Comparing Net Present Value of the Installation of Carbon-Active and Nano-Tube-Carbon Filters Using Monte Carlo Simulation
The paper purposes to evaluate the Net Present Value (NPV) of the installation of Carbon-active and Nano-tube-Carbon filters to filter (refine) Mononitrotoluene. The evaluation will help us recognize the more economical filter. The lifetime of Carbon-active filters and Nano-tube-Carbon filters are 9 and 50 days, respectively. Hence their NPVs will be calculated during 450 days. Since the costs of installation are probabilistic, Monte Carlo simulation is used to calculate the NPVs. The average amounts of installation for Carbon-active filters and Nano-tube-Carbon filters are 2331168140 Rials and 12038414350 Rials, respectively. Therefore, the Nano-tube-Carbon filter is much more economical to be installed than the Carbon-active one.
Content
International Journal of Economy, Management and Social Sciences, 2(6) June 2013, Pages: 318-321
TI Journals
International Journal of Economy, Management and Social Sciences
ISSN
2306-7276
www.tijournals.com
Comparing Net Present Value of the Installation of
Carbon-Active and Nano-Tube-Carbon Filters Using
Monte Carlo Simulation
Ehsan Izadi1, Hamid Reza Sobhi 2, Seyed Mojtaba Sajadi1, Ali Behmaneshfar*3
1
2
3
Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Isfahan, Iran.
Department of Chemistry, Tehran Payamenoor University, Tehran, Iran.
Young Researchers and Elite Club, Najafabad Branch, Islamic Azad University, Najafabad, Isfahan, Iran.
AR TIC LE INF O
AB STR AC T
Keywords:
The paper purposes to evaluate the Net Present Value (NPV) of the installation of Carbon-active
and Nano-tube-Carbon filters to filter (refine) Mononitrotoluene. The evaluation will help us
recognize the more economical filter. The lifetime of Carbon-active filters and Nano-tube-Carbon
filters are 9 and 50 days, respectively. Hence their NPVs will be calculated during 450 days. Since
the costs of installation are probabilistic, Monte Carlo simulation is used to calculate the NPVs.
The average amounts of installation for Carbon-active filters and Nano-tube-Carbon filters are
2331168140 Rials and 12038414350 Rials, respectively. Therefore, the Nano-tube-Carbon filter is
much more economical to be installed than the Carbon-active one.
Carbon active filter
Nano tube carbon filter
Economic evaluation
Monte Carlo simulation
Net present value
© 2013 Int. j. econ. manag. soc. sci. All rights reserved for TI Journals.
1.
Introduction
In munitions industry- the explosives production sector, and even more precisely, in Trinitrotoluene (TNT) production cycle, it is always
common also to produce a parallel material, called Mononitrotoluene which is highly poisonous, fatal and dangerous for human and causes
nature pollution. There are two kinds of filters suggested in order to filter (refine) the material: Carbon-active filters and Nano-tube-Carbon
filters. The purpose of this paper is to recognize and introduce the more economical filter.
Most economic evaluations set Net Present Value as the evaluation criterion and use Monte Carlo simulation when the variables of NPV
are probabilistic. Li et al. did an investment risk analysis of wind power project in China [1] in the same way. Gebrezgabher et al.
investigated the economic feasibility of producing green gas from digestion of dairy manure and other co substrates [2]. Amigun et al.
examined the contribution of parametric uncertainty to economic feasibility studies for biomass-to ethanol process plants [3]. Tsamboulas
and Kapros presented a method and models for assessing the financial viability of a new Freight village financed by private and public
investments [4]. Bryan et al. assessed the potential economic viability of biomass production in the South Australian River Murray Corridor
and quantified the resultant benefits for local and global scale environmental objectives [5].Walters and Walsh evaluated the effect of the
upcoming 2010 UK Feed-in Tariff on decentralized small wind-energy installations at the household and building level in urban locations
[6].Yu and Tao assessed and compared the economic viabilities and investment risks of three biomass-based fuel ethanol projects in
different feedstock planting areas in China [7].
There are some studies for economic evaluation of filtration. For example, Listowski established an economic evaluation model for urban
recycled water [8]. In this paper, we perform an economic evaluation for installation of Nano tube and Carbon-active filters.
The rest of this paper is structured as follows: In Section 2, we introduce the NPV method. In Section 3, the process of utilizing Monte
Carlo simulation method to calculate the NPV is established. In section 4, we compare two types of filter from economic point of view.
Conclusion is presented in the last section.
2. Methodology
Net Present Value
We use NPV as an evaluation criterion. The net cash flow, calculated by subtracting the cost from the revenue, was discounted by the
interest rate to obtain the NPV of the project. If NPV is a function of all both deterministic and stochastic variables, the resulting NPV gets
a range of values instead of a single value obtained in a conventional deterministic financial evaluation. NPV is obtained from the below
formula.
* Corresponding author.
Email address: [email protected]
Comparing Net Present Value of the Installation of Carbon-Active and Nano-Tube-Carbon Filters Using Monte Carlo Simulation
319
Internat ional Jour nal of Economy, Mana ge ment and Social Sciences , 2(6) June 2013
n
(rt ct )
t
t 0 (1 i )
NPV
(1)
Where i is the interest (discount) rate, rt is the revenue at year t, ct is costs at year t, n is the number of years.
Monte Carlo simulation
Monte Carlo simulation is a computational algorithm designed to evaluate the variability or stochastic of the input variables of a model. It
can be used to model the effects of key variables on the NPV of a given proposal. The process involves, first, the identification and
assessment of the key variables. For each key variable, we fit a probability density function that best describes the range of uncertainty
around the expected value. For this purpose, we can use Kolmogorov-Smirnov, Chi-Squared and Anderson-Darling Criteria [9-11]. The
model including these variables is then calculated using randomly-generated input values taken from the underlying probabilistic
distribution function. The computer model combines these inputs to generate an estimated outcome value (for example an NPV). The
process is repeated (one hundred times).
3. Comparison of the filters
The mutual costs of production and utilization of the two kinds of filters are as follows:
1)
2)
3)
4)
5)
Rinsing through one liter of acetonitrile
Filter shield (box)
Filtering material
Production operation
Initial material (the Carbon-absorbent material for Carbon-active filters and Nano-absorbent material for Nano-tube-Carbon
filters)
Nano-tube-Carbon filters should be rinsed every 10 days, while Carbon-active ones should be rinsed every 3 days. Thus, the first cost of
above is paid every 10 and every 3 days for the first and the second kind, respectively. It is necessary to add up all the costs 2, 3, 4, and 5 to
produce any kind of filter which is assumed as the finance cost. This cost in Nano-tube-Carbon filter is more than Carbon-active ones due
to the fifth cost, the only cost which is not the same for both filters. Therefore, it is required to finance more in order to produce Nano-tubeCarbon filters. The price fluctuations in ten consecutive months of 2012 are illustrated in Table 1.The suitable probability density function
of costs is fitted by Kolmogorov-Smirnov criterion, regarding to the price fluctuations. The results are shown in Table 2.
Table 1. The fluctuation of prices for the costs of construction and utilization of filters
Month
January
February
March
April
May
June
July
August
September
October
acetonitrile
56000
57200
57900
58000
58150
59820
63000
67000
67650
69000
Container
15000
15500
16300
17100
17900
18300
19000
19150
19470
19900
Filter Material
1000
1200
1500
1800
2100
2300
2350
2470
2590
2750
Carbon-active
Absorbents
33000
35000
38000
42000
46000
47500
48900
51200
53000
53750
Nanoabsorbents
83000
87000
91000
95000
99000
102000
103400
104700
105200
105900
3000
3300
3600
4000
4400
5000
5200
5450
5450
5450
Production
Operation
Table 2. Probability functions fitted to the costs of construction and utilization of filters
Type of Cost
acetonitrile
Pruchase
Filter Container
Purchase
Filter Material
Purchase
Production
Operation
Carbon-active Absorbents
Material Purchase
Nano-absorbents
Material Purchase
Probability density
function
Wakeby
GenExtreme
GenExtreme
GenLogistic
GenExtreme
GenExtreme
P-Value
0.92004
0.99776
0.99801
0.89412
0.99499
0.94465
Ehsan Izadi et al.
320
Int ernational Journal of Ec onomy, Mana ge me nt and Soci al Sc iences , 2(6) June 2013
In the case of not installing any filters, the Nature Protection Organization will fine the firm for 30000000 Rials daily, due the pollution
caused by Mononitrotoluene entrance to the nature. If Carbon-active filters are used, the fine amount will be reduced to 24000000 Rials
daily, because of less pollution consequents. If Nano-tube-Carbon filters are installed, no fine will occur. Therefore, the amounts 6000000
Rials and 300000000 Rials are considered as daily incomes of the Carbon-active filters and Nano-tube-Carbon filters, respectively. The
lifetimes of the Carbon-active filters and Nano-tube-Carbon filters are estimated 9 and 50 days, respectively. The economic comparison of
the two kinds is executed in a 450-day period with an annual interest rate of 0.2 (which is converted to daily interest rate through the
following equation as it is equal to 0.0005).
annual interest rate=(1+daily interest rate)365 1
(2)
The simulation was iterated 100 times. The NPV histograms of the Carbon-active filters and Nano-tube-Carbon filters are shown in Figures
1 and 2, respectively. The NPV average of the Carbon-active filters and Nano-tube-Carbon filters are 2331168140 and 12038414350,
respectively. For the NPV amount of the Nano-tube-Carbon filters is much more than the other one, this is much more economical than the
Carbon-active filter; on the other hand, the initial finance in the Nano-tube-Carbon filters is more than the one in Carbon-active filters. The
fact of being more economical is due to two things: first, the lifetime of the Nano-tube-Carbon filters is more than the lifetime of its
counterpart. Second, the installation of the Carbon-active filters leads to pay for the fine which the Nature Protection Organization imposed
the firm.
4.
Conclusion
It is possible to use two kinds of filters (Carbon-active or Nano-tube-Carbon), in order to eliminate the pollutant, Mononitrotoluene. The
production and utilization costs of these two kinds of filters are stochastic. Therefore, it is not possible to use the deterministic version of
NPV for economic evaluation of them. Monte Carlo simulation is an appropriate method for economic evaluation of those choices which
have stochastic variables. That is why we also used the Monte Carlo simulation to evaluate the economical value of the Carbon-active
filters and Nano-tube-Carbon filters. Despite the more initial finance for the installation of the Nano-tube-Carbon filters, the resulting NPV
average output of the simulation for them was much more economical than the Carbon-active filters. The exorbitant difference between the
two average amounts was due to the following two reasons. Not only the lifetime of the Carbon-active filters is less than the lifetime of the
Nano-tube-Carbon filters, but also the installation of the Carbon-active filters ends in fines coming from the Nature Protection
Organization. Thus, Nano-tube-Carbon filters are more economical than Carbon-active filters.
Acknowledgements
The authors wish to acknowledge Mr. Siyavash Khaledan and Mr. Milad Anvari for their constructive comments.
Histogram
25
Frequency
20
15
10
5
0
231500000 232000000 232500000 233000000 233500000 234000000 234500000
NPV
Figure 1. Histogram of NPV for Carbon-active filter
Comparing Net Present Value of the Installation of Carbon-Active and Nano-Tube-Carbon Filters Using Monte Carlo Simulation
321
Internat ional Jour nal of Economy, Mana ge ment and Social Sciences , 2(6) June 2013
Histogram
18
16
Frequency
14
12
10
8
6
4
2
0
02
12
00
00
0
8
12
00
00
03
00
12
00
20
03
00
0
12
00
00
0
34
0
12
00
00
6
3
0
12
0
80
03
0
00
12
04
00
00
00
12
04
00
20
00
NPV
Figure 2. Histogram of NPV for Nano-tube carbon filter
References
[1] Li, C.B., Lu, G.S., Wu, S., 2013. The investment risk analysis of wind power project in China. Renewable Energy 50, 481-7.
[2] Gebrezgabher, S.A., Meuwissen, M.P.M., Oude Lansink, A.G.J.M., 2 0 1 2. Energy-neutral dairy chain in the Netherlands: An economic feasibility
analysis. Biomass and Bio energy 36, 60-8.
[3] Amigun, B., Petrie, D., Görgens, J., 2011. Economic risk assessment of advanced process technologies for bioethanol production in South Africa: Monte
Carlo analysis. Renewable Energy 36, 3178-86.
[4] Tsamboulas, D.A., Kapros, S., 2003. Freight village evaluation under uncertainty with public and private financing. Transport Policy 10, 141–156.
[5] Bryan, B.A., Ward, J., Hobbs, T., 2008. An assessment of the economic and environmental potential of biomass production in an agricultural region.
Land Use Policy 25, 533–49.
[6] Walters, R., Walsh, P.R., 2011. Examining the financial performance of micro-generation wind projects and the subsidy effect of feed-in tariffs for urban
locations in the United Kingdom. Energy Policy 39, 5167–81.
[7] Yu, S., Tao, J., 2008. Life cycle simulation-based economic and risk assessment of biomass-based fuel ethanol (BFE) projects in different feedstock
planting areas. Energy 33, 375–84.
[8] Listowski, A., Ngo, H.H., Guo, W.S., 2013. Establishment of an economic evaluation model for urban recycled water. Resources, Conservation and
Recycling 72, 67– 75.
[9] Nikulin, M. S., 1973. Chi-squared test for normality. in Proceedings of the International Vilnius Conference on Probability Theory and Mathematical
Statistics 2, 119–22.
[10] Anderson, T. JV., and Darling, D. A., 1952. Asymptotic theory of certain 'goodness of fit' criteria based on stochastic processes. Annals of
Mathematical Statistics 23, 193-212.
[11] Smirnov, N.V., 1948. Tables for estimating the goodness of fit of empirical istributions", Annals of Mathematical Statistics 19, 279.
TI Journals
International Journal of Economy, Management and Social Sciences
ISSN
2306-7276
www.tijournals.com
Comparing Net Present Value of the Installation of
Carbon-Active and Nano-Tube-Carbon Filters Using
Monte Carlo Simulation
Ehsan Izadi1, Hamid Reza Sobhi 2, Seyed Mojtaba Sajadi1, Ali Behmaneshfar*3
1
2
3
Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Isfahan, Iran.
Department of Chemistry, Tehran Payamenoor University, Tehran, Iran.
Young Researchers and Elite Club, Najafabad Branch, Islamic Azad University, Najafabad, Isfahan, Iran.
AR TIC LE INF O
AB STR AC T
Keywords:
The paper purposes to evaluate the Net Present Value (NPV) of the installation of Carbon-active
and Nano-tube-Carbon filters to filter (refine) Mononitrotoluene. The evaluation will help us
recognize the more economical filter. The lifetime of Carbon-active filters and Nano-tube-Carbon
filters are 9 and 50 days, respectively. Hence their NPVs will be calculated during 450 days. Since
the costs of installation are probabilistic, Monte Carlo simulation is used to calculate the NPVs.
The average amounts of installation for Carbon-active filters and Nano-tube-Carbon filters are
2331168140 Rials and 12038414350 Rials, respectively. Therefore, the Nano-tube-Carbon filter is
much more economical to be installed than the Carbon-active one.
Carbon active filter
Nano tube carbon filter
Economic evaluation
Monte Carlo simulation
Net present value
© 2013 Int. j. econ. manag. soc. sci. All rights reserved for TI Journals.
1.
Introduction
In munitions industry- the explosives production sector, and even more precisely, in Trinitrotoluene (TNT) production cycle, it is always
common also to produce a parallel material, called Mononitrotoluene which is highly poisonous, fatal and dangerous for human and causes
nature pollution. There are two kinds of filters suggested in order to filter (refine) the material: Carbon-active filters and Nano-tube-Carbon
filters. The purpose of this paper is to recognize and introduce the more economical filter.
Most economic evaluations set Net Present Value as the evaluation criterion and use Monte Carlo simulation when the variables of NPV
are probabilistic. Li et al. did an investment risk analysis of wind power project in China [1] in the same way. Gebrezgabher et al.
investigated the economic feasibility of producing green gas from digestion of dairy manure and other co substrates [2]. Amigun et al.
examined the contribution of parametric uncertainty to economic feasibility studies for biomass-to ethanol process plants [3]. Tsamboulas
and Kapros presented a method and models for assessing the financial viability of a new Freight village financed by private and public
investments [4]. Bryan et al. assessed the potential economic viability of biomass production in the South Australian River Murray Corridor
and quantified the resultant benefits for local and global scale environmental objectives [5].Walters and Walsh evaluated the effect of the
upcoming 2010 UK Feed-in Tariff on decentralized small wind-energy installations at the household and building level in urban locations
[6].Yu and Tao assessed and compared the economic viabilities and investment risks of three biomass-based fuel ethanol projects in
different feedstock planting areas in China [7].
There are some studies for economic evaluation of filtration. For example, Listowski established an economic evaluation model for urban
recycled water [8]. In this paper, we perform an economic evaluation for installation of Nano tube and Carbon-active filters.
The rest of this paper is structured as follows: In Section 2, we introduce the NPV method. In Section 3, the process of utilizing Monte
Carlo simulation method to calculate the NPV is established. In section 4, we compare two types of filter from economic point of view.
Conclusion is presented in the last section.
2. Methodology
Net Present Value
We use NPV as an evaluation criterion. The net cash flow, calculated by subtracting the cost from the revenue, was discounted by the
interest rate to obtain the NPV of the project. If NPV is a function of all both deterministic and stochastic variables, the resulting NPV gets
a range of values instead of a single value obtained in a conventional deterministic financial evaluation. NPV is obtained from the below
formula.
* Corresponding author.
Email address: [email protected]
Comparing Net Present Value of the Installation of Carbon-Active and Nano-Tube-Carbon Filters Using Monte Carlo Simulation
319
Internat ional Jour nal of Economy, Mana ge ment and Social Sciences , 2(6) June 2013
n
(rt ct )
t
t 0 (1 i )
NPV
(1)
Where i is the interest (discount) rate, rt is the revenue at year t, ct is costs at year t, n is the number of years.
Monte Carlo simulation
Monte Carlo simulation is a computational algorithm designed to evaluate the variability or stochastic of the input variables of a model. It
can be used to model the effects of key variables on the NPV of a given proposal. The process involves, first, the identification and
assessment of the key variables. For each key variable, we fit a probability density function that best describes the range of uncertainty
around the expected value. For this purpose, we can use Kolmogorov-Smirnov, Chi-Squared and Anderson-Darling Criteria [9-11]. The
model including these variables is then calculated using randomly-generated input values taken from the underlying probabilistic
distribution function. The computer model combines these inputs to generate an estimated outcome value (for example an NPV). The
process is repeated (one hundred times).
3. Comparison of the filters
The mutual costs of production and utilization of the two kinds of filters are as follows:
1)
2)
3)
4)
5)
Rinsing through one liter of acetonitrile
Filter shield (box)
Filtering material
Production operation
Initial material (the Carbon-absorbent material for Carbon-active filters and Nano-absorbent material for Nano-tube-Carbon
filters)
Nano-tube-Carbon filters should be rinsed every 10 days, while Carbon-active ones should be rinsed every 3 days. Thus, the first cost of
above is paid every 10 and every 3 days for the first and the second kind, respectively. It is necessary to add up all the costs 2, 3, 4, and 5 to
produce any kind of filter which is assumed as the finance cost. This cost in Nano-tube-Carbon filter is more than Carbon-active ones due
to the fifth cost, the only cost which is not the same for both filters. Therefore, it is required to finance more in order to produce Nano-tubeCarbon filters. The price fluctuations in ten consecutive months of 2012 are illustrated in Table 1.The suitable probability density function
of costs is fitted by Kolmogorov-Smirnov criterion, regarding to the price fluctuations. The results are shown in Table 2.
Table 1. The fluctuation of prices for the costs of construction and utilization of filters
Month
January
February
March
April
May
June
July
August
September
October
acetonitrile
56000
57200
57900
58000
58150
59820
63000
67000
67650
69000
Container
15000
15500
16300
17100
17900
18300
19000
19150
19470
19900
Filter Material
1000
1200
1500
1800
2100
2300
2350
2470
2590
2750
Carbon-active
Absorbents
33000
35000
38000
42000
46000
47500
48900
51200
53000
53750
Nanoabsorbents
83000
87000
91000
95000
99000
102000
103400
104700
105200
105900
3000
3300
3600
4000
4400
5000
5200
5450
5450
5450
Production
Operation
Table 2. Probability functions fitted to the costs of construction and utilization of filters
Type of Cost
acetonitrile
Pruchase
Filter Container
Purchase
Filter Material
Purchase
Production
Operation
Carbon-active Absorbents
Material Purchase
Nano-absorbents
Material Purchase
Probability density
function
Wakeby
GenExtreme
GenExtreme
GenLogistic
GenExtreme
GenExtreme
P-Value
0.92004
0.99776
0.99801
0.89412
0.99499
0.94465
Ehsan Izadi et al.
320
Int ernational Journal of Ec onomy, Mana ge me nt and Soci al Sc iences , 2(6) June 2013
In the case of not installing any filters, the Nature Protection Organization will fine the firm for 30000000 Rials daily, due the pollution
caused by Mononitrotoluene entrance to the nature. If Carbon-active filters are used, the fine amount will be reduced to 24000000 Rials
daily, because of less pollution consequents. If Nano-tube-Carbon filters are installed, no fine will occur. Therefore, the amounts 6000000
Rials and 300000000 Rials are considered as daily incomes of the Carbon-active filters and Nano-tube-Carbon filters, respectively. The
lifetimes of the Carbon-active filters and Nano-tube-Carbon filters are estimated 9 and 50 days, respectively. The economic comparison of
the two kinds is executed in a 450-day period with an annual interest rate of 0.2 (which is converted to daily interest rate through the
following equation as it is equal to 0.0005).
annual interest rate=(1+daily interest rate)365 1
(2)
The simulation was iterated 100 times. The NPV histograms of the Carbon-active filters and Nano-tube-Carbon filters are shown in Figures
1 and 2, respectively. The NPV average of the Carbon-active filters and Nano-tube-Carbon filters are 2331168140 and 12038414350,
respectively. For the NPV amount of the Nano-tube-Carbon filters is much more than the other one, this is much more economical than the
Carbon-active filter; on the other hand, the initial finance in the Nano-tube-Carbon filters is more than the one in Carbon-active filters. The
fact of being more economical is due to two things: first, the lifetime of the Nano-tube-Carbon filters is more than the lifetime of its
counterpart. Second, the installation of the Carbon-active filters leads to pay for the fine which the Nature Protection Organization imposed
the firm.
4.
Conclusion
It is possible to use two kinds of filters (Carbon-active or Nano-tube-Carbon), in order to eliminate the pollutant, Mononitrotoluene. The
production and utilization costs of these two kinds of filters are stochastic. Therefore, it is not possible to use the deterministic version of
NPV for economic evaluation of them. Monte Carlo simulation is an appropriate method for economic evaluation of those choices which
have stochastic variables. That is why we also used the Monte Carlo simulation to evaluate the economical value of the Carbon-active
filters and Nano-tube-Carbon filters. Despite the more initial finance for the installation of the Nano-tube-Carbon filters, the resulting NPV
average output of the simulation for them was much more economical than the Carbon-active filters. The exorbitant difference between the
two average amounts was due to the following two reasons. Not only the lifetime of the Carbon-active filters is less than the lifetime of the
Nano-tube-Carbon filters, but also the installation of the Carbon-active filters ends in fines coming from the Nature Protection
Organization. Thus, Nano-tube-Carbon filters are more economical than Carbon-active filters.
Acknowledgements
The authors wish to acknowledge Mr. Siyavash Khaledan and Mr. Milad Anvari for their constructive comments.
Histogram
25
Frequency
20
15
10
5
0
231500000 232000000 232500000 233000000 233500000 234000000 234500000
NPV
Figure 1. Histogram of NPV for Carbon-active filter
Comparing Net Present Value of the Installation of Carbon-Active and Nano-Tube-Carbon Filters Using Monte Carlo Simulation
321
Internat ional Jour nal of Economy, Mana ge ment and Social Sciences , 2(6) June 2013
Histogram
18
16
Frequency
14
12
10
8
6
4
2
0
02
12
00
00
0
8
12
00
00
03
00
12
00
20
03
00
0
12
00
00
0
34
0
12
00
00
6
3
0
12
0
80
03
0
00
12
04
00
00
00
12
04
00
20
00
NPV
Figure 2. Histogram of NPV for Nano-tube carbon filter
References
[1] Li, C.B., Lu, G.S., Wu, S., 2013. The investment risk analysis of wind power project in China. Renewable Energy 50, 481-7.
[2] Gebrezgabher, S.A., Meuwissen, M.P.M., Oude Lansink, A.G.J.M., 2 0 1 2. Energy-neutral dairy chain in the Netherlands: An economic feasibility
analysis. Biomass and Bio energy 36, 60-8.
[3] Amigun, B., Petrie, D., Görgens, J., 2011. Economic risk assessment of advanced process technologies for bioethanol production in South Africa: Monte
Carlo analysis. Renewable Energy 36, 3178-86.
[4] Tsamboulas, D.A., Kapros, S., 2003. Freight village evaluation under uncertainty with public and private financing. Transport Policy 10, 141–156.
[5] Bryan, B.A., Ward, J., Hobbs, T., 2008. An assessment of the economic and environmental potential of biomass production in an agricultural region.
Land Use Policy 25, 533–49.
[6] Walters, R., Walsh, P.R., 2011. Examining the financial performance of micro-generation wind projects and the subsidy effect of feed-in tariffs for urban
locations in the United Kingdom. Energy Policy 39, 5167–81.
[7] Yu, S., Tao, J., 2008. Life cycle simulation-based economic and risk assessment of biomass-based fuel ethanol (BFE) projects in different feedstock
planting areas. Energy 33, 375–84.
[8] Listowski, A., Ngo, H.H., Guo, W.S., 2013. Establishment of an economic evaluation model for urban recycled water. Resources, Conservation and
Recycling 72, 67– 75.
[9] Nikulin, M. S., 1973. Chi-squared test for normality. in Proceedings of the International Vilnius Conference on Probability Theory and Mathematical
Statistics 2, 119–22.
[10] Anderson, T. JV., and Darling, D. A., 1952. Asymptotic theory of certain 'goodness of fit' criteria based on stochastic processes. Annals of
Mathematical Statistics 23, 193-212.
[11] Smirnov, N.V., 1948. Tables for estimating the goodness of fit of empirical istributions", Annals of Mathematical Statistics 19, 279.
