Assessment of the Availability of Forest Biomass for Bioenergy Production in Southwest Portugal.

In 2014, Portugal was the seventh largest pellets producer in the World. Since the shortage of raw material is one of the major obstacles that the Portuguese sellets market faces, the need for a good assessment of biomass availability for energy purposes at both country and regional levels is reinforced. This work uses a Geographical Information System environment and remote sensing data to assess the availability and sustainability of forest biomass residues in a management unit with around 940 ha of maritime pine forest. The period considered goes from 2004 to 2015. The study area is located in Southwestern Portugal, close to a pellets factory; therefore the potential Contribution of the residual biomass generated in the management unit to the production of pellets is evaluated. An allometric function is used for the estimation of maritime pine above ground biomass. With this estimate, and considering several forest operations, the residual biomass available was assessed, according to stand composition and structure. This study shows that, when maritime pine forests are managed to produce wood, the amount of residues available for energy production is small (an average of 0.37 t ha -1  year -1 were generated in the study area between 2004 and 2015). As a contribution to the sustainability of the Portuguese pellets industries, new management models for maritime pine forests may be developed. The effect of the pinewood nematode on the availability of residual biomass can be clearly seen in this study. In the management unit considered, cuts were made to prevent dissemination of the disease. This contributes to a higher availability of forest residues in a specific period of time, but, in the medium term, they lead to a decrease in the amount of residues that can be used for energy purposes.

Black carbon trends in southwestern Iberia in the context of the financial and economic crisis. The role of bioenergy.

Since black carbon concentrations are useful to reveal changes in anthropogenic activities, measurements taken from 2007 to 2015 in a Portuguese city are used to assess to which extent the ambient air was impacted by the economic crisis. The average black carbon concentrations are representative of an urban area of small size (1.3 ± 1.3 μg m−3). The highest concentrations are observed in the heating season, being biomass combustion one of the causes for the high values. The daily cycle of black carbon concentrations presents both morning and evening peaks, mainly due to road traffic and, in the heating season, to domestic heating as well. The yearly averaged black carbon mass concentrations decreased 33 % from 2007 to 2015, possibly due to a combination of the economic recession and environmental legislation. The reduction in road traffic led to a decrease in the daily morning peak from 2007 to 2015. This reduction was not followed by a decrease in the evening peak, explained by an increase in biomass burning. Biomass is the cheapest heating fuel in Portugal, and its consumption increased in the aftermath of the economic crisis. The use of bioenergy is an alternative to fossil fuels and presents many advantages. However, energy policies should discourage inefficient biomass burning and promote better ways of exploiting the available energy resources and emission air pollution mitigation strategies.

Above ground biomass estimation in Mediterranean multiple use systems with high spatial resolution satellite images

Forest biomass has been having an increasing importance in the world economy and in the evaluation of the forests development and monitoring. It was identified as a global strategic reserve, due to its applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. The estimation of above ground biomass is frequently done with allometric functions per species with plot inventory data. An adequate sampling design and intensity for an error threshold is required. The estimation per unit area is done using an extrapolation method. This procedure is labour demanding and costly. The mail goal of this study is the development of allometric functions for the estimation of above ground biomass with ground cover as independent variable, for forest areas of holm aok (Quercus rotundifolia), cork oak (Quercus suber) and umbrella pine (Pinus pinea) in multiple use systems. Ground cover per species was derived from crown horizontal projection obtained by processing high resolution satellite images, orthorectified, geometrically and atmospheric corrected, with multi-resolution segmentation method and object oriented classification. Forest inventory data were used to estimate plot above ground biomass with published allometric functions at tree level. The developed functions were fitted for monospecies stands and for multispecies stands of Quercus rotundifolia and Quercus suber, and Quercus suber and Pinus pinea. The stand composition was considered adding dummy variables to distinguish monospecies from multispecies stands. The models showed a good performance. Noteworthy is that the dummy variables, reflecting the differences between species, originated improvements in the models. Significant differences were found for above ground biomass estimation with the functions with and without the dummy variables. An error threshold of 10% corresponds to stand areas of about 40 ha. This method enables the overall area evaluation, not requiring extrapolation procedures, for the three species, which occur frequently in multispecies stands.

Evolutionary algorithms for the modeling of bioreactors

This work aims to study the application of Genetic Algorithms in anaerobic digestion modeling, in particular when using dynamical models. Along the work, different types of bioreactors are shown, such as batch, semi-batch and continuous, as well as their mathematical modeling. The work intendeds to estimate the parameter values of two biological reaction model. For that, simulated results, where only one output variable, the produced biogas, is known, are fitted to the model results. For this reason, the problems associated with reverse optimization are studied, using some graphics that provide clues to the sensitivity and identifiability associated with the problem. Particular solutions obtained by the identifiability analysis using GENSSI and DAISY softwares are also presented. Finally, the optimization is performed using genetic algorithms. During this optimization the need to improve the convergence of genetic algorithms was felt. This need has led to the development of an adaptation of the genetic algorithms, which we called Neighbored Genetic Algorithms (NGA1 and NGA2). In order to understand if this new approach overcomes the Basic Genetic Algorithms (BGA) and achieves the proposed goals, a study of 100 full optimization runs for each situation was further developed. Results show that NGA1 and NGA2 are statistically better than BGA. However, because it was not possible to obtain consistent results, the Nealder-Mead method was used, where the initial guesses were the estimated results from GA; Algoritmos Evolucionários para a Modelação de Bioreactores Resumo: Neste trabalho procura-se estudar os algoritmos genéticos com aplicação na modelação da digestão anaeróbia e, em particular, quando se utilizam modelos dinâmicos. Ao longo do mesmo, são apresentados diferentes tipos de bioreactores, como os batch, semi-batch e contínuos, bem como a modelação matemática dos mesmos. Neste trabalho procurou-se estimar o valor dos parâmetros que constam num modelo de digestão anaeróbia para o ajustar a uma situação simulada onde apenas se conhece uma variável de output, o biogas produzido. São ainda estudados os problemas associados à optimização inversa com recurso a alguns gráficos que fornecem pistas sobre a sensibilidade e identifiacabilidade associadas ao problema da modelação da digestão anaeróbia. São ainda apresentadas soluções particulares de idenficabilidade obtidas através dos softwares GENSSI e DAISY. Finalmente é realizada a optimização do modelo com recurso aos algoritmos genéticos. No decorrer dessa optimização sentiu-se a necessidade de melhorar a convergência e, portanto, desenvolveu-se ainda uma adaptação dos algoritmos genéticos a que se deu o nome de Neighboured Genetic Algorithms (NGA1 e NGA2). No sentido de se compreender se as adaptações permitiam superar os algoritmos genéticos básicos e atingir as metas propostas, foi ainda desenvolvido um estudo em que o processo de optimização foi realizado 100 vezes para cada um dos métodos, o que permitiu concluir, estatisticamente, que os BGA foram superados pelos NGA1 e NGA2. Ainda assim, porque não foi possivel obter consistência nos resultados, foi usado o método de Nealder-Mead utilizado como estimativa inicial os resultados obtidos pelos algoritmos genéticos.