Evaluation of Analytical Chemical Methods for Detection of Estrogens in the Environment

4 Application of analytical methods for steroid estrogens

4.1 Sewage and sewage sludge
4.2 Surface water and sediment
4.3 Manure and soil
4.4 Other matrices
      4.4.1 Groundwater
      4.4.2 Bank filtration, septic tanks etc.

This section describes the properties of the different environmental matrices of relevance in this report. The main objective is to identify the problems that should be considered in the analysis of steroid estrogens in different types of environmental samples. A further objective is to recommend which methods should be used for the different purposes.

4.1 Sewage and sewage sludge

In samples of influent, effluent, and sludge from sewage treatment plants (STPs), the concentrations of steroid estrogens are so low that the most sensitive analytical detection techniques are needed. Additionally, complicated sample clean up techniques must be used especially in raw sewage and sewage sludge. Although sewage treatment plants are the main source of pollution with steroid estrogens, they also provide an important process for reduction of the problem. The key for solving the problem is a detailed understanding of the processes which determine the fate of the steroid estrogens in the sewage treatment plant. To achieve this understanding, analytical data of high precision and accuracy are needed. Although many methods exist for analysing sewage-related samples, the combined requirements of high sensitivity, high precision/accuracy and sophisticated sample cleanup techniques necessitate the development of suitable methods for analysing STP products.

Detection of steroid estrogens in samples from sewage effluent has been successfully accomplished by using both GC-MS, GC-MS-MS, and LC-MS-MS (see appendices 1 to 3). As previously mentioned, false positive signals may be detected using these techniques. The combination of LC with MS-MS is the only method suitable for analysing the conjugated metabolites of the steroid estrogens. Cleanup and pre-concentration of the samples can be made using conventional C18 SPE-columns, but often an additional cleaning step using silica gel, etc., is needed in order to remove ionic substances that may interfere with the analysis (e.g., humic acids, etc.). The use of GC based techniques necessitates derivatisation of the analyte due to the low vapour pressure of the steroid estrogens.

Sewage influent has a higher content of particulate matter and other substances which may interfere with the detection of steroid estrogens. Therefore, sample preparation of sewage influent is more cumbersome than preparation of sewage effluent. Generally, the methods presented for sewage influent are the same as for sewage effluent but the number of times the sample can be pre-concentrated is lower due to problems of clogging in the SPE-cartridges. While the presence of conjugated steroid estrogens is low in the sewage effluent due to de-conjugation in the STP, conjugates are expected to occur in sewage influent making the use of LC-MS-MS–methods more appropriate in this case.

Analysis of estrogens in sewage sludge is obviously extremely complicated. Hitherto, only one study has presented a viable analytical method (26). In this case, the sludge is freeze dried and extracted using methanol. The extracts are subsequently cleaned up using gel permeation chromatography and silica gel. Finally, the steroid estrogens are silylated using MSTFA before analysis using GC-MS-MS.

4.2 Surface water and sediment

Surface water typically contains enough particulate matter that filtration of the sample prior to pre-concentration is necessary. The low concentrations of steroid estrogens in surface water (rivers, lakes, sea-water) require sample pre-concentration of a thousand-fold or more prior to analysis which preferably should be made on tandem MS-systems (LC or GC). The pre-concentration is generally achieved using C18 cartridges but graphitized carbon is also an alternative. After pre-concentration, further clean-up procedures using silica gel, etc., may be recommended, but many methods which avoid this step have been presented.

A range of methods has been presented using other detection techniques (UV-detection, Fluorescence, GC- or LC-MS) but these are less sensitive and less reproducible.

Analysis of steroid estrogens in seawater has only been performed in a few cases. Chemically, the major difference between seawater and freshwater is the content of various inorganic salts. Steroid estrogens are expected to occur at lower concentrations in seawater than in freshwater due to greater dilution in seawater. Consequently, the methods used for seawater do not differ from methods used for freshwater.

A few examples of analytical methods for sediments of freshwaters (26;94-(96) and seawater (97) have been presented. All methods use liquid extraction followed by various methods for cleaning up the extract. In the methods for freshwater, the sediment has been freeze dried prior to extraction. Due to the low concentrations, a pre-concentration step is needed before analysis. Both GC and LC coupled to mass spectrometry have been used to detect the steroid estrogens. Although LC-MS has been demonstrated to work, MS-MS is preferred because of the high concentrations of potentially interfering substances that may be present in the sample.

4.3 Manure and soil

Animal excreta come in different forms depending on the animal species, the production methods on the farm and other similar factors. In the current context a division between liquid (urine, water, etc.) and solids (faeces, straw, soil, etc.) is sufficient. Animal excreta contain numerous substances and matrix problems are severe. Although the animal excreta often occur as slurry, the solid phase constitutes a major obstacle for analytical chemists. This problem is predominant for steroid estrogens as a significant portion of the substances are sorbed to the solid phase. Thus, in order to overcome the challenge of analysing steroid estrogens in animal excreta, an efficient method for cleanup and extraction is essential.

The number of reports presenting data on the occurrence of estrogens in manure is limited (27-29), and when data are presented, the documentation is sparse. The lack of published data and documented methodology indicates that further development of methods for the detection of steroid estrogens in manure is needed. A number of authors have published methods for the analysis of antibiotics from manure using liquid-liquid extraction (98;99) or lyophilization followed by accelerated solvent extraction (100). Although antibiotics are much more hydrophilic, similar methods may be used for steroid estrogens. Despite the difficulties foreseen with regard to extraction and cleanup of the samples, steroid estrogens may occur in these matrices at such high concentrations that less advanced techniques can be used for their detection.

At present, no methods have been presented for the analysis of steroid estrogens in soil. The difficulties that can be foreseen resemble those of analysing sediment and to some extent manure. Therefore it is believed that soil can be analyzed using methods similar to those used for sediment.

4.4 Other matrices

4.4.1 Groundwater

Groundwater is considered to be a clean matrix; therefore, the major problem encountered in analysing for steroid estrogens in groundwater is the low concentrations that are expected. Analytically, the difference from surface water analysis is insignificant. Therefore, the most sensitive methods should be used, implying the need for thorough pre-concentration and sophisticated instruments (MS-MS-techniques).

4.4.2 Bank filtration, septic tanks etc.

The presence of estrogens in drainage water and water influenced by release from scattered settlements have not been reported, but exposure routes shown in Figures 2.2 and 2.3 imply that estrogens (both E1, E2 and EE2) may be present in samples from such sources. Existing analytical methods provide an adequate starting point for the development of methods for analysing these matrices.