Comparative Assessment of Life Cycle Assessment Methods Used for Personal Computers

Intel Corporation, 2200 Mission College Boulevard, Santa Clara, California 95054, USA.
Environmental Science & Technology (Impact Factor: 5.33). 10/2010; 44(19):7335-46. DOI: 10.1021/es903297k
Source: PubMed


This article begins with a summary of findings from commonly cited life cycle assessments (LCA) of Information and Communication Technology (ICT) products. While differing conclusions regarding environmental impact are expected across product segments (mobile phones, personal computers, servers, etc.) significant variation and conflicting conclusions are observed even within product segments such as the desktop Personal Computer (PC). This lack of consistent conclusions and accurate data limits the effectiveness of LCA to influence policy and product design decisions. From 1997 to 2010, the majority of published studies focused on the PC concluded that the use phase contributes most to the life cycle energy demand of PC products with a handful of studies suggesting that manufacturing phase of the PC has the largest impact. The purpose of this article is to critically review these studies in order to analyze sources of uncertainty, including factors that extend beyond data quality to the models and assumptions used. These findings suggest existing methods to combine process-based LCA data with product price data and remaining value adjustments are not reliable in conducting life cycle assessments for PC products. Recommendations are provided to assist future LCA work.

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    • "From extraction of " conflict " minerals to inordinate quantities of energy consumption in manufacture through to low collection and recycling rates, uncontrolled treatment, and finally resource loss, they are among the most studied and problematic of all product groups (Epstein and Yuthas, 2011; Williams et al., 2002; UNU, 2008; Chancerel and et al., 2009). There have been a number of LCA studies undertaken on personal computers to identify the hot-spots in the life cycle and two reviews have been conducted on this body of literature (Teehan and Kandlikar, 2012; Yao et al., 2010). Most of these studies use either energy consumption or global warming potential as indicators of environmental impact and while there is not a consensus on the life cycle stage with the highest impact due to differences in methodologies and assumptions it can be concluded that the manufacturing and use phases are both high for energy consumption. "
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    ABSTRACT: During the last decades the electronics industry has undergone tremendous changes due to intense research leading to advanced technology development. Multiple life cycle assessments (LCA) have been performed on the environmental implications of consumer electronics. The aim of this report is to provide knowledge of the use of LCA for assessment of environmental impacts of electronics, as well as to provide insight into the environmental implications of using monodisperse polymer particles, so-called Ugelstad particles, in microelectronics, specifically in Ball Grid Arrays (BGA) used in Chip Scale Package (CSP) manufacturing. In the review of LCAs we wanted to assess the consistency between different LCA studies for desktop computers, laptop computers, mobile phones, and televisions. A literature study was thus conducted covering some key LCA contributions to the consumer electronics field. The focus is primarily on GWP100 efficiency in different life cycle phases, and secondarily on primary energy usage/electricity usages which are normalized per year to find inconsistencies. The LCIA GWP100 results for consumer electronics over the years suggest that most studies are of comparable quality, however, some studies are neither coherent nor transparent. Published LCAs for mobile phone and TV sets are consistent, whereas for laptop and desktop computers the studies occasionally give conflicting messages. The inconsistencies appear to be rooted in subjective choices and different system boundaries and life time, rather than lack of standardization. If included, the amounts of emissions of sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3) are crucial to the GWP100 in the various life cycle phases for a desktop using LCD screen. The GWP100 of SF6 is 22,800, while that of NF6 is 17,200. Another important observation is that the MEEuP Methodology report/tool underestimates the GWP100 of electronic component manufacturing processes. Between 1997 and 2010, the ISO 14040/44 standards have ensured a rather consistent set of GWP100 results for the studied products. However, the lack of transparency for consumer electronics LCAs sometimes makes benchmarking difficult. It is nevertheless possible to compare new LCA calculations to existing studies. It is also possible to reveal which product studies are consistent with studies of sub–materials and sub–components. In most cases, the GWP100 results for consumer electronics are consistent. Based on the survey of published work, recycling and other end–of–life processes have a tiny share of the total GWP100 score for consumer electronics. It is important for Conpart to know this, in order to focus on areas with the largest impact. Few studies have been published on the micro/nanosystems technologies providing same benefit. Nano structured polymer particles are produced to be used in ball grid array (BGA) and chip scale packaging (CSP). The technology could replace conventional BGA and CSP metal balls and the hypothesis is that the shift will be eco-efficient as polymer core particles might increase reliability. For the first time these particles are environmentally evaluated in their system perspective. The relative impact share of BGA balls in a BGA package was estimated. Moreover, change in environmental loadings when replacing traditional component packaging, here Quad Flat Pack (QFP) to BGA/CSP, was explored both on component and printed circuit board assembly (PCBA) level. This was followed by LCI comparisons between BGA packages using different types of metal plated polymer balls and conventional balls, respectively. On top of this LCIs were explored for GWP100 and Eco–Indicator’99 (H) single weighting scores in order to estimate eco–efficiencies. For BGAs the silicon (Si) die dominates CO2e emissions, but Eco–Indicator’99 (H) scores for solder balls are not negligible. Excluding the Si die and component assembly, changing a Thin Quad Flat Pack (TQFP)–64 for a Low–profile Fine–pitch Ball Grid Array (LFBGA)–84 would reduce CO2e by about 4% and increase Eco–Indicator’99 (H) by about 25%. Changing the LFBGA–84 to WCSP–64 would reduce CO2e by about 98% and Eco–Indicator’99 (H) by about 90%. Overall for BGA–256 using same size balls, gold plated ball technology decreases the Eco–Indicator’99 (H) score by about 25% compared to Pb based or Pb–free balls. Excluding all sub–parts of BGA–256 components, except the balls, showed that gold production dominated the environmental impact, as expressed by the GWP100 and Eco–indicator’99 (H), for the gold plated alternative. This research has conservatively demonstrated how to quantify the environmental change induced by miniaturization of specific electronic components. Not all BGAs will reduce the environmental footprint from the package materials alone. Each micro-system is unique and new environmental impact estimations must be done for the sub–structures of each electronics device. Even though the metal mass per ball is greatly reduced, it is a weak indicator of environmental impacts, which are driven by each materials specific environmental characteristics. The ball share of the BGA–256 GWP100 and Eco–indicator’99 (H) scores are small and the BGA/CSP producers can only marginally improve the environmental performance by focusing on the balls. On PCBA level the contribution from BGA balls is negligible. Results for metal plated monodisperse polymer particles (MPP) BGA balls suggest that gold usage is the key environmental performance indicator of interest. The eco–efficiency of using gold makes up for it to a certain degree. Especially metal plated MPP balls of reduced size and identical functionality, could demonstrate eco–efficiency by being more reliable. For metal plated MPP balls, the eco–efficiency scores increase with decreasing ball diameter. Screening LCA is a good method for identifying environmental improvement possibilities in technology development. The off–set effect of CSP miniaturization, driven by more and more PWB layers, must be included in further electronics micro-system expansions. For LCA in general, it is necessary to update all LCIA methods which include ozone depletion, with the latest results for nitrous oxide (N2O).
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    ABSTRACT: Life cycle assessment (LCA) studies of desktop personal computers (PCs) are analyzed to assess the environmental impact of PCs and to explain inconsistencies and disagreements across existing studies. Impacts, characterized in this work in terms of primary energy demand and global warming potential, are decomposed into inventory components and impact per component in order to expose such inconsistencies. Additional information from related studies, especially regarding use-phase energy consumption, helps interpret the LCA results. The weight of evidence strongly suggests that for primary energy demand and contribution to climate change, the use phase is the dominant life cycle phase; manufacturing impacts are smaller but substantial, and impacts due to product transportation and end-of-life activities are much smaller. Each of the few LCA studies that report manufacturing impacts as being greater than use-phase impacts make unrealistically low assumptions regarding use-phase energy consumption. Estimates of manufacturing impacts, especially those related to printed circuit boards and integrated circuits, are highly uncertain and variable; such estimates are very difficult to evaluate, and more systematic research is needed to reduce these uncertainties. The type of computer analyzed, such as low-power light desktop or high-power workstation, may dominate the total impact; future studies should therefore base their estimates on a large sample to smooth out this variation, or explicitly restrict the analysis to a specific type of computer.
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