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USC Chemical Engineering Student Research Annual 2010
Calorific Values and Proximate Analysis of
Sargassum spp. and Ulva spp.
Carlo S. Alburo, Radzwell H. Conje, Maria Gracelda B. Pino,
Engr. Patrick U. Tan*Department of Chemical Engineering, University of San Carlos, 6000 Cebu City, Philippines
*Corresponding Author
Abstract
The potential of seaweeds, Sargassum spp. and Ulva spp., as biomass for energy production was investigated based on their calorific values. Further, calorific values were correlated with the proximate analysis, which covers moisture, ash, volatile matter and fixed carbon contents of the seaweeds, using multiple linear regression. The calorific value was measured using bomb calorimetry while the proximate analysis was conducted using gravimetric method. The seaweed samples were taken from three different spots in Mactan Island, namely, Cordova, Buaya, and Maribago. It was found that the calorific values of Sargassum spp. range from 8.50 MJ/kg to 12.94 MJ/kg while Ulva spp. have a mean calorific value of 13.48 MJ/kg on dry basis. This shows that the seaweeds have comparable calorific values with those of the conventional biomass fuels like bagasse, rice husks and corn cobs. Correlation between calorific values and proximate analysis for Sargassum spp.and Ulva spp. was finally established in this study as:
CV ( MJkg )=13.3832−0.1546 M+0.0164 VM−0.0802 ASH with R2 = 0.80.
Keywords: Calorific Values, Proximate Analysis, Seaweeds, Correlations
1. Introduction
1.1. Seaweeds as Biofuels
The Philippines has an abundant supply of biomass resources which include agricultural crops (rice
hulls, coconut husk and meat, cocoa, cassava and bagasse), saw mill (forest logs) and furniture residues
(sawn timber). These biomass resources readily compete with food production and agricultural land [1].
To avoid this competition with food production, a potentially viable alternative is to use aquatic biomass,
such as algae, as the feedstock biofuel and bioenergy production.
Page 1 of 16
Macroalgae (or seaweeds), as biofuel, have the advantage of higher growth rates compared to
terrestrial crops and avoids competing with the agricultural land. Moreover, seaweeds can mitigate
greenhouse gas emissions since CO2 from flue gas can be utilized as carbon source in algae growth. Aside
from that, wastewater can be used to provide nutrients for seaweed growth [2].
Past attempts in utilizing seaweed as source of fuel started in 1970’s oil crisis. Among the programs
started to compensate for the energy crisis, the Giant Kelp Program of United States used the brown
seaweed Macrocystis pyrifera as energy crop. However the program was discontinued when it was
thought that the crisis was over [3]. But with the serious problems posed by global warming and the rapid
depletion of oil reserves today, the use of aquatic biomass energy is now being reconsidered as a means of
CO2 mitigation. Processes that are now considered for energy generation from aquatic biomass include
direct combustion, anaerobic digestion, fermentation to alcohol, thermal liquefaction, thermal
gasification, and pyrolysis [4]. In Germany, studies are ongoing for the closed cycle Solar Oxygen Fuel
Turbine (SOFT) in which dried seaweeds (specifically Ulva spp.) are combusted in a fluidized bed boiler
in Rankine cycle and the combusted products are returned to the cultivation ponds as algae nutrients
source [5]. According to Bruton et al. [6], in France, annual green tides generate about 60,000 tons of wet
Ulva spp, (or 8,000 tons dry weight) which have been considered to be utilized for local energy
production.
Seaweed species suitable for biomass energy should display high productivity in terms of standing
crop (total amount algae in a specific area at a given time) and biomass yield. The species should be
easily cultivated and harvested. Also, chemical composition of seaweeds should be accounted since it
determines the fuel quality and dictates the process of energy production [4]. Seaweeds that are
considered as potential energy crops include Macrocystis pyrifera, Laminaria, Sargassum and Ulva [3, 4,
6]. These seaweeds are said to have high productivity and biomass yield (45 tons dry weight annually)
[2].
Among the five species mentioned above, Sargassum and Ulva species are chosen in this study
because of their local abundance and little economic value. Sargassum is a dominant genus in tropical and
subtropical waters in terms of standing crop, percent cover and height.
Ulva species are common in the intertidal zones of the Philippines, but, at certain times, could over-
proliferate, producing blooms or ‘green tide’ in some protected bays. Common Ulva species that
proliferate in Cebu province are Ulva lactuca, Ulva fasciata and Ulva reticulata [7]. In Mactan Island
Page 2 of 16
(Cebu), central Philippines, at least two species constitute the Ulva population, either as free-living or
attached form. Ulva lactuca mainly consists of free-living population while the species referred to as Ulva
reticulata consists mainly of attached population [7]. Ulva species are frequently found in nutrient-rich
saline waters, attached to the bottom of the waters [8].
1.2 The Calorific Values
Good knowledge of the heating or calorific value of a fuel is needed for heat rate calculations, and
modifying operating parameters. Knowing the ash composition of fuels is needed to control of ash-related
conditions such as slagging, fouling, or erosion and management of environmental emissions [9,10]. The
calorific value of a material is the amount of heat released by a material during combustion. It is affected
by the ash and moisture contents of the biomass. The net calorific value or lower heating value is defined
as the heat to be removed from the reaction products to obtain a final temperature equal to the initial
temperature of the reactants, assuming that the reaction products remain in gaseous phase, i.e. that the
heat of condensation of water is not available. On the other hand, the reference state of the water for the
gross calorific value (higher heating value) is liquid state.
The ash (inorganic) content of a fuel lowers down the calorific value and may cause major problems at
high temperature combustion (melting of ash and clogging of reactors) [9,10]. Weber and Zygarlicke [10]
reported that ash-related problems, including slagging, agglomeration, corrosion, and erosion, can cause
frequent unscheduled shutdowns, decreasing the availability and reliability of the energy source.
The calorific value decreases with increasing moisture content. The presence of moisture in fuel lowers
its effective heating value since a portion of the heat of combustion is utilized in evaporating the
contained moisture, hence decreasing the calorific value. It is highly desirable, therefore, that the moisture
content be kept as low as possible [9].
The fixed carbon also affects the heating value of the fuel in such a way that the higher the fixed
carbon, the higher the calorific value of fuel. In general, an increase in the ash content corresponds to a
decrease in the fixed carbon content and hence a decrease in heating value [11]. Table 1 shows the
heating values of commonly used biomass fuels.
Page 3 of 16
Table 1. Typical characteristics of different biomass fuels used commercially for energy generation
Type Calorific Value (MJ/kg) % moisture % ashFruit Stems[1] 5 63 -Oil-palm husks[3] 7-8 55 5Oil-palm fibers[3] 7-8 55 10Bagasse[1] 7.7-8 40-60 1.7-3.8Fibers[1] 11 40 -Phaeophyta[2] 9-11 - 25-45Chlorophyta[2] 8-13 - 24-40Rhodophyta[2] 4 - 12 - 20-79Rice husks[1] 14 9 19Maize Cobs[1] 13-15 10-20 2Coffee husks[1] 16 10 0.6Cocoa husks[1] 13-16 7-9 7-14Groundnut shells[3] 16.7 3-10 4-14Wood[1] 8.4-17 10-60 0.25-1.7Coconut shell[1] 18 8 4Wheat straw and husk[3] 17-19 7-15 8-9Switch grass[3] 18-20 8-15 6Charcoal[1] 25-32 1-10 0.5-6
Very few studies have been done to establish the calorific values of seaweeds, much less those of
endemic seaweeds in the Philippines. Lamare and Wing [12] reported the calorific values of 28 species in
New Zealand. Their report showed that for the macroalgae species, the calorific value varies from species
to species depending on the type of storage products that range from high-energy polysaccharide starch to
mannitol and glycerol. The constituents that contribute to the calorific value of the seaweeds are
carbohydrates, proteins and fats, which are all found to differ from species to species. It was reported that
Chlorophyta (green algae), Rhodophyta (red algae) and Phaeophyta (brown algae) have different calorific
values with Chlorophyta having the highest mean calorific content and the Rhodophyta having the lowest
as shown in Table 1. In a similar study, Littler and Murray [13] reported that Chlorophyta had the highest
average ash-free calorific content followed by Rhodophyta and lastly Phaeophyta.
1.3 The Calorific Value Determination
The calorific value can be determined using proximate analysis or adiabatic calorimetry [14].
However, obtaining data from bomb calorimetry is usually tedious and expensive. For that reason several
correlations are devised to predict the higher heating value from the proximate analysis data. Parikh et al.
[15] used 450 different types of biomass and presented the correlation:
HHV = 0.3536FC + 0.1559VM – 0.0078ASH [ 1]
Page 4 of 16
where HHV is the higher heating value in MJ/kg, FC is the fixed carbon content, VM is the volatile
matter content and ASH is the ash content of the sample content in weight % on dry basis.
Demirbas [16] calculated the calorific values (higher heating values, HHV) of 16 biomass samples
experimentally from both ultimate and proximate analyses. The HHV (MJ kg−1) of the biomass samples
as a function of fixed carbon was calculated from the following equation:
HHV (MJ/kg) = 0.196(FC) + 14.119 (R2= 0.9997) [2]
Sheng et al. [17] gave new correlation between the HHV and dry ash content of biomass (in weight
percent) as follows:
HHV (MJ/kg) = 19.914–0.2324 ASH [3]
Lamare and Wing [12] correlated ash and calorific values of seaweeds with an R2 of 0.859 as follows:
HHV (MJ/kg) = 19.59 – 0.2106 ASH [4]
The major advantage of these correlations is that they allow the determination of HHV of fuels simply
from their proximate analysis and thereby provide a useful tool for modelling of combustion processes.
These can also be used in examining old/new data for probable errors when experimental results lie much
outside the predicted results of HHV [15].
This study sought to explore the possibility of using locally available seaweeds as biomass fuel by
comparing their heating values against those of the conventional biomass outlined in Table 1. The study
also sought to establish relation between heating values and moisture contents of sun-dried seaweeds and
finally correlations between heating values and the proximate analysis were established for Ulva and
Sargassum species.
Page 5 of 16
2. Materials and Methods
2.1 Sampling
Algal samples were taken from different areas around Mactan Island. The places chosen were
dependent primarily on the abundance of seaweeds in one particular place. Ortiz and Trono [18] reported
that 72 species of Sargassum are found in the Philippines. Table 2 gives the standing crop of Sargassum
beds in Central Visayas.
Table 2. Standing crop of dominant Sargassum spp. in Central Visayas [18]
Site Standing Crop(kg wet weight per m2 )
Dominant Sargassum species
Tongo, Mactan Is. 2.5 S. siliquosum
Cordova, Mactan Is. 3.4 S. binderiMaribago, Mactan Is. 2.7 S. polycystum , S. oligocystumCaubyan Is. 4.9 S. polycystumDanajon Reef 6.7 S. polycystumBilangbilangan Is. 2.6 S. polycystum, S. oligocystumOlango Is. 1.28 S. polycystum, S. oligocystum
and S. siliquosum
In this study, Sargassum polycystum seaweeds were taken from the shores of Barangay Buagsong,
Cordova while Ulva lactuca was taken from Barangay Buaya. Both Sargassum oligocystum and Ulva
reticulata were taken from the shores of Maribago. The seaweeds were collected during low tides. One
liter of seawater samples was also taken during the collection of the species to determine its DO, pH,
temperature and salinity.
The seaweeds were collected by thallus (vegetative body of algae). Three thalli were collected for
Sargassum polycystum, Sargassum oligocystum and Ulva lactuca. The thalli would serve as the samples
of each species. There were three samples for each kind of species. And since Ulva reticulata thrive in
continuous mats, this species was obtained by composite sampling. The collection of seaweeds was done
by hand. Specimens adhering to the seaweeds were removed using knife and the collected species were
wrapped in a newspaper and placed in an ice bucket.
Water samples were analyzed within 24 hours after they were collected. pH was determined using the
pH meter and the salinity was measured using the hand refractometer. The temperature of the seawater
and its dissolved oxygen were measured using the thermometer and DO meter, respectively.
Page 6 of 16
The seaweed samples were brought to the University of San Carlos Marine Biology Department for
identification. The identification of the species was based on their external morphology, color and shape.
Pictures of the macroalgae aided the determination of species.
2.2 Preparation of Specimens for Analyses
The seaweed samples were cleaned with water and the epiphytes (any plant that grows upon or is
attached to the seaweeds) were removed. Excess water from the samples was then removed by gently
pressing the algae against tissue paper.
All the collected seaweed samples were sun-dried. To determine relationship between calorific value
and moisture content during sun-drying of seaweeds, one whole thallus of each species, Sargassum
polycystum and Ulva reticulata, was sampled for moisture content and calorific values analyses at
different intervals of time for three days. A total of seven samples were taken from the whole thallus of
each species during the sun-drying period and each sample had three replicates. Also, fresh samples were
oven-dried overnight to be moisture free (assumed 0% moisture) and their corresponding calorific values
were determined.
After all the seaweeds were sun-dried, they were stored and cut into small pieces for the proximate
analyses and calorific value determination. The whole experiment was conducted in two trials, one
month apart.
2.3 Proximate Analysis
Proximate analysis is an indirect method of measuring the calorific value of a sample. It converts the
component weights of proteins, fats and carbohydrates in the sample to their equivalent heating values.
Proximate analysis requires the values of the ash content, moisture content, volatile combustible matter
content, and the fixed carbon in order to determine the heating value of the sample. The Proximate
analysis method used in this study was based on AOAC[19].
2.4 Calorific Value Determination
In adiabatic calorimetry, direct combustion of the samples is done in a temperature-controlled bomb.
This jacket is maintained at the temperature of the bomb throughout the combustion process to eliminate
Page 7 of 16
the heat-leakage. The calorific value of the sample obtained from calorimetry is said to be more accurate
than that obtained from proximate analysis [14].
The calorific value was determined using Parr 1108 Oxygen Bomb Calorimeter based on ISO
1928:1995 [20]. Oxygen was supplied at a gauge pressure of 23 atm.
2.5 Correlations
Multiple linear regression analysis was employed to establish the correlations relating the calorific
values of seaweeds with their corresponding proximate analysis data. The methods of least squares
minimizing the error squared, was used to evaluate the adjustable parameters for each correlation
expression [21]. Calculations were aided using the 4-unknown calculator software [22]. Correlation
equations established were compared with those in the literature.
3. Results and Discussion
3.1. Calorific Values of Different Seaweed Species from Different Places (Maribago, Cordova and
Buaya)
A preliminary run was done to investigate available seaweed species in Maribago, Cordova and
Buaya. Table 3 shows the seawater conditions when the seaweed samples were obtained.
Table 3. Seawater conditions of sampling locations
Parameter Maribago Buaya Cordova
T (oC) 30.8 30 30
DO (g/ml) 7.17 3.14 3.12
Salinity (%) 29 26 36
pH 7.99 8.31 8.34
In Maribago, the most abundant species were S. oligocystum and U. reticulata. In Cordova, the most
abundant specie was S. polycystum. Figure 1 shows the calorific values of different seaweed species
harvested.
Page 8 of 16
S. Polyc
ystum
S. Olig
ocystu
m
S. Cras
sifoliu
m
S. Crys
taefoliu
m
U. Reti
culat
a
Ulva la
ctuca
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
Maribago
Cordova
Buaya
Species
Cal
orif
ic V
alu
es (
MJ/
kg)
Figure 1. Calorific Values of Different Seaweed Species from Maribago, Cordova and Buaya
From the Figure 1, it can be seen that the calorific values of Sargassum spp. range from 8.50 MJ/kg to
12.94 MJ/kg while Ulva spp. have a mean calorific value of 13.48 MJ/kg on dry basis which is in
agreement with values reported by Lamare and Wing [12].
The results also show that the local species of Ulva and Sargassum collected in Mactan have
comparable calorific values with those of the conventional biomass fuels like bagasse, rice husks and corn
cobs as cited in Table 2.
3.2 . Calorific value as a function of moisture content during sun drying
The most serious disadvantage of biomass fuel is that they often have high moisture content which
readily inhibits combustion [23]. In general, aquatic biomass contains 80 to 90% water [24]. The best way
to recover the lost energy because of high moisture content is through drying of biomass. In the study,
samples of Sargassum polycystum and Ulva reticulata were sun-dried to minimize the moisture content. It
was observed that when the moisture content was still higher than 40%, the calorific value of the seaweed
samples could not be determined by bomb calorimetry since no temperature change is observed during
ignition.
Figures 2 and 3 below show the relation between moisture content of the seaweed and its calorific
value for Sargassum polycystum and Ulva reticulata samples, respectively.
Page 9 of 16
0 5 10 15 20 25 30 35 406.0
7.0
8.0
9.0
10.0
11.0
trial 1
Moisture Content (kg/kg)
Cal
orif
ic V
alu
e (M
J/k
g)
In both figures, it can be clearly seen that at moisture content below 40%, the calorific values have
negative linear correlations with moisture content consistently in the two experimental trials done.
However, Figure 2 shows that the two experimental trials produced different correlations despite
involving the same species. This may be attributed to the morphology of Sargassum species. On the other
hand, Figure 3 shows that the two trials produced almost identical correlations. Compared to Sargassum
species, Ulva species are more homogenous in form and structure hence may promote uniform drying. It
is also seen that at moisture content 15% (or below), the calorific value of seaweeds is at par with those of
the conventional biomass fuels. Since the two trials produced two different correlations, only correlation
of Figure 3, using linear regression, is thus developed as:
CV ( MJkg )=11.20 — 0.098 M [5]
3.3 Correlation between the calorific values of seaweeds and proximate analysis data
After two to three days of sun-drying, the moisture content of the seaweeds lowered to 10 to 15% by
weight. Essentially all seaweed samples have negligible fixed carbon content (~0%) and have high
volatile matter (40-75%) and ash content (15-45%) on dry basis as shown in Table 4 and 5. The
combustibles of a solid fuel are the volatile matter and the fixed carbon. Since the fixed carbon content is
negligible, the volatile matter is the only contributor to the energy of seaweeds.
Page 10 of 16
Figure 3. Calorific Value of Ulva reticulata versus
moisture content
Figure 2. Calorific Value of Sargassum polycystum
versus moisture content
0 5 10 15 20 25 30 35 407.0
8.0
9.0
10.0
11.0
12.0
13.0
14.0
trial 1Linear (trial 1)trial 2
Moisture Content (kg/kg)
Cal
orif
ic V
alu
e (M
J/k
g)
Table 4. Proximate analysis and Calorific values of seaweeds for the 1st trial
TRIAL 1
SpeciesMoisture (kg/kg)
VM (kg/kg)
Ash (kg/kg) CV(MJ/kg)
Sargassum oligocystum 1 15.34 40.60 44.00 8.6273Sargassum oligocystum 2 14.66 42.77 42.57 8.8402Sargassum oligocystum 3 12.99 45.59 41.09 9.1552Sargassum polycystum 1 12.79 57.83 29.37 10.0125Sargassum polycystum 2 10.36 53.30 36.30 9.7074Sargassum polycystum 3 11.57 59.50 28.90 10.1191
Ulva lactuca 1 15.46 55.70 28.24 9.5692Ulva lactuca 2 13.26 59.31 26.61 9.6820Ulva reticulata 9.17 70.54 20.29 10.5727
Table 5. Proximate analysis and Calorific values of seaweeds for the 2nd trial
TRIAL 2
Species Moisture (kg/kg)VM
(kg/kg)Ash
(kg/kg) CV(MJ/kg)Sargassum oligocystum 1 14.91 57.02 28.25 9.7883Sargassum oligocystum 2 14.55 49.85 35.64 7.8535Sargassum oligocystum 3 15.62 54.68 30.01 9.79368Sargassum oligocystum 4 17.27 51.89 31.03 8.52993Sargassum polycystum 1 14.41 46.56 39.42 8.79003Sargassum polycystum 2 14.12 49.61 36.21 8.9893Sargassum polycystum 3 14.23 57.35 42.31 8.7221Sargassum polycystum 4 13.71 49.30 37.69 8.9265
Ulva lactuca 1 14.37 64.31 21.33 11.1842Ulva lactuca 2 11.87 67.80 20.36 11.4925Ulva lactuca 3 10.23 69.20 20.55 12.2723Ulva reticulata 10.23 75.03 15.56 11.6259
Ash content is the remaining incombustible minerals of a fuel. Consequently, the calorific value
decreases with increasing ash content. In general, fuels should have ash content less than 5% [9]. But
seaweeds in this study have been found to have high ash content which would then restrict the direct
combustion of seaweeds as biofuels.
Figure 4, 5 and 6 are plots of calorific values against moisture contents, volatile matter contents, and
ash contents, respectively, covering all the sampled species of Ulva and Sargassum. It can be seen in
Figure 4 that the moisture content has a poor correlation with the calorific value, while volatile matter
Page 11 of 16
content and ash content each have good correlations with the calorific value (R2 = 0.739 and R2 = 0.723,
respectively).
By multiple linear regression and single linear regression analyses, moisture, volatile matter and ash
contents were correlated with the calorific value as tabulated in Table 6 with their corresponding R 2.
Constraints in the use of these correlations include 10 to 20% moisture content, 40 to 75% volatile matter
and 15 to 45% ash content.
To measure how well the correlation fits the data, coefficient of determination (R2) was computed.
The highest R2 computed was 0.80. This means that 80% of the variation of the calorific values of the
seaweed samples has been explained by the linear regression equation established in the study.
Page 12 of 16
Figure 6. Calorific value versus ash content
Figure 5. Calorific value versus volatile matter contentFigure 4. Calorific value versus moisture content
10 15 20 25 30 35 40 45 506.0
7.0
8.0
9.0
10.0
11.0
12.0
Ash Content (kg/kg)
Cal
orif
ic V
alu
e (M
J/k
g)
10 11 12 13 14 15 16 17 187.0
8.0
9.0
10.0
11.0
12.0
13.0
Moisture Content (kg/kg)
Cal
orif
ic V
alu
e (M
J/k
g)
40 45 50 55 60 65 70 75 807.0
8.0
9.0
10.0
11.0
12.0
13.0
14.0
15.0
VM content (kg/kg)
Calo
rific V
alue
(MJ/
kg)
The correlation equations established were compared with those from literature as shown in Figures 7
and 8. Figure 7 shows that Lamare and Wing [12] and Sheng et al. [17] have almost the same slope while
the correlation established in the study differed from the two. It can be seen in Figure 8 that the
correlation by Parikh et. al.[15] have the almost the same slope with the one established in the study.
Table 6. Correlation equations
In this Study In literatureCorrelation equation R2 Correlation R2 Reference
CV ( MJkg )=7.8398+0.0626 VM−0.0521 ASH0.761 CV ( MJ
kg )=0.3536 FC+0.1559VM−0.0078 ASH0.997 Parikh et al.
[15]
CV ( MJkg )=13.34−0.115 AS H 0.723 CV ( MJ
kg )=19.914−0.2324 ASH0.89 Sheng et al.[17]
CV ( MJkg )=19.914−0.0 .2324 ASH
0.859 Lamare and Wing [12]
CV ( MJkg )=13.3832−0.1546 M+0.0164 VM−0.0802 AS H 0.802
30.00 40.00 50.00 60.006.00
8.00
10.00
12.00
In the StudyLamare and Wing[12]Sheng et. al[17]
Ash Content (kg/kg)
Cal
orif
ic V
alu
e (M
J/k
g)
Figure 7. Comparison with established correlations in literature
Page 13 of 16
Figure 8. Comparison
with established correlations in
literature
4. Conclusion and Recommendation
Seaweeds have potential to be used as solid biofuel since they have comparable calorific values to the
conventional biomass like bagasse, rice husks and corn cobs. However, seaweeds have to be dried from
about 87% to 15% moisture content in order to obtain calorific values close to those of the conventional
biomass (9-12 MJ/kg). Moreover, both Sargassum and Ulva species have high ash content (15 %-45%)
which may restrict their use in direct combustion.
In the case of Ulva reticulata species, there was a highly negative correlation between moisture
content and calorific values. The last equation on table 6 can be used to predict calorific values of Ulva
and Sargassum species.
In the case of sun-drying of Sargassum species, more experiments should be conducted to establish a
consistent correlation between moisture contents and calorific values. To improve linearity, more species
of Sargassum should be included.
Because of the high ash content, studies should be performed on the fluidized bed combustor (i.e. Solar
Oxygen Fuel Turbine) which operates using seaweeds as fuels and which allows recycling of ash as
nutrient source for seaweed cultivation [25].
5. References
[1] Hoi, W. (2003). Potential of biomass utilization for energy in asia pacific sharing of specific
experience of Philippine situation. Forest Reasearch Institute. Kepong, Kuala Lumpur Malaysia.
[2] Rasmussen, M. and et. al. 2007. Primary Biomass Production from Marine Algae. University of
Aarhus : National Environmental Research Institute; Memorandum for VE-net, 2007.
Page 14 of 16
10.00 20.00 30.00 40.00 50.00 60.002.03.04.05.06.07.08.09.0
10.0
In the StudyParikh et. al[15]
VM Content (kg/kg)
Calo
rific V
alue
(MJ/
kg)
[3] Yokoyama, S., Jonouchi, K., Imou, K. (2007). Energy production from marine biomass: fuel cell
power generation driven by methane produced from seaweed. World Academy. 5: 1131-1151.
[4] Chywoneth, D. (2002). Review of biomethane from marine biomass. Fuel. 10:1025-1030
[5] Yantovski, E. (2008). Seaweed Ulva photosynthesis and zero emissions power generation.
Proceedings of ECOS 2008. 3: 1117-1130.
[6] Bruton, T., Lyons, H., Lerat, Y., Stanley, M. and Rasmussen, M. (2006). A review of the potential
of marine algae as a source of biofuel in Ireland. Sustainable Energy Ireland. 13-24.
[7] Trono, G. (1997). Field guide and atlas of the seaweed resources of the Philippines. Bookmark, Inc.
264-A Pablo Ocampo Sr. Ave.
[8] Hulsbergen, R. (2006). Predicting Ulva growth in a saline Volkelrak-Zoomlake. Delft University of
Technology report. 8-19.
[9] Quaak, P., Knoef, H., Stassen, H. (1999). Energy from biomass (A review of combustion and
gasification techniques). New York, USA. 2-7.
[10] Weber, G. And Zygarlicke, C. (2001). Barrier issues to the utilization of biomass. AAD Document
Control, 2:765-770.
[11] Unesco. (1988). Engineering schools and endogenous technology development. Paris.
[12] Lamare, M. and Wing, S. (2001). Calorific content of New Zealand marine macrophytes. New
Zealand Journal of Marine and Freshwater Research. 35:335-341.
[13] Littler, M., Murray, S. (1977). Analyses of pathways of energy flow. In: Littler, M. and Murray, S.
(Eds.). Influence of domestic wastes on the structure and energetic of intertidal communities near
Wilson Cove, San Clemente Island. University of California, Davis: California Water. 47-56.
[14] Carefoot, T. (1985). Calorimetry. Press Syndicate of the University of Cambridge. In Handbook of
Phycological Methods: Macroalgae. New York, USA. 480-490
[15] Parikh, J., Channiwala, S., and Gosal, G. (2004). A correlation of calculating HHV from proximate
analysis of solid fuels. Fuel.10.1018
[16] Demirbas, A. (1996). Calculation of higher heating values of Biomass fuels. Fuel, 10:1016-1020
[17] Sheng, C., and Azevedo, J. (2004). Estimating the HHV of biomass fuels from basic analysis of data.
Fuel. 10.1020.
[18] Ortiz, A., Trono, G. (2000). Growth and reproductive pattern of intertidal and subtidal Sargassum
(Sargassaceae, Fucales) population in Bolinao, Pangasinan. Science Diliman. 12:2:45-50.
[19] Williams, S.(2002). Official Methods of Analysis of A.O.A.C. AOAC International. Maryland, USA.
[20] Determination of gross calorific value by the bomb calorimetric method, and calculation of net
calorific value
Page 15 of 16
[21] Walpole, E., Myers, R. And Myers, S.(1998). Probability and Statistics for Engineers and Scientists.
Prentice Hall, Inc. New Jersey, USA.
[22] http://www.1728.com/unknwn4.htm
[23] Henrich, R., Vodegel, G., Kocj, M. (2004). Definition of standard a biomass. RENEW.
[24] Hennenberg, K., Fritsche, U., Herrera, R., (2009). Aquatic biomass: sustainable bioenergy from
algae? Oko-Institut, Darmstadt, Germany.
6. Acknowledgement The researchers would like to express gratitude to Dr. Anthony Ilano, PhD and the University of San
Carlos Marine Biology Department for helping with the identification of the seaweed species and
allowing the researchers to use Marine Biology Laboratory for the analyses of the seawater samples.
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