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An Introduction to Drinking Water Contaminants, Treatment and Management

1 Introduction

2 Roles and Responsibilities in the Production of Drinking Water

3 Water Supply Management – Information Sources

4 Origins of Contaminants in Drinking Water Sources

5 Water Treatment

Appendix 1: Activities and the Contaminants That May Contribute to Source Waters

Appendix 2: Treatment Processes and Their Efficacies

Appendix 2: Treatment Processes and Their Efficacies

A2.1 Microbiological contaminants

Table A2.1 lists the extent to which microbiological contaminants are removed by a range of treatment processes. The data in the table are ‘log removal values’: a value of 3, for instance, indicates that the concentration of the contaminant is reduced by 3 log10 units, ie, 103 or 1000-fold or 99.9% reduction. The absence of an entry in the table indicates that no information about the efficacy in removing that contaminant has been found.

The table is based on:

1. the maximum values, or combinations of these, tabulated in the Guidelines for Drinking-water Quality (WHO, 2004).
   The WHO guidelines list the conditions under which each disinfection process can achieve a 100-fold (2 log) inactivation of each organism type. A default value of 2 is therefore entered in the table, although this is probably an under-estimate of the inactivation achievable by the disinfection processes. Chlorine is given an inactivation value of 3.5 log (c. 3,200-fold reduction) which is a conservative estimate based on a study by Hijnen et al²⁷.
2. for protozoa removal: the log removals assigned to treatment processes by the DWSNZ²⁸.

Removal values for Giardia are assumed to be the same as Cryptosporidium except for chlorination. Although chlorine is ineffective against Cryptosporidium for water treatment, it can inactivate Giardia provided sufficient chlorine is used.

The efficacies of all the processes depend on the conditions of operation, such as pH, chemical dose, and temperature.

Table A2.1: Treatment efficacies for micro-organisms (log10 units)

a Requires chemical pre-treatment with coagulants.

b Higher log removals may be achieved depending on the nature of the membrane.

c For a water temperature of 10°C and a contact time of 30 min, a chlorine concentration of c. 3 mg/L free available chlorine at pH 7–7.5 is required to achieve this level of removal (WHO, 2004).

Most treatment plants will contain more than one treatment process. The order of treatment processes has been discussed in section 5.2.1 and Table A2.1 has been set out so that the expected order in which the processes will be encountered is from top to bottom. (Note that not all the processes listed will be used in one treatment plant.)

The order in which the processes occur does not affect the calculation of their combined effect on the microbial concentration. In the simplest situation, the overall log removal is calculated by adding the values of the individual processes from the table together.

Example 1: The removal of bacteria by a treatment plant using coagulation / clarification / filtration followed by chlorination can be estimated to be 3 log + 3 log = 6 log, or 106 (1,000,000-fold reduction). Note that the value 2 for the ‘Rapid sand filtration’ in the table is not in the calculation because this is included in the ‘filtration’ part of the coagulation/clarification/filtration combination.

Example 2: The removal of Cryptosporidium by coagulation/dissolved air flotation/filtration followed by chlorination can be estimated to be 3 log or 103 (1,000-fold reduction). Chlorine makes no contribution to reducing the Cryptosporidium concentration, therefore only the value from the particle removal processes is used in the calculation.

It is important to note that simply adding the log values in the table may not give a reliable indication of the reduction in the concentration of micro-organisms if treatment processes acting by similar mechanisms are used. For example, if the disinfection processes ozonation and UV disinfection were both being used together in a treatment plant, only one of these processes would be included in the calculation, ie, a maximum of 3 log units (1,000-fold reduction). A similar situation would apply if two particle removal processes using the same mechanism were in use, eg, coagulation/flocculation/clarification and precipitation softening/clarification (which both operate by chemical precipitation) were used. These restrictions occur because once a particular process has achieved its maximum reduction of a contaminant, a second process that works in the same way is unlikely to be able to further reduce the contaminant.

Advice should be sought from a consulting engineer, or a drinking water assessor, if there is uncertainty about estimating the reduction achievable by a combination of processes.

A2.2 Chemical contaminants (listed in the DWSNZ)

Tables A2.2–A2.6 show the extent to which chemical contaminants are removed by various treatment processes. Where it is known, the minimum concentration (in mg/L) of a contaminant that can be achieved by a treatment process is also provided.²⁹ For some contaminant-process combinations, more than the treatment explicitly noted in the table may be required for removal. For example, the removal of manganese by chlorination or ozonation also requires a particle removal process to reduce the precipitated metal. Section 4.2 of the users’ guide provides the information that will assist in knowing what combination of processes is required.

The absence of an entry in the table indicates that either the treatment process has been found to have no effect on the contaminant concentration, or no information about the efficacy in removing that contaminant has been found. In the absence of any information it should be assumed that the treatment process achieves no significant removal of the contaminant.

The tables provide only a guide to the removal capabilities of the various treatment processes, and should not be used to attempt quantitative calculations. It is not possible in summary tables such as these, to take account of the different variables that may affect the performance of a treatment process. These include different types of membrane, different activated carbon types, the nature of coagulants used, and the chemistry of the raw water. Further discussion of the limitations of the tables is provided in section 5.3.

Some advanced treatment technologies that are not used in New Zealand are reported to be able to remove some of the contaminants in Tables A2.2–A2.6 (eg, ozone/hydrogen peroxide oxidation; reverse osmosis filtration). Removal capabilities for these processes have not been recorded.³⁰

Information in the tables is from WHO (2004) unless otherwise indicated.

For a discussion on estimating the removal of chemical contaminants by combinations of treatment processes, see the note after Table A2.6.

Table A2.2: Treatment efficacies for inorganic chemical contaminants of health significance

View treatment efficacies for inorganic chemical contaminants of health significance (large table).

Table A2.3: Treatment efficacies for agrichemical contaminants of health significance

View treatment efficacies for agrichemical contaminants of health significance (large table).

Table A2.4: Treatment efficacies for industrial contaminants and miscellaneous organic compounds of health significance

View treatment efficacies for industrial contaminants and miscellaneous organic compounds of health significance (large table).

Table A2.5: Treatment efficacies for cyanotoxins

View treatment efficacies for cyanotoxins (large table).

Table A2.6: Treatment efficacies for water constituents/contaminants of aesthetic significance

View treatment efficacies for water constituents/contaminants of aesthetic significance (large table).

Estimating removals by combinations of processes

Most treatment plants will contain more than one treatment process. The order of treatment processes has been discussed in section 5.2.1 and Tables A2.2–A2.6 have been set out so that the approximate order in which the processes will be encountered is from left to right (remember that not all the processes listed will be used in one treatment plant).

The order in which the processes occur does not affect the calculation of their combined effect on the microbial concentration. In the simplest situation, the overall percentage removal can be estimated by considering the percentage of a contaminant remaining after each treatment process.

Example: Consider a hypothetical situation in which there are three treatment processes in use that are able to remove the contaminant to some degree (in practice, it is unlikely that there will be more than two). The efficacy of each process is as follows: Process A – **; Process B – ***, and Process C – **. Using the precautionary approach, the lowest percentage removal in each bracket should be used. This gives Process A – 50% removal; Process B – 80% removal and Process C – 50% removal.

Consider starting with an initial contaminant concentration of 100 units, after each process step the remaining concentration will be as follows:

Remaining concentration 100 > Process A > 50 > Process B > 10 > Process C > 5

The overall percentage removal is therefore 95% (initial concentration minus final concentration, assuming the initial concentration is taken as 100 units).

As with the calculation of the combined effects of treatment processes that operate by the same mechanism for removing microbial contaminants (see notes with Table A2.1), it may not be valid to calculate the effect of combinations of treatment processes for chemical contaminants assuming that all processes will contribute to the removal. For example, the removal of manganese by ion-exchange or greensand filtration relies on adsorption. As a result, if the two processes were used sequentially, the overall percentage removal should not be estimated based on a contribution to removal from each process. The efficacy of the process with the greatest individual removal efficacy should be used in the estimation. In this case both have a *** (minimum 80%) efficacy, so that the overall efficacy would be conservatively estimated at 80%.

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