Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models

The concept of gray water footprint (GWF) was introduced as an indicator of the volume of freshwater required to dilute the total pollutant load, generated from a particular production process, to maintain water quality standards. In crop production, for example, the theoretical calculation of the G...
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Gespeichert in:

Autor*in:	Barreto, Mikaela de Lavôr Paes [verfasserIn] Netto, André Maciel [verfasserIn] Silva, João Paulo Siqueira da [verfasserIn] Amaral, Ademir [verfasserIn] Borges, Edvane [verfasserIn] França, Elvis Joacir de [verfasserIn] Vale, Ricardo Lins [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Gray water footprint Pesticide Pesticide rank Water contamination

Übergeordnetes Werk:	Enthalten in: Journal of cleaner production - Amsterdam [u.a.] : Elsevier Science, 1993, 276
Übergeordnetes Werk:	volume:276

DOI / URN:	10.1016/j.jclepro.2020.124254

Katalog-ID:	ELV004821866

Internformat


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allfields	10.1016/j.jclepro.2020.124254 doi (DE-627)ELV004821866 (ELSEVIER)S0959-6526(20)34299-2 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Barreto, Mikaela de Lavôr Paes verfasserin aut Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The concept of gray water footprint (GWF) was introduced as an indicator of the volume of freshwater required to dilute the total pollutant load, generated from a particular production process, to maintain water quality standards. In crop production, for example, the theoretical calculation of the GWF can be employed as a sound tool for assessing the environmental impacts due to the use of pesticides. In this context, we compared two models for estimating the GWF of pesticide mixtures applied to the soil in a sugarcane crop, in Pernambuco, Brazil. One model was proposed by Hoekstra et al. (2011) and calculates the GWF based on the maximum concentration limit acceptable in water. The other one was designed by Paraiba et al. (2014) and employs the concept of Concentration Addition. This latter model also takes into account the effect of toxicity of pesticide mixtures on aquatic organisms and water quality, considering the characteristics of the soil and cultivation data obtained through the field and physical-chemical tests pesticides used in agricultural activities. The model of Paraiba et al. (2014) has shown to be more conservative in determining the GWF of the pesticide mixtures (2.00 × 107 m³ ha−1) in the aquatic ecosystem, than the model of Hoekstra et al. (2011) (6.25 × 105 m³ ha−1 for Sulfentrazone). The results presented and discussed in this study reinforce the use of the GWF as an indicator of water quality for agricultural sustainability. Our work also contributes to a better understanding of the advantages and limitations of each model approach in the assessment of the volume of freshwater needed to dilute the contaminant load in agriculture activities as, for instance, in sugarcane crops. Gray water footprint Pesticide Pesticide rank Water contamination Netto, André Maciel verfasserin aut Silva, João Paulo Siqueira da verfasserin aut Amaral, Ademir verfasserin aut Borges, Edvane verfasserin (orcid)0000-0001-7839-9945 aut França, Elvis Joacir de verfasserin aut Vale, Ricardo Lins verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 276 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:276 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 276
spelling	10.1016/j.jclepro.2020.124254 doi (DE-627)ELV004821866 (ELSEVIER)S0959-6526(20)34299-2 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Barreto, Mikaela de Lavôr Paes verfasserin aut Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The concept of gray water footprint (GWF) was introduced as an indicator of the volume of freshwater required to dilute the total pollutant load, generated from a particular production process, to maintain water quality standards. In crop production, for example, the theoretical calculation of the GWF can be employed as a sound tool for assessing the environmental impacts due to the use of pesticides. In this context, we compared two models for estimating the GWF of pesticide mixtures applied to the soil in a sugarcane crop, in Pernambuco, Brazil. One model was proposed by Hoekstra et al. (2011) and calculates the GWF based on the maximum concentration limit acceptable in water. The other one was designed by Paraiba et al. (2014) and employs the concept of Concentration Addition. This latter model also takes into account the effect of toxicity of pesticide mixtures on aquatic organisms and water quality, considering the characteristics of the soil and cultivation data obtained through the field and physical-chemical tests pesticides used in agricultural activities. The model of Paraiba et al. (2014) has shown to be more conservative in determining the GWF of the pesticide mixtures (2.00 × 107 m³ ha−1) in the aquatic ecosystem, than the model of Hoekstra et al. (2011) (6.25 × 105 m³ ha−1 for Sulfentrazone). The results presented and discussed in this study reinforce the use of the GWF as an indicator of water quality for agricultural sustainability. Our work also contributes to a better understanding of the advantages and limitations of each model approach in the assessment of the volume of freshwater needed to dilute the contaminant load in agriculture activities as, for instance, in sugarcane crops. Gray water footprint Pesticide Pesticide rank Water contamination Netto, André Maciel verfasserin aut Silva, João Paulo Siqueira da verfasserin aut Amaral, Ademir verfasserin aut Borges, Edvane verfasserin (orcid)0000-0001-7839-9945 aut França, Elvis Joacir de verfasserin aut Vale, Ricardo Lins verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 276 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:276 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 276
allfields_unstemmed	10.1016/j.jclepro.2020.124254 doi (DE-627)ELV004821866 (ELSEVIER)S0959-6526(20)34299-2 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Barreto, Mikaela de Lavôr Paes verfasserin aut Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The concept of gray water footprint (GWF) was introduced as an indicator of the volume of freshwater required to dilute the total pollutant load, generated from a particular production process, to maintain water quality standards. In crop production, for example, the theoretical calculation of the GWF can be employed as a sound tool for assessing the environmental impacts due to the use of pesticides. In this context, we compared two models for estimating the GWF of pesticide mixtures applied to the soil in a sugarcane crop, in Pernambuco, Brazil. One model was proposed by Hoekstra et al. (2011) and calculates the GWF based on the maximum concentration limit acceptable in water. The other one was designed by Paraiba et al. (2014) and employs the concept of Concentration Addition. This latter model also takes into account the effect of toxicity of pesticide mixtures on aquatic organisms and water quality, considering the characteristics of the soil and cultivation data obtained through the field and physical-chemical tests pesticides used in agricultural activities. The model of Paraiba et al. (2014) has shown to be more conservative in determining the GWF of the pesticide mixtures (2.00 × 107 m³ ha−1) in the aquatic ecosystem, than the model of Hoekstra et al. (2011) (6.25 × 105 m³ ha−1 for Sulfentrazone). The results presented and discussed in this study reinforce the use of the GWF as an indicator of water quality for agricultural sustainability. Our work also contributes to a better understanding of the advantages and limitations of each model approach in the assessment of the volume of freshwater needed to dilute the contaminant load in agriculture activities as, for instance, in sugarcane crops. Gray water footprint Pesticide Pesticide rank Water contamination Netto, André Maciel verfasserin aut Silva, João Paulo Siqueira da verfasserin aut Amaral, Ademir verfasserin aut Borges, Edvane verfasserin (orcid)0000-0001-7839-9945 aut França, Elvis Joacir de verfasserin aut Vale, Ricardo Lins verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 276 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:276 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 276
allfieldsGer	10.1016/j.jclepro.2020.124254 doi (DE-627)ELV004821866 (ELSEVIER)S0959-6526(20)34299-2 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Barreto, Mikaela de Lavôr Paes verfasserin aut Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The concept of gray water footprint (GWF) was introduced as an indicator of the volume of freshwater required to dilute the total pollutant load, generated from a particular production process, to maintain water quality standards. In crop production, for example, the theoretical calculation of the GWF can be employed as a sound tool for assessing the environmental impacts due to the use of pesticides. In this context, we compared two models for estimating the GWF of pesticide mixtures applied to the soil in a sugarcane crop, in Pernambuco, Brazil. One model was proposed by Hoekstra et al. (2011) and calculates the GWF based on the maximum concentration limit acceptable in water. The other one was designed by Paraiba et al. (2014) and employs the concept of Concentration Addition. This latter model also takes into account the effect of toxicity of pesticide mixtures on aquatic organisms and water quality, considering the characteristics of the soil and cultivation data obtained through the field and physical-chemical tests pesticides used in agricultural activities. The model of Paraiba et al. (2014) has shown to be more conservative in determining the GWF of the pesticide mixtures (2.00 × 107 m³ ha−1) in the aquatic ecosystem, than the model of Hoekstra et al. (2011) (6.25 × 105 m³ ha−1 for Sulfentrazone). The results presented and discussed in this study reinforce the use of the GWF as an indicator of water quality for agricultural sustainability. Our work also contributes to a better understanding of the advantages and limitations of each model approach in the assessment of the volume of freshwater needed to dilute the contaminant load in agriculture activities as, for instance, in sugarcane crops. Gray water footprint Pesticide Pesticide rank Water contamination Netto, André Maciel verfasserin aut Silva, João Paulo Siqueira da verfasserin aut Amaral, Ademir verfasserin aut Borges, Edvane verfasserin (orcid)0000-0001-7839-9945 aut França, Elvis Joacir de verfasserin aut Vale, Ricardo Lins verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 276 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:276 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 276
allfieldsSound	10.1016/j.jclepro.2020.124254 doi (DE-627)ELV004821866 (ELSEVIER)S0959-6526(20)34299-2 DE-627 ger DE-627 rda eng 690 330 DE-600 43.35 bkl 85.35 bkl Barreto, Mikaela de Lavôr Paes verfasserin aut Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The concept of gray water footprint (GWF) was introduced as an indicator of the volume of freshwater required to dilute the total pollutant load, generated from a particular production process, to maintain water quality standards. In crop production, for example, the theoretical calculation of the GWF can be employed as a sound tool for assessing the environmental impacts due to the use of pesticides. In this context, we compared two models for estimating the GWF of pesticide mixtures applied to the soil in a sugarcane crop, in Pernambuco, Brazil. One model was proposed by Hoekstra et al. (2011) and calculates the GWF based on the maximum concentration limit acceptable in water. The other one was designed by Paraiba et al. (2014) and employs the concept of Concentration Addition. This latter model also takes into account the effect of toxicity of pesticide mixtures on aquatic organisms and water quality, considering the characteristics of the soil and cultivation data obtained through the field and physical-chemical tests pesticides used in agricultural activities. The model of Paraiba et al. (2014) has shown to be more conservative in determining the GWF of the pesticide mixtures (2.00 × 107 m³ ha−1) in the aquatic ecosystem, than the model of Hoekstra et al. (2011) (6.25 × 105 m³ ha−1 for Sulfentrazone). The results presented and discussed in this study reinforce the use of the GWF as an indicator of water quality for agricultural sustainability. Our work also contributes to a better understanding of the advantages and limitations of each model approach in the assessment of the volume of freshwater needed to dilute the contaminant load in agriculture activities as, for instance, in sugarcane crops. Gray water footprint Pesticide Pesticide rank Water contamination Netto, André Maciel verfasserin aut Silva, João Paulo Siqueira da verfasserin aut Amaral, Ademir verfasserin aut Borges, Edvane verfasserin (orcid)0000-0001-7839-9945 aut França, Elvis Joacir de verfasserin aut Vale, Ricardo Lins verfasserin aut Enthalten in Journal of cleaner production Amsterdam [u.a.] : Elsevier Science, 1993 276 Online-Ressource (DE-627)324655878 (DE-600)2029338-0 (DE-576)252613988 0959-6526 nnns volume:276 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 43.35 Umweltrichtlinien Umweltnormen 85.35 Fertigung AR 276
language	English
source	Enthalten in Journal of cleaner production 276 volume:276
sourceStr	Enthalten in Journal of cleaner production 276 volume:276
format_phy_str_mv	Article
bklname	Umweltrichtlinien Umweltnormen Fertigung
institution	findex.gbv.de
topic_facet	Gray water footprint Pesticide Pesticide rank Water contamination
dewey-raw	690
isfreeaccess_bool	false
container_title	Journal of cleaner production
authorswithroles_txt_mv	Barreto, Mikaela de Lavôr Paes @@aut@@ Netto, André Maciel @@aut@@ Silva, João Paulo Siqueira da @@aut@@ Amaral, Ademir @@aut@@ Borges, Edvane @@aut@@ França, Elvis Joacir de @@aut@@ Vale, Ricardo Lins @@aut@@
publishDateDaySort_date	2020-01-01T00:00:00Z
hierarchy_top_id	324655878
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author	Barreto, Mikaela de Lavôr Paes
spellingShingle	Barreto, Mikaela de Lavôr Paes ddc 690 bkl 43.35 bkl 85.35 misc Gray water footprint misc Pesticide misc Pesticide rank misc Water contamination Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models
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topic_title	690 330 DE-600 43.35 bkl 85.35 bkl Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models Gray water footprint Pesticide Pesticide rank Water contamination
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title	Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models
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title_full	Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models
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title_sort	gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in brazil: a comparison between two models
title_auth	Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models
abstract	The concept of gray water footprint (GWF) was introduced as an indicator of the volume of freshwater required to dilute the total pollutant load, generated from a particular production process, to maintain water quality standards. In crop production, for example, the theoretical calculation of the GWF can be employed as a sound tool for assessing the environmental impacts due to the use of pesticides. In this context, we compared two models for estimating the GWF of pesticide mixtures applied to the soil in a sugarcane crop, in Pernambuco, Brazil. One model was proposed by Hoekstra et al. (2011) and calculates the GWF based on the maximum concentration limit acceptable in water. The other one was designed by Paraiba et al. (2014) and employs the concept of Concentration Addition. This latter model also takes into account the effect of toxicity of pesticide mixtures on aquatic organisms and water quality, considering the characteristics of the soil and cultivation data obtained through the field and physical-chemical tests pesticides used in agricultural activities. The model of Paraiba et al. (2014) has shown to be more conservative in determining the GWF of the pesticide mixtures (2.00 × 107 m³ ha−1) in the aquatic ecosystem, than the model of Hoekstra et al. (2011) (6.25 × 105 m³ ha−1 for Sulfentrazone). The results presented and discussed in this study reinforce the use of the GWF as an indicator of water quality for agricultural sustainability. Our work also contributes to a better understanding of the advantages and limitations of each model approach in the assessment of the volume of freshwater needed to dilute the contaminant load in agriculture activities as, for instance, in sugarcane crops.
abstractGer	The concept of gray water footprint (GWF) was introduced as an indicator of the volume of freshwater required to dilute the total pollutant load, generated from a particular production process, to maintain water quality standards. In crop production, for example, the theoretical calculation of the GWF can be employed as a sound tool for assessing the environmental impacts due to the use of pesticides. In this context, we compared two models for estimating the GWF of pesticide mixtures applied to the soil in a sugarcane crop, in Pernambuco, Brazil. One model was proposed by Hoekstra et al. (2011) and calculates the GWF based on the maximum concentration limit acceptable in water. The other one was designed by Paraiba et al. (2014) and employs the concept of Concentration Addition. This latter model also takes into account the effect of toxicity of pesticide mixtures on aquatic organisms and water quality, considering the characteristics of the soil and cultivation data obtained through the field and physical-chemical tests pesticides used in agricultural activities. The model of Paraiba et al. (2014) has shown to be more conservative in determining the GWF of the pesticide mixtures (2.00 × 107 m³ ha−1) in the aquatic ecosystem, than the model of Hoekstra et al. (2011) (6.25 × 105 m³ ha−1 for Sulfentrazone). The results presented and discussed in this study reinforce the use of the GWF as an indicator of water quality for agricultural sustainability. Our work also contributes to a better understanding of the advantages and limitations of each model approach in the assessment of the volume of freshwater needed to dilute the contaminant load in agriculture activities as, for instance, in sugarcane crops.
abstract_unstemmed	The concept of gray water footprint (GWF) was introduced as an indicator of the volume of freshwater required to dilute the total pollutant load, generated from a particular production process, to maintain water quality standards. In crop production, for example, the theoretical calculation of the GWF can be employed as a sound tool for assessing the environmental impacts due to the use of pesticides. In this context, we compared two models for estimating the GWF of pesticide mixtures applied to the soil in a sugarcane crop, in Pernambuco, Brazil. One model was proposed by Hoekstra et al. (2011) and calculates the GWF based on the maximum concentration limit acceptable in water. The other one was designed by Paraiba et al. (2014) and employs the concept of Concentration Addition. This latter model also takes into account the effect of toxicity of pesticide mixtures on aquatic organisms and water quality, considering the characteristics of the soil and cultivation data obtained through the field and physical-chemical tests pesticides used in agricultural activities. The model of Paraiba et al. (2014) has shown to be more conservative in determining the GWF of the pesticide mixtures (2.00 × 107 m³ ha−1) in the aquatic ecosystem, than the model of Hoekstra et al. (2011) (6.25 × 105 m³ ha−1 for Sulfentrazone). The results presented and discussed in this study reinforce the use of the GWF as an indicator of water quality for agricultural sustainability. Our work also contributes to a better understanding of the advantages and limitations of each model approach in the assessment of the volume of freshwater needed to dilute the contaminant load in agriculture activities as, for instance, in sugarcane crops.
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title_short	Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models
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Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models

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