feasibility study of gasification of biomass for … study of gasification of biomass for synthetic...
TRANSCRIPT
Feasibility study of gasification of biomass for
synthetic natural gas (SNG) production
Final report
Presented to
Energiforsk and Lund University, Faculty of Engineering, LTH
May 29, 2015
Principal investigators
Adam Eliasson, Johan Karstensson, Anders Kronander
Tutors
Hans T. Karlsson, Christian Hulteberg and Helena Svensson
Disclaimer
This project was carried out in the course “Feasibility Studies on Industrial Plants, (KET050)”, Department of
Chemical Engineering, Faculty of Engineering, Lund University. This report was prepared in cooperation with
Energiforsk. The report may not be reproduced without the written permission from the authors or Energiforsk.
Abstract
In this study, a production plant for Bio-Synthetic Natural Gas (Bio-SNG) from gasification of
biomass has been compiled. First, a literature review of possible utilities is presented followed
by a presentation of a process plant with necessary utilities. After the literature report, a brief
introduction regarding how the calculations were carried out is presented and followed by the
conclusions regarding process cost for the final product, SNG. The economy of a green field
erection was compared with an integrated SNG plant at an existing pulp and paper industry,
referred to as a brown field erection.
The calculations were partly carried out and integrated using Aspen Plus v8.2 as well as
MATLAB and Excel. The overall conclusion was that bark- SNG- and steam prices have a
significant influence on the economy evaluation. The brown field plant would benefit slightly
due to the knowledge of and the possibility to produce electricity from the high pressure steam
obtained from the exothermic reactions in the methanation step. However, with the base case
and today’s prices, the payback time is about 12 years based on the payback model, including
interest rate. This is a fairly good payback time for the investment. However, the calculations
are very sensitive to changes in prices, both in those of the products and in those of the biomass.
Thus it is still a risky investment considering a lifetime of 15-20 years.
Contents
1. Introduction ........................................................................................................................... 1
2. Production of SNG from biomass ......................................................................................... 2
2.1. Pretreatment .................................................................................................................... 3
2.1.1. Hammer mill ............................................................................................................ 3
2.1.2. Drying of Biomass ................................................................................................... 4
2.2. Gasification .................................................................................................................... 6
2.3. Particle removal, purification and gas treatment ............................................................ 7
2.3.1. Particle removal ....................................................................................................... 7
2.3.2. Hydrogenation ......................................................................................................... 9
2.3.3. Water Gas Shift ....................................................................................................... 9
2.3.4. Hydrolysis ............................................................................................................. 10
2.3.5. Acid gas removal ................................................................................................... 10
2.3.6. Methanation ........................................................................................................... 12
2.3.7. Gas upgrade ........................................................................................................... 15
2.4. Desulfurization of flue gas leaving combustion chamber ............................................ 16
3. Overall process .................................................................................................................... 17
4. Discussion literature review ................................................................................................ 21
5. Method for cost estimates .................................................................................................... 22
5.1. Operating costs ............................................................................................................. 22
5.2. Capital costs ................................................................................................................. 22
6. Economical evaluation ........................................................................................................ 23
7. Discussion ........................................................................................................................... 27
8. Conclusions ......................................................................................................................... 29
9. References ........................................................................................................................... 30
Appendix A Calculations ..................................................................................................... 33
Appendix B Economy Summary ......................................................................................... 48
Appendix C Aspen flowsheet .............................................................................................. 58
Appendix D MATLAB SCRIPT .......................................................................................... 60
1
1. Introduction
A high energy security with a continuously accessible supply of energy is vital for all countries.
With decreasing levels of fossil fuel reserves combined with military conflicts and increased
fuel prices, there is a strong ambition for many countries to replace the use of fossil fuels with
sustainable, renewable resources1. As Sweden has a net import of 100 % of its natural gas, the
energy demand is strongly dependent of our neighbors2. Biomass gasification would therefore
increase energy security and at the same time, decrease the risk of climate change.
The capacity of large-scale production of substitute natural gas, SNG, from biomass
gasification, could help increase the amount of renewable resources, especially in electricity
production. The processes are quite simple and there are several ways of converting biomass to
SNG. Also, there is a large pallet of available resources to be used. As natural gas is the world’s
third most important energy source, covering about 21 % of the world’s total primary energy
usage, the infrastructure is well developed and can be used for SNG3. Furthermore, the use of
natural gas is believed to increase, as can be seen in figure 1. In Europe, most natural gas is
used for heat and power generation plants. However, IEA estimates that about 30 % of the
transport fuel can be covered by biofuels in 20504.
Figure 1. Natural gas usage on a global level5.
In figure 2, the total Swedish transport energy demand is visualized. With a total energy demand
of about 122 TWh of which biogas from fermentation accounts for 0.6 TWh. In 2010 there is a
strong need to increase the amount of renewable resources in this sector to reach a more
sustainable transport sector. According to recent studies, the introduction of Bio-SNG together
with an increased amount of biogas from fermentation, up to 70 TWh could be achieved6. This
would account for about 57 % of the total energy usage in the transport sector, which thereby
could be covered by renewable resources6.
2
Figure 2. Current- and potential methane production compared with the total energy consumption of the transport
sector in Sweden6.
This project compares a production plant for SNG which is integrated into an existing pulp mill
against a green field erection. An economic evaluation and comparison between the two is
performed and discussed to determine which one that would be the cheapest one to construct.
A broad investigation regarding potential synergies at integration with existing infrastructure
will be compared to a green field installation. The project will render a suggested process design
capable of receiving 200 MWth input of biomass.
The goal for this study is to design and evaluate economic aspects of a production plant for
Bio-SNG through gasification. A decision will be made whether the production plant should be
built as an integrated process, a green field erection or if it should be built at all. The integrated
process will be connected into an existing pulp mill located in Värö, outside Varberg, Sweden.
The feedstock for this case consists of residues from the pulp mill, most of which is bark.
Certain limitations have been set in this project. As mentioned before, there are several different
sorts of feedstock that could be used. However, in this project, only bark have been investigated.
This project was based on the considerable input of 200 MWth. Therefore, small size processes
and laboratory scale gasifiers have not been taken into account.
2. Production of SNG from biomass
A general process setup for the production of Bio-SNG is visualized in the box scheme seen in
figure 4. The biomass is transported to the process by train or heavy vehicles. Pretreatment
consists of drying the biomass as well as grinding it to the necessary size before it enters the
gasifier. The gasifier generates producer gas that has to be cleaned downstream in the process.
The total process releases a lot of excess heat which could be used to satisfy heat demands in
other utilities in the process or eventually even district heating. By cleaning the combustion
flue gas, gypsum will be obtained as a byproduct. In the best case, this gypsum could be sold
to increase the revenue. However, gypsum is very cheap and will be treated as a byproduct of
no value (might actually become a smaller cost).
3
Figure 4. Box scheme over the bio-SNG production.
The gas that leaves the methane step of figure 4 consists of methane, carbon dioxide and water
and some trace elements of nitrogen, hydrogen and carbon monoxide. Before the gas can be
injected into the gas grid, it has to fulfill certain quality requirements which have been set by
the European Association for the Streamlining of Energy Exchange - gas (EASEE-gas). These
quality requirements are listed in table 1. Therefore, additional upgrading of the gas might be
necessary to increase pressure, increase energy density (adding propene) or to decrease the
amount of water or other components in the gas.
There are several gas quality requirements that the gas has to fulfill before it’s injected to the
gas grid. The requirements that have to be met can be seen in table 1.
Table 1. Gas quality requirements from European Association for the Streamlining of Energy Exchange – gas
[EASEE-gas, 2005].
Parameter Unit Min Max
Wobbeindedx (WI)a kWh/m3 13.60 15.81
Relative Density RDb m3 /m3 0.555 0.70
Total sulfur mg/m3 - 30
H2S + COS mg/m3 - 5
Mercaptans mg/m3 - 6
Oxygen mol-% - 0.001
Carbon Dioxide mol-% - 2.5
Water Dewpoint ˚C at 70 bar - -8
Hydrocarbon Dewpoint ˚C at 70 bar - -2 aThe Wobbe Index WI is defined as the higher heating value divided by the square root of the relative density RD b The relative density RD is defined as the gas density in relation to the density of air at standard conditions (0˚C,
1.01325 bar)
2.1. Pretreatment
Storage will be needed for quicklime, water, carbon dioxide and for gypsum. These storages
have an influence on the economy as they require investments and large areal. At Värö, there
are no unused silos or storages that could potentially be used. This would have been very
valuable as no investments had to be considered regarding the storage. The storage utilities
have not been presented in the process sheet above but will be taken into account in the
economy analysis for the process calculations.
2.1.1. Hammer mill
To reach the highest conversion of biomass to SNG, a uniform particle size of the bark is
necessary. This is due to that they will have the same residue time inside the gasifier. Therefore,
the bark has to be grinded before entering the gasifier as well as the drying utilities. There are
many different grinders that can produce the necessary size, and the economy aspect is
important. In this case, a hammer mill is installed to reach a particle size of about 30 mm.
Different sizes required for the different types of gasifiers are listed in table 2 below.
4
Table 2. Different particle size required for different gasifiers [Bio-SNG from Thermal Gasification – Process
synthesis, Integration and Performance].
Fixed bed Fluidised bed Entrained Flow
Input particle size [mm] 10-300 <50 <0.1
2.1.2. Drying of Biomass
As the bark contains a lot of water (up to 50 wt-%7), it has to be dried in order to obtain a high
energy value. Considerable amounts of energy would otherwise be used to evaporate water
inside the gasifier and the temperature would not rise as high compared to dry biomass. The
efficiency of the gasifier is generally increased significantly with lower moisture content of the
biomass, but is rarely dried below 10 wt-% due to economic considerations7. The biological
degradation (microbial degradation) of the fuel is also lower after the water levels have been
decreased and therefore it can be stored for a longer period of time8. As much as 2.5-3 % of the
biomass dry matter can be degraded due to biological degradation if it is kept at 35 wt-%
moisture level9. The degradation of dry matter is strongly dependent on storage time and what
sort of biomass that’s being used. The drying process could be built with three different
techniques;
Low-temperature air drying
Drying using steam
Flue gas drying
Drying demands energy which is supplied as electricity (blowing the hot gases with turbines
and rotation of biomass thus exposing it to the warm air) and as heat. There are four different
specific factors that has to be taken into account:
Evaporation enthalpy (most important; about 2650 kJ/kg H2O)
Heating of the biomass and the air
Heating of the drying ware
Heat losses to the surroundings
The biggest energy demand is supplied to evaporate water, about 2650 kJ/kg H2O. Hot air has
a higher solubility of water compared to cold air. Therefore, a smaller volumetric amount of air
is needed if the air is preheated. This leads to lower electricity costs for the fans that draw air
from outside. There are patented solutions as Mabarex Dry-RexTM that are designed to fit drying
of bark. According to Mabarex the temperature of the air has to be about 30-90°C which is
considered as excess heat.
Problems associated with biomass drying is emission of volatile organic compounds (VOC).
High temperature in the dryer leads to higher emissions and flue gases might contain impurities
which have to be treated10. Lower temperatures lead to lower emissions and lower temperatures
could be achieved by using excess heat that can’t be used anywhere else. This makes it very
attractive from a design perspective so that as little as possible of the excess heat goes unused.
These low- temperature drying systems have an energy demand of just above 2700 kJ/kg H2O
with a heat source of 80°C11. Figure 5 shows a basic flow chart for bark drying.
5
Figure 5. Basic flow chart of drying of bark.
In figure 6 below an example of a fluidized bed dryer is visualized.
Figure 6. Example of fluidized bed dryer12. Hot air is fed in the bottom and introduced to the biomass through small
holes in the bottom and removed as wet gas.
Air is first pre-heated in a heat exchanger with flue gases leaving the combustion chamber. The
air reaches a temperature of 30-90˚C after which the drying begins. As the drying begins, the
temperature of the air is decreased due to the evaporation of the moisture inside the biomass. If
the temperature of the air increases, the solubility of water in air increases. This will have an
impact on the amount of air that is necessary to reach a certain moisture level as visualized in
figure 7.
6
Figure 7. Amount (kg) of dry air necessary to evaporate one kilogram water as a function of dry air temperature.
Higher temperatures give much lower amounts of air needed9.
2.2. Gasification
After drying, the biomass is fed to the gasifier which is the major conversion step in the process.
Inside the gasifier, the remaining water (moisture) is evaporated and the biomass is converted
by pyrolysis into a char as well as gas. The chemical reactions that occur in the gasification is
seen below.
→ 𝑐ℎ𝑎𝑟 + 𝑡𝑎𝑟𝑠 + 𝐶𝑂2 +𝐻2𝑂 + 𝐶𝐻4 + 𝐶𝑂 + 𝐻2 + NH3 + (𝐶2 − 𝐶3) + 𝑖𝑚𝑝𝑢𝑟𝑖𝑡𝑖𝑒𝑠 (R1)
𝐶 +1
2𝑂2 → 𝐶𝑂 Δ𝐻𝑟
298 𝐾 = −109 𝐾𝐽/𝑚𝑜𝑙 (partial oxidation) (R2)
𝐶 + 𝐶𝑂2 → 2𝐶𝑂 Δ𝐻𝑟298 𝐾 = +172 𝐾𝐽/𝑚𝑜𝑙 (reversed Boudouard) (R3)
𝐶 + 𝐻2𝑂 → 𝐶𝑂 + 𝐻2 Δ𝐻𝑟298 𝐾 = +131 𝐾𝐽/𝑚𝑜𝑙 (steam gasification) (R4)
𝐶𝐻4 +𝐻2𝑂 → 𝐶𝑂 + 3𝐻2 Δ𝐻𝑟298 𝐾 = +159 𝐾𝐽/𝑚𝑜𝑙 (steam reforming) (R5)
𝐶𝑂 + 𝐻2𝑂 → 𝐶𝑂2 +𝐻2 Δ𝐻𝑟298 𝐾 = −42 𝐾𝐽/𝑚𝑜𝑙 (water-gas shift) (R6)
R1 and R2 represent pyrolysis while R2-R6 are gasification reactions.
The overall function of the gasifier can be seen in figure 8. The technology represents an
indirect gasification and are based on indirect fluidized bed technology with <50 mm required
particle size (table 2). Biomass is fed into the riser (1) and steam (or air, if nitrogen dilution of
the producer gas is not a problem) is fed to the bottom. The gasifier consists of a fluidized bed
which is comprised of sand and/or olivine. The particle size of the bed medium is 0.2 mm to
0.3 mm. The particles of the bed medium heat the biomass to about 850°C and the biomass are
to some extent converted to gas which creates an updraft in the riser. In the riser, pyrolysis takes
place. Larger solids, such as bed material and biomass pieces and char, falls back down into the
down comers.
7
In the combustion zone, particles such as char (which is carbon that have not been converted
into gas), tar and dust, burns at high temperature with air and heats the bed material to about
925°C.13 The combustor is typically operated at an air to fuel ratio of 1.2514. Flue gas leaves the
reactor and is further mixed with air and cooled. This technology’s name is Multipurpose
Integrated Lab-unit for Explorative and iNovative Achievements, called MILENA, and is
developed by Energy research Centre of the Netherlands, ECN.
Figure 8. Schematic overview of MILENA gasifier15.
Olivine as bed material show positive results regarding tar reduction in the producer gas and
also promotes the production of H2 in the CO shift reactions16.The loss of bed material is taken
care of by adding fresh bed material to the combustor continuously and therefore maintaining
the amounts necessary in the combustor. Low gasification temperatures gives a high yield of
methane but the lowest temperature limit (before the yield of methane is heavily decreased) is
about 750°C16. The producer gas consists mainly of carbon monoxide, hydrogen, carbon
dioxide, methane and water vapor. There are some trace components which have to be dealt
with prior to synthesizing methane. These components consist of particulate matter (ash and
bed particles), unsaturated hydrocarbons, tars and chars, sulfur, nitrogen compounds and alkali
metals. There are solutions to decrease the production of tars inside the gasifier by using
catalytic bed materials as mentioned before. However, post-gasification producer gas cleaning
technologies are mostly used16. Sulfur compounds that are present in the producer gas will
damage downstream catalysts and have to be reduced to well below 1 ppm.17
2.3. Particle removal, purification and gas treatment
2.3.1. Particle removal
The produced gas from the gasifier must be purified in several stages. This is due to that they
are corrosive for the system, harmful to the environment and their fouling in downstream heat
exchangers. Tars, both heavy and light tars, as well as cleaning of the gas from sulfur and
chloride is needed. Tars and heterocyclics are initially removed from a cleaning station of some
8
kind consisting of several stages which could be based by oil, water or another media. The one
used in this project is called OLGA and can be seen in figure 9. These OLGA utilities are
followed by the removal of the remaining unwanted substances.
Tars can be explained as very complex heterogeneous aqueous mixtures of organic molecules
(aromatics, phenols, bases, asphaltenes, preasphaltenes, and particulate matter) in a broad range
of concentrations related to the formation conditions (temperature, residence time pressure,
feedstock, reactor design). It can be divided into four sections: primary products, secondary
products, alkyl tertiary products and condensed tertiary products18.
The producer gas leaving MILENA is cooled down to 400°C (which is above the dew point of
the tar in the gas19) with a heat exchanger. The OLGA system consists of three stages which are
collector, absorber and stripper, all using liquid oil as working media. The first stage is the
collector that condenses heavy tars from the producer gas and also removes most of the
remaining dust (dust that did not get caught in the cyclone) with scrubbing oil. The second stage
handles removal of fine dust and entrained oil aerosols using a wet electrostatic precipitator (w-
esp). To the first scrubber through a separator heavy tars are condensed by the cooled scrubbing
oil. Once the remains are separated from the scrubbing oil it’s led back into the MILENA as
recycled feedstock together with the remains from the stripper20. In the third stage the absorber
removes light tars with scrubbing oil which is operated above the dew point of water to avoid
mixing of tars and water. The temperature of the liquid scrubbing feed in the absorber controls
the outlet temperature of OLGA, which is about 60-80°C21. The stripper, operated with air at
180°C, is regenerating the scrubbing oil used in the absorber.
OLGA gas cleaning system is developed ECN, and compudised by Dahlman industrial group
and is chosen because it generates a product with least unwanted compounds. The product gas
will be totally clean from heavy tars and light tars but contains about 1 % of heterocyclics. Also,
the dew point is well below 20°C, which is a lot higher for other systems. With low dew point
there is no tar condensation and fouling so the gas is applicable without any risk further in the
process.22
Figure 9. Simplified process flow diagram for OLGA cleaning system22.
9
The gas leaving the OLGA gas cleaning system is free of tars and dust. However, to guarantee
this a hot gas filter is installed downstream of the OLGA as seen in figure 10. Depending on
the size the filter contains different amounts of sintered metal fiber candles.
Figure 10. Hot gas filter21.
2.3.2. Hydrogenation
The gas stream out of OLGA contains small amounts of olefins, unsaturated hydrocarbons with
double c-c bonds, are created during the gasification. Without any removal of olefins it will
continue to be created and generate long chains of polyethylene and polypropylene etc. which
could be of major trouble inside the system. The olefins are removed by hydrogenation which
will saturate the double bonds of the hydrocarbons and form ethane and propane. This is done
with hydrogen in presence of a metal catalyst, often platinum or palladium, at about 150-200°C.
The reaction for ethylene to ethane is seen in reaction (1) below.23
𝐻2𝐶 = 𝐶𝐻2 +𝐻2𝑃𝑡, 𝑃𝑑→ 𝐻3𝐶 − 𝐶𝐻3 𝛥𝐻298
0 = −134 𝑘𝐽/𝑚𝑜𝑙 (1)
2.3.3. Water Gas Shift
To meet downstream process requirements, where the ratio of hydrogen to carbon monoxide
into the methanation step has to be as close as possible to 3. This is to receive a high conversion
of methane in the process. By using a reaction step called water gas shift (WGS), consisting of
one reactor with catalyst. In this reactor syngas will pass through a fixed-bed of catalyst where
CO and water is converted to H2 and CO2 according to the WGS reaction (2).
𝐶𝑂 +𝐻2𝑂 ↔ 𝐻2 + 𝐶𝑂2 𝛥𝐻2980 = −41 𝑘𝐽/𝑚𝑜𝑙 (2)
The reaction, depending on the catalysts, operates between 200°C and 500°C. The pressure
dependents for the reaction are small due to the stationary total mole. High moisture content
and low temperatures favor the right side of the reaction. The existing moisture from the
scrubber upstream is normally enough to drive the reaction to the decried ratio. To avoid
exceeding the H2-to-CO ratio a bypass stream of syngas may be needed.
10
The WGS reactor can be placed both before (sour shift) and after the sulfur removal step (sweet
shift). In this case it is crucial to the downstream process that the carbon dioxide is held to a
minimum. Therefore the sour shift is preferable. Another benefit with this placement of the
reactor is that the reactor will hydrate carbonyl sulfate (COS) and other organic sulfur to
hydrogen sulfide (H2S). This will allow the reactor for hydrolysis of COS to be smaller because
it only has to take care of the bypass stream. Sour shift uses a cobalt-molybdenum catalyst. To
avoid getting liquid water in the shift reaction and damaging the catalyst the syngas is heated
to about 20°C above the saturation temperature. After the shift the gas flow is cooled by
generating low pressure steam before entering the acid gas removal system for removal of
H2S.24
2.3.4. Hydrolysis
Most of the sulfur in the biomass is converted to H2S in the gasifier. However, some of it, about
3 % to 10 %, forms a carbon-sulfide component (COS). In the sulfur removal step the COS will
not be efficiently separated, so to remove enough COS to reach the expectable concentration
for the product of SNG, a hydrolysis step will be needed. COS is converted to H2S by reaction
(3).
𝐶𝑂𝑆 + 𝐻2𝑂 ↔ 𝐻2𝑆 + 𝐶𝑂2 𝛥𝐻2980 = −34 𝑘𝐽/𝑚𝑜𝑙 (3)
𝐶𝑆2 + 2𝐻2𝑂 ↔ 2𝐻2𝑆 + 𝐶𝑂2 𝛥𝐻2980 = −20 𝑘𝐽/𝑚𝑜𝑙 (4)
2𝑅𝑆𝐻 + 2𝐻2𝑂 ↔ 2𝑅𝐻 + 2𝐻2𝑆 + 𝐶𝑂2 (5)
As mentioned earlier the sour WGS will work as a hydrolysis step for the COS and an additional
reactor will only be needed for the by-pass stream passing the WGS-reactor. To avoid getting
liquid water in the reaction and damaging the catalyst the syngas is heated to about 20°C above
the saturation temperature. An activated alumina-based catalyst is used in the COS hydrolysis
and usually operates at a temperature of 175-200°C. The pressure dependents for the reaction
are small due to the stationary total mole. Because of the reaction’s exothermic nature the
conversion of COS is favored at a low temperature. The temperature is however almost constant
throughout the reactor due to the large amount of non-reacting components in the stream.
After the hydrolysis, the gas stream is cooled by generating low pressure steam before entering
the acid gas removal.25 26
2.3.5. Acid gas removal
Within production of SNG in connection with gasification some CO2 will form. The biomass,
bark in this case, contains low amounts of sulfur and chloride but still needs purification from
the product gas out of OLGA. About 90 % of the sulfur content out of OLGA converts into H2S
and 10 % into COS. Low concentrations of HCl, below 5 ppm follows within the raw producer
gas. The chloride is removed from the gas together with the ash.
There are two widely used methods for sulfur removal. One is by adsorption of sulfur on zinc
oxide (ZnO) and the other is amine absorption. An equilibrium reaction for the ZnO absorption
technique removal is seen in reaction (6). ZnO can be used as sorbent for removal of both H2S
and COS. Volatile compounds from reacted zinc with halogens might occur and these need to
be removed by a secondary guard bed. The most common technique for this is using activated
11
aluminum oxide, alumina27. 100 ppb as inlet concentration is acceptable according to
litterature29. An equilibrium reaction for the sulfur removal is seen in reaction (6).
𝑍𝑛𝑂 + 𝐻2𝑆 ↔ 𝑍𝑛𝑆 + 𝐻2𝑂 Δ𝐻2980 = −78 𝑘𝐽/𝑚𝑜𝑙 (6)
ZnO was used as sorbent, which can remove both H2S and COS, for the bulk removal of sulfur.
Remaining H2S is removed via a guard bed at 160°C and is also used for the removal of HCl.
Higher temperatures generate more volatile zinc compounds.27
The other widely used method for sulfur removal is the one implemented in this process. It
removes CO2 and H2S with amine absorption, which can be seen in figure 11. The absorption
system contains two large columns, one absorber and one stripper. The producer gas is fed into
the absorber via the bottom, while regenerated amine solution enters at the top. H2S and CO2
are absorbed into the amine solvent. When the absorption is done, the loaded amine solution is
preheated with the lean alkanolamine solution from the stripper and fed to the stripper. After
the acid gases has passed through the stripper, they are removed with steam generated in the
reboiler. This is fed to the condenser and later returns back into the regeneration column.
Figure 11. Flow scheme over removal of H2S by amine absorption28.
The amine absorption is performed with methyldiethanolamine with an additive of piperazine,
MDEA-PZ, because of the low energy demand for the regeneration compared to other amines
listed in table 3 below28. This is due to weaker bonds between CO2-amine for MDEA. It also
doesn’t form corrosive compounds so the additives, like piperazine, are mostly for
improvement of the mass transfer rate. Monoethanolamine, MEA, and diethanolamine, DEA,
have higher mass transfer rates but requires a lot more energy for the regeneration. A
comparison is seen in table 3. The reaction formula between CO2 and MDEA is seen below.
𝐻2𝑂(𝑙) + 𝐶𝑂2(𝑎𝑞) + 𝑀𝐷𝐸𝐴(𝑎𝑞) ↔ 𝐻𝑀𝐷𝐸𝐴+ +𝐻𝐶𝑂3−(𝑎𝑞)
Table 3. Concentrations over the solvents and energy requirements for removal of CO228.
12
Removal system Amine concentration (wt-%) Energy requirement [GJ/mol CO2]
MEA 15-20 210
MDEA-PZ 40-55 40-60
2.3.6. Methanation
In order to obtain a composition of gas that reaches the standards for natural gas the content of
methane has to be increased. To reach the required composition, a methanation stage is
required. This catalytic synthetic production of methane from hydrogen and carbon monoxide
is described by the CO methanation reaction (7):
𝐶𝑂 + 3𝐻2 → 𝐶𝐻4 +𝐻2𝑂 Δ𝐻2980 = −206 𝑘𝐽/𝑚𝑜𝑙 (7)
It’s also possible to convert carbon dioxide to methane as in the following reaction (8):
𝐶𝑂2 + 4𝐻2 → 𝐶𝐻4 + 2𝐻2𝑂 Δ𝐻2980 = −165 𝑘𝐽/𝑚𝑜𝑙 (8)
To get the right ratio of the components in to the methanation stage the WGS reaction is used
upstream the process.
Both reactions (7) and (8) are very exothermic and it requires low temperatures and high
pressures to get a high yield of methane.29
Technologies for methanation can be classified into two main categories: fixed bed and
fluidized bed. There are several different types of technologies in both categories. One of the
fixed bed technologies is Topsoe’s Recycle Energy-efficient Methanation Process, called
TREMP™30. Through figure 12 the TREMPTM is visualized.
13
700˚CR1
600˚CR2
400˚CR3
HE 13
HE 14
HE 16
HE 17
HE 18
HE 12
Compressor
Condensate
SNG to GRID
Compressor
250-300˚CR4
HE 20
HE 15
HE 19
Figure 12. Simplified process flow diagram for TREMP™ methanation.
The TREMP™ process is developed by Haldor Topsoe. This process converts CO and H2 with
a ratio of 3/1 into methane. The reaction that occurs is manly reaction 7. TREMP™ has a
chemical efficiency of about 80 % and produces a product with up to 98 % methane. The system
uses three or four adiabatic reactors with recycle and intermediate cooling. The temperature in
the first reactor is controlled by changing the reflux ratio. The concentration of reactants in the
stream entering the first reactor is controlled by recirculate parts of the stream leaving it. This
results in a lower temperature in the reactor. The catalyst is able to work in an interval between
250-700°C.
One of the advantages with this process is that, due to the MCR-2X methanation catalyst,
TREMP™ can run at fairly high temperatures, up to 700°C and therefore it’s possible to recover
a lot of the exothermic heat as high pressure steam, illustrated in figure 13. The high
temperature also makes it possible to lower the amount of methane that has to be recycled in
the process. Most catalysts used in methanation are ceramic based with nickel crystals as the
active part. The same goes for the MCR-2X.Any recycle involves a loss of energy but the MCR-
2X catalyst is a good choice to minimize the need for that, resulting in a more energy efficient
system and lower equipment costs. The high purity of methane in the product is compatible
with the specification for pipelines, ensuring easy distribution of the product.31
14
Figure 13. Illustration of the use of the excess heat31.
Before the TREMP™ the process is designed so that the feed in to the TREMP™ provides a
1:3 ratio of carbon monoxide and hydrogen according to the methanation reaction (Eq1). Figure
14 show how the composition of the gas from the TREMP™ varies with the value of the module
(M) As can be seen in the figure 14 it is important to get the module as close to 3 as possible to
get a high yield of methane in the product.
𝑀 =𝑋𝐻2,𝑓𝑒𝑒𝑑−𝑋𝐶𝑂2,𝑓𝑒𝑒𝑑
𝑋𝐶𝑂,𝑓𝑒𝑒𝑑+𝑋𝐶𝑂2,𝑓𝑒𝑒𝑑 𝐸𝑞(1)
Figure 14. Illustration of how the how the gas composition varies with the module31.
To change the ratio between CO and H2 the WGS reaction is used upstream to the methanation
stage. The module of the inlet gas is adjusted by controlling the by-pass around the WGS stage.
The gas that leaves the first reactor is cooled in two stages, the first will heat a super-heated
steam stream and the second one will cool it to the temperature wanted at the inlet of reactor
two (200-250°C). As can be seen in figure 15, low temperatures favor a high yeild of methane.
To get a high yeild it’s reqiured to use a series of methanation steps.
15
In TREMP™ the first reactor will operate close to the maximum allowed temperature for the
catalys (700°C). To operate at that temperature the stream into the first reactor should contain
about 20 % methane. The following steps the temperature will be decreased to get the yields
required. For 98 % methane for reactors will be needed. The last reactor will operate at 200-
300°C. Before the last reactor water will be separated from the gas stream to drive reaction 7
to the right.31
Figure 15. Illustrates the change in mol-% for methane over the reactors31.
The syngas composition will vary depending on what biomass that has been used in the process
and on the properties of the plants design parameters and conditions. In table 4 an example is
shown. In this case the amount of methane into the methanation was 15 mol-%.
The methanation was performed in four reactors at a product pressure of 2.4 MPa.31
Table 4. Example composition of the syngas leaving the TREMP™.
Substance Typical
composition
CH4 97.93 %
CO2 0.16 %
H2 1.36 %
N2 + Ar 0.53 %
CO 11 ppm
2.3.7. Gas upgrade
As the gas leaving the methanation step is a mixture of methane, carbon dioxide, water and
small amounts of trace elements such as nitrogen, hydrogen and carbon monoxide. It might
have to be upgraded before it enters the gas grid. However, the output concentration from the
methanation will be known first after the process has been fully simulated. If there is too much
carbon dioxide and moisture – an upgrading step will be installed and investigated to fit the
European Union standard requirements of natural gas (EASEE-gas, 2005). If the gas has to be
upgraded, the most important part is to remove carbon dioxide. This is a process which demands
a lot of energy and further investment costs.
Further upgrading of the gas consists of adding propane gas which will increase the energy
density necessary to reach the Wobbe Index (WI).
16
2.4. Desulfurization of flue gas leaving combustion chamber
As SO2 emissions cause detrimental impacts on human health, it has to be removed from the
flue gas leaving the combustion chamber which is connected to the gasifier before it is released
to the atmosphere through a chimney. Flue gas desulfurization also decreases the problematic
acid rain which is part of the Acid Rain SO2 Reduction Program32. Another benefit from
cleaning SO2 is the decreased amount of aerosols in the atmosphere and there are also
regulations regarding SO2 emissions that has to be fulfilled.
Flue gas desulfurization (FGD) is usually based on an alkaline reagent such as calcium or
sodium. The alkaline reagent is injected to the flue gas using a spray tower. The SO2 binds to
the reagent and creates a solid compound, calcium or sodium sulfate. There are two separate
main processes called “once-through” or “regenerable”. Regenerable systems reuse the solids
generated from the process and once-through processes dispose the solids as waste. Available
technologies are wet-, semi-dry and dry systems.
In dry systems, dry sorbent is injected into the furnace. This requires very high flue gas
temperatures ranging between 950-1000°C which is higher than the obtained flue gas
temperature in the MILENA technology where a maximum of 850°C is reached33. Therefore
the dry system cannot be used in this case.
In wet systems the flue gas is put into contact with a solution containing the sorbent. The gas
becomes saturated with water due to the water content in the slurry. The SO2 in the flue gas
reacts with the alkaline reagents in the slurry, creating calcium sulfate solid particles. These
particles are collected at the bottom of the absorber and collected. If the slurry is then oxidized,
gypsum scale is formed.
Semi-Dry systems injects a higher concentration of the alkaline reagent into the flue gas by
using spray dryers. Most of the water in the slurry is evaporated creating a dry excess product
which can be removed from the flue gas using a particulate matter (PM) collection device such
as an ESP. About 10-15°C below saturation temperature is the optimum temperature for semi-
dry spray dryers33.
About 85 % of all flue gas desulfurization (FGD) systems are based on wet systems34. Different
technologies have efficiencies in the range from 50-90 %. 90 % efficiency is reached when
using wet scrubbers. Typical temperatures for wet scrubbers are 150-370°C35 and therefore, the
flue gas from the combustion chamber has to be cooled using a heat exchanger before the
scrubber. As there is a potential pressure drop across the absorber, an additional induced draft
(ID) fan may be required. The reactions that occurs in the absorber can be summarized by:
𝑆𝑂2 + 𝐶𝑎𝐶𝑂3 +1
2𝐻2𝑂 → 𝐶𝑎𝑆𝑂3 ∙
1
2𝐻2𝑂 + 𝐶𝑂2 (10)
𝑆𝑂2 +1
2𝑂2 + 𝐶𝑎𝐶𝑂3 + 2𝐻2𝑂 → 𝐶𝑎𝑆𝑂4 ∙ 2𝐻2𝑂 + 𝐶𝑂2 (11)
The required amount of limestone in wet FGD systems is about 1 mole of CaCO3 per mole
SO2.36 Process variables include flue gas flow rate, SO2 concentration, liquid-to-gas ratio (L/G),
pH and retention time. Retention time is about 12-16 hours.
17
The chosen process used for flue gas desulfurization FGD is based on a wet system. Quicklime
is crushed using a Ball Mill into a fine powder with desired particle size. It is then mixed with
water in a feed tank. The flue gas is then mixed with the aqueous solution and the calcium
sulfate is collected at the bottom. In figure 16 the flue gas is inserted at the top of the spray
tower which is not the general case. In general, the flue gas flows upwards and the water is
sprayed downwards. An ESP device is used as particulate matter collector and the solid particles
is collected at the bottom and disposed of.
Figure 16. Typical process sheet of a wet FGD system using lime.
3. Overall process
Based on the above necessary utilities, a possible process scheme is presented below. The final
set up will have a high redundancy, meaning that some of the components (pumps, compressors
and heat exchangers) will have a double setup to ensure safety. In figure 17, a scheme over the
complete proposed process setup is presented. Table 5 below shows what every step of the
process changes. This is an overall simplified scheme that covers the idea of every unit
operation.
18
Table 5. Composition through the process. 1 represents that the component is present and 0 that it has been removed.
0.5 is somewhere in between meaning that the utility will remove part of the component in the gas.
MILENA CYCLONE OLGA Hydrogenation Hydrolysis/WGS Acid
gas
removal
TREMP
Ash 1 0.5 0 0 0 0 0
CO 1 1 1 1 1 1 0
CO2 1 1 1 1 1 0 0
CH4 1 1 1 1 1 1 1
Tars 1 1 0 0 0 0 0
H2 1 1 1 1 1 1 0
H2S 1 1 1 1 1 0 0
COS 1 1 1 1 0 0 0
S 1 1 1 1 0 0 0
Ethene/propene 1 1 1 0 0 0 0
Benzene 1 1 1 0 0 0 0
Particles(sand,
dust)
1 0.5 0 0 0 0 0
Heterocyclics 1 1 0 0 0 0 0
19
Fig
ure
17
. C
om
ple
te p
roce
ss s
chem
e fo
r p
rod
uct
ion
of
Bio
-SN
G f
rom
bio
mas
s.
20
The production plant suggested in figure 17 begins with a hammer mill where the bark is
grinded to a maximum size of about 5 mm after which the drying begins. The dryer is based on
a rotary drum dryer with counter current flow of preheated air through the vessel. After drying,
the bark will be stored in a silo before transportation to the amount of gasifiers required to cover
the input of 200 MWth. The gasification is carried out using a Milena gasifier after which a
cyclone will recover most of the char, sand and particles. These particulates will be combusted
in the combustion chamber after which the flue gas will be cleaned using a FGD system based
on quicklime.
The primary gas that leaves the Milena has a temperature of 850˚C and has to be cooled prior
the absorber and collector (the OLGA) apparatus. A heat exchanger is installed which will
produce steam that can be used downstream in the process. The Collector will collect
particulates and, together with the W-ESP also large tars. The gas will be cleaned even further
using an absorber in which light tars are removed to the countercurrent flow of oil. The rich oil
solution is restored in a stripper and recovered to the system.
To satisfy purity requirements downstream, additional filters (HGF) is installed downstream of
the absorber. The gas now enters hydrogenation where unsaturated hydrocarbons (double c-c
bonds) becomes saturated and create mostly ethane and propene in the presence of platinum or
palladium catalyst.
The following step is hydrolysis which converts most of the sulfur from the biomass to H2S and
COS. This is installed closely to the WGS-reactors where CO and water is converted to H2 and
CO2 according to the WGS reaction (2). Heat exchanger #9 in figure 17 will cool the gas
intermediately. The following step consists of removing almost all of the sulfur components
which is obtained by absorption using MDEA-PZ amine. These components are recycled to the
combustion chamber, thus help drive the gasification process.
The final step is the methanation step which is based on fixed bed technology, called
TREMP™. Here, methane is produced to methane from hydrogen and carbon monoxide using
four reaction vessels and several heat exchangers. Before the gas can be inserted to the
TREMPTM process the pressure has to be increased to about 24 bar using compressors.
In table 6 all the compositions have been listed after each sub-process. The final gas
composition is not entirely qualified to be injected into the gas grid when compared to the gas
quality requirements from European Association for the Streamlining of Energy Exchange, in
table 1. This is because there is too much carbon monoxide present in the gas (maximum
allowed amount if 1 ppm).
21
Table 6. Complete gas composition through the proposed process seen in figure 17. The simulations were carried
out using Aspen and MATLAB.
MILENA OLGA HYDG WGS/HYDR Acid gas
removal
TREMP
N2 0.06 % 0.06 % 0.061 % 0.06 % 0.16 % -
CO2 7.35 % 7.367 % 7.554 % 11.72 % 0.03 % 0.45 %
CO 10.34 % 10.377 % 10.640 % 6.47 % 17.39 % 19 ppm
H2 17.56 % 17.638 % 15.247 % 19.42 % 52.16 % 0.57 %
CH4 5.20 % 5.216 % 5.348 % 5.35 % 14.37 % 95.62 %
H2O 57.08 % 57.245 % 58.695 % 54.53 % 9.33 % 3.35 %
H2S 100 ppm 80 ppm 80 ppm 100 ppm 1 ppm 1 ppm
COS 9 ppm 10 ppm 10 ppm - - -
H3N 600 ppm 640 ppm 650 ppm 700 ppm 1 800 ppm 650 ppm
C2H2 0.10 % 0.105 % - - - -
C2H4 1.66 % 1.666 % - - - -
C2H6 0.10 % 0.105 % 2.38 % 2.38 % 6.39 % 50 ppm
C6H6 0.42 % 0.149 % - - - -
C7H8 50 ppm - - - - -
As can be seen in table 6 the gas does not meet the requirements. It could be altered by adding
a flash apparatus to the process flow sheet in order to remove a lot of water. The carbon
monoxide levels has to be decreased which should be taken care of in the bypass before the
WGS reactor. However, there have been some issues regarding the robustness of the
calculations in this case and the model have been problematic.
The total received composition out of TREMPTM nearly corresponds to the demands for
injecting it into the gas grid. Methane have a higher heating value (HHV) of 55.53 MJ/kg and
the after simulations in Aspen showed that the received flow rate was 1.7 kg/s. A value of 94.4
MWth from 200 MWth input of bark gives a chemical efficiency of 47.2 %.
Calculations for the energy output and the total chemical efficiency is seen below, Eq(14-15).
𝑄𝑜𝑢𝑡 = 1.7𝑘𝑔𝐶𝐻4𝑠∙55.53 𝑀𝐽
𝑘𝑔= 94.4 𝑀𝑊 𝐸𝑞(14)
𝜂𝑐ℎ𝑒𝑚 =𝑄𝑜𝑢𝑡
𝑄𝑖𝑛=94.4 𝑀𝑊
200 𝑀𝑊= 47.2 % Eq(15)
4. Discussion literature review
When different industrial gasification technologies were investigated and studied, no laboratory
scale gasifiers were included in the project. Only up to date, large scale gasifiers, gas cleaning
and upgrading utilities were compared. However, there are several different technologies which
have been proved promising in laboratory scale.
Due to time constraints there have not been any in depth studies in the matter of different
process utilities. As mentioned before, time was of essence and therefore process utilities were
22
put together without optimization calculations for each utility. In further work, several in depth
studies have to be carried out at each and every utility to maximize revenue.
The combined process of MILENA, OLGA and TREMP™ has been chosen because of their
overall efficiency as well as lower investment and operating costs than their alternatives. The
production plant renders an input of 200 MWth which will demand an upscaling about ten times
of the gasifier. Not to mention along with all the production equipment such as vessels,
pipelines, pumps etc.
5. Method for cost estimates
To determine and investigate the feasibility of the SNG production plant an economical
evaluation was carried out. Capital and operating costs have been taken into consideration.
Detailed tables and calculations are found in appendix B.
5.1. Operating costs
Operating costs are divided into three sub groups, direct-, indirect- and fixed capital costs.
Direct costs include raw materials, catalysts, solvents, labor and utilities. Catalysts are lost due
to abrasion during usage. They also have a certain available lifetime including a number of
cycles before degeneration occur. This include purchase costs for the chemical company using
them. Solvents are lost due to leaks, incomplete recovery and degeneration. Utilities include
electricity, cooling/process water, compressed air, waste treatment and energy.
5.2. Capital costs
A capital cost estimation was carried out according to the Ulrich method37. The equipment’s
total contribution to both indirect and direct construction cost, CBM, is calculated using the
equation below, Eq(12).
𝐶𝐵𝑀 = 𝐶𝑃 · 𝐹𝐵𝑀 𝑎 𝐸𝑞(12)
CBM is the installed module cost, CP is the purchased equipment cost. FaBM is an addition factor
which takes both the material and different process parameters into consideration but also
installation costs, land improvements, transportation, piping, materials, labor for installation
and other costs associated to the apparatus. All costs are seen in appendix B.
To determine the necessary sizes for different process vessels the macroscopic behavior within
the unit is not considered. Instead, the relation between the inlet and the outlet streams are
compared using mass and energy balances for each vessel inside the process. Different process
vessels are calculated based on normal gas/liquid velocities and catalyst vessels including
reactors are based on necessary residence times.
23
The module costs will sum up to the total capital cost of the plant according to the equation
below in which ffees represents contingency and contracting and fauxiliary takes auxiliary
equipment and buildings into consideration, seen in Eq(13).
𝐾2004 = (∑ 𝑐𝐵𝑀𝑖𝑛𝑖=1 ) · 𝑓𝑓𝑒𝑒𝑠 · 𝑓𝑎𝑢𝑥𝑖𝑙𝑖𝑎𝑟𝑦 𝐸𝑞(13)
As the process has fulfilled its requirements and cannot operate further, the process utilities
could be sold. In this case, as the project is based on worst case scenario, the final value of the
process equipment after expected lifespan is set to zero.
6. Economical evaluation
This part contains calculations and assumptions regarding all process utilities used for the
production of synthetic natural gas, SNG. All calculations are discussed separately after each
part and will provide the reader with a good overview. Each section contains a short
introduction and a brief discussion regarding the approach in which the problems have been
handled. Finally, the total cost for a green field erection is compared to an integration process
at Södra Cell Värö. This provides a total process cost for both processes.
The capital cost is calculated using Eq(13). Where ffees is about 1.15 and fauxiliary = 1.30 for green
field plants. As the brown field erection is considered an upgrade, the fauxiliary factor is set to
1.00 for this plant.
The total cost for the brown field was calculated to 860 Mkr and for green field installation the
cost was 1 118 Mkr. The annual net income was calculated to 130 Mkr.
The cost for the storage of bark was calculated using annuity method with a life span of 20
years and an interest rate of 10 %. With a storage time for the bark of three days gives an annual
cost of 225 000 kr/yr.
The payback time without interest date was calculated accordingly:
𝑇 =𝐺
𝑎
and with consideration of 10 % interest rate calculated as:
𝑛 = −(ln (1 − 𝐺 ∙
𝑋
𝑎)
ln(1 + 𝑋))
A payback time of 7 and 11 years, respectively, was obtained for the base case.
In table 7 a complete list of the base case items are gathered.
24
Table 7. Compiled list for the base case scenario.
Investment G (kr) 860 000 000
Residual value 0
Yearly incomes and costs
Number of employees (st) 10
Salary/person (kr/yr) 750 000
Salary (kr/yr) 7 500 000
Maintenance (kr/yr) 43 000 000
Steam
Steam price (kr/GJ) 90
Steam production (GJ/yr) 560 000
Steam sales (kr/yr) 50 400 000
Bark
Bark price (kr/GJ) 37
Bark input (GJ/yr) 6 220 800
Bark purchase (kr/yr) 230 169 600
Restricted equity in bark (kr) 225 000
SNG
SNG price (kr/GJ) 124
SNG production (GJ/yr) 2 908 224
SNG sales (kr/yr) 360 619 776
Catalyst
Cost (kr/yr) 2 670 000
Annual net income
a (kr/yr) 130 000 000
Interest rate (10 %) 0.1
Payback T = G/a
T (yr) 6.7
Payback with interest rate (10 %)
n (yr) 11.8
The payback method based on an interest rate of 10 % was used to create figure 18-22. To
visualize the sensitivity and the influence of market prices, a sensitivity analysis was carried
out based on fluctuating bark prices, SNG-prices and steam prices. The total investment cost
and the number of shift workers at the process was changed to develop an understanding of
where the costs are located. In the base case, bark was assumed to be purchased at 37 kr/GJ,
SNG to be sold at 124 kr/GJ and steam to be sold for 90 kr/GJ.
25
As can be seen in figure 18, a slight increase of the bark price would have large unfavorable
impact on the payback time. As much as a few percent would lead to significant changes in the
process economy.
Figure 18. Sensitivity analysis of fluctuating bark prices. A small change towards higher bark prices gives a
significant impact on the payback time.
In figure 19 an increase in SNG prices would lead to shorter payback times according to the
payback method. If the price of bark would decrease at the same time as the price of SNG
increased, there would be significant changes in the payback time. Furthermore, the steam
should be sold to increase revenue, and depending on the price the outcome fluctuates.
Figure 19. Sensitivity analysis of fluctuating SNG prices.
15 20 25 30 35 40 454
6
8
10
12
14
16
18
20
22
24Payback
Bark price kr/GJ
Payback t
ime in y
ears
110 120 130 140 150 160 1704
6
8
10
12
14
16
18
20Payback
SNG price kr/GJ
Payback t
ime in y
ears
26
In figure 20, a sensitivity analysis was carried out at the steam price. This is to visualize the
importance of selling the steam to a high price. It is clear from the figure that the investment
will not be profitable if the steam can’t be sold for above 70 kr/GJ.
Figure 20. Sensitivity analysis of fluctuating steam prices. There is a high importance of selling the steam to a high
price to increase revenue.
Figure 21 shows the payback time for the current product and bark prices with a change in
investment cost of ± 30 %.
Figure 21. Sensitivity analysis of the investment cost ± 30 %.
20 30 40 50 60 70 80 90 10010
15
20
25
30
35
40Payback
Steam price kr/GJ
Payback t
ime in y
ears
6 7 8 9 10 11 12
x 108
5
10
15
20
25
30
35
40Payback
Investment cost kr
Payback t
ime in y
ears
27
Figure 22 below shows a sensitivity analysis over number of employees.
Figure 22. Sensitivity analyses of the amount of employees needed at the plant.
7. Discussion
This project was based on commercial available gasification technologies and not promising
laboratory scale gasification techniques. However, these promising projects might help reduce
capital costs and increase efficiency in the future which will enhance SNG production in total.
The capital cost for the different apparatus in this process was calculated using the Ulrich’s
method which could lead to a slight different outcome.
As the process develops high pressure steam (100 bar at about 5 kg/s) this should be sold or
used somehow to increase revenue. If there is a strong need in the surrounding industries for
high pressure steam, the steam would reach high prices (at efficiencies of 80 % of turbines, the
price could correspond to the price of natural gas divided by 0.8). However, if there is not a
steam demand nearby, the price could also be set to zero as there would be nowhere to use it.
This gives a very varying economic situation which has to be taken into consideration. The
annual net income from steam in table 7 could therefore be very different from the base case.
Analyzing the composition in the steps downstream from the MILENA shows clearly that a big
part of the gas flow contains water. Some water is required in the WGS and the hydrolysis.
Throughout the simulation it’s clear that the amount of water is more than sufficient. Therefore
it could be possible to reduce the size of all vessels, pipes etc. if the water in the gas flow is
reduced to the amount needed for the downstream reactors.
In appendix C, the Aspen flow sheets of the combustion chamber can be seen to operate without
an inflow of the components removed from the acid gas removal. These will have impact on
10 12 14 16 18 20 22 24 26 28 3011.5
12
12.5
13
13.5
14
14.5
15
15.5Payback
Number of employee
Payback t
ime in y
ears
28
the energy of the flue gas leaving the combustion chamber and will also increase the amount of
flue gases. However, these values were neglected. This might have a small impact on the heat
exchanger areas nearby. The energy in the recirculated chars, tars and sulfuric components are
assumed to have enough energy to supply the Milena gasifiers.
In this project, the site location have not been taken into consideration. However, as the price
of biomass and products could consist of about +40 % transportation costs, the site location
have a huge influence on the economy evaluation in total. Furthermore, if the product could be
sold nearby or injected straight away onto the gas grid, it would be very profitable. These
considerations have not been evaluated, as well as Väro’s potential electricity production which
is influenced by the electricity price. In a future study, these considerations should be interesting
to discuss further.
The familiarity at handling large amounts of biomass at Värö would decrease the number of
personnel necessary at each shift. According to a rule of thumb, about 1/3 of the total number
of personnel at a new plant would be needed at a plant like Värö. Furthermore, as annual salary
is just a fraction of the cost of the bark this would not have a great impact of the payback time,
which are illustrated in figure 18 and 21.
29
8. Conclusions
Using the base case with today’s prices, the plant would have payback time of about 10 years.
However, as mentioned in the discussion, the payback time is strongly dependent on the price
of energy which fluctuate heavily from time to time. Further, as there might be a need for high
pressure steam nearby, the steam could be sold for about the same price as for the natural gas.
In this case, the price for bio-SNG is slightly higher compared to natural gas as there are both
tax incentives which promotes the bio-SNG.
See appendix B. With today’s prices, the payback time is pretty good but the income changes
rapidly with the prices of products and biomass which indicates an unreliable investment.
The literature review was developed to construct a solid fundament on which the process should
be designed. The objective was to determine whether or not this process should be built at all,
if it should be integrated to a pulp and paper industry or as a green field erection. However, as
the apparatus found on site at Värö will not have major influence on the handling of biomass
nor the handling of bark and gasification, one has to have a broader view of the problem. The
employees at Värö have valuable knowledge in this regard which could be of great value when
constructing a new plant. Though, this knowledge is hard to put a price tag on.
Värö do not have further, unused storage capacity of bark but they do have a steam network
and a steam generator which could make valuable electricity from the high pressure steam. If
there is a strong demand of high pressure steam at Värö, the steam produced could be of high
value and very useful, or the electricity could be sold and injected onto the grid. Also, tax
incentives could change the outcome of this newly developed technology. Nevertheless, as
there is a new government every 4th year, calculations regarding tax incentives should be treated
rather as a bonus than anything else.
If the bark could be purchased at a very low price, as would be the case if the company would
harvest bark from the company’s own forest, the economy analysis would be different.
30
9. References
1 Asif M, Muneer T. Energy supply, its demand and security issues for development and emerging
Economies. 29 November 2005. School of Engineering, Napier University UK. Available from:
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33
APPENDIX A CALCULATIONS
In this Appendix A, “Calculations” some calculations are compiled to provide the reader
knowledge regarding the apparatus design and size.
HANDLING OF BARK
Calculate how many kg of bark that represents 200 MWth. Use this value to decide how many
kg of water that have to be evaporated from the bark (50 % wet in, and 10 % out) → necessary
energy for evaporation will be known and then we can calculate the volumetric amount of air
needed in the dryer. This amount of air will decide how many and how much energy that is
needed for the fans.
Table HB1. Summary of component balance in bark38
Dry Weight of constituents
Carbon (C) Oxygen (O) Hydrogen (H) Nitrogen (N) Ash
Bark Content
(%)
50.6 40.7 5.9 0 2.8
In Eq (17) A = Ash, Hcal higher heating value, hvap water 1bar, H hydrogen content F = moisture
content Higher heating value Norway spruce = 4.76 Kcal/kg39.
𝐻𝑏𝑖𝑜𝑓𝑢𝑒𝑙 = (1 − 𝐹) ∙ (1 − 𝐴)𝐻𝑐𝑎𝑙 − 𝛥ℎ𝑣𝑎𝑝((1 − 𝐹) ∙ 8.94 ∙ 𝐻 + 𝐹) = 14MJ
kg 𝐸𝑞(16)
Total amount of bark is calculated using Eq(17).
𝑚𝑏𝑎𝑟𝑘 = (1 − 𝐹) ·200 𝑀𝑊
𝐻𝑏𝑖𝑜𝑓𝑢𝑒𝑙= 11.5
𝑘𝑔
𝑠 𝐸𝑞(17)
Total net input of biomass to the dryer is twice as large due to its water content (22 kg/s). The
total amount of water driven of is:
𝑚ℎ2𝑂 = 𝑚𝑏𝑎𝑟𝑘 −𝑚𝑏𝑎𝑟𝑘 · 𝐹 = 9.2 𝑘𝑔
𝑠 𝐸𝑞(18)
The amount of air is calculated by using mollier diagram. Start temperature of air is set to 10-
20˚C with maximum of 0.02 kg water/kg air (this is corresponding to a relative humidity of 100
% which is worse than the worst case scenario). Final temperature of air (after preheating) is
80˚C with a maximum water content of 0.045 kg/kg.
FANS FOR DRYING OF BARK
The necessary amount of air is calculated using Eq(19).The total amount of energy required for
drying of biomass is about 2700 kJ/kg water evaporated. This value include heating of the
biomass as well as evaporation of water.
𝑚𝑎𝑖𝑟 =𝑚ℎ2𝑂
(𝑋𝑢𝑡 − 𝑋𝑖𝑛)= 306
𝑘𝑔𝑎𝑖𝑟𝑠
𝐸𝑞(19)
34
With a density of 1kg/m3 this equals 306 m3/s of air required for the fans. The energy needed
for the dryer is:
𝐸𝑛𝑒𝑟𝑔𝑦𝑑𝑟𝑦𝑒𝑟 = 2700𝑘𝐽
𝑘𝑔· 12
𝑘𝑔
𝑠= 32 400
𝑘𝐽
𝑠
The fan installed for this purpose is a centrifugal backward-curved fan. One fan is used, with a
capacity of 500 standard m3 per second at 1 atm pressure and 273 K using Ulrich’s method
which was described before and according to graph figure 5.29 p 379.
𝐶𝐵𝑀 = 𝐶𝑝 · 𝐹𝐵𝑀 · 𝐹𝑝 Eq(20)
Eq(20) is used to determine the final purchase cost for the fans. Table TF1 shows received data
for the fan.
Table TF1. Parameter values for calculation of purchase cost of fan equipment.
Parameter Value
Cp 5·105
FBM (Carbon steel) 2.2
FP (1 kPa) 1
CBM ends up at a final price of:
𝐶𝐵𝑀 = 5 · 105 · 2,2 · 1 = 1.1 · 106 𝑈𝑆𝐷
STORAGE OF BARK
The storage of bark will need a capacity of 3 days of full SNG-production without any delivery
of biomass. The total mass will be, according to equation ES1 about 3000 ton of bark.
𝑀𝑠𝑡𝑜𝑟𝑎𝑔𝑒 = 11.5𝑘𝑔𝑓𝑢𝑒𝑙
𝑠· 3 600
𝑠
ℎ· 24
ℎ
𝑑𝑎𝑦· 3 𝑑𝑎𝑦𝑠 ·
1
1 000
𝑡𝑜𝑛
𝑘𝑔= 3 000 𝑡𝑜𝑛 (𝐸𝑆1)
The bark density is about 105-135kg/m3 when dry which corresponds to a total volumetric
storage capacity of:
𝑉𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 = 3 000 𝑡𝑜𝑛 · 1 000 𝑘𝑔
𝑡𝑜𝑛· 1
105
𝑚3
𝑘𝑔= 29 000 𝑚3
The bark is stored in piles with an angle at the top of the cone of 50˚ and a height of 12 m. The
radius is calculated using equation ES2.
𝑟𝑏𝑜𝑡𝑡𝑜𝑚 = 𝐶𝑜𝑠(40˚)
𝑆𝑖𝑛(40˚)· 12 𝑚 = 14.30 𝑚 (𝐸𝑆2)
35
The volume of 1 cone will be the following:
𝑉𝑐𝑜𝑛𝑒 = 𝜋 · 𝑟2 · ℎ
3= 2 569
𝑚3
𝑐𝑜𝑛𝑒
The amount of piles is calculated:
𝑛𝑐𝑜𝑛𝑒𝑠 = 29 000 𝑚3 ·
1
2 500
𝑐𝑜𝑛𝑒
𝑚3= 12 𝑠𝑡
The total amount of area necessary is:
𝐴𝑡𝑜𝑡 = 𝜋 · 𝑟2 · 𝑛𝑐𝑜𝑛𝑒𝑠 = 𝜋 · 14.3
2 · 14 = 9 000 𝑚2
The cones will not be placed right beside each other. They must be reachable and therefore, a
room in between the piles of 5 m is believed to be necessary. The piles are placed in 4∙3 with 5
m road in between each pile.
𝐴𝑊𝑖𝑡ℎ𝑟𝑜𝑎𝑑𝑠 = 𝑑𝑝𝑖𝑙𝑒 · 𝑛𝑝𝑖𝑙𝑒 + 5 · 𝑛𝑟𝑜𝑎𝑑𝑠 = (30𝑚 · 4 𝑝𝑖𝑙𝑒𝑠 + 3 · 5) · (30 · 3 + 2 · 5)
= 13 500 𝑚2
The construction cost this area will be added to the final process unit with different variables.
BARK DRYER
The dryer will be based on a rotary dryer. The cost is based on figure 5.33 p 381. The cost for
the dryer will be related to the necessary Volume. To calculate this, the bark density was set to
105-135 kg/m3 when dry.40
With a density of 135 kg/m3 dry substance give a total volumetric flow of biomass to about 0.1
m3/s as Eq(21).
1
135
𝑚3
𝑘𝑔· 12
𝑘𝑔
𝑠≈ 0.09
𝑚3
𝑠 𝐸𝑞(21)
The residence time is set to 2 minutes which gives a total volumetric flow of bark to 10.8 m3.
The bark is set to be 1/10 of the total volume of the rotary drum. This gives a necessary drum
of 100 m3. The following parameters are compiled in table TD1 for calculation of the purchase
cost of the dryer.
Table TD1. Compiled parameters for purchase cost of dryer.
Parameter Value
V 100 m3
Cp (Direct rotary dryer) 2 ·105
FBM (stainless steel) 4.5
Using the following equation for the total purchase cost is: 𝐶𝐵𝑀 = 𝐶𝑝 · 𝐹𝐵𝑀 = 2 · 105 · 4.5 =
9 · 105 𝑈𝑆𝐷. This cost is complete including drives.
36
TRANSPORTATION OF BIOMASS (BARK)
The transportation of crushed, biomass to the dryer and from the dryer to the MILENA utilities
is carried out using conveyor belts. As there are 10 different MILENA’S, the conveyor belt will
transport the biomass to a silo in which the bottom is connected to pipes with valves that control
the amount of biomass to each MILENA utility.
For the conveyor, a closed belt conveyor is designed to carry out the work. From the dryer to
the silo a distance of 30 m is believed to be sufficient enough. The purchase cost parameters
are obtained from figure 5.14 p 372 and compiled in table C1.
Table T1. Compiled parameters for conveyor belt purchase costs.
Parameter Value
Cp 2.5·105
Conveyer distance (m) 30 m
Width (m) 1.5 m
FBM (closed belt) 2.4
These values are inserted to equation below. This cost is purchased equipment cost including
drives.
𝐶𝐵𝑀 = 𝐶𝑃 · 𝐹𝐵𝑀 = 2.5 · 105 · 2.4 = 6 · 105 𝑈𝑆𝐷
BARK CRUSHER (MILL)
As the bark has to be grinded to smaller pieces, a crusher is installed before the dryer. The dryer
is installed after the crusher to increase the drying efficiency. The calculations are made for a
hammer mill. The total mass of bark to the crusher is about 45 kg/h.
Table C1. These parameters represent the necessary values for calculations regarding the crusher cost.
Parameter Value
Cp 2.5·105
FBM (hammer mill) 2.8
Discussion
Recirculation of air could be implemented in the drying system which would increase the
efficiency. This has not been included in this project and in these calculations. A worst case
scenario of the inlet air has been chosen and the efficiency will be higher during most time of
the year.
MILENA
The MILENA gasifier consists of 10 different vertical vessels with 20 MWth each. The
maximum gas velocity inside them is set to 10 m/s and a residual time of 1.5 s. With a total
amount of gas produced (received from Aspen simulations) of 77 m3/s the total flow per
MILENA is about 8 m3/s.
𝐴𝑚𝑖𝑙𝑒𝑛𝑎 = 8𝑚3
𝑠·1
10
𝑠
𝑚= 0.8 𝑚2
𝐷 = √𝐴𝑚𝑖𝑙𝑒𝑛𝑎 · 4
𝜋 ≈ 1 𝑚
ℎ = 𝑣𝑔𝑎𝑠 · 𝑡𝑟𝑒𝑠𝑖𝑑𝑢𝑎𝑙 = 10𝑚
𝑠· 1.5 𝑠 = 15 𝑚
37
TARS
The recycled tars from the OLGA purification step will be recycled to the combustion chambers
to drive the gasification process. Therefore, the lower- and higher heating value (LHV, HHV)
has to be calculated. The compositions of the tars is heavily influenced by reactor type,
temperature and used biomass. Therefore, it is very difficult to determine exact composition in
different cases. However, a general assumption carried out by Mason and Ghandi41 in which
XCtar is the mass percent of carbon, XHtar is the mass percent hydrogen and XOtar is the mass
percent oxygen.
𝐻𝐻𝑉 = 340.95 · 𝑋𝐶𝑡𝑎𝑟 + 1322.98 · 𝑋𝐻𝑡𝑎𝑟 − 119.86 · 𝑋𝑂𝑡𝑎𝑟
As the composition varies with temperature, an assumption that the tars can be represented by
lumped hydrocarbons was made42. These hydrocarbons have different heating value depending
on their gasification temperature. These temperatures and corresponding heating values are
listed in table T1.
Table T1. Different heating values for different temperatures. Corresponding to lumped hydrocarbons.
Temperature interval (K) Heating value (MJ/kg)
673-923 22-26
973-1273 40
To verify this heating value of 40 MJ/kg, this value have been double checked with
corresponding heating value for different components of the tars. As can be seen, the amount
of 40 MJ/kg seems reasonable.
Table T2. Compiled heating value for the different major components of the tars.
Component Lower heating value (MJ/kg)
Benzene 40.3
Toluene 40.6
Naphthalene 40.2
H2S 17.4
Phenol 31.9
The temperature of the MILENA is about 1100 K the heating value for further calculations is
set to 40 MJ/kg.
DISCUSSION CONCERNING TARS
The tar composition can vary in many ways depending on the residence time, gasification
temperature and the use of biomass. However, this will not have a major impact on the economy
calculations in this report and therefore, no further investigations regarding the tars have been
made. The heating value of tars is, according to literature42, between 27 MJ/kg to 40 MJ/kg
and stays in this interval even if the current biomass is swapped for another. The temperature
has the major influence in this energy density of the tar.
38
OLGA
For removal of tars OLGA is used and it’s modelled as two process vessels in Aspen but
calculated as three vertical vessels. Also within the gas treatment station a w-esp, three pumps,
a cooler and a separator was the cost calculated for.
The OLGA process units consists of 3 vertical columns with 12 trays in each one. Between
each tray, there has to be enough space for a man to climb in and clean the utilities. This space
is set to 80 cm/tray. In the bottom as well as in the top additional 1.5 m is added in both the
bottom and the top. This gives a total height of 13m.
ℎ𝑂𝐿𝐺𝐴 = 0.8 · 12 + 2 · 1.5 ≈ 13 𝑚
The total gas flow to the OLGA utilities is 12 m3/s and a total maximum gas velocity inside an
absorber is about 3 m/s. This gives a total area of 4 m2, which gives a diameter of 1.13 m. The
material is Stainless Steel and the cost is calculated for vertical vessels by using the Ulrich’s
method.
The cost for the 3 different OLGA vessels is calculated to 3 600 000 USD.
W-ESP
With the total gas flow to the W-ESP the total cost can be calculated. The gas flow is about 70
m3/s and the total cost of the W-ESP becomes 4 510 000 USD according to the Ulrich method.
PUMP 2, 4, AND 5
Total flow to these pumps is 500 kmol/h of Dotriacontane (C32H66) and the density for the oil
solution is about 812 kg/m3 and the molar weight is 450 kg/kmol. The height difference is
approximately 15 m and the pump used are centrifugal pumps. A pump efficiency of 95 % was
used for cost calculations. However, friction is not considered a problem for these pumps.
Equation P1 was used for calculations where q is the flow capacity (m3/h), ρ is the density
(kg/m3), h is the height difference (m) and g is (9.82 kg/s2).
𝑚𝑝𝑢𝑚𝑝 = 500𝑘𝑚𝑜𝑙
ℎ· 450
𝑘𝑔
𝑘𝑚𝑜𝑙·
1
3 600
ℎ
𝑠= 62
𝑘𝑔
𝑠
𝑝𝑝𝑢𝑚𝑝(𝑘𝑊) =𝑞 · ℎ · 𝑔 · 𝜌
3.6 · 106
The shaft work required for these pumps is about 10 kW. This gives a total cost using Ulrich’s
method to 42 500 USD / pump · 3 pumps = 127 500 USD.
CHAR
During pyrolysis and gasification of biomass the amount of char formed decrease with higher
surrounding temperatures4242. Using cyclones, the char will be recycled to the combustion
chamber, producing energy to help drive the gasification process.
The mass percent of char of the combustible part of the fuel created during pyrolysis can be
determined from the equations C1, C2, C3 below42 or from laboratory experiments. Where C1
represents biomass from pinewood and bark and the other represent biomass constituents.
39
𝑌𝑐ℎ𝑎𝑟 = 180 · 𝑒(−0,0037·(𝑇−273)), 𝐶1
𝑌𝑐ℎ𝑎𝑟 = 90 · 𝑒(−0,0027·(𝑇−273)), 𝐶2
𝑌𝑐ℎ𝑎𝑟 =5
(1 − 1.25 · 𝑒(−5 · 0,0002·(𝑇−273)), 𝐶3
Models from the literature were chosen to model the combustion heating value of chars43. These
are compiled in equation C4, C5 below.
𝐻𝑐ℎ𝑎𝑟 = 16700 +2930
𝑌𝑐ℎ𝑎𝑟 , 𝑦𝑐ℎ𝑎𝑟 > 0.7, 𝐶4
𝐻𝑐ℎ𝑎𝑟 = 34000 , 𝑦𝑐ℎ𝑎𝑟 < 0.7, 𝐶5
Another way to determine the heating value of tar is to calculate the heating value by using the
molar percent of carbon, hydrogen and oxygen in the chars. The molar percent of carbon
increases with temperature and the molar percent of hydrogen and oxygen decrease with higher
temperatures. To determine these amounts, different empirical expressions can be used. To
determine the amount of carbon in the char equation C6 is used. Hydrogen, equation C7 and
oxygen equation C8.
𝑋𝐶𝑐ℎ𝑎𝑟 = 98
(1 + exp [−98 · 0.00035 · (T − 273)], 𝐶6
𝑋𝐻𝑐ℎ𝑎𝑟 = 53 · exp[−0.00177 · (𝑇 − 273)] , 𝐶7
𝑋𝑂𝑐ℎ𝑎𝑟 = 25 · exp[−0.0027 · (𝑇 − 273)] , 𝐶8
As soon as these percentages are known, the following expression found in literature44, equation
C9 can be used to determine the heating value of the char42.
𝐻𝐻𝑉 = 318.1 · 𝑋𝐶𝐶ℎ𝑎𝑟 + 142.3 · 𝑋𝐻𝐶ℎ𝑎𝑟 + 154 · 𝑋𝑂𝐶ℎ𝑎𝑟 , 𝐶9
Gasification occurs at 1123 K and at T = 1123 K the HHV was calculated using C9 to 33 MJ/kg
char. Using equation C1, the total mass percent of char is calculated to 7.75 wt-%. The total
amount of char produced with a mass flow of biomass of 11.5 kg/s becomes
𝑚𝑐ℎ𝑎𝑟 = 0.0775 · 11.5 = 0.89 𝑘𝑔𝑐ℎ𝑎𝑟𝑠
, 𝐶10
Using equation C9 together with the mass flow of char to the combustion chamber (equation
C10) the total energy released in the combustion chambers is calculated using equation C11.
𝑄𝑐ℎ𝑎𝑟 = 0.89 𝑘𝑔𝑐ℎ𝑎𝑟𝑠
· 33𝑀𝐽
𝑘𝑔𝑐ℎ𝑎𝑟= 29.6
𝑀𝐽
𝑠
These calculations show that the components are almost the same as tabulated work.
40
DISCUSSION CONCERNING CHARS
To check the validity of 33 MJ/kg higher heating value of char, the value was compared and
verified with literature45 in which values ranging from 17.4 MJ/kg (at 573 K) to 32 MJ/kg (1073
K). As the temperature is even higher in the combustion chamber (1123 K) these values seems
reasonable. It also works well with equation C5 which indicates a heating value of about 34
MJ/kg.
HYDROGENATION, HYDROLYSIS, WGS AND METHANATION
The calculation in all these above apparatus were calculated using the same approach as the one
for hydrolysis as can be seen below. The total costs are stated in a separate table seen in
Appendix B economy summary.
Hydrolysis work flow. To calculate the volume of the vessel the total gas flow was divided by
the residence time for the vessel. Through the flow and the max velocity of the gas through the
reactor vessel, the area and diameter as well as the height was calculated.
𝑚𝑔𝑎𝑠3
𝑠∙ 3 600
𝑠
ℎ
𝑚𝑘𝑎𝑡3 ∙ ℎ
= 𝑉
𝐴 =𝑚3
𝑠𝑚
𝑠
, the diameter was calculated through: 𝐴 =𝜋∙𝑑2
4.
The cost for these vessels are compiled in Appendix B, economy summary.
The cost for the catalyst was done by calculating the amount of needed catalyst, through
dividing the volume with the density and multiply it with the price.
𝐶𝑜𝑠𝑡𝑐𝑎𝑙𝑐𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑠 = 𝑚3 ∙
𝑘𝑔
𝑚3∙𝐸𝑈𝑅
𝑘𝑔∙𝑈𝑆𝐷
𝐸𝑈𝑅= 𝑈𝑆𝐷.
ACID GAS REMOVAL
The removal of H2S and CO2 is done with MDEA – PZ absorption through two columns, an
absorption tower and a stripper. Since there are ten MILENA gasifiers, the removal of these
components are done through ten absorption systems. The cost for the complete system with
installation costs, all utilities included, will have a cost of, 1.9 ∙ 106 ∙ 10 = 19 ∙ 106 𝑈𝑆𝐷
DESULFURIZATION
The desulfurization is dependent on the total flue gas flow rate (m3/s) leaving the combustion
chamber. To calculate the amount of flue gas that leaves the combustion chamber, the amount
of fuel entering the combustion chamber has to be known. During steady-state the combustion
chamber will operate based on char, Sulfur components and tars. During startup, oil will be
used to reach the appropriate temperature. However, oil cost has not been taken into
consideration in this project.
41
As mentioned in the “Char” part, about 10 % of the total biomass will end up as char in the
combustion chamber delivering energy to the gasification process. The combustion chamber
will also receive a lot of energy from tars leaving the OLGA utilities. The total amount of tars
in the biofuel is approximately 10 % according to the literature study.
With a total amount of bark entering the gasification process of 11.5 kg/s, 20 % will end up in
the combustion chamber. Of these approximate 2.3 kg, 1.7 kg is believed to be char and 1.6 kg
is believed to be tars.
In this stage of the project, a very approximate calculation regarding the amount of flue gas is
necessary. Instead of using the exact amounts of different components in the charcoal,
tabulated46values are used instead. The table used is stated in table DS1 which shows values for
mineral coal used for the charcoal.
Table DS1. Combustion data for mineral coal in m3/kg at NTP (0˚C, 100 kPa)
Flue gas
Component O2 Air g0t g0 CO2 %dry
Mineral coal 1.857 8.85 8.59 9.21 18.65 %
As can be seen in figure DS1 the total gas flow from the combustion chamber is described by
“g”. This value is calculated by adding the excess air factor l-l0 to g0 seen in table DS1.
l = 1.25 · l0 = 11 m3/s
𝑔𝑐ℎ𝑎𝑟𝑠 ≈ 11 − 8.85 + 9.21 = 11.4𝑚3
𝑠
Flue gas
Air
Char Combustion
Tars
H2S
COS Figure DS1. Overview of the combustion chamber ingoing and outgoing processes for mass balance equations.
42
There are also flue gas coming from the tars and the sulfuric flow rates. The amount of tars
entering the combustion chamber is about 1 kg/s. Even though the composition of tars are
different from benzene, benzene has been used to model the approximate amount of flue gas
created from tars. Benzene has a lower heating value of 40 MJ/kg, which is close to the lower
heating value of tars. Values are compiled in table DS2. The air to fuel ratio is set to 1.25, l =
1.25·10.5 = 13.25 m3/kg.
Table DS2. Combustion data for benzene in m3/kg at NTP (0˚C, 100 kPa)
Flue gas
Component O2 Air g0t g0 CO2 %dry
Benzene 2.18 10.5 10.05 10.92 17.38 %
gtars ≈ (13.25 − 10.5 + 10.92) · 1kg
s= 13.7
𝑚3
𝑠
Summary of the flue gas and necessary amount of air is compiled in table DS3. Additional flue
gas will come from H2S and COS. However, these are of less importance (additional 5 m3 was
added to the final flow). It is important to notice that these volumetric flows are evaluated at
NTP. The total gas flow becomes 13.7 m3/s + 11.4 m3/s which is about 25 m3/s evaluated at
NTP without the sulfur components. The total flue gas flow is about 30 m3/s NTP. These values
are actual (at the appropriate temperature) flows using aspen in calculations in HE1. The total
cost for the entire desulfurization step was verbally received from the supervisors to be 3.6 M
USD for this size.
Excess air
l-l0
Moisture
g gt g0 g0,t
Fuel
Figure DS2. Relation between stoichiometric and excess air amounts in the flue gas of a combustion chamber.
43
HEAT EXCHANGER 1
The first heat exchanger will preheat the air prior combustion to reach a more efficient
combustion. As the temperature inside the combustion chamber is about 950˚C the air is set to
be preheated to about 500˚C using the hot flue gases which leaves the combustion chamber. To
calculate the flow of flue gas as well as to model the incoming carbon dioxide (4 kg/s from
MDEA-PZ stripper column) the following setup was constructed in aspen plus. In these
calculations, a k value of 150 W/(m2∙K) has been used for all heat exchangers.
Figure HE 1. Flow sheet of Aspen simulations of the combustion chamber and the heat exchanger preheating the
air to the combustion chamber using energy from the flue gas leaving the combustion chamber.
The CO2 input stream to the reactor comes from the CO2 removal system and should include
H2S and COS but these are neglected to zero. Instead, a total flow of 4 kg/s of CO2 is
simulated (because this will have impact on the total flow out of the reactor). The reactor will
model combustion reactions automatically as seen in figure HE 1.2.
Figure HE 1.2. Combustion reactions simulated automatically in Aspen.
To obtain an outlet flue gas temperature of 80˚C (which is necessary for the drying utilities) a
total heat exchanger area of about 5100 m2 is necessary according to the exchanger details in
Aspen. The heat exchanger will manage to increase the temperature of the air to approximately
500˚C which is sufficient for the combustion chamber.
44
Figure HE 1.3. Summary of results for HE1 from Aspen plus. A K value of 150W/(m2∙K) have been used for
simulations.
The total flowrates and temperatures are listed in figure HE1.4 below.
The amount of flue gas leaving the combustion chamber is about 90 m3/s (figure HE1.4 flue
gas total flow) which includes all components entering the combustion chamber from the
process.
Cp = 500 000
FM = 3;
FaBM = FP ∙ FM = 6
CBM = CP ∙ FaBM = 500 000 ∙ 6 = 3 000 000 USD
Figure HE 1.4. Compiled flow rates and temperatures according to figure HE1 above.
45
HEAT EXCHANGER 2 AND 4-9
Small temperature differences, therefore these exchangers are neglected. Heat exchanger 2 in
the flow sheet (figure 17) is inserted to Heat exchanger 1 in order to retrieve a hot temperature
of the necessary air into the combustion chamber.
HEAT EXCHANGER 10
Temperature leaving the WGS-reactors have a temperature of 200˚C and should be decreased
to 40˚C prior amine scrubbing. This heat exchanger was calculated using Aspen plus in the
same way as heat exchanger 1. Shell and tube.
The cost is 900 000 USD. See Appendix C Economy summary for Cp, CBM, Fa, and FaBM.
HEAT EXCHANGER 3
Heat exchanger number 3 in Figure 17 will decrease the gas temperature from 1123 K to 673
K prior OLGA apparatus. The hot gas will evaporate water which enters the heat exchanger at
about boiling temperature (100˚C). The heat of evaporation for water is 2650 kJ/kg. The setup
can be seen in figure HE3.
The ingoing mass flow of gas is compiled in table HE 3.1 it was achieved from Aspen modelling
with a starting biomass flow of 15.2 kg/s. The mass flow is constant through the system and to
develop an energy balance of the heat exchanger, the component’s specific heat capacity is
needed. These values change with temperature and therefore one value is stated for the inlet
temperature (1123 K) and one for the outlet required temperature (673 K).
Figure HE 3.1. Heat exchanger number 3 ingoing and outgoing streams and pressures.
Producer gas 1; T1 = 1123 K
Producer gas 2; T2 = 673 K
Water; Tw1 = 373 K; Liquid
Water; Tw2 = 373 K; Gas
46
Table HE 3.1. Compiled mass flow components of gas stream.
Component Mass flow
(kg/h)
NAPHT-01 5
TOLUE-01 58
PHENO-01 5
N2 50
CO2 9 787
CO 8 761
H2 1 071
C2H2 41
CH4 2 523
C2H4 718
C2H6 48
H2S 7
COS 1.5
H3N 49
H2O 31 121
C6H6 470
The specific heat capacity is listed in table HE3.2 below.
Table HE 3.2. Components specific heat capacity for different temperatures.
Component T = 1123K
Cp (kJ/kg·K)
T = 673 K
Cp (kJ/kg·K)
CO2 0.84 1.10
CO 1.20 1.10
CH4 2.20 3.43
C2H4 1.53 2.65
H2 15.15 14.57
N2 1.19 1.81
C7H8 1.72 1.72
H2O 2.36 2.05
The total energy balance was stated as below where the specific heat capacity was multiplied
with the total mass flow of each component. The equation used is stated in Eq HE3.1 where
ΔTL is expressed in eq HE3.2.
𝑄𝑡𝑜𝑡 = 𝑄𝑝𝑟𝑜𝑑𝑢𝑐𝑒𝑟𝑔𝑎𝑠1 −𝑄𝑝𝑟𝑜𝑑𝑢𝑐𝑒𝑟𝑔𝑎𝑠2 = 𝑘 · 𝐴 · ∆𝑇𝐿̅̅ ̅̅ ̅ = 𝑚𝐻2𝑂 · ∆𝐻𝑉𝑎𝑝 Eq HE3.1
∆𝑇𝐿̅̅ ̅̅ ̅ = ∆𝑇1−∆𝑇2
ln∆𝑇1∆𝑇2
Eq HE3.2
47
Figure HE3.2 is from Aspen simulations. Feed gas has a temperature of 850˚C with the
components in table HE3.1. The stream S1 has the same constituents but a temperature of
400˚C.
Figure HE3.2. Into
With a k value of 100 W/(m2·K) the area becomes 306 m2.
The compiled values from Aspen is seen in figure He 3.3 below. In which the heat duty is about
15 MWth.
Figure HE 3.3. Compiled values from the heat exchanger 3 in Aspen. The heating duty is -15 MWth.
With a heat duty of 15 MWth, the necessary area becomes about 310 m2 using equation HE3.1.
Cp = 30 000
FM = 3;
FaBM = FP ∙ FM = 7
CBM = CP ∙ FaBM = 30 000 ∙ 7 = 210 000 USD
48
APPENDIX B ECONOMY SUMMARY
A summary of the compiled equipment costs are seen in table 7-11.
Table 7. Process cost for pretreatment and gasification.
Unit Op. Operating
Conditions
Material Cp (USD) FaBM CBM (USD)
Bark
storage
• 3 days cap.
• 3 000 ton
• No roof
• 9 000 m2
Asphalt
Fans • 400 m3/s 500 000 2.2 1 100 000
Bark Dryer • 0.1 m3/s
• V = 100 m3
Stainless steel 200 000 4.5 900 000
Conveyor
Belt
• Δh = 30 m
• width 1.5 m
250 000 2.4 600 000
Bark
Crusher
• 45 kg/s bark
• hammer mill
Stainless steel 250 000 2.8 700 000
MILENA Stainless steel 30 000 12 360 000∙10
Cyclone Stainless steel 80 000 5 400 000
TOTAL 7 300 000
49
Table 8. Heat exchanger calculations in USD.
Heat exchanger
calculations
Operating
conditions
Material Cp (USD) FaBM CBM (USD)
Heat exchanger 1 • Type: Shell/tube
• Area: 5 000 m2
s.s 500 000 6 3 000 000
Heat exchanger 3 • Type: Shell/tube
• Area: 310 m2
s.s 30 000 7 210 000
Heat exchanger 10 • Type: Shell/tube
• Area: 2 200 m2
s.s 150 000 6 900 000
Heat exchanger 14-15 • Type: Shell/tube
• Area: 442 m2
• Pressure: 100 bar
s.s 30 000 4 120 000
Heat exchanger 16-17 • Type: Shell/tube
• Area: 300 m2
• Pressure: 100 bar
s.s 25 000 4 100 000
Heat exchanger 18-19 • Type: Shell/tube
• Area: 70 m2
• Pressure: 100 bar
s.s 10 000 4 40 000
Heat exchanger 20-21 • Type: Shell/tube
• Area: 85 m2
• Pressure: 100 bar
s.s 10 000 4 40 000
TOTAL 4 410 000
50
Table 9. Process apparatus costs.
Unit op. Operating conditions Material Cp FaBM CBM (USD)
OLGA vessels • D = 1 m
• h = 13 m
• Number of trays = 12
• A = 4 m2
• vGmax = 3 m/s
• Oil: 500 l/h
s.s 300 000 12 3 600 000
W-Esp • vg = 46.5 m3/s s.s 1 100 000 4.1 4 510 000
Hydrogenation • 3 000 rh =
m3gas/(m3cat·h)
• h = 5.7 m
• D = 3.9 m
• vg = 35 m3/s
s.s 60 000 12 720 000
WGS reactor • 5 000 rh =
m3gas/(m3cat·h)
• h = 3.9 m
• D = 1.05 m
• vg = 12 m3/s
s.s 60 000 12 720 000
MDEA s.s 18 072 289
Compressor 1 • 24 MPa
s.s 4 000 000 6.3 25 200 000
Compressor 2 • 2 bar 15 000 6.3 100 000
Compressor 3 Maintain pressure in the
system. ΔP ~ 3 bar
s.s 1 500 000 6.3 9 450 000
Chimney - -
Desulfurization 3 614 457
TOTAL 65 986 746
51
Table 10. All costs for hydrolysis and total TREMPTM with utilities steps.
Unit op. Operating
conditions
Material Cp FaBM CBM (USD)
Hydrolysis • 1 000 rh
• Gas flow rate =
20.3 m3/s
• Catalysts
Stainless steel 70 000 12 840 000
TREMP Reactor 1 • 5 000 rh
• Gas flow rate =
1.2 m3/s
• D = 1.2 m
• h = 1.9 m
Stainless steel 14 000 20 280 000
TREMP Reactor 2 • 3 000 rh
• Gas flow rate =
0.7 m3/s
• D = 0.9 m
• h = 2.6 m
Stainless steel 9 000 20 180 000
TREMP Reactor 3 • 3 000 rh
• Gas flow rate =
0.5 m3/s
• D = 0.8 m
• h = 2.6 m
Stainless steel 9 000 20 180 000
TREMP Reactor 4 • 3 000 rh
• Gas flow rate =
0.2 m3/s
• D = 0,5 m
• h = 2.6 m
Stainless steel 6 000 20 120 000
Pump 2
Pump 4
Pump 5
• 500 l/h
• rho = 800 kg/m3
• Δh = 15 m
• Centrifugal
Stainless steel 8500 5 127 500
Pump 8 • 5 l/s (Water)
• ΔP = 99 bar
• Fp = 2.75
• Fm = 1.9
Stainless steel 20 000 10 200 000
TOTAL 1 927 500
52
TOTAL CAPITAL COST
(∑(𝐶𝐵𝑀)𝑖
𝑛
𝑖=1
) = 1 927 500 + 65 986 746 + 4 410 000 + 7 300 000 = 79 630 000 𝑈𝑆𝐷
As the brown field erection is considered an upgrade, the fauxiliary factor is set to 1.00 for this
plant.
𝐶𝑜𝑠𝑡$ 2004 = (∑(𝐶𝐵𝑀)𝑖
𝑛
𝑖=1
) · 𝑓𝑓𝑒𝑒𝑠 · 𝑓𝑎𝑢𝑥𝑖𝑙𝑖𝑎𝑟𝑦
Where ffees is about 1.15 and fauxiliary = 1.30 for green field plants.
𝐶𝑜𝑠𝑡𝑏𝑟𝑜𝑤𝑛 𝑓𝑖𝑒𝑙𝑑 = 79 630 000 · 1.15 · 1.00 ≈ 91 600 000 𝑈𝑆𝐷
𝐶𝑜𝑠𝑡𝑔𝑟𝑒𝑒𝑛 𝑓𝑖𝑒𝑙𝑑 = 79 630 000 · 1.15 · 1.30 ≈ 119 040 000 𝑈𝑆𝐷
The costs for the brown field and green field installations are converted from USD in 2004 to
Swedish crowns (kr) in 2012 which is seen below.
𝐶𝑜𝑠𝑡𝑘𝑟 2012 = 𝐶𝑜𝑠𝑡$ 2004 ∙ 𝑉𝐾𝐾 ∙𝐼𝐴𝐾 2012𝐼𝐴𝐾 2004
VKK is the exchange rate (7.3 kr/USD) from Ulrich database. IAK is equipment construction cost
index for Swedish currency. Where IAK 2012 is 148 and IAK 2004 is 115.
The cost for brown field was calculated to 860 Mkr and green field to 1 118 Mkr. The annual
net income was 130 Mkr/yr.
WASTE TREATMENT
Disposal cost for poisoned catalyst has been neglected.
CATALYST COST
In table 11, all the different costs for catalysts have been compiled. The lifetime of the catalysts
is about 3 years. The price for each catalyst was received from the course supervisors.
Table 11. Total cost for catalysts and the different catalyst based process utilities.
Hydrolysis WGS TREMP
I
TREMP
II
TREMP
III
TREMP
IV
Hydrogenation
Flow 20 11 1 1 0 0 35
Vmax 3 3 1 1 1 1 3
Rh 1 000 5 000 5 000 3 000 3 000 3 000 3 000
Volume 95 11 1 1 1 0 55
Area 7 4 1 1 0 0 12
Diameter 3 2 1 1 1 1 4
height 15 4 2 3 3 3 6
price 30 31 50 50 50 50 70
cost USD 3 155 083 366 176 62 169 56 125 38 856 17 269 4 230 954
TOTAL (USD) 7 926 632
53
ANNUAL NET INCOME
The resulting costs for the “base case” process was calculated and compiled in table 12 below.
These values correspond to up to date prices. However, the price for SNG is set to
approximately 50 % higher than for natural gas. The steam price depend on the demands of the
surroundings. In the base case, bark was assumed to be purchased at 37 kr/GJ, SNG to be sold
at 124 kr/GJ and steam to be sold for 90 kr/GJ.
If Värö would invest in building a new SNG production, the annual extra income would be
approximately 154 Mkr/yr. Table 12 shows the results from made payback method using both
Eq(22) without interest rate, and Eq(23) with (X) as interest rate. The interest rate is set to be
10 % in these calculations.
Using Eq(22) the payback time was received, where G is the total investment cost and a is the
annual net income. The calculations were made with MATLAB, a script is shown in Appendix
D.
𝑇𝑃𝑎𝑦𝑏𝑎𝑐𝑘 = 𝐺
𝑎 𝐸𝑞(22)
In regards of the interest rate using the payback method the outcome differs.
𝑛 = −(ln(1 − 𝐺 ∙
𝑋
𝑎)
ln(1 + 𝑋)) 𝐸𝑞(23)
54
Table 12. Compiled list for the base case scenario.
Investment G (kr) 860 000 000
Residual value 0
Yearly incomes and costs
Number of employees (st) 10
Salary/person (kr/yr) 750 000
Salary (kr/yr) 7 500 000
Maintenance (kr/yr) 43 000 000
Steam
Steam price (kr/GJ) 90
Steam production (GJ/yr) 560 000
Steam sales (kr/yr) 50 400 000
Bark
Bark price (kr/GJ) 37
Bark input (GJ/yr) 6 220 800
Bark purchase (kr/yr) 230 169 600
Restricted equity in bark (kr) 225 000
SNG
SNG price (kr/GJ) 124
SNG production (GJ/yr) 2 908 224
SNG sales (kr/yr) 360 619 776
Catalyst
Cost (kr/yr) 2 670 000
Annual net income
a (kr/yr) 130 000 000
Interest rate (10 %) 0.1
Payback T = G/a
T (yr) 6.7
Payback with interest rate (10 %)
n (yr) 11.8
To visualize the sensitivity and the influence of market prices, a sensitivity analysis was carried
out based on fluctuating bark prices, SNG-prices and steam prices. Also, the number employees
at the plant was changed to develop an understanding of where the costs are located.
As can be seen in figure AI.1 a slight increase of the bark price would have large unfavorable
impact on the payback time. As much as a few percent would lead to significant changes in the
process economy.
55
Figure AI.1. Fluctuating bark prices and payback time. Higher bark prices would lead to a significant change in
payback time.
In figure AI.2 an increase in SNG prices would lead to shorter payback times. In figure AI.3
the payback time is visualized towards the price of which the steam could be sold.
Figure AI.2. Changes in SNG prices and its impact on payback time.
15 20 25 30 35 40 454
6
8
10
12
14
16
18
20
22
24Payback
Bark price kr/GJ
Payback t
ime in y
ears
110 120 130 140 150 160 1704
6
8
10
12
14
16
18
20Payback
SNG price kr/GJ
Payback t
ime in y
ears
56
Figure AI.3. Payback time versus steam price. The importance of selling the steam to a high price to receive a good,
short payback time.
As can be seen in figure AI.4 the payback time is not as sensitive to change in number of
employees as in change of bark price, SNG-price and steam price.
Figure AI.4. Payback time versus number of employee. Cost dependence on how many employee’s working at the
site.
20 30 40 50 60 70 80 90 10010
15
20
25
30
35
40Payback
Steam price kr/GJ
Payback t
ime in y
ears
10 12 14 16 18 20 22 24 26 28 3011.5
12
12.5
13
13.5
14
14.5
15
15.5Payback
Number of employee
Payback t
ime in y
ears
57
Figure AI5 shows a sensitivity analysis over the investment cost for the plant shifting ±30 %.
Figure AI.5. Payback time versus investment cost, shifting ±30 %.
6 7 8 9 10 11 12
x 108
5
10
15
20
25
30
35
40Payback
Investment cost kr
Payback t
ime in y
ears
58
APPENDIX C ASPEN FLOWSHEET
Simulations using aspen is compiled below. These were modelled one by one instead of a total
flow sheet. Figure AB1 consists of the OLGA utility which was simulated using only two
vertical vessels instead of three.
Figure AB1. Simulation of the OLGA utilities. Two vertical vessels in which tars and particulates are removed
from the product gas.
59
Figure AB2. This process sheet consists of the hydrogenation, hydrolysis and WGS apparatus followed by the
MDEA-PZ absorption column.
The TREMPTM was simulated using the flow sheet in Figure AB3. However, in stream S2, one
compressor should be installed to increase the pressure to about 24 bar. This simulation was
done outside the simulation below.
Figure AB3. Simulation of TREMPTM using Aspen. Two compressors are missing from this flow sheet because the
compressors were simulated outside the process sheet.
60
APPENDIX D MATLAB SCRIPT
N=100; G=860e6; Personal=10; lon=750e3*Personal; p=0.1; %kalkylränta n=20; %livslängd Eout=linspace(1,1,N)*55*1.7/1000*3600*24*360; %GJ/år %Eout=transpose(Eout) Ein=linspace(1,1,N)*200/1000*3600*24*360; %GJ/år Esteam=linspace(1,1,N)*560000; %Ein=transpose(Ein) PriceOut=linspace(115,84*2,N); %PriceOut=transpose(PriceOut); PriceIn=linspace(42,37/2,N); %PriceIn=transpose(PriceIn) PriceSteam=linspace(20,100,N); A1=-G*p/(1-(1+p)^(-n))+(Eout.*PriceOut+90*Esteam(1,1)-Ein(1,1)*37-
G*0.05-lon-8e6/3); PB1=-log(1-(G./(Eout.*PriceOut+90*Esteam(1,1)-Ein(1,1)*37-G*0.05-lon-
8e6/3))*p)/(log(1+p)); %surf(PriceOut,PriceIn,Income) figure(1) plot(PriceOut,PB1,124,-log(1-G./(Eout(1,1)*124+90*Esteam(1,1)-
Ein(1,1)*37-G*0.05-lon-8e6/3)*p)/(log(1+p)),'*') title('Payback') xlabel('SNG price kr/GJ') ylabel('Payback time in years') grid
figure(2) A2=-G*p/(1-(1+p)^(-n))+(Eout(1,1)*124+90*Esteam(1,1)-Ein.*PriceIn-
G*0.05-lon-8e6/3); PB2=-log(1-G./(Eout(1,1)*124+90*Esteam(1,1)-Ein.*PriceIn-G*0.05-lon-
8e6/3)*p)/(log(1+p));
plot(PriceIn,PB2,37,-log(1-G./(Eout(1,1)*124+90*Esteam(1,1)-
Ein(1,1)*37-G*0.05-lon-8e6/3)*p)/(log(1+p)),'*') title('Payback') xlabel('Bark price kr/GJ') ylabel('Payback time in years') grid
figure (3) A3=-G*p/(1-(1+p)^(-n))+(Eout(1,1)*124+Esteam.*PriceSteam-Ein(1,1)*37-
G*0.05-lon-8e6/3); PB3=-log(1-G./(Eout(1,1)*124+Esteam.*PriceSteam-Ein(1,1)*37-G*0.05-
lon-8e6/3)*p)/(log(1+p)); plot(PriceSteam,PB3,90,-log(1-G./(Eout(1,1)*124+90*Esteam(1,1)-
Ein(1,1)*37-G*0.05-lon-8e6/3)*p)/(log(1+p)),'*') title('Payback') xlabel('Steam price kr/GJ') ylabel('Payback time in years') grid
61
figure (4) dPersonal=linspace(10,30); dlon=750e3*dPersonal; plot(dPersonal,-log(1-G./(Eout(1,1)*124+90*Esteam(1,1)-Ein(1,1)*37-
G*0.05-dlon-8e6/3)*p)/(log(1+p))) title('Payback') xlabel('Number of employee') ylabel('Payback time in years') grid
figure (5) A3=-G*p/(1-(1+p)^(-n))+(Eout(1,1)*124+Esteam.*PriceSteam-Ein(1,1)*37-
G*0.05-lon-8e6/3); dG=linspace(0.7*G,1.3*G,N) PB3=-log(1-dG./(Eout(1,1)*124+90*Esteam(1,1)-Ein(1,1)*37-dG.*0.05-
lon-8e6/3)*p)/(log(1+p)); plot(dG,PB3,G,-log(1-G./(Eout(1,1)*124+90*Esteam(1,1)-Ein(1,1)*37-
G*0.05-lon-8e6/3)*p)/(log(1+p)),'*') title('Payback') xlabel('Investment cost kr') ylabel('Payback time in years') grid
62
Calculation References
38 Forest Research Laboratory; Shool of forestry; Oregon April 1976 research Paper 31. “Properties and
uses of Bark as an Energy Source”; Stanley E. Corder; Table 4 ”A summary of Some published Ultimate
Analyses of bark.
39 Forest Research Laboratory; Shool of forestry; Oregon April 1976 research Paper 31. “Properties and
uses of Bark as an Energy Source”; Stanley E. Corder; Table 2 ” A Summary of Some Published Heating
Values and Ash Contents for Bark of Coniferous Species.”.
40 Forest Research Laboratory; Shool of forestry; Oregon April 1976 research Paper 31. “Properties and
uses of Bark as an Energy Source”; Stanley E. Corder; P.9 Bulk density
41 T. R. Nunn, J.B. Howard, J.P. Longwell, W. A. Peters; Product Compositions and Kinetics in the
Rapid Pyrolysis of Sweet Gum Hardwood, Ind. Eng. Chem. Process Des. Dev., 1985, 24, 3, 836-844
42 Richard. N, Thunman H; General equations for Biomass Properties, Chamers University, August 2002,
P. 10
43 H. Thunman, F. Niklasson, F. Johnsson, B. Leckner; Composition of Volatiles Gases and
Thermochemical Properties of Wood for Modelling of Fixed or Fluidized Beds, Energy & Fuels, 2001,
15, 1488-1497
44 A. Demirbas, Properties of charcoal derived from hazelnut shell and the production of briquettes using
pyrolytic oil, Energy, 1999, 24, 141-150 45 J.M. Encinar, J.F. Gonzàlez, J. Gonzàlez; Fixed-bed pyrolysis of Cynara cardunculus L. Products
yields and compositions, Fuel Processing Technology, 2000, 68, 209-222
46 Alveteg M. “Handbook”, Department of Chemical Engineering. Faculty of Engineering Lund
University of technology. P31 Table 3.5