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Plastic recycling: A panacea or environmental pollution problem

Increasing plastic waste is a critical global challenge to ecological and human health requiring focused solutions to reduce omnipresent plastic pollution in the environment. While recycling has been touted as one solution to counter plastic waste and resource utilization, it has been largely ineffective in offsetting the impact of rising global plastic production of more than 400 million metric tonnes annually, due to low global recycling rates of only 9%. Over three decades since implementing plastic resin codes, recycling has favoured thermoplastics, neglecting thermoset plastics. There is a constant need to enhance overall recycling efficiency by exploring advanced methods, as enormous gaps exist in fully unlocking the potential of plastic recycling. We identify critical gaps associated with plastic waste recycling and its potential environmental impacts. We discuss substantial progress in recycling technology, designs-for-recyclability with controlled chemical use, and economic incentives to expand markets for recycled plastics and to curb plastic leakage into the environment. Additionally, we highlight some emerging strategies and legally binding international policy instruments, such as the Global Plastics Treaty that require further development to reduce plastic waste and improve plastic recyclability.

The risk effects of corporate digitalization: exacerbate or mitigate?

This study elaborates on the risk effects of corporate digital transformation (CDT). Using the ratio of added value of digital assets to total intangible assets as a measure of CDT, this study overall reveals an inverse relationship between CDT and revenue volatility, even after employing a range of technical techniques to address potential endogeneity. Heterogeneity analysis highlights that the firms with small size, high capital intensity, and high agency costs benefit more from CDT. It also reveals that advancing information infrastructure, intellectual property protection, and digital taxation enhances the effectiveness of CDT. Mechanism analysis uncovers that CDT not only enhances financial advantages such as bolstering core business and mitigating non-business risks but also fosters non-financial advantages like improving corporate governance and ESG performance. Further inquiries into the side effects of CDT and the dynamics of revenue volatility indicate that CDT might compromise cash flow availability. Excessive digital investments exacerbate operating risks. Importantly, the reduction in operating risk associated with CDT does not sacrifice the potential for enhanced company performance; rather, it appears to augment the value of real options.

Plastics matter in the food system

Agriculture and food systems are major sources of plastic pollution but they are also vulnerable to their diverse lifecycle impacts. However, this problem is not well-recognized in global policy and scientific discourse, agendas, and monitoring of food systems. The United Nations-led Global Plastics Treaty, which has been under negotiation since 2022, is a critical opportunity to address pollution across the entire plastics lifecycle for more sustainable and resilient food systems. Here, we offer aspirational indicators for future monitoring of food systems’ plastics related to (1) plastic polymers and chemicals, (2) land use, (3) trade and waste, and (4) environmental and human health. We call for interdisciplinary research collaborations to continue improving and harmonising the evidence base necessary to track and trace plastics and plastic chemicals in food systems. We also highlight the need for collaboration across disciplines and sectors to tackle this urgent challenge for biodiversity, climate change, food security and nutrition, health and human rights at a whole systems level.

Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives

Diagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.

Diversity of biomass usage pathways to achieve emissions targets in the European energy system

Biomass is a versatile renewable energy source with applications across the energy system, but it is a limited resource and its usage needs prioritization. We use a sector-coupled European energy system model to explore near-optimal solutions for achieving emissions targets. We find that provision of biogenic carbon has higher value than bioenergy provision. Energy system costs increase by 20% if biomass is excluded at a net-negative (−110%) emissions target and by 14% at a net-zero target. Dispatchable bioelectricity covering ~1% of total electricity generation strengthens supply reliability. Otherwise, it is not crucial in which sector biomass is used, if combined with carbon capture to enable negative emissions and feedstock for e-fuel production. A shortage of renewable electricity or hydrogen supply primarily increases the value of using biomass for fuel production. Results are sensitive to upstream emissions of biomass, carbon sequestration capacity and costs of direct air capture.

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