Related papers: Footprinting in a course on energy
Estimating the greenhouse gas emissions of research-related activities is a critical first step towards the design of mitigation policies and actions. Here we propose and motivate a transparent framework for reporting research-related…
The sustainability of urban environments is an increasingly relevant problem. Air pollution plays a key role in the degradation of the environment as well as the health of the citizens exposed to it. In this chapter we provide a review of…
There is a perception that climate science can only be approached with complex computer simulations. But working climate scientists often use simple models to understand their simulations and make order-of-magnitude estimates. This article…
Carbon matching aims to improve corporate carbon accounting by tracking emissions rather than energy consumption and production. We present a mathematical derivation of carbon matching using marginal emission rates, where the unit of…
We make a case for "planetary computing" -- infrastructure to handle the ingestion, transformation, analysis and publication of global data products for furthering environmental science and enabling better informed policy-making. We draw on…
Future accelerators and experiments for energy-frontier particle physics will be built and operated during a period in which society must also address the climate change emergency by significantly reducing emissions of carbon dioxide. The…
In classical thermodynamic processes the unavoidable presence of irreversibility, quantified by the entropy production, carries two energetic footprints: the reduction of extractable work from the optimal, reversible case, and the…
Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is…
An increasing number of individuals, companies and organizations are interested in computing and minimizing the carbon emissions associated with their real-time electricity consumption. To achieve this, they require a carbon signal, i.e. a…
These lecture notes provide a comprehensive guide on Grid Modeling of Renewable Energy, offering a foundational overview of power system network modeling, power flow, and load flow algorithms critical for electrical and renewable energy…
Course selection is a crucial activity for students as it directly impacts their workload and performance. It is also time-consuming, prone to subjectivity, and often carried out based on incomplete information. This task can, nevertheless,…
Rapid advances in artificial intelligence (AI) in the last decade have largely been built upon the wide applications of deep learning (DL). However, the high carbon footprint yielded by larger and larger DL networks becomes a concern for…
Road infrastructure significantly impacts how people move and live and the emissions associated with travel behaviour. The design of roads is crucial in mitigating emissions. This paper reviews existing transport life cycle assessment tools…
From ride-hailing to car rentals, consumers are often presented with eco-friendly options. Beyond highlighting a "green" vehicle and CO2 emissions, CO2 equivalencies have been designed to provide understandable amounts; we ask which…
To enhance decarbonization efforts in electric power systems, we propose a novel electricity market clearing model that internalizes the allocation of emissions from generations to loads and allows for consideration of consumer-side carbon…
Scientific workflows are critical to scientific data analysis and often involve computationally intensive processing of large datasets on compute clusters. As such, their execution tends to be long-running and resource-intensive, resulting…
The ongoing massive global environmental changes and the past learnings have highlighted the urgency and importance of further detailed understanding of the earth system and implementation of social ecological sustainability measures in a…
The evaluation of Deep Learning models has traditionally focused on criteria such as accuracy, F1 score, and related measures. The increasing availability of high computational power environments allows the creation of deeper and more…
Along with the accumulation of atmospheric carbon dioxide, the loss of primary forests and other natural ecosystems is a major disruption of the Earth system causing global concern. Quantifying planetary warming from carbon emissions,…
The spotlight is on the intertwined nature of sustainability and energy transition. As the world grapples with environmental challenges, the push for a green approach to energy is more crucial than ever. This transition promises not just a…