Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI's assessment.
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http://dx.doi.org/10.1080/10473289.2005.10464676 | DOI Listing |
Expert Opin Biol Ther
January 2025
OU Stephenson Cancer Center, Oklahoma City.
Introduction: Antibody-drug conjugates (ADCs) are a rapidly evolving class of anti-cancer drugs with a significant impact on management of hematological malignancies including diffuse large B-cell lymphoma (DLBCL). ADCs combine a cytotoxic drug (a.k.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Departamento de Geografía, Facultad de Ciencias, Universidad de la República, Montevideo 4225, Uruguay.
Recent advancements in Earth Observation sensors, improved accessibility to imagery and the development of corresponding processing tools have significantly empowered researchers to extract insights from Multisource Remote Sensing. This study aims to use these technologies for mapping summer and winter Land Use/Land Cover features in Cuenca de la Laguna Merín, Uruguay, while comparing the performance of Random Forests, Support Vector Machines, and Gradient-Boosting Tree classifiers. The materials include Sentinel-2, Sentinel-1 and Shuttle Radar Topography Mission imagery, Google Earth Engine, training and validation datasets and quoted classifiers.
View Article and Find Full Text PDFSci Rep
January 2025
Conservative Dentistry Department, Faculty of Dentistry, Mansoura University, Mansoura, Egypt.
The main objective of the current study is to compare short-term fluoride release of three ion releasing restorative materials and assess their inhibitory effect on secondary caries. Materials used in this study included, Self-adhesive hybrid composite (group A), Ion releasing flowable composite liner (group B), and alkasite restorative material (group C). Twenty-two discs were fabricated from each material for short-term fluoride release test, conducted on days 1, 7, and 14.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Natural Resources Management, Irrigation, and Salinity Program, Arba Minch Agricultural Research Center, PO.BOX, 2228, Arba Minch, Ethiopia.
This study investigated the distribution of salinity and sodicity in the irrigated areas of Abaya Chamo. Representative water and soil samples were collected from different soil depths (0-30 cm and 30-60 cm). Sodium absorption ratio (SAR), electrical conductivity (Ec), pH, exchange sodium, magnesium, calcium, and potassium cations, and exchange sodium percentage (ESP) of the sampled sites were analyzed for soil salinity classification and severity analysis.
View Article and Find Full Text PDFChaos
January 2025
Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana, Slovenia.
Detecting directional couplings from time series is crucial in understanding complex dynamical systems. Various approaches based on reconstructed state-spaces have been developed for this purpose, including a cross-distance vector measure, which we introduced in our recent work. Here, we devise two new cross-vector measures that utilize ranks and time series estimates instead of distances.
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