WCA Environment Ltd., Brunel House, Volunteer Way, Faringdon, Oxfordshire, SN7 7YR, UK,
Environ Sci Pollut Res Int. 2014 Jan;21(1):105-17. doi: 10.1007/s11356-013-1720-z. Epub 2013 May 2.
Recent years have seen considerable improvement in water quality standards (QS) for metals by taking account of the effect of local water chemistry conditions on their bioavailability. We describe preliminary efforts to further refine water quality standards, by taking account of the composition of the local ecological community (the ultimate protection objective) in addition to bioavailability. Relevance of QS to the local ecological community is critical as it is important to minimise instances where quality classification using QS does not reconcile with a quality classification based on an assessment of the composition of the local ecology (e.g. using benthic macroinvertebrate quality assessment metrics such as River InVertebrate Prediction and Classification System (RIVPACS)), particularly where ecology is assessed to be at good or better status, whilst chemical quality is determined to be failing relevant standards. The alternative approach outlined here describes a method to derive a site-specific species sensitivity distribution (SSD) based on the ecological community which is expected to be present at the site in the absence of anthropogenic pressures (reference conditions). The method combines a conventional laboratory ecotoxicity dataset normalised for bioavailability with field measurements of the response of benthic macroinvertebrate abundance to chemical exposure. Site-specific QSref are then derived from the 5%ile of this SSD. Using this method, site QSref have been derived for zinc in an area impacted by historic mining activities. Application of QSref can result in greater agreement between chemical and ecological metrics of environmental quality compared with the use of either conventional (QScon) or bioavailability-based QS (QSbio). In addition to zinc, the approach is likely to be applicable to other metals and possibly other types of chemical stressors (e.g. pesticides). However, the methodology for deriving site-specific targets requires additional development and validation before they can be robustly applied during surface water classification.
近年来，通过考虑当地水化学条件对金属生物利用度的影响，水质标准（QS）在金属方面有了相当大的提高。我们描述了进一步完善水质标准的初步努力，除了生物利用度之外，还考虑了当地生态群落的组成（最终保护目标）。QS 与当地生态群落的相关性至关重要，因为重要的是要尽量减少使用 QS 进行质量分类与基于当地生态组成评估的质量分类（例如，使用底栖大型无脊椎动物质量评估指标，如河流无脊椎动物预测和分类系统（RIVPACS））不一致的情况，特别是在生态评估为良好或更好状态，而化学质量被确定为不符合相关标准的情况下。这里概述的替代方法描述了一种基于预期在没有人为压力（参考条件）下存在于该地点的生态群落来推导特定地点物种敏感性分布（SSD）的方法。该方法将生物利用度归一化的常规实验室生态毒性数据集与底栖大型无脊椎动物对化学暴露的响应的现场测量相结合。然后，从 SSD 的 5%ile 中得出特定地点的 QSref。使用这种方法，已经从受历史采矿活动影响的地区推导了锌的 QSref。与使用传统的（QScon）或基于生物利用度的 QS（QSbio）相比，QSref 的应用可以在化学和生态质量指标之间产生更大的一致性。除了锌之外，该方法可能适用于其他金属和可能的其他类型的化学胁迫源（例如农药）。然而，推导特定地点目标的方法需要进一步的开发和验证，然后才能在地表水分类中可靠地应用。
