Long-term monitoring of heavy metals in Chilean coastal sediments in the eastern South Pacific Ocean

Marine Pollution Bulletin 64 (2012) 2254–2260

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Baseline

Long-term monitoring of heavy metals in Chilean coastal sediments in the eastern South Pacific Ocean Cristian Chandía b,c,⇑, Marco Salamanca a,b,c a

Laboratorio de Oceanografía Química (LOQ), Universidad de Concepción, Chile Departamento de Oceanografía, Universidad de Concepción, Casilla 160-C, Barrio Universitario s/n, Concepción, Chile c Programa de Monitoreo Marino Nueva Aldea (PROMNA), Universidad de Concepción, Chile b

a r t i c l e

i n f o

Keywords: Metals Marine sediments Geoaccumulation index Enrichment factor Chile

a b s t r a c t Concentrations of seven metals (Al, Cd, Cu, Fe, Pb, Ni, Zn) were determined in 256 surface sediment samples, collected between May 2006 and November 2009, from 15 stations at the mouth of the Itata River and its adjacent marine zone (central-southern Chile) as part of an environmental monitoring program. The objectives of the work were to: (i) establish baseline metal concentrations in the sediments of the area and (ii) identify tendencies in the spatial and temporal distribution of the metals in these marine sediments. Concentrations were highest in the north zone of the Itata River mouth (stations E2C, E13C) for all the metals and at the stations farthest offshore from the mouth (E4, E6) for Cu, Fe, Pb, and Ni. The ranges in those concentrations were lower than those reported in other studies performed along the Chilean coast and lower than those observed in most other coastal systems around the world. Based on results of the indices used (geoaccumulation index, enrichment factor), the coastal sediments were not measurably elevated above natural levels. Ó 2012 Elsevier Ltd. All rights reserved.

Over the last 15 years, environmental concern over the use of the coastal areas as recipients of potential contaminants has grown considerably in Chile. Due to its particular geography, a long and narrow country, any major industrial project in Chile considers eliminating its liquid wastes into coastal waters, which may adversely impact that zone. Consequently, any industrial project in Chile that may have an adverse effect on its coastal waters is required to conduct an environmental impact assessment and then maintain a monitoring program throughout its operation. In this context, the Chilean pulp industry mainly located in central Chile has expanded notably, growing exponentially from the 1990s, to a current a total production of 4.79 million tons of pulp annually (Chiang et al., 2010). When authorized by the national environmental agency (CONAMA), these factories can eliminate their treated liquid waste in the nearby coastal zone. An industrial forestry complex, located 50 km inland in the Bío Bío Region with an annual production of 1,300,000 tons discharges its treated liquid residues into the sea, through a submarine discharge located near the mouth of the Itata River. This complex began an environmental monitoring program in May 2006 that has continued uninterrupted ever since. Every three months a sampling survey is conducted to (i) measure physical and microbiological parameters ⇑ Corresponding author at: Programa de Monitoreo Marino Nueva Aldea (PROMNA), Universidad de Concepción, Casilla 160-C, Barrio Universitario s/n, Concepción, Chile. Tel.: +56 41 2661149; fax: +56 41 2256227. E-mail address: [email protected] (C. Chandía). 0025-326X/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.marpolbul.2012.06.030

in the water column, sediments, and marine organisms and (ii) measure metal concentrations and organic compounds in those sediments. Currently, this is the largest, most intensive environmental monitoring plan being carried out in Chile. The parameters being monitored include trace metals in sediments (Al, Cd, Cu, Fe, Ni, Pb, Zn) due to their relatively high toxicity and/or potential to bioaccumulate (Tam and Wong, 2000; Liu et al., 2003; Yuan et al., 2004; Ramirez et al., 2005; Singh et al., 2005; González-Macias et al., 2006; Corbett et al., 2009; Duan et al., 2010). The continuous seasonal monitoring of these metals has provided a unique opportunity for determining their spatial, annual, and inter-annual variability. The present work includes the results obtained through the mentioned monitoring program from May 2006 to November 2009, prior to any discharge of liquid industrial residue through the emissary. Therefore, the objectives of this study are: (i) to establish baseline metal concentrations in the sediments of the study area and (ii) to identify trends in the spatial and temporal distribution of the metals in marine sediments. The study area is located between 36° 10 –36° 50 S and 72° 90 –73° 10 W over the continental shelf, which is 40–60 km wide in this part of the Chilean coast, with submarine canyons to the north (Itata River) and south (Bío Bío River) (Thornburg et al., 1990). The coastal shelf between the canyons was filled with sand transported by the nearby rivers between the end of the Pleistocene period and the beginning of the Holocene period, facilitated by deltaic sand depositions. This generated extensive straight beaches to the north

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of Coliumo Bay and a continental shelf with a low slope (Biro, 1979; Ilabaca, 1979) filled with sediments of terrigenous origins (Pineda, 1999). The area monitored (Fig. 1) stretches from Cobquecura in the north (stations E1C, E2C, E13C) to Coliumo Bay in the south (stations E14C, E16C). Most of the stations (11) were located at the mouth of the Itata River (central zone). The area is characterized by the presence of Equatorial Subsurface Water, with low dissolved oxygen and high nutrient contents (Ahumada, 1992). This water mass is transported southward over the continental shelf along

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the Chilean coast by the Günther subsurface current (Alheit and Bernal, 1993). The oceanographic variability in the area is markedly seasonal, as reflected by the presence of intermittent summer coastal upwelling processes (Sobarzo et al., 2001, 2007) and important seasonal fluvial contributions from the Itata River, mainly in winter (Quiñones and Montes, 2001; Sobarzo et al., 2007; Sánchez et al., 2008). This river, fed by several tributaries that have their origin in the Andes Mountains, runs for 195 km with an average flow of 240 m3 s1 (Dussaillant, 2009). The study area also has a high biological productivity, which supports important pelagic

Fig. 1. Location of the stations in the coastal area of the Itata River and its adjacent zone.

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and benthic fisheries (Cubillos et al., 1996, 2004; Daneri et al., 2000; Cubillos et al., 2004; Lillo et al., 2004; Araya et al., 2006). Between May 2006 and November 2009, 16 stations near the mouth of the Itata River (Fig. 1) were sampled every three months, and a total of 256 surface sediment samples were collected. For this, a van Veen grab (20 cm2 area) covered with epoxy paint was used. The collected sediments were stored in plastic bags and kept at 4 °C until further analysis. The sediment grain size was determined by sieving and each fraction weighed was expressed as a percentage of the total weight. The total organic matter (TOM) content was determined by calcination in a furnace at 500 °C (Buchanan, 1971) in the Chemical Oceanography Laboratory of the University of Concepción, Chile. Mineralogical analysis of the sediment samples were done by X-ray diffraction (Rigaku, Model RAD-2) at the Institute of Applied Economic Geology of the Universidad de Concepción. To determine the metals concentrations, about 0.25 grams (dry weight) of homogenized sediments were weighed and leached through an acid digestion, using established protocols (EPA method 3050B, 1996). The metal concentrations were then measured by inductively coupled mass spectrometry (ICP-MS, Thermo Scientific, Model X Series 2). The QA/QC of the analysis consisted of the estimation of the precision and accuracy using three replicates of certified reference material (MESS-3). Additionally, a blank reagent was checked every batch of 10 samples. All the reagents used in the analyses were ultrapure quality. The percentages of recovery and the estimated method detection limits (MDL) for the trace metals results are shown in Table 1. Several different indices were used to evaluate the degree of pollution in the sediments: (i) An enrichment factor (EF) was calculated according to Zhang and Liu (2002):

EF ¼ ½ðMeÞs =ðAlÞs =½ðMeÞc =ðAlÞc  where, (Me)s is the concentration of the metal in sample (s); (Al)s is the concentration of Al, (Me)c is the reference concentration of the metal, and (Al)c is the reference concentration of Al. (ii) The pollution load index (PLI), defined by Tomlinson et al. (1980), was used to compare the total content of metals at different sampling sites.

PLI ¼ ðCf1  Cf2 . . . Cfn Þ1=n where, n is the number of metals (here, seven) and Cfn is a contamination factor. This factor is calculated from the following equation: Cfn = Metal concentration/Background value of metal. (iii) The geoaccumulation index (Igeo) proposed by Müller (1981) was used for comparing current and pre-industrial metal concentrations in sediments.

Cn Igeo ¼ logð Þ 1:5  Bn

Table 1 Quality Assurance and Control values, recovery and Method Detection Limits (MDL) for the trace metals studied.

a b

Metal

MESS-3a

MESS-3b

Recovery (%)

MDL (lg g1)

Al Cd Cu Fe Ni Pb Zn

8.6 ± 0.23 0.24 ± 0.01 33.9 ± 1.6 4.34 ± 0.11 46.9 ± 2.2 21.1 ± 0.7 159 ± 8

7.8 ± 0.55 0.25 ± 0.03 33.7 ± 1.18 4.08 ± 0.17 45.3 ± 2.68 20.9 ± 1.12 151.9 ± 5.9

90.7 104.2 99.4 94.0 96.6 99.1 95.5

0.3 0.3 0.01 0.03 0.01 0.01 0.01

Certificate values in lg g1, except Al and Fe in %. Measured values in lg g1, except Al and Fe in %.

where, Cn is the measured concentration of a given metal in the sediments and Bn is the reference concentration of the metal. The factor 1.5 is the correction factor of the reference matrix due to the lithogenic effects. The pollution classes proposed by Müller (1981) were used for this evaluation. (iv) A non-metric multidimensional scaling (MDS) statistical analysis, based on the Bray-Curtis similarity coefficient, transforming the data to square roots was used to observe the spatial patterns of the trace metals. (v) A cluster analysis, based on normalized Euclidian distances and the sampling stations was performed using the software PRIMER v.6 developed in Plymouth Marine Laboratory to compare and establish relationships between the concentrations of the trace metals and the physical–chemical parameters of the sediments. (vi) Finally, the Mann–Kendall non-parametric test was used to evaluate positive or negative temporal monotonic tendencies (Mann, 1945; Kendall, 1975) and the Sen method was used to estimate the slope of the lineal tendency (Sen, 1968). The marine sediments in the study area had a mineralogical composition of a plagioclase in the dominant phase and quartz, mica, halite, clinochlore, amphibole, and pyroxene in the trace phase. The average grain size in the study area was <0.125 mm (Table 2), equivalent to fine to very fine sands on the Wentworth scale. Coarse grain was found around the mouth of the Itata River and fine grain to the north and south of this zone. The granulometric composition of the sediment showed a moderate selection with positive asymmetry at most stations. Nonetheless, the shallowest stations exhibited very negative asymmetries. The highest percentages of organic matter (1.51–9.66%; Table 2) were associated with the deepest stations and the presence of fine grain fractions. Aluminum: The Al concentrations in the sediments varied between 2.54 and 5.3% (Table 2). The highest concentration was found to the north of the Itata River mouth at station E13C, a deep station with high content of fine sediments (<0.063 mm). The concentrations at the river mouth ranged from 3.12 to 4.60%. The Igeo values were negative for all stations (Table 3). The analysis of tendencies indicated a significant increment (p = 0.05) in Al from the beginning of the monitoring program, but with a low slope (Table 4) and a random distribution according to the residue analysis. Cadmium: The Cd concentrations varied between 0.08 and 1.25 lg g1 (Table 2). The lowest concentrations were found around the river mouth and the highest at station E13C. The EF was >1.5 at stations E1C, E13C, and E16C, to the north and south of the mouth. The Igeo was positive at stations E1C and E13C (Table 3), north of the Itata River mouth, where the highest Cd concentrations (0.65 and 1.25 mg kg1, respectively) were found. The analysis of tendencies was not significant (p > 0.05). Nonetheless, the analysis of residue indicated a random distribution with pulses. Copper: The Cu concentrations varied between 13.57 and 28.03 lg g1 (Table 2). The highest concentrations were found at stations E4 and E13C, with a Cu concentration of 22.54 and 28.03 lg g1, respectively. The EF was <1.5 and the Igeo was negative for all the monitoring stations (Table 3). The analysis of tendencies was not significant (p > 0.05) and the analysis of the residue showed a random distribution with pulses. Iron: The Fe concentrations varied between 27.23 and 39.86% (Table 2). The highest content was found at stations E13C and E6, with concentrations of 39.86 and 34.51%, respectively. The EF was <1.5 and the Igeo was negative for all the stations sampled (Table 3). The analysis of tendencies was not significant (p > 0.05), and the analysis of the residue exhibited a random distribution. Nickel: The Ni concentrations in the sediments fluctuated between 12.19 and 39.47 lg g1 (Table 2). The highest levels were found at stations E2C and E6, with values of 39.47 and

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Table 2 Average concentration of trace metals in marine sediments, expressed as lg g1, except for Al and Fe, which are given in %. Total Organic Matter (TOM), dominant sediment size fraction (mm), and Pollution Load Index (PLI) per metal. Stations

E1C E2C E13C E2 E4 E5 E6 E7 E9 E10 E12 E15 E17 E18 E14C E16C

% TOM

2.21 ± 0.96 1.73 ± 0.23 9.66 ± 2.78 2.41 ± 0.91 5.43 ± 4.17 2.33 ± 0.55 1.71 ± 1.36 1.69 ± 0.58 1.51 ± 0.43 2.04 ± 0.55 2.52 ± 1.71 2.58 ± 0.90 1.93 ± 0.49 1.74 ± 0.36 2.18 ± 0.21 4.08 ± 1.88

mm

0.125 0.125 0.063 0.063 0.125 0.125 0.250 0.250 0.250 0.063 0.063 0.125 0.250 0.125 0.063 0.063

PLI

Metal concentration. Mean ± standard deviation

0.47 0.41 0.78 0.42 0.59 0.42 0.45 0.36 0.36 0.40 0.42 0.41 0.36 0.37 0.44 0.44

Al

Cd

Cu

Fe

Ni

Pb

Zn

2.54 ± 1.47 3.44 ± 0.70 5.30 ± 1.27 3.24 ± 0.71 4.60 ± 1.27 3.68 ± 0.98 3.53 ± 1.21 3.24 ± 1.08 3.18 ± 0.85 3.34 ± 0.80 3.50 ± 1.33 3.38 ± 0.50 3.12 ± 0.75 3.33 ± 0.91 3.74 ± 1.16 4.21 ± 0.78

0.65 ± 0.74 0.09 ± 0.02 1.25 ± 1.19 0.13 ± 0.03 0.30 ± 0.20 0.11 ± 0.04 0.15 ± 0.12 0.08 ± 0.01 0.09 ± 0.03 0.11 ± 0.05 0.11 ± 0.04 0.12 ± 0.03 0.09 ± 0.02 0.08 ± 0.00 0.14 ± 0.09 0.26 ± 0.10

13.57 ± 4.83 15.91 ± 2.65 28.03 ± 7.71 14.32 ± 2.83 22.54 ± 12.05 16.18 ± 2.10 17.22 ± 2.89 15.99 ± 2.29 17.68 ± 4.50 17.48 ± 2.83 17.96 ± 2.68 16.10 ± 2.12 16.21 ± 2.11 16.59 ± 2.41 16.93 ± 2.33 15.94 ± 3.18

27.61 ± 1.41 31.08 ± 1.05 39.86 ± 0.60 31.21 ± 1.08 31.00 ± 0.75 33.58 ± 0.41 34.51 ± 0.87 28.11 ± 0.44 27.23 ± 0.37 30.53 ± 0.46 33.42 ± 0.84 31.70 ± 0.42 28.33 ± 00.35 30.08 ± 0.47 32.57 ± 0.43 28.91 ± 0.56

35.48 ± 18.00 39.47 ± 10.73 22.97 ± 3.47 35.34 ± 9.39 29.66 ± 17.47 30.11 ± 7.04 37.41 ± 16.54 28.33 ± 16.36 24.62 ± 10.28 24.36 ± 6.70 26.05 ± 7.46 29.69 ± 7.59 23.17 ± 9.34 27.74 ± 13.34 30.54 ± 4.05 12.19 ± 1.77

3.26 ± 2.35 3.78 ± 2.61 8.95 ± 2.04 3.68 ± 2.60 9.04 ± 2.16 3.69 ± 2.66 3.71 ± 3.86 3.20 ± 2.88 2.90 ± 2.47 3.78 ± 2.73 3.83 ± 2.77 3.58 ± 2.50 3.23 ± 2.26 3.12 ± 2.26 4.13 ± 2.96 6.28 ± 1.68

39.23 ± 15.72 50.37 ± 6.58 61.33 ± 15.56 47.08 ± 7.15 54.06 ± 18.05 49.21 ± 8.20 47.52 ± 6.32 39.12 ± 7.87 42.51 ± 6.42 49.13 ± 6.77 49.47 ± 9.04 45.32 ± 9.16 43.89 ± 9.20 43.01 ± 8.31 47.67 ± 8.01 46.09 ± 13.24

Table 3 Values of the geoaccumulation index (Igeo) and enrichment factors (EF) for metals in marine sediments of the coastal zone of the Itata River.

E1C E2C E13C E2 E4 E5 E6 E7 E9 E10 E12 E15 E17 E18 E14C E16C

Al

Cd

Fe

Ni

Igeo

Igeo

EF

Cu Igeo

EF

Igeo

Igeo

EF

Igeo

EF

Igeo

EF

2.38 1.94 1.31 2.03 1.52 1.84 1.90 2.03 2.05 1.98 1.91 1.96 2.08 1.99 1.82 1.65

0.53 2.39 1.48 1.76 0.59 1.98 1.59 2.50 2.37 2.03 2.03 1.91 2.32 2.54 1.67 0.81

7.50 0.73 6.93 1.20 1.90 0.91 1.24 0.73 0.80 0.97 0.92 1.04 0.85 0.68 1.11 1.79

2.31 2.09 1.27 2.24 1.58 2.06 1.97 2.08 1.93 1.95 1.91 2.07 2.06 2.02 2.00 2.08

1.04 0.90 1.03 0.86 0.96 0.86 0.95 0.97 1.09 1.02 1.00 0.93 1.02 0.97 0.89 0.74

1.36 1.19 0.83 1.18 1.19 1.08 1.04 1.33 1.38 1.21 1.08 1.16 1.32 1.23 1.12 1.29

1.08 0.93 1.71 1.09 1.34 1.32 1.00 1.40 1.61 1.62 1.53 1.34 1.69 1.43 1.30 2.62

2.46 2.02 0.76 1.92 1.13 1.44 1.87 1.55 1.36 1.28 1.31 1.55 1.31 1.47 1.44 0.51

3.20 2.99 1.75 3.03 1.73 3.02 3.02 3.23 3.37 2.99 2.97 3.07 3.21 3.27 2.86 2.26

0.56 0.48 0.74 0.50 0.87 0.44 0.46 0.44 0.40 0.50 0.48 0.47 0.46 0.41 0.49 0.66

1.86 1.50 1.22 1.60 1.40 1.53 1.58 1.87 1.74 1.54 1.53 1.65 1.70 1.73 1.58 1.63

1.43 1.36 1.07 1.35 1.09 1.24 1.25 1.13 1.24 1.36 1.31 1.24 1.30 1.20 1.18 1.01

Table 4 Analysis of tendencies (Z-test) and slopes (Q-test) of the trace metals in the coastal sediments of central-southern Chile. Metals

N

P

Z (Mann–Kendall)

Q (Sen)

Al Cd Cu Fe Pb Ni Zn

21 21 21 21 21 21 21

0.05 >0.1 >0.1 0.1 0.05 >0.1 >0.1

2.51 1.54 1.06 1.84 2.85 0.63 1.36

0.038 0.003 0.016 0.030 0.023 0.016 0.029

37.41 lg g1, respectively. The EF values at stations E1C, E2C, E2, E6, E7 and E15 were >1.5 (Table 3). The Igeo values were negative for all the stations during the monitoring. Nonetheless, the analysis of tendencies was not significant (p > 0.05) and the analysis of residue indicated a random distribution with pulses. Lead: The sediment Pb concentrations varied between 2.90 and 9.04 lg g1 (Table 2). The values were highest at stations E4 (9.04 lg g1), E13C (8.95 lg g1), and E16C (6.28 lg g1). The EF was <1 and the Igeo was negative for all the stations. The analysis of tendencies indicated a significant increment (p < 0.05) of Pb from the onset of the monitoring (Table 4) and had a random distribution with pulses based on the analysis of residues.

Pb

Zn

Zinc: The Zn concentrations in the sediments varied between 39.12 and 61.33 lg g1 (Table 2). The lowest level was at station E7, around the mouth of the Itata River, and the highest level was at station E13C. The EF was <1.5 and the Igeo was negative for all the stations. The analysis of tendencies was not significant (p > 0.05) and that of the residues indicated a random distribution with pulses. According to the Pollution Load Index (PLI), the highest concentrations of heavy metals were found at stations E1C, E13C, E4, and E16C (Table 2). These stations also had the highest percentages of organic matter and the finest sediments (Table 2), and their dissimilarity with the other stations was corroborated by the MDS (Fig. 2). Moreover, the cluster analysis identified five groups at a Euclidean distance level of 0.4 (Fig. 3). Group A included only one station (E13C), characterized by the largest percentage of organic matter and the deepest station. Group B included only station E4, which had the highest levels of Ni and Pb. Group C consisted of the southernmost monitoring station (E16C), with high concentrations of Al, Cd, and Pb; and Group D also consisted of just one station (E1C), with the lowest levels of Al, Cu, Fe, Pb, and Zn. Finally, group E consisted of 12 stations, all located in the central monitoring zone, with shallow depths and low percentages of organic matter. The mineralogical composition identified the sediments as schists, a sedimentary composition typical of the South Pacific (Li

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Fig. 2. Representation in MDS elaborated with the trace metal data. The results of the cluster analysis are superimposed over the figure.

Fig. 3. Similarity dendrogram based on Euclidian distances normalized for the sampled stations.

and Schoonmaker, 2001). The percentages of total organic matter in the study area were moderate in comparison with those determined in the sediments of Concepción Bay (Carrasco et al., 1999) and Chile’s southern channels and fjords (Silva, 2006).

The concentrations of Cd, Cu, and Pb were lower than those reported in the coastal sediments of central Chile by Salamanca et al. (1988) and Lépez et al. (2001). Likewise, the levels of Ni and Zn fell within the ranges reported for the coastal systems of the eastern

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South Pacific by Ramirez et al. (2005), Valdés et al. (2005) and Valdés and Sifeddine (2009). Nevertheless, the concentrations of metals determined in the present study were lower than those observed in many other coastal systems around the world (Buccolieri et al., 2006; Corbett et al., 2009; Siddique et al., 2009; Ghrefat et al., 2011; Gargouri et al., 2011). The different indices used to evaluate the degree of pollution of these sediments suggest that most metal concentrations in the sediments were at natural levels. The Igeo values were negative for all the metals, further indicating that the sediments were not contaminated with respect to the reference levels of the schists. Only Cd and Ni had some EF values >1.5, which indicate an origin different to a natural source, according to Zhang and Liu (2002). The two anomalously high values of Cd were at stations E1C (0.5) and E13C (1.5), which are both located in the northern sector of the study area. They also were the deepest stations, with relatively fine sediments and high percentages of total organic matter. Those factors favor the natural accumulation of metals since fine grains have relatively specific high surface area/volume ratios that allow greater surface adsorption and organic matter may complex those metals (Chester, 2000; Navarro et al., 2006). The temporal and spatial analysis of the information obtained through this environmental monitoring program, based on the sampling of 16 near shore stations every three months over four years (May 2006 to November 2009), revealed that the coastal sediments at the mouth of the Itata River and to the north and south of this are not measurably contaminated with metals. This determination is consistent with the relative absence of large industrial activities or urbanization in the adjacent coastal area. Consequently, these data provide a baseline to measure the impact of future developments in this sensitive coastal marine environment.

Acknowledgements The authors wish to thank the Management of Environmental and Occupational Health office, Arauco Company for facilitating the use of the information presented in this study. Also, we thank for the analytical support of the Chemical Oceanography Laboratory, Oceanography Department, University of Concepcion. Chile. We are grateful to Russell Flegal for English correction and helpful comments on the manuscript.

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