Material Flow Analysis of Carbon Nanotube Lithium-Ion Batteries Used in Portable Computers
Vicente Sebastian Espinoza †, Serkan Erbis †, Leila Pourzahedi ‡, Matthew J. Eckelman *‡, and Jacqueline A. Isaacs †
† Department of Mechanical and Industrial Engineering and Center for High-rate Nanomanufacturing, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
‡ Department of Civil and Environmental Engineering, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
ACS Sustainable Chem. Eng., 2014, 2 (7), pp 1642–1648
DOI: 10.1021/sc500111y
Publication Date (Web): April 21, 2014
Copyright © 2014 American Chemical Society
Supporting documents (6 pages): high and low saturation demand curves for number of obsolete portable computers as a function of time and waste management rates for all US states using two scenarios
In this paper, the authors detail a study whose aim is to provide a quantitative assessment of managing waste (or material flow analysis) carbon nanotube (CNT) components now found in batteries used in portable computers. Their goal is to provide a quantitative basis for understanding the waste, environmental impact, and recycling implications of carbon nanotube for use by company stakeholders and public policy makers. They point out that the rate of commercial availability of emerging technologies will outpace the evaluation process for the end-of-life environmental impacts of these newly developed engineered materials.
Selecting this article is based on a couple of motivating interests: one on learning about how a material flow analysis is done and the other curiosity about how waste material can be managed, ideally recycled or reused.
The Methods section define material flow analysis (MFA) as follows: “Material flow analysis (MFA) is a method used to describe, investigate, and evaluate the flows and accumulations of materials and substances through both the economy and the environment. MFA is based on a stock and flow model (principle of mass conservation), in which time step changes in stock are determined by tracking additions (flows in) and subtractions (flows out) to stock.”
The authors describe the derivation for the equation to estimate the mass of carbon nanotube material in obsolete personal computers (both desktops and laptops). For details of the mathematical derivation, see paper. The derivation began with the general equation for stocks and flows given by:
Stock of material or product in use in year i
= stock of material from previous year (i – 1) + input in year i – output in year i
Some of the assumptions and models used are (see paper for full details):
· The number of input is estimated by multiplying the stock of material in use by the penetration rate of the product.
· The number of obsolete products or output is calculated by multiplying the input from previous years by the probability that the product is obsolete after some number of years. The authors used the number (from a previous study) of 0.5 after 3 years (average use span).
· The authors used a model (technology substitution) from a previous study that estimate the fraction of portable computers using Li ion batteries in a given year containing CNT’s.
· The number of exported obsolete computers were also taken into account and subtracted from the total obsolete numbers predicted by the model (this number was estimated at 871,000 in 2010).
· To determine the mass of CNT, each Li ion battery is assumed to have between 3-5 cells, each one containing about 1 gram of multi-walled CNT’s.
Multiplying the gram amount of CNT’s in each obsolete computer that end up as output by the number of estimated obsolete computer, the mass of CNT’s in obsolete batteries can then be estimated.
The number of obsolete computers containing CNT was estimated for each state. This was calculated using available data on the percentage use of portable computers by age group and age distribution in each state.
Scenario 1: Baseline estimation based on current rates of electronic waste recovery for recycling:
To predict the fate and how much of CNT’s end up incinerated, recycled, or landfilled, statistics on the disposition of electronic waste in each state was used. State-specific recycling rates for electronic waste were estimated by dividing the quantities collected by national per capita electronic waste generation rates; for states without data, the national average of 16.4% was used. The rest were assumed incinerated or landfilled “according to state proportions for solid municipal waste in 2008”.
Scenario 2: Using a national 85% recovery target by 2040 for all states and linear interpolation from current baseline.
These waste management rates are given in Tables S1 and S2 in the supporting documents.
RESULTS AND DISCUSSION:
The number of portable computers sold in each country was calculated based on the relative GDP of each country (relative to highest GDP) times its population. This estimated a value for the US of 47 million units sold in 2009.
The penetration rate in the market for computers was estimated using a previous study and model and used to calculate the number of portable computers sold in the US using the 2009 data above to determine the error margin.
Prospective number of sales of portable computers and obsolete numbers generated were estimated (see numbers given in paper) with lower and upper bound values. These numbers assume a 3-year average lifetime for portable computers.
The technology penetration of CNT Li ion batteries was estimated using the transition rate from non-CNT Li ion batteries in portable computers to CNT-containing portable computers calculated using the technology substitution model mentioned in the Methods section. This model has shown a good fit for desktop to laptop and from CRT to LCD display transitions. No statistical for CNT’s can be done, however, due to lack of historical data. These calculations indicate a low-growth estimate of 100% after 25 years and a medium- to high-growth estimate of 100% market share in 12 – 18 years.
· High technology transition case: nearly all obsolete portable computers (69 million untis) have CNT’s by 2029
· Low to medium transition case: 2040 and 2036, respectively
These large numbers present a major concern due to the uncertainty in how these CNT’s will be have when recycled, incinerated, or landfilled. Figure 3 shows the material flow curves for these CNT’s over time and the growth in annual waste flow using both scenarios of current recycling rates versus 85% recycling rate. Some notable information from the curves:
· A drop off in metric tonnes of CNT waste is predicted starting 2027 if the target recycling rate of 85% is implemented.
· At current recycling rates, the annual waste curve sees a flattening but with a slight increase at around 150 metric tonnes starting at around 2027.
· At the high technology transition scenario, a cumulative 3731 tonnes of CNT’s are expected in the next 25 years from just a few hundred kilograms at current amounts. “If current recycling practices remain in place, of this cumulative total, 602 tons are projected to be collected, 288 tons incinerated, and 2842 tons landfilled nationally (Table S1, Supporting Information). For context, current use of CNTs in all electronics and optics applications is approximately 800 tons per year.”
UNCERTAINTIES, LIMITATIONS, AND OPPORTUNITIES FOR FUTURE WORK
“Technology forecasting is highly uncertain, and the present study makes a number of simplifying, mostly static, assumptions regarding the pace of technology development, consumer behavior, and the management of electronic waste in the United States.”
Some scenarios not considered in the assumptions include:
· Storage or hibernation of obsolete computers which would delay the entry into waste flow
· Reuse of batteries which is not very likely or frequent because refurbishment replaces the battery
· Replacement of the battery during the 3-year lifetime average which will increase the estimated waste flow
· Decrease in average lifetime use of computers due to accelerated technology improvements
· The mass in grams of CNT per battery may change
· Market disruptions will affect assumptions made using the logistic model
The authors end with the following concluding and summarizing paragraph:
“On the basis of the current state of technology, however, the scenario results presented here provide useful projections of the quantities and likely location of CNTs generated for an important component of electronic waste, which is information that can be used to plan investments in collection and recycling efforts and ensure safe and responsible handling and disposal measures.”
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