riskassessment of domestic and industrial efﬂuents unloaded into a freshwater environment

7/29/2019 Riskassessment of domestic and industrial effluents unloaded into a freshwater environment

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Risk assessment of domestic and industrial effluents unloaded

into a freshwater environment

W.D. Di Marzioa,b,, M. Sa enza, J. Alberdia, M. Tortorellia, Galassi Silvanac

aPrograma de Investigacion en Ecotoxicolog a, Departamento de Ciencias Basicas, Universidad Nacional de Lujan, C.C. 221, 6700 Lujan B, ArgentinabComision Nacional de Investigaciones Cient ficas y Tecnicas CONICET

cUniversita degli Studi di Milano-Bicocca, Dip. di Biotecnologie e Bioscienze, Milano, Italia

Received 13 November 2003; received in revised form 14 September 2004; accepted 18 October 2004

Available online 26 January 2005

Abstract

An ecotoxicologic study was performed to assess the environmental status of the Luja n River. It is an important freshwater

system in the northeast of Buenos Aires Province, Argentina. Surface waters (SWs) and liquids effluents (LEs), before they reached

the river, and sediments were assessed via acute toxicity screening using a battery of tests with native species. Additionally, the

presence, in each LE and SW sample, of bioaccumulatable compounds was checked by SPME extraction and gas chromatograph-

MS determination. An environmental risk assessment of each LE was carried out via toxic units and assessment factors approach

and through extrapolation methods. Hazardous concentrations for each LE were compared with their river effluent concentrations.

Ninety-one percent (91%) of the total toxic load of the river was due to 4 of 11 LEs (37%) evaluated. Although SW samples were

not toxic, a real environmental risk was found for this freshwater environment. Sediment toxicity was found to be related to the

proximity to pipe discharges. Bioaccumulatable compounds were found in SWs and in LEs. Esters of phthalic acids, morpholine,

hydroquinone, and nonylphenol were found throughout the river at different sample sites and in different months during the 1-year

sampling program.

r 2004 Elsevier Inc. All rights reserved.

Keywords: Environmental risk assessment; River; Bioaccumulatable compounds; Acute toxicity; Sediments; Toxic units; Assessment factors;

Extrapolation methods

1. Introduction

The utility of a battery of biotests is well established

for environmental hazard assessment of chemicals and

chemical products, and biotests are used routinely to

evaluate the toxicity of complex mixtures such as

industrial wastewaters (Baun and Nyholm, 1996). Atoxicity evaluation is an important parameter in waste-

water quality monitoring, as it provides an overview of

the response of test organisms to all the compounds in

the wastewater (Wang et al., 2003).

The Luja n Rivers basin is situated in the northeast of

Buenos Aires Province, Argentina. It emerges from the

confluence of the Los Leones and El Durazno streams

and runs 130 km through an area of 2300km2. One

million people are connected to this area. It receives thedischarge of industrial and sewage effluents from its

source to its outlet in the Ro de la Plata River.

Furthermore, the Luja n River runs through a region

with typical agricultural and cattle activity. Its water

quality had deteriorated throughout the three decades

prior to this study (Sa enz et al., 1996; Alberdi et al.,

1996). Sporadic fish die-offs had been observed through-

out the river. As a result, the interaction of people with

the river was reduced, since almost no recreational

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0147-6513/$- see front matter r 2004 Elsevier Inc. All rights reserved.

doi:10.1016/j.ecoenv.2004.10.002

Corresponding author. Programa de Investigacio n en Ecotoxico-

loga, Departamento de Ciencias Ba sicas, Universidad Nacional de

Luja n, C.C. 221, 6700 Luja n B, Argentina. Fax: +54 2323 423171x285.

E-mail addresses: [email protected], [email protected].

edu.ar (W.D. Di Marzio).
http://www.elsevier.com/locate/ecoenv


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activities on the river were possible. The people of the

region feel that the river is polluted and that anything

originating in its water is contaminated. No one seems

to be responsible for this deterioration or for halting it.

As in lotic systems, pollution seems to come from

upstream; thus, each city and industry minimizes its

responsibility.Environmental legislation does not include toxicity

evaluation of liquid effluents (LEs) discharged into the

Luja n River. To assess the environmental hazard of the

discharges into the river, both the physico-chemical (PC)

and toxic characteristics should be evaluated (Grothe

and Reed-Judkins, 1996). An evaluation of the toxicity

of the surface water (SW) and the toxic load that is

being incorporated into the system should give us a

picture of the rivers status. Studies of wastewater

effluents indicate that toxicity tests have a viable role

in water quality monitoring and control in rural areas.

Sponza (2003) demonstrated that there is no single

method that constitutes a comprehensive approach to

aquatic life protection. For this reason, a spectrum of

toxicity tests containing sensitive microorganisms

should be applied to complement each other and

chemical analyses. Wang et al. (2003) indicated that

bioassays of SW and domestic effluent concentrates

have considerable potential as a monitoring tool for

organic contaminants in water. Bioassays of aquatic

concentrates provide a direct functional response to the

overall toxic properties of the mixtures of compounds

present in a sample. Bioassays also are a cost-effective

alternative to comprehensive chemical analysis. A

toxicity identification approach allows connections tobe drawn between the toxic effects observed with the

compounds detected. This type of information can help

one select appropriate treatments or source-reduction

methodologies.

We proposed a study to identify zones within the river

that show acute toxicity to native organisms, to create

toxic load profiles for the more important industries and

domestic effluents discharged, and to measure the

environmental risk via a toxic-unit approach and by

using extrapolation methods. Bioassays with native

aquatic organisms were performed. We also conducted

a qualitative survey of the bioaccumulatable compoundsfound in water samples of the Luja n River and in liquids

effluents (LEs) prior to discharge.

2. Materials and methods

During 2003, water samples were taken from the

surface of the Luja n River at 2-month intervals. During

each sampling period samples were taken for 15 days at

six sampling points. Fig. 1 shows the area under study

and the sampling sites that cover the run of the river

from sources to outlet. These sites are characterized as

follows: Site 1 (Los Leones), an unpolluted stream. Site

2 (El Durazno) is a stream that is influenced by effluents

from the milk industry. Site 3 (Suipacha) is where the

Luja n River rises from the confluence of the Los Leones

and El Durazno streams. Site 4 is where the river

receives effluents from chemical industries and from the

city of Mercedes, which had no wastewater treatmentplant at the time of this study. At Site 5 (Las Tropas) the

river receives effluents from the textile, meat, tannery,

and enzyme purification industries. At Site 6 (La Loma)

the river receives the effluents of the sewage plant of the

city of Luja n, of textile, chemical, and food industries.

At each point water samples were taken at 1 m below

the surface by a horizontal water bottle made of

polyvinyl chloride (Wildco Beta). The river flow

measurement was obtained from an automatic flow

meter placed downstream of the city of Mercedes by

personnel of the Department of Hydrology of Buenos

Aires Province. PC parameters of water samples were

measured in situ by a water quality checker for

simultaneous multiparameter measurement (HORIBA

U10). These parameters were dissolved in oxygen

concentration, turbidity, salinity, conductivity, tempera-

ture, and pH. We also evaluated the chemical oxygen

demand (COD) and biochemical oxygen demand (BOD)

of each water sample according to APHA-AWWA-

WPCF (1998). An Ekman dredge was used to take

sediment samples. All sediment samples were compo-

sites of five grab samples at each sampling point. They

were characterized by pH, ammonia, sulfide, and

organic matter. Standard methods for these parameters

were according to APHA-AWWA-WPCF (1998).

2.1. Toxicity tests

Acute toxicity assessment of water samples was

performed with the green alga Scenedesmus quadricauda

and the following native organisms: the microcrustacean

Daphnia spinulata, the amphipod Hyalella curvispina,

and the poeciliid Cnesterodon decemmaculatum. Tests

were performed following the United States Environ-

mental Protection Agency (US EPA, 1991) and OECD

(1981) guidelines for receiving waters and LEs.

2.1.1. Algal toxicity tests

The strain S. quadricauda CCAP 276-21 was used in

96-h algal toxicity tests. Algal stock cultures were

maintained in modified Detmers nutrient medium (pH

7.5) under controlled conditions in a climatized room at

2271 1C, 3000 lx/cm2 of continuous cool-white fluor-

escent lighting, and 100 excursions/min on a shaker

(Walsh, 1988). The inocula were prepared from these

cultures to provide an initial cell density of 5 104 cell/

ml in treated and control flasks. Test solutions consisted

of enriched river water samples with algal medium

nutrient solutions. Control cultures were incubated in

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the same medium. Control and treated cultures were

grown under the same conditions of temperature,

photoperiod, and shaking and were carried out intriplicate. Each toxicity test was conducted three times.

Cell counts were correlated with absorbance (750 nm) on

a Shimadzu MUV 240 spectrophotometer (Walsh,

1988). Definitive protocols for toxicity testing using this

species are described in Sa enz et al. (1996).

2.1.2. Microcrustacean toxicity test

Microcrustacean tests were performed with D. spinu-

lata, a native Argentine cladoceran zooplankton that is

widespread in freshwater environments of Buenos Aires

Province. Acute toxicity tests under static conditions

were carried out with D. spinulatao

24h old. Testconditions were static or without the renewal of

medium, 48 h in duration, and conducted at 2071 1C

in the dark. Organisms placed in artificial pond water

(pH, 7.870.2; total hardness, 95.876m g CO3Ca/L;

conductivity, 475.5746.3mS/cm; and alkalinity,

189.3714.5 mg CO3Ca/L) served as controls. Definitive

protocols for toxicity testing using these species are

described in Alberdi et al. (1996).

2.1.3. Amphipod toxicity tests

The native amphipod H. curvispina was selected as the

test organism. H. curvispina were collected from a

population in an artificial pond in a field of Universidad

Nacional de Luja n. They were placed in laboratory

tanks of 500 L with a continuous flow of groundwaterunder natural conditions (water quality: hardness,

126mg CO3Ca/L; conductivity, 800mS/cm; pH, 8.26;

alkalinity, 412 mg CO3Ca/L). Ten-day-old individuals

were chosen because of there relative sensitivity [EC50,

96 h in 0.31 mg potassium dichromate/L (confidence

interval of 0.120.53 at Po0:05)] and size appropriatefor test handling (Simionato et al., 1997). An age control

was made using the equation Tlen 0:71 0:037t;where Tlen is the total length in millimeters and t is the

time in days. The dilution water (DW) proposed for

Borgmann (1996) was used in the experiments because it

includes the bromide ion essential to Hyalella sp. Thewater quality for the DW was hardness, 82 mg CO3Ca/

L; conductivity, 500mS/cm; pH, 8.3; and alkalinity,

212 mg CO3Ca/L. Other conditions were a temperature

of 2171 1C and a 12-h dark/light photoperiod. SWs and

LEs were assayed with 10-day-old and adult organisms.

A 96-h static test was carried out in darkness with 40

amphipods of each age per sample. Definitive protocols

are described in Di Marzio et al. (1999).

2.1.4. Fish toxicity tests

Fish toxicity tests were performed with species C.

decemmaculatum. It is a native member of the Family

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N

20 kmSuipacha

Mercedes

Lujn

Buenos Aires

city

Rio de la Plata

Lujn river

Argentine

4

1 2 3

56

sampling sites

Fig. 1. Map of the study area (the Luja n River basin). Numbers are the SW and sediment sampling sites.

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Poeciliidae that is widespread in the temperate water

region throughout Buenos Aires Province. Its regional

distribution reaches larger rivers in the Patagonia area,

such as the Neuque n River, which has colder waters.

Ninety-six-hour semistatic acute tests were conducted.

Fish captured in an artificial freshwater pond were

acclimated in groundwater (pH, 7.9; conductivity,400mS/cm; dissolved oxygen (DO) concentration.

8.20 mg/L; hardness, 98 mg CaCO3/L) for 20 days under

environmental test conditions. During this period

they were fed daily with natural (algae+Daphnia sp.)

and artificial food, not exceeding 5% of their total

individual weight. Tests were made using ground-

water in glass aquaria at 2071 1C and a photoperiod

of 12 h light/12 h dark. The final volume was 2 L in order

to get a loading rate of 0.5 g of fish/L. Samples and the

control were quadruplicated. Eighty individuals of 1

month in age were used for each sample (40 males/40

females). Each aquarium was aerated to ensure a

DO concentration greater than 5 mg/L. The solutions

were renewed daily. Every 24h the mortality was

recorded. The definitive protocol is described in Di

Marzio et al. (1996).

2.2. Sediment test

Sediment toxicity was assessed with H. curvispina in a

10-day test. Sediment test conditions are summarized as

follows: river sediment/control sediment; homogenized

50 g/250-mL DW; eight replicates; 1015-day-old H.

curvispina. The overlying water was aerated and cleaned

every 24 h. Mortality and growth were recorded at theend of exposure. Sediment of an unpolluted stream

containing less than 3% organic matter was used as the

control in the experiments. Sediment organic matter was

measured according to APHA-AWWA-WPCF (1998).

Further details of the protocol used are in US EPA

(1998) and Di Marzio et al. (1999).

2.3. Analytical determination of bioaccumulatable

compounds in surface water and liquid effluents

Grab samples for analytical determinations were

collected at each sampling point or effluent. They wererefrigerated at 4 1C and kept in glass containers that

were rinsed with tap water followed by high-purity

water prior to the addition of the samples. They were

filtered across a 0.45-m-fiber glass filter and pH

corrected at 7.5 according to Gert Jan de Maagd

(2000). Samples were placed in 4-ml vials with a Teflon-

faced septum. A manual solid-phase microextraction

holder was used with unbonded fibers of polydimethyl-

siloxane (PDMS) at a stationary phase of 100- and 7-mm

film thickness and one of 85 mm of polyacrylate (PAC)

(Supelco, Bellefonte, PA, USA). These were conditioned

as follows: PDMS 100 at 250 1C for 1h, PDMS 7 at

320 1C for 3 h, and PAC 85 at a 3001C gas chromato-

graph (GC) injector temperature for 2 h. The fibers were

immersed into the sample, which was heated to 25 1C

and agitated with a magnetic stirring bar at 560 rpm.

The adsorption time was 1 h. The fibers were then

immediately inserted into the GC injector and the

analysis was carried out. The desorption time was 4 minand the desorption temperature was set at 2801C. A

Shimadzu gas chromatograph 17A V 1.3 model with

mass spectrometer QP 5050A and an MS Workstation

Class 5000 (Shimadzu Corp., 1999) were used. Experi-

mental conditions included PTE-5 fused-silica capillary

column 30 m 0.25 mm 0.25-mm film thickness (Su-

pelco); a linear velocity of carrier Helio, 36.2 cm/s,

splitless, with sampling time of 4 min and total flow of

11.7 mL/min; a temperature program of 100 1C for 2 min

heated to a final temperature of 280 1C at 10 1C/min and

held at this temperature for 10min; an injector

temperature of 2801C; and a capillary interface tem-

perature of 280 1C. The mass spectrometer detector scan

mode ranged from 50 to 350m/z.

Computer searching of the acquired mass spectral

data against libraries of reference mass spectra was used.

The NIST (1998) and Wiley Library (1995) libraries of

mass spectra were used. The NIST database reference

mass spectra was of 142,341 compounds with 99% of

molecular formula associated. Wiley had 229,119

compounds with more than 40% of the molecular

structure associated. PBM o probability-based matching

algorithm for calculating the similarity index (SI)

between spectra was used. The SI quantitatively

expresses the difference between the spectrum of anunknown sample and a spectrum registered in a library.

In general, the differences between the respective

intensities of the spectral peaks at a certain mass

number are determined and the smaller those differences

are, the greater the degree of similarity. The following

equation was used:

SI 1 Ium=z Itm=z Pm=zm=z

Ium=z Itm=z

26666

4

37777

5

100:

where Ium=z is the relative spectral intensity for massnumber m=z of the mass spectrum of an unknownsample. Itm=z is the relative spectral intensity for massnumber m=z of the mass spectrum registered in a library.If the patterns of the two mass spectra are identical the

SI is 100, and, conversely, if they are completely

different the SI will be 0. We take into account

compounds with a SI greater than 70. The coefficient

of partition octanol/water log Por log Kow was obtained

for each compound by using the Clog P program.

Bioconcentration factors (BCF) were determined by

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Connells equation (Connell, 1990) as follows:

log BCF 6:9 103log Kow41:85 101log Kow

3

1:55log Kow2 4:18 log Kow 4:79:

2.4. Physico-chemical characterization of liquid effluents

The following parameters were used according to

APHA-AWWA-WPCF (1998): COD, BOD, pH, alka-

linity, sulfide, sulfate, conductivity, free chlorine, am-

monium, salinity, chloride, reactive phosphorous,

nitrate, hardness, and residual solids after 10 and

120 min of settling. The majority of these are included

in the official regulations for LEs discharged into SW.

2.5. Statistical analysis

A one-way statistical analysis of variance (ANOVA)

(Po0:05) in conjunction with Dunnets test was used tocompare responses with the control using the computer

program Toxstat V 3.5 (WEST, Inc., 1996). Regression

analysis in conjunction with ANOVA was made

between mortality and organic matter data from

sediment toxicity tests using the program Statistica for

Windows.

LC50 or EC50 and their fiducial limits at 95% were

determined by a probit method using the US EPA

program V5 1.4 (US EPA, 1991; Berthouex and Brown,

1994; Sparks, 2000). Effluent samples were analyzed by

principal component analysis (PCA) to explore the

degree of correlation in the toxicity tests and PC

parameters. Two matrices were constructed, one usingthe PC parameters alone and the second considering the

PC and the toxicity indices for all species assayed. The

11 LEs were the horizontal rows of the PCA data

matrix. The PCA was performed using StatGraphics

Plus software V 2.1.

3. Results

3.1. Water quality

The range of in situ physicochemical parameters

measured for 1 year is shown in Table 1. The arithmetic

mean of the flow of the Luja n River is 1.159 m3/s with a

standard deviation of 4.513 and a coefficient of variation

of 389%. The COD and BOD values are plotted with

DO concentrations in Fig. 2.

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Table 1

The range of physico-chemical parameters measured in 150 water samples from the Luja n River

Parameter Summer Autumn Winter Spring

Total flow (m3/s) 07.44 1.312.3 110.4 0.2314.69

Dissolved oxygen (mg/L) 018.95 1.946.76 2.597.34 0.5313.11

Conductivity (mS/cm) 159011790 12006500 10205000 6005500

Salinity (%)[AU: What unit intended here?] 0.013.00 0.011.90 0.011.79 0.012.5

Turbidity (nephelometric units) 90 to 1000 50700 50400 120 to 41000

Temperature (1C) 1827.5 1219 813 1024

PH 8.511.4 89.2 7.69 810.9

Fig. 2. The DO concentration, BOD, and COD averages of all sampling sites. Values are in mg/L.

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3.2. Surface water toxicity tests

Nontoxicity effects were observed for the algal tests in

the majority of the samples. On the contrary, a

stimulation of algal growth ranging between 20% and

70% with respect to the control was observed for all

samples taken in winter and spring. This could berelated to the accumulation of nutrients or their

improved bioavailability, which occurs during this

period in aquatic environments (Margalef, 1983).

Samples taken in the summer close to pipe discharges

of chemical industries, in the cities of Mercedes and

Luja n, showed toxicity of about 60% inhibition,

conductivity values of 12,000mS/cm, and a pH of 11

(Fig. 3).

In the majority of experiments with D. spinulata,

immobility was not observed in the organisms exposed

or was lower than 15%; only in five experiments was the

immobility 100% after 48 h of exposure. Nontoxicity

effects were observed in D. spinulata in the majority of

samples, excepts in Sites 46 in the summer samples and

Site 4 in the winter samples (significant differences,

ANOVADunnettest at Po0:05). These results coin-cided when high values of conductivity and salinity and

low values of DO were recorded. Fish mortality was not

recorded in any surface samples.

3.3. Effluent toxicity tests and physico-chemical

parameters

Physicochemical data and the results of toxicity tests

for each LE are reported in Table 2.Fig. 4 shows the PCA results taking the PC data of

each effluent. Three groups were obtained: Group a,

Mme, MCMe, and MS formed for domestic liquids;

Group b, TL1, TL2, TMCMe, FS, Cme, ML, and CL

(this joined mainly chemical effluents or mixed with

organics); and Group c, with only BL as a member (M,

municipal; T, textile; C, chemical; F, food; B, biotech-

nology; L, city of Luja n; Me, city of Mercedes; S, city of

Suipacha.; 1, component 1; 2, component 2). Group b

was discriminated in PCA analysis according to specific

PC values regarding pH, conductivity, sulfate, ammo-nium, BOD, and COD variables.

However, PCA performed with all parameters, PC

plus the toxicity index (Figs. 5 and 6), defines the

following groups: Group a, MCMe, Mme, and MS;

Group b, FS, TMCMe, and Cme; Group c, TL2, TL1,

ML, and CL; and Group d, BL. The latter is the more

toxic effluent assayed and between Groups a, b, and c it

is possible to say that there are differences in both PC

and toxicity values, defining the rank of toxicity as

aoboc.

3.4. Sediment toxicity tests

Sediment samples were toxic in sites close to industrial

and municipal discharges (Sites 46). There was a

relationship between organic matter concentration and

individual mortality (Fig. 7). Sediment pH values ranged

from 6 to 7.6; sulfide concentrations were not detectable;

ionized ammonia (NH4+) was 50600 mg/L. Higher

values of NH4+ were found next to higher organic

matter contents (OMC) and ranged between 350 and

600 mg/L for sampling Sites 46.

3.5. Bioaccumulatable compounds

Table 3 indicates a qualitative screening of the

bioaccumulatable compounds and suspected hormonal

disruptors found.

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Time relative scale (days)

20

40

60

80

100

120

140

160

180

200

-5 5 15 25 35 45 5

algal growth

Stimulation growth %

Inhibition growth %

summerautumn

winter springsampling points order

12

3

4

56

5

Fig. 3. Algae growth responses in the Luja n River samples. Control growth at 96 h is considered to be 100%. Growth lesser or greater than that of

the control is considered inhibition or stimulation, respectively. Growth o80 or 4120% was significant at Po0:05 (ANOVADunnets test).


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4. Discussion

Acute toxicity of SWs was infrequent for animals (fish

and invertebrates) and related to special environmental

conditions, such as samples with heavy conductivity and

salinity. On the other hand, algal growth stimulation

was observed in many of the assayed samples. It is

possible that this stimulation is related to phosphorous

(P) bioavailability, since it is a key factor that defines the

algal growth. Phosphorous is usually the limiting

nutrient for algal growth in freshwater environments.

In the regional legislation, before discharge an effluent

must meet a limit concentration of total phosphorous

(TP) of less than 10 mg/L. But TP alone is not the best

criterion for eutrophication control measures (Ekholm

and Krogerus, 1998). Fig. 3 shows that a stimulation of

growth, with respect to the control, was largely

observed, despite all controls and river samples being

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Table 2

Physico-chemicals parameters of assayed effluents, all values are expressed in mg/L

Parameter TL TL BL ML CL T+M+CM MM M+CM CM MS FS

COD 548 190 1754 468 240 792 216 36 71 159 250

BOD 300 40 890 140 50 270 110 10 20 54 90

SS 10 min 0 0 0 0.6 0 0 4 0 0.25 0 0

SS 120 min 0 0 0.1 0.9 0 0 4 0.1 0.25 0 0pH 11.42 8.26 7.6 7.82 8.1 7.12 6.84 7.15 7.91 7.20 7.09

Conductivity 2900 1200 8000 1480 12,000 631 210 152 158 251 184

Salinity 2 1 5.3 0.9 5 0.32 0.09 0.06 0.07 0.11 0.08

Free chlorine 0 0.06 0.05 0.09 0.04 0 0.06 0.05 0.09 0 0.06

Sulfide 0.13 0.08 13.9 0.04 0.2 0.072 0.052 0.004 0.009 0.004 0.032

Ammonium 5.4 5.4 1214.2 28.4 100 12.5 12.9 0.20 0.25 2.9 13.6

Nitrate 4.8 3.5 11.4 1.1 3.5 13.2 10.5 32.9 13.7 14.7 14.9

Reactive phosphorous 0.14 1.49 54.13 12.33 0.1 0.81 6.53 2.09 0.68 3.21 8.88

Sulfate 103.7 147 2647.2 121 40 86 90 112 25 79 120

Alkalinity 170 65 135 60 400 600 580 510 470 630 700

Chloride 15 35 20 25 2,000 200 35 20 22 38 20

Hardness 0 17.1 58.5 19.5 130 258.1 325 334.5 152.9 372.8 219.8

Algae 17.32 100 35 4.25 71 5.61 100 100 4.3 100 6.89

Cladocerans 16.52 100 4.95 71 17.32 NT 17.32 70.71 NT NT NT

Amphipod adult 17.32 70 4.24 28.98 70.7 NT 30.33 55.82 NT NT NT

Amphipod young 3 4.24 1.97 50.86 17.32 NT 11.77 43.75 NT NT NT

Fish 6 100 3 71 35.35 NT 2.22 6.86 NT 71 NT

Conductivity is expressed in mS/cm, salinity in %, acute toxicity endpoints as effluent percentage (%). SS are solids at 10 and 120 min of

sedimentation. NT, not acute toxicity; T, textile; B, biotechnology; C, chemical; M, municipal; F, food effluents. Superscripts: L, city of Luja n; M,

city of Mercedes; S, city of Suipacha.

Component 1 (62 %)

Component2(

17%)

BL

MMeMCMe

MS

TL1

ML

TMCMe

FS

CLTL2

-7 -5 -3 -1 1 3-1.8

-0.8

0.2

1.2

2.2

CMe

Fig. 4. Two-dimensional scattergrams corresponding to the distribu-

tion of the PC parameters of each effluent. M, municipal; T, textile; C,

chemical; F, food; B, biotechnology; L, city of Luja n; Me, city of

Mercedes; and S, city of Suipacha. The two components explained

75% of total variance.

Component 1

Component2

CL

TL2

ML

BL

CMe

TMCMe

MS

MCMe

TL1

MMe

FS

-2 0 2 4 6 8

-1.8

-0.8

0.2

1.2

2.2

Fig. 5. Two-dimensional scattergram corresponding to the distribu-

tion of the PC parameters of each effluent and the toxicity indices for

all assayed species. M, municipal; T, textile; C, chemical; F, food; B,

biotechnology; L, city of Luja n; Me, city of Mercedes; and S, city of

Suipacha. The two components explained 75% of total variance.

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spiked with the same PO4-P concentrations. Algae are

able to use several sources of P, such as reactive and

nonreactive phosphorous and particulate P. In addition,

increased bioavailability due to strongly alkaline condi-

tions likely occurs during toxicity testing carried out

with algae (Persson, 1990). Also, algal toxicity may be

correlated significantly with some components of SWs.Graff et al. (2003) found that parameters like COD,

hardness, conductivity, total suspended solids, and

dissolved organic carbon were significant factors affect-

ing toxicity from river waters.

The importance of using a battery of species in the

LEs evaluation is remarked upon in this study. PCA

analysis was a good tool to express how PC parameters

and TI can together give a complete understanding of

each effluent. LEs could be grouped regarding their

organic, industrial, or mixed nature based on their

toxicity. Results from toxicity tests performed with

aquatic invertebrates seem to be explained by some PC

variables like COD or ammonium (Fig. 7). Fish and

algae were not linked with any effluent-based PC

measured. This would confirm the idea that an effluent

might be within permitted PC limits yet still be toxic.

The discharge of sewage into SWs represents a major

source of pollutants globally (Walker et al., 1996). Wang

et al. (2003) showed that municipal sewage treatment

plants were contributing to the total biological toxicityemission of receiving water bodies. They remarked that

the preservation of the ecology of rivers and lakes

requires regulations that consider ecotoxicity.

Domestic wastes are discharged mainly into sewage

systems. Industrial wastes are discharged either into

sewage systems or directly into SWs. Several treatments

may be applied to these effluents to improve their

quality before they are discharged. The more popular

wastewater treatment plant consists of a suspended and

aerated culture of microorganisms forming microstruc-

tures called flocs or activated sludges. Others include

oxidation lagoons, biofilters, and bed reactors. All of

these treatments improve the water quality of the

effluents in terms of COD, BOD, and suspended solids

removal; further treatments will remove mainly phos-

phate and nitrate. Before effluents are discharged, they

must meet the threshold values for these parameters as

defined on environmental legislation. The aim of this

regulation is to prevent oxygen depletion and eutrophi-

cation of water bodies. But it does not include limits on

toxicity and the toxic load of effluents into the

environment. Buenos Aires Province has no regulatory

protocol to measure either acute or chronic ecotoxicity.

In this work, we have shown that LEs being discharged

into the Luja n River are ecotoxic even when they meetthe legal requirements for an authorized discharge.

The toxic unit (TU) measures the strength of each LE

assessed. It is expressed as a fraction or proportion of its

lethal or effective threshold concentration: actual

percentage of the (LE)/L(E)C50. If this number is

ARTICLE IN PRESS

Component 1

Component2

COD

Algae

ALK

NH4

Cond

NO3

AnfA

AnfC

daph

Fish

PO4

-2.1 -0.1 1.9 3.9 5.9 7.9

-1.8

-0.8

0.2

1.2

2.2

Fig. 6. Biplot of two-dimensional scattergram corresponding to the

distribution of PC parameters of each effluent and the toxicity indices

for all assayed species. The partial correlation for each variable is

shown. The two components explained 75% of total variance.

Organic matter OM (%)

MortalityM

(%)

0

20

40

60

80

100

120

0 4 8 12 16 20 24 28 32

Regression95% confid.

R2

= 0.905

M = 3.929 * OM - 10.85Fisher's value = 36.06 p < 0.05

Los Leones S1

Suipacha S3 El durazno S2

Las Tropas S5

Mercedes S4 La Loma S6

Fig. 7. Regression analysis (significant at Po0:05) between OMC in sediments and mortality recorded for the amphipod H. curvispina. The Fvaluewas 14.11 at Po0:05; the confidence interval of the slopes was 1.096.61 at Po0:05: S1 is Site 1, S2 is Site 2, etc.


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greater than 1, more than half of a group of aquatic

organisms will be killed or affected by the LE. TUs were

used to calculate the toxic load of each effluent as

ToxLoad UT FLE, where FLE is the flow of LE (see

Table 4).

A frequent approach to defining an environmental

threshold of LE to avoid acute effects on native

organisms is to consider that no effect occurs when thepercentage of LE dilution in the river water is lower than

0.3 TUs (Grothe and Reed-Judkins, 1996). The toxicity

index for the more sensitive species is taken and is

compared with the expected LE dilution, taking into

account its flow and the mean flow or some critical flow

value for the river and to obtain a river concentration

value (RCV). [The RCV could also be termed the

predicted environmental concentration for each efflu-

ent.] The RCV in our study was calculated according to

the following equation:

RCV FLE=FLE FRM100;

where FLE is the flow of LE and FRM is the mean flow

for the river. Table 4 shows the RCV and TU for each

LE evaluated. Six of 11 of the LEs studied represent a

hazard in terms of acute toxicity to aquatic organisms.

The assessment factor (AF) may also be used to

extrapolate from the lowest chronic no observed effect

concentration (NOEC) to the field situation, from short

to long exposure time, and from the concentration with

acute effects to the NOEC. For each extrapolation step

a factor of 10 is suggested. Consequently, if a data set

contains only one LC(E)50 for one species, the environ-

mental concern level is estimated from LC(E)50/

10 10 10 (OECD, 1995). We use also this approach

taking an AF of 100 since our scope was to define an

acute environmental threshold. We have taken for each

LE the more sensitive species and divided it by 100 as

the acute AF. Obtained data are shown in Table 3;

according to the AF approach, we find environmental

risk only for one effluent, a chemical industry discharged

near the city of Mercedes.Another approach to defining a hazardous concentra-

tion (HC) for the substances or LEs is through

extrapolation methods. A common feature of these

methods is that they use the toxicity data for all tested

species instead of those for more sensitive species and

derive a maximum tolerable concentration or a HC

(OECD, 1995). The variability in the sensitivity of the

test species is assumed to be representative of the

variability of all species in the aquatic community. Table

4 indicates these HC values according to the models of

Wagner and Lkke (1991) and Aldenberg and Slob

(1993), both recommended methods by OECD (1995).In this case, all LEs will be hazardous for the aquatic

organisms present in the waters of the Luja n River, at

least with respect to their potential to exert acute

toxicity.

Although the SWs have not produced an acute

toxicity it is probable that a real environmental risk

exists in this freshwater environment. However, from an

empirical point of view, we must also remark that the

three approaches overestimated the environmental risk

for the assayed LEs in the order TUoAFoHC. The

breach between the LEs and SW toxicity could be

explained by chelation and the distribution process. It is

ARTICLE IN PRESS

Table 3

Organic compounds found in surface water and liquid effluents

Log Kow Log BCF Compound Effluents Sample

4.51 3.35 1,2-Dichloronaphtalene TMCMe Mercedes (4)

2 1.26 Phenol, 4-methyl ML, CL La Loma (6)

NC NC Phenol, 2-chloro-5-methyl CL La Loma (6)

0.59 2.83 Hydroquinonea TL1, TL2, ML La Loma (6), Las Tropas (5)4.79 3.33 Phenanthrene Not found La Loma (6)

8.23 3.9 p-Nonylphenola MS, FS, ML, TMCMe La Loma (6)

NC NC Nonylphenol diethoxylate ML Las Tropas (6)

3.53 2.28 4-Heptanol TL1, TL2 Las Tropas (6)

5.29 4.07 Phenol, 4,40methylethylidene,bis- Not found Las Tropas (5)

3.80 2.58 1-Butanol, 4-butoxy TL1, TL2 Las Tropas (5)

4.98 3.81 3,3-Dimethyl, 14-heptanol Not found Las Tropas (5)

3.42 2.17 1,2-Benzenedicarboxylic acid MS, ML, Cme La Loma (6)

5.19 4.32 di-n-Butyl phthalatea Ml, CL, MS, MMe Mercedes (4)

1.08 NC Morpholinea TL1, TL2, ML Mercedes (4)

4.79 3.99 Diethyl phthalatea ML, TL1, TL2 Mercedes (4), La Loma (6)

3.02 1.78 Furanone, 5-ethyldihydro-5-methyl Not found Las Tropas (5)

BCF, bioconcentration factor; Kow, coefficient of partition for octanol/water; NC, not calculated; M, municipal; T, textile; C, chemical; F, food; L,

city of Luja n; Me, city of Mercedes; S, city of Suipacha; 1, component 1; 2, component 2. In parentheses are the numbers of each site sample (referFig. 1).

aDetected throughout the sampling year.

W.D. Di Marzio et al. / Ecotoxicology and Environmental Safety 61 (2005) 380391388


10/12

known that humic and fulvic acids reduce the bioavail-

ability of heavy metals. Organic compounds could reach

bottom sediments by being adsorbed by suspended

solids. Biodegradation of these compounds is also

possible, but the results showed a permanent deficit of

oxygen in all sampling sites, indicating an oxygen-

stressed environment with a COD:BOD:DO relation-

ship as high as 350:25:5 (see Fig. 2). In that way, aerobic

processes could be reduced, resulting in an increasing

environmental half-life for these organic chemicals.

In this scenario, one would expect to find toxicity in

the sediments. This is related to interstitial waterconcentrations of chemicals and is a function of the

concentrations sorbed to sediment organic carbon under

equilibrium conditions. It has been reported that the

toxicity of sediments is largely due to interstitial water

(Swartz and Di Toro, 1997). Organic matter plays an

important part in determining chemical bioavailability.

Higher OMC increases chemical sorption, reducing the

final concentration in interstitial water (Power and

Chapman, 1992; Swartz and Di Toro, 1997). The

positive relationship between OMC and sediment

toxicity on H. curvispina would be related to higher

NH4+

concentrations, which were measured in samplingpoints with lesser DO concentrations. High values of

NH4+ concentrations could be able to mask chronic

effects due to other organic and inorganic chemicals. In

these environments nitrification processes could be

reduced. The results obtained with sediment toxicity

tests can be an important tool for making decisions

regarding the extent of remedial action needed for the

Mercedes, Las Tropas, and La Loma contaminated

sites. Lethal effects on fish were not found in any of the

water samples assayed. Toxicity tests with different

aquatic organisms indicated that zones with potential

acute toxicity were near the points of discharge of LEs

from the cities of Mercedes and Luja n. This acute

toxicity could be related to high conductivity, salinity,

and pH and low DO concentrations. This study

indicated that toxicity and possible eutrophication

problems were mainly located in the lower river due to

the discharge of both industrial and sewage effluents

from the cities of Mercedes and Luja n.

As was shown in Table 3, potential bioaccumulatable

compounds were found. Ester of phthalic acids,

morpholine, hydroquinone, and nonylphenol (NP) were

found in all samples taken at Sites 46 and in many of

the tested effluents. NP, an estrogen agonist, is theultimate degradation product of nonylphenol poly-

ethoxylate nonionic surfactants (NPE) and has been

reported to be an endocrine disruptor. Long-chain NPE

also breaks down into shorter-chain NPEs, with toxicity

inversely related to ethoxyl chain length. It has been

suggested that disruption of endocrine balance due to

exposure to NP might compromise the reproductive

fitness and survival of fishes (Purdom et al., 1994). NP

reduced fecundity, disrupted testosterone metabolism,

and increased production of larval storage protein in

aquatic invertebrates (DeFur et al., 1999).

Di-n-butyl phthalate (DBP) is another suspectedcompound that shows a weak estrogenic activity and

can adversely affect the endocrine systems of animals

(McNeal et al., 2000). DBP is used mainly as a specialty

plasticizer for nitrocellulose polyvinyl acetate and

polyvinyl chloride. It also is used in coatings, adhesives,

lacquers, and paper coating (WHO (World Health

Organization), 1997). DBP is biodegradable in natural

SWs with an estimated half-life in the range of 114

days, although longer in anaerobic or anoxic conditions.

The log Kow values of DBP and diethyl phthalate

indicate that they potentially could be bioaccumulated

by aquatic organisms. However, their accumulation is

ARTICLE IN PRESS

Table 4

Environmental risk assessment according to toxic unit and extrapolation methods for each assayed effluent

Toxic load RCV in TU RA 1 RCV in % HC 5% AS RA 2 HC 5% WL AF RA 3

ML 1180 2.52 R 10.70 0.02 R 0.02 0.042 R

TL1 1000 2.24 R 6.71 0.06 R 0.07 0.03 R

TL2 710 1.58 R 6.71 0.01 R 0.01 0.042 R

CL 690 1.29 R 22.34 0.15 R 0.18 0.17 RTMCMe 81.99 0.21 NR 1.18 0.01 R 0.02 0.056 R

FS 59.02 1.27 R 8.75 0.02 R 0.03 0.069 R

MS 56.40 0.12 NR 8.75 2.29 R 2.38 0.71 R

MCMe 53.35 0.13 NR 0.87 0.03 R 0.04 0.069 R

MMe 47.54 1.11 R 2.45 0.00 R 0.01 0.022 R

BL 40 0.10 NR 0.19 0.01 R 0.01 0.02 R

CMe 3.41 0.01 NR 0.04 0.01 R 0.01 0.04 NR

R, acute risk; NR, no acute risk; RCV, river concentration value, obtained with mean river flow; RA 1, risk assessment for toxic unit (TU), if

RCV40.3 risk; RA 2, risk assessment for extrapolation methods, if RCV in % 4HC (hazardous concentration) risk for 5% of species; AS,

Aldenberg and Slob (1993); WL, Wagner and Lkke (1991); RA 3, risk assessment for assessment factor (AF) ( OECD, 1995), if RCV in %

4AF risk. Toxic load is UT FLE.


11/12

influenced by the capability of an organism to metabo-

lize them. Several authors have shown the ability of fish

to metabolize DBP (WHO (World Health Organiza-

tion), 1997). The laboratory BCF for Pimephales

promelas ranged between 570 and 590 and for Cyprino-

don variegatus to 11.7. The greater BCF recorded was

1400 for the amphipod Gammarus pseudolimnaeus(WHO (World Health Organization), 1996). The theo-

retical BCF for DBP from Table 2 is 20,890, which

would confirm the aforementioned.

Hydroquinone has a multitude of uses; it is used as a

developer in black and white photography and related

graphic arts such as lithography, rotogravure, and

medical and industrial X-ray films. It is also widely

used in the manufacture of rubber antioxidants and

antiozonants, monomer inhibitors, and food antioxi-

dants to prevent deterioration in many oxidizable

products. With a log Kow of 0.59 it can be considered

that hydroquinone does not bioaccumulate. The

logBCF found in the literature for aquatic organisms

is between 1.60 and 2.94. Biodegradation of hydro-

quinone is closely related to many variables, such as pH,

temperature, and whether conditions are aerobic or

anaerobic. Its BOD/COD relationship is 0.53, indicating

that it is readily biodegradable under aerobic conditions.

It is a carcinogenic, neurotoxic, and nephrotoxic

chemical.

Morpholine is an extremely versatile chemical. It is

most important as a chemical intermediate product,

such as for the production of agrochemicals and

performance polymers (WHO (World Health Organiza-

tion), 1996). Morpholine can undergo a variety ofreactions. It behaves chemically as a secondary amine.

Under environmental and physiological conditions, the

proven animal carcinogen N-nitrosomorpholine is

formed by the reaction of solutions of nitrite or gaseous

nitrogen oxides with dilute solutions of morpholine.

Among the aquatic organisms tested, cyanobacteria and

unicellular green algae appear to be the most sensitive

taxa, with toxicity threshold values of 1.74.1 mg/L

(WHO (World Health Organization), 1996). Because of

its log Kow (1.08) it is not a bioaccumulatable

chemical. Morpholine is biodegraded in aerobic condi-

tions by a restricted range of microbes, which have a lowgrowth rate and a lag period greater than 8 days. The

presence of morpholine in the environment indicates the

lack of treatment of industrial wastewater or bad

operational conditions in an activated sludge plant.

5. Conclusions

A field ecotoxicological study was performed to define

the environmental status of the Luja n River plain. The

toxic load was quantified, and four industries of the 11

evaluated represent 91% of the total toxic load

incorporated into the river. The environmental risk for

these effluents exists, but it was overestimated, although

different risk evaluation methods were used. Even if

SWs did not show acute toxicity, it is possible that

aquatic organisms are bioaccumulating organic com-

pounds. Besides, they are exposed to hormonally

disrupting chemicals. The environmental half-life ofthese organic compounds could be increased since the

permanent lack of DO slows all aerobic biodegradation

process. It is also possible that the sediment remains a

natural reservoir of chemicals. Although we recorded

sediment toxicity, this would be an overestimate due to a

high interstitial ammonium concentration.

Acknowledgments

The authors thank Jean Franc-ois Masfaraud (ESE,

Universite de Metz, Metz, France) for his assistance inPCA analysis. The research was supported by grants

from the Departamento de Ciencias Ba sicas and

SECYT of Universidad Nacional de Luja n, Argentina,

and from the Agregadura Cientfica de la Ambasciata

dItalia en Buenos Aires, Argentina.

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riskassessment of domestic and industrial efﬂuents unloaded into a freshwater environment

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