Ensure access to affordable, reliable, sustainable and modern energy for all

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SDGs have been added on Scopus' author profile pages, appearing under the rebranded “Impact” section.

This study demonstrates the large rooftop photovoltaic energy potential of China’s capital cities, showing that rooftop installations could also mitigate heat.

Focusing on carbon capture, utilization, and storage (CCUS) technologies, this piece underscores their significance in realizing sustainability and carbon neutrality goals, particularly within challenging sectors.

More than 1100 people came together virtually on 18 June 2024 for the tenth edition of the RELX SDG Inspiration Day: "In the Age of AI: Information to Advance the UN Sustainable Development Goals (SDGs)." The annual online event brings together thought leaders, corporate representatives, students, investors, governments, and NGOs to explore pressing issues, gain practical insight, and inspire action on the United Nations Sustainable Development Goals (SDGs).

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Recognising our customers' exceptional work to achieve the UN Sustainable Development Goals.

RELX,

Gala, D., Khetan, S., & Mehendale, N. (2024). Assessing opportunities for enhanced lighting energy conservation via occupancy and daylight monitoring. Measurement: Energy, 3, 100015.

This article addresses SDGs 7, 12 and 13 by examining responsible energy consumption and automated systems that provide potential efficiencies through lighting optimization.

With evident relevance to SDG 6, the research explores a water pollution control technology evaluation model based on the Pythagorean language neutrosophic set (PLNS) in the context of the pulp and paper industry. The authors' model aims to assist in the choice of appropriate water pollution control technology for those working within the paper industry. It is tested in an example based in China.

This paper systematically reviews the current state-of-the-art and future perspectives of AI in battery research and applications for EVs.

In the pursuit of improving engine performance and mitigating emissions, researchers have explored the intriguing domain of fuel blends incorporating butanol and gasoline. This innovative study aims to unravel the intricate dynamics between butanol and gasoline when utilized as a blended fuel in internal combustion engines. The current study integrates cutting-edge techniques such as Artificial Neural Networks (ANN) and Response Surface Methodology (RSM) for the optimization of engine performance.

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