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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.

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.

Background: Climate change has been shown to be directly linked to multiple physiological sequelae and to impact health consequences. However, the impact of climate change on mental health globally, particularly among vulnerable populations, is less well understood. Objective: To explore the mental health impacts of climate change in vulnerable populations globally. Methods: We performed an integrative literature review to identify published articles that addressed the research question: What are the mental health impacts of climate change among vulnerable populations globally? The Vulnerable Populations Conceptual Model served as a theoretical model during the review process and data synthesis. Findings/Results: One hundred and four articles were selected for inclusion in this review after a comprehensive review of 1828 manuscripts. Articles were diverse in scope and populations addressed. Land-vulnerable persons (either due to occupation or geographic location), Indigenous persons, children, older adults, and climate migrants were among the vulnerable populations whose mental health was most impacted by climate change. The most prevalent mental health responses to climate change included solastalgia, suicidality, depression, anxiety/eco-anxiety, PTSD, substance use, insomnia, and behavioral disturbance. Conclusions: Mental health professionals including physicians, nurses, physician assistants and other healthcare providers have the opportunity to mitigate the mental health impacts of climate change among vulnerable populations through assessment, preventative education and care. An inclusive and trauma-informed response to climate-related disasters, use of validated measures of mental health, and a long-term therapeutic relationship that extends beyond the immediate consequences of climate change-related events are approaches to successful mental health care in a climate-changing world.

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].

A transition from fossil to renewable energy requires the development of sustainable electric energy storage systems capable to accommodate an increasing amount of energy, at larger power and for a longer time. Flow batteries are seen as one promising technology to face this challenge. As different innovations in this field of technology are still under development, reproducible, comparable and verifiable life cycle assessment studies are crucial to providing clear evidence on the sustainability of different flow battery systems. Based on a review of 20 relevant life cycle assessment studies for different flow battery systems, published between 1999 and 2021, this contribution explored relevant methodological choices regarding the sequence of phases defined in the ISO 14,040 series: goal and scope definition, inventory analysis, impact assessment and interpretation. Inspired by good practice examples, common gaps and weaknesses were identified and recommendations for comparative life cycle assessment studies were derived. This includes suggestions for an expanded functional unit definition, a provision of more detailed and transparent reporting of LCI data while using input/output tables. Outcomes of this study are also of relevance for the amendment of the Batteries Directive 2006/66/EC, where first drafts are under revision in the European Council, including the introduction of a battery passport, which should encourage battery producers to reduce their carbon footprint and avoid problematic materials.

AbstractThe planetary boundary framework constitutes an opportunity for decision makers to define climate policy through the lens of adaptive governance. Here, we use the DICE model to analyze the set of adaptive climate policies that comply with the two planetary boundaries related to climate change: (1) staying below a CO2 concentration of 550 ppm until 2100 and (2) returning to 350 ppm in 2100. Our results enable decision makers to assess the following milestones: (1) a minimum of 33% reduction of CO2 emissions by 2055 in order to stay below 550 ppm by 2100 (this milestone goes up to 46% in the case of delayed policies); and (2) carbon neutrality and the effective implementation of innovative geoengineering technologies (10% negative emissions) before 2060 in order to return to 350 ppm in 2100, under the assumption of getting out of the baseline scenario without delay. Finally, we emphasize the need to use adaptive path-based approach instead of single point target for climate policy design.