Sensors Network as an Added Value for the Characterization of Spatial and Temporal Air Quality Patterns at the Urban Scale

Author:

Graça Daniel1ORCID,Reis Johnny1ORCID,Gama Carla1ORCID,Monteiro Alexandra1ORCID,Rodrigues Vera1ORCID,Rebelo Micael1ORCID,Borrego Carlos1ORCID,Lopes Myriam1ORCID,Miranda Ana Isabel1ORCID

Affiliation:

1. Centre for Environmental and Marine Studies (CESAM), Department of Environment and Planning, University of Aveiro, 3810-193 Aveiro, Portugal

Abstract

Within the scope of the Aveiro STEAM City project, an air quality monitoring network was installed in the city of Aveiro (Portugal), to evaluate the potential of sensors to characterize spatial and temporal patterns of air quality in the city. The network consists of nine sensors stations with air quality sensors (PM10, PM2.5, NO2, O3 and CO) and two meteorological stations, distributed within selected locations in the city of Aveiro. The analysis of the data was done for a one-year measurement period, from June 2020 to May 2021, using temporal profiles, statistical comparisons with reference stations and Air Quality Indexes (AQI). The analysis of sensors data indicated that air quality variability exists for all pollutants and stations. The majority of the study area is characterized by good air quality, but specific areas—associated with hotspot traffic zones—exhibit medium, poor and bad air quality more frequently. The daily patterns registered are significantly different between the affected and non-affected road traffic sites, mainly for PM and NO2 pollutants. The weekly profile, significative deltas are found between week and weekend: NO2 is reduced on the weekends at traffic sites, but PM10 is higher in specific areas during winter weekends, which is explained by residential combustion sources.

Funder

European Regional Development Fund – ERDF

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Using synthetic data to benchmark correction methods for low-cost air quality sensor networks;Air Quality, Atmosphere & Health;2024-01-16

2. Road traffic noise monitoring in a Smart City: Sensor and Model-Based approach;Transportation Research Part D: Transport and Environment;2023-12

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