Isolation of new flavonol oligosaccharie from the petals of Leucojum vernum L. and Galanthus nivais L

Full text of DOI:10.1515/znb-1967-0823

Folia Forestalia Polonica, Series A – Forestry, 2016, Vol. 58 (2), 62–71
ORIGINAL ARTICLE
DOI: 10.1515/ffp-2016-0007
Variability of energy woodchips and their economic effects
Arkadiusz Gendek , Tomasz Nurek
Warsaw University of Life Sciences – SGGW, Faculty of Production Engineering, Department of Agricultural and Forestry
Machines, Nowoursynowska 164, 02-787 Warsaw, Poland, phone: +48 22 5934513, email: arkadiusz_gendek@sggw.pl
ABSTRACT
The main aim of the work is to assess physical parameters of forest woodchips and their impact on the prices
achieved by the supplier in transactions with a power plant. During fragmentation of logging residue, high content
of green matter and contaminants negatively impacts the quality parameters that serve as basis for settlements. The
analysis concerns data on the main parameters – water content, fuel value, sulphur and ash content – from 252 days
of deliveries of forest chips to a power plant. The deliveries were realised from forested areas on an average about
340 km from the plant. Average water content and the resultant fuel value of forest chips was within 27–47% and
8.7–12.9 GJ×Mg−1 (appropriately), respectively. They depend on the month in which they are delivered to the power
plant. The threshold values for the above-mentioned parameters are set by the plant at a real level and the suppliers
have no problems with meeting them. The parameter that is most frequently exceeded is ash content (11.5% of cases).
The settlement system does not differentiate on the basis of the transport distance but gives possibility to lower the
settlement price when the quality parameters are not met but provides no reward for deliveries with parameters bet-
ter than the average ones. On the basis of results obtained, it was calculated that average annual settlement price is
lower than the contract price by about 0.20 PLN×GJ−1, which in case of the analysed company may translate into an
average daily loss of about 700 PLN.
KEY WORDS
forest biomass, transport, fuel value, ash content, forest woodchips, woodchip prices
INTRODUCTION
the Czech Republic, Slovakia, Germany) is above 30%
(GUS 2013). The research realised and study works in-
dicate that the rational forest coverage for Poland be-
cause of the structure of land use and maintenance of
environment at the present stage of civilisation should
be about 33–34%. Increasing the forest coverage, apart
from the environmental and ecological aspects, directly
impacts the supply of lumber and biomass intended for
energy production (Gołos and Kaliszewski 2013; Ka-
liszewski and Gołos 2014).
Apart from the energy policies (Polityka energetyc-
zna… 2009), an important document that impacts the
quantity of energy biomass is the ‘National Forest
Policy’ whose aim is to increase the forest coverage of
Poland to 30% up to 2020 and to 33% after 2050. Ac-
cording to the Raport o stanie lasów w Polsce (2014),
currently, the forest coverage in Poland is 29.4%, where-
as that in the surrounding countries (Latvia, Belarus,
© 2016 by Forest Research Institute
© 2016 by the Committee on Forestry Sciences and Wood
Technology of the Polish Academy of Sciences
Received 24 February 2016 / Accepted 23 March 2016
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Variability of energy woodchips and their economic effects
63
Technologies that transform biomass into heat and
interest in wood resources that were used to a small
extent up to this point. This means that logging residue
and biomass are mostly acquired during cutting activi-
ties. Creation of chips from such material is, however,
burdened by a number of problem. The most crucial
problems are the high degree of dispersal of biomass
in forests, low yields and high content of green mass.
This results in higher acquisition costs for the chips.
Attention should also be given to the type of material
from which the chips are formed and the resultant en-
ergy. The characteristics of woodchips are presented
in Table 1.
As with all types of business activity, also in this
case, all the business entities involved in the process of
acquisition, transport and burning of the material must
achieve an acceptable level of economic gains. Many
of the characteristics of this sector results in a situ-
ation that not all the entities present in the individual
segments of the sector achieve the expected profit. In
most cases, this is due to the circumstances beyond the
control or any choice of the companies. Such factors in-
clude dispersal of material on large areas, low ‘density’
of the material in the forest, location of power plants,
high share of transport costs (large distances) and vari-
ability of physical and chemical characteristics of chips
(fragment size, water content, ash content, hydrogen
content, sulphur content, fuel value).
electric energy are currently amongst the cheapest and
most environment friendly. This thesis is backed by
a large number of authors who analysed the utilisation
of forest biomass for energy production (Grilli et al.
2015). However, in this case, the problem is the size of
available resource base and the need to take the trans-
port into consideration (Roszkowski 2008, 2012).
There are also many other barriers that impact
the ease with which the biomass may be utilised
and the growth of its market. Amongst such barriers
mentioned is the lack of forecast for share of forest-
related biomass (including lumber) that could be fea-
sibly used for energy creation in the forecasts up to
2020. According to the research of Płotkowski (2007)
and different simulations performed for three differ-
ent scenarios, it may be assumed that the quantity of
forest biomass that can be used for energy production
is somewhere between 11 and 16 million m3. These
are, however, theoretical values that, when taking the
availability of forest biomass into account, decrease to
about 3–5 million m3. Zajączkowski (2013) forecasts
that the theoretical lumber availability for energy pro-
duction in the forests shall be 7.94 million m3 in 2021
and shall reach 8.91 million m3 in 2031, where the en-
ergy small wood and logging residue will be about 3.76
and 4.21 million m3 (respectively).
According to the Ordinance of the Minister of
Economy, dated 18 October 2012 (Rozporządzenie
2012), the renewable energy sources do not include
electricity or heat produced from full-value wood.
This provision secures the valuable wood resource
being used as fuel and, at the same time, results in
Owing to the location and dispersal of forests, the
main type of transport used for chips is vehicular trans-
port. During the past years, this type of transport has
developed significantly and the transport work realised
by this segment has increased many fold (Talbot and
Suadicani 2006; Asikainen 2010; Pieriegud 2015).
Table 1. Selected characteristics of logging residues (Hałuzo and Musiał 2004)
Details
Water content (fresh material)
Fuel value
Unit
Branch chips
50–60
Whole-tree chips
45–55
Trunk chips
40–55
Stump chips
30–50
%
MJ×kg−1 s.m.
MJ×kg−1
18.5–20
6–9
18.5–20
6–9
18.5–20
6–10
18.5–20
6–11
Fuel value of fresh material
Bulk density
kg×m−3
250–400
0.7–0.9
1–3
250–350
0.7–0.9
1–2
250–350
0.7–0.9
0.5–2
200–300
0.8–1.0
1–3
Energy per volume unit
Ash content
MWh×m−3
% dry content
% dry content
% dry content
% dry content
Hydrogen content
Sulphur content
6–6.2
5.4–6
5.4–6
5.4–6
<0.05
<0.05
<0.05
<0.05
Nitrogen content
0.3–0.5
0.3–0.5
0.3–0.5
0.3–0.5
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Arkadiusz Gendek, Tomasz Nurek
64
Lisowski et al. (2015) stated that biomass should
2008, 2009). However, here we can only analyse natu-
ral drying – without adding additional energy, as such
approach would make impossible achieving favourable
financial results. Many suppliers use favourable condi-
tions and stores the material in open yards.
This work aims to assess the physical parameters
of woodchips during a calendar year and their impact
on prices on the industrial market in settlements with
a power plant.
be transported in a compacted form, when analysing
the form and density of energy biomass. But, as other
authors point out, for example, Baum et al. (2012), full
utilisation of energy biomass for the creation of the so-
called ‘green energy’ may be achieved only by proper
organisation of the biomass market (Rentizelas 2009),
starting at the level of individual communes or districts.
Jasiulewicz (2006) in his research pointed to the lack
of economic efficiency of burning biomass in highly
concentrated power plants (high costs of long-distance
transport and negative environmental impact). He indi-
cated the need to create local markets for biomass and
local logistic centres.
From the viewpoint of the recipient of the chips
– the power plant – the most crucial parameter of the
material is the fuel value that is directly related to the
water content of the material. The water content, in
turn, is dependent on environmental conditions and, to
a large extent, on the season in which the chips were ac-
quired. The prices that the power plant is willing to pay
is the result of these parameters. But is the supplier able
to impact the physical parameters of the material sup-
plied? – The impact is very limited. Therefore, should
the supplier bear the costs related to lower parameters of
the material that are beyond its control?
The answer to these questions must be preceded by
the explanation of how determined is the price of the en-
ergy fuel in the form of the chips. The contract between
the recipient (power plant) and the supplier of the chips
determines the basic price for supplying 1 GJ of energy.
This value may be corrected (only downwards) if the
quality parameters of the supplied biomass are below
the threshold values. These parameters are fuel value,
water content, sulphur content, chloride content and ash
content. The amount paid for the delivery on a given day
is based only on the weight of the chips. After analys-
ing their actual water content, fuel value and content
of unnecessary substances, the price is corrected and
final settlement is realised at the next delivery or at the
end of a given month. The rate paid for the supplied en-
ergy material is not dependent on the distance that the
material travelled. This issue, if it is possible, should
be negotiated when the basic rate of the contract is de-
termined.
MATERIAL AND METHODS
The subject of the analysis was information originating
in a period from August 2013 to April 2015 which cov-
ered 252 days of chips deliveries by a single company
to the power plant. Owing to the maintenance works in
the power block fuelled by the biomass, there were no
deliveries in July.
The research material was woodchips acquired
during cleaning of logging areas. The residue, that is,
branches of trees of different forest species, assessed in
accordance with size/quality norms as small wood, was
acquired in forests of the North-Eastern Poland, mostly
from the Podlaskie, Warmińsko-Mazurskie and the
Northern part of the Mazowieckie regions. The residue
was fragmented using Bruks 805C machines installed
on the chassis of a forwarder for a period of two to six
months after logging.
Timber acquisition during the months when the
data were collected was realised using varied meth-
ods: using machinery or by a mixed machinery/manual
method. Regardless of the method of acquisition, chip-
ping was realised directly in the forest or the residues
were extracted using a self-loading tractor, piled at the
exit road and chipped there.
Transport from forests to the power plant (average
distance of 300 km) was realised using trailer trucks
with capacity of 90 m3 equipped with movable floors.
Exemplary routes of transport vehicles and geographi-
cal location of forests and the power plant are presented
in Figure 1.
The chips were delivered to the power plant lo-
cated in the central area of the country. Out of every
transport, a sample of about 10 l was taken. Samples
from all deliveries during a given day were mixed
in order to ensure uniformity of material. Such pre-
There is a certain possibility of increasing the pa-
rameters of the chips by drying (Gendek and Głowacki
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Variability of energy woodchips and their economic effects
65
pared samples were analysed in order to assess their
The procedures used to assess the water content,
heat of combustion, fuel value, sulphur content and ash
content were based on norms PN-EN 13183-1:2004, PN-
ISO 1928:2002, PN-G-04584:2001, PN-EN 15289:2011,
PN-EN ISO 16994:2015 and PN-ISO 1171:2002.
The distance between the forests and the power
plant (accuracy ±1 km) was analysed based on the data
from the vehicle fleet database of one of the chips sup-
pliers and the analysis of parameters of chips was based
on the data agreed and signed in the contract between
the supplier and the energy company. Detailed require-
ments for energy chips supplied to the power plant are
given in Table 2.
water content, fuel value, sulphur content and ash con-
tent in the laboratory of the power plant. There was
a protocol created for every day that allowed for the
identification of date for a given supply, the physical
parameters of the chips and the related basic and set-
tlement prices.
Determination of basic and settlement value
of delivery
The values for individual deliveries of chips is based
on weight and physical parameters of the chips, which
include fuel value, water content, sulphur content and
ash content. The threshold value for water content of
the chips, as given in Table 2, is dependent on the de-
livery date. During the fall, winter and early spring
months, because of precipitation, the power plant al-
lows higher water content of about 60%, which makes
it easier for the supplier to meet the required water
content level.
Figure 1. The route of an exemplary transport vehicle and
the location of forests in relation to the base and the power
plant
Table 2. Requirements for forest biomass established
by the power plant
The value of chips at the delivery date is deter-
mined roughly, only on the basis of their weight and
basic price (ppm) agreed in the contract in accordance
with equation 1.
Min/
max
Parameter Symbol
Unit
GJ×Mg−1
%
Value
7.0
Fuel value
cvg
wg
min
50 (Apr–Sep)
60 (Oct–Mar)
Water content
max
Ki = mi × ppm
(1)
Sulphur
content
zsg
zpg
%
%
max
max
–
0.3
5.0
where
Ki – the basic value of ith delivery [PLN],
mi – the weight of the ith delivery [Mg],
ppm – the basic price ‘weight’ [PLN × Mg−1].
Ash content
Basic price
(weight)
ppm
PLN × Mg−1
193.50
Basic price
(fuel value)
ppc
PLN × GJ−1
–
21.50
The biomass is subsequently subjected to detailed
analysis in the laboratory of the power company, in
order to measure the individual parameters. In case of
noncompliance with the values set in the contract, the
power plant corrects the value of the realised delivery,
and the difference with the ‘basic’ value is settled when
the next delivery is settled. The price and settlement
value of ith delivery are established on basis of equa-
tions 2 and 3.
Price decreased for exceeding contractual limits of
Fuel value
pcj
PLN × GJ−1
PLN × GJ−1
–
–
1.08–1.12
1.08–1.12
Water content
pwj
Sulphur
content
psj
ppj
PLN × GJ−1
PLN × GJ−1
–
–
1.08–1.12
1.08–1.12
Ash content
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Arkadiusz Gendek, Tomasz Nurek
66
ppri = ppc – pwj – pcj – psj – ppj
Kri = mi × cvi × ppri
(2)
(3)
lated to the atmospheric conditions and the month of
delivery. The basic statistics are presented in Table 3.
where
Table 3. Descriptive statistics for water content and fuel
value of chips
ppri – the delivery settlement price [PLN × GJ−1],
Kri – the settlement value of ith delivery [PLN],
cvi – the fuel value of chips in the ith delivery
[GJ × Mg−1],
Month
ppc – the basic price ‘fuel’ [PLN × Mg−1],
pwj – the decrease in unit price for excessive water con-
tent [PLN × GJ−1],
Water content [%]
pcj – the decrease in the unit price for lower fuel value
[PLN × GJ−1],
psj – the decrease in the unit price for sulphur content
[PLN × GJ−1],
ppj – the decrease in the unit price for ash content
[PLN × GJ−1].
January
February
March
35
25
30
24
17
8
46.58 34.20 56.10 5.35 11.49
47.12 36.60 54.60 4.49
45.94 35.80 59.10 4.57
43.77 36.30 50.10 3.92
9.52
9.95
8.95
April
May
41.23 35.70 57.80 5.29 12.83
June
35.56 32.90 39.90 2.72
7.65
–
As visible in equations 2 and 3, the basis for final
settlement are the characteristic values for the biomass
and the unit price is related to the fuel value of the chips
and not directly to their weight. The basic unit price
(per one GJ) is reduced if the supplier fails to meet the
threshold levels of the quality parameters. The rule of
determining the final settlement price for the delivered
chips (in relation to their fuel value) is price reduction,
if the parameters of the chips are lower than the ones
defined in the contract. The mechanism does not award
(price increase) the supplier in cases where the chips are
significantly better, that is, with low water content and
higher fuel value.
July
0
–
–
–
–
August
September
October
November
December
8
39.24 29.10 55.60 8.95 22.80
27.74 23.00 31.30 3.00 10.82
36.04 26.00 46.10 5.59 15.52
37.83 25.70 50.80 7.54 19.94
43.65 31.30 55.70 6.63 15.19
Fuel value [GJ × Mg−1]
8
48
29
20
January
February
March
35
25
30
24
17
8
8.74
8.71
8.81
9.26
6.21 10.68 1.11 12.75
7.30 11.13 0.98 11.31
6.24 10.37 0.87
8.11 10.94 0.83
9.82
8.93
Using the above-defined values, it is possible to es-
tablish the average weighted delivery price (psr) in the
analysed period:
April
May
10.01 6.28 11.48 1.23 12.33
10.92 8.82 12.05 1.12 10.25
June
n
ppri × mi × cvi
July
0
–
–
–
–
–
∑
i=1


psr =
PLN/GJ
(4)


n
August
September
October
November
December
8
10.12 6.93 12.53 2.05 20.26
12.94 12.40 14.19 0.55 4.25
mi × cvi
∑
i=1
8
48
29
20
11.10 9.14 13.65 1.23 11.12
10.61 7.59 13.24 1.66 15.63
RESULTS AND DISCUSSION
9.45
7.04 11.85 1.32 13.96
On basis of analysis of randomly chosen 186 deliveries
of chips, it was established that the average transport
distance was 341.25 km (SD = 65.12) and was between
188 and 499 km.
Average water content and the resultant fuel value
of the chips supplied to the power plant is directly re-
The lowest average water content (27.74%;
SD = 3.00) and the highest fuel value (12.94 GJ × Mg-1)
were observed in case of chips supplied to the pow-
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Variability of energy woodchips and their economic effects
67
er plant in September. Owing to the fact that timber
0.027) and did not exceed the upper threshold value of
0.3% (Fig. 3), which corresponds to biomass sulphur
content of 0.02%, determined by Komorowicz et al.
(2009).
harvesting took place a few months before chipping,
the forest biomass in form of branches and treetops
rested on the ground during the summer season and
decreased its water content naturally. From October
onward, the water content increased – lower tem-
perature, rainfall and snowfall – down to the maxi-
mum water content in February, 47.12% (SD = 4.47).
From March to September (spring/summer), the water
content decreased and the fuel value increased. The
fuel value of chips delivered to the power plant was
similar to the values determined by, amongst others,
Gendek and Zychowicz (2014), Günther et al. (2012) or
Phanphanich and Mani (2009), which at low humidity
(5–7%) may achieve about 18 GJ × Mg−1.
15
14
13
12
11
10
9
8
7
The recurring character of changes in water con-
tent and fuel value indicates that the best period for
the chips suppliers are months from June to November,
when the material is characterised by the lowest aver-
age water content (<40%) and highest fuel value (>10
GJ × Mg−1). This relation is shown in Table 3 (grey
background).
6
5
20
25
30
35
40
45
50
55
60
65
Moisure content [%]
Figure 2. Relationship between the fuel value of forest wood
chips and their humidity
The problem here is the varied seasons in the year
and the heating season. During the summer months,
the power plants have lower demand for chips. In the
analysed case, the average size of daily deliveries to the
power plant was 270 Mg in June and 145 Mg in August,
while in the December–February period, it was on an
average 340–370 Mg a day.
The threshold value for water content determined
between the supplier and the recipient and the mini-
mum threshold value for fuel value (Tab. 2) regardless
of the month are values that the supplier is able to meet.
Amongst the 252 delivery days analysed, there were
eight instances of exceeding the above-mentioned pa-
rameters, including five cases of too low fuel value and
three cases of excessive water content in the chips.
The obtained results made possible to determine
the relationship between the fuel value of the chips and
their humidity (Fig. 2), that is, the following equation:
9
average
average SE
8
average SD
7
6
5
4
3
2
1
0
Figure 3. Sulphur content in chips in individual months
An important parameter from the viewpoint of the
supplier, which results in decrease in price for exceed-
ing the threshold values is the ash content (Fig. 4). The
average ash content in the analysed chips, in most cas-
es, was about 3–4%. This is about 1 percentage point
above the values present in the literature for branch
chips (Phanphanich M., Mani S. 2011) and about 1–2
percentage points above the values given for chips ac-
quired from whole trees (Tab. 1). In the analysed period,
y = −0.2139x × 18.7222; r2 = 0.9610
(5)
Another important parameters controlled by the
power plant are the content of sulphur and ash. The
average sulphur content in individual months was be-
tween 0.016% and 0.022% (minimum 0.01; maximum
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Arkadiusz Gendek, Tomasz Nurek
68
there were 29 days (11.5% of all deliveries) of deliver-
on Figures 2 and 3 shows that the average monthly val-
ues of parameters of the analysed biomass exceed the
threshold levels only in a few instances.
ies where the value exceeded the threshold. The highest
values were recorded during the summer months (June
and August), whereas the average ash content in June
was above 5% and close to that value in August. Dur-
ing the above-mentioned months, the largest diversity
of measured values was observed.
Average monthly fuel values meet the contractual
requirements every month and exceed the minimal
required values. Similarly, the sulphur content never
exceeded the threshold level. Only in the case of ash
content, there was one case of exceeding the threshold
value in June. The analysis of the average values shows
that the quality of the provided biomass is satisfactory.
Therefore, why was it so (which is shown in the graph of
Fig. 5) that the settlement price was lower than the basic
contractual price through the whole year. This situation
is due to the method that is used for calculating the set-
tlement price.
0,028
average
average SE
average SD
0,024
0,026
0,022
0,020
0,018
0,016
0,014
0,012
0,010
0,008
22,0
21,8
21,6
21,4
21,2
21,0
20,8
Figure 4. Ash content in chips in individual months
20,6
average
Ash content in chips is a parameter that may be
under certain degree of control by the supplier if the
proper method of works during chipping is selected.
It may be assumed that the excess ash comes most-
ly from mineral contaminants, which are present in
the form of sand in the forest floor and tree bark and
are acquired during unskilful grabbing of the logging
residue.
average SE
20,4
average SE
ppc
psr
20,2
20,0
July
May
April
June
March
August
September
January
February
October
November
December
Figure 5. Unit price after the reduction for exceeding the
norms [PLN × GJ−1]; ppc, basic price; psr, average settlement
price
Taking into consideration the contractual and the
measured parameters of chips supplied to the power
plant after accounting for the deductions for exceeding
the norms, the average settlement price for GJ of energy
is calculated. Results are presented in Figure 5. De-
pending on the month of deliveries, the settlement price
is from less than 10 to more than a few dozen groszy
(1/100 PLN) worse than the basic price. The largest dif-
ference is present in June and August, when the number
of deliveries with excessive ash content was the largest.
These are, however, summer months where the demand
for energy is lower and the daily deliveries are reduced
in comparison to other months.
The settlement price is related to daily deliveries
and may be corrected only downwards if the required
parameters are not met by the supplier. As it was men-
tioned earlier, there is no award for deliveries of higher
quality. This system means that every negative devia-
tion from the set values decreases the settlement price
and that there is no mechanism that could increase the
said price. In such a case, determination of the settle-
ment price on the basis of average monthly values of
quality parameters is not the correct mechanism.
When assessing the settlement system between the
suppliers and the recipients of the forest woodchips, we
have to state that in many cases, it works to the detri-
Interesting conclusions may be drawn by compar-
ing the above-mentioned data. The data in Table 3 and
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Variability of energy woodchips and their economic effects
69
ment of the supplier, resulting in the basic price being
lowered in all the analysed months.
ku biomasy [Logistic model project for the local
biomass market]. Logistyka, 4, 846–854 [in Polish
with English abstract].
In the analysed case of a single supplier (Fig. 5),
the average annual settlement price for 1 GJ of energy
was about 0.2 PLN lower than the contract price, which
translates into daily loss for the supplier of about 700
PLN and during a month (depending the number of days
with deliveries) from a few thousand PLNs to (in some
extreme cases) about 14,000 PLN.
Gendek A., Głowacki S. 2008. Badania wstępne susze-
nia zrębków sosnowych przeznaczonych na cele
energetyczne [Preliminary studies drying pine
wood chips intended for energy purposes]. In: Ten-
dencje i problemy techniki leśnej w warunkach leś-
nictwa wielofunkcyjnego (eds.: H. Różański, K. Ja-
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CONCLUSIONS
Gendek A., Głowacki S. 2009. Convectional drying of
chips for energy purposes. Annals of Warsaw Uni-
versity of Life Sciences – SGGW. Agriculture, 53,
67–72.
Gendek A., Zychowicz W. 2014. Investigations on the
calorific value of forest chips. Annals of Warsaw
University of Life Sciences – SGGW. Agriculture,
63, 65–72.
Gołos P., Kaliszewski A. 2013. Biomasa leśna na cele
energetyczne [Forest biomass for energy purposes].
Wydawnictwo IBL, Sękocin Stary, Poland [in Po-
lish].
Grilli G., Garegnani G., Poljanec A., Ficko A., Vetto-
rato D., De Meo I., Paletto A. 2015 Stakeholder ana-
lysis in the biomass energy development based on
the experts’ opinions: the example of Triglav Na-
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ffp-2015-0017.
In the analysed period, there were 11.5% of all deliver-
ies where the values exceeded the contractual threshold.
However, it turned out that the average price in every
analysed months was lower than the one agreed with
the recipient.
Sulphur content did not impact the base price in set-
tlements between the supplier and the recipient as the
threshold levels have not been exceeded.
The problem is the excessive ash content. There is
a need for further research concerning factors impact-
ing the ash content in the chips: contents of the forest
biomass (wood, needles, bark) and contaminants (sand,
forest flooring).
The settlement system used for the delivered chips
is disadvantageous for the suppliers. It allows for the
price being lowered if some of the parameters are not
met but does not foresee a method for increasing the
price.
GUS 2013. Leśnictwo 2013. Informacje i opracowania
statystyczne [GUS 2013. Forestry 2013. Statistical
information and reports]. Główny Urząd Statystyc-
zny, Warszawa [in Polish].
The analysed method of settlement between the
supplier and the recipient of forest chips does not take
into consideration the distance between the location
where the material is acquired and the location of the re-
cipient. If this is possible, the transport distance should
be taken into consideration when setting the basic price.
Günther B., Gebauer K., Barkowski R., Rosenthal M.,
Bues C.T. 2012. Calorific value of selected wood
species and wood products. European Journal of
Wood and Wood Products, 70 (5), 755–757.
Hałuzo M., Musiał R. 2004. Ocena zasobów i potencjal-
nych możliwości pozyskania surowców dla ener-
getyki odnawialnej w województwie pomorskim
[Evaluation of resources and the potential to obtain
raw materials for renewable energy in Pomorskie].
Biuro Planowania Przestrzennego w Słupsku,
Słupsk [in Polish].
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