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Evaluation of the methods for quantifying particle wash-off loadings in urban impervious surfaces at small scales.
Environ Sci Pollut Res Int ; 25(7): 6969-6979, 2018 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-29273986
ABSTRACT
Quantifying road-deposited sediment (RDS) wash-off is critical in estimating pollutant load and for supporting the designs of urban storm water low-impact development (LID) best management practices (BMPs). The objective of this study was to identify a simple and effective small-scale wash-off load estimation and prediction method suitable for BMP engineering. The reliabilities, complexities, and applicabilities of four prediction methods (i.e., the event mean concentration (EMC) equation method, the exponential equation method, and the RDS mass difference before and after rainfall event method, and the RDS index model) were tested for three sites (i.e., a newly built area, and built-up area, and conservation area) during five natural rainfall events. Taking the calculations by the EMC method as standard results revealed the following. (1) The degree of agreement of the methods with the standard results in descending order was exponential equation method > RDS index model > RDS mass difference. (2) The degree of complexity of the studied methods in descending order was exponential equation method > the EMC equation method > the RDS index model > the RDS mass difference. (3) When considering the applicability of the models in terms of LID-BMP engineering, the RDS index model could be considered optimal for supporting the design of urban storm water BMPs.
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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Assunto principal: Chuva / Movimentos da Água / Poluentes Químicos da Água / Monitoramento Ambiental / Material Particulado / Modelos Teóricos Aspecto clínico: Predição / Prognóstico País/Região como assunto: Ásia Idioma: Inglês Revista: Environ Sci Pollut Res Int Assunto da revista: Saúde Ambiental / Toxicologia Ano de publicação: 2018 Tipo de documento: Artigo País de afiliação: China