Environment-Friendly Deoxygenation of Non-Edible Ceiba oil to Liquid Hydrocarbon Biofuel: Process Parameters and Optimization Study

doi:10.21203/rs.3.rs-582604/v1

Non-edible Ceiba oil has feasibility as a sustainable biofuel resource in tropical countries that act as alternative to a portion of the fossil fuels used today.Catalytic deoxygenation of the Ceiba oil (high O/C ratio) was conducted to produce hydrocarbon biofuel (high H/C ratio)over NiO-CaO₅/SiO₂-Al₂O₃catalyst with aims of high diesel selectivity and catalyst reusability. In the present study, Box-Behnken experimental design was used to evaluate and optimize liquid hydrocarbon yieldby considering following reaction factors: catalyst loading (1-9 wt.%), reaction temperature (300 - 380°C) and reaction time (30 -180 min). It was discovered that the optimum yield for hydrocarbon fractionsn-(C₈– C₂₀) was 77% under deoxygenation condition of 5 wt.% catalyst loading, reaction temperature of 340°C within 105 min. Besides, deoxygenationmodel indicated that interaction effects of catalyst loading-reaction time influence the deoxygenation activity greatly. Based on the product analysis, oxygenated species(e.g. CO₂ and CO) were removed mainly via decarboxylation/decarbonylation (deCOx) pathways. The NiO-CaO₅/SiO₂-Al₂O₃catalyst is stable for five consecutive runs with hydrocarbon fractions within range of 66-75% and n-(C₁₅+C₁₇) selectivity of 64-72% as well. The stability profile of NiO-CaO₅/SiO₂-Al₂O₃ catalyst indicated that the catalyst able to maintain deoxygenation reactivity throughout five cycles with hydrocarbon yield of 66-75% and n-(C15+C17) selectivity of 64–72 %. However, coke deposition was noticed for the spent catalyst after several times of usage, which due to the high reaction temperature above 300 ^oC.

Environmental Chemistry

Toxicology

C8-C20 hydrocarbon

free fatty acid

green diesel

RSM

Alternative fuel

catalyst

Green diesel has potential as a bio-based hydrocarbon fractions for the blending with petrol-based diesel for the sake of sustainable and clean energy with climate change mitigation, that in line with sustainable development goals (goal 7 and goal 13) (Khan et al. 2015)(Shamanaev et al. 2020). The green diesel is renewable fuel that composed of petro-mimicked structures obtained from triglyceride-based plant oil conversion via deoxygenation (DO) processes (Rogers and Zheng 2019)(Asikin-Mijan et al. 2020a). The deoxygenation process involves both decarboxylation/decarbonylation (deCOx) pathways that produce diesel-range hydrocarbons from triglycerides and fatty acid derivatives by removal of CO₂/CO gas under inert condition (Pattanaik and Misra 2017)(Asikin-Mijan et al. 2020b).

The feedstock for green diesel recently focused on the utilization of non-edible feedstock, this is due to the food versus fuel issue and land degradation due to over agriculture crops plantation activity (Khan et al. 2015)(Abdulkareem-Alsultan et al. 2019)(Liu et al. 2012). Ceiba pentandra generally known as silk-cotton tree that highly available in Southeast Asia, India and Sri Lanka (Dharma et al. 2016). The ceiba pentandra also plays role as drought-resistant plant, which is easily growth in humid and tropical regions. The ceiba trees consisted of 25–28 wt.% of seeds with oil productivity of 11–28 %, which is 1280 kg/ha of oil(Ong et al. 2014). Ceiba oil is potential oils with production of 280516 million tonnes per annum but only few % is being utilized (Balajii and Niju 2020). Recently, ceiba pentandra oil (CPO) was selected for the production of renewable fuel such as biodiesel, yet it is believed that there is no studies focus on process optimization for the production of CPO-derived green diesel by using response surface methodology (RSM) tool.

Catalyst is important to drive the deoxygenation reaction. Previously, we have reported the used of NiO-CaO₅/SiO₂-Al₂O₃ catalyst as effective catalyst for deoxygenation of triglycerides model compound (triolein) and real feedstocks (Asikin-Mijan et al. 2016b)(Asikin-Mijan et al. 2018). Based on those studies, the catalytic reactivity of NiO-CaO₅/SiO₂-Al₂O₃ catalyst was efficiently deoxygenizing various type of feeds (triolein, jatropha oil, waste cooking oil and palm fatty acid distillate) through selective deCOx pathways with 54–74% of n-(C₁₅ + C₁₇) selectivity and hydrocarbon liquid yield of > 74%. Yet, this catalyst still exhibited higher affinity toward coking after reused multiples cycles with coke > 14 wt.%. It is believed that cracking and coking were motivated by existence of high unsaturated fatty acid species in the feedstock (FFA > 15%) (Abdulkareem-Alsultan et al. 2020)(Li et al. 2017). Considering this problem herein the cracking and the coking can be suppressed by utilization of low FFA feedstock such as CPO. Furthermore, the present study also highlights the optimization of CPO via RSM approach and the stability of the used catalyst investigated in detail.

2.1 Materials

Nickel (II) nitrate hexahydrate (Ni(NO₃)₂·6H₂O, > 99%) and calcium nitrate tetrahydrate (Ca(NO₃)₂·4H₂O, > 99%) were obtained from R&M Company. Silica-alumina (SiO₂-Al₂O₃, grade 135) was procured from Sigma-Aldrich. The standard solvents and chemicals for gas chromatography (GC) analysis: alkane (C₈–C₂₀), nonene standard solutions and internal standard (1-bromohexane, > 98%) were purchased from Sigma-Aldrich. For GC solvent dilution, analytical grade n-hexane with purity > 98% was obtained from Merck. Ceiba Pentandra seeds were purchased from West Java, Indonesia. The CPO were extracted from its seeds via similar method reported by Ong et al. (Ong et al. 2013). The physicochemical properties and fatty acid composition of CPO were tabulated in Table 1.

Table 1

The physicochemical properties and fatty acid composition of CPO.
Oil properties	Value	Method
Acid value (mg KOH − 1)	11.9	AOCS Ca5a-40
FFA value (%)	5.9	AOCS Ca-5a-40
Fatty acid composition of oil (%)		AOCS Ce1-62 & Ce-661
Lauric (C12:0)	0.1
Myristic (C14:0)	0.1
Palmitic (C16:0)	19.2
Palmitoleic (C16:1)	0.3
Stearic (C18:0)	2.6
Oleic (C18:1)	17.4
Linoleic (C18:2)	39.6
Linolenic (C18:3)	1.5
Arachinic (C20:0)	0.56
Malvaloyl C18:CE)	18.5
Others	0.34

2.2 Catalyst synthesis

The SiO₂-Al₂O₃ supported Ni-Ca oxides catalyst was synthesized via wet impregnation method, which is similar to our previous study (Asikin-Mijan et al. 2016b)(Asikin-Mijan et al. 2018). The catalyst support (SiO₂-Al₂O₃) was mixed to the metal salts solutions and stirred for 6 h under ambient conditions. The final mixtures then further dried at a temperature of 100°C in the oven. Then, the dried sample further ground into fine powder prior to calcine at a temperature of 500°C for 2 h under atmosphere condition. The catalyst was denoted as NiO-CaO₅/SiO₂-Al₂O₃.

2.3 Deoxygenation of CPO

The catalytic deoxygenation reaction of CPO was conducted in a 250 mL semi-batch reactor (Fig. 1). Approximately 10 g of CPO and selective amount of catalyst was added into reactor vessel. The deoxygenation process was performed under N₂ flow with respective reaction conditions that created by RSM tools (refer to Sect. 2.4).

2.4 Optimization design by Box-Behnken of RSM

Response surface methodology (RSM) with Box–Behnken experimental design was used to investigate the effects of different factors on deoxygenation of CPO and the interaction effects of factors towards the hydrocarbon yield response. Based on our former finding (Asikin-Mijan et al. 2017b), the three factors [catalyst loading (A), time (B) and temperature (C)] were identified as important parameters that highly influence the catalytic deoxygenation of CPO. The coded and uncoded levels of the independent parameters, as well as 17 runs of experimental design was depicted in Table 2 and Table 3, respectively.

Table 2

Box – Behnken coded and uncoded independent variables for optimization of ceiba oil over NiO-CaO₅/SiO₂-Al₂O₃ catalyst
Factors	Units	Level
Factors	Units	-1	0	+ 1
A: Catalyst Loading	wt. %	1	5	9
B: Time	min	30	105	180
C: Temperature	°C	300	340	380

Table 3

Experimental design generated by RSM and responses from each reaction
No.	A:Catalyst Loading (wt.%)	B:Reaction Time (min)	C:Temperature (°C)	Hydrocarbon Yield (%)
No.	A:Catalyst Loading (wt.%)	B:Reaction Time (min)	C:Temperature (°C)	Experimental response	Predicted response
1	1	30	340	79.01	71.89
2	9	30	340	74.60	75.41
3	1	180	340	66.09	65.28
4	9	180	340	25.00	45.52
5	1	105	300	71.39	78.30
6	9	105	300	83.43	72.02
7	1	105	380	65.25	76.67
8	9	105	380	70.63	63.71
9	5	30	300	74.39	85.00
10	5	180	300	70.98	64.86
11	5	30	380	73.53	79.64
12	5	180	380	70.89	60.28
13	5	105	340	72.26	73.54
14	5	105	340	75.23	73.54
15	5	105	340	73.40	73.54
16	5	105	340	74.50	73.54
17	5	105	340	74.10	73.54

2.5 Product analysis

Quantitative tests of produced CPO green diesel such as total hydrocarbon fractions ranged C₈–C₂₀ (X_A, yield %) and selectivity of product carbon number (S_i, %) were determined by GC-FID (Shimadzu GC-14B) equipped with a HP-5 capillary column (length 30 m × inner diameter 0.32 mm × film thickness 0.25 µm) at analysis temperature of 300°C. The analysis condition and method of calculation was according to our previous study (Asikin-Mijan et al. 2019)(Asikin-Mijan et al. 2020c). For qualitative analysis that used to determine chemical composition of samples, both raw CPO and the CPO green diesels were characterised by using GC-MS (model SHIMADZU QP5050A) with a non-polar DB-5HT column (30m × 0.25 mm × 0.1 µm) that used a splitless inlet. The selectivity of the deoxygenated products was determine according to our previous study (Asikin-Mijan et al. 2019)(Asikin-Mijan et al. 2020c). The chemical functional group of the CPO and CPO green diesel further determined by fourier transform infrared (FTIR) spectrometer Model: Perkin-Elmer (PS) equipped with a detector having a spectral range 300–3500 cm^− 1 with resolution 4 cm^− 1.

In our previous study (Asikin-Mijan et al. 2018), the optimum condition for deoxygenation of triglycerides model compound (triolein) and realistic feedstock (WCO, JCO, PFAD) for green diesel production over NiO-CaO₅/SiO₂-Al₂O₃ catalyst were studied under N₂ flow atmosphere condition. Table 4 compilation of optimum condition data in experimental work that were done in this system. Due to an excellent achievement of the NiO-CaO₅/SiO₂-Al₂O₃ catalyst in optimizing the deoxygenation activity using 7 wt.% catalyst loading at 350 ^oC within 60 min, hence, this optimum condition was used as a basis to conduct optimization of CPO via RSM approach and the response of each experimental runs are depicted in Table 3. The suitability of quadratic model as well as the adequacy of the generated RSM model was explained in supplementary section.

Table 4

Summary from experimental studies conducted in semi-batch reactor under N₂ flow condition over NiO-CaO₅/SiO₂-Al₂O₃ catalyst [16].
Feedstock	FFA (%)	Optimum condition	Hydrocarbon yield (%)	n-(C₁₅ + C₁₇) product selectivity
Triolein	2.5	Catalyst Loading: 7 wt.% Time: 60 min Temperature: 350 ^oC	92	61
WCO	18.4		87	54
JCO	15.4		74	80
PFAD	86.3		81	80

3.1 Interaction effect between deoxygenation parameters

The effect of the three reaction parameters towards the reactivity of deoxygenation process were presented in the form of three-dimensional (3D) response surface plot and contour plot. The presence of surface shape from 3D-surface plot indicated the effectiveness of interaction of two deoxygenation parameters towards the hydrocarbon yield and product selectivity. Meanwhile, the straightforward contour plot explains the overall nature of the response surface for the reaction model. Based on the interpretation from the model’s plots, a narrow and precise range of optimum value corresponding to the high yield of hydrocarbon as well as product selectivity can be obtained (Kılıç et al. 2014).

Figure 2a-b shows the 3D response plot and 2D contour plot for interaction between catalyst loading (A) and reaction time (B) towards hydrocarbon yield, where the temperature is fixed at 340°C. Result shows that maximum hydrocarbon yield obtains more than 77% when the catalyst loading in the range 4.5 wt.%, and at time between ~ 70 min. Nevertheless, increment of catalyst amount along with reaction time exhibit negative impact on the hydrocarbon yield. This agreed with negative interaction of AB in Eq. S1, which suggesting that simultaneous increase of both parameters will render negative impact on product yield. It was noted that reduced hydrocarbon yield at longer reaction time is caused by the unfavourable side reactions such as over-cracking or further polymerization of the deoxygenated liquid into lighter fractions. Additionally, longer reaction time reaction time will cause extensive catalyst deactivation due to coking, which in thus lowered deoxygenation activity (Pattanaik and Misra 2017).

Figure 2c-d displays 3D response surface plot and 2D contour plot of interactions between catalyst loading (A) and temperature (C) towards hydrocarbon yield, with reaction time at 105 min. Similar with above finding, high catalyst loading (> 7 wt.%) dramatically decrease the hydrocarbon yield. This phenomena was due to the excess of catalyst that resulted to mass transfer limitation between the oil and solid catalyst, which reduced the rate of deoxygenation process (Hermida et al. 2015). Based on the 2D contour plot, maximum hydrocarbon yield (77%) is achieved when 4.5 wt.% of catalyst were loaded into the reaction with reaction temperature ~ 320°C within 105 min. When comparing with data obtained in Fig. 2a-b, it clearly seen that reaction temperature plays an critical role in intensifying the kinetic reactivity of deCOx. The reaction model indicated that deoxygenation process was positively assisted at milder reaction temperature (320^oC).

The 3D response surface plot and 2D contour plot of interaction between reaction time (B) and temperature (C) of toward hydrocarbon yield using fix amount of catalyst loading (5 wt.% catalyst) were shown in Fig. 2e-f. Short reaction time and higher reaction temperature positively influence the deoxygenation activity. Notably, prolonging the reaction time in deoxygenation process does not improve the reaction activity and yield of product especially at intermediate temperature. High deoxygenation activity at higher reaction temperature was in agreement with Kubicka et al., (Kubičková and Kubička 2010), which yielded greater hydrocarbon yield when the reaction proceeded at higher reaction temperature. Similar finding also was reported by Pattanaik & Misra (Pattanaik and Misra 2017). Rich hydrocarbon obtained at high reaction temperature is highly correlated with the occurrence of cracking reaction via C-C bond cleavage (Ishihara et al. 2012). Whereby high cracking of CPO generally will lead to the formation of condensable reaction product which mainly comprised of short hydrocarbon fractions (gasoline: C₈-C₁₂) (Asikin-Mijan et al. 2017a). Based on the results generated from the Box-Behnken study, it can be concluded that optimum condition CPO deoxygenation toward formation of straight chain hydrocarbon fractions (77–81%) can be achieved at lower reaction temperature 300–340 ^oC, 5 wt.% catalyst loading and short reaction time ≤ 105 min.

Based on the curvatures nature of 3D surfaces in Fig. 2b, 2d and 2f, the results indicated that the mutual interaction of catalyst loading (A) with reaction time (B) was higher, as compared to the interaction parameters of AC and BC. Besides, the 3D surface plot revealed that the hydrocarbon yield varies remarkably with the increase of reaction time and catalyst loading. This revealed that most important variable in motivating the deoxygenation of CPO are reaction time and catalyst loading.

3.2 Product distribution profile for optimized hydrocarbon liquid product

To examine the predicted validity of Box-Behnken experimental design, the optimum condition of deoxygenation reaction of CPO over NiO-CaO₅/SiO₂-Al₂O₃ catalyst was performed under one optimized condition; reaction condition: 5 wt.% catalyst loading, 105 min at 340 ^oC under N₂ flow. Based on GC-FID analysis, the experimental result showed that the total hydrocarbon yield obtained is 75%, which is slightly less than predicted value from the reaction model (77%). The small degree of error (average of error = 2.2%) indicated the high accuracy of this deoxygenation model. It should be noticed that the liquid deoxygenated product also mainly diesel hydrocarbon fractions (n-(C₁₅ + C₁₇)) (72%) and minor of gasoline fractions n-(C₈-C₁₂) (Fig. 3a-b). As mentioned in Table 1, majority of fatty acid composition in CPO are C₁₆ (palmitic acid − 9.2 wt.%) and C₁₈ (oleic acid – 17.4 wt.% and linoleic acid – 39.6 wt.%). As shown in the product selectivity profile, the NiO-CaO₅/SiO₂-Al₂O₃ catalysed process rendered high deCOx selectivity with product favored of C_n−1 hydrocarbons. As a result, n-C₁₅ and n-C₁₇ hydrocarbon fractions are dominant in the liquid hydrocarbon. GC-MS analysis was conducted to determine the chemical composition of deoxygenated liquid product. As shown in Fig. 3c, majority of compounds in the liquid product consist of alkanes and alkenes with carbon range of C₈ – C₂₀ (selectivity ~ 77%), followed by alcohol which are E-11,13-Tetradecadien-1-ol, 1-Dodecanol and cis-7-Dodecen-1-yl acetate (selectivity 5.33%) and ketone (selectivity 0.47%). The chemical functional group of CPO and optimized deoxygenated liquid product is displayed in Fig. 3d. The FTIR spectra of CPO showed the chemical characteristics of triglyceride (vegetable oil), with five main absorption bands at 715 cm^− 1 (C-H stretch), 1160 cm^− 1 (C-O stretch, carbonyl ester), 1453 cm^− 1 (C-H bend), 1740 cm^− 1 (C = O, ester) and 2920 cm^− 1 (C-H bend). In the case of deoxygenated liquid product, result indicated shifting of absorption band from 1740 cm^− 1 (attributed to C = O of ester group in triglyceride) into the absorption band at 1709 cm^− 1 (attributed to C = O of carboxylic acid) (Asikin-Mijan et al. 2016a). Disappearance of C-O group from deoxygenated product strongly affirmed that the oxygenated species is removed during the reaction.

3.3 Stability and reusability of NiO-CaO₅/SiO₂-Al₂O₃

According to the literature (Lee et al. 2013), catalyst’s reusability play critical role in determining the economical application of NiO-CaO₅/SiO₂-Al₂O₃ for for large-scale green diesel production. Due to this reason, the NiO-CaO₅/SiO₂-Al₂O₃ catalyst was reused for several runs under optimum deoxygenation condition at 340 ^oC, 105 min, and 3 wt.% catalyst loading under N₂. The catalyst was treated with hexane after each cycle, in oder to remove adsorbed organic materials followed by drying for 2 h in an oven. The results (Fig. 4a) indicated constant reactivity for five runs, which hydrocarbon yield was 75%, 71%, 70%, 69% and 66% for respective cycles, and the n-(C₁₅ + C₁₇) selectivity of 64–72 % for the five consecutive runs. It was suggested that the occurrence of coke deposition on the catalyst’s active sites during each reaction cycles has resulted the marginal decrease of catalytic activity (Asikin-Mijan et al. 2020c)(Basyar et al. 2018).

The coke deposition of fresh and spent NiO-CaO₅/SiO₂-Al₂O₃ (after fifth runs) was investigated by using TGA analysis (Fig. 4b). TGA profile indicated that fresh catalyst rendered minor weight-loss stage (5.01 ± 0.21%) at the temperature of 100–250°C, which attributed to decomposition of adsorbed water. Nevertheless, insignificant water weight loss is observed for spent catalyst, which suggesting multiple thermal deoxygenation process throughout the five runs facilitated the dehydration pathway, thus resulted in moisture-free NiO-CaO₅/SiO₂-Al₂O₃ catalysts (Communication et al. 2016). However, the spent catalyst showed significant second weight loss (23.2 ± 0.25%) at heating range of 300–600 ^oC that due to desorption of coke as CO or CO₂ (Asikin-Mijan et al. 2016b). Generally, the coke that desorbed at this range of temperature considered as “soft coke”, where the soft coke originates from the physicorbed carbonaceous or side product. Owing to the noticeable amount of coke formation on spent catalyst after five runs, hence it is strong affirmed that the reduction of the deoxygenation reactivity and deCOx product highly correlated with the coke deposited on the active sites of NiO-CaO₅/SiO₂-Al₂O₃ catalysts.

The study presented on the effect of deoxygenation parameters towards productivity of hydrocarbon fractions from non-edible CPO by using Box-Behnken-RSM tool. The deoxygenation model revealed that the most important variables to affect the process reactivity are reaction temperature and catalyst loading. Results indicated that NiO-CaO₅/SiO₂-Al₂O₃ catalysed process rendered optimal hydrocarbon yield (77%) and n-(C₁₅ + C₁₇) hydrocarbon fractions (72%) at reaction condition of 340 ^oC, 105 min, 5 wt.% catalyst loading under N₂ flow condition. It was noted that the NiO-CaO₅/SiO₂-Al₂O₃ catalyst favor of high deCOx pathways, which produced majority of diesel-ranged fractions at C₁₅ and C₁₇. The reusability profile explained that the NiO-CaO₅/SiO₂-Al₂O₃ catalyst was a stable catalyst with hydrocarbon yield within range of 66–75% and the n-(C₁₅ + C₁₇) selectivity of 64–72 % throught five consecutive runs. However, undesirable coking deposition of catalyst occurred at deoxygenation process above 300 ^oC resulted slight decrement of hydrocarbon yield and n-(C₁₅ + C₁₇) selectivity during each runs.

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

The sources of funding provided by University of Malaya MOHE-Top 100 (IIRG)-IISS (IIRG002A-2020IISS) and Geran Galakan Penyelidik Muda (GGPM) 2020-15 were used for the purpose of design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Authors' contributions

Nur Hafawati Binti Abdullah: Investigation, Validation, Writing-Original draft. Nurul Asikin Mijan: Conceptualization, Writing-Review & Editing. Yun Hin Taufiq-Yap: Writing-Review & Editing, Resources. Hwai Chyuan Ong: Writing-Review & Editing, Resources. Hwei Voon Lee: Supervision, Funding acquisition, Project administration, Writing-Review & Editing, Resources. All authors read and approved the final manuscript.

Acknowledgements

The authors of this work acknowledge financial support for this project from University of Malaya MOHE-Top 100 (IIRG)-IISS (IIRG002A-2020IISS), as well as external technical support from Geran Galakan Penyelidik Muda (GGPM) 2020-15.

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Graphicalabstract2.docx

Environment-Friendly Deoxygenation of Non-Edible Ceiba oil to Liquid Hydrocarbon Biofuel: Process Parameters and Optimization Study

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. Experimental

2.1 Materials

2.2 Catalyst synthesis

2.3 Deoxygenation of CPO

2.4 Optimization design by Box-Behnken of RSM

2.5 Product analysis

3. Results And Discussion

3.1 Interaction effect between deoxygenation parameters

3.2 Product distribution profile for optimized hydrocarbon liquid product

3.3 Stability and reusability of NiO-CaO₅/SiO₂-Al₂O₃

4. Conclusion

5. Declarations

6. References

Supplementary Files

Status:

Journal Publication

Version 1

Environment-Friendly Deoxygenation of Non-Edible Ceiba oil to Liquid Hydrocarbon Biofuel: Process Parameters and Optimization Study

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. Experimental

2.1 Materials

2.2 Catalyst synthesis

2.3 Deoxygenation of CPO

2.4 Optimization design by Box-Behnken of RSM

2.5 Product analysis

3. Results And Discussion

3.1 Interaction effect between deoxygenation parameters

3.2 Product distribution profile for optimized hydrocarbon liquid product

3.3 Stability and reusability of NiO-CaO5/SiO2-Al2O3

4. Conclusion

5. Declarations

6. References

Supplementary Files

Status:

Journal Publication

Version 1

3.3 Stability and reusability of NiO-CaO₅/SiO₂-Al₂O₃