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ACKNOWLEDGEMENT
This research work was partially supported by Graduate School of Chiang Mai University
REFERENCE
[1] Shestakova, M. and Sillanpää, M. 2013. Removal of dichloromethane from ground and wastewater: A
review. Chemosphere. 93: 1258-1267.
[2] Dridi-Dhaouadi, S., Douissa-Lazreg, N. and Ben & M’Henni, M. F. 2011. Removal of lead and yellow
44 acid dye in single and binary component systems by raw Posidonia oceanica and the cellulose
extracted from the raw biomass. Environmental Technology. 32(3-4): 325-340.
[3] Wanassi, B., Hariz, I.B., Ghimbeu, C.M., Vaulot, C., Hassen, M.B., and Jeguirim, M. 2017.
Carbonaceous adsorbents derived from textile cotton waste for the removal of Alizarin S dye from
aqueous effluent: kinetic and equilibrium studies. Environ. Sci. Pollut. Res. Int. 24: 10041-10055.
[4] Boudrahem, N., Delpeux-Ouldriane, S., Khenniche, L., Boudrahem, F., Aissani-Benissad, F., and
Gineys, M. 2017. Single and mixture adsorption of clofibric acid, tetracycline and paracetamol onto
activated carbon developed from cotton cloth residue. Process. Saf. Environ. Prot. 111: 544-559.
[5] Üner, O. and Bayrak, Y. 2018 The effect of carbonization temperature, carbonization time and
impregnation ratio on the properties of activated carbon produced from Arundo donax. Microporous
Mesoporous Mater. 268: 225-234.
[6] Zheng, J., Zhao, Q., and Ye, Z. 2014. Preparation and characterization of activated carbon fiber (ACF)
from cotton woven waste. Applied Surface Science. 299: 86-91.
[7] Ramos-Fernández, J.M., Martínez-Escandell, M., and Rodríguez-Reinoso, F. 2008. Production of
binderless activated carbon monoliths by KOH activation of carbon mesophase materials. Carbon. 46:
384-386.
[8] Xu, Z., Tian, D., Sun, Z., Zhang, D., Zhou, Y., Chen, W., and Deng H. 2019. Highly porous activated
carbon synthesized by pyrolysis of polyester fabric wastes with different iron salts: Pore development
and adsorption behavior. Colloids and Surfaces A. 565: 180-187.
[9] Siyasukh, A., Chimupala, Y. and Tonanon, N. 2018. Preparation of magnetic hierarchical porous
carbon spheres with graphitic features for high methyl orange adsorption capacity. Carbon. 134: 207-
221.
[10] Rufford, T.E., Hulicova-Jurcakova, D., Zhu, Z., and Lu, G.Q. 2011. A comparative study of chemical
treatment by FeCl3, MgCl2, and ZnCl2 on microstructure, surface chemistry, and double-
layercapacitance of carbons from waste biomass. J. Mater. Res. 25: 1451–1459.
[11] Weidenthaler, C. 2011. Pitfalls in the characterization of nanoporous and nanosized materials.
Nanoscale. 3(3): 792-810.
[12] Von Gunten, U., 2003. Ozonation of drinking water: Part II. Disinfection and by-product formation in
presence of bromide iodide or chloride. Water Res. 37: 1469-1487.
[13] Richardson, S.D., Plewa, M.,Wagner, E., Schoeny, R., De Marini, D., 2007. Occurrence, genotoxicity,
and carcinogenicity of regulated and emerging disinfection byproducts in drinking water: a review and
roadmap for research. Mutat. Res. 636: 178-242.
[14] Deng, Y., Zhang, Y., Lu, Y., Lu, K., Bai, H., and Ren, H. 2017. Metabolomics evaluation of the in
vivo toxicity of bromoacetonitriles: One class of high-risk nitrogenous disinfection byproducts.
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[15] Sing, K.S.W. 1985. Reporting physisorption data for gas/solid systems with special reference to the
determination of surface area and porosity (recommendations 1984). Pure & Appl. Chem. 57(4): 603-
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[16] Nieto-Delgado, C., Partida-Gutierrez, D., and Rangel-Mendez, J. R. 2019. Preparation of activated
carbon cloths from renewable natural fabrics and their performance during the adsorption of model
organic and inorganic pollutants in water. Journal of Cleaner Production. 213: 650-658.
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Characterization of MOF/PVDF Composite Membrane for
Dichloroacetic Acid Removal from Tap Water through
Electrochemical Oxidation
Toungnutcha Chantaramusagarn1* Jenyuk Lohwacharin2, §, * and Chalita Ratanatawanate3
1 Graduate student; 2Lecturer ; 3Researcher
Engineering, Chulalongkorn University, Bangkok, Thailand; § Research Network NANOTEC – CU on
Environment, Department of Environmental Engineering, Chulalongkorn University, Thailand.
*Phone : (+66)2-218-6671, Fax : (+66)2-218-6666, E-mail : [email protected]
ABSTRACT
Haloacetic acids (HAAs) received public concerns due to potential toxicity, carcinogenicity and their
presence in chlorinated tap water. Membrane-based processes is one of the promising technologies for
advanced water purification. Herein, composite membrane was developed by incorporating Metal Organic
Frameworks (MOFs), are a new class of crystalline materials, within the membrane. The objective of this
study is to develop the composite membrane for removing dichloroacetic acid (DCAA) via indirect
electrochemical oxidation. Fe-based metal-organic frameworks (Fe-MOFs) such as MIL-88B and NH2-MIL-
88B were used as electrocatalysts. As synthesis MOFs were characterized by (i) powder X-ray diffraction
(XRD); (ii) scanning electron microscopy (SEM); and (iii) Fourier-transform infrared spectroscopy (FTIR).
The SEM image shows that MIL-88B(Fe) was spindle-shaped crystals with 5-10 micron in length and NH2-
MIL-88B(Fe) was needle-shaped crystals with micron and 1-3 micron in length. The XRD pattern of the
prepared MOFs was in a good agreement with the simulated MIL-88B(Fe) from reference. FT-IR result of
NH2-MIL-88B(Fe) confirms vibrational bands of the amino groups around 3450 and 3300 cm–1. Adsorption
kinetics of these MOFs were also investigated and both MOFs fitted with pseudo-second order model
indicated that the process is predominantly chemisorption. The Langmuir and Freundlich isotherm models
were used for validating the experimental data, where the Freundlich model provided a good fit for the
adsorption of DCAA on MIL-88B(Fe). Composite membrane, composed of polymers as a supportive
material, conductive carbon material and Fe-based metal organic frameworks was prepared and investigated
its surface and cross-section by using SEM. The results showed that DCAA removal efficiency of MIL-
88B(Fe) and NH2-MIL-88B(Fe) were 34% and 47%, respectively. This DCAA removal technique is eco-
friendly and might be further developed as a water purifier in household.
Keywords : : Haloacetic acid, Iron-based metal organic framework, Electro-catalytic oxidation
INTRODUCTION
Chlorine is the most widely used disinfectant in the drinking water treatment according to its
effectiveness, low cost, and the ease of application. However, it was recently found that chlorination poses
potential health risks due to its potential to react with natural organic matter (NOM) and form chlorinated
disinfectant by-products (DBPs). Haloacetic acids (HAAs) are a prevalent class of DBPs widely reported
with considerable concentrations and potent toxicity; so, there are great concerns for human health and
environment. According to the Drinking Water Standards and Health Advisories, the US Environmental
Protection Agency (US EPA) has established the maximum contaminant level (MCL) for the concentrations
of five regulated HAAs (e.g. monochloroacetic acid, dichloroacetic acid, trichloroacetic acid,
monobromoacetic acid, and dibromoacetic acid) in drinking water is 60 ug/l (ppb) [1,2]. HAAs are detected
as contaminant in tap water in many countries; for example, Taiwan, Korea, Spain and Thailand. Because of
their widespread occurrence and toxicity to human health and aquatic organisms, many researchers attempt
to study the efficiency technologies for HAA removal. Reduction of HAAs can be divided into two general
approaches: (1) removal of precursors (i.e., NOM) prior to disinfection such as coagulation [3], ion exchange
[4] adsorption and advanced oxidation processes [5] (2) removal of disinfection by-products after formation
such as membrane filtration [6], electrochemical reduction [7], adsorption by activated carbon and ozonation
. Recently, Membrane-based processes is one of the promising technologies for advanced water purification.
This technology can be applied to use as household filtration. Metal-organic frameworks (MOFs) are highly
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porous crystalline materials. Due to their unique structural and practical properties, they have received great
attention in various applications including energy conversions and storage, catalysis, gas storage, sensors and
drug delivery. Among various MOFs, iron-containing MOFs are the most promising nanomaterials in many
fields because of their readily available and low-cost raw materials, nontoxic metal source with good
biocompatibility, and notable physico-chemical features (e.g., high porosity, framework flexibility, and
semiconductor properties). Moreover, iron-containing MOFs have gradually emerged as environmentally
benign alternatives for reducing environmental contamination levels [8].
Herein, an electrochemical filtration-oxidation process is proposed to reduce dichloroacetic acid in tap
water. MOFs (i.e. MIL-88B(Fe), NH2-MILL-88B(Fe)) were used as catalyst in electrochemical oxidation by
blending with composite membrane including graphene, carbon nanotube and PVDF. This technology is eco-
friendly for DCAA removal and can be further developed as a water purifier in household.
METHODOLOGY
1. Preparation of MIL-88B(Fe)
MIL-88B(Fe) was prepared by the improved reflux method from NANOTEC, Thailand. Firstly, 8.56 g
of FeCl3·6H2O and 5.26 g of terephthalic acid, were transferred to the three-necked round bottom flask and
dissolved in 360 mL of DMF. This solution stirred at room temperature for 30 min until it completely
dissolved. The solution was cured at 110 °C for 24 hours. After cooling down at room temperature, the solid
was centrifuged at 9,000 rpm for 10 min. The product was washed with DMF for three times, then were
soaked in methanol for 24 hours and three times. Finally, orange powder was dried overnight at 60-70 °C.
The obtained catalysts were stored in a glass desiccator until later use.
2.Preparation of NH2-MIL-88B(Fe)
The NH2-MIL-88B(Fe) was synthesized by using reflux method that like MIL-88B(Fe) synthesis, but
different kind of organic linker. For amino-MIL-88B(Fe) preparation, 2-aminoterephthalic acid was used as
organic linker.
3. Fabrication of composite membrane
First, desired amounts of graphene, CNT and MOFs were mixed with DMF, then dispersed by
sonication for 30 minutes in an ultrasonic bath and stirring by stirrer for 30 minutes alternately until
complete dispersion. After that, the PVDF/DMF solution was prepared by adding PVDF powder to DMF and
stirring solution at 70◦C until complete dissolution. Next, the polymer solution was dropped to the
suspension of graphene, CNT and MOF with continuous stirring and heating on hotplate at 70°C. After the
mixture was smooth, adding the remained PVDF powder and DMF slowly in that mixture. The final mixture
was stirred for an hour and ultra-sonicated for 40 minutes continuously until it was completely mixed, then
the mixed casting solution was degassed and casted on a glass plate. The thickness was controlled to be 70
μm. After the membrane was washed by water three times, set enough in 30% glycerol and air-dried, the
sheet was cut in a circular shape with a 47.5 mm diameter.
4. Adsorption kinetics
All adsorption experiments for DCAA were carried out at room temperature (25±2°C). For the
adsorption kinetics experiments, 50 µg/L of DCAA in 1L of DI water was added 20mM HEPES for pH
control and 50 mg of MIL-88B(Fe) or NH2-MIL-88B(Fe)) to solution. The samples were collected at 0 to
360 minutes and filtered through the 0.22 μm nylon filter to the glass tube with teflon cap for DCAA
extraction in next step. For adsorption calculation, adsorption kinetic data is calculated by using model that
shown in table 1.
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Table 1 Models used for fitting of kinetics data [9]
Name Equation Term definition
Pseudo first-order model Non – Linear: k1 [min-1]: adsorption rate constant
Pseudo second-order model
) V0 [mg/g h]: initial adsorption rate
Intra-particle diffusion model k2 [g/mg h]: pseudo second-order rate constant
Linear: log(qe - qt) = log qe -
Kp [mg/g h0.5]: rate constant for intra-particle
Non – Linear: qt = diffusion
Linear: =
V0 = k2
Non – Linear: q1 = kpt0.5
qt represent the adsorption capacity (mg/g) at time t.
5. Adsorption isotherm
The adsorption isotherms of MOFs were obtained with different initial DCAA concentrations from 10
to 300 µg/L. Then, HEPES was added for pH control. After the solution was added 50 mg of MOFs and was
shaken at 200 rpm at room temperature. The contact time was calculated from kinetic model, and then the
solutions were filtered through the 0.22 μm nylon filter to the glass tube with Teflon-cap for DCAA
extraction in next step. For adsorption calculation, adsorption isotherm data is calculated by using model that
shown in table 2.
Table 2 Models used for fitting of isotherm data [9]
Name Equation Term definition*
Freundlich model Non - Linear: qe = KF KF[(mg/g)/(mg/L)1/n]: Freundlich affinity coefficient
Linear: logqe = logKF + (1/n)logCe 1/n: Freundlich exponential coefficient
Langmuir model
Non - Linear: qe = Q0Ce / (KL+Ce) KL[mg/L]: affinity coefficient
Linea : =
Partition-adsorption model Qe = KpCe + Q0Ce / (KL + Ce) Kp[L/g]: partition coefficient
KL[mg/L]: affinity coefficient
Note: *qe [mg/g] is the equilibrium concentration of adsorbate in solid; Ce [mg/L] is the equilibrium aqueous concentration
of adsorbate; Q0 [mg/g] is the maximum sorption capacity for adsorbate.
6. Characterization of MOFs and composite membranes
The crystallographic information was analyzed by X-ray diffraction (XRD). Surface functional groups
were characterized by Fourier transform infrared spectroscopy (FT-IR). The surface and cross-sectional
morphology was investigated by Scanning Electron Microscopy (SEM).
RESULTS AND DISCUSSIONS
1. MOF Characterization
Synthesized MOFs were characterized on the physical and chemical properties by using various
techniques.
1.1 X-ray Diffraction (XRD)
The XRD pattern of MIL-88B(Fe) and NH2-MIL88B(Fe) were showed that both agreed well with the
simulated one (shown as “reference” in Fig.1), indicating the successful synthesis of MOFs by the reflux
method. For MIL-88B(Fe), the results present a high degree of crystallinity with main peaks appearing at
around 9.4°, 9.6°, 12.5°and 18.8°. For NH2-MIL88B(Fe), the diffraction patterns have many emergent peaks
at 9.2°, 10.4°, 13.1°, 16.7°, 18.6° and 19.2°. Furthermore, The XRD results of both MOFs suggested that
these MOFs contained a highly crystalline structure.
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Fig. 1 XRD patterns of a) MIL-88B(Fe) b) NH2-MIL88B(Fe)
1.2 Scanning Electron Microscopy (SEM)
The morphology and particle size of these obtained MIL‐88B(Fe) and NH2–MIL‐88B(Fe) crystals
were observed by scanning electron microscopy (SEM). Figure 2a, b showed that MIL‐88B(Fe) crystals have
a spindle‐shaped morphology with an average size of 5-10 μm in length and 5 μm in diameter. In
comparison, the NH2–MIL‐88B(Fe) crystals were needle‐shaped with a length of about 1-3 μm and a
diameter of 250 nm. The shapes of synthesized MOFs are similar to those reported by Ma et al. [12], but
different size of MIL-88B(Fe) crystals that have a length of 2.4 μm and a diameter of 1.2 μm. In their work,
MOFs were prepared by a rapid microwave-assisted solvothermal under heating to 150°C for 10 min that is
the different method. Therefore, the result indicates that the synthetic method and temperature influence the
size of MIL-88B(Fe).
ab
.
)
Fig. 2 SEM micrographs of a.) MIL-88B(Fe) b.) NH2- MIL-88B(Fe)
1.3 Fourier transform infrared spectroscopy (FT-IR)
FT-IR was used to identify the presence of amino groups in the resulting nanocrystals. The FTIR
spectra showed two small sharp bands at around 3450 and 3300 cm-1, which are attributed to the symmetric
and asymmetric stretching absorptions of primary amine groups, were observed. Furthermore, two peaks at
1600 and 1384 cm−1 are attributed to typical carboxyl groups vibrations. The C-H bending vibration in the
organic linkers can be observed at 760 cm−1[13].
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Transmittance (%T) 3450 3300
1600
760
1390
a.) MIL-88B(Fe)
b.) NH2-MIL-88B(Fe)
4000 3500 3000 2500 2000 1500 1000 500
Wavenumber (cm-1)
Fig. 3 FTIR results of a.) MIL-88B(Fe) b.) NH2- MIL-88B(Fe)
2. Adsorption test
2.1 Kinetic adsorption
NH2-MIL-88B(Fe)
MIL-88B(Fe)
Fig. 4 Kinetics adsorption of DCAA on MIL-88B(Fe) and NH2-MIL-88B(Fe)
at 50 µg/L of DCAA
Kinetic curve of DCAA adsorption on MIL-88B(Fe) and NH2-MIL-88B(Fe) were shown in Figure 6.
The result indicates that adsorptions of DCAA on MIL-88B(Fe) and NH2-MIL-88B(Fe) reached equilibrium
when the contact is more than 360 minutes. According to adsorption kinetics, the adsorption capacity (qt) of
DCAA on NH2-MIL-88B(Fe) showed higher than MIL-88B(Fe) at equilibria.
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Table 3 Parameters of DCAA kinetic adsorption on MIL-88B(Fe) and NH2-MIL-88B(Fe) using the
pseudo-first order and pseudo-second order kinetic models.
Pseudo-first order Pseudo-second order
MOFs q (mg g=1) k (min-1) R2 q (mg g-1) k (g mg-1min-1) T R2 h (g mg-1min-1)
e1 e2 eq
MIL-88B(Fe) 0.1621 0.0048 0.637 0.1573 1.172 6 hrs. 0.989 0.0290
NH2-MIL-88B(Fe) 0.2539 0.0071 0.736 0.2763 0.0998 8 hrs. 0.980 0.0076
Table 3 presents the kinetic parameter of DCAA (i.e. qe, k1, k2, h and Teq) on both types of MOFs and
found that the adsorption data of these MOFs fitted to a linear model of pseudo-second order kinetics with a
correlation coefficients (R2) of 0.980–0.989. Therefore, the adsorptions of DCAA on these MOFs were
suitable to explain with pseudo-second order model than pseudo-first order model, indicating that the
adsorption is dominated by chemisorption. Moreover, the initial rate adsorption (h) and second-order rate
constant of DCAA on MIL-88B(Fe) was significantly higher than NH2-MIL-88B(Fe) although the calculated
adsorption capacity at equilibrium (qe) of NH2-MIL-88B(Fe) nearly twice as large as that of MIL-88B(Fe).
This might be due to different surface area available for adsorption of DCAA and surface functional groups
responsible for complexation between two MOFs.
2.2 Isotherm adsorption
Table 4 Isotherm adsorption parameters of DCAA on MIL-88B(Fe) and NH2-MIL-88B(Fe)
using Langmuir model and Freundlish model.
Freundlich Model Langmuir Model
KL(mg/L)
MOFs
Kf (mg g-1) 1/n R2 Q(mg/g) R2
MIL-88B(Fe) 463.4 0.313 0.980 -0.006 -0.054 0.907
NH2-MIL-88B(Fe) 139.3 2.736 0.737 -0.004 -0.046 0.971
According to isotherm parameters that showed in Table 4, the data of DCAA adsorption on MIL-
88B(Fe) fits well to the Freundich model by considering the high correlation coefficient value (R2). It
suggests that adsorption obeys multilayer adsorption on heterogeneous surface. Moreover, n value can
determine the nonlinearity degree between concentration of solution and adsorption. If n=1, the adsorption is
linear. If n less than one, the adsorption is chemical process, and if n more than one, the adsorption is
physical process. Thus, the DCAA adsorption on MIL-88B(Fe) was chemical process. For the NH2-MIL-
88B(Fe), negative values of Langmuir constants reveal that DCAA adsorption mechanism to NH2-MIL-
88B(Fe) was not based on monolayer formation on the homogeneous surface.
3. Characterization of membrane
The surface morphologies of the membrane were monitored through SEM images in Fig 7. These
membranes were almost homogenous with no apparent phase separation, and the surface of the membrane
was flat. In the Figs. c) and d) that show cross-section images of three membranes, there are many
micropores on the membrane, created during phase inversion process, which were suitable for filtration and
the thickness of membranes after drying is approximately 200-250 μm.
.
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ab
cd
Fig. 7 Surface and cross-section SEM images of membranes
a), c) carbon + PVDF membrane
b), d) carbon + MIL-88B(Fe)+ PVDF membrane
CONCLUSION
Crystalline MIL-88B(Fe) and NH2-MIL-88B(Fe) were successfully synthesized by the reflux method.
MIL‐88B(Fe) crystals had a spindle‐shaped morphology, whereas the NH2–MIL‐88B(Fe) crystals were
needle‐shaped. Both MOFs had different particle size and aspect ratio. Adsorption kinetics of DCAA on both
MOFs obey the pseudo second-order kinetic model, suggesting chemisorption. Adsorption isotherm with
MIL-88B(Fe) fits to Freundlich model and attains DCAA removal of 34%. NH2-MIL-88B(Fe) is non-
monolayer adsorption at the DCAA removal of 47%. Two microporous MOF-carbon composite membranes
were successfully fabricated and had an asymmetric finger-like structure of phase inversion polymeric
membranes.
ACKNOWLEDGEMENT
This work has been partially supported by the National Nanotechnology Center (NANOTEC), NSTDA,
Ministry of Science and Technology, Thailand, through its Research Network NANOTEC (RNN) program.
REFERENCE
[1] U.S.EPA. (2003). Toxicological review of dichloroacetic acid (CAS No. 79- 43-6). Retrieved from
https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=654
[2] U.S.EPA. (2011). Toxicological review of trichloroacetic acid (CAS No. 76-03-9). Retrieved from
https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=655
[3] Wu, Y., Zhou, S., Ye, X., Zhao, R., and Chen, D. 2011. Oxidation and coagulation removal of humic acid using
Fenton process. Colloids and Surfaces A: Physicochemical and Engineering Aspects. 379(1-3): 151-156.
[4] Nkambule, T. I., Krause, R. W., Mamba, B. B., and Haarhoff, J. 2009. Removal of natural organic matter from
water using ion-exchange resins and cyclodextrin polyurethanes. Physics and Chemistry of the Earth. 34(13-16):
812-818.
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[5] Ndlangamandla, N. G. et al. 2018. A novel photodegradation approach for the efficient removal of natural organic
matter (NOM) from water. Physics and Chemistry of the Earth. 106: 97-106.
[6] Wang, L., Sun, Y., and Chen, B. 2018. Rejection of haloacetic acids in water by multi-stage reverse osmosis:
Efficiency, mechanisms, and influencing factors. Water Research. 144: 383-392.
[7] Zhao, X., Li, A., Mao, R., Liu, H., and Qua, J. 2014. Electrochemical removal of haloacetic acids in a three-
dimensional electrochemical reactor with Pd-GAC particles as fixed filler and Pd-modified carbon paper as
cathode. Water Research. 51: 134-143.
[8] Hou, S. et al. 2018. Green synthesis and evaluation of an iron-based metal–organic framework MIL-88B for
efficient decontamination of arsenate from water. Dalton Transactions. 47(7): 2222-2231.
[9] Naghdi, M. et al. 2017 Pine-wood derived nanobiochar for removal of carbamazepine from aqueous media:
Adsorption behavior and influential parameters. Arabian Journal of Chemistry. 12(8): 5292-5301
[10] Pertiwi, R. et al. (2019). Replacement of chromium by non-toxic metals in lewis-acid MOFs: assessment of
stability as glucose conversion catalysts. Catalysts. 9(5): 437.
[11] Ma, M. et al. (2013). Iron-based metal−organic frameworks MIL-88B and NH2‑MIL-88B: high quality
microwave synthesis and solvent-induced lattice “Breathing”. Crystal Growth & Design. 13: 2286-2291.
[12] Ma, M. et al. 2013. Iron metal–organic frameworks MIL-88B and NH2-MIL-88B for the loading and delivery of
the gasotransmitter carbon monoxide. Chemistry a European Journal. 19: 6785-6790.
[13] Shao, L. et al. 2020. Carbon nanodots anchored onto the metal-organic framework NH2-MIL-88B(Fe) as a novel
visible light-driven photocatalyst: Photocatalytic performance and mechanism investigation. Applied Surface
Science. 505: 144616.
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I 026
Effects of Polyvinyl Alcohol Gel Beads in the Methanogenic Reactor
on Performance Improvement of Two Stage Thermophilic
Anaerobic Bioreactor
Kanidtha Hanvajanawong1 Jenyuk Lohwacharin 2, §, * and Benjaporn Suwannasilp3
1 Graduate student ; 2Lecturer ; 3Associate Professor, Department of Environmental Engineering, Faculty of
Engineering, Chulalongkorn University, Bangkok, Thailand; § Research Network NANOTEC – CU on
Environment, Department of Environmental Engineering, Chulalongkorn University, Thailand.
*Phone : (+66)2-218-6671, Fax : (+66)2-218-6666, E-mail : [email protected]
ABSTRACT
Recently, field of immobilized cells was stated in many recent publications. There are various kinds
of media used in wastewater treatment, but polyvinyl alcohol gel bead (PVA) was utilized in this study. PVA
is claimed by previous studies that can alleviate inhibitory effect and has resilience against shock scenario
[2-3]. PVA was filled into methanogenic reactor (M2) in two stage thermophilic anaerobic bioreactor (ThAn)
for enhancing the performance and compared with M1 contained only freely suspended biomass. There were
lot of fluctuations of VFA production and COD removal efficiency in the operation of M1, which was
mainly affected by unsuitable pH and short HRT. Whilst, M2 was very stable throughout the operation
period. Reactor with PVA (M2), if compared with freely suspended ones (M1), exhibited more stable
condition (pH was stable around 7 along the experiment). Moreover, COD removal efficiency of M2 was
91.3% which higher that 80.7% of M1. Protein was the dominant substance in EPS composition in this study,
while polysaccharide was the least matter. Surprisingly, anaerobic microbes grew as biofilm on the PVA
surface which was observed change in the color of the beads. On Day 235, it was found that the outer surface
of all sampled beads was thoroughly covered by biofilm, which implied that biofilm layers on the PVA
surface was the main factor that enhancing the performance of the system.
Keywords : thermophilic anaerobic bioreactor (ThAn); polyvinyl alcohol (PVA) gel; molasses;
methanogens
INTRODUCTION
Treatment of high-strength industrial wastewater typically employs an anaerobic process operated at
a high organic loading rate (OLR) as a primary treatment because of several advantages e.g. cost
effectiveness. A thermophilic anaerobic bioreactor (ThAn) poses various advantages such as high
biodegradation rate, enhanced biogas generation, inactivation of pathogens and treatment of as-received hot
waste stream from industrial processes. However, pH is the critical factor, which affects performance of the
system because of the different growth rates of acidogenic bacteria and methanogenic archaea. To solve this
problem, two stage anaerobic treatment comprising hydrolytic and methanogenic reactors is the alternative
way, capable of operating separately at their optimal conditions. Chaikasem et al. [1] reported an effect of
PVA as a biocarrier on VFA production in a hybrid two-stage anaerobic membrane bioreactor under
thermophilic condition which improved hydrolytic reactor performance by increasing VFA production and
decreased inhibitory effect of propionic acid. Furthermore, a use of two stage anaerobic treatment system
incorporating PVA gel beads at the mesophilic temperature has been studied and reported. Interestingly, the
addition of PVA gel was taken place in both packed-bed reactors as a biofilm carrier which immobilized
microorganisms inside leading to increasing reaction rates and performance. The steady state condition can
be recovered soon after confronting a shock condition, like temperature variation. However, study about its
resilience against other shock scenario is limited [2]. Referred to an early publication on methanogen
immobilization in PVA gel, the immobilized cells recovered their methanogenic activity faster than the free
cells (suspended biomass) from the inhibition caused by temporary low pH of 5.0. Theoretically, there is a
formation of a pH gradient inside the biocarrier that becomes beneficial characteristic, which seems to
alleviate the inhibition by propionic acid and sulfide. Other inhibitory effects of interfered compounds were
also relieved by the adsorption on the bead material [3].
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The purpose of this study was to assess performance of two-stage ThAn, which was equipped with
ultrafiltration operated in a semi dead-end configuration on the COD removal. PVA gel was added into one
methanogenic reactor for comparison as it was anticipated that PVA enhance the system performance.
METHODOLOGY
1. Enrichment and Acclimatization
Under thermophilic condition (55˚C), the two-stage ThAn consisted of hydrolytic reactor (HR),
methanogenic reactors 1 and 2 (M1 and M2), which acidogenic bacteria and methanogenic archaea were
enriched individually, respectively. To enrich these two different microbes, anaerobic seed sludge which was
operated under mesophilic condition was fed into the reactors with HRT of 2 days. Then, different feeds and
environmental conditions were provided for different microbes. Only M2 was filled with pre-cultured PVA
at 30% of the working volume, operated as a moving bed regime. M1 contained only suspended biomass
from the same source for comparison.
To sustain COD:N:P ratio of the synthetic wastewater at 100:5:1, molasses (for HR) and butyric acid
(for M1 and M2) were used as sole carbon source, while NH4Cl, KH2PO4 and K2HPO4 were added as
nitrogen source and phosphorus source, respectively. In addition, micronutrients (trace elements) were also
added. The alkalinity of M1 and M2 were maintained at 1500 mg as CaCO3/L by adding NaHCO3. The
reactor (HR) fed with molasses was expected to have acidogenic bacteria as a dominant microbe. While,
methanogenic archaea were expected to be mostly found in the reactors (M1 and M2) that fed by butyric
acid.
Firstly, seed sludge was enriched in batch reactors and operated under 500 and 1000 mg COD/L
condition for 1 month. Then, sludge was transferred into thermophilic anaerobic reactors (Figure 1), which
was 30% of the working volume. Synthetic wastewater (1000 mg COD/L) was fed under mesophilic
condition for 2 weeks before increasing the temperature from 35˚C to 55˚C.Then COD was raised stepwise
to 2500, 5000, 7500 and 10000 mg COD/L. During the operation, pH, ORP, VFA, alkalinity, COD, MLSS,
MLVSS, EPS and SMP were regularly measured. PVA gel, collected from the M2 after each feed-COD
increment, was visually monitored for surface color change and bead deformation.
2. Two stage ThAn Operation
Figure 1 Two stage thermophilic anaerobic bioreactor (ThAn)
(a) Front view of the reactors used in this research (b) Back view
Set 1: Hydrolytic reactor (HR) 4.0 L + Methanogenic reactor (M1) 4.3 L without PVA
Set 2: Hydrolytic reactor (HR) 4.0 L + Methanogenic reactor (M2) 4.3 L with PVA 1.3 L
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After enrichment and acclimatization, HR was separately connected to M1 (Set 1) and M2 (Set 2).
Molasses-based synthetic wastewater was fed to each set at the flow rate of 4 L/day, giving the OLR of 6 kg
COD/m3.d and HRT of 37.8 hr (HR: 12 hr and M1&2: 25.8 hr). Wastewater was fed into HR, then the
effluent was overflowed to M1 and M2. In M2, PVA was used at the volume of 1.3 L or volumetric packing
ratio of 30%, and it was mixed by wastewater recirculation, which is controlled intermittently by IWAKI
magnetic water pumps (15 min mixing and 15 min non-mixing). There was only suspended biomass in M1,
which was also mixed by wastewater recirculation. Finally, wastewater from M1 and M2 was filtered by
PVDF ultrafiltration membrane for retaining any residual biomass, or eliminating biomass wash out problem.
During the operation, pH, ORP, COD, MLSS, MLVSS, SMP and VFA production were regularly measured.
The operation conditions are described in the following table (Table 1).
Table 1 Operating conditions of two stage ThAn
Parameters Unit HR M1 M2 Overall/Set
4.5 -
Adding NaHCO3 g/L - 4.5 55 55
Temperature °C 55 55
Influent COD g/L 9.45 7.56* 7.56* 9.45
Loading rate kgCOD/m3.d 18.9 8.79 8.79 6
HRT hr 12 25.8 25.8 37.8
Flow rate L/d 8 4 4 4
Working volume L 4 4.3 4.3 6.3
*Influent COD of methanogenic reactor is calculated by assuming COD removal efficiency of hydrolytic
reactor is approximately 20%.
RESULTS AND DISCUSSIONS
1. MLSS and MLVSS concentrations
At the beginning, HR and M1 were filled with mesophilic sludge by 30% of the working volume,
which gave MLSS of 3950 and 1460 mg/L, respectively. About 1.3 L of PVA enriched in the batch reactors
were filled into the M2 (~ 30% of the working volume), so it was firstly assumed that there is no MLSS on
the PVA. Then, MLSS increased with time, which yielded the MLSS of 6900 and 3775 mg/L for HR and
M1, respectively. For M2, biofilm on PVA was measured by randomly sampling 30 beads of PVA in the
M2, dried at 105˚C for 24 hours. The total weight of 30 beads was subtracted by weight of 30 beads of
pristine PVA, which also dried at 105˚C for 24 hours. Figure 3 (c) shows MLSS/PVA bead as a function of
operating time, indicating occurrence of biofilm on PVA. Figure 2 showed color evolution of the PVA
during different operation periods of 30, 140 and 235 days. Since Day 30, it was observed small change in
the color of the beads, which suggested growth of anaerobes. On Day 140, it was found that the outer surface
of all sampled beads was thoroughly covered by biofilm. Progressively, relatively darker colored beads were
monitored for Day 235 in comparison to those at Day 140, indicating more anaerobic microbes attached on
the bead surface. There was no deformation and fragmentation of the PVA gel beads noticeably over 235
days of observation in the thermophilic condition. Therefore, the substantial increase in the mg-MLSS/PVA
ratio during Day 113 to 170 (Figure 3 (c)) is mainly attributable to greater biomass attached growth on the
PVA. PVA is claimed by Kuraray Company (Tokyo, Japan) [5] that it has porous structure with only 10%
solids and a continuum of passages 10 to 20 microns in diameter tunneling throughout each bead [6].
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(a) (b) (c)
Figure 2 PVA gel beads: (a) surface on day 30, (b) after 140 days, and (c) after 235 days.
(a) (b) (c)
Figure 3 MLSS during enrichment and acclimatization a) HR, (b) M1 and (c) M2 (on PVA)
2. pH profiles and COD removal efficiency
The anaerobic degradation comprises a complex metabolic pathway and biochemical reactions. In HR,
several reactions take place, including hydrolysis, fermentation, acidogenesis and acetogenesis process. Molasses
was complexed organic substances, which were degraded into smaller molecules, VFAs and other products in
small proportions. M1 and M2 were the following reactors representing methanogenesis. During 71 days of
enrichment process, pH in HR was ca. 6.4, and declined to about 4.0 at the feed COD of 5000 mg/L (Figure
4 (a)), owing to an increasing VFA production. VFA concentration dramatically rose together with COD
concentration in Figure 5 (a). The hydrolytic microorganism has a capability to resist environmental
parameter fluctuations and the toxins, so they can work in a wide range of pH (4–11) [4]. On the other hand,
pH range of 6.5-8.0 provides favorable conditions for methanogens. In this study, pH of M1 and M2 reached
a plateau at ca 7.2 after the addition of alkalinity. Moreover, M2 provided relatively lower effluent VFA than
M1 at all OLRs applied (Figure 5).
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(a) (b)
Figure 4 pH during (a) enrichment and acclimatization (b) Two stage ThAn operation
(a) (b)
Figure 5 VFA concentration during (a) enrichment and acclimatization (b) Two stage ThAn operation
Similarly, the COD removal of HR clearly decreased from 72% to 32% (Figure 6), indicating that at
the first period there was a mixed culture that consisted of both acidogenic bacteria and methanogens. After
pH dropped to 4, acidogenic bacteria became a dominant group of microbes. Meanwhile, the COD removal
efficiency of M1 and M2 were around 70% in the enrichment and acclimatization stage.
For Two stage ThAn operation, after connecting HR to M1 and M2 without adding alkalinity
directly to M1 and M2, pH of M1 decreased from 7.0 to about 5, whereas pH of M2 (PVA added) slightly
changed (Figure 4 (b)). In fact, PVA gel beads are hydrophilic in nature [6], which are typically charge-
polarized. PVA can exchange ion in bulk water, but the quantity of ions that exchanged by PVA can be
neglected comparing with proton (H+) in the system. From figure 4 (b), pH of M1 declined from c.a. 7.0 to
below 5.0. During Day 30-42, alkalinity (as NaHCO3) was directly added into M1 and M2, resulting in pH
fluctuation. Then, Cole-Parmer Masterflex L/S Model 7523-60 was used for persistently feeding sodium
bicarbonate (NaHCO3) into M1 and M2 instead of direct addition. Obviously, pH of M1 bounced back to
normal which was neutral. Correspondingly, M2 containing PVA exhibited a high COD removal efficiency
of 91.3%, which was higher than M1 (80.7%) (Figure 7). The COD removal efficiency of HR was about
30%, similar to the stage before connecting to the methanogenic reactors. Accordingly, there is a study
finding that adding PVA provided satisfactory performance, resulting in high COD removal efficiency and
process resilience against the extreme condition such as low-pH shock. [2]
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Figure 6 COD of HR during enrichment and acclimatization stage
Figure 7 COD during Two stage ThAn and (a) M1 (b) M2
3. Total VFA production and individual VFA species
VFAs measured in this study were acetic, propionic and butyric acids using high performance liquid
chromatography (HPLC) to estimate the ratio of VFA fractions. At the feed COD of 10,000 mg/L in the
enrichment and acclimatization stages, the VFA result indicated that the ratio of Acetic: Propionic: Butyric
in HR was 5:4:1, i.e. 694, 538, 161 mg/L, respectively. On the contrary, the ratio of Acetic: Propionic:
Butyric in HR turned to 5:2.5:8 in two-stage ThAn operation, i.e. 212, 106, 345 mg/L, respectively. The
result indicates that HRT was the important factor that determined the VFA composition: namely HR during
enrichment stage had HRT of 48 hr, while HRT was only 12 hr during a full operation. Hence, total VFA
concentration during enrichment stage was relatively high due to sufficient time for organic degradation.
Indeed, a shorter HRT at a full operation lowered production of propionic acid, which are one of the
inhibitors for anaerobic process. Propionic acid has a relatively high positive value of ∆G, compared to other
VFAs; hence propionic can be accumulated easily when facing the poor system performance, so it is the
critical inhibitor in anaerobic process, which should be seriously focused on [7-8].
Figure 5 (a) shows that total VFA concentration during enrichment and acclimatization, which
increased by raising COD concentration, reached the highest peak at c.a. 2800 mg/L (in HR). Whilst, VFA of
M1 dramatically increased to around 4400 mg/L (Figure 5 (b)) in the period of day 35 in Two-stage ThAn
operation. In the same period, the fluctuation of pH in M1 adversely affected the system performance, so
effluent from HR that was transferred to M1 was not treated well. VFA could not be converted into CH4,
CO2 or H2, resulting in accumulation of VFAs due to more residual organic matter in wastewater, which led
to bulky VFA in M1. Afterwards, pH of M1 became stable (neutral) after consistently adding alkalinity,
which led to lower VFA in the M1 effluent, while pH and VFA of M2 effluent were very stable. Total VFA
concentration of M2 effluent was always below 500 mg/L along with stable pH. Thus, pH and HRT were
probably major factors that influenced both quantity and quality of total VFA. Indeed, PVA added in M2
demonstrates the process resilience against an extreme condition such as low-pH shock and high organic
substance, which could be referred from the previous studies [2-3].
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4. Extracellular polymeric substances (EPS)
During enrichment and acclimatization stage, EPS in biomass and on the PVA surfaces were
extracted by cation exchange resin (CER) method and analyzed by modified Lowry and Anthrone method
[9-10], which employs the UV-Vis spectroscopy technique. EPS analysis estimated the polysaccharide,
protein and humic concentration from each reactor. The carbon source used in HR and M1&M2 were
different (Molasses for HR; butyric acid for M1&M2), so the EPS composition of each reactor would be
different. In all reactors, protein was the largest fraction amount among others, and polysaccharide was the
lowest contribution. Surprisingly, polysaccharide in HR increased from 3.03 to 6.07 mg/gVSS when feed
COD increased from 2500 to 10000 mg/L. Furthermore, polysaccharide in M1 and M2 exhibits an inverse
trend, as it decreased at increasing COD concentration. Furthermore, the trend of protein and humic in M1
were raised from 11.45 to 25.7 and 8.04 to 12.23 mg/gVSS, respectively. On the other hand, M2 shows
differently; namely both protein and humic declined with increasing COD concentration. Protein reduced
from 12.62 to 6.41 mg/gVSS, and humic acid from 7.30 to 4.55 mg/gVSS. Since there was thick biofilm
layer on the PVA leading to higher MLVSS, EPS covered only to the outer layer, giving lower normalized
EPS by MLVSS. The composition of EPS could be related to with membrane fouling, which requires further
study.
CONCLUSION
It was found that since Day 30, growth of anaerobes on the PVA gel beads was confirmed by visual
observation. M1 (without PVA) and M2 (PVA added) achieved nearly 70% of COD removal in the
enrichment and acclimatization stage. For VFA and COD removals during full operation, M2 provided
relatively lower effluent VFA than M1 at all OLRs, while M2 exhibited a higher COD removal efficiency
(91.3%) than M1 (80.7%). In brief, adding PVA in the methanogenic reactor was an alternative way for
enhancing performance of two-stage ThAn and process resilience against low-pH and high-organic loading
shock.
ACKNOWLEDGEMENT
This work has been partially supported by the National Nanotechnology Center (NANOTEC), NSTDA,
Ministry of Science and Technology, Thailand, through its Research Network NANOTEC (RNN) program.
In association with, the 90th Anniversary of Chulalongkorn University Fund (Ratchadaphiseksomphot
Endowment Fund), and Conference Grant for Master Degree student.
REFERENCE
[1] Chaikasem, S., Abeynayaka, A. and Visvanathan, C. 2014. Effect of polyvinyl alcohol hydrogel as a
biocarrier on volatile fatty acids production of a two-stage thermophilic anaerobic membrane
bioreactor. Bioresour Technol 168: 100-105.
[2] Pandey, S. and Sarkar, S. 2017. Anaerobic treatment of wastewater using a two-stage packed-bed
reactor containing polyvinyl alcohol gel beads as biofilm carrier. Journal of Environmental Chemical
Engineering 5(2): 1575-1585.
[3] Hanaki, K., Hirunmasuwan, S. and Matsuo, T. 1994. Protection of methanogenic bacteria from low pH
and toxic materials by immobilization using polyvinyl alcohol. Water research 28(4): 877-885.
[4] Zhang, P., Chen, Y. and Zhou, Q. 2009. Waste activated sludge hydrolysis and short-chain fatty acids
accumulation under mesophilic and thermophilic conditions: effect of pH. Water research 43(15):
3735-3742.
[5] Kuraray Co. Ltd., in: PVA GEL -presentation leaflet, Okayama, Japan, 2005.
[6] Levstek, M., Plazl, I. and Rouse, J. D. 2010. Estimation of the specific surface area for a porous
carrier. Acta chimica slovenica 57(1).
[7] Schmidt, J. E. and Ahring, B. K. 1993. Effects of hydrogen and formate on the degradation of
propionate and butyrate in thermophilic granules from an upflow anaerobic sludge blanket reactor.
Applied and Environmental Microbiology 59(8): 2546-2551.
[8] Camacho, C. G. and Ruggeri, B. 2018. Syntrophic Microorganisms Interactions in Anaerobic
Digestion (Ad): a Critical Review in the Light of Increase Energy Production. Chemical Engineering
Transactions 64: 391-396.
[9] Lowry, O. H., Rosebrough, N. J., Farr, A. L. and Randall, R. J. 1951. Protein measurement with the
Folin phenol reagent. Journal of biological chemistry 193: 265-275.
[10] Dubois, M., Gilles, K. A., Hamilton, J. K., Rebers, P. t. and Smith, F. 1956. Colorimetric method for
determination of sugars and related substances. Analytical chemistry 28(3): 350-356.
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I 027
Greenhouse Gas Emissions and Climate Change Impacts from
Plastic Waste Recycling Processes: Polypropylene and Polyethylene as
Case Studies
Katreeya Saejew1 Mongkolchai Assawadithalerd2 Danai Tipmanee3 Laksana Laokiat4
Pummarin Khamdahsag5 and Suthirat Kittipongvises5*
1Graduate student, International Postgraduate Programs in Hazardous Substance and Environmental
Management, Graduate School, Chulalongkorn University, Bangkok, Thailand;
2Researcher, Center of Excellence for Environmental and Hazardous Waste Management (EHWM),
Chulalongkorn University, Bangkok, Thailand;
3Lecturer, Faculty of Technology and Environment, Prince of Songkla University Phuket Campus, Thailand;
4Associate Professor, Faculty of Public Health, Thammasat University, Thailand;
5 Environmental Research Institute, Chulalongkorn University (ERIC), Bangkok 10330, Thailand
E-mail*: [email protected]
ABSTRACT
There is a strong evidence that mismanagement of plastic waste is considered as one of the major global
environmental concerns. An inefficient waste management may cause negative impacts on environmental
contamination, population health risk, social well-being and economic sustainability. Recycling is an
environmental friendly approach that helps reduce all environmental burdens. It is therefore important to
understand all environmental impacts of recycling practice and related activities. The aim of this study was
to systematically assess all possible environmental and climate change related impacts of the recycling
processes of the postconsumer polyethylene (PE) and polypropylene (PP) in Thailand. By employing the
concepts of LCA and carbon footprint assessment, a gate-to-gate study was performed. The results
demonstrated that about 23.08 and 62.18 tCO2 eq. were annually emitted from PP and PE recycling plants,
respectively. Approximately 93% of the total emissions were indirect emissions mainly from purchased
electricity. The results of IMPACT 2002+ analysis showed that per 1 kg recycled PP and PE resin
production, resources and climate change categories were the two largest environmental impacts of plastic
waste recycling processes. Diesel and electricity consumption was the main cause for those impact
categories. Similarly, the Greenhouse Gas Protocol method found that approximately 60% of total fossil-fuel
CO2 emissions came from electricity consumption for recycled PP/PE resin production. Therefore, it should
be recognized that energy efficiency improvement can contribute to achieving the mitigation of GHG
footprint and environmental impacts from plastic waste recycling processes.
Keywords : carbon dioxide emissions; plastic recycling; environmental impacts; life cycle assessment
(LCA); carbon footprint
INTRODUCTION
Plastic material is widely used in many applications due to their unique properties such as tough, flexible,
easy to fabricate with low production cost [1]. Globally, plastic production has tremendously increased from
1.5 million tonnes in 1950 to 350 million tonnes in 2017 [2]. In 2018, Thailand generated 9 million tonnes of
plastic resin (approximately 3.54% of annual plastic growth rate during 2013-2018) [3]. As one of the
energy-intensive industries, plastic processing contributes to emission of greenhouse gases (GHGs) at every
stage of its life cycle, from raw material extraction, production, transportation, and end-of-life disposal [4].
According to the Thailand’s Intended Nationally Determined Contribution (INDC), Thailand has agreed to
reduce their GHGs by approximately 20-25% below the business-as-usual level by 2030 [5]. In waste sector,
recycling seems to be one of the most appropriate methods, compared to other treatment options (i.e.
landfilling and incineration) [6]. It should be, however, highlighted that most of plastic recycling factories
are often small and medium scale enterprises. Still, there is a lack of managerial experience, technological
advancement and good management practices in these small factories. Due to the limited number of studied
available climate change and recycling practices, the aim of this research was to assess both GHGs emissions
and climate change related impacts from plastic waste recycling processes. Recycled polypropylene (PP) and
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polyethylene (PE) plastic resin produced from small-sized plastic recycling plant in Thailand were selected
as product case studies.
METHODOLOGY
1. Case Studies
The plastic waste recycling plants (Plants A and B), located in Thailand were selected as case studies. This
plants produced recycled plastic both PP and PE resins for industrial purposes with a monthly full capacity of
120 tonnes. This factory operated 24 hours with one-stream production line, thereby each type of plastic is
being processed separately in a recycling facility. In general, the recycling processes of Plants A and B
involve manual sorting, shredding, washing/drying, melting/extrusion, pelletisation and storage (Figure1). In
terms of resource consumption, both inputs and outputs of plastic waste recycling processes of Plants A and B
were summarized in Table 1.
Table 1 Inputs and outputs of the recycled plastic processing of Plants A and B (per month)
Detail Unit Plant A Plant B
Productivity ton 36 84
Electricity consumption kWh 2,554
Diesel consumption L 34.5 5,961
Gasoline consumption L 25.8 80.5
60.2
2. Carbon Footprint Estimation
According to GHG protocol (2014) [7], both direct and indirect GHGs emissions must be quantified and
reported by considering the following 3 scopes:
Scope 1 (Direct emissions) include onsite fuel combustion and vehicle fuel consumption
Scope 2 (Indirect emissions) include emissions from generation of electricity, heat or stream purchased
from utility provider.
Scope 3 (Other indirect emissions) are emissions from sources not owned by organization (i.e., solid
waste disposal and wastewater treatment).
In this study, only scopes 1 and 2 were accounted, while scope 3 was excluded. GHG emission was
estimated by multiplied activity data with an emission factor as shown in equation (1). The value of emission
factor used in this research was followed the Thailand Greenhouse Gas Management organization (TGO) [8]
as presented in Table 2. The total amount of GHG emitted was expressed in the unit of carbon dioxide
equivalent (CO2 eq.)
Emission = Activity Data (AD) x Emission Factor (1)
Table 2 Emission factor for each activity
Types of emission Activity Emission factor Unit
Indirect emission from Electricity 0.6933 kgCO2eq/kWh
purchased electricity consumption
2.7446 kgCO2eq/kg
Direct emissions from fuel Diesel fuel 2.2380 kgCO2eq/kg
combustion for off-road consumption
transportation Benzene fuel
consumption
3. Life Cycle Assessment
Life cycle assessment (LCA) is a tool that commonly used to evaluate all direct and indirect environmental
impacts of a product or service system throughout its life cycle from raw material extraction to waste
treatment [9]. In this study, the LCA comprises the following four steps:
3.1 Goal and scope definition
The goal of this study was to quantify the possible environmental and climate change impacts of
manufacturing of recycled PP and PE. As a partial product life cycle assessment, a gate-to-gate LCA was
performed. A life cycle begins at the receiving of raw materials and ends at the final stage of recycled
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plastic resin production (i.e., pelletisation and storage) (Figure 1). Importantly, functional unit of this
assessment was 1 kg of recycled PP/PE resin.
3.2 Inventory analysis
Both inputs and outputs of the production of 1 kg of recycled plastic resin was collected in the inventory
analysis stage. As shown in Figure 1, related inputs used for producing recycled plastic resin (i.e., grid-
electricity and fuels) and environmental emissions (i.e. air emissions) were collected and listed in the
inventory of LCA. However, as a gate-to-gate approach, all activities related to the consumption of final
product and end-of-life disposal treatment that occurs out of the system boundary was excluded in this
LCA study. In this study, air sampling was performed according to NIOSH 1500 method [10].
Figure 1 Inputs and outputs of plastic waste recycling processes
3.3 Impact assessment
Regarding to ISO 14040 and 14044 standards, life cycle impact assessment (LCIA) is the third phase of
the LCA, which aims at quantifying the potential environmental impacts of the studied system. By using
SimaPro 8.3.0, climate change impact assessment methods were using IMPACT 2002+ and Greenhouse
gas protocol, which expressed the results in carbon dioxide equivalent (CO2 eq.) unit.
3.4 Interpretation
The findings of the impact assessment were interpreted to indicate environmental impacts of the
production of 1 kg of recycled plastic resin. Normalization and weighting were reported by combining the
environmental midpoint impact categories into a single score and helping identify which impacts are the
most important.
RESULTS AND DISCUSSIONS
1. GHG emissions from plastic waste recycling processes
The result of this study revealed that annual CO2 emission from recycled PP and PE resin production were
equivalent to 23.08 and 62.18 tCO2 eq., respectively. In terms of emission intensity, recycled resins
contributed 0.53 kg CO2/ kg of PP production and 0.62 kg CO2/ kg of PE production. These results are
similar to other previous studies. For example, a research conducted by Astrup [11], reported the emission
intensity of 0.5-0.6 kg/ kg CO2 per kg recycled plastic waste (both direct and indirect emissions were
accounted and included). Moreover, Rahim [12] found that the production of recycled PP resins derived from
PP and oriented polypropylene (OPP) waste emitted 0.84 kg CO2/ kg of plastic resin product. As shown in
Figure 2, it is well observed from this study that indirect CO2 emissions from purchased electricity source of
emissions (92-93%), whereas direct CO2 emissions emitted only 7-8 % of total emissions. These findings are
also in accordance with the results of Friedrich [13], who found that high amount of GHGs were emitted due
to the energy consumption for the processes of plastic recycling (i.e., washing, drying, compaction and
granulation and final pelletisation).
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Figure 2 GHG emissions categorized, by scope and types of recycled plastic product
2. Life Cycle Assessment: Climate change impact
Figure 3 CO2 emission based on the LCA: Greenhouse Gas Protocol method
By employing the Greenhouse Gas Protocol method, recycled plastic resin production contributed 0.00158
kg CO2 eq. for PP and 0.003 kg CO2 eq. for PE, respectively. Electricity consumption in the waste recycling
processes was by far the biggest contribution to the total fossil-fuel CO2 emission (60%) (Figure 3). In
polymer recycling process, Rajendran [14] applied the Eco-Indicator LCA method to evaluate all
environmental impacts and found that utilization of fossil fuels was the major contributor of natural resource
depletion. Furthermore, the mechanical recycling of PE and PET was the greatest consumer of energy,
compared to other processes. (i.e., collection of plastic material, transportation, and sorting) [15].
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Figure 4 Normalized environmental impacts of 1 kg recycled PP/PE resin based on the LCA: IMPACT
2002+ method
As depicted in Figure 4, it can be seen that the resources category presented the greatest environmental
impacts for both recycled PP and PE resins production, in which the two midpoint categories contributing to
the resources category are the consumption of non-renewable energy and the extraction of mineral. Diesel
fuel consumption for transport machinery make the largest contributions (54-55 %) to the resources category.
These results were consistent with previous researches. Climate change was the second largest impact on
environment attributable to electricity used for manufacturing recycled PP and PE. For instance, Wäger and
Hischier [16] reported that transportation of plastic waste had the largest environmental impacts on abiotic
depletion (fossil fuels) due to high amount of diesel is consumed for transporting PE and PET waste to
recycling facilities. Bataineh [17] revealed that the reprocessing to recycled HDPE pellets was the biggest
contributor to energy use impact of recycling process compared to other processes (i.e. collection/transport
and sorting/separation). Dodbiba et al. [18] found that the environmental burdens associated with plastic
recycling are mainly due to the global warning potential (GWP) (i.e. the emission of greenhouse gases),
followed by the depletion of abiotic resources (ADP). In this study, both recycled PP and PE resin
production contribute to human health indicator about 11.5% of total impacts. Recycling of plastic
contributed with impacts on the toxicity categories are mainly resulted from emissions of PAH, dioxins and
mercury during the melting/extrusion process of PE [19].
CONCLUSION
The recycling plastic industry is considered as one of the innovations under a circular economy concept.
Moreover, the possible environmental impacts from the recycling processes should be clearly defined. This
research aimed to investigate both GHGs emissions and climate change related impacts from the production
processes by applying both carbon footprint and LCA concepts. The key results found that electricity
consumption (defined as scope 2) emitted the largest proportion of GHGs emissions for both PP and PE recycled
products. Therefore, the integration of energy efficiency should be realized in the recycling manufacturing
processes.
ACKNOWLEDGEMENT
The authors are grateful to the Center of Excellence on Hazardous Substance Management (HSM)
Chulalongkorn University for the financial support of the Research Program. The scholarship from Graduate
School, Chulalongkorn University to commemorate the 72th anniversary of his Majesty King Bhumibala
Aduladeja is gratefully acknowledged. The authors also wish to thank the Environmental Research Institute
Chulalongkorn University (ERIC) for their supports in terms of facilities and scientific equipment.
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REFERENCE
[1] Shrivastava, A., 1 - Introduction to Plastics Engineering, in Introduction to Plastics Engineering, A.
Shrivastava, Editor. 2018, William Andrew Publishing. p. 1-16.
[2] Chalmin, P., The history of plastics: from the Capitol to the Tarpeian Rock Field Actions Science
Reports, 2019(Special Issue 19): p. 6-1.
[3] Plastics Institute of Thailand. Growth of Thailand resin production [in Thai]. 2019 [cited 25 July
2019]; Available from: http://www.plastats.com/.
[4] Shen, M., et al., (Micro)plastic crisis: Un-ignorable contribution to global greenhouse gas emissions
and climate change. Journal of Cleaner Production, 2020: p. 120138.
[5] Office of Natural Resources and Environmental Policy and Planning, Thailand’s Intended Nationally
Determined Contribution (INDC) 2015: Thailand. p. 1-7.
[6] Hiltunen, M.-R., H. Dahlbo, and T. Myllymaa. Reducing Greenhouse Gas Emissions by Recycling
Plastics or Textile Waste ? in ISWA. 2007.
[7] Fong, W.K., et al., Global Protocol for Community-Scale Greenhouse Gas Emission Inventories
(GPC), in An Accounting and Reporting Standard for Cities. 2014. p. 176.
[8] Greenhouse Gas Management Organization. Emission Factor [in Thai]. 2019 [December 12, 2019];
Available from: http://thaicarbonlabel.tgo.or.th/admin/uploadfiles/emission/ts_f2e7bb377d.pdf.
[9] Widheden, J. and E. Ringström, 2.2 - Life Cycle Assessment, in Handbook for
Cleaning/Decontamination of Surfaces, I. Johansson and P. Somasundaran, Editors. 2007, Elsevier
Science B.V.: Amsterdam. p. 695-720.
[10] US National Institute for Occupational Safety and Health (NIOSH), NIOSH Manual of Analytical
Methods (NMAM) Fourth Edition, in HYDROCARBONS, BP 36-216 °C: METHOD 1500, P.M. Eller
and M.E. Cassinelli, Editors. 2003. p. 8.
[11] Astrup, T., T. Fruergaard, and T.H. Christensen, Recycling of plastic: accounting of greenhouse gases
and global warming contributions. 2009. 27(8): p. 763-772.
[12] Rahim, R. and A.A. Abdul Raman, Carbon dioxide emission reduction through cleaner production
strategies in a recycled plastic resins producing plant. Journal of Cleaner Production, 2017. 141: p.
1067-1073.
[13] Friedrich, E. and C. Trois, GHG emission factors developed for the recycling and composting of
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[14] Rajendran, S., et al., Plastics recycling: insights into life cycle impact assessment methods. Plastics,
Rubber and Composites, 2013. 42(1): p. 1-10.
[15] Perugini, F., M.L. Mastellone, and U. Arena, Environmental Aspects of Mechanical Recycling of PE
and PET: A Life Cycle Assessment Study. Progress in Rubber, Plastics and Recycling Technology,
2004. 20(1): p. 69-84.
[16] Wäger, P.A. and R. Hischier, Life cycle assessment of post-consumer plastics production from waste
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[17] Bataineh, K., Life-Cycle Assessment of Recycling Postconsumer High-Density Polyethylene and
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[18] Dodbiba, G., et al., The recycling of plastic wastes from discarded TV sets: comparing energy
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[19] Manfredi, S., D. Tonini, and T.H. Christensen, Environmental assessment of different management
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Conservation and Recycling, 2011. 55(11): p. 995-1004.
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I 028
Development of Flotation Enhanced Stirred Tank (FEST) Process
for Petroleum Hydrocarbons Removal from Drill Cuttings
Marina Phea1,3 Nattawin Chawaloesphonsiya1 Thaksina Poyai2 Saret Bun3 and Pisut Painmanakul1,2,4*
1Department of Environmental Engineering, Faculty of Engineering,
Chulalongkorn University, Bangkok 10330, Thailand
2Center of Excellence on Hazardous Substance Management (HSM), Bangkok 10330, Thailand
3Water and Environmental Engineering, Faculty of Hydrology and Water Resources Engineering,
Institute of Technology of Cambodia, Phnom Penh 12156, Cambodia
4Research Unit on Technology for Oil Spill and Contamination Management,
Chulalongkorn University; Bangkok 10330, Thailand
*Phone : (66) 02-2186671, Fax : (66) 02-2186666, E-mail: [email protected]
ABSTRACT
Environmental pollution by petroleum hydrocarbons has become a widespread problem impacting human
health and the environment. For instance, Drill cuttings (DC) are one type of waste that contaminated by
petroleum hydrocarbons as they are generated mainly within drilling muds in the drilling operations of
petroleum exploration and production industries. To handle this issue, many innovative and sustainable
treatment technologies are required to study. Therefore, this work aims to optimize and develop the treatment
process for the removal of total petroleum hydrocarbons (TPH) from DC by using the combination of air
floatation and stirring processes, called Flotation Enhanced Stirred Tank (FEST). Initially, stirring, induced
air flotation (IAF), and dissolved air flotation (DAF) are individually investigated over DC washing. The
result of the stirring process shows that installing one of the pitch 4-blades impeller provides better removal
performance compared to 2 and 3 impellers of itself and hydrofoil types in the experimental reactor.
Moreover, higher rotational speed shows a better result of removal efficiency, i.e., 200, 400, and 600 rpm,
which can remove TPH about 22%, 25%, and 28%, respectively, for an hour of treatment time. For IAF
treatment only, the lowest air flow rate (0.5 LPM) gives the least treatment performance (19.4%) compared
to the higher air flow rate (2-3 LPM). In the first 30 minutes of treatment time, the washing performance
using 2 and 3 LPM show the removal percentage as 22.3% and 25%, respectively. However, it is comparable
after 30 minutes (~25.7%). From the experiment and the analyses of the hydrodynamic parameter in terms of
a/G results, DAF shows better TPH removal compared to the mechanical stirring and the IAF. Almost 40%
of TPH removal is removed by the DAF system at the saturated pressure of 4 bars with a washing time of 60
min. Also, the combination process between stirring with one of IAF and DAF was examined in order to
maximize TPH removal efficiency. The result shown that stirring combined with DAF with the optimum
condition, i.e., 3 bar, 400 rpm and 40 minutes treatment, is more effective (46% removal efficiency)
compared to single treatment, stirring combined with IAF, and other conditions: 2 bar-200 rpm-20 minutes,
and 4 bar-600 rpm-60 minutes.
Keywords: drill cuttings; air flotation; stirring process; total petroleum hydrocarbon
INTRODUCTION
As petroleum is the major energy source for industrial and economic development, drilling operation has
become an essential activity in the exploration and production of petroleum products. Many drilling wells are
extracted and drilled into the ground in order to bring the accumulated hydrocarbons up to the platform for
commercial and innovative petroleum products. In the system, drilling fluids are circulated or continuously
pumped from the surface down to drill string through drilling pipe to enhance cuttings extraction; then, they
bring the cuttings back to the rigs via annulus to store at settling pit. Drill cuttings are separated from muds
using vibrating screens, hydrocyclone, or centrifuges. Moreover, the cuttings will be managed and treated on
the platform to remove the adhered fluids as much as possible before either discharging to the ocean,
transporting to the shore for land disposal, or re-injecting into a disposal well, depends on the local
infrastructure and environmental regulations [1].
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Consequently, waste management is one issue facing the oil and gas industry because oil and gas drilling
processes generate a large volume of drill cuttings and spent mud during the operations. This has frequently
thrown the industries into numerous challenges and concerns of finding technological development for
controlling the wastes and safe environment. When those wastes are not properly managed, the process can
pose many significant impacts on the environment, such as soils/sediments, surface water, groundwater, and
aquatic environment due to the largely generated drill cuttings (DC) within drilling fluids throughout the
operation [2]. The reason is that these DC contain both organic and inorganic contaminants, including
petroleum hydrocarbons, polychlorinated biphenyls, and heavy metals, etc., which are very toxic to the
environment and human health [3,4]. For instance, the discharge of petroleum hydrocarbons and petroleum
affects human health, socio-economic problems, and degradation of host communities in the nine oil-
producing states in the Niger Delta area. In a similar vein, soils and sediments are the most vulnerable
petroleum contaminants. Precisely, they are easily contaminated with benzene, toluene, ethylbenzene, and
xylenes, aliphatic, and polycyclic aromatic hydrocarbons (PAHs). Therefore, hydrocarbons contaminated
soils and sediments are one of the discerning problems because its characteristics of aromatic components
cause oxygen depletion [2]. Similarly, DC are easily contaminated by drilling muds due to their broken and
small size, which fully coated by drilling muds during their transportation from the borehole to the platform.
It has known to be complicated in removing the drilling muds from DC, even after repeated washing [5].
So far, to deal with the disposal concerns, several treatment technologies have been explored, including
physical, chemical, and biological methods to reach the effective treatment in terms of efficiency, affordable
cost, non-hazard chemical use, and saving the environment [6]. However, some chemical methods are not so
popular as the use of harsh chemical agents affected the environment. At the same time, bioremediation is
another treatment method that offers advantages such as natural products from renewable resources,
excellent biodegradability, less toxic, and good environmental compatibility. Nevertheless, this technique has
known as a prolonged process and difficult to address with bio-refractory organic contaminations. Besides,
other physical approaches, such as thermal desorption, microwave, supercritical fluid extraction, and
ultrasonication, etc., are also observed, yet they are extremely costly and high energy usage [7].
Induced air flotation (IAF) is one of the physical processes that utilize diffusers, spargers, and other
mechanical methods to create as bubbles in a size range from 700 to 1500 micrometers (μm) in diameter.
Additionally, Dissolved Air Flotation (DAF) is another physical process that bubbles are generated by the
reduction in two different pressure (30 and 65 psi) of the supersaturated water in the air. Bubbles are formed
by the precipitation of the air within the range of 30 to 100 micrometers (μm) in diameter [8]. These two
processes have known as the very effective methods for oil-in-water emulsion separation. However, for DC
particle washing, these processes were used to combine either with another mechanical approach such as
stirring or surfactants to improve the treatment performance [9]. Hence, this study aims to investigate and
evaluate the effects of a potential treatment for TPH removal from DC washing by using the combination of
the flotation process with mechanical stirring under the environmentally friendly, economical, and less
operational installation.
MATERIALS AND METHODS
Experimental Set-up
In this study, the experiment was conducted in a small cylinder made by transparent acrylic material with 6
cm and 25 cm in diameter and height, respectively, as illustrated in Figure 1. The experimental set-up of
stirring was equipped with stirrer motor and impeller(s). At the same time, air diffuser installed at the bottom
connecting to air compressor was installed for IAF process (see Figure 1 (left)). The air flow rate of IAF was
regulated by air flow meter. For the DAF experiment, air compressor and pressure vessel were connected to
the bottom of the cell (see Figure 1 (right). All experiments were carried out under room temperature
(~28°C).
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Figure 1 Experimental set-up: IAF with stirring (left) and DAF with stirring (right)
Characteristic of Drill Cutting Samples
Drill cutting samples were collected from the offshore site of a real petroleum drilling operation. All samples
were kept at 4ºC before processing for characterization. First, samples were dried at room temperature and
screened by using sieve analysis from 3 mm to the smallest (< 2 µm) classifying into three classes, i.e., sand
(50-3000 µm), silt (2-50 µm), and clay (< 2 µm). The characteristics of the cutting sample were shown in
Table 1. The larger particles that retained on mesh 7 (2,830 µm) were separated due to their bigger properties
such as soil grains, gravels, etc. These grand particles were assumed not to be significantly polluted by total
petroleum hydrocarbon (TPH).
Table 1 Drill cuttings characteristics
Parameters Unit Value Parameters Unit Value
Size Distribution % 14.43 pH - 7.74
Sand (50 - 2000 μm) % 82.00 Moisture Content % 5.26
Silt (2 - 50 μm) % 3.56 Zeta Potential mV - 23.6
Clay (< 2 μm) TPH Concentration mg/kg 236,000
Washing Process Experiment
Tap water was used as the washing reagents in this study. It was initially examined in the individual process,
i.e., stirring, IAF, and DAF processes. This single process aimed to define the efficient system as well as the
optimum condition of each process. Therefore, the combination of each washing process was studied in order
to maximize the TPH removal performance. In an individual stirring process experiment, four main influent
variables were varied, including types of the impeller (pitch 4-blades and hydrofoil impellers), number of the
impeller (1 to 3 impellers), rotational speed (200 to 600 rpm), and washing time (0 to 60 minutes). However,
only two main parameters were investigated in IAF process, i.e., air flow rate (0.5 to 3.0 LPM) and washing
time (0 to 60 minutes), and in DAF process, i.e., saturated pressure in a pressure vessel (2 to 4 bar) and
washing time (0 to 60 minutes). In the process combination experiment, it was simultaneously operated
stirring with IAF and with DAF with the same range as individual investigation. It should be noted that the
solid-to-liquid ratio (S/L) is 1:10 since it was found as the optimum condition [10].
Analytical Parameters
In this study, the process performance was mainly examined in terms of TPH removal efficiency. It can be
determined by using initial and final TPH concentrations, as shown in equation (1). It should be noted that
gas chromatography equipped with a flame ionization detector (GC-FID) was used in this work for analysing
TPH concentration in DC, followed by the USEPA method 8015B [11].
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TPH removal (%) Initial TPH Residual TPH 100 (1)
Initial TPH
Bubble interfacial area (a) is one of the main parameters to describe the bubble hydrodynamic
characteristics. It is the ratio of total gas bubble surface and total volume in the system (included gas and
liquid phases), which can be determined in terms of formation frequency (fB), bubble rising velocity (UB),
and the bubble diameter as shown in equation (2), where NB, SB, VTotal, and HL are the total amount of bubble
in the system, total gas bubble surface area, the total volume of liquid and gas, and liquid height during
operation, respectively [12].
a f B HL SB f B HL DB2 (2)
UB VTotal UB AH L NBVB
Another important parameter is the velocity gradient (G). It represented the mixing level in the flotation cell.
Velocity gradient (G) can be determined by using equation (3) [13], where P is the power required, µ is the
dynamic viscosity, and V is the volume of the reactor. For the stirring process, P can be calculated from the
mixing device parameters, as expressed in equation (4), where n is rotational speed, D is impeller diameter, ρ
is the density of the liquid, KT is impeller constant for turbulent flow. For IAF and DAF processes, P can be
estimated by using pneumatic mixing parameters, as expressed in equation (5), where C1 is a constant equal
to 3904, Qg was air flow rate, and H was depth from the water surface to the diffuser [14].
G P 0.5 (3)
V
P KT n3D5 (4)
P C1Qg log H 10.4 (5)
10.4
RESULTS AND DISCUSSIONS
The present work was divided into two main parts of individual and combined process experiments for covering
five subsections, i.e., TPH removal by the individual process including stirring, IAF, and DAF, and by the
combined process including stirring with IAF, and stirring with DAF.
TPH Removal by Mechanical Stirring
Prior to studying the performance of mechanical stirring for DC washing, the selection of the suitable type
(Pitch-4 blades and hydrofoil impellers) and the number of the impeller (1 to 3 impellers) used in mixing
column for optimizing the process conditions of the mechanical stirring process were preliminarily
investigated. DC 50 g washed by tap water 500 mL with 300 rpm of rotational speed for 30 minutes of
washing time was designed for this preliminary test. The result of each impellers set-up was illustrated in
Figure 2 (a). It was found that using only one impeller of PBT-4 resulted in the highest removal efficiency
compared to 2 and 3 impellers of itself and hydrofoil impellers. One impeller of PBT-4 had enough ability to
suspend the soil matrix within the studied ratio of solid to liquid (1:10), whereas using two and three
impellers were quite far to suspend the soil matrix effectively. This could be explained based on the off-
bottom clearance C, which was the height from the bottom of the reactor to the impeller located in the tank.
It was recommended to be 0.25 of tank diameter (C/DT = 0.25) [15]. Therefore, one impeller of PBT-4 was
selected for the next experimental work of this study.
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Figure 2 Effect of impeller design and operation on TPH removal efficiency: (a) type and number of
the impeller, (b) impeller rotational speed
Then, three different rotational speeds, i.e., 200 rpm, 400 rpm, and 600 rpm, were employed for an hour with
10 minutes sampling step to study the performance of mechanical stirring on the removal of TPH. According
to Figure 2 (b), it showed that the TPH removal increased with the increase of rotational speed. For one hour
of washing time, 600 rpm of rotational speed provided the highest performance with 28% of TPH removal,
while 400 rpm and 200 rpm gave 25% and 22% of TPH removal, respectively. This phenomenon could
explain based on the turbulence in mixing conditions generated by rotational speed. The turbulence
conditions might break the attraction between the TPH and the soils; hence, the TPH molecules detached
from the soil and resulted in greater removal efficiency.
TPH Removal by Induced Air Floatation (IAF)
Three air flowrate conditions, including 0.5, 2, and 3 LPM, were investigated on TPH removal, as depicted
in Figure 3 (a). It showed that 0.5 LPM provided the lowest treatment performance compared to the other
two conditions (2 and 3 LPM). Since the IAF process related to bubbles, hence the bubble hydrodynamic in
terms of interfacial area to velocity gradient (a/G) was employed to explain the effect of air flow rate on TPH
removal. Greater a/G indicates higher contact probability between bubbles and oils with the high interfacial
area of bubble and low turbulence. Oils preferably attached to the bubbles, which accelerated the flotation of
oils to the liquid surface, resulted in greater TPH removal. As shown in Figure 3 (b), the removal efficiency
linearly increased with the increase of a/G values. The highest a/G was obtained from the IAF process
operating with air flow rate of 3.0 LPM. Therefore, the presumption mentioned earlier that greater a/G
provided higher TPH removal was confirmed.
Figure 3 Effect of (a) air flow rate and washing time, and (b) a/G value on TPH removal efficiency in
IAF process
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TPH Removal by Dissolved Air Floatation (DAF)
In this part, three saturated pressures of the DAF process (2, 3, 4 bars) were explored with the same washing
time. The result was shown that this process was more effective for DC washing compared to stirring and
IAF processes. Almost 40% of removal efficiency was observed at the saturated pressure of 4 bars with a
washing time of 60 min, as seen in Figure 4 (a). From the observation, there were not many of the bubbles
produced in the flotation cell at the saturated pressure of 2 bars, which caused TPH removal efficiency from
DC was less (roughly 26%). Meanwhile, TPH was removed around 40% at the saturated pressure 4 bars
because there were many tiny bubbles produced at this pressure, providing high interfacial area value and
resulting in more TPH removal. In addition, a to G ratio was very large, as seen in Figure 4 (b). This
phenomenon could explain according to the differences between the air bubble diameter produced in IAF
and DAF processes. Due to the diameter of the air bubble in the DAF process were much smaller (roughly
from 80 to 180 µm) than that in the IAF process (1.3 to 2 mm); hence, a/G ranged largely and represented as
better results in TPH removal from DC too.
Figure 4 Effect of (a) saturated pressure and washing time, and (b) a/G value on TPH removal
efficiency in the DAF process
TPH Removal by Mechanical Stirring Combined with IAF/DAF
Afterward, the combination of stirring wit one of IAF and DAF were examined in order to maximize TPH
removal efficiency. Three designed conditions, such as lowest value (200 rpm, 1 LPM, and 20 min), middle
value (400 rpm, 2 LPM, and 40 min), and the highest value (600 rpm, 3 LPM, 60 min) were observed and
compared each other. The results in Figure 5 showed that stirring combined with DAF with the optimum
condition, i.e., 3 bars, 400 rpm, and 40 min of treatment time was more effective (46% removal efficiency)
compared to the single treatment, stirring combined with IAF, and other conditions: 2 bars-200 rpm-20
minutes, and 4 bars-600 rpm-60 minutes. This was because microbubbles generated by DAF provided a high
interfacial area, which enhanced the attachment between oils and bubbles, accelerating the flotation of oils to
the liquid surface and resulting in high TPH removal percentage. Additionally, operating at high rotational
speed (600 rpm) not only provided high turbulence that decreased the contact probability between oils and
bubbles but also caused the coalescence of bubbles, which decreased the interfacial area value. Therefore,
this a/G ratio could be possibly applied as the design and controlling parameters for DC washing by the
stirring combined with the flotation process.
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Figure 5 TPH removal efficiency at designed conditions for stirring combined with IAF and stirring
combined with DAF
CONCLUSION
In summary, this work aimed to develop a flotation enhanced stirred tank (FEST) process for TPH removal
from drill cuttings. The IAF and DAF processes were individually investigated and analyzed following a/G
ratio, which could define a better performance of the removal efficiency and could explain the bubble
interfacial area in mixing conditions. In addition, both the IAF combined with stirring and DAF combined
with stirring were found to be more effective in TPH removal then every individual process. As a result,
roughly 40% were found as the removal percentage of TPH from DC at air flow rate of 3 LPM with the
rotational speed of 600 rpm at the washing time of 60 min in stirring combined with the IAF unit. In a
similar vein, the optimum removal percentage was approximately 50% at saturated pressure of 3 bar,
rotational speed 400 rpm for 40 min of washing time in stirring combined with DAF unit. It was notified that
this percentage represented as the better results since it operated with tap water only to remove TPH. It was
expected that this study was beneficial for further research since it offered chemical-free alternatives for
preliminary treatments of drill cuttings.
ACKNOWLEDGEMENT
The authors would like to acknowledge Department of Environment, Faculty of Engineering, Chulalongkorn
University, for the facilities and laboratory services. A grateful thank is also extended to the Research Unit
on Technology for Oil Spill and Contamination Management, Chulalongkorn University, and ASEAN
scholarship program of Chulalongkorn University for the research fund.
REFERENCE
[1] IOGP. (2016). Environmental Fates and Effects of Ocean Discharge of Drill Cuttings and Associated
Drilling Fluids from Offshore Oil and Gas Developments. Report 543, (pp. 144).
[2] Ite, A. E., Ibok, U. J., Ite, M. U., and Petters, S. W. J. A. J. o. E. P. Petroleum exploration and
production: Past and present environmental issues in the Nigeria’s Niger Delta. 1(4) (2013): 78-90.
[3] Onwukwe, S., Nwakaudu, M. J. I. J. o. E. S., and Development. Drilling wastes generation and
management approach. 3(3) (2012): 252.
[4] Yan, P., Lu, M., Guan, Y., Zhang, W., and Zhang, Z. J. B. t. Remediation of oil-based drill cuttings
through a biosurfactant-based washing followed by a biodegradation treatment. 102(22) (2011):
10252-10259.
[5] Kubo, Y. s., Kido, Y., Fuwa, Y., Hoshino, H. J. J. R. o. R., and Development. Experiments on method
for washing drill cuttings: evaluation of soaking, stirring, and milling effects. 22 (2016): 39-48.
[6] Agarwal, A., Zhou, Y., Liu, Y. J. E. S., and Research, P. Remediation of oil-contaminated sand with
self-collapsing air microbubbles. 23(23) (2016): 23876-23883.
[7] Sun, H., Liu, H., Wang, S., and Liu, Y. J. J. o. h. m. Remediation of oil spill-contaminated sands by
chemical-free microbubbles generated in tap and saline water. 366 (2019): 124-129.
[8] Rubio, J., Souza, M., and Smith, R. J. M. e. Overview of flotation as a wastewater treatment
technique. 15(3) (2002): 139-155.
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[9] Urum, K., Pekdemir, T., Ross, D., and Grigson, S. J. C. Crude oil contaminated soil washing in air
sparging assisted stirred tank reactor using biosurfactants. 60(3) (2005): 334-343.
[10] Potiruch, C., and Painmanakul, P. Reactor development for oil removal from drill cuttings.
Chulalongkorn University. 2019.
[11] U.S. EPA. (1996). Test methods for evaluating solid waste physical/chemical methods. Washington,
DC, USA.
[12] Painmanakul, P., Sastaravet, P., Lersjintanakarn, S., Khaodhiar, S. J. C. E. R., and Design. Effect of
bubble hydrodynamic and chemical dosage on treatment of oily wastewater by induced air flotation
(IAF) process. 88(5-6) (2010): 693-702.
[13] Crittenden, J. C., Trussell, R. R., Hand, D. W., Howe, K. J., and Tchobanoglous, G. MWH's water
treatment: principles and design. John Wiley & Sons, 2012.
[14] Reynolds, T. D., and Richards, P. A. Unit Operation and Processes in Environmental Engineering.
(1996).
[15] Ayranci, I., Kresta, S. M., Derksen, J. J. J. C. E., and Technology. Experiments and simulations on
bidisperse solids suspension in a mixing tank. 36(11) (2013): 1957-1967.
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Bio-char Production from Co-pyrolysis between
Rice Husk and Plastic: A Morphology Study
Nichakorn Wantaneeyakul1* and Ketwalee Kositkanawuth2
1*Master student ; 2Lecturer, Department of Environmental Engineering, Faculty of Engineering,
King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok 10140, Thailand
*Phone : 080-806-5959, E-mail : [email protected]
ABSTRACT
In Thailand, rice husk (RH) is an abundant residue and its amount is increased annually. The improper waste
management of rice husk such as open burning usually produces a significant amount of air pollutants,
especially PM10. Pyrolysis is therefore applied to convert rice husk into more valuable product like bio-char.
However, the quantity and quality of rice husk bio-char are relatively poor. Thus, this study aims to
investigate the effect of high-density polyethylene (HDPE) addition at ratio of 1:1 on bio-char yields and
properties. The pyrolysis experiments were carried out using a fixed-bed reactor under varied temperatures
(400/500/600ºC) and holding times (15/30/45 min) for both individual rice husk pyrolysis and co-pyrolysis.
Then, only specific bio-char samples were selected according to the bio-char yield, proximate, and ultimate
analysis for further surface analysis including Scanning Electron Microscope (SEM), Brunauer-Emmett-
Teller (BET), and Fourier Transform Infrared Spectroscopy (FTIR). The characterizations revealed the
effects of co-pyrolysis on the surface properties of the bio-char obtained at 400oC and 15 minutes (RHPE-
400-15). The SEM images showed that the RHPE-400-15 bio-char surface was welded together, and its pore
was hardly seen; whereas, morphological structure of rice husk bio-char obtained at the same condition (RH-
400-15) normally contained a number of pores in different sizes. Besides, a decrease of more than half in
surface area (from 1.546 to 0.286 m2 g-1), pore volume (from 88.576 x10-4 to 5.580 x 10-4 cm3 g-1), and pore
size (from 22.913 to 8.137 nm) was observed when comparing between RHPE-400-15 to RH-400-15. In
addition, the stretching of -CH bonds resulting from HDPE was presented on the FTIR result of the RHPE
bio-char.
Keywords : Bio-char; Co-pyrolysis; HDPE; Plastic; Rice husk
INTRODUCTION
Since rice is a staple food in Thailand, an abundant amount of rice husk, a by-product from milling process,
is annually generated as high as 7.5 million tons [1]. Due to low bulk density and high ash content, rice husk
residue causes a difficulty in handling process of solid waste management [2]. Consequently, an improper
way such as open burning is used to manage the residue, which leads to emission of air pollutants, especially
PM10 [3]. Thus, a conversion of rice husk into more valuable products like bio-char through pyrolysis
process should be considered.
Pyrolysis is a thermochemical process that can convert lignocellulosic materials into bio-oil, bio-char, and
gaseous product under an absence of air or oxygen atmosphere. Pyrolysis has become an attractive process
since the operational steps are less complex and easy to optimize the preferable product yields . The bio-char
from individual biomass pyrolysis has been investigated for solid fuel utilization. Unfortunately, the bio-char
has relatively low quality, inherited from the low ratio of hydrogen to carbon but high oxygen content in the
biomass itself [4]. For example, Maiti, et al. [5] studied on rice husk pyrolysis and found that a little
decrement in oxygen content was occurred when temperature was increased from 450ºC to 650ºC, resulting
in a slight increase in carbon content from 66.76 wt% to 69.29 wt%. To remove more oxygen content and
improve the quality of the bio-char, additional hydrogen content from another material is possibly needed.
Plastic waste is typically an organic material rich in hydrogen with negligible oxygen. Thus, it can be a
hydrogen donor during co-pyrolysis with the biomass. In addition, the plastic waste has been increasing
annually, approximately 1.5 million tons of the waste was reported in 2018 which was 1.45 times greater
than the previous year [6]. Most of single-use plastic is immediately discarded into landfills, causing
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environmental problems. Thus, using the plastic in co-pyrolysis is not only a solution to improve bio-char
quality, but it is also an environmentally friendly way to manage the plastic waste.
This study aims to investigate the effect of the plastic on bio-char yields and properties. For comparison,
individual pyrolysis of rice husk and co-pyrolysis between rice husk and high-density polyethylene (HDPE)
at ratio of 1:1 were performed under several temperatures (400/500/600ºC) and holding times (15/30/45
min). The analytical techniques of proximate and elemental analysis were used to identify the effect of
HDPE on bio-char chemical compositions. The morphological aspect was analyzed by Scanning Electron
Microscope (SEM), Brunauer-Emmett-Teller (BET), and Fourier Transform Infrared Spectroscopy (FTIR)
techniques.
METHODOLOGY
The feedstocks used in this study included rice husk (RH) and recycled high-density polyethylene (HDPE).
Prior to the experiment, proximate analysis of the raw samples was performed by Thermogravimetric
analyzer (TGA801, Leco). The elemental analysis of the raw sample was conducted using a CHN628, Leco
elemental analyzer. The results of proximate as well as ultimate analysis are presented in Table 1. The
pyrolysis experiments were performed under non-sweeping nitrogen gas atmosphere using a fixed-bed
reactor as shown in Fig. 1. For individual pyrolysis, 15 grams of dry individual feedstock (RH, HDPE) was
used in each experiment. At the beginning of each run, the nitrogen gas was firstly fed into the reactor for
approximately 10 min to flush all of the air from inside. The reactor was externally heated from room
temperature up to three different desired temperatures of 400°C, 500°C, and 600°C with 10°C/min heating
rate. Once the desired temperature was reached, it was maintained for 15 to 45 min holding time. For co-
pyrolysis, the blended feedstock at ratio of 1:1 by weight was observed under the same pyrolysis conditions
as individual pyrolysis.
After each experiment, the bio-char was collected and weighted. The bio-char yield (YC) and fixed carbon
yield (YFC) were calculated using equation (1) and (2), respectively. Only the selected bio-char samples
obtained at temperature of 400ºC and 15 minute holding time were further characterized on their morphology
and surface properties.
Yc = (MChar) / (Mfeedstock) (1)
where MChar indicates weight of bio-char (g)
Mfeedstock indicate weight of dry weight of initial feedstock (g)
YFC = (Yc) * (FC/100) (2)
where Yc indicates bio-char yield (wt%)
FC indicates fixed carbon content (wt%)
Fig.1 Schematic of pyrolysis setup
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A JEOL Scanning Electron Microscope (SEM) with the model of JSM-6610 LV was used for bio-char
external morphology characterization. The specific area, pore volume, and pore size of the samples were
obtained using Belsorp mini II BET analyzer (Microtrac-BEL Corporation). For Fourier Transform Infrared
Spectroscopy (FTIR), the samples were analyzed within the spectrum range from 4000 to 400 cm-1 by KBr
FTIR, Perkin Elmer. Each bio-char was labeled as feedstock (RH as rice husk or RHPE as rice husk with
HDPE) -temperature (400/500/600oC) -holding time (15/30/45 minutes). For example, RH-400-15 refers to
the bio-char from rice husk pyrolysis at 400ºC with 15 minute holding time.
Table 1 Ultimate and proximate analysis for raw feedstocks (RH and HDPE)
Proximate analysis, wt% RH HDPE
Moisture
Volatile matter 7.04 0.22
Fixed carbon 61.70 97.13
Ash 15.31 0.00
15.95 2.65
Ultimate analysis, wt%
Carbon 40.67 83.69
Hydrogen 5.80 15.23
Oxygena 52.96 0.87
Nitrogen 0.57 0.21
O/C molar ratio 1.30 0.01
H/C molar ratio 0.14 0.18
a Calculated by difference
RESULTS AND DISCUSSIONS
The bio-char yields from both individual and co-pyrolysis under all conditions were illustrated in Fig. 2. The
maximum bio-char yields for both individual and co-pyrolysis were obtained at temperature of 400ºC under
different holding times; 55.06 wt% for RH-400-15 and 55.68 wt% for RHPE-400-30. For individual pyrolysis of
rice husk, the bio-char yields continuously decreased as the temperature was increased, due to more cracking of
biomass from solid to vapor phase at higher temperature. For co-pyrolysis, there was also an apparent decrease in
bio-char yields; however, it only occurred when temperature was shifted from 400ºC to 500ºC under all holding
times. Interestingly, the effect of holding time was more noticeable for RHPE than RH at 400ºC. This result was
possibly related to the addition of HDPE.
After considering bio-char yields along with their ultimate and proximate analysis results from all pyrolysis
conditions. The the most improvement in carbon content of bio-char was found at pyrolysis temperature of 400ºC,
regardless of holding time. Approximately 9.27, 9.06 and 5.19 wt% increase in carbon could be noticed
comparing between RHPE-400 and RH-400 at 45, 15 and 30 min holding time, respectively (Table 2). The higher
carbon content possibly came from melted HDPE over the rice husk char [7].
Proximate analysis obviously revealed that the increase in carbon content mainly came from the higher in volatile
matter fraction. However, bio-char mostly focused on fixed carbon rather than volatile matter. Thus, in order to
compare the process performance, YFC value (fixed carbon yield) was calculated and reported in Table 2. Even
though the maximum fixed carbon yield was obtained from RHPE-400-30 sample, the percent improvement of
carbon content was the lowest. Thus, the RHPE-400-15 sample was more attractive since it provided the second
maximum values for both fixed carbon yield (9.32 wt%) and the percent upgrade of carbon content (9.06 wt%).
Consequently, the RHPE-400-15 sample was therefore chosen for further analysis.
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60.00
Yc (wt%) 55.00 55.68
50.00 49.29
45.00 45.23
40.00
35.00
30.00
25.00
20.00 400 500 600 700
300 Temperature (ºC)
RH-15 RH-30 RH-45
RHPE-15 RHPE-30 RHPE-45
Fig. 2 Bio-char yields from RH pyrolysis and RHPE co-pyrolysis at
different temperatures and holding times
Table 2 Ultimate and proximate analysis for RH and RHPE at 400ºC
Sample 15 RH 45 15 RHPE 45
Holding times (min) 30 30
Proximate analysis, wt% 26.64 25.68 66.28 65.84
Volatile matter 42.27 25.46 43.03 18.91 65.21 19.29
Fixed carbon 31.08 43.01 31.30 14.81 18.95 14.88
Ash 31.53 9.32 15.85 8.72
Fixed carbon yield - - 10.55
Ultimate analysis, wt% - 80.98 81.41
Carbon 71.92 72.14 10.37 78.35 10.32
Hydrogen 5.26 73.16 5.15 8.15 9.88 7.89
Oxygena 22.05 5.16 21.99 0.50 11.36 0.38
Nitrogen 0.77 20.92 0.73 0.10 0.42 0.10
O/C molar ratio 0.31 0.77 0.30 0.13 0.14 0.13
H/C molar ratio 0.07 0.29 0.07 0.13
a Calculated by difference 0.07
The comparisons of surface morphology and properties between RH-400-15 and RHPE-400-15 were shown in
Fig. 3-4 and Table 3. The SEM usually provides the information about structure and morphological appearance of
bio-char. The image at magnification of 1,000 times showed that the interior structure of pure rice husk bio-char
(RH-400-15) was composed of many pores in different sizes due to volatilization of volatile compounds
(Fig. 3(a)) [8]. In contrast, the opposite result was illustrated for rice husk and plastic bio-char (RHPE-400-15) as
shown in Fig. 3(b). The surface of the bio-char obtained from co-pyrolysis was welded together and the pores
were hardly seen. In addition, it could be noticed that HDPE material coated on bio-char since little degradation of
HDPE would be occurred at 400ºC [9]. In agreement with the SEM images, the BET surface area pore volume,
and the average pore size of RH-400-15 were greater than the RHPE one as shown in Table 3.
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(a) (b)
Fig. 3 SEM images of (a) RH and (b) RHPE bio-char obtained at pyrolysis temperature of 400ºC and 15
minute holding time
Table 3 Specific surface area, pore volume, and average pore size of RH and RHPE bio-char obtained at
pyrolysis temperature of 400ºC and 15 minute holding time
Sample Surface area Pore volume Average pore size
(m2 g-1) (x 10-4 cm3 g-1) (nm)
RH-400-15 22.913
RHPE-400-15 1.546 88.576 8.137
0.286 5.580
According to FTIR analysis, the chemical functional groups on bio-char surface was presented in Fig. 4. In
overall, the absorption bands reported in this study were a combination of typical absorption bands found in rice
husk and HDPE, including water, inorganic components, functional groups of hemicellulose, cellulose, and lignin,
and also methylene group from plastic materials.
Based on FTIR spectra database from related literatures [7,9,10,11], the wide band of around 3400 cm-1 was found
for RH, attributing to O-H in water molecules with hydrogen bonds, or the hydroxyl group (-OH) normally
presenting in cellulose, hemicellulose, and lignin. However, the peak of around 1600 cm-1 was found only for RH.
The peak could represent both the deformation vibration of the water molecules (δ-H2O) as well as the aromatic
groups in lignin (C=C stretching) that normally found in bio-char. Moreover, the peak of 1435 cm-1 on RH was
defined as C-H deformation in the lignin and carbohydrates (cellulose and hemicellulose). The intense band of
1099 cm-1 on RH responded to the vibration of silicon-oxygen tetrahedrons (SiO4) and the main vibrations of the
C-OH bond in cellulose. In addition, absorption peak at around 790 cm-1 representing the presence of symmetric
vibration of Si-O bond (SiO4) was also detected on RH [12].
Like FTIR result of the RH bio-char, the same several peaks were found on the RHPE bio-char, including 3400
cm-1, 2915 cm-1, 2850 cm-1, 1600 cm-1, 1470 cm-1, 1099 cm-1 and 790 cm-1. However, the presence of distinct three
peaks was apparently exhibited on RHPE. Firstly, the distinct peaks of 2915 cm-1 and 2850 cm-1 were related to
asymmetric and symmetric of stretching of C-H in -CH2 groups from PE matrix. Secondly, the peak of 1470 cm-1
demonstrated the C-H bending band of CH2 groups which affected from HDPE addition. Finally, the peak of
approximately 720 cm-1 attributed to C-H bending bond of CH2 rocking mode of the sequence of CH2 groups in
paraffin structure [9]. Thus, these results could be claimed as the evidences of HDPE deposition on rice husk
surface during co-pyrolysis.
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Raw RH
RH
RHPE
Raw HDPE
Fig. 4 FTIR spectrum of RH and RHPE bio-char obtained at pyrolysis temperature of 400ºC with 15
minute holding time and raw RH, HDPE from literatures [12,13]
CONCLUSION
In this study, individual pyrolysis of rice husk and co-pyrolysis between rice husk and HDPE were carried
out under varied temperatures and holding times to investigate the effect of HDPE addition on both quality
and quantity of the final bio-char products. According to the bio-char yields, proximate, and ultimate
analysis, RHPE-400-15 was selected for further study on the effect of HDPE on bio-char surface.
Co-pyrolysis between rice husk and HDPE certainly impacted the carbon content of bio-char product.
Additionally, it also affected some of surface properties due to the deposition of volatiles from the plastic,
especially surface area and pore volume which decreased more than half as compare to the original RH bio-
char obtained at the same condition (RH-400-15).The deposition of HDPE was confirmed by the stretching
of C-H found on the RHPE bio-char; however, it could be beneficial for some pollutant removals such as
2,4-Dinitrotoluene (DNT) and 2,4-dichlorophenol (DCP) [14].
ACKNOWLEDGEMENT
The authors gratefully acknowledge Dr. Scott Turn and Dr. Jinxia Fu (Hawaii Natural Energy Institute) at
University of Hawaii at Manoa for proximate and ultimate analysis.
REFERENCE
[1] Ministry of Agriculture and Cooperatives, ASEAN Agricultural Commodity outlook in 2017. Ministry
of Agriculture and Cooperatives: Bangkok, Thailand, 2017. Available Online:
http://www.aptfsis.org/uploads/normal/ACO%20Report%2019/ACOreport%20no19.pdf [accessed on
5 April 2020,].
[2] Kumar, S., Sangwan, P., Dhankhar R.M.V. and Bidra, S. 2013. Utilization of rice husk and Their ash:
A Review. Research Journal of Chemical and Environmental Sciences. 1(5): 126-129.
[3] Junpen, A., Pansuk, J., Kamnoet, O., Cheewaphongphan, P. and Garivait, S. 2018. Emission of Air
Pollutants from Rice Residue Open Burning in Thailand, 2018. Atmosphere. 9(11): 449
[4] Wang, S., Jiang, D., Cao, B., Qian, L., Hu, Y., Liu, L., Yuan, C., Abomohra, A., He, Z., Wang, Q.
and Zhang, B. 2018. Bio-char and bio-oil characteristics produced from theinteraction of
Enteromorpha clathrate volatiles and rice husk-bio-char during co-pyrolysis in a sectional pyrolysis
furnace: A complementary study. Journal of Analytical and Applied Pyrolysis. 135: 219-230.
[5] Maiti, S., Dey, s., Purakayastha, S. and Ghosh, B. 2006. Physical and thermochemical characterization
of rice husk char as a potential biomass energy source. Bioresource Technology. 97: 2065-2070.
[6] Pollution Control Department (PCD), Booklet on Thailand State of Pollution 2018. Ministry of Natural
Resources and Environment: Bangkok, Thailand, 2019. Available Online:
http://www.pcd.go.th/file/Booklet%20on%20Thailand%20State%20of%20Pollution%202018.pdf
[accessed on 5 April 2020,].
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[7] Cai, H., Ba, Z., Yang, K., Zhang, Q., Zhao, K. and Gu S. 2017. Pyrolysis characteristics of typical
biomass thermoplastic composites. Results in Physics: 7: 3230-3235.
[8] Uzunova, S., Angelova, D., Anchev, B., Uzanov, I. and Gigova, A. 2014. Changs in structure of solid
pyrolysis residue during slow pyrolysis of rice husk. Bulgarian Chemical Communications. 46(1):
184-191.
[9] Krehula, L.K., Katancic, Z., Sirocic, A.P. and Hrnjak-Murgic Z. 2014. Weathering of High-Density
Polyethylene-Wood Plastic Composites. Journal of Wood Chemistry and Technology. 34: 39-54
[10] Liu, Z., Quek, A., Hoekman, S.K. and Balasubramanian, R. 2013. Production of solid biochar fuel
from waste biomass by hydrothermal carbonization. Fuel. 103: 943-949.
[11] Kizito, S., Wu, S., Kirui, W.K., Lei, M., Lu, Q., Bah, H. and Dong, R. 2015. Evaluation of slow
pyrolyzed wood and rice husks biochar for adsorption of ammonium nitrogen from piggery manure
anaerobic digestate slurry. Science of the Total Environment. 505: 102-112.
[12] Cruz, G., Braz, C.E.M., Ferreira, S.L., Santos, A.M.D. and Crnkovic, P. M. Physicochemical
properties of brazilian biomasses: Potential applications as renewable energy source. At 22nd
International Congress of Mechanical Engineering, Ribeirão Preto, SP, Brazil on November 3-7, 2013.
[13] Morais, J.A.D.M. and Paoli M.A.D. 2016. Curaua fiber reinforced high-density polyethylene
composites: effect of impact modifier and fiber loading. Polímeros. 26(2): 115-122
[14] Oh, SY. and Seo, TC. 2019. Upgrading biochar via co-pyrolyzation of agricultural biomass and
polyethylene terephthalate wastes. RSC Advances. 48: 28284-28290.
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Comparison of Various Pretreatment Techniques on Enhancing Sugar
Yields from Sugarcane Trash
Pavarisa Chaipet1*, Wanwipa Siriwatwechakul 2, and Verawat Champreda 3
1* Graduate student, School of Bio-Chemical Engineering and Technology, Sirindhorn International Institute
of Technology, Thammasat University, Thailand;
2Advisor, School of Bio-Chemical Engineering and Technology, Sirindhorn International Institute of
Technology, Thammasat University, Thailand
3Co-advisor, National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand
*Phone : (+66)830218456, E-mail : [email protected]
ABSTRACT
As a feedstock in a biorefinery, sugarcane trash (leaves and tops) can be converted to
monosaccharides by enzymatic hydrolysis and fermentation. Pretreatment is required to increase the
efficiency of enzymatic hydrolysis. Three well-known pretreatments were investigated with varying catalyst
dosage: dilute acid (ACD), alkaline sodium hydroxide (ALK-NaOH), and alkaline hydrogen peroxide (ALK-
H2O2). The best glucose recovery yields were 58.64%, 81.77%, and 92.66% achieved with ACD, ALK-
NaOH, and ALK-H2O2, respectively. This was based on the available glucose in the raw material after
enzymatic hydrolysis using 20 filter paper units (20 FPU)/g of Cellic®CTec2. For the shortest reaction time,
alkaline sodium hydroxide resulted in the highest yield. In contrast, alkaline hydrogen peroxide generated
more fermentable sugar with longer reaction time. This work provides a selection of pretreatment methods
for sugarcane trash in biorefineries.
Keywords: sugarcane trash; biorefinery; enzymatic hydrolysis; dilute acid, alkaline sodium hydroxide,
alkaline hydrogen peroxide
INTRODUCTION
Because of a societal goal to decrease the use of fossil fuels, the production of biofuel from
lignocellulosic biomasses has become interesting. Lignocellulosic biomass mainly comprises three
biopolymers: cellulose, hemicellulose, and lignin. Bioethanol production from agricultural wastes, woody
crops, forest wastes, and paper wastes could be an attractive disposal alternative for these residues.
Transforming the lignocellulosic agricultural waste into biofuels, biochemicals, and biomaterials is
called the ―biorefinery‖ process. This process maximizes the benefits of biomass conversion and value-added
products [1]. Lignocellulosic biomass is processed through major steps in biorefineries: pretreatments for
delignification, crystalizing cellulose, and hemicellulose reduction; hydrolysis to breakdown the chains of
cellulose and hemicellulose to a fermentable sugar; and fermentation of monomer sugar to biofuel.
Sugarcane trash is an agricultural waste that consists of sugarcane leaves and cane tops. Normally, it
is burned after or before harvesting, to facilitate easier sugarcane stalk collection. Nowadays, agricultural
burning is a source of particulate matter. Burning generates many particles that have a diameter of less than
2.5 micrometers (PM 2.5), and this activity is restricted by the Thai national policy [2]. Biofuel production
from sugarcane trash is a useful alternative. However, sugarcane trash has a complex structure that decreases
the performance of enzymatic hydrolysis. Hence, an effective pretreatment step is essential for its conversion
to fermentable sugars.
A proper pretreatment method increases the enzyme accessibility to cellulose, lignin, and/or
hemicellulose to achieve greater cellulose degradation by cellulolytic enzymes and greater concentration of
fermentable sugars for the fermentation step [3]. Many methods have been developed for lignocellulosic
pretreatment. Several of them have been reported, such as dilute acid pretreatment, steam explosion, alkaline
pretreatment, alkaline hydrogen peroxide, organic solvents, organosolv, and liquid hot water [4].
In this study, we evaluated three well-known pretreatment methods: dilute acid (ACD), alkaline
sodium hydroxide (ALK-NaOH), and alkaline hydrogen peroxide (ALK-H2O2). We studied their impacts on
the main compositions of biomass (cellulose, hemicellulose, lignin, ash) and enzymatic digestibility. Dilute
acid pretreatment is a combined action of pH, pressure, and heat during a period of time. Adding acid as a
catalyst for lignocellulosic hydrolysis is common and effective pretreatment. Sulfuric acid is a commonly
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applied acid among various types of acids, such as hydrochloric acid, phosphoric acid, and nitric acid [3].
Several research groups have proposed dilute acid pretreatment with sulfuric acid. A maximum yield of 71%
was obtained for sugarcane bagasse hydrolyzed with 2% H2SO4 at 155ºC for 10 min [5]. Another paper
showed that the optimum hydrolysis conditions were 1% v/v of H2SO4, 60 minutes of reaction time by solid
loading of sugarcane leaves (100 g /L) at a constant temperature of 122 . After hydrolysis, the maximum
sugars (16.52±0.48 g/L of xylose, 2.59±0.28 g/L of glucose and 2.27±0.1 g/L of arabinose) were obtained.
[6]. Moreover, the largest amount of glucose (0.35 g glucose/g biomass) approximately 60% of conversion
yield was at the conditions of 1.5% sulfuric acid, 15 minutes of reaction time, at 170 and 20% solids
loading [7].
Alkaline hydrolysis affected the swelling of cellulose and the saponification of ester-bond cross-links
with lignin and hemicellulose. This leads to an increase in the internal surface area of biomass [4]. A
previous paper studied the alkaline oxidation pretreatment on various agricultural wastes. After enzymatic
hydrolysis, glucose yields of 80%, 91%, and 97% were obtained for spruce, birch, and bagasse, respectively
[8]. The lowest pretreated bagasse lignin content (7.16%) was treated by 1N NaOH for 30 minutes to
increase the enzyme accessibility. Moreover, 1N NaOH was more effective than 2N NaOH in decreasing the
lignin content and increasing the cellulose content in sugarcane bagasse [9]. A previous study investigated
the effects of alkaline pretreatment on various lignocellulosic biomasses with 5%-15% sodium hydroxide
(%w/w NaOH). The results showed that the maximum ethanol yields were achieved using 10%, 15%, and
5% w/w NaOH for eucalyptus, straw, and bagasse, respectively [10].
For alkaline hydrogen peroxide (ALK-H2O2), hydrogen peroxide is added to hydrolyze the
lignocellulosic structure of biomass. However, it affects the degradation and delignification of biomass. This
pretreatment method was pH-dependent and produces hydroxyl radicals. A previous study reacted cane
bagasse with alkaline hydrogen peroxide. The results showed that with 2% alkaline hydrogen peroxide at
30°C with 8 h of reaction time, 50% of the lignin and most of the hemicellulose content of sugarcane bagasse
were solubilized. Moreover, the cellulose content was increased from 42% to 75% in the pretreated pulp, to
obtain a 95% glucose yield [11]. Furthermore, alkaline hydrogen peroxide was studied for the
saccharification of sugarcane bagasse. The results showed that with pretreatment of 6.25% H2O2, 160 , for
60 minutes of reaction time, the highest glucose yield of 77.6% was obtained [12]. Moreover, other
researchers combined the peroxide with alkaline pretreatment for sugarcane wastes, bagasse, and trash. The
pretreated sugarcane trash contained 36% cellulose after pretreatment with 3% H2O22 and 42 % after
pretreatment with 5% H2O2 at pH 11.5 [13].
METHODOLOGY
The experiment consists of two steps as shown in Figure 1. First, the raw material (biomass) was
pretreated by different methods to decompose the biomass. Second, the pretreated solid was converted to
fermentable sugars by enzymatic hydrolysis under preoptimized conditions.
Figure 1: Schematic diagram of experiment
Materials preparation
Sugarcane trash was milled (Retsh SM 2000) prior to use and sieved. Only particles of 0.45 mm – 1
mm in diameter were used in this study. This biomass was used as a starting material in each pretreatment.
The chemical compositions (percent of cellulose, hemicellulose, lignin, and ash) were analyzed by the
standard NREL (National Renewable Energy Laboratory, Golden, USA) method [14].
Pretreatments
The control variable of this experiment is the solid per liquid ratio and was performed at 10% w/v.
The dilute acid and alkaline pretreatments were performed in an autoclave (Tomy SX-700). Ten grams of
sugarcane trash sample were added with 100 mL of distilled water in a 250 mL Duran bottle. Sulfuric acid
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was added (0.25-1% (v/v)) as a catalyst for the dilute acid pretreatment and sodium hydroxide was added (2-
6% (w/w)) for the alkaline pretreatment. The reaction was heated to 120 for 30 min.
The alkaline hydrogen peroxide pretreatment was performed in a water bath (Grant JB nova). Ten
grams of sugarcane trash processed were added with 100 mL of distilled water in a 250 mL Duran bottle.
Hydrogen peroxide was added (1-4% (w/w)) as a catalyst, and the pH was adjusted by 5 M sodium
hydroxide to reach pH 11.5. The reaction was heated to 60 for 3 h.
After heating pretreatment, the Duran bottle was quenched in a water bath to cool. The solid and
liquid fractions were separated by filtration, and the solid fraction was thoroughly washed with tap water.
The sample was dried in an oven at 70 overnight before performing enzymatic hydrolysis.
Enzymatic Hydrolysis
The pretreatments depended on the digestibility of treated biomass using commercial enzyme
mixture (Cellic® CTec2). The enzymatic hydrolysis of 1 mL total volume contained 5% (w/v) pretreated
biomass with 20 filter paper units (20 FPU)/g Cellic® CTec2 in 50 mM sodium acetate buffer, at pH 5.0.
NaN3 was added to prevent microorganism growth. The reaction was performed in a shaking incubator (VS-
8480SFN) at 50 for 72 h with vertical mixing at 200 rpm. The liquid fraction was collected to quantify the
amount of glucan and calculate the yield of the pretreatment process. The efficiency of enzymatic hydrolysis
is shown in table 1 in the terms of hydrolysis yield (mg/g pretreated biomass), hydrolysis yield (mg/g native
biomass), and glucose recovery yield.
Analytical Procedures
The amounts of cellulose, hemicellulose, lignin, and ash that were obtained in a solid fraction from
pretreatments were analyzed by the standard NREL (National Renewable Energy Laboratory, Golden, USA)
method. Conversion yields of sugar were calculated as the percentage of glucose and pentose, based on the
percentage of cellulose (×1.11) and hemicellulose (×1.13), respectively [14].
A liquid fraction from the enzymatic hydrolysis was used in the analysis profile of sugar. High-
performance liquid chromatography was performed, using an Aminex HPX-87H column, operating at 65
with 5 mM H2SO4 as a mobile phase at a flow rate of 0.5 mL/min.
RESULTS AND DISCUSSIONS
Figure 2 shows the chemical composition of pretreated and untreated sugarcane trash with the
glucose recovery yield. The chemical composition of untreated sugarcane trash (control) contained cellulose
(34.49%±0.53), hemicellulose (29.72%±0.68), lignin (19.58%±0.25), and ash (6.44%±0.13). The untreated
sugarcane trash composition was in the same range, compared to previous studies [15]. The pretreatment
process led to an increase in the cellulose yield for the pretreated biomass compared to the raw material, as
shown in Figure 2. The more cellulose content, the higher the glucose recovery yield. For example, 4% w/w
H2O2 alkaline hydrogen peroxide showed the highest percent of cellulose (53.36%) and led to the highest
total sugar yield (763.56±15.16 mg/g pretreated) and a 92.66% glucose recovery yield, as shown in table 1.
For the dilute acid pretreatment (ACD) in Figure 2(a), the highest cellulose content is 50.22%±1.39,
which resulted in a glucose recovery yield of 58.64% with 1% v/v H2SO4 catalyst added. Furthermore, the
alkaline sodium hydroxide (ALK-NaOH) pretreated biomass (Figure 2(b)) obtained the highest cellulose
content (48.46%±0.44) and a glucose recovery yield of 81.77% with 6% w/w NaOH catalyst added.
The glucose release would be expected to be similar among these three pretreatment methods since
the amount of cellulose was 50.22%, 48.46%, and 53.36% for ACD, ALK-NaOH, and ALK-H2O2 pretreated
sugarcane trash, respectively. The greater amount of removal of lignin by ALK-NaOH and ALK-H2O2 than
ACD, which are more effective to the enzymatic hydrolysis of biomass, could be the reason for the larger
amount of glucose obtained [16].
Table 1 showed the sugar yield obtained from enzymatic hydrolysis with a commercial enzyme
mixture (Cellic® CTec2). The total sugar recovery was obtained in the order ALK-H2O2 > ALK-NaOH >
ACD for 272.05±16.03 - 763.56±15.16 mg/g pretreated biomass with a 48.85%- 92.66% glucose recovery
yield. The result showed that the more catalyst added, the higher the glucose recovery yield for all the
pretreatment methods.
9th International Conference on Environmental Engineering, Science and Management
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a)
b)
c)
Figure 2 Chemical composition of pretreated and untreated sugarcane trash, with glucose recovery
yield after enzymatic hydrolysis
a) Dilute acid pretreatment (ACD)
b) Alkaline sodium hydroxide pretreatment (ALK-NaOH)
c) Alkaline hydrogen peroxide pretreatment (ALK-H2O2)
9th International Conference on Environmental Engineering, Science and Management
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Pretreatment method Hydrolysis yield Hydrolysis yield Glucose
(mg/g pretreated (mg/g recovery
Control 0.25% v/v H2SO4
0.5% v/v H2SO4 biomass) native biomass) yield
Dilute acid (ACD) 1% v/v H2SO4 (%)
2% w/w NaOH 30.16±7.28 34.49±7.28 2.76
Alkaline sodium hydroxide 4% w/w NaOH 272.05±16.03 234.90±16.03 48.85
(Alk-NaOH) 6% w/w NaOH 315.06±14.14 223.66±14.14 54.48
357.01±8.18 240.50±8.18 58.64
Alkaline hydrogen peroxide 1% w/w H2O2 201.22±14.87 169.51±14.87
(Alk-H2O2) 2% w/w H2O2 418.59±17.95 322.13±17.95 36.89
4% w/w H2O2 588.32±17.62 400.77±17.62 64.00
351.33±12.52 273.73±12.52 81.77
432.90±12.76 283.80±12.76
763.56±15.16 450.82±15.16 45.34
66.18
92.66
Table 1 Sugar yields from enzymatic hydrolysis
CONCLUSION
Effective pretreatment processes were demonstrated for increasing the enzymatic digestibility of
sugarcane trash, and thus, the sugar yields obtained. The developed pretreatment process can be further
optimized and applied in the conversion of sugarcane trash to bioproducts in biorefineries.
ACKNOWLEDGEMENT
We are grateful for the valuable knowledge of Dr. Verawat Champreda. The authors thank BIOTEC
and NSTDA for knowledge, chemicals, and laboratory equipment and usage. P.C. thanks SIIT for
scholarship support.
REFERENCE
[1] Ghatak, Himadri Roy, 2011. Biorefineries from the perspective of sustainability: Feedstocks, products,
and processes. Renewable and Sustainable Energy Reviews, Elsevier. 15(8): 4042-4052.
[2] Pongpiachan, S., Hattayanone, M., & Cao, J., 2017. Effect of agricultural waste burning season on
PM2.5-bound polycyclic aromatic hydrocarbon (PAH) levels in Northern Thailand. Atmospheric
Pollution Research. 8(6): 1069-1080.
[3] Sarkar, N., Ghosh, S. K., Bannerjee, S., & Aikat, K., 2012. Bioethanol production from agricultural
wastes: An overview. Renewable Energy. 37(1): 19-27.
[4] Chiaramonti, D., Prussi, M., Ferrero, S., Oriani, L., Ottonello, P., Torre, P., & Cherchi, F., 2012.
Review of pretreatment processes for lignocellulosic ethanol production, and development of an
innovative method. Biomass and Bioenergy. 46: 25-35.
[5] Dussan, K., Virginio da Silva, D., Moraes, E., Arruda, P., & Felipe, M., 2014. Dilute-acid hydrolysis
of cellulose to glucose from sugarcane bagasse. Chemical Engineering Transactions. 38: 433.
[6] Boochapun, S., Lamamorphanth, W., & Kamwilaisak, K., 2014. The acid hydrolysis of sugarcane
leaves as a biofeedstock for bioethanol production. Advanced Materials Research. 931-932, 194-199.
[7] Soares, I., Mendes, K., Benachour, M., & Abreu, C., 2017. Evaluation of the operational parameters
effects in the pretreatment of sugarcane bagasse with diluted sulphuric acid by using analysis of
variance. Chemical Engineering Communications. 204: 1369-1390.
[8] Kallioinen, A., Hakola, M., Riekkola, T., Repo, T., Leskelä, M., Weymarn, N., & Siika-aho, M., 2013.
A novel alkaline oxidation pretreatment for spruce, birch and sugar cane bagasse. Bioresource
Technology. 140C: 414-420.
[9] Maryana, R., Ma’rifatun, D., Wheni, A. I., Wahono, S., & Rizal, W., 2014. Alkaline pretreatment on
sugarcane bagasse for bioethanol production. Energy Procedia. 47: 250–254.
[10] Carvalho, D., Queiroz, J., & Colodette, J., 2016. Assessment of alkaline pretreatment for the
production of bioethanol from eucalyptus, sugarcane bagasse and sugarcane straw. Industrial Crops
and Products. 94.
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[11] Azzam, A. M., 1989. Pretreatment of cane bagasse with alkaline hydrogen peroxide for enzymatic
hydrolysis of cellulose and ethanol fermentation. Journal of Environmental Science and Health. Part
B, 24(4): 421-433.
[12] Huang, S., Wei, W., Zhang, J., & Xie, J., 2019. Investigation of alkaline hydrogen peroxide
pretreatment and Tween 80 to enhance enzymatic hydrolysis of sugarcane bagasse. Biotechnology for
Biofuels. 12.
[13] Dodo, C. M., Mamphweli, S., & Okoh, O., 2019. Combining alkali and peroxide for pretreatment of
sugarcane wastes, bagasse and trash for bioethanol synthesis. South African Journal of Chemistry. 72:
154-159.
[14] Sluiter, A., Hames, B., Ruiz, R., Scarlata, C., Sluiter, J., Templeton, D., & Crocker, D., 2008.
Determination of Structural Carbohydrates and Lignin in Biomass—NREL/TP-510-42618. Laboratory
Analytical Procedure (LAP).
[15] Guilherme, A. de A., Dantas, P. V. F., Soares, J. C. J., Santos, E. S. dos, Fernandes, F. A. N., &
Macedo, G. R. de., 2017. Pretreatments and enzymatic hydrolysis of sugarcane bagasse aiming at the
enhancement of the yield of glucose and xylose. Brazilian Journal of Chemical Engineering. 34(4):
937-947.
[16] Yang, B. & Wyman, C.E., 2004. Effect of xylan and lignin removal by batch and flowthrough
pretreatment on the enzymatic digestibility of corn stover cellulose. Biotechnol. Bioeng. 86: 88-98.
9th International Conference on Environmental Engineering, Science and Management
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Impact of Bioeconomy Policy on the Monthly Water Scarcity
Footprints in the Northern Biohubs Region
Pitak Ngammuangtueng1* Pariyapat Nilsalab2 and Napat Jakrawatana3
1* Ph.D.’s Degree Program in Environmental Engineering; 3Assistant Professor, Department of Environmental
Engineering, Chiang Mai University, Chiang Mai 50200, Thailand
3Researcher, The Joint Graduate School of Energy and Environment, King Mongkut’s University of
Technology Thonburi, Bangkok, Thailand
*Phone : (+66)88-260-5600, E-mail : [email protected]
ABSTRACT
The bioeconomy has been one of the new growth engines of Thailand's economy. The related policy
expects to increase the bio-based industry and related agricultural supply-chain over the country, especially
in Northern and Northeastern Thailand. This research applied the Water scarcity footprint of area (WSFarea)
calculated from the monthly irrigation water footprints of sectors inside the sub-basins, and the monthly
Water Stress Index (WSI) of each watershed to investigate the water stress situation in these relate sub-
basins from the impact of land-use change scenario from the related policy and suggest a solution for
managing the water and economic tread-off challenges of these areas. The result of changing 32,000 ha of
the rice area in Lower Nan and 48,000 ha in Upper Chaopraya sub-basin to sugar cane cultivation and 32,000
ha of rice to cassava in Lower Yom sub-basin indicated that the monthly WSF on the biohubs could be
decreased clearly in the first half of the year(dry season). Planting cassava or the other lower-water
requirement crop (about 500 m3/rai-crop approximately) to replace secondary rice can reduce the water stress
mostly in March, April, and February at 70.1 %, 50.3%, and 32.5%, respectively. However, the stress
remains at the beginning of the wet season (June and July) since the sugarcane cultivation still requires an
amount of water much different at the starting of plantation compared to the rice. In conclusion, alternative
crops should not only considered under the economic or policy aspect but also the monthly water
consumption requirement to improve the better crop plantation management in each sub-basin area,
especially Upper Chaopraya and Lower Yom. Suitable low water crops, i.e., Maize, Watermelon, Cucumber,
etc. should be promoted in these areas together with the conventional economic crops.
Keywords: bioeconomy; land-use change; Water Stress Index (WSI); Water Scarcity Footprints (WSF);
INTRODUCTION
Since the strategy of bioeconomy policy has been established as one of the new growth engines of
Thailand's economy, the government and other private sectors have already provided a plan to increase the
bio-based industry and related agricultural supply-chain in several areas over the country[1]. The Northern
Biohub Region situated in Nakornsawan and Khampaengphet provinces is one of the regional focus on
bioeconomy area since they are the major area of sugarcane and cassava cultivation in the northern part of
Thailand, as shown in Fig.1. The land-use changing from a medium or low suitable rice plantation area to
sugarcane or cassava cultivation was expected to be expanded at least 32,000-80,000 ha for increasing the
fresh raw material input of the continuous sugar and starch industry about 1.5-3 million tonnes sugarcane and
starch per year in the biohubs province itself and the others in several sub-basins within the region[2]. Owing
to the high irrigation water requirement of major crop productions such as first and second rice, sugar cane,
and others have resulted in the different Water Stress Index(WSI) in each sub-basin depends on the water
sufficient of the area[3]. The WSI, which is the evaluation of water withdrawal and water availability in the
area, indicates the higher water scarcity in many basins, especially in the starting month of wet and dry
season crop plantation and becoming a critical challenge for a stakeholder to manage the future water
utilization. Moreover, the impact of climate change not only affects on the fluctuation of regional and local
precipitation and water supply in Thailand but also decreases the rice yield by 14% and 10% under RCP4.5
and 8.5 scenarios respectively [4] and require more water to cultivate in the future[5]. Thus, suitable
alternative crops should be carefully considered to deal with these issues. This research aims to investigate
the water stress situation in these related sub-basins from the impact of land-use change projection and
suggest a solution for managing the water and economic tread-off challenges of these areas.
9th International Conference on Environmental Engineering, Science and Management
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METHODOLOGY
The study focuses on the northern biohubs region,
including Lower Ping, Lower Yom, Lower Nan, and Upper
Chaopraya sub-basins. The current land use data were
evaluated from the 2015-2016 map from LDD [6]. The
projection land-use change area was derived from the
Thailand bioeconomy strategy 2018[1] to study the effect
of this policy on local water resource utilization, which
mainly located in Phitsanulok, Phichit, Khampaengphet,
and Nakonsawan provinces, as shown in Fig. 1. In this
research, the Water scarcity footprint of area (WSFarea) was
calculated from the monthly irrigation water footprints of
sectors (WF(Irr)sector) inside the sub-basins (gathered from
ONESDC(2017) report data [7] using Hoekstra et al.
(2011) method [8]) and the monthly Water Stress Index
(WSI) of each watershed (derived from Gheewala et al.
(2017)) [3] as described in equation 1
WSFarea, month = ∑WF(Irr)sector k, area j × WSImonth i (1)
The results would be exhibit in the monthly WSFarea
of each sub-basin. In order to study the WSFarea results of
land-use changes related to the bioeconomy policy, the
selected scenario is presented in the description table 1.
Fig.1 The study area of the research
Table 1 Scenario applied in the study
Scenario Description
Base case Current land use (2017)
R2Ca/Cs LU-Change from rice to sugar cane (32,000 ha in Lower Nan
and 48,000 ha in Upper Chaopraya sub-basin) and 32,000 ha
of rice to cassava in Lower Yom sub-basin
RESULTS AND DISCUSSIONS
In the base case, the WSF of the biohub sub-basin indicates the high volume in January, February, July,
and December, about 1,672-2,293 million m3-H2Oeq per month, as shown in Fig. 2. These characteristics are
the effect of the high irrigation water use of agriculture plantation in the dry season (December, January, and
February) and wet season crop initialization (July and August). These processes are done in the high WSI
month, especially in Upper Chaopraya, Lower Nan sub-basins, and Lower Yom and result in the rivalry of
water supply in many areas each year.
Fig. 2 Montly irrigation water use in all sector (left) and
only agriculture (right) in base case
9th International Conference on Environmental Engineering, Science and Management
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The result of applying the R2Ca/Cs scenario explicit that the monthly WSF on the biohubs can be
decreased in the first half of the year, which are the initial phase of the dry season cultivation and always
face with the water-scarce situation every year. Planting cassava or the other lower-water requirement crop
(require 500 m3/rai-crop approximately) to replace secondary rice can reduce the water stress mostly in
March, April, and February at 70.1 %, 50.3%, and 32.5%, respectively, as shown in Fig. 3. But in the
volumetric aspect, as shown in Fig. 4, the scenario results in the most WSF reduction in February, January,
and March at 565, 477, and 260 million m3-H2Oeq per month, respectively. However, the stress remains at the
beginning of the wet season (June and July) since the sugarcane cultivation still requires an amount of water
much different at the starting of plantation compared to the rice[3] while the area is facing with the rain-
delayed period and low storage volume. Moreover, in December, this area indices the most monthly WSF at
2,293 million m3-H2Oeq per month and a bit increasing thought the R2Ca/Cs scenario applied. These
situations are the reflection from the major rice still dominant over the area (about 590,000 or 76% of the
total study area), and the rainy period has already done this month.
Fig. 3 The increment of WSFarea change of R2Ca/Cs scenario in the biohubs
compare to the base case
Fig. 4 WSFmonthly result in the base case and scenario
In the sub-basin aspect, the result of applying an alternative crop plantation scenario states
the characteristics of each area. LU-Change from rice to sugar cane (32,000 ha in Lower Nan and
48,000 ha in Upper Chaopraya sub-basin) and 32,000 ha of rice to cassava in Lower Yom sub-basin
explicitly effect the different on the reduction of WSF intensity (WSF per area of cultivation:
WSFi), as shown in Fig. 5. Although the LU-change of Upper Chaopraya has a more significant
applying area than Lower Nan (32,000 and 48,000 ha), the WSFi reduction of the agriculture area in
Upper Chaopraya has lower than Upper Nan (11.3% and 49.2% respectively). This result is because
of the agriculture practice in Chaopraya mainly being cultivated in the irrigation project area, which
requires more irrigation water than Lower Nan sub-basin, and the sugar cane plantation is not much
lower water consumption than rice. While the changing 32,000 ha of rice to cassava in Lower Yom sub-
9th International Conference on Environmental Engineering, Science and Management
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basin shown the better result in WSFi reduction at 30.2% since the cassava cultivation requires lower
water consumption than sugar cane(520 and 1,100 m3/rai respectively)[9][3]. This result indicates
that alternative crops not only considered under the economic or policy aspect but also the water
consumption monthly requirement to improve the better crop plantation management in each sub-
basin area, especially Upper Chaopraya and Lower Yom. Suitable low water crops, i.e., Maize,
Watermelon, Cucumber, etc.[10] should be promoted in these areas.
Fig. 5 The reduction of WSF intensity of R2Ca/Cs scenario in the biohubs
comparing to the base case(left), and the percentage change(right)
CONCLUSION
The Water Scarcity Footprints of the area in monthly timestep can describe more detail of the land-
use change impact on the water resource in the local basin scale. The results state that, although the
bioeconomy and its related policy is the proper solution to support socio-economic development. However,
not only the crop change promoting and industrial-factory investment, the balancing of monthly water
utilization issues, especially in the high-stress area including the Lower Nan and Upper Chaopraya sub-
basins, should be inspected together with the low water requirement alternative crop consideration in order to
manage both economic and environmental challenges on the area over a year.
ACKNOWLEDGEMENT
This research has financial support from the TA/RA scholarship by the Graduate School, Chiang
Mai University.
REFERENCE
[1] Tanticharoen, M. Bioeconomy in the Context of Thailand. In Proceedings of the Global Bioeconomic
Summit(GBS); Berlin, 2018.
[2] Prachachat KTIS Focusing on Nakornsawan biohub investment Available online:
https://www.prachachat.net/local-economy/news-183435.
[3] Gheewala, S.; Silalertruksa, T.; Nilsalab, P.; Lecksiwilai, N.; Sawaengsak, W.; Mungkung, R.; Ganasut, J. Water
stress index and its implication for agricultural land-use policy in Thailand. Int. J. Environ. Sci. Technol. 2017, 15.
[4] Boonwichai, S.; Shrestha, S.; Babel, M.S.; Weesakul, S.; Datta, A. Climate change impacts on irrigation water
requirement, crop water productivity and rice yield in the Songkhram River Basin, Thailand. J. Clean. Prod. 2018,
198, 1157–1164.
[5] Shrestha, S.; Chapagain, R.; Babel, M.S. Quantifying the impact of climate change on crop yield and water
footprint of rice in the Nam Oon Irrigation Project, Thailand. Sci. Total Environ. 2017, 599–600, 689–699.
[6] LDD Land Use Map Updated 2015-2016; 2016;
[7] ONESDC A study of water balance management practices in the Chao Phraya River Basin (Ping, Wang Yom,
Nan, Pasak, Chao Phraya, Tha Chin, and Mae Klong); Bangkok, 2017;
[8] Hoekstra, A.; Chapagain, A.; Aldaya, M.; Mekonnen, M. The Water Footprint Assessment Manual; 2011;
[9] Pingmuanglek, P.; Jakrawatana, N.; Gheewala, S. Freshwater use analysis of cassava for food feed fuel in the Mun
River basin, Thailand. Int. J. Life Cycle Assess. 2017, 22.
[10] DOAE Low water requirement crop for farmer project; Ministry of Agriculture: Bangkok, 2019;
9th International Conference on Environmental Engineering, Science and Management
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Abundance and Distribution of Suspended Microplastics in
the Surface Water of Chao Phraya River Estuary
Phyo Zaw Oo1 Suwanna Kitpati Boontanon2* Narin Boontanon3 Shuhei Tanaka4 and Shigeo Fujii5
1Graduate Student, Department of Civil and Environmental Engineering, Faculty of Engineering, Mahidol
University, Thailand; 2*Associate Professor, Department of Civil and Environmental Engineering, Faculty of
Engineering, Mahidol University, Thailand; 3Lecturer, Faculty of Environmental and Resource Studies, Mahidol
University, Thailand; 2, 4Associate Professor and 5Professor, Graduate School of Global Environmental Studies,
Kyoto University, Yoshida, Sakyo-Ku, Kyoto, 606-8501, Japan.
*Phone : 66-2-8892138 ext. 6390, Fax : +66-2-8892138 ext. 6388, E-mail : [email protected]
ABSTRACT
This study investigated the abundance and distribution of microplastics in the surface water of Chao Phraya
River Estuary and estimated the possible emission sources. Three surface water samples were collected by
Menta trawl and then sample pretreatment steps were performed, and analyzed using Fourier Transformed
Infrared Spectroscopy (FTIR). The results indicated the prevalence of microplastics with the mean
concentration of 2.3 105 particles/km2 in the Chao Phraya river estuary, representing high microplastics
pollution. The collected microplastics were categorized into different size ranges, shapes, colors and
chemical structures. The smallest size range (335 to 515 microns) was the most abundant size approximately
70% of total collected microplastics. The abundance of larger size ranges of MPs significantly decreased
with distance far from land but the smallest size range remained nearly the same quantity. The dominant
shapes of MPs were film and fragment with white and transparent colors indicated that these were derived
from the fragmentation of mismanaged plastic waste from the land as the secondary MPs. The result of this
study provides the overview of microplastics pollution in the study area to the government and
environmental organizations to enforce to reduce the plastics usage and to improve the solid waste
management to prevent the plastic debris entering into the estuary.
Keywords : microplastics; plastic-debris; Menta Net; FTIR; river transport; Chao Phraya Estuary
INTRODUCTION
Microplastics (MPs) in the water bodies are considered as anthropogenic emerging pollutant and one of the
pressing issues to the global environment nowadays. MPs in the aquatic environment are reported as
hazardous waste because hydrophobic toxic pollutants in the water could be adsorbed and concentrated on
the MPs while they transverse through the environment. In the aquatic environment, plastics provide
substratum for adsorption of various contaminants including persistent organic pollutants (POPs), metals
(e.g., Cu, Pb) and pathogenic species [1]. When a small piece of plastic waste in water bodies degrades, it
could produce small sizes, varied shapes, and particular colours of MPs that could be ingested by a variety of
organisms. Meanwhile, aquatic organisms at the lower level of food chain ingest MPs, these contaminants
threaten to ingesting organisms and the connected food chain [2]. MPs in the estuary are described as one of
the sources of plastic debris entering into the sea [3]. Most studies about MPs are in the rivers and the marine
environment so the information about the estuarine environment is very limited globally.
Studies of MPs conducted in Thailand have investigated in rivers, sediments, and biota in the respective area
but abundance of MPs within the estuaries are sparsely investigated [4][5]. Furthermore, estuaries are
identified as MPs hotspots because of the discharge of mismanaged plastic waste transported by the river
discharge. Chao Phraya River flows through the most heavily populated regions of Thailand, as a result,
large quantity of domestic and industrial wastes is discharged to the Gulf of Thailand by the river.
Unfortunately, there is no extensive information on the abundance of MPs in the Chao Phraya River Estuary.
Therefore, the objectives of this study are 1) to investigate the abundance, composition, and distribution of
MPs in the Chao Phraya River Estuary, and 2) to characterize the chemical structure of MPs and identify
possible emission sources. Results from this study may contribute to support the current status of
microplastics pollution in the study area for decision makers and environmental organizations to draw public
awareness of wastewater and the solid waste management system.
9th International Conference on Environmental Engineering, Science and Management
The Heritage Chiang Rai, Thailand, May 27-29, 2020
- 184 -
METHODOLOGY
Study area
Chao Phraya River is the largest river in Thailand and flows south through Bangkok and several other large
cities, the drainage area is about 177,000 km2 [6]. As a result, its basin is one of the most heavily populated
regions of Thailand, where agricultural and industrial activities are developed and as a consequence, large
amounts of domestic and industrial wastes are carried by the river to the Gulf of Thailand. The mean river
discharge is 430 m3/s and the high flows can reach about 3,000 m3/s during large flood conditions. The mean
depth of the estuary is very shallow with an average depth of 15 meters (minimum 8 m to maximum 24 m)
[7]. The Chao Phraya River Estuary is relatively close to Bangkok and heavily affected by a variety of
anthropogenic activities along its length. The surface water samples of Chao Phraya River Estuary were
collected from three stations of the study area in August, 2019 (Figure 1). The sample collection route was
selected in the navigation channel to obtain the representative discharge flow of river in the estuary. The
coordinates of the sampling stations and distance from the nearest land are listed in Table 1.
Table 1 GPS coordinates of sample collection stations
Sampling Start Point End Point Distance from
Station Latitude Longitude Latitude Longitude the nearest land (km)
ST1 13.51844 100.62574 13.50322 100.63770 0.6
ST2 13.50343 100.63795 13.48013 100.64839 1.7
ST3 13.47972 100.64915 13.45519 100.66157 4.0
Figure 1 Locations of sample collection stations in Chao Phraya River Estuary
Sample collection and preparation
The sample collections were conducted on the same day at high tide period to obtain the same metrological
condition. Menta net with 335 microns mesh size, 30 15 cm rectangular metal mouth opening and the
depth from the centre of side wing to the bottom of the mouth opening is 10 cm (Hydro-Bios, Germany) was
attached to the boat, “Samut Prakan 220” and trawled about 25 to 30 minutes. The distance between the boat
and the net was maintained about 1.4 m to reduce the disturbance of the bow wave (Figure 2). The speed of
the boat was maintained approximately 3 knots when sampling. The trawl distance was recorded from the
mechanical flow meter with pitch 0.3 m/rev (Hydro-Bios, Germany) installed in the lower frame of the
mouth opening. The GPS positions of the start and end point of the sampling were recorded. The collected
9th International Conference on Environmental Engineering, Science and Management
The Heritage Chiang Rai, Thailand, May 27-29, 2020
- 185 -
debris in the net were rinsed with the tap water (filtrated with 100 microns filter sheet) and transferred to the
1 L glass jar (Figure 3). The glass jars were kept in the cooler box and brought back to the Water Quality
Engineering Lab (Mahidol University).
Figure 2 Sampling with Menta net in the study area
Large debris and aquatic organisms from the collected sample were separated and discarded by 5 mm
stainless-steel sieve in the laboratory. The organic matter in the samples were digested with 30% hydrogen
peroxide for 24 hours at room temperature. Density separation with 5 M NaCl solution (density 1.2 g/cm-3)
was performed to separate the remaining particles. The floated particles were collected and separated to four
different size ranges (335 to 515 microns, 516 to 990 microns, 991 to 2100 microns and 2101 to 5000
microns) with the stainless-steel sieves. The separated particles from four size ranges were transferred to
glass petri dishes and dried at 40C in the oven and then weighted with precision balance (5 decimal places,
0.00001 g).
Sample from ST1 Sample from ST2 Sample from ST3
Figure 3 Samples collected from the study area
Sample analysis
The collected particles were quantified and identified by the Stereomicroscope and Motic Plus3 program to
classify physical features such as size, shape, and color. The particles from two large size ranges were
analyzed all but for two small size ranges were picked quarter from the glass petri dish, approximate 25% by
total weight to analyze. To identify the chemical composition of polymer, Fourier Transformed Infrared
Spectroscopy (Thermo Fisher, USA) was used in Attenuated Total Reflectance (ATR) mode to collect the
spectra of the collected MPs. FTIR was operated in the single reflection mode and analyzed 32 scans per
9th International Conference on Environmental Engineering, Science and Management
The Heritage Chiang Rai, Thailand, May 27-29, 2020
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