Modeling is a cost-effective measure to estimate ultrafine particle (UFP) levels. Previous UFP estimates generally relied on land-use regression with insufficient temporal resolution. We carried out in-situ measurements for UFP in central Taiwan and developed a model incorporating satellite-based measurements, meteorological variables, and land-use data to estimate daily UFP levels at a 1-km resolution. Two sampling campaigns were conducted for measuring hourly UFP concentrations at six sites between 2008-2010 and 2017-2021, respectively, using scanning mobility particle sizers. Three machine learning algorithms, namely random forest, eXtreme gradient boosting (XGBoost), and deep neural network, were used to develop UFP estimation models. The performances were evaluated with a 10-fold cross-validation, temporal, and spatial validation. A total of 1,022 effective sampling days were conducted. The XGBoost model had the best performance with a training coefficient of determination (R) of 0.99 [normalized root mean square error (nRMSE): 6.52%] and a cross-validation R of 0.78 (nRMSE: 31.0%). The ten most important variables were surface pressure, distance to the nearest road, temperature, calendar year, day of the year, NO, meridional wind, the total length of roads, PM, and zonal wind. The UFP levels were elevated along the main roads across different seasons, suggesting that traffic emission is an important contributor to UFP. This hybrid model outperformed prior land use regression models and thus can provide more accurate estimates of UFP for epidemiological studies.
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http://dx.doi.org/10.1016/j.envint.2023.107937 | DOI Listing |
Sci Total Environ
February 2025
Institute of Environmental Assessment and Water Research, Spanish Research Council (IDÆA-CSIC), c/Jordi Girona 18-26, 08034 Barcelona, Spain.
The maritime transport sector poses significant air quality concerns, particularly in nearby cities. Ultrafine particles (UFP, diameter < 100 nm) are of particular concern due to their potential health impacts. This study measured particle number concentrations (PNC), size distributions (PNSD), and other pollutants including particulate matter (PM), nitrogen oxides (NO), black carbon (BC), sulfur dioxide (SO) and ozone (O), organic markers and trace elements at a major European harbor and an urban background (UB) location.
View Article and Find Full Text PDFClin Nutr ESPEN
February 2025
Programa de Pós-Graduação em Nutrição, Escola Paulista de Medicina, Universidade Federal de São Paulo, Brazil. Electronic address:
Background & Aims: Eating habits during childhood have undergone significant changes, with a notable increase in the consumption of ultra-processed foods (UPF). This situation deserves attention, given the close relationship between UPF and adverse health outcomes. This is due to the nutritional composition of UPF, which has high levels of health-critical nutrients such as sugar, fat, and sodium, thus compromising the overall quality of the diet.
View Article and Find Full Text PDFChemosphere
January 2025
Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, FISABIO-Public Health, 21, Av. Catalunya, 46020, Valencia, Spain.
This work aims to establish a strategy to comprehensively assess the indoor air quality in schools including the analysis of chemical pollutants, bio-aerosols like fungi, bacteria and respiratory viruses and the identification of volatile and semi-volatile organic compounds applying non-targeted approaches. For this, a pilot study was performed in four primary schools from Spain, located in different urban and rural areas during different seasons. Common indoor pollutants, like CO NO, O, CO, particulate matter (PM, PM), ultrafine particles (UFP), total volatile organic compounds (TVOCs), and formaldehyde (HCHO), were assessed in terms of maximum recommended levels, daily variations, seasonality, and school location.
View Article and Find Full Text PDFHeliyon
December 2024
Unit of Occupational Health and Industrial Hygiene, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, 25121, Brescia, Italy.
Unlabelled: Welding fumes are a main source of occupational exposure to particulate matter (PM), besides gases and ultraviolet radiations, that involves millions of operators worldwide and is related to several health effects, including lung cancer. Our study aims to evaluate the exposure to fine and ultrafine airborne particulate in welding operators working in a steel making factory.In October 2019, air monitoring was performed for four days in five different welding scenarios and in the external area of a steelmaking factory to assess the exposure to airborne particles, ultrafine (UFP) particulate and inhalable fraction, during welding activities.
View Article and Find Full Text PDFEnviron Sci Technol
December 2024
Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, Ontario M5S 3H6, Canada.
Cannabis smoke is a complex aerosol mixture, featuring characteristic monoterpenes and sesquiterpenes which are susceptible to reaction with ozone and other oxidants. These reactions form less-volatile species which can contribute to secondary organic aerosol (SOA) and ultrafine particle (UFP) formation. In this work, the reaction of ozone with cannabis smoke was observed in an environmental chamber.
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