Background: Over the past 10–15 years, a substantial amount of work has been done by the scientific, regulatory, and business communities to elucidate the effects and risks of pharmaceuticals and personal care products (PPCPs) in the environment.Objective: This review was undertaken to identify key outstanding issues regarding the effects of PPCPs on human and ecological health in order to ensure that future resources will be focused on the most important areas.Data sources: To better understand and manage the risks of PPCPs in the environment, we used the “key question” approach to identify the principle issues that need to be addressed. Initially, questions were solicited from academic, government, and business communities around the world. A list of 101 questions was then discussed at an international expert workshop, and a top-20 list was developed. Following the workshop, workshop attendees ranked the 20 questions by importance.Data synthesis: The top 20 priority questions fell into seven categories: a) prioritization of substances for assessment, b) pathways of exposure, c) bioavailability and uptake, d) effects characterization, e) risk and relative risk, f ) antibiotic resistance, and g) risk management.Conclusions: A large body of information is now available on PPCPs in the environment. This exercise prioritized the most critical questions to aid in development of future research programs on the topic.

The biological clogging of natural porous media, often in conjunction with physical or chemical clogging, is encountered under a wide range of conditions. Wastewater disposal, artificial groundwater recharge, in situ bioremediation of contaminated aquifers, construction of water reservoirs, or secondary oil recovery are all affected by this process. The present review provides an overview of the techniques that are used to study clogging in the laboratory, or to monitor it in field applications. After a brief survey of the clogging patterns most commonly observed in practice, and of a number of physical and chemical causes of clogging, the various mechanisms by which microorganisms clog soils and other natural porous media are analyzed in detail. A critical assessment is also provided of the few mathematical models that have been developed in the last few years to describe the biological clogging process. The overall conclusion of the review is that although information is available on several aspects of the biological clogging of natural porous media, further research is required to predict its extent quantitatively in a given situation. This is particularly true in cases that involve complicating factors such as predation or competition among organisms.

Bacterial reductions of the saturated hydraulic conductivity of natural porous media appear to be caused by a wide range of mechanisms, few of which have been carefully studied. Nevertheless, a number of mathematical models have been developed in recent years to describe the microbial clogging process, based on the assumption that bacterial cells form impermeable biofilms uniformly covering pore walls. In the present study, two independent sets of experimental data available in the literature are used to test the existing bioclogging models. To broaden the scope of the assessment, an additional model, initially developed to describe the deep filtration of suspended colloids, is also included in the comparisons. Analysis of the experimental data reveals a clear relationship between the texture of a porous medium and the ability of a given level of biomass to reduce its saturated hydraulic conductivity; at equal biomass, clogging is much more pronounced in fine-textured materials than in coarse-textured ones. In addition, the results of the model comparisons suggest that none of the existing models can predict satisfactorily the saturated hydraulic conductivity reductions observed in fine sands, whereas they fare somewhat better in coarser materials. It is argued that this inadequacy of existing models is due to the continuous biofilm assumption on which they are founded. Indeed, a simplistic model that assumes the biomass to be distributed as plugs instead of as continuous biofilms produces quantitatively much improved predictions of the saturated hydraulic conductivity reductions. Reference is made to the consequences of this observation in terms of future research.

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The "in-stream exposure model" iSTREEM(®) , a Web-based model made freely available to the public by the American Cleaning Institute, provides a means to estimate concentrations of "down-the-drain" chemicals in effluent, receiving waters, and drinking water intakes across national and regional scales under mean annual and low-flow conditions. We provide an overview of the evolution and utility of the iSTREEM model as a screening-level risk assessment tool relevant for down-the-drain products. The spatial nature of the model, integrating point locations of facilities along a hydrologic network, provides a powerful framework to assess environmental exposure and risk in a spatial context. A case study compared national distributions of modeled concentrations of the fragrance 1,3,4,6,7,8-Hexahydro-4,6,6,7,8,8,-hexamethylcyclopenta-γ-2-benzopyran (HHCB) and the insect repellent N,N-Diethyl-m-toluamide (DEET) to available monitoring data at comparable flow conditions. The iSTREEM low-flow model results yielded a conservative distribution of values, whereas the mean-flow model results more closely resembled the concentration distribution of monitoring data. We demonstrate how model results can be used to construct a conservative estimation of the distribution of chemical concentrations for effluents and streams leading to the derivation of a predicted environmental concentration (PEC) using the high end of the concentration distribution (e.g., 90th percentile). Data requirements, assumptions, and applications of iSTREEM are discussed in the context of other down-the-drain modeling approaches to enhance understanding of comparative advantages and uncertainties for prospective users interested in exposure modeling for ecological risk assessment. Integr Environ Assess Manag 2016;12:782-792. © 2016 SETAC.