Simultaneous removal of As, Cd, Cr, Cu, Ni and Zn from stormwater using high-efficiency industrial sorbents: Effect of pH, contact time and humic acid.

The effect of contact time, solution pH, and the presence of humic acid (HA) on the combined removal of As, Cd, Cr, Cu, Ni and Zn is investigated in batch tests using alumina, granulated activated carbon (GAC), and bauxsol coated sand (BCS) as sorbents. It is found that the equilibrium time for Cd, Cu, Ni and Zn is about 4h, while no clear equilibrium is observed for As and Cr. It is also found that increasing the pH until pH~8 enhanced Cd, Cu, Ni and Zn removal, but increasing the pH above this point had no major effect. In the cases of As and Cr, higher pH values (i.e. >7) decreased their removal. The presence of both 20 and 100mg/L HA suppressed the heavy metal removal except for Cr, and the suppression was higher at the higher HA concentration. Geochemical simulations suggest that this is due to the formation of dissolved HA-metal complexes preventing effective metal sorption. In the case of Cr, the presence of HA increased the removal when using alumina or BCS, while hindering the removal when using GAC. The findings show that the pH-value of the stormwater to be treated must be in the range of 6-7 in order to achieve removal of the full spectrum of metals. The results also show that natural organic matter may severely influence the removal efficiency, such that, for most metals the removal was reduced to the half, while for Cr it was increased to the double for alumina and BCS. Consequently, a properly working filter set up may not work properly anymore when receiving high loads of natural organic acids during the pollen season in spring or during defoliation in autumn and early winter, and during mixing of runoff with snowmelt having a low pH.

Velocity dependent passive sampling for monitoring of micropollutants in dynamic stormwater discharges.

Micropollutant monitoring in stormwater discharges is challenging because of the diversity of sources and thus large number of pollutants found in stormwater. This is further complicated by the dynamics in runoff flows and the large number of discharge points. Most passive samplers are nonideal for sampling such systems because they sample in a time-integrative manner. This paper reports test of a flow-through passive sampler, deployed in stormwater runoff at the outlet of a residential-industrial catchment. Momentum from the water velocity during runoff events created flow through the sampler resulting in velocity dependent sampling. This approach enables the integrative sampling of stormwater runoff during periods of weeks to months while weighting actual runoff events higher than no flow periods. Results were comparable to results from volume-proportional samples and results obtained from using a dynamic stormwater quality model (DSQM). The paper illustrates how velocity-dependent flow-through passive sampling may revolutionize the way stormwater discharges are monitored. It also opens the possibility to monitor a larger range of discharge sites over longer time periods instead of focusing on single sites and single events, and it shows how this may be combined with DSQMs to interpret results and estimate loads over extended time periods.

Modelling the fate of organic micropollutants in stormwater ponds.

Urban water managers need to estimate the potential removal of organic micropollutants (MP) in stormwater treatment systems to support MP pollution control strategies. This study documents how the potential removal of organic MP in stormwater treatment systems can be quantified by using multimedia models. The fate of four different MP in a stormwater retention pond was simulated by applying two steady-state multimedia fate models (EPI Suite and SimpleBox) commonly applied in chemical risk assessment and a dynamic multimedia fate model (Stormwater Treatment Unit Model for Micro Pollutants--STUMP). The four simulated organic stormwater MP (iodopropynyl butylcarbamate--IPBC, benzene, glyphosate and pyrene) were selected according to their different urban sources and environmental fate. This ensures that the results can be extended to other relevant stormwater pollutants. All three models use substance inherent properties to calculate MP fate but differ in their ability to represent the small physical scale and high temporal variability of stormwater treatment systems. Therefore the three models generate different results. A Global Sensitivity Analysis (GSA) highlighted that settling/resuspension of particulate matter was the most sensitive process for the dynamic model. The uncertainty of the estimated MP fluxes can be reduced by calibrating the dynamic model against total suspended solids data. This reduction in uncertainty was more significant for the substances with strong tendency to sorb, i.e. glyphosate and pyrene and less significant for substances with a smaller tendency to sorb, i.e. IPBC and benzene. The results provide support to the elaboration of MP pollution control strategies by limiting the need for extensive and complex monitoring campaigns targeting the wide range of specific organic MP found in stormwater runoff.

Dynamic experiments with high bisphenol-A concentrations modelled with an ASM model extended to include a separate XOC degrading microorganism.

The perspective of this work is to develop a model, which can be used to better understand and optimize wastewater treatment plants that are able to remove xenobiotic organic compounds (XOCs) in combination with removal of traditional pollutants. Results from dynamic experiments conducted with the endocrine disrupting XOC bisphenol-A (BPA) in an activated sludge process with real wastewater were used to hypothesize an ASM-based process model including aerobic growth of a specific BPA-degrading microorganism and sorption of BPA to sludge. A parameter estimation method was developed, which simultaneously utilizes steady-state background concentrations and dynamic step response data, as well as conceptual simplifications of the plant configuration. Validation results show that biodegradation of BPA is sensitive to operational conditions before and during the experiment and that the proposed model structure is capable of capturing important characteristics of the observed BPA removal, thus increasing the potential for generalizing knowledge obtained from plant specific experiments.

Simultaneous removal of As, Cd, Cr, Cu, Ni and Zn from stormwater: experimental comparison of 11 different sorbents.

The potential of using alumina, activated bauxsol-coated sand (ABCS), bark, bauxsol-coated sand (BCS), fly ash (FA), granulated activated carbon (GAC), granulated ferric hydroxide (GFH), iron oxide-coated sand (IOCS), natural zeolite (NZ), sand, and spinel (MgAl(2)O(4)) as sorbents for removing heavy metals from stormwater are investigated in the present study. The ability of the sorbents to remove a mixture of As, Cd, Cr, Cu, Ni and Zn from synthetic stormwater samples were evaluated in batch tests at a starting pH of 6.5. The metal speciation and saturation data is obtained using the PHREEQ-C geochemical model and used to elucidate the sorption data. It is found that BCS, FA, and spinel have significantly higher affinity towards heavy metals mainly present as cationic or non-charged species (i.e. Cd, Cu, Ni and Zn) compared to those present as anionic species (i.e. As and Cr). However, IOCS, NZ and sand have higher affinity towards As and Cr, while alumina has equally high affinity to all tested heavy metals. The Freundlich isotherm model is found to fit the data in many cases, but ill fitted results are also observed, especially for FA, BCS and GAC, possibly due to leaching of some metals from the sorbents (i.e. for FA) and oversaturated conditions making precipitation the dominant removal mechanism over sorption in batches with high heavy metal concentrations and pH. Calculated sorption constants (i.e. K(d)) are used to compare the overall heavy metal removal efficiency of the sorbents, which in a decreasing order are found to be: alumina, BCS, GFH, FA, GAC, spinel, ABCS, IOCS, NZ, bark, and sand. These findings are significant for future development of secondary filters for removal of dissolved heavy metals from stormwater runoff under realistic competitive conditions in terms of initial heavy metal concentrations, pH and ionic strength.