Published at : 30 Dec 2018
Volume : IJtech Vol 9, No 8 (2018)
DOI : https://doi.org/10.14716/ijtech.v9i8.2754
|Junidah Abdul Shukor||School of Quantitative Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia|
|Mohd Faizal Omar||School of Quantitative Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia|
|Maznah Mat Kasim||School of Quantitative Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia|
|Mohd Hafiz Jamaludin||Faculty of Agro Based Industry, Universiti Malaysia Kelantan, 17600 Jeli, Kelantan, Malaysia|
|Mohd Azrul Naim||Kulliyyah of Science, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia|
Organic waste disposal in landfills has created various environmental issues, such as greenhouse gas emissions and leachate. Awareness of this issue has resulted in diverting landfill to compost. Thus, there is a need to develop an analytical tool to select the best composting technology. Therefore, this paper reviews a range of assessment steps designed to evaluate specific sustainability criteria (environmental, social, economic, and technical) for organic waste management to select the most suitable composting technology. Due to the complexity of conflicting criteria and alternatives in composting technology, a multi-criteria decision-making (MCDM) technique is suggested to ensure the quality of the decision-making process. As an additional benefit, the synthesis results via the MCDM tool will be more credible when seeking validation by stakeholders.
Composting; Composting criteria; Decision making; Organic waste
Organic waste or green waste can be defined as organic material that is easily biodegradable (Kadir et al., 2016). Organic material is derived from natural sources. Essentially, any residual kitchen waste (vegetable peelings, food, tea bags, and egg shells), agro-waste (food and beverage processing waste, dairy products, animal waste, and crops), grass clippings, dried leaves, and timber can degrade naturally (Hartono et al., 2015; Ng & Yusoff, 2015; Kadir et al., 2016). The process of degradation is performed by microbial (fungi, bacteria, actinomycetes, and protozoa) and invertebrate (insects and earthworm) organisms, which digest and break down the organic matter (Basri et al., 2005; Fauziah & Agamuthu, 2009; Kadir et al., 2016).
Due to the ability of organic waste to degrade naturally, dumping it into landfills is the most common waste disposal method. Unfortunately, various studies have indicated the undesirable environmental impacts of using landfills to manage the disposal of organic waste (Manfredi et al., 2009; Fauziah & Agamuthu, 2010). Leachate contamination in surface and groundwater, infestation by pests, and the emission of greenhouse gases are some effects of organic waste disposed into landfills (Manfredi et al., 2009; Fauziah & Agamuthu, 2010). These effects contribute to global warming and environmental pollution.
The awareness of environmental issues has encouraged society to find other alternatives to manage the organic waste disposal process instead of landfills. The composting process can be used for biological decomposition, and this technology has the potential to manage organic waste, transform it into valuable agricultural products, and minimize pollution (Basri et al., 2005; Hartono et al., 2015; Kadir et al., 2016). However, several important aspects need to be considered before implement composting technology. These include sources of waste feedstock in terms of quantity (small scale like home composting, medium scale, or large scale composting) and quality (moisture content and nutrient content) (Basri et al., 2005; Fauziah & Agamuthu, 2009; Zabaleta et al., 2014; Hartono et al., 2015; Ng & Yusoff, 2015), technology set-up in terms of site location and area required (Basri et al., 2005; Zabaleta et al., 2014), required operational skill, and capital and operating costs (Basri et al., 2005; Malakahmad et al., 2017). Besides these, the quality of the compost end-product also needs to be taken into consideration (Zabaleta et al., 2014). Most of these aspects or criteria vary with composting technology. Composting can be performed using different methods or systems, such as the static pile system (Ilham & Esa, 2017; Lim et al., 2017), windrow system (Zaini et al., 2015; Ilham & Esa, 2017), in-vessel system (Zaini et al., 2015; Ilham & Esa, 2017; Malakahmad et al., 2017), and vermicomposting system (Fauziah & Agamuthu, 2009).
Therefore, selecting the best composting technology is not a straightforward process. Specific decisions must be made based on these various criteria. The decision maker needs to understand the assessment steps required to make the best decision and to identify the specific weaknesses and strengths of that decision. This procedure can decrease the probability of mistakes and risk during the process planning and execution phases. Additionally, assessment activities will help the decision maker to evaluate each technology proposed so that the optimal alternative can be identified (Zurbrügg et al., 2014; Abdullah, 2015).
MCDM can be applied in any discipline to make effective and accurate decisions based on various evaluation criteria. This study focused on how the MCDM approach can be used to choose the best composting technology for organic waste. However, the assessment step (basic step as mention in section 2.3, the four steps commonly used: (1) Determine of work objective; (2) Define theoretical framework; (3) Determine relevant of criteria, sub-criteria, and alternative or possible solution; and (4) Data collection and data processing) is fundamental not specifically for technology selection, but rather expansion knowledge of decision maker system. Using the MCDM system can result in improved outcomes and more comprehensive support for the decision makers. As an additional benefit, the synthesis results made using MCDM will be more convincing and valid to the stakeholders.
The authors gratefully acknowledge the support and assistance from UUM Collaboration 1+3 Research Grant (S/O Code: 14036) for this research and the cooperation of research teams from IIUM, UMK, and D&Y Coldchain Venture. M.H.J was supported by Niche Research Grant Scheme from Ministry of Higher Education of Malaysia (grant number: R/NRGS/A07.00/00413A/004/2014/000150) and M.A.N was supported by Research Matching Scheme of IIUM (grant number: RMGS17-004-0030).
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