Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models
| Autor: | Romà Tauler, Marta Terrado, Albert Soret, Stefan Platikanov, María Teresa Pay |
|---|---|
| Přispěvatelé: | Ministerio de Ciencia e Innovación (España), Tauler, Romà, Barcelona Supercomputing Center, Tauler, Romà [0000-0001-8559-9670] |
| Rok vydání: | 2022 |
| Předmět: |
Quimiometria
Qualitat de l'aire Environmental Engineering Multivariate analysis Traffic emission Atmospheric sciences Air quality monitoring Ozone Simulació per ordinador Air quality modelling CALIOPE system Environmental Chemistry Chemometrics Waste Management and Disposal Spatial analysis Air quality index Nitrogen dioxide Multivariate curve resolution Pollution MCR-ALS Air quality Environmental science Air--Pollution Ozó Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica [Àrees temàtiques de la UPC] |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Digital.CSIC. Repositorio Institucional del CSIC instname |
| ISSN: | 0048-9697 2019-1057 |
| Popis: | The application of the multivariate curve resolution method to the analysis of temporal and spatial data variability of hourly measured O3 and NO2 concentrations at nineteen air quality monitoring stations across Catalonia, Spain, during 2015 is shown. Data analyzed included ground-based experimental measurements and predicted concentrations by the CALIOPE air quality modelling system at three horizontal resolutions (Europe at 12 × 12 km2, Iberian Peninsula at 4 × 4 km2 and Catalonia at 1 × 1 km2). Results obtained in the analysis of these different data sets allowed a better understanding of O3 and NO2 concentration changes as a sum of a small number of different contributions related to daily sunlight radiation, seasonal dynamics, traffic emission patterns, and local station environments (urban, suburban and rural). The evaluation of O3 and NO2 concentrations predicted by the CALIOPE system revealed some differences among data sets at different spatial resolutions. NO2 predictions, showed in general a better performance than O3 predictions for the three model resolutions, specially at urban stations. Our results confirmed that the application of the trilinearity constraint during the multivariate curve resolution factor analysis decomposition of the analyzed data sets is a useful tool to facilitate the understanding of the resolved variability sources. SP and RT would like to acknowledge the Spanish Ministerio de Ciencia e Innovación for the project PID2019-105732GB-C21. SP and RT work at IDAEA-CSIC which is a Center of Excellence Severo Ochoa (Spanish Ministry of Science and Innovation, Project CEX2018-000794-S). MTP would like to acknowledge the Spanish Ministry of Economy and Competitiveness and FEDER funds under the PAISA (CGL2016-75725-R) project. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect