This paper seeks to inform an improved understanding of the energy tradeoff associated with on-site manufacturing water reuse in the U.S. from a lifecycle perspective, in part by developing an analytical framework for understanding when this tradeoff for reuse is beneficial. We survey the literature to assess the current state of reuse and its motives and barriers in the U.S., before synthesizing information from publicly available EPA data on contaminants in U.S. manufacturing wastewaters and technologies for treating them. Using the available data, we derive a set of "ubiquitous contaminants" among the top ten in terms of mass discharged in more than half of U.S. manufacturing subsectors (NAICS 31-33) according to EPA permit data. We also present information on proven treatment trains and their energy requirements. We then compare water quality requirements for specific contaminants in reclaimed water to those characteristic of wastewater streams currently being discharged from manufacturing plants into surface waters to highlight sectors with reuse opportunities that could require little cost to realize, such as primary metals and, to a lesser extent, petroleum and coal products. We conclude by highlighting data limitations that need to be rectified before applying the framework more broadly and discussing how these data gaps could be filled. Better understanding the relationship between energy and water in the context of on-site manufacturing water reuse would allow manufacturers to improve resiliency by reducing regulatory, physical, and reputational risks while lessening their footprint on local watersheds.
Since 2006, the U.S. Environmental Protection Agency (EPA) has operated WaterSense® in partnership with manufacturers, utilities, and consumer groups. Similar to EPA's ENERGY STAR® role for energy-efficient products, WaterSense® employs a labeling system to identify water-efficient products, homes, and services. As of 2015, the WaterSense® program can claim credit for a total savings of 1.5 trillion gallons of water and $32.6 billion in consumer water and energy bills. Savings are tracked in the National Water Savings (NWS) model that combines innovative analyses with methodologies established in the energy sector. Merging life-cycle cost and national impact analysis models, the NWS model estimates savings from a bottom-up accounting method for individual products. The model extends those savings to the national level by employing parameters such as frequency of product use by number of people and building type, product lifetime, stock accounting, and market saturation. The NWS model tracks the water and consumer monetary savings of WaterSense-labeled products for residential and commercial water use both indoors and out.includes labeled toilets, faucets, showerheads, and faucet aerators for the residential sector; and flushometer valve toilets, urinals, and pre-rinse spray valves for the commercial
. Moreover, we are grateful to Thomas Burke and Danielle Fox for script development, process documentation and troubleshooting of several metering issues, and to Deborah Ash for the procurement and delivery of meters to LBNL, space and storage logistics, as well as handling of on-going mailing of meters. We thank Mohan Ganeshalingam and Steven Lanzisera for helpful comments that improved this report. Finally we are grateful to Gregory J. Rosenquist and Alex Lekov, project co-leaders of the LBNL Energy Efficiency Standards Group, for providing high-level project support and encouragement. 3 AbstractThe electricity consumption of miscellaneous electronic loads (MELs) in the home has grown in recent years, and is expected to continue rising. Consumer electronics, in particular, are characterized by swift technological innovation, with varying impacts on energy use. Desktop and laptop computers make up a significant share of MELs' electricity consumption, but their national energy use is difficult to estimate, given uncertainties around shifting user behavior. This report analyzes usage data from 64 computers (45 desktop, 11 laptop, and 8 unknown) collected in 2012 as part of a larger field monitoring effort of 880 households in the San Francisco Bay Area, and compares our results to recent values from the literature. We find that desktop computers are used for an average of 7.3 hours per day (median = 4.2 h/d), while laptops are used for a mean 4.8 hours per day (median = 2.1 h/d). The results for laptops are likely underestimated since they can be charged in other, unmetered outlets. Average unit annual energy consumption (AEC) for desktops is estimated to be 194 kWh/yr (median = 125 kWh/yr), and for laptops 75 kWh/yr (median = 31 kWh/yr). We estimate national annual energy consumption for desktop computers to be 20 TWh. National annual energy use for laptops is estimated to be 11 TWh, markedly higher than previous estimates, likely reflective of laptops drawing more power in On mode in addition to greater market penetration. This result for laptops, however, carries relatively higher uncertainty compared to desktops. Different study methodologies and definitions, changing usage patterns, and uncertainty about how consumers use computers must be considered when interpreting our results with respect to existing analyses. Finally, as energy consumption in On mode is predominant, we outline several energy savings opportunities: improved power management (defaulting to low-power modes after periods of inactivity as well as power scaling), matching the rated power of power supplies to computing needs, and improving the efficiency of individual components.
No abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.