compost product to end users within an average
distance of 20 km each way. The use of trucks
results in CO 2 emissions ranging from 2.6 to
3 kg/L of diesel fuel (Ruiz et al. 2013). In this
study, CO 2 emissions of 3 kg/L of diesel fuel
were used and the CO 2 emissions are calculated
based on a mean distance of 20 km and diesel
consumption of 0.45 L/km.
4.3 Sensitivity Analysis Using Monte
Carlo Simulation
To assess the sensitivity of the results to variation
in input variables such as variation in unit
investment cost, production cost, price of compost and other variables, a simulation model is
developed using the Monte Carlo approach.
Using this simulation model, the uncertainty of
variations in input cost and price of outputs was
incorporated into the economic assessment.
Using this simulation model, the uncertainty of
variations in input cost and price of outputs was
incorporated into the economic assessment.
Table 4 presents the stochastic variables and
the distribution assumed for each variable. The
unit investment cost, production cost and price of
compost showed variations across the surveyed
compost plants in Kenya (Table 2). A distribution was fitted on the data collected from the field
to determine the probability distributions for the
value of investment cost, production cost and
price per ton of compost. The mean value of unit
investment cost is 213 USD/ton of compost,
mean production cost is 55 USD/ton and mean
selling price of compost is 162 USD/ton based
on the observed values from the field survey.
Normal and lognormal distributions were
assumed to model the variations in investment
cost, price of compost and production cost. For
Table 3 GHG emissions
under baseline and
alternative scenario (ton
CO 2 -eq/ton of waste)
Value
Avoided GHG emissions under baseline scenario
Emissions from open dumping
0.47
Emissions from transporting MSW to dumpsite
0.0036
GHG emissions under decentralized compost business scenario
Emissions from composting MSW (organic fraction)
0.32
Emissions from transporting inorganic fraction of MSW
0.0009
Emissions from transporting compost to end users
0.0005
Table 4 Stochastic
variables and distribution
assumed for each variable
in the simulation model
Variable
Unit
Distribution
type
Description/value
Investment cost
USD/ton
Normal
Mean = 213
SD = 139
Production cost
USD/ton
Lognormal
Mean = 55
SD = 43
Price of compost
USD/ton
Normal
Mean = 162
SD = 73
Price of carbon credit
USD/ton CO 2 -
eq
Triangular
Minimum = 7
Most likely = 10
Maximum = 14
Discount factor
%
Triangular
Minimum = 10
Most likely = 12
Maximum = 14.5
Nutrient Recovery for Use in Agriculture …
33
distance of 20 km each way. The use of trucks
results in CO 2 emissions ranging from 2.6 to
3 kg/L of diesel fuel (Ruiz et al. 2013). In this
study, CO 2 emissions of 3 kg/L of diesel fuel
were used and the CO 2 emissions are calculated
based on a mean distance of 20 km and diesel
consumption of 0.45 L/km.
4.3 Sensitivity Analysis Using Monte
Carlo Simulation
To assess the sensitivity of the results to variation
in input variables such as variation in unit
investment cost, production cost, price of compost and other variables, a simulation model is
developed using the Monte Carlo approach.
Using this simulation model, the uncertainty of
variations in input cost and price of outputs was
incorporated into the economic assessment.
Using this simulation model, the uncertainty of
variations in input cost and price of outputs was
incorporated into the economic assessment.
Table 4 presents the stochastic variables and
the distribution assumed for each variable. The
unit investment cost, production cost and price of
compost showed variations across the surveyed
compost plants in Kenya (Table 2). A distribution was fitted on the data collected from the field
to determine the probability distributions for the
value of investment cost, production cost and
price per ton of compost. The mean value of unit
investment cost is 213 USD/ton of compost,
mean production cost is 55 USD/ton and mean
selling price of compost is 162 USD/ton based
on the observed values from the field survey.
Normal and lognormal distributions were
assumed to model the variations in investment
cost, price of compost and production cost. For
Table 3 GHG emissions
under baseline and
alternative scenario (ton
CO 2 -eq/ton of waste)
Value
Avoided GHG emissions under baseline scenario
Emissions from open dumping
0.47
Emissions from transporting MSW to dumpsite
0.0036
GHG emissions under decentralized compost business scenario
Emissions from composting MSW (organic fraction)
0.32
Emissions from transporting inorganic fraction of MSW
0.0009
Emissions from transporting compost to end users
0.0005
Table 4 Stochastic
variables and distribution
assumed for each variable
in the simulation model
Variable
Unit
Distribution
type
Description/value
Investment cost
USD/ton
Normal
Mean = 213
SD = 139
Production cost
USD/ton
Lognormal
Mean = 55
SD = 43
Price of compost
USD/ton
Normal
Mean = 162
SD = 73
Price of carbon credit
USD/ton CO 2 -
eq
Triangular
Minimum = 7
Most likely = 10
Maximum = 14
Discount factor
%
Triangular
Minimum = 10
Most likely = 12
Maximum = 14.5
Nutrient Recovery for Use in Agriculture …
33