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- Beelen, Rob, et al.
(författare)
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Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe : the ESCAPE project
- 2013
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Ingår i: Atmospheric Environment. - : Elsevier. - 1352-2310 .- 1873-2844. ; 72, s. 10-23
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Tidskriftsartikel (refereegranskat)abstract
- Estimating within-city variability in air pollution concentrations is important. Land use regression (LUR) models are able to explain such small-scale within-city variations. Transparency in LUR model development methods is important to facilitate comparison of methods between different studies. We therefore developed LUR models in a standardized way in 36 study areas in Europe for the ESCAPE (European Study of Cohorts for Air Pollution Effects) project.Nitrogen dioxide (NO2) and nitrogen oxides (NOx) were measured with Ogawa passive samplers at 40 or 80 sites in each of the 36 study areas. The spatial variation in each area was explained by LUR modeling. Centrally and locally available Geographic Information System (GIS) variables were used as potential predictors. A leave-one out cross-validation procedure was used to evaluate the model performance.There was substantial contrast in annual average NO2 and NOx concentrations within the study areas. The model explained variances (R2) of the LUR models ranged from 55% to 92% (median 82%) for NO2 and from 49% to 91% (median 78%) for NOx. For most areas the cross-validation R2 was less than 10% lower than the model R2. Small-scale traffic and population/household density were the most common predictors. The magnitude of the explained variance depended on the contrast in measured concentrations as well as availability of GIS predictors, especially traffic intensity data were important. In an additional evaluation, models in which local traffic intensity was not offered had 10% lower R2 compared to models in the same areas in which these variables were offered.Within the ESCAPE project it was possible to develop LUR models that explained a large fraction of the spatial variance in measured annual average NO2 and NOx concentrations. These LUR models are being used to estimate outdoor concentrations at the home addresses of participants in over 30 cohort studies.
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| 2. |
- Westerlund, J., et al.
(författare)
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Application of air quality combination forecasting to Bogota
- 2014
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Ingår i: Atmospheric Environment. - : Elsevier BV. - 1352-2310. ; 89, s. 22-28
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Tidskriftsartikel (refereegranskat)abstract
- The bulk of existing work on the statistical forecasting of air quality is based on either neural networks or linear regressions, which are both subject to important drawbacks. In particular, while neural networks are complicated and prone to in-sample overfitting, linear regressions are highly dependent on the specification of the regression function. The present paper shows how combining linear regression forecasts can be used to circumvent all of these problems. The usefulness of the proposed combination approach is verified using both Monte Carlo simulation and an extensive application to air quality in Bogota, one of the largest and most polluted cities in Latin America. (C) 2014 Elsevier Ltd. All rights reserved.
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| 3. |
- Buccoliere, Riccardo, et al.
(författare)
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City breathability and its link to pollutant concentration distribution within urban-like geometries
- 2010
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Ingår i: Atmospheric Environment. - : Elsevier. - 1352-2310 .- 1873-2844. ; 44:15, s. 1894-1903
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Tidskriftsartikel (refereegranskat)abstract
- This paper is devoted to the study of pollutant concentration distribution within urban-like geometries. By applying efficiency concepts originally developed for indoor environments, the term ventilation is used as a measure of city “breathability”. It can be applied to analyse pollutant removal within a city in operational contexts. This implies the evaluation of the bulk flow balance over the city and of the mean age of air. The influence of building packing density on flow and pollutant removal is, therefore, evaluated using those quantities. Idealized cities of regular cubical buildings were created with packing density ranging from 6.25% to 69% to represent configurations from urban sprawl to compact cities. The relative simplicity of these arrangements allowed us to apply the Computational Fluid Dynamics (CFD) flow and dispersion simulations using the standard k– turbulence model. Results show that city breathability within the urban canopy layer is strongly dependent from the building packing density. At the lower packing densities, the city responds to the wind as an agglomeration of obstacles, at larger densities (from about 44%) the city itself responds as a single obstacle. With the exception of the lowest packing density, airflow enters the array through lateral sides and leaves throughout the street top and flow out downstream. The air entering through lateral sides increases with increasing packing density.At the street top of the windward side of compact building configurations, a large upward flow is observed. This vertical transport reduces over short distance to turn into a downward flow further downstream of the building array. These findings suggest a practical way of identifying city breathability. Even though the application of these results to real scenarios require further analyses the paper illustrates a practical framework to be adopted in the assessment of the optimum neighbourhood building layout to minimize pollution levels.
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