Hossein Davarzani
email: h.davarzani@brgm.fr

Daniel Hube

Manfred Flum

Manuel Marcoux

Meteorological impacts on the transport of mercury vapor pollution in the vadose zone

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Abstract

Large amounts of mercury are widely spread out in ecosystems due to anthropogenic activities (from chlor-alkali plants for instance). Understanding the mechanisms of mercury vapor transport (which is mainly in its elemental form) from soil to the atmosphere and aquifer is necessary, principally, for assessing health potential effects on the environment following by an effective emergency response and removal program.

In this study, a theoretical model, taking into account non-isothermal conditions for transport of mercury vapor in unsaturated zone covered by a concrete slab is developed. The simulation of the mercury vapor transport from a pollution source zone shows a large difference on the soil vapor distribution between winter and summer. The mercury vapor emission changes in winter mainly because of onset of natural convection in the vadose zone. We also found that the diurnal variations of the atmospheric temperature affect strongly the transport of the mercury vapor in a thin layer of subsurface zone.

Finally, theoretical results are compared with the ongoing real case in-situ measurements obtained using dynamic flux chamber.


Javier Almendros

Rafael Abella

Mauricio Mora

Philippe Lesage

Time-dependent spatial amplitude patterns of harmonic tremor at Arenal volcano, Costa Rica: seismic wave interferences?

Abstract.

Seismograms recorded at the receivers of a small-aperture seismic array usually display very similar waveforms and amplitudes, as a consequence of their close proximity. During the analysis of the volcanic tremor wavefield at Arenal volcano, Costa Rica, we detected significant differences in the amplitudes of harmonic tremor recorded at the stations of a small-aperture (∼210 m) seismic array. The amplitude distributions are geometrically complex and characterized by strong gradients. They occur just for harmonic tremors; any other type of seismic event produces nearly uniform amplitudes across the array. This suggests some relation with harmonic frequency content. Moreover, the spatial amplitude patterns change with time. Some of these observations could be explained by an extreme combination of source, path and site effects. But they could be also produced by interference of different components of the seismic wavefield. We use numerical calculations to investigate the amplitude pattern generated by two interfering plane waves, and are able to reproduce the main features of the observed amplitude patterns. We propose mechanisms that might generate seismic wavefields with multiple components and conclude that interference can explain the complexity and variability of the harmonic tremor wavefield at Arenal volcano.

Introduction

Harmonic tremor is a continuous seismo-volcanic signal with a duration of minutes to hours and a spectrum characterized by the presence of several regularly spaced peaks. It has been reported at volcanoes around the world, for example Sakurajima, Japan [START_REF] Maryanto | Constraints on the source mechanism of harmonic tremors based on seismological, ground deformation, and visual observations at Sakurajima volcano, Japan[END_REF], Semeru, Indonesia [START_REF] Schlindwein | Spectral analysis of harmonic tremor signals at Mt. Semeru Volcano, Indonesia[END_REF], Erebus, Antarctica [START_REF] Rowe | Seismic and acoustic observations at Mount Erebus volcano, Ross Island, Antarctica, 1994-1998[END_REF], Soufriere Hills, Montserrat [START_REF] Neuberg | Models of tremor and low-frequency earthquake swarms on Montserrat[END_REF], Karymsky, Russia, and Sangay,

Ecuador [START_REF] Johnson | Plugs and chugs-seismic and acoustic observations of degassing explosions at Karymsky, Russia and Sangay, Ecuador[END_REF], Lascar, Chile [START_REF] Hellweg | Physical models for the source of Lascar's harmonic tremor[END_REF], and Arenal, Costa Rica [START_REF] Benoit | New constraints on source processes of volcanic tremor at Arenal volcano, Costa Rica, using broadband seismic data[END_REF]Garces et al., 1998a;[START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF][START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF].

Most studies of harmonic tremor are based on data from single seismic stations or distributed networks. They focus mainly on detailed investigations of the harmonic tremor spectrum and its temporal evolution, which constitutes indeed their most striking feature [START_REF] Schlindwein | Spectral analysis of harmonic tremor signals at Mt. Semeru Volcano, Indonesia[END_REF][START_REF] Benoit | New constraints on source processes of volcanic tremor at Arenal volcano, Costa Rica, using broadband seismic data[END_REF][START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF][START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF][START_REF] Maryanto | Constraints on the source mechanism of harmonic tremors based on seismological, ground deformation, and visual observations at Sakurajima volcano, Japan[END_REF]. Some of them also include analyses of wave polarization [START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF][START_REF] Lees | Explosions and periodic tremor at Karymsky volcano, Kamchatka, Russia[END_REF][START_REF] Maryanto | Constraints on the source mechanism of harmonic tremors based on seismological, ground deformation, and visual observations at Sakurajima volcano, Japan[END_REF], non-linear dynamics [START_REF] Julian | Period doubling and other nonlinear phenomena in volcanic earthquakes and tremor[END_REF]Lees and Ruiz , 2008], comparisons between seismic and acoustic observations [Garces et al., 1998a;[START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF][START_REF] Johnson | Plugs and chugs-seismic and acoustic observations of degassing explosions at Karymsky, Russia and Sangay, Ecuador[END_REF]Lees et al., 2008], etc. The origin of harmonic tremors is still poorly understood, although feasible models have been proposed.

We can mention the resonance of fluid-filled cavities [START_REF] Chouet | A seismic model for the source of long-period events and harmonic tremor[END_REF][START_REF] Benoit | New constraints on source processes of volcanic tremor at Arenal volcano, Costa Rica, using broadband seismic data[END_REF], the excitation of conduit walls due to unsteady fluid flow [START_REF] Julian | Volcanic tremor: nonlinear excitation by fluid flow[END_REF][START_REF] Julian | Period doubling and other nonlinear phenomena in volcanic earthquakes and tremor[END_REF][START_REF] Rust | The feasibility of generating low-frequency volcano seismicity by flow through a deformable channel, in Fluid motions in volcanic conduits: A source of seismic and acoustic signals[END_REF][START_REF] Fujita | Volcanic tremor induced by gas-liquid twophase flow: Implications of density wave oscillation[END_REF], and the repetition of highly periodic transients originated in the fluid dynamics [START_REF] Schlindwein | Spectral analysis of harmonic tremor signals at Mt. Semeru Volcano, Indonesia[END_REF][START_REF] Hellweg | Physical models for the source of Lascar's harmonic tremor[END_REF][START_REF] Johnson | Plugs and chugs-seismic and acoustic observations of degassing explosions at Karymsky, Russia and Sangay, Ecuador[END_REF][START_REF] Powell | Time dependent features in tremor spectra[END_REF].

In this paper, we investigate the seismic amplitudes of harmonic tremors recorded at the receivers of a dense, small-aperture seismic array deployed at Arenal volcano, Costa Rica.

The results show the occurrence of complex spatial and temporal patterns, and may shed some light on the nature of the harmonic tremor wavefields.

Harmonic tremors at Arenal volcano

Arenal is a small stratovolcano located in northwestern Costa Rica (Figure 1). It remained very active during 42 years from 1968 when eruption began, until october 2010, when the volcanic activity suddenly stopped. During this period, volcanic activity was characterized by lava extrusion, strombolian explosions, and gas emissions, at an approximately constant rate [START_REF] Williams-Jones | A model of degassing and seismicity at Arenal volcano, Costa Rica[END_REF][START_REF] Wadge | The magma budget of Volcán Arenal, Costa Rica from 1980 to 2004[END_REF]. The magma composition was almost constant as well, suggesting a steady recharge of the magmatic chamber (Streck et al., 2002). Seismic activity was characterized by a variety of signals including harmonic and spasmodic tremor, explosion quakes, long-period (LP) events, rockfall events and some volcano-tectonic (VT) swarms [START_REF] Alvarado | First observations of volcanic seismicity at Arenal volcano (Costa Rica) using a new three-component seismic digital network[END_REF][START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF]. Some of the events were accompanied by acoustic waves [START_REF] Barquero | Arenal volcano (Costa Rica) premonitory seismicity[END_REF]Garces et al., 1998a;[START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF].

Harmonic tremor was the most conspicuous seismic signal at Arenal volcano, lasting several hours per day. The fundamental frequencies are generally around 1-2 Hz [START_REF] Benoit | New constraints on source processes of volcanic tremor at Arenal volcano, Costa Rica, using broadband seismic data[END_REF][START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF], although they are far from stable. Detailed analyses of the spectral content of Arenal harmonic tremors [START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF] show the occurrence of a few distinct behaviors: (1) smooth variations of the fundamental frequency (and its overtones) as large as 50% in time scales of minutes to tens of minutes (frequency gliding); (2) sudden jumps in the fundamental frequency (and its overtones); (3) generation of harmonic tremor following some LP events or explosion quakes and evolution of harmonic tremor into spasmodic tremor and viceversa; and (4) simultaneous presence of several, independent systems of overtones, indicating the activation of multiple tremor sources.

The interpretation of the spectral properties of Arenal harmonic tremor in the framework of different source models and the comparison between seismic and acoustic observations hint at a shallow source at the volcano summit [Garces et al., 1998a;[START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF].

Quantitative source locations using multiple seismic arrays [START_REF] Metaxian | Locating sources of volcanic tremor and emergent events by seismic triangulation: Application to Arenal volcano, Costa Rica[END_REF] show that the seismogenetic area lays within 600 m of the active crater. The sources of discrete LP events and explosions are also located in the same area [START_REF] Alvarado | First observations of volcanic seismicity at Arenal volcano (Costa Rica) using a new three-component seismic digital network[END_REF][START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF][START_REF] Metaxian | Locating sources of volcanic tremor and emergent events by seismic triangulation: Application to Arenal volcano, Costa Rica[END_REF]. Moreover, moment tensor inversions hint to a source at about 100 and 200 m depth under the crater for tremor and explosions, respectively [START_REF] Davi | Moment tensor inversion of explosive long period events recorded on Arenal volcano, Costa Rica, constrained by synthetic tests[END_REF][START_REF] Davi | Seismic source mechanisms of tremor recorded on Arenal volcano, Costa Rica, retrieved by waveform inversion[END_REF]. Thus the source of Arenal harmonic tremors seems to be linked to the fluid dynamics of the active volcanic conduits located at shallow depths below the crater.

Instruments and data

In February 2004 a dense, small-aperture seismic array was deployed during 2.5 days (Feb 22 01:00 -Feb 24 14:00) on the western slopes of Arenal volcano, at about 2 km from the volcano summit (Figure 1). The array was composed by 19 short-period Lennartz LE-3Dlite seismometers, with natural frequency of 1 Hz. We used Reftek 130 dataloggers with a sampling frequency of 100 sps. Synchronism was achieved using GPS time. The seismometers were distributed in a spiral configuration (Figure 1) with an aperture of 210 m. Stations are numbered clockwise from the array center. Stations 1-5 are located near the center and stations 10, 13, 16, 19 are the farthest to the west, north, east, and south, respectively. Station 13 did not work for the first 20 hours and a few more stations were intermittently up and down from 12:00 to 14:00 on February 22.

The seismic data recorded during the 60-hour interval of array operations reflect the continuous character of the volcanic activity at Arenal volcano. The data contain several (∼200) LP events and different types of volcanic tremor. Harmonic tremor characterized by narrow peaks at equal frequency intervals is conspicuous, covering about 75% of the time.

Spatial amplitude patterns at the array stations

Seismic records from small-aperture arrays usually display similar amplitudes and waveforms. This is a consequence of the close proximity of the array receivers and constitutes the basis of array processing techniques.

Figure 2a shows the waveforms of an LP event recorded at the 19 array stations. We can see that amplitudes are similar at all stations. This is the expected behavior of a plane wavefront propagating in a homogeneous medium. In other words, this is the expected farfield behavior when the effects of attenuation, wavefront distortions due to the topography and other lateral heterogeneities, local velocity anomalies under the stations, etc., are small.

In order to quantify the amplitude of the seismic wavefield recorded at the different array channels, we use the RMS of the filtered vertical-component seismograms. We select the 1-4

Hz band for the analysis, mainly for two reasons: (1) this band contains most of the energy of the LP seismicity and the fundamental peak of harmonic tremors; and (2) wavelengths are large compared with interstation distances, which ensures that the similarity of waveforms is maintained. Figure 2b shows the filtered traces (left plot) corresponding to the window highlighted in Figure 2a Figure 3a shows a sample of two minutes of vertical-component array data corresponding to a harmonic tremor with a dominant frequency of about 2 Hz. During the first part of the window, tremor amplitudes are similar at all stations, just as in the case of the LP event described above. However, a closer look at Figure 3a shows that a minute later the amplitude pattern of harmonic tremor is significantly different. If we compare the two highlighted windows, we find that at station 19 (the southern tip of the array) tremor amplitudes are approximately the same; while at station 1 (located at the array center) the tremor amplitude is clearly larger for the first window. Figure 3b shows the filtered data, absolute RMS, and normalized RMS displayed at the corresponding station locations for the first window highlighted in Figure 3a. The amplitudes are approximately constant throughout the array, as denoted by the flat curve of RMS versus station number, and the light colors of the normalized RMS plot. Figure 3c corresponds to the analysis of the second window highlighted in Figure 3a. In this case, the amplitudes are large in the north and south stations, at the same level than the data shown in Figure 3b. However, amplitudes are quite small around an ESE-WNW band across the array center. For some of them, amplitudes are as low as 20% of the maximum. The comparison of the right plots in Figures 3b and3c shows that the wave amplitude distribution varies both in time and in space throughout the array, even if the waveforms remain similar. Therefore, we have to state the conclusion that seismograms recorded at very close stations do not always display similar amplitudes. We underscore that both patterns shown in Figure 3 In order to visualize the temporal variations of the amplitude patterns at the array for all the dataset (60 hours), we calculate the RMS at every station using a 10-s moving window, These patterns remain stable from tens of seconds to minutes. The right plots of Figure 5 show the average spatial amplitude patterns observed within the windows marked by dashed lines in the left plots, where amplitude differences are noticeable and stable. These windows are dominated by harmonic tremor, as can be seen in the spectrograms. Dark circles indicate that, at those particular stations, harmonic tremor reaches only a small fraction of the amplitude recorded at other, nearby stations. The patterns are quite diverse, reflecting that they are not linked to any particular site or receiver. There are periods with uniform amplitudes followed by periods with strong amplitude differences among the array stations.

At this point, it is very important to underline that the stations with reduced amplitudes are not always the same. Hence, it appears that the spatial amplitude distributions produced by the seismic wavefield at our array are geometrically complex and strongly time-dependent at time scales of minutes.

The presence of strong spatial amplitude gradients at the seismic array is very common in our dataset, and is usually linked to harmonic tremors. Complex amplitude patterns are clearest during harmonic tremors with clean, well-developed overtones and relatively stationary fundamental frequencies. They are least obvious during episodes of fast frequency gliding or when multiple sets of overtones appear simultaneously. Other types of signals (tectonic earthquakes, LP events, spasmodic tremor, even background noise) are recorded with approximately uniform amplitudes at all array receivers (see Figures 2 and5).

Origin of the complex spatial amplitude pattern of harmonic tremor

Any mechanism proposed to explain the origin of the amplitude variations detected at the array has to take into account the observations described in the previous section: (1) there are large amplitude differences among array stations separated by just 20-200 m, which produces strong amplitude gradients; (2) the spatial amplitude patterns at the array stations are geometrically complex;

(3) they are stable at time scales of tens of seconds, but change drastically with time at longer scales; and (4) these patterns are related solely to harmonic tremors and disappear for any other type of seismic events.

Source, path, and site effects

The first two observations above can be explained invoking extreme site and/or path effects. Site effects related to a heterogeneous shallow structure under the array may produce differential amplifications at the array stations [START_REF] Aki | Seismic monitoring and modeling of an active volcano for prediction[END_REF][START_REF] Almendros | Microtremor analyses at Teide volcano (Canary Islands, Spain): Assessment of natural frequencies of vibration using timedependent horizontal-to-vertical spectral ratios[END_REF][START_REF] Tramelli | A detailed study of the site effects in the volcanic area of Campi Flegrei using empirical approaches[END_REF]. Site effects at Arenal volcano have been investigated by [START_REF] Mora | Study of seismic site effects using H/V spectral ratios at Arenal volcano, Costa Rica[END_REF] and [START_REF] Mora | Shallow velocity structure and seismic site effects at Arenal volcano, Costa Rica[END_REF]. They found that the shallow structure under our array site is laterally heterogeneous, as evidenced by a refraction profile and by the different behavior of the H/V ratios at nearby stations. They also observed strong variations of the relative amplitude of the harmonic tremor spectral peaks between close stations (∼200 m) of linear arrays located on the east and west flanks of the volcano. Using H/V spectral ratios, they were partially able to relate these variations to the shallow velocity structure.

We have also calculated H/V spectral ratios using the current array data. Figure 6 displays the H/V spectral ratios calculated by using the Geopsy software (www.geopsy.org, e.g.

Wathelet et al. [2008]

). The distribution of peak frequencies clearly shows two regions.

Stations 11 to 16, located at the northern and eastern parts of the array, are characterized by frequencies of 1.6 Hz, while the remainders have frequencies close to 2 Hz. The transition in frequency occurs in a few tens of meters, as can be observed between stations 10 and 11 and between stations 16 and 17. This is probably related to a strong local heterogeneity in the shallow structure below the array. However, no geological evidence of such heterogeneity is observed at the surface.

These results indicate that site effects may be partially responsible of the disparate seismic amplitudes observed in the array records. Path effects related to wavefield distortions and seismic energy focusing [START_REF] Auger | Locating and quantifying migration and ava analysis of reflected and converted waves: An application to the Mt. Vesuvius volcano[END_REF][START_REF] Blacic | Converted phases analysis of the Campi Flegrei caldera using active seismic data[END_REF][START_REF] Garcia-Yeguas | Quantitative analysis of seismic wave propagation anomalies in azimuth and apparent slowness at Deception Island volcano (Antarctica) using seismic arrays[END_REF], effect of surface topography [START_REF] Almendros | Spatial extent of a hydrothermal system at Kilauea Volcano, Hawaii, determined from array analyses of shallow long-period seismicity[END_REF][START_REF] Ripperger | Seismic wave simulation in the presence of real volcano topography[END_REF][START_REF] Metaxian | Locating volcanoseismic signals in the presence of rough topography: wave simulations on Arenal volcano, Costa Rica[END_REF], etc., may also produce variations of seismic amplitudes among nearby stations.

However, since the volcano velocity structure does not change significantly with time (at least at short time scales), site and path effects by themselves are not able to explain the third observation above.

In order to explain the temporal variability of the amplitude patterns, we could hypothesize that they are related to changes in the tremor source location. The tremor source at Arenal volcano is located within a few hundred meters of the summit [START_REF] Metaxian | Locating sources of volcanic tremor and emergent events by seismic triangulation: Application to Arenal volcano, Costa Rica[END_REF][START_REF] Davi | Moment tensor inversion of explosive long period events recorded on Arenal volcano, Costa Rica, constrained by synthetic tests[END_REF][START_REF] Davi | Seismic source mechanisms of tremor recorded on Arenal volcano, Costa Rica, retrieved by waveform inversion[END_REF]. There are evidences that point to the activation of different source areas, either sequentially or simultaneously [e.g. [START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF]. In a highly heterogeneous medium, even small changes in source location may produce significantly different ray paths between the source and the receiver. Therefore, we could account for the first three observations by invoking changes in the source location combined with extreme path effects in a highly heterogeneous medium.

But even if we justify the appearance of complex spatial amplitude patterns and why they change with time, we must explain why they occur only for harmonic tremors. Array analyses demonstrate that LP events are have fast first arrivals, what points to a deeper source region. And perhaps the path effects are not as remarkable there. The same applies to VT and regional earthquakes, and even noise. However, spasmodic tremors are generally regarded as a different manifestation of the harmonic tremor source, lacking only its striking regularity [START_REF] Benoit | New constraints on source processes of volcanic tremor at Arenal volcano, Costa Rica, using broadband seismic data[END_REF][START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF][START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF]. Thus the spasmodic tremor source location would be similar to that of harmonic tremor. In this context, both harmonic and spasmodic tremors should display complex amplitude patterns, which are not observed. Therefore, we need another explanation.

Amplitude patterns produced by interference

The characteristics of the amplitude distributions at the array stations and the peculiar spectral features of harmonic tremor, the only signal that produces the complex patterns described above, suggest the idea that they might be related to constructive and destructive interference effects.

Two plane waves with different frequencies and different apparent slowness vectors produce an interference pattern characterized by the presence of crests where the amplitude is maximum and nodes where the amplitude is minimum or even no motion is observed at all.

The square amplitude S of the wavefield depends on spatial position r and time t, and is given by

S = A 2 + B 2 + 2AB cos(2π∆f t -∆ k • r + 2πΦ) (1)
where A, B are the two wave amplitudes, ∆ k is the difference of wavenumber vectors of the two plane waves, ∆f is the difference of frequencies, and Φ is a number between 0 and 1 that represents an arbitrary phase. Thus the seismic amplitude produced by interference of two plane waves behaves as a plane wave itself, with a frequency given by the difference of frequencies and a wavenumber vector given by the difference of the wavenumber vectors of the interfering waves. The crests corresponding to the maximum amplitude (A + B) 2

(constructive interference) verify the equation

∆ k • r = 2π(∆f t + Φ + N ) ( 2
)
where N is an integer number. We can see that when the two interfering waves have the same frequency, the amplitude pattern is stationary. When the wave frequencies are slightly different, the amplitudes change slowly with time. In these cases, waveforms display a pulsating (or beating) envelope, a phenomenon that is frequently observed in the raw data at different time scales (Figure 7). The variations are faster when the two wave frequencies are more different. In the limit, when the frequencies are not similar, the amplitude beats occur several times during the averaging window, and the amplitude variations cannot be observed any more.

We use synthetic data to calculate the spatial amplitude pattern generated at the array stations by the interference of two harmonic tremor signals. We use two models of harmonic tremor. The simplest model considers a sine function and represents the fundamental mode of harmonic tremor. The second model is based on the periodic repetition of a transient signal [START_REF] Schlindwein | Spectral analysis of harmonic tremor signals at Mt. Semeru Volcano, Indonesia[END_REF][START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF][START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF]. We use a Ricker wavelet to represent the seismic signature of the source. In this case the synthetic tremor signal is more realistic, and reproduces not only the fundamental frequency but the overtones as well.

Figure 8 shows an example of the spatial amplitude pattern generated by the interference of two plane waves. The waves have the same frequencies of 2.5 Hz. They propagate with apparent slownesses of 0.9 and 1.4 s/km and azimuths of 225 and 280 • N (back-azimuths of 45 and 100 • N). The resulting destructive interference fringes are linear, and perpendicular to the difference of wavenumber vectors, as inferred from Equation (2). The spatial amplitude pattern resulting from this particular case of wave interference is similar to the examples shown in Figures 3c and5d, in the sense that amplitudes are large in the northern and southern stations and small along an ESE-WNW band crossing the array center. The pattern is a bit more complex when using the repetitive-source tremor model, due to the presence of shorter-wavelength overtones. The reduced amplitudes are mostly due to interference of the fundamental mode. At the interference nodes, the fundamental mode would be basically filtered out. This filtering effect is clear in the synthetics of Figure 8c, but can also be observed in the real data shown in Figure 3c.

Interference is able to justify the main features of the spatial amplitude patterns. It explains the strong gradients and complex geometries (at least partially, more work should be done in this direction). Moreover, it provides a reason why we only find these patterns for harmonic tremors. Indeed, stable interference patterns require narrow-band signals; wide band signals do not produce interference patterns. Finally, in order to explain the temporal variations of the spatial amplitude patterns we have to hypothesize that different waves with varying apparent slowness vectors can be simultaneously present in the wavefield. This possibility is discussed below.

Possible causes of interference at Arenal volcano

Interference requires the presence of multiple, simultaneous narrow-band seismic waves.

We have analyzed the present dataset using frequency-slowness array methods. These techniques allow for the identification of different, simultaneous components of the seismic wavefield recorded at the array. In this case, we identify several periods when multiple components are present in the wavefield. All of them coincide with periods dominated by harmonic tremors. The behavior of these wavefield components varies along the dataset. There are examples of waves with similar apparent slownesses but quite different back-azimuths in the range 40-120 • N, which do not usually coincide with the array-crater direction; waves with similar azimuths but different apparent slownesses in the range from 0.5 up to 3 s/km; and waves with both different apparent slownesses and different azimuths. In some occasions, simultaneous components may be arriving with propagation azimuths that differ by up to

∼80 • .
Figure 9 shows two examples of results obtained using the MUSIC algorithm [START_REF] Schmidt | Multiple emitter location and signal parameter estimation[END_REF][START_REF] Goldstein | Array analysis of seismic signals[END_REF] with our array data. In Figure 9a we display the results for the same data used for Figure 3. The two gray bands indicate the 5-s windows detailed in Figures 3b,c. We recall that we have found different behaviors in terms of amplitude distributions for these two windows. The first one is characterized by quasi-uniform amplitudes at all array stations, while the second one presents large amplitude differences across the array. Looking at the frequency-slowness results, we notice a single solution for the first window, with apparent slowness of 0.6-0.9 s/km and back-azimuth of 55-65 • N. On the contrary, around the second window, we are able to determine the presence of two components in the harmonic tremor wavefield. They propagate with apparent slownesses of 0.8-1.0 and 1.2-1.5 s/km and back-azimuths of 85-110 and 35-50 • N, respectively. These apparent slowness vectors were selected for the synthetic example of Figure 8.

The presence of two wavefield components is even clearer in Figure 9b. Around the center of the window, and for about one minute, we find two stable trends corresponding to the main and secondary peaks of the MUSIC estimate (gray and white diamonds, respectively).

The main wavefield component propagates with apparent slowness of 0.6-0.9 s/km and back-azimuth of 90-120 • N. The secondary component propagates with apparent slowness of 2.5-2.8 s/km (very slow) and back-azimuth of 30-45 • N.

The quality of the estimates (bottom plots) shows that in the second window highlighted in Figure 9a the wavefield is composed by two waves with similar power and coherency.

In Figure 9b one of the components is clearly dominant, as demonstrated by the quality differences between the estimates for the main and secondary peaks.

The presence of multiple components in the wavefield can be generated by a number of phenomena, including source and path effects. The first hypothesis is that these waves are a consequence of multiple, simultaneous harmonic tremor sources. In fact, several studies evidence the occurrence of multiple harmonic tremor sources at Arenal volcano [START_REF] Benoit | New constraints on source processes of volcanic tremor at Arenal volcano, Costa Rica, using broadband seismic data[END_REF][START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF][START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF]. At some periods, different sets of overtones evolving independently are clearly detected. Each set has to be related to a different tremor source. Moreover, [START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF] documented the simultaneous activity of two craters at the Arenal volcano summit, and linked them to a double tremor source related to shallow conduit branching. These sources are located at shallow depths below the crater [e.g. [START_REF] Metaxian | Locating sources of volcanic tremor and emergent events by seismic triangulation: Application to Arenal volcano, Costa Rica[END_REF]. But the results of the frequency-slowness analysis cannot be easily reconciled with multiple harmonic tremor sources located at shallow depths below the crater area. The crater is small compared to the distance to the seismic array (of about 2 km). The expected propagation azimuth at the array site for a wavefield generated by a source located in the crater can be far from the summit-array direction, up to tens of degrees. This is a consequence of the deviations produced by the heterogeneous velocity structure, topography, etc. [e.g. [START_REF] Garcia-Yeguas | Quantitative analysis of seismic wave propagation anomalies in azimuth and apparent slowness at Deception Island volcano (Antarctica) using seismic arrays[END_REF]. However, the waves generated by two sources located at the crater area should in principle follow similar paths through the medium and reach the array site with similar azimuths, even if different from the arraysummit direction, and similar apparent slownesses. In such a case, the wavenumber vectors would be similar as well. Thus the interference pattern would have a long wavelength and the amplitude differences among array stations would not be noticeable.

There are two options to overcome this situation. First, we might consider the possibility of two harmonic tremor sources occurring at two distant source regions within the volcano.

One of them would be located in the crater area, as reported by several authors, and the other somewhere else. The problem is that there are no evidences whatsoever of such a secondary tremor source. Alternatively, we may picture a volcano with a dramatically heterogeneous velocity structure. In this case, seismic rays could follow quite different paths even for nearby sources, and this could explain the presence of wavefield components with different apparent slowness vectors at the array site.

On the other hand, multiple wavefield components can be generated by path effects. For example, the presence of efficient reflectors in the medium would generate secondary wavefields that would interfere with the direct radiation from a single source. Other structures may contribute to split the wavefield, for example a low-velocity, high-attenuation body located between the source and the array. Similar effects could be produced by scattering by topography and other velocity heterogeneities [START_REF] Rocca | Array analysis of seismograms from explosive sources: evidence for surface waves scattered at the main topographical features[END_REF][START_REF] Almendros | Spatial extent of a hydrothermal system at Kilauea Volcano, Hawaii, determined from array analyses of shallow long-period seismicity[END_REF][START_REF] Almendros | Spatial extent of a hydrothermal system at Kilauea Volcano, Hawaii, determined from array analyses of shallow long-period seismicity[END_REF][START_REF] Metaxian | Locating volcanoseismic signals in the presence of rough topography: wave simulations on Arenal volcano, Costa Rica[END_REF]. The secondary wavefield would be characterized by an apparent slowness vector that depends mainly on the scatterer location relative to the source (crater) and the array. Another possibility comes from the superposition of surface wave modes. These modes travel with different apparent slowness vectors (different velocities)

and can contribute to the variability of the seismic amplitudes at the array stations.

Whatever mechanism producing the observed interferences, the temporal changes of the amplitude pattern show that a time varying process is involved in the phenomena. A first cause of variability that can be considered is the coupling between seismic and acoustic waves. The propagation of seismic waves with apparent slowness close to 3 s/km (Fig-

ure 9b) suggests a link with the propagation of acoustic waves in the atmosphere. The time-dependent spatial amplitude patterns related to harmonic tremors at Arenal volcano could be produced by interference between the seismic wavefield radiated by a single tremor source and the associated acoustic wavefield. Acoustic waves in the atmosphere have a great variability in terms of propagation azimuths, due to continuous changes in atmospheric conditions, specially the wind strength and direction [Garces et al., 1998b;[START_REF] Le Pichon | Infrasound monitoring of volcanoes to probe high-altitude winds[END_REF][START_REF] Matoza | An infrasound array study of Mount St. Helens[END_REF].

However, a number of issues are raised. The most important is that, in general, acoustic waves in the atmosphere are not very efficient in producing seismic waves in the ground.

For example, typical values of the transmission factor for normal incidence are smaller than 0.1%. [START_REF] Matoza | The source of infrasound associated with long-period events at Mount St. Helens[END_REF] analyzed the acoustic observations at St. Helens and modeled the interactions between the solid surface and the air. They found evidences of seismic energy radiated into the atmosphere as acoustic waves, but not the opposite. [START_REF] Kitov | An analysis of seismic and acoustic signals measured from a series of atmospheric and near-surface explosions[END_REF] investigated acoustic and seismic signals from atmospheric and near-surface bomb blasts. They documented energy conversion processes between acoustic waves in the atmosphere and seismic waves in the ground. These processes are most efficient when the surface wave velocity is similar to the apparent velocity of the acoustic waves. This condition is likely achieved at Arenal and most volcanic areas, given the presence of slow shallow layers with velocities near the sound speed in the air. At Arenal volcano, some large explosions produce ground-coupled acoustic waves that are recorded with significant amplitudes in the seismograms [START_REF] Hagerty | Analysis of seismic and acoustic observations at Arenal Volcano, Costa Rica, 1995-1997[END_REF]. But this might not be the case for the harmonic tremors analyzed here, which display much smaller amplitudes.

Thus, it appears more likely that the temporal variations of the amplitude patterns are related to source variability. Indeed, several studies have pointed that the source and surrounding medium is constantly changing at different time scales [START_REF] Cole | Explosive activity and generation mechanisms of pyroclastic flows at Arenal volcano, Costa Rica between 1987 and 2001[END_REF][START_REF] Wadge | The magma budget of Volcán Arenal, Costa Rica from 1980 to 2004[END_REF][START_REF] Lesage | Complex behavior and source model of the tremor at Arenal volcano, Costa Rica[END_REF][START_REF] Valade | Explosion mechanisms at Arenal volcano, Costa Rica: An interpretation from integration of seismic and Doppler radar data[END_REF]. In particular, an integrated analysis of seismic and Doppler radar recordings of mild explosions, degassing events, and tremor demonstrated the strong variability of these types of signal and the lack of correlation between them [START_REF] Valade | Explosion mechanisms at Arenal volcano, Costa Rica: An interpretation from integration of seismic and Doppler radar data[END_REF]. These authors propose a source model for explosions and tremor whereby more or less ash-laden gas flow is controlled by the opening and closing of fractures in the highly viscous cap atop the conduit. The constantly varying state of the lava cap and the fractures produces non repeatable source conditions that can yield rapid changes in the seismic wave radiation pattern, amplitude and frequency as well as fluctuations in the location and depth of the hypocenter. Combined with multiple path and site effects due to topography and highly heterogeneous structure, even slight variations at the source may result in large modifications of the wavefield which are thus reflected in the amplitude pattern evolution.

Conclusions

We use data from a dense, small-aperture seismic array to show that seismic amplitudes during harmonic tremor episodes at Arenal volcano display complex spatial distributions.

We have found strong amplitude variations among array receivers separated just a few tens of meters. The amplitude patterns may remain stable for some tens of seconds, but change drastically with time at longer scales. This phenomenon is observed just for harmonic tremors and disappears for any other type of seismic event.

We discuss the source, path, and site effects reported at Arenal volcano. Our observations could be explained invoking a combination of extreme source, path, and site effects. However it would produce similar effects on other types of seismic events. Thus we conclude that such a combination is not very likely to happen. Alternatively, we propose that the complex spatial amplitude patterns could be related to interference of multiple components of the seismic wavefield. This phenomenon explains the characteristics of the spatial amplitude patterns, including their mere existence, their temporal variations and dependence on the harmonic content of the signal. We propose that the interfering waves might originate by a number of mechanisms, for example the simultaneous occurrence of multiple harmonic tremor sources, the superposition of a tremor wavefield from a single source with a scattered wavefield, and the interaction between seismic and acoustic energy radiated by a single tremor source at the volcano.

Our observations document the generation of complex amplitude patterns during harmonic tremors at Arenal volcano. Our interpretation in terms of interference phenomena explains also other observations of strong variations in waveform and relative amplitude of spectral peaks between close stations at different locations of Arenal volcano [START_REF] Mora | Study of seismic site effects using H/V spectral ratios at Arenal volcano, Costa Rica[END_REF][START_REF] Mora | Shallow velocity structure and seismic site effects at Arenal volcano, Costa Rica[END_REF]]. An interesting question is whether these patterns are a common feature elsewhere. Unfortunately most seismic studies on volcanoes rely on distributed networks of seismometers, which cannot be used to analyze short-scale variations in the wavefield amplitude. To solve this question, studies of the amplitude distribution within dense seismic arrays should be performed at other volcanoes producing harmonic tremors similar to Arenal. Interference between seismic and acoustic wavefields originated by harmonic tremors should be also further investigated. Experiments combining seismic and infrasonic instruments would be highly desirable.

In any case, there is more information in our data, in different aspects that we have not addressed so far. The present analysis will be completed with the study of the three components of motion and a wavefield decomposition using array methods, both of them already in progress. The results may help us understand the complex behavior of the harmonic tremor wavefield at Arenal volcano.

Data and resources. Seismograms used in this study were collected during a short experiment carried out by the Observatorio Sismológico y Vulcanológico de Arenal y Miravalles (OSIVAM-ICE) in February 2004. Data will be available after exploitation and can be obtained through request to Taylor Castillo Waldo (wtaylor@ice.go.cr). Some plots and analyses were made using MATLAB (http://www.mathworks.com).

  , and two representations of their RMS: the absolute RMS values for the different array channels (center plot) and the RMS values normalized by their maximum (right plot). The normalized values are plotted as colored circles at the corresponding station locations. Therefore, this plot gives a representation of the spatial amplitude pattern of the seismic wavefield. Normalized RMS values may range from 0 (flat seismogram, dark colors)to 1 (RMS equal to the maximum, light colors). Since RMS values are normalized, there is always at least one white point with normalized RMS of 1. The question is whether the remaining values are lower or not. In this case, since seismic amplitudes are nearly the same at all stations, the circles are all white, indicating normalized RMS values near 1.

  remain stable for several tens of seconds. They are not random transients, but imply a fundamental change in the harmonic tremor wavefield. The meaning of the right plot of Figure 3c is further illustrated in Figure 4. Here we show snapshots of the vertical component of the wavefield during half a second for the initial part of the data window shown in Figure 3c. Triangles indicate the positions of the array stations. Black dots above these triangles represent the corresponding vertical velocities at each of the array stations. We have added a triangular mesh to simplify the comparison among snapshots. The black dots are projected on a vertical, NNE-SSW plane,approximately perpendicular to the dark band observed in the right plot of Figure3c. We keep these projections as small gray dots on the following snapshots, in order to illustrate the amplitude span of the vertical motion at each array station. These snapshots illustrated in Figure4can be visualized in an animation provided as an electronic supplement to this article. We can see that although vertical velocities oscillate with the same period at all stations, the amplitudes are not the same. Seismograms recorded at stations along the dark band of Figure3cdisplay small amplitudes compared to the north and south stations. This can be seen clearly in the last snapshot, where the vertical distribution of gray dots spans a larger vertical range for the north and south stations than for stations projected near the center.

  sliding 2.5 s each step. For each time window, we normalize the RMS values dividing by the maximum RMS of the array stations. In this way we remove the effect of temporal variations in the seismogram amplitude and simplify the comparison of spatial amplitude patterns. We obtain 19 time series of normalized RMS, one for each receiver. With these data, we build plots that display the normalized RMS (with a color scale) as a function of time (x-axis) and station number (y-axis). In these plots, vertical sections represent the normalized RMS distributions across the array for particular times. They are just straightened versions of the spatial amplitude patterns. Although we lose the spatial information contained for example in the right panels of Figures2b and 3b,c, we can easily compare the amplitude patterns for successive time windows.

Figure 5

 5 Figure5shows examples of these plots corresponding to four selected 5-minute-long data

Figure 1 .

 1 Figure 1. Location of the seismic array about 2 km west of the Arenal volcano summit. The

Figure 2 .

 2 Figure 2. (a) Unfiltered vertical-component seismograms from the 19 array stations, showing 1

Figure 3 .

 3 Figure 3. (a) Unfiltered vertical-component seismograms from the 19 array stations, showing 2

Figure 4 .

 4 Figure 4. Snapshots of the vertical ground motion recorded at the array during 0.55 s at the start

Figure 5 .

 5 Figure 5. Temporal variations of the spectral content and spatial amplitude patterns along four

Figure 6 .

 6 Figure 6.Representation of the resonance frequency of the shallow structure estimated by

Figure 7 .

 7 Figure 7. Examples of harmonic tremors recorded at one of the seismic array receivers (station

Figure 8 .

 8 Figure 8.Calculation of the spatial amplitude distribution of a complex wavefield generated

Figure 9 .

 9 Figure 9.Two examples of the results of the frequency-slowness analysis for 2-minute long

Acknowledgments. We thank Dr. Chalotte Rowe and two anonymous reviewers for their useful comments and suggestions. We are grateful to ICE for supporting the logistical work and the data acquisition. We are also grateful to the Arenal Conservation Area staff for the facilities provided during the field work. The financial support from the projects No 113-A4-501 and 113-A6-503 from University of Costa Rica, Ministry of Science and Technology (MICIT) and National Council for Scientific and Technological Research (CONICIT) is acknowledged. Partial support was also provided by projects CTM2010-11740 and CGL2011-29499-C02-01 of the Spanish Ministry of Science and Innovation.


Manabu Tsukada

Extended interface ID for virtual link selection in GeoNetworking to IPv6 Adaptation Sub-layer (GN6ASL)

Background

Intelligent Transportation Systems (ITS) are systems deployed to optimize the road traffic and realize safe, efficient and comfortable human mobility. Cooperative ITS is a new vision of ITS where vehicles, the roadside infrastructure, traffic control centers, road users, road authorities, road operators, etc. exchange and share information based on a common communication architecture -known as the ITS station reference architecture [ISO-21217-CALM-Arch, ETSI-EN-302-665-Arch] -supporting all types of ITS use cases 2. PROBLEM STATEMENT over a diversity of access technologies (11p, 11n, 3G/4G, infra-red, ...). The building blocks of the ITS station are specified within ISO, ETSI, IETF and IEEE.

[ETSI-TS-102-636-6-1-GN6] specifies the transmission of IPv6 packets over ETSI GeoNetworking protocol [ETSI-TS-102-636-4-1-GN] via a protocol adaptation sub-layer referred as the GN6ASL (GeoNetworking to IPv6 Adaptation Sub-layer) (See Figure 1).

GN6ASL in the ITS station architecture

With respect to the ITS station reference architecture [START_REF]Arch] Intelligent Transport Systems (ITS)[END_REF], the present document only affects the layer block "Networking and Transport". As depicted in figure 1, within the layer block "Networking and Transport", the present document introduces GN6ASL, an adaptation sub-layer for the transmission of IPv6 packets over GeoNetworking. The other protocols depicted in figure 1 (e.g. TCP and UDP) are represented for sake of completeness in order to represent a typical usage of the present document. We describe the limitation of Draft EN 302 636-6-1 V0. 1.2 (2012-11) in this Section. Note that this study is based on year December 2012 versions of the ETSI Standards and that the standards constantly evolve. As a result, parameters, primitives and virtual links on GN6ASL may have changed at the time of reading. Figure 2 illustrates the overview of the addressing scheme in each layer from access layer to IPv6 layer in ITS Station Architecture. As illustrated in the figure, a 48bits MAC address is used for ITS-G5A media in the access layer in order to identify the physical communication interface (detailed in section 3.1). In the GeoNetworking layer, a GeoNetworking (GN) address is used in order to identify the node. The GeoNetworking address is generated based on the MAC address used in the access layer [ETSI-TS-102-636-4-1-GN] (detailed in section 3.2).

A GeoNetworking node may have several Geographical Virtual Links (GVL) and a Topological Virtual Interface (TVL) in GN6ASL. Each virtual link may be seen as an virtual interface in the IPv6 layer. The current specification [ETSI-TS-102-636-6-1-GN6] defines that the IPv6 link-local address assigned to the virtual interfaces contain interface identifier (IID) generated from MAC address (see section 3.3 for detail).

The issue of the current specification is that the GN6ASL cannot distinguish destination GVL/TVL for incoming packets by checking the destination address of IPv6 header. Let's see what happens when an incoming packet is received in the node in Figure 2. First, the destination MAC address is checked in the access layer, then if it matches to the MAC address of the received communication interface (MAC address "M"), the packet are GeoNetworking address (if GeoUnicast), and if the destination GeoNetworking address is matched to the received node's one (GN address "G"), the packet is sent to the upper layer. GN6ASL needs to selects the virtual interface to the IPv6 layer, however one problem arises here. GN6ASL cannot select the destination virtual interface because all the virtual interfaces have same link-local address generated by modified EUI64 as in the GN6 specification.

The current specification of GN6 gives some solution for this issues. It examines the source node position vector in order to determine the GVL to send the packets to the IPv6 layer.

Typically this solution gives a problem in the situation illustrated in Figure 3. Node X sends ICMPv6 echo request to an specific GVL area, however the ICMPv6 echo reply is received in different interface.

Thus it requires the way to allocate different IPv6 address on each virtual interface in order to distinguish them without changing the addressing scheme in MAC address and GeoNetworking address. 3 Identifier in each layer

IDENTIFIER IN EACH LAYER

MAC address

Media Access Control address (MAC address) is a unique identifier assigned to network interfaces for communications on the physical network segment.

GeoNetworking Address

Every GeoAdhoc router shall have a unique GeoNetworking address. This address shall be used in the header of a GeoNetworking packet and identify the communicating GeoNetworking entities. The format of the GeoNetworking address is described in figure 4. 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 0 1 2 3 4 5

General

Every GeoAdhoc router shall have a unique GeoNetworking address. This address shall be used in the header of a GeoNetworking packet and identify the communicating GeoNetworking entities.

GeoNetworking address format

The format of the GeoNetworking address is described in figure 3. 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6

0 1 2 3

Fields of the GeoNetworking address

The GeoNetworking address shall be comprised of the fields specified in table 1. The GeoNetworking address shall be comprised of the fields specified in table 1.

IPv6 unicast addresses

IPv6 addresses are 128-bit identifiers for interfaces and sets of interfaces. There are three types of addresses:Unicast, Anycast and Multicast. IPv6 addresses of all types are assigned to interfaces, not nodes. An IPv6 unicast address refers to a single interface. In IPv6 nodes, all interfaces are required to have at least one Link-Local unicast address [rfc4291].

IPv6 unicast address consists of subnet prefix and interface identifier. Interface identifiers in IPv6 unicast addresses are used to identify interfaces on a link. They are required to be unique within a subnet prefix. Generally, Interface IDs are required to be 64 bits long and to be constructed in Modified EUI-64 format.

Modified EUI-64 format-based interface identifiers may have universal scope when derived from an universal token (e.g., IEEE 802 48-bit MAC or IEEE EUI-64 identifiers The MID field corresponds to the access layer address. In case of IEEE 802.11p [i.4] MAC layer, the 48-bit MAC layer address shall be used.

In order to allow for the resolution of a GeoUnicast destination GN_ADDR from an IPv6 destination address using virtual interfaces of type Ethernet V2.0/IEEE 802.3 LAN, the GeoNetworking address space shall remain 48-bit wide (size of the MID field in the GeoNetworking address). In particular, as described in TS 102 636-6-1 [6], table 1, note 1, the GN6ASL resolves an MID from a unicast destination IPv6 address and passes it to GeoNetworking via the GN-DATA.request primitive (clause H.2). Then, the GeoNetworking protocol entity is responsible for deriving a full GN_ADDR from the MID. This full GN_ADDR shall be derived from a LocTE (if it exists) or by executing the Location Service with Request GN_ADDR field containing only the MID part and the other bits set to 0.

To be compliant with the IPv6 over GeoNetworking architecture, the GeoNetworking address space shall remain 48-bit wide (size of the MID field in the GeoNetworking address) in order to provide a virtual interface of Ethernet type to IPv6 layer and to perform the forwarding via GeoNetworking in a transparent way (see TS 102 636-6-1 [6]).

If the address is updated for privacy reasons, i.e. by assignment of a short-term identity, only the last field of the address shall be updated and derived from the short-term identity (pseudonym).

Table 1: Fields of the GeoNetworking address[ETSI-TS-102-636-4-1-GN]

[IEEE-EUI-64]) or may have local scope where a global token is not available (e.g., serial links, tunnel end-points) or where global tokens are undesirable (e.g., temporary tokens for privacy [rfc4941]).

Modified EUI-64 format interface identifiers are formed by inverting the "u" bit (universal/local bit in IEEE EUI-64 terminology) when forming the interface identifier from IEEE EUI-64 identifiers. In the resulting Modified EUI-64 format, the "u" bit is set to one [START_REF]Arch] Intelligent Transport Systems (ITS)[END_REF] to indicate universal scope, and it is set to zero (0) to indicate local scope. [IEEE-EUI-64] defines a method to create an IEEE EUI-64 identifier from an IEEE 48-bit MAC identifier. This is to insert two octets, with hexadecimal values of 0xFF and 0xFE, in the middle of the 48-bit MAC (between the company ID and vendor-supplied ID).

IPv6 Address on GN6ASL virtual interfaces

ITS-G5A media have IEEE 802 48-bit MAC addresses. GN6ASL assumes interface identifiers for virtual interfaces are modified EUI-64 format-based interface identifiers constructed from 48-bit MAC addresses.

INRIA technical paper (11th December 2012)

We propose a solution to allocate different IPv6 address on each virtual interface in order to distinguish them without changing the addressing scheme in MAC address and GeoNetworking address. The proposition complies also with Dynamic Geographical Virtual Link (DVL) proposed in [INRIA-report-DVL] that is going to be applied to [ETSI-TS-102-636-6-1-GN6].

Generation of Extended interface ID

Instead of inserting 0xFF 0xFE in the middle of the 48-bit MAC between the company ID and vendor-supplied ID in the modified EUI-64 format, our proposition inserts the ID to distinguish the virtual link (Figure 5). The company ID and vender-supplied ID of MAC address is treated as EUI-64 does. In other words, the only change from MAC address is inverting the value of the universal/local bit in company ID (indicated as "B" bit in Figure 5). Geographical Virtual Link ID A 12 bits ID assigned to a virtual link in order to distinguish the virtual link. Virtual link ID is unique in the all the virtual link created from a single physical interface. GN6ASL allocates ID 0 to DVL [INRIA-report-DVL] INRIA technical paper (11th December 2012)

CONSIDERATION

(which is created only one per a singe physical interface) and from ID 1 to ID 4095 are allocated GVLs when it is created upon reception of RA. When number of GVL created in a GVL exceed 4095, the ID of unused GVL can be reused.

Reserved bits 4 bits are reserved in order to record the property of the links. The bits are not yet specified, however they will indicates whether global uniqueness of ID or locally administrated, and whether the link is multicast-capable or not.

The interface ID by EUI-64 (with 0xFFFE) is allocated to TVL in order to keep compatibility with unsupported nodes.

GN6ASL operation with Extended interface ID

When a outbound packet is sent, GN6ASL resolves the destination MAC address by exactly same way described in section 10.3 in [ETSI-TS-102-636-6-1-GN6] (Non-ND-based address resolution) for both packets which has the IPv6 destination with Interface ID by EUI64 and the proposed scheme. When a inbound packet is received, GN6ASL selects the virtual link matched to the destination IPv6 address (if exists). If the matched virtual link is not found, GN6ASL passes the packet to the IPv6 layer with default virtual link (this is proposed to be DVL in [INRIA-report-DVL]). In the case that the IPv6 destination address is not on the virtual link, the importance of selected virtual link is low, because these packets are forwarded or dropped in the IPv6 layer, and not passed to upper layer than the IPv6 layer.

Consideration

The 4bits reserved bits shall indicate the property of the virtual link. Further discussion is necessary what is important property in the virtual link. This maybe whether global uniqueness of ID or locally administrated, and whether the link is multicast-capable or not.

INRIA technical paper (11th December 2012)

CONCLUSION 6 Conclusion

In the document, we presented the limitation of Draft EN 302 636-6-1 V0. 1.2 (2012-11) at this moment. In order to overcome all of these issues, extended interface ID is proposed. We propose a solution to allocate different IPv6 address on each virtual interface in order to distinguish them without changing the addressing scheme in MAC address and GeoNetworking address. The proposition complies also with Dynamic Geographical Virtual Link (DVL) proposed in [INRIA-report-DVL] that is going to be applied to [ETSI-TS-102-636-6-1-GN6]. Instead of inserting 0xFF 0xFE in the middle of the 48-bit MAC between the company ID and vendor-supplied ID in the modified EUI-64 format, our proposition inserts the ID to distinguish the virtual link. Proposed Extended interface ID has Reserved bits (4 bits) and Geographic Virtual Link ID (12bits) in the middle of company ID and vendor supplied ID.

As considerations, we leave the reserved bits undefined at this moment. We consider that further discussion is necessary in ETSI ITS_WG3 (ITS_WG3@LIST.ETSI.ORG) for approval of the specification of [ETSI-TS-102-636-6-1-GN6].

Figure 1 :Figure 1 :

 11 Figure 1: GN6ASL in the ITS station architecture As depicted in figure 1, the present document builds an adaptation sub-layer (GN6ASL) between the ETSI GeoNetworking protocol [i.25] and an IPv6-compliant protocol layer and extended with mobility extensions. The default IPv6 mobility extensions in the ETSI ITS architecture [1] (as well as in [i.19]) is the Network Mobility Basic Support (NEMO BS) protocol [15]. The present document enables the usage of NEMO BS over the ETSI GeoNetworking protocol [i.25]. NOTE: With respect to the figure 1, the scope of [i.19] includes the protocol layer IPv6 + Mobility Extensions, directly above the adaptation sub-layer specified in the present document.

Figure 2 :

 2 Figure 2: Problem Statement

Figure 3 :

 3 Figure 3: Problem of link-local communications

  Figure 2: Format convention

Figure 3 :

 3 Figure 3: GeoNetworking address format

Figure 4 :

 4 Figure 4: GeoNetworking address format[ETSI-TS-102-636-4-1-GN]

  The first bit is reserved for the recognition of manual configured GeoNetworking addresses. The allocation of ITS Station Country Codes (SCC) is administered by the ITU-T [9].

Figure 5 :

 5 Figure 5: Generation of Extended Interface ID Proposed Extended interface ID has Reserved bits (4 bits) and Geographic Virtual Link ID (12bits) in the middle of company ID and vendor supplied ID.

Table 1 : Fields of the GeoNetworking address Field # Field name Octet/bit position

 1

					Type	Description
			First	Last
	1	M	Octet 0	Octet 0	1 bit unsigned integer This bit allows distinguishing between
			Bit 0	Bit 0		manually configured network address and the
						initial GeoNetworking address. M is set to 1 if
						the address is manually configured otherwise
						it equals 0.
	2	ST	Octet 0	Octet 0	4 bit unsigned integer ITS Station Type.
			Bit 1	Bit 4		To identify the ITS Station type.
						Bit 1:
						0 -Vehicle ITS station.
						1 -Roadside ITS station.
						Bit 2 to Bit 4:
						For Roadside ITS station:
						0 -Traffic light.
						1 -Ordinary Roadside ITS station.
						For Vehicle ITS station:
						0 -Bike.
						1 -Motorbike.
						2 -Car.
						3 -Truck.
						4 -Bus.
	3	SST	Octet 0	Octet 0	1 bit unsigned integer ITS Station sub-type.
			Bit 5	Bit 5		To distinguish between public transport and
						private ITS stations.
						0 -Public (e.g. school bus, public safety
						vehicle).
						1 -Private (e.g. non-public transport
						vehicle).
	4	SCC	Octet 0	Octet 1	10 bit unsigned integer ITS Station Country Code.
			Bit 6	Bit 7
	5	MID	Octet 2	Octet 7	48 bit address	This field represents the LL_ADDR.

Table 2 :

 2 Table 2 summarized the assignment of interface ID to TVL, DVL and GVL. Assignment of Interface ID on virtual links

	Type of Link Assignment of Interface ID
	TVL	TVL is created only one to a single physical interface upon enabling
		interface. EUI-64 (with 0xFFFE) is assigned in order to keep
		compatibility with unsupported node.
	DVL	DVL is created only one to a single physical interface upon enabling
		the interface. GVL ID = 0 is allocated.
	GVL	GVL is created upon each reception of different RA. An unique GVL
		ID from 1 to 4095 is assigned. The ID of unused GVL can be reused.