Aeroallergens in Canada: Distribution, Public Health Impacts, and Opportunities for Prevention

Aeroallergens occur naturally in the environment and are widely dispersed across Canada, yet their public health implications are not well-understood. This review intends to provide a scientific and public health-oriented perspective on aeroallergens in Canada: their distribution, health impacts, and new developments including the effects of climate change and the potential role of aeroallergens in the development of allergies and asthma. The review also describes anthropogenic effects on plant distribution and diversity, and how aeroallergens interact with other environmental elements, such as air pollution and weather events. Increased understanding of the relationships between aeroallergens and health will enhance our ability to provide accurate information, improve preventive measures and provide timely treatments for affected populations

The Joint Damping Experiment (JDX)

The Joint Damping Experiment (JDX), flown on the Shuttle STS-69 Mission, is designed to measure the influence of gravity on the structural damping of a high precision three bay truss. Principal objectives are: (1) Measure vibration damping of a small-scale, pinjointed truss to determine how pin gaps give rise to gravity-dependent damping rates; (2) Evaluate the applicability of ground and low-g aircraft tests for predicting on-orbit behavior; and (3) Evaluate the ability of current nonlinear finite element codes to model the dynamic behavior of the truss. Damping of the truss was inferred from 'Twang' tests that involve plucking the truss structure and recording the decay of the oscillations. Results are summarized as follows. (1) Damping, rates can change by a factor of 3 to 8 through changing the truss orientation; (2) The addition of a few pinned joints to a truss structure can increase the damping by a factor as high as 30; (3) Damping is amplitude dependent; (4) As gravity induced preloads become large (truss long axis perpendicular to gravity vector) the damping is similar to non-pinjointed truss; (5) Impacting in joints drives higher modes in structure; (6) The torsion mode disappears if gravity induced preloads are low

Overestimate of Committed Warming

Palaeoclimate variations are an essential component in constraining future projections of climate change as a function of increasing anthropogenic greenhouse gases. The Earth System Sensitivity (ESS) describes the multi-millennial response of Earth (in terms of global mean temperature) to a doubling of CO2 concentrations. A recent study used a correlation of inferred temperatures and radiative forcing from greenhouse gases over the past 800,000 years to estimate the ESS from present day CO2 is about 9 degrees C, and to imply a long-term commitment of 3-7 degrees C even if greenhouse gas levels remain at present-day concentrations. However, we demonstrate that the methodology of ref. 2 does not reliably estimate the ESS in the presence of orbital forcing of ice age cycles and therefore conclude that the inferred present-day committed warming is considerably overestimated

Lodgepole pine management guidelines for land managers in the wildland-urban interface

As a consequence of the current mountain pine beetle epidemic, many landowners and land managers are concerned about how to actively manage lodgepole pine stands. The following guidelines cover treating the dead standing trees killed by the insects, protecting homes and communities from wildfire, and ensuring that the future forest is better structured to prevent widespread mortality from insect epidemics and wildfire

Comparison of Questionnaire Responses with Biomarkers of Tobacco Smoke Exposure in A Canadian Birth Cohort at Three Months of Age

Background Exposure to tobacco smoke increases the risk for several adverse health effects in children including wheeze, asthma, and asthma exacerbation. Accurately assessing tobacco smoke exposure is important for understanding and preventing these health effects. Questionnaires are a flexible and relatively inexpensive method of assessing exposure, but biomarkers of tobacco smoke exposure are considered more accurate. We developed questionnaire-based exposure models predicting urinary levels of biomarkers cotinine and trans-3’-hydroxycotinine (3HC) (metabolites of nicotine) in 3-month old infants using parent-reported questionnaire responses about tobacco smoke exposure from the Canadian Healthy Infant Longitudinal Development (CHILD) Study. Methods We used a manual model building process to build multiple linear regression models predicting urinary concentrations of cotinine, 3HC, and the sum of cotinine and 3HC on a molar basis (Cot+3HC) for 987, 1003, and 983 infants, respectively. Questions were included on the infant’s exposure assessed at 3 months of age and tobacco smoke odour in the home. We also included questions on maternal smoking status and history, passive exposure, and family socio-economic status assessed during pregnancy, as potential indirect measures of the infant’s exposure at 3 months. Adjusted R2 values were maximized in the final models. Results During pregnancy, the prevalence of maternal smoking was 2.4 %, and 115 (11.4 %) mothers reported smoking by at least 1 person at home. Of the 144 (14.3 %) infants whose mothers reported that smoking occurred at home when their child was 3 months, 129 (89.6%) and 136 (94.4%) had cotinine and 3HC levels above the detection limit (0.03 ng/mL), respectively. Of the 811 infants who had no parent-reported exposure at 3 months, 538 (66.3%) and 715 (88.2%) had detectable cotinine and 3HC levels, respectively. After correcting for urine dilution, the geometric mean levels were 0.085 ng/mL for cotinine, 0.20 ng/mL for 3HC, and 1.62 picomole/mL for Cot+3HC. The final questionnaire models explained 43.4%, 41.0%, and 42.9% of the variance in cotinine, 3HC, and Cot+3HC levels, respectively. Conclusions Our results indicate that exposure of these infants to tobacco smoke is not completely captured by questionnaires, suggesting that exposure assessment could be improved by using a combination of biomarker and questionnaire methods. Though more detectable, the inclusion of 3HC did not increase the ability of the questionnaires to explain variance in metabolite levels, but 3HC may be important since the ratio of 3HC to cotinine can be used to quantify the rate of nicotine metabolism and variation within population

City Know-How

Human health and planetary health are influenced by city lifestyles, city leadership, and city development. For both, worrying trends are leading to increasing concern and it is imperative that human health and environmental impacts become core foci in urban policy. Changing trajectory will require concerted action; the journal Cities & Health is dedicated to supporting the flow of knowledge, in all directions, to help make this happen. We wish to foster communication between researchers, practitioners, policy-makers, communities, and decision-makers in cities. This is the purpose of the City Know-how section of the journal. ‘Research for city practice’ disseminates lessons from research by explaining key messages for city leaders, communities, and the professions involved in city policy and practice. ‘City shorts’ provide glimpses of what is being attempted or achieved ‘on the ground’ and ’case studies’ are where you will find evaluations of interventions. Last, ‘Commentary and debate’ extends conversations we are having to develop and mobilize much needed new thinking. Join in these conversations. In order to strengthen the community of interest, we would like to include many and varied voices, including those from younger practitioners and researchers who are supporting health and health equity in everyday urban lives

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2

Motion-activated wildlife cameras (or “camera traps”) are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the “species model,” and one that determines if an image is empty or if it contains an animal, the “empty-animal model.” Our species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36%–91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91%–94% on out-of-sample datasets from different continents. Our software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths

Long-Term Exposure to Traffic-Related Air Pollution and Diabetes: A Systematic Review and Meta-Analysis

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population.Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022.Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO2 was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10 μg/m3), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10 μg/m3). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies.Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes