There are limited data on air quality parameters, including airborne particulate matter (PM) in residential green buildings, which are increasing in prevalence. Exposure to PM is associated with cardiovascular and pulmonary diseases, and since Americans spend almost 90% of their time indoors, residential exposures may substantially contribute to overall airborne PM exposure. Our objectives were to: (1) measure various PM fractions longitudinally in apartments in multi-family green buildings with natural (Building E) and mechanical (Building L) ventilation; (2) compare indoor and outdoor PM mass concentrations and their ratios (I/O) in these buildings, taking into account the effects of occupant behavior; and (3) evaluate the effect of green building designs and operations on indoor PM. We evaluated effects of ventilation, occupant behaviors, and overall building design on PM mass concentrations and I/O. Median PMTOTAL was higher in Building E (56 µg/m3) than in Building L (37 µg/m3); I/O was higher in Building E (1.3–2.0) than in Building L (0.5–0.8) for all particle size fractions. Our data show that the building design and occupant behaviors that either produce or dilute indoor PM (e.g., ventilation systems, combustion sources, and window operation) are important factors affecting residents’ exposure to PM in residential green buildings.

Objectives. Worldwide, over 200 million children are involved in child labor, with another 20 million children subjected to forced labor, leading to acute and chronic exposures resulting in safety and health (S&H) risks, plus removal from formal education and play. This review summarized S&H issues in child labor, including forced or indentured domestic labor as other sectors of child labor. Specifically, we focused on exposures leading to S&H risks. Methods. We used PubMed, Scopus, Science Direct, and Google Scholar. References were in English, published in 1990–2015, and included data focused on exposures and S&H concerns of child labor. Results. Seventy-six journal articles were identified, 67 met criteria, 57 focused on individual countries, and 10 focused on data from multiple countries (comparing 3–83 countries). Major themes of concern were physical exposures including ergonomic hazards, chemical exposure hazards, and missed education. Childhood labor, especially forced, exploitative labor, created a significant burden on child development, welfare, and S&H. Conclusions. More field researche data emphasizing longitudinal quantitative effects of exposures and S&H risks are needed. Findings warranted developing policies and educational interventions with proper monitoring and evaluation data collection, plus multiple governmental, international organization and global economic reform efforts, particularly in lower-income, less developed countries.

Several frameworks incorporate social and psychological elements of environmentally significant behaviour, and most assume cognitive and deliberate decision-making. Household energy consumption behaviours, however, span a spectrum from reasoned and deliberate to unplanned and automatic. The aim of this paper is to advance knowledge of reasoned and unplanned behaviours in the context of pro-environmental action. Using results of a survey administered to occupants of an urban residential green building, this study explores five household consumption behaviours and tests the hypothesis that unplanned behaviours will be poorly predicted by a reasoned, values-based behavioural framework. Using path analyses, variables in a values-based framework are used to predict surveyed behaviours. Findings indicate that behaviours hypothesized to be unplanned were not well predicted by the valuesbased framework. The framework successfully predicted what was hypothesized to be a fully reasoned behaviour. Three potential reasons are discussed for the lack of prediction of some behaviours. A deeper understanding of how unplanned, automatic or habitual behaviours intervene in conservation intentions can help policy-makers and building designers better respond to influences of occupant behaviour on building performance.

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This paper addresses the challenge of incorporating occupant behavior into building performance simulation models used during the design process-that is, before the actual occupants are known. It proposes the use of synthetic population data, an approach that is novel in building performance modeling although common in urban planning and public health. A simpler approach embodied in the ASHRAE Fundamentals volume is to report standard distributions of values for behavioral variables, assuming that parameters vary independently of one another when in fact many co-vary or are interdependent. An alternative approach calibrates models of occupant behavior against actual occupants in specific existing buildings, but this raises questions of transferability. Needed is a database of "generic" occupants that designers can use prospectively during the design process. This paper documents a process of combining disparate field studies of commercial buildings into a larger occupant behavior database and generating a statistically similar synthetic data set that can be shared without compromising confidentiality requirements associated with field studies. The synthetic data set successfully incorporates much of the covariance structure of the underlying field data and supports multivariate modeling. Its scope and structure necessarily serve the needs of the associated modeling framework. Cooperative and systematic sharing of data by field researchers is crucial for building large enough data sets to serve as a behaviorally-robust basis for building design.