sector. These synergies with a nexus approach in
mind present a great opportunity to mitigate the
prevailing waste management problems while
addressing soil nutrient depletion and environmental pollution (Sallwey et al. 2017).
The link between waste and water is also
equally important as wastewater can be used as a
source of water and plant nutrients (Hettiarachchi
et al. 2018; Weckenbrock and Alabaster 2015).
Recovering and reuse of waste as a source of
nutrient not only adds to the restoration of
ecosystem services but also reduces negative
externalities such as GHG emissions associated
with improper management of waste in developing countries (Kong et al. 2012).
4 Materials and Methods
4.1 Economic Assessment
The economic assessment is done based on
Return on Investment (ROI), Net Present Value
(NPV) and Benefit Cost Ratio (BCR) valuation
criteria. ROI measures per period; the rates of
return on money invested in the business and is
determined by dividing net profit by total
investment. The NPV is the total sum of the
present value of expected future cash flows.
Higher ROI and NPV values represent greater
economic benefits. The BCR is the ratio of the
total benefit of a project relative to its costs, both
benefits and costs expressed in discounted present values.
The economic analysis of the decentralized
compost business model is based on the data
collected in 2015 from 22 operating compost
plants located in different counties and cities of
Kenya. In this section, we first provide descriptive statistics of the surveyed plants, which will
be used as a basis for building the financial
model for the decentralized compost business
model.
4.1.1 Technical and Financial Data
of Compost Plants in Kenya
Table 2 shows data from the year 2014 on
selected parameters of surveyed compost plants
in Kenya. Data was collected pertaining to the
production capacity, capacity utilization, quantity
Table 2 Technical and economic data of compost plants in Kenya
Item
Capacity of the plant (tons of compost/year)
All
<100 tons
(n = 6)
100–500 tons
(n = 11)
>500 tons
(n = 3)
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Technical data
Land size (acres)
0.70
0.39
1.84
1.99
1.74
1.04
1.64
1.75
Capital utilization (%)
53
16
51
21
75
35
52
23
Quantity of waste
(ton/year)
139
68
466
154
1050
212
420
311
Input–output ratio (%)
0.55
0.24
0.51
0.16
0.50
0.25
0.53
0.19
Financial data
Investment cost
(KES
a /ton)
15,433
18,092
14,365
12,891
12,583
16,381
14,523
14,170
Production cost (KES/ton)
4,833
2,020
3,908
3,222
1,784
422
3,831
2,620
O & M cost (%)
1.2
1.6
1.5
1
3
0
2
3
Depreciation (%)
3
4
2
2
7
9
3
4
Price of compost
(KES/ton)
20,000
6,324
14,000
5,676
22,500
10,606
19,210
11,933
a 1 USD = 100.76 KES
Nutrient Recovery for Use in Agriculture …
29
mind present a great opportunity to mitigate the
prevailing waste management problems while
addressing soil nutrient depletion and environmental pollution (Sallwey et al. 2017).
The link between waste and water is also
equally important as wastewater can be used as a
source of water and plant nutrients (Hettiarachchi
et al. 2018; Weckenbrock and Alabaster 2015).
Recovering and reuse of waste as a source of
nutrient not only adds to the restoration of
ecosystem services but also reduces negative
externalities such as GHG emissions associated
with improper management of waste in developing countries (Kong et al. 2012).
4 Materials and Methods
4.1 Economic Assessment
The economic assessment is done based on
Return on Investment (ROI), Net Present Value
(NPV) and Benefit Cost Ratio (BCR) valuation
criteria. ROI measures per period; the rates of
return on money invested in the business and is
determined by dividing net profit by total
investment. The NPV is the total sum of the
present value of expected future cash flows.
Higher ROI and NPV values represent greater
economic benefits. The BCR is the ratio of the
total benefit of a project relative to its costs, both
benefits and costs expressed in discounted present values.
The economic analysis of the decentralized
compost business model is based on the data
collected in 2015 from 22 operating compost
plants located in different counties and cities of
Kenya. In this section, we first provide descriptive statistics of the surveyed plants, which will
be used as a basis for building the financial
model for the decentralized compost business
model.
4.1.1 Technical and Financial Data
of Compost Plants in Kenya
Table 2 shows data from the year 2014 on
selected parameters of surveyed compost plants
in Kenya. Data was collected pertaining to the
production capacity, capacity utilization, quantity
Table 2 Technical and economic data of compost plants in Kenya
Item
Capacity of the plant (tons of compost/year)
All
<100 tons
(n = 6)
100–500 tons
(n = 11)
>500 tons
(n = 3)
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Technical data
Land size (acres)
0.70
0.39
1.84
1.99
1.74
1.04
1.64
1.75
Capital utilization (%)
53
16
51
21
75
35
52
23
Quantity of waste
(ton/year)
139
68
466
154
1050
212
420
311
Input–output ratio (%)
0.55
0.24
0.51
0.16
0.50
0.25
0.53
0.19
Financial data
Investment cost
(KES
a /ton)
15,433
18,092
14,365
12,891
12,583
16,381
14,523
14,170
Production cost (KES/ton)
4,833
2,020
3,908
3,222
1,784
422
3,831
2,620
O & M cost (%)
1.2
1.6
1.5
1
3
0
2
3
Depreciation (%)
3
4
2
2
7
9
3
4
Price of compost
(KES/ton)
20,000
6,324
14,000
5,676
22,500
10,606
19,210
11,933
a 1 USD = 100.76 KES
Nutrient Recovery for Use in Agriculture …
29