Multimedia modelers from the United States Environmental Protection Agency (EPA) and the United States Department of Energy (DOE) collaborated to conduct a detailed and quantitative benchmarking analysis of three multimedia models. The three models--RESRAD (DOE), MMSOILS (EPA), and MEPAS (DOE)--represent analytically-based tools that are used by the respective agencies for performing human exposure and health risk assessments. The study is performed by individuals who participate directly in the ongoing design, development, and application of the models. Model form and function are compared by applying the models to a series of hypothetical problems, first isolating individual modules (e.g., atmospheric, surface water, groundwater) and then simulating multimedia-based risk resulting from contaminant release from a single source to multiple environmental media. Study results show that the models differ with respect to environmental processes included (i.e., model features) and the mathematical formulation and assumptions related to the implementation of solutions. Depending on the application, numerical estimates resulting from the models may vary over several orders-of-magnitude. On the other hand, two or more differences may offset each other such that model predictions are virtually equal. The conclusion from these results is that multimedia models are complex due to the integration of the many components of a risk assessment and this complexity must be fully appreciated during each step of the modeling process (i.e., model selection, problem conceptualization, model application, and interpretation of results).
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http://dx.doi.org/10.1111/j.1539-6924.1997.tb00859.x | DOI Listing |
J Environ Qual
March 2025
College of Science, Inner Mongolia University of Technology, Hohhot, China.
Climate change, driven by greenhouse gas emissions, has emerged as a pressing global ecological and environmental challenge. Our study is dedicated to exploring the various factors influencing greenhouse gas emissions from animal husbandry and predicting their future trends. To this end, we have analyzed data from China's Inner Mongolia Autonomous Region spanning from 1978 to 2022, aiming to estimate the carbon emissions associated with animal husbandry in the region.
View Article and Find Full Text PDFJ Colloid Interface Sci
March 2025
Battery Research Center of Green Energy, Ming Chi University of Technology, New Taipei City 24301, Taiwan, ROC; Department of Chemical Engineering, Ming Chi University of Technology, New Taipei City 24301, Taiwan, ROC; Department of Chemical and Materials Engineering & Center for Sustainability and Energy Technologies, Chang Gung University, Taoyuan City 333, Taiwan, ROC. Electronic address:
Lithium has become a critical element in the modern era due to the emergence of lithium-ion battery (LIB) technologies as a mean to lessen the environmental burden created by the energy usage from conventional sources. In this study, LiCO was obtained from spent LIBs using a hydrometallurgical method and sintered with Taylor Flow Reactor (TFR) synthesized NiMn(OH) precursor to synthesize high-voltage LiNiMnO (R-LNMO) cathode material for the first time and conducted a series of tests and inspections for structure, morphology, electrochemical lithium cycling behaviour and its controlling factors, electronic conductivity, lithium ion diffusion characteristics and self-discharge behaviour. The results are benchmarked with C-LNMO synthesized through a similar processing but using LiCO obtained from a commercial source.
View Article and Find Full Text PDFWater Res
March 2025
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, PR China. Electronic address:
Accurate wave propagation models are essential for effective monitoring and automated localization in water supply pipelines. The recently-established Physics-Informed Neural Networks (PINNs) can enhance the wave analysis and reduce uncertainties by integrating mathematical models with sensor data. However, the application of PINN in modelling transient waves remains limited to the time domain, though frequency domain models are preferred for system identification due to their sensitivity to anomalies.
View Article and Find Full Text PDFMol Inform
March 2025
Faculty of Information Technology, HUTECH University, Ho Chi Minh City, Vietnam.
Within a recent decade, graph neural network (GNN) has emerged as a powerful neural architecture for various graph-structured data modelling and task-driven representation learning problems. Recent studies have highlighted the remarkable capabilities of GNNs in handling complex graph representation learning tasks, achieving state-of-the-art results in node/graph classification, regression, and generation. However, most traditional GNN-based architectures like GCN and GraphSAGE still faced several challenges related to the capability of preserving the multi-scaled topological structures.
View Article and Find Full Text PDFJ Am Acad Orthop Surg
March 2025
From the Yale School of Medicine, New Haven, CT (Kammien and Yu), theDivision of Plastic and Reconstructive Surgery, Department of Surgery, Yale School of Medicine, New Haven, CT (Zhao and Colen), and Department of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT (Grauer).
Background: Single-institution studies demonstrate reduced cost and similar outcomes for wide-awake fasciectomy compared with those with standard anesthesia. This retrospective cohort study examines these findings on a national level, comparing adverse events and cost for partial fasciectomies performed wide-awake and with standard anesthesia.
Methods: Partial fasciectomies were identified in the 2010-2022 PearlDiver database.
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