A GIS-Based Transportation Model for Solid Waste Disposal: A Case Study on Asansol Municipality

A GIS based transportation model for solid waste disposal – A case study on Asansol municipality
M.K. Ghose a,*, A.K. Dikshit b, S.K. Sharma c a Regional Remote Sensing Service Center, ISRO, IIT Campus, Kharagpur 721 302, India b Centre of Environmental Science and Engineering, Indian Institute of Technology, Bombay, India c Department of Civil Engineering, Indian Institute of Technology, Kharagpur, India

Abstract

Uncontrolled growth of the urban population in developing countries in recent years has made solid waste management an important issue. Very often, a substantial amount of total expenditures is spent on the collection of solid waste by city authorities. Optimization of the routing system for collection and transport of solid waste thus constitutes an important component of an effective solid waste man- agement system. This paper describes an attempt to design and develop an appropriate storage, collection and disposal plan for the Asansol Municipality Corporation (AMC) of West Bengal State (India).
A GIS optimal routing model is proposed to determine the minimum cost/distance efficient collection paths for transporting the solid wastes to the landfill. The model uses information on population density, waste generation capacity, road network and the types of road, storage bins and collection vehicles, etc. The proposed model can be used as a decision support tool by municipal authorities for efficient management of the daily operations for transporting solid wastes, load balancing within vehicles, managing fuel consumption and gen- erating work schedules for the workers and vehicles.
The total cost of the proposed collection systems is estimated to be around 80 million rupees for the fixed cost of storage bins, col- lection vehicles and a sanitary landfill and around 8.4 million rupees for the annual operating cost of crews, vehicles and landfill main- tenance. A substantial amount (25 million rupees/yr) is currently being spent by AMC on waste collection alone without any proper storage/collection system and sanitary landfill. Over a projected period of 15 yr, the overall savings is thus very significant.

1. Introduction

Technological development, globalization and popula- tion growth have accelerated the dynamics of the urbaniza- tion process in developing countries. In India alone, the urban population has increased from 11% in 1901 to 26% in 2001. The rapid growth rates of many cities, combined with their huge population base, has left many Indian cities deficient in infrastructure services like water supply, sewer- age and solid waste management. Due to a lack of serious efforts by town/city authorities, the management of garbage has become a tenacious prob- lem, notwithstanding the fact that the largest part of any municipal expenditure is allotted to it. It is estimated that the urban local bodies spend about 500 rupees (1 US$ = 45 rupees approx.) per ton on solid waste collec- tion, transport and disposal, which may rise to 1500 rupees per ton in some instances. A substantial amount of the total expenditure (85%) is spent on collection and as such improvement in the design of the collection systems could result in substantial savings, thereby saving a large propor- tion of the funds.
However just collecting the waste from different parts of city does not solve the problem, it requires disposing the waste in environmentally safe and economically sustainable 1288

manner. An effective solid waste management system is needed to ensure better human health and safety.
In general, an effective solid waste management system should include one or more of the following options: waste collection and transportation; resource recovery through waste processing; waste transportation without recovery of resources, i.e., reduction of volume, toxicity, or other physical/chemical properties of waste to make it suitable for final disposal; and disposal on land, i.e., environmen- tally safe and sustainable disposal in landfills (Tchobanog- lous et al., 1993; Kreith, 1994; CPHEEO, 2000).
Most often, it appears difficult to minimize two variables
– cost and environmental impact – simultaneously. Hence, the balance that needs to be struck is to reduce the overall environmental impact of the waste management system as far as possible within an acceptable cost limit.
In this paper, an attempt has been made to propose an efficient solid waste management system for municipal solid waste, excluding industrial, constructional and hospi- tal waste. The framework of the proposed waste manage- ment plan is mainly based on the following considerations: Appropriate method of on-site storage. Appropriate method of bulk storage of waste. Appropriate method of primary collection of waste. Appropriate method of transportation of waste using
Geographical Information System (GIS). Appropriate method of waste disposal. Financial expenditure on whole solid waste management plan. Development of an optimal routing scheme for waste disposal involves determination of a number of selection criteria, which is a tedious job for a planner to do manu- ally. Various optimization models are discussed in the liter- ature. Pelms and Clark (1971) proposed a location model for optimal location allocation, while Male and Liebman (1978) used the districting and routing for solid waste col- lection. Clark and Gillean (1974) gave a system analytical approach, and Baetz (1990) adapted simulation modeling for optimal solid waste collection. In the present study, the principles of the Geographical Information System (Heywood et al., 1988) are mainly emphasized in planning an effective solid waste management system.

2. Description of the study area and the existing waste management system

The proposed solid waste management system is designed for the Asansol Municipality Corporation (AMC). Asansol (Longitude 87 E and Latitude 23 400 N) is an industrial town covering an area of 127.24 km2 situ- ated in the Barddhaman District of the state of West Ben- gal, India. The Asansol Municipality has 50 wards and
95,293 households, with an average number of occupants per house of 5. It is estimated that the city produces 180
MT of total solid waste daily, which includes 60 MT of Table 1
Solid waste data of Asansol City
Particulars of solid waste Value
Solid waste generation rate 0.250 kg/capita/day Total quantity of solid waste generated 180 MT/day Quantity of domestic solid waste 120 MT/day
Total number of community bins 1350
Total annual expenditure for SWM Rs 25 million
Total number of supervisory staff 20
Total number of sub-ordinate staff 487
Source: National Institute of Urban Affairs, Ministry of Urban Devel- opment, Govt. of India.

non-domestic waste such as industrial, construction and hospital waste – for which the owners of the respective organizations have responsibility for managing.
Asansol Municipal Corporation (AMC) is solely responsible for collection and disposal of 120 MT/day of domestic solid waste. Presently, the existing 1350 masonry dustbins at selected places are used for primary storage. The waste materials are transported using 200 hand carts,
23 trucks and 2 tractors for disposal in open space at the outskirts of the city. About 25 million rupees annually are expended for the entire solid waste disposal process, without any proper collection system or sanitary landfill.
The detailed supportive data on waste collection statistics of Asansol city is given in Table 1.

3. Proposed GIS based solid waste collection system

The proposed GIS model for solid waste disposal involves the planning of bins, vehicles and optimal routing. The generation of a spatial database on the road network, bin locations, landfill site and garage uses collateral infor- mation and updating the same using satellite data.

3.1. Storage of waste

Based on population density, width of roads, availabil- ity of space and minimum travel distance from a house, three types of bins viz. type-A (7.0 m3), type-B (0.75 m3), type-C (0.5 m3) have been proposed to be placed in differ- ent parts of the city. Some extra capacity is being provided for unforeseen factors such as slippage, overflow, etc., and the container utilization factor is assumed to be 50%.
All roads in AMC have been classified into three catego- ries: major roads (width: 5–7 m), minor roads (width: 2.5–
5 m) and other roads (width: less than 2.5 m). The road network, along with the ward boundaries and the adminis- trative boundary, of AMC is shown in Fig. 1.
It has been estimated that about 55 bins of type-A, 570 bins of type-B and 780 bins of type-C will need to be placed at different parts of the city along its major, minor and other roads. It is assumed that the frequency of collection for bin type-A is daily, but for bin type-B and bin type-C collection is every second day of the week as shown in
Table 2. The spatial distribution of storage bins over the road network of AMC is shown in Fig. 2. 1289

Fig. 1. Road network and ward/administrative boundaries of AMC. Fig. 2. Spatial distribution of storage bins over the road network of
AMC.

3.2. Collection of waste

Collection of solid waste is carried out by using suitable vehicles. The type of vehicle to be used depends on the type of collection bin and width of road (Chiplunkar et al.,
1981). Hence, three types of vehicles are used for the three types of bins. All of the mechanised vehicles are chosen to reduce the pick-up time of bins at different locations and thus to reduce the number of vehicle requirements. The three types of vehicles designed for managing the solid waste in AMC are as follows:

Vehicle Type-A: It is a skipper type of vehicle having a length of 4.5 m. It lifts only A-type bins and travels only on the major roads. It can carry only one bin at a time. Vehicle Type-B: It is a lifter type of vehicle with a front- loading mechanism and lifts B-type bins and travels both on major and minor roads.

Vehicle Type-C: It is an auto-rickshaw type of vehicle and is used for the collection of waste from the con- gested areas. It can collect wastes from C-type bins and unload it into the nearest A-type bin. The collection configurations of various vehicles planned for the pres- ent study is given in Table 3. The configurations of dif- ferent types of vehicles and those of the storage bins are shown in Figs. 3 and 4.

3.3. Collection methodology adopted

Only one landfill and one garage are assumed for the present study.
The sanitary landfill has been designed for an active life of 15 yr and post closure height of 20 m. Considering the provision for infrastructures viz. site fencing all around Table 2
Configuration of different types of bins

Bin type Volume (m3) Population served Sources of waste generation Total No. of bins Period of filling Frequency of clearance
A 7.00 >300 Market places, street vendors and C-type bins 55 1 day Every day
B
C 0.75
0.50 300
200 Multi-storied buildings, commercial complexes, community and other private societies
Slums and congested areas 570
780 2 days
2 days Every second day
Every second day
Container utilization factor = 50%. Extra capacity is being provided for unforeseen factors. 1290

Table 3
Collection configuration of vehicles

Vehicle type Volume (m3) Crew Bins collected in a trip Estimated waste collected in a trip
(at actual utilization of bins)
A – 2 1 –
B 20 (4 • 2.5 • 2) 2 50 50 • 0.75 • 0.5 = 19
C 7.5 (2 • 1.5 • 2.5) 2 28 28 • 0.5 • 0.5 = 7

Fig. 3. Configurations of different types of storage bins.

Fig. 4. Configurations of different types of collection vehicles.

the landfill, two weigh bridges of 50 ton capacity, an administration office of 30 m • 10 m, a site control office of 3 m • 2 m (potable office), access roads (all main roads are 7 m wide and all arterial roads are 3.5 m wide) all around the periphery, the total area needed for the landfill- ing operation has been estimated as 414.5 • 103 m2. For 1291

managing solid waste each day, a daily cell of size
30 m • 22 m with a lift of 2 m will be used. The naturally available soil cover of 20 cm thickness will be provided on each cell daily. The volume of soil needed as the cover for the cell will be 132 m3/day. After the end of each phase,
i.e., 1 yr, all surfaces will be covered with 40 cm thick nat- urally available soil. All of the essential components of a landfill, including the liner system, leachate collection sys- tem, gas collection system, final cover system, surface water drainage system, environmental monitoring system and closure and post closure plan have been designed and are discussed elsewhere (Sharma, 2002).
Normally, daily working hours for a crew is 8 h, includ- ing time of lunch and clearance at the landfill. Each vehicle consists of two crew members who are fully responsible for the collection and disposal of the wastes from the bins.
The speed limit is assumed to be the same for all vehicles of the same type. However, the GIS router model has the option to input the user defined speed limit for respective types of vehicles. Moreover, delays due to traffic jams, one-way roads, etc., can be input through link/arc-imped- ances of the proposed GIS-model.
The vehicle type-A starts from the garage; travels to the location of the type-A bin; transports the bin to the landfill and then returns back to previous place to replace the bin.
Then the vehicle moves to the next nearest type-A bin and repeats the same process. At the end of the day, the vehicle will return to the garage after replacing the last bin served, at its original location.
The vehicle type-B starts from the garage, collects the waste from 50 B-type containers and moves to the landfill.
The vehicle will then come to the next B type bin location and repeat the process. At the end of the day, the vehicle will return to the garage from the landfill.
The vehicle type-C starts from the garage, collects the waste from 28 C-type bins and disposes the waste at its nearest A-type bin. The vehicle will then come to the next
C-type bin location and repeat the process. At the end of the day, the vehicle will return to the garage from the loca- tion of the last A-type bin served.

3.4. Optimal GIS routing model for collection and disposal of solid waste

Collection routes are worked out by using GIS (Hey- wood et al., 1988). The NETWORK module (ESRI,
1995) of Arc/Info GIS software is used with the planned infrastructure to find the shortest or minimum impedance path through a network. The speed of the vehicle is taken as the arc impedance and no turn impedance is being used.
For the present study, the speed limit for all the vehicles are assumed to be the same; however, the user defined speed limit for respective types of vehicles can be fed into the model as the values of arc impedances. Moreover, delays due to traffic-jams and signals, one-way roads, etc,. can be input through link/arc-impedances of the proposed model. The time spent at the landfill and at the bins for clearance of the wastes is taken as the node/stop-imped- ance and it can vary from bin to bin. The time taken to tra- vel each line segment is calculated by the speed of the vehicle and the road type. Three types of ARC/INFO NETWORK modules named as GIS-router modules have been developed using AML (Arc Macro Language) depending upon the type of collection methodology to facilitate the modeling of spatial networks. The shortest path computed by using a heuristic procedure viz. the trav- eling salesman problem (Sharma, 1974) is saved as a route in a route-system and displayed using the route display commands in ARCPLOT. The NETWORK commands PATH and TOUR are used for finding minimum paths.

3.5. Optimal routing of transport system

A-type vehicle: The major roads and the A-type bins are selected from the spatial data. The order in which the bins have to be visited is calculated based upon the proximity of bins. This initial planning can also be edited later. Then the optimal path is generated for each vehicle. In this process, clusters of bins are formed and each cluster is allocated to a vehicle. The clusters are made by taking the time into account, which may be plus or minus the total working hours for the day. The last cluster may need less time if the number of bins to be cleared is less. In such cases, the last cluster may be merged with other clusters by increasing the total working hours.
B-type vehicle: The ordering of the B-type bins is per- formed as done for the A-type vehicle. Based upon the ordering, clusters of 50 bins are formed, which is the max- imum capacity that a B-type vehicle can clear at a time. The total time required to clear each cluster through the optimal path is calculated and displayed to the user. Now the user can select a subset of clusters to be cleared by a vehicle. Once the user enters the group of clusters to be cleared, a final optimal path between these clusters is gen- erated. The total time required and other results are calculated.
C-type vehicle: Here all of the A-type bins that are hav- ing links to C-type bins are selected. The visiting order of A-type bins is calculated. Then the optimal path is calcu- lated for each C-type cluster attached with A-type bins. Based upon the total working hours, the number of vehi- cles required to clear the C-type bins is then calculated.

4. Results and discussion

4.1. Clearance of A-type bins

The user is provided with the various optimum paths that an A-type vehicle has to take for clearing A-type bins in a given time. Each vehicle is provided with the cluster of bins and the order in which it has to be cleared. The num- ber of trips required, time and total number of km each vehicle has to run is also calculated. Based on the number of vehicles available, the user can generate a schedule for

1292 vehicles and wages for workers. For example, a sample out- Table 5 put of the optimal path for one A-type vehicle is shown in
Fig. 5. The travel time, distance covered, and number of Travel time, distance covered and number of bins cleared by type-B vehicle bins cleared by A-type vehicle are shown in Table 4. Day of clearance Vehicle No. Travel time (h) Distance traveled (km) No. of B-type bins cleared

4.2. Clearance of B-type bins

As one B-type vehicle can clear a group of B-type bins at a stretch, the user is initially given the estimated time for clearing the clusters of B-type bins. From the set of clus- ters, the user can schedule a vehicle for a day. Once the input is given by the user, all of the results as obtained for B-type bin are generated. The travel time, distance cov- ered and number of bins cleared by the B-type vehicle is shown in Table 5.

Fig. 5. A sample output of the optimal path for one A-type vehicle. Table 4
Travel time, distance covered and number of bins cleared by type-A vehicles Day 1 1 9 (8.76) 98 (98.13) 200
2 9 (9.17) 94 (93.48) 200
3 7 (7.31) 74 (73.65) 170
Day 2 1 8 (8.41) 91 (91.40) 200
2 7 (7.37) 77 (77.20) 170
3 8 (7.90) 95 (95.27) 200
Day 3 1 8 (7.61) 76 (75.80) 170
2 9 (8.77) 97 (97.34) 200
3 9 (8.75) 98 (97.45) 200
Total 3 74 800 –

4.3. Clearance of C-type bins

Here the waste from C-type bins is cleared by a C-type vehicle and disposed in the designated A-type bin. The same set of results as in the case of A-type bin is generated. The travel time, distance covered and number of bins cleared by a C-type vehicle is shown in Table 6.
The total number of different types of vehicles, distance traveled and total working hours as calculated in the GIS
Table 6
Travel time, distance covered and number of bins cleared by type-C vehicles Vehicle No. Time of travel (h) Distance traveled (km) Number of bin type-A cleared in a day

Table 7
Details of collection and transportation system 1 7 (7.20) 116 (116.26) 8
2 7 (6.91) 95 (94.45) 9 Types of Number of Total distance Total working 3 7 (6.58) 97 (97.40) 8 vehicles vehicles required traveled (km/week) hours (h/week) 1293

1,950,000 In this paper an attempt has been made to design and

Total 80,005,000 Approx. 80 million

Table 9
Estimated annual operating cost for the proposed solid waste management plan of AMC such as population density, waste generation capacity, road network and the types of road, storage bins and collection vehicles, etc., is developed and used to trace the minimum cost/distance efficient collection paths for transporting the solid wastes to the landfill. The proposed model can be used as a decision support tool by the municipal authorities S.No. Item Unit cost Total cost for efficient management of the daily operations for mov- in rupees in rupees ing solid wastes, load balancing within vehicles, managing 1 Vehicles running cost including the maintenance 20/km 5,591,040
(5376 • 52 • 20) fuel consumption and generating work schedules for the workers and vehicles. 2 Labor cost in collection 5000/crew 1,800,000
(15 • 2 • 5000 • 12)
3 Landfill running cost – 1,000,000
Total 8,391,040 Approx. 8.4 million

environment for the whole solid waste management system is given in Table 7.

5. Financial expenditure

Being a ‘‘public utility’’ and an essential service, invest- ment in solid waste management does not require a justifi- cation in terms of ‘‘positive return on investment’’ or
‘‘minimum profits’’. Such an investment, however, needs to be justified on the basis of being ‘‘the least cost techno- logically feasible option’’ for achieving the required degree of efficiency.
Disposal cost can be defined as total cost incurred by
AMC in disposing of the municipal solid waste and, accordingly, the estimated fixed and operating cost for solid waste management are obtained as shown in Tables
8 and 9, respectively.
The total cost for the newly designed collection systems is estimated to be around 80 million rupees for the fixed cost of storage bins, collection vehicles and a sanitary land- fill and around 8.4 million rupees for the annual operating cost of crews, vehicles and landfill maintenance. Presently, References

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References: Baetz, Brian W., 1990. Optimization/simulation modeling for waste management capacity planning. Journal of Urban Planning and Development 88, 59–79. Chiplunkar, A.V., Mehndiratta, S.L., Khanna, P., 1981. Optimization of refuse collection systems Division, ASCE 107 (EE6), 1203–1211. Clark, Robert M., Gillean, James I., 1974. System analysis and solid waste planning CPHEEO (Central Public Health and Environmental Engineering Orga- nization), 2000 ESRI, 1995. Network Analysis-Modeling Network Systems. Environmen- tal Systems Research Institute Inc., Redlands, CA, USA. Heywood, I., Cornelius, S., Carver, S., 1988. An Introduction to Geographical Information Systems Kreith, F., 1994. Handbook of Solid Waste Management. McGraw Hill, New York, USA. Male, J.W., Liebman, J.C., 1978. Districting and routing for solid waste collection Pelms, Billy P., Clark, Robert M., 1971. Location model for solid waste management Sharma, S.D., 1974. Operations Research. Kedar Nath Ram Nath & Co., Meerut. Sharma, S., 2002. Developing an integrated solid waste management plan for Asansol city, M.Tech Tchobanoglous, G., Theisen, H., Vigil, S.A., 1993. Integrated Solid Waste Management: Engineering Principles and Management Issues.