Concentrations of 54 volatile organic compounds (VOCs) and ventilation rates were measured in four new manufactured houses over 2-9.5 months following installation and in seven new site-built houses 1-2 months after completion. The houses were in four projects located in hot-humid and mixed-humid climates. They were finished and operational, but unoccupied. Ventilation rates ranged from 0.14-0.78 h-1. Several of the site-built houses had ventilation rates below the ASHRAE recommended value. In both manufactured and site-built houses, the predominant airborne compounds were alpha-pinene, formaldehyde, hexanal, and acetic acid. Formaldehyde concentrations were below or near 50 ppb with a geometric mean value for all houses of 40 ppb. Similarities in the types of VOCs and in VOC concentrations indicated that indoor air quality in the houses was impacted by the same or similar sources. Major identified sources included plywood flooring, latex paint and sheet vinyl flooring. One site-built house was operated at ventilation rates of 0.14 and 0.32 h-1. VOC emission rates calculated at the two conditions agreed within +/- 10% for the most volatile compounds. Generally, the ratios of emission rates at the low and high ventilation rates decreased with decreasing compound volatility. Changes in VOC emission rates in the manufactured houses over 2-9.5 months after installation varied by compound. Only several compounds showed a consistent decrease in emission rate over this period.

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SummaryThis study examined a range of factors influencing energy consumption in households that had participated in residential energy-efficiency upgrades. The study was funded under a subcontract with the U.S. Department of Energy's Pacific Northwest National Laboratory and was conducted by faculty and staff of Portland State University Center for Urban Studies and Department of Economics. This work was made possible through the assistance and support of the Energy Trust of Oregon (ETO), whose residential energy-efficiency programs provided the population from which the sample cases were drawn. All households in the study had participated in the ETO Home Performance with Energy Star (HPwES) program. A number of these had concurrently pursued measures through other ETO programs.Post-retrofit energy outcomes are rarely investigated on a house-by-house basis. Rather, aggregate changes are ordinarily the focus of program impact evaluations, with deviation from aggregate expectations chalked up to measurement error, the vagaries of weather, and idiosyncrasies of occupants. However, understanding how homes perform post-retrofit on an individual basis can give important insights to increase energy savings at the participant and the programmatic level. Taking a more disaggregated approach, this study analyzed energy consumption data from before and after the retrofit activity and made comparisons with engineering estimates for the upgrades, to identify households that performed differently from what may have been expected based on the estimates. A statistical analysis using hierarchal linear models, which accounted for weather variations, was performed looking separately at gas and electrical use during the periods before and after upgrades took place. A more straightforward comparison of billing data for 12-month periods before and after the intervention was also performed, yielding the majority of the cases examined. The latter approach allowed total energy use and costs to be assessed but did not account for weather variation.From this statistical analysis, 18 study participants were selected and interviewed. The participants completed an in-home interview covering a range of topics, including changes in occupancy and additional changes to the homes that may have affected energy use. The goal of the interviews was to identify factors that may have contributed to unusual energy performance. These factors were identified by their frequency of occurrence in outperforming or underperforming homes, or simply by identifying factors that had the largest impact on overall savings. The motivations and levels of satisfaction with the outcomes of the upgrades were covered in detail, and behaviors pertaining to thermal control, lighting, water, and appliance use were extensively discussed.Most of the cases studied achieved substantial energy savings, although it was more common for the projected savings to be greater than the demonstrated savings. Two factors that played a very large role in savings variation were 1) changes in...

Just‐in‐time (JIT) manufacturing systems have attracted the attention of industries all over the world. The perceptible impact of JIT lies in attaining the far‐reaching productivity and quality standards. Attempts have been made to examine JIT, its benefits and elements for their feasibility in Indian industries. Despite the profound interest of prospective managers and researchers, the extent of JIT implementation in Indian industries so far is not satisfactory. The real challenge before Indian managers is to establish priorities among potential JIT techniques to achieve best possible advantage of JIT implementation in Indian industries. This paper attempts to evaluate the relative importance of decision attributes in the hierarchy for a case situation given herein. The present work describes a multi‐attribute decision model using analytical hierarchy process for the justification of JIT for Indian industries.

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