Crowdfunding is a response to the financing problem of innovative projects in an environment of severe economic crisis. Its competitive advantage lies in its independence from banking institutions and the distribution of risk among a certain number of funders. Since its inception, the number of successfully completed projects has grown to a point where it has started to suffer a downturn that puts its sustainability at risk. This study concerns this particular period of downturn, in order to identify attributes that characterize it, and to define behavioral stereotypes that may be associated with new projects. On a wide data set from sufficiently contrasted projects, and through the use data mining techniques, we extracted the most influential factors in determining the success or failure of the projects, that will subsequently be grouped together using clustering techniques. Six groups of projects have been identified, each with their own characteristics that define them, two of them clearly guide the projects to success and another one allows the modification its characteristics to move away from failure. This achieved strategy allows us to estimate which potential group would be the result of a new project.

Rare earths have appeared in the market with new energy and Information Technology and Communications (ITC) applications. While their demand grows exponentially, their production is experiencing a bottleneck given that their deposits are concentrated in very few locations, mainly in China. This scarcity and dependence have turned them into strategic minerals, and the location of new sources has become vital. On the other hand, the inevitable trend towards sustainability favors the reuse of waste to avoid the degradation of new areas and the need for waste storage. One of the biggest generators of waste is iron mining. The tailings are stored in huge ponds with consequent environmental problems and risks. As tailings come from a concentration process, they incorporate different amounts of rare earths depending on their separation behavior. To evaluate the viability of these resources as potential repositories of rare earths, samples of different types of deposits and treatments were selected. The presence of different rare earths in them was determined through spectroscopy techniques to evaluate their use as a deposit. The results show an increase in the concentration of rare earths, especially high-density ones, which, although currently not economically feasible given the very wide geographical distribution of iron mining, represent a fundamental strategic reserve.

Fresh-cut vegetables, namely those that undergo processes such as washing, sorting, or chopping while keeping their fresh state, constitute an important market element nowadays. Among those operations, the washing step becomes really important due both to the extensive use of water resources and to the utilization of controversial water sanitizing agents, such as chlorine. To ideally eliminate those chlorinated compounds while decreasing water consumption, four novel filtrating technologies (pulsed corona discharge combined with nanofiltration, NF-PCD; classical ultrafiltration, UF; nanofiltration membranes integrating silver nanoparticles, NF-AgNP; and microfiltration with cellulose acetate membranes containing chitin nanocrystals, ChCA) have been proposed to eliminate any contaminating agent in recirculated water. Here, we performed a life cycle assessment (LCA) to assess the environmental effects of introducing these new solutions and to compare those impacts with the burden derived from the current strategy. The novel technologies showed a decreased environmental burden, mainly due to the enhanced water recirculation and the subsequent decrease in energy consumption for pumping and cooling the water stream. The environmental gain would be maintained even if a certain amount of chlorine was still needed. This analysis could serve as an aid to decision-making while evaluating the introduction of new sanitizing techniques.

Many organizations are currently face significant challenges in terms of sustainability and technological development. Achieving sustainability in business activities, interweaving social, economic, and environmental perspectives, is one of the most challenging goals for companies. On the other hand, as technology advances exponentially, organizations grow in a linear way. This fact causes a gap which increases over the time. Models and tools have been developed to try to solve both problems separately; on one side to make the organization grow exponentially, and on the other side to incorporate sustainability into the business model. However, they do not allow enough time to know if the actions carried out really achieve their aim. The model presented provides a solution to both problems by monitoring the evolution of organizations towards an exponential structure through the analysis of the project portfolio. The main objective is to know how the orientation of ongoing projects has changed during the last period, in order to position them in terms of achieving the desired sustainability-oriented transformation. With the model designed, it is possible to know if the actions developed by the company are really heading towards a sustainable model and exponential growth. With the aim of validating the model, it has been applied in an innovation organization. With this model, the level of exponential progress of the organization was determined, as well as the goals that have been attained best and worst so far.

Off-gas is one of the by-products of the steelmaking process. Its potential energy can be transformed into heat and electricity by means of cogeneration. A case study using a coke oven and Linz–Donawitz converter gas is presented. This work addresses the gas allocation problem for a cogeneration system producing steam and electricity. In the studied facility, located in northern Spain, the annual production of the plant requires 95,000 MWh of electrical energy and 525,000 MWh of thermal energy. The installed electrical and thermal power is 20.4 MW and 81 MW, respectively. A mixed integer linear programming model is built to optimize gas allocation, thus maximizing its benefits. This model is applied to a 24-h scenario with real data from the plant, where gas allocation decision-making was performed by the plant operators. Application of the model generated profit in a scenario where there were losses, increasing benefits by 16.9%. A sensitivity analysis is also performed. The proposed model is useful not only from the perspective of daily plant operation but also as a tool to simulate different design scenarios, such as the capacity of gasholders.

Nowadays, the industry produces an enormous amount of solid waste that has very negative environmental effects. Owing to waste variety and its scattered sites of production, selecting the most proper solid waste treatment is difficult. Simultaneously, social concern about environmental sustainability rises every day and, as a consequence, improvement on waste treatment systems is being demanded. However, when a waste treatment system is being designed, not only environmental but also technical and economic issues should be considered. This article puts forward a methodology to provide industrial factories with an easy way to identify, evaluate and select the most suitable solid waste treatment.