CHEMICAL ENGINEERING TRANSACTIONS VOL. 76, 2019 A publication of The Italian Association of Chemical Engineering Online at www.aidic.it/cet Blue Water Footprint of the Czech Republic Xuexiu Jiaa,*, Jiří Jaromír Klemeša, Petar Sabev Varbanova, Sharifah R Wan Alwib aSustainable Process Integration Laboratory – SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology - VUT Brno, Technická 2896/2, 616 69 Brno, Czech Republic bProcess Systems Engineering Centre (PROSPECT), Research Institute for Sustainable Environment, Universiti Teknologi Malaysia (UTM), 81310 UTM Johor Bahru, Johor, Malaysia jia@fme.vutbr.cz Water scarcity has been a serious concern as a global issue in various regions around the world. Located in the central Europe, the Czech Republic is also affected by the shortage of water. To improve the understanding of water use at a country level and identify the potential for optimal water management, this study investigated the internal blue water footprint of the Czech Republic from 2013 to 2017 and the national blue water footprint in 2017. Based on the existing method, treated water and water loss, as the water recharged to natural water supply, are considered as an offset of the water footprint. The results showed a slight increase in the internal blue water footprint in 2013 - 2017. The national blue water footprint showed that fossil fuel and paper are the two major imported commodities contributing to virtual water import, and wheat and beer are the major commodities contributing to virtual water export in 2017. 1. Introduction Water scarcity has become a severe issue as a result of increasing water consumption and degradation. Even in regions and countries such as Central Europe and the Czech Republic, drought has become an issue concerned by the decision makers and scientific research (State Land Office, 2019). A study (Data.Brno, 2018) claimed that the Czech Republic went through the driest summer season in 2018. A series of satellite images of the second largest city in the Czech Republic, Brno, showed that the soil moisture content in the city had reduced obviously in three years from 2015 to 2018. The drought affects not only the agriculture but also the climate, their study also showed the city has become hotter in the three years, and the region is 3.8 °C higher than the average of years from 1981 to 2010 (Data.Brno, 2018). Figure 1: Satellite-derived soil moisture content of Brno, the Czech Republic in a) Aug. 2015 and b) Aug. 2018 (Data.Brno, 2018) Human activity plays an essential role in the occurrence of water scarcity. The increase of population, industry and trade, as well as over-consuming/wasting can increase the water demand. While low water returns and high water pollution would decrease the usability of the water supply. In addition, the policy and pricing system of water resource can also affect the water demand and use at a large scale. It is important to investigate the water a) Brno, 2015 b) Brno, 2018 Guest Editors: Petar S. Varbanov, Timothy G. Walmsley, Jiří J. Klemeš, Panos Seferlis Copyright © 2019, AIDIC Servizi S.r.l. ISBN 978-88-95608-73-0; ISSN 2283-9216 1063 DOI: 10.3303/CET1976178 Paper Received: 13/05/2019; Revised: 16/06/2019; Accepted: 28/06/2019 Please cite this article as: Jia X., Klemes J.J., Varbanov P.S., Wan Alwi S.R., 2019, Blue Water Footprint of the Czech Republic, Chemical Engineering Transactions, 76, 1063-1068 DOI:10.3303/CET1976178 use patterns to better understand the national water flows, in order to identify the potentials for the solutions for regional water scarcity issues. As a widely used indicator, water footprint (WF) (Hoekstra, 2003) is helpful to represent the water consumption and track the virtual water flow in international trade. As a consumption-based water use indicator, the concept and methodology of WF have been well investigated and improved by the team (Hoekstra et al., 2011) and others (Zhuo et al., 2016). Water footprint assessment (WFA) has been widely implemented at various levels including product (Schyns and Vanham, 2019), sectors (Hoekstra, 2015), regions (Vanham, 2018), as well as the national level (Steen-Olsen et al., 2012). The original water footprint on a national level is applied to improve the understanding of the relative significance of a country’s impacts in a global perspective, and shed light on the poetntial drivers of these impacts. On the other hand it can only provide limited information for the national water resources management. In this study, WFA method is modified to benchmark the water use from an input-output perspective, to provide supportive results for water resources management. The blue water footprint of the Czech Republic is carried out as a case study to illustrate the implementation of the method. This is made necessary by the current water scarcity issues of the Czech Republic and a lack of water use information at the national level. The ultimate goal of this study is to benchmark the overall internal and external virtual water consumptions of the country, and consequently track the water use pattern and identify the potential for optimal water management. The novelty of the study is 1) providing a different interpretation of the WFA in terms of national water resources management, and 2) modifying the WFA method of including water return and recalculating external virtual water footprint. By calculating the water footprint stemming from the national territory and identifying the critical production paths and final demand products, and the results can identify potentials for national water optimisation. 2. Methods and data sources 2.1 National water footprint assessment Chapagain and Hoekstra (2004) initiated the research report determining the water footprint of the nation. The water footprint of a nation [m3/y] includes the internal water footprint (IWFP) and the external water footprint (EWFP), as shown in Eq(1). 𝑊𝐹𝑃 = 𝐼𝑊𝐹𝑃 + 𝐸𝑊𝐹𝑃 (1) where WFP is the national water footprint [m3/y]. IWFP is the Internal Water Footprint [m3/y], represents the total volume of water used, directly or indirectly, to produce the goods and services consumed by the inhabitants of the country. EWFP is the External Water Footprint [m3/y], represents water embodied in the products imported from abroad and consumed in the current country. The IWFP and EWFP are calculated as Eq(2) and Eq(3). 𝐼𝑊𝐹𝑃 = 𝐴𝑊𝑈 + 𝐼𝑊𝑊 + 𝐷𝑊𝑊 − 𝑉𝑊𝐸𝑑𝑜𝑚 = 𝑇𝑊𝑊 − 𝑉𝑊𝐸𝑑𝑜𝑚 (2) where AWU is the agricultural water consumption [m3/y], IWW and DWW are the industrial and domestic water withdrawals [m3/y], TWW is the total water withdrawal [m3/y]. VWEdom is the volume of the virtual water embodied in the domestically produced products that are exported to other countries [m3/y]. 𝐸𝑊𝐹𝑃 = 𝑉𝑊𝐼 − 𝑉𝑊𝐸𝑟𝑒−𝑒𝑥𝑝𝑜𝑟𝑡 (3) VWI is the virtual water import [m3/y], and VWEre-export is the virtual water exported to other countries as a result of the re-export of imported products [m3/y]. The virtual water footprint of the product p from exporting country e to the importing country i is calculated as Eq(4). 𝑉𝑊𝐹(𝑒,𝑖,𝑝) = 𝑃𝑇(𝑒, 𝑖,𝑝) × 𝑉𝑊𝐶(𝑒,𝑝) (4) where, PT is the product trade [t/y] from exporting country e to importing country i, and VWC is the virtual water content [m3/t] of product p in the exporting country. In Eq(2), VWEdom is deducted from IWFP to avoid the double counting of the part included in the industrial and/or agricultural water consumption. However, it is challenging to extract the re-export product data from overall export data. In this study, the VWEre-export and VWEdom are aggregated as the international trade water footprint (TWFP) to replace EWFP, as shown in Eq(5). 𝑇𝑊𝐹𝑃 = 𝑉𝑊𝐼 − (𝑉𝑊𝐸𝑟𝑒−𝑒𝑥𝑝𝑜𝑟𝑡 − 𝑉𝑊𝐸𝑑𝑜𝑚) = 𝑉𝑀𝐼 − 𝑉𝑀𝐸 (5) where TWFP is an international trade virtual water footprint [m3/y]. VWE is the virtual water embodied in the product exported from the Czech Republic to other countries [m3/y]. In addition, the water discharged from the Wastewater Treatment Plant (WWTP) and water loss during transportation, which is returned to the natural water supply, are deducted from the total water withdrawal (TWW) as an offset of the water footprint Eq(6). 1064 𝐼𝑊𝐹𝑃 = 𝑇𝑊𝑊 − 𝑇𝑊 − 𝑊𝐿 (6) Where, TW is the treated water (including rainwater) from WWTPand WL is the pipeline water loss [m3/y]. Both of which are returned to the natural water supply. In order to provide results for future cross-border comparison, it would be helpful to calculate the water footprint per capita, which is the national water footprint divide by the population. 2.2 System boundary and data sources Figure 2 shows the system boundary of the WFA. The inventory water flow includes domestic water use (agriculture, residential and industry), water recharges from WWTP to natural water bodies and virtual water during international trade. The water evaporation and transpiration are not considered due to the lack of data. Focusing on the water use flow, only the blue water footprint (Hoekstra, 2003) is assessed in this study. Figure 2: System boundary of the water footprint assessment in the Czech Republic The domestic water consumption data, including the sectoral water absorption and water discharge, are extracted from the report on water management of the Czech Republic (MACR and MECR, 2018). The international trade data used to calculate the virtual water flow, are extracted from the database of the Czech Statistical Office (2019a). The mid-year population of the Czech Republic from 2013 to 2015 is 10.5 M, and from 2016-2017 is 10.6 M (2019b). Other data sources are marked where mentioned. Based on the selected data, the national WF is calculated for the year of 2017, and the internal WF is calculated from 2013 - 2017. 3. Water footprint inventory 3.1 Internal water flows The internal water consumption covers the water withdrawal from natural water supply (agricultural, industrial, and residential) and water discharge and loss, as shown in Table 1, derived from MACR and MECR (2018). Table 1: Water withdrawal, recharge and loss in the Czech Republic (2017), [Mm3/y] Year Total water withdrawal (TWW) Treated water (TW) Water loss (WL) 2013 1,630 912 106 2014 1,638 812 96 2015 1,585 779 99 2016 1,625 803 90 2017 1,642 826 98 The treated water, including rainwater and the water loss in pipelines, is considered as the water recharged to the natural supply and would be deducted from the domestic water consumption, as an offset of internal water footprint. 3.2 International trade data of selected commodities From the External Trade database of the Czech Statistical Office (2019a), 16 commodities are selected from the top 7 categories of exported and imported commodities based on the traded weight for the external water footprint calculation, as shown in Table 2. 1065 Table 2: Selected imported and exported commodities in the Czech Republic in 2017 (based on weight) No. Import Commodities Weight [Mt] Imported country Export Commodities Weight [Mt] 1 Coal 3.71 PL Pallets collars of wood 0.66 2 Conventional oil 8.05 PL, GE, AT Coal 2.31 3 Lignite 0.13 PL Conventional oil 0.83 4 Natural gas 6.63 GE Lignite 0.98 5 Unalloyed steel 1.50 PL, GE, SK Natural gas 0.47 6 Portland cement 0.03 AT Unalloyed steel 1.80 7 Pallets collars of wood 0.21 PL Beer 0.47 8 Polyesters 0.34 GE, SK Bottled water 0.38 9 Paper/paper board 0.08 GE, SK Portland cement 0.56 10 Unalloyed steel 0.09 GE Wheat 1.44 11 Barley 0.48 12 Maize 0.37 13 Oats 0.04 14 Rye 0.03 15 Unalloyed steel 0.20 16 Polyesters 0.01 The virtual water contents (VWC) of the products are collected and presented in Table 3. Table 3: VWC of traded commodities in the Czech Republic in 2017 [m3/t] Commodity VWC Reference Commodity VWC Reference Coal 4.20 Mekonnen et al., 2015 Steel 6.10 Bosman, 2016 Conventional oil 4.62 Beer 300 Hoekstra, 2008 Lignite 0.72 Bottled water 17.4 Tandon et al., 2014 Natural gas 1.70 Gerbens-Leenes et al., 2018 Wheat 342 Mekonnen and Hoekstra, 2011 Portland cement 0.51 Bosman, 2016 Barley 79.0 Pallets 41.0 Schyns et al., 2017 Maize 81.0 Polyesters 50.7 Freitas et al., 2017 Oats 181 Paper 616 van Oel and Hoekstra, 2010 Rye 25.0 4. Results and discussion The internal water footprint and per capita value of the Czech Republic in 2013-2017 is calculated (Figure 3). From 2013 to 2017, the internal water footprint (IWFP) of the Czech Republic has the lowest value in the year 2013 (600 Mm3/y), increasing to 718 Mm3/y in 2014 (19.6 %) and maintained at a stable level around 700 m3/y. The significant contribution is the water recharge increase, means more water is returned to the natural water supply. The average IWFP per capita is 65.2 m3/capita/y, which is much lower than the average water consumption of 157 m3/capita/y by Hunkar (2017). The difference is that the original WFA does not count the water returned to the natural water supply, and their results are higher. Figure 3. IWFP and per capita value of the Czech Republic from 2013 to 2017 1066 Figure 4. Breakdown of the national water footprint of the Czech Republic in 2017 The national water footprint of the Czech Republic with selected commodities is 87.4 Mm3/y and is lower than the result of Chapagain and Hoekstra (2004), 636 Mm3/y. A reason is that water discharge (water recharged to the natural water supply) offsets part of the water footprint. Another is due to the different selections of international trade products. Figure 4 showed the breakdowns of the national water footprint of the Czech Republic in 2017. The virtual water footprint from international trade (TWFP) is -619 Mm3/y in 2017, the negative value indicates a net water export (the virtual water exported to other countries is more than imported from other countries). Fuel (coal, oil, natural gas, etc.) contributes the most (43.0 %) to the virtual water import, the following is paper, with a contribution of 33.2 %. Wheat contributes 63.9 % to the virtual water export (63.9 %) with a larger mass and high virtual water content, and the following is beer with a contribution of 18.3 %. When water recharge is considered, the blue water footprint per capita of the Czech Republic is 8.25 m3/capita/y. The blue WFP per capita increase to 95.5 m3/capita/y when exclude the water recharge. The value is about 27 % higher than the blue WFP of the Czech Republic (75 m3/capita/y) in 2012 (Steen-Olsen et al., 2012), which covers the production and trade of primary products of agriculture and forestry in the country. It is evident that the selections of traded commodities, data availability and quality can affect the result in a large extent. This indicates a need to discuss the role and contribution of water footprint assessment. The methodology for WFA should be specified when used for different aims and scope. The previously existing method for WFA is a effective tool for global environmental impact quantification. There is a need for the future efforts to improve the methodology to facilitate national and regional water resources management and provide insights to mitigate water scarcity. Future directions of WFA include 1) a comprehensive assessment of volumetric consumption and and water quality degradation, 2) water integration within the system boundary, and the extension of efforts in WFA using mathematical programming methods by Avison et al. (2011), and 3) water-energy nexus footprinting methods development and implementation. 5. Conclusions This study determined the internal water footprint of the Czech Republic from 2013 to 2017, and the overall national water footprint of 2017. The main conclusions are i) The internal water footprint of the Czech Republic increased from 600 Mm3/y to 706 Mm3/y in the five years and maintained at around 700 Mm3/y from 2014 – 2017. ii) the national water footprint per capita is 8.25 m3/capita/y, and iii) Fossil fuel (coal, oil, natural gas, etc.) and paper are the major contributors to virtual water import, and wheat and beer are the significant contributors to the virtual water export. Recommendations derived from the studies are: i) Increase the water return, including water discharge, and rainwater collection can offset the water footprint increase. ii) The impact of importing water-intensive commodities should be further investigated, mainly agricultural products (e.g. crops, beer, etc.). and iii) There is a need to extend the water use database to more accurate assessment. Future efforts should be taken to identify the most important virtual water flows out of the country. Mathematical Programming based methods can be further investigated for water footprint optimisation. Acknowledgements The EU supported project Sustainable Process Integration Laboratory – SPIL funded as project No. CZ.02.1.01/0.0/0.0/15_003/0000456, by Czech Republic Operational Programme Research and Development, Education, Priority 1: Strengthening capacity for quality research in the collaboration agreement with the Universiti Teknologi Malaysia (UTM) based on the SPIL project have been gratefully acknowledged. 1067 References Aviso, K.B., Tan, R.R., Culaba, A.B., Cruz, J.B., 2011. Fuzzy input–output model for optimizing eco-industrial supply chains under water footprint constraints. Journal of Cleaner Production 19, 187–196. Bosman, R., 2016. Water Footprint of Widely Used Construction Materials - Steel, Cement, and Glass. The University of Twente, the Netherlands. Chapagain, A.K., Hoekstra, A.Y., 2004. Water footprints of nations (No. 16), The University of Twente, the Netherlands. 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