municipal solid waste landfill site selection in the sekondi-takoradi metropolis of ghana using...

Municipal solid waste landfill site selection in the Sekondi-Takoradi metropolis of Ghana using fuzzy logic in a GIS environment

JEWM


TM Bilintoh1 and E Stemn2

1Geosurvey Engineering (Ghana) Limited, P. O. Box 2363, Accra, Ghana.

2Environmental and Safety Engineering Department, University of Mines and Technology, P. O. Box 237 Tarkwa,

Ghana.

One of the threats to global environmental health is waste generation. Growth in population as well as rise in the quantity of municipal solid waste generated has made it difficult to locate appropriate site for waste disposal in most urban areas. Land filling is now accepted as the most widely used method for addressing this problem in all countries of the world. However, appropriate site selection for land filling is a problem in waste management and therefore needs to be addressed. This research sought to identify a suitable landfill site for waste disposal in Sekondi-Takoradi Metropolis of Ghana. To achieve this, Geographical Information System (GIS), Fuzzy Logic and Multi-criteria Evaluation (MCE) were applied in order to display and rank candidate sites. The analysis was limited to criteria that were selected and relevant to the area under investigation. The results obtained provide clear areas for landfill sites in the study area and finally arrives at suitable areas.

Keywords: Fuzzy, GIS, landfill, multi-criteria, weighted linear combination INTRODUCTION One of the unavoidable products of the human society is Municipal Solid Waste (MSW). The increasing trends in the generation of MSW in time past led to the establishment of a management system known as the municipal solid waste management system (MSWMS) which has gained popularity in recent past (Rafiee et al., 2011). The MSWMS is an integrated approach of managing MSW and involves several techniques involving recycling, recovering, reuse, incineration/gasification, composting and landfilling (Tchobanoglous et al., 1993). Even though, there is a worldwide convergence on waste reuse and recycling, landfill stills becomes unavoidable in the MSWMS especially in most developing countries such as Ghana. In most developing countries, the technical know-how and the finance required to engage recycling of MSW is readily non-available and therefore many resort to the use of landfill as the cheapest mean of managing MSW. In Ghana, the country is seriously plagued with several waste generation problems. According to GEPA (2002),

there is an increased concern for MSW management, this is due to increased production of MSW, especially in large urban areas. Based on an estimated population of 20 million and an average daily waste production per capita of 0.45 kg, Ghana generates annually about 3.3 million tons of solid waste. The quantities of waste generated are increasing rapidly and may double by the next decade (GEPA, 2002).Municipal solid waste has been disposed of anywhere anyhow without regard to the nuisance and harm caused to the environment. Improved waste disposal is therefore called for by the Government’s Environmental Sanitation Policy, in pursuit of the development and maintenance of a clean, safe and pleasant physical environment in all human settlements to promote the social, economic and physical wellbeing of all sections of the population. *Corresponding Author: Environmental and Safety Engineering Department, University of Mines and Technology, P. O. Box 237 Tarkwa, Ghana, [email protected]

Journal of Environment and Waste Management Vol. 2(2), pp. 071-078, June, 2015. © www.premierpublishers.org, ISSN: 1936-8798x

Research Article

mailto:[email protected]


Bilintoh and Stemn 071 It was due to this that necessitated the development of the Landfill Guideline by the Environmental Protection Agency (EPA). The purpose of the guideline was to provide the basis upon which the EPA will issue Environmental Permits and Certificates and District Assemblies will issue and renew licences for landfill operations in the country. A landfill is a large area of land or an excavated site that is specifically designed and built to receive wastes (USEPA, 2014). Landfills and related MSW facilities are becoming difficult to locate in urban areas because of a shortage of large tracts of land and community opposition (Rafiee et al., 2011). The ‘‘not in my backyard’’ (NIMBY) and ‘‘build absolutely nothing anywhere near anyone’’ and ‘‘not on planet Earth’’ syndromes have become popular, creating a tremendous pressure on decision makers in selecting sites for MSW facilities. All these make site selection of landfill very challenging especially in urban areas like the Sekondi-Takoradi Metropolis (Rafiee, 2007). Therefore there is the need to adopt methods that will incorporate all these concerns during the selection of site for landfill. One of the main goals of the MSWMS is to determine the type, location, and capacity of facilities that will be used for disposal and/or treatment of the waste, based on environmental, economic, social, and health considerations. Therefore, suitable location of disposal facilities is a major issue in waste management. Over the years several methodologies have been applied for sitting a landfill in combination with GIS, such as, expert systems, raster-based C programs with optimal compactness, multi-criteria analysis (Lin et al., 1999).Mahamid et al. (2010), in an effort to site an appropriate landfill for Ramallah Governorate in Palestine, used thematic maps to create vulnerability map for the area and the result was compiled to the buffer zones around sensitive areas by using multi-criteria analysis in GIS. Javaheri et al. (2006)adopted GIS as a tool to evaluate the suitability of the vicinity of Giroft city in Kerman province of Iran for a landfill using several criteria such as water permeability, slope, distance from rivers, depth of underground water table, distance from residential areas, distance from generation centres and distance from roads. Considering relative priority of all criteria in comparison with others, a specific weight was designated to each criterion according to their total influence on the whole process of decision making. Furthermore, Zeinhom et al. (2009) used an integration of GIS and Multi-Criteria Decision Making (MCDM) to locate a landfill sites in Mansoura city, Egypt. In their research, eight criteria were used. They used both Weighted Linear Combination (WLC) and Analytical Hierarchy Process (AHP) in a GIS environment(Zeinhom et al., 2009). In this study, WLC was implemented in a GIS-Fuzzy Logic environment to locate a site for landfill in the Sekondi-Takoradi Metropolis of Ghana.

MATERIALS AND METHODS Study Area Size and Location Sekondi-Takoradi Metropolis, the capital of the Western Region of Ghana is located between Latitude 4° 52' 30" N and 5° 04' 00" N and Longitudes 1° 37' 00" W and 1° 52' 30"W. The Metropolis is surrounded by the Mpohor Wassa District to the north, the south by the Gulf of Guinea, the West and East by the Ahanta West District the Shama District respectively. The metropolis is strategically located in the south-western part of the country, about 242 km to the west of Accra and approximately 280 km from the La Côte d’Ivoire in the west. The Metropolis lies within the South-Western Equatorial Zone. It therefore has fairly uniform temperature, ranging between 22

oC in August and 30

oC

in March. (Stemn et al., 2014; Kumi-Baoteng et al., 2015). The metropolis is the smallest (with a land size of 230 km

2) among the 22 districts in the Western

Region but however the most developed and populated in the region. It is the third largest metropolis in Ghana (STMA, 2006). Figure 1 is a map of the study area. Waste Management in Sekondi-Takoradi Metropolis The collection, transportation and final disposal of both solid and liquid waste is the responsibility of the Waste Management Department, a department within the Metropolitan Assembly. A total of 206 kg per day with a collection rate of 70% is the estimated solid waste generated within the metropolis. According to Fei-Baffoe et al. (2014), the capita waste output in the city is estimated at 0.6 kg. Just like most cities in Ghana, waste generated at source is stored using various containers ranging from plastic bags, paper boxes, baskets, unused buckets, or any container considered appropriate for such purpose (Kreith, 1994). Nonetheless, some high to middle income household within the metropolis store their solid waste in dustbin with proper covering. Additionally, sorting and segregation of waste at source is not a common practice within the metropolis (Fei-Baffoe et al., 2014). Solid waste collection system employed within the metropolis is of two main types and is either on a franchise or contract basis. The major cities and towns within the municipality have been zoned into units and private waste collection company have been assigned the responsibility of collecting and transporting solid waste from the various zones to the final disposal site. The two main methods of solid waste collection within the metropolis are the door to door collection and the communal waste container system (Fei-Baffoe et al., 2014). All wastes collected within the metropolis are disposed of at the newly constructed landfill at Sofokrom, a suburb of Essipon in the Sekondi-Takoradi Metropolis.


J. Environ. Waste Manag. 072

Figure 1. Map of the Study Area

Table 1. Datasets used for the Study

Dataset Scale or Resolution Source

DEM 30 m By 30 m US Geological Survey

Properties (Settlement) 1 : 50 000 Town and Country Department

Roads 1 : 50 000 Survey and Mapping Division of Ghana

Water Bodies 1 : 50 000 Survey and Mapping Division of Ghana

Materials In this research, several datasets, both vector and raster at different scales were used. These data were obtained from different sectors based on availability and suitability for the purpose of the study. Table 1 show the datasets used together with their sources. Methods This research made use of fuzzy logic in a GIS environment to determine a suitable site for landfill. The fuzzy logic method is one of the most widely used GIS-based decision rules. This is because unlike Classic Boolean logic which is binary, fuzzy logic permits the notion of difference in shades of colour, meaning and expression (Zadeh, 1965). The methodology adopted was divided into four main procedures namely; determination of criteria and constraints; development of attributes of each criteria and standardisation of each criterion unto a common scale; determination of degree of influence of each criterion and finally combination of all the criteria to determine the suitability index. Four criteria namely, properties, water bodies, roads and slope were used to evaluate the suitability of a land as

a landfill site. Apart from these criteria, constraints such as 2 km from recreational site and protected areas, 5 km from airport and 2 km from institution such as schools and hospitals were also used in the suitability evaluation process (Nilchiyan, 2002; USEPA, 2004; Ayat, 2006; Rafiee et al., 2011). Selection and Standardisation of Criteria This first step involved the selection of the criteria for the evaluation. At this stage, several criteria were considered however due to unavailability of data, some were rejected; thus the criteria were selected solely based on the availability of data. Database was developed for each of the criterion and was followed by standardisation of each criterion with regards to the suitability for locating a landfill site. Data was imported from a vector format into a raster format at a pixel size of 30 m. This was necessary because the dataset required for the use of fuzzy logic in the GIS environment is raster. A straight line distance was used to determine the distance from a fixed point to all other points on water bodies, properties and road raster maps.


Bilintoh and Stemn 073

Table 2. Rating of Each Criterion

Rating

Suitability Level Road Water Bodies Property Elevation

0.0000 - 0.1172 0.0000 - 0.1211 0.0000 - 0.1133 0.0000 - 0.1133 Highly Suitable

0.1172 - 0.3633 0.1211 - 0.3633 0.1133 - 0.3398 0.1133 - 0.3398 Suitable

0.3633 - 0.6133 0.3633 - 0.6133 0.3398 - 0.5898 0.3398 - 0.5898 Fairly suitable

0.6133 - 0.8672 0.6133 - 0.8672 0.5898 - 0.8555 0.5898 - 0.8555 Low Suitability

0.8672 - 1.0000 0.8672- 1.0000 0.8555 - 1.0000 0.8555 - 1.0000 Unsuitable

The four criteria selected could be grouped into two main categories: (1) favourable (would result in higher suitability) and (2) unfavourable (would result in lower suitability). The suitability score of each criterion was standardised with a fuzzy subset membership (Rafiee et al., 2011). Fuzzy logic was introduced to supplement interpretation of intangible factors or measured uncertainties. Unlike the Boolean set, boundaries in the fuzzy set are not sharply defined. In this way, the fuzzy set provides a convenient way to treat intangible environmental phenomena. As a result of the logic behind fuzzy set memberships as well as the possibility of creating a continuous scale map in GIS, fuzzy set memberships are highly appealing in criteria standardization (Jiang et al., 2000; Rafiee et al., 2011). Rasteralgebra was used to execute fuzzy analysis on each map generated. To do this, information obtained with regard to siting of landfills was used as the criteria to write logical statements using the fuzzy logic membership function shown in equation 1(Karkazi et al., 2001). µA (X) = {0, x ≤ a, (x-a)/(b-a)} a ˂ x ˃ b, 1, x ≥ b; x ϵ X Equation (1) Where μA represents the fuzzy membership function, X is the universal set with a and b being the limits or internal of that universal set and x is a member of the universal set whose upper limit is b (standardized as 1) and lower limit is a (standardized as 0). This logical statement was used to create fuzzy membership functions for all the criteria as shown below. The map layers were standardized using fuzzy set membership functions in a GIS environment. According toRafiee et al. (2011), there are variety of functions that could be used for fuzzy set membership standardization, including sigmoidal, J-shaped and linear functions. To apply each of these, there is the need to define control points for the standardization curve (Eastman, 2009). In this research, a linear function membership standardisation was used to assign rank to each of the four criteria in a range of 0 to 1. Negative public reaction and general opposition from people living close to transfer stations and landfills are well documented(Omrani et al., 1998; Ayat, 2006). The distance between the settlements (residential and commercial areas) and the landfill site is therefore important. The properties map obtained from the Town and Country Planning Department of the Metropolis at

a scale of 1:50 000 was used as an imput to create a straight line distance map. Areas within 1 km of residences were considered unsuitable with the suitability values increasing linearly from 0 to 1 for locations between 1 km and 5 km from residences; the highest value was assigned for locations beyond 5 km from residences(Rafiee et al., 2011). Streams and rivers channels within 1 km were classified as unsuitable whiles those beyond 3 km were considered unsuitable; those between 1 km and 3 km were considered suitable with land suitability increasing linearly from 0 to 1. Current highway data obtained from the Survey and Mapping Division was used to determined the suitability of the landfill. Locations within 500 m and beyond 5 km from a highway were considered unsuitable. Locations situated between 1 km to 4 km from the highway were considered more suitable. Slope class was determined from the digital elevation model obtained from the United State Geological Survey (USGS). According to Makhdum (1993), areas with a slope of >9˚ were considered unsuitable and were assigned a score of 0; slopes measuring from 0˚ to 6˚were considered most suitable, receiving a score of 1 (Rafiee et al., 2011). The results obtained from the fuzzy analysis were reclassified into various sections of suitability ranging from unsuitable to highly suitable. However since unsuitability for one criterion might reflect high suitability for other criterion, as in the case of the elevation and property criteria the reclassification was done separately for each criterion. Table 2 shows the reclassified rating for each of the criterion. Assignment of Weights to the Criteria Since each criterion has a certain degree of importance, the concept of weighting was employed to give the required levels of importance to each criterion. This was essential because all the criteria were not of equal significance. According to Kirkwood (1997), one of two methods could be adopted in ensuring that each criterion is evaluated based on its relative importance. The first approach consist of selecting the same numerical range (0–1) for each of the various criteria and then assigning each criterion a score based on its weight, and finally multiplying each standardised



Table 3. Weight of each Criterion

Criteria Weight

Water body fuzzy map 0.35

Property fuzzy map 0.30

Road fuzzy map 0.20

Elevation fuzzy map 0.15

Total 1.00

criterion by the value assigned to its relative weight to calculate its suitability index. In the second approach, a variable numerical range is used for the various criteria depending upon the relative importance of each criterion (Rafiee et al., 2011). In this research the first method was adopted. There exist several methods by which the weight of criterion is determined. These methods includes, the pairwise comparison method, the ratio methods, the ranking methods and the trade-off analysis methods (Malczewki, 1999). In this research the ranking method was adopted. The various criteria were ranking after a thorough discussion with city planner and various stakeholders. These ranks were also determined from knowledge obtained from the current landfill within the metropolis. The engineers that sited and constructed the current landfill were consulted to provide information on how the relative importance of each of the criterion was determined. It was observed from the field consultation that, nearness to water body should be ranked highest among all the four criteria whiles slope receives the lowest rank. Table 3 shows the weights that were determined from the ranking method. Combination of Criteria to Determine Suitability Index The various maps obtained after the fuzzy analysis was then combined to generate a single map, showing areas of different suitability levels for siting a landfill within the study area. In this research, the Weighted Linear Combination (WLC) method was used to combine the criteria and compute the suitability index. The WLC method was chosen over the Boolean Intersection (BI) and the Ordered Weighting Average (OWA) because it is simpler and the most widely applied method (Malczewki, 2004; Rafiee et al., 2011). Using the WLC method, the suitability index was calculated by summing the product of each of the weight of each criterion with its standard score according to equation 2.

iixw Index ySuitabilit

Equation (2) Where wi is the weight of each criterion i and xi is the standardised score (0-1) of each criterion.

Selection of the Best Site After obtaining the suitability index, there was the need to select best sites that should be considered for the landfill. In doing this, the constraint map which was obtained by applying a Boolean logic was used. Suitability score was then determined from the product of the constraints and the suitability index using equation 3.

jii C xw Score ySuitabilit Equation (3)

Where Cj is the score of constraint j and ∏ is the product sign for the constraints. This means that the product of the constraint was multiplied by the suitability index of each pixel. In selecting the best site, a minimum suitability score of 0.65 was determined for suitability and land area of 20 ha to accommodate vehicles and equipment as well as to provide additional space for future expansion. The 20 ha was determined through several consultations with city planners. According to the Ghana Environmental Protection Agency (EPA), waste generation in the proposed catchment area should be estimated from the existing population and expected growth rate; this was done accordingly. Additionally, domestic solid waste production can be estimated as about 0.45 kg per person per day. Extra quantities of waste such as those generated from major market, commercial areas and industrial activities were all considered during the determination of the minimum land area for the landfill site (GEPA, 2002). RESULTS AND DISCUSSIONS Results Generation of Straight Line Distance and Slope Figure 2 shows the straight line distances that were generated from the properties, water bodies and roads datasets after it was converted to a raster format. The figure also shows the slope map in degrees that was generated from the DEM. There was the need to generate straight line distances because the landfill site should be of a certain distance from those datasets (properties, water bodies, roads).



Figure 2. Map Showing Straight line Distance and Slope of Evaluated Criteria for the Landfill Site

(a: straight line distance from properties to all points, b: straight line distance from water bodies to all points, c: straight line distance from roads to all points, d: slope in degrees)

Standardisation of Criteria Figure 3 are map that shows all the criteria after they were standardised by the assignment of fuzzy membership based on an evaluation scale of 0 to 1. Suitability Index The Suitability Index (SI) of landfill for the study area is shown in Figure 4. Suitability index values ranged from 0 to 1, with higher index values showing greater suitability of land for siting a landfill. The index values were reclassified into five levels of suitability ranging from unsuitable to very highly suitable. Table 4 shows these suitability classes as well as their corresponding index values and total area. Selection of Best Sites Applying the constraint map together with a minimum area of 20 ha, 4best sites were selected from the very highly suitable class range. These potential sites together with the constraints are shown in Figure 5.

Discussions To ascertain the accuracy and reliability of the selected best site, spatial autocorrelation was conducted. This has the capability to determine the total area threshold and the suitability threshold; and accordingto Eastman (2009) and Rafiee et al. (2011), it refers to the correlation between each pixel and its neighbouring pixels. In this research, spatial autocorrelation was carried out to ensure that the Fuzzy-GIS-WLC approach which was used worked correctly for all the best selected sites. The spatial autocorrelation for sites 1, 2, 3 and 4 were 0.92, 0.95, 0.90 and 0.89 which indicate a high spatial autocorrelation. In the determination of the final best four sites, the prevailing wind of the entire study was also considered. Prevailing wind refers to the wind direction mostly observed in an area during a given time period. In order to determine the prevailing wind, a 20 year data of both wind direction and wind speed was obtained from the Ghana Meteorological Agency and used to generate a wind rose diagram. The wind rose diagrams showed that the prevailing wind emanates from South-Western

b. a.

d.

c.



Figure 3.Maps showing suitability of evaluation (standardised) criteria for landfill site (a: distance to settlement; b: distance to water bodies; c: distance to roads; d: slope)

Figure 4. Landfill Suitability Index of the Study Area

direction to the North-Eastern direction. All the four best sites were located in the northern part of the study areas and therefore all of them could be developed with minimal mitigation. For site 1, no mitigation plan is required since it is located in the North-East; the prevailing wind which emanates from South-West would have reduced before arriving in the North-Eastern side. In order to avoid the transfer and

deposition of pollutants from the landfill sites into residential areas, the wind rose was used to rank the four best sites. Site 1 had the highest rank followed by site 4 and 2 with site 3 having the lowest rank. Other factors should be considered in making a choice on which of the best site to select. According to Rafiee et al. (2011), economic factors such as cost of land acquisition, cost of development and operation of the



Table 4. Suitable Classes with their Areas

Suitability Index Class Name

Area

Ha %

0.00 - 0.10 Unsuitable 8748.36 40.23

0.10 - 0.20 Low Suitable 1430.46 6.58

0.20 - 0.5 Moderately Suitable 6882.75 31.65

0.50 - 0.65 Highly Suitable 4242.87 19.51

0.65 - 1.00 Very Highly Suitable 442.08 2.03

TOTAL 21746.52 100.00

Figure 5. Locations of Best Sites for Landfill Site in the Study Area

facility must all be considered in choosing which of the best sites to develop. Additionally, the selected site should be evaluated in terms of the land ownership, land use and availability of utilities (Erkut et al., 1991). If all these other factors are considered, there would be a significant reduction in both the cost and time associated with detailed site investigations (Rafiee et al., 2011). CONCLUSIONS Siting of landfill site is multidisciplinary and a very complex process, therefore careful consideration of all factors ranging from environmental to economic is required. This research has demonstrated the use of multi-criteria evaluation (MCE) in GIS-Fuzzy Logic environment for selecting of a landfill site in the Sekondi-Takoradi Metropolis. The MCE was therefore proven to be an effective and efficient method of siting a landfill.

Through a thorough consultation with city planners and experts and based on availability of data, criteria were selected; attribute were developed for the criteria; the criteria were standardised and weighted in terms of their relative importance. The standardisation of the criteria was based on suitability for landfill site. Using WLC, the standardised maps were then combined and several constraints applied on the combined map. The study demonstrated that fuzzy logic is a straightforward method that can be implemented easily in a raster GIS environment. Using fuzzy logic and WLC in the GIS environment city planners and decision makers are provided with a reliable and useful tool for decision making. The results of this study therefore offer decision makers in the study area variety of options with which to site a landfill. The method adopted in this study is very flexible, it allows inclusion of many criteria based on decision-makers’ ideas, the method has great potential for application in other areas. The method is also repeatable and understandable in terms of


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Accepted 05 June, 2015. Citation: Stemn E, Bilintoh TM (2015). Municipal solid waste landfill site selection in the Sekondi-Takoradi metropolis of Ghana using fuzzy logic in a GIS environment: Case study. Journal of Environment and Waste Management 2(2): 071-078.

Copyright: © 2015 Stemn and Bilintoh. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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