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“More research is needed” is an iconic catchphrase used by scientists worldwide. Yet policy and management decisions are continually being made with variable levels of reliance on scientific knowledge. Funding agencies have provided incentives for knowledge exchange at the interfaces between science and policy or practice, yet it remains the exception rather than the rule within academic institutions. An important step forward would be the establishment and professionalization of knowledge brokering (i.e., as a complement to existing technology transfer and communications departments). This would require an explicit commitment of resources by both funding agencies and institutions. Many academic scientists are genuinely interested in the applications of their research. This interest could be stimulated by providing support for the process of knowledge brokering and by integrating the natural, social, and engineering sciences to address broad policy- and practice-relevant questions.

What methods and procedures support transdisciplinary knowledge integration? We address this question by exploring knowledge integration within four thematic synthesis processes of the Swiss National Research Programme 61 Sustainable Water Management (NRP 61). Drawing on literature from inter- and transdisciplinary research, we developed an analytical framework to map different methods and procedures of knowledge integration. We use this framework to characterize the variety of methods and procedures that were combined in the four processes to produce thematic synthesis reports. We suggest that the variety of combinations observed reflects the different objectives and questions that guided the processes of knowledge integration as well as the different roles that leaders assumed in these processes. Although the framework was developed in the course of NRP 61, we consider it as a basis for designing ex ante new synthesis processes by defining and sequencing different synthesis stages and by identifying, for each stage, the contributions of specific scientific and societal actors, the purpose of their contributions, and the methods and procedures supporting their contributions. Used in a formative evaluation process, the framework supports reflection on and adaptation of synthesis processes and also facilitates the generation of new knowledge for designing future processes.

The Fourier harmonics,$$v_2$$v 2 and$$v_3$$v 3 of negative pions are measured at center-of-mass energy per nucleon pair of$$\\sqrt{s_{\\textrm{NN}}}$$s NN = 17.3 GeV around midrapidity by the CERES/NA45 experiment at the CERN SPS in 0–30% central PbAu collisions with a mean centrality of 5.5%. The analysis is performed in two centrality bins as a function of the transverse momentum$$\\mathrm {p_{\\textrm{T}}}$$p T from 0.05 GeV/ c to more than 2 GeV/ c . This is the first measurement of the$$v^{1/3}_{3}/v^{1/2}_{2}$$v 3 1 / 3 / v 2 1 / 2 ratio as a function of transverse momentum at SPS energies, that reveals, independently of the hydrodynamic models, hydrodynamic behavior of the formed system. For$$\\mathrm {p_{\\textrm{T}}}$$p T above 0.5 GeV/ c , the ratio is nearly flat in accordance with the hydrodynamic prediction and as previously observed by the ATLAS and ALICE experiments at the much higher LHC energies. The results are also compared with the SMASH-vHLLE hybrid model predictions, as well as with the SMASH model applied alone.

Arsenate [As(V)]-respiring bacteria affect the speciation and mobilization of arsenic in the environment. This can lead to arsenic contamination of drinking water supplies and deleterious consequences for human health. Using molecular genetics, we show that the functional gene for As(V) respiration, arrA , is highly conserved; that it is required for As(V) reduction to arsenite when arsenic is sorbed onto iron minerals; and that it can be used to identify the presence and activity of As(V)-respiring bacteria in arsenic-contaminated iron-rich sediments. The expression of arrA thus can be used to monitor sites in which As(V)-respiring bacteria may be controlling arsenic geochemistry.

An artificial nanostructure inspired by the sea anemone can be used for efficient removal of a wide range of water contaminants.

The Fourier harmonics, v 2 and v 3 of negative pions are measured at center-of-mass energy per nucleon pair of s NN = 17.3 GeV around midrapidity by the CERES/NA45 experiment at the CERN SPS in 0–30% central PbAu collisions with a mean centrality of 5.5%. The analysis is performed in two centrality bins as a function of the transverse momentum p T from 0.05 GeV/ c to more than 2 GeV/ c . This is the first measurement of the v 3 1 / 3 / v 2 1 / 2 ratio as a function of transverse momentum at SPS energies, that reveals, independently of the hydrodynamic models, hydrodynamic behavior of the formed system. For p T above 0.5 GeV/ c , the ratio is nearly flat in accordance with the hydrodynamic prediction and as previously observed by the ATLAS and ALICE experiments at the much higher LHC energies. The results are also compared with the SMASH-vHLLE hybrid model predictions, as well as with the SMASH model applied alone.

Appropriately bounded integration can be a basis for sustainable management of water resources. Sustainable management of water resources (including provision of safe and reliable supplies for drinking water and irrigation, adequate sanitation, protection of aquatic ecosystems, and flood protection) poses enormous challenges in many parts of the world. Despite the global abundance of water and the mainly renewable character of this resource, it is estimated that one-fifth of the world's population lives under conditions of water scarcity ( 1 ). This is primarily the result of the heterogeneous distribution of freshwater in space and time, which is exacerbated by economic disparities, civil unrest, and failures of institutions ( 2 ).

Even though waste is an inevitable accompaniment to all processes, contemplating an end to waste can force us to think about how we define, generate, and manage it. Two common definitions of waste are a substance or object that is discarded and the avoidable loss of a resource. The current waste management practices in industrialized countries are widely recognized to be unsustainable, yet it is clear that we are not changing our practices effectively or fast enough. What are the impediments and how can we overcome them?

Higher education and research institutions are critical to the well-being and success of societies, meaning their financial support is strongly in the public interest. At the same time, value-for-money principles demand that such investment delivers. Unfortunately, these principles are currently violated by one of the biggest sources of public funding inefficiency: sexism.

Monitoring the Sustainable Development Goal (SDG) 6 for water and sanitation builds on monitoring frameworks that were developed for the Millennium Development Goals (MDGs), specifically the WHO/UNICEF Joint Monitoring Programme (JMP). Yet, since SDG 6 goes beyond the MDG focus on drinking water and sanitation, it also significantly expands monitoring and reporting responsibilities. The target to improve water quality (Target 6.3) calls for water quality monitoring and data reporting that are likely to pose a significant challenge to countries that lack an established monitoring program. At the same time, redundant burdens may be imposed on countries that already have established programs and report out water quality data to inter- or supranational agencies. In this context, there is a risk that the intention that water quality data should serve as a basis for evidence-based decision making will become subsidiary to the resource-intensive activities of data collection and management. Alternatively, policies could be designed based on historical experience with measures of proven effectiveness, prioritizing policies that could have multiple benefits. Policies could be implemented in parallel with the development of monitoring programs and conventional monitoring data could be complemented by information gained from sources such as remote sensing and unstructured data.