Insights into advanced packed bed latent heat storage systems through explainable artificial intelligence techniques

Packed Bed Latent Heat Storage Systems (PBLHS) play a crucial role in improving energy efficiency for industrial waste heat recovery, yet their optimization remains difficult due to system complexity and the high computational cost of traditional simulation methods. This study aims to develop a data-driven framework that leverages machine learning (ML) and explainable artificial intelligence (XAI) to model, interpret, and optimize PBLHS performance under varying operational conditions. Using a dataset generated from high-fidelity computational fluid dynamics simulations, Light Gradient Boosting Machine, Extreme Gradient Boosting, and Random Forest models were trained to predict heat storage and extraction. LightGBM achieved the highest predictive accuracy (R2 = 0.966 for storage, 0.92 for extraction). To enhance interpretability, Shapley Additive Explanations and Local Interpretable Model-agnostic Explanations were applied, identifying inlet flow rate, upstream temperature, and tank geometry as the most influential features. LIME further revealed case-specific conditions linked to suboptimal performance. These insights enabled a targeted optimization process, reducing computational effort by 63 % with negligible loss in accuracy. The proposed methodology offers a transparent and efficient approach for designing advanced thermal energy storage systems tailored to industrial waste heat recovery scenarios

The link between e-waste and GDP—new insights from data from the pan-European region

Waste electrical and electronic equipment (WEEE) is difficult to sustainably manage. One key issue is the challenge of planning for WEEE flows as current and future quantities of waste are difficult to predict. To address this, WEEE generation and gross domestic product (GDP) data from 50 countries of the pan-European region were assessed. A high economic elasticity was identified, indicating that WEEE and GDP are closely interlinked. More detailed analyses revealed that GDP at purchasing power parity (GDP PPP) is a more meaningful measure when looking at WEEE flows, as a linear dependency between WEEE generation and GDP PPP was identified. This dependency applies to the whole region, regardless of the conomic developmental stage of individual countries. In the pan-European region, an increase of 1000 international $ GDP PPP means an additional 0.5 kg WEEE is generated that requires management

Life Cycle Assessment of Nitrate and Compound Fertilizers Production—A Case Study

The production and utilization of fertilizers are processes with known and noteworthy environmental impacts. Direct greenhouse gas (GHG) emissions and a high contribution to water eutrophication due to the nitrogen (N) and phosphorus (P) derivatives are some of the most crucial impacts derived from the overall life cycle of fertilizer use. The life cycle assessment (LCA) has been reliable and analytical tool for the identification, quantification, and evaluation of potential environmental impacts of fertilizers related to the products, production processes, or activities throughout their lifecycle. In this paper, a gate-to-gate LCA approach was applied in order to identify and evaluate the impacts derived from the production processes of nitrate and compound fertilizers the production industry in Northeastern Greece. The results from this study prove that compound fertilizers have a greater impact compared with nitrate fertilizers, contributing up to 70% of the total production impacts. Furthermore, climate change, freshwater eutrophication, and fossil fuel depletion were identified as the most crucial impact categories. Finally, a comparison with relevant LCA studies was conducted, in order to identify the possibility of a consistency pattern of the fertilizer production impacts in general.</jats:p

Life Cycle Assessment of Nitrate and Compound Fertilizers Production—A Case Study

The production and utilization of fertilizers are processes with known and noteworthy environmental impacts. Direct greenhouse gas (GHG) emissions and a high contribution to water eutrophication due to the nitrogen (N) and phosphorus (P) derivatives are some of the most crucial impacts derived from the overall life cycle of fertilizer use. The life cycle assessment (LCA) has been reliable and analytical tool for the identification, quantification, and evaluation of potential environmental impacts of fertilizers related to the products, production processes, or activities throughout their lifecycle. In this paper, a gate-to-gate LCA approach was applied in order to identify and evaluate the impacts derived from the production processes of nitrate and compound fertilizers the production industry in Northeastern Greece. The results from this study prove that compound fertilizers have a greater impact compared with nitrate fertilizers, contributing up to 70% of the total production impacts. Furthermore, climate change, freshwater eutrophication, and fossil fuel depletion were identified as the most crucial impact categories. Finally, a comparison with relevant LCA studies was conducted, in order to identify the possibility of a consistency pattern of the fertilizer production impacts in general

A Case Study on Environmental Sustainability Assessment of Spatial Entities with Anthropogenic Activities: The National Park of Eastern Macedonia and Thrace, Greece

The current paper presents a methodological framework that is able to evaluate the carrying capacity of protected areas where various human activities, apart from recreation and tourism, take place. The proposed framework converts the energy and product consumption into land required to satisfy those needs (Ecological Footprint) and compares them with the current land uses and available land (Biocapacity), in order to calculate carrying capacity. To facilitate the evaluation, an algorithm that calculates the Ecological Footprint, the Biocapacity, and the Carrying Capacity of the protected area under study by introducing 48 inputs was developed. The inputs were related to the evaluation of individual indicators assessing energy and product consumption of human activities such as households, tertiary sector, municipal buildings, public lighting, private and public transportation, and tourism. A new unit is introduced, the “equivalent person,” since the anthropogenic activities within the boundaries of the protected area contribute in a dissimilar way to the total land requirements. The framework is applied, as case study, in the National Park of Eastern Macedonia and Thrace (NPEMT), Greece, with a view to validate and improve its applicability. Within the NPEMT, habitats of significant biodiversity and ecological value are in coexistence with extensive human activities (urban, rural, tourist, light industrial). The study area covers up to approximately 73,000 ha and its population is estimated at about 29,000 people. The Carrying Capacity of the NPEMT according to the current consumption patterns was estimated at 39,193 equivalent residents, which was higher than the current equivalent residents (36,960), indicating a potential for tourism development at the NPEMT. The Ecological Footprint of the NPEMT was estimated at 181,324 Gha or 4.9 Gha/perseq, slightly higher than the European mean (4.69 Gha/perseq). Among activities, households and private transportation (with approximately 79% and 10%, respectively), among land use, agriculture, livestock, and CO2 emissions (with approximately 36%, 30%, and 30%, respectively), and among products, beef, fruits/vegetables, and beverages (with approximately 22%, 15%, and 14%, respectively) were the main contributors of the total Ecological Footprint of the NPEMT. The area of the NPEMT is able to meet the needs of its population provided that the consumption patterns will be stable. The results encourage the expansion of tourism development, as the tourism activity within the NPEMT is limited compared to other adjacent domestic destinations.</jats:p