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Lecture

Water Consumption in Geneva

In course

ENV-370: Environmental system analysis and assessment

Les enjeux environnementaux doivent être abordés de façon systémique. L'Analyse du Cycle de Vie (ACV) et l'Analyse de Flux de Matière (AFM) sont des méthodes permettant d'évaluer de façon globale les performances environnementales des produits, des service ...

Description

This lecture covers the water consumption data in Geneva, including charts on water consumption and losses, available datasets, and the data processing phases. It also discusses the context, biophysical characteristics, infrastructure, and stocks and flows of the city.

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Instructors (3)

Claudia Rebeca Binder Signer

Claudia R. Binder, a Swiss, Canadian and Colombian citizen, was born in Montreal and spent most of her childhood in Switzerland and Colombia. She studied at ETH Zurich from 1985 to 1996, earning a degree in biochemistry and then a PhD in environmental sciences. After conducting her post-doctoral research at the University of Maryland in the US from 1996 to 1998, she returned to Switzerland and took a position as a senior research scientist at ETH Zurich, studying the interaction between human and environmental systems at the Institute for Natural and Social Science Interface. In 2006, Binder joined the University of Zurich as an assistant professor in the Department of Geography, and in 2009 moved to the University of Graz in Austria where she served as a full professor of systems science. In 2011, she took a position at the University of Munich’s Department of Geography as a full professor of human-environment relations. Binder joined EPFL in March 2016 and set up the Laboratory for Human-Environment Relations in Urban Systems (HERUS) at ENAC; she also holds the La Mobilière Chair on Urban Ecology and Sustainable Living. Her research involves analyzing, modelling and assessing the transition of urban systems towards sustainability. She looks in particular at how we can better understand the dynamics of urban metabolism, what characterizes a sustainable city, and what drives and hinders transformation processes. She does so by combining knowledge from social, natural and data science. Her research focuses on food, energy, and sustainable living and transport in urban systems. In Switzerland, Binder was appointed to the Research Council, Programs Division of the Swiss National Science Foundation (SNSF) in 2016 and serves on the Steering Committee of the SNSF’s National Research Program 71, “Managing Energy Consumption” and the Swiss Competence Centers for Energy Research (SCCER). She is also a member of the Steering Board on Sustainability Research for the Swiss Academies of Arts and Sciences. In 2019, she was elected as a member of the University Council of the University of Munich (LMU). At EPFL, Binder is the academic director of Design Together, a cross-disciplinary teaching initiative. She was appointed to the management team of the Energy Center in 2018 and as head of the working group on EPFL’s energy and sustainability strategy in 2019.

Aristide Henri Roger Athanassiadis

Aristide has a joint-PhD in Urbanism from the Université Libre de Bruxelles and The University of Melbourne on the topic of comprehensive urban environmental assessments. Since 2018, he was co-Chair of Circular Economy and Urban Metabolism at the Université Libre de Bruxelles where he advised local administrations on the regional circular economy plan and facilitated exchanges between researchers, policy makers and practitioners in order to develop projects that helped Brussels' economy and metabolism transition towards a more circular state. During the last years, he has collaborated and worked with/for several universities, research centres, environmental administrations, NGOs, youth organisations and consultancy firms on a great variety of projects around the topics of urban metabolism and circular economy. Finally, Aristide co-created the non-profit organisation and open-source initiative Metabolism of Cities (www.metabolismofcities.org) that aims to bring to create, share and apply urban metabolism knowledge, in policy and practice.

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Data Preprocessing

Data preprocessing can refer to manipulation or dropping of data before it is used in order to ensure or enhance performance, and is an important step in the data mining process. The phrase "garbage in, garbage out" is particularly applicable to data mining and machine learning projects. Data collection methods are often loosely controlled, resulting in out-of-range values, impossible data combinations, and missing values, amongst other issues. Analyzing data that has not been carefully screened for such problems can produce misleading results.

Data mining

Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD.

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In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

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