Respiratory Health Effects of Exposure to Low-NOx Unflued Gas Heaters in the Classroom: A Double-Blind, Cluster-Randomized, Crossover Study

There are long-standing concerns about adverse effects of gas appliances on respiratory health. However, the potential adverse effect of low-NOx (nitrogen oxide) unflued gas heaters on children’s health has not been assessed. Our goal was to compare the respiratory health effects and air quality consequences of exposure to low-NOx unflued gas heaters with exposure to non–indoor-air-emitting flued gas heaters in school classrooms. We conducted a double-blind, cluster-randomized, crossover study in 400 primary school students attending 22 schools in New South Wales, Australia. Children measured their lung function and recorded symptoms and medication use twice daily. Nitrogen dioxide (NO₂) and formaldehyde concentrations were measured in classrooms using passive diffusion badges.NO₂ concentrations were, on average, 1.8 times higher [95% confidence interval (CI), 1.6–2.1] and formaldehyde concentrations were, on average, 9.4 ppb higher (95% CI, 5.7–13.1) during exposure to unflued gas versus flued gas heaters. Exposure to the unflued gas heaters was associated with increased cough reported in the evening [odds ratio (OR) = 1.16; 95% CI, 1.01–1.34] and wheeze reported in the morning (OR = 1.38; 95% CI, 1.04–1.83). The association with wheeze was greater in atopic subjects. There was no evidence of an adverse effect on lung function. We conclude that classroom exposure to low-NOx unflued gas heaters causes increased respiratory symptoms, particularly in atopic children, but is not associated with significant decrements in lung function. It is important to seek alternative sources of heating that do not have adverse effects on health

World Opportunity Week: Dan Aust & Nathan Vogel

Dan Aust and Nathan Vogel speak at Taylor University about their work in Africa for World Opportunities Week

Pulmonary Oxidative Stress, Inflammation and Cancer: Respirable Particulate Matter, Fibrous Dusts and Ozone as Major Causes of Lung Carcinogenesis through Reactive Oxygen Species Mechanisms

Reactive oxygen or nitrogen species (ROS, RNS) and oxidative stress in the respiratory system increase the production of mediators of pulmonary inflammation and initiate or promote mechanisms of carcinogenesis. The lungs are exposed daily to oxidants generated either endogenously or exogenously (air pollutants, cigarette smoke, etc.). Cells in aerobic organisms are protected against oxidative damage by enzymatic and non-enzymatic antioxidant systems. Recent epidemiologic investigations have shown associations between increased incidence of respiratory diseases and lung cancer from exposure to low levels of various forms of respirable fibers and particulate matter (PM), at occupational or urban air polluting environments. Lung cancer increases substantially for tobacco smokers due to the synergistic effects in the generation of ROS, leading to oxidative stress and inflammation with high DNA damage potential. Physical and chemical characteristics of particles (size, transition metal content, speciation, stable free radicals, etc.) play an important role in oxidative stress. In turn, oxidative stress initiates the synthesis of mediators of pulmonary inflammation in lung epithelial cells and initiation of carcinogenic mechanisms. Inhalable quartz, metal powders, mineral asbestos fibers, ozone, soot from gasoline and diesel engines, tobacco smoke and PM from ambient air pollution (PM10 and PM2.5) are involved in various oxidative stress mechanisms. Pulmonary cancer initiation and promotion has been linked to a series of biochemical pathways of oxidative stress, DNA oxidative damage, macrophage stimulation, telomere shortening, modulation of gene expression and activation of transcription factors with important role in carcinogenesis. In this review we are presenting the role of ROS and oxidative stress in the production of mediators of pulmonary inflammation and mechanisms of carcinogenesis

Uncertainty analysis in design rainfall estimation due to limited data length : a case study in Qatar

This chapter presents a statistical modeling framework to quantify uncertainty in design rainfall estimation due to sampling error arising from limited data length. We used rainfall data from three stations in Qatar and adopted Monte Carlo simulation technique to carry out uncertainty analysis where bootstrapping is used to define standard error in the sample estimates of mean, standard deviation, and skewness of the observed annual maximum (AM) for the 24-h duration rainfall data. From the results of three goodness-of-fit tests it has been found that Log-Pearson Type 3 (LP3) is the most favorable distribution for the three selected stations. Results from bootstrapping show that the estimate of the mean is associated with the smallest degree of standard error, while skewness has the highest error level. By applying the developed statistical modeling framework, the confidence intervals for design rainfall are derived for 2- to 100-year return periods at the three selected stations in Qatar