Reshaping WEEE management in Australia: An investigation on the untapped WEEE products

Journal Pre-proof Reshaping WEEE management in Australia: An investigation on the untapped WEEE products Md Tasbirul Islam, Nazmul Huda PII:

S0959-6526(19)34366-5

DOI:

https://doi.org/10.1016/j.jclepro.2019.119496

Reference:

JCLP 119496

To appear in:

Journal of Cleaner Production

Received Date: 12 June 2019 Revised Date:

26 November 2019

Accepted Date: 27 November 2019

Please cite this article as: Islam MT, Huda N, Reshaping WEEE management in Australia: An investigation on the untapped WEEE products, Journal of Cleaner Production (2020), doi: https:// doi.org/10.1016/j.jclepro.2019.119496. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

CRediT author statement

Md Tasbirul Islam: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Writing - Original Draft

Nazmul Huda: Validation, Writing - Review & Editing, Supervision, Visualization, Project administration

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Ms. Ref. No.: JCLEPRO-D-19-08667R4

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Reshaping WEEE management in Australia: an investigation on the untapped WEEE products

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Md Tasbirul Islama*, Nazmul Hudaa*

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a

School of Engineering, Macquarie University, NSW 2109, Australia

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Highlights

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• • • • •

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Abstract

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In Australia, the National Television and Computer Recycling Scheme (NTCRS) considers only waste televisions, computers, printers, and IT peripherals as e-waste. This study utilizes a combined Delphi-AHP approach to identify potential candidate products that are outside of the scheme. Besides, implementing the traditional AHP method, this study employed an AHP-rating model to minimize computation time in the approach. The results of the study reveal that seven evaluation criteria are crucial for product selection. From 47 initially selected products, 22 products are identified as priority products. Sensitivity analysis was performed based on the different weighting of the evaluation criteria. Potential future activities that need to be performed by the policymakers on the issue are also discussed in the light of the circular economy and environmental protection. This study will also help academics performing the approach, and subsequently, the AHP rating model for selecting/prioritizing alternatives that focused on multi-criteria decision-making problems.

A combined Delphi-AHP approach was used for product prioritization An AHP rating model was utilized for quantitative weighting for a product Out of 47 products, 22 priority products were identified for Australia A product-centric material characterization mapping has been performed Sensitivity analysis was conducted to observe the variability of products’ ranking

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Keywords: Circular economy; Delphi-AHP approach; AHP rating model; Product-centric material characterization; Priority products; e-waste

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*Corresponding author: E-mail: [email protected] (N. [email protected]; [email protected] (M. T. Islam)

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Huda);

md-

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1. Introduction

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Modern households are packed with electrical and electronic equipment (EEE), making human life more comfortable and convenient. The technological revolution, inventing a variety of products coupled with insatiable customer demand for new and ultra-high-tech features in products and enhanced purchasing power; triggered large-scale consumption of EEE all over the world. However, the dark side of such a proliferated pattern of EEE usage results in a massive amount of electronic waste (e-waste) generation. The waste stream contains a significant amount of toxic elements such as lead (Pb), cadmium (Cd), mercury (Hg), polychlorinated biphenyls (PCBs), and brominated flame retardants (Islam and Huda, 2019b, Messmann et al., 2019, Song and Li, 2015). Besides, these elements, if e-waste is improperly open burnt and indiscriminately acid leached (via informal crude recycling process), additional toxic pollutants such as polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), Polybrominated dibenzo-p-dioxins and dibenzofurans (PBDD/Fs), polycyclic aromatic hydrocarbons (PAHs), and heavy metals are emitted to air and soil which are detrimental to human health and environment (Tao et al., 2015, Zeng et al., 2017). Developing countries such as China, India, and Nigeria are facing tremendous challenges in managing e-waste due to illegal import to the nations, and widespread informal sector recycling (Orlins and Guan, 2016, Shumon et al., 2014). The temporal trend of PCB concentrations at an abandoned e-waste site in South China showed that mean PCB concentration (in a bioindicator) increased by eleven times within six years’ period (Wu et al., 2019). Uncontrolled processing of e-waste also causing severe damage to vegetation and harvesting soil in the region (Luo et al., 2011). The high concentration of Pb and PAHs were traced in the urine of informal sector e-waste recycling workers in Ghana (Asante et al., 2012, Feldt et al., 2014). Similar toxic metal contamination (by Pb, Cd, and Cr) was found in children’s blood (Guo et al., 2010, Xu et al., 2012). High-level of Hg, Pb, and Bi were also found in soil, and in workers’ hair; who were working at the informal e-waste recycling sites in India. All these pieces of evidence conclude that e-waste contains a substantial amount of toxic metals and contaminants, and crude recycling and inappropriate disposal of e-waste lead to environmental pollution and human health damage (Ha et al., 2009). Dumping of ewaste and associated items (such as batteries) in landfills also creates significant burdens on the environment and a long-term threat to human health (Sayilgan et al., 2009).

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The responsible authorities in the waste-management sector found e-waste a complex waste stream that is challenging to manage. This situation is valid for both developing and developed countries (Islam et al., 2016, Islam and Huda, 2018a). According to the United Nations University (UNU) study, global waste electrical and electronic equipment (WEEE) generation reached 44.7 million metric tonnes (Mt) in the year 2016 (Balde et al., 2017). It is expected that, by the year 2021, e-waste generation will reach 52.2 Mt (Balde et al., 2017, Forti et al., 2018). On the other hand, per capita, e-waste generation in the Oceania region is one of the highest in the world (Morris and Metternicht, 2016). Australia is the largest and most developed country in the region with a high EEE penetration rate; for instance, in 2014, EEE sales were 35 kg per capita (Golev et al., 2016). Islam and Huda (2019a) estimated that in the year 2014, e-waste generation was 788 kilotons (kt), where per capita e-waste generation was 33 kg/person in Australia. The amount is almost 1.7 times higher than the per capita e-waste generation in the European Union (EU) member states (excluding Cyprus) in the same year. Ylä-Mella and Román (2019) mentioned that in 2014, per capita e-waste Page 2 of 44

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generation was 18.9 kg in the EU. From the year 2018 to 2047, the annual projected growth rate of e-waste generation in Australia is estimated to be around 3% Islam and Huda (2019a). Nevertheless, the UNU study also mentioned that only 6% of the e-waste that was collected and recycled in the region in 2016 were documented (Balde et al., 2017). The statement indicates that either bulk amount of e-waste is out-of-scope (under the current regulation) or comprehensive national statistics on the e-waste generation is absent. According to Islam and Huda (2019a), product scope expansion is the most urgent task for the current Australian ewaste management system.

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As mentioned, due to the variety of EEE consumption, a diverse range of products is found in the present e-waste stream (Islam and Huda, 2020). According to Forti et al. (2018), there are approximately 900 different EEE items available in the global markets. EU WEEE Directive (Directive, 2012a) categorized these products into six categories with specific targets for collection and recycling rate. Table 1 shows the product categories considered under the recast of the EU WEEE Directive 2012 with the targets. Member countries in the EU collect and recycle e-waste products under these categories and report back to the European Commission assessing the achievement of the goals (Ibanescu et al., 2018). The Extended Producer Responsibility (EPR) is the key strategy implemented in the Directive, which makes the manufacturers responsible for the entire product lifecycle. Furthermore, the action plan of achieving a circular economy (CE) has become a strategic mandate within the EU region recently that aims to gain better resource efficiency and sustainability in the wastemanagement sector. According to Lieder and Rashid (2016), CE is [a] closed-loop material flow in the whole economic system […] in association with the so-called 3R principles […] Taking into account economic aspects CE […] minimizes matter […] without restricting economic growth.”

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Table 1. WEEE product categories with targets of the recast of EU WEEE Directive 2012/19/EU, adapted from (Directive, 2012b, Islam and Huda, 2018b, StEP, 2019c) Category no.

Category

1 Temperatureexchange equipment (TEE) 2 Screens, monitors, equip. with surface screens >100 cm2 3 Lamps

4 Large equipment (LE)

Sample products

Refrigerators, freezers, air conditioners, heat pumps

Recovered (%)

Prepared for re-use or recycled (%) 85 80

Television sets, monitors, laptops, notebooks, and tablets

80

70

Fluorescent lamps, highintensity-discharge lamps, and LED lamps Washing machines, clothes dryers, dish-washing machines, electric stoves, large printing machines, copying equipment, and photovoltaic

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80

85

80

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panels 5 Small equipment Vacuum cleaners, microwave (SE) ovens, ventilation equipment, toasters, electric kettles, electric shavers, scales, calculators, radio sets, video cameras, electrical and electronic toys, small electrical and electronic tools, small medical devices, small monitoring and control instruments 6 Small IT and Mobile phones, Global telecommunication Positioning Systems (GPS), equipment (Small pocket calculators, routers, IT) personal computers, printers, telephones

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75

55

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Note: the products that are in the bold and italic form are considered in the current e-waste management system in Australia. A detailed description of the system will be discussed in Section 2.

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Unlike the EU, the Australian e-waste management system currently recognizes products only from categories 2 and 6, as shown in Table 1 (Section 2 will discuss in detail), with no policy indication on how to manage other electronic and electrical products. As of 30 June 2017, the Department of the Environment and Energy (DOEE), Government of Australia, published a master product list mentioning that batteries, photovoltaic systems (solar PV panels), and general electrical and electronic products as the essential items in the context (DOEE, 2018a). A recent study by Mahmoudi et al. (2019) and Salim et al. (2019) showed that waste solar PV panels are one of the significant e-waste streams in Australia. However, there are no specific decision-making criteria evaluated, so far, by which it can be understood what other products should be included in the future e-waste management system in the country. Thus, this is exclusively a multi-criteria decision-making (MCDM) problem which can be solved by available methods. This study employs a combined Delphi-Analytic Hierarchy process (AHP) approach to identify the critical end-of-life (EoL) EEE products for future inclusion. The approach and subsequent results will help policymakers in e-waste product scope expansion. This issue is particularly challenging due to the lack of precise and objective-oriented decision-making procedures, and evaluation criteria agreed by wastemanagement professionals and policymakers (Kim et al., 2013).

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The Delphi method was employed, identifying critical evaluation criteria that a product should have for future inclusion. Later, using the AHP method with an additional AHP-rating model, the critical criteria were weighted along with a rated value for individual products to develop a final list of priority products. In this study, priority products are defined as those products that are currently outside of the product scope of the e-waste management system in Australia. These products are also characterized by the presence of valuable (base and precious) metals; at the same time have considerable risk if disposed of inappropriately due to the presence of hazardous and toxic elements such as Pb, Cr, Cd, Hg. The research contributions of this article are:

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Despite the widespread use of Delphi method that engages expert to provide their opinion on a specific issue identifying key criteria (for a system or process) (Venkatesh et al., 2017) and AHP as the process for quantitative assessment of the criteria (weighting the criteria by pair-wise comparison) (Yurdakul* and Ic, 2005), in most the cases, these methods are implemented separately. In this study, a combined Delphi-AHP approach was applied to finalize a priority product list for future inclusion in the e-waste management system for Australia, and to the best of the authors’ knowledge this has not been done before (Section 5 for data and methodology, and Section 6 for results). A product-centric material dataset has been developed by which quantitative assessments of the inherent metal content were investigated for the individual product (Section 5.2). This study will help policymakers in making decisions on what other products should be considered in the system as well as providing necessary directions into the future. This study will also be beneficial for academics utilizing methodological procedures of the methods in a combined fashion and particularly, implementing the AHP-rating model in the e-waste management-related decision-making problems that fall under the MCDM (Section 6 and Section 8).

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2. E-waste management in Australia

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As of 2017, the population of Australia reached 24.6 million (ABS, 2017), and the country is a net importer of EEE (Golev et al., 2016). EEE imports in various categories have increased tremendously in the past decades and will continue to grow in the future as the population is projected to increase (Islam and Huda, 2019a). Fig. 1 shows the EEE import (or sales) of various TV and information technology (IT) equipment in the country from the year 2000 to 2017 by weight (in tons). The data on the average weight of the equipment was taken from Islam and Huda (2019a). Analysis of historical product sales is crucial for estimating future e-waste generation using various methods, such as Weibull distribution based sales-stocklifespan model, consumption and use (C&U) (Islam and Huda, 2019b). Desktop computer sales were consistent over the years, and starting from 2007, sales of printers, LCD monitors, and LCD TV increased significantly. On the other hand, after the introduction of flat-paneldisplay (FPD) television sets and monitors (under “screen” category as per Table 1), CRT monitors and television sales declined dramatically due to the technological breakthroughs (from 2000 to 2006). This trend is very similar to other parts of the world, and this is considered as a global phenomenon (Gusukuma and Kahhat, 2018).

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Fig. 1. NTCRS and mobile-phone imports in Australia (Golev et al., 2016, UNComtrade, 2019)

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Besides, imports of mobile phones, under the category of small IT, showed an exponential trend. Current household possession of mobile phones in Australia is approximately 6.5 (Golev et al., 2016). The waste mobile phones are managed by a voluntary scheme named Mobile Muster in Australia. In 2018, the program collected and recycled 90 tonnes of waste mobile phones with a 99% resource recovery rate. Since 1998, the scheme recycled over 1412 tonnes of mobile phones (MobileMuster, 2018).

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As of 2011, the Product Stewardship Act was implemented in Australia. As part of the Act, the National Television and Computer Recycling Scheme (NTCRS) was initiated in the year 2012. Television, IT equipment such as computers (personal and laptop computers and all cables), tablets, notebooks and palmtops, computer monitors and parts (e.g. internal hard drives and CD drives), computer peripherals and printing devices (printers, faxes, scanners and multi-functional devices) are included as e-waste under the scheme (DOEE, 2018b). Ewaste products under the NTCRS scheme (later called as NTCRS-products) are managed via multiple actors – such as the liable parties (importers/manufacturers that fund the system), coregulatory arrangements (CRAs) who make necessary arrangements for collecting and recycling activities. Finally, the recognized recyclers (both first-stage recyclers, who are based locally, and overseas recyclers for downstream recycling) (Dias et al., 2018). The primary objects of this scheme are: 1) diversion of e-waste from landfill because of the presence of hazardous materials in the products; 2) introducing safe, scientific and environmentally sound methods for extracting more recoverable and reusable materials from the e-waste stream, and finally, 3) providing an industry-funded recycling service which is “free-of-charge” for households and small businesses (DOEE, 2015). In the 2015-16 financial year, the Department of Environment and Energy, Government of Australia, set the recycling target to 50% (with 90% material recovery rate), which is proposed to increase by 80% in the year 2026-27 (DOEE, 2015). After the inception of the scheme in 2012, CRAs diverted a significant amount of e-waste from landfills and recycled a considerable amount of e-waste. Page 6 of 44

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Fig. 2 shows the amount of collected and recycled e-waste by various CRAs from 2013 to 2017.

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Fig. 2. E-waste collection and recycling quantities (in tonnes) of various CRAs from 2017 to 2013 (ANZRP, 2014, 2015, 2016, 2017a, DHL, 205, 2014, E-Waste, 2014, Ecycle, 2014, 2015, 2016, 2018, EPSA, 2014, 2015, 2018, MRI, 2016, 2018)

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In 2013 and 2014, the CRAs published reports mentioning the amount of waste TV and computer collected and recycled separately, which were missing in the subsequent years’ report. However, these products constitute less than 10% of the total e-waste generation in Australia (ABC, 2018). If trade statistics are observed for other types of electronic products, it is found that almost all possible types of EEE are imported into the country, and the per capita possession of EEE reached approximately 62 kg in the year 2014 (Islam and Huda, 2019a). Table S1 in the supplementary information (SI) of this article shows the EEE import (or sales) of various types of EEE, which are currently outside of the scheme. In general, ewaste from TEE (category 1) and LE (category 4) products are considered as scrap metals which are recycled by scrap-metal recyclers working as “for-profit” and “non-profit” (social) business enterprises (Lane et al., 2015). Islam and Huda (2020) called these products as “unregulated” products. Again, there is no national-level statistics available on the collected and recycled amount of unregulated products, for instance, the washing machine. At the local government council’s collection points (other than the community recycling centers), a customer needs to pay approximately $25 per unit for disposing of their TEE and LE products.

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In most cases, during the council’s collection day, a large amount of EEE (especially e-waste items under the category of LE, TEE, and SE) are disposed of by the households directly goes to the landfills without further separation and recycling. Some councils collect SE (category 5) items at their collection facilities (details given in Table S2 in the SI), but this amount is Page 7 of 44

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insignificant. This practice eventually results in a loss of resources and creates an overall system inefficiencies (Islam et al., 2018). On the other hand, there is a lack of adequate ewaste volume for the CRAs and the recyclers in Australia, which increases the per-unit cost of recycling (DOEE, 2018b). The stakeholders often urge for expanding the product scope for increased economies of scale, and avoiding customer confusion on what can be recycled and what cannot (ANZRP, 2017c). Overall, the effectiveness of the e-waste management policy in Australia was found inadequate (Morris and Metternicht, 2016). From this aspect, there is an urgent need to investigate what other products can be included in the e-waste management system in the future. The current study aims at developing a priority product list those are currently outside of the scheme. As the first step towards that attempt, analyzing global and local scenarios would be beneficial. In the next section (Section 3), global experience in expanding the product scope is investigated and discussed in detail. After analyzing the global experience, how the lesson learned can be utilized in the context of Australia is detailed in Section 4.

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3. Global effort in product scope expansion for better e-waste management

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In order to understand the global effort in product scope expansion for e-waste management, four different countries were taken into consideration: China, Japan, South Korea, and Denmark. The first three countries include specific products on a rolling basis, meaning that not all products were included in the first place when a key piece of legislation was enacted. On the contrary, in the EU WEEE Directive, specific product categorization was made by the EU Commission (Directive, 2012b). Denmark is one of the countries in the EU that follows the Directive (Zaman, 2013). Note that NTCRS products are transferred to China, South Korea, and Japan for the downstream recycling process under the scheme as well (ANZRP, 2017a, b, Ecycle, 2018, EPSA, 2018, MRI, 2018).

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In 2011, China introduced the “Management Regulation on the recycling of Waste Electrical and Electronic Products” regulation under which television (TV) sets, refrigerators, washing machines, air conditioners, and personal computer (PC) were considered as e-waste. In 2015, the regulation was amended, and under a new catalogue, products such as range hoods, electric water heaters, gas water heaters, printers, copiers, fax machines, monitors, mobile phones and single-machine telephones were added in addition to the previous items (Zeng et al., 2016).

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In Japan, under the “Home Appliance Recycling Act” (enacted in June 1998) (StEP, 2019a), air conditioners, TV, refrigerators, freezers, washing machines, and clothes dryers were included (Yagai, 2015). The legislation focused on large electrical items, which are bulky (Oguchi et al., 2011). Later, in August 2012, Small Electrical and Electronic Equipment Recycling Act was introduced in which PC was included. In 2013, this law was changed to Promotion of Recycling of Small Waste Electrical and Electronic Equipment (PRSWEEE) as a promotion-type system aiming to recover more resources from small-sized WEEE, for example, small rechargeable batteries (Sugimura and Murakami, 2016). Research conducted by Oguchi et al. (2011) and Oguchi et al. (2013) addressed that in addition to the products mentioned above, in the future e-waste management system in Japan other products such as printers, fax machines, video games, notebook computers, and audio-video equipment should be included. These products were identified as the most significant e-waste products (outside Page 8 of 44

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of the system boundary), as they contain both precious-metals and the presence of toxic elements.

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South Korea is one of the strong economies in the Asia-Pacific region, where major EEE manufacturers are located. Under the regulation of Resource Recycling of Electrical and Electronic Equipment and Vehicles enforced by the Korea Ministry of Environment (MOE), ten products were initially included namely, refrigerators, washing machines, TVs, air conditioners, computers, audio equipment, mobile phones, copying machines, fax machines, and printers. A study by Kim et al. (2008) identified vacuum cleaners, electric mixers, electric fans, electric rice cookers, telephones, humidifiers, microwave ovens, and coffee makers are needed to be considered based-on household consumption and disposal patterns in the Korean e-waste management system.

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Unlike these countries, where products are gradually included in the e-waste management system, Denmark in Europe is one of the countries that are better positioned both in terms of products considered in the system as well as mandatory collection and recycling targets (under the EU WEEE Directive). The Directive aims to reduce the environmental effects from e-waste generation as well as envisions maximizing resource utilization by re-use, recycling, and other forms of recovery from the WEEE. According to Cole et al. (2019), the Directive “offered the potential to improve waste collection and recycling infrastructure and drive environmental benefits in terms of resource efficiency and reduced carbon emissions”. Mitigating environmental damage (by safe disposal of e-waste) is the most critical criterion of the Directive (Directive, 2012b). On 27 January 2003, the EU WEEE Directive (2002/96/EC) was enacted in which an exhaustive product list with ten (10) categories (in the Annex 1B) was prescribed under the broad definition of any appliances that work with electricity (Khetriwal et al., 2011, Wang et al., 2012). In this case, no proper grouping by function and EoL characteristics were taken into consideration, and this was a productoriented categorization effort (Council, 2009). Although establishing the take-back mechanism by the producer, setting weight-based recycling and collection targets, and developing a framework for monitoring and financing of the entire reverse supply chain were the essential requirements stipulated in the Directive for the member states (Khetriwal et al., 2011). After a series of scientific consultations with various research entities such as UNU (with a review on the Directive) (Huisman, 2008) and analyzing real-world practice in the ewaste collection and recycling industry in the EU, a more collection and treatment-oriented product categorization had been made that consisted of six (6) categories. The categorization is mentioned in the Directive 2012/19/EU (Directive, 2012a), and the collection and recycling target set under the six categories came in to force on 15 August 2018. Three fundamental criteria were implemented in this revised categorization: “1) product type (functionality and industry sector); 2) waste management (return stream characteristics) and; 3) legislative relevancy (material composition, hazardous and valuable content)” (Wang et al., 2012). Despite the substantial changes evolved in the product categorization in the Directive, the presence of both toxic hazardous and valuable metals was one of the fundamental aspects introducing the Directive.

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Parajuly and Wenzel (2017a) conducted a field study in the Danish e-waste collection points. They found that electric kettles, irons, coffee machines, scales, food mixers, hairdryers, toasters, sandwich makers, window and glass vacuum cleaners, shavers, electric fans, DVDplayers, blenders, portable vacuum cleaners, screwdrivers, audio systems, portable audio Page 9 of 44

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systems, TV receiver/set-top boxes, VHS players, mice, modems, docking stations, microwave ovens, routers,, heaters, , speakers, vacuum cleaners were the major products under SE category disposed of by the local residents.

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4. Comparison of e-waste management in Australia with global efforts

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Golev and Corder (2017) conducted an e-waste quantification study, in which they investigated the e-waste density in Australia by addressing the fact that the country shares a similar pattern of GDP per capita, purchasing-power-parity and e-waste generation per capita like European countries. This is furthered confirmed by global e-waste map dataset prepared by UNU-StEP Initiative (StEP, 2019b). As mentioned earlier, at present, under the NTCRS, only computers, laptops, tablets, notebooks, palmtops, monitors, IT peripherals (mice, keyboards, web cameras, USBs, and modems), TV, printers, faxes, scanners, and multifunction devices (on a co-regulatory basis) and mobile phones (on voluntary basis) are collected and recycled in Australia. Other products are neither considered under the scheme nor do have specific collection options. A recent study by Islam and Huda (2019a) estimated that the total material value encased in e-waste products that were outside of NTCRS reached 4.7 billion US$ in the year 2017. Furthermore, the gap between revenue potential between NTCRS and unregulated products (products outside of NTCRS) reached approximately 1.2 billion US$ in the same year. Although minimal data can be found on NTCRS and mobilephones-related e-waste generation, for the case of LE, SE, and TEE product categories, there are hardly any official statistics found from publicly available sources. In such a scenario, comparing the products that are collected at the CA sites in Denmark provides a basis to assume which e-waste items are frequently disposed of and consider them to be similar for Australia, mainly SE product categories. The selection of the Asian countries and their ongoing effort in including products in the e-waste management system is rational from the viewpoint of continuous inclusion and improvement, which is also a lesson for Australia. These countries started their system with relatively bulky items, as discussed above. Besides the global experience, local collection points in the Greater Sydney metropolitan areas were visited to identify the products that are currently being disposed of by households other than the NTCRS-products and mobile phones. Fig. 3 shows that; besides computers and other IT equipment, stereo, and music systems and DVD players are also being disposed of at the points. This evidence also ensures that these products share the same characteristics as NTCRS-products, and CRAs are accepting these items (unofficially) at the collection points. This phenomenon also indirectly pointed out to the fact that local recyclers do have the necessary logistics and technological capability recycling unregulated items. However, it was also found that several local-government councils only consider NTCRS products.

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Fig. 3. Non-NTCRS products (A) stereo and music systems and (B) DVD players, disposed of at a local collection point by Ryde council, NSW (Source: Author’s field visit)

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Some of the councils in the state of New South Wales (NSW) collect unregulated products at their collection points. Table S2 (in the SI) shows a list of councils that collect the products. This comprehensive list is created by conducting interviews with waste managers and/or resource-recovery officers and, in some cases, visiting the collection points and/or contacting the officers via email. The NSW councils (in total 128 councils) are divided into three major categories: Greater Sydney metropolitan (GSM), Sydney surrounds (SS), and rural and regional areas (RRA). Out of 30 councils of GSM, only nine councils collect products outside the NTCRS. For RRA and SS councils, this number is 6 out of 94 and 2 out of 4, respectively. However, on e-waste event collection days, this is different from the (permanent) collection points where it is seen that in many cases, customers can dispose of any e-waste regardless of the size and category.

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5. Data and methodology

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In this study, several steps have been implemented for collecting data and analyze the results as described below:

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5.1 Product selection for analysis

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First, which products should be included in the future e-waste management system in Australia was determined. For this, global efforts (explained in Section 3) and local experience (as seen in Section 4) are assessed for creating a preliminary product list. A literature survey (for global experience and lessons learned), field visits to local collection points and community recycling centers (CRCs) (shown above), interviews with localcouncil resource-recovery officers (for local knowledge) were conducted to understand the current consumption and disposal patterns of specific products. A preliminary list of products was developed based on the understanding of product import, consumption, and disposal patterns.

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5.2 Analysis of product characteristics

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As product prioritization is the primary focus of this study, extensive characterization of product is essential to understand which products contain valuable materials as well as which Page 11 of 44

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carry toxic elements. In order to initiate the process, the selected products (assessment done in the previous stage as Section 5.1) were first categorized into six different categories as per the EU WEEE Directive. Categorization of products (large vs. small) is an essential part of overall system-level improvement, as consumer behavior and their willingness to recycle vary with the size of the products (EIU, 2015). Note that the category “screen” is excluded in the categorization as these products are already included in the NTCRS. This exclusion was also done for some products (e.g., routers, personal computers, printers) under the “small IT equipment” category, as seen in Table 1. Later, the material composition of each product was analyzed based on an extensive literature survey, and a material composition list was developed based on common metals, toxic metals, precious metals, and less-common metals. Table S3 in the SI shows the complete list of the material content. This provides a preliminary understanding of the toxic and valuable metal content of a product. Lifespan data of the products were also analyzed, as some of the products have a shorter life (e.g., SE items) than the others (e.g., TEE and LE categories). Based on an extensive literature survey of 143 articles, a lifespan data set was developed for this study. After compiling the data on the lifespan of various products, the average lifespan of the products was calculated based on a median value. Fig. S1 in the SI shows the final lifespan of the items. Import statistics from the UNCOMTRADE database were also analyzed (described in Section 2) to assess which products are more imported than others (in units rather than in weights). To achieve greater economic efficiency in the recycling material-recovery process, a “per unit” basis of assessment is often preferable for recycling process cost estimation (EIU, 2015).

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5.3 The Delphi method

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The Delphi method was first postulated by Olaf Helmer and Norman Dalkey of the RAND corporation, forecasting the impact of technology on warfare (Twin, 2019). It is particularly helpful in a situation of developing priorities, policies, and forecasts about the future. When a research problem does not lend itself to precise analytical techniques, the Delphi method is useful (Keeney et al., 2011). The method is a widely implemented practical tool obtaining opinions on an issue that needs to be addressed at present for which no information (or consensus) available on the topic (Venkatesh et al., 2017). The consensus on multifaceted and complicated issues is generally derived from a team of experts in a specific field(s), and the method follows a systematic procedure arriving at the consensus on some evaluation criteria (Grisham, 2009). In the waste management research area, Estay-Ossandon et al. (2018) used the method to improve municipal solid-waste management planning and forecasting. Veiga et al. (2016) utilized it to develop sustainability indicators for solid-waste management. Zakaria et al. (2013) implemented the technique for identifying selection criteria for establishing a hazardous-waste disposal facility. Although there is widespread use of the Delphi method in decision-making studies, there is a lack of universal guidelines using the method (Keeney et al., 2011).

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In a Delphi method, the group of experts answers questionnaires on the specific topic, which is generally conducted in two or more rounds (Giunipero et al., 2012). In this study, conventional two rounds of the expert survey were implemented, and the research methodology proposed by Keeney et al. (2011) for the Delphi method was utilized. After each round, a facilitator was involved in circulating experts’ opinions with an anonymous Page 12 of 44

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summary, and reason for selecting judgments. For this study, in the first expert survey, an open-ended question was asked to identify which criteria should be selected for a product if it would introduce in the future e-waste management system in Australia. After the first round of the expert survey, a preliminary list of criteria was obtained. For the research purposes, in this study, to summarize the initial responses (identified criteria) from the experts, unique criteria/factors were selected using an affinity diagram. The second round of the expert survey was performed as part of the Delphi method. In the survey, the experts were encouraged to revise their opinion based on the opinions received from other experts on the criteria. Additional quantitative assessment was carried out as per methodology proposed by Keeney et al. (2011) in order to identify the level of consensus on a particular criterion, which made the overall procedure more robust and accurate.

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At the end of the second expert survey, besides reviewing the opinions on the criteria, experts were also asked to rank the criteria in a rating scale (in a semantic differential scale where 1 was set for least important factor and 9 being the most important). The consensus was assessed for items with an Interquartile range (IQR). If a criterion reached with a value of IQR≤1.00 on the scale, that represented the consensus on a specific criterion (Nast et al., 2016). In this process, the final evaluation criteria were selected that were used for the subsequent AHP method (described in Section 5.4). For estimating the IQR, the interquartile function (QUARTILE.EXC) of MS Excel was utilized in the analysis. Finally, the relationship of the IQR and the mean (from the scaled responses) was found for the essential criteria. In general, when the mean is high for a criterion, the IQR value reaches close to 1.

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Two crucial aspects are crucial for a Delphi study, 1) the number of experts (participants’ size), those participating in the study, and 2) the quality or level of expertise of the experts who provided the final list of criteria or factors that need to be known.

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According to Skulmoski et al. (2007) mentioned in Keeney et al. (2011), if the sample (of experts) is homogeneous (from the same industry/area), then generally, the number of experts in a Delphi study varies in between 10 and 15 participants. However, this number increases with the complexity and diversity of an issue/problem. On the other hand, in a broader context, Akins et al. (2005) stated that the number of experts in a Delphi study found in the published articles varied from 10 to 100. In general, the size of a decision-making group should not be large enough, and a minimum of 5 to a maximum of about 50 is ideal (Robbins, 1994). Keeney et al. (2011) found that there were also numerous articles published where the number of experts in the method consisted of less than ten experts. For example, Hsu et al. (2010) employed nine experts from the academic community in order to evaluate technology selection for waste lubricant recycling. Malone et al. (2004) considered opinions from 5 experts exploring drug interactions in ambulatory pharmacy settings. Hsu et al. (2008) used the Delphi method, where six experts’ opinions were utilized evaluating the selection criteria for medical waste disposal firms. A Delphi study was conducted with seven experts by dos Muchangos et al. (2015) in order to analyze the structural barriers to municipal solid waste management policy planning in Mozambique. Giunipero et al. (2012) employed three experts (in the first phase of a Delphi study) identifying significant barriers to achieving sustainability in the field of purchasing and supply chain management. Nevertheless, Dalkey and Helmer (1963) argued that statistical emphasis on the size of an expert panel should not be stressed on a Delphi method. Instead of the sample size (number of experts in a panel),

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capability, knowledge, professional qualifications and relevant experience of the experts in the field are the most significant issues for expert panel selection (Loo, 2002).

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This study aimed to invite experts from different areas of expertise related to the e-waste management system in Australia. In this study, a total of eight (8) experts from the local government authority, recycling industry, academia, and CRAs participated, giving their opinions on evaluation criteria in order to develop a priority list of products that need to be considered for future e-waste management and recycling in Australia. Table 2 shows the profiles of the experts who participated in the Delphi method. As per the requests of the participants, their names and affiliations are kept confidential.

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Table 2. Participants’ profile in the Delphi method Industry sector

Number of experts

Academics conducting research on e-waste management, circular economy, urban mining, and resource conservation Waste education officers/resource recovery officers from local government councils located at New South Wales (NSW) Officers responsible for e-waste collection and recycling at co-regulatory arrangements (CRAs) E-waste recyclers located in the state of New South Wales (NSW) Total

Year of experience in the field 2 More than 10 years 2

More than 8 years

2

More than 5 years More than 5 years

2 8

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5.4 AHP method

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Subsequently, when several evaluation criteria are found on an issue, these factors can be quantitatively assessed based on various MCDM models. In a decision-making process, when multiple complex factors need to be considered for several alternatives, AHP is particularly useful and can divide the decision-making process into several hierarchy levels by using pairwise comparison at each level based on expert opinions (Saaty, 2005). Under the MCDM models, the use of the AHP in recent literature has increased quite dramatically. Kumar and Dixit (2018) investigated critical barriers to the e-waste management system in India. On the other hand, Wang et al. (2019) established an evaluation system of a partial-disassembly line to reduce environmental impacts and save natural resources. Banar et al. (2014) utilized the AHP method for selecting sites for a recycling plant in Turkey.

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Conceptually, when individual performance indicators are to be combined into one key performance indicator (KPI), it is possible to give each indicator a different weight. For this, Page 14 of 44

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a mathematical method can be applied known as AHP. The method is one of the powerful tools under MCDM models found by Kiddee et al. (2013). In general, class analysis is done in AHP, as the first step, which is one of the critical steps of the method, where elements in criteria, sub-criteria, and alternatives are structured to attain the goal of selecting the best alternatives/priorities. In the second step, using a pairwise comparison between preferences, a matrix emerges deriving ratio scales from the comparison. These are expressed as weights (w1, w2, w3………wn) along with information on the relative importance of an evaluation criterion (c1, c2, c3……….cn). This method allows for some small level of inconsistency in judgment. As an input, either actual measurement (e.g., price, weight) or subjective judgment (e.g., satisfaction feelings, preferences) can be given to a model. The output of the model is found as a ratio scale (RS) (derived from pairwise comparison and expressed as weight) and a consistency index (CI). During the process of calculating the weights, the consistency ratio (CR) is another measure that is developed. The method is based on a solution of an eigenvalue problem. The RS results from Eigenvectors and the CI from an eigenvalue. Saaty (2005) defined the eigenvalue method as a weight evaluation, as shown in equation (1):

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A/ . W / = λ

. W / … … … … … … … … … … … … … … … … … … … . (1)

where A is the square matrix found from the pairwise comparison (as RS), is the maximum eigenvalue, and W is the eigenvector. When gets close to n, matrix A has greater consistency. For CI, is greater than n which is expressed by the following equation (2) and CR by equation (3): Consistency index (CI) = Consistency Ratio (CR) =

λ

−n … … … … … … … … … … … … … … (2) n−1

CI(Consistency index) … … … … … … … … … … … … … . . (4) RI (Random index)

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RI is determined by the size of n. CI and CR become 0 when the consistency is ideal or perfect, and is equal to n. On the other hand, when the consistency of judgment is lower, becomes greater than n and the values of CI and CR tend to be both greater than 0. For CR, according to Saaty (2005), the value must be less than 10% (or 0.1). If the CR value becomes greater than 10%, the pairwise comparison must be revised.

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It is important to determine the number of comparisons with the criteria, sub-criteria, and alternatives. The number of pairwise comparisons is expressed by

531

Number of comparisons =

532

where n is the number of criteria/sub-criteria/alternatives.

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In an ideal case of the AHP method, criteria and sub-criteria are evaluated for each alternative with a pairwise comparison, which later provides the weights (in the form of RS). Nevertheless, this scenario is particularly useful when there are 3 or 4 alternatives. For example, for four alternatives, the number of pairwise comparisons considering a single evaluation criterion will be 6 using equation (4). If the number reaches 10, several comparisons will be 45 for a single evaluation criterion, which is often difficult to analyze

+(+,-) .

… … … … … … … … … … … … … (4)

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(both manually and/or in a software package) from the researchers as well as experts’ perspectives. To eliminate such difficulties, in this study, an AHP rating model is utilized. Instead of conducting a pairwise comparison of all alternatives (in our case, products) considering several evaluation criteria, alternatives are rated for the criteria, which dramatically shortens the number of judgments required. The main advantage of a rating model is that an evaluation structure can be set up conveniently (for a relatively large number of alternatives), and each alternative is evaluated as to how it performs on each criterion. According to Topcu (2004), Van Huylenbroeck (1995), Munda (1993), Al-Rashdan et al. (1999), Kleindorfer et al. (1993) and Hwang and Yoon (1995) “the decision-makers who do not want to make pairwise comparisons can also use different weight determination methods such as direct rating, swing, trade-off, ranking, regression”. Another reason for selecting such a model in the AHP-related research is the availability, convenience, and user-friendliness of this specific model in various software applications such as Expert Choice, Super decision, and others. In this study, an AHP rating model was developed, and results were analyzed using Super Decision software, version 2.10.

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Several researchers in the field of operation research and decision sciences utilized the AHP rating model. Hua Lu et al. (1994) applied an AHP rating model in determining strategic marketing orientation to adopt, from the perspective of total quality management for companies. For selecting a construction contractor in Turkey, Topcu (2004) proposed a framework evaluating the prequalification of contractors and implemented a rating model to determine the construction firm that wins with the lowest bid. For protecting coastal landscape resources, decision-making strategies were optimized by Baby (2013), in which the authors used the Super Decision application package and mentioned that implementing a rating model in the software provided easy-to-use solutions to sophisticated decision-making strategies; those needed to be prioritized and optimized. In the analysis process, potential bias was also eliminated. Peniwati and Brenner (2008) used a modified version of the AHP method (which was a rating model) identifying optimized policies for regional drinking water companies in Indonesia. From the viewpoint of multiple sourcing decisions for the carton industry, Sharma and Dubey (2010) used an AHP-rating model. Sueyoshi et al. (2009) employed a normalized rating scale in an AHP-rating model in order to assess the prioritization for a rental car company. Deng (2015) developed a threat assessment model for human under uncertain environment (e.g., military application and physical protection systems) using an AHP-rating model. Carlucci and Kujansivu (2014) used a similar model, selecting a suitable approach for intellectual capital management in Italy. With a model that had three levels with eight main objectives and 53 alternatives, Noaman et al. (2017) provided an optimized solution using an AHP-rating model in the quality assessment of higher education in Saudi Arabia. For enhancing speech intelligibility and learning quality in the classrooms, Madbouly et al. (2016) used such a model in order to determine the main criteria that affect the learning process.

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From the above literature, it is clear that in many different fields within the scope of MCDM models applied the AHP rating model previously, however, to the best of the authors’ knowledge, no previous studies (in the field of e-waste management) on product prioritization have been utilized the model.

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After identifying evaluation criteria through the Delphi method, pairwise comparisons on the criteria were made by the experts using the conventional AHP method at the first stage, in Page 16 of 44

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order to determine the weight of each criterion. Later, each criterion with a specific weight is rated for a product (during the second expert survey). For example, from the expert opinion if “increasing generation rate” would have found as one of the criteria (having a weight of 0.054 after pairwise comparison), so later on, this criterion was then rated as extremely high, above average, average, below average, or poor for a product (under the AHP-rating model). Note that these ratings have individual weights (done by the pairwise comparison) that eventually give an overall normalized weight considering all criteria (with their respective weights) for a product. In this case, judgments were made by the experts using the material composition table, product lifespans, import statistics, and product size (large and small), showing which product has an extremely high generation rate and so on. However, it must be understood that the product-level data structure (e.g., statistics and material composition data and tables) was prepared for a reference only. The experts provided their opinion on their discretion and expertise for which they might or might not use the data. In this process, the products were rated. A final ranking was made for each product under a different e-waste category. Fig. 4 illustrates the overall structure of the research framework of this study.

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Fig. 4. Research framework

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6. Results

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6.1 Product selection

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Based on the analysis, several products were identified as potential candidates for inclusion in the future e-waste management system in Australia. Table 3 shows the products as per the categories of the EU WEEE Directive. Solar PV is a relatively new e-waste product that is being considered strongly by recyclers and CRAs in Australia as it contains a high level of both toxic and valuable metals. Besides the five categories (except “screen”), the battery was also considered in this study. This is placed as the “Other” category. There is a separate regulation for battery in the EU names as Battery Directive 2006/66/EC (Directive, 2006). In the subsequent analysis in terms of toxic and other-element content, only household handheld batteries (single-use and rechargeable) were considered, excluding car and large industrial Page 17 of 44

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applications. In this study, for categorization of other kinds of e-waste, the exclusive category and product listing of ANNEX IV of the EU WEEE Directive is utilized (Directive, 2012a).

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Table 3. Products considered under AHP evaluation process (categories are based on the recast of the EU WEEE Directive) Category name Temperature-exchange equipment Large equipment

Small equipment

Small IT and telecommunication equipment Lamp Others

Products Fridges, air conditioners, freezers, heat pumps, space heaters Solar PV panels, washing machines, dishwashing machines, clothes dryers, electric ovens, electric stoves, range hoods, rice cookers Microwaves ovens, equipment for food preparation (e.g. toasters, grills, food processors, frying pans), personal care equipment (e.g. toothbrushes, hairdryers), video cameras/camcorders, digital cameras, projectors, vacuum cleaners, electric coffee machines, stereo and music systems (e.g. sound boxes, radios, portable loudspeakers), video (e.g. video recorders, DVD, VCR, Blue Ray, set-top boxes) and projectors, portable audio & video (e.g. MP3, e-readers, car navigation), electrical and electronic toys, small electrical and electronic tools, electric fan, electric irons, game consoles (Xbox/play stations) Cordless phones/answering machines Lamps (e.g., fluorescent lamps, high-intensitydischarge lamps, and LED lamps) Batteries (e.g., household handheld excluding car and large industrial applications)

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6.2 Product characterization based on material content

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After product-level categorization, it was determined what the material content (e.g., toxic, common, less-common, and precious metals) of the products under consideration is. One critical issue is highlighted was that products that contain more toxic elements, as well as high-inherent-value resources, should be considered on a priority basis in the future e-waste management system (Oguchi et al., 2013). In this context, it is necessary to look at the material content of the NTCRS products, comparing them with the products under consideration (listed in Table 3). From the data collected, the individual material composition of the product was determined and compared, taking the average material content (of the NTCRS products) in different categories of metals as an average value. This outcome is then used in selecting the preferences/judgments during the AHP process as a preliminary basis (as shown in Table S4 in the SI). This overall identification sheds valuable insights to decide priority rankings, which also minimized the lead-time in developing the product-level pairwise comparison matrix in the AHP rating model. It should be mentioned that in determining metal content particularly toxic and common metals, primary data sources were Parajuly and Page 18 of 44

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Wenzel (2017a), Oguchi et al. (2011) and Oguchi et al. (2013). If the material content of a product (under SE category) was not available in the three sources mentioned above, data provided by Reuter et al. (2013) for SE was considered. However, in that case, SE specific material content mentioned by Reuter et al. (2013) was commonly used for SE, for instance, the same metal content for both blender and food mixer. A similar approach was performed by Parajuly et al. (2017) in quantifying metal content for comparable product categories.

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Fig. 5 shows the toxic-metal content (Ba, Be, Cd, Cr, Pb, Sb, and Hg) per kg of the selected product with an average value of NTCRS product and mobile phones. It is found that, in terms of toxicity, microwave ovens (25760 mg/kg-product), household handheld batteries (118230 mg/kg-product), portable audio and video devices (e.g. GPS trackers, MP3 players) (33560 mg/kg-product), game consoles (21801 mg/kg-product), video VHS systems (22659 mg/kg-product), digital cameras (37421 mg/kg-product), video cameras/camcorders (50302 mg/kg-product), stereo and music systems (21544 mg/kg-product), TV receivers (or set-top boxes) (23055 mg/kg-product), speakers and sound boxes (20875 mg/kg-product), freezers (23894 mg/kg-product), electric ovens (34570 mg/kg-product), headphones (23055 mg/kgproduct), projectors (23055 mg/kg-product), and fridges (23894 mg/kg-product) are the major products that need to be considered in terms of toxicity.

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Fig. 5. Toxic-metal content (in mg/kg) of the individual product under consideration

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Considering the common metals (Al, Fe, Cu, Sn, Zn) in the products, microwave ovens, batteries, cordless phones/answering machines, DVD players/Blu-ray players, electrical and electronic toys, portable audio and video, game consoles, digital cameras, video cameras/camcorders, stereo and music systems, TV receivers, rice cookers, freezers, electric ovens, headphones, projectors, and fridges are the prime products that possess higher metal content than NTCRS-products. Fig. 6 shows the total common-metal content of the selected product.

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Fig. 6. Common-metal content (in mg/kg) of the individual product under consideration

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In Fig. 6, solar PV contains approximately 179523 mg/kg-product of common metals (collectively for Al, Fe, Cu, Sn, Zn) considering the average weight of each technology. In the literature, data on common metal content (in mg/kg) of solar PV were not found. The initial data on material composition and weight of the four different types of solar panels were collected from Domínguez and Geyer (2017), which were then converted to mg/kg. Table 4 shows the different metal content of the solar panels along with the individual average weight.

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Table 4. Weight and various material content in four types of solar panels in mg/kg

Weight of the panel (kg/unit) Material content (mg/kg) Ag Al Cd Cr Cu Ga In Fe Mg Mn Mo Ni Pb Se Si Sn Steel Te Ti Zn EVA Glass

Solar PV technology c-Si a-Si CdTe CIGS 23.66 19.21 13.25 16.48 c-Si

a-Si

577 165000 0 0 7310 0 0 0 5200 0 0 10.6 46.7 0 7910 0.586 95100 0 0.052 0.0781 65000 654000

0 416000 51.3 5.65 8990 0 116 7.45 13100 9.37 0 0 0 0 25.7 0 398000 64.2 0 3.72 159000 4590

CdTe 0 904 1200 181 30100 0 0 0 0 0 0 0 42.2 0 3010 0.0139 12000 1200 0.00139 0.00181 36100 915000

CIGS 0 85800 1710 0 2840 568 284 0 2670 0 568 0 0 568 0 568 0 0 0 568 51200 853000

Average 144.25 166926 740.325 46.6625 12310 142 100 1.8625 5242.5 2.3425 142 2.65 22.225 142 2736.425 142.15 126275 316.05 0.013348 142.95 77825 606647.5

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In terms of precious-metal content (Ag, Au and Pd), the result of this study shows that, under small equipment, microwave ovens, cordless phones, DVD players, portable audio and video, digital cameras, video cameras, TV receivers, projectors, headphones are the products that exceed the average metal content of NTCRS and mobile phones (1466 mg/kg). On the other hand, some of the large equipment such as freezers, electric ovens, and fridges cross the average value due to a higher presence of Ag compared to NTCRS-products and mobile phones. Based on the presence of precious metal in DVD players (880 mg/kg), electrical and electronic toys (1013 mg/kg), game consoles (1013 mg/kg), and rice cookers (840 mg/kg), Page 21 of 44

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these are found as relatively significant. Fig. 7 shows the distribution of the total preciousmetal content of the selected products.

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Fig. 7. Precious-metal content (in mg/kg) of the individual product under consideration

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Considering Bi, Co, Ga, Sr, and Ta; solar PV, batteries, cordless phones/answering machines, DVD players, portable audio and video equipment, video VHS systems, digital cameras, stereo and music systems, TV receivers, speakers, headphones and projectors are the specific products that exceed the average (1859 mg/kg) of less-common metals found in NTCRSproducts and mobile phones. The detailed material composition can be found in Table S3 in the SI.

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Fig. 8. Less-common-metal content (in mg/kg) of the individual product under consideration

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6.3 Outcome of Delphi method for evaluation criteria

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During the first expert survey in the Delphi method, a total of 12 evaluation criteria were identified. Later, seven final criteria were selected at the time of the second expert survey including increasing generation rate; existing collection network; existing sorting, recycling technology, infrastructure; the convenience of customers; potential reduction of environmental impact and finally, product similarity. Table 5 shows the mean and IQR values that meet the criteria for selecting the final set of evaluation criteria (those arrived at IQR value ≤1) and these were increasing generation rate; existing sorting and recycling technology and infrastructure; convenience of customers; similar product characteristics and potential reduction of environmental impacts.

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Table 5. Mean and interquartile range (IQR) results of final evaluation criteria Criterion Increasing generation rate Existing collection networks Existing sorting and recycling technology, and infrastructure

Mean 6.375 6.125 6.5

IQR 1 0.75 1

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Potential reduction of environmental impact Convenience of customers Similar product characteristics Efficient reverse logistics Economies of scale Stakeholder capacity Impact on market High metal and material content

7

0

6.625 6.25

0.75 1

5.125 5.25 5.25 5.00 5.875

1.75 2.5 1.75 1.5 2

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The sub-section 5.3 already described the significance of the mean and IQR values obtained for the study. Similar evaluation criteria were then grouped into one specific criterion. For example, the convenience of the customer, existing collection network and existing sorting, recycling technology, and infrastructure (as the secondary evaluation criteria) were put under the broad category of collection and recycling, which is found as one of the primary evaluation criteria. Fig. 9 shows the criteria and sub-criteria that were used in the AHP

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method.

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Fig. 9. Criteria and sub-criteria selected in AHP process

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6.4 Weighting of criteria and sub-criteria by AHP method

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Delphi method provided important indications for criteria and sub-criteria that need to be taken care of for selecting the priority products in the future e-waste management system in Australia. After the method, criteria and sub-criteria were weighted quantitatively by the Page 24 of 44

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AHP method. The relative weight of the criteria (named primary evaluation criteria) and subcriteria (called secondary evaluation criteria) are shown in Fig. 10.

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Fig. 10. Primary evaluation criteria (A) and secondary evaluation criteria (B) with the relative importance

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The results showed that the potential reduction of the environmental impact is the most significant factor, with a weight percentage of 57.50%, followed by product similarity (23.60%), collection and recycling (13.50%), and finally increasing generation rate (5.40%). Product similarity refers to the characteristics of the products that share almost identical characteristics (of NTCRS-products) in terms of metal content. According to the analysis, it is found that products that have a high risk of polluting the environment; in other words, have a higher toxic-elements than others, need to be considered on a priority basis. To some stakeholders, increasing generation rate is not a major concern, which is also seen in the pairwise comparison, representing only 5.4% of the overall weight. The reason could be that most of the products included in this study are either disposed of with household solid waste or with the council clean-up collection (that eventually go to the landfill without further processing) for which there are no statistics available. However, if the UNCOMTRADE database is considered for each product group (under the category of small equipment), a considerable volume of EEE products were imported in the last ten years that will eventually end up as e-waste. Recyclers and CRAs need to consider this fact in the future effort in integrating products for a new scheme or a similar existing scheme (like the NTCRS).

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On the other hand, secondary evaluation criteria (or the sub-criteria) of the “collection and recycling” factor, “customer convenience” is considered as the most significant factor (64.80%), and the weight percentage of the existing collection network and existing sorting and recycling technology and infrastructure were 23% and 12.20%, respectively. Lessons learned from the NTCRS program for collecting and recycling TV sets, computers, laptops, and other IT peripherals showed that there is a need to ensure that customers can dispose of Page 25 of 44

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e-waste regardless of its category at a single place, eliminating the confusion of what can be recycled and what cannot. This system structure is widely being placed in operation under the EU WEEE Directive in the European countries, for example, in Denmark (Parajuly and Wenzel, 2017a), Switzerland (Islam et al., 2018). This practice will also increase the overall economies of scale for the collectors and recyclers (ACIG, 2017). Furthermore, from the demand-side management, customers must have the ease to dispose of their e-waste at the least distance possible. Before the start of the NTCRS scheme, in 2010, it was modeled and assumed that the optimum distance of the collection points from the customer would be approximately 20 km (DEWHA, 2010), which was found not appropriately optimized, identified by Dias et al. (2018). It is to be mentioned that reasonable access is one of the fundamental mandates of the NTCRS, providing an adequate number of collection sites for all residents in Australia – regardless of whether metropolitan, regional or remote area (DOEE, 2018b). However, this is also found as one of the critical issues for the future sustainability of the system (ANZRP, 2018). From this aspect, customer convenience was found as one of the most significant factors among the secondary evaluation criteria.

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After finding the weights of the criteria and sub-criteria, 47 products were ranked using an AHP-rating model. With the selected products, if an ordinary AHP pair-wise comparison would have done, the total number of pair-wise comparisons for a single criterion reaches 1081 (using equation 4) which is predominantly a cumbersome and challenging way of analyzing the results, both from the researchers’ perspective as well as for the experts who evaluate product-level priority. At this stage, product-rating preferences were introduced in the model using Super Decision software to eliminate such a rigorous computation. Experts provided a rating scale for which the overall weight of an individual product was calculated. The preferential rating was divided into four levels (with weighting values), namely as excellent (1.00), above average (0.74), average (0.32), below average (0.13), and poor (0.06). The CR found, in this case, was approximately 7%, which met the criterion for the rating scales to be valid and useful in the AHP rating model to rank the product individually.

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By considering primary evaluation criteria, secondary evaluation criteria, and rating-specific scales, the normalized weight of each product was ranked for each category, as presented in Fig. 11. The final rankings of the products are listed in Table 6. The products that showed overall weight higher than 2% are only included. Under the TEE, space heaters, fridges, freezers, and air conditioners are ranked first to last. Solar PV and washing machines were found as the most crucial products under the LE product category. Among the SE products, vacuum cleaners, microwave ovens, DVD/blue-ray players, stereo and music systems and speakers/sound boxes, headphones, game consoles, digital cameras, video cameras/camcorders, TV receivers/Set-top boxes, power tools, projectors, frying pans were found to be the top 13 products from first to last (out of 30 products). Cordless phones/answering machines (3.07%), portable audio and video devices (2.16%) (e.g., MP3, e-reader, car navigation), and batteries (3.16%) are the other significant products under small IT and Other categories, respectively. Here, the percentages (shown in Fig. 11) are the normalized weight for a product (considering all the factors and their evaluation weights) obtained from the AHP rating model. Finally, it is to be mentioned that the experts then validated the result (priority product ranking), and they all agreed to the list.

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Fig. 11. Product prioritization under various categories in future e-waste management system based on weights of criteria Page 27 of 44

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Table 6. The priority list of products needing to be considered under expanded NTCRS scheme or in a new collection and recycling scheme E-waste category Temperature-exchange equipment (TEE)

Rank 1 2 3 4

Product Space heaters Fridges Freezers Air conditioners

Large equipment (LE)

1 2

Solar PV panels Washing machines

Small equipment (SE)

1 2 3 4 5 6 7 8 9 10 11 12 13

Vacuum cleaners Microwave ovens DVD players/Blue-ray players Stereo and music systems Speakers/sound boxes Headphones Game consoles Digital cameras Video cameras/camcorders TV receivers/Set-top boxes Power tools Projectors Frying pans

Small IT and telecommunication equipment (Small IT)

1 2

Cordless phones/answering machines Portable audio and video devices (e.g. MP3, ereader, car navigation)

Other

1

Batteries (household handheld)

840 841

7. Sensitivity analysis

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Sensitivity analysis is an integral part of the AHP method, identifying the impact of changing the weight of the criteria in the priority ranking of a product or service under a “what-if” scenario (Mu and Pereyra-Rojas, 2016).

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Sensitivity analysis was performed considering three factors (potential reduction of environmental impact, collection and recycling, and increasing generation rate) for all products. It is already identified from the material-composition datasheet (presented in Table S3 in the SI) that cordless phones/answering machines, digital cameras, DVD/Blu-ray players, game consoles, headphones, microwave ovens, solar PV, space heaters, speakers/sound boxes, stereo and music systems, TV receiver/set-top boxes, vacuum cleaners, video cameras/camcorders, video VHS systems and electrical and electronic toys are the products that share almost similar pattern of material composition and lifespan characteristics as NTCRS-products. Thus, “product similarity” as an evaluation criterion was excluded from the sensitivity analysis. Page 28 of 44

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The “increasing generation rate” (which had the original weight of 5.4% in the overall evaluation process), was changed to the different weights shown in Fig. 11. When the weight of the factor increased to 50% (close to the weight of the potential reduction of the environmental impact factor (as 57.50%), it is found that batteries, cordless phones/answering machines, DVD/Blu-ray players, fridges, game consoles, headphones, microwave ovens, space heaters, speakers/sound boxes, stereo and music systems, toasters, TV receivers, and vacuum cleaners were the top products among the selected items. This result also shows similar values for the products if the weight of this factor increases to 67%. The impact of other weights for the criterion on the product priority can also be found in Fig. 12.

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Fig. 12. Sensitivity analysis of the increasing generation rate criterion

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With 50% of the weight of the collection and recycling factor (which had an original weight of 13.50%), it is found that batteries, digital cameras, DVD/Blu-ray players, fridges, microwave ovens, space heaters, vacuum cleaners, and washing machines are the critical products to be considered in the future e-waste management system in Australia. Fig. 13 illustrates the sensitivity analysis result of this factor, starting from 0% up until 100%.

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Fig. 13. Sensitivity analysis of the collection and recycling criterion

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If 67% weight is used for the “potential reduction of the environmental impact” factor (original weight was 57.5%), then air conditioners, batteries, cordless phones, digital cameras, DVD/Blu-ray players, freezers, fridges, game consoles, headphones, microwave ovens, solar PV panels, space heaters, speakers/sound boxes, stereo and music systems, toasters, TV receivers, vacuum cleaners, video cameras/camcorders and video VHS systems are the most critical products. The sensitivity of the factor in the products is illustrated in Fig. 14.

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Fig. 14. Sensitivity analysis of the potential reduction of the environmental impact criterion Page 30 of 44

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8. Discussion

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8.1 Managerial and policy implications of the research for the circular economy

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The study identified that “potential reduction of environmental impact” was the most significant criterion (among the experts) that needs to be considered while “increasing generation rate” as the least weighted evaluation criterion under the primary evaluation criteria. Similarly, the “convenience of customers” was found as the most significant aspect in the secondary evaluation criterion under the broad criterion of “collection and recycling”. However, “existing sorting and recycling technology and infrastructure” was preferred the least among the evaluation criteria. The possible reason that might explain this fact that it is already perceived that necessary infrastructures are already in place that can deal with the growing generation rate if new products are included. Although the issue was found less important, local recycling infrastructure development, and the use of advanced technology are indeed relatively critical issues that need further attention in Australia (Khaliq et al., 2014). A study by Dias et al. (2018) showed that there are very few recyclers that used stateof-the-art technologies in the e-waste recycling process in Australia. After expensive manual dismantling and sorting operation, pre-processed fractions of e-waste are sent to developing counties such as China, India, Vietnam, and Indonesia for further downstream processing. Besides, downstream material recycling is not being monitored by the CRAs, and this became a critical malfunctioning area that needs further attention (Islam and Huda, 2019a). Instead of such expansive and cross border operation, local recycling infrastructure and technology, particularly, pyro and hydrometallurgy processes, need to be implemented in Australia (Golev and Corder, 2017). Besides, downstream recyclers in foreign countries, especially China and Thailand, are putting pressure on CRAs for limiting their volume of preprocessed transferred to the country under the NTCRS (ANZRP, 2017a). Also, existing recyclers those work under the scheme are seriously in need of sufficient volume, which can be achieved by introducing new products in the management system (ANZRP, 2017c). Combining both scenarios, expansion of product scope, and developing local recycling infrastructure according to the e-waste generation is one of the most critical tasks to accomplish by the policymakers. Collaboration and coordination mechanisms among various stakeholders, incentives, and strategic value alignment in circulating used or end of life products/components/materials are some of the essential aspects making the circular economy a reality (Farooque et al., 2019).

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Cyber-physical system integration with the existing e-waste management system could be the next-level product recovery and inventory management solution that can achieve the goals of the circular economy. In the big picture, substantial transformation is occurring in the waste management sector implementing smart technologies in the area of data acquisition and sensor-based technology, technologies applicable for field experiments, and vehicle routing (Esmaeilian et al., 2018). For this case, use of internet-of-things (IoT), big data, and RFIDbased technology that could potentially improve the data quality on EoL product traceability, product lifecycle information management (Zhang et al., 2010). Hong et al. (2014) mentioned that companies like Compology, Sensoneo, and RecycleSmart are already implementing IoT Page 31 of 44

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sensor-based technologies and web-based software for bin-level waste assessment and monitoring and optimized logistics service planning. Zhang et al. (2019) identified four types of smart enabling technologies that can be used for smart waste management, namely “IoT including RFID tags, NFC sensors, and GPS sensors” for reverse logistics planning; “Cloud Computing” for planning recycling-oriented activities; “Big data analytics” for combining socio-economic data with the distribution of waste across a geographical location; “Cyberbased Decision Support Systems” focusing on monitoring and analyzing carbon foot-printing of waste management and finally consumers’ waste generation behavior via “Artificial intelligence including machine learning and deep learning”. Ghaffar et al. (2020) proposed the implementation potential of artificial intelligence, additive manufacturing, nanotechnology, virtual/augmented reality, and robotics for the construction and demolition waste sector. This entire development and integration of the technologies would provide better national-level e-waste generation statistics as well as better material accounting from generated e-waste ensuring circular economy (Islam and Huda, 2018b, 2019b). Implementation of the smart technologies in waste management, in general, should focus on cost-reduction, improved quality of service, and contribution to environmental protection (Nižetić et al., 2019). However, there are substantial opportunities in applying the technologies in the e-waste sector.

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Furthermore, as “consumer convenience” is one of the significant issues in the product EoL management, understanding public opinion for collection system might provide useful insight on which specific channels (such as local collection points, take-back arranged by manufacturers/third-party reverse logistics provider, door-to-door collection) are suitable for consumers. Understanding the consumer perspective in the circular economy is relatively less researched areas that need close attention (Farooque et al., 2019). Islam and Huda (2019a) mentioned that exporting pre-processed e-waste is currently a loss for Australia, and the yearly potential revenue generation gap between NTCRS products and products outside of the scheme is widening, which is also a significant inhibitor achieving circular economy and close looping the material cycle for the country. Besides, the existing collection network might be suitable for SE; however, for LE and TEE, individual collection system development, particularly, reverse logistic network design might be an essential task for the policymakers. Furthermore, additional products and its management could potentially create opportunities for jobs (in the form of a logistic service provider for LE and TEE e-waste products), which is also one of the main agendas for circular economy and achieving sustainable development goals.

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Another vital aspect that the government should further investigate is identifying manufacturers and importers of the (priority) products (identified by this study) and dealing with them under the principle of EPR. In conjunction with that, setting a target on the collection and recycling rate is another task for the government. As it is seen that products do contain both toxic and valuable metals (under all categories), making the producers liable for systematic product take-back and subsequent recycling and material management are the critical conditions under the broad perspective of the circular economy, and these need to be ensured by the policymakers. With a ‘functional service’ approach under the comprehensive product-service system (in circular economy), manufacturers can be benefitted managing Page 32 of 44

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EoL products (Farooque et al., 2019). According to Nasir et al. (2017), functional service is defined as a system in which “producers retain the ownership of physical products and act as service providers focusing on the service end-user wants.”

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Existing manufacturers and importers (under the NTCRS) fund the e-waste system, which can be replicated for the new products. Alternatively, separate producer responsibility organizations (PROs) can be developed for the collection and recycling of new products by taking examples from Switzerland (Khetriwal et al., 2009, Thiébaud et al., 2018). Advanced Recycling Fees (ARFs) could be implemented in products, particularly LE and TEE, for which consumers might be interested in participating in the take-back scheme (via the PROs or retailers or manufacturers directly). However, strategies and incentives for consumers in alignment with the circular economy need further investigation (Farooque et al., 2019). The approach might substantially reduce the significant bottlenecks of the current local council’s collection activities (which do not collect products for recycling, instead send the products directly go to landfills). With the introduction of new products in the system, local government councils should have specific tasks to perform. During council clean-up, instead of collecting all types of (e-waste) products then transferring them to the landfills, some intervention in the form of reuse and recycling should be taken. For small WEEE, retail shops can be used as collection points, which are encouraged in the EU WEEE Directive (Directive, 2012b). Charity organizations and repair shops could play an essential role in this aspect, and councils have a considerable role to play integrating collective actions. However, all these issues need to be consulted further at the federal, state and territory, and local government levels.

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8.2 Comparison of results Of course, it is often hard to compare the identified products from the study with other researches, as it involves a different set of selection criteria and policy priorities, which substantially vary across the countries. Previously, Kim et al. (2013) proposed that vacuum cleaners, electric fans, electric rice cookers, freezers, and microwave ovens are the top five priority products in South Korea due to the increase in generation. For Japan, Oguchi et al. (2011) and Oguchi et al. (2013) identified that video games devices, notebook computers, and printers, fax machines, and audio/video equipment was needed to be included in the e-waste collection and recycling system. The reason was that the products contain high toxic and valuable metals. Zeng et al. (2016) mentioned that the Chinese government already identified range hood, electric water heater, gas water-heater, fax machine, mobile phone, singlemachine telephone, printer, copier, and monitor as new e-waste in the management system. Previously only television, refrigerator, washing machine, air conditioner, personal computer were included in the Chinese WEEE Directive. In this study, similar products were identified in various categories, as shown in Table 5. Initially, this study started analyzing 47 different products, which could be a starting point for Australia. Notably, products under the small equipment category can be considered directly in Australian case (taken from the study of Parajuly and Wenzel (2017a)), as Danmark and Australia share similar economic status and e-waste generation pattern. For developing more in-depth product listing for the master Page 33 of 44

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product list (in Australia), policymakers can use this as essential reference. Previously for South Korea, a growing generation rate was considered as a significant factor for product inclusion in the e-waste management system, which is found as a relatively less critical fact for Australia (as per experts’ opinions). From here, it can be seen that policy-related decisionmaking in e-waste product inclusion in the existing e-waste management system substantially varies across the countries. Sensitivity analysis for different weighting of the evaluation criteria showed that in total, 19 products had very insignificant changes (in terms of overall normalized weight), which means that these products were found to be more consistent in determining their importance as priority products in the future e-waste management system in Australia. These products were batteries, cordless phone/answering machine, DVD players, fridges, freezers, game console, headphones, microwave ovens, power tools, solar PV panels, space heaters, speaker/soundboxes, toasters, TV receivers/ set-top box, vacuum cleaners, video cameras, Video VHS system and washing machine.

1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045

This paper identified priority products for Australia that are currently outside of the current national recycling scheme. A combined Delphi-AHP approach was implemented in this regard. Results showed that seven evaluation criteria were found importance among the experts in which “potential reduction of environmental impact” (with a weight of 57.50%) was the most important criteria for product inclusion. Applying all the weighted criteria and preferential rating in an AHP rating model, this study found 22 significant products that need to be considered in the future e-waste management. Sensitivity analysis applied to the weighting of the evaluation criteria showed that variations do exist in the raking of the products. However, products under small equipment categories and solar PV panels and washing machines showed relatively stable positions (in the list). This study could be an essential reference for policymakers and decision-making authorities in the e-waste management sector. The methodological procedure followed in this study could be replicated in other countries, and from that aspect, this study will also be beneficial for academics. Several future research directions are highlighted in this study that can be utilized by the research communities not only in Australia but also in other countries who want to introduce a product-specific e-waste management system or expand product scope within the existing system.

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Although this study is the first systematic study that identifies priority products for Australia, several limitations exist in the study, which should be addressed in the future. First, initial product list (with 47 products) was prepared predominantly based on a literature review which can be done by more field visits to all collection points and resource recovery facilities, and in particular, during council’s clean up collection days on which households dispose of various kinds of e-waste items. Second, a material characterization of a product was done by an extensive literature survey, but there are considerable scopes in this area developing material flowsheet by the product disassembly and laboratory-based material characterization for products. This issue is particularly important for products under the small equipment category. On the other hand, there is a substantial scope investigating product

9. Conclusion, limitations and future research

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categorization based on its material content that focuses on the circular economy (Commission, 2015). Parajuly and Wenzel (2017b) argued that the categorization of products needs to be done based on the inherent material content of products or groups of products (under product family approach), rather functionality and size. Currently, significant losses occur in the e-waste management system in the EU despite the existing categorization of the products made in the recast of the Directive. Thus, product disassembly and material characterization (named as “product-centric material characterization” in this study) could ensure batter categorization of products from the concept of circular economy considering potential reuse and repair and recycling. Farooque et al. (2019) mentioned there are ample opportunities in design for dismantling, design for remanufacturing, design for recycling under the framework of the circular economy. However, capitalizing these scopes is a challenging task for the international research community identifying the prospects at the national level. Third, in terms of the methodological aspect, this study took opinions from 8 experts in two survey rounds (in the Delphi method), which can be improved by increasing the number of experts and rounds of the survey. Fourth, the background of selecting the factor “potential reduction of environmental impact” was made based on metal content data. It must be understood that the representation of the data that showed on the metal content of the product (higher/lower values compared to NTCRS-product and mobile phones), is just a simplified approach for general understanding. However, this type of preliminary assessment for product selection in the e-waste management system was previously applied by Oguchi et al. (2013) and Oguchi et al. (2011) in Japan. In this study, experts provided the final responses on the issue, and it was attempted analyzing a product’s metal content as the background or reference along with other data (such as lifespan, trade statistics). To make the decision-making process more robust and accurate (in the area of potential environmental impact from a product), environmental impact assessment using recognized life-cycle assessment (LCA) methods such as “USEtox” would be more appropriate. In such an aspect, further work is required in this area to enhance/refine the methodology before it can be used to inform policy measures in selecting priority products, and the use of the LCA method could be particularly helpful. However, the procedures implemented in this study should be considered as a starting point investigating the issue. In addition, toxicity assessment using USEtox can be done with organic substances (such as PCDD/Fs, PBDD/Fs, PAH), as well as inorganic substances (Rosenbaum et al., 2008). A recent article by Singh et al. (2019) analyzed toxicity trends of waste mobile phones using the method with a focus on inorganic metals such as Cu, Ag, Fe, and others. However, there are other sources of toxicity present in e-waste, such as adhesives, coatings, and recyclable materials like polymers (Zanghelini et al., 2014). However, in many cases, extensive productlevel inorganic toxic materials are not found in the academic literature - for example, toxic inorganic materials in “food processing equipment” as e-waste. Singh et al. (2019) mentioned the lack of current recovery and recycling strategies for toxic inorganic substances present in waste mobile phones, which were one of the reasons for restricting the assessment only with inorganic substances. For other types of e-waste, particularly products under small equipment category seriously lack this issue as well. A typical product-oriented material content (inorganic and organic toxic and valuable metals) database for all categories of products is Page 35 of 44

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required, which is one of the areas for future research. It is an open research opportunity for Australia and also for other countries where impact assessment method needs to be applied for unregulated products (or for products that need to be considered for a new e-waste management system) assessing toxicity. Besides, although AHP rating model substantially reduced the computation time and effort in the final analysis process, future research might look into using the conventional AHP method for a group of products (e.g., only SE or LE) to observe the variations in the final result that attempted in this study. The use of other variations of the AHP method, such as fuzzy AHP, could be an option in this particular aspect.

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Supplementary information

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Supplementary information of this article is available at:

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Declaration of Competing Interest

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Acknowledgments

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The authors would like to thank three anonymous reviewers for their constructive comments on the manuscript. The first author acknowledges the financial support from Macquarie University under the scholarship scheme “International Macquarie University Research Training Program (iMQRTP)” for conducting this research.

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Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Kind regards,

Dr Nazmul Huda

Senior Lecturer in Mechanical Engineering Program Director - Master of Engineering Management School of Engineering | 44 Waterloo Road (44 WR), Room 118 Macquarie University, NSW 2109, Australia Phone: +61 2 9850 2249 | science.mq.edu.au/pace/ | mq.edu.au