Spatial PM2.5, NO2, O3 and BC models for Western Europe – Evaluation of spatiotemporal stability

Hoogh, Kees de; Chen, Jie; Gulliver, John; Hoffmann, Barbara; Hertel, Ole; Ketzel, Matthias; Bauwelinck, Mariska; Donkelaar, Aaron van; Hvidtfeldt, Ulla Arthur; Katsouyanni, Klea; Klompmaker, Jochem O.; Martin, Randal V.; Samoli, Evangelia; Schwartz, Per E.; Stafoggia, Massimo; Bellander, Tom; Strak, Maciej; Wolf, Kathrin; Vienneau, Danielle; Brunekreef, Bert; Hoek, Gerard

doi:10.1016/j.envint.2018.07.036

Cited by 251 publications

(224 citation statements)

References 36 publications

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“…We assigned annual mean concentrations (µg/m 3 ) of 5 different air pollutants—NO 2 , PM 2.5 , PM 10 , black carbon (BC) and O 3 —to each participant based on their geocoded residential history. The exposures were assigned from air pollution rasters developed previously [ 31 , 32 , 33 ]. Annual mean PM 10 exposures were extracted for 2005 to 2007 from surfaces (100 × 100 m) based on western Europe-wide hybrid land use regression (LUR) models [ 31 ].…”

Section: Methodsmentioning

confidence: 99%

Associations of Preconception Exposure to Air Pollution and Greenness with Offspring Asthma and Hay Fever

Kuiper

Markevych

Accordini

et al. 2020

IJERPH

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We investigated if greenness and air pollution exposure in parents’ childhood affect offspring asthma and hay fever, and if effects were mediated through parental asthma, pregnancy greenness/pollution exposure, and offspring exposure. We analysed 1106 parents with 1949 offspring (mean age 35 and 6) from the Respiratory Health in Northern Europe, Spain and Australia (RHINESSA) generation study. Mean particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), black carbon (BC), ozone (O3) (µg/m3) and greenness (normalized difference vegetation index (NDVI)) were calculated for parents 0–18 years old and offspring 0–10 years old, and were categorised in tertiles. We performed logistic regression and mediation analyses for two-pollutant models (clustered by family and centre, stratified by parental lines, and adjusted for grandparental asthma and education). Maternal medium PM2.5 and PM10 exposure was associated with higher offspring asthma risk (odds ratio (OR) 2.23, 95%CI 1.32–3.78, OR 2.27, 95%CI 1.36–3.80), and paternal high BC exposure with lower asthma risk (OR 0.31, 95%CI 0.11–0.87). Hay fever risk increased for offspring of fathers with medium O3 exposure (OR 4.15, 95%CI 1.28–13.50) and mothers with high PM10 exposure (OR 2.66, 95%CI 1.19–5.91). The effect of maternal PM10 exposure on offspring asthma was direct, while for hay fever, it was mediated through exposures in pregnancy and offspring’s own exposures. Paternal O3 exposure had a direct effect on offspring hay fever. To conclude, parental exposure to air pollution appears to influence the risk of asthma and allergies in future offspring.

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Section: Methodsmentioning

confidence: 99%

Associations of Preconception Exposure to Air Pollution and Greenness with Offspring Asthma and Hay Fever

Kuiper

Markevych

Accordini

et al. 2020

IJERPH

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“…Recent reports [21][22][23] have increasingly pointed to the need for reviewing the impacts of air pollution in the Nordic countries due to the large uncertainties in estimating the effects at low exposure levels. Currently there is no consensus on which shape of the concentration-response function should be applied and whether a threshold should be used.…”

Section: Introductionmentioning

confidence: 99%

Deaths Attributable to Air Pollution in Nordic Countries: Disparities in the Estimates

et al. 2020

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Particulate matter air pollution is widely considered as the leading environmental cause of premature mortality. However, there are substantial differences in the estimated health burden between the assessments. The aim of this work is to quantify the deaths attributable to ambient air pollution in Nordic countries applying selected assessment tools and approaches, and to identify the main disparities. We quantified and compared the estimated deaths from three health risk assessment tools and from a set of different concentration-response functions. A separate analysis was conducted for the impacts of spatial resolution of the exposure model on the estimated deaths. We found that the death rate (deaths per million) attributable to PM2.5 and O3 were the highest in Denmark and the lowest in Iceland. In the five Nordic countries, the results between the three tools ranged from 8500 to 11,400 for PM2.5 related deaths, and for ozone from 230 to 260 deaths in 2015. Substantially larger differences were found between five concentration-response functions. The shape of concentration-response functions, and applied theoretical thresholds led to substantial differences in the estimated deaths. Nordic countries are especially sensitive to theoretical thresholds due to low exposures. Sensitivity analysis demonstrated that when using spatial exposure assessment methods, high spatial resolution is necessary to avoid underestimation of exposures and health effects.

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“…We obtained estimates of exposure to outdoor air pollutants at the 1,814 geocoded addresses by applying models available from three projects for baseline (or closest year), and new exposure models for 2017-18. For baseline, we used the ordinary kriging models of NO 2 and formaldehyde concentrations that we had previously devised using data from the passive sampling campaigns in 2010 (Marcon et al 2014). For the same year, we also used the land-use regression (LUR) models for PM 2.5 , NO 2 , and black carbon (BC) concentrations developed for Western Europe within the ELAPSE study (Effects of Low-Level Air Pollution: A study in Europe) (de Hoogh et al 2018). ELAPSE models are based on routine air quality monitoring data for PM 2.5 and NO 2 , and ad hoc monitoring data for BC, in combination with satellite data, dispersion model estimates, land cover and traffic indicators.…”

Section: Exposure Assignmentmentioning

confidence: 99%

“…LUR models based on routine monitors from country-wide or larger areas perform well in the Po Plain (de Hoogh et al 2018;Stafoggia et al 2017) but they may not be ideal to capture variability in industrial pollution. This can in part be attributed to the relatively small number of industrial monitoring sites that can be included at the modelling stage (Stafoggia et al 2017), but also to the fact that spatial LUR predictors are unable to accurately reflect specific types of industrial productions and facilities.…”

Section: Comparison Between Air Pollution Exposure Modelsmentioning

confidence: 99%

Spatial variability of nitrogen dioxide and formaldehyde and residential exposure of children in the industrial area of Viadana, Northern Italy

Marcon

Panunzi

Stafoggia

et al. 2020

Preprint

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Chipboard production is a source of ambient air pollution. We assessed the spatial variability of outdoor pollutants and residential exposure of children living in proximity to the largest industry for chipboard production in Italy, aiming at evaluating the reliability of exposure estimates obtained from passive sampling for an ongoing epidemiological study. We obtained data on NO2 and formaldehyde, collected by the environmental protection agency of Lombardia region, at 25 passive sampling sites in the municipality of Viadana during 10 weeks (2017-18), and compared NO2 measurements with average weekly concentrations from continuous monitors. We compared interpolated surfaces of NO2 and formaldehyde for 2017-18 with previous maps for 2010. We assessed the relationship between residential proximity to the industry and pollutant exposures, assigned both using our maps and available countrywide/continental models based on routine monitoring data on NO2, PM10, and PM2.5. The correlation between weekly NO2 concentrations from a continuous monitor and a co-located passive sampler was high (Pearson's r = 0.89), although passive sampling underestimated NO2 during the cold season. For both 2010 and 2017-18, we observed higher NO2 and formaldehyde concentrations in the southern part of Viadana, with hot-spots in proximity to the industry. PM10 and PM2.5 exposures were higher for children at <1km to the industry and NO2 exposure was higher at 1-1.7 km, compared to the children living at >3.5 km. The density of roads and population was also higher in proximity to the industry. Findings from a variety of exposure models suggest that children living in proximity to the chipboard industry in Viadana are more exposed to air pollution and that exposure gradients are relatively stable over time.

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Spatial PM2.5, NO2, O3 and BC models for Western Europe – Evaluation of spatiotemporal stability

Cited by 251 publications

References 36 publications

Associations of Preconception Exposure to Air Pollution and Greenness with Offspring Asthma and Hay Fever

Associations of Preconception Exposure to Air Pollution and Greenness with Offspring Asthma and Hay Fever

Deaths Attributable to Air Pollution in Nordic Countries: Disparities in the Estimates

Spatial variability of nitrogen dioxide and formaldehyde and residential exposure of children in the industrial area of Viadana, Northern Italy

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