DIVERSIFIED AGRO-WASTE IN CHINAwheat straw using FTIR microspectroscopic imaging Total stress Total...
Transcript of DIVERSIFIED AGRO-WASTE IN CHINAwheat straw using FTIR microspectroscopic imaging Total stress Total...
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DIVERSIFIED AGRO-WASTE IN CHINA
—Multiple approaches for better understanding and efficient utilization
Lujia Han, PhDDean and Professor of the College of EngineeringChina Agricultural University (CAU)Email: [email protected]
Agricultural waste and residue management
for a circular bio-economy:
Shared China and EU impact-oriented solutions
22nd - 23th October, 2018, Beijing
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Outline
◆ Background
◆ Research Cases
◆ Summary
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1 Background
⚫ Annual output in China
➢Animal manure: 3.8 billion tons
➢Crop residues: 900 million tons
⚫ Nutrients applied do not end up in edible food:
➢50% of agro-inputs goes to non-edible parts of crops
➢30-50% of applied fertilizer is absorbed by crops
⚫ The waste of AgroWaste is a waste of agricultural inputs!
⚫ Environmental and sustainable concerns……
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⚫ Utilization of AgroWaste in China
➢Animal manure: <60% comprehensive utilization rate
➢Crop residues: 200 million tons are not utilized
⚫ Opportunities for innovative technologies to address the efficient utilisation
1 Background
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2 Research Cases
➢ AgroWaste Feedstock
—Property Characterization
—Non-destructive Analysis by NIR/IR/NIRM
➢Modeling for Mechanism Elucidation
—Acid pretreatment of Crop Residues
—Mechanical Fragmentation Pretreatment of Crop Residues
—GHG Emission during Manure Composting
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2.1 AgroWaste Feedstock Characterization
Research on agro-biomass properties
Research on analysis methods of agro-biomass properties
Research and development of agro-biomass properties database
Research on
rapid analysis
techniques for
agro-biomass
properties
Chemical
composition
Proximate and
ultimate analysis
Thermal
properties
Mechanical
properties
Physical
properties
Construction of web-based database
Database of chemical composition
Database of physical properties
Database of proximate and ultimate
analysis
Database of thermal properties
Database of mechanical properties
Correlation analysis among agro-biomass properties
Representative
straw samples
Representative
manure samples
• W Niu, L Han*, X Liu, G Huang, L Chen. Energy, 2016• X Shen, G Huang, Z Yang, L Han*. Applied Energy, 2015• C Cao, Z Yang*, L Han. Cellulose, 2015• W Niu, G Huang, X Liu, L Chen, L Han*. Energy & Fuels, 2014
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Cellulose Hemicellulose Lignin
Soluble Sugar Neutral Detergent Fiber (NDF) Acid Detergent (ADF)
Chemical composition of crop residue
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Proximate analysis of animal manure
Ash Fixed Carbon
Moisture Volatile Matter
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Ultimate analysis and High Heat Value (HHV) of crop residue
C H N
S O HHV
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Mineral elements composition of animal manure
Cu Zn
Na Mg Fe
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Mechanical properties of crop residues
Tensile Compression Bending Shear
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Pyrolysis characteristics
Beef Manure Dairy Manure Broiler Manure Layer Manure Swine Manure
Wheat Straw Corn Stalk Rice Straw Rape Straw Cotton Stalk
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2.2 NIR/IR/NIRM Techniques for AgroWaste Analysis
• J Xue, Z Yang*, L Han. Applied Energy, 2015• X Jiang, Z Yang, L Han*. Analytical and Bioanalytical Chemistry, 2014• C Lü, L Chen, Z Yang, X Liu, L Han*. Applied Spectroscopy, 2013• X Zhou, Z Yang, G Huang, L Han*. Journal of Near Infrared Spectroscopy, 2012
2
NIRM/IRM NIR/IR
4000 3500 3000 2500 1500 1000 500
0.0
0.2
0.4
0.6
0.8
1.0
Ab
so
rba
nce
Wavenumber/cm-1
CJR02
JG01
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NIRS for rapid detecting manure composition
C N Calorific Value
Organic Matter Volatile Solid Ash
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10
11
12
13
14
15
16
17
18
0 1 2 3 4 5 6 7 8 9 10 11 12
C/N
SECTION
Y Measured (ST)
10
11
12
13
14
15
16
17
18
0 1 2 3 4 5 6 7 8 9
C/N
SECTION
Y Measured (LT-1)
Y Measured (LT-2)
Y NIR (LT-1)
Y NIR (LT-2)
15
20
25
30
35
40
45
50
55
60
0 1 2 3 4 5 6 7 8 9 10 11 12
MO
IST
/%
SECTION
Y Measured (ST) Y NIR (ST)
15
20
25
30
35
40
45
50
55
60
0 1 2 3 4 5 6 7 8 9
MO
IST
/%
SECTION
Y Measured (LT-1) Y Measured (LT-2)
Y NIR (LT-1) Y NIR (LT-2)
Handheld NIRS sensors for real time and field monitoring composting process
C/N
Calibration models Monitoring composting process in small and big trough
Moisture
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Schematic diagram for on-line system
全息凹面光栅取消反射镜,提高稳定性
无摩擦空气轴承取代机械轴承
光电编码器取代机械编码
行星轮精密电机
光纤型狭缝精简结构,简化调光
二级制冷控温InGaAs传感器
光阑
整体成型结构铟钢材料,温漂<0.007nm每度
Spectrometer Detection probe
J Xue, Z Yang*, L Han, Y Liu, Y Liu, C Zhou. Applied Energy, 2015, 137: 18–25
On-line analytical technology based on NIRS in lab
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Pipe
Sensor
Sample Window
NIRS
On-line NIRS analysis in feed factory
No. Time CP/% MC/% CF/% Ash/%
1 2017/4/18 10:45:24 46.82 12.25 6.32 5.89
2 2017/4/18 10:46:01 46.82 12.14 6.53 5.80
3 2017/4/18 10:46:38 46.81 12.16 6.64 5.81
4 2017/4/18 10:47:15 46.74 12.03 6.76 5.80
5 2017/4/18 10:47:52 46.67 11.98 6.47 5.81
6 2017/4/18 10:48:29 46.39 12.16 6.89 5.83
7 2017/4/18 10:49:06 46.39 12.01 7.00 5.74
8 2017/4/18 10:49:43 46.44 11.94 6.55 5.81
9 2017/4/18 10:50:19 46.37 11.82 7.09 5.82
10 2017/4/18 10:50:56 46.55 11.84 6.65 5.82
11 2017/4/18 10:51:33 46.45 11.76 6.54 5.78
12 2017/4/18 10:52:10 46.54 11.74 6.56 5.82
13 2017/4/18 10:52:47 46.69 11.55 6.58 5.76
14 2017/4/18 10:53:24 46.55 11.68 6.67 5.74
15 2017/4/18 10:54:01 46.29 12.37 7.25 5.69
16 2017/4/18 10:54:38 46.17 12.35 6.33 5.82
17 2017/4/18 10:55:14 46.44 12.18 6.41 5.78
18 2017/4/18 10:55:51 46.48 12.09 6.66 5.73
19 2017/4/18 10:56:28 46.43 12.20 6.22 5.78
20 2017/4/18 10:57:05 46.64 12.02 5.99 5.74
21 2017/4/18 10:57:42 46.34 12.16 6.70 5.82
22 2017/4/18 10:58:19 46.47 12.14 6.38 5.79
23 2017/4/18 10:58:56 46.40 11.95 7.09 5.71
24 2017/4/18 10:59:33 46.19 11.98 6.23 5.79
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C Cao, Z Yang*, L Han, X Jiang, G Ji. Cellulose, 2015, 22: 139–149
In situ analysis of components distribution linked to tissue structure of crop stalk based on FTIR microspectroscopic imaging
Cotton stalk
① pith ② primary xylem
③ secondary xylem
④ vessel ⑤bark
Visible image
False color intensity image
Lignin
Corn stalk
① epidermis ②vascular bundle
③ parenchymal cell
Cellulose
Hemicellulose
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Z Yang, J Mei, Z Liu, G Huang, G Huang, L Han*. Analytical Chemistry, 2018, 90 : 7332-7340
光谱仪
小麦茎秆切面全图红外总吸光
度图像
5条纯光谱
特征峰成像图
Leica显微镜
染色
图As Validation
Spotlight 400Imaging System Spectrum 400
Leica DM2500
Sliced around the middle of
the node
Image of section dyed with safranin O-fast green
Chemical imaging at characteristic wavelength 1432 cm-1, 1507 cm-1, 987 cm-1
FTIR analysis
microscope observation
Semi-quantitative analysis based on fast NNLS fitting in selected histological structure
FTIR microspectroscopic
image
Chemical imaging from fast-NNLSCellulose Hemicellulose Lignin Pectin Starch
Wheat straw
Starch
Pectin
Lignin
Hemicellulose
Cellulose
1800 1600 1400 1200 1000 800Wavenumber/cm-1
Fast-NNLS fitting
Abs
orba
nce
kkkkkkk 987
1082
1162
1264
1421 1432
146215071595
16111640
1652
1736
k
Growth stage
Cellulose Hemicellulose Lignin Pectin Starch80
70
60
50
40
30
20
10
0
Con
tent
/%
kk
80
70
60
50
40
30
20
10
0
Con
tent
/%
kk
80
70
60
50
40
30
20
10
0
Con
tent
/%
kk
80
70
60
50
40
30
20
10
0
Con
tent
/%
kk
80
70
60
50
40
30
20
10
0
Con
tent
/%
kk
kkepidermisvascular bundlessclerenchymaparenchyma
kk kk kk kkepidermisvascular bundlessclerenchymaparenchyma
epidermisvascular bundlessclerenchymaparenchyma
epidermisvascular bundlessclerenchymaparenchyma
epidermisvascular bundlessclerenchymaparenchyma
k
Growth stage
k
Growth stage
k
Growth stage
k
Growth stage
epidermis
parenchyma
vascular bundles
Sclerenchyma
Semiquantitative study of the distribution of major components in wheat straw using FTIR microspectroscopic imaging
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Total stress Total strain
Elastic strain Plastic strain
L Chen, A Li, X He, L Han*. Carbohydrate Polymers, 2015, 133: 135–143
Biomechanical behavior is a fundamental property for the efficient utilization Coupled with the microscopic microfibril model and the macroscopic tissue model
A multi-scale biomechanical FE model of wheat straw
Lignocellulose Components
Physiological Structure
+
2.3 Modeling for Mechanism Elucidation of Straw Bio-behavior
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Mechanism investigation of the acid pretreatment and enzymatic hydrolysis of corn stover
Reviewer:“This work should be an example paper forpeople working on the subject …… ”
L Chen, J Li, M Lu, X Guo, H Zhang, L Han*. Carbohydrate Polymers, 2016, 141: 1–9
Acid pretreatment caused structural changes, thereby improving the polysaccharide digestibility
AFMSEM
FTIR XPS
Chemical characterization
Structure characterization
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A novel diffusion–biphasic hydrolysis coupled kinetic model for dilute sulfuric acid pretreatment of corn stover
L Chen, H Zhang, J Li, M Lu, X Guo, L Han*. Bioresource Technology, 2015, 177: 8–16
Highlight:
✓ The contributions of the fast-hydrolyzing xylan, slow-hydrolyzing xylan and the inhibitorfurfural to xylose yield were quantitatively analyzed.
✓ The impact of particle size and acid concentration on xylose yield was investigated.
Diffusion coupled with biphasic hydrolysis for xylan hydrolysis process
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H Zhang, L Chen*, M Lu, J Li, L Han. Biotechnol Biofuels, 2016, 9: 181
A film–pore–surface diffusion model to explain the enhanced enzyme adsorption of corn stover pretreated by ultrafine grinding
The schematic illustration ofmass transfer for enzymeadsorption on a poroussubstrate
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Y Yang, G Ji, W Xiao, L Han*. Cellulose, 2014, 21(5): 3257–3268
“Biomass Now - Cultivation and Utilization”, book edited by Miodrag Darko Matovic, ISBN 978-953-51-1106-1,2013
Retsch ZM100
1.00 mm 0.50 mm 0.25 mm Ultrafine
Plant scale Tissue scale Cellular scale
Vibration ball mill CJM-SY-B
2.4 Multi-scale Mechanical Fragmentation of Crop Residues
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G Ji, C Gao, W Xiao, L Han*. Bioresource Technology, 2016, 205: 159–165C Gao, W Xiao, G Ji, Y Zhang, Y Cao, L Han*. Bioresource Technology, 2017, 241: 214–219G Ji, L Han*, C Gao, W Xiao, Y Zhang, Y Cao. Bioresource Technology, 2017, 241: 262–268H Zhang, L Chen*, J Li, M Lu, L Han. Bioresource Technology, 2017, 234: 23–32H Zhang, J Li, G Huang, Z Yang, L Han*. Bioresource Technology, 2018, 264:327-334
Quantified correlations among particle size, crystalline property and glucose yield
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Mechanical fragmentation: Energy requirement in relation to microstructure properties and enzymatic hydrolysis
G Ji, W Xiao, C Gao, Y Cao, Y Zhang, L Han*. Energy Conversion and Management, 2018, 171: 38–47
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Particle Structure Variation Particle Size Variation
2.5 Multivariate and Multi-scale Approaches for Low GHG Emission during Manure Composting
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Frozen section technique FT-IR
J Ge, G Huang, Z Yang, J Huang, L Han*. Environmental Science & Technology, 2014, 48: 5043−5050
Characterization of the dynamic thickness of the aerobic layer during pig manure aerobic composting by FT-IR microspectroscopy
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Particle-scale visualization of the evolution of methanogens and methanotrophs by FISH-CLSM
➢Microbial mechanisms for CH4 emissions during manure aerobic composting
J Ge, G Huang, J Li, L Han*. Waste Management, 2018, 78: 135–143
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Particle-scale modeling of oxygen uptake rate (OUR)during pig manure–wheat straw composting
J Ge, G Huang, J Huang, J Zeng, L Han*. Chemical Engineering Journal, 2015, 276: 29–36
J Ge, G Huang, J Huang, J Zeng, L Han*. International Journal of Heat and Mass Transfer, 2016, 97: 735–741
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Particle-scale modeling of methane (CH4) emission during pig manure/wheat straw aerobic composting
J Ge, G Huang, J Huang, J Zeng, L Han*. Environmental Science & Technology, 2016, 50: 4374–4383
Reviewer:
This is an excellent paper that supposes a step forward tounderstand the mechanism of emissions of methaneduring composting, a known problem and well referred,but not with the deepness that the authors have used witha realistic model to predict these emissions.
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Multivariate and multiscale approaches for interpreting the mechanisms of nitrous oxide (N2O) emission during pig manure–wheat straw aerobic composting
➢Microbial mechanisms for N2O emissions during manure aerobic composting
J Ge, G Huang, J Li, X Sun, L Han*. Environmental Science & Technology, 2018, 52(15): 8408–8418
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Biobased chemicals
Biobased materials
Bioenergy & Biofuels
Bio-organic fertilizers
Ruminant Feed
3 Summary
➢ Diversified distribution
➢ Significant variation in compositions
➢ Complex or unique lignocellulose structure
➢ Heterogeneous
➢ Economic feasibility
➢ Cleaner production
Better understanding needed for efficient AgroWaste valorizing
Challenges:
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Team Members
Acknowledgements
Prof. Dr. LJ Han Prof. Dr. ZL Yang Dr. GQ Huang Dr. X Liu Dr. WH Xiao Dr. JY Ge
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Acknowledgements
➢ Special Fund for Agro-scientific Research in the Public Interest, theMinistry of Agriculture of China (MoA)
➢ Program for Innovative Research Team in University, the Ministry ofEducation of China (MoE)
➢ China-Belgium international S&T Cooperation Project, the Ministry ofScience & Technology of China (MoST)
➢ NSFC Projects, the National Natural Science Foundation of China (NSFC)
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Thank you very much for your attention!