Optimal Route Analysis For Solid Waste Disposal Using Geographical Information SsystemA.P.Poun Lakshumi A.M.Ramiya R.Ssthya Abstract The growth in the urban population and activity has resulted in an increased solid waste generation. Uncontrolled urbanization in Chennai, the fourth largest metropolitan city,has placed a heavy stress in the management of solid waste. In the process of solid waste management, more attention needs to be paid towards collection as it itself requires 60-70% of the total cost. Transportation plays a vital role in waste collection and disposal. Hence an attempt is made in this study to generate an optimum route for solid waste collection and hence to reduce the distance run by the vehicle, using Geographical Information System.For effective management, the corporation of Chennai has divided the entire region into ten zones, out of which three zones have been privatized under CES ONYX Pvt Ltd. Our study area falls under zone X sector 7 which covers Gandhi nagar, Shastri nagar, and Indira nagar.Optimal routes for compactor run,to collect the solid waste,have been generated based on two criteria namely distance and time. A comparison is made between the cost of the fuel consumed for the routes generated and the fuel cost for the existing route. SOLID WASTE MANAGEMENT Solid waste management is the discipline associated with control of waste generation, an organization of storage, collection, transfer and disposal practices. Most urban areas in the country are plagued by acute problems related to solid waste management. It is estimated that about 1, 00,000 MT of solid waste is generated everyday in the country. Per capita waste generation in major cities ranges from 0.2 kg to 0.6 kg. The collection efficiency ranges from 50 to 90% only, leaving the balance unattended. It is estimated that the urban local bodies spend about Rs. 500 to Rs. 1500 per ton on solid waste for collection, transportation, treatment and disposal. About 60 – 70% of this amount is spent on collection, 20 to 30% on transportation and less than 5% on final disposal of waste. Therefore waste collection must be regarded as an important issue in order to increase the efficiency of waste management. NEED FOR THE STUDY Lack of plan in the management of solid waste can lead to epidemic of plague, malaria and hence increased death tolls. The problem of solid waste can cause serious and long term pollution of land, air and water. Improvement in solid waste management will lead to minimization of environmental impact. The problems encountered during collection are:
Very few urban local bodies in the country have prepared long term plans for effective solid waste management in their respective cities. For obtaining a long term economic solution, planning of the system on long term sustainable basis is very essential. In this regard, the local body of Chennai has done a good job. Chennai characteristics Chennai is the fourth largest metropolitan city in India. The Chennai metropolitan area covers an extent of 1172 sq km of which the corporation extends over 172 sq km.CMA has a population of 7.05 million, out of which 4.34 million is within the city. There are 28 town panchayats, 8 municipalities and 1 cantonment area within the metropolitan area. There are 10614 streets in the city with the total length of 2188kms. The city has been divided into 10 administrative zones, 30 units and 155 wards. In Chennai, on an average 830 g/day of garbage is being generated by an individual. The total waste generated is about 3700 tons/day. It is the highest followed by Delhi, Kolkata and Mumbai.For effective management of this accumulated waste, the Corporation of Chennai has divided the city into ten zones, which is further divided into 30 units having 155 divisions. The waste is collected by street sweeping and kerbside collection and it is at present being disposed in the outskirts i.e., Perungudi (in the south) and kodungaiyur (in the north). The volumetric capacities of the two sites are 12 million and 1.2 million cubic meters respectively. As a part of our “Singara Chennai” project by our former mayor Mr.M.K.Stalin, the corporation of Chennai has privatized the collection in three zones. It has handed the work to CES ONYX, a French based company which is carrying out the work appreciably. As already specified, the collection of solid waste in terms of economic aspect needs to be taken into account. So the optimization of the collection route is vital. OBJECTIVES The following are the primary objectives of the study
STUDY AREA Of the ten zones in Chennai, our study area comes under zone 10 which comprises Adyar, Velachery and Thiruvanmaiyur. Onyx has divided this zone into 10 sectors for better management. We have restricted our study to sector 7 which includes Gandhi nagar, Shastri nagar and Indira nagar. The major land use in this area is residential. The area has a diverse range of slums, commercial establishments, schools. The area is bounded by Buckingham canal bank road in the west, Karpagam garden in the east, Indira nagar main road in the south and Gandhi nagar main road in the north.  FIGURE 1: STUDY AREA EXISTING SCENARIO Chennai is going hi-tech. Not just in its Tidel Park or its Cyber Corridor, but also in the way it manages its garbage. With the new CES-ONYX privatized conservancy operations, the city is on its way to becoming cleaner. The company removes a minimum of 1,000 tons of garbage every day from its allotted zones within the city. This French multi national company has been given the waste removal contract for a period of seven years. The company is paid, based on the amount of waste transported to the two dumping grounds (Perungudi and Kodungaiyur). Overall the company employs over 2,038 employees for its operations. It also has a mobile fleet of nearly 1,052 vehicles, which include compactor trucks, hook lift trucks, autorickshaws, palm fingers, modified bicycles, loose litter collectors, sanitation vehicles and bob carts. The clean-up activities include collection, storing, transporting and disposal. After the garbage is removed from the streets, it is moved into a temporary place, the transfer station. The temporarily stored garbage is shifted to the landfill sites (Kodungaiyur and Perungudi) using huge hippo trucks. Our study area which falls under sector 7, zone X comprising of Indiranagar, Shastrinagar and Gandhinagar consists of 113 roads. There are 185 bins located in our study area. Out of these, 163 are plastic bins of 660 litres capacity, and the rest are the metal bins of 1100 litres capacity. To clear these bins, compactors and autorickshaws are being used. We have restricted our study to compactors only. A single compactor is used to clear the garbage twice during the day time and once during the night time  FIGURE 2: Loading by the compactor The compactor starts it’s dayshift run at 6:30 a.m and finishes at 2:30 p.m. In some areas such as Nehru Nagar, Padmanaban nagar and Kasturbai nagar, the waste gets accumulated easily during the daytime soon after the first trip gets over and hence, is collected the second time. The total distance covered in both these trips is 50 kms. The nightshift run starts at 8:30 p.m and finishes at 4:30 a.m covering a total distance of 32 kms. The compactor clears 113 bins in the dayshift and 97 bins in the nightshift. The compactor uses diesel as fuel and gives a mileage of 1.4 km/litre. The vehicle can hold about 120 bins of solid waste, if the bins are getting filled about 50 – 75% of their total capacity. On an average 2 to 3 minutes are taken for transferring the waste from the storage bin to the vehicle. The collected solid waste is moved to the transfer station at Mandaveli from where it is taken to Perungudi for disposal. DATA COLLECTION For generating the optimal routes for the solid waste collection, the following data were obtained from Chennai Metropolitan Development Authority, CES Onyx Pvt Ltd., and Traffic Commissioner of Police.
Detailed Development Plan of Gandhi nagar, Indira nagar, Shastri nagar of scale 1:5000 GIS is an institutional entity, reflecting an organizational structure that integrates technology with a database, expertise and continuing financial support over time. It is a powerful tool for collecting , storing, retrieving at will, transforming , analyzing, and displaying spatial data from the real world for a particular set of purposes. This technique is used to generate optimal route for collecting solid waste. DIGITISATION The separate detailed development plans of Gandhi nagar, Shastri nagar and Indira nagar at a scale of 1:5000 were scanned. The scanned images are then digitized using Arc View GIS 3.2a. Arc View GIS 3.2a Arc View GIS 3.2a is a powerful, easy-to-use tool that brings geographic information to your desktop Arc View GIS 3.2a gives you the power to visualize, explore, query and analyze data spatially. Arc View GIS 3.2a is made by Environmental Systems Research Institute (ESRI), the makers of ARC/INFO, the leading geographic information system (GIS) software. It helps to solve spatial problems. Using Arc View GIS 3.2a, the raster image displayed on the computer screen is converted into vector graphics. This process is known as heads up digitizing. The digitized files will be in the .shp format. EDITING AND BUIDING TOPOLOGY The spatial relationships among the topographic features can be established using PC Arc Info 3.5.2. PC Arc Info 3.5.2 PC Arc Info 3.5.2 is a fully integrated system. It is basically a vector based overlay geographical information system, developed by ESRI. It is a very powerful tool for handling a greater volume of data for automated mapping. The shape files obtained from digitizing using Arc View GIS 3.2a are converted into coverages using PC Arc Info 3.5.2.A topology is built. It is then edited using Arc Edit. The coverages are then projected into polyconic system using the control points obtained from the toposheets. The projected coverages are then transformed to shape files. MAP JOIN Using the GEOPROCESSING WIZARD, an extension of Arc View GIS 3.2a, the maps are merged together. Geoprocessing Wizard The GeoProcessing Wizard offers six geoprocessing options to create or augment feature themes comprising of dissolve, merge, clip, intersect, union, assign data by location. Merge process will create one theme that contains the features of two or more themes. The new theme will contain the fields of one of the input themes. The option ‘Merge themes together’ was used to join the three individual shape files together. ADDING ATTRIBUTES Non spatial data such as road name, speed limit, number of bins and travel time in each road are added.
 FIGURE 3: FLOWCHART SHOWING THE STEPS INVOLVED IN ANALYSIS ROUTE GENERATION After all the data were given as input, the optimum route was generated using Network Analyst, an extension of Arc View GIS 3.2a. Network analyst The Arc View Network Analyst is an extension product designed to use networks more efficiently. It can solve common network problems on any theme containing lines that connect. Network Analyst can
It is generated based on two criteria
The route was generated taking the location of bins only into consideration. The volume of traffic in the roads was not considered in this case. Three routes were generated, one taking into consideration, the bins which are cleared up during the daytime, the second considering the bins cleared up again during the day time and the final one considering the bins cleared up during the night time. TIME CRITERIA
 Source: Saaty (1980) Ranks were assigned to all the above mentioned parameters of each road based on their priority. CSI was then calculated twice using the individual weights obtained by the following assumptions as per the Saaty table. In the first case, length was assumed to be moderately preferred to width, traffic volume was equally to moderately preferred to length, and width was equally to moderately preferred over volume. In the second case, width was strongly preferred to length, traffic volume was moderately preferred to length and width was moderately to strongly preferred to volume. CSI was calculated as follows:  Two routes were generated for the dayshift and nightshift based on the CSI values using Network Analyst. RESULTS AND ANALYSIS OPTIMAL ROUTING FOR DAY SHIFT Based on the distance criteria, the total distance traveled by the compactor vehicle is 29.234 km out of which 19.408 km is covered during the first trip, the rest being covered during the second trip. This is 20.766 km less than the existing run route of the compactor. Hence a total of Rs.611.82 is saved per day. Based on the time taken by the compactor to cross a particular segment of the road, routes were generated. It was found that it takes 6 hrs 56 mins 39.6 secs to clear the bins out of which the first trip takes 5 hrs 7 mins 34.2 secs and the second trip takes 1 hr 49 mins 5.4 secs. Hence the clearing time gets reduced by 1 hr 3 mins 20.4 secs which in turns saves an amount of Rs.344.67 per day. Based on the relative criterion weightages established between length, width and volume, routes were generated. The clearing up process takes a total of 6 hrs 52 mins 16.2 secs out of which the first trip takes 4 hrs 35 mins 46.2 secs and the next trip takes 2 hrs 16 mins 30 secs. By this a total of Rs.368.55 per day is saved. OPTIMAL ROUTING FOR NIGHT SHIFT Based on the distance criteria, the total distance traveled by the compactor vehicle is 17.8918 km. This is 14.1082 km less than the existing run route of the compactor. Hence a total of Rs.295.294 is saved per day. Based on the time taken by the compactor to cross a particular segment of the road, routes were generated. It was found that it takes 4 hrs 28 mins 4.2 secs to clear the bins. Hence the clearing time gets reduced by 3 hr 31 mins 55.8 secs which in turns saves an amount of Rs.1146.94 per day. Based on the relative criterion weightages established between length, width and volume, routes were generated. The clearing up process takes a total of 4hrs 24 mins 58.2 secs. By this a total of Rs.1170.07 per day is saved. DISTANCE CRITERIA Table 2: DAY SHIFT   TIME CRITERIA Table 4: DAY SHIFT   RELATIVE CRITERION WEIGHTAGE METHOD WEIGHTAGE 1 Table 6: DAY SHIFT   WEIGHTAGE 2 Table 8: DAY SHIFT   CONCLUSIONS AND DISCUSSIONS In the present study an attempt has been made to optimize the solid waste route for compactor vehicle in zone X sector VII comprising of Gandhi nagar, Shastri nagar, Indira nagar using Arc view Network Analyst. With the GIS technique, optimum route was identified which found to be cost effective and less time consuming when compared with the existing run route. SCOPE OF FUTURE STUDY Optimum route can also be generated for the auto rickshaws. Similar studies can be extended to other zones of Chennai. If a database can be created with all the attributes and if it can be updated periodically, then an effective management of solid waste with the help of GIS tool, in this rapidly growing urban scenario can be achieved. |