CONTROL OF A III-PHASE OLIVE POMACE COMPOSTING PROCESS USING THE - - PowerPoint PPT Presentation

7th International Conference on Sustainable Solid Waste Management, Heraklion 26-29 June 2019

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

7th International Conference οn 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

• n-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

7th 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

7th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019

Flow diagram of a III-phase olive mill facility

Olive mill ΙΙΙ-Phase 134.4 t water 100 t olives 163.4 t olive mill wastewater 21.4 t olive oil 49.6 t solid residue (olive pomace and leaves) 22.4 t of dry matter

 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

7th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019

Composting

Equation: 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

• Degree of completeness of composting
• Stability of the fjnal product

Measurement of at least 2 parameters (maturity indexes)

Organic matter Oxygen consumed

Compos t Water evap. Water prod. Carbon dioxide prod.

7th 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/80
• Stable measuring conditions
• Rapid, inexpensive measurement

7th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019

Composting process

• Raw materials : III-phase olive mill solid residue (olive pomace,
• live 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

7th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019

Results

Physicochemical parameters of composting

• Physicochemical parameters Maturity indexes

20 40 60 80 3 4 5 6 7 20 40 60 80 0,5 1,0 1,5 2,0 2,5 20 40 60 80 2 4 6 8 20 40 60 80 50 51 52 53 54 55 pH Time (Days) T K N (% ) Time (Days) A sh (% ) Time (Days) T O C (% ) Time (Days)

7th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019

CIELab color variables

• Decreasing trend of a, b variables during the whole

period of composting

• Evaluation of maturity using a, b variables

1st Day 30th day 50th day

Mature Immature

7th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019

Color variables that derive from the CIELab model

• a/b and h  Increasing and decreasing trend respectively after the 15th day of composting
• C and ΔΕ  Decreasing and increasing trend respectively during the whole composting period

10 20 30 40 50 60 70 80 170180 0,20 0,25 0,30 0,35 0,40 0,45 0,50 10 20 30 40 50 60 70 80 170180 64 66 68 70 72 74 76 78 10 20 30 40 50 60 70 80 170180 4 8 12 16 20 24 28 10 20 30 40 50 60 70 80 170180 4 8 12 16 20 24 a/b Time (Days) Hue (0) Time (Days) C Time (Days) DE Time (Days)

1

tan a >0, b b h a

−

=

• (

) ( )

2 2

C a b = +

( ) ( ) ( )

2 2 2

L a b ∆Ε = ∆ + ∆ + ∆

7th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019

Linear correlation between CIELab color variables and physicochemical parameters – R2

Total Organic Carbon (ΤΟC%) Total Kjeldahl Nitrogen (ΤΚN%)

• Investigation of linear correlation between compost

maturity indices and the CIELab color variables

1,8 1,9 2,0 2,1 3 4 5 6 7 a TKN (%) y =

• 9,8686x +

24,108 R² = 0,9603 51,5 52,0 52,5 53,0 7 14 21 y =

• 14,695x +

779,8 R² = 0,9946 DE TOC (%)

7th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019

Linear correlation between CIELab color variables and physicochemical parameters – R2

pH Carbon to Nitrogen ratio (C/N)

Very strong linear correlation between a, b, C, ΔΕ and TOC%, TKN%, C/N (R2>0.93) Strong linear correlation between a, b, C, ΔΕ and pH (R2>0.85) Strong linear correlation between a/b, h and ΤΟC% during t=15-80 days (R2>0.81)

25 26 27 28 29 30 3 4 5 6 7

y = 0,9311x - 21,081 R² = 0,9545

a C/N 5,0 5,5 6,0 6,5 7,0 10 20 30

y =

• 9,9253x +

78,457 R² = 0,8691

C pH

7th 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 15th 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

15th day

• Rapid and inexpensive compost maturity analysis

7th 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.

7th International Conference οn Sustainable Solid Waste Management Heraklion 26-29 June 2019

Acknowledgements

 Organohumiki Thrakis, Alexandroupolis, Greece

Thank you for your attention