Effects of indoor particulate matter exposure on daily asthma control.

BACKGROUND: Household dust often contains aeroallergens, such as the house dust mite antigen Der p 1. It has been proposed that overnight exposure to particulate matter from bedding and other sources may be an important driver of atopic asthma. Whether variability in overnight particulate matter exposure is a significant determinant of asthma control is unknown. OBJECTIVE: To test the hypothesis that overnight particulate matter exposure is associated with day-to-day symptoms, lung function, and airway inflammation in patients with asthma who are sensitized to house dust mite. METHODS: We undertook a prospective, single-center panel study in 28 adults with asthma and house dust mite sensitization. Overnight exposure to particulate matter was measured using a commercially available indoor air quality monitor. Symptom scores, peak expiratory flow, and exhaled nitric oxide were measured and electronically recorded daily. Participants were followed up for 12 weeks and attended study visits every 4 weeks, at which they underwent spirometry and completed the Asthma Control Questionnaire and Asthma Quality of Life Questionnaire. Data were analyzed using cross-correlation and linear mixed-effects models. RESULTS: No significant associations were observed between overnight particulate matter exposure and clinical outcomes measured daily or at study visits. CONCLUSION: Natural variability in overnight particulate matter exposure does not appear to be a major determinant of daily asthma control in patients with asthma and house dust mite sensitization.

Practical Use of Metal Oxide Semiconductor Gas Sensors for Measuring Nitrogen Dioxide and Ozone in Urban Environments.

The potential of inexpensive Metal Oxide Semiconductor (MOS) gas sensors to be used for urban air quality monitoring has been the topic of increasing interest in the last decade. This paper discusses some of the lessons of three years of experience working with such sensors on a novel instrument platform (Small Open General purpose Sensor (SOGS)) in the measurement of atmospheric nitrogen dioxide and ozone concentrations. Analytic methods for increasing long-term accuracy of measurements are discussed, which permit nitrogen dioxide measurements with 95% confidence intervals of 20.0 µ g m - 3 and ozone precision of 26.8 µ g m - 3 , for measurements over a period one month away from calibration, averaged over 18 months of such calibrations. Beyond four months from calibration, sensor drift becomes significant, and accuracy is significantly reduced. Successful calibration schemes are discussed with the use of controlled artificial atmospheres complementing deployment on a reference weather station exposed to the elements. Manufacturing variation in the attributes of individual sensors are examined, an experiment possible due to the instrument being equipped with pairs of sensors of the same kind. Good repeatability (better than 0.7 correlation) between individual sensor elements is shown. The results from sensors that used fans to push air past an internal sensor element are compared with mounting the sensors on the outside of the enclosure, the latter design increasing effective integration time to more than a day. Finally, possible paths forward are suggested for improving the reliability of this promising sensor technology for measuring pollution in an urban environment.

The association between air pollution and type 2 diabetes in a large cross-sectional study in Leicester: The CHAMPIONS Study.

BACKGROUND: Observational evidence suggests there is an association between air pollution and type 2 diabetes; however, there is high risk of bias. OBJECTIVE: To investigate the association between air pollution and type 2 diabetes, while reducing bias due to exposure assessment, outcome assessment, and confounder assessment. METHODS: Data were collected from 10,443 participants in three diabetes screening studies in Leicestershire, UK. Exposure assessment included standard, prevailing estimates of outdoor nitrogen dioxide and particulate matter concentrations in a 1×1km area at the participant's home postcode. Three-year exposure was investigated in the primary analysis and one-year exposure in a sensitivity analysis. Outcome assessment included the oral glucose tolerance test for type 2 diabetes. Confounder assessment included demographic factors (age, sex, ethnicity, smoking, area social deprivation, urban or rural location), lifestyle factors (body mass index and physical activity), and neighbourhood green space. RESULTS: Nitrogen dioxide and particulate matter concentrations were associated with type 2 diabetes in unadjusted models. There was no statistically significant association between nitrogen dioxide concentration and type 2 diabetes after adjustment for demographic factors (odds: 1.08; 95% CI: 0.91, 1.29). The odds of type 2 diabetes was 1.10 (95% CI: 0.92, 1.32) after further adjustment for lifestyle factors and 0.91 (95% CI: 0.72, 1.16) after yet further adjustment for neighbourhood green space. The associations between particulate matter concentrations and type 2 diabetes were also explained away by demographic factors. There was no evidence of exposure definition bias. CONCLUSIONS: Demographic factors seemed to explain the association between air pollution and type 2 diabetes in this cross-sectional study. High-quality longitudinal studies are needed to improve our understanding of the association.

Concurrent multiaxis differential optical absorption spectroscopy system for the measurement of tropospheric nitrogen dioxide.

The development of a new concurrent multiaxis (CMAX) sky viewing spectrometer to monitor rapidly changing urban concentrations of nitrogen dioxide is detailed. The CMAX differential optical absorption spectroscopy (DOAS) technique involves simultaneous spectral imaging of the zenith and off-axis measurements of spatially resolved scattered sunlight. Trace-gas amounts are retrieved from the measured spectra using the established DOAS technique. The potential of the CMAX DOAS technique to derive information on rapidly changing concentrations and the spatial distribution of NO2 in an urban environment is demonstrated. Three example data sets are presented from measurements during 2004 of tropospheric NO2 over Leicester, UK (52.62 degrees N, 1.12 degrees W). The data demonstrate the current capabilities and future potential of the CMAX DOAS method in terms of the ability to measure real-time spatially disaggregated urban NO2.