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PurposeThis paper seeks to describe a protocol to estimate annual community energy consumption baselines for single‐family detached homes in the Gainesville Regional Utility service area of Alachua County, Florida, USA. Further, it details methods using these baselines to make direct comparisons of individual households' energy consumption and evaluate the energy impacts of three prescriptive demand side management (DSM) programs.Design/methodology/approachTo improve estimates of energy savings, the paper proposes using a “micro” scale multivariate regression methodology based on a census of utility and property appraiser household data.FindingsResults suggest that traditional analysis approaches are likely to overestimate savings significantly and that the annual community baseline technique provides more consistent estimates of energy savings than most commonly used methods.Practical implicationsThis type of analysis could provide a tool that utilities can use to more accurately and cost effectively measure DSM savings. This could result in reduced energy demand related to streamlined program setup and management.Originality/valueThe proposed methodology is unique in that it defines a new household‐level energy consumption baseline measure that we think is a more appropriate performance measure, uses a census of publicly available data for the population of interest, merging metered utility data with property appraiser data, and works upward to construct a simple model for evaluating household‐level energy consumption. The critical element that distinguishes our proposed energy performance measures is that they are calculated and interpreted using annual, population‐level, comparison‐group baselines that effectively normalize for community energy consumption patterns in any given year.

Interest in understanding water use and irrigation costs has risen in recent years. This case study is a 5-page evaluation of water use and associated costs for residential landscape irrigation in Osceola County and Orange County, Florida. Homeowners in central Florida can use the results to assess their water consumption and bills in relation to similar homes in the area. Written by Nick Taylor, Tricia Kyzar, Pierce Jones, and Kaitlin O. Robb Price, and published by the UF/IFAS Department of Agricultural and Biological Engineering, December 2019.https://edis.ifas.ufl.edu/ae536

Healthcare demand for liquid oxygen during the COVID-19 pandemic limited the availability of oxygen needed for ozone disinfection of drinking water in several urban areas of Florida. While the situation reduced the state’s capacity to provide normal drinking water treatment for millions of people, calls for water conservation during the emergency period resulted in virtually no change in water consumption. Here, we point out that 38–40% of the potable water produced by one of the major utilities in Florida is not used for drinking water but instead is used for outdoor landscape irrigation. This suggests that emergency-level calls for reduced water use could have been made if outdoor irrigation was limited, but we present data showing that there was little change in public behavior, and the state was unable to meet necessary water use reductions during the emergency. This inability to meet short-term emergency water conservation needs foretells a long-term lack of resilience against other global change scenarios and suggests that much work is still needed to build resilience into Florida’s water future. We conclude this Viewpoint paper by calling for more urgent sociohydrological research to understand the coupled human-natural drivers of how water supplies respond to global change.

To obtain additional information on these and other American Community Survey (ACS) subjects, see the list of Census Contacts on the Internet at http://www.census.gov/about/contact-us.html.Scope: These definitions apply to the data collected in both the United States and Puerto Rico. The text specifically notes any differences. References about comparability to the previous ACS years refer only to the ACS in the United States. Beginning in 2006, the population in group quarters was included in the data tabulations. Historical Census Comparability:For additional information about the data in previous decennial censuses, see http://www.census.gov/prod/www/decennial.html. Why We Ask:For additional information about the Federal Uses and why we ask specific questions, see https://www.census.gov/programs-surveys/acs/operations-and-administration/2014-contentreview/federal-uses.html. Weighting Methodology:The weighting methodology in the 2006 ACS was modified in order to ensure consistent estimates of occupied housing units, households, and householders. For more information on the 2006 weighting methodology changes, see "User Notes" on the ACS website (http://www.census.gov/programs-surveys/acs/technical-documentation/usernotes.html). There were no significant changes to the 2007 or 2008 weighting methodology. Beginning in 2009, the weighting methodology has changed to include the use of controls for total population for incorporated places and minor civil divisions.For subject definitions from previous years, visit http://www.census.gov and search for "ACS Code Lists, Definitions, and Accuracy." 8 Vacant Housing Unit -A housing unit is vacant if no one is living in it at the time of interview. Units occupied at the time of interview entirely by persons who are staying two months or less and who have a more permanent residence elsewhere are considered to be temporarily occupied, and are classified as "vacant." New units not yet occupied are classified as vacant housing units if construction has reached a point where all exterior windows and doors are installed and final usable floors are in place. Vacant units are excluded from the housing inventory if they are open to the elements, that is, the roof, walls, windows, and/or doors no longer protect the interior from the elements. Also excluded are vacant units with a sign that they are condemned or they are to be demolished.