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Registro Completo |
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
14/11/2014 |
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Data da última atualização: |
04/01/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
PARAIBA, L. C.; PAZIANOTTO, R. A. A.; LUIZ, A. J. B.; MAIA, A. de H. N.; JONSSON, C. M. |
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Afiliação: |
LOURIVAL COSTA PARAIBA, CNPMA; RICARDO ANTONIO ALMEIDA PAZIANOTTO, CNPMA; ALFREDO JOSE BARRETO LUIZ, CNPMA; ALINE DE HOLANDA NUNES MAIA, CNPMA; CLAUDIO MARTIN JONSSON, CNPMA. |
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Título: |
A mathematical model to estimate the volume of grey water of pesticide mixtures. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Spanish Journal of Agricultural Research, Madrid, v. 12, n. 2, p. 509-518, 2014. |
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Idioma: |
Inglês |
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Conteúdo: |
The usual method to calculate grey water footprint does not take into account the volume of water required to dilute concentrations of pesticide mixtures in freshwater and it also depends on maximum concentration limit acceptable in water. We propose a model to estimate the grey water footprint of crops by calculating the volume of water necessary to dilute pesticide mixtures reaching freshwaters. The model requires short-term toxicity data from aquatic organisms based on EC50 values, soil pesticide half-life and soil sorption coefficient values, and does not require maximum concentration limit acceptable in water. The lixiviation rate and runoff rate of each pesticide was estimated by attenuation factor and by Soilfug model, respectively. The usefulness of the proposed model was illustrated by estimating the volume of grey water required to dilute the 17 most widely used herbicides in sugarcane crops of Brazil. The grey water footprint corresponding to the recommended agronomic dose for each herbicide varied between 4.20×106 m3 yr-1 and 1.20×1012 m3 yr-1 and the grey water footprint of the mixture of herbicides was 2.36×1012 m3 yr-1 in a cultivated area of 8.4×106 ha. These results establish the ranking position of each herbicide in the composition of the grey water footprint of mixture of herbicides. The rank of each herbicide could be used to create a label to be placed on the package of the pesticide, thus informing farmers about the volume of grey water per hectare due to the use of this herbicide. MenosThe usual method to calculate grey water footprint does not take into account the volume of water required to dilute concentrations of pesticide mixtures in freshwater and it also depends on maximum concentration limit acceptable in water. We propose a model to estimate the grey water footprint of crops by calculating the volume of water necessary to dilute pesticide mixtures reaching freshwaters. The model requires short-term toxicity data from aquatic organisms based on EC50 values, soil pesticide half-life and soil sorption coefficient values, and does not require maximum concentration limit acceptable in water. The lixiviation rate and runoff rate of each pesticide was estimated by attenuation factor and by Soilfug model, respectively. The usefulness of the proposed model was illustrated by estimating the volume of grey water required to dilute the 17 most widely used herbicides in sugarcane crops of Brazil. The grey water footprint corresponding to the recommended agronomic dose for each herbicide varied between 4.20×106 m3 yr-1 and 1.20×1012 m3 yr-1 and the grey water footprint of the mixture of herbicides was 2.36×1012 m3 yr-1 in a cultivated area of 8.4×106 ha. These results establish the ranking position of each herbicide in the composition of the grey water footprint of mixture of herbicides. The rank of each herbicide could be used to create a label to be placed on the package of the pesticide, thus informing farmers about the volume of grey water per hectare due ... Mostrar Tudo |
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Palavras-Chave: |
Cana-de-açúcar; Pesticide management; Water quality objective. |
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Thesagro: |
Agrotóxico; Herbicida; Modelo matemático; Qualidade da água. |
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Thesaurus Nal: |
Environmental impact; Herbicides; Mathematical models; Sugarcane; Water footprint; Water quality. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/111687/1/2014AP013.pdf
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Marc: |
LEADER 02495naa a2200325 a 4500
001 2000149
005 2023-01-04
008 2014 bl uuuu u00u1 u #d
100 1 $aPARAIBA, L. C.
245 $aA mathematical model to estimate the volume of grey water of pesticide mixtures.$h[electronic resource]
260 $c2014
520 $aThe usual method to calculate grey water footprint does not take into account the volume of water required to dilute concentrations of pesticide mixtures in freshwater and it also depends on maximum concentration limit acceptable in water. We propose a model to estimate the grey water footprint of crops by calculating the volume of water necessary to dilute pesticide mixtures reaching freshwaters. The model requires short-term toxicity data from aquatic organisms based on EC50 values, soil pesticide half-life and soil sorption coefficient values, and does not require maximum concentration limit acceptable in water. The lixiviation rate and runoff rate of each pesticide was estimated by attenuation factor and by Soilfug model, respectively. The usefulness of the proposed model was illustrated by estimating the volume of grey water required to dilute the 17 most widely used herbicides in sugarcane crops of Brazil. The grey water footprint corresponding to the recommended agronomic dose for each herbicide varied between 4.20×106 m3 yr-1 and 1.20×1012 m3 yr-1 and the grey water footprint of the mixture of herbicides was 2.36×1012 m3 yr-1 in a cultivated area of 8.4×106 ha. These results establish the ranking position of each herbicide in the composition of the grey water footprint of mixture of herbicides. The rank of each herbicide could be used to create a label to be placed on the package of the pesticide, thus informing farmers about the volume of grey water per hectare due to the use of this herbicide.
650 $aEnvironmental impact
650 $aHerbicides
650 $aMathematical models
650 $aSugarcane
650 $aWater footprint
650 $aWater quality
650 $aAgrotóxico
650 $aHerbicida
650 $aModelo matemático
650 $aQualidade da água
653 $aCana-de-açúcar
653 $aPesticide management
653 $aWater quality objective
700 1 $aPAZIANOTTO, R. A. A.
700 1 $aLUIZ, A. J. B.
700 1 $aMAIA, A. de H. N.
700 1 $aJONSSON, C. M.
773 $tSpanish Journal of Agricultural Research, Madrid$gv. 12, n. 2, p. 509-518, 2014.
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Embrapa Meio Ambiente (CNPMA) |
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