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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.

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].

Abstract The improvement of thermodynamic efficiency of power plants is of great interest for the whole energy industry. The use of Kalina cycle has a great potential to improve the thermal efficiency of a nuclear power plant. This cycle uses a mixture of ammonia and water as working fluid. In this paper, we discuss the development of an Ammonia-Water mixture Property Code (AWProC). The estimation of the mixture properties are based on the Gibbs free energy functions. The code is verified and validated against experimental data available in the literature and REFPROP code. It is shown that AWProC can accurately estimate the thermodynamic properties of ammonia-water mixtures over a wide range of conditions, including high temperature and pressure regions. The code is then used to investigate the feasibility of applying the Kalina cycle to a typical Pressurizer Water Reactor (PWR) plant as an effective way to improve the plant efficiency. The fundamental of Basic-Kalina (B-K) cycle is described in detail firstly. Then, two modified configurations, Recuperation-Kalina (R-K) and Flash-Kalina (F-K) cycles respectively, are proposed for a typical 1000 MWe PWR. The simulation results indicate that the R-K type cycle can reach about 31.2% efficiency with simple equipment requirements, while the F-K type cycle can reach efficiencies up to about 34.8%, but at the expenses of a slightly more complex design. The present work demonstrates the applicability of the Kalina cycle as a way to improve the thermal efficiency of a nuclear power plant. This concept is meaningful for improving nuclear power plants economic and competitiveness.

Purpose This paper aims to propose a liquidity management solution for Islamic financial institutions (IFIs) that concurs with sustainable development and financial stability. Design/methodology/approach The study is a qualitative research. It uses the exploratory research methodology, specifically the content analysis approach, to gather primary data and identify and interpret relevant secondary data and Sharīʿah concepts. The purpose is to develop a liquidity management solution for IFIs. The proposal is based on the Unleveraged Green Investment Trust (UGIT) model, which is consistent with Basel III regulatory requirements. In developing the UGIT model, the exploratory research was complemented by a case study to examine the UGIT solution for the particular case of renewable energy. Findings The model demonstrates how financial innovation can meet both financial stability and sustainable development objectives, thereby achieving the spirit of Islamic finance. The structure further highlights the importance of regulatory and fiscal frameworks to enhance liquidity management and investor appeal for green financial instruments. Originality/value This study suggests a structure of UGIT to enable IFIs to meet their liquidity management needs while promoting sustainable development.

Since its invention in 2009, Perovskite solar cells (PSCs) has attracted great attention because of its low cost, numerous options of efficiency enhancement, ease of manufacturing and high-performance. Within a short span of time, the PSC has already outperformed thin-film and multicrystalline silicon solar cells. A current certified efficiency of 25.2% demonstrates that it has the potential to replace its forerunner generations. However, to commercialize PSCs, some problems need to be addressed. The toxic nature of lead which is the major component of light absorbing layer, and inherited stability issues of fabricated devices are the major hurdles in the industrialization of this technology. Therefore, new researching areas focus on the lead-free metal halide perovskites with analogous optical and photovoltaic performances. Tin being nontoxic and as one of group IV(A) elements, is considered as the most suitable alternate for lead because of their similarities in chemical properties. Efficiencies exceeding 13% have been recorded using Tin halide perovskite based devices. This review summarizes progress made so far in this field, mainly focusing on the stability and photovoltaic performances. Role of different cations and their composition on device performances and stability have been involved and discussed. With a considerable room for enhancement of both efficiency and device stability, different optimized strategies reported so far have also been presented. Finally, the future developing trends and prospects of the PSCs are analyzed and forecasted.

This open access book brings together a collection of cutting-edge insights into how action can and is already being taken against climate change at multiple levels of our societies, amidst growing calls for transformative and inclusive climate action. In an era of increasing recognition regarding climate and ecological breakdown, this book offers hope, inspiration and analyses for multi-level climate action, spanning varied communities, places, spaces, agents and disciplines, demonstrating how the energy and dynamism of local scales are a powerful resource in turning the tide. Interconnected yet conceptually distinct, the book’s three sections span multiple levels of analysis, interrogating diverse perspectives and practices inherent to the vivid tapestry of climate action emerging locally, nationally and internationally. Delivered in collaboration with the UK’s ‘Place-Based Climate Action Network’, chapters are drawn from a wide range of authors with varying backgrounds spread across academia, policy and practice.