Continuous monitoring of CO2 soil di¡use degassing atPhlegraean Fields (Italy):

in£uence of environmental and volcanic parameters

D. Granieri �, G. Chiodini, W. Marzocchi, R. AvinoINGV-Osservatorio Vesuviano, Via Diocleziano 328, 80124 Napoli, Italy

Received 3 September 2002; received in revised form 16 April 2003; accepted 17 April 2003

Abstract

Carbon dioxide soil flux was continuously measured during 4 years (1998^2002) inside the crater of Solfatara byusing the ‘time 0, depth 0’ accumulation chamber method. The CO2 soil flux (BCO2 ) is strongly influenced by externalfactors, such as the barometric pressure, the air and soil temperature and humidity, the wind speed, the amount ofrain, and so on. Here, we apply a two-step filtering technique to remove the contribution of these external factorsfrom the raw data and to highlight variations in gas flow from depth. In the first step we apply multiple regressionand a best-subset search procedure to determine the minimal number of parameters to insert in the regression model.In the second step we apply time filtering on the residuals of the previous analysis through an ARIMA (integratedautoregressive moving average) model which allows us to quantify long-term trends and short-term periodicities. Thestatistical analysis showed that (1) the highest frequency fluctuations are due to variations of environmentalparameters (particularly soil humidity and air temperature) and (2) the long-term trend of the filtered data iscorrelated with the ground deformation. This correlation is enhanced by back-shifting the CO2 flux signal by3 months. These observations, along with the likelihood that the ground deformation at Phlegraean Fields iscontrolled by fluid pressure within the hydrothermal system, indicate that the long-term trend in soil CO2 flux isrelated to fluid pressure changes at depth. The delay between the soil CO2 flux and the ground deformation is mostprobably due to the inertia of the gas moving in the subsoil.= 2003 Elsevier Science B.V. All rights reserved.

Keywords: carbon dioxide soil £ux; Solfatara; accumulation chamber method; monitoring

1. Introduction

A useful tool in the surveillance of an activevolcanic area is continuous monitoring of geo-

chemical parameters. Changes in degassing ofCO2 or trace gases for which CO2 acts as a carrier(i.e. Rn and He) have been observed before and/or during volcanic unrest in many volcanoes(i.e. Etna, Stromboli, Vulcano, Phlegraean Fields[1^8]).

Previous studies have been focussed on degas-sing fumarolic features or volcanic plumes [1,9,10]. Nevertheless important amounts of CO2,

0012-821X / 03 / $ ^ see front matter = 2003 Elsevier Science B.V. All rights reserved.doi:10.1016/S0012-821X(03)00232-2

* Corresponding author. Tel. : +39-081-6108449;Fax: +39-081-6108466.E-mail address: granieri@ov.ingv.it (D. Granieri).

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even higher than the gas discharged by activefumarolic systems, are often released through dif-fuse soil degassing [5,11,12]. In some cases, thedi¡use soil emissions of CO2 are comparable tothe rates of gas emitted by plumes at eruptingvolcanoes [1,13].

This paper describes the continuous monitoringof di¡use CO2 degassing from the Solfatara crater(Phlegraean Fields, Italy). At Solfatara CO2 de-gassing at anomalously high rates occurs over anarea of V0.5 km2 (Fig. 1). This area, namedthe di¡use degassing structure (DDS), releasesV1500 t day31 of CO2, an amount even higherof that released by many erupting volcanoes [13].Assuming that the original £uids that feed the soil

di¡use degassing have the same composition ofthe high temperature fumaroles of Solfatara (i.e.160‡C, H2O/CO2V2.2 by weight), an amount ofV3300 t day31 of steam condenses during theprocess [13] releasing thermal energy at V0.81013 J day31.

In the present period of quiescence, this amountrepresents the main energy release of the Phle-graean Fields volcanic system. It is several timeshigher than the energy released through conduc-tion over the entire caldera, the elastic energy as-sociated with seismic events, and the energy dis-sipated by ground deformation [13].

The monitoring of the di¡use degassing at Sol-fatara is done through a combination of an auto-matic continuously operating station at a selectedsite and periodic measurements of £ux over anarray of sites.

The continuous monitoring station measuressoil CO2 £ux and various environmental parame-ters which can potentially a¡ect the soil gas £ux.

Measurements of soil CO2 £ux and soil temper-ature (10 cm depth) at 30 ¢xed stations homoge-neously distributed in the £oor of the Solfataracrater are made one to two times per month(Fig. 2). In addition, more detailed measurements(200 points regularly distributed in a 20 m2 grid)are repeated several times per year.

Here, we report the CO2 £ux data collectedfrom continuous monitoring at the Solfatara cra-ter during the period 1998^2002. In order to sep-arate the part of the signal linked to variations inthe deep source of the CO2 £ux, we must removethe in£uence of environmental external factorsfrom the raw data. To accomplish this goal, weinvestigate the relations between external factors(i.e. rain, barometric pressure, soil and air temper-ature and humidity, wind speed) and the CO2

£ux.Moreover, on the base of the results obtained

during the 4 years of continuous and periodicmonitoring, we delineate the representativenessof the soil BCO2 measured in the continuous mon-itoring site (few dm2) to the degassing over theentire Solfatara DDS (107 dm2).

In Section 4 we will consider also the results ofanother automatic station (FLXOV4) which is in-stalled inside the crater of Mt. Vesuvio.

Fig. 1. Map of log soil BCO2 of the Solfatara DDS. The sur-vey of the soil BCO2 was carried out from December 16 to18, 1998, and consists of 406 measurements [13].

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2. Soil CO2 automatic station (SCAS)

The SCAS acquires, at selectable time intervals,values of CO2 £ux (BCO2 ) and various parametersthat can potentially in£uence the CO2 £ux, i.e.barometric pressure, air and soil temperature,air and soil humidity, wind speed and rainfall.The BCO2 is measured by the accumulation cham-ber method [14,15,16]. The accuracy of individualmeasurements of gas £ux is better than 10% forCO2 £uxes over a range of 100^10 000 g m32

day31 [12,16]. The use of the accumulation cham-ber method with the SCAS allows a direct mea-surement of the CO2 transferred from the groundto the atmosphere, independent of the transportregime in the system (di¡usive and/or e¡usive)and the physical properties of the soil. Each mea-surement is made over a time ranging from a fewseconds to 1^2 min. The SCAS is equipped withspeci¢c sensors for the measurement of environ-mental parameters during the same time intervalas the CO2 £ux measurement. Solar panels andbatteries provide the required electric power.

The SCAS prototype was jointly developed byIGGI (Istituto di Geocronologia e GeochimicaIsotopica) of Pisa, University of Perugia andWest System srl, and tested at Santorini (Greece)in the framework of the European project ‘San-torini Volcano Laboratory’ in 1995. Since 1998,25 SCAS units have been installed in the follow-ing volcanic areas: Masaya Volcano (Nicaragua);Poa's Volcano (Costa Rica); La Palma (CanaryIslands, Spain); San Salvador, San Miguel, SanVincente and Santa Ana volcanoes (El Salvador);Usu Volcano (Japan); Mammoth Mountain (Cal-ifornia, USA); Etna (Italy) ; Stromboli (Italy).The Osservatorio Vesuviano, Neapolitan Depart-ment of Istituto Nazionale di Geo¢sica e Vulcan-ologia (Italy), has installed one SCAS at the Sol-fatara crater (FLXOV1) and one SCAS atVesuvio (FLXOV4).

The data measured from the SCAS installationare summarized in Table 1. Both £ux stationswere installed in November 1998, and measure-ments with portable equipment were made to se-lect suitable sites. Since that time, the Solfatarastation has been collecting data every 2 h whileVesuvio station every 4 h.

3. Filtering the CO2 £ux data

The ¢ltering of CO2 £ux data is applied only tothe data of Solfatara where an almost continuoussampling in time, from November 1998 to June2002, is available. In the case of Vesuvio, a com-plete and detailed analysis of the signals was notpossible because of data gaps due to battery fail-ures from absence of solar radiation during wintertime, landslides which occasionally damaged thestation, and short periods of failure of the auto-matic accumulation chamber device.

The SCAS FLXOV1 is located inside the DDSof Solfatara, in a zone where the degassed CO2 isderived from a hydrothermal system [17]. Thedeep origin of the gas is consistent with the highmeasured £ux values (300^5000 g m32 day31 inTable 1), orders of magnitude higher than thevalues of the local biological background (30 gm32 day31 [13]). Variations in CO2 £ux couldbe caused by variations in both the up£ow of

Fig. 2. The crater of Solfatara and the location of the 30-point network. The position of FLXOV1 SCAS coincideswith a point of the network.

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hydrothermal £uids, called the endogenous signalin the following, and in environmental parame-ters.

In order to better determine the e¡ects of var-iations in the hydrothermal system on di¡use CO2

£ux, we used multivariate regression analysis(MRA) to delineate the relations between £uxand external factors and then used these relationsto ¢lter out the e¡ects of these factors on themeasured £ux history. Before discussing the de-tails of the analysis, some cautionary remarksare warranted. In particular, when we do regres-sion calculations on unplanned data (that is, dataarising from continuous operations and not froma designed experiment), some potentially errone-ous results can arise. For example, a false e¡ect (abias) on a visible variable may be caused by anunmeasured latent variable. Another undesired ef-fect arises when a correlated variable undergoes avariation whose range is small compared to itsaverage value, leading to an apparent lack of sig-

ni¢cance. A third problem is that the use of un-planned data often causes large correlations be-tween predictors; this makes it impossible toattribute a causal e¡ect to one speci¢c predictor.This technical problem can be avoided by usingorthogonal dummy variables obtained, for exam-ple, through the PCA (principal component anal-ysis) procedure [18,19]. However, because thesedummy variables have no physical meaning, wechose not to use this technique. From a qualita-tive graphical analysis we built a linear model inwhich the dependent variable is the natural loga-rithm of the CO2 £ux, and the independent vari-ables are the external factors that have been mea-sured at the station. In order to verify the qualityof the model, the dataset was divided into threesubsets, one learning dataset (LD) and two con-trol datasets (CDs). LD, which has been used tobuild the model, represents the data from the cen-tral period (November 1999^November 2000,1-year interval), while CDs are the data used to

Table 1Summary of results from two sites

FLXOV1 FLXOV4November 1998^June 2002 November 1998^March 2002

CO2 £ux (g m32 day31) Range 315^4 724 34^19 952Mean 746 2 479No. of data 15 655 3 849

Air relative humidity (%) Range 17.3^98.2Mean 78.5No. of data 15 655

Air temperature (‡C) Range 32^38.2 38.3^17.8Mean 16.3 5.7No. of data 15 655 4 423

Bar pressure (mbar) Range 979^1 023 879^919Mean 1 004 905No. of data 15 655 4 475

Soil relative humidity (a.u.) Range 37^86.2Mean 45.5No. of data 15 655

Soil temperature (‡C) Range 37.6^68.6 51.7^91.5Mean 52 78.3No. of data 14 754 4 110

Wind speed (m s31) Range 0^9.56Mean 0.81No. of data 15 655

Rain (mm) Range 0^36.6 0^58.6Mean 0.17 0.386No. of data 10 265 3 111

a.u. = arbitrary unit proportional to soil water content.

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check the model (CD #1, November 1998^No-vember 1999, the year preceding LD; and CD#2, November 2000^June 2002, 19 months fol-lowing LD).

The ¢rst important step in the regression anal-ysis consists of selecting the relevant parametersto explain the variability of the CO2 £ux in LD.Here, we select the most relevant variables by us-ing the procedure called the ‘best-subset search’,described by Garside [20]. The procedure ¢rst re-quires the ¢tting of every possible regressionequation which involves any combination of inde-pendent variables, and then selecting the casewhich is the best respect one criterion. The crite-rion adopted here is based on the R2 coe⁄cient.In other words, we report the case with the high-est R2 coe⁄cient obtained by using a single inde-pendent variable, two independent variables, threeindependent variables, and so on (Table 2). The‘best’ regression is the one for which, adding morevariables, further gain in the R2 coe⁄cient is onlyminor.

Table 2 shows that the ‘best’ regression is thesecond one, with Hs (humidity of soil) and Ta

(temperature of air) as independent variables.The linear ¢ltering model obtained for LD is:

lnðBCO2Þ ¼ ð5:78 � 0:03Þ3ð1:36 � 0:05ÞU1032Ta

þð2:07 � 0:05ÞU1032Hs

The quality of the model is further veri¢ed byusing this equation on the other two independentdatasets (CD #1 and CD #2). For each datasetwe calculate the Pearson correlation coe⁄cient rthat can be used as an indicator of the degree ofsimilarity between the observed and predictedtime series. The high values of the correlation co-e⁄cient r obtained for LD (0.774) and CD #1(0.825) are a clear indication of the applicabilityof the model (Fig. 3a). Actually, the r value forCD #2 dataset (0.402), is signi¢cantly lower.However, by reducing the temporal length of thewhole CD #2 (19 months) to the same size as LDand CD #1 (1 year, following LD) the value of ris 0.802, i.e. quite comparable to the values forLD and CD #1. In other words, the correlationcoe⁄cient r is lowered by the inclusion of theadditional 7 months of CD #2. This worsening

might be due to either technical or physical fac-tors. By reducing the length of the CD #2 inter-val, we may have eliminated a bias introduced bya di¡erent performance of the model as a functionof the seasons. We may also have eliminated thepossible in£uence of physical changes in the soilor in the hydrothermal system that may havechanged the response of the site to the externalparameters. This is an intrinsic factor that mustbe considered in modelling non-stationary pro-cesses. In such cases, the extrapolation of anymodel tends unavoidably to worsen, movingaway from the time interval used for the learningphase.

The time evolution of the residuals of MRA¢ltering is reported in Fig. 3b. The time depen-dence in the residuals of the regression can at leastpartially be attributed to an endogenous signal.However, some changes in non-measured varia-bles might explain the variation of BCO2 , or theremight be some non-linear e¡ects in operationamong the external variables.

The time dependence of the residuals of theregression (Zt) can be expressed as:

Zt ¼ Xt þ St þ O t

where Xt is a low-order ARIMA (integrated au-toregressive moving average; see [21]) processwhich can be used to characterize the long-termtrend of the signal, St is a periodic componentwhich can characterize signals with higher fre-quencies, and Ot is a random noise. The compo-nent Xt can be estimated by ¢tting an ARIMA(1, 1, 1) model to the £ux data:

BXt ¼ a þ a1Xt31 þ R t3b1R t31

where a is a calibration constant, a1 is the param-

Table 2The best-subset search process for FLXOV1 data

No. ofvariables

Variables in the equation Best R2

(%)

1 ln(BCO2 ) = f(Hs) 57.82 ln(BCO2 ) = f(Hs,Ta) 67.93 ln(BCO2 ) = f(Hs,Ta,Vw) 68.44 ln(BCO2 ) = f(Hs,Ta,Vw,R) 68.85 ln(BCO2 ) = f(Hs,Ta,Vw,R,Pa) 69.06 ln(BCO2 ) = f(Hs,Ta,Vw,R,Pa,Ha) 69.0

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eter of the autoregressive process, b1 is the param-eter of the moving average process, Rt is the re-sidual process, and B is the backward shift oper-ator de¢ned as BXt =Xt3Xt31 [21,22]. Here, wedo not ¢t a general ARIMA (k, p, l) process, butwe apply only p= 1, and k, l9 1. This choice usu-ally guarantees a satisfactory ¢t of the non-peri-odic and low-frequency (long-term) time depen-dence of the time series. The parameters of themodel a, a1, b1 and the variance of the residualprocess Rt are estimated through a least-squaretechnique [21,22]. The correct values of k and l(0 or 1) are selected through the AIC criterion(Akaike information criterion; [23]). By analyzingthe residuals relative to LD, we obtain:

BXt ¼ ð0:44 � 0:03ÞXt31 þ R t3ð0:77 � 0:02ÞR t31

In the above equation, Rt represents the timeseries of the ‘new’ residuals further ¢ltered bythe non-periodic time dependence. In otherwords, while the multivariate regression, de-scribed above, removes the e¡ects of the external

parameters from the CO2 £ux variations, theARIMA ¢ltering removes (if it exists) the long-term time dependence. Fig. 4 reports the residualsof the ARIMA ¢ltering for LD and CDs of theFLXOV1 station. In the case without a periodiccomponent (St = 0), the results of the ¢ltering,namely the Rt process, should be white, or at leastuncorrelated, noise. Instead, the spectral analysis[22,24] on these residuals shows a peak at 24 hand some related harmonics (Fig. 5). These cyclesrepresent the main feature of the St component.

We argue this residual periodicity is still due toexternal processes, rather than endogenous pro-cesses which would likely be characterized by lon-ger periods. The presence of an exact 24-h cyclerules out a predominant e¡ect of the tides that actat di¡erent periods; the strongest luni^solar e¡ect,for instance, is at 12.42 h. We suggest this peri-odicity could be due to one or more external fac-tors that we did not consider, or, more likely, dueto the fact that the link between the CO2 £ux andthe air temperature might be non-linear; the air

Fig. 3. (a) Observed (black line) and predicted (gray line) log soil BCO2 for the data series of Solfatara. Dashed vertical linesmark the intervals used to construct the linear model (LD) and to check the model (CD #1 and CD #2). (b) Residuals of theMRA for the same data series.

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temperature, in fact, has an exact 24-h periodicity.It is worthwhile to note that the same 24-h peri-odicity was also found in the seismic activity ofthe Phlegraean Fields (e.g. [25]).

Although some e¡ects of external factors werenot removed by the ¢ltering, the ¢ltering processwas successful because of the great di¡erence be-tween the period observed in the residuals and theexpected characteristic transient of the internalprocesses. We argue, therefore, that endogenousprocesses are responsible for the long-term trendand that the computed variable Xt is the bestrepresentation of the endogenous ‘signal’ con-tained on the original BCO2 data. The ¢ltered var-iation in the average daily Xt values (Fig. 6)shows a general decreasing trend passing fromvalues of +0.8 in 1998 to 30.6 at the end of thesampling period (June 2002). A period of generaldecline of the signal was evident in the periodNovember 1998^February 2000, followed by,from March 2000 to March 2002, a period inwhich the signal remained almost constant, oscil-lating around a value of 0 and showing two pos-itive peaks in October 2000^April 2001 and Octo-ber 2001^March 2002. During the last 3 monthsof 2002 a new phase of decrease in the Xt valueswas observed.

4. Discussion and conclusions

The variance of BCO2 data at FLXOV1 during1998^2002 is linked to environmental parametersand deep sources. Regarding the environmentalparameters, the multivariate regression analysisof raw data showed a main control from the hu-

midity of the soil, i.e. rain, and from the air tem-perature. These two parameters alone can explainmost of the observed variance. However, the anal-ysis of the residuals, performed with an ARIMAprocess, showed further, minor, correlation withenvironmental parameters characterized by varia-tions of 24-h frequency, which could be hypothe-sized to be due either to wind or to air temper-ature. This result applied exclusively to theFLXOV1 site and it should not be considered toapply everywhere. Di¡use soil degassing is in facta¡ected by a number of environmental factors,i.e. meteorological parameters, soil properties (po-rosity, hydraulic conductivity, soil water condi-tions, soil temperature) and topographic e¡ects.

Localized e¡ects on BCO2 at FLXOV1 are indi-cated by comparing the results obtained at Solfa-tara FLXOV1 with the data of other two SCAS:one located at Vesuvio (FLXOV4) and the other

Fig. 4. Results of the ARIMA ¢ltering for LD and CDs.

Fig. 5. Spectral analysis of the ARIMA residuals showing apeak at 1 cycle day31 (24 h). The peaks at 2,3,4 cycles day31

represent the harmonics of the diurnal signal.

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at Mammoth Mt., California. At all three sites theCO2 £ux originates from deep sources [26]. De-tails of the SCAS installed at Mammoth are re-ported in [27] while the main characteristics of theFLXOV4 station are shown in Table 1.

At the Solfatara FLXOV1 site, we found thatthe main controlling factor is the humidity of thesoil which alone explains about 58% of the £uxvariance. A graphical example of the strong cor-relation between soil BCO2 , soil humidity and rainepisodes is seen in the £ux data for the periodMay^August 1999 (Fig. 7). Each of the threerain episodes was accompanied by concurrent in-crements of soil humidity and BCO2 . This positivecorrelation could appear surprising because thein¢ltrating waters should decrease the e¡ective

porosity and possibly dissolve some of the £owinggas, leading to a decrease in the £ux. Instead,there is a topographic e¡ect of rainfall on gas£ux related to the fact that FLXOV1 is situatedon ground that is higher than the surroundingdegassing area. Rainfall preferentially drains intothe low-lying areas and gas £ow is diverted to thehigh ground. In contrast, a more normal inversecorrelation between rain and £ux was observed atthe Vesuvio station FLXOV4. The chronogram(time history) of Fig. 8, relative in the autumn2000, clearly shows that the rain events caused asharp decrease in the soil BCO2 .

During the dry summer months, another di¡er-ence was observed between the £ux stations atSolfatara and Vesuvio in terms of the relation

Fig. 6. General trend of the soil BCO2 after MRA and ARIMA ¢ltering. Xt is the best representation of the endogenous ‘signal’contained in the original BCO2 data.

Fig. 7. Soil relative humidity, soil BCO2 and rainfall chronograms at the FLXOV1 site from May to August, 1999. The positiveanomalies of the soil humidity, due to rainfall episodes, produce a growth in the soil BCO2 .

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between £ux and barometric pressure. The £uxdata for FLXOV4 (Fig. 9) show a signi¢cant in-verse correlation, whereas the data for FLXOV1show little in the way of variations with baromet-ric pressure. An inverse correlation between £uxand barometric pressure has been reported for aSCAS at Mammoth Mountain (California). Rogieet al. [27] attribute this relation to the rising airpressure that retards viscous gas £ux (pressuregradient driven) while falling atmospheric pres-sure enhances viscous gas £ux from the soil ex-plaining the inverse correlation. The same inter-pretation can be valid for Vesuvio, while theabsence of a clear correlation between barometricpressure and £ux at the Solfatara FLXOV1 site ismost probably due to the fact that the £ux ismainly di¡usive (gradient concentration driven)instead of viscous.

The regression analysis and the subsequentARIMA process on FLXOV1 data permit us tohighlight the part of the signal most probablylinked to the variation of the deep source. In or-der to interpret this link we consider the seismicactivity and the ground deformation which areregularly monitored at Phlegraean Fields in theframework of volcanic surveillance. A subsidenceperiod characterized the area of Pozzuoli in the¢rst part of the last century (V0.8 m from 1905to 1968 [28]). The subsidence was interrupted bytwo main periods of uplift : 1969^1972, when amaximum vertical displacement of 174 cm wasmeasured at the benchmark 25 sited near the

town of Pozzuoli, and 1982^1984, when the max-imum vertical displacement was 179 cm at thesame benchmark 25 ([29] ; Fig. 10). Since the be-ginning of 1985, the area has been a¡ected by ageneral subsidence (Fig. 10) which has been inter-rupted by three minor uplifting phases in 1989,1995 and 2000. Recent geochemical and geophys-ical studies suggest that the ground deformationat Phlegraean Fields is controlled by £uid pres-sure within the hydrothermal system [13,30,31]. Inagreement with this interpretation, both the gen-eral subsidence since 1985 and the general de-crease of the soil CO2 £ux at site FLXOV1 couldbe related to £uid pressure declines at depth. Incontrast, a £uid pressure increase at depth could

Fig. 8. Rain and soil BCO2 at the FLXOV4 site in September^November 2000. The rainfall episodes induce a decrease in the soilBCO2 , in contrast to the results found at Solfatara.

Fig. 9. Barometric pressure and soil BCO2 at the FLXOV4site in dry periods. Note their inverse correlation.

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have caused both the minor uplift episode thatoccurred in 2000 (Fig. 10, inset), and the tempo-rary rise in the CO2 £ux decrease observed atFLXOV1 during February 2000^March 2002(Fig. 6). The correlation between the two signalsincreases if we back-shift the CO2 £ux signal by3 months (Fig. 11), which could suggest a delaydue to the inertia of the gas di¡usion in the sub-soil. A better correlation between the soil CO2

£ux and ground deformation is obtained consid-ering the monthly mean of di¡use CO2 £ux mea-

sured in a network of 30 selected measuringpoints (Fig. 12). In this case the correlation be-tween the two independent parameters is evident.The period of uplift in the year 2000 was accom-panied by a doubling of the total out£ow of CO2,which from 2000 g m32 day31 at the end of 1999passed to 4000 g m32 day31 in the summer^au-tumn 2000.

During the period of continuous £ux measure-ments at Solfatara no correlation was observedbetween seismic activity and changes in gas £ux,

Fig. 10. Ground deformations at Phlegraean Fields based on the periodical measurements at the benchmark 25 located at thePozzuoli port. Two main uplift episodes in 1969^1972 and 1982^1984 and three minor uplifting phases in 1989, in 1995 and in2000 are evident. Inset: soil deformation during the activity of FLXOV1 SCAS.

Fig. 11. Xt and soil deformation chronograms at the Solfatara site. The best correlation is obtained by back-shifting the Xt seriesof 3 months.

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although one cluster of ML 9 2.2 events did occurin the area in July^August 2000 [32]. At Vesuvio,many periods of seismic events occurred between1999 and 2002, with hypocenters clustered withinthe volcanic conduit. However, there is again nocorrelation between the timing of these events andthe timing of periods of anomalous gas £ux atFLXOV4 (Fig. 13). The chronogram shows in-stead two very marked anomalies in CO2 £uxesin periods of low seismic activity. The ¢rst periodoccurred in May 2001, when the £uxes doubled infew days, and the second in October 2001 whenthe £uxes increased by a factor of 10, simulatingan anomalous degassing of the volcano. The ab-

sence of any other anomaly in the monitored pa-rameters (seismicity, deformation, fumarolic gascomposition) and the results of a ¢eld survey sug-gested that the anomalies could be caused bylandslides which a¡ected the degassing structureof Vesuvio, possibly changing the up£ow patternof the gases.

The comparison between the signal £ux histo-ries at FLXOV1, the results of the periodic gas£ux campaigns, the ground deformation at Phle-graean Fields, and the ‘false’ anomalies at Vesu-vio highlight some limitations of the monitoringof soil CO2 £ux performed with the SCAS. Wethink that the main limitation is the small dimen-

Fig. 12. Monthly average of the soil BCO2 at 30 selected points located on the £oor of the Solfatara crater together with the soildeformation. From January 1998 to June 2002, 110 surveys of di¡use soil CO2 £ux have been carried out on a network of 30measurement points. The soil BCO2 values range from 150 g m32 day31 to 22 000 g m32 day31, with an average of 4840 g m32

day31.

Fig. 13. July 1, 1999, to March 31, 2002, soil BCO2 and seismic energy at Vesuvio. The marked anomalies of the soil BCO2 inJune 2001 and in October 2001 do not coincide with the periods of anomalous seismic activity, but with the episodes of land-slides located inside the crater.

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sion of the monitored area (few dm2) with respectto the size of the DDSs (V0.5 km2 in the case ofSolfatara). In the small monitored sites the £uxvariations can depend on local factors (i.e. a per-manent permeability change caused by alluvialepisodes or landslides in the degassing area)more than on changes in the deep £uid up£ow.

Such super¢cial and localized processes a¡ect ina lesser way the total output of gas from a DDSand the total gas £ow from a large array of peri-odically measured £ux sites.

In conclusion, SCAS FLXOV1 furnished datauseful for a better understanding of the in£uenceof environmental parameters on the CO2 £ux.However, the strong site e¡ects which can changethe £uxes in the small portion of the monitoringpoint can blur the detection of deep variations. Apossible method to improve the monitoring of thedi¡use degassing process is to couple automaticstation data with the execution of periodic mea-surement campaigns.

Acknowledgements

This work was supported by the National Vol-canic Group of Italy (GNV) and by the EuropeanCommunity (Geowarn project). We thank Dr.Mike Sorey for helpful comments and sugges-tions.[SK]

References

[1] P. Allard, J.M. Carbonelle, R. Faivre-Peirret, D. Martin,J.C. Sabroux, P. Zettwoog, Eruptive and di¡usive emis-sions of CO2 from Mt, Etna Nat. 351 (1991) 387^391.

[2] B. Badalamenti, S. Gurrieri, S. Hauser, M. Valenza, SoilCO2 output in the Island of Vulcano during the period1984^1988: surveillance of gas hazard and volcanic activ-ity, S.I.M.P. Carapezza Meml. 43 (1988) 893^899.

[3] B. Badalamenti, S. Gurrieri, S. Hauser, F. Parello, M.Valenza, Change in the soil CO2 output at Vulcano dur-ing the summer 1998, Acta Vulcanol. 1 (1991) 219^221.

[4] B. Badalamenti, S. Gurrieri, P.M. Nuccio, M. Valenza,Gas hazard on Vulcano Island, Nature 350 (1991) 26^27.

[5] J.C. Baubron, P. Allard, J.P. Toutain, Di¡use volcanicemission of carbon dioxide from Vulcano Island, ItalyNat. 344 (1990) 51^53.

[6] M.L. Carapezza, S. Giammanco, S. Gurrieri, S. Hauser,P.M. Nuccio, F. Parello, M. Valenza, Soil gas geochem-istry: CO2. In: F. Barberi, A. Bertagnini, P. Landi (Eds.),Mt. Etna the 1989 eruption, Giardini Editori e Stampa-tori, Pisa, 1990, pp. 62^64.

[7] S. Lombardi, M. DiFilippo, L. Zantederchi, Helium inPhlegraean Fields, Bull. Volcanol. 47 (1984) 259^265.

[8] S. Lombardi, G. Nappi, Helium in soil gas at Lipari andStromboli Volcanoes, Period. Mineral. 55 (1986) 165^176.

[9] S.N. Williams, J.S. Schaefet, L.C. Stephen, M.L. Calv-ache, D. Lopez, Global carbon dioxide emissions to theatmosphere by volcanoes, Geochim. Cosmochim. Acta 56(1992) 1765^1770.

[10] S.L. Brantley, K.W. Koepenick, Measured carbon dioxideemissions from Oloinyo Lengai and skewed distributionof passive volcanic £uxes, Geology 23 (1995) 933^936.

[11] J.C. Baubron, P. Allard, J.C. Sabroux, D. Tedesco, J.P.Toutain, Soil gas emanations as precursory indicators ofvolcanic eruptions, J. Geol. Soc. Lond. 148 (1991) 571^576.

[12] G. Chiodini, F. Frondini, B. Raco, Di¡use emission ofCO2 from the Fossa crater, Vulcano Island, Bull. Volca-nol. 58 (1996) 41^50.

[13] G. Chiodini, C. Cardellini, F. Frondini, D. Granieri, L.Marini, G. Ventura, CO2 degassing and energy release atSolfatara Volcano, Campi Flegrei, Italy, J. Geophys. Res.106 (B8) (2001) 16213^16221.

[14] K.J. Parkinson, An improved method for measuring soilrespiration in the ¢eld, J. Appl. Ecol. 18 (1981) 221^228.

[15] F. Tonani, G. Miele, Methods for measuring £ow of car-bon dioxide through soils in the volcanic setting, Int.Conf. on Active Volcanoes and Risk Mitigation, Napoli,27 August^1 September, 1991.

[16] G. Chiodini, R. Cioni, M. Guidi, L. Marini, B. Raco, SoilCO2 £ux measurements in volcanics and geothermalareas, Appl. Geochem. 13 (1998) 543^552.

[17] R. Cioni, E. Corazza, L. Marini, The gas/steam ratio asindicator of heat transfer at the Solfatara fumaroles, Phle-graean Fields (Italy), Bull. Volcanol. 47 (1984) 295^302.

[18] N. Draper, H. Smith, Applied Regression Analysis, 2ndedn., Wiley, New York 1981.

[19] G.E.P. Box, Use and abuse of regression, Technometrics8 (1966) 625^629.

[20] M.J. Garside, Best subset search, Appl. Stat. 20 (1971)112^115.

[21] G.E.P. Box, G.M. Jenkins, Time Series Analysis: Fore-casting and Control, Holden-Day, Merri¢eld, VA,1976.

[22] M.B. Priestley, Spectral Analysis and Time Series, Vol. 1,Academic, San Diego, CA, 1981.

[23] H. Akaike, A Bayesian analysis of the minimum AICprocedure, Ann. Inst. Stat. Math. 30A (1978) 9^14.

[24] W.A. Fuller, Introduction to Statistical Time Series, Wi-ley, New York, 1976.

[25] W. Marzocchi, G. Vilardo, D.P. Hill, G.P. Ricciardi, C.

EPSL 6666 23-6-03

D. Granieri et al. / Earth and Planetary Science Letters 212 (2003) 167^179178

Ricco, Common features and peculiarities of the seismicactivity at Campi Flegrei, Long Valley, and Vesuvius,Bull. Seismol. Soc. Am. 91 (2001) 191^205.

[26] G. Chiodini, L. Marini, M. Russo, Geochemical evidencefor the existence of high-temperature hydrothermal brinesat Vesuvio volcano, Italy, Geochim. Cosmochim. Acta 6514 (2001) 1^19.

[27] J.D. Rogie, D.M. Kerrick, M.L. Sorey, Dynamics of Car-bon Dioxide emission at Mammoth Mountain, California,Earth Planet. Sci. Lett. 188 (2001) 535^541.

[28] G. Orsi, L. Civetta, C. DelGaudio, S. DeVita, M. DiVito,R. Isaia, S.M. Petrazzuoli, G.P. Ricciardi, C. Ricco,Short-term deformations and seismicity in the resurgentCampi Flegrei caldera (Italy): An example of activeblock-resurgence in a densely populeted area, J. Volcanol.Geotherm. Res. 91 (1999) 415^451.

[29] F. Barberi, G. Corrado, F. Innocenti, G. Luongo, Phle-graean Fields 1982^1984: Brief chronicle of a volcanoemergency in a densely populated area, Bull. Volcanol.47 (1984) 175^185.

[30] M. Bonafede, Hot £uid migration, an e⁄cient source ofground deformation, application to the 1982^1985 crisisat Campi Flegrei, Italy, J. Volcanol. Geotherm. Res. 48(1991) 187^198.

[31] M. Bonafede, M. Mazzanti, Modeling gravity variationsconsistents with ground deformation in the Campi FlegreiCaldera (Italy), J. Volcanol. Geotherm. Res. 81 (1998)137^157.

[32] G. Saccorotti, F. Bianco, M. Castellano, E. DelPezzo,The July^August 2000 seismic swarms at Campi Flegreivolcanic complex, Italy, Geophys. Res. Lett. 28 (2001)2525^2528.

EPSL 6666 23-6-03

D. Granieri et al. / Earth and Planetary Science Letters 212 (2003) 167^179 179