New high resolution maps of estimated background ambient NOx and NO2 concentrations in the U.K.

Stedman, John; Vincent, Keith; Campbell, G. W.; Goodwin, Justin; Downing, C.

doi:10.1016/s1352-2310(97)00159-3

Cited by 57 publications

(24 citation statements)

References 2 publications

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“…The methodology is similar to the methods used to estimate nationwide NO 2 concentrations ( Stedman et al, 1997 ). The basic idea is that because NO 2 concentrations vary on a fine spatial scale, direct interpolation will result in systematic prediction errors related to emission sources in the area __________ = 50 km Figure 1.…”

Section: Estimation Methodsmentioning

confidence: 99%

“…Long-term exposure to air pollution Hoek et al ( Stedman et al, 1997 ) . Therefore, regional background, urban background, and local source contributions are estimated separately.…”

Section: Estimation Methodsmentioning

confidence: 99%

“…On a smaller spatial scale, the SAVIAH study has found that regression -based methods using external information, such as distance to major roads, were superior to interpolation methods in explaining within-city variation of NO 2 concentrations (Briggs et al, 1997 ). In a UK study (Stedman et al, 1997 ), the percentage of urban and suburban land cover at two spatial scales ( 100 and 25 km 2 around the sites) and estimated emission from major road vehicle sources in an area of 4 km 2 around the site were used as predictors in a regression model for NO 2 . The developed model correlated moderately high with independently measured concentrations (r =0.6).…”

Section: Urban Backgroundmentioning

confidence: 98%

“…Second, we did not want to assign concentration values from the nearest measurement site without taking into account the nature of the site ( regional, urban background ). Because NO 2 concentrations vary on a fine spatial scale, direct interpolation will result in systematic prediction errors related to emission sources in the area ( Stedman et al, 1997 ). On a smaller spatial scale, the SAVIAH study has found that regression -based methods using external information, such as distance to major roads, were superior to interpolation methods in explaining within-city variation of NO 2 concentrations (Briggs et al, 1997 ).…”

Section: Urban Backgroundmentioning

confidence: 99%

“…This regression model was next applied to the addresses of the study subjects (Briggs et al, 1997 ). A similar approach has been applied to describe the variation of the NO 2 concentration in a dense network spread over the UK ( Stedman et al, 1997 ).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Estimation of long-term average exposure to outdoor air pollution for a cohort study on mortality

Hoek

Fischer

Brandt

et al. 2001

J Expo Sci Environ Epidemiol

138

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Recent prospective cohort studies have suggested that long -term exposure to low levels of particulate matter ( PM ) air pollution is associated with increased mortality due to, especially, cardio -pulmonary disease. Exposure to ambient air pollution was estimated mostly as city average concentrations, assuming homogenous exposure within the city. We used an ongoing cohort study -The Netherlands Cohort Study ( NLCS ) on diet and cancer -to investigate the relationship between traffic -related air pollution and mortality. The baseline data collection took place in 1986. A study was conducted to develop methods for exposure assessment and evaluate the contrast in exposure to air pollution within the cohort. Assessment of long -term exposure to two traffic -related air pollutants, Black Smoke ( BS ) and Nitrogen Dioxide ( NO 2 ) , consisted of separate estimation of regional background, urban background, and local traffic contributions at the home address. Interpolation of concentration data from a routine monitoring network was used to estimate the regional background concentration. A regression model relating degree of urbanization to air pollution was used to allow for differences between different towns / neighborhoods of cities. Distance to major roads was calculated to characterize local traffic contributions, using a Geographic Information System ( GIS ) . Interpolation resulted in reasonably precise regional background estimation when distant sites were not used and distance squared was used as the weight. Cross -validation showed that prediction errors were about 15% of the range in regional background concentration. Urban and local scales contributed significantly to the contrast within the cohort. Prediction errors for estimating the urban background were about 25% of the range in background concentrations. When the developed model was applied to the study cohort, there was substantial contrast in estimated exposure to BS and NO 2 . About 90% of the study population lived 10 years or more at its 1986 home address -supporting the use of the estimated concentration at the 1986 address as a relevant exposure variable.

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Section: Estimation Methodsmentioning

confidence: 99%

“…Long-term exposure to air pollution Hoek et al ( Stedman et al, 1997 ) . Therefore, regional background, urban background, and local source contributions are estimated separately.…”

Section: Estimation Methodsmentioning

confidence: 99%