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
The result's identifiers
Result code in 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>
Alternative codes found
RIV/00216208:11320/25:10508883 RIV/00020699:_____/25:N0000028
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
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
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10509 - Meteorology and atmospheric sciences
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Atmospheric Chemistry and Physics
ISSN
1680-7316
e-ISSN
1680-7324
Volume of the periodical
25
Issue of the periodical within the volume
8
Country of publishing house
DE - GERMANY
Number of pages
28
Pages from-to
4477-4504
UT code for WoS article
001473576500001
EID of the result in the Scopus database
2-s2.0-105003698856