Spatial and Temporal Variation of Watertype-Specific No-Effect Concentrations and Risks of Cu, Ni, and Zn

Abstract

Geographical and temporal variations in metal speciation were calculated and water-type specific sensitivities were derived for a range of aquatic species, using surveillance water chemistry data that cover almost all surface water types in The Netherlands. Biotic ligand models for Cu, Zn, and Ni were used to normalize chronic no-effect concentrations (NOEC) determined in test media toward site-specific NOEC for 372 sites sampled repeatedly over 2007-2010. Site-specific species sensitivity distributions were constructed accounting for chemical speciation. Sensitivity of species as well as predicted risks shifted among species over space and time, due to changes in metal concentrations, speciation, and biotic ligand binding. Sensitivity of individual species (NOEC) and of the ecosystem (HC5) for Cu, Ni, and Zn showed a spatial variation up to 2 orders of magnitude. Seasonality of risks was shown, with an average ratio between lowest and highest risk of 1.3, 2.0, and 3.6 for Cu, Ni, and Zn, respectively. Maximum risks of Cu, Ni, and Zn to ecosystems were predicted in February and minimum risks in September. A risk assessment using space-time specific HC5 of Cu and Zn resulted in a reduction of sites at risk, whereas for Ni the number of sites at risks increased.

Temporal assessment of copper speciation, bioavailability and toxicity in UK freshwaters using chemical equilibrium and biotic ligand models: Implications for compliance with copper environmental quality standards

“…It is advised that the characteristics of the freshwater sites should be considered when assessing compliance with environmental quality standards (Lathouri, 2012). A similar pattern in terms of the temporal variations of the BLM parameters and risk assessment has been reported by Verschoor et al (2011) in their study in the Netherlands. In this case too, the selected surface water types covered a range of water quality parameters levels (pH 6.6-7.6; DOC 1-16 mg l −1 ; Ca 30-55 mg l −1 and Cu 1-8 μg l −1 ) but the analysis used annual averages.…”

“…In this case too, the selected surface water types covered a range of water quality parameters levels (pH 6.6-7.6; DOC 1-16 mg l −1 ; Ca 30-55 mg l −1 and Cu 1-8 μg l −1 ) but the analysis used annual averages. Verschoor et al (2011) identified that the highest Cu risk was found from December until March and the lowest from July until October. They emphasised that seasonal risk patterns were dominated by changes in water chemistry and seasonal Cu concentration patterns, with Cu concentrations peak during winter months.…”

Consideration of the bioavailability of metal/metalloid species in freshwaters: experiences regarding the implementation of biotic ligand model-based approaches in risk assessment frameworks

“…Water quality data were collected from monitoring programs covering a four-year period, thereby enabling both the geographic and the temporal (time dependent) variation analysis (Verschoor et al 2011). Water compositions varied for pH: 5.7 -8.7; DOC: 1.5 -33 mg/L; Ca: 10.7 -175 mg/L; Mg: 1.9 -42.7 mg/L; Na: 7.1 -153 mg/L.…”

Fate of Trace Metals in Anaerobic Digestion

“…For Cd, a bioavailability correction factor based on water hardness has been suggested (e.g., [87]). Recently, Verschoor et al [93] performed a geographical and temporal analysis of TM in surface waters, and concluded that "sensitive" and "robust" waters occur, based on their physic-chemical composition. By incorporating chemical speciation of TM in the assessment of ecotoxicological risks for aquatic species, site-specific variations are made visible that remain undetected when checked with generic quality standards.…”