Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models

Stefan Platikanov,Marta Terrado,María Teresa Pay,Albert Soret,Romà Tauler

doi:10.1016/j.scitotenv.2021.150923

Abstract

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.

Highlights

Air pollution is a serious threat to both human and environmental health, being currently one of the most pressing challenges for cities in Europe and around the globe (EEA, 2019; World Health Organization (WHO), 2016)
The application of Multivariate Curve Resolution Alternating Least Squares (MCR-alternating least squares (ALS)) to the analysis of hourly measured O3 and NO2 concentrations at nineteen air quality monitoring stations across Catalonia, spatial resolutions in Catalonia (Spain), during 2015 allowed the resolution of three major variability contributions of these two pollutants, described by their hourly, daily, and spatial profiles, which can be correlated with the major physicochemical and pollution patterns acting over the investigated region
The results obtained by MCR-ALS analysis of the measured experimental data were compared with those obtained by the MCR-ALS analysis of the CALIOPE predicted data

Summary

Introduction

Air pollution is a serious threat to both human and environmental health, being currently one of the most pressing challenges for cities in Europe and around the globe (EEA, 2019; WHO, 2016). Having information about air pollution contributions and dynamics is essential to design adequate policies to improve air quality and reduce the negative impacts of pollution on health (European Environmental Agency (EEA), 2011; Nieuwenhuijsen, 2018). Monitoring and modelling of air pollutants are essential tasks to evaluate the impact from the continuous increase of human activities on the environment and public health. Current research efforts are mainly focused on the improvement of monitoring and modelling systems, and on accurately forecasting the behavior of hazardous air pollutants in order to understand their origin, transport, geographical distribution and time evolution (Schaap et al, 2015; Pay et al, 2019; Massagué et al, 2019). Ozone (O3) and nitrogen dioxide (NO2) are among the major air pollutants directly associated with negative effects on the human health (Bell et al, 2004; WHO, 2013; VicedoCabrera et al, 2020)

Methods

Results

Conclusion