Temporal patterns and trends of particulate matter over Portugal: a long-term analysis of background concentrations
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Air quality management regarding PM concentrations in the atmosphere is a complex problem to tackle. In this paper, we aim to characterize the temporal patterns and trends of aerosol background levels over Portugal. Hourly data from the national air quality monitoring network, gathered from 2007 to 2016, is analyzed using statistical methods. Data from 20 monitoring stations was processed to prepare datasets with different time scales, and results were grouped by their type of surrounding area (urban, suburban, or rural). Urban and suburban background sites are characterized by strong seasonal patterns, with higher monthly mean concentrations in winter than in summer. In contrast, rural background PM10 concentrations are highest during August and September. This study suggests that urban background concentrations are significantly influenced by anthropogenic non-combustion sources, which contribute to the coarser aerosol fraction (PMc). PMc is about 3 μg m−3 higher during weekdays than during Sundays, at urban sites. However, there is no clear relationship between the value of the PM2.5/PMc ratio and the type of monitoring station. During the 10-year period of study, a decrease of 1.83, 3.58, and 4.89%/year was registered in PM10 concentrations at Portuguese rural, urban, and suburban areas, respectively. Despite the higher decrease at suburban monitoring stations, those sites present the highest 10-year mean PM10 concentrations. This work provides an import insight on temporal variations of PM10, PM2.5, and PMc concentrations over Portugal and summarizes trends through the last decade, contributing to the discussion on sources and processes influencing those concentrations.
KeywordsParticulate matter Portugal Seasonal patterns Air quality PM2.5/PMc ratio
Thanks are due to the Portuguese Agency for the Environment (APA) and the Regional Coordination and Development Commissions (CCDRs) for their effort in establishing and maintaining the air quality monitoring sites used in this investigation.
The authors gratefully acknowledge FCT—Portuguese Foundation for Science and Technology and FEDER (within the PT2020 Partnership Agreement and Compete 2020) for financing the PhD fellowship of C. Gama (SFRH/BD/87468/2012), the AIRSHIP research project (PTDC/AAG- MAA/1581/2014), and CESAM (UID/AMB/50017—POCI-01-0145-FEDER-007638) associated laboratory.
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