Comparison of the IFDM building downwash model predictions with field data

Lefebvre, Wouter; Cosemans, G.; Kegels, J.

doi:10.1016/j.atmosenv.2013.04.022

Cited by 10 publications

(8 citation statements)

References 9 publications

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“…This data is coupled to regional concentration levels from the land-use regression model RIO. The RIO model combines data from fixed air quality monitoring stations based on a land-use (CORINE) derived covariate (Lefebvre et al, 2013). The performance of air pollution exposure models has been exhaustively validated with cross-validation (leaving one out) and with independent measurement campaigns.…”

Section: Modelled Air Pollution Estimatesmentioning

confidence: 99%

“…The performance of air pollution exposure models has been exhaustively validated with cross-validation (leaving one out) and with independent measurement campaigns. The RIO model has been shown to be the most accurate way of mapping air pollution in Belgium (Hooyberghs et al, 2006;Janssen et al, 2008;Lefebvre & Vranckx, 2013). Annual mean concentrations of PM2.5 for the year 2005 were assigned to the residential address at baseline (2001).…”

Section: Modelled Air Pollution Estimatesmentioning

confidence: 99%

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Are air quality perception and PM2.5 exposure differently associated with cardiovascular and respiratory disease mortality in Brussels? Findings from a census-based study

Kangas

Gadeyne

Lefebvre

et al. 2023

Environmental Research

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Section: Modelled Air Pollution Estimatesmentioning

confidence: 99%

Section: Modelled Air Pollution Estimatesmentioning

confidence: 99%

Are air quality perception and PM2.5 exposure differently associated with cardiovascular and respiratory disease mortality in Brussels? Findings from a census-based study

Kangas

Gadeyne

Lefebvre

et al. 2023

Environmental Research

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“…BC represents one of the most health-relevant components of particulate matter (PM) and is a valuable indicator to assess the health effects of air quality dominated by primary combustion particles [ 42 ]. BC exposure was obtained as a continuous grid through the Belgian Interregional Environment Agency (IRCEL – CELINE) which supervises the national monitoring system assessing air pollutant concentrations through a dense network of stations, and estimates local exposure through interpolation, taking into account land cover data in combination with a dispersion model [ 43 , 44 ]. BHIS data of 2008, 2013, and 2018 were respectively linked to BC exposure data of 2010, 2013, and 2018.…”

Section: Methodsmentioning

confidence: 99%

The potential impact fraction of population weight reduction scenarios on non-communicable diseases in Belgium: application of the g-computation approach

Pelgrims,

Devleesschauwer,

Vandevijvere

et al. 2024

BMC Med Res Methodol

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Background Overweight is a major risk factor for non-communicable diseases (NCDs) in Europe, affecting almost 60% of all adults. Tackling obesity is therefore a key long-term health challenge and is vital to reduce premature mortality from NCDs. Methodological challenges remain however, to provide actionable evidence on the potential health benefits of population weight reduction interventions. This study aims to use a g-computation approach to assess the impact of hypothetical weight reduction scenarios on NCDs in Belgium in a multi-exposure context. Methods Belgian health interview survey data (2008/2013/2018, n = 27 536) were linked to environmental data at the residential address. A g-computation approach was used to evaluate the potential impact fraction (PIF) of population weight reduction scenarios on four NCDs: diabetes, hypertension, cardiovascular disease (CVD), and musculoskeletal (MSK) disease. Four scenarios were considered: 1) a distribution shift where, for each individual with overweight, a counterfactual weight was drawn from the distribution of individuals with a “normal” BMI 2) a one-unit reduction of the BMI of individuals with overweight, 3) a modification of the BMI of individuals with overweight based on a weight loss of 10%, 4) a reduction of the waist circumference (WC) to half of the height among all people with a WC:height ratio greater than 0.5. Regression models were adjusted for socio-demographic, lifestyle, and environmental factors. Results The first scenario resulted in preventing a proportion of cases ranging from 32.3% for diabetes to 6% for MSK diseases. The second scenario prevented a proportion of cases ranging from 4.5% for diabetes to 0.8% for MSK diseases. The third scenario prevented a proportion of cases, ranging from 13.6% for diabetes to 2.4% for MSK diseases and the fourth scenario prevented a proportion of cases ranging from 36.4% for diabetes to 7.1% for MSK diseases. Conclusion Implementing weight reduction scenarios among individuals with excess weight could lead to a substantial and statistically significant decrease in the prevalence of diabetes, hypertension, cardiovascular disease (CVD), and musculoskeletal (MSK) diseases in Belgium. The g-computation approach to assess PIF of interventions represents a straightforward approach for drawing causal inferences from observational data while providing useful information for policy makers.

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“…The core of the methodology consists of a traffic emission model and a Gaussian dispersion model coupled to a street-canyon module 26 . The model chain has been validated using several measurement campaigns, focusing on spatial patterns and time series alike 26 , 48 , 49 . The model chain relies on several input datasets: background atmospheric concentrations, meteorological data, traffic volumes and fleets, industrial emissions, and 3-D building data.…”

Section: Methodsmentioning

confidence: 99%

Copernicus for urban resilience in Europe

Chrysoulakis,

Ludlow,

Mitraka

et al. 2023

Sci Rep

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The urban community faces a significant obstacle in effectively utilising Earth Observation (EO) intelligence, particularly the Copernicus EO program of the European Union, to address the multifaceted aspects of urban sustainability and bolster urban resilience in the face of climate change challenges. In this context, here we present the efforts of the CURE project, which received funding under the European Union’s Horizon 2020 Research and Innovation Framework Programme, to leverage the Copernicus Core Services (CCS) in supporting urban resilience. CURE provides spatially disaggregated environmental intelligence at a local scale, demonstrating that CCS can facilitate urban planning and management strategies to improve the resilience of cities. With a strong emphasis on stakeholder engagement, CURE has identified eleven cross-cutting applications between CCS that correspond to the major dimensions of urban sustainability and align with user needs. These applications have been integrated into a cloud-based platform known as DIAS (Data and Information Access Services), which is capable of delivering reliable, usable and relevant intelligence to support the development of downstream services towards enhancing resilience planning of cities throughout Europe.

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Comparison of the IFDM building downwash model predictions with field data

Cited by 10 publications

References 9 publications

Are air quality perception and PM2.5 exposure differently associated with cardiovascular and respiratory disease mortality in Brussels? Findings from a census-based study

Are air quality perception and PM2.5 exposure differently associated with cardiovascular and respiratory disease mortality in Brussels? Findings from a census-based study

The potential impact fraction of population weight reduction scenarios on non-communicable diseases in Belgium: application of the g-computation approach

Copernicus for urban resilience in Europe

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