Suspended solids and indicator bacteria in stormwater runoff Sources of bias in field measurements

Abstract: Stormwater quality monitoring and control is a prerequisite for sustainable water resources management in urban areas. Stormwater monitoring programs are based on general water sampling guidance and, in the absence of standard procedures, employ various sampling and analytical methods. The aim of this thesis is to assess stormwater sampling methods and sample analyses with respect to the bias which may be introduced at different stages of the process of monitoring suspended solids and indicator bacteria. The focus was on the bias introduced by automated sampling methods and by analyses of suspended solids. Towards this end, suspended solids and four indicator bacteria (total coliforms, E. coli, int. enterococci and C. perfringens) concentrations were compared in stormwater samples in two urban catchments, which were collected manually or by automatic samplers. The impact of automatic samplers on E. coli concentrations in stormwater samples was further investigated by conducting a study of sampling line cross-contamination. The representativeness of suspended solids results obtained by the standard Total Suspended Solids (TSS) method was studied in urban bulk snow by assessing the ratio of suspended and settleable solids. TSS concentrations were compared to those obtained by other analytical procedures, including the Suspended Sediment Concentration (SSC) method and a newly introduced Multiple Filter Procedure (MFP). The MFP builds on the existing standard methods involving the filtration of whole water samples, but uses three filters with decreasing pore sizes to reduce filter clogging, and is designed to retain a broad range of solids, which is typical for stormwater. Finally, recognizing the affinity of indicator bacteria to suspended solids, both constituents were manually sampled in stormwater in four urban catchments during fall to assess their natural variation and correlation patterns between these contaminants. The comparison of samples collected manually and by automatic samplers yielded large differences in suspended solids concentrations, especially in the lower concentration range (0-100 mg/L), whereas the agreement between the two types of samples was within the analytical uncertainty (±30%) for all the four indicator bacteria. During the laboratory study, E. coli concentration in the first sample (following sudden bacteria concentration changes) were positively biased in automated samples due to the stormwater residue in the sampling line. When high E. coli concentrations were followed by low concentrations, the low concentrations were overestimated 10-20 times depending on the sampling line length (tested up to 5 m). The study findings should be helpful for improving field protocols for suspended solids and indicator bacteria sampling. The standard TSS analytical method underestimated solids in urban snow packs, because of high amounts of settleable particles remaining in situ, rather than leaving with snowmelt. The comparison between analytical procedures, including TSS, SSC and MFP yielded highly varying results for stormwater samples. The methods using whole water-samples, rather than aliquots withdrawn from such samples, as done in the case of TSS, produced more accurate estimates of solids concentrations, with a fairly good precision. The precision of the newly proposed MFP was generally better than ±10% and its results were comparable to those of standard methods using whole water samples, but the new procedure was less labourious. Consequently, the MFP was recommended for use when the total mass of solids in stormwater runoff is needed. The suspended solids and indicator bacteria concentrations in stormwater runoff varied from catchment to catchment and weak correlations were found between solids and bacteria, partly due to low concentrations of bacteria during the fall period. However, it was shown that the natural variation of the studied concentrations was affected by the sampling and the analytical method. Thus, the bias introduced during the stormwater quality monitoring process is relevant when assessing pollutant concentrations and the compliance of stormwater discharges with prescribed threshold values in the receiving waters.