Low-Cost Air Quality Stations’ Capability to Integrate Reference Stations in Particulate Matter Dynamics Assessment
Lorenzo Brilli,
Federico Carotenuto,
Bianca Patrizia Andreini,
Alice Cavaliere,
Andrea Esposito,
Beniamino Gioli,
Francesca Martelli,
Marco Stefanelli,
Carolina Vagnoli,
Stefania Venturi,
Alessandro Zaldei,
Giovanni Gualtieri
Affiliations
Lorenzo Brilli
CNR-IBE, National Research Council Institute for the BioEconomy, Via Caproni 8, 50145 Firenze, Italy
Federico Carotenuto
CNR-IBE, National Research Council Institute for the BioEconomy, Via Caproni 8, 50145 Firenze, Italy
Bianca Patrizia Andreini
ARPAT, Tuscany Region Environmental Protection Agency, Via Porpora, 22, 50144 Firenze, Italy
Alice Cavaliere
CNR-IBE, National Research Council Institute for the BioEconomy, Via Caproni 8, 50145 Firenze, Italy
Andrea Esposito
CNR-ISAFOM, National Research Council Institute of Mediterranean Agricultural and Forestry Systems, P. le Enrico Fermi 1—Loc. Porto del Granatello, 80055 Portici, Italy
Beniamino Gioli
CNR-IBE, National Research Council Institute for the BioEconomy, Via Caproni 8, 50145 Firenze, Italy
Francesca Martelli
CNR-IBE, National Research Council Institute for the BioEconomy, Via Caproni 8, 50145 Firenze, Italy
Marco Stefanelli
ARPAT, Tuscany Region Environmental Protection Agency, Via Porpora, 22, 50144 Firenze, Italy
Carolina Vagnoli
CNR-IBE, National Research Council Institute for the BioEconomy, Via Caproni 8, 50145 Firenze, Italy
Stefania Venturi
DST-Unifi, Department of Earth Sciences, University of Florence, Via G. La Pira 4, 50121 Firenze, Italy
Alessandro Zaldei
CNR-IBE, National Research Council Institute for the BioEconomy, Via Caproni 8, 50145 Firenze, Italy
Giovanni Gualtieri
CNR-IBE, National Research Council Institute for the BioEconomy, Via Caproni 8, 50145 Firenze, Italy
Low-cost air quality stations can provide useful data that can offer a complete picture of urban air quality dynamics, especially when integrated with daily measurements from reference air quality stations. However, the success of such deployment depends on the measurement accuracy and the capability of resolving spatial and temporal gradients within a spatial domain. In this work, an ensemble of three low-cost stations named “AirQino” was deployed to monitor particulate matter (PM) concentrations over three different sites in an area affected by poor air quality conditions. Data of PM2.5 and PM10 concentrations were collected for about two years following a protocol based on field calibration and validation with a reference station. Results indicated that: (i) AirQino station measurements were accurate and stable during co-location periods over time (R2 = 0.5–0.83 and RMSE = 6.4–11.2 μg m−3; valid data: 87.7–95.7%), resolving current spatial and temporal gradients; (ii) spatial variability of anthropogenic emissions was mainly due to extensive use of wood for household heating; (iii) the high temporal resolution made it possible to detect time occurrence and strength of PM10 concentration peaks; (iv) the number of episodes above the 1-h threshold of 90 μg m−3 and their persistence were higher under urban and industrial sites compared to the rural area.