Wood Polypropylene (PP) Composites Manufactured by Mango Wood Waste with Virgin or Recycled PP: Mechanical,Morphology, Melt Flow Index and Crystalline Behaviour

Compositions of wood-polypropylene composites (WPCs) are prepared through melt compounding followed by injection moulding. WPCs are formulated for eight compositions with a different weight ratio of wood, virgin or recycled polypropylene and coupling agent. WPCs compositions are compared in terms of Melt Flow Index, Tensile, FESEM images, Flexural and crystallinity index for same operating variable conditions. From the results, recycled polypropylene based WPCs are superior in comparison to virgin polypropylene based WPCs. With the addition of 5 % coupling agent in recycled polypropylene-based composites for 45:50 composition, tensile and flexural values of WPCs are higher in comparison to all composition and neat virgin or recycled polypropylene. This work stands for the utilization of waste wood with recycled plastic for replacement of wood and virgin plastic.     

Value chain for next-generation biofuels: resilience and sustainability of the product life cycle

Multiple factors including climate change, price uncertainties, and geopolitical instability have prompted many industries to investigate the feasibility of replacing traditional petroleum-based fuels with biofuel alternatives. However, to make this transition successful, these new biofuels must be environmentally sustainable and the necessary support infrastructure must be in place to make the production, distribution, and storage of these biofuels technologically feasible and cost effective. Developing a value chain, spanning from feedstock production to distribution to end users, requires garnering buy-in from multiple stakeholders by demonstrating environmental, economic, and social benefits and incentives. Two critical factors are the environmental benefits achieved from the use of the biofuel technology and the degree of resilience of the value chain to emergent conditions to ensure steady supply to consumers. Moreover, different biofuel pathways have different costs, benefits, and risks which must be compared. In this paper, we describe how environmental sustainability can be modeled using life cycle assessment (LCA) and how the resilience of value chain initiatives can be modeled using a scenario-based decision model. We then describe how sustainability and resilience assessments can be integrated in an iterative, anticipatory LCA framework. These assessments can be used as the basis for a business case for various investments, as well as a means for promoting responsible innovations, with the aviation industry used as a case study.     

How Good? Ethical Criteria for a ‘Good Life’ for Farm Animals

The Farm Animal Welfare Council’s concept of a Good Life gives an idea of an animal’s quality of life that is over and above that of a mere life worth living. The concept needs explanation and clarification, in order to be meaningful, particularly for consumers who purchase farm animal produce. The concept could allow assurance schemes to apply the label to assessments of both the potential of each method of production, conceptualised in ways expected to enhance consumers’ engagement such as ‘naturalness’ and ‘freedom’; and the concept of a life worth living as a safeguard threshold below which no animal’s actual welfare should fall, based on each animal’s overall affective states. This may provide a framework for development of the Good Life concept, within scientific and sociological fields, in order to allow reliable and influential use by assessors, consumers and retailers.     

Trace elements in surface sediments of the Hooghly (Ganges) estuary: distribution and contamination risk assessment

Our objective was to evaluate distribution and accumulation of trace elements (TEs) in surface sediments along the Hooghly (Ganges) River Estuary, India, and to assess the potential risk with view to human health. The TE concentrations (mg kg^?1 dry weight) exhibited a wide range in the following order: Al (31.801 ± 15.943) > Fe (23.337 ± 7584) > Mn (461 ± 147) > S (381 ± 235) > Zn (54 ± 18) > V (43 ± 14) > Cr (39 ± 15) > As (34 ± 15) > Cu (27 ± 11) > Ni (24 ± 9) > Se (17 ± 8) > Co (11 ± 3) > Mo (10 ± 2) > Hg (0.02 ± 0.01). Clay, silt, iron, manganese and sulphur were important for the accumulation of TE in the sediments as confirmed by factor analysis and Pearson correlation. The accumulation and dispersal of TEs were most likely to be governed by both tide-induced processes and anthropogenic inputs from point and non-point sources. Enrichment factor analysis and geoaccumulation index revealed serious contamination of the sediments with Se and As, while comparing the consensus-based sediment quality guidelines (SQGs), adverse biological effects to benthic fauna might be caused by As, Cu, Ni and Cr. This investigation may serve as a model study and recommends continuous monitoring of As, Se, Cu, Ni and Cr to ascertain that SQGs with respect to acceptable levels of TEs to safeguard geochemical health and ecology in the vicinity of this estuary.     

Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

Ecosystem responses to climate change at a Low Arctic and a High Arctic long-term research site

Long-term measurements of ecological effects of warming are often not statistically significant because of annual variability or signal noise. These are reduced in indicators that filter or reduce the noise around the signal and allow effects of climate warming to emerge. In this way, certain indicators act as medium pass filters integrating the signal over years-to-decades. In the Alaskan Arctic, the 25-year record of warming of air temperature revealed no significant trend, yet environmental and ecological changes prove that warming is affecting the ecosystem. The useful indicators are deep permafrost temperatures, vegetation and shrub biomass, satellite measures of canopy reflectance (NDVI), and chemical measures of soil weathering. In contrast, the 18-year record in the Greenland Arctic revealed an extremely high summer air-warming of 1.3 °C/decade; the cover of some plant species increased while the cover of others decreased. Useful indicators of change are NDVI and the active layer thickness.     

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.     

High-frequency measurements reveal spatial and temporal patterns of dissolved organic matter in an urban water conveyance

Stormwater runoff in urban areas can contribute high concentrations of dissolved organic matter (DOM) to receiving waters, potentially causing impairment to the aquatic ecosystem of urban streams and downstream water bodies. Compositional changes in DOM due to storm events in forested, agricultural, and urban landscapes have been well studied, but in situ sensors have not been widely applied to monitor stormwater contributions in urbanized areas, leaving the spatial and temporal characteristics of DOM within these systems poorly understood. We deployed fluorescent DOM (FDOM) sensors at upstream and downstream locations within a study reach to characterize the spatial and temporal changes in DOM quantity and sources within an urban water conveyance that receives stormwater runoff. Baseflow FDOM decreased over the summer season as seasonal flows upstream transported less DOM. FDOM fluctuated diurnally, the amplitude of which also declined as the summer season progressed. During storms, FDOM concentrations were rapidly elevated to values orders of magnitude greater than baseflow measurements, with greater concentrations at the downstream monitoring site, revealing high contributions from stormwater outfalls between the two locations. Observations from custom, in situ fluorometers resembled results obtained using laboratory methods for identifying DOM source material and indicated that DOM transitioned to a more microbially derived composition as the summer season progressed, while stormwater contributions contributed DOM from terrestrial sources. Deployment of a mobile sensing platform during varying flow conditions captured spatial changes in DOM concentration and composition and revealed contributions of DOM from outfalls during stormflows that would have otherwise been unobserved.     

Application of Adjoint Approach to Oil Spill Problems

Adjoint method is applied to various oil spill problems. A three-dimensional model for describing the dispersion of a quasi-passive substance (a pollutant or a nutrient) and its adjoint model are considered in a limited sea region. Direct and adjoint estimates are used to get dual (equivalent) estimates of the mean concentration of the substance in important zones of the region. The role of dual estimates is illustrated with a few examples. They include such oil spill problems as the search of the most dangerous point of the oil tanker route, the oil dispersion with a climatic velocity, and the dependence of the oil concentration estimates on the oil spill rate. One more example is the application of optimal bioremediation strategy for cleaning a few zones polluted by oil. In this case, instead of oil, the model describes the dispersion of a nutrient released to marine environment. Balanced, unconditionally stable second-order finite-difference schemes based on the splitting method for the solution of the dispersion model and its adjoint are suggested. The main and adjoint difference schemes are compatible in the sense that at every fractional step of the splitting algorithm, the one-dimensional split operators of both schemes satisfy a discrete form of Lagrange identity. In the special unforced and non-dissipative case, each scheme has two conservation laws. Every split one-dimensional problem is solved by Thomas’ factorization method.