Impact of climate change and population growth on a risk assessment for endocrine disruption in fish due to steroid estrogens in England and Wales

In England and Wales, steroid estrogens: estrone, estradiol and ethinylestradiol have previously been identified as the main chemicals causing endocrine disruption in male fish. A national risk assessment is already available for intersex in fish arising from estrogens under current flow conditions. This study presents, to our knowledge, the first set of national catchment-based risk assessments for steroid estrogen under future scenarios. The river flows and temperatures were perturbed using three climate change scenarios (ranging from relatively dry to wet). The effects of demographic changes on estrogen consumption and human population served by sewage treatment works were also included. Compared to the current situation, the results indicated increased future risk:the percentage of high risk category sites, where endocrine disruption is more likely to occur, increased. These increases were mainly caused by changes in human population. This study provides regulators with valuable information to prepare for this potential increased risk

Exploiting monitoring data in environmental exposure modelling and risk assessment of pharmaceuticals

In order to establish the environmental impact of an active pharmaceutical ingredient (API), good information on the level of exposure in surface waters is needed. Exposure concentrations are typically estimated using information on the usage of an API as well as removal rates in the patient, the wastewater system and in surface waters. These input data are often highly variable and difficult to obtain, so model estimates often do not agree with measurements made in the field. In this paper we present an approach which uses inverse modelling to estimate overall removal rates of pharmaceuticals at the catchment scale using a hydrological model as well as prescription and monitoring data for a few representative sites for a country or region. These overall removal rates are then used to model exposure across the broader landscape. Evaluation of this approach for APIs in surface waters across England and Wales showed good agreement between modelled exposure distributions and available monitoring data. Use of the approach, alongside estimates of predicted no-effect concentrations for the 12 study compounds, to assess risk of the APIs across the UK landscape, indicated that, for most of the compounds, risks to aquatic life were low. However, ibuprofen was predicted to pose an unacceptable risk in 49.5% of the river reaches studied. For diclofenac, predicted exposure concentrations were also compared to the Environmental Quality Standard previously proposed by the European Commission and 4.5% of river reaches were predicted to exceed this concentration. While the current study focused on pharmaceuticals, the approach could also be valuable in assessing the risks of other ‘down the drain’ chemicals and could help inform our understanding of the important dissipation processes for pharmaceuticals in the pathway from the patient to ecological receptors

CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological and other applications

The Centre for Ecology & Hydrology – Gridded Estimates of Areal Rainfall (CEH-GEAR) data set was developed to provide reliable 1 km gridded estimates of daily and monthly rainfall for Great Britain (GB) and Northern Ireland (NI) (together with approximately 3500 km2 of catchment in the Republic of Ireland) from 1890 onwards. The data set was primarily required to support hydrological modelling. The rainfall estimates are derived from the Met Office collated historical weather observations for the UK which include a national database of rain gauge observations. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall (AAR), was used to generate the daily and monthly rainfall grids. To derive the monthly estimates, rainfall totals from monthly and daily (when complete month available) rain gauges were used in order to obtain maximum information from the rain gauge network. The daily grids were adjusted so that the monthly grids are fully consistent with the daily grids. The CEH-GEAR data set was developed according to the guidance provided by the British Standards Institution. The CEH-GEAR data set contains 1 km grids of daily and monthly rainfall estimates for GB and NI for the period 1890–2012. For each day and month, CEH-GEAR includes a secondary grid of distance to the nearest operational rain gauge. This may be used as an indicator of the quality of the estimates. When this distance is greater than 100 km, the estimates are not calculated due to high uncertainty

Impact of climate change on a risk assessment for intersex in fish due to steroid estrogens

The impact of climate on the natural environment has been a reason for concern for many scientists across the globe. Although water quantity and water resources have been the focus of many studies over the past years, water quality raised less attention. In England and Wales, steroid estrogens, namely estrone (E1), estradiol (E2) and ethinylestradiol (EE2) were identified as being the main chemicals causing intersex in male fish. A national risk assessment is already available for intersex in fish arising from these estrogens under current flow conditions. This study, presents to our knowledge, the first set of national catchment-based risk assessments for steroid estrogen under future flow scenarios. A geographically referenced model was used to predict concentrations in surface waters across England and Wales for E1, E2 and EE2. The river flows were perturbed using 3 climate change scenarios for the 2050’s defined by the 2009 UK Climate Projections (UKCP09). These climate change scenarios were chosen to represent a selection of possible changes: ranging from a relatively dry scenario to the wettest scenario available. The effects of demographic changes on estrogen consumption and population served by sewage treatment works were also included by using population projections for the UK in 2050. These predicted concentrations were then combined into estradiol equivalent (E2 eq) and compared to known biological effect levels to assess the risk of endocrine disruption across England and Wales. This risk was then mapped in order to identify hotspots and quantify how the risk could change in the future compared to the current situation. For the 2050s, depending on the climate scenario selected, between 51 and 54% of the total river length modelled is predicted to be at no risk from endocrine disruption ([E2 eq] < 1 ng/l). A significant proportion of reaches are predicted to be at risk (1 ≤ [E2 eq] < 10 ng/l): between 43 and 45%, and there are between 3 and 4% of reaches estimated to be at high risk ([E2 eq] ≥ 10 ng/l). Compared to the present situation (no risk: 61%, at risk: 38, and high risk: 1%), this study indicates the possibility of an increased future risk of endocrine disruption in particular within the high risk category where fish intersex is likely to occur. This study provides a spatial overview of this possible change in risks and may provide regulators and policy makers useful information to prepare for this potential risk

A global assessment of the temporal and spatial variability of national dilution factors

Of the many factors which influence the exposure of the freshwater aquatic environment to contaminating chemicals none has a more dramatic effect than dilution. Both where and when a chemical enters surface water will make an enormous difference to its impact on wildlife. This is of particular importance for "down-the-drain” chemicals as these substances are discharged to freshwaters via sewer systems after consumer use. However, too often, this dilution capacity is fixed to a “generic” value. Although the spatial variability of dilution factors is often acknowledged, temporal variability is often unaccounted for which may potentially lead to underestimating the environmental risk. To address the magnitude of these dilution differences across the world, estimates of dilution factors were developed globally at a 0.5° resolution using gridded data. Thus, the focus here is on the numbers and location of the human population and the river water available to dilute their waste. The river flows estimates are calculated at both annual and monthly resolution based on readily available annual and monthly runoff estimates. The domestic waste water effluent is derived from combining gridded population and national per capita domestic water use estimates. For each grid cell both annual and monthly dilution factors were generated. This approach allowed the quantification of temporal and spatial variability of dilution factors not only at a catchment level but also at a national level, by means of statistical measures such as median and percentiles. This method revealed the dramatic differences in available dilution of chemicals both within and between countries, for example Canada has on average 4-orders of magnitude more dilution available than Tunisia, and Finland 3-orders of magnitude more than Spain. Over the course of a year, national dilution could vary between 10 and a 1000-fold depending on the country. The work presented here is a significant step forward in terms of understanding the impact of river flow temporal variability on dilution factors at a national and global scale. The proposed methodology has great potential for scientists and decision makers across the globe, as it provides the means to improve screening-level chemical risk assessments

Estimating surface water concentrations of “down-the-drain” chemicals in China using a global model

Predictions of surface water exposure to “down-the-drain” chemicals are presented which employ grid-based spatially-referenced data on average monthly runoff, population density, country-specific per capita domestic water and substance use rates and sewage treatment provision. Water and chemical load are routed through the landscape using flow directions derived from digital elevation data, accounting for in-stream chemical losses using simple first order kinetics. Although the spatial and temporal resolution of the model are relatively coarse, the model still has advantages over spatially inexplicit “unit-world” approaches, which apply arbitrary dilution factors, in terms of predicting the location of exposure hotspots and the statistical distribution of concentrations. The latter can be employed in probabilistic risk assessments. Here the model was applied to predict surface water exposure to “down-the-drain” chemicals in China for different levels of sewage treatment provision. Predicted spatial patterns of concentration were consistent with observed water quality classes for China