Using stated preference methods to assess environmental impacts of forest biomass power plants in Portugal

As a renewable energy source, the use of forest biomass for electricity generation is advantageous in comparison with fossil fuels, however the activity of forest biomass power plants causes adverse impacts, affecting particularly neighbouring communities. The main objective of this study is to estimate the effects of the activity of forest biomass power plants on the welfare of two groups of stakeholders, namely local residents and the general population and we apply two stated preference methods: contingent valuation and discrete choice experiments, respectively. The former method was applied to estimate the minimum compensation residents of neighbouring communities of two forest biomass power plants in Portugal would be willing to accept. The latter method was applied among the general population to estimate their willingness to pay to avoid specific environmental impacts. The results show that the presence of the selected facilities affects individuals’ well-being. On the other hand, in the discrete choice experiments conducted among the general population all impacts considered were significant determinants of respondents’ welfare levels. The results of this study stress the importance of performing an equity analysis of the welfare effects on different groups of stakeholders from the installation of forest biomass power plants, as their effects on welfare are location and impact specific. Policy makers should take into account the views of all stakeholders either directly or indirectly involved when deciding crucial issues regarding the sitting of new forest biomass power plants, in order to achieve an efficient and equitable outcome.

Decision methods applied to solve a safety problem on a waste treatment facility

To solve a health and safety problem on a waste treatment facility, different multicriteria decision methods were used, including the PROV Exponential decision method. Four alternatives and ten attributes were considered. We found a congruent solution, validated by the different methods. The AHP and the PROV Exponential decision method led us to the same options ordering, but the last method reinforced one of the options as being the best performing one, and detached the least performing option. Also, the ELECTRE I method results led to the same ordering which allowed to point the best solution with reasonable confidence. This paper demonstrates the potential of using multicriteria decision methods to support decision making on complex problems such as risk control and accidents prevention.

Defining risk acceptance criteria in occupational settings: A case study in the furniture industrial sector

The use of appropriate acceptance criteria in the risk assessment process for occupational accidents is an important issue but often overlooked in the literature, particularly when new risk assessment methods are proposed and discussed. In most cases, there is no information on how or by whom they were defined, or even how companies can adapt them to their own circumstances. Bearing this in mind, this study analysed the problem of the definition of risk acceptance criteria for occupational settings, defining the quantitative acceptance criteria for the specific case study of the Portuguese furniture industrial sector. The key steps to be considered in formulating acceptance criteria were analysed in the literature review. By applying the identified steps, the acceptance criteria for the furniture industrial sector were then defined. The Cumulative Distribution Function (CDF) for the injury statistics of the industrial sector was identified as the maximum tolerable risk level. The acceptable threshold was defined by adjusting the CDF to the Occupational, Safety & Health (OSH) practitioners’ risk acceptance judgement. Adjustments of acceptance criteria to the companies’ safety cultures were exemplified by adjusting the Burr distribution parameters. An example of a risk matrix was also used to demonstrate the integration of the defined acceptance criteria into a risk metric. This work has provided substantial contributions to the issue of acceptance criteria for occupational accidents, which may be useful in overcoming the practical difficulties faced by authorities, companies and experts.

Qualitative risk assessment during polymer mortar test specimens preparation - methods comparison

Polymer binder modification with inorganic nanomaterials (NM) could be a potential and efficient solution to control matrix flammability of polymer concrete (PC) materials without sacrificing other important properties. Occupational exposures can occur all along the life cycle of a NM and “nanoproducts” from research through scale-up, product development, manufacturing, and end of life. The main objective of the present study is to analyse and compare different qualitative risk assessment methods during the production of polymer mortars (PM) with NM. The laboratory scale production process was divided in 3 main phases (pre-production, production and post-production), which allow testing the assessment methods in different situations. The risk assessment involved in the manufacturing process of PM was made by using the qualitative analyses based on: French Agency for Food, Environmental and Occupational Health & Safety method (ANSES); Control Banding Nanotool (CB Nanotool); Ecole Polytechnique Fédérale de Lausanne method (EPFL); Guidance working safely with nanomaterials and nanoproducts (GWSNN); Istituto Superiore per la Prevenzione e la Sicurezza del Lavoro, Italy method (ISPESL); Precautionary Matrix for Synthetic Nanomaterials (PMSN); and Stoffenmanager Nano. It was verified that the different methods applied also produce different final results. In phases 1 and 3 the risk assessment tends to be classified as medium-high risk, while for phase 2 the more common result is medium level. It is necessary to improve the use of qualitative methods by defining narrow criteria for the methods selection for each assessed situation, bearing in mind that the uncertainties are also a relevant factor when dealing with the risk related to nanotechnologies field.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Comparison of different numerical methods for the solution of the time-fractional reaction-diffusion equation with variable diffusion coefficient

In this work we perform a comparison of two different numerical schemes for the solution of the time-fractional diffusion equation with variable diffusion coefficient and a nonlinear source term. The two methods are the implicit numerical scheme presented in [M.L. Morgado, M. Rebelo, Numerical approximation of distributed order reaction- diffusion equations, Journal of Computational and Applied Mathematics 275 (2015) 216-227] that is adapted to our type of equation, and a colocation method where Chebyshev polynomials are used to reduce the fractional differential equation to a system of ordinary differential equations