A mass balance approach to urban water analysis using multi‐resolution data
Bibliographic Data
| ID | 19469642 |
|---|---|
| Authors | Allisa G Hastie (0000-0002-5063-8403, Department of Civil and Environmental Engineering University of Illinois at Urbana‐Champaign Urbana Illinois), Christopher M Chini (0000-0002-1208-3646, Department of Systems Engineering and Management Air Force Institute of Technology Wright Patterson AFB Ohio), Ashlynn S Stillwell (0000-0002-6781-6480, Department of Civil and Environmental Engineering University of Illinois at Urbana‐Champaign Urbana Illinois, corresponding author) |
| Year | 2022 |
| Volume | 26 |
| Issue | 1 |
| Pages | 213-224 |
| Publication date | 2022-02-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Industrial Ecology (JOURNAL) |
| Journal identifiers | ISSN: 1088-1980 • E-ISSN: 1530-9290 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1111/jiec.12995 |
| OpenAlex | W3007221977 |
| Language | EN |
| Citations received | 1 |
| References cited | 47 |
With a growing urban population and increasing climate uncertainty, it is necessary to quantitatively understand the flux of resources through cities, specifically energy and water resources. Many methods exist to analyze the urban energy–water nexus based on either physical characteristics of the system or using available data. While data‐driven approaches can be valuable, they are often challenging to duplicate on a large scale due to data availability, or they do not allow for drawing specific, detailed conclusions. Our work seeks to remedy these challenges by using multi‐resolution data and a mass balance approach to provide a reproducible and scalable method for analyzing water and embedded energy systems in cities with varying levels of infrastructure and technological advancements. Using a combination of utility‐scale and meter‐level data, we provide several quantitative performance gauges on a monthly and annual time scale. This process reveals notable seasonal variation in water demand, non‐revenue water, and embedded energy, providing a holistic understanding of water and its embedded resources. Our work further confronts the challenges of integrating disparate data sets into a uniform format to allow for accurate analysis. These particular data, coupled with a mass balance methodology, facilitate the examination of an urban area from top‐down and bottom‐up perspectives, yielding opportunities to quantify additional performance metrics beyond a single approach
Data science · Database · Geography · Population · Scalability · Water balance · Water resources · Computer Science · Engineering · Environmental Science · Water resources management and optimization · Water Systems and Optimization · Water-Energy-Food Nexus Studies
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Evaluating the electricity intensity of evolving water supply mixes
Evaluating the energy consumed for water use in the United States
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| Citations per year | 0.25 |
|---|---|
| Citation span | 2022 - 2022 (1) |
| Highly cited | No |