Article Challenges in Waste Electrical and Electronic Equipment Management: A Profitability Assessment in Three European Countries

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1 Article Challenges in Waste Electrical and Electronic Eqipment Management: A Profitability Assessment in Three Eropean Contries Idiano D Adamo 1, Paolo Rosa 2, * and Sergio Terzi 2 1 Department of Indstrial and Information Engineering and Economics, University of L Aqila, Via G. Gronchi 18, L Aqila, Italy; idiano.dadamo@nivaq.it 2 Department of Management, Economics and Indstrial Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milano, Italy; sergio.terzi@polimi.it * Correspondence: paolo1.rosa@polimi.it; Tel.: Academic Editor: Vincenzo Torretta Received: 16 April 2016; Accepted: 29 Jne 2016; Pblished: date Abstract: Waste electrical and electronic eqipment (WEEE) is known as an important sorce of secondary raw materials. Since decades, its treatment allowed to recover great amonts of basic resorces. However, the management of electronic components embedded in WEEE still presents many challenges. The prpose of the paper is to cope with some of these challenges throgh the definition of an economic model able to identify the presence of profitability within the recovery process of waste printed circit boards (WPCBs). To this aim, a set of common economic indexes is sed within the paper. Frthermore, a sensitivity analysis on a set of critical variables is condcted to evalate their impact on the reslts. Finally, the combination of predicted WEEE volmes (collected dring the period) in three Eropean contries (Germany, Italy and the United Kingdom) and related economic indexes qantify the potential advantage coming from the recovery of this kind of waste in the next ftre. Keywords: waste electrical and electronic eqipment; waste printed circit boards; end of life management; profitability assessment; sensitivity analysis 1. Introdction WEEE (waste electrical and electronic eqipment) is one of the most important sorces of complex waste [1]. In economic terms, potential revenes coming from the e-waste recycling are estimated in 2 billion and USD 16 billion in Erope and China, respectively [1, 2]. A great improvement in material recovery rates has been enabled by worldwide initiatives dring the last decades spporting the integration of end-of-life (EoL) strategies within the vale chain of companies [3, 4]. However, crrent performances are still too low to be able to conteract the annal increase of generated waste, especially considering WPCBs (waste printed circit boards), the most complex, hazardos, and valable elements embedded in e-waste [5-8]. Basic gidelines for the rese, recovery and recycling of WEEE have been already established and many athors analysed and compared different WEEE directives and national recovery systems [9-11]. Their aim was the assessment of the presence of basic principles able to spport the development of a circlar economy based on the exploitation of both critical materials and resorces recovered from WEEE. From this side, the Eropean Commission played (and contine to play) a key role in financing several dedicated projects (e.g., Innovative hydrometallrgical processes to recover metals from WEEE inclding lamps and batteries (HydroWEEE), Contering WEEE Illegal Trade (CWIT), Prospecting Secondary raw materials from the Urban Mine and Mining waste (ProSUM) and Critical Raw Material Closed Loop Recovery (CRM Recovery)). Sstainability 2016, 8, x; doi: /

2 Sstainability 2016, 8, x 2 of 20 Even if the sstainability of WPCB recycling processes is a timely topic in the literatre [12, 13], their economic implications are rarely analysed by the experts [14, 15]. Given the limited set of application fields and the relevant growth of WEEE, this paper proposes a feasibility analysis on the recovery process of PCBs from WEEE trying to follow mltiple aims. First, the paper assesses the potential profitability characterizing all the phases of a typical PCB recovery process focsed on WEEE, in both mobile and field configrations. Second, in order to spport the obtained reslts, a set of alternative scenarios is analysed for each plant configration, by taking into accont the following critical variables: gold/palladim/copper market prices, gold prity level, WPCB prchasing cost, plant satration level and opportnity cost. Third, the estimates of ftre profitability trends in three Eropean nations (Germany, Italy and the U Kingdom) within the period are proposed. The reslts cold spport governmental and indstrial actors dring the revision of crrent directives and the evalation of corrective measres. The paper is organized as follows: Section 2 proposes a literatre review abot the crrent economic models focsed on WEEE. Section 3 presents the research framework and a description of the economic model taken into accont within the paper. Section 4 presents the main reslts coming from the introdction in the model of crrent data on WEEE. Section 5 describes a sensitivity analysis on the main critical variables inflencing decisions. Section 6 estimates the ftre profitability trends in Erope. Finally, Section 7 proposes a discssion of the reslts and Section 8 presents some conclding remarks. 2. Literatre Review Crrent electrical and electronic eqipment (EEEs) is replaced with an even faster rate creating enormos qantities of e-waste [17]. This phenomenon is de to both the rapid technological development and the reqirement of higher performances to mass electronic prodcts. Considering that, on average, each EEE embeds at least one PCB acconting for almost 3% 5% of its overall weight, WPCB expected volmes are impressive and accontable in several million tons [18]. Frthermore, PCBs are the most valable elements embedded in EEEs [16-18]. However, crrent WEEE directives do not adeqately manage neither their recovery process nor the reqired prity level of otpt materials [5, 19]. In addition, the existing economic models assessing the profitability of recycling plants are very few and three main isses characterize them: (i) the limited set of application fields [23]; (ii) the absence of standard materials composition of PCBs taken into accont [14] and (iii) the focs on a particlar phase of the process, considering both costs and revene performance [24]. Some examples of the crrent economic models available in the literatre are introdced here and briefly discssed. A cost comparison of different PCB dismantling processes (manal verss mechanical ones) is proposed in [25]. When the treated WPCB amont is less than 1 kton, the cost of manal dismantling is lower than the mechanical one (eqal to USD 25,000 verss USD 50,000, considering 0.5 ktons of WPCBs). When 10 ktons of WPCBs are treated, the total cost of the mechanical dismantling is eqal to USD 350,000, while the one for the manal dismantling is eqal to USD 400,000. The feasibility of a hydrometallrgical process for the recovery of WPCBs is evalated in [26]. Positive performances are reached when gold exceeds the tipping point of 500 ppm. In addition, considering 1000 ppm of gold, the payback time varies from one to three years, with 100 kg and 50 kg of WEEE per batch, respectively. The key role of gold is highlighted also by other athors [20]. However, this dependency comes not only from the amont of precios metal characterizing a WPCB, bt also from its crrent market price. Potential revenes are estimated to be eqal to 21,500 USD/ton in a baseline scenario, becoming eqal to ,700 USD/ton in alternative scenarios. Another work evalates the electrostatic separation, by assessing the payback time eqal to 2.5 years [27]. Sales revenes are defined as the most sensitive factor in the economic performance of the recycling system, bt also feedstock stocks have a critical impact [28].

3 Sstainability 2016, 8, x 3 of 20 A comparison of PCB mechanical treatment lines is evalated in [29]. Gross profit is estimated to be eqal to 18 USD/ton with a traditional flid bed line, 129 USD/ton with a process done in a developed contry and 256 USD/ton with an atomatic line. Another comparison of economic performances from alternative treatment plants is proposed in [21]. Gross profit is estimated to be eqal to 83 USD/ton with a field plant in a developing contry, 101 USD/ton with a field plant in a developed contry and 14 USD/ton with an integrated mobile recycling plant. These two works analyse an horly prodctivity eqal to 0.3 tons of WPCBs per hor and tons of WPCBs per hor, respectively. A recent work tries to cover these literatre gaps by proposing an economic model able to assess the profitability of a complete PCB recycling process [15]. Net present vale (NPV) is estimated to vary within the range 96, ,726 /ton in a field plant (horly prodctivity eqal to 0.3 tons of WPCBs per hor) and within the range 52, ,267 /ton in a mobile plant (horly prodctivity eqal to tons of WPCBs per hor). Disconted payback time (DPBT) is eqal to one year. Within the same paper, a sensitivity analysis defines the following critical variables: gold content, gold price, final prity level, WPCB prchasing cost, plant satration level and opportnity cost. However, this last work assesses PCBs coming from the only atomotive sector. This paper wants to extend the analysis to WEEE PCBs, in order to evalate this growing market. 3. Materials and Methods The following Figre 1 gives a smmarizing view of the strctre of the paper. Figre 1. A smmarizing view of the strctre of the paper. Starting from a detailed state of the art analysis, the paper assesses the existing literatre gaps, focsing on lacks related to the available economic models. This way, a new economic model is defined trying to fill in some of these gaps. Sbseqently, the reslts obtained are assessed throgh a sensitivity analysis. In order to add vale to the paper, a set of the most relevant nations in terms of e-waste generation are compared and an estimation of ftre trends is implemented WEEE Volmes The entire work starts from the overall amont of WEEE collected in three Eropean contries (Germany, Italy and the United Kingdom) in 2013 [30]. The choice of these three nations depends on the fact that they represent 47% of the overall WEEE market in Erope. Sbseqently, WEEE collected from hoseholds (abot 87% in EU-28) are considered becase of the lack of data within Erostat abot Italy and its total amont of single WEEE categories.

4 Sstainability 2016, 8, x 4 of 20 This lack of data is de to a different way of classification followed by Italy. According to the Italian legislation, WEEE is classified as follows: heaters and refrigerators (R1), large hosehold appliances (R2), TV and monitors (R3), small hosehold appliances (R4) and lighting eqipment (R5) [31]. Instead, other Eropean contries divide WEEE into ten categories (Cat#), by following the WEEE Directive classification gideline. Among these ten grops, only for are selected becase of their relevance (abot 95% in EU-28) on the overall amont of WEEE volmes. Considering the Eropean classification the following grops are taken into accont: Cat1 WEEE represents big hosehold appliances (e.g., fridges, washing machines and air conditioners); Cat2 WEEE considers small hosehold appliances (e.g., vacm cleaners, toasters and fryers); Cat3 WEEE represents IT and telecommnication eqipment (e.g., PCs, tablets, notebooks and smartphones); Cat4 WEEE considers consmer eqipment (e.g., TVs, monitors, stereos and cameras). Table 1 reports data abot WEEE annal collected volmes in EU-28. Table 1. Eropean WEEE collected volmes in 2013 (tons) Sorce: [22]. Germany Italy The United Kingdom EU-28 Total (tons) 727, , ,490 3,513,906 Collected from hh (tons) 616, , ,711 3,056,843 Collected from hh/total 85% 48% 96% 87% Cat1 from hh (tons) 248, , ,406 1,550,546 Cat2 from hh (tons) 76, , ,802 Cat3 from hh (tons) 116,681 32, , ,454 Cat4 from hh (tons) 132,931 58,610 33, ,420 (Cat1+Cat2+Cat+Cat4) (tons) 574, , ,211 2,907,222 (Cat1+Cat2+Cat+Cat4)/Tot hh 93% 98% 96% 95% 3.2. WPCB Recycling Process hh = hosehold. A PCB recycling process can be described as the sm of three macro phases that, starting from waste PCBs, are able to recover a set of (almost pre) raw materials. These phases can be distingished as follows: disassembly, treatment and refining [23, 24] Figre 2. Dring disassembly, hazardos components (e.g., condensers or batteries containing dangeros materials) are disassembled from the main board and destined to specific treatment plants. Dring treatment, PCBs are crshed in micro pieces p to become a niform powder throgh several technologies (e.g., shredders and grinders). Then, powders are separated in metal and non-metal ones by exploiting different physical principles (e.g., density, magnetism and weight). Finally, metal powders are refined throgh the available technologies (e.g., pyrometallrgy, hydrometallrgy, or a mix of them) p to becoming almost pre secondary materials [14, 25]. Generally, pyrometallrgy is sed for its wide application range and high level of efficiency. In contrast, hydrometallrgy is preferred when high prity prodcts are needed and emissions have to be limited [26]. Considering this paper, the refining process taken into accont is the hydrometallrgical one. However, the same economic principles can be sed to also assess other refining methods, withot twisting the overall vale of the work. Hydrometallrgy is the optimal choice to implement field and mobile plants, given both its high sstainability level in comparison to other metal refining methods and the flexibility level of related plants [27-29]. The mobile strctre presents a limited capacity bt can be easily transferred from one site to another. In contrast, the field one presents a greater capacity and can be sed to manage higher volmes. Figre 2 reports a seqence of flows characterizing a PCB recovery process. Qw+Qe are flows of PCBs and cases in which they are embedded. Qw are flows of PCBs entering the recovery process.

5 Sstainability 2016, 8, x 5 of 20 Qend are flows of cases leaving the process and Qhwd are flows of hazardos components directed to dedicated recovery plants. Q(lmpp) are flows of powders lost dring the shredding process. QP-rmat are flows of powders after shredding. QP-rnm are flows of nonmetal powders ending into landfills. QP-rmbr are flows of metal powders entering the refining process. After refining, QP-hrm are valable metals and QP-srm are low vale metals, both destined to be sold in the secondary material market. Q(lmrp) are materials lost dring chemical reactions. Figre 2. A typical printed circit board recovery process. Two kinds of plants (based on the same constrctive philosophy) are taken into accont: a mobile and a field one. Their horly prodctivity (ph) is set in tons/h and 0.3 tons/h (for mobile and field plants, respectively) [21, 30]: Q W = p h n h n d. (1) Frthermore, by considering a working period (nd) of 240 days and eight working hors per day (nh). According to Eqation (1), the plant sizes (Qw) are: 240 tons of powders/year (mobile plant); 576 tons of powders/year (field plant) Economic Model Disconted Cash Flow (DCF) is a well-known economic assessment method estimating the attractiveness of an investment opportnity and several economic indexes can be selected, as NPV and DPBT: NPV is defined as the sm of present vales of individal cash flows; DPBT represents the nmber of years needed to balance cmlative disconted cash flows and the initial investment. NPV does not consider the size of the plant. For this reason, the ratio between NPV and size of the recycling plant is proposed within this paper. A smmary of the main formlas constitting the original model [15] are reported below: NPV = n t = 0 (I t O t )/(1 + r) t (2)

6 Sstainability 2016, 8, x 6 of 20 n rm DPBT t = 0 (I t O t )/(1 + r) t = 0 (3) NPV/Size = NPV/QW (4) I t = j = 1 Q P srm,j pl rm pr rm,j,t, t = 1 n (5) C 2 s inv = C,2 s inv Q W (6) C 2 s lcs,t = C 2 s inv /n debt, t = 0 ndebt 1 (7) C 2 s lis,t = (C 2 s inv C 2 s lcs,t ) r d, t = 0 ndebt 1 (8) C inv = C, inv Q P rmbr (9) C lcs,t = C inv /n debt, t = 0 ndebt 1 (10) C lis,t = (C inv C lcs,t ) r d, t = 0 ndebt 1 (11) 0 t = C 2 s lcs,t + C 2 s lis,t + C lcs,t + C lcs,t + C a Q W + C l n d n 1 s op + C d Q hwd + C cm Q P rnm + C e (e 2 s /p h ) Q W + p i C 2 s inv + C l n d n 2 s op + p 2 s m C 2 s inv + C cm,t Q P hrm + C e e Q P rmbr + p i C inv + C l n d n op + p m C inv + C rem,t (1 + inf) + C tr (Q W + Q e ) d tf + ebt t C tax, t = 1 n (12) C t+1 = C t (1 + inf), t = 1 n (13) Within Eqations (2) (13), the 1 s apex identifies disassembly, the 2 s apex identifies treatment, and the apex identifies refinement Table 2. Table 2. Technical-Economic Nomenclatre ID Definition ID Definition Ca: Acqisition cost of WPCBs nop: Nmber of operators C a : Unitary acqisition cost of WPCB nrm: Nmber of recycled metals C cm : Unitary conferred material cost nnrm: Nmber of non-recycled metals C d : Unitary disposal cost NPV: Net present vale C e : Unitary electric power cost NPV/Size: Ratio between NPV and size Cinv: Investment cost Ot: Disconted cash otflows C inv : Unitary investment cost pe: % of envelope C l : Unitary labor cost p ed : % of dangeros envelope Clcs: Loan capital share cost ph: Horly prodctivity Clis: Loan interest share cost pi: % of insrance cost C rem : Unitary reactant materials cost pm: % of maintenance cost Ct: Cost in period t prm,j: % of metal j in 1 kg of WPCB C tax : Unitary taxes prnm: % of not metals in recycled materials

7 Sstainability 2016, 8, x 7 of 20 C tr : Unitary transportation cost of the plant plrm: Prity level of recycled metal dtf: Distances of transportation of the plant prrm: Price of recycled metal DPBT: Disconted payback time Qe: Qantity of envelope ebt: Earnings before taxes Q P hrm : Qantity of hazardos recycled Metal e: Energy power Qhwd: Qantity of hazardos waste It: Disconted cash inflows QP-rmbr: Qantity of powders (before refinement) inf: Rate of inflation QP-rnm: lmpp: Lost materials in treatment process QP-srm,j: Qantity of powders (recycled non- metals) Qantity of powders (selling recycled metal j) lmrp: Lost materials in refinement process QW: Qantity of WPCBs n: Lifetime of investment r: Opportnity cost nd: Nmber of days rd: Interest rate on loan ndebt: Period of loan t: Time of the cash flow nh: Nmber of hors The profitability of a recycling plant is hgely inflenced by two main variables: (i) the set of materials embedded in WPCBs (available from the literatre), and (ii) the plant capacity [15]. For this reason, the total nmber of sets of selected scenarios evalated within the paper are eight, or the combination of for WPCB grops (Cat1, Cat2, Cat3 and Cat4 WPCBs) as defined in Table 1 and two plant sizes (240 tons/year and 576 tons/year), as defined before. Finally, potential revenes coming from materials recovered by cases embedding PCBs (Qend) are not considered within this paper Economic and Technical Inpts Table 3 reports data abot economic and technical inpts of the model and Table 4 reports the initial assmptions abot the materials concentration taken directly from the literatre [24]. Inpt data show that a mobile plant investment cost is estimated in abot k 639, while a field plant is assmed to be abot k 1533 [21, 30-32]. Economy of scale is the main case of this difference, qantified in abot 29%. The recovered materials evalation occrs in fnction of historical trends of market prices, within a defined time-period. By taking into accont the Febrary 2015 Febrary 2016 timeframe as a reference, monthly observations were gathered from the most relevant websites focsed on raw materials exchanges [33, 34] Table 5. Table 3. Economic and technical inpts. Variable Vale Reference Variable Vale Reference C a 1195 /ton [21] nh 8 h [30] C cm 90 /ton [40] 1 s n op 1 i 2 ii [35] C d 325 /ton [21] 2 s n op 2 i 3 ii [21] C e 0.11 /kwh [21] n op 2 i 3 ii [21],2 s C inv 646 ii 913 i /ton [21, 30] nrm Table 4 [24], C inv 2740 ii 3860 i /ton [31, 32] nhrm Table 4 [24] C l 150 /day [41] nrnm Table4 [24] C rem 830 /ton [31] pe 70% [15] 36% [31] ped 5% [15] C tax

8 Sstainability 2016, 8, x 8 of 20 C tr 0.34 /(km ton) [42] ph i 0.3 ii ton/h [21, 30] 2 s e 50 i 141 ii kw [21] pi 2% [40] e 3.9 i 9.5 ii MWh/ton [31] 2 s p m 25% [43] dtf 0 ii 200 i km [31] p m 5% [32] inf 2% [36] prnm Table 4 [24] lmpp 20% [24] prm Table 4 [24] lmrp 5% [24] plrm 95% [24] n 5 i 10 ii year [30] prrm Table 5 [33, 34] nd 240 day [30] R 5% [36] ndebt 5 year [36] rd 4% [36] i = Mobile plant; ii = Field plant. Table 4. Characterization of materials embedded in printed circit boards (percentages) [24]. Cat1 WPCBs Cat2 WPCBs Cat3 WPCBs Cat4 WPCBs Selling materials (prm-nrm) Iron (Fe) Copper (C) Alminim (Al) Tin (Sn) Zinc (Zn) Silver (Ag) Gold (A) * Palladim (Pd) Beryllim (Be) Bismth (Bi) Chromim (Cr) Hazardos metals (prm-nhrm) Antimony (Sb) Arsenic (As) Bromine (Br) Cadmim (Cd) Chlorine (Cl) Lead (Pb) Nickel (Ni) Conferred materials (prnm-nrnm) Plastics Epoxy Ceramics Glass Others Liqid crystals * 0.003% of gold is eqal to 30 ppm, or 30 g of gold in 1 ton of WPCBs. Table 5. Materials market prices [33, 34]. nrm prrm ( /kg) prrm ( /kg) min-max Notes Copper (C) Since Jly, continosly nder 5 /kg Silver (Ag) Since Jly, within the 400/450 /kg range

9 Sstainability 2016, 8, x 9 of 20 Zinc (Zn) Since Agst, nder 1.8 /kg Tin (Sn) Since March, nder 16 /kg Beryllim (Be) 850 n.d. No commodity markets setting this price Chromim (Cr) Since April, nder 2 /kg Iron (Fe) Since September, nder 0.05 /kg Palladim (Pd) 18,000 13,900 24,500 Until May, over 22,000 /kg Alminim (Al) Since May, nder 1.6 /kg Bismth (Bi) Negative trend Gold (A) 33,300 31,200 36,600 Since May, nder 35,000; Positive trend After having defined the economic model strctre (and related inpt vales), all of the financial indexes sefl to assess the investment are estimated in Section Reslts Waste recycling processes represent not only an environmental protection action, bt also an economic opportnity. Here, it is possible to identify the bsiness plan reqired to define the investment s profitability. Table 6 presents some examples. Table 6. Bsiness plans for mobile plants. Bsiness Plan-Cat3 WPCBs (k ) Bsiness Plan Cat4 WPCBs (k ) Year It (Fe) It (C) It (Ag) It (A) It (Pd) It (Al) It (Be) It (Bi) It (Cr) It (Sn) It (Zn) It s C a,t s C l,t s C d,t s C lcs,t s C lis,t s C cm,t s C e,t s C i,t s C l,t s C m,t C lcs,t C lis,t C d,t C m,t C i,t C l,t C rem,t C e,t

10 Sstainability 2016, 8, x 10 of 20 C tr,t C tax,t Ot It-Ot DCF DCF As already presented in Section 3, eight scenarios are analysed within this work, and it is clear that the financial feasibility is verified only for two categories of WPCBs (Table 7). Table 7. Economic indexes baseline scenarios. Index Cat1 WPCBs Cat2 WPCBs Cat3 WPCBs Cat4 WPCBs Mobile plant (240 tons of powders/year) DPBT (year) >5 >5 1 >5 NPV (k ) NPV/QW ( /ton) , Field plant (576 tons of powders/year) DPBT (year) >10 > NPV (k ) , NPV/QW ( /ton) , Going into detail, positive reslts come from both Cat3 WPCBs (NPV eqal to k 29,140 and k 6413 in field and mobile plants, respectively), and Cat4 WPCBs, bt only for field plants (NPV eqal to k 1351). DPBT follows NPV vales, and it is eqal to one year for Cat3 WPCBs and two years for Cat4 WPCBs. This means that cash flows allow recovery of the investments already dring the initial period of activity. Field plants present a longer lifecycle than mobile plants (10 years ot of five years). This aspect, starting from eqal gross profits, explains the greater NPV (both in positive and negative terms). However, as explained in other papers [21, 37], mobile facilities can represent an ideal soltion for small contries or cities, where volmes are limited. The obtained reslts confirm that the profitability is not always verified (see Section 2). Frthermore, in comparison to the atomotive sector, vales coming from WEEE are lower, given their limited gold amont ( ppm in the atomotive PCBs [45], ppm in WEEE PCBs). However, DPBT is confirmed by this stdy. Abot the gold relevance among revene items, data showed in Table 8 are significant (eqal for both the plant configrations). 415 ppm of gold are estimated for Cat3 WPCBs (max vale, acconting for 72% of revenes), and 20 ppm of gold are estimated in Cat2 WPCBS (min vale, acconting for 32% of revenes) representing the main profitability items. Among other materials, particlarly interesting is the inflence of palladim (with a high market price), and copper (present in a high percentage). Table 8. Plant revene distribtion (percentages). Index Cat1 WPCBs Cat2 WPCBs Cat3 WPCBs Cat4 WPCBs Gold (A) Copper (C) Palladim (Pd) Tin (Sn) Silver (Ag) Other metals

11 Sstainability 2016, 8, x 11 of 20 The cost distribtion analysis shows that operational costs are eqal to 94% of the overall costs for a field plant and 87% for a mobile one (Table 9). These reslts are coherent to what proposed by other works [15, 32]. The most relevant cost item is represented by WPCB prchasing, for both field and mobile plants (42% and 34%, respectively). This vale is followed by labor costs (18% and 21%, respectively). Finally, transportation costs are eqal to 6.5% in a mobile plant. Table 9. Plant cost distribtion (percentages) average vales. Index Field Plant Mobile Plant Acqisition Labor Energy 14 5 Reactant materials 9 8 Maintenance 7 8 Investment 6 13 Transport 0 7 Other items 4 4 Given the strctre of the presented economic model (see Section 3.3), it is easily possible to extend the analysis to other case stdies. In order to strengthen the obtained reslts, a sensitivity analysis comparing alternative scenarios is implemented in the next section. 5. Sensitivity Analysis The obtained reslts are related to hypotheses on inpt variables. Hence, a strong variance of the expected economic profitability cold occr. This limit can be overtaken by implementing a sensitivity analysis on the following critical variables [15] (Tables 10 and 11): The material content, as a percentage of a WPCB total weight for all the for categories. This variable is already analysed and for WPCB categories are evalated within this paper. The materials market price is evalated for three materials that, more than others, impact revenes (see Table 8), or gold, palladim and copper. Pessimistic and optimistic scenarios are analysed, by increasing (or decreasing) the initial price by its extreme vales (31,200 36,600 /kg for gold, 13,900 24,500 /kg for palladim and /kg for copper respectively). The final prity level is applied only to gold de to its high relevance on revenes. For pessimistic scenarios are analysed, with prity levels decreased within the range 60% 90% in comparison to the initial vale of 95%. The WPCB prchasing cost, representing the main cost item (see Table 9). Pessimistic and optimistic scenarios are assessed, with cost variations between 1000 /ton p to 1400 /ton (or an offset of abot 200 /ton from the baseline scenario); The plant satration, in which a lower amont of WPCBs in inpt represents a lower horly prodctivity. To this aim, five pessimistic scenarios are assessed, with satration levels going from 50% p to 90%. For example, by considering a mobile plant, 90% of 240 tons per hor is eqal to 216 tons per hor. Instead, by considering a field plant, 90% of 576 tons per hor is eqal to 518 tons per hor; The opportnity cost, able to evalate the money vale in different periods. Even in this case, an optimistic and pessimistic scenarios are assessed, with vales varying from 4% p to 6%; Table 10. Sensitivity analysis Net present vale (k ) in field plants. Variable Vale Cat1 WPCBs Cat2 WPCBs Cat3 WPCBs Cat4 WPCBs 36, , pra ( /kg) 31, , prpd ( /kg) 24, ,

12 Sstainability 2016, 8, x 12 of 20 prc ( /kg) pla (%) C a ( /t) QW (t) r (%) 13, , , , , , , , , , , , , , , , , Table 11. Sensitivity analysis Net present vale (k ) in mobile plants. Variable Vale Cat1 WPCBs Cat2 WPCBs Cat3 WPCBs Cat4 WPCBs pra ( /kg) 36, , prpd ( /kg) 24, , prc ( /kg) pla (%) C a ( /t) QW (t) r (%) These vales confirm that, sometimes, the profitability is not verified. In particlar, field plants treating Cat4 WPCBs become nprofitable when the gold prity level falls to 80%, or when the satration level reaches 60%. More in general: NPV is always negative with mobile and field plants treating Cat1 and Cat2 WPCBs; NPV is always positive with mobile and field plants treating Cat3 WPCBs; NPV is always negative with mobile plants treating Cat4 WPCBs and almost positive with field plants (14 scenarios ot of 19). Higher vales of NPV can be reached in both the plant configrations when the satration level reaches 50% for WPCBs pertaining to Cat1 and Cat2 grops (k 959 and k 1025, respectively, for the mobile plant, k 2914 and k 3195, respectively, for the field plant), when the gold market price reaches 36,600 /kg for WPCBs pertaining to Cat3 grop (k 7085 and k 32,019 respectively for

13 Sstainability 2016, 8, x 13 of 20 mobile and field plants) and when the WPCB prchasing cost reaches 1000 /ton for Cat4 grop (k 78 and k 1393, respectively, for mobile and field plants). Lower vales of NPV can occr in mobile plants when the gold prity level reaches 60% for WPCBs pertaining to Cat1, Cat2 and Cat4 grops (k 1804, k 1875 and k 1050, respectively), and with a satration level of 50% for WPCBs pertaining to Cat3 (k 2942 ). Instead, lower vales of NPV are present in field plants with gold prity level of abot 60% for Cat1 and Cat4 WPCBs (k 4905 and k 1374, respectively), when the WPCB prchasing cost reaches 1400 /ton for Cat2 WPCBs (k 5459) and with a satration level of 50% for Cat3 WPCBs (k 13,781). The sensitivity analysis allows for analysis of several alternative scenarios, in which decision makers can evalate different NPV vales. No probabilities are assigned to each scenario, bt real changes concerning the following critical variables are considered: Secondary materials market price can be sbjected to great oscillations (see trends proposed in Table 5) reaching maximm variations for precios metals (e.g., gold and palladim). Gold prity level cold fall de to low performing technologies. In fact, the selection of the recycling process is connected to mltiple parameters and technological soltions are able to favor environmental or economic performances or both [46,47]. WPCB prchasing costs can differ becase of the different material composition of cores. This isse is not well analysed in the literatre [14, 38]. In particlar, this cost can be inflenced by several aspects sch as: (i) spply chain dimension (short or long ones); (ii) type of PCBs (low, medim or high grade ones); and (iii) PCB volmes. Plant satration level is strictly linked to the historical prodctive capacity and the actal working hors. However, a key role is played by the difference between generated and collected volmes [49]. They depend by for aspects: (i) illegal flows; (ii) no attention of citizens towards environmental problems; (iii) absence of reglations; and (iv) inadeqate nmber (or location) of collection centres. Opportnity cost of capital can change becase of either the effect of macro-economic conditions related to the specific nation or the natre of investors (private or pblic capitals) [36]. This section proposed a more complete overview on profitability coming from mono-core plants. The sbseqent section offers an assessment on the economic impact related to the recovery of these wastes in three main Eropean WEEE markets. 6. Assessment of National Economic Potentials and Eropean Ftre Trends The development of the recycling sector concerns all the Eropean contries. A significant amont of potential secondary raw materials is crrently lost and the application of EoL strategies accelerated the transition towards a circlar economy Economic Potential of the German, Italian and English WEEE Markets This section evalates the economic potential coming from the recovery of WPCBs embedded in WEEE collected from hoseholds in Germany, Italy and the United Kingdom. Potential vales are obtained by mltiplying the economic vale proposed in Table 7 and the related volmes estimated in Starting from WEEE volmes from hoseholds presented in Table 1, WPCB volmes are calclated. To this aim, the fractional weight of WPCBs (ot of the overall WEEE weight) are defined. Estimated vales are 0.4%, 0.5%, 13% and 11% for Cat1, Cat2, Cat3 and Cat4 WPCBs, respectively [24]. Table 12 proposes total NPV for both the types of plants and the three contries in For example, total NPV for Germany is eqal to abot 777 million by considering only field plants. This vale can be calclated as follows: 0.4% 248,618 ( 7382) + 0.5% 76,331 ( 8354) + 13% 116,681 (50,590) + 11% 132,931 (1351) = k 776,601.

14 Sstainability 2016, 8, x 14 of 20 Table 12. Total NPV (k ) in three Eropean contries in Contries Field Plant Mobile Plant Germany 776, ,042 Italy 217, ,870 The United Kingdom 871, ,163 EU-28 3,442,084 1,698,762 The profitability is always verified and it depends on both the presence of Cat3 WPCBs (49% in Germany, 38% in Italy, 78% in the United Kingdom and 48% in EU-28) and the qasi-absence of Cat1 and Cat2 WPCBs within the related fractional mix (varying from 4% p to 6%). The Eropean economic potential related to the recovery of WPCBs embedded in WEEE collected from hoseholds is estimated in 3442 million in a scenario with only field plants and 1699 million in a scenario with only mobile ones. The United Kingdom and Germany present relevant reslts and they represent almost 48% of the overall Eropean economic vales. In contrast, Italy even if constitting one of the main nations generating WEEE in Erope (see Table 1) has very low volmes becase of the different classifications followed by its government. This way, a direct comparison with performances reached by other nations has low/no sense. Frthermore, the selection between mobile and field plants is related to each nation. Given national WEEE volmes, WEEE mix and poplation density estimates within a particlar territory, an evalation abot the best type of plant to be constrcted is possible. Generally, mobile plants are preferred when poplation density (and related WEEE volmes) are low. This way, the chance to transfer the plant into different sites allows to reach a higher satration level and to take into accont different WEEE mixes. When poplation density (and related WEEE volmes) increases, the selection of a field plant is preferable. This way, the economy of scale allows a better distribtion of costs and enables a faster recovery of the initial investment. However, these considerations are only theoretical and great relevance is associated to WEEE collection trends. These reslts mst be verified with optimization models (both economic and environmental ones) in ftre research Ftre Trends in the Eropean WEEE Market An estimate of the potential dimension of the WEEE PCB recycling market in the near ftre is a sefl tool for decision makers. To that aim, the overall amont of expected WEEE collected from hoseholds from 2015 p to 2030 can be predicted. Within Erostat, 2013 is the most pdated year, presenting data for Erope; 2015 is the crrent year; and 2020 and 2030 are the years taken into accont by Erope as reference targets. Growth rates are hypothesized to be eqal to 3% per year [23], eqally increasing for each of the for WPCB categories [15]. Table 12 proposes the expected profits coming from the correct management of these amonts of WPCBs. Minimm and maximm vales are associated to mobile and field plants, respectively. The estimated PCB volmes are obtained by considering that WPCB weights impact abot 5% (on average) of the overall weight of a generic WEEE (Table 1 [24]). Considering an amont of WEEE eqal to 2,907,222 tons in the EU-28 (see Table 1) for the only Cat1, Cat2, Cat3 and Cat4 categories, it is possible to define the qantity of related WPCBs, estimated to be eqal to 145,361 tons. By considering the Eropean average mix, mobile and field plant vales are eqal to 11,686 per ton (obtained by dividing k 1,698,762 and 145,361 tons) and 23,680 per ton (obtained by dividing k 3,442,084 and 145,361 tons). These vales refers to Total WPCB expected NPV is eqal to 1895 million in 2015 for mobile plants (obtained by mltiplying 11,686 per ton and 162 ktons). Frthermore, it is important to clarify that Table 12 vales refers to the first for WEEE categories (ot of ten). Instead, Table 13 refers to the overall volmes coming from all of the ten WEEE categories together and considering the percentage mix of EU-28.

15 Sstainability 2016, 8, x 15 of 20 Table 13. Estimates of collected WPCB volmes and profits in 28 Eropean contries from WEEE collected from hoseholds WEEE expected annal collection (ktons) WPCB expected annal collection (ktons) Total WPCB expected NPV min vales (M ) Total WPCB expected NPV max vales (M ) Estimates on profits in 28 Eropean contries from WEEE PCB recycling are relevant, going from 1.79 billion to 3.62 billion in Ftre trends define 2.95 billion as minimm vale and 5.98 billion as maximm vale in This difference depends on the development level of field and/or mobile plants. In addition, 2013 data are directly dependent from Erostat data and can give an immediate idea of the crrent dimension of the sector. In contrast, 2030 data are only an estimate, bt they allow for comprehension of how the sitation cold evolve with the crrent expected trends. Obviosly, these vales will depend from the mix of mobile and field plants that will be implemented dring the next years. However, qantitative data abot the probability of implementation of these two kinds of plants is information absent in the literatre. Finally, these vales demonstrate once again that the development of a circlar economy based on the exploitation of both critical materials and resorces recovered from WEEE is important and cold offer interesting revenesto indstrial companies. 7. Discssion The previos Sections 4 6 represent the core part of the paper and they proceed to assess the three main objectives of the paper. Information gathered from these previos sections allow for responding to the three main targets listed in Section 1, as follows: The profitability assessment of PCB recovery processes; The evalation of alternative scenarios throgh a sensitivity analysis; The estimation of ftre profitability trends in three selected Eropean nations. Considering the first point, NPV and DPBT vales reported in Table 7 show that positive reslts are related especially to the chance to recover only some specific types of WEEE, in particlar Cat3 and Cat4. These two grops allow for recovery of high amonts of critical and precios materials and garantee interesting revenes (at least in theory) shortening the payback time. In addition, the se of mobile or field plants does not inflence the most remnerable types of WEEE to be treated. The decision to se one or the other is only a qestion of potentially manageable volmes. One point favoring mobile plants is that they cold enable several small medim enterprises to work together, bypassing bigger recyclers and secondary materials processes. This way, they can reach the qantities of recovered materials needed to compete in the market, whilst minimizing the investments needed. The presented reslts are in line with the ones described by the experts within the scientific literatre [21, 27, 29, 37]. However, it is important to point ot that a direct comparison with the reslts coming from the literatre is not possible de to two reasons. First, the literatre generally considers the recovery of an entire WEEE and not only PCBs. This way, the materials characterization can vary a lot. Second, papers describing WEEE consider all ten categories and not only the for categories taken into accont in this paper. Another element to point ot is the comparison between mobile and field plant performance. It is ot of the scope of this paper to decide if it is better to se either a mobile or a field plant. The aim of the athors is the only assessment of their economic indexes to spport the critical decision abot whether to invest in these types of plants. Considering the second point, the role of several critical variables on the overall economic reslts that cold be reached by the two different plants is clear. Given their lower capacity in comparison

16 Sstainability 2016, 8, x 16 of 20 with field plants, mobile plants are more ssceptible to strong variations of these variables. This means that, in the case of low WEEE volmes, the plant performance mst be very high, exploiting state-of-the-art technologies and always trying to satrate the available capacity. Only in this way can companies implement mobile recovery plants protect themselves from exogenos oscillations coming from the raw materials market. Considering the third point, data show as Italy, in comparison with Germany and the United Kingdom, needs to do a lot of work to reach the Eropean average regarding WEEE collected volmes and improve the overall WEEE recovery chain performance. However, a direct comparison of Italy and other Eropean contries is not completely possible, given the different WEEE classification adopted. However, even the comparison between Germany and the United Kingdom offers some interesting points of discssion. Even if Germany presents higher WEEE volmes, the United Kingdom thanks to a higher presence of Cat3 and Cat4 WEEE in its mix is the Eropean nation with the highest NPV among the three contries taken into accont. This reslt has vale whatever the type of plant taken into accont. Once again, the importance of the national WEEE mix is highlighted. Another important point related to these two nations is the presence of already established sites focsed on the recovery of materials, generally owned by mltinational companies, like Arbis (Smethwick - United Kingdom), Umicore (Hoboken - Belgim), SIMS (Stratford-pon Avon - United Kingdom) and Boliden (Stockholm - Sweden). Given their dimensions, these plants, generally big field ones, are able to take into accont relevant qantities of WEEE. This cold represent an isse for the implementation of new plants. However, the economic impact given by these already existing plants is not measrable, given the absence of data in the literatre abot their physical and economic characteristics. 8. Conclsions Great qantities of WEEE are thrown away worldwide every year. The literatre defines WPCBs as the most complex, hazardos, and valable elements in e-waste. However, the economic evalation of recovery process of WEEE PCBs is not well analysed. This paper tries to cover this gap. The profitability of both mobile (240 tons of powders per year) and field plants (576 of powders per year) considering for WPCB grops (large hosehold appliances (Cat1), small hosehold appliances (Cat2), IT and telecommnications eqipment (Cat3) and consmer eqipment (Cat4) are evalated. Three main points can be discssed. First, the recovery of materials from WEEE PCB recycling processes can be environmentally sstainable, according to the WEEE Directive, while the economic sstainability is verified only for some categories of WEEE. In a baseline scenario, NPV is positive in both the plant configrations treating Cat3 WPCBs (eqal to k 6413 and k 29,140 in mobile and field plants, respectively) and in field plants treating Cat4 WPCBs (eqal to k 778). DPBT confirms this assessment, varying from one to two years in profitable scenarios. From the revene side, gold plays a key role, followed by palladim and copper. From the costs side, there are low investment costs, and the most relevant item is represented by WPCB prchasing. The evalation of specific prodcts represents the following step. The material characterization of PCBs can vary significantly. A soltion can be represented by mlti-core plants, in which the lower profits are balanced by higher satration levels. As highlighted within this paper, a qantitative analysis can spport the choice from this side. Second, the evalation of alternative scenarios allows for confirmation of the obtained reslts. From one side, the profitability is garanteed for Cat3 WPCBs and both the plant configrations and for Cat4 WPCBs considering field plants in several scenarios. From the other side, NPV is negative for Cat1 WPCBs and Cat2 WPCBs in both the plant configrations and for Cat4 WPCBs in mobile plants. Satration level, gold market price, WPCB prchasing cost and gold prity level prodce the most significant variations in fnctions of both plant configrations and WEEE categories taken into

17 Sstainability 2016, 8, x 17 of 20 accont. This analysis is a relevant phase in an Engineering Economics framework, and it provides a snapshot that aims to redce the sbjectivity of the initial choice of inpts. However, only vales defined in other scientific works are proposed within this paper. Third, the economic potential related to the recovery of WPCBs embedded into WEEE collected from hoseholds in EU-28 is estimated in 3619 million in a scenario with only field plants and 1786 million in a scenario with only mobile ones in The United Kingdom and Germany represent almost 48% of these vales. Germany has greater WEEE volmes than the United Kingdom, bt this last contry presents better economic performance de to the high presence of medim-high grade PCBs within its mix. Ftre trends concerning the Eropean market show very interesting vales and NPV varies from 2952 million to 5982 million in Materials and metals are present in many energy and material prodction processes and their recoveries play a key role in the development of circlar economy. Reslts obtained in this paper confirm the advantage in economic terms. The recycling of WPCBs is an important topic not only in terms of waste treatment bt also in terms of valable material recovery. Natral resorces are essential and critical components of the modern society. This activity increases the sstainability of a contry and policy-makers, and citizens and firms can cooperate in order to make WEEE a resorce and not a problem. Acknowledgments: All sorces of fnding of the stdy shold be disclosed. Please clearly indicate grants that yo have received in spport of yor research work. Clearly state if yo received fnds for covering the costs to pblish in open access. Athor Contribtions: The athors eqally gave their contribtion to this work. Mr. D Adamo designed the research and analysed the data; Mr. Rosa performed part of the research and wrote the draft paper; Dr. Terzi performed part of the research and finalized writing of the paper. Conflicts of Interest: The athors declare no conflict of interest. Abbreviations A C a Cat1 Cat2 Cat3 Cat4 C DCF DPBT EEEs NPV PCBs Pd PlA prrm QW r WEEE WPCBs Gold Unitary acqisition cost of WPCB Large hosehold appliances Small hosehold appliances IT and telecommnications eqipment Consmer eqipment Copper Disconted cash flow Disconted payback time Electrical and electronic eqipment Net present vale Printed circit boards Palladim Prity level of recycled metal (gold) Price of recycled metal (gold, palladim, copper) Qantity of WPCBs Opportnity cost Waste electrical and electronic Waste printed circit boards References 1. Barletta, I.; Larborn, J.; Mani, M.; Johannson, B. Towards an Assessment Methodology to Spport Decision Making for Sstainable Electronic Waste Management Systems: Atomatic Sorting Technology. Sstainability 2016, 8, 84.