• Energy Research

A major challenge in sustainability science is identifying targets that maximize ecosystem benefits to humanity while minimizing the risk of crossing critical system thresholds. One critical threshold is the biomass at which populations become so depleted that their population growth rates become negative—depensation. Here, we evaluate how the value of monitoring information increases as a natural resource spends more time near the critical threshold. This benefit emerges because higher monitoring precision promotes higher yield and a greater capacity to recover from overharvest. We show that precautionary buffers that trigger increased monitoring precision as resource levels decline may offer a way to minimize monitoring costs and maximize profits. In a world of finite resources, improving our understanding of the trade-off between precision in estimates of population status and the costs of mismanagement will benefit stakeholders that shoulder the burden of these economic and social costs.

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 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].

Historical exploitation of the Mediterranean Sea and the absence of rigorous baselines makes it difficult to evaluate the current health of the marine ecosystems and the efficacy of conservation actions at the ecosystem level. Here we establish the first current baseline and gradient of ecosystem structure of nearshore rocky reefs at the Mediterranean scale. We conducted underwater surveys in 14 marine protected areas and 18 open access sites across the Mediterranean, and across a 31-fold range of fish biomass (from 3.8 to 118 g m(-2)). Our data showed remarkable variation in the structure of rocky reef ecosystems. Multivariate analysis showed three alternative community states: (1) large fish biomass and reefs dominated by non-canopy algae, (2) lower fish biomass but abundant native algal canopies and suspension feeders, and (3) low fish biomass and extensive barrens, with areas covered by turf algae. Our results suggest that the healthiest shallow rocky reef ecosystems in the Mediterranean have both large fish and algal biomass. Protection level and primary production were the only variables significantly correlated to community biomass structure. Fish biomass was significantly larger in well-enforced no-take marine reserves, but there were no significant differences between multi-use marine protected areas (which allow some fishing) and open access areas at the regional scale. The gradients reported here represent a trajectory of degradation that can be used to assess the health of any similar habitat in the Mediterranean, and to evaluate the efficacy of marine protected areas.

This is a postprint version of the Book Chapter. Information regarding the official publication is available from the link below - Copyright @ 2011 Springer Implementation of a Life Cycle Sustainability Management (LCSM) strategy can involve significant challenges because of competing or conflicting objectives between stakeholders. These differences may, if not identified and managed, hinder successful adoption of sustainability initiatives. This article proposes a conceptual framework for stakeholder management in a LCSM context. The framework identifies the key sustainability stakeholder groups and suggests strategic ambiguity as a management tool to harness dysfunctional conflict into constructive collaboration. The framework is of practical value as it can be used as a guideline by managers who wish to improve collaboration with stakeholders along the supply chain. The article also fills a gap in the academic literature where there is only limited research on sustainability stakeholder management through strategic ambiguity.