Carbon footprint of canned mussels from a business-to-consumer approach. A starting point for mussel processors and policy makers

The increasing demand for environmental information on the global warming impact of products requires a solid methodological framework which guarantees comparability and communicability. The publicly available specification PAS 2050 combines approaches to a variety of greenhouse gas specific assessment issues to deliver a globally applicable product Carbon Footprinting (CF) method, which is expected to be widely accepted. Specifically, this paper aims to demonstrate the implementation of a CF scheme for a common canned mussel product according to PAS 2050 guidelines. A final value of 4.35 kg CO₂e per triple pack of round cans of mussels was calculated. Furthermore, this CF study led to identify primary packaging (can production) and mussel shell management as the main activities where efforts should focus for climate change mitigation. Throughout this case study, CF opportunities and drawbacks are discussed. The whole text tries to provide a starting point for both mussel processors and policy makers to benefit from the potential advantages of a responsible use of this increasingly popular tool.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Stabilization/solidification of ashes in clays used in the manufacturing of ceramic bricks.

This paper presents the results of the lixiviation of metals from different mixtures of fly and bottom ashes that have been stabilized and solidified in clays used in the manufacture of bricks. The ashes used for this study were obtained from a Hoffmann-type brick furnace adapted for the incineration of municipal solid waste during the manufacturing of ceramic bricks. The ashes were stabilized in clay in different proportions of clay:ash mix (99:1, 95:5, 90:10, 80:20 and 60:40). Such mixes were used to manufacture bricks that were calcined at a temperature ranging from 50 to 1100 degrees C. The clay, ashes and manufactured bricks were characterized using X-ray diffraction, fluorescent X-ray, thermogravimetry, differential thermal analysis, atomic absorption spectroscopy and scanning electronic microscopy. In addition, toxicity characteristic leaching procedure lixiviation tests were performed according to the EPA 1311 method for the determination of heavy metals. The results showed an affinity between clay and ash, and also that the bricks manufactured with these mixtures present low lixiviation levels. The tests also showed the highest decrease in the concentration of arsenic, nickel, chromium, zinc and silver for 99:1 mixtures. The 95:5 mixture was found to be the most favourable for the stabilization (greater concentration decrease) of lead and cadmium. Selenium was the metal with the lowest concentration change whereas arsenic, nickel, chromium, zinc and cadmium showed the greatest concentration change in all mixtures, with the exception of cadmium in the mixture 99:1.     

Managers as drivers of CSR in state-owned enterprises

Corporate social responsibility (CSR) is increasingly required not only of private sector companies, but also of state-owned enterprises (SOEs), whose main function is to provide services to society and not principally to obtain financial reward. The important role played by managers in implementing CSR has been demonstrated by prior research. The objective of this paper is to examine how managers of SOEs perceive the concept of CSR, the reasons for their involvement and how it is integrated into everyday business practices. In addition, we examine whether managers' attitudes towards CSR policies are influenced by their personal profiles and by the sector in which the SOEs work. We find that, although these managers are aware of the importance of the CSR principles underlying their activities and understand the meaning, scope and dimensions of CSR, there remains an evident need to enhance the application of CSR policies among the strategies of SOEs. The manager profile and the sector in which the SOEs work both have a strong influence on their behaviour regarding CSR issues.