CONTROL OF A III-PHASE OLIVE POMACE COMPOSTING PROCESS USING THE CIELab COLORIMETRIC METHOD D. Tsivas, A. Vlysidis, G.K. Lamprou, K. Tzathas, A.G. Vlyssides Organic Chemical T echnology Laboratory School of Chemical Engineering National T echnical University of Athens 7 th International Conference on Sustainable Solid Waste Management, Heraklion 26-29 June 2019
Development of an integrated OMW biorefjnery On going research of the Laboratory of Organic Chemical Technology, NTUA Process Diagram of the on-going research performed in the lab • Implementation of holistic schemes for valorizing OMW under the concept of integrated biorefjneries • Extraction of high added-value compounds • Residual oil and phenolic compounds • Production of bioenergy and/or biochemical • Production of compost 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
The scope of the study Objective • Monitoring the composting process with a new colorimetric method • Eliminate the need for complex maturity analyses during composting Methodology • Composting of three-phase olive pomace in an industrial scale facility • Monitoring the most important physicochemical properties of the compost pile • Measurement of the color variables using the CIELab color model • Correlation between physicochemical parameters and color variables • Compost maturity graphs using the CIELab color variables 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Flow diagram of a III-phase olive mill facility 21.4 t olive oil 100 t olives 49.6 t solid residue (olive pomace and Olive mill leaves) ΙΙΙ-Phase 134.4 t water 22.4 t of dry matter 163.4 t olive mill wastewater Olive oil extraction: one of the most traditional agricultural industry in the Mediterranean Region Large amounts of two main by-products: solid residue and olive mill wastewater • Harmful to the environment A non-complex integrated utilization strategy is the co- composting of the two waste streams 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Composting Equation: Oxygen Carbon Organic Compos Water Water consumed dioxide t prod. matter evap. prod. Biological decomposition of organic matter: Heterogeneous-heterotrophic microorganisms Controlled aerobic conditions Exothermic procedure Organic waste management: Agricultural by-products Food industry waste Municipal solid waste The fjnal product is Compost Compost Maturity Measurement of at least 2 • Degree of completeness of composting parameters (maturity indexes) • Stability of the fjnal product 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Colorimetry Numeric calculation of color using color models and spectrophotometers CIELab color model 3D color space L ( lightness) from (0) dark to (100) light a from (-) green to (+) red b from (-) blue to (+) yellow Spectrophotometer: • Portable device simulating the human eye • Circular geometry of d/8 0 • Stable measuring conditions • Rapid, inexpensive measurement 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Composting process • Raw materials : III-phase olive mill solid residue (olive pomace, olive leaves) • Open composting system : dynamic aeration - windrows • Aeration: turning of the compost pile using a tractor • Industrial scale: 34.5 t (fjrst day of composting) • Sample collection: zigzag method • Composting duration: 80 days Measurement: • pH, TKN, TOC, color 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Results Physicochemical parameters of composting 2,5 7 2,0 6 T K N (% ) 1,5 pH 5 1,0 4 3 0,5 0 20 40 60 80 0 20 40 60 80 Time (Days) Time (Days) 8 55 54 6 T O C (% ) 53 A sh (% ) 4 52 2 51 50 0 0 20 40 60 80 0 20 40 60 80 Time (Days) Time (Days) Physicochemical parameters Maturity indexes 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
CIELab color variables 1 st Day Immature Mature 30 th day • Decreasing trend of a, b variables during the whole 50 th day period of composting • Evaluation of maturity using a, b variables 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Color variables that derive from the CIELab model 0,50 78 76 0,45 74 0,40 Hue (0) 72 0,35 a/b 70 b 0,30 − � � 1 68 h tan a >0, b � 0 = � � a � � 0,25 66 0,20 64 2 2 C a b ( ) ( ) = + 0 10 20 30 40 50 60 70 80 170180 0 10 20 30 40 50 60 70 80 170180 Time (Days) Time (Days) 28 24 2 2 2 L a b ( ) ( ) ( ) ∆Ε = ∆ + ∆ + ∆ 24 20 20 16 16 12 DE C 12 8 8 4 4 0 0 10 20 30 40 50 60 70 80 170180 0 10 20 30 40 50 60 70 80 170180 Time (Days) Time (Days) • a/b and h Increasing and decreasing trend respectively after the 15 th day of composting • C and ΔΕ Decreasing and increasing trend respectively during the whole composting period 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Linear correlation between CIELab color variables and physicochemical parameters – R 2 • Investigation of linear correlation between compost maturity indices and the CIELab color variables Total Organic Carbon (ΤΟC%) Total Kjeldahl Nitrogen (ΤΚN%) 21 7 y = -14,695x + 779,8 R² = 0,9946 y = -9,8686x + 24,108 14 R² = 0,9603 6 DE 5 a 7 4 0 3 51,5 52,0 52,5 53,0 1,8 1,9 2,0 2,1 TOC (%) TKN (%) 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Linear correlation between CIELab color variables and physicochemical parameters – R 2 pH Carbon to Nitrogen ratio (C/N) 30 7 y = -9,9253x + 78,457 6 R² = 0,8691 20 5 C a y = 0,9311x - 21,081 4 R² = 0,9545 10 3 5,0 5,5 6,0 6,5 7,0 25 26 27 28 29 30 pH C/N Very strong linear correlation between a, b, C, ΔΕ and TOC%, TKN%, C/N (R 2 >0.93) Strong linear correlation between a, b, C, ΔΕ and pH (R 2 >0.85) Strong linear correlation between a/b, h and ΤΟC% during t=15-80 days (R 2 >0.81) 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Conclusions Determination of the stage/maturity of composting • Constant change trend of color variables a, b, C, DΕ during composting • Constant change trend of color variables a/b, h after the 15 th day • Strong linear correlation between color and maturity indexes Determination of each individual physicochemical parameter of composting • Very strong linear correlation between parameters ΤΟC%, ΤΚN%, pH, C/N with color variables a, b, C, DΕ • Strong linear correlation between TOC% and color variables a/b, h after the 15 th day Rapid and inexpensive compost maturity analysis 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Suggestions for future research Complete composting study to locate the point of maturity Additional physicochemical parameters evaluation • Phytotoxicity, humic and fulvic acids, SOUR T est, Dewar T est etc. Multiple composting tests to determine the confjdence levels of the color model Difgerent substrate study • Anaerobic digestate, municipal solid waste, manure, etc . 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
Acknowledgements Organohumiki Thrakis, Alexandroupolis, Greece Thank you for your attention 7 th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019
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