INTRODUCTION<\/h2>\n
Agriculture is the\u00a0largest consumer of\u00a0freshwater in\u00a0the\u00a0world, accounting for approximately 70 % of\u00a0total water resource consumption [1, 2]. Intensive agricultural practices, including the\u00a0excessive use of\u00a0pesticides and fertilizers, have a\u00a0significant impact on aquatic ecosystems by leaching excessive amounts of\u00a0these substances into the\u00a0aquatic environment. Leaching of\u00a0nutrients, especially nitrates, into groundwater often contributes to exceeding permitted limits for drinking water. In\u00a0surface waters, elevated nitrate concentrations promote the\u00a0growth of\u00a0phytoplankton, dominated by algae and cyanobacteria. These reduce the\u00a0dissolved oxygen in\u00a0water and consequently lead to hypoxia or anoxia (process of\u00a0eutrophication). These changes cause a\u00a0loss of\u00a0biodiversity and can lead to massive mortality of\u00a0some aquatic organisms [3].<\/span><\/p>\n Pesticides, which are applied to protect crops from pests and diseases, leach into soil and water bodies, where they can threaten aquatic ecosystems and human health. Long-term exposure to these substances has been linked to endocrine system disruption, increased risk of\u00a0cancer, and other health problems [2]. Water contamination by pesticides is particularly problematic due to the\u00a0persistence of\u00a0some of\u00a0these substances, their ability to spread in\u00a0the\u00a0aquatic environment, and effect areas at high distances from sites of\u00a0their application.<\/span><\/p>\n Various methods have been developed to quantify the\u00a0environmental impact of\u00a0agriculture, including the\u00a0ecological footprint [4], the\u00a0nitrogen footprint [5], and the\u00a0water footprint, specifically the\u00a0Grey Water Footprint (GWF) [6, 7]. The\u00a0water footprint [8] consists of\u00a0three components. The\u00a0blue and green water footprints represent the\u00a0physical volume of\u00a0freshwater consumed for production. Consumption refers to the\u00a0unavailability of\u00a0the\u00a0consumed water to other users in\u00a0a\u00a0given catchment and within\u00a0a\u00a0given period of\u00a0time; this distinguishes the\u00a0water footprint from other environmental indicators that reflect any water use, regardless of\u00a0its availability to other users. The\u00a0grey water footprint represents the\u00a0theoretical volume of\u00a0water required to dilute pollutants entering water to a\u00a0level that meets the\u00a0water quality standards in\u00a0the\u00a0recipient at a\u00a0given location. It also represents the\u00a0\u201cconsumption\u201d of\u00a0water, as a\u00a0given volume of\u00a0water is no longer available to dilute the\u00a0same pollutant. This indicator allows an assessment of\u00a0the\u00a0level of\u00a0water resource pollution and provides a\u00a0basis for decision-making on sustainable water use.<\/span><\/p>\n The\u00a0GWF calculation in\u00a0this study focuses on identifying the\u00a0amount of\u00a0water needed to dilute the\u00a0pollutants, mainly nitrogen, phosphorus, and pesticides, used in\u00a0malting barley production in\u00a0the\u00a0Czech Republic. Previous studies have focused mainly on fertilizers when calculating the\u00a0grey water footprint of\u00a0crops, while the\u00a0impact of\u00a0pesticides was\/and is often underestimated.<\/span><\/p>\n Nutrient runoff into surface waters leads to eutrophication and subsequent deterioration in\u00a0water quality [9]. Nitrogen is highly mobile and its presence in\u00a0surface and groundwater can cause significant ecological problems. The\u00a0lack of\u00a0data on the\u00a0persistence of\u00a0pesticides in\u00a0the\u00a0aquatic environment and their cumulative impacts on ecosystems makes it difficult to accurately quantify their contribution to GWF. However, a\u00a0recent study by Yi et al. [10] and this study highlight the\u00a0need to include pesticides as their environmental impact can be much more significant than that of\u00a0fertilizers.<\/span><\/p>\n In\u00a0areas with limited water resources and vulnerable ecosystems, the\u00a0negative impact of\u00a0contamination may be more pronounced than in\u00a0regions with a\u00a0higher capacity of\u00a0natural systems to dilute pollution. Therefore, monitoring and reducing GWF is of\u00a0critical importance not only for agriculture but also for downstream industries that use agricultural products as feedstock, such as the\u00a0food and beverage industry. Quantification of\u00a0GWF [11] allows the\u00a0identification of\u00a0critical points in\u00a0the\u00a0supply chain\u00a0and in\u00a0the\u00a0production process. GWF assessment in\u00a0barley production thus provides important information for environmental policy, agricultural practice, and the\u00a0downstream food and beverage industry. This approach allows for a\u00a0more efficient use of\u00a0water resources and minimisation of\u00a0their pollution, as well as environmentally sustainable production of\u00a0food, beverages, and other agricultural products.<\/span><\/p>\n The\u00a0methodology used provides a\u00a0comprehensive approach to calculating the\u00a0GWF of\u00a0malting barley and allows a\u00a0detailed analysis of\u00a0the\u00a0impact of\u00a0agricultural production on water resources. The\u00a0results of\u00a0the\u00a0study may be key to the\u00a0design of\u00a0more sustainable agricultural practices and better management of\u00a0aquatic ecosystems. GWF monitoring and optimization is an important tool for farmers, industrial producers, and environmental policy makers to minimize negative environmental impacts and increase the\u00a0efficiency of\u00a0water resource use.<\/span><\/p>\n This study focuses on the\u00a0GWF analysis of\u00a0malting barley grown on an area of\u00a09,674.05 ha in\u00a0different parts of\u00a0the\u00a0Czech Republic, specifically in\u00a0the\u00a0districts of\u00a0Brunt\u00e1l, Fr\u00fddek-M\u00edstek, Hodon\u00edn, Jesen\u00edk, Karvin\u00e1, Krom\u011b\u0159\u00ed\u017e, Nov\u00fd Ji\u010d\u00edn, Olomouc, Opava, Ostrava-city, Prost\u011bjov, P\u0159erov, Rychnov nad Kn\u011b\u017enou, Semily, Svitavy, \u0160umperk, and \u00dast\u00ed nad Orlic\u00ed. To calculate the\u00a0GWF of\u00a0malting barley production, detailed data on fertilisers and pesticides used were obtained directly from growers supplying malting barley to Radegast Brewery. A\u00a0questionnaire was prepared to collect the\u00a0data, and Radegast Brewery representatives arranged for their suppliers to complete it. The\u00a0collected data were provided to the\u00a0study authors in\u00a0aggregated form, i.e., as an average amount of\u00a0applied substances per hectare of\u00a0cultivated area.<\/span><\/p>\n The\u00a0questionnaire survey focused on detailed information on the\u00a0types and quantities of\u00a0fertilisers and pesticides applied in\u00a0the\u00a0cultivation of\u00a0malting barley. Based on the\u00a0products used and their volume, the\u00a0amount of\u00a0active substance applied was determined.<\/span><\/p>\n To calculate GWF in\u00a0cubic metres per tonne of\u00a0crop grown, the\u00a0Hoekstra and Hung equations [9] and Water Footprint Assessment Manual<\/span> [8] were used:<\/span><\/p>\n <\/p>\n <\/p>\n where:<\/p>\n \u03b1\u00a0\u00a0\u00a0\u00a0\u00a0 is\u00a0\u00a0\u00a0 is proportion of\u00a0fertiliser and pesticide losses (%), the\u00a0so-called leaching factor<\/p>\n AR\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0amount of\u00a0fertilisers and pesticides applied to each crop\u00a0(kg\/ha)<\/p>\n cmax<\/sub>\u00a0 \u00a0 \u00a0 \u00a0critical concentration of\u00a0the\u00a0monitored substance from fertilisers and pesticides in\u00a0the\u00a0recipient (g\/m3<\/sup>)<\/p>\n cnat<\/sub>\u00a0 \u00a0 \u00a0 \u00a0 \u00a0natural (backround) concentration of\u00a0the\u00a0monitored substance from fertilisers and pesticides in\u00a0the\u00a0recipient (g\/m3<\/sup>)<\/p>\n Y\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0crop production (t\/ha)<\/p>\n The\u00a0average leaching factor \u03b1 was determined based on the\u00a0official Water Footprint Network methodology [12]. It has the\u00a0following values: 0.1 for nitrogen fertilisers, 0.03 for phosphate fertilisers, 0.7 for potassium fertilisers, and 0.01 for pesticides. The\u00a0leaching factor for pesticides was set at 0.01 due to the\u00a0lack of\u00a0detailed data on the\u00a0soil properties at the\u00a0monitored sites. The\u00a0necessary data for calculating the\u00a0regionalized \u03b1 factor according to the\u00a0methodology [12] were not provided.<\/p>\n The\u00a0difference between the\u00a0cmax and cnat represents the\u00a0assimilation capacity of\u00a0the\u00a0watercourse. For nitrogen, phosphorus, and potassium fertilizers, the\u00a0following assimilation capacity values were determined: nitrogen 3 g\/m\u00b3, phosphorus 0.1 g\/m\u00b3, and potassium 5 g\/m\u00b3 [12]. For pesticides, the\u00a0cnat value was set to zero, while cmax values were derived from the\u00a0lowest Predicted No Effect Concentration (PNEC) freshwater values from the\u00a0NORMAN database [13]. PNEC values are commonly used as cmax in\u00a0wastewater GWF studies [14\u201317], and can also be used in\u00a0calculating GWF of\u00a0pesticides in\u00a0agriculture [18]. The\u00a0PNEC values used for this study are listed in\u00a0Tab.\u00a02<\/em>.<\/p>\n Information on the\u00a0malting barley Y production in\u00a0the\u00a0studied districts was provided by representatives of\u00a0the\u00a0Radegast Brewery based on information from a\u00a0questionnaire survey among farmers. All data are valid for the\u00a0reference year 2022.<\/p>\n Tab.\u00a01<\/em> shows the\u00a0GWF values of\u00a0different fertilisers applied to malting barley fields. The\u00a0highest GWF values were found for phosphorus. Tab.\u00a02 shows the\u00a0GWF values for individual pesticides applied to malting barley fields. Insecticides reach the\u00a0highest GWF values due to their high ecotoxicity to aquatic organisms. The\u00a0insecticide deltamethrin\u00a0has the\u00a0significantly highest GWF, even at very low concentrations. The\u00a0GWF of\u00a0deltamethrin\u00a0is an order of\u00a0magnitude higher than the\u00a0GWF of\u00a0two other important insecticides (gamma-cyhalothrin\u00a0and esfenvalerate), three orders of\u00a0magnitude higher than the\u00a0GWF of\u00a0fungicides (prothioconazole), herbicides (2,4-D 2-EHE), fertilisers (phosphorus), and four orders of\u00a0magnitude higher than the\u00a0GWF of\u00a0a\u00a0morphine regulator (trinexapac-ethyl).<\/p>\n Fig.\u00a03<\/span><\/span><\/em> provides summary values of\u00a0the\u00a0GWF associated with fertiliser and pesticide use in\u00a0malting barley production. Insecticides show the\u00a0highest GWF values, which is related to their high ecotoxicity to aquatic organisms. Among them, deltamethrin\u00a0dominates, with a\u00a0GWF approximately one order of\u00a0magnitude higher than the\u00a0other two major insecticides (gamma-cyhalothrin\u00a0and esfenvalerate). Also, it is three orders of\u00a0magnitude higher than the\u00a0GWF of\u00a0fungicides (prothioconazole), herbicides (2,4-D 2-EHE), and phosphate fertilisers, and even four orders of\u00a0magnitude higher than that of\u00a0a\u00a0morphoregulator (trinexapac-ethyl). Although only small amounts of\u00a0deltamethrin\u00a0have been applied, its overall impact on aquatic ecosystems is most significant. The\u00a0total GWF associated with malting barley production amounts to 302,440.814 m\u00b3\/t, with insecticides with the\u00a0active substance deltamethrin\u00a0accounting for the\u00a0most significant part of\u00a0the\u00a0pollution.<\/span><\/p>\n While the\u00a0application of\u00a0fertilisers and pesticides has a\u00a0noticeable positive effect on boosting crop yields, the\u00a0massive use of\u00a0these substances causes environmental contamination both locally and globally. Studies published to date have generally focused on GWF caused by fertilisers, which are generally used in\u00a0large quantities. Pesticides have not been included in\u00a0most studies, both because of\u00a0their relatively small quantities (compared to fertilisers) and because of\u00a0methodological issues associated with their inclusion in\u00a0the\u00a0GWF model.<\/span><\/p>\n Pesticides usually break down very slowly; their residues remain\u00a0in\u00a0agricultural soil for many years after application. Their negative effects on water quality are evident at significantly lower concentrations than those of\u00a0nutrients. Humans exposed to water poluted with pesticide residues are at risk of\u00a0diseases such as cancer, endocrine disruption, etc. Aquatic ecosystems are even more sensitive to the\u00a0effects of\u00a0these substances.<\/span><\/p>\n The results described above show that for a correct assessment of the GWF of crops, it is necessary to assess not only the GWF of fertilisers but also the GWF of pesticides. Based on current knowledge, crop GWF studies can no longer be\u00a0<\/span>considered representative if they only focus on the\u00a0GWF of\u00a0fertilisers. There is a\u00a0need to compare the\u00a0GWF of\u00a0fertilisers with the\u00a0GWF of\u00a0pesticides in\u00a0future crop GWF studies is evident. Without such a\u00a0comparison, the\u00a0results are incomplete and may be misleading.<\/span><\/p>\n On the\u00a0other hand, it is important to note the\u00a0possible limitations of\u00a0our results. The\u00a0first limitation is the\u00a0application to a\u00a0single crop species grown on 9,674.05 ha. The\u00a0amount of\u00a0fertilizers and pesticides applied and their composition vary depending on the\u00a0crop grown, soil characteristics, as well as on management practices. These variable factors influence the\u00a0GWF value, as demonstrated in\u00a0the\u00a0study by Borsat et al. [19]. The\u00a0second limitation is the\u00a0use of\u00a0a\u00a0constant leaching factor \u03b1, which is in\u00a0accordance with TIER 1 according to Franke et al [12]. The\u00a0use of\u00a0a\u00a0constant leaching factor \u03b1 represents a\u00a0certain\u00a0simplification of\u00a0the\u00a0heterogeneous conditions prevailing in\u00a0agriculture. Such a\u00a0simplification is therefore appropriate for large-scale studies or, in\u00a0the\u00a0absence of\u00a0basic data, for more detailed approaches to the\u00a0expression of\u00a0the\u00a0leaching factor (TIER 2 or TIER 3). In\u00a0our case, it was used due to the\u00a0lack of\u00a0supporting information for the\u00a0application of\u00a0a\u00a0more detailed solution.<\/span><\/p>\n A\u00a0final simplification that we used due to the\u00a0lack of\u00a0detailed data is the\u00a0composition of\u00a0the\u00a0individual mixtures applied to each field within\u00a0the\u00a0study area. The\u00a0data obtained from individual farmers and provided by the\u00a0Radegast Brewery representatives only gave the\u00a0total amounts of\u00a0the\u00a0product applied in\u00a0the\u00a0area of\u00a0interest, not in\u00a0particular fields. Therefore, we considered the\u00a0application rate applied to the\u00a0entire area of\u00a0interest of\u00a09,674.05 ha. The\u00a0mixture of\u00a0products shown in\u00a0Tabs. 2<\/span> and 3<\/span> thus represents a\u00a0kind of\u00a0\u2018common average mixture\u2019 used in\u00a0production.<\/span><\/p>\n The\u00a0problem in\u00a0determining the\u00a0GWF of\u00a0pesticides lies in\u00a0the\u00a0common application of\u00a0pesticides in\u00a0the\u00a0form of\u00a0mixtures of\u00a0different active ingredients. All pollutants entering water from human activities are mixtures of\u00a0several substances. The\u00a0Water Footprint Assessment Manual<\/span> [8] assumes that the\u00a0individual substances in\u00a0the\u00a0mixture do not interact with each other, and the\u00a0GWF is determined by the\u00a0substance with the\u00a0highest value. However, this assumption of\u00a0the\u00a0GWF model is often not met in\u00a0reality. When different bioactive substances are mixed, they interact with each other, and their toxicity and impact on the\u00a0receiving water body change depending on the\u00a0mixture composition. Therefore, some researchers have proposed alternative approaches to address GWF mixtures.<\/span><\/p>\n One approach is to modify the\u00a0GWF model. Paraiba et al. [18] proposed a\u00a0model that assumes that the\u00a0toxicity of\u00a0a\u00a0mixture is the\u00a0sum of\u00a0the\u00a0toxicities of\u00a0each substance in\u00a0the\u00a0mixture. De Lavor Paes Barreto et al. [20] compared such an approach with the\u00a0original approach described in\u00a0the\u00a0Water Footprint Assessment Manual<\/span> [8] and found that the\u00a0model proposed by Paraiba et al. [18] is usually more precise. This is a\u00a0logical conclusion, considering that in\u00a0the\u00a0model, each additional substance added to the\u00a0model mixture will increase its toxicity.<\/span><\/p>\n Another approach to addressing mixtures is to include the\u00a0self-purification capacity of\u00a0the\u00a0watercourse. For example, the\u00a0GWF study on urban wastewater\u00a0[21] identified ammonium nitrogen (N-NH4<\/span>+<\/span>) as the\u00a0substance most often determining GWF. In\u00a0rivers, ammonium nitrogen is rapidly oxidized to other forms of\u00a0nitrogen, however, the\u00a0Water Footprint Assessment Manual<\/span> GWF model does not account for this fact. Therefore, some researchers include the\u00a0self-purification process directly into GWF models [22, 23].<\/span><\/p>\n A\u00a0yet different approach to addressing GWF of\u00a0mixtures can be found in\u00a0the\u00a0L\u2019Or\u00e9al product eco-design article [24]. Their methodology is based on the\u00a0use of\u00a0techniques used in\u00a0LCA, i.e., on the\u00a0principle of\u00a0additivity of\u00a0the\u00a0effects of\u00a0each component in\u00a0proportion to its concentration in\u00a0the\u00a0formula.<\/span><\/p>\n The\u00a0above-mentioned uncertainties of\u00a0the\u00a0solution, as well as the\u00a0different approaches to GWF by different authors, highlight the\u00a0need for further research on GWF. In\u00a0our view, this research should focus on three areas:<\/span><\/p>\n The\u00a0first area is the\u00a0identification of\u00a0substances that may determine GWF. Our studies of\u00a0malting barley GWF (this paper) and micropollutants in\u00a0treated urban wastewater [14] have shown that commonly monitored pollutants may not be (and often are not) the\u00a0most critical ones for GWF determination. Thus, the\u00a0selection of\u00a0non-representative pollutants leads to a systematic underestimation of\u00a0GWF values. A number of\u00a0research studies in\u00a0different water-related fields are needed to find relevant pollutants for different sectors and water uses.<\/p>\n The\u00a0second area deals with mixtures in\u00a0GWF models. On the\u00a0one hand, the\u00a0\u201cindependence\u201d of\u00a0the\u00a0water footprint values from external influences must be maintained. The\u00a0water footprint is one of\u00a0the\u00a0environmental indicators that describes the\u00a0behaviour of\u00a0the\u00a0assessed system. An indicator whose value would change without changing the\u00a0assessed system itself is not well set. On the\u00a0other hand, issues related to new, so-called emergent pollutants, which are often bioactive substances and behave differently in\u00a0different mixtures, need to be adequately addressed.<\/p>\n The\u00a0third area where we consider the\u00a0current state of\u00a0knowledge to be incomplete is in\u00a0assessing the\u00a0GWF sustainability. We do not consider approaches that introduce a self-purification process into GWF models to be appropriate practice. The\u00a0self-purification capacity of\u00a0the\u00a0aquatic environment is independent of\u00a0the\u00a0product systems assessed by GWF. Therefore, the\u00a0water self-purification capacity should not be included in\u00a0a GWF model. A modification of\u00a0the\u00a0sustainability assessment seems to be a more appropriate solution. The\u00a0current system, described in\u00a0the\u00a0Water Footprint Assessment Manual<\/span> [8], compares GWF values with available sources to dilute pollution using actual runoff from the\u00a0catchment. Thus, this approach compares the\u00a0runoff in\u00a0a particular catchment with the\u00a0dilution water needs in\u00a0different parts of\u00a0the\u00a0assessed catchment. This can lead to an overestimation of\u00a0the\u00a0discharged pollution impact due to the\u00a0neglect of\u00a0the\u00a0self-purification capacity in\u00a0the\u00a0aquatic environment.<\/p>\n This study confirmed that GWF is an important indicator for assessing the\u00a0environmental impacts of\u00a0agriculture, and that all applied substances, i.e. not only fertilisers but also pesticides, should be included. In\u00a0malting barley production, the\u00a0insecticide deltamethrin\u00a0had the\u00a0greatest impact on water resources. Due to the\u00a0high ecotoxicity of\u00a0pesticides and their long-term persistence in\u00a0aquatic ecosystems, it is important that future studies include a\u00a0detailed analysis. Local conditions such as climatic factors, soil types, and water availability must be considered in\u00a0GWF assessment. The\u00a0implementation of\u00a0measures to reduce GWF, such as optimising the\u00a0use of\u00a0agrochemicals and innovative technologies in\u00a0agriculture, can contribute significantly to a\u00a0more sustainable use of\u00a0water resources and environmental protection.<\/span><\/p>\n This study was created as part of\u00a0a\u00a0commercial contract with the\u00a0Radegast Brewery. We would like to thank the\u00a0representatives of\u00a0Radegast Brewery for their help in\u00a0obtaining input data for the\u00a0study.<\/span><\/span><\/em><\/p>\n The\u00a0article was supported by the\u00a0funds of\u00a0the\u00a0Institutional Support within\u00a0the\u00a0framework of\u00a0internal grants provided by the\u00a0T. G. Masaryk Water Research Institute.<\/span><\/span><\/em><\/p>\n The representatives of Radegast Brewery and the related companies had no influence on the results of the study. The second author is part of the TGM WRI management, which publishes the VTEI journal, and chairman of the VTEI\u00a0<\/span>journal editorial board. However, these facts had no influence on the\u00a0support provided for the\u00a0writing of\u00a0the\u00a0article or on the\u00a0acceptance of\u00a0the\u00a0article for publication in\u00a0the\u00a0VTEI journal.<\/span><\/p>\n The\u00a0Czech version of\u00a0this article was peer-reviewed, the\u00a0English version was\u00a0translated from the\u00a0Czech original by Environmental Translation Ltd.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":" Agriculture is the world\u2019s main freshwater consumer; it also contributes to its contamination through fertilizers and pesticides. This article focuses on the grey water footprint (GWF) as an environmental indicator assessing the impact of agricultural production on water resources. The study analyses the GWF of malting barley production on an area of 9,674 ha in different regions of the Czech Republic. Special empha-sis is placed on including pesticides in the GWF calculation, as their impact on freshwater ecosystems and human health may exceed the impact of fertilizers. The analysis shows that insecticides have the highest GWF, especially deltamethrin, whose GWF is an order of magnitude higher than that of other agrochemicals. The study highlights the importance of including pesticides in future GWF assess-ments to better assess the environmental impacts of agricultural production and optimize sustainable water resource management strategies. At the same time, the study discusses different approaches to including biologically active substances in grey water footprint models.<\/p>\n","protected":false},"author":8,"featured_media":35501,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[87],"tags":[3843,2814,3844,2870,454],"coauthors":[334,399,808],"class_list":["post-35773","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-hydrochemistry-radioecology-microbiology","tag-fertilizers","tag-grey-water-footprint","tag-malting-barley","tag-micropollutants","tag-pesticides"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/posts\/35773","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/comments?post=35773"}],"version-history":[{"count":7,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/posts\/35773\/revisions"}],"predecessor-version":[{"id":35829,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/posts\/35773\/revisions\/35829"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/media\/35501"}],"wp:attachment":[{"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/media?parent=35773"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/categories?post=35773"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/tags?post=35773"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.vtei.cz\/en\/wp-json\/wp\/v2\/coauthors?post=35773"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Methodology and data sources<\/h2>\n
![\"\"](\"https:\/\/www.vtei.cz\/wp-content\/uploads\/2025\/06\/Volosinova-vzorec-1.jpg\")
<\/a>\n<\/a>\n<\/a>\nRESULT<\/h2>\n
Tab. 1. Grey water footprint of nutrients \u2013 malting barley<\/h5>\n
<\/a>\nFig. 1. Grey water footprint of\u00a0nutrients \u2013 malting barley<\/h6>\n
Tab. 2. Grey water footprint of pesticides \u2013 malting barley<\/h5>\n
<\/a>\n<\/a>\nFig. 2. Grey water footprint of\u00a0pesticides \u2013 malting barley<\/h6>\n
<\/h6>\n
<\/a><\/h6>\nFig. 3. Grey water footprint of\u00a0malting barley production<\/h6>\n
DISCUSSION<\/h2>\n
CONCLUSION<\/h2>\n
Acknowledgements<\/h3>\n
Declaration of\u00a0conflict of\u00a0interest<\/h3>\n