How much e-waste is there in US basements and attics? Results from a national survey

The fate of used electronic products (e-waste) is of increasing concern because of their toxicity and the growing volume of e-waste. Addressing these concerns requires developing the recycling infrastructure, but good estimates of the volume of e-waste stored by US households are still unavailable. In this context, we make two contributions based on a national random survey of 2136 US households. First, we explain how much e-waste is stored by US households using count models. Significant explanatory variables include age, marital and employment status, ethnicity, household size, previous e-waste recycling behavior, and to some extent education, home ownership, and understanding the consequences of recycling, but neither income nor knowledge of e-waste recycling laws. Second, we estimate that on average, each US household has 4.1 small (≤10 pounds) and 2.4 large e-waste items in storage. Although these numbers are likely lower bounds, they are higher than recent US Environmental Protection Agency (EPA) estimates (based on narrower product categories). This suggests that the backlog of e-waste in the US is likely larger than generally believed; it calls for developing the recycling infrastructure but also for targeted recycling campaigns.     

The use of materials from demolition in construction

The author looks at economic and technical factors involved in the reuse of materials from demolition within the construction industry. Past experience in the use of such materials is reviewed and the results of a survey of the present usage of demolition materials in this country are presented. The prospects for increased utilisation are discussed in the light of the need to ensure the durability of building materials made from them.     

Convergence and emergence in organizations: An integrative framework and review

In reaction to the growing attention to connecting individual‐level and unit‐level constructs, we first briefly review emergence terminology and theories that address the dynamic process by which a higher‐level phenomenon emerges from lower‐level elements. Next, we review the extant theory and research on emergence and convergence in organization science using an organizing framework that simultaneously considers the content area of lower‐level elements, the emergent factors, and the target of the emergent property. In addition to organizing and bridging current literature on emergence and convergence, gaps of existing research and new directions for future research, including compilation and divergence, are identified. Copyright © 2015 John Wiley & Sons, Ltd.     

Evaluation of developmental metrics for utilization in a pediatric advanced automatic crash notification algorithm

Objective: Appropriate treatment at designated trauma centers (TCs) improves outcomes among injured children after motor vehicle crashes (MVCs). Advanced Automatic Crash Notification (AACN) has shown promise in improving triage to appropriate TCs. Pediatric-specific AACN algorithms have not yet been created. To create such an algorithm, it will be necessary to include some metric of development (age, height, or weight) as a covariate in the injury risk algorithm. This study sought to determine which marker of development should serve as a covariate in such an algorithm and to quantify injury risk at different levels of this metric.

Methods: A retrospective review of occupants age < 19 years within the MVC data set NASS-CDS 2000–2011 was performed. R² values of logistic regression models using age, height, or weight to predict 18 key injury types were compared to determine which metric should be used as a covariate in a pediatric AACN algorithm. Clinical judgment, literature review, and chi-square analysis were used to create groupings of the chosen metric that would discriminate injury patterns. Adjusted odds of particular injury types at the different levels of this metric were calculated from logistic regression while controlling for gender, vehicle velocity change (delta V), belted status (optimal, suboptimal, or unrestrained), and crash mode (rollover, rear, frontal, near-side, or far-side).

Results: NASS-CDS analysis produced 11,541 occupants age < 19 years with nonmissing data. Age, height, and weight were correlated with one another and with injury patterns. Age demonstrated the best predictive power in injury patterns and was categorized into bins of 0–4 years, 5–9 years, 10–14 years, and 15–18 years. Age was a significant predictor of all 18 injury types evaluated even when controlling for all other confounders and when controlling for age- and gender-specific body mass index (BMI) classifications. Adjusted odds of key injury types with respect to these age categorizations revealed that younger children were at increased odds of sustaining Abbreviated Injury Scale (AIS) 2+ and 3+ head injuries and AIS 3+ spinal injuries, whereas older children were at increased odds of sustaining thoracic fractures, AIS 3+ abdominal injuries, and AIS 2+ upper and lower extremity injuries.

Conclusions: The injury patterns observed across developmental metrics in this study mirror those previously described among children with blunt trauma. This study identifies age as the metric best suited for use in a pediatric AACN algorithm and utilizes 12 years of data to provide quantifiable risks of particular injuries at different levels of this metric. This risk quantification will have important predictive purposes in a pediatric-specific AACN algorithm.     

The Truth About Science: A middle school curriculum teaching the scientific method and data analysis in an ecology context

The Truth About Science is a 40-lesson middle school curriculum module that teaches the process of scientific research, integrating mathematics and science concepts and skills. The goal of the curriculum is to teach students to think systematically and statistically about science inquiry. Students participate in each step of the scientific inquiry process, from asking testable research questions, designing unbiased experiments, and collecting their own data, to analyzing these data via graphical representations and statistical summaries, and communicating their research results as both poster and oral presentations. While the necessary statistical skills depend on difficult and abstract mathematical concepts, middle school students have been successful in applying them to their own research projects. The curriculum meets local and national standards in science and mathematics education and fills a gap in available educational materials. It has been piloted and revised through multiple iterations and published by the National Science Teachers Association Press. Feedback from teachers and students has been extremely positive.     

Random denominators and the analysis of ratio data

Ratio data, observations in which one random value is divided by another random value, present unique analytical challenges. The best statistical technique varies depending on the unit on which the inference is based. We present three environmental case studies where ratios are used to compare two groups, and we provide three parametric models from which to simulate ratio data. The models describe situations in which (1) the numerator variance and mean are proportional to the denominator, (2) the numerator mean is proportional to the denominator but its variance is proportional to a quadratic function of the denominator and (3) the numerator and denominator are independent. We compared standard approaches for drawing inference about differences between two distributions of ratios: t-tests, t-tests with transformations, permutation tests, the Wilcoxon rank test, and ANCOVA-based tests. Comparisons between tests were based both on achieving the specified alpha-level and on statistical power. The tests performed comparably with a few notable exceptions. We developed simple guidelines for choosing a test based on the unit of inference and relationship between the numerator and denominator.     

Lessons learned from applying adaptation pathways in flood risk management and challenges for the further development of this approach

Worldwide, an increase in flood damage is observed. Governments are looking for effective ways to protect lives, buildings, and infrastructure. At the same time, a large investment gap seems to exist—a big difference between what should necessarily be done to curb the increase in damage and what is actually being done. Decision-makers involved in climate adaptation are facing fundamental (so-called deep) uncertainties. In the course of time, the scientific community has developed a wide range of different approaches for dealing with these uncertainties. One of these approaches, adaptation pathways, is gaining traction as a way of framing and informing climate adaptation. But research shows that “very little work has been done to evaluate the current use of adaptation pathways and its utility to practitioners and decision makers” (Lin et al. 2017, p. 387). With this paper, the authors, as action researchers and practitioners involved in two of the world’s largest real-life applications of this approach in flood risk management, aim to contribute to filling in that gap. Analysis of the experience in the United Kingdom and the Netherlands in long-term planning in flood risk management shows that the adaptation pathways approach is effective in keeping decision processes going forward, to the final approval of a long-term plan, and helps increase awareness about uncertainties. It contributes to political support for keeping long-term options open and motivates decision-makers to modify their plans to better accommodate future conditions. When it comes to implementing the plans, there are still some major challenges, yet to be addressed, amongst others: the timely detection of tipping points in situations with large natural variability, the inclusion of measures that prepare for a switch to transformational strategies, and the retention of commitment of regional and local authorities, non government organizations, and the private sector, to climate adaptation as national policies move from blueprint planning to adaptive plans. In delivering this feedback, the authors hope to motivate the scientific community to take on these challenges.     

The Influence of Varying Planktonic and Periphytic Algal Biomass On Exposure to Polychlorinated Biphenyls in Mesocosms

Algal populations, either suspended in the water column (planktonic) or present on the walls of an enclosure (periphytic), develop differently depending upon the physical scale of the system. This study determined whether these variations altered the speciation and therefore exposure of polychlorinated biphenyls (PCBs) in estuarine mesocosms. Exposure was defined as the fraction of applied contaminant taken up by plankton after two hours. Using a three phase equilibrium model, the partitioning of a suite of PCBs within variously-sized mesocosms was predicted using laboratory derived distribution coefficients and measured levels of planktonic and periphytic algal biomass. in mesocosms having large wall surface area to volume ratios, sorption of hydrophobic PCBs to periphyton significantly decreased contaminant exposure. However, within the range of planktonic algal biomasses observed in this study, the regulation of PCB exposure was relatively invariant between variously-sized mesocosms. to minimize sorption of hydrophobic organic contaminants (HOCs) to periphyton and reduce artefacts inherent with this partitioning, we suggest using mesocosms with low wall surface area to volume ratios (less than or equal to 1). in addition, periphytic biomass should be quantified regularly and a three-phase equilibrium approach used to predict the actual exposure concentrations.     

Ecological Responses to Trout Habitat Rehabilitation in a Northern Michigan Stream

Monitoring of stream restoration projects is often limited and success often focuses on a single taxon (e.g., salmonids), even though other aspects of stream structure and function may also respond to restoration activities. The Ottawa National Forest (ONF), Michigan, conducted a site-specific trout habitat improvement to enhance the trout fishery in Cook’s Run, a 3^rd-order stream that the ONF determined was negatively affected by past logging. Our objectives were to determine if the habitat improvement increased trout abundances and enhanced other ecological variables (overall habitat quality, organic matter retention, seston concentration, periphyton abundance, sediment organic matter content, and macroinvertebrate abundance and diversity) following rehabilitation. The addition of skybooms (underbank cover structures) and k-dams (pool-creating structures) increased the relative abundance of harvestable trout (>25 cm in total length) as intended but not overall trout abundances. Both rehabilitation techniques also increased maximum channel depth and organic matter retention, but only k-dams increased overall habitat quality. Neither approach significantly affected other ecological variables. The modest ecological response to this habitat improvement likely occurred because the system was not severely degraded beforehand, and thus small, local changes in habitat did not measurably affect most physical and ecological variables measured. However, increases in habitat volume and in organic matter retention may enhance stream biota in the long term.