http://bura.brunel.ac.uk/handle/2438/25428 Sat, 16 May 2026 03:59:57 GMT 2026-05-16T03:59:57Z http://bura.brunel.ac.uk/handle/2438/33272 Title: Beyond the kitchen: co-creating sustainable menu strategies through participatory action learning Authors: Zick, A; Schmidt Rivera, X; Reynolds, C; Farinha, C; Case-Humphries, E; Cross, P Abstract: Introduction: This study explores the systems-level dynamics of menu transformation in the hospitality and food service (HaFS) sector through participatory action learning (PAL) workshops with professional chefs. Framing the menu not merely as a list of dishes but as an “operating principle” within a business, the research investigates how chefs navigate competing priorities and stakeholder influences in the context of sustainability goals, particularly reducing food waste and greenhouse gas emissions (GHGE). Methods: Two PAL workshops were conducted with professional chefs (n = 8 and n = 12). Drawing on Bronfenbrenner's ecological systems theory, stakeholder maps and menu priority artefacts generated during the workshops were analysed to identify the relative influence of micro, meso, exo, macro, and chrono-level influencing agents on menu decision-making. Results: Findings indicate that meso-level agents, such as procurement teams, business owners, and restaurant managers, are perceived as the most influential on menu decisions, while micro-level agents, including chef colleagues and friends, are seen as the least impactful. Menu priorities were similarly ranked, with product/dish and customer-related factors dominating over sustainability and acceptability considerations. The workshops also revealed a shift in participant thinking from identifying “who” influences menus to understanding “how” decisions are shaped by systemic constraints such as shelf life, infrastructure, and profitability. Discussion: The participatory format enabled chefs to surface tacit knowledge, reflect on their agency, and engage in systems thinking. While the findings are context-dependent, they highlight the need for multi-level stakeholder engagement in menu transformation and suggest that sustainability goals must be embedded within the operational logic of the menu to be actionable. This research contributes to the growing literature on participatory methods in food systems change and offers a replicable model for chef-led sustainability interventions. Highlights: • Chefs ranked product/dish and customer factors above sustainability in menu design. • Meso-level actors were seen as most influential in shaping menu decisions. • Workshops enabled chefs to reflect on food waste and GHGE in their practices. • GHGE calculations triggered critical learning and inspired recipe reformulation. • Participatory methods surfaced tacit knowledge and fostered systems thinking. Description: Data availability statement: The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.; Supplementary material: The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fsufs.2026.1698446/full#supplementary-material Tue, 05 May 2026 00:00:00 GMT http://bura.brunel.ac.uk/handle/2438/33272 2026-05-05T00:00:00Z http://bura.brunel.ac.uk/handle/2438/33168 Title: Liquid Smoke characterisation and production from empty fruit bunches via consecutive pascalisation and microwave-assisted pyrolysis Authors: Rachmaniah, O; Meka, W; Nurkhamidah, S; Saputra, NDS; Ashshiddiqi, MK; Tan, TB; Tan, CP; Fahrudin Rois, M; Lalasari, LH; Vanin, FM; Masoudi Soltani, S Abstract: Empty fruit bunches (EFBs) were pascalised at 200–400 MPa, then pyrolysed with microwave oven at 350 and 450 °C. Physical and thermal properties of EFBs were characterised. Yields, chemical compositions, and functional properties including total phenolic content, antioxidant capacity, acidity, antimicrobial activity, and colour of the liquid smoke were also evaluated. Results showed that pascalisation at 300 MPa produced the maximum surface area of 6.385 m2 g−1 and pore volume of 0.5511 cm3 g−1, whilst pascalisation at 400 MPa caused pore collapse. Liquid smoke yield showed irregular trends: at 350 °C, 400 MPa achieved the highest yield of 21.2 ± 2.3% despite collapsed pores, whilst 200 MPa yielded the lowest at 5.2 ± 1.4%; at 450 °C, the trend reversed, with 200 MPa reaching the highest yield of 11.9 ± 1.7% whilst 400 MPa fell sharply to 5.4 ± 2.0% due to rapid heating rate. GC–MS analysis identified phenolic compounds and ketones, showing compositional shifts related to pore structure modifications. The irregular trend of most functional properties suggests that densified EFB structures concentrated phenolic compounds whilst more open structures produced dilute liquid smoke. These findings demonstrate that pascalisation modifies EFB structure and influences liquid smoke yields and composition through structural mechanisms. Description: Highlights: • Pascalisation at 300 MPa optimised EFB mesoporosity for pyrolysis efficiency. • Pressure-temperature interaction governed liquid smoke yield and phenol content. • 400 MPa/450 °C maximised antimicrobial activity via phenol-pH synergy. • Samples met SNI colour/pH standards, but high TPC requires phenol control. • Post-condensation fractionation proposed to achieve regulatory compliance.; Data availability: The authors declare that all produced data have been presented in this paper.; Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S2589014X26002239#s0160 . Thu, 16 Apr 2026 00:00:00 GMT http://bura.brunel.ac.uk/handle/2438/33168 2026-04-16T00:00:00Z http://bura.brunel.ac.uk/handle/2438/33106 Title: Machine learning approaches for data-driven hydrocarbon bioaugmentation and phytoremediation: the role of multi-omics insights Authors: Okafor, UC; Alghamdi, SM; Anguilano, L; Yang, Y Abstract: Hydrocarbon contamination, particularly with polycyclic aromatic hydrocarbons (PAHs), poses a significant environmental challenge due to its persistence and carcinogenic effects on ecosystems and human health globally. This review explores how ML algorithms can enhance the efficiency of bio-augmentation and phytoremediation through predictive modeling, real-time optimization of microbial consortia, and plant species selection. Traditional bioremediation methods, such as bioaugmentation and phytoremediation, are characterized by slow degradation rates and sub-optimal performance in complex, multi-contaminant environmental milieus. The use of machine learning (ML) models with multi-omics data presents an advanced predictive approach to optimizing bioremediation processes by providing a systematic understanding of microbial and plant-mediated hydrocarbon degradation strategies and processes. ML models can predict which microbial strains or plant species will effectively degrade hydrocarbons under specific environmental conditions by utilizing supervised learning methods such as support vector machines and neural networks. Additionally, the combination of multi-omics data with ML facilitates the identification of critical genes, enzymes, and metabolic pathways involved in the degradation of hydrocarbons, and offers insights into the molecular mechanisms which drive the bioremediation process. The translation of laboratory-based ML models into large-scale, real-world bioremediation strategy is hindered by the complex, dynamic nature of our contaminated environments. This review paper showcases these hinderances and provides a direction for future research, including the development of field-deployable technologies, adaptive ML models, and real-time environmental monitoring strategies. The integration of ML with multi-omics holds substantial promise for enhanced efficiency, adaptability, and scalability of bioremediation strategies which ultimately mitigates carcinogenic risks often associated with hydrocarbon-polluted lithosphere. Thu, 05 Mar 2026 00:00:00 GMT http://bura.brunel.ac.uk/handle/2438/33106 2026-03-05T00:00:00Z http://bura.brunel.ac.uk/handle/2438/33067 Title: Environmental life cycle assessment of novel PV systems for desert conditions Authors: Cruz, JM; Schmidt Rivera, X; Jalil-Vega, F; O'Ryan, R; Valencia, F; Rabanal-Arabach, J; Ayllón Opazo, E; Morris Carmona, PA; Larrain Yañez, P Abstract: Solar photovoltaic (PV) systems are currently seen as an affordable and mainstream renewable energy option to support energy decarbonisation, aligning with commitments of the UN Sustainable Development Goals (SDG 7). This technology prevails in high irradiance places such as deserts, where some of the largest PV systems are installed globally. However, harsh desert conditions reduce PV systems' efficiency and lifespan, among other negative effects. While research on designing PV systems that endure desert conditions is ongoing, little is known about the environmental impacts of these novel PV solutions. This study uses the life cycle assessment (LCA) methodology to assess the environmental impacts of four novel PV system designs (HJT 1–4) for desert conditions and compares them with three systems available in the current market (PERC, PERC+ and TOPCon). The functional unit of the study is ‘the production of 1 kWh of electricity AC, considering a PV system connected to a 570kWp grid in the Atacama Desert with a lifespan of 25 years’. The inventories were built using data from tested designs in the desert. 18 environmental impact indicators were included following ReCiPe method, and complemented with energy payback time (EPBT). Results show that the novel design (HJT 3) achieves up to 30% reduction in GWP100 per kWh of electricity generated compared to conventional monofacial PERC modules, and a 15% reduction compared to TOPCon modules, primarily due to higher efficiency and reduced materials consumption. The Balance of System (BOS) and installation stage shows the greatest impact on PV systems, contributing 46% on average across all environmental burden, followed by the wafer manufacturing (25% on average) and module manufacturing stages (18% on average). Across all impact categories, including EPBT, PERC is the worst performer, and HJT 3 and HJT 4 are the best performers, followed by TOPCon. This study validates the effort of performing environmental impact assessments on new designs, to ensure both technical performance and the environmental and economic sustainability of renewable energy systems. Description: Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S2352550926000333#s0170 . Wed, 18 Mar 2026 00:00:00 GMT http://bura.brunel.ac.uk/handle/2438/33067 2026-03-18T00:00:00Z