Inorganic salts

Rationale  1

Conditions for using this variable  2

Benchmarks  2

Reference conditions  2

Present state classification  3

Ecological specifications  4

Additional information  4

References  6

 

Report status (This text box should be removed on completion of this document)

Editor:                      Nico Rossouw (nico.Rossouw@shands.co.za)

Version:                  01

Date:                        4 September 2003

Status:                     Ready for review   

Author’s notes:       Add 2 references

Rationale

Inorganic salts: Sodium chloride, sodium sulphate, magnesium chloride,   magnesium sulphate, calcium chloride, calcium sulphate

Why use salts rather than ions?

There is no doubt that in some cases sufficient data exist to ascribe the toxicity of a salt to either a cation (such as Cd 2+) or an anion (such as CN-).  However, in the case of common salts such as Na2SO4, MgCl2, MgSO4, NaCl etc., it is considerably more difficult to ascribe the effect to either the cationic or anionic component of the salt.  There are indications that some of the alkaline cations (such as Na+ and K+) and alkaline earth cations (such as Ca 2+ and Mg 2+) are physiologically important, either by innately or as ratios.  However, insufficient data appear to exist to derive EcoSpecs for ions in isolation.  Consequently the approach used is based on the measured toxicity of salts.

 

The approach for setting the Reserve for major inorganic salts is based on a hazard assessment.  More information on hazard assessment appears in Jooste & Rossouw (2002).

The database used

For water quality (salts and toxics) the ECOTOX database maintained by the USEPA (http://www.epa.gov/ecotox) was considered the most extensive and most accessible.  All toxicity data were extracted. The database was not expanded to include results obtained with South African species.  Care was exercised to ensure representation of toxicity data for: a) fish, b) other aquatic vertebrates, c) invertebrates, d) plants (no distinction was made between vascular plants and algae).

 

Where sufficient LC50 data at various exposure times were available an estimate of the LC50 at 2 weeks of exposure was made. The actual data and projection techniques appear in  Jooste & Rossouw (2002).

 

 

A value for TDS is not included in the specifications for the water quality Reserve.   While it is recognized that there are important biotic effects related to high composite salt concentrations, there is evidence that the effects of individual salts will outweigh the effects attributable to TDS. For this reason individual salts have been specified. The concentration of salts is calculated from ionic data  (In the final manual there will be a reference to a DWAF web-site where a spreadsheet with the calculations can be down-loaded).  A method for using TDS/EC as an end-point is under development.

Conditions for using this variable

Obligatory group of variables. This is a standard water quality Reserve group of variables and must always be considered.

Benchmarks

The benchmark table (Table 1 ) has been derived from an interpolation of the hazard-based stressor response curve generated from two radical points: the lethality benchmark and the sub-lethality benchmark (See additional information).  The hazard was characterised in terms of the likelihood of loss of species expressed on a scale of 0 (unlikely) to 1 (very likely).  Table 1 is the benchmark table for major inorganic salts which are listed in decreasing toxicity.

   

 Table 1 The default benchmark category boundaries for inorganic salts

Variables

Natural boundary  (mg/l)

Good boundary (mg/l)

Fair boundary

(mg/l)

MgSO4

16

27

37

Na2SO4

20

36

51

MgCl2

15

33

51

CaCl2

21

63

105

NaCl

45

217

389

CaSO4

351

773

1195

 

Reference conditions

The Reference condition for salinity components is derived from sites that are known to have a high biotic integrity and that would be known to correspond to the description of a Natural site or one at which there is solid evidence that there is no significant anthropogenic impact.

 

If no inorganic salts data are available

 

If inorganic salts data are available

For a medium confidence determination

For a high confidence determination

* - Note that 60 samples are the minimum number of samples that would yield a power statistic greater than 0.8 which is regarded as high confidence.

 

Present state classification

The present state is assessed by calculating the 95th percentiles of the hazard for each salt.  This calculation is automated within the spreadsheet, EWQCalc Version 2.3, within the Spatsim software. 

 

The EWQCalc spreadsheet automates the following for each data record:

  1. For each data record: Convert all relevant ionic data to units of millimoles/l.  This is accomplished by dividing the concentration in mg/l by the ionic atomic or molecular mass (Na = 23; Mg=24.3; Ca = 40; Cl = 35.5; SO4 = 96).
  2. For each record, calculate the salts concentration in mM from the ionic concentrations in mM, as shown in Table 2 .

Table 2 Formulae for the calculation of TIMS from ionic concentrations in millimoles/litre units

Salt (mM)

Calculation

MgSO4

Minimum {Mg, SO4}

Na2SO4

Minimum {Na/2, (SO4 - MgSO4)}

MgCl2

Minimum {(Mg – MgSO4), Cl/2}

CaCl2

Minimum {Ca, (Cl - 2*MgCl2)/2}

NaCl

Minimum {(Na – 2*Na2SO4), (Cl – 2*MgCl2 – 2*CaCl2)}

CaSO4

Minimum {(Ca – CaCl2), (SO4 – MgSO4 – Na2SO4)}

 

  1. For each data record: Calculate the hazard for each salt by using the formula

y = 1/ (1+axe-bx)

where              y is the hazard for a specific salt

                        X is the concentration of a specific salt in mM/L

                        a and b are parameters from Table 5a in Jooste & Rossouw (2002).

 

  1. Calculate the 95th percentile of each salt in mM/L and their hazards using suitable statistical software.

 

  1. Convert the 95th percentile salt values in mM/L to concentrations in mg/l by multiplying by the associated formula mass of the salts in Table 3 .

 

 

Table 3 Formula mass of TIMS salts

Salt (mM)

Formula mass

Salt (mM)

Formula mass

MgSO4

120.3

CaCl2

111

Na2SO4

142

NaCl

58.5

MgCl2

95.3

CaSO4

136

 

  1. Classify the hazard posed by the salts by comparing the 95th percentile of the calculated hazards to the value in Table 5c of Jooste & Rossouw (2002).

 

  1. Use the power statistic calculated in Step 3 of the water quality Reserve process to determine the confidence of the present state classification.

 

  1. Each salt is assigned a category and reported as such.

 

In special cases, the salt concentration to category relationship method of Palmer and Scherman (2000) and IWR Environmental (2001) is useful, particularly for the assessment of the Good and Fair boundaries. Salt category boundaries established using this method have been found to relate well to SASS-category relationships. 

 

 

All the category-salt concentration relationships used in this manual relate only to concentration, and do not take account of seasonality.  Other than a somewhat conservative assumption of 2 weeks of exposure at the lethality benchmarks the duration of exposure to concentrations is not addressed. Methods are being developed to take account of the duration and frequency of concentrations. (Malan & Day, 2002)

 

 

Ecological specifications

The Ecological specifications are read off the calibrated benchmark boundary table (or the default benchmark boundary table if no adjustments were made).

Additional information

Calculating the theoretical salt content of a water sample

This procedure is described in the technical support document (Jooste, 2002).  It is comprises composing theoretical ion associations corresponding to major salts in a specific order dictated by the toxicity of these salts (expressed on a molar basis).

 

Background: the concept of a Toxicologically Important Major Salt

The data on which the benchmarks are based were derived from experiments where a population is exposed to a salt solution.  For the most part, the salt will exist in solution as ions stabilised by water molecules.  When a second salt is added, the same process occurs.  Two possibilities now exist: either the organism reacts to the individual salts or it reacts to a macro characteristic of the water such as the osmolality.  For the present, until more information on mixture toxicity is available, it is assumed that organisms react to concentrations of the virtual or theoretical salts it perceives in its environment.

 

This means, for example, that although initially there may only have been sodium and chloride in solution, the addition of a small amount of calcium sulphate (both of which are relatively non-hazardous) may give rise to a situation where an organism in the water perceives sodium sulphate in its environment.  The resulting “virtual” sodium sulphate only depends on the limiting ion (probably sulphate in this case) and the ionic ratio sodium:sulphate.

 

From the example above it is clear that this “virtual” or toxicologically important salt may never actually have been discharged into the system.  Its existence does not depend on any specific discharge, but rather on the combination that exists in the water sample.

 

The key to the assessment of salinity is, therefore, the calculation of these toxicologically important major salts (TIMS).  It should be stressed that at its most fundamental level this is not a calculation of chemical equilibria but something more like a salt toxicity index.

 

Toxicologically Important Major Salts (TIMS) Calculation Procedure

Since the calculation deals with toxicologically important salts, the most toxic salts, i.e. those with the lowest molar benchmark values, are calculated first.  The order in which the salts are composed is given in Table 2 .

 

The lethality benchmark

The lethality benchmark has been calculated as the 5th percentile of the LC50 (336) dataset.  Ideally this would be a non-parametric estimate of the percentile.  Values are shown in Table 4 . 

 

This benchmark indicates the level at which less than 95% of all (theoretical) organisms will be protected from significant mortality and corresponds to a very high hazard.

 

The sub-lethality benchmark

The sub-lethality benchmark has been set at the 5th percentile of all the sub-lethal data available.  This should be a non-parametric estimate of the percentile.  Where insufficient sub-lethal data exist, the average ratio of 5th percentiles of sub-lethal to lethal data is used to calculate the sub-lethal benchmark.

 

This benchmark indicates the level at which it is expected that 95% of all (theoretical) organisms will be protected from sub-lethal effects and corresponds to a very low hazard.

 

Table 4 Stressor response benchmarks for major salts based on 95% protection of species.  The order of toxicity based on molar concentration increases from top to bottom in the Table

Salt

Sub lethal (mg/l)

Lethal (mg/l)

MgSO4

16

37

Na2SO4

20

51

MgCl2

15

51

CaCl2

21

105

NaCl

45

389

CaSO4

351

1 195

 

Calculating the Benchmark Table

The benchmark table is generated from an S-shaped curve that is assumed to describe the hazard as a function of salt concentration.  The curve is derived such that the sublethal benchmark yields a response (hazard) of 0.01 and the lethal benchmark yield a response of 0.99. These benchmarks also defines the upper boundaries of the “Natural” and “Fair” categories.  The “Good” upper boundary is derived by interpolation.

 

The Natural boundary values correspond approximately to the CEV’s (Chronic Effects Values) in the South African Water Quality Guidelines (DWAF, 1996) while the Fair boundary values correspond approximately to the AEV’s (Acute Effects Values).

 

An Excel spreadsheet to calculate the salt concentrations is available on the IWQS web site (http://www.dwaf.gov.za/iwqs/iwqso/ecorivreserve.htm).  The detail of the procedure appears in the technical support document (Jooste & Rossouw, 2002)

References

DWAF (1996)  South African Water Quality Guidelines (2nd edition). Volume 7: Aquatic Ecosystems.  Department of Water Affairs and Forestry, Pretoria South Africa.

 

Jooste, S. & Rossouw, J.N. (2002)  Hazard-based Water Quality EcoSpecs for the Ecological Reserve in Fresh Surface Water Resources.  Report No N/0000/REQ0000. Institute for Water Quality Studies, Department of Water Affairs and Forestry, Pretoria, South Africa.

 

Malan, H/L.& Day, J.A. (2002). Development of numerical methods for predicting relationships between streamflow, water quality and biotic responses in rivers.  WRC Report No. 956/1/02, Water Research Commission, Pretoria.

 

Palmer & Scherman  [TALLY PLEASE ADD THIS]

 

IWR Environmental (2001).  Olifants River Ecological Water Requirements Assessment: Water Quality. Report No. 000/00/599. Prepared for the Department of Water Affairs and Forestry.