As part of the EU-funded SAVIAH project, a regression-based methodology for mapping tra c-related air pollution was developed within a GIS environment. Mapping was carried out for NO2 in Amsterdam, Hudders® eld and Prague. In each centre, surveys of NO2 , as a marker for tra c-related pollution, were conducted using passive di usion tubes, exposed for four 2-week periods. A GIS was also established, containing data on monitored air pollution levels, road network, tra c volume, land cover, altitude and other, locally determined, features. Data from 80 of the monitoring sites were then used to construct a regression equation, on the basis of predictor environmental variables, and the resulting equation used to map air pollution across the study area. The accuracy of the map was then assessed by comparing predicted pollution levels with monitored levels at a range of independent reference sites. Results showed that the map produced extremely good predictions of monitored pollution levels, both for individual surveys and for the mean annual concentration, with r 2~0´7 9± 0´87 across 8± 10 reference points, though the accuracy of predictions for individual survey periods was more variable. In Hudders® eld and Amsterdam, further monitoring also showed that the pollution map provided reliable estimates of NO2 concentrations in the following year (r 2~0´5 9± 0´86 for n=20).

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Background: Specific characteristics of particulate matter (PM) responsible for associations with respiratory health observed in epidemiological studies are not well established. High correlations among, and differential measurement errors of, individual components contribute to this uncertainty.Objectives: We investigated which characteristics of PM have the most consistent associations with acute changes in respiratory function in healthy volunteers.Methods: We used a semiexperimental design to accurately assess exposure. We increased exposure contrast and reduced correlations among PM characteristics by exposing volunteers at five different locations: an underground train station, two traffic sites, a farm, and an urban background site. Each of the 31 participants was exposed for 5 hr while exercising intermittently, three to seven times at different locations during March–October 2009. We measured PM10, PM2.5, particle number concentrations (PNC), absorbance, elemental/organic carbon, trace metals, secondary inorganic components, endotoxin content, gaseous pollutants, and PM oxidative potential. Lung function [FEV1 (forced expiratory volume in 1 sec), FVC (forced vital capacity), FEF25–75 (forced expiratory flow at 25–75% of vital capacity), and PEF (peak expiratory flow)] and fractional exhaled nitric oxide (FENO) were measured before and at three time points after exposure. Data were analyzed with mixed linear regression.Results: An interquartile increase in PNC (33,000 particles/cm3) was associated with an 11% [95% confidence interval (CI): 5, 17%] and 12% (95% CI: 6, 17%) FENO increase over baseline immediately and at 2 hr postexposure, respectively. A 7% (95% CI: 0.5, 14%) increase persisted until the following morning. These associations were robust and insensitive to adjustment for other pollutants. Similarly consistent associations were seen between FVC and FEV1 with PNC, NO2 (nitrogen dioxide), and NOx (nitrogen oxides).Conclusions: Changes in PNC, NO2, and NOx were associated with evidence of acute airway inflammation (i.e., FENO) and impaired lung function. PM mass concentration and PM10 oxidative potential were not predictive of the observed acute responses.

BackgroundEnvironmental health impact assessments often have to deal with substantial uncertainties. Typically, the knowledge-base is limited with incomplete, or inconsistent evidence and missing or ambiguous data. Consulting experts can help to identify and address uncertainties.MethodsFormal expert elicitation is a structured approach to systematically consult experts on uncertain issues. It is most often used to quantify ranges for poorly known parameters, but may also be useful to further develop qualitative issues such as definitions, assumptions or conceptual (causal) models. A thorough preparation and systematic design and execution of an expert elicitation process may increase the validity of its outcomes and transparency and trustworthiness of its conclusions. Various expert elicitation protocols and methods exist. However, these are often not universally applicable, and need customization to suite the needs of a specific study. In this paper, we set out to develop a widely applicable method for the use of expert elicitation in environmental health impact assessment.ResultsWe present a practical yet flexible seven step procedure towards organising expert elicitation in the context of environmental health impact assessment, based on existing protocols. We describe how customization for specific applications is always necessary. In particular, three issues affect the choice of methods for a particular application: the types of uncertainties considered, the intended use of the elicited information, and the available resources. We outline how these three considerations guide choices regarding the design and execution of expert elicitation. We present signposts to sources where the issues are discussed in more depth to give the newcomer the insights needed to make the protocol work. The seven step procedure is illustrated using examples from earlier published elicitations in the field of environmental health research.ConclusionsWe conclude that, despite some known criticism on its validity, formal expert elicitation can support environmental health research in various ways. Its main purpose is to provide a temporary summary of the limited available knowledge, which can serve as a provisional basis for policy until further research has been carried out.