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Evidence-backed gain

Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (AI)

Abstract This study examines the multifaceted impact of artificial intelligence (AI) on environmental sustainability, specifically targeting ecological footprints, carbon emissions, and energy transitions. Utilizing panel data from 67 countries, we employ System Generalized Method of Moments (SYS-GMM) and Dynamic Panel Threshold Models (DPTM) to analyze the complex interactions between AI development and key environmental metrics. The estimated coefficients of the benchmark model show that AI significantly reduc…

Humanities and Social Sciences Communications · Climate

Evidence-backed gain

Impact of Artificial Intelligence on the Planning and Operation of Distributed Energy Systems in Smart Grids

This review paper thoroughly explores the impact of artificial intelligence on the planning and operation of distributed energy systems in smart grids. With the rapid advancement of artificial intelligence techniques such as machine learning, optimization, and cognitive computing, new opportunities are emerging to enhance the efficiency and reliability of electrical grids. From demand and generation prediction to energy flow optimization and load management, artificial intelligence is playing a pivotal role in t…

Climate

Evidence-backed gain

Artificial intelligence in environmental monitoring: Advancements, challenges, and future directions

• AI-driven pollution detection enhances environmental protection. • Real-time monitoring facilitates prompt interventions for pollution prevention. • Accurate air quality forecasting aids in planning pollution-reducing activities. • AI's role in smart cities fosters sustainable urban development. • AI algorithms integrate diverse data sources for pollution detection. The application of Artificial Intelligence (AI) in environmental monitoring offers accurate disaster forecasts, pollution source detection, and co…

Climate

Model-prefilled problem

Datacentres drive up big tech’s carbon emissions to a third of those of France

Microsoft, Amazon and Google’s collective carbon emissions have increased by nearly a fifth in the past year, driven largely by datacentre construction. In the financial year ending March 2026, the three tech companies emitted 119m mTCO₂e (metric tonnes of carbon dioxide equivalent), or about a third of those of France. The previous year, they emitted roughly 101m mTCO₂e, roughly equivalent to the 2024 emissions of Czechia. The US companies’ climate ambitions have been hit in recent years by a boom in demand for…

Climate

Both readings

Automation and Sustainability—The Impact of AI on Energy Consumption and Other Key Features of Industry 4.0/5.0 Technologies

Automation and sustainability are closely intertwined in the evolution of Industry 4.0 and 5.0, where artificial intelligence (AI) plays a key role in transforming energy consumption and production efficiency. For Industry 4.0, AI-based automation has optimized production, logistics, and resource management, reducing waste and improving throughput through predictive analytics and intelligent control systems. These systems have enabled energy-efficient production lines by automatically adjusting processes to mini…

Climate

Evidence-backed gain

Challenges of Artificial Intelligence Development in the Context of Energy Consumption and Impact on Climate Change

With accelerating climate change and rising global energy consumption, the application of artificial intelligence (AI) and machine learning (ML) has emerged as a crucial tool for enhancing energy efficiency and mitigating the impacts of climate change. However, their implementation has a dual character: on one hand, AI facilitates sustainable solutions, including energy optimization, renewable energy integration and carbon reduction; on the other hand, the training and operation of large language models (LLMs) e…

Climate

Evidence-backed gain

Digital Technologies and Sustainable Development: Evidence from FinTech, AI, and Blockchain Adoption in G20 Economies

In the wake of rapid digital transformation, emerging technologies like FinTech, AI, and Blockchain are reimagining how countries pursue sustainable development. This study examines how FinTech adoption, Artificial Intelligence (AI) readiness, and Blockchain activity influence sustainable development performance across G20 economies over the period 2015–2023. Drawing on Innovation-Driven Growth Theory, the Technology–Organization–Environment framework, and Institutional Theory, the analysis evaluates both the di…

Climate

Optimizing solar and wind forecasting with iHow optimization algorithm and multi-scale attention networks

Deep learning models often encounter two key challenges in developing intelligent and scalable forecasting frameworks for renewable energy systems: input feature space dimensionality and sensitivity to hyperparameter settings. These limitations increase computational cost and compromise generalization and robustness. This paper presents a hybrid deep learning-optimization framework that leverages cognitively inspired metaheuristics to address these challenges, employing the Binary iHow Optimization Algorithm (bi…

Climate

Optimizing solar and wind forecasting with iHow optimization algorithm and multi-scale attention networks

Knowledge-Based Feature Selection Substantially Enhances Data-Driven Wastewater Treatment Modeling

Data-driven modeling in wastewater treatment is increasingly constrained by the reality of small, high-dimensional data, where the abundant monitoring parameters in small-sized data sets obscure fundamental mechanistic understandings. This study proposes a knowledge-driven feature selection framework that integrates mechanistic insights with statistical correlations to identify the most informative predictive features. Using nitrous oxide (N 2 O) emission prediction at a full-scale plant as a case study, we comp…

Climate

Knowledge-Based Feature Selection Substantially Enhances Data-Driven Wastewater Treatment Modeling

‘There were stoats in kitchen cupboards’: AI deployed to help save Orkney’s birds

At first, the stoat looks like a faint smudge in the distance. But, as it jumps closer, its sleek body is identified by a heat-detecting camera and, with it, an alert goes out to Orkney’s stoat hunters. Aided by an artificial intelligence programme trained to detect a stoat’s sinuous shape and movement, trapping teams are dispatched with the explicit aim of finding and killing it. It is the most sophisticated technology deployed in one of the world’s largest mammal eradication projects, which has the aim of dete…

Climate

‘There were stoats in kitchen cupboards’: AI deployed to help save Orkney’s birds

AI is guzzling energy for slop content – could it be reimagined to help the climate?

Artificial intelligence is often associated with ludicrous amounts of electricity, and therefore planet-heating emissions, expended to create nonsensical or misleading slop that is of meagre value to humanity. Some AI advocates at a major UN climate summit are posing an alternative view, though – what if AI could help us solve, rather than worsen, the climate crisis? The “AI for good” argument has been made repeatedly at the Cop30 talks in Belém, Brazil, with supporters arguing AI can be used to lower, rather th…

Climate

US leads record global surge in gas-fired power driven by AI demands, with big costs for the climate

The US is leading a huge global surge in new gas-fired power generation that will cause a major leap in planet-heating emissions, with this record boom driven by the expansion of energy-hungry datacenters to service artificial intelligence, according to a new forecast. This year is set to shatter the annual record for new gas power additions around the world, with projects in development expected to grow existing global gas capacity by nearly 50%, a report by Global Energy Monitor (GEM) found. The US is at the f…

Climate