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Abstract Hybrid TiO2/SiO2 thin films deposited by material printing technique on flexible substrates were prepared, characterized and tested for solar photocatalytic disinfection. Effect of surface hydrophilicity/hydrophobicity of printed coatings on photocatalytic disinfection was studied by means of (i) drinking water contaminated with natural consortia of fecal bacteria (gram-negative: Escherichia coli and total coliforms; gram-positive: Enterococci), and (ii) seawater containing pathogenic gram-negative bacteria (Vibrio owensii, Vibrio alfacsensis and Vibrio harveyi). Inactivation of gram-negative bacteria in drinking water with fecal contamination by solar photocatalysis was slightly more efficient than solar disinfection, while for gram-positive bacteria similar efficiency was observed. These results, in combination with observed release of titanium from coatings (detected by means of inductively coupled plasma atomic emission spectrometer), indicate that TiO2/SiO2 needs further improvements for solar photocatalytic disinfection of drinking water. Efficiency of seawater disinfection towards gram-negative Vibrio spp. (Vibrio owensii, Vibrio alfacsensis and Vibrio harveyi) was significantly enhanced when TiO2/SiO2 coatings were used under natural solar light. Moreover, hydrophobic thin films led to faster Vibrio spp. inactivation as compared to hydrophilic ones, which was attributed to higher bacteria adhesion on hydrophobic coatings. However, decrease of photocatalytic activity of hydrophobic TiO2/SiO2 coatings was observed after ten experimental cycles mainly due to deposition of salts on the surface of photocatalyst. Generally, results of this study suggest that autochthonous bacteria such as Vibrio spp. in seawater are significantly more resistant to solar disinfection in comparison with not autochthonous bacteria such as Escherichia coli, total coliforms and Enterococci in contaminated drinking water.

Alterations of abiotic factors (e.g., river water temperature and discharge) will definitely affect the fundamental processes of aquatic ecosystems. The purpose of this study was to examine the impact of climate change on the structure of fish assemblages in fast-flowing rivers belonging to the catchment of the major Eastern European river, the Nemunas. Five catchments of semi-natural rivers were selected for the study. Projections of abiotic factors were developed for the near (2016-2035) and far future (2081-2100) periods, according to four RCP scenarios and three climate models using the HBV hydrological modelling tool. Fish metric projections were developed based on a multiple regression using spatial data. No significant changes in projections of abiotic and biotic variables are generally expected in the near future. In the far future period, the abiotic factors are projected to change significantly, i.e., river water temperature is going to increase by 4.0-5.1 °C, and river discharge is projected to decrease by 16.7-40.6%, according to RCP8.5. By the end of century, the relative abundance of stenothermal fish is projected to decline from 24 to 51% in the reference period to 0-20% under RCP8.5. Eurythermal fish should benefit from climate change, and their abundance is likely to increase from 16 to 38% in the reference period to 38-65% under RCP8.5. Future alterations of river water temperature will have significantly more influence on the abundance of the analysed fish assemblages than river discharge.

Coral reefs face a diverse array of threats, from eutrophication and overfishing to climate change. As live corals are lost and their skeletons eroded, the structural complexity of reefs declines. This may have important consequences for the survival and growth of reef fish because complex habitats mediate predator-prey interactions [1, 2] and influence competition [3-5] through the provision of prey refugia. A positive correlation exists between structural complexity and reef fish abundance and diversity in both temperate and tropical ecosystems [6-10]. However, it is not clear how the diversity of available refugia interacts with individual predator-prey relationships to explain emergent properties at the community scale. Furthermore, we do not yet have the ability to predict how habitat loss might affect the productivity of whole reef communities and the fisheries they support. Using data from an unfished reserve in The Bahamas, we find that structural complexity is associated not only with increased fish biomass and abundance, but also with nonlinearities in the size spectra of fish, implying disproportionately high abundances of certain size classes. By developing a size spectrum food web model that links the vulnerability of prey to predation with the structural complexity of a reef, we show that these nonlinearities can be explained by size-structured prey refugia that reduce mortality rates and alter growth rates in different parts of the size spectrum. Fitting the model with data from a structurally complex habitat, we predict that a loss of complexity could cause more than a 3-fold reduction in fishery productivity.

This work presents a crude bioethanol fueled integrated power system for backup and off-grid applications. The system is based on ethanol steam reformation to hydrogen that is used in polymer electrolyte fuel cells to produce electricity. We introduce the system design and overall system specifications, and report the experimental process of defining specifications for the produced hydrogen quality, a key variable affecting the final system cost, efficiency and durability. Results from development of individual subsystems are also presented together with discussion on the complete system integration.

In an idealised industrial ecosystem (IE), firms and organisations utilise each other's material and energy flows including wastes and by-products to reduce the system's virgin material and energy input as well as the waste and emission output from the system as a whole, and contribute to sustainable development (SD). IE complements the more conventional individual flow, product, process, organisation, individual actor or sector-focused environmental management approaches and tools with network or systems level approaches. The first research objective of this paper is to construct indicators for IE. The second task is to test the use of these indicators with "what if?" material and energy flow scenarios for the energy and waste system of Satakunta region in Finland including 28 municipalities. Using literature analysis as a source, we arrive at environmental indicators of carbon dioxide (CO2) equivalents, and at economic indicators of fuel, energy and waste management costs and revenues. The social indicators show the employment effects of the waste management system. The scenarios analyse the current situation (0-scenario) against alternative situations in the future. The future scenarios are developed according to the known and anticipated trends in international and national policy and legislation. The indicator application in the scenarios produces social, environmental and economic effects of waste management in four categories: direct negative, direct positive, indirect negative and indirect positive. Industrial ecosystem theory emphasises the utilisation of wastes as a resource with value alongside the objective of reducing waste. Therefore, the indirect positive effects of waste management are important, as well as the conventional focus of waste management, which has usually been on direct positive effects. The main difficulties in our argument are the system boundary definition, the qualitatively different nature of environmental, economic and social effects and indicators as well as the lack of qualitative or interview data on the preferences and interests of the actors involved.

ABSTRACTWind power forecasts are useful tools for power load balancing, energy trading and wind farm operations. Long range monthly‐to‐seasonal forecasting allows the prediction of departures from average weather conditions beyond traditional weather forecast timescales, months in advance. However, it has not yet been demonstrated how these forecasts can be optimally transformed to wind power. The predictable part of a seasonal forecast is for longer monthly averages, not daily averages, but to use monthly averages misses information on variability. To investigate, here a model relating average weather conditions to average wind power output was built, based on the relationship between instantaneous wind speed and power production and incorporating fluctuations in air density due to temperature and wind speed variability. Observed monthly average power output from UK stations was used to validate the model and to investigate the optimal temporal resolution for the data used to drive the model. Multiple simulations of wind power were performed based on reanalysis data, making separate simulations based on monthly, daily and sub‐daily averages, using a distribution defined by the mean across the period to incorporate information on variability. Basing the simulation on monthly averages alone is sub‐optimal: using daily average winds gives the highest correlation against observations. No improvement over this is gained by using sub‐daily averages or including temperature variability. This signifies that to transform seasonal forecasts to wind power a compromise must be made between using the daily averages with debatable skill and the more predictable monthly averages, losing information on day‐to‐day variability.