applied environmental science - diva...

HALMSTAD UNIVERSITY

SCHOOL OF BUSINESS AND ENGINEERING

Applied Environmental Science

Ecological Risk Assessment of Salts in

Swedish Freshwater Ecosystem

----A preliminary assessment for invertebrates and vertebrates

JIANG Huan

Supervisor: Sylvia Waara

Master Thesis in Applied Environmental Science, 15 Credits

Halmstad University, 2011/6

Ecological Risk Assessment of Salts in the Swedish Freshwater Ecosystem

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Abstract

Increasing salinity in freshwater ecosystems is considered as a serious environmental

problem in all inhabited continents. In order to know whether Swedish freshwater is at

risk an ecological risk assessment for some organism groups has been conducted for

seven kinds of salt (NaCl, KCl, Na2SO4, K2SO4, MgCl2, CaCl2, MgSO4). The

exposure assessment data was obtained from a database containing data from a

Swedish Monitoring Program conducted in 2000. Short-term and long-term toxicity

data for vertebrates and invertebrates were obtained from the open scientific literature

and the ECOTOX database hosted by the U.S. Environmental Protection Agency.

Fixed assessment factors were used for derivation of PNEC values. For short-term

testes it was set to 1000 and for long-term testes it was set to 100 or 50. The exposure

assessment data showed that the concentration of many salts in Gotland is higher than

in other region. The effect assessment result showed that invertebrates are more

sensitive to salts than vertebrates. Most data sets were recovered for Daphnia magna

which was shown to be most sensitive to K2SO4 and KCl. Very high risk quotients

were obtained for many Swedish freshwater ecosystems even though many of them

have a high biodiversity. The reason for this is unclear but it could be due to the size

of the fixed assessment factors which in general are used for persistent pollutants but

might not be suitable for salts. Another plausible explanation is that the treatment of

the effect data to fit the exposure data is not adequate and other methods have to be

explored.

Keywords: Salinity, Salt, Sweden, Freshwater, Risk Assessment.


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Abbreviations

PNEC Predicted No Effect Concentration

PEC Predicted Environmental Concentration

RQ Risk Quotients

EC50 Effect concentration to 50% of test organisms

LC50 Lethal concentration to 50% of test organisms

NOEC No Observed Effect Concentration


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Content

Abstract ................................................................................................................... 1

Abbreviations .......................................................................................................... 2

Content .................................................................................................................... 3

1. Introduction ...................................................................................................... 5

2. Background ....................................................................................................... 6

2.1. Description of Swedish ecological freshwater ecosystem ...................... 6

2.2. Source of high concentration of salt in freshwater ecosystem............... 6

2.2.1. Road salt ....................................................................................... 6

2.2.2. Landfill leachate ........................................................................... 7

2.3. Effect of salt on invertebrate and vertebrate ......................................... 7

2.4. Description of Ecological risk assessment.............................................. 7

2.4.1. Hazard Identification ................................................................... 8

2.4.2. Ecological Exposure Assessment .................................................. 8

2.4.3. Ecological Effect Assessment........................................................ 8

2.4.4. Risk Characterization .................................................................. 8

3. Material and Methods ...................................................................................... 9

3.1. Hazard Identification ............................................................................. 9

3.2. Environmental Exposure Assessment .................................................... 9

3.3. Environmental Effect Assessment .......................................................... 9

3.3.1. Data collection for Effect Assessment .......................................... 9

3.3.2. Calculation of PNEC .................................................................. 10

3.4. Risk Characterization .......................................................................... 10

4. Result and Discussion ..................................................................................... 13

4.1. Environmental Exposure Assessment .................................................. 13

4.2. Environmental Effect Assessment ........................................................ 16

4.2.1. The biology of organisms used for studying the effect of salts .. 16

4.2.2. KCl .............................................................................................. 16

4.2.3. NaCl ............................................................................................ 16

4.2.4. MgCl2 .......................................................................................... 17

4.2.5. CaCl2 ........................................................................................... 28

4.2.6. K2SO4 .......................................................................................... 28

4.2.7. Na2SO4 ........................................................................................ 28

4.2.8. MgSO4 ......................................................................................... 29

4.2.9. PNEC values ............................................................................... 29

4.2.10. Sensitivity of Daphnia magna to different salts ........................ 30

4.2.11. General overview of PNEC values ............................................. 30

4.3. Risk Characterization .......................................................................... 31

4.3.1. RQ result for Chloride ............................................................... 31

4.3.2. RQ results for Sulfate ................................................................. 31

4.3.3. RQ results for Sodium ................................................................ 31


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4.3.4. RQ results for Potassium............................................................ 31

4.3.5. RQ results for Magnesium ......................................................... 32

4.3.6. RQ results for Calcium............................................................... 32

4.3.7. General overview of RQ values .................................................. 32

5. Conclusion....................................................................................................... 41

Acknowledgement ................................................................................................. 42

References .............................................................................................................. 43


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1. Introduction

Salinization is a serious environmental issue. Although salts are natural components

of the freshwater ecosystem, increasing concentrations of salts in water have a great

effect on freshwater aquatic ecosystems (Dunlop et al., 2008). With the increasing of

salinity levels, the species richness and growth of freshwater biota is decreasing (Hart

et al., 1991). In recent years the frequent use of road salt in Sweden may cause high

salt concentrations in the Swedish freshwater ecosystem. Many constructed wetlands

were applied in many fields to solve the problem of eutrophication. If the wetlands

were not treated well this may increase the salt level in wetland (Nielsen et al., 2003).

Some studies about salt toxicity have been done recent years, but few researches

about the salinity tolerance of plant, so this study is only focus on the salinity

tolerance of invertebrate and vertebrate. Sweden has 21 regions and it has many

freshwater resources it is therefore of importance to know whether the salt level in

Sweden pose a risk to the freshwater ecosystem.

According to the research work by (Tietge et al., 1997), the major toxic ions are Na+,

K+, Mg

2+, Ca

2+, Cl

-, SO4

2- and HCO-. While in another paper (Mount et al., 1997)

state that NaCl, Na2SO4, NaHCO3, KCl, K2SO4, KHCO3, CaCl2, CaSO4, MgCl2 and

MgSO4 are considered as major toxicants in freshwater test. So this study is mainly

focused on compounds NaCl, Na2SO4, NaHCO3, KCl, K2SO4, KHCO3, CaCl2, CaSO4,

MgCl2 and MgSO4. As only a very limited amount of data could be found about the

toxicities of CaSO4, NaHCO3, KHCO3 these salt were excluded from the study.

Therefore in this study only a risk assessment of NaCl, KCl, Na2SO4, K2SO4, MgCl2,

CaCl2, MgSO4 in Sweden freshwater ecosystems has been conducted.

The specific aims of this study were to:

- Conduct an ecological risk assessment of K+, Na

+, Mg

2+, Ca

2+, Cl

- and SO4

2-

in Swedish lakes and water courses.

- By comparing effect data from different species, identify which kind of

species that is the most sensitive one, and which compound that is the most

toxic to certain species.

- Quantify the potential threat of salts to freshwater ecosystem by conduct an

ecological risk assessments according to the European guidelines, and use the

predicted environmental concentrations from Sweden to predict the risk of

salinity in Sweden.

- Provide some data to support the decision making regarding the risk of

salinization in Swedish lakes and water courses.


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2. Background

2.1. Description of Swedish ecological freshwater ecosystem

Freshwater ecosystems are aquatic systems that contain drinkable water or water with

almost no salt content. Lakes and ponds, reservoirs, wetland, rivers and streams and

ground water are the major resources of freshwater. Freshwater is the main drinking

water resources for human and animals on the earth. Some major groups of organisms

known to inhabit freshwater ecosystems include vertebrates (e.g., fish, amphibians,

reptiles, birds, and mammals), invertebrates (e.g., protozoan, myxozoans, rotifers,

worms, and mollusks), plants, algae, fungi, and bacteria. Infectious agents such as

viruses may also be present. Periphyton, macrophytes (aquatic plants), insects, fish,

and amphibians are also found in freshwater environments (United State

Environmental Protection Agency, 2010).

Natural freshwater contain several ionic constituents at a higher level more than trace

level. Although ions as Na+, Ca

2+，Cl-, and some other ions are supporting aquatic life

many natural and anthropogenic sources can increase ion concentration to level toxic

o aquatic life (Mount et al., 1997). The major sources of salts like landfill leached

which bring lots of major ions and persistent pollutants into freshwater, deicing salt

bring lots of salts into streams from the roadscape or groundwater, using pesticide

also bring toxic compounds to the freshwater ecosystem. As a consequence, some

species are being threatened. Nowadays, people are much more concerned about the

safety of freshwater, because it is related to our drinking water and the conservation of

biodiversity. Study about the ecological risk assessment of salts became popular.

Sweden is the third largest country in West Europe with around 50% of land covered

by forests and about 10% of lands covered by lakes and rivers. Sweden have 21

regions, each region has different water condition. Some are in good condition, some

were polluted by people. In order to evaluate and monitor the water quality, some

sensitive species like Daphnia magna and Daphnia similis were used to test the water

quality. All test procedures assume that if the most sensitive species can stand the

certain concentration of toxicants, other species will not affected by the toxicants and

the water quality can be approved. This study used exposure data from a Nature

Survey conducted in 2000 (Swedish Environmental Protection Agencya, 2011) and

the previous toxicity test result to see each region’s water condition and see whether

the salt in Swedish freshwater have a risk to organisms.

2.2. Source of high concentration of salt in freshwater ecosystem

2.2.1. Road salt

The primary compound of road salt is sodium chloride. It is widely used worldwide to

aid in snow and ice removal. With the increasing of population pressures, the level of

migration from urban communities to suburbs, and the increasing commuting suggest


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a need for higher usage of road salts in the future. From the roadscape, large amounts

of salts are delivered to rivers and streams by surface runoff. Although the application

of road salt has reduced the number of accidents caused by snow and ice, some

reports showed that NaCl has an effect on groundwater and surface water quality

(Blasius & Merritt, 2002). Road salt has also greatly contributed to the high

concentration of salt in the freshwater ecosystem.

2.2.2. Landfill leachate

Landfill leachate is liquid that percolates through a landfill. It converts the solids into

liquid form through a combination of physical, chemical and microbial processes (Xie

et al., 2010). The leachate has large amount of organic compounds, nutrients (nitrogen,

phosphorus), minerals and heavy metals, which will contribute to the increase of salt

concentration.

2.3. Effect of salt on invertebrate and vertebrate

- Invertebrates

Invertebrates are more sensitive to salt in freshwater compared to other species. From

research (Blasius & Merritt, 2002), the author demonstrated that high concentration of

NaCl may affect the movement of many kinds of invertebrate like Gammarus

(Amphipoda), and two species of limnephilid caddisflie. The survival of most

freshwater invertebrates dramatically decreased at water salinity between minimum

(0-20mg/L) and maximum values (>8g/L). (Berezina, 2003) When invertebrate

expose to high concentration of salt their heart rate will increase or decrease appetite.

With the increasing of salinity level, invertebrates become immobilized and

eventually die.

- Vertebrates

Fish are the most common vertebrates in freshwater. Fish are usually used as an

indicator for testing whether there is a risk for an ecological system. Several large

families of fishes are observably so strictly to freshwater, it’s hard to find them in

salinities approaching that of the sea(Myers, 1949). In most species egg fertilization

and incubation, yolk sac resorption, early embryogenesis, swim bladder inflation and

larval growth are dependent on salinity. For larger fish, the growth of fish is

controlled by salinity (Boeuf & Payan, 2001).

2.4. Description of Ecological risk assessment

An ecological risk assessment is the determination of a quantitative value of risk

about the specific situation and the assessment of the possible threat. The whole

ecological risk assessment consists of four parts. These are: hazard identification,

ecological exposure assessment, ecological effect assessment and risk

characterization.


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2.4.1. Hazard Identification

Hazard identification aims to determine the potential adverse effects of salt by

reviewing scientific articles.

2.4.2. Ecological Exposure Assessment

The ecological exposure assessment aims to determine the contaminant concentration

in the targeted ecosystem. It will also determine the predicted environmental

concentration by collecting data from authoritative organization.

2.4.3. Ecological Effect Assessment

Ecological effect assessment aims to find out the most sensitive species to each

contaminant and the highest concentration the species can tolerate over a long time.

The response of species to toxicants are showed in two ways, one is acute response

another is chronic response. Acute response like LC50 (lethal concentration to 50% of

test organisms) and EC50 (effect concentration to 50% of test organisms), they are all

test the short-term response of organisms to toxicants. Chronic responses like NOEC

(No Observed Effect Concentration) show the long-term response of organisms to

toxicants. The predicted no environmental concentration is calculated by using an

assessment factor. Assessment factors will consider the value of data and reduce the

uncertainty of the general factors that under certain circumstances may be changed.

2.4.4. Risk Characterization

Risk characterization aims to quantify the potential risk of contaminants to the

concrete situation.

This is usually presented for a selected chemical as a ratio between a measured or

predicted concentration in the environment as a PEC–value (Predicted Environmental

Concentration) and the result from an effect assessment as a PNEC-value (Predicted

No Effect Concentration).


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3. Material and Methods

The whole study followed the European Chemicals Technical Guidance Document on

Risk Assessment Part 2 (European Commission, 2003) to evaluate the salt risk for

Swedish lakes and water courses. The general procedure is showed in Figure 1. The

risk assessment included four parts: the hazard identification, the environmental

exposure assessment, the environmental effect assessment and the risk

characterization. The procedures are shortly described below:

3.1. Hazard Identification

In the first instance, it is necessary to identify the major compound of salts in the

freshwater ecosystem. Several articles were read to find out which compounds are

more toxic to the ecosystem. According to the research work by (Tietge et al., 1996),

the major toxic ions are Na+, K

+, Mg

2+, Ca

2+, Cl

-, SO4

2- and HCO-. While in another

paper (Mount et al., 1997) NaCl, Na2SO4, NaHCO3, KCl, K2SO4, KHCO3, CaCl2,

CaSO4, MgCl2 and MgSO4 were considered as major toxicants in freshwater toxicity

test. Therefore, the intent of this study was to focus on the following compounds:

NaCl, Na2SO4, NaHCO3, KCl, K2SO4, KHCO3, CaCl2, CaSO4, MgCl2 and MgSO4.

As only a few data could be found about the toxicities of CaSO4, NaHCO3, KHCO3

only effect data for NaCl, KCl, Na2SO4, K2SO4, MgCl2, CaCl2, MgSO4 in Sweden

freshwater was used for derivation of RQs.

3.2. Environmental Exposure Assessment

Measured data was extracted from databases hosted by the Department of Aquatic

Sciences and Assessment, Swedish Agricultural University, Uppsala, Sweden for the

Swedish Natural Protection Agency. Data was obtained from a National Survey

Program in 2000 (Riksinventering), because the research in 2000 is more complete

than in other years. The data is only available in Swedish at the present time. This

study focus on the environmental concentration of the following ions: K+, Na

+, Mg

2+,

Ca2+

, Cl- and SO4

2-.

The measured data from each region in Sweden was compiled and a PECmax value and

a PECmin value for each region were calculated using the measured data.

3.3. Environmental Effect Assessment

3.3.1. Data collection for Effect Assessment

The U.S. Environmental Protection Agency ECOTOX database (United State

Environmental Protection Agencyb, 2011) was used to identify report and articles with

relevant toxicity data. The information was used to retrieve the original articles

through the library databases from Halmstad University.

Only a few articles provide the toxicity data in ionic forms, so this study only


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collected the toxic data for salts.

The key words used in the search process were: salt, salinity, tolerance, NaCl, KCl,

Na2SO4, K2SO4, MgCl2, CaCl2, MgSO4, CaSO4, salt effect, EC50, LC50, NOEC,

freshwater, ecosystem.

3.3.2. Calculation of PNEC

Most data collected in this study were toxicity values for fish and water fleas. The

ecotoxicity data was evaluated for both the completeness and the adequacy. After the

evaluation of data, the PNEC was calculated by using fixed assessment factors. The

assessment factors are showed in Table 1.

Table 1. Fixed Assessment factors used to derive a PNECaquatic (European Commission,

2003)

Available data Assessment factor

At least one short-term L(E)C50 from

each of three trophic levels of the

baseset (fish, Daphnia and algae)

1000

One long-term NOEC (either fish or

Daphnia) 100

Two long-term NOECs from species

representing two trophic level (fish and

/or Daphnia and/or algae)

50

Long-term NOECs from at least three

species (normally fish, Daphnia and

algae) representing three trophic levels

10

Species sensitivity distribution (SSD)

method

5-1

(to be fully justified case by case)

Field data or model ecosystems Reviewed on a case by case basis

PNEC ensures an overall protection of the environment. It assumes the ecosystems

sensitivity depends on the most sensitive species in the ecosystem and protecting the

structure of ecosystem will protect the community function. By using these factors to

calculate PNEC it will reduce the difference between different tolerance values.

In the case of this study, assessment factor 1000, 100 and 50 were used to calculate

the PNEC depending upon the number and type of effect data obtained.

3.4. Risk Characterization

The quantitative risk characterizations were carried out by calculating PEC/PNEC

ratio (risk quotients) with the exposure assessment and the dose

concentration-response (effect) assessment.


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- In this study the unit of PEC values was converted from mekv into mmol/L to

make all data’s unit into mmol/L. 1 mekv= 1/∣x∣mmol/L, x refers to the

number of electron lost or got in one compound. For example, if the

concentration of SO42-

is 1 mekv, then it also can also be express as 0.5

mmol/L.

- In order to compare all the toxicity data easily, all units of toxicity data were

converted to mmol/L to make all units the same. Some data with unit mg/L, in

this study I used the data to divide the compound’s molecular weight, then I

got the data in unit mmol/L. For example, the concentration of NaCl is 1

mg/L, the concentration also can express like 0.001 g/L / 58.44 g/mol =

0.0171 mmol/L.

- The PNEC values for salts were used to calculate several ionic PNEC values

of each salt i.e. for NaCl an ionic PNEC values for Na and one for Cl was

derived.

- Predict the risk of each salt by using RQ.

RQ = PEC / PEC

If RQ > 1, there is a risk of the specific ion.

IF RQ < 1, there is no risk of the specific ion.

Since the RQ for each ion was made based upon PNEC values obtained from salts, the

combined ions have not been taken into account. The results derived by RQ may not

be quite accurate, but no other method is available at the present time unless all values

were converted to conductivity.


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Figure 1. General procedure for environmental risk assessment. Redrawn from

(European Commission, 2003)


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4. Result and Discussion

The major salts considered in this study were NaCl, KCl, Na2SO4, K2SO4, MgCl2,

CaCl2, and MgSO4.

The major ions considered in this research were chloride (Cl-), sulfate (SO4

2-), sodium

(Na+), potassium (K

+), magnesium (Mg

2+) and calcium (Ca

2+).

4.1. Environmental Exposure Assessment

The exposure assessment data were obtained from Department of Aquatic Sciences

and Assessment, Swedish Agricultural University, Uppsala, Sweden. The data

presents the concentration of compounds in 2000. The data contain the highest

(PECmax) and lowest concentrations (PECmin) of chloride, fluoride, sulphate, sodium,

potassium, calcium and magnesium from different region. The data is shown in Table

2.

From Table 2, it is clear that the concentrations of major ions in freshwater ecosystem

in Gotland are quite high. This is probably due to the bedrock consisting of limestone

and the penetration of sea water from the Baltic Sea into the groundwater sources.


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Table 2. Measured concentrations of ions from different regions of a administration that were used as PEC values (Swedish Environmental

Protection Agency, 2000)

PEC

Administrative region Chloride（mmol/L） Sulfate (mmol/L) Sodium (mmol/L) Potassium (mmol/L) Magnesium (mmol/L) Calcium (mmol/L)

Max min max min max Min max min max min max min

Stockholms 10.63 0.054 1.3495 0.0305 7.861 0.068 0.249 0.006 1.0625 0.0225 2.691 0.052

Uppsala 0.954 0.05 2.074 0.01 1.239 0.097 0.151 0.01 0.5635 0.041 2.456 0.1255

Södermanlands 0.75 0.047 0.28 0.027 0.751 0.067 0.1 0.006 0.243 0.023 0.662 0.039

Östergötlands 0.787 0.055 1.2055 0.0165 0.799 0.076 0.135 0.009 0.271 0.02 2.6705 0.032

Jönköpings 0.58 0.068 0.481 0.0155 0.848 0.078 0.108 0.009 0.2315 0.0205 1.09 0.0345

Kronobergs 0.918 0.114 0.162 0.029 0.912 0.141 0.088 0.006 0.133 0.0295 0.3405 0.028

Kalmar 1.639 0.075 0.266 0.037 1.369 0.103 0.162 0.01 0.2485 0.036 0.4925 0.059

Gotlands 96.07 0.171 4.871 0.093 54.942 0.176 1.83 0.017 7.3075 0.091 2.9985 0.976

Blekinge 0.492 0.156 0.167 0.0255 0.615 0.198 0.061 0.012 0.1205 0.041 0.483 0.0635

Skåne 6.059 0.125 1.5275 0.025 4.282 0.174 0.172 0.013 1.157 0.028 3.2655 0.034

Hallands 0.47 0.115 0.187 0.0355 0.46 0.123 0.131 0.007 0.2425 0.0205 0.3425 0.012

Västra Götalands 65.838 0.067 3.295 0.012 41.71 0.075 1.312 0.005 5.2015 0.013 2.352 0.0065

Värmlands 0.947 0.017 0.0655 0.0055 0.9 0.025 0.052 0.002 0.093 0.0065 0.3705 0.015

Örebro 0.285 0.033 0.248 0.0135 0.24 0.039 0.08 0.004 0.1185 0.0135 1.284 0.019

Västmanlands 0.788 0.033 0.2445 0.012 0.725 0.047 0.11 0.004 0.2245 0.012 0.6685 0.0185

Dalarnas 0.24 0.003 2.846 0.0035 0.484 0.008 0.434 0 0.8295 0.002 2.401 0.002

Gävleborgs 0.559 0.008 0.3115 0.005 0.824 0.024 0.203 0.003 0.195 0.005 1.161 0.0155

Västernorrlands 0.544 0.011 0.1095 0.0085 0.556 0.029 0.092 0.002 0.139 0.009 0.324 0.018

Jämtlands 0.1 0.004 0.2885 0.004 0.12 0.009 0.039 0 0.281 0.002 1.78 0.003


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Västerbottens 4.017 0.004 11.922 0.003 3.068 0.006 0.156 0 3.015 0.003 3.2085 0.003

Norrbottens 0.264 0.003 1.3365 0.0025 0.467 0.004 0.146 0 0.3515 0.0015 1.524 0.0015

max 96.07 0.171 11.922 0.0305 54.942 0.918 1.83 0.017 7.3075 0.091 3.2655 0.796

min 0.1 0.003 0.0655 0.0025 0.12 0.004 0.039 0 0.093 0.0015 0.324 0.0015

*Data with underline showed the highest PEC value in Sweden


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4.2. Environmental Effect Assessment

4.2.1. The biology of organisms used for studying the effect of salts

In Table 3 and Table 4 biological information for the species included in the effect

assessment is presented.

4.2.2. KCl

- Data comparison

In Table 5, for the short-term data, 1.851 mmol/L is the lowest concentration;

Dreissena polymorpha is the most sensitive species to KCl.

For the long-term data, there are three toxicity data for fish; the most sensitive fish is

Pimephales promelas with a lowest value of 6.7 mmol/L. In the table 5, there are two

sets of data for Daphnia magna with the same exposure duration and age of organism,

but the values of them are different (9.926 mmol/L and 14.968-15.272 mmol/L

respectively), it may due to the different test parameters used in the experiment.

For the species group crustaceans, although the values are different, the difference are

not significant, they are all around 10 mmol/L, the most sensitive species to KCl is

Ceriodaphnia dubia.

For the fishes, the highest value comes from hepatocytes, the reason may due to the

short test duration and that cell lines was used. Among fish, the most sensitive species

to KCl is Pimephales promelas.

- Calculation of PNECKCl

In Table 5, three long-term NOECs from species representing one trophic level (fish)

is presented, fixed assessment factor 50 should be used. The lowest NOEC is higher

than the short term 24h-LC50 of Dreissena polymorpha, so according to the European

Commission Guideline the data of Dreissena polymorpha is used and a fixed factor of

100 to calculate PNECKCl.

PNECKCl = 1.851mmol/L / 100 = 0.01851 mmol/L

4.2.3. NaCl

- Data comparison

It can be seen in Table 6, for the short-term data that, there are five data sets for

Daphnia magna. The test parameters in the different experiments don’t seem to vary,

but there is still a difference in effect values as the data ranges from 28.421 mmol/L to

93.767mmol/L. Some differences can be explained by the use of different diets for

Daphnia magna or the use of different clones. The short-term data also included three

data for fish; the data for Carassius auratus are lower than that of Oncorhynchus

mykiss, this may due to the different exposure duration or sensitivity. For the

short-term data, the lowest value is 27.206 mmol/L.


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There are two long-term-data obtained in Table 6, one for fish and one for

Crustaceans. They were both tested for 7 days. The data for Ceriodaphnia dubia is

lower than the data for Pimephales promelas (25.666 mmol/L and 68.443 mmol/L

respectively).

For the Crustaceans group, there is one long-term data set and seven short-term data

sets, the data for Ceriodaphnia dubia is lower than the data for other species, this

indicated that Ceriodaphnia dubia is the most sensitive species to NaCl.

For the fish group, there is one long-term data set and three short-term data sets, the

lowest values come from the long-term value for Pimephales promelas

(68.443mmol/L). The differences between two data sets for Carassius auratus are

probably due to differences in the test solution range.

In all, 25.666 mmol/L is the lowest value; Ceriodaphnia dubia is the most sensitive to

NaCl.

- Calculation of PENCNaCl

In Table 6, two long-term NOECs from species representing two trophic levels (fish

and Crustaceans) are shown, so a fixed assessment factor of 50 can be used for

calculating PNECNaCl.

PNECNaCl = 25.666 mmol/L / 50 = 0.513 mmol/L

4.2.4. MgCl2

- Data comparison

All data in Table 7 are short-term data sets. Data sets are obtained from two species

(Daphnia magna and Pimephales promelas).

For the Crustaceans group, two day LC50 test for Daphnia magna has the lowest

value. Longer exposure duration shows lower toxicity values.

For the fish group, longer exposure duration shows lower toxicity data, the lowest

value is 22.266 mmol/L.

The lowest value in Table 7 is 13.969 mmol/L for Daphnia magna, accordingly,

Daphnia magna is more sensitive to MgCl2 than Pimephales promelas.

- Calculation of PENCMgCl2

The data presented in Table 7 are all short-term LE(C)50 values from two trophic

levels (fish and Daphnia). This study assumes that the two trophic levels can present

the toxicity of MgCl2. Therefore a fixed assessment factor 1000 was used to calculate

PNECMgCl2.

PNECMgCl2 = 13.969 mmol/L / 1000 = 0.014 mmol/L


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Table 3. The biology of invertebrates used in the effect assessment

Species name Common

name Distribution

Life

span

Feeding

habits Size Productive habits Use

References

Ceriodaphnia dubia Water flea All over the world - - <1mm - live source food,

laboratory animal.

MBL Aquaculture,

2005

Daphnia magna Water flea Eurasia, Africa, North

America

< 2

month bacteria

5-6

mm

Sexual reproduction, sometimes it clones

itself, each produce 400 or more

generations.

fish food,

laboratory animal.

MBL Aquaculture,

2005; Koto et al.，2011

Dreissena

polymorpha

Zebra

mussel

German, America,

Poland 4-5years Particles 5.1cm

After 6-7 weeks it begins to reproduce,

may produce 30000-1000000 eggs per

year per female.

-

National Atlas of the

United States, 2005

Streptocephalus

rubicaudatus Shrimp

Africa, Australia,

Eurasia, North

America

- - - - -

Dumont & Adriaens,

2009


19

Table 4. The biology of vertebrates used in the effect assessment

Species name Common

name

Distribu

tion Life span Feeding habits Size Productive habits Use References

Carassius

auratus Goldfish East Asia

Maximum

41 years

Crustaceans, insects,

plant matter.

10cm,

0.91-2.3kg Egg hatch within 48-72h.

Game fish,

aquarium

fish.

Fishbase, 2010

Oncorhynchus

mykiss

Rainbow

trout

Asia, North

America 11 years

Insets, crustaceans, small

fish.

Maximum:

12m, 24kg

Sexually nature 2-3 years, egg

hatch in 50 days. Fishing food.

National Geographic,

2011

Pimephales

promelas

Fathead

minnow North America 3 years

A variety of aquatic

plants and animals. 66-70 mm

Sexual maturity during 1st

growing season, produce 10000

eggs in 3 month breeding season.

Baitfish, pets.

Paulson & Hatch,

2011; Montana Field

Guide, 2011

Salvelinus

fontinalis Brook trout North America 4-5 years

Crustaceans, frogs,

amphibians, insets,

molluscs, small fish.

25-65 cm,

0.3-3 kg -

Game fish

Trout Unlimited, 2011

Table 5. Short-term and long-term toxicity data for KCl Data in bold text represent the effect value used for derivation of the PNEC


20

Species Scientific

Name

Species

Common Name

Species

Group

Test

Type

Exposure

Duration

Age of

Species

Test

Temperature (℃)

weight

(g)

Length

(cm) Value (mmol/L) Reference

Ceriodaphnia

dubia Water flea Crustaceans LC50 1d <24h 20 - -

8.451

(7.914-8.451) Mount et al., 1997

Daphnia magna Water flea Crustaceans LC50 1d <24h 20 - - 9.926

(7.780-1.180) Mount et al., 1997

Daphnia magna Water flea Crustaceans EC50 1d <24h 21±1 - - 14.968-15.272 Lilius et al., 1994

Daphnia similis Water flea Crustaceans EC50 2d <16h 20 - - 9.255-15.962 Utz & Bohrer,

2001

Dreissena

polymorpha Zebra mussel Bivalve LC50 1d - - - 1.5-2.0 1.851 Fisher et al., 1991

Oncorhynchus

mykiss Rainbow trout Fish EC50 3h - 15 370 - 164.303-390.899 Lilius et al., 1994

Oncorhynchus

mykiss Rainbow trout Fish NOEC 7d 15-25d 15±1 - - 13.413-26.827

Lazorchak &

Smith, 2007

Pimephales

promelas Fathead minnow Fish NOEC 7d 4-16h 25±1 - - 6.707

Pickering et al.,

1996

Salvelinus

fontinalis Brook trout Fish NOEC 7d 30-45d 15±1 - - 26.827

Lazorchak &

Smith, 2007

Table 6. Short-term and long-term toxicity data for NaCl Data in bold text represent the effect value used for derivation of the PNEC


21

Species Scientific

Name

Species

Common

Name

Species

Group

Test

Type

Exposure

Duration

Age of

Species

Test

Temperature

(℃)

weight

(g)

Length


Ceriodaphnia

dubia Water flea Crustaceans NOEC 7d <24h 20 - - 25.666 Degraeve et al., 1992

Ceriodaphnia

dubia Water flea Crustaceans LC50 2d <24h 25±2 - -

27.206

(26.008-28.574) Harmon et al., 2003

Carassius auratusc Goldfish Fish LC50 10d - 23.5 0.38-4.02 200

Threader & Houston,

1983

Carassius auratusd Goldfish Fish LC50 10d - 23.5 - 0.38-4.02 201.1

Threader & Houston,

1983

Daphnia ambigua Water flea Crustaceans LC50 2d <24h 21±2 - - 34.222

(30.970-37.644) Harmon et al., 2003

Daphnia magna Water flea Crustaceans LC50 2d <24h 21±1 - - 93.767

(86.752-103.007)

Martınez-Jeronimo&

Martınez-Jeronimo , 2007

Daphnia magna Water flea Crustaceans EC50 2d <24h 20 - - 64.256 Arambasic et al., 1995

Daphnia magna Water flea Crustaceans EC50 1d 21±1 - - 37.37 Lilius et al., 1994


22

Daphnia magnaa Water flea Crustaceans LC50 1d - - - - 28.421 Cowgill, 1987

Daphnia magnab Water flea Crustaceans LC50 1d - - - - 38.499 Cowgill, 1987

Oncorhynchus

mykiss

Rainbow

trout Fish EC50 3h 15 370 - 304.9 Lilius et al., 1994

Pimephales

promelas

Fathead

minnow Fish NOEC 7d 4-16h 25±1 - - 68.443 Pickering et al., 1996

Sreptocephalus

rubricaudatus - Shrimp LC50 1d 18h 25±0.5 - - 52.53 Crisinel et al., 1994

a Diet: Trout chow + alfalfa

b Diet: Chlamydomonas reinhardti Dangeard

c Broader range of concentration

d Small range of concentration

Table 7. Short-term and long-term toxicity data for MgCl2 Data in bold text represent the effect value used for derivation of the PNEC


23

Species

Scientific

Name

Species

Common

Name

Species Group Test Type Exposure

Duration

Age of

Species

Test

Temperature

(℃)

weight

(g)

Length


Daphnia

magna Water flea Crustaceans LC50 1d <24h 20 - - 16.385 Mount et al., 1997

Daphnia

magna Water flea Crustaceans LC50 2d <24 20 - - 13.969 Mount et al., 1997

Pimephales

promelas

Fathead

minnow Fish LC50 1d 1-7d 25 - - 36.971 Mount et al., 1997

Pimephales

promelas

Fathead


Pimephales

promelas

Fathead


Table 8. Short-term and long-term toxicity data for CaCl2 Data in bold text represent the effect value used for derivation of the PNEC


24

Species Scientific

Name

Species Common

Name

Species

Group

Test

Type

Exposure

Duration

Age of

Species

Test Temperature

(℃)

weight

(g)

Length

(cm)

Value

(mmol/L) Reference

Daphnia magna Water flea Crustaceans LC50 1d <24h 20 - - 29.284 Mount et al.,

1997

Daphnia magna Water flea Crustaceans LC50 2d <24 20 - - 24.959 Mount et al.,

1997

Pimephales

promelas Fathead minnow Fish LC50 1d 1-7d 25 - - 60.009

Mount et al.,

1997

Pimephales


Mount et al.,

1997

Pimephales


Mount et al.,

1997

Table 9. Short-term and long-term toxicity data for K2SO4 Data in bold text represent the effect value used for derivation of the PNEC


25

Species Scientific

Name

Species

Common Name

Species

Group

Test

Type

Exposure

Duration

Age of

Species

Test Temperature

(℃)

weight

(g)

Length

(cm)

Value

(mmol/L) Reference

Daphnia magna Water flea Crustaceans LC50 1d <24h 20 - - 4.878 Mount et al.,

1997

Daphnia magna Water flea Crustaceans LC50 2d <24 20 - - 4.132 Mount et al.,

1997

Dreissena

polymorpha

Zebra mussel Bivalve LC50 1d - - - 1.5-2.0 0.643

Fisher et al.,

1991

Pimephales


Mount et al.,

1997

Pimephales


Mount et al.,

1997

Pimephales


Mount et al.,

1997

Table 10. Short-term and long-term toxicity data for Na2SO4 Data in bold text represent the effect value used for derivation of the PNEC


26

Species Scientific

Name

Species

Common Name

Species

Group

Test

Type

Exposure

Duration

Age of

Species

Test Temperature

(℃)

weight

(g)

Length


Ceriodaphnia

dubia Water flea Crustaceans LC50 7d - - - - 14.425 Soucek, 2007

Daphnia magna Water flea Crustaceans LC50 2d 24h 20 - - 60.545

(59.067-61.742)

Meyer et al.,

1985

Daphnia magna Water flea Crustaceans LC50 2d 24h 20 - - 64.246 Arambasic et

al., 1995

Pimephales

promelas Fathead minnow Fish LC50 3d 96h - - -

107.010

(101.871-112.220)

Meyer et al.,

1985

Pimephales

Promelas Fathead minnow Fish LC50 4d 1-7d 20-25 - -

56.040

(47.873-70.402)

Mount et al.,

2007

Table 11. Short-term and long-term toxicity data for MgSO4 Data in bold text represent the effect value used for derivation of the PNEC


27

Species

Scientific

Name

Species

Common

Name

Species Group Test Type Exposure

Duration

Age of

Species

Test

Temperature

(℃)

weight

(g)

Length


Daphnia

magna Water flea Crustaceans LC50 1d <24h 20 - - 19.607 Mount et al., 1997

Daphnia

magna Water flea Crustaceans LC50 2d <24 20 - - 15.12 Mount et al., 1997

Pimephales

promelas

Fathead


Pimephales

promelas

Fathead


Pimephales

promelas

Fathead



28

4.2.5. CaCl2

- Data comparison



For the crustaceans group, two days’ LC50 of Daphnia magna has the lowest value

(24.959 mmol/L).

For the fish group, three days’ LC50 of Pimephales promelas has the lowest value

(41.718 mmol/L).

The lowest value is shown in Crustaceans (24.959 mmol/L). So compared with fish

the Crustaceans are more sensitive to CaCl2. Longer exposure duration leads to lower

toxicity value.

- Calculation of PNECCaCl2

Data in Table 8 are all short-term LE(C)50 values from two trophic levels (fish and

crustaceans). This study assumes that the data from two trophic levels can present the

toxicity of CaCl2. Therefore a fixed assessment factor 1000 was used to calculate

PNECCaCl2.

PNECCaCl2 = 24.959 mmol/L / 1000 = 2.5×10-2

mmol/L

4.2.6. K2SO4

- Data comparison

All data in Table 9 are short-term data sets. Data sets are obtained from three species

(Daphnia magna, Pimephales promelas and Dreissena polymorpha).

For the crustaceans group, 2d LC50 of Daphnia magna has the lowest value (4.132

mmol/L).

For the fish group,3d LC50 of Brood Stock has the lowest value (3.902 mmol/L).

Data for Dreissena polymorpha is the lowest value in Table 9 (0.642 mmol/L).

Dreissena polymorpha are more sensitive to K2SO4 than Water fleas and fishes.

- Calculation of PNEC K2SO4

Data in Table 9 are all short-term LC50 values from two trophic levels. This study

assumes that the data from two trophic levels can present the toxicity of K2SO4.

Therefore a fixed assessment factor 1000 was used to calculate PNECK2SO4

PNEC K2SO4 = 0.643 mmol/L / 1000 = 6.43×10-4

mmol/L

4.2.7. Na2SO4

- Data comparison

All data in table 10 are short-term data sets. Data sets are obtained from three species


29

(Daphnia magna, Ceriodaphnia dubia and Pimephales promelas).

For the crustacean group, there are two kinds of data for Daphnia magna, the values

of these two kinds of data are similar (around 62 mmol/L). The toxicity value of

Ceriodaphnia dubia is lower than that of Daphnia magna (14.425 mmol/L).

For the fish group, the 4d LC50 test has a lower tolerance value (56.04 mmol/L),

while 3 hour LC50 test of Pimephales promelas has the highest tolerance value

(107.01 mmol/L), this may due to the short exposure duration.

The tolerance value of Ceriodaphnia dubia (14.425 mmol/L) is the lowest one in

Table 10, Ceriodaphnia dubia is the most sensitive species to Na2SO4.

- Calculation of PNECNa2SO4

All data in Table 10 are derived from short-term LE(C)50 values, which represents

two trophic level (crustaceans and fish). In this study, data from two trophic levels is

assumed to present the toxicity of Na2SO4. Therefore a fixed assessment factor of

1000 was used for calculating PNEC Na2SO4 value.

PNECNa2SO4 = 14.425 mmol/L / 1000 = 1.442×10-2

mmol/L

4.2.8. MgSO4

- Data comparison



For the crustaceans group, two day toxicity test data of Daphnia magna are lower

than that in one day test.

For the fish group, longer exposure duration leads to lower toxicity value.

15.12 mmol/L is the lowest tolerance value in Table 11. Daphnia magna is more

sensitive to MgSO4 than Pimephales promelas.

- Calculation of PNECMgSO4

All data in Table 11 is short-term data which only presented in two trophic levels.

This study assumed that two trophic levels can present the toxicity of MgSO4.

Therefore a fixed assessment factor 1000 was used to calculate PNECMgSO4.

PNECMgSO4 = 15.12 mmol/L / 1000 = 1.512×10-2

mmol/L

4.2.9. PNEC values

All PNEC values are showed in Table 12.


30

Table 12. PNEC value for each salt

Salt PNEC (mmol/L) Salt PNEC (mmol/L)

KCl 0.019 NaCl 0.51

MgCl2 0.014 CaCl2 0.025

K2SO4 0.00064 Na2SO4 0.014

MgSO4 0.015

From the table above, 0.00064 is the lowest value; this indicates of the salts studied

K2SO4 is the most toxic to freshwater species; K2SO4 can influence the freshwater

species in a quite low concentration.

4.2.10. Sensitivity of Daphnia magna to different salts

Each kind of salt considered in this study has at least one toxicity value of Daphnia

magna. Table 13 showed the lowest toxicity values of Daphnia magna for each salt.

Table 13. Sensitivity of Daphnia magna to salts

Salt Test Type Exposure

Duration

Effect Value

(mmol/L) Reference

KCl LC50 1d 9.9 Mount et al., 1997

NaCl LC50 1d 28.4 Cowgill, 1987

MgCl2 LC50 1d 14.01 Mount et al., 1997

CaCl2 LC50 2d 25.02 Mount et al., 1997

K2SO4 LC50 2d 4.13 Mount et al., 1997

Na2SO4 LC50 2d 60.54 Meyer et al., 1985

MgSO4 LC50 2d 15.1 Mount et al., 1997 1 [Cl

-] = 29.0 mmol/L

2 [Cl

-] = 50.0 mmol/L

3 [K

+] = 8.2 mmol/L

4 [Na

+] = 121 mmol/L

All the values presented are short term response. For the one day experiments

Daphnia magna is more sensitive to KCl. And for the two day experiments, Daphnia

magna is more sensitive to K2SO4. That indicated Daphnia magna is more sensitive to

K2SO4 and KCl than the other salts. Among the cations potassium seem to be more

toxic than the others. For the anions there is no trend.

4.2.11. General overview of PNEC values

Invertebrates appear to be more sensitive to salts than vertebrates. It may due to their

small size and short life span. Most salt toxicity data is also available for invertebrates

like Daphnia magna and Ceriodaphnia dubia.

The procedure for calculation of PNEC values using Fixed Assessment Factors values

is generally used for persistent compounds. Some Fixed assessment values are very

high like 100 and 1000. This will make the PNEC values very low and the RQ value


31

very high and this might lead to an overestimation of the risk.

4.3. Risk Characterization

4.3.1. RQ result for Chloride

Table 14 shows that all regions face a high risk of chloride from KCl, CaCl2 and

MgCl2 in freshwater since all RQmaxs values are above 1 and only in a few regions’

RQmins values are lower than 1 (Table 14). Chloride in NaCl has risk to most of the

regions except in the regions of Gävleborg and Jämtland.

The risk of chloride in NaCl is lower than for other forms of chloride.

Gotland has the highest risk of chloride.

4.3.2. RQ results for Sulfate

Table 15 shows all RQmaxs values of sulfate are higher than 1, all regions have risks of

sulfate in freshwater. Only a few RQmins values are lower than 1. The concentration of

sulfate in Sweden varies significantly which indicates some regions have risks of

sulfate while some have no risks of sulfate (eg. there is no risk of sulfate to parts of

the regions of Dalarna and Norrbotten).

The risk of sulfate in Na2SO4 is lower than that of other sulfate salts.

The region of Västerbotten suffers the highest risk of sulfate followed by Gotland.

4.3.3. RQ results for Sodium

In Table 16, sodium concentrations in almost all regions’ are quite high which means

the freshwater ecosystem in Sweden have a high risk of sodium.

When considering the sodium concentration in Na2SO4 form, just in a few regions like

Värmland, Dalarnas, Gävleborg, Jämtland, Västerbotten and Norrbotten there is no

risks. Considering the sodium concentration in NaCl form, most regions are suffering

the risk of sodium except Halland, Örebro, Dalarna, Jämtland and Norrbotten.

In general, the risk of sodium shown in NaCl form is lower than that for the other

sodium salts.

Gotland has the highest risk of sodium.

4.3.4. RQ results for Potassium

In Table 16, the concentrations of potassium in all regions show risks to freshwater

ecosystems, except some parts of some regions with no potassium compounds in

freshwater ecosystem.

In general, the RQmins values of potassium concentration in potassium chloride form

present lower risk to the freshwater ecosystem than potassium sulfate.

Gotland has the highest risk of potassium.


32

4.3.5. RQ results for Magnesium

In Table 17, the concentrations of magnesium in Sweden show a risk in most of the

places in Sweden because there is only few RQmin values of MgCl2 and MgSO4 that

are lower than 1 (RQmin values below 1 occur in the following regions: Västra

Götaland, Värmland, Örebro, Västmanland, Dalarna, Gävleborg, Västernorrland,

Jämtland, Västerbotten and Norrbotten).

The risks of magnesium in MgCl2 form and MgSO4 form are similar.

Gotland presents the highest risk of magnesium in the freshwater ecosystem.

4.3.6. RQ results for Calcium

In Table 17, when considering the calcium concentration in CaCl2 form, the

concentration of calcium is a risk to most places of Sweden since there are only a few

RQmin values in some places in the regions of Halland, Västra Götaland, Dalarna,

Jämtland, Västerbotten and Norrbotten that are below 1.

Skåne has the highest risk of calcium in freshwater ecosystem followed by

Västerbotten and Gotland.

4.3.7. General overview of RQ values

- The RQ values for sulfate are much higher than the other toxic compound; it

indicates that the concentration of sulfate in Swedish freshwater is much

higher than the most sensitive freshwater species can tolerate.

- Most RQ value are above 1, the reason could be:

a. The data of effect assessments are limited to two trophic levels, this

causes the fix assessment factor to be quite high, then the calculated

PNEC is quite low, and the generated RQ is quite high. It is also possible

that the fixed assessment factors which generally are used for persistent

chemicals might not be suitable for risk assessment of salts.

b. Using the ion concentration in salt as PNEC value to calculate RQ has

some limitations to present the real risk of salt in the Swedish freshwater

ecosystem. However, the RQ value can still show which compound that

is most toxic to freshwater organisms.


33

Table 14. RQ values for chloride

RQs for chloride

KCl NaCl MgCl2 CaCl2

Region max min max min max min max min

Stockholm 574.3 2.9 41.4 0.2 380.5 1.9 212.9 1.1

Uppsala 51.5 2.7 3.7 0.2 34.1 1.8 19.1 1.0

Södermanland 40.5 2.5 2.9 0.2 26.8 1.7 15.0 0.9

Östergötland 42.5 3.0 3.1 0.2 28.2 2.0 15.8 1.1

Jönköping 31.3 3.7 2.3 0.3 20.8 2.4 11.6 1.4

Kronoberg 49.6 6.2 3.6 0.4 32.9 4.1 18.4 2.3

Kalmar 88.5 4.1 6.4 0.3 58.7 2.7 32.8 1.5

Gotland 5190.2 9.2 374.3 0.7 3438.7 6.1 1924.6 3.4

Blekinge 26.6 8.4 1.9 0.6 17.6 5.6 9.9 3.1

Skåne 327.3 6.8 23.6 0.5 216.9 4.5 121.4 2.5

Halland 25.4 6.2 1.8 0.4 16.8 4.1 9.4 2.3

Västra Götaland 3556.9 3.6 256.5 0.3 2356.6 2.4 1318.9 1.3

Värmland 51.2 0.9 3.7 0.1 33.9 0.6 19.0 0.3

Örebro 15.4 1.8 1.1 0.1 10.2 1.2 5.7 0.7

Västmanland 42.6 1.8 3.1 0.1 28.2 1.2 15.8 0.7

Dalarna 13.0 0.2 0.9 0.0 8.6 0.1 4.8 0.1

Gävleborg 30.2 0.4 2.2 0.0 20.0 0.3 11.2 0.2

Västernorrland 29.4 0.6 2.1 0.0 19.5 0.4 10.9 0.2

Jämtland 5.4 0.2 0.4 0.0 3.6 0.1 2.0 0.1


34

Västerbotten 217.0 0.2 15.7 0.0 143.8 0.1 80.5 0.1

Norrbotten 14.3 0.2 1.0 0.0 9.4 0.1 5.3 0.1

max 5190.2 9.2 374.3 0.7 3438.7 6.1 1924.6 3.4

min 5.4 0.2 0.4 0.0 3.6 0.1 2.0 0.1

*All data in bold text have a RQ above 1 and there is therefore a risk to the freshwater ecosystem.


35

Table 15. RQ values for sulfate

RQs for sulfate

K2SO4 Na2SO4 MgSO4

Region max min max min max min

Stockholm 1049.4 23.7 46.8 1.1 89.3 2.0

Uppsala 1612.8 7.8 71.9 0.3 137.2 0.7

Södermanland 217.7 21.0 9.7 0.9 18.5 1.8

Östergötland 937.4 12.8 41.8 0.6 79.7 1.1

Jönköping 374.0 12.1 16.7 0.5 31.8 1.0

Kronoberg 126.0 22.6 5.6 1.0 10.7 1.9

Kalmar 206.8 28.8 9.2 1.3 17.6 2.4

Gotland 3787.7 72.3 168.8 3.2 322.2 6.2

Blekinge 129.9 19.8 5.8 0.9 11.0 1.7

Skåne 1187.8 19.4 52.9 0.9 101.0 1.7

Halland 145.4 27.6 6.5 1.2 12.4 2.3

Västra Götaland 2562.2 9.3 114.2 0.4 217.9 0.8

Värmland 50.9 4.3 2.3 0.2 4.3 0.4

Örebro 192.8 10.5 8.6 0.5 16.4 0.9

Västmanland 190.1 9.3 8.5 0.4 16.2 0.8

Dalarna 2213.1 2.7 98.6 0.1 188.2 0.2

Gävleborg 242.2 3.9 10.8 0.2 20.6 0.3

Västernorrland 85.1 6.6 3.8 0.3 7.2 0.6

Jämtland 224.3 3.1 10.0 0.1 19.1 0.3


36

Västerbotten 9270.6 2.3 413.2 0.1 788.5 0.2

Norrbotten 1039.3 1.9 46.3 0.1 88.4 0.2

max 9270.6 23.7 413.2 1.1 788.5 2.0

min 50.9 1.9 2.3 0.1 4.3 0.2



37

Table 16. RQ values for sodium and potassium

RQs for sodium RQs for potassium

NaCl Na2SO4 KCl K2SO4

Region Max min max min max min max min

Stockholm 15.3 0.1 272.5 2.4 13.5 0.3 193.9 4.7

Uppsala 2.4 0.2 42.9 3.4 8.2 0.5 117.6 7.8

Södermanland 1.5 0.1 26.0 2.3 5.4 0.3 77.9 4.7

Östergötland 1.6 0.1 27.7 2.6 7.3 0.5 105.1 7.0

Jönköping 1.7 0.2 29.4 2.7 5.8 0.5 84.1 7.0

Kronoberg 1.8 0.3 31.6 4.9 4.8 0.3 68.5 4.7

Kalmar 2.7 0.2 47.5 3.6 8.8 0.5 126.2 7.8

Gotland 107.0 0.3 1904.4 6.1 98.9 0.9 1425.2 13.2

Blekinge 1.2 0.4 21.3 6.9 3.3 0.6 47.5 9.3

Skåne 8.3 0.3 148.4 6.0 9.3 0.7 134.0 10.1

Halland 0.9 0.2 15.9 4.3 7.1 0.4 102.0 5.4

Västra Götaland 81.3 0.1 1445.8 2.6 70.9 0.3 1021.8 3.9

Värmland 1.8 0.0 31.2 0.9 2.8 0.1 40.5 1.6

Örebro 0.5 0.1 8.3 1.4 4.3 0.2 62.3 3.1

Västmanland 1.4 0.1 25.1 1.6 5.9 0.2 85.7 3.1

Dalarna 0.9 0.0 16.8 0.3 23.4 0.0 338.0 0.0

Gävleborg 1.6 0.0 28.6 0.8 11.0 0.2 158.1 2.3

Västernorrland 1.1 0.1 19.3 1.0 5.0 0.1 71.7 1.6

Jämtland 0.2 0.0 4.2 0.3 2.1 0.0 30.4 0.0

Västerbotten 6.0 0.0 106.3 0.2 8.4 0.0 121.5 0.0


38

Norrbotten 0.9 0.0 16.2 0.1 7.9 0.0 113.7 0.0

max 107.0 1.8 1904.4 31.8 98.9 0.9 1425.2 13.2

min 0.2 0.0 4.2 0.1 2.1 0.0 30.4 0.0



39

Table 17. RQ values for magnesium and calcium

RQs for magnesium RQs for calcium

MgCl2 MgSO4 CaCl2

Region max min max min max min

Stockholm 76.1 1.6 70.3 1.5 107.8 2.1

Uppsala 40.3 2.9 37.3 2.7 98.4 5.0

Södermanland 17.4 1.6 16.1 1.5 26.5 1.6

Östergötland 19.4 1.4 17.9 1.3 107.0 1.3

Jönköping 16.6 1.5 15.3 1.4 43.7 1.4

Kronoberg 9.5 2.1 8.8 2.0 13.6 1.1

Kalmar 17.8 2.6 16.4 2.4 19.7 2.4

Gotland 523.1 6.5 483.3 6.0 120.1 39.1

Blekinge 8.6 2.9 8.0 2.7 19.4 2.5

Skåne 82.8 2.0 76.5 1.9 130.8 1.4

Halland 17.4 1.5 16.0 1.4 13.7 0.5

Västra Götaland 372.4 0.9 344.0 0.9 94.2 0.3

Värmland 6.7 0.5 6.2 0.4 14.8 0.6

Örebro 8.5 1.0 7.8 0.9 51.4 0.8

Västmanland 16.1 0.9 14.8 0.8 26.8 0.7

Dalarna 59.4 0.1 54.9 0.1 96.2 0.1

Gävleborg 14.0 0.4 12.9 0.3 46.5 0.6

Västernorrland 10.0 0.6 9.2 0.6 13.0 0.7


40

Jämtland 20.1 0.1 18.6 0.1 71.3 0.1

Västerbotten 215.8 0.2 199.4 0.2 128.6 0.1

Norrbotten 25.2 0.1 23.2 0.1 61.1 0.1

max 523.1 6.5 483.3 6.0 130.8 31.9

min 6.7 0.1 6.2 0.1 13.0 0.1



41

5. Conclusion

The concentration of cations and anions in Gotland is quite high compared to

other regions.

Most toxicity data found was short term responses for crustaceans like Daphnia

magna.

Invertebrates appear to be more sensitive to salts than fish.

The most sensitive endpoint was found for Dreissena polymorpha in short term

test where LC50 for K2SO4 was 0.643 mmol/L. The lowest LC50 values were also

in general obtained for K2SO4.

Daphnia magna was more sensitive to K2SO4 and KCl than to the other salts.

Most RQ values in Swedish freshwater were above 1 and showed risk for the

freshwater ecosystem.

The risk of sulfate to Swedish freshwater ecosystem is much higher than the risk

of other toxic ions.

Gotland had the highest RQ values.

Very high risk quotients were obtained for many Swedish freshwater ecosystems

even though many of them have a high biodiversity. The reason for this is unclear

but it could be due to the size of the fixed assessment factors which in general are

used for persistent pollutions but might not be suitable for salts. Another plausible

explanation is that the treatment of the effect data to fit the exposure data is not

adequate and other methods have to be explored.


42

Acknowledgement

This thesis could not be finished without the help and support of many people who are

gratefully acknowledged here.

At the very first, I’m honored to express my deepest gratitude to my dedicated

supervisor, Prof. Sylvia Waara, with whose able guidance I could have worked out

this thesis. She has offered me valuable ideas, suggestions and criticisms with her

profound knowledge in research experience. Her patience and kindness are greatly

appreciated. Besides, she always puts high priority on our dissertation writing and is

willing to discuss with me anytime she is available. I have learnt from her a lot not

only about dissertation writing, but also the professional ethics. I’m very much

obliged to her efforts of helping me complete the dissertation.

What’s more, I wish to extend my thanks to Prof. Stefan Weisner. I learned how to

write a good report in his class. This gave me an idea about how to write this thesis.

At last but not least, I would like to thank my family for their support all the way from

the very beginning of my study. I am thankful to all my family members for their

thoughtfulness and encouragement.

JIANG Huan

2011. 5. 25


43

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