City-level mapping of air quality at fine spatial resolution – the Prague case study. NO2, PM10 and PM2.5 maps on a 100 m spatial grid. ETC HE Report 2022/24.

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F23%3AN0000151" target="_blank" >RIV/00020699:_____/23:N0000151 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.5281/zenodo.8383115" target="_blank" >https://doi.org/10.5281/zenodo.8383115</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

City-level mapping of air quality at fine spatial resolution – the Prague case study. NO2, PM10 and PM2.5 maps on a 100 m spatial grid. ETC HE Report 2022/24.

Original language description

This paper examines the creation of fine resolution maps at 100 m x 100 m resolution using statistical downscaling for the area of Prague, as a case study. This Czech city was selected due to the fine resolution proxy data available for this city. The reference downscaling methodology used is the linear regression and the interpolation of its residuals by the area-to-point kriging. Next to this, several other methods of statistical downscaling have been also executed. The results of different downscaling methods have been compared mutually and against the data from the monitoring stations of Prague, separately for urban background and traffic areas. The downscaled maps in 100 m x 100 m resolution have been constructed for the area of Prague for three pollutants, namely for NO2, PM10 and PM2.5. Several methods of the statistical downscaling have been compared mutually and against the data from the monitoring stations. In general, the best results are given by the linear regression and the interpolation of its residuals, either by the area-to-point kriging or the bilinear interpolation. In the maps, one can see overall realistic spatial patterns, the main roads in Prague are visible through higher air pollution levels. This is distinct especially for NO2, while for PM10 and PM2.5 the differences between road increments and urban background are smaller as would be expected. The results of the case study for Prague have proven the usefulness of the statistical downscaling for the air quality mapping, especially for NO2. In addition, the population exposure estimates based on the downscaled mapping results have been also calculated.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

10509 - Meteorology and atmospheric sciences

Project

<a href="/en/project/SS02030031" target="_blank" >SS02030031: Air quality Research, Assessment and Monitoring Integrated System</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů