Incorrect method for calculation of grey water footprint in several articles

Author(s):  
Libor Ansorge
Keyword(s):  
2015 ◽  
Vol 671 ◽  
pp. 412-418
Author(s):  
Lu Lu Xu ◽  
Li Zhu Chen ◽  
Hugh Gong ◽  
Xue Mei Ding

Water footprint is a volumetric indicator of freshwater appropriation. The grey water footprint (GWF) provides a tool to assess the water volume needed to assimilate a pollutant. However, evaluating the impact on water environment cannot rely solely on volumetric consumption of freshwater. It demands accurate assessment criteria to reflect its environmental and ecological effects on ambient water resource. In this paper, a new assessment method is proposed: the effluent toxicity and the Potential Eco-toxic Effects Probe (PEEP) index of aquatic environment are taken into consideration. This method provides a comprehensive indicator for evaluating water footprint, specified in effluents’ ecological impact on ambient water sources.


2017 ◽  
Vol 11 (06) ◽  
pp. 749-756 ◽  
Author(s):  
Rigoberto Moreira de Matos ◽  
◽  
Vitória Ediclécia Borges ◽  
Antônio Suassuna de Lima ◽  
Patrícia Ferreira da Silva ◽  
...  

2011 ◽  
Vol 8 (1) ◽  
pp. 763-809 ◽  
Author(s):  
M. M. Mekonnen ◽  
A. Y. Hoekstra

Abstract. This study quantifies the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996–2005. The assessment is global and improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc min grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the water footprint network. Considering the water footprints of primary crops, we see that global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton−1), vegetables (300 m3 ton−1), roots and tubers (400 m3 ton−1), fruits (1000 m3 ton−1), cereals} (1600 m3 ton−1), oil crops (2400 m3 ton−1) to pulses (4000 m3 ton−1). The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio-ethanol has a lower water footprint (in m3 GJ−1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio-ethanol based on sugar beet amounts to 51 m3 GJ−1, while this is 121 m3 GJ−1 for maize. The global water footprint related to crop production in the period 1996–2005 was 7404 billion cubic meters per year (78% green, 12% blue, 10% grey). A large total water footprint was calculated for wheat (1087 Gm3 yr−1), rice (992 Gm3 yr−1) and maize (770 Gm3 yr−1). Wheat and rice have the largest blue water footprints, together accounting for 45% of the global blue water footprint. At country level, the total water footprint was largest for India (1047 Gm3 yr−1), China (967 Gm3 yr−1) and the USA (826 Gm3 yr−1). A relatively large total blue water footprint as a result of crop production is observed in the Indus River Basin (117 Gm3 yr−1) and the Ganges River Basin (108 Gm3 yr−1). The two basins together account for 25% of the blue water footprint related to global crop production. Globally, rain-fed agriculture has a water footprint of 5173 Gm3 yr−1 (91% green, 9% grey); irrigated agriculture has a water footprint of 2230 Gm3 yr−1 (48% green, 40% blue, 12% grey).


2020 ◽  
Vol 246 ◽  
pp. 119077 ◽  
Author(s):  
Hongying Li ◽  
Yufei Wang ◽  
Lijie Qin ◽  
Hongshi He ◽  
Tianyu Zhang ◽  
...  

2020 ◽  
pp. 124915
Author(s):  
Huijuan Dong ◽  
Lei Zhang ◽  
Yong Geng ◽  
Peng Li ◽  
Chenhui Yu

2017 ◽  
Vol 147 ◽  
pp. 1-9 ◽  
Author(s):  
Wenfeng Liu ◽  
Marta Antonelli ◽  
Xingcai Liu ◽  
Hong Yang

2016 ◽  
Vol 36 (1) ◽  
Author(s):  
孙才志 SUN Caizhi ◽  
韩琴 HAN Qin ◽  
郑德凤 ZHENG Defeng

2014 ◽  
Vol 18 (2) ◽  
pp. 503-510 ◽  
Author(s):  
C. O'Bannon ◽  
J. Carr ◽  
D. A. Seekell ◽  
P. D'Odorico

Abstract. Almost 90% of freshwater resources consumed globally are used to produce plant and animal commodities. Water-scarce countries can balance their water needs by importing food from other countries. This process, known as virtual water transfer, represents the externalization of water use. The volume and geographic reach of virtual water transfers is increasing, but little is known about how these transfers redistribute the environmental costs of agricultural production. The grey water footprint quantifies the environmental costs of virtual water transfers. The grey water footprint is calculated as the amount of water necessary to reduce nitrogen concentrations from fertilizers and pesticides released into streams and aquifers to allowed standards. We reconstructed the global network of virtual grey water transfers for the period 1986–2010 based on international trade data and grey water footprints for 309 commodities. We tracked changes in the structure of the grey water transfer network with network and inequality statistics. Pollution is increasing and is becoming more strongly concentrated in only a handful of countries. The global external grey water footprint, the pollution created by countries outside of their borders, increased 136% during the period. The extent of externalization of pollution is highly unequal between countries, and most of this inequality is due to differences in social development status. Our results demonstrate a growing globalization of pollution due to virtual water transfers.


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