1 Introduction
2 Materials and methods
2.1 Samples
Batch | Pellet raw material and treatment at production | Pelletizing Plant | Density of pellets (kg/m3) |
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1 | Pine 100%. Ground material stored 4 days in big bag at 20 °C before pelletizing | German, RP | 1254 |
2 | Spruce 100%. Ground material stored 8 days in big bag at 20 °C before pelletizing | German, RP | 1258 |
3 | Pine 100%. Pelletized immediately after grinding | German, RP | 1254 |
4 | Spruce 100%. Pelletized immediately after grinding | German, RP | 1258 |
5 | Pine 100%. Sample from ordinary production | German, CP 1 | 1213 |
6 | Spruce 80%/Pine 20%. Sample straight from ordinary production | Swedish, CP 1 | 1217 |
7 | 83% straw, 11% seed residue, 6% spruce. Sample straight from ordinary production | Danish, CP 1 | 1183 |
8 | Spruce 100%. Sample straight from ordinary production | German, CP 2 | 1180 |
9 | Pine 40%/Spruce 60%. Sample from ordinary production | Swedish, CP 2 | 1212 |
10 | Pine 60%/Spruce 40%. Sample from ordinary production | Swedish CP 3 | 1225 |
11 | Eucalyptus 100%. Stored one year at the company | Spain CP 1 | 1211 |
12 | Pine 50%/Spruce 50%. Sample straight from ordinary production | Swedish CP 4 | 1201 |
13 | Vine pruning 50%/vine pomace 50% | German RP | 1324 |
14 | Pine 100%, scCO2 extracted (extracted at York, Swedish raw material), run 1 | German RP | 1191 |
15 | Pine 100% | Austrian RP | 1256 |
16 | Pine 100%, RP (same raw material as in Batch 15 but different equipment with pelletizing) | German RP | 1185 |
17 | Straw pellets (100%). Stored in a flat storage for 6 months before delivery | Danish CP 2 | 1116 |
18 | Spruce 80%/ Pine 20% - mixed pellets | German CP 3 | 1182 |
19 | Pine 100%, torrefied at 308 °C, 12 min, pelletized after cooling | Swedish RP | 1259 |
20 | Pine 100%, torrefied at 315 °C, 12 min, pelletized after cooling | Swedish RP | 1177 |
21 | Obtained from pellet company after fire accident | Swedish CP 3 | N/A |
22 | Eucalyptus 100% | German CP 4 | 1290 |
23 | Pine 100%, reference to Batches 24, 25, 27, pelletized after cooling | Swedish RP | 1243 |
24 | Pine 100%, with TBHQ as antioxidant, pelletized after cooling | Swedish RP | 1232 |
25 | Pine 100%, with PG as antioxidant, pelletized after cooling | Swedish RP | 1225 |
26 | 75% pine, 25% fir and larch | Danish CP 3 | 1274 |
27 | Pine 95%, with 5% spruce bark | Swedish RP | 1248 |
28 | Spruce 100%. Flat storage trial in Denmark, sampling after 1 week | Danish CP | 1252 |
29 | Spruce 100%. Flat storage trial in Denmark, sampling right after production | Danish CP | 1250 |
30 | Obtained from pellet company after a fire accident | German CP 5 | 1225 |
31 | 100% pine, reference to Batch 14 | German RP | 1270 |
32 | Pine 100%, scCO2 extracted (extracted at York, Swedish raw material, run 2) Attard et al. (2016) | German RP | 1238 |
33 | Reference to Batch 32. Attard et al. (2016) | German RP | 1139 |
35 | Pine 100%, with 0.5% additive | Swedish RP | 1137 |
36 | Reference to Batch 35 | Swedish RP | 1159 |
2.2 Dynamic vapour sorption analysis
2.2.1 Sample preparation
2.2.2 Instrument
2.3 Data collection and interpretation
3 Results and discussion
3.1 General considerations and basis for interpretation
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Total water uptake for the pellet batch (%)
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Speed of water uptake (i.e. dm/dt)
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Calculated values of the parameters in the model equation that reflect the properties of water uptake for each batch individually (MC1 and MC2).
3.2 Measured data and method repeatability
Batch | “Infinite” water uptake (%) | Solver solution parameters | dm/dt (g/min) | ||||||
---|---|---|---|---|---|---|---|---|---|
Water uptake (%) after 2 h | MC1 | MC2 | t1 (min) | t2 (min) | At 10 min | At 30 min | At 60 min | ||
1 | 4.50 | 1.72 | 0.00184 | 0.00756 | 49.37 | 405.7 | 0.02954 | 0.01839 | 0.01306 |
2 | 4.32 | 2.10 | 0.00339 | 0.00533 | 78.46 | 342.9 | 0.03507 | 0.02343 | 0.01636 |
3 | 3.91 | 2.02 | 0.00189 | 0.00483 | 51.13 | 260.4 | 0.03650 | 0.02246 | 0.01541 |
4 | 4.62 | 2.37 | 0.00194 | 0.00628 | 46.33 | 247.7 | 0.03978 | 0.02654 | 0.01845 |
5 | 4.90 | 2.38 | 0.00254 | 0.00625 | 78.90 | 260.5 | 0.03538 | 0.02552 | 0.01943 |
6 | 4.20 | 2.32 | 0.00222 | 0.00609 | 46.40 | 221.2 | 0.04001 | 0.02689 | 0.01777 |
7 | 5.77 | 2.73 | 0.00250 | 0.00930 | 63.90 | 256.7 | 0.03986 | 0.02957 | 0.02223 |
8 | 4.20 | 1.80 | 0.00158 | 0.00676 | 47.11 | 316.4 | 0.02977 | 0.01952 | 0.01407 |
9 | 4.82 | 1.97 | 0.00146 | 0.00863 | 50.00 | 302.9 | 0.02964 | 0.02085 | 0.01585 |
10 | 4.68 | 2.03 | 0.00096 | 0.00842 | 38.77 | 246.2 | 0.02995 | 0.02169 | 0.01640 |
11 | 4.07 | 2.18 | 0.00231 | 0.00511 | 45.46 | 270.2 | 0.04005 | 0.02552 | 0.01643 |
12 | 4.92 | 1.98 | 0.00235 | 0.00640 | 60.67 | 235.6 | 0.03926 | 0.02795 | 0.02052 |
13 | 10.3 | 0.54 | 0.00190 | 0.01589 | 69.84 | 688.3 | 0.03202 | 0.02457 | 0.01954 |
14 | 4.10 | 2.28 | 0.00183 | 0.00583 | 42.96 | 207.7 | 0.04010 | 0.02624 | 0.01760 |
15 | 4.54 | 2.85 | 0.00177 | 0.00684 | 50.58 | 318.8 | 0.03277 | 0.02159 | 0.01535 |
16 | 3.81 | 2.45 | 0.00233 | 0.00419 | 46.25 | 178.7 | 0.04469 | 0.02909 | 0.01867 |
17 | 6.86 | 2.83 | 0.00210 | 0.00821 | 41.58 | 250.3 | 0.04536 | 0.03140 | 0.02226 |
18 | 3.92 | 1.75 | 0.00044 | 0.00709 | 8.66 | 225.3 | 0.03195 | 0.01601 | 0.01294 |
19 | 3.80 | 1.54 | 0.00085 | 0.00684 | 37.34 | 289.7 | 0.02453 | 0.01639 | 0.01214 |
20 | 3.96 | 2.26 | 0.00311 | 0.00467 | 57.77 | 258.8 | 0.03962 | 0.02626 | 0.01752 |
21 | 4.54 | 2.37 | 0.00239 | 0.00708 | 61.06 | 227.7 | 0.03688 | 0.02592 | 0.01885 |
22 | 5.83 | 2.09 | 0.00189 | 0.00956 | 60.74 | 395.8 | 0.03117 | 0.02229 | 0.01668 |
23 | 4.00 | 1.74 | 0.00135 | 0.00753 | 39.46 | 287.9 | 0.02887 | 0.01880 | 0.01345 |
24 | 4.37 | 2.33 | 0.00187 | 0.00701 | 50.39 | 210.7 | 0.03778 | 0.02563 | 0.01820 |
25 | 4.25 | 2.47 | 0.00243 | 0.00433 | 54.81 | 226.0 | 0.04324 | 0.02837 | 0.01914 |
26 | 4.35 | 2.07 | 0.00167 | 0.00619 | 49.69 | 268.7 | 0.03346 | 0.02292 | 0.01638 |
27 | 3.69 | 2.00 | 0.00089 | 0.00586 | 26.94 | 187.2 | 0.03546 | 0.02230 | 0.01530 |
28 | 4.97 | 2.22 | 0.00143 | 0.00775 | 60.55 | 258.6 | 0.03176 | 0.02357 | 0.01818 |
29 | 5.49 | 2.20 | 0.00158 | 0.00981 | 53.77 | 309.3 | 0.03166 | 0.02353 | 0.01790 |
30 | 4.32 | 1.82 | 0.00133 | 0.00641 | 45.70 | 314.4 | 0.02998 | 0.01958 | 0.01421 |
31 | 4.47 | 1.61 | 0.00135 | 0.00674 | 43.82 | 425.9 | 0.02828 | 0.01739 | 0.01216 |
32 | 5.06 | 1.98 | 0.00123 | 0.00786 | 46.68 | 326.1 | 0.03156 | 0.02058 | 0.01550 |
33 | 4.93 | 2.70 | 0.00154 | 0.00684 | 47.23 | 192.4 | 0.04325 | 0.02967 | 0.02154 |
35 | 4.41 | 2.07 | 0.00268 | 0.00617 | 68.62 | 322.0 | 0.03329 | 0.02259 | 0.01625 |
36 | 4.51 | 1.99 | 0.00167 | 0.00722 | 51.61 | 294.2 | 0.03113 | 0.02142 | 0.01585 |
3.3 “Infinite” water uptake—influences of raw material and production
Raw material | Mean (%) | sd | RSD | n |
---|---|---|---|---|
Pine (P) | 4.36 | 0.41 | 9.4 | 14 |
Spruce (S) | 4.66 | 0.45 | 9.6 | 6 |
Pine/spruce mix (PS) | 4.48 | 0.31 | 6.9 | 8 |
Straw | 6.32 | – | – | 2 |
Eucalyptus | 4.95 | 0.88 | 17.8 | 2 |
Wine pruings/pomace | 10.33 | – | – | 1 |
Torrefied pine | 7.00 | – | – | 2 |
P + S + PS | 4.61 | 0.63 | 13.7 | 28 |
All types | 4.73 | 1.16 | 24.5 | 35 |
Production
| ||||
Industry | 4.61 | 0.74 | 16.1 | 17 |
Pilot plant | 4.84 | 1.44 | 29.7 | 18 |
3.4 Modelling of the water up-take process
3.5 Rate of water up-take
3.6 Water uptake, heat of condensation and potential temperature rise
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the mean porosityϕ (air space between the pellets in bulk) was calculated from pellet bulk density and single pellet density, to be 0.471 (range 0.415–0.557, RSD 6.4%,) and
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the mean pellet MC at 40% RH was 7.53% (range 6.58–8.65%, RSD 6.52%).
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This (water uptake/heat of condensation) gives an estimation that a heat release of 100 kJ/kg pellets (range 81–151 kJ/kg, RSD 14.3%) would be possible and a potential temperature increase (heat release/CP) of 87 °C (range 72–169, RSD 12.2).
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Thus, the water uptake during the first 2 h at RH 80% was determined to be 2.15% (Table 2, range 1.54–2.85%, RDS 15.2%), corresponding to 48% of the infinite water uptake at 80 RH%, resulting in a potential heat release of 47 kJ/kg (range 12–63 kJ/kg, RSD 15.2%) and temperature rise of 45 °C (range 12–58 °C, RSD 14%).
4 Conclusion
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The heat of condensation released during water condensation in a pellet silo has a potential to considerably contribute to increasing the temperature, especially in a situation with a fast and/or large change in relative air humidity, and should be expected to be a major contributing factor to initiating temperature increase incidents. The correlation between water uptake and heat release of lignocellulosic material is a well-known process (Back and Johansson 1990; Back 1981). In addition, such a temperature rise can be expected to contribute to the initiation and acceleration of autoxidation.
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The water uptake between pellets made from pine, spruce and pine/spruce mixtures did not differ significantly but was higher for batches made from wine prunings/pomace, straw and torrefied pine (although these types of samples were few).
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The water uptake rate (dm/dt) in the initial part of the process gives an indication of the potential for a fast temperature rise associated with changes in air relative humidity and the following condensation in pellet storage. The uptake rate varies considerably between the pellet samples made from different raw materials.
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From the potential water uptake it is possible to calculate a heat release potential due to heat of condensation and to make an estimation of potential local temperature rise. In addition, this implies that the different batches have varying potential to release heat of condensation and initiate/accelerate a self-heating process in a silo.
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Thus, DVS analysis has the potential to complement other physical/chemical measurements on fuel pellets in predicting how the choice of fuel raw material and pellet processing parameters might influence the potential risk for self-heating, off-gassing and fire incidents.
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The results are based on a fairly large and representative number of fuel pellet batches on the European market and should provide a strong basis in modelling physical/chemical processes in pellet storage. Such further studies have the potential to give a tool to predict the self-heating potential of various pellet batches. Such a tool should increase the possibility to reduce the risks associated with pellets storage/transportation and to avoid the conditions/situations involving highest risk for off-gassing, oxygen depletion and uncontrolled heat formation/fire.