Economic evaluation of an electrochemical process for the recovery of metals from electronic waste

Waste Management xxx (2017) xxx–xxx

Contents lists available at ScienceDirect

Waste Management journal homepage: www.elsevier.com/locate/wasman

Economic evaluation of an electrochemical process for the recovery of metals from electronic waste Luis A. Diaz, Tedd E. Lister ⇑ Biological and Chemical Processing Department, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 38415-3731, USA

a r t i c l e

i n f o

Article history: Received 14 September 2017 Revised 21 November 2017 Accepted 27 November 2017 Available online xxxx Keywords: Electronic waste Recycling Economic analysis Smelting Electrometallurgy

a b s t r a c t As the market of electronic devices continues to evolve, the waste stream generated from antiquated technology is increasingly view as an alternative to substitute primary sources of critical a value metals. Nevertheless, the sustainable recovery of materials can only be achieved by environmentally friendly processes that are economically competitive with the extraction from mineral ores. Hence, This paper presents the techno-economic assessment for a comprehensive process for the recovery of metals and critical materials from e-waste, which is based in an electrochemical recovery (ER) technology. Economic comparison is performed with the treatment of e-waste via smelting, which is currently the primary route for recycling metals from electronics. Results indicate that the electrochemical recovery process is a competitive alternative for the recovery of value from electronic waste when compared with the traditional black Cu smelting process. A significantly lower capital investment, 2.9 kg e-waste per dollar of capital investment, can be achieved with the ER process vs. 1.3 kg per dollar in the black Cu smelting process. Ó 2017 Elsevier Ltd. All rights reserved.

1. Introduction The growing sales of small short-lived electronic devices is resulting in a significant stream of electronic scrap containing a wide variety of technology metals. These devices, which eventually become electronic waste (e-waste), are an important resource that could be leveraged to produce a sustainable supply chain for scarce and critical materials (Baldé et al., 2015; Dodson et al., 2012). The diversity of elements, in concentrations exceeding those found in mineral ores (Akcil et al., 2015), reveals an economic opportunity for the recovery of different value streams. Extensive research efforts are currently under development for the recovery of precious metals (Ag, Pd, and Au) and base metals (Cu, Sn, Pb, Ni, and Zn), for both economic and waste management purposes (Sun et al., 2015). Small information technology (IT) waste, such as cell phones, personal computers, tablets, etc., is one of the six different ewaste categories, which is showing the most accelerated growth driven by changes in consumer habits and rapid technology developments (Geyer and Doctori Blass, 2010). Others e-waste categories are temperature exchange equipment, screens, lamps, large equipment, and small equipment (Baldé et al., 2015). Based

⇑ Corresponding author. E-mail address: [email protected] (T.E. Lister).

on the data presented in the Global E-Waste Monitor 2014 (Baldé et al., 2015), it can be estimated that almost 707 kt of small IT e-waste were generated in the United States alone during 2014. In addition to precious and base metals, small IT waste contains low but significant quantities of materials that are considered critical for the renewable energy sector and the manufacturing of new IT products (DOE, 2011; Tukker, 2014). Rare earth elements (REE) such as Nd, Pr, Dy, and Gd, can be found and recovered from speakers, hard disk drives, and vibrators (Lister et al., 2014; Tukker, 2014). However, The compact design of the small IT waste makes it the most difficult e-waste category for recycling (Zeng and Li, 2016).

1.1. Current e-waste management technologies Despite significant increases in the recycling of e-waste in the United States, which was estimated to increase from 37.8 to 41.7% between 2013 and 2014 (EPA, 2016), the majority of the ewaste is still retained by the end consumers and/or disposed in landfills. The development of an effective collection system would be necessary to assure a full advantage of the recoverable value of the e-waste (Geyer and Doctori Blass, 2010). For the recycled fraction, existing metal recovery technologies are based on pyrometallurgy, hydrometallurgy, or combinations of both process (Hagelüken, 2006a). Under western environmental standards

https://doi.org/10.1016/j.wasman.2017.11.050 0956-053X/Ó 2017 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Diaz, L.A., Lister, T.E. Economic evaluation of an electrochemical process for the recovery of metals from electronic waste. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.050

2

L.A. Diaz, T.E. Lister / Waste Management xxx (2017) xxx–xxx

smelting appears to be the primary recovery method employed (Cui and Zhang, 2008; Tuncuk et al., 2012). While currently performed primarly in large smelters in Europe and Asia, research continues to seek cleaner methods as presented in recent reviews on the subject (Cui and Zhang, 2008; Ghosh et al., 2015; Kaya, 2016). Modern smelters take advantage of the organic load (polymers) in the e-waste to reduce the consumption of coke as energy and reducing agent in the smelting process (Hagelüken, 2006a). Metals such as copper and lead are being recovered via pyrometallurgical routes, while hydrometallurgical processes are used at the back-end for the extraction and refining of precious metals (Hagelüken, 2006b). Umicore’s integrated metals smelter and refinery plant in Belgium is one example of an operating Pb/Cu/ Ni pyrometallurgical based process with a total capacity of 250 kt of feedstock that includes but is not limited to printed circuit boards and electronic components. This plant produces Au, Ag, platinum group metals (Pd, Pt, Rh, Ir, Ru), special metals (Se, Te, In), secondary metals (Sb, As, Bi), and base metals (Cu, Sn, Pb, Ni) as value streams (Hagelüken, 2006b; Khaliq et al., 2014). Several challenges exist for the processing of e-waste in smelting facilities. Among them are high energy consumption, large capital costs, and hazardous emissions of dioxins generated from the presence of halogenated flame retardants in the e-waste (Hagelüken, 2006a; Khaliq et al., 2014). In order to comply with dioxin emission regulations, an additional capital investment is required for smelting facilities (Hagelüken, 2006a; Hagelüken, 2006b). Smelters that use feedstock composed of pyrite (FeS2), such as the lead smelters, can significantly reduce dioxin emissions from e-waste (Mukherjee et al., 2016). However, the copper produced as matte in lead smelters steel needs to be refined through black copper smelting (Khaliq et al., 2014). This problem limits processing of electronic waste to existing smelters. Therefore, large scale operation plants are required for the financial sustainability of the pyrometallurgical process (Ghodrat et al., 2016; Hagelüken, 2006a). Hydrometallurgical processes are often described as a cleaner and less expensive alternative to pyrometallurgy, which can be implemented at smaller scales (Tuncuk et al., 2012). However, high operational costs and a significant environmental impact come as a result of the slow processing rates, high liquid to solid ratio (ratio of leaching solution to solid waste), and extensive use of chemicals. These problems are caused by the complex elemental distribution of metals in the e-waste where over 80% of the total recovery value is held in the precious metals, which are less than 1% of the total metal content (Diaz et al., 2016; Vats and Singh, 2015). Thereby, the hydrometallurgical processing of e-waste requires extensive consumption of chemicals for the removal of the less noble metal content, which are higher in quantity but have limited contribution to the total recoverable value (Diaz et al., 2016). Moreover, the presence of metals like copper, which consume the oxidants required for the extraction of precious metals, makes necessary the removal of such metals before the precious metals extraction (Torres and Lapidus, 2016). 1.2. Electro-recycling (ER) as alternative process In order to address some of previously mentioned issues associated with the current metal recovery processes, an electrochemi cal-hydrometallurgical mediated approach has been proposed by (Diaz et al., 2016; Lister et al., 2014). In the (ER) process a weak oxidant (Fe3+), is continuously regenerated at the anode of an electrochemical cell (Eq. (1)), and used for the extraction of base metals in an external extraction column (Eq. (2)) (Lister et al., 2014). The solution with the reduced oxidant and the leached metals is then returned to the cathode side of the electrochemical cell, where the leached metals are recovered (Eq. (3)). A more detailed descrip-

tion of the ER process can be found elsewhere (Diaz et al., 2017; Diaz et al., 2016; Lister et al., 2016; Nguyen et al., 2017). The ER technology has been developed as an alternative to reduce chemical consumption and enrich the e-waste material for the further extraction and recovery of precious metals. In a comprehensive approach, with the addition of physical separation steps, REE can also be recovered as a separated value stream (Diaz et al., 2016).

Fe2þ ! Fe3þ þ e 3þ

nFe

nþ

M

þM!M

nþ



þ ne ! M

E0 ¼ 0:771 V vs: SHE þ nFe2þ

ð1Þ ð2Þ ð3Þ

Although the technical viability of the ER process has been demonstrated, an economic analysis is necessary, in every development stage, to assess the economic feasibility as the main factor to determine the project continuation and to establish performance targets. In the early stage, there are several factors that that could affect the project financial behavior, which cannot be known with any certainty. Therefore, one of the best ways to evaluate early development technologies is by comparison with competing processes or alternatives (Smith, 2005). For the processing of e-waste, the pyrometallurgical route has being identified as the alternative technology for which the ER process would need to demonstrate economic competitiveness in order to be implemented. While detailed data on operating smelters is not widely available, limited data exists on the process economics of smelting electronics with copper. Ghodrat et al. recently presented a technoeconomic analysis (TEA) for black copper smelting (BCS) using ewaste as co-feedstock (Ghodrat et al., 2016). In this work, the authors demonstrated that the economic viability of the process is mostly affected by the cost of the e-waste along with process capacity. The minimum viable smelting operation requires an annual throughput of 30 kt/year (48% of which corresponds to ewaste). For the TEA, the mass and energy balances were completely supported on thermodynamic calculations. A second paper, by the same research group, extended the information on the thermodynamic analysis for the processing of e-waste through the BCS route (Ghodrat et al., 2017). In order to evaluate the economic feasibility of the ER process, this paper presents a TEA and a comparison of the value recovery from e-waste through the ER and BCS routes. A base scenario of 20 kt/year of cell phone material is considered to assess the processing of small IT waste. Sensitivity analyses are used to account for the effect of plant size, TEA assumptions, and uncertainties such as operational costs and precious metals recovery efficiencies. A brief description of the extraction steps of the process is presented, as well as the analysis of the ER process effect on operational costs and economic feasibility of the process.

2. Methodology Process flow diagrams (Figs. 1 and 2 for Cu smelting and ER process, respectively) were established for comprehensive e-waste processing that includes comminution, separation, and the recovery of value streams of metals and critical materials (including REEs) from scrap mobile electronics. Mass and energy balances for the BCS route were based on the information presented by Ghodrat et al. (2016, 2017), but adjusted to the composition of cell phone waste presented in Diaz et al. (2016). Mass and energy balances for the ER process were obtained from experimental data reported elsewhere (Diaz et al., 2017, 2016). A brief description of the BCS route and the ER process is presented below. The REE extraction and recovery route, which is identical for both processing routes is also described.

Please cite this article in press as: Diaz, L.A., Lister, T.E. Economic evaluation of an electrochemical process for the recovery of metals from electronic waste. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.050

3

L.A. Diaz, T.E. Lister / Waste Management xxx (2017) xxx–xxx

Magnetic Fraction 11.1 t/day

SC-1

BH-1

E-waste 54.8 t/day

Enriched air 25.12 t/day Coal 0.6 t/day

Electro Refining ER-1

Exhaust +dust 74.9 t/day

SS-1

FCS slag 3.1 t/day

Electrolyte 20.7 t/day Off gas 76.4 t/day

Exhaust gas + Oxide dust 32.8 t/day E-waste 43.7 t/day Cu scrap 44.2 t/day

Electrolyte to Purification 20.6 t/day

Reducon Furnace F-1

Black Cu 47.5 t/day

Oxidaon Furnace F-2

Anode Cu 37.8 t/day

Enriched air Red-slag 68.9 t/day + SSO 36.4 t/day Coal 13.3 t/day

Fire Refining F-3

Natural Gas 5.8 t/day Air 69.9 t/day

Anode Cu 37.2 t/day

Cu 99.9% 37 t/day

Slimes 0.37 t/day Precious Metals refining

Gangue 0.37 t/day

HCl 2.7 t/day Water 26.5 t/day

Steel scrap 10.3 t/day

R-3

Na2SO4 0.3 t/day Water 0.9 t/day NaOH 0.073 t/day

R-4

Au 25.3 kg/day Ag 115.7 kg/day

O-1 REO3 93 kg/day

Flux FCS 4.1 t/day Fig. 1. Process flow diagram of the e-waste processing through BCS route.

Fig. 2. Process flow diagram of the e-waste processing through the ER process.

2.1. Processes description 2.1.1. Black copper smelting The BCS route is applied to recover copper from scrap with considerable content of metal impurities such as, Fe, Pb, Zn, Sn, and oxides (Anindya et al., 2013). In the first stage, crude Cu is obtained by reduction with coal or coke at temperature ca. 1300 °C. Metal impurities are then segregated from the Cu crude as slag and oxide dust in the following oxidation stage with oxygen enriched air. Although reduction and oxidation can be performed in the same smelting furnace, high throughput plants require separate furnaces to achieve stable operation (Ghodrat et al., 2016). The final stage involves the reduction of the oxygen content on the molten Cu phase and the formation of a Cu anode (99 wt% purity) using natural gas as reducing agent. Precious metals remain on the Cu anode

to be recovered after electrorefining (Moskalyk and Alfantazi, 2003). An electrorefining process is required to obtain high grade copper with purity >99.9 wt%. Cu is oxidized on the formed anode and reduced on a pure Cu cathode at low currents (controlled potential). Metals more noble than Cu do not oxidize, getting released as anode slimes as the Cu anode dissolves. Metals less noble than Cu will be dissolved from the Cu anode but will not reduce in the cathode as more negative potentials are required. Specific energy consumptions for the electrorefining process is estimated ca. 0.31 kWh/kg (Pletcher and Walsh, 2012). Precious metals such as Au and Ag can then be refined from the anode slimes (Amer, 2003). Precious metals recoveries for the BCS route are assumed to be 96.5% and 88.5% for Au and Ag, respectively, as reported by Ghodrat et al. (2016, 2017). However, it should be mentioned, as

Please cite this article in press as: Diaz, L.A., Lister, T.E. Economic evaluation of an electrochemical process for the recovery of metals from electronic waste. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.050

4

L.A. Diaz, T.E. Lister / Waste Management xxx (2017) xxx–xxx

it is reported in these publications, that these values do not correspond to thermodynamic calculation but rather literature and industry databases. No information was found for the recovery efficiencies of Pd from anode slimes; therefore, the economic analysis does not include Pd recovery. 2.1.2. ER process After separation of the ferromagnetic fraction, the milled nonmagnetic fraction of small IT waste is packed in a series of extraction columns. A mild oxidant (Fe3+) is generated in the anode of an electrochemical reactor from a 0.6 M FeCl2 solution in 0.5 M HCl. The leaching solution is fed to the bottom of the first packed column, in a series of three, to oxidize the base metals without attacking precious metals like Au and Pd. Galvanic reactions among the metals present in the e-waste define the metal ions exiting the column such that the least noble metals are first to leave (Diaz et al., 2016). The mass transfer zone moves through the packed columns, therefore, the first column in the series can be replaced by the next column on the series after base metals depletion, and a new fresh column can be added at the end of the series allowing a semicontinuous operation. The metal rich solution leaving the columns is directed back to the cathode side of the electrochemical cell where the extracted material is electrowon. The metal powder, product of the ER process, has a composition similar to that found in bronze or tin bronze. The oxidizer can be continuously regenerated, which represents a significant decrease in chemicals consumption. Although Ag can also be oxidized by Fe3+, most of the silver is retained in the columns as AgCl, which can be selectively recovered by complexation with Na2S2O3 reaching recovery efficiencies as high as 82% (Lister et al., 2016). Precious metals such as Au and Pd can then be recovered with the minimum chemical consumption by means of hydrometallurgical methods (Akcil et al., 2015; Behnamfard et al., 2013). The Au recovery was assumed as 96.5%, as in the Cu smelting process, for the base-case scenario but included in the sensitivity analysis because Au extraction and recovery optimization is still under progress. Note that Pd was excluded from the economic analysis to be consistent with the assumption made for the Cu smelting route. 2.2. Rare earths extraction and recovery For a comprehensive process, REE recovery has been included, in a parallel process after the magnetic separation of milled ewaste, as additional revenue for the ER and BCS routes (Figs. 1 and 2). The REE extraction takes place in an acidic environment where the REEs present in the ferromagnetic fraction of the small IT e-waste are selectively dissolved. After dissolution in dilute acid, the rare earth content is recovered as a precipitate (NaRE(SO4)2xH2O) by addition of Na2SO4 (D Abreu and Morais, 2010). In a second stage, the precipitate is converted to RE(OH)3 with stoichiometric amounts of 2 M NaOH at 70 °C (Diaz et al., 2016). Finally RE2O3 (REO) can be obtained after calcination of the RE (OH)3 at 500 °C for three hours. The same chemistry and REE recovery process is assumed for both the ER and BCS routes. The product is a mixed REO powder that approximates composition of the precursor used to produce the magnets dissolved. 2.3. Economic assessment methodology 2.3.1. Cost estimation A TEA was performed for each process alternative (BCS and ER), following the study estimate approach using preliminary process designs. Capital costs of the major equipment for each unit operation were calculated based on equipment sizing and design factors obtained from the mass and energy balances (Seider et al., 2009;

Smith, 2005; Turton et al., 1998). A process capacity of 20 kt/year of scrap mobile electronics was established as the base-case analysis. Equipment costs were brought to 2014 price using the Chemical Engineering Plant Cost Index (CEPCI). Finally, using Eqs. (4) and (5), Lang factors were applied to calculate the fixed capital investment (FCI), and total capital investment (TCI):

X  Q i CEPCI14  Cbi Q bi CEPCIrd i X  Q i CEPCI14  Cbi TCI ¼ 1:05  LTCI  Q bi CEPCIrd i

FCI ¼ 1:05  LFCI 

ð4Þ ð5Þ

where Cbi is the equipment base cost, Qbi the equipment base capacity, Qi the equipment estimated capacity, and CEPCI14, CEPCIrd correspond to the CEPCI for 2014 and the reference year, respectively. The 1.05 factor accounts for delivery of equipment to the plant site, and LFCI = 4.1, and LTCI = 4.9 are the recommended Lang factors without and with the inclusion of working capital, respectively (Seider et al., 2009). All cost and values are reported in U.S. dollars (USD). 2.3.2. Economic model A nth-plant assumption was considered to perform the technical cost modeling (TCM) (Ghodrat et al., 2016; Kang and Schoenung, 2006) for each process. While this assumption ignores additional costs for the ER process, which are associated with a technology under development (e.g. market and financing risks, equipment over/under-design, and start-up over costs), consistent assumptions are necessary when comparing competing projects (Smith, 2005). Obviously the ER process presents a greater risk as commercial scale ER operations do not exist. The results of the TEA, while not entirely certain, provide a valid estimation method to compare the ER process to an established technology. Project cash flow evaluations for the process alternatives were performed based on the assumptions shown in Table 1. Note that the cost of land is not included as a more detailed engineering design is required for better estimation of the land requirements. Base values for operational costs, revenue streams, and consumables are presented in Table 2. Value of metals for revenue calculation were considered as the average reported value in 2014, The process alternatives were compared in terms of the projected cash flow and return on investment (ROI = net earnings/TCI). Analyses of product costs and revenues were performed on the second year as an example of full capacity and stable operation. 3. Results 3.1. E-waste material processing through black Cu smelting route Once the energy consumption for all the unit operations was established (reduction furnace, oxidation furnace, fire refining, Table 1 Parameters for the techno economic analysis. Assumption

Assumed value

Plant financing debt/equity

50%/50% (100% Capital investments + 40% First year operational costs) 20 years 10% annually 20 years Straight line depreciation over 20 years 35% 10% reagents and feedstock 6 months Revenue = 50% of normal Operational costs = 50% normal Administrative costs = 100% of normal 365 days

Term of debt financing Interest for debt financing Evaluation period for IRR Depreciation term Income tax rate Inventory Startup period Revenue and costs during start

Operating time

Please cite this article in press as: Diaz, L.A., Lister, T.E. Economic evaluation of an electrochemical process for the recovery of metals from electronic waste. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.050

5

L.A. Diaz, T.E. Lister / Waste Management xxx (2017) xxx–xxx Table 2 Based values for cost and revenue estimations in USD. Fixed operating costs

Revenues Cost/Unit

Watera Energya Labor Coala Natural gasb Maintenancec General operating expensesc Plant overheadc Insurancec Royaltiesc a b c d e

Consumables Cost/Unit

Cu 99.9%c Cu scrapc,e Bronzed Agc Auc REOd Steeld

12.8 ȼ/Gl 7 ȼ/kWh 40 $/h 40 $/t 3.5 $/Mm3 6.9% FCI 31% COL 70.8% COL + 0.9% FCI 3.2% CEf.o.b 6.5% CEf.o.b

5.97 $/kg 4.5 $/kg 4.41 $/kg 590 $/kg 39,133 $/kg 66 $/kg 0.18 $/kg

Cost/Unit E-wasted Slagc Na2S2O3 HCl NaClO3 NaCl Na2S2O5 Zn H2SO4 Na2S2O4 NaOH

7.79 $/kg 0.1 $/kg 370 $/t 200 $/t 490 $/t 55 $/t 0.352 $/t 500 $/t 130 $/t 120 $/t 400 $/t

EIA (2016a). EIA (2016b). Ghodrat et al. (2016). Scrapregister (2015). Cu scrap is considered as consumable for the smelting process.

electro refining, and precious metals refining), the capital costs were estimated for all the unit operations except for the precious metals refining due to lack of information regarding the processing route. In this work, as in the work of Ghodrat et al. (2016), standard equipment for the treatment of gas emissions, such as bag houses and scrubbers, were considered. However, it should be pointed out that a significant additional capital investment may be required for the abatement of dioxin emissions (Hagelüken, 2006b). The size factors used for the equipment cost calculations are presented in Table 3. Additional costs that were not included in the capital and operational costs estimation include: solid handling systems, gas effluents cooling, electrolyte recovery, and air enrichment. A process flow diagram of the BCS process (Anindya et al., 2013; Ghodrat et al., 2016) with the inclusion of REE recovery is presented in Fig. 1. The estimated TCI calculated with Eq. (5) for the BCS plant is presented in Table 3. A distribution of the annual production cost and revenues for the second year of operation is presented in Fig. 3 for the BCS process. The second year of operation was chosen as an example of stable operation at full capacity. As it can be seen from Fig. 3a, consumables (feedstock plus reagents) are the largest contribution to the total production cost ($236,786,449.5) for the second year. The cost of the e-waste alone represents over 63% of the total operational costs of the BCS process followed by Cu scrap with 29% of the total operational costs. Other operational costs including labor-related expenses (COL), utilities (e.g. electricity and fuels), insurance, plant overhead, and depreciation do not add more than

Table 3 Cost of equipment and total capital cost for the black Cu smelting route. Size factor for costing

Size reduction and separation (S-1) Reduction furnace (F-1) Oxidation furnace (F-2) Fire refining (F-3) Bag house (BH-1) Scrubber (SC-1) Electro refining (ER-1) REE extraction/precipitation (R-3) REE digestion(R-4) Cost of equipment (CEf.o.b) Fixed capital investment (FCI) Total capital investment (TCI)

Value

Units

0.055 3346.5 8977.2 5386.3 222.4 222.4 22.1 33.8 1.1

t/day kW kW kW m3/min m3/min m3 m3 m3

Cost

$ $ $ $ $ $ $ $ $

29,324.0 503,531.4 1,128,593.7 743,168.9 57,089.2 51,193.4 524,000.0 74,422.0 15,831.2

$ 3,127,153.9 $ 12,805,695.4 $ 15,104,153.5

10% of the total operational costs. The results presented in Fig. 3 agree with previous work (Ghodrat et al., 2016), which identified the cost of feedstock as one of the critical parameters for process feasibility. Smelting takes advantage of combustion of organic material present in the e-waste, where estimates were found to produce a 23% fuel savings (Ghodrat et al., 2016). 3.2. E-waste material processing through electrochemical recovery (ER) process For the ER process, capital costs were estimated for the principal equipment on each unit operation using the equipment size factors presented in Table 4. Other costs that were not included in the capital and operational costs estimation are solid handling systems such as bucket elevators or pneumatic conveyors. A process flow diagram of the e-waste treatment through the ER process is presented in Fig. 2. The estimated TCI for the ER process is presented in Table 4. As in the BCS process, a distribution of the annual production cost and revenues for the second year of operation of the ER process is presented in Fig. 4. A 30% lower operational cost for the ER process was obtained by the comparison of the total operations costs in Figs. 3a, and 4a. The lower operational costs for the ER process resulted in the e-waste feedstock contributing more significantly (98% of total) than observed for BCS. Hence, other operational costs, which include reagents, labor-related expenses (COL), utilities (electricity and water), insurance, plant overhead, and depreciation represent less than 2%. While the operational costs of the ER process are 30% less than that of BCS, total revenue was reduced by 15.5%. This was primarily due to the lower overall amount of metal recovered, as smelting uses recycled metals as an additional feed. Combined, these values show an overall advantage for the ER process in this analysis. For both processes, based on the low content and the market value reported for REE in Table 2, the revenue from REEs averaged only about 0.5% of the total recovery value. Nevertheless, the recovery of REE becomes important due to their relevance to technology development, and risks of potential of supply restrictions (DOE, 2011; Graedel et al., 2015). Higher revenues can be obtained from REE if highly enriched e-waste sources, such as hard disk drives (HDD), are added to the feedstock (Nguyen et al., 2017). One additional revenue that was not considered for the ER process corresponds to the undissolved material. After metal extraction, this material, which is mostly composed of polymers and fiber glass, can find application as filler for polymer aggregates or

Please cite this article in press as: Diaz, L.A., Lister, T.E. Economic evaluation of an electrochemical process for the recovery of metals from electronic waste. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.050

6

L.A. Diaz, T.E. Lister / Waste Management xxx (2017) xxx–xxx

(a)

Reagents, $74,397,097.3

Feedstock, $162,389,352.2

(b) Au, $361,630,940.2

REO, $2,246,002.9

Labor related operaons, $6,708,819.6

steel, $675,640

General Operaonal expenses, $2,079,73… Ulies, $795,199.4 Manteinance, $883,593.0

Cu 99.9%, $80,684,248.5

Ag, $24,929,730.4

Others, $5,943,104.8

Fig. 3. Operational (a), and revenue (b), cost distribution for the second year of operation for the BCS process.

3.3. Processes comparison

Table 4 Cost of equipment and total capital cost for the ER process in USD. Size factor for costing

Cost

Value

Units

Size reduction and separation (SS-1)

54.8

t/day

$ 146,416.0

ER process Electrolyzer (ER-1) Columns (EC-1) Pump (P-1)

14.4 52.8 33.0

m3 m3 kW

$ 327,500.0 $ 249,973.2 $ 41,712.3

Precious metals extraction Reactor Ag cementation and digestion (R-1) Reactor Au precipitation (R-2) PUMP (P-2)

51.4 38.6 6.01

m3 m3 kW

$ 131,618.7 $ 78,982.1 $ 7844.2

REE extraction Reactor REE extraction/precipitation (R-3) Reactor REE digestion (R-4) Oven

33.8 1.1 80.0

m3 m3 kW

$ 74,422.0 $ 15,831.2 $ 40,000.0

Plant balance Vacuum filter + vacuum pump (VF-1) Pumps (P-3, P4, P-5)

0.5 1.0

m2 kW

$ 199,895.9 $ 7844.2

Cost of equipment (CEf.o.b) Fixed capital investment (FCI) Total capital investment (TCI)

$ 1,333,692.3 $ 5,741,545.5 $ 6,861,847.1

in concrete application (Ghosh et al., 2015). Current development research aims for the selective recovery of polymers from the ewaste (Zhao et al., 2017). However, the most obvious application is related to energy generation through low temperature pyrolysis processes (Ghosh et al., 2015; Zhao et al., 2017)

(a)

Reagents, $2,514,438.8

Feedstock, $160,887,733.3

Based on the TEA analysis, using previously described assumptions, a similar cumulative cash flow is observed for both routes (Fig. 5). Despite 18.4% higher revenue for the BCS process, a 30% lower operational cost, and lower capital cost for the ER process contribute to an advantage for the ER process in terms of economic performance. Fig. 6 shows the operational margin profiles evaluated for 20 years for the ER and the BCS, where the operational profit for the ER process is 21% higher on average. The operational margin shows the ratio of operational income to the total revenue and it is a direct measurement of the operational profit of the processes. In terms of processing cost of e-waste, including the effect of capital costs for the base-case (20 kt/year of e-waste), 2.9 kg of ewaste can be processed per dollar of capital investment with the ER process, while less than half, 1.3 kg, can be processed in the smelting route. The inset in Fig. 5 shows the ROI and the internal rate of return (IRR) for the two evaluated process alternatives. These two values represent the ratio of the yearly income to the total investment, and the total return to the investment during the evaluation period, respectively. Based on these two profitability figures of merit, it is possible to conclude that the ER process is a more favorable alternative for the processing of e-waste and the recovery of value and critical materials. Consistent assumptions for both options allows one to conclude with a good degree of confidence that the ER process is a competitive/profitable option for the processing of electronic waste, which can substitute the pyrometallurgical approach when capital investment or environmental restrictions would require it.

(b)

Au, $361,630,940.2

Labor related operaons, $6,646,783.0 General Operaonal expenses, $2,060,502.7

Ulies, $958,073.7 Manteinance, $396,166.6

REO, $2,246,002.9 steel, $675,640 Deposit, $9,260,904.1 Ag, $23,177,300.3

Others, $5,235,983.9

Fig. 4. (a) Operational and (b) revenue cost distribution for the second year of operation of the ER process.

Please cite this article in press as: Diaz, L.A., Lister, T.E. Economic evaluation of an electrochemical process for the recovery of metals from electronic waste. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.050

7

L.A. Diaz, T.E. Lister / Waste Management xxx (2017) xxx–xxx

2500%

5,000

Cumulave cash flow (M$)

4,000 3,500

Percentage

2000%

4,500

ER

ER Smelng

1500% 1000%

500%

Smelng

3,000 0%

2,500

ROI

IRR

2,000 1,500

1,000 500 0 0

5

10

-500

15

20

Year

Fig. 5. Graph of cumulative cash flow over first 20 years of operation for ER and BCS. Inset shows the ROI and IRR for both processes.

60%

Operaonal margin / %

ER 50% 40%

Smelng

30%

20% 10%

0% 0

2

4

6

8

10

12

14

16

18

20

Year Fig. 6. Operational margins for the ER and BCS processes during the 20 year evaluation period.

3.4. Sensitivity analysis Due to the uncertainty associated with the base-case parameter selection and the information available in early-stage project eval-

uations, a sensitivity analysis was performed to independently assess the effect of a ±30% variability of the assumed and calculated costs for the variables (consumables, utilities, capital cost, and labor cost) in the ROI of the ER and BCS processes. Fig. 7 shows a high ROI sensitivity with fluctuations of both the capital and consumable costs, for the two evaluated processes. Changes in utilities and labor cost have no significant effect as their contribution to the total operational costs is less than 5% for both processes. Figs. 3a and 4a show that over 90% of the total operational costs correspond to consumables. Feedstock cost can be significantly reduced by developing effective e-waste collection strategies. It can be observed from Fig. 7 that even for an extremely pessimistic scenario (30% higher operational and capital costs) the ROI for the ER process is higher than the ROI for the BCS process at the more optimistic scenario (30% lower operational and capital costs), which show an economic advantage for the ER process. Among the 30% variations of the evaluated parameters the ROI of both processes remained positive. A separate sensitivity analysis examined the effect of precious metals recovery, particularly Au, due to the large contribution to revenue as shown in Figs. 3b, and 4b. In order to capture the effect of recovery of both Ag and Au, an analysis was performed by vary-

(a)

(b) 1400%

2900% 1300% 2700% 1200% 2500% 1100%

2100%

ROI

ROI

Labor 2300%

Labor

1000%

Ulies 1900%

800%

1700%

700%

1500% -30%

-20%

Ulies

900%

-10%

0%

10%

Change in variable

20%

30%

600% -30%

-20%

-10%

0%

10%

20%

30%

Change in variable

Fig. 7. Sensitivity of ROI with gold grade of the feedstock, capital, and operational costs for (a) ER and (b) BCS processes.

Please cite this article in press as: Diaz, L.A., Lister, T.E. Economic evaluation of an electrochemical process for the recovery of metals from electronic waste. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.050

L.A. Diaz, T.E. Lister / Waste Management xxx (2017) xxx–xxx

(a)

(b)

2500%

2500%

2000%

2000%

1500%

1500%

ROI

ROI

8

1000%

Ag recovery

1000% 500%

500%

0%

0%

-500%

-500% 20%

40%

60%

80%

20%

100%

40%

60%

80%

100%

Precious metals recovery

Precious metals recovery

Fig. 8. Sensitivity of ROI to precious metals recovery efficiency (Au and Ag) for (a) ER and (b) BCS processes. Analysis held one element (Ag or Au) to the base-case while varying the other.

(b) $30

$1,000

$25

$800

$20

$600

$15

$400

$10

$200

$5

$0

$0 10

20

30

40

50

E-waste capacity / kt/year

$35

$1,200

$30

$1,000

$25

$800

$20

$600

$15

$400

$10

$200

$5

$0

TCI / Millions $

$1,200

$1,400

Revenues and operaonal costs Millions $

$35

TCI / Millions $

Revenues and operaonal costs Millions $

(a) $1,400

$0 10

20

30

40

50

E-waste capacity / kt/year

Fig. 9. Sensitivity of operational costs, revenues and TCI with changes in plant capacity for (a) ER and (b) BCS processes.

ing the recovery for one element (Ag or Au) while holding the other at the recovery value used in the base-case. As presented in Fig. 8, ROI was much less sensitive to Ag recovery than for Au for both options. It is then clear that Au recovery efficiencies are more critical for the project performance as Au holds 77% and 91% of the revenues for the BCS and ER processes, respectively. To have a minimum ROI of 10%, for the BCS process, the lowest Au recovery allowed is 40% as long as the Ag recovery exceeds 80%. In the case of the ER process, the same lowest limit for Au recovery applies, but the lowest recovery limit of Ag recovery drops to 65%. Note that it is unlikely a recovery process would operate at such low recoveries. Effect of plant capacity was also included within the sensitivity analysis. Although the capacity range is limited by the lower and upper values of the cost estimation factors, it was possible to perform a stability analysis between 15 kt/y and 50 kt/y of e-waste processed. Fig. 9 shows the plant capacity effect on revenues, operational and capital costs. It is clearly observed that operational profit increases with the plant size. While the economic model considers linear relationships among operational cost factors, such as feedstock and utilities, the labor-related operating costs are assumed constant for a plant size with automated control and a production range of 10–100 t/day (Seider et al., 2009). The slope of the revenues and operational costs suggest a limiting lower capacity for a profitable operation. These results are in agreement with the results reported by Ghodrat et al. (2016) in which it was concluded that smelting plant capacities below or equal to 20 kt/y

total throughput (ca. 10 kt/y e-waste) are not economically feasible. 4. Conclusions The TEAs of two process alternatives for the recovery of base, precious and critical metals from electronic waste were performed using the study estimate approach. Although an equitable comparison of the two technologies is difficult considering the significant differences in product distribution and feedstock requirements, a simple comparison can be performed in terms of process cost of e-waste for each technology. Based on the considered assumptions, which were applied for both of the evaluated process alternatives, the ER process shows to be a cost-competitive alternative for the recovery of value from electronic waste as it can process 2.9 kg e-waste per dollar of capital investment versus 1.3 kg for the BCS process. Along with the economic evaluation, minimum performance targets were established for the ER recovery in terms of recovery of precious metals, Au and Ag, as 40% and 60%, respectively. The ER process can reduce the e-waste processing cost from 12.8 $/kg to 9 $/kg when compared with the BCS route. Low chemical consumption, by means of the regeneration of the oxidant used for the extraction and recovery of base metals, makes ER process economically viable despite producing a lower value mixed Cu alloy vs. 99.9% Cu. Lower capital investment, waste generation, and simplicity make the ER process a viable alternative for the processing of e-waste in the United States. Using primarily electricity

Please cite this article in press as: Diaz, L.A., Lister, T.E. Economic evaluation of an electrochemical process for the recovery of metals from electronic waste. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.050

L.A. Diaz, T.E. Lister / Waste Management xxx (2017) xxx–xxx

as a reagent, the ER process can produce metals using renewable energy and thus may become an even more attractive option in the future. Acknowledgments This work is supported by the Critical Materials Institute, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Advanced Manufacturing Office. This manuscript has been authored by Battelle Energy Alliance, LLC under Contract No. DE-AC07-05ID14517 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paidup, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. References Akcil, A., Erust, C., Gahan, C.S., Ozgun, M., Sahin, M., Tuncuk, A., 2015. Precious metal recovery from waste printed circuit boards using cyanide and non-cyanide lixiviants – a review. Waste Manage. 45, 258–271. Amer, A.M., 2003. Processing of copper anodic-slimes for extraction of valuable metals. Waste Manage. 23, 763–770. Anindya, A., Swinbourne, D.R., Reuter, M.A., Matusewicz, R.W., 2013. Distribution of elements between copper and FeOx–CaO–SiO2 slags during pyrometallurgical processing of WEEE. Miner. Process. Extract. Metall. 122, 165–173. Baldé, C.P., Wang, F., Kuehr, R., Huisman, J., 2015. The global e-waste monitor – 2014. United Nations University, IAS – SCYCLE. Behnamfard, A., Salarirad, M.M., Veglio, F., 2013. Process development for recovery of copper and precious metals from waste printed circuit boards with emphasize on palladium and gold leaching and precipitation. Waste Manage. 33, 2354–2363. Cui, J., Zhang, L., 2008. Metallurgical recovery of metals from electronic waste: a review. J. Hazard. Mater. 158, 228–256. D Abreu, R., Morais, C.A., 2010. Purification of rare earth elements from monazite sulphuric acid leach liquor and the production of high-purity ceric oxide. Miner. Eng. 23, 536–540. Diaz, L.A., Clark, G.G., Lister, T.E., 2017. Optimization of the electrochemical extraction and recovery of metals from electronic waste using response surface methodology. Ind. Eng. Chem. Res. 56, 7516–7524. Diaz, L.A., Lister, T.E., Parkman, J., Clark, G., 2016. Comprehensive process for the recovery of value and critical materials from electronic waste. J. Clean. Prod. 125, 236–244. Dodson, J.R., Hunt, A.J., Parker, H.L., Yang, Y., Clark, J.H., 2012. Elemental sustainability: towards the total recovery of scarce metals. Chem. Eng. Process. 51, 69–78. DOE, 2011. Critical materials strategy. Report PI-0009. U.S. Department of Energy, http://energy.gov/sites/prod/files/DOE_CMS2011_FINAL_Full.pdf. EIA, 2015.Coal prices and outlook. Retrieved May 2016, from https://www.eia.gov/ energyexplained/index.cfm?page=coal_prices. EIA, 2016.Natural gas prices. Retrieved May 2016, from https://www.eia.gov/dnav/ ng/ng_pri_sum_dcu_nus_m.htm EPA, 2016. Electronic Products Generation and Recycling in the United States, 2013 and 2014. Environmental Protection Agency, U.S. Geyer, R., Doctori Blass, V., 2010. The economics of cell phone reuse and recycling. Int. J. Adv. Manuf. Technol. 47, 515–525. Ghodrat, M., Rhamdhani, M.A., Brooks, G., Masood, S., Corder, G., 2016. Techno economic analysis of electronic waste processing through black copper smelting route. J. Clean. Prod. 126, 178–190.

9

Ghodrat, M., Rhamdhani, M.A., Khaliq, A., Brooks, G., Samali, B., 2017. Thermodynamic analysis of metals recycling out of waste printed circuit board through secondary copper smelting. J. Mater. Cycles Waste Manage., 1– 16 Ghosh, B., Ghosh, M.K., Parhi, P., Mukherjee, P.S., Mishra, B.K., 2015. Waste printed circuit boards recycling: an extensive assessment of current status. J. Clean. Prod. 94, 5–19. Graedel, T.E., Harper, E.M., Nassar, N.T., Nuss, P., Reck, B.K., 2015. Criticality of metals and metalloids. Proc. Natl. Acad. Sci. U. S. A. 112, 4257–4262. Hagelüken, C., 2006a. Improving metal returns and eco-efficiency in electronics recycling - a holistic approach for interface optimisation between preprocessing and integrated metals smelting and refining, Electronics and the Environment. In: Proceedings of the 2006 IEEE International Symposium on, pp. 218–223. Hagelüken, C., 2006b. Recycling of electronic scrap at Umicore’s integrated metals smelter and refinery. World Metall.–Erzmet. 59, 152–161. Kang, H.-Y., Schoenung, J.M., 2006. Economic analysis of electronic waste recycling: modeling the cost and revenue of a materials recovery facility in California. Environ. Sci. Technol. 40, 1672–1680. Kaya, M., 2016. Recovery of metals and nonmetals from electronic waste by physical and chemical recycling processes. Waste Manage. 57, 64–90. Khaliq, A., Rhamdhani, M.A., Brooks, G., Masood, S., 2014. Metal extraction processes for electronic waste and existing industrial routes: a review and Australian perspective. Resources 3, 152–179. Lister, T.E., Diaz, L.A., Clark, G., Keller, P., 2016. Process Development for the Recovery of Critical Materials from Electronic Waste, IMPC, Québec, Canada. Lister, T.E., Wang, P., Anderko, A., 2014. Recovery of critical and value metals from mobile electronics enabled by electrochemical processing. Hydrometallurgy 149, 228–237. Moskalyk, R.R., Alfantazi, A.M., 2003. Review of copper pyrometallurgical practice: today and tomorrow. Miner. Eng. 16, 893–919. Mukherjee, A., Debnath, B., Ghosh, S.K., 2016. A Review on technologies of removal of dioxins and furans from incinerator flue gas. Procedia Environ. Sci. 35, 528– 540. Nguyen, R.T., Diaz, L.A., Imholte, D.D., Lister, T.E., 2017. Economic assessment for recycling critical metals from hard disk drives using a comprehensive recovery process. JOM 69, 1546–1552. Pletcher, D., Walsh, F.C., 2012. Industrial Electrochemistry. Springer Science & Business Media. Scrapregister. SCRAPREGISTER. Retrieved November 15 2015, from http://www. scrapregister.com/scrap-prices/united-states/260 Seider, W.D., Seader, J.D., Lewin, D.R., 2009. Product & Process Design principles: Synthesis, Analysis and Evaluation. John Wiley & Sons. Smith, R.M., 2005. Chemical Process: Design and Integration. John Wiley & Sons, Chichester, UK. Sun, Z., Xiao, Y., Sietsma, J., Agterhuis, H., Yang, Y., 2015. A cleaner process for selective recovery of valuable metals from electronic waste of complex mixtures of end-of-life electronic products. Environ. Sci. Technol. 49, 7981– 7988. Torres, R., Lapidus, G.T., 2016. Copper leaching from electronic waste for the improvement of gold recycling. Waste Manage. 57, 131–139. Tukker, A., 2014. Rare earth elements supply restrictions: market failures, not scarcity, hamper their current use in high-tech applications. Environ. Sci. Technol. 48, 9973–9974. Tuncuk, A., Stazi, V., Akcil, A., Yazici, E.Y., Deveci, H., 2012. Aqueous metal recovery techniques from e-scrap: hydrometallurgy in recycling. Miner. Eng. 25, 28–37. Turton, R., Bailie, R., Whiting, W.B., Shaeiwitz, J.A., 1998. Analysis Synthesis and Design of Chemical Processes. McGraw-Hill. Vats, M.C., Singh, S.K., 2015. Assessment of gold and silver in assorted mobile phone printed circuit boards (PCBs): original article. Waste Manage. 45, 280–288. Zeng, X., Li, J., 2016. Measuring the recyclability of e-waste: an innovative method and its implications. J. Clean. Prod. 131, 156–162. Zhao, Y.-B., Lv, X.-D., Yang, W.-D., Ni, H.-G., 2017. Laboratory simulations of the mixed solvent extraction recovery of dominate polymers in electronic waste. Waste Manage. 69, 393–399.

Please cite this article in press as: Diaz, L.A., Lister, T.E. Economic evaluation of an electrochemical process for the recovery of metals from electronic waste. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.050