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In the current study, we examine the Indonesian government's watershed management program, which was established in 2001. In 2005, the Coordination Team for Rescue of Water Resources (CTRWR) was established to execute the program on a national level. However, at the time, field implementation was a sectoral interest due to the lack of program integration. To this end, the Indonesian government promoted integrated watershed management in 2009, which since then has been implemented by all stakeholders (in Top–Down management form), with application limited to preparing and planning documents. This is mainly driven by the stakeholders’ lack of understanding with regard to watershed systems as integrated management units. Field implementation results have not yet been realized, including the promotion of community-based watershed management (through Bottom–Up management). The purpose of our research was to determine the index numbers by measuring the level of cooperation between watershed management workers based on the Village Watershed Model (VWM) specifically surface water which includes six variables: planning, participation, institutional, fund sharing, gender, and management systems. The method used was an ordinal measure with the Likert scale. Our data showed successful watershed management, in which five of the six VWM variables—planning, participation, institutional, fund sharing, and management systems—were in the “good” category with indices ranging from 73.08 to 78.27. The gender variable index (69.12) was in the “medium” category.

Grid connected energy storage systems are regarded as promising solutions for providing ancillary services to electricity networks and to play an important role in the development of smart grids. Thus far, the more mature battery technologies have been installed in pilot projects and studies have indicated their main advantages and shortcomings. The main concerns for wide adoption are the overall cost, the limited number of charging cycles (or lifetime), the depth of discharge, the low energy density and the sustainability of materials used. Vanadium Redox Flow Batteries (VRFB) are a promising option to mitigate many of these shortcomings, and demonstration projects using this technology are being implemented both in Europe and in the USA. This study presents a model using MATLAB/Simulink, to demonstrate how a VRFB based storage device can provide multi-ancillary services, focusing on frequency regulation and peak-shaving functions. The study presents a storage system at a medium voltage substation and considers a small grid load profile, originating from a residential neighbourhood and fast charging stations demand. The model also includes an inverter controller that provides a net power output from the battery system, in order to offer both services simultaneously. Simulation results show that the VRFB storage device can regulate frequency effectively due to its fast response time, while still performing peak-shaving services. VRFB potential in grid connected systems is discussed to increase awareness of decision makers, while identifying the main challenges for wider implementation of storage systems, particularly related to market structure and standardisation requirements.

AbstractThis paper presents the experimental plans and designs as well as examples of predictive modeling of a pilot-scale CO2 injection experiment at the Heletz site (Israel). The overall objective of the experiment is to find optimal ways to characterize CO2 -relevant in-situ medium properties, including field-scale residual and dissolution trapping, to explore ways of characterizing heterogeneity through joint analysis of different types of data, and to detect leakage. The experiment will involve two wells, an injection well and a monitoring well. Prior to the actual CO2 injection, hydraulic, thermal and tracer tests will be carried out for standard site characterization. The actual CO2 injection experiments will include (i) a single well injection-withdrawal experiment, with the main objective to estimate in-situ residual trapping and (ii) a two-well injection-withdrawal test with injection of CO2 in a dipole mode (injection of CO2 in one well with simultaneous withdrawal of water in the monitoring well), with the objective to understand the CO2 transport in heterogeneous geology as well as the associated dissolution and residual trapping. Tracers will be introduced in both experiments to further aid in detecting the development of the phase composition during CO2 transport. Geophysical monitoring will also be implemented. By means of modeling, different experimental sequences and injection/withdrawal patterns have been analyzed, as have parameter uncertainties. The objectives have been to (i) evaluate key aspects of the experimental design, (ii) to identify key parameters affecting the fate of the CO2 and (iii) to evaluate the relationships between measurable quantities and parameters of interest.

AbstractSulfate reduction in salt‐rich wastewaters using unadapted granular sludge was investigated in 0.9 L UASB reactors (pH 7.0 ± 0.2; hydraulic retention time from 8–14 h) fed with acetate, propionate, or ethanol at organic loading rates up to 10 gCOD.L−1.day−1 and in excess sulfate (COD/SO of 0.5). High‐rate sulfate reduction rates (up to 3.7 gSO42‐.L−1.day−1) were achieved at salinities exceeding 50 gNaCl.L−1 and 1 gMgCl2.L−1. Sulfate reduction proceeded at a salinity of up to 70 gNaCl.L−1 and 1 gMgCl2.L−1 (corresponding to a conductivity of about 85–90 mS.cm−1), although at lower rates compared to a conductivity of 60–70 mS.cm−1. Ethanol as well as propionate were suitable substrates for sulfate reduction, with acetate and sulfide as the end products. The successful high‐rate treatment was due to the proliferation of a halotolerant incomplete oxidizing SRB population present in the unadapted inoculum sludge. Bioaugmentation of this sludge with the acetate oxidizing halotolerant SRB Desulfobacter halotolerans was unsuccessful, as the strain washed out from the UASB reactor without colonizing the UASB granules. © 2004 Wiley Periodicals, Inc.

Reverse electrodialysis (RED) is a technology to generate power from mixing waters with different salinity. The net power density (i.e. power per membrane area) is determined by 1) the membrane potential, 2) the ohmic resistance, 3) the resistance due to changing bulk concentrations, 4) the boundary layer resistance and 5) the power required to pump the feed water. Previous power density estimations often neglected the latter three terms. This paper provides a set of analytical equations to estimate the net power density obtainable from RED stacks with spacers and RED stacks with profiled membranes. With the current technology, the obtained maximum net power density is calculated at 2.7 W/m2. Higher power densities could be obtained by changing the cell design, in particular the membrane resistance and the cell length. Changing these parameters one and two orders of magnitude respectively, the calculated net power density is close to 20 W/m2

Abstract This study investigated in-situ and ex-situ biological methanation strategies for biogas upgrading potential. The addition and circulation of hydrogen with a ceramic gas diffuser unit revealed positive effects on the methanogenic process. A short-term maximum methane productivity of 2.5 L CH4 per L reactor volume per day (LVR−1 d−1) was obtained in-situ. Adverse effects of elevated dissolved hydrogen concentrations on acetogenesis became evident. Ex-situ methanation in a reactor subjected to gas recirculation for recurrent 24 h periods achieved methane formation rates of 3.7 L CH4 LVR−1 d−1. A biomethane with methane concentrations in excess of 96% successfully demonstrated the potential for gas grid injection. A theoretic model supplying gases continuously into a sequential ex-situ reactor system and steadily displacing the upgraded biogas confirmed similar methane formation performance and was advanced to a full-scale concept. Gas conversion efficiency of 95% producing biomethane at 85% methane content was attained. A hybrid model, where an in-situ grass digester is followed by an ex-situ reactor, is proposed as a novel upgrading strategy.

Industry 4.0 concepts and technologies ensure the ongoing development of micro- and macro-economic entities by focusing on the principles of interconnectivity, digitalization, and automation. In this context, artificial intelligence is seen as one of the major enablers for Smart Logistics and Smart Production initiatives. This paper systematically analyzes the scientific literature on artificial intelligence, machine learning, and deep learning in the context of Smart Logistics management in industrial enterprises. Furthermore, based on the results of the systematic literature review, the authors present a conceptual framework, which provides fruitful implications based on recent research findings and insights to be used for directing and starting future research initiatives in the field of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in Smart Logistics.

This paper analyses the role of barriers preventing the worldwide take-up of a clean technology: the electrical arc furnace. It also identifies which barriers affect a parameter that summarises the combined effect of all of them. The first step, determination of the combined effect of the barriers, is carried out using a novel approach to model the diffusion of innovations. This new approach is composed only by terms that account for the driver of innovations and the parameter that summarises the effect of barriers. The objective quantification of the effect of barriers in the diffusion of innovations opens up new opportunities for designing policies to overcome the barriers identified as the most relevant, for identifying the effect of existing policies, for relating innovation indicators with those barriers or for better incorporating the effect of barriers in bottom-up models that forecast the technological evolution of the economy.