample 101 locations. 102

103

Figure 1. Location map of study area 104

105

5

2.2 Data collection 106

Adequate quantities of the spent drillingmud from five oil fields were sampled from well-agitated 107

mud tanks and transported to the laboratory as quickly as possible to ensure that the parameters of 108

the mud did not change before testing. Convenience sampling method was used because of low 109

drilling activities in Nigeria,at the time of this study.In the laboratory, the samples were again 110

thoroughly agitated with sample mixers to ensure proper mixing.The samples were marked MUD-111

A to E and tested for baseline values of the physicochemical parameters (Table 2). For each 112

sample, 25 (twenty-five) sub samples of 20L each were created: (i) One sub-sample for baseline 113

studies; (ii) Eighteen (18) sub-samples for bioremediation treatment for Total Petroleum 114

Hydrocarbons(TPHs) and PAHs with urea fertilizer (6 sub-samples each for 20g, 25g, and 30g 115

doses); (iii) Six (6) sub-samples for control. The control samplesare the original spent drillingmud 116

without treatment. Urea fertilizer was used as a source of nutrients for the hydrocarbon utilizing 117

bacteria (HUB) for the remediation of the mud impacted with Total Petroleum Hydrocarbonsand 118

PAHs. Both the treated and control samples were tested bi-weekly for 12 weeks. The tests 119

conducted and methods used are shown in Table 1. 120

Table 1: Analytical methods employed in the study 121

Parameter Analytical Method STANDARD

TPHs and PAHs GC/FID (Agilent 7890A GC systems) ASTM D 3921

THB and HUB Total Plate Count ASTM D5465-16

Total Nitrogen Kjeldahl ASTM D8001-16e1

Temperature Meter reading ASTM E2251-14

pH Meter reading ASTM D1293-18

Moisture Content Gravimetric method ASTM D2216-98

CO2 Standard method for dissolved carbon

dioxide in liquid ASTM D513-16

DO Standard method for dissolved oxygen in

liquid ASTM D888-12e1

Phosphorous Total phosphorous-EPA method EPA 365.1

6

TOC Standard test method for total carbon and

organic carbon in liquid by ultraviolet and

infrared dictation

ASTM D4839-03(2017)

122

2.3 Predictive model 123

Nonlinear regression analyses were applied in modeling the duration of the effective biological 124

treatment of the spent drilling mud. XLSTAT 2018 was the statistical tool employed as an aid for 125

the model development (Ziegler, 2005; Nwaogazie, 2011). 126

127

3. RESULTS AND DISCUSSION 128

3.1 Results 129

Baseline physicochemical parameters of spent drilling mud samples 130

The baseline values of the physicochemical parameters of the spent drilling mud are shown in 131

Table 2. Nigerian and US EPA effluent limits for TPHs and PAHs are also shown in Table 3.It can 132

be seen that spent drilling mud from different oil wells have varying concentrations of the 133

contaminants. 134

135

Table 2: Physico-chemical parameters of the spent drilling muds 136

S/NO

Parameters

A

Sample

B

C

D

E

1 pH 7.5 ± 0.01b 7.3 ± 0.01

a 7.8 ± 0.00

c 7.4 ± 0.09

a 7.9 ± 0.00

c

2 Temperature(oC) 28 ± 0.00

a 28.3 ± 0.10

b 28.7 ± 0.05

c 29.0 ± 0.00

d 28.5 ± 0.10

bc

3 Nitrogen (mg/L) 0.06 ± 0.004b 0.08 ± 0.005

d 0.06 ± 0.004

b 0.04 ± 0.002

a 0.05 ± 0.003

ab

4 Potassium (mg/L) 2.0 ± 0.3ab

2.7 ± 0.3d 1.7 ± 0.2

a 2.2 ± 0.1

ab 2.0 ± 0.2

ab

5 Sodium (mg/L) 2.4 ± 0.03b 1.7 ± 0.02

a 2.3 ± 0.03

b 1.7 ± 0.10

a 2.4 ± 0.10

b

6 Calcium (mg/L) 13.4 ± 0.2a 16.3 ± 0.2

c 17.4 ± 0.00

d 14.7 ± 0.10

b 19.10 ± 0.2

e

7 Phosphate(mg/L) 2.3 ± 0.03a 7.4 ± 0.03

d 7.6 ± 0.05

e 5.8 ± 0.03

c 3.8 ± 0.04

b

8 Conductivity 2.58 ± 0.02a 2.68 ± 0.02

b 2.84 ± 0.03

c 2.62 ± 0.02

ab 2.86 ± 0.02

c

9 Chlorides (mg/L) 18.8 ± 0.2a 22.2 ± 0.4

b 23.3 ± 0.43

c 19.64 ± 0.04

a 25.47 ± 0.03

d

10 TOC (%) 1.4 ± 0.2a 1.8 ± 0.2

a 1.95 ± 0.3

a 2.0 ± 0.3

a 1.6 ± 0.3

a

11 DO (mg/L) 7.1 ± 0.3a 7.95 ± 0.45

a 10.4 ± 0.4

b 8.4 ± 0.5

a 7.2 ± 0.4

a

12 Moisture Content (%) 8.9 ± 0.6bc

9.2 ± 0.4bc

7.6 ± 0.3ab

10.3 ± 0.3c 6.8 ± 0.5

a

13 CO2 (mg/L) 1.6 ± 0.1a 1.8 ± 0.1

a 2.2 ± 0.2

a 1.7 ± 0.3

a 2.1 ± 0.4

a

7

14 TPHs (mg/L) 6211 ± 10a 8591 ± 8

c 9474 ± 10

d 10110 ± 10

e 7482 ± 8

b

15 PAHs(mg/L) 82.0 ± 0.5a 94.6 ± 0.4

d 84.7 ± 0.3

b 86.25 ± 0.55

b 92.6 ± 0.4

c

16 THB (CFU/ml) 9.4 ± 0.1×105e

7.6 ± 0.02×105a

8.4 ±0.01×104b

9.3 ± 0.0×105d

8.9 ± 0.05×105c

17 HUB (CFU/ml) 4.3 ± 0.1×104c

6.3 ±0.1×104a

5.2 ± 0.01×105d

6.4 ±0.1×104e

9.9 ± 0.01×104b

a-e

Results are presented as mean ± standard error. Means with different superscript, the 137

homogenous subset of means, (a, ab, b, bc, c, d and e) within the same rows indicate significant 138

differences (p < 0.05), 139

140

Legend: 141

DO = Dissolved Oxygen; 142

TOC=Total Organic Carbon; 143

TPHs=Total Petroleum Hydrocarbons; 144

PAHs=Polycyclic Aromatic Hydrocarbons; 145

HUB=Hydrocarbon Utilizing Bacteria, and; 146

THB=Total Heterotrophic Bacteria. 147

148

Table 3: DPR (Nigeria) and US EPA guidelines and standards for TPHs and PAHs 149

Parameters Nigeria (DPR) USEPA

TPHs (Inland-fresh waters) (mg/L) 10 -

TPHs (Nearshore-brackish/saline waters) (mg/L) 20 -

TPHs (mg/L) - 5

PAHs (mg/L) 1 0.1

Sources:Department of Petroleum Resources (DPR2002);U.S. Environmental Protection Agency 150

(2018). 151

152

TPHs and PAHsbiodegradation 153

The laboratory test results for biodegradation of TPHs and microbial growth (HUB and THB) for 154

sample-A of the drilling mud impacted with Total Petroleum Hydrocarbonsand Polycyclic 155

AromaticHydrocarbonsusing 20g,25g, and 30g doses of urea fertilizer are presented in Figures 2 156

through 5. The population of the microorganisms varied from sample to sample. When stimulated 157

by the addition of nutrients, the microbial population count of the indigenous heterotrophic 158

bacteria increased. On amendment with 30g urea fertilizer, the total heterotrophic bacteria (THB) 159

grew from 9.40×105 CFU/ml and peaked in week 6 with a population of 6.27×10

8 CFU/ml before 160

8

dropping to 3.79×108 in week 12. The hydrocarbon utilizing bacteria (HUB) grew from 4.30×10

5 161

CFU/ml peaking in week 6 to 4.52×105 CFU/ml. After reaching this peak, the HUB started 162

dropping gradually to 2.63×108 in week 12. The same trend was observed with treatment using 163

20g, and 25g of urea fertilizer. This is represented in Figures 2 through 5. It is this growth that can 164

lead to the metabolizing of the hydrocarbons. 165

166

The biodegradation of hydrocarbon contaminants (TPHs and PAHs) for the study period of 12 167

weeks (using 20g, 25g, and 30g urea fertilizer amendments) is also shown in Figures 2 through 5. 168

The results show a sharp decrease in TPHs and PAHs concentrations in the first four weeks. This 169

indicates a period of active degradation by the microorganisms. After week 6, the degradation 170

level decreased, and that may be attributed to the microorganisms transiting into the stationary 171

phase after massive degradation had taken place between week 1 and 6. The results show an 172

average percentage degradation of 99.9% in 12 weeks for TPHs for the 5 samples studied. Also, 173

PAHs showed an average percentage degradation of 99.3% in 12 weeks for the five samples 174

175

176

4.30E+05

5.04E+07

1.00E+08

1.50E+08

2.00E+08

2.50E+08

3.00E+08

3.50E+08

4.00E+08

4.50E+08

5.00E+08

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

0 2 4 6 8 10 12 14

HU

B (

CF

U/m

l)

TP

H (

mg

/L)

Time (week))

20gTPH (mg/L)

25gTPH (mg/L)

30g TPH (mg/L)

20g HUB (CFU/ml)

25g HUB (CFU/ml)

30g HUB (CFU/ml)

9

Figure 2: Distribution of TPHs and HUB for Sample-A 177

178

179

180

Figure 3: Distribution of TPHs and THB for Sample-A 181

182

183

184

185

9.40E+05

1.01E+08

2.01E+08

3.01E+08

4.01E+08

5.01E+08

6.01E+08

7.01E+08

0

1000

2000

3000

4000

5000

6000

7000

0 2 4 6 8 10 12 14

THB

(CFU

/ml)

TPH

(mg/

L)

Time(week)

20g TPH (mg/L)

25g TPH (mg/L)

30g TPH (mg/L)

20g THB (CFU/ml)

25g THB (CFU/ml)

30g THB (CFU/ml)

10

186

187

188

11

189

Figure 4: Distribution of PAHs and HUB for Sample-A 190

191

4.30E+05

5.04E+07

1.00E+08

1.50E+08

2.00E+08

2.50E+08

3.00E+08

3.50E+08

4.00E+08

4.50E+08

5.00E+08

0

10

20

30

40

50

60

70

80

90

0 2 4 6 8 10 12 14

HU

B(C

FU/m

l)

PA

Hs(

mg/

L)

Time(week)

20g PAHS (mg/L)

25g PAHS (mg/L)

30g PAHS (mg/L)

20g HUB (CFU/ml)

25g HUB (CFU/ml)

30g HUB (CFU/ml)

12

192

Figure 5: Distribution of PAHs and THB for Sample-A 193

194

195

Control for Sample-A 196

The result of TPHs, PAHs, and the ratio of HUB and THB for Control Sample-A is shown in 197

Figure 6.The control sample did not show any appreciable decontamination. 198

199

200

9.40E+05

1.01E+08

2.01E+08

3.01E+08

4.01E+08

5.01E+08

6.01E+08

7.01E+08

0

10

20

30

40

50

60

70

80

90

0 2 4 6 8 10 12 14

TH

B (

CF

U/m

l)

PA

Hs

(mg

/l)

Time (week)

20g PAHS

(mg/L) 25g PAHS

(mg/L) 30g PAHS

(mg/L) 20g THB

(CFU/ml) 25g THB

(CFU/ml)

13

201

Figure 6: Distribution of TPHs, PAHs and HUB/THB ratio for Control Sample-A 202

203

Bioremediation Indicators for Sample-A 204

The result of bioremediation indicators for Sample-A using 30g of urea fertilizer is shown in 205

Figure 7. The corresponding result for thecontrol sample is presented in Figure 8.The 206

bioremediation indicators for the amended sample,reflected the decontamination process, as 207

against the control sample where the indicators were inactive. 208

209

0

10

20

30

40

50

60

70

80

90

1000

2000

3000

4000

5000

6000

0 2 4 6 8 10 12 14

PA

H(m

g/l

) ;

HU

B/T

HB

(%

)

TP

H (

mg

/l)

Time (weeks)

TPH (mg/L)

(HUB/THB)*100

PAHS (mg/L)

14

210

Figure 7: Distribution of bioremediation indicators for treatment of Sample-A using 30g urea fertilizer 211

212

213

0

2

4

6

8

10

12

14

16

18

0

5

10

15

20

25

30

35

0 2 4 6 8 10 12 14

P(m

g/L)

;N(m

g/L)

TOC

(mg/

L);C

O2

(mg/

L);O

2(m

g/L)

;pH

;Te

mp

(oC

);H

20

(%)

Tme(week)

TOC (%)

O2 (mg/L)

Temp(Oc)

P (mg/L)

N (mg/L)

CO2 (mg/L)

Ph

H2O

pH

CO2(mg/L)

H2O (%)

O2 (mg/L)

15

214

Figure 8: Distribution of bioremediation indicators for control Sample-A 215

216

Percentage removal of TPHs and PAHs in Sample-A in week six and week twelve 217

The percentage removal of TPHs and PAHs in Sample-A using 30g urea fertilizer, in week six and 218

twelve are shown in Figure 9. Also shown in Figure 9 is the corresponding TPHs and PAHs 219

reduction in the control samples for week six and twelve. 220

221

222

223

0

2

4

6

8

10

12

14

16

0

5

10

15

20

25

30

35

0 2 4 6 8 10 12 14

TOC

(%);

P(m

g/L)

;CO

2(m

g/L)

;O2(m

g/L)

;H2O

(%)

N(m

g/L)

;PH

;Tem

p(o

C)

Time(weeks)

N (mg/L)

Ph

Temp(oC)

TOC (%)

P (mg/L)

CO2 (mg/L)

O2 (mg/L)

H2O(%)

CO2 (mg/L)

H2O(%)

O2 (mg/L)

pH

16

Fig 9: Percentage removal of TPHs and PAHs in Sample-A for week 6 and 12 224

Model for the prediction of residual concentration of TPHs and PAHs, and microbial growth 225

using 20g, 25g, and 30g urea fertilizer treatment of spent synthetic based mud 226

The average of the collected data (MUD A-E) with respect to the experimental set up with 20g 227

urea fertilizer is presented in Table 4. 228

Table 4: Average results of Petroleum contaminants (TPHs and PAHs) degradation and microbial 229

counts using 20g of urea fertilizer 230

Time

(week)

THB

(CFU/ml)

HUB

(CFU/ml)

TPHs

(mg/L)

PAHs

(mg/L)

0 8.72×105 3.50×10

5 8373.6 88.06

2 6.24×106 2.94×10

6 3686.4 44.46

4 4.52×107 2.41×10

7 1620.4 21.88

6 3.33×108 2.12×10

8 714.6 11.48

8 2.86×108 1.80×10

8 314.0 5.72

10 2.45×108 1.52×10

8 139.0 2.86

12 2.10×108 1.29×10

8 62.0 1.48

231

Note: log10 equivalent of HUB and THB were used for the model 232

233

Table 5 shows a summary of regression power models of PAHs treatment using 20g urea fertilizer. 234

The exponential model is the best model with respect to R2, Mean Square Error, MSE and Root 235

Mean Square Error, RMSE values. 236

237

238

239

240

Table 5: Summary of regression power models of PAHs using 20 ,25 and 30g urea fertilizer treatment 241

Model Type Equation R2 MSE RMSE

17

± The best model with respect to R2, MSE and RMSE values 242

A repetition of regression power modeling was carried out for the other parameters, based on R2, 243

MSE, and RMSE values. The resultant model equations for biodegradation of TPHs and PAHs and 244

microbial growth using 20g, 25g, and 30g urea fertilizer are given in Table 6. 245

Table 6: Model equations for TPHs and PAHs degradation and microbial growth using 20g 25g 246

and 30g urea fertilizer treatment 247

Parameter Model Type Model Equations R2 MSE

20g urea fertilizer Application

TPHs (mg/L)

Exponential 8373.6e

-0.409t 1 1.191

PAHs (mg/L) Exponential 88.06e-0.341t

0.9999 0.054

HUB (CFU/ml) 4th order Polynomial 0.0009t4 – 0.0228t

3 + 0.1343t

2 + 0.2512t + 5.552 0.9944 0.021

THB (CFU/ml) 4th order Polynomial 0.0009t4 - 0213t

3 + 0.1253t

2 + 0.2333t + 5.9467 0.9943 0.017

25g urea fertilizer Application

TPHs (mg/L)

Exponential 8373.6e

-0.472t 1 8.662

PAHs (mg/L) 4th order Polynomial 0.0091t4 - 0.3283t

3 + 4.6054t

2 - 30.892t + 88.049 1 0.055

HUB (CFU/ml) 4th order Polynomial 0.0001t4 – 0.0242t

3 + 0.1413t

2 + 0.2734t + 5.5515 0.9944 0.022

THB (CFU/ml) 4th order Polynomial 0.0009t4 – 0.0224t

3 + 0.1315t

2 + 0.2475t + 5.947 0.9943 0.019

30g urea fertilizer Application

TPHs (mg/L)

Exponential 8373.6e

-0.571t 0.9997126.751

PAHs (mg/L) Exponential 88.06e-0.404t

0.9998 0.025

HUB (CFU/ml) 4th order Polynomial 0.001t4 – 0.0251t

3 + 0.1459t

2 – 0.2902t + 5.5507 0.9947 0.022

THB (CFU/ml) 4th order Polynomial 0.0001t4 – 0.0234t

3 + 0.1373t

2 + 0.2611t + 5.9473 0.9943 0.021

248

249

±Exponential PAHs = 88.06e-0.341t 0.9999 0.054 0.233

Polynomial

2nd order PAHs = 0.9493t2 - 17.805t + 82.596 0.9755 36.50 6.041

3rd order PAHs = -0.1001t3 + 2.7506t

2 - 25.81t + 87.4 0.9987 2.521 1.588

4th order PAHs = 0.008t4 - 0.2925t

3 + 4.1752t

2 - 29.053t + 88.059 1 0.06 0.244

5th order PAHs = -0.0001t5 + 0.0118t

4 - 0.3324t

3 + 4.3436t

2 - 29.288t + 88.071 1 0.108 0.328

6th order PAHs = -0.0002t6 + 0.0077t

5 -0.0937t

4 + 0.3291t

3 + 2.4632t2 -27.409t + 88.06 1

18

Parameter Model Type Model Equations R2 MSE

20g urea fertilizer Application

TPHs (mg/L)

Exponential 8373.6e

-0.409t 1.000 1.191

PAHs (mg/L) Exponential 88.06e-0.341t 0.9999 0.054

HUB

(CFU/ml)

4th order

Polynomial 0.0009t

4 – 0.0228t

3 + 0.1343t

2 + 0.2512t + 5.552

0.9944 0.021

THB

(CFU/ml)

4th order

Polynomial 0.0009t

4 - 0213t

3 + 0.1253t

2 + 0.2333t + 5.9467

0.9943 0.017

25g urea fertilizer Application

TPHs (mg/L)

Exponential 8373.6e

-0.472t 1 8.662

PAHs (mg/L) 4th order

Polynomial 0.0091t

4 - 0.3283t

3 + 4.6054t

2 - 30.892t + 88.049

1 0.055

HUB

(CFU/ml)

4th order

Polynomial 0.0001t

4 – 0.0242t

3 + 0.1413t

2 + 0.2734t + 5.5515

0.9944 0.022

THB

(CFU/ml)

4th order

Polynomial 0.0009t

4 – 0.0224t

3 + 0.1315t

2 + 0.2475t + 5.947

0.9943 0.019

30g urea fertilizer Application

TPHs (mg/L)

Exponential 8373.6e

-0.571t 0.9997 126.751

PAHs (mg/L) Exponential 88.06e-0.404t 0.9998 0.025

HUB

(CFU/ml)

4th order

Polynomial 0.001t

4 – 0.0251t

3 + 0.1459t

2 – 0.2902t + 5.5507

0.9947 0.022

THB

(CFU/ml)

4th order

Polynomial 0.0001t

4 – 0.0234t

3 + 0.1373t

2 + 0.2611t + 5.9473

0.9943 0.021

250

3.2 Discussion 251

19

Maximum allowable limits of hydrocarbon pollutants in waste media 252

The baseline results of the spent drilling mud (Table 2), show that the concentrations of TPHs and 253

PAHs in the five samples exceeded the maximum allowable limits for Nigeria and US EPA (Table 254

3). The high levels of TPHs and PAHsrecordedin the mud are capable of affecting the nutrient 255

levels, aeration and soil microbial diversity, and can even enter the food chain if disposed 256

untreated (Liu et al., 2016). This means that the spent mud has to be treated before disposal. The 257

Department of Petroleum Resources (DPR), the regulatory body in Nigeria, demands a reduction 258

of TPHs to less than 10mg/L and 20mg/L for inland and nearshore waters disposal respectively, 259

while the US EPA requires a concentration of less than 5mg/L. For PAHs, DPR requires a 260

concentration of less than 1mg/L, while the US EPA demands less than 0.1 mg/L for effluent 261

disposal. The remediation method employed in this study met the above limits for both TPHs and 262

PAHs. 263

The measured pH values were within the neutral range (provide the neutral pH range that was 264

measured here). Measured pH is an important factor that affects microbial growth (Wu, 2016). The 265

relationship between pH and microbial growth fits into a quadratic model: higher growth in neutral 266

media and lower in acidic and alkaline media. Temperature is in the mesophilic range. Both 267

temperature and pH conditions support bioremediation (Adam et al.,2015). ). Solubility of TPHs 268

and PAHs increases with temperature, which improves their bioavailability (Chen et al., 2015). 269

Most hydrocarbon degrading microorganisms perform optimally in the mesothermic temperature 270

range (20oC to 35

oC) (Wu, 2016). Though some microorganisms have been known to degrade 271

TPHs and PAHs under acidic and alkaline conditions (Shalluet al., 2014), most microorganisms 272

metabolize TPHs and PAHs in neutral pH ranges (Vila et al., 2015). 273

274

The measured dissolved oxygen had values that support bioremediation. Though bioremediation of 275

organic contaminants such as TPHs and PAHs can take place under both aerobic and anaerobic 276

conditions, it has been reported that the magnitude of anaerobic degradation is less than that of 277

20

aerobic (Xu et al., 2014). In aerobic degradation, dissolved oxygen is needed for respiration of the 278

microbes, and is required throughout the subsequent degradation process (Ren et al., 2015). The 279

aeration of the samples during biodegradation, provided more oxygen for the process. 280

The spent drilling mud contained low levels of micro nutrients such as nitrogen, phosphorous, 281

potassium and calcium. The measured organic matter contents (total organic carbon: TOC) of the 282

samples can be classified as average for spent drilling mud. TOC facilitates the moisture retaining 283

capacity of the mud (Chen et al., 2016). The measured average nitrogen level of 0.06% is low for 284

effective microbial growth (Xu et al.,2014). This is in line with several findings on hydrocarbon 285

contaminated sites (Azarbadet al., 2015). Also, the average phosphorous level of 5.4mg/L was low 286

and promoted microbial growth (Subathra, et al, 2013). The high carbon-to-phosphorous (C/P) 287

ratio resulting from crude oil addition, in crude oil-contaminated media, and the utilization of 288

inorganic phosphorous by the microorganisms, which attack the hydrocarbons, are responsible for 289

the low level of phosphorous recorded (Thenmozhiet al., 2012). 290

The ability of microorganisms to degrade hydrocarbons depends on the microbes’ population (Abu 291

et al., 2008). The spent drilling mud microorganisms’ number is usually in the range 104

to 107 292

Colony Forming Units (CFUs)/ml. This number should not be less than 103 per milligram of spent 293

drilling mud for successful biodegradation (Margesin, et al., 2003). The microbial load recorded in 294

the five samples were good enough for bioremediation (Sawulski, 2014). 295

Bioremediation is a rate limiting process,best described by the Monod equation 296

µ= (µmax *S)/ (KS +S) 297

where µmax =maximum specific growth rate, KS=Monod constant, S= substrate concentration. 298

21

The specific growth rate (µ)is controlled by the nature of the organism and the limiting nutrients 299

in the medium, such as N and P.This leads to the uptake of the contaminants and subsequent 300

removal i.e, the impacted medium is remediated. 301

Moisture is essential in the biodegradation process for the transportation of foods, nutrients and 302

waste products in and out of the microorganisms (Sawulskiet al.,2014). Moisture content of the 303

mud samples ranged from 6.8 to 10.3%. 304

The degradation of TPHs and PAHs support previous studies that by improving the limiting factors 305

to bioremediation of hydrocarbon contaminated spent drill mud, the degradation rate would be 306

improved (Ofoegbuet al., 2015). The pH remained largely neutral throughout the treatment. 307

The control samples showed low microbial growth. TPHs and PAHs degradation was also low. 308

Bioremediation indicators, TOC, nitrogen, dissolved oxygen, CO2, and phosphorous recorded 309

during the remediation period both for the stimulated samples and the control samples showed that 310

the degradation of TPHs and PAHs were a result of bioremediation. For the stimulated samples, 311

TOC, nitrogen, dissolved oxygen, and phosphorous, showed a decline because of their utilization 312

by the microorganisms, while CO2 and water, which are by-products of bioremediation, increased. 313

However, in the control samples, these parameters showed slight changes, which could be 314

attributed to other natural attenuation processes including volatilization, photo oxidation, etc. (Al-315

Awadhi, 2013;Abu and Dike,2008). 316

317

Nonlinear Regression Equations 318

Nonlinear regression equations developed for the petroleum contaminants (TPHs and PAHs) 319

treatment with 20g, 25g, and 30g urea fertilizer show a high goodness of fit, R2 of 0.999. With 320

these models, it may no longer be necessary to repeat all the experiments in the treatment of spent 321

22

drilling mud during bioremediation. Once the parameters in the model equations are established, 322

the model can be used to predict the residual concentration of TPHs and PAHs at any time, to a 323

very high accuracy. The microbial growth can also be predicted, accurately. This will give a good 324

idea of when treatment would be completed and save a lot of time and resources in the treatment of 325

spent drilling mud using this method. 326

327

4. CONCLUSION 328

Based on this study, the following conclusions can be drawn: 329

(1) Spent drilling mud from different fields have different concentrations of TPHs and PAHs. 330

(2) Urea fertilizer is effective in bioremediation of hydrocarbon impacted spent drilling mud. All 331

of the five amended samples achieved more than 97% removal in 6 weeks. A removal of up to 332

99.5% was achieved in 12 weeks. 333

(3) The residual levels of TPHs and PAHs in the five spent drilling mud samples tested complied 334

with Nigerian DPR and US EPA prescribed limits for disposal. 335

(4) Regression models of exponential and higher order polynomials were developed to predict with 336

high accuracy, the residual concentration of TPHs and PAHs, at any given time, in a hydrocarbon -337

impacted spent drilling mud using urea fertilizer. 338

339 340 341 342

343 344 345

346

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