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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.

Dynamic optimizers for complex industrial systems via direct data-driven synthesis

The chemical process industry (CPI) faces significant challenges in improving sustainability and efficiency while maintaining conservative principles for managing cost, complexity, and uncertainty. This work introduces a data-driven approach to dynamic real-time optimization (D-RTO) that addresses the aforementioned concerns by directly extracting process optimization policies from historical plant data. Our method constructs a value function to evaluate trajectory quality and employs weighted regression to derive improved policies. When applied to a plant-wide industrial process control problem, the proposed optimizer demonstrates superior performance in adapting to disturbances while maintaining stability and product quality. These results challenge conventional assumptions regarding the potential of data-driven optimization in the CPI. Although limitations exist due to the black-box nature of neural networks, this study presents a promising avenue for enhancing operational efficiency in industrial settings. The proposed approach offers a practical solution for process optimization, as it leverages readily available historical data and does not require extensive modeling efforts. By demonstrating significant efficiency improvement on a realistic industrial benchmark problem, this work paves the way for the adoption of data-driven optimization techniques in real-world CPI applications.

Brine management with zero and minimal liquid discharge

Zero liquid discharge (ZLD) and minimal liquid discharge (MLD) are brine management approaches that aim to reduce the environmental impacts of brine discharge and recover water for reuse. ZLD maximizes water recovery and avoids the needs for brine disposal, but is expensive and energy-intensive. MLD (which reduces the brine volume and recovers some water) has been proposed as a practical and cost-effective alternative to ZLD, but brine disposal is needed. In this Review, we examine the concepts, technologies and industrial applications of ZLD and MLD. These brine management strategies have current and potential applications in the desalination, energy, mining and semiconductor industries, all of which produce large volumes of brine. Brine concentration and crystallization in ZLD and MLD often rely on mechanical vapour compression and thermal crystallizers, which are effective but energy-intensive. Novel engineered systems for brine volume reduction and crystallization are under active development to achieve MLD and/or ZLD. These emerging systems, such as membrane distillation, electrodialytic crystallization and solvent extraction desalination, still face challenges to outcompete mechanical vapour compression and thermal crystallizers, underscoring the critical need to maximize the full potential of reverse osmosis to attain ultrahigh water recovery. Brine valorization has potential to partially offset the cost of ZLD and MLD, provided that resource recovery can be integrated into treatment trains economically and in accordance with regulations.

Management practices and manufacturing firm responses to a randomized energy audit

Increasing the efficiency of industrial energy use is widely considered important for mitigating climate change. We randomize assignment of an energy audit intervention aimed at improving energy efficiency and reducing energy expenditures of small- and medium-sized metal processing firms in Shandong Province, China, and examine impacts on energy outcomes and interactions with firms’ management practices. We find that the intervention reduced firms’ unit cost of electricity by 8% on average. Firms with more developed structured management practices showed higher rates of recommendation adoption. However, the post-intervention electricity unit cost reduction is larger in firms with less developed practices, primarily driven by a single recommendation that corrected managers’ inaccurate reporting of transformer usage at baseline, lowering their electricity costs. By closing management-associated gaps in awareness of energy expenditures, energy audit programmes may reduce a firm’s unit cost of energy but have an ambiguous impact on energy use and climate change.

State-level policies alone are insufficient to meet the federal food waste reduction goal in the United States

The United States Food Loss and Waste Reduction Goal seeks to reduce national food waste by 50%, down to 74 kg per capita, by 2030. Here we investigate state policies’ alignment with the federal goal across four policy categories. We develop a policy scoring matrix and apply it to wasted food solutions listed in the non-profit ReFED’s database to derive ranges of food waste diversion potential and projected generation across states. On the basis of state policies alone, no state can meet the federal target. We estimated a diversion potential of 5–14 kg per capita and a food waste generation of 149 kg per capita nationally in 2022, equivalent to the 2016 baseline. Without additional intervention at the state and federal level promoting a shift from food waste recycling towards prevention, rescue and repurposing, food generation in the United States will probably remain high.

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