Literature Review of Using Gis to Solve Recycling Problems

Expenditure for waste collection and transport in Tunisia constitutes 75–100% of the total solid waste material direction budget. In this study, optimized scenarios were developed using ArcGIS Network Analyst tool in order to ameliorate the efficiency of waste collection and transportation in the district Cité El Habib of Sfax city, Tunisia. Geographic Information System (GIS) was created based on information collection and GPS tracking (collection route/bins position). The actual country (Scenario S0) was evaluated, and past modifying its particular parameters, other scenarios were generated and analyzed to identify optimal routes: S1, road optimized with the same working resource (alter of stops sequencing simply); S2, route optimized with change of vehicles; and S3, road optimized with change of collection method (vehicles and reallocation of bins). The results showed that the three scenarios guarantee savings compared to S0 in terms of collection time (fourteen%, 57%, and 57% for S1, S2, and S3, resp.) and distance (xiii.5%, 13.5%, and 40.v% for S1, S2, and S3, resp.). Thus, a direct affect on fuel consumption can be expected with savings of xvi%, xx%, and 48% for S1, S2, and S3, respectively, without mentioning the additional benefits related to CO_two emissions, hours of work, vehicles wear/maintenance, and so forth.

1. Introduction

Technological evolution, globalization, and population growth have accelerated the dynamics of urbanization processes in developing countries, which contributed to the generation of increasingly big quantities of solid waste (SW) in more or less full-bodied areas. Therefore, issues related to solid waste direction (SWM) remain at the forefront of the global environmental policy for sustainable development. Indeed, an effective SWM system is necessary to ensure better wellness and man security.

The procedure of SWM is very complex as it involves many technologies and disciplines associated with the control of generation, handling, storage, collection, transfer, transportation, processing, and disposal of SW [1]. SWM practices vary with the economical/social weather condition and with the regulatory framework.

The drove/ship component is the showcase for any SWM system whose implications are straightforward to evaluate the success of the system and its costs. The performance involves the removal and transfer of waste from product or assembly points to transfer station or from transfer station to processing or to last landfill site. It is therefore the well-nigh influential and most plush component as information technology absorbs the biggest fraction of the budget allocated by municipalities for SWM in detriment of other operations in the waste product management system [ii, 3]. The challenge is therefore to attain optimal waste collection and ship operation (hauling, equipment, manipulation, etc.). However, the evolution of an optimal collection/transportation system for SW involves the determination of a number of pick criteria, which is a very complicated task for a planner to do manually. The use of Geographic Data System (GIS) is recognized as 1 of the most promising approaches to analyze complex spatial phenomena. GIS has been successfully employed for a wide range of applications, such as geology, protection and direction of natural resources, risk management, urban planning, transportation, and various modeling aspects of the environment [4, 5].

Present, integrated GIS technology provides an advanced modeling framework for conclusion makers to analyze and simulate various problems related to SWM. Indeed, the GIS tool has been used to model diverse applications in waste direction such as siting of transfer stations and landfill, optimizing the collection and transportation, and local forecasting of waste [7–9].

The use of spatial modeling tools and GIS for drove and transportation optimization tin can provide economic and environmental gains by reducing travel fourth dimension, distance, fuel consumption, and pollutant emissions [10].

Several models for the drove and ship of SW accept been developed based on appropriate software for route optimization. A 3D GIS modeling was used by Tavares et al. [eleven] in Cape Verde and helped to attain up to eight–12% of fuel savings even past traveling a longer distance compared to the shortest path. An awarding on MapInfo software with the use of "test and adjustment" method for optimizing the road in the city of Tin can Tho, Vietnam, showed that altitude and travel fourth dimension tin exist reduced by 19% and 12%, respectively, and could save 20% of fuel consumption [12]. Furthermore, the traveled altitude has been reduced by 12 to 20% and the working time past viii% using the software RouteSmart^TM for the case of Northamptonshire, Uk [thirteen]. A x% reduction in the number of SW collection trips was achieved by Sahoo et al. [fourteen] using the WasteRoute software in the surface area of Elgin, Illinois, Usa. Using the software TransCAD®, Moustafa et al. [fifteen] developed the best solutions to the problem of collection/ship of SW in Alexandria, Egypt. Apaydin and Gonullu [16] used RouteViewPro™ for the city of Trabzon, Turkey, showing that 24.vii% benefits in the total expenses could exist granted. On the other mitt, the ArcGIS Network Analyst application was used by several authors to optimize the collection and transportation of waste matter: Ghose et al. [17] who adult a GIS model for calculating optimal route in the state of W Bengal, India, and accept shown that its awarding would allow colossal savings over a period of 15 years; Chalkias and Lasaridi [10] proposed various scenarios developed upon field real state of affairs in the municipality of Nikea, Greece, assuasive reductions of up to 17% for working time and 12.five% for the distance traveled.

In Tunisia, collection and transportation expenses currently corporeality for up to 75% of SWM total costs, most of which are spent on salaries and fuel. However, the results on the field are in almost cases unsatisfactory and are the object of multiple complaints from citizens. Indeed, the choices are ofttimes taken empirically and irrationally under the effects of communal pressure and/or personal interests of decision makers. Thus, in the present work, an optimization was developed using the ArcGIS Network Analyst tool in order to improve the efficiency of the collection and transportation of waste in Cité El Habib district of Sfax metropolis, Tunisia, by ways of waste bins reallocation and optimization of vehicle routing in terms of traveled distance and operating time while taking into consideration all the required settings parameters, that is, population density, waste generation charge per unit, bins locations, road network and traffic/circulation, drove vehicles chapters, and and then forth.

2. Background of SWM in Sfax City

The example study in this work relates to a commune in the Sfax city, which is the economic heart and the 2nd largest metropolis of Tunisia. It has a very disperse agglomeration with 300,000 inhabitants resulting in a density of 48 persons per hectare. The boondocks of Sfax is divided into 7 districts: El Medina, El Boustane, Sidi Mansour, Sfax Nord, Errbadh, Merkez Chaker, and Cité El Habib (Figure 1). Each of these districts involves one or more than municipal communities.

The amount of municipal SW collected by the municipality of Sfax was 74501 t in 2010, but it decreased to 53455 t in 2013 due to the social and political events in the country during the concluding v years. Based on 2010 data, the corresponding average of collected waste is 0.68 kg/capita/day (projected average being 0.71 kg/capita/day). It should exist pointed out that the municipal SW is characterized by a loftier level of organic matter (68%) and thus a high rate of water content ranging betwixt 65% and 70%. Besides individual citizens, potential producers of waste material are schools, kinder gardens (227); hospitals, clinics, drugstores, and fuel stations (118); touristic areas (iv); cafes, restaurants, bakeries, and other businesses (3934); and hotels (xviii) and shopping centers (24).

Citizens dispose off their waste product in plastic bags, plastic/metal dustbins (buckets and one-half steel drums), or polyethylene or metal containers of unlike capacity or but in majority left on ground (Figure 2).

The municipality of Sfax makes 400 metal waste matter bins of 770-liter capacity available in some areas.

Waste collection is carried out manually and/or mechanically. The vehicles available in the municipality for the collection are 4 packer trucks of 12 chiliad³ capacity, fourteen rear-terminate loaded compaction trucks of 16 one thousand³ capacity, 10 dump trucks of 7 t capacity, 13 tractors of five k³ capacity, 2 pickup trucks of 3 chiliadⁱⁱⁱ, and three mini tractors. Multidump trucks (30 g³) are also available to evacuate the anarchic dumps and ensure transfer of waste material to the municipal landfill.

The communal area is swept by a full of 44 circuits, including 19 circuits of drove operated by rear-end loaded compaction trucks, 15 by dump trucks, and 10 by tractors [half-dozen]. Besides, laborers carrying paw cart ensure the collection of waste from inappreciably accessible places and unload information technology into trucks at certain predefined gathering places (Figure 2(d)).

The staff ratio is about one collection agent per 600 inhabitants in the district of El Medina to reach up to one per 2200 inhabitants in the district of Merkez Chaker, knowing that the crew of each drove vehicle consists of a driver and 2 workers. The collected waste material is split between two transfer stations before being transferred to the municipal landfill site in the absence of any source separation process or sorting at transfer stations.

Multiple expenditures (straight and indirect expenses) are required to handle one ton of waste from drove until landfilling operations. These expenses are as shown in Figure 3(a) where it is noted that the sum of salaries and equipment costs exceeds 70%. In Figure iii(b) is presented the cost of collection and ship of 1 ton of waste matter (based on 2012 information in [half dozen]) for the districts of Sfax urban center. The average is 76 TND/t (therefore an annual assart per capita of around 19 TND/cap/yr) showing huge gaps between different districts. On the other manus, the costs are nearly 45% lower for the districts whose drove is ensured by private companies than by municipal service, as the case of El Boustane and Sfax Nord whose costs are 41 and 51 TND/t, respectively. In comparing to the national boilerplate (53–73 TND/t) these values are excessively high and suggest that an infrequent quality of service is offered!

(a)
(a)

(b)
(b)

It should be noted that the recovery of expenses past revenues from municipal taxes does non exceed 30% and the deficit (70%) would be borne by the state (recovery of other taxes and subsidies).

3. Methodology and Tools

The current case study concerns one of x collection routes in the district Cité El Habib, Sfax urban center (Figure ane).

The arroyo for optimizing the collection system relies on GIS which provides an effective ways to import, manage, and clarify spatial data. The methodology followed in this work consists mainly of two procedures (Figure 4): the design of the geodatabase and analysis of the results.

iii.1. Data Collection and GIS Design

A geodatabase was prepared using the GIS environment "ESRI ArcGIS" from maps, municipal and statistical services information, satellite images, monitoring and field work, and literature information. The required data are related to geographic/urban characteristics of the study area also as characteristics of the waste collection procedure.

The following data were obtained and processed in suitable forms (vectors, tables, and raster): delimitation of the study area; detailed state use plan of the municipality; population distribution and density; satellite epitome (Google Earth); route network; and information on roads (traffic, restrictions, and signs).

We accept been tracking the collection route with a GPS (Global Positioning System) to take all relevant data and facts: location of the starting bespeak, starting time, number of workers, itinerary and coordinates of collection points, condition of waste material on site, condition of container and bins, odometer reading before departure and after collection, fourth dimension of arrival at the transfer station, amount of waste collected, and quantity of energy consumed.

In one case our database is established, the optimization model is performed with the apply of the Network Annotator (NA) tool on ArcGIS. This work was carried out because the actual scheme of collection and transportation as well as other proposed scenarios.

3.2. GIS Analyses: ArcGIS NA

ArcGIS NA is a user-friendly powerful ArcGIS extension that provides easily and directly the most efficient route solutions. The optimal path searching algorithm solves the trouble of selecting the optimal road on a nonnegative weighted undirected graph in a reasonable calculating fourth dimension. This is mainly to build a cost matrix containing costs (length) between origins and destinations. These points represent to pairs of vehicle end point (location of the bins) [x].

In ArcGIS NA, routes tin can exist calculated co-ordinate to the distance and time criteria where full travel time is the sum of the vehicle operating time plus the time of waste material loading/unloading.

The user is able to fix or modify all the dynamic factors needed to create an initial scenario. Past changing these particular parameters, other scenarios can be generated leading to several solutions. Finally, the solution is identified by a function that refers to various parameters, such as the shortest distance, the road network, and the social and environmental implications [18].

iv. Results and Discussion

The electric current report for the chosen drove route is based on the actual real state (initial scenario, S0) along with 3 other suggested scenarios (S1, S2, and S3). The master results of analyses are shown in Table one.


Scenarios	Transport equipment	Workers	Traveled distance [km]		Duration of collection [h]		Fuel consumption [Fifty]

S₀	one truck 2 paw carts	five	37 undefined	37	vii 7	vii	25 0	25

Due south₁	1 truck 2 hand carts	v	32 undefined	32	half dozen 6	6	21 0	21

S₂	i truck 1 tractor	half dozen	xix 13	32	ii three	3 2	thirteen vii	twenty

S₃	1 truck	3	22	22	3	3	13	13

4.i. Scenario S0: Current Route

In Figure five we illustrate the tracing of journeying made by rear-end loaded compaction trucks during collection, the coming together places of the truck with manus cart, and anarchic points that show waste matter accumulation areas. The collection is fabricated by a team of 5 persons: the driver and two collectors in the truck and two collectors with hand cart. The altitude traveled by truck from the starting indicate (the municipal garage) to the transfer station is 37 km and lasts seven hours including 2.5 hours of driving, 4 hours to load/unload bins, and 30 min intermission. The corporeality of waste collected during a trip is around 3 to v tons.

4.2. Scenario S1: Optimized Route Using the Same Piece of work Method

For this scenario nosotros kept the aforementioned work method as in S0 (equipment and number of workers) and therefore the same stop points. Merely the route and the sequencing of stoppages differ.

The truck goes through all the anarchic points and information technology meets with paw cart allowing the workers enough fourth dimension to collect the waste from those areas as well. The driver should non backtrack in order to minimize the risks of accident. The vehicle does not pass twice through the aforementioned route.

Nosotros notice, though with the same equipment and the same staff, that waste material collection is performed with decreased altitude (31 km) and therefore with less fuel consumption (21 L) and less working hours (half dozen hours).

4.three. Scenario S2: Optimized Route with a Modify of Vehicles

The passage of rear-end loaded compaction truck in tight areas hinders traffic. Too, it is not cost effective to carry out door to door waste collection with such a vehicle. Therefore, we proposed the employ of a tractor or pickup truck-type vehicle (Figure 6).

For this scenario the work will be divided into a function made by compaction truck and the other by the tractor or pickup as the following instructions: (i) zones with large quantity of waste product must be collected by the compaction truck besides collection ensured with hand cart; (ii) zones with low quantity of waste product will be nerveless door to door by the tractor; (iii) the path fabricated past the compaction truck does not overlap that performed by the tractor as shown in Effigy half-dozen; (four) truck meets the manus cart only twice; (v) residents in areas non covered past manus cart should be informed so that they carry their waste material until the placed containers.

Nosotros found out that the travel distances of the truck and the tractor are curt (19 km and xiii km, resp.), then this allows increasing the perimeter of working area performed by the aforementioned team for the same working session.

iv.4. Scenario S3: Optimized Route with Modified Collection Method

This scenario consists of an optimized path with a modified collection mode, that is, change of vehicle and reallocation of waste matter bins. This scenario assumes enough containers and imperatively requires the cooperation of citizens to make the try of bringing their waste material until allocated containers.

The number of containers to put is proportional to the daily product of waste material and has to exist enough to serve the entire population as follows:

The proximity distance to container is causeless to be 125 m; that is, the furthest citizen in a container buffer zone volition walk a maximum altitude of 125 m. We considered an average waste density of 0.4 t/m^three and 0.77 m^three capacity containers. Drove points were selected based on the availability of sufficient space for the containers placement. The number of locations/points was deducted from a prepared map of waste material product distribution by area (Effigy 7). The result and then obtained empirically allows roofing about 92% of the whole study area and suggests that citizens living outside the covered area have to walk for more than 125 yard to reach the nearest container. However, a better effect is obtainable if an appropriate optimization of containers number/location/buffer zone is carried out.

The optimization of this scenario (Figure eight) will allow a better service and might contribute to eradicating anarchic points. In addition to that, it results in significant gains for the drove/transportation functioning with reductions of 40%, 57%, xl.5%, and 48% in the number of workers, working time, traveled distance, and fuel consumption, respectively, without mentioning the extra benefits related to CO₂ emissions, wear/maintenance of vehicle, so forth.

Because the main components of the direct charge to the cost of collection/transport of waste (vehicles expenses, drivers and collecting workers expenses), the savings rise up to xl TND/t; hence the management cost of ane ton of waste may drop from 95 TND/t to effectually 55 TND/t.

Nosotros can estimate the almanac earnings in the order of lx,000 TND/year subsequently optimization with just an investment of about 14,000 TND for granting sufficient number (twoscore) of containers.

five. Conclusions

In this study, an optimization was developed using the ArcGIS NA tool in order to improve the efficiency of the collection and transportation of waste product in the Cité El Habib district of the municipality of Sfax, Tunisia.

Iii scenarios were generated and analyzed for the identification of optimal routes: S1—optimized route using the same piece of work devices (alter of sequencing stops only); S2—optimized route with change of vehicles; and S3—optimized road with a change of drove mode (irresolute the transportation equipment and reallocation of containers).

Compared to the current situation, the results showed that Scenario S3 allows savings of about 40%, 57%, twoscore.5%, and 48% in the number of workers, working time, traveled distance, and fuel consumption, respectively, and hence a gain of about 60,000 TND/yr, in addition to other benefits related to CO_two emissions, hours of work, vehicles wear/maintenance, and then forth. These findings bespeak that GIS-based optimized scenarios can provide pregnant improvements to the collection/transportation organisation of SW and consequently to its financial and environmental costs.

These results could exist further enhanced by optimizing the location of containers and later on this could be tried to be applied for the whole city of Sfax.

Competing Interests

The authors declare that they take no competing interests.

Acknowledgments

The authors would like to give thanks the Department of Environs and Cleanliness, Municipality of Sfax, for their help in providing data and for their cooperation and logistic support during fieldwork.

Copyright

Copyright © 2016 Amjad Kallel et al. This is an open admission article distributed under the Artistic Eatables Attribution License, which permits unrestricted use, distribution, and reproduction in whatsoever medium, provided the original work is properly cited.

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Source: https://www.hindawi.com/journals/je/2016/4596849/