According to the European Union data, on average 173 kg per person of total food waste (organic waste) is produced annually, of which 92 kg per person comes from households (organic waste). Food waste is defined as the waste from households, restaurants, canteens, and food industries, as well as markets. The importance of food waste stretches from the environmental pressures to the economic and social impacts. An environmental technology for the biodegradation of food waste is anaerobic digestion. It is a very attractive technique and combines waste treatment and renewable energy recovery. This study investigates the characteristics of food waste leachates from composting buckets and their valorization as a substrate for the anaerobic digestion process. A complete characterization of different food waste leachates was conducted (pH, COD, VFAs, heavy metals, etc.). The food waste leachates proved to be an ideal feedstock for anaerobic digestion. In this direction, batch tests were performed to evaluate the methane yield of the food waste leachates under different operating conditions. Three different SIR ratios were tested (0.5, 1.0, and 1.5). An SIR equal to 0.5 proved to be the best as the higher methane yield was achieved. The removal of the COD under all the operating conditions was higher than 70%, with the higher removal (85.18%) for an SIR equal to 1.5.

The mercury content is among the parameters that characterise the quality of Solid Recovered Fuels (SRFs), which constitute alternative solid fuels of increasing interest. In this study, a direct mercury analyser was utilised in the analyses of SRF samples originating from Automotive Shredded Residues (ASRs). Two SRFs and one liquid reference material were measured to test the accuracy and sensitivity of the instrument. The mean values of the two SRFs and one liquid reference material (RM) were 0.171, 0.324 mg/kg, and 0.141 mg/L. These values were compared with the reference ones as follows: 0.168, 0.382 mg/kg, and 0.137 mg/L. Mercury content was detected in the analysis samples of four different particle sizes (8 mm, 2 mm, 1 mm, 0.5 mm, and 0.25 mm) for each SRF sample in order to demonstrate the direct mercury analyser operation and to compare it as an alternative to mercury determination via atomic absorption spectrometry. The measurements showed that grinding down to 1 mm was sufficient for most SRF cases while grinding down to 2 mm might be enough for a few cases. As an overall conclusion, the direct mercury analyser can be regarded as an efficient laboratory tool, offering a robust alternative to the atomic absorption spectrometry procedure, especially in terms of accuracy, speed, safety, and cost-effectiveness.

Background Vertical farming offers a promising solution to food production challenges in urban and climate-constrained regions, yet its high energy demand raises concerns about sustainability. Methods This study evaluates the performance and carbon footprint of a pilot vertical farming unit in Northern Greece using TRNSYS 18 simulations and high- resolution environmental data. Forty-eight cultivation scenarios were generated by varying photoperiods, humidity levels, and HVAC setpoints to reflect seasonal Mediterranean conditions. Each scenario was analyzed for energy consumption, grid reliance, photovoltaic sufficiency, and life cycle and CO 2 emissions. A dynamic crop cycle estimation model was applied to capture seasonal variability and align planting windows with solar energy availability. Performance benchmarking was conducted through a multi-criteria framework introducing the Grid Independence Index, Seasonal Resilience Score, and energy-per-cycle indicators. Results The median carbon footprint across scenarios was 3.67kg CO 2 per kilogram of lettuce (Lactuca Sativa), representing favorable performance compared to conventional methods such as greenhouse cultivation. The analysis demonstrated seasonal fluctuations in photovoltaic sufficiency, with certain scenarios achieving higher autonomy during spring and summer. A Lighting Flexibility Classification was developed to identify the maximum lighting reduction tolerance per scenario without increasing total energy demand, resulting in five flexibility levels and supporting adaptive climate-responsive strategies. Conclusions The findings highlight the potential of simulation-based design for optimizing energy use and minimizing environmental impacts in control-environment agriculture. The proposed metrics and classification provide practical tools for improving the resilience and sustainability of vertical farming under Mediterranean conditions.

This study presents an overview of the role that clean energy technologies can play in the decarbonisation path of Greece’s most carbon-intensive region, namely Western Macedonia. The region has been requested to adjust its production model to the new requirements of the Green Deal Initiative, while simultaneously proceeding to restructure its productive model towards a full phase-out of coal activities. The survey presented below will summarise the main findings and estimates of the clean energy potential from a technical and research point of view, and furthermore present assessments on the potential impact this could have on job creation and regional economic development in terms of potential investments. This study’s goals are to identify and promote actions to accelerate innovation performance in the clean energy domain and, simultaneously, serve as a co-working space among key stakeholders from business, government, civil society and innovation who share a vision for a sustainable future. Finally, this study highlights the importance of accelerating innovation in the clean energy domain—spanning energy production, distribution and consumption.

This work offers a comprehensive examination of ICP-MS as a higher-level analytical method compared to atomic absorption spectrometry (AAS) and X-ray fluorescence (XRF). Comparisons between the ICP-MS average mean difference and AAS were made with the determination of the concentration of trace elements in the same solid alternative fuel samples, while comparisons between ICP-MS and XRF were made by the determination of the concentration of major elements in the same solid alternative fuel samples, resulting in the superiority of the method. The results of the relative mean differences (RDMs) between ICP-MS (7.56%) and XRF (9.42%) regarding the concentration of major elements compared with the reference values in solid biofuel samples, while the RDMs for the solid recovered fuel samples were 8.9% for ICP-MS and 12.27% for XRF. The same procedure was followed for the determination of the concentration of trace elements with ICP-MS and AAS, thus obtaining the results for solid biofuel samples (average %RMD_ICP-MS = 12.77 and RMD_AAS = 13.9) and SRF samples (average %RMD_ICP-MS = 10.02 and RDM_AAS = 11.10) in relation to the reference values. While acknowledging that the initial cost and complexity of operation may deter some from adopting ICP-MS, the study asserts that the advantages of enhanced precision, sensitivity and speed of analysis validate the investment. Hence, ICP-MS is an extremely important laboratory tool used in modern physics and chemistry and has a wide range of applications: biological materials, high purity reagents and metals, atomic nuclear materials, geological samples and food.

Background Vertical farming offers a promising solution to food production challenges in urban and climate-constrained regions, yet its high energy demand raises concerns about sustainability. Most existing studies assess energy demand and CO 2 emissions under static operational assumptions and lack a comprehensive framework linking seasonal renewable availability, crop cycle timing, and operational flexibility to system resilience and grid dependency. Methods This study evaluates the performance and carbon footprint of a fully enclosed pilot vertical farming unit in Northern Greece using TRNSYS 18 simulations and high-resolution environmental data. Forty-eight cultivation scenarios were generated by varying photoperiods, humidity levels, and HVAC setpoints to reflect seasonal Mediterranean conditions. Each scenario was analyzed for energy consumption, grid reliance, photovoltaic sufficiency, and life cycle CO 2 emissions. A dynamic crop cycle estimation model was applied to capture seasonal variability and align planting windows with solar energy availability. Performance benchmarking was implemented through a novel resilience-based multi-criteria framework combining energy-per-cycle metrics with two composite indices, the Grid Independence Index (GII) and the Seasonal Resilience Score (SRS), formulated in this study as a key methodological innovation. A Lighting Flexibility Classification System was further developed to determine the maximum safe reduction in artificial lighting without increasing total energy demand. Results The median carbon footprint across the 48 simulated scenarios was 3.67 kg CO 2 kg −1 of lettuce (Lactuca Sativa), with optimized configurations achieving substantially lower emissions compared to conventional greenhouse cultivation. Crop cycle duration varied between 34 and 52 days depending on photoperiod and temperature setpoints. Aligning cultivation cycles with high solar availability, combined with dynamic lighting adjustments, PV contribution to annual electricity coverage was significantly enhanced. In such configurations, lighting inputs were reduced by up to 10% without causing an increase in total system energy requirements. Conclusions The findings highlight the potential of simulation-based design for optimizing energy use and minimizing environmental impacts in control-environment agriculture. The proposed metrics and classification provide practical tools for improving the resilience and sustainability of vertical farming under Mediterranean conditions.