Visionary management

The study describes a futures-oriented leadership process called visionary management as developed in the Finland Futures Research Centre and experienced successfully with several medium-sized companies in the 1990s. It is regarded as an addition to the advanced management processes aimed at making good business decisions. The aim of the visionary process is to create new business ideas for the company in the form of a vision. The visionary process enriches the strategic management of the company by motivating key persons to work jointly as a creative team for longer-term success. It starts from finding a common understanding of the future business situation, and discovers the resources and options available to the company. It ends up with a vision, a synthesis of the common understanding of success and the will to accomplish it. Tools and approaches applied in this communication process are presented. Inside the company the vision becomes an empowering means for directing the future course of the company, and it is an effective means to communicate the aims of the company and attract external interest and support. The examples in the article represent real cases with the kind permission of the companies involved

The Nature of biodesigned systems: Directions for HCI

The nascent field of biodesign uses the biological affordances of organisms to address some user need. These can range from the development of novel materials, which the designer actively investigates, to applications of synthetic biology or the creation of bio-digital hybrid systems. Within biodesign there is a question for interaction design: what will interactive systems look like in a guided and grown environment, rather than a built environment? In this workshop, we will explore new technologies that rely on symbiotic relationships between the user and organisms that participate in interactive systems. The goal of this workshop is to engage the interaction design community in exploring new aspects of designing for living computational systems

Preterm birth associated with maternal fine particulate matter exposure : A global, regional and national assessment

Reduction of preterm births (< 37 completed weeks of gestation) would substantially reduce neonatal and infant mortality, and deleterious health effects in survivors. Maternal fine particulate matter (PM2.5) exposure has been identified as a possible risk factor contributing to preterm birth. The aim of this study was to produce the first estimates of ambient PM2.5-associated preterm births for 183 individual countries and globally. To do this, national, population-weighted, annual average ambient PM2.5 concentration, preterm birth rate and number of livebirths were combined to calculate the number of PM2.5-associated preterm births in 2010 for 183 countries. Uncertainty was quantified using Monte-Carlo simulations, and analyses were undertaken to investigate the sensitivity of PM2.5-associated preterm birth estimates to assumptions about the shape of the concentration-response function at low and high PM2.5 exposures, inclusion of provider-initiated preterm births, and exposure to indoor air pollution. Globally, in 2010, the number of PM2.5-associated preterm births was estimated as 2.7 million (1.8–3.5 million, 18% (12–24%) of total preterm births globally) with a low concentration cut-off (LCC) set at 10 μg m− 3, and 3.4 million (2.4–4.2 million, 23% (16–28%)) with a LCC of 4.3 μg m− 3. South and East Asia, North Africa/Middle East and West sub-Saharan Africa had the largest contribution to the global total, and the largest percentage of preterm births associated with PM2.5. Sensitivity analyses showed that PM2.5-associated preterm birth estimates were 24% lower when provider-initiated preterm births were excluded, 38–51% lower when risk was confined to the PM2.5 exposure range in the studies used to derive the effect estimate, and 56% lower when mothers who live in households that cook with solid fuels (and whose personal PM2.5 exposure is likely dominated by indoor air pollution) were excluded. The concentration-response function applied here derives from a meta-analysis of studies, most of which were conducted in the US and Europe, and its application to the areas of the world where we estimate the greatest effects on preterm births remains uncertain. Nevertheless, the substantial percentage of preterm births estimated to be associated with anthropogenic PM2.5 (18% (13%–24%) of total preterm births globally) indicates that reduction of maternal PM2.5 exposure through emission reduction strategies should be considered alongside mitigation of other risk factors associated with preterm births

A systematic review of the physical health impacts from non-occupational exposure to wildfire smoke

Background: Climate change is likely to increase the threat of wildfires, and little is known about how wildfires affect health in exposed communities. A better understanding of the impacts of the resulting air pollution has important public health implications for the present day and the future. Method: We performed a systematic search to identify peer-reviewed scientific studies published since 1986 regarding impacts of wildfire smoke on health in exposed communities. We reviewed and synthesized the state of science of this issue including methods to estimate exposure, and identified limitations in current research. Results: We identified 61 epidemiological studies linking wildfire and human health in communities. The U.S. and Australia were the most frequently studied countries (18 studies on the U.S., 15 on Australia). Geographic scales ranged from a single small city (population about 55,000) to the entire globe. Most studies focused on areas close to fire events. Exposure was most commonly assessed with stationary air pollutant monitors (35 of 61 studies). Other methods included using satellite remote sensing and measurements from air samples collected during fires. Most studies compared risk of health outcomes between 1) periods with no fire events and periods during or after fire events, or 2) regions affected by wildfire smoke and unaffected regions. Daily pollution levels during or after wildfire in most studies exceeded U.S. EPA regulations. Levels of PM10, the most frequently studied pollutant, were 1.2 to 10 times higher due to wildfire smoke compared to non-fire periods and/or locations. Respiratory disease was the most frequently studied health condition, and had the most consistent results. Over 90% of these 45 studies reported that wildfire smoke was significantly associated with risk of respiratory morbidity.Conclusion: Exposure measurement is a key challenge in current literature on wildfire and human health. A limitation is the difficulty of estimating pollution specific to wildfires. New methods are needed to separate air pollution levels of wildfires from those from ambient sources, such as transportation. The majority of studies found that wildfire smoke was associated with increased risk of respiratory and cardiovascular diseases. Children, the elderly and those with underlying chronic diseases appear to be susceptible. More studies on mortality and cardiovascular morbidity are needed. Further exploration with new methods could help ascertain the public health impacts of wildfires under climate change and guide mitigation policies

Personal exposure monitoring of PM2.5 in indoor and outdoor microenvironments

Copyright © 2014. Published by Elsevier B.V. Open Access funded by Natural Environment Research CouncilPeer reviewedPublisher PD

Advanced strategic thinking: visionary management

siirretty Doriast

Monitoring Particulate Matter with Commodity Hardware

Health effects attributed to outdoor fine particulate matter (PM 2.5) rank it among the risk factors with the highest health burdens in the world, annually accounting for over 3.2 million premature deaths and over 76 million lost disability-adjusted life years. Existing PM2.5 monitoring infrastructure cannot, however, be used to resolve variations in ambient PM2.5 concentrations with adequate spatial and temporal density, or with adequate coverage of human time-activity patterns, such that the needs of modern exposure science and control can be met. Small, inexpensive, and portable devices, relying on newly available off-the-shelf sensors, may facilitate the creation of PM2.5 datasets with improved resolution and coverage, especially if many such devices can be deployed concurrently with low system cost. Datasets generated with such technology could be used to overcome many important problems associated with exposure misclassification in air pollution epidemiology. Chapter 2 presents an epidemiological study of PM2.5 that used data from ambient monitoring stations in the Los Angeles basin to observe a decrease of 6.1 g (95% CI: 3.5, 8.7) in population mean birthweight following in utero exposure to the Southern California wildfires of 2003, but was otherwise limited by the sparsity of the empirical basis for exposure assessment. Chapter 3 demonstrates technical potential for remedying PM2.5 monitoring deficiencies, beginning with the generation of low-cost yet useful estimates of hourly and daily PM2.5 concentrations at a regulatory monitoring site. The context (an urban neighborhood proximate to a major goods-movement corridor) and the method (an off-the-shelf sensor costing approximately USD $10, combined with other low-cost, open-source, readily available hardware) were selected to have special significance among researchers and practitioners affiliated with contemporary communities of practice in public health and citizen science. As operationalized by correlation with 1h data from a Federal Equivalent Method (FEM) β-attenuation data, prototype instruments performed as well as commercially available equipment costing considerably more, and as well as another reference instrument under similar conditions at the same timescale (R2 = 0.6). Correlations were stronger when 24 h integrating times were used instead (R2 = 0.72). Chapter 4 replicates and extends the results of Chapter 3, showing that similar calibrations may be reasonably exchangeable between near-roadway and background monitoring sites. Chapter 4 also employs triplicate sensors to obtain data consistent with near-field (< 50 m) observations of plumes from a major highway (I-880). At 1 minute timescales, maximum PM2.5 concentrations on the order of 100 μg m–3 to 200 μg m–3 were observed, commensurate with the magnitude of plumes from wildfires on longer timescales, as well as the magnitude of plumes that might be expected near other major highways on the same timescale. Finally, Chapter 4 quantifies variance among calibration parameters for a large sample of the sensors, as well as the error associated with the remote transfer of calibrations between two sufficiently large sets (± 10 % for n = 12). These findings suggest that datasets generated with similar sensors could also improve upstream scientific understandings of fluxes resulting from indoor and outdoor emissions, atmospheric transformations, and transport, and may also facilitate timely and empirical verification of interventions to reduce emissions and exposures, in many important contexts (e.g., the provision of improved cookstoves; congestion pricing; mitigation policies attached to infill development; etc.). They also demonstrate that calibrations against continuous reference monitoring equipment could be remotely transferred, within practical tolerances, to reasonably sized and adequately resourced participatory monitoring campaigns, with minimal risk of disruption to existing monitoring infrastructure (i.e., established monitoring sites). Given a collaborator with a short window of access to a reference monitoring site, this would overcome a nominally important barrier associated with non-gravimetric, in-situ calibration of continuous PM2.5 monitors. Progressive and disruptive prospects linked to a proliferation of comparable sensing technologies based on commodity hardware are discussed in Chapter 5