Personal exposures to NO2 in the EXPOLIS-study: relation to residential indoor, outdoor and workplace concentrations in Basel, Helsinki and Prague

Self Cite

Exposure analysis is a crucial part of effective management of public health risks caused by pollutants and chemicals in our environment. During the last decades, more data required for exposure analysis has become available, but the need for direct population based measurements of exposures is still clear. The current work (i) describes the European EXPOLIS study, designed to produce this kind of exposure data for major air pollutants in Europe, and the database created to make the collected data available for researchers (ii) reviews the exposure analysis conducted and results published so far using these data and (iii) discusses the implications of the results from the point of view of research and environmental policy in Europe. Fine particle (with 37 elements and black smoke), nitrogen dioxide, volatile organic compounds (30 compounds) and carbon monoxide inhalation exposures and exposurerelated questionnaire data were measured in seven European cities during 1996-2000. The EXPOLIS database has been used for exposure analysis of these pollutants for 4 years now and results have been published in approximately 30 peer-reviewed journal papers, demonstrating the versatility, usability and scientific value of such a data set. The multipollutant exposure data from the same subjects in the random population samples allows for analyses of the determinants, microenvironments and sources of exposures to multipollutant mixtures and associations between the different air pollutants. This information is necessary and useful for developing effective policies and control strategies for healthier environment.

Section: Comentioning

confidence: 99%

The EXPOLIS study: implications for exposure research and environmental policy in Europe

Hänninen

Alm

Katsouyanni

et al. 2004

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“…A study of nitrogen dioxide (NO 2 ) in Portage, Wisconsin, correlated personal exposure with outdoor NO 2 at residence, full-time worker status, and commute distance (Quackenboss et al, 1986). In Helsinki, Kousa et al (2001) found that work locations downtown were one of the strongest predictors of personal exposure to NO 2 ; other predictors included outdoor concentrations at residential or central locations. Nethery et al (2008) compared personal exposure monitoring of NO 2 with land-use regression (LUR) estimates of outdoor concentrations developed by Henderson et al (2007).…”

Section: Introductionmentioning

confidence: 99%

The impact of daily mobility on exposure to traffic-related air pollution and health effect estimates

Setton

Marshall

Bräuer

et al. 2010

205

128

Epidemiological studies of traffic-related air pollution typically estimate exposures at residential locations only; however, if study subjects spend time away from home, exposure measurement error, and therefore bias, may be introduced into epidemiological analyses. For two study areas (Vancouver, British Columbia, and Southern California), we use paired residence-and mobility-based estimates of individual exposure to ambient nitrogen dioxide, and apply error theory to calculate bias for scenarios when mobility is not considered. In Vancouver, the mean bias was 0.84 (range: 0.79-0.89; SD: 0.01), indicating potential bias of an effect estimate toward the null by B16% when using residence-based exposure estimates. Bias was more strongly negative (mean: 0.70, range: 0.63-0.77, SD: 0.02) when the underlying pollution estimates had higher spatial variation (land-use regression versus monitor interpolation). In Southern California, bias was seen to become more strongly negative with increasing time and distance spent away from home (e.g., 0.99 for 0-2 h spent at least 10 km away, 0.66 for Z10 h spent at least 40 km away). Our results suggest that ignoring daily mobility patterns can contribute to bias toward the null hypothesis in epidemiological studies using individual-level exposure estimates.

“…Studies have consistently demonstrated that residential indoor concentrations are more strongly correlated with personal exposures than outdoor concentrations Koistinen et al, 2001;Kousa et al, 2001). While numerous studies have identified important sources affecting longer-term indoor exposures (e.g.…”

Section: Introductionmentioning

confidence: 99%

Predictors of concentrations of nitrogen dioxide, fine particulate matter, and particle constituents inside of lower socioeconomic status urban homes

Baxter

Clougherty

Laden

et al. 2006

104

Air pollution exposure patterns may contribute to known spatial patterning of asthma morbidity within urban areas. While studies have evaluated the relationship between traffic and outdoor concentrations, few have considered indoor exposure patterns within low socioeconomic status (SES) urban communities. In this study, part of a prospective birth cohort study assessing asthma etiology in urban Boston, we collected indoor and outdoor 3-4 day samples of nitrogen dioxide (NO 2 ) and fine particulate matter (PM 2.5 ) in 43 residences across multiple seasons from 2003 to 2005. Homes were chosen to represent low SES households, including both cohort and non-cohort residences in similar neighborhoods, and consisted almost entirely of multiunit residences. Reflectance analysis and X-ray fluorescence spectroscopy were performed on the particle filters to determine elemental carbon (EC) and trace element concentrations, respectively. Additionally, information on home characteristics (e.g. type, age, stove fuel) and occupant behaviors (e.g. smoking, cooking, cleaning) were collected via a standardized questionnaire. The contributions of outdoor and indoor sources to indoor concentrations were quantified with regression analyses using mass balance principles. For NO 2 and most particle constituents (except outdoor-dominated constituents like sulfur and vanadium), the addition of selected indoor source terms improved the model's predictive power. Cooking time, gas stove usage, occupant density, and humidifiers were identified as important contributors to indoor levels of various pollutants. A comparison between cohort and non-cohort participants provided another means to determine the influence of occupant activity patterns on indoor-outdoor ratios. Although the groups had similar housing characteristics and were located in similar neighborhoods, cohort members had significantly higher indoor concentrations of PM 2.5 and NO 2 , associated with indoor activities. We conclude that the effect of indoor sources may be more pronounced in high-density multiunit dwellings, and that future epidemiological studies in these populations should explicitly consider these sources in assigning exposures.