Trait groups as management entities in a complex,multispecies reef fishery

Localized stressors compound the ongoing climate-driven decline of coral reefs, requiring natural resource managers to work with rapidly shifting paradigms. Trait-based adaptive management (TBAM) is a new framework to help address changing conditions by choosing and implementing management actions specific to species groups that share key traits, vulnerabilities, and management responses. In TBAM maintenance of functioning ecosystems is balanced with provisioning for human subsistence and livelihoods. We first identified trait-based groups of food fish in a Pacific coral reef with hierarchical clustering. Positing that trait-based groups performing comparable functions respond similarly to both stressors and management actions, we ascertained biophysical and socioeconomic drivers of trait-group biomass and evaluated their vulnerabilities with generalized additive models. Clustering identified 7 trait groups from 131 species. Groups responded to different drivers and displayed divergent vulnerabilities; human activities emerged as important predictors of community structuring. Biomass of small, solitary reef-associated species increased with distance from key fishing ports, and large, solitary piscivores exhibited a decline in biomass with distance from a port. Group biomass also varied in response to different habitat types, the presence or absence of reported dynamite fishing activity, and exposure to wave energy. The differential vulnerabilities of trait groups revealed how the community structure of food fishes is driven by different aspects of resource use and habitat. This inherent variability in the responses of trait-based groups presents opportunities to apply selective TBAM strategies for complex, multispecies fisheries. This approach can be widely adjusted to suit local contexts and priorities.     

Multi-objective optimization of waste and resource management in industrial networks – Part I: Model description

This article presents a general multi-objective mixed-integer linear programming (MILP) optimization model aimed at providing decision support for waste and resources management in industrial networks. The MILP model combines material flow analysis, process models of waste treatments and other industrial processes, life cycle assessment, and mathematical optimization techniques within a unified framework. The optimization is based on a simplified representation of industrial networks that makes use of linear process models to describe the flows of mass and energy. Waste-specific characteristics, e.g. heating value or heavy metal contamination, are considered explicitly along with potential technologies or process configurations. The systems perspective, including both provision of waste treatment and industrial production, enables constraints imposed upon the systems, e.g. available treatment capacities, to be explicitly considered in the model. The model output is a set of alternative system configurations in terms of distribution of waste and resources that optimize environmental and economic performance. The MILP also enables quantification of the improvement potential compared to a given reference state. Trade-offs between conflicting objectives are identified through the generation of a set of Pareto-efficient solutions. This information supports the decision making process by revealing the quantified performance of the efficient trade-offs without relying on weighting being expressed prior to the analysis. Key features of the modeling approach are illustrated in a hypothetical case. The optimization model described in this article is applied in a subsequent paper (Part II) to assess and optimize the thermal treatment of sewage sludge in a region in Switzerland.     

Based on material flow analysis: Value chain analysis of China iron resources

Iron is an important basic resource for national economic development in China. It is of great strategic importance for the sustainable development of China's economy to study the utilization and circulation status of iron resources. In this paper, using the material flow and value chain analysis method, we quantitatively analyzed the value flow of iron resources in China. According to the value chain and price theory of element M, a value stream diagram of iron resources corresponding to the substance flow chart was plotted. Based on the previous material flow analysis result of iron resources, the diagram quantitatively depicted the value of the circulating flow of iron resources in China in 2011. The results show that by recycling materials, the value of the circulating flow of iron resources can bring considerable economic benefits to both producers and consumers. In the production stage, the expenditures of the entire economic system was reduced by 91.77 billion RMB by circulating iron and the income increased by 95 billion RMB by recycling home scrap, which was generated in the crude steel production stage. In the use stage of iron and steel products, the recycling of old scrap enabled the entire economic system to recover 370.78 billion RMB. It should be noted that analysis within a single framework of physical and economic characteristics of iron resources in the economic system can further extend the research chain of substance flow and value flow at the macro level, enhancing the economic value of substances flow research. In addition, by tracking and depicting the value flow cycle of elements, the improvement potentials and the value situations can be determined to provide useful information for conducting processing and technological innovation for waste minimization.     

Techno-economic analysis and environmental impact assessment of energy recovery from Municipal Solid Waste (MSW) in Brazil

Due to the lack of appropriate policies in the last decades, 60% of Brazilian cities still dump their waste in non-regulated landfills (the remaining ones dump their trash in regulated landfills), which represent a serious environmental and social problem. The key objective of this study is to compare, from a techno-economic and environmental point of view, different alternatives to the energy recovery from the Municipal Solid Waste (MSW) generated in Brazilian cities. The environmental analysis was carried out using current data collected in Betim, a 450,000 inhabitants city that currently produces 200 tonnes of MSW/day. Four scenarios were designed, whose environmental behaviour were studied applying the Life Cycle Assessment (LCA) methodology, in accordance with the ISO 14040 and ISO 14044 standards. The results show the landfill systems as the worst waste management option and that a significant environmental savings is achieved when a wasted energy recovery is done. The best option, which presented the best performance based on considered indicators, is the direct combustion of waste as fuel for electricity generation. The study also includes a techno-economical evaluation of the options, using a developed computer simulation tool. The economic indicators of an MSW energy recovery project were calculated. The selected methodology allows to calculate the energy content of the MSW and the CH₄ generated by the landfill, the costs and incomes associated with the energy recovery, the sales of electricity and carbon credits from the Clean Development Mechanism (CDM). The studies were based on urban centres of 100,000, 500,000 and 1,000,000 inhabitants, using the MSW characteristics of the metropolitan region of Belo Horizonte. Two alternatives to recovering waste energy were analyzed: a landfill that used landfill biogas to generate electricity through generator modules and a Waste-to-Energy (WtE) facility also with electricity generation. The results show that power generation projects using landfill biogas in Brazil strongly depend on the existence of a market for emissions reduction credits. The WtE plant projects, due to its high installation, Operation and Maintenance (O&M) costs, are highly dependent on MSW treatment fees. And they still rely on an increase of three times the city taxes to become attractive.     

Environmental evaluation of plastic waste management scenarios

The management of the plastic fraction is one of the most debated issues in the discussion on integrated municipal solid waste systems. Both material and energy recovery can be performed on such a waste stream, and different separate collection schemes can be implemented. The aim of the paper is to contribute to the debate, based on the analysis of different plastic waste recovery routes. Five scenarios were defined and modelled with a life cycle assessment approach using the EASEWASTE model. In the baseline scenario (P0) the plastic is treated as residual waste and routed partly to incineration with energy recovery and partly to mechanical biological treatment. A range of potential improvements in plastic management is introduced in the other four scenarios (P1–P4). P1 includes a source separation of clean plastic fractions for material recycling, whereas P2 a source separation of mixed plastic fraction for mechanical upgrading and separation into specific polymer types, with the residual plastic fraction being down-cycled and used for “wood items”. In P3 a mixed plastic fraction is source separated together with metals in a “dry bin”. In P4 plastic is mechanically separated from residual waste prior to incineration.A sensitivity analysis on the marginal energy was carried out. Scenarios were modelled as a first step assuming that marginal electricity and heat were based on coal and on a mix of fuels and then, in the sensitivity analysis, the marginal energy was based on natural gas.The study confirmed the difficulty to clearly identify an optimal strategy for plastic waste management. In fact none of the examined scenarios emerged univocally as the best option for all impact categories. When moving from the P0 treatment strategy to the other scenarios, substantial improvements can be obtained for “Global Warming”. For the other impact categories, results are affected by the assumption about the substituted marginal energy. Nevertheless, irrespective of the assumptions on marginal energy, scenario P4, which implies the highest quantities of specific polymer types sent to recycling, resulted the best option in most impact categories.