• Energy Research
• natural sciences close

IntroductionWith the much-needed transformation from linear to more circular resource flows, it is imperative for enterprises to understand their financial prospects. Transforming towards Product-as-a-Service (PaaS) with circular elements introduces new considerations that must be addressed to ensure profitability and sustainability. However, there is a lack of comprehensive financial assessments based on empirical cases to guide companies in assessing the lucrativeness of their transformations. This paper addresses this gap by proposing a simple-to-use and flexible financial assessment model for PaaS, helping practitioners identify the conditions necessary for financial viability from both provider and user perspectives.MethodsGrounded in transdisciplinary research, this study focuses on a construction machine manufacturer's transformation from a traditional one-off sales business model to PaaS. The transformation is analysed through the development of a life cycle costing financial assessment model that addresses relevant cost drivers.ResultsUsing discounting methods, the model can help practitioners generate scenarios to identify feasible solutions for profitable PaaS setups. Additionally, the paper presents an analytical procedure to identify conditions for a financially viable PaaS. The procedure includes scenario-based analysis that accounts for systemic changes often necessary for successfully realising PaaS.DiscussionBy following the proposed procedure, along with the financial assessment model, manufacturers can streamline their financial assessments to identify necessary changes. For the analysed case company, the modelling results indicate that it must redesign its products for PaaS to outperform its previous business model.

Microalgae are recognized as a third generation feedstock for biofuel production due to their rapid growth rates and lignin-free characteristics. In this study, a lipid extracted microalgal biomass residues was used as the raw material to produce isoprene, α-pinene and β-pinene with an engineered E. coli strain. We adopted an optimal sulfuric acid hydrolysis method (1:7 ratio of solid to acid solution, 32% (w/v) concentration of sulfuric acid solution at 90 °C for 90 min) to efficiently convert holocellulose into glucose efficiently (6.37 g/L). Futhermore, we explored a novel detoxification strategy (phosphoric acid/calcium hydroxide) to remove inhibitors and notably acetic acid, furfural and 5-hydroxymethylfurfural (5-HMF) were reduced by 5.32%, different number given later 99.19% and 98.22%, respectively. Finally, the fermentation concentrations of isoprene (223.23 mg/L), α-pinene (382.21 μg/L) and β-pinene (17.4 mg/L) were achieved using the detoxified hydrolysate as the carbon source, equivalent to approximately 86.02%, 90.16% and 88.32% of those produced by the engineered E. coli strain fermented on pure glucose, respectively.

AbstractWe have measured the effect of degradation on the I-V characteristics in APFO3:PCBM solar cells. The solar cell devices were subject to ambient air under simulated solar illumination. We found that the degradation resulted in a lowering of the fill factor and short circuit current while the open circuit voltage remained unchanged. In order to gain insight into what has caused the degraded I-V characteristics we have studied the active layer film using various techniques. We found clear spectral changes both in absorption and in photoinduced absorption spectroscopy correlated with increased carrier lifetimes and lowered mobility when comparing the degraded film with a pristine one. The results show a significant degradation of the active layer causing a lower fill-factor and short circuit current.

Abstract Three-dimensional (3D) metal halide perovskite solar cells (PSCs) have a power conversion efficiency that is now comparable with conventional silicon solar cells. For PSC applications to succeed in the market, long-term reliability under open-air conditions is essential. Recent experiments have shown that two-dimensional (2D) perovskites seem to exhibit good stability due to the presence of hydrophobic organic spacers, but 2D PSCs are incapable of generating and transporting a large amount of charge due to their extended optical bandgaps. Mixed dimensional perovskites with dimension lies between 2D and 3D recently became a promising candidate to sustain long-term stability and high performances concurrently to address this obstacle. The current research article presents the finding of simulation-based studies performed on novel device architecture consisting of ITO/Nb-Ti2O3/3D Perovskite/2D Perovskite/Spiro-OMeTAD/Au. Using optical simulation features of SCAPS, absorption of light is computed in the proposed device. The computational results show that the thickness of the 2D perovskite layer badly affects the solar cell parameters. A thin 2D perovskite behaves as a capped coating that avoids the deterioration of 3D perovskite in open-air environments. The effect of a multivalent defect in the 3D perovskite layer is mathematically modelled, and their impact on overall performance parameters are analyzed. The findings are compared to the same configuration results, except where the absorber layer’s multivalent defect has been substituted by a neutral defect of the same defect density of about (1011 cm−3). Results show that the multivalent defect leads to an underestimation of the efficiency by 4.2%.

The effect of the combined application of nano-hydroxyapatite (NHAP) or nano-carbon black (NCB) on the phytoextraction of Pb by ryegrass was investigated as an enhanced remediation technique for soils by field-scale experiment. After the addition of 0.2% NHAP or NCB to the soil, temporal variation of the uptake of Pb in aboveground parts and roots were observed. Ryegrass shoot concentrations of Pb were lower with nano-materials application than without nano-materials for the first month. However, the shoot concentrations of Pb were significantly increased with nano-materials application, in particular NHAP groups. The ryegrass root concentrations of Pb were lower with nano-materials application for the first month. These results indicated that nano-materials had significant effects on stabilization of lead, especially at the beginning of the experiment. Along with the experimental proceeding, phytotoxicity was alleviated after the incorporation of nano-materials. The ryegrass biomass was significantly higher with nano-materials application. Consequently, the Pb phytoextraction potential of ryegrass significantly increased with nano-materials application compared to the gounps without nano-materials application. The total removal rates of soil Pb were higher after combined application of NHAP than NCB. NHAP is more suitable than NCB for in-situ remediation of Pb-contaminated soils. The ryegrass translocation factor exhibited a marked increase with time. It was thought that the major role of NHP and NBA might be to alleviate the Pb phytotoxicity and increase biomass of plants.

The shipping industry faces a large challenge as it needs to significantly lower the amounts of Green House Gas emissions. Traditionally, reducing the fuel consumption for ships has been achieved during the design stage and, after building a ship, through optimisation of ship operations. In recent years, ship efficiency improvements using Machine Learning (ML) methods are quickly progressing, facilitated by available data from remote sensing, experiments and high-fidelity simulations. The data have been successfully applied to extract intricate empirical rules that can reduce emissions thereby helping achieve green shipping. This article presents an overview of applying ML techniques to enhance ships’ sustainability. The work covers the ML fundamentals and applications in relevant areas: ship design, operational performance, and voyage planning. Suitable ML approaches are analysed and compared on a scenario basis, with their space for improvements also discussed. Meanwhile, a reminder is given that ML has many inherent uncertainties and hence should be used with caution.

AbstractElevated carbon-dioxide concentration [eCO2] is a key climate change factor affecting plant growth and yield. Conventionally, crop modeling work has evaluated the effect of climatic parameters on crop growth, without considering CO2. It is conjectured that a novel multimodal ensemble approach may improve the accuracy of modelled responses to eCO2. To demonstrate the applicability of a multimodel ensemble of crop models to simulation of eCO2, APSIM, CropSyst, DSSAT, EPIC and STICS were calibrated to observed data for crop phenology, biomass and yield. Significant variability in simulated biomass production was shown among the models particularly at dryland sites (44%) compared to the irrigated site (22%). Increased yield was observed for all models with the highest average yield at dryland site by EPIC (49%) and lowest under irrigated conditions (17%) by APSIM and CropSyst. For the ensemble, maximum yield was 45% for the dryland site and a minimum 22% at the irrigated site. We concluded from our study that process-based crop models have variability in the simulation of crop response to [eCO2] with greater difference under water-stressed conditions. We recommend the use of ensembles to improve accuracy in modeled responses to [eCO2].