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Decentraized solid waste management
1. - Presented by
- Nisarg Shah (13BME 100)
- Harshil Solanki (13BME 108)
- Pradip Bariya (13BME 010)
- Guide : Dr. Anurag Mudgal
Feasibility of Decentralized
Solid Waste Management
System.
Study and Prototype
Development
2. Objective
To understand
and study Solid
Waste
Management
Models that are
currently in use.
Develop and
study the
feasibility of the
decentralised
SWM Model.
Selecting
equipment and
designing of
Vibrating
Screen.
Find the
parameters for
the most
efficient system
3. Methodology
Literature Study.
Visit to Centre of Environmental
Education (Government Organisation
Visit to NEPRA (Solid waste
Segregation Plant).
Feasibility Study
Design development
5. Functional Elements of Waste Management
To implement proper waste management, various aspects
have to be considered such as
– source reduction
– onsite storage
– collection and transfer
– processing techniques
– disposal
7. Decentralised SWM
Segregation Processes
• 2D and 3D objects are manually fed into a Vibratoscope which is a device that segregates
dimensional and dimensional objects.
• The design of the device is similar to a piston crank mechanism of an engine. Here the lateral
motion of the piston movement is converted into a rotary motion through fulcrum.
8. • The 3D objects are pulled over by the movement of the blocks.
• The 2D objects are flown away by the upward movement of the blocks.
9. Vibrating Screen
• The vibrating screen is used to separate the
sand particles and smaller particulate to
bottom of the screen and rest matter is carried
forward to the conveyer belt for manual
segregation.
10. Manual Segregation
• The Manual segregation process consists
of an oval shaped conveyor system
where workers are arranged on the
periphery.
• These workers are divided into a group
of three in a line and are given a specific
matter to pick from the conveyor belt
and collect it in a bag or the fill it in the
blue box that form a ballet of a particular
item.
11. Hydraulic Press
• The press shown here is a two
container Hydraulic Press.
• When one container is pressed the
other is filled up manually by the
workers hence increasing efficiency
and saving time.
12.
13. Feasibility of DSWM
Waste
percentage of
waste output price per unit total revenue
percentage of
revenue
green waste(fertilizer) 38.6 0.75 3 86.85 22.93947518
green waste(biogas) 38.6 0.25 9.5 91.675 24.21389047
paper 5.6 1 7 39.2 10.35379881
plastic 6 1 8 48 12.678121
RDF(refuse derived fuel) 6.6 1 1.5 9.9 2.614862456
metals 0.2 1 15 3 0.792382562
C&D (construction and demolition) 25 1 0.3 7.5 1.980956406
non recyclable materials 13 1 0 0 0
Fish market/Caracas + Hotel Restaurant
and Kitchen Waste 5 0.6 25 75 19.80956406
fish market/Caracas 1 0.4 9.5 3.8 1.003684579
hotel restaurant and Kitchen waste 4 0.36 9.5 13.68 3.613264484
Total 100 378.605 100
18. • Break-even point
Considering capital investment break-even including compound interest @ 10%
E = A . r(1+r)n / ((1+r)n - 1)
Where,
A = Amount borrowed
E = EMI or Monthly payment
r = interest rate in % divided by 12
n = total number of months
Break-even point =57 months
19. 2. For medium scale SWM plant
• Factors taken into consideration
municipal solid waste generation per month
cost of collection
cost of transportation
cost of disposal
• Cost of collection
waste generated per day
waste that can be collected by each worker per day
salary of each worker per day
collection cost per day
number of bins used for collection
cost of each bin
total cost of bins
20. • Cost of transportation
length of travel per truck per year
cost of travel per truck per tonne in a month
number of trucks required
travel cost per tonne
total cost of transport
• Cost of disposal
cost of maintenance of disposal sites
21.
22.
23.
24.
25. 3. Break-even point
• Considering capital investment break-even including compound interest @ 10%
E = A . r(1+r)n / ((1+r)n - 1)
Where,
A = Amount borrowed
E = EMI or Monthly payment
r = interest rate in % divided by 12
n = total number of months
Break-even point =23 months
(This does not include the value of land saved by not dumping the waste.)
26. Result and Conclusion
• Thus the distance travelled is kept such that the door to door pickup truck can gather
the waste and deliver it to the waste processing and segregation plant.
• Amount of waste collected by one door to door pickup truck -2 tonnes=5000 people
considering a population density of 5000 people/Km2 this truck is expected to cover an
area of 0.5 Km2 covering a total distance of 5-6 Km in the process
• A solid waste management system for 30000 people is the most efficient because it has
a better breakeven period than domestic waste management system due to material
recovery
• While considering the population density for more than 30000 people if the plant is
made, the cost of collection and disposal is the same per tonne while the cost of
transportation increases as the waste has to collected at a dumping site by the door to
door collectors .this waste has to be transported to a processing plant by a different
truck and hence the cost adds up.
36. Cost analysis for Large Scale Plants
Assumptions taken for calculations
• The waste collected in all cities is similar to the waste breakup found in Ahmedabad.
• The land value is not taken into consideration as it depends on the city as well as it
varies from area to area. The land required by segregation plants is assumed to be
the same as the saving in land required by landfill sites.
• The value of 3.8 Rs. Per Kg is derived for the case of Ahmedabad based on current
price trends of obtained components
• Each collector truck goes for one trip a day and has a capacity of 2 Tonnes
• Each Dumper truck has a carrying capacity of 12 Tonnes and goes for 3 trips a day
• The cost of collector vehicle is 600000 Rs.
• The cost of Dumper truck is 2000000 Rs.
• Maintenance and depreciation is kept at 2% per month or 24% per year in line with
industry standards
37. • Compound interest is taken into consideration for payback period
• Total capital costs for segregation plants is taken from sources and interpolated
linearly
• The salaries of workers and the number of workers required are taken from the AMC
models and NEPRA plants.
• The cost of segregation plant varies linearly with its size for a plant of sufficient size.
• The waste segregation takes place at the source where green waste, recyclable
materials and non recyclable materials go in different bins
• Operating cost of collector vehicles is kept at Rs. 8 per Km
• Operating costs of Dumper vehicles is kept at Rs. 30 per Km
• The collector vehicles are assumed to travel every road of the city and the total
distance travelled by them is equal to the total road length of the city
42. Conclusion
• The feasibility analysis of DSWM as used in our matlab analysis fall in line with the current budget
of AMC. It is observed that after a landfill ratio of more than 50% to the total waste, the business is
unprofitable.
• It is also seen that as the number of waste segregation centers increase, the profitability increases
as expected. This is because of the fact that collector trucks have to travel shorter distance saving
on fuel cost.
• It is seen that almost 60-70% of the revenue comes from green waste conversion into biogas and
fertilizer while 30-40% revenue comes from segregation of waste.
43. Bibliography
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with the garbage crisis. Presented for: Scientific Committee on Problems of the Environment
(SCOPE) Urban Solid Waste Management Review Session, Durban, South Africa, 1-13.
Zia, H., & Devadas, V. (2008). Urban solid waste management in Kanpur: Opportunities and
perspectives. Habitat International, 32(1), 58-73.
Talyan, V., Dahiya, R. P., & Sreekrishnan, T. R. (2008). State of municipal solid waste
management in Delhi, the capital of India. Waste Management, 28(7), 1276-1287.
Yedla, S., & Kansal, S. (2003). Economic insight into municipal solid waste management in
Mumbai: a critical analysis. International Journal of Environment and Pollution, 19(5), 516-527.
Srivastava, P. K., Kulshreshtha, K., Mohanty, C. S., Pushpangadan, P., & Singh, A. (2005).
Stakeholder-based SWOT analysis for successful municipal solid waste management in Lucknow,
India. Waste management, 25(5), 531-537.
44. Rathi, S. (2007). Optimization model for integrated municipal solid waste management in Mumbai,
India. Environment and development economics, 12(01), 105-121.
Subramani, T., Umarani, R., & Devi, S. B. (2014). Sustainable Decentralized Model For Solid
Waste Management In Urban India. International Journal of engineering Research and
Applications, 1(4), 264-269.
Hokkanen, J., & Salminen, P. (1997). Choosing a solid waste management system using
multicriteria decision analysis. European journal of operational research, 98(1), 19-36.
Arena, U., Mastellone, M. L., & Perugini, F. (2003). The environmental performance of alternative
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