Impact of forest fires on PAH level and distribution in soils

Environmental Research 111 (2011) 193–198

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Impact of forest fires on PAH level and distribution in soils$ Aurore Vergnoux a,b,n, Laure Malleret a, Laurence Asia a, Pierre Doumenq a, Frederic Theraulaz b a b

Universite´ Paul Ce´zanne Aix-Marseille 3. ISM2, UMR 6263, e´quipe AD2EM. FR ECCOREV. Europole de l’Arbois. Bˆ atiment Villemin BP 80. 13545 Aix-en-Provence Cedex 4, France Universite´ de Provence Aix-Marseille 1. Laboratoire Chimie Provence. UMR 6264. FR ECCOREV 3pl. Victor Hugo–Case 29, 13331 Marseille Cedex 3, France

a r t i c l e in fo

abstract

Article history: Received 22 July 2009 Received in revised form 31 December 2009 Accepted 14 January 2010 Available online 10 February 2010

Surface (0–5 cm) and subsurface ( 5 to 15 cm) soils from burned forest areas in South of France were analyzed to determine contents of 14 priority polycyclic aromatic hydrocarbons (PAHs) and their distribution profile. The sampling procedure allowed us to study the effect of the frequency of fire as well as the influence of the time elapsed since the last fire. The contribution of forest fires to the content of PAHs in soils was demonstrated, as well as the decrease of their total level with time. The hypothesis is that a natural remediation takes place a few years after the last fire event. The lowest molecular weight studied PAHs (naphthalene, acenaphtene, fluorene, phenanthrene, anthracene, fluoranthene and pyrene) appear to be the major ones produced by forest fire. Naphtalene levels are remarkably high in burned soils (more than 70 mg kg  1, i.e. more than 20 times higher than in the control soils) and still remain important years after the last fire event. The time elapsed since the last fire appears to be a more influencing factor than the fire frequency. The index defined from the PAH levels shows values reflecting the time elapsed since the last fire. & 2010 Elsevier Inc. All rights reserved.

Keywords: PAHs Forest fire Soil PLE HPLC/PFD PCA

1. Introduction Several thousand billions of squared meter of forest are affected by fires every year, at a global scale (Gonzalez-Perez et al., 2004). Recently, warm climate areas were extensively affected by such events, as for instance in Portugal, Spain, Italy (2005), Australia (2009), Greece (2007), South of France and Corse (2003). Furthermore, North Europa as Scandinavic states are also hit by this problem. Indeed, forest fire damage is mainly due to criminal act and also aggravated in few cases by drought spells. Inflammation and combustion require 3 factors: fuel, oxygen and heat. So, fire intensity depends on several environmental factors which affect the inflammation and combustion processes like amount, nature and moisture of live and dead fuel, air temperature and humidity, wind speed and topography of the site (Certini, 2005). But, when dealing with wildfires, it is not possible to obtain precise information on fire intensity. Independently of fire type and intensity, the combustion process generates huge amounts of carbon dioxide in the

$ Funding sources supporting the work: Financial support was provided by Region PACA, the IRISE project (http://irise.mediasfrance.org/) funded by the European Union, Forest Focus Regulation (No. 2152/2003) and the French National Forest Service (ONF). n Corresponding author at. Universite´ Paul Ce´zanne Aix-Marseille 3. ISM2, UMR 6263, e´quipe AD2EM. FR ECCOREV. Europole de l’Arbois. Bˆatiment Villemin BP 80. 13545 Aix-en-Provence Cedex 4, France. Fax: + 33 491106377. E-mail address: [email protected] (A. Vergnoux).

0013-9351/$ - see front matter & 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.envres.2010.01.008

atmosphere and several groups of ‘‘priority’’ pollutants such as polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and polycyclic aromatic hydrocarbons (PAHs) (Kim et al., 2003). During the last 15 years, scientists have considerably drawn attention to these latter compounds because of their potential adverse effects on humans and wildlife (Nisbet and LaGoy, 1992). Hence 16 PAHs are registered on European and American lists (U.S. Environmental Protection Agency, EPA) of priority pollutants, they must be monitored in the environment. Environmental PAH contaminations can be due to either anthropogenic or natural sources. Human activities produce PAHs through the combustion of fossil fuels for heat and power generation, automobiles, coke ovens. Forest fires and volcanic eruption are the main natural sources of PAHs (Harvey, 1991; Menzie et al., 1992). Due to their resistance to the biodegradation, PAHs are well known as persistent organic pollutants in the environment (Wania and Mackay, 1996). Their propriety of adsorption on solid particles of soil, sediments or atmosphere implies their dissemination into the different environmental compartments at a global scale, explaining their ubiquity. Numerous research works demonstrate the link between PAH pattern and source apportionment (Soclo et al., 2000; Asia et al., 2009). More specifically, a few concentration ratios, as for example phenanthrene/anthracene, allow to distinguish between petrogenic or pyrolytic sources (Gschwend and Hites, 1981; Klamer and Fomsgarrd, 1993; Benlahcen et al., 1997; Olivella et al., 2005). Owing to the generation of PAHs through natural combustion and to the relation between PAH pattern and origin, the objective of this work was to study the impact of forest fires on PAH level

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and distribution in soils. The main issue is to determine if forest fire is a significant source of PAHs in burned soils depending on fire frequency and/or on the time elapsed since the last fire. Soils are more or less impacted depending on the frequency, severity and properties of fires, but also on climatic conditions following the event. In particular, the erosion due to wind and rain accentuated on bare landscape can durably or even definitely change the soil composition after a fire (Shakesby and Doerr, 2006). So, the study aims to evaluate if PAHs could be used as long-term fire biomarkers in burned soils. Forests situated in the South of France are particularly vulnerable to repeated fires. The experimental work was carried out in situ in a Mediterranean forest located in Maures Mountains. This region was selected because it presents areas affected by different fire regimes and also unburned areas for 50 years which could be considered as control areas.

2. Experimental 2.1. Sampling The studied area is a Mediterranean ecosystem located in the Maures Mountains, in the south-east of France, Cote d’Azur, near the famous touristy spot of ‘‘Saint-Tropez’’. Soils were sampled in two layers (A: 0–5 cm and B:  5 to 15 cm) at 30 different sites. These sites were subdivided in 6 groups representative of 6 different fire conditions: (i) numerous very recent fires (NVR), (ii) numerous and recent fires (NR), (iii) numerous and old fires (NO), (iv) few and recent fires (FR), (v) few and old fires (FO), (vi) control sites (C) unburned since summer 1950. These selected sites enable the investigation on the influence of the fire frequency on PAH levels, as well as their evolution with time elapsed after the last event. To achieve statistical representativeness, each group includes 5 different sites. The different sites present similarities in aspect, exposition, slope, altitude and ecological characteristics. The aim of this study is the effect of forest fires on PAH levels. That is why studied areas are also situated far from cities or industrial areas and then, are as much as possible preserved from anthropogenic impact. Even if particulate matter and hence PAHs associated with particulate matter can inevitably be transported over long distances, we tried to choose sites with a minimum risk of interferences from other inputs than forest fires. So, the ‘‘fire factor’’ was supposed to be the sole influencing factor. Further detailed information about the site and the sampling methodology are given in a previous work (Vergnoux et al., 2009).

obtained from Supelco (Bellefonte, PA, USA). A Certified Reference Matrix of soil (CRM, 131 COA, lot 002402) containing 15 of the 16 targeted PAHs, used to check the reliability of the analytical procedure, was purchased from Techlab (Metz, France). 2.3. Extraction and clean-up In order to minimize the loss of the volatile PAHs, soil samples were dried at 40 1C, rather than at higher temperature or with freeze-drying (Berset et al., 1999). Then, they were ground and homogenized. Pressurized liquid extraction (PLE) was performed using an ASE 200 Accelerated Solvent Extraction system (Dionex, Sunnyvale, CA, USA) equipped with 33 mL stainless steel extraction cells. PLE extraction with ‘‘in-cell cleanup’’ adapted from previous works (Ong et al., 2003; Vergnoux et al., 2007) were performed using cells lined with filter paper, packed (from bottom to top) with 4 g silice, 15 g of soil mixed with 7.5 g Na2SO4 and topped with ultra-clean pre-extracted Fontainebleau sand. Extractions were performed with nC6 at 150 1C and 14 MPa, using one dynamic (7 min) and two static steps (5 min each), a flush volume of 75%, and a purge time of 60 s. Organic extracts were then concentrated to 0.5 mL under N2 at 25 1C using a Turbovap II (Caliper Lifesciences, Hopkinton, MA, USA). To prevent PAH losses due to evaporation, 200 mL of DMF were added to the extract and the residual nC6 was eliminated under a gentle stream of N2. Before the HPLC analyses, the extract volumes were adjusted to 1 mL using ACN. To evaluate analytical uncertainties, 3 replicates per sample were carried out. 2.4. HPLC analyses Analyses were performed using HPLC equipped with a pump (Prostar Model 230, Varian, Palo Alto, CA, USA), a thermally controlled auto-sampler (Model 410, Varian) and a programmable fluorescence detector (Prostar, Varian). The injection vial and the analytical column were respectively placed at 10 and 35 1C for all analyses. The separations were carried out on a reverse phase C18 column (250 mm  4.6 mm  5 mm, ChromSpher 5PAH, Varian) protected by a guard column (packed with the same stationary phase, 10 mm  3 mm  5 mm, Chromguard HPLC column). Aliquots of 20 mL were injected, the flow rate was held at 1.2 mL min  1 and the run time was 55 min. Data were acquired and processed using the GalaxieTM software package (Varian). 2.5. Statistical treatment

2.2. Chemicals Analytical grade solvents were used. Acetonitrile (ACN), n-hexane (nC6) and H2O HPLC quality were purchased from VWR International (Fontenay sous bois, France) and dimethylformamide (DMF) was provided by Sigma-Aldrich (St. Louis, MO). Fontainebleau sand was provided by Carlo Erba reagents (Milan, Italy). Silica gel 60 (200–300 mesh) and anhydrous sodium sulphate (Na2SO4) were purchased from VWR International. The silica was deactivated with 10% water (w:w), and Na2SO4 was baked for 48 h at 550 1C before use. The reference standard mixture containing the 16 EPA-PAHs namely naphthalene (Na), acenaphtylene (Acy), acenaphtene (Ace), fluorene (Fluo), phenanthrene (Phe), anthracene (Ant), fluoranthene (Fla), pyrene (Pyr), benzo(a)anthracene (B(a)ant), chrysene (Chr), benzo(b/k)fluoranthene (B(b/k)fla), benzo(a)pyrene (B(a)pyr), indeno(1,2,3-cd)pyrene (Ind), dibenzo(a,h)anthracene (DB(ah)ant), and benzo(ghi) perylene (B(ghi)p) at a concentration level between 100 and 2000 mg mL  1 in methanol:dichloromethane (1:1; v-v) was

The analytical results for samples and sites replicates were statistically studied by using principal component analysis (PCA) which enables the extraction of the systematic variations in one data set (Qualls and Haines, 1992). This method can be used to depict information from a large data set as well as to help in data interpretation. In this work, PCA was employed to explore the influence of different fire conditions on the PAH distribution using the Analysis of Ecological Data in R (Ade4). At the same time, PCA was used to evaluate the relative contribution of each PAH to fire condition discrimination.

3. Results and discussion 3.1. Method calibration and validation To check the accuracy of PAH analyses, a Certified Reference Matrix of soil containing 15 PAHs was used. The 16 EPA-PAHs,

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250 200 150

A layer B layer

100

In published works dealing with the influence of forest fire on the organic compounds of soils, a few are studying the total PAH content (Kim et al., 2003) and to our knowledge, none is investigating the influence of forest fire on PAH pattern. Fig. 2 shows the concentration profile of the 14 EPA-PAH in A layers of controls and soils affected by NVR fires. The levels of the heaviest PAHs (4–6 benzene rings except Fla and Pyr) are at concentration levels not significantly different in burned and control soils due to large confidence interval. For instance, the mean results of the control soils and soils affected by NVR fires are (C level/NVR level): B(a)ant: 1.4/2.1; Chry: 3.3/4.3; B(b)fla: 3.8/2.3; B(k)fla: 1.3/0.7; B(a)py: 2.4/1.7; DB(ah)ant: 0.4/0.4 and B(ghi)per: 5.7/1.4. Thus, it is possible to assume that wildfires in the studied area do not generate heaviest EPA-PAHs. Besides, PAHs formation being quite dependent upon combustion temperature/condition and types of trees/forest, the apparent non-generation of 5–6 rings PAHs is probably a reflection of types of forest and burning conditions in the studied area. Furthermore, the 5- or 6-ring PAHs being not very sensitive to biodegradation, the results not significantly different between burned and unburned soils cannot be attributed to a fire generation of PAHs compensated by a loss due to biodegradation. Comparing results for soils affected by NVR fires and for the controls, it is possible to assess the PAH generation by fires in this

120 100 80

NVR C

60

20

0 B(

50 0

3.3. Molecular distribution of the 14 EPA-PAHs in burned and control soils

Na Ac e Flu o Ph e An t Fla

PAH total level (µg.kg-1)

Fig. 1 shows the total content of the 14 EPA-PAHs studied for the A and B layers of soils affected by NVR, NR, FR, NO and FO fires plus controls. Total PAH contents in A layers of the control soils reaches 40 mg kg  1. This level is consistent with typical total 16 EPA-PAH contents reported for area subjected to weak anthropogenic influence. As example, a total 16 EPA-PAH content of 49 mg kg  1 was determined in a Korean forest surface soil located far from cities or industrial areas (Kim et al., 2003). Moreover, the two layers of controls are not significantly different (Student test, P= 0.05). PAH formation by forest biomass combustion has been previously mentioned (Freeman and Cattell, 1990; Jenkins et al., 1996; Conde et al., 2005; Olsson and Kjallstrand, 2006). Thus, the total 14 EPA-PAH contents of the A layers of very recently and recently burned soils (NVR, NR and FR) are significantly greater than those of the controls (Student test, P o0.05). These soils exhibit 157, 77 and 89 mg kg  1 respectively. A recent study concerning the total 16 EPA-PAH levels in a Korean forest soil after a fire showed levels reaching 1570 mg kg  1 one month after the fire which then decreased to 220 mg kg  1 nine months after the fire (Kim et al., 2003). The relative low levels observed in our study could be due to the fact that sampling was carried out one and three years after the wildfire, for soils affected by very recent (NVR) and recent fires (FR and NR) respectively. On the other hand, the detected amounts are not significantly different between soils affected by few and numerous fires indicating that the fire frequency does not increase the PAH accumulation in soils. The surface contents for NO and FO are not significantly different from the controls suggesting that significant decrease of the total level on the surface layers has occurred with time since the last fire. Regarding EPA-PAH levels, the soils are restored to the initial state 16 years after the last fire. The loss or rather decrease in PAH concentrations with time were probably due to erosion and leaching rather than biodegradation since these compounds are known to be persistent. These phenomena lead to

Py r a)a nt Ch B( ry b)f lua B( k)f lua B( a)p y B( ah r )an B( t gh i)p er

3.2. Total 14 EPA-PAH contents in burned and control soils

the PAH transport toward close rivers. Hence, previous studies showed that waters and sediments of different rivers were polluted by PAH produced by forest fire event (Olivella et al., 2005; Gabos et al., 2001). Concerning the B layers, whatever the fire conditions were, the PAH contents of burned soils are not significantly different from the control. Thus the fires have little to no impact on the total EPA-PAH levels in deep layers of soils. Results for A and B layers of soils affected by FO fires are not significantly different from those of the soils affected by NO fires. Moreover, it is possible to make the same observation between the layers of soils affected by FR and NR fires. Thus, the fire frequency is not an influent factor. The more relevant factor seems to be the time elapsed since the last fire.

PAH level (µg.kg-1)

except acenaphtylene, were quantified by using HPLC-PFD and external standard calibration. The validation of the employed method was achieved only for 13 of the 15 analyzed PAHs because benzo(ghi)perylene was not present in the CRM and indeno(1,2,3cd)pyrene was slightly underestimated. Mean recoveries (n= 4) were in the range 72–131%, but the PAH values presented in this work have not been corrected for recovery. The precision of the procedure, calculated as RSD on 4 replicates, was between 4% and 10%. Consequently, the reliability of the analytical method was considered to be satisfactory.

195

NVR

NR

FR

NO

FO

C

Fig. 1. Sum of 14 EPA-PAHs in burned and control soils. Mean values per fire condition with confidence intervals (n= 5, P = 0.05). A layer: 0 to  5 cm; B layer:  5 to  15 cm. NVR: numerous very recent fires, NR: numerous recent fires, FR: few recent fires, NO: numerous old fires, FO: few old fires, C: control.

Fig. 2. Levels of 14 PAHs in A layers (0–5 cm) of soils affected by numerous very recent fires (NVR) and controls (C). Mean values with confidence intervals (n= 5, P= 0.05). Na: naphthalene; Ace: acenaphtene; Fluo: fluorene; Phe: phenanthrene; Ant: anthracene; Fla: fluoranthene; Pyr: pyrene; B(a)Ant: benzo(a)anthracene; Chr:chrysene; B(b/k)Fla: benzo(b/k)fluoranthene; B(a)Pyr: benzo(a)pyrene; DB(ah)Ant: dibenzo(a,h)anthracene; B(ghi)P: benzo(ghi)perylene.

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area. For the 7 low molecular weight (LMW) studied PAHs, e.g. Na, Ace, Fluo, Phe, Ant, Fla and Pyr (2–4 benzene rings), significant differences were observed between the very recently burned soils and the controls (Student test, P= 0.05), particularly the Na level which is about 20 times higher in the soil affected by NVR fires than in controls. For Ace, Fluo, Phe and Ant, the amounts are increased by a factor ranging 6–12, whereas this factor is about 2 for Fla and Pyr. The remarkably higher levels reached by the 7 LMW PAHs in very recently burned soils is in good agreement with the fact that they are the most produced aromatic compounds during forest fires (Yuan et al., 2008). Taking into account our results and this latter remark, it has to be concluded that particulate deposition of PAHs was occurring close to the fire source (Meharg et al., 1998). Some authors assume that PAH patterns in the surface horizons resemble to those of the atmospheric smokes due to the deposition (Wilcke and Zech, 1997; Genualdi et al., 2009; Hays et al., 2002). Furthermore, LMW PAHs are the most common in smokes from agricultural and sylvicultural debris combustion (Conde et al., 2005). Furthermore, the most volatile PAHs, e.g. Na, Fluo, Phe, Ant and Fla appear to be the major EPA-PAHs produced by pine wood and needles combustion (Conde et al., 2005) which is consistent with the present work. 3.4. Evolution of PAH molecular distribution with time Soil erosion is usually responsible to the rapid decrease of total PAH content, in the first year consecutive to the fire event. In addition to the erosion, fires generate only LMW PAHs, which are the preferentially volatilized, leached and degraded ones (Berteigne et al., 1988; Park et al., 1990). So, it could justify why the PAH contents in burned soils decrease with the time elapsed since the last fire (Fig. 1). Consequently, Fig. 3a shows the distribution of the LMW PAHs in the A layers of soils affected by NVR, NR, NO fires and controls in order to examine the temporal evolution of PAH level. The LMW PAH level evolutions could be described by 3 differentiated group of behaviors. The first one concerns Fla and Pyr which are produced at a relatively low amount and restored to the initial state less than 3 years after the last fire. Ace, Fluo, Phe and Ant are gathered in a second group behavior with a longer restoration time estimated between 3 and 16 years, since levels in soils affected by NR fires are still significantly higher than in controls. For both group behaviors as well as for heavier PAHs, none of the individual PAH concentrations in burned B layers present a significant difference with control B layers. The last behavior is depicted by Na evolution. The concentration level of Na, which is the most produced PAH by fires (Yuan et al., 2008), is

Fig. 3. Temporal evolution of PAH patterns of soils affected by different fire conditions. (a) A layers (0–5 cm); (b) B layers ( 5 to 15 cm). Mean values with confidence intervals (n =5, P= 0.05). NVR: numerous very recent; NR: numerous recent; NO: numerous old; C: control. Na: naphthalene; Ace: acenaphtene; Fluo: fluorene; Phe: phenanthrene; Ant: anthracene; Fla: fluoranthene; Pyr: pyrene.

divided by 2 in the soils affected by NR fires compared to the NVR and by 3 in the soils affected by NO fires relatively to the NR, resulting in a removal yield of 86% between NVR and NO fires. This aromatic compound decreases relatively rapidly with the time, even if it is still at a noticeably high level in the soils affected by NO fires compared to the controls. After 16 years, the levels of Na in NO soils have not reached the level of Na in ‘‘control’’ soils (unburned for 56 years). However, among the observed PAHs, this 2-ring aromatic compound is the most subjected to volatilization, leaching and biodegradation. But these processes do not balance the great amount initial produced. The leaching effect is nevertheless observed because of the presence of Na in the B layers of all burned soils at significant higher levels than controls (Fig. 3b). The slower decrease of Na levels with time in B than in A layers could be explained by the removal process of Na, mainly due to volatilization, which obviously occurs on the soil surface. To conclude, Na could probably be used as an effective mid- to longterm fire biomarker. For less volatile PAHs, potential volatilization is slower and removals could be achieved by abiotic transformations, which are responsible for 20% of the total reduction in PAHs during remediation of soils (Hansen et al., 2004). The biotic mechanisms are one of the main processes making possible the removal of PAHs containing more than 3 rings. PAHs are strongly adsorbed onto soil particles, especially clays (Luthy et al., 1997). The biodegradability decreases with the capability of PAHs desorption from soil (Hansen et al., 2004) and with the increase of the number of benzene rings. Hence, on one’s hand, remarkable reductions are observed one year after the fire for 3-ring PAHs with 84%, 80%, 76% and 88% of removal yields for Ace, Fluo, Phe and Ant respectively. On the other hand, Fla and Pyr (4-ring PAHs) present lower removal yields of 56% and 63% respectively.

3.5. Principal component analysis Fig. 4a and b represents the results of PCA for the 14 EPA-PAH levels of the A layers of soils affected by different fire conditions. Fig. 4a shows the samples position as a function of the two first principal components (PC). By using the first two PCs, it is possible to differentiate the fire conditions. The cluster corresponding to the A layers of soils affected by NVR fires differ from the others. It is located at the left top of Fig. 4a. Then, the clusters of the A layers of soils affected by FR and NR fires are gathered as well as the clusters of the A layers of soils affected by FO and NO fires. They are respectively placed at the origin of the graph and on the abscissa, slightly on the right. The control cluster is located in the right bottom of the graph. Fig. 4b shows that 78% of the total variance is explained by two components. The first PC, explaining 48% of the compositional data, is negatively correlated to the LMW PAHs. In the same way, the second PC, explaining 30% of the compositional data, is negatively correlated to B(k)Fla, B(b)Fla, B(a)Pyr, and slightly to B(ghi)Per. B(a)Ant and Chry correlate negatively the two PCs and DB(ah)ant is not an important influencing PAH for the sample ordination. The combined analysis of Fig. 4a and b gives a global view of results observed in Fig. 2 and 3. The position of the cluster corresponding to soils affected by NVR fires shows that the fires have an impact on the PAHs levels of burned soils. These soils present the highest levels of PAHs with LMW, e.g. Na, Ace, Fluo, Phe, Ant, Fla and Pyr. Regarding the first PC, the clusters of the different soils are arranged from the left to the right according to the time elapsed since the last fire. The levels of the 7 LMW PAHs decrease with the increase of the time elapsed since the last fire. The observation of the gathering of soils affected by FO and NO

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Fig. 4. Results of principal component analysis of 14 EPA-PAH levels for A layers (0–5 cm) of soils affected by different fire conditions. PC1 = 48% and PC2 = 30%. (a) sample representation; (b) correlation loadings. NVR: numerous very recent fires; NR: numerous recent fires; FR: few recent fires; NO: numerous old fires; FO: few old fires; C: control. Na: naphthalene; Ace: acenaphtene; Fluo: fluorene; Phe: phenanthrene; Ant: anthracene; Fla: fluoranthene; Pyr: pyrene; B.a.Ant: benzo(a)anthracene; Chry :chrysene; B.b/k.Fla: benzo(b/k)fluoranthene; B.a.Pyr: benzo(a)pyrene; DB.ah.Ant: dibenzo(a,h)anthracene; B.ghi.Pe´r: benzo(ghi)perylene.

P ðNa Ace Fluo Phe Ant Flua PyrÞ Fig. 5. Temporal evolution of the index ITE ¼ PðBðbÞFlua BðkÞFlua BðaÞPyr BðghiÞPerÞ. Results for the A layers (0–5 cm) of the different studied sites.

fires as well as soils affected by FR and NR fires confirm the previous observation that the frequency of fires is not an important influencing factor in the differentiation of the soils. Taking into account only the first PC, the controls have a position close to the position of soils affected by old fires. Now considering the second PC, the position of the controls is different to the position of the other soils. Even if the differences of 5–6 ring PAHs are not significantly different between burned and control soils, as it is precised latter, the levels of some highest molecular weight PAHs (B(ghi)Per, B(a)Pyr, B(k)Fla, B(b)Fla) are higher in the control soils whereas the soils affected by NVR fires show lower levels concerning these PAHs. Thus, this information is represented on the figure since these results have weight in the principal component construction. The levels of these heaviest

PAHs are similar for the 4 other kinds of soils, the position of the corresponding clusters being all close to the origin.

3.6. Definition of an index reflecting the time elapsed since the last fire The possible sources of PAHs in soils can be evaluated by the calculation of ratios of individual PAH concentrations (Gschwend and Hites, 1981, Klamer and Fomsgarrd, 1993; Benlahcen et al., 1997). Thus, a ratio of Phe/Ant o10 reveals a pyrolytic origin of the PAHs. The mean Phe/Ant ratios calculated are 3.1 70.4, 4.471.7, 5.3 70.9, 6.07 2.1, 7.272.4, 7.172.4 for soils affected by NVR, NR, FR, NO, FO fires and C respectively. These results

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confirm the pyrolytic origin of the PAHs in these soils. Moreover, this pyrolytic origin is accentuated for soils affected by NVR and NR fires, because the ratio values of these latter soils are significantly lower than those of the controls. To extend the ratioing concept of source apportionment and on the basis of molecular PAH distribution results, we try to define a new ratio reflecting the time elapsed since the last fire (ITE). The examination of PCA could help us to build this index. The first PC correlated to the LMW PAHs separate the burned soils according to the time elapsed since the fire but the controls do not differ from soils affected by FO and NO fires. Nevertheless, the second PC correlated to the heaviest PAHs does not separate soils affected by FO, NO, FR and NR fires but it separates the controls from FO and NO fires. So, the ratio of the sum of PAH levels correlating the first PC on the sum of PAH levels correlating the second PC could differentiate the soils according to the time elapsed since the fire. Accordingly, this index was defined as following: P ðNa AceFluo Phe Ant Flua PyrÞ ITE ¼ P ð1Þ ðBðbÞFlua BðkÞFlua BðaÞPyr BðghiÞPerÞ P where (Na Ace Fluo Phe Ant Flua Pyr) and S (B(b)Flua B(k)Flua B(a)Pyr B(ghi)Per) are the total concentrations of Na, Ace, Fluo, Phe, Ant, Flua, Pyr and B(b)Flua, B(k)Flua, B(a)Pyr, B(ghi)Per respectively. In order to validate this index, Fig. 5 plots the evolution of the calculated index values in function of time elapsed since the fire. The more recent the fire, the higher the index value. More precisely, when ITE 415 the last fire happened 1 year ago; when 154ITE 45 the last fire happened 3 years ago; when 54ITE 42.9 the last fire happened 16 years ago; and when ITE o2.9 the last fire happened more than 56 years ago. Finally, this index can be used to approximately evaluate the date of the last fire. ITE seems at least to enable the discrimination between recent and old last fire event. But more investigations have to be carried out with other data to demonstrate the validity of the hereby proposed index. Nevertheless, the index value can rather be considered as an indicator of the soil remediation.

Acknowledgment Special thanks are addressed for considerable sampling work, particularly to M. Bresson for equipment support and active sampling.

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