| Literature DB >> 34917811 |
Md Kaviul Islam1, Mst Sharifa Khatun2, Md Arman Arefin2, Mohammad Rofiqul Islam2, Mehadi Hassan2.
Abstract
The paper aims to study different aspects of liquid fuel production through pyrolysis from agricultural residues, MSW, and e-waste available in Bangladesh. The abundant production of various crops generates massive amounts of residue such as rice straw, wheat straw, rice husk, jute stick, and sugarcane bagasse in Bangladesh have great potential for liquid fuel production for pyrolysis conversion. Bangladesh produces almost 25,000 tons of solid waste per day from urban areas, and Dhaka city alone contributes to one-quarter of all urban waste in the country. The biomass and waste-derived pyrolysis fuel can be successfully used in turbines, boilers, engines and upgraded to high-quality hydrocarbon transportation fuels through distillation. The concise data obtained from the study is anticipated to provide valuable information regarding the effective utilization of municipal solid waste and agricultural residues by using pyrolysis process so that further detailed work on these resources can pave a pathway towards scientific research and significant energy contribution in Bangladesh. The feasibility study has been conducted through physical properties, proximate analysis, elemental analysis, and thermogravimetric analysis of the selected agricultural residues, municipal solid wastes, and plastic e-wastes for pyrolysis conversion in Bangladesh. It has been found that polythene has a better thermochemical potential than rice straw (13.71 MJ/kg) owing to its high calorific value (46.41 MJ/kg). The foremost volatile matter obtained from plastic waste is 98.1 wt.%, and the minimum from rice husk is 57.19 wt.%. The maximum carbon amount is possessed by plastic waste (84.03 wt.%). The ultimate analysis showed that the MSW sample contains more sulfur content than agricultural residue and e-waste, whereas the case is the opposite in terms of oxygen. Rice husk and tire waste have the highest ash content, i.e., 19.70 and 4.38 (wt.%), respectively, indicating a significant amount of unwanted material. TGA examination of feedstock revealed that the majority of mass loss occurred between 250-450 °C for agricultural residue attributed to the release of volatile materials during the formation of char and the evolution of pyrolysis gases. For MSW samples, the range varies between 350-500 °C, which is the appropriate temperature for optimizing liquid oil production in plastic pyrolysis.Entities:
Keywords: Agricultural residues; Feedstock characterization; MSW; Pyrolysis; Waste management
Year: 2021 PMID: 34917811 PMCID: PMC8665337 DOI: 10.1016/j.heliyon.2021.e08530
Source DB: PubMed Journal: Heliyon ISSN: 2405-8440
The energy potential of agricultural residue in 2020 in Bangladesh.
| Crop Residues | Crops Production (kton | Residue Generation Ratio (kton/capita/day) | Residue Generation (kton/year) | Residue Recovery (kton/year) | Dry residue recovery (kton/year) | Energy potential |
|---|---|---|---|---|---|---|
| Rice husk | 36604 [ | 0.28 [ | 9773.27 | 9773.26 | 8561.38 | 157.02 |
| Rice straw | 36604 [ | 1.69 [ | 62043.78 | 21715.32 | 18957.47 | 289.67 |
| Wheat straw | 1029 [ | 1.75 [ | 1800.75 | 630.26 | 582.99 | 9.50 |
| Jute stick | 8045 [ | 3 [ | 24135 | 8447.25 | 7644.76 | 147.93 |
| Sugarcane | 3683 [ | 0.29 [ | 1068.07 | 1068.07 | 544.70 | 9.99 |
Composition of waste generated in Bangladesh's urban regions [18].
| Types of waste (wt.%) | City/Town | ||||||
|---|---|---|---|---|---|---|---|
| Dhaka | Chittagong | Khulna | Rajshahi | Barisal | Sylhet | Average | |
| Food Waste | 68.30 | 70.50 | 78.90 | 70.00 | 81.10 | 73.5 | 74 |
| Paper | 10.70 | 4.63 | 9.50 | 9.00 | 7.20 | 8.60 | 8 |
| Plastic | 4.30 | 8.70 | 3.10 | 9.00 | 3.50 | 3.50 | 5 |
| Textile and wood | 2.20 | 2.40 | 1.30 | 6.00 | 1.90 | 2.10 | 2 |
| Leather and rubber | 1.40 | 5.80 | 0.50 | 1.10 | 0.10 | 0.60 | 2 |
| Metal | 2.00 | 2.65 | 1.10 | 3.00 | 1.20 | 1.10 | 2 |
| Glass | 0.70 | 1.00 | 0.50 | 1.10 | 0.50 | 0.70 | 1 |
| Others | 10.40 | 7.40 | 5.10 | 0.80 | 4.50 | 9.90 | 6 |
Comparison between three basic thermochemical conversion technologies.
| Parameters | Incineration | Gasification | Pyrolysis |
|---|---|---|---|
| Atmosphere | No oxidant | Partial oxidizing | Oxidizing atmosphere |
| Temperature | (850–1200) ˚C | (550–1600) ˚C | (500–800) ˚C |
| Feedstock | Municipal solid waste, hazardous waste, medical waste, etc. [ | Numerous waste streams, including municipal solid waste, industrial waste, and agricultural residue, are noteworthy examples [ | Municipal solid waste, plastic waste, organic waste, forest residue, industrial wastes, agricultural residue are important examples [ |
| Primary product | Heat | Gas | Gas, tar and oils, char |
| Product recovery | Boiler | Boiler, gas turbine, engine, synthesis | Gas (Boiler, gas turbine, engine, synthesis) |
| Tar and oils (boiler, gas turbine, upgrading extraction) | |||
| Secondary product | Electricity | Electricity | Electricity |
| Ammonia methanol, chemicals from synthesis | |||
| Ammonia methanol, chemicals from synthesis | Gasoline | ||
| Char used in soil amendment | |||
| High heating value (MJ/kg) | 16–19 | nil | 5-20 [ |
| Energy requirement [ | Less than gasification and pyrolysis | Less than pyrolysis | More energy requirement but compensates by lower emission and energy recovery |
| Storage and transportation | Heat is used in the production site for heating purposes | Syngas needs immediate use after production | Bio-oil is easier to transport than syngas but difficult to store for long due to its corrosiveness [ |
| Economic viability | Expensive | Comparatively expensive [ | Cost effective [ |
| Pollutants | SO2, NOx, HCl particulate matter, dioxins and furans etc. | H2S, HCl,NH3,HCN, | H2S, HCl, NH3, HCN, |
| Emission | Higher emission of air pollutants [ | Lower emissions of air pollutants than incineration | Lower emissions of air pollutants than incineration [ |
| Emission control | Particulate collector | Bulk particle removal using a cyclone separator and filters | To remove heavy metals and dioxins in pyrolysis, the flue gas may be cleaned with an injection of reactive hydrated lime, perhaps in conjunction with active carbon, and then passed through a ceramic fiber filter before being released to the atmosphere. |
| Fine particles, ammonia, and chlorides are removed by wet scrubbing. | |||
| Acid gas scrubbers | Mercury and trace heavy metal removal using solid absorbents | ||
| Adjusting the H2/CO ratio via a water-gas shift (WGS) | |||
| In a variety of municipal waste incinerators, add-on NOx flue gas control systems include selective noncatalytic reduction (SNCR), mercury-based dioxin and furan removal, with powdered activated carbon injection [ | Acid gas removal (AGR) for removing sulfur-bearing gases and converting COS (Carbonyl sulfide) to H2S, and catalytic hydrolysis for converting COS (Carbonyl sulfide) to H2S | ||
| Engross grate combustion, Ebara fluidized bed process, plasma-assisted gasification etc. [ | |||
| Social aspects | Reduce waste volumes | Reduce the waste volumes dumped in landfills | Reduce the waste volumes, mainly plastic waste, which will be dumped in landfills |
| Hazardous emission affects the public health of the locality | Release less GHG gases | Release less GHG gases | |
| Create concern about the environmental emission | Water pollution used for cooling affects the locality | Danger related public health is less | |
| Employment opportunities | Employment opportunities | Employment opportunities | |
| Can supply particular energy demand of the surrounding cities from the output product | Can supply particular energy demand of the surrounding cities from the output product | Can supply energy demand of the surrounding cities from the output product | |
| Awareness of waste and residues used for energy production | The consciousness of waste and residues used for energy production |
Product yield from different feedstock.
| Feedstock | Liquid (%) | Char (%) | Gas (%) | Temperature (˚C) | Reference |
|---|---|---|---|---|---|
| Rice husk | 47 | 24.71 | 28.29 | 550 | [ |
| Rice Straw | 26 | 47 | 17 | 500 | [ |
| Sugarcane bagasse | 46 | 26 | 28 | 500 | [ |
| Jute stick | 66.70 | 22.60 | 10.70 | 500 | [ |
| Wheat straw | 49.90 | 32.90 | 15.60 | 400 | [ |
| Waste paper | 48 | 28 | 24 | 600 | [ |
| Polythene | 80 | 20 | 0 | 500 | [ |
| Plastic waste | 79 | 20 | 1 | 500 | [ |
| Electronic waste | 28.20 | 68.70 | 3.10 | 240 | [ |
| Tire | 42 | 48 | 10 | 450 | [ |
| Furniture waste | 58.10 | 21.30 | 20.60 | 450 | [ |
Higher Calorific Value of Selected feed materials.
| Feed Material | Higher Calorific value in (MJ/kg) | |
|---|---|---|
| Rice Husk | Mean | 18.34 |
| Standard Deviation | 0.72 | |
| Rice Straw | Mean | 15.28 |
| Standard Deviation | 1.23 | |
| Sugarcane Bagasse | Mean | 18.34 |
| Standard Deviation | 1.24 | |
| Jute Stick | Mean | 19.35 |
| Standard Deviation | 1.20 | |
| Wheat Straw | Mean | 16.30 |
| Standard Deviation | 0.49 | |
| Waste paper | Mean | 15.28 |
| Standard Deviation | 1.32 | |
| Polythene | Mean | 42.79 |
| Standard Deviation | 3.07 | |
| Plastic Waste | Mean | 31.58 |
| Standard Deviation | 1.23 | |
| Electronic Waste | Mean | 31.58 |
| Standard Deviation | 1.93 | |
| Tire Waste | Mean | 35.66 |
| Standard Deviation | 0.48 | |
| Furniture Waste | Mean | 37.7 |
| Standard Deviation | 2.77 |
Proximate Analysis of Selected Feed Material on wt.% basis.
| Feed Material | Moisture Content (wt.%) | Volatile Matter (wt.%) | Ash Content | Fixed Carbon | |
|---|---|---|---|---|---|
| Rice Husk | Mean | 7.31 | 65 | 16 | 11 |
| Standard Deviation | 0.87 | 4.78 | 2.83 | 2.46 | |
| Rice Straw | Mean | 9.54 | 68.11 | 10.19 | 12.16 |
| Standard Deviation | 1.05 | 6.64 | 2.20 | 3.29 | |
| Sugarcane Bagasse | Mean | 6.41 | 81.77 | 0.97 | 10.85 |
| Standard Deviation | 1.30 | 3.22 | 0.24 | 1.63 | |
| Jute Stick | Mean | 11.23 | 85.33 | 0.30 | 2.63 |
| Standard Deviation | 1.47 | 1.81 | 0.078 | 0.38 | |
| Wheat Straw | Mean | 17.81 | 76.66 | 2.21 | 3.32 |
| Standard Deviation | 0.52 | 0.70 | 0.70 | 0.67 | |
| Waste Paper | Mean | 7.89 | 78.92 | 2.68 | 10.50 |
| Standard Deviation | 0.40 | 2.40 | 0.54 | 0.35 | |
| Polythene | Mean | 4.98 | 92.55 | 1.46 | 1.31 |
| Standard Deviation | 0.24 | 2.28 | 0.42 | 0.44 | |
| Plastic Waste | Mean | 2.09 | 97.3 | 0.23 | 0.37 |
| Standard Deviation | 0.8940 | 0.7422 | 0.0632 | 0.0989 | |
| Electronic Waste | Mean | 1.33 | 88 | 1.83 | 8.84 |
| Standard Deviation | 0.57 | 2.46 | 0.12 | 0.11 | |
| Tire Waste | Mean | 1.66 | 67.03 | 3.28 | 28 |
| Standard Deviation | 0.27 | 2.15 | 0.96 | 2.12 | |
| Furniture Waste | Mean | 6.63 | 74.99 | 2.7 | 15.68 |
| Standard Deviation | 1.35 | 0.90 | 0.41 | 1.23 |
Ultimate Analysis of Selected Feed Material on wt.% basis.
| Feed Material | Carbon (wt.%) | Hydrogen (wt.%) | Nitrogen | Sulfur | Oxygen | |
|---|---|---|---|---|---|---|
| Rice Husk | Mean | 36.21 | 5.63 | 1.67 | 0.19 | 56.21 |
| Standard Deviation | 2.40 | 0.39 | 0.40 | 0.38 | 2.34 | |
| Rice Straw | Mean | 48.30 | 5.80 | 1.40 | 0.18 | 44.32 |
| Standard Deviation | 0.73 | 0.43 | 0.59 | 0.02 | 3.45 | |
| Sugarcane Bagasse | Mean | 49.23 | 5.62 | 0.19 | 0.02 | 44.94 |
| Standard Deviation | 0.61 | 0.70 | 0.30 | 0.01 | 1.18 | |
| Jute Stick | Mean | 48.21 | 5.83 | 0.46 | 0.04 | 45.46 |
| Standard Deviation | 1.02 | 0.10 | 0.17 | 0.01 | 0.79 | |
| Wheat Straw | Mean | 42.7 | 6.21 | 2.78 | 0.17 | 48.14 |
| Standard Deviation | 0.66 | 0.38 | 0.20 | 0.06 | 1.18 | |
| Waste Paper | Mean | 40.27 | 7.12 | 0.24 | 0.05 | 52.32 |
| Standard Deviation | 0.89 | 0.45 | 0.07 | 0.02 | 0.80 | |
| Polythene | Mean | 84.12 | 12.43 | 0.31 | 0.09 | 3.05 |
| Standard Deviation | 1.30 | 0.51 | 0.08 | 0.01 | 0.48 | |
| Plastic Waste | Mean | 83.91 | 8.43 | 0.06 | 1.32 | 6.40 |
| Standard Deviation | 0.11 | 0.58 | 0.02 | 0.16 | 0.14 | |
| Electronic Waste | Mean | 67.01 | 6.25 | 1.43 | 0.61 | 24.7 |
| Standard Deviation | 0.26 | 0.52 | 0.22 | 0.12 | 1.87 | |
| Tire Waste | Mean | 83.90 | 8.00 | 0.44 | 1.46 | 6.3 |
| Standard Deviation | 3.09 | 0.20 | 0.07 | 0.16 | 0.84 | |
| Furniture Waste | Mean | 41.28 | 6.23 | 0.17 | 1.65 | 50.67 |
| Standard Deviation | 2.237 | 1.03 | 0.06 | 0.25 | 1.38 |
TGA Analysis of Selected Feed Material on wt.% basis.
| Temp (°C) | Weight (%) | Weight (%) for | Weight (%) (Sugarcane | Weight (%) (Jute Stick) | Weight (%) (Wheat Straw) | Weight (%) (Waste Paper) | Weight (%) | Weight (%) (Electronic Waste) | Weight (%) (Furniture Waste) | |
|---|---|---|---|---|---|---|---|---|---|---|
| 30.41 | Mean | 99.86 | 99.46 | 99.94 | 99.93 | 99.82 | 99.94 | 99.71 | 99.99 | 99.90 |
| Standard Deviation | 0.01 | 0.54 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 50 | Mean | 98.38 | 97.82 | 99.20 | 98.86 | 97.49 | 98.99 | 99.05 | 100.01 | 98.37 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 75 | Mean | 95.36 | 93.91 | 97.29 | 95.89 | 94.15 | 96.46 | 98.73 | 99.88 | 94.24 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 100 | Mean | 93.60 | 92.04 | 96.39 | 95.22 | 93.08 | 95.08 | 98.81 | 99.66 | 90.62 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 125 | Mean | 93.07 | 91.52 | 96.27 | 94.97 | 92.91 | 94.68 | 98.78 | 99.44 | 89.39 |
| Standard Deviation | 0.01 | 0.01 | 0.05 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 150 | Mean | 92.90 | 91.23 | 96.29 | 94.53 | 92.87 | 94.53 | 98.89 | 99.26 | 89.11 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 175 | Mean | 92.78 | 91.08 | 96.20 | 94.20 | 92.84 | 94.49 | 98.84 | 99.12 | 88.94 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 200 | Mean | 92.53 | 90.71 | 95.81 | 94.04 | 92.68 | 94.43 | 98.83 | 98.99 | 88.65 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 225 | Mean | 91.89 | 89.55 | 94.46 | 93.45 | 91.94 | 94.25 | 98.76 | 98.83 | 87.94 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 250 | Mean | 89.98 | 85.20 | 91.50 | 91.34 | 88.74 | 73.70 | 98.67 | 98.46 | 85.65 |
| Standard Deviation | 0.02 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 275 | Mean | 84.23 | 73.31 | 82.80 | 84.16 | 78.59 | 91.88 | 98.44 | 97.73 | 79.33 |
| Standard Deviation | 0.04 | 0.02 | 0.01 | 0.02 | 0.02 | 0.01 | 0.01 | 0.01 | 0.02 | |
| 300 | Mean | 7.48 | 56.83 | 65.69 | 71.00 | 57.96 | 85.74 | 98.11 | 95.89 | 59.16 |
| Standard Deviation | 0.05 | 0.02 | 0.03 | 0.02 | 0.01 | 0.02 | 0.01 | 0.01 | 0.06 | |
| 325 | Mean | 57.73 | 44.60 | 42.32 | 43.36 | 40.58 | 62.12 | 97.45 | 93.75 | 37.35 |
| Standard Deviation | 0.04 | 0.01 | 0.02 | 0.08 | 0.12 | 0.07 | 0.03 | 0.01 | 0.02 | |
| 350 | Mean | 48.93 | 39.23 | 34.21 | 25.45 | 33.55 | 39.01 | 96.14 | 91.94 | 28.52 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 375 | Mean | 44.25 | 34.72 | 29.29 | 20.29 | 28.00 | 35.70 | 92.12 | 88.37 | 19.33 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.02 | |
| 400 | Mean | 40.08 | 29.25 | 24.40 | 15.54 | 21.65 | 32.86 | 77.59 | 79.74 | 9.23 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.03 | 0.02 | 0.01 | |
| 425 | Mean | 35.75 | 22.45 | 18.06 | 10.51 | 14.02 | 29.41 | 39.03 | 66.01 | 1.09 |
| Standard Deviation | 0.01 | 0.31 | 0.10 | 0.01 | 0.01 | 0.01 | 0.07 | 0.03 | 0.01 | |
| 450 | Mean | 30.65 | 14.75 | 9.86 | 5.09 | 8.71 | 23.52 | 6.06 | 56.78 | -4.01 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.02 | 0.01 | 0.01 | |
| 475 | Mean | 24.45 | 10.45 | 4.06 | 2.49 | 6.68 | 20.28 | 0.56 | 51.17 | -5.13 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 500 | Mean | 20.56 | 10.09 | 2.56 | 2.94 | 6.47 | 20.18 | -3.52 | 44.24 | -5.20 |
| Standard Deviation | 0.01 | 0.01 | 0.09 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 525 | Mean | 19.55 | 9.96 | 2.60 | 2.27 | 6.41 | 20.12 | -8.76 | 37.07 | -5.21 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 550 | Mean | 19.17 | 9.85 | 2.60 | 2.23 | 6.35 | 20.10 | -9.43 | 34.20 | -5.22 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 575 | Mean | 18.99 | 9.74 | 2.59 | 2.19 | 6.30 | 20.09 | -9.44 | 32.65 | -5.24 |
| Standard Deviation | 0.01 | 0.02 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 600 | Mean | 18.88 | 9.63 | 2.54 | 2.05 | 6.23 | 20.05 | -9.45 | 31.35 | -5.28 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 625 | Mean | 18.80 | 9.48 | 2.53 | 2.01 | 6.09 | 19.82 | -9.47 | 30.30 | -5.36 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 650 | Mean | 18.72 | 9.36 | 2.51 | 1.95 | 6.05 | 19.26 | -9.44 | 29.71 | -5.44 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 675 | Mean | 18.64 | 9.33 | 2.50 | 1.87 | 6.02 | 18.02 | -9.42 | 29.45 | -5.49 |
| Standard Deviation | 0.01 | 0.02 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 700 | Mean | 18.59 | 9.32 | 2.48 | 1.74 | 6.00 | 15.83 | -9.40 | 29.34 | -5.51 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 725 | Mean | 18.54 | 9.28 | 2.45 | 1.56 | 5.94 | 13.08 | -9.40 | 29.29 | -5.53 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 750 | Mean | 18.48 | 9.21 | 2.42 | 1.34 | 5.87 | 12.91 | -9.43 | 29.25 | -5.56 |
| Standard Deviation | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 775 | Mean | 18.43 | 9.08 | 2.36 | 1.02 | 5.73 | 12.87 | -9.50 | 29.21 | -5.61 |
| Standard Deviation | 0.01 | 0.05 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |
| 791 | Mean | 18.38 | 8.97 | 2.30 | 0.72 | 5.60 | 12.84 | -9.58 | 29.18 | -5.64 |
| Standard Deviation | 0.01 | 0.04 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 |