Aurélie Villard

Alan Lelah
email: alan.lelah@g-scop.grenoble-inp.fr

Daniel Brissaud

Drawing a chip environmental profile: Environmental indicators for the semiconductor industry

Keywords: environmental impacts, indicators, semiconductor industry, chips, life cycle assessment

The semiconductor industry plays an ever-increasing role in society, providing microelectronic components called chips that are used in a wide variety of electronic applications. The rapid increase of the production of chips is responsible for considerable effects on the environment during the different phases of their lifecycle. In spite of increasing pressure from stakeholders to control these effects, no international standard or agreement has yet been established. In this context, the paper proposes a set of environmental indicators that take into account the most serious damages induced by these products.

To establish an exhaustive list of indicators, the specificities of the semiconductor branch are first analyzed in literature, identifying pressures on the sector coming from the downstream chain -chip buyers and users -and finally by analyzing data from industrial case studies. In order to highlight the most significant direct and indirect impacts, each aspect of the chips" life cycle phases is studied independently. The indicators reflect the particularities of the industry and point out the major impact categories. They can be therefore be used for standardized environmental analysis of microelectronic products. The paper retains seven environmental indicators: resource depletion, eutrophication, water stress, toxicity, summer smog and local electrical consumption. The final set of indicators will help draw the environmental profile of the microelectronic chips over the full life cycle of the products. It is a step towards necessary standardization in the microelectronic industry. The indicators are consistent with current state of the art and can evolve as progress is made on the definition and calculation of new indicators.

Introduction

The relatively low cost of production of microelectronic components, also called chips or integrated circuits (ICs), has made computers, mobile phones and other electronic devices inextricable parts of the structure of modern societies. Their very fast expansion into all sectors of the economy contributes to worrying effects on the environment: pollution in manufacturing plants; depletion of raw materials; electricity consumption during use; and accumulation of electronic waste, amongst others. This trend justifies current efforts to improve knowledge on the environmental risks and impacts of products in the microelectronic industry. This paper starts with the different potential impacts of the industry and determines the significant indicators that could be used to monitor the environmental consequences of the activity. Different indicators are currently available to characterize environmental impacts so the paper does not develop new ones but proceeds with state of the art indicators. Life Cycle Assessment (LCA) is identified as a powerful technique to present a global vision of the impacts generated by products. Results are presented in the form of a profile, providing a baseline to control the environmental state of the product and suggest ways to improve it. In theory, the schema should account for all the aspects: climate change, eco-systems quality, biodiversity, etc., without minimizing or intensifying one effect rather than another. The reason for considering all the aspects is to avoid impact transfers: attempts to improve one type of impact can deteriorate another one, which had hitherto been neglected or not at all regarded as important for the industry. However, each industry has its own particular concerns and should act in priority to reduce the most significant impacts it produces and determine the adequate indicators to guide this. The choice of indicators can be made by considering factors such as image, communication on previously achieved efforts and the ease of data collection [START_REF] Olsthoorn | Environmental indicators for business: a review of the literature and standardisation method[END_REF], however, a scientific determination of indicators requires a deep analysis of every stage of the lifecycle. The effect on the environment of a product can be visualised through the approach developed by the OECD 1 called DPSIR: Driving force, Pressure, State, Impact, Response [START_REF] Long | Indicators to identify the agricultural pressures on environmental functions and their use in the development of agri-environmental measures[END_REF]. It was developed to clarify the causalities between the actions of society and the consequences on the environment and ecosystems, and also to identify the needs for action. Furthermore, according to ISO 2 14031 (ISO, 1999), the selection and definition of environmental performance indicators has to take into account the significance of environmental aspects, the influence on the aspects and policy of the organization concerned and the views of other stakeholders. Indeed, the strategic positioning of a company is motivated essentially by external environmental, economic and social facets. In the semi-conductor sector it has mainly been external pressure that has, in the past, pushed the industry to learn more about the environmental impacts of its products. As a chip is only a small part of electronic applications, it is not intended for the general public but for industrial clients and has therefore not been a primary target of NGOs (Non Government Organizations) and consumers associations. Today, concerns are driven by generic stakeholder considerations, materialised by demands from extra-financial marking agencies. These agencies deliver ethical indexes like the Dow Jones Sustainability Index and usually call for reports on three major themes: climate strategy, water related risks and hazardous chemicals. In recent years, life cycle thinking has appeared in regulations across the world, most often initiated by the European Union (Szendiuch and Schischke 2007): RoHS (Restriction of the use of certain Hazardous Substances) (European Commission, 2002a), WEEE (Waste Electrical and Electronic Equipment) (European Commission, 2002b) and EuP (Eco-Design of Energy-using Products) (European Commission, 2005). These directives extend the responsibility of producers to the full product lifecycle. Expectations from society can therefore be taken as the first motivation to study the environmental impacts of the micro-electronic products. The second motivation comes from industrial applications that need to evaluate the environmental potential of consumer products incorporating semi-conductors. The environmental performances of the applications are dependent on the chips embedded inside. The selection of significant aspects of a chip cannot therefore be detached from customer demands. However, indicators should cover the needs of the industrial customers without losing the original microelectronic specificities. Electronic and computer industries are the historical customers of the microelectronic industry but lately, many new applications with electric and electronic devices have appeared and common appliances, like coffee machines, cars, ink cartridges, light bulbs, medical applications, etc. integrate electronic functions. The diversity of customer markets tends to multiply environmental obligations. First of all, the electronic sector as a whole has been facing an increasing problem of electronic waste leading to the legislative 1 OECD: Organization for Economic Co-operation and Development -http://www.oecd.org 2 ISO: International Organization for Standardization -http://www.iso.org/iso/home.html frameworks mentioned above. In addition, the ITU3 has been focusing on the greenhouse gas (GHG) emissions and energy consumption. Although the scope may seem restricted due to the international focus on GHGs, according to recent working groups (ITU, 2010), other environmental impacts like raw material depletion or water stress would be tackled later. Furthermore, the automotive sector insists on the use phase (limitation of air exhausts) and end-of-life (European Commission, 2002). In this way each particular applicative sector introduces new requirements for the semiconductors. Finally, the third motivation comes from microelectronic associations that have decided to take the lead on environmental concerns in their own industry. Chip manufacturers are regrouped in associations, such as ESIA4 , that defend interests on a national, regional or global level. These associations reflect the trends within the sector in their reports. ITRS5 , sponsored by the five leading chip manufacturing regions in the world: Europe, Japan, Korea, Taiwan, and the United States, includes an Environment Safety and Health Summary in their yearly roadmap (ITRS, 2013). However, ITRS is essentially a technology roadmap and the document insists on the needs for more robust and rapid assessment methodologies for chemicals, global warming, water and energy, along with some equipment life-cycle issues (ITRS, 2013). Another international consortium of leading semiconductor manufacturers, SEMATECH6 (2009) has developed Key Environmental Priority Indicators (KEPIs) for the microelectronic sector as "specific expressions that provide information about an organization"s environmental performances" (ISO, 1999). These KEPIs cover restricted concerns: global warming, water resource, chemical consumption and waste generation impacts. No knowledge management and classification of chemicals are available so no severity analysis can be performed. The indicators are handy for benchmarking but not linked to real product pressure. The purpose of the Life Cycle Assessment White Paper published by SEMATECH (2002) was to gather information about chiprelated LCA activities already completed or still under development. The white paper advised that in coming years a consensus be developed on lifecycle impact assessment methods and tools.

To help the industry formalise information on environmental concerns, this paper contributes to develop a suitable set of environmental indicators for the semiconductor industry and finally supply scientific information for the definition of standards. The indicators will help clarify the environmental load of a chip and alert the semiconductor industry on environmental issues for which it has real responsibilities in a lifecycle perspective. It provides elements to help industrial and public policies decrease the environmental footprint of activities by acting on lifecycle impacts. Moreover, seeing that environmental constraints should be considered in early design phases (Gehin et al., 2008), the profile will be very useful for eco-design perspectives. The designer can thereby decrease or, at least, limit, environmental effects of the future chips. The paper is organised as follows. Section 2 establishes a state of the art of knowledge at a sectorial level of interactions of the microelectronic industry and the environment. Section 3 studies the chips" lifecycle stages and derives a list of impact categories according to literature and the experience of practitioners. From these results, section 4 determines the nature of the strongest pressures and consequently proposes a set of indicators that account for the important aspects of the microelectronic activity. Finally conclusions are drawn in section 5 on the indicators that the semiconductor industry could lean on to develop environmental profiles of the chips.

State-of-the-art of environmental knowledge in the microelectronic sector

Characterizing the environmental impacts of industrial activities can generally be done from two different methodological standpoints: top-down, based on environmental input output analysis or bottom-up, based on process analysis (Wiedmann andMinx, 2008, Scipioniet et al., 2012). Input output analysis is useful to determine the effects of all economic activities at a sector level, while process analysis is used to measure impacts of individual products from cradle to grave [START_REF] Wiedmann | A Definition of "Carbon Footprint[END_REF]. Pure input output approaches are not specific enough to treat integrated product policy, assessment of individual products, or the benchmarking of single business against the sector average [START_REF] Minx | Input-Output Analysis and Carbon Footprinting: An Overview of Applications[END_REF]) and a product level method and is more adapted to a lifecycle approach (Scipioniet et al., 2012). However it requires appropriate definition of system boundaries [START_REF] Wiedmann | A Definition of "Carbon Footprint[END_REF]. For example, the Carbon footprint indicator identifies three levels of analysis, or scopes: Scope 1 reports GHG emissions owned or controlled by the industry; 2, covers indirect emissions associated with the external electricity supply; while 3, considers other indirect emissions associated with the operations of the organization concerned [START_REF] Minx | Input-Output Analysis and Carbon Footprinting: An Overview of Applications[END_REF]. Scope 3 is not relevant in this study.

After a brief description of the semiconductor lifecycle to introduce the major stages semiconductor products go through, this section reviews scientific literature and resumes the state of environmental knowledge in the industry.

Semiconductor lifecycles

A chip is basically a silicon substrate to which complex surface treatment processes are applied. As the component size constantly decreases on the nano and micrometric scale, the manufacturing phase becomes more and more complex. The major specificity lies in the fact that a lot of secondary materials used during manufacturing do not remain on the final chip [START_REF] Williams | The 1.7 kilogram microchip: energy and material use in the production of semiconductor devices[END_REF]. There are two types of production plants involved in the industry: front-end plants, producing wafers containing a large number of semiconductor chips and back-end plants that package the chips. The package provides protection and electrical connexions when the chip is integrated onto a circuit board. The same chips can be embedded in different electronic equipment. A microchip is environmentally neutral during its use, excepting the energy required to make it work. After disposal, it can contaminate soils, water and air because of the presence of metals and dangerous compounds like lead used in soldering. Other than potentially uncontrolled emissions, e-waste management generates issues from intensive electricity, water and chemical consumption, whatever the end-of-life process used. Figure 1 illustrates the general phases involved in a microelectronic component lifecycle. The life cycle can be separated in two: the production of the microelectronic chips and their applications. Production starts with the extraction and processing of raw materials, including silicon before entering the microelectronic manufacturing plants. The actual microelectronic manufacturing comprises two stages: chip manufacturing and packaging, which are not usually done in the same plants. The main focus of the case study is on these two stages. In this study, the extraction and processing of raw materials is considered as being relatively well documented in existing lifecycle inventory (LCI) databases and therefore data concerning these phases is taken directly from them. After production, the chips are integrated into the final application. It is the application that is used and disposed of in the end. Intermediary transportation phases interlace within these phases. Microelectronic chips are integrated into a wide variety of applications, so use and transport are too vast and varied for detailed study here. These phases are therefore only considered in general here, in order to determine their part of impacts and the categories involved (see Section 3.1).

Fig. 2. General phases in a component lifecycle.

Figure 2 resumes the details that have to be accounted for to determine the environmental impacts of the microelectronic chips. From the supply chain, it is necessary to identify raw material compositions; chemical compositions and densities; gas compositions and densities; as well as the suppliers footprints. During microelectronic manufacturing and packaging, it is necessary to specify raw material masses; chemical, gas and water volumes or flows; machine power and the length of the processes. Hypotheses have usually to be made for the future end of life scenarios and the compositions and densities of the gases emitted must be estimated as well as polluting effects from the lixiviation of metals.

Scientific reviews in literature

Compared to other sectors, microelectronics seems to fall behind in the environmental field. Analysis of the current state of art regarding LCA of microelectronic chips alone is insufficient to draw the profile of this complex industrial sector. Indeed generic literature reviews showed that very few LCArelated cases of study from industrial initiatives have been published [START_REF] Schischke | Life cycle inventory analysis and identification of environmentally significant aspects in semiconductor manufacturing[END_REF][START_REF] Taiariol | Life cycle assessment of an integrated circuit product[END_REF][START_REF] Dickinson | Application of the sustainability target method: supply line case studies[END_REF]. Moreover, Schmidt et al. (2011) found that the present eco-invent dataset for wafers fabricated for ICs was obsolete because it "shows large differences" with the results from deeper studies. There are several reasons to explain the limited state of art compared to other industries. First of all, up to now, the microelectronic sector has replied to external pressure without particularly having to change its natural strategic roadmaps. The semiconductor industry is essentially driven by Moore"s law (Shaller, 1997), which states that the number of transistors that can be placed inexpensively on an IC doubles approximately every two years. This trend tends to induce a beneficial effect on the environment because there are more components per wafer (the unit of production) for quasi equivalent manufacturing flows between different generations. Moreover, smaller transistor devices also naturally consume much less energy in use. Technological roadmaps for packaging also tend to reduce the mass of packaging and add the possibility of encapsulating several components in one package, which further reduces raw material consumption. Besides, the application of the RoHS directive alone strongly contributes to reduce impacts on human health, especially during end-of-life treatment. Another possible explanation is that microelectronic applications are reputed to consume much less energy than other traditional industrial sectors. However, as [START_REF] Bonvoisin | An integrated method for environmental assessment and ecodesign of ICT-based optimization services[END_REF] remarked, although microelectronic chips embedded into applications provide services that may help to avoid impacts, they use impact-intensive semiconductor technologies and it is therefore necessary to insure that the impact reductions they allow at least balance the impacts generated by the infrastructures they rely on. The scientific community has therefore expressed concern on the LCA quality of microchips. The evergrowing technological complexity is a major obstacle for LCI in the manufacturing phase [START_REF] Schischke | Is small green? Life Cycle Aspects of Technology Trends in Microelectronics and Microsystems[END_REF]. Since most existing LCI databases had been piloted by other industries, data reliability of models for dedicated materials (moulding resins, ultrapure chemicals, pre-doped wafers or packaging substrate) is too low for microelectronic purposes [START_REF] Plepys | The environmental impacts of electronics. Going beyond the walls of semiconductor fabs[END_REF]. These singularities hinder the realization of in-depth analysis at a sectorial scale.

The profession's knowledge on environmental responsibility

To compensate lacking literature and understand how the microelectronic industry faces environmental questions during production, eight interviews with actors of environment strategies and policies were conducted in a leading semiconductor company. The company is well representative of the sector: factories are located worldwide; all the design centres and manufacturing plants are certified ISO14000; the products, designed and manufactured internally, are competitive in the international market. The professionals that were interviewed are corporate business managers dealing with international legislation and external pressure; environmental experts in manufacturing sites dealing with local production concerns; and environment managers dealing with external pressure from regulations and customers in design centres, where the chips are actually designed. The question asked was to "classify the most sensitive environmental themes your activity has to manage". Critical themes were ranked with plus and minus marks (explained in Table 1-a). A mark was given for environmental reporting indicating the existence of stakeholder pressure: 1 if the pressure existed, 0 if not. The categories proposed were selected beforehand according to their availability in LCA software, like Gabi 7 or SimaPro 8 . As environmental issues can be very different, front and backend sites were studied separately. The results of the interviews are summarised in Table 1-a. and generation of waste (waste). Here, most of the categories are covered by environmental reporting except for water acidification and waste. The last group is not considered as an important concern of the industry: noise, ozone layer depletion, air and soil toxicity, land occupation and smell. Some differences can be seen between the front and back-end sites. The major difference in the front end sites results from the intensive use of ultra-pure water affects the water stress which is far less important in the back-end sites. Also, more intensive use of acids affects the front-end sites more than the back-end (acidification and eutrophication), however in some front end-sites adequate treatment of waste water and air reduces, or eliminates these problems. Back-end sites have more difficulties with water toxicity and waste due to the use of metals.

As design and manufacturing view-points are very different, they were also treated separately. The results from the design centre interviews are summarised in Table 1-b. No influence or low positive/negative impacts, i.e. ecological sustainability is maintained (-)

Presence of medium and positive impacts (--)

Presence of high positive impacts The overall score is indicated by the different grey shades, darker for the most recurring effects. Some impacts strongly depend on plant location and the efficiency of treatment units: in this case there may be several marks.

Design has lower effects on the environment. Designers do not modify the production process itself; they however influence the use phase of the products to a great extent and do manually intervene on partially manufactured chips or packages for research and development purposes. The effects on the environment can be classed into three groups of categories. The major concerns are from global warming (design greatly effects the use phase of the chips, and therefore electrical consumption) and human health (manual intervention for research and development purposes). Then comes waste that is not directly a problem of design, but rather because certain customers prohibit certain alloys that affect recycling adversely. The other categories are not directly affected by design choices, except for resources, but in this case, technological evolutions generally have a positive effect because of shrinking sizes of chips and packages.

The Case of Rare Earth Elements

Recently, there have been growing concerns on the supply of rare earth elements (RREs) due to high market volatility and supply uncertainties from China [START_REF] Golev | Rare earths supply chains: Current status, constraints and opportunities[END_REF]. REEs enter into the fabrication of microelectronic products during different life cycle phases. However, precise information is not very easy to obtain and open sources are scarce. USGS 9 provides statistics and other information. In the case of microelectronics, REEs cited in literature (see for ex. [START_REF] Binnemans | Recycling of rare earths: a critical review[END_REF][START_REF] Long | Indicators to identify the agricultural pressures on environmental functions and their use in the development of agri-environmental measures[END_REF] essentially cover application products rather than actual semiconductor ICs. Devices like hard drive disks (magnets); nickel metal hydride batteries; glass (digital cameras); display panels; ceramic capacitors etc. often include REEs [START_REF] Long | Indicators to identify the agricultural pressures on environmental functions and their use in the development of agri-environmental measures[END_REF]. During the fabrication phase of semiconductor ICs, Cerium is used in chemical polishing processes [START_REF] Bleiwas | Preliminary Estimates of the Quantities of Rare-Earth Elements Contained in Selected Products and in Imports of Semimanufactured Products to the United States[END_REF], while REEs will be used in future ultra-thin oxides [START_REF] Iwai | Silicon integrated circuit technology from past to future[END_REF]. Currently, Praseodymium and Samarium are used for their magnetic properties in integrated MRAM circuits. A boom in the use of REEs in the semiconductor industry is expected in 2018.

According to [START_REF] Golev | Rare earths supply chains: Current status, constraints and opportunities[END_REF] REE processing is characterized by high levels of water consumption, energy inputs and chemical use. Land allocation can also be significant for both mining and processing operations, as well as for the tailings dams, and long term storages of the radioactive materials [START_REF] Golev | Rare earths supply chains: Current status, constraints and opportunities[END_REF]. Recycling techniques have appeared recently, such as for lamp phosphors; nickel metal hydride batteries; and magnets but concern only relatively small quantities [START_REF] Binnemans | Recycling of rare earths: a critical review[END_REF].

Current recycling processes focus mainly on REEs in magnets (USGS, 2014). Recycling is however not well developed and neglected for semiconductors today, because of technical difficulties as well as the small quantities in play [START_REF] Binnemans | Recycling of rare earths: a critical review[END_REF][START_REF] Golev | Rare earths supply chains: Current status, constraints and opportunities[END_REF].

Discussions on environmental knowledge in the industry

The observations made in this section consolidate first impressions that the knowledge on chip lifecycles is weak, even within the microelectronic companies, and needs to be reinforced. Although the evaluations were subjective and qualitative, it was not easy to distinguish how the chips really impact the environment from the simple expression of external international pressure. Furthermore, the "electronification" of society made it difficult to define a "standard chip" that could be used as a reference for discussion.

External pressures converge on specific concerns: climate change, energy saving, resource conservation, e-waste and water consumption. However, these consensual aspects provide a narrow scope to the issue and depend on the application or on the particular case and are not scientifically proved. To determine an environmental profile of a chip, an international consensus is necessary to characterise the impacts of the semi-conductor sector activities. The state-of-the art showed that life cycle thinking is not yet mature in the sector and we can conclude on the need to define standards for reporting on chip performance. The definition of standard indicators must meet stakeholder expectations, ensure that the microelectronic sector is responsible in relevant environmental issues and make comparison of chip profiles possible.

Environmental impacts of microelectronic components

This section aims to determine a complete list of significant environmental pressures by identifying the flows during the chip lifecycles that cause most of the environmental changes. To do so, a methodology including both direct and indirect impacts is proposed. The direct impacts can be directly controlled by chips manufacturers. Indirect impacts include all the effects that result from the purchase and the use of the chip, the manufacturing of raw materials, the production of energy to use the chip and chip disposal.

Repartition of the environmental impacts of a chip during the life cycle phases

As literature is quite poor, a LCA study was performed in an industrial context with one of the international leaders in the semi-conductor field in 2009 [START_REF] Villard | Développement de méthodologies d"éco-conception pour le secteur microélectronique[END_REF]. It was carried out on four representative products of the industry: a microcontroller embedded in cars, a security card managing access to television, a memory for play stations and a circuit board with several chips used for battery control in cell phones. The results of the study are displayed in figure 3. They show that for global warming, the most significant aspects of a chip are alternatively related to manufacturing and use by the end-user. [START_REF] Villard | Développement de méthodologies d"éco-conception pour le secteur microélectronique[END_REF].

Fig. 3. Carbon dioxide emissions (IPPC) in 4 case studies

These results agree with other results reported in the recent state of the art. [START_REF] Higgs | Developing an overall CO2 footprint for semiconductor products[END_REF] and [START_REF] Boyd | Life-cycle assessment of computational logic produced from 1995 through 2010[END_REF] showed that for memories and compilation logic components the largest impacts were in the use phase. However they cannot be generalised to all chips. Schmidt et al. ( 2011) studied manufacturing and found that the contribution of the value chain compared to the whole manufacturing impact varied from 15% to 98% in function of the damage categories of IMPACT2002+ 10 indicators. Detailed results for manufacturing, use and transport phases of a current microelectronic product assessed by Simapro 8 using IMPACT2002+ indicators are provides in Table 3 [START_REF] Villard | Développement de méthodologies d"éco-conception pour le secteur microélectronique[END_REF]. [START_REF] Bare | Traci[END_REF]. These results were based on front-end production. In the internal case study carried out here, the contributions, including the back-end, vary from 6 to 58%. Moreover according [START_REF] Williams | Environmental impacts of microchip manufacture[END_REF], the scope for LCA of a chip must focus in priority on the secondary raw materials used by the processes rather than the material structure. These results lead us to conclude on the importance of separating the impacts from the manufacturing plants and the impacts due to the value chain before manufacturing and after manufacturing.

Impacts of the manufacturing plants

A top-down approach considers the impacts of manufacturing plants as a whole. It considers both manufacturing operations and facilities. Chip manufacturing requires an extremely clean environment. This involves energy intensive heating, ventilation and air conditioning units. According to a report of Lawrence Berkeley National Laboratory (2000), process tools represent 35% of electricity consumption in semiconductor fabrication. The top-down approach also presents the interest of not specifically focusing on a particular chip family and therefore avoids drawing conclusions on marginal chip families. Using a top-down approach is only relevant because industrial activities are homogenous in all front-and back-end plants.

In front-end plants, silicon wafers are processed in iterative homogenous cycles of surface treatment, called mask levels. Any component can be seen as a series of mask levels and its complexity is directly dependant of the number of masks. In back-end plants, there are about 20 families of packages. Within each family, only the size and number of interconnections (pins or balls) differ. This provides a very simple way to describe the environmental burden with a unique parameter characterizing both production and technology: the number of masks in the front-end and the number of pins in the backend. The input inventories of typical front-end and back-end processes are presented in Tables 4-a and b [START_REF] Villard | Développement de méthodologies d"éco-conception pour le secteur microélectronique[END_REF]. As production is also comparable from one plant to another, the conclusions can be extended to the whole industry. Environmental management systems applied to sites help understand the evolution, the problems and the most significant pollutions that can be attributed to industrial activities. In ISO 14000 certification, a list of significant aspects is regularly updated in function of severity, frequency, control and sensitivity of the environment. These aspects are related to air, water, soil or waste, and are generated by the plant itself, the processes or the activities. The lists are shown in Tables 5-a and b respectively for front-end and back-end manufacturing sites. The significant aspects observed in the top-down approach on the macroscopic scale of a microelectronic plant are representative for a single component and the results can therefore be compared to the chip in a bottom-up approach (Section 3.3). Intensive electricity consumption Indirect effects due to energy use

Impacts of the up-phase value chain

The up-phase value chain is the supply chain producing inputs for the manufacturing plant. A bottomup approach to the environmental assessment of semi-conductor manufacturing considers a particular chip family by studying the input and output flows of each step in production. In a bottom-up approach of the supply chain, the focus is on the quantities of raw materials used in the manufacturing process without considering manufacturing plants performances. Results of the analysis of the supply chain can be found in literature.

In key LCA-related papers [START_REF] Schischke | Life cycle inventory analysis and identification of environmentally significant aspects in semiconductor manufacturing[END_REF][START_REF] Williams | The 1.7 kilogram microchip: energy and material use in the production of semiconductor devices[END_REF]Smati et al., 2001), the impacts underlined were related to global warming, water and energy use. [START_REF] Cullen | The Environmental Performance Strategy Map: an integrated LCA approach to support the strategic decision-making process[END_REF] placed global warming, energetic resources depletion and particle emissions as the most significant aspects. Besides, for Chang and Kim (2011), the different chemicals used in considerable amounts during chip manufacturing were responsible for effects on toxicity of eco-systems and health. Most of these papers consider a restrictive set of environmental aspects. However, a state of the art permits to highlight the most damaging items of the supply chain (Table 6). Our internal case study highlighted a particular environmental aspect: rare gas production, used during manufacturing (helium and argon in vacuums of etching and Chemical Vapour Deposition (CVD) and xenon used during ionic implantation). In-house study

The aspects identified will modify the state of the surrounding environment. This requires understanding how these forces contribute to the state of the environment and so what indicators should be used to characterise their effects. A review on different sectors (mining, chemistry, electricity producers) helps to define the main aspects of raw material production (Table 7). The relative impacts of raw materials are characterised by scores from databases like CML 12 , TRACI or USEtox 13 using Eco-Invent 14 items.

Impact of the down-phases

The down-phases of the value chain are situated after the manufacturing plant and include the electronic application: chip distribution, use and disposal.

12 CML: Chain Management by Life Cycle Assessment -http://www.cmlca.eu/ 13 UseTOX: http://www.usetox.org/ 14 Eco-Invent: http://www.ecoinvent.org/database/ The effects of use phase are due to emissions generated by electricity consumed in the final application. Product disposal issues are linked to the end of life treatment of heavy metals: lixiviation of metals in landfill leading to soil pollution and metals released into the atmosphere after incineration. LCA showed that for all disposal scenarios, including the worst cases, the impact of end of life represents less than 0.1% of the total impact and can therefore be neglected (fig. 2). Concerning transport of the product itself, wafers are transported from front-end sites to back-end sites.

According to sectorial roadmaps, wafer diameter increases while component size decreases and there is a similar trend for packaging with less mass and volume. Finally the environmental contribution of inhouse distribution remains a feeble part of the total impact of the product life cycle. Table 8 summarises the effects of the other life cycle phases.

Rare Earth Elements

As mentioned in section 2.4, impacts of REEs are currently neglected in the semiconductor industry because of the very small quantities used compared with other industrial sectors. REEs are automatically taken into consideration in LCA software like Simapro. However their impacts are differently included in impact calculation methods (for example, CML considers them) although this question is not specific to semiconductor products. In the future REEs in the industry should be surveyed if their use is considerably increased and the recycling of REEs in microelectronic products should be accounted for (though abiotic depletion indicators and water resources for example.

Environmental hot-spots

The previous section identified the aspects for which the environmental impacts must necessarily be considered. This section summarises the different impacts of semi-conductor manufacturing across the important life cycle stages and selects a reduced set of significant impact categories that cover all the issues that should be monitored. Next, the relevance of each impact category is carefully analysed. Indeed, one particular effect can be of more importance than others. Additionally, the same information can be considered twice leading to difficulties in the interpretation of LCA results and incorrect monitoring of performance.

Significant environmental impact categories

Table 9 starts by listing the main contributors to each impact category and indicates the life cycle phases that are concerned. It is now possible to choose a set of significant impact categories for the microelectronic industry.

A first set of categories is easy to define because it re-joins sectorial concerns on LCA: "global warming", "resources depletion" and "water stress". "Local summer smog" is also very relevant because it is the only category that takes into account the effects of the production and consumption of solvents and all the organic compounds. It also highlights one of the major issues of the production of electricity. "Eutrophication" is relevant too, because it takes into account the use of chemicals and ultrapure water in manufacturing.

Secondly, three categories "eco-toxicity", "acidification" and "modification of water composition" are highlighted to qualify the effects of chips on water quality. They all respond to the extensive use of hazardous chemicals in semi-conductor manufacturing.

It should be noted that the plants have no direct effect on "water acidification". Even though manufacturers are big consumers of acids in the wet cleaning processes for wafers, they generally end up eliminated in wastewater treatment plants.

The effects of the use of metals are highlighted by the second set of categories. Direct risks of toxicity are limited for workers and final users. The main direct risk linked to metals is their potential rejection to water so it is better to focus on water toxicity or human toxicity. Extensive needs for mineral extraction appears strongly in the first set of impact categories, under "resource depletion". However, some metals, especially copper, have a strong effect on acidification but these effects can also be taken into account in "toxicity", whereas indirect effects of liquid chemicals (acids and bases) are considered in the categories: "eutrophication" and "toxicity". Water composition, directly linked to the preservation of neighbouring eco-systems, is modified by microelectronic activities and also, presumably, by supplier activities. However, the main influences are already taken into account through "eutrophication" and "toxicity". The effects of silicon and fluor emissions in water are not extremely serious issues compared to phenomenon linked to toxicity in water (contamination of eco-systems) or eutrophication (deoxygenation of aquatic eco-systems).

Finally, the effects of waste could be considered. However, according to [START_REF] Ernst | La production de déchets non dangereux dans l"industrie manufacturière en[END_REF], an overview of the quantity of waste in manufacturing business shows that the consideration of waste in microelectronic industry is not really legitimate compared to other industrial sectors, all the more seeing that the recycling rate of plastic parts in back-end sites is improving. Furthermore, the risks of solvents and liquids are already taken into account in "summer smog" and the consideration as waste would therefore become redundant.

In conclusion, we propose to retain six of the ten initial impact categories that cover all the important sources of impacts: global warming, resource depletion, water stress, local summer smog, eutrophication and toxicity.

Considerations for suitable indicators

For each impact category, different indicators are currently available. Some of them have led to international consensus and others have advantages and drawbacks which must be taken into consideration. The selection of a particular model is neither a certification of the model, nor does it necessarily mean that it is the best available. ISO 14031, ISO 14044 and SETAC 15 working groups [START_REF] Dreyer | Comparison of three different LCIA methods: EDIP97, CML2001 and ECO-indicator99[END_REF] defined criteria for their evaluation that should be used to select indicators. Their proposals can be applied to the microelectronic sector. In this section, some additional more specific suggestions are proposed.

Resource depletion

The models for resource consumption and depletion can be very different according the life cycle impact assessment methods used. In our case, this category should be related to the extraction of minerals and fossil fuels, both energetic and mineral resources from ground, water and air, and including the use of rare materials (gases: xenon, argon and helium; and metals: palladium and gold).

To monitor electricity consumption during manufacturing, we prone the use of local electricity consumption, in mega joules, so as to compare energy performances of plants irrespectively of their location and the local energy mix. This indicator reflects the important issue concerning the control of electricity consumption during manufacturing and helps to define the most energy-demanding manufacturing steps. Indeed the local energy mix which the microelectronic industry is not necessarily responsible for tends to bias the interpretation of the electrical consumption of the manufacturing processes. This is especially true as the local energy mix efficiency is already taken into account in global warming reporting.

Water stress

Water stress results from the imbalance between water use and water resources and causes deterioration of fresh water resources in terms of quantity (aquifer over-exploitation, dry rivers, etc.) and quality (eutrophication, organic matter pollution, saline intrusion, etc.). Water consumption in temperate zones induces less critical impacts than in arid climatic zones where water becomes scarce and the resources available for exploitation and provision to populations are not equivalent. The water stress indicator measures the proportion of water withdrawal with respect to total renewable resources [START_REF] Alcamo | World water in 2025: global modeling and scenario analysis[END_REF]. It is a criticality ratio, which implies that water stress depends on the variability of resources. However, today, no indicator on water stress in terms of environmental impacts has yet been developed. Consequently, the only reasonable indicator available for use today is the imported volume of raw water. The ultra-pure water is taken into account because raw water is transformed directly in the plant"s ultrapure water generator.

Toxicity

Toxicity is measured regarding impacts on eco-systems or on human health. We advise the use of human health indicators because the risk assessment of chemicals is a real issue facing the microelectronic industry. The growing importance of these issues is reflected by recent accent on REACH and RoHS legislations in Europe and the rest of the world.

A final set of indicators

The six impact categories identified above can be resumed by a set of seven indicators. Summer smog (or photochemical oxidation) accounts for these pollutions.

Local electrical consumption

This indicator is the most suitable to account for the total energy consumed by equipments and facilities during manufacturing. It helps to identify hotspots.

Conclusion

This paper draws an environmental profile of products in the microelectronic industry. It proposes a reduced set of seven environmental indicators that cover the most significant effects on the environment caused during the life cycle of semiconductors. The indicators are global warming, abiotic depletion, and water eutrophication, imported volume of raw water, human eco-toxicity, summer smog and local electrical consumption. The indicators have been derived from practical considerations and observations in existing semiconductor front-end and back-end plants combined with information from databases, when they are sufficient, for stabilized processes. They also account for general profiles of product use and disposal. They can effectively be used to cover all the stages in semiconductor chip manufacturing.

The set of indicators will help construct more robust and systematic assessment methodologies for the semiconductor industry. This approach satisfies growing concerns expressed by stakeholders including issues on chemicals, global warming and water and energy consumption as suggested in the industry"s roadmaps. The indicators can be used to assess and improve environmental performances of semiconductor products in a full life cycle and multi-indicator prospective.

In line with ISO environmental recommendations, eco-design in the microelectronic industry must account for complete life cycle impacts, and be used in a systematic approach to chip design. LCA will help decision-making when it provides accurate indications covering the large spectrum of environmental effects and can be used during design phases. In this sense the paper encourages the industry to move a step further from current semiconductor roadmaps and establish a consistent policy of standard multi-indicators integrating the full life cycle of its" products.

Reducing the number of indicators to the most significant ones will strongly contribute to fixing priorities for environmental strategies. Drawing a profile of the impacts generated by the microelectronic chips can help making design decisions and determine the effectiveness of proposed solutions. During the chip lifecycles, the paper points out that the most significant aspects are linked to climate change, abiotic depletion, human toxicity, eutrophication and summer smog. These categories are attributed to heavy energy-demanding manufacturing process flows which consume and release large quantities of different chemicals (metals, acids, solvents). Besides these, energy flows (MJ) and water consumption (m 3 ) in equipment and facilities during manufacturing are also relevant indicators.

In the current state of art, the paper recommends that the microelectronic industry limit environmental analysis to these indicators. A reduced set of standardized significant indicators will more effectively underline environmental pressures caused by the industry and contribute to understanding the major causes of these impacts. They will also help control potential impact transfers, from one impact category to another and from one life cycle phase to another. In this way, the indicators contribute to building and driving environmental strategies. Impact assessment should therefore focus on these categories.

In conclusion, a standardized method for the environmental characterization of micro-chip technologies is necessary to compare the performance of different products and specify product profiles. A suitable set of LCA indicators strongly contributes to increase life cycle knowledge of the chips. They must be accepted by the international scientific community, be stable and induce reasonable and constructive remarks on the main contributors to impacts. In this paper, a set of seven indicators are proposed, consistent with current state of art, but they can be expected to evolve as new methods and indicators, such as biodiversity or water stress, become available in LCA software. This paper argues for the development of standard indicators leading to an international consensus, such as the case of global warming. Finally, the definition of a standard for indicators must be associated with the creation of similar standards for other LCA aspects: LCI, impact assessment methods, interpretation of results and publication.

Fig. 1 .

 1 Fig. 1. General phases in a component lifecycle.

Table 1 -

 1 a. Expert ranking of environmental concerns in manufacturing plants

	IMPACTS	REPORTING	FRONT END	SITES	BACK END	SITES	REASON FOR IMPACT CONTROL: DESIRABLE LEVEL OF SITE RESPONSIBILITY
	Toxicity in	1	++	+++	Many dangerous chemicals are consumed; the risk of toxic
	water						effects on health and ecosystems by waste water exists
	Global	1	+++	+++	Direct -perfluorocarbons (PFCs) -or indirect -energy -
	warming						emissions
							The level of severity depends on the efficiency of PFC treatment
							units
							Intensive use of electricity
	Resource	1	+++	+++	Intensive use of raw materials
	depletion
	Water stress	0	+++	+	Intensive use of ultrapure water
	Water	0	++	+	Many acids are consumed; the severity level depends on the
	Acidification						sensitivity of local ecosystems and the efficiency of waste water
							treatment plants
	Eutrophication	1	= / ++	+	Many acids are consumed; the severity level depends on the
							sensitivity of local ecosystems and the efficiency of waste water
							treatment plants
	Air	1	+ / ++	=	A few acidifying gases are used; the majority of emissions is
	acidification						controlled by air treatment units; site-dependent
	Summer smog	1	++/+++	++	Emissions in air due to general plant functioning; the severity
							level depends on the sensitivity of local ecosystems and the
							efficiency of Volatile Organic Compounds (VOCs) treatment
							units
	Human health	0	+	+	A few dangerous substances have to be managed for worker
							safety
	Waste	1	=	+	Considerable quantity of plastic waste; variable rate of recycling
	Noise	0	=	=
	Ozone layer	0	=	=
	depletion
	Toxicity in air	0	=	=	A few toxic gases are consumed; All are under control by air
							treatment units
	Land	0	=	=
	occupation
	Toxicity (soil)	0	=	=
	Smell	0	=	=

7 Gabi: http://www.gabi-software.com 8 SimaPro: http://www.pre-sustainability.com/simapro

Table 1 -

 1 a shows that in the manufacturing stages, three levels can be discerned. A first group concerns major issues of water toxicity, global warning, resource depletion and water stress. The group highlights intensive use of electricity, raw materials and chemicals. These categories are generally covered by environmental reporting, except for the notable case of water stress. The second group poses fewer problems and results from the consumption of acids (water and air acidification and eutrophication); air emissions (summer smog); manipulation of dangerous substances (human health)

Table 1

 1

		-b. Expert ranking of environmental concerns in design centres
		IMPACTS	DESIGN	REASON FOR IMPACT CONTROL:
			CENTRES	RESPONSIBILITY OF PRODUCT DESIGN
		Global warming	++	External requirements on the carbon footprint of chips
				Chip energy efficiency challenges (EuP)
		Human health	++	Dangerous substances to be banned by Design Centres (RoHS)
		Waste	+	No end of life responsibility of the chip but some customers
				require removing certain metal alloys, deleterious for recycling
		Acidification,	=
	Eutrophication, Land
	occupation, Noise, Odour,
	Ozone layer depletion,
	Summer smog, Toxicity
	(water, air, soil), Water
		stress
		Resources	-	Shrinking dimensions of chips and packages
	(++)	Presence of high and only negative impacts
	(+)	Presence of only medium and negative impacts
	(=)

Table 2 .

 2 Table 2 resumes major uses of REEs in products in the USA. Relative use of REEs for different application categories (extracted from[START_REF] Long | Indicators to identify the agricultural pressures on environmental functions and their use in the development of agri-environmental measures[END_REF]

	Use Category	Market Share by Volume (%)
	Catalysts	22
	Magnets	22
	Metal alloys	20
	Polishing	9
	Glass	9
	Phosphors	5
	Other	13

9 USGS: US Geological Survey: http://minerals.usgs.gov/minerals/pubs/commodity/rare_earths/

Table 3 .

 3 Relative

	Impacts according to IMPACT 2000+ for a microelectronic product (approximations
	based on Villard, 2009)
	IMPACT CATEGORY	MANUFACTURING	USE	TRANSPORT
	Carcinogens	85%	10%	5%
	Non-carcinogens	95%	5%	1%
	Respiratory inorganics	40%	40%	20%
	Ionizing radiation	5%	95%	1%
	Ozone layer depletion	70%	10%	20%
	Respiratory organics	45%	15%	40%
	Aquatic ecotoxicity	40%	55%	5%
	Terrestrial ecotoxicity	50%	40%	10%
	Terrestrial acid/nutri	35%	35%	30%
	Land occupation	30%	30%	40%
	Global warming	40%	35%	25%
	Non-renewable energy	10%	80%	10%
	Mineral extraction	99%	1%	0%
	For Boyd et al. (2010) studying the manufacturing of several generations of integrated circuits, this
	same contribution varied from 9% to 28% in function of the different damage categories considered

10 IMPACT2002+: Impact assessment methodology originally developed at the Swiss Federal Institute of Technology -Lausanne -http://www.impactmodeling.net/

Table 4 -

 4 a. Input Inventory of a Typical Front-End Plant Process (approximations based on Villard,

	2009)
	FRONT-END: DIE	70	MG
	Silicon	70	mg
	Chemicals	25000	mg
	Electricity/heat	1000	Wh
	Water, river	10	l
	Transport die	0,1	kg km
	Emissions to air	80	g
	Emissions to water	0,1	g
	Waste	10	g
	Table 4-b. Input Inventory of a Typical Back-End Plant Process (Villard, 2009)
	BACK-END : CHIP		4500	MG
	Metals		1500	mg
	Chemicals/Plastics/Minerals	600	mg
	Resin/epoxy		2000	mg
	Electricity		200	Wh
	Indirect chemicals		60	mg
	Raw Water		100	l
	Transport		50	kg km
	Emissions water		1	mg
	Emissions air		100	mg
	Waste		5	g

Table 5 -

 5 a. Significant input and output flows and their influence on the environment in front-end sites

	INPUT AND OUTPUT FLOWS	ASPECTS	STATE CHANGE
	INFLUENCING THE
	ENVIRONMENT
	Liquid substances containing	Toxic compounds in wastewater
	metals and toxic compounds
	Acids	Chlorine, Fluor, nitrogen and
		phosphorous compounds in
		wastewater, water pH change
	Bases	Nitrogen compounds in wastewater,	Degraded water quality: toxicity,
		water pH change	acidification, modification of
	Nitrogenous & phosphorous	Phosphorous and Nitrogen	composition, eutrophication
	substances	compounds in wastewater
	Silicon products	Silica compounds in wastewater
	Fluor compounds	Fluor compounds in wastewater
	Organic compounds	VOC formation	Degraded air quality
			Effects on local summer smog
	PFC, SF6	Direct emissions of greenhouse	Greenhouse gases released
		gases
	Toxic gases and liquids	Doping gases (silane, phosphine,	Toxicity for eco-systems in air and
		diborane)	water
		Liquids for photolithography
		(acetone, tetramethylammonium
		hydroxide)
		Etchants (nitrous oxide, chlorine,
		boron trichloride)
	Solvents / liquid acids	Hazardous waste	Hazardous waste
		Emissions of CO	Effects on local summer smog
	Infrastructures (boilers, air	Emissions of NOX and VOC	Degraded air quality
	treatment units)		Effects on local summer smog
	Energy (tools, facilities)	Intensive electricity consumption	Indirect effects due to energy use
	Ultra Pure Water consumption	Intensive water usage	Increased water stress
	Table 5-b. Significant input and output flows and their influence on the environment in back-end sites
	INPUT AND OUTPUT FLOWS	ASPECTS	STATE CHANGE
	INFLUENCING THE
	ENVIRONMENT
	Metals	Toxic compounds in wastewater	Degraded water quality
	Plastics	Plastic waste	Waste
	Organic compounds	VOC formation	Degraded air quality
			Effects on local summer smog
	Energy (equipment and facilities)

Table 6 .

 6 Literature studies of raw material contributions from up-phase manufacturing of a typical product

	INPUT AND OUTPUT FLOWS	SOURCES
	INFLUENCING THE ENVIRONMENT
	Electricity production	Schischke et al., 2001; Williams et al. 2002; Liu et al.,
		2010; Higgs et al. 2009, Andrae and Andersen 2004
	Metals production	Andrae and Anderson 2004
	Bulk gas production	Chang and Kim 2011, Higgs 2009, Schischke et al. 2004
	Organic chemicals	Chang and Kim 2011
	Ultrapure water production	Taiariol et al. 2001, Schischke et al. 20
	Ultrapure products	Higgs 2009
	PFC gas production	Liu et al. 2010
	Silicon substrate production	Higgs2009
	Package substrate production	Higgs2009
	Rare gas production

Table 7 .

 7 Literature studies and environmental impacts during up-phase production of raw materials

	PRODUCTION OF:	DIRECT EFFECTS	SOURCES
		Environmental pressure due to fossil fuels:
		-energetic resource depletion
		-greenhouse effect gas emission due to fuel
	Electricity	combustion -pollutant emissions into the atmosphere: acidifying	European Energy Agency, 2006 Dincer, 1999
		substances, particles and tropospheric ozone
		precursors
		-oil discharge
	Metals	Resources depletion, toxicity, acidification	Salomons 1995; Pizzol, 2011; Norgate, 2007
	Bulk gases (nitrogen, hydrogen and oxygen)	Electricity consumption during energy-consuming cryogenic processes	Smith and Klosek, 2001
	Organic chemicals	Photochemical oxidation, global warming	Bowman and Seinfeld, 1994
	Ultrapure water	Eutrophication (use of chemical products) Electricity consumption during purification phase	STMicroelectronics: performances of ultrapure water station
	Ultrapure liquid chemicals	Water and air pollution (various phenomena) Electricity consumption during purification phase	Weidenhaupt and Hungerbühler, 1997 Williams 2002
	PFC gases	Global warming, toxicity	Tsai, 2002
	Silicon wafer	Electricity consumption during energy-consuming process	Duque Ciceri, 2010
	Package substrate	Electricity consumption during energy-consuming process	Duque Ciceri, 2010
	Rare gases	Resources depletion	CML

Table 8 .

 8 Input and output flows and environmental impacts during down-phases

	INPUT AND OUTPUT FLOWS	ASPECTS	STATE CHANGE
	INFLUENCING THE
	ENVIRONMENT
	Electricity consumption	Electricity	Impacts linked to electricity
		production	production
	Electronic waste	Neglected	Neglected
	Transportation	Neglected	Neglected

Table 9 .

 9 Main flows and life cycle phases contributing to impact categories

	IMPACT	INPUT AND OUTPUT FLOWS INFLUENCING	SUPPLY	MANUFAC	USE
	CATEGORIES	THE ENVIRONMENT	CHAIN	TURING
	Global warming	PFC gases, electricity	x	x	x
	Resource depletion	Rare gases, metals, electricity	x		x
	Water stress	Ultrapure water production from tape water		x
	Local summer smog	Organic compounds, solvents, infrastructures,	x	x	x
		electricity (particles)
	Eutrophication	liquids Ultrapure water, nitrogenous and phosphorous	x	x
	Toxicity (aquatic, human)	Metals, toxic compounds in liquids, toxic gases	x	x
	Acidification	acids, bases, electricity Ultrapure chemicals, ultrapure water, metal (copper),	x		x
	composition Modification of water	compounds compounds, acids, bases, silicon products, fluorine Liquid substances: containing metals and toxic		x
	Hazardous waste	Solvents / liquid acids		x
	Waste (part of)	Plastics		x

Table 10 .

 10 Table10lists them and shows the major reasons for their choice as indicators suitable to draw the environmental profile of a chip. Final set of indicators and their relevance in the microelectronic industry the package, rejects a large range of metals, in different physical forms (particulate and solid). The release of metals in water induces potential effects on toxicity. This indicator showed the beneficial effect of the RoHS legislation. Other specific liquids (resins, solvents, silicon products, bases and acids) must be controlled regarding potential toxic effects during manufacturing and use in plants.Summer smogSeveral steps of wafer and package processing consume solvents producing VOCs and plant facilities damage the quality of air (boilers, air refrigerators).

	INDICATORS FOR IMPACT	RELEVANCE
	ASSESSMENT
	Global Warming	It is the most common indicator used to report on environmental changes. In
		the microelectronic industry it is all the more important that there is a huge
		amount of electricity consumed throughout the life cycle, including raw
		material extraction, energy intensive production processes and the use of the
		final product in an application. Moreover, a considerable quantity of PFCs is
		consumed during manufacturing.
	Abiotic depletion	Chip manufacturing consumes both energy and mineral resources (table 1).
		Other than coal, rare gases, precious metals and REEs should be mentioned.
		It is a crucial topic for the whole electronic industry.
	Water eutrophication	The quality of water surrounding microelectronic plants is largely damaged
		by intensive usage of nitrogen and phosphorous acids, especially in wet
		cleaning processes.
	Imported volume of raw water	Stress on water is mainly due to ultrapure water used for production and
		general plant functioning. Manufacturers are more and more challenged on
		water control issues.
	Human eco-toxicity	Manufacturing, especially

15 SETAC: Society of Environmental Toxicology and Chemistry -http://www.setac.org

ITU: International Telecommunication Union -http://www.itu.int/en/Pages/default.aspx

ESIA: European Semiconductor Industry Association -http://www.eeca.be/esia/home

ITRS: International Technology Roadmap for Semiconductors -http://www.itrs.net/home.html

SEMATECH: http://sematech.org/index.htm

TRACI: Tool for the Reduction and Assessment of Chemical and other Environmental Impactshttp://www.earthshift.com/software/simapro/traci2


Zahia Bidai
email: bidai.zahia@univ-oran.dz

Moufida Maimour
email: moufida.maimour@univ-lorraine.fr

Interference-Aware Multipath Routing Protocol for Video Transmission over ZigBee Wireless Sensor Networks

Keywords: IEEE 802.15.4/ZigBee, MPEG-4 video, Multipath routing, Interference, Performance evaluation

The IEEE 802.15.4/ZigBee technology is emerging as an important wireless sensor networking solution for short and medium range communication due to its numerous advantages. On the other hand, multimedia applications have gained increasing popularity that gives us the opportunity to improve this technology to support video transmission. In limited bandwidth ZigBee networks (250 kbps at 2.4 GHz), how to increase the throughput in constrained environments has become the main challenge. Multi-path becomes a crucial feature in supporting video transmission. Using simultaneous multiple paths provides the bandwidth requirements of multimedia applications. Unfortunately, concurrent transmission creates the problem of inter-path interference mainly due to the broadcast nature of the underlying medium. In this paper, we propose an interference-minimized multipath routing to facilitate MPEG-4 video transmission over ZigBee-based WSNs. This latter is evaluated using comparison with an interfering multipath routing version and the single path routing under different video frame rates. Results show that the proposed interference-aware multipath routing for ZigBee-based WSNs can dramatically reduce the level of interference and thus maximize the overall throughput and improve the received video quality.

I. INTRODUCTION

Wireless Multimedia Sensor Networks (WMSNs) have been developed with the availability of low-cost cameras and microphones which allow a tiny sensor to be equipped with modules for collecting visual and audio informations. WMSN can significantly enhance a wide range of applications like object detection, recognition, tracking and video surveillance, etc. However, multimedia applications produce a huge amount of data to be transmitted with high reporting rates.

The importance of WSN has been enforced by the delivery of the most popular ZigBee technology [START_REF]Zigbee alliance[END_REF]. ZigBee is a standard for low rate wireless personal area networks (LR-WPANs) which is designed for low cost, low power and short range communications making it very suitable for WSN. ZigBee networks implement the IEEE 802.15.4 [START_REF]Ieee standards part 15.4: Wireless medium access control (mac) and physical layer (phy) specifications for low-rate wireless personal area networks (lr-wpans)[END_REF] as their physical and MAC layers. However, this technology suffers from its limited bandwidth (250 kbps at 2.4 GHz) and extending it to meet multimedia applications requirements is a real challenge.

Recently, video transmission over low data-rate networks becomes feasible thanks to a number of reasons such as advanced video compression techniques as MPEG4 and H.264 [START_REF] Richardson | 264 and MPEG-4 Video Compression Video Coding for Next-generation Multimedia[END_REF], advanced content based video segmentation and rate control algorithms. Such efforts have indeed contributed to reduce the complexity and difficulty of video transmission over such low rate networks. Various works were proposed to handle multimedia and high data applications over ZigBee networks and have focused especially on the MAC/physical layers [START_REF] Garcia-Sanchez | A cross-layer solution for enabling real-time video transmission over IEEE 802.15.4 networks[END_REF] [START_REF] Qin | Technologies to improve the performance of wireless sensor networks in high-traffic applications[END_REF].

At the network level, multipath routing approach can be used to satisfy the bandwidth requirement of multimedia applications. This approach, has been one of the most important current direction in the area of routing. It is known for its benefits to Adhoc and WSNs and allows the establishment of multiple paths between one source and a destination node. According to the application goal, multipath routing may be proposed in order to increase the reliability of data transmission (i.e. fault tolerance) or to provide load balancing and higher aggregated bandwidth since data packets can be propagated simultaneously over several paths. However, because a wireless channel is a broadcast medium, transmitting data concurrently over multiples paths seems to be less profitable than transmitting data over a single path and can annul all theoretical benefits of multipath routing if the effects of interpath interference are not controlled.

The overlapping of radio ranges of (some) nodes belonging to paths that are close to each other is known in the literature as the route coupling problem. Generally, the paths that have nodes or links in common are considered as strongly coupled paths. However, the route coupling problem can occur in multi-hop wireless networks even if two paths have no links or nodes in common (node disjoint paths). To reduce the effects of the route coupling problem, geographic routing based on localization is one of the most obvious techniques allowing construction of non-interfering paths [START_REF] Zijian | Energy efficient collision aware multipath routing for wireless sensor networks[END_REF]. Alternatively, other techniques such as radio resources management (using directional transmission [START_REF] Roy | Multipath routing in ad hoc wireless networks with omni directional and directional antenna: A comparative study[END_REF], multi-channel transmission [START_REF] Tarn | Joint multi-channel link layer and multipath routing design for wireless mesh networks[END_REF] , etc.), scheduling transmission (S-TDMA) [START_REF] Nelson | Spatial TDMA: A collision-free multihop channel access control[END_REF]) and the use of conflict graphs approach [START_REF] Wei | Interference aware multipath selection for video streaming in wireless ad hoc networks[END_REF] have been proposed to minimize the effects of the inter-path interference. However, geographic routing requires additional localization algorithms which consumes resources. The use of directional antenna to reduce interference also requires specific hardware equipment that may not be attractive for low cost wireless sensor nodes. Furthermore, although the multi-channel communication may increase network throughput and reduce interference, it requires a special mechanism at the MAC layer to support channels switching. This mechanism is costly in terms of energy consumption for WSNs and it is quite suitable for mesh networks than WSNs. Consequently, these approaches may not be effective solutions to reduce the negative effects of interference in many WSN applications with limited resources.

Wu and Harms [START_REF] Wu | Performance study of a multipath routing method for wireless mobile ad hoc networks[END_REF] introduced a metric called correlation factor, to measure the relative independance degree between two node-disjoint paths. The correlation factor of two paths is defined as the number of links which are inside the transmission range of each other. Another metric was proposed in [START_REF] Pearlman | On the impact of alternate path routing for load balancing in mobile ad hoc networks[END_REF] called route coupling. This metric describes the average number of nodes of a path that are blocked for receiving data while a node on another path transmits its data. Selecting paths with low correlation factor and route coupling offers better performances when several paths are used simultaneously as it was proved in [START_REF] Wu | Performance study of a multipath routing method for wireless mobile ad hoc networks[END_REF] and [START_REF] Pearlman | On the impact of alternate path routing for load balancing in mobile ad hoc networks[END_REF]. Nevertheless, both these approaches require the computation of the network connectivity graph to select minimized interference paths, the use of such technique in dense WSNs requires therefore intensive additional calculations. In contrast to the not suitable techniques for WSNs cited above, other approaches have been used to reduce the effects of inter-path interference.

Authors in [START_REF] Teo | Interference-minimized multipath routing with congestion control in wireless sensor network for high-rate streaming[END_REF] proposed an interference-minimized multipath routing (I2MR) protocol that increases throughput by discovering zone-disjoint paths and distributes network traffic over the discovered paths. Based on the first shortest path discovered, I2MR marks one and two-hop neighboring nodes of all the intermediate nodes along the first path as the interference zone of the primary path and constructs interference minimized secondary and backup paths through the nodes that are not marked as the interference zone of the primary path. In [START_REF] Maimour | Maximally radio-disjoint multipath routing for wireless multimedia sensor networks[END_REF], a Maximally Radio-Disjoint Multipath Routing (MR2) protocol is presented. MR2 addresses the interference problem between adjacent paths to satisfy the bandwidth requirements of multimedia applications. It utilizes an adaptive incremental technique to construct minimum-interfering paths. When the first path is built and becomes active, all the intermediate nodes along this active path should notify their neighboring nodes to act as the passive nodes in order to prevent them from participating in any route discovery process.

The broadcast nature of the wireless medium has been used by various multipath routing to achieve different purposes. For instance, the work in [START_REF] Radi | Interference-aware multipath routing protocol for qos improvement in event-driven wireless sensor networks[END_REF] proposes an adaptive iterative approach to construct minimum-interfering paths based on the broadcast nature of the wireless medium approach. A cost function, which considers, amongst other, the interference level that a node has experienced, is utilized to build such paths.

Unlike our work, none of the previously proposed solutions consider a low data rate ZigBee networks based on IEEE 802.15.4 standard and a real video traffic to evaluate the performance of the proposed multipath routing. Furthermore, the approach that blocks the neighboring nodes for constructing non-interfering paths introduces, either a highly complicated algorithm or a flooding strategy which imposes a high control overhead. In our proposed protocol, the overhearing characteristic of the wireless medium is used to construct node disjoint paths with minimum interference.

This paper is the extension of the authors previous publication [?]. We have designed and implemented a node disjoint multipath routing for ZigBee networks. The main goal was to increase the global throughput, basically insufficient in ZigBee-based WSNs, to satisfy bandwidth requirements for high traffic applications. We have showed that the quality of transmissions may be degraded due to interference, even though the paths are physically separated (node disjoint paths) and therefore, the selection of non-interfering paths is the main criterion to be addressed when simultaneous transmission through multiple paths is used.

In this article, we propose an enhanced ZigBee multipath routing taking interference into account when using simultaneous transmission data through multiple paths over ZigBee networks. The new contributions of this paper include : (i) defining a novel metric to estimate the interference level of each path during discovery phase to select multiple paths with a reduced effect of interferences, (ii) a video quality evaluation through the proposed interference-minimized ZigBee multipath routing from several Quality of Service (QoS) metrics at both the network and the application levels.

The rest of the paper is organized as follows. Section II describes two standards IEEE 802.15.4 /ZigBee and MPEG-4 video, which are used in the paper. Our proposed interferenceminimized ZigBee multipath routing protocol is described in Section III and Section IV provides our simulation results for video transmission over ZigBee networks. Finally, Section V concludes the paper. II. IEEE 802.15.4/ZIGBEE AND MPEG-4 VIDEO A. MAC IEEE 802. [START_REF] Radi | Interference-aware multipath routing protocol for qos improvement in event-driven wireless sensor networks[END_REF]

.4 and ZigBee

ZigBee is a robust wireless communication standard managed by the ZigBee Alliance [START_REF]Zigbee alliance[END_REF] and based on the IEEE 802.15.4 physical and MAC layers standard [START_REF]Ieee standards part 15.4: Wireless medium access control (mac) and physical layer (phy) specifications for low-rate wireless personal area networks (lr-wpans)[END_REF]. It defines a network layer, application framework as well as security services. The MAC layer defines two types of nodes: Reduced Function Devices (RFDs) and Fully Functional Devices (FFDs) and two operational modes, non-beacon-enabled mode and beacon-enabled mode. The ZigBee network layer defines how a network address is assigned to each participant ZigBee device and how a data packet is routed. ZigBee specification extends the basic star topology of IEEE 802.15.4 to a mesh or a cluster-tree topology. Two routing protocols are considered in ZigBee depending on the adopted topology. The table-driven routing (similar to AODV : Ad hoc On demand Distance Vector) is used in the mesh topology while tree routing is adopted for a tree topology.

B. MPEG-4 video

MPEG-4 [?] is among the most efficient compression formats in terms of bandwidth utilization. It is one of video streaming encoding technologies which generate low bit rate video streams, therefore it is suitable for bandwidth limited wireless networks. There are three types of MPEG-4 encoded frames which are I, P and B frame. An I frame is a frame compressed solely on the information contained in the frame, no other reference is made to any other video frames before or after it. A P frame is a frame that has been compressed using the data encoded in the frame itself and the predictions from preceding I or P frames. P frames require less bandwidth than I frames. Bidirectionally (B) frames are encoded using predictions from the preceding and succeeding I or P frames. All these different frame types are then combined in a specific repeating order to create what is known as a Group of Pictures (GoP ).

III. INTERFERENCE-AWARE ZIGBEE MULTIPATH ROUTING PROTOCOL

A. ZigBee multipath routing protocol overview

As mentionned above, the proposed multipath routing protocol is an enhanced of the protocol designed and implemented in our previous work [?]. It is a hybrid (proactive/reactive) node disjoint multipath routing protocol for ZigBee cluster tree based WSNs. To build multiple node disjoint paths, three main mechanisms were considered : (i) the MAC parent-child relationships between IEEE 802.15.4 devices in the cluster tree topology, (ii) the neighbor links maintained by every node using the neighbors table and (iii) the labelling scheme deduced from the ZigBee addressing scheme in order to apply our disjoint multipath routing. When the cluster-tree topology is formed, each node of the tree structure is assigned a label which describes the hierarchical path from the root (the PAN coordinator which corresponds to the network Sink) to it. To allow the construction of additional paths, we have, on the one hand, added new fields to the neighbors table. On the other hand, we have extended the parent-child relationships by non-tree neighbors relationships. When the node disjoint paths are built, the source node used two paths simultaneously for transmitting its data packets to the Sink. However, the data transmission quality may be degraded due to inter-path interference even if the paths are physically separated.

To improve the ZigBee multipath routing performances and make it more susceptible to support multimedia applications, we introduce a novel metric called Interference Level that calculates the interference level of the path P noted IL(P ) based on the overhearing approach. IL(P ) allows selecting multiple paths by reducing the effect of inter-path interference between paths as far as possible. The discovery of completely radio disjoint paths (no nodes in the interference range of each other) is not always feasible in real wireless networks. However, selecting node disjoint paths with minimum interference allows avoiding the performance degradation of wireless network and reaching the load balancing or bandwidth aggregation goals. The calculation of IL(P ) is performed during the discovery phase of node disjoint paths. The same path discovery messages sent by the source and the Sink in unicast mode were used to perform this calculation. The main advantage of this solution is to not overload the network with additional control messages.

B. Path interference level metric

The basic idea to calculate the path interference level is as follow: when the source detects an event and in order to reduce the end-to-end latency, it starts immediately transmitting data packets DP to the Sink using the proactive tree routing already established during the association phase at the MAC layer. Also, it starts the route discovery phase, which represents the reactive part of the multipath routing protocol, by sending the Explore message ExploreM sg to the Sink. ExploreM sg is forwarded (unicast and never broadcast) from node to node using forwarding decisions [?]. A node can compute the interfering nodes list when it overhears all the discovery messages from its neighbors correctly and without any loss. In instance, node 2 in Fig. 1 may know the interfering neighbors nodes belonging to other paths, namely, nodes 10, 12 and 13. However, node 2 may not overhear the discovery messages sent by these nodes due to link unreliability, if a message is lost, the list is incomplete. So to strengthen the interference level calculation process, the acknowledgment mechanism with ACK can be used at each hop. The data packets DP transmitted to the Sink can also be used for the IL(P ) calculation. When the Sink receives a DP or a ExploreM sg, it replies by transmitting a RepDP M sg or a ReplyM sg respectively along the proactive or the reactive reverse path estabilished during the path discovery phase. Whenever the reply messages move from the Sink to the source node on the reverse path, the total number of interfering nodes with nodes belonging to path P is calculated. with respect to other paths, we use hereinafter, the following notations :

• Long(P ) is the number of hops (links) of the path P .

• N b(P ) is the intermediate nodes number of the path P .

N b(P ) = Long(P ) -1. if the IN field associated to the neighbor u is zero then nodes of the path P (IN T (P )) is calculated as follows :

IN T (P ) = N b(P ) i=1 Size(IN L(i)) (1)
When the source node receives the reply packet from the discovered path P , it calculates the interference level of this path IL(P ) as a function of the total interfering nodes that interfere with this path and the number of the intermediate nodes of this path given by equation 2.

IL(P ) = IN T (P ) N b(P ) (2)
The best path is the one with the lowest value of the interference level. Table I shows that P 3 is the best path, following by the path P 2 and the last one is the path P 1 which is between the two other paths P 2 and P 3. In Fig. 1, we see that P 2 and P 3 are completely radio disjoint paths (spaced from each other by more than two hops), P 1 and P 3 are partielly radio disjoint paths and P 1 and P 2 are not radio disjoint paths.

Once the source node has calculated the interference level of each path, it sorts the values in ascending order and select the best pair of paths that minimize the inter-path interference for data transmission.

IV. SIMULATION RESULTS

Different simulations have been carried out to evaluate the performances of our interference-aware ZigBee multipath routing protocol with respect to the interfering ZigBee multipath routing version (without IL(P ) metric) and to the classical single ZigBee tree routing referred to Multipath-PIL, Multipath and Monopath respectively in our simulations.

For the tests, we selected one video sequence of QCIF resolution (128 * 128), called HallM onitor, encoded in MPEG-4 format with an open source f f mpeg encoder/decoder [?] and comprises 300 frames. The number of nodes in the network topology is fixed to 101 stationary nodes. Only a video sensor node captures, encodes and sends, over two paths, the video sequence to the Sink at the center of the area. The communication range is of 11m, it allows to cover at least three neighbors and at most eight neighbors. The nonbeacon mode with unslotted CSMA/CA mechanism of the IEEE 802.15.4 standard and the two-ray ground propagation model are used at the MAC and physical levels respectively. The MTU (Maximum Transfer Unit) size is 100 bytes. The frame rates is varied from 3fps to 24fps to evaluate different metrics for different routing strategies. All the experiments in this paper were conducted with an open source framework Evalvid [?] integrated to the simulator network NS2 with the IEEE 802.15.4 implementation provided by Zheng [START_REF] Zheng | NS2 simulator for IEEE 802[END_REF]. In our simulation study, B frames are not considered in order to minimize complexity process and latency caused by this type of frames.

Video quality was evaluated from a network level point of view by using QoS metrics, such as frame loss and throughput. At the application level, an objective metric was also used to analyse the perceived video quality by calculating the frame Peak-Signal-to-Roise Ratio (P SN R) [?].

The results show that when the number of frames per second increases from 3fps to 24fps, the network performance degrades due to the high rate of video frames loss which negatively affects the video quality received at the Sink. This is true for all the routing strategies. However, for a video traffic load less than or equal to 6fps (not exceeding the theoretical capacity of the network bandwidth 250kbps), we note that the non-interfering multi-path routing Multipath-PIL is more efficient than the two other routing strategies Monopath and Multipath in terms of frame loss rates (Fig. 2, Fig. 3), throughput (Fig. 4) and video quality measured by P SN R (Fig. 5). These results are explained by the fact that, when the network is overloaded, the single-path routing M onopath can not handle such a traffic load that exceeds its capacity while the inter-path interferences increase in the case of Multipath routing strategy, which lead to high frame loss rates that deteriorates the video quality.

MPEG-4 has particular characteristics. The received video quality not only depends on the frames loss rate but also on the nature of the lost data. Indeed, for MPEG-4 video, I frames provide reference information and are necessary for decoding P frames and therefore the loss of I frames has a greater impact on the quality of the received video than the loss of a frame of type P . As we can see in Fig. 3, the use of Multipath-PIL routing strategie reduces the percentage of I frames loss which ensures video playback improved for the user. These simulation results are consistent with those in Fig. 5, this can be explained by the fact that the lost of frames containing the most important information leads to a severe degradation of video quality.

The results also show that Monopath and Multipath routing strategies have almost the same behavior despite that the multipath routing approach offers several benefits over the monopath routing technique. These findings confirms that the use of simultaneous data transmission over multiple paths can be effective unless the effects of inter-path interference are minimized.

V. CONCLUSION

In this paper, we presented a multipath routing for ZigBee based WSNs to handle multimedia applications taking into account the effects of inter-path interference. The multipath routing tries to establish multiple node disjoint paths from the source to the Sink, calculates the interference level for each discovered path and gets to select the most noninterfering paths to send video traffic. Simulation results show that the proposed interference-minimized ZigBee multipath routing provides the best performances with regard to the two other strategies routing. This was found by evaluating the proposed protocol through QoS metrics and the well known objective metric P SN R as well as showing video frames. Thus, we can conclude that the proposed protocol is a multipath solution which provides a good human acceptable video quality required for applications like video surveillance where high video quality is not needed.

Figure 1 .

 1 Figure 1. Path interference level computationTo calculate the interference level of a path P (IL(P ))

  end ifThis algorithm measures the rate of overhearing that node w can record from different transmissions of ExploreM sg or DP packets carried in its vicinity. This overhearing rate is represented by the size of the list containing all neighbors of node w which belong to other concurrent paths and interfere with it. When the Sink receives ExploreM sg or DP packets, it replies by transmitting ReplyM sg or RepDP M sg packets respectively along the reverse paths. When an intermediate node u of the reverse path P receives ReplyM sg or RepDP M sg packet, it executes algorithm 2. For the other nodes in the neighborhood who listen passively ReplyM sg or RepDP M sg packet and do not participate in routing set their IN field to zero in order to discover other possible paths. IN T is a field of both ReplyM sg and RepDP M sg packets. It contains the total number of nodes that interfere with nodes belonging to path P . When the Sink sends these packets, the initial value of IN T is zero and, at each hop, this value is incremented by the number of nodes that interfere with each node along the reverse path. Details of the three discovered node disjoint paths P 1 : 4 → 3 → 2 → 1 → 0, P 2 : 4 → 14 → 13 → 12 → 15 → 0 and P 3 : 4 → 8 → 19 → 18 → 10 → 11 → 0, between the source node 4 and the Sink node 0 (Fig. 1) are shown in table I. The list of interfering nodes with the node i (IN L(i)) is calculated from the values of the IN field of each neighbor of the node i. They are neighbors that have the value 1 in their IN field. The total of nodes that interfere with the N b(P ) intermediate Algorithm 2 Calcul INT (P ) when receiving a ReplyM sg or RepDP M sg by a node u ∈ P Input : ReplyM sg or RepDP M sg packet. Output : update the IN T field. 1: for all neighbor v of node u do 2: if IN field of node v is égal to 1 then 3: increment the value of IN T of the ReplyM sg or RepDP M sg packet 4: end if 5: end for

Figure 2 .Figure 3 .

 23 Figure 2. I Frame loss rate for different frame rates

Figure 4 .

 4 Figure 4. Throughput for different frame rates

Fig. 6

 6 Fig.6displays a frame selected randomly from the transmitted video. It shows the benefits of transmitting simultaneously video traffic using the proposed protocol by comparing the received frame (Fig.6(b)) with the other solutions (Fig.6(c), Fig.6(d)) and also with the original frame (Fig.6(a)). The

Figure 5 .

 5 Figure 5. PSNR for different frame rates

Figure 6 .

 6 Figure 6. Frame 216 of Hall Monitor sequence video

  • IN L(i) represents the list of nodes belonging to other used paths that interfere with node i. • IN T (P ) represents the total nodes that cause interference with the path P . Algorithm 1 is executed when node w listens passively the unicast transmission of ExploreM sg or DP packet from the sender node u to the receiver node v. In this situation, node w is not the intended recipient of ExploreM sg or DP packet, but it has just heard it. IN (Interferent Node) is a field in the neighbors table of each network node. Initially, its value is zero, and it is sets to 1 for a neighbor when it is the source of a packet of type DP or ExploreM sg. Algorithm 1 Overhearing (following the overhearing of DP or ExploreM sg by node w.) Input : DP ou ExploreM sg packet. Output : update of the neighbors table of node w .

1: if the sender node u is a neighbor of node w then 2:

Table I CALCUL

 I OF IN T (P ) AND IL(P ) FOR THE EXAMPLE OF THE FIG. 1.

	Path Node i	INL(i)	Size of INL(i) INT(P ) IL(P )
		node 3	{14, 13}	2
	P 1	node 2	{10, 12, 13}	3	8	2.66
		node 1	{12, 11, 15}	3
		node 14	{3}	1
	P 2	node 13	{2, 3}	2	6	1.5
		node 12	{1, 2}	2
		node 15	{1}	1
		node 8	{}	0
		node 19	{}	0
	P 3	node 18	{}	0	2	0.4
		node 10	{2}	1
		node 11	{1}	1