Goal based water conservation projections based on historical water use data and trends in Miami-Dade County

Lee, Mengshan; Tansel, Berrin; Balbin, Maribel

doi:10.1016/j.scs.2011.04.002

Cited by 14 publications

(9 citation statements)

References 8 publications

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“…Meeting this increased need will be a daunting challenge, with only 60% of global demand for potable water expected to be satisfied in 2030 (Boccaletti, Grobbel, & Stuchtey, 2010). Despite having substantial natural water resources, the United States is facing significant water shortages, especially in the western states, and current water conservation projects are not expected to meet goals set by the United States Environmental Protection Agency (EPA) (Christen, 2003;Lee, Tansel, & Balbin, 2011). Taking into account the impact of climate change effects over time, a large portion of National Multi-Housing Council, 63% of households in multi-family rental housing earn less than $35,000, with a median income of just $25,768 compared to $45,964 for all U.S.…”

Section: Introductionmentioning

confidence: 99%

Modeling the determinants of large-scale building water use: Implications for data-driven urban sustainability policy

Kontokosta

Jain

2015

Sustainable Cities and Society

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a b s t r a c tAs the world's population continues to urbanize, cities are struggling to meet the demand for key resources such as clean water. In urban areas, enhancing the sustainability and water efficiency of buildings is crucial to meeting the resource needs of a growing population. Nevertheless, the understanding of the determinants of urban water consumption -and specifically of multi-family residential buildings that constitute the bulk of the urban building stock -is limited. Using an extensive database of actual water use from New York City's Local Law 84, coupled with land use and demographic data from the NYC Primary Land Use Tax Lot Output (PLUTO) database and Census data, we apply weighted robust regression and geographically weighted regression (GWR) models to analyze the determinants and spatial patterns of water consumption in over 2300 multi-family buildings located in New York City. Our results indicate that occupancy, building size, building age, ownership structure, neighborhood demographic and socioeconomic characteristics, and the energy use intensity (EUI) of a building all have statistically significant effects on the water use intensity (WUI) of multi-family housing. Results of the GWR spatial analysis demonstrate large spatial variability across building characteristics, demographic variables and household income. The analysis and findings presented here give further support to the potential of targeted measures and incentives, segmented and classified by building characteristics and neighborhoods, to be effective tools for policymakers seeking to increase water efficiency in urban buildings and to accelerate reductions in resource use at the city scale.

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Section: Introductionmentioning

confidence: 99%

Modeling the determinants of large-scale building water use: Implications for data-driven urban sustainability policy

Kontokosta

Jain

2015

Sustainable Cities and Society

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“…In the US and Canada, there is a decline in per-capita water use across many cities [66][67][68][69] In Botswana and South Africa, reduced per-capita potable water use has been reported in cities [3,72].…”

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confidence: 99%

Promoting Water Conservation: Where to from here?

Moglia¹,

Cook²,

Tapsuwan³

2018

Water

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This paper reports on a review of international water conservation efforts, but with a particular focus on the Australian context. The aim is to take stock of the current understanding of water conservation, in particular: what influences people's decision to conserve water, what influences whether people persist with water conservation behavior and what contributes to awareness and familiarity of water conservation behaviors. We also explore how all these factors jointly can achieve water savings over time, and the efficacy of past efforts to save water. Subsequently, this is used to identify where leading practice for managing water conservation is heading, which we argue is the application of recent developments in behavioral science and advances in smart metering to personalize water conservation programs. To support individualized water conservation efforts, we need more longitudinal studies of water conservation behavior, a greater focus on behavioral science, as well as the development of modelling tools that embed insights and lessons of this research into decision support capability. This can help to develop the capacity to better implement water conservation programs that respond to short-term water scarcity crises, such as droughts, while also providing persistent reductions in per-capita water demand that can help meet strategic water planning needs, such as deferring or downsizing capital investment in supply infrastructure to accommodate demands associated with population growth.

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“…Residential water conservation practices (i.e., installation of water efficiency appliances) can be beneficial from several aspects: 1. residential appliances have a major contribution on household water demand, and, 2. the potential water savings for efficient appliances could be significant Baumann et al, 1998;Fidar et al, 2010;Kenney et al, 2008;Lee et al, 2011b;Millock and Nauges, 2010;Olmstead and Stavins, 2009;Pathakamuri et al, 2010). Furthermore, water efficiency incentives (i.e., rebate or exchange programs) for household appliances are considered to be more acceptable by the public in comparison to other water management policies such as price increase or water restrictions (Millock and Nauges, 2010;Randolph and Troy, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…Water consumption for different waterusing appliances in this study is presented in Table 5.1 (Anand and Apul, 2011;Davis, 2008;Lee et al, 2011b;Mayer et al, 1999;Pakula and Stamminger, 2010 (Davis, 2008). Electricity consumption for various processes in the water systems, including water supply and wastewater treatments is provided in Table 5.2 (Lundie et al, 2004;Racoviceanu et al, 2007;Vince et al, 2008).…”

Section: End-use and Demandmentioning

confidence: 99%

Integrated Assessment of Water Conservation Practices For Sustainable Management Strategies

Lee

Self Cite

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Approximately 6 to 10 % of water has been saved in the first and second year of implementation of high efficiency appliances, and with continuing savings in the third and fourth years. Water savings (gallons per household per day) for water efficiency appliances were observed at 28 (11.1%) for SH, 34.7 (13.3%) for HET, and 39.7 (14.5%) for HEW. Furthermore, the estimated contributions of high efficiency appliances for reducing water demand in the integrated water demand model were between 5 and 19% viii (highest in the AR program). Results indicated that adoption of more than one type of water efficiency appliance could significantly reduce residential water demand.For the sustainable water management strategies, the appropriate water conservation rate was projected to be 1 to 2 million gallons per day (MGD) through 2030.With 2 MGD of water savings, the estimated per capita water use (GPCD) could be reduced from approximately 140 to 122 GPCD. Additional efforts are needed to reduce the water demand to US EPA's "Water Sense" conservation levels of 70 GPCD by 2030.Life cycle assessment results showed that environmental impacts (water and energy demands and greenhouse gas emissions) from end-use and demand phases are most significant within the water system, particularly due to water heating (73% for clothes washer and 93% for showerhead). Estimations of optimal lifespan for appliances (8 to 21 years) implied that earlier replacement with efficiency models is encouraged in order to minimize the environmental impacts brought by current practice.

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Goal based water conservation projections based on historical water use data and trends in Miami-Dade County

Cited by 14 publications

References 8 publications

Modeling the determinants of large-scale building water use: Implications for data-driven urban sustainability policy

Modeling the determinants of large-scale building water use: Implications for data-driven urban sustainability policy

Promoting Water Conservation: Where to from here?

Integrated Assessment of Water Conservation Practices For Sustainable Management Strategies

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