Spatial Modeling of Trace Element Concentrations in PM<sub>10</sub> Using Generalized Additive Models (GAMs)
GAMs were implemented to evaluate the spatial variation in concentrations of 33 elements in PM<sub>10</sub>, in their water-soluble and insoluble fractions used as tracers for different emission sources. Data were collected during monitoring campaigns (November 2016–February 2018) in the...
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MDPI AG
2025-04-01
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| Online Access: | https://www.mdpi.com/2073-4433/16/4/464 |
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| author | Mariacarmela Cusano Alessandra Gaeta Raffaele Morelli Giorgio Cattani Silvia Canepari Lorenzo Massimi Gianluca Leone |
| author_facet | Mariacarmela Cusano Alessandra Gaeta Raffaele Morelli Giorgio Cattani Silvia Canepari Lorenzo Massimi Gianluca Leone |
| author_sort | Mariacarmela Cusano |
| collection | DOAJ |
| description | GAMs were implemented to evaluate the spatial variation in concentrations of 33 elements in PM<sub>10</sub>, in their water-soluble and insoluble fractions used as tracers for different emission sources. Data were collected during monitoring campaigns (November 2016–February 2018) in the Terni basin (an urban and industrial hotspot of Central Italy), using an innovative experimental approach based on high-spatial-resolution (23 sites, approximately 1 km apart) monthly samplings and the chemical characterization of PM<sub>10</sub>. For each element, a model was developed using monthly mean concentrations as the response variable. As covariates, the temporal predictors included meteorological parameters (temperature, relative humidity, wind speed and direction, irradiance, precipitation, planet boundary layer height), while the spatial predictors encompassed distances from major sources, road length, building heights, land use variables, imperviousness, and population. A stepwise procedure was followed to determine the model with the optimal set of covariates. A leave-one-out cross-validation method was used to estimate the prediction error. Statistical indicators (Adjusted R-Squared, RMSE, FAC2, FB) were used to evaluate the performance of the GAMs. The spatial distribution of the fitted values of PM<sub>10</sub> and its elemental components, weighted over all sampling periods, was mapped at a resolution of 100 m. |
| format | Article |
| id | doaj-art-694a4a734bb648a08ba247f8bd1f22d6 |
| institution | OA Journals |
| issn | 2073-4433 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-694a4a734bb648a08ba247f8bd1f22d62025-08-20T02:17:19ZengMDPI AGAtmosphere2073-44332025-04-0116446410.3390/atmos16040464Spatial Modeling of Trace Element Concentrations in PM<sub>10</sub> Using Generalized Additive Models (GAMs)Mariacarmela Cusano0Alessandra Gaeta1Raffaele Morelli2Giorgio Cattani3Silvia Canepari4Lorenzo Massimi5Gianluca Leone6Department for Environmental Assessment, Monitoring and Sustainability, Italian Institute for Environmental Protection and Research (ISPRA), 00144 Rome, ItalyDepartment for Environmental Assessment, Monitoring and Sustainability, Italian Institute for Environmental Protection and Research (ISPRA), 00144 Rome, ItalyDepartment for Environmental Assessment, Monitoring and Sustainability, Italian Institute for Environmental Protection and Research (ISPRA), 00144 Rome, ItalyDepartment for Environmental Assessment, Monitoring and Sustainability, Italian Institute for Environmental Protection and Research (ISPRA), 00144 Rome, ItalyDepartment of Environmental Biology (DBA), Sapienza University of Rome, P. le Aldo Moro, 5, 00185 Rome, ItalyDepartment of Environmental Biology (DBA), Sapienza University of Rome, P. le Aldo Moro, 5, 00185 Rome, ItalyDepartment for Environmental Assessment, Monitoring and Sustainability, Italian Institute for Environmental Protection and Research (ISPRA), 00144 Rome, ItalyGAMs were implemented to evaluate the spatial variation in concentrations of 33 elements in PM<sub>10</sub>, in their water-soluble and insoluble fractions used as tracers for different emission sources. Data were collected during monitoring campaigns (November 2016–February 2018) in the Terni basin (an urban and industrial hotspot of Central Italy), using an innovative experimental approach based on high-spatial-resolution (23 sites, approximately 1 km apart) monthly samplings and the chemical characterization of PM<sub>10</sub>. For each element, a model was developed using monthly mean concentrations as the response variable. As covariates, the temporal predictors included meteorological parameters (temperature, relative humidity, wind speed and direction, irradiance, precipitation, planet boundary layer height), while the spatial predictors encompassed distances from major sources, road length, building heights, land use variables, imperviousness, and population. A stepwise procedure was followed to determine the model with the optimal set of covariates. A leave-one-out cross-validation method was used to estimate the prediction error. Statistical indicators (Adjusted R-Squared, RMSE, FAC2, FB) were used to evaluate the performance of the GAMs. The spatial distribution of the fitted values of PM<sub>10</sub> and its elemental components, weighted over all sampling periods, was mapped at a resolution of 100 m.https://www.mdpi.com/2073-4433/16/4/464air pollutionPM<sub>10</sub>elementssource tracergeneralized additive model (GAM)spatial mapping |
| spellingShingle | Mariacarmela Cusano Alessandra Gaeta Raffaele Morelli Giorgio Cattani Silvia Canepari Lorenzo Massimi Gianluca Leone Spatial Modeling of Trace Element Concentrations in PM<sub>10</sub> Using Generalized Additive Models (GAMs) Atmosphere air pollution PM<sub>10</sub> elements source tracer generalized additive model (GAM) spatial mapping |
| title | Spatial Modeling of Trace Element Concentrations in PM<sub>10</sub> Using Generalized Additive Models (GAMs) |
| title_full | Spatial Modeling of Trace Element Concentrations in PM<sub>10</sub> Using Generalized Additive Models (GAMs) |
| title_fullStr | Spatial Modeling of Trace Element Concentrations in PM<sub>10</sub> Using Generalized Additive Models (GAMs) |
| title_full_unstemmed | Spatial Modeling of Trace Element Concentrations in PM<sub>10</sub> Using Generalized Additive Models (GAMs) |
| title_short | Spatial Modeling of Trace Element Concentrations in PM<sub>10</sub> Using Generalized Additive Models (GAMs) |
| title_sort | spatial modeling of trace element concentrations in pm sub 10 sub using generalized additive models gams |
| topic | air pollution PM<sub>10</sub> elements source tracer generalized additive model (GAM) spatial mapping |
| url | https://www.mdpi.com/2073-4433/16/4/464 |
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