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Rapid progress in the field of machine-learning for weather prediction has led to the emergence of algorithms whose forecasting skill can exceed that of traditional physically based models. This development represents an opportunity to…

Energy saving and carbon emission reduction in buildings is one of the key measures in combating climate change. Heating, Ventilation, and Air Conditioning (HVAC) system account for the majority of the energy consumption in the built…

Carbon emissions significantly contribute to climate change, and carbon credits have emerged as a key tool for mitigating environmental damage and helping organizations manage their carbon footprint. Despite their growing importance across…

AI has been proposed as an important tool to support several efforts related to nature-based climate solutions such as the detection of wildfires that affect forests and vegetation-based offsets. While this and other use-cases provide…

In recent years, large-scale auto-regressive models have made significant progress in various tasks, such as text or video generation. However, the environmental impact of these models has been largely overlooked, with a lack of assessment…

This paper addresses challenges of designing and managing Complex Performance Indicators (CPI), which amalgamate individual indicators to measure latent, yet crucial business factors like customer satisfaction or sustainability indices.…

Concerns about the environmental footprint of machine learning are increasing. While studies of energy use and emissions of ML models are a growing subfield, most ML researchers and developers still do not incorporate energy measurement as…

Development of air pollution models for large regions is a priority for population-based epidemiologic studies. The rapid development of big data information systems and machine learning algorithms have opened new grounds for refinements of…

Robust generalization under climate change remains a major challenge for machine learning applications in climate science. Most existing approaches struggle to extrapolate beyond the climate they were trained on, leading to a strong…

The rapid advancement of Artificial Intelligence (AI) has created unprecedented demands for computational power, yet methods for evaluating the performance, efficiency, and environmental impact of deployed models remain fragmented. Current…

Climate change has intensified the need for transparency and accountability in organizational practices, making Environmental, Social, and Governance (ESG) reporting increasingly crucial. Frameworks like the Global Reporting Initiative…

Predictive Business Process Monitoring (PBPM) aims to forecast future outcomes of ongoing business processes. However, existing methods often lack flexibility to handle real-world challenges such as simultaneous events, class imbalance, and…

We document the data transfer workflow, data transfer performance, and other aspects of staging approximately 56 terabytes of climate model output data from the distributed Coupled Model Intercomparison Project (CMIP5) archive to the…

To address the problem of combined heat and power economic emission dispatch (CHPEED), a two-stage approach is proposed by combining multi-objective optimization (MOO) with integrated decision making (IDM). First, a practical CHPEED model…

A vital strategy for ports to mitigate the environmental impact of the maritime industry, while complying with frameworks such as the European Green Deal and the Sustainable Development Goals (SDGs), entails the systematic implementation of…

Global ambient air pollution, a transboundary challenge, is typically addressed through interventions relying on data from spatially sparse and heterogeneously placed monitoring stations. These stations often encounter temporal data gaps…

In the last fifty years, researchers have developed statistical, data-driven, analytical, and algorithmic approaches for designing and improving emergency response management (ERM) systems. The problem has been noted as inherently difficult…

Growing concerns about climate change and sustainability are driving manufacturers to take significant steps toward reducing their carbon footprints. For these manufacturers, a first step towards this goal is to identify the environmental…

With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates…

Commuting contributes substantially to urban greenhouse gas emissions and represents a critical focus for climate mitigation efforts. This paper explores the multifaceted nature of commuting-related carbon dioxide emissions by analyzing the…