Landfill siting is a complex, multicriteria decision-making problem that needs an extensive evaluation of environmental, social, land use, and operational criteria. Integration of a median ranked sample set (MRSS) and an analytic network process (ANP) has been implemented to rank the associated criteria and select a suitable landfill site. It minimizes the uncertainty and the subjectivity of human judgments. Four groups of experts with different backgrounds participated in this study, and each group contained four experts. The respondent preferences were ranked in a 4-by-4 matrix to obtain the judgment sets for the MRSS. These sets were subsequently analyzed using ANP to obtain the priorities in the landfill siting criteria. The results show that land topology and distance from surface water are the most influential factors, with priorities of 0.18 and 0.17, respectively. The proposed integrated model may become a promising tool for the environmental planners and decision makers.
Facility site selection model is complex and needs extensive assessment and comparison efforts [
Decision support systems like the analytic hierarchy process (AHP) and its generalization (ANP) have been widely implemented to handle the complex problems. Multicriteria decision-making (MCDM) using ANP is composed of the following steps: (i) identifying the factors and the components within the network together with their interactions and relations; (ii) conducting pairwise comparisons among the network elements and the main/subcriteria to build the unweighted supermatrix; (iii) obtaining the weighted supermatrix via weighting the blocks of the unweighted supermatrix by the corresponding priorities of the clusters (from which the resulting matrix is column stochastic); and (iv) developing the limit matrix by increasing the power of the weighted supermatrix until the weights converge [
The ANP is implemented to drive the relative priorities of the criteria using the judgment of individuals [
The ranked sample set (RSS) was first proposed by Mc Intyre in 1952 to estimate the population mean, and since that time it was modified and developed many times [
This study presents a model to reduce the imprecision and vagueness of the human decision-making. It identifies the relative importance of landfill siting criteria as a case study. The presented model leverages the power of an expert system to extract knowledge that is subsequently applied to a hybrid MRSS-ANP system to obtain the criteria weights.
Landfill siting is a multicriteria decision-making process. The proposed model decomposes this process into three levels: problem construction, criteria analysis, and selection [
The problem construction starts with a literature review used to determine the main and subcriteria of the landfill site selection. There are no general approaches to select a set of evaluation criteria but it can be selected through an examination of the relevant literature, analysis study, and expert opinions [
Hierarchical structure of the landfill siting criteria.
A developed questionnaire asked the stakeholders to draw pairwise comparisons among the criteria and the subcriteria with respect to landfill site selection. The used questionnaire takes into account the interactions and feedbacks between the criteria. Table
Definition of the scale of importance [
Intensity of importance | Definition | Explanation |
---|---|---|
9 | Extremely important | This activity is of the highest possible order of affirmation |
7 | Strongly important | This activity is strongly favored (dominant) over other activities |
5 | Moderately important | This activity is moderately favored over other activities |
3 | Slightly important | This activity is slightly favored over other activities |
1 | Equally important | This activity equally contributes to the objective |
2, 4, 6, and 8 | Intermediate importance between two adjacent responses |
The stakeholders preferences were grouped into four random sets. Each set consists of the responses of one government, private, academia, and NGO respondent. The respondents are experts in the field of solid waste management and landfill siting issues through their work experience. Table If the sample size, If the sample size
then the median is selected by
Comparison of the importance of land use with the importance of operation methods.
Sector | Government | Private sector | NGO | Academia |
---|---|---|---|---|
Expert group number 1 | 7 | 0.33 | 0.20 | 1 |
Expert group number 2 | 1 | 3 | 1 | 0.14 |
Expert group number 3 | 7 | 5 | 3 | 7 |
Expert group number 4 | 3 | 3 | 3 | 0.20 |
Ranked comparison of the importance of land use with operational methods.
Ranked experts preferences | ||||
---|---|---|---|---|
Expert group number 1 | 0.20 | 0.33 | 1 | 7 |
Expert group number 2 | 0.14 |
|
1 | 3 |
Expert group number 3 | 3 |
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|
7 |
Expert group number 4 | 0.20 | 3 |
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3 |
The study aim is to determine the overall priority of each criterion and apply it in the case study considering the interactions and the feedbacks among the main and subcriteria. ANP systematically breaks down the problem to justify the decision [
Interactions and feedback between criteria.
The resulting relative importance sets from the previous step contain the preferences of government, private, NGO, and academic stakeholders and are used in the ANP. This step is repeated for the sixty-three pairwise comparisons to build the comparison matrix (unweighted supermatrix). The inputs of the supermatrix depend on the presence and the type of dependence among the group elements that are shown in Figure
The landfill site selection algorithm.
Selangor is the most populated and highly developed state in Malaysia; it has a diversified economy including industry, commerce, agriculture, and tourism. Moreover, Selangor completely surrounds two federal territories, which are Kuala Lumpur (KL), the national capital of Malaysia, and Putrajaya the federal capital. The areas of Selangor, Kuala Lumpur, and Putrajaya are 7,930, 243, and 92 km2, respectively. There is a great demand to depend on scientific approach for determining a landfill site in Selangor due to increasing amounts of solid waste and land scarcity. Thus Boolean logic was implemented to exclude unsuitable areas that cannot be used as a disposal site [
Selangor and potential landfill sites maps.
Figure
Moreover, land use involves the locations of critical sites highways and roads that are identified by the town planning department and these locations are highlighted for specific consideration in future plans. Examples of critical sites include airports, hospitals, railway, and other institutes [
Figure
Based on the interactions and feedback among the criteria, sixty-three pairwise comparisons were required. The preferences of each respondent were recorded for each comparison. Every set of responses contained the opinion of one expert from each group, that is, government, private, academia, and NGO. Therefore, the response range within the same set is relatively large because of the conflicts of interest of the stakeholders. The expert responses within the same group were observed to converge, but outlier responses were noted due to human nature and the various backgrounds of the experts. For instance, one governmental expert might emphasize environmental concerns because of personal involvement in environmental regulations, whereas another governmental expert may emphasize planning and land development because of personal involvement in a planning department. Similarly, one NGO representative could emphasize conservation, whereas another NGO representative might emphasize service to society. Therefore, points of view can diverge within an identical group.
Sixty-three pairwise comparisons were performed to identify the relative importance of the landfill siting criteria. An example of one of these comparisons is shown in Table
The ANP uses three matrices: unweighted supermatrix, weighted supermatrix, and limit matrix. The unweighted supermatrix is the relative importance of all main components and subcomponents. The weighted supermatrix clarifies the values of each group and its elements. The limit matrix represents the priorities results and is obtained by raising the weighted supermatrix to a high power to acquire constant values.
Table
Priorities group matrix of the main criteria.
Sector | Land use | Environmental | Operational | Social |
---|---|---|---|---|
Land use | 0.183 | 0.143 | 0.116 | 0.540 |
Environmental | 0.526 | 0.571 | 0.488 | 0.0 |
Operational | 0.204 | 0.286 | 0.275 | 0.163 |
Social | 0.087 | 0.0 | 0.121 | 0.297 |
The final priorities of the main criteria group are shown in Table
Final priorities of the main criteria.
Main criteria | Final priority |
---|---|
Land use | 0.142 |
Environmental | 0.546 |
Operational | 0.262 |
Social | 0.05 |
The final priorities of the factors related to landfill site selection are shown in Table
Weight priorities of the overall subcriteria.
Group | Criteria | Priority normalized by group | Final priority |
---|---|---|---|
Environmental | SW | 0.317 | 0.173 |
GW | 0.157 | 0.085 | |
FZ | 0.181 | 0.099 | |
TO | 0.345 | 0.188 | |
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Land use | CS | 0.409 | 0.058 |
RA | 0.591 | 0.083 | |
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Operational | HD | 0.145 | 0.038 |
LA | 0.511 | 0.135 | |
SA | 0.344 | 0.091 | |
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Social | AE | 0.579 | 0.029 |
NS | 0.421 | 0.021 |
SW: proximity to surface water, GW: depth of ground water, FZ: proximity to fault zone, TO: topology, CS: proximity to critical site, RA: road accessibility, HD: haul distance, LA: landfill area, SA: soil availability, AE: aesthetic, and NS: nearest settlement.
However, applying (
Finally, incorporating the participation of conflicting stakeholders minimizes the uncertainty and risk of reproducing homogenous decisions and enhances the quality of the decisions. Additionally, consistent and reliable results must be achieved [
As consequence of rapid urbanization and economic growth the solid waste generation is increased dramatically in Selangor state. Owing to this increase, the search for and the provision of an efficient solid waste management method has become an essential matter [
Summary of the rankings and SI for the potential landfill sites.
Site number | Environmental | Land use | Operational | Social | SI | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
SW | GW | FZ | TO | CS | RA | HD | LA | SA | AE | NS | ||
LF1 | 0.173 | 0.085 | 0.040 | 0.113 | 0.058 | 0.017 | 0.038 | 0.135 | 0.091 | 0.029 | 0.004 | 0.782 |
LF2 | 0.173 | 0.068 | 0.040 | 0.113 | 0.058 | 0.083 | 0.038 | 0.135 | 0.091 | 0.029 | 0.004 | 0.832 |
LF3 | 0.035 | 0.017 | 0.020 | 0.188 | 0.058 | 0.083 | 0.038 | 0.135 | 0.091 | 0.029 | 0.008 | 0.702 |
LF4 | 0.138 | 0.068 | 0.099 | 0.113 | 0.058 | 0.083 | 0.038 | 0.135 | 0.091 | 0.023 | 0.013 | 0.859 |
LF5 | 0.104 | 0.085 | 0.020 | 0.075 | 0.058 | 0.066 | 0.038 | 0.135 | 0.091 | 0.017 | 0.021 | 0.711 |
LF6 | 0.138 | 0.051 | 0.040 | 0.150 | 0.058 | 0.064 | 0.038 | 0.135 | 0.091 | 0.017 | 0.004 | 0.787 |
LF7 | 0.035 | 0.017 | 0.099 | 0.113 | 0.058 | 0.083 | 0.038 | 0.135 | 0.091 | 0.029 | 0.008 | 0.706 |
MRSS preference sets.
Number | Comparison target | Comparison elements | MRSS preference sets |
---|---|---|---|
1 | To create positive social opinion | Land use (operational) | 0.33, 1, 7, and 3 |
2 | Land use (social) | 1, 1, 5, and 1 | |
3 | Operation (social) | 0.2, 1, 0.2, and 1 | |
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4 | To protect environmental elements | Environmental (land use) | 1, 3, 5, and 5 |
5 | Environmental (operational) | 1, 1, 5, and 1 | |
6 | Land use (operational) | 1, 1, 5, and 1 | |
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7 | For sustainable and strategic land use planning | Environmental (land use) | 1, 3, 3, and 3 |
8 | Environmental (operational) | 1, 1, 7, and 3 | |
9 | Environmental (social) | 5, 1, 7, and 7 | |
10 | Land use (operational) | 0.33, 0.2, 1, and 3 | |
11 | Land use (social) | 1, 0.14, 3, and 3 | |
12 | Operation (social) | 1, 1, 5, and 5 | |
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13 | To minimize the operational cost and to operate the landfill with best available techniques and best environmental practices | Environmental (land use) | 1, 7, 5, and 5 |
14 | Environmental (operational) | 1, 1, 3, and 3 | |
15 | Environmental (social) | 1, 1, 5, and 3 | |
16 | Land use (operational) | 0.33, 1, 1, and 1 | |
17 | Land use (social) | 1, 0.2, 3, and 1 | |
18 | Operation (social) | 5, 1, 5, and 3 | |
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19 | To protect surface water | Proximity to critical sites (road accessibility) | 0.2, 0.11, 0.33, and 1 |
20 | Soil cove availability (landfill area) | 0.33, 1, 5, and 1 | |
21 | Avoiding faulting zones (depth of ground water) | 0.33, 0.14, 3, and 1 | |
22 | Avoiding faulting zones (topology) | 1, 0.14, 3, and 1 | |
23 | Depth of ground water (topology) | 3, 1, 1, and 1 | |
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24 | To reduce the effects on fault zones | Landfill area (soil cover) | 1, 0.2, 5, and 3 |
25 | Proximity to surface water (depth of ground water) | 1, 1, 3, and 1 | |
26 | Proximity to surface water (topology) | 1, 1, 1, and 1 | |
27 | Depth of ground water (topology) | 1, 1, 1, and 1 | |
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28 | To protect the ground water from pollutants | Landfill area (soil cover) | 1, 1, 5, and 1 |
29 | Proximity to surface water (avoiding fault zones) | 1, 1, 1, and 1 | |
30 | Proximity to surface water (topology) | 1, 1, 0.2, and 0.3 | |
31 | Avoiding fault zones (topology) | 1, 1, 5, and 3 | |
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32 | To reduce altering the land topology | Landfill area (soil cover) | 1, 0.14, 3, and 1 |
33 | Proximity to surface water (avoiding fault zones) | 1, 1, 3, and 3 | |
34 | Proximity to surface water (topology) | 1, 1, 1, and 1 | |
35 | Avoiding fault zones (topology) | 1, 0.2, 0.33, and 1 | |
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36 | To protect the critical sites | Proximity to surface water (avoiding fault zones) | 1, 1, 5, and 1 |
37 | Proximity to surface water (depth of ground water) | 1, 1, 5, and 7 |
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38 | Avoiding fault zones (depth of ground water) | 1, 1, 3, and 3 | |
39 | Aesthetic (proximity to living settlement) | 0.33, 1, 5, and 3 | |
40 | Road accessibility (proximity to critical sites) | 0.33, 1, 1, and 3 | |
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41 | To locate landfill in places easily accessed by roads | Proximity to surface water (topology) | 0.33, 1, 0.2, and 0.2 |
42 | Haul Distance (landfill Area) | 5, 5, 5, and 5 | |
43 | Aesthetic (proximity to living settlement) | 0.33, 1, 3, and 1 | |
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44 | To minimize the solid waste haul distance | Proximity to surface water (topology) | 1, 3, 5, and 1 |
45 | Proximity to critical sites (road accessibility) | 0.33, 0.2, 0.2, and 0.14 | |
46 | Landfill area (soil cover) | 1, 1, 1, and 1 | |
47 | Aesthetic (proximity to living settlement) | 0.33, 0.3, 1, and 1 | |
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48 | To determine the optimum landfill area | Proximity to surface water (avoiding fault zones) | 1, 1, 3, and 3 |
49 | Proximity to surface water(depth of ground water) | 1, 1, 3, and 5 | |
50 | Proximity to surface water(topology) | 3, 1, 7, and 7 | |
51 | Avoiding fault zones (depth of ground water) | 1, 1, 3, and 3 | |
52 | Avoiding fault zones (topology) | 3, 1, 7, and 3 | |
53 | Depth of ground water (topology) | 0.33, 1, 3, and 3 | |
54 | Proximity to critical sites (road accessibility) | 1, 1, 3, and 5 | |
55 | Solid waste haul distance (landfill area) | 1, 1, 1, and 5 | |
56 | Solid waste haul distance (soil cover) | 1, 1, 3, and 3 | |
57 | Landfill area (soil cover) | 0.33, 1, 5, and 1 | |
58 | Aesthetic (proximity to living settlement) | 0.33, 1, 1, and 1 | |
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59 | To protect the soil cover from pollution | Proximity to surface water (topology) | 0.33, 1, 0.2, and 0.33 |
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60 | To minimize the possibility of the landfill being seen | Proximity to critical sites (road accessibility) | 0.33, 0.33, 1, and 1 |
61 | Solid waste haul distance (landfill area) | 1, 1, 3, and 1 | |
62 | Aesthetic (proximity to living settlement) | 1, 0.33, 3, and 1 | |
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63 | To locate the landfill as far as possible from settlements | Solid waste haul distance (landfill area) | 1, 1, 7, and 7 |
Unweighted supermatrix.
Group labels | Environmental | Land use | Operational | Social | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
SW | GW | FZ | TO | CS | RA | HD | LA | SA | AE | NS | |
Environmental | |||||||||||
SW | 0.00 | 0.25 | 0.41 | 0.40 | 0.54 | 0.25 | 0.75 | 0.48 | 0.25 | 0.00 | 0.00 |
GW | 0.55 | 0.00 | 0.26 | 0.00 | 0.16 | 0.00 | 0.00 | 0.15 | 0.00 | 0.00 | 0.00 |
FZ | 0.21 | 0.46 | 0.00 | 0.20 | 0.30 | 0.00 | 0.00 | 0.29 | 0.00 | 0.00 | 0.00 |
TO | 0.24 | 0.28 | 0.33 | 0.40 | 0.00 | 0.75 | 0.25 | 0.08 | 0.75 | 0.00 | 0.00 |
Land use | |||||||||||
CS | 0.25 | 0.00 | 1.00 | 0.00 | 0.33 | 1.00 | 0.17 | 0.75 | 0.00 | 0.33 | 0.00 |
RA | 0.75 | 0.00 | 0.00 | 1.00 | 0.67 | 0.00 | 0.83 | 0.25 | 0.00 | 0.67 | 1.00 |
Operational | |||||||||||
HD | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.83 | 0.00 | 0.49 | 0.00 | 0.67 | 0.83 |
LA | 0.33 | 0.67 | 0.67 | 0.50 | 0.00 | 0.17 | 0.50 | 0.31 | 1.00 | 0.33 | 0.17 |
SA | 0.67 | 0.33 | 0.33 | 0.50 | 0.00 | 0.00 | 0.50 | 0.20 | 0.00 | 0.00 | 0.00 |
Social | |||||||||||
AE | 0.00 | 0.00 | 0.00 | 0.00 | 0.75 | 0.50 | 0.33 | 0.50 | 0.00 | 0.50 | 1.00 |
NS | 0.00 | 0.00 | 0.00 | 0.00 | 0.25 | 0.50 | 0.67 | 0.50 | 0.00 | 0.55 | 0.00 |
Weighted supermatrix.
Group labels | Environmental | Land use | Operational | Social | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
SW | GW | FZ | TO | CS | RA | HD | LA | SA | AE | NS | |
Environmental | |||||||||||
SW | 0.00 | 0.17 | 0.24 | 0.23 | 0.36 | 0.13 | 0.37 | 0.23 | 0.16 | 0.00 | 0.00 |
GW | 0.31 | 0.00 | 0.15 | 0.00 | 0.11 | 0.00 | 0.00 | 0.08 | 0.00 | 0.00 | 0.00 |
FZ | 0.12 | 0.31 | 0.00 | 0.11 | 0.20 | 0.00 | 0.00 | 0.14 | 0.00 | 0.00 | 0.00 |
TO | 0.14 | 0.19 | 0.19 | 0.23 | 0.00 | 0.39 | 0.12 | 0.04 | 0.48 | 0.00 | 0.00 |
Land use | |||||||||||
CS | 0.04 | 0.00 | 0.14 | 0.00 | 0.08 | 0.18 | 0.02 | 0.09 | 0.00 | 0.18 | 0.00 |
RA | 0.11 | 0.00 | 0.00 | 0.14 | 0.15 | 0.00 | 0.10 | 0.03 | 0.00 | 0.36 | 0.54 |
Operational | |||||||||||
HD | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.17 | 0.00 | 0.14 | 0.00 | 0.11 | 0.14 |
LA | 0.09 | 0.22 | 0.19 | 0.14 | 0.00 | 0.03 | 0.14 | 0.09 | 0.36 | 0.05 | 0.03 |
SA | 0.19 | 0.11 | 0.10 | 0.14 | 0.00 | 0.00 | 0.14 | 0.05 | 0.00 | 0.00 | 0.00 |
Social | |||||||||||
AE | 0.00 | 0.00 | 0.00 | 0.00 | 0.08 | 0.04 | 0.04 | 0.06 | 0.00 | 0.15 | 0.30 |
NS | 0.00 | 0.00 | 0.00 | 0.00 | 0.03 | 0.04 | 0.08 | 0.06 | 0.00 | 0.15 | 0.00 |
Limit matrix.
Group labels | Environmental | Land use | Operational | Social | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
SW | GW | FZ | TO | CS | RA | HD | LA | SA | AE | NS | |
Environmental | |||||||||||
SW | 0.173 | 0.173 | 0.173 | 0.173 | 0.173 | 0.173 | 0.173 | 0.173 | 0.173 | 0.173 | 0.173 |
GW | 0.085 | 0.085 | 0.085 | 0.085 | 0.085 | 0.085 | 0.085 | 0.085 | 0.085 | 0.085 | 0.085 |
FZ | 0.099 | 0.099 | 0.099 | 0.099 | 0.099 | 0.099 | 0.099 | 0.099 | 0.099 | 0.099 | 0.099 |
TO | 0.188 | 0.188 | 0.188 | 0.188 | 0.188 | 0.188 | 0.188 | 0.188 | 0.188 | 0.188 | 0.188 |
Land use | |||||||||||
CS | 0.058 | 0.058 | 0.058 | 0.058 | 0.058 | 0.058 | 0.058 | 0.058 | 0.058 | 0.058 | 0.058 |
RA | 0.083 | 0.083 | 0.083 | 0.083 | 0.083 | 0.083 | 0.083 | 0.083 | 0.083 | 0.083 | 0.083 |
Operational | |||||||||||
HD | 0.038 | 0.038 | 0.038 | 0.038 | 0.038 | 0.038 | 0.038 | 0.038 | 0.038 | 0.038 | 0.038 |
LA | 0.135 | 0.135 | 0.135 | 0.135 | 0.135 | 0.135 | 0.135 | 0.135 | 0.135 | 0.135 | 0.135 |
SA | 0.091 | 0.091 | 0.091 | 0.091 | 0.091 | 0.091 | 0.091 | 0.091 | 0.091 | 0.091 | 0.091 |
Social | |||||||||||
AE | 0.029 | 0.029 | 0.029 | 0.029 | 0.029 | 0.029 | 0.029 | 0.029 | 0.029 | 0.029 | 0.029 |
NS | 0.021 | 0.021 | 0.021 | 0.021 | 0.021 | 0.021 | 0.021 | 0.021 | 0.021 | 0.021 | 0.021 |
The siting of undesirable facilities is a process characterized by uncertainty and complexity, as well as multiple and conflicting criteria. Determining the site evaluation criteria and constructing the dependence and connections among these factors is the key preliminary step in the siting process. Therefore, an appropriate hierarchical structure must be constructed for the evaluation criteria, and the expert groups must be determined. However, participation of all potential stakeholders in decision-making process is essential to justify and increase the decision acceptance and quality. Moreover, it minimizes the risk and avoids production of identical decision. Stakeholders grouping and interviewing are efficient way to collect their perceptions. Moreover, MRSS is a statistical tool that guarantees gathering unbiased representation of the study society, and thus it was used in this study.
Environmental criteria were assigned the highest priority (54.6%). Environmental effects have the highest complexity and represent the core of the mitigation measures. The second highest criterion was operational methods and techniques. These processes are pivotal in reducing the effects of a landfill. Social criteria were the least important because the social issues related to landfill sites can be minimized by proper management. Overall, land topology and distance from surface water were the most important subcriteria and have weights equal to 18.8% and 17.3%, respectively, whereas aesthetics and proximity to the nearest settlement have the lowest priorities of 2.9% and 2.2%, respectively. These results can be justified as the proposed site is a sanitary landfill with gas and leachate collection system; therefore, the main pollution threats are from the outside, namely, from rainwater. The risk of odor pollution is low because of the applied mitigation measures, that is, leachate and gas collection and buffering zones around the site. Furthermore, the landfill area lacks vegetation; therefore, the topology of the land primarily controls the water runoff and permeability, thus directly affecting soil erosion and surface and ground water.
Finally, this paper incorporated an MRSS and ANP to obtain a methodological framework with which to evaluate the landfill siting criteria. Compared with a traditional ANP, several additional benefits can be achieved using an MRSS-ANP model. First, this process can enhance handling of the vagueness and imprecision associated with the pairwise comparison process. Second benefit is addressing the interactions, interdependencies, and feedback among the decision evaluation criteria. Third, the combined approach can assist the decision makers to more confidently justify their decisions with minimum funds and expertise. This approach serves as a guide for applying the complex MCDM process to real-life and environmental problems in which the adequate participation of stakeholders and influence factors must be considered. This study represents a first attempt to combine statistical analysis with an ANP to prioritize landfill siting criteria, and further sensitivity analyses are suggested for future work.
For details see Tables
The authors declare that there is no conflict of interests regarding the publication of this paper.
The authors thank Universiti Kebangsaan Malaysia (UKM) and the Malaysian Ministry of Higher Education (MOHE) for funding through FRGS/1/2013/TK03/UKM/02/5.