Leonel J. R. Nunes’s research while affiliated with Prometheus and other places

Stochastic models can be used for predicting the availability of residual woody forest biomass, considering the variability and uncertainty associated with climatic, operational, and economic factors. These models, such as ARIMA, GARCH, state transition models, and Monte Carlo simulations, are widely used to capture seasonal patterns, dynamic variations, and complex uncertainties. Their application supports critical decisions in forest and energy operations planning. The implementation of the models was carried out in Python, using specialized packages such as Statsmodels for ARIMA, Arch for GARCH, and PyMC3 for state transition models. Probabilistic calculations were performed with Numpy and Scipy, while Matplotlib and Seaborn were used for data visualization. Hypothetical data simulating real-world scenarios were analyzed, divided into training and testing sets, with cross-validation and metrics such as RMSE, MAPE, and R2. ARIMA demonstrated high accuracy in capturing seasonality, while GARCH effectively modeled volatility. Monte Carlo simulations provided the most reliable forecasts, capturing uncertainties across multiple scenarios. The models excelled in predicting periods of high biomass availability with robust projections. The results confirm the efficacy of stochastic models in predicting residual biomass, with a positive impact on sustainable planning. However, challenges such as data dependency and computational resources still need to be addressed, pointing to directions for future research and methodological improvements.

The circular economy is strategically based on the three R's policy: reduce, recycle and reuse, which is not easy to apply to waste for which there are no processes that allow them to be recycled, or others for which reuse is not possible. One group of wastes that is particularly problematic because of its volume, quantity and diversity is the group of construction and demolition materials, including fibrous materials such as asbestos, for which there are still no clear alternatives for reintroduction into the supply chains of new processes. The destination of these end-of-life materials is landfill, with all the well-known drawbacks of limited landfill space, the high volume of material to be landfilled and the associated costs. In order to promote the reuse of asbestos fibres, it is essential to characterise them in physico-chemical terms and to assess how effectively mechanical and thermal treatments can transform these fibres for reuse, in order to provide the basis for a systematic approach to the incorporation of asbestos-containing waste into new construction applications. This analysis focuses on sustainable construction practices aimed at reusing waste materials to achieve significant reductions in carbon emissions over the entire life cycle of buildings.

Radon exposure is a major health concern associated with an increased risk of lung cancer, particularly in smokers, highlighting the need for effective mitigation measures in enclosed spaces by improving indoor air quality (IAQ), thus ensuring more sustainable buildings. The Euratom Directive, a key piece of EU legislation, sets standards for the protection of workers and the general public from ionizing radiation throughout Europe. It requires member states to implement safety measures, set exposure limits, monitor radon levels, and develop emergency plans and mitigation strategies for nuclear accidents and radiation incidents. The directive also sets reference and action levels for indoor radon. The aim of this article is to analyze the legislation on indoor radon exposure in European countries and to evaluate the impact of the directive on the standardization of the action and intervention levels. By conducting a comprehensive legislative review, this study will compare the action levels, assess the directive’s ability to harmonize the regulations, and identify legislative trends and developments. In addition, it will examine the factors contributing to the discrepancies between countries and highlight areas for improvement to ensure adequate protection against the risks of radon exposure and thereby increase the sustainability of buildings.

Sustainability is under threat due to inefficient waste management. In the industrial sector, mechanisms such as value chains and producer obligations have advanced circular economy practices. However, in the agroforestry sector, open burning of waste remains prevalent, resulting in resource loss and heightened fire risks. This scenario jeopardizes the environmental, social, and economic pillars of sustainability, underscoring the need for legal frameworks to ensure waste recovery. This study proposes a regulatory framework to enhance the circular economy in agroforestry waste management. A benchmarking analysis was conducted to examine waste recovery systems where circular economy principles are successfully implemented. Insights from these systems were integrated with an in-depth assessment of the agroforestry biomass recovery chain to develop actionable regulatory measures. The proposed framework includes measures such as mandatory delivery of biomass, creation of aggregation centers, and incentives for biomass recovery. These measures are tailored to reduce fire risks, improve resource efficiency, and align stakeholders’ practices with sustainability goals. Visual tools, including comparative tables and diagrams, illustrate the framework’s impact. The study highlights the potential of regulatory interventions to promote agroforestry waste recovery, supporting sustainable development. Future work should focus on pilot implementations to validate the framework’s effectiveness in real-world scenarios.

Background: The forest products industry plays a significant role in global carbon emissions, highlighting the need for sustainable practices to address the climate crisis. Reverse logistics (RL), focusing on the return, reuse, and recycling of materials, offers a promising approach to decarbonizing supply chains. However, its application within forest products supply chains remains underexplored. Methods: This study conducts a review of the literature on RL, its environmental implications, and its potential to reduce carbon emissions in forest products supply chains. Key areas examined include greenhouse gas reduction, waste management, and the promotion of circular economy principles. Additionally, the study evaluates case studies and models that integrate RL practices into forest-based industries. Results: The findings reveal that RL can significantly reduce greenhouse gas emissions by optimizing transportation routes, minimizing waste, and extending product life cycles. Incorporating these practices into forestry operations reduces the environmental impact and aligns with sustainable forestry goals. The study identifies gaps in current research, particularly regarding empirical data and the scalability of RL solutions. Conclusions: RL represents a critical strategy for decarbonizing forest products supply chains and advancing sustainable development. Future research should focus on developing standardized methodologies, enhancing technological integration, and fostering policy support to maximize its impact. These steps are essential to fully leverage RL as a tool for mitigating climate change and promoting a circular economy.

Background: This study explores the use of Mixed-Integer Linear Programming (MILP) models to optimize the collection and transportation of vineyard pruning biomass, a crucial resource for sustainable energy and material production. Efficient biomass logistics play a key role in supporting circular bioeconomy principles by improving resource utilization and reducing operational costs. Methods: Two optimization approaches are evaluated: a base MILP model designed for scenarios with single processing points and an advanced model that incorporates intermediate processing steps to enhance logistical efficiency. The models were tested using synthetic datasets simulating vineyard regions to assess their performance. Results: The models demonstrated significant improvements, achieving cost reductions of up to 30% while enhancing operational efficiency and resource utilization. The study highlights the scalability and real-world applicability of the proposed models. Conclusions: The findings underscore the potential of MILP models in optimizing biomass supply chains and advancing circular bioeconomy goals. However, key limitations, such as computational complexity and adaptability to dynamic environments, are noted. Future research should focus on real-time data integration, dynamic updates, and multi-objective optimization to improve model robustness and applicability across diverse supply chain scenarios.

The use of asbestos, once celebrated for its versatility and fire-resistant properties, has left a lasting legacy of environmental degradation and public health risks. This paper provides a comprehensive assessment of the environmental impacts and health risks associated with asbestos, highlighting its widespread use, environmental persistence, and adverse effects on human health. Through a literature review, this study examines the historical context of asbestos use, its adverse environmental effects and the mechanisms by which exposure to asbestos poses significant health risks, including the development of asbestos-related diseases such as mesothelioma, lung cancer, asbestosis, etc. It also assesses the current regulatory framework and provides a methodological analysis of the strategy for recycling end-of-life materials containing asbestos fibers, proposing the inclusion of asbestos-containing materials (ACMs) in the rock wool industry to reduce Greenhouse Gasses (GHG) emissions. Drawing on interdisciplinary insights from environmental science, public health, and regulatory analysis, this paper concludes with recommendations for improving asbestos management strategies, promoting safer alternatives and mitigating the long-term environmental and human health impacts of asbestos.

Rural fires have been a constant concern, with most being associated with land abandonment. However, some fires occur due to negligent attitudes towards fire, which is often used to remove agroforestry leftovers. In addition to the fire risk, this burning also represents a waste of the energy present in this residual biomass. Both rural fires and energy waste affect the three dimensions of sustainability. The ideal solution seems to be to use this biomass, avoiding the need for burning and recovering the energy potential. However, this process is strongly affected by logistical costs, making this recovery unfeasible. In this context, this study aims to propose an optimization model for this chain, focusing on the three dimensions of sustainability. The results of the present study comprise a summary of the current state of the art in supply-chain optimization, as well as a disruptive mathematical model to optimize the residual biomass supply chain. To achieve this objective, a literature review was carried out in the first phase, incorporating the specificities of the context under study to arrive at the final model. To conclude, this study provides a review covering several metaheuristics, including ant colony optimization, genetic algorithms, particle swarm optimization, and simulated annealing, which can be used in this context, adding another valuable input to the final discussion.