Gas geochemistry and seismotectonics: a review

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Tectonophysics 304 (1999) 1–27

Gas geochemistry and seismotectonics: a review Jean-Paul Toutain a,Ł , Jean-Claude Baubron b a

Observatoire Midi-Pyre´ne´es, UMR CNRS 5563, Laboratoire de Ge´ochimie, 38 rue des trente-six ponts, Toulouse, France b BRGM, Service Ge ´ ologique National, 45060 Orle´ans La Source, France Received 16 January 1998; accepted 20 November 1998

Abstract Publications on soil and spring gases have been examined regarding their relationships with both tectonic and seismic activities. The main sources, behaviours and uses of species detected in soils and springs are displayed, and their mode of sampling and analysing briefly described. The main patterns of degassing in soils are described and we outline the wide range of geochemical signatures as the result of both permeability and mineralogical contrasts. Because thermomineral waters have been in contact with great volumes of crustal rocks at various depths, spring gases might be more representative of the local environment than soil gases. Moreover, gas signature comparisons show that spring gases are much more enriched with deep gases and slightly contaminated by atmospheric gases. Therefore, they can be considered as better samples for identifying precursors of earthquakes. Environmental perturbations are examined, and it is shown from divergent cases that pressure, temperature, soil moisture or earth tides may generate very high perturbations of the degassing process. Such effects demonstrate that no systematic correction law can be proposed and that removing external contributions from gas concentrations must be performed case by case. This demonstrates therefore the need for the simultaneous measurement of external parameters during gas monitoring. A qualitative examination of about 150 claimed precursors proposed in the literature has been reviewed. As noted by previous authors, anomalies appear at distances sometimes much greater than typical source dimensions, and occur in the field of strain higher than 10 9 , most of them being in the field of strain higher than 10 8 . Taking into account the very high heterogeneity of such a set of data, we can suggest that amplitudes of gas anomalies are independent of both magnitudes and epicentral distances of related earthquakes, suggesting local conditions to control amplitudes. On the contrary, precursory time and duration of anomalies seem to increase both with magnitudes and epicentral distances. Abundant evidence demonstrates the major role of crustal fluids in the earthquake cycle. Many works have outlined the fact that crustal instabilities can appear as the result of low stress=strain perturbations during loading. It has been suggested that motion of fluids may occur at various scales, from microcrack fluid transfer up to changes of hydraulic levels of water tables. The study of subsequent anomalies is expected to supply a tool for earthquake prediction. Following previous authors, we outline the need for further methodological improvements, including the setting up of multiparameter station networks and the simultaneous recording of the main external parameters (atmospheric pressure, water and air temperature, soil moisture) for signal processing.  1999 Elsevier Science B.V. All rights reserved. Keywords: precursors; earthquake prediction; soil gases; spring gases

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author. Fax: C33 561 5505 44; E-mail: [email protected]

0040-1951/99/$ – see front matter  1999 Elsevier Science B.V. All rights reserved. PII: S 0 0 4 0 - 1 9 5 1 ( 9 8 ) 0 0 2 9 5 - 9

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1. Introduction Earthquakes constitute a severe source of human disasters all around the world. Consequently, short-term considerations — through the search for precursory signals — have received great attention in the last several decades. As earthquakes are physical phenomena, most techniques used currently with prediction purposes are based on geophysical approaches, including seismology, magnetism, electricity, and geodesy. So, a wide range of methods have been proposed, using the monitoring of parameters such as b-values (i.e. the slope of the Gutenberg– Richter law relating the local number of earthquakes and their magnitude), vP=vS-values (ratio of the propagation velocities of P and S seismic waves), coda Q, tilt values, self-potential anomalies and electromagnetic data, that allowed to exhibit case by case precursory signals (Johnston and Mortensen, 1974; Mizutani et al., 1976; Varostos and Alexopoulos, 1984; Jin and Aki, 1986; Molchan and Dmitrieva, 1990; Le Ravalec et al., 1996). The most relevant success in this field is probably the successful prediction of the February 4, 1975 magnitude 7.3 earthquake of Haicheng (China), on the basis of multiple precursory phenomena (Ku, 1980; Turcotte, 1991). However, one has to note, following the review of Turcotte (1991) on earthquake prediction, that at the present day no detectable, systematic and reliable precursory phenomena precede large earthquakes. Indeed, even if a number of precursory phenomena have been identified subsequently to many earthquakes, there are no statistically based reliable data for the recognition of a method based on the search for precursors. However, even if some authors claim that earthquakes cannot be predicted (Geller et al., 1997), many others argue that rock properties are drastically altered upon mechanisms linked to the preparation of an earthquake (e.g. Wyss, 1997). At the moment, what we can assume is that we have not sufficient numbers of events to establish a cause-andeffect relationship (Aceves and Park, 1997), and that we have to develop a high-density monitoring of seismic faults in order to search for reliable precursors. Among the techniques used for the search of precursors, geochemistry has provided some high-quality signals, especially since the 1960’s, mainly as

the result of instrumental developments. Significant results, however, were published as early as 1927 (see the review of King, 1986). Focusing interest on geochemical anomalies linked to seismo-tectonic activity is not an unexpected development, owing to the multiple evidence of a genetic link existing between fluid flows and faulting processes (see a review by Hickman et al., 1995). Most of the studies concerning geochemical precursors related in literature have been performed in seismically active countries such as the former USSR, P.R. China, Japan and the USA. A number of reviews have been published in this domain, the basic ones being Teng (1980), Hauksson (1981), Barzukov et al. (1985), King (1986, 1989), Thomas (1988) and Wakita et al. (1988). Some of these reviews are mainly devoted to case evocations (Teng, 1980; Barzukov et al., 1985; Wakita et al., 1988; King, 1989), whereas some others deal with physical interpretations of the phenomena (Hauksson, 1981; King, 1986; Thomas, 1988). Hauksson (1981) evaluated world-wide radon data and examined magnitude, precursory time interval, relative amplitude of signal and epicentral distance relationships. Most data have been obtained on hydrothermal systems, mainly by using gas monitoring. The relatively high velocity of gas transfers within these systems account for the focusing on hydrothermal gases. Recent results, however, suggest that dissolved ion anomalies also occur prior to some earthquakes, as shown by studies performed after to the quake on bottled mineral waters (O’Neil and King, 1981; Igarashi et al., 1995; Toutain et al., 1997). Finally, soil gases also likely constitute a target for gas precursors of earthquakes (Pinault and Baubron, 1997). Very contrasted conclusions concerning both the mechanisms that generate geochemical anomalies and the information that such studies can provide have been proposed. Hauksson (1981) suggested that radon emission in seismic zones could represent a stress intensity factor for a local crack system and that anomalies were due to slow growth of small cracks in the crust caused by stress corrosion by groundwater. He suggested also that radon anomalies were strongly dependent on local conditions (rock type, stress intensity factor, degree of saturation of rock, etc.). King (1989) outlined the general features of earthquake-related gas changes.

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They occur mainly at the intersections and bends of active faults at sometimes considerable epicentral distances, spike-like anomalies can predict the time of the earthquake, and the spatial and temporal extent of anomalies might be useful for predicting earthquake magnitudes. At present, while generating-anomaly models are still largely under debate, most authors agree in invoking episodic crustal strain=stress field changes as the source mechanism (Fleischer, 1981; King, 1986; Thomas, 1988). Most geophysicists, though sceptical about the reliability of geophysical precursors, speculate on the possibility of long-distance signals (SES, SP, chemical, hydrological, gas) due to water and gas surging through the crust (Kerr, 1995). With many authors we agree in claiming that research on geochemical precursors of earthquakes is at the very beginning, but that recording techniques and methods of analysis used must be strongly improved. We will outline in this paper the main concepts that justify such studies, illustrated with literature data and with some of our new results. First, we will display some new data obtained in either prospecting or monitoring programs performed in geodynamically active areas (Bulgaria, Spain, Italy, southern France, Costa-Rica). We will then draw attention to soil and spring degassing systems, gas species characteristics and origin, and the chemical analyses used for prospection and continuous monitoring. We will then examine the dynamic systems constituted by soils and thermal springs and consider the external factors that perturb the degassing. Finally, we will display a world-wide compilation of data available in literature, try to outline the main features and discuss the possible mechanisms that might generate such gas anomalies.

2. Nature and origin of earth gas leaks Abundant evidence of preferential degassing at active faults is available. On a global scale, Irwin and Barnes (1980) outlined the coincidence of HCO3 -bearing groundwaters with major seismic belts. They suggest that systematic CO2 discharges in seismically active faults is a long-term, permanent (with respect to earthquakes) phenomenon which indicates that active faults are characterised by high

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permeability and porosity and act as drains in the crust. CO2 discharges are commonly associated with seismic faults as the result of thermal crustal anomalies. The carbon dioxide discharges are preserved until microseismicity prevents travertine deposits to plug the permeability. But seismic faults also occur without CO2 discharges. In this latter case, they are usually associated with degassing of heliumenriched nitrogen. Degassing at active faults is also a valid feature for many other terrestrially generated gases, such as He, H2 , Rn, CH4 , various alkanes and alkyl aromatic hydrocarbons, and also highly volatile metals such as Hg, As, Sb (Sugisaki et al., 1980; Crenshaw et al., 1982; King et al., 1993; Klusman, 1993). Fault gases display a very wide range of geochemical signatures, even on a single fault. In a first attempt, one can relate this feature to the contrasted characters and sources of the respective leaking gases. Indeed, thermal, radiogenic and geodynamic processes are involved in earth degassing at active faults, therefore inducing complex patterns of degassing from the crust. – Radon is a rare gas and is probably the gas used the most frequently for mapping and predicting purposes. 222 Rn is a naturally occurring radioactive daughter product of the uranium decay chain, with a short half-life (3.8 days). In the geologic environment, it displays a poor intrinsic mobility (Tanner, 1964; Dubois et al., 1995). In diffusive systems, due to its low mobility and its short half-life, radon obviously comes from a short distance below the measuring instrument. Information of a deep origin, however, is expected to be noticed when Rn of a subsurficial origin is extracted by a rising gas=water column. In this latter case, Rn being incorporated in the fluid during the last steps of the process, it can be used as a tracer, acting as a relative flow meter and velocity meter of the bulk fluid. It gives therefore information about both the steady state conditions and disequilibrium features of a global reservoir, which can be a hydrothermal cell, possibly magmagenerated (Pinault and Baubron, 1996). Soil radon activities analysed in surface conditions depend upon the following main factors: the emanating power of the rock and soil (Morawska and Phillips, 1993), the permeability of the host rock and the flow of the carrying gas (Ball et al., 1991). Generally, radon activities increase with increasing flows (because the

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gas velocity increases, causing both less time for decay and more extraction). For higher flows, however, dilution of radon by the flux may occur with a subsequent decrease of radon activities measured at the surface. Radon is known to be associated with fumarolic gases and hot springs (D’Amore and Sabroux, 1976; Aubert and Baubron, 1988), with radon activities usually increasing with water temperature, although its solubility decreases with increasing temperature. It is usually carried away by underground waters, but also by gases such as carbon dioxide, nitrogen, methane (Shapiro et al., 1982; Toutain et al., 1992; Heinicke et al., 1992). These characteristics allow radon to be used as a tool for mapping and determining characteristics of hydrothermal systems (D’Amore et al., 1978; Cox, 1980; Etiope and Lombardi, 1995; Liritzis et al., 1995), for fault detection in volcanic terrains (Crenshaw et al., 1982; Aubert and Baubron, 1988; Baubron et al., 1990, 1991), for uranium exploration (Fleischer et al., 1972; Klusman, 1993; Wattananikorn et al., 1995; Charlet et al., 1995) and for groundwater flow characterization (Gascoyne et al., 1993). 222 Rn monitoring has long been used for earthquake prediction purposes (King, 1978; Fleischer and Magro-Campero, 1985; Segovia et al., 1989; Shapiro et al., 1989; Woith et al., 1991) as well as for volcanic ones (Cox et al., 1980; Del Pezzo et al., 1981; Thomas et al., 1986; Thomas, 1988; Toutain et al., 1992). Up to now, most of these studies used low-frequency sampling techniques, namely the track-etch method with film records acting as passive detectors (Fleischer et al., 1972). Recent technological improvements now allow to use autonomous sensors working with silicon detectors and in-situ data storage systems (Ball et al., 1991; Pane et al., 1995; Pinault and Baubron, 1996, 1997). – Helium (4 He) is a product of the uranium decay chain. This rare gas is the second lightest element with a molecular weight of 4, and it is characterised by a high mobility, a monoatomic structure, chemical inertia and a low solubility in water. Due to these characteristics lead helium to display a highly diffusive character with a diffusion coefficient about ten times those of N2 , O2 and CO2 (Jenkins and Cook, 1961). Helium has a low and constant concentration (5:2204 š 0:0041 ppm) in air (Holland

and Emerson, 1990). Due to its deep origin (with respect to radon) and characteristics, helium appears as a powerful indicator of deep and early demixing processes, and must be considered as a good marker of uprising magma (Wakita et al., 1978; Toutain et al., 1992). It appears also as an exceptional marker of crustal discontinuities, using faults, tiny fractures and paths to rise to the surface (Roberts et al., 1975; Kahler, 1981; Barberi and Carapezza, 1994). In hydrothermal systems not related to active volcanoes, helium is considered to be primarily originating from radioactive decay, with lesser contributions from the atmosphere and a small amount from the mantle. The 3 He=4 He isotopic ratio allows the distinction between atmospheric, crustal and mantlederived contributions. However, as no continuous measurements of this ratio are now possible, we will not consider helium isotopes in this review. 4 He has been commonly used for continuous monitoring for earthquake prediction (Sugisaki, 1978, 1987; Reimer, 1981, 1985, 1990; Sugisaki and Sugiura, 1986; Chalov and Komissarov, 1987; Gorgoni et al., 1988; Nagamine, 1994). – Carbon dioxide is (generally next to water or nitrogen) the most abundant gas species in hydrothermal to volcanic environments. Kerrick et al. (1995) calculated that non-volcanic CO2 emissions from high heat flow areas may substantially contribute to the balance of the carbon cycle. Natural discharges of CO2 have several sources: the mantle, metamorphism of carbonate-bearing rocks, decomposition of organic material and surface biological activity (Irwin and Barnes, 1980). Generally, carbon dioxide in fault zones is a mixture of some of these sources (Sugisaki et al., 1983). Isotopes of carbon allow one to discriminate between the different sources: δ13 C=12 C-values are about 25‰, 7 to 4‰, and 0‰ for organic, mantle-, and sedimentary carbon, respectively (Allard, 1986). Finally, one has to consider phase fractionation processes with care because CO2 reacts with gaseous, liquid or solid constitutive components of hydrothermal systems. Dissolution of CO2 in deep alkaline waters is a frequent feature and can lead to subsequent enrichment of poorly soluble elements such as He (Sugisaki et al., 1980). High CO2 fluxes appear correlated with both high heat flux areas (associated with active and ancient volcanism) and limited areas with deep fracturing

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(emitting carbon originated from the mantle and from decarbonation processes, with possible mixing of these two sources). Irwin and Barnes (1980) suggested that discharges of CO2 might indicate areas with high pore pressure at depth, and therefore may serve to identify potential seismic regions. CO2 is used for fault mapping (Irwin and Barnes, 1980; Sugisaki et al., 1980, 1983; Baubron et al., 1990, 1991) as well as for both seismic and volcanic monitoring (Shapiro et al., 1982; Toutain et al., 1992; Rahn et al., 1996). – Methane is a highly reduced form of carbon which is thought to derive from a variety of carbon sources. Major processes involved in CH4 genesis are microbiological (bacterial) and thermogenic, both operating on biologically formed organic matter (Klusman, 1993). Klusman (1993) considered also of little importance the production of methane by equilibrium reactions in geothermal reservoirs, through the Fischer–Tropsch reaction which acts on inorganic sources of carbon, such as mantle-derived C. In active tectonic environments, methane is released close to major crustal discontinuities that show heat anomalies, and therefore is often associated with indicators of deep leaks such as He. CH4 -bearing spring gases are known in volcanic environments (from central discontinuities to adjacent sedimentary basins). Methane has been rarely used in some contexts for continuous monitoring (Kawabe, 1984; Sugisaki and Sugiura, 1986; Nagamine, 1994). – Hydrogen concentrations can vary in fault zone soils from less than 1 ppm to some tens of percent. It is thought to be produced by reactions between fractured rocks and groundwater (Sugisaki et al., 1983; Sugisaki, 1987). Kita et al. (1982) suggested Si–O radicals to react with water in faults at temperatures ranging from 25 to 270ºC. King and Luo (1990) suggested reactions of water vapour and either FeO impurities or Si and SiO radicals at fresh crack surfaces. Sato et al. (1985) suggested serpentinization to generate H2 anomalies at the San Andreas fault. Other “unknown processes acting along active faults” are also cited by Sugisaki (1987). Sugisaki et al. (1983) excluded a biogenic process for H2 generation because this gas usually is not associated with typically biogenic gases (mainly CH4 ) in fault air. On the contrary, Nagamine (1994) suggested the very low content (1.0 ppm) of H2 in Byakko spring

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(Japan) gases to be generated by bacterial oxidation of H2 S. The fact that H2 is probably generated within faulted zones at fresh mineral interfaces leads one to consider hydrogen as a good indicator of fault activity, H2 -bearing fault gas being considered as historically active (Sugisaki et al., 1983; Sugisaki, 1987). Problems may lie, however, in possible reactions of hydrogen with the surrounding environment. Continuous monitoring of hydrogen has been performed at various sites (Sato and McGee, 1980; Sugisaki et al., 1983; Sugisaki and Sugiura, 1985, 1986; Sato et al., 1986). – Nitrogen, oxygen and inert gases such as neon, argon, krypton and xenon have been detected in soil and spring gases. They are considered to be derived from the atmosphere upon dissolution in groundwater during meteoric recharge of hydrothermal systems. Recent works are generally performed by using two or more gas species. Sugisaki (1978) and Nagamine (1994) have investigated He=Ar and N2 =Ar ratios in spring gas. Baubron et al. (1990) and Toutain et al. (1992) used Rn, He and CO2 . Helium and Rn, which have very contrasting sources, are expected to mark deep and superficial gas transfers, respectively. Continuous monitoring of the He=Rn ratio is therefore expected to quantify the fluctuations of the respective contributions.

3. Sampling and analysis In soils, gases are commonly sampled at depths of 0.7–1.0 m with steel probes, sunk in the ground with a sliding hammer and equipped with a Teflon pipe. A disadvantage of this technique lies in the fact that lithologic heterogeneities of soils can lead to the use of varying sampling depths along a single transect. We recently used a new technique: digging with an electrical drill a hole 1 m deep and 3 cm diameter. The hole is coated with a cardboard tube insuring that it is airtight thanks to soil moisture (Fig. 1). The system is assumed to be at equilibrium at about 2 days after the setting up of the cardboard tube. This technique allows both that sampling is performed at the same regular depth along a profile and makes it possible to reiterate the measurements under identical conditions. During

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Fig. 1. Schematic diagram of discrete and in-situ measurements of soil gases. Cardboard tubes prevent atmospheric air contamination, and allow both air sampling at constant depth and repetition of profiles in similar conditions.

field sampling=analysing campaigns, we commonly get through 80 to 100 points a day by using holes previously coated with tubes (that is also a one-day performance) and specific on-line analysers carried in a car for CO2 , He and Rn determination. A variety of techniques have been used for soil gas analysis (Ball et al., 1991). Early measurements of radon were performed by using Lucas cells (Lucas, 1957). Activities of 222 Rn have been mostly measured with the particle track-etching method (counting of alpha-tracks with films acting as passive detectors, Fleischer et al., 1972). This method supplies integrated track formation rates over time sequences (usually lasting 3 to 30 days, depending on the radon concentration), thus smoothing effects of high frequency variations due to variation of atmospheric pressure, temperature, but also low-duration picks due to tectonic purposes. More accurate methods now use either ionisation chambers, scintillation methods or autonomous radon sensors that allow continuous monitoring (Baubron et al., 1991; Chambaudet et al., 1991; Toutain et al., 1992; Abbad et al., 1995; Pane et al., 1995; Pinault and Baubron, 1996, 1997). These latter techniques allow high-frequency

sampling (down to minute sampling) and therefore detection of short-duration spikes. Recent improvements for radon analysis led to the use of portable autonomous instruments operating with silicon sensors that supply electrical charges for incident alpha particles (for example BARASOL, Algade, Fr.). Other gases are analysed according to two main philosophies. The first one, used by Japanese teams, usually favour the use of gas chromatography (GC), allowing simultaneous analysis of H2 , He, Ne, Ar, N2 and CH4 in the field (Sugisaki et al., 1982; Nagamine and Sugisaki, 1991a). Nagamine (1994) used 2 GCs in order to cross-check analyses and to allow O2 detection to estimate atmospheric contamination. Advantages of the GC technique are the relatively low costs and the simultaneous analysis of various gases. Disadvantages are mainly the loss of all data in case of a breakdown and the need for a constant maintenance for column and carrier gas changing. The second improved method for continuous field analysis uses specific analysers. These are mainly infra-red spectrometers for CO2 , CH4 , H2 S, an electrochemical cell for O2 , and a specific mass spectrometer for He (Reimer et al., 1979; Hart et al., 1985; Marty et al., 1987; Baubron et al., 1991; Toutain et al., 1992). Advantages for this latter method are mainly the high-precision analysis (especially for helium), the high reliability of these machines which need only infrequent maintenance, and the small size and light weight of the He mass spectrometer (20 kg for the 100 HDS, ALCATEL, spectrometer). Gas chromatography appears to be adapted to the monitoring of gas phases with given compositions (high He concentrations), whereas mass spectrometry, as a result of the spectacular accuracy of measurements of 0.2%, is adapted to the monitoring of very peculiar mixing phases, even with very low He concentrations.

4. New results from geodynamically active areas In the last ten years, we have performed several studies dealing with both monitoring of geochemical parameters and prospecting of tectonically active structures. Bulk results are presented below and will be discussed in the following sections together with literature data.

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Bulgaria. Measurements have been made in the Balkan peninsula, that is linked with the Alpine orogenic belt. Southern Bulgaria displays various active tectonic zones with well-developed hydrothermal activity. In this area, many mineral waters appear controlled by tectonic lines, with most springs rising at the intersections of faults (Piperov et al., 1994). We have performed geochemical profiles across faults in the area of Velingrad, which was selected on the basis of its recurrent high level of seismicity. Fig. 2 is a geochemical profile across the Draginovo graben, in the northern Velingrad area (Baubron, 1989a), which outlines the variability of gas compositions at a spacing of 10 m. Italian Alps. Various geochemical transects have been performed across the Argentera–Vinadio fault. This is a seismically active NW–SE transform fault that cuts the Argentera and Mercantour massifs.

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Fig. 3 is a representative transect (He–CO2 –Ar) across the fault (Baubron, 1988). Profiles A and C show clear He and Ar anomalies which are evidence of gas leaking and which suggest deep rooting of the fault. Southern Spain. Fig. 4 displays time-series of atmospheric pressure, temperature, rain, local soil moisture together with radon activity sampled with four probes located within a 500-m large zone in soils over faults next to a hidden (200 m depth) sulphide deposit in southern Spain (copper belt, west of Sevilla). These time-series show very contrasting and independent patterns and suggest that different mechanisms are likely to operate as a function of the site. Costa-Rica. We have continuously monitored the radon in soil-air within an E–W fault located on the upper slope of the active Irazu volcano and filled with pyroclast. The objective was to document the radon response to hydrothermal changes related to seismic and=or volcanic events. Our results (Fig. 5) indicate that soil moisture and water content fluctuations can trigger increases of radon activities by a factor of 2 to 4.

5. Main patterns of degassing in soils and springs

Fig. 2. Geochemical transect across the graben of Draginovo (Bulgaria). Sampling step 10 m. Analyses are performed in the field by mass spectrometry for N2 , O2 , Ar and He, by infra-red spectrometry for CO2 , and by alpha counting for 222 Rn. Values are in vol.% (CO2 and Rn), ppmV (He) and pCi=l (Rn). These techniques have been already used in volcanic environments (Baubron et al., 1990, 1991; Toutain et al., 1992).

Faults can be described as least-strength zones composed of highly fractured material, gouge and fluids. These fluids are of particular interest, because they are thought to control both the strength and the rupture pattern of the fault and because they generate very high spatial contrasts for many geophysical parameters as the result of fluid-pressure heterogeneities (Eberhart-Phillips et al., 1995). Active faults favour gas leaks because they increase permeability of soils, getting easy gas migration. These anomalies, however, display a complex character, both in space and time. For example, anomalies may differ according to the structure of faults. Sugisaki et al. (1980) suggested that gases charged in fault gouges differ chemically from those that issue through intensely sheared zones which are commonly composed of highly fractured rocks. King et al. (1993) showed that radon patterns of creeping faults exhibit double peaks, which may be due to a low gas permeability of fault-gouge materials of

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Fig. 3. Geochemical transects (A, B, C, D) across the Argentera–Vinadio fault (Argentera–Mercantour massif, Italian Alps). Soil gases are sampled at dephts of 0.7–1.0 m in the ground by using stainless-steel probes, 1 cm diameter, filled with a Teflon capillary. Sampling step is usually of 10 m, sometimes 5 m. Horizontal axes are distances in meters. Open squares, open lozanges and filled lozanges are CO2 (%), Ar (%), and He (ppm) concentrations, respectively. Analyses are made by mass spectrometer and infra-red spectrometer. Helium concentration in air is 5.24 ppm, and soil He background values are about 5.3 š 0.3 ppm. He anomalies are therefore defined as values above 5.7 ppm (solid horizontal line on graphs). Both punctual and scattered He anomalies recorded on the A and C transects, respectively, suggest deep rooting of the fault. The negative helium anomalies of transects B and D suggest meteoric water infiltration processes with subsequent solubilization of He. Carbon dioxide levels lie within biogenic activity. From Baubron (1988).

the creeping zone and high permeability of fractured rocks in the adjacent shear zones. This suggests that lithofacies cut by the fault partly control the shape of the anomaly. The type of fault may be also of considerable importance for the degassing level. Muir-Wood and King (1993) investigated deformation patterns occurring during the interseismic regime in the vicinity of faults. They suggested that normal faults tend to increase the effective porosity through the opening of cracks, whereas reverse faults display lower porosity due to crack closure. Within this frame, higher fluid flows are expected in reverse fault environments than in normal faults during interseismic regimes (Muir-Wood and King, 1993). Accordingly, soil gas prospecting might be better able to detect fractures in the compressional

regime. Systematic soil gas investigations over seismic faults, however, fail to assert whether the type of fault is a discriminant factor in soil degassing. Geochemical anomalies at active faults can be either ‘direct leak anomalies’ with the gas measured corresponding to the deep gas phase, or ‘secondary anomalies’ linked to the different petrochemical nature of the fault-constituting rocks, with intermediate terms. Fig. 2 is a geochemical profile (He, Rn, Ar, CO2 ) across the Draginovo graben (Bulgaria, Baubron, 1989b) which outlines the variability of gas compositions at a spacing of 10 m. A large CO2 – Rn–Ar-bearing anomaly along the boarding fault of the graben and a narrow and strong He and CO 2 on which a drill successfully found groundwater can be recognized. Temporal fluctuations due to weath-

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Fig. 4. Time-series of rainfall (Rf, mm=h), soil moisture (Hum, in g H2 O=100 g soil), atmospheric pressure (P, mm Hg), atmospheric temperature (Ta, ºC) and Rn (counts per hour) measured in a soil in southern Spain over a hidden sulfide deposit. Radon is measured at 4 sites located within 500 m by using automated radon monitors (alpha counters equiped with a static silicon detector). Sampling rate is 1 measure=h. See Pinault and Baubron (1996) for mutichannel spectral analysis of these signals.

ering can also alter the nature and the distribution of anomalies. Phenomena of self-sealing of the fractures, or pyroclastic rock alteration in volcanic areas (Lombardi et al., 1984) may disturb initial permeability and porosity characteristics, having effects on soil-air composition and distribution. These characteristics of selected degassing have been widely used for prospecting and=or mapping purposes, especially by studying radon emanation and helium degassing. Israe¨l and Bjornsson (1967) first identified faults using radon and thoron anomalies in soil air. Woith et al. (1991) performed 600 discrete Rn measurements

in springs and showed that radon peaks are lined up along a 60-km-long fault system in eastern Turkey. Wakita et al. (1980) showed hydrogen leaks along the Yamasaki fault (Japan). Baubron (1989a) mapped active faults in the Velingrad and Plovdiv regions (Bulgaria). Fig. 3 shows the results of He–CO2 –Ar transects across the Argentera fault in the Italian Alps (Baubron, 1988). Transects A and C show clear He and Ar anomalies which outline significant leaking, suggesting a deep rooting of the fault. Other transects (B and D) show soil He levels below background values, suggesting that the Argentera fault is

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Fig. 5. Example of a soil radon anomaly created by soil water content changes. After a 3-month period of a stable regime emanation for radon measured at 90 cm depth in the ground at Irazu Volcano, displaying a mean value of 15; 000 š 5000 Bq=m3 , an anomaly up to 50,000 Bq=m3 lasted for 10 days and was followed by oscillations between 10,000 and 20,000 Bq=m3 . The anomaly corresponds to a tropical trough which was followed by an atmospheric unsteadiness for 1 month. The daily fluctuations of Rn (1 or 2 cycle=day) are evidence to the advective regime of the emanating gas carring Rn. Monitoring of soil radon with Barasol probes. Station I7. Irazu volcano, Costa-Rica.

formed of various segments, some of them having only superficial roots. Soil-gas prospection constitutes a powerful tool for locating faults, and supplies data that may be used to quantify the level of activity of a fault. Baubron et al. (1991) showed at the Lamongan seismo-volcanic field that concentrations of CO2 measured across a hidden fracture varied as a function of seismic activity. Sugisaki et al. (1983) pointed out that H2 mapping of faults may help to discriminate recently moved faults from other inactive Quaternary faults, with concentrations in soils ranging from 1 ppm up to 104 ppm. Soils in faulted zones appear therefore as suitable tools for studying spatial and temporal patterns of gas leaks. Disadvantages of soil gases, however, lie in the weak gas concentrations generally due to the thickness of the sedimentary cover and the high level of atmospheric contamination usually found (Sugisaki et al., 1980). It seems reasonable to consider that multi-component (e.g. He, Rn and CO2 ) soil gas analysis is a powerful tool for fault investigations with sedimentary cover less than 1000 or 2000 m. Because they outline the persistent link between deep crustal rocks and surface aquifers for thousands of years, thermal springs may provide better sites for quantitative considerations and continuous monitoring. Thermal waters, indeed, need persistent structural conditions for surface emission and rising

of deep and hot water needs high-permeability pipes related to recent tectonics. Gastil and Bertine (1986) displayed the close relationship between the distribution of thermal waters and both seismicity and active fault distribution in California. They suggested that areas with abundant thermal waters display earthquakes with a higher frequency and a lower energy than areas without thermal waters, probably because faults release stress more frequently when they occur within thermal-water provinces. Owing to the persistence in time of thermal springs, they proposed that a map of thermal springs may constitute a better indicator of potential earthquake magnitude and frequency than does an instrumental seismic record (Gastil and Bertine, 1986). This is not unexpected since microseismicity is likely to avoid the sealing of the fractures. Hydrothermal CO2 -bearing faults without microseismicity should develop travertine deposits with time, which in turn should stop the rising of water. Within this frame, one should consider as potentially hazardous active faults with travertine deposits. Sugisaki et al. (1980) postulated that bubbles observed in mineral springs collect gases from a voluminous rock body at depth, thereby leaching and assimilating numerous trace elements and gases. Moreover, the volume of related fault rock involved in degassing might be considerable as springs often occur at intersections of faults. Ac-

J.-P. Toutain, J.-C. Baubron / Tectonophysics 304 (1999) 1–27

cordingly, they could be much more representative of the geologic environment and could be more reactive to stress=strain changes acting at depth than soil gases. Inhomogeneities, however, also occur in spring systems. Local patterns of superficial fractures might control hydrologic systems (Muir-Wood and King, 1993). Moreover, because the sign of the strain change in the vicinity of a fault can be independent of the regional strain field, the response of a spring in a fault may be untypical of the region. Spring gases may also reflect lithological features of the system, with mineral waters in granitic areas being particularly Rn- and He-rich, whereas carbonate springs with free CO2 rise from carbonated sedimentary layers. In this latter case, He concentrations are often very low, due to dilution by sediment-derived carbon dioxide. CO2 -free springs, however, may also occur within granitic areas, usually related to thermal flux anomalies. A considerable advantage of spring gases as compared to soil gases is the lack of significant contact of the mineral water with atmospheric air. Fig. 6 is a N2 =Ar versus He=Ar plot which enables to discrim-

Fig. 6. Geochemical discrimination between soil and spring gases from faulted zones of central Japan, from Sugisaki et al. (1983). He=Ar and N2 =Ar are normalized by the ratios in atmospheric air. Lines of unity represent atmospheric air composition. Filled squares are spring gases, open squares are soil gases. This representation outlines the high degree of contamination of soil gases by atmospheric air. Note the spring gas composition from Inuyama in the field of soil gases (He: 7.3 ppm), probably as the result of air contamination due to a low discharge of water (Sugisaki and Sugiura, 1986).

11

inate soil and spring gases from central Japan (Sugisaki et al., 1980). Fig. 7 shows He–CO2 systematics for soil and spring gases, and also that spring gas is much more enriched in He and CO2 than soil air. Accordingly, spring gases appear as more suitable for continuous monitoring with the objective of detecting precursory signals of earthquakes. Absolute concentrations of soil and spring gases, however, must be examined with caution with regard to source considerations. Fluids may undergo severe chemical modifications upon migration to the surface. Dilution by superficial waters and re-equilibration can affect thermal waters as seen from major and trace elements chemistry (Michard, 1990) and from water temperature measurements. Dilution by surface gases of biological origin may alter CO2 and CH4 signatures. Physical processes such as early deep demixing of some gases — due to their different solubilities — from a single reservoir can lead to heterogeneous gas ratios at the surface.

6. Environmental perturbations Because measurement of gases is performed at the ground surface (air and=or water-filled soil or spring water), the result is highly perturbated by external factors, such as atmospheric pressure and temperature variations, soil humidity and earth tides. Many relations of external factor-induced variations of gases are available in literature. Most of them concern radon and, in a lesser extent, carbon dioxide and helium. Clear correlations have been found between atmospheric pressure variations and ground gas concentrations. Segovia et al. (1987) outlined experimentally the influence of pressure gradients for longterm observations of radon concentration. Shapiro et al. (1982) and Toutain et al. (1992) showed that daily carbon dioxide and radon fluctuations of spring gases were in phase anti-correlated with barometric pressure. The severe influence of atmospheric pressure on radon emanation has been shown by several authors (Clements and Wilkening, 1974; Duenas and Fernandez, 1987; Schery et al., 1993; Chen et al., 1995). Pressure variations controlling methane fluxes from sediments have been also reported (Mattson and Likens, 1990). This pressure response is interpreted to be the result of the compression and

12

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Fig. 7. He–CO2 systematics for soil and spring gases. Soil data are from geochemical traverses performed across the following faults: Santa-Anna (Argentera, Italian Alps), Marie-Galante (French Guadeloupe), Draginovo (Bulgaria) and Les Salles (French Arde`che). See Baubron (1988, 1989a,b, 1990) for details. Spring analyses are from east Bulgaria (Piperov et al., 1994) and French Arde`che and Alps (Marty et al., 1992).

expansion of the soil gas column between the surface and the top of the water table (Chen and Thomas, 1994). A recent study used this antagonism between atmospheric and advection pressures to calculate the velocity of the gas transfer (Pinault and Baubron, 1997). One study (Morin, 1992) showed the lack of effects of pressure on radon concentration. In this latter case, Rn mobility was probably only due to diffusion. Temperature-related fluctuations of gas concentrations have also been discussed. Shapiro et al. (1980) related thermo-elastic strains in the vicinity of the borehole to the annual cycle of radon concentration. Reimer (1980) suggests that air temperature changes act on soil moisture contents and therefore partially control He concentrations in soils. From experiments Segovia et al. (1987) suggested the existence of a temperature effect. On the contrary, King (1980) concluded there was a lack of temperature effects on radon concentration of the San Andreas fault for measurements over longer periods (weeks to months). Wind influence has been investigated and does not seem to generate any deep influence (Chen and Thomas, 1994). Reimer (1980), on the contrary,

suggests that wind can affect gas emission through atmospheric pumping effects. Besides such effects, serious variations of gas composition of thermal springs have been pointed out as the result of fluctuations of local hydrologic regime (Klusman and Webster, 1981; Segovia et al., 1986; Borchiellini et al., 1991; Morin, 1992). Some observations suggest that infiltrating rainwater over an aquifer in a karstic environment causes dilution of radon concentrations in the aquifer and that radon is carried off by the descending waters (Eisenlohr and Surbeck, 1995). In California soils, seasonal trends of radon concentration in high permeability soils suggest that water-saturated surface soil during the rainy season tends to reduce gas permeability, whereas the dry season is characterized by high levels of degassing (King and Minissale, 1994). Opposite trends are recorded in soils of low permeability, which are expected to display higher radon values during the rainy season. Sugisaki (1981) suggested the existence of a positive correlation between fluctuations of the He=Ar ratio of spring gases and earth tide-related strain. This author postulated that water was squeezed out from fissures and crystal boundaries of minerals by

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earth-tide-induced stress in the ground. In this case, gases dissolved in deep waters have a higher He=Ar ratio than superficial waters, and successive phases of compression and expansion of the crust due the earth tides cause the periodic variation of the ratio in spring gas. This is not unexpected since water level and temperature fluctuations in shallow wells in relation to earth tides have been widely described (Roeleofs, 1988; Mogi et al., 1989). Such correlations need, however, to be confirmed with long-term and high-frequency recording of gas compositions at selected sites. Pinault and Baubron (1996) suggested that in systems driven by diffusion or slow advection processes, 222 Rn activities in soils might be controlled by soil moisture and rainfall through the opening of cracks in the surface, the effects of this being still noticeable twenty days after the rainfall. On the other hand, these authors suggest that in convective=advective systems, which display generally higher gas flows, radon concentrations in soils are controlled mainly by atmospheric pressure. Assuming that those relatively high gas flows generally characterise active faults, one may suggest that Rn response to atmospheric pressure can be used as an indication of appropriate sites for continuous monitoring. Complex responses to atmospheric effects, however, can occur even on the same site. Fig. 4 displays time-series of atmospheric pressure and temperature, rain, soil moisture and radon activity sampled with four probes located within a 500 m large zone in soils over faults next to a hidden sulphide deposit (southern Spain, Baubron, unpublished results). Radon concentration varies at probe 2 with soil moisture, being probably dependent upon crack opening and closing. Radon at probe 4 varies with atmospheric pressure for daily variations and with atmospheric temperature for longer-period variations. Radon concentrations at probes 1 and 3 vary in opposite ways in response to the same rainy event. Such heterogeneities in responses are likely to be related to micro-scale soil heterogeneities in permeability, porosity and lithology, in accord with similar observations of King and Minissale (1994). This late case study outlines the need for soil gas prospecting before choosing monitoring sites in soils. Case studies that relate such changes to external factors are numerous and often divergent. They

13

demonstrate, however, that the geochemical composition of soil or spring fluids may strongly vary with time without any tectonic=seismic effect, and that in some cases seasonal variations can be greater than the signal expected from structural considerations (Ball et al., 1983). They also outline the complexity and the diversity of geological, hydrological and meteorological local contexts. Such results point out the poor representation of discrete measurements and exhibit the need for continuous monitoring for prediction purposes, especially for spring gas measurements. This review shows that no systematic predetermined law for correcting gas measurements can be proposed. Therefore, studies aimed at detecting gaseous precursors need the simultaneous record of meteorological parameters in order to perform statistical analysis for removing meteorological effects (Igarashi et al., 1990; Igarashi and Wakita, 1990; Nagamine and Sugisaki, 1991b; Matsumoto, 1992; Pinault and Baubron, 1996). Finally, as already stated by Hinkle (1994), the very large dynamics of gas fluctuations at some sites requires severe interrogations about the representation of discrete measurements — especially in spring gases — as well as the reliability of some data performed without external parameters controls.

7. Evaluation of literature data More than 150 gas anomalies have been proposed as precursors of tectonic earthquakes in the literature, and are listed in Table 1. Most of them concern radon emanation from soils or groundwater because analysis of 222 Rn has been easily performed as early as the 1940’s by using the track-etch method. Moreover, as this is an inexpensive method, relatively high density networks of radon stations were set up, mainly in P.R. of China, the former USSR and USA, making possible the multiple detection at various sites of single earthquakes. Evaluating the main parameters of these signals may provide a better understanding of the phenomenon. The main parameters which are commonly displayed in papers (magnitude and location of earthquakes), together with the nature, the relative amplitude, the duration and the epicentral distance of the geochemical signal are listed in Table 1. This list includes radon as well as other gaseous pre-

14

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Table 1 List of gas precursors related in literature Area

Date

Iceland Southern Iceland Seismic Seismic Seismic Seismic Seismic Tjornes fracture

03=07=78 28=08=78 28=08=78 19=11=78 29=06=79 05=09=79 05=09=79 15=12=79

z Gas Deviation, δa (km) (%)

M

D (km)

2.7 3.4 3.4 4.3 1.9 2.8 2.8 4.1

14 5 21 16 9 8 5 56

Duration, d (days)

Hauksson and Goddart, 1981 a Hauksson and Goddart, 1981 Hauksson and Goddart, 1981 Hauksson and Goddart, 1981 Hauksson and Goddart, 1981 Hauksson and Goddart, 1981 Hauksson and Goddart, 1981 Hauksson and Goddart, 1981

(C) 380 (C) 60 (C) 280 ( ) 80 (C) 40 (C) 40 (C) 100 (C) 100 (C) 120 (C) 500 (C) 400 (C) 200 (C) 44 (C) 40 4 spikes (C) 800 (C) 100

Loma Prieta Coyote Lake Mt Diabolo Salinas Livermore St Juan Bautista

??=06=83 13=10=79 22=12=79 17=10=89 06=08=79 24=01=80 13=04=80 24=08=80 07=01=81

Rn Rn Rn Rn Rn Rn Rn H2 Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn He Rn Rn Rn He He He He He He

4.3 4 4 4.2 2.9 2.8 4.6 5.2–6.7 5.6 3.9 1.5 (C) 36 3.5 ( ) 50 2.3 (C) 62 2.9 (C) 25 2.8 (C) 72 4.7 (C) 225 4.7 (C) 310 5 (C) 72 5 (C) 400 6.6 (C) 200 6.6 (C) 72 6.6 (C) 64 6.6 6.6 (C) 375 3.9 (C) 60 4.8 (C) 65 4.8 (C) 1200 3.7 (C) 400; (C) 60 3.4 (C) 800; (C) 8 3.3 (C) 4 7.1 ( ) 5.9 ( ) 5.5 ( ) 4.9 (C) 4.1 ( ) 4.5

25 60 25 47 90 25 45 15 30 75 240 90 21 1 5 12 10 24 54 4 spikes 40–120 300 10 7 14 1 25 31 1 14 21 3 5 12 9 54 42 20 82 85 12 31 45 335 116 310 95 265 145 260 2 300 nd 33 60 30 150 120 30 150 120 13 3 15 40 0.5 0.2 20 1 0.5 60 1 65 21 155 35 35 28 120 45 10

King, 1980 King, 1980 King, 1980 King, 1980 Shapiro et al., 1980 Shapiro et al., 1980 Shapiro et al., 1980 Sato et al., 1986 b Teng and Sun, 1986 Fleischer, 1981 Fleischer, 1981 Hauksson, 1981 Hauksson, 1981 Shapiro et al., 1980 Shapiro et al., 1980 Shapiro et al., 1980 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Fleischer, 1981 Steele, 1981 Chung, 1985 c Chung, 1985 Shapiro et al., 1985 King, 1985 King, 1985 Reimer, 1990 Reimer, 1990 Reimer, 1990 Reimer, 1990 Reimer, 1990 Reimer, 1990

Mexico Mexico

19=09=85

Rn

(C) 200

260

Segovia et al., 1989

Alandale San Andreas

17=03=76 19=01=77 15=12=77 29=08=78 24=09=77 20=12=77 01=01=79 07=06=09 08=04=85

22=11=76 23=02=77 24=09=77 20=12=77 01=01=79 01=01=79 28=06=79 28=06=79 15=10=79 15=10=79 15=10=79 15=10=79 15=10=79 ??=06=79 30=06=79

9 6 11 6 15 6 ?

8.1

nd

25 30 27 10 25 20 33 50

Author(s)

Rn Rn Rn Rn Rn Rn Rn Rn

USA San Andreas fault San Andreas fault San Andreas fault San Andreas fault South California South California Malibu Coalinga fault Kettleman Hill Raquette Lake Blue Mountain Lake Pearblossom Jocasse Pasadena Pasadena Malibu Malibu Big Bear Big Bear Imperial Valley Imperial Valley Imperial Valley Imperial Valley Imperial Valley Caruthersville Big Bear

22 17 17 18 19 17 33 50

δt, days before

nd

J.-P. Toutain, J.-C. Baubron / Tectonophysics 304 (1999) 1–27

15

Table 1 (continued) Area

Date

Ecuador Reventador

06=03=87

France Ligurian Sea

01=05=86

Japan Western Nagano

14=09=84

Western Nagano

14=09=84

? Byakko

z Gas (km)

M

D (km)

Duration, δt, days d (days) before

Rn

6.9 (C) 230 6.9 (C) 400 6.9 (C) 100 6.9 (C) 100 6.9 (C) 300; ( ) 90 6.9

Rn

(C) 100

3.9

( ) ( ) ( ) ( ) (C) 2000

6.8 50 6.8 50 6.8 50 6.8 50 6.8 70 3.8 8.6 6.6 280 4.2 31 3.9 35 6.0 200 4.1 100 4.3 15 4.3 45 7.0 216 6.8 25 6.8 25 7.7 480 4.9 50 7.9 1000 6.7 130 7.2 30 7.2 30

230 230 230 120

06=08=82 ? 24=09=90 16=10=90 11=05=91 01=06=90 59 03=04=77 06=08=77 15=08=77 14=01=78 14=01=78 14=01=78 26=05=83 10=12=82 06=03=84 452 06=02=87 35 17=01=95 17=01=95

N2 =Ar He=Ar Ch4 =Ar H2 H2 H2 He=Ar He=Ar He=Ar Rn He=Ar He=Ar He=Ar He=Ar Rn Rn H2 Ch4 =Ar Rn Rn Rn Rn

P.R. China Pohai Bay Ningshin Hsingtang Haicheng Haicheng Haicheng Haicheng Haicheng

18=06=69 05=08=71 06=06=74 04=02=75 04=02=75 04=02=75 04=02=75 04=02=75

Rn Rn Rn Rn Rn Rn Rn Rn

(C) 60 (C) 200 (C) 290 (C) 38 (C) 17 ( ) 43 (C) 20

7.4 4.3 4.9 7.3 7.3 7.3 7.3 7.3

170 40 16 270 50 66 8

Liaoyang Tangshan Tangshan Tangshan Tangshan Tangshan Chienan Sabteh

27=06=76 27=06=76 27=06=76 27=06=76 27=06=76 07=03=77 08=04=72

Rn Rn Rn Rn Rn Rn Rn

(C) 15 (C) 50 ( ) 40 (C) 27

Chiba-Ken-Oki Nagoya

Izu-Oshirna Izu-Oshirna ? Matsuyama area Subducted zone Kobe

14

Deviation, δa (%)

3.8 3.8 3.8 3.8

(C) (C) (C) ( )3 (C) (C) (C) (C) (C) 7 ( )8 (C) 100,000 (C) 120

(C) 200 (C) 1000

(C) 70 (C) 55

4.8 7.8 7.8 7.8 7.8 7.8 6 5.2

367 377 339 388 183 350 56

170 42 18 50 50 140 140 26 14 32 50 100 130 130 1800 200 70

50 15–50 15–35 50 15–40 10–40 5

0.1 0.15 0.25 1 60 60 75 130 230 7 ? 120 2 4 90 3

3 120 120 120 50 15 70 Coseismi Coseismi Coseismi 60 50 50 120

? 100 9 3 75 10

970 15 1370 162 3 12

1

Author(s)

Humanante et Humanante et Humanante et Humanante et Humanante et Humanante et

al., 1990 d al., 1990 al., 1990 al., 1990 al., 1990 al., 1990

Borchiellini et al., 1991 Sugisaki and Sugiura, 1986 Sugisaki and Sugiura, 1986 Sugisaki and Sugiura, 1986 Sugisaki and Sugiura, 1986 Sugisaki and Sugiura, 1986 Sugisaki and Sugiura, 1986 Nagamine and Sugisaki, 1991a Nagamine and Sugisaki, 1991a Nagamine and Sugisaki, 1991a Wakita et al., 1989 Sugisaki, 1978 Sugisaki, 1978 Sugisaki, 1978 Sugisaki, 1978 Wakita et al., 1988 Wakita et al., 1988 Satake et al., 1985 Kawabe, 1984 Igarashi and Wakita, 1990 Igarashi and Wakita, 1990 Igarashi et al., 1995 e Igarashi et al., 1995 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Fleischer, 1981 Fleischer, 1981 Fleischer, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Fleischer, 1981 Teng, 1980 Teng, 1980

16

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Table 1 (continued) Area

Date

Takung Luhuo Yiliang Songpan Mapien Lungling Lungling Lungling Lungling Lungling Lungling Lungling Songpan-Pingwu Songpan-Pingwu Songpan-Pingwu Songpan-Pingwu Songpan-Pingwu Songpan-Pingwu Songpan-Pingwu Songpan-Pingwu Songpan-Pingwu Fengzhen Tangshan Ninghe Songpan

27=09=72 06=02=73 22=04=73 08=05=73 29=06=73 29=05=76 29=05=76 29=05=76 29=05=76 29=05=76 29=05=76 29=05=76 16=08=76 16=08=76 16=08=76 16=08=76 16=08=76 16=08=76 16=08=76 16=08=76 16=08=76 ??=??=81 27=07=76 15=11=76 16=08=76

Ex-USSR Taschkent Taschkent Taschkent Taschkent Taschkent Taschkent Taschkent Uzbekistan Markansu Tien Shan Gazli Gazli

26=04=66 24=03=67 20=06=67 22=07=67 09=11=67 17111=67 17=12=67 13=02=73 11=08=74 12=02=75 17=05=76 17=05=76

Gazli Isfarin-Batnen Isfarin-Batnen Alma-Ata Zaalai Zaalai Zaalai Zaalai Iran Duchambe

17=05=76 31=01=77 31=01=77 24=03=78 01=11=78 01=11=78 01=11=78 01=11=78 16=09=78 29=09=81

Deviation, δa (%)

M

D (km)

Duration, d (days)

Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn H2 Rn H2 Rn

(C) 34 (C) 120 (C) 41 (C) 40 (C) 89 (C) 20 (C) 15 (C) 8 (C) 12 (C) 7 (C) 20 (C) 200 (C) 29 (C) 11 (C) 20 (C) 70 ( ) 12 (C) 90 ( ) 60 (C) 55 (C) 110 (C) 1000 (C) 50 (C) 900 (C) 100

5.8 7.9 5.2 5.2 5.5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 5.8 7.8 6.9 7.2

54 200 340 345 200 20 190 210 215 360 420 450 40 100 100 320 320 340 340 390 560 285 460 nd 350

12 9 14 14 9 510 425 160 130 75 290 12 480 420 190 1 200 48 160 160 34 15 8 12 1.5

Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn Rn H2 S Hggas

(C) 20 (C) 100 (C) 23 (C) 20 (C) 23 (C) 23 (C) 23 (C) 47 (C) 100 (C) 10 (C) 220 (C) 25

5.3 4 3.5 3.5 3 3.3 3 4.7 7.3 5.3 7.3 7.3 7 7.3 6.6 6.6 7.1 6.7 6.7 6.7 6.7 ? ? ?

5 5 5 5 5 5 5 130 530 100 470 550 700 400 190 200 65 270 300 150 150 nd 20

400 11 3 3 8 7 4 5 100 110 4 90

z Gas (km)

( ) 30 ( ) 20 (C) 32 ( ) 30 ( ) 40 (C) 20 ( ) 20 (C) 170 (C) 400 (C) 9000

60 125 50 470 470 75 70 2

δt, days before

Author(s)

7 10 8 10

Teng, 1980 Wakita et al., 1988 Teng, 1980 Hauksson, 1981 Wakita et al., 1988 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Teng, 1980 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Shi and Cai, 1986 Shi and Cai, 1986 Jiang et al., 1981 Jiang and Li, 1981

25 1.2 0.8

Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Fleischer, 1981 Fleischer, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Hauksson, 1981 Barzukov et al., 1985 Varshal et al., 1985 Varshal et al., 1985

J.-P. Toutain, J.-C. Baubron / Tectonophysics 304 (1999) 1–27

17

Table 1 (continued) Gas Deviation, δa (%)

M

D (km)

Duration, d (days)

δt, days before

Author(s)

Rn Rn

(C) 25 (C) 170

6.5 6.5

220 200

150 180

150 180

Allegri et al., 1983 Allegri et al., 1983

Rn Rn Rn Rn Rn

nd nd nd nd nd

5.8 5.2 4.6 5 5.3

39 23 14 37 45

nd nd nd nd nd

19 11 15 4 51

Liu et al., 1985 Liu et al., 1985 Liu et al., 1985 Liu et al., 1985 Liu et al., 1985

20=10=91

Rn

Rn Rn Rn Rn Rn Rn Rn

7 7 7 2.2 2.7 4.4 4.4 3.6 3.7 3.7

450 270 330 166 105 440 440 265 325 325

7 7 7

09=04=92 23=05=95 12=01=93 12=01=93 21=07=92 05=08=93 05=08=93

(C) 200 (C) 300 (C) 180 (C) 195 (C) 165 (C) 153 (C) 183 (C) 250 (C) 242 (C) 227

15 15 3 2 3 9 9 13 10 10

Virk and Baljinder, 1994 f Virk and Baljinder, 1994 Virk and Baljinder, 1994 Virk, 1995 g Virk, 1995 Virk, 1995 Virk, 1995 Virk, 1995 Virk, 1995 Virk, 1995

Area

Date

Italy Irpinia Irpinia

23=11180 23=11=80

Taiwan Northern Taiwan

India Uttarkashi

Himachal Pradesh

18=10=80 14=05=81 21=06=81 18=07=81 31=10=82

z (km)

8.2 8.2 8.4 6.7 9.8

a Values

from Hauksson (1981). This author does not supply time lag values. Hydrogen values from Sato et al. (1986). H2 displays a very complex pattern probably linked to a sudden increase in seismicity (11 events of magnitude 5.2 to 6.7 within 6 months). c The Big Bear earthquake swarm occured on June 29 and 30. The main shock was M D 4.8 and was considered as the total event. d Time lags vary at some sites which have several probes. No duration of anomalies are showed because of the track-etch method used. Values of deviation of signal at each site are from one of the several probes. Values at one site (epicentral distance of 350 km) are either positive or negative, depending on the probe (Humanante et al., 1990). e According to data by Igarashi et al. (1995), we can assume the existence of two precursors, one lasting about 3 months and the other being a spike-like one occurring 7 days before the onset. f Magnitudes were indicated to be 6.5 (M ) and 7.0 (M ). b S g Only anomalies above 2¦ have been selected. Graphical data are not enough precise to estimate values of duration and time lags of claimed anomalies. b

cursors. To constitute this listing, we have used the evaluations of world-wide data published by Hauksson (1981), some general reviews on geochemical precursors (Teng, 1980; Barzukov et al., 1985; King, 1986, 1989; Wakita et al., 1988) and other papers which were focused on specific case studies. These data should be evaluated with caution. Indeed, precise information about both instrumental and site-related background noise are rarely supplied by authors. Moreover, data related to seismic activity, such as focal depths, focal mechanisms, number and magnitude of earthquakes for both preand post-seismic periods, nature of the rules chosen by authors for selecting couples of data (anomalies and earthquakes), the maximum epicentral distance

considered, are poorly displayed. Another source of heterogeneity is probably due to different analytical methods used, from low-frequency sampling methods (with integration periods as long as several weeks for track-etch) to high-frequency continuous measurements (up to 1 measurement per minute) and spike-like anomalies obviously cannot be detected with low-frequency sampling methods. Without rejecting the published data, we consider that the main source of uncertainty — probably up to error — with respect to claimed precursor identification lies probably both in the lack of consideration of external effects and in the too short sampling periods that many authors considered. Our results of radon monitoring in volcanic soils (Fig. 5), indeed, as well

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as those of Pinault and Baubron (1996) indicate that increase of radon activities by a factor of 2 to 4 (that is a 100 to 200% increase of signal) are commonly recorded as the result of soil moisture and water content fluctuations. Pinault and Baubron (1997) have demonstrated how atmospheric pressure fluctuations may control the emission of gas from soils in convection=advection-dominated systems and that numerous geochemical variations might be related to meteorological effects rather than to seismo-tectonic ones. All these deficiencies or imprecise data likely contribute to a high level of uncertainties for identification of anomalies, therefore leading to potential errors in correlating earthquakes to anomalies. Besides these heterogeneities, however, considering these data may supply qualitative information. We have investigated our set of data following the method of Hauksson (1981) who displayed a worldwide set of radon data with correlations between precursory time intervals .Žt/ and signal amplitudes .Ža/ with both earthquake magnitudes (M), duration

(d) and epicentral distances (D). From his compilation concerning radon, Hauksson (1981) concluded mainly that (1) radon anomalies occur at distances which increase with increasing magnitudes, (2) precursory times increase with both increasing magnitudes and decreasing epicentral distances, and (3) relative peak amplitudes decrease with increasing distances for a given magnitude. 7.1. Relationships between magnitudes and epicentral distances Fig. 8 is a plot of epicentral distances (D) of anomalies as a function of magnitude (M) of correlated earthquakes listed in Table 1. It confirms that gas anomalies are detected at epicentral distances sometimes very large (maximum distance proposed is about 1800 km for a M D 7.8 earthquake; Fleischer, 1981). The dashed line on Fig. 8 characterises also typical rupture lengths (L) for given magnitudes

Fig. 8. Plot of the epicentral distances versus magnitudes for data listed in Table 1. Open and filled squares represent Rn and other gas anomalies, respectively. Greyish lozenges correspond to Rn values obtained in Himachal Pradesh (India) by Virk (1995). Plain lines characterize the relationship between strain radius and magnitudes for strains ranging from 10 7 to 10 9 using the empirical reationship proposed by Dobrovolsky et al. (1989) on the basis of an ellipsoidal earthquake preparation zone that produces a long-range strain field under stress. The single bold line characterizes the empirical relationship of Fleischer (1981) who calibrated the maximum distance of a radon anomaly for a given magnitude on the basis of a shear dislocation of an earthquake. Dashed line L characterizes typical rupture length of active faults as a function of magnitude by using the empirical law of Aki and Richards (1980).

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calculated with the following equations: Mw D 2=3 log Mo

6:0

(1)

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7.2. Effects of magnitude (M) on duration (d), precursory time intervals (Žt) and amplitudes (Ža) of anomalies

and Mo D ¼W Lu

(2)

where Mo is the seismic moment, Mw is the energy magnitude, L is the rupture length, W is the rupture width, u is the displacment, ¼ the shear modulus. u and ¼ are assumed to be 6 ð 10 5 L and 3:3 ð 1010 , respectively (Aki and Richards, 1980). Fig. 8 outlines that even if anomalies occur sometimes in the vicinity of preparation zones, most of them are detected at epicentral distances much greater than typical lengths. This pattern was already noted by various authors (i.e. Hauksson, 1981; Fleischer, 1981; King, 1986). Fig. 8 shows also that radon and other gases behave similarly, suggesting that all crustal gases are involved by common driving mechanisms in the generation of gas anomalies. In this figure lines are drawn which characterise the relationship between strain radius and magnitudes for strain ranging from 10 7 to 10 9 , by using an empirical relationship .E D 100:43M km) proposed by Dobrovolsky et al. (1989) on the basis of an ellipsoidal earthquake preparation zone which produces a long-range strain field under stress. One can see that the manifestation zone of much of the anomalies is limited by a straight line corresponding to a deformation of 10 9 , most of them being limited by the deformation limit of 10 8 . This limitation is in good agreement with calculations of Fleischer (1981) who proposed a similar relationship (bold line in Fig. 8) based on a shear dislocation model of an earthquake. The fact that anomalies occur down to the field of deformation of 10 8 to 10 9 is also consistent with the known earth tides-related fluctuations of spring gas ratios already detected (Sugisaki, 1981). Some scattered points (greyish lozenges in Fig. 8) seem to occur at epicentral distances up to one order of magnitude higher than the maximum strain=magnitude relationship would suggest. These are radon data, obtained both in soils and wells in Himachal Pradesh (northern India) by Virk (1995). As information about meteorological effects and background values were not supplied, we consider these data as uncertain and we will not include them in the following discussion.

Fig. 9C shows that most anomalies last less than 500 days and that their durations increase with increasing magnitude. Precursory time intervals (δt, Fig. 9B) also increase with magnitudes at least until M D 7. The detection of long-term anomalies (>500 days), however, might be difficult and are rarely proposed because they need continuous recording during several years for reliable background considerations. Moreover, in areas with high-magnitude earthquakes, more than one earthquake might be proposed to account for a single anomaly. For example, no information about Žt is supplied for the intermediate-term anomalies of 970 and 1370 days (Table 1). Both are proposed by Hauksson (1981) concerning the Tangshan earthquake (1976, M D 7.8), but it has been suggested elsewhere (King, 1989) that these

Fig. 9. Plot of relative amplitudes (A) (log scale), (B) time lag (time between the onset of the anomaly and the related earthquake, in days) and duration (C) (in days) of anomalies listed in Table 1 as a function of magnitudes. A general increase of maximum time lag and duration is seen with increasing magnitude.

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anomalies might be related to both the Haicheng (1975, M D 7.3) and Tangshan earthquake, owing to their proximity in time (1.5 years) and space (350 km). However, up to 500 days, the maximum duration of anomalies seem to increase with magnitudes. This might be, as proposed by King (1989), of some use for predicting earthquake magnitudes. Fig. 9A shows that amplitudes of anomalies are widely distributed and are not correlated with magnitudes. As noted by Hauksson (1981) and King (1986), this pattern suggests that amplitudes of variations are more likely controlled by local characteristics of soil or spring systems.

7.3. Effects of epicentral distances (D) on duration (d), precursory time (Žt) and amplitudes (Ža) In Fig. 10, data have been displayed according to magnitude ranges (0–3, 3–6, 6–9) as a function of epicentral distances. If we exclude the single point (amplitude Ža D 10,000, epicentral distance D D 490 km), one can see that relative amplitudes do not vary significantly with epicentral distances, unlike the evaluation suggested by Hauksson. On the contrary, maximum durations of long-term anomalies clearly increase both with magnitude range and epicentral distances (Fig. 10B). They are about 35, 400 and 1300 days for quakes of magnitudes 0–3, 3–

Fig. 10. Plot of relative amplitudes (log scale), time lag (time between the onset of the anomaly and the related earthquake, in days) and duration (in days) of anomalies listed in Table 1 as a function of epicentral distances for selected magnitudes. Dots, squares and lozenges display earthquakes with magnitudes 0–3, 3–6 and 6–9, respectively. As in Fig. 9, a general increase of maximum time lag and duration is seen with increasing epicentral distance.

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6 and 6–9, respectively. Precursory time (Fig. 10C) also seems to increase with distance and magnitude. These data support Hauksson’s primary conclusions about radon anomalies, suggesting that precursory time interval and duration scale with both magnitudes and epicentral distances. These features might be related to the preseismic deformation which increases (in volume as well as in radius) when the magnitude increases. Further considerations may appear as doubtful because of the heterogeneity of the data. The setting up of networks of pluriparametric stations distributed over selected sites seems necessary to fully investigate the role of focal depths, focal mechanisms, local hydraulics, and the relationships between the main parameters.

8. Discussion Some striking evidence can be outlined from literature. The first one is the coincidence of detected gas anomalies with active fault systems (King, 1986, 1989; King et al., 1993). The second one is their remoteness to relevant earthquakes. The third one is that calculated distances of anomalies are, at any level of magnitude, much greater than the estimated source dimensions of earthquakes. The fourth one is that tidal strain can produce significant periodic variations of spring gas compositions (Sugisaki, 1981). This latter observation is probably one of the most important observations for mechanism considerations and it demonstrates that processes of gas transfer in hydrological systems within the upper crust are affected by strains much smaller (less than 10 7 for earth tides) than crustal strains which cause earthquakes. The involvement of the stress=strain field in the generation of geochemical anomalies was first proposed by King (1978). This author, owing to radon properties in soils, suggested that strain-induced vertical fluid flows were the source of soil radon anomalies at the San Andreas fault. Since long-distance transport of radon from preparation zones of earthquakes is not possible for short-term events — owing both to the common fluid velocities within the crust and the short half-life of 222 Rn — farfield effects relevant to the preparation mechanisms of earthquakes have to be admitted. This statement

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concerning geochemical signals is not unexpected because other kinds of anomalies (electric, magnetic, etc.) are known to occur at similarly great distances (Rikitake, 1976; Dobrovolsky et al., 1989). One can assume that preseismic effects from elastic strain fields are not confined to the fault plane of an impending earthquake. King (1986) suggested that small strains may generate anomalies because they “could be greatly amplified at pre-existing faults and fractures, where pre-existing stresses may be already near the critical levels” and where pore fluids were abundant. According to this model, local instabilities may generate the anomalies as a result of distant stress centres, in accord with Bernard (1992) who assumed that numerous specific instabilities within the crust have a low failure level, possibly down to the tidal stress. Increases of the pore pressure or decrease of the rock matrix pressure are thought to result from elastic strains that reach the tidal strain values at distances much larger than the length of rupture (Bernard, 1992). Such an effect is probably amplified by the increase of effective permeability of enlarged fault zones as the effect of intersections of faults with minor fractures acting as channels concentrating flow. 8.1. Geophysical evidences of local fluid flows Growing evidence in the field of electric, magnetic and geochemical anomalies of earthquakes tend to indicate local crustal fluid circulations operating in the few upper kilometers of the crust to be the main factor of anomalies in remote and selected areas. Many works have outlined the involvement of fluids within the seismic cycle. Huge quantities of water are known to be produced by reactions of dehydration and therefore trapped in sequences of sediments and the role of pore fluids in reducing the strength of rocks has been early evidenced (Fyfe et al., 1978). Dilatation of the focal zone of a quake generates intermittent flow of hydrothermal fluids in and around the fault zone (‘pumping effect’, Sibson et al., 1975; Fyfe et al., 1978). Simple calculation shows that a moderate earthquake of M D 6, with a typical rupture length of L D 10 km, if we assume a dilatant volume of L=2 and a dilatant strain dV=V of 10 5 , generates a flow of 5 ð 106 m3 of water. This is confirmed by tomographic studies which out-

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line low velocities and a high Poisson ratio due to overpressured, fluid-filled, fractured rocks close to seismogenic layers (Zhao et al., 1996). Crustal fluid instabilities are known to occur mainly in tectonically active regions and normal and thrust faulting are believed to generate fluctuations of reservoir depths, pore pressures and trigger subsequent fluid flows (Bernard, 1992). Strain-induced permeability variations have been experimentally recorded. Under loading, compaction and then microcracking occur, with a subsequent decrease followed by an increase of permeability (Jouniaux and Pozzi, 1995). Evidence of flows occurring in the vicinity of the faults is abundant (i.e. Jouniaux and Pozzi, 1995) as the result of the dilatancy phenomenon, generating volume increase of rocks due to opening up of cracks in their interior. Source dilatancy, however, is assumed by Dobrovolsky et al. (1989) to be noticeable only in the immediate vicinity of the source region, at epicentral distances close to the source dimension. Sibson (1990), however, suggested the existence of hydrofracture dilatancy at low stress levels principally in the vicinity of normal faults, this phenomenon occurring during the fault loading cycle. Bernard (1992) assumes, to account for precursory electrokinetic effects, that aseismic strain waves may pass by and trigger a fluid instability before triggering the earthquake. Assuming that no instability occurs at strains with thresholds lower than tidal strains, he suggested that precursory deformation might be large enough for triggering numerous small-scale fluid flows. 8.2. Spatial inhomogeneities in anomaly distribution A classic feature of gas anomalies is that they are often observed at some sites and not at many other sites which appear to be similarly situated, or at a comparable epicentral distance. It has been suggested that zones of crustal weakness act as natural amplifiers (Healy and Urban, 1985). Some authors have investigated the sign of variation of anomalies. Fleischer and Magro-Campero (1985) suggested that it is much more dependent on local circumstances (subsurface plumbing) than on large-scale effects of strain field. This is not unlikely because the sign of the strain change in the vicinity of a fault can be independent of the regional strain field (Muir-Wood

and King, 1993). The geochemical response of a spring or a soil in a fault may therefore be not typical of the region. However, focal mechanisms have been suggested to partly control physical and chemical changes. Hoang-Trong and Yin (1995) calculated that, for a single event, variations of the water level in wells could be either positive or negative, depending on their location with respect to the radiation pattern of the earthquake. This is in agreement with MuirWood and King (1993) who calculated that, during interseismic periods, outflows are expected in a compressional regime, whereas inflows are expected in a tensile extensional regime. Such developments need, however, more data. Other reasons for the spatial heterogeneity of signals lie in the strain memory. From experiments it has been suggested that rocks retain a stress history during a certain period (Wakita et al., 1988), generating subsequent heterogeneities in magnitudes of anomalies as a function of various pre-existing stress levels. King (1986) invoked such hysteresis to account for the high potential of anomalies of faults and intersections of faults, where pre-existing stress levels may already be near the critical level for anomalies.

9. Conclusions Wakita et al. (1988) and King (1989) have demonstrated that chemical precursory signals are detectable especially in faults and at intersections of faults. Large-distance anomalies make necessary the consideration of fluid-driven phenomena acting at great distances from the source region. Assuming that the distribution of anomalies is strongly controlled by the broad-scale strain–stress field, but also by fault distribution and pre-existing local stress conditions (King, 1986), one can infer that sites for monitoring stations have to be selected carefully. Because of the very high variability of gas concentrations at the surface, soil and=or spring gas prospection appears necessary in order to select potential optimum sites for surveillance (Pinault and Baubron, 1996). Assuming that radon is essentially an indicator of local flow variability, multi-elemental monitoring (He, CO2 , CH4 , H2 , etc.) appears much more appropriate to identify complex phenomena occurring within the crust. Severe perturbations due to external pa-

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rameters demonstrate that only corrected time-series may supply reliable data for precursory identification. Due to the complex relationship between local conditions and the regional distribution of the strain field, it seems reasonable to suggest that a network of stations will be much more useful for identifying regional changes of strain fields than a single station. Various phenomena have been proposed to account for the observed variations. Expulsion of fluids from various depths, mixing between aquifers, changing of hydraulic heads of aquifers, increasing chemical exchanges of ions and gases between rock matrix and ground water, have been suggested to occur as the result of strain change effects (Thomas, 1988). Recent works on dissolved ions seem to favour the limited mixing between aquifers (Tsunogai and Wakita, 1995; Toutain et al., 1997). It is possible to postulate that one or more of these phenomena may act to generate the final anomaly. Moreover, one can suggest that even if the driving force is a unique one (strain field changes), mechanisms leading to the anomaly may be different depending on epicentral distance, depth and nature of gas. For a better understanding of the phenomena involved in such processes, we suggest that monitoring campaigns do lead to the simultaneous recording of various gases (He, Rn, CO2 , CH4 ) in spring and of meteorological parameters, together with multiple continuous measurements of radon in selected points in soils, where gases are driven out by advection=convection. Unambiguous identification of precursors need both the long-term working of this network for baseline drawing and the statistical treatment of signal for removing of external effects. Finally, it seems reasonable to promote the simultaneous monitoring of various physical and chemical parameters that are probably changing with stress, such as water chemistry, level and temperature, tilt, VP =VS ratio, low-level seismicity and electrical conductivity.

Acknowledgements Authors express thanks to A. Rigo and A. Souriau (Observatoire Midi-Pyre´ ne´es) for helpful discussions about seismotectonic processes. We also thank C.Y. King and G.M. Reimer for their very helpful reviews, corrections and suggestions.

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