Ofei D. Mante* and FA Agblevor Biological Engineering, Utah State University, Logan UT; *RTI International, Research Triangle, NC

Transcription

1 Physicochemical properties of biomass catalytic pyrolysis oils: A 13 C NMR spectroscopic investigation of the effects of functional groups on oil properties. Ofei D. Mante* and FA Agblevor Biological Engineering, Utah State University, Logan UT; *RTI International, Research Triangle, NC

2 Introduction The production of infrastructure-ready biocrude oil from catalytic pyrolysis offers an opportunity to co-process biomass derived intermediates alongside petroleum feedstock. One of the critical success factors for commercial scale biocrude coprocessing is the physicochemical properties of the upgraded bio-oil. Fuel properties such as specific gravity, viscosity, acidity, storage stability, carbon residue, and etc., are of interest to a Refiner. The bulk oxygen content of the biocrude do not reflect the fuel properties and may not per se be the yardstick in determining the suitability of upgraded pyrolysis as a supplemental feedstock in a conventional petroleum refinery. The chemical components responsible for the physical properties of biocrude is still not well understood.

3 Objectives Develop advanced characterization methods to understand the effect of functional groups on the physicochemical properties of catalytic pyrolysis oils(cpo). Develop catalysts that can completely eliminate the functional groups that have adverse effect on the fuel property of CPOs.

4 Materials and Methods Materials Corn stover, switchgrass, pinyon juniper, poplar, pine wood and pine bark Catalysts: HZSM-5 (Clariant Inc) Methods Pilot scale bubbling fluidized bed catalytic pyrolysis reactor Reactor capacity: 2 kg/h

5 Pyrolysis System Temperature = 475 o C, Fluidizing gas flow rate = (N 2 = 0.4 SCFM, NCG=2.0 SCFM) Biomass feed rate = 1kg/h, Catalyst loading = 1 kg, Run time = 3 h

6 Product Analysis Gas chromatography H 2, CH 4, CO, CO 2 and C 2 -C 5 hydrocarbons. (Varian 490 micro GC) Elemental analysis C, H, N, S and O (ThermoFisher Scientific organic elemental analyzer) Physical properties: Acidity, Viscosity, Density, Storage Stability, TGA residue, HHV, and Moisture 13 C-NMR Solvent = dimethyl sulfoxide-d 6, Number of scans = 3000, Temperature = 35 o C. (Varian 400 MHz, JOEL 300 MHz Spectrometer)

7 Results: Elemental and ash analysis of the various biomass feedstocks Elemental Composition (wt.%) d.b Poplar Pine Pinyon- Juniper Biomass Feedstock Switchgrass Corn Stover Pine Bark C H N O* Ash ([d.b]-dry basis, *by difference)

8 Results: Product Yields (wt% on biomass) from the pilot-scale catalytic pyrolysis with ZSM-5 zeolite Pyrolysis Product Total liquid product WESP Fraction Condenser Fraction Char/coke Gases (by difference) Yields (wt %) Hybrid Pinyon- Corn Pine Pine Switchgrass Poplar Juniper Stover bark 41.1± ± ± ± ± 34.8± 8.4± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

9 Results: Physical properties of CPOs Physical properties Pine Hybrid poplar Corn Stover Switchgrass Pinyon juniper Pine Bark ph Density (g/cm 3 ) Estimated gravity, o API Kinematic Viscosity (at 40 o C, cst) Dynamic Viscosity (at 40 o C, cp) Long term storage Stability (Viscosity after 18 months of storage, at 40 o C, cst) Average rate of viscosity change, (cst/day) TGA residue at 550 o C, wt.%

10 Results : 13 C-NMR Analysis Aromatic C-C DMSO-d 6 solvent Aromatic C-O Aromatic C-H Aliphatic hydrocarbons COOH, COOR, CONR 2 COR & COH C-OH, C-OR O-CH 3 13 C-NMR spectrum of biocrude oil produced from pinyon juniper

11 Results : 13 C-NMR of CPOs (percentage total carbon) Type of carbon Chemical Biocrude oils Shift, δ (ppm) Pine Poplar Corn Stover Switchgrass Pinyon Juniper Pine Bark Aliphatic C-C Methoxy C (-OCH 3 ) Aliphatic C-O (including levoglucosan) Aromatic C-H Aromatic C-C (carbons in aromatic hydrocarbons further from an O atom) Aromatic C-O Carbonyl (carboxylic acids and derivatives) Carbonyl (aldehydes, ketones)

12 Effect of Aromatic Hydrocarbon and Phenolics on Viscosity Aromatic hydrocarbons decreases viscosity Phenolic compounds appear to increase viscosity

13 Effect of Sugars and Hydrocarbons on Density Anhydrosugars increases the density Hydrocarbons decreases the density

14 Effect of Carbonyls and Hydrocarbons on Storage Instability Carbonyl species appear to increase instability Aromatic hydrocarbons appear to decrease instability

15 Effect of Elemental Composition on Carbon Residue and Acidity High carbon content results in less formation of residue Relatively high nitrogen contents reduces the acidity

16 Summary Property Total C-C carbons Phenolic Carbons Carbons types determined by 13 CNMR Levogluco Phenolic/ Carbons levogluco Carbonyls Oxyge nates Aroma C-C Aroma C-O Elemental ph Density (g/cm 3 ) Gravity, o API Kinematic Viscosity (at 40 oc, cst) Storage Stability- Rate of change in viscosity (cst/day) TGA residue at 550 o C, wt.% Pearson Correlation Coefficients (Values in bold are different from 0 with a significance level alpha=0.05) C N

17 Conclusions Catalytic pyrolysis with product gas recycle was conducted on six different biomass feedstocks using HZSM-5 catalyst in a 2 kg/h fluidized bed reactor. Partially deoxygenated biocrudes oils with improved fuel properties was achieved with zeolite based-catalysts. 13 C-NMR analysis revealed that the physicochemical property of the biocrudes is dependent on functional groups present. The aromatic carbon content of the the biocrude oils showed negative linear correlation with the viscosity of the oils. Phenolic carbons had a positive linear relationship with viscosity. Anhydrosugars and phenolics had a positive linear correlation with density, but the aromatic carbons decreases the density. Carbonyl species appear to have a positive linear effect on the storage stability of the oils; thus increases the rate of viscosity change. Bio-crude carbon content had a negative linear correlation with the formation of residue. Nitrogen content also showed a positive linear correlation with the ph of the oils and so could have a positive influence on corrosion of the oils.

18 Acknowledgements The authors acknowledge DOE BETO Program and the USTAR Program for financial support.

19 Thank you!! Questions?