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Abstract Recent publications on the successful mineralisation of carbon dioxide in basalts in Iceland and Washington State, USA, have shown that mineral storage can be a serious alternative to more mainstream geologic carbon storage efforts to lock away permanently carbon dioxide. In this study we look at the pore solution chemistry and mineralogy of basaltic glass and crystalline basalt under post-injection conditions, i.e. after rise of the pH via matrix dissolution and the first phase of carbonate formation. Experimental findings indicate that further precipitation of carbonates under more alkaline conditions is highly dependent on the availability of divalent cations. If the pore water is deficient in divalent cations, smectites and/or zeolites will dominate the secondary mineralogy of the pore space, depending on the basalt matrix. At low carbonate alkalinity no additional secondary carbonates are expected to form meaning the remaining pore space is lost to secondary silicates, irrespective of the basalt matrix. At high carbonate alkalinity, some of this limited storage volume may additionally be occupied by dawsonite −if the Na concentration in the percolating groundwater (brine) is high. Using synthetic seawater as a proxy for the groundwater composition and thus furnishing considerable amounts of divalent cations to the carbonated solution, results in massive precipitation of calcite, magnesite, and other Ca/Mg-carbonates under already moderate carbonate alkalinity. More efficient use of the basaltic storage volume can thus be attained by promoting formation of secondary carbonates compared to the inevitable formation of secondary silicate phases at higher pH. This can be done by ensuring that the pore water does not become depleted in divalent cations, even after carbonate formation. Using seawater as carbonating fluid or injection of CO2 into the basaltic oceanic crust, where saline fluids percolate, can reach this goal. However, such an approach needs sophisticated reactive transport modelling to adjust CO2 injection rates in order to avoid too rapid carbonate deposition and clogging of the pore space too close to the injection well.

China is confronted with an unprecedented water crisis regarding its quantity and quality. In this study, we quantified the dynamics of China?s embodied water use and chemical oxygen demand (COD) discharge from 2010 to 2015. The analysis was conducted with the latest available water use data across sectors in primary, secondary and tertiary industries and input?output models. The results showed that (1) China?s water crisis was alleviated under urbanisation. Urban consumption occupied the largest percentages (over 30%) of embodied water use and COD discharge, but embodied water intensities in urban consumption were far lower than those in rural consumption. (2) The ?new normal? phase witnessed the optimisation of China?s water use structures. Embodied water use in light-manufacturing and tertiary sectors increased while those in heavy-manufacturing sectors (except chemicals and transport equipment) dropped. (3) Transformation of China?s international market brought positive effects on its domestic water use. China?s water use (116?80 billion tonnes (Bts))(9) and COD discharge (3.95?2.22 million tonnes (Mts)) embodied in export tremendously decreased while its total export values (11?25 trillion CNY) soared. Furthermore, embodied water use and COD discharge in relatively low-end sectors, such as textile, started to transfer from international to domestic markets when a part of China?s production activities had been relocated to other developing countries.

Abstract An assessment of the human impact on the global water cycle requires estimating the volume of water withdrawn for irrigated agriculture. A key parameter in this calculation is the irrigation efficiency, which corrects for the fraction of water lost between irrigation withdrawals and the crop due to management, distribution or conveyance losses. Here we show that the irrigation efficiency used in global irrigation models is flawed for it overlooks key ambiguities in partial efficiencies, irrigation technologies, the definition of ‘large-scale’ irrigated areas or managerial factors. Once accounted for, these uncertainties can make irrigation withdrawal estimates fluctuate by more than one order of magnitude at the country level. Such variability is larger and leads to more extreme values than that caused by the uncertainties related with climate change. Our results highlight the need to embrace deep uncertainties in irrigation efficiency to prevent the design of shortsighted policies at the river basin-water-agricultural interface.

Silver nanoparticles (AgNP) are currently defined as emerging pollutants in surface water ecosystems. Whether the toxic effects of AgNP towards freshwater organisms are fully explainable by the release of ionic silver (Ag(+)) has not been conclusively elucidated. Long-term effects to benthic microbial communities (periphyton) that provide essential functions in stream ecosystems are unknown. The effects of exposure of periphyton to 2 and 20 μg/L Ag(+) (AgNO3) and AgNP (polyvinylpyrrolidone stabilised) were investigated in artificial indoor streams. The extracellular polymeric substances (EPS) and 3D biofilm structure, biomass, algae species, Ag concentrations in the water phase and bioassociated Ag were analysed. A strong decrease in total Ag was observed within 4 days. Bioassociated Ag was proportional to dissolved Ag indicating a rate limitation by diffusion across the diffusive boundary layer. Two micrograms per liter of AgNO3 or AgNP did not induce significant effects despite detectable bioassociation of Ag. The 20-μg/L AgNO3 affected green algae and diatom communities, biomass and the ratio of polysaccharides to proteins in EPS. The 20-μg/L AgNO3 and AgNP decreased biofilm volume to about 50 %, while the decrease of biomass was lower in 20 μg/L AgNP samples than the 20-μg/L AgNO3 indicating a compaction of the NP-exposed biofilms. Roughness coefficients were lower in 20 μg/L AgNP-treated samples. The more traditional endpoints (biomass and diversity) indicated silver ion concentration-dependent effects, while the newly introduced parameters (3D structure and EPS) indicated both silver ion concentration-dependent effects and effects related to the silver species applied.

Global-scale hydrological models are routinely used to assess water scarcity, flood hazards and droughts worldwide. Recent efforts to incorporate anthropogenic activities in these models have enabled more realistic comparisons with observations. Here we evaluate simulations from an ensemble of six models participating in the second phase of the Inter-Sectoral Impact Model Inter-comparison Project (ISIMIP2a). We simulate monthly runoff in 40 catchments, spatially distributed across eight global hydrobelts. The performance of each model and the ensemble mean is examined with respect to their ability to replicate observed mean and extreme runoff under human-influenced conditions. Application of a novel integrated evaluation metric to quantify the models' ability to simulate timeseries of monthly runoff suggests that the models generally perform better in the wetter equatorial and northern hydrobelts than in drier southern hydrobelts. When model outputs are temporally aggregated to assess mean annual and extreme runoff, the models perform better. Nevertheless, we find a general trend in the majority of models towards the overestimation of mean annual runoff and all indicators of upper and lower extreme runoff. The models struggle to capture the timing of the seasonal cycle, particularly in northern hydrobelts, while in southern hydrobelts the models struggle to reproduce the magnitude of the seasonal cycle. It is noteworthy that over all hydrological indicators, the ensemble mean fails to perform better than any individual model—a finding that challenges the commonly held perception that model ensemble estimates deliver superior performance over individual models. The study highlights the need for continued model development and improvement. It also suggests that caution should be taken when summarising the simulations from a model ensemble based upon its mean output. Environmental Research Letters, 13 (6) ISSN:1748-9326 ISSN:1748-9318