Gatti, U.; Migliaccio, G.; Bogus, S.M.; Priyadarshini, S.; Scharrer, A. (2013). Using Workforce’s Physiological Strain Monitoring to Enhance Social Sustainability of Construction. Journal Of Architectural Engineering, 19(3), 179 – 85.
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Abstract
Sustainability is often described in terms of the triple bottom line, which refers to its environmental, economic, and social dimensions. However, the economic and environmental impacts of decisions have been easier to determine than have been the social impacts. One area of social sustainability that is particularly applicable to construction projects is that of construction workforce safety and well-being. This is a critical part of sustainability, and a socially sustainable construction industry needs to consider the safety and well-being of construction workers. However, construction activities are generally physically demanding and performed in harsh environments. Monitoring workers' physical strain may be an important step toward enhancing the social sustainability of construction. Recently introduced physiological status monitors (PSMs) have overcome the past limitations, allowing physical strain to be monitored without hindering workers' activities. Three commercially available PSMs have been selected and tested to assess their reliability in monitoring a construction workforce during dynamic activities. The results show that two of the PSMs are suitable candidates for monitoring the physiological conditions of construction workers. A survey was also conducted among industry practitioners to gain insight into industry needs and challenges for physical strain monitoring.
Keywords
Construction Industry; Environmental Factors; Labour Resources; Occupational Safety; Socio-economic Effects; Sustainable Development; Workforce Physiological Strain Monitoring; Social Sustainability; Socioeconomic Impacts; Environmental Impacts; Social Impacts; Construction Projects; Construction Workforce Safety; Physical Strain
Hong, Jinhyun; Shen, Qing. (2013). Residential Density and Transportation Emissions: Examining the Connection by Addressing Spatial Autocorrelation and Self-Selection. Transportation Research Part D-transport And Environment, 22, 75 – 79.
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Abstract
This paper examines the effect of residential density on CO2 equivalent from automobile using more specific emission factors based on vehicle and trip characteristics, and by addressing problems of spatial autocorrelation and self-selection. Drawing on the 2006 Puget Sound Regional Council Household Activity Survey data, the 2005 parcel and building database, the 2000 US Census data, and emission factors estimated using the Motor Vehicle Emission Simulator, we analyze the influence of residential density on road-based transportation emissions. In addition, a Bayesian multilevel model with spatial random effects and instrumental variables is employed to control for spatial autocorrelation and self-selection. The results indicate that the effect of residential density on transportation emissions is influenced by spatial correlation and self-selection. Our results still show, however, that increasing residential density leads to a significant reduction in transportation emissions. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords
Urban Form; Travel; Transportation Emissions; Residential Density; Confounding By Location; Self-selection
Kang, Bumjoon; Moudon, Anne V.; Hurvitz, Philip M.; Reichley, Lucas; Saelens, Brian E. (2013). Walking Objectively Measured: Classifying Accelerometer Data with GPS and Travel Diaries. Medicine & Science In Sports & Exercise, 45(7), 1419 – 1428.
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Abstract
Purpose: This study developed and tested an algorithm to classify accelerometer data as walking or nonwalking using either GPS or travel diary data within a large sample of adults under free-living conditions. Methods: Participants wore an accelerometer and a GPS unit and concurrently completed a travel diary for seven consecutive days. Physical activity (PA) bouts were identified using accelerometry count sequences. PA bouts were then classified as walking or nonwalking based on a decision-tree algorithm consisting of seven classification scenarios. Algorithm reliability was examined relative to two independent analysts' classification of a 100-bout verification sample. The algorithm was then applied to the entire set of PA bouts. Results: The 706 participants' (mean age = 51 yr, 62% female, 80% non-Hispanic white, 70% college graduate or higher) yielded 4702 person-days of data and had a total of 13,971 PA bouts. The algorithm showed a mean agreement of 95% with the independent analysts. It classified PA into 8170 walking bouts (58.5 %) and 5337 nonwalking bouts (38.2%); 464 bouts (3.3%) were not classified for lack of GPS and diary data. Nearly 70% of the walking bouts and 68% of the nonwalking bouts were classified using only the objective accelerometer and GPS data. Travel diary data helped classify 30% of all bouts with no GPS data. The mean + SD duration of PA bouts classified as walking was 15.2 + 12.9 min. On average, participants had 1.7 walking bouts and 25.4 total walking minutes per day. Conclusions: GPS and travel diary information can be helpful in classifying most accelerometer-derived PA bouts into walking or nonwalking behavior.
Keywords
Walking; Algorithms; Decision Trees; Geographic Information Systems; Research Funding; Travel; Accelerometry; Diary (literary Form); Descriptive Statistics; Algorithm; Classification; Physical Activity; Walk Trip; Global Positioning Systems; Physical-activity; Environment; Behaviors; Validity; Location
Kim, Yong-Woo; Azari-N, Rahman; Yi, June-Seong; Bae, Jinwoo. (2013). Environmental Impacts Comparison between On-site vs. Prefabricated Just-in-Time (Prefab-JIT) Rebar Supply in Construction Projects. Journal Of Civil Engineering And Management, 19(5), 647 – 655.
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Abstract
In the on-site rebar delivery system, as the common method of rebar supply in the construction industry, reinforced steel bars are delivered in large batches from supplier's facilities through contractor's warehouse to the construction site. Rebars are then fabricated on-site and installed after assembly. In the new delivery system, called prefabrication Just-In-Time (prefab-JIT) system, the off-site cut and bend along with frequent rebar delivery to the site are applied in order to improve the process and increase its efficiency. The main objective of this paper is to assess and compare the environmental impacts resulting from the air emissions associated with the two rebar delivery systems in a case study construction project. Environmental impact categories of interest include global warming, acidification, eutrophication, and smog formation. A process-based cradle-to-gate life cycle assessment methodology is applied to perform the analysis. The results show that the prefab-JIT rebar delivery system causes less contribution to all mentioned environmental impact categories compared with a traditional on-site delivery system.
Keywords
Environmental Impact Analysis; Comparative Studies; Microfabrication; Construction Industry; Reinforcing Bars; Contractors; Product Life Cycle; Environmental Impacts; Life Cycle; On-site Rebar Delivery System; Prefab-jit; Bars; Contracts; Global Warming; Just-in-time; Prefabricated Construction; Product Life Cycle Management; Project Management; Rebar; Steel; Warehousing; Waste Reduction; Smog Formation; Eutrophication; Acidification; Air Emissions; Prefab-jit System; Construction Site; Contractors Warehouse; Reinforced Steel Bars; Construction Projects; Prefabricated Just-in-time Rebar Supply; Environmental Impacts Comparison; Process-based Cradle-to-gate Life Cycle Assessment Methodology; Energy; Products; Wood
Lee, Namhun; Dossick, Carrie S.; Foley, Sean P. (2013). Guideline for Building Information Modeling in Construction Engineering and Management Education. Journal Of Professional Issues In Engineering Education And Practice, 139(4), 266 – 274.
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Keywords
Buildings (structures); Computer Aided Instruction; Construction Industry; Educational Courses; Management Education; Structural Engineering Computing; Building Information Modeling; Construction Engineering And Management Education; Cem Education; Bim; Cem Curriculum
Maliszewski, Paul; Larson, Elisabeth; Perrings, Charles. (2013). Valuing the Reliability of the Electrical Power Infrastructure: A Two-Stage Hedonic Approach. Urban Studies, 50(1), 72 – 87.
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Abstract
The reliability of electrical power supply is amongst the conditions that inform house purchase decisions in all urban areas. Reliability depends in part on the conditions of the power generation and distribution infrastructures involved, and in part on environmental conditions. Its value to homeowners may be capitalised into the value of the house. In this paper, a hedonic pricing approach is used to estimate the capitalised value of the reliability offered by distribution infrastructures and the environmental conditions with which they interact in Phoenix, Arizona. A first stage estimates the impact of infrastructure and environmental conditions on reliability. In a second stage, the capitalised value of reliability from the marginal willingness to pay for reliability revealed by house purchase decisions is estimated and used to infer the value of both infrastructural characteristics and environmental conditions.
Keywords
Willingness-to-pay; Residential Property-values; Economic Valuation; Choice Experiment; Urban Wetlands; Air-quality; Benefits; Identifiability; Specification; Determinants