Measurement report: A complex street-level air quality observation campaign in a heavy-traffic area utilizing the multivariate adaptive regression splines method for field calibration of low-cost sensors

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F25%3A00619340" target="_blank" >RIV/67985807:_____/25:00619340 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/25:10508883 RIV/00020699:_____/25:N0000028

Výsledek na webu

<a href="https://doi.org/10.5194/acp-25-4477-2025" target="_blank" >https://doi.org/10.5194/acp-25-4477-2025</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5194/acp-25-4477-2025" target="_blank" >10.5194/acp-25-4477-2025</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Measurement report: A complex street-level air quality observation campaign in a heavy-traffic area utilizing the multivariate adaptive regression splines method for field calibration of low-cost sensors

Popis výsledku v původním jazyce

As part of the TURBAN project, the “Legerova campaign” investigated air quality and meteorology in a traffic-dense area of Prague, Czech Republic, from 30 May 2022 to 28 March 2023. The study deployed a network of 20 low-cost sensor (LCS) stations to measure NO2, O3, PM10 and PM2.5 concentrations, complemented by advanced meteorological instruments such as a microwave radiometer and Doppler lidar. Ensuring data quality from LCS measurements presented significant challenges. Initial field tests at a reference monitoring station revealed strong correlations between raw LCS and reference data (r > 0.90 for NO2 and PM2.5, r > 0.80 for O3 and PM10). However, individual biases were observed. Applying the multivariate adaptive regression splines (MARS) method effectively reduced biases and enhanced alignment with reference measurements for all pollutants (R2 0.88–0.97). During the campaign, sensor ageing and technical issues were identified through double mass curve analysis and final field testing. The highest NO2 concentrations were recorded in streets with dense building blocks and traffic lights, corresponding to peak traffic patterns (with medians of concentrations 20–34 ppb). Aerosol concentrations were generally low (medians of PM10 < 25 µg m−3 at all sites), with less temporal and spatial variability than NO2. Elevated PM10 and PM2.5 levels occurred primarily during temperature inversions, often linked to local sources, and during a short, non-local episode. This study highlights the MARS method as a reliable tool for field calibration of LCS networks and provides valuable data on urban air quality and its dynamics with high spatiotemporal resolution.

Název v anglickém jazyce

Measurement report: A complex street-level air quality observation campaign in a heavy-traffic area utilizing the multivariate adaptive regression splines method for field calibration of low-cost sensors

Popis výsledku anglicky

As part of the TURBAN project, the “Legerova campaign” investigated air quality and meteorology in a traffic-dense area of Prague, Czech Republic, from 30 May 2022 to 28 March 2023. The study deployed a network of 20 low-cost sensor (LCS) stations to measure NO2, O3, PM10 and PM2.5 concentrations, complemented by advanced meteorological instruments such as a microwave radiometer and Doppler lidar. Ensuring data quality from LCS measurements presented significant challenges. Initial field tests at a reference monitoring station revealed strong correlations between raw LCS and reference data (r > 0.90 for NO2 and PM2.5, r > 0.80 for O3 and PM10). However, individual biases were observed. Applying the multivariate adaptive regression splines (MARS) method effectively reduced biases and enhanced alignment with reference measurements for all pollutants (R2 0.88–0.97). During the campaign, sensor ageing and technical issues were identified through double mass curve analysis and final field testing. The highest NO2 concentrations were recorded in streets with dense building blocks and traffic lights, corresponding to peak traffic patterns (with medians of concentrations 20–34 ppb). Aerosol concentrations were generally low (medians of PM10 < 25 µg m−3 at all sites), with less temporal and spatial variability than NO2. Elevated PM10 and PM2.5 levels occurred primarily during temperature inversions, often linked to local sources, and during a short, non-local episode. This study highlights the MARS method as a reliable tool for field calibration of LCS networks and provides valuable data on urban air quality and its dynamics with high spatiotemporal resolution.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Atmospheric Chemistry and Physics

ISSN

1680-7316

e-ISSN

1680-7324

Svazek periodika

25

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

28

Strana od-do

4477-4504

Kód UT WoS článku

001473576500001

EID výsledku v databázi Scopus

2-s2.0-105003698856