The use of coal as a fuel in utility and other industries in the United States is increasing. Typically, these utilities store their coal outdoors in large piles, and rainfall on the piles produces a runoff containing hazardous inorganic and organic materials. Four coals of varying sulfur contents, all used for fuel in the United States, were tested. Organic materials were extracted from simulated runoffs of model coal piles and were tested for mutagenicity with a Salmonella/microsomal assay and for clastogenicity and cytotoxicity in Chinese hamster ovary cells. The extracts of the high-sulfur coals and the lignite were more mutagenic and clastogenic than extracts from the low-sulfur coal.
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http://dx.doi.org/10.1002/tcm.1770040206 | DOI Listing |
Environ Sci Pollut Res Int
January 2025
Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China.
Land use changes profoundly affect hydrological processes and water quality at various scales, necessitating a comprehensive understanding of sustainable water resource management. This paper investigates the implications of land use alterations in the Gap-Cheon watershed, analyzing data from 2012 and 2022 and predicting changes up to 2052 using the Future Land Use Simulation (FLUS) model. The study employs the Hydrological Simulation Program-FORTRAN (HSPF) model to assess water quantity and quality dynamics.
View Article and Find Full Text PDFSci Data
January 2025
Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC, Canada.
This dataset contains outputs from a calibrated version of the GEM-Hydro model developed at Environment and Climate Change Canada (ECCC) and is available on the Federated Research Data Repository. The dataset covers the basins of the Laurentian Great Lakes and the Ottawa River and extends over the period 2001-2018. The data consist of all variables (hourly fluxes and state variables) related to the water balance of GEM-Hydro's land-surface scheme (including precipitation, surface and sub-surface runoff, drainage, evaporation, snow water equivalent, soil moisture…) and mean daily streamflow at 212 gauge locations.
View Article and Find Full Text PDFSci Rep
January 2025
UNESCO Centre of Water Law, Policy & Science, University of Dundee, Dundee, UK.
Understanding snow and ice melt dynamics is vital for flood risk assessment and effective water resource management in populated river basins sourced in inaccessible high-mountains. This study provides an AI-enabled hybrid approach integrating glacio-hydrological model outputs (GSM-SOCONT), with different machine learning and deep learning techniques framed as alternative 'computational scenarios, leveraging both physical processes and data-driven insights for enhanced predictive capabilities. The standalone deep learning model (CNN-LSTM), relying solely on meteorological data, outperformed its counterpart machine learning and glacio-hydrological model equivalents.
View Article and Find Full Text PDFSci Rep
January 2025
Business School, Sichuan University, 610059, Chengdu, China.
The comprehensive benefit evaluation of LID based on multi-criteria decision-making methods faces technical issues such as the uncertainties and vagueness in hybrid information sources, which can affect the overall evaluation results and ranking of alternatives. This study introduces a multi-indicator fuzzy comprehensive benefit evaluation approach for the selection of LID measures, aiming to provide a robust and holistic framework for evaluating their benefits at the community level. The proposed methodology integrates quantitative environmental and economic indicators with qualitative social benefit indicators, combining the use of the Storm Water Management Model (SWMM) and ArcGIS for scenario-based analysis, and the use of hesitant fuzzy language sets and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for decision-making.
View Article and Find Full Text PDFJ Contam Hydrol
January 2025
USDA ARS, National Soil Erosion Research Laboratory, West Lafayette, IN 47907, United States of America.
Agricultural phosphorus (P) losses may result from either recently applied fertilizers or from P accumulated in soil and sediment. While both P sources pose an environmental risk to freshwater systems, differentiating between sources is crucial for identifying and implementing management practices to decrease loss. In this study, laboratory rainfall simulations were completed on runoff boxes and undisturbed soil columns before and after fertilizer application.
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