Zhang, Su; Bogus, Susan M.; Lippitt, Christopher D.; Migliaccio, Giovanni C. (2017). Estimating Location-Adjustment Factors for Conceptual Cost Estimating Based on Nighttime Light Satellite Imagery. Journal Of Construction Engineering And Management, 143(1).
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Abstract
A fundamental process in construction cost estimation is the appropriate adjustment of costs to reflect project location. Unfortunately, location adjustment factors are not available for all locations. To overcome this lack of data, cost estimators in the United States often use adjustment factors from adjacent locations, referred to as the nearest neighbor (NN) method. However, these adjacent locations may not have similar economic conditions, which limit the accuracy of the NN method. This research proposes a new method of using nighttime light satellite imagery (NLSI) to estimate location adjustment factors where they do not exist. The NLSI method for estimating location adjustment factors was evaluated against an established cost index database, and results show that NLSI can be used to effectively estimate location adjustment factors. When compared with NN and other alternative proximity-based location adjustment methods, the proposed NLSI method leads to a 25-40% reduction of the median absolute error. This work contributes to the body of knowledge by introducing a more accurate method for estimating location adjustment factors which can improve cost estimates for construction projects where location adjustment factors do not currently exist. (C) 2016 American Society of Civil Engineers.
Keywords
Construction Industry; Costing; Industrial Economics; Project Management; Remote Sensing; Location-adjustment Factors; Nighttime Light Satellite Imagery; Construction Cost Estimation; Project Location; United States; Economic Conditions; Nlsi Method; Cost Index Database; Median Absolute Error Reduction; Construction Projects; Nearest Neighbor Method; Urbanization Dynamics; Proxy; Construction Costs; Estimation; Construction Management; Pricing; Cost And Schedule
Cowling, Krycia; Lindberg, Ruth; Dannenberg, Andrew L.; Neff, Roni A.; Pollack, Keshia M. (2017). Review of Health Impact Assessments Informing Agriculture, Food, and Nutrition Policies, Programs, and Projects in the United States. Journal Of Agriculture Food Systems And Community Development, 7(3), 139 – 157.
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Abstract
Policies, programs, and projects related to agriculture, food, and nutrition can significantly affect public health. Health impact assessment (HIA) is one tool that can be used to improve awareness of the health effects of decisions outside the health sector, and increasing the use of HIA for agriculture, food, and nutrition decisions presents an opportunity to improve public health. This study identifies and reviews all HIAs completed in the United States on agriculture, food, and nutrition topics. Studies were identified from HIA databases, an Internet search, and expert consultation. Key characteristics were extracted from each study: type of decision assessed, location, level of jurisdiction, lead organization, methods of analysis, and recommendations. Twenty-five eligible HIAs that were conducted between 2007 and 2016 address topics such as regulations on land use for agriculture; food and beverage taxes; and developing grocery stores in food deserts. These HIAs have predominantly supported policy, as opposed to program or project, decisions. Four case studies are presented to illustrate in detail the HIA process and the mechanisms through which HIA findings affected policy decisions. Among other influences, these four HIAs affected the language of legislation and provided guidance for federal regulations. These examples demonstrate several findings: appropriate timing is critical for findings to have an influence; diverse stakeholder involvement generates support for recommendations; and the clear communication of feasible recommendations is highly important. There is substantial scope to increase the use of HIA in the agriculture, food, and nutrition sectors. Challenges include the paucity of monitoring and evaluation of HIAs' effects on health outcomes, and the limited funding available to conduct HIAs. Opportunities include integrating HIAs and community food assessments, and more widely sharing HIA findings to inform related decisions in different jurisdictions and to increase support for additional HIAs that address the food system.
Keywords
Environments; Obesity; Health Impact Assessment; Policy; Food; Nutrition; Agriculture
Neff, Gina; Tanweer, Anissa; Fiore-Gartland, Brittany; Osburn, Laura. (2017). Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies And Data Science. Big Data, 5(2), 85 – 97.
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Abstract
What would data science look like if its key critics were engaged to help improve it, and how might critiques of data science improve with an approach that considers the day-to-day practices of data science? This article argues for scholars to bridge the conversations that seek to critique data science and those that seek to advance data science practice to identify and create the social and organizational arrangements necessary for a more ethical data science. We summarize four critiques that are commonly made in critical data studies: data are inherently interpretive, data are inextricable from context, data are mediated through the sociomaterial arrangements that produce them, and data serve as a medium for the negotiation and communication of values. We present qualitative research with academic data scientists, data for good projects, and specialized cross-disciplinary engineering teams to show evidence of these critiques in the day-to-day experience of data scientists as they acknowledge and grapple with the complexities of their work. Using ethnographic vignettes from two large multiresearcher field sites, we develop a set of concepts for analyzing and advancing the practice of data science and improving critical data studies, including (1) communication is central to the data science endeavor; (2) making sense of data is a collective process; (3) data are starting, not end points, and (4) data are sets of stories. We conclude with two calls to action for researchers and practitioners in data science and critical data studies alike. First, creating opportunities for bringing social scientific and humanistic expertise into data science practice simultaneously will advance both data science and critical data studies. Second, practitioners should leverage the insights from critical data studies to build new kinds of organizational arrangements, which we argue will help advance a more ethical data science. Engaging the insights of critical data studies will improve data science. Careful attention to the practices of data science will improve scholarly critiques. Genuine collaborative conversations between these different communities will help push for more ethical, and better, ways of knowing in increasingly datum-saturated societies.
Keywords
Big; Communication; Politics; Critical Data Studies; Data For Good; Data Science; Ethics; Qualitative Methods; Theory
Zhu, Panyu; Gilbride, Michael; Yan, Da; Sun, Hongshan; Meek, Christopher. (2017). Lighting Energy Consumption in Ultra-Low Energy Buildings: Using a Simulation and Measurement Methodology to Model Occupant Behavior and Lighting Controls. Building Simulation, 10(6), 799 – 810.
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Abstract
As building owners, designers, and operators aim to achieve significant reductions in overall energy consumption, understanding and evaluating the probable impacts of occupant behavior becomes a critical component of a holistic energy conservation strategy. This becomes significantly more pronounced in ultra-efficient buildings, where system loads such as heating, cooling, lighting, and ventilation are reduced or eliminated through high-performance building design and where occupant behavior-driven impacts reflect a large portion of end-use energy. Further, variation in behavior patterns can substantially impact the persistence of any performance gains. This paper describes a methodology of building occupant behavior modeling using simulation methods developed by the Building Energy Research Center (BERC) at Tsinghua University using measured energy consumption data collected by the University of Washington Integrated Design Lab (UW IDL). The Bullitt Center, a six-story 4831 m(2) (52,000 ft(2)) net-positive-energy urban office building in Seattle, WA, USA, is one of the most energy-efficient buildings in the world (2013 WAN Sustainable Building of the Year Winner). Its measured energy consumption in 2015 was approximately 34.8 kWh/(m(2)a (TM) yr) (11 kBtu/(ft(2)a (TM) yr)). Occupant behavior exerts an out-sized influence on the energy performance of the building. Nearly 33% of the end-use energy consumption at the Bullitt Center consists of unregulated miscellaneous electrical loads (plug-loads), which are directly attributable to occupant behavior and equipment procurement choices. Approximately 16% of end-use energy is attributable to electric lighting which is also largely determined by occupant behavior. Key to the building's energy efficiency is employment of lighting controls and daylighting strategies to minimize the lighting load. This paper uses measured energy use in a 330 m(2) (3550 ft(2)) open office space in this building to inform occupant profiles that are then modified to create four scenarios to model the impact of behavior on lighting use. By using measured energy consumption and an energy model to simulate the energy performance of this space, this paper evaluates the potential energy savings based on different occupant behavior. This paper describes occupant behavior simulation methods and evaluates them using a robust dataset of 15 minute interval sub-metered energy consumption data. Lighting control strategies are compared via simulation results, in order to achieve the best match between occupant schedules, controls, and energy savings. Using these findings, we propose a simulation methodology that incorporates measured energy use data to generate occupant schedules and control schemes with the ultimate aim of using simulation results to evaluate energy saving measures that target occupant behavior.
Keywords
Control-systems; Patterns; Offices; Lighting Control; Ultra-low Energy Building; Occupant Behavior; Building Simulation; Energy Consumption
Doescher, Mark P.; Lee, Chanam; Saelens, Brian E.; Lee, Chunkuen; Berke, Ethan M.; Adachi-mejia, Anna M.; Patterson, Davis G.; Moudon, Anne Vernez. (2017). Utilitarian and Recreational Walking Among Spanish- and English-Speaking Latino Adults in Micropolitan US Towns. Journal Of Immigrant & Minority Health, 19(2), 237 – 245.
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Abstract
Walking among Latinos in US Micropolitan towns may vary by language spoken. In 2011-2012, we collected telephone survey and built environment (BE) data from adults in six towns located within micropolitan counties from two states with sizable Latino populations. We performed mixed-effects logistic regression modeling to examine relationships between ethnicity-language group [Spanish-speaking Latinos (SSLs); English-speaking Latinos (ESLs); and English-speaking non-Latinos (ENLs)] and utilitarian walking and recreational walking, accounting for socio-demographic, lifestyle and BE characteristics. Low-income SSLs reported higher amounts of utilitarian walking than ENLs (p = 0.007), but utilitarian walking in this group decreased as income increased. SSLs reported lower amounts of recreational walking than ENLs (p = 0.004). ESL-ENL differences were not significant. We identified no statistically significant interactions between ethnicity-language group and BE characteristics. Approaches to increase walking in micropolitan towns with sizable SSL populations may need to account for this group's differences in walking behaviors.
Keywords
Walking; Confidence Intervals; Ecology; Ethnic Groups; Hispanic Americans; Income; Language & Languages; Metropolitan Areas; Population; Public Health; Recreation; Rural Conditions; White People; Logistic Regression Analysis; Socioeconomic Factors; Social Context; Body Mass Index; Acquisition Of Data; Physical Activity; Data Analysis Software; Odds Ratio; United States; Environment Design; Ethnicity; Rural Populations; Physical-activity; Built Environment; United-states; Postmenopausal Women; Acculturation; Risk; Transportation; Mortality; Health; Associations; Studies; Demographic Aspects; Telephone Surveys; Minority & Ethnic Groups; Physical Fitness; Low Income Groups; Urban Environments; Demographics; Language; Accounting; Statistical Analysis; Urban Areas; Towns; Populations; Adults; Lifestyles; Latin American Cultural Groups; Sociodemographics; Landscape Architecture; Population Growth; Pediatrics; Leisure; Health Care; Noncitizens; Preventive Medicine; United States--us
Nilon, Charles H.; Aronson, Myla F. J.; Cilliers, Sarel S.; Dobbs, Cynnamon; Frazee, Lauren J.; Goddard, Mark A.; O’Neill, Karen M.; Roberts, Debra; Stander, Emilie K.; Werner, Peter; Winter, Marten; Yocom, Ken P. (2017). Planning For The Future Of Urban Biodiversity: A Global Review Of City-scale Initiatives. Bioscience, 67(4), 331 – 341.
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Abstract
Cities represent considerable opportunities for forwarding global biodiversity and sustainability goals. We developed key attributes for conserving biodiversity and for ecosystem services that should be included in urban-planning documents and reviewed 135 plans from 40 cities globally. The most common attributes in city plans were goals for habitat conservation, air and water quality, cultural ecosystem services, and ecological connectivity. Few plans included quantitative targets. This lack of measurable targets may render plans unsuccessful for an actionable approach to local biodiversity conservation. Although most cities include both biodiversity and ecosystem services, each city tends to focus on one or the other. Comprehensive planning for biodiversity should include the full range of attributes identified, but few cities do this, and the majority that do are mandated by local, regional, or federal governments to plan specifically for biodiversity conservation. This research provides planning recommendations for protecting urban biodiversity based on ecological knowledge.
Keywords
Sustainability; Urban Planning; Urban Biodiversity; Urban Ecology (biology); Water Quality; Air Quality; Biodiversity Conservation; Ecosystem Services; Governance; Policy Regulation; Green Infrastructure; Climate-change; Human Health; Cities; Opportunities; Metaanalysis; Framework; Richness